Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis on the Optimum Location of an Wet Air Cleaner in a Livestock House using CFD technology

ABSTRACT In South Korea, as the living standard has been getting higher, meat consumption is steadily increasing. To meet the country's demand, livestock houses become larger and wider with increased raising density. In larger livestock houses, pollutants such as flake of pig skin, excrement, odor, various dusts and noxious gas like ammonia are excessively accumulated inside the facility. These will cause weak immunity for the pigs, diminution of productivity and degeneration of working condition. These problems can be solved through the ventilation performance of the facility. In the winter time, ventilation must be controlled to minimum to maintain a suitable thermal condition. However, this affects the other internal environmental condition because of the minimum ventilation. The installation of “wet air cleaner” especially in the winter time can be an alternative solution. For efficient application of this machine, there is a need to understand the existing ventilation condition and analyze the interaction of existing ventilation system with the wet air cleaner considering its appropriate location. In this study, the existing ventilation system as well as the internal environmental condition negatively inside the facility with the wet air cleaner has been studied using CFD technology. The CFD simulation model was validated from the study conducted by Seo et al. (2008). Results show that the elimination rate of ammonia was 39.4 % and stability could be improved to 35.1 % (Comparing case 5 to 1 where wet air cleaner machine was not used). It can therefore be concluded that case 5 shows the optimum location of a wet air cleaner in the livestock house.
THE INDIAN SOCIETY FOR HYDRAULICS JOURNAL OF HYDRAULIC ENGINEERING BEHAVIOUR OF NON-LINEAR FLOW AND APPLICATION OF NEURAL NETWORK IN CONVERGING BOUNDARIES

The objective of this study is to develop NNCF (Neural Network on Convergent Flow) models on "Convergent Flow Through Homogeneous Porous Media" to predict the friction factor ( fk) and Reynolds number ( R k) for different ( C w-) values, when the media is packed in convergent boundaries. This paper presents the results of experiments conducted on Convergent flow permeameter using crushed rock of size 4.73 mm as the media and water as fluid. Theoretical curves, similar to the Moody diagram used in pipe, relating fk and R k for different C w values taken as the third parameter have been developed and the experimental data and the data predicted by using NNCF models are plotted on theoretical curves using square root of intrinsic permeability as characteristic length.
Capital Account Liberalization and Inequality; by Davide Furceri and Prakash Loungani; IMF Working Paper WP/15243; November 2015

This paper examines the distributional impact of capital account liberalization. Using panel data for 149 countries from 1970 to 2010, we find that, on average, capital account liberalization reforms increase inequality and reduce the labor share of income in the short and medium term. We also find that the level of financial development and the occurrence of crises play a key role in shaping the response of inequality to capital account liberalization reforms. JEL Classification Numbers: F13, G32, O11.
Hybrid Decision Support System Framework for Leaf Image Analysis to Improve Crop Productivity

Crop disease is one of the major problems with agriculture in India. Identifying the disease and classifying the type of disease is most important which can be made possible using the deep learning technique. To perform this verified dataset is required which consists of healthy and disease leaf images of all crops. The proposed model uses a hybrid approach which integrates VGG16 classifier with an attention mechanism, transfer learning approach and dropout operation. The proposed model uses a rice disease dataset and using the proposed approach it achieves an train accuracy of 96.45 percent and train loss 0.09 and validation loss of 0.44. The dataset is collected from the plant village project for rice leaf which consists of 4955 images which include Brown Spot, Healthy, Hipsa, and Leaf Blast type of images. The proposed model use attention mechanism that focuses mainly on the part of the image rather than the whole part of the image using a glimpse ratio of 3:1. The traditional method of detecting crop diseases needs high experience and knowledge of experts in the field which is time consuming, ineffective, and high cost. In this study, Deep Convolutional Neural Networks (DCNN) and Transfer Learning with Attention models are used to detect diseases associated with rice plants without overfitting the model. Keywords—Deep learning; activation function; attention mechanism; dropout operation; transfer learning; VGG16
The basic psychological needs satisfaction and frustration scale at work: A validation in the Polish language

The aim of this research project was to validate the work-related version of the Basic Psychological Need Satisfaction and Frustration Scale (BPNSFS) into the Polish language and culture. Although studies have demonstrated the benefits associated with basic psychological need satisfaction and the costs associated with need frustration at work, the concept of needs has been neglected both in Polish scientific research and in practical organizational studies. The adaptation of the BPNSFS-Work Domain may change this situation and stimulate research in the Polish community. The scale has been validated in a sample consisting of three occupational groups: healthcare workers, education staff and customer service workers (N = 1315, Mage = 43.8). The findings suggest that the Polish scale has robust psychometric features. The CFA analysis proves that the scale has a six-dimensional structure similar to the original scale. These dimensions show satisfactory to high Cronbach’s α and McDonalds ω reliability, and high criterion validity is shown by association of the six need dimensions with correlates of both positive (i.e., engagement, job crafting and self-efficacy) and negative aspects of work (i.e., burnout and stress). The structure of the scale is the same in all three occupational groups, although the regression weights and covariances are only partially invariant. The validated version of the BPNSFS-Work Domain can be used in future basic and applied studies in the paradigm of self-determination theory.
Prevalence of Depression Among Patients With Type 2 Diabetes at King Abdullah Medical City

Introduction Diabetes is one of the most common endocrine diseases worldwide. Type 2 diabetes and depression are commonly comorbid, high-prevalence, chronic disorders. Individuals with diabetes mellitus may have concurrent mental health disorders and are shown to have poorer disease outcomes. However, the evidence for clinical correlation is still unclear. Objectives To find the prevalence of depression among patients with type 2 diabetes at King Abdullah Medical City (KAMC). Materials and methods A cross-sectional observational study was conducted at KAMC in Makkah, the Kingdom of Saudi Arabia. Study participants were 267 people with type 2 diabetes (aged between 18-70 years). Those who had preexisting depression or drank alcohol, pregnant women, and postpartum women were excluded from the study. Participants’ clinical and demographic data and depression assessment were obtained on phone through an interview and using the Arabic version of the Patient Health Questionnaire-9 (PHQ-9), respectively. Glycated hemoglobin (HbA1c) test results of participants were collected electronically. Results The participants’ mean age was 57.88 ± 8.71 years, and 64.4% were males. Only 15.4% were current smokers and 16.9% were ex-smokers. The most common medical condition was hypertension (65.2%) and the majority (92.1%) had uncontrolled HbA1c with a mean value of 8.37 ± 1.92. Among the studied patients, 73% suffered from different degrees of depression; 36%, 19.9%, 8.6%, 5.2%, and 3.4% of the participants were suffering from minimal, mild, moderate, moderately severe, and severe depression, respectively. Only neuropathy was a significant risk factor of depression (odds ratio=2.87, 95% confidence interval=1.18-6.97, p=0.02). Conclusion Depressive symptoms are common in patients with uncontrolled type 2 diabetes who also suffer from neuropathy and retinopathy. Hypertension, cardiovascular diseases, and unhealthy diet had a significant correlation with depression.
Morpho-physiological and biochemical attributes of Chili (Capsicum annum L.) genotypes grown under varying salinity levels

Climate change is causing soil salinization, resulting in huge crop losses throughout the world. Multiple physiological and biochemical pathways determine the ability of plants to tolerate salt stress. Chili (Capsicum annum L.) is a salt-susceptible crop; therefore, its growth and yield is negatively impacted by salinity. Irreversible damage at cell level and photo inhibition due to high production of reactive oxygen species (ROS) and less CO2 availability caused by water stress is directly linked with salinity. A pot experiment was conducted to determine the impact of five NaCl salinity levels, i.e., 0,1.5, 3.0, 5.0 and 7.0 dS m-1 on growth, biochemical attributes and yield of two chili genotypes (‘Plahi’ and ‘A-120’). Salinity stress significantly reduced fresh and dry weight, relative water contents, water use efficiency, leaf osmotic potential, glycine betaine (GB) contents, photosynthetic rate (A), transpiration rate (E), stomatal conductance (Ci), and chlorophyll contents of tested genotypes. Salinity stress significantly enhanced malondialdehyde (MDA) contents and activities of the enzymatic antioxidants such as superoxide dismutase (SOD), catalase (CAT) and peroxidase (POD). In addition, increasing salinity levels significantly reduced the tissue phosphorus and potassium concentrations, while enhanced the tissue sodium and chloride concentrations. Genotype ‘Plahi’ had better growth and biochemical attributes compared to ‘A-120’. Therefore, ‘Plahi’ is recommended for saline areas to improve chili production.
Based on improved deep convolutional neural network model pneumonia image classification

Pneumonia remains the leading infectious cause of death in children under the age of five, killing about 700,000 children each year and affecting 7% of the world’s population. X-ray images of lung become the key to the diagnosis of this disease, skilled doctors in the diagnosis of a certain degree of subjectivity, if the use of computer-aided medical diagnosis to automatically detect lung abnormalities, will improve the accuracy of diagnosis. This research aims to introduce a deep learning technology based on the combination of Xception neural network and long-term short-term memory (LSTM), which can realize automatic diagnosis of patients with pneumonia in X-ray images. First, the model uses the Xception network to extract the deep features of the data, passes the extracted features to the LSTM, and then the LSTM detects the extracted features, and finally selects the most needed features. Secondly, in the training set samples, the traditional cross-entropy loss cannot more balance the mismatch between categories. Therefore, this research combines Pearson’s feature selection ideas, fusion of the correlation between the two loss functions, and optimizes the problem. The experimental results show that the accuracy rate of this paper is 96%, the receiver operator characteristic curve accuracy rate is 99%, the precision rate is 98%, the recall rate is 91%, and the F1 score accuracy rate is 94%. Compared with the existing technical methods, the research has achieved expected results on the currently available datasets. And assist doctors to provide higher reliability in the classification task of childhood pneumonia.
Capturing Contentiousness: Constructing the Contentious Terms in Context Corpus

Recent initiatives by cultural heritage institutions in addressing outdated and offensive language used in their collections demonstrate the need for further understanding into when terms are problematic or contentious. This paper presents an annotated dataset of 2,715 unique samples of terms in context, drawn from a historical newspaper archive, collating 21,800 annotations of contentiousness from expert and crowd workers. We describe the contents of the corpus by analysing inter-rater agreement and differences between experts and crowd workers. In addition, we demonstrate the potential of the corpus for automated detection of contentiousness. We show that a simple classifier applied to the embedding representation of a target word provides a better than baseline performance in predicting contentiousness. We find that the term itself and the context play a role in whether a term is considered contentious.
TOBI, a vehicle for deep ocean survey

TOBI is an instrumented vehicle which is towed close to the bottom of the deep ocean from a ship, and uses sound to form detailed images of the sea floor. The authors describe the mechanical design of this vehicle and its instrument package. The way in which sonar images are formed is discussed and the acoustic design parameters are considered. Signals are frequency multiplexed on to 10 km of armoured coaxial towing cable, which also provides the power to the vehicle and a two-way communication link. At the ship these signals are separated, displayed and logged onto magneto-optical cartridges. Examples of results are shown and some future developments are identified.
A Highly Selective and Sensitive Spectrophotometric Method for the Determination of Lead at Ultra-trace Levels in Some Real, Environmental, Biological, Food and Soil Samples Using 5,7-Dibromo-8-Hydroxyquinoline

A very simple, ultra-sensitive and highly selective non-extractive spectrophotometric method for the determination of trace amounts of lead using 5,7-dibromo-8-hydroxyquinoline (DBHQ) has been developed. DBHQ reacts in a slightly acidic (0.0006-0.0025 M HCl) aqueous solution with lead (II) in 30% ethanolic media to produce highly absorbent a greenish-yellow chelate which has an absorption maximum at 390 nm. The reaction is instantaneous and the absorbance remains stable for over 24 h. The average molar absorption co-efficient and Sandal’s sensitivity were found to be 6.16 x 105 L mol-1cm-1 and 5 ng cm-2 of lead (II), respectively. Linear calibration graphs were obtained for 0.01- 60.0 mg L-1 of lead (II) having detection limit of 1.0 μg L-1 and RSD 0-2%. The stoichiometric composition of the chelate is 1:2 (Pb: DBHQ). A large excess of over 60 cations, anions and complexing agents (like, chloride, phosphate, azide, tartrate, oxalate, SCN- etc.) do not interfere in the determination. The developed method was successfully used in the determination of lead levels in several Standard Reference Materials (alloys, steels, natural water, bovine liver, human urine and hair) as well as in some environmental waters (potable and polluted), biological samples (human blood, urine and hair), soil samples, food samples (vegetables, rice, wheat) solutions containing both lead (II) and lead (IV) and complex synthetic mixtures. The results of biological and food analyses by the spectrophotometric method were found to be in excellent agreement with those obtained by AAS.
EPIDEMIOLOGY EVALUATION OF ATHLETIC INJURY IN UNIVERSITY CENTER

Introduction: Athletics is a sport with varied modalities, which are based on patterns and activities that are natural to human beings. As a sport, it has several benefits, such as improved physical condition and interpersonal interactions, but it is not free from risks, especially injuries related to competitions or training. Objectives: Characterize injuries presented by the university athletics group of the medical course and identify possible risk factors. Methods: Participants, enrolled in the athletics group of the medicine course, of both sexes, had anthropometric measurements evaluated and answered an injury screening questionnaire modified from the "Injury Surveillance System". Results: 31 participants responded to the questionnaire where 65% of them had at least one injury. A total of 23 injuries were reported, 20 of which were serious, with no significant difference between both sexes. The total practice time was almost 2 times longer in injured practitioners than in non-injured ones. Conclusion: The practice of university athletics is associated with a high occurrence of serious injuries.
Transcranial Direct Current Stimulation Does Not Affect Sprint Performance or the Horizontal Force-Velocity Profile

ABSTRACT Purpose: The aim of this study was to explore the effects of transcranial direct current stimulation (tDCS) on sprint performance and the horizontal force-velocity (F-v) profile. Method: Thirty-two healthy subjects (25 men and 7 women; age = 21.8 ± 2.4 years) completed three sessions separated by 1 week following a double-blinded crossover design. Each session consisted of two maximal sprints of 30 meters that were performed after applying ANODAL, CATHODAL or SHAM tDCS over the left dorsolateral prefrontal cortex (DLPFC) for 15 minutes at 2 mA. The 30-m time and the horizontal F-v profile variables (theoretical maximal force [F 0], theoretical maximal velocity, Fv slope, maximal power [Pmax], decrease in the ratio of horizontal-to-resultant force, and maximal ratio of horizontal-to-resultant force) were compared between the tDCS conditions. Results: No significant differences between the tDCS conditions were observed for any variable (p range = 0.061 to 0.842). The magnitude of the differences was negligible for most of the comparisons (effect size [ES] < 0.20) with the only exception of Pmax and F 0 which were greater for the ANODAL compared to the SHAM condition (both ES = 0.20). Conclusions: The application of tDCS over the DLPFC is not effective to increase non-fatigued sprint performance.
The 4K reference load for the Planck low frequency instrument

The Low Frequency Instrument (LFI) on-board the Planck satellite, is composed by an array of 54 receivers. They follow a pseudo-correlation scheme, continuously observing the sky and a stable reference load, at a temperature T∼4 K. The so-called 4 K Reference Load is made of 54 small absorbing targets, mechanically and thermally connected to the High Frequency Instrument (HFI) cryostat. The 4K Reference Load requirements pose severe limits to its mass, dimensions, power dissipation and performance.
Statistical distractor learning modulates perceptual sensitivity

The present study used perceptual sensitivity (d′) to determine the spatial distribution of attention in displays in which participants have learned to suppress a location that is most likely to contain a distractor. Participants had to indicate whether a horizontal or a vertical line, which was shown only briefly before it was masked, was present within a target shape. Critically, the target shape could be accompanied by a singleton distractor color, which when present appeared with a high probability at one display location. The results show that perceptual sensitivity was reduced for locations likely to contain a distractor, as d′ was lower for this location than for all other locations in the display. We also found that the presence of an irrelevant color singleton reduced the gain for input at the target location, particularly when the irrelevant singleton was close to the target singleton. We conclude that, through the repeated encounter with a distractor at a particular location, the weights within the attentional priority map are changed such that the perceptual sensitivity for objects presented at that location is reduced relative to all other locations. This reduction of perceptual sensitivity signifies that this location competes less for attention than all other locations.
Opportunities in high-power fiber lasers

Fiber lasers and amplifiers offer unique characteristics that are derived from the use of a waveguide and the properties of rare-earth doped silica glass. Their capability for high output power, with high efficiency, has been demonstrated both in CW and pulsed regimes. Cladding-pumped Yb-doped fiber lasers have now reached beyond kW levels with good beam quality. Advances in both fiber technology and high-power multimode diode pump sources, and the inherent power scalability of cladding-pumped fibers, lie behind this power surge. However, there are still many challenges to overcome in the high-power fiber laser area. These include, for example, single-mode output at higher powers and power scaling of a three-level laser. This paper reviews novel W-type fiber and depressed clad hollow optical fiber waveguide structures designed with distributed wavelength filter characteristics to achieve an efficient and high power cladding-pumped three-level lasers such as Nd-doped fiber laser operating at 930 nm and Yb-doped fiber laser at 980 nm. Moreover, such fiber geometries enable to scale up the output power in a small and single-mode core for generating a single-mode output beam in a robust and reliable manner.
Specific age‐correlated activation of top hierarchical motor control areas during gait‐like plantar stimulation: An fMRI study

A better understanding of gait disorders that are associated with aging is crucial to prevent adverse outcomes. The functional study of gait remains a thorny issue due to technical constraints inherent to neuroimaging procedures, as most of them require to stay supine and motionless. Using an MRI‐compatible system of boots reproducing gait‐like plantar stimulation, we investigated the correlation between age and brain fMRI activation during simulated gait in healthy adults. Sixty‐seven right‐handed healthy volunteers aged between 20 and 77 years old (49.2 ± 18.0 years; 35 women) were recruited. Two paradigms were assessed consecutively: (a) gait‐like plantar stimulation and (b) chaotic and not gait‐related plantar stimulation. Resulting statistical parametric maps were analyzed with a multiple‐factor regression that included age and a threshold determined by Monte‐Carlo simulation to fulfill a family‐wise error rate correction of p < . 05. In the first paradigm, there was an age‐correlated activation of the right pallidum, thalamus and putamen. The second paradigm showed an age‐correlated deactivation of both primary visual areas (V1). The subtraction between results of the first and second paradigms showed age‐correlated activation of the right presupplementary motor area (Brodmann Area [BA] 6) and right mid‐dorsolateral prefrontal cortex (BA9‐10). Our results show age‐correlated activity in areas that have been associated with the control of gait, highlighting the relevance of this simulation model for functional gait study. The specific progressive activation of top hierarchical control areas in simulated gait and advancing age corroborate a progressive loss of automation in healthy older adults.