Background: Multi Drug Therapy approved by WHO is the best treatment option for Leprosy. There is a significant decline of mortality and morbidity after the introduction of multi drug therapy. But the adverse effects causing changes in clinical and laboratory parameters to multi drug therapy are the main limiting obstacle for the treatment course completion. Objective: The aim of this study is to find out the effects on routine laboratory parameters including (...) hematological and biochemical changes before, during and after the treatment of multi drug therapy in leprosy. Methodology: A descriptive cohort hospital based study on 85 multi drug therapy treated leprosy patients using standard laboratory tools for routine investigations for 18 months. Results: During the one year multidrug treatment period, most of the routine laboratory parameters showed mild to moderate change from normal level during the first 3 months with gradual recovery in the following months. Complete blood count assessment revealed mild decline in Hb, PCV, MCH, MCHC, and moderate decline in WBC and Platelet count. A mild increase in liver function tests (Bilirubin, AST, ALT, Alkaline phosphatase) and renal function tests (S.Creatinine, b. Urea) was observed. A moderate decline in S. Sodium with mild increase in S. Potassium was found on investigating S. Electrolytes. Patients were fully recovered from all hemato-biochemical adverse effects after 6 months of completion of the multi drug therapy. Conclusion: Despite of mild to moderate hematological and biochemical adverse reactions with multi drug therapy, recovery was excellent after 6 months of completion of therapy. (shrink)

Objective: The aim of this study was to compare oral Artemether-Lumefantrine to intravenous Quinine by exploring its effectiveness in cerebral malaria in hospitalized patients. Materials and Methods: A randomized prospective study was conducted among 64 hospitalized cases of cerebral malaria. One group of patients was treated with intravenous Quinine and another group was treated with oral Artemether-Lumefantrine. Response in clinical, laboratory parameters and outcome of treatment were noted every eight hours. Results: Oral Artemether-Lumefantrine showed almost similar response in clinical (...) and laboratory parameters with median temperature (101º F), pulse rate (102 b/m), systolic BP (110mmHg), GCS (12), hemoglobin (9.8 g/dl), WBC (9000/μl), platelet (130000/μl), B. glucose (101 mg/dl), S. creatinine (1.8 mg/dl), ALT (32 U/L), mean disappearance time of parasite from blood (40 hours), and mean time for regaining full consciousness (30 hours). Final outcome was also similar in both drugs with only 1 death (3.1%) reported in each group. Conclusion: In cerebral malaria intravenous Quinine or oral Artemether-Lumefantrine therapy does not have any statistically significant difference in terms of clinical parameter, laboratory parameter and final outcome. (shrink)

Drug regulation is fraught with inductive risk. Regulators must make a prediction about whether or not an experimental pharmaceutical will be effective and relatively safe when used by typical patients, and such predictions are based on a complex, indeterminate, and incomplete evidential basis. Such inductive risk has important practical consequences. If regulators reject an experimental drug when it in fact has a favourable benefit/harm profile, then a valuable intervention is denied to the public and a company’s material interests (...) are needlessly thwarted. Conversely, if regulators approve an experimental drug when it in fact has an unfavourable benefit/harm profile, then resources are wasted, people are needlessly harmed, and other potentially more effective treatments are underutilized. Given that such regulatory decisions have these practical consequences, non-epistemic values about the relative importance of these consequences impact the way such regulatory decisions are made (similar to the analysis of laboratory studies on the toxic effects of dioxins presented in Douglas [2000]). To balance the competing demands of the pertinent non-epistemic values, regulators must perform what I call an “inductive risk calculus.” At least in the American context this inductive risk calculus is not well-managed. (shrink)

Stimulants have been shown to be safe and effective for reduction of the symptoms of attention deficit hyperactivity disorder. Despite much debate, however, there has been little empirical evidence as to whether stimulants affect authenticity and moral agency in children. Singh presents evidence that stimulants do not undercut children's' sense of self and increase their experience of agency. These findings are consistent with laboratory evidence that stimulant drugs in therapeutic doses improve cognitive control over thought and behavior.

Ascorbic acid (vitamin C) is a water-soluble vitamin; it is present in the highest concentration in the brain. Ascorbic acid in high doses acts as a potential treatment for various neuropathological and psychiatric conditions. Flumazenil is a benzodiazepine antagonist; it competitively inhibits the activity of benzodiazepine and non-benzodiazepine substances that interact with benzodiazepine receptors site on the GABA/benzodiazepine receptor complex. This study aims to investigate the effect of flumazenil on the anxiolytic action of ascorbic acid using an elevated plus maze (...) model of anxiety in rats. Male Albino Wistar rats weighing between 250 and 320 grams were used. Rats were divided into four equal groups of seven rats each and treated as follows: Group I, the control group received a single dose of 1.0% tween 80; Group II treated with a single dose of 125 mg/kg ascorbic acid; Group III was injected by a single dose of 1.0 mg/kg flumazenil; Group IV received a combination treatment of 125 mg/kg ascorbic acid and 1.0 mg/kg flumazenil. Behavioural measurements using a plus maze were scored 30 min after the administration. The parameters scored are the time spent on the open and closed arms, the lines and number of entries into open and closed arms, and the anxiety measure. Ascorbic acid decreased anxiety measure and increased the total lines and total number of entries; this effect was abolished by the administration of flumazenil with ascorbic acid. Thus, ascorbic acid produces an anxiolytic-like effect in rats; this effect was abolished by flumazenil administration with ascorbic acid. This may indicate that the GABA/benzodiazepine receptor complex has to be stimulated to produce the anxiolytic effect. (shrink)

Solanum melongena (Eggplant) is a medicinal plant belonging to the family Solanaceae. This study aimed to perform a comparative assessment of the methanol extracts of the fruit and the leaf of Solanum melongena against multi-drug-resistant Staphylococcus aureus and Pseudomonas aeruginosa. The crude extracts were obtained from the leaves and fruits of the plant using methanol. The plant extracts were tested for the presence of various phytochemical constituents qualitatively. The antibacterial assay and minimum inhibitory concentration for the crude extracts (...) were carried out using the agar well diffusion and agar dilution methods, respectively. Phytochemical analysis of methanol extracts of Solanum melongena revealed the presence of various phytoconstituents. Antibacterial assay of methanol extracts of Staphylococcus melongena against multi-drug-resistant Staphylococcus aureus isolates with ciprofloxacin as a reference control revealed inhibition zone diameter ranging from 04.0±0.0 to 11.0±0.0 mm; in contrast that of multi-drug-resistant Pseudomonas aeruginosa isolates revealed inhibition zone diameter, with ciprofloxacin showing no inhibition. The minimum inhibitory concentration of the methanol extracts on Pseudomonas aeruginosa isolates ranges from 25.0 to 50.0 mg/ml and 25.0->50.0 mg/ml, respectively, in comparison, the minimum inhibitory concentration of the methanol extracts on Staphylococcus aureus isolates ranges from 6.25 to 50.0 mg/ml and 6.25->50.0 mg/ml respectively. Thus, the fruit extract had better activity against test multi-drug-resistant Pseudomonas aeruginosa and Staphylococcus aureus than the leaf extract of Solanum melongena. (shrink)

Solanum melongena (Eggplant) is a medicinal plant belonging to the family Solanaceae. This study aimed to perform a comparative assessment of the methanol extracts of the fruit and the leaf of Solanum melongena against multi-drug-resistant Staphylococcus aureus and Pseudomonas aeruginosa. The crude extracts were obtained from the leaves and fruits of the plant using methanol. The plant extracts were tested for the presence of various phytochemical constituents qualitatively. The antibacterial assay and minimum inhibitory concentration for the crude extracts (...) were carried out using the agar well diffusion and agar dilution methods, respectively. Phytochemical analysis of methanol extracts of Solanum melongena revealed the presence of various phytoconstituents. Antibacterial assay of methanol extracts of Staphylococcus melongena against multi-drug-resistant Staphylococcus aureus isolates with ciprofloxacin as a reference control revealed inhibition zone diameter ranging from 04.0±0.0 to 11.0±0.0 mm; in contrast that of multi-drug-resistant Pseudomonas aeruginosa isolates revealed inhibition zone diameter, with ciprofloxacin showing no inhibition. The minimum inhibitory concentration of the methanol extracts on Pseudomonas aeruginosa isolates ranges from 25.0 to 50.0 mg/ml and 25.0->50.0 mg/ml, respectively, in comparison, the minimum inhibitory concentration of the methanol extracts on Staphylococcus aureus isolates ranges from 6.25 to 50.0 mg/ml and 6.25->50.0 mg/ml respectively. Thus, the fruit extract had better activity against test multi-drug-resistant Pseudomonas aeruginosa and Staphylococcus aureus than the leaf extract of Solanum melongena. (shrink)

Precision medicine and molecular systems medicine (MSM) are highly utilized and successful approaches to improve understanding, diagnosis, and treatment of many diseases from bench-to-bedside. Especially in the COVID-19 pandemic, molecular techniques and biotechnological innovation have proven to be of utmost importance for rapid developments in disease diagnostics and treatment, including DNA and RNA sequencing technology, treatment with drugs and natural products and vaccine development. The COVID-19 crisis, however, has also demonstrated the need for systemic thinking and transdisciplinarity and the limits (...) of MSM: the neglect of the bio-psycho-social systemic nature of humans and their context as the object of individual therapeutic and population-oriented interventions. COVID-19 illustrates how a medical problem requires a transdisciplinary approach in epidemiology, pathology, internal medicine, public health, environmental medicine, and socio-economic modeling. Regarding the need for conceptual integration of these different kinds of knowledge we suggest the application of general system theory (GST). This approach endorses an organism-centered view on health and disease, which according to Ludwig von Bertalanffy who was the founder of GST, we call Organismal Systems Medicine (OSM). We argue that systems science offers wider applications in the field of pathology and can contribute to an integrative systems medicine by (i) integration of evidence across functional and structural differentially scaled subsystems, (ii) conceptualization of complex multilevel systems, and (iii) suggesting mechanisms and non-linear relationships underlying the observed phenomena. We underline these points with a proposal on multi-level systems pathology including neurophysiology, endocrinology, immune system, genetics, and general metabolism. An integration of these areas is necessary to understand excess mortality rates and polypharmacological treatments. In the pandemic era this multi-level systems pathology is most important to assess potential vaccines, their effectiveness, short-, and long-time adverse effects. We further argue that these conceptual frameworks are not only valid in the COVID-19 era but also important to be integrated in a medicinal curriculum. (shrink)

Response to commentary. We are grateful to Crockett and Craigie for their interesting remarks on our paper. We accept Crockett’s claim that there is a need for caution in drawing inferences about patient groups from work on healthy volunteers in the laboratory. However, we believe that the evidence we cited established a strong presumption that many of the patients who are routinely taking a medication, including many people properly prescribed the medication for a medical condition, have morally significant aspects (...) of their cognition and behavior modified in a way that is unintended and may sometimes be unwelcome. Crockett notes that in some cases the effects of long-term drug use may differ, sometimes markedly, from the effects of short-term use. However, if acute use of a drug affects a neural system involved in mediating moral cognition or behavior, this nevertheless provides some evidence that chronic use of the drug may affect that same system and thus have morally significant effects. It is also plausible, in some cases, that an acute moral effect would give rise to a chronic moral effect via cognitive mechanisms. ... (shrink)

Bayne and Carter argue that the mode of consciousness induced by psychedelic drugs does not fit squarely within the traditional account of modes as levels of consciousness, and favor instead a multi-dimensional account according to which modes of consciousness differ along several dimensions—none of which warrants a linear ordering of modes. We discuss the assumption that psychedelic drugs induce a single or paradigmatic mode of consciousness, as well as conceptual issues related to Bayne and Carter’s main argument against the (...) traditional account. Finally, we raise a set of questions about the individuation of dimensions selected to differentiate modes of consciousness that could be addressed in future discussions of the multi-dimensional account. (shrink)

While many different mechanisms contribute to the generation of spatial order in biological development, the formation of morphogenetic fields which in turn direct cell responses giving rise to pattern and form are of major importance and essential for embryogenesis and regeneration. Most likely the fields represent concentration patterns of substances produced by molecular kinetics. Short range autocatalytic activation in conjunction with longer range “lateral” inhibition or depletion effects is capable of generating such patterns (Gierer and Meinhardt, 1972). Non-linear reactions are (...) required, and mathematical criteria were derived to design molecular models capable of pattern generation. The classical embryological feature of proportion regulation can be incorporated into the models. The conditions are mathematically necessary for the simplest two-factor case, and are likely to be a fair approximation in multi-component systems in which activation and inhibition are systems parameters subsuming the action of several agents. Gradients, symmetric and periodic patterns, in one or two dimensions, stable or pulsing in time, can be generated on this basis. Our basic concept of autocatalysis in conjunction with lateral inhibition accounts for self-regulatory biological features, including the reproducible formation of structures from near-uniform initial conditions as required by the logic of the generation cycle. Real tissue form, for instance that of budding Hydra, may often be traced back to local curvature arising within an initially relatively flat cell sheet, the position of evagination being determined by morphogenetic fields. Shell theory developed for architecture may also be applied to such biological processes. (shrink)

The rapid increase of the old age people imposes the reconsideration of the rehabilitation techniques and procedures and/or the development of the existing ones, at least from two points of view: the limitation use of the pharmaceutical drugs because of their secondary effects in the debilitated organisms and their avoidance; the high risk of the induced anxiety states, depression or other symptoms as a consequence of the main disease, i.e. the neuro-degenerative or mobility dysfunctions, limiting again the use of such (...) excessive drug medication. Moreover, Alzheimer’s or Parknson’s diseases are otherwise incurable, so the application of rehabilitating procedures like music-based therapy becomes preferential. The advances both in the identification of the specific auditory musical-sensitive circuits and of the non- musical neuro-connections but activated indirectly by music, otherwise inaccessible by other techniques, and in the understanding of consciousness, which can be described by seven cognitive centers, allows to improve and develop the music based therapy. A multitask procedure based on the activation of these cognition centers is presented, allowing to increase the personal psychical engagement of the patient in the recommended music based therapeutic program, addressed both to the rehabilitation of the main degenerative disease and to the secondary induced dysfunctions. This procedure combines the evidence based medicine assisted by laboratory expertise for the determination of a correct diagnostic, and narrative based medicine allowing to quantify the personal engaging qualities of the patient with respect to the proposed music based program, reducing in this way the gap between these two basic procedures and bringing in a first plane the patient care, not only the disease, with beneficial consequence for the therapy efficiency and for the patient-medical care relations. (shrink)

Metformin hydrochloride is the first-line anti-diabetic drug used to treat type 2 diabetes mellites and helps to control blood sugar levels. Various brands of metformin are available in the Libyan market which makes it challenging to select, an effective and economical one. This study aimed to compare different brands of metformin available in the Misurata and evaluate the quality parameter according to the British Pharmacopoeia. Six brands of metformin tablets (850 mg) were taken from the market and assessed. To (...) achieve this purpose five tests were done on each brand, the uniformity of weight test shows the average weight and 5.0% deviation, the friability test gives how much the tablet can stand attrition, the disintegration time test shows the time taken by the tablet to disintegrate, dissolution test to confirm the rate of drug release, weight variation and friability test of all brands was within the specified limit. Disintegration time for all the brands was within 30 minutes. All six brands of metformin hydrochloride tablets fulfilled the in-vitro dissolution rate test specification not less than 80% of the drug is released within 45 minutes. Using Ultraviolet-visible (UV) spectroscopy, UV analysis of different samples shows that the percentage content of active ingredients of five brands of metformin hydrochloride tablets was within the monograph specification (95%-105%) of drug content but one brand failed this test. The study indicated that strict quality control of imported drugs should enforced to ensure effective and safe medicines in the Libyan market. (shrink)

The spatial-ecological modeling is relating sustainable dispersions with social development. Sustainability with spatial-ecological model gives attention to urban environments in the design review management to comply with Earth’s system. Naturally exchanged patterns of ecosystems have consistent and periodic cycles to preserve energy flows and materials in Earth’s system. The Probabilistic Risk Assessment (PRA) technique is utilized to assess the safety of an industrial complex. The other analytical approach is the Failure-Safe Mode and Effect Analysis (FMEA) for critical components. The plant (...) safety parameters are identified for engineering topology as employed in assessment safety of industrial ecology. In particular, the most severe accidental release of hazardous gaseous is postulated, analyzed and assessment in industrial region. The IAEA-safety assessment procedure is used to account the duration and rate of discharge of liquid chlorine. The ecological model of plume dispersion width and concentration of chlorine gas in the downwind direction is determined using Gaussian Plume Model in urban and rural areas and presented with SURFER®. The prediction of accident consequences is traced in risk contour concentration lines. The local greenhouse effect is predicted with relevant conclusions. The spatial-ecological model is predicted for multiple factors distribution schemes of multi-criteria analysis. The input–output analysis is explored from the spillover effect, and we conducted Monte Carlo simulations for sensitivity analysis. Their unique structure is balanced within “equilibrium patterns”, such as the composite index for biosphere with collective structure of many distributed feedback flows. These dynamic structures are related to have their physical and chemical properties and enable a gradual and prolonged incremental pattern. While this spatial model structure argues from ecology, resource savings, static load design, financial and other pragmatic reasons, the outcomes are not decisive in an artistic/architectural perspective. The hypothesis is deployed to unify analytic and analogical spatial structure in development urban environments using optimization loads as an example of integrated industrial structure where the process is based on engineering topology of systems ecology. (shrink)

Disintegration is the most important step for drug bioavailability because after, the disintegration process, the ingredients of solid dosage forms dissolve and become bioavailable. Generally, the tablets and capsules should be taken with a glass of water otherwise the manufacturer gives instructions to use the proper beverage. Several drugs are taken with different forms of beverages to ensure easy swallowing of the tablet, masking the bad taste of the drug and overcoming the drug aftertaste, these beverages can (...) influence the disintegration of the solid dosage form. The most common cold beverages consumed by the Libyan population are juice, milk, and Coca-Cola. These beverages are consumed without awareness of the possible effect of these beverages on drugs, especially over-the-counter drugs such as analgesic, antipyretic, and anti-inflammatory drugs that are taken without a prescription. This study aimed to evaluate the influence of three beverages, namely: orange juice, milk, and Coca-Cola on the disintegration time of four over-the-counter-drugs: Panadol, Congestal, Brufen, and Reality Extra using disintegration test of drugs in 0.1 N HCL and in hybrid medium prepared by combination of 150 ml 0.1 N HCL and 550 ml of beverage to simulate in vivo condition. The findings show that the orange juice significantly increases the disintegration time of all the investigated drugs. Coca-Cola significantly increases the disintegration time of Reality Extra, and slightly increases the disintegration time of Brufen, Congestal, and Panadol and the full-fat milk significantly increases the disintegration time of Reality Extra and Panadol while slightly increasing the disintegration time for Brufen and Congestal. It is concluded that commonly used beverages affect the disintegration time of the examined over-the-counter drugs. Patients should be advised to take these medications without beverages which may delay the disintegration and the onset of action of the drug. (shrink)

The second volume of “Advancing Uncertain Combinatorics through Graphization, Hyperization, and Uncertainization: Fuzzy, Neutrosophic, Soft, Rough, and Beyond” presents a deep exploration of the progress in uncertain combinatorics through innovative methodologies like graphization, hyperization, and uncertainization. This volume integrates foundational concepts from fuzzy, neutrosophic, soft, and rough set theory, among others, to further advance the field. Combinatorics and set theory, two central pillars of mathematics, focus on counting, arrangement, and the study of collections under defined rules. Combinatorics excels in handling (...) uncertainty, while set theory has evolved with concepts such as fuzzy and neutrosophic sets, which enable the modeling of complex real-world uncertainties by addressing truth, indeterminacy, and falsehood. These advancements, when combined with graph theory, give rise to novel forms of uncertain sets in "graphized" structures, including hypergraphs and superhypergraphs. Innovations such as Neutrosophic Oversets, Undersets, and Offsets, as well as the Nonstandard Real Set, build upon traditional graph concepts, pushing both theoretical and practical boundaries. The synthesis of combinatorics, set theory, and graph theory in this volume provides a robust framework for addressing the complexities and uncertainties inherent in both mathematical and real-world systems, paving the way for future research and application. In the first chapter, “A Review of the Hierarchy of Plithogenic, Neutrosophic, and Fuzzy Graphs: Survey and Applications”, the authors investigate the interrelationships among various graph classes, including Plithogenic graphs, and explore other related structures. Graph theory, a fundamental branch of mathematics, focuses on networks of nodes and edges, studying their paths, structures, and properties. A Fuzzy Graph extends this concept by assigning a membership degree between 0 and 1 to each edge and vertex, representing the level of uncertainty. The Turiyam Neutrosophic Graph is introduced as an extension of both Neutrosophic and Fuzzy Graphs, while Plithogenic graphs offer a potent method for managing uncertainty. The second chapter, “Review of Some Superhypergraph Classes: Directed, Bidirected, Soft, and Rough”, examines advanced graph structures such as directed superhypergraphs, bidirected hypergraphs, soft superhypergraphs, and rough superhypergraphs. Classical graph classes include undirected graphs, where edges lack orientation, and directed graphs, where edges have specific directions. Recent innovations, including bidirected graphs, have sparked ongoing research and significant advancements in the field. Soft Sets and their extension to Soft Graphs provide a flexible framework for managing uncertainty, while Rough Sets and Rough Graphs address uncertainty by using lower and upper approximations to handle imprecise data. Hypergraphs generalize traditional graphs by allowing edges, or hyperedges, to connect more than two vertices. Superhypergraphs further extend this by allowing both vertices and edges to represent subsets, facilitating the modeling of hierarchical and group-based relationships. The third chapter, “Survey of Intersection Graphs, Fuzzy Graphs, and Neutrosophic Graphs”, explores the intersection graph models within the realms of Fuzzy Graphs, Intuitionistic Fuzzy Graphs, Neutrosophic Graphs, Turiyam Neutrosophic Graphs, and Plithogenic Graphs. The chapter highlights their mathematical properties and interrelationships, reflecting the growing number of graph classes being developed in these areas. Intersection graphs, such as Unit Square Graphs, Circle Graphs, and Ray Intersection Graphs, are crucial for understanding complex graph structures in uncertain environments. The fourth chapter, “Fundamental Computational Problems and Algorithms for SuperHyperGraphs”, addresses optimization problems within the SuperHypergraph framework, such as the SuperHypergraph Partition Problem, Reachability, and Minimum Spanning SuperHypertree. The chapter also adapts classical problems like the Traveling Salesman Problem and the Chinese Postman Problem to the SuperHypergraph context, exploring how hypergraphs, which allow hyperedges to connect more than two vertices, can be used to solve complex hierarchical and relational problems. The fifth chapter, “A Short Note on the Basic Graph Construction Algorithm for Plithogenic Graphs”, delves into algorithms designed for Plithogenic Graphs and Intuitionistic Plithogenic Graphs, analyzing their complexity and validity. Plithogenic Graphs model multi-valued attributes by incorporating membership and contradiction functions, offering a nuanced representation of complex relationships. The sixth chapter, “Short Note of Bunch Graph in Fuzzy, Neutrosophic, and Plithogenic Graphs”, generalizes traditional graph theory by representing nodes as groups (bunches) rather than individual entities. This approach enables the modeling of both competition and collaboration within a network. The chapter explores various uncertain models of bunch graphs, including Fuzzy Graphs, Neutrosophic Graphs, Turiyam Neutrosophic Graphs, and Plithogenic Graphs. In the seventh chapter, “A Reconsideration of Advanced Concepts in Neutrosophic Graphs: Smart, Zero Divisor, Layered, Weak, Semi, and Chemical Graphs”, the authors extend several fuzzy graph classes to Neutrosophic graphs and analyze their properties. Neutrosophic Graphs, a generalization of fuzzy graphs, incorporate degrees of truth, indeterminacy, and falsity to model uncertainty more effectively. The eighth chapter, “Short Note of Even-Hole-Graph for Uncertain Graph”, focuses on Even-Hole-Free and Meyniel Graphs analyzed within the frameworks of Fuzzy, Neutrosophic, Turiyam Neutrosophic, and Plithogenic Graphs. The study investigates the structure of these graphs, with an emphasis on their implications for uncertainty modeling. The ninth chapter, “Survey of Planar and Outerplanar Graphs in Fuzzy and Neutrosophic Graphs”, explores planar and outerplanar graphs, as well as apex graphs, within the contexts of fuzzy, neutrosophic, Turiyam Neutrosophic, and plithogenic graphs. The chapter examines how these types of graphs are used to model uncertain parameters and relationships in mathematical and real-world systems. The tenth chapter, “General Plithogenic Soft Rough Graphs and Some Related Graph Classes”, introduces and explores new concepts such as Turiyam Neutrosophic Soft Graphs and General Plithogenic Soft Graphs. The chapter also examines models of uncertain graphs, including Fuzzy, Intuitionistic Fuzzy, Neutrosophic, and Plithogenic Graphs, all designed to handle uncertainty in diverse contexts. The eleventh chapter, “Survey of Trees, Forests, and Paths in Fuzzy and Neutrosophic Graphs”, provides a comprehensive study of Trees, Forests, and Paths within the framework of Fuzzy and Neutrosophic Graphs. This chapter focuses on classifying and analyzing graph structures like trees and paths in uncertain environments, contributing to the ongoing development of graph theory in the context of uncertainty. (shrink)

This book is the sixth volume in the series of Collected Papers on Advancing Uncertain Combinatorics through Graphization, Hyperization, and Uncertainization: Fuzzy, Neutrosophic, Soft, Rough, and Beyond. Building upon the foundational contributions of previous volumes, this edition focuses on the exploration and development of Various New Uncertain Concepts, further enriching the study of uncertainty and complexity through innovative theoretical advancements and practical applications. The volume is meticulously organized into 15 chapters, each presenting unique perspectives and contributions to the field. From (...) theoretical explorations to real-world applications, these chapters provide a cohesive and comprehensive overview of the state of the art in uncertain combinatorics, emphasizing the versatility and power of the newly introduced concepts and methodologies. The first chapter (SuperHypertree-depth – Structural Analysis in SuperHyperGraphs) explores the concept of SuperHypertree-depth, an extension of the classical graph parameter Tree-depth and its hypergraph counterpart Hypertree-depth. By introducing hierarchical nesting within SuperHyperGraphs, where both vertices and edges can represent recursive subsets, this study investigates the mathematical properties and structural implications of these extended parameters. The findings highlight the relationships between SuperHypertree-depth and its traditional graph-theoretic equivalents, providing a deeper understanding of their applicability to hierarchical and complex systems. The second chapter (Obstructions for Hypertree-width and SuperHypertree-width) examines the role of ultrafilters as obstructions in determining Hypertree-width and extends the concept to SuperHypertree-width. Building on hypergraph theory, which abstracts traditional graph frameworks into more complex domains, the study investigates how recursive structures within SuperHyperGraphs redefine the computational and structural properties of these parameters. Ultrafilters, with their broad mathematical significance, serve as critical tools for understanding the limitations and potentials of these advanced graph metrics. The third chapter (SuperHypertree-Length and SuperHypertree-Breadth in SuperHyperGraphs) investigates the extension of the graph-theoretic parameters Tree-length and Tree-breadth to the realms of hypergraphs and SuperHyperGraphs. By leveraging the hierarchical nesting of SuperHyperGraphs, the study explores how these parameters adapt to increasingly complex and multi-level structures. Comparative analyses between these extended parameters and their classical counterparts reveal new insights into their relevance and utility in advanced graph and hypergraph theory. Plithogenic Sets, which generalize Fuzzy and Neutrosophic Sets, are extended in the fourth chapter (Extended HyperPlithogenic Sets and Generalized Plithogenic Graphs) to Extended Plithogenic Sets, HyperPlithogenic Sets, and SuperHyperPlithogenic Sets. This study further investigates their application to graph theory through the concepts of Extended Plithogenic Graphs and Generalized Extended Plithogenic Graphs. The chapter provides a concise exploration of these frameworks, offering insights into their potential for addressing uncertainty and complexity in graph structures. Soft Sets provide an effective framework for decision-making by mapping parameters to subsets of a universal set, addressing uncertainty and vagueness. The fifth chapter (Double-Framed Superhypersoft Set and Double-Framed Treesoft Set) introduces the Double-Framed SuperHypersoft Set and the Double-Framed Treesoft Set as extensions of traditional and advanced soft set frameworks, such as Hypersoft and SuperHypersoft Sets. The chapter explores their relationships with existing concepts, offering new tools to handle complex decision-making scenarios with enhanced structural flexibility. The sixth paper (HyperPlithogenic Cubic Set and SuperHyperPlithogenic Cubic Set) introduces the concepts of the HyperPlithogenic Cubic Set and SuperHyperPlithogenic Cubic Set, which extend the Plithogenic Cubic Set by integrating both interval-valued and single-valued fuzzy memberships. These sets leverage multi-attribute aggregation techniques inherent to plithogenic structures, allowing for nuanced representations of uncertainty. Additionally, related constructs such as the HyperPlithogenic Fuzzy Cubic Set, HyperPlithogenic Intuitionistic Fuzzy Cubic Set, and HyperPlithogenic Neutrosophic Cubic Set are explored, further enriching the theoretical and practical applications of this framework. The seventh chapter (L-Neutrosophic Sets and Nonstationary Neutrosophic Sets) extends the foundational concepts of fuzzy sets by integrating Neutrosophic and Plithogenic frameworks. By introducing L-Neutrosophic Sets and Nonstationary Neutrosophic Sets, the study enhances the representation of uncertainty through independent membership components: truth, indeterminacy, and falsity. These advanced constructs also incorporate multi-dimensional and contradictory attributes, providing a robust means of modeling complex decision-making and uncertain data. Plithogenic and Rough Sets, known for generalizing uncertainty modeling and classification, are extended in the eight chapter (Forest HyperPlithogenic and Forest HyperRough Sets) to Forest HyperPlithogenic Sets, Forest SuperHyperPlithogenic Sets, Forest HyperRough Sets, and Forest SuperHyperRough Sets. These frameworks incorporate hierarchical and recursive structures to advance existing set-theoretic paradigms. The chapter explores their applications in multi-level data analysis and uncertainty classification, demonstrating their adaptability to complex systems. Building on Fuzzy, Neutrosophic, and Plithogenic Sets, the tenth chapter (Symbolic HyperPlithogenic Sets) introduces Symbolic HyperPlithogenic Sets and Symbolic n-SuperHyperPlithogenic Sets. These sets incorporate symbolic components and algebraic coefficients, enabling flexible operations within a defined prevalence order. By extending symbolic representation into hyperplithogenic and superhyperplithogenic domains, the chapter opens new pathways for addressing uncertainty and hierarchical complexity in mathematical modeling. Soft Sets, designed to manage uncertainty and imprecision, have evolved through various extensions like Hypersoft Sets and SuperHypersoft Sets. The eleventh chapter (N-SuperHypersoft and Bijective SuperHypersoft Sets) introduces N-SuperHypersoft Sets, N-Treesoft Sets, Bijective SuperHypersoft Sets, and Bijective Treesoft Sets. These new constructs enhance decision-making frameworks by incorporating advanced hierarchical and bijective relationships, building on existing theories and expanding their applications. Plithogenic Sets, known for integrating multi-valued attributes and contradictions, and Rough Sets, which partition data into definable approximations, are combined in the twelfth chapter (Plithogenic Rough Sets) to form Plithogenic Rough Sets. This fusion provides a powerful framework for addressing uncertainty in dynamic and complex decision-making scenarios, offering a novel approach to uncertainty modeling. Expanding on Neutrosophic Sets, which represent truth, indeterminacy, and falsehood, this chapter introduces Plithogenic Duplets and Plithogenic Triplets. These constructs leverage the Plithogenic framework to incorporate attributes, values, and contradiction measures. The thirteenth chapter (Plithogenic Duplets and Triplets) examines their relationships with Neutrosophic Duplets and Triplets, offering new tools for multi-dimensional data representation and decision-making. Building on foundational concepts like Rough Sets and Vague Sets, the fourteenth chapter (SuperRough and SuperVague Sets) introduces SuperRough Sets and SuperVague Sets. These generalized frameworks extend uncertainty modeling by incorporating hierarchical structures. The study also demonstrates that SuperRough Sets can evolve into SuperHyperRough Sets, providing further generalizations for advanced data classification and analysis. The fifteenth chapter (Neutrosophic TreeSoft Expert and ForestSoft Sets) revisits the Neutrosophic TreeSoft Set, which combines the hierarchical structure of TreeSoft Sets with the Neutrosophic framework for uncertainty representation. Additionally, it introduces the Neutrosophic TreeSoft Expert Set, incorporating expert knowledge into the model. The chapter also explores the ForestSoft Set and its extension, the Neutrosophic ForestSoft Set, to provide multi-level, tree-structured approaches for complex data representation and analysis. (shrink)

Translation failure occurs when a treatment shown to be safe and effective in one type of population does not produce the same result in another. We are currently in a crisis involving the translatability of preclinical studies to human populations. Animal trials are no better than a coin toss at predicting the safety and efficacy of drugs in human trials, and the high failure rate of drugs entering human trials suggests that most of the suffering of laboratory animals is (...) futile, creating no commensurate benefit for human patients. Here, I argue that animal ethics committees have a role to play in getting us out of this crisis. Inadequate representation is a known contributor to translation failures and is a matter of both scientific and ethical concern. Ethical review committees have the authority to address it by reprioritising the values already enshrined in their guiding principles. (shrink)

The research evaluates generative AI’s capabilities through a multi-phase framework, addressing how data synthesis, language models, and predictive algorithms contribute to sector-specific applications. In banking, the model assesses the impact of AI-driven chatbot interactions, credit risk assessment, and personalized financial services on customer experience and bank performance. Healthcare applications are explored through image synthesis for diagnostics, predictive modeling in patient care, and drug discovery simulations. The experimental setup is rigorously tested across metrics such as response accuracy, cost-effectiveness, and (...) data privacy to determine the benefits and potential risks associated with generative AI in these fields. (shrink)

Psoriatic arthritis is a chronic, systemic inflammatory disorder. It has been classified in spondyloarthropathies group which shares clinical, radiologic, serologic features, familial and genetic relationship. Up to 5-30% of patients with psoriasis may go on to develop psoriatic arthritis, usually within 5-10 years. Adalimumab (ADA) is the first human monoclonal antibody against TNF-α. ADA is a biologic agent effective in both skin lesions and joint signs. Anti-TNF agents are powerful immunmodulating drugs with potentially side effects. Our case is 38 years (...) old woman complaining about swelling and pain in hand joints. In physical examination she has asymmetrical arthritis in wrist, proximal (PIP) and distal interphalangeal (DIP) hand joints and right knee joint. In laboratory; sedimentation rate: 80 mm/h, C-reactive protein: 17 mg/l, rheumatoid factor (RF): 8.7 IU/ml and HLA B27 was positive. Radiologically, erosions and narrowing were determined in PIP and DIP hand joints and grade 3 sacroiliitis bilaterally. In clinical monitoring, psoriaform lesions progressed in her scalp, so we diagnosed psoriatic artritis. We started ADA therapy 40 mg subcutaneously every two weeks. She developed periorbital infection in left-sided in tertiary month following. Streptococcal proliferation was seen in lesion culture, so we began amoxicillin-clavulanate therapy. She benefit antibiotic therapy, infectious signs regressed. ADA therapy discontinued, instead of it, etanercept 50 mg twice weekly subcutaneous and methylprednisolone 12 mg/daily oral therapy is started. We purposed to declare our case with literature selection. (shrink)

Disintegration is the most important step for drug bioavailability because after, the disintegration process, the ingredients of solid dosage forms dissolve and become bioavailable. Generally, the tablets and capsules should be taken with a glass of water otherwise the manufacturer gives instructions to use the proper beverage. Several drugs are taken with different forms of beverages to ensure easy swallowing of the tablet, masking the bad taste of the drug and overcoming the drug aftertaste, these beverages can (...) influence the disintegration of the solid dosage form. The most common cold beverages consumed by the Libyan population are juice, milk, and Coca-Cola. These beverages are consumed without awareness of the possible effect of these beverages on drugs, especially over-the-counter drugs such as analgesic, antipyretic, and anti-inflammatory drugs that are taken without a prescription. This study aimed to evaluate the influence of three beverages, namely: orange juice, milk, and Coca-Cola on the disintegration time of four over-the-counter-drugs: Panadol, Congestal, Brufen, and Reality Extra using disintegration test of drugs in 0.1 N HCL and in hybrid medium prepared by combination of 150 ml 0.1 N HCL and 550 ml of beverage to simulate in vivo condition. The findings show that the orange juice significantly increases the disintegration time of all the investigated drugs. Coca-Cola significantly increases the disintegration time of Reality Extra, and slightly increases the disintegration time of Brufen, Congestal, and Panadol and the full-fat milk significantly increases the disintegration time of Reality Extra and Panadol while slightly increasing the disintegration time for Brufen and Congestal. It is concluded that commonly used beverages affect the disintegration time of the examined over-the-counter drugs. Patients should be advised to take these medications without beverages which may delay the disintegration and the onset of action of the drug. (shrink)

Building information modeling can help in predicting the energy efficiency in future based on dynamic patterns obtained by visualization of data. The aim of this study was to investigate the effective parameters of energy consumption using BIM technology which can evaluate the buildings energy performance. First, three forms of general states in the building were modeled to evaluate the proposed designs in Autodesk Revit Software. Then, the main building form for energy modeling and analysis was selected. Autodesk Revit 2020 software (...) was also used to obtain the results of climate data analysis and building energy consumption index. Finally, the most optimal mode was selected by examining different energy consumption modes. The results showed that the use of building information modeling technology in adjusting the parameters affecting energy consumption can save energy cost up to 58.23% in block D. Energy cost savings for block C and the western lobby were obtained as 51.03% and 43.05%, respectively. Based on energy use intensity, energy cost savings for blocks C, D, and the western lobby were estimated as 16.67%, 16.30%, and 11%, respectively. The results of parametric studies on alternative schemes of energy use intensity optimization showed that 16.30% savings could be achieved by the base building model in a 30-year time horizon. Therefore, it was concluded that optimization of energy consumption would reduce the environmental pollutants emission and contribute to preservation and sustainability of the environment. (shrink)

Cloud Computing provides vast storage facility. The requirement of this system is to improve the security and transmission performance in the cloud storage environment. Methods: This system provides two level of security for the cloud data. The Client Data Security Contrivance (CDSC) and Cloud Service Provider (CSP) Data Security Contrivance are the two methods which transforms the original data to cipher text. The security algorithm used in CDSC is Linguistic Steganography. Blowfish algorithm is used in CSP Data Security Contrivance to (...) convert the cipher text using a secret-key block cipher of 64-bits. This system is designed to increase security and to improve the transmission performance. Storage-cheating attack model and Privacy-cheating attack model are implemented to protect the data on cloud. Findings: This system increases security and improves transmission performance. The blowfish algorithm is secure against unauthorized attacks and runs faster than the popular existing algorithms. Storage-cheating attack model and Privacy-cheating attack model provides the data confidentiality for data stored in the cloud in higher way. Improvements: The system can be implemented in real cloud system in the future. (shrink)

Prevention, they say, is cheaper, easier and better than curing. It is from this maxim that this study was conceptualized. Metallurgical laboratory accidents are an issue of great concern because it not only affect the productivity and economic growth of an organization but also the physical, mental, and entire wellbeing of the victim. This study was aimed at reviewing the types and causes of metallurgical laboratory accidents, their effects, and their preventive measures. It was concluded that if the (...) identified preventive measures are strictly adhered to, the prevalence of such accidents would be curtailed tremendously. (shrink)

Newer antidepressant drugs are frequently cited as having reduced side effect profiles to that of their older counterparts. However, recent studies have begun to dispute this claim, citing selective sampling, short clinical trials, and clinical trial environments as influencing reported outcomes. At present, little research on antidepressant side effects draws on RWD (Real-World Data). Despite this, interest in examining RWD samples for antidepressant drug side effects is increasing as of 2020. The reported study asked a random sample of 300+ (...) individuals taking a variety of different antidepressant medications to complete online drug side effect self-report scales with previously high validity. Newer antidepressants belonging to the atypical antidepressant drug class were reported as having only slightly reduced side effects of weight gain compared with older SSRI-class medications. No reduced side effects of increased depression, anxiety, sexual dysfunction (SD), sleepiness, or suicidal ideation (SI) were found for the newer atypical-class medications vs older SSRI-class agents. Medication adherence did not differ significantly between SSRI and atypical classes. No evidence for reduced side effects was found for newer SSRI and atypical antidepressants vs older same-class drugs when comparing six new and old medications drawn from atypical and SSRI classes. However, atypical antidepressants were associated with increased use of adjunct medications to bolster primary treatment. (shrink)

We often get evidence concerning the reliability of our own thinking about some particular matter. This “higher-order evidence” can come from the disagreement of others, or from information about our being subject to the effects of drugs, fatigue, emotional ties, implicit biases, etc. This paper examines some pros and cons of two fairly general models for accommodating higher-order evidence. The one that currently seems most promising also turns out to have the consequence that epistemic akrasia should occur more frequently than (...) is sometimes supposed. But it also helps us see why this might not be a bad thing. (shrink)

Prescribing drugs for elderly patients is not an easy task since elderly patients frequently have comorbid conditions. In Libya, there are no guidelines for the management of medications used in elderly patients and no specialized geriatric health institutions. This study aims to assess the pattern of medication use among hospitalized elderly patients in Sebha Medical Centre and the drug-related problems associated with these patterns. This report is a descriptive and retrospective cross-sectional study conducted at Sebha Medical Center in 2021. (...) Potential drug-related problems were assessed based on the classification of Hepler and Strand. In this study, out of 195 participants, most patients have been given antibiotics (92.0%). The majority of patients have been prescribed anti-gastric agents, vitamins and anti-thrombotic agents which accounted for 75.0%, 62.0% and 55.0%, respectively. To a lesser extent, anti-hypertensive agents, analgesics and antihyperlipidemic were reported by 45.0%, 43.0% and 38.0%, respectively. Almost all the patients have at least one event of drug-related problem and more than three-quarters of the patients had more than one event of drug-related problems. The highest rate was untreated indications which were reported for 77.0% then followed by drug use without indication in nearly half of the events 48.0%. To fewer extent rates were reported: “in improper drug selection”, “drug interaction” and “adverse effects” which were reported for 25.0%, 23.0% and 18.0% of the total events, respectively. Almost all elderly patients have been prescribed antibiotics, analgesics and vitamins. Drug-related problems are predominantly prevalent in the clinical practice at the center. This study highlights the importance of activation of clinical pharmacist interventions at hospitals which can contribute to reducing the chance of risk of drug-related problems events among hospitalized elderly patients and ensuring rational drug prescribing in the geriatric clinical settings. (shrink)

The integration of Artificial Intelligence (AI) and Machine Learning (ML) into the research landscape has transforming almost every extending field, including pharmaceutical research. The idea of drug discovery itself is very conventional and has long been criticized for being overly lengthy and expensive, which sometimes may take more than 10 years and billions of dollars to develop a certain drug. AI and ML formulate the future of the drug discovery process by using big data to provide preliminary (...) drug candidates more effectively. This paper overviews the innovations defined by AI and ML in the field of drug discovery, major achievements, techniques, and use cases. Additionally, we explore how AI algorithms can enter biological data, inspect drug-target relations, determine optimal drug design, and potentially recompose famous drugs. This means through using big data with the help of AI in the process of research, previously undisclosed patterns that help in developing effective treatments for patients are found. The paper also addresses the related issues and limitations in applying AI in this domain, namely, data quality issues, the interpretability of AI solutions, and some ethical concerns. Herein, to provide a concrete foundation to the concepts mentioned so far, we discuss the different AI applications and case studies in drug discovery from a survey of the available literature. The article also provides information regarding the methodologies used in AI-enabled drug discovery like deep learning, reinforcement learning, and natural language processing. Moreover, we compare the use of conventional and artificial intelligence methods, while demonstrating what is good and what maybe in both. The results section offers a review and an integration of the most recent objectives and recommendations for subsequent research instruction. Therefore, despite these prohibitive AI and ML forecasts for drug discovery improvement, continuous interaction between computational scientists, biologists, and regulatory authorities is functional to fully unlock this potential. (shrink)

Promotion of prescription drugs may appear to be severely limited in some jurisdictions due to restrictions on direct-to-consumer advertising. However, in most jurisdictions, strategies exist to raise consumer awareness about prescription drugs, notably through the deployment of direct-to-consumer information campaigns that encourage patients to seek help for particular medical conditions. In Canada, DTCI is presented by industry and regulated by Health Canada as being purely informational activities, but their design and integration in broader promotional campaigns raise very similar ethical concerns (...) as those associated with DTCA. Specifically, DTCI can be an effective means of familiarizing the public with the scope and benefits of a particular prescription drug and so, like DTCA, can promote increased patient-consumer demand and thus a problematic rise in the prescribing and use of medications that may be neither the most appropriate nor the most cost-effective. Yet, with DTCI the industry is playing within the existing rules and regulations set by health regulators. To respond appropriately to this regulatory incoherence, we argue that DTCI should be regulated as a type of direct-to-consumer indirect advertising. Even if the case and specific regulations presented here are Canadian, the implications extend to every country that has a partial or total prohibition on DTCA. (shrink)

Do multi-level selection explanations of the evolution of social traits deepen the understanding provided by single-level explanations? Central to the former is a mathematical theorem, the multi-level Price decomposition. I build a framework through which to understand the explanatory role of such non-empirical decompositions in scientific practice. Applying this general framework to the present case places two tasks on the agenda. The first task is to distinguish the various ways of suppressing within-collective variation in fitness, and moreover to (...) evaluate their biological interest. I distinguish four such ways: increasing retaliatory capacity, homogenising assortment, and collapsing either fitness structure or character distribution to a mean value. The second task is to discover whether the third term of the Price decomposition measures the effect of any of these hypothetical interventions. On this basis I argue that the multi-level Price decomposition has explanatory value primarily when the sharing-out of collective resources is `subtractable'. Thus its value is more circumscribed than its champions Sober and Wilson (1998) suppose. (shrink)

This paper is devoted to present Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method for multi-attribute group decision making under rough neutrosophic environment. The concept of rough neutrosophic set is a powerful mathematical tool to deal with uncertainty, indeterminacy and inconsistency. In this paper, a new approach for multi-attribute group decision making problems is proposed by extending the TOPSIS method under rough neutrosophic environment. Rough neutrosophic set is characterized by the upper and lower approximation operators (...) and the pair of neutrosophic sets that are characterized by truth-membership degree, indeterminacy membership degree, and falsity membership degree. In the decision situation, ratings of alternatives with respect to each attribute are characterized by rough neutrosophic sets that reflect the decision makers’ opinion. Rough neutrosophic weighted averaging operator has been used to aggregate the individual decision maker’s opinion into group opinion for rating the importance of attributes and alternatives. Finally, a numerical example has been provided to demonstrate the applicability and effectiveness of the proposed approach. (shrink)

The aesthetics of tea, in some practices, seems to focus on appreciating the mental effects of tea — the altered states of mind. Wine aesthetics, on the other hand, seems to actively exclude any inebriative effects. Wine experts are supposed to spit, in order to avoid inebriation when they judge wine. Why? The answer, I suggest, lies deep in several key suppositions in the traditional model of aesthetic experience: that aesthetic experience needs to be accurate of its object, and that (...) it needs to be inseparable from the particular details of its object. But, I argue, that model is not really incompatible with an aesthetics of drugs. The problematic presupposition is that the aesthetics of drugs is either an aesthetics of the world, as experienced while drugged, or an aesthetics of the physical substance itself. The aesthetics of some drugs, such as LSD, will turn out, instead, to be a self-reflective aesthetics — one in which the primary object of appreciation is the alteration of one’s own cognitive faculties. This can be valuable as a humbling aesthetic vision, of one’s own cognitive fragility. But the aesthetics of gastronomical drugs, such as wine and tea, will turn out to be even more complicated. Gastronomical drugs demand that we bridge the inwardly-focused aesthetics of inebriation and an outwardly focused gastronomical aesthetics. They open the door to the possibility of an aesthetic reconciliation between our capacity to get onto the world, and our fears about the fragility of that capacity. (shrink)

In this paper, we define projection and bidirectional projection measures between interval rough neutrosophic sets and prove their basic properties. Then two new multi attribute decision making strategies are proposed based on interval rough neutrosophic projection and bidirectional projection measures respectively. Then the proposed methods are applied for solving multi attribute decision making problems. Finally, a numerical example is solved to show the feasibility, applicability and effectiveness of the proposed strategies.

The illegal drug trade is a world phenomenon, which has had some adverse impact on societies. Significantly, the impact is damning in developing economies in Africa and Ghana in particular. This paper therefore seeks to address the causes and effects of the use and peddle of these illegal drugs in three communities in the capital city of the Asante Region of Ghana. It further ascertains the extent to which these drugs burden the security agencies in the communities and the (...) country in general. We have used documentary and non-documentary sources to arrive at some postulations on this important social question which has wider ramifications on Kumase, Asante, Ghana and Africa in general. (shrink)

Measuring the effectiveness of medical interventions faces three epistemological challenges: the choice of good measuring instruments, the use of appropriate analytic measures, and the use of a reliable method of extrapolating measures from an experimental context to a more general context. In practice each of these challenges contributes to overestimating the effectiveness of medical interventions. These challenges suggest the need for corrective normative principles. The instruments employed in clinical research should measure patient-relevant and disease-specific parameters, and should not be sensitive (...) to parameters that are only indirectly relevant. Effectiveness always should be measured and reported in absolute terms (using measures such as 'absolute risk reduction'), and only sometimes should effectiveness also be measured and reported in relative terms (using measures such as 'relative risk reduction')-employment of relative measures promotes an informal fallacy akin to the base-rate fallacy, which can be exploited to exaggerate claims of effectiveness. Finally, extrapolating from research settings to clinical settings should more rigorously take into account possible ways in which the intervention in question can fail to be effective in a target population. (shrink)

The banking sector faces growing challenges in identifying and managing risks due to the complexity of financial transactions and increasing fraud. This research presents a framework that combines multiple agents with deep learning to improve risk prediction in banking. Each agent focuses on specific tasks like cleaning data, selecting important features, and detecting unusual activities, ensuring a detailed risk assessment. A deep learning model is used to analyze large amounts of transaction data and identify patterns that may signal potential risks. (...) Tests on real-world banking data show that this approach is more accurate, faster, and effective than traditional methods. By combining the strengths of multi-agent systems and deep learning, this study offers a reliable and flexible solution to help banks manage and adapt to changing risks more effectively. (shrink)

It has long been thought that observing distinctive traces of quantum gravity in a laboratory setting is effectively impossible, since gravity is so much weaker than all the other familiar forces in particle physics. But the quantum gravity phenomenology community today seeks to do the (effectively) impossible, using a challenging novel class of `tabletop' Gravitationally Induced Entanglement (GIE) experiments, surveyed here. The hypothesized outcomes of the GIE experiments are claimed by some (but disputed by others) to provide a `witness' (...) of the underlying quantum nature of gravity in the non-relativistic limit, using superpositions of Planck-mass bodies. We inspect what sort of achievement it would possibly be to perform GIE experiments, as proposed, ultimately arguing that the positive claim of witness is equivocal. Despite various sweeping arguments to the contrary in the vicinity of quantum information theory or given low-energy quantum gravity, whether or not one can claim to witness the quantum nature of the gravitational field in these experiments decisively depends on which out of two legitimate modelling paradigms one finds oneself in. However, by situating GIE experiments in a tradition of existing experiments aimed at making gravity interestingly quantum in the laboratory, we argue that, independently of witnessing or paradigms, there are powerful reasons to perform the experiments, and that their successful undertaking would indeed be a major advance in physics. (shrink)

Philosophical and empirical research on bodily awareness has mostly focused so far on bodily disorders – such as anorexia nervosa, somatoparaphrenia, or xenomelia (body integrity dysphoria) – and bodily illusions induced in an experimental setting – such as the rubber hand illusion, or the thermal grid illusion. Studying these conditions can be illuminating to investigate a broad range of issues about the nature, function, and etiology of bodily experience. However, a number of psychoactive compounds can also induce a remarkably wide (...) variety of bodily effects that have received little attention despite their relevance to these issues. Some of these effects are similar to those associated with bodily disorders or experimental bodily illusions, while others appear to be unique. The purpose of this chapter is to provide an overview of these lesser known bodily effects of psychoactive compounds, and outline some ways in which they can bear on recent debates regarding bodily awareness and bodily ownership. (shrink)

Historically, laws and policies to criminalize drug use or possession were rooted in explicit racism, and they continue to wreak havoc on certain racialized communities. We are a group of bioethicists, drug experts, legal scholars, criminal justice researchers, sociologists, psychologists, and other allied professionals who have come together in support of a policy proposal that is evidence-based and ethically recommended. We call for the immediate decriminalization of all so-called recreational drugs and, ultimately, for their timely and appropriate legal (...) regulation. We also call for criminal convictions for nonviolent offenses pertaining to the use or possession of small quantities of such drugs to be expunged, and for those currently serving time for these offenses to be released. In effect, we call for an end to the “war on drugs.”. (shrink)

The purpose of this study is to propose new similarity measures namely rough variational coefficient similarity measure under the rough neutrosophic environment. The weighted rough variational coefficient similarity measure has been also defined. The weighted rough variational coefficient similarity measures between the rough ideal alternative and each alternative are xxxxx calculated to find the best alternative. The ranking order of all the alternatives can be determined by using the numerical values of similarity measures. Finally, an illustrative example has been provided (...) to show the effectiveness and validity of the proposed approach. Comparisons of decision results of existing rough similarity measures have been provided. (shrink)

Access to students’ perspectives on substance abuse is essential for effective youth intervention projects development. This study aimed to explore students’ perspectives on abuse of drugs and alcohol with probable development of student-led intervention strategies. The study was conducted at public universities in Zambia. Student’s perspectives on drugs and alcohol abuse were documented using a mixed method design that employed purposive and snowball sampling to select 200 respondents to questionnaires and 10 to in-depth interviews. A humanistic theory approach was applied (...) in the interpretation and analysis of the data collected. The findings showed that cannabis (30%) and codeine contained in Benylin (17%) were commonly abused. Further findings showed that students’ academic pressure was the leading cause of substance abuse (27%), followed by peer pressure (20%). Students knew that abuse of drugs and alcohol led to low academic performance, violence and theft, risks of contracting sexually transmitted infections (STIs), and other social maladjustments. The study recommends that institutions of learning increase student-led awareness campaigns, security surveillance on campus, and collaboration with government drug enforcement agencies. Institutions of learning should involve students in the planning of programmes to deal with drug and alcohol abuse. Contribution: The study will inform amendment of drug and alcohol abuse policies in institutions of learning. The study will contribute towards the UNESCO O3 PLUS project goal of making campuses safe and inclusive, and overall, the Sustainable Development Goal 3 and 4. The study serves as basis for scholars in the field of biblical theology engaged with justice, health and human development. The article is a contribution to the research project Biblical Theology and Hermeneutics. The results of this research can especially be utilised by scholars in the field of psychology of religion, the sociology of religion and practical theologians focusing on youth ministry. (shrink)

The adoption of multi-cloud environments has become a strategic necessity for organizations seeking scalability, flexibility, and operational efficiency. However, distributing workloads across multiple cloud providers introduces significant security challenges, including authentication vulnerabilities, inconsistent security policies, data breaches, and compliance risks. Traditional security approaches often fail to address the complexity of multi-cloud ecosystems, requiring a more comprehensive risk mitigation strategy. This paper analyses key security risks in multi-cloud architectures and evaluates industry-standard risk assessment frameworks to prioritize effective countermeasures. (...) Our findings indicate that authentication, access control, and secure cloud networking are the most critical areas requiring immediate attention. Threats such as identity mismanagement, insecure data transfers, and lack of unified monitoring further escalate security concerns. To mitigate these risks, we propose a combination of zero-trust architecture, robust identity and access management (IAM), encryption protocols, and AI-driven threat detection. Implementing these strategies can enhance data integrity, regulatory compliance, and overall cloud security posture. By adopting a proactive approach, IT leaders can optimize cybersecurity investments and ensure the resilience of multi-cloud environments. This study provides actionable insights to strengthen security in distributed cloud architectures, enabling organizations to defend against evolving cyber threats. (shrink)

On edge computing, mobile devices can offload some computing intensive tasks to the cloud so that the time delay and battery losses can be reduced. Different from cloud computing, an edge computing model is under the constraint of radio transmitting bandwidth, power and etc. With regard to most models in presence, each user is assigned to a single mission, transmitting power or local CPU frequency on mobile terminals is deemed to be a constant. Furthermore, energy consumption has a positive correlation (...) with the above two parameters. In a context of multitask, such values could be increased or reduced according to workload to save energy. Additionally, the existing offloading methods are inappropriate if all the compute densities of multiple tasks are high. In this paper, a single-user multi-task with high computing density model is proposed and partial task is offloaded when use the different offload algorithm. Simulated annealing algorithm is the best method to select offloading tasks, which can enhance the offloading ratio and save energy consumption. (shrink)

Efforts by governments, firms, and patients to deliver pioneering drugs for critical health needs face a challenge of diminishing efficiency in developing those medicines. While multi-sectoral collaborations involving firms, researchers, patients, and policymakers are widely recognized as crucial for countering this decline, existing incentives to engage in drug development predominantly target drug manufacturers and thereby do little to stimulate collaborative innovation. In this mini review, we consider the unexplored potential within pharmaceutical regulations to create novel incentives to (...) encourage a diverse set of actors from the public and private spheres to engage in the kind of collaborative knowledge exchange requisite for fostering enhanced innovation in early drug development. (shrink)

There are a number of premises underlying much of the vigorous debate on pharmacological cognitive enhancement. Among these are claims in the enhancement literature that such drugs exist and are effective among the cognitively normal. These drugs are deemed to enhance cognition specifically, as opposed to other non-cognitive facets of our psychology, such as mood and motivation. The focus on these drugs as cognitive enhancers also suggests that they raise particular ethical questions, or perhaps more pressing ones, compared to those (...) raised by other kinds of neuroenhancement. Finally, the use of these drugs is often claimed to be significant and increasing. Taken together, these premises are at the heart of the flurry of debate on pharmacological cognitive enhancement. In this article, it is argued that these are presumptions for which the evidence does not hold up. Respectively, the evidence for the efficacy of these drugs is inconsistent; neurologically it makes little sense to distinguish the cognitive from non-cognitive as separate targets of pharmacological intervention; ethically, the questions raised by cognitive enhancement are in fact no different from those raised by other kinds of neuroenhancement; and finally the prevalence rates of these drugs are far from clear, with the bulk of the claims resting on poor or misrepresented data. Greater conceptual clarity along with a more tempered appreciation of the evidence can serve to deflate some of the hype in the associated literature, leading to a more realistic and sober assessment of these prospective technologies. (shrink)

Side effects are ubiquitous in medicine and they often play a role in treatment decisions for patients and clinicians alike. Philosophers and health researchers often use side effects to illustrate issues with contemporary medical research and practice. However, technical definitions of ‘side effect’ differ among health authorities. Thus, determining the side effects of an intervention can differ depending on whose definition we assume. Here I review some of the common definitions of side effect and highlight their issues. In response, I (...) offer an account of side effects as jointly (i) unintended and (ii) effects due to the causal capacities or invariances of an intervention. I discuss (i) by examining the intentions or reasons behind therapeutic interventions, and I discuss (ii) by appealing to a manipulationist model of causation. The analysis here highlights that side effects are conceptually distinct from related outcomes like adverse events, adverse drug reactions, and placebo effects. The analysis also allows for reflection on the utility of ‘side effect’ as a technical term in medical research and practice. (shrink)

The proliferation of Internet of Things (IoT) devices has introduced a range of opportunities for enhanced connectivity, automation, and efficiency. However, the vast array of interconnected devices has also raised concerns regarding cybersecurity, particularly due to the limited resources and diverse nature of IoT devices. Intrusion detection systems (IDS) have emerged as critical tools for identifying and mitigating security threats. This paper proposes a Multi-Layer Intrusion Detection Framework for IoT systems, leveraging Ensemble Machine Learning (EML) techniques to improve the (...) accuracy and effectiveness of detecting intrusions. The proposed framework integrates multiple layers of defense, including data preprocessing, feature extraction, classification, and post-processing, to provide a robust solution to IoT security challenges. This research explores the application of EML methods such as Random Forests, AdaBoost, and Gradient Boosting, combining them into a unified model to detect and mitigate various types of attacks in IoT environments. Experimental results demonstrate the superiority of the proposed framework in terms of detection accuracy, false positive rate, and computational efficiency. (shrink)

The paper proposes a new technique for dealing with multi-attribute decision making problems through an extended TOPSIS method under neutrosophic cubic environment. Neutrosophic cubic set is the generalized form of cubic set and is the hybridization of a neutrosophic set with an interval neutrosophic set. In this study, we have defined some operation rules for neutrosophic cubic sets and proposed the Euclidean distance between neutrosophic cubic sets. In the decision making situation, the rating of alternatives with respect to some (...) predefined attributes are presented in terms of neutrosophic cubic information where weights of the attributes are completely unknown. In the selection process, neutrosophic cubic positive and negative ideal solutions have been defined. An extended TOPSIS method is then proposed for ranking the alternatives and finally choosing the best one. Lastly, an illustrative example is solved to demonstrate the decision making procedure and effectiveness of the developed approach. (shrink)

Many multinational corporations develop business operations in Europe. The current research attempts to fill the gap on how corporations can increase their political influence in this geography by exploring the joint effect of corporate political activity(CPA) and social responsibility (CSR) on political embeddedness and financial performance. Based on institutional theory and on a sample of autochthonous (European Union [EU]) and allochthonous (non-EU) firms with declared EU lobbying (from 2008to 2019) we conducted two studies. Based on a multi-level model, Study (...) 1 finds strong and robust evidence that boardroom gender diversity and EU lobbyists inter-actively increase EU political embeddedness. Complementarily, Study 2, which relies on general linear Modeling, suggests that allochthonous corporations are more profit-able when they display high-level political embeddedness and lobbying expenditures, combined with adoption of United Nations (UN) guidelines. Overall, findings show that lobbying in Europe pays off, especially when corporations strive to be aligned with EU ethical values and aspirations. Hiring lobbyists to be based in Brussels and promoting gender equality help establish EU political connections. Subsequently, findings highlight the role that EU political embeddedness, lobbying expenditures, and UN guidelines play in leveraging financial performance, especially across non-EU corporations. Regarding EU corporations, results show that a firm-level investment on CPA-CSR is particularly important. Overall, findings from this research support corporations that are growing businesses in Europe. KEYWORDScorporate political activity, corporate social responsibility, lobbying, return on assets (ROA),United Nations (UN_. (shrink)

The underreporting of suspected adverse drug reactions remains a primary issue for contemporary post-market drug surveillance or ‘pharmacovigilance.’ Pharmacovigilance pioneer W.H.W. Inman argued that ‘deadly sins’ committed by clinicians are to blame for underreporting. Of these ‘sins,’ ignorance and lethargy are the most obvious and impactful in causing underreporting. However, recent analyses show that diffidence, insecurity, and indifference additionally play a major role. I aim to augment our understanding of diffidence, insecurity, and indifference by arguing these sins are (...) underwritten by value judgments arising via epistemic risk. I contend that ‘evidence-based’ medicine codifies these sins. (shrink)