bluuebunny/crossref_metadata_2025 huggingface dataset:
Malagasy Amphibian Wildlife Trade Revisited: Improving Management Knowledge of the Trade
Authors: Carpenter Angus I. , Andreone Franco
Published: July 2023

Madagascar is a biodiversity hotspot with a long history of trading in its wildlife, especially its hyper-diverse amphibian taxa. Due to globally raised concerns over the conservation of harvested species, CITES was introduced as a global mechanism with which to monitor and regulate the trade. Utilising data collated from the CITES Trade database, this study sought to investigate the trade and CITES’ effectiveness in managing the trade with respect to Madagascar. Over a 28-year period, 20 known amphibian species were exported from Madagascar, constituting a total of nearly 271,000 individuals. Formal descriptions of Malagasy amphibian species have increased and continue to increase greatly over time. However, there was no longitudinal relationship regarding the numbers of individuals traded as new species were described. Overall, the number of individuals traded has declined over time, but where assessments were provided by the IUCN Redlist, population declines were reported in all but one species of Malagasy amphibian. Mantella (97.5%) continues to be the predominantly traded genus, with certain, high-conservation-concern, species continuing to be traded. Despite initial concerns over the effectiveness of CITES’s actions, after concerted efforts, it appears that CITES’ actions were having positive impacts on regulating the trade. However, going forward, concerns remain over the appropriateness of the quotas set and the robustness of their underpinning NDFs. Furthermore, with the increase in the number of recognised species, the potential for incorrect species labelling on the CITES permits increases and requires greater attention.
Laricitrin 3-Rutinoside from Ginkgo biloba Fruits Prevents Damage in TNF-α-Stimulated Normal Human Dermal Fibroblasts
Authors: Lee Sullim , Choi Yea Jung , Huo Chen , Alishir Akida , Kang Ki Sung , Park Il-Ho , Jang Taesu , Kim Ki Hyun
Published: July 2023

Human skin comprises the epidermis and dermis, which perform interactive functional activities with each other in order to maintain the skin’s tensile strength. In particular, the dermal layer is crucial for skin protection. However, skin aging destroys collagen and elastin fibers, causing wrinkles, pigments, and sagging. Skin aging-related factors, such as tumor necrosis factor-α (TNF-α), promote the generation of intercellular reactive oxygen species (ROS). These are known to stimulate the hypersecretion of matrix metalloproteinase-1 (MMP-1), which degrades collagen and inhibits collagen synthesis. In this study, as part of our ongoing discovery of natural products, we investigated potential natural products derived from ginkgo fruit (Ginkgo biloba fruit) with protective effects against TNF-α-induced skin aging. Phytochemical investigation of the MeOH extract of G. biloba fruits, aided by liquid chromatography–mass spectrometry, led to the isolation of 14 compounds (1–14) from the n-butanol-soluble fraction. These were structurally determined to be: (E)-coniferin (1), syringin (2), 4-hydroxybenzoic acid 4-O-β-D-glucopyranoside (3), vanillic acid 4-O-β-D-glucopyranoside (4), glucosyringic acid (5), (E)-ferulic acid 4-O-β-D-glucoside (6), (E)-sinapic acid 4-O-β-D-glucopyranoside (7), ginkgotoxin-5-glucoside (8), ginkgopanoside (9), (Z)-4-coumaric acid 4-O-β-D-glucopyranoside (10), (1′R,2′S,5′R,8′S,2′Z,4′E)-dihydrophaseic acid 3’-O-β-D-glucopyranoside (11), eucomic acid (12), rutin (13), and laricitrin 3-rutinoside (L3R) (14). Biological evaluation of the isolated compounds for their effects on intracellular ROS generation showed that, of these 14 compounds, L3R (14) inhibited TNF-α-stimulated ROS generation (p < 0.001 at 100 μM). Inhibition of ROS generation by L3R led to the suppression of MMP-1 secretion and protection against collagen degradation. The inhibitory effect of L3R was mediated by the inhibition of extracellular signal regulated kinase (ERK) phosphorylation. Furthermore, L3R diminished the secretion of pro-inflammatory cytokines interleukin 6 (IL-6) and interleukin 8 (IL-8). Based on these experimental results, L3R is a potential bioactive natural product that can be used to protect against skin damage, including aging, in cosmetics and pharmaceuticals.
Validation of a Qualification Procedure Applied to the Verification of Partial Discharge Analysers Used for HVDC or HVAC Networks
Authors: Vera Carlos , Garnacho Fernando , Klüss Joni , Mier Christian , Álvarez Fernando , Lahti Kari , Khamlichi Abderrahim , Elg Alf-Peter , Rodrigo Mor Armando , Arcones Eduardo , Camuñas Álvaro , Pakonen Pertti , Ortego Javier , Vidal José Ramón , Haider Miran , Rovira Jorge , Simon Pascual , Squicciarini Antonio
Published: July 2023

The insulation condition of HVDC grids consisting of cable systems, GIS, and converters should be monitored by partial discharge (PD) analysers using artificial intelligence (AI) tools for efficient insulation diagnosis. Although there are many experiences of PD monitoring solutions developed for the supervision of the insulation condition of HVAC grids using PD analysers, there are no standardised requirements for their qualification available yet. The international technical specification TS IEC 62478 provides general rules for PD measurements using electromagnetic methods but does not define performance requirements for qualification tests. HVDC and HVAC PD analysers must be tested by unambiguous test procedures. This paper compiles experiences of using PD analysers with HFCT sensors in HVAC grids (cable systems, GIS, and AIS) to define a qualification procedure for HVAC systems. This procedure is applicable to HVDC grids (cable systems, GIS, AIS, and converters) because the particularities related to the insulation behaviour under HVDC voltage are also considered. Representative PD sources are discussed in HVAC and HVDC positive and negative polarity. The PD pulse trend of representative insulation defects in HVDC cable systems is quite different from that of HVAC grids. Special attention should be paid to the acquisition of PD signals in HVDC grids since few pulses appear in solid insulations, mainly during voltage changes (polarity reversals or surges), but rarely in continuous operation with constant direct voltage. A synthetic PD simulator has been developed to reproduce trains of PD pulses or noise signals, similar to those that can appear in the power network. A set of three functionality tests has been developed for qualification of the diagnostic capabilities of PD analysers working up to 30 MHz addressed to HVDC or HVAC grids: (1) PD recognition test, (2) PD clustering test, and (3) PD location test. This qualification procedure has been validated by means of a round-robin test performed by five research institutes (RISE, FFII, TUDelft, TAU, and UPM) using commercial and in-development AI PD recognition and clustering tools to demonstrate its robustness and applicability. Applying this qualification procedure, two PD methods for electrical detection and prevention of insulation defects have been approved, one for HVAC and the other for HVDC grids.
Acoustics of Compressed Earth Blocks Bound Using Sugarcane Bagasse Ash and Water Hyacinth Ash
Authors: Ongwen Nicholas O. , Alruqi Adel Bandar
Published: July 2023

Mechanical compaction is often used to densify building earth blocks by reducing the void between the particles. Compacted stabilised earth involves a binder, which holds the particles of the materials together. The compaction and addition of binders to the earth can modify its transport, mechanical, and acoustical properties. In this study, the acoustic transmission coefficient, porosity, and airflow resistivity were investigated by varying the concentrations of water hyacinth ash (WHA) and sugarcane bagasse ash (SBA) binders. An acoustic test rig comprising an acoustic wave guide made from joined water pipes was employed to analyse the influence of the WHA and SBA binders on the acoustical performance of the earth blocks. It was found out that the measured acoustic wave transmission was sensitive to the variation in the composition of WHA and SBA in the earth blocks. Increasing the WHA concentration led to an increase in the acoustic transmission coefficient and porosity, but reduced the airflow resistivity of the compressed earth blocks; while increasing the SBA reduced the transmission coefficient and porosity, but increased the airflow resistivity. This shows that SBA has a stronger binding property than WHA, which is ideal for the manufacture of stronger earth blocks, while the higher porosity of the earth blocks obtained with WHA is good for the construction of porous walls, which is good for maintaining the airflow between the inside of buildings and the surrounding.
Enhancing an Imbalanced Lung Disease X-ray Image Classification with the CNN-LSTM Model
Authors: Fachrel Julio , Pravitasari Anindya Apriliyanti , Yulita Intan Nurma , Ardhisasmita Mulya Nurmansyah , Indrayatna Fajar
Published: July 2023

Lung diseases have a significant impact on respiratory health, causing various symptoms and posing challenges in diagnosis and treatment. This research presents a methodology for classifying lung diseases using chest X-ray images, specifically focusing on COVID-19, pneumonia, and normal cases. The study introduces an optimal architecture for convolutional neural network (CNN) and long short-term memory (LSTM) models, considering evaluation metrics and training efficiency. Furthermore, the issue of imbalanced datasets is addressed through the application of some image augmentation techniques to enhance model performance. The most effective model comprises five convolutional blocks, two LSTM layers, and no augmentation, achieving an impressive F1 score of 0.9887 with a training duration of 91 s per epoch. Misclassifications primarily occurred in normal cases, accounting for only 3.05% of COVID-19 data. The pneumonia class demonstrated excellent precision, while the normal class exhibited high recall and an F1 score. Comparatively, the CNN-LSTM model outperformed the CNN model in accurately classifying chest X-ray images and identifying infected lungs. This research provides valuable insights for improving lung disease diagnosis, enabling timely and accurate identification of lung diseases, and ultimately enhancing patients’ outcomes.
Radiation-Induced Thermal Runaway Propagation in a Cylindrical Li-Ion Battery Pack: Non-Monotonicity, Chemical Kinetics, and Geometric Considerations
Authors: Zhang Liwen , Chen Yi , Ge Haiwen , Jain Ankur , Zhao Peng
Published: July 2023

Li-ion batteries play a key role in energy storage and conversion in engineering systems such as electric vehicles and grid energy storage, with critical impact on electrification and storage of renewable energy. A key unresolved technological challenge in Li-ion batteries pertains to thermal runaway initiation and propagation in a battery pack, which can lead to subsequent fire and explosion. Despite significant past work, there remains a critical need to understand how thermal runaway propagates in a pack. This work presents a comprehensive investigation of the effect of radiative heat transfer on thermal runaway propagation. Radiation can be important when a battery is exposed to adjacent heat and fire sources, as well as in thermal runaway propagation from one hot cell to another. A theoretical radiative heat transfer model based on view factor theory is developed. Calculations based on this model for a simple 2D cylinder-to-cylinder geometry are found to be in very good agreement with analytical expressions. Radiation-induced thermal runaway propagation between two cylindrical 18650 batteries is evaluated. It is shown that radiation may play a key role in thermal runaway propagation, depending strongly on the triggering temperature. It is found that radiative effects in thermal runaway propagation exhibit both nonlinear and non-monotonic characteristics. At high temperatures, thermal runaway is triggered rapidly in the region close to the battery surface, where the chemical reactions are strongly coupled, and radiation plays a dominant role. In contrast, at lower temperatures, thermal runaway is triggered much more slowly and towards the core of the cell, where some chemical reactions may be decoupled, and pre-runaway chemical heat release plays an increasingly important role. The results presented here suggest that radiation can either facilitate or mitigate thermal runaway. The net radiation heat flux has a cross-over instant, beyond which radiation starts to retard thermal runaway. Additionally, the blocking effect in radiative heat transfer between cells arranged in equal-spacing homogenous or orthogonal arrangements in a battery pack is investigated, along with the effect of the hot spot size. Results from this work help understand the role of radiation in thermal runaway propagation and provide useful insights into the thermal runaway control and design of safe Li-ion battery packs.
Quantification of the Effective Detectable Period for Concrete Voids of CLP by Lock-In Thermography
Authors: Kim Chunyoung , Kang Seongmin , Chung Yoonjae , Kim Okhwan , Kim Wontae
Published: July 2023

This study is to inspect the voids between the concrete containment building and the containment liner plate (CLP) in the light-water reactor type nuclear power plant with lock-in thermography (LIT) inspection technology. For that, a finite element method (FEM) model containing concrete voids was created, and the thermal distribution change of the CLP surface was simulated through numerical analysis simulation of various LIT inspection conditions and converted with real-time thermography data. For the simulated temperature distribution image and the amplitude and phase images calculated by the four-point method, the signal-to-noise ratio (SNR) is analyzed based on the sound area and void areas. As a result, the difference in SNR according to the size of voids was remarkable, and the effective detectable period (EDP), which was common to each inspection condition, was derived. Furthermore, a CLP concrete mockup identical to the model shape is produced, and the thermal image of the EDP is analyzed through the experiment with the same analysis technique, and the results are compared. Although there are some differences between the numerical analysis conditions and the experimental environments, the deduction and utilization of EDP through FEM simulation are considered useful approaches to applying LIT to inspect concrete voids on the back of the CLP.
Buckling-Restrained Bracing System with Ultra-High-Performance Fiber Concrete
Authors: Ostovar Nima , Hejazi Farzad
Published: July 2023

Recently, buckling-restrained braces (BRBs) have been widely implemented as seismic load resistance systems in buildings to enhance their response against dynamic vibration. However, during catastrophic earthquakes, the steel core in BRB devices fully yields, which causes the BRB to lose its functionality. While the incorporation of various filler materials, such as new high-performance concretes, has the potential to enhance the performance of buckling-restrained braces (BRBs), there remains a notable gap regarding comprehensive research investigating this aspect. Therefore, this study assessed the effect of implementing ultra-high-performance concrete (UHPFRC) as filler material on BRB behavior. For this purpose, the finite element model for the proposed BRB was developed and hysteresis analysis results under incremental cyclic loads were investigated. Then, the prototype of a BRB with UHPFRC concrete was cast and experimentally tested under cyclic loads by using a dynamic actuator. Based on the testing results, a new design for a BRB device named as rubber buckling-restrained brace (RBRB) was developed, implementing hyperelastic rubber components between the steel core and UHPFRC as an additional load-bearing mechanism to enhance the device vibration dissipation capacity. Subsequently, a finite element model of the newly proposed rubber buckling-restrained brace (RBRB) was developed to assess the device’s performance. The analysis results demonstrate a notable enhancement in load capacity and energy dissipation for the RBRB device compared to conventional BRBs.
Machine Learning and miRNAs as Potential Biomarkers of Breast Cancer: A Systematic Review of Classification Methods
Authors: Contreras-Rodríguez Jorge Alberto , Córdova-Esparza Diana Margarita , Saavedra-Leos María Zenaida , Silva-Cázares Macrina Beatriz
Published: July 2023

This work aims to offer an analysis of empirical research on the automatic learning methods used in detecting microRNA (miRNA) as potential markers of breast cancer. To carry out this study, we consulted the sources of Google Scholar, IEEE, PubMed, and Science Direct using appropriate keywords to meet the objective of the research. The selection of interesting articles was carried out using exclusion and inclusion criteria, as well as research questions. The results obtained in the search were 36 articles, of which PubMed = 14, IEEE = 8, Science Direct = 4, Google Scholar = 10; among them, six were selected, since they met the search perspective. In conclusion, we observed that the machine learning methods frequently mentioned in the reviewed studies were Support Vector Machine (SVM) and Random Forest (RF), the latter obtaining the best performance in terms of precision.
Similarities of Three Most Extreme Precipitation Events in North China
Authors: Dong Quan , Sun Jun , Chen Boyu , Chen Yun , Shu Yu
Published: July 2023

In this study, three typical and most extreme precipitation events in the history of North China are analyzed and compared in terms of accumulated precipitation and synoptical circulation using surface station observations of China and the ERA5 dataset. The three events happened in August 1963 (“63.8” event, hereafter), August 1975 (“75.8” event), and July 2021 (“21.7” event), respectively, mainly in Hebei and Henan Provinces of North China. The results show that the maximum daily and 4-day accumulated precipitation of all three events exceeded 500 mm and 800 mm, with many stations’ daily precipitation ranking Top 1. The “63.8” event persisted for the longest time, affected the largest area, and rained the most in 7 days (over 1000 mm). The “75.8” event was characterized by the most extreme daily precipitation and a concentrated area. All three events characterize a normal northward subtropical high that was located in North China and Northeast China. At 500 hPa, the area from South China to the South China Sea was dominated by a uniform pressure field. In the upper levels, there were troughs and divergence anomalies in all three events. In the low levels, there were anomalous low-level jets and the associated water vapor flux anomalies, which were located at different levels and came from different directions. Stable synoptical circulation and persistent jet and water vapor flux anomalies are the key factors in these extreme events.
Temperature Evolution of Cooling Zones on Global Land Surface since the 1900s
Authors: Wu Luhua , Bai Xiaoyong , Tian Yichao , Li Yue , Luo Guangjie , Wang Jinfeng , Chen Fei
Published: July 2023

The existence of global warming is common knowledge. However, it can be predicted that there may be cooling zones worldwide based on the mechanism of terrestrial biophysical processes. Here, the Theil–Sen median trend, the Mann–Kendall trend test method, continuous wavelet transformation, and the Hurst exponent were used to study the cooling trends, abrupt change times, periodicity, and future sustainability of temperature changes in different cooling zones since the 1900s based on the CRU dataset. We found an amazing result; 8,305,500 km2 of land surface had been cooling since the 1900s, covering five continents and 32 countries, accounting for 86% of land area in China, and distributed over 16 zones. The average cooling rate of the cooling zones was −0.24 °C/century. The maximum cooling rate was −1.40 °C/century, and it was 1.43 times the average rate of global land warming (0.98 °C/century). The cooling zones near the sea were greatly influenced by ocean currents and were mainly affected by a small time scale periodicity of less than 30 years, whereas the cold zones located relatively far from the sea and less affected by ocean currents were mainly affected by medium time scales of more than 30 years. Moreover, 32.33% of the cooling zones, involving 2,684,900 km2, will be continuously cooling in the future, and the rest will probably warm up in 2114, 2041, 2096, 2099, 2119, 2073, 2048, and 2101, respectively. The study will help us to further understand the essential characteristics of global climate change, and to find more theoretical bases for mitigating global warming and exploring surface cooling mechanisms.
Analysis of WE Parameters of Life Using Adaptive-Progressively Type-II Hybrid Censored Mechanical Equipment Data
Authors: Elshahhat Ahmed , Almetwally Ehab M. , Dey Sanku , Mohammed Heba S.
Published: July 2023

A new two-parameter weighted-exponential (WE) distribution, as a beneficial competitor model to other lifetime distributions, namely: generalized exponential, gamma, and Weibull distributions, is studied in the presence of adaptive progressive Type-II hybrid data. Thus, based on different frequentist and Bayesian estimation methods, we study the inferential problem of the WE parameters as well as related reliability indices, including survival and failure functions. In frequentist setups, besides the standard likelihood-based estimation, the product of spacing (PS) approach is also taken into account for estimating all unknown parameters of life. Making use of the delta method and the observed Fisher information of the frequentist estimators, approximated asymptotic confidence intervals for all unknown parameters are acquired. In Bayes methodology, from the squared-error loss with independent gamma density priors, the point and interval estimates of the unknown parameters are offered using both joint likelihood and the product of spacings functions. Because a closed solution to the Bayes estimators is not accessible, the Metropolis–Hastings sampler is presented to approximate the Bayes estimates and also to create their associated highest interval posterior density estimates. To figure out the effectiveness of the developed approaches, extensive Monte Carlo experiments are implemented. To highlight the applicability of the offered methodologies in practice, one real-life data set consisting of 30 failure times of repairable mechanical equipment is analyzed. This application demonstrated that the offered WE model provides a better fit compared to the other eight lifetime models.
Techno-Economic Analysis of Different Battery Cell Chemistries for the Passenger Vehicle Market
Authors: Hasselwander Samuel , Meyer Markus , Österle Ines
Published: July 2023

The introduction of battery electric vehicles on the global market has triggered a sustained upheaval in the automotive industry. In this process, the new properties of a battery-electric powertrain lead to a different set of central requirements, such as increasing the range, lifetime or the fast-charging capability of the vehicle battery. This paper develops a bottom-up systematic model to assess the current and future impact of different battery technologies on vehicle costs. For this purpose, it summarises the scientific findings of automotive battery cell chemistries and, flanked by novel expert interviews and teardown data, derives key values for them. Based on the data obtained, modelling is carried out to demonstrate the technical and economic suitability of the identified cell chemistries and their impact on the range and total cost of electric vehicles. Lithium iron phosphate batteries appear to be able to achieve a price saving of up to 21% in the small vehicle segment compared to nickel-rich cell chemistries, provided that customers are prepared to accept a reduced range. At the same time, further efficiency improvements of the powertrain lead us to expect that, in combination with future high-energy cells, ranges of more than 800 km can be achieved even in the mid-size vehicle segment. It turns out that depending on whether the focus of the vehicle is on cost, range or performance, different battery technologies are likely to be used in the future.
A Real-Time Vehicle Speed Prediction Method Based on a Lightweight Informer Driven by Big Temporal Data
Authors: Tian Xinyu , Zheng Qinghe , Yu Zhiguo , Yang Mingqiang , Ding Yao , Elhanashi Abdussalam , Saponara Sergio , Kpalma Kidiyo
Published: July 2023

At present, the design of modern vehicles requires improving driving performance while meeting emission standards, leading to increasingly complex power systems. In autonomous driving systems, accurate, real-time vehicle speed prediction is one of the key factors in achieving automated driving. Accurate prediction and optimal control based on future vehicle speeds are key strategies for dealing with ever-changing and complex actual driving environments. However, predicting driver behavior is uncertain and may be influenced by the surrounding driving environment, such as weather and road conditions. To overcome these limitations, we propose a real-time vehicle speed prediction method based on a lightweight deep learning model driven by big temporal data. Firstly, the temporal data collected by automotive sensors are decomposed into a feature matrix through empirical mode decomposition (EMD). Then, an informer model based on the attention mechanism is designed to extract key information for learning and prediction. During the iterative training process of the informer, redundant parameters are removed through importance measurement criteria to achieve real-time inference. Finally, experimental results demonstrate that the proposed method achieves superior speed prediction performance through comparing it with state-of-the-art statistical modelling methods and deep learning models. Tests on edge computing devices also confirmed that the designed model can meet the requirements of actual tasks.
Securing Group Patient Communication in 6G-Aided Dynamic Ubiquitous Healthcare with Real-Time Mobile DNA Sequencing
Authors: Le Tuan-Vinh
Published: July 2023

(1) Background: With an advanced technique, third-generation sequencing (TGS) provides services with long deoxyribonucleic acid (DNA) reads and super short sequencing time. It enables onsite mobile DNA sequencing solutions for enabling ubiquitous healthcare (U-healthcare) services with modern mobile technology and smart entities in the internet of living things (IoLT). Due to some strict requirements, 6G technology can efficiently facilitate communications in a truly intelligent U-healthcare IoLT system. (2) Research problems: conventional single user–server architecture is not able to enable group conversations where “multiple patients–server” communication or “patient–patient” communication in the group is required. The communications are carried out via the open Internet, which is not a trusted channel. Since heath data and medical information are very sensitive, security and privacy concerns in the communication systems have become extremely important. (3) Purpose: the author aims to propose a dynamic group-based patient-authenticated key distribution protocol for 6G-aided U-healthcare services enabled by mobile DNA sequencing. In the protocol, an authenticated common session key is distributed by the server to the patients. Using the key, patients in a healthcare group are allowed to securely connect with the service provider or with each other for specific purposes of communication. (4) Results: the group key distribution process is protected by a secure three-factor authentication mechanism along with an efficient sequencing-device-based single sign-on (SD-SSO) solution. Based on traceable information stored in the server database, the proposed approach can provide patient-centered services which are available on multiple mobile devices. Security robustness of the proposed protocol is proven by well-known verification tools and a detailed semantic discussion. Performance evaluation shows that the protocol provides more functionality and incurs a reasonable overhead in comparison with the existing works.
Glucose Inhibits Yeast AMPK (Snf1) by Three Independent Mechanisms
Authors: Simpson-Lavy Kobi , Kupiec Martin
Published: July 2023

Snf1, the fungal homologue of mammalian AMP-dependent kinase (AMPK), is a key protein kinase coordinating the response of cells to a shortage of glucose. In fungi, the response is to activate respiratory gene expression and metabolism. The major regulation of Snf1 activity has been extensively investigated: In the absence of glucose, it becomes activated by phosphorylation of its threonine at position 210. This modification can be erased by phosphatases when glucose is restored. In the past decade, two additional independent mechanisms of Snf1 regulation have been elucidated. In response to glucose (or, surprisingly, also to DNA damage), Snf1 is SUMOylated by Mms21 at lysine 549. This inactivates Snf1 and leads to Snf1 degradation. More recently, glucose-induced proton export has been found to result in Snf1 inhibition via a polyhistidine tract (13 consecutive histidine residues) at the N-terminus of the Snf1 protein. Interestingly, the polyhistidine tract plays also a central role in the response to iron scarcity. This review will present some of the glucose-sensing mechanisms of S. cerevisiae, how they interact, and how their interplay results in Snf1 inhibition by three different, and independent, mechanisms.
Analyzing the Combined Effect of Multiple Environmental Factors on Fish Distribution, by Means of the Mixed Distribution–Decomposition Approach, as Illustrated by the East China Sea Hairtail
Authors: Liu Yong , Cheng Jia-Hua
Published: July 2023

An organism’s habits are formed primarily as a result of environmental circumstances. Analyzing an organism’s habits and examining their causes requires a thorough understanding of the peculiarities of an organism’s living environments. Analyzing the environmental factors necessary for an organism’s survival is a crucial component of studying how the environment and biology interact. The favorable temperature range for the species has been discovered in previous investigations of the hairtails’ main water temperature distribution range, covering both the water regions with and without the hairtails. It is implied that there may be other elements besides water temperature that also affect dispersion. The hairtail, though, is still the subject of the study. To investigate and confirm the corollaries, salinity and water depth were added as variables. We observed that the intersection of the main ranges of two environmental factors, as well as the main hairtail range of interest, were greatly reduced when compared to a single factor range; the sum of the three factors will further increase the reduction. The primary cause is that the main range of hairtail relative to each factor is incomplete, and the target bodies specified by various factors are very varied. To further investigate the factors that affect the distribution of the organism’s active areas, a comparison between aggregated and non-aggregated waters relative to one factor can be done in the next step. A good sequence of environmental elements, namely temperature>salinity>water depth, is obtained in the above analysis procedure by comparing the accuracy and significance of each factor for the primary range of the hairtail. Additionally, it was noted that the main population of the hairtail covered different areas depending on the season, with less coverage in spring and autumn and greater coverage in summer and winter. The main part of the hairtail population also tended to be distributed closer to the coast in summer and winter, and farther offshore in spring and autumn. These seasonal variations may be related to the two distinct reproductive cycles of hairtail, occuring in spring and autumn.
Predicting Drug–Gene–Disease Associations by Tensor Decomposition for Network-Based Computational Drug Repositioning
Authors: Kim Yoonbee , Cho Young-Rae
Published: July 2023

Drug repositioning offers the significant advantage of greatly reducing the cost and time of drug discovery by identifying new therapeutic indications for existing drugs. In particular, computational approaches using networks in drug repositioning have attracted attention for inferring potential associations between drugs and diseases efficiently based on the network connectivity. In this article, we proposed a network-based drug repositioning method to construct a drug–gene–disease tensor by integrating drug–disease, drug–gene, and disease–gene associations and predict drug–gene–disease triple associations through tensor decomposition. The proposed method, which ensembles generalized tensor decomposition (GTD) and multi-layer perceptron (MLP), models drug–gene–disease associations through GTD and learns the features of drugs, genes, and diseases through MLP, providing more flexibility and non-linearity than conventional tensor decomposition. We experimented with drug–gene–disease association prediction using two distinct networks created by chemical structures and ATC codes as drug features. Moreover, we leveraged drug, gene, and disease latent vectors obtained from the predicted triple associations to predict drug–disease, drug–gene, and disease–gene pairwise associations. Our experimental results revealed that the proposed ensemble method was superior for triple association prediction. The ensemble model achieved an AUC of 0.96 in predicting triple associations for new drugs, resulting in an approximately 7% improvement over the performance of existing models. It also showed competitive accuracy for pairwise association prediction compared with previous methods. This study demonstrated that incorporating genetic information leads to notable advancements in drug repositioning.
TGF-β Isoforms Affect the Planar and Subepithelial Fibrogenesis of Human Conjunctival Fibroblasts in Different Manners
Authors: Watanabe Megumi , Tsugeno Yuri , Sato Tatsuya , Umetsu Araya , Nishikiori Nami , Furuhashi Masato , Ohguro Hiroshi
Published: July 2023

Three highly homologous isoforms of TGF-β, TGF-β-1~3, are involved in the regulation of various pathophysiological conditions such as wound healing processes in different manners, despite the fact that they bind to the same receptors during their activation. The purpose of the current investigation was to elucidate the contributions of TGF-β-1 ~3 to the pathology associated with conjunctiva. For this purpose, the biological effects of these TGF-β isoforms on the structural and functional properties of two-dimensional (2D) and three-dimensional (3D) cultured human conjunctival fibroblasts (HconF) were subjected to the following analyses: 1) transendothelial electrical resistance (TEER), a Seahorse cellular metabolic measurement (2D), size and stiffness measurements of the 3D HTM spheroids, and the qPCR gene expression analyses of extracellular matrix (ECM) components (2D and 3D). The TGF-β isoforms caused different effects on the proliferation of the HconF cell monolayer evaluated by TEER measurements. The differences included a significant increase in the presence of 5 ng/mL TGF-β-1 and -2 and a substantial decrease in the presence of 5 ng/mL TGF-β-3, although there were no significant differences in the response to the TGF-β isoforms for cellular metabolism among the three groups. Similar to planar proliferation, the TGF-β isoforms also induced diverse effects toward the mechanical aspects of 3D HconF spheroids, where TGF-β-1 increased stiffness, TGF-β-2 caused no significant effects, and TGF-β-3 caused the downsizing of the spheroids and stiffness enhancement. The mRNA expression of the ECMs were also modulated in diverse manners by the TGF-β isoforms as well as the culture conditions for the 2D vs. 3D isoforms. Many of these TGF-β-3 inducible effects were markedly different from those caused by TGF-β1 and TGF-β-2. The findings presented herein suggest that the three TGF-β isoforms induce diverse and distinctly different effects on cellular properties and the expressions of ECM molecules in HconF and that these changes are independent of cellular metabolism, thereby inducing different effects on the epithelial and subepithelial proliferation of human conjunctiva.
Diagnosis of Monkeypox Disease Using Transfer Learning and Binary Advanced Dipper Throated Optimization Algorithm
Authors: Alharbi Amal H. , Towfek S. K. , Abdelhamid Abdelaziz A. , Ibrahim Abdelhameed , Eid Marwa M. , Khafaga Doaa Sami , Khodadadi Nima , Abualigah Laith , Saber Mohamed
Published: July 2023

The virus that causes monkeypox has been observed in Africa for several years, and it has been linked to the development of skin lesions. Public panic and anxiety have resulted from the deadly repercussions of virus infections following the COVID-19 pandemic. Rapid detection approaches are crucial since COVID-19 has reached a pandemic level. This study’s overarching goal is to use metaheuristic optimization to boost the performance of feature selection and classification methods to identify skin lesions as indicators of monkeypox in the event of a pandemic. Deep learning and transfer learning approaches are used to extract the necessary features. The GoogLeNet network is the deep learning framework used for feature extraction. In addition, a binary implementation of the dipper throated optimization (DTO) algorithm is used for feature selection. The decision tree classifier is then used to label the selected set of features. The decision tree classifier is optimized using the continuous version of the DTO algorithm to improve the classification accuracy. Various evaluation methods are used to compare and contrast the proposed approach and the other competing methods using the following metrics: accuracy, sensitivity, specificity, p-Value, N-Value, and F1-score. Through feature selection and a decision tree classifier, the following results are achieved using the proposed approach; F1-score of 0.92, sensitivity of 0.95, specificity of 0.61, p-Value of 0.89, and N-Value of 0.79. The overall accuracy of the proposed methodology after optimizing the parameters of the decision tree classifier is 94.35%. Furthermore, the analysis of variation (ANOVA) and Wilcoxon signed rank test have been applied to the results to investigate the statistical distinction between the proposed methodology and the alternatives. This comparison verified the uniqueness and importance of the proposed approach to Monkeypox case detection.
Specific Fluorescent Probes for Imaging DNA in Cell-Free Solution and in Mitochondria in Living Cells
Authors: Efimova Anna S. , Ustimova Mariya A. , Chmelyuk Nelly S. , Abakumov Maxim A. , Fedorov Yury V. , Fedorova Olga A.
Published: July 2023

New styryl dyes consisting of N-methylpyridine or N-methylquinoline scaffolds were synthesized, and their binding affinities for DNA in cell-free solution were studied. The replacement of heterocyclic residue from the pyridine to quinoline group as well as variation in the phenyl part strongly influenced their binding modes, binding affinities, and spectroscopic responses. Biological experiments showed the low toxicity of the obtained dyes and their applicability as selective dyes for mitochondria in living cells.
LSPR-Based Aptasensor for Rapid Urinary Detection of NT-proBNP
Authors: António Maria , Vitorino Rui , Daniel-da-Silva Ana L.
Published: July 2023

N-terminal pro-brain natriuretic peptide (NT-proBNP) is a myocardial stress biomarker that can be found in serum or plasma, saliva, and urine in the context of cardiovascular disease. In this study, we developed a rapid (~25 min) and straightforward localized surface plasmon resonance (LSPR)-based assay for detecting NT-proBNP in urine. The assay employs citrate-capped gold nanoparticles (AuNPs) and an aptamer specific for NT-proBNP, which initially interacts with NT-proBNP. The remaining unbound aptamer then interacts with the AuNPs, and the addition of NaCl induces the aggregation of the unprotected AuNPs, resulting in a decrease in absorbance at the LSPR band (A521) and an increase in absorbance at 750 nm (A750). The concentration of NT-proBNP showed a linear correlation with the aggregation ratio (A521/A750), and the assay demonstrated a limit of detection (LOD) of 0.303 µg·L−1 and a detection range of 0.566–8 µg·L−1. However, the presence of sulfur-containing proteins in saliva and fetal bovine serum hindered the detection of NT-proBNP in these biofluids. Nevertheless, the assay successfully detected NT-proBNP in diluted urine with an LOD of 0.417 µg·L−1 and a detection range of 0.589–6 µg·L−1. The observed values in urine samples from preterm infants with cardiovascular disease fell within this range, indicating the potential clinical relevance of the assay. The recovery percentages ranged from 92.3 to 116.3%. Overall, our findings suggest that the LSPR-based assay for NT-proBNP detection in urine can be a valuable tool for the diagnosis and treatment of cardiovascular disease.
Association between Empathy and Clinical Symptoms among Overweight and Non-Overweight Chinese Chronic Schizophrenia Patients
Authors: Li Yuchen , Luo Ruichenxi , Wang Dongmei , Zhang Xiangyang
Published: July 2023

Patients with schizophrenia are afflicted by severe clinical symptoms and serious cognitive dysfunction. The aim of this study is to investigate the potential relationships between clinical symptoms and empathy and their variations between overweight and non-overweight schizophrenia patients. To address this problem, a group of 776 inpatients diagnosed with chronic schizophrenia (504 overweight patients and 272 non-overweight patients) was recruited. The Positive and Negative Syndrome Scale (PANSS) and its five-factor model were employed to assess clinical symptoms, while empathy levels were measured using the Interpersonal Reactivity Index (IRI). The overweight patients had lower education levels but higher positive symptoms than the non-overweight patients (all p < 0.05). In addition, the overweight patients performed significantly better with respect to empathy (FDR-corrected p < 0.05). Additional multiple regression analyses indicated significant associations between the total score of the IRI and PANSS negative symptoms, gender, and family history of psychiatric disorders among the overweight group; among non-overweight patients, there was a significant correlation between suicide and the total score of the IRI. This study provides evidence suggesting that chronic schizophrenia patients who are overweight may have distinct clinical characteristics, particularly with respect to their empathy, compared with non-overweight patients. Moreover, different variables are associated with empathy in different groups.
Mitophagy: A Bridge Linking HMGB1 and Parkinson’s Disease Using Adult Zebrafish as a Model Organism
Authors: Razali Khairiah , Mohd Nasir Mohd Hamzah , Kumar Jaya , Mohamed Wael M. Y.
Published: July 2023

High-mobility group box 1 (HMGB1) has been implicated as a key player in two critical factors of Parkinson’s disease (PD): mitochondrial dysfunction and neuroinflammation. However, the specific role of HMGB1 in PD remains elusive. We investigated the effect of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) administration on mitochondrial dysfunction and HMGB1-associated inflammatory genes as well as locomotor activity in zebrafish, aiming to elucidate the role of HMGB1 in PD. Adult zebrafish received MPTP injections, and locomotor activity was measured at 24- and 48-h post-administration. Gene expression levels related to mitophagy (fis1, pink1, and park2) and HMGB1-mediated inflammation (hmgb1, tlr4, and nfkb) were quantified through RT-qPCR analysis. Following MPTP injection, the significant increase in transcript levels of fis1, pink1, and park2 indicated notable changes in PINK1/Parkin mitophagy, while the upregulation of hmgb1, tlr4, and nfkb genes pointed to the activation of the HMGB1/TLR4/NFκB inflammatory pathway. Furthermore, MPTP-injected zebrafish exhibited decreased locomotor activity, evident through reduced distance travelled, mean speed, and increased freezing durations. HMGB1 plays a major role in cellular processes as it is involved in both the mitophagy process and functions as a pro-inflammatory protein. MPTP administration in adult zebrafish activated mitophagy and inflammatory signaling, highlighting the significant role of HMGB1 as a mediator in both processes and further emphasizing its significant contribution to PD pathogenesis.
From Coaching to Neurocoaching: A Neuroscientific Approach during a Coaching Session to Assess the Relational Dynamics between Coach and Coachee—A Pilot Study
Authors: Valesi Riccardo , Gabrielli Giorgio , Zito Margherita , Bellati Mara , Bilucaglia Marco , Caponetto Alessia , Fici Alessandro , Galanto Annarita , Falcone Massimiliano Giuseppe , Russo Vincenzo
Published: July 2023

Life transitions represent moments characterized by changes that can profoundly influence individual life trajectories and subjective well-being. Recently, career coaching has become an important method of helping people expand their self-awareness, facilitate personal development, and increase their performance in the school-to-work transition. Although previous studies have confirmed that one of the most important keys to the success of a coaching program is the quality of the relationship between coach and coachee, there is a lack of knowledge regarding how to objectively measure it. In this pilot study, we adopted a neuroscientific approach to introduce objective measures of the relationship between coach and coachee through the phases of a coaching session. A sample of 14 university students and a professional coach participated in career-coaching sessions while their affective states were measured by recording brain (EEG) and physiological (Skin conductance) activity. Electroencephalographic indicators of valence, arousal, and engagement showed differences between session phases, highlighting the possibility of a neurophysiological measurement of relational dynamics. Our results provide initial evidence that neurophysiological activity can be considered a way to understand differences in the coach-coachee relationship, thereby providing information on the effectiveness of coaching interventions and facilitating a better life transition from school to work.
Ideal L2 Self, Self-Efficacy, and Pragmatic Production: The Mediating Role of Willingness to Communicate in Learning English as a Foreign Language
Authors: Yang He , Lian Zheyu
Published: July 2023

The role that individual difference factors play in pragmatic learning behavior has received increasing attention in second-language (L2) pragmatics. However, there is a dearth of studies exploring the relationship between learners’ motivational variables and their pragmatic production. To address this gap, the present study aims to examine a model of the ideal L2 self, self-efficacy, willingness to communicate (WTC), and pragmatic production among English-as-a-foreign-language (EFL) learners. The study also seeks to explore the mediating role of WTC within this structural model. For this purpose, a total of 427 undergraduate students at a public university in China were recruited for an online survey. The structural validity of the questionnaires was established using a confirmatory-factor analysis, while the hypothesized structural relations between the variables were tested through structural-equation modeling. The results demonstrated that self-efficacy and WTC significantly and directly predicated pragmatic production. Nevertheless, the ideal L2 self influenced pragmatic production indirectly, through the mediation of WTC. The study concludes by providing implications for teaching and by offering suggestions for future research.