Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling Natural Communication and a Multichannel Resource: The Deceleration Effect

Many AI systems imitate human communication. Specific solutions are often based on implicit theories about communication. We propose that, in order to improve performance, it is useful to consult linguistic resources registering actual communicative behavior. The study is based on a multichannel resource named RUPEX. A variety of parameters of communicative behaviors are annotated in RUPEX and can be used to improve AI systems, such as conversational agents. We focus on the deceleration effect, characteristic of elementary chunks of human speech. Specific data on deceleration can be derived from the RUPEX annotation. An assessment of deceleration in the speech produced by conversational agents is presented. Features found in linguistic annotation may provide the algorithm with certain hints on what to attend to. Annotated linguistic resources provide more direct information on what to imitate, and taking them into account may lead to better pattern recognition and therefore better speech production. RUPEX is an example of a rich resource that can help to synthesize more natural behavior.
Beyond Geolocation: Micro-Dialect Identification in Diaglossic and Code-Switched Environments

Although the prediction of dialects is an important language processing task, with a wide range of applications, existing work is largely limited to coarse-grained varieties. Inspired by geolocation research, we propose the novel task of Micro-Dialect Identification (MDI) and introduce MARBERT, a new language model with striking abilities to predict a fine-grained variety (as small as that of a city) given a single, short message. For modeling, we offer a range of novel spatially and linguistically-motivated multi-task learning models. To showcase the utility of our models, we introduce a new, large-scale dataset of Arabic micro-varieties (low-resource) suited to our tasks. MARBERT predicts micro-dialects with 9.9% F1, ~76X better than a majority class baseline. Our new language model also establishes new state-of-the-art on several external tasks.
A cross-sectional study

The relationship between supraspinatus tendon thickness and the acromiohumeral distance (AHD) at both rest position and shoulder elevation is still to be explored in those with chronic shoulder pain. The aim is to compare supraspinatus occupation ratio (OR) at 0° and 60° of shoulder elevationmeasured by ultrasound imaging in the symptomatic shoulder, the contralateral asymptomatic shoulder and in healthy subjects. This was across-sectional, observational study. A sample of 56 participants with subacromial pain syndrome in their dominant arm was recruited in 3 different primary care centres. Forty participants without shoulder pain were also recruited. The AHD at 0° and 60° of active shoulder abduction as well as the supraspinatus tendon thickness were measured by ultrasound in these groups. Supraspinatus OR at 60°was significantly greater in symptomatic compared to asymptomatic shoulders (P= .04) and healthy shoulders (P= .008). The percentage of change in supraspinatus OR from rest position to 60° was also greater in symptomatic shoulders when comparing with asymptomatic (P= .01) and healthy shoulders (P= .03). No other statistically significant differences for the rest of comparisons were found. Supraspinatus OR may explain shoulder pain in chronic conditions. Further studies at acute and chronic conditions after a physiotherapy treatment are needed to explore its usefulness in clinical practice. Abbreviations: AHD = acromiohumeral distance, MRI =magnetic resonance imaging, OR = occupation ratio, RC = rotator cuff, SAPS = subacromial pain syndrome, US = ultrasound imaging.
Long-term functional outcomes of diffuse pigmented villonodular synovitis of knee

Supplemental Digital Content is available in the text Abstract Diffuse pigmented villonodular synovitis (PVNS) of knee is a rare benign disease that has a destructive clinical course. Synovectomy and adjuvant radiotherapy (RT) have been reported as treatment options but literatures reporting functional outcomes were sparse. This study aimed to evaluate the long-term functional outcomes and disease control among treatment modalities through the 22 years of experience. A single-center database was searched for patients who received synovectomy of knee with the pathologic diagnosis of PVNS. General data, treatment modalities, and recurrent status were retrospectively collected from medical records. Functional outcomes were evaluated by Western Ontario and McMaster Universities Osteoarthritis Index through phone interviews by an independent orthopedist. From January 1995 to December 2017, 24 patients with diffuse PVNS of knee were identified, including 19 receiving open synovectomy (OP) and 5 undergoing arthroscopic surgery. Adjuvant RT was performed on 14 patients with a median dose of 35 Gy (range 20–40 Gy). After median follow up of 6 years, recurrences were recorded in 10 cases. The recurrence rate was significantly lower in the OP + RT group than the OP group (8.3% vs 57.1%, P = .038). Among those with preserved knee joints, there was no significant difference in the Western Ontario and McMaster Universities Osteoarthritis Index score and stiffness score between patients in the OP + RT and OP groups. For patients with diffuse PVNS of knee, the addition of moderate-dose adjuvant RT following OP provided excellent local control while maintaining good joint function with limited treatment-related morbidity. Our study emphasized the importance of moderate dose RT in diffuse PVNS of knee joint.
Do accountable care organizations differ according to physician-hospital integration?

Supplemental Digital Content is available in the text Abstract Physician-hospital integration among accountable care organizations (ACOs) has raised concern over impacts on prices and spending. However, characteristics of ACOs with greater integration between physicians and hospitals are unknown. We examined whether ACOs systematically differ by physician-hospital integration among 16 commercial ACOs operating in Massachusetts. Using claims data linked to information on physician affiliation, we measured hospital integration with primary care physicians for each ACO and categorized them into high-, medium-, and low-integrated ACOs. We conducted cross-sectional descriptive analysis to compare differences in patient population, organizational characteristics, and healthcare spending between the three groups. In addition, using multivariate generalized linear models, we compared ACO spending by integration level, adjusting for organization and patient characteristics. We identified non-elderly adults (aged 18–64) served by 16 Massachusetts ACOs over the period 2009 to 2013. High- and medium-integrated ACOs were more likely to be an integrated delivery system or an organization with a large number of providers. Compared to low-integrated ACOs, higher-integrated ACOs had larger inpatient care capacity, smaller composition of primary care physicians, and were more likely to employ physicians directly or through an affiliated hospital or physician group. A greater proportion of high-/medium-integrated ACO patients lived in affluent neighborhoods or areas with a larger minority population. Healthcare spending per enrollee in high-integrated ACOs was higher, which was mainly driven by a higher spending on outpatient facility services. This study shows that higher-integrated ACOs differ from their counterparts with low integration in many respects including higher healthcare spending, which persisted after adjusting for organizational characteristics and patient mix. Further investigation into the effects of integration on expenditures will inform the ongoing development of ACOs.
Probabilistic Machine Learning: Models, Algorithms and a Programming Library

Probabilistic machine learning provides a suite of powerful tools for modeling uncertainty, performing probabilistic inference, and making predictions or decisions in uncertain environments. In this paper, we present an overview of our recent work on probabilistic machine learning, including the theory of regularized Bayesian inference, Bayesian deep learning, scalable inference algorithms, a probabilistic programming library named ZhuSuan, and applications in representation learning as well as learning from crowds.
Filtering facepiece respirators with an exhalation valve: measurements of filtration efficiency to evaluate their potential for source control.

Filtering facepiece respirators (FFRs) are used extensively by healthcare personnel (HCP) during a pandemic. FFRs are primarily reserved for those personnel who have a greater risk and longer duration of exposure compared with other workers and the general public. Some FFR models contain an exhalation valve, which is a device that closes to allow inhaled breath to be pulled through the filter media and opens to allow exhaled breath to be expelled from the respirator through the exhalation valve as well as the filter media. These FFR models provide the wearer with a level of protection like that of an FFR without an exhalation valve, and they are thought to increase the wearer’s comfort at high work rates and be suitable for longer periods of use. However, respiratory secretions expelled by wearers may exit along with air through the exhalation valve. A concern with FFRs with an exhalation valve is that individuals may spread disease if unfiltered, virus-laden aerosols pass through the valve.
Calmodulin-protein 4.1R rendez-vous: Chaperon-like function for calmodulin and protein 4.1R in erythrocytes

An intriguing observation is that human erythrocytes can maintain their structural integrity over their 120day life span despite the fact that they can no longer synthesize new proteins as they undergo enucleation upon maturation. Calmodulin (CaM), a canonical Ca binding protein, plays a key role in keeping homeostasis of Ca concentration in the cell through activation of Ca-ATPase. Membrane skeletal protein 4.1R is the prototypical member of a family of four highly paralogous proteins that include 4.1G, 4.1N and 4.1B. Human protein 4.1R is expressed as two major isoforms in the erythrocyte lineage, a 135kDa isoform (4.1R) expressed in erythroblasts but no longer expressed in mature erythrocytes and a 80kDa isoform (4.1R) expressed solely in mature erythrocytes. Interestingly, these two 4.1R isoforms, that differ by the presence or absence of an N-terminal 209 amino acid head-piece region (HP), have different CaM binding sites. Not only 4.1R and 4.1R differ by the location of their CaM binding sites but also by the way CaM regulates their interactions with other membrane proteins. Thus, whereas CaM binding to 4.1R is strongly Ca-dependent and the dissociation constant in equilibrium (Kd) of their interaction is in the 10 M range, CaM binding to 4.1R is Ca-independent and the Kd of this interaction is in the 10 -7 M range both in the presence and absence of Ca. We have previously documented that the interaction of CaM with 4.1R is physiologically important in maintaining the structural and mechanical properties of erythrocytes. Indeed, even in the absence of Ca, CaM promotes the thermostability of the 4.1R FERM (Four.one-Ezrin-Radixin-Moesin) domain through its interaction with a peptide encoded by exon 11, pep11 (AKKLWKVCVEHHTFFRL). In this review, we discuss the structural functions of 4.1R in erythrocytes, focusing primarily on the FERM domain, and propose a chaperon-like function for CaM and 4.1R in erythrocytes based on our published data.
3-D Numerical Study of a Bottom Ramp Fish Passage Using Smoothed Particle Hydrodynamics

Worldwide, the overwhelming number of man-made barriers in fluvial systems has been identified as one of the major causes of the reported staggering average declines of migratory fish. Fish passages have been shown to help mitigate such problems. Close-to-nature types of fish passages, such as bottom ramps, bypass channels, and fish ramps can be used to minimize the impact of artificial steep drops (e.g., weirs) on the migration of aquatic fauna, especially in cases of low-head barriers. This study focuses on the characterization of the flow pattern in a bottom ramp. A 3-D numerical model based on the meshless smoothed particle hydrodynamics (SPH) method was successfully validated and then employed for the simulation of turbulent free-surface flow in a straight channel with complex geometry. The effects of bed roughness, channel slope, and flow rate were quantified in terms of flow depth, velocity fields, and area‒velocity ratios. During the study, several new tools were developed, leading to new functionalities in pre-processing, solver, and post-processing which increase the applicability of DualSPHysics in the field of eco-hydraulics.
FACEBOOK USAGE AND STUDENT ENGAGEMENT OF PRE-SERVICE TEACHERS

Academics and researchers are interested to study how social networking sites affect the students who are enrolled in higher education. Among all social networking sites, particular interest towards “Facebook” is quite evident. Previous researches have documented positive, negative or no significant relationship between Facebook usage and student engagement. Owing to paucity of similar studies in Indian landscape, the present study attempts to explore the relationship between Facebook usage and pre-service teachers’ engagement. Data was collected from 120 preservice teachers of two central universities. Questionnaire was developed by the researchers to examine the general use of Facebook by pre-service teachers. The second section of questionnaire dealt with student engagement which was ascertained by adapting certain items of National Survey of Student Engagement (2013). Data was analysed both i.e. quantitatively and qualitatively. Results indicated that use of Facebook pages was significantly correlated with active and collaborative learning. However, there was no significant correlation between some dimensions of Facebook usage, such as messenger, groups and events with student engagement.
Effects of Zinc Nanoparticles on Growth Performance, Carcass Characteristics, Immunity, and Meat Quality of Broiler Chickens

Zinc (Zn) supplementation of food can be used in broilers to overcome Zn deficiencies in human and also to improve the growth rate and immune system of birds. Due to the lack of information about the impact of Zn nanoparticles (Zn-NPs) on meat quality, this study was conducted to evaluate the differences between dietary Zn-NPs and other Zn sources on broiler performance, carcass characteristics, humoral immunity, meat quality, meat Zn content, as well as fresh and frozen meat oxidative values. Day-old broiler chicks (Ross 308, n=240) were randomly divided into six dietary treatments with four replicates, based on a completely randomized design (d 1-42). Dietary treatments composed of different Zn sources supplemented per kg of basal diet (30 mg/kg Zn) included: control (70 mg from ZnSO4), 70ZAAC (70 mg from Zn amino acid complex), 30BZMO (30 mg Zn from Zn-NPs), 50BZMO (50 mg Zn from Zn-NPs), 70BZMO (70 mg Zn from Zn-NPs), and 90BZMO (90 mg Zn from Zn-NPs). Results showed a higher amount of IgM in chickens fed with Zn-NPs and 70ZAAC, though no effect was found on performance, carcass characteristics, and also the relative weight of lymphatic organs. Breast meat shear force, redness and lightness indexes, malondialdehyde (MDA) content, and Zn content were significantly affected by experimental diets, though no effect of treatments was observed on MDA and Zn content of thigh muscle. Lower pH value of breast meat was found in chickens fed with Zn-NPs and 70ZAAC. The present results showed that 30BZMO, as a recommended Zn-NPs treatment, supported growth performance, improved humoral immunity, Zn content of breast meat, and meat quality, while decreasing MDA content of breast meat.
CMAR_A_230274 7467..7474

1Department of Radiation Oncology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325000, People’s Republic of China; 2Department of Pathology, Yancheng Hospital Affiliated of Southeast University, Yancheng, Jiangsu 224000, People’s Republic of China; 3Radiation and Medical Oncology Department, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, People’s Republic of China
PHMT_A_293261 177..187

Arsi University College of Health Science, Asella, Ethiopia Background: Globally, anemia is a public health problem affecting children living in both developed and developing countries with bad consequences on children’s cognitive, social, and economic development. Objective: To assess the prevalence and predictors of anemia among children aged 6–23 months residing at Dodota district, Southeast Ethiopia. Methods: A community-based cross-sectional study was conducted from January– July 2019, at Dodota district, in Southeast Ethiopia. Multistage, random, and systematic sampling techniques were employed to recruit households and study participants. Trained community health extension workers were involved in the data collection. Data were entered into Epi_info 7.2. 2 for clean-up and exported to SPSS 21 for analysis. Frequency and proportion were used to describe nominal and ordinal variables. Mean with SD were used to describe continuous variables. Pearson correlation coefficient was used to assess correlation between numeric variables. Regressional analysis was used to assess factors predicting the occurrence of anemia. P<0.05 with 95% CI was considered significant. Results: A total of 917 children were included and the prevalence of anemia was found to be 407 (44.4%, 95% CI=41.1–47.4). When stratified to age category, the prevalence of anemia was highest among the age group of 6–12 months. Lack of ANC visits, lack of iron supplementation during pregnancy, untimely initiation of complementary feeding, and initiation of cow’s milk before 1 year of age were factors associated with anemia. Conclusion: The prevalence of anemia was at the level of major public health problems. Antenatal and obstetric factors as well as child feeding practices were risk factors associated with anemia; and utilizing obstetric and childcare practices is highly recommended to mitigate this public health problem.
Dynamics of Fermentation Parameters and Bacterial Community in High-Moisture Alfalfa Silage with or without Lactic Acid Bacteria

The aim of this study was to gain deeper insights into the dynamics of fermentation parameters and the bacterial community during the ensiling of high-moisture alfalfa. A commercial lactic acid bacteria (YX) inoculant was used as an additive. After 15 and 30 days of ensiling, the control silage (CK) exhibited a high pH and a high concentration of ammoniacal nitrogen (NH3-N); Enterobacter and Hafnia-Obesumbacterium were the dominant genera. At 60 d, the pH value and the concentration of NH3-N in CK silage increased compared with 15 and 30 d, propionic acid and butyric acid (BA) were detected, and Garciella had the highest abundance in the bacterial community. Compared with CK silage, inoculation of YX significantly promoted lactic acid and acetic acid accumulation and reduced pH and BA formation, did not significantly reduce the concentration of NH3-N except at 60 d, and significantly promoted the abundance of Lactobacillus and decreased the abundance of Garciella and Anaerosporobacter, but did not significantly inhibit the growth of Enterobacter and Hafnia-Obesumbacterium. In conclusion, high-moisture alfalfa naturally ensiled is prone to rot. Adding YX can delay the process of silage spoilage by inhibiting the growth of undesirable microorganisms to a certain extent.
Abnormal Liver Biochemistry Tests and Acute Liver Injury in COVID-19 Patients: Current Evidence and Potential Pathogenesis

Globally, millions of persons have contracted the coronavirus disease 2019 (COVID-19) over the past several months, resulting in significant mortality. Health care systems are negatively impacted including the care of individuals with cancers and other chronic diseases such as chronic active hepatitis, cirrhosis and hepatocellular carcinoma. There are various probable pathogenic mechanisms that have been presented to account for liver injury in COVID-19 patients such as hepatotoxicity cause by therapeutic drugs, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection of the bile duct cells and hepatocytes, hypoxia and systemic inflammatory response. Liver biochemistry tests such as aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT) and alkaline phosphatase (ALP) are deranged in COVID-19 patients with liver injury. Hepatocellular damage results in the elevation of serum AST and ALT levels in early onset disease while a cholestatic pattern that develops as the disease progress causes higher levels of ALP, GGT, direct and total bilirubin. These liver biochemistry tests are prognostic markers of disease severity and should be carefully monitored in COVID-19 patients. We conducted a systematic review of abnormal liver biochemistry tests in COVID-19 and the possible pathogenesis involved. Significant findings regarding the severity, hepatocellular pattern, incidence and related clinical outcomes in COVID-19 patients are highlighted.
Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks

Many natural systems, especially biological ones, exhibit complex multivariate nonlinear dynamical behaviors that can be hard to capture by linear autoregressive models. On the other hand, generic nonlinear models such as deep recurrent neural networks often require large amounts of training data, not always available in domains such as brain imaging; also, they often lack interpretability. Domain knowledge about the types of dynamics typically observed in such systems, such as a certain type of dynamical systems models, could complement purely data-driven techniques by providing a good prior. In this work, we consider a class of ordinary differential equation (ODE) models known as van der Pol (VDP) oscil lators and evaluate their ability to capture a low-dimensional representation of neural activity measured by different brain imaging modalities, such as calcium imaging (CaI) and fMRI, in different living organisms: larval zebrafish, rat, and human. We develop a novel and efficient approach to the nontrivial problem of parameters estimation for a network of coupled dynamical systems from multivariate data and demonstrate that the resulting VDP models are both accurate and interpretable, as VDP's coupling matrix reveals anatomically meaningful excitatory and inhibitory interactions across different brain subsystems. VDP outperforms linear autoregressive models (VAR) in terms of both the data fit accuracy and the quality of insight provided by the coupling matrices and often tends to generalize better to unseen data when predicting future brain activity, being comparable to and sometimes better than the recurrent neural networks (LSTMs). Finally, we demonstrate that our (generative) VDP model can also serve as a data-augmentation tool leading to marked improvements in predictive accuracy of recurrent neural networks. Thus, our work contributes to both basic and applied dimensions of neuroimaging: gaining scientific insights and improving brain-based predictive models, an area of potentially high practical importance in clinical diagnosis and neurotechnology.