Miracle-dz/UniFAR-FTUs huggingface dataset:
In-Field Emission Measurements from Biogas and Liquified Petroleum Gas (LPG) Stoves

Household air pollution from solid fuel cooking causes millions of deaths each year and contributes to climate change. These emissions can be reduced if households transition to cleaner cooking fuels such as LPG or biogas, yet emission measurements during actual use are limited. Six LPG and 57 biogas cooking event emissions were measured during typical cooking practices in Nepal. Emission factors are reported for elemental carbon (EC), organic carbon (OC), particulate matter (PM 2.5 ), and carbon monoxide (CO) and compared to measurements from wood stoves in the same households. Biogas cooking emission factors were 7.4 ± 10.9 mg MJ − 1 for PM 2.5 and 0.2 ± 0.3 mg MJ − 1 for EC on a fuel energy basis, and were not significantly different from LPG stoves (9.5 ± 6.8 mg MJ − 1 for PM 2.5 and 0.3 ± 0.3 mg MJ − 1 for EC, p > 0.05). Wood stoves emitted 50 times more PM 2.5 than biogas on a fuel energy basis and 230 times more EC. EC emissions were about 3% of total particle emissions from biogas and LPG stoves. Most PM 2.5 emissions from gas stoves were attributed to food frying and stove ignition (90%), not the gas fuel (10%), implying that there is a limit to emission reductions that can be achieved with improved fuels.
Conjunctival mycoflora in patients presenting to eye ward of Imam Khomeini Hospital, Ahvaz.

Objectives: To investigate the incidence of fungal mycoflora of conjunctiva in patients attending teaching department of ophthalmology, Imam Khomeini Hospital, Ahvaz, Iran. Methodology: One hundred and seventy two swabs were collected from the conjunctiva of patients attending to eye ward of the hospital during autumn 2007 to summer 2008. Swabs were cultured on Sabouraud’s Dextrose Agar and incubated at ambient temperature for one week. Results: Eleven patients were positive for saprophytic fungi. The most common saprophytic fungus was Cladopsporium (four cases). Other filamentous fungi were Drechslera (one case), Alternaria (one case), Fusarium (one case) and Epicoccum (one case). In addition, three isolates of yeasts include Cryptococcus, Candida albicans and Rhodotorula rubra were also isolated from patients. Conclusion: There was a remarkable presence of fungi in the conjunctiva of patients. The environmental conditions, the socioeconomic status and personal poor hygienic conditions, led to the high incidence of conjunctival fungus isolation (6.4%). The incidence was much higher in males (72.7%) as (27.3%) in females.
A history of “ food addiction ” 1

Concepts of diseases and mental disorders are not set in stone. References to drink madness can be found in ancient civilizations and terms such as drunkenness, intemperance, inebriety, dipsomania, or alcoholism were used in the 18th and 19th centuries to describe substance-related addictive disorders (White, 2000). While the fourth version of the Diagnostic and Statistical Manual of Mental Disorders (DSM) distinguished between substance abuse and substance dependence (American Psychiatric Association, 1994), this distinction has been repealed in its fifth revision. The DSM-5 now lists several substance use disorders and, for the first time, a nonesubstance-related addiction: gambling disorder (American Psychiatric Association, 2013). Similar dynamics can be found in the field of eating disorders. Anorexia nervosa was the first eating disorder included in DSM-I in 1952 and appeared along pica and rumination in DSM-II in 1968 (Dell’Osso et al., 2016). Bulimia nervosa was added to the DSM-III in 1980. The DSM-IV yet again involved some slight changes in the categorization of eating disorders and nowdin addition to changes made to the diagnostic criteria for anorexia and bulimia nervosadthe DSM-5 lists pica, rumination disorder, avoidant/restrictive food intake disorder, anorexia nervosa, bulimia nervosa, binge eating disorder, and other specified eating disorders (e.g., night eating syndrome). In the light of high prevalence rates of obesity in the past decades, there is an increased interest if certain foods may have an addiction potential and if obese individualsdor at least a subgroup of themdcan be considered “food-addicted. ” In fact, it seems widely accepted that “food addiction” is a relatively new idea that was conceived in the past 20 years to explain the rising obesity prevalence (Davis, Edge, & Gold, 2014; Yau, Gottlieb, Krasna, & Potenza, 2014). Yet, is this CHAPTER
Use of A Neural Network-Based Ocean Body Radiative Transfer Model for Aerosol Retrievals from Multi-Angle Polarimetric Measurements

For aerosol retrieval from multi-angle polarimetric (MAP) measurements over the ocean it is important to accurately account for the contribution of the ocean-body to the top-of-atmosphere signal, especially for wavelengths <500 nm. Performing online radiative transfer calculations in the coupled atmosphere ocean system is too time consuming for operational retrieval algorithms. Therefore, mostly lookup-tables of the ocean body reflection matrix are used to represent the lower boundary in an atmospheric radiative transfer model. For hyperspectral measurements such as those from Spectro-Polarimeter for Planetary Exploration (SPEXone) on the NASA Plankton, Aerosol, Cloud and ocean Ecosystem (PACE) mission, also the use of look-up tables is unfeasible because they will become too big. In this paper, we propose a new method for aerosol retrieval over ocean from MAP measurements using a neural network (NN) to model the ocean body reflection matrix. We apply the NN approach to synthetic SPEXone measurements and also to real data collected by SPEX airborne during the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign. We conclude that the NN approach is well capable for aerosol retrievals over ocean, introducing no significant error on the retrieved aerosol properties
Sex Differences in Glutathione Peroxidase Activity and Central Obesity in Patients with Type 2 Diabetes at High Risk of Cardio-Renal Disease

Women with type 2 diabetes (T2DM) have an increased susceptibility of developing cardio-renal disease compared to men, the reasons and the mechanisms of this vulnerability are unclear. Since oxidative stress plays a key role in the development of cardio-renal disease, we investigated the relationship between sex, plasma antioxidants status (glutathione peroxidase (GPx-3 activity), vitamin E and selenium), and adiposity in patients with T2DM at high risk of cardio-renal disease. Women compared to men had higher GPx-3 activity (p = 0.02), bio-impedance (p ≤ 0.0001), and an increase in waist circumference in relation to recommended cut off-points (p = 0.0001). Waist circumference and BMI were negatively correlated with GPx-3 activity (p ≤ 0.05 and p ≤ 0.01, respectively) and selenium concentration (p ≤ 0.01 and p ≤ 0.02, respectively). In multiple regression analysis, waist circumference and sex were independent predictors of GPx-3 activity (p ≤ 0.05 and p ≤ 0.05, respectively). The data suggest that increased central fat deposits are associated with reduced plasma antioxidants which could contribute to the future risk of cardio-renal disease. The increased GPx-3 activity in women could represent a preserved response to the disproportionate increase in visceral fat. Future studies should be aimed at evaluating if the modulation of GPx-3 activity reduces cardio-renal risk in men and women with T2DM.
Combustion Theory and Modelling

A transported probability density function/photon Monte Carlo method for high-temperature oxy–natural gas combustion with spectral gas and wall radiation X. Y. Zhao a b , D. C. Haworth a b , T. Ren c & M. F. Modest c a National Energy Technology Laboratory – Regional , University Alliance (NETL-RUA) b Department of Mechanical and Nuclear Engineering , Pennsylvania State University , University Park , PA , 16802 , USA c Department of Mechanical and Applied Mechanics , University of California , Merced , CA , 95343 , USA Published online: 14 Mar 2013.
Quantifying the Effects of Climate Change and Land Management on Vegetation Dynamics from 1982 to 1985 in the Source Region of Three-Rivers, China

Vegetation dynamics under a warming climate in the source region of the Three Rivers (SRTR) and its ecological impacts are a source of serious concern. In this study, we investigated the spatial and temporal variations of normalized difference vegetation index during the growing season (NDVIgr) and the start of the vegetation growing season (SOS) for six ecosystems. We examined the relationships between vegetation parameters, air temperature, precipitation and land management using residual trend method from 1982 to 2015. The NDVIgr increased at a rate of 0.0061/10a, and SOS advanced by 0.96 d/10a during the study period. The NDVIgr increased for the all six vegetation ecosystem from 1982 to 2015. The SOS showed advancing trend for the vegetation types for meadow (0.1236 d/a) and steppe (0.3480 d/a), but showing delaying trends for forest, shrub, barren land and alpine vegetation. The results of the correlation analysis indicate an increase in the air temperature in the SRTR is the main factor explaining increases in the NDVI and advancement of the SOS. In general, awarming-wetting climate and reasonable human activities had positive effects on vegetation growth, while the positive impact of human activities was weaker than that of climatic factors. This study provides a necessary basis for research on and the prediction of vegetation changes and their response to the climate warming of the SRTR in the Qinghai-Tibet Plateau (QTP).
Ectopic Expression of WOX5 Dramatically Alters Root-tip Morphology in Transgenic Tobacco

This paper examines the effects of ectopic expression of WUSCHEL (WUS)-RELATED HOMEOBOX5 (WOX5) on the morphology of transgenic tobacco plantlets and seedlings under the control of a chemical-inducible expression system. In the presence of the expression inducer, -estradiol, the root-tip region developed a swelling of callus tissue from which adventitious shoots emerged. Except at the root tip itself, no abnormality was evident in any other parts of treated plantlets such as in the leaf, stem or other parts of the root. Transgenic seedlings also generated ectopic shoots from similar root swellings after treatment with the inducer. Expression analyses reveal that WOX5 may induce transdifferentiation of root-tip cells that possess competence for the formation of an apical shoot meristem. It is suggested that WOX5 may execute a common functional regulation in transgenic tobacco as previously reported in the case of WUS, during the process of adventitious shoot formation, and from the root-tip region. _____________________________________________________________________________________________________________
CongestionNet: Routing Congestion Prediction Using Deep Graph Neural Networks

As feature size shrinks, routing constraints become a more significant limiting factor to the manufacturability of VLSI designs. Routing congestion significantly impacts quality metrics such as area and timing performance, but congestion is not known accurately until late in the design cycle, after placement and routing. This can lead to unpleasant surprises during the design process. Accordingly, early prediction of routing requirements would enable design engineers to iterate faster, with more confidence that their designs were routable and high quality. Additionally, routability estimates can inform placement itself, preemptively eliminating routing problems. In this work, we present a graph-based deep learning method for quickly predicting logic-induced routing congestion hotspots from a gate-level netlist before placement. This model can provide early feedback to designers and EDA tools, indicating logic that may be difficult to route. Compared to using previous congestion prediction metrics to predict congestion hotspots without placement information, our solution provides a 29% increase in the Kendall ranking correlation score. Because our focus is on predicting congestion due to local logic structure, which manifests itself on lower metal layers, we also report accuracy for predicting lower metal layer congestion. When predicting congestion for the lower metal layers, the benefit of our solution over previous metrics increases to 75%. Additionally, our approach is fast. On a circuit with 1.3 million cells, our approach takes 19 seconds to predict congestion, compared with 10–60 minutes for other methods.
Residual MLP Network for Mental Fatigue Classification in Mining Workers from Brain Data

At the mining industry, human safety and productivity are both desirable in the logistics pipeline. Since the operation of heavy machines requires continued vigilance and mental activity, fatigue caused by long hours of work and constant effort generally occurs in this environment. In general, mental fatigue is related to a loss of efficiency, leading to a decrease in productivity and inducing critical errors, which can provoke equipment breakups or accidents with human victims. At this high cognitive workload environment, there is a need for the development of robust monitoring techniques aiming to predict mental fatigue before workers' movement responses become slower, more variable, and more error-prone. In this work, we introduce a residual multilayer perceptron (MLP) network (ResMLPNet) and assess its performance in the challenging problem of mental fatigue classification from cognitive electrophysiology data, acquired during Virtual Reality (VR) training sessions mimicking a real operation faced by excavator workers at the mining industry. In a three-step training strategy, the ResMLPNet achieved slightly better classification accuracies compared to its plain MLP architecture.
Quantitative estimation of recovery parameters after combined action of ionizing radiation and chemical agents

The combined action of ionizing radiation with various chemical agents is often used to enhance the inactivation effect of tumor cells in cancer treatment. The enhancing effect seems to be accountable by direct chemical toxicity, cell recovery inhibition or the higher probability to produce primary radiation damage without changing the recovery process (1–4). Repair of DNA, as re lected in rejoining of strand breaks, may be of relevance to the cell recovery from sub lethal and potentially lethal damage (2, 5). Preferential impairment of DNA repair in malignant cells would be of great relevance in improving cancer treatment. The inhibition of cell recovery (2, 3, 6, 7) and DNA single and double strand breaks repair (8–11) by chemicals is expressed both as a deceleration of recovery rate and a lesser extent of recovery. It is obvious that the inhibition of cell recovery may be caused by the following reasons: (i) the damage or impairment of the recovery process itself, (ii) the increase in the portion of irreversible damage, and (iii) both these reasons may took place simultaneously. V.G. Petin1, J.K. Kim2*, E.S. Evstratova1, L.N. Komarova1
ARU-Net: Research and Application for Wrist Reference Bone Segmentation

Segmenting reference bones from radiographs of the hand is important for bone age assessment. Due to the influence of the irregular shapes and the adjacent positions of the wrist reference bones, it is difficult for the expert to accurately estimate the mature indication of the wrist reference bones in the figures. How to precisely segment the reference bones automatically from the radiographs is a challenge. For this is problem, an improved U-Net, Attention Residual U-Net (ARU-Net) proposed in this paper. Firstly, we extract the reference bone region of interest (ROI) by faster region-based convolutional neural networks(R-CNN). Then, the pre-processed ROI is fed into ARU-Net for segmentation. On the basis of traditional U-Net, ARU-Net adds residual mapping and attention mechanism, which improves the utilization rate of features and the accuracy of reference bone segmentation. Finally, a post-processing method including the flood fill algorithm and the morphological operation is used to eliminate jagged edges and holes in the segmented result. The hamate is one of the most difficult reference bones to segment in the wrist. This paper takes it as an example to assess the performance of ARU-Net. Experiments show that compared with Fully Convolutional Neural Network (FCN), U-Net and ResUnet, the accuracy and F1 scores of ARU-Net are higher. Its accuracy rate is 96.41%, and F1 score is 0.9529. The post-processing method can further improve the result. Finally, the accuracy rate reaches 96.51%, and the F1 score reaches 0.9544. ARU-Net can precisely segment the reference bone, which facilitates the expert to assess its mature indication, so as to accurately evaluate the bone age.
The Lasting Impact of a Short SSR Experience on EFL Teachers in Korea

This follow-up study examined whether elementary school teachers in Korea who had had sustained silent reading experiences implemented self-selected reading in their English class. The results were remarkable: 70 % of the teachers had implemented SSR in their English as a foreign language class. Reasons for not implementing self-selected reading among teachers were mostly a lack of time, the pressure of exams and a lack of access to English books.
MANAGING JUNIOR HIGH SCHOOLS IN THE SUNYANI EAST AND WEST MUNICIPALITIES (GHANA): THE CONTINUOUS PROFESSIONAL DEVELOPMENT NEEDS OF HEADTEACHERS AND STRATEGIES FOR THEIR PROVISION.

he study explored the continuous professional development needs of headteachers in the Sunyani east and west municipalities of Brong Ahafo Region (Ghana) and strategies for the provision of such needs. Informed by the interpretive paradigm, the study employed a case study approach. Data for the study was collected in two phases. Phase one involved a semi-structured questionnaire with 69 participants comprising 60 headteachers and 9 circuit supervisors (school inspectors in the Ghanaian educational context). The second phase also involved a semi-structured interview with 15 headteachers and 6 circuit supervisors who had responded to the initial questionnaire. The study identified barriers to effective continuous professional development of the headteachers, including incompetent resource persons, use of inappropriate methods for the delivery of the programmes, and the contents of the programmes having no bearing on areas the headteachers' needed training in. The training needs of the headteachers were also identified. The study further indicated that the training opportunities that would enable the headteachers to acquire the relevant knowledge, skills and competences included regional-based courses in leadership and management, and the formation of cluster-based working groups. Based on the findings relating to the barriers to effective continuous professional development, it was recommended, among others, that resource persons for the programmes should broaden their knowledge about the topics they handle to sustain the interest of the participants in the programmes; and T
Study of harmonic content and influence of common electrical appliances used in residential installations

In this paper, we report the findings derived from measurements in a typical residential installation in the state of Veracruz, Mexico. Common electrical appliances were studied individually and then measurements were made to the whole house installation using a digital analyser for the monitoring of harmonic distortion in voltage and current. Individual results were out of the norm specifications for several appliances, but it was found that the combination of them produced a less distorted home system.
Upper Gastrointestinal Bleeding in the Medical Intensive Care Unit (MICU) Doha, Qatar: A one-year survey

Upper gastrointestinal bleeding is a common problem and is an important cause of morbidity and mortality. Between June 1999 to May 2000 eight hundred and sixty patients were admitted to the Medical Intensive Care Unit, Hamad Medical Corporation, 102 of whom (11.8%) were admitted with a diagnosis of upper gastrointestinal bleeding. The most common nationality was Qatari (42.2%) and the most common age group was between 50-60years old (28.4%). The most frequent cause of bleeding was peptic ulcer disease (50 patients) followed by variceal bleeding. Our results are compatible with other reports.
You Only Move Once: An Efficient Convolutional Neural Network for Face Detection

Our “You Only Move Once” (YOMO) detector based on depthwise separable convolutions is a single stage face detector that balances accuracy and latency. YOMO performs scale-invariantly by utilizing top-down architecture with feature agglomeration, and multiple detection modules instead of in an image pyramid approach. At the same time, we propose a semi-soft random cropping algorithm that enables different detection module adequately trained by different scales of samples. Several experiments are conducted on the FDDB dataset with discrete and continuous measures, to demonstrate that the methods have strongly competitiveness results. After using an ellipses regressor, the recall rates reached a satisfactory 97.59% and 83.66%, respectively. Surprisingly, YOMO has only 21 million parameters and achieves superior performance with 51 frames per second (FPS) for a $544\times544$ input image on a GPU.
A Single Channel EEG-based All AASM Sleep Stages Classifier for Neurodegenerative Disorder

Sleep stages classification is an effective tool for the diagnosis and treatment of neurodegenerative disorders. This paper presents the first non-invasive electroencephalograph (EEG)-based processor for classifying all the sleep stages implemented on hardware. It utilizes a single EEG channel and multi-machine-learning classifiers to form a home-based polysomnography. These multiple one-vs-one binary Linear Support Vector Machine (LSVM) classifiers are combined to classify all the sleep stages using two features only. To implement the desired features efficiently on hardware, an exponent-eliminate (EE) Split-Radix 256-point FFT is proposed that decreases the area by 60% compared to the conventional design by avoiding the majority of complex floating-point multiplications and divisions. The proposed all sleep stages classification system is implemented using 180nm CMOS process and experimentally verified using FPGA based on the EEG recordings of 197 patients from Physionet Sleep database. It utilizes a miniaturized active area of 0.32mm2 and achieves a Cohen Kappa score of 0.847 while consuming 0. 7µJ/classification.
Operation of Four-Level ANPC Inverter Based on Space-Vector Modulation for Common-Mode Voltage Reduction

In this paper, the problem of common-mode voltage (CMV) in four-level active neutral-point clamped (ANPC) inverters is alleviated with a modified space-vector modulation. With the proposed technique, the CMV peak value is reduced by 40 % compared to the in-phase disposition (IPD) carrier-based modulation, whereas the total harmonic distortions (THDs) are similar at high modulation indices. The effectiveness of the proposed method and the power losses across the switching devices have been verified by simulation results.