bluuebunny/crossref_metadata_2025 huggingface dataset:
AI Techniques of Dermoscopy Image Analysis for the Early Detection of Skin Lesions Based on Combined CNN Features
Authors: Olayah Fekry , Senan Ebrahim Mohammed , Ahmed Ibrahim Abdulrab , Awaji Bakri
Published: April 2023

Melanoma is one of the deadliest types of skin cancer that leads to death if not diagnosed early. Many skin lesions are similar in the early stages, which causes an inaccurate diagnosis. Accurate diagnosis of the types of skin lesions helps dermatologists save patients’ lives. In this paper, we propose hybrid systems based on the advantages of fused CNN models. CNN models receive dermoscopy images of the ISIC 2019 dataset after segmenting the area of lesions and isolating them from healthy skin through the Geometric Active Contour (GAC) algorithm. Artificial neural network (ANN) and Random Forest (Rf) receive fused CNN features and classify them with high accuracy. The first methodology involved analyzing the area of skin lesions and diagnosing their type early using the hybrid models CNN-ANN and CNN-RF. CNN models (AlexNet, GoogLeNet and VGG16) receive lesions area only and produce high depth feature maps. Thus, the deep feature maps were reduced by the PCA and then classified by ANN and RF networks. The second methodology involved analyzing the area of skin lesions and diagnosing their type early using the hybrid CNN-ANN and CNN-RF models based on the features of the fused CNN models. It is worth noting that the features of the CNN models were serially integrated after reducing their high dimensions by Principal Component Analysis (PCA). Hybrid models based on fused CNN features achieved promising results for diagnosing dermatoscopic images of the ISIC 2019 data set and distinguishing skin cancer from other skin lesions. The AlexNet-GoogLeNet-VGG16-ANN hybrid model achieved an AUC of 94.41%, sensitivity of 88.90%, accuracy of 96.10%, precision of 88.69%, and specificity of 99.44%.
Weighted Average Ensemble Deep Learning Model for Stratification of Brain Tumor in MRI Images
Authors: Anand Vatsala , Gupta Sheifali , Gupta Deepali , Gulzar Yonis , Xin Qin , Juneja Sapna , Shah Asadullah , Shaikh Asadullah
Published: April 2023

Brain tumor diagnosis at an early stage can improve the chances of successful treatment and better patient outcomes. In the biomedical industry, non-invasive diagnostic procedures, such as magnetic resonance imaging (MRI), can be used to diagnose brain tumors. Deep learning, a type of artificial intelligence, can analyze MRI images in a matter of seconds, reducing the time it takes for diagnosis and potentially improving patient outcomes. Furthermore, an ensemble model can help increase the accuracy of classification by combining the strengths of multiple models and compensating for their individual weaknesses. Therefore, in this research, a weighted average ensemble deep learning model is proposed for the classification of brain tumors. For the weighted ensemble classification model, three different feature spaces are taken from the transfer learning VGG19 model, Convolution Neural Network (CNN) model without augmentation, and CNN model with augmentation. These three feature spaces are ensembled with the best combination of weights, i.e., weight1, weight2, and weight3 by using grid search. The dataset used for simulation is taken from The Cancer Genome Atlas (TCGA), having a lower-grade glioma collection with 3929 MRI images of 110 patients. The ensemble model helps reduce overfitting by combining multiple models that have learned different aspects of the data. The proposed ensemble model outperforms the three individual models for detecting brain tumors in terms of accuracy, precision, and F1-score. Therefore, the proposed model can act as a second opinion tool for radiologists to diagnose the tumor from MRI images of the brain.
CT and MRI Features of Hairy Polyps in Neonates and Infants: A Retrospective Study of 14 Patients
Authors: Yang Shuangfeng , Li Hang , Gao Jun , Han Zhonglong , Tang Xiaolu , Wu Rongchang , Kang Huiying , Zhang Fengzhen , Xu Jiatong , Peng Yun
Published: April 2023

Background: The typical imaging findings of hairy polyps have been described mostly in case reports. This study was conducted to describe the CT and MRI features of hairy polyps and their common associated abnormalities. Methods: Medical records of 14 patients with pathological diagnosis of hairy polyps were collected for this study. For each patient, the medical records, including demographics, clinical manifestations, and imaging findings were reviewed. Results: The female-to-male ratio was 3.7:1. The age at first episode varied from birth to 2.7 years. The masses were derived from the back side of the soft palate in seven (50.0%) cases, from the lateral pharyngeal wall in four (28.6%) cases, from the soft palate in one (7.1%) case, from the nasal vestibule in one (7.1%) case, and from the parapharyngeal space in one (7.1%) case. A total of 11 (78.6%) cases presented with pedicled masses containing fat and a central core of soft tissue, there were 3 (21.4%) cases whose imaging findings were atypical, and there were 6 (42.9%) patients who had other pathologies. Conclusions: Hairy polyps typically presented as pedicled masses containing fat and a central core of soft tissue, but sometimes their imaging findings can be atypical and they can be associated with other congenital abnormalities. CT and MRI are reliable methods for the diagnosis of hairy polyps and their associated abnormalities.
To Obtain Informed Consent or Not to Obtain Informed Consent? Drones for Health Programs in the Grey Zone between Research and Public Health
Authors: Jeyabalan Vyshnave , Donelle Lorie , Meier Patrick , Nouvet Elysée
Published: April 2023

Drones are increasingly being introduced to support healthcare delivery around the world. Most Drones for Health projects are currently in the pilot phase, where frontline staff are testing the feasibility of implementing drones into their healthcare system. Many of these projects are happening in remote localities where populations have been historically under-served within national healthcare systems. Currently, there exists limited drone-specific guidance on best practices for engaging individuals in decision-making about drone use in their communities. Towards supporting the development of such guidance, this paper focuses on the issue of obtaining community and individual consent for implementing Drones for Health projects. This paper is based on original qualitative research involving semi-structured interviews (N = 16) with program managers and implementation staff hired to work on health-related projects using drone technologies. In this paper, we introduce a scenario described by one participant to highlight the ethical and practical challenges associated with the implementation and use of drones for health-related purposes. We explore the ethical and practical complexities of obtaining informed consent from individuals who reside in communities where Drones for Health projects are implemented.
Substrate Integrated Waveguide Based Cavity-Backed Circularly-Polarized Antenna for Satellite Communication
Authors: Choubey Prem Narayan , Zhang Xuewei , He Tong , Hao Nan , Xu Kuiwen
Published: April 2023

This article presents the methodology to design a single-fed circularly-polarized antenna with low front-to-back ratio (FBR). A circular-patch (CPatch) antenna has been incorporated within the rectangular-cavity, made of, substrate integrated waveguide (SIW). The size of the CPatch and the SIW cavity has been chosen appropriately, in a manner, that the both resonators dominant mode coincide. This arrangement has been adopted to realize the basic radiating unit with no surface-wave and the significantly lower FBR. The circularly polarization has been excited through shorting the periphery of CPatch radiator to the “one of the two metallic grounds” of this SIW cavity. The patch periphery has been shorted from two distinct points, separated by the quarter wavelength—over center frequency of working band. The antenna has been designed and manufactured over Rogers RT/Duroid 5880 substrate with dielectric constant (εr) of 2.2, loss-tangent (tan δ, at 10 GHz) of 0.0009, and substrate height of 0.508 mm. Southwest® end launcher (SEL) along with SIW-to-GCPW (Grounded Co-Planar Waveguide) transition has been used here to facilitate the measurement of antenna’s electrical and the radiation performance. The designed antenna’s impedance bandwidth and the 3 dB axial-ratio (AR) bandwidth is 9.5% and the 2.3%, respectively. It’s simulated and the measured peak gain, within working frequency band, is higher than 8.5dBic. The proposed antenna’s FBR is antenna is significantly lower than the conventional circularly-polarized antennas. Through comparative study, with work in open literature, it has been demonstrated that the designed antenna, based on proposed method, can a potential candidate for applicable in satellite and in the other spaceborne communication system’s module—at ground and in the space station.
Radar-Assisted Multiple Base Station Cooperative mmWave Beam Tracking
Authors: Chen Kean , Liu Danpu , Zhang Zhilong
Published: April 2023

In the future vehicular networks with an increased number of transceiver antennas and higher vehicle speeds, more frequent beam switching is required to ensure the quality of communication, which poses challenges to beam tracking speed and resource efficiency. Integrated sensing and communication (ISAC) provide a new solution to cope with this problem since radar echo can help to predict the vehicle’s future location and beam direction. Therefore, we present a radar-assisted beam tracking algorithm based on Extended Kalman filtering (EKF) and multi-road side unit (RSU) cooperation in this article. Each RSU uses EKF and radar echo to predict and track the vehicle position and upload the prediction information to the edge server (ES). By deploying multiple RSUs, the ES uses the uploaded distributed sensing information for joint estimation and thus improves the accuracy of vehicle location prediction, which is used for the beam tracking task at the next moment. Considering the real complex road conditions, we investigate two scenarios where vehicles move linearly or curvilinearly. Simulation results show that the proposed method with multiple base station cooperation improves the spectral efficiency by 34% and 20% over non-cooperative beam tracking in linear and curvilinear mobility, respectively. In addition, compared with traditional beam tracking based on beam scanning and signaling feedback, radar-assisted beam tracking significantly reduces the communication overhead.
Validation and Discussion of Severity Evaluation and Disease Classification Using Tremor Video
Authors: Hayashida Takafumi , Sugiyama Takashi , Sakai Katsuya , Ishii Nobuyuki , Mochizuki Hitoshi , Zin Thi Thi
Published: April 2023

A tremor is a significant symptom of Parkinson’s disease, but it can also be a characteristic of essential tremor, thereby hampering even specialists’ ability to differentiate between the two. This study proposes a system that leverages a single RGB camera to evaluate tremor severity and support the differential diagnosis of Parkinson’s disease and essential tremor. The system captures motor symptoms, performs time–frequency analysis using wavelet transforms, and classifies severity and disease using linear classification models. The results showed an accuracy rate of 0.56 for disease classification and 0.50 for severity classification (with an acceptable accuracy rate of 0.96). The analysis indicated that there was a low level of correlation between disease and each feature and a moderate correlation (about 0.6) between severity and each feature. Based on these results, this study recommends classifying severity with a linear model and disease with a nonlinear model to obtain improved accuracy.
Survey on NLOS Identification and Error Mitigation for UWB Indoor Positioning
Authors: Wang Fang , Tang Hai , Chen Jialei
Published: April 2023

Ultra-wideband (UWB) positioning systems often operate in a non-line-of-sight (NLOS) environment. NLOS propagation has become the main source of ultra-wideband indoor positioning errors. As such, how to identify and correct NLOS errors has become a key problem that must be solved in high-accuracy indoor positioning technology. This paper firstly describes the influence of the NLOS propagation path on localization accuracy and the generation method of ultra-wideband signals, and secondly classifies and analyzes the currently available algorithms for ultra-wideband non-line-of-sight (NLOS) identification and error suppression. For the identification of NLOS, the residual analysis judgement method, statistical feature class identification method, machine learning method and geometric feature judgement method are discussed. For the suppression of NLOS propagation errors, weighting-based methods, filtering-based methods, line-of-sight reconstruction algorithms, neural network algorithms, optimization methods with constraints, and path tracing methods are discussed. Finally, we conclude the paper and point out the problems that need to be solved in NLOS indoor positioning.
Moving Target Defense for Detecting Coordinated Cyber-Physical Attacks on Power Grids via a Modified Sensor Measurement Expression
Authors: Yu Jian , Li Qiang
Published: April 2023

This paper proposes a modified sensor measurement expression for a moving target defense (MTD) strategy to detect coordinated cyber-physical attacks (CCPAs). Essentially, the MTD defense characteristics for detecting false data injection attacks (FDIAs) differ from those used to detect CCPAs. In the first case, the MTD performance in detecting FDIAs at the attack-execution stage is mainly considered, which is generally denoted by the detection probability; however, whether the construction of undetectable CCPAs is disrupted via the MTD strategy used during the attack-preparation stage is the focus of the latter case. There has been little work on the detection of undetectable CCPAs in the context of MTD post-activation. In our work, a novel approach to detecting undetectable CCPAs via a modified sensor measurement expression is proposed. First, the production mechanism for undetectable CCPAs without the application of an MTD strategy is transferred to that which occurs after MTD activation; then, based on an in-depth analysis of the CCPAs’ production mechanism after MTD activation, a novel modified sensor measurement expression is presented to detect undetectable CCPAs. Extensive simulations were conducted on three standard power systems to verify the effectiveness and simplicity of our approach to detecting CCPAs.
Deep Learning for Forecasting-Based Applications in Cyber–Physical Microgrids: Recent Advances and Future Directions
Authors: Habibi Mohammad Reza , Golestan Saeed , Guerrero Josep M. , Vasquez Juan C.
Published: April 2023

Renewable energy resources can be deployed locally and efficiently using the concept of microgrids. Due to the natural uncertainty of the output power of renewable energy resources, the planning for a proper operation of microgrids can be a challenging task. In addition, the information about the loads and the power consumption of them can create benefits to increase the efficiency of the microgrids. However, electrical loads can have uncertainty due to reasons such as unpredictable behavior of the consumers. To exploit a microgrid, energy management is required at the upper level of operation and control in order to reduce the costs. One of the most important tasks of the energy management system is to satisfy the loads and, in other words, develop a plan to maintain equilibrium between the power generation and power consumption. To obtain information about the output power of renewable energy resources and power consumption, deep learning can be implemented as a powerful tool, which is able to predict the desired values. In addition, weather conditions can affect the output power of renewable energy-based resources and the behavior of the consumers and, as a result, the power consumption. So, deep learning can be deployed for the anticipation of the weather conditions. This paper will study the recent works related to deep learning, which has been implemented for the prediction of the output power of renewable energy resources (i.e., PVs and wind turbines), electrical loads, and weather conditions (i.e., solar irradiance and wind speed). In addition, for possible future directions some strategies are suggested, the most important of which is the implementation of quantum computing in cyber–physical microgrids.
Impact Assessment of Electric Vehicle Charging in an AC and DC Microgrid: A Comparative Study
Authors: Cleenwerck Rémy , Azaioud Hakim , Vafaeipour Majid , Coosemans Thierry , Desmet Jan
Published: April 2023

This paper presents an in-depth comparison of the benefits and limitations of using a low-voltage DC (LVDC) microgrid versus an AC microgrid with regard to the integration of low-carbon technologies. To this end, a novel approach for charging electric vehicles (EVs) on low-voltage distribution networks by utilizing an LVDC backbone is discussed. The global aim of the conducted study is to investigate the overall energy losses as well as voltage stability problems on DC and AC microgrids. Both architectures are assessed and compared to each other by performing a power flow analysis. Along this line, an actual low-voltage distribution network with various penetration levels of EVs, combined with photovoltaic (PV) systems and battery energy storage systems is considered. Obtained results indicate significant power quality improvements in voltage imbalances and conversion losses thanks to the proposed backbone. Moreover, the study concludes with a discussion of the impact level of EVs and PVs penetration degrees on energy efficiency, besides charging power levels’ impact on local self-consumption reduction of the studied system. The outcomes of the study can provide extensive insights for hybrid microgrid and EV charging infrastructure designers in a holistic manner in all aspects.
Vibroacoustic Pollution in the Neonatal Ward
Authors: Lora-Martín Alberto , Sequí-Sabater Jose , del Rey-Tormos Romina , Alba-Fernández Jesús , Sequí-Canet Jose
Published: April 2023

Excessive noise pollution is often a problem for neonatal nurseries. Noise pollution involves not only noise but also vibrations. The main difference between them is that noise can be heard, and vibrations are felt. The human ear cannot detect waves outside the range of 20 Hz–20 KHz. Waves from 0 Hz to 80–100 Hz should be considered vibrations. Both can be transmitted to the neonate through the incubator’s operational mechanisms and other noise sources. Neonatal units’ noise is well studied but very little is known about vibration. This entry focuses on the importance of vibrations reaching the inside of incubators in neonatal nurseries.
Alzheimer’s Disease and Premature Ovarian Insufficiency
Authors: Vujović Svetlana , Ivović Miomira , Tančić Gajić Milina , Marina Ljiljana , Jovičić Svetlana Pavlović , Pavlović Natalija , Jovičić Milena Eric
Published: April 2023

Estradiol promotes neuronal growth, transmission, survival, myelinization, plasticity, synaptogenesis, and dendritic branching and it improves cognitive function. Alzheimer’s disease (AD) is characterized by amyloid plaques, neurofibrillary tangles, and the loss of neuronal connection in the brain. Genomic analysis has concluded that hypoestrogenism influences the APOE gene and increases the risk of AD. Premature ovarian insufficiency (POI) is defined as oligo/amenorrhea in women below 40 years of age, low estradiol, and high-gonadotropin levels. Early symptoms and signs of POI must be detected in time in order to prevent subsequent complications, such as Alzheimer’s disease. Meta-analysis has shown favorable effects of estrogen in preventing Alzheimer’s. We measured some of the typical markers of AD in women with POI such as interleukin 6 (IL-6), interleukin 8 (IL-8), tissue necrosis factor α (TNFα), TAU1, TREM2, and amyloid precursor proteins (APP). While FSH, LH, and IL-8 were significantly higher in POI group, compared to controls, testosterone and DHEAS were lower. A significant decrease in IL-6 was found in the POI group during a 6-month therapy, as well as an increase in amyloid precursor proteins. CONCLUSION: Neurological complications of POI, such as declining short-term memory, cognitive function, and dementia, have to be promptly stopped by initiating estro-progestogen therapy in POI. A long-term continuation of the therapy would be strongly advised.
Bearing Habit of Sapindus mukorossi and the Relationship between the Shoot Characteristics of the Parent and Bearing Shoots and Yield
Authors: Song Yijing , Wei Songpo , Li Chao , Qin Cai , Jia Liming , Su Shuchai
Published: April 2023

(1) Research Highlights: Sapindus mukorossi Gaertn has substantial economic and medicinal value as a high-quality raw material for energy, traditional Chinese medicine, and landscaping. However, few studies have focused on the bearing habit and shoot characteristics of S. mukorossi. (2) Background and Objectives: We aimed to investigate the bearing habit of “Yuanhua,” a selective breeding variety of S. mukorossi, and to identify the relationships among shoot characteristics, fruiting, and yield. (3) Materials and Methods: Ten healthy S. mukorossi trees were randomly selected to investigate the number of current-year shoots and bearing shoots. Eight-hundred-fifty current-year shoots of “Yuanhua” S. mukorossi were selected to investigate the number and position of the bearing and vegetative shoots. A total of 210 parent shoots and 145 bearing shoots of “Yuanhua” S. mukorossi were selected to investigate the characteristics. A generalized linear mixed model and a zero-inflated model were used for the analysis. (4) Results: (i) “Yuanhua” S. mukorossi has two types of current-year new shoots. After the new shoots produce leaves, if the growth points at the top continue to produce inflorescences that grow, bloom, and bear fruits, the new shoots are classified as bearing shoots. When the top growth points do not grow and do not produce inflorescences, the new shoots are termed vegetative shoots. The bearing shoots and vegetative shoots sprouted on the S. mukorossi parent shoots and developed into parent shoots in the following year, either developing from the bearing shoots or the vegetative shoots. (ii) The yield was affected by parent shoot characteristics. The type, length, diameter, and slenderness of parent shoots had significant effects on the number of current-year bearing shoots; the top diameter of the parent shoots and the number of current-year vegetative shoots had significant effects on parent shoot yield. (iii) The type of parent shoots, the length, and the top diameter of the current-year bearing shoots had significant effects on the single yield of a bearing shoot. (5) Conclusions: Selecting parent shoots with more bearing shoots and more fruit production according to the type, length, and thickness is a more efficient method for production management.
Effect of Lipid Type on the Acidogenic Performance of Food Waste
Authors: Liu Chao , Li Sheng , Niu Hongyu , Yang Haijun , Tan Ju , Zhang Jiachao , Ren Liheng , Yan Binghua
Published: April 2023

Due to its high lipid content and intricate constitution, food waste poses a considerable challenge for biotreatment. This research aims to investigate the potential influence of diverse lipid species on anaerobic fermentation, induced by the varying dietary patterns observed in distinct regions. The investigation involved incorporating 5% (w/w) of beef tallow, mutton fat, soybean oil, peanut oil, and rapeseed oil, separately, into simulated food waste, and subjected it to batch mode acidogenic fermentation. The inclusion of unsaturated fatty acids resulted in a redirection of the metabolic pathway from the lactic acid type to the ethanol, acetic acid, and butyric acid types. The succession of the acidogenic metabolic pathway was highly correlated with the lipid types; beef tallow, mutton fat, soybean oil, and peanut oil delayed the metabolic process by 1, 2, 3, and 8 d, respectively, whereas rapeseed oil accelerated it by 2 d. The lipids contained within the food waste did not facilitate the buildup of soluble substances, resulting in a decrease of 14.0~59.7%. Notwithstanding, valeric acid was exclusively generated during the beef tallow and peanut oil treatments, whereas the production of lactic acid in peanut oil showed a 35.9% increase in comparison to the control.
Effective IoT Congestion Control Algorithm
Authors: Hasan Husam H. , Alisa Zainab T.
Published: April 2023

The Internet of Things (IoT) connects devices via the Internet. Network congestion is one of the key problems that has been identified by researchers in the IoT field. When there is a huge number of IoT devices connected to the internet, this creates network congestion. Transfer control protocol is a transport layer protocol that provides a reliable end-to-end connection between two devices. Many Congestion Control Algorithms have been proposed to solve network congestion. However, there is no perfect solution to this problem. This paper proposes an effective loss-based Congestion Control Algorithm to effectively adapt the congestion window in the IoT environment. It uses simple experiment scenarios to test the algorithm for wired and wireless channels and observes important performance metrics: link utilization, inter-protocol fairness, intra-protocol fairness and throughput. The results are impressive, and the proposed algorithm is shown to outperform other standard algorithms.
Contrastive Refinement for Dense Retrieval Inference in the Open-Domain Question Answering Task
Authors: Zhai Qiuhong , Zhu Wenhao , Zhang Xiaoyu , Liu Chenyun
Published: April 2023

In recent years, dense retrieval has emerged as the primary method for open-domain question-answering (OpenQA). However, previous research often focused on the query side, neglecting the importance of the passage side. We believe that both the query and passage sides are equally important and should be considered for improved OpenQA performance. In this paper, we propose a contrastive pseudo-labeled data constructed around passages and queries separately. We employ an improved pseudo-relevance feedback (PRF) algorithm with a knowledge-filtering strategy to enrich the semantic information in dense representations. Additionally, we proposed an Auto Text Representation Optimization Model (AOpt) to iteratively update the dense representations. Experimental results demonstrate that our methods effectively optimize dense representations, making them more distinguishable in dense retrieval, thus improving the OpenQA system’s overall performance.
CFD-Based Validation Study on the Fire Prevention Wisdom of Ancient Village Houses in Western Hunan
Authors: Zhang Fupeng , Shi Lei , Liu Simian , Zhang Chi , Liu Zhezheng
Published: April 2023

Ancient villages are precious architectural treasures that have been protected from fire hazards for centuries through traditional fire prevention strategies. However, research on traditional fire response strategies is limited, with existing studies mainly focusing on climate response strategies, conservation, and renewal. No prior research has revealed the quantitative fire response strategies used for ancient buildings. This paper takes the first ancient village in western Hunan, High-Chair village, as an example, and it (1) assesses the fire risk of High-Chair village; (2) determines the traditional fire response strategies of the ancient village, including fire prevention culture, residential layout, wall forms, and fire resistant materials; and (3) uses CFD simulation to reveal and verify the science and rationale of the traditional patio layout and hill wall forms. The study suggests utilizing CFD simulation to quantitatively assess and validate fire response strategies. Such knowledge of fire prevention can provide fire mitigation solutions for rural construction.
Total Value Adjustment of Multi-Asset Derivatives under Multivariate CGMY Processes
Authors: Wu Fengyan , Ding Deng , Yin Juliang , Lu Weiguo , Yuan Gangnan
Published: April 2023

Counterparty credit risk (CCR) is a significant risk factor that financial institutions have to consider in today’s context, and the COVID-19 pandemic and military conflicts worldwide have heightened concerns about potential default risk. In this work, we investigate the changes in the value of financial derivatives due to counterparty default risk, i.e., total value adjustment (XVA). We perform the XVA for multi-asset option based on the multivariate Carr–Geman–Madan–Yor (CGMY) processes, which can be applied to a wider range of financial derivatives, such as basket options, rainbow options, and index options. For the numerical methods, we use the Monte Carlo method in combination with the alternating direction implicit method (MC-ADI) and the two-dimensional Fourier cosine expansion method (MC-CC) to find the risk exposure and make value adjustments for multi-asset derivatives.
Legal Framework for Rear-End Crashes in Mixed-Traffic Platooning: A Matrix Game Approach
Authors: Chen Xu , Di Xuan
Published: April 2023

Autonomous vehicles (AV) hold great potential to increase road safety, reduce traffic congestion, and improve mobility systems. However, the deployment of AVs introduces new liability challenges when they are involved in car accidents. A new legal framework should be developed to tackle such a challenge. This paper proposes a legal framework, incorporating liability rules to rear-end crashes in mixed-traffic platoons with AVs and human-propelled vehicles (HV). We leverage a matrix game approach to understand interactions among players whose utility captures crash loss for drivers according to liability rules. We investigate how liability rules may impact the game equilibrium between vehicles and whether human drivers’ moral hazards arise if liability is not designed properly. We find that compared to the no-fault liability rule, contributory and comparative rules make road users have incentives to execute a smaller reaction time to improve road safety. There exists moral hazards for human drivers when risk-averse AV players are in the car platoon.
Features of Liver Injury in COVID-19 Pathophysiological, Biological and Clinical Particularities
Authors: Marginean Cristina Maria , Cinteza Eliza , Vasile Corina Maria , Popescu Mihaela , Biciusca Viorel , Docea Anca Oana , Mitrut Radu , Popescu Marian Sorin , Mitrut Paul
Published: April 2023

The outbreak of the coronavirus pandemic in March 2020 has caused unprecedented pressure on public health and healthcare. The spectrum of COVID-19 onset is large, from mild cases with minor symptoms to severe forms with multi-organ dysfunction and death. In COVID-19, multiple organ damage has been described, including lung damage, acute kidney injury, liver damage, stroke, cardiovascular and digestive tract disorders. The aspects of liver injury are different, sometimes presenting with only a slight increase in liver enzymes, but sometimes with severe liver injury, leading to acute liver failure requiring liver transplantation. In patients with chronic liver disease, especially liver cirrhosis, immune dysfunction can increase the risk of infection. Immune dysfunction has a multifactorial physiopathological mechanism, implying a complement system and macrophage activation, lymphocyte and neutrophil activity dysfunction, and intestinal dysbiosis. This review aims to evaluate the most relevant studies published in the last years related to the etiopathogenetic, biochemical, and histological aspects of liver injury in patients diagnosed with COVID-19. Liver damage is more evident in patients with underlying chronic liver disease, with a significantly higher risk of developing severe outcomes of COVID-19 and death. Systemic inflammation, coagulation disorders, endothelial damage, and immune dysfunction explain the pathogenic mechanisms involved in impaired liver function. Although various mechanisms of action of SARS-CoV-2 on the liver cell have been studied, the impact of the direct viral effect on hepatocytes is not yet established.
Phenotypes and Genotypes in Patients with SMC1A-Related Developmental and Epileptic Encephalopathy
Authors: Bozarth Xiuhua L. , Lopez Jonathan , Fang He , Lee-Eng Jacqueline , Duan Zhijun , Deng Xinxian
Published: April 2023

The X-linked SMC1A gene encodes a core subunit of the cohesin complex that plays a pivotal role in genome organization and gene regulation. Pathogenic variants in SMC1A are often dominant-negative and cause Cornelia de Lange syndrome (CdLS) with growth retardation and typical facial features; however, rare SMC1A variants cause a developmental and epileptic encephalopathy (DEE) with intractable early-onset epilepsy that is absent in CdLS. Unlike the male-to-female ratio of 1:2 in those with CdLS associated with dominant-negative SMC1A variants, SMC1A-DEE loss-of-function (LOF) variants are found exclusively in females due to presumed lethality in males. It is unclear how different SMC1A variants cause CdLS or DEE. Here, we report on phenotypes and genotypes of three females with DEE and de novo SMC1A variants, including a novel splice-site variant. We also summarize 41 known SMC1A-DEE variants to characterize common and patient-specific features. Interestingly, compared to 33 LOFs detected throughout the gene, 7/8 non-LOFs are specifically located in the N/C-terminal ATPase head or the central hinge domain, both of which are predicted to affect cohesin assembly, thus mimicking LOFs. Along with the characterization of X-chromosome inactivation (XCI) and SMC1A transcription, these variants strongly suggest that a differential SMC1A dosage effect of SMC1A-DEE variants is closely associated with the manifestation of DEE phenotypes.
Retinal Phenotyping of a Murine Model of Lafora Disease
Authors: Vincent Ajoy , Ahmed Kashif , Hussein Rowaida , Berberovic Zorana , Tumber Anupreet , Zhao Xiaochu , Minassian Berge A.
Published: April 2023

Lafora disease (LD) is a progressive neurologic disorder caused by biallelic pathogenic variants in EPM2A or EPM2B, leading to tissue accumulation of polyglucosan aggregates termed Lafora bodies (LBs). This study aimed to characterize the retinal phenotype in Epm2a−/− mice by examining knockout (KO; Epm2a−/−) and control (WT) littermates at two time points (10 and 14 months, respectively). In vivo exams included electroretinogram (ERG) testing, optical coherence tomography (OCT) and retinal photography. Ex vivo retinal testing included Periodic acid Schiff Diastase (PASD) staining, followed by imaging to assess and quantify LB deposition. There was no significant difference in any dark-adapted or light-adapted ERG parameters between KO and WT mice. The total retinal thickness was comparable between the groups and the retinal appearance was normal in both groups. On PASD staining, LBs were observed in KO mice within the inner and outer plexiform layers and in the inner nuclear layer. The average number of LBs within the inner plexiform layer in KO mice were 1743 ± 533 and 2615 ± 915 per mm2, at 10 and 14 months, respectively. This is the first study to characterize the retinal phenotype in an Epm2a−/− mouse model, demonstrating significant LB deposition in the bipolar cell nuclear layer and its synapses. This finding may be used to monitor the efficacy of experimental treatments in mouse models.
Genome-Wide Association Study Reveals the Genetic Basis of Duck Plumage Colors
Authors: Zhang Xinye , Zhu Tao , Wang Liang , Lv Xueze , Yang Weifang , Qu Changqing , Li Haiying , Wang Huie , Ning Zhonghua , Qu Lujiang
Published: April 2023

Plumage color is an artificially and naturally selected trait in domestic ducks. Black, white, and spotty are the main feather colors in domestic ducks. Previous studies have shown that black plumage color is caused by MC1R, and white plumage color is caused by MITF. We performed a genome-wide association study (GWAS) to identify candidate genes associated with white, black, and spotty plumage in ducks. Two non-synonymous SNPs in MC1R (c.52G>A and c.376G>A) were significantly related to duck black plumage, and three SNPs in MITF (chr13:15411658A>G, chr13:15412570T>C and chr13:15412592C>G) were associated with white plumage. Additionally, we also identified the epistatic interactions between causing loci. Some ducks with white plumage carry the c.52G>A and c.376G>A in MC1R, which also compensated for black and spotty plumage color phenotypes, suggesting that MC1R and MITF have an epistatic effect. The MITF locus was supposed to be an upstream gene to MC1R underlying the white, black, and spotty colors. Although the specific mechanism remains to be further clarified, these findings support the importance of epistasis in plumage color variation in ducks.
Maternal Immune Activation and Enriched Environments Impact B2 SINE Expression in Stress Sensitive Brain Regions of Rodent Offspring
Authors: Richter Troy A. , Aiken Ariel A. , Puracchio Madeline J. , Maganga-Bakita Ismael , Hunter Richard G.
Published: April 2023

Early life stress (ELS) can have wide-spread neurodevelopmental effects with support accumulating for the idea that genomic mechanisms may induce lasting physiological and behavioral changes following stress exposure. Previous work found that a sub-family of transposable elements, SINEs, are repressed epigenetically after acute stress. This gives support to the concept that the mammalian genome may be regulating retrotransposon RNA expression allowing for adaptation in response to environmental challenges, such as maternal immune activation (MIA). Transposon (TE) RNAs are now thought to work at the epigenetic level and to have an adaptive response to environmental stressors. Abnormal expression of TEs has been linked to neuropsychiatric disorders like schizophrenia, which is also linked to maternal immune activation. Environmental enrichment (EE), a clinically utilized intervention, is understood to protect the brain, enhance cognitive performance, and attenuate responses to stress. This study examines the effects of MIA on offspring B2 SINE expression and further, the impact that EE, experienced throughout gestation and early life, may have in conjunction with MIA during development. Utilizing RT-PCR to quantify the expression of B2 SINE RNA in the juvenile brain of MIA exposed rat offspring, we found dysregulation of B2 SINE expression associated with MIA in the prefrontal cortex. For offspring experiencing EE, the prefrontal cortex exhibited an attenuation of the MIA response observed in standard housed animals. Here, the adaptive nature of B2 is observed and thought to be aiding in the animal’s adaptation to stress. The present changes indicate a wide-spread stress-response system adaptation that impacts not only changes at the genomic level but potentially observable behavioral impacts throughout the lifespan, with possible translational relevance to psychotic disorders.
Cloning, Expression Analysis and SNP Screening of the kiss1 Gene in Male Schizothorax biddulphi
Authors: Nie Zhulan , Zhao Nianhua , Zhao He , Fu Zhengyi , Ma Zhenhua , Wei Jie
Published: April 2023

Schizothorax biddulphi is an endemic fish distributed only in southern Xinjiang, China. Due to overfishing, water conservancy facilities, and other factors, as well as inherent biological limitations, resource recovery is quite difficult. For endangered fish with slow growth, late sexual maturity, and insufficient natural population supplementation, large-scale artificial reproduction and breeding are important for restoring resources. Therefore, it is urgent to optimize the reproductive regulation methods of the fish. The kiss1 gene is a key regulator of the reproductive regulation cascade, and identifying and analyzing the role of kiss1 are important for further elucidating the reproductive mechanism of S. biddulphi. To understand the characteristics of the kiss1 of S. biddulphi, the full-length cDNA sequence of kiss1 was obtained in this study, and its tissue expression specificity and association with phenotypic traits were analyzed in male fish. The full-length cDNA sequence of kiss1 in S. biddulphi was 658 bp, with an ORF of 327 bp, and encoded a 108-amino acid, unstable protein. Homology results indicated that kiss1 was highly conserved. qPCR showed kiss1 expression in different tissues in male S. biddulphi, with the highest expression in the gonads, followed by muscle, and significantly lower expression in the swim bladder, pituitary gland, heart, hypothalamus, gill, fin, liver, eye, and mid-kidney. qPCR revealed three SNP loci in the exonic region of kiss1. The c.3G>T locus was significantly correlated (p < 0.05) with gonad mass and the maturation coefficient in S. biddulphi. These results will help uncover the reproductive endocrinology network of S. biddulphi, improve artificial breeding technology for fish, and unveil new directions for breeding excellent strains of S. biddulphi and molecular marker-assisted breeding.
Numerical Experiments for Surfactant Infiltration in the Vadose Zone to Demonstrate Concentration-Dependent Capillarity, Viscosity, and Sorption Characteristics
Authors: Boduroglu Sebnem , Bashir Rashid
Published: April 2023

Surfactants (i.e., solutes that reduce the surface tension of water) exist in the subsurface either naturally or are introduced to the subsurface due to anthropogenic activities (e.g., agricultural purposes, environmental remediation strategies). Surfactant-induced changes in surface tension, contact angle, density, and viscosity alter the water retention and conduction properties of the vadose zone. This research numerically investigates the effects of surfactants in the vadose zone by comparing the flow and transport of three different surfactant solutions, namely butanol, ethanol, and Triton X-100. For each surfactant case, surfactant-specific concentration-dependent surface tension, contact angle, density, and viscosity relationships were incorporated by modifying a finite element unsaturated flow and transport code. The modified code was used to simulate surfactant infiltration in the vadose zone at residual state under intermittent boundary conditions. The modelling results show that all three surfactant solutions led to unique and noteworthy differences in comparison to the infiltration of pure water containing a conservative tracer. Results indicate that surfactant infiltrations led to complex patterns with reduced vertical movement and enhanced horizontal spreading, which are a function of concentration-dependent surface tension, density, contact angle, viscosity and sorption characteristics. The findings of this research will help understanding the effects of surfactant presence in the subsurface on unsaturated flow and its possible links to future environmental problems.
Efficacy of Colour Protectors in Urban Art Paintings under Different Conditions: From a Real Mural to the Laboratory
Authors: Alonso-Villar Enrique M. , Rivas Teresa , Pozo-Antonio José S. , Pellis Giulia , Scalarone Dominique
Published: April 2023

Contemporary muralism is one of the most widespread manifestations of urban art in cities nowadays. Loss of colour (fading) due to degradation of the pictorial materials is one of the main manifestations of deterioration in this type of artwork. However, the application of protective coatings is considered to slow down fading. In this study, two acrylic-based protective coatings were applied to selected areas of a real mural painted with six different alkyd paints and one acrylic paint. The impact of the protective coatings on the original paint colour and the long-term efficacy were evaluated. For purposes of comparison, the same protective coatings were applied to paint mock-ups prepared under controlled conditions and exposed to an outdoor environment with marine influence and to an ultraviolet aging test. At the end of the exposure periods, physical and chemical changes were evaluated using a multi-analytical approach based on stereomicroscopy, Fourier transform infrared spectroscopy and scanning electron microscopy. Both protective coatings modified the original colour of the paints, with the impact being greater in the mural than in the mock-ups. The efficacy of the coatings as colour protectors is more appreciable in the most colour-stable paints. Thus, neither of the coatings provided good protection for the paints most sensitive to deterioration. The protective efficacy of the coatings was also influenced by their chemical composition and affinity for the painted surfaces.
Relationship between Muscle Strength and Gait Parameters in Healthy Older Women and Men
Authors: Stotz Andreas , Hamacher Daniel , Zech Astrid
Published: April 2023

Maintaining sufficient muscle strength is fundamental to prevent a decline in basic physical functions such as gait, and is therefore a prerequisite for a healthy independent life in older people. However, the relationship between gait parameters and the strength of single muscle groups is reported with inconclusive results. The objective of this study was to analyze the relationship of strength of nine single muscle groups of lower and upper leg muscles as well as handgrip strength for gait parameters in older adults. Sixty-nine independently living older adults participated in the study. Maximum ankle plantar- and dorsiflexion, knee flexion and extension, as well as hip abduction, adduction, flexion, and extension strength, were measured using an isokinetic dynamometer. Additionally, hand grip strength measured via a hand dynamometer was obtained. Walking gait parameters were recorded with a 3D motion capture system on an instrumented treadmill. The relationships between multiple strength and gait variables were analyzed by Pearson’s correlation coefficient. Linear regression analyses were performed to identify the predictive ability of muscle strength (normalized to body weight) for gait speed, stride time, stance time, stride length and step width. Multiple significant weak to moderate positive ([r = 0.343, p = 0.047]–[r = 0.538, p = 0.002]) and negative ([r = −0.340, p = 0.046]–[r = 0.593, p = 0.001]) correlations that were unequally distributed between both sexes were detected. Significant regression models explained ([r2 = 16.6%, p = 0.015]–[r2 = 44.3 %, p = 0.003]) and ([r2 = 21.8%, p = 0.022]–[r2 = 36.1%, p = 0.044]) of the gait parameter variations for men and women, respectively. The results suggest a sex-specific relevance of single muscle groups for all gait parameters. This may be attributed to anatomical differences and it is important to prevent strength-related changes in gait parameters.