bluuebunny/crossref_metadata_2025 huggingface dataset:
Visualized Lead Selection for Arrhythmia Classification Based on a Lead Activation Heatmap Using Multi-Lead ECGs
Authors: Wang Heng , Shen Tengqun , Jiang Shoufen , Wang Jilin , Ma Yijun , Zhang Yatao
Published: June 2024

Visualizing the decision-making process is a key aspect of research regarding explainable arrhythmia recognition. This study proposed a visualized lead selection method to classify arrhythmia for multi-lead ECG signals. The proposed method has several advantages, as it uses a visualized approach to select effective leads, avoiding redundant leads and invalid information. It also captures the temporal dependencies of ECG signals and the complementary information between leads. The method deployed a lead activation heatmap (LA heatmap) based on a lead-wise network to select the proper 5 leads from 12-lead ECG heartbeats extracted from the public 2018 Chinese Physiological Signal Challenge database (CPSC 2018 DB), which were then fed into a ResBiTime network combining bidirectional long short-term memory (Bi-LSTM) networks and residual connections for a classification task of nine heartbeat categories (i.e., N, AF, I-AVB, RBBB, PAC, PVC, STD, LBBB, and STE). The results indicate an average precision of 93.25%, an average recall of 93.03%, an average F1-score of 0.9313, and that the proposed method can effectively extract additional information from ECG heartbeat data.
The Landscape of Pediatric High-Grade Gliomas: The Virtues and Pitfalls of Pre-Clinical Models
Authors: Furst Liam M. , Roussel Enola M. , Leung Ryan F. , George Ankita M. , Best Sarah A. , Whittle James R. , Firestein Ron , Faux Maree C. , Eisenstat David D.
Published: June 2024

Pediatric high-grade gliomas (pHGG) are malignant and usually fatal central nervous system (CNS) WHO Grade 4 tumors. The majority of pHGG consist of diffuse midline gliomas (DMG), H3.3 or H3.1 K27 altered, or diffuse hemispheric gliomas (DHG) (H3.3 G34-mutant). Due to diffuse tumor infiltration of eloquent brain areas, especially for DMG, surgery has often been limited and chemotherapy has not been effective, leaving fractionated radiation to the involved field as the current standard of care. pHGG has only been classified as molecularly distinct from adult HGG since 2012 through Next-Generation sequencing approaches, which have shown pHGG to be epigenetically regulated and specific tumor sub-types to be representative of dysregulated differentiating cells. To translate discovery research into novel therapies, improved pre-clinical models that more adequately represent the tumor biology of pHGG are required. This review will summarize the molecular characteristics of different pHGG sub-types, with a specific focus on histone K27M mutations and the dysregulated gene expression profiles arising from these mutations. Current and emerging pre-clinical models for pHGG will be discussed, including commonly used patient-derived cell lines and in vivo modeling techniques, encompassing patient-derived xenograft murine models and genetically engineered mouse models (GEMMs). Lastly, emerging techniques to model CNS tumors within a human brain environment using brain organoids through co-culture will be explored. As models that more reliably represent pHGG continue to be developed, targetable biological and genetic vulnerabilities in the disease will be more rapidly identified, leading to better treatments and improved clinical outcomes.
Unveiling the Druggable Landscape of Bacterial Peptidyl tRNA Hydrolase: Insights into Structure, Function, and Therapeutic Potential
Authors: Mundra Surbhi , Kabra Ashish
Published: June 2024

Bacterial peptidyl tRNA hydrolase (Pth) or Pth1 emerges as a pivotal enzyme involved in the maintenance of cellular homeostasis by catalyzing the release of peptidyl moieties from peptidyl-tRNA molecules and the maintenance of a free pool of specific tRNAs. This enzyme is vital for bacterial cells and an emerging drug target for various bacterial infections. Understanding the enzymatic mechanisms and structural intricacies of bacterial Pth is pivotal in designing novel therapeutics to combat antibiotic resistance. This review provides a comprehensive analysis of the multifaceted roles of Pth in bacterial physiology, shedding light on its significance as a potential drug target. This article delves into the diverse functions of Pth, encompassing its involvement in ribosome rescue, the maintenance of a free tRNA pool in bacterial systems, the regulation of translation fidelity, and stress response pathways within bacterial systems. Moreover, it also explores the druggability of bacterial Pth, emphasizing its promise as a target for antibacterial agents and highlighting the challenges associated with developing specific inhibitors against this enzyme. Structural elucidation represents a cornerstone in unraveling the catalytic mechanisms and substrate recognition of Pth. This review encapsulates the current structural insights of Pth garnered through various biophysical techniques, such as X-ray crystallography and NMR spectroscopy, providing a detailed understanding of the enzyme’s architecture and conformational dynamics. Additionally, biophysical aspects, including its interaction with ligands, inhibitors, and substrates, are discussed, elucidating the molecular basis of bacterial Pth’s function and its potential use in drug design strategies. Through this review article, we aim to put together all the available information on bacterial Pth and emphasize its potential in advancing innovative therapeutic interventions and combating bacterial infections.
Molecular Genetics of Acquired Temporal Lobe Epilepsy
Authors: Neumann Anne-Marie , Britsch Stefan
Published: June 2024

An epilepsy diagnosis reduces a patient’s quality of life tremendously, and it is a fate shared by over 50 million people worldwide. Temporal lobe epilepsy (TLE) is largely considered a nongenetic or acquired form of epilepsy that develops in consequence of neuronal trauma by injury, malformations, inflammation, or a prolonged (febrile) seizure. Although extensive research has been conducted to understand the process of epileptogenesis, a therapeutic approach to stop its manifestation or to reliably cure the disease has yet to be developed. In this review, we briefly summarize the current literature predominately based on data from excitotoxic rodent models on the cellular events proposed to drive epileptogenesis and thoroughly discuss the major molecular pathways involved, with a focus on neurogenesis-related processes and transcription factors. Furthermore, recent investigations emphasized the role of the genetic background for the acquisition of epilepsy, including variants of neurodevelopmental genes. Mutations in associated transcription factors may have the potential to innately increase the vulnerability of the hippocampus to develop epilepsy following an injury—an emerging perspective on the epileptogenic process in acquired forms of epilepsy.
Rats Lacking the Dopamine Transporter Display Inflexibility in Innate and Learned Behavior
Authors: Belskaya Anastasia , Kurzina Natalia , Savchenko Artem , Sukhanov Ilya , Gromova Arina , Gainetdinov Raul R. , Volnova Anna
Published: June 2024

Playing a key role in the organization of striatal motor output, the dopamine (DA)-ergic system regulates both innate and complex learned behaviors. Growing evidence clearly indicates the involvement of the DA-ergic system in different forms of repetitive (perseverative) behavior. Some of these behaviors accompany such disorders as obsessive–compulsive disorder (OCD), Tourette’s syndrome, schizophrenia, and addiction. In this study, we have traced how the inflexibility of repetitive reactions in the recently developed animal model of hyper-DA-ergia, dopamine transporter knockout rats (DAT-KO rats), affects the realization of innate behavior (grooming) and the learning of spatial (learning and reversal learning in T-maze) and non-spatial (extinction of operant reaction) tasks. We found that the microstructure of grooming in DAT-KO rats significantly differed in comparison to control rats. DAT-KO rats more often demonstrated a fixed syntactic chain, making fewer errors and very rarely missing the chain steps in comparison to control rats. DAT-KO rats’ behavior during inter-grooming intervals was completely different to the control animals. During learning and reversal learning in the T-maze, DAT-KO rats displayed pronounced patterns of hyperactivity and perseverative (stereotypical) activity, which led to worse learning and a worse performance of the task. Most of the DAT-KO rats could not properly learn the behavioral task in question. During re-learning, DAT-KO rats demonstrated rigid perseverative activity even in the absence of any reinforcement. In operant tasks, the mutant rats demonstrated poor extinction of operant lever pressing: they continued to perform lever presses despite no there being reinforcement. Our results suggest that abnormally elevated DA levels may be responsible for behavioral rigidity. It is conceivable that this phenomenon in DAT-KO rats reflects some of the behavioral traits observed in clinical conditions associated with endogenous or exogenous hyper-DA-ergia, such as schizophrenia, substance abuse, OCD, patients with Parkinson disease treated with DA mimetics, etc. Thus, DAT-KO rats may be a valuable behavioral model in the search for new pharmacological approaches to treat such illnesses.
Growth and Performance: Business Model Innovation in Family Firms
Authors: Meroño-Cerdan Angel-Luis , Molina-Castillo Francisco-Jose , Lopez-Nicolas Carolina , Ruiz-Nicolas Jesus
Published: June 2024

A business model, defined as the underlying logic of a company, is not permanent over time. Instead, companies need to introduce innovations in the business model to be competitive in the market. This is even more critical for family firms which are continuously looking for a way to obtain sustainable growth, together with satisfactory performance. The objective of this research is to analyze the impact that business model innovation activities have in the short/long-term growth and performance of family firms. This study was obtained from panel data made up of 112 valid responses from family firms involved in business model innovation. A composite model approach has been used for data analysis. The significant components of BMI that lead to greater growth and performance are identified, the distinction between long-term and short-term effects of BMI on those outcomes is made, and BMI is proven as an authoritative source of competitive advantage and growth in family firms. Those aspects are valuable insights for researchers and managers with regards to which innovation propositions help sustain growth and performance over time.
Lethal Complications and Complex Genotypes in Shwachman Diamond Syndrome: Report of a Family with Recurrent Neonatal Deaths and a Case-Based Brief Review of the Literature
Authors: Veltra Danai , Marinakis Nikolaos M. , Kotsios Ioannis , Delaporta Polyxeni , Kekou Kyriaki , Kosma Konstantina , Traeger-Synodinos Joanne , Sofocleous Christalena
Published: June 2024

Shwachman Diamond Syndrome (SDS) is a multi-system disease characterized by exocrine pancreatic insufficiency with malabsorption, infantile neutropenia and aplastic anemia. Life-threatening complications include progression to acute myeloid leukemia (AML) or myelodysplastic syndrome (MDS), critical deep-tissue infections and asphyxiating thoracic dystrophy. In most patients, SDS results from biallelic pathogenic variants in the SBDS gene, different combinations of which contribute to heterogenous clinical presentations. Null variants are not well tolerated, supporting the theory that the loss of SBDS expression is likely lethal in both mice and humans. A novel complex genotype (SBDS:c.[242C>G;258+2T>C];[460-1G>A]/WFS1:c.[2327A>T];[1371G>T]) was detected in a family with recurrent neonatal deaths. A female neonate died three hours after birth with hemolytic anemia, and a male neonate with severe anemia, thrombocytopenia and neutropenia succumbed on day 40 after Staphylococcus epidermidis infection. A subsequent review of the literature focused on fatal complications, complex SBDS genotypes and/or unusual clinical presentations and disclosed rare cases, of which some had unexpected combinations of genetic and clinical findings. The impact of pathogenic variants and associated phenotypes is discussed in the context of data sharing towards expanding scientific expert networks, consolidating knowledge and advancing an understanding of novel underlying genotypes and complex phenotypes, facilitating informed clinical decisions and disease management.
Interventions through Art Therapy and Music Therapy in Autism Spectrum Disorder, ADHD, Language Disorders, and Learning Disabilities in Pediatric-Aged Children: A Systematic Review
Authors: Martínez-Vérez Victoria , Gil-Ruíz Paula , Domínguez-Lloria Sara
Published: June 2024

Traditional pharmacological treatments, although effective, often carry potential side effects, which positions art therapy and music therapy as promising non-pharmacological alternatives to alleviate symptoms and improve social, cognitive, and emotional skills without the associated risks. Through a review in the SCOPUS and WOS databases following the PRISMA protocol, a total of 80 articles were analyzed through a series of determined categories and subcategories of analysis. The aim of this study is to evaluate and synthesize the existing evidence on the efficacy and applicability of art therapy and music therapy in the treatment of children with autism spectrum disorder (ASD), hyperactivity disorder (HSDD), developmental language disorders, and language learning difficulties, identifying best practices and key areas for future research. Among the main findings is that art therapy and music therapy have a significant impact on symptomatology, behavior, and communication as well as social, cognitive, and emotional skills in the pediatric populations studied. These therapies are highly valued by the participants with a large majority recognizing their adaptability to different educational and clinical contexts. It is concluded that these therapies have a high potential as viable alternatives or complements to traditional pharmacological treatments, justifying their application and further study in broader therapeutic contexts.
NMR Studies of the Interactions between Sialyllactoses and the Polysialytransferase Domain for Polysialylation Inhibition
Authors: Lu Bo , Liao Si-Ming , Liang Shi-Jie , Li Jian-Xiu , Liu Xue-Hui , Huang Ri-Bo , Zhou Guo-Ping
Published: June 2024

It is known that sialyllactose (SL) in mammalians is a major source of sialic acid (Sia), which can further form cytidine monophosphate sialic acid (CMP-Sia), and the final product is polysialic acid (polySia) using polysialyltransferases (polySTs) on the neural cell adhesion molecule (NCAM). This process is called NCAM polysialylation. The overexpression of polysialylation is strongly related to cancer cell migration, invasion, and metastasis. In order to inhibit the overexpression of polysialylation, in this study, SL was selected as an inhibitor to test whether polysialylation could be inhibited. Our results suggest that the interactions between the polysialyltransferase domain (PSTD) in polyST and CMP-Siaand the PSTD and polySia could be inhibited when the 3′-sialyllactose (3′-SL) or 6′-sialyllactose (6′-SL) concentration is about 0.5 mM or 6′-SL and 3 mM, respectively. The results also show that SLs (particularly for 3′-SL) are the ideal inhibitors compared with another two inhibitors, low-molecular-weight heparin (LMWH) and cytidine monophosphate (CMP), because 3’-SL can not only be used to inhibit NCAM polysialylation, but is also one of the best supplements for infant formula and the gut health system.
Unlocking Blockchain UTXO Transactional Patterns and Their Effect on Storage and Throughput Trade-Offs
Authors: Melo David , Pomares-Hernández Saúl Eduardo , Rodríguez-Henríquez Lil María Xibai , Pérez-Sansalvador Julio César
Published: June 2024

Blockchain technology ensures record-keeping by redundantly storing and verifying transactions on a distributed network of nodes. Permissionless blockchains have pushed the development of decentralized applications (DApps) characterized by distributed business logic, resilience to centralized failures, and data immutability. However, storage scalability without sacrificing throughput is one of the remaining open challenges in permissionless blockchains. Enhancing throughput often compromises storage, as seen in projects such as Elastico, OmniLedger, and RapidChain. On the other hand, solutions seeking to save storage, such as CUB, Jidar, SASLedger, and SE-Chain, reduce the transactional throughput. To our knowledge, no analysis has been performed that relates storage growth to transactional throughput. In this article, we delve into the execution of the Bitcoin and Ethereum transactional models, unlocking patterns that represent any transaction on the blockchain. We reveal the trade-off between transactional throughput and storage. To achieve this, we introduce the spent-by relation, a new abstraction of the UTXO model that utilizes a directed acyclic graph (DAG) to reveal the patterns and allows for a graph with granular information. We then analyze the transactional patterns to identify the most storage-intensive ones and those that offer greater flexibility in the throughput/storage trade-off. Finally, we present an analytical study showing that the UTXO model is more storage-intensive than the account model but scales better in transactional throughput.
A Data-Driven Motor Optimization Method Based on Support Vector Regression—Multi-Objective, Multivariate, and with a Limited Sample Size
Authors: Li Guanghao , Li Ruicheng , Hou Haobo , Zhang Guoyi , Li Zhiyong
Published: June 2024

The increasing demand for sustainable development and energy efficiency underscores the importance of optimizing motors in driving the upgrade of energy structures. This paper studies a data-driven approach for the multi-objective optimization of motors designed for scenarios involving multiple variables, objectives, and limited sample sizes and validates its efficacy. Initially, sensitivity analysis is employed to identify potentially influential variables, thus selecting key design parameters. Subsequently, Latin hypercube sampling (LHS) is utilized to select experimental points, ensuring the coverage of the modeled test points across the experimental space to enhance fitting accuracy. Finally, the support vector regression (SVR) algorithm is employed to fit the objective function, in conjunction with multi-objective particle swarm optimization (MOPSO) for solution derivation. The presented method is used to optimize the efficiency, average output torque, and induced electromotive force harmonic distortion rate of a permanent magnet synchronous motor (PMSM). The results show an improvement of approximately 6.80% in average output torque and a significant decrease of about 59.5% in the induced electromotive force harmonic distortion rate, with minimal impact on efficiency. This study offers a pathway for enhancing motor performance, holding practical significance.
Flying Base Station Channel Capacity Limits: Dependent on Stationary Base Station and Independent of Positioning
Authors: Chang Sang-Yoon , Park Kyungmin , Kim Jonghyun , Kim Jinoh
Published: June 2024

Flying base stations, also known as aerial base stations, provide wireless connectivity to the user and utilize their aerial mobility to improve communication performance. Flying base stations depend on traditional stationary terrestrial base stations for connectivity, as stationary base stations act as the gateway to the backhaul/cloud via a wired connection. We introduce the flying base station channel capacity to build on the Shannon channel capacity, which quantifies the upper-bound limit of the rate at which information can be reliably transmitted using the communication channel regardless of the modulation and coding techniques used. The flying base station’s channel capacity assumes aerial mobility and ideal positioning for maximum channel capacity. Therefore, the channel capacity limit holds for any digital and signal processing technique used and for any location or positioning of the flying base station. Because of its inherent reliance on the stationary terrestrial base station, the flying base station channel capacity depends on the stationary base station’s parameters, such as its location and SNR performance to the user, in contrast to previous research, which focused on the link between the user and the flying base station without the stationary base station. For example, the beneficial region (where there is a positive flying base station capacity gain) depends on the stationary base station’s power and channel SNR in addition to the flying base station’s own transmission power and whether it has full duplex vs. half-duplex capability. We jointly study the mobility and the wireless communications of the flying base station to analyze its position, channel capacity, and beneficialness over the stationary terrestrial base station (capacity gain). As communication protocols and implementations for flying base stations undergo development for next-generation wireless networking, we focus on information-theoretical analyses and channel capacity to inform future research and development in flying base station networking.
Analysis of DC-Link Low-Frequency Current Harmonics in Multi-Source Multi-Three-Phase Electric Drives
Authors: Lai Yiyu , Cizeron Antoine , Voldoire Adrien , Ojeda Javier , Béthoux Olivier
Published: June 2024

In a multi-source permanent magnet synchronous motor (PMSM) drive, three distinct winding structures can be implemented: multi-sector, multi-three-phase, and highly coupled. However, due to variations in the magnetic coupling between windings, their low-frequency DC-link current ripple components differ. This paper presents a method to identify the phenomena associated with each low-frequency harmonic content. Three analytical models are developed for the DC current ripple induced by unbalanced winding, counter-electromotive force (back-EMF) harmonics and aliasing effects, respectively, with the results validated through simulations. Experimental validation is conducted for highly coupled winding drives, demonstrating agreement with the analytical models and simulations. The maximum DC current ripple ratio found in the analytical model, the simulation and the experiments is less than 15%, which is deemed acceptable for motor drive applications.
Zynerator: Bridging Model-Driven Architecture and Microservices for Enhanced Software Development
Authors: Zouani Younes , Lachgar Mohamed
Published: June 2024

Model-driven architecture (MDA) has demonstrated significant potential in automating code generation processes, yet its application often falls short in addressing the complexities of modern architectural styles, notably microservices. Microservice architecture, characterized by its decomposition of applications into small, independently deployable services, presents unique challenges and opportunities that traditional MDA approaches struggle to accommodate. In this paper, Zynerator, a novel framework that bridges the gap between model-driven architecture and microservice development, is presented. By integrating semantic decorators into the PIM, Zynerator empowers end-users to express intricate functional and non-functional requirements, laying the foundation for the generation of contextually appropriate code. Moreover, Zynerator goes beyond traditional MDA capabilities by offering a solution for microservice architecture integration, enabling the generation of service gateways, service discovery mechanisms, and other essential components inherent to microservice ecosystems. This integration not only streamlines the development process but also ensures the scalability, resilience, and maintainability of microservice-based applications. Through Zynerator, a flexible and comprehensive solution is presented that leverages the strengths of model-driven architecture (MDA), while addressing the evolving needs of modern software architecture, particularly in the realm of microservice development. Empirical results showed that Zynerator enhances code generation alignment to functional requirements by 55%, reduces microservice adoption in terms of communication and deployment times by 30%, and increases system scalability by supporting up to 10,000 concurrent users, without performance degradation.
Applying “Two Heads Are Better Than One” Human Intelligence to Develop Self-Adaptive Algorithms for Ridesharing Recommendation Systems
Authors: Hsieh Fu-Shiung
Published: June 2024

Human beings have created numerous laws, sayings and proverbs that still influence behaviors and decision-making processes of people. Some of the laws, sayings or proverbs are used by people to understand the phenomena that may take place in daily life. For example, Murphy’s law states that “Anything that can go wrong will go wrong.” Murphy’s law is helpful for project planning with analysis and the consideration of risk. Similar to Murphy’s law, the old saying “Two heads are better than one” also influences the determination of the ways for people to get jobs done effectively. Although the old saying “Two heads are better than one” has been extensively discussed in different contexts, there is a lack of studies about whether this saying is valid and can be applied in evolutionary computation. Evolutionary computation is an important optimization approach in artificial intelligence. In this paper, we attempt to study the validity of this saying in the context of evolutionary computation approach to the decision making of ridesharing systems with trust constraints. We study the validity of the saying “Two heads are better than one” by developing a series of self-adaptive evolutionary algorithms for solving the optimization problem of ridesharing systems with trust constraints based on the saying, conducting several series of experiments and comparing the effectiveness of these self-adaptive evolutionary algorithms. The new finding is that the old saying “Two heads are better than one” is valid in most cases and hence can be applied to facilitate the development of effective self-adaptive evolutionary algorithms. Our new finding paves the way for developing a better evolutionary computation approach for ridesharing recommendation systems based on sayings created by human beings or human intelligence.
Wearable Loops for Dynamic Monitoring of Joint Flexion: A Machine Learning Approach
Authors: Saltzman Henry , Rajaram Rahul , Zhang Yingzhe , Islam Md Asiful , Kiourti Asimina
Published: June 2024

We present a machine learning driven system to monitor joint flexion angles during dynamic motion, using a wearable loop-based sensor. Our approach uses wearable loops to collect transmission coefficient data and an Artificial Neural Network (ANN) with fine-tuned parameters to increase accuracy of the measured angles. We train and validate the ANN for sagittal plane flexion of a leg phantom emulating slow motion, walking, brisk walking, and jogging. We fabricate the loops on conductive threads and evaluate the effect of fabric drift via measurements in the absence and presence of fabric. In the absence of fabric, our model produced a root mean square error (RMSE) of 5.90°, 6.11°, 5.90°, and 5.44° during slow motion, walking, brisk walking, and jogging. The presence of fabric degraded the RMSE to 8.97°, 7.21°, 9.41°, and 7.79°, respectively. Without the proposed ANN method, errors exceeded 35.07° for all scenarios. Proof-of-concept results on three human subjects further validate this performance. Our approach empowers feasibility of wearable loop sensors for motion capture in dynamic, real-world environments. Increasing speed of motion and the presence of fabric degrade sensor performance due to added noise. Nevertheless, the proposed framework is generalizable and can be expanded upon in the future to improve upon the reported angular resolution.
Detecting Logos for Indoor Environmental Perception Using Unsupervised and Few-Shot Learning
Authors: Yin Changjiang , Ye Qin , Zhang Shaoming , Yang Zexin
Published: June 2024

Indoor scenes are crucial components of urban spaces, with logos serving as vital information within these environments. The accurate perception of logos is essential for effectively operating mobile robots in indoor environments, which significantly contributes to many upper-level applications. With the rapid development of neural networks, numerous deep-learning-based object-detection methods have been applied to logo detection. However, most of these methods depend on large labeled datasets. Given the fast-changing nature of logos in indoor scenes, achieving reliable detection performance with either the existing large labeled datasets or a limited number of labeled logos remains challenging. In this article, we propose a method named MobileNetV2-YOLOv4-UP, which integrates unsupervised learning with few-shot learning for logo detection. We develop an autoencoder to obtain latent feature representations of logos by pre-training on a public unlabeled logo dataset. Subsequently, we construct a lightweight logo-detection network and embed the encoder weights as prior information. Training is performed on a small dataset of labeled indoor-scene logos to update the weights of the logo-detection network. Experimental results on the public logo625 dataset and our self-collected LOGO2000 dataset demonstrate that our method outperforms classic object-detection methods, achieving a mean average detection precision of 83.8%. Notably, our unsupervised pre-training strategy (UP) has proven effective, delivering a 15.4% improvement.
Continuous Recording of Resonator Characteristics Using Single-Sideband Modulation
Authors: Lippmann Martin , Hitzemann Moritz , Hermeling Leonardo , Dehning Kirsten J. , Winkelholz Jonas , Wantosch Rene , Zimmermann Stefan
Published: June 2024

Electrical resonators are usually characterized by their resonance frequency, attenuation and quality factor. External quantities can affect these parameters, resulting in a characteristic change in the resonator, which can be used as a sensor effect. This work presents a new concept and electronic device for the continuous recording of resonator characteristics using single-sideband modulation. A test signal consisting of a center frequency and two sidebands is generated and the center frequency is set close to the resonator’s resonance frequency while the two sidebands are adjusted symmetrically around the center frequency. By exiting the resonator with the test signal and demodulating the resulting output into individual frequency components, a continuous measurement of the attenuation is possible. The center frequency is adjusted so that both sidebands have equal attenuation, resulting in a center frequency that corresponds to the resonance frequency of the resonator. If the resonator does not show a symmetrical frequency response, the sideband attenuation ratio can be adjusted accordingly. Continuous recording of the resonator characteristics at a sampling rate of 100 Sps was verified using a digitally tunable RLC series resonator with resonance frequencies between 250 MHz and 450 MHz, resulting in a maximum error below 1.5%.
Study of Performance Changes in Centrifugal Compressors Working in Different Refrigerants
Authors: Wang Yintao , Yan Jin
Published: June 2024

Centrifugal compressors are commonly used in heating, ventilation, and air conditioning (HVAC) systems. The current generation of refrigerants in HVAC systems have very low ozone depletion potential, but most of them are still considered as containing high global warming potential (GWP) chemicals. Facing the regulatory pressure to eliminate the high-level GWP refrigerants, some of the existing HVAC systems will need to switch to low-GWP refrigerants. In this paper, we studied the performance changes in a refrigerant centrifugal compressor when switching from R134a to R1234ze(E) and R1234yf through a method that combined numerical simulation and an 1D meanline code. By combining these two methods, a reliable compressor performance change prediction was generated using limited results from the computational fluid dynamics (CFD) simulations. The results show that the property differences in the working fluid can significantly change the refrigerant compressor performance, including the compressor efficiency, pressure ratio, power consumption, working range and cooling capacity.
What Occurs within the Mangrove Ecosystems of the Douala Region in Cameroon? Exploring the Challenging Governance of Readily Available Woody Resources in the Wouri Estuary
Authors: Bissonnette Jean-François , Dossa Kossivi Fabrice , Nsangou Celestin Arnaud , Satchie Yangue Abidah , Moussa Haman , Miassi Yann Emmanuel , Gravel Nathalie , Marie Guillaume , Onguene Raphaël
Published: June 2024

Mangrove ecosystems provide key ecosystem services in coastal areas. This study describes the riparian mangrove of the Wouri estuary, in the Douala region (Cameroon), emphasizing the changes in this ecosystem over the past decade and its current state. It highlights the different groups of actors who participate in the management and regulation of the resource. Finally, an analysis of the governance of the mangrove wood resource based on the theory of common goods by Elinor Ostrom (1990) is proposed by examining the results obtained from the previous points. The scientific interest lies in contributing to a better understanding of the socio-ecological changes in the mangrove in the context of increasing anthropogenic pressures, highlighting the governance challenges and conservation opportunities in a strategic region of Central Africa. This research reveals complex processes that characterize mangrove ecosystems on the Manoka and Cap Cameroon Islands. The lack of urbanization regulations, continued infrastructure growth, repeated flooding, and coastal erosion all have a negative impact on natural landscapes and forests. The use of wood for smoking and fishing, as well as coastal pollution resulting from deficient garbage management, also have a considerable influence. Strategic interventions are needed to ensure sustainable ecosystem management. Recommendations include the application of rules to prevent forest overexploitation.
Effect of Different Yeasts on the Higher Alcohol Content of Mulberry Wine
Authors: Lian Weijia , Lei Jing , Han Chen , Wu Jiuyun , Liu Zhigang , Liu Wei , Jiapaer Ayijiamali , Su Hanming , Xu Yanjun , Chen Ya , Liu Fengjuan
Published: June 2024

Healthy, nutritious, and delicious mulberry wine is loved by everyone, but there is no specific yeast for mulberry wine. To screen for yeasts with low-yield higher alcohols for the fermentation of mulberry wine, we tested five commonly used commercial yeasts available on the market to ferment mulberry wine. All five yeasts were able to meet the requirements in terms of yeast fermentation capacity, speed, and physical and chemical markers of mulberry wine. The national standards were met by the fermentation requirements and the fermented mulberry wine. We identified yeast DV10 as a yeast with low-yield higher alcohols suitable for mulberry wine fermentation. The total higher alcohol content in fermented mulberry wine was 298 mg/L, which was 41.9% lower than that of fermented mulberry wine with yeast EC118. The contents of 17 free amino acids and five sugars in mulberry juice and five yeast-fermented mulberry wines were tested. The results showed that the higher the amino acid and sugar content in yeast-fermented mulberry wine, the higher the content of higher alcohols produced by fermentation. A correlation analysis performed on each higher alcohol produced when yeast DV10 fermented the mulberry wine indicated decreased sugar and related amino acids. The findings demonstrated a substantial negative correlation among the levels of increased alcohol, decreased sugar, and matching amino acid content. Considering the correlation values among increased alcohol, decreased sugar, and related amino acids, the very slight difference suggests that both sugar anabolism and amino acid catabolism pathways have an equivalent impact on the synthesis of higher alcohols during the fermentation of mulberry wine. These results provide a theoretical basis for reducing the content of higher alcohols in mulberry wines, given the history and foundation for producing mulberry wine.
Integrating Image Analysis and Machine Learning for Moisture Prediction and Appearance Quality Evaluation: A Case Study of Kiwifruit Drying Pretreatment
Authors: Yu Shuai , Zheng Haoran , Wilson David I. , Yu Wei , Young Brent R.
Published: June 2024

The appearance of dried fruit clearly influences the consumer’s perception of the quality of the product but is a subtle and nuanced characteristic that is difficult to quantitatively measure, especially online. This paper describes a method that combines several simple strategies to assess a suitable surrogate for the elusive quality using imaging, combined with multivariate statistics and machine learning. With such a convenient tool, this study also shows how one can vary the pretreatments and drying conditions to optimize the resultant product quality. Specifically, an image batch processing method was developed to extract color (hue, saturation, and value) and morphological (area, perimeter, and compactness) features. The accuracy of this method was verified using data from a case study experiment on the pretreatment of hot-air-dried kiwifruit slices. Based on the extracted image features, partial least squares and random forest models were developed to satisfactorily predict the moisture ratio (MR) during drying process. The MR of kiwifruit slices during drying could be accurately predicted from changes in appearance without using any weighing device. This study also explored determining the optimal drying strategy based on appearance quality using principal component analysis. Optimal drying was achieved at 60 °C with 4 mm thick slices under ultrasonic pretreatment. For the 70 °C, 6 mm sample groups, citric acid showed decent performance.
Unraveling the In Vitro Anti-Advanced Glycation End-Product (Anti-AGE) Potential of Fermented Red Cabbage and Beetroot: Insights into Composition and Activities
Authors: Starowicz Małgorzata , Płatosz Natalia , Bączek Natalia , Szawara-Nowak Dorota , Šimková Kristýna , Wiczkowski Wiesław
Published: June 2024

This study verified the in vitro activity of red cabbage and beetroot against the formation of advanced glycation end-products (AGEs) and their relationship with the biomolecules’ content. Fermentation of cabbage increased the total phenolic (~10%) and flavonoid contents (~14%), whereas decreased total phenolics/flavonoids in beetroot. Fermented cabbage exhibited higher ability against AGEs, i.e., 17% in the bovine serum albumin–methylglyoxal (BSA-MGO) model and 25% in the BSA–glucose model, while beetroot exhibited 23% and 18%, respectively. The major compounds of cabbage products were cyanidin 3-(sinapoyl)(sinapoyl)-diglucoside-5-glucoside, sinapic acid, and epicatechin. Syringic acid and epicatechin were predominantly present in fermented beetroot. 2,17-bidecarboxy- and 2,15,17-tridecarboxy-betanin were the major betalains. Fermented vegetables can be effective inhibitors of the AGE formation/accumulation and could be recommended in the prevention of diet-related diseases.
Antioxidant Activity of Aqueous Extracts Obtained from By-Products of Grape, Olive, Tomato, Lemon, Red Pepper and Pomegranate
Authors: Timón María Luisa , Andrés Ana Isabel , Petrón María Jesús
Published: June 2024

The aim of this work was to study the antioxidant potential of aqueous extracts obtained from different by-products. The effectiveness of these extracts was compared with that of rosemary extract. Total phenol carotenoid and vitamin C contents, as well as in vitro antioxidant activity, were assessed. Phenol content was positively correlated with in vitro antioxidant activity in extracts, while carotenoids showed a less clear relationship. Vitamin C was associated with antioxidant activity in lemon and pepper pomace extracts. Extracts from olive, grape, and lemon by-products displayed the highest antioxidant activity (radical scavenging activity), this being similar to the activity of rosemary extracts. Moreover, the phenolic profile of the extracts was analyzed, revealing diverse phenolic compounds. Rosemary extracts contained the highest variety and quantity of phenolic compounds, while olive pomace extracts were rich in hydroxytyrosol and 4-hydroxybenzoic acid. Lemon and pepper extracts contained high amounts of tyrosol, and tomato extracts had abundant epicatechin. The PCA analysis distinguished extracts based on in vitro antioxidant activity, phenol, carotenoid, and vitamin C content, along with their phenolic compound profiles. This study emphasizes the capacity of aqueous extract by-products as valuable sources of antioxidants and highlights the importance of understanding their bioactive components.
Planetary Nebula Morphologies Indicate a Jet-Driven Explosion of SN 1987A and Other Core-Collapse Supernovae
Authors: Soker Noam
Published: June 2024

I demonstrate the usage of planetary nebulae (PNe) to infer that a pair of jets shaped the ejecta of the core-collapse supernova (CCSN) SN 1987A. The main structure of the SN 1987A inner ejecta, the ‘keyhole’, comprises two low-intensity zones. The northern one has a bright rim on its front, while the southern one has an elongated nozzle. An earlier comparison of the SN 1987A ‘keyhole’ with bubbles in the galaxy group NGC 5813 led to its identification as a jet-shaped rim–nozzle structure. Here, I present rim–nozzle asymmetry in planetary nebulae (PNe), thought to be shaped by jets, which solidifies the claim that jets powered the ejecta of SN 1987A and other CCSNe. This finding for the iconic SN 1987A with its unique properties strengthens the jittering-jets explosion mechanism (JJEM) of CCSNe. In a few hundred years, the CCSN 1987A will have a complicated structure with two main symmetry axes, one along the axis of the three circumstellar rings that was shaped by two opposite 20,000-year pre-explosion jets, and the other along the long axis of the ‘keyhole’ that was shaped by the main (but not the only) jet pair of the exploding jets of SN 1987A in the frame of the JJEM.
Fine Mapping of QTLs for Alkaline Tolerance in Crucian Carp (Carassius auratus) Using Genome-Wide SNP Markers
Authors: Zhang Liang , Su Baofeng , Huang Jing , Zhang Limin , Chang Yumei , Hu Guo
Published: June 2024

Crucian carp (Carassius auratus) is widely distributed in the world and has become an economically freshwater fish. The population in Lake Dali Nur can tolerate the extreme alkaline environment with alkalinity over 50 mmol/L (pH 9.6), thus providing a special model for exploring alkali-tolerant molecular markers in an extremely alkaline environment. In this study, we constructed a high-density and high-resolution linkage map with 16,224 SNP markers based on genotyping-by-sequencing (GBS) consisting of 152 progenies and conducted QTL studies for alkali-tolerant traits. The total length of the linkage map was 3918.893 cM, with an average distance of 0.241 cM. Two QTLs for the ammonia-N-tolerant trait were detected on LG27 and LG45. A QTL for the urea-N-tolerant trait was detected on LG27. Interestingly, mapping the two QTLs on LG27 revealed that the mapped genes were both located in the intron of CDC42. GO functional annotation and KEGG enrichment analysis results indicated that the biological functions might be involved in the cell cycle, cellular senescence, MAPK, and Ras signaling pathways. These findings suggest that CDC42 may play an important role in the process of dealing with extremely alkaline environments.
Rare Pathogenic Variants in Pooled Whole-Exome Sequencing Data Suggest Hyperammonemia as a Possible Cause of Dementia Not Classified as Alzheimer’s Disease or Frontotemporal Dementia
Authors: Karachanak-Yankova Sena , Serbezov Dimitar , Antov Georgi , Stancheva Mikaela , Mihaylova Marta , Hadjidekova Savina , Toncheva Draga , Pashov Anastas , Belejanska Diyana , Zhelev Yavor , Petrova Mariya , Mehrabian Shima , Traykov Latchezar
Published: June 2024

The genetic bases of Alzheimer’s disease (AD) and frontotemporal dementia (FTD) have been comprehensively studied, which is not the case for atypical cases not classified into these diagnoses. In the present study, we aim to contribute to the molecular understanding of the development of non-AD and non-FTD dementia due to hyperammonemia caused by mutations in urea cycle genes. The analysis was performed by pooled whole-exome sequencing (WES) of 90 patients and by searching for rare pathogenic variants in autosomal genes for enzymes or transporters of the urea cycle pathway. The survey returned two rare pathogenic coding mutations leading to citrullinemia type I: rs148918985, p.Arg265Cys, C>T; and rs121908641, p.Gly390Arg, G>A in the argininosuccinate synthase 1 (ASS1) gene. The p.Arg265Cys variant leads to enzyme deficiency, whereas p.Gly390Arg renders the enzyme inactive. These variants found in simple or compound heterozygosity can lead to the late-onset form of citrullinemia type I, associated with high ammonia levels, which can lead to cerebral dysfunction and thus to the development of dementia. The presence of urea cycle disorder-causing mutations can be used for the early initiation of antihyperammonemia therapy in order to prevent the neurotoxic effects.
Adipokines as Possible Players in Inflammatory Bowel Disease: Electrophysiological Evaluation of Their Role in Causing Functional Gastrointestinal Alterations in Murine Tissue
Authors: Garella Rachele , Palmieri Francesco , Squecco Roberta
Published: June 2024

Inflammatory bowel disease (IBD) is a clinical condition of the gastrointestinal tract that has significant incidence in childhood. Major symptoms include abdominal pain, dyspepsia, delayed gastric emptying, anorexia, diarrhea and weight loss. IBD etiopathogenesis is multifactorial, with a proven involvement of cytokines. In this regard, cytokines like resistin and adiponectin produced by adipose tissue play a crucial role in inflammation. Particularly, resistin seems related to IBD severity and is considered a promising marker of disease occurrence and progression. Unraveling its mechanism of action and downstream effectors is mandatory when designing novel therapies. This preclinical study aims to further elucidate the action of resistin in causing functional gastrointestinal alterations, comparing it with the well-defined effect of adiponectin. To this end, we carried out electrophysiological analysis on murine gastric fundus. We found that resistin, similarly to adiponectin, increases smooth muscle cell (SMC) capacitance, indicative of cell surface remodeling, which is consistent with relaxation. However, contrary to adiponectin, resistin unalters membrane potential and inward Ca2+ entry and scarcely affects outward current, suggesting its inefficacy in markedly modifying electrical phenomena on the SMC membrane. This outcome, supporting the role of resistin in gastrointestinal distention, as observed in IBD, rules out a strikingly direct effect on SMCs.
The Paradox of Chivalric Madness: Ariosto’s and Cervantes’s Madness Representations’ Impact on Disability Representation
Authors: Johnson Nicholas L.
Published: June 2024

This study investigates the connection between madness and critiques of the chivalric romance genre in two late Renaissance works, Ludovico Ariosto’s Orlando Furioso and Miguel de Cervantes’s Don Quijote de la Mancha. The satire of chivalric romance in these works of fiction caution against nascent modes of thinking in imperial societies for the implementation of chivalric ideas to inspire and promote imperial conquests in Latin America through juxtaposition with the Muslim and Moorish conquest in the Maghreb and through metaphorical island governance. In order to make such critiques, these novels implement the madness of their parodic knights to disguise their critiques. This practice establishes a precedent which later literature can employ to make sociocultural critique covertly, to the detriment of disability representations as literary devices or metaphors.