Miracle-dz/UniFAR-FTUs huggingface dataset:
Cumulative risk factors for adolescent depressive symptoms: findings from a Taiwanese school-based sample

ABSTRACT This cross-sectional study investigated the cumulative effect of risk factors for depressive symptoms. The primary hypothesis was that an increase in the risk factor exposure is associated with the odds of adolescent depression. A multi-stage cluster sampling method was administered to recruit participants. 1,306 Taiwanese high school students aged 15 to 18 completed self-report questionnaires to report their levels of individual risk factor and depressive symptoms. Risk factors under investigation included low self-esteem, family economic constrain, parent-adolescent conflict, negative peer relationship and academic expectation stress. All risk factors significantly predict adolescents’ risk for developing depression. A graded dose-response relationship was observed, meaning the odds of having depression rose along with an increase in the cumulative risk index. The findings yield support for the individual and cumulative effects of these salient risk factor on adolescent depression. The cumulative risk index can provide a useful instrument for depression screening and intervention.
Analysis of Canopy Height Model (CHM) Extraction using Quick Terrain Modeller (QTM) for Tropical Forest Area

Forest biomass or above-ground carbon stock is the mass of carbon that stored in trees which requires a continuous monitoring in order to predict the amount of potential carbon accumulation of the forest. Therefore, the forest has an important role at absorbing carbon Dioxide (CO2) from the atmosphere. This research aims to measure the capability of Quick Terrain Modeller software at estimating above-ground carbon stock by single tree segmentation combining ground inventory, Light Detection and Ranging (LiDAR), and by using allometric equations. In particular, to achieve the aim, there are three (3) objectives were outlined. Canopy Height Models (CHM) was generated via Quick Terrain Modeller (QTM) and ArcGIS. Non-linear Regression analyses were performed for both surface models to ensure the models were fit to estimate carbon stock. Secondly, tree contours were delineated using watershed transformation. Local maxima were determined at the raster as a pour point for watershed and also represent the highest peak of the tree crown. In addition, flow direction, drop output, and flow accumulation of the raster were also determined to generate contour from the watershed transformation. Manual tree crown projection was performed by watershed tree contour to generate Crown Projection Area (CPA). Then, from the digitized CPA, carbon stock and above-ground biomass was calculated using equations from [1] and [2]. Thirdly, tree species on the selected area were extracted and finally a map of tree carbon stock by species was produced. From the generated map, total carbon stock according to species and total carbon stock in single tree according to species information were extracted. As a result, Hopea sulcata; the endangered tree species appeared to be the highest appearance in the map followed by Dipterocarpus verrucosus, Shorea macroptera, Endospermum diadenum, and the other less appeal species. Also from the map, Hopea Sulcata has the highest carbon stock which is 23% compared to the other species. However, for a single tree, Dipterocarpus verrucosus held the highest carbon stock which is 1565.401 kg/tree.
Economic evaluation of cleaning and disinfection of facilities from broiler chickens challenged with Campylobacter jejuni

Abstract: For a new management practice to be adopted in broiler production, it must be efficient and economically viable. Few studies have been conducted with the purpose of evaluating costs and revenues relative to cleaning and disinfection. Based on the need to show economic efficiency of these practices, we compared two cleaning and disinfection protocols. The first method is more detailed and developed in seven steps, whereas the second method is more simplified with three steps. The costs, estimated total revenue from poultry carcass sale, and gross margin of sale were calculated for each cleaning and disinfection program. As expected, the cost of executing the first protocol was greater than the second one. However, due to the positive influences of preventive procedures, such as cleaning and disinfection on broiler performance, it was hypothesized that the two protocols would have similar gross margins from the sale of chicken carcasses. This study demonstrates an increase in economic viability when invested in a more detailed and complete cleaning and disinfection protocol. From the results obtained with the present study, it is possible to demonstrate a greater profitability and economic feasibility when a more detailed cleaning and disinfection protocol was carried out, due to similarity of its gross margin from the sale of product compared with simplified protocol.
Safety Challenges in Transportation in Nigeria – A Relative Risk Approach

This study investigates safety challenges in transportation in Nigeria across the six geopolitical zones of the country comprising South-South, South-East, North-West, North-Central, North-East and South-West geopolitical Zones. Both primary and secondary data were employed, and the Multinomial Logistic Regression Model, with specific adoption of the Relative Risk Ratio approach, is the method of analysis. The main concern is examination of exposed and unexposed commuters in the various locations to determine the degrees of exposure to risks associated with ‘basket’ of modes, state of infrastructures and specific risk factors, which account for the fatalities observed on the different roads under consideration. It is found that the six geopolitical zones have various degrees of risks exposure while North-West, North-Central and South-West zones showed significant risk difference between the exposed and the unexposed groups due to risk factors such as bad roads, road blockage/obstruction, kidnaping, unmaintained vehicles, overloading, over speeding and other forms of reckless use of the roads etc. The study recommends risk avoidance education to commuters as new strategies in vulnerable zones and increased deployment of well-trained community road marshals and other relevant security personnel to monitor situations and provide safety for road users. Also, a working transportation policy must be evolve to mitigate the risk factors highlighted above.
Comparative Assessment of the Unsupervised Land Use Classification by Using Proprietary GIS and Open Source Software

Mapping and investigating land use land cover (LULC) changes over a particular region is crucial for resource management, sustainability development, and holistic planning. An increasing rate of urban growth and urban sprawl could induce changes in land use as well as land transformation. However, accurate and up-to-date information about LULC is required for providing better understanding and assessing the environmental consequences of such changes. In this study, the 2017 image from the Sentinel-2A Satellite was utilized to demonstrate the land cover classification analysis in Iskandar Malaysia. Usually, land use classification analysis is conducted through proprietary GIS software. However, this decade shows the advancement in software development, thus the emerging of free/open source software in the geospatial world. Hence, to execute land cover analysis using the Unsupervised Classification technique, the proprietary GIS software (ArcGIS) and free/open source software (QGIS) were deployed. Then, the examination of accuracy assessment was carried out for the selected software. The sum of 250 random points was established for the assessment purpose. The results showed the overall accuracy for ArcGIS and QGIS were 82.80% and 80.40% respectively. The kappa coefficient for ArcGIS was 0.7395, while kappa coefficient for QGIS was 0.7094. Besides that, ArcGIS demonstrated better producer’s accuracy in the forest and agriculture land covers classification. Meanwhile, QGIS exhibited better producer’s accuracy in the built-up and water features classification. To summarize, ArcGIS and QGIS software are reliable to be used in the land cover classification.
Trading off financial and non-financial performance information to evaluate state-owned enterprise performance – a process tracing-experiment

Abstract New public management initiatives have pushed municipal authorities to evaluate state-owned enterprises (SOEs) based on multidimensional performance reports. Little is known, however, about policymakers’ pre-decisional information search and tradeoff processes between different performance dimensions when evaluating SOE performance. We apply a mouse-cursor-tracking experiment with a master students sample and show that participants consider multiple performance dimensions but focus their attention on financial and customer performance information when evaluating SOEs for allocating a budget. We also observe a tradeoff between financial and non-financial performance information in participants’ budget allocations. Finally, we show that participants devote more effort to the performance evaluation process when municipalities’ financial resources are scarce. However, the municipalities’ financial status affects neither the attention paid to financial and non-financial performance nor the budget allocation decisions.
Introduction to Health Systems Science: Experiential Learning Through Patient Interviews in the Emergency Department

Increased complexity in health care delivery is now a problem of national proportions. Traditional medical education fails to sufficiently prepare students for the realities of practicing medicine in the 21st century. To address this critical problem, health systems science (HSS), which focuses on the broader system of care, has emerged as the “third pillar” of undergraduate medical education complementing the basic and clinical sciences. The authors identified a need to increase the amount and quality of HSS education in a way that would engage students and provide a platform to learn how patients interact with the health care system. UNITED (Understanding Needs in the Emergency Department) was thus designed and implemented to introduce preclinical medical students to HSS through patient interactions in the emergency department (ED). EDs serve as America's health care “safety net” and there is no lack of opportunity to learn how the current system of care does and does not work for patients. Qualitative analysis of students’ written reflections revealed the following themes of the UNITED experience: 1) medical students question their understanding of the health care system after listening to patients' stories, 2) focused patient interviews about the health care system provides a unique perspective of the patient experience not found elsewhere in the preclinical curriculum, and 3) discussing the realities of being a patient in the U.S. health care system is an emotional experience for students. Based on these data, the authors concluded that asking preclinical students to interview patients about their experience in the health care system leads to emotional activation and a subsequent stated desire to improve care delivery.
Seismic Damage Rapid Assessment of Road Networks considering Individual Road Damage State and Reliability of Road Networks in Emergency Conditions

Road networks are one of the vital components of a transportation system that influence the traffic capacity and disaster losses after the earthquakes. The road network reliability is crucial for the postearthquake emergency decision-making. In this study, a method is proposed to assess the seismic damage of road networks considering individual road damage state and reliability of road networks in emergency conditions. First, we assess the importance of the factors that affect seismic road damage using the AdaBoost algorithm. In addition, artificial neural networks are used to evaluate the damage state of an individual road based on the factors that are selected with higher importance. Then, the improved estimation for the reliability of road networks is adopted to assess the damage of road networks. Last, the method is demonstrated using the road networks in Karamay, China.
Seasonal variation in the composition of ground-dwelling anuran (Amphibia) assemblages in southern Brazil

Climate seasonality may differently influence habitat quality and heterogeneity depending on habitat type. We examined whether the taxonomic, functional and phylogenetic composition of ground-dwelling anuran assemblages from grassland and forest habitats vary seasonally. We tested the hypothesis that the forest anuran assemblage varies less seasonally than the grassland assemblage. We monitored anurans using pitfall trap arrays in two areas, sampled across four seasons over a two-year period. For the functional composition, we acquired information on species morphology, reproduction, and habitat use to represent the anuran niche. For the phylogenetic composition, we used the most comprehensive anuran phylogeny. We used Principal Coordinate Analysis and Analysis of Variance to evaluate seasonal variations in assemblage composition along the study period. Our data revealed significant seasonal variation in the taxonomic and phylogenetic composition of anuran assemblages. Variation in taxonomic composition was higher in the grassland than in the forest assemblage, while variation in phylogenetic composition was higher in the spring-summer than in the autumn-winter seasons. We did not identify seasonal variation in functional composition. Seasonal variations in taxonomic and phylogenetic composition, but not in functional composition, indicate that the species with a fluctuating seasonal abundance have similar life-history traits, but belong to different lineages. Keywords: anuran traits, Brazilian highland grasslands, habitat variability, temporal beta diversity, temporal turnover.
Assessment and screening of positive childhood experiences along with childhood adversity in research, practice, and policy

ABSTRACT Despite empirical evidence documenting the role of positive childhood experiences in predicting adaptation over the lifespan and across generations, this research has not yet been fully integrated into public health and policy efforts. We argue that adults' benevolent childhood experiences (BCEs) should be measured in large-scale data collection efforts, such as statewide surveys, alongside more routinely collected adverse childhood experiences (ACEs). We also outline several recommended strategies in which the assessment and screening of positive childhood experiences could be implemented as a counterpart to community health and primary care screening for childhood adversity in adults, with short- and long-term benefits. Pediatric physicians should screen children and adolescents for their current positive childhood experiences as well. The assessment of positive childhood experiences is essential to empirically identifying resilience resources linked with better long-term adaptation, understanding how positive experiences may counteract the long-term effects of childhood adversity in underserved and traumatized individuals, informing medical providers' knowledge about patients' strengths in addition to challenges, and instilling hope in individuals and families experiencing stress.
Reaction Kinetics Modeling of OH*, CH*, and C2* Chemiluminescence

In the combustion processes, spontaneous emission of chemiluminescence species responsible for ultra-violet and visible light is in abundance. Due to its natural occurrence, it offers an inexpensive diagnostic tool for flames and other combustion processes. It is non-intrusive in nature and gives the facility to avoid expensive laser instrumentation. In hydrocarbon oxidation most common electronically excited species are OH*, CH*, C2*, and CO2*, where * represents the electronically excited state of a given radical or molecule. In the early 1970s chemiluminescence has been identified as a marker for heat release, reaction zone, and equivalence ratio, thereby providing a relatively easy diagnostics alternative for online measurement of these features in practical combustion applications. However, the quantitative relationship between chemiluminescence, heat release, and equivalence ratio is mostly unknown except for a few correlations available in literature over small range of conditions. Therefore a reaction kinetic model predicting these species is necessary for the fundamental understanding of the chemiluminescence. This mechanism then can be provided for predicting excited species in simulations of various combustion devices. A detailed reaction mechanism of chemiluminescence is not well studied. Therefore, the objective of this work is to develop a reaction mechanism of chemiluminescent species which can predict their concentrations in shock-tube and one-dimensional laminar flame experiments. The mechanism developed in this thesis is validated against various experimental conditions in shock-tube experiments where it reproduces the ignition delay time very well. In addition, the species profiles which provide a more stringent test on the mechanism validation are calculated to reproduce the measured excited species concentrations in laminar premixed and non-premixed flames. The comparison proves accuracy of the mechanism. The mechanism presented provides therefore a first step to quantitative understanding of the excited species and can be further used in the simulation of practical combustion systems.
Slice Allocation Management Model in 5G Networks for IoT Services with Reliable Low Latency

Network slicing is a promising technology for 5G networks in which operators can sell customized services to different tenants at various prices and Quality of Services (QoS) demands. Thus, the latest 4th Generation (4G) and upcoming 5th Generation (5G) mobile technologies are expected to offer massive connectivity and management of high volume of data traffic in the presence of immense interferences from mobile networks of IoT devices. Further, it will face challenges of congestion and overload of data traffic due to humongous number of IoT devices. Nevertheless, these devices are likely to demand high throughput, low latency and high level of reliability especially for critical real-time applications such as in Vehicular Communication System (VCS). To address these issues in 5G mobile networks, this paper proposes a Slice Allocation Management (SAM) Model based on critical services of smart systems such as VCS to satisfy QoS demands. The proposed model aims at providing dedicated slices on the basis of service requirements such as expected throughput and latency for VCS. To ensure such performance and provide data traffic priorities of IoT devices in uplink of Relay Nodes (RNs) cells in the 5G mobile networks, we have sliced the Radio Access Networks (RAN), along with assignment of the nearest Mobile Edge Computing (MEC) with isolated slices based on the priorities for each IoT nodes to reduce latency level. The proposed model was simulated and validated using the OPNET simulator. The results obtained demonstrate that SAM Model is able to achieve improvement of end to end delays and uplink throughputs of the networks in high-density networks of IoT devices.
Soft Start-Up Control Strategy for Dual Active Bridge Converter with a Supercapacitor

Renewable energy needs are steadily on the rise. Bidirectional DC/DC converters are essential in charging and discharging various storage batteries, such as PV/ESS (photovoltaic/energy storage system). A dual active bridge (DAB) converter, in particular, transfers power in both directions by phase shift using a soiled state transformer (SST). To reduce switching inrush current in batteries under high voltages, a soft start-up is demonstrated during the initial switching operation. When a supercapacitor (SC) is used as a battery, the reverse power caused by the inrush current appears under high voltage at the DC-link side. This causes serious electrical damage to the PV/ESS’ boost converter and inverter. To suppress peak overshoot voltage and stabilize soft start-up transients, we propose a three-step soft start-up controller and algorithm for bidirectional DAB converter implementation at virtual ESS and UPS. The step-by-step control strategy by OLDC (open loop duty control), OLPSC (open loop phase shift control), and OLFC (open loop frequency control) provides a stable soft start-up operation. In the initial stage of the OLDC, the duty ratio is gradually increased by the PWM (Pulse width modulation) signal. In the middle stage, a phase difference is seen as per the voltage of the SC. The OLPSC is performed to reduce the phase difference. In the final stage, the OLFC is performed to smoothly control the small phase difference. The overshoot or inrush current is drastically suppressed toward the DC-link and SC module. Consequently, we demonstrate a proposed controller and algorithm with prototype 5 kW DAB converter.
Application of Mushroom as Food and Medicine

The word mushroom is used through world to express the different species of fungus belongs to the order of Basidomyecets or Ascomycetes. Basidomyecets or Ascomycetes can be found everywhere in soils rich in organic matter and humus, moist wood, animals waste after heavy rain or a sudden change of temperature and soon after a few hours or day’s they disappear, leaving no sign but, mycelium [1]. As estimated by different researchers, there are over 70,000 fungi species on the world. About 2000 species (31 genera) are primarily edible mushrooms. However, about 10% of some 30 species are poisonous mushrooms and relatively small, numbers are considered as lethal [2].
Chemical relaxation in porous ionic–electronic conducting materials represented by the distribution of characteristic times

High-temperature catalytic and transport properties of porous ionic–electronic conducting materials (MIECs) are vital for device-level performance and are sensitive to microstructure, however they are indirectly characterized using dense MIECs with simple geometry. The structure–property relationship can be misinterpreted, as the fabrication procedures and microstructures of the dense MIECs are different from those of the porous MIECs. Here, the distribution of characteristic times (DCT) is proposed to resolve chemical relaxation (CR) kinetics in porous MIECs. The peak in a DCT spectrum has a clear physical origin, with its integral area being the fractional volume involved. In contrast to previous treatments that assume surface exchange-limited kinetics, the DCT spectra of porous La0.6Sr0. 4Co0.2Fe0. 8O3−δ (LSCF) show that gaseous oxygen diffusion can dominate the CR kinetics in 0–40 percent volume, depending on the sintering temperature of the sample. The surface exchange coefficient and its thermal activation energy are much lower than those of the dense bulk LSCF. These findings indicate a different catalytic mechanism on the internal surface of porous LSCF, compared to in the dense bulk material. The DCT approach opens up a way to reveal the CR kinetics in porous MIECs, and can readily be extended from e−/O2− to e−/H+ and e−/H+/O2− conducting oxides.