Miracle-dz/UniFAR-FTUs huggingface dataset:
ÉTUDE STRUCTURALE ET DYNAMIQUE PAR RÉSONANCE MAGNÉTIQUE NUCLÉAIRE, D'UNE PROTÉINE DE TRANSFERT DE LIPIDES ISOLÉE DANS LE TABAC

La LTP1 extraite de feuille de Nicotiana tabacum, nommee LTP1_1, a ete produite dans Pichia pastoris. Nous avons ainsi determine sa structure tridimensionnelle par RMN 2D, 3D et modelisation moleculaire. Differentes etudes d'interaction et de dynamique ont ensuite mis en evidence des proprietes de fixation particulieres comparativement aux autres LTPs. Ces travaux ont servi de base a la determination de structures d'autres LTP1 de tabac par modelisation comparative et a des simulations de dynamique moleculaire a temperature ambiante et a haute temperature. De plus, nous avons cartographie la cavite hydrophobe de la LTP1_1 en utilisant la RMN du xenon hyperpolarise. L'ensemble de ces travaux a permis d'identifier les acides amines impliques specifiquement dans la fixation des lipides. Nous avons decouvert que les proprietes remarquables de fixation des LTP1 sont liees non seulement a leur structure originale mais egalement a leur dynamique particuliere.
Multi-Stream Deep Architecture for Surgical Phase Recognition on Multi-View RGBD Videos

With the increasing volume of surgeries and the advancement in medicine and technology, having a context-aware system (CAS) is becoming a necessity in the operating room (OR). By understanding the surrounding physical environment, a CAS will allow the possibility to improve OR scheduling, to design context-sensitive user interfaces, and to develop the automatic transcription of medical procedures. In this paper, we address one of the essential components of a CAS, namely the ability to recognize surgical phases during a surgical procedure. Here, we focus on performing this recognition task on vertebroplasty procedures recorded by a ceiling-mounted multi-view RGBD camera system. Instead of using hand-crafted visual features, we propose to learn multi-modal visual features using deep learning techniques. We design a neural network architecture which takes RGB, depth, and motion images as input and computes a visual feature representation shared among the modalities. Using this network, visual features are then extracted and passed to a recognition pipeline, which consists of SVM and HHMM. This pipeline is used to enforce the temporal constraints from surgical workﬂow into the recognition process. To investigate the performance and generalizability of the network, we perform the task on two new multi-view RGBD datasets, capturing in total 37 surgeries performed in two diﬀerent hybrid ORs. Through an extensive comparison with other visual features, we show that the features extracted from the proposed network yield state-of-the art results for this recognition task.
Incorporating toxicokinetics and toxicodynamics in metal bioavailability models using Enchytraeus crypticus

Metal toxicity is usually determined at a fixed time point, which may bias the assessment of risks associated with varied exposure time. Time-dependent accumulation and toxicity of nickel in the potworm Enchytraeus crypticus were investigated in solutions embedded in an inert quartz sand matrix. Internal Ni concentration and mortality were determined at seven different time intervals and interpreted from the perspective of toxicokinetics and toxicodynamics. A one-compartment model was used to describe the uptake and elimination kinetics of Ni. At each exposure concentration, Ni concentration in the organisms increased with increasing exposure time, reaching equilibrium after approximately 14 d. Median lethal concentration (LC50) decreased with time and reached an ultimate value of 0.182 mg/L. LC50 values expressed as internal Ni concentrations (LC50inter) were almost constant (16.7 mg/kg body dry weight) at each exposure time. The LC50inter was independent of exposure time, suggesting that internal concentration was a better indicator of Ni toxicity than external concentration. Uptake rate constant was 11.9 L/kg/d and elimination rate constants were 0.325 per day (based on internal concentration) and 0.070 per day (based on survival), indicating not all internal Ni contributes to toxicity. The present study highlights the importance of taking time into account in future toxicity testing and risk assessment practices. Erkai He & Cornelis A.M. Van Gestel Environmental Toxicology and Chemistry, 2013, 32: 1835–1841
A Comparative Study of Reinforcement Learning Agents on Non-Stationary Bus Schedule

We are living in a highly non-stationary world where we learn to adapt to the changes in dynamics. Besides human, there are robots on the streets interacting with the world. In this paper, I introduce Bus Gridworld, composed of bus route and walking path which a novel way of creating a non-stationary environment in tabular setting, that can be used to test the adaptability of the agents on the non-stationary environment. The result shows that Dyna-Q and Dyna-Q+ agents adapt well to the non-stationary environment, and Sarsa agent also works well when promoted to explore at the time the environment changed.
Intermittent energy restriction vs. continuous energy restriction on cardiometabolic risk factors in patients with metabolic syndrome: a meta-analysis and systematic review

Background This is a systematic review and meta-analysis to compare the efficacy of intermittent energy restriction (IER) vs. continuous energy restriction (CER) on weight loss, body composition, blood pressure, and other cardiometabolic risk factors in patients with metabolic syndrome (MetS) risk factors. Methods We searched and screened PubMed, Embase, Cochrane Library, and Web of Science from inception to May 8, 2022 for randomized controlled trials. Two review authors independently selected studies, extracted data, assessed quality and risk of bias and cross-checked extracts to resolve discrepancies when required. We expressed effect size as mean difference (MD) and 95% confidence interval (CI). The major outcome was the improvement of MetS risk factors, including changes in waist circumference (WC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-c), blood pressure (BP), and fasting plasma glucose (FPG) levels. The secondary outcomes were body weight (BW), body mass index (BMI), body fat (BF), fat free mass (FFM), hip circumference (HC), fasting insulin (FINs), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-c). Results The meta-analysis included 16 articles (20 trials) with a total of 1,511 participants. All studies had a low risk of bias for random sequence generation. The IER and CER intervention equally improved MetS risk factors WC (MD = −0.47, 95% CI [−1.19, 0.25]), TG (MD = −0.02 mmol/L, 95% CI [−0.11, 0.07]), FPG (MD = −0.02 mmol/L, 95% CI [−0.10, 0.05]) and BP (systolic blood pressure: MD = 0.93 mmHg, 95% CI [−2.74, 4.61]; diastolic blood pressure: MD =1.15 mmHg, 95% CI [−0.24, 2.55]), but HDL-c (MD = 0.03 mmol/L, 95% CI [0.01, 0.05]) was significant improved in IER when compared with CER. For second outcomes, BW (MD = −0.8 kg, 95% CI [−1.26, −0.33]), BF (MD = −0.75 kg, 95% CI [−1.73, −0.13]) and FFM (MD = −0.49 kg, 95% CI [−0.92, −0.05]) were also significant improved in IER, and not for other outcomes. Conclusion Both IER and CER could improve MetS biomarkers, but IER was more effective than CER in the improvement of HDL-c only. For secondary outcomes, IER was also more effective for BW, BF and FFM, but there were no differences in effects for other outcomes.
Impact of uncertainty in behavioural factors on irrigation demands

In this paper, analyses of uncertainty in the results of modelling irrigation demands in two irrigation areas are presented. The Next GENeration IRRigation (NGenIrr) demand model has been used for the analyses. This model incorporates behavioural and biophysical irrigation demand factors and associated uncertainties. On-farm decision making is represented using compromise programming, where tradeoffs between conflicting objectives are modelled, e.g. when deciding on crop areas at the start of an irrigation season, the model chooses crop mixes that achieve a compromise between maximising gross margins and minimizing risk of suffering a water shortage during the season. In the NGenIrr model, behavioural factors affect crop areas and irrigation scheduling. Biophysical factors affect crop water usage, soil water balances and on-farm storage volumes. Several irrigation seasons with varying climatic and water availability conditions were simulated for Shepparton and Coleambally Irrigation Districts. After establishing satisfactory performance of the model for the two districts, the uncertainties in behavioural and biophysical parameters were each varied systematically. The measure used to determine the effects of these changes was the number of observed data points remaining outside the 90% confidence interval of the model outputs. The modelling results show that the contribution of uncertainty in demand estimates from uncertainty in behavioural and biophysical parameters are likely to vary from region to region. In annual cropping regions, uncertainty in human behavioural factors can play a more important role than uncertainty in biophysical factors. Thus for the Coleambally Irrigation District, where annual cropping dominates, the uncertainty in behavioural factors contributed more to the uncertainty in demand estimates. However, in the Shepparton Irrigation District, which is dominated by perennial and horticultural crops, uncertainty in biophysical factors can account for most of the uncertainty in irrigation demand estimates. The results for both districts showed that with minimal modelling uncertainty the number of points outside the 90% confidence interval was quite high: 43 and 47 for Shepparton and Coleambally respectively (out of 60 points). For Shepparton, the number of outlying points decreases asymptotically to 19 as more and more uncertainty is added to the model. For Coleambally, the number of outlying points decreases to 5.
Understanding the motivation process of the players experiencing homelessness in the Homeless World Cup

Homeless World Cup (HWC) program contributes to supporting and inspiring homeless people in order to positively change their own lives. There has been diverse research on the HWC, but most have emphasized outcomes. An effort for understanding of specific motivation process still remains scarce. Therefore, the purpose of this study is to understand the motivational process of the participants and describe the process in view of ERG theory. For the study, qualitative approach is conducted with using semi-structured interview. Findings show that the motivation could be thought as a result of their feeling of security, self-esteem and the desire to achieve their goals. Their behavioral changes toward others are related with the satisfied their psychological basic needs, and existence needs seemed to be based on the social relationship. In spite of several limitations, the findings give a chance to consider about how the HWC program should be developed.
Genome-wide analysis of the MADS-box gene family involved in salt and waterlogging tolerance in barley (Hordeum vulgare L.)

MADS-box transcription factors are crucial members of regulatory networks underlying multiple developmental pathways and abiotic stress regulatory networks in plants. Studies on stress resistance-related functions of MADS-box genes are very limited in barley. To gain insight into this gene family and elucidate their roles in salt and waterlogging stress resistance, we performed genome-wide identification, characterization and expression analysis of MADS-box genes in barley. A whole-genome survey of barley revealed 83 MADS-box genes, which were categorized into type I (Mα, Mβ and Mγ) and type II (AP1, SEP1, AGL12, STK, AGL16, SVP and MIKC*) lineages based on phylogeny, protein motif structure. Twenty conserved motifs were determined and each HvMADS contained one to six motifs. We also found tandem repeat duplication was the driven force for HvMADS gene family expansion. Additionally, the co-expression regulatory network of 10 and 14 HvMADS genes was predicted in response to salt and waterlogging stress, and we proposed HvMADS11,13 and 35 as candidate genes for further exploration of the functions in abiotic stress. The extensive annotations and transcriptome profiling reported in this study ultimately provides the basis for MADS functional characterization in genetic engineering of barley and other gramineous crops.
A Snapshot of Mental Health and Wellness of Engineering Students Across the Western United States

This work in progress research paper characterizes mental wellness in engineering at five institutions across the Western United States to better understand what mental health issues most affect the broader engineering student community. Anecdotal evidence has long suggested that stress and certain mental wellness issues are particularly acute in the field of Engineering, and some recent research has shown elevated rates of mental wellness issues at different institutions around the country. This paper presents the results of a previously validated mental health survey conducted with first– and second–year students at several universities. The results of this work include screening rates for major mental health issues (e.g. DSM diagnosable) and moderate mental health issues as captured by the Kessler 6 screening instrument; screening rates for depressive, anxiety, and eating disorders as measured by the Patient Health Questionnaire (PHQ); and screening rates for post-traumatic stress disorder (PTSD) as measured by the Primary-Care Post Traumatic Stress Disorder (PC-PTSD) instrument. This work also includes a preliminary analysis of screen rates by demographic groups so that educators and academic facilitators may be better aware of the types of challenges that face a diverse engineering student populace. Overall, we find that 28.4% percent of respondents potentially suffer from a diagnosable mental health condition as measured by Kessler 6. We also find that an additional 55.2% of students screen positive for moderate psychological distress. Breaking measurements down by demographic groups, we find that female respondents, particularly those from historically excluded ethnic groups and races, show elevated rates of Panic and PTSD disorders when compared to the male population.
The Usage of Physiotherapeutic Intervention to Improve the Function Ability of the Upper Limb

Introduction Clinical study has tested usage robotic-assisted therapy to improve movements of the upper limb in children and adolescents with cerebral palsy (CP). Cerebral palsy is the commonly used name for a group of conditions characterised by motor dysfunction due to non-progressive brain damage early in life [1]. CP is one of the most common disabilities in childhood and makes heavy demands on families, children, and health, educational, and social services [2]. The range of severity may be from total dependency and immobility to adequate abilities of talking, independent self-care and walking, running and other skills, although with some clumsy actions [1]. The most frequently cited definitions of CP are: a disorder of posture and movement due to a defect or lesion in the immature brain or a group of movement and posture disorders that are associated with progressive alteration of the immature brain during fetal or infant growth. The disorders are permanent but not invariable, and these disorders do place some limitations on daily living. CP is often associated with sensory deficits, cognition impairments, communication and motor disabilities, behavior issues, seizure disorder, pain, and secondary musculoskeletal problems. The main causes and risk factors are: multiple birth, extreme prematurity, birth asphyxia, feeding issues, prolonged hospitalization, or postnatal infection [2]. A number of people with cerebral palsy are now able to benefit from mainstream education and further education. They participate more in various activities in society. These opportunities are assisted by legislation, advances in technology and changing attitudes in their society [1]. A cure for CP, which means repair of the underlying brain damage, is not currently available; therefore, the management of children with CP usually focuses on maintaining and improving quality of life and function and preventing secondary complications. Patients with CP are at a high risk of developing musculoskeletal problems that are mainly related to physical growth, abnormal muscle tone, weakness, a lack of mobility, poor balance, and a loss of selective motor control. Treatments for CP patients depend on the specific patient’s pathology and range from physical therapy to medication and surgery [2]. When distinguishing therapeutic approaches by Abstract Background: The aim of clinical study was to investigate and compare impact of robotic assisted therapy by using virtual reality to classical kinesiotherapy improving the function abilities of upper limb.
Skip the clicker: A narrative inquiry of a professor’s ‘Teaching Toolbox’ for large class sizes

This full research paper uses narrative inquiry to examine the emergent ‘Teaching Toolbox’ of a faculty member in an electrical and computer engineering department amid the backdrop of increasing class sizes. Four years ago, this ECE department received an NSF RED grant (Revolutionizing Engineering Departments) to enact large-scale curricular and culture change in the department over five years. The work under the grant has uncovered faculty-driven pedagogies that had formerly been at the periphery of the values held by the department - but did not receive much attention prior to the award. We use narrative inquiry to investigate the experiences of one electrical and computer engineering professor through a single case study. Our case study comprises multiple reflexive interviews contextualized within the history of the department through institutional documents and department meeting notes. This work is focused on the emergent pedagogical innovations one professor has enacted to [at least] maintain, [at most] improve, class engagement and participation as class sizes have increased. These pedagogical innovations reveal the multiple ways in which a professor has adapted their teaching practice to the institutional and departmental changes brought on in the past decade.
Optimising Reinforcement learning for neural networks

– Reinforcement learning traditionally utilises binary encoders and/or linear function approximators to accomplish its Artificial Intelligence goals. The use of nonlinear function approximators such as neural networks is often shunned, due to excessive difficulties in implementation, usually resulting from stability issues. In this paper the implementation of reinforcement learning for training a neural network is examined, being applied to the problem of learning to play Tic Tac Toe. Methods of ensuring stability are examined, and differing training methodologies are compared in order to optimise the reinforcement learning of the system. TD( λ ) methods are compared with database methods, as well as a hybridised system that combines the two, which outperforms all of the homogenous systems.
Temporally Aligning Clusters of Social Media Reaction to Speech Events

— This paper describes our approach to analyzing social media response to speech events, such as the President’s State of the Union address. Our approach clusters Tweets by topic and in time, and this paper speciﬁcally focuses on analyzing the temporal dynamics of the topically clustered Tweets. We classify topical clusters as either being temporally clustered around a speciﬁc period of time or not (e.g., referring to the whole speech). For instance, a topical cluster related to a speciﬁc line in the speech is likely clustered in time as well. In contrast, a cluster about the speakers suit could be composed of Tweets written anytime during the speech. We demonstrate the approach on a number of real world data sets, and show that an analysis of these temporal dynamics can lead to a structuring of the social media responses that can support deeper analysis than just topical clustering alone.
Animal scientists and students perception toward xenotransplantation

Xenotransplantation is a burgeoning technology that could provide a solution to the shortage of organs and tissue for transplantation. It does, however, raise many moral and ethical dilemmas. The aim of this study was to evaluate the perception of veterinary students' and scientists at Lala Lajpat Rai University of Veterinary and Animal Sciences, Hisar to determine factors that affect their acceptance. The sample constituted randomly chosen scientists and students. The perception was conceptualized as positive or negative inclination towards acceptance of xenotransplantation and was assessed using a questionnaire. Mean perception about xenotransplantation score of respondents was 61.27 and the differences in mean score of scientists and students was negligible. Further, a majority of respondents were having moderate acceptance of xenotransplantation. Almost one third were having a strongly favourable perception. Educational qualification was significantly having an impact on the perception about xenotransplantation.
Different methods of embryo sexing: A review

For providing the most efficient livestock production to meet the World’s demand of food supply, predetermination of sex in the livestock offspring is nececssary. Nowadays it is a great demand to identify or predetermine the sex of offspring, which was not followed in earlier days. Latest technologies which are followed to predetrmine the sex of embryo is mainly based on the principle difference in the presence of X or Y chromosome. Different techniques or methods which are followed to pre-determine the sex of embryos are discussed in the present view. Embryo sexing will be highly necessary in case of conservation of endangered species and also in various laboratory and pet animals. Sexing of embryo will be in a great demnad for the upcoming years since it has the ability to improve the livestock production efficiency so that the global need for food will be met
A teaching proposal for the software measurement process using gamification: an experimental study

This Research to Practice Full Paper presents a proposal to teach the software measurement process from a gamification class that makes use of games elements and serious game. This class aims to encourage interaction in the classroom and thereby foster interest in the process. In addition, the proposal was applied in two classes with a total of 22 students from a Federal University in Brazil. As a result, one of the experiments yielded a level of 80% of the evaluations with positive criteria for the class using the gamification. Finally, the gamification had a positive effect on those involved when it is not only the use of game elements in a non-gaming context, but it is the intelligent use of this concept. In conclusion, the proposal helped in the teaching process of software measurement from the creation of a competitive and collaborative environment with the core in classroom interactions.