Miracle-dz/UniFAR-FTUs huggingface dataset:
Carcass characteristics of feedlot-finished Nellore heifers slaughtered at different weights

Carcass and meat characteristics of 48 Nellore heifers at 24 to 30 months of age, with an initial weight of 263.4 ± 13.9 kg, were evaluated. The experiment was set up as a completely randomized design with four treatments, which consisted of four slaughter-weight classes, namely <340, 340-370, 370-400, or >400 kg. Back fat thickness was not influenced (p > 0.05) by slaughter weight in any of the forms it was expressed (mm or %), averaging 5.3 mm. Loin eye area in cm2 increased (p < 0.05) with the increase in slaughter weight. Animals slaughtered at a live weight (LW) of more than 400 kg showed better (p < 0.05) carcass conformation than the other experimental groups (9.8 points). Heifers slaughtered at over 400 kg LW had a more compact (p < 0.05) carcass (1.65 cm kg-1 cold carcass). The marbling degree of meat was lower (p < 0.05) in the animals slaughtered at less than 340 kg LW. In conclusion, cull heifers must not be slaughtered at a LW of less than 340 kg and slaughter weights greater than 400 kg have positive implications on important carcass characteristics, notably conformation and marbling.
Multilevel Mesh Partitioning for Optimizing Domain Shape

Multilevel algorithms are a successful class of optimization techniques that address the mesh partitioning problem for mapping meshes onto parallel computers. They usually combine a graph contraction algorithm together with a lo-cal optimization method that refines the partition at each graph level. To date, these algorithms have been used al-most exclusively to minimize the cut-edge weight in the graph with the aim of minimizing the parallel communication overhead. However, it has been shown that for certain classes of problems, the convergence of the underlying solution algorithm is strongly influenced by the shape or aspect ratio of the subdomains. Therefore, in this paper, the authors modify the multilevel algorithms to optimize a cost function based on the aspect ratio. Several variants of the algorithms are tested and shown to provide excellent results.
Gene-environment interactions in genome-wide association studies: current approaches and new directions.

BACKGROUND Complex psychiatric traits have long been thought to be the result of a combination of genetic and environmental factors, and gene-environment interactions are thought to play a crucial role in behavioral phenotypes and the susceptibility and progression of psychiatric disorders. Candidate gene studies to investigate hypothesized gene-environment interactions are now fairly common in human genetic research, and with the shift toward genome-wide association studies, genome-wide gene-environment interaction studies are beginning to emerge. METHODS We summarize the basic ideas behind gene-environment interaction, and provide an overview of possible study designs and traditional analysis methods in the context of genome-wide analysis. We then discuss novel approaches beyond the traditional strategy of analyzing the interaction between the environmental factor and each polymorphism individually. RESULTS Two-step filtering approaches that reduce the number of polymorphisms tested for interactions can substantially increase the power of genome-wide gene-environment studies. New analytical methods including data-mining approaches, and gene-level and pathway-level analyses, also have the capacity to improve our understanding of how complex genetic and environmental factors interact to influence psychologic and psychiatric traits. Such methods, however, have not yet been utilized much in behavioral and mental health research. CONCLUSIONS Although methods to investigate gene-environment interactions are available, there is a need for further development and extension of these methods to identify gene-environment interactions in the context of genome-wide association studies. These novel approaches need to be applied in studies of psychology and psychiatry.
Expanders That Beat the Eigenvalue Bound: Explicit Construction and Applications

n and 0 < δ < 1, we construct graphs on n nodes such that every two sets of size share an edge, having essentially optimal maximum degree . Using known and new reductions from these graphs, we derive new explicit constructions of: 1. A k round sorting algorithm using comparisons. 2. A k round selection algorithm using comparisons. 3. A depth 2 superconcentrator of size . 4. A depth k wide-sense nonblocking generalized connector of size . All of these results improve on previous constructions by factors of , and are optimal to within factors of . These results are based on an improvement to the extractor construction of Nisan & Zuckerman: our algorithm extracts an asymptotically optimal number of random bits from a defective random source using a small additional number of truly random bits.
Modeling the language of life – Deep Learning Protein Sequences

Background One common task in Computational Biology is the prediction of aspects of protein function and structure from their amino acid sequence. For 26 years, most state-of-the-art approaches toward this end have been marrying machine learning and evolutionary information. The retrieval of related proteins from ever growing sequence databases is becoming so time-consuming that the analysis of entire proteomes becomes challenging. On top, evolutionary information is less powerful for small families, e.g. for proteins from the Dark Proteome. Results We introduce a novel way to represent protein sequences as continuous vectors (embeddings) by using the deep bi-directional model ELMo taken from natural language processing (NLP). The model has effectively captured the biophysical properties of protein sequences from unlabeled big data (UniRef50). After training, this knowledge is transferred to single protein sequences by predicting relevant sequence features. We refer to these new embeddings as SeqVec (Sequence-to-Vector) and demonstrate their effectiveness by training simple convolutional neural networks on existing data sets for two completely different prediction tasks. At the per-residue level, we significantly improved secondary structure (for NetSurfP-2.0 data set: Q3=79%±1, Q8=68%±1) and disorder predictions (MCC=0.59±0.03) over methods not using evolutionary information. At the per-protein level, we predicted subcellular localization in ten classes (for DeepLoc data set: Q10=68%±1) and distinguished membrane-bound from water-soluble proteins (Q2= 87%±1). All results built upon the embeddings gained from the new tool SeqVec neither explicitly nor implicitly using evolutionary information. Nevertheless, it improved over some methods using such information. Where the lightning-fast HHblits needed on average about two minutes to generate the evolutionary information for a target protein, SeqVec created the vector representation on average in 0.03 seconds. Conclusion We have shown that transfer learning can be used to capture biochemical or biophysical properties of protein sequences from large unlabeled sequence databases. The effectiveness of the proposed approach was showcased for different prediction tasks using only single protein sequences. SeqVec embeddings enable predictions that outperform even some methods using evolutionary information. Thus, they prove to condense the underlying principles of protein sequences. This might be the first step towards competitive predictions based only on single protein sequences. Availability SeqVec: https://github.com/mheinzinger/SeqVec Prediction server: https://embed.protein. properties
Convergence of the Iterates of Descent Methods for Analytic Cost Functions

In the early eighties Lojasiewicz [in Seminari di Geometria 1982-1983, Universita di Bologna, Istituto di Geometria, Dipartimento di Matematica, 1984, pp. 115--117] proved that a bounded solution of a gradient flow for an analytic cost function converges to a well-defined limit point. In this paper, we show that the iterates of numerical descent algorithms, for an analytic cost function, share this convergence property if they satisfy certain natural descent conditions. The results obtained are applicable to a broad class of optimization schemes and strengthen classical "weak convergence" results for descent methods to "strong limit-point convergence" for a large class of cost functions of practical interest. The result does not require that the cost has isolated critical points and requires no assumptions on the convexity of the cost nor any nondegeneracy conditions on the Hessian of the cost at critical points.
Space-Time block codes from orthogonal designs

We introduce space-time block coding, a new paradigm for communication over Rayleigh fading channels using multiple transmit antennas. Data is encoded using a space-time block code and the encoded data is split into n streams which are simultaneously transmitted using n transmit antennas. The received signal at each receive antenna is a linear superposition of the n transmitted signals perturbed by noise. Maximum-likelihood decoding is achieved in a simple way through decoupling of the signals transmitted from different antennas rather than joint detection. This uses the orthogonal structure of the space-time block code and gives a maximum-likelihood decoding algorithm which is based only on linear processing at the receiver. Space-time block codes are designed to achieve the maximum diversity order for a given number of transmit and receive antennas subject to the constraint of having a simple decoding algorithm. The classical mathematical framework of orthogonal designs is applied to construct space-time block codes. It is shown that space-time block codes constructed in this way only exist for few sporadic values of n. Subsequently, a generalization of orthogonal designs is shown to provide space-time block codes for both real and complex constellations for any number of transmit antennas. These codes achieve the maximum possible transmission rate for any number of transmit antennas using any arbitrary real constellation such as PAM. For an arbitrary complex constellation such as PSK and QAM, space-time block codes are designed that achieve 1/2 of the maximum possible transmission rate for any number of transmit antennas. For the specific cases of two, three, and four transmit antennas, space-time block codes are designed that achieve, respectively, all, 3/4, and 3/4 of maximum possible transmission rate using arbitrary complex constellations. The best tradeoff between the decoding delay and the number of transmit antennas is also computed and it is shown that many of the codes presented here are optimal in this sense as well.
Physical Activity and Health Beliefs among Saudi Women

Background. Physical activity (PA) is associated with health benefits and disease prevention and is often prescribed in managing many health conditions. Understanding the cultural influences is relevant in order to effectively promote PA. The objective of this study was to assess the level of PA among Saudi women, measured by daily step count, and the association between PA and health beliefs. Methods. A total of 161 eligible participants were asked to complete two questionnaires to assess health beliefs: Health Locus of Control (HLC) and Self-Efficacy Assessment Scale. Each participant was given a pedometer and a diary to record their daily PA for two weeks. Results. One hundred and five participants completed the two weeks pedometer data (mean age 26.3 ± 7.1 years, BMI 25 ± 4.2 kg/m2). The average pedometer score over two weeks was 5114 ± 2213 steps. Step count had strong correlation with self-efficacy (r s = 0.75), mild correlation with internal HLC (r s = 0.42), and mild negative correlation with external HLC (r s = −0.35). Conclusion. The study demonstrates high level of inactivity among Saudi females in reference to the international recommendation for minimum activity. The data also reveal an association between PA and health beliefs. Ultimately, such information can be used to design gender- and culture-sensitive interventions that could enhance adherence to PA.
Do online communication attitudes mitigate the association between Facebook use and relational interdependence? An extension of media multiplexity theory

Given Facebook’s popularity for the maintenance of interpersonal relationships, this investigation examined the extent to which frequency of Facebook communication with a specific friend predicts relational interdependence. The chief goal of the investigation was to extend media multiplexity theory by examining whether attitudes toward (a) online self-disclosure and (b) online social connection moderated this association. Results not only replicated previous findings that multiple media are associated with relational interdependence, but also supported the hypothesized moderation of online communication attitude. Based on these results, the manuscript explores how media multiplexity theory might be extended to account for communicator cognitions about communication media.
Can HIT Work Alone? A Security and Socio-Economic Perspective of Healthcare Quality

HIT Impact on clinical quality has been a long talking point. However, reduced effect of HIT has been proven so far. This motivated us to identify factors that might influence HIT impact and overall clinical quality. Our paper discusses the effect of security on HIT as well as the impact of socio-economic factors on clinical quality while performing predictive analysis. We observe that while socio-economic factors indeed help in quality improvement, low integration of technology and security is impacting overall effect. Our study will lead managers to consider proper technology integration and socio-economic factors for future prediction.
Effects of Acupressure on Fatigue and Depression in Hepatocellular Carcinoma Patients Treated with Transcatheter Arterial Chemoembolization: A Quasi-Experimental Study

This study was to examine the effects of acupressure on fatigue and depression in HCC patients undergoing TACE. A quasiexperimental study design was used. Patients were evaluated at five time points: before treatment (T1) and 2, 3, 4, and 5 days after treating TACE (T2, T3, T4, and T5). Fatigue and depression were assessed by a VAS fatigue scale and a VAS depression scale at each time point. TFRS and BDI were administered at T1 and T5. Patients' fatigue and depression were significantly higher at T5 than at T1 in two groups. Fatigue and depression increased in both the experimental and control groups' patients over the five days of hospitalization during which TACE and chemotherapy were administered. The experimental group had significantly less fatigue than the control group, with lower subscale scores on physical, psychosocial, daily, and overall fatigue. There were no differences between the groups on depression. At posttest, the experimental group experienced lower physical, psychosocial, daily, and overall fatigue than the control group. Acupressure can improve fatigue in HCC patients during treatment with TACE but did not alleviate depression. Discharge planning should include home care for management of fatigue and depression.
Fluoxetine for depression in diabetes: a randomized double-blind placebo-controlled trial.

OBJECTIVE Depression is prevalent in patients with diabetes. It is associated with poor glycemic control and is linked to an increased risk for diabetic complications. In this study, we assessed the efficacy of fluoxetine for depression in patients with diabetes. RESEARCH DESIGN AND METHODS Sixty patients with diabetes (type 1, n = 26; type 2, n = 34) and major depressive disorder entered an 8-week randomized placebo-controlled double-blind trial. Patients were given daily doses of fluoxetine (up to 40 mg/day). The Beck Depression Inventory (BDI) and Hamilton Rating Scale for Depression (HAMD) were used to measure the severity of depression and to determine the percentage of patients who achieved substantial improvement or complete remission. GHb levels were obtained to monitor glycemic control. RESULTS Reduction in depression symptoms was significantly greater in patients treated with fluoxetine compared with those receiving placebo (BDI, -14.0 vs. -8.8, P = 0.03; HAMD, -10.7 vs. -5.2, P = 0.01). The percentage of patients achieving a significant improvement in depression per the BDI was also higher in the fluoxetine group (66.7 vs. 37.0%, P = 0.03). Additionally, trends toward a greater rate of depression remission (48.1 vs. 25.9%, P = 0.09 per the HAMD) and greater reduction in GHb (-0.40 vs. -0.07%, P = 0.13) were observed in the fluoxetine group. CONCLUSIONS Fluoxetine effectively reduces the severity of depression in diabetic patients. Our study demonstrated that after only 8 weeks, this treatment also produced a trend toward better glycemic control.
Computer analysis of cardiovascular changes during sleep-wake cycle in Sprague-Dawley rats.

Blood pressure (BP) and heart rate (HR) were recorded in seven Sprague-Dawley rats during a total of 491 normal sleep-wake cycles with the use of a computer-assisted method developed for this study. Significant changes of BP, HR, and BP variability (BPV) were found between the three states within the cycle, i.e., wakefulness (W), slow-wave sleep (SWS), and paradoxical sleep (PS). The highest BP, BPV, and HR values were found during W. Then all cardiovascular (CV) variables fell during SWS, whereas BP and BPV rose again during PS. The fall of BPV observed during SWS was the most important CV change observed within the cycle. These state-dependent CV changes suggest that, in the rat, circulation during the sleep-wake cycle is controlled by the same central factors that operate in cats. In addition, significant BP and HR modifications between different cycles have been found. On the other hand, BP and HR differences between animals were also observed. The latter differences were found to be stable across the states, but no significant relation was found between BP and HR within any state. Thus the present data also suggest that BP and HR measurements are influenced not only by state-dependent factors but also by at least three different factors that are each independent of the state: one leads to BP and HR values that are influenced by the cycle the animal is in and the other two influence, respectively, the ranking of the individual's BP and HR levels within the population.
Postprandial lipaemia does not affect resting haemodynamic responses but does influence cardiovascular reactivity to dynamic exercise

Postprandial lipaemia impairs endothelial function, possibly by changes in oxidative stress, but whether this affects cardiac output and/or systemic vascular resistance (SVR) at rest and in response to dynamic exercise remains uncertain. The present study set out to investigate the effects of a high-fat meal (HFM) v. a low-fat, high-carbohydrate meal (HCM) on cardiac output and SVR. A HFM (50 g fat) and an isoenergetic HCM (5 g fat) were randomly fed to thirty healthy adults using a crossover design. Cardiac output, heart rate and blood pressure (BP) were measured, and stroke volume and SVR were calculated over a 3 h rest following the meal, during exercise 3 h postprandially and for 45 min post-exercise. Blood samples were collected at fasting, 3 h postprandially and immediately post-exercise. Plasma TAG increased by 63·8 % 3 h following the HFM, and NEFA fell by 94·1 % 3 h after the HCM. There was a 9·8 % rise in plasma 8-isoprostane-F2α concentration following the HFM, and a 6·2 % fall following the HCM. Cardiac output increased postprandially, but the difference between meals at rest or exercise was not statistically significant. The HFM resulted in a 3·2 mmHg (95 % CI 0·7, 5·7) smaller increase in exercise mean arterial BP compared with the HCM due to a greater fall in exercise SVR. Postprandial lipaemia induced by a HFM does not affect cardiac output and/or SVR at rest, but it blunts the increase in BP during exercise.
GRANULOMA PIOGÊNICO: RELATO DE CASO CLÍNICO-CIRÚRGICO

O granuloma piogenico e considerado um processo proliferativo reacional nao neoplasico, podendo acometer pele e mucosas. Na boca e comum em gengiva, mas pode acometer a lingua e as mucosas palatina e jugal. Clinicamente manifesta-se como uma lesao lobulada ou plana, pediculada e em alguns casos de superficie ulcerada. Como caracteristicas histologicas evidentes tem-se a presenca tecido de granulacao, em areas de proliferacao endotelial e de espacos vasculares e massas lobuladas de tecido hiperplasico. O tratamento de escolha e a exerese cirurgica acrescida de cuidados com a higiene e controle de placa bacteriana, podendo ocorrer recidivas. O presente estudo tem como finalidade apresentar um caso clinico de paciente de 40 anos de idade portador da referida lesao ha cerca de 6 meses em regiao de gengiva lingual inferior tratado cirurgicamente.
Endovascular Aneurysm Repair Using Anaconda Repositionable Aortic Stent Graft Assisted Exclusively by Intravascular Ultrasound Imaging

Arteriography with contrast medium (CM) injection is normally employed to visualise the lowest renal artery during endovascular aneurysm repair (EVAR). Intravascular ultrasound (IVUS) has been proposed as an alternative, real-time imaging diagnostic technique to arteriography. In this study, we evaluated the feasibility of EVAR using Anaconda repositionable aortic stent graft (Vascutek) assisted by IVUS (Volcano Visions, Philips) during intraluminal navigation without CM. From January 2016 to December 2017, 25 patients with infrarenal abdominal aortic aneurysms, identified through anatomical inclusion criteria, underwent EVAR. All of the patients had an arteriogram at the end of the EVAR procedure to confirm aortic stent graft patency and to exclude type 1 endoleaks. The primary objective was the technical and clinical success of this CM-free aortic stent graft delivery procedure. At the end of the period, 150 target vessels were evaluated. IVUS versus angio-CT sensitivity and specificity rate were 97.3% and 100%, respectively. The primary technical success was obtained in 88% of the cases. Three patients (12%) needed CM injection to complete the procedure and there were no cases of type 1 endoleak. Primary clinical success was 100%. During follow-up at a mean of 20 months, none of the patients died or had complications. We conclude that a full EVAR procedure is feasible using only IVUS navigation and repositionable aortic stent graft without CM injection in anatomically selected cases.
Effects of Different Anti-Stressors on Growth, Serum Chemistry and Meat Quality Attributes of Japanese Quail

The aim of the present study was to evaluate the effect of different anti-stressors on growth performance, carcass traits, bloodchemistry and meat quality attributes of broiler Japanese quail. For this purpose, a total of 1,875 quail chicks were procured and arranged according to completely randomized design, birds were divided into 5 treatment groups having 5 replicates of 75 birds each. The treatments consisted of four anti-stressors i.e., synthetic anti-stressors (Vitamin C and Betaine) and natural anti-stressors (Turmeric and Chia Seed) along with a control group. Bird’s diets were supplemented with vitamin C, betaine, turmeric and chia seed @ 600 mg/kg, 700 mg /kg, 300 mg/kg and 7,000 mg/kg, respectively. After four weeks, 10 birds per treatment were slaughtered (Halal method), de-feathered, eviscerated and their carcass traits, serum chemistry and meat quality attributes were calculated. Birds supplemented with betaine revealed significantly (p≤0.05) lower feed intake, glucose, cholesterol, H:L ratio, better weight gain, times of gain, FCR and highest anti-oxidant assay and total viable count. However, carcass traits, processing traits and blood cortisol level did not differ (p>0.05) among the treatment groups. In conclusion, addition of antistressors (especially betaine) in the diet of growing Japanese quail had positive influence on growth and serum chemistry.