Miracle-dz/UniFAR-FTUs huggingface dataset:
Chaotic based Pteropus algorithm for solving optimal reactive power problem

In this work, a Chaotic based Pteropus algorithm (CPA) has been proposed for solving optimal reactive power problem. Pteropus algorithm imitates deeds of the Pteropus. Normally Pteropus while flying it avoid obstacles by using sonar echoes, particularly utilize time delay. To the original Pteropus algorithm chaotic disturbance has been applied and the optimal capability of the algorithm has been improved in search of global solution. In order to augment the population diversity and prevent early convergence, adaptively chaotic disturbance is added at the time of stagnation. Furthermore exploration and exploitation capability of the proposed algorithm has been improved. Proposed CPA technique has been tested in standard IEEE 14,300 bus systems & real power loss has been considerably reduced.
Does the time horizon of the return predictive effect of investor sentiment vary with stock characteristics? A Granger causality analysis in the frequency domain

Behavioral theories posit that investor sentiment exhibits predictive power for stock returns, whereas there is little study have investigated the relationship between the time horizon of the predictive effect of investor sentiment and the firm characteristics. To this end, by using a Granger causality analysis in the frequency domain proposed by Lemmens et al. (2008), this paper examine whether the time horizon of the predictive effect of investor sentiment on the U.S. returns of stocks vary with different firm characteristics (e.g., firm size (Size), book-to-market equity (B/M) rate, operating profitability (OP) and investment (Inv)). The empirical results indicate that investor sentiment has a long-term (more than 12 months) or short-term (less than 12 months) predictive effect on stock returns with different firm characteristics. Specifically, the investor sentiment has strong predictability in the stock returns for smaller Size stocks, lower B/M stocks and lower OP stocks, both in the short term and long term, but only has a short-term predictability for higher quantile ones. The investor sentiment merely has predictability for the returns of smaller Inv stocks in the short term, but has a strong short-term and long-term predictability for larger Inv stocks. These results have important implications for the investors for the planning of the short and the long run stock investment strategy.
Is symptom prevalence and burden associated with HIV treatment status and disease stage among adult HIV outpatients in Kenya? A cross-sectional self-report study

ABSTRACT People with HIV experience a high prevalence and burden of physical and psychological symptoms throughout their disease trajectory. These have important public and clinical health implications. We aimed to measure: the seven-day period prevalence of symptoms, the most burdensome symptoms, and determine if self-reported symptom burden is associated with treatment status, clinical stage and physical performance. We conducted a cross-sectional study among adult (aged at least 18 years) patients with HIV, attending HIV outpatient care in Kenya. Data was gathered through self-report using the Memorial Symptom Assessment Scale-Short Form (MSAS-SF), file extraction (sociodemographic data, treatment status, CD4 count, clinical stage) and through observation using the Karnofsky Performance Scale (KPS). Multivariable ordinal logistic regression assessed the association of symptom burden (MSAS-SF) controlling for demographic and clinical variables. Of the 475 participants approached, 400 (84.2%) participated. Ordinal logistic regression showed that being on HIV treatment was associated lower global distress index (in quartiles) (odds ratio .45, 95% CI .23 to .88; p = 0.019). Pain and symptom burden still persist in the era of antiretroviral therapy. Routine clinical practice should incorporate assessment and management of pain and symptoms irrespective of disease stage and treatment status in order to achieve the proposed fourth “90” in the UNAIDS 90-90-90 targets (that is good quality of life).
Soft dielectric elastomer microactuator for robot locomotion

This paper presents dielectric elastomer actuated robot locomotion and the development of a robotic model structure based using a dielectric elastomer actuator. A pre-stretched dielectric elastomer actuator is fabricated onto acrylic frames to form single and multiple robotic crawler models. The crawler models demonstrate forwards motion upon application of high voltage to the attached dielectric elastomer actuator. Characterizations revealed that the fabricated multiple crawler models showed results over the single crawler model in terms of locomotion potential. The maximum forward locomotion speed of the multiple crawler models is recorded as 1.2 mm/s. Nonetheless, precise results are highly attainable provided a structured and coherent fabrication technique of the dielectric elastomer actuator is implemented.
Occupational violence among female workers in an Iranian industrial area

ABSTRACT Few studies have examined violence against female workers in the industrial sector. This study explored the prevalence of various types of violence and associated factors among female workers in the industrial sector. This descriptive survey was conducted in eleven industrial sites in Kashan, Iran, from April through September 2014. We used a 78-item questionnaire to obtain data from 817 female workers. More than half of the participants reported having experienced at least one type of violence. The prevalence rates of verbal aggression, sexual harassment, and physical violence were 52.5%, 12% and 11.5%, respectively. Single female workers (adjusted odds ratio [AOR] = 2.06, 95% CI = 1.09–4.27), and age older than 35 years were (AOR = 2.37, 95% CI = 1.26–2.93) each significantly related to increased odds of verbal violence. Short duration of employment (≤ five years) was the most strongly associated factor for sexual harassment (AOR = 2.82, 95% CI = 1.7–2.94). Working the night shift was significantly associated with encountering verbal violence (AOR = 2.79, 95% CI = 1.69–3.06). The high prevalence of violence suggests that management in industrial workplaces should invest time and resources in addressing violence. Developing a reporting procedure and training programs are recommended in dealing with workplace violence risk.
On‐chip electromembrane extraction of acidic drugs

In the present work, a new supported liquid membrane (SLM) has been developed for on‐chip electromembrane extraction of acidic drugs combined with HPLC or CE, providing significantly higher stability than those reported up to date. The target analytes are five widely used non‐steroidal anti‐inflammatory drugs (NSAIDs): ibuprofen (IBU), diclofenac (DIC), naproxen (NAX), ketoprofen (KTP) and salicylic acid (SAL). Two different microchip devices were used, both consisted basically of two poly(methyl methacrylate) (PMMA) plates with individual channels for acceptor and sample solutions, respectively, and a 25 µm thick porous polypropylene membrane impregnated with the organic solvent in between. The SLM consisting of a mixture of 1‐undecanol and 2‐nitrophenyl octyl ether (NPOE) in a ratio 1:3 was found to be the most suitable liquid membrane for the extraction of these acidic drugs under dynamic conditions. It showed a long‐term stability of at least 8 hours, a low system current around 20 µA, and recoveries over 94% for the target analytes. NPOE was included in the SLM to significantly decrease the extraction current compared to pure 1‐undecanol, while the extraction properties was almost unaffected. Moreover, it has been successfully applied to the determination of the target analytes in human urine samples, providing high extraction efficiency.
Effect of Values and Technology Use on Exercise: Implications for Personalized Behavior Change Interventions

Technology has recently been recruited in the war against the ongoing obesity crisis; however, the adoption of Health & Fitness applications for regular exercise is a struggle. In this study, we present a unique demographically representative dataset of 15k US residents that combines technology use logs with surveys on moral views, human values, and emotional contagion. Combining these data, we provide a holistic view of individuals to model their physical exercise behavior. First, we show which values determine the adoption of Health & Fitness mobile applications, finding that users who prioritize the value of purity and de-emphasize values of conformity, hedonism, and security are more likely to use such apps. Further, we achieve a weighted AUROC of . 673 in predicting whether individual exercises, and we also show that the application usage data allows for substantially better classification performance (.608) compared to using basic demographics (.513) or internet browsing data (.546). We also find a strong link of exercise to respondent socioeconomic status, as well as the value of happiness. Using these insights, we propose actionable design guidelines for persuasive technologies targeting health behavior modification.
Estimating Treatment Effects in Mover Designs

Researchers increasingly leverage movement across multiple treatments to estimate causal effects. While these "mover regressions" are often motivated by a linear constant-effects model, it is not clear what they capture under weaker quasi-experimental assumptions. I show that binary treatment mover regressions recover a convex average of four difference-in-difference comparisons and are thus causally interpretable under a standard parallel trends assumption. Estimates from multiple-treatment models, however, need not be causal without stronger restrictions on the heterogeneity of treatment effects and time-varying shocks. I propose a class of two-step estimators to isolate and combine the large set of difference-in-difference quasi-experiments generated by a mover design, identifying mover average treatment effects under conditional-on-covariate parallel trends and effect homogeneity restrictions. I characterize the efficient estimators in this class and derive specification tests based on the model's overidentifying restrictions. Future drafts will apply the theory to the Finkelstein et al. (2016) movers design, analyzing the causal effects of geography on healthcare utilization.
Granger causality on horizontal sum of Boolean algebras

The intention of this paper is to discuss the mathematical model of causality introduced by C.W. J. Granger in 1969. The Granger's model of causality has become well-known and often used in various econometric models describing causal systems, e.g., between commodity prices and exchange rates. Our paper presents a new mathematical model of causality between two measured objects. We have slightly modified the well-known Kolmogorovian probability model. In particular, we use the horizontal sum of set $\sigma$-algebras instead of their direct product.
Real-time data assimilation and control on mechanical systems under uncertainties

The work is placed into the framework of data assimilation and control in structural mechanics. It aims at developing new numerical tools in order to permit real-time and robust data assimilation and control that could then be used in various engineering activities. A specific targeted activity is the implementation of the DDDAS (Dynamic Data Driven Application System) technology in which a continuous exchange between simulation tools and experimental measurements is envisioned to the end of creating retroactive control loops on mechanical systems [1]. In this context, and in order to take various uncertainty sources (modeling error, measurement noise,.) into account, a powerful and general stochastic methodology with Bayesian inference is considered [2]. However, a well-known drawback of such an approach is the computational complexity which makes real-time simulations and sequential assimilation some difficult tasks [3]. The presented work thus proposes to couple Bayesian inference with attractive and advanced numerical techniques so that real-time and sequential assimilation can be envisioned. First, PGD model reduction [4] is introduced to facilitate the computation of the likelihood function, the uncertainty propagation through complex models, and the sampling of the posterior density. PGD builds a multi-parametric solution in an offline phase and leads to cost effective evaluation of the numerical model depending on parameters in the online inversion phase [5]. Second, Transport Map sampling [6, 7] is investigated as a substitute to classical MCMC procedures for posterior sampling. It is shown that this technique leads to deterministic computations, with clear convergence criteria, and that it is particularly suited to sequential data assimilation. Here again, the use of PGD model reduction highly facilitates the process by recovering gradient and Hessian information in a straightforward manner [8]. Third, and to increase robustness, on-the-fly correction of model bias is addressed in a stochastic context using data-based enrichment terms [9]. Eventually, the synthesis of control laws in a stochastic context, using both PGD model reduction and dynamically updated model parameters, is investigated into the DDDAS framework in order to drive the physical system accordingly. The overall methodology is applied and illustrated on specific test-cases dealing with
Temperature‐induced developmental plasticity in Plodia interpunctella: Reproductive behaviour and sperm length

In both plants and animals, male gametogenesis is particularly sensitive to heat stress, to the extent that a single hot or cold day can compromise crop productivity or population persistence. In animals, heat stress during development can impact a male's ability to secure copulations and/or his post‐copulatory fertility. Despite such observations, relatively few studies have examined the consequences of developmental temperature on the reproductive behaviour and physiology of individuals. Here, we report for the first time the effects of developmental temperature on the phenotypic expression of both apyrene and eupyrene sperm and the copulatory behaviour of the Indian meal moth, Plodia interpunctella. We show that the length of both apyrene and eupyrene sperm decreases with increasing developmental temperature and that males are less likely to engage in copulation when reared at the highest and lowest temperatures. Where copulation occurred, the duration of copula decreased as male developmental temperature increased. We argue that identification of the mechanisms and consequences of reproductive failure in animals facing heat stress will help understand how wild and domesticated populations will respond to global climate change. We also contend that such studies will help elucidate long‐standing evolutionary questions around the maintenance of genetic variation in traits highly relevant to fitness and the role of phenotypic plasticity in driving the evolution of novel traits.
Graded Relevance Assessments and Graded Relevance Measures of NTCIR: A Survey of the First Twenty Years

NTCIR was the first large-scale IR evaluation conference to construct test collections with graded relevance assessments: the NTCIR-1 test collections from 1998 already featured relevant and partially relevant documents. In this paper, I first describe a few graded-relevance measures that originated from NTCIR (and a few variants) which are used across different NTCIR tasks. I then provide a survey on the use of graded relevance assessments and of graded relevance measures in the past NTCIR tasks which primarily tackled ranked retrieval. My survey shows that the majority of the past tasks fully utilised graded relevance by means of graded evaluation measures, but not all of them; interestingly, even a few relatively recent tasks chose to adhere to binary relevance measures. I conclude this paper by a summary of my survey in table form, and a brief discussion on what may lie beyond graded relevance.
Difference-in-Differences Estimation with High-Dimensional Common Trend Confounding

In this study, we consider difference-in-differences models with a common trend assumption that is only valid after conditioning on covariates. We suggest estimators that allow the covariates to enter the model in a very flexible form. In particular, we propose estimation procedures that involve supervised machine learning methods. We derive asymptotic results for new semiparametric and linear model based estimators for repeated cross-sections and panel data and show that they have desirable statistical properties like asymptotic normality and double robustness. Further, we establish a semiparametric efficiency bound for panel difference-in-differences estimation. The proposed semiparametric estimator attains this bound. The usability of the methods is assessed by replicating a study on an employment protection reform. We demonstrate that the notion of high-dimensional common trend confounding has implications for the economic interpretation of the policy evaluation results. Notably, measured reform effects are substantially decreased or even reversed when covariates are included in a data-driven manner.
Kti12, a PSTK-like tRNA dependent ATPase essential for tRNA modification by Elongator

Abstract Posttranscriptional RNA modifications occur in all domains of life. Modifications of anticodon bases are of particular importance for ribosomal decoding and proteome homeostasis. The Elongator complex modifies uridines in the wobble position and is highly conserved in eukaryotes. Despite recent insights into Elongator's architecture, the structure and function of its regulatory factor Kti12 have remained elusive. Here, we present the crystal structure of Kti12′s nucleotide hydrolase domain trapped in a transition state of ATP hydrolysis. The structure reveals striking similarities to an O-phosphoseryl-tRNA kinase involved in the selenocysteine pathway. Both proteins employ similar mechanisms of tRNA binding and show tRNASec-dependent ATPase activity. In addition, we demonstrate that Kti12 binds directly to Elongator and that ATP hydrolysis is crucial for Elongator to maintain proper tRNA anticodon modification levels in vivo. In summary, our data reveal a hitherto uncharacterized link between two translational control pathways that regulate selenocysteine incorporation and affect ribosomal tRNA selection via specific tRNA modifications.
Cyto- and Myelo-Architecture of the Amygdaloid Complex of the Common Marmoset Monkey (Callithrix jacchus)

The amygdaloid complex (AC) is a heterogeneous aggregate of nuclei located in the rostromedial region of the temporal lobe. In addition to being partly connected among themselves, the AC nuclei are strongly interconnected with the cerebral cortex, striatum, basal forebrain, hypothalamus and brainstem. Animal and human functional studies have established that the AC is a central hub of the neuronal networks supporting emotional responsivity, particularly its negative/aversive components. Dysfunction of AC circuits in humans has been implicated in anxiety, depression, schizophrenia and bipolar disorder. The small New-World marmoset monkey (Callithrix jacchus) has recently become a key model for neuroscience research. However, the nuclear and fiber tract organization of marmoset AC has not been examined in detail. Thus, the extent to which it can be compared to the AC of Old-World (human and macaque) primates is yet unclear. Here, using Nissl and acetylcholinesterase (AChE) histochemical stains as a reference, we analyzed the cytoarchitecture and nuclear parcellation of the marmoset AC. In addition, given the increasing relevance of tractographic localization for high-resolution in vivo imaging studies in non-human primates, we also identified the myelin fiber tracts present within and around the AC as revealed by the Gallyas method. The present study provides a detailed atlas of marmoset AC. Moreover, it reveals that, despite phylogenetic distance and brain size differences, every nucleus and myelinated axon bundle described in human and macaque studies can be confidently recognized in marmosets.
A real-time drowsiness and fatigue recognition using support vector machine

A drowsiness and fatigue problems among the drivers are the main factor that contributes to road accidents. These problems are vital to be resolved as they could contribute to damage of road facilities, vehicles and most importantly the loss of lives. In avoiding these matters, a proper mechanism is needed to alert the driver to stay awake throughout the driving journey. Thus, this study proposed a real-time prototype for recognizing the drowsiness and fatigue face expression of the driver. The methodology of this study involves facial features detection using Viola-Jones algorithm to detect the exact position of both left and right eyes and mouth. Next, based on the detected eyes and mouth beforehand, the segmentation processes performed on both eyes and mouth using Sobel edge detection to obtain facial regions. The feature extraction phase is conducted using shape-based feature to obtain the extraction values. Support vector machine (SVM) classifier is deployed for the recognition task. A total of 100 images are used during the testing stages. This study achieved a competetive result of 90.00% of accuracy. Yet, hybridization or integration of more image processing techniques will be performed in the future to improve the current accuracy obtained.
Parasitic nematodes simultaneously suppress and benefit from coccidian coinfection in their natural mouse host

Abstract Within-host interactions among coinfecting parasites are common and have important consequences for host health and disease dynamics. However, these within-host interactions have traditionally been studied in laboratory mouse models, which often exclude important variation and use unnatural host–parasite combinations. Conversely, the few wild studies of within-host interactions often lack knowledge of parasite exposure and infection history. Here we exposed laboratory-reared wood mice (Apodemus sylvaticus) that were derived from wild-caught animals to two naturally-occurring parasites (nematode: Heligmosomoides polygyrus, coccidia: Eimeria hungaryensis) to investigate the impact of coinfection on parasite infection dynamics, and to determine if the host immune response mediates this interaction. Coinfection led to delayed worm expulsion and prolonged egg shedding in H. polygyrus infections and lower peak E. hungaryensis oocyst burdens. By comparing antibody levels between wild and colony-housed mice, we also found that wild mice had elevated H. polygyrus-IgG1 titres even if currently uninfected with H. polygyrus. Using this unique wild-laboratory system, we demonstrate, for the first time, clear evidence for a reciprocal interaction between these intestinal parasites, and that there is a great discrepancy between antibody levels measured in the wild vs those measured under controlled laboratory conditions in relation to parasite infection and coinfection.
Interdistrict School Choice: A Theory of Student Assignment

Interdistrict school choice programs—where a student can be assigned to a school outside of her district—are widespread in the US, yet the market-design literature has not considered such programs. We introduce a model of interdistrict school choice and present two mechanisms that produce stable or efficient assignments. We consider three cate- gories of policy goals on assignments and identify when the mechanisms can achieve them. By introducing a novel framework of interdistrict school choice, we provide a new avenue of research in market design.