Five aspects of visual change detection are reviewed. The first concerns the concept of change itself, in particular the ways it differs from the related notions of motion and difference. The second involves the various methodological approaches that have been developed to study change detection; it is shown that under a variety of conditions observers are often unable to see large changes directly in their field of view. Next, it is argued that this “change blindness” indicates that focused attention (...) is needed to detect change, and that this can help map out the nature of visual attention. The fourth aspect concerns how these results affect our understanding of visual perception—for example, the implication that a sparse, dynamic representation underlies much of our visual experience. Finally, a brief discussion is presented concerning the limits to our current understanding of change detection. (shrink)

The recent emergence of machine-manipulated media raises an important societal question: How can we know whether a video that we watch is real or fake? In two online studies with 15,016 participants, we present authentic videos and deepfakes and ask participants to identify which is which. We compare the performance of ordinary human observers with the leading computer vision deepfake detection model and find them similarly accurate, while making different kinds of mistakes. Together, participants with access to the model’s prediction (...) are more accurate than either alone, but inaccurate model predictions often decrease participants’ accuracy. To probe the relative strengths and weaknesses of humans and machines as detectors of deepfakes, we examine human and machine performance across video-level features, and we evaluate the impact of preregistered randomized interventions on deepfake detection. We find that manipulations designed to disrupt visual processing of faces hinder human participants’ performance while mostly not affecting the model’s performance, suggesting a role for specialized cognitive capacities in explaining human deepfake detection performance. -/- . (shrink)

In the face of continuing assumptions by many scientists and journal editors that p-values provide a gold standard for inference, counter warnings are published periodically. But the core problem is not with p-values, per se. A finding that “p-value is less than α” could merely signal that a critical value has been exceeded. The question is why, when estimating a parameter, we provide a range (a confidence interval), but when testing a hypothesis about a parameter (e.g. µ = x) we (...) proceed as if “=” entails exact equality of the parameter with x. That standard is hard to meet, and is not a standard expected for power calculations, where we are satisfied to reject a null hypothesis H0 if the result is merely “detectably” different from (exact) H0. This paper explores, with resampling (simulation) methods, the impacts on p-values, and alternatives, if the null hypothesis is defined as a thick or thin range of values. It also examines, empirically, the extent to which the p-value may or may not be a good predictor of the probability that H0 is true, given the distribution of the data. (shrink)

Driver drowsiness is a significant factor contributing to road accidents, resulting in severe injuries and fatalities. This study presents an optimized approach for detecting driver drowsiness using machine learning techniques. The proposed system utilizes real-time data to analyze driver behavior and physiological signals to identify signs of fatigue. Various machine learning algorithms, including Support Vector Machines (SVM), Convolutional Neural Networks (CNN), and Random Forest, are explored for their efficacy in detecting drowsiness. The system incorporates an optimization technique—such as Genetic Algorithms (...) (GA) or Particle Swarm Optimization (PSO)—to enhance the accuracy and response time of the detection process. The integration of optimization methods ensures that the model adapts to various driving conditions and individual differences, providing a more reliable and robust detection mechanism. (shrink)

: Driver drowsiness is a significant factor contributing to road accidents, resulting in severe injuries and fatalities. This study presents an optimized approach for detecting driver drowsiness using machine learning techniques. The proposed system utilizes real-time data to analyze driver behavior and physiological signals to identify signs of fatigue. Various machine learning algorithms, including Support Vector Machines (SVM), Convolutional Neural Networks (CNN), and Random Forest, are explored for their efficacy in detecting drowsiness. The system incorporates an optimization technique—such as Genetic (...) Algorithms (GA) or Particle Swarm Optimization (PSO)—to enhance the accuracy and response time of the detection process. The integration of optimization methods ensures that the model adapts to various driving conditions and individual differences, providing a more reliable and robust detection mechanism. Data from multiple sources, including camera feeds and wearable sensors, are used to train and validate the models, ensuring a comprehensive understanding of drowsiness indicators. (shrink)

Abstract: Lemons are an important fruit that have a wide range of uses and benefits, from culinary to health to household and beauty applications. Deep learning techniques have shown promising results in image classification tasks, including fruit quality detection. In this paper, we propose a convolutional neural network (CNN)-based approach for detecting the quality of lemons by analysing visual features such as colour and texture. The study aims to develop and train a deep learning model to classify lemons based on (...) their quality, evaluate the model's performance, compare it to traditional machine learning approaches, and identify key factors that affect the model's performance. The dataset used in the study consists of approximately 2533 images of lemons and an empty surface, divided into training, test, and validation data, and includes images of both good and bad quality lemons under different lighting conditions. The deep learning model achieved an accuracy of 99.74% on the test dataset and outperformed traditional machine learning approaches. The developed model has the potential to improve efficiency and accuracy in lemon quality control in the agriculture and food industry. (shrink)

It is crucial to actively detect the risks of transactions in a financial company to improve customer experience and minimize financial loss. In this study, we compare different machine learning algorithms to effectively and efficiently predict the legitimacy of financial transactions. The algorithms used in this study were: MLP Repressor, Random Forest Classifier, Complement NB, MLP Classifier, Gaussian NB, Bernoulli NB, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Bagging Classifier, Decision Tree Classifier and Deep Learning. The dataset (...) was collected from Kaggle depository. It consists of 6362620 rows and 10 columns. The best classifier with unbalanced dataset was the Random Forest Classifier. The Accuracy 99.97%, precession 99.96%, Recall 99.97% and the F1-score 99.96%. However, the best classifier with balanced dataset was the Bagging Classifier. The Accuracy 99.96%, precession 99.95%, Recall 99.98% and the F1-score 99.96%. (shrink)

Driver drowsiness is a significant factor contributing to road accidents, resulting in severe injuries and fatalities. This study presents an optimized approach for detecting driver drowsiness using machine learning techniques. The proposed system utilizes real-time data to analyze driver behavior and physiological signals to identify signs of fatigue. Various machine learning algorithms, including Support Vector Machines (SVM), Convolutional Neural Networks (CNN), and Random Forest, are explored for their efficacy in detecting drowsiness. The system incorporates an optimization technique—such as Genetic Algorithms (...) (GA) or Particle Swarm Optimization (PSO)—to enhance the accuracy and response time of the detection process. The integration of optimization methods ensures that the model adapts to various driving conditions and individual differences, providing a more reliable and robust detection mechanism. Data from multiple sources, including camera feeds and wearable sensors, are used to train and validate the models, ensuring a comprehensive understanding of drowsiness indicators. (shrink)

Quality assurance in large terminologies is a difficult issue. We present two algorithms that can help terminology developers and users to identify potential mistakes. We demon­strate the methodology by outlining the different types of mistakes that are found when the algorithms are applied to SNOMED-CT. On the basis of the results, we argue that both formal logical and linguistic tools should be used in the development and quality-assurance process of large terminologies.

The detection and analysis of misunderstandings are crucial aspects of discourse analysis, and presuppose a twofold investigation of their structure. First, misunderstandings need to be identified and, more importantly, justified. For this reason, a classification of the types and force of evidence of a misunderstanding is needed. Second, misunderstandings reveal differences in the interlocutors’ interpretations of an utterance, which can be examined by considering the presumptions that they use in their interpretation. This paper proposes a functional approach to misunderstandings grounded (...) on presumptive reasoning and types of presumptions, in which incompatible interpretations or interpretative failures are examined as defaults of the underlying interpretative reasoning, caused by overlooked evidence or conflicting presumptions. Moreover, it advances a classification of the types and the probative weights of the evidence that can be used to detect misunderstandings. The proposed methodology and its implications are illustrated through the analysis of doctor–patient communication in diabetes care. (shrink)

Political fact-checkers evaluate the truthfulness of politicians’ claims. This paper contributes to an emerging scholarly debate on whether fact-checkers treat political parties differently in a systematic manner depending on their ideology (bias). We first examine the available approaches to analyze bias and then present a new approach in two steps. First, we propose a logistic regression model to analyze the outcomes of fact-checks and calculate how likely each political party will obtain a truth score. We test our model with a (...) sample of fact-checks from Newtral, a major Spanish fact-checker. Our model would signal bias under two assumptions: a) all political parties are on average equally accurate in their statements; b) the verification method gives precise instructions and is implemented systematically. We investigate this second assumption with a series of interviews with Newtral fact-checkers. We show that standard verification protocols are so loosely implemented that fact-checks reflect a set of journalistic decisions, rather than a bias in the statistical sense. We call for a more rigorous definition of verification methods as a pre-requisite for an unbiased assessment of politician’s claims. (shrink)

In the classical Turing test, participants are challenged to tell whether they are interacting with another human being or with a machine. The way the interaction takes place is not direct, but a distant conversation through computer screen messages. Basic forms of interaction are face-to-face and embodied, context-dependent and based on the detection of reciprocal sensorimotor contingencies. Our idea is that interaction detection requires the integration of proprioceptive and interoceptive patterns with sensorimotor patterns, within quite short time lapses, so that (...) they appear as mutually contingent, as reciprocal. In other words, the experience of interaction takes place when sensorimotor patterns are contingent upon one’s own movements, and vice versa. I react to your movement, you react to mine. When I notice both components, I come to experience an interaction. Therefore, we designed a “minimal” Turing test to investigate how much information is required to detect these reciprocal sensorimotor contingencies. Using a new version of the perceptual crossing paradigm, we tested whether participants resorted to interaction detection to tell apart human from machine agents in repeated encounters with these agents. In two studies, we presented participants with movements of a human agent, either online or offline, and movements of a computerized oscillatory agent in three different blocks. In each block, either auditory or audiovisual feedback was provided along each trial. Analysis of participants’ explicit responses and of the implicit information subsumed in the dynamics of their series will reveal evidence that participants use the reciprocal sensorimotor contingencies within short time windows. For a machine to pass this minimal Turing test, it should be able to generate this sort of reciprocal contingencies. (shrink)

In “Normativity and Epistemic Intuitions”, Weinberg, Nichols and Stich famously argue from empirical data that East Asians and Westerners have different intuitions about Gettier -style cases. We attempted to replicate their study about the Car case, but failed to detect a cross - cultural difference. Our study used the same methods and case taken verbatim, but sampled an East Asian population 2.5 times greater than NEI’s 23 participants. We found no evidence supporting the existence of cross - cultural (...) class='Hi'>difference about the intuition concerning the Gettier car case. Taken together with the failures of both of the existing replication studies, our results provide strong evidence that the purported cross - cultural difference in Gettier intuitions does not exist. (shrink)

The mental risk poses a high threat to the individuals, especially overseas demographic, including expatriates in comparison to the general Arab demographic. Since Arab countries are renowned for their multicultural environment with half of the population of students and faculties being international, this paper focuses on a comprehensive analysis of mental health problems such as depression, stress, anxiety, isolation, and other unfortunate conditions. The dataset is developed from a web-based survey. The detailed exploratory data analysis is conducted on the dataset (...) collected from Arab countries to study an individual’s mental health and indicative help-seeking pointers based on their responses to specific pre-defined questions in a multicultural society. The proposed model validates the claims mathematically and uses different machine learning classifiers to identify individuals who are either currently or previously diagnosed with depression or demonstrate unintentional “save our souls” (SOS) behaviors for an early prediction to prevent risks of danger in life going forward. The accuracy is measured by comparing with the classifiers using several visualization tools. This analysis provides the claims and authentic sources for further research in the multicultural public medical sector and decision-making rules by the government. (shrink)

Although the character of the “lady detective”is a staple of the cozy mystery genre, we contend that there are no great lady detectives to rival Holmes or Poirot. This is not because there are no clever or interesting lady detective characters, but ratherbecause the concept of greatness is sociallyconstructed and, like coolness, depends on public acclaim and perception. We explore the mechanics of genre formation, arguing that the very structure of cozy mysteries precludes female greatness. To create a “great”character,theauthor cannot (...) just endowher with certain attributes; she must actively work to overcome her audience’s tendency to import structures of oppression into the story, and she must wrestle against the conventions of the genre. In doing so, however, authors risk setting their stories in a wholly different genre. (shrink)

We present the details of a methodology for quality assurance in large medical terminologies and describe three algorithms that can help terminology developers and users to identify potential mistakes. The methodology is based in part on linguistic criteria and in part on logical and ontological principles governing sound classifications. We conclude by outlining the results of applying the methodology in the form of a taxonomy different types of errors and potential errors detected in SNOMED-CT.

Current state-of-the-art out-of-distribution algorithm does not address the variation in dynamic and static behavior between malware variants from the same family as evidence in their poor performance against an out-of-distribution malware attack. We aims to address this limitation by: 1) exploitation of the in-dimensional embedding space between variants from the same malware family to account for all variations 2) exploitation of the inter-dimensional space between different malware family 3) building a deep learning-based model with a shallow neural network with maximum (...) of two connected layers to overcome overfitting from the scratch 4) building a Bayesian inference based computation algorithm that intertwine with connected network and is able to create new and adjust existing data points in response to an exposure to new out-of-distribution variants of existing or new malware family which determines the extent at which model weight is adjusted which in turn triggers update on the gradient. Preliminary result of our proposed framework gave an accuracy of 81\% in the successful classification of a novel out-of-distribution malware attack, something that could not be achieve by any of the state-of-the-art algorithms on novel malware classification. (shrink)

Current state-of-the-art out-of-distribution algorithm does not address the variation in dynamic and static behavior between malware variants from the same family as evidence in their poor performance against an out-of-distribution malware attack. We aims to address this limitation by: 1) exploitation of the in-dimensional embedding space between variants from the same malware family to account for all variations 2) exploitation of the inter-dimensional space between different malware family 3) building a deep learning-based model with a shallow neural network with maximum (...) of two connected layers to overcome overfitting from the scratch 4) building a Bayesian inference based computation algorithm that intertwine with connected network and is able to create new and adjust existing data points in response to an exposure to new out-of-distribution variants of existing or new malware family which determines the extent at which model weight is adjusted which in turn triggers update on the gradient. Preliminary result of our proposed framework gave an accuracy of 81\% in the successful classification of a novel out-of-distribution malware attack, something that could not be achieve by any of the state-of-the-art algorithms on novel malware classification. (shrink)

Demographic diversity might often be present in a group without group members noticing it. What are the epistemic effects if they do? Several philosophers and social scientists have recently argued that when individuals detect demographic diversity in their group, this can result in epistemic benefits even if that diversity doesn’t involve cognitive differences. Here I critically discuss research advocating this proposal, introduce a distinction between two types of detection of demographic diversity, and apply this distinction to the theorizing on diversity (...) in science. Focusing on ‘invisible’ diversity, I argue that in one common kind of group in science, if group members have full insight into their group’s diversity, this is likely to create epistemic costs. These costs can be avoided and epistemic benefits gained if group members only partly detect their group’s diversity. There is thus an epistemic reason for context-dependent limitations on scientists’ insight into the diversity of their group. (shrink)

In this paper we propose an non-machine learning artificial intelligence (AI) based approach for telecom data analysis, with a special focus on clique detection. Clique detection can be used to identify households, which is a major challenge in telecom data analysis and predictive analytics. Our approach does not use any form of machine learning, but another type of algorithm: satisfiability for propositional logic. This is a neglected approach in modern AI, and we aim to demonstrate that for certain tasks, it (...) may be a good alternative to machine learning-based approaches. We have used a simple DPLL satisfiability solver over an artificially generated telecom dataset (due to GDPR regulations), but our approach can be implemented on any telecom data by following the SAT encoding we have developed, and the DPLL solver can be substituted by a more advanced alternative such as CDCL. This paper extends the method presented in [1] for banking logs to data containing caller information, and proposes a more efficient encoding. -/- . (shrink)

Air pollution is a significant environmental concern that affects human health, ecosystems, and climate change. Effective monitoring and management of outdoor air quality are crucial for mitigating its adverse effects. This paper presents an advanced approach to outdoor pollution measurement utilizing Internet of Things (IoT) technology, combined with optimization techniques to enhance system efficiency and data accuracy. The proposed framework integrates a network of IoT sensors that continuously monitor various air pollutants, such as particulate matter (PM), carbon monoxide (CO), sulfur (...) dioxide (SO₂), nitrogen dioxide (NO₂), and ozone (O₃), across different geographic locations. The data collected by these sensors are transmitted to a centralized system where optimization algorithms, such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA), are applied to optimize sensor placement, data transmission, and processing efficiency. This ensures accurate, real-time pollution monitoring and data analysis, providing actionable insights for policymakers, environmental agencies, and the general public. (shrink)

To secure computers and information systems from attackers taking advantage of vulnerabilities in the system to commit cybercrime, several methods have been proposed for real-time detection of vulnerabilities to improve security around information systems. Of all the proposed methods, machine learning had been the most effective method in securing a system with capabilities ranging from early detection of software vulnerabilities to real-time detection of ongoing compromise in a system. As there are different types of cyberattacks, each of the existing state-of-the-art (...) machine learning models depends on different algorithms for training which also impact their suitability for detection of a particular type of cyberattack. In this research, we analyzed each of the current state-of-the art machine learning models for different types of cyberattack detection from the past 10 years with a major emphasis on the most recent works for comparative study to identify the knowledge gap where work is still needed to be done with regard to detection of each category of cyberattack. (shrink)

Mindfulness training has been used to improve emotional wellbeing in early adolescents. However, little is known about treatment outcome moderators, or individual differences that may differentially impact responses to treatment. The current study focused on gender as a potential moderator for affective outcomes in response to school-based mindfulness training. Sixth grade students (N = 100) were randomly assigned to either the six weeks of mindfulness meditation or the active control group as part of a history class curriculum. Participants in the (...) mindfulness meditation group completed short mindfulness meditation sessions four to five times per week, in addition to didactic instruction (Asian history). The control group received matched experiential activity in addition to didactic instruction (African history) from the same teacher with no meditation component. Self-reported measures of emotional wellbeing/affect, mindfulness, and self-compassion were obtained at pre and post intervention. Meditators reported greater improvement in emotional wellbeing compared to those in the control group. Importantly, gender differences were detected, such that female meditators reported greater increases in positive affect compared to females in the control group, whereas male meditators and control males displayed equivalent gains. Uniquely among females but not males, increases in self-reported self-compassion were associated with improvements in affect. These findings support the efficacy of school-based mindfulness interventions, and interventions tailored to accommodate distinct developmental needs of female and male adolescents. (shrink)

This study aimed to evaluate if eye blinks can be used to discriminate players with different performance in a session of Nintendo Entertainment System (NES) Tetris. To that end, we developed a state-of-the-art method for blink extraction from EAR measures, which is robust enough to be used with data collected by a low-grade webcam such as the ones widely available on laptop computers. Our results show a significant decrease in blink rate per minute (blinks/m) during the first minute of playing (...) Tetris. After having defined 3 groups of proficiency based on in-game performance (Novices, Intermediates, and Experts) we found out that expert players display a significantly lower decrease in blinks/m compared to novices during the first minute of gameplay, which shows that Tetris players' proficiency can be detected by looking at eye blinks/m variations during the early phase of a game session. This difference in blinks/m is observed throughout the entire game session, which supports the general conclusion that proficient Tetris players have a lower decrease in blinks/m, even when playing more difficult levels. Finally, we offer some interpretations of this effect and the relationship that our results may have with the visual cognitive workload experienced during the gameplay. (shrink)

Power transients faults on high voltage lines are prominently due to high frequency transients. These transients affect the predicted life and efficiency of equipment. The Fast Fourier Transform (FFT) is helpful in analysing the effect of high frequencies and Frequency Response Analysis (FRA) provide support in diagnosis and detection of deformation in a transformers. The major aim of this study is to analyse the incorporation of frequencies based on resonating core of a particular transformer. Using transfer function method an impedance (...) change in transformer has been observed when equipment is subjected to high voltage transients. The effect of change in impedance is that it degrade the life of a core with respect to time. In this paper, research that has been done already on Transformers of different ratings i.e. 100, 50 and 30 kVA are studied and then an experiment is performed on 50-kVA transformer. It was concluded that the core of a transformer having rating equal or less than 50 kVA practically shows single resonance behavior while above 50 kVA for instance 100-kVA transformer core resonates twice. In actual, result defines the core deviating frequency with respect to the rating of a transformer. (shrink)

In this paper, I want to look at Deleuze’s philosophical heritage in two different senses. In the first part of the paper, I explore his relationship to perhaps the most influential philosopher of the twentieth century, Martin Heidegger. Heidegger plays a central role in Deleuze’s early philosophy, and even when in his later collaborations with Guattari their explicit references to Heidegger are dismissive, Heidegger’s influence can clearly be detected, particularly in their critiques of other philosophers. In the second part of (...) the paper, I look at Deleuze’s own contribution to philosophy, and to see how this contribution has been assessed by one of the most influential contemporary French philosophers, Alain Badiou. For Heidegger, Deleuze, and Badiou, perhaps the central problem for philosophy emerges from thinking about totality. For all three, the traditional metaphysical view of totality, derived from Aristotle’s concept of paronymy, occludes rather than solves the problem of how we characterise our most general concepts. As we shall see, Heidegger’s diagnosis of metaphysics, as constituted by what he calls onto-theology, is shared by all three philosophers, while their responses to this diagnosis differ. Deleuze and Badiou both reject Heidegger’s poetics of being in favour of the language of mathematics, but the question I want to explore in the final part of the paper is, which mathematics? The mathematics of the continuous, or the mathematics of the discrete? (shrink)

Analyses of factual causation face perennial problems, including preemption, overdetermination, and omissions. Arguably, the thorniest, are cases of omissive overdetermination, involving two independent omissions, each sufficient for the harm, and neither, independently, making a difference. A famous example is Saunders, where pedestrian was hit by a driver of a rental car who never pressed on the (unbeknownst to the driver) defective (and, negligently, never inspected) brakes. Causal intuitions in such cases are messy, reflected in disagreement about which omission mattered. (...) What these analyses mistakenly take for granted, is that at issue is the 'efficacy' of each omission. I argue, on the contrary, the puzzle of omissive overdetermination favors taking the act/omission distinction seriously. Factual causation, properly understood precludes omissions (i.e. omissions are not causal). Of course, the law also attaches liability to omissions, but this works differently from liability for real causes (e.g. omissions have a duty requirement, they also respond differentially to difference-making considerations). The manner in which liability attaches for omissions differs from that of straightforward causal liability, and is entirely dependent on the underlying causal structure. Attention to that structure (e.g. that the driver's hitting the pedestrian with his car is what actually caused the injury) sheds light on which omissions matter (e.g. driver's failure to press on the brakes) and why (because that failure removes a defense the driver would have to liability for the accident he caused). Other cases, where the parties' connection is entirely omissive (e.g. two physicians fail to detect independently lethal conditions), come out differently (tracking moralized elements). The analysis offered makes better sense of both why omissive determination cases are puzzling and how to resolve them. (shrink)

Prior research found correlations between reflection test performance and philosophical tendencies among laypeople. In two large studies (total N = 1299)—one pre-registered—many of these correlations were replicated in a sample that included both laypeople and philosophers. For example, reflection test performance predicted preferring atheism over theism and instrumental harm over harm avoidance on the trolley problem. However, most reflection-philosophy correlations were undetected when controlling for other factors such as numeracy, preferences for open-minded thinking, personality, philosophical training, age, and gender. Nonetheless, (...) some correlations between reflection and philosophical views survived this multivariate analysis and were only partially confounded with either education or self-reported reasoning preferences. Unreflective thinking still predicted believing in God whereas reflective thinking still predicted believing that (a) proper names like ‘Santa’ do not necessarily refer to entities that actually exist and (b) science does reveal the fundamental nature of the world. So some robust relationships between reflection and philosophical tendencies were detected even among philosophers, and yet there was clearly more to the link between reflection and philosophy. To this end, demographic and metaphilosophical hypotheses are considered. (shrink)

A major question in sensory science is how a sensation of magnitude F (such as loudness) depends upon a sensory stimulus of physical intensity I (such as a sound-pressure-wave of root-mean-square sound-pressure-level). An empirical just-noticeable sensation difference (∆F)_j at F_j specifies a just-noticeable intensity difference (∆I)_j at I_j. Classically, intensity differences accumulate from a stimulus-detection threshold I_th up to a desired intensity I. The corresponding sensation differences likewise accumulate up to F(I) from F(I_th ), the non-zero sensation (as (...) suggested by hearing studies) at I_th. Consequently, sensation growth F(I) can be obtained through classic Fechnerian integration, in which some empirically-based relation for the Weber Fraction, ∆I⁄I, is combined with either Fechner’s Law ∆F=B or Ekman’s Law (∆F⁄F)=g. The number of steps in I is equated to the number of steps in F; an infinite series ensues, whose higher-order terms are traditionally ignored (Fechnerian integration). But also, remarkably, so are the integration bounds I_th and F(I_th ). Here, we depart from orthodoxy by including those bounds. Bounded Fechnerian integration is first used to derive hypothetical sensation-growth equations for which the differential ∆F(I)=F(I+∆I)-F(I) does indeed return either Fechner’s Law or Ekman’s Law respectively. One relation emerges: linear growth of sensation F with intensity I. Subsequently, 24 sensation-growth equations F(I) that the author had derived using bounded Fechnerian integration (12 equations for the Weber Fraction (∆I⁄I), each combined with either Fechner’s Law or with Ekman’s Law) are scrutinized for whether their differentials F(I+∆I)-F(I) return the respective Fechner’s Law or Ekman’s Law, particularly in the previously-unexamined limits (∆I⁄I)≪1 and (∆I⁄I)→0. Classic claims made by Luce and Edwards (1958) are then examined, viz., that three popular forms of the Weber Fraction, when combined with Fechner’s Law, produce sensation-magnitude equations that subsequently return the selfsame Fechner’s Law. When sensation-growth equations are derived here using bounded Fechnerian integration, Luce and Edwards (1958) prove to be wrong. (shrink)

An ongoing mystery in sensory science is how sensation magnitude F(I), such as loudness, increases with increasing stimulus intensity I. No credible, direct experimental measures exist. Nonetheless, F(I) can be inferred algebraically. Differences in sensation have empirical (but non-quantifiable) minimum sizes called just-noticeable sensation differences, ∆F, which correspond to empirically-measurable just-noticeable intensity differences, ∆I. The ∆Is presumably cumulate from an empirical stimulus-detection threshold I_th up to the intensity of interest, I. Likewise, corresponding ∆Fs cumulate from the sensation at the stimulus-detection (...) threshold, F(I_th ), up to F(I). Regarding the ∆Is, however, it is unlikely that all of them will be known experimentally; the procedures are too lengthy. The customary approach, then, is to find ∆I at a few widely-spaced intensities, and then use those ∆Is to interpolate all ∆Is using some smooth continuous function. The most popular of those functions is Weber’s Law, ∆I⁄I=K. But that is often not even a credible approximation to the data. However, there are other equations for ∆I⁄I. Any such equation for ∆I⁄I can be combined with any equation for ∆F, through calculus, to altogether obtain F(I). Here, two assumptions for ∆F are considered: ∆F=B (Fechner’s Law) and (∆F⁄F)=g (Ekman’s Law). The respective integrals involve lower bounds I_th and F(I_th ). This stands in broad contrast to the literature, which heavily favors non-bounded integrals. We, hence, obtain 24 new, alternative equations for sensation magnitude F(I) (12 equations for (∆I⁄I) × 2 equations for ∆F). (shrink)

In one of the earlier influential papers in the field of experimental philosophy titled Normativity and Epistemic Intuitions published in 2001, Jonathan M. Weinberg, Shaun Nichols and Stephen Stich reported that respondents answered Gettier type questions differently depending on their ethnic background as well as socioeconomic status. There is currently a debate going on, on the significance of the results of Weinberg et al. (2001) and its implications for philosophical methodology in general and epistemology in specific. Despite the debates, however, (...) to our knowledge, there has not been a replication attempt of the experiments of the original paper. We collected data from four different sources (two on-line and two in-person) to replicate the experiments. Despite several different data sets and in various cases larger sample sizes and hence greater power to detect differences, we failed to detect significant differences between the above-mentioned ethnic and socioeconomic groups. Our results suggest that epistemic intuitions are more robust across ethnic and socioeconomic groups than Weinberg et al. (2001) indicates. Given our data, we believe that the notion of differences in epistemic intuitions among different ethnic and socioeconomic groups that follows from Weinberg et al. (2001) needs to be corrected. (shrink)

The study aimed to identify the reality of total quality management in university colleges in Gaza Strip, through its dimensions, which are (commitment of senior management; organizational building; employee empowerment; continuous improvement; focus on beneficiaries; management by facts), and to detect differences in the responses of sample members according to For personal variables (type; educational qualification; college; nature of work; years of service). The researchers used the descriptive analytical method, and used a main tool to collect information: the questionnaire consisted (...) of (42) phrases, and the study population reached (596) academic and administrative employees distributed to (5) university colleges in Gaza Strip, and it was chosen A stratified random sample of them consisted of (240) employees, approximately (40.3%) of the study population. (SPSS) was used to analyze the data. The study concluded a set of results, the most important of which are: (1) The application of the requirements of total quality management in university colleges in Gaza Strip is generally appropriate in terms of: (the commitment of senior management to total quality management, organizational building, facts management, focus on beneficiaries, employee empowerment, continuous improvement), where the response of the sample members was about the dimensions Total quality management with relative weight (69.93%). (2) There are differences at the level of significance (α =.05) between the averages of the respondents' responses to total quality management in university colleges in Gaza Strip due to gender and differences in favor of the male category. And differences attributed to the college and in favor of the University College of Professional Sciences. (3) There are no differences between the averages of the respondents' responses to total quality management in university colleges in Gaza Strip due to (Educational Qualification, Nature of Work, and Years of Service). Among the most important recommendations of the study: The need for university colleges to ensure: (achieving job satisfaction, employee participation when setting regulations and policies and making important decisions, adhering to the requirements of scientific research and encouraging scientific achievements and job creativity among employees, while providing material and moral facilities for scientific research and development, developing Mechanisms and patterns of electronic work). And that university colleges give attention to handling complaints and grievances through: (assigning a competent and competent committee to handle complaints and grievances in all fairness and transparency, adopting and following up on the results of implementing complaints and grievances, protecting the complainants from any arbitrary procedure against them). (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. We also explore the ethical implications and challenges associated with deploying such systems, particularly regarding privacy concerns and the potential for misuse. Through extensive experiments, our model achieved an average accuracy rate of 92%, highlighting its robustness across different environments and user demographics. This research not only contributes to the growing field of affective computing but also lays the groundwork for future developments in emotionally intelligent systems. (shrink)

Studying the neural correlates of conscious awareness depends on a reliable comparison between activations associated with awareness and unawareness. One particularly difficult confound to remove is task performance capacity, i.e. the difference in performance between the conditions of interest. While ideally task performance capacity should be matched across different conditions, this is difficult to achieve experimentally. However, differences in performance could theoretically be corrected for mathematically. One such proposal is found in a recent paper by Lamy, Salti and Bar-Haim (...) [Lamy D, Salti M, Bar-Haim Y. Neural correlates of subjective awareness and unconscious processing: an ERP study. J Cognitive Neurosci 2009,21:1435-46], who put forward a corrective method for an electroencephalography experiment. We argue that their analysis is essentially grounded in a version of High Threshold Theory, which has been shown to be inferior in general to Signal Detection Theory. We show through a series of computer simulations that their correction method only partially removes the influence of perfor- mance capacity, which can yield misleading results. We present a mathematical correction method based on Signal Detection Theory that is theoretically capable of removing performance capacity confounds. We discuss the limitations of mathemati- cally correcting for performance capacity confounds in imaging studies and its impact for theories about consciousness. (shrink)

Local reports from different international societies have considered the achievement of the successful Glocalized architecture model in line with the 2030 UN Sustainable Development Goals (SDGs). The Aga Khan Cultural Foundation’s International Program for Islamic Architecture has also prioritized the understanding of the success drivers in architectural projects. This study aimed to detect the potentials of the common global indicators to access qualitative design assessment through analyzing the Aga Khan Award’s reports. The selected methodology in the present study is a (...) quantitative approach using the systematic content analysis and coding techniques for qualitative data obtained from the technical. The physical, non-physical, modern, and traditional factors that have contributed to the success of the works as well as their combinations were extracted and analyzed using Sensible and Abstract international, national, and local indications. There is a relative superiority for Sensible indications (A combination of modern and physical factors). The hybrid data distribution provides the ground to assess the works, and this can be used to manage the globalization challenges in the contemporary architecture of Muslim societies. (shrink)

When visual attention is directed away from a stimulus, neural processing is weak and strength and precision of sensory data decreases. From a computational perspective, in such situations observers should give more weight to prior expectations in order to behave optimally during a discrimination task. Here we test a signal detection theoretic model that counter-intuitively predicts subjects will do just the opposite in a discrimination task with two stimuli, one attended and one unattended: when subjects are probed to discriminate the (...) unattended stimulus, they rely less on prior information about the probed stimulus’ identity. The model is in part inspired by recent findings that attention reduces trial-by-trial variability of the neuronal population response and that they use a common criterion for attended and unattended trials. In five different visual discrimination experiments, when attention was directed away from the target stimulus, subjects did not adjust their response bias in reaction to a change in stimulus presentation frequency despite being fully informed and despite the presence of performance feedback and monetary and social incentives. This indicates that subjects did not rely more on the priors under conditions of inattention as would be predicted by a Bayes-optimal observer model. These results inform and constrain future models of Bayesian inference in the human brain. (shrink)

The detection of hate speech and fake news in political discourse is at the same time a crucial necessity for democratic societies and a challenge for several areas of study. However, most of the studies have focused on what is explicitly stated: false article information, language that expresses hatred, derogatory expressions. This paper argues that the explicit dimension of manipulation is only one – and the least problematic – of the risks of political discourse. The language of the unsaid is (...) much more dangerous and incomparably more difficult to detect, hidden in different types of fallacies and inappropriate uses of emotive language. Through a threefold coding scheme based on the instruments of argumentation theory and pragmatics, a corpus of argumentative tweets published by 4 politicians (Matteo Salvini, Donald Trump, Jair Bolsonaro, and Joseph Biden) within 6 months from their taking office (corresponding to the official end of their election campaign) is analyzed, detecting the types of argument, the fallacies, and the uses and misuses of “emotive words.” This coding results in the argumentation profiles of the speakers, which are compared statistically to show their different implicit strategies and deceptive tactics. (shrink)

Detecting quality in large unstructured datasets requires capacities far beyond the limits of human perception and communicability and, as a result, there is an emerging trend towards increasingly complex analytic solutions in data science to cope with this problem. This new trend towards analytic complexity represents a severe challenge for the principle of parsimony (Occam’s razor) in science. This review article combines insight from various domains such as physics, computational science, data engineering, and cognitive science to review the specific properties (...) of big data. Problems for detecting data quality without losing the principle of parsimony are then highlighted on the basis of specific examples. Computational building block approaches for data clustering can help to deal with large unstructured datasets in minimized computation time, and meaning can be extracted rapidly from large sets of unstructured image or video data parsimoniously through relatively simple unsupervised machine learning algorithms. Why we still massively lack in expertise for exploiting big data wisely to extract relevant information for specific tasks, recognize patterns and generate new information, or simply store and further process large amounts of sensor data is then reviewed, and examples illustrating why we need subjective views and pragmatic methods to analyze big data contents are brought forward. The review concludes on how cultural differences between East and West are likely to affect the course of big data analytics, and the development of increasingly autonomous artificial intelligence (AI) aimed at coping with the big data deluge in the near future. Keywords: big data; non-dimensionality; applied data science; paradigm shift; artificial intelligence; principle of parsimony (Occam’s razor) . (shrink)

Anamoly detection in videos plays an important role in various real-life applications. Most of traditional approaches depend on utilizing handcrafted features which are problem-dependent and optimal for specific tasks. Nowadays, there has been a rise in the amount of disruptive and offensive activities that have been happening. Due to this, security has been given principal significance. Public places like shopping centers, avenues, banks, etc. are increasingly being equipped with CCTVs to guarantee the security of individuals. Subsequently, this inconvenience is making (...) a need to computerize this system with high accuracy. Since constant observation of these surveillance cameras by humans is a near-impossible task. It requires workforces and their constant attention to judge if the captured activities are anomalous or suspicious. Hence, this drawback is creating a need to automate this process with high accuracy. Moreover, there is a need to display which frame and which parts of the recording contain the uncommon activity which helps the quicker judgment of that unordinary action being unusual or suspicious. Therefore, to reduce the wastage of time and labour, we are utilizing deep learning algorithms for Automating Threat Recognition System. Its goal is to automatically identify signs of aggression and violence in real-time, which filters out irregularities from normal patterns. We intend to utilize different Deep Learning models (CNN and RNN) to identify and classify levels of high movement in the frame. From there, we can raise a detection alert for the situation of a threat, indicating the suspicious activities at an instance of time and spray the smoke spray. (shrink)

To find the neural substrates of consciousness, researchers compare subjects’ neural activity when they are aware of stimuli against neural activity when they are not aware. Ideally, to guarantee that the neural substrates of consciousness—and nothing but the neural substrates of consciousness—are isolated, the only difference between these two contrast conditions should be conscious awareness. Nevertheless, in practice, it is quite challenging to eliminate confounds and irrelevant differences between conscious and unconscious conditions. In particular, there is an often-neglected confound (...) that is crucial to eliminate from neuroimaging studies: task performance. Unless subjects’ task performance is matched (and hence perceptual signal processing is matched), researchers risk finding the neural correlates of perception, rather than conscious perception. Here, we discuss the theoretical motivations for the performance matching framework and review empirical demonstrations of, and theoretical inferences derived from, obtaining differences in consciousness while controlling for task performance. We summarize signal detection theoretic modeling frameworks that explain how it is that we can derive performance-matched differences in consciousness without the effect being trivially driven by differences in criterion setting, and also provide principles for designing experimental paradigms that yield performance-matched differences in awareness. Finally, we address potential technical and theoretical issues that stem from matching performance across conditions of awareness, and we introduce the notion of “triangulation” for designing comprehensive experimental sets that can better reveal the neural substrates of consciousness. (shrink)

The thresholds of human observers detecting line targets improve significantly when the targets are presented in a spatial context of collinear inducing stimuli. This phenomenon is referred to as spatial facilitation, and may reflect the output of long-range interactions between cortical feature detectors. Spatial facilitation has thus far been observed with luminance-defined, achromatic stimuli on achromatic backgrounds. This study compares spatial facilitation with line targets and collinear, edge-like inducers defined by luminance contrast to spatial facilitation with targets and inducers defined (...) by color contrast. The results of a first experiment show that achromatic inducers facilitate the detection of achromatic targets on gray and colored backgrounds, but tend to suppress the detection of chromatic targets. Chromatic inducers facilitate the detection of chromatic targets on gray and colored backgrounds, but tend to suppress the detection of achromatic targets. Chromatic spatial facilitation appears to be strongest when inducers and background are isoluminant. The results of a second experiment show that spatial facilitation with chromatic targets and inducers requires a longer exposure duration of the inducers than spatial facilitation with achromatic targets and inducers, which is already fully effective at an inducer exposure of 30 ms only. The findings point towards two separate mechanisms for spatial facilitation with collinear form stimuli: one that operates in the domain of luminance, and one that operates in the domain of color contrast. These results are consistent with neural models of boundary and surface formation which suggest that achromatic and chromatic visual cues are represented on different cortical surface representations that are capable of selectively attracting attention. Multiple copies of these achromatic and chromatic surface representations exist corresponding to different ranges of perceived depth from an observer, and each can attract attention to itself. Color and contrast differences between inducing and test stimuli, and transient responses to inducing stimuli, can cause attention to shift across these surface representations in ways that sometimes enhance and sometimes interfere with target detection. (shrink)

Solar radiation management (SRM) may help to reduce the negative outcomes of climate change by minimising or reversing global warming. However, many express the worry that SRM may pose a moral hazard, i.e., that information about SRM may lead to a reduction in climate change mitigation efforts. In this paper, we report a large-scale preregistered, money-incentivised, online experiment with a representative US sample (N = 2284). We compare actual behaviour (donations to climate change charities and clicks on climate change petition (...) links) as well as stated preferences (support for a carbon tax and self-reported intentions to reduce emissions) between participants who receive information about SRM with two control groups (a salience control that includes information about climate change generally and a content control that includes information about a different topic). Behavioural choices are made with an earned real-money endowment, and stated preference responses are incentivised via the Bayesian Truth Serum. We fail to find a significant impact of receiving information about SRM and, based on equivalence tests, we provide evidence in favour of the absence of a meaningfully large effect. Our results thus provide evidence for the claim that there is no detectable moral hazard with respect to SRM. [Open access]. (shrink)

Academic integrity is an essential pillar of any educational system. It is defined as acting in a manner consistent with the values and accepted standards of ethical practices in teaching, learning, and scholarship (Fishman, 2015). Contract cheating, or ghostwriting, is currently one of the most severe violations of academic integrity. It involves students engaging a third party, usually an online essay writing service, to complete their academic works on their behalf (Draper et al., 2021). Some of these services offer pre-written (...) essays, whereas others offer bespoke custom-written essays. According to the academic literature, the advent of the internet and digital technologies underlay this rapid deterioration of academic integrity (Ison, 2020; Lancaster & Clarke, 2014). Different learning environments, such as face-to-face (i.e., a learning environment involving the physical presence of both instructor and students) and online web-based (i.e., teaching mode that takes place partially or entirely over the internet), have been shown to affect academic integrity in different ways (Eshet et al., 2021). While contract cheating is common in both conventional face-to-face (F2F) and online settings, it is more likely to take place in the latter (Lancaster & Clarke, 2014; Slade et al., 2018). There are several possible explanations for why online students engage in contract cheating more often than F2F students. In particular, this includes the problem issue of psychological distance, which adversely affects interpersonal relationships; and the problem issue of moral distancing, because the internet can obscure the line between academically honest and dishonest behavior (Sharma & Maleyeff, 2003). These issues were further exacerbated by the sudden shift from F2F to emergency remote teaching (ERT) in response to the COVID-19 pandemic (Ahsan et al., 2021; Bjelobaba, 2021). Indeed, contract cheating had become a significant COVID-19 side effect for higher education institutions. In contrast to the well-planned F2F or online learning courses, ERTbased courses are not originally designed to be delivered virtually (Fatonia et al., 2020). The chaos brought by the abrupt campus closure and related unexpected transition to ERT provided both the opportunity and the incentive for contract cheating (Hill et al., 2021). Through social media, students have very quickly become fully aware of the possibilities of a wide variety of options to carry out Plagiarism (Bautista et al., 2022). There has been an increase in ways to try to bypass text-matching or text-reuse (i.e., plagiarism) detection systems, for example using micro-spaces, white ink, punctuation, and typos (Abdelhamid et al., 2022). Even though ghostwriters, especially commercial ones, claim their essays are original and therefore cannot be detected using text-matching software, third-party assignments may still contain recycled text (Aitken et al., 2017; Newton & Lang, 2015). Text matching detection software could use these breaches to identify outsourced academic work (Lancaster & Clarke, 2016; Wang & Xu, 2021). This study compared about four thousand term papers written in languages other than Hebrew. (shrink)

In the Dunhuang manuscript IOL Tib J 709, which is a collection of writings concerning meditation, we come across a short text attributed to a Tibetan master called Byaṅ-cub-klu-dbaṅ (allegedly eighth-ninth centuries CE). In his work, Byaṅ-cub-klu-dbaṅ exposes a method of meditation that seems to be strongly indebted to Indian Mahāyāna scriptural sources. Besides, also a Chinese Chan influence is here detectable. Therefore, the method of meditation taught by Byaṅ-cub-klu-dbaṅ seems to represent a commingling of different elements from different (...) contexts. After a general introduction to the manuscript IOL Tib J 709, this study focuses on Byaṅ-cub-klu-dbaṅ’s text, discussing and analysing the following topics: its author and date, the Indian Mahāyāna possible sources, Chinese Chan elements, the meditational path described. An annotated translation of the text, along with its transliteration and the reproduction of the fac-simile of the corresponding portion of the manuscript, concludes the study. (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)

Scientists use visualisations of different kinds in a variety of ways in their scientific work. In the following article, we will take a closer look at the use of photographic pictures as scientific evidence. In accordance with Patrick Maynard’s thesis, photography will be regarded as a family of technologies serving different purposes in divergent contexts. One of these is its ability to detect certain phenomena. Nonetheless, with regard to the philosophical thesis of theory-ladenness of observation, we encounter certain reservations concerning (...) the status of photography and that of photographic pictures in the process of measurement in science. Accordingly, the aim of this paper is twofold: We will discuss suggested solutions both for the technological and for the psychological part of the problem of theory-ladenness appearing in the context of the use of photography in scientific observations. The essential proposal will be to follow Christian Suhm in his advice to make a distinction between theory-relativity and theory-ladenness. (shrink)

Resumo: Sabe-se que a pecuária é uma parcela do agronegócio que move a economia do país, e incluso está a produção leiteira, que tem, a cada ano seu desenvolvimento elevado, de forma em que é priorizado a eficiência no aumento de sua produção, com o objetivo de suprir a demanda, e a maior rentabilidade do produtor. Diante disso, medidas de manejo reprodutivo e alimentar são adotadas, sendo estas capazes de elevar a produtividade com o menor custo possível. O trabalho objetivou (...) pautar acerca do conhecimento sobre o manejo nutricional correto e escore corporal, que afetam diretamente a produtividade do animal, o conhecimento acerca do ciclo reprodutivo de vacas, expondo a detecção de estro, bem como metodologias eficazes aplicadas na reprodução, e práticas de bem estar, que, quando ausente, é apontado como um dos precursores da ineficiência reprodutiva. Palavras-chave: Inseminação Artificial 1; detecção de cio 2; leite 3. Abstract: It is known that livestock is a part of agribusiness that drives the country's economy, and is even milk production, which has, every year, its high development, so that it is prioritizing efficiency in increasing its production, with the objective of supplying the demand, and the greater producer profitability. Therefore, reproductive and food management measures are adopted, being able to increase productivity with the lowest possible cost. The work aimed guide about knowledge about correct nutritional management and body score, which affect directly the animal's productivity, knowledge about the reproductive cycle of cows, exposing estrus detection, as well as effective methodologies applied in reproduction, and practices of well-being, which, when absent, is pointed out as one of the precursors of inefficiency reproductive. Keywords: Artificial Insemination 1; heat detection 2; milk 3. -/- REFERÊNCIAS BIBLIOGRÁFICAS ALFIERI, A. A. LEME, R. ALFIERI, A.F. Tecnologias para o manejo sanitário de qualidade de doenças infecciosas na bovinocultura de corte. Bovinocultura de corte: desafios e tecnologias. Revista eletrônica da Universidade Federal da Bahia - UFBA. ed. 2. v. 1. p. 115-132. 2013. ARBOLEDA, José Leonardo Ruiz; URIBE-VELÁSQUEZ, Luis Fernando; OSORIO, José Henry. Factor de crecimiento semejante a insulina tipo 1 (IGF-1) en la reproducción de la hembra bovina. Vet. zootec, v. 5, n. 2, p. 68-81, 2011. BAUMGARD, L.; RHOADS, R. Efeito do estresse calórico no metabolismo e na produção de leite, e estratégias para minimizar efeitos negativos. Em: XVI Curso Novos Enfoques na Produção e Reprodução de Bovinos. Uberlandia, Brasil, 2012. BARUSELLI, P. S. et al. Evolução e perspectivas da inseminação artificial em bovinos. Revista Brasileira de Reprodução Animal. v 43. n 2. p 308-314. 2019. BARUSELLI, Pietro Sampaio; GIMENES, Lindsay Unno; SALES, José Nélio de Sousa. Fisiologia reprodutiva de fêmeas taurinas e zebuínas. Revista Brasileira de Reprodução Animal, v. 31, n. 2, p. 205-211, 2007. BERGAMASCHI, M. A. C. M., MACHADO, R. BARBOSA, R. T. Eficiência reprodutiva das vacas leiteiras. Embrapa - Pecuária Sudeste- Circular Técnica (INFOTECA-E). 2010. Arquivo digitaldisponívelem:. Acesso em: 15 de Novembro de 2021. BORGES, A. M.; MARTINS, T. M. Relação entre nutrição e reprodução em rebanhos mestiços leiteiros. In: IV SIMPÓSIO NACIONAL DE BOVINOCULTURA DE LEITE, 2013, Viçosa. Anais ... Viçosa, p. 215-236, 2013. BORGES, A. et al. Reprodução de vacas mestiças: potencialidade e desafios. Revista Brasileira de Reprodução Animal. v 39. n 1. p 155-163. 2015. CAETANO, R. P. et. al. Manejo reprodutivo da bovinocultura de leite nos assentamentos rurais do município de Ilha Solteira, São Paulo. 8º Congresso de Extensão Universitária da UNESP. ISSN 2176- 9761. p 4. 2015. Arquivo disponível em: CARNEIRO M.A., Bergamaschi M., Machado R. & Barbosa R.T. (2010) Eficiência reprodutiva das vacas leiteiras. Embrapa Pecuária Sudeste. Circular Técnica,64. ISSN: 1981- 2086. CERVO. H J. Fatores intrínsecos à produção, o uso da inseminação artificial e os objetivos de seleção na pecuária leiteira do sul do Brasil, Rio Grande do Sul, Brasil. 2014. 228f. Tese (Doutorado em Zootecnia) - Universidade Federal do Rio Grande do Sul – UFRS, Porto Alegre. DA SILVA, Emanuel Isaque Cordeiro. Fisiologia Clínica do Ciclo Estral de Vacas Leiteiras: Desenvolvimento Folicular, Corpo Lúteo e Etapas do Estro. 2020. DA SILVA, Emanuel Isaque Cordeiro. Fisiologia da Reprodução Animal: Ovulação, Controle e Sincronização do Cio. 2020. DA SILVA, et al. Manual de Exame Ginecológico da Vaca. IX Mostra Nacional de Iniciação Científica e Tecnológica Interdisciplinar (MICTI) - IFC - Instituto Federal Catarinense. 2016. Arquivo digital disponível em: Acesso em: 15 de Novembro de 2021. DIAS. J C. et al. Alguns aspectos da interação nutrição-reprodução em bovinos: energia, proteínas, minerais e vitaminas. 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Dissertação (Mestrado em Medicina Veterinária) - Universidade de Évora - Escola de Ciências e Tecnologia, Évora. MANTECA, X. et al. Bem-estar animal: conceitos e formas práticas de avaliação dos sistemas deprodução de suínos. Revista - Semina: Ciências Agrárias. v. 34 n. 2. p 4213-4229. 2013. MOURA, M. S. et al. Manejo reprodutivo de bovinos na propriedade rural. Revista PUBVET. v. 5. n 9.ed. 156. art. 1055, 2011. MUNIS DE OLIVEIRA, G. Fisiologia da Reprodução Bovina e Métodos de Controle do Ciclo Estral. Trabalho de conclusão do curso de especialização em Reprodução e Produção de Bovinos–UCB. Rio de Janeiro, Brasil, 2006. NETO, Alberto Chambela. Avaliação da taxa de prenhez de vacas de leite com a utilização de protocolos com e sem a presença de folículos estimulantes. Revista Ifes Ciência-ISSN 2359- 4799, v. 5, n. 1, 2019. NOGUEIRA, E. et al. Nutrição aplicada à reprodução de bovinos de corte. Embrapa PantanalCapítuloem livro científico. Embrapa Pantanal - Capítulo em livro científico (ALICE). ed. 10. p 141-156. 2015. PEGORARO, L. M. C.; SAALFELD, M. H.; WEISSHEIMER, C. F.; VIEIRA, A. D. Manejo Reprodutivo em Bovinos de Leite. Embrapa Clima Temperado, id.13081, 2009. PEIXOTO JUNIOR, K.C. FIRMIANO, A. C. CRESPILHO, A.M. Relação entre reprodução e produção debovinos de leite. Revista PUBVET, Londrina. v 7. n 24. ed 247. art. 1635. 2013. PEREIRA, M.A et al. Parâmetros da Fisiologia reprodutiva e utilização de hormônios na sincronizaçãode estro em vacas leiteiras. Revista VeZ em Minas. a XXII. p 117. 2013. PRATA, M. A.; PEREIRA, M. C.; FARO, L; CARDOSO, V. L. et al. Efeito do intervalo de partos sobre a eficiência produtiva e econômica em rebanhos gir leiteiro. B. Indústr. Anim., Nova Odessa, v.71, n.1, p.1-7, 2014. Rebanho bovino tem leve alta em 2019, após dois anosseguidos de quedas. Agência de notícias IBGE, 2020. Disponível em: . Acesso em: 26, setembro de 2021. RENNO F.P; BARLETTA, R.V.; FRIETAS JUNIOR J.E.; et al. 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Embrapa Clima Temperado - Livro técnico. ed 1. p 437. 2016. SOUSA, G. G. T. et al. Monta natural versus inseminação artificial em bovinos. Revista PUBVET. v 6. n35. ed 222. art. 1473. 2012. TRIANA, E. L. C. JIMENEZ, C. R. TORRES, C A. A. Eficiência reprodutiva em bovinos de leite. Revista Eletrônica da Universidade Federal de Viçosa - UFV. v 1. 2012. Artigo eletrônico disponível em: Acesso em: 02 de outubro de 2021. (shrink)

Harms of medical interventions are systematically underestimated in clinical research. Numerous factors—conceptual, methodological, and social—contribute to this underestimation. I articulate the depth of such underestimation by describing these factors at the various stages of clinical research. Before any evidence is gathered, the ways harms are operationalized in clinical research contributes to their underestimation. Medical interventions are first tested in phase 1 ‘first in human’ trials, but evidence from these trials is rarely published, despite the fact that such trials provide the (...) foundation for assessing the harm profile of medical interventions. If a medical intervention is deemed safe in a phase 1 trial, it is tested in larger phase 2 and 3 clinical trials. One way to think about the problem of underestimating harms is in terms of the statistical ‘power’ of a clinical trial—the ability of a trial to detect a difference of a certain effect size between the experimental group and the control group. Power is normally thought to be pertinent to detecting benefits of medical interventions. It is important, though, to distinguish between the ability of a trial to detect benefits and the ability of a trial to detect harms. I refer to the former as power-B and the latter as power-H. I identify several factors that maximize power-B by sacrificing powerH in phase 3 clinical trials. If a medical intervention is approved for general use, it is evaluated by phase 4 post-market surveillance. Phase 4 surveillance of harms further contributes to underestimating the harm profile of medical interventions. At every stage of clinical research the hunt for harms is shrouded in secrecy, which further contributes to the underestimation of the harm profiles of medical interventions. (shrink)

Does perceptual consciousness require cognitive access? Ned Block argues that it does not. Central to his case are visual memory experiments that employ post-stimulus cueing—in particular, Sperling's classic partial report studies, change-detection work by Lamme and colleagues, and a recent paper by Bronfman and colleagues that exploits our perception of ‘gist’ properties. We argue contra Block that these experiments do not support his claim. Our reinterpretations differ from previous critics' in challenging as well a longstanding and common view of visual (...) memory as involving declining capacity across a series of stores. We conclude by discussing the relation of probabilistic perceptual representations and phenomenal consciousness. (shrink)

Large changes in a scene often become difficult to notice if made during an eye movement, image flicker, movie cut, or other such disturbance. It is argued here that this _change blindness_ can serve as a useful tool to explore various aspects of vision. This argument centers around the proposal that focused attention is needed for the explicit perception of change. Given this, the study of change perception can provide a useful way to determine the nature of visual attention, and (...) to cast new light on the way that it is?and is not?involved in visual perception. To illustrate the power of this approach, this paper surveys its use in exploring three different aspects of vision. The first concerns the general nature of _seeing_. To explain why change blindness can be easily induced in experiments but apparently not in everyday life, it is proposed that perception involves a _virtual representation_, where object representations do not accumulate, but are formed as needed. An architecture containing both attentional and nonattentional streams is proposed as a way to implement this scheme. The second aspect concerns the ability of observers to detect change even when they have no visual experience of it. This _sensing_ is found to take on at least two forms: detection without visual experience (but still with conscious awareness), and detection without any awareness at all. It is proposed that these are both due to the operation of a nonattentional visual stream. The final aspect considered is the nature of visual attention itself?the mechanisms involved when _scrutinizing_ items. Experiments using controlled stimuli show the existence of various limits on visual search for change. It is shown that these limits provide a powerful means to map out the attentional mechanisms involved. (shrink)