bluuebunny/crossref_metadata_2025 huggingface dataset:
ANALISIS KEMAMPUAN PEMAHAMAN KONSEP MATEMATIS SISWA SEKOLAH MENENGAH PERTAMA BERDASARKAN GAYA KOGNITIF
Authors: Septiani Linda , Pujiastuti Heni
Published: January 2021

Tujuan penelitian ini adalah menganalisis kemampuan pemahaman konsep matematis siswa sekolah menengah pertama yang ditinjau dari gaya kognitif Field Independent (FI), Field Intermediate (FID), dan Field Dependent (FD). Subjek penelitian ini adalah adalah siswa MtsN Pandeglang 1 kelas IX-C berjumlahkan 20 siswa yang dikelompokkan berdasarkan gaya kognitif yang dimiliki oleh setiap siswa, setiap kelompok gaya kogitif diambil perwakilan 2 siswa dengan menggunakan metode purposive sampling untuk diukur kemampuan pemahaman konsep matematisnya. Kemampuan pemahaman konsep matematis pada penelitian ini memiliki tujuh indikator. Berdasarkan hasil penelitian ini kemampuan pemahaman konsep matematis siswa memiliki kesamaan dan perbedaan. Siswa dengan kelompok gaya kognitif Field Independent (FI) memiliki kesamaan kemampuan pemahaman konsep matematis, yaitu mereka mampu mencapai semua indikator yang terdapat pada kemampuan pemahaman konsep matematis. Siswa dengan kelompok gaya kognitif Field Intermediate (FID) memiliki perbedaan kemampuan pemahaman konsep matematis, salah satu siswa dapat mencapai semua indikator dan siswa lainnya hanya memenuhi beberapa indikator kemampuan pemahaman konsep matematis. Hal ini menunjukkan bahwa siswa yang termasuk dalam kelompol gaya kognitif yang sama belum tentu memiliki kemampuan pemahaman konsep matematis yang sama. Siswa dengan kelompok gaya kognitif Field Dependent (FD) hanya sedikit indikator yang mampu dicapai oleh siswa dalam indikator kemampuan pemahaman konsep matematis.
Analisis Kesulitan Siswa Berdasarkan Kemampuan Pemahaman Matematis dalam Menyelesaikan Soal Cerita Pada Materi SPLDV
Authors: Agustini Desti , Pujiastuti Heni
Published: January 2021

Tujuan dari penelitian ini adalah untuk mengetahui kesulitan siswa berdasarkan kemampuan pemahaman matematis nya dalam menyelesaikan soal cerita pada materi Sistem Persamaan Linear Dua Variabel(SPLDV).  Jenis penelitian ini menggunakan penelitian deskriptif dengan pendekatan kualitatif. Sasaran dalam penelitian ini yaitu siswa kelas VIII SMP/MTs sederajat sebanyak 10 orang. Pengumpulan data dilakukan berdasarkan lembar tes kemampuan pemahaman matematis dan wawancara tidak terstruktur. Subjek penelitian yaitu 3 orang siswa dengan hasil tes kemampuan pemahaman matematis terendah. Berdasarkan hasil tes dan wawancara dapat disimpulkan bahwa terdapat kesulitan pada siswa dalam menyelesaikan soal SPLDV dalam bentuk cerita berdasarkan pada kemampuan pemahaman matematisnya. Hal ini dapat kita lihat dari hasil skor rata-rata nya yaitu sebesar 57% yang termasuk ke dalam kategori kurang. Adapun kesulitan-kesulitan yang di alami siswa yaitu belum memahami apa yang di tanyakan dalam soal, kesulitan mengubah soal cerita ke dalam simbol matematika, siswa masih kurang mampu memisalkan istilah karena masih kesulitan dalam mengklasifikasikan objek yang diketahui dalam soal, kesulitan menerapkan konsep penyelesaian secara algoritma dengan metode yang tepat, dan kesulitan mengaitkan berbagai konsep dalam penyelesaian soal.
ANALISIS KREATIVTAS MAHASISWA DALAM MENYELESAIKAN PEMBUKTIAN LANGSUNG PADA MATA KULIAH TEORI BILANGAN
Authors: Prajitno Sunyoto Hadi
Published: January 2021

The way of thinking logically and reasoning in number theory courses can be seen by the number of proofs of the properties of numbers in some basic set of numbers. This qualitative research aims to analyze student creativity in solving proving questions directly. The research involved 37 third semester students taking lectures on number theory. The technique in this research is to provide a test of proving questions then ask students with their own desires to do in front of the class, analyze the result of students work and interview students about their work. Data analysis was performed by analyzing the creativity of the evidence carried out by students fulfilling which aspects of the aspects of creative thinking behavior and indicators of creative thinking abilities based on Mahmudi. As many as four students have beeb able to use different evidentiary techniques. The four students are creative with very low, low, medium, high creativity ability levels based on fulfillent of indicators of creative thiking abilities based Mahmudi.
Avrupa İnsan Hakları Mahkemesi ve Türk Anayasa Mahkemesi Kararları Işığında Yasaklanan Ayrımcılık Temeli Olarak Cinsel Yönelim
Authors: KUDRET Hüseyin Ali
Published: January 2021

Eşitlik ilkesi ve bu ilkenin koruduğu hukuki menfaatin olumsuz ifadesi olan ayrımcılık yasağı, herkese eşit muamele yapılmasını, insanlar arasında ayrım yapılmamasını amaçlayan temel ilkelerdir. Demokratik toplumların temel yapı taşlarından biri olmakla birlikle, insan hakları hukukunun üzerine kurulduğu temel kavramlardır. Nitekim ulusal mevzuatlarda ve birçok uluslararası sözleşmede de düzenlenmiş ve uluslararası buyurucu kural haline gelmiştir. Bu çalışmanın konusunu, bu ilkeyle yasaklanan ayrımcılık temeli olarak cinsel yönelim oluşturmaktadır. Çalışmada, heteroseksüellik dışındaki cinsel yönelimlere sahip insanların maruz kaldığı ayrımcılıkların Avrupa İnsan Hakları Mahkemesi ve Türk Anayasa Mahkemesince nasıl ele alındığı, Avrupa İnsan Hakları Sözleşmesi madde 14 ve Anayasa madde 10 bağlamında ele alınmıştır. Bu çerçevede mahkeme kararlarından karşılaştırmalı olarak örnek verilerek, bu ayrımcılık türünün Türk Anayasa Mahkemesince nasıl ele alınması gerektiği konusuna katkı sunmayı amaçlamaktadır.
Keanekaragaman odonata di kawasan bendungan lempake, sungai karang mumus dan sungai berambai samarinda
Authors: Nisita Ratri Arbia , Hariani Nova , Trimurti Sus
Published: January 2021

Knowledge of the diversity of dragonflies (Odonata) is very important for river management which is used for various purposes by humans. This research aims to determine the diversity of Odonata in the waters of Bendungan Lempake, Karang Mumus River, and Berambai River Samarinda. Sampling was done by using purposive sampling technique through insect net with transect method along with the river flow, 5 times at each location for one month in the morning and evening. The samples obtained were prepared, stored on triangular paper containing camphor, and identified using entomological guidelines. Environmental temperature, humidity, and acidity of the water are calculated using standard measurement tools. Data is displayed in the form of the number of types and a description of each type. The results showed that 1025 individual dragonflies were found belonging to 22 species and 4 families of Odonata. The diversity index value (H') of dragonflies in the waters of the Bendungan Lempake is 2.83, the Karang Mumus River is 2.52 and the Berambai River is 2.53, which are classified as a medium category. The conclusion of this research is that the waters of Bendungan Lempake, Karang Mumus River, and Berambai River are still supporting as habitat for dragonflies to live and breed.
Social origins of risk semiotics
Authors: Shcherbin Vyacheslav K.
Published: January 2021

The article examines the structure of the inter-relationship between society and its inherent risks, the main components of which are society’s accumulated experience in predicting and mitigating risks, the continuous complication of modern society and the new social risks it generates. The reasons for the formation of these components, the positive and negative results of their use by society are analyzed. The reactions of managers and scientists to existing social risks are described. The main difference between these reactions is the diametrically opposite attitude of managers and scientists to the phenomenon of reductionism in solving complex social problems. The article defines the role of interdisciplinary research areas (synergetics, systemology, the combined social analysis, science of science, etc.) in solving problems related to social risks. The proposed by A. G. Teslinov’s classification of existing worlds (the material world, the world of ideas, the social world and the world of signs) correlates with traditional disciplinary classifications. The place of a new scientific direction (risk semiotics) in the system of existing risk sciences, as well as among other artificial semiotics is established. The conclusion about the need for interrelated development of social semiotics and risk semiotics is substantiated.
Motivational Mindsets and Reasons for Studying: Development and Validation of a Classification Tool
Authors: Hudig Job , Scheepers Ad W. A. , Schippers Michaéla C. , Smeets Guus
Published: January 2021

First-year university students have multiple motives for studying and these motives may interact. Yet, past research has primarily focused on a variable-centered, dimensional approach missing out on the possibility to study the joint effect of multiple motives that students may have. Examining the interplay between motives is key to (a) better explain student differences in study success and wellbeing, and (b) to understand different effects that interventions can have in terms of wellbeing and study success. We therefore applied a student-centered, multidimensional approach in which we explored motivational profiles of first-year university students by combining three dimensions of motives for studying (self-transcendent, self-oriented, and extrinsic) which have been shown to be differently related to academic functioning. Using cluster analysis in two independent, consecutive university student cohorts (n = 763 and n = 815), we identified four meaningful profiles and coined them motivational mindsets. We validated the four mindset profiles not only within each student sample but also found almost identical profiles between the student samples. The motivational mindset profiles were labeled: high-impact mindset, low-impact mindset, social-impact mindset, and self-impact mindset. In addition to validating the paradigm, we developed a mindset classification tool to further use these mindsets in practice and in future research.
Effects of Reduced Nitrogen Fertilization and Irrigation on Structure and Physicochemical Properties of Starch in Two Bread Wheat Cultivars
Authors: Tong Jingyang , Wang Shujun , He Zhonghu , Zhang Yan
Published: January 2021

Nitrogen (N) fertilization and irrigation are significant agronomic factors affecting wheat production, but little information is available on the effects of reduced N fertilization and irrigation on internal starch structure and physicochemical properties associated with the quality of wheat-based foods. In this study, reduced N fertilization and irrigation were separately applied to investigate their effects on composition and morphological changes, crystalline and external region structure features, swelling power, and gelatinization characteristics of starch granules in bread wheat, with a high N-use-efficiency and water-saving wheat cultivar Zhongmai 175 and a widely grown cultivar Jingdong 17. Compared with a non-N control, reduced N fertilization did not change the crystallinity type and short-range ordered degree of starch; however, it significantly increased relative crystallinity, swelling power and gelatinization enthalpy, whereas amylose content and transition temperatures were decreased. Under reduced irrigation, more small starch granules with compact arrangements appeared in comparison with non-water control. Relative crystallinity, swelling power and gelatinization enthalpy of starch were increased, whereas short-range ordered degree and transition temperatures were decreased. Moreover, the starch of the two cultivars appeared to differ in response to both the N and water treatments. The findings indicated that reduced N fertilization or irrigation markedly influenced the structure and physicochemical characteristics of wheat starch, providing important information for developing elite cultivars with high N and water use efficiency and outstanding starch quality.
Effect of Bentonite and Barley Straw on the Restoration of the Biological Quality of Agriculture Soil Contaminated with the Herbicide Successor T 550 SE
Authors: Wyszkowska Jadwiga , Tomkiel Monika , Borowik Agata , Baćmaga Małgorzata , Kucharski Jan
Published: January 2021

Environmentally safe ways are sought to prevent the accumulation and to accelerate the degradation of herbicide active substances in agricultural soil. This study aimed to determine the effectiveness of finely-ground barley straw and bentonite in mitigating the effects of agricultural soil contamination with Successor T 550 SE. This herbicide was applied in the following doses: 0, 0.73, and 14.63 mg of the active substance per kg. The bentonite and spring barley straw were used at 10 g/kg. The action of these additives was compared to soil without the addition of straw and bentonite. The application of the experimental herbicide disturbed microbial systems, such as organotrophic bacteria, oligotrophic bacteria and their spores, actinobacteria, and fungi. A positive response to the herbicide dose of 14.63 mg a.s./kg was observed only for spores of oligotrophic bacteria. Further disturbances were observed in the agricultural soil biochemical properties, i.e., in the activity of dehydrogenases, urease, catalase, acid, and alkaline phosphatase, arylsulfatase, and β-glucosidase. A significant decrease in the activity of dehydrogenases, acid phosphatase, and arylsulfatase was observed following the application of 14.63 mg a.s./kg. The yield of maize decreased following the application of the analysed plant protection agent. Based on the soil quality index (BA), the addition of straw was more effective in restoring soil homeostasis than bentonite. Both bentonite and straw can be successfully used to improve agricultural soil biological activity. However, more effective mitigation of the negative effects of the herbicide in soil was observed in objects supplemented with barley straw. This improved the microbiological and biochemical properties of the soil. Barley straw was more effective than bentonite in restoring soil biological balance.
Decision Trees to Forecast Risks of Strawberry Powdery Mildew Caused by Podosphaera aphanis
Authors: Carisse Odile , Fall Mamadou Lamine
Published: January 2021

Powdery mildew (Podosphaera aphanis) is a major disease in day-neutral strawberry. Up to 30% yield losses have been observed in Eastern Canada. Currently, management of powdery mildew is mostly based on fungicide applications without consideration of risk. The objective of this study is to use P. aphanis inoculum, host ontogenic resistance, and weather predictors to forecast the risk of strawberry powdery mildew using CART models (classification trees). The data used to build the trees were collected in 2006, 2007, and 2008 at one experimental farm and six commercial farms located in two main strawberry-production areas, while external validation data were collected at the same experimental farm in 2015, 2016, and 2018. Data on proportion of leaf area diseased (PLAD) were grouped into four severity classes (1: PLAD = 0; 2: PLAD > 0 and <5%; 3: >5% and <15%; and 4: PLAD > 15%) for a total of 681 and 136 cases for training and external validation, respectively. From the initial 92 weather variables, 21 were selected following clustering. The tree with the best balance between the number of predictors and highest accuracy was built with: airborne inoculum concentration and number of susceptible leaves on the day of sampling, and mean relative humidity, mean daily number of hours at temperature between 18 and 30 °C, and mean daily number of hours at saturation vapor pressure between 10 and 25 mmHg during the previous 6 days. For training, internal validation, and external validation datasets, the sensitivity, specificity, and accuracy ranged from 0.70 to 0.90, 0.87 to 0.98, and 0.82 to 0.97, respectively. The classification rules to estimate strawberry powdery mildew risk can be easily implemented into disease decision support systems and used to treat only when necessary and thus avoid preventable yield losses and unnecessary treatments.
Evaluation of the Susceptibility of Some Eggplant Cultivars to Green Peach Aphid, Myzus persicae (Sulzer) (Hemiptera: Aphididae)
Authors: Raeyat Zienab , Razmjou Jabraiel , Naseri Bahram , Ebadollahi Asgar , Krutmuang Patcharin
Published: January 2021

Due to the detrimental side-effects of synthetic pesticides, the use of nonchemical strategies in the management of insect pests is necessary. In the present study, the susceptibility of fourteen eggplant cultivars to green peach aphid (M. persicae) were investigated. According to preliminary screening tests, ‘Long-Green’, ‘Ravaya’ and ‘Red-Round’ as relatively resistant, and ‘White-Casper’ and ‘Pearl-Round’ as susceptible cultivars were recognized. In the antixenosis tests, the highest hosting preference was documented for ‘White-Casper’. Population growth parameters were used for evaluation of antibiosis. The highest and lowest developmental time (d) was observed on ‘Long-Green’ (4.33 d) and ‘White-Casper’ (3.26 d), respectively. The highest and lowest intrinsic rates of population increase (rm) were on ‘White-Casper’ (0.384 d−1) and ‘Long-Green’ (0.265 d−1), respectively. Significant differences were observed in the height and fresh and dry weight of infested and noninfected plants. Plant resistance index (PRI), as a simplified way to assess all resistance mechanisms, provides a particular value to determine the proper resistant cultivar. The greatest PRI value was observed on ‘Long-Green’. In general, the ‘Long-Green’ showed the least, and the ‘White-Casper’ displayed the most susceptibility among tested cultivars infested by M. persicae, which might be useful in integrated management of this pest.
Detection of Sub-Aroma Threshold Concentrations of Wine Methoxypyrazines by Multidimensional GCMS
Authors: Olejar Kenneth , Breitmeyer Jason , Wimalasiri Pradeep , Tian Bin , Field Stewart
Published: January 2021

Complex matrices, such as wine, provide a challenge in the quantification of compounds. There exists a high likelihood of co-elution in these matrices, thereby artificially increasing the observed concentration. This can often lead to confusing data where compounds are above aroma detection thresholds, but are not detected by olfactory analysis. Additionally, the lack of sensitivity in assays can lead to the non-detection of sub-aroma threshold concentrations and contrasting data when olfactory analysis detects these aromas. To eliminate these pitfalls and gain a better understanding of the role that methoxypyrazines impart green character to wine, a quantitative method using headspace solid-phase microextraction coupled to heart-cutting multidimensional gas chromatography mass spectrometry was developed. The method can quantitate the three common methoxypyrazines found in wine at the picogram per liter level while resolving co-eluting compounds. The proposed method was validated using model wine and wine solutions and was ultimately used for the comparative analysis of white, rosé, and red wines.
It’s Not Easy Being Green: A Narrative Review on the Microbiology, Virulence and Therapeutic Prospects of Multidrug-Resistant Pseudomonas aeruginosa
Authors: Behzadi Payam , Baráth Zoltán , Gajdács Márió
Published: January 2021

Pseudomonas aeruginosa is the most frequent cause of infection among non-fermenting Gram-negative bacteria, predominantly affecting immunocompromised patients, but its pathogenic role should not be disregarded in immunocompetent patients. These pathogens present a concerning therapeutic challenge to clinicians, both in community and in hospital settings, due to their increasing prevalence of resistance, and this may lead to prolonged therapy, sequelae, and excess mortality in the affected patient population. The resistance mechanisms of P. aeruginosa may be classified into intrinsic and acquired resistance mechanisms. These mechanisms lead to occurrence of resistant strains against important antibiotics—relevant in the treatment of P. aeruginosa infections—such as β-lactams, quinolones, aminoglycosides, and colistin. The occurrence of a specific resistotype of P. aeruginosa, namely the emergence of carbapenem-resistant but cephalosporin-susceptible (Car-R/Ceph-S) strains, has received substantial attention from clinical microbiologists and infection control specialists; nevertheless, the available literature on this topic is still scarce. The aim of this present review paper is to provide a concise summary on the adaptability, virulence, and antibiotic resistance of P. aeruginosa to a readership of basic scientists and clinicians.
Detection of Cardiac Structural Abnormalities in Fetal Ultrasound Videos Using Deep Learning
Authors: Komatsu Masaaki , Sakai Akira , Komatsu Reina , Matsuoka Ryu , Yasutomi Suguru , Shozu Kanto , Dozen Ai , Machino Hidenori , Hidaka Hirokazu , Arakaki Tatsuya , Asada Ken , Kaneko Syuzo , Sekizawa Akihiko , Hamamoto Ryuji
Published: January 2021

Artificial Intelligence (AI) technologies have recently been applied to medical imaging for diagnostic support. With respect to fetal ultrasound screening of congenital heart disease (CHD), it is still challenging to achieve consistently accurate diagnoses owing to its manual operation and the technical differences among examiners. Hence, we proposed an architecture of Supervised Object detection with Normal data Only (SONO), based on a convolutional neural network (CNN), to detect cardiac substructures and structural abnormalities in fetal ultrasound videos. We used a barcode-like timeline to visualize the probability of detection and calculated an abnormality score of each video. Performance evaluations of detecting cardiac structural abnormalities utilized videos of sequential cross-sections around a four-chamber view (Heart) and three-vessel trachea view (Vessels). The mean value of abnormality scores in CHD cases was significantly higher than normal cases (p < 0.001). The areas under the receiver operating characteristic curve in Heart and Vessels produced by SONO were 0.787 and 0.891, respectively, higher than the other conventional algorithms. SONO achieves an automatic detection of each cardiac substructure in fetal ultrasound videos, and shows an applicability to detect cardiac structural abnormalities. The barcode-like timeline is informative for examiners to capture the clinical characteristic of each case, and it is also expected to acquire one of the important features in the field of medical AI: the development of “explainable AI.”
Diarylureas as Antitumor Agents
Authors: Catalano Alessia , Iacopetta Domenico , Sinicropi Maria Stefania , Franchini Carlo
Published: January 2021

The diarylurea is a scaffold of great importance in medicinal chemistry as it is present in numerous heterocyclic compounds with antithrombotic, antimalarial, antibacterial, and anti-inflammatory properties. Some diarylureas, serine-threonine kinase or tyrosine kinase inhibitors, were recently reported in literature. The first to come into the market as an anticancer agent was sorafenib, followed by some others. In this review, we survey progress over the past 10 years in the development of new diarylureas as anticancer agents.
DeepFogSim: A Toolbox for Execution and Performance Evaluation of the Inference Phase of Conditional Deep Neural Networks with Early Exits Atop Distributed Fog Platforms
Authors: Scarpiniti Michele , Baccarelli Enzo , Momenzadeh Alireza , Sarv Ahrabi Sima
Published: January 2021

The recent introduction of the so-called Conditional Neural Networks (CDNNs) with multiple early exits, executed atop virtualized multi-tier Fog platforms, makes feasible the real-time and energy-efficient execution of analytics required by future Internet applications. However, until now, toolkits for the evaluation of energy-vs.-delay performance of the inference phase of CDNNs executed on such platforms, have not been available. Motivated by these considerations, in this contribution, we present DeepFogSim. It is a MATLAB-supported software toolbox aiming at testing the performance of virtualized technological platforms for the real-time distributed execution of the inference phase of CDNNs with early exits under IoT realms. The main peculiar features of the proposed DeepFogSim toolbox are that: (i) it allows the joint dynamic energy-aware optimization of the Fog-hosted computing-networking resources under hard constraints on the tolerated inference delays; (ii) it allows the repeatable and customizable simulation of the resulting energy-delay performance of the overall Fog execution platform; (iii) it allows the dynamic tracking of the performed resource allocation under time-varying operating conditions and/or failure events; and (iv) it is equipped with a user-friendly Graphic User Interface (GUI) that supports a number of graphic formats for data rendering. Some numerical results give evidence for about the actual capabilities of the proposed DeepFogSim toolbox.
An Investigation of Radial Basis Function Method for Strain Reconstruction by Energy-Resolved Neutron Imaging
Authors: Aggarwal Riya , Lamichhane Bishnu P. , Meylan Michael H. , Wensrich Chris M.
Published: January 2021

The main objective of the current work is to determine meshless methods using the radial basis function (rbf) approach to estimate the elastic strain field from energy-resolved neutron imaging. To this end, we first discretize the longitudinal ray transformation with rbf methods to give us an unconstrained optimization problem. This discretization is then transformed into a constrained optimization problem by adding equilibrium conditions to ensure uniqueness. The efficiency and accuracy of this approach are investigated for the situation of 2d plane stress. In addition, comparisons are made between the results obtained with rbf collocation, finite-element (fem) and analytical solution methods for test problems. The method is then applied to experimentally measured continuous and discontinuous strain fields using steel samples for an offset ring-and-plug and crushed ring, respectively.
Effect of Distributed Photovoltaic Generation on Short-Circuit Currents and Fault Detection in Distribution Networks: A Practical Case Study
Authors: Alcala-Gonzalez Daniel , García del Toro Eva Maria , Más-López María Isabel , Pindado Santiago
Published: January 2021

The increase in the installation of renewable energy sources in electrical systems has changed the power distribution networks, and a new scenario regarding protection devices has arisen. Distributed generation (DG) might produce artificial delays regarding the performance of protection devices when acting as a result of short-circuits. In this study, the preliminary research results carried out to analyze the effect of renewable energy sources (photovoltaic, wind generation, etc.) on the protection devices of a power grid are described. In order to study this problem in a well-defined scenario, a quite simple distribution network (similar to the ones present in rural areas) was selected. The distribution network was divided into three protection zones so that each of them had DG. In the Institute of Electrical and Electronic Engineers (IEEE) system 13 bus test feeder, the short-circuits with different levels of penetration were performed from 1 MVA to 3 MVA (that represent 25%, 50%, and 75% of the total load in the network). In the simulations carried out, it was observed that the installation of DG in this distribution network produced significant changes in the short-circuit currents, and the inadequate performance of the protection devices and the delay in their operating times (with differences of up to 180% in relation to the case without DG). The latter, that is, the impacts of photovoltaic DG on the reactions of protection devices in a radial distribution network, is the most relevant outcome of this work. These are the first results obtained from a research collaboration framework established by staff from ETSI Civil and the IDR/UPM Institute, to analyze the effect of renewable energy sources (as DG) on the protection devices of a radial distribution network.
Synergistic Regulation Mechanism of Inorganic Thermal Oxidation Coating and Poly (Vinylphosphonic Acid) (PVPA) Coating for High Load Bearing Superlubricity
Authors: Liu Mengmeng , Liu Zhifeng , Chen Junmin , Jiang Liang , Zhang Caixia , Li Xianyong
Published: January 2021

A low friction coefficient and high bearing capacity can improve the service life of implants in the human body. In this study, we firstly investigate the mechanical properties of inorganic thermal oxide coatings on titanium alloy (Ti6Al4V). Tribological experiments were performed for different tribo-pairs under uniform conditions. The inorganic thermal oxide coating on Ti6Al4V formed at 300℃ was found to have excellent tribological properties and can effectively improve the bearing capacity of Ti6Al4V. The organic poly (vinylphosphonic acid) (PVPA) on Ti6Al4V has excellent anti-friction properties, which can help achieve superlubricity. An inorganic thermal oxide/organic PVPA composite coating was fabricated on Ti6Al4V to obtain a surface with low friction and high bearing capacity. It is found that the presence of the thermal oxide doubled the bearing capacity of the composite coating compared to that of the PVPA coating alone. This study can serve as a guide for the modification of artificial joints.
Angiotensin II Type 1 Receptor Antagonist Losartan Inhibits TNF-α-Induced Inflammation and Degeneration Processes in Human Nucleus Pulposus Cells
Authors: Saravi Babak , Li Zhen , Pfannkuche Judith , Wystrach Laura , Häckel Sonja , E. Albers Christoph , Grad Sibylle , Alini Mauro , Richards Robert Geoffrey , Lang Corinna , Südkamp Norbert , Schmal Hagen , Lang Gernot
Published: January 2021

Our recent study detected the expression of a tissue renin–angiotensin system (tRAS) in human intervertebral discs (IVDs). The present study sought to investigate the impact of the angiotensin II receptor type 1 (AGTR1) antagonist losartan on human nucleus pulposus (NP) cell inflammation and degeneration induced by tumor necrosis factor-α (TNF-α). Human NP cells (4 donors; Pfirrmann grade 2–3; 30–37-years–old; male) were isolated and expanded. TNF-α (10 ng/mL) was used to induce inflammation and degeneration. We examined the impact of losartan supplementation and measured gene expression of tRAS, anabolic, catabolic, and inflammatory markers in NP cells after 24 and 72 h of exposure. T0070907, a PPAR gamma antagonist, was applied to examine the regulatory pathway of losartan. Losartan (1 mM) significantly impaired the TNF-α-induced increase of pro-inflammatory (nitric oxide and TNF-α), catabolic (matrix metalloproteinases), and tRAS (AGTR1a and angiotensin-converting enzyme) markers. Further, losartan maintained the NP cell phenotype by upregulating aggrecan and downregulating collagen type I expression. In summary, losartan showed anti-inflammatory, anti-catabolic, and positive phenotype-modulating effects on human NP cells. These results indicate that tRAS signaling plays an important role in IVD degeneration, and tRAS modulation with losartan could represent a novel therapeutic approach.
Design of 3D Printing Thermo-Sensored Medical Gear in Detecting COVID-19 Symptoms
Authors: Djukanović Milena , Mavrić Ardijan , Jovanović Jovana , Roganović Milovan , Bošković Velibor
Published: January 2021

Shortly after the outbreak of the COVID-19 pandemic, there was a need to provide protective equipment to the medical facilities whose supplies were threatened to be depleted. Just like many countries in Europe, Montenegro responded to the need for medical equipment by using the advantages of 3D printers while establishing a state network of production hubs, ensuring closed connectivity, communication, and the mutual fulfilment of personal protective equipment (PPE) demands whenever and wherever required. With the second wave of the pandemic, Montenegro rose to second place in the world with the number of coronavirus cases, which also led to an increasing number of infected medical staff. Since fever is a frequent symptom of SA+RS-CoV2 infection, a type of innovative 3D-printed thermo-sensored medical gear has been designed and tested in hospital conditions. This medical gear shaped like a bracelet, which changes color in the presence of high human body temperatures, proves to be efficient and easy to use for medical staff as well as patients.
A New Circuit Design of AC/DC Converter for T8 LED Tube
Authors: Kim Sunghwan , Jung Haiyoung
Published: January 2021

This study is about an improved high-quality light-emitting diode (LED) converter for a T8 LED tube. The converter is separated into the AC driving circuit and DC driving circuit. Also, the LED tube was applied with an output ripple eliminator for the optical performance. The AC driving circuit and DC driving circuit are assembled at the end of the LED tube in a G13 base and a G13 base dummy, respectively, and the output ripple eliminator is located on an LED PCB. The proposed LED converter is founded on a SSBB (single-stage buck-boost) converter topology and was designed for 10 W operation for a 600 mm T8 LED tube. The light waveform of the LED tube was measured by a photosensor. The waveform had almost no ripple and was the same as a straight line. The average calculated percent flicker of the proposed LED converter was an average of 1.9% at 100 and 240 VAC, 50 and 60 Hz. The proposed converter has lower power efficiency than a conventional converter by 2.7% at 100–240 VAC, but it still has high power efficiency (>87%). The measurement results represent that the LED output current regulation is below 0.92% at 100–240 VAC and the converter obtains the power factor more than 0.84 and the total harmonic distortion is less than 14.3%. All of the current harmonics reach the IEC 61000-3-2 Class D standards for high-quality LED converters.
ReLU Network with Bounded Width Is a Universal Approximator in View of an Approximate Identity
Authors: Moon Sunghwan
Published: January 2021

Deep neural networks have shown very successful performance in a wide range of tasks, but a theory of why they work so well is in the early stage. Recently, the expressive power of neural networks, important for understanding deep learning, has received considerable attention. Classic results, provided by Cybenko, Barron, etc., state that a network with a single hidden layer and suitable activation functions is a universal approximator. A few years ago, one started to study how width affects the expressiveness of neural networks, i.e., a universal approximation theorem for a deep neural network with a Rectified Linear Unit (ReLU) activation function and bounded width. Here, we show how any continuous function on a compact set of Rnin,nin∈N can be approximated by a ReLU network having hidden layers with at most nin+5 nodes in view of an approximate identity.
Hierarchical Phoneme Classification for Improved Speech Recognition
Authors: Oh Donghoon , Park Jeong-Sik , Kim Ji-Hwan , Jang Gil-Jin
Published: January 2021

Speech recognition consists of converting input sound into a sequence of phonemes, then finding text for the input using language models. Therefore, phoneme classification performance is a critical factor for the successful implementation of a speech recognition system. However, correctly distinguishing phonemes with similar characteristics is still a challenging problem even for state-of-the-art classification methods, and the classification errors are hard to be recovered in the subsequent language processing steps. This paper proposes a hierarchical phoneme clustering method to exploit more suitable recognition models to different phonemes. The phonemes of the TIMIT database are carefully analyzed using a confusion matrix from a baseline speech recognition model. Using automatic phoneme clustering results, a set of phoneme classification models optimized for the generated phoneme groups is constructed and integrated into a hierarchical phoneme classification method. According to the results of a number of phoneme classification experiments, the proposed hierarchical phoneme group models improved performance over the baseline by 3%, 2.1%, 6.0%, and 2.2% for fricative, affricate, stop, and nasal sounds, respectively. The average accuracy was 69.5% and 71.7% for the baseline and proposed hierarchical models, showing a 2.2% overall improvement.
An Empirical Algorithm for COVID-19 Nowcasting and Short-Term Forecast in Spain: A Kinematic Approach
Authors: Orihuel Enrique , Sapena Juan , Navarro-Ortiz Josep
Published: January 2021

In the context of the COVID-19 pandemic, the use of forecasting techniques can play an advisory role in policymakers’ early implementation of non-pharmaceutical interventions (NPIs) in order to reduce SARS-CoV-2 transmission. In this article, we present a simple approach to even day and 14 day forecasts of the number of COVID-19 cases. The 14 day forecast can be taken as a proxy nowcast of infections that occur on the calculation day in question, if we assume the hypothesis that about two weeks elapse from the day a person is infected until the health authorities register it as a confirmed case. Our approach relies on polynomial regression between the dependent variable y (cumulative number of cases) and the independent variable x (time) and is modeled as a third-degree polynomial in x. The analogy between the pandemic spread and the kinematics of linear motion with variable acceleration is useful in assessing the rate and acceleration of spread. Our frame is applied to official data of the cumulative number of cases in Spain from 15 June until 17 October 2020. The epidemic curve of the cumulative number of cases adequately fits the cubic function for periods of up to two months with coefficients of determination R-squared greater than 0.97. The results obtained when testing the algorithm developed with the pandemic figures in Spain lead to short-term forecasts with relative errors of less than ±1.1% in the seven day predictions and less than ±4.0% in the 14 day predictions.
Analysis on the Evolution and Microphysical Characteristics of Two Consecutive Hailstorms in Spring in Yunnan, China
Authors: Zhang Sidou , Liu Shiyin , Zhang Tengfei
Published: January 2021

By using products of the cloud model, National Centers for Environmental Prediction (NCEP) Final Operational Global Analysis (FNL) reanalysis data, and Doppler weather radar data, the mesoscale characteristics, microphysical structure, and mechanism of two hail cloud systems which occurred successively within 24 h in southeastern Yunnan have been analyzed. The results show that under the influence of two southwest jets in front of the south branch trough (SBT) and the periphery of the western Pacific subtropical high (WPSH), the northeast-southwest banded echoes affect the southeastern Yunnan of China twice. Meanwhile, the local mesoscale radial wind convergence and uneven wind speed lead to the intense development of convective echoes and the occurrence of hail. The simulated convective cloud bands are similar to the observation. The high-level mesoscale convergence line leads to the development of convective cloud bands. The low-level wind direction or wind speed convergence and the high-level wind speed divergence form a deep tilted updraft, with the maximum velocity of 15 m·s−1 at the −40~−10 °C layer, resulting in the intense development of local convective clouds. The hail embryos form through the conversion or collision growth of cloud water and snowflakes and have little to do with rain and ice crystals. Abundant cloud water, especially the accumulation region of high supercooled water (cloud water) near the 0 °C layer, is the key to the formation of hail embryos, in which qc is up to 1.92 g·kg−1 at the −4~−2 °C layer. The hail embryos mainly grow by collision-coalescence (collision-freezing) with cloud water (supercooled cloud drops) and snow crystal riming.
Electret Filters—From the Influence of Discharging Methods to Optimization Potential
Authors: Kerner Maximilian , Schmidt Kilian , Schumacher Stefan , Asbach Christof , Antonyuk Sergiy
Published: January 2021

Electret filters are electrostatically charged nonwovens which are commonly used in aerosol filtration to remove fine particles from gases. It is known that the charge and thus also the filtration efficiency can degrade over time. Thus, many testing standards require to remove the charge by treatment with liquid isopropanol (IPA) or IPA-saturated air. However, the parameters influencing this discharge have not been completely clarified yet. The aim of this work was, on the one hand, to experimentally investigate the influence of the IPA treatment on different electret filters and, on the other hand, to show the optimization potential of electret filters with respect to efficiency and long-term stability by numerical simulations. The experiments revealed that the air permeability is a central influencing parameter. Small pores lead to a reduced discharge efficiency using liquid IPA, while both treatment methods are suitable for larger pores. The simulations showed that a homogeneous charge distribution within the filter depth is advantageous for the initial performance. In contrast, charge penetrating deeper in the filter medium delays the charge decay and thus increases the operating time, with the trade-off of a lower initial performance.
RP-UHPLC-MS Chemical Profiling, Biological and In Silico Docking Studies to Unravel the Therapeutic Potential of Heliotropium crispum Desf. as a Novel Source of Neuroprotective Bioactive Compounds
Authors: Arshad Adeel , Ahemad Saeed , Saleem Hammad , Saleem Muhammad , Zengin Gokhan , Abdallah Hassan H. , Tousif Muhammad Imran , Ahemad Nafees , Fawzi Mahomoodally Mohamad
Published: January 2021

Heliotropium is one of the most important plant genera to have conventional folklore importance, and hence is a potential source of bioactive compounds. Thus, the present study was designed to explore the therapeutic potential of Heliotropium crispum Desf., a relatively under-explored medicinal plant species. Methanolic extracts prepared from a whole plant of H. crispum were studied for phytochemical composition and possible in vitro and in silico biological properties. Antioxidant potential was assessed via six different assays, and enzyme inhibition potential against key clinical enzymes involved in neurodegenerative diseases (acetylcholinesterase (AChE) and butyrylcholinesterase (BChE)), diabetes (α-amylase and α-glucosidase), and skin problems (tyrosinase) was assayed. Phytochemical composition was established via determination of the total bioactive contents and reverse phase ultra-high performance liquid chromatography mass spectrometry (RP-UHPLC-MS) analysis. Chemical profiling revealed the tentative presence of 50 secondary metabolites. The plant extract exhibited significant inhibition against AChE and BChE enzymes, with values of 3.80 and 3.44 mg GALAE/g extract, respectively. Further, the extract displayed considerable free radical scavenging activity against DPPH and ABTS radicals, with potential values of 43.19 and 41.80 mg TE/g extract, respectively. In addition, the selected compounds were then docked against the tested enzymes, which have shown high inhibition affinity. To conclude, H. crispum was found to harbor bioactive compounds and showed potent biological activities which could be further explored for potential uses in nutraceutical and pharmaceutical industries, particularly as a neuroprotective agent.
Summary of over Fifty Years with Brain-Computer Interfaces—A Review
Authors: Kawala-Sterniuk Aleksandra , Browarska Natalia , Al-Bakri Amir , Pelc Mariusz , Zygarlicki Jaroslaw , Sidikova Michaela , Martinek Radek , Gorzelanczyk Edward Jacek
Published: January 2021

Over the last few decades, the Brain-Computer Interfaces have been gradually making their way to the epicenter of scientific interest. Many scientists from all around the world have contributed to the state of the art in this scientific domain by developing numerous tools and methods for brain signal acquisition and processing. Such a spectacular progress would not be achievable without accompanying technological development to equip the researchers with the proper devices providing what is absolutely necessary for any kind of discovery as the core of every analysis: the data reflecting the brain activity. The common effort has resulted in pushing the whole domain to the point where the communication between a human being and the external world through BCI interfaces is no longer science fiction but nowadays reality. In this work we present the most relevant aspects of the BCIs and all the milestones that have been made over nearly 50-year history of this research domain. We mention people who were pioneers in this area as well as we highlight all the technological and methodological advances that have transformed something available and understandable by a very few into something that has a potential to be a breathtaking change for so many. Aiming to fully understand how the human brain works is a very ambitious goal and it will surely take time to succeed. However, even that fraction of what has already been determined is sufficient e.g., to allow impaired people to regain control on their lives and significantly improve its quality. The more is discovered in this domain, the more benefit for all of us this can potentially bring.
Examining Mental Workload in a Spatial Navigation Transfer Game via Functional near Infrared Spectroscopy
Authors: Galoyan Tamara , Betts Kristen , Abramian Hovag , Reddy Pratusha , Izzetoglu Kurtulus , Shewokis Patricia A.
Published: January 2021

The goal of this study was to examine the effects of task-related variables, such as the difficulty level, problem scenario, and experiment week, on performance and mental workload of 27 healthy adult subjects during problem solving within the spatial navigation transfer (SNT) game. The study reports task performance measures such as total time spent on a task (TT) and reaction time (RT); neurophysiological measures involving the use of functional near-infrared spectroscopy (fNIRS); and a subjective rating scale for self-assessment of mental workload (NASA TLX) to test the related hypothesis. Several within-subject repeated-measures factorial ANOVA models were developed to test the main hypothesis. The results revealed a number of interaction effects for the dependent measures of TT, RT, fNIRS, and NASA TLX. The results showed (1) a decrease in TT and RT across the three levels of difficulty from Week 1 to Week 2; (2) an increase in TT and RT for high and medium cognitive load tasks as compared to low cognitive load tasks in both Week 1 and Week 2; (3) an overall increase in oxygenation from Week 1 to Week 2. These findings confirmed that both the behavioral performance and mental workload were sensitive to task manipulations.