bluuebunny/crossref_metadata_2025 huggingface dataset:
Central Asia in Context of Afghan Situation
Authors: Labinskaya I.
Published: April 2021

The session of IMEMO academic council in December 2010 discussed the problems of Central Asia in the context of the Afghan situation. In her keynote report D. Malysheva, doctor of political sciences, pointed at the increased attention to Central Asia by regional and international players. This is explained by the new and extremely worrying situation in neighboring Afghanistan. There is a prospect that NATO will lose the war in Afghanistan and that the coalition troops will be withdrawn from that country. In its turn, this generates a threat of Taliban’s return to power in this country. Thus, we cannot exclude the political upheavals in the Central Asian republics that will inevitably affect Russia's interests. The discussion highlighted Russia’s stable interest to Afghanistan both politically and economically.
A Pavilion Made from Scrap Acrylic and Physically Form-found at Full Scale
Authors: Segal Edward M. , Chao Albert , Ramsburg Lisa , Draper Powell
Published: April 2021

Location of Project: Barcelona, Spain
 Structural Type: thin shell roof
 Project Scale: 1.9 m by 3.55 m in plan
 Architect: Lisa Ramsburg and Albert Chao
 Structural Engineer: Edward M. Segal and Powell Draper
 Construction year:
2019
From Information and Quantum Physics to Consciousness and Reality
Authors: Verheyen Peter
Published: April 2021

How does the world around us work and what is real? This question has preoccupied humanity since its beginnings. From the 16th century onwards, it has been periodically necessary to revise the prevailing worldview. But things became very strange at the beginning of the 20th century with the advent of relativity theory and quantum physics. The current focus is on the role of information, there being a debate about whether this is ontological or epistemological. A theory has recently been formulated in which spacetime and gravity emerges from microscopic quantum information, more specifically from quantum entanglement via entanglement entropy. A latest theory describes the emergence of reality itself through first-person perspective experiences and algorithmic information theory. In quantum physics, perception and observation play a central role. Perception, interaction with the environment, requires an exchange of information. Via biochemical projection, information is given an interpretation that is necessary to make life and consciousness possible. The world around us is not at all what it seems.
THz-TDS Reflection Measurement of Coating Thicknesses at Non-Perpendicular Incidence: Experiment and Simulation
Authors: Burger Ruben , Frisch Julia , Hübner Matthias , Goldammer Matthias , Peters Ole , Rönneberg Enno , Wu Datong
Published: April 2021

Time-domain spectroscopy (TDS) in the Terahertz (THz) frequency range is gaining in importance in nondestructive testing of dielectric materials. One application is the layer thickness measurement of a coating layer. To determine the thickness from the measurement data, the refractive index of the coating layer must be known in the surveyed frequency range. For perpendicular incidence of the radiation, methods exist to extract the refractive index from the measurement data itself without prior knowledge. This paper extends these methods for non-perpendicular incidence, where the polarization of the radiation becomes important. Furthermore, modifications considering effects of surface roughness of the coating are introduced. The new methods are verified using measurement data of a sample of Inconel steel coated with yttria-stabilized zirconia (YSZ) and with COMSOL simulations of the measurement setup. To validate the thickness measurements, scanning electron microscopy (SEM) images of the layer structure are used. The results show good agreement with an average error of 1% for the simulation data and under 4% for the experimental data compared to reference measurements.
Germplasm Conservation: Instrumental in Agricultural Biodiversity-A Review
Authors: Priyanka Veerala , Kumar Rahul , Dhaliwal Inderpreet , Kaushik Prashant
Published: April 2021

Germplasm is a valuable natural resource in plant diversity that is crucial for its potential use. It provides knowledge about a species genetic composition. Germplasm protection strategies are not just planting hope threatened with extinction, they preserve medicinal and other essential plants on which survival rests. The successful use of genetic plant resources necessitates diligent collection, storage, analysis, documentation, and germplasm exchange. Slow growth cultures, cryopreservation, pollen and DNA banks, botanic gardens, genetic reserves and farmer’s fields are few conservation techniques. However, usage of an in vitro procedure with any chance of genetic instability leads to the destruction of the entire substance. Improved understanding of basic regeneration biology would, in turn, undoubtedly increase the capacity to regenerate plants from in vitro harvested explants, thus expanding selection possibilities. Germplasm conservation seeks to conserve endangered and vulnerable plant species worldwide for future proliferation and development; it is also the bedrock of agricultural production.
Electrophilic Aromatic Substitution: theoretical insight into halonium ion self-existence in catalytic system
Authors: Cerkovnik Janez , Stamenković Nikola
Published: April 2021

Potential Energy Scan (PES) has already proven to be a powerful tool in computational chemistry to detect critical points in the energy path of a system, such as transition states and local minima/maxima in energy convergence. Previous studies showed a wide application of PES in many different fields of physical-chemical sciences, such as materials, supramolecular, and catalysis chemistry. Moreover, the evaluation of the basic PES algorithms at a reasonably affordable level of theory has in principle revealed good basic statistical relationships that allow further investigations in this research area. Herein, a simple and fast graphical method for accurate PES evaluation was proposed, performed at the PM7 semiempirical level of theory for catalytic systems in electrophilic aromatic substitution processes. The results presented in this case study showed a relative error ranging from 1.5 to 27.1% for most catalytic-electrophiloid systems. The treatment of such systems with PES algorithms led to novel iron(V) species and opened a completely new field in tandem transition metal-nonmetal catalysis, implying entirely new insights. Moreover, the basic statistical analysis showed that there are no significant outliers, and therefore it can be concluded that the graphical analysis approach can be used in further detailed treatment of PES results in the search for saddle points and prediction of transition state properties under known conditions in the DFT and MP2 functions discussed here. The novel graphical methodology has been introduced by two applied graphical methods, and its accuracy demonstrated in semiempirical methods provides solid results in view of future development and application in a wide range of chemical sciences.
Opioid Distribution Trends in California Post Recreational Marijuana Legalization
Authors: Anyaehie Michelle N , Pardo Christian , Johnson Elijah J , Anachebe Chucks , Piper Brian J
Published: April 2021

The US opioid overdose epidemic has risen to an all-time high. Prescription opioids often serve as a gateway to illicit opioids which have appreciable overdose potential. Recent investigations have highlighted the efficacy and safety of marijuana-based products for pain management. Providing alternative pain treatment options may help mitigate the opioid epidemic. The distribution of codeine, fentanyl, hydrocodone, morphine, and oxycodone per 100K people and by 3-digit zip codes and overdose rates from 2014 to 2018 in California, which legalized recreational marijuana in 2016, were compared to Texas, where marijuana is functionally prohibited. Drug weights were obtained from the Automation of Reports and Consolidated Orders System and converted to oral morphine milligram equivalents. Overdose data was retrieved from the Centers for Disease Control’s WONDER database. California (-43.7%) and Texas (-27.3%) showed significant reductions in cumulative opioid distribution from 2014 to 2018. Opioid distribution per 100K people decreased -38.9% in California relative to -26.4% in Texas. Opioid and heroin overdoses increased between 1999 and 2019 by +11.6% in California but +272.7% in Texas. This evidence supports marijuana legalization as a mitigating factor to the opioid epidemic and opioid misuse.
Wireless Body Area Network Control Policies for Energy-Efficient Health Monitoring
Authors: David Yair Bar , Geller Tal , Bistritz Ilai , Ben-Gal Irad , Bambos Nicholas , Khmelnitsky Evgeni
Published: April 2021

Abstract: Wireless body area networks (WBANs) have strong potential in the field of health monitoring. However, the energy consumption required for accurate monitoring limits the time between battery charges of the wearable sensors, which is a key performance factor (and can be critical in the case of implantable devices). In this paper, we study the inherent trade-off between the power consumption of the sensors and the probability of misclassifying a patient’s health state. We formulate this trade-off as a dynamic problem, in which at each step we can choose to activate a subset of sensors that provide noisy measurements of the patient’s health state. We assume that the (unknown) health state follows a Markov chain, so our problem is formulated as a partially observable Markov decision problem (POMDP). We show that all the past measurements can be summarized as a belief state on the true health state of the patient, which allows tackling the POMDP problem as an MDP on the belief state. We then empirically study the performance of a greedy one-step look-ahead policy compared to the optimal policy obtained by solving the dynamic program. For that purpose, we use an open-source Continuous Glucose Monitoring (CGM) data set of 232 patients over six months and extract the transition matrix and sensor accuracies from the data. We find that the greedy policy saves ~50% of the energy costs while reducing the misclassification costs by less than 2% compared to the most accurate policy possible that always activates all sensors. Our sensitivity analysis reveals that the greedy policy remains nearly optimal across different cost parameters and a varying number of sensors. The results also have practical importance, because while the optimal policy is too complicated, a greedy one-step look-ahead policy can be easily implemented in WBAN systems.
Information Technology and Democracy. Chances and Challenges
Authors: Czajkowski Waldemar
Published: April 2021

We live in the time of profound transformations commonly labelled with the word “globalization”. The rise of one ecological-technological-social system encompassing our whole planet is an important element of these processes. Solving big global problems demands knowledge of two complementary sorts: on the one hand – going “in depth”, on the other – going “in breadth”. The present paper assumes the second (in a sense: philosophical) perspective. It tries to analyze some relations between the development of technology (IT) and the development of democracy. The notion of democracy, its various forms and axiological reasons for it are considered first. In the subsequent chapter different consequences (both positive and negative) the IT development has for contemporary democracy are discussed. In the next chapter the evolutionary nature of the technological development is debated as well as the question of (democratic) control of this process. The development of Artificial General Intelligence is presented as a challenge for democracy
Study of How Clinical and Sociodemographic Variables Influence Chemotherapy-induced Cognitive Deterioration in Women with Breast Cancer
Authors: Rodríguez Martín Blanca , Fernandez Rodríguez Eduardo José , Sánchez Gómez Celia , Cruz Hernandez Juan Jesus , Rihuete Galve María Isabel
Published: April 2021

Background: Of the many side effects suffered by cancer patients, those related to cognitive performance have become increasingly prominent in clinical practice. We know that chemotherapy generates a series of side effects, such as nausea and vomiting, alopecia, and so on, which can be counteracted by complementary medication. However, in the case of post-chemotherapy cognitive impairment, or chemo brain, these cannot be controlled with drug therapies. However, before any intervention can be considered, it is necessary to know exactly what cognitive impairment is being triggered. For this reason, we decided to study the cognitive status of breast cancer patients. Methods: analytical, prospective, three-measure longitudinal, intrasubject unifactorial, non-probabilistic and accidental assignment study. The sample came from the Medical Oncology Department at Hospital de Salamanca, in Spain. Cognitive function (Trail Making Test and Stroop Test) was established as the primary variable; the presence of sleep disorders (Insomnia Severity Index, ISI) and anaemia (haemoglobin levels in blood) were analysed as secondary variables, in addition to intervening variables (age, stage, type of carcinoma, radiotherapy, menopause, social support network, marital status, years of schooling and employment status). Results: We recruited 151 individuals according to the selection criteria. We can confirm that factors including anaemia, menopause, patient support network and marital status, years of schooling, and employment status did affect the cognitive performance of the patients in the study. In contrast, sleep disorders, age, radiotherapy treatment, stage of disease, and type of carcinoma did not affect the cognitive performance of the cancer patients. Conclusions: Chemotherapy does impact the cognitive performance of breast cancer patients.
Multiplex-Heterogeneous Network Embedding for Drug Repositioning
Authors: Pio-Lopez Léo
Published: April 2021

Drug repositioning (also called drug repurposing) is a strategy for identifying new therapeutic targets for existing drugs. This approach is of great importance in pharmacology as it is a faster and cheaper way to develop new medical treatments. In this paper, we present, to our knowledge, the first application of multiplex-heterogeneous network embedding to drug repositioning. Network embedding learns the vector representations of nodes, opening the whole machine learning toolbox for a wide variety of applications including link prediction, node labelling or clustering. So far, the application of network embedding for drug repositioning focused on heterogeneous networks. Our approach for drug repositioning is based on multiplex-heterogeneous network embedding. Such method allows the richness and complexity of multiplex and heterogeneous networks to be projected in the same vector space. In other words, multiplex-heterogeneous networks aggregate different multi-omics data in the same network representation. We validate the approach on a task of link prediction and on a case study for SARS-CoV2 drug repositioning. Experimental results show that our approach is highly robust and effective for finding new drug-target associations.
Motion Analysis of Butterfly-Style Flapping Robot Using CFD Based on 3D-CAD Model and Experimental Flight Data
Authors: Sanuki Keisuke ,   Graduate School of Science and Technology for Future Life, Tokyo Denki University 5 Senju Asahi-cho, Adachi-ku, Tokyo 120-8551, Japan, Fujikawa Taro
Published: April 2021

In this paper, a computational fluid dynamics (CFD) analysis system based on a 3D-CAD model of a butterfly-style flapping robot using its experimental flight data is proposed. The butterfly-style flapping robot can control its attitude by changing its flapping and lead-lag angles; however, measuring the lift, thrust, and body pitch moment directly during flight is difficult. In the case of the flight motion analysis of insects, the state of flight has been photographed, and numerical analysis has been performed to obtain the flow field around the wings. However, when performing the motion analysis of hardware, it is difficult to reflect the shape of the body accurately using this method. In this study, a CFD analysis system considered the shape of the developed butterfly-style flapping robot as 3D-CAD data and analyzed the flow field around the wings using the experimental flight data of the hardware. The results of motion analysis showed that the attitude during flight differs due to the difference in lifts and body pitch moments in the flight experiment data of the hardware with different neutral angles of the flapping wings.
Small Flying Object Classifications Based on Trajectories and Support Vector Machines
Authors: Chan Jalvin Jia Xiang , Srigrarom Sutthiphong , Cao Jiawei , Wang Pengfei , Ratsamee Photchara ,   Department of Mechanical Engineering, National University of Singapore 9 Engineering Drive 1, Block EA #07-08 117575, Singapore,   Temasek Laboratories, National University of Singapore T-Lab Building, 5A Engineering Drive 1, #09-02 117411, Singapore,   Cyber Media Center, Osaka University 5-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan
Published: April 2021

This paper presents an alternative approach to identify and classify the group of small flying objects especially drones from others, notably birds and kites (inclusive of kiteflying), in near field, by examining the pattern of their flight paths and trajectories. The trajectories of the drones and other flying objects were extracted from multiple clips of videos including various natural and synthetic database. Four trajectories characteristics are observed and extracted from the object’s flight paths, i.e., heading or turning angle, curvature, pace velocity, and pace acceleration. Subsequently, principal component analyses were applied to reduce the number of these trajectory features from 4 to 2 parameters. Multi-class classification by support vector machine (SVM) with non-linear transformation kernel was used. Multiple classification models were developed by several algorithms with various transformation kernels. The hyperparameters were optimized using Bayesian optimization. The performances of the different models are compared through the prediction accuracy of the test data.
Biplanar Osteosynthesis for Severely Displaced Proximal-Third Clavicle Fracture
Authors: Zúñiga Daniela Gutiérrez , García Luisa Fernanda , Leal Jaime Andrés
Published: April 2021

Case:

We present the case of a 41-year-old man with a displaced extra-articular proximal-third clavicle fracture managed with open reduction and double-plate internal fixation. Twelve months after the procedure, the patient had recovered full range of motion and returned to work.

Conclusions:

Proximal-third clavicle fractures are infrequent injuries and are usually treated conservatively. They are associated with thoracic injuries or high-energy dorsal or cervical spinal trauma. In the case of displaced fractures and small medial fragments, orthopaedic management may have unsatisfactory results, creating symptomatic nonunions and functional limitation, we propose a biplanar osteosynthesis, which could be an effective treatment.
Peran Guru dalam Kegiatan Pembelajaran dari Rumah pada Masa Pandemi Covid-19 di SD Islam Sari Bumi Sidoarjo
Authors: Lil Ummah Alfiyatul Maghfiroh , Sartika Septi Budi
Published: April 2021

The research aims to describe the role of teachers and constraints in learning activities from home during the covid-19 pandemic at SD Islam Sari Bumi Sidoarjo. The focus of teacher role research includes pedagogical competencies, namely the ability of teachers to manage classes with 3 indicators namely planning, implementation, and assessment of learning. The research method uses a qualitative approach to phenomenological types. Research instruments use questionnaires, interviews, and documentation. Data analysis techniques using the Miles and Huberman models include data reduction, data display, verification and conclusions. The results showed that the role of teachers in learning activities from home during the covid-19 pandemic at SD Islam Sari Bumi Sidoarjo on planning indicators, and learning assessments have been achieved. As for the obstacles faced by teachers in learning activities from home during the covid-19 pandemic at SD Islam Sari Bumi Sidoarjo is a network / signal that is not good and parents who pay less attention to the child's duties because they are busy working. Further research is expected to uncover the facts through different sources, because the learning activities are done from home then the checking of the validity of the role of the teacher can be done to the student or the parents, thus the analysis and conclusion will be in-depth.
HOW THE COVID-19 CRISIS IS AFFECTING CUSTOMERS’ INTENTION TO USE ISLAMIC FINTECH SERVICES: EVIDENCE FROM INDONESIA
Authors: Nurfadilah Dety , Samidi Sudarmawan
Published: April 2021

The objective of this study is to investigate the factors that are affecting customers’ intention to use Islamic FinTech services during the Covid-19 crisis. It expands the technology acceptance model (TAM) by adding government support as a new variable for the context of Islamic FinTech services during the pandemic. Using TAM as a framework, we propose a model outlining the impact of government regulation, perceived usefulness, perceived ease of use, perceived trust, and user innovativeness on consumer attitude behaviour and the intention to use Islamic FinTech services, such as payment and peer-to-peer lending. 220 sets of data were collected from an online survey and analysed using partial least squares-structural equation modelling (PLS-SEM). The results show that government support for Islamic FinTech during the Covid-19 pandemic has had an indirect impact on attitude behaviour in using Islamic services through perceived ease of use and perceived usefulness. Attitude behaviour was found to have an impact on intention.
BETTER SAFE HAVENS DURING COVID-19: A COMPARISON BETWEEN ISLAMIC AND SELECTED FINANCIAL ASSETS
Authors: Ben Haddad Hedi , Trabelsi Nader
Published: April 2021

This study examines the safe haven properties of six assets (the S&P Technology Index, S&P GSCI Commodity Index, bitcoin, the Dow Jones Islamic Equity Index, the Dow Jones Global Sukuk Index and US Treasury bonds) during contiguous infectious diseases, employing the equity index returns of three regional markets (S&P500,S&P Europe, and S&P Asia-Pacific) over the period 2010 - 2020 Q2. In the research, information-rich methodological tools such as the Markov switching approach and the DCC-GARCH model are used. Our results suggest that Sukuk and bonds act as safe havens for different types of investors during the ongoing COVID-19 crisis. This property is, however, is not confirmed for the S&P Technology Index, Commodity Index, bitcoin or the DJ Islamic Equity Index. Moreover, using the time-varying VAR model and the new measure of pandemic uncertainty proposed by Baker et al. (2020), the results demonstrate that the COVID-19 pandemic has led to uncertainty and heightened volatility spillovers among regional equities and the safe haven assets examined. The key results of the study are robust and useful for portfolio managers and investors.
HOW HAS THE COVID-19 PANDEMIC AFFECTED THE REAL AND MONETARY SECTORS IN INDONESIA?
Authors: Yunita Patria
Published: April 2021

This study aims to find empirical evidence for the effects of the Covid-19 pandemic on the Indonesia real and monetary sectors. The real sector condition is represented by fluctuations in the farmer exchange rate in ten provinces; this rate has direct and indirect effects on farmers’ welfare. On the other hand, the condition of the monetary sector is illustrated by shifts in the consumer confidence index due to fluctuations in Islamic and conventional financial system indicators. We used a panel regression model to examine the farmer exchange rate and a binary logistic regression model to examine the consumer confidence index. The results statistically demonstrate that the pandemic conditions have affected both the real sector and the consumer confidence index of the Islamic financial sector. However, the pandemic has not affected the consumer confidence index of the conventional financial sector. This phenomenon exists because of the speculative action from conventional investors in taking risks and opportunities, which are forbidden in the Islamic context. The indicator which shifts the conventional consumer confidence index is the composite stock index (IHSG), while the Islamic consumer confidence index is shifted by changes in the Islamic money market rate, the Jakarta Islamic index and the Islamic banking capital ratio. Our empirical findings conclude that, in such a critical situation, the behaviour of conventional and Islamic consumers is totally different, thus influencing consumer confidence in each sector.
Fuzzy Representation of Environmental Flow in Multi-Objective Risk Analysis of Reservoir Operation
Authors: Li Jiqing , Huang Jing , Liang Pengteng , Lund Jay R.
Published: April 2021

In the context of water shortages, environmental flow is the key to alleviating the negative environmental impact of reservoir operation. Environmentally, the suitable stream flow for the survival and reproduction of aquatic organisms is a varying range, although most of studies now give it a fixed value, which leads to unreasonable resource allocations. In this study, we proposed a fuzzy representation of environmental flow by using the fuzzy theory and the ecological hydraulic radius. Furthermore, we used the Three Gorges-Gezhouba cascade reservoirs as a study case and Four Major Chinese Carps as indicator species. In addition, a multi-objective operation optimization model was established, which solved by the Evolver Palisade software, and a multi-objective risk analysis method was proposed based on the design reliability and risk rate of various benefit operations. The results show that: (1) Based on the environmental flow membership function, flow ranges suitable for the aquatic organism survival and reproduction at specific locations can be determined to help guide reservoir discharge. (2) Taking environmental flow membership as an optimization objective rather than a constraint is conducive to formulating environmentally friendly reservoir operation schemes and make more rational use of water resources. (3) The multi-objective risk analysis can avoid the one-sidedness of a single objective and analyze the risks brought by various benefit operations. Ecological demand has long been a factor considered when formulating reservoir operation schemes. Following the environmentally friendly operation scheme is helpful to protect the environment and maximize the overall benefits of reservoirs.
Precision cooking for printed foods via multi-wavelength lasers
Authors: Blutinger Jonathan , Tsai Alissa , Storvick Erika , Seymour Gabriel , Liu Elise , Samarelli Noà , Karthik Shravan , Meijers Yorán , Lipson Hod
Published: April 2021

Additive manufacturing of food is a method of creating three-dimensional edible products layer-by-layer. While food printers have been in use since 2007, precision cooking appliances to simultaneously cook and print food layers do not yet exist. A key challenge has been the spatially controlled delivery of cooking energy. Here, we explore precision laser cooking which offers precise temporal and spatial control over heat delivery and the ability to cook, broil, cut and otherwise transform food products via customized software-driven patterns, including through packaging. Using chicken as a model food, we combine the cooking capabilities of a blue laser (λ = 445 nm), a near-infrared (NIR) laser (λ = 980 nm), and a mid-infrared (MIR) laser (λ = 10.6 µm) to broil printed chicken and find that IR light browns more efficiently than blue light, NIR light can brown and cook foods through packaging, laser-cooked foods experience about 50% less cooking loss than foods broiled in an oven, and calculate the cooking resolution of a laser to be approximately 1 mm. Infusing software into the cooking process will enable more creative food design, allow individuals to more precisely customize their meals, disintermediate food supply chains, streamline at-home food production, and generate horizontal markets for this burgeoning industry.
Potential of Nb2O5 nanofibers in photocatalytic response for organic pollutants remediation
Authors: Jesus Edson Tobias , Moreira Ailton José , Sá Mayara Coelho , Freschi Gian Paulo Giovanni , Joya Miryam Rincón , Li Maximo Siu , Paris Elaine Cristina
Published: April 2021

Due to the pollution caused by different organic pollutants, various photocatalytic nanomaterials for environmental remediation have been promoted. In this study, Nb2O5 nanofibers were obtained by electrospinning technique, presenting controlled crystallinity and high specific surface area to improve the photoactivity response. The structural characterization indicated Nb2O5 nanofibres with orthorhombic phase formation, and the photoluminescence measurements showed different energy levels contributing to the electronic transition events. The nanofibers with a bandgap up to 3.6 eV were applied to photocatalysis of dyes [Rhodamine B (RhB) or Methylene Blue (MB)], and Prozac®, listed as an emergent pollutant. In the optimized condition (pH = 9), the RhB and MB photocatalysis was 59% and 93% more efficient than photolysis due to ζ = − 50 ± 5 mV for EtOH_550 sample that increased the interaction with MB (cationic) compared to RhB unprotonated (pKa = 3.7). Therefore, Prozac® (pKa = 10.7) was selected due to protonated form at pH = 9 and showed 68% ±1 adsorption in 30 min for EtOH_550. The Prozac® photocatalytic degradation under UV light irradiation was up to 17% higher than the photolytic degradation. The formation of hydroxyl radicals in the photocatalytic system (EtOH_550) was proven by the Coumarine probe assay, corroborating with the greater amount of α-[2-(Methylamino)ethyl]benzylalcohol (MAEB), a by-product obtained after Prozac® oxidation. Additionally, the material achieved specific catalytic activity for the different organic compounds (RhB, MB, or Prozac®), showing that only using dyes may not be ideal to conclude the great material applicability in environmental remediation studies. Therefore, Nb2O5 nanofibers were efficient for the degradation of three different pollutants under UV light, proving to be a viable alternative for environmental remediation.
Automated classification of human lung sound signals using phase space representation of intrinsic mode function
Authors: Khan Sibghatullah I. , Palodiya Vikram , Poluboyina Lavanya
Published: April 2021

Bronchiectasis and chronic obstructive pulmonary disease (COPD) are common human lung diseases. In general, the expert pulmonologistcarries preliminary screening and detection of these lung abnormalities by listening to the adventitious lung sounds. The present paper is an attempt towards the automatic detection of adventitious lung sounds ofBronchiectasis,COPD from normal lung sounds of healthy subjects. For classification of the lung sounds into a normaland adventitious category, we obtain features from phase space representation (PSR). At first, the empirical mode decomposition (EMD) is applied to lung sound signals to obtain intrinsic mode functions (IMFs). The IMFs are then further processed to construct two dimensional (2D) and three dimensional (3D) PSR. The feature space includes the 95% confidence ellipse area and interquartile range (IQR) of Euclidian distances computed from 2D and 3D PSRs, respectively. The process is carried out for the first four IMFs correspondings to normal and adventitious lung sound signals. The computed features depicta significant ability to discriminate the two categories of lung sound signals.To perform classification, we use the least square support vector machine with two kernels, namely, polynomial and radial basis function (RBF).Simulation outcomes on ICBHI 2017 lung sound dataset show the ability of the proposed method in effectively classifying normal and adventitious lung sound signals. LS-SVM is employing RBF kernel provides the highest classification accuracy of 97.67 % over feature space constituted by first, second, and fourth IMF.
Design of All-Optical Directional Coupler Using Plasmonic MIM Waveguide for Switching Applications
Authors: Nanda Rupalin , Rath Ramakrushna , Swarnakar Sandip , Kumar Santosh
Published: April 2021

In this paper, we have proposed, analyzed, and verified theperformance of an optimized plasmonic 10-dB directional coupler and a 3-dB directional coupler in 2-D plasmonic waveguides using finite-difference-time-domain (FDTD) method. A plasmonic 10-dB directional coupler and a 3-dB directional coupler are based on the metal-insulator-metal (MIM) slab waveguide and analyzed at the telecommunication wavelength (λ) of 1550 nm. Here, coupling and transmission characteristics are analyzed with the optimized separation distance between the two parallel waveguides. The developed approach ensures the minimization of the crosstalk and overall directional coupler length via simultaneous adjustment of the separation distance between the parallel waveguide and length of the linear waveguide. Then an optimized structure is acquired by trading off between coupling length and separation distance. The proposed 10-dB directional coupler and 3-dB directional coupler features good energy confinement, ultra-compact and low propagation loss, which has potential applications in photonic integrated devices, optical signal processors, and other all-optical switching devices.
Tanshinone IIA Prevents Acetaminophen-Induced Nephrotoxicity by Stimulating the Efflux of its Toxic Intermediate Metabolite From Kidney
Authors: Zhang Xiqian , Wang Ting , Li Ruina , Yang Yujie , Long Fangyi , He Qin , Xu Min , Wang Ling , Jiang Xuehua
Published: April 2021

It’s known that acetaminophen (APAP) overdose often leads to hepatotoxicity and nephrotoxicity. Previous studies have shown that Tanshinone IIA (Tan IIA) could protect against APAP-induced hepatotoxicity via activating the Nrf2 pathway. In the present study, we further investigated the preventative effect of Tan IIA to APAP-induced nephrotoxicity. Oral supplementation of Tan IIA (30 mg/kg/day) prior to APAP intoxication (200 mg/kg) dramatically reduced APAP-induced nephrotoxicity as evidenced by histopathological evaluation and serum CRE levels. Tan IIA pretreatment promoted the efflux of the toxic intermediate metabolite N-acetyl-p-benzoquinone imine (NAPQI) from mouse kidney, thus reducing its injury to tissue. After Tan IIA pretreatment, significant induction of Nrf2, Mrp2, and Mrp4 mRNA and protein expression was detected in Nrf2+/+ mice kidneys, however, much lower increase of Mrp2 and Mrp4 mRNA and protein expression was observed in Nrf2−/− mice kidneys. Consistent with our observations in vivo, Tan IIA increased the mRNA and protein expression of Nrf2-MRP2/4 pathway and promoted the nuclear Nrf2 accumulation compared with APAP treatment alone in HK-2 cells. Collectively, the findings in this study demonstrated that Tan IIA facilitates the clearance of toxic intermediate metabolite NAPQI from the kidney by up-regulating the Nrf2-Mrp2/4 pathway, thereby, performing a preventive effect against APAP-induced nephrotoxicity.
Joint Transcriptomic and Metabolomic Analysis Reveals the Mechanism of Low Temperature Tolerance in Hosta Ventricosa
Authors: Zhuang QianQian , Chen Shaopeng , Jua ZhiXin , Yue Yao
Published: April 2021

Background: Hosta ventricosa is a robust ornamental perennial plant that can tolerate low temperatures, and which is widely used in urban landscaping design in Northeast China. However, the mechanism of cold stress tolerance in this species is unclear. Methods:This study used a combination of transcriptomic and metabolomic analysis to explore the mechanism of low temperature tolerance in H. ventricosa.Results: A total of 12 059 differentially expressed genes (DEGs) and 131 differentially expressed metabolites were obtained, which were mainly concentrated in the signal transduction and phenylpropanoid metabolic pathways. In the process of low temperature signal transduction, H. ventricosa is mainly through the ion channels on the three cell membranes of COLD, CNGCs and CRLK to transmit Ca2+ inside and outside the cell to sense temperature changes, and stimulate SCRM to combine with DREB through the MAPK signal pathway and Ca2+ signal sensors such as CBL. Strengthen the low temperature resistance of H. ventricosa. The pathways of phenylpropanoid and flavonoid metabolism represent the main mechanism of low temperature tolerance in this species. The plant protects itself from low temperature damage by increasing its content of genistein, scopolentin and scopolin. It is speculated that H. ventricosa can also adjust the content ratio of sinapyl alcohol and coniferyl alcohol and thereby alter the morphological structure of its cell walls and so increase its resistance to low temperatures.Conclusions: In H. ventricosa that is subjected to low temperature stress, temperature changes are perceived through COLD, CNGCs and CRLK, and protection from low temperature damage is achieved by an increase in the levels of genistein, scopolentin and scopolin through the pathways of phenylpropanoid biosynthesis and flavonoid biosynthesis.
The applied ability in infant crawling and the importance of prone motor experience for subsequent development
Authors: Yamamoto Shimpei , Lee Yeonghee , Matsumura Umi , Tsurusaki Toshiya
Published: April 2021

Background: In the process of motor learning in human, many movement patterns, that is, many variations, are tried first, and more efficient movements come to be selected based on experience of trial and error. Although this process for selection (i.e., variability) is particularly active in infancy neurodevelopment and motor development, few studies have explored the variation / variability of infant crawling.Aims: The first is to investigate the difference in the variability of hands-knees crawling between typically developing infants with and without belly crawling experience. The second is to examine the relationship between development after 2 years of age and crawling variability.Study design: This study was longitudinal. Crawling variability was evaluated by encoding crawling variation in infants not pointed out neurological or orthopedic problems. We investigated the differences in the quantity and content of hands-knees crawling variation between infants with and without belly crawling experience. Further, we retrospectively explored the difference in the whole quantity of crawling variation during both belly and hands-knees crawling stages between two groups, suspicious and normal in DENVER Ⅱ conducted after 2 years of age.Results: The quantity of hands-knees crawling variation was significantly smaller in the group with belly crawling experience than the group without the experience. On the other hand, the content of hands-knees crawling variation was almost the same between these two groups. In addition, there was a significant difference in the whole quantity of crawling variation between the suspicious and the normal group.Conclusions: The current study shows that infants improve the learning efficiency and variability of hands-knees crawling movements by applying skills acquired through belly crawling experience, which provides one interpretation of the importance of sensorimotor experience in the prone position in infancy. Furthermore, this study suggests a link between crawling variability and subsequent development.
Solving localized wave solutions of the derivative nonlinear Schrodinger equation using an improved PINN method
Authors: Pu J.C. , Li J. , Chen Y.
Published: April 2021

The solving of the derivative nonlinear Schrodinger equation (DNLS) has attracted considerable attention in theoretical analysis and physical applications. Based on the physicsinformed neural network (PINN) which has been put forward to uncover dynamical behaviors of nonlinear partial different equation from spatiotemporal data directly, an improved PINN method with neuron-wise locally adaptive activation function is presented to derive localized wave solutions of the DNLS in complex space. In order to compare the performance of above two methods, we reveal the dynamical behaviors and error analysis for localized wave solutions which include one-rational soliton solution, genuine rational soliton solutions and rogue wave solution of the DNLS by employing two methods, also exhibit vivid diagrams and detailed analysis. The numerical results demonstrate the improved method has faster convergence and better simulation effect. On the bases of the improved method, the effects for different numbers of initial points sampled, residual collocation points sampled, network layers, neurons per hidden layer on the second order genuine rational soliton solution dynamics of the DNLS are considered, and the
relevant analysis when the locally adaptive activation function chooses different initial values of scalable parameters are also exhibited in the simulation of the two-order rogue wave solution.
Prey Abundance Regulating the Response of an Important Marine Eel Species Conger Myriaster Growth to Water Temperature
Authors: Mu Xiuxia , Zhang Chongliang , Xu Binduo , Ji Yupeng , Xue Ying , Ren Yiping
Published: April 2021

Whitespotted conger (Conger myriaster) is a commercially important species in East Asia but the fisheries stock has drastically declined in recent years. Environmental changes are assumed to have profound impacts on the growth pattern of this species, yet the mechanisms that regulate growth remain poorly understood. Here we used otolith measurements to establish growth chronologies of 9-year period (2010–2018) for whitespotted conger in the Yellow Sea and evaluated the effects of environmental variables on the growth pattern. Linear mixed-effects models were used to explain growth variation with abiotic and biotic environmental variables, including seasonal water temperature, prey availability, and population density, and to assess age-dependent responses in growth and the interactions between abiotic and biotic factors. The results indicated that the growth of whitespotted conger positively correlated with spring sea bottom temperature (March-May) and prey per capita, and the influence of prey availability became larger with increasing ages. The model detected significant negative interactions between sea temperature and prey availability, indicating a higher degree of temperature-dependent growth when prey availability was low. Our findings imply that the growth of whitespotted conger is less likely to be influenced by food availability when the spring water temperature is high in the Yellow Sea, and a combination of cold spring and low food availability may result in substantial constrained growth. This study provided the first evidence for the joint effects of abiotic and biotic factors on the growth variation of whitespotted conger, and the information may contribute to sustainable management policies.
Investigation the effects of cation/anion structure on distribution of Thiophene between IL-rich and Hydrocarbon-rich phases by QSPR approach
Authors: Moheb-Aleaba Zahra , Khosravi-Nikou Mohammadreza
Published: April 2021

Selecting an appropriate ionic liquid as extraction solvent for extracting sulfur compounds from fuel, is a promising way to reduce SOx emissions and to prevent environmental pollution. In this regard, the best structural descriptors of different cation and anion, which play an important role on the thiophene distribution between ionic liquid (IL) and hydrocarbon phases in the ternary systems, that is helpful for selecting a proper IL, have been investigated using quantitative structure − property relationship (QSPR) approach. Five different datasets were collected from the literature containing {(Cation/[NTf2] − thiophene − n-heptane), (Cation/[NTf2] − thiophene − n-hexane), (Cation/[FAP] − thiophene − n-heptane), (Cation/[TCM] − thiophene − n-heptane), ([C2MIM]/Anion − thiophene − hydrocarbon), ([C8MIM]/Anion–thiophene − hydrocarbon)} with 664 data points. By investigating the various kinds of molecular descriptors of 1D, 2D and 3D, it was found that the increment of Spanning Tree Number (STN) descriptor as cation structure descriptor, causes a decrease in mole fraction of thiophene in IL-rich phase due to the increase in steric hindrance. STN descriptor reflects the complexity of structure of cation and the information about steric hindrance. Also, it was found that an increase in E1p value as anion structure descriptor leads to the decrement of mole fraction of thiophene in IL-rich phase, in order to increase the interaction between cation and anion in ionic liquid, that reduced the available space of cation to interact with thiophene. The E1p descriptor represents the density of atoms projected along the length or unfilled space of the anion, thus it is informative of the accessibility of them by thiophene.
MarkerCount: A stable, count-based cell type identifier for single cell RNA-Seq experiments
Authors: Kim Hanbyeol , Lee Joongho , Kang Keunsoo , Yoon Seokhyun
Published: April 2021

Cell type identification is a key step to downstream analysis of single cell RNA-seq experiments. Indispensible information for this is gene expression, which is used to cluster cells, train the model and set rejection thresholds. Problem is they are subject to batch effect arising from different platforms and preprocessing. We present MarkerCount, which uses the number of markers expressed regardless of their expression level to initially identify cell types and, then, reassign cell type in cluster-basis. MarkerCount works both in reference and marker-based mode, where the latter utilizes only the existing lists of markers, while the former required pre-annotated dataset to train the model. The performance was evaluated and compared with the existing identifiers, both marker and reference-based, that can be customized with publicly available datasets and marker DB. The results show that MarkerCount provides a stable performance when comparing with other reference-based and marker-based cell type identifiers.