bluuebunny/crossref_metadata_2025 huggingface dataset:
In Vitro Fermentation of Sheep and Cow Milk Using Infant Fecal Bacteria
Authors: Ahlborn Natalie , Young Wayne , Mullaney Jane , Samuelsson Linda M.
Published: June 2020

While human milk is the optimal food for infants, formulas that contain ruminant milk can have an important role where breastfeeding is not possible. In this regard, cow milk is most commonly used. However, recent years have brought interest in other ruminant milk. While many similarities exist between ruminant milk, there are likely enough compositional differences to promote different effects in the infant. This may include effects on different bacteria in the large bowel, leading to different metabolites in the gut. In this study sheep and cow milk were digested using an in vitro infant digestive model, followed by fecal fermentation using cultures inoculated with fecal material from two infants of one month and five months of age. The effects of the cow and sheep milk on the fecal microbiota, short-chain fatty acids (SCFA), and other metabolites were investigated. Significant differences in microbial, SCFA, and metabolite composition were observed between fermentation of sheep and cow milk using fecal inoculum from a one-month-old infant, but comparatively minimal differences using fecal inoculum from a five-month-old infant. These results show that sheep milk and cow milk can have differential effects on the gut microbiota, while demonstrating the individuality of the gut microbiome.
Religion across Axes of Inequality in the United States: Belonging, Behaving, and Believing at the Intersections of Gender, Race, Class, and Sexuality
Authors: Schnabel Landon
Published: June 2020

Much research considers group differences in religious belonging, behaving, and/or believing by gender, race, ethnicity, class, or sexuality. This study, however, considers all these factors at once, providing the first comprehensive snapshot of religious belonging, behaving, and believing across and within these axes of inequality in the United States. Leveraging unique data with an exceptionally large sample, I explore religion across 40 unique configurations of intersecting identities (e.g., one is non-Latina Black heterosexual college-educated women). Across all measures considered, Black women are at the top—however, depending on the measure, there are different subsets of Black women at the top. And whereas most sexual minorities are among the least religious Americans, Black sexual minorities—and especially those with a college degree—exhibit high levels of religious belonging, behaving, and believing. In fact, Black sexual minority women with a college degree meditate more frequently than any other group considered. Overall, whereas we see clear divides in how religious people are by factors like gender, education, and sexual orientation among most racial groups, race appears to overpower other factors for Black Americans who are consistently religious regardless of their other characteristics. By presenting levels of religious belonging, behaving, and believing across configurations of gender, race, ethnicity, class, and sexuality in the contemporary United States, this study provides a more complex and complete picture of American religion and spirituality.
Editorial for the Special Issue on Selected Papers from the “2019 International Symposium on Remote Sensing”
Authors: Tsai Fuan , Lin Chao-Hung , Chen Walter W. , Jaw Jen-Jer , Tseng Kuo-Hsin
Published: June 2020

The 2019 International Symposium on Remote Sensing (ISRS-2019) took place in Taipei, Taiwan from 17 to 19 April 2019. ISRS is one of the distinguished conferences on the photogrammetry, remote sensing and spatial information sciences, especially in East Asia. More than 220 papers were presented in 37 technical sessions organized at the conference. This Special Issue publishes a limited number of featured peer-reviewed papers extended from their original contributions at ISRS-2019. The selected papers highlight a variety of topics pertaining to innovative concepts, algorithms and applications with geospatial sensors, systems, and data, in conjunction with emerging technologies such as artificial intelligence, machine leaning and advanced spatial analysis algorithms. The topics of the selected papers include the following: the on-orbit radiometric calibration of satellite optical sensors, environmental characteristics assessment with remote sensing, machine learning-based photogrammetry and image analysis, and the integration of remote sensing and spatial analysis. The selected contributions also demonstrate and discuss various sophisticated applications in utilizing remote sensing, geospatial data, and technologies to address different environmental and societal issues. Readers should find the Special Issue enlightening and insightful for understanding state-of-the-art remote sensing and spatial information science research, development and applications.
Uncertainty in Satellite-Derived Surface Irradiances and Challenges in Producing Surface Radiation Budget Climate Data Record
Authors: Kato Seiji , Rutan David A. , Rose Fred G. , Caldwell Thomas E. , Ham Seung-Hee , Radkevich Alexander , Thorsen Tyler J. , Viudez-Mora Antonio , Fillmore David , Huang Xianglei
Published: June 2020

The Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Edition 4.1 data product provides global surface irradiances. Uncertainties in the global and regional monthly and annual mean all-sky net shortwave, longwave, and shortwave plus longwave (total) irradiances are estimated using ground-based observations. Error covariance is derived from surface irradiance sensitivity to surface, atmospheric, cloud and aerosol property perturbations. Uncertainties in global annual mean net shortwave, longwave, and total irradiances at the surface are, respectively, 5.7 Wm−2, 6.7 Wm−2, and 9.7 Wm−2. In addition, the uncertainty in surface downward irradiance monthly anomalies and their trends are estimated based on the difference derived from EBAF surface irradiances and observations. The uncertainty in the decadal trend suggests that when differences of decadal global mean downward shortwave and longwave irradiances are, respectively, greater than 0.45 Wm−2 and 0.52 Wm−2, the difference is larger than 1σ uncertainties. However, surface irradiance observation sites are located predominately over tropical oceans and the northern hemisphere mid-latitude. As a consequence, the effect of a discontinuity introduced by using multiple geostationary satellites in deriving cloud properties is likely to be excluded from these trend and decadal change uncertainty estimates. Nevertheless, the monthly anomaly timeseries of radiative cooling in the atmosphere (multiplied by −1) agrees reasonably well with the anomaly time series of diabatic heating derived from global mean precipitation and sensible heat flux with a correlation coefficient of 0.46.
Assimilation of Snowmelt Runoff Model (SRM) Using Satellite Remote Sensing Data in Budhi Gandaki River Basin, Nepal
Authors: Pangali Sharma Til Prasad , Zhang Jiahua , Khanal Narendra Raj , Prodhan Foyez Ahmed , Paudel Basanta , Shi Lamei , Nepal Nirdesh
Published: June 2020

The Himalayan region, a major source of fresh water, is recognized as a water tower of the world. Many perennial rivers originate from Nepal Himalaya, located in the central part of the Himalayan region. Snowmelt water is essential freshwater for living, whereas it poses flood disaster potential, which is a major challenge for sustainable development. Climate change also largely affects snowmelt hydrology. Therefore, river discharge measurement requires crucial attention in the face of climate change, particularly in the Himalayan region. The snowmelt runoff model (SRM) is a frequently used method to measure river discharge in snow-fed mountain river basins. This study attempts to investigate snowmelt contribution in the overall discharge of the Budhi Gandaki River Basin (BGRB) using satellite remote sensing data products through the application of the SRM model. The model outputs were validated based on station measured river discharge data. The results show that SRM performed well in the study basin with a coefficient of determination (R2) >0.880. Moreover, this study found that the moderate resolution imaging spectroradiometer (MODIS) snow cover data and European Centre for Medium-Range Weather Forecasts (ECMWF) meteorological datasets are highly applicable to the SRM in the Himalayan region. The study also shows that snow days have slightly decreased in the last three years, hence snowmelt contribution in overall discharge has decreased slightly in the study area. Finally, this study concludes that MOD10A2 and ECMWF precipitation and two-meter temperature products are highly applicable to measure snowmelt and associated discharge through SRM in the BGRB. Moreover, it also helps with proper freshwater planning, efficient use of winter water flow, and mitigating and preventive measures for the flood disaster.
A New Algorithm for Daily Sea Ice Lead Identification in the Arctic and Antarctic Winter from Thermal-Infrared Satellite Imagery
Authors: Reiser Fabian , Willmes Sascha , Heinemann Günther
Published: June 2020

The presence of sea ice leads in the sea ice cover represents a key feature in polar regions by controlling the heat exchange between the relatively warm ocean and cold atmosphere due to increased fluxes of turbulent sensible and latent heat. Sea ice leads contribute to the sea ice production and are sources for the formation of dense water which affects the ocean circulation. Atmospheric and ocean models strongly rely on observational data to describe the respective state of the sea ice since numerical models are not able to produce sea ice leads explicitly. For the Arctic, some lead datasets are available, but for the Antarctic, no such data yet exist. Our study presents a new algorithm with which leads are automatically identified in satellite thermal infrared images. A variety of lead metrics is used to distinguish between true leads and detection artefacts with the use of fuzzy logic. We evaluate the outputs and provide pixel-wise uncertainties. Our data yield daily sea ice lead maps at a resolution of 1 km2 for the winter months November– April 2002/03–2018/19 (Arctic) and April–September 2003–2019 (Antarctic), respectively. The long-term average of the lead frequency distributions show distinct features related to bathymetric structures in both hemispheres.
Developing a Low-Cost Passive Method for Long-Term Average Levels of Light-Absorbing Carbon Air Pollution in Polluted Indoor Environments
Authors: Clark Lara P. , Sreekanth V. , Bekbulat Bujin , Baum Michael , Yang Songlin , Baylon Pao , Gould Timothy R. , Larson Timothy V. , Seto Edmund Y. W. , Space Chris D. , Marshall Julian D.
Published: June 2020

We propose a low-cost passive method for monitoring long-term average levels of light-absorbing carbon air pollution in polluted indoor environments. Building on prior work, the method here estimates the change in reflectance of a passively exposed surface through analysis of digital images. To determine reproducibility and limits of detection, we tested low-cost passive samplers with exposure to kerosene smoke in the laboratory and to environmental pollution in 20 indoor locations. Preliminary results suggest robust reproducibility (r = 0.99) and limits of detection appropriate for longer-term (~1–3 months) monitoring in households that use solid fuels. The results here suggest high precision; further testing involving “gold standard” measurements is needed to investigate accuracy.
A Sheaf Theoretical Approach to Uncertainty Quantification of Heterogeneous Geolocation Information
Authors: Joslyn Cliff A. , Charles Lauren , DePerno Chris , Gould Nicholas , Nowak Kathleen , Praggastis Brenda , Purvine Emilie , Robinson Michael , Strules Jennifer , Whitney Paul
Published: June 2020

Integration of multiple, heterogeneous sensors is a challenging problem across a range of applications. Prominent among these are multi-target tracking, where one must combine observations from different sensor types in a meaningful and efficient way to track multiple targets. Because different sensors have differing error models, we seek a theoretically justified quantification of the agreement among ensembles of sensors, both overall for a sensor collection, and also at a fine-grained level specifying pairwise and multi-way interactions among sensors. We demonstrate that the theory of mathematical sheaves provides a unified answer to this need, supporting both quantitative and qualitative data. Furthermore, the theory provides algorithms to globalize data across the network of deployed sensors, and to diagnose issues when the data do not globalize cleanly. We demonstrate and illustrate the utility of sheaf-based tracking models based on experimental data of a wild population of black bears in Asheville, North Carolina. A measurement model involving four sensors deployed among the bears and the team of scientists charged with tracking their location is deployed. This provides a sheaf-based integration model which is small enough to fully interpret, but of sufficient complexity to demonstrate the sheaf’s ability to recover a holistic picture of the locations and behaviors of both individual bears and the bear-human tracking system. A statistical approach was developed in parallel for comparison, a dynamic linear model which was estimated using a Kalman filter. This approach also recovered bear and human locations and sensor accuracies. When the observations are normalized into a common coordinate system, the structure of the dynamic linear observation model recapitulates the structure of the sheaf model, demonstrating the canonicity of the sheaf-based approach. However, when the observations are not so normalized, the sheaf model still remains valid.
Deep Features Homography Transformation Fusion Network—A Universal Foreground Segmentation Algorithm for PTZ Cameras and a Comparative Study
Authors: Tao Ye , Ling Zhihao
Published: June 2020

The foreground segmentation method is a crucial first step for many video analysis methods such as action recognition and object tracking. In the past five years, convolutional neural network based foreground segmentation methods have made a great breakthrough. However, most of them pay more attention to stationary cameras and have constrained performance on the pan–tilt–zoom (PTZ) cameras. In this paper, an end-to-end deep features homography transformation and fusion network based foreground segmentation method (HTFnetSeg) is proposed for surveillance videos recorded by PTZ cameras. In the kernel of HTFnetSeg, there is the combination of an unsupervised semantic attention homography estimation network (SAHnet) for frames alignment and a spatial transformed deep features fusion network (STDFFnet) for segmentation. The semantic attention mask in SAHnet reinforces the network to focus on background alignment by reducing the noise that comes from the foreground. STDFFnet is designed to reuse the deep features extracted during the semantic attention mask generation step by aligning the features rather than only the frames, with a spatial transformation technique in order to reduce the algorithm complexity. Additionally, a conservative strategy is proposed for the motion map based post-processing step to further reduce the false positives that are brought by semantic noise. The experiments on both CDnet2014 and Lasiesta show that our method outperforms many state-of-the-art methods, quantitively and qualitatively.
Demosaicing of CFA 3.0 with Applications to Low Lighting Images
Authors: Kwan Chiman , Larkin Jude , Ayhan Bulent
Published: June 2020

Low lighting images usually contain Poisson noise, which is pixel amplitude-dependent. More panchromatic or white pixels in a color filter array (CFA) are believed to help the demosaicing performance in dark environments. In this paper, we first introduce a CFA pattern known as CFA 3.0 that has 75% white pixels, 12.5% green pixels, and 6.25% of red and blue pixels. We then present algorithms to demosaic this CFA, and demonstrate its performance for normal and low lighting images. In addition, a comparative study was performed to evaluate the demosaicing performance of three CFAs, namely the Bayer pattern (CFA 1.0), the Kodak CFA 2.0, and the proposed CFA 3.0. Using a clean Kodak dataset with 12 images, we emulated low lighting conditions by introducing Poisson noise into the clean images. In our experiments, normal and low lighting images were used. For the low lighting conditions, images with signal-to-noise (SNR) of 10 dBs and 20 dBs were studied. We observed that the demosaicing performance in low lighting conditions was improved when there are more white pixels. Moreover, denoising can further enhance the demosaicing performance for all CFAs. The most important finding is that CFA 3.0 performs better than CFA 1.0, but is slightly inferior to CFA 2.0, in low lighting images.
Postural Stability in Athletes: The Role of Age, Sex, Performance Level, and Athlete Shoe Features
Authors: Andreeva Albina , Melnikov Andrey , Skvortsov Dmitry , Akhmerova Kadriya , Vavaev Alexander , Golov Andrey , Draugelite Viktorya , Nikolaev Roman , Chechelnickaia Serafima , Zhuk Daria , Bayerbakh Alexandra , Nikulin Vladislav , Zemková Erika
Published: June 2020

The effects of different factors—such as age, sex, performance level, and athletic shoe features—on postural balance in athletes remain unclear. The main objective of our study is to identify the features of postural stability in athletes of different age, sex, performance level, and using different types of athletic shoes. This study assessed postural stability in athletes (n = 936, 6–47 years) in a normal bipedal stance with eyes open (EO) and eyes closed (EC). Postural stability was evaluated based on the center of pressure (COP), sway area (AS), and velocity (VCP) while standing on a stabiloplatform. Children (6–12 years) and teen athletes (13–17 years) showed reduced AS-EO (p < 0.01) and VCP-EO (p < 0.01) compared to control (n = 225, 7–30 years). In male and female athletes aged 18+, only VCP-EC was lower versus control. In females (13–17 and 18+), VCP-EO and EC were lower than in males (p < 0.05). Only in the Shooting group, the athletes’ performance levels had an effect on VCP-EO (p = 0.020). Long use of rigid athletic shoes with stiff ankle support was associated with reduced posture stability. Postural stability in athletes was mostly influenced by the athlete‘s age, and, to a lesser extent, by their sex, performance level, and athlete shoe features.
Repeated Menthol Mouth Swilling Affects Neither Strength nor Power Performance
Authors: Best Russ , Temm Dani , Hucker Holly , McDonald Kerin
Published: June 2020

This study aimed to assess the effects of repeated menthol mouth swilling upon strength and power performance. Nineteen (10 male) participants completed familiarisation and experimental trials of repeated menthol mouth swilling (0.1% concentration) or control (no swill) in a randomised crossover design. Participants performed an isometric mid-thigh pull (IMTP; peak and mean force; N), vertical jump (peak; cm) and six second sprint (peak and mean power; W) under each condition. Participants completed three efforts per exercise task interspersed with three-minute recoveries. Mean best values were analysed via a two-way mixed repeated measures ANOVA, and differences reported as effect sizes ± 95% confidence intervals, with accompanying descriptors and p values. Differences in peak IMTP values were unclear between familiarisation and experimental trials, and between menthol and control conditions. Mean IMTP force differed between familiarisation and control (0.51; −0.15 to 1.14; p = 0.001) and familiarisation and menthol conditions (0.50; −0.15 to 1.14; p = 0.002) by a small degree, but were unclear between control and menthol conditions. Unclear differences were also noted on vertical jump performance compared to familiarisation and between experimental conditions, with repeated six second peak and average power performance also showing unclear effects across all comparisons. We conclude that repeated menthol mouth swilling does not improve strength or power performance.
Population-Based Study of the Influence of the COVID-19 Pandemic on Hand Hygiene Behaviors—Polish Adolescents’ COVID-19 Experience (PLACE-19) Study
Authors: Głąbska Dominika , Skolmowska Dominika , Guzek Dominika
Published: June 2020

Due to the COVID-19 pandemic, the World Health Organization and other major authorities recommend frequent hand washing and applying proper hand hygiene procedures as one of the cheapest, easiest, and most important ways to prevent the spread of a virus. For adolescents it is especially important as it should become for them a lifelong habit. The aim of the study was to assess the hand hygiene behaviors during the COVID-19 pandemic in a national Polish sample of secondary school adolescents and to verify the influence of the COVID-19 pandemic on those behaviors. The study was conducted in April 2020 in a national sample of 2323 secondary school students recruited based on secondary school sampling procedure (random quota sampling with quotas for voivodeships). The hand hygiene behaviors that were assessed included: frequency of washing hands, reasons for not washing hands, circumstances of washing hands, and procedure of handwashing. Participants were asked each question twice—for the current period of the COVID-19 pandemic and for the period before the COVID-19 issue. The declared frequency of washing hands during the COVID-19 pandemic was significantly higher than before (p < 0.0001), as the majority of respondents declared doing it 6–15 times a day (58.4%) while before the pandemic, it was 3–10 times a day (68.1%). The share of respondents declaring washing their hands always while it would be needed was significantly higher for the period during the COVID-19 pandemic (54.8%) than it was for the period before (35.6%; p < 0.0001), and there was a lower share of respondents declaring various reasons for not washing hands. For the majority of circumstances of washing hands, including those associated with meals, personal hygiene, leaving home, socializing, health, and household chores, the share of respondents declaring always washing their hands was significantly higher for the period during the COVID-19 pandemic than for the period before (p < 0.0001). For the majority of steps of handwashing procedure, the share of respondents declaring including them always was significantly higher for the period during the COVID-19 pandemic than for the period before (p < 0.0001), but a higher share declared not wearing a watch and bracelet (p = 0.0006), and rings (p = 0.0129). It was concluded that during the COVID-19 pandemic all the assessed hand hygiene behaviors of Polish adolescents were improved, compared with those before, but hand hygiene education is still necessary.
Climate Change, Rangelands, and Sustainability of Ranching in the Western United States
Authors: Holechek Jerry L. , Geli Hatim M. E. , Cibils Andres F. , Sawalhah Mohammed N.
Published: June 2020

Accelerated climate change is a global challenge that is increasingly putting pressure on the sustainability of livestock production systems that heavily depend on rangeland ecosystems. Rangeland management practices have low potential to sequester greenhouse gases. However, mismanagement of rangelands and their conversion into ex-urban, urban, and industrial landscapes can significantly exacerbate the climate change process. Under conditions of more droughts, heat waves, and other extreme weather events, management of risks (climate, biological, financial, political) will probably be more important to the sustainability of ranching than capability to expand output of livestock products in response to rising demand due to population growth. Replacing traditional domestic livestock with a combination of highly adapted livestock and game animals valued for both hunting and meat may be the best strategy on many arid rangelands. Eventually, traditional ranching could become financially unsound across large areas if climate change is not adequately addressed. Rangeland policy, management, and research will need to be heavily focused on the climate change problem.
Can Both the Economic Value and Energy Performance of Small- and Mid-Sized Buildings Be Satisfied? Development of a Design Expert System in the Context of Korea
Authors: Kim Sean Hay , Nam Jungmin
Published: June 2020

To design a High-Performance Building (HPB), a performance goal should be clearly set from very early design phases, and then a decision path of what performance measures have been chosen in the past stages and shall be chosen in a later stage should be visible. In particular, for small- and mid-sized HPBs that are constructed with a smaller budget, if applicable performance measures are subjective to change, supplementary design costs can increase due to intermittent performance evaluations. To help this situation, we are developing a design expert system for small- and mid-sized buildings that pursues a balance between economic value and energy performance. The economy rule base suggests the most economic building volumetry and form in view of the site context, while the energy rule base suggests a series of energy-sensitive design variables and their options. Based on these rule bases, the expert system presents multiple design decision paths. The design decision support model of the inference engine helps stakeholders choose a preferred design path out of multiple paths, compare the paths, trace back the paths, and effectively revoke past decisions. An actual small retail and office construction project was chosen as a test case to compare the utility and robustness of the pilot system against the conventional design practice. In case of a rather risky design change scenario, the decision-making using the pilot expert system outperforms the conventional practice in terms of selecting designs with a good balance between economic value and energy performance. In addition, it was easier for users of the pilot system to forecast risks upon critical design changes and, in turn, to identify reasonable alternatives.
Sustainable Smart City Building Construction Methods
Authors: Zhuang Haoran , Zhang Jian , C. B. Sivaparthipan , Muthu Bala Anand
Published: June 2020

In a global world, the human population invariably increases while resources gradually decrease as cities and towns constantly consume resources to satisfy their needs and requirements. At this point, it is very necessary to focus on making these urban areas more sustainable and greener. The need for some advanced and automated systems improves the situation, which leads to the innovation of smart cities. Smart city is the concept that helps in developing sustainable cities via optimized resource utilization methods. In smart city development, various sensing technologies can be used that can sense and utilize natural resources in better ways, like storing rainwater to use afterward, intelligent and smart control system, smart infrastructure monitoring system, smart healthcare system, smart transportation system, and smart system for energy consumption and generation by various facilities. To make the city smart and sustainable with efficient energy consumption, we propose renewable solar and wind energy-enabled hybrid heating and cooling HVAC-DHW (heating, ventilation, and air conditioning-Domestic Hot Water) system in which energy consumption is evaluated using optimized NARX-ANN and fuzzy controller based on user needs, dynamic behavior of the atmospheric environment, and spatial distribution of energy supply. To achieve the proposed goal, first, via sensor, heating and cooling effect of environment and building is sensed and these sensed inputs are then fed into deep-learning-based NARX-ANN that forecast internal building temperature. This forecasted temperature is fed into a fuzzy controller for optimizing output based on user demand. This processed information leads to energy distribution based on their requirement using a smart energy sensing system. Based on the experimentation result and performance analysis, it was found that the proposed system is more robust and has a high control response in comparison to the existing systems with minimum energy consumption. The analytical results support the feasibility of the proposed framework architecture to facilitate energy conserving in smart city buildings.
The Influence of Carbon Management on the Financial Performance of European Companies
Authors: Naranjo Tuesta Yenny , Crespo Soler Cristina , Ripoll Feliu Vicente
Published: June 2020

This document shows the relationship between carbon management and the financial performance of the European Union’s best market capitalization companies. Different measures are used to understand it by adopting a quantitative approach. After analyzing the validity and reliability of the construct, the study empirically tests its hypotheses by performing a multiple regression analysis with a sample of 497 companies. The study identified how factors related to carbon management could affect the financial performance of European organizations. Furthermore, it recognizes that carbon management affects profitability, in particular, ROA (Return on Assets). The study highlights the differences between companies that are considered sensitive and those that are not, as the management of emission reductions and performance impacts are handled differently.
Performance Prediction of Proton Exchange Membrane Fuel Cells (PEMFC) Using Adaptive Neuro Inference System (ANFIS)
Authors: Wilberforce Tabbi , Olabi Abdul Ghani
Published: June 2020

This investigation explored the performance of PEMFC for varying ambient conditions with the aid of an adaptive neuro-fuzzy inference system. The experimental data obtained from the laboratory were initially trained using both the input and output parameters. The model that was trained was then evaluated using an independent variable. The training and testing of the model were then utilized in the prediction of the cell-characteristic performance. The model exhibited a perfect correlation between the predicted and experimental data, and this stipulates that ANFIS can predict characteristic behavior of fuel cell performance with very high accuracy.
Essential Safety Factors for the Transport of Dangerous Goods by Road: A Case Study of Lithuania
Authors: Batarliene Nijole
Published: June 2020

Dangerous goods accidents occur infrequently, but the consequences are extremely large and cause many losses. The transport of hazardous substances itself is time consuming and requires a great deal of responsibility compared to a simple load. The safe transport of dangerous goods depends on a large number of factors. The purpose of this article is to examine the conditions of carriage of dangerous goods and to evaluate the factors affecting the carriage of these goods by road transport. This is done by analyzing the scientific literature and statistics and conducting a qualitative survey. The study identified three group factors that have the greatest impact on the safe transport of dangerous goods by road. The survey results were processed using the Kendall ratings correlation method, and the compatibility of the expert sample was studied using the matching factor. The study, using the medium-range transformation weights (ARTIW) method, identified the main factors of normalized subjective weights that influence the safe transport of dangerous goods. The outcomes of the research presented in the paper show that the main factors of Group I have the greatest impact on the likelihood of an accident during dangerous goods transportation by road transport; they include incorrect loading of cargo, driver fatigue, vehicle condition, and weather and road surface conditions. The most important technical/technological factors of Group II are correct loading or unloading of the cargo, tightness of the vehicle semi-trailer/container/tank, and the technical condition of the vehicle. The most important organizational factors in Group III are the risks associated with the carriage of goods, the choice of route, and communication with the emergency services. In the following stages of research, the main factors of the three groups identified should be used to develop models to make the transport of dangerous goods safer.
The African Swine Fever Virus (ASFV) Topoisomerase II as a Target for Viral Prevention and Control
Authors: Coelho João , Leitão Alexandre
Published: June 2020

African swine fever (ASF) is, once more, spreading throughout the world. After its recent reintroduction in Georgia, it quickly reached many neighboring countries in Eastern Europe. It was also detected in Asia, infecting China, the world’s biggest pig producer, and spreading to many of the surrounding countries. Without any vaccine or effective treatment currently available, new strategies for the control of the disease are mandatory. Its etiological agent, the African swine fever virus (ASFV), has been shown to code for a type II DNA topoisomerase. These are enzymes capable of modulating the topology of DNA molecules, known to be essential in unicellular and multicellular organisms, and constitute targets in antibacterial and anti-cancer treatments. In this review, we summarize most of what is known about this viral enzyme, pP1192R, and discuss about its possible role(s) during infection. Given the essential role of type II topoisomerases in cells, the data so far suggest that pP1192R is likely to be equally essential for the virus and thus a promising target for the elaboration of a replication-defective virus, which could provide the basis for an effective vaccine. Furthermore, the use of inhibitors could be considered to control the spread of the infection during outbreaks and therefore limit the spreading of the disease.
FAMILY EDUCATION MODEL AND DIVORCE PREVENTION ON SASAK COMMUNITY IN INDONESIA
Authors: Syafruddin Syafruddin , Sumardi L. , Wadi Hairil , Sukardi Sukardi
Published: June 2020

Abstrtak. Penelitian ini bertujuan untuk menemukan dan memetakan model pendidikan keluarga  sebagai upaya mencegah perceraian  pada masyarakat Suku Sasak. Pendekatan yang digunakan  adalah  penelitian kualitatif dengan metode studi kasus. Hasil penelitian menemukan bahwa model program pendidikan keluarga pada masyarakat dilakukan dengan tahapan sebagai berikut;  (1) Orientasi Program Pendidikan, meliputi; menyiapkan lembaga masyarakat, Orientasi Nara Sumber, Orientasi Obyek Sasaran. (2). Penetapan Program Pendidikan keluarga. Ada 3 tiga program yang dipilih masyarakat sebagai program pendidikan yang dapat mencegah  terjadinya perceraian : a) Program Pendidikan Gender dan Seksualitas. b) Program Pendidikan Hukum Keluarga. c) Program Pendidikan Konseling Sebelum Nikah. (3) Pelaksanaan Program. Untuk merealisasikan program pendidikan keluarga guna mencegah terjadinya perceraian dilaksanakan dengan pola pendidikan dan latihan keterampilan berkeluarga, workshop, dan klinik konsultasi pernikahan. Kata Kunci. Model Pendidikan, Pencegahan Perceraian, Suku Sasak
HUBUNGAN KEJADIAN STUNTING DENGAN PERKEMBANGAN ANAK USIA 24-59 BULAN DI DESA WANGEN POLANHARJO KLATEN
Authors: Qoyyimah Anna Uswatun , Hartati Lilik , Fitriani Siska Amyranda
Published: June 2020

ABSTRAKStunting adalah kondisi gagal tumbuh pada anak balita (bawah lima tahun) sehaingga anak terlalu pendek untuk seusianya, tetapi baru nampak setelah anak usia 2 tahun. Angka kejadian stunting di Indonesia cukup tinggi yaitu 30,8% (11,5% sangat pendek dan 19,3% pendek). Dampak dari stunting sendiri salah satunya yaitu penurunan perkembangan kognitif, motorik, dan kemampuan berbicara, sehingga diperlukannyaa deteksi dini perawakan pendek pada anak  agar diberi intervensi secepatnyaJenis penelitian ini menggunakan metode korelasi. Populasi dalam penelitian ini adalah seluruh balita stunting  usia 24-59 bulan di Desa Wangen Polanharjo periode Maret 2020.  Teknik pengambilan sampel dalam penelitian ini menggunakan teknik total sampling dengan jumlah sampel 30 balita stunting usia 24-59 bulan di Desa Wangen Polanharjo. Hasil penelitian menunjukkan balita stunting  dengan kategori pendek 23 anak (77%) dengan perkembangan sesuai 11 anak (36,6%), meragukan 11 anak (36,6%), dan penyimpangan 1 anak (0,3%). Sedangkan balita stunting dengan kategori sangat pendek yaitu 7 anak (23%) menunjukkan perkembangan sesuai 1 anak (0,3%), meragukan 3 anak (1,0%),  dan penyimpangan 4 anak (13,3%).  Simpulan dalam penelitian ini adalah  ada hubungan kejadian stunting dengan perkembangan anak usia 23-59 bulan di Desa Wangen Polanharjo dengan nilai p=0,024(p<0,05). Kata Kunci : Stunting, Perkembangan Anak                     EVENT RELATIONSHIP STUNTING WITH THE DEVELOPMENT OF CHILDREN AGED 24-59 MONTHS IN WANGEN VILLAGE POLANHARJOABSTRACTStunting is a condition of failing to grow in a toddler (under five years) child so is too short for his age, but only appears after two years of age.  Indonesia's stunting rate is quite high which is 30.8% (11.5% very short and 19.3% short). The impact of its own stunting is the decline in cognitive development, motor, and speech ability, so that the introduction of early detection of short stature in children to be intervened immediately. This type of research uses a correlation method. The population in this study was stunting the whole toddler aged 24-59 months in the village of Wangen Polanharjo on the period of March 2020.  Sampling techniques in this study used total sampling techniques with a sample number of 30 toddlers stunting age 24-59 months in the village of Wangen Polanharjo. The results showed toddlers stunting with a short category of 23 children (77%) With the corresponding development 11 children (36.6%), doubtful 11 children (36.6%), and deviation of 1 child (0.3%). The toddler stunting with very short category is 7 children (23%) Shows the development According to 1 child (0.3%), doubtful 3 children (1.0%), and deviations of 4 children (13.3%). The conclusion In this study was that there was a stunting incident with the development of children aged 23-59 months in the village of Wangen Polanharjo with a value of p = 0.024 (p < 0.05). Keywords : Stunting, Child development
EVALUASI KETERSEDIAAN FASILITAS KESEHATAN YANG MEMADAI TERHADAP PENCAPAIAN REVOLUSI KIA DI MANGGARAI
Authors: Nanur Fransiska Nova , Norce Halu Silfia Angela , Juita Enjelina
Published: June 2020

ABSTRAKRevolusi KIA merupakan salah satu terobosan pemerintah Provinsi Nusa Tenggara Timur dalam rangka mempercepat penurunan kematian ibu dan bayi dengan cara luar biasa melalui persalinan pada fasilitas kesehatan yang memadai dan siap 24 jam. Penelitian ini bertujuan untuk mengevaluasi ketersediaan fasilitas kesehatan memadai yang meliputi kuantitas dan kualitas tenaga kesehatan, ketersediaan sarana fisik, obat dan peralatan kesehatan serta pembiayaan. Penelitian ini menggunakan metode kualitatif dengan wawancara mendalam pada 15 partisipan kunci yang meliputi kepala bidang kesehatan masyarakat Dinas Kesehatan Kabupaten Manggarai, kepala puskesmas, bidan, masyarakat (ibu nifas). Data dianalisis secara thematic. Hasil penelitian menunjukkan bahwa ketersediaan fasilitas kesehatan yang memadai untuk mendukung kebijakan revolusi KIA di Kabupaten Manggarai belum optimal seperti jumlah dokter yang sangat terbatas, kualitas tenaga kesehatan yang belum memadai, belum semua fasilitas kesehatan memiliki fasilitas rumah tunggu persalinan, peralatan kesehatan yang masih terbatas. Oleh karena itu, diperlukan komitmen pemerintah Kabupaten Manggarai untuk terus berupaya meningkatkan kualitas tenaga kesehatan, merekrut tenaga dokter, menyediakan rumah tunggu persalinan dan mengalokasikan anggaran yang cukup untuk pembiayaan kesehatan. Kata Kunci : Revolusi, KIA, Fasilitas, kesehatan, memadai   THE EVALUATION OF THE AVAILABILITY OF GOOD HEALTH FACILITIES TO SUPPORT THE REVOLUSI KIA PROGRAM IN MANGGARAI ABSTRACTRevolusi KIA is one of the programs of Nusa Tenggara Timur Province (NTT) aim at decreasing the maternal and infant mortality by providing the good health facilities for 24 hour service. This research aims to evaluate the availability of the good health facilities by looking at some aspects such as the quantity and quality of professional health, the availability of physical buildings, medicine, medical tools and finance. This research uses qualitative model by depth interview with 15 key informants from varied background like health public health office of Manggarai Regency, the head of Puskesmas, midwife and puerperal mother. Data analyzed thematically. The result shows that from the side of providing the good health facilities, the Revolusi KIA Program of Manggarai Regency has not run optimally in decreasing the maternal and infant mortality. In indicates through the lack of doctors, the bad quality of health workers, lack of maternity waiting house and the limit of medical tools. Therefore, the local government must seriously improve the quality of health workers, increase the number of doctors, provide the maternity waiting house and allocate the enough budget for health financing.  Keyword : Revolusi, KIA, facilities, health
Data Fast Transmission Method in Wireless Vehicle Ad-hoc Network
Authors: Niknamian Sorush
Published: June 2020

In vehicular ad hoc networks, the current method does not consider the delay of data transmission, resulting in slower vehicle data transmission speed. A vehicle data transmission method based on backbone network is proposed in this paper. Firstly, the characteristics of vehicle ad hoc network are analyzed. Based on the statistics of the road, the vehicle cluster is composed of the vehicles parking on the roadside and no roadside according to the different directions of the vehicle driving. The backbone network is constructed on the basis of the cluster of vehicles, and the data transmission between the vehicles is implemented by the data transmission method of overlay network. This method can overcome the disadvantages of traditional data transmission methods, improve the efficiency of on-board data transmission, and complete the research on fast data transmission method in wireless vehicle ad hoc network. The experimental results show that the proposed method can achieve higher data transmission success rate with lower data transmission overhead and smaller transmission delay.
An Empirical Evaluation On Comparative Machine Learning Techniques For Detection of The Distributed Denial of Service (DDoS) Attacks
Authors: Ojugo Arnold , Eboka Andrew Okonji
Published: June 2020

The advent of the Internet that aided the efficient sharing of resources. Also, it has introduced adversaries whom are today restlessly in their continued efforts at an effective, non-detectable means to invade secure systems, either for fun or personal gains. They achieve these feats via the use of malware, which is both on the rise, wreaks havoc alongside causing loads of financial losses to users. With the upsurge to counter these escapades, users and businesses today seek means to detect these evolving behavior and pattern by these adversaries. It is also to worthy of note that adversaries have also evolved, changing their own structure to make signature detection somewhat unreliable and anomaly detection tedious to network administrators. Our study investigates the detection of the distributed denial of service (DDoS) attacks using machine learning techniques. Results shows that though evolutionary models have been successfully implemented in the detection DDoS, the search for optima is an inconclusive and continuous task. That no one method yields a better optima than hybrids. That with hybrids, users must adequately resolve the issues of data conflicts arising from the dataset to be used, conflict from the adapted statistical methods arising from data encoding, and conflicts in parameter selection to avoid model overtraining, over-fitting and over-parameterization.
The date predicted 200.000 cases of Covid-19 in Spain
Authors: Ahmar Ansari Saleh , Boj Eva
Published: June 2020

The aim of this study is to predict 200.000 cases of Covid-19 in Spain. Covid-19 Spanish confirmed data obtained from Worldometer from 01 March 2020 – 17 April 2020. The data from 01 March 2020 – 10 April 2020 using to fitting with data from 11 April – 17 April 2020. For the evaluation of the forecasting accuracy measures, we use the mean absolute percentage error (MAPE). Based on the results of SutteARIMA fitting data, the accuracy of SutteARIMA for the period 11 April 2020 - 17 April 2020 is 0.61% and we forecast 20.000 confirmed cases of Spain by the WHO situation report day 90/91 which is 19 April 2020 / 20 April 2020.
Scattered Point Cloud Data Reconstruction Algorithm Based on Local Convexity
Authors: Niknamian Sorush
Published: June 2020

Point cloud data reconstruction is the basis of point cloud data processing. The reconstruction effect has a great impact on application. For the problems of low precision, large error, and high time consumption of the current scattered point cloud data reconstruction algorithm, a new algorithm of scattered point cloud data reconstruction based on local convexity is proposed in this paper. Firstly, according to surface variation based on local outlier factor (SVLOF), the noise points of point cloud data are divided into near outlier and far outlier, and filtered for point cloud data preprocessing. Based on this, the algorithm based on local convexity is improved. The method of constructing local connection point set is used to replace triangulation to analyze the relationship of neighbor points. The connection part identification method is used for data reconstruction. Experimental results show that, the proposed method can reconstruct the scattered point cloud data accurately, with high precision, small error and low time consumption.
PEMANFAATAN E-COMMERCE BUSINESS TO CONSUMER (B2C) MARKETPLACE UNTUK PENGEMBANGAN USAHA MIKRO,KECIL DAN MENENGAH (UMKM)
Authors: Dono Saputro Prasetyo
Published: June 2020

In welcoming the Industrial Revolution 4.0 marked the era of the digital economy (Digital Economy Era). The new economic era is characterized by the application of information technology in carrying out its economic activities. Internet users in Indonesia aged 13-18 years = 16.68%, age 19-34 years = 49.52%, age 35-54 years = 29.55%, age> 54 years = 4.24%. And the number of internet users by sex, male gender is = 51.43%, female gender is = 48.57%. The use of the internet today has even penetrated into the e-commerce market place system which is a sale and purchase of goods / services through electronic networks (internet). Transactions through e-commerce involve 3 parties, namely: suppliers / partners, website managers (our company), and customers (customers). The data on internet usage are as follows: looking for prices = 45.12%, helping jobs = 41.04%, buying information = 37.82%, buying online = 32.19%, looking for work = 26.19%, banking transactions = 17.04%, selling online = 16.83%. The stages that occur in e-commerce market place are: (1) Orders are made online (carried out by the buyer); (2) Confirming payment (carried out by the buyer); (3) Checking the condition of the stock of goods (carried out by the seller); (4) Arranging the delivery of goods (arranging shipping services provided by the e-commerce marketplace system, usually carried out by the seller); e-commerce market place, the goal is that customer trust can be achieved / fulfilled)