Abstract: The Spotify Status Dataset is a valuable resource that provides real-time insights into the operational status and performance of Spotify, a popular music streaming platform. This dataset contains a wide array of information related to server uptime, user activity, service disruptions, and more, serving as a critical tool for both Spotify's internal monitoring and the broader data analysis community. As digital services like Spotify continue to play a central role in music consumption, understanding the platform's status becomes crucial for (...) ensuring a seamless user experience. This dataset offers numerous research and analysis opportunities, whether you're interested in exploring service availability trends or investigating user behavior patterns during service disruptions. This study highlights the significance of the Spotify Status Dataset, its potential applications, and the valuable insights it can offer to various stakeholders, from Spotify engineers working to enhance service reliability to researchers studying the effects of downtime on user engagement. It invites readers on a journey through this dataset to uncover the secrets of Spotify's operational status and its impact on music enthusiasts worldwide. (shrink)

Abstract Alzheimer's disease has spread insanely throughout the world. Early detection and intervention are essential to improve the chances of a positive outcome. This study presents a new method to predict a person's likelihood of developing Alzheimer's using a neural network model. The dataset includes 373 samples with 10 features, such as Group,M/F,Age,EDUC, SES,MMSE,CDR ,eTIV,nWBV,Oldpeak,ASF.. A four-layer neural network model (1 input, 2 hidden, 1 output) was trained on the dataset and achieved an accuracy of 98.10% and an average error (...) of 0.01. This study provides a valuable tool for early detection and intervention of Alzheimer's, thus contributing to the field of health and medicine. (shrink)

Abstract: This research delves into the utilization of Artificial Neural Networks (ANNs) as a powerful tool for predicting the overall ratings of books by leveraging a diverse set of attributes. To achieve this, we employ a comprehensive dataset sourced from Goodreads, enabling us to thoroughly examine the intricate connections between the different attributes of books and the ratings they receive from readers. In our investigation, we meticulously scrutinize how attributes such as genre, author, page count, publication year, and reader reviews (...) influence a book's overall rating. Through rigorous analysis and experimentation, we construct an advanced ANN model tailored for predictive analysis in the realm of book ratings. The outcomes of our study reveal the remarkable potential of ANNs in this domain. The ANN model exhibits an impressive level of accuracy when it comes to forecasting book ratings, underlining the efficacy and promise of artificial neural networks in enhancing our understanding and prediction of book evaluations. This research opens up new avenues for leveraging machine learning techniques to gain deeper insights into the dynamics of book ratings and reader preferences. (shrink)

In this review, we present some ethical imperatives observed in this pandemic from a data ethics perspective. Our exposition connects recurrent ethical problems in the discipline, such as, privacy, surveillance, transparency, accountability, and trust, to broader societal concerns about equality, discrimination, and justice. We acknowledge data ethics role as significant to develop technological, inclusive, and pluralist societies. - - - Resumen: En esta revisión, exponemos algunos de los imperativos éticos observados desde la ética de datos en esta pandemia. Nuestra exposición (...) busca conectar problemas éticos típicos dentro de esta disciplina, a saber, privacidad, vigilancia, transparencia, responsabilidad y confianza, con preocupaciones a nivel social relacionadas con la igualdad, discrimi nación y justicia. Consideramos que la ética de datos tiene un rol significativo para desarrollar sociedades tecnificadas, inclusivas y pluralistas. (shrink)

Anydomainofscientificresearchhasitssustainingorthodoxy. Thatis, research on a problem, whether in astronomy, physics, or biology, is con- ducted against a backdrop of broadly shared assumptions. It is these as- sumptionsthatguideinquiryandprovidethecanonofwhatisreasonable-- of what "makes sense." And it is these shared assumptions that constitute a framework for the interpretation of research results. Research on the problem of how we see is likewise sustained by broadly shared assump- tions, where the current orthodoxy embraces the very general idea that the business of the visual system is to (...) create a detailed replica of the visual world, and that it accomplishes its business via hierarchical organization and by operatingessentiallyindependently of other sensorymodalitiesas well as independently of previous learning, goals, motor planning, and motor execution. (shrink)

Coronary artery vasospasm (CAVS) is a clinical entity that can cause angina, but also unstable angina pectoris, acute myocardial infarction, fatal arrhythmias, and sudden death. Although it is a condition that is usually controlled with medical treatment, more aggressive treatments may rarely be required. In this case, the patient with a known diagnosis of CAVS had multiple arrests despite optimal medical treatment. We observed that fatal arrhythmias persisted in the Implantable Cardioverter Defibrillator (ICD) records, even though we implanted a stent (...) and gave the patient maximal medical treatment. We performed sympathectomy as a last resort and we did not detect any recurrence in the 6-month follow-up of the patient. ICD implantation and sympathectomy should always be considered in resistant CAVS cases. (shrink)

Abstract: This study aims to identify the level of creativity in the University of Palestine from the point of view of the employees, as the researchers used the descriptive and analytical method, through a questionnaire distributed to a sample of employees at the University of Palestine, where the size of the study population is (234) employees, and the size of the sample (117) employees, of which (90) employees responded. The study reached a set of results, the most important of which (...) are: A high degree of creativity from the employees 'point of view, and the study confirmed that there were no differences in the level of creativity at the University of Palestine from the Employees point of view, according to demographic variables. The study presented a set of recommendations, the most important of which are: The need for universities to enhance creativity. (shrink)

Family members can provide crucial support to individuals participating in clinical trials. In research on the “newest frontier” of Deep Brain Stimulation (DBS)—the use of DBS for psychiatric conditions—family member support is frequently listed as a criterion for trial enrollment. Despite the significance of family members, qualitative ethics research on DBS for psychiatric conditions has focused almost exclusively on the perspectives and experiences of DBS recipients. This qualitative study is one of the first to include both DBS recipients and their (...) family members as interview participants. Using dyadic thematic analysis—an approach that takes both the individuals and the relationship as units of analyses—this study analyzes the complex ways in which family relationships can affect DBS trial participation, and how DBS trial participation in turn influences family relationships. Based on these findings, we propose ways to improve study designs to better take family relationships into account, and better support family members in taking on the complex, essential roles that they play in DBS trials for psychiatric conditions. (shrink)

Water quality assessment is critical for environmental sustainability and public health. This research employs neural networks to predict water quality, utilizing a dataset of 21 diverse features, including metals, chemicals, and biological indicators. With 8000 samples, our neural network model, consisting of four layers, achieved an impressive 94.22% accuracy with an average error of 0.031. Feature importance analysis revealed arsenic, perchlorate, cadmium, and others as pivotal factors in water quality prediction. This study offers a valuable contribution to enhancing water quality (...) monitoring and decision-making for stakeholders and policymakers. (shrink)

Malaria is a life-threatening disease spread to humans by some types of mosquitoes. It is mostly found in tropical countries. It is preventable and curable. The infection is caused by a parasite and does not spread from person to person. Symptoms can be mild or life-threatening. Mild symptoms are fever, chills and headache. Severe symptoms include fatigue, confusion, seizures, and difficulty breathing. Infants, children under 5 years, pregnant women, travelers and people with HIV or AIDS are at higher risk of (...) severe infection. Discovering this disease is a good step for proper and correct treatment. Determining the treatment with high accuracy depends on the method used in the diagnosis. Correctly, expert systems can greatly help to avoid spreading this disease. The expert system diagnoses malaria disease correctly to facilitate doctors to find the correct treatment based on the appropriate diagnosis. Objectives: An expert system has been established based on CLIPS to diagnose malaria disease. (shrink)

Background: Obstetrics and gynaecology are many and common, where a woman suffers from problems related to pregnancy or her reproductive organs. Any part of her body may be affected due to some symptoms that are completely related to the reproductive organs when she is in a critical period for her, whether in her menstrual cycle, pregnancy, or disease conditions. The bulk of cases of diseases related to women and childbirth are dealt with great care and special care, as all diseases (...) related to women are considered very sensitive diseases due to the presence of the disease in sensitive and not simple places. A gynaecologist is a specialist in all diseases and problems related to the female sexual organs. They perform regular preventive medical exams, such as cervical smear tests and breast exams. It also provides consultations for women of all ages about the problems of contraception, infertility and menopause. Objectives: The objective of this expert system is to help and facilitate women in diagnosing diseases related to their obstetrics and gynaecology, a simple expert system has been designed consisting of ten various common diseases that affect women whether During or without pregnancy, Methods: In this system, the system consists of a list of some common symptoms, the correct diagnosis adopted for these diseases, and how to treat diseases in the correct way with the help of a consultant obstetrician and gynaecologist, Dr. Fathi Muhammad Al-Habibi, and these diseases are: uterine cancer, cervical cancer, Infertility, double uterus, ectopic pregnancy, endometrial cancer, female sexual dysfunction, endometriosis, faecal incontinence, female infertility, CLIPS Expert System language was used to design and implement the proposed expert system. Results: The proposed ten obstetrics and gynaecology diagnostic expert system was evaluated by medical students and they were satisfied with its performance. Conclusions: The proposed expert system is very useful for obstetricians and gynaecologists, patients with reproductive system problems, and recent graduates. (shrink)

heart attack analysis & prediction dataset is a major cause of death worldwide. Early detection and intervention are essential for improving the chances of a positive outcome. This study presents a novel approach to predicting the likelihood of a person having heart failure using a neural network model. The dataset comprises 304 samples with 11 features, such as age, sex, chest pain type, Trtbps, cholesterol, fasting blood sugar, resting electrocardiogram results, maximum heart rate achieved, exercise-induced angina, oldpeak, ST_Slope, and HeartDisease. (...) A neural network model with four layers (1 input, 2 hidden, 1 output) was trained on the dataset and achieved an accuracy of 88% and an average error of 0078296. The most influential factors in heart failure prediction were found to be oldpeak, ST_Slope, sex, fastingBS, chestPainType, exerciseAngina, cholesterol, restingBP, maxHR, restingBP, and age. This study provides a valuable tool for early detection and intervention of heart failure, thereby contributing to the field of health and medicine. (shrink)

Historically, republicans were of different minds about markets: some, such as Rousseau, reviled them, while others, like Adam Smith, praised them. The recent republican resurgence has revived this issue. Classical liberals such as Gerald Gaus contend that neo-republicanism is inherently hostile to markets, while neo-republicans like Richard Dagger and Philip Pettit reject this characterization—though with less enthusiasm than one might expect. I argue here that the right republican attitude toward competitive markets is celebratory rather than acquiescent and that republicanism demands (...) such markets for the same reason it requires the rule of law: because both are essential institutions for protecting individuals from arbitrary interference. I reveal how competition restrains—and in the limit, even eradicates—market power and thereby helps us realize “market freedom,” i.e., freedom as non-domination in the context of economic exchange. Finally, I show that such freedom necessitates “Anglo-Nordic” economic policies. (shrink)

This research paper presents the development and evaluation of an expert system for diagnosing kidney diseases. The expert system utilizes a decision-making tree approach and is implemented using the CLIPS and Delphi frameworks. The system's accuracy in diagnosing kidney diseases and user satisfaction were evaluated. The results demonstrate the effectiveness of the expert system in providing accurate diagnoses and high user satisfaction.

Abstract: The emergence of the novel coronavirus (COVID-19) in 2019 has presented the world with an unprecedented global health crisis. The rapid and widespread transmission of the virus has strained healthcare systems, disrupted economies, and challenged societies. In response to this monumental challenge, the intersection of technology and healthcare has become a focal point for innovation. This research endeavors to leverage the capabilities of Artificial Neural Networks (ANNs) to develop an advanced predictive model for forecasting the spread of COVID-19. It (...) involves the collection, analysis, and integration of diverse datasets encompassing epidemiological, clinical, and social factors that influence the virus's dissemination. (shrink)

This introduction to the Journal of Business Research special issue on anti-consumption briefly defines and highlights the importance of anticonsumption research, provides an overview of the latest studies in the area, and suggests an agenda for future research on anti-consumption.

A nation’s economy runs on the knowledge and skills of its people.Quality assurance mechanisms for higher education institutions must take cognizance of the graduates' acquisition of skills to become productive and contributory for societal development. The study is a quantitative survey assessing the attainment of the immediate program learning outcomes of the graduating Bachelor of Science in Information Technology of one campus of a public higher education institution in the Philippines. It also assessed the introspection and level of satisfaction of (...) the graduates in their studies. Findings disclosed that the graduates have a high level of attainment of the program's learning outcomes and a high level of satisfaction. The high school where the respondents graduated is the single variable that defined the difference in attainment of program intended learning outcomes. As to the graduates' introspections, themost significant percentage of them learned the program from family, relatives, and friends. Reasons for pursuing the degree program are because of parents’ influence, prestige of IT profession. Meanwhile, the university's reputation, affordable tuition fees, and proximity to home were the factors affecting the enrolment in the BSIT program. The findings will be the basis for strategic program interventions of the program. (shrink)

Ever since Darwin people have worried about the sceptical implications of evolution. If our minds are products of evolution like those of other animals, why suppose that the beliefs they produce are true, rather than merely useful? We consider this problem for beliefs in three different domains: religion, morality, and commonsense and scientific claims about matters of empirical fact. We identify replies to evolutionary scepticism that work in some domains but not in others. One reply is that evolution can be (...) expected to design systems that produce true beliefs in some domain. This reply works for commonsense beliefs and can be extended to scientific beliefs. But it does not work for moral or religious beliefs. An alternative reply which has been used defend moral beliefs is that their truth does not consist in their tracking some external state of affairs. Whether or not it is successful in the case of moral beliefs, this reply is less plausible for religious beliefs. So religious beliefs emerge as particularly vulnerable to evolutionary debunking. (shrink)

Abstract: The aim behind analyzing the Goodreads dataset is to get a fair idea about the relationships between the multiple attributes a book might have, such as: the aggregate rating of each book, the trend of the authors over the years and books with numerous languages. With over a hundred thousand ratings, there are books which just tend to become popular as each day seems to pass. We proposed an Artificial Neural Network (ANN) model for predicting the overall rating of (...) books. The prediction is based on these features (bookID, title, authors, isbn, language_code, isbn13, # num_pages, ratings_count, text_reviews_count), which were used as input variables and (average_rating) as output variable for our ANN model. Our model were created, trained, and validated using data set in JNN environment, which its title is “Goodreads-books”. Model evaluation showed that the ANN model is able to predict correctly 99.78% of the validation samples. (shrink)

Host-microbiome interactions (HMIs) are critical for the modulation of biological processes and are associated with several diseases, and extensive HMI studies have generated large amounts of data. We propose that the logical representation of the knowledge derived from these data and the standardized representation of experimental variables and processes can foster integration of data and reproducibility of experiments and thereby further HMI knowledge discovery. A community-based Ontology of Host-Microbiome Interactions (OHMI) was developed following the OBO Foundry principles. OHMI leverages established (...) ontologies to create logically structured representations of microbiomes, microbial taxonomy, host species, host anatomical entities, and HMIs under different conditions and associated study protocols and types of data analysis and experimental results. (shrink)

The major competing statistical paradigms share a common remarkable but unremarked thread: in many of their inferential applications, different probability interpretations are combined. How this plays out in different theories of inference depends on the type of question asked. We distinguish four question types: confirmation, evidence, decision, and prediction. We show that Bayesian confirmation theory mixes what are intuitively “subjective” and “objective” interpretations of probability, whereas the likelihood-based account of evidence melds three conceptions of what constitutes an “objective” probability.

The past four decades of research in the social sciences have shed light on two important phenomena. One is that human decision-making is full of predicable errors and biases that often lead individuals to make choices that defeat their own ends (i.e., the bad choice phenomenon), and the other is that individuals’ decisions and behaviors are powerfully shaped by their environment (i.e., the influence phenomenon). Some have argued that it is ethically defensible that the influence phenomenon be utilized to address (...) the bad choice phenomenon. They propose that “choice architects” learn about the various ways in which choices can be influenced and directed by the environment, and then work to design environments, broadly construed, that influence individuals towards choices that make them better off. Those who advocate intentionally creating choice environments that lead people to better choices believe that doing so is ethically permissible because (1) it makes people better off, and (2) it does so in a way that is entirely compatible with individual liberty. The evaluation of these two claims is the main focus of this paper. (shrink)

Comparing the degree of openness of the economy of Poland and the Netherlands, we can say the following. The Netherlands is more dependent on foreign trade than Poland. The Netherlands export quota reaches almost 50%, unlike 41,37% in Poland in 2016. However, Poland has become more import-dependent. Poland, in contrast to the Netherlands, is continuing to increase the indicators of "economic globalization". To date, the Netherlands has been pursuing more moderate foreign trade policy and trying to protect itself from external (...) risks by focusing on an internal market with high purchasing power. On the contrary, Polish politics tries to focus on the new markets for its products in order to increase the prosperity and well-being of its citizens. Poland as a country and an economic entity has made a qualitative leap in its development. The economy of this country has become more open and integrated into the world economy. (shrink)

In the longstanding debate between liberals and libertarians over the morality of redistributive labor taxation, liberals such as John Rawls and Ronald Dworkin have consistently taken the position that such taxation is perfectly compatible with individual liberty, whereas libertarians such as Robert Nozick and Murray Rothbard have adopted the (very) contrary position that such taxation is tantamount to slavery. In this paper, I argue that the debate over redistributive labor taxation can be usefully reconstituted as a debate over the incidents (...) (or components) of self-ownership, with liberals arguing for a narrow definition of the concept and libertarians arguing for a broad one. By using what Alan Ryan has called the “language of proprietorship,” I pinpoint precisely the source of the disagreement between liberals and libertarians and assess the relative strengths of their arguments. I also show that the respective definitions of self-ownership used by liberals and libertarians are deeply problematic—though for strikingly different reasons. (shrink)

The question of authenticity centers in the lives of women of color to invite and restrict their representative roles. For this reason, Gayatri Chakravorty Spivak and Uma Narayan advocate responding with strategic essentialism. This paper argues against such a strategy and proposes an epistemic understanding of the question of authentic- ity. The question stems from a kernel of truth—the connection between experience and knowledge. But a coherence theory of knowledge better captures the sociality and the holism of experience and knowledge.

A liberal antinomy of parenting exists: strong liberal intuitions militate in favor of both denying special resources to parenting projects (on grounds of project-neutrality) and granting them (on grounds of respect for personhood). I show that we can reconcile these two claims by rejecting a premise common to both--viz. that liberalism is necessarily committed to extensive procreative liberties--and limiting procreation and subsequent parenting to adults who meet certain psychological and especially financial criteria. I also defend this argument, which provides a (...) Kantian complement to utilitarian arguments for restricting procreation, against a variety of objections. (shrink)

Robert Nozick, in chapter two of the nature of rationality, proposes two famous problems in decision theory (i.e., Newcomb's problem and Prisoner Dilemma) and two main strategies toward these problems i.e. dominant strategy and dominated or cooperative one. He will try to give a formal principles to calculate the decision values in these situations. In this calculation he goes beyond the standard principle of maximizing expected utility and would try to put forth less ideal and more realistic principles that fit (...) the decision situation in the real world. (shrink)

Clark and Chalmers (1998) defend the hypothesis of an ‘Extended Mind’, maintaining that beliefs and other paradigmatic mental states can be implemented outside the central nervous system or body. Aspects of the problem of ‘language acquisition’ are considered in the light of the extended mind hypothesis. Rather than ‘language’ as typically understood, the object of study is something called ‘utterance-activity’, a term of art intended to refer to the full range of kinetic and prosodic features of the on-line behaviour of (...) interacting humans. It is argued that utterance activity is plausibly regarded as jointly controlled by the embodied activity of interacting people, and that it contributes to the control of their behaviour. By means of specific examples it is suggested that this complex joint control facilitates easier learning of at least some features of language. This in turn suggests a striking form of the extended mind, in which infants’ cognitive powers are augmented by those of the people with whom they interact. (shrink)

In the summer of 2016, the University of Dallas and the Instituto Tecnológico Autónomo de México organized a conference to discuss the topic of the middle class and its continued decline—recognizing that, despite some historical, political and cultural differences, healthy democracies throughout the hemisphere depend upon a strong and prosperous middle class. This volume brings together contributions by nine scholars from both institutions. The chapters reflect diverse disciplinary perspectives that are historical, political, economic, anthropological, and philosophical. Despite this diversity, the (...) volume possesses a conceptual unity that stems from its foundation in Aristotle’s approach to the middle class. On this basis, the topic is given a rigorous study that is both theoretical and data-driven. The chapters include treatments of Aristotle, Montesquieu, Adam Smith and Sir James Steuart, Catholic social teaching, the problem of inequality in the US, the definition and measurement of the middle class in Mexico, as well as its values and political attitudes, the rise of middle-class politics in early-twentieth-century Latin America, and a comparative analysis of healthcare for the middle class in North America. (shrink)

In this paper I argue that self-respect constitutes an important value, and further, serves as an important basis for equality. I also argue that under conditions of inequality-producing segregation, voluntary separation in schooling may be more likely to provide the resources necessary for self respect. Accordingly, I defend a prima facie case of voluntary separation for stigmatized minorities when equality – as equal status and treatment – is not an option under either the terms of integration or involuntary segregation.

A newborn baby is an infant within the first 28 days of birth. Diagnosis and treatment of infant diseases require specialized medical resources and expert knowledge. However, there is a shortage of such professionals globally, particularly in low-income countries. To address this challenge, a knowledge-based system was designed to aid in the diagnosis and treatment of neonatal diseases. The system utilizes both machine learning and health expert knowledge, and a hybrid data mining process model was used to extract knowledge from (...) a clinical dataset. The PART algorithm achieved the highest performance result with 98.06% accuracy under 10-fold cross-validation, and the generated rules were used to develop the knowledge-based system. The system achieved 90.9% accuracy in system performance testing and 89.2% in user acceptance testing, and is intended to serve as an assistant tool for healthcare experts. (shrink)

One of the many arguments against capital punishment is that execution is irrevocable. At its most simple, the argument has three premises. First, legal institutions should abolish penalties that do not admit correction of error, unless there are no alternative penalties. Second, irrevocable penalties are those that do not admit of correction. Third, execution is irrevocable. It follows that capital punishment should be abolished. This paper argues for the third premise. One might think that the truth of this premise is (...) self-evident. But in his paper “Is the Death Penalty Irrevocable?” Mike Davis argues that it is false: the death penalty is not irrevocable. While Davis’ argument is itself somewhat compelling, it receives additional support from work in the metaphysics of death, specifically the literature on posthumous harm. Strengthened in this way, the argument deserves careful consideration. I begin with a quick sketch of Davis’ argument, then show how the Pitcher-Feinberg theory of posthumous harm enables a more robust argument against the irrevocability of capital punishment, defending their theory of harm against standard objections in the literature. Having established the coherency of the robust argument, I conclude that it nevertheless fails to make the case against irrevocability. This is because it ignores the full set of practical requirements incumbent on legal institutions that wrongly punish someone. (shrink)

Abstract: In this study, we explore the possibility of classifying the plant species. We collected the plant species from Kaggle website. This dataset encompasses 544 samples, encompassing 136 distinct plant species. Recent advancements in machine learning, particularly Artificial Neural Networks (ANNs), offer promise in enhancing plant Species classification accuracy and efficiency. This research explores plant Species classification, harnessing neural networks' power. Utilizing a rich dataset from Kaggle, containing 544 entries, we develop and evaluate a neural network model. Our neural network, (...) featuring a single hidden layer, achieves remarkable results—a staggering 100% accuracy and a minute average error rate of 0.002. Beyond performance metrics, we delve into the intricacies of plant Species classification through feature importance analysis. The most influential features— Vegsout, durflow, semiros, pdias, begflow, wind, leafy, autopoll and insects— uncover the physiological traits underpinning accurate rice classification. This research contributes to advancing rice classification methods and highlights the potential of ANNs in optimizing agricultural practices, ensuring plant safety, and bolstering global trade. (shrink)

Accurate assessment and comprehension of smoking behavior are pivotal for elucidating associated health risks and formulating effective public health strategies. In this study, we introduce an innovative approach to predict and analyze smoking prevalence using an artificial neural network (ANN) model. Leveraging a comprehensive dataset spanning multiple years and geographic regions, our model incorporates various features, including demographic data, economic indicators, and tobacco control policies. This research investigates smoking trends with a specific focus on gender-based analyses. These findings are pivotal (...) for enhancing public health initiatives aimed at mitigating tobacco use, assessing associated health risks, and mitigating smoking-related diseases. (shrink)

This study presents a neural network-based model for predicting smoke potential in a specific area using a Kaggle-derived dataset with 15 environmental features and 62,631 samples. Our five-layer neural network achieved an accuracy of 89.14% and an average error of 0.000715, demonstrating its effectiveness. Key influential features, including temperature, humidity, crude ethanol, pressure, NC1.0, NC2.5, SCNT, and PM2.5, were identified, providing insights into smoke occurrence. This research aids in proactive smoke mitigation and public health protection. The model's accuracy and feature (...) analysis empower decision-makers, with potential applications in real-time smoke event monitoring and preparedness strategies. This work contributes to the field of air quality forecasting and environmental stewardship, offering a data-driven approach to address smoke-related challenges and enhance community well-being. (shrink)

The concept of sustainable development considers environmental, social and economic issues in general. And the goals of resource conservation and socio-economic development do not contradict each other, but contribute to mutual reinforcement. The purpose of this study is to build and test an economic and mathematical model for the formation of strategies for the behavior of an economic entity with an increase in the impact of negative environmental factors. The proposed strategies and their models are based on the income-expenditure balance (...) equation, which takes into account both quantitative and qualitative characteristics. The constructed models are considered in the state space. The research methodology is based on building models in the form of linear combinations of functions of a homogeneous external impact and various spatial combinations of economic sources (sinks). The study makes it possible to assess the dependence of the amount of resources used for life support on the chosen adaptive strategy. Within the framework of the proposed model, it was found that the criterion for the effectiveness of the applied strategy can be an indicator of satisfaction with the state, the preservation of which, simultaneously with the preservation of the size of resources used, corresponds to the direction of optimization. This approach is consistent with the concept of sustainable development. (shrink)

Artificial intelligence is one of the most rapidly evolving fields today. It is used in the majority of computer science applications nowadays. Expert systems are one of the most valuable types of AI; they are used to deliver predictions and decisions in order to make scientific, medical, and even architectural challenges easier to address; they will eventually take the place of a human expert. Without having to meet with a genuine human specialist, the user will be able to get a (...) precise solution or diagnose to his problem. This study provides an illustration of how computer systems can be used in agriculture. In order to construct an expert system that can forecast a disease based on its symptoms, we chose a Coriander plant and five of its recognized ailments. CLIPS was used to develop the system. This article contains a full summary of the work that has been done. (shrink)

To naturalize religion, we must identify what religion is, and what aspects of it we are trying to explain. In this paper, religious social institutional behavior is the explanatory target, and an explanatory hypothesis based on shared primate social dominance psychology is given. The argument is that various religious features, including the high status afforded the religious, and the high status afforded to deities, are an expression of this social dominance psychology in a context for which it did not evolve: (...) high-density populations made possible by agriculture. (shrink)

The aim of the research is to identify the reality of the practice of crisis management in light of The Corona Pandemic, and to achieve the research objectives, the researchers used the descriptive and analytical approach using the comprehensive survey method for the total research community, which numbered (110) individuals, while (90) were recovered: That the level of crisis management practice came with a relative weight (75.60%). Among the most important recommendations made by the research: Work to disburse a health (...) risk premium to all workers in health centers, in addition to paying attention to training and building work teams in various fields, including the crisis team. (shrink)

The study aimed to identify the level of organizational performance in ceramic companies in the Tenth of Ramadan City, where the researchers used the descriptive analytical method, through a questionnaire distributed. The study reached a set of results, the most important of which are: the presence of a clear consensus of the study sample from the members of the senior management that all dimensions of the balanced scorecard variable are largely present in the ceramic companies under study, and the results (...) showed the approval of the study sample of workers in an average way on the application of the financial dimension and that it is applied Well, the approval of the study sample of the employees in an average way that tends to decline on the degree of application of the customer dimension and that it is applied by the senior management in an inappropriate way, the approval of the study sample of the employees in a large way on the degree of application of the internal operations dimension and that it is applied by the senior management in a large and appropriate way, approval The study sample of workers applying the learning and growth dimension is moderately low and it is applied inappropriately by the senior management. The study presented a set of recommendations, the most important of which are: working on clarifying and translating the vision and strategy of the institution, working on clarifying the strategy and linking it to the goals, planning and setting goals and arranging strategic initiatives, promoting strategic feedback. (shrink)

This essay represents a novel contribution to Nietzschean studies by combining an assessment of Friedrich Nietzsche’s challenging uses of “truth” and the “eternal return” with his insights drawn from Indian philosophies. Specifically, drawing on Martin Heidegger’s Nietzsche, I argue that Nietzsche’s critique of a static philosophy of being underpinning conceptual truth is best understood in line with the Theravada Buddhist critique of “self ” and “ego” as transitory. In conclusion, I find that Nietzsche’s “eternal return” can be understood as a (...) direct inversion of “nirvana”: Nietzsche celebrates profound attachment to each and every moment, independent from its pleasurable or distasteful registry. (shrink)