Miracle-dz/UniFAR-FTUs huggingface dataset:
Developments in Non-expected Utility Theory: The Hunt for a Descriptive Theory of Choice under Risk

This article reviews recent developments in the economic theory of individual decision making under risk. Since the 1950s it has been known that individual choices violate the standard model of expected utility in predictable ways. Considerable research effort has now been devoted to the project of developing a superior descriptive model. Following an overview of non-expected utility theories which distinguishes between "conventional" and "non-conventional" approaches, the paper seeks to assess these alternative models in terms of empirical success (using laboratory and field data) and theoretical usefulness. The closing sections reflect on some new directions emerging in this literature.
Treadmill Training With Partial Body Weight Support and an Electromechanical Gait Trainer for Restoration of Gait in Subacute Stroke Patients: A Randomized Crossover Study

Background and Purpose— The purpose of this study was to compare treadmill and electromechanical gait trainer therapy in subacute, nonambulatory stroke survivors. The gait trainer was designed to provide nonambulatory subjects the repetitive practice of a gait-like movement without overexerting therapists. Methods— This was a randomized, controlled study with a crossover design following an A-B-A versus a B-A-B pattern. A consisted of 2 weeks of gait trainer therapy, and B consisted of 2 weeks of treadmill therapy. Thirty nonambulatory hemiparetic patients, 4 to 12 weeks after stroke, were randomly assigned to 1 of the 2 groups receiving locomotor therapy every workday for 15 to 20 minutes for 6 weeks. Weekly gait ability (functional ambulation category [FAC]), gait velocity, and the required physical assistance during both kinds of locomotor therapy were the primary outcome measures, and other motor functions (Rivermead motor assessment score) and ankle spasticity (modified Ashworth score) were the secondary outcome measures. Follow-up occurred 6 months later. Results— The groups did not differ at study onset with respect to the clinical characteristics and effector variables. During treatment, the FAC, gait velocity, and Rivermead scores improved in both groups, and ankle spasticity did not change. Median FAC level was 4 (3 to 4) in group A compared with 3 (2 to 3) in group B at the end of treatment (P =0.018), but the difference at 6-month follow up was not significant. The therapeutic effort was less on the gait trainer, with 1 instead of 2 therapists assisting the patient at study onset. All but seven patients preferred the gait trainer. Conclusions— The newly developed gait trainer was at least as effective as treadmill therapy with partial body weight support while requiring less input from the therapist. Further studies are warranted.
Scalable and Self-Adaptive Service Selection Method for the Internet of Things

The Internet of Things goes beyond the regular Internet by offering new functionalities and creating new range of services provided by the deployed objects. Therefore, one of the most challenging issues is to select the best service among similar functionally available ones. In this paper, we propose to involve both artifcial intelligence through the use of Artifcial Neural Network (ANN) and multi criteria analysis through the use of Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) model in order to return the best service to the requestor. First, The ANN is introduced as a predictive model to estimate the Qualities of services (QoS) according to user context, service context and network context. Second, the TOPSIS model evaluates, then aggregates these QoS values in order to provide the best service according to user preferences. To improve the scalability of the proposed service selection system we conduct a parallel implementation of the prototype.
Performance Evaluation of Asynchronous Concurrent Systems Using Petri Nets

Some analysis techniques for real-time asynchronous concurrent systems are presented. In order to model clearly the synchronization involved in these systems, an extended timed Petri net model is used. The system to be studied is first modeled by a Petri net. Based on the Petri net model, a system is classified into either: 1) a consistent system; or 2) an inconsistent system. Most real-world systems fall into the first class which is further subclassified into i) decision-free systems; ii) safe persistent systems; and iii) general systems. Procedures for predicting and verifying the system performance of all three types are presented. It is found that the computational complexity involved increases in the same order as they are listed above.
Automated trading with boosting and expert weighting

We propose a multi-stock automated trading system that relies on a layered structure consisting of a machine learning algorithm, an online learning utility, and a risk management overlay. Alternating decision tree (ADT), which is implemented with Logitboost, was chosen as the underlying algorithm. One of the strengths of our approach is that the algorithm is able to select the best combination of rules derived from well-known technical analysis indicators and is also able to select the best parameters of the technical indicators. Additionally, the online learning layer combines the output of several ADTs and suggests a short or long position. Finally, the risk management layer can validate the trading signal when it exceeds a specified non-zero threshold and limit the application of our trading strategy when it is not profitable. We test the expert weighting algorithm with data of 100 randomly selected companies of the S&P 500 index during the period 2003–2005. We find that this algorithm generates abnormal returns during the test period. Our experiments show that the boosting approach is able to improve the predictive capacity when indicators are combined and aggregated as a single predictor. Even more, the combination of indicators of different stocks demonstrated to be adequate in order to reduce the use of computational resources, and still maintain an adequate predictive capacity.
ParFormer: Vision Transformer Baseline with Parallel Local Global Token Mixer and Convolution Attention Patch Embedding

This work presents ParFormer as an enhanced transformer architecture that allows the incorporation of different token mixers into a single stage, hence improving feature extraction capabilities. Integrating both local and global data allows for precise representation of short- and long-range spatial relationships without the need for computationally intensive methods such as shifting windows. Along with the parallel token mixer encoder, We offer the Convolutional Attention Patch Embedding (CAPE) as an enhancement of standard patch embedding to improve token mixer extraction with a convolutional attention module. Our comprehensive evaluation demonstrates that our ParFormer outperforms CNN-based and state-of-the-art transformer-based architectures in image classification and several complex tasks such as object recognition. The proposed CAPE has been demonstrated to benefit the overall MetaFormer architecture, even while utilizing the Identity Mapping Token Mixer, resulting in a 0.5\% increase in accuracy. The ParFormer models outperformed ConvNeXt and Swin Transformer for the pure convolution and transformer model in accuracy. Furthermore, our model surpasses the current leading hybrid transformer by reaching competitive Top-1 scores in the ImageNet-1K classification test. Specifically, our model variants with 11M, 23M, and 34M parameters achieve scores of 80.4\%, 82.1\%, and 83.1\%, respectively. Code: https://github.com/novendrastywn/ParFormer-CAPE-2024
Number of Available Associations and Rate of Association For Categories in Semantic Memory

Summary Bousfield and Sedgewick showed that the cumulative number of associations produced to a category as a function of time could be described by an exponential function having the parameters m (rate of association) and C (total number of associates produced). In two experiments using male and female college students (N = 16 and N = 14, respectively), the present study investigated the hypothesis suggested by previous research, that the values of m and C for different categories are negatively correlated. S s produced examples of different categories in four-minute periods per category on mimeographed sheets. The predicted negative correlation across categories was found (Experiment I, r = .54, p < .05, one-tailed test; Experiment 2, r = .75, p < .01). Categories with a low m value had a high C value and vice versa. The effect can be explained by a model which assumes exemplars are stored more or less densely in semantic memory.
Algae as Protein Factories: Expression of a Human Antibody and the Respective Antigen in the Diatom Phaeodactylum tricornutum

Microalgae are thought to offer great potential as expression system for various industrial, therapeutic and diagnostic recombinant proteins as they combine high growth rates with all benefits of eukaryotic expression systems. Moreover, microalgae exhibit a phototrophic lifestyle like land plants, hence protein expression is fuelled by photosynthesis, which is CO2-neutral and involves only low production costs. So far, however, research on algal bioreactors for recombinant protein expression is very rare calling for further investigations in this highly promising field. In this study, we present data on the expression of a monoclonal human IgG antibody against the Hepatitis B surface protein and the respective antigen in the diatom Phaeodactylum tricornutum. Antibodies are fully-assembled and functional and accumulate to 8.7% of total soluble protein, which complies with 21 mg antibody per gram algal dry weight. The Hepatitis B surface protein is functional as well and is recognized by algae-produced and commercial antibodies.
Seniors’ Body Weight Dissatisfaction and Longitudinal Associations With Weight Changes, Anorexia of Aging, and Obesity

Objective: We examined longitudinal associations between weight dissatisfaction, weight changes, anorexia of aging, and obesity among 1,793 seniors followed over 4 years between 2003 and 2009. Method: Obesity prevalence (body mass index [BMI] ≥ 30) and prevalence/incidence of weight dissatisfaction, anorexia of aging (self-reported appetite loss), and weight changes ≥5% were assessed. Predictors of weight loss ≥5%, anorexia of aging, and weight dissatisfaction were examined using logistic regressions. Results: Half of seniors experienced weight dissatisfaction (50.6%, 95% confidence interval [CI] = [48.1, 53.1]). Anorexia of aging and obesity prevalence was 7.0% (95% CI = [5.7, 8.3]) and 25.1% (95% CI = [22.9, 27.3]), whereas incidence of weight gain/loss ≥5% was 6.6% (95% CI = [1.3, 11.9]) and 8.8% (95% CI = [3.3, 14.3]). Weight gain ≥5% predicts men’s subsequent weight dissatisfaction (odds ratio [OR] = 6.66, 95% CI = [2.06, 21.60]). No other association was observed. Discussion: Weight dissatisfaction is frequent but not associated with subsequent eating disorders. In men, weight gain predicted weight dissatisfaction. Seniors’ weight dissatisfaction does not necessarily equate weight changes. Due to its high prevalence, it is of public health interest to understand how seniors’ weight dissatisfaction may impact health.
Contrasting Cognitive Deficits in Attention Deficit Hyperactivity Disorder versus Reading Disability.

We compared 2 common and sometimes comorbid developmental disorders, reading disability (RD) and attention deficit hyperactivity disorder (ADHD), in 2 cognitive domains, phonological processes (PP) and executive functions (EF). Subjects were 70 boys of early school age, studied by means of a 2 (RD vs. no RD) × 2 (ADHD vs. no ADHD) × 2 (domain type) mixed-model design. The 2 RD groups (RD-only and RD plus ADHD) were significantly impaired compared with both the control and ADHD-only groups on a PP composite score but performed normally on the EF composite score. The ADHD-only group had an opposite profile and was significantly different from both RD groups and from controls on the EF composite score. Thus, there was a double-dissociation between the RD-only and ADHD-only groups. The comorbid group resembled the RDonly group, consisttent with the hypothesis that their ADHD symptoms are secondary to RD
Role of the Long Non-Coding RNA MAPT-AS1 in Regulation of Microtubule Associated Protein Tau (MAPT) Expression in Parkinson's Disease

Studies investigating the pathogenic role of the microtubule associated protein tau (MAPT) gene in Parkinson’s disease (PD) have indicated that DNA methylation of the promoter region is aberrant in disease, leading to dysregulated MAPT expression. We examined two potential regulators of MAPT gene expression in respect to PD, a promoter-associated long non-coding RNA MAPT-AS1, and DNA methyltransferases (DNMTs), enzymes responsible for new and maintenance of DNA methylation. We assessed the relationship between expression levels of MAPT and the candidate MAPT-AS1, DNMT1, DNMT3A and DNMT3B transcripts in four brain regions with varying degrees of cell loss and pathology (putamen, anterior cingulate cortex, visual cortex and cerebellum) in N = 10 PD and N = 10 controls. We found a significant decrease in MAPT-AS1 expression in PD (p = 7.154 x 10−6). The transcript levels of both MAPT-AS1 (p = 2.569 x 10−4) and DNMT1 (p = 0.001) correlated with those of MAPT across the four brain regions, but not with each other. Overexpression of MAPT-AS1 decreased MAPT promoter activity by ∼2.2 to 4.3 fold in an in vitro luciferase assay performed in two cell lines (p ≤ 2.678 x 10−4). Knock-down expression of MAPT-AS1 led to a 1.3 to 6.3 fold increase in methylation of the endogenous MAPT promoter (p ≤ 0.011) and a 1.2 to 1.5 fold increased expression of the 4-repeat MAPT isoform transcript (p ≤ 0.013). In conclusion, MAPT-AS1 and DNMT1 have been identified as potential epigenetic regulators of MAPT expression in PD across four different brain regions. Our data also suggest that increased MAPT expression could be associated with disease state, but not with PD neuropathology severity.
The DNA Methylation Inhibitor 5-Azacytidine Increases Regulatory T Cells and Alleviates Airway Inflammation in Ovalbumin-Sensitized Mice

Background: Asthma is characterized as a chronic inflammatory disorder of the airways associated with an enhanced TH2 response to inhaled allergens. CD4+ T regulatory (Treg) cells are controlled by the master transcription factor FoxP3 and strictly maintain peripheral immunotolerance. Epigenetic regulation of FoxP3 by DNA methyltransferase inhibitors, such as 5-azacytidine (Aza), can generate a steady supply of functional Treg cells. Therefore, we propose that Aza can augment Treg cells in vivo to prevent the pathogenesis of asthma. Methods: BALB/c mice were sensitized with chicken ovalbumin (OVA) and treated with different doses of Aza. Airway hyperresponsiveness to methacholine, eosinophilia in bronchoalveolar lavage fluid, circulating titers of OVA-specific IgG1 and IgE, and stimulating levels of TH2 cytokines from splenocytes were then determined. Cellular populations were examined by flow cytometry. PC61 antibody, which depletes CD25+ cells, was used to verify the role of CD25+ cells in Aza-induced tolerance. Results: Administration of Aza to OVA-sensitized mice diminished airway hyperreactivity, pulmonary eosinophilia, levels of OVA-specific IgG1 and IgE in serum, and secretion of TH2 cytokines from OVA-stimulated splenocytes in a dose-dependent manner. Percentages of CD25+ and FoxP3+ cells in the CD4+ cell population were notably increased in Aza-treated mice compared to sensitized control mice. Furthermore, the major symptoms of asthma were exacerbated by depleting CD25+ cells in Aza-treated mice. Conclusions: Aza may have applications as a novel clinical strategy to increase the production of Treg cells in order to modulate the airway inflammation associated with asthma.
On the predictive validity of attitudes: The roles of direct experience and confidence1

Previous research has demonstrated that behavior is more accurately predicted from attitudes formed via direct, behavioral interaction with the attitude object than from attitudes developed via indirect, nonbehavioral experience. The present research examined the hypothesis that the confidence with which an attitude is held may be a mediating variable in the observed relationship between the manner of attitude formation and attitude-behavior consistency. In the first experiment, it was demonstrated that subjects who formed their attitudes through direct experience held those attitudes more confidently and behaved more consistently with those attitudes than did subjects who formed their attitudes through indirect experience. In the second experiment, it was found that, regardless of the manner of attitude formation, subjects who were led to believe that they held their attitudes confidently displayed greater attitude-behavior consistency than did subjects led to believe that they held their attitudes with little confidence. Taken together, the results suggest that it may be fruitful to view confidence both as a variable which mediates the effect of the manner of attitude formation on attitude-behavior consistency and as one which, independent of how an attitude is formed, acts as a determinant of attitude-behavior consistency.
Habitat selection by translocated black howler monkeys in Belize

Habitat selection by translocated black howler monkeys (Alouatta pigra) was studied in Belize, Central America. Ranging patterns of two recently translocated groups were contrasted with those of two groups in the same area with established home ranges, on a yearly and monthly basis. All groups concentrated their activities along stream beds at elevations below 200 m. Newly translocated groups increased the percentage of their monthly ranges in riverine areas (within 100 m of a water source) over the year of the study (with the exception of the last month) while established groups did not. Areas used more than five times by the monkeys contained larger trees and a greater relative coverage of major food species than low‐use areas even though they had a lower overall species richness and diversity. These monkeys may be selecting habitat within the forest based upon vegetative differences and ranging patterns may be affected by patterns of food availability.
Decisions for Others Become Less Impulsive the Further Away They Are on the Family Tree

Background People tend to prefer a smaller immediate reward to a larger but delayed reward. Although this discounting of future rewards is often associated with impulsivity, it is not necessarily irrational. Instead it has been suggested that it reflects the decision maker’s greater interest in the ‘me now’ than the ‘me in 10 years’, such that the concern for our future self is about the same as for someone else who is close to us. Methodology/Principal Findings To investigate this we used a delay-discounting task to compare discount functions for choices that people would make for themselves against decisions that they think that other people should make, e.g. to accept $500 now or $1000 next week. The psychological distance of the hypothetical beneficiaries was manipulated in terms of the genetic coefficient of relatedness ranging from zero (e.g. a stranger, or unrelated close friend), . 125 (e.g. a cousin), . 25 (e.g. a nephew or niece), to . 5 (parent or sibling). Conclusions/Significance The observed discount functions were steeper (i.e. more impulsive) for choices in which the decision-maker was the beneficiary than for all other beneficiaries. Impulsiveness of decisions declined systematically with the distance of the beneficiary from the decision-maker. The data are discussed with reference to the implusivity and interpersonal empathy gaps in decision-making.
EM Algorithms for Weighted-Data Clustering with Application to Audio-Visual Scene Analysis

Data clustering has received a lot of attention and numerous methods, algorithms and software packages are available. Among these techniques, parametric finite-mixture models play a central role due to their interesting mathematical properties and to the existence of maximum-likelihood estimators based on expectation-maximization (EM). In this paper we propose a new mixture model that associates a weight with each observed point. We introduce the weighted-data Gaussian mixture and we derive two EM algorithms. The first one considers a fixed weight for each observation. The second one treats each weight as a random variable following a gamma distribution. We propose a model selection method based on a minimum message length criterion, provide a weight initialization strategy, and validate the proposed algorithms by comparing them with several state of the art parametric and nonparametric clustering techniques. We also demonstrate the effectiveness and robustness of the proposed clustering technique in the presence of heterogeneous data, namely audio-visual scene analysis.
Joint Trajectory and Power Optimization for UAV Relay Networks

In this letter, we consider an unmanned aerial vehicle (UAV) relay network, where the UAV works as an amplify-and-forward relay. We optimize the trajectory of UAV, the transmit power of UAV, and the mobile device by minimizing the outage probability of this relay network. The analytical expression of outage probability is derived first. A closed-form low-complexity solution with joint trajectory design and power control is proposed to solve this non-convex problem. Simulation results show that the outage probability of the proposed solution is significantly lower than that of the fixed power relay and circle trajectory for the UAV relay.
Influences of Work-Family Conflict on Job Satisfaction, Life Satisfaction and Quitting Intentions Among Business Owners: The Case of Family-Operated Businesses

This study examines the effect of inter-role conflict between the family and business domains among operators of small businesses and family-owned businesses. Findings indicate that work-family conflict can significantly affect both job and life satisfaction of owners as well as their propensity to seek a new line of work. Results vary among owners depending on whether or not they work with other members of their immediate family. Owners that employ other family members experience significantly higher levels of work-family conflict.
When beliefs are not enough: Examining the interaction of diversity faultlines, task motivation, and diversity beliefs on team performance

Diversity faultline strength – the extent to which diversity attributes within a group converge in such a way that they split a group into homogeneous subgroups – can decrease group performance. Based on the categorization–elaboration model (CEM) of workgroup diversity, we assumed that task motivation can overcome the detrimental effects of faultlines. We further assumed that this effect is contingent on the groups' diversity beliefs and that it is mediated by the elaboration of task-relevant information. Forty-three student groups worked on a computer-simulated complex problem solving scenario. The group faultline strength was calculated over the attributes gender, age and educational background. Information elaboration was elicited by means of behavioural coding. Results revealed a three-way interaction of faultline strength, diversity beliefs and task motivation: groups overcame the detrimental effects of faultlines only if they exhibited pro-diversity beliefs and high task motivation. The three-way interaction of faultline strength, diversity beliefs and task motivation was partly mediated by information elaboration. Practical and theoretic implications are discussed.