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Gold prices have been of major interest for a lot of investors, analysts, and economists. Accordingly, a number of different modeling approaches have been used to forecast gold prices. In this manuscript, the geometric Brownian motion approach, used in the pricing of numerous types of assets, is used to forecast the prices of gold at yearly, monthly, and quarterly frequencies. This approach allows for simulating one-period-ahead prices and the associated probabilities. The expected prices obtained from the simulated prices and probabilities are found to provide reliable forecasts when compared with the observed yearly, monthly, and quarterly prices. [ABSTRACT FROM AUTHOR]

The International Society for Animal Genetics (ISAG) currently advocates for a transition towards single nucleotide polymorphism (SNP) markers as a potential alternative for equine parentage verification. To ascertain the efficacy of this transition, it is imperative to evaluate the performance of parentage testing using SNPs in juxtaposition with short tandem repeats (STRs). As per ISAG's recommendation, we used an equine genotyping‐by‐sequencing panel with 144 SNPs for this purpose. Equine parentage is currently realized using 16 microsatellites (STRs) excluding the LEX3 marker. In this study, 1074 horses were genotyped using the 144 SNPs panel, including 432 foals, 414 mares, and 228 stallions, from five different breeds: 293 Arabians, 167 Barbs, 189 Thoroughbreds, 73 Anglo‐Arabians, and 352 Arabian‐Barbs. As a result, two SNPs markers were eliminated from the panel system due to inconsistent amplification across all examined individuals leaving 142 SNPs markers for analysis. A comparative analysis between SNPs and STRs markers revealed that the mean expected heterozygosity was 0.457 for SNPs and 0.76 for STRs, while the mean observed heterozygosity stood at 0.472 for SNPs and 0.72 for STRs. Furthermore, the probability of identity was calculated to be 5.722 × 10−57 for SNPs and 1.25 × 10−15 for STRs markers. In alignment with the Hardy–Weinberg equilibrium in polyploids test, 110 out of the total SNPs were consistent with the Hardy–Weinberg equilibrium in polyploids test (p > 0.05). Employing both SNPs and STRs markers, the mean polymorphic information content was discerned to be 0.351 for SNPs and 0.72 for STRs. The cumulative exclusion probabilities for SNP markers exceeded 99.99%, indicating that the 142 SNPs panel might be adequate for parentage testing. In contrast, when utilizing STRs markers, the combined average exclusion probabilities for one and both parents were determined to be 99.8% and 99.9%, respectively. Our comprehensive study underscores the potential of SNPs in equine parentage verification, especially when compared to STRs in terms of exclusion probabilities. As a corollary, the application of SNPs for parentage verification and identification can significantly contribute to the conservation initiative for the five Moroccan horse breeds. Nonetheless, further research is required to address and replace the deficient SNPs within the panel. [ABSTRACT FROM AUTHOR]

Denić (2018, 2019, To appear) observes that the availability of distributive inferences—for sentences with disjunction embedded in the scope of a universal quantifier—depends on the size of the domain quantified over as it relates to the number of disjuncts. Based on her observations, she argues that probabilistic considerations play a role in the computation of implicatures. In this paper we explore a different possibility. We argue for a modification of Denić's generalization, and provide an explanation that is based on intricate logical computations but is blind to probabilities. The explanation is based on the observation that when the domain size is no larger than the number of disjuncts, universal and existential alternatives are equivalent if distributive inferences are obtained. We argue that under such conditions a general ban on 'fatal competition' (Magri 2009a,b, Spector 2014) is activated, thereby predicting distributive inferences to be unavailable. [ABSTRACT FROM AUTHOR]

In this perspective review, we assess fundamental flaws in Darwinian evolution, including its modern versions. Fixed mutations 'explain' microevolution but not macroevolution including speciation events and the origination of all the major body plans of the Cambrian explosion. Complex, multifactorial change is required for speciation events and inevitably requires self-organization beyond what is accomplished by known mechanisms. The assembly of ribosomes and ATP synthase are specific examples. We propose their origin is a model for what is unexplained in biological evolution. Probability of evolution is modeled in Section 9 and values are absurdly improbable. Speciation and higher taxonomic changes become exponentially less probable as the number of required, genetically-based events increase. Also, the power required of the proposed selection mechanism (survival of the fittest) is nil for any biological advance requiring multiple changes, because they regularly occur in multiple generations (different genomes) and would not be selectively conserved by the concept survival of the fittest (a concept ultimately centered on the individual). Thus, survival of the fittest cannot 'explain' the origin of the millions of current and extinct species. We also focus on the inadequacies of laboratory chemistry to explain the complex, required biological self-organization seen in cells. We propose that a 'bioelectromagnetic' field/principle emerges in living cells. Synthesis by self-organization of massive molecular complexes involves biochemical responses to this emergent field/principle. There are ramifications for philosophy, science, and religion. Physics and mathematics must be more strongly integrated with biology and integration should receive dedicated funding with special emphasis for medical applications; treatment of cancer and genetic diseases are examples. [ABSTRACT FROM AUTHOR]

Mathematical education in Greece is constantly evolving in the pursuit of optimal learning outcomes for students despite their cognitive differences. This study seeks to gain insight into the use of new technologies in teaching probability theory and the gender differences in the comprehension of probability theory. To this end, a survey was conducted involving 500 students of the Department of Statistics and Insurance Science at the University of Piraeus. The respective questionnaire involves questions of self-reported results and employs the Likert scale to obtain the students' perceptions. Our data demonstrate no difference among the genders regarding the use of new technologies or their performance (i.e., the test scores) in the relevant courses. [ABSTRACT FROM AUTHOR]

The study uses numerical weather prediction models to predict the occurrence of heavy convective rainfall associated with the passage of the African Easterly Wave (AEW) during the period 23–26 August 2017 over Nigeria. Fraction skill score (FSS) and method for object‐based diagnostic evaluation (MODE) verification techniques were applied to verify how well the models predict the high‐impact event and to demonstrate how these tools can support operational forecasting. Ensemble model forecasts at a convective scale from UK Met Office Unified Model (MetUM) and a one‐way nested weather research and forecasting (WRF) model were compared with the integrated multisatellite retrievals for global precipitation measurement (IMERG GPM). The purpose is to examine skills of improved model resolution and ensemble in reproducing rainfall forecasts on useful scales and how the skill varies with spatial scale. WRF 2 and 6 km model forecasts show comparable skill at smaller grid scales. The skill of MetUM improves dramatically when the verification statistics are applied to the ensemble mean of the binary fields of the individual member forecast. The object‐based analysis reveals a similar structure as observed, although displaced eastwards. Most improvement occurred for heavier rainfall events associated with the passage of the AEW. WRF 6 km compares reasonably well with WRF 2 km in terms of shape and structure of rainfall underscoring the ability of the model to reasonably represent convection at 6 km horizontal resolution. The ensemble members in MetUM explicitly reproduce convection at 4 km resolution but are displaced at about 166 km behind observed rainfall. [ABSTRACT FROM AUTHOR]

This study seeks to identify the ontological and epistemological foundations of linguistic theory, in light of recent developments in scientific practice that takes language as its object. It requires a reconsideration of the existential concept of language and raises the issue of the existence of ontological and epistemological constants in linguistic theory. Taking into consideration the difference in the nature of linguistic sound and meaning. The approach adopted is historical and comparative, examining the major ontological and epistemological milestones. At the ontological level, the study notes that René Descartes linked the existence of language to mental existence, but the theory of relativity and statistical theory have transformed language into a virtual digital system, calling into question its ontological framework. Not to mention the fact that language is no longer merely a mental product, as evidenced by the existence of automatically generated linguistic texts. Epistemologically, the verification of linguistic knowledge has evolved, moving from logical proof to experimentation, and is now tied to utility and added value, with the virtual simulation of artificial intelligence as the environment for experimentation and proof. [ABSTRACT FROM AUTHOR]

In recent years, brain tumors have become one of the most common fatal diseases. Despite the existence of an important number of research studies on tumors, the proportion of research on predicting the growth of tumors remains insufficient due to the intricate nature of this research domain. Therefore, the presence of any application able to predict the growth of the tumor may have a role in eliminating the tumor by finding the appropriate treatment for it before it grows. This paper investigates tumor growth and presents a technique for tumor growth prediction based on the Discrete Time Markov Chain (DTMC) and K-Nearest Neighbor (KNN) algorithms. The design and development of this technique consists of a proposition of a stochastic model of tumor progression. This is followed by an extension of the mode to several cases that allow the derivation of new cases based on the study of predictive probabilities. The aim of this paper is to develop a model based on the KNN and DTMC algorithms that can classify tumors and predict the future state based on the current state of the tumor without the knowledge of the past state. In other words, all relevant information about the past and the present that would be useful in making predictions is available in the current state. In terms of performance evaluation metrics, the results show that the proposed method exceeds the existing methods with 97.65% accuracy, 71.65% specificity and 99.087% sensitivity. [ABSTRACT FROM AUTHOR]

Copyright of Al-Zaytoonah University of Jordan Journal for Human & Social Studies is the property of Al-Zaytoonah University of Jordan and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

BACKGROUND AND OBJECTIVES: One of the most important issues that insurance companies face when introducing new insurance products is how to price such products. In this article, in addition to introducing the increased annuity product, the payments of this product for cancer insureds, taking into account the probability of death or survival have been calculated for use in the country’s insurance industry. METHODS: This research is of a quantitative type and in it, the amount of annuity insurance payment increased for the insured who are cancer patients, for a single net insurance premium, is calculated using two different approaches to adjust the probability of death. Also in this research the data of the American Cancer Society and the list of technical profit rates announced in the supplement of Regulation No. 68 of the Supreme Council of Insurance, as well as the announced data table of the Iranian life insurance at the year 2021, were used. FINDINGS: In this article, the effect of adjusting the mortality probability using “adjustment multiplier” and “age rating” approaches on the amount of annuity payouts for insureds of different ages were investigated. It is expected that with an increase in the adjustment factor, which means an increase in the insured’s health problems, the life expectancy will decrease and the amount of pension payment will increase, which the findings of the article also confirm this issue. In addition, based on the relative survival assessment of 5 years and with the amount of pension payment for the insured, the life expectancy using the adjustment factor and the increased amount of pension payment for the 65-year-old insured with various cancers of the breast, colon, lung and skin with Standard health status was compared. Based on the findings of this research, local skin cancer and local breast cancer with a 5-year survival probability of 99% have the lowest pension payment increase of 2.13%. On the other hand, diffuse lung cancer and diffuse colon cancer with survival probability of 8 and 15 percent, have the highest increase in pension payments, i.e. 413.57 and 309.47 compared to standard pension payments. The fuzzy payout of annuity for the insured with local skin cancer and local breast cancer was obtained the interval [161/04, 167/88], and the payout of age rating approach with the value of 167/34 is also included in this interval. It should be noted that, in general, the payout of the “age rating” approach is higher than the “adjustment multiplier” approach. CONCLUSION: If a person has a certain health condition, the mortality and survival probability, as well as life expectancy, will be different from the standard state. For this purpose, an adjustment factor is considered for the mortality probability, and the annuity payout will be adjusted accordingly. In this article, the amount annuity payouts for the insured with different types of cancer was investigated, compared and analyzed based on two different adjustment mortality probabilities approaches. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic revealed that many countries have failed to provide the general population with the cognitive tools to thoroughly understand and cope with a global health crisis. While scientists and leaders worldwide have struggled to discover ways to contain the spread of the virus, this difficult task has become overwhelming due to the limited ability of many citizens to grasp the urgency of the situation. Although in today's digitized world we have endless access to data and more ways to represent information and statistics than ever before, numerous incidents have demonstrated that the frequent misapprehension of data can cause confusion rather than clarity. This opinion paper examines how issues such as the misunderstanding of large quantities, fractions, probabilities, and mathematical modeling may be affecting the way people view the current pandemic. Finally, we also discuss how numeracy can act as a protective factor against motivated reasoning, which often affects how we consume information related to the pandemic. [ABSTRACT FROM AUTHOR]

Entropy is the concepts from the science of information must be used in the situation where undefined behaviors of the parameters are unknown. The behavior of the casual parameters representing the processes under investigation is a problem that the essay explores from many angles. The provided uniformity criterion, which was developed utilizing the maximum entropy of the metric, has high efficiency and straightforward implementation in manual computation, computer software and hardware, and a variety of similarity, recognition, and classification indicators. The tools required to automate the decision-making process in real-world applications, such as the automatic classification of acoustic events or the fault-detection via vibroacoustic methods, are provided by statistical decision theory to the noise and vibration engineer. Other statistical analysis issues can also be resolved using the provided uniformity criterion.

Avoiding loss is a crucial, adaptive guide to human behavior. While previous developmental research has primarily focused on gaining rewards, less attention has been paid to loss processing and its avoidance. In daily life, it is often unknown how likely an action will result in a loss, making the role of uncertainty in loss processing particularly important. By using functional magnetic resonance imaging, we investigated the influence of varying outcome probabilities (12%, 34%, and 67%) on brain regions implicated in loss processing (ventral striatum (VS), anterior insula (AI)) by comparing 28 adolescents (10-18 years) and 24 adults (22-32 years) during the anticipation of potential monetary loss. Overall, results revealed slower RTs in adolescents compared to adults with both groups being faster in the experimental (monetary condition) vs. control trials (verbal condition). Fastest RTs were observed for the 67% outcome probability in both age groups. An age group outcome probability interaction effect revealed the greatest differences between the groups for the 12% vs. the 67% outcome probability. Neurally, both age groups demonstrated a higher percent signal change in the VS and AI during the anticipation of potential monetary loss versus the verbal condition. However, adults demonstrated an even greater activation of VS and AI than adolescents during the anticipation of potential monetary loss, but not during the verbal condition. This may indicate that adolescents differ from adults regarding their experience of avoiding losing monetary rewards. [ABSTRACT FROM AUTHOR]

This article presents a study based on evaluating different techniques to automatically recognize the basic emotions of people with Down syndrome, such as anger, happiness, sadness, surprise, and neutrality, as well as the statistical analysis of the Facial Action Coding System, determine the symmetry of the Action Units present in each emotion, identify the facial features that represent this group of people. First, a dataset of images of faces of people with Down syndrome classified according to their emotions is built. Then, the characteristics of facial micro-expressions (Action Units) present in the feelings of the target group through statistical analysis are evaluated. This analysis uses the intensity values of the most representative exclusive action units to classify people's emotions. Subsequently, the collected dataset was evaluated using machine learning and deep learning techniques to recognize emotions. In the beginning, different supervised learning techniques were used, with the Support Vector Machine technique obtaining the best precision with a value of 66.20%. In the case of deep learning methods, the mini-Xception convolutional neural network was used to recognize people's emotions with typical development, obtaining an accuracy of 74.8%. [ABSTRACT FROM AUTHOR]

Copyright of Quetes Litteraires is the property of Katolicki Uniwersityt Lubelski Jana Pawla II, Wydzial Nauk Humanistycznych, Institut Filologii Romaj and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Artificial Intelligence (AI) is revolutionizing micro and macro-aided decision-making processes across various sectors and disciplines worldwide. This paper uses the probability technique to theoretically forecast AI-aided integration program potential to offer accelerated, concrete and individualized integration support for new and 'old' resident immigrants throughout their stay in Finland. The algorithms are base on various taxonomies and topologies for individualized self-paced, life-long situation-specific integration support. This action research article theoretically reviews two high-quality peer-reviewed publications on AI in aging through systematic reviews and meta-analyses, combining results from multiple impact evaluation studies to construct arguments and draw conclusions for the use of AI in accelerating new migrants' integration in Finland. Data is analyzed qualitatively and quantitively to deduce realistic predictions. This article uses grounded theory to test theories that underscore the role and impact of AI in accelerating integration. This article presents the foundation on which future integration programs will be implemented. [ABSTRACT FROM AUTHOR]

Demographers and other social scientists often study effect heterogeneity (defined here as differences in outcome-predictor associations across groups defined by the values of a third variable) to understand how inequalities evolve between groups or how groups differentially benefit from treatments. Yet answering the question "Is the effect larger in group A or group B?" is surprisingly difficult. In fact, the answer sometimes reverses across scales. For example, researchers might conclude that the effect of education on mortality is larger among women than among men if they quantify education's effect on an odds-ratio scale, but their conclusion might flip (to indicate a larger effect among men) if they instead quantify education's effect on a percentage-point scale. We illuminate this flipped-signs phenomenon in the context of nonlinear probability models, which were used in about one third of articles published in Demography in 2018-2019. Although methodologists are aware that flipped signs can occur, applied researchers have not integrated this insight into their work. We provide formal inequalities that researchers can use to easily determine if flipped signs are a problem in their own applications. We also share practical tips to help researchers handle flipped signs and, thus, generate clear and substantively correct descriptions of effect heterogeneity. Our findings advance researchers' ability to accurately characterize population variation. [ABSTRACT FROM AUTHOR]

A strong foundation in early number concepts is crucial for students' future success in statistics. Despite its importance in statistics, many first-year students struggle to comprehend the normal distribution due to a lack of basic number sense. Students get confused about the order and magnitude of negative z-scores on a standard normal curve or when problems about normally distributed random variables are presented in word questions which involve phrases that indicate inequalities. As a result, students shade wrong areas on the bell-shaped curve when they have to calculate probabilities for normally distributed variables. Visual representations such as the number line can support students' development of quantitative literacy or number sense by helping them create a mental representation of the order and magnitude of numbers as well as inequalities. Based on a comprehensive investigation of evidence demonstrating this weakness, this experienced-based perspective proposes a framework that demonstrates how the number line can be used as a powerful teaching tool to promote students' conceptual understanding about the normal distribution. The framework illustrates with authentic examples how the number line relates to the horizontal axis of the normal and standard normal curve and how it can be used to address erroneous quantitative reasoning when students are required to calculate probabilities for normally distributed variables. To determine if the number line teaching intervention affects student performance, the researcher adopted a non-equivalent pretest-posttest design with two intact classes. The results of the analysis show that students who received the intervention performed significantly better in the posttest. [ABSTRACT FROM AUTHOR]