bluuebunny/crossref_metadata_2025 huggingface dataset:
IMPLEMENTASI KEBIJAKAN USAHA PERIKANAN MELALUI PROGRAM PENGEMBANGAN PERIKANAN TANGKAP DI KOTA TANJUNGPINANG PROVINSI KEPULAUAN RIAU
Authors: Malik Hilman , Saribulan Nur
Published: June 2020

ABSTRACTThis research aims to understand and describe the implementation of the policy efforts of fisheries through the catch fisheries development program in Tanjungpinang city. Knowing the supporting factors and obstacles and efforts made by the government to overcome the obstacles. This research is carried out by qualitative approach with data collection techniques are observation, interview and documentation. Determination of informants using purposive and snowball sampling. The theory used is a model of policy implementation according by Van Meter and Van Horn. The results of this research show that implementation of the policy efforts of fisheries through the catch fisheries development program in Tanjungpinang city has been well established dueto the low fisherman mindset, budget constraints, lack of coordination in the implementation of the program, the presence of persons or private beneficiaries, the limitations of the use fishing gear and catching areas with the regulation implication of the Minister of Marine and Fishery Number 2 of 2015, the unavailability of fish shelters for the fisherman and the existance of local fisherman competition to fisherman from outside the region.

Keywords: implementation, efforts of fisheries, catch fisheries development program.
The Determinants of Purchasing Decisions: The Case of Snack Products
Authors: Paramita Eristia Lidia , Sanjaya Wahyuni Ratna
Published: June 2020

Parents’ decisions to buy snacks are likely influenced by packaging designs, the colors of the snack packagings, and their children. Children are unique influencers because they cannot afford to buy snacks they desire, but they can influence and even direct their parents to buy the desired snacks. In this article, I investigate how snack packaging designs and colors attract consumers’ attention and affect their purchasing decisions. In particular, this study seeks to analyze the effects of snack packaging design and snack packaging color on parents’ purchasing decisions. The data was generated by using questionnaires that asked 90 parents who have children aged 4-7 years old. Findings. The Study demonstrate that snack packaging designs and colors affect parents’ purchasing decisions.
ANALISIS RASIO LIKUIDITAS, PROFITABILITAS, SOLVABILITAS DAN PERPUTARAN PERSEDIAAN UNTUK MENILAI KINERJA PERUSAHAAN RETAIL YANG TERDAFTAR DI BEI
Authors: Sembiring Masta
Published: June 2020

Measurement of a company's performance can be seen from financial ratio or stock returns. This study aims to know whether liquidity, profitability, solvency, and inventory turnover have an effect after being analyzed on the performance of company on companies listed on Indonesia Stock Exchange. The variables used are Current Ratio, Return on Investment, Debt to Asset Ratio, Inventory Turnover to Net Profit Margin. The population in this study consisted of 148 companies in retail trade, service and investment group that were listed on the Indonesia Stock Exchange. The sample chosen by purposive sampling was chosen to be 17 companies listed on Indonesia Stock Exchange during 2014 to 2017. Data collection techniques used were documentation techniques. Data processing technique used is data processing with SPSS version 21. Data analysis method used is multiple linear regression method. Results of the T test show that partially Current Ratio, Debt to Asset Ratio, and inventory turnover have a negative and significant effect on company performance, while Return On Investment has a positive and significant influence on company performance. The results of the F test analysis  indicate that the variable Liquidity Ratio, Profitability, Solvability and Inventory Turnover together have a significant effect on company performance.
Multi-Fidelity Design Optimization of a Long-Range Blended Wing Body Aircraft with New Airframe Technologies
Authors: Karpuk Stanislav , Liu Yaolong , Elham Ali
Published: June 2020

The German Cluster of Excellence SE²A (Sustainable and Energy Efficient Aviation) is established in order to investigate the influence of game-changing technologies on the energy efficiency of future transport aircraft. In this paper, the preliminary investigation of the four game-changing technologies active flow control, active load alleviation, boundary layer ingestion, and novel materials and structure concepts on the performance of a long-range Blended Wing Body (BWB) aircraft is presented. The BWB that was equipped with the mentioned technologies was designed and optimized using the multi-fidelity aircraft design code SUAVE with a connection to the Computational Fluid Dynamics (CFD) code SU2. The conceptual design of the BWB aircraft is performed within the SUAVE framework, where the influence of the new technologies is investigated. In the second step, the initially designed BWB aircraft is improved by an aerodynamic shape optimization while using the SU2 CFD code. In the third step, the performance of the optimized aircraft is evaluated again using the SUAVE code. The results showed more than 60% reduction in the aircraft fuel burn when compared to the Boeing 777.
Honey Extracts Exhibit Cytoprotective Properties against UVB-Induced Photodamage in Human Experimental Skin Models
Authors: Karapetsas Athanasios , Voulgaridou Georgia-Persephoni , Iliadi Dimitra , Tsochantaridis Ilias , Michail Panagiota , Kynigopoulos Spyridon , Lambropoulou Maria , Stavropoulou Maria-Ioanna , Stathopoulou Konstantina , Karabournioti Sofia , Aligiannis Nektarios , Gardikis Konstantinos , Galanis Alex , Panayiotidis Mihalis I. , Pappa Aglaia
Published: June 2020

In the present study, we aimed to examine the antioxidant, antiaging and photoprotective properties of Greek honey samples of various botanical and geographical origin. Ethyl-acetate extracts were used and the and the total phenolic/flavonoid content and antioxidant capacity were evaluated. Honey extracts were then studied for their cytoprotective properties against UVB-induced photodamage using human immortalized keratinocytes (HaCaT) and/or reconstituted human skin tissue models. Specifically, the cytotoxicity, oxidative status, DNA damage and gene expression levels of specific matrix metalloproteinases (MMPs) were examined. Overall, the treatment of HaCaT cells with honey extracts resulted in lower levels of DNA strand breaks and attenuated the decrease in cell viability following UVB exposure. Additionally, honey extracts significantly decreased the total protein carbonyl content of the irradiated cells, however, they had no significant effect on their total antioxidant status. Finally, the extracts alleviated the UVB-induced up-regulation of MMPs-3, -7 and -9 in a model of reconstituted skin tissue. In conclusion, honey extracts exhibited significant photoprotective and antiaging properties under UVB exposure conditions and thus could be further exploited as promising agents for developing novel and naturally-based, antiaging cosmeceutical products.
Towards a Better Understanding of Transfer Learning for Medical Imaging: A Case Study
Authors: Alzubaidi Laith , Fadhel Mohammed A. , Al-Shamma Omran , Zhang Jinglan , Santamaría J. , Duan Ye , R. Oleiwi Sameer
Published: June 2020

One of the main challenges of employing deep learning models in the field of medicine is a lack of training data due to difficulty in collecting and labeling data, which needs to be performed by experts. To overcome this drawback, transfer learning (TL) has been utilized to solve several medical imaging tasks using pre-trained state-of-the-art models from the ImageNet dataset. However, there are primary divergences in data features, sizes, and task characteristics between the natural image classification and the targeted medical imaging tasks. Therefore, TL can slightly improve performance if the source domain is completely different from the target domain. In this paper, we explore the benefit of TL from the same and different domains of the target tasks. To do so, we designed a deep convolutional neural network (DCNN) model that integrates three ideas including traditional and parallel convolutional layers and residual connections along with global average pooling. We trained the proposed model against several scenarios. We utilized the same and different domain TL with the diabetic foot ulcer (DFU) classification task and with the animal classification task. We have empirically shown that the source of TL from the same domain can significantly improve the performance considering a reduced number of images in the same domain of the target dataset. The proposed model with the DFU dataset achieved F1-score value of 86.6% when trained from scratch, 89.4% with TL from a different domain of the targeted dataset, and 97.6% with TL from the same domain of the targeted dataset.
LEED-CI V3 and V4 Silver and Gold Projects in China and the U.S.
Authors: Pushkar Svetlana
Published: June 2020

Leadership in Energy and Environmental Design Commercial Interiors (LEED-CI) versions 4 (v4) and 3 (v3) Silver and Gold projects have been widely used in both the U.S. and China. This study aimed to compare the LEED-CI-Silver and LEED-CI-Gold v3 and v4 in China and the U.S. The design of the study comprised two stages: (1) to identify all LEED-CIv4 projects in China and the U.S. at the Silver and Gold levels for 2014–2019; and (2) to collect the same number of LEED-CIv3 projects for each certification level from the same cities of China and from the same states of the U.S. at the same times, if possible. Cliff’s δ or the log odds ratio effect size was used to evaluate the difference between the achieved and the possible points, and the difference between the Silver and Gold projects in China and the U.S. The results show that, in the Silver-to-Gold transition, in China, the water–energy–site–human health saving strategy was used, while in the U.S., only the water–energy saving strategy was used.
Effects of Plyometric Training on Surface Electromyographic Activity and Performance during Blocking Jumps in College Division I Men’s Volleyball Athletes
Authors: Wang Min-Hsien , Chen Ke-Chou , Hung Min-Hao , Chang Chi-Yao , Ho Chin-Shan , Chang Chun-Hao , Lin Kuo-Chuan
Published: June 2020

In volleyball matches, there are three minute intervals between sets. Therefore, the improvement of the muscle output ratio is one of the most import foundational physical elements for the players. The purpose of this study was to investigate the effects of plyometric training on the changes in electrical signals in the lower limb muscles of male college volleyball players during continuous blocking and to examine the benefits of plyometric training on blocking agility and maximum vertical jump height. In this study, twenty elite male college volleyball players were recruited and divided into a plyometric training group (PTG) and a control group (CG). The wireless electromyography was used for data acquisition, and the electrodes were applied to the left and right rectus femoris, biceps femoris, tibialis anterior, and gastrocnemius. The median frequency was used as the measurement of the electromyographic signals during the jumping blocks. This study used covariate analysis methods, with previously measured results used as covariates to perform a two-way analysis of covariance for the independent samples. Based on the results of this study, after 6 weeks of training, the median frequency of the rectus femoris (2.13% to 4.75% improved) and that of the tibialis anterior muscles (4.14% to 7.71% improved) were significantly lower in the PTG than in the CG. Additionally, the blocking agility increased by 6.26% and the maximum vertical jump height increased by 3.33% in the PTG compared to the CG. The findings provide important insights on the neuromuscular status for volleyball players during continuous blocking jumps. Six weeks of appropriate plyometric training can facilitate the performance of volleyball players.
Chatter and Stability Analysis of the Slender Composite Boring Bar with Constrained Damping Layer
Authors: Zhang Jinfeng , Wang Hao , Ren Yongsheng , Feng Chao , Zhang Chunjin
Published: June 2020

This study investigates the chattering stability of the composite boring bar with a constrained damping layer during the deep-hole boring process in depth. Based on the Euler-Bernoulli beam theory, the regenerative chattering linear kinetic model of the composite boring bar with a constrained damping layer was established, and the computational formulas of the rotating speed of the spindle and the corresponding limit cutting depth were derived. By analyzing the chattering stability, the cutting stability lobe curves of the composite boring bar with a constrained damping layer were plotted so as to reveal the effects of the materials of both base layer and constrained layer, the ply angle, the damping composite structure (free or constrained damping structure) and the thickness of various layers on the chattering stability of the boring bar. Through the analysis of dynamic stiffness, the chatter stability analysis theory of a composite boring bar with a constrained damping layer is verified.
Text Normalization Using Encoder–Decoder Networks Based on the Causal Feature Extractor
Authors: Javaloy Adrián , García-Mateos Ginés
Published: June 2020

The encoder–decoder architecture is a well-established, effective and widely used approach in many tasks of natural language processing (NLP), among other domains. It consists of two closely-collaborating components: An encoder that transforms the input into an intermediate form, and a decoder producing the output. This paper proposes a new method for the encoder, named Causal Feature Extractor (CFE), based on three main ideas: Causal convolutions, dilatations and bidirectionality. We apply this method to text normalization, which is a ubiquitous problem that appears as the first step of many text-to-speech (TTS) systems. Given a text with symbols, the problem consists in writing the text exactly as it should be read by the TTS system. We make use of an attention-based encoder–decoder architecture using a fine-grained character-level approach rather than the usual word-level one. The proposed CFE is compared to other common encoders, such as convolutional neural networks (CNN) and long-short term memories (LSTM). Experimental results show the feasibility of CFE, achieving better results in terms of accuracy, number of parameters, convergence time, and use of an attention mechanism based on attention matrices. The obtained accuracy ranges from 83.5% to 96.8% correctly normalized sentences, depending on the dataset. Moreover, the proposed method is generic and can be applied to different types of input such as text, audio and images.
Investigation of the Influence of Liquid Motion in a Flow-based System on an Enzyme Aggregation State with an Atomic Force Microscopy Sensor: The Effect of Water Flow
Authors: Ivanov Yuri D. , Pleshakova Tatyana O. , Shumov Ivan D. , Kozlov Andrey F. , Romanova Tatyana S. , Valueva Anastasia A. , Tatur Vadim Yu. , Stepanov Igor N. , Ziborov Vadim S.
Published: June 2020

The influence of liquid motion in flow-based systems on the aggregation state of an enzyme and on its enzymatic activity was studied, with horseradish peroxidase (HRP) as an example. Our experiments were carried out in a setup modeling the flow section of the biosensor communication with a measuring cell containing a protein solution. Studies were conducted for a biosensor measuring cell located along the axis of a spiral-moving liquid flow. The aggregation state of the protein was determined with an atomic force microscopy-based sensor (AFM sensor). It has been demonstrated that upon flowing of water through silicone biosensor communications, an increased aggregation of HRP protein was observed, but, at the same time, its enzymatic activity did not change. Our results obtained herein are useful in the development of models describing the influence of liquid flow in biosensor communications on the properties of enzymes and other proteins. This is particularly important for the development of serologic protein biosensors, which are beginning to be used for the early diagnosis of oncological diseases (such as brain cancer, prostate cancer, breast cancer etc.). The results obtained herein should also be taken into account when considering possible changes in hemodynamics due to increased protein aggregation.
Microwave Assisted Surfactant-Thermal Synthesis of Metal-Organic Framework Materials
Authors: Forsyth Cory , Taras Tyler , Johnson Adam , Zagari Jessica , Collado Crystal , Hoffmann Markus M. , Reed Carly R.
Published: June 2020

This research explores the application of surfactants as green solvents for the rapid microwave synthesis of metal-organic framework (MOF) materials. Lead, copper, and iron metal-organic framework materials were synthesized using surfactant-thermal microwave synthesis. The MOF materials were characterized by powder X-ray diffraction, infrared spectroscopy, scanning electron microscopy, and thermogravimetric analysis. With the exception of the iron MOF, which was expected to be amorphous, the MOF materials are crystalline, though generally exhibiting smaller crystals than those achieved with traditional solvothermal synthesis. This green synthetic method reduced synthesis time and reduced the use of traditional organic solvents as the reaction media.
Applying Statistical Analysis and Machine Learning for Modeling the UCS from P-Wave Velocity, Density and Porosity on Dry Travertine
Authors: Saldaña Manuel , González Javier , Pérez-Rey Ignacio , Jeldres Matías , Toro Norman
Published: June 2020

In the rock mechanics and rock engineering field, the strength parameter considered to characterize the rock is the uniaxial compressive strength (UCS). It is usually determined in the laboratory through a few statistically representative numbers of specimens, with a recommended minimum of five. The UCS can also be estimated from rock index properties, such as the effective porosity, density, and P-wave velocity. In the case of a porous rock such as travertine, the random distribution of voids inside the test specimen (not detectable in the density-porosity test, but in the compressive strength test) causes large variations on the UCS value, which were found in the range of 62 MPa for this rock. This fact complicates a sufficiently accurate determination of experimental results, also affecting the estimations based on regression analyses. Aiming to solve this problem, statistical analysis, and machine learning models (artificial neural network) was developed to generate a reliable predictive model, through which the best results for a multiple regression model between uniaxial compressive strength (UCS), P-wave velocity and porosity were obtained.
Automated Assessment and Microlearning Units as Predictors of At-Risk Students and Students’ Outcomes in the Introductory Programming Courses
Authors: Skalka Jan , Drlik Martin
Published: June 2020

The number of students who decided to study information technology related study programs is continually increasing. Introductory programming courses represent the most crucial milestone in information technology education and often reflect students’ ability to think abstractly and systematically, solve problems, and design their solutions. Even though many students who attend universities have already completed some introductory courses of programming, there is still a large group of students with limited programming skills. This drawback often increases during the first term, and it is often the main reason why students leave study too early. There is a myriad of technologies and tools which can be involved in the programming course to increase students’ chances of mastering programming. The introductory programming courses used in this study has been gradually extended over the four academic years with the automated source code assessment of students’ programming assignments followed by the implementation of a set of suitably designed microlearning units. The final four datasets were analysed to confirm the suitability of automated assessment and microlearning units as predictors of at-risk students and students’ outcomes in the introductory programming courses. The research results proved the significant contribution of automated code assessment in students’ learning outcomes in the elementary topics of learning programming. Simultaneously, it proved a moderate to strong dependence between the students’ activity and achievement in the activities and final students’ outcomes.
A Smartphone-Based Cell Segmentation to Support Nasal Cytology
Authors: Dimauro Giovanni , Di Pierro Davide , Deperte Francesca , Simone Lorenzo , Fina Pio Raffaele
Published: June 2020

Rhinology studies the anatomy, physiology, and diseases affecting the nasal region—one of the most modern techniques to diagnose these diseases is nasal cytology, which involves microscopic analysis of the cells contained in the nasal mucosa. The standard clinical protocol regulates the compilation of the rhino-cytogram by observing, for each slide, at least 50 fields under an optical microscope to evaluate the cell population and search for cells important for diagnosis. The time and effort required for the specialist to analyze a slide are significant. In this paper, we present a smartphones-based system to support cell segmentation on images acquired directly from the microscope. Then, the specialist can analyze the cells and the other elements extracted directly or, alternatively, he can send them to Rhino-cyt, a server system recently presented in the literature, that also performs the automatic cell classification, giving back the final rhinocytogram. This way he significantly reduces the time for diagnosing. The system crops cells with sensitivity = 0.96, which is satisfactory because it shows that cells are not overlooked as false negatives are few, and therefore largely sufficient to support the specialist effectively. The use of traditional image processing techniques to preprocess the images also makes the process sustainable from the computational point of view for medium–low end architectures and is battery-efficient on a mobile phone.
Structural Insights into the Evolutionarily Conserved BAF Chromatin Remodeling Complex
Authors: Marcum Ryan D. , Reyes Alexis A. , He Yuan
Published: June 2020

The switch/sucrose nonfermentable (SWI/SNF) family of proteins acts to regulate chromatin accessibility and plays an essential role in multiple cellular processes. A high frequency of mutations has been found in SWI/SNF family subunits by exome sequencing in human cancer, and multiple studies support its role in tumor suppression. Recent structural studies of yeast SWI/SNF and its human homolog, BAF (BRG1/BRM associated factor), have provided a model for their complex assembly and their interaction with nucleosomal substrates, revealing the molecular function of individual subunits as well as the potential impact of cancer-associated mutations on the remodeling function. Here we review the structural conservation between yeast SWI/SNF and BAF and examine the role of highly mutated subunits within the BAF complex.
Encapsulins—Bacterial Protein Nanocompartments: Structure, Properties, and Application
Authors: Gabashvili Anna N. , Chmelyuk Nelly S. , Efremova Maria V. , Malinovskaya Julia A. , Semkina Alevtina S. , Abakumov Maxim A.
Published: June 2020

Recently, a new class of prokaryotic compartments, collectively called encapsulins or protein nanocompartments, has been discovered. The shell proteins of these structures self-organize to form icosahedral compartments with a diameter of 25–42 nm, while one or more cargo proteins with various functions can be encapsulated in the nanocompartment. Non-native cargo proteins can be loaded into nanocompartments and the surface of the shells can be further functionalized, which allows for developing targeted drug delivery systems or using encapsulins as contrast agents for magnetic resonance imaging. Since the genes encoding encapsulins can be integrated into the cell genome, encapsulins are attractive for investigation in various scientific fields, including biomedicine and nanotechnology.
Evaluation of Resin-Based Material Containing Copaiba Oleoresin (Copaifera Reticulata Ducke): Biological Effects on the Human Dental Pulp Stem Cells
Authors: Couto Roberta Souza D’Almeida , Rodrigues Maria Fernanda Setubal Destro , Ferreira Leila Soares , Diniz Ivana Márcia Alves , Silva Fernando de Sá , Lopez Talita Christine Camilo , Lima Rafael Rodrigues , Marques Márcia Martins
Published: June 2020

The purpose of this study was to analyze in vitro the biological effects on human dental pulp stem cells triggered in response to substances leached or dissolved from two experimental cements for dental pulp capping. The experimental materials, based on extracts from Copaifera reticulata Ducke (COP), were compared to calcium hydroxide [Ca(OH)2] and mineral trioxide aggregate (MTA), materials commonly used for direct dental pulp capping in restorative dentistry. For this, human dental pulp stem cells were exposed to COP associated or not with Ca(OH)2 or MTA. Cell cytocompatibility, migration, and differentiation (mineralized nodule formation (Alizarin red assay) and gene expression (RT-qPCR) of OCN, DSPP, and HSP-27 (genes regulated in biomineralization events)) were evaluated. The results showed that the association of COP reduced the cytotoxicity of Ca(OH)2. Upregulations of the OCN, DSPP, and HSP-27 genes were observed in response to the association of COP to MTA, and the DSPP and HSP-27 genes were upregulated in the Ca(OH)2 + COP group. In up to 24 h, cell migration was significantly enhanced in the MTA + COP and Ca(OH)2 + COP groups. In conclusion, the combination of COP with the currently used materials for dental pulp capping [Ca(OH)2 and MTA] improved the cell activities related to pulp repair (i.e., cytocompatibility, differentiation, mineralization, and migration) including a protective effect against the cytotoxicity of Ca(OH)2.
Mesothelin-Targeted Recombinant Immunotoxins for Solid Tumors
Authors: Hagerty Brendan L. , Pegna Guillaume J. , Xu Jian , Tai Chin-Hsien , Alewine Christine
Published: June 2020

Mesothelin (MSLN) is a cell surface glycoprotein normally expressed only on serosal surfaces, and not found in the parenchyma of vital organs. Many solid tumors also express MSLN, including mesothelioma and pancreatic adenocarcinoma. Due to this favorable expression profile, MSLN represents a viable target for directed anti-neoplastic therapies, such as recombinant immunotoxins (iToxs). Pre-clinical testing of MSLN-targeted iTox’s has yielded a strong body of evidence for activity against a number of solid tumors. This has led to multiple clinical trials, testing the safety and efficacy of the clinical leads SS1P and LMB-100. While promising clinical results have been observed, neutralizing anti-drug antibody (ADA) formation presents a major challenge to overcome in the therapeutic development process. Additionally, on-target, off-tumor toxicity from serositis and non-specific capillary leak syndrome (CLS) also limits the dose, and therefore, impact anti-tumor activity. This review summarizes existing pre-clinical and clinical data on MSLN-targeted iTox’s. In addition, we address the potential future directions of research to enhance the activity of these anti-tumor agents.
Unveiling the Mechanism of Action of 7α-acetoxy-6β-hydroxyroyleanone on an MRSA/VISA Strain: Membrane and Cell Wall Interactions
Authors: Pereira Filipe , Figueiredo Teresa , de Almeida Rodrigo F. M. , Antunes Catarina A. C. , Garcia Catarina , Reis Catarina P. , Ascensão Lia , Sobral Rita G. , Rijo Patricia
Published: June 2020

The number of cases of failure in the treatment of infections associated with resistant bacteria is on the rise, due to the decreasing efficacy of current antibiotics. Notably, 7α-Acetoxy-6β-hydroxyroyleanone (AHR), a diterpene isolated from different Plectranthus species, showed antibacterial activity, namely against Methicillin-resistant Staphylococcus aureus (MRSA) strains. The high antibacterial activity and low cytotoxicity render this natural compound an interesting alternative against resistant bacteria. The aim of this study is to understand the mechanism of action of AHR on MRSA, using the MRSA/Vancomycin-intermediate S. aureus (VISA) strain CIP 106760, and to study the AHR effect on lipid bilayers and on the cell wall. Although AHR interacted with lipid bilayers, it did not have a significant effect on membrane passive permeability. Alternatively, bacteria treated with this royleanone displayed cell wall disruption, without revealing cell lysis. In conclusion, the results gathered so far point to a yet undescribed mode of action that needs further investigation.
Kynurenines in the Pathogenesis of Multiple Sclerosis: Therapeutic Perspectives
Authors: Biernacki Tamás , Sandi Dániel , Bencsik Krisztina , Vécsei László
Published: June 2020

Over the past years, an increasing amount of evidence has emerged in support of the kynurenine pathway’s (KP) pivotal role in the pathogenesis of several neurodegenerative, psychiatric, vascular and autoimmune diseases. Different neuroactive metabolites of the KP are known to exert opposite effects on neurons, some being neuroprotective (e.g., picolinic acid, kynurenic acid, and the cofactor nicotinamide adenine dinucleotide), while others are toxic to neurons (e.g., 3-hydroxykynurenine, quinolinic acid). Not only the alterations in the levels of the metabolites but also disturbances in their ratio (quinolinic acid/kynurenic acid) have been reported in several diseases. In addition to the metabolites, the enzymes participating in the KP have been unearthed to be involved in modulation of the immune system, the energetic upkeep of neurons and have been shown to influence redox processes and inflammatory cascades, revealing a sophisticated, intertwined system. This review considers various methods through which enzymes and metabolites of the kynurenine pathway influence the immune system, the roles they play in the pathogenesis of neuroinflammatory diseases based on current evidence with a focus on their involvement in multiple sclerosis, as well as therapeutic approaches.
Clinical and Histopathological Features and Potential Pathological Mechanisms of Skin Lesions in COVID-19: Review of the Literature
Authors: Kaya Gürkan , Kaya Aysin , Saurat Jean-Hilaire
Published: June 2020

In recent weeks, several reports have emerged of skin lesions with different clinical presentations in COVID-19 cases. All dermatologists should be aware of these cutaneous lesions, which may be early clinical symptoms of infection. We reviewed the literature on cutaneous manifestations in the PubMed database from December 2019 and June 2020. From the cases described as case reports or series in 57 recent articles, it appears that skin lesions (i) are highly varied, (ii) may not be related to the severity of the condition and (iii) resolve spontaneously in a few days. The frequency of these lesions in COVID-19 patients varies between 1.8% and 20.4%. The major clinical forms described were maculopapular eruptions, acral areas of erythema with vesicles or pustules (pseudochilblain), urticarial lesions, other vesicular eruptions and livedo or necrosis. The lesions were mainly localized in the trunk and extremities. The majority of patients were male, aged between 4.5 and 89 years. A minority of the patients were children presenting with acral, chilblain-like lesions, papulo-vesicular eruptions or Kawasaki disease-like pediatric inflammatory multisystem syndrome. The mean duration of the lesions was a few days, but some lasting as little as 20 min and others as long as four weeks have been reported. The mean latency time in the majority of cases was between 1 and 14 days; however, in some patients, lesions appeared 2 to 5 days before the onset of COVID-19 symptoms. The histopathological features of these lesions also vary, corresponding to the diversity of clinical manifestations. These features underline the nature of epidermal and dermal vascular lesions—and in severe cases, microvascular injury and thrombosis—associated with COVID-19, and provide important clues to their pathological mechanisms.
A Measurement Model of Mutual Influence for Information Dissemination
Authors: Zhang Liang , Quan Yong , Zhou Bin , Jia Yan , Gao Liqun
Published: June 2020

The recent development of the mobile Internet and the rise of social media have significantly enriched the way people access information. Accurate modeling of the probability of information propagation between users is essential for studying information dissemination issues in social networks. As the dissemination of information is inseparable from the interactions between users, the probability of propagation can be characterized by such interactions. In general, there are differences in the dissemination modes of information that carry different topics in a real social network. Using these factors, we propose a method (TMIVM) to measure the mutual influence between users at the topic level. The method associates two vectorization parameters for each user—an influence vector and a susceptibility vector—where the dimensions of the vector represent different topic categories. The magnitude of the mutual influence between users on different topics can be obtained by the product of the corresponding elements of the vectors. Specifically, in this article, we fit a social network historical information cascade data through Survival Analysis to learn the parameters of the influence and susceptibility vectors. The experimental results on a synthetic data set and a real Microblog data set show that this method better measures the propagation probability and information cascade predictions compared to other methods.
Natural Time Analysis of Seismicity within the Mexican Flat Slab before the M7.1 Earthquake on 19 September 2017
Authors: Flores-Márquez E. Leticia , Ramírez-Rojas Alejandro , Perez-Oregon Jennifer , Sarlis N. V. , Skordas E. S. , Varotsos P. A.
Published: June 2020

One of the most important subduction zones in the world is located in the Mexican Pacific Coast, where the Cocos plate inserts beneath the North American plate. One part of it is located in the Mexican Pacific Coast, where the Cocos plate inserts beneath the North American plate with different dip angles, showing important seismicity. Under the central Mexican area, such a dip angle becomes practically horizontal and such an area is known as flat slab. An earthquake of magnitude M7.1 occurred on 19 September 2017, the epicenter of which was located in this flat slab. It caused important human and material losses of urban communities including a large area of Mexico City. The seismicity recorded in the flat slab region is analyzed here in natural time from 1995 until the occurrence of this M7.1 earthquake in 2017 by studying the entropy change under time reversal and the variability β of the order parameter of seismicity as well as characterize the risk of an impending earthquake by applying the nowcasting method. The entropy change ΔS under time reversal minimizes on 21 June 2017 that is almost one week after the observation of such a minimum in the Chiapas region where a magnitude M8.2 earthquake took place on 7 September 2017 being Mexico’s largest quake in more than a century. A minimum of β was also observed during the period February–March 2017. Moreover, we show that, after the minimum of ΔS, the order parameter of seismicity starts diminishing, thus approaching gradually the critical value 0.070 around the end of August and the beginning of September 2017, which signals that a strong earthquake is anticipated shortly in the flat slab.
Research on Stability Design of Differential Drive Fork-Type AGV Based on PID Control
Authors: Wang Tingting , Dong Ruoyan , Zhang Rui , Qin Dongchen
Published: June 2020

As one of the important components of intelligent warehousing logistics, Automated Guided Vehicles (AGVs) have greatly improved the efficiency of warehousing operations. AGVs are responsible for the delivery of goods in warehousing and logistics, and it is extremely important to maintain a stable running state. In this paper, an AGV in-situ steering dynamic model is established according to the actual size, and the center deviation phenomenon during AGV steering is theoretically analyzed to obtain the parameters that affect the AGV’s in-situ steering stability. Secondly, the dynamic simulation method is used to analyze the law of the stability of the AGV in-situ steering parameters to verify the correctness of the theoretical derivation equation. According to the analysis results, the motion parameters related to AGV in-situ steering are analyzed, and a reasonable design scheme is given. Based on the optimized fork-type AGV, the AGV in-situ steering control strategy is studied, and the adaptive fuzzy PID control algorithm is used to construct the fork-type AGV steering control system. Then the software and hardware design of the AGV steering control system is carried out. The optimized fork-type AGV has been turned to work stably after commissioning, meeting the actual work requirements.
Optimized Adaptive Overcurrent Protection Using Hybridized Nature-Inspired Algorithm and Clustering in Microgrids
Authors: Senarathna Thiramuni Sisitha Sameera , Hemapala Kullappu Thantrige Manjula Udayanga
Published: June 2020

Microgrids have been popularized in the past decade because of their ability to add distributed generation into the classic distribution systems. Protection problems are among several other problems that need solutions in order to extract the full capability of these novel networks. This research follows the branches of two major solutions, namely adaptive protection and protection optimization. Adaptive protection implementation with a novel concept of clustering is considered, and protection setting optimization is done using a novel hybrid nature-inspired algorithm. Adaptive protection is utilized to cope with the topology variations, while optimization techniques are used to calculate the protection settings that provide faster fault clearances in coordination with backup protection. A modified IEEE 14 bus system is used as the test system. Validation was done for the fault clearing performance. The selected algorithm was effective than most other algorithms, and the clustering approach for adaptive overcurrent protection was able to reduce the number of relays’ setting groups.
Influence of Innovative Woodchipper Speed Control Systems on Exhaust Gas Emissions and Fuel Consumption in Urban Areas
Authors: Warguła Łukasz , Kukla Mateusz , Lijewski Piotr , Dobrzyński Michał , Markiewicz Filip
Published: June 2020

This paper discusses the determination of fuel consumption and exhaust gas emissions when shredding branches in urban areas. It aimed to determine the hourly emission of exhaust gases to the atmosphere during such work and to identify the designs that can reduce it. The research was carried out with a cylinder woodchipper driven by a low-power (9.5 kW) combustion engine. There were three configurations of the tested drive unit: The factory setting (A) with a carburettor fuel supply system, modernized by us to include an electronic injection system (B). This system (B) was expanded with an adaptation system patented by the authors (P. 423369), thus creating the third configuration (C). The research was carried out when shredding cherry plum (Prunus cerasifera Ehrh. Beitr. Naturk. 4:17. 1789 (Gartenkalender 4:189-204. 1784)) branches with a diameter of 80 mm, which presented a large load for the machine. The machine was operated by one experienced operator. The average operating conditions during the tests were as follows: Branch delivery frequency of about 4 min−1 and mass flow rate of about 0.72 t h−1. During the tests with the use of PEMS (portable emissions measurement system, here Axion RS from Global MRV), we analyzed the emissions of compounds, such as CO, CO2, HC, and NOx, and determined the fuel consumption based on the carbon balance. The research showed that the use of an injection system (B) reduced fuel consumption from 1.38 to 1.29 l h−1 (by 6.7%) when compared to the carburettor system (A). Modernization of the injection system (B) with an adaptive system (C) reduced fuel consumption from 1.38 to 0.91 l h−1 (by 34%) when compared to the carburettor system (A). An hour of shredding with a cylinder chopper emits the following amounts of flue gases: design A (HC 0.013 kg h−1; CO 0.24 kg h−1; CO2 2.91 kg h−1; NOx 0.0036 kg h−1), design B (HC 0.0061 kg h−1; CO 0.20 kg h−1; CO2 2.77 kg h−1; NOx 0.0038 kg h−1), and design C (HC 0.017 kg h−1; CO 0.22 kg h−1; CO2 1.79 kg h−1; NOx 0.0030 kg h−1). The adaptive system entails significant reductions in non-HC emissions, which indicates that the system needs to be improved with respect to fuel-air mixture control for its enrichment of the low-to-high-speed change. The admissible emission limits for harmful compounds in exhaust gas for the tested group of propulsion units are in accordance with the provisions in force in the European Union from 2019 for the tested propulsion units during operation, with a full CO load about 6100 g h−1 and HC + NOx about 80 g h−1. The tested propulsion units emitted significantly less pollution under real operating conditions (because they did not work under full load throughout the entire test sample).
Crystallization of Amorphous Silicon via Excimer Laser Annealing and Evaluation of Its Passivation Properties
Authors: Chowdhury Sanchari , Park Jinsu , Kim Jaemin , Kim Sehyeon , Kim Youngkuk , Cho Eun-Chel , Cho Younghyun , Yi Junsin
Published: June 2020

The crystallization of hydrogenated amorphous silicon (a-Si:H) is essential for improving solar cell efficiency. In this study, we analyzed the crystallization of a-Si:H via excimer laser annealing (ELA) and compared this process with conventional thermal annealing. ELA prevents thermal damage to the substrate while maintaining the melting point temperature. Here, we used xenon monochloride (XeCl), krypton fluoride (KrF), and deep ultra-violet (UV) lasers with wavelengths of 308, 248, and 266 nm, respectively. Laser energy densities and shot counts were varied during ELA for a-Si:H films between 20 and 80 nm thick. All the samples were subjected to forming gas annealing to eliminate the dangling bonds in the film. The ELA samples were compared with samples subjected to thermal annealing performed at 850–950 °C for a-Si:H films of the same thickness. The crystallinity obtained via deep UV laser annealing was similar to that obtained using conventional thermal annealing. The optimal passivation property was achieved when crystallizing a 20 nm thick a-Si:H layer using the XeCl excimer laser at an energy density of 430 mJ/cm2. Thus, deep UV laser annealing exhibits potential for the crystallization of a-Si:H films for TOPCon cell fabrication, as compared to conventional thermal annealing.
Design Synchronous Generator Using Taguchi-Based Multi-Objective Optimization
Authors: Li Ruiye , Cheng Peng , Hong Yingyi , Lan Hai , Yin He
Published: June 2020

The extensive use of finite element models accurately simulates the temperature distribution of electrical machines. The simulation model can be quickly modified to reflect changes in design. However, the long runtime of the simulation prevents any direct application of the optimization algorithm. In this paper, research focused on improving efficiency with which expensive analysis (finite element method) is used in generator temperature distribution. A novel surrogate model based optimization method is presented. First, the Taguchi orthogonal array relates a series of stator geometric parameters as input and the temperatures of a generator as output by sampling the design decision space. A number of stator temperature designs were generated and analyzed using 3-D multi-physical field collaborative finite element model. A suitable shallow neural network was then selected and fitted to the available data to obtain a continuous optimization objective function. The accuracy of the function was verified using randomly generated geometric parameters to the extent that they were feasible. Finally, a multi-objective genetic optimization algorithm was applied in the function to reduce the average and maximum temperature of the machine simultaneously. As a result, when the Pareto front was compared with the initial data, these temperatures showed a significant decrease.
Electromagnetic and Calorimetric Validation of a Direct Oil Cooled Tooth Coil Winding PM Machine for Traction Application
Authors: Acquaviva Alessandro , Skoog Stefan , Grunditz Emma , Thiringer Torbjörn
Published: June 2020

Tooth coil winding machines offer a low cost manufacturing process, high efficiency and high power density, making these attractive for traction applications. Using direct oil cooling in combination with tooth coil windings is an effective way of reaching higher power densities compared to an external cooling jacket. In this paper, the validation of the electromagnetic design for an automotive 600 V, 50 kW tooth coil winding traction machine is presented. The design process is a combination of an analytical sizing process and FEA optimization. It is shown that removing iron in the stator yoke for cooling channels does not affect electromagnetic performance significantly. In a previous publication, the machine is shown to be thermally capable of 25 A/mm 2 (105 Nm) continuously, and 35 A/mm 2 (140 Nm) during a 10 s peak with 6 l/min oil cooling. In this paper, inductance, torque and back EMF are measured and compared with FEA results showing very good agreement with the numerical design. Furthermore, the efficiency of the machine is validated by direct loss measurements, using a custom built calorimetric set-up in six operating points with an agreement within 0.9 units of percent between FEA and measured results.
Application of Support Vector Machine Modeling for the Rapid Seismic Hazard Safety Evaluation of Existing Buildings
Authors: Harirchian Ehsan , Lahmer Tom , Kumari Vandana , Jadhav Kirti
Published: June 2020

The economic losses from earthquakes tend to hit the national economy considerably; therefore, models that are capable of estimating the vulnerability and losses of future earthquakes are highly consequential for emergency planners with the purpose of risk mitigation. This demands a mass prioritization filtering of structures to identify vulnerable buildings for retrofitting purposes. The application of advanced structural analysis on each building to study the earthquake response is impractical due to complex calculations, long computational time, and exorbitant cost. This exhibits the need for a fast, reliable, and rapid method, commonly known as Rapid Visual Screening (RVS). The method serves as a preliminary screening platform, using an optimum number of seismic parameters of the structure and predefined output damage states. In this study, the efficacy of the Machine Learning (ML) application in damage prediction through a Support Vector Machine (SVM) model as the damage classification technique has been investigated. The developed model was trained and examined based on damage data from the 1999 Düzce Earthquake in Turkey, where the building’s data consists of 22 performance modifiers that have been implemented with supervised machine learning.