bluuebunny/crossref_metadata_2025 huggingface dataset:
Конституціоналізація соціально- економічних прав: український ракурс постановки проблеми
Authors: Загоруй І. С.
Published: September 2019

Конкретизація проблеми забезпечення соціально-економічних прав громадян України в теоретико-правовому аспекті набула вигляду необхідності їх конституціоналізації. Надзвичайна трудність процесів державотворення на сучасному етапі потребує не тільки постановки цієї проблеми, але й якомога швидкого її вирішення. У статті розглянуто: а) поняття та б) процес конституціоналізації в сучасних їх інтерпретаціях як вітчизняними вченими, так і зарубіжними. Теоретичні положення ілюстровано історичними прикладами, зокрема з історії України. Показано, що процес  конституціоналізації соціально-економічних й інших прав людини і громадянина розпочатий Конституцією України 1996 року; подано його основні характеристики: порівняння з іншими правами, поява нових прав, яких раніше ніколи не було, орієнтування на міжнародні правові акти. У висновках йдеться про відповідність поняття конституціоналізації в зазначеній сфері вітчизняної практики та процесу конституціоналізації міжнародним вимогам.
Зміст суб’єктивного авторського права
Authors: Любчик О. А.
Published: September 2019

У статті проаналізовано наукові погляди на проблему визначення сутності та змісту суб’єктивного авторського права на твір науки, мистецтва та літератури, а саме визначення змісту виключних прав на нього. Акцентовано увагу щодо зміни формулювання поняття цих прав, їх обсягу та видів різними авторами, які були представниками різних соціально-економічних формацій, ідеолого-політичних напрямів розвитку держави. Визначено наукове поняття та зміст виключних прав як складових суб’єктивного авторського права. Аргументовано пропозиції щодо вдосконалення законодавчого регулювання цього питання.
Право як феномен культури: спроба концептуальної самокритики. Стаття перша. Про доцільність постановки проблеми і деякі питання методології та термінології. Частина 4. Про термінологію: новели дослідження (закінчення)
Authors: Литвинов О. М.
Published: September 2019

У статті подано критичний огляд тлумачення термінопонять, запропонованих уперше в попередніх працях автора в процесі дослідження права як феномена культури. На основі виокремлення імітаційних культур (передусім у правовому сенсі) як «вторинних» доведено необхідність введення нових термінопонять, що більш адекватно передають особливості соціальних (і правових зокрема) процесів у сучасному світі, які розглядаються як етап чи то період, означений в культурно-історичному сенсі як «другий осьовий час». В останній частині статті розглянуто термінопоняття «штучна бідність» (як створена переважно східною–азійською чи то візантійською – за своїми інтенціями владою), «негативна селекція» (як прояв водночас архаїзму та «візантійщини»), «територія нещастя» (як результат постійного панування кримінальної свідомості), «біоп’ютер» (як характеристика типу людини, яка формується в сучасних технологічних умовах, але без досвіду свободи), «нові форми рабства» (як результат криміналізації соціуму), а також сформульовано висновки як підсумки самокритики у вигляді постановки проблем, необхідність осмислення яких є результатом розробленого автором підходу, котрий означено як культурологічний. Одним з основних висновків є той, що стосується конкретизації поняття «люди минулого» в понятті «радянська людина» як тип людини, створений за часів панування тоталітарного режиму.
Правове забезпечення формування єдиного медичного простору України (теоретико-методологічні аспекти дослідження)
Authors: Сіделковський О. Л.
Published: September 2019

У статті акцентовано увагу на проблематиці формування єдиного медичного простору України. Констатовано, що це важливий чинник поліпшення стану справ із забезпеченням прав пацієнтів. Запропоновано враховувати тенденції децентралізації при побудові єдиного медичного простору України.
Окремі аспекти інституту забезпечення безпеки учасників кримінального провадження
Authors: Глобенко Г. І.
Published: September 2019

У статті розглянуто окремі питання забезпечення захисту учасників кримінального провадження. Здійснено характеристику міжнародно-правових актів та порівняльно-правовий аналіз положень КПК України 1960 та 2012 рр., що стосуються досліджуваного інституту. Автор на підставі розробленихміжнародною спільнотою документів доходить висновку, що зближення національного законодавства з цими стандартами є природним і потрібним. Обґрунтовано доконечну потребу систематизації та осмислення науковцями й практиками наявного фактичного та наукового матеріалу з окреслених питань.Визначено прогалини законодавчого регулювання та пріоритетні напрями досліджуваного інституту.
Проблема зарахування попереднього ув’язнення в строк покарання в контексті забезпечення єдності судової практики
Authors: Дудоров О. О. , Письменський Є. О.
Published: September 2019

Статтю присвячено проблемі зарахування попереднього ув’язнення в строк покарання. Розкрито правову природу такого зарахування. За допомогою аналізу відповідних рішень Верховного Суду з’ясовано питання про дію в часі змінюваної у 2015 і 2017 роках частини 5 статті 72 Кримінального кодексу України.
Study for Development of Health Belief Scale Related to Lead Exposure
Authors: Gultekin Tugba , Kitis Yeter
Published: September 2019

Background/Aim: This methodological study was conducted to develop a health belief scale for lead exposure, and to analyze the validity and reliability of the scale.

Materials and Methods: The study was carried out on 525 male workers applying to Ankara Occupational Diseases Hospital between February 1 and April 30, 2013. The Participant Information Form and the Health Belief Scale Related to Lead Exposure (HBSRLE) were used to collect data. Data content validity was analyzed with Law she technique by the experts of the subject, construct validity with factor analysis, and reliability with Cronbach's alpha coefficient and Spearman correlation analysis.

Results: Construct validity analysis revealed that the scale was composed of six factors with factor loads ranging from .615 to .832 (p<0.05). Reliability analysis revealed that HBSRLE's Cronbach's alpha reliability coefficient was .94 and sub-dimensions ranged from .81 to .94. Based on split-half reliability analysis, Spearman- Brown coefficient of the Scale was .740 and the Gutman Split- Half Coefficient was .739 (p<0.05). Spearman correlation analysis showed that item-total score correlations (Rho) ranged from .233 to .868 (p<0.001).

Discussion and Conclusions: As a result of validity and reliability analyses, it was found that HBSRLE, consisting of 33 items and six sub-dimensions, is a valid and reliable scale.
Clinical and Psychosocial Characteristics of HIV-Positive and HIV-Negative Females with Opiate Dependence
Authors: EP Stan’ko , SA Igumnov , A Nestsiarovich , EV Grinevich
Published: September 2019

The objective of the study was to explore the clinical-psychological and social characteristics of injecting drugs women users (IDWU) with opiate dependence with different HIV status living on the territory of the Republic of Belarus based on multi-dimensional assessment of opiate dependence dynamics in order to develop therapeutic measures for relapse prevention and achievement of the long-term remission.

Materials and methods: Totally 217 IDWU were examined. The research cohort was randomized into 2 groups: HIV-positive women (HPW) (104 persons, mean age 30.8 years (SD=4.86) and HIV-negative women (HNW) (113 persons, mean age 29.9 years (SD=6.67). The level of patients social functioning, quality of life, craving for narcotic substances were studied by means of the Scale of the social and functioning, SF-36 and the Scale of the craving for drugs. The particularities of the social functioning and life quality of women with opiate addiction and different HIV status were described.

The results: show that the majority of IDWU were characterized by frequent work replacement and labor skipping (27/25.9% in HPW group vs 30/26.5% in HNW group; P>0.05). 21 /20.1% HPW vs 15/13.2% HNW (P<0.05) was characterized by low qualification, 43/43.3% HPW vs 41/36.2% HNW (P>0.05) - vocational education. HPW have more severely impaired psychosocial parameters compared to HNW. Family climate can be described as hostile aggressive (84/80.7% in HNW group vs 69/61.0% in HNW group; P<0.05). For women of both groups were characteristic parental alcohol abuse (18/17.3% in HPW vs 16/14.1% in HNW; P>0.05), and high level of parental divorces (24/23.1% in HPW vs 32/28.3% in HNW; P>0.05). It was found that the treatment itself allows to diminish the problems associated with drug use and HIV infection. Nevertheless, the short-term treatment course can only provide the clinical improvement but not stabilization of psychosomatic state of HIV-positive patients with opiate dependence.

Conclusions: The results of the study indicates the vast majority of women who are injecting drug users, living in Belarus, can be characterized by high level of social functioning disturbances including domestic, social and professional relationship. They need for development of specific tactics of management to suit their needs, including the long-term complex treatment and rehabilitation programs.
Developing Effective Collaborations: Learning from Our Practice
Authors: Kennedy Jo , McKenzie Ian , Thomas Joette
Published: September 2019

In this article we explore the challenges inherent in developing effective interorganizational relationships in the context of supporting the integration of health and social care in Scotland. We begin by outlining the context of health and social care integration and the nature of the program. We then describe the theories that underpinned our approach and outline in detail how the approach worked in practice in one area. We go on to discuss our reflections on six practices participants found helpful in creating the conditions necessary for effective collaboration. Finally, we end by reflecting on our learning.
Evaluation of the ‘Irish Rules’: The Potato Late Blight Forecasting Model and Its Operational Use in the Republic of Ireland
Authors: Cucak Mladen , Sparks Adam , Moral Rafael , Kildea Stephen , Lambkin Keith , Fealy Rowan
Published: September 2019

Potato late blight caused by Phytophthora infestans is one of the most important plant diseases known, requiring high pesticide inputs to prevent disease occurrence. The disease development is highly dependent on weather conditions, and as such, several forecasting schemes have been developed worldwide which seek to reduce the inputs required to control the disease. The Irish Rules, developed in the 1950s and calibrated to accommodate the meteorological network, the characteristics of potato production and the P. infestans population at the time, is still operationally utilized by the national meteorological agency, Met Éireann. However, numerous changes in the composition and dynamics of the pathosystem and the risks of production/economic consequences associated with potato late blight outbreaks have occurred since the inception of the Irish Rules model. Additionally, model and decision thresholds appear to have been selected ad hoc and without a clear criteria. We developed a systematic methodology to evaluate the model using the empirical receiver operating curve (ROC) analysis and the response surface methodology for the interpretation of the results. The methodology, written in the R language, is provided as an open, accessible and reproducible platform to facilitate the ongoing seasonal re-evaluation of the Irish Rules and corresponding decision thresholds. Following this initial analysis, based on the available data, we recommend the reduction of the thresholds for relative humidity and an initial period duration from 90% and 12 h to 88% and 10 h, respectively. Contrary to recent reports, we found that the risk of blight epidemics remains low at temperatures below 12 °C. With the availability of more comprehensive outbreak data and with greater insight into the founder population to confirm our findings as robust, the temperature threshold in the model could potentially be increased from 10 °C to 12 °C, providing more opportunities for reductions of pesticide usage. We propose a dynamic operational decision threshold between four and 11 effective blight hours (EBH) set according to frequency of the disease outbreaks in the region of interest. Although the risk estimation according to the new model calibrations is higher, estimated chemical inputs, on average, are lower than the usual grower’s practice. Importantly, the research outlined here provides a robust and reproducible methodological approach to evaluate a semi-empirical plant disease forecasting model.
Chlorophyll α Fluorescence Parameters as an Indicator to Identify Drought Susceptibility in Common Bush Bean
Authors: Sánchez-Reinoso Alefsi David , Ligarreto-Moreno Gustavo Adolfo , Restrepo-Díaz Hermann
Published: September 2019

The common bean is susceptible to drought conditions and the evaluation of plant responses to low water availability can be difficult. The quantification of chlorophyll fluorescence as a sensitive trait to environmental stresses is an important alternative in the characterization of drought-susceptible genotypes. The objective of this study was to evaluate mainly the use of chlorophyll α fluorescence (maximum efficiency of PSII (Fv/Fm), photochemical quenching (qP), non-photochemical quenching (NPQ)) and rapid light-response curves (RLCs) (initial slope of the curve (α), minimum saturation irradiance (Ik) and maximum relative electron transport rate (ETRmax)) parameters as tools for the identification of susceptible or tolerant bush bean cultivars to water deficit stress conditions in two different phenological stages. Using a randomized block design in a factorial arrangement, five bush bean cultivars (Cerinza, Bachue, NUA35, Bacata and Bianca) were evaluated under water deficit conditions by the suspension of irrigation for 15 days from 40 to 55 Days after Emergence (DAE) (vegetative stage) or 50 to 65 DAE (reproductive stage). The results showed that Fv/Fm and NPQ recorded the highest variation due to water deficit conditions, especially in the vegetative stage. The greatest reductions in Fv/Fm (0.67) and NPQ (0.71) were evidenced in cultivar NUA35 compared to its control plants (0.78 and 1.07, respectively). The parameters obtained from RLCs showed that cultivar Bacata registered the lowest α (0.17) and Ik (838.19 μmol∙m−2∙s−1) values compared to its control plants (α 0.23; Ik 769.99 μmol∙m−2∙s−1). Differences were only obtained in ETRmax in the reproductive stage (50–65 DAE) in which cultivar NUA35 reached values of 158.5 in stressed plants compared to control plants (251.22). In conclusion, the parameters derived from RLCs such as α and Ik can be used as tools to identify drought susceptibility in the vegetative stage, whereas ETRmax can be used in the reproductive stage. In addition, PSII photochemistry (Fv/Fm and NPQ) can also help to understand the agronomic responses of common bush bean cultivars to drought conditions.
Antioxidant Effects of Apocynum venetum Tea Extracts on d-Galactose-Induced Aging Model in Mice
Authors: Li Chong , Tan Fang , Yang Jianjun , Yang Yue , Gou Yuting , Li Shuting , Zhao Xin
Published: September 2019

As a traditional Chinese medicinal drink, Apocynum venetum, a local tea from Xinjiang, China, is favored for its rich flavor and biological functionality. This study looked at aging mice induced by d-galactose to determine the in vivo anti-aging effect of Apocynum venetum tea extracts (AVTEs) and its bioactive components. We evaluated the weight of major organs (via organ index) and pathological changes in the liver. We also detailed the effects of AVTE (250 mg/kg in the low dose group, 500 mg/kg in the high dose group) on biochemical parameters (malondialdehyde, superoxide dismutase, glutathione, glutathione peroxidase, catalase, total antioxidant capacity, and nitric oxide) and cytokines (IL-6, IL-12, TNF-α and IL-1β) in the serum of aging mice. We investigated the anti-aging effects of AVTE in d-galactose-induced aging mice via quantitative real-time reverse transcription-polymerase chain reaction (RT-qPCR) assay. In addition, we analyzed the biological components of AVTEs by high performance liquid chromatography (HPLC). The results were remarkable, suggesting that AVTE significantly improved d-galactose-induced aging mice, with the high dose group showing the best results among other groups. ATVE can effectively alleviate hepatocyte edema, as well as inflammatory cell infiltration and injury in mice, induce a protective effect via up-regulation of glutathione (GSH), glutathione peroxidase (GSH-Px), superoxide dismutase (SOD), and catalase (CAT) antioxidant related factors, and play an important role in the up-regulation of anti-inflammatory factors (IL-10) and the down-regulation of pro-inflammatory factors (IL-6, TNF-α and IL-1β). At the same time, HPLC analysis showed that AVTEs contain neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, rutin, isoquercitrin, isochlorogenic acid B, isochlorogenic acid A, astragalin, isochlorogenic acid C, rosmarinic acid, and trans-cinnamic acid. Thus, AVTE appears to be an effectively functional drink due to its rich functional components and anti-aging activities.
Weak Fault Feature Extraction and Enhancement of Wind Turbine Bearing Based on OCYCBD and SVDD
Authors: Wang Xiaolong , Yan Xiaoli , He Yuling
Published: September 2019

The fault feature of wind turbine bearing is usually very weak in the early injury stage, in order to accurately identify the defect location, an original approach based on optimized cyclostationary blind deconvolution (OCYCBD) and singular value decomposition denoising (SVDD) is put forward to extract and enhance the fault feature effectively. In this diagnosis method, the fast spectral coherence is fused with the equal step size search strategy for the cyclic frequency parameter and the filter length parameter optimization, and a new frequency weighted energy entropy (FWEE) indicator which combining the advantages of the frequency weighted energy operator (FWEO) and the Shannon entropy, is developed for deconvolution signal evaluation during parameter optimization process. In addition, a novel singular value order determination approach based on fitting error minimum principle is utilized by SVDD to enhance the fault feature. During the process of defect identification, OCYCBD with the optimal parameters is firstly used to recover the informative source from the collected vibration signal. FWEO is further utilized to highlight the potential impulsive characteristics, and the instantaneous energy signal of deconvolution result can be acquired. The whole interferences contained in the instantaneous energy signal can’t be removed due to the weak fault signature and the severe background noise. Then, SVDD is applied to purify the instantaneous energy signal of deconvolution signal, by which the residual interference component is eliminated and the fault feature is strengthened immensely. Finally, frequency domain analysis is performed on the denoised instantaneous energy signal, and the defect location identification of wind turbine bearing can be achieved through analyzing the obvious spectral lines in the obtained enhanced energy spectrum. The collected signals from the experimental platform and the engineering field are both utilized to verify the feasibility of proposed method, and its superiority is further demonstrated through comparing with several well known diagnosis methods. The results indicate this novel method has distinct advantage on bearing weak feature extraction and enhancement.
The Direct Integration Method with Virtual Initial Conditions on the Free and Forced Vibration of a System with Hysteretic Damping
Authors: Pan Danguang , Fu Xiangqiu , Qi Wenrui
Published: September 2019

The energy dissipated in hysteretic damping is independent of cyclic frequency, which agrees with the experimental results of energy dispersion of many materials under cyclic loading. Despite these desirable properties, hysteretic damping suffers from a notable drawback; the direct integration solution of the equation of motion is divergent. In this paper, a virtual initial condition is proposed to address the instability of the solution. The new method develops virtual initial conditions associated to the real initial conditions, which make the direct integration solution eliminate the divergence term of the complementary solution and converge to the exact solution. The stability and accuracy of the proposed direct integration method are demonstrated to be effective in solving the divergence problem by the comparison of the numerical and theoretical solutions on the free and forced vibration of a system with hysteretic damping.
Research on Optimal Landing Trajectory Planning Method between an UAV and a Moving Vessel
Authors: Tan Liguo , Wu Juncheng , Yang Xiaoyan , Song Senmin
Published: September 2019

The location, velocity, and flight path angle of an autonomous unmanned aerial vehicle (UAV) landing on a moving vessel are key factors for an optimal landing trajectory. To tackle this challenge, this paper proposes a method for calculating the optimal approach landing trajectory between an UAV and a small vessel. A numerical approach (iterative method) is used to calculate the optimal approach landing trajectory, and the initial lead is introduced in the calculation process of the UAV trajectory for the inclination and heading angle for accuracy improvement, so that the UAV can track and calculate the optimal landing trajectory with high precision. Compared with the variational method, the proposed method can calculate an optimal turning direction angle for the UAV during the landing. Simulation experiments verify the effectiveness of the proposed algorithm and give optimal initialization values.
A Statistical Performance Analysis of Named Data Ultra Dense Networks
Authors: Rehman Muhammad Atif Ur , Kim Donghak , Choi Kyungmee , Ullah Rehmat , Kim Byung Seo
Published: September 2019

Named data networking (NDN) is a novel communication paradigm that employs names rather than references to the location of the content. It exploits in-network caching among different nodes in a network to provide the fast delivery of content. Thus, it reduces the backhaul traffic on the original producer and also eliminates the need for a stable connection between the source (consumer) and destination (producer). However, a bottleneck or congestion may still occur in very crowded areas, such as shopping malls, concerts, or stadiums, where thousands of users are requesting information from a device that resides at the edge of the network. This paper provides an analysis of content delivery in terms of the interest satisfaction rate (ISR) in ultra-dense network traffic situations and presents a final and an adequate statistical model based on multiple linear regression (MLR) to enhance ISR. A four-way factorial design was used to generate the dataset by performing simulations in ndnSIM. The results show that there is no significant interaction between four predictors: number of nodes (NN), number of interests (NI) per second, router bandwidth (RB), and router delay (RD). Moreover, the NI has a negative effect, and log(RB) has a positive effect on the ISR. The NN less than 10 has a significantly higher effect on the ISR compared with other nodes’ densities.
Supervised Machine Learning Techniques to the Prediction of Tunnel Boring Machine Penetration Rate
Authors: Xu Hai , Zhou Jian , G. Asteris Panagiotis , Jahed Armaghani Danial , Tahir Mahmood Md
Published: September 2019

Predicting the penetration rate is a complex and challenging task due to the interaction between the tunnel boring machine (TBM) and the rock mass. Many studies highlight the use of empirical and theoretical techniques in predicting TBM performance. However, reliable performance prediction of TBM is of crucial importance to mining and civil projects as it can minimize the risks associated with capital costs. This study presents new applications of supervised machine learning techniques, i.e., k-nearest neighbor (KNN), chi-squared automatic interaction detection (CHAID), support vector machine (SVM), classification and regression trees (CART) and neural network (NN) in predicting the penetration rate (PR) of a TBM. To achieve this aim, an experimental database was set up, based on field observations and laboratory tests for a tunneling project in Malaysia. In the database, uniaxial compressive strength, Brazilian tensile strength, rock quality designation, weathering zone, thrust force, and revolution per minute were utilized as inputs to predict PR of TBM. Then, KNN, CHAID, SVM, CART, and NN predictive models were developed to select the best one. A simple ranking technique, as well as some performance indices, were calculated for each developed model. According to the obtained results, KNN received the highest-ranking value among all five predictive models and was selected as the best predictive model of this study. It can be concluded that KNN is able to provide high-performance capacity in predicting TBM PR. KNN model identified uniaxial compressive strength (0.2) as the most important and revolution per minutes (0.14) as the least important factor for predicting the TBM penetration rate.
An Empirical Approach for Extreme Behavior Identification through Tweets Using Machine Learning
Authors: Sharif Waqas , Mumtaz Shahzad , Shafiq Zubair , Riaz Omer , Ali Tenvir , Husnain Mujtaba , Choi Gyu Sang
Published: September 2019

The rise of social media has led to an increasing online cyber-war via hate and violent comments or speeches, and even slick videos that lead to the promotion of extremism and radicalization. An analysis to sense cyber-extreme content from microblogging sites, specifically Twitter, is a challenging, and an evolving research area since it poses several challenges owing short, noisy, context-dependent, and dynamic nature content. The related tweets were crawled using query words and then carefully labelled into two classes: Extreme (having two sub-classes: pro-Afghanistan government and pro-Taliban) and Neutral. An Exploratory Data Analysis (EDA) using Principal Component Analysis (PCA), was performed for tweets data (having Term Frequency—Inverse Document Frequency (TF-IDF) features) to reduce a high-dimensional data space into a low-dimensional (usually 2-D or 3-D) space. PCA-based visualization has shown better cluster separation between two classes (extreme and neutral), whereas cluster separation, within sub-classes of extreme class, was not clear. The paper also discusses the pros and cons of applying PCA as an EDA in the context of textual data that is usually represented by a high-dimensional feature set. Furthermore, the classification algorithms like naïve Bayes’, K Nearest Neighbors (KNN), random forest, Support Vector Machine (SVM) and ensemble classification methods (with bagging and boosting), etc., were applied with PCA-based reduced features and with a complete set of features (TF-IDF features extracted from n-gram terms in the tweets). The analysis has shown that an SVM demonstrated an average accuracy of 84% compared with other classification models. It is pertinent to mention that this is the novel reported research work in the context of Afghanistan war zone for Twitter content analysis using machine learning methods.
Siamese Tracking with Adaptive Template-Updating Strategy
Authors: Xu Zheng , Luo Haibo , Hui Bin , Chang Zheng , Ju Moran
Published: September 2019

Recently, we combined a contour-detection network and a fully convolutional Siamese tracking network to initialize a new start-up of vehicle tracking by clicking on the target, generating a contour proposal template instead of using a fixed bounding box. Tests on the OTB100 and Defense Advanced Research Projects Agency (DARPA) datasets proved that our method outperformed the state of the art and effectively solved the partial-occlusion problem. However, the current Siamese tracking method uses the target in the first frame as a template during the whole tracking period, and leads to the failed tracking of target deformation. In this paper, we propose a new template-update method and reconstruct the whole tracking process with a template-updating module. To be specific, the innovative adaptive template-updating module is comprised of a neural contour-detection network and a target-detection network. Experiment results on the DARPA dataset prove that our new tracking algorithm with the template-updating strategy prominently improved tracking accuracy regarding the deformation condition.
Arsenic Removal from Water by Adsorption onto Iron Oxide/Nano-Porous Carbon Magnetic Composite
Authors: Joshi Sahira , Sharma Manobin , Kumari Anshu , Shrestha Surendra , Shrestha Bhanu
Published: September 2019

This study aimed to develop magnetic Fe3O4/sugarcane bagasse activated carbon composite for the adsorption of arsenic (III) from aqueous solutions. Activated carbon (AC) was prepared from sugarcane bagasse by chemical activation using H3PO4 as an activating agent at 400 °C. To enhance adsorption capacity for arsenic, the resultant AC was composited with Fe3O4 particles by facile one-pot hydrothermal treatment. This method involves mixing the AC with aqueous solution of iron (II) chloride tetrahydrate, polyvinyl pyrrolidone (PVP), and ethanol. Batch adsorption experiments were conducted for the adsorption of As (III) onto the composite. The effects of pH, adsorbent dosage, and contact time on the arsenic adsorption were studied. The result showed that the composite could remove the arsenic from the water far more effectively than the plain AC. The highest percentage of arsenic removal was found at pH at 8, adsorbent dose of 1.8 g/L, and contact time of 60 min. Langmuir and Freundlich adsorption isotherm was used to analyze the equilibrium experimental data. Langmuir model showed the best fit compared to the Freundlich model with a maximal capacity of 6.69 mg/g. These findings indicated that magnetic Fe3O4/sugarcane bagasse AC composite could be potentially applied for adsorptive removal of arsenic (III) from aqueous solutions.
Application of an Adaptive “Neuro-Fuzzy” Inference System in Modeling Cutting Temperature during Hard Turning
Authors: Savkovic Borislav , Kovac Pavel , Dudic Branislav , Rodic Dragan , Taric Mirfad , Gregus Michal
Published: September 2019

The machining of hard materials with the most economical process is a challenge that is the aim of production systems. Increasing demands of the market require a hard processing hardened steel in order to avoid finishing grinding. This research considers the turning of hardened steel without cooling with two types of tools: cubic boron nitride (CBN) and hard metal (HM) inserts. To estimate the influence of machining conditions on cutting temperature, a central composition design with three factors on five levels was used. The development of advanced models allows one to meet the accelerated demands in terms of productivity, product quality, and reduced production costs. Based on experimental data, three input regimes (cutting speed, feed, and depth of cut), and one attributive factor (tool material) were used as input variables, while cutting temperature was used as the output of the adaptive neuro-fuzzy inference systems (ANFIS). The model was trained, tested, and validated with a combined input/output data set. The obtained ANFIS model could be applied with high precision to determine the cutting temperature in machining of hardened steel. From an economic point of view, the obtained model can directly affect the cost of processing because cutting temperature and tool life are directly relieved.
Non-Thermal Plasma Accelerates Astrocyte Regrowth and Neurite Regeneration Following Physical Trauma In Vitro
Authors: Katiyar Kritika S. , Lin Abraham , Fridman Alexander , Keating Carolyn E. , Cullen D. Kacy , Miller Vandana
Published: September 2019

Non-thermal plasma (NTP), defined as a partially ionized gas, is an emerging technology with several biomedical applications, including tissue regeneration. In particular, NTP treatment has been shown to activate endogenous biological processes to promote cell regrowth, differentiation, and proliferation in multiple cell types. However, the effects of this therapy on nervous system regeneration have not yet been established. Accordingly, the current study explored the effects of a nanosecond-pulsed dielectric barrier discharge plasma on neural regeneration. Following mechanical trauma in vitro, plasma was applied either directly to (1) astrocytes alone, (2) neurons alone, or (3) neurons or astrocytes in a non-contact co-culture. Remarkably, we identified NTP treatment intensities that accelerated both neurite regeneration and astrocyte regrowth. In astrocyte cultures alone, an exposure of 20–90 mJ accelerated astrocyte re-growth up to three days post-injury, while neurons required lower treatment intensities (≤20 mJ) to achieve sub-lethal outgrowth. Following injury to neurons in non-contact co-culture with astrocytes, 20 mJ exposure of plasma to only neurons or astrocytes resulted in increased neurite regeneration at three days post-treatment compared to the untreated, but no enhancement was observed when both cell types were treated. At day seven, although regeneration further increased, NTP did not elicit a significant increase from the control. However, plasma exposure at higher intensities was found to be injurious, underscoring the need to optimize exposure levels. These results suggest that growth-promoting physiological responses may be elicited via properly calibrated NTP treatment to neurons and/or astrocytes. This could be exploited to accelerate neurite re-growth and modulate neuron-astrocyte interactions, thereby hastening nervous system regeneration.
A Cloud-Based Real-Time Mechanism to Protect End Hosts against Malware
Authors: Hsu Fu-Hau , Lee Chia-Hao , Luo Ting , Chang Ting-Cheng , Wu Min-Hao
Published: September 2019

Nowadays, antivirus is one of the most popular tools used to protect computer systems. Diverse antivirus vendors are established to protect their customers against malware. However, antivirus is facing some critical problems, such as significant detection windows, vulnerability inside antivirus, and long scanning time. In this paper, we recommend a cloud-based real-time defense mechanism named Skywalker to allow users to safely utilize antivirus without the above problems. After Skywalker is installed in a host, the host does not need to install any antivirus. However, Skywalker guarantees that the host only executes programs that have been verified by a cloud-based scanner, such as VirusTotal. VirusTotal uses 56 antivirus engines to check whether a program is malware. Research shows that the more antivirus engines are used, the more accurate the result is. Because the above scan is performed right before the execution of every program, Skywalker provides 24/7 real-time protection to a system. Besides, Skywalker eliminates the need to spend a lot of time scanning all files in a host. Experimental results show that after a program has been executed once, it takes Skywalker, at most, 0.47091 s to start the program again. Meanwhile, VirusTotal provides a secure protection to client hosts.
All-in-Focused Image Combination in the Frequency Domain Using Light Field Images
Authors: Chantara Wisarut , Jeon Moongu
Published: September 2019

All-in-focused image combination is a fusion technique used to acquire related data from a set of focused images at different depth levels, which suggests that one can determine objects in the foreground and background regions. When attempting to reconstruct an all-in-focused image, we need to identify in-focused regions from multiple input images captured with different focal lengths. This paper presents a new method to find and fuse the in-focused regions of the different focal stack images. After we apply the two-dimensional discrete cosine transform (DCT) to transform the focal stack images into the frequency domain, we utilize the sum of the updated modified Laplacian (SUML), enhancement of the SUML, and harmonic mean (HM) for calculating in-focused regions of the stack images. After fusing all the in-focused information, we transform the result back by using the inverse DCT. Hence, the out-focused parts are removed. Finally, we combine all the in-focused image regions and reconstruct the all-in-focused image.
A Fast Signal Estimation Method Based on Probability Density Functions for Fault Feature Extraction of Rolling Bearings
Authors: Li Shijun , Huang Weiguo , Shi Juanjuan , Jiang Xingxing , Zhu Zhongkui
Published: September 2019

Fault diagnosis of rolling bearings is essential to ensure the efficient and safe operation of mechanical equipment. The extraction of fault features of the repetitive transient component from noisy vibration signals is key to bearing fault diagnosis. However, the bearing fault-induced transients are often submerged by strong background noise and interference. To effectively detect such fault-related transient components, this paper proposes a probability- and statistics-based method. The maximum-a-posteriori (MAP) estimator combined with probability density functions (pdfs) of the repetitive transient component, which is modeled by a mixture of two Laplace pdfs and noise, were used to derive the fast estimation model of the transient component. Subsequently, the LapGauss pdf was adopted to model the noisy coefficients. The parameters of the model derived could then be estimated quickly using the iterative expectation–maximization (EM) algorithm. The main contributions of the proposed statistic-based method are that: (1) transients and their wavelet coefficients are modeled as mixed Laplace pdfs; (2) LapGauss pdf is used to model noisy signals and their wavelet coefficients, facilitating the computation of the proposed method; and (3) computational complexity changes linearly with the size of the dataset and thus contributing to the fast estimation, indicated by analysis of the computational performance of the proposed method. The simulation and experimental vibration signals of faulty bearings were applied to test the effectiveness of the proposed method for fast fault feature extraction. Comparisons of computational complexity between the proposed method and other transient extraction methods were also conducted, showing that the computational complexity of the proposed method is proportional to the size of the dataset, leading to a high computational efficiency.
Design and Analysis of Novel Linear Oscillating Loading System
Authors: Jiao Zongxia , Cao Yuan , Yan Liang , Li Xinglu , Zhang Lu
Published: September 2019

Although linear motor has vital and potential applications in air compressors, hydraulic pumps, earphones and electric vehicles because of its good reliability, high power density and convenient maintenance, most researchers rarely concentrate on the dynamic performance of the linear oscillating motor with external force loads. It is essential to study the dynamic performance of the linear oscillating motor with accurate and multi-mode force loads. In this paper, a novel linear oscillating loading system is proposed and the loading system structure is depicted. Then, a mathematical model is built to match the simulation analyses of the dynamic performance of the linear oscillating motor with multi-mode external force loads. Moreover, the linear oscillating loading system platform is built and experiments are undertaken to verify the simulation analyses about the dynamic performance and efficiency with respect to different external force loads, and the simulation and experimental results show good agreement and will have promising significance for linear oscillating motor research and applications.
The Role of Background Wind and Moisture in the Atmospheric Response to Oceanic Eddies During Winter in the Kuroshio Extension Region
Authors: Jia Yinglai , Chen Longjing , Liu Qinyu , Yang Xiaohui , Wu Yifei
Published: September 2019

The role of background wind and moisture in the atmospheric response to oceanic eddies during winter in the Kuroshio Extension (KE) region is examined by numerical experiments (EXPs) using the Weather Research and Forecasting (WRF) model. We designed two sets of parallel experiments (dry and wet EXPs). The dry EXPs exclude the moisture in the air and the evaporation process. Each experiment differs only in the background wind speed during the initial condition. The wet EXPs include humidity in the initial condition and evaporation during the integration; the other settings are the same as the dry EXPs. The atmosphere in the two sets of EXPs are forced by the same mesoscale sea surface temperature anomaly which resembles the oceanic warm eddy in KE region. The results of these EXPs confirm that under weak background wind conditions, the atmospheric secondary circulation over oceanic eddies is driven by the pressure adjustment process due to weak advection. In the case of the dry run, the increase in background wind enhances the sea surface wind (SSW) by increasing vertical mixing. The convergence of SSW induces vertical motion and heating in the boundary layer, which further decreases the instability. The atmospheric secondary circulation in the dry run remains within the boundary layer. In wet EXPs, the atmospheric response is similar to that in dry runs when the background wind is very weak. When the background wind speed is increased to the climatology value (in KE region) or higher, the vertical motion triggers the precipitation process and diabatic heating above the boundary layer, and the heating in turn reinforces the upward flow.
Regional Inhaled Deposited Dose of Urban Aerosols in an Eastern Mediterranean City
Authors: Hussein Tareq , Saleh Shatha , dos Santos Vanessa , Boor Brandon , Koivisto Antti , Löndahl Jakob
Published: September 2019

We calculated the regional deposited dose of inhaled particulate matter based on number/mass concentrations in Amman, Jordan. The dose rate was the highest during exercising but was generally lower for females compared to males. The fine particles dose rate was 1010–1011 particles/h (101–102 µg/h). The PM10 dose rate was 49–439 µg/h for males and 36–381 µg/h for females. While resting, the PM10 deposited in the head airways was 67–77% and 8–12% in the tracheobronchial region. When exercising, the head airways received 37–44% of the PM10, whereas the tracheobronchial region received 31–35%. About 8% (exercise) and 14–16% (rest) of the PM2.5 was received in the head airways, whereas the alveolar received 74–76% (exercise) and 54–62% (rest). Extending the results for common exposure scenarios in the city revealed alarming results for service workers and police officers; they might receive PM2.5 and 220 µg/h PM10 while doing their duty on main roads adjacent to traffic. This is especially critical for a pregnant police officer. Outdoor athletic activities (e.g., jogging along main roads) are associated with high PM2.5 and PM10 dose rates (100 µg/h and ~425 µg/h, respectively).
Heteroplasmic Variants of Mitochondrial DNA in Atherosclerotic Lesions of Human Aortic Intima
Authors: Sobenin Igor A. , Zhelankin Andrey V. , Khasanova Zukhra B. , Sinyov Vasily V. , Medvedeva Lyudmila V. , Sagaidak Maria O. , Makeev Vsevolod J. , Kolmychkova Kira I. , Smirnova Anna S. , Sukhorukov Vasily N. , Postnov Anton Y. , Grechko Andrey V. , Orekhov Alexander N.
Published: September 2019

Mitochondrial dysfunction and oxidative stress are likely involved in atherogenesis. Since the mitochondrial genome variation can alter functional activity of cells, it is necessary to assess the presence in atherosclerotic lesions of mitochondrial DNA (mtDNA) heteroplasmic mutations known to be associated with different pathological processes and ageing. In this study, mtDNA heteroplasmy and copy number (mtCN) were evaluated in the autopsy-derived samples of aortic intima differing by the type of atherosclerotic lesions. To detect mtDNA heteroplasmic variants, next generation sequencing was used, and mtCN measurement was performed by qPCR. It was shown that mtDNA heteroplasmic mutations are characteristic for particular areas of intimal tissue; in 83 intimal samples 55 heteroplasmic variants were found; mean minor allele frequencies level accounted for 0.09, with 12% mean heteroplasmy level. The mtCN variance measured in adjacent areas of intima was high, but atherosclerotic lesions and unaffected intima did not differ significantly in mtCN values. Basing on the ratio of minor and major nucleotide mtDNA variants, we can conclude that there exists the increase in the number of heteroplasmic mtDNA variants, which corresponds to the extent of atherosclerotic morphologic phenotype.
Comparison of PD-L1 Expression Status between Pure-Solid Versus Part-Solid Lung Adenocarcinomas
Authors: Suda Kenichi , Shimoji Masaki , Shimizu Shigeki , Sato Katsuaki , Chiba Masato , Tomizawa Kenji , Takemoto Toshiki , Soh Junichi , Mitsudomi Tetsuya
Published: September 2019

Although lung adenocarcinomas (LADs) with ground-glass opacity (GGO; part-solid tumors) have been shown to differ from those without GGO (pure-solid tumors) in clinicopathological features and prognoses, whether programmed death ligand-1 (PD-L1) protein expression differs between these two tumor types is unclear. This study included 124 patients with clinical T1a–c LAD who received pulmonary resections during 2007–2009. The E1L3N antibody was used to stain for PD-L1 in primary LAD specimens. The specimens were considered PD-L1+ if ≥1% of tumor cells showed membrane staining, and were classified as having a high PD-L1+ tumor proportion score (TPS) if ≥50% of the tumor cells did so. Among the 124 patients, 45 had part-solid tumors and 79 had pure-solid tumors. These two groups did not significantly differ in terms of clinical factors. However, the rates for PD-L1 positivity (4% vs. 25%, p < 0.01) and high PD-L1+ TPS (2% vs. 16%, p = 0.02) were significantly higher in the pure-solid tumors. The multivariate analyses (logistic regression model) showed that the odds ratios for PD-L1 positivity and high PD-L1+ TPS in pure-solid LADs were 5.9 (95% CI; 1.2–29.7) and 8.0 (95% CI; 1.0–63.8), respectively. In conclusion, LADs with GGO were correlated with a lower incidence of PD-L1 expression than pure-solid tumors.
Inhibition of Rho GTPases in Invertebrate Growth Cones Induces a Switch in Responsiveness to Retinoic Acid
Authors: Johnson Alysha , Nasser Tamara I. N. , Spencer Gaynor E.
Published: September 2019

During development, growth cones are essential for axon pathfinding by sensing numerous guidance cues in their environment. Retinoic acid, the metabolite of vitamin A, is important for neurite outgrowth during vertebrate development, but may also play a role in axon guidance, though little is known of the cellular mechanisms involved. Our previous studies showed that retinoid-induced growth cone turning of invertebrate motorneurons requires local protein synthesis and calcium influx. However, the signalling pathways that link calcium influx to cytoskeletal dynamics involved in retinoid-mediated growth cone turning are not currently known. The Rho GTPases, Cdc42 and Rac, are known regulators of the growth cone cytoskeleton. Here, we demonstrated that inhibition of Cdc42 or Rac not only prevented growth cone turning toward retinoic acid but could also induce a switch in growth cone responsiveness to chemorepulsion or growth cone collapse. However, the effects of Cdc42 or Rac inhibition on growth cone responsiveness differed, depending on whether the turning was induced by the all-trans or 9-cis retinoid isomer. The effects also differed depending on whether the growth cones maintained communication with the cell body. These data strongly suggest that Cdc42 and Rac are downstream effectors of retinoic acid during growth cone guidance.