Review of George Berkeley. Siris. Łańcuch filozoficznych refleksji i dociekań wraz z Dodatkami. Trans. A. Grzeliński and M. Szymańska-Lewoszewska. Toruń: Wydawnictwo Naukowe Uniwersytetu Mikołaja Kopernika, 2013.

There is no doubt that custard apple diseases are among the important reasons that destroy the Custard Apple plant and its agricultural crops. This leads to obvious damage to these plants and they become inedible. Discovering these diseases is a good step to provide the appropriate and correct treatment. Determining the treatment with high accuracy depends on the method used to correctly diagnose the disease, expert systems can greatly help in avoiding damage to these plants. The expert system correctly diagnoses (...) Custard Apple disease to make it easier for farmers to find the right treatment based on the appropriate diagnosis. Objectives: A specialized syllable language system was established for the diagnosis of Custard Apple plant disease. (shrink)

Deep learning may transform health care, but model development has largely been dependent on availability of advanced technical expertise. The aim of this study is to develop a deep learning model to predict the gender from retinal fundus images. The proposed model was based on the Xception pre-trained model. The proposed model was trained on 20,000 retinal fundus images from Kaggle depository. The dataset was preprocessed them split into three datasets (training, validation, Testing). After training and cross-validating the proposed model, (...) it was evaluated using the testing dataset. The result of testing, the area under receiver operating characteristic curve (AUROC) of the model was 0.99, precision, recall, f1-score and accuracy were 99%, precision, recall, f1-score and accuracy were 96.83%, 96.83%, 96.82% and 96.83% respectively.. Clinicians are presently unaware of dissimilar retinal feature variants between females and males, stressing the importance of model explain ability for the prediction of gender from retinal fundus images. The proposed deep learning may enable clinician-driven automated discovery of novel visions and disease biomarkers. (shrink)

We consider emergence from the perspective of dynamics: states of a system evolving with time. We focus on the role of a decomposition of wholes into parts, and attempt to characterize relationships between levels without reference to whether higher-level properties are “novel” or “unexpected.” We offer a classification of different varieties of emergence, with and without new ontological elements at higher levels. -/- Submitted to a volume on Real Patterns (Tyler Milhouse, ed.), to be published by MIT Press.

Some philosophers argue that martial arts training is maladaptive, contributes to psychological illness, and provides a social harm, whereas others argue that martial arts training is adaptive, contributes to psychological wellness, and provides a social benefit. This debate is important to scholars and the general public since beliefs about martial arts training can have a real impact on how we evaluate martial artists for job opportunities and career advancement, and in general, how we treat martial artists from different cultures in (...) our communities. This debate is also important for children and adults that have considered enrolling in martial arts training programs but remain uncertain about potential outcomes of training due to the lack of research in this area. This article therefore contributes to the literature on martial arts by (1) outlining a framework that characterizes psychological well-being in terms of five elements, (2) discussing how results from empirical research support the hypothesis that Muay Thai training can contribute to psychological well-being by contributing to all five component elements, (3) discussing the psychological benefits of martial arts training from the perspective of an Everlast Master Instructor, and (4) discussing how martial arts training involves the cultivation of combat-relevant affordances. (shrink)

The genetic modification of pigs as a source of transplantable organs is one of several possible solutions to the chronic organ shortage. This paper describes existing ethical tensions in xenotransplantation (XTx) that argue against pursuing it. Recommendations for lifelong infectious disease surveillance and notification of close contacts of recipients are in tension with the rights of human research subjects. Parental/guardian consent for pediatric xenograft recipients is in tension with a child’s right to an open future. Individual consent to transplant is (...) in tension with public health threats that include zoonotic diseases. XTx amplifies concerns about justice in organ transplantation and could exacerbate existing inequities. The prevention of infectious disease in source animals is in tension with the best practices of animal care and animal welfare, requiring isolation, ethologically inappropriate housing, and invasive reproductive procedures that would severely impact the well-being of intelligent social creatures like pigs. (shrink)

It is tempting to think that a process of choosing a point at random from the surface of a sphere can be probabilistically symmetric, in the sense that any two regions of the sphere which differ by a rotation are equally likely to include the chosen point. Isaacs, Hájek, and Hawthorne (2022) argue from such symmetry principles and the mathematical paradoxes of measure to the existence of imprecise chances and the rationality of imprecise credences. Williamson (2007) has argued from a (...) related symmetry principle to the failure of probabilistic regularity. We contend that these arguments fail, because they rely on auxiliary assumptions about probability which are inconsistent with symmetry to begin with. We argue, moreover, that symmetry should be rejected in light of this inconsistency, and because it has implausible decision- theoretic implications. -/- The weaker principle of probabilistic invariance says that the probabilistic comparison of any two regions is unchanged by rotations of the sphere. This principle supports a more compelling argument for imprecise probability. We show, however, that invariance is incompatible with mundane judgments about what is probable. Ultimately, we find reason to be suspicious of the application of principles like symmetry and invariance to nonmeasurable regions. (shrink)

Welfarism is the view that individual welfare is the only thing that matters. One important contribution of social choice theory has been to provide a precise formulation and axiomatic characterization of welfarism using Amartya Sen's framework of social welfare functionals. This paper is motivated by the observation that the standard formalization of welfarism is too restrictive, since a welfarist social planner need not be committed to maximizing a preference ordering or any other binary relation over alternatives. We therefore provide a (...) characterization of welfarism in a more general choice-functional setting and show that welfarism, so understood, carries no commitment to rationalizability. This characterization is compatible with welfare values having any structure whatsoever. It also sheds light on different formulations of anonymity, revealing only some of these to be fundamental requirements of impartiality. (shrink)

Recently, the concept of "gender identity" has enjoyed a great deal of attention in gender metaphysics. This seems to be motivated by the goal of creating trans-inclusive theory, by explaining trans people's genders. In this paper, we aim to unmotivate this project. Notions of "gender identity" serve important pragmatic purposes for trans people, such as satisfying the curiosity of non-trans people, and, relatedly, securing our access to important goods like legal rights and medical care. However, we argue that this does (...) not mean that "gender identity" is a metaphysically substantial thing that deserves extensive theoretical attention. There are reasons to be skeptical of such a concept. We trace the history of "gender identity," primarily to identify its roots in trans-antagonistic medical theory and its connections to the problematic "wrong-body" model--a legacy that has pathologized and flattened trans experience. Moreover, we argue that trans people primarily use "gender identity" to explain ourselves to non-trans people, rather than to discuss ourselves among ourselves. Thus, we urge theorists to resist the urge to substantiate gender identity. Instead, we encourage the development of new and better concepts, ones that attend to the lived realities of trans community and the flourishing gender terms and practices that are constructed there. If these lived realities are taken seriously, there is no need to “explain” trans people’s genders; we can simply see them as they are. (shrink)

Abstract: Artificial Intelligence (AI) has rapidly evolved, offering transformative capabilities for business decision-making. This paper explores how AI can be leveraged to enhance strategic decision-making in business contexts. It examines the integration of AI-driven analytics, predictive modeling, and automation to improve decision accuracy and operational efficiency. By analyzing current applications and case studies, the paper highlights the opportunities AI presents, including enhanced data insights, risk management, and personalized customer experiences. Additionally, it addresses the challenges businesses face in adopting AI, such (...) as data privacy concerns, integration issues, and the need for skilled personnel. The paper concludes with recommendations for effectively implementing AI solutions to maximize their benefits while navigating potential pitfalls. (shrink)

Background: Mint is a grassy, perennial plant, belonging to the oral platoon, fast growing and spreading, its leaves are green in color, fragrant, tart, refreshing, square-shaped leg, bifurcated, erect, ranging in height from (10 - 201 cm). Home to Europe and Asia. The mint plant has many benefits, the most important of which are pain relief, treatment of gallbladder disorders, the expulsion of gases, anti-inflammatory, and relaxing nerves. While the mint plant is the ideal option for the start of gardens, (...) it is prone to some common diseases that affect the plant's growth. Objectives: The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment. Methods: In this paper, the design of the proposed Expert System was produced to help Farmers and those interested in agriculture in diagnosing many of the Mint diseases such as Mint rust, Verticillium wilt, Anthracnose, Powdery mildew, Black Stem Rot, Stem and stolon canker, Septoria leaf spot. The proposed expert system presents an overview of mint diseases are given, the cause of diseases outlined and the treatment of disease whenever possible is given out. CLIPS Expert System language was used for designing and implementing the proposed expert system. Results: The proposed Mint diseases diagnosis expert system was evaluated by Agricultural Students at AL Azhar University and some friends interested in agriculture and they were satisfied with its performance. Conclusions: The proposed expert system is very useful for Farmers and those interested in agriculture. (shrink)

The concept of bias is pervasive in both popular discourse and empirical theorizing within philosophy, cognitive science, and artificial intelligence. This widespread application threatens to render the concept too heterogeneous and unwieldy for systematic investigation. This article explores recent philosophical literature attempting to identify a single theoretical category—termed ‘bias’—that could be unified across different contexts. To achieve this aim, the article provides a comprehensive review of theories of bias that are significant in the fields of philosophy of mind, cognitive science, (...) machine learning, and epistemology. It focuses on key examples such as perceptual bias, implicit bias, explicit bias, and algorithmic bias, scrutinizing their similarities and differences. Although these explorations may not conclusively establish the existence of a natural theoretical kind, pursuing the possibility offers valuable insights into how bias is conceptualized and deployed across diverse domains, thus deepening our understanding of its complexities across a wide range of cognitive and computational processes. (shrink)

Abstract: Artificial Intelligence (AI) is transforming the agricultural sector, enhancing both productivity and sustainability. This paper delves into the impact of AI technologies on agriculture, emphasizing their application in precision farming, predictive analytics, and automation. AI-driven tools facilitate more efficient crop and resource management, leading to higher yields and a reduced environmental footprint. The paper explores key AI technologies, such as machine learning algorithms for crop monitoring, robotics for automated planting and harvesting, and data analytics for optimizing resource use. Additionally, (...) it discusses challenges like data privacy, barriers to technology adoption, and the ethical implications of AI in farming. Integrating AI into agricultural practices holds the promise of greater efficiency and sustainability, paving the way for future innovations. (shrink)

Many scholars of organizations see social enterprise as a promising approach to advancing social justice but neglect to scrutinize the normative foundations and limitations of this optimism. This article draws on Rawlsian political philosophy to investigate whether and how social enterprises can support social justice. We propose that this perspective assigns organizations a duty to foster institutional capacity, a concept we define and elaborate. We investigate how this duty might apply specifically to social enterprises, given their characteristic features. We theorize (...) six different mechanisms through which social enterprises might successfully discharge this duty. These results affirm the value of conversation between organizational studies and political philosophy and shed new light on debates regarding social enterprise, institutional theory, and several other topics. (shrink)

Issues on plagiarism among pre-service teachers (PSTs) have increased in modular and online learning. To confirm this, the study determined the PSTs’ level of awareness on plagiarism; their knowledge on referencing and citation; and the correlation between their level of awareness on plagiarism and knowledge on referencing and citation, with their academic performance. The study employed a descriptive-correlational research design participated by 235 PSTs randomly sampled through strata. The data were gathered through a web-based survey. Results showed that the PSTs’ (...) level of awareness of plagiarism was moderate, while the majority have fair knowledge in referencing and citation. Also, results showed a significant relationship among the level of awareness on plagiarism, knowledge on referencing and citation, and academic performance. It is recommended that institutions equip librarians and educators to teach PSTs about citation and referencing skills. Besides, the institution should make sure that a policy is implemented to pursue academic integrity. This policy must articulate the various types of plagiarism, plagiarism measurement, and fair and consistent disciplinary actions. (shrink)

Numerous societal issues, from climate change to pandemics, require public engagement with scientific research. Such engagement reveals challenges that can arise when experts communicate with laypeople. One of the most common frameworks for framing these communicative interactions is the deficit model of science communication, which holds that laypeople lack scientific knowledge and/or positive attitudes towards science, and that imparting knowledge will fill knowledge gaps, lead to desirable attitude/behavior changes, and increase trust in science. §1 introduces the deficit model in more (...) detail and shows that adhering to this model often fails to achieve its aims, which motivates the main question of this chapter: how can Ludwik Fleck’s theory of thinking collectives address the persistent problem of deficit approaches in science communication? I suggest that it can do so by exposing the deficit model’s implicit assumption of an expert-lay divide. Accordingly, §2 lays out Fleck’s theory and §3 contrasts it with contemporary debates about science communication. Following this descriptive work, §4 draws on Fleck’s ideas to make four concrete suggestions for further questioning the expert-lay divide. (shrink)

Knowledge representation (KR) is actually more than representation: It involves also inference, namely inference of “new” knowledge, i.e. new facts. Logic programming is a suitable KR medium, but more often than not discussions on this programming paradigm focus on aspects other than KR. In this paper, I elaborate on the general theory of logic programming and give the essentials of two of its main implementations, to wit, Prolog and Datalog, from the viewpoint of deductive computing over knowledge bases, which includes (...) deductive programming. (shrink)

This paper explores the complex nature of social biases, arguing for a functional framework that recognizes their unity and diversity. The functional approach posits that all biases share a common functional role in overcoming underdetermination. This framework, I argue, provides a comprehensive understanding of how all psychological biases, including social biases, are unified. I then turn to the question of disunity, demonstrating how psychological social biases differ systematically in the mental states and processes that constitute them. These differences indicate that (...) biases at various levels of the cognitive architecture require distinct treatment along at least two dimensions: epistemic evaluation and mitigation strategies. By examining social biases through this dual lens of unity and diversity, we can more effectively identify when and how to intervene on problematic biases. Ultimately, this approach provides a nuanced understanding of the nature of social bias, offering practical guidance for addressing existing biases and proactively managing emerging biases in both human and artificial minds. (shrink)

In Wollstonecraft’s early writings, she articulates the foundational theological and philosophical principles that would underpin her work throughout her career. One difference between her early and later work lies in the way that the values to which she refers are combined. Whereas Wollstonecraft at first appeals to the separate ideals of independence, equality, and virtue, from the 1790s onwards she integrates these into a characteristic republican framework that was in common use amongst dissenting theorists at the time. The set of (...) values on which Wollstonecraft draws, and the version of the republican framework that she develops, closely resemble those of Richard Price with whose work she was familiar. Examining the structural similarities between their respective models, I argue, gives us an insight into the systematic manner of aspects of Wollstonecraft’s own thought. It also allows us to see how Wollstonecraft goes beyond the republicanism of Price and others as she develops her own feminist solutions to the problems of structural domination. (shrink)

Some theories of goodness are descriptively rich: they have much to say about what makes things good. Neo-Aristotelian accounts, for instance, detail the various features that make a human being, a dog, a bee good relative to facts about those forms of life. Famously, such theories of relative goodness tend to be comparatively poor: they have little or nothing to say about what makes one kind of being better than another kind. Other theories of goodness—those that take there to be (...) absolute goodness—are comparatively rich: they offer grounds for judging some types of things better than others because they have more absolute goodness. Moorean accounts, for example, can tell us that humans and human experiences are superior to bees and blades of grass. But such theories tend to be descriptively poor: they struggle to tell us in virtue of what this is so. In this essay we motivate and flesh out a view that splits the difference between accounts of goodness as relative and accounts of goodness as absolute. Such a view holds promise only if the mechanics of this kind of metaphysics of goodness can be worked out. Here we present a view on which the paradigm for absolute goodness is God and the paradigm for each kind of relative goodness is a divine idea. (shrink)

Abstract: Ensuring the proactive detection of transaction risks is paramount for financial institutions, particularly in the context of managing credit scores. In this study, we compare different machine learning algorithms to effectively and efficiently. The algorithms used in this study were: MLogisticRegressionCV, ExtraTreeClassifier,LGBMClassifier,AdaBoostClassifier, GradientBoostingClassifier,Perceptron,RandomForestClassifier,KNeighborsClassifier,BaggingClassifier, DecisionTreeClassifier, CalibratedClassifierCV, LabelPropagation, Deep Learning. The dataset was collected from Kaggle depository. It consists of 164 rows and 8 columns. The best classifier with unbalanced dataset was the LogisticRegressionCV. The Accuracy 100.0%, precession 100.0%,Recall100.0% and the F1-score (...) 100.0%. However, the best classifier with balanced dataset was the LogisticRegressionCV. The Accuracy 100.0%, precession 100.0%, Recall 100.0% and the F1-score 100.0%. (shrink)

The policy of earmarked paternity leave aims to promote mothers’ position in the labor market and fathers’ relationship with their child. Critics argue that the policy prevents parents from pursuing their own ideas about what is best for them. This provides reason to consider whether the policy is paternalistic or, in other ways, disrespectful of parental autonomy. I argue that the state implicates itself in the gender inequalities that result from parents’ unequal parental leave agreements when the state financially facilitates (...) such agreements. This argument for earmarked paternity leave is not disrespectful of parental autonomy. (shrink)

This paper analyzes the specific shift in the meaning of “civilization” that took place in texts and documents of early American philosophical naturalism. Particularly, it will focus on the specific role that naturalization plays in the edification of a newly secularized, science-oriented, and democratic society, as well as of a naturalized conception of culture and civilization. Indeed, as the work of many philosophers and intellectuals of the Forties highlights, naturalism represents not only the banner of a new idea of civilization, (...) but at the same time becomes the symbol of a powerful postwar ideology. (shrink)

Comparative religion scholar Thomas Berry’s influential concept of “Earth jurisprudence” has been helpfully elaborated in three principal books. My first section identifies four of their common themes, deriving therefrom an implicit narrative: (1) the basis of ecology is autopoiesis, which (2) originally generated human communities and Indigenous vernacular laws, which were (3) later reasserted by forest defenders who fought to create the Magna Carta’s “Charter of the Forest,” which is (4) now championed globally by the Indian physicist and eco-activist Vandana (...) Shiva’s Earth Democracy movement. My next three sections identify mutually exclusive elements of the three books, deriving the following alternative narrative: self-conscious new dancing rituals (Cullinan) could empower an historically informed reconstruction of private property (Burdon) via commons-based vernacular law (Weston and Bollier). And my conclusion offers one template for such a strategy, namely a new environmental variation on my dancing-poetic conception of legal justice, christened “emerald star-law.”. (shrink)

People often discriminate based on negative or positive stereotypes about others. Important examples of this are highlighted by the theory of ambivalent sexism. This theory distinguishes sexist stereotypes that are negative (hostile sexism) from those that are positive (benevolent sexism). While both forms of sexism are considered wrong towards women, hostile sexism seems intuitively worse than benevolent sexism. In this article, we ask whether the difference between discriminating based on positive vs. negative stereotypes in itself makes a morally relevant difference. (...) We suggest that it does not. By examining a number of prominent accounts of what makes discrimination wrong, we defend the Moral Irrelevance View according to which stereotype valence is irrelevant to the moral evaluation of discrimination, all else equal. (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)

Diabetic ketoacidosis is a serious, medical emergency that can be fatal but treatable, we aimed to evaluate the clinical profile of patients admitted with diabetic ketoacidosis. This case series study enrolled 213 non-pregnant adult and adolescent patients admitted with diabetic ketoacidosis at Tripoli Diabetes Hospital from January to September 2023. Demographic data, clinical characteristics, laboratory findings, precipitating factors, and patient outcomes were extracted from medical records and analyzed. Type 1 diabetes mellitus was present in 187 (87.8%) of patients, the age (...) range 11-84 years, (30.26±13.28), with 130 patients ≤30 years old (61.0%), females accounting for 110 of the patients (51.6%), 109 had a diabetes duration of less than 10 years (51.2%). The most common precipitating factor was insulin omission 92 (43.2%) in patients with known diabetes mellitus, whereas, diabetic ketoacidosis as the first presentation of diabetes mellitus in 24 patients (11.7%), systolic blood pressure ranged 50-160 mmHg (112.82±16.19), diastolic blood pressure varied 30-100 mmHg (70.24±11.32). Plasma glucose at presentation ranged 183-1494 mg/dl (462.92±169.85), with Eu-glycemic diabetic ketoacidosis 100-249 mg/dl were in nine patients (4.2%), whereas most of cases (135 patients, 63.4%) present with plasma glucose 250-500 mg/dl, while hyperosmolar status (≥701 mg/dl) were present in 13 patients (6.1%). Venous pH varied from 6.7-7.42 (7.13±0.14), 132 (62.0%) patients presented with pH <7.24, while severe acidosis was pH < 7 in 32 of patients (14.6%), serum bicarbonate with 10.93±4.95, severe (<5 mmol) in 91 patients (42.7%) and moderate (5-10 mmol) were in 79 patients (37.08%). The mean length of hospital stay was 3.33 days, with an average of 2.11 days spent in the high-dependent unit. Serum potassium varied from 2.4-6.7 meq/L with 3.66± 0.63, most common complications of diabetic ketoacidosis treatment were hypokalemia observed in 82 (35.7%) of cases, and hypoglycemia was detected in 41 patients (19.2%). 170 patients were discharged in good condition (79.8%), and 17.8% of patients were transferred to another hospital to receive further management for co-morbid diseases with diabetes after controlling their hyperglycemic crises. The majority of patients presented with the critical status of diabetic ketoacidosis. The findings emphasize the importance of patient education about prevention measures prompt presentation to the hospital, and clinicians' awareness for early and aggressive treatment of hyperglycemic crises. (shrink)

Academic excellence and intelligence are commonly lauded as commendable attributes synonymous with success. However, a disconcerting trend has surfaced within educational institutions, challenging the prevailing narrative of scholastic accomplishment—smart shaming. This research delves into the increasing concern of smart shaming within educational settings, particularly at Immaculate Conception College of Balayan, Inc., questioning the predominant emphasis on academic excellence and intelligence. A qualitative case study design, along with judgmental sampling, was employed to examine fifteen (15) student leaders who had experienced smart (...) shaming on campus. Thematic analysis revealed that sarcastic remarks including "edi wow," "Okay ikaw na matalino," "bidabida," and "sipsip" were a prevalent manifestation of smart shaming, adversely affecting emotional well-being, academic and leadership prowess, mental health, and self-perception. Coping mechanisms, predominantly centered around ignoring and focusing on goals, were identified. The findings underscore the imperative for educators to remain vigilant regarding instances of smart shaming in classrooms, promoting open communication to ensure student well-being. Additionally, guidance counselors play a pivotal role in aiding students in effectively navigating the repercussions of smart shaming. This study advocates for proactive programs and interventions to address and alleviate the deleterious effects of smart shaming on students. (shrink)

Wil Waluchow has advanced perhaps the most convincing argument in favour of what he eloquently termed ‘inclusive legal positivism’, the view that a given legal system could make legal validity depend on moral truths. This chapter refocuses the case for the opposing view of exclusive positivism on the metaphysical tension in seeing law as an institutional social fact and yet for its validity to depend on something that is not a social fact, developing an understanding of official mistake as a (...) way of highlighting that tension. If legal validity itself is understood as a socially constructed status (something with which any legal positivist would agree), key officials (as a group) cannot be wrong about the criteria sufficient for institutional membership having been met. While the officials cannot be wrong about the sufficient conditions, they can be wrong about the necessary (gatekeeping) ones and the moral criteria that inclusive positivists say could be included among the criteria of validity are invariably understood to be necessary conditions. That might look like a point in favour of inclusive positivism, but it is only the sufficient conditions that are constitutive of legal validity. Two facets of legal decisions are then marshalled to buttress the case for exclusive positivism: that almost every legal decision is also a determination of validity, and that all such decisions are systemically treated as correct until reviewed by a court of superior jurisdiction (which is itself a sufficient condition for membership). The implication of this is that moral criteria, understood as gatekeepers for legal validity, cannot be constitutive of legal validity. (shrink)

Abstract: Forests are areas with a high density of trees, and they play a vital role in the health of the planet. They provide a habitat for a wide variety of plant and animal species, and they help to regulate the climate by absorbing carbon dioxide from the atmosphere. While in 2010, the world had 3.92Gha of forest cover, covering 30% of its land area, in 2019, there was a loss of forest cover of 24.2Mha according to the Global Forest (...) Watch institute. Discovery and classification depend on human experience and effort, so the error in the results of this process can lead to forest fires and disasters. Therefore, deep learning algorithms from artificial intelligence and machine learning sciences have been applied to help specialists avoid false or inaccurate diagnoses when detecting Forest fires in images using a pre-trained convolutional neural network called VGG16. The model was customized to fit the Forest fires classification and then applied to a dataset consisting of (14,000) of the Forests collected from the Kaggle depository. We trained, validated, and tested the modified VGG16 model. The proposed VGG16 model obtained Precision (99.96%), Recall (99.96%), and F1-Score (99.96%). (shrink)

Two problems are considered here. One relates to who has moral status, and the other relates to who has moral responsibility. The criteria for mattering morally have long been disputed, and many humans and nonhuman animals have been considered “marginal cases,” on the contested edges of moral considerability and concern. The marginalization of humans and other species is frequently the pretext for denying their rights, including the rights to health care, to reproductive freedom, and to bodily autonomy. There is broad (...) agreement across cultural and philosophical traditions about the capacities and responsibilities of moral agents. I propose an inclusive and expansive way of thinking about moral status, situating it not in the characteristics or capacities of individuals, but in the responsibilities and obligations of moral agents. Moral agents, under this view, are not privileged or entitled to special treatment but rather have responsibilities. I approach this by considering some African communitarian conceptions of moral status and moral agency. I propose that moral agency can also be more expansive and include not just individual moral agents but collective entities that have some of the traits of moral agents: power, freedom, and the capacity to recognize and act on the demands of morality and acknowledge and respect the rights of others. Expanding who and what is a moral agent correspondingly extends moral responsibility for respecting rights and fostering the conditions for the health and well-being of humans and animals onto the collective entities who uniquely have the capacity to attend to global-scale health threats such as pandemics and human-caused climate change. (shrink)

Abstract: Context: grapevine leaves are an important agricultural product that is used in many Middle Eastern dishes. The species from which the grapevine leaf originates can differ in terms of both taste and price. Method: In this study, we build a deep learning model to tackle the problem of grape leaf classification. 500 images were used (100 for each species) that were then increased to 10,000 using data augmentation methods. Convolutional Neural Network (CNN) algorithms were applied to build this model (...) specifically using the pre-trained model on top of the VGG16 architecture. Then, dense layers were added to classify the output of the Convolutional layers and classify outputs to the five classes (species) the leaf belonged to. Results: It was found that feature extraction without fine-tuning the convolutional layers yielded poor results, about 86% accuracy, while training the whole network along with some data preprocessing gave the best results, about 99.45% accuracy on the testing dataset. Conclusions: The proposed CNN model is an effective one for the problem of classification of grape leaf species. (shrink)

The paper also discusses the technical architecture, including the network protocols, data management strategies, and user interface design considerations necessary to implement such a system. Additionally, it addresses the challenges related to data security, privacy, and system interoperability. Finally, the paper outlines potential future enhancements, such as the incorporation of AI-driven predictive analytics and advanced AR features, to further elevate the smart home experience.

The ever-evolving landscape of cyber threats necessitates robust and adaptable intrusion detection systems (IDS) capable of identifying both known and emerging attacks. Traditional IDS models often struggle with detecting novel threats, leading to significant security vulnerabilities. This paper proposes an optimized intrusion detection model using Support Vector Machine (SVM) algorithms tailored to detect known and innovative cyberattacks with high accuracy and efficiency. The model integrates feature selection and dimensionality reduction techniques to enhance detection performance while reducing computational overhead. By leveraging (...) advanced optimization techniques such as Grid Search and Particle Swarm Optimization (PSO), the proposed SVM-based IDS achieves superior classification results. (shrink)

The first purpose of this series of articles is to introduce case studies on how current AI models can be used in the development of a possible theory of quantum gravity, their limitations, and the role the researcher has in steering the development in the right direction, even highlighting the errors, weaknesses and strengths of the whole process. The second is to introduce the new Presentist Fragmentalist ontology as a framework and use it for developing theories of quantum gravity and (...) speculate on achieving a TOE. We emphasize it is necessary for the researcher to check everything in these articles for themselves. While there are many good ideas in this series of papers, the AI is known to make even arithmetic and algebraic mistakes. To select just five apparently good ideas, there is a causal interaction tensor Cαβγδ(F1, F2) that encodes the causal relationship and the strength of the (possibly non-local) interaction between two fragments of reality (formed by each quantum system). There is a quantitative prediction for a testable table-top experiment. There is an explanation of how spacetime emerges from the fragments and their interactions. There is an explicit account of the double-slit experiment. And there is an explanation how this theory accommodates dark matter and dark energy simultaneously. We explore ideas, equations they lead to, concrete calculations, and give corrections along the way. While these are generally morally right within this framework they must be checked by the researcher. Given this caveat, we believe we have made significant progress with the PF interpretation in developing a theory of quantum gravity and pointing out a possible path to a TOE. (shrink)

Emotion detection and management have emerged as pivotal areas in humancomputer interaction, offering potential applications in healthcare, entertainment, and customer service. This study explores the use of deep learning (DL) models to enhance emotion recognition accuracy and enable effective emotion regulation mechanisms. By leveraging large datasets of facial expressions, voice tones, and physiological signals, we train deep neural networks to recognize a wide array of emotions with high precision. The proposed system integrates emotion recognition with adaptive management strategies that provide (...) personalized feedback and interventions based on detected emotional states. Our approach surpasses traditional machine learning methods, demonstrating superior performance in real-time applications. (shrink)

With increased visibility of trans people comes increased philosophical interest in gendered language. This chapter aims to look at the research on gendered language in analytic philosophy of language so far, which has focused on two concerns: (1) determining how to define gender terms like ‘man’ and ‘woman’ such that they are trans inclusive and (2) if, or to what extent, we should use gendered language at all. We argue that the literature has focused too heavily on how gendered language (...) can harm trans people, and has not considered how trans people use gendered language to create meaning and joy for ourselves. Pulling from the literature in sociolinguistics, we look at examples of how trans people use language to make their lives better by gaining recognition, playing with gendered language, finding joy in gendered language, and taking control of definitional power, concluding that debates about gendered language need to consider not only how such language harms trans people but also how trans people use it for our own liberation. (shrink)

The research outlines a workflow that incorporates data collection, preprocessing, model training, and optimization. Real-world datasets from retail and e-commerce sectors are utilized to validate the proposed methodology, showcasing substantial improvements in model performance. The results indicate that optimized models not only provide better predictions of consumer behaviour but also enhance customer segmentation and targeting strategies. The study concludes with recommendations for future research, including the exploration of hybrid optimization techniques and the application of these methods in real-time analytics.

The relations between ontology and information are many and fundamental, and they help us to understand the present gulf between (formal) ontology and (philosophical) Ontology: We can speak of respectively ontology-driven information and information-driven ontology as the focus on being informed vs. informed being. The question of whether these two (can) coincide is relevant to both fields, and in this article I elaborate on what needs to be addressed first of all to provide us with an answer: The form. This (...) core ontological concept rooting in Aristotelian metaphysics was central to philosophical ontology, in particular in Latin Scholasticism, when it was clearly put into relation with information as that which defines an entity. In this context, Dietrich of Freiberg synthesized this long debate in a way that matters not only to the philosophical effort of producing information-driven ontologies but also to the engineering constructs of ontology-driven information systems. (shrink)

In this paper I investigate central temporal and spatial notions in the second part of Plato’s Parmenides and argue that also these notions, and not only the metaphysical ones usually discussed in the literature, can be understood as a response to positions and problems put on the table by Parmenides and Zeno. Of the spatial notions examined in the dialogue, I look at the problems raised for possessing location and shape, while with respect to temporal notions, I focus on the (...) discussion of ‘being in time’ and exaiphnês (the latter notion will be shown to be also an important influence for Aristotle’s Physics). In displaying a paradoxical character and taking up crucial notions from Parmenides, the second part of the Parmenides seems to display some resemblance to Zeno’s paradoxes. I will show, however, that in contrast to Zeno, the second part of Plato’s Parmenides also demonstrates Parmenides’ One to be problematic on its own terms. Furthermore, the dialogue presents not only important problems that these spatial and temporal notions seem to lead us into, but also establishes some positive features necessary to think of time and space. In this way, Plato’s Parmenides can be seen as contributing to the development of temporal and spatial conceptualisations in ancient Greek thought. (shrink)

In today's data-driven world, the efficient management of network resources is crucial for optimizing performance in data centers and large-scale networks. Load balancing is a critical process in ensuring the equitable distribution of data across multiple paths, thereby enhancing network throughput and minimizing latency. This paper presents a comprehensive approach to load balancing using advanced optimization techniques integrated with multipath routing protocols. The primary focus is on dynamically allocating network resources to manage the massive volume of data generated by modern (...) applications. By leveraging algorithms such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), the proposed method efficiently distributes data across multiple paths, ensuring balanced network utilization. The combination of these algorithms with multipath routing significantly reduces congestion and improves overall network performance. (shrink)

Background: Persimmon is a grassy, perennial plant, belonging to the oral platoon, square-shaped leg, bifurcated, erect, and ranging in height from (10 - 201 cm). Home to Europe and Asia. The Persimmon plant has many benefits, the most important of which are pain relief, treatment of gallbladder disorders, the expulsion of gases, anti-inflammatory, and relaxing nerves. While the Persimmon plant is the ideal option for the start of gardens, it is prone to some common diseases that affect the plant's growth. (...) Objectives: The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment. Methods: In this paper, the design of the proposed Expert System was produced to help Farmers and those interested in agriculture in diagnosing many of the Persimmon diseases such as Persimmon rust, Verticillium wilt, Anthracnose, Powdery mildew, Black Stem Rot, Stem and stolon canker, Septoria leaf spot. The proposed expert system presents an overview of Persimmon diseases are given, the cause of diseases outlined and the treatment of disease whenever possible is given out. CLIPS Expert System language was used for designing and implementing the proposed expert system. Results: The proposed Persimmon diseases diagnosis expert system was evaluated by Agricultural Students at AL Azhar University and some friends interested in agriculture and they were satisfied with its performance. Conclusions: The proposed expert system is very useful for Farmers and those interested in agriculture. (shrink)

As part of a review symposium on DARWIN'S ARGUMENT BY ANALOGY: FROM ARTIFICIAL TO NATURAL SELECTION (2021), the journal METASCIENCE invited Roger White, Jon Hodge and me to submit a response to the thoughtful commentaries on our book by Andrea Sullivan-Clarke, David Depew and Andrew Inkpen.

Drawing from the work of Mabogo More, this paper will attempt to present a comprehensive analysis of Steve Biko’s views on race and racism. The analysis will commence by reviewing and outlining the broad philosophical schools of thought regarding the conceptualization of race, and it’s relevance within society, namely; Racial Naturalism, Racial Nihilism or Skepticism, and Racial Constructivism. Subsequently, this paper will attempt to locate More’s interpretation of Biko’s views as being constructivist, despite the prevalence of non-racial, skeptical conceptions within (...) contemporary South Africa. In light of these skeptical conceptions, this paper will apply Biko’s philosophical views to specifically answer the following questions: Firstly, Can black people be racist? Secondly, Could racism ever go out of existence? Finally, this paper will address the question: Could race ever cease to exist? (shrink)

This implementation framework bridges the theoretical concepts of the Instructional Modular Approach with the practical development of Science Teaching Competency. It offers prospective teachers a structured, adaptive, and technology-enhanced pathway to becoming competent and innovative science educators. Each unit is meticulously designed to not only equip teachers with theoretical knowledge but also to hone their practical skills and competencies essential for a dynamic science teaching environment.

Rainfall prediction is one of the challenging tasks in weather forecasting. Accurate and timely rainfall prediction can be very helpful to take effective security measures in dvance regarding: on-going construction projects, transportation activities, agricultural tasks, flight operations and flood situation, etc. Data mining techniques can effectively predict the rainfall by extracting the hidden patterns among available features of past weather data. This research contributes by providing a critical analysis and review of latest data mining techniques, used for rainfall prediction. In (...) our proposed system we propose a new forecasting method that uses a Convolutional Neural Network monthly rainfall for a selected location. In our proposed system we are going to forecast the rainfall result based on the mean square error, mean absolute error and root mean square error, which we get in train and test of the dataset based deep learning technique. (shrink)

"This self-consistent evolution of the fragments, their causal relationships, and their quantum properties is at the heart of the FCQG-SM framework, providing a unified description of quantum mechanics, general relativity, and the Standard Model.".

The rise of social media has created a new platform for communication and interaction, but it has also facilitated the spread of harmful behaviors such as cyberbullying. Detecting and mitigating cyberbullying on social media platforms is a critical challenge that requires advanced technological solutions. This paper presents a novel approach to cyberbullying detection using a combination of supervised machine learning (ML) and natural language processing (NLP) techniques, enhanced by optimization algorithms. The proposed system is designed to identify and classify cyberbullying (...) behavior in real-time, analyzing textual data from social media posts to detect harmful content. The model is trained on a large dataset of labeled instances of bullying and non-bullying content, using supervised ML algorithms such as Support Vector Machines (SVM), Decision Trees, and Random Forest. NLP techniques, including sentiment analysis, keyword extraction, and text vectorization, are employed to preprocess and transform the data into a format suitable for machine learning. To optimize the performance of the detection model, techniques such as Grid Search, Genetic Algorithms, and Particle Swarm Optimization are used to fine-tune hyperparameters, resulting in improved accuracy and reduced false positives. The system's effectiveness is validated through experiments conducted on various social media platforms, demonstrating its potential to detect cyberbullying with high precision. Future work will focus on enhancing the model's adaptability to emerging slang and evolving language patterns in social media. Key words: Cyberbullying Detection, Social Media, Supervised Machine Learning, Natural Language Processing (NLP), Optimization Techniques. (shrink)