Miracle-dz/UniFAR-FTUs huggingface dataset:
Development and Validation of Decision Rules Models to Stratify Coronary Artery Disease, Diabetes, and Hypertension Risk in Preventive Care: Cohort Study of Returning UK Biobank Participants

Background A wide range of predictive models exist that predict risk of common lifestyle conditions. However, these have not focused on identifying pre-clinical higher risk groups that would benefit from lifestyle interventions and do not include genetic risk scores. In this study, we developed, validated, and compared the performance of three decision rule algorithms including biomarkers, physical measurements and genetic risk scores for incident coronary artery disease (CAD), diabetes (T2D), and hypertension in the general population against commonly used clinical risk scoring tools. Methods and findings Of all individuals recruited between 2006 and 2010 from the UK Biobank study for whom re-measurement data were available, 60782 were included in the analyses (mean age 56.3 (7.59), 51.2% female). Follow-up data were available until 2016. Three decision rules models with three risk strata were developed and tested for an association with incident disease. Hazard ratios (HR with 95% confidence interval) for incident CAD, T2D, and hypertension were calculated from survival models. Model performance in discriminating between higher risk individuals suitable for lifestyle intervention and individuals at low risk was assessed using the area under the receiver operating characteristic curve (AUROC). From the initial baseline measurement until the follow-up re-measurements, 500 incident CAD cases, 1005 incident T2D cases, and 2379 incident hypertension cases were ascertained. The higher risk group in the decision rules model had a 40-, 40.9-, and 21.6-fold increase in risk of CAD, T2D, and hypertension, respectively (P < 0.001 for all), and the risk increased significantly between the three strata for all three conditions (P < 0.05). Risk stratification based on decision rules identified both a low risk group which would not have benefited from lifestyle intervention (only 1.3% incident disease across all models), as well as a high risk group where 72%, 81.5%, and 74% of those who developed disease within 8 years would have been recommended lifestyle intervention. Based on genetic risk alone, we identified not only a high risk group, but also a group at elevated risk for all health conditions. This study was limited by the restricted number of participants with follow-up data, and the lack of ethnic diversity in the UK Biobank cohort. Conclusion In this analysis of returning UK Biobank participants, we found that decision rule models comprising blood biomarkers, physical measurements, and polygenic risk scores were superior at identifying individuals likely to benefit from lifestyle intervention for three of the most common lifestyle-related chronic health conditions compared to commonly used clinical risk scores.
Fake, Faulty, and Authentic Stand-Taking: What Determines the Legitimacy of Corporate Social Advocacy?

ABSTRACT This study experimentally interrogates the critical preconditions of how an organization legitimizes its corporate social advocacy (CSA) initiatives as an integral part of strategic communication. A 2 × 2 factorial design survey (N = 398) indicates that companies must find a way to bridge two perceptual gaps a factual gap and a conformity gap. The factual gap refers to perceived inconsistency of values – that is, that the company may not walk its talk on moral values. In contrast, the conformity gap refers to values incongruity between public expectations and corporate performance. Using these two conceptual constructs, we classify CSA initiatives into authentic, faulty, and fake. Authentic CSA initiatives project clear corporate moral values and meet public value expectations; unsurprisingly, they are found to generate more substantial perceptions of legitimacy and more positive behavioral willingness than other types of CSA initiative. Previously, few attempts to measure experimentally the legitimacy gaps that frequently arise between public expectations and companies’ actual CSA performance. The authentic CSA could not only fulﬁll corporate strategic communication missions but also generate the legitimate end of mutual understanding between the organization and the publics.
Can a ‘modern’ irrigation system and a traditional smallholder gravitational system coexist? A view from Marakwet, Kenya

ABSTRACT Irrigation and improved agricultural inputs have been promoted by the New African Green Revolution to close yield gaps in Sub-Saharan Africa. Can this approach coexist with local indigenous irrigation systems? We examine an irrigation scheme financed by both the Kenyan and Canadian Red Cross and put in place in 2015 in Marakwet, Kenya, where a gravity irrigation system has been operated by local people for three centuries. Grounded on ethnographic data, we show how the current rhetoric and operationalization of top-down irrigation projects disregard, instead of harnessing, local agricultural knowledge which would ensure sustainable farming in the context of resource-poor and climate-challenged communities.
Design on electrohydraulic servo driving system with walking assisting control for lower limb exoskeleton robot

According to the characteristics of human gait and the requirements of power assistance, locomotive mechanisms and electrohydraulic servo driving are designed on a lower limb exoskeleton robot, in which the miniaturization and lightweight of driving system are realized. The kinematics of the robot is analyzed and verified via the typical movements of the exoskeleton. In this article, the simulation on the power of joints during level walking was analyzed in ADAMS 2016, which is a multibody simulation and motion analysis software. Motion ranges and driving strokes are then optimized. A proportional integral derivative (PID) control method with error estimation and pressure compensation is proposed to satisfy the requirements of joints power assistance and comply with the motion of human lower limb. The proposed method is implemented into the exoskeleton for assisted walking and is verified by experimental results. Finally, experiments show that the tracking accuracy and power-assisted performance of exoskeleton robot joints are improved.
Processing chain for 3D histogram of gradients based real-time object recognition

3D object recognition has been a cutting-edge research topic since the popularization of depth cameras. These cameras enhance the perception of the environment and so are particularly suitable for autonomous robot navigation applications. Advanced deep learning approaches for 3D object recognition are based on complex algorithms and demand powerful hardware resources. However, autonomous robots and powered wheelchairs have limited resources, which affects the implementation of these algorithms for real-time performance. We propose to use instead a 3D voxel-based extension of the 2D histogram of oriented gradients (3DVHOG) as a handcrafted object descriptor for 3D object recognition in combination with a pose normalization method for rotational invariance and a supervised object classifier. The experimental goal is to reduce the overall complexity and the system hardware requirements, and thus enable a feasible real-time hardware implementation. This article compares the 3DVHOG object recognition rates with those of other 3D recognition approaches, using the ModelNet10 object data set as a reference. We analyze the recognition accuracy for 3DVHOG using a variety of voxel grid selections, different numbers of neurons (Nh ) in the single hidden layer feedforward neural network, and feature dimensionality reduction using principal component analysis. The experimental results show that the 3DVHOG descriptor achieves a recognition accuracy of 84.91% with a total processing time of 21.4 ms. Despite the lower recognition accuracy, this is close to the current state-of-the-art approaches for deep learning while enabling real-time performance.
ZnO thin-film transistor grown by rf sputtering using carbon dioxide and substrate bias modulation

ZnO thin-film transistor (TFT) grown by rf magnetron sputtering in Ar/O2 atmosphere shows inferior turn-off characteristics compared to ZnO TFT grown by other methods. We thought that reactions between Zn and O2 might produce defects responsible for the poor turn-off behavior. In order to solve this problem, we studied sputtering growth in Ar/CO2 atmosphere at 450°C. During sputtering growth, we modulated substrate dc bias to control ion supply to the substrate. After growth ZnO was annealed in CO2 and O2 gas. With these methods, our bottom-gate ZnO thin-film transistor showed 4.7 cm2/Vsec mobility, 4×106 on/off ratio, and -2 V threshold voltage.
Reducing Thermal Noise in Molecular Force Spectroscopy | NIST

Molecular force spectroscopy is the practice of measuring the mechanical properties of single molecules. The precision determination of these properties requires an instrument capable of piconewton-level force measurement. The atomic force microscope (AFM) is capable of such measurements if experiments are performed carefully. One factor limiting the force measurement resolution of the AFM in wet chemical environments is the presence of a squeeze film damper between the microfabricated cantilever used for force measurement and the surface to which the molecules of interest are attached. The effect of this damping on the force sensor’s thermal noise is examined, and a new method is proposed to reduce this noise at low frequency by using a micropipette.
Bending and SAR analysis on UWB wearable MIMO antenna for on-arm WBAN applications

Abstract Here, a planar Ultra-Wideband (UWB) wearable Multiple Input Multiple Output (MIMO) antenna is designed for on-arm wearable Wireless Body Area Network (WBAN) applications. This antenna is designed on a 100% cotton cloth substrate. The two-port MIMO antenna has a dual spinning wheel shape like radiators with the partial ground and microstrip feedings. The two partial grounds are connected to a rectangular strip to have common ground. The complete surface area of the antenna is 40 × 70 mm2. In comparison with recently published papers in the same research area, the bending and SAR analysis are also done to estimate the performance of this wearable antenna, which is the novelty of this research work. For entire UWB bandwidth, S–parameters, gain, efficiency, and diversity parameters (Channel Capacity Loss [CCL] and Envelope Correlation Coefficient [ECC]) and far-field simulations are done for all cases such as flat, bend, on body antenna, which demonstrates the appropriateness of the presented antenna to be operated to the human arm.
A New Method to Monitor the Process of Laser Ablation: Measurements on the Current Induced by Ablated Particles

An induced current signal due to the ejection of charged particles in the laser ablation process was observed. The signal displayed an ablation threshold which was in accord with the ablation threshold measured by mass spectrometry, and showed a nonlinear relationship of its intensity till much higher laser fluences. The mechanism of the occurrence of the signal and its potential applications are discussed.
Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition

Speech emotion recognition (SER) is a difficult and challenging task because of the affective variances between different speakers. The performances of SER are extremely reliant on the extracted features from speech signals. To establish an effective features extracting and classification model is still a challenging task. In this paper, we propose a new method for SER based on Deep Convolution Neural Network (DCNN) and Bidirectional Long Short-Term Memory with Attention (BLSTMwA) model (DCNN-BLSTMwA). We first preprocess the speech samples by data enhancement and datasets balancing. Secondly, we extract three-channel of log Mel-spectrograms (static, delta, and delta-delta) as DCNN input. Then the DCNN model pre-trained on ImageNet dataset is applied to generate the segment-level features. We stack these features of a sentence into utterance-level features. Next, we adopt BLSTM to learn the high-level emotional features for temporal summarization, followed by an attention layer which can focus on emotionally relevant features. Finally, the learned high-level emotional features are fed into the Deep Neural Network (DNN) to predict the final emotion. Experiments on EMO-DB and IEMOCAP database obtain the unweighted average recall (UAR) of 87.86 and 68.50%, respectively, which are better than most popular SER methods and demonstrate the effectiveness of our propose method.
Usefulness of the Ranking Technique in the Microscopic Agglutination Test (MAT) to Predict the Most Likely Infecting Serogroup of Leptospira

The microscopic agglutination test (MAT) used for the serological diagnosis of leptospirosis, as a robust and inexpensive method, is still the reality in many laboratories worldwide. Both the performance and the interpretation of the MAT vary from region to region, making standardization difficult. The prediction of the probable infecting serogroup using this test is indispensable for elucidating the epidemiology of the disease; however, in veterinary medicine, many studies consider any reaction detected with a titer of 100, which may ultimately overestimate some serogroups. Thus, the aim of this study was to evaluate the usefulness of the ranking technique for predicting the probable infecting serogroup identified by the MAT, eliminating cross reactions with other serogroups. Leptospira strains (12 samples) were inoculated in hamsters, and after 30 days, serology was performed by the MAT for these animals to confirm the infecting serogroup. Using the ranking technique, the probable infectious serogroup found with the MAT was the same as that in which the strains of inoculated leptospires belonged; additionally, the technique can be applied in epidemiological studies involving herds.
Evidence of Surface Rupture Associated With Historical Earthquakes in the Lower Tagus Valley, Portugal. Implications for Seismic Hazard in the Greater Lisbon Area

The Lower Tagus Valley Fault, Portugal, has long been associated with the damaging earthquakes that affected the Greater Lisbon Area in historical times. These include a poorly documented earthquake that occurred in 1344, the relatively well-documented 1531 earthquake, and the most recent M6.0 1909 earthquake. In this work, we use a 0.5 m resolution LiDAR-based digital elevation model and a 0.5 cm resolution digital surface model based on UAV photogrammetry to accurately locate the fault scarps in the northernmost portion of the western fault strand and to select sites to perform paleoseimolological investigations. The paleoseismological and geochronological analysis performed in the Alviela trench site document the fault activity in the last 3000 years, including two earthquakes during historical times. We performed ground motion scenarios for 20 km, 40 km, and 60 km ruptures including the trench site. The ground motion fields obtained for the 40 km and 60 km ruptures are in agreement with most macroseismic intensity data available for the 1531 earthquake, implying a magnitude in the range M6.8–7.4. However, the degree of deformation preserved in the trench suggests a value closer to the lower magnitude bound. The intensity level observed in Lisbon in 1531 (IX) is lower than the modeled intensities for all considered scenarios and could be related to a particularly high level of vulnerability of the building stock.
Reduced Placental Transfer of Antibodies Against a Wide Range of Microbial and Vaccine Antigens in HIV-Infected Women in Mozambique

Transplacental transfer of antibodies is essential for conferring protection in newborns against infectious diseases. We assessed the impact of different factors, including gestational age and maternal infections such as HIV and malaria, on the efficiency of cord blood levels and placental transfer of IgG subclasses. We measured total IgG and IgG subclasses by quantitative suspension array technology against 14 pathogens and vaccine antigens, including targets of maternal immunization, in 341 delivering HIV-uninfected and HIV-infected mother-infant pairs from southern Mozambique. We analyzed the association of maternal HIV infection, Plasmodium falciparum exposure, maternal variables and pregnancy outcomes on cord antibody levels and transplacental transfer. Our results show that maternal antibody levels were the main determinant of cord antibody levels. Univariable and multivariable analysis showed that HIV reduced the placental transfer and cord levels of IgG and IgG1 principally, but also IgG2 to half of the antigens tested. P. falciparum exposure and prematurity were negatively associated with cord antibody levels and placental transfer, but this was antigen-subclass dependent. Our findings suggest that lower maternally transferred antibodies may underlie increased susceptibility to infections of HIV-exposed infants. This could affect efficacy of maternal vaccination, especially in sub-Saharan Africa, where there is a high prevalence of HIV, malaria and unfavorable environmental factors.
Is Mindfulness Linked to Life Satisfaction? Testing Savoring Positive Experiences and Gratitude as Mediators

Grounded in Mindfulness-to-Meaning Theory, this study examined the relation between dispositional mindfulness and life satisfaction through mediating mechanisms including savoring positive experiences and gratitude. A total of 133 Chinese mindfulness practitioners at 20–72 years old were recruited from a 3-day transnational meditation event in Hong Kong. Findings based on structural equation modeling indicated that controlling for sex, age, education, family income, number of hours of mindfulness practice per week, and type of administration, dispositional mindfulness was associated with satisfaction with life through savoring positive experiences and gratitude as mediators. The findings provided initial evidence for these processes between mindfulness and life satisfaction in the Chinese context. To promote life satisfaction, researchers and mental health practitioners should recognize the chain of mechanisms related to mindfulness.
Repeat-Driven Generation of Antigenic Diversity in a Major Human Pathogen, Trypanosoma cruzi

Trypanosoma cruzi, a zoonotic kinetoplastid protozoan parasite, is the causative agent of American trypanosomiasis (Chagas disease). Having a very plastic, repetitive and complex genome, the parasite displays a highly diverse repertoire of surface molecules, with pivotal roles in cell invasion, immune evasion and pathogenesis. Before 2016, the complexity of the genomic regions containing these genes impaired the assembly of a genome at chromosomal level, making it impossible to study the structure and function of the several thousand repetitive genes encoding the surface molecules of the parasite. We here describe the genome assembly of the Sylvio X10/1 genome sequence, which since 2016 has been used as a reference genome sequence for T. cruzi clade I (TcI), produced using high coverage PacBio single-molecule sequencing. It was used to analyze deep Illumina sequence data from 34 T. cruzi TcI isolates and clones from different geographic locations, sample sources and clinical outcomes. Resolution of the surface molecule gene distribution showed the unusual duality in the organization of the parasite genome, a synteny of the core genomic region with related protozoa flanked by unique and highly plastic multigene family clusters encoding surface antigens. The presence of abundant interspersed retrotransposons in these multigene family clusters suggests that these elements are involved in a recombination mechanism for the generation of antigenic variation and evasion of the host immune response on these TcI strains. The comparative genomic analysis of the cohort of TcI strains revealed multiple cases of such recombination events involving surface molecule genes and has provided new insights into T. cruzi population structure.
Descriptive Analysis of Real-World Data on Fingolimod Long-Term Treatment of Young Adult RRMS Patients

Background: Fingolimod (Gilenya®) is approved for adult and pediatric patients with highly active relapsing–remitting multiple sclerosis (RRMS). Objectives: The objective was to describe the effectiveness of fingolimod in young adults compared to older patients in clinical practice. Methods: PANGAEA is the largest prospective, multi-center, non-interventional, long-term study evaluating fingolimod in RRMS. We descriptively analyzed demographics, MS characteristics, and severity in two subgroups of young adults (≤20 and >20 to ≤30 years) and older patients (>30 years). Results: Young adults had lower Expanded Disability Status Scale (EDSS) scores compared to older patients (1.8 and 2.3 vs. 3.2) at baseline. The mean EDSS scores remained stable over 5 years in all subgroups. Young adults had higher annual relapse rates (2.0 and 1.7 vs. 1.4) at study entry, which were reduced by approximately 80% in all subgroups over 5 years. The proportion of patients with no clinical disease activity in year 4 was 52.6 and 73.4 vs. 66.9% in patients ≤20, >20 to ≤30 years and >30 years, respectively. The symbol digit modalities test score increased by 15.25 ± 8.3 and 8.3 ± 11.3 (mean ± SD) from baseline in patients >20 to ≤30 and >30 years. Conclusions: Real-world evidence suggests a long-term treatment benefit of fingolimod in young RRMS patients.
Indian Medicinal Plants and Formulations and Their Potential Against COVID-19–Preclinical and Clinical Research

The cases of COVID-19 are still increasing day-by-day worldwide, even after a year of its first occurrence in Wuhan city of China. The spreading of SARS-CoV-2 infection is very fast and different from other SARS-CoV infections possibly due to structural differences in S proteins. The patients with severe diseases may die due to acute respiratory distress syndrome (ARDS) caused by systemic inflammatory reactions due to the excessive release of pro-inflammatory cytokines and chemokines by the immune effector cells. In India too, it is spreading very rapidly, although the case fatality rate is below 1.50% (https://www.statista.com), which is markedly less than in other countries, despite the dense population and minimal health infrastructure in rural areas. This may be due to the routine use of many immunomodulator medicinal plants and traditional AYUSH formulations by the Indian people. This communication reviews the AYUSH recommended formulations and their ingredients, routinely used medicinal plants and formulations by Indian population as well as other promising Indian medicinal plants, which can be tested against COVID-19. Special emphasis is placed on Indian medicinal plants reported for antiviral, immunomodulatory and anti-allergic/anti-inflammatory activities and they are categorized for prioritization in research on the basis of earlier reports. The traditional AYUSH medicines currently under clinical trials against COVID-19 are also discussed as well as furtherance of pre-clinical and clinical testing of the potential traditional medicines against COVID-19 and SARS-CoV-2. The results of the clinical studies on AYUSH drugs will guide the policymakers from the AYUSH systems of medicines to maneuver their policies for public health, provide information to the global scientific community and could form a platform for collaborative studies at national and global levels. It is thereby suggested that promising AYUSH formulations and Indian medicinal plants must be investigated on a priority basis to solve the current crisis.