En Electromecánicas IV, – Despliegue y activación de un espacio-tiempo barroco, Mónica Salinero socióloga y Renzo Filinich artista, se sumergen en el trabajo de análisis de la obra de Raúl Díaz, “Electromecánicas IV, poniendo en valor la diferencia conceptual y la diversidad del universo latinoamericano como espacio de creación situado. Inspirados en las teorías de Bolivar Echevarria, discuten la complejidad simbólica que rodea a esta experiencia estética, deteniéndose en los valores y funciones que se encuentran dentro del espectro cultural andino (...) que la contiene. El relato persigue desentrañar el armazón de pensamiento que alumbra el proceso de creación, cuando la puesta en marcha de dispositivos obsoletos, se vuelve metáfora de intervención local, sobre una reciclada y reconvertida tradición occidental, que representa la idea de Modernidad barroca. (shrink)

Most of our best scientific descriptions of the world employ rates of change of some continuous quantity with respect to some other continuous quantity. For instance, in classical physics we arrive at a particle’s velocity by taking the time-derivative of its position, and we arrive at a particle’s acceleration by taking the time-derivative of its velocity. Because rates of change are defined in terms of other continuous quantities, most think that facts about some rate of change obtain in virtue (...) of facts about those other continuous quantities. For example, on this view facts about a particle’s velocity at a time obtain in virtue of facts about how that particle’s position is changing at that time. In this paper we raise a puzzle for this orthodox reductionist account of rate of change quantities and evaluate some possible replies. We don’t decisively come down in favour of one reply over the others, though we say some things to support taking our puzzle to cast doubt on the standard view that spacetime is continuous. (shrink)

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

For decades, student ratings of university faculty have been used by administrators in high stakes faculty employment decisions such as tenure, promotion, contract renewal and reappointment, and merit pay. However, virtually no attention has been paid to the ethical questions of using ratings in employment decisions. Instead, the ratings literature is generally limited to psychometric issues such as whether a given student ratings instrument exhibits the statistical properties of reliability and validity. There is no consensus understanding of teaching effectiveness, the (...) very attribute that students are alleged to “evaluate.” What students are actually doing when they complete a ratings form—whether measuring, evaluating, reporting, judging, opining, etc.—remains unsettled in the ratings literature. If ratings are surveys of student satisfaction, they have no logical or ethical connection with teaching expertise. I argue that the administrative use of student ratings in faculty employment decisions violates basic moral principles including nonmaleficence, beneficence, professional autonomy and clinical independence, and multiple aspects of justice including due care, truthfulness, and equitable treatment. These ethical violations rule against any administrative use of student ratings in faculty employment decisions, including the “use with caution in conjunction with other evaluative methods” deployment of student ratings. My conclusion is that such use should be immediately and universally terminated. Formative use of student questionnaires as part of ordinary instructional communication and feedback between instructor and students is a separate issue and outside of the scope of this paper. (shrink)

Abstract: Online book review platforms generate vast user data, making accurate rating prediction crucial for personalized recommendations. This research explores neural networks as simple models for predicting book ratings without complex algorithms. Our novel approach uses neural networks to predict ratings solely from user-book interactions, eliminating manual feature engineering. The model processes data, learns patterns, and predicts ratings. We discuss data preprocessing, neural network design, and training techniques. Real-world data experiments show the model's effectiveness, surpassing traditional methods. This research can (...) enhance user experience, book catalog organization, and aid publishers, simplifying recommendation processes and providing tailored suggestions based on user preferences. (shrink)

The inflation of Type I error rates is thought to be one of the causes of the replication crisis. Questionable research practices such as p-hacking are thought to inflate Type I error rates above their nominal level, leading to unexpectedly high levels of false positives in the literature and, consequently, unexpectedly low replication rates. In this article, I offer an alternative view. I argue that questionable and other research practices do not usually inflate relevant Type I error rates. I begin (...) by introducing the concept of Type I error rates and distinguishing between statistical errors and theoretical errors. I then illustrate my argument with respect to model misspecification, multiple testing, selective inference, forking paths, exploratory analyses, p-hacking, optional stopping, double dipping, and HARKing. In each case, I demonstrate that relevant Type I error rates are not usually inflated above their nominal level, and in the rare cases that they are, the inflation is easily identified and resolved. I conclude that the replication crisis may be explained, at least in part, by researchers’ misinterpretation of statistical errors and their underestimation of theoretical errors. (shrink)

Fixed-rate versions of rule-consequentialism and rule-utilitarianism evaluate rules in terms of the expected net value of one particular level of social acceptance, but one far enough below 100% social acceptance to make salient the complexities created by partial compliance. Variable-rate versions of rule-consequentialism and rule-utilitarianism instead evaluate rules in terms of their expected net value at all different levels of social acceptance. Brad Hooker has advocated a fixed-rate version. Michael Ridge has argued that the variable-rate version (...) is better. The debate continues here. Of particular interest is the difference between the implications of Hooker's and Ridge's rules about doing good for others. (shrink)

Molecular clocks based upon amino acid sequences in proteins have played a major role in the clarification of evolutionary phylogenies. Creationist criticisms of these methods sometimes rely upon data that might initially seem to be paradoxical. For example, human cytochrome c differs from that of an alligator by 13 amino acids but differs by 14 amino acids from a much more closely related primate, Otolemur garnettii. The apparent anomaly is resolved by taking into consideration the variable substitution rate of (...) cytochrome c, particularly among primates. This paper traces some of the history of extensive research into the topic of rate heterogeneity in cytochrome c including data from cytochrome c pseudogenes. (shrink)

In 2011, Hibbard suggested an intelligence measure for agents who compete in an adversarial sequence prediction game. We argue that Hibbard’s idea should actually be considered as two separate ideas: first, that the intelligence of such agents can be measured based on the growth rates of the runtimes of the competitors that they defeat; and second, one specific (somewhat arbitrary) method for measuring said growth rates. Whereas Hibbard’s intelligence measure is based on the latter growth-rate-measuring method, we survey other (...) methods for measuring function growth rates, and exhibit the resulting Hibbard-like intelligence measures and taxonomies. Of particular interest, we obtain intelligence taxonomies based on Big-O and Big-Theta notation systems, which taxonomies are novel in that they challenge conventional notions of what an intelligence measure should look like. We discuss how intelligence measurement of sequence predictors can indirectly serve as intelligence measurement for agents with Artificial General Intelligence (AGIs). (shrink)

It is not yet clear which response behavior requires self-regulatory effort in the moral dilemma task. Previous research has proposed that utilitarian responses require cognitive control, but subsequent studies have found inconsistencies with the empirical predictions of that hypothesis. In this paper we treat participants’ sensitivity to utilitarian gradients as a measure of performance. We confronted participants (N = 82) with a set of five dilemmas evoking a gradient of mean utilitarian responses in a 4-point scale and collected data on (...) heart rate variability and on utilitarian responses. We found positive correlations between tonic and phasic HRV and sensitivity to the utilitarian gradient in the high tonic group, but not in the low tonic group. Moreover, the low tonic group misplaced a scenario with a selfish incentive at the high end of the gradient. Results suggest that performance is represented by sensitivity correlated with HRV and accompanied with a reasonable placement of individual scenarios within the gradient. (shrink)

During multiple testing, researchers often adjust their alpha level to control the familywise error rate for a statistical inference about a joint union alternative hypothesis (e.g., “H1,1 or H1,2”). However, in some cases, they do not make this inference. Instead, they make separate inferences about each of the individual hypotheses that comprise the joint hypothesis (e.g., H1,1 and H1,2). For example, a researcher might use a Bonferroni correction to adjust their alpha level from the conventional level of 0.050 to (...) 0.025 when testing H1,1 and H1,2, find a significant result for H1,1 (p < 0.025) and not for H1,2 (p > .0.025), and so claim support for H1,1 and not for H1,2. However, these separate individual inferences do not require an alpha adjustment. Only a statistical inference about the union alternative hypothesis “H1,1 or H1,2” requires an alpha adjustment because it is based on “at least one” significant result among the two tests, and so it refers to the familywise error rate. Hence, an inconsistent correction occurs when a researcher corrects their alpha level during multiple testing but does not make an inference about a union alternative hypothesis. In the present article, I discuss this inconsistent correction problem, including its reduction in statistical power for tests of individual hypotheses and its potential causes vis-à-vis error rate confusions and the alpha adjustment ritual. I also provide three illustrations of inconsistent corrections from recent psychology studies. I conclude that inconsistent corrections represent a symptom of statisticism, and I call for a more nuanced inference-based approach to multiple testing corrections. (shrink)

Uncertainty plays an important role in The General Theory, particularly in the theory of interest rates. Keynes did not provide a theory of uncertainty, but he did make some enlightening remarks about the direction he thought such a theory should take. I argue that some modern innovations in the theory of probability allow us to build a theory which captures these Keynesian insights. If this is the right theory, however, uncertainty cannot carry its weight in Keynes’s arguments. This does not (...) mean that the conclusions of these arguments are necessarily mistaken; in their best formulation they may succeed with merely an appeal to risk. (shrink)

There is a theorem that shows that it is impossible for an algorithm to jointly satisfy the statistical fairness criteria of Calibration and Equalized Odds non-trivially. But what about the recently advocated alternative to Calibration, Base Rate Tracking? Here we show that Base Rate Tracking is strictly weaker than Calibration, and then take up the question of whether it is possible to jointly satisfy Base Rate Tracking and Equalized Odds in non-trivial scenarios. We show that it is (...) not, thereby establishing an even more general impossibility theorem. (shrink)

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

According to the No Alternate Possibilities argument, if time passes then the rate at which it passes could be different but time cannot pass at different rates, and hence time cannot pass. Typically, defenders of the NAP argument have focussed on defending premise, and have taken the truth of for granted: they accept the orthodox view of rate necessitarianism. In this paper we argue that the defender of the NAP argument needs to turn her attention to. We describe (...) a series of worlds that appear to contain differential passage: worlds where time passes at different rates in different subregions. If the NAP argument is to succeed, rate necessitarians must show that each of these worlds is either metaphysically impossible, or does not contain differential passage. (shrink)

The meaning of an experimental result depends on the experiment's conceptual backdrop, particularly its null hypothesis. This observation provides the basis for a functional interpretation of belief in the base rate fallacy. On this interpretation, if the base rate fallacy is to be labelled a “myth,” then it should be recognized that this label is not necessarily a disparaging one.

Wildfires have become an increasing global threat to public health and quality of life. Many countries employ air quality monitoring and reporting systems to mitigate health risks associated with air pollution, including wildfire smoke. This study investigates the factors influencing individuals’ sensitivity to air quality information, specifically their likelihood of reducing or ceasing outdoor activities in response to air quality ratings, with a focus on wildfire smoke exposure in the western United States. Using the Bayesian Mindsponge Framework (BMF) analytics, the (...) study analyzed data from 2,237 participants in the Boise Metropolitan Area of Idaho and Boise State University. The findings reveal that women, older individuals, and those with higher educational levels are more likely to reduce outdoor activities at lower unhealthy AQI levels (the lowest being ‘good air quality,’ while the highest being ‘hazardous air quality’), while individuals with higher incomes are less responsive. Women and older adults, in particular, are even more likely to eliminate all outdoor activities. Additionally, individuals who perceive wildfire smoke as more severe than other natural disasters are more inclined to reduce or eliminate outdoor activities at lower unhealthy air quality levels. Experiences of wildfire smoke-related illness—either personally or within their households—further amplify this effect. These findings highlight the importance of localized, context-specific approaches to AQI dissemination and wildfire smoke risk communication to build resilience and safeguard public health in the face of escalating wildfire challenges driven by climate change. (shrink)

In this research, we develop a machine learning model to predict the ratings of Google Play Store applications using a comprehensive dataset. Our approach includes extensive data preprocessing, feature engineering, and model optimization using Random Forest Regressor and ensemble methods. The proposed model demonstrates significant improvements in prediction accuracy, emphasizing the importance of advanced preprocessing techniques and ensemble learning in regression tasks.

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

Purpose of Review Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is identified from Wuhan, China, and has spread almost worldwide. Recently, the newly identified SARS-CoV-2 has been confirmed to kill millions of people worldwide and is dangerous to society health, survival, and livelihood. The people with cardiovascular problems are noticed as most common patients of coronavirus disease 2019 (COVID-19). There is a greater risk of mortality and morbidity in these patients than other patients of COVID-19. In the heart, expressed angiotensin-converting enzyme (...) 2 (ACE2) and response effect of hyperactivity with angiotensin II associated to the renin-angiotensin mechanism are key factors of hypertension, atherosclerosis, and congestive heart failure. -/- Recent Findings Mortality rates have been observed about 10.5% cases in patients with cardiovascular disease; however, a mortality rate of 52% was recorded in patients with heart failure, while 12% recovered ultimately. The occupancy of intense injury controlled by troponin elevation was a noteworthy factor in relation to mortality. Among 187 patients infected with SARS-CoV-2, about 35% were diagnosed with cardiovascular disease (CVD) history and 28% with raised troponin. Troponin elevation was identified more frequently (55%) in patients with cardiovascular diseases. Mortality rate in patients without cardiovascular diseases and normal troponin was 7.6%, normal troponin and cardiovascular disease with 13.3%, augmented troponin and without cardiovascular disease 37.5%, however 69.4% among cardiovascular disease and advanced troponin. -/- Summary The study reflected a significant association of case fatality rate (CFR) to COVID-19 patients with cardiovascular diseases which supposed to be the most common dangerous risk factor and health challenge during the current pandemic situation. (shrink)

In 1937 Joan Robinson proposed that “when capitalism is rightly understood, the rate of interest will be set at zero and the major evils of capitalism will disappear”. A permanent zero rate would abolish capitalist profit except in limited cases, leaving nearly all output to be claimed by labour as wages. It would allow capital to be allocated on the basis of prospective social benefit rather than short-term profitability and a collateral basis that favours the wealthy. It would (...) remove some of the economic pressure to use resources unsustainably. So why not do this? I argue that the few available philosophical arguments for positive interest rates are unsatisfactory. Those who want a just and sustainable form of capitalism should target net zero for the interest rate. (shrink)

Tripura was a princely state and ruled by the rulers of Manikya dynasty for a long period. She merged with the Indian Union on 15th Oct 1949. The rulers of Tripura wanted to modernise their state and educational modernisation was only a part of it. However, that process of modernisation was started only from the last quarter of 19th century. Many schools, both primary and secondary were established during that short span of time. Nevertheless, due to its primitive and patriarchal (...) character the ratio between the male and female literacy growth rate was not uniform. In this article the researcher tried to find out the female literacy growth rate in Tripura before her amalgamation and historically analyse the real cause behind the negligence of women education in the Princely state Tripura on the basis of various statistical records. (shrink)

This chapter argues for deregulation of the credit-rating market. Credit-rating agencies are supposed to contribute to the informational needs of investors trading bonds. They provide ratings of debt issued by corporations and governments, as well as of structured debt instruments (e.g. mortgage-backed securities). As many academics, regulators, and commentators have pointed out, the ratings of structured instruments turned out to be highly inaccurate, and, as a result, they have argued for tighter regulation of the industry. This chapter shows, however, that (...) the role of credit-rating agencies in achieving justice in finance is not as great as these commentators believe. It therefore argues instead for deregulation. Since the 1930s, lawgivers have unjustifiably elevated the rating agencies into official, legally binding sources of information concerning credit risk, thereby unjustifiably causing many institutional investors to outsource their epistemic responsibilities, that is, their responsibility to investigate credit risk themselves. (shrink)

This article proposes a term structure model for dual-currency interest rate markets. The model assumes that volatility is a deterministic function of time alone. This volatility structure can reduce the dimension of the required state variables. An important special case is presented, which corresponds essentially to a Vasicek/Hull-White yield curve model in each currency. The model is very useful for pricing cross-currency derivatives.

According to the No Alternate Possibilities argument, if time passes then the rate at which it passes could be different. Thus, time cannot pass, since if time passes, then necessarily it passes at a rate of 1 second per second. One response to this argument is to posit hypertime, and to argue that at different worlds, time passes at different rates when measured against hypertime. Since many A-theorists think we can make sense of temporal passage without positing hypertime, (...) we pursue a different response. We describe several worlds that do not contain hypertime, but do contain differential passage: worlds where time passes at different rates in different subregions within the same world. Hence we argue that even if we focus just on the set of worlds that do not contain hypertime (whether this is all, or only some of the worlds) we find that not all these worlds are such that time passes at a rate of 1 second per second. Thus the No Alternate Possibilities argument fails even when restricted to just this set of worlds. (shrink)

The no-miracles argument and the pessimistic induction are arguably the main considerations for and against scientific realism. Recently these arguments have been accused of embodying a familiar, seductive fallacy. In each case, we are tricked by a base rate fallacy, one much-discussed in the psychological literature. In this paper we consider this accusation and use it as an explanation for why the two most prominent `wholesale' arguments in the literature seem irresolvable. Framed probabilistically, we can see very clearly why (...) realists and anti-realists have been talking past one another. We then formulate a dilemma for advocates of either argument, answer potential objections to our criticism, discuss what remains (if anything) of these two major arguments, and then speculate about a future philosophy of science freed from these two arguments. In so doing, we connect the point about base rates to the wholesale/retail distinction; we believe it hints at an answer of how to distinguish profitable from unprofitable realism debates. In short, we offer a probabilistic analysis of the feeling of ennui afflicting contemporary philosophy of science. (shrink)

Customer ratings and reviews are playing a key role in the contemporary platform economy. To establish trust among stran- gers without having to directly monitor platform users themselves, companies ask people to evaluate each other. Firms like Uber, Deliveroo, or Airbnb construct digital reputation scores by combining these consumer data with their own information from the algorithmic surveillance of workers. Trustworthy behavior is subsequently rewarded with a good reputation score and higher potential earnings, while untrustworthy behavior can be algorithmically penalized. (...) However, can these technolo- gies themselves be trusted? Are they reliable communicators of trustworthy market behavior and do they fairly distribute the benefits and burdens of the online economy among platform companies, consumers, and workers? The implementation of Digital Reputation Systems (DRSs) has obvious advantages, like reducing adjudication costs and enhancing consumer trust, but there are also disadvantages that are predominantly offloaded on workers. Taking Airbnb’s DRS as my case study, I use Stephan Lessenich’s theory of the externalization society to argue that DRSs concentrate the benefits of the platform economy among consumers and platform companies while pushing negative externalities mostly unto workers. (shrink)

According to Critical-Level Views in population axiology, an extra life improves a population only if that life’s welfare exceeds some fixed ‘critical level.’ An extra life at the critical level leaves the new population equally good as the original. According to Critical-Range Views, an extra life improves a population only if that life’s welfare exceeds some fixed ‘critical range.’ An extra life within the critical range leaves the new population incommensurable with the original. -/- In this paper, I sharpen some (...) old objections to these views and offer some new ones. Critical-Level Views cannot avoid certain Repugnant and Sadistic Conclusions. Critical-Range Views imply that lives featuring no good or bad components whatsoever can nevertheless swallow up and neutralise goodness or badness. Both classes of view entail that certain small changes in welfare correspond to worryingly large differences in contributive value. -/- I then offer a view that retains much of the appeal of Critical-Level and Critical-Range Views while avoiding the above pitfalls. On the Imprecise Exchange Rates View, the quantity of some good required to outweigh a given unit of some bad is imprecise. This imprecision is the source of incommensurability between lives and populations. (shrink)

Crime Forecasting refers to the basic process of predicting crimes before they occur. Crimes are a common social problem affecting the quality of life and the economic growth of a society. A crime is a deliberate act that can cause physical or psychological harm, as well as property damage or loss, and can lead to punishment by a state or other authority according to the severity of the crime. For our daily purposes we have to go many places every day (...) and many times in our daily lives we face numerous security issues such as hijacking, kidnapping, harassment, etc. Daily there are huge numbers of crimes occurring frequently. These require keeping track of all the crimes and maintaining a database for same which may be used for future reference. (shrink)

Every higher education institution (HEI) needs to monitor the employability status of its graduates as this reflects the quality education that HEIs provide to their students. In this study, a retrospective approach was used to analyze the employment status of graduates of a state university in the Philippines from 2015 to 2019. A data mining procedure was adopted to obtain necessary data and analysis. It was hypothesized in the study that the employment rates are the same across programs per year. (...) Also, the employment rates from 2015 to 2019 are the same as the targeted employment rate in the strategic plan of the university. Statistical treatments such as mean, median, and standard deviation, Shapiro-Wilk test, and Analysis of Variance (ANOVA) were used to test the hypothesis. Results show that the employment rate of graduates of 2015-2019 is in the high-level category and significantly higher than the targeted employment rate in the university strategic plan. Similarly, findings show significant differences in the employability rates of graduates considering the programs they enrolled in. On the contrary, no significant difference in the employment rate of graduates per year graduated. The study concluded that the university is consistent in producing employable graduates. (shrink)

Several researchers have recently argued that p values lose their meaning in exploratory analyses due to an unknown inflation of the alpha level (e.g., Nosek & Lakens, 2014; Wagenmakers, 2016). For this argument to be tenable, the familywise error rate must be defined in relation to the number of hypotheses that are tested in the same study or article. Under this conceptualization, the familywise error rate is usually unknowable in exploratory analyses because it is usually unclear how many (...) hypotheses have been tested on a spontaneous basis and then omitted from the final research report. In the present article, I argue that it is inappropriate to conceptualize the familywise error rate in relation to the number of hypotheses that are tested. Instead, it is more appropriate to conceptualize familywise error in relation to the number of different tests that are conducted on the same null hypothesis in the same study. Under this conceptualization, alpha level adjustments in exploratory analyses are (a) less necessary and (b) objectively verifiable. As a result, p values do not lose their meaning in exploratory analyses. (shrink)

Exchange rate movement is a mostly debatable issue amongst economists and strategic financial planners in the economies as a vital phenomenon, of every economy in the developing the world. This study sets out to examine the impact of cash conversion cycle, Size, Age, and exchange rate movement on firms’ financial decisions. The estimation used techniques of static panel data analysis in this study; pooled OLS, random effects, and fixed effects. Interaction techniques are applied to check the impact of (...) the exchange rate by multiplying this variable with the main variables of cash conversion cycle, that is receivable in days and payables in days. The results depict there is a significant negative relationship between return on assets and exchanger rate during the period of review while the beta of cash conversion cycle has negative value; age and size are positive and significant at 1% level with return on assets. Therefore, it is recommended that organizations that have some measure to agreement in foreign currencies can adopt some advanced hedging technique to occupy the exchange rate movements risk to improve firm’s performance. (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)

Doctoral graduates in philosophy are an excellent source of information about the discipline: they are at the cutting edge of research trends, have an inside view of researchfocused departments, and their employment prospects provide early insights on the future health of the discipline. We report on the results of a survey sent to recent PhD graduates and current students, as well as data gathering efforts by Academic Placement Data and Analysis that have taken place over the past ten years. In (...) this report we especially focus on demographic representation, program ratings, academic job placement, and non-academic careers. (shrink)

This paper presents an analytical model for valuing interest rate swaps, subject to bilateral counterparty credit risk. The counterparty defaults are modeled by the reduced-form model as the first jump of a time-inhomogeneous Poisson process. All quantities modeled are market-observable. The closed-form solution gives us a better understanding of the impact of the credit asymmetry on swap value, credit value adjustment, swap rate and swap spread.

The current study is conducted to examine the following research question: 1) Who were the people who had no access to wildfire smoke notifications during the smoke event in the summer of 2018 in the Boise Metropolitan Area in Idaho? 2) Who were the people who were not familiar with the air quality rating system?

Credit scoring is vital for assessing borrowers' creditworthiness and managing risks in financial systems. Traditional credit scoring models often fail to capture non-linear relationships and handle high-dimensional data, leading to less accurate predictions. This research explores the application of advanced data mining algorithms, such as ensemble learning methods, neural networks, and hybrid models, for predicting default rates. Empirical findings reveal significant improvements in predictive accuracy and interpretability. Key takeaways emphasize the importance of effective preprocessing and feature engineering techniques in creating (...) scalable and efficient credit scoring models. (shrink)

Credit scoring is vital for assessing borrowers' creditworthiness and managing risks in financial systems. Traditional credit scoring models often fail to capture non-linear relationships and handle high-dimensional data, leading to less accurate predictions. This research explores the application of advanced data mining algorithms, such as ensemble learning methods, neural networks, and hybrid models, for predicting default rates. Empirical findings reveal significant improvements in predictive accuracy and interpretability. Key takeaways emphasize the importance of effective preprocessing and feature engineering techniques in creating (...) scalable and efficient credit scoring models. (shrink)

Introduction: Universal health coverage (UHC) was introduced in Iran in 2014. The aim of this study was to evaluate the usage rate of health services by human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) patients after UHC implementation. Material and methods: In 2018, in a cross-sectional study, we evaluated the outpatients’ needs (within its previous month) and inpatients’ needs (within its previous 6 months) of HIV/AIDS patients in Isfahan province (the center of Iran). Concurrently, we estimated the essential health care (...) services that HIV/AIDS patients have to receive regularly, including vaccination for hepatitis B, measurement of CD4, tuberculosis (TB) assessments and TB treatment, anti-retroviral therapy, examination of viral load, treatment approach, and drug side effects counseling. Two checklists were used for assessing the utilization of health services and essential health cares for HIV/AIDS patients, validated by the Ministry of Health and Medical Education of Iran. Data were analyzed by χ2 test, Pearson’s correlation coefficient, and Spearman’s correlation test. Results: Two hundred and thirteen HIV/AIDS patients completed the questionnaires. The mean age of participants was 41.14 ± 9.23. The outpatient service utilization rate was 31.94% in the previous month and the rate of hospitalization was 126 per 1,000 HIV/AIDS patients in the previous 6 months. The majority of HIV/AIDS patients received essential health services more often than the national standard goals estimation. Conclusions: After UHC implementation, the utilization rate of outpatients and inpatients services in HIV/AIDS patients was more than similar indices in the general population. In addition, HIV/AIDS patients received essential health services adequately. (shrink)

In 2012, a major traffic safety organization tasked the MIT AgeLab with developing a data-driven system for rating the effectiveness of new technologies intended to improve safety. Such a system was envisioned as having the potential to educate and guide consumers towards more confident and strategic purchasing decisions, ideally encouraging adoption of technologies with demonstrated safety benefit. In addition, an evaluation of the status and extent of existing data was seen as a way of identifying research gaps in the state (...) of knowledge about safety systems. The focus was on technologies as a class, not on a rating review of individual vehicle model implementations. As conceptualized, the system aimed to complement traditional NCAP style ratings as well as to provide consumers with transparent information on early stage and often improving safety technologies. Development of the rating system and identification of data was undertaken in consultation with a range of academic, industrial, consumer, NGO, and governmental experts as well as with representatives of many of the major automotive manufacturers and suppliers. -/- A key observation that emerged was that data on objectively demonstrable real-world benefits were generally sparse and often lower than expectations based on theoretical considerations, simulation studies, or pre-production evaluations. A number of experts and industry representatives expressed some surprise at both the divergence between theoretical and observed benefits and the relative scarcity of data upon which to make objective assessments, while others were quite aware of these issues and the need for the development of objective data under real-world operating conditions. A number of factors that might be relevant to understanding why such differences between expected and observed benefits exist were identified. One outcome of this effort was the founding of the Advanced Vehicle Technology (AVT) consortium to collect and examine objective data under naturalistic driving conditions of how drivers interact with, engage or don’t engage, various production safety and driver assistance systems. This ongoing effort is contributing to insights concerning actual benefits and reasons for benefit gaps. -/- Drawing from our initial work, as well as newer sources of data, we argue that the evaluation and rating of safety and driver assistance technologies for informing the consumer and the public at large should consider both theoretical potential and existing demonstrated benefit of specific technologies. This position is increasingly relevant as the effectiveness of many newer technologies have the potential to actually improve over the lifecycle of a vehicle through software updates. The emphasis on ratings based on observed benefit for actual drivers under real-world conditions is proposed to be complementary, rather than competing with, ratings focused largely on controlled test track evaluations of engineered capability. In addition, a case is made for providing ratings that assesses benefit relative to overall crash, injury, and fatality rates – and in relation to the specific scenario / crash event type that a given technology is intended to address. This approach should aid consumers in considering the extent to which a specific technology is or is not relevant to their particular driving needs. (shrink)

Metformin is considered the first-line treatment as a monotherapy for patients with type 2 diabetes mellitus. Emerging evidence suggests that metformin may have a renoprotective role; therefore, understanding the impact of metformin dose and therapy duration on renal function may significantly improve renal outcomes in type 2 diabetes patients. This study aims to investigate the renoprotective effects of metformin by analyzing its dose-dependent impacts on the estimated glomerular filtration rate in patients with type 2 diabetes mellitus. A retrospective cross-sectional (...) study design was used from September 2022 to October 2023. Data from 302 type 2 diabetes patients were collected from patient files at the Benghazi Diabetic Center and the Aljabal Al-Alkdar Diabetic Center, including all with type 2 diabetes mellitus patients on varying doses of metformin. The collected data included age, gender, metformin dose, duration of metformin therapy, urea, and creatinine. Exclusion criteria included patients with significant comorbidities such as chronic kidney disease (other than diabetic nephropathy), liver disease, heart failure, or malignancy; those taking nephrotoxic medications; individuals with recent acute illnesses or surgical procedures; pregnant or lactating women; participants with inadequate medical records; and patients who were non-adherent to metformin therapy. Survival analysis was conducted to evaluate the effect of different metformin doses on the estimated glomerular filtration rate. The study analyzed 302 diabetic patients, of whom 46.0% were male and 54.0% were female. The age was 58.3±11.9 years. The HbA1c was 7.7%±1.3%. The duration of diabetes was 11.4±8.1 years. The creatinine was 1.0±0.9 mg/dL, and the urea was 36.7±23.8 mg/dL. Data analysis revealed a statistically significant difference in survival distribution across the dose groups. Different metformin doses significantly impact the estimated glomerular filtration rate, suggesting that dosage plays a crucial role in maintaining renal function. (shrink)

Status of the national currency of Ukraine exchange rate has been characterized as unstable in recent years. Herewith, the Government has not implemented decisive measures on its stabilization, as a rule, underestimating the importance of the Hryvnia exchange rate stability for the successful economic growth in terms of socio-economic transformations. It should also be noted that in modern conditions among scientific and methodical approaches to the State exchange rate formation mechanisms some uncertainty regarding basic and additional tools (...) for such regulatory activities allocation is still persist. The problem relevance is exacerbated by the lack of effective policy (coordination between the NBU and the Government actions) regarding the national currency stabilization as an indispensable prerequisite for an effective macroeconomic development. These circumstances determine the importance of factors influencing the national currency exchange rate and its regulation tools research, as well as new organizational and economic mechanisms for the national currency exchange rate in Ukraine stabilization identification. In the emerging market economy conditions formation of the efficient State currency exchange-rate regulation system provides an opportunity not only to stabilize its exchange rate in different socio-economic conditions, but to create the basis for improvement the country economic development as a whole. Given this, the issue of effective tools for the national currency exchange-rate regulation by the state determination is of theoretical, practical and methodological significance. This emphasizes the relevance of further scientific-methodological and practical principles in-depth development for the national currency exchange-rate regulation. (shrink)

In the given article the problems of choice as for the types and forms of debt and share financing on the developing and “frontier markets” with high interest rates have been considered, the definition of what kind of interest rates can be viewed as high and under which circumstances nominal interest rate and in which ones – the real interest rate is important for business. Also, the classification of debt and sharing financing is given and the comparative analysis (...) of such financing is made. Some close attention has been paid to the calculation of the real interest rate according to the inflation forecast. Recommendations concerning attracting of relatively cheap trade financing including international financial and credit organizations, development of operation factoring, financing from captive financial institutions of the exporters of the materials and equipment from the EU and the US have been grounded. The opportunity of relatively free of charge share financing through the mechanism of placing shares IPO/SPO is emphasized, exemplified by the results of placing shares on stock exchanges and their alternative platforms of issuing banks with businesses in Ukraine in 2005 – 2013. As a result, the conclusion concerning the necessity of thorough analysis of financial conditions on the developing and frontier markets before gaining such financing has been made. High interest rates within the average indicators even on the basis of prime rates do not necessarily mean absence of attractive conditions of financing. (shrink)

The aim of this article is to address the issue of measuring radio audience from a methodological perspective. Although our approach is contextualized, the case study of radio audience measurement in Romania is relevant to a large number of EU countries, in which scholars and practitioners use Day-After-Recall technique. Considering the size of the radio advertising market, as well as the number of radio listeners (about 90% in EU), it is crucial for both radio broadcasters and advertisers to measure radio (...) audience with high accuracy. First, we briefly review the main definitions of key concepts used in radio audience evaluation: audience, listener, rating, market share, daily-reach, or time spent listening. Next, we discuss two paradigms of audience and two theoretical models of mass communication used as a framework for measuring radio audience. Further, we briefly approach the issue of potential sources of error in rating data, by focusing on response error. Next, we emphasize the advantages and disadvantages of each quantitative method utilized in radio audience measurement, and present the case study of radio audience measurement in Romania. Based on a methodological critical review, we outline challenges and potential solutions for assessing more accurately radio audience. Finally, we reflect on the future of radio in digital era, and refer to new perspectives of upgrading existing research techniques. (shrink)

The market for environmental, social and governance (ESG) rating and data is expected to grow immensely in the next decades. This brief zooms in both on the integration of ESG risks into “traditional” operations of Credit Rating Agencies (CRAs) as well as on the emergence of a market exclusively dedicated to ESG rating. As will become clear, the market for ESG ratings suffers from serious shortcomings, a lack of transparency and standardisation, significant biases and conflicts of interests, and a dependence (...) on large, oligopolistic, credit rating agencies. (shrink)

On Einstein's Train and the Big Bang in Fragmental Presentism, Temporal Flow Rates, Existence, Free Will, Qualia, Hard Problems, etc.

This paper presents a comprehensive analysis of the SEIRS COVID-19 pandemic model with saturated incidence rate. By modifying the existing model and proposing a new simplified version, we investigate the dynamics of disease transmission, including the impact of saturation terms on disease spread. Through stability analysis at disease-free and endemic equilibria, we aim to enhance understanding of the spread of COVID-19 and inform effective control strategies. Drawing on mathematical models and epidemiological insights, this study contributes to the ongoing efforts (...) to combat the global pandemic. (shrink)

Objectives To increase postmortem organ donation rates, several countries are adopting an opt-out (presumed consent) policy, meaning that individuals are deemed donors unless they expressly refused so. Although opt-out countries tend to have higher donation rates, there is no conclusive evidence that this is caused by the policy itself. The main objective of this study is to better assess the direct impact of consent policy defaults per se on deceased organ recovery rates when considering the role of the family in (...) the decision-making process. This study does not take into account any indirect effects of defaults, such as potential psychological and behavioural effects on individuals and their relatives. -/- Design Based on previous work regarding consent policies, we created a conceptual model of the decision-making process for deceased organ recovery that included any scenario that could be directly influenced by opt-in or opt-out policies. We then applied this model to internationally published data of the consent process to determine how frequently policy defaults could apply. -/- Main outcome measures We measure the direct impact that opt-in and opt-out policies have per se on deceased organ recovery. -/- Results Our analysis shows that opt-in and opt-out have strictly identical outcomes in eight out of nine situations. They only differ when neither the deceased nor the family have expressed a preference and defaults therefore apply. The direct impact of consent policy defaults is typically circumscribed to a range of 0%–5% of all opportunities for organ recovery. Our study also shows that the intervention of the family improves organ retrieval under opt-in but hinders it under opt-out. -/- Conclusions This study may warn policy makers that, by emphasising the need to introduce presumed consent to increase organ recovery rates, they might be overestimating the influence of the default and underestimating the power granted to families. (shrink)

Throughout history, education has always been essential for humanity's justice and fundamental for the creation of a free and satisfying society with the dissemination of knowledge. Hence, in addition to the life occurrences educating people, traditional higher education methods have played an important role for a long period. However, the age of technology has changed the educational system along with the people's lifestyles to meet the continuously changing conditions. During the past twenty years, the Information and Communication Technologies (ICTs) led (...) to the emergence of e-learning non-traditional educational methods bringing about an innovative dimension of virtual learning. With its beneficial features provided by the Internet and various technologies, this method passes the control of time and location from the tutors to the students during the learning process. Despite the entrance of online education into the students' life many years ago, the Covid-19 outbreak initiated in 2020 turned this method into the only possible way of education for almost two years. Afterward, plenty of studies investigated its effects on students' social and academic life, mostly considering its negative impacts on their mental health and motivation due to interaction issues. They also pointed out the specific problems of tactile learner students in the lack of face-to-face design courses. As an innovative solution able to be adopted, game technologies, increasing immersion of the learner in a real-world skill, and triggering motivation are one of the best methods integrated into educational systems. Known as serious games, these games, adopted by almost any domain, convey educational content along with entertainment, increasing interaction. They train or enhance a certain skill or topic to the player by immersing them. While serious games are more expanded nowadays, they are still not being played by the mass public due to people's immersiveness expectations of a game. Hence, the Head-Mounted Displays (HMDs), with their emergence, increased the players' engagement and immersion with all types of virtual environments in digital games. This technology, however, evolved serious games area most, among others, by enabling the opportunity to provide a riskless and low-cost learning environment for real-world skills. In the process of suggesting serious games as a replacement for the traditional educational methods, the most important factor is being aware of their effectiveness for education. Generally, digital games, one of the world's biggest and fastest-growing industries, rely heavily on the virtual landscape, a major part of its development process. Its design demands remarkable effort, and it directly affects the whole game's characteristics. Hence, serious games, as a type of digital game, carry the same attributes. With the appearance of virtual reality technology, gaming started to gain more immersiveness and engagement with artificial elements and environments. Although virtual landscapes were always being developed since the emergence of digital games, the studies taking virtual landscapes into account are mostly using them as a tool for enhancing real spaces, not as a domain for the sake of its development. While other design domains are applying various design methodologies, it is challenging to find a standard design methodology for the design and production of virtual landscapes in the gaming industry, leading to inconsistent and low-quality results. Hence, it comes to the question of what is the virtual landscapes' role in serious games and their effect on the data comprehension rate. Since the literature lacks regarding the gradual change of the virtual landscape in serious games and the content they transmit, this thesis aims to figure out the gradual chronological evolution of the virtual landscapes in serious games. It also aims to seek how this change and the virtual reality technology invention have affected the contents transmitted by digital games and its influence on the player interaction and learning rate. To do so, in the process of this thesis, we developed, tested, and evaluated various serious games, both text-based and with 360° photos. The steps taken revealed the reluctance of the players to follow the providing educational content and their inadequacy of interaction. Hence, the thesis seeks the reasons ending to this result and the ways of increasing this learning rate. Afterward, the thesis uses a currently available but not massively used digital game classification methodology. This methodology, which is based on the principles of architecture, landscape architecture, and urban planning, classifies the games based on their constituting virtual landscapes. Hence, the thesis considers all Steam games, one of the biggest video game digital distribution services, filtered with the 'education' tag, ending in 2531 digital games. Afterward, adding the 'game' tag the result reduced to 1102 games. Finally, with some manual filterings ignoring the irrelevant content, the final number decreased to 702. Sorting chronologically, we made an Excel database including the games' introductory information, the content they transmit, their release date, if they support HMD or not, and whether they are simulation games or not. Due to Steam's dating spectrum, our database includes games dating back from 1992 to 2020. Afterward, we classified all of these games using the virtual landscape classification methodology and generated their related codes based on their player scale, story, dimension, space shape, and interaction level. Investigating the results, they revealed some growth patterns relating to the content educated in the game, the VR technology, and the virtual landscape evolution. Adding the user reviews of Steam, we reverse engineered five of the best serious games on the database due to the digital game design methodology. This methodology divides the games' virtual environment into five layers, namely, player activity map (PAM), story layer, natural environment layer, virtual environment layer, and media layer. Reverse engineering the five best digital games ever, based on the IGN database, enabled us to compare the outcomes. Due to released data, we understand how the games' assets are distributed within the various layers of the virtual environment in the most successful games. Finally, the thesis aims to provide a framework based on these results for developing serious games to increase player interaction and enhance the learning rate. However, these results can be expanded to any virtual landscape other than only serious games' for their interaction enhancement. Currently, the landscape architecture domain only adopts the virtual landscape area as a tool for enhancing design in the real world. However, in the near future, landscape architects will perform in the virtual landscape area as a domain to be enhanced. Hence, that day, the results of this study will play an important role and will be a roadmap for generating highly interactive virtual landscapes. (shrink)