bluuebunny/crossref_metadata_2025 huggingface dataset:
Speech Enhancement Based on Enhanced Empirical Wavelet Transform and Teager Energy Operator
Authors: Kuwałek Piotr , Jęśko Waldemar
Published: July 2023

This paper presents a new speech-enhancement approach based on an enhanced empirical wavelet transform, considering the time and scale adaptation of thresholds for individual component signals obtained from the used transform. The time adaptation is performed using the Teager energy operator on the individual component signals, and the scale adaptation of thresholds is performed by the modified level-dependent threshold principle for the individual component signals. The proposed approach does not require an explicit estimation of the noise level or a priori knowledge of the signal-to-noise ratio as is usually needed in most common speech-enhancement methods. The effectiveness of the proposed method has been assessed based on over 1000 speech recordings from the public Librispeech database. The research included various types of noise (among others white, violet, brown, blue, and pink) and various types of disturbance (among others traffic sounds, hair dryer, and fan), which were added to the selected test signals. The score of perceptual evaluation of speech quality, allowing for the assessment of the quality of enhanced speech, and signal-to-noise ratio, allowing for the assessment of the effectiveness of disturbance attenuation, are selected for the evaluation of the resultant effectiveness of the proposed approach. The resultant effectiveness of the proposed approach is compared with other selected speech-enhancement methods or denoising techniques available in the literature. The experimental research results show that the proposed method performs better than conventional methods in many types of high-noise conditions in terms of producing less residual noise and lower speech distortion.
Graph Embedding-Based Money Laundering Detection for Ethereum
Authors: Liu Jiayi , Yin Changchun , Wang Hao , Wu Xiaofei , Lan Dongwan , Zhou Lu , Ge Chunpeng
Published: July 2023

The number of money laundering crimes for Ethereum and the amount involved have grown exponentially in recent years. However, previous studies related to anomaly detection for Ethereum usually consider multiple types of financial crimes as a whole, ignoring the apparent differences between money laundering and other malicious activities and lacking a more granular detection targeting money laundering. In this paper, for the first time, we propose an improved graph embedding algorithm specifically for money laundering detection called GTN2vec. By mining Ethereum transaction records, the algorithm comprehensively considers the behavioral patterns of money launderers and structural information of transaction networks and can automatically extract features of money laundering addresses. Specifically, we fuse the gas price and timestamp from the transaction records into a new weight and set appropriate return and exploration parameters to modulate the sampling tendency of random walk to characterize the money laundering nodes. We construct the dataset using real Ethereum data and evaluate the effectiveness of GTN2vec on the dataset by various classifiers such as random forest. The experimental results show that GTN2vec can accurately and effectively extract money laundering account features and significantly outperform other advanced graph embedding methods.
Edge-Computing-Enabled Low-Latency Communication for a Wireless Networked Control System
Authors: Mtowe Daniel Poul , Kim Dong Min
Published: July 2023

This study proposes a novel strategy for enhancing low-latency control performance in Wireless Networked Control Systems (WNCSs) through the integration of edge computing. Traditional networked control systems require the receipt of raw data from remote sensors to enable the controller to generate an appropriate control command, a process that can result in substantial periodic communication traffic and consequent performance degradation in some applications. To counteract this, we suggest the use of edge computing to preprocess the raw data, extract the essential features, and subsequently transmit them. Additionally, we introduce an adaptive scheme designed to curtail frequent data traffic by adaptively modifying periodic data transmission based on necessity. This scheme is achieved by refraining from data transmission when a comparative analysis of the previously transmitted and newly generated data shows no significant change. The effectiveness of our proposed strategy is empirically validated through experiments conducted on a remote control system testbed using a mobile robot that navigates the road by utilizing camera information. Through leveraging edge computing, only 3.42% of the raw data was transmitted. Our adaptive scheme reduced the transmission frequency by 20%, while maintaining an acceptable control performance. Moreover, we conducted a comparative analysis between our proposed solution and the state-of-the-art communication framework, WebRTC technology. The results demonstrate that our method effectively reduces the latency by 58.16% compared to utilizing the WebRTC alone in a 5G environment. The experimental results confirm that our proposed strategy significantly improves the latency performance of a WNCS.
Vertical Federated Unlearning on the Logistic Regression Model
Authors: Deng Zihao , Han Zhaoyang , Ma Chuan , Ding Ming , Yuan Long , Ge Chunpeng , Liu Zhe
Published: July 2023

Vertical federated learning is designed to protect user privacy by building local models over disparate datasets and transferring intermediate parameters without directly revealing the underlying data. However, the intermediate parameters uploaded by participants may memorize information about the training data. With the recent legislation on the“right to be forgotten”, it is crucial for vertical federated learning systems to have the ability to forget or remove previous training information of any client. For the first time, this work fills in this research gap by proposing a vertical federated unlearning method on logistic regression model. The proposed method is achieved by imposing constraints on intermediate parameters during the training process and then subtracting target client updates from the global model. The proposed method boasts the advantages that it does not need any new clients for training and requires only one extra round of updates to recover the performance of the previous model. Moreover, data-poisoning attacks are introduced to evaluate the effectiveness of the unlearning process. The effectiveness of the method is demonstrated through experiments conducted on four benchmark datasets. Compared to the conventional unlearning by retraining from scratch, the proposed unlearning method has a negligible decrease in accuracy but can improve training efficiency by over 400%.
Open Innovation for the Construction Sector: Concept Overview and Test Bed Development to Boost Energy-Efficient Solutions
Authors: Salvalai Graziano , Sesana Marta Maria , Dell’Oro Paolo , Brutti Diletta
Published: July 2023

Open innovation has recently emerged as an important concept in both academic research and industrial practice, and it is now also becoming increasingly important in the public policy field due to the innovation challenges in different domains, such as climate change, sustainability, and growth to name a few, but only in some value chains (i.e., automotive, manufacturing, aerospace). According to a report by McKinsey and Co., the construction industry lags behind others in adopting innovations; in fact, less than 1% of the construction industry’s revenue goes back into technology research and development. This work focuses on the current debate on the underdeveloped application of the open innovation (OI) approach to the construction sector. Namely, the foundational question is whether the OI model can be the answer to boosting innovation for the decarbonization of buildings. The research goal is to go a step further by analyzing its internal effectiveness, focusing on introducing and defining the Open Innovation Test Bed (OITB) concept. The study provides a systematic and bibliometric literature review of OI starting from a critical analysis of the concept definition and the evolution of the paradigm from the initial application to the first declination for the construction sector. All the steps analyzed allowed us to make an overall and comprehensive review of the OI concept, which is usually applied to other sectors, considering the ecosystem as the most effective declination of the OI paradigm for OITB development for building envelope solutions, thus providing answers to the two objectives identified in the introduction. Finally, the limitations of prior OI studies and the challenges for the OITB new construction paradigm are discussed, and we make recommendations for future opportunities and approach development to tackle and boost energy-efficient envelope solutions for the construction industries.
Study on Flow and Heat Transfer Characteristics and Anti-Clogging Performance of Tree-Like Branching Microchannels
Authors: Shui Linqi , Hu Zhongkai , Song Hang , Zhai Zhi , Wang Jiatao
Published: July 2023

In this paper, a tree-like branching microchannel with bifurcating interconnections is designed for gas turbine blade cooling. A theoretical analysis, experimental study, and numerical simulation of the heat transfer and hydrodynamic characteristics of the tree-like branching microchannel is performed, and the influence of the total number of branching levels m on the anti-clogging performance is also studied. The results indicate that the total heat transfer ratio and pressure drop ratio are closely related to the structur ne parameters. The comprehensive thermal performance increase with an increase in the ratio of Lb/L0 and fractal dimension D. Nu/Nus, f/fs, and η are increased as m increases from 3 to 5. Furthermore, the tree-like microchannel network exhibits robustness for cooling gas turbine blades. A greater total number of branching levels and a higher Re number are advantageous for enhancing the anti-clogging performance of the tree-like branching microchannel.
The State of the Art of Laminar Burning Velocities of H2-Enriched n-C4H10–Air Mixtures
Authors: Movileanu Codina , Mitu Maria , Giurcan Venera
Published: July 2023

Currently, hydrogen-enriched n-butane blends present a real interest due to their potential to reduce emissions and increase the efficiency of combustion processes, as an alternative fuel for internal combustion engines. This paper summarises the recent research on laminar burning velocities of hydrogen-enriched n-C4H10–air mixtures. The laminar burning velocity is a significative parameter that characterises the combustion process of any fuel–air mixture. Accurately measured or computed laminar burning velocities have an important role in the design, testing, and performance of n-C4H10–H2 fuelled devices. With this perspective, a brief review on the influence of hydrogen amount, initial pressure and temperature, and equivalence ratio on the laminar burning velocity of hydrogen-enriched n-C4H10–air mixtures is presented. Hydrogen has a strong influence on the combustion of butane–air mixtures. It was observed that a parabola with a maximum at a value slightly higher than the stoichiometric ratio describes the variation in the laminar burning velocity of hydrogen-enriched n-butane–air mixtures with the equivalence ratio. An increase in initial pressure or hydrogen amount led to an increase in this important combustion parameter, while an increase in initial pressure led to a decrease in laminar burning velocity. Overall, these studies demonstrate that hydrogen addition to n-C4H10–air mixtures can increase the laminar burning velocity and flame temperature and improve flame stability. These findings could be useful for the optimisation of combustion processes, particularly in internal combustion engines and gas turbines. However, the literature shows a paucity of investigations on the laminar burning velocities of hydrogen-enriched n-C4H10–air mixtures at initial temperatures and pressures differing from those in ambient conditions. This suggests that experimental and theoretical investigations of these flames at sub-atmospheric and elevated pressures and temperatures are necessary.
Machine Learning Estimation of Battery Efficiency and Related Key Performance Indicators in Smart Energy Systems
Authors: Luque Joaquín , Tepe Benedikt , Larios Diego , León Carlos , Hesse Holger
Published: July 2023

Battery systems are extensively used in smart energy systems in many different applications, such as Frequency Containment Reserve or Self-Consumption Increase. The behavior of a battery in a particular operation scenario is usually summarized using different key performance indicators (KPIs). Some of these indicators such as efficiency indicate how much of the total electric power supplied to the battery is actually used. Other indicators, such as the number of charging-discharging cycles or the number of charging-discharging swaps, are of relevance for deriving the aging and degradation of a battery system. Obtaining these indicators is very time-demanding: either a set of lab experiments is run, or the battery system is simulated using a battery simulation model. This work instead proposes a machine learning (ML) estimation of battery performance indicators derived from time series input data. For this purpose, a random forest regressor has been trained using the real data of electricity grid frequency evolution, household power demand, and photovoltaic power generation. The results obtained in the research show that the required KPIs can be estimated rapidly with an average relative error of less than 10%. The article demonstrates that the machine learning approach is a suitable alternative to obtain a very fast rough approximation of the expected behavior of a battery system and can be scaled and adapted well for estimation queries of entire fleets of battery systems.
Performance Analysis and Comprehensive Evaluation of Solar Organic Rankine Cycle Combined with Transcritical CO2 Refrigeration Cycle
Authors: Zhang Na , Xu Po , Wang Yiming , Tong Wencai , Yang Zhao
Published: July 2023

In order to achieve efficient utilization of solar energy resources, this study combines the trans-critical organic Rankine cycle (ORC) power cycle (TORC) with the trans-critical CO2 refrigeration cycle (TCO2). Additionally, a comprehensive three-level index decision evaluation system is developed based on system safety and environmental protection, thermodynamics, and techno-economic performance. The evaluation focuses on typical medium- and high-temperature solar energy applications and considers six organic working gases. The evaluation results demonstrate that the R600 + CO2 solution outperformed the others. This solution achieved a maximum net output power (Pnet) of 1531.31 kW and 2306.43 kW, a maximum coefficient of performance (COP) of 3.16, a predicted payback period of 2.651 years and 2.033 years, and a benefit–investment ratio of 4.533 and 5.773.
Experimental Investigation of a Self-Sustained Liquid Fuel Burner Using Inert Porous Media
Authors: Gao Huaibin , Wang Yongyong , Zong Shouchao , Ma Yu , Zhang Chuanwei
Published: July 2023

A self-sustained porous burner without a sprayed atomizer was built for diesel oil. It consisted of metal fiber felt as an evaporator upstream and ceramic foam as an emitter downstream. The liquid fuel underwent film boiling in the porous evaporator and was rapidly evaporated by the heat recirculated from the porous emitter to the porous evaporator through intense irradiative heat flux. The effect of the porous structure and its installation location on the performance of the porous burner was investigated. The results indicated that the evaporation and combustion of liquid fuel could be prompted by the radiation of porous media. The position of the flame moved downstream, and the flame temperature decreased when the distance between the metal fiber felt and the ceramic foam was increased. The lowest NOx concentration was obtained when the distance between the foam and the metal fiber felt was 90 mm. When the diameter of the central hole of the ceramic foam was increased, the position of the flame moved towards the burner outlet, and the flame temperature and NOx emission declined. The flame temperature of the divergent configuration as emitter was higher than that of the convergent configuration, and the flame temperature of the C–D configuration was higher than that of the D–C configuration. Different ceramic foam structures had a significant effect on the temperature and emission in the combustion chamber, which showed that the evaporation and radiation performance of inert porous media burners with different structures is quite different.
Balanced Charging Algorithm for CHB in an EV Powertrain
Authors: Gemma Filippo , Tresca Giulia , Formentini Andrea , Zanchetta Pericle
Published: July 2023

The scientific literature acknowledges cascaded H-bridge (CHB) converters as a viable alternative to two-level inverters in electric vehicle (EV) powertrain applications. In the context of an electric vehicle engine connected to a DC charger, this study introduces a state of charge (SOC)-governed method for charging li-ion battery modules using a cascaded H-bridge converter. The key strength of this algorithm lies in its ability to achieve balanced charging of battery modules across all three-phase submodules while simultaneously controlling the DC charger, eliminating the need for an additional intermediate converter. Moreover, the algorithm is highly customizable, allowing adaptation to various configurations involving different numbers of submodules per phase. Simulative and experimental results are presented to demonstrate the effectiveness of the proposed charging algorithm, validating its practical application.
Improving Compliance with Medical Treatment Using Eye Drop Aids
Authors: Biran Amit , Goldberg Mordechai , Shemesh Nadav , Achiron Asaf
Published: July 2023

Achieving optimal treatment outcomes in glaucoma requires patients to adhere to their medication regimens. Possible barriers to patients’ cooperation include the misunderstanding of a treatment’s importance or errors in applying instructions, forgetfulness, financial constraints and others. Due to the fact that glaucoma usually causes no apparent symptoms or pain, on the one hand, and the significant inconvenience that the eye drops used for glaucoma treatment can cause due to local irritation, on the other, patient compliance is a challenge. To address this challenge, we require strategies for improving adherence to glaucoma treatment. The importance of proper eye drop administration techniques cannot be overstated, particularly for vulnerable populations such as the elderly, the sick and the visually handicapped. Studies have shown that failure to comply with glaucoma treatment is a significant factor affecting disease progression, emphasizing the need for interventions that improve patient compliance. Educational interventions, medication reminders and the use of assistive devices such as eye drop aids have been shown to improve adherence to glaucoma treatment. By promoting strategies that can be used to enhance treatment adherence, healthcare providers can ensure that glaucoma patients receive the full benefits of their treatment plans, reducing the risk of disease progression. Many patients struggle with the complexity of their treatment regimens and the challenges of administering eye drops. This entry provides a comprehensive overview of the different barriers to patient adherence to glaucoma eye drop treatment, emphasizing the difficulties associated with eye drop instillation. This entry examines a range of eye drop aids available to patients, evaluating their modes of action, benefits, drawbacks and effectiveness in improving patient compliance. By providing detailed information on the barriers to adherence and the range of eye drop aids available, this entry aims to support healthcare providers in helping glaucoma patients to achieve better treatment adherence and outcomes.
Distribution, Potential Sources, and Health Risk of Microplastics (MPs) in Street Dust during and after COVID-19 Lockdown in Bangladesh
Authors: Rabin Mominul Haque , Wang Qingyue , Enyoh Christian Ebere , Kai Xiao , Sheuty Tasnoba Firoze
Published: July 2023

The advent of the COVID-19 era has ushered in significant changes to both the environment and daily life. During the COVID-19 lockdown, a unique opportunity emerged to improve environmental quality and mitigate certain impacts on the planet. The distribution and health risks of microplastics (MPs) in the street dust of Dhaka city, Bangladesh during and after COVID-19 lockdowns were examined in this study. The study covered sites selected based on land usage, including an industrial area (IA), commercial area (CA), public facilities area (PFA), and residential area (RA). The particles in the dust samples were analyzed using a fluorescent microscope and attenuated total reflectance Fourier-transform infrared spectroscopy. The results show that the maximum number of MP particles/g of street dust sample was recorded from industrial areas (17.33 MP particles/g) and the minimum was recorded from residential areas (13.99 MP particles/g) without lockdown. The trends in the MPs were as follows: without lockdown > partial lockdown > complete lockdown. Risk analysis showed that the MPs in dust pose low non-carcinogenic risk to inhabitants of the study area and across lockdown periods. Principal component analysis showed that during the partial lockdown period, comparable sources were detected for the cellulose/low-density polyethylene (LDPE)/high-density polyethylene (HDPE), polychloroprene (PCP)/polyethylene terephthalate (PET)/polypropylene (PP)/polyacrylamide (PAA)/nylon, and polyethylene (PE)/polydimethylsiloxane (PDMS)/polyvinyl alcohol (PVA)/fiber groups of MPs, but various sources were discovered during the complete and without lockdown periods. The results further showed that all MP types would pose no non-carcinogenic or carcinogenic risks in dust from all land-use areas. However, the highest risks were obtained from inhaling dust. The study shows that human activities have a significant impact on the generation and distribution of MPs in the environment. The changes in MP type distribution during lockdown suggest that reducing human activities, such as traffic and industrial activity, can lead to a decrease in the quantity of MPs generated and released into the environment.
Silkworm Pupae Coupled with Glucose Control pH Mediates GABA Hyperproduction by Lactobacillus hilgardii
Authors: Gong Luchan , Li Tingting , Lv Shuyi , Zou Xiaozhou , Wang Jun , Wang Bowen
Published: July 2023

γ-Aminobutyric acid (GABA) is a ubiquitous nonprotein amino acid that has multiple physiological functions and has received significant attention in the pharmaceutical and food industries. Although there are many GABA-producing bacteria, the high cost of strain cultivation limits its food additive and pharmaceutical raw material application. In our study, Lactobacillus hilgardii GZ2, a novel GABA-producing strain, was investigated. We attempted to replace nitrogen sources with silkworm pupae, the waste resource of the silk reeling industry, in GYP complex medium. The GABA titer reached 33.2 g/L by using 10 g/L silkworm pupae meal instead of tryptone. Meanwhile, the pH of fermentation was automatically controlled by adjusting the addition of glucose and monosodium glutamate. Finally, the highest GABA yield and productivity were 229.3 g/L and 3.2 g/L/h in L. hilgardii when silkworm pupae meal was replaced with tryptone combined with glucose and monosodium glutamate feeding. By utilizing the waste resource to reduce the cost of the nitrogen source and automatically controlling the pH in L. hilgardii, a hyper titer and productivity of GABA was generated for applications in the food and pharmaceutical industries.
A Comprehensive Framework for Cyber Behavioral Analysis Based on a Systematic Review of Cyber Profiling Literature
Authors: Martineau Melissa , Spiridon Elena , Aiken Mary
Published: July 2023

Cybercrime presents a significant threat to global society. With the number of cybercrimes increasing year after year and the financial losses escalating, law enforcement must advance its capacity to identify cybercriminals, collect probative evidence, and bring cybercriminals before the courts. Arguably to date, the approach to combatting cybercrime has been technologically centric (e.g., anti-virus, anti-spyware). Cybercrimes, however, are the result of human activities based on human motives. It is, therefore, important that any comprehensive law enforcement strategy for combatting cybercrime includes a deeper understanding of the hackers that sit behind the keyboards. The purpose of this systematic review was to examine the state of the literature relating to the application of a human-centric investigative tool (i.e., profiling) to cybercrime by conducting a qualitative meta-synthesis. Adhering to the PRISMA 2020 guidelines, this systematic review focuses specifically on cybercrime where a computer is the target (e.g., hacking, DDoS, distribution of malware). Using a comprehensive search strategy, this review used the following search terms: “cybercrime”, “computer crime”, “internet crime”, “cybercriminal”, “hacker”, “black hat”, “profiling”, “criminal profiling”, “psychological profiling”, “offender profiling”, “criminal investigative analysis”, “behavioral profiling”, “behavioral analysis”, “personality profiling”, “investigative psychology”, and “behavioral evidence analysis” in all combinations to identify the relevant literature in the ACM Digital Library, EBSCOhost databases, IEEE Xplore, ProQuest, Scopus, PsychInfo, and Google Scholar. After applying the inclusion/exclusion criteria, a total of 72 articles were included in the review. This article utilizes a systematic review of the current literature on cyber profiling as a foundation for the development of a comprehensive framework for applying profiling techniques to cybercrime—described as cyber behavioral analysis (CBA). Despite decades of research, our understanding of cybercriminals remains limited. A lack of dedicated researchers, the paucity of research regarding human behavior mediated by technology, and limited access to datasets have hindered progress. The aim of this article was to advance the knowledge base in cyber behavioral sciences, and in doing so, inform future empirical research relating to the traits and characteristics of cybercriminals along with the application of profiling techniques and methodologies to cybercrime.
A Finite-Dimensional Control Scheme for Fractional-Order Systems under Denial-of-Service Attacks
Authors: Zou Ying , Li Xinyao , Deng Chao , Wu Xiaowen
Published: July 2023

In this article, the security control problem of discrete-time fractional-order networked systems under denial-of-service (DoS) attacks is considered. A practically applicable finite-dimensional control strategy will be developed for fractional-order systems that possess nonlocal characteristics. By employing the Lyapunov method, it is theoretically proved that under the proposed controller, the obtained closed-loop fractional system is globally input-to-state stable (ISS), even in the presence of DoS attacks. Finally, the effectiveness of the designed control method is demonstrated by the numerical example.
Integrated Genomic Selection for Accelerating Breeding Programs of Climate-Smart Cereals
Authors: Sinha Dwaipayan , Maurya Arun Kumar , Abdi Gholamreza , Majeed Muhammad , Agarwal Rachna , Mukherjee Rashmi , Ganguly Sharmistha , Aziz Robina , Bhatia Manika , Majgaonkar Aqsa , Seal Sanchita , Das Moumita , Banerjee Swastika , Chowdhury Shahana , Adeyemi Sherif Babatunde , Chen Jen-Tsung
Published: July 2023

Rapidly rising population and climate changes are two critical issues that require immediate action to achieve sustainable development goals. The rising population is posing increased demand for food, thereby pushing for an acceleration in agricultural production. Furthermore, increased anthropogenic activities have resulted in environmental pollution such as water pollution and soil degradation as well as alterations in the composition and concentration of environmental gases. These changes are affecting not only biodiversity loss but also affecting the physio-biochemical processes of crop plants, resulting in a stress-induced decline in crop yield. To overcome such problems and ensure the supply of food material, consistent efforts are being made to develop strategies and techniques to increase crop yield and to enhance tolerance toward climate-induced stress. Plant breeding evolved after domestication and initially remained dependent on phenotype-based selection for crop improvement. But it has grown through cytological and biochemical methods, and the newer contemporary methods are based on DNA-marker-based strategies that help in the selection of agronomically useful traits. These are now supported by high-end molecular biology tools like PCR, high-throughput genotyping and phenotyping, data from crop morpho-physiology, statistical tools, bioinformatics, and machine learning. After establishing its worth in animal breeding, genomic selection (GS), an improved variant of marker-assisted selection (MAS), has made its way into crop-breeding programs as a powerful selection tool. To develop novel breeding programs as well as innovative marker-based models for genetic evaluation, GS makes use of molecular genetic markers. GS can amend complex traits like yield as well as shorten the breeding period, making it advantageous over pedigree breeding and marker-assisted selection (MAS). It reduces the time and resources that are required for plant breeding while allowing for an increased genetic gain of complex attributes. It has been taken to new heights by integrating innovative and advanced technologies such as speed breeding, machine learning, and environmental/weather data to further harness the GS potential, an approach known as integrated genomic selection (IGS). This review highlights the IGS strategies, procedures, integrated approaches, and associated emerging issues, with a special emphasis on cereal crops. In this domain, efforts have been taken to highlight the potential of this cutting-edge innovation to develop climate-smart crops that can endure abiotic stresses with the motive of keeping production and quality at par with the global food demand.
Presence of Human DNA on Household Dogs and Its Bi-Directional Transfer
Authors: Monkman Heidi , Szkuta Bianca , van Oorschot Roland A. H.
Published: July 2023

Awareness of the factors surrounding the transfer of DNA from a person, item, or surface to another person, item, or surface is highly relevant during investigations of alleged criminal activity. Animals in domestic environments could be a victim, offender, or innocent party associated with a crime. There is, however, very limited knowledge of human DNA transfer, persistence, prevalence, and recovery (DNA TPPR) associated with domestic animals. This pilot study aimed to improve our understanding of DNA TPPR associated with domestic dogs by collecting and analysing samples from various external areas of dogs of various breeds, interactions with humans, and living arrangements, and conducting a series of tests to investigate the possibility of dogs being vectors for the indirect transfer of human DNA. Reference DNA profiles from the dog owners and others living in the same residence were acquired to assist interpretation of the findings. The findings show that human DNA is prevalent on dogs, and in the majority of samples, two-person mixtures are present. Dogs were also found to be vectors for the transfer of human DNA, with DNA transferred from the dog to a gloved hand during patting and a sheet while walking.
Tumor Necrosis Factor-α G-308A Polymorphism and Sporadic IgA Nephropathy: A Meta-Analysis Using a Genetic Model-Free Approach
Authors: Tziastoudi Maria , Chronopoulou Ioanna , Pissas Georgios , Cholevas Christos , Eleftheriadis Theodoros , Stefanidis Ioannis
Published: July 2023

Tumor necrosis factor-α (TNF-α) is a potent pro-inflammatory cytokine, involved in the pathogenesis and progression of immunoglobulin A nephropathy (IgAN). A bi-allelic polymorphism in the promoter region, at position -308 (G/A) of the TNF-α gene (rs1800629) is associated with an increased TNF-a production. However, several previous association studies of TNF-α G-308A polymorphism and IgAN rendered contradictory findings. The objective of the present study is to shed light on these inconclusive results and clarify the role of TNF-α and any possible contribution of this factor in the development and progression of sporadic IgAN. Therefore, a meta-analysis of all available genetic association studies relating the TNF-α G-308A polymorphism to the risk for development and/or progression of IgAN was conducted. Seven studies were included in the meta-analysis. Three of them included populations of European descent (Caucasians) and four involved Asians. The generalized odds ratio (ORG) was used to estimate the risk for the development and/or progression of the disease. Overall, the meta-analysis did not detect any significant association between the G-308A variant and both the risk of developing IgAN and the risk for progression of IgAN. In conclusion, these results suggest that TNF-α does not constitute a key component in the genetic architecture of sporadic IgAN. However, further evidence deciphering the influence of TNF-α on IgAN is still needed.
Integration of Phenotype Term Prioritization and Gene Expression Analysis Reveals a Novel Variant in the PERP Gene Associated with Autosomal Recessive Erythrokeratoderma
Authors: González-Quintana Adrián , Garrido-Moraga Rocío , Palencia-Pérez Sara I. , Hernández-Martín Ángela , Sánchez-Munárriz Jon , Lezana-Rosales José M. , Quesada-Espinosa Juan F. , Martín Miguel A. , Arteche-López Ana
Published: July 2023

Hereditary palmoplantar keratodermas (PPKs) are a clinically and genetically heterogeneous group of disorders characterized by excessive epidermal thickening of palms and soles. Several genes have been associated with PPK including PERP, a gene encoding a crucial component of desmosomes that has been associated with dominant and recessive keratoderma. We report a patient with recessive erythrokeratoderma (EK) in which whole exome sequencing (WES) prioritized by human phenotype ontology (HPO) terms revealed the presence of the novel variant c.153C > A in the N-terminal region the PERP gene. This variant is predicted to have a nonsense effect, p.(Cys51Ter), resulting in a premature stop codon. We demonstrated a marked reduction in gene expression in cultured skin fibroblasts obtained from the patient. Despite the PERP gene is expressed at low levels in fibroblasts, our finding supports a loss-of-function (LoF) mechanism for the identified variant, as previously suggested in recessive EK. Our study underscores the importance of integrating HPO analysis when using WES for molecular genetic diagnosis in a clinical setting, as it facilitates continuous updates regarding gene–clinical feature associations.
Comparison of Mitochondrial Genome Sequences between Two Palaemon Species of the Family Palaemonidae (Decapoda: Caridea): Gene Rearrangement and Phylogenetic Implications
Authors: Sun Yuman , Chen Jian , Ye Yingying , Xu Kaida , Li Jiji
Published: July 2023

To further understand the origin and evolution of Palaemonidae (Decapoda: Caridea), we determined the mitochondrial genome sequence of Palaemon macrodactylus and Palaemon tenuidactylus. The entire mitochondrial genome sequences of these two Palaemon species encompassed 37 typical genes, including 13 protein-coding genes (PCGs), 2 ribosomal RNA genes (rRNAs), and 22 transfer RNA genes (tRNAs), and a control region (CR). The lengths of their mitochondrial genomes were 15,744 bp (P. macrodactylus) and 15,735 bp (P. tenuidactylus), respectively. We analyzed their genomic features and structural functions. In comparison with the ancestral Decapoda, these two newly sequenced Palaemon species exhibited a translocation event, where the gene order was trnK-trnD instead of trnD-trnK. Based on phylogenetic analysis constructed from 13 PCGs, the 12 families from Caridea can be divided into four major clades. Furthermore, it was revealed that Alpheidae and Palaemonidae formed sister groups, supporting the monophyly of various families within Caridea. These findings highlight the significant gene rearrangements within Palaemonidae and provide valuable evidence for the phylogenetic relationships within Caridea.
Drosophila as Model System to Study Ras-Mediated Oncogenesis: The Case of the Tensin Family of Proteins
Authors: Martínez-Abarca Millán Ana , Soler Beatty Jennifer , Valencia Expósito Andrea , Martín-Bermudo María D.
Published: July 2023

Oncogenic mutations in the small GTPase Ras contribute to ~30% of human cancers. However, tissue growth induced by oncogenic Ras is restrained by the induction of cellular senescence, and additional mutations are required to induce tumor progression. Therefore, identifying cooperating cancer genes is of paramount importance. Recently, the tensin family of focal adhesion proteins, TNS1-4, have emerged as regulators of carcinogenesis, yet their role in cancer appears somewhat controversial. Around 90% of human cancers are of epithelial origin. We have used the Drosophila wing imaginal disc epithelium as a model system to gain insight into the roles of two orthologs of human TNS2 and 4, blistery (by) and PVRAP, in epithelial cancer progression. We have generated null mutations in PVRAP and found that, as is the case for by and mammalian tensins, PVRAP mutants are viable. We have also found that elimination of either PVRAP or by potentiates RasV12-mediated wing disc hyperplasia. Furthermore, our results have unraveled a mechanism by which tensins may limit Ras oncogenic capacity, the regulation of cell shape and growth. These results demonstrate that Drosophila tensins behave as suppressors of Ras-driven tissue hyperplasia, suggesting that the roles of tensins as modulators of cancer progression might be evolutionarily conserved.
Accuracy of Structure-from-Motion/Multiview Stereo Terrain Models: A Practical Assessment for Applications in Field Geology
Authors: Pavlis Terry L. , Serpa Laura F.
Published: July 2023

We assess the accuracy of Structure-from-Motion/Multiview stereo (SM) terrain models acquired ad hoc or without high-resolution ground control to analyze their usage as a base for inexpensive 3D bedrock geologic mapping. Our focus is on techniques that can be utilized in field projects without the use of heavy and/or expensive equipment or the placement of ground control in logistically challenging sites (e.g., steep cliff faces or remote settings). We use a Terrestrial Light Detection and Ranging (LiDAR) survey as a basis for the comparison of two types of SM models: (1) models developed from images acquired in a chartered airplane flight with ground control referenced by natural objects located on Google Earth scenes; and (2) drone flights with a georeference established solely from camera positions located by conventional, differentially corrected Global Navigation Satellite systems (GNSS). We find that all our SM models are indistinguishable in scale from the LiDAR reference model. The SM models do, however, show rigid body translations and rotations, with translations generally within the 1–5 m size of the natural objects used for ground control, the resolution of the GNSS receivers, or both. The rigid body rotations can be attributed to a poor imaging plan, which can be avoided with survey planning. Analyses of point densities in various models show a limitation of Terrestrial LiDAR point clouds as a mapping base due to the rapid falloff of resolution with distance. In contrast, SM models are characterized by relatively uniform point densities controlled by camera optics, the numbers of images, and the distance from the target. This uniform density is the product of the Multiview stereo step in SM processing that fills areas between key points and is important for bedrock geologic mapping because it affords direct interpretation on a point cloud at a relatively uniform scale throughout a model. Our results indicate that these simple methods allow SM model construction to be accurate to the range of conventional GNSS with resolutions to the submeter, even cm, scale depending on data acquisition parameters. Thus, SM models can, and should, serve as a base for high-resolution geologic mapping, particularly in a steep terrain where conventional techniques fail. Our SM models appear to provide accurate visualizations of geologic features over km scales that allow detailed geologic mapping in 3D with a relative accuracy to the decimeter or centimeter level and absolute positioning in the 2–5 m precision of GNSS; a geometric precision that will allow unprecedented new studies of any geologic system where geometry is the fundamental data.
¿Por qué los Hombres tienen diversas Maneras de Ojos? Curiosities about the Eyes in Juan de Jarava’s Problemas o Preguntas problemáticas (1544)
Authors: Gernert Folke
Published: July 2023

The so-called ‘problem books’ of the 15th and 16th centuries originate from the pseudo-Aristotelian Problemata, which were rediscovered around 1300. Their authors were often physicians who prepared medical information for a broad public and combined it with highly heterogeneous pools of knowledge. This article deals with different questions in regards to the eye and the sense of sight in Juan de Jarava’s Problemas o Preguntas Problemáticas, published in 1544. The physician, a man with Erasmist inclinations whose existence remains a mystery, divides his work into three parts, with each relating to love, natural phenomena, and wine. In all three parts, questions related to the eyes are raised. These issues are contextualized in the scholarly discourse of the time in order to determine to what extent Jarava is representative of knowledge about the eyes in the early modern period. The example of vision and the eyes can be used to show how early modern medical writers such as Juan de Jarava and Agustín de Ruescas tackled the complexity of the world in their problem books.
Load Testing of Cultural Heritage Structures and Sculptures: Unconventional Methods for Assessing Safety
Authors: Drdácký Miloš , Urushadze Shota
Published: July 2023

The paper presents the results of static and dynamic experimental tests conducted on historical heritage structures and sculptures. In recent years, there was an increasing need to address the behaviour of these types of structures due to several reasons. Diagnosing the actual condition of a historical structure involves not only identifying the cause of a detected defect, but also determining its impact and assessing whether the structure can continue to perform safely. This article utilises unconventional loading methods to generate measurable mechanical responses. In one case, a lifting procedure is employed to study strains in a composite structure, while in another example, the mass and movement of people are used as a form of loading. Proof load tests conducted on a monumental sculpture allowed for the determination of load distribution among its heterogeneous structural components, namely a bronze shell and an iron reinforcing frame. Furthermore, the static and dynamic loading of a ceiling supported by a masonry vault demonstrated its ability to withstand anticipated loads resulting from unconventional use as a temporary exhibition space.
Genome-Wide Identification and Expression Profiling of the NCED Gene Family in Cold Stress Response of Prunus mume Siebold & Zucc
Authors: Chen Ke , Li Xue , Guo Xiaoyu , Yang Lichen , Qiu Like , Liu Weichao , Wang Jia , Zheng Tangchun
Published: July 2023

The 9-cis-epoxy carotenoid dioxygenase (NCED) is an enzyme that is crucial in abscisic acid (ABA) biosynthesis, and its role is vital in plant development and abiotic stress. However, the function of the NCED family in Rosaceae plant species remains unclear. Through genome-wide screening, we identified 10, 10, 11, 12 and 13 NCED genes in Prunus mume, Prunus apricot, Prunus salicina, Prunus persica, and Rosa chinensis, respectively. Phylogenetic analysis showed that these NCED genes were divided into six groups. Gene structure analysis showed that the number and size of introns were relatively constant in each subfamily, while the motif composition differed significantly among them. Collinearity analysis revealed a high homology of NCEDs in the Prunus genus. Promoter cis-acting element analysis showed that eight PmNCEDs contained abscisic acid-responsive elements (ABRE). Furthermore, expression profile analysis based on qRT-PCR revealed that PmNCED3, PmNCED8 and PmNCED9 were up-regulated in response to low temperature stress, suggesting their significant role in the plant’s response to cold stress. These findings provide insights into the structure and evolution of PmNCEDs and lay the foundation for further studies regarding their function during cold stress.
Association of Emotional Self-Regulation with Psychological Distress and Positive Functioning Dimensions in Brazilian University Students during the COVID-19 Pandemic
Authors: Rech Maurício , Diaz Gabriela Bertoletti , Schaab Bruno Luis , Rech Carolina Garcia Soares Leães , Calvetti Prisla Ücker , Reppold Caroline Tozzi
Published: July 2023

Emotional self-regulation is a relevant factor for human development capable of minimizing emotional difficulties in the face of adverse events, as was particularly useful during the COVID-19 pandemic. The present study aimed to evaluate emotional self-regulation in Brazilian health science university students and its relationship with positive psychology constructs (subjective well-being, hope, optimism, spirituality, self-compassion, and self-efficacy) and psychological distress (depression, anxiety, and stress). This was a prospective, cross-sectional, observational, analytic study of 1062 Brazilian undergraduate students with data collected using self-administered online questionnaires. Students in the first years of their undergraduate degree programs had significantly higher dysregulation scores than those in the final years. Multiple linear regression yielded a model that explained 71.8% of the variation in emotion dysregulation. The correlations of emotion dysregulation were significant and strong, scoring negatively with self-compassion, optimism, and subjective well-being and positively with psychological distress.
Psychometric Properties of the Polish Version of the Sports Anxiety Scale-2 (SAS-2)
Authors: Rawat Kanupriya , Błachnio Aleksandra , Suppan Krzysztof
Published: July 2023

The main aim of the study was to assess the psychometric properties of the Polish version of the Sports Anxiety scale-2 (SAS-2). The study covered 396 athletes, ages ranging from 18 years to 35 years. The task and ego orientation in sport questionnaire (TEOSQ) and State and Trait Anxiety Inventory (STAI) were used for validation of the scale. Cronbach’s alpha for the somatic anxiety subscale was 0.88, for the worry subscale was 0.95, and for the concentration disruption was 0.86, respectively. The three-factor model and hierarchical model fits perfectly as CFI > 0.95, TLI > 0.95, and RMSEA < 0.08. Satisfactory results in measurement invariance show the use of the tool for any gender or athlete (high-performance, recreational) group. The internal consistency (α = 0.86–0.95) and the test–retest reliability (ICC = 0.87–0.90) were satisfactory. There was a statistically significant negative correlation between task orientation and total anxiety along with its three subscales, and a weak positive correlation between ego orientation and worry subscale. Meanwhile, a weak to moderate positive correlation was exhibited between total anxiety and its subscales with the STAI-T and STAI-S. Additionally, female, recreational, and female recreational athletes’ groups had weak negative associations between worry and concentration disruption trait anxiety and task orientation, and a weak positive association between somatic anxiety and ego orientation.