Miracle-dz/UniFAR-FTUs huggingface dataset:
The Automatic Assessment of Strength and Mobility in Older Adults: A Test-Retest Reliability Study

Background: Simple field tests such as the Timed Up and Go test (TUG) and 30 s Chair Stand test are commonly used to evaluate physical function in the elderly, providing crude outcome measures. Using an automatic chronometer, it is possible to obtain additional kinematic parameters that may lead to obtaining extra information and drawing further conclusions. However, there is a lack of studies that evaluate the test-retest reliability of these parameters, which may help to judge and interpret changes caused by an intervention or differences between populations. Thus, the aim of this study was to evaluate the test-retest reliability of the Timed Up and Go test (TUG) and 30 s Chair Stand test in healthy older adults. Methods: A total of 99 healthy older adults participated in this cross-sectional study. The TUG and the 30 s Chair Stand test were performed five times and twice, respectively, using an automatic chronometer. The sit-to-stand-to-sit cycle from the 30 s Chair Stand test was divided into two phases. Results: Overall, reliability for the 30 s Chair Stand test was good for almost each variable (intraclass correlation coefficient (ICC) >0.70). Furthermore, the use of an automatic chronometer improved the reliability for the TUG (ICC >0.86 for a manual chronometer and ICC >0.88 for an automatic chronometer). Conclusions: The TUG and the 30 s Chair Stand test are reliable in older adults. The use of an automatic chronometer in the TUG is strongly recommended as it increased the reliability of the test. This device enables researchers to obtain relevant and reliable data from the 30 s Chair Stand test, such as the duration of the sit-to-stand-to-sit cycles and phases.
LIN28B regulates androgen receptor in human trophoblast cells through Let‐7c

LIN28B is an RNA‐binding protein necessary for maintaining pluripotency in stem cells and plays an important role in trophoblast cell differentiation. LIN28B action on target gene function often involves the Let‐7 miRNA family. Previous work in cancer cells revealed that LIN28 through Let‐7 miRNA regulates expression of androgen receptor (AR). Considering the similarities between cancer and trophoblast cells, we hypothesize that LIN28B also is necessary for the presence of AR in human trophoblast cells. The human first‐trimester trophoblast cell line, ACH‐3P was used to evaluate the regulation of AR by LIN28B, and a LIN28B knockdown cell line was constructed using lentiviral‐based vectors. LIN28B knockdown in ACH‐3P cells resulted in significantly decreased levels of AR and increased levels of Let‐7 miRNAs. Moreover, treatment of ACH‐3P cells with Let‐7c mimic, but not Let‐7e or Let‐7f, resulted in a significant reduction in LIN28B and AR. Finally, forskolin‐induced syncytialization and Let‐7c treatment both resulted in increased expression of syncytiotrophoblast marker ERVW‐1 and a significant decrease in AR in ACH‐3P. These data reveal that LIN28B regulates AR levels in trophoblast cells likely through its inhibitory actions on let‐7c, which may be necessary for trophoblast cell differentiation into the syncytiotrophoblast.
Antidiabetic Activity and Potential Mechanism of Amentoflavone in Diabetic Mice

Aim: To investigate the anti-diabetic activity of amentoflavone (AME) in diabetic mice, and to explore the potential mechanisms. Methods: Diabetic mice induced by high fat diet and streptozotocin were administered with amentoflavone for 8 weeks. Biochemical indexes were tested to evaluate its anti-diabetic effect. Hepatic steatosis, the histopathology change of the pancreas was evaluated. The activity of glucose metabolic enzymes, the expression of Akt and pAkt, and the glucose transporter type 4 (GLUT4) immunoreactivity were detected. Results: AME decreased the level of glucose, total cholesterol (TC), triglyceride (TG), low density lipoprotein cholesterol (LDL-C) and glucagon, and increased the levels of high density lipoprotein cholesterol (HDL-C) and insulin. Additionally, AME increased the activity of glucokinase (GCK), phosphofructokinase-1 (PFK-1), and pyruvate kinase (PK), and inhibited the activity of glycogen synthase kinase-3 (GSK-3), phosphoenolpyruvate carboxykinase (PEPCK), and glucose-6-phosphatase (G-6-Pase). Mechanistically, AME increased superoxide dismutase (SOD), decreased malondialdehyde (MDA), activation of several key signaling molecules including pAkt (Ser473), and increased the translocation to the sedimenting membranes of GLUT4 in skeletal muscle tissue. Conclusions: AME exerted anti-diabetic effects by regulating glucose and lipid metabolism, perhaps via anti-oxidant effects and activating the PI3K/Akt pathway. Our study provided novel insight into the role and underlying mechanisms of AME in diabetes.
Dissimilar Impact of a Mediterranean Diet and Physical Activity on Anthropometric Indices: A Cross-Sectional Study from the ILERVAS Project

There is a close relationship between lifestyle behaviors and excess adiposity. Although body mass index (BMI) is the most used approach to estimate excess weight, other anthropometric indices have been developed to measure total body and abdominal adiposity. However, little is known about the impact of physical activity and adherence to a Mediterranean diet on these indices. Here we report the results of a cross-sectional study with 6672 middle-aged subjects with low to moderate cardiovascular risk from the Ilerda Vascular (ILERVAS) project. The participants’ adherence to physical activity (International Physical Activity Questionnaire short form) and MedDiet (Mediterranean Diet Adherence Screener) was evaluated. Measures of total adiposity (BMI, Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE), and Deurenberg’s formula), central adiposity (waist and neck circumferences, conicity index, waist to height ratio, Bonora’s equation, A body adiposity index, and body roundness index), and lean body mass (Hume formula) were assessed. Irrespective of sex, lower indices of physical activity were associated with higher values of total body fat and central adiposity. This result was constant regardless of the indices used to estimate adiposity. However, the association between MedDiet and obesity indices was much less marked and more dependent on sex than that observed for physical activity. Lean body mass was influenced by neither physical activity nor MedDiet adherence. No joint effect between physical activity and MedDiet to lower estimated total or central adiposity indices was shown. In conclusion, physical activity is related to lower obesity indices in a large cohort of middle-aged subjects. MedDiet showed a slight impact on estimated anthropometric indices, with no joint effect when considering both lifestyle variables. ClinTrials.gov Identifier: NCT03228459.
Randomized clinical trial of accelerated enhanced recovery after minimally invasive colorectal cancer surgery (RecoverMI trial)

Minimally invasive surgery (MIS) and enhanced recovery protocols (ERPs) have improved postoperative recovery and shortened length of hospital stay (LOS). Telemedicine technology has potential to improve outcomes and patient experience further. This study was designed to determine whether the combination of MIS, ERP and a structured telemedicine programme (TeleRecovery) could shorten total 30‐day LOS by 50 per cent.
Antimicrobial and Immunomodulatory Properties and Applications of Marine-Derived Proteins and Peptides

Marine organisms provide an abundant source of potential medicines. Many of the marine-derived biomaterials have been shown to act as different mechanisms in immune responses, and in each case they can significantly control the immune system to produce effective reactions. Marine-derived proteins, peptides, and protein hydrolysates exhibit various physiologic functions, such as antimicrobial, anticancer, antioxidant, antihypertensive, and anti-inflammatory activities. Recently, the immunomodulatory properties of several antimicrobial peptides have been demonstrated. Some of these peptides directly kill bacteria and exhibit a variety of immunomodulatory activities that improve the host innate immune response and effectively eliminate infection. The properties of immunomodulatory proteins and peptides correlate with their amino acid composition, sequence, and length. Proteins and peptides with immunomodulatory properties have been tested in vitro and in vivo, and some of them have undergone different clinical and preclinical trials. This review provides a comprehensive overview of marine immunomodulatory proteins, peptides, and protein hydrolysates as well as their production, mechanisms of action, and applications in human therapy.
SGLT2 Inhibitors: Nephroprotective Efficacy and Side Effects

The burden of diabetic kidney disease (DKD) has increased worldwide in the last two decades. Besides the growth of diabetic population, the main contributors to this phenomenon are the absence of novel nephroprotective drugs and the limited efficacy of those currently available, that is, the inhibitors of renin-angiotensin system. Nephroprotection in DKD therefore remains a major unmet need. Three recent trials testing effectiveness of sodium-glucose cotransporter 2 inhibitors (SGLT2-i) have produced great expectations on this therapy by consistently evidencing positive effects on hyperglycemia control, and more importantly, on the cardiovascular outcome of type 2 diabetes mellitus. Notably, these trials also disclosed nephroprotective effects when renal outcomes (glomerular filtration rate and albuminuria) were analyzed as secondary endpoints. On the other hand, the use of SGLT2-i can be potentially associated with some adverse effects. However, the balance between positive and negative effects is in favor of the former. The recent results of Canagliflozin and Renal Endpoints in Diabetes with Established Nephropathy Clinical Evaluation Study and of other trials specifically testing these drugs in the population with chronic kidney disease, either diabetic or non-diabetic, do contribute to further improving our knowledge of these antihyperglycemic drugs. Here, we review the current state of the art of SGLT2-i by addressing all aspects of therapy, from the pathophysiological basis to clinical effectiveness.
Overexpression of a Metallothionein 2A Gene from Date Palm Confers Abiotic Stress Tolerance to Yeast and Arabidopsis thaliana

Although the date palm tree is an extremophile with tolerance to drought and certain levels of salinity, the damage caused by extreme salt concentrations in the soil, has created a need to explore stress-responsive traits and decode their mechanisms. Metallothioneins (MTs) are low-molecular-weight cysteine-rich proteins that are known to play a role in decreasing oxidative damage during abiotic stress conditions. Our previous study identified date palm metallothionein 2A (PdMT2A) as a salt-responsive gene, which has been functionally characterized in yeast and Arabidopsis in this study. The recombinant PdMT2A protein produced in Escherichia coli showed high reactivity against the substrate 5′-dithiobis-2-nitrobenzoic acid (DTNB), implying that the protein has the property of scavenging reactive oxygen species (ROS). Heterologous overexpression of PdMT2A in yeast (Saccharomyces cerevisiae) conferred tolerance to drought, salinity and oxidative stresses. The PdMT2A gene was also overexpressed in Arabidopsis, to assess its stress protective function in planta. Compared to the wild-type control, the transgenic plants accumulated less Na+ and maintained a high K+/Na+ ratio, which could be attributed to the regulatory role of the transgene on transporters such as HKT, as demonstrated by qPCR assay. In addition, transgenic lines exhibited higher chlorophyll content, higher superoxide dismutase (SOD) activity and improved scavenging ability for reactive oxygen species (ROS), coupled with a better survival rate during salt stress conditions. Similarly, the transgenic plants also displayed better drought and oxidative stress tolerance. Collectively, both in vitro and in planta studies revealed a role for PdMT2A in salt, drought, and oxidative stress tolerance.
Neonatal hemochromatosis in a newborn with Down syndrome

Abstract Background: Neonatal hemochromatosis (NH) is a cause of neonatal/pediatric acute liver failure. Liver dysfunction/failure in Down syndrome had been described in relation to increased susceptibility to infection and transient myeloproliferative disease (TMD). The occurrence of NH in Down syndrome is described in only a few case reports. Material and methods: A complete autopsy have been performed in a 79-day-old infant with severe liver dysfunction. TMD was suspected antemortem following a report of peripheral blood leukocytosis with 14% atypical cells. Results: The complete autopsy revealed NH-phenotype to be the cause of liver dysfunction and subsequent death. Conclusion: Though TMD is a common cause of liver dysfunction in Down syndrome, NH should also be considered in its differential.
Vocal threat enhances visual perception as a function of attention and sex

Abstract This pre-registered event-related potential study explored how vocal emotions shape visual perception as a function of attention and listener sex. Visual task displays occurred in silence or with a neutral or an angry voice. Voices were task-irrelevant in a single-task block, but had to be categorized by speaker sex in a dual-task block. In the single task, angry voices increased the occipital N2 component relative to neutral voices in women, but not men. In the dual task, angry voices relative to neutral voices increased occipital N1 and N2 components, as well as accuracy, in women and marginally decreased accuracy in men. Thus, in women, vocal anger produced a strong, multifaceted visual enhancement comprising attention-dependent and attention-independent processes, whereas in men, it produced a small, behavior-focused visual processing impairment that was strictly attention-dependent. In sum, these data indicate that attention and listener sex critically modulate whether and how vocal emotions shape visual perception.
Effects of mesh resolution for hydrodynamic and transport modelling in coastal area

This paper investigates the effects of mesh resolution on the numerical modelling in coastal studies. Flexible meshes with different resolutions are generated by DHI software packages and then applied to simulate flood events. The performance of the meshes is summarised and compared, which shows the model with higher-resolution meshes produces more accurate hydrodynamic results. The performance of the mesh structure in the simulation depends on the flow magnitude, and therefore, a higher-resolution mesh is required when a higher-magnitude flood event is investigated. A case study of a high-resolution unstructured mesh was proposed for Moreton Bay in Australia, which was expected to lead to useful suggestions for further studies for this area.
Measure transformation and efficient quadrature in reduced‐dimensional stochastic modeling of coupled problems

Coupled problems with various combinations of multiple physics, scales, and domains are found in numerous areas of science and engineering. A key challenge in the formulation and implementation of corresponding coupled numerical models is to facilitate the communication of information across physics, scale, and domain interfaces, as well as between the iterations of solvers used for response computations. In a probabilistic context, any information that is to be communicated between subproblems or iterations should be characterized by an appropriate probabilistic representation. Although the number of sources of uncertainty can be expected to be large in most coupled problems, our contention is that exchanged probabilistic information often resides in a considerably lower‐dimensional space than the sources themselves. In this work, we thus propose to use a dimension reduction technique for obtaining the representation of the exchanged information, and we propose a measure transformation technique that allows subproblem implementations to exploit this dimension reduction to achieve computational gains. The effectiveness of the proposed dimension reduction and measure transformation methodology is demonstrated through a multiphysics problem relevant to nuclear engineering. Copyright © 2012 John Wiley & Sons, Ltd.
Exploring the use of social software by master of library and information science students

Purpose – The purpose of this paper is to explore the perceptions of master of library and information science (MLIS) students of social software.Design/methodology/approach – A web‐based questionnaire is used as a survey instrument. The MLIS students at Kuwait University (KU) and the University of Wisconsin‐Milwaukee (UWM) are identified as the population of this study. In total, 132 MLIS students participate in the survey.Findings – The majority of students from the two schools are aware of social software applications and their use. Blogs, video sharing, collaborative authoring, communication and social networking received the highest mean scores. Their perceptions about online activities, their use of social software and the obstacles to its use were not significantly affected by institutional affiliation. It was further found that the institutional affiliation exhibited significant differences for their perceptions of social software applications in education.Research limitations/implications – The s.
CHANGES IN THE USE OF SOCIOLOGICAL ARTICLES WITH TIME: A COMPARISON OF DIACHRONOUS AND SYNCHRONOUS DATA

In a paper published in 1973 Oromaner included an analysis of citations to articles in three sociological journals in 1960 by subsequent volumes of those journals 1961–70. This study was unusual in that it was one of very few that followed citations to a given set of articles through in time (diachronous study), as opposed to analysing by date a set of references to articles made by journals or articles of a given date (synchronous study) — a far more common procedure.
Effectiveness of Data Augmentation in Cellular-based Localization Using Deep Learning

Recently, deep learning-based positioning systems have gained attention due to their higher performance relative to traditional methods. However, obtaining the expected performance of deep learning-based systems requires large amounts of data to train model. Obtaining this data is usually a tedious process which hinders the utilization of such deep learning approaches. In this paper, we introduce a number of techniques for addressing the data collection problem for deep learning-based cellular localization systems. The basic idea is to generate synthetic data that reflects the typical pattern of the wireless data as observed from a small collected dataset. Evaluation of the proposed data augmentation techniques using different Android phones in a cellular localization case study shows that we can enhance the performance of the localization systems in both indoor and outdoor scenarios by 157% and 50.5%, respectively. This highlights the promise of the proposed techniques for enabling deep learning-based localization systems.
Information matrices and generalization

This work revisits the use of information criteria to characterize the generalization of deep learning models. In particular, we empirically demonstrate the effectiveness of the Takeuchi information criterion (TIC), an extension of the Akaike information criterion (AIC) for misspecified models, in estimating the generalization gap, shedding light on why quantities such as the number of parameters cannot quantify generalization. The TIC depends on both the Hessian of the loss H and the covariance of the gradients C. By exploring the similarities and differences between these two matrices as well as the Fisher information matrix F, we study the interplay between noise and curvature in deep models. We also address the question of whether C is a reasonable approximation to F, as is commonly assumed.
Poisoning Attacks with Generative Adversarial Nets

Machine learning algorithms are vulnerable to poisoning attacks: An adversary can inject malicious points in the training dataset to influence the learning process and degrade its performance. Optimal poisoning attacks have already been proposed to evaluate worst-case scenarios, modelling attacks as a bi-level optimisation problem. Solving these problems is computationally demanding and has limited applicability for some models such as deep networks. In this paper we introduce a novel generative model to craft systematic poisoning attacks against machine learning classifiers generating adversarial training examples, i.e. samples that look like genuine data points but that degrade the classifier's accuracy when used for training. We propose a Generative Adversarial Net with three components: generator, discriminator, and the target classifier. This approach allows us to model naturally the detectability constrains that can be expected in realistic attacks and to identify the regions of the underlying data distribution that can be more vulnerable to data poisoning. Our experimental evaluation shows the effectiveness of our attack to compromise machine learning classifiers, including deep networks.
On recovering of solutions of Schr\"odinger equations from their time averages

The paper study a possibility to recover solutions of Schrodinger equations from its time-averages in the setting where the values at the initial time are unknown. This problem can be reformulated as a new boundary value problem where a Cauchy condition is replaced by a prescribed time-average of the solution. It is shown that this new problem is well-posed in certain classes of solutions. The paper establishes existence, uniqueness, and a regularity of the solution for this new problem.
Pre-Training with Whole Word Masking for Chinese BERT

Bidirectional Encoder Representations from Transformers (BERT) has shown marvelous improvements across various NLP tasks. Recently, an upgraded version of BERT has been released with Whole Word Masking (WWM), which mitigate the drawbacks of masking partial WordPiece tokens in pre-training BERT. In this technical report, we adapt whole word masking in Chinese text, that masking the whole word instead of masking Chinese characters, which could bring another challenge in Masked Language Model (MLM) pre-training task. The proposed models are verified on various NLP tasks, across sentence-level to document-level, including machine reading comprehension (CMRC 2018, DRCD, CJRC), natural language inference (XNLI), sentiment classification (ChnSentiCorp), sentence pair matching (LCQMC, BQ Corpus), and document classification (THUCNews). Experimental results on these datasets show that the whole word masking could bring another significant gain. Moreover, we also examine the effectiveness of the Chinese pre-trained models: BERT, ERNIE, BERT-wwm, BERT-wwm-ext, RoBERTa-wwm-ext, and RoBERTa-wwm-ext-large. We release all the pre-trained models: \url{this https URL
A Dynamic Object Allocation And Replication Algorithm For Distributed Systems With Centralized Control

Abstract The design of distributed systems can be based on exercising either centralized or decentralized control mechanisms as per the application requirements. In this paper, for a centralized controlled distributed system, we design a dynamic object allocation and replication algorithm that adapts to the arriving requests patterns. We propose a mathematical cost model that considers the costs involved in servicing a request, such as I/O cost and communication cost, and design a dynamic algorithm, referred to as dynamic window mechanism (DWM). Our objective is to minimize the total servicing cost of all the arriving requests. We use competitive analysis to quantify the performance of DWM algorithm in the stationary computing environment (SCE) and extend our analytical study to the mobile computing environment (MCE).