Miracle-dz/UniFAR-FTUs huggingface dataset:
Antimicrobial Resistance Profile of Staphylococcus hyicus Strains Isolated from Brazilian Swine Herds

Staphylococcus hyicus is the causative agent of porcine exudative epidermitis. This disorder affects animals in all producing countries and presents a widespread occurrence in Brazil. This study evaluated strains from a historical collection in order to detect the presence of exfoliative-toxin-encoding genes (SHETB, ExhA, ExhB, ExhC, ExhD), characterize the strains using PFGE, and determine their respective antimicrobial resistance profiles. The results obtained from the evaluation of 77 strains from 1982 to 1987 and 103 strains from 2012 reveal a significant change in resistance profiles between the two periods, especially regarding the antimicrobial classes of fluoroquinolones, amphenicols, lincosamides, and pleuromutilins. The levels of multidrug resistance observed in 2012 were significantly higher than those detected in the 1980s. It was not possible to correlate the resistance profiles and presence of genes encoding toxins with the groups obtained via PFGE. Only 10.5% of the strains were negative for exfoliative toxins, and different combinations of toxins genes were identified. The changes observed in the resistance pattern of this bacterial species over the 30-year period analyzed indicate that S. hyicus could be a useful indicator in resistance monitoring programs in swine production. In a country with animal protein production such as Brazil, the results of this study reinforce the need to establish consistent monitoring programs of antimicrobial resistance in animals, as already implemented in various countries of the world.
Vibration Control for Pivoting by Robot Hand Equipped with CAVS and FingerVision

We explore in-hand manipulation, especially pivoting, with a robot hand equipped with a contact area variable surface (CAVS) and a vision-based tactile sensor FingerVision. CAVS is a skin for robots where the surface friction coefficient passively changes according to the external force; during holding objects with a small force, the friction coefficient is low, while the friction coefficient becomes higher when increasing the holding force. FingerVision provides multimodal sensations, including force and slip distributions, and orientation of grasped objects. On our robot hand, CAVS is embedded on the surface of the fingertips, and FingerVision is installed under the CAVS skin. With this hand, we expect a gentle in-hand manipulation of objects where we properly control objects by slipping them on purpose to achieve a desired operation, however an adequate control method for such operations has been unclear. This paper focuses on the control methods of the CAVS+FingerVision hand for pivoting objects as an example of in-hand manipulation. Through the empirical comparisons, we found that a vibration control of fingertips achieves the best accuracy and outperforms a simple fuzzy control, and CAVS outperforms a usual flat skin.
Effectiveness of adjunctive low-frequency repetitive transcranial magnetic stimulation therapy over the left dorsolateral prefrontal cortex in patients with obsessive-compulsive disorder refractory to medical treatment:A double-blind, randomized clinical trial.

BACKGROUND Obsessive-compulsive disorder (OCD) is a common psychiatric disorder. The Food and Drug Administration (FDA) approved repetitive transcranial magnetic stimulation (rTMS) to treat OCD in 2018. So far, various approaches to treat this disorder have been evaluated. We evaluated the effect of adjunctive low-frequency rtMS over the left dorsolateral prefrontal cortex in patients with OCD refractory to treatment. METHODS The present clinical trial was done on 37 patients with OCD referring from the psychiatry clinic, 22 Bahman Hospital, Qazvin province, between 2018 and 2020 and patients were randomly divided into two groups. The intervention group received rTMS treatment at 1 Hz for 20 min (1200 pulses/day) over the left DLPFC area as adjunctive to the medical treatment three times a week and for five weeks, whereas those in the control group were subjected to only the sham condition plus their medical treatment. The Yale-Brown Obsessive-Compulsive Scale (Y-BOC.S) was completed by patients before the study, following sessions 5 and 10 during the intervention, at the end of the intervention, and three to six months after the intervention under the direct supervision of a psychiatrist. SPSS software version 26 was used to compare the results between the two groups. RESULTS The intervention group showed significantly lower mean Y-BOCS scores after the intervention and at follow-up (P < 0.05) and all patients of the intervention group showed significantly lower Y-BOCS scores than their own baseline scores (P < 0.05). Also, using antipsychotic agents along with the serotonergic agents yielded significantly lower scores in the intervention group at the end of the intervention (P < 0.05). All the patients were found with higher follow-up scores than their scores at the end of the intervention; however, this difference was not significant (p > 0.05). CONCLUSION Adjunctive low-frequency (1 Hz) rTMS over the left DLPFC is able to effectively reduce Y-BOCS score in OCD patients refractory to treatment following 15 sessions, and the reduction was durable even after three to six months. Using antipsychotic agents as an adjuvant with serotonergic agents was identified as a possible predictor for response to adjunctive rTMS therapy.
Mixed Reality-Based Interaction between Human and Virtual Cat for Mental Stress Management

Human–animal interaction (HAI) has been observed to effectively reduce stress and induce positive emotions owing to the process of directly petting and interacting with animals. Interaction with virtual animals has recently emerged as an alternative due to the limitations in general physical interactions, both due to the COVID-19 pandemic and, more generally, due to the difficulties involved in providing adequate care for animals. This study proposes mixed reality (MR)-based human–animal interaction content along with presenting the experimental verification of its effect on the reduction of mental stress. A mental arithmetic task was employed to induce acute mental stress, which was followed by either MR content, in which a participant interacted with virtual animals via gestures and voice commands, or a slide show of animal images. During the experiment, an electrocardiogram (ECG) was continuously recorded with a patch-type, wireless ECG sensor on the chest of the subject, and their psychological state was evaluated with the help of questionnaires after each task. The findings of the study demonstrate that the MR-based interaction with virtual animals significantly reduces mental stress and induces positive emotions. We expect that this study could provide a basis for the widespread use of MR-based content in the field of mental health.
An activity-based bottleneck model for autonomous vehicles

From the perspective of activities, this article considers the differences in commuting behavior between autonomous vehicles and regular vehicles, and studies the morning peak travel behavior in the bottleneck corridor when the two coexist. Considering that autonomous vehicles affect the value of time of commuters, the changes in commuting behavior of commuters in the morning peak are studied and the equilibrium travel mode at this time is analyzed.
Design and Characterisation of a Muscle-mimetic Dielectrophoretic Ratcheting Actuator

The high potential impact of soft robotics is hampered by a lack of actuators that combine high-force, high-work and high-power capabilities, limiting application in real-world problems. Typically, soft actuators are tuned to an application by gearing - for example, trading power for strain. An example of a recently developed soft-actuator which exploits such gearing is the dielectrophoretic liquid zipping (DLZ) actuator. DLZs can produce large strains (90$) and power densities comparable to biological muscles, but cannot achieve both in a single actuator. In this work, we introduce a muscle-mimetic DLZ ratcheting actuator (DLZ-R) that allows multiple DLZ-R heads to operate in parallel, thereby increasing force output without sacrificing stroke or power. We first characterise the effect of geometry on the performance of a 1-head DLZ-R, before demonstrating that the force, work, and power output of the DLZ-R scale linearly with the number of active DLZ heads. Next, we investigate the relationship between driving frequency and power output. Finally, we demonstrate a 12-head DLZ ratchet. We believe the DLZ-R represents a step towards soft actuators that can provide both high-work and high-power and the widespread use of soft technologies.
Cat viral diseases patern in Prof. Soeparwi Animal Hospital in 2017-2019

Feline Panleukopenia Virus (FPV), Feline Infectious Peritonitis (FIP), Feline Calici Virus (FCV), and other cat’s viral diseases were reported in Indonesia. Viral diseases that appear usually appear in each season with different intensities depending on the type of virus. The research data was taken from Animal Hospital Prof. Soeparwi’s medical record in 2017-2019 along with rainfall, humidity, and temperature data in the Yogyakarta area in 2017-2019 obtained from the Climatology and Geophysics Meteorology Agency (BMKG). Disease data are grouped by diagnosis; temperature, humidity, and rainfall data. Data analysis was performed with Microsoft Excel 2016 in the form of a frequency chart and descriptive. The results of the analysis between the incidence patterns of FPV, FIP, FCV, Feline Viral Rhinotracheitis (FVR), and Papilloma with climatic conditions in the dry and rainy season periods show patterns that vary depending on the character of the virus that causes the disease. High incidence in the rainy season is seen in FPV and FCV, for FIP the incidence of each season is almost the same in each year, whereas the incidence of FVR and Papilloma can be higher in the rainy season and sometimes also can be higher in the dry season. These findings indicate that the incidence of viral diseases in cats has a seasonally based pattern of events.
Dynamic Control Model and Logic Rule Control of Piezoelectric Actuators

A dynamic control model for piezoelectric actuators was presented. The control model is stated by pan-Boolean algebra symbol through a series of control rules depending on control practice of piezoelectric actuators. Combining with PID controller, off-line simulation with Rule and PI control was conducted in piezoelectric actuators based on the control model. The simulation results prove that the proposed control model is simple in structure, and easy to be controlled and realized.
How Sensory and Affective Attributes Describe Touch Targeting C-Tactile Fibers

When gently stroked with velocities between 0.1 and 30 cm/s, participants typically rate velocities around 3 cm/s as most pleasant, and the ratings follow an inverted u-shape. This pleasantness curve correlates often, but not always, with the firing rate of unmyelinated C-tactile (CT) afferents, leading to the notion that CT afferents code for the hedonic or emotional aspect of gentle touch. However, there is also evidence that CT firing does not necessarily equal pleasantness, and the range of attributes that CT afferents code for is not known. Here, participants were stroked with different velocities assumed to activate CT afferents to a different extent while they rated the touch on several sensory and emotional attributes. We expected an inverted u-shaped rating curve for pleasantness and other emotional attributes, but not for sensory attributes. Inverted u-shaped rating patterns were found for the emotional attributes “pleasant” and “not burdensome,” but also for the sensory attribute “rough. ” CT-directed stimulation is thus not only experienced as hedonic. The sensations arising from CTs together with all other types of mechanoreceptors might be centrally integrated into a percept that represents those aspects which are most salient for the stimulation at hand.
Variation in age, annual usage and resale price of cut-to-length machinery in different regions of Europe

ABSTRACT The high price of cut-to-length machines requires careful planning of investment in new or second-hand machines. The investment is influenced by machine usage, and is also affected by maintenance, insurance and repair costs, harvesting conditions, number of machine relocations, and availability of working opportunities and employment. In this study, age, size, annual usage and price of the cut-to-length harvesters and forwarders for sale in Europe was investigated, using sales data from the online marketplace. The average age of harvesters was 7.3 years and the average age of forwarders was 7.5 years. The newest machines were on offer in the Northern countries (6.5 and 6.1 years for harvesters and forwarders, respectively). The oldest harvesters were on offer in Western Europe (8.1 years) and Eastern Europe (8.2 years) and the oldest forwarders in Eastern Europe (9.9 years). The average annual use of both harvesters and forwarders were notably high in the Baltic and Northern countries compared to the Western and Eastern Europe. On average, the annual use was 1759 and 1913 h year−1 for the harvesters and forwarders, respectively. The average resale price of harvesters was more dependent on age than total use. For forwarders, both age and total usage had a similar explanatory value. For newer CTL machines, aged between 1 and 5 years, the bigger size class of the machine corresponded to higher price. Older machines did not exhibit such correspondence, whereas the annual usage showed high correspondence on the resale value of the machine.
Integration of genomics, transcriptomics and metabolomics identifies candidate loci underlying fruit weight in loquat

Abstract Fruit weight is an integral part of fruit quality and directly influences the commodity value and economic return of fruit crops. Despite the importance of fruit weight, its underlying molecular mechanisms remain understudied, especially for perennial fruit tree crops such as cultivated loquat (Eriobotrya japonica Lindl.). Auxin is known to regulate fruit development, but its role and metabolism during the development of loquat fruit remain obscure. In this study, we used a multi-omics approach, integrating whole-genome resequencing-based quantitative trait locus (QTL) mapping with an F1 population, population genomics analysis using germplasm accessions, transcriptome analysis, and metabolic profiling to identify genomic regions potentially associated with fruit weight in loquat. We identified three major loci associated with fruit weight, supported by both QTL mapping and comparative genomic analysis between small- and large-fruited loquat cultivars. Comparison between two genotypes with contrasting fruit weight performance by transcriptomic and metabolic profiling revealed an important role for auxin in the regulation of fruit development, especially at the fruit enlargement stage. The multi-omics approach identified homologs of ETHYLENE INSENSITIVE 4 (EjEIN4) and TORNADO 1 (EjTRN1) as promising candidates for the control of fruit weight. Three single nucleotide polymorphism (SNP) markers were also closely associated with fruit weight. Results from this study provide insights into the genetic and metabolic controls of fruit weight in loquat from multiple perspectives. The candidate genomic regions, genes, and sequence variants will facilitate our understanding of the molecular basis of fruit weight and lay a foundation for future breeding and manipulation of fruit weight in loquat.
ETA: An Efficient Training Accelerator for DNNs Based on Hardware-Algorithm Co-Optimization

Recently, the efficient training of deep neural networks (DNNs) on resource-constrained platforms has attracted increasing attention for protecting user privacy. However, it is still a severe challenge since the DNN training involves intensive computations and a large amount of data access. To deal with these issues, in this work, we implement an efficient training accelerator (ETA) on field-programmable gate array (FPGA) by adopting a hardware-algorithm co-optimization approach. A novel training scheme is proposed to effectively train DNNs using 8-bit precision with arbitrary batch sizes, in which a compact but powerful data format and a hardware-oriented normalization layer are introduced. Thus the computational complexity and memory accesses are significantly reduced. In the ETA, a reconfigurable processing element (PE) is designed to support various computational patterns during training while avoiding redundant calculations from nonunit-stride convolutional layers. With a flexible network-on-chip (NoC) and a hierarchical PE array, computational parallelism and data reuse can be fully exploited, and memory accesses are further reduced. In addition, a unified computing core is developed to execute auxiliary layers such as normalization and weight update (WU), which works in a time-multiplexed manner and consumes only a small amount of hardware resources. The experiments show that our training scheme achieves the state-of-the-art accuracy across multiple models, including CIFAR-VGG16, CIFAR-ResNet20, CIFAR-InceptionV3, ResNet18, and ResNet50. Evaluated on three networks (CIFAR-VGG16, CIFAR-ResNet20, and ResNet18), our ETA on Xilinx VC709 FPGA achieves 610.98, 658.64, and 811.24 GOPS in terms of throughput, respectively. Compared with the prior art, our design demonstrates a speedup of $3.65\times $ and an energy efficiency improvement of $8.54\times $ on CIFAR-ResNet20.
Can achievement at medical admission tests predict future performance in postgraduate clinical assessments? A UK-based national cohort study

Objective To determine whether scores on two undergraduate admissions tests (BioMedical Admissions Test (BMAT) and University Clinical Aptitude Test (UCAT)) predict performance on the postgraduate Membership of the Royal Colleges of Physicians (MRCP) examination, including the clinical examination Practical Assessment of Clinical Examination Skills (PACES). Design National cohort study. Setting Doctors who graduated medical school between 2006 and 2018. Participants 3045 doctors who had sat BMAT, UCAT and the MRCP. Primary outcome measures Passing each section of the MRCP at the first attempt, including the clinical assessment PACES. Results Several BMAT and UCAT subtest scores displayed incremental predictive validity for performance on the first two (written) parts of the MRCP. Only aptitude and skills on BMAT (OR 1.34, 1.08 to 1.67, p=0.01) and verbal reasoning on UCAT (OR 1.34, 1.04 to 1.71, p=0.02) incrementally predicted passing PACES at the first attempt. Conclusions Our results imply that the abilities assessed by aptitude and skills and verbal reasoning may be the most important cognitive attributes, of those routinely assessed at selection, for predicting future clinical performance. Selectors may wish to consider placing particular weight on scales assessing these attributes if they wish to select applicants likely to become more competent clinicians. These results are potentially relevant in an international context too, since many admission tests used globally, such as the Medical College Admission Test, assess similar abilities.
An update on the use of tolvaptan for autosomal dominant polycystic kidney disease: consensus statement on behalf of the ERA Working Group on Inherited Kidney Disorders, the European Rare Kidney Disease Reference Network and Polycystic Kidney Disease International

ABSTRACT Approval of the vasopressin V2 receptor antagonist tolvaptan—based on the landmark TEMPO 3:4 trial—marked a transformation in the management of autosomal dominant polycystic kidney disease (ADPKD). This development has advanced patient care in ADPKD from general measures to prevent progression of chronic kidney disease to targeting disease-specific mechanisms. However, considering the long-term nature of this treatment, as well as potential side effects, evidence-based approaches to initiate treatment only in patients with rapidly progressing disease are crucial. In 2016, the position statement issued by the European Renal Association (ERA) was the first society-based recommendation on the use of tolvaptan and has served as a widely used decision-making tool for nephrologists. Since then, considerable practical experience regarding the use of tolvaptan in ADPKD has accumulated. More importantly, additional data from REPRISE, a second randomized clinical trial (RCT) examining the use of tolvaptan in later-stage disease, have added important evidence to the field, as have post hoc studies of these RCTs. To incorporate this new knowledge, we provide an updated algorithm to guide patient selection for treatment with tolvaptan and add practical advice for its use.
Measurement of benefits in economic evaluations of nutrition interventions in low‐ and middle‐income countries: A systematic review

Abstract Economic evaluation of nutrition interventions that compares the costs to benefits is essential to priority‐setting. However, there are unique challenges to synthesizing the findings of multi‐sectoral nutrition interventions due to the diversity of potential benefits and the methodological differences among sectors in measuring them. This systematic review summarises literature on the interventions, sectors, benefit terminology and benefit types included in cost‐effectiveness, cost‐utility and benefit‐cost analyses (CEA, CUA and BCA, respectively) of nutrition interventions in low‐ and middle‐income countries. A systematic search of five databases published from January 2010 to September 2019 with expert consultation yielded 2794 studies, of which 93 met all inclusion criteria. Eighty‐seven per cent of the included studies included interventions delivered from only one sector, with almost half from the health sector (43%), followed by food/agriculture (27%), water, sanitation and hygiene (WASH) (10%), and social protection (8%). Only 9% of studies assessed programmes involving more than one sector (health, food/agriculture, social protection and/or WASH). Eighty‐one per cent of studies used more than one term to refer to intervention benefits. The included studies calculated 128 economic evaluation ratios (57 CEAs, 39 CUAs and 32 BCAs), and the benefits they included varied by sector. Nearly 60% measured a single benefit category, most frequently nutritional status improvements; other health benefits, cognitive/education gains, dietary diversity, food security, knowledge/attitudes/practices and income were included in less than 10% of all ratios. Additional economic evaluation of non‐health and multi‐sector interventions, and incorporation of benefits beyond nutritional improvements (including cost savings) in future economic evaluations is recommended.
Using Support Vector Machines for Facet Partitioning in Multidimensional Scaling

Abstract In this article we focus on interpreting multidimensional scaling (MDS) configurations using facet theory. The facet theory approach is attempting to partition a representational space, facet by facet, into regions with certain simplifying constraints on the regions’ boundaries (e.g., concentric circular sub-spaces). A long-standing problem has been the lack of computational methods for optimal facet-based partitioning. We propose using support vector machines (SVM) to perform this task. SVM is highly attractive for this purpose as they allow for linear as well as nonlinear classification boundaries in any dimensionality. Using various classical examples from the facet theory literature we elaborate on the combined use of MDS and SVM for facet-based partitioning. Different types of MDS are discussed, and options for SVM kernel specification, tuning, and performance evaluation are illustrated.