Miracle-dz/UniFAR-FTUs huggingface dataset:
Sexual and Reproductive Health Vulnerabilities of Young People in Jharkhand

Jharkhand is, one of the few states in the country that has developed a specific youth policy in which its commitment to redressing youth vulnerabilities is outlined. The Jharkhand Youth Policy 2007 recognises the need to empower youth and reduce their vulnerabilities. It advocates multi-sectoral actions in the areas of education, employment and health; and it recognises the importance of making youth friendly services accessible and of strengthening the capacity of service providers to address the needs of youth in acceptable ways. Moreover, it underscores the importance of providing counselling and services to youth, addressing their nutritional and reproductive health vulnerabilities and countering early marriage. Efforts to improve the sexual and reproductive health of youth are reiterated in the state’s Health Policy. The objective of this paper is to synthesise, from available evidence, what is known about the sexual and reproductive health of young people in Jharkhand, and draw from this synthesis, implications for policy and programmes.
The Grammars of Conjunction Agreement in Slovenian Franc

In this paper we report on the results of five experiments documenting the existence of three distinct grammars of conjunct agreement in Slovenian, found both within and across individuals: agreement with the highest conjunct, agreement with the closest conjunct, or agreement with the Boolean Phrase itself. We show that this variation is constrained and that some of these mechanisms can be blocked and/or forced depending on the properties of the conjuncts. Finally, we offer the suggestion that the presence of intraindividual variation arises because of ambiguous properties of the primary linguistic data.
Age-Based Scheduling Policy for Federated Learning in Mobile Edge Networks

Federated learning (FL) is a machine learning model that preserves data privacy in the training process. Specifically, FL brings the model directly to the user equipments (UEs) for local training, where an edge server periodically collects the trained parameters to produce an improved model and sends it back to the UEs. However, since communication usually occurs through a limited spectrum, only a portion of the UEs can update their parameters upon each global aggregation. As such, new scheduling algorithms have to be engineered to facilitate the full implementation of FL. In this paper, based on a metric termed the age of update (AoU), we propose a scheduling policy by jointly accounting for the staleness of the received parameters and the instantaneous channel qualities to improve the running efficiency of FL. The proposed algorithm has low complexity and its effectiveness is demonstrated by Monte Carlo simulations.
DiaNet: BERT and Hierarchical Attention Multi-Task Learning of Fine-Grained Dialect

Prediction of language varieties and dialects is an important language processing task, with a wide range of applications. For Arabic, the native tongue of ~ 300 million people, most varieties remain unsupported. To ease this bottleneck, we present a very large scale dataset covering 319 cities from all 21 Arab countries. We introduce a hierarchical attention multi-task learning (HA-MTL) approach for dialect identification exploiting our data at the city, state, and country levels. We also evaluate use of BERT on the three tasks, comparing it to the MTL approach. We benchmark and release our data and models.
Tweeting the Night Away: Using Twitter to Enhance Social Presence

To be truly effective, online learning must facilitate the social process of learning. This involves providing space and opportunities for students and faculty to engage in social activities. Although learning management systems offer several tools that support social learning and student engagement, the scope, structure, and functionality of those tools can inhibit and restrain just-in-time social connections and interactions. In this teaching tip, we describe our use of Twitter to encourage freeflowing just-in-time interactions and how these interactions can enhance social presence in online courses. We then describe instructional benefits of Twitter, and conclude with guidelines for incorporating Twitter in online courses.
Decadal variability of droughts and floods in the Yellow River basin during the last five centuries and relations with the North Atlantic SST

Droughts and floods are frequent disasters in the Yellow River basin in northern China. They have a strong impact on agriculture and water resource management. To explore the physical mechanisms of these droughts and floods, influences exerted by the sea surface temperature (SST) anomalies in the mid‐latitude North Atlantic on the wetness and dryness in the Yellow River basin have been investigated. The drought/flood index (DFI), derived from a reconstructed dataset covering the last five centuries, is used. Numerical simulations are conducted with the Community Atmospheric Model version 3.0 (CAM3) to study the influence of various mechanisms. It is found that DFI in the entire Yellow River basin experienced oscillations at about 50–60 years during the past five centuries. Droughts and floods have inconsistent patterns in different areas of the Yellow River. The periodic variation of DFI in Xi'an, a station in a semi‐humid subarea, is in contrast to the North Atlantic SST (10°N–55°N and 70°W–10°W) oscillation in spring and summer; the periodic variation of the Yinchuan DFI in a semi‐arid subarea (the upper reaches of Yellow River) correlates with the North Atlantic SST oscillation variation in spring and summer. The North Atlantic SST is probably one of the key sources of internal variability of the climate system, which results in Rossby wave adjusting. The warm phase of the North Atlantic SST is related to the operation of a Northern Atlantic Oscillation (NAO) like pattern conducive to easterly wind anomalies in northern China and enhances anti‐cyclones around Lake Baikal that leads to less precipitation or more frequent droughts in the semi‐arid subarea in the upper reaches of the Yellow River, but wet conditions in the semi‐humid subarea in the middle reaches, monsoon subarea in the lower reaches and plateau subarea in the upper reaches of the river.
Spatial distribution of Calomera littoralis nemoralis (Olivier, 1790) in a coastal habitat of Southern Italy and its importance for conservation (Coleoptera Carabidae Cicindelinae)

The spatial distribution of Calomera littoralis nemoralis (Olivier, 1790) (Coleoptera Carabidae Cicindelinae) was studied on the marine sandy beach area of 1 km, near the mouth of a stream in Catanzaro province (Southern Italy, Calabria). During the sampling period (July-August 2011- 2012) we investigated the distribution of adults of C. littoralis nemoralis by visual census method and the spatial distribution of larval burrows of C. littoralis nemoralis along three transects (A, B, parallel to the coast line; C, embracing the river mouth). All the transects were selected by soil microclimate (a higher or lower humidity) and food availability. Larval burrows distribution was performed using QGIS. The dispersal index (ID) shows regular distribution of adults along transects A and B while in C the individuals are aggregated. Concerning the larval galleries distribution, the QGIS analysis shows a significant difference in their spatial distribution. The sampled data were analyzed using univariate and multivariate statistical methods. This is the first report on spatial distribution of adults and larvae of C. littoralis nemoralis in relation to soil humidity and food availability. The adult home range of this species is much larger than the reproductive habitat, that seems limited to wet sandy river bank around the mouth. The importance of such experimental studies for cicindelid conservation is briefly discussed.
Paediatric tuberculosis in a low burden setting of Saudi Arabia: Drug and multidrug resistance patterns

In this study, the infection of young children with Mycobacterium tuberculosis and drug-resistant M. tuberculosis in a mass gathering area in Al-Madinah Al-Munawwarah, was investigated and discussed. All the children, 15 years old and younger, who were referred to the central tuberculosis laboratory in Al-Madinah between January 2012 and December 2014 were included in this study. Among a total of 622 registered new cases, 68 (10.9%) were children, males were 40 (58.8%) while 28 (41.2 %) were females. All the children were vaccinated with Bacillus Calmette-Guerin (BCG) within their first week of birth. Sixty (88.2%) children were infected with M. tuberculosis, whereas 8 (11.8%) had non tuberculous mycobacteria (NTM). Clinically, pulmonary tuberculosis was confirmed in 20 (29.4%) cases, whereas the remaining 48 (70.6%) had extra pulmonary tuberculosis. Multidrug-resistant M. tuberculosis (MDR) was isolated from 3 (4.4%) cases, all of whom were younger than five years; one with pulmonary and two with extrapulmonary tuberculosis. All the isolated MDR organisms belonged to the M. tuberculosis complex. The rates of mono-resistance to isoniazid (H), streptomycin (S), ethambutol (E) and pyrazinamide (Z) were 5.9, 1.5, 5.9 and 8.8%, respectively. No case was registered as mono-resistant to rifampin (R). The prevalence of childhood tuberculosis in the current study area is higher than the globally estimated rate. Since all the cases were new, MDR-TB was mostly due to infection with originally MDR strains. Key words: Mycobacteria, polymerase chain reaction, resistance, antibiotics, antimicrobials.
Optimal control for conservation laws in presence of shocks

This notes contain a short introduction to the the study of numerical approximation of control problems for conservation laws in presence of shocks. We are mainly interested in aerodynamic applications where problems are formulated in a very complex framework with a large number of constraints. Here we present and analyze simplied models where some of the main diculties arise and are easier to understand.
Differences in Dietary Components and Oxidative Stress Markers between Cervical Cancer Patients and Matched Controls

Background and objective: Cervical cancer is a leading cause of death among women in developing countries. Diet has been suggested to play an important role in the pathophysiology of malignant tumors as an imbalance between dietary antioxidant intake and free radical production-from the inflammatory stateresults in oxidative stress, which may contibute to both initiation and progression of carcinogenesis. The aims of the present study were to assess the difference regarding dietary intake and oxidative stress plasmatic markers differences between cervical cancer patients and matched controls. Methods: A case-control study -nested within a larger clinical trialincluding 100 patients diagnosed with locally advanced cervical cancer and 80 women without the malignant disease was conducted. A food frequency questionnaire was used for assessing diet. Plasmatic oxidative stress markers -malondialdehyde and free carbonylswere also determined. Results: Patients with cervical cancer presented a significantly higher body mass index and higher consumption of dietary protein and fat, niacin, cholesterol, sodium, cyanocobalamin, vitamin E, and zinc. A significantly lower intake of vitamin C was found in the case group. MDA levels were found to be statistically higher in cervical cancer patients while free carbonyls did not show significant differences. Conclusions: A high-fat/high-protein diet, together with lower consuption of ascorbic acid may contribute to an increase risk of developing cervical cancer. However, further prospective and longitudinal research should be promoted in order to elucidate such associations.
Selecting Energy Efficient Poultry Egg Producers: A Fuzzy Data Envelopment Analysis Approach

This study examined the energy use pattern of poultry for egg production farms of Iran and ranked the selected farmers using fuzzy data envelopment analysis (FDEA) from the viewpoint of energy efficiency. Since data used in our study were not measured precisely, fuzzy forms of them could help us to reach the ideal situations. Hence, the conventional data envelopment analysis (DEA) was remodeled using triangular fuzzy numbers and finally the resulted efficiency scores of decision making units (DMUs) were compared. Those with efficiency score of less than one were reported as inefficient units and they were also ranked by calculating an index. The results of this study indicated that from 40 poultry farms selected randomly, 33 of them were inefficient. FDEA was performed using α-cut approach and eleven α-levels (0 to 1 by 0.1) were examined. According to our results, the efficiency scores showed a decreasing trend as α- levels increasing to crisp situations. It is obvious that applying fuzzy data can show the real situation more accurately. Based on the results of this study, decision makers and farmers can improve their attitudes against energy use and applying well established practices. To achieve this, firstly, we should distinguish efficient units from inefficient ones.
Energy-Efficient Data Collection by Mobile Sink in Wireless Sensor Networks

This paper is to explore how to enhance the benefits of mobile sink data collection in the wireless sensor network (WSN). Mobile sink moves along a scheduled route to collect data. A shorten traveling salesman problem (TSP) route is explored in this study. Along the resultant route, energy efficiency is achieved for the mobile sink to collect data in a round. Finally, experimental results show that the total energy consumption of mobile sink consumed including the sensor communication and the sink movement distances compared to the existing work can be minimized.
Learning Depth from Endoscopic Images

We propose an unsupervised approach to predict depth maps from images captured by a wireless endoscopic capsule. Recent advances in deep learning have shown that accurate depth maps can be predicted from a single image, where the deep network is trained via unsupervised or self-supervised learning by using monocular video sequences or stereo image pairs. However, directly applying these techniques to endoscopic images does not yield satisfactory results owing to the inherent difficulties of the wireless capsule imaging such as dim lighting and low-resolution of images, which are different from normal imaging conditions. For that reason, we exploit the environmental characteristics of endoscopic images — there is no external light source except ones attached to the capsule. Based on this condition, we propose the direct attenuation model-based depth map prediction scheme to guide depth prediction and to add meaningful cues to the loss function. We experimentally verify the proposed method with various endoscopic images.
ELECTRON HEATING IN MAGNETOROTATIONAL INSTABILITY: IMPLICATIONS FOR TURBULENCE STRENGTH IN THE OUTER REGIONS OF PROTOPLANETARY DISKS

The magnetorotational instability (MRI) drives vigorous turbulence in a region of protoplanetary disks where the ionization fraction is sufficiently high. It has recently been shown that the electric field induced by the MRI can heat up electrons and thereby affect the ionization balance in the gas. In particular, in a disk where abundant dust grains are present, the electron heating causes a reduction of the electron abundance, thereby preventing further growth of the MRI. By using the nonlinear Ohm's law that takes into account electron heating, we investigate where in protoplanetary disks this negative feedback between the MRI and ionization chemistry becomes important. We find that the “e-heating zone,” the region where the electron heating limits the saturation of the MRI, extends out up to 80 AU in the minimum-mass solar nebula with abundant submicron-sized grains. This region is considerably larger than the conventional dead zone whose radial extent is ∼20 AU in the same disk model. Scaling arguments show that the MRI turbulence in the e-heating zone should have a significantly lower saturation level. Submicron-sized grains in the e-heating zone are so negatively charged that their collisional growth is unlikely to occur. Our present model neglects ambipolar and Hall diffusion, but our estimate shows that ambipolar diffusion would also affect the MRI in the e-heating zone.
Where is the level of neutral buoyancy for deep convection?

This study revisits an old concept in meteorology ‐ level of neutral buoyancy (LNB). The classic definition of LNB is derived from the parcel theory and can be estimated from the ambient sounding (LNB_sounding) without having to observe any actual convective cloud development. In reality, however, convection interacts with the environment in complicated ways; it will eventually manage to find its own effective LNB and manifests it through detraining masses and developing anvils (LNB_observation). This study conducts a near‐global survey of LNB_observation for tropical deep convection using CloudSat data and makes comparison with the corresponding LNB_sounding. The principal findings are as follows: First, although LNB_sounding provides a reasonable upper bound for convective development, correlation between LNB_sounding and LNB_observation is low suggesting that ambient sounding contains limited information for accurately predicting the actual LNB. Second, maximum mass outflow is located more than 3 km lower than LNB_sounding. Hence, from convective transport perspective, LNB_sounding is a significant overestimate of the “destination” height level of the detrained mass. Third, LNB_observation is consistently higher over land than over ocean, although LNB_sounding is similar between land and ocean. This difference is likely related to the contrasts in convective strength and environment between land and ocean. Finally, we estimate the bulk entrainment rates associated with the observed deep convection, which can serve as an observational basis for adjusting GCM cumulus parameterization.
Optical colours and spectral indices of z = 0.1 eagle galaxies with the 3D dust radiative transfer code skirt

We present mock optical images, broad-band and H α fluxes, and D4000 spectral indices for 30 145 galaxies from the EAGLE hydrodynamical simulation at redshift z = 0.1, modelling dust with the SKIRT Monte Carlo radiative transfer code. The modelling includes a subgrid prescription for dusty star-forming regions, with both the subgrid obscuration of these regions and the fraction of metals in diffuse interstellar dust calibrated against far-infrared fluxes of local galaxies. The predicted optical colours as a function of stellar mass agree well with observation, with the SKIRT model showing marked improvement over a simple dust-screen model. The orientation dependence of attenuation is weaker than observed because EAGLE galaxies are generally puffier than real galaxies, due to the pressure floor imposed on the interstellar medium (ISM). The mock H α luminosity function agrees reasonably well with the data, and we quantify the extent to which dust obscuration affects observed H α fluxes. The distribution of D4000 break values is bimodal, as observed. In the simulation, 20 per cent of galaxies deemed ‘passive’ for the SKIRT model, i.e. exhibiting D4000 >1.8, are classified ‘active’ when ISM dust attenuation is not included. The fraction of galaxies with stellar mass greater than 1010 M that are deemed passive is slightly smaller than observed, which is due to low levels of residual star formation in these simulated galaxies. Colour images, fluxes and spectra of EAGLE galaxies are to be made available through the public EAGLE data base.
POWER OUTPUT DURING THE 1ST AND 2ND PULL PHASES IN THE SNATCH BY WOMEN WEIGHTLIFTERS

The purpose of this study was to compare the power outputs of the 1st, 2nd, and total pulls in the snatch lift for women competing in the 1999 United States national championships. The performance of ten lifters was recorded and analyzed using a Peak5 2D Motion Analysis system. The power output values for the 1st, 2nd, and total pulls ranged from 604.41 W to 2329.45 W, 756.45 W to 4532.75 W, and 702.39 W to 1909.67 W, respectively. These lifters demonstrated statistically significant differences (p < 0.05) during each phase of the snatch pull, and total power output values were comparable to values previously reported (Garhammer, 1991). Knowledge of the power output during each phase of the pull may help athletes to fully refine the training leading to competition.
Augment to Prevent: Short-Text Data Augmentation in Deep Learning for Hate-Speech Classification

In this paper, we address the issue of augmenting text data in supervised Natural Language Processing problems, exemplified by deep online hate speech classification. A great challenge in this domain is that although the presence of hate speech can be deleterious to the quality of service provided by social platforms, it still comprises only a tiny fraction of the content that can be found online, which can lead to performance deterioration due to majority class overfitting. To this end, we perform a thorough study on the application of deep learning to the hate speech detection problem: a) we propose three text-based data augmentation techniques aimed at reducing the degree of class imbalance and to maximise the amount of information we can extract from our limited resources and b) we apply them on a selection of top-performing deep architectures and hate speech databases in order to showcase their generalisation properties. The data augmentation techniques are based on a) synonym replacement based on word embedding vector closeness, b) warping of the word tokens along the padded sequence or c) class-conditional, recurrent neural language generation. Our proposed framework yields a significant increase in multi-class hate speech detection, outperforming the baseline in the largest online hate speech database by an absolute 5.7% increase in Macro-F1 score and 30% in hate speech class recall.