bluuebunny/crossref_metadata_2025 huggingface dataset:
Amelioration of Sensorineural Hearing Loss through Regulation of Trpv1, Cacna1h, and Ngf Gene Expression by a Combination of Cuscutae Semen and Rehmanniae Radix Preparata
Authors: Hong Bin Na , Shin Sung Woo , Nam Youn Hee , Shim Ji Heon , Kim Na Woo , Kim Min Cheol , Nuankaew Wanlapa , Kwak Jong Hwan , Kang Tong Ho
Published: April 2023

Sensorineural hearing loss (SNHL) is a common condition that results from the loss of function of hair cells, which are responsible for converting sound into electrical signals within the cochlea and auditory nerve. Despite the prevalence of SNHL, a universally effective treatment has yet to be approved. To address this absence, the present study aimed to investigate the potential therapeutic effects of TS, a combination of Cuscutae Semen and Rehmanniae Radix Preparata. To this end, both in vitro and in vivo experiments were performed to evaluate the efficacy of TS with respect to SNHL. The results showed that TS was able to protect against ototoxic neomycin-induced damage in both HEI-OC1 cells and otic hair cells in zebrafish. Furthermore, in images obtained using scanning electron microscopy (SEM), an increase in the number of kinocilia, which was prompted by the TS treatment, was observed in the zebrafish larvae. In a noise-induced hearing loss (NIHL) mouse model, TS improved hearing thresholds as determined by the auditory brainstem response (ABR) test. Additionally, TS was found to regulate several genes related to hearing loss, including Trpv1, Cacna1h, and Ngf, as determined by quantitative real-time polymerase chain reaction (RT-PCR) analysis. In conclusion, the findings of this study suggest that TS holds promise as a potential treatment for sensorineural hearing loss. Further research is necessary to confirm these results and evaluate the safety and efficacy of TS in a clinical setting.
Use of a Silkworm (Bombyx mori) Larvae By-Product for the Treatment of Atopic Dermatitis: Inhibition of NF-κB Nuclear Translocation and MAPK Signaling
Authors: Fan Meiqi , Choi Young-Jin , Wedamulla Nishala Erandi , Zhang Qun , Kim Seong Wan , Bae Sung Moon , Seok Young-Seek , Kim Eun-Kyung
Published: April 2023

Atopic dermatitis (AD) is a long-lasting inflammatory skin disease that contributes to the global health burden and impacts 10–20% of the world’s population. In this study, we determined the anti-AD effect of a by-product of silkworm (Bombyx mori) larval powder, strain Yeonnokjam (SLPY), as a sustainable, natural source for the development of therapeutic agents for AD. HaCaT cells were used to assess the in vitro anti-inflammatory activity of SLPY, and a 1-chloro-2,4-dinitrobenzene (DNCB)-induced mouse model was used to study the in vivo anti-AD effects. SLPY treatment downregulated the expression of the inflammatory cytokines TNF-α, IL1β, IL-8, and Cox-2 in stimulated HaCaT cells. Similarly, the topical application of SLPY in DNCB-treated mice downregulated the expression of inflammatory cytokines and proteins while ameliorating the clinical features of AD. Further, SLPY treatment inhibited the nuclear translocation of NF-κb p65, thereby supporting the efficacy of SLPY in the treatment of AD.
Alginate-Based Materials Loaded with Nanoparticles in Wound Healing
Authors: Froelich Anna , Jakubowska Emilia , Wojtyłko Monika , Jadach Barbara , Gackowski Michał , Gadziński Piotr , Napierała Olga , Ravliv Yulia , Osmałek Tomasz
Published: April 2023

Alginate is a naturally derived polysaccharide widely applied in drug delivery, as well as regenerative medicine, tissue engineering and wound care. Due to its excellent biocompatibility, low toxicity, and the ability to absorb a high amount of exudate, it is widely used in modern wound dressings. Numerous studies indicate that alginate applied in wound care can be enhanced with the incorporation of nanoparticles, revealing additional properties beneficial in the healing process. Among the most extensively explored materials, composite dressings with alginate loaded with antimicrobial inorganic nanoparticles can be mentioned. However, other types of nanoparticles with antibiotics, growth factors, and other active ingredients are also investigated. This review article focuses on the most recent findings regarding novel alginate-based materials loaded with nanoparticles and their applicability as wound dressings, with special attention paid to the materials of potential use in the treatment of chronic wounds.
Cancer Resistance to Immunotherapy: Comprehensive Insights with Future Perspectives
Authors: Said Sawsan Sudqi , Ibrahim Wisam Nabeel
Published: April 2023

Cancer immunotherapy is a type of treatment that harnesses the power of the immune systems of patients to target cancer cells with better precision compared to traditional chemotherapy. Several lines of treatment have been approved by the US Food and Drug Administration (FDA) and have led to remarkable success in the treatment of solid tumors, such as melanoma and small-cell lung cancer. These immunotherapies include checkpoint inhibitors, cytokines, and vaccines, while the chimeric antigen receptor (CAR) T-cell treatment has shown better responses in hematological malignancies. Despite these breakthrough achievements, the response to treatment has been variable among patients, and only a small percentage of cancer patients gained from this treatment, depending on the histological type of tumor and other host factors. Cancer cells develop mechanisms to avoid interacting with immune cells in these circumstances, which has an adverse effect on how effectively they react to therapy. These mechanisms arise either due to intrinsic factors within cancer cells or due other cells within the tumor microenvironment (TME). When this scenario is used in a therapeutic setting, the term “resistance to immunotherapy” is applied; “primary resistance” denotes a failure to respond to treatment from the start, and “secondary resistance” denotes a relapse following the initial response to immunotherapy. Here, we provide a thorough summary of the internal and external mechanisms underlying tumor resistance to immunotherapy. Furthermore, a variety of immunotherapies are briefly discussed, along with recent developments that have been employed to prevent relapses following treatment, with a focus on upcoming initiatives to improve the efficacy of immunotherapy for cancer patients.
Pharmacokinetic Boosting of Kinase Inhibitors
Authors: Westra Niels , Touw Daan , Lub-de Hooge Marjolijn , Kosterink Jos , Oude Munnink Thijs
Published: April 2023

(1) Introduction: Pharmacokinetic boosting of kinase inhibitors can be a strategy to enhance drug exposure and to reduce dose and associated treatment costs. Most kinase inhibitors are predominantly metabolized by CYP3A4, enabling boosting using CYP3A4 inhibition. Kinase inhibitors with food enhanced absorption can be boosted using food optimized intake schedules. The aim of this narrative review is to provide answers to the following questions: Which different boosting strategies can be useful in boosting kinase inhibitors? Which kinase inhibitors are potential candidates for either CYP3A4 or food boosting? Which clinical studies on CYP3A4 or food boosting have been published or are ongoing? (2) Methods: PubMed was searched for boosting studies of kinase inhibitors. (3) Results/Discussion: This review describes 13 studies on exposure boosting of kinase inhibitors. Boosting strategies included cobicistat, ritonavir, itraconazole, ketoconazole, posaconazole, grapefruit juice and food. Clinical trial design for conducting pharmacokinetic boosting trials and risk management is discussed. (4) Conclusion: Pharmacokinetic boosting of kinase inhibitors is a promising, rapidly evolving and already partly proven strategy to increase drug exposure and to potentially reduce treatment costs. Therapeutic drug monitoring can be of added value in guiding boosted regimens.
A Bird’s Eye View of Various Cell-Based Biomimetic Nanomedicines for the Treatment of Arthritis
Authors: Vasdev Nupur , Pawar Bhakti , Gupta Tanisha , Mhatre Mahi , Tekade Rakesh Kumar
Published: April 2023

Arthritis is the inflammation and tenderness of the joints because of some metabolic, infectious, or constitutional reasons. Existing arthritis treatments help in controlling the arthritic flares, but more advancement is required to cure arthritis meticulously. Biomimetic nanomedicine represents an exceptional biocompatible treatment to cure arthritis by minimizing the toxic effect and eliminating the boundaries of current therapeutics. Various intracellular and extracellular pathways can be targeted by mimicking the surface, shape, or movement of the biological system to form a bioinspired or biomimetic drug delivery system. Different cell-membrane-coated biomimetic systems, and extracellular-vesicle-based and platelets-based biomimetic systems represent an emerging and efficient class of therapeutics to treat arthritis. The cell membrane from various cells such as RBC, platelets, macrophage cells, and NK cells is isolated and utilized to mimic the biological environment. Extracellular vesicles isolated from arthritis patients can be used as diagnostic tools, and plasma or MSCs-derived extracellular vesicles can be used as a therapeutic target for arthritis. Biomimetic systems guide the nanomedicines to the targeted site by hiding them from the surveillance of the immune system. Nanomedicines can be functionalized using targeted ligand and stimuli-responsive systems to reinforce their efficacy and minimize off-target effects. This review expounds on various biomimetic systems and their functionalization for the therapeutic targets of arthritis treatment, and discusses the challenges for the clinical translation of the biomimetic system.
Seed Priming with the Selenium Nanoparticles Maintains the Redox Status in the Water Stressed Tomato Plants by Modulating the Antioxidant Defense Enzymes
Authors: Ishtiaq Muhammad , Mazhar Muhammad Waqas , Maqbool Mehwish , Hussain Tanveer , Hussain Syed Atiq , Casini Ryan , Abd-ElGawad Ahmed M. , Elansary Hosam O.
Published: April 2023

In the present research, selenium nanoparticles (SeNPs) were tested for their use as seed priming agents under field trials on tomatoes (Solanum lycopersicum L.) for their efficacy in conferring drought tolerance. Four different seed priming regimes of SeNPs were created, comprising 25, 50, 75, and 100 ppm, along with a control treatment of 0 ppm. Seeds were planted in split plots under two irrigation regimes comprising water and water stress. The results suggest that seed priming with SeNPs can improve tomato crop performance under drought stress. Plants grown with 75 ppm SeNPs-primed seeds had lower hydrogen peroxide (H2O2) and malondialdehyde (MDA) levels by 39.3% and 28.9%, respectively. Seed priming with 75 ppm SeNPs further increased the superoxide dismutase (SOD) and catalase (CAT) functions by 34.9 and 25.4%, respectively. The same treatment increased the total carotenoids content by 13.5%, α-tocopherols content by 22.8%, total flavonoids content by 25.2%, total anthocyanins content by 19.6%, ascorbic acid content by 26.4%, reduced glutathione (GSH) content by 14.8%, and oxidized glutathione (GSSG) content by 13.12%. Furthermore, seed priming with SeNPs upregulated the functions of enzymes of ascorbate glutathione cycle. Seed priming with SeNPs is a smart application to sustain tomato production in arid lands.
The Effect of Stress Hormones, Ultraviolet C, and Stilbene Precursors on Expression of Calcineurin B-like Protein (CBL) and CBL-Interacting Protein Kinase (CIPK) Genes in Cell Cultures and Leaves of Vitis amurensis Rupr
Authors: Kiselev Konstantin V. , Aleynova Olga A. , Ogneva Zlata V. , Suprun Andrey R. , Ananev Alexey A. , Nityagovsky Nikolay N. , Dneprovskaya Alina A. , Beresh Alina A. , Dubrovina Alexandra S.
Published: April 2023

Calcium serves as a crucial messenger in plant stress adaptation and developmental processes. Plants encode several multigene families of calcium sensor proteins with diverse functions in plant growth and stress responses. Several studies indicated that some calcium sensors may be involved in the regulation of secondary metabolite production in plant cells. The present study aimed to investigate expression of calcineurin B-like proteins (CBL) and CBL-interacting protein kinase (CIPK) in response to conditions inducting biosynthesis of stilbenes in grapevine. We investigated CBL and CIPK gene expression in wild-growing grapevine Vitis amurensis Rupr., known as a rich stilbene source, in response to the application of stilbene biosynthesis-inducing conditions, including application of stress hormones (salicylic acid or SA, methyl jasmonate or MeJA), phenolic precursors (p-coumaric acids or CA), and ultraviolet irradiation (UV-C). The influence of these effectors on the levels of 13 VaCBL and 27 VaCIPK mRNA transcripts as well as on stilbene production was analyzed by quantitative real-time RT-PCR in the leaves and cell cultures of V. amurensis. The data revealed that VaCBL4-1 expression considerably increased after UV-C treatment in both grapevine cell cultures and leaves. The expression of VaCIPK31, 41-1, and 41-2 also increased, but this increase was mostly detected in cell cultures of V. amurensis. At the same time, expression of most VaCBL and VaCIPK genes was markedly down-regulated both in leaves and cell cultures of V. amurensis, which may indicate that the CBLs and CIPKs are involved in negative regulation of stilbene accumulation (VaCBL8, 10a-2, 10a-4, 11, 12, VaCIPK3, 9-1, 9-2, 12, 21-1, 21-2, 33, 34, 35, 36, 37, 39, 40, 41-3, 41-4). The results obtained provide new information of CBL and CIPK implication in the regulation of plant secondary metabolism in response to stress hormones, metabolite precursors, and UV-C irradiation.
Polysaccharides Are Effective Inhibitors of Natural Gas Hydrate Formation
Authors: Fakhreeva Alsu Venerovna , Nosov Vasily Viktorovich , Voloshin Alexander Iosifovich , Dokichev Vladimir Anatolyevich
Published: April 2023

This review covers the types and applications of chemical inhibitors of gas hydrate formation in the oil and gas industry. The main directions of the development of new types of highly effective and environmentally safe “green” kinetic hydrate inhibitors (KHIs) based on biopolymers are analyzed. The structure, physicochemical properties, efficiency of gas hydrate formation inhibition, and commercial prospects of polysaccharides in preventing and controlling the formation of gas hydrates are considered. The criteria for their selection, current experimental data, and the mechanism of inhibition are presented. Recent research in the development of cost-effective, efficient, and biodegradable KHIs for industrial applications in the oil and gas industry is also presented.
Molecular Weight Distribution of Branched Polymers: Comparison between Monte Carlo Simulation and Flory-Stockmayer Theory
Authors: Wen Chengyuan , Odle Roy , Cheng Shengfeng
Published: April 2023

It is challenging to predict the molecular weight distribution (MWD) for a polymer with a branched architecture, though such information will significantly benefit the design and development of branched polymers with desired properties and functions. A Monte Carlo (MC) simulation method based on the Gillespie algorithm is developed to quickly compute the MWD of branched polymers formed through step-growth polymerization, with a branched polyetherimide from two backbone monomers (4,4′-bisphenol A dianhydride and m-phenylenediamine), a chain terminator (phthalic anhydride), and a branching agent (tris[4-(4-aminophenoxy)phenyl] ethane) as an example. This polymerization involves four reactions that can be all reduced to a condensation reaction between an amine group and a carboxylic anhydride group. A comparison between the MC simulation results and the predictions of the Flory-Stockmayer theory on MWD shows that the rates of the reactions are determined by the concentrations of the functional groups on the monomers involved in each reaction. It further shows that the Flory-Stockmayer theory predicts MWD well for systems below the gel point but starts to fail for systems around or above the gel point. However, for all the systems, the MC method can be used to reliably predict MWD no matter if they are below or above the gel point. Even for a macroscopic system, a converging distribution can be quickly obtained through MC simulations on a system of only a few hundred to a few thousand monomers that have the same molar ratios as in the macroscopic system.
Deformation Behavior Investigation of Auxetic Structure Made of Poly(butylene adipate-co-terephthalate) Biopolymers Using Finite Element Method
Authors: Schneider Yanling , Guski Vinzenz , Schmauder Siegfried , Kadkhodapour Javad , Hufert Jonas , Grebhardt Axel , Bonten Christian
Published: April 2023

Auxetic structures made of biodegradable polymers are favorable for industrial and daily life applications. In this work, poly(butylene adipate-co-terephthalate) (PBAT) is chosen for the study of the deformation behavior of an inverse-honeycomb auxetic structure manufactured using the fused filament fabrication. The study focus is on auxetic behavior. One characteristic of polymer deformation prediction using finite element (FE) simulation is that no sounded FE model exists, due to the significantly different behavior of polymers under loading. The deformation behavior prediction of auxetic structures made of polymers poses more challenges, due to the coupled influences of material and topology on the overall behavior. Our work presents a general process to simulate auxetic structural deformation behavior for various polymers, such as PBAT, PLA (polylactic acid), and their blends. The current report emphasizes the first one. Limited by the state of the art, there is no unified regulation for calculating the Poisson’s ratio ν for auxetic structures. Here, three calculation ways of ν are presented based on measured data, one of which is found to be suitable to present the auxetic structural behavior. Still, the influence of the auxetic structural topology on the calculated Poisson’s ratio value is also discussed, and a suggestion is presented. The numerically predicted force–displacement curve, Poisson’s ratio evolution, and the deformed auxetic structural status match the testing results very well. Furthermore, FE simulation results can easily illustrate the stress distribution both statistically and local-topology particularized, which is very helpful in analyzing in-depth the auxetic behavior.
Experimental and Simulation Study on the Direct Contact Condensation of Saturated Steam on Moving Droplets at Sub-Atmospheric Pressure
Authors: Jing Yuanlin , Wang Yiping , Huang Qunwu
Published: April 2023

The recovery of low-temperature steam is of great significance to the effective utilization of energy. Direct contact condensation (DCC) technology is an effective heat recovery method with a low initial investment. An evaluation of the direct contact condensation heat transfer technology of water droplets and low-temperature saturated steam (at an absolute pressure of 7.3–19.9 kPa) was performed using both experimental and computational approaches. In the experiment, an experimental device based on the weighing method was set up, and the direct contact heat transfer process between droplets with a normalized diameter of less than 21.7 and saturated pure steam at 40–60 °C was experimentally investigated. The transient condensation efficiency and heat transfer coefficient were calculated by the real-time mass variation. The rapid condensation stage was classified to discuss the effects of initial droplet diameter, pressure, temperature, and mass flow rate on the heat transfer process. A two-dimensional model was developed using computational fluid dynamics techniques and verified by experimental results. The results indicated that when the normalized diameter of the droplet is less than two, 1.6 is the optimal value for DCC. For droplets with a normalized diameter greater than two, the optimal droplet temperature and mass flow rate are 15 °C and 10 g/s, respectively.
Corn Extrudates Enriched with Health-Promoting Ingredients: Physicochemical, Nutritional, and Functional Characteristics
Authors: Culețu Alina , Susman Iulia Elena , Mulțescu Mihaela , Cucu Șerban Eugen , Belc Nastasia
Published: April 2023

The objective of this study was to evaluate the effects of different types of powder additions on the properties of corn extrudates. The following ingredients, which are good sources of bioactive compounds, were used to substitute corn flour: legume protein sources (2% pea, 5% broccoli, and 5% lucerne), plants (15% beetroot and 15% rosehip), and condiments (2% chili, 2% turmeric, 2% paprika, and 2% basil). The total polyphenolic content (TPC) and antioxidant activity (AA) increased when the corn flour was replaced with the different types of ingredients. The highest TPC was found for rosehip followed by the beet, basil, and broccoli additions. Compared to the raw formulations, all the extrudates, except the rosehip extrudate, showed a decrease in the TPC ranging from 11 to 41%, with the smallest loss (11%) occurring for basil and the highest loss (41%) occurring for the control extrudate, respectively. The same observation was recorded for the AA. For the extrudate enriched with rosehip, the TPC and AA increased by 20% and 16%, respectively. The highest level of protein digestibility was in the corn extrudate with the pea addition followed by broccoli and lucerne. The extruded corn samples with condiment additions had a lower glycemic index than the control extrudate. This study demonstrated the potential for the production of gluten-free corn extrudates enriched with ingredients from different sources with improved nutritional properties, conferring also a natural color in the final extrudates.
Single-Cell Techniques in Environmental Microbiology
Authors: Shan Yongping , Guo Yuting , Jiao Wentao , Zeng Ping
Published: April 2023

Environmental microbiology has been an essential part of environmental research because it provides effective solutions to most pollutants. Hence, there is an interest in investigating microorganism behavior, such as observation, identification, isolation of pollutant degraders, and interactions between microbial species. To comprehensively understand cell heterogeneity, diverse approaches at the single-cell level are demanded. Thus far, the traditional bulk biological tools such as petri dishes are technically challenging for single cells, which could mask the heterogeneity. Single-cell technologies can reveal complex and rare cell populations by detecting heterogeneity among individual cells, which offers advantages of higher resolution, higher throughput, more accurate analysis, etc. Here, we overviewed several single-cell techniques on observation, isolation, and identification from aspects of methods and applications. Microscopic observation, sequencing identification, flow cytometric identification and isolation, Raman spectroscopy-based identification and isolation, and their applications are mainly discussed. Further development on multi-technique integrations at the single-cell level may highly advance the research progress of environmental microbiology, thereby giving more indication in the environmental microbial ecology.
Techniques Used for Bond Strengthening of Sub-Standard Splices in Concrete: A Review Study
Authors: Fayed Sabry , Mansour Walid , Tawfik Taher A. , Sabol Peter , Katunský Dušan
Published: April 2023

Bar splicing is considered an essential part of the construction process of reinforced concrete (RC) due to the ease of installation in construction, transportation constraints, and restricted length of reinforcing bars. Splices serve the primary role of joining reinforcement bars in standard RC elements such as columns, walls, beams, slabs, and joints. Bond behavior between the bars and the concrete is one of the fundamental qualities required for appropriate RC structure design and analysis, as it affects serviceability and ultimate limit states. The most common failure found in lap splice locations is debonding, which occurs at the splice region and insufficient lapped length is considered as the primary cause because of design or construction mistakes, design by outmoded code, and natural catastrophes. As a result, strengthening existing substandard splices in RC structures is critical. The purpose of this research is to analyze and summarize experimental strengthening solutions for inadequate splices. The most common methods are confining spirals, confining with internal or external steel stirrups or carbon fiber reinforced polymer (CFRP), concrete jacketing, fiber reinforced polymers (FRP), post-tensioning prestressed RC, external confining with CFRP, near surface mounted (NSM) techniques, ultra-high-performance concrete (UHPC), fiber reinforced concrete (FRC) and combinations of two methods. Each method of strengthening is evaluated based on its performance, benefits, drawbacks, application-specific elements, and variables influencing the design and scope of applicability. A comparison of the key methodologies was also carried out. The most recent studies and recommendations for improving inadequate lapped splices are provided.
Deconstruction of the Trance Model: Historical, Ethnographic, and Contextual Studies of Manchu Shamanism
Authors: Qu Feng
Published: April 2023

Social trends and historical contexts have popularized Eliade’s trance model in shamanism studies and have contributed to a famous academic debate. A case study on Manchu shamanism conducted in this article shows that a Manchu shaman functions primarily as a sacrificial specialist rather than a mental state adept. Three types of Manchu shamanism—court shamanism, clan shamanism, and wild shamanism—are examined based on historical and ethnographic analyses. This study deconstructs the trance model and demonstrates that shamanism among Manchus has a dynamic, reactive, constitutive, and unstable historical process.
SCAP SigFox: A Scalable Communication Protocol for Low-Power Wide-Area IoT Networks
Authors: Alqurashi Halah , Bouabdallah Fatma , Khairullah Enas
Published: April 2023

The Internet of Things (IoT) is a new future technology that is aimed at connecting billions of physical-world objects to the IT infrastructure via a wireless medium. Many radio access technologies exist, but few address the requirements of IoT applications such as low cost, low energy consumption, and long range. Low-Power wide-area network (LPWAN) technologies, especially SigFox, have a low data rate that makes them suitable for IoT applications, especially since the lower the data rate, the longer the usable distance for the radio link. SigFox technology achieves as a main objective network reliability by striving for the successful delivery of data messages through redundancy. Doing so results in one of the SigFox weaknesses, namely the high collision rate, which questions SigFox scalability. In this work, we aimed at avoiding collisions by changing SigFox’s Aloha-based medium access protocol to TDMA and by using only orthogonal channels while removing redundancy. Consequently, every node sends a single copy of the data message on a given orthogonal channel in a specific time slot. To achieve this, we implemented a slot- and channel-allocation protocol (SCAP) on top of SigFox. In other words, our goal was to improve SigFox’s scalability by implementing two mechanisms: time slot allocation and channel allocation. Performance analysis was conducted on large networks with sizes ranging from 1000 to 10,000 nodes to evaluate both technologies: the original SigFox and SCAP SigFox. The simulation results showed that SCAP SigFox highly reduced the probability of collision and energy consumption when compared to the original SigFox. Additionally, SCAP SigFox had a greater throughput and packet delivery ratio (PDR).
On the Comparison of Records from Standard and Engineered Fiber Optic Cables at Etna Volcano (Italy)
Authors: Diaz-Meza Sergio , Jousset Philippe , Currenti Gilda , Wollin Christopher , Krawczyk Charlotte , Clarke Andy , Chalari Athena
Published: April 2023

Distributed Dynamic Strain Sensing (DDSS), also known as Distributed Acoustic Sensing (DAS), is becoming a popular tool in array seismology. A new generation of engineered fibers is being developed to improve sensitivity and reduce the noise floor in comparison to standard fibers, which are conventionally used in telecommunication networks. Nevertheless, standard fibers already have extensive coverage around the Earth’s surface, so it motivates the use of the existing infrastructure in DDSS surveys to avoid costs and logistics. In this study, we compare DDSS data from stack instances of standard multi-fiber cable with DDSS data from a co-located single-fiber engineered cable. Both cables were buried in an area located 2.5 km NE from the craters of Mt. Etna. We analyze how stacking can improve signal quality. Our findings indicate that the stack of DDSS records from five standard fiber instances, each 1.5 km long, can reduce optical noise of up to 20%. We also present an algorithm to correct artifacts in the time series that stem from dynamic range saturation. Although stacking is able to reduce optical noise, it is not sufficient for restoring the strain-rate amplitude from saturated signals in standard fiber DDSS. Nevertheless, the algorithm can restore the strain-rate amplitude from saturated DDSS signals of the engineered fiber, allowing us to exceed the dynamic range of the record. We present measurement strategies to increase the dynamic range and avoid saturation.
Enhanced Intrusion Detection with Data Stream Classification and Concept Drift Guided by the Incremental Learning Genetic Programming Combiner
Authors: Shyaa Methaq A. , Zainol Zurinahni , Abdullah Rosni , Anbar Mohammed , Alzubaidi Laith , Santamaría José
Published: April 2023

Concept drift (CD) in data streaming scenarios such as networking intrusion detection systems (IDS) refers to the change in the statistical distribution of the data over time. There are five principal variants related to CD: incremental, gradual, recurrent, sudden, and blip. Genetic programming combiner (GPC) classification is an effective core candidate for data stream classification for IDS. However, its basic structure relies on the usage of traditional static machine learning models that receive onetime training, limiting its ability to handle CD. To address this issue, we propose an extended variant of the GPC using three main components. First, we replace existing classifiers with alternatives: online sequential extreme learning machine (OSELM), feature adaptive OSELM (FA-OSELM), and knowledge preservation OSELM (KP-OSELM). Second, we add two new components to the GPC, specifically, a data balancing and a classifier update. Third, the coordination between the sub-models produces three novel variants of the GPC: GPC-KOS for KA-OSELM; GPC-FOS for FA-OSELM; and GPC-OS for OSELM. This article presents the first data stream-based classification framework that provides novel strategies for handling CD variants. The experimental results demonstrate that both GPC-KOS and GPC-FOS outperform the traditional GPC and other state-of-the-art methods, and the transfer learning and memory features contribute to the effective handling of most types of CD. Moreover, the application of our incremental variants on real-world datasets (KDD Cup ‘99, CICIDS-2017, CSE-CIC-IDS-2018, and ISCX ‘12) demonstrate improved performance (GPC-FOS in connection with CSE-CIC-IDS-2018 and CICIDS-2017; GPC-KOS in connection with ISCX2012 and KDD Cup ‘99), with maximum accuracy rates of 100% and 98% by GPC-KOS and GPC-FOS, respectively. Additionally, our GPC variants do not show superior performance in handling blip drift.
Dynamic Finite Element Model Based on Timoshenko Beam Theory for Simulating High-Speed Nonlinear Helical Springs
Authors: Zhao Jianwei , Gu Zewen , Yang Quan , Shao Jian , Hou Xiaonan
Published: April 2023

Helical springs with nonlinear geometric parameters nowadays have shown great advantages over classical linear springs, especially due to their superior performance in diminishing dynamic responses in high-speed situations. However, existing studies are mostly available for springs with linear properties, and the sole FE spring models using solid elements occupy significant computational resources. This study presents an FE spring model based on Timoshenko beam theory, which allows for high-speed dynamic simulations of nonlinear springs using a beehive valve spring sample. The dynamic results are also compared with the results of the FE model using solid elements and the results of the engine head test and indicate that the proposed FE model can accurately predict dynamic spring forces and the phenomenon of coil clash when simulating the beehive spring at engine speeds of both 5600 and 8000 RPM. The results also indicate that rapid coil impact brings significant spike forces. It should also be noted that the FE spring model using beam elements displays sufficient accuracy in predicting the dynamic responses of nonlinear springs while occupying much fewer computational resources than the FE model using solid elements.
Sensorless Model Predictive Control of Single-Phase Inverter for UPS Applications via Accurate Load Current Estimation
Authors: Li Po , Tong Xiaoshan , Wang Zhoujing , Xu Maoguang , Zhu Jianfeng
Published: April 2023

Single-phase inverters with an output LC filter, can generate low distortion output voltages, which are suitable for uninterruptible power supply (UPS) systems. The UPS system provides emergency power in the case of utility power failure, requiring high reliability and clean power. The sensorless control method is actually a soft-sensing technique, that reduces system cost, measurement-related losses, and, especially important for UPS systems, enhances the system reliability. This paper proposes a load current sensorless finite control set model predictive control (FCS-MPC) scheme for a single-phase UPS inverter. A time varying observer is proposed, which offers the accurate estimation for individual components simultaneously in periodic load current signal, without subsequent complex calculations. Compared with another two typical sensorless methods (the low-pass filter and the Kalman filter), the proposed observer-based FCS-MPC strategy has smaller load current estimation error and lower output voltage distortion, under both linear and nonlinear loads. The theoretical analysis is verified through simulation and experiment. A single-phase inverter rapid control prototype (RCP) is set up with the Speedgoat real-time target machine, to confirm the effectiveness of the system.
Aggregating Different Scales of Attention on Feature Variants for Tomato Leaf Disease Diagnosis from Image Data: A Transformer Driven Study
Authors: Hossain Shahriar , Tanzim Reza Md , Chakrabarty Amitabha , Jung Yong Ju
Published: April 2023

Tomato leaf diseases can incur significant financial damage by having adverse impacts on crops and, consequently, they are a major concern for tomato growers all over the world. The diseases may come in a variety of forms, caused by environmental stress and various pathogens. An automated approach to detect leaf disease from images would assist farmers to take effective control measures quickly and affordably. Therefore, the proposed study aims to analyze the effects of transformer-based approaches that aggregate different scales of attention on variants of features for the classification of tomato leaf diseases from image data. Four state-of-the-art transformer-based models, namely, External Attention Transformer (EANet), Multi-Axis Vision Transformer (MaxViT), Compact Convolutional Transformers (CCT), and Pyramid Vision Transformer (PVT), are trained and tested on a multiclass tomato disease dataset. The result analysis showcases that MaxViT comfortably outperforms the other three transformer models with 97% overall accuracy, as opposed to the 89% accuracy achieved by EANet, 91% by CCT, and 93% by PVT. MaxViT also achieves a smoother learning curve compared to the other transformers. Afterwards, we further verified the legitimacy of the results on another relatively smaller dataset. Overall, the exhaustive empirical analysis presented in the paper proves that the MaxViT architecture is the most effective transformer model to classify tomato leaf disease, providing the availability of powerful hardware to incorporate the model.
Biometric Technologies Based on Optical Coherence Tomography
Authors: Marciniak Tomasz
Published: April 2023

Optical coherence tomography (OCT) is one of the newest and most important optical non-invasive methods for the investigation and testing of various materials (e [...]
Path Planning for Obstacle Avoidance of Robot Arm Based on Improved Potential Field Method
Authors: Xia Xinkai , Li Tao , Sang Shengbo , Cheng Yongqiang , Ma Huanzhou , Zhang Qiang , Yang Kun
Published: April 2023

In medical and surgical scenarios, the trajectory planning of a collaborative robot arm is a difficult problem. The artificial potential field (APF) algorithm is a classic method for robot trajectory planning, which has the characteristics of good real-time performance and low computing consumption. There are many variants of the APF algorithm, among which the most widely used variants is the velocity potential field (VPF) algorithm. However, the traditional VPF algorithm has inherent defects and problems, such as easily falling into local minimum, being unable to reach the target, poor dynamic obstacle avoidance ability, and safety and efficiency problems. Therefore, this work presents the improved velocity potential field (IVPF) algorithm, which considers direction factors, obstacle velocity factor, and tangential velocity. When encountering dynamic obstacles, the IVPF algorithm can avoid obstacles better to ensure the safety of both the human and robot arm. The IVPF algorithm also does not easily fall into a local problem when encountering different obstacles. The experiments informed the RRT* algorithm, VPF algorithm, and IVPF algorithm for comparison. Compared with the informed RRT* and VPF algorithm, the result of experiments indicate that the performances of the IVPF algorithm have significant improvements when dealing with different obstacles. The main aim of this paper is to provide a safe and efficient path planning algorithm for the robot arm in the medical field. The proposed algorithm can ensure the safety of both the human and the robot arm when the medical and surgical robot arm is working, and enables the robot arm to cope with emergencies and perform tasks better. The application of the proposed algorithm could make the collaborative robots work in a flexible and safe condition, which could open up new opportunities for the future development of medical and surgical scenarios.
Social Determinants of Health and Vascular Diseases: A Systematic Review and Call for Action
Authors: Costa Davide , Ielapi Nicola , Bevacqua Egidio , Ciranni Salvatore , Cristodoro Lucia , Torcia Giuseppina , Serra Raffaele
Published: April 2023

Several factors that underlie health inequality have been studied and defined as the social determinants of health (SDHs). The main SDHs are gender, socioeconomic status (SES), and ethnicity. In this study, disparity was analyzed in the context of vascular diseases (VDs) such as Peripheral Artery Disease (PAD), Chronic Venous Disease (CVD), Abdominal Arterial Aneurysm (AAA), and Carotid Stenosis (CS). This article aims to provide a comprehensive overview of the published evidence of the SDHs in VDs. For this purpose, Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used. Published articles using the Scopus and ScienceDirect databases were searched. The criteria for the articles’ inclusion/exclusion were decided using a modified PICOTS framework. For the selected articles, the data sheets were organized in such a way to extract all data of potential relevance. Our findings showed that in VDs, gender, SES, and ethnicity are very important, with some specific problems for VDs analyzed. In conclusion, having detected the presence of SDHs that act negatively on VDs, a model based on action items for the SDHs associated with VDs was proposed.
Proposed Method for the Design of Geosynthetic-Reinforced Pile-Supported (GRPS) Embankments
Authors: Alsirawan Rashad , Koch Edina , Alnmr Ammar
Published: April 2023

Soft soils with unfavorable properties can be improved using various ground-improvement methods. Among these methods, geosynthetic-reinforced pile-supported (GRPS) embankments are considered a reliable option for challenging ground conditions and time-bound projects. Nevertheless, the intricate load transfer mechanism of the GRPS embankment presents challenges due to the multiple interactions among its components. To overcome the limitations of current design methods that do not fully account for all interactions, a simplified design method has been developed for GRPS embankments. This method uses numerical analysis to predict pile load efficiency and geosynthetic tension. In this study, a validated model of the GRPS embankment, which incorporates certain simplifications for design purposes, was adopted. Based on this simplified model, a database of load efficiency and geosynthetic tension was collected to derive the design equations. The design method employed six parameters, namely, pile cap width, pile spacing, embankment height, oedometric modulus of the subsoil, geosynthetic stiffness, and embankment fill unit weight. The design process utilized Plaxis 3D and Curve Expert software. The results showed reasonable agreement between the findings of the proposed design method and the field measurements of eight case studies.
Intra-Household Income Management and Couple’s Relative Sharing of Income and Environment Sustainability in Japan
Authors: Piao Xiangdan
Published: April 2023

This study aims to identify household members’ income sharing, when the amount of said income is governed by a particular household member. The results are expected to provide insightful evidence that identifies who is under the poverty line within families. This will illustrate the intra-household allocation inequality by observing the members’ household income dominance. Using the information on household income management obtained from the Japanese Household Panel Survey data (1993–2013) and the original Internet survey, this paper develops an alternative methodology to estimate the household income distribution of couples. A two-step estimation process was employed to estimate the wife’s manageable income equation. Then, the parameters were substituted into the husband’s manageable income equation to estimate the parameters for calculating the wife’s sharing rule. The results are as follows. First, a wife’s share of intra-household resources positively correlates to her manageable income resources. However, wives have weak power in expending the transferred income from their husbands. Second, the remarkable feature is that, on average, wives share 37% of the resources, meaning that the wives’ relative bargaining is weaker than the husbands’. Narrowing the gap in terms of hourly wage between husbands and wives is a crucial tool to reduce the intra-household allocation gap. Third, the wives’ relative intrahousehold income allocation improvement is associated with household environment sustainability activities. To improve the intra-household income allocation inequality, we provide an original approach to explore the intra-household head of household members’ relative income sharing. The results highlight the inequality of intra-household income distribution and confirm that reducing the income gap would be a crucial improvement factor.
Spatial Heterogeneity Effects of Green Finance on Absolute and Relative Poverty
Authors: Tang Yonghong , Wang Hui , Lin Zirong
Published: April 2023

In light of the growing emphasis on sustainable development, financial poverty alleviation has become an increasingly important strategy. This study explores whether green finance, a new financial tool aimed at achieving sustainable development, can effectively reduce poverty. Using data from 25 provinces in China between 2004 and 2019, the study builds the China Green Financial Development Index, using the improved entropy power method, and uses a spatial econometric model to analyze the linear and non-linear impact of green finance on absolute and relatively poor poverty. The results demonstrate that green finance has a positive impact on poverty reduction, with a more significant impact on rural poverty reduction than urban poverty reduction. Interestingly, non-linear results reveal that the impact of green finance on rural poverty alleviation has gradually weakened, while the impact on urban poverty alleviation has gradually increased. Moreover, the introduction of technological progress as an intermediary variable has revealed an intermediary effect between green finance and poverty reduction. Overall, this study contributes to our understanding of the link between green finance and poverty and suggests a new approach to poverty alleviation.
Developing Female Sustainable Entrepreneurial Intentions through an Entrepreneurial Mindset and Motives
Authors: Abdelwahed Nadia Abdelhamid Abdelmegeed , Alshaikhmubarak Abdulrahman
Published: April 2023

In this study, we investigated the effect of entrepreneurial competencies (ECs) on entrepreneurial mindset (EM), entrepreneurial intention (EI), and entrepreneurial motives (EMTs) among female Saudi Arabian university students. We applied a quantitative approach and collected the data through a survey questionnaire by using convenience sampling to trace the respondents. Finally, the results of this study were based on 388 samples. By using a structural equation model (SEM), the findings demonstrate that ECs have positive and significant effects on EM, EI, and EMTs. In addition, there are positive and significant relationships between EM and EI as well as between EMTs and EI. Finally, EM and EMTs mediate the connection between ECs and EI. The findings of this study could support policymakers at different levels in developing their financial models, plans, and suggestions for entrepreneurial development. In addition, the findings should inspire well motivated people to engage in entrepreneurial activities and to aspire to become entrepreneurs. Finally, the originality and value of this research contribute to the existing literature, by demonstrating among Saudi Arabian female university students, the effects of ECs on EM, EI, and EMTs.
Opportunities or Risks: Economic Impacts of Climate Change on Crop Structure Adjustment in Ecologically Vulnerable Regions in China
Authors: Ma Mingying , Huang Delin , Hossain Syed Shoyeb
Published: April 2023

Global warming by 2 °C or above will frequently see weather beyond the critical tolerance threshold for agricultural extreme high temperatures. If so, people will have to more accurately evaluate the opportunities and risks posed by future climate change while adjusting the structure of agricultural production. However, accurate assessment results of the impacts of climate change on crop yield are absent in the current studies on the impact of climate change on the agricultural economy. To address this gap, this paper sets forth a comprehensive evaluation method using a crop model coupled with a computable general equilibrium model. According to research findings, future climate change may continue with the trend of the continued decline of grain planting areas and the continued growth of cash crop planting areas in ecologically vulnerable regions. This will make grain security more difficult. On one hand, perennial crop planting broadens the eco-space for future economic and social development in ecologically vulnerable regions. Therefore, attention should be paid to grain security. The cash crop planting area should not be excessively expanded. On the other hand, it is advised to plant perennial crops in those areas which are unsuitable for planting cash crops.