Miracle-dz/UniFAR-FTUs huggingface dataset:
Dog and Cat Contact as Risk Factor for Human Toxocariasis: Systematic Review and Meta-Analysis

Toxocariasis, a neglected parasitic zoonosis with worldwide distribution, has been reportedly associated to different risk factors in several epidemiological and meta-analysis studies. However, dog and cat contact (environmental and animal exposure) as isolated associated risk factor for children and adults remains to be fully established. Accordingly, the present meta-analysis has aimed to directly assess dog and cat contact for toxocariasis seropositivity in under-18 and adult persons, using a survey strategy of PubMed/Medline, Embase, Scopus and Scielo Databases, from January 2009 to December 2021. A meta-analysis model of random effects was applied to estimate odds ratio (OR) with 95% Confidence Interval (CI). The statistical heterogeneity was evaluated by the Cochran Q-Test and I2 values. A total of 41 transversal studies (n = 20.515 individuals) from different geographic regions (classified by the World Health Organization) were included herein. In overall, 1,882/13,496 (13.95%; 95% IC = 13.4–14.5) youngers and 513/7.019 (7.3%; 95% CI = 6.7–7.9) adults in contact with dogs or cats were serologically reagent for anti-Toxocara antibodies. Association of dog and cat contact was observed only in youngers, with both dogs (OR = 1.53; p < 0.0001) and cats (OR = 1.64; p = 0.0001). In addition, association of dog and contact and serology was statistically significant in populations of Americas (OR = 1.37; 95% CI = 1.1–1.7), Middle East (OR = 2.9; 95% CI = 1.6–5.1) and West Pacific (OR = 1.6; 95% IC = 1.3–1.9). In conclusion, contact with dogs and cats, particularly by younger individuals and in regions such as Americas, Middle East, and West Pacific, should be always a public health concern for toxocariasis. Moreover, dogs and cats should be periodically dewormed, washed and hair cleaned prior to contact with youngers. Finally, robust statistical results herein may serve as basis for future strategies and preventive measures for safer dog and cat contact.
Comparative analysis of machine learning methods to detect fake news in an Urdu language corpus

Wide availability and large use of social media enable easy and rapid dissemination of news. The extensive spread of engineered news with intentionally false information has been observed over the past few years. Consequently, fake news detection has emerged as an important research area. Fake news detection in the Urdu language spoken by more than 230 million people has not been investigated very well. This study analyzes the use and efficacy of various machine learning classifiers along with a deep learning model to detect fake news in the Urdu language. Logistic regression, support vector machine, random forest (RF), naive Bayes, gradient boosting, and passive aggression have been utilized to this end. The influence of term frequency-inverse document frequency and BoW features has also been investigated. For experiments, a manually collected dataset that contains 900 news articles was used. Results suggest that RF performs better and achieves the highest accuracy of 0.92 for Urdu fake news with BoW features. In comparison with machine learning models, neural networks models long short term memory, and multi-layer perceptron are used. Machine learning models tend to show better performance than deep learning models.
The Footprint of Kynurenine Pathway in Cardiovascular Diseases

Kynurenine pathway is the main route of tryptophan metabolism and produces several metabolites with various biologic properties. It has been uncovered that several cardiovascular diseases are associated with the overactivation of kynurenine pathway and kynurenine and its metabolites have diagnostic and prognostic value in cardiovascular diseases. Furthermore, it was found that several kynurenine metabolites can differently affect cardiovascular health. For instance, preclinical studies have shown that kynurenine, xanthurenic acid and cis-WOOH decrease blood pressure; kynurenine and 3-hydroxyanthranilic acid prevent atherosclerosis; kynurenic acid supplementation and kynurenine 3-monooxygenase (KMO) inhibition improve the outcome of stroke. Indoleamine 2,3-dioxygenase (IDO) overactivity and increased kynurenine levels improve cardiac and vascular transplantation outcomes, whereas exacerbating the outcome of myocardial ischemia, post-ischemic myocardial remodeling, and abdominal aorta aneurysm. IDO inhibition and KMO inhibition are also protective against viral myocarditis. In addition, dysregulation of kynurenine pathway is observed in several conditions such as senescence, depression, diabetes, chronic kidney disease (CKD), cirrhosis, and cancer closely connected to cardiovascular dysfunction. It is worth defining the exact effect of each metabolite of kynurenine pathway on cardiovascular health. This narrative review is the first review that separately discusses the involvement of kynurenine pathway in different cardiovascular diseases and dissects the underlying molecular mechanisms.
Retrospective Evaluation of Method of Treatment, Laboratory Findings, and Concurrent Diseases in Dairy Cattle Diagnosed with Left Displacement of the Abomasum during Time of Hospitalization

Simple Summary Left displacement of the abomasum (LDA) is a common disease in high-producing dairy cattle, resulting in direct and indirect costs, discomfort for the cattle, and death if not treated. The objectives of this retrospective study were to assess the effect of treatment on recovery from LDA during time of hospitalization, to investigate the influence of concurrent diseases on the recovery, and to identify prognostic indicators in laboratory findings. Neither the number of concurrent diseases nor the method of surgery had any influence on the outcome (death or recovery). The most common concurrent disease was metritis/endometritis (38.4% of cows). Conservative treatment (abomasal rolling) was successful in 92.8% of cows, with a recurrence rate of 56.7%. Neither oral nor analgesic therapy had any influence on the recurrence of LDA following abomasal rolling during hospitalization. In cows undergoing surgery, endoscopic abomasopexy as described by Janowitz and right flank laparotomy were performed most often (40.8% and 40.2%, respectively). A significantly (p < 0.01) higher number of cows showed the outcome “recovery” compared with “death”. The results of this study indicate that the outcome after surgery for LDA under clinical conditions does not depend on the method of surgery, and that concurrent diseases are often diagnosed in cattle with LDA. Conservative treatment has a high recurrence rate. Abstract Left displacement of the abomasum (LDA) is a disease often diagnosed in high-producing dairy cattle, resulting in direct and in indirect costs for the farmer, and discomfort and death for the cows. For the present retrospective study, the aims were to assess the effect of treatment on recovery during the time of hospitalization of the cows, to investigate the influence of concurrent diseases on the recovery, and to identify prognostic indicators in laboratory findings. Metritis/endometritis (38.4% of cows) was the concurrent disease diagnosed most often. Conservative treatment (abomasal rolling) was performed successfully in 92.8% of cows; the recurrence rate was 56.7%. Neither treatment with an oral drench nor treatment with analgesics had any influence on the recurrence of LDA following abomasal rolling during hospitalization. Endoscopic abomasopexy as described by Janowitz was performed more often than right flank laparotomy (40.8% and 40.2%, respectively). A significantly (p < 0.01) higher number of cows had the outcome “recovery” compared with “death”. The results of this study show that the outcome after surgery for LDA under clinical conditions does not depend on the method of surgery. Moreover, cows with LDA often suffer from concurrent diseases. If conservative treatment is decided on, farmers should be informed that there is a high recurrence rate, and other treatment options should be discussed.
Genome sequence of the necrotrophic plant pathogen , Pythium ultimum , reveals original pathogenicity mechanisms and effector repertoire

C ANDRE Levesque (LevesqueCA@AGR.GC.CA) Henk Brouwer (h.brouwer@cbs.knaw.nl) Liliana Cano (liliana.cano@sainsbury-laboratory.ac.uk) John P Hamilton (Hamilton@plantbiology.msu.edu) Carson Holt (carson.holt@utah.edu) Edgar Huitema (e.huitema@dundee.ac.uk) Sylvain Raffaele (sylvain.raffaele@sainsbury-laboratory.ac.uk) Gregg P Robideau (RobideauG@AGR.GC.CA) Marco Thines (thines@uni-hohenheim.de) Joe Win (Joe.Win@bbsrc.ac.uk) Marcelo M Zerillo (Marcelo.Zerillo@colostate.edu) Gordon W Beakes (g.w.beakes@ncl.ac.uk) Jeffrey L Boore (Jlboore@calmail.berkeley.edu) Dana Busam (dbusam@jcvi.org) Bernard Dumas (dumas@scsv.ups-tlse.fr) Steve Ferriera (sferriera@jcvi.org) Susan I Fuerstenberg (sifuerst@GenomeProjectSolutions.com) Claire MM Gachon (claire.gachon@sams.ac.uk) Elodie Gaulin (gaulin@scsv.ups-tlse.fr) Francine Govers (francine.govers@wur.nl) Laura Grenville-Briggs (l.grenville-briggs@abdn.ac.uk) Neil Horner (neil.horner@anu.edu.au) Jessica Hostetler (Jessicah@jcvi.org) Rays HY Jiang (rjiang@broad.mit.edu) Justin Johnson (jhjohnsn@gmail.com) Theerapong Krajaejun (mr_en@hotmail.com) Haining Lin (linha@msu.edu) Harold JG Meijer (Harold.Meijer@wur.nl) Barry Moore (bmoore@genetics.utah.edu) Paul Morris (pmorris@bgsu.edu) Vipaporn Phuntmart (vphuntu@bgsu.edu) Daniela Puiu (dpuiu@umiacs.umd.edu) Jyoti Shetty (jshetty@jcvi.org) Jason E Stajich (jason.stajich@ucr.edu) Sucheta Tripathy (sutripa@vbi.vt.edu) Stephan Wawra (s.wawra@abdn.ac.uk) Pieter van West (p.vanwest@abdn.ac.uk) Brett R Whitty (whitty@msu.edu) Pedro M Coutinho (pedro.coutinho@afmb.univ-mrs.fr) Genome Biology
Application of Virtual Reality Technology in the Restoration of Architectural Decoration Space

This paper investigates the application method of architectural decoration space transformation construction, constructs the architectural decoration model based on virtual reality technology, realizes the three-dimensional display of architectural decoration space structure, and optimizes the construction of architectural decoration space transformations in order to solve the unreasonable problem of architectural decoration space combined with virtual reality technology. The experimental results show that using virtual reality technology in the construction of architectural decoration space transformation can better ensure the rationality of building structure and improve the construction efficiency of architectural decoration space transformation, thereby simplifying the space transformation process and improving space transformation quality.
The Influence of Parents’ Nutritional Education Program on Their Infants’ Metabolic Health

Childhood obesity is considered an epidemic in both developing and developed countries. Children obesity plays a vital role in children’s development and has a profound impact on their health in adult life. Although the etiology of obesity is multifactorial, it can be prevented. According to research, feeding practices, developing eating habits, and parenting styles are of primary importance. Despite the widespread access to information on children’s nutrition, parents still make many mistakes preparing their meals. Thus, this study aimed to evaluate the impact of parents’ nutritional education on children’s selected anthropometric-metabolic parameters during their first year of life. The study comprised a group of parents of 203 Polish infants. Their parents were randomly assigned to one of two groups: the intervention group received intensive mobile nutritional education for a year, while the control group received no intervention. Blood tests and anthropometric measures were performed on both groups at the beginning of the study and one year later. Our study showed that parental nutritional education influences, among others. the BMI Z-score (the difference between the groups was 1.039) and the TG/HDL ratio (p < 0.001) in children. The final results of our study showed that proper nutritional education could improve children’s nutritional status at the population level.
Informing water harvesting technology contract design using choice experiments

Introducing water harvesting technology is expected to be more effective and last longer if farm households are involved in their design. The main objective of this study is to inform policymakers in Ethiopia about the most important terms and conditions to incentivize farmers to enter into a contractual agreement to invest in water harvesting on their land. In order to test the influence of the way the specific contractual terms and conditions are communicated to farm households, many of whom are illiterate, a split sample approach is applied with and without visual aids for technical, institutional, and economic contract characteristics. Both samples generate significantly different results, highlighting the importance of how information is conveyed to farm households. This pattern is confirmed when examining the self‐reported importance attached to the various contract characteristics. Equality Constrained Latent Class models show that contract characteristics for which visual aids were developed are considered more attentively, emphasizing the importance of adequate communication tools in a developing country context where literacy rates are limited to increase water technology innovation uptake and reduce farm household vulnerability to droughts.
Interaction Task Motion Learning for Human–Robot Interaction Control

Traditional applications of robot manipulators are mainly limited to tracking control tasks, in which the desired objectives are specified as desired positions or trajectories. In such applications, a convenient and easy way of programming robots is the traditional teach-and-playback method. However, advances in sensing and robotic technologies have led to the requirements of more demanding tasks, in which robots may need to interact with a human or follow the human’s instructions in performing a sequence of more complex tasks. In such applications, it is not sufficient to just learn the positions or motion and play it back using a robot controller. In this article, a task learning approach is proposed for human–robot interaction systems, where a set of interaction behaviors is formulated and solved by specifying the task requirements in terms of potential energy. The motion behaviors demonstrated by humans can thus be acquired by the robot by seeking the appropriate task parameters of the dynamic potential energy function. To play back and combine the tasks in a sequential way by using a single controller, a new robot controller is also proposed. Lyapunov-like analysis is adopted to guarantee the stability of the control system, and experimental results are given to validate the performance of the proposed learning and control strategies.
Psychotherapists’ experience of the transition to telepsychotherapy amidst COVID-19 in India

ABSTRACT Since the onset of COVID-19, the provision of psychotherapy services has shifted online. Thus, telepsychotherapy has been the focus of much research to document therapists’ experiences; however, it has been mainly quantitative. In the Indian context, no known empirical research has focused on the implications of this transition on psychotherapists. Therefore, the present paper presents an in-depth idiographic study exploring psychotherapists’ experiences in India, who had to transition to telepsychotherapy rapidly. Ten novice psychotherapists providing clinical services virtually were individually interviewed. The transcripts were analysed using interpretative phenomenological analysis. The main themes that emerged from the analysis were: negative impact on therapeutic process, detrimental effect on personal and professional self, positive impact of telepsychotherapy for therapist and, strategies for helping the adjustment to telepsychotherapy practice. The idiographic and psychological focus enabled a detailed exploration of the profound impact the sudden transition had on novice psychotherapists’ work with clients and their self-efficacy. Despite contextual constraints faced by the psychotherapy profession in India, the participants demonstrated creative ways of working around the challenges encountered during telepsychotherapy. Nonetheless, their experiences highlight the need to initiate training programs in telepsychotherapy.
Perceived ownership of urban parks: The role of the social environment

Abstract Prior studies have provided evidence that park user characteristics and park social context can contribute to a sense of park ownership. However, less is known about the collective contributions of these constructs to perceived park ownership. Therefore, we examined how park proximity to residential neighborhoods, frequency of park use, social cohesion, social capital, and social motivation are related to perceived park ownership. Visitor data (n = 493) were collected within two urban parks in Philadelphia, Pennsylvania. Path analysis indicated that park proximity, frequency of use, social cohesion, informal social control, and social motivations were significantly associated with perceived ownership of park spaces. Moreover, park proximity was positively related to perceived park ownership through social cohesion, informal social control, and social motivation. Our results highlight the critical role of the park social environment in shaping perceived ownership and the need for purposive action aimed at its modification in future park renovation and design concepts.
The permanent or transitory nature of shocks to tourism expenditures and receipts: Evidence from new panel stationarity tests with breaks and factors

Tourism expenditures and receipts are an important component of many countries’ balance of payments. Indeed, the determination of whether shocks to tourism expenditures and receipts are permanent or transitory in nature is relevant to understanding the appropriate policy response. This study introduces new panel stationarity tests that simultaneously model structural breaks and a common factor structure. The results from several panel stationarity tests including the new tests reject the null hypothesis of stationarity for the panel of 63 countries. Based on tests of stationarity with a common factor structure without structural breaks at the individual country level, the null hypothesis of stationarity is rejected in 24 and 26 countries with respect to per capita international tourism expenditures and tourism receipts, respectively. The inclusion of the Fourier approximation for smooth structural breaks alongside the common factor structure increases the number of rejections of the null hypothesis of stationarity to 48 and 54 countries for per capita international tourism expenditures and receipts, respectively. Hence, shocks to either tourism expenditures or receipts will likely be permanent in nature requiring a policy response in order to return tourism expenditures and receipts to their original trend path. JEL Codes: Z32, C33.
The complete mitochondrial genome of the Riparia riparia (Passeriformes: Hirundinidae)

Abstract The Sand Martin (Riparia riparia) belongs to Hirundinidae. In this study, the complete mitochondrial genome of R. riparia was sequenced and characterized. The genome was 17,963 bases in length (GenBank accession no. OK537984) including 13 protein-coding genes, two ribosomal RNA (rRNA) genes, 22 transfer RNA (tRNA) genes, and two control regions. The overall base composition of R. riparia mitogenome was 30.5% for A, 31.8% for C, 14.5% for G, and 23.2% for T. Phylogenetic analysis revealed that R. riparia was genetically closest to the species of genus Tachycineta. R. riparia mitogenome could contribute to our understanding of the phylogeny and evolution of this species.
A 16–43 GHz low-noise amplifer with 2.5–4.0 dB noise figure

This paper presents an ultra-broadband low-noise amplifier (LNA) operating from 16 to 43 GHz in a 0.25 pm SiGe:C BiCMOS technology. Across this band, the LNA achieves simultaneous low-noise performance (2.5–4.0 dB) and power matching (S11 < −10 dB) using dual-LC tank matching. The measured minimal noise figure is 2.5 dB at 26 GHz with an average value of 3.25 (±0.75) dB from 16 to 44 GHz. The best gain is 10.5 dB at 26 GHz with a 3-dB gain bandwidth from 16 to 43 GHz (90% fractional bandwidth). The measured input 1-dB compression point and input IP3 are better than −8.5 dBm and 1.8 dBm over the 16–43 GHz band, respectively, for a total power consumption of 24 mW.
Structure of Amorphous (Ge,Si)_{1-x}Y_{x} Alloys

I propose kinetically determined topological models of lightly doped ($x\ensuremath{\lesssim}0.05$) amorphous ${(\mathrm{G}\mathrm{e},\mathrm{S}\mathrm{i})}_{1\ensuremath{-}x}{Y}_{x}$ alloys ($Y=\mathrm{H},\mathrm{F},\mathrm{B},\mathrm{P},\dots{}$). Without adjustable parameters the model relates the lowest concentration ${{x}_{\mathrm{H}}}^{0}$ of hydrogen atoms required to quench paramagnetic dangling bonds to the concentration ${c}_{0}$ of unpaired spins at $x=0$. Also discussed are the structural differences between freshly evaporated $\ensuremath{\alpha}$-(Ge, Si) and various stages of ion-bombarded ("amorphized") crystalline material.
Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow

Current development in precision agriculture has underscored the role of machine learning in crop yield prediction. Machine learning algorithms are capable of learning linear and nonlinear patterns in complex agro-meteorological data. However, the application of machine learning methods for predictive analysis is lacking in the oil palm industry. This work evaluated a supervised machine learning approach to develop an explainable and reusable oil palm yield prediction workflow. The input data included 12 weather and three soil moisture parameters along with 420 months of actual yield records of the study site. Multisource data and conventional machine learning techniques were coupled with an automated model selection process. The performance of two top regression models, namely Extra Tree and AdaBoost was evaluated using six statistical evaluation metrics. The prediction was followed by data preprocessing and feature selection. Selected regression models were compared with Random Forest, Gradient Boosting, Decision Tree, and other non-tree algorithms to prove the R2 driven performance superiority of tree-based ensemble models. In addition, the learning process of the models was examined using model-based feature importance, learning curve, validation curve, residual analysis, and prediction error. Results indicated that rainfall frequency, root-zone soil moisture, and temperature could make a significant impact on oil palm yield. Most influential features that contributed to the prediction process are rainfall, cloud amount, number of rain days, wind speed, and root zone soil wetness. It is concluded that the means of machine learning have great potential for the application to predict oil palm yield using weather and soil moisture data.