bluuebunny/crossref_metadata_2025 huggingface dataset:
One Factor at a Time Analysis to Modify Potting Technique for Manufacturing of Bubble-Free High-Voltage Polyester Insulated Automotive Coils
Authors: Nawaz Ahmad , Ahmad Ishaq , Akram Waseem , Islam Bilal , Pimenov Danil , Giasin Khaled , Aamir Muhammad
Published: May 2022

The current study focuses on minimising the bubbles in polyester-insulated ignition coils, which were produced with a defect level of ~21–25% or 210–250 coils per 1000 batch size by using the potting method. This high-level rejection makes a substantial financial impact by increasing waste material, manufacturing, and after-sales costs. Hence, to control the bubbled problem without using expensive and maintenance-heavy techniques, the process parameters in the potting method were alternated and investigated using one factor at a time, which played a vital role in the formation/reduction of bubbles in the ignition coil insulation. Process parameters, including pre/process heating, the appropriate MEKP/cobalt naphthenate ratio, the pouring amount/increments, and the stirring speeds, reduced the bubble formation per lot from 205 ± 30 to 146 ± 25, 108 ± 21, 61 ± 17, and 10 ± 2 per 1000 lot accordingly. In addition, a comparative study was conducted in terms of performance and life cycle endurance, using Japanese and Indian standards. Furthermore, an after-sale warranty claim also supports the proposed changes in the potting technique. This modification may reduce the after-sales rejection within two years to approximately ~85%. This modification in the potting technique is extremely cost-effective in comparison to expensive processes, i.e., vacuum-pressure impregnation and vacuum impregnation, which require extensive labour and maintenance.
Acute Hepatitis of Unknown Origin (AHUO)—The Puzzle Ahead
Authors: Sergi Consolato M.
Published: May 2022

An intriguing form of hepatitis has been detected in more than a hundred children worldwide [...]
Jointly Optimized Deep Neural Networks to Synthesize Monoenergetic Images from Single-Energy CT Angiography for Improving Classification of Pulmonary Embolism
Authors: Fink Matthias A. , Seibold Constantin , Kauczor Hans-Ulrich , Stiefelhagen Rainer , Kleesiek Jens
Published: May 2022

Detector-based spectral CT offers the possibility of obtaining spectral information from which discrete acquisitions at different energy levels can be derived, yielding so-called virtual monoenergetic images (VMI). In this study, we aimed to develop a jointly optimized deep-learning framework based on dual-energy CT pulmonary angiography (DE-CTPA) data to generate synthetic monoenergetic images (SMI) for improving automatic pulmonary embolism (PE) detection in single-energy CTPA scans. For this purpose, we used two datasets: our institutional DE-CTPA dataset D1, comprising polyenergetic arterial series and the corresponding VMI at low-energy levels (40 keV) with 7892 image pairs, and a 10% subset of the 2020 RSNA Pulmonary Embolism CT Dataset D2, which consisted of 161,253 polyenergetic images with dichotomous slice-wise annotations (PE/no PE). We trained a fully convolutional encoder-decoder on D1 to generate SMI from single-energy CTPA scans of D2, which were then fed into a ResNet50 network for training of the downstream PE classification task. The quantitative results on the reconstruction ability of our framework revealed high-quality visual SMI predictions with reconstruction results of 0.984 ± 0.002 (structural similarity) and 41.706 ± 0.547 dB (peak signal-to-noise ratio). PE classification resulted in an AUC of 0.84 for our model, which achieved improved performance compared to other naïve approaches with AUCs up to 0.81. Our study stresses the role of using joint optimization strategies for deep-learning algorithms to improve automatic PE detection. The proposed pipeline may prove to be beneficial for computer-aided detection systems and could help rescue CTPA studies with suboptimal opacification of the pulmonary arteries from single-energy CT scanners.
Torque Ripple Suppression Method of Switched Reluctance Motor Based on an Improved Torque Distribution Function
Authors: Ling Xiao , Zhou Chenhao , Yang Lianqiao , Zhang Jianhua
Published: May 2022

Currently, torque ripple is a crucial factor hindering the application of the switched reluctance motor (SRM). Hence, it is of crucial importance to suppress this undesirable torque ripple. This paper proposes a new torque ripple suppression method of SRM based on the improved torque distribution function. Firstly, the electromagnetic characteristic model of a 8/6-pole four-phase SRM is established, and the cerebellar model articulation controller (CMAC) is used to complete the learning of each model. Then, the improved torque distribution function is planned based on the torque model to give the reference torque of each phase, and the inverse torque model is used to realize the mapping of the reference torque to the reference flux linkage. Finally, the duty of each phase voltage PWM wave modulation is output based on the PID control theory. The proposed accurate model-based planning scheme is implemented on the simulation platform, and the results shows that the maximum torque fluctuation of the output results is reduced to within 3%, and the average error is reduced to within 1%, which is much lower than the error of 15% under the traditional direct torque control method.
An IoT System for Real-Time Monitoring of DC Motor Overload
Authors: Radonjić Milutin , Zečević Žarko , Krstajić Božo
Published: May 2022

The excavators are heavy machines widely used in the civil engineering and surface mining industry. Recent studies show that 95% of contractors face the problem of finding skilled operators. Unskilled operators not only worsen productivity but also very often cause machine failures through unprofessional handling. Motivated by these studies and guided by the mining company’s requirements, we present a prototype of an IoT system for monitoring DC motor overload on the EKG-15 excavator. The IoT system consists of a microprocessor device mounted inside the excavator and an external cloud platform that can be accessed via the Internet. The proposed solution detects and warns the operator when the DC motor overload occurs, thus reducing the probability of its damage. In addition, overload data is sent to the cloud platform for later research, analysis and processing. The main benefit of the proposed solution is that it can be applied to existing industry machinery, thus reducing the maintenance cost and increasing productivity. After several months of use of the proposed system in real working conditions, it has been shown that the overload occurrence and its duration time are approximately reduced by 60% and 80%, respectively.
An Optimized Algorithm for Dangerous Driving Behavior Identification Based on Unbalanced Data
Authors: Zhu Shengxue , Li Chongyi , Fang Kexin , Peng Yichuan , Jiang Yuming , Zou Yajie
Published: May 2022

It is of great significance to identify dangerous driving behavior by extracting vehicle trajectory through video monitoring to ensure highway traffic safety. At present, there is no suitable method to identify dangerous driving vehicles accurately based on trajectory data. This paper aims to develop a detection algorithm for identifying dangerous driving behavior based on the road scene, which is mainly composed of imbalanced dangerous driver detection and labeling, extraction of driving behavior characteristics and the establishment of a recognition model about dangerous driving behavior. Firstly, this paper defines the risk index of the vehicle related to five types of dangerous driving behavior: dangerous following, lateral deviation, frequent acceleration and deceleration, frequent lane change, and forced insertion. Then, a variety of methods, including K-means clustering, local factor anomaly algorithm, isolation forest and OneClassSVM, are used to carry out anomaly detection on the risk indicators of drivers, and the optimal method is proposed to identify dangerous drivers. Then, the speed and acceleration of each vehicle are Fourier transformed to obtain the characteristics of the driver’s driving behavior. Finally, considering the imbalanced characteristic of the analyzed dataset with a very small proportion of dangerous drivers, this paper compares a variety of imbalanced classification algorithms to optimize the recognition performance of dangerous driving behavior. The results show that the OneClassSVM detection algorithm can be effectively applied to the identification of dangerous driving behavior. The improved Xgboost algorithm performs best for the extremely imbalanced data of dangerous drivers.
Traffic Sign Based Point Cloud Data Registration with Roadside LiDARs in Complex Traffic Environments
Authors: Zhang Zheyuan , Zheng Jianying , Tao Yanyun , Xiao Yang , Yu Shumei , Asiri Sultan , Li Jiacheng , Li Tieshan
Published: May 2022

The intelligent road is an important component of the intelligent vehicle infrastructure cooperative system, the latest development of intelligent transportation systems. As an advanced sensor, Light Detection and Ranging (LiDAR) has gradually been used to collect high-resolution micro-traffic data on the roadside of intelligent roads. Furthermore, a fusion of multiple LiDARs has become a current hot spot to extend the data collection range and improve detection accuracy. This paper focuses on point cloud registration in a complex traffic environment and proposes a three-dimensional (3D) registration method based on traffic signs and prior knowledge of traffic scenes. Traffic signs with their reflective films are used as reference targets to register 3D point cloud data from roadside LiDARs. The proposed method consists of a vertical registration and a horizontal registration. For the vertical registration, we propose a panel rotation algorithm to rotate the initial point cloud to register it vertically, converting the 3D point cloud registration into a two-dimensional (2D) rigid body transformation. For the vertical registration, our system registers traffic signs from different LiDARs. Our method has been verified in some actual scenarios. Compared with previous methods, the proposed method is automatic and does not need to search reference targets manually. Furthermore, it is suitable for actual engineering use and can be applied to sparse point cloud data from LiDAR with few beams, realizing point cloud registration of large disparity.
A New mm-Wave Antenna Array with Wideband Characteristics for Next Generation Communication Systems
Authors: Munir Mehr E , Al Harbi Abdullah G. , Kiani Saad Hassan , Marey Mohamed , Parchin Naser Ojaroudi , Khan Jehanzeb , Mostafa Hala , Iqbal Javed , Khan Muhammad Abbas , See Chan Hwang , Abd-Alhameed Raed A.
Published: May 2022

This paper presents a planar multi-circular loop antenna with a wide impedance bandwidth for next generation mm-wave systems. The proposed antenna comprises three circular rings with a partial ground plane with a square slot. The resonating structure is designed on a 0.254 mm thin RO5880 substrate with a relative permittivity of 2.3. The single element of the proposed design showed a resonance response from 26.5 to 41 GHz, with a peak gain of 4 dBi and radiation efficiency of 96%. The proposed multicircular ring antenna element is transformed into a four-element array system. The array size is kept at 18.25 × 12.5 × 0.254 mm3 with a peak gain of 11 dBi. The antenna array is fabricated and measured using the in-house facility. The simulated and measured results are well agreed upon and are found to be suitable for mm-wave communication systems.
Defect Detection for Metal Base of TO-Can Packaged Laser Diode Based on Improved YOLO Algorithm
Authors: Liu Jiayi , Zhu Xingfei , Zhou Xingyu , Qian Shanhua , Yu Jinghu
Published: May 2022

Defect detection is an important part of the manufacturing process of mechanical products. In order to detect the appearance defects quickly and accurately, a method of defect detection for the metal base of TO-can packaged laser diode (metal TO-base) based on the improved You Only Look Once (YOLO) algorithm named YOLO-SO is proposed in this study. Firstly, convolutional block attention mechanism (CBAM) module was added to the convolutional layer of the backbone network. Then, a random-paste-mosaic (RPM) small object data augmentation module was proposed on the basis of Mosaic algorithm in YOLO-V5. Finally, the K-means++ clustering algorithm was applied to reduce the sensitivity to the initial clustering center, making the positioning more accurate and reducing the network loss. The proposed YOLO-SO model was compared with other object detection algorithms such as YOLO-V3, YOLO-V4, and Faster R-CNN. Experimental results demonstrated that the YOLO-SO model reaches 84.0% mAP, 5.5% higher than the original YOLO-V5 algorithm. Moreover, the YOLO-SO model had clear advantages in terms of the smallest weight size and detection speed of 25 FPS. These advantages make the YOLO-SO model more suitable for the real-time detection of metal TO-base appearance defects.
Preoperative Virtual Reality Surgical Rehearsal of Renal Access during Percutaneous Nephrolithotomy: A Pilot Study
Authors: Sainsbury Ben , Wilz Olivia , Ren Jing , Green Mark , Fergie Martin , Rossa Carlos
Published: May 2022

Percutaneous Nephrolithotomy (PCNL) is a procedure used to treat kidney stones. In PCNL, a needle punctures the kidney through an incision in a patient’s back and thin tools are threaded through the incision to gain access to kidney stones for removal. Despite being one of the main endoscopic procedures for managing kidney stones, PCNL remains a difficult procedure to learn with a long and steep learning curve. Virtual reality simulation with haptic feedback is emerging as a new method for PCNL training. It offers benefits for both novices and experienced surgeons. In the first case, novices can practice and gain kidney access in a variety of simulation scenarios without offering any risk to patients. In the second case, surgeons can use the simulator for preoperative surgical rehearsal. This paper proposes the first preliminary study of PCNL surgical rehearsal using the Marion Surgical PCNL simulator. Preoperative CT scans of a patient scheduled to undergo PCNL are used in the simulator to create a 3D model of the renal system. An experienced surgeon then planned and practiced the procedure in the simulator before performing the surgery in the operating room. This is the first study involving survival rehearsal using a combination of VR and haptic feedback in PCNL before surgery. Preliminary results confirm that surgical rehearsal using a combination of virtual reality and haptic feedback strongly affects decision making during the procedure.
Cement with Fly Ash and Metakaolin Blend—Drive towards a More Sustainable Construction
Authors: Dvorkin Leonid , Zhitkovsky Vadim , Sitarz Mateusz , Hager Izabela
Published: May 2022

This article presents experimental studies that have shown the effectiveness of using a composition of fly ash and metakaolin as an active mineral admixture to cement. It is shown that composite ash–metakaolin additives (AMAd) have on the one hand increased pozzolanic activity and surface energy, and, on the other hand, moderated water demand and provided a significant increase in strength, which is especially important for low-cement concretes. The obtained experimental–statistical models make it possible to determine the effect of the AMAd composition, its content in combination with the addition of a superplasticizer on the rheological properties, the kinetics of structure formation and the main physical and mechanical properties of cement.
Study of Pressure Retarded Osmosis Process in Hollow Fiber Membrane: Cylindrical Model for Description of Energy Production
Authors: Nagy Endre , Ibrar Ibrar , Braytee Ali , Iván Béla
Published: May 2022

A new mathematical model was developed to predict the cylindrical effect of the membrane performance in the pressure retarded osmosis process. The cylindrical membrane transport layers (the draw side boundary and the porous membrane) were divided into very thin sublayers with constant mass transport parameters, among others with a constant radius in every sublayer. The obtained second-order differential mass balance equations were solved analytically, with constant parameters written for every sublayer. The algebraic equation system involving 2N equations was then solved for the determinant solution. It was shown that the membrane properties, water permeability (A), salt permeability (B), structural parameter (S) and the operating conditions (inlet draw side solute concentration and draw side mass transfer coefficient) affect the water flux strongly, and thus the membrane performance, due to the cylindrical effect caused by the variable surface and volume of the sublayers. This effect significantly depends on the lumen radius. The lower radius means a larger change in the internal surface/volume of sublayers with ΔR thickness. The predicted results correspond to that of the flat-sheet membrane layer at ro = 10,000 μm. At the end of this manuscript, the calculated mass transfer rates were compared to those measured. It was stated that the curvature effect in using a capillary membrane must not be left out of consideration when applying hollow fiber membrane modules due to their relatively low lumen radius. The presented model provides more precise prediction of the performance in the case of hollow fiber membranes.
Renewable and Non-Renewable Energy Consumption and Trade Policy: Do They Matter for Environmental Sustainability?
Authors: He Yugang
Published: May 2022

In the extant literature, there are numerous discussions on China’s environmental sustainability. However, few scholars have considered renewable energy consumption and trade policy simultaneously to debate environmental sustainability. Therefore, this paper attempts to examine how renewable and non-renewable energy consumption, bio-capacity, economic growth, and trade policy dynamically affect the ecological footprint (a proxy for environmental sustainability). Using the data from 1971 to 2017 and employing the auto-regressive distributed lag model to perform an empirical analysis, the results demonstrate that renewable energy consumption and trade policy are conducive to environmental sustainability because of their negative impacts on the ecological footprint. However, the results also indicate that bio-capacity, non-renewable energy consumption, and economic growth are putting increasing pressure on environmental sustainability due to their positive impacts on the ecological footprint. Moreover, to determine the direction of causality between the highlighted variables, the Yoda-Yamamoto causality test was conducted. The results suggest a two-way causal relationship between renewable energy consumption and ecological footprint, non-renewable energy consumption and ecological footprint, and economic growth and ecological footprint. Conversely, the results also suggest a one-way causal relationship running from bio-capacity and trade policy to the ecological footprint.
Compact Thermal Modeling of Power Semiconductor Devices with the Influence of Atmospheric Pressure
Authors: Górecki Paweł
Published: May 2022

The efficiency of the heat dissipation process generated in semiconductor devices depends on many factors, related both to the parameters of the cooling system and environmental factors. Regarding the latter factors, ambient temperature and volume in which the device operates are typically indicated as the most important. However, in the case of the operation of semiconductor devices in non-standard conditions, e.g., in stratospheric airships, the thermal parameters of the device are significantly affected by a low value of atmospheric pressure. This paper presents a compact thermal model of a semiconductor device, considering the effects of reduced atmospheric pressure along with its experimental verification under various cooling conditions, thus obtaining high compliance for computation and measurement results. The formulated model is dedicated to circuit-level simulations, and it enables computations of the junction temperature of the semiconductor device in a short time. It is also shown that lowering atmospheric pressure can double the value of the junction-ambient thermal resistance.
Computational Optimization of Free-Piston Stirling Engine by Variable-Step Simplified Conjugate Gradient Method with Compatible Strategies
Authors: Cheng Chin-Hsiang , Lin Yu-Ting
Published: May 2022

This study aimed at the development of an algorithm for the computational optimization of free-piston Stirling engines. The design algorithm includes an optimization method and two compatible strategies. The optimization method is an improved version of traditional conjugate gradient method and is named the variable-step simplified conjugate gradient method (VSCGM). The free-piston Stirling engine is operable only in narrow-bounded parameter regions. Using the present approach, the operable variable combinations can be found efficiently. Two compatible strategies, the wake-up and backward-comparison strategies, are integrated with the VSCGM. The present design algorithm can handle multiple-parameter optimization with more flexible objective function definitions. Meanwhile, it features faster convergence as compared with the traditional conjugate gradient methods. Moreover, the feasibility of the VSCGM and the two compatible strategies is demonstrated in two test cases. It was found that the present approach can optimize the ten designed variables simultaneously, and the optimal designs can be yielded in a finite number of iterations. The results show that the inoperable initial designs were successfully optimized to reach a high power output.
International Natural Gas Price Trends Prediction with Historical Prices and Related News
Authors: Guan Renchu , Wang Aoqing , Liang Yanchun , Fu Jiasheng , Han Xiaosong
Published: May 2022

Under the idea of low carbon economy, natural gas has drawn widely attention all over the world and becomes one of the fastest growing energies because of its clean, high calorific value, and environmental protection properties. However, policy and political factors, supply-demand relationship and hurricanes can cause the jump in natural gas prices volatility. To address this issue, a deep learning model based on oil and gas news is proposed to predict natural gas price trends in this paper. In this model, news text embedding is conducted by BERT-Base, Uncased on natural gas-related news. Attention model is adopted to balance the weight of the news vector. Meanwhile, corresponding natural gas price embedding is conducted by a BiLSTM module. The Attention-weighted news vectors and price embedding are the inputs of the fused network with transformer is built. BiLSTM is used to extract used price information related with news features. Transformer is employed to capture time series trend of mixed features. Finally, the network achieves an accuracy as 79%, and the performance is better than most traditional machine learning algorithms.
Quality of Hydrochar from Wine Sludge under Variable Conditions of Hydrothermal Carbonization: The Case of Lesvos Island
Authors: Vasileiadou Maria A. , Altiparmaki Georgia , Moustakas Konstantinos , Vakalis Stergios
Published: May 2022

Lesvos island has several food and beverage production industries and the valorization of their waste has been an unexplored task. The focus of this study is the valorization of wine sludge which is a very interesting waste stream due to the high phenolic content. This study identified all the operating wineries on the island and sampled local wine sludge. Hydrothermal carbonization (HTC) was utilized for the valorization of wine sludge and the production of hydrochar and liquid HTC liquor. The experiments had a residence time of 24 h and were performed at 200 °C. Except the uniqueness of wine sludge as a utilized material, this study performed HTC under different pressure regimes that were developed by different filling percentages of the reactor, i.e., 24–48%. The different pressure regimes influenced the measured parameters of both the liquid and the solid products of HTC. The Chemical Oxygen Demand (COD) ranged between 230 and 280 g/L with the maximum reduction was observed at a filling percentage of 32%. At the same time, lower filling percentages favored the total phenolic content (max value: 21 g/L) and higher filling percentages favored the Higher Heating Value (HHV) of the hydrochar (max value: 20.36 MJ/Kg) and the produced mass yield of hydrochar (max value: 234.3 mg). For all cases, low pH values were measured on the liquid fraction and this can be attributed to the presence of organic acids. Future work will focus on the characterization of the specific phenolic content of the liquid fraction.
A Comparison of Radial Wood Property Variation on Pinus radiata between an IML PD-400 ‘Resi’ Instrument and Increment Cores Analysed by SilviScan
Authors: Downes Geoffrey M. , Harrington Jonathan J. , Drew David M. , Lausberg Marco , Muyambo Phillip , Watt Duncan , Lee David J.
Published: May 2022

Mature age Pinus radiata D. Don trees were sampled across nine sites in northern New South Wales, Australia, that were expected, based on site quality and inventory metrics, to exhibit significant variation in productivity and wood quality. Twenty trees per site were harvested and 13 mm diameter, pith-to-bark increment cores were extracted from three trees per site from eight of the nine sites for SilviScan analysis. Outerwood increment cores were collected from all trees for basic density measurement. The same trees were also sampled using an IML PD400 (Resi) instrument. Radial mean properties of wood basic density derived from Resi traces were found to correlate strongly with the mean density data derived from SilviScan analyses and from increment cores. The Resi-derived basic density of 10 mm radial segments was strongly correlated with SilviScan measures of basic density averaged at similar intervals.
Field Assessment of Downed Timber Strength Deterioration Rate and Wood Quality Using Acoustic Technologies
Authors: Musah Munkaila , Diaz Javier Hernandez , Alawode Abiodun Oluseun , Gallagher Tom , Peresin Maria Soledad , Mitchell Dana , Smidt Mathew , Via Brian
Published: May 2022

Hurricane and tornado events cause significant damage to high-value timber in the United States each year. Forest managers and landowners are keenly interested in finding solutions to salvage and repurpose these downed timbers before they cause pest infestations and fire outbreaks, completely losing their value or increasing processing costs. To better understand the wood quality of the downed timber, we used acoustic waves techniques as a nondestructive testing approach to assess the wood degradation rate of downed trees and determine the extent of fracture and voids in the damaged regions. We periodically monitored the acoustic velocity of the downed trees for 12 consecutive months using a time of flight (TOF) acoustic method. Acoustic measurements were conducted using three different techniques—longitudinal, transverse, and off-set methods. Wood density, age, and the diameter at breast height (dbh) class measurement for southern timber (chip-n-saw for dbh 8″–11″ and sawtimber with dbh 12″ and up) were used as the predictive parameters of the downed trees. The results indicated positive relationships between dbh class, stand age, and acoustic velocity measurement (R2 > 65%). The TOF acoustic velocity was indicated to potentially separate higher-stiffness timber from lower-stiffness timber in a hurricane event for structural or non-structural applications. The regression coefficient from the repeated measurements indicated that both age and diameter class strongly impacted the acoustic properties of the downed trees (p-value ≤ 0.001). The sawtimber dbh class recorded a higher acoustic velocity compared to the chip-n-saw type. Fracture, voids, and massive decay in downed trees were detected beyond the visible inspection, features that often are identified by loggers in lower quality wood; however, TOF showed a weak response in picking up incremental deterioration due to changes in specific environmental factors that affected acoustic readings. This study showed that acoustic wave methods could potentially be used as a field evaluation tool for assessing the quality of downed trees.
A Framework to Model Bursty Electronic Data Interchange Messages for Queueing Systems
Authors: Leech Sonya , Dunne Jonathan , Malone David
Published: May 2022

Within a supply chain organisation, where millions of messages are processed, reliability and performance of message throughput are important. Problems can occur with the ingestion of messages; if they arrive more quickly than they can be processed, they can cause queue congestion. This paper models data interchange (EDI) messages. We sought to understand how best DevOps should model these messages for performance testing and how best to apply smart EDI content awareness that enhance the realms of Ambient Intelligence (Aml) with a Business-to business (B2B) supply chain organisation. We considered key performance indicators (KPI) for over- or under-utilisation of these queueing systems. We modelled message service and inter-arrival times, partitioned data along various axes to facilitate statistical modelling and used continuous parametric and non-parametric techniques. Our results include the best fit for parametric and non-parametric techniques. We noted that a one-size-fits-all model is inappropriate for this heavy-tailed enterprise dataset. Our results showed that parametric distribution models were suitable for modelling the distribution’s tail, whilst non-parametric kernel density estimation models were better suited for modelling the head of a distribution. Depending on how we partitioned our data along the axes, our data suffer from quantisation noise.
A Review of Blockchain Technology Applications in Ambient Assisted Living
Authors: Florea Alexandru-Ioan , Anghel Ionut , Cioara Tudor
Published: May 2022

The adoption of remote assisted care was accelerated by the COVID-19 pandemic. This type of system acquires data from various sensors, runs analytics to understand people’s activities, behavior, and living problems, and disseminates information with healthcare stakeholders to support timely follow-up and intervention. Blockchain technology may offer good technical solutions for tackling Internet of Things monitoring, data management, interventions, and privacy concerns in ambient assisted living applications. Even though the integration of blockchain technology with assisted care is still at the beginning, it has the potential to change the health and care processes through a secure transfer of patient data, better integration of care services, or by increasing coordination and awareness across the continuum of care. The motivation of this paper is to systematically review and organize these elements according to the main problems addressed. To the best of our knowledge, there are no studies conducted that address the solutions for integrating blockchain technology with ambient assisted living systems. To conduct the review, we have followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology with clear criteria for including and excluding papers, allowing the reader to effortlessly gain insights into the current state-of-the-art research in the field. The results highlight the advantages and open issues that would require increased attention from the research community in the coming years. As for directions for further research, we have identified data sharing and integration of care paths with blockchain, storage, and transactional costs, personalization of data disclosure paths, interoperability with legacy care systems, legal issues, and digital rights management.
Application and Prospects of Hydrogel Additive Manufacturing
Authors: Zhao Changlong , Lv Qiyin , Wu Wenzheng
Published: May 2022

Hydrogel has become a commonly used material for 3D and 4D printing due to its favorable biocompatibility and low cost. Additive manufacturing, also known as 3D printing, was originally referred to as rapid prototyping manufacturing. Variable-feature rapid prototyping technology, also known as 4D printing, is a combination of materials, mathematics, and additives. This study constitutes a literature review to address hydrogel-based additive manufacturing technologies, introducing the characteristics of commonly used 3D printing hydrogel methods, such as direct ink writing, fused deposition modeling, and stereolithography. With this review, we also investigated the stimulus types, as well as the advantages and disadvantages of various stimulus-responsive hydrogels in smart hydrogels; non-responsive hydrogels; and various applications of additive manufacturing hydrogels, such as neural catheter preparation and drug delivery. The opportunities, challenges, and future prospects of hydrogel additive manufacturing technologies are discussed.
Genome-Wide Identification and Evolution Analysis of the Gibberellin Oxidase Gene Family in Six Gramineae Crops
Authors: Zhang Chenhao , Nie Xin , Kong Weilong , Deng Xiaoxiao , Sun Tong , Liu Xuhui , Li Yangsheng
Published: May 2022

The plant hormones gibberellins (GAs) regulate plant growth and development and are closely related to the yield of cash crops. The GA oxidases (GAoxs), including the GA2ox, GA3ox, and GA20ox subfamilies, play pivotal roles in GAs’ biosynthesis and metabolism, but their classification and evolutionary pattern in Gramineae crops remain unclear. We thus conducted a comparative genomic study of GAox genes in six Gramineae representative crops, namely, Setaria italica (Si), Zea mays (Zm), Sorghum bicolor (Sb), Hordeum vulgare (Hv), Brachypodium distachyon (Bd), and Oryza sativa (Os). A total of 105 GAox genes were identified in these six crop genomes, belonging to the C19-GA2ox, C20-GA2ox, GA3ox, and GA20ox subfamilies. Based on orthogroup (OG) analysis, GAox genes were divided into nine OGs and the number of GAox genes in each of the OGs was similar among all tested crops, which indicated that GAox genes may have completed their family differentiations before the species differentiations of the tested species. The motif composition of GAox proteins showed that motifs 1, 2, 4, and 5, forming the 2OG-FeII_Oxy domain, were conserved in all identified GAox protein sequences, while motifs 11, 14, and 15 existed specifically in the GA20ox, C19-GA2ox, and C20-GA2ox protein sequences. Subsequently, the results of gene duplication events suggested that GAox genes mainly expanded in the form of WGD/SD and underwent purification selection and that maize had more GAox genes than other species due to its recent duplication events. The cis-acting elements analysis indicated that GAox genes may respond to growth and development, stress, hormones, and light signals. Moreover, the expression profiles of rice and maize showed that GAox genes were predominantly expressed in the panicles of the above two plants and the expression of several GAox genes was significantly induced by salt or cold stresses. In conclusion, our results provided further insight into GAox genes’ evolutionary differences among six representative Gramineae and highlighted GAox genes that may play a role in abiotic stress.
RET c.1901G>A and Novel SLC12A3 Mutations in Familial Pheochromocytomas
Authors: Zhao Lin , Yang Kun-Qi , Fan Peng , Gong Ding-Xu , Zhang Lin , Lu Yi-Ting , Meng Xu , Zhou Xian-Liang
Published: May 2022

Familial PHEOs (pheochromocytomas) are inherited as an autosomal dominant trait, and inherited PHEOs can be one clinical phenotype of clinical syndromes, such as multiple endocrine neoplasia type 2A (MEN2A). In recent years, there has been a lot of controversy about the factors affecting the penetrance of PHEOs in MEN2A, of which the effects of RET (rearranged during transfection) proto-oncogene mutations are the primary concern. In this report, we performed genetic screening of patients in one family presenting with PHEOs and found they carried a RET c.1901G>A mutation. They were ultimately diagnosed with familial MEN2A. We found that MEN2A patients with the RET c.1901G>A mutation tended to have bilateral PHEOs that appeared earlier than medullary thyroid carcinoma. Genetic analysis showed that the patients also carried novel SLC12A3 (solute carrier family 12 member 3) variants, which are highly associated with Giteman syndrome. The results of protein structure prediction models suggest this SLC12A3 mutant has altered both the protein structure and the interaction with surrounding amino acids. Further studies of the phenotypes and related mechanisms of the gene mutations are required to guide individual assessment and treatment.
The Sigma Factor AlgU Regulates Exopolysaccharide Production and Nitrogen-Fixing Biofilm Formation by Directly Activating the Transcription of pslA in Pseudomonas stutzeri A1501
Authors: Shao Yahui , Yin Changyan , Lv Fanyang , Jiang Shanshan , Wu Shaoyu , Han Yueyue , Xue Wei , Ma Yiyuan , Zheng Juan , Zhan Yuhua , Ke Xiubin , Lu Wei , Lin Min , Shang Liguo , Yan Yongliang
Published: May 2022

Pseudomonas stutzeri A1501, a plant-associated diazotrophic bacterium, prefers to conform to a nitrogen-fixing biofilm state under nitrogen-deficient conditions. The extracytoplasmic function (ECF) sigma factor AlgU is reported to play key roles in exopolysaccharide (EPS) production and biofilm formation in the Pseudomonas genus; however, the function of AlgU in P. stutzeri A1501 is still unclear. In this work, we mainly investigated the role of algU in EPS production, biofilm formation and nitrogenase activity in A1501. The algU mutant ΔalgU showed a dramatic decrease both in the EPS production and the biofilm formation capabilities. In addition, the biofilm-based nitrogenase activity was reduced by 81.4% in the ΔalgU mutant. The transcriptional level of pslA, a key Psl-like (a major EPS in A1501) synthesis-related gene, was almost completely inhibited in the algU mutant and was upregulated by 2.8-fold in the algU-overexpressing strain. A predicted AlgU-binding site was identified in the promoter region of pslA. The DNase I footprinting assays indicated that AlgU could directly bind to the pslA promoter, and β-galactosidase activity analysis further revealed mutations of the AlgU-binding boxes drastically reduced the transcriptional activity of the pslA promoter; moreover, we also demonstrated that AlgU was positively regulated by RpoN at the transcriptional level and negatively regulated by the RNA-binding protein RsmA at the posttranscriptional level. Taken together, these data suggest that AlgU promotes EPS production and nitrogen-fixing biofilm formation by directly activating the transcription of pslA, and the expression of AlgU is controlled by RpoN and RsmA at different regulatory levels.
The Benefit of Multigene Panel Testing for the Diagnosis and Management of the Genetic Epilepsies
Authors: Leduc-Pessah Heather , White-Brown Alexandre , Hartley Taila , Pohl Daniela , Dyment David A.
Published: May 2022

With the increasing use of genetic testing in pediatric epilepsy, it is important to describe the diagnostic outcomes as they relate to clinical care. The goal of this study was to assess the diagnostic yield and impact on patient care of genetic epilepsy panel testing. We conducted a retrospective chart review of patients at the Children’s Hospital of Eastern Ontario (CHEO) who had genetic testing between the years of 2013–2020. We identified 227 patients that met criteria for inclusion. The majority of patients had their testing performed as “out-of-province” tests since province-based testing during this period was limited. The diagnostic yield for multi-gene epilepsy panel testing was 17% (39/227) and consistent with the literature. Variants of unknown significance (VUS) were reported in a significant number of undiagnosed individuals (77%; 128/163). A higher diagnostic rate was observed in patients with a younger age of onset of seizures (before one year of age; 32%; 29/90). A genetic diagnosis informed prognosis, recurrence risk counselling and expedited access to resources in all those with a diagnosis. A direct change in clinical management as a result of the molecular diagnosis was evident for 9% (20/227) of patients. The information gathered in this study provides evidence of the clinical benefits of genetic testing in epilepsy and serves as a benchmark for comparison with the current provincial Ontario Epilepsy Genetic Testing Program (OEGTP) that began in 2020.
Comparative Analysis of Transcriptomes of Diploid and Tetraploid Miscanthus lutarioriparius under Drought Stress
Authors: Xu Xitong , Wang Shukai , Han Yanbin , Wang Yancui , Xu Pingping , Chen Cuixia , Zhang Guobin
Published: May 2022

Miscanthus lutarioriparius is a species of bioenergy crop unique to China. It is widely distributed in the south of China with high resistance to drought and salt stress. To date, the molecular mechanism of the adaption to drought stress in M. lutarioriparius is little known. In this study, RNA-seq technology was employed to analyze the transcriptome changes of diploid and tetraploid M. lutarioriparius after drought treatment. It was found that the number of differentially expressed genes in diploid M. lutarioriparius was much higher than tetraploid, whereas the tetraploid M. lutarioriparius may require fewer transcriptional changes. While the transcriptional changes in drought-tolerant tetraploid M. lutarioriparius are less than that of diploid, more known drought-tolerant pathways were significantly enriched than drought-sensitive diploid M. lutarioriparius. In addition, many drought-tolerance-related genes were constitutively and highly expressed in tetraploid under either normal condition or drought stress. These results together demonstrated that drought-tolerant tetraploid M. lutarioriparius, on the one hand, may preadapt to drought by constitutively overexpressing a series of drought-tolerant genes and, on the other hand, may adapt to drought by actively inducing other drought-tolerant-related pathways. Overall, this study could deepen our understanding of the molecular mechanism of drought-tolerance in bioenergy plants.
STIM1–Orai1 Interaction Exacerbates LPS-Induced Inflammation and Endoplasmic Reticulum Stress in Bovine Hepatocytes through Store-Operated Calcium Entry
Authors: Xue Yang , Zhou Shendong , Xie Wan , Meng Meijuan , Ma Nana , Zhang Hongzhu , Wang Yan , Chang Guangjun , Shen Xiangzhen
Published: May 2022

(1) Background: The basic mechanism of store-operated Ca2+ entry (SOCE) in bovine hepatocytes (BHEC) is related to the activation of STIM1 and Orai1. The effect of STIM1- and Orai1-dependent calcium ion signaling on the NF-κB signaling pathway is unclear. (2) Methods: In this study, the expression of STIM1 and Orai1 in BHEC was regulated. RT-qPCR, Western blotting, and an immunofluorescence antibody (IFA) assay were performed to elucidate the effect of inflammation and endoplasmic reticulum stress (ERS) in BHEC. (3) Results: First of all, in this study, RT-PCR and Western blotting were used to detect the levels of IκB, NF-κB, and inflammatory factors (IL-6, IL-8, and TNF-α) and the expression of genes and proteins related to ERS (PERK, IRE1, ATF6, GRP78, and CHOP), which reached peak levels simultaneously when BHEC were treated with 16 μg/mL LPS for 1 h. For STIM1, we overexpressed STIM1 in BHEC by using plasmid transfection technology. The results showed that after overexpression of STIM1, the gene and protein expression of STIM1 levels were significantly upregulated, and the expression of Orai1 on the cell membrane was also upregulated, which directly activated the SOCE channel and induced inflammation and ERS in BHEC. The overexpression group was then treated with LPS, and it was found that the overexpression of STIM1 could enhance LPS-induced BHEC inflammation and ERS in BHEC. For Orai1, BHEC were pretreated with 8 μg/mL of the specific inhibitor BTP2 for 6 h. It was found that BTP2 could inhibit the expression of mRNA in Orai1, significantly reduce the gene expression of STIM1, inhibit the activation of the NF-κB signaling pathway, and alleviate inflammation and ERS in BHEC under LPS stimulation. (4) Conclusions: In conclusion, STIM1/Orai1 can intervene and exacerbate LPS-induced inflammation and ERS in bovine hepatocytes through SOCE.
Selected Correlates of Attitudes towards Rape Victims among Polish Medical Students
Authors: Perenc Lidia , Podgórska-Bednarz Justyna , Guzik Agnieszka , Drużbicki Mariusz
Published: May 2022

Sexual violence against women, including rape, is a serious public health issue in many countries. Rape victims often meet health professionals in medical institutions for a range of health problems. The aim of this research was investigation of attitudes towards rape victims among medical students. Methods: The study sample consisted of 1183 university students who represented various medical disciplines. The average age of the respondents was 23.3 years. The Attitudes toward Rape Victims Scale (ARVS) was used in this study. Results: Higher scores in men indicate that they held less sympathetic attitudes towards rape victims than women (61.6 vs. 52.6, p = 0.0000). Given the univariate interaction, social environment, and religious commitment did not significantly differentiate the respondents in this respect. Students of the medical faculty obtained the lowest results (medicine 49.7 vs. midwifery and nursing: 54.1, other fields: 54.4, p = 0.0008), showing much understanding and empathy for rape victims. Conclusions: The surveyed medical students presented moderately positive attitudes towards rape victims, among them men somewhat negative than women who made more pro-victim judgments. Among all medical field of study, medicine was distinguished by higher empathy. Religion and social environment independently do not differentiate respondents in this respect.
The Association between Greenness and Urbanization Level with Weight Status among Adolescents: New Evidence from the HBSC 2018 Italian Survey
Authors: Bellisario Valeria , Comoretto Rosanna , Berchialla Paola , Koumantakis Emanuele , Squillacioti Giulia , Borraccino Alberto , Bono Roberto , Lemma Patrizia , Charrier Lorena , Dalmasso Paola
Published: May 2022

Recent studies have examined how the environment can influence obesity in young people. The research findings are conflicting: in some studies, green spaces have shown a protective association with obesity and urbanization has turned out to worsen this condition, while other studies contradicted these results. The aim of the study was to examine the relationships between greenness, urbanization, and weight status among Italian adolescents. Student data (11–13 years old) on weight and height, physical activity (PA), and demographic characteristics were extracted from the 2018 Health Behaviour in School-aged Children (HBSC) survey in Piedmont, Northwest of Italy. Data on Normalized Difference Vegetation Index (NDVI) and urbanization were obtained from satellite images and the National Institute of Statistics (ISTAT). A multilevel regression model was used to assess the association between NDVI, urbanization, and obesity, controlling for PA. Students living in greener areas reported a lower likelihood of being obese [OR = 0.11, 95% CI 0.02–0.56, p = 0.007], while students living in areas with a higher level of urbanization showed a significantly increased risk of obesity [OR = 2.3, 95% CI:1.14–4.6, p = 0.02]. Living surrounded by higher amounts of greenness and lower levels of urbanization may positively influence health status through lower risk of obesity among youth.