bluuebunny/crossref_metadata_2025 huggingface dataset:
Depth Estimation for Egocentric Rehabilitation Monitoring Using Deep Learning Algorithms
Authors: Izadmehr Yasaman , Satizábal Héctor F. , Aminian Kamiar , Perez-Uribe Andres
Published: June 2022

Upper limb impairment is one of the most common problems for people with neurological disabilities, affecting their activity, quality of life (QOL), and independence. Objective assessment of upper limb performance is a promising way to help patients with neurological upper limb disorders. By using wearable sensors, such as an egocentric camera, it is possible to monitor and objectively assess patients’ actual performance in activities of daily life (ADLs). We analyzed the possibility of using Deep Learning models for depth estimation based on a single RGB image to allow the monitoring of patients with 2D (RGB) cameras. We conducted experiments placing objects at different distances from the camera and varying the lighting conditions to evaluate the performance of the depth estimation provided by two deep learning models (MiDaS & Alhashim). Finally, we integrated the best performing model for depth-estimation (MiDaS) with other Deep Learning models for hand (MediaPipe) and object detection (YOLO) and evaluated the system in a task of hand-object interaction. Our tests showed that our final system has a 78% performance in detecting interactions, while the reference performance using a 3D (depth) camera is 84%.
Influence of Pulse Amplitude and Frequency on Plasma Properties of a Pulsed Low-Current High-Voltage Discharge Operated at Atmospheric Pressure
Authors: Szulc Michał , Forster Günter , Marques-Lopez Jose-Luis , Schein Jochen
Published: June 2022

Non-equilibrium conditions in plasma are often achieved by pulsed power delivery, where the pulse shape and repetition rate determine the properties of the plasma constituents and thus its chemical reactivity. The evaluation of the latter is becoming increasingly important to understand the observed effects, especially when new application fields are targeted. The composition of the plasma and the occurring chemical reactions can be calculated using various models. Thereby, the temperature of the electrons, the electron number density, as well as the heavy particle temperature are usually required as the basis of such calculations. In this work, the influence of pulse amplitude and repetition rate on these plasma parameters is determined by laser scattering for a low-current, high-voltage discharge operated with nitrogen at atmospheric pressure. In particular, the characteristic parameters regarding the plasma free electrons in such discharges have not yet been experimentally determined to this extent. The results are validated by spectroscopic measurements, i.e., the electron density is estimated from the Stark broadening of the hydrogen beta line and the heavy particle temperature is estimated by fitting the spectrum of nitrogen molecular transitions. Depending on the operating frequency, a pure nitrogen discharge with an input power of about 650 W displays an electron density between 1.7×1021m−3 and 2.0×1021m−3 with electron temperatures in the range of 40,000 K and heavy particle temperatures of about 6000 K in the core of the discharge channel. Furthermore, a relatively slow electron recombination rate in the range of 20 µs is observed.
Overall Heat Transfer Coefficient Evaluation Method for Uncracked Hydrocarbon Fuel in a Regeneratively-Cooled Heat Exchanger of a Scramjet
Authors: Li Haowei , Lin Guowei , Xu Qing , Fang Xiaojia , Xian Shengxian
Published: June 2022

Regenerative cooling is critical for the thermal protection of hypersonic propulsion systems, wherein the flow and heat transfer characteristics of the hydrocarbon fuel in the cooling channel are crucial. Restricted by measurement, the distribution of the fuel temperature inside the cooling channel cannot be directly detected. As a result, the measurement of the convective heat transfer coefficient is more an overall heat transfer coefficient. Furthermore, the existing overall heat transfer coefficient calculation method is derived without considering the flow state of the hydrocarbon fuel in the cooling channel, which should be taken into consideration. Therefore, a modified calculation method of the overall heat transfer coefficient is proposed in this study. The results of the characteristics of the turbulence-related parameters show that the overall heat transfer coefficient is mainly determined by the effective thermal conductivity and surface convective heat transfer coefficient, which are related to the fuel temperature and flow state. Furthermore, the existing method might overestimate the overall heat transfer coefficient. The modified method is suitable for the calculation of the overall heat transfer coefficient in the heat transfer enhancement process in a cooling channel.
Influence of Soil Colloids on Ni Adsorption and Transport in the Saturated Porous Media: Effects of pH, Ionic Strength, and Humic Acid
Authors: Wei Zhanxi , Zhu Yidan , Wang Yuanyuan , Song Zefeng , Wu Yuanzhao , Ma Wenli , Hou Yongxia , Zhang Wenqing , Yang Yuesuo
Published: June 2022

Natural colloids are widely distributed in soil and groundwater. Due to their specific characteristics, colloids can actively involve various transport contaminants, resulting in a complicated fate and the transport of heavy metals to the environment. This study investigated the effects of soil colloids on the adsorption and transport of Ni2+ in saturated porous media under different conditions, including pH, ion strength (IS), and humic acid (HA), because these indexes are non-negligible in the fates of various organic or inorganic matters in the subsurface environment. The results indicate that Ni2+ adsorption by soil colloids slightly increased from 17% to 25% with the increase of pH from 5.5 to 7.5 at the IS of 30 mmol·L−1, whilst it significantly reduced from 55% to 17% with the increase of IS from 0 to 30 mmol·L−1 at a pH of 5.5. Both Langmuir and Freundlich models can fit the adsorption isotherms of Ni2+ on soil colloids and quartz sand. According to the column experiment, the presence of soil colloids increased the initial penetration rate, but could not increase the final transport efficiency of Ni2+ in the effluent. The presence of soil colloids has weakened the effect of IS on Ni2+ transport in the sand column. Moreover, this experiment implies that HA remarkably decreased the Ni2+ transport efficiency from 71.3% to 58.0% in the presence of soil colloids and that there was no significant difference in the HA effect on the Ni2+ transport in the absence of soil colloids.
Dynamic Innovation Information System (DIIS) for a New Management Age
Authors: Gallego-García Sergio , Ren Diqian , Gallego-García Diego , Pérez-García Salvador , García-García Manuel
Published: June 2022

Innovations are essential for global development and market dynamics. Innovation management is central to organizations for gaining adaptability and dynamic capabilities to ensure their sustainability over time. Right decisions are essential for the implementation of innovations. However, on many occasions, especially in the product development process, decisions are taken based on static analysis, qualitative criteria, questionnaires, and/or quantitative evaluations that are outdated. Moreover, many innovation developments do not consider the existing databases in their information systems of similar innovation projects, especially in the early phases of new innovations when evaluations are mainly driven by area, group, or person. Furthermore, inventions are introduced in different regions, plants, and socio-economic situations, providing different results. In this context, considering that innovations shape our current and future world, including all products and services, as well as how humans, organizations, and machines interact, the significance of the paper is clear. Therefore, it is necessary to develop an innovation management model based on the Viable System Model to cope with any potential future environment based on internal organizational capabilities. For this purpose, the paper designs a Digital Ecosystem for the Fourth Industrial Revolution (DE4.0) based on the Plan-Do-Check-Act methodology applicable to any information system consisting of a digital twin, a simulation model, databases from existing information systems, and quality management techniques. This DE4.0 provides a huge advantage for the applicability and scalability of innovations as it allows one to plan, monitor, assess, and improve. Moreover, based on the conceptual model, a generic project evaluation scheme is developed, providing a platform for innovation project management and control during the whole innovation life cycle. As a result, the research provides a scientific and practical contribution for an integrated management of innovations based on the best information and set of techniques available. Based on this framework, a supply-chain case study is developed. The results show how, depending on the intended goals, the past experiences, the evolution of the innovation, and the innovation scope, indicators can be influenced towards reaching the initial goals and reducing the innovation risks. Finally, a discussion about the potential use and role of the DE4.0 for innovation projects and the related learning process is performed.
ExpGen: A 2-Step Vulnerability Exploitability Evaluation Solution for Binary Programs under ASLR Environment
Authors: Huang Hui , Lu Yuliang , Pan Zulie , Zhu Kailong , Yu Lu , Zhang Liqun
Published: June 2022

Current automatic exploit generation solutions generally adopt an 1-step exploit generation philosophy and neglect the potential difference between analysis-time environment and runtime environment. Therefore, they usually fail in evaluating exploitability for vulnerable programs running in an ASLR environment. We propose ExpGen, a 2-step vulnerability-exploitability evaluation solution for binary programs running in an ASLR environment, with three novel techniques introduced, separately partial-exploit sensitive-POC generation, exploitation context sensitive analysis-time exploit generation, and runtime exploit relocation. ExpGen firstly generates an analysis-time exploit that can carry out all the desired exploitation steps through applying the first two techniques in an iterative manner, then dynamically gaps the address-space layout differences between the analysis-time environment and runtime environment by adopting the runtime exploit-relocation technique, making the analysis-time exploit dynamically adaptable to the runtime exploitation session. Using a benchmark containing six test programs, 10 CTF&RHG programs and four real-world applications with known vulnerabilities, we demonstrate that ExpGen can effectively generate partial exploit input that carries out some address-leakage event and provide a complete automated exploitability evaluation workflow on vulnerable programs running in the ASLR environment.
Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
Authors: Janczyk Kamil , Rumiński Jacek , Neumann Tomasz , Głowacka Natalia , Wiśniewski Piotr
Published: June 2022

Age prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this study, we used low-resolution, dual-energy, full-body X-ray absorptiometry images to train deep learning models to predict age. In particular, we proposed a preprocessing framework and adapted many partially pretrained convolutional neural network (CNN) models to predict the age of children and young adults. We used a new dataset of 910 multispectral images that were weakly annotated by specialists. The experimental results showed that the proposed preprocessing techniques and the adapted approach to the CNN model achieved a discrepancy between chronological age and predicted age of around 15.56 months for low-resolution whole-body X-rays. Furthermore, we found that the main factor that influenced age prediction scores was spatial features, not multispectral features.
Reflectance Transformation Imaging as a Tool for Computer-Aided Visual Inspection
Authors: Zendagui Abir , Le Goïc Gaëtan , Chatoux Hermine , Thomas Jean-Baptiste , Jochum Pierre , Maniglier Stéphane , Mansouri Alamin
Published: June 2022

This work investigates the use of Reflectance Transformation Imaging (RTI) rendering for visual inspection. This imaging technique is being used more and more often for the inspection of the visual quality of manufactured surfaces. It allows reconstructing a dynamic virtual rendering of a surface from the acquisition of a sequence of images where only the illumination direction varies. We investigate, through psychometric experimentation, the influence of different essential parameters in the RTI approach, including modeling methods, the number of lighting positions and the measurement scale. In addition, to include the dynamic aspect of perception mechanisms in the methodology, the psychometric experiments are based on a design of experiments approach and conducted on reconstructed visual rendering videos. The proposed methodology is applied to different industrial surfaces. The results show that the RTI approach can be a relevant tool for computer-aided visual inspection. The proposed methodology makes it possible to objectively quantify the influence of RTI acquisition and processing factors on the perception of visual properties, and the results obtained show that their impact in terms of visual perception can be significant.
Non-Invasive-Monitoring Methodology for the Evaluation of Environmental Impacts on Istrian Stone Surfaces in Venice
Authors: Gnemmi Margherita , Falchi Laura , Zendri Elisabetta
Published: June 2022

This work proposes a non-invasive, affordable, and easily reproducible methodology for monitoring limestone surfaces vulnerability. The proposed methodology integrates the study of environmental factors impacting limestone surfaces with physical–chemical and morphological observations of historical Istria stone surfaces in Venice. Pollutant trends of particulate matters (PPM), NO2, SO2, O3, and the meteorological forcing were considered over a 20-year period. To collect information on the conservation state of stone surfaces, visual, optical microscopy observation, chemical analysis via FT-IR-ATR spectroscopy, and the evaluation of morphological and profilometric parameters by digitalizing the surface of silicone molds were carried out. The surfaces of Ca’ Foscari, Ca’ Dolfin, and Garzoni Palace were monitored in 2015 and five years after. Indicators, such as site, sheltered or exposed position, and location of the stone surfaces, were taken into consideration for data interpretation. A relationship between surface conservation state and the proposed environmental indicators has been evaluated. Deposits and crusts were found only in the courtyard façade and in sheltered points, reflecting SO2 reduction; large, eroded areas were found on exposed surfaces related to rain runoff and possibly related to the locally high NOx levels.
Self-Organized Criticality of Precipitation in the Rainy Season in East China
Authors: Qian Zhonghua , Xiao Yuxin , Wang Luyao , Zhou Qianjin
Published: June 2022

Based on daily precipitation data from 1960 to 2017 in the rainy season in east China, to a given percentile threshold of one observation station, the time that precipitation spends below threshold is defined as quiet time τ. The probability density functions τ in different thresholds follow power-law distributions with exponent β of approximately 1.2 in the day, pentad and ten-day period time scales, respectively. The probability density functions τ in different regions follow the same rules, too. Compared with sandpile model, Γ function describing the collapse behavior can effectively scale the quiet time distribution of precipitation events. These results confirm the assumption that for observation station data and low-resolution precipitation data, even in China, affected by complex weather and climate systems, precipitation is still a real world example of self-organized criticality in synoptic. Moreover, exponent β of the probability density function τ, mean quiet time τ¯q and hazard function Hq of quiet times can give sensitive regions of precipitation events in China. Usual intensity precipitation events (UPEs) easily occur and cluster mainly in the middle Yangtze River basin, east of the Sichuan Province and north of the Gansu Province. Extreme intensity precipitation events (EPEs) more easily occur in northern China in the rainy season. UPEs in the Hubei Province and the Hunan Province are more likely to occur in the future. EPEs in the eastern Sichuan Province, the Guizhou Province, the Guangxi Province and Northeast China are more likely to occur.
Improving the Performance of Pipeline Leak Detection Algorithms for the Mobile Monitoring of Methane Leaks
Authors: Xia Tian , Raneses Julia , Batterman Stuart
Published: June 2022

Methane (CH4) is the major component of natural gas, a potent greenhouse gas, and a precursor for the formation of tropospheric ozone. Sizable CH4 releases can occur during gas extraction, distribution, and use, thus, the detection and the control of leaks can help to reduce emissions. This study develops, refines, and tests algorithms for detecting CH4 peaks and estimating the background levels of CH4 using mobile monitoring, an approach that has been used to determine the location and the magnitude of pipeline leaks in a number of cities. The algorithm uses four passes of the data to provide initial and refined estimates of baseline levels, peak excursions above baseline, peak locations, peak start and stop times, and indicators of potential issues, such as a baseline shift. Peaks that are adjacent in time or in space are merged using explicit criteria. The algorithm is refined and tested using 1-s near-ground CH4 measurements collected on 20 days while driving about 1100 km on surface streets in Detroit, Michigan by the Michigan Pollution Assessment Laboratory (MPAL). Sensitivity and other analyses are used to evaluate the effects of each parameter and to recommend a parameter set for general applications. The new algorithm improves the baseline estimates, increases sensitivity, and more consistently merges nearby peaks. Comparisons of two data subsets show that results are repeatable and reliable. In the field study application, we detected 534 distinct CH4 peaks, equivalent to ~0.5 peaks per km traveled; larger peaks detected at nine locations on multiple occasions suggested sizable pipeline leaks or possibly other CH4 sources.
CT-Integral on Interval-Valued Sugeno Probability Measure and Its Application in Multi-Criteria Decision-Making Problems
Authors: Yang Hong , Shang Liyan , Gong Zengtai
Published: June 2022

It is well known that the complexity of the decision-making environment frequently coexists with the diversity of linguistic information in the decision-making process. In order to solve this kind of uncertain multi-criteria decision-making problem, reasonable measures and integrals should be established. In this paper, the discrete expression of the CT-integral on the interval-valued Sugeno probability measure is proposed. The CT-integral is the Choquet integral when the t-norm is T(x,y)=xy in the CT-integral and is a pre-aggregation function. Then, the CT-integral on interval-valued Sugeno probability measure is applied to solve end-of-life (EOL) strategy in order to determine multi-criteria decision-making problems. Compared with the general Choquet integral, the method proposed in this paper significantly improves the calculation process, that is, the calculation is simpler and the amount of calculation is smaller. A case study was performed in order to validate the effectiveness of this conclusion.
On Newton’s First Law of Motion
Authors: Peskir Goran
Published: June 2022

We present arguments in support of the view that Newton’s first law of motion extends itself to stochastic motions as follows: Every entity perseveres in its state of independent and stationary increments except insofar as it is compelled to change its state by forces impressed. Some of the far-reaching consequences of the extended law are briefly touched upon as well.
Transition Metal Dichalcogenides for High−Performance Aqueous Zinc Ion Batteries
Authors: Liu Baishan
Published: June 2022

Aqueous zinc ion batteries (ZIBs) with cost—effectiveness, air stability, and remarkable energy density have attracted increasing attention for potential energy storage system applications. The unique electrical properties and competitive layer spacing of transition metal dichalcogenides (TMDs) provide dramatical freedom for facilitating ion diffusion and intercalation, making TMDs suitable for ZIB cathode materials. The recently updated advance of TMDs for high−performance ZIB cathode materials have been summarized in this review. In particular, the key modification strategies of TMDs for realizing the full potential in ZIBs are highlighted. Finally, the insights for further development of TMDs as ZIB cathodes are proposed, to guide the research directions related to the design of aqueous ZIBs while approaching the theoretical performance metrics.
Effect of x on the Electrochemical Performance of Two-Layered Cathode Materials xLi2MnO3–(1−x)LiNi0.5Mn0.5O2
Authors: Nazario-Naveda Renny , Rojas-Flores Segundo , Juárez-Cortijo Luisa , Gallozzo-Cardenas Moises , Díaz Félix N. , Angelats-Silva Luis , Benites Santiago M.
Published: June 2022

In our study, the cathodic material xLi2MnO3–(1−x)LiNi0.5Mn0.5O2 was synthesized by means of the co-precipitation technique. The effect of x (proportion of components Li2MnO3 and LiNi0.5Mn0.5O2) on the structural, morphological, and electrochemical performance of the material was evaluated. Materials were structurally characterized using X-ray diffraction (XRD), and the morphological analysis was performed using the scanning electron microscopy (SEM) technique, while charge–discharge curves and differential capacity and impedance spectroscopy (EIS) were used to study the electrochemical behavior. The results confirm the formation of the structures with two phases corresponding to the rhombohedral space group R3m and the monoclinic space group C2/m, which was associated to the components of the layered material. Very dense agglomerations of particles between 10 and 20 µm were also observed. In addition, the increase in the proportion of the LiNi0.5Mn0.5O2 component affected the initial irreversible capacity and the Li2MnO3 layer’s activation and cycling performance, suggesting an optimal chemical ratio of the material’s component layers to ensure high energy density and long-term durability.
Structural and Functional Basis of JAMM Deubiquitinating Enzymes in Disease
Authors: Pan Xin , Wu Sihua , Wei Wenping , Chen Zixuan , Wu Yong , Gong Kaizheng
Published: June 2022

Deubiquitinating enzymes (DUBs) are a group of proteases that are important for maintaining cell homeostasis by regulating the balance between ubiquitination and deubiquitination. As the only known metalloproteinase family of DUBs, JAB1/MPN/Mov34 metalloenzymes (JAMMs) are specifically associated with tumorigenesis and immunological and inflammatory diseases at multiple levels. The far smaller numbers and distinct catalytic mechanism of JAMMs render them attractive drug targets. Currently, several JAMM inhibitors have been successfully developed and have shown promising therapeutic efficacy. To gain greater insight into JAMMs, in this review, we focus on several key proteins in this family, including AMSH, AMSH-LP, BRCC36, Rpn11, and CSN5, and emphatically discuss their structural basis, diverse functions, catalytic mechanism, and current reported inhibitors targeting JAMMs. These advances set the stage for the exploitation of JAMMs as a target for the treatment of various diseases.
Alleviating Heavy Metal Toxicity in Milk and Water through a Synergistic Approach of Absorption Technique and High Voltage Atmospheric Cold Plasma and Probable Rheological Changes
Authors: Habib Mohammad Ruzlan , Mahanta Shikhadri , Jolly Yeasmin Nahar , Moore Janie McClurkin
Published: June 2022

In this study, we combined atmospheric pressure cold plasma, a novel treatment technology, with an absorption technique with soybean husk to remove Pb and Cd from milk. Different combinations of treatment duration, voltage, and post treatment retention time were used to determine the effectiveness of cold plasma. Soybean husk was used for metal extraction, and it was observed that when the milk samples were plasma treated with a discharge voltage of 50 kV for 2 min and held for 24 h, the highest mean elimination of about 27.37% for Pb and 14.89% for Cd was obtained. Reactive oxygen and nitrogen species produced from plasma treatment were identified using Optical Emission Spectra analysis. A high voltage of 50 kV plasma for a 2 min duration could produce 500 ± 100 ppm of ozone concentration inside the treated package. The value of ΔE, which indicates overall color difference measurement, was significantly (p < 0.05) higher in all the treated samples than control samples. However, in the frequency range from 0.01 to 100 Hz, there was not much difference between the control and treated sample in the frequency sweep test. The identified functional groups at different wavenumbers (cm−1) in the treated samples were found to be similar compared to the control samples.
Optimized AAV Vectors for TMC1 Gene Therapy in a Humanized Mouse Model of DFNB7/11
Authors: Marcovich Irina , Baer Nicholas K. , Shubina-Oleinik Olga , Eclov Rachel , Beard Clayton W. , Holt Jeffrey R.
Published: June 2022

Gene therapy for genetic hearing loss is an emerging therapeutic modality for hearing restoration. However, the approach has not yet been translated into clinical application. To further develop inner-ear gene therapy, we engineered a novel mouse model bearing a human mutation in the transmembrane channel-1 gene (Tmc1) and characterized the auditory phenotype of the mice. TMC1 forms the mechanosensory transduction channel in mice and humans and is necessary for auditory function. We found that mice harboring the equivalent of the human p.N199I mutation (p.N193I) had profound congenital hearing loss due to loss of hair cell sensory transduction. Next, we optimized and screened viral payloads packaged into AAV9-PHP.B capsids. The vectors were injected into the inner ears of Tmc1Δ/Δ mice and the new humanized Tmc1-p.N193I mouse model. Auditory brainstem responses (ABRs), distortion product otoacoustic emissions (DPOAEs), cell survival, and biodistribution were evaluated in the injected mice. We found broad-spectrum, durable recovery of auditory function in Tmc1-p.N193I mice injected with AAV9-PHP.B-CB6-hTMC1-WPRE. ABR and DPOAE thresholds were equivalent to those of wild-type mice across the entire frequency range. Biodistribution analysis revealed viral DNA/RNA in the contralateral ear, brain, and liver but no overt toxicity. We conclude that the AAV9-PHP.B-CB6-hTMC1-WPRE construct may be suitable for further development as a gene therapy reagent for treatment of humans with genetic hearing loss due to recessive TMC1 mutations.
Selenium Metabolism and Selenoproteins in Prokaryotes: A Bioinformatics Perspective
Authors: Zhang Yan , Jin Jiao , Huang Biyan , Ying Huimin , He Jie , Jiang Liang
Published: June 2022

Selenium (Se) is an important trace element that mainly occurs in the form of selenocysteine in selected proteins. In prokaryotes, Se is also required for the synthesis of selenouridine and Se-containing cofactor. A large number of selenoprotein families have been identified in diverse prokaryotic organisms, most of which are thought to be involved in various redox reactions. In the last decade or two, computational prediction of selenoprotein genes and comparative genomics of Se metabolic pathways and selenoproteomes have arisen, providing new insights into the metabolism and function of Se and their evolutionary trends in bacteria and archaea. This review aims to offer an overview of recent advances in bioinformatics analysis of Se utilization in prokaryotes. We describe current computational strategies for the identification of selenoprotein genes and generate the most comprehensive list of prokaryotic selenoproteins reported to date. Furthermore, we highlight the latest research progress in comparative genomics and metagenomics of Se utilization in prokaryotes, which demonstrates the divergent and dynamic evolutionary patterns of different Se metabolic pathways, selenoprotein families, and selenoproteomes in sequenced organisms and environmental samples. Overall, bioinformatics analyses of Se utilization, function, and evolution may contribute to a systematic understanding of how this micronutrient is used in nature.
Comprehensive Genetic Analyses of Inherited Peripheral Neuropathies in Japan: Making Early Diagnosis Possible
Authors: Ando Masahiro , Higuchi Yujiro , Yuan Junhui , Yoshimura Akiko , Taniguchi Takaki , Kojima Fumikazu , Noguchi Yutaka , Hobara Takahiro , Takeuchi Mika , Takei Jun , Hiramatsu Yu , Sakiyama Yusuke , Hashiguchi Akihiro , Okamoto Yuji , Mitsui Jun , Ishiura Hiroyuki , Tsuji Shoji , Takashima Hiroshi
Published: June 2022

Various genomic variants were linked to inherited peripheral neuropathies (IPNs), including large duplication/deletion and repeat expansion, making genetic diagnosis challenging. This large case series aimed to identify the genetic characteristics of Japanese patients with IPNs. We collected data on 2695 IPN cases throughout Japan, in which PMP22 copy number variation (CNV) was pre-excluded. Genetic analyses were performed using DNA microarrays, next-generation sequencing-based gene panel sequencing, whole-exome sequencing, CNV analysis, and RFC1 repeat expansion analysis. The overall diagnostic rate and the genetic spectrum of patients were summarized. We identified 909 cases with suspected IPNs, pathogenic or likely pathogenic variants. The most common causative genes were MFN2, GJB1, MPZ, and MME. MFN2 was the most common cause for early-onset patients, whereas GJB1 and MPZ were the leading causes of middle-onset and late-onset patients, respectively. Meanwhile, GJB1 and MFN2 were leading causes for demyelinating and axonal subtypes, respectively. Additionally, we identified CNVs in MPZ and GJB1 genes and RFC1 repeat expansions. Comprehensive genetic analyses explicitly demonstrated the genetic basis of our IPN case series. A further understanding of the clinical characteristics of IPN and genetic spectrum would assist in developing efficient genetic testing strategies and facilitate early diagnosis.
Transcription Factor-Based Biosensors for Detecting Pathogens
Authors: Jeon Yangwon , Lee Yejin , Kim Keugtae , Jang Geupil , Yoon Youngdae
Published: June 2022

Microorganisms are omnipresent and inseparable from our life. Many of them are beneficial to humans, while some are not. Importantly, foods and beverages are susceptible to microbial contamination, with their toxins causing illnesses and even death in some cases. Therefore, monitoring and detecting harmful microorganisms are critical to ensuring human health and safety. For several decades, many methods have been developed to detect and monitor microorganisms and their toxicants. Conventionally, nucleic acid analysis and antibody-based analysis were used to detect pathogens. Additionally, diverse chromatographic methods were employed to detect toxins based on their chemical and structural properties. However, conventional techniques have several disadvantages concerning analysis time, sensitivity, and expense. With the advances in biotechnology, new approaches to detect pathogens and toxins have been reported to compensate for the disadvantages of conventional analysis from different research fields, including electrochemistry, nanotechnology, and molecular biology. Among them, we focused on the recent studies of transcription factor (TF)-based biosensors to detect microorganisms and discuss their perspectives and applications. Additionally, the other biosensors for detecting microorganisms reported in recent studies were also introduced in this review.
Highly Porous 3D Gold Enhances Sensitivity of Amperometric Biosensors Based on Oxidases and CuCe Nanoparticles
Authors: Stasyuk Nataliya , Demkiv Olha , Gayda Galina , Zakalskiy Andriy , Klepach Halyna , Bisko Nina , Gonchar Mykhailo , Nisnevitch Marina
Published: June 2022

Metallic nanoparticles potentially have wide practical applications in various fields of science and industry. In biosensorics, they usually act as catalysts or nanozymes (NZs) and as mediators of electron transfer. We describe here the development of amperometric biosensors (ABSs) based on purified oxidases, synthesized nanoparticles of CuCe (nCuCe), and micro/nanoporous gold (pAu), which were electro-deposited on a graphite electrode (GE). As an effective peroxidase (PO)-like NZ, nCuCe was used here as a hydrogen-peroxide-sensing platform in ABSs that were based on glucose oxidase, alcohol oxidase, methylamine oxidase, and L-arginine oxidase. At the same time, nCuCe is an electroactive mediator and has been used in laccase-based ABSs. As a result, the ABSs we constructed and characterized were based on glucose, methanol, methyl amine, L-arginine, and catechol, respectively. The developed nCuCe-based ABSs exhibited improved analytical characteristics in comparison with the corresponding PO-based ABSs. Additionally, the presence of pAu, with its extremely advanced chemo-sensing surface layer, was shown to significantly increase the sensitivities of all constructed ABSs. As an example, the bioelectrodes containing laccase/GE, laccase/nCuCe/GE, and laccase/nCuCe/pAu/GE exhibited sensitivities to catechol at 2300, 5055, and 9280 A·M−1·m−2, respectively. We demonstrate here that pAu is an effective carrier of electroactive nanomaterials coupled with oxidases, which may be promising in biosensors.
Utilizing Electrochemical-Based Sensing Approaches for the Detection of SARS-CoV-2 in Clinical Samples: A Review
Authors: Zambry Nor Syafirah , Obande Godwin Attah , Khalid Muhammad Fazli , Bustami Yazmin , Hamzah Hairul Hisham , Awang Mohd Syafiq , Aziah Ismail , Manaf Asrulnizam Abd
Published: June 2022

The development of precise and efficient diagnostic tools enables early treatment and proper isolation of infected individuals, hence limiting the spread of coronavirus disease 2019 (COVID-19). The standard diagnostic tests used by healthcare workers to diagnose severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection have some limitations, including longer detection time, the need for qualified individuals, and the use of sophisticated bench-top equipment, which limit their use for rapid SARS-CoV-2 assessment. Advances in sensor technology have renewed the interest in electrochemical biosensors miniaturization, which provide improved diagnostic qualities such as rapid response, simplicity of operation, portability, and readiness for on-site screening of infection. This review gives a condensed overview of the current electrochemical sensing platform strategies for SARS-CoV-2 detection in clinical samples. The fundamentals of fabricating electrochemical biosensors, such as the chosen electrode materials, electrochemical transducing techniques, and sensitive biorecognition molecules, are thoroughly discussed in this paper. Furthermore, we summarised electrochemical biosensors detection strategies and their analytical performance on diverse clinical samples, including saliva, blood, and nasopharyngeal swab. Finally, we address the employment of miniaturized electrochemical biosensors integrated with microfluidic technology in viral electrochemical biosensors, emphasizing its potential for on-site diagnostics applications.
Shedding Light on the Effects of Orienteering Exercise on Spatial Memory Performance in College Students of Different Genders: An fNIRS Study
Authors: Bao Shengbin , Liu Jingru , Liu Yang
Published: June 2022

Objective: To investigate the intervention effect of orienteering exercises on the spatial memory ability of college students of different genders and its underlying mechanism. Methods: Forty-eight college students were randomly screened into experimental and control groups, 12 each of male and female, by SBSOD scale. The effects of 12 weeks of orienteering exercises on the behavioral performance and brain activation patterns during the spatial memory tasks of college students of different genders were explored by behavioral tests and the fNIRS technique. Results: After the orienteering exercise intervention in the experimental group, the male students had significantly greater correct rates and significantly lower reaction times than the female students; left and right dorsolateral prefrontal activation was significantly reduced in the experimental group, and the male students had a significantly greater reduction in the left dorsolateral prefrontal than the female students. The degree of activation in the left and right dorsolateral prefrontals of the male students and the right dorsolateral prefrontals of the female students correlated significantly with behavioral performance, and the functional coupling between the brain regions showed an enhanced performance. Discussion: Orienteering exercises improve the spatial memory ability of college students, more significantly in male students. The degree of activation of different brain regions correlated with behavioral performance and showed some gender differences.
Feasibility of EEG Phase-Amplitude Coupling to Stratify Encephalopathy Severity in Neonatal HIE Using Short Time Window
Authors: Wang Xinlong , Liu Hanli , Ortigoza Eric B. , Kota Srinivas , Liu Yulun , Zhang Rong , Chalak Lina F.
Published: June 2022

Goal: It is challenging to clinically discern the severity of neonatal hypoxic ischemic encephalopathy (HIE) within hours after birth in time for therapeutic decision-making for hypothermia. The goal of this study was to determine the shortest duration of the EEG based PAC index to provide real-time guidance for clinical decision-making for neonates with HIE. Methods: Neonates were recruited from a single-center Level III NICU between 2017 and 2019. A time-dependent, PAC-frequency-averaged index, tPACm, was calculated to characterize intrinsic coupling between the amplitudes of 12–30 Hz and the phases of 1–2 Hz oscillation from 6-h EEG data at electrode P3 during the first day of life, using different sizes of moving windows including 10 s, 20 s, 1 min, 2 min, 5 min, 10 min, 20 min, 30 min, 60 min, and 120 min. Time-dependent receiver operating characteristic (ROC) curves were generated to examine the performance of the accurate window tPACm as a neurophysiologic biomarker. Results: A total of 33 neonates (mild-HIE, n = 15 and moderate/severe HIE, n = 18) were enrolled. Mixed effects models demonstrated that tPACm between the two groups was significantly different with window time segments of 3–120 min. By observing the estimates of group differences in tPACm across different window sizes, we found 20 min was the shortest window size to optimally distinguish the two groups (p < 0.001). Time-varying ROC showed significant average area-under-the-curve of 0.82. Conclusions: We demonstrated the feasibility of using tPACm with a 20 min EEG time window to differentiate the severity of HIE and facilitate earlier diagnosis and treatment initiation.
A Short Functional Neuroimaging Assay Using Attachment Scenes to Recruit Neural Correlates of Social Cognition—A Replication Study
Authors: Labek Karin , Dommes Lisa , Bosch Julia Eva , Schurz Matthias , Viviani Roberto , Buchheim Anna
Published: June 2022

Attachment theory provides a conceptual framework to understand the impact of early child–caregiver experiences, such as loss or separation, on adult functioning and psychopathology. In the current study, scenes from the Adult Attachment Projective Picture System (AAP), a validated, commonly used standardized diagnostic instrument to assess adult attachment representations, were used to develop a short fMRI assay eliciting the neural correlates of encoding of potentially hurtful and threatening social situations such as social losses, rejections or loneliness. Data from healthy participants (N = 19) showed activations in brain areas associated with social cognition and semantic knowledge during exposure to attachment-related scenes compared to control scenes. Extensive activation of the temporal poles was observed, suggesting the use of semantic knowledge for generating social concepts and scripts. This knowledge may underlie our ability to explain and predict social interactions, a specific aspect of theory of mind or mentalization. In this replication study, we verified the effectiveness of a modified fMRI assay to assess the external validity of a previously used imaging paradigm to investigate the processing of emotionally negatively valenced and painful social interactions. Our data confirm the recruitment of brain areas associated with social cognition with our very short neuroimaging assay.
More Information, Greater Appreciation: The Correlation between Background Information and Aesthetic Judgment of Tourist Crafts
Authors: Liu Yang , Zhang Jie , Shen Shiwei , Lu Kaixiang
Published: June 2022

More information is often correlated with greater appreciation. Drawing on the model of aesthetic appreciation and aesthetic judgment in art psychology, this study aims to investigate changes in tourists’ aesthetic judgments of tourist crafts when provided with different background information. Blue calico, an art form created through white pulp dyeing and printing, is an intangible cultural heritage of China. The photographs used in this study illustrate typical examples of blue calicos that are commonly sold in tourist gift shops in Wuzhen, China. Data from a sample of 133 participants (49 women and 84 men) was analyzed using Two-Way Repeated Measures ANOVA. We examined to what extent respondents varied their assessments of the calicos based on author manipulation of background factors, such as commentaries by the artist or details about the production process. We found that tourists’ impressions of the aesthetics of blue calicos were predicted by background factors, especially those of tourists who were less interested in high arts. Specifically, blue calicos reported to tourists with names that conveyed an auspicious meaning predicted tourists’ assessments of the calicos as more aesthetically pleasing. Explanations of the production process also predicted an increased appreciation of calico aesthetics. Conversely, artists’ commentaries were not significantly correlated with an increased aesthetic merit of calicos. Understanding what may affect tourists’ assessment of art could help those in the tourism industry market souvenirs to drive sales and enhance tourists’ understanding and appreciation of intangible cultural heritage.
Exploring Korean Middle- and Old-Aged Citizens’ Subjective Health and Quality of Life
Authors: Moon Joonho , Lee Won Seok , Shim Jimin
Published: June 2022

The goal of this research is to investigate the determinants of subjective health and quality of life with a particular focus on middle- and old-aged citizens. Subjective health is an antecedent of quality of life. For both attributes, travel frequency, economic activity, and cultural activity frequency are the main explanatory variables. Korean middle- and old-aged citizen research panel data was used to derive the data; the study periods are 2008, 2010, 2012, 2014, and 2016. The present work used an econometric method to analyze this panel data. The results show that subjective health positively affects quality of life; meanwhile, economic activity positively affects both subjective health and quality of life. It is also found that cultural activity and travel exert inverted U-shape impacts on subjective health and quality of life. The control variables in this research were gender, body mass index, birth year, and personal assets. These results could help guide policy makers in designing more efficient welfare policies for middle- and old-aged citizens.
Integrated Economic and Environmental Assessment-Based Optimization Design Method of Building Roof Thermal Insulation
Authors: Wang Haitao , Huang Yuge , Yang Liu
Published: June 2022

The design of thermal insulation in roofs is very important to reduce energy consumption and decrease the environmental impacts of buildings. An integrated economic and environmental assessment-based optimization design method is presented in this paper to find the best candidate insulation design scheme for building roofs, including the determination of roof thermal insulation type and the optimum insulation thickness. In the optimization design method, a zonal method-based double-skin ventilation roof heat transfer model is developed to predict the roof energy consumption. Economic and environmental benefits due to thermal insulation are calculated by using the economic analysis model, the environmental analysis model, and roof energy consumption. Moreover, an integrated dimensionless economic and environmental assessment index is proposed to evaluate different roof thermal insulation design schemes. The optimum insulation thickness is determined by maximizing the sum of economic benefit and environmental benefit due to thermal insulation. The validation results in a real building show that the predicted data for the zonal-based double-skin ventilation roof heat transfer model agreed well with the measured data, with a maximum relative error of 8.2%. The optimum insulation thickness of extruded polystyrene (EPS), mineral wool (MW), and polyurethane (PU) was between 0.082 m and 0.171 m for the single-skin roof in a low-temperature granary in Changsha region in China. The ranking of the integrated assessment indexes of thermal insulation is EPS > MW > PU. A double-skin ventilation roof can reduce the optimum thickness of thermal insulation. The best result is obtained by EPS for the double-skin roof with a grey outer surface color for the low-temperature granary roof in Changsha region in China. The influencing factors of insulation type, roof structure, and roof outer-surface color should be considered in finding the best candidate insulation design solution for building roofs. The integrated economic and environmental assessment-based optimization design method can help designers to efficiently find the best design scheme of thermal insulation to maximize the sum of economic benefit and environmental benefit for building roofs.
Behavior of Prefabricated Composite Arch Coupling Beam for Shear Walls Subjected to Cyclic Loading
Authors: Wang Tan , Yuan Shuaifeng , Jiang Ruinian , Li Liwei , Liu Jun , Dou Lijun , Zou Guangyu
Published: June 2022

Under seismic loading, the coupling beam not only connects the wall stems together, but also plays a role in energy dissipation and shock absorption. On the basis of a literature review, this paper presents a new type of prefabricated concrete arch coupling beam with steel connectors. The structure of the prefabricated beam and its connection with the wall stems are introduced. The seismic performance of the beam-wall joint is analyzed through experimental research and finite element analysis. The results show that the arch beam effectively improves the shear bearing capacity of the beam-wall connection, thus improves the overall seismic performance of the coupled wall structures. This research provides a useful reference for developing design codes for prefabricated coupling beams.