bluuebunny/crossref_metadata_2025 huggingface dataset:
Antioxidant and Cytotoxic Activities of Leaf and Stem Extracts of Barleria albostellata C.B. Clarke
Authors: Gangaram Serisha , Naidoo Yougasphree , Dewir Yaser Hassan , Singh Moganavelli , Daniels Aliscia Nicole , Magyar-Tábori Katalin , Mendler-Drienyovszki Nóra
Published: November 2023

Barleria albostellata C.B. Clarke (Acanthaceae) is a plant native to South Africa and relatively few studies have been performed on it. Species in this genus are known for their ethnopharmacological and phyto-medicinal values. In this study, the total flavonoid and phenolic contents and the antioxidant and cytotoxic activities of hexane, chloroform, and methanol extracts were evaluated at five different concentrations (15, 30, 60, 120, and 240 μg/mL). The antioxidant activity of the extracts of B. albostellata was assessed in vitro using the 2,2′-diphenyl-1-picrylhydrazyl (DPPH) scavenging and ferric reducing antioxidant power (FRAP) assays, while the phenolic content was determined using a Folin–Ciocalteu assay. The extracts’ cytotoxicity was established using a 3-[(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide] (MTT) assay in human embryonic kidney (HEK293), cervical cancer (HeLa), and breast adenocarcinoma (MCF-7) cell lines. Methanolic leaf extracts had the highest total flavonoid content (42.39 ± 1.14 mg GAE/g DW) compared to other solvents. Additionally, the total phenolic content was the greatest in the methanol leaf extract (6.05 ± 0.09 GAE/g DW), followed by the methanol stem extracts (2.93 ± 0.73 GAE/g DW). The methanolic leaf and stem extract concentrations needed for 50% inhibition (DPPH) were 16.95 µg/mL and 14.27 µg/mL, respectively, whereas for FRAP, the reducing powers of all extracts were considerably lower than the ascorbic acid standard. The IC50 values of extracts tested in the three cell lines were >63 µg/mL. According to the findings of our study, the leaves and stems of B. albostellata are rich in several bioactive compounds that may be a possible source of natural antioxidants and may have the potential to treat certain diseases. The extraction of the bioactive compounds from the leaves and stems of B. albostellata using bioassay-guided fractionation and the assessment of their safety will be essential for further investigations into this species in the search of potential novel therapeutic drug leads. To the best of our knowledge, this is the first report of the cytotoxic activities of leaf and stem extracts of Barleria albostellata.
Context-Aware Personalization: A Systems Engineering Framework
Authors: Oguntola Olurotimi , Simske Steven
Published: November 2023

This study proposes a framework for a systems engineering-based approach to context-aware personalization, which is applied to e-commerce through the understanding and modeling of user behavior from their interactions with sales channels and media. The framework is practical and built on systems engineering principles. It combines three conceptual components to produce signals that provide content relevant to the users based on their behavior, thus enhancing their experience. These components are the ‘recognition and knowledge’ of the users and their behavior (persona); the awareness of users’ current contexts; and the comprehension of their situation and projection of their future status (intent prediction). The persona generator is implemented by leveraging an unsupervised machine learning algorithm to assign users into cohorts and learn cohort behavior while preserving their privacy in an ethical framework. The component of the users’ current context is fulfilled as a microservice that adopts novel e-commerce data interpretations. The best result of 97.3% accuracy for the intent prediction component was obtained by tokenizing categorical features with a pre-trained BERT (bidirectional encoder representations from transformers) model and passing these, as the contextual embedding input, to an LSTM (long short-term memory) neural network. Paired cohort-directed prescriptive action is generated from learned behavior as a recommended alternative to users’ shopping steps. The practical implementation of this e-commerce personalization framework is demonstrated in this study through the empirical evaluation of experimental results.
An Integrated Time Series Prediction Model Based on Empirical Mode Decomposition and Two Attention Mechanisms
Authors: Wang Xianchang , Dong Siyu , Zhang Rui
Published: November 2023

In the prediction of time series, Empirical Mode Decomposition (EMD) generates subsequences and separates short-term tendencies from long-term ones. However, a single prediction model, including attention mechanism, has varying effects on each subsequence. To accurately capture the regularities of subsequences using an attention mechanism, we propose an integrated model for time series prediction based on signal decomposition and two attention mechanisms. This model combines the results of three networks—LSTM, LSTM-self-attention, and LSTM-temporal attention—all trained using subsequences obtained from EMD. Additionally, since previous research on EMD has been limited to single series analysis, this paper includes multiple series by employing two data pre-processing methods: ‘overall normalization’ and ‘respective normalization’. Experimental results on various datasets demonstrate that compared to models without attention mechanisms, temporal attention improves the prediction accuracy of short- and medium-term decomposed series by 15~28% and 45~72%, respectively; furthermore, it reduces the overall prediction error by 10~17%. The integrated model with temporal attention achieves a reduction in error of approximately 0.3%, primarily when compared to models utilizing only general forms of attention mechanisms. Moreover, after normalizing multiple series separately, the predictive performance is equivalent to that achieved for individual series.
Data-Driven Condition Assessment and Life Cycle Analysis Methods for Dynamically and Fatigue-Loaded Railway Infrastructure Components
Authors: Granzner Maximilian , Strauss Alfred , Reiterer Michael , Cao Maosen , Novák Drahomír
Published: November 2023

Railway noise barrier constructions are subjected to high aerodynamic loads during the train passages, and the knowledge of their actual structural condition is relevant to assure safety for railway users and to create a basis for forecasting. This paper deals with deterministic and probabilistic approaches for the condition assessment and prediction of the remaining lifetime of railway noise barriers that are embedded in a safety concept that takes into account the damage consequence classes. These approaches are combined into a holistic assessment concept, in other words, a progressive four-stage model in which the information content increases with each model stage and thus successively increases the accuracy of the determined structural conditions at the time of observation and the forecast of the remaining service life of the structure. The analytical methods used in the first stage of the developed holistic framework are based on common static calculations used in engineering practice and, together with expert knowledge and large-scale fatigue test results of noise barrier constructions, form the basis for the subsequent stages. In the second stage of the data-driven condition assessment and life cycle analysis approach, linking routines are implemented that combine the condition assessments from the visual inspections with the additional information from temporary or permanent monitoring systems with the analytical methods. With the application of numerical finite element methods for the development of a digital twin of the noise barrier in the third stage and the probabilistic approaches in the fourth stage, a maximum determination accuracy of the noise barrier condition at the time of observation and prediction accuracy of the remaining service life is achieved. The data-driven condition assessment and life cycle analysis approach enables infrastructure operators to plan their future investments more economically regarding the maintenance, retrofitting, or new construction of railway noise barriers. Ultimately, the aim is to integrate the presented four-stage holistic assessment concept into the specific maintenance and repair planning of infrastructure operators for aerodynamically loaded railway noise barrier constructions.
Assessment of Office-Based Probing with Dacryoendoscopy for Treatment of Congenital Nasolacrimal Duct Obstruction: A Retrospective Study
Authors: Ueta Yoshiki , Watanabe Yuji , Kamada Ryoma , Tanaka Nobuya
Published: November 2023

We aimed to evaluate the safety and efficacy of office-based probing with dacryoendoscopy under local anesthesia for congenital nasolacrimal duct obstruction (CNLDO). This single-institution study retrospectively reviewed data on 72 eyes of 64 consecutive children (38 boys, 43 eyes; 26 girls, 29 eyes), aged between 6 and 17 (mean age: 10.0 ± 2.7) months with suspected CNLDO, from July 2016 to February 2022. These patients underwent probing with dacryoendoscopy under local anesthesia. CNLDO was diagnosed clinically based on the presence of epiphora and sticky eyes due to mucous discharge commencing within the first 3 months of life, increased tear meniscus height, and fluorescein dye disappearance test results. A total of 63 of the 72 eyes had narrowly defined CNLDO, and 9 eyes had other types of obstructions. The intervention success rate was 100% (63/63 eyes) for patients with typical CNLDO and 97.2% (70/72 eyes) for the entire study cohort. Moreover, CNLDO was classified into five types based on the features of the distal end of the nasolacrimal duct. Probing with dacryoendoscopy is safe and yields a high success rate in pediatric patients with CNLDO. This is the first study to assess the safety and efficacy of probing with dacryoendoscopy under local anesthesia in pediatric patients with CNLDO.
Electrochemical Detection of Heavy Metal Ions Based on Nanocomposite Materials
Authors: Shirsat Mahendra D. , Hianik Tibor
Published: November 2023

Heavy metal ions (HMIs) have acute toxic effects on health and are dangerous for human existence and the ecosystem. Therefore, their sensitive and selective detection is of great importance. In recent years, various nanocomposite materials have been used by researchers for the detection of HMIs by using various modalities of electrochemical techniques. This review summarizes the recent advances in developing electrochemical sensors based on numerous nanocomposite materials for detecting HMIs. Nanocomposite materials, such as metal–organic frameworks (MOFs), organic conducting polymer (OCPs), carbon nanotubes (CNTs), graphene oxide (GO), graphene/reduced graphene oxide (rGO), graphitic carbon nitride, metal oxide, chitosan, MXenes, metal nanoparticle-based nanocomposites, etc., have been explored by various researchers to improve the sensing properties of electrochemical sensors. This review emphasizes nanocomposite materials’ synthesis and characterization techniques, modalities for HMI detection using electrochemical techniques, and electrochemical sensors. Moreover, this review highlights the development of portable biosensors for detecting HMIs in real-world scenarios, such as environmental monitoring, food safety, and clinical diagnosis. This review also demonstrates the importance of electrochemical sensors based on nanocomposite materials as a reliable, sensitive, and selective tool for detecting HMIs.
Breast Cancer Detection with an Ensemble of Deep Learning Networks Using a Consensus-Adaptive Weighting Method
Authors: Dehghan Rouzi Mohammad , Moshiri Behzad , Khoshnevisan Mohammad , Akhaee Mohammad Ali , Jaryani Farhang , Salehi Nasab Samaneh , Lee Myeounggon
Published: November 2023

Breast cancer’s high mortality rate is often linked to late diagnosis, with mammograms as key but sometimes limited tools in early detection. To enhance diagnostic accuracy and speed, this study introduces a novel computer-aided detection (CAD) ensemble system. This system incorporates advanced deep learning networks—EfficientNet, Xception, MobileNetV2, InceptionV3, and Resnet50—integrated via our innovative consensus-adaptive weighting (CAW) method. This method permits the dynamic adjustment of multiple deep networks, bolstering the system’s detection capabilities. Our approach also addresses a major challenge in pixel-level data annotation of faster R-CNNs, highlighted in a prominent previous study. Evaluations on various datasets, including the cropped DDSM (Digital Database for Screening Mammography), DDSM, and INbreast, demonstrated the system’s superior performance. In particular, our CAD system showed marked improvement on the cropped DDSM dataset, enhancing detection rates by approximately 1.59% and achieving an accuracy of 95.48%. This innovative system represents a significant advancement in early breast cancer detection, offering the potential for more precise and timely diagnosis, ultimately fostering improved patient outcomes.
Are We Underestimating the Risk of Coastal Flooding in Europe? The Relevance of Critical Infrastructure
Authors: Barrios-Crespo Esther , Torres-Ortega Saúl , Díaz-Simal Pedro
Published: November 2023

The effects of climate change imply an increase in the risk levels due to coastal flooding. These areas present a high concentration of population and economic activity. The failure of critical infrastructures (CI) serving these communities can have significant impacts on these sectors. This study aims to analyze the risk and its future evolution due to climate change in coastal areas, considering the increased impact that the population would experience if the CI (of the energy or water and waste treatment sectors) were affected by coastal flooding. The methodology used has made it possible to analyze the risk of the Functional Urban Areas (FUA) of the European coasts, identifying the areas in which the level of risk to the population is significantly underestimated. In some of these areas and scenarios, the population affected by coastal flooding if the failure of the CI occurs would be up to 4.5 times higher than what is estimated if only their direct impact is considered.
Impacts of Arctic Sea Fog on the Change of Route Planning and Navigational Efficiency in the Northeast Passage during the First Two Decades of the 21st Century
Authors: Wang Kun , Zhang Yu , Chen Changsheng , Song Shutong , Chen Yue
Published: November 2023

Under the background of climate change, the Northeast Passage’s navigability is on the rise. Arctic sea fog significantly influences navigational efficiency in this region. Existing research primarily focuses on routes accumulating the lowest distance, neglecting routes with the lowest time and sea fog’s influence on route planning and navigational efficiency. This study compares the fastest and shortest routes and analyzes Arctic sea fog’s impact on the Northeast Passage from June to September (2001–2020). The results show that coastal areas are covered with less sea ice under notable monthly variations. Sea fog frequency is highest near coasts, declining with latitude. September offers optimal navigation conditions due to minimal ice and fog. When only sea ice is considered, the fastest route is approximately 4 days quicker than the shortest. The shortest route has migrated towards the higher latitude over two decades, while the fastest route remains closer to the Russian coast. Adding the impact of sea fog on the fastest route, the speed decreased by 30.2%, increasing sailing time to 45.1%. The new fastest route considering both sea ice and sea fog achieved a 13.9% increase in sailing speed and an 11.5% reduction in sailing time compared to the original fastest route.
Morphological Response of a Highly Engineered Estuary to Altering Channel Depth and Restoring Wetlands
Authors: Siemes Rutger W. A. , Duong Trang Minh , Willemsen Pim W. J. M. , Borsje Bas W. , Hulscher Suzanne J. M. H.
Published: November 2023

Estuaries are continuously adapting to anthropogenic pressure. Because of sea-level rise and reduced fluvial sediment supply, they are at risk of sediment starvation. Contrarily, some estuaries require frequent dredging after artificially deepening the channel to maintain port operations. To optimize current estuarine functions and make estuaries more resilient to future threats, improved understanding of estuarine development after system changes is essential. This paper investigates the estuarine response related to two large-scale human interventions: (1) altering channel depth, following global trends of channel deepening for port navigability; and (2) creating or restoring wetlands, a nature-based solution increasingly explored for its ecosystem services. A schematized 2D-morphological model is set up using Delft3D-FM reflecting a highly engineered estuary in a micro-tidal and wave-dominant environment. Results demonstrate how channel deepening (from 13 m to 17 m, without wetland presence) increased sedimentation in the channel by +31%. Sedimentation rates in the wetland were mostly unaffected by channel depth. After restoring the wetland area (wetland width from 0 km to 1 km, constant channel depth of 15 m), sedimentation within the channel was reduced by −72%. The wetland area not only served as sediment sink, but also increased the tidal flow, diminishing sedimentation throughout the estuarine channel. Further analysis showed that restoring wetland areas along a specific segment mostly affected channel sedimentation locally (i.e., at the channel segment along the restored wetland). As such, to alleviate dredging operations at critical locations in the navigation channel, strategic restoration of wetlands can be considered which can provide a sustainable alternative to dredging within highly engineered estuaries.
A Probabilistic Methodology for Determining Collision Risk of Marine Animals with Tidal Energy Turbines
Authors: Copping Andrea E. , Hasselman Daniel J. , Bangley Charles W. , Culina Joel , Carcas Max
Published: November 2023

Commercial development of tidal stream energy is hampered by technical and financial challenges, and impeded by uncertainty about potential environmental effects that drive environmental risk assessments and permitting (consenting) processes. The effect of greatest concern for operational tidal stream energy devices is the potential for marine animals to collide with turbine blades, resulting in injury or death. Due to the turbulent and often turbid waters that frequently characterize tidal turbine sites, there is an absence of empirical evidence about collisions with marine animals. This paucity of observations often leads to risk-averse permitting decisions that further restrict the deployment of tidal energy devices that are needed to collect this evidence. This paper relies on the framework of stressors and receptors that is widely used in marine energy studies and outlines a stepwise probabilistic methodology that applies existing knowledge to further elucidate the risk to marine animals from operational tidal turbines. A case study using striped bass from the Bay of Fundy, Canada, accompanies the methodology, to partially demonstrate its application.
Detection of Small Objects in Side-Scan Sonar Images Using an Enhanced YOLOv7-Based Approach
Authors: Zhang Feihu , Zhang Wei , Cheng Chensheng , Hou Xujia , Cao Chun
Published: November 2023

Deep learning-based object detection methods have demonstrated remarkable effectiveness across various domains. Recently, there has been growing interest in applying these techniques to underwater environments. Conventional optical imaging methods face severe limitations when operating in underwater conditions, restricting their ability to identify objects with good visibility and at close distances. Consequently, side-scan sonar (SSS) has emerged as a common equipment choice for underwater detection due to its compatibility with the characteristics of sound waves in water. This paper introduces a novel method, termed the Enhanced YOLOv7-Based Approach, for detecting small objects in SSS images. Building upon the widely-adopted YOLOv7 method, the proposed approach incorporates several enhancements aimed at improving detection accuracy. First, a dedicated detection layer tailored for small objects is added to the original network architecture. Additionally, two attention mechanisms are integrated within the backbone and neck components of the network, respectively, to strengthen the network’s focus on object features. Finally, the network features are recombined based on the BiFPN structure. Experimental results demonstrate that the proposed method outperforms mainstream object detection algorithms. In comparison to the original YOLOv7 network, it achieves a Precision of 95.5%, indicating a significant improvement of 4.8%. Moreover, its Recall reaches 87.0%, representing an enhancement of 5.1%, while the mean Average Precision (mAP) at an IoU threshold of 0.5 (mAP@.5) reaches 86.9%, reflecting a 6.7% improvement. Furthermore, the mAP@.5:.95 reaches 55.1%, a 4.8% enhancement. Therefore, the method presented in this paper enhances the performance of YOLOv7 for object detection in SSS images, providing a fresh perspective on small object detection based on SSS images and contributing to the advancement of underwater detection techniques.
A Deep Learning-Based Lightweight Model for the Detection of Marine Fishes
Authors: Wu Fei , Zhang Yitao , Wang Lang , Hu Qiu , Fan Shengli , Cai Weiming
Published: November 2023

The species and population size of marine fish are important for maintaining the ecological environment and reflecting climate change. Traditional fish detection methods mainly rely on manual or traditional computer vision, which has disadvantages such as complex design, low detection accuracy, and poor generalization. The widespread use of ocean observation systems has accumulated a large number of images and videos, which makes the application of deep learning on marine fish detection possible. In this paper, a real-time high-precision fish detection algorithm based on YOLOv5s is constructed. Considering the enhancement of the channel representation and spatial interaction ability of the model, the attention mechanism and gated convolution are introduced, respectively, and GhostNet is introduced to lighten the model. Through a series of model comparisons, two improved models, S-Head-Ghost-Fish9 and S-SE-HorBlock-Head-Ghost-Fish9, are finally obtained. Compared with the original model, in terms of model size, the former reduces by 19% and the latter increases by 9.5%; in terms of computation, the former reduces by 15.7% and the latter reduces by 3.1%; in terms of detection speed, both take about 17 ms to detect a single image, and both can meet the real-time detection requirements; in terms of detection accuracy, the former improves by 3% and the latter by 3.6%. Compared with the latest detection algorithms of YOLOv6 and YOLOv8, the detection accuracy is slightly lower than 1%, but the model size and computation amount are only 1/3 to 1/2 of them. The improved models can help assess the population size and growth of the fish, which is of great significance in maintaining the stability of the fish population.
Wave Energy Assessment for the Atlantic Coast of Morocco
Authors: Schneider Magnus , Bernardino Mariana , Gonçalves Marta , Guedes Soares C.
Published: November 2023

This study estimates wave energy for the Moroccan Atlantic coast using SWAN, a third-generation wave model, covering a period of 30 years, from 1991 to 2020. The model is forced by the wind from the ERA-5 reanalysis dataset and uses boundary conditions generated by the WAVEWATCH III model. The significant wave height and period are used to obtain wave energy, which is analyzed at a regional scale. The mean wave energy density within the domain is assessed to be about 20 kW/m. Five specific locations are evaluated along the coast in order to determine the most energetic ones. The most energetic area of the Moroccan Atlantic coast is located at the center, between the cities of Agadir and Essaouira. Finally, the performance of six different wave energy converters is assessed through their power matrix for each of the five locations.
A Preliminary Snapshot Investigation of the Marine Soundscape for Malta: A Steppingstone towards Achieving ‘Good Ecological Status’
Authors: Filletti Julia Micallef , Gauci Adam , Deidun Alan , Riccobene Giorgio , Viola Salvatore
Published: November 2023

The ever-accelerating rate of research focusing on the issue of underwater noise pollution, particularly concerning low-frequency, continuous noise, has steadily been unveiling the myriad of detrimental ecological implications caused to marine life. Despite this, many European Member States, such as Malta, still lack solid monitoring and regulatory frameworks aimed at characterising and improving the state of the marine acoustic environment and achieving ‘Good Ecological Status’ in accordance with the Marine Strategy Framework Directive. This shortcoming is directly reflected in the complete absence of baseline information covering the quality of the national soundscape. This paper aims to serve as a preliminary investigation into continuous underwater noise generation within Maltese waters, focusing on two sites characterised by heavy marine activity: Ċirkewwa and the Grand Harbour. Digital signal processing software packages (dBWav version 1.3.4) were used to extract and analyse sound pressure levels from in situ recorded audio files. Further statistical analysis was also carried out so as to evaluate the resultant snapshot of the baseline marine soundscapes at both sites. Furthermore, AIS data were used to tentatively identify the identifiable sources of underwater noise pollution. Given the current information lacuna revolving around the issue of underwater noise pollution in Malta, this paper may serve as a pilot study, with the aim of bridging this knowledge gap and forming the basis of future national research for Maltese marine conservation.
Proteomics of Paracoccidioides lutzii: Overview of Changes Triggered by Nitrogen Catabolite Repression
Authors: Cruz-Leite Vanessa Rafaela Milhomem , Moreira André Luís Elias , Silva Lana O’Hara Souza , Inácio Moises Morais , Parente-Rocha Juliana Alves , Ruiz Orville Hernandez , Weber Simone Schneider , Soares Célia Maria de Almeida , Borges Clayton Luiz
Published: November 2023

Members of the Paracoccidioides complex are the causative agents of Paracoccidioidomycosis (PCM), a human systemic mycosis endemic in Latin America. Upon initial contact with the host, the pathogen needs to uptake micronutrients. Nitrogen is an essential source for biosynthetic pathways. Adaptation to nutritional stress is a key feature of fungi in host tissues. Fungi utilize nitrogen sources through Nitrogen Catabolite Repression (NCR). NCR ensures the scavenging, uptake and catabolism of alternative nitrogen sources, when preferential ones, such as glutamine or ammonium, are unavailable. The NanoUPLC-MSE proteomic approach was used to investigate the NCR response of Paracoccidioides lutzii after growth on proline or glutamine as a nitrogen source. A total of 338 differentially expressed proteins were identified. P. lutzii demonstrated that gluconeogenesis, β-oxidation, glyoxylate cycle, adhesin-like proteins, stress response and cell wall remodeling were triggered in NCR-proline conditions. In addition, within macrophages, yeast cells trained under NCR-proline conditions showed an increased ability to survive. In general, this study allows a comprehensive understanding of the NCR response employed by the fungus to overcome nutritional starvation, which in the human host is represented by nutritional immunity. In turn, the pathogen requires rapid adaptation to the changing microenvironment induced by macrophages to achieve successful infection.
Individualization in Online Markets: A Generalized Model of Price Discrimination through Learning
Authors: Ahmed Rasha
Published: November 2023

This paper builds a theoretical framework to model individualization in online markets. In a market with consumers of varying levels of demand, a seller offers multiple product bundles and prices. Relative to brick-and-mortar stores, an online seller can use pricing algorithms that can observe a buyer’s online behavior and infer a buyer’s type. I build a generalized model of price discrimination with Bayesian learning where a seller offers different bundles of the product that are sized and priced contingent on the posterior probability that the consumer is of a given type. Bayesian learning allows the seller to individualize product menus over time as new information becomes available. I explain how this strategy differs from first- or second-degree price discrimination models and how Bayesian learning over time affects equilibrium values and welfare.
Current State and Future of International Logistics Networks—The Role of Digitalization and Sustainability in a Globalized World
Authors: Nitsche Benjamin , Straube Frank
Published: November 2023

The management of international logistics networks poses major challenges for companies [...]
Application of Multiple Deep Neural Networks to Multi-Solution Synthesis of Linkage Mechanisms
Authors: Chen Chiu-Hung
Published: November 2023

This paper studies the problem of linkage-bar synthesis by means of multiple deep neural networks (DNNs), which requires the inverse solution of linkage parameters based on a desired trajectory curve. This problem is highly complex due to the fact that the solution space is nonlinear and may contain multiple solutions, while a good quality of learning cannot be obtained by a single neural network approach. Therefore, this paper proposes employing Fourier descriptors to represent trajectory curves in a systematic and normalized form, developing a multi-solution distribution evaluation by random restart local searches (MDE-RRLS) to examine a better solution-space partitioning scheme, utilizing multiple DNNs to learn subspace regions separately, and creating a multi-facet query (MFQuery) to cooperatively predict multiple solutions. The experiments demonstrate that the proposed approach can obtain better or at least competitive outcomes compared to previous work in the literature. Furthermore, to verify the effectiveness and applicability, this paper investigates the design problem of an industrial six-linkage-bar ladle mechanism used in a die-casting system, and the proposed method can obtain several superior design solutions and offer alternatives in a short period of time when faced with redesign requirements.
On Topp-Leone-G Power Series: Saturation in the Hausdorff Sense and Applications
Authors: Vasileva Maria T.
Published: November 2023

This paper discusses the Topp-Leone-G power series class of distributions. The greatest attention is paid to the investigation of intrinsic characteristic “saturation” to the horizontal asymptote in the Hausdorff sense. Some estimates for the value of the Hausdorff distance are obtained. We present a new family of recurrence generated adaptive functions with corresponding applications. The usefulness of the obtained results is demonstrated in a simulation study of some real data sets from the medical sector and insurance. Some suitable software modules within the programming environment CAS MATHEMATICA are proposed.
The Role of Immune Cells in the Pathogenesis of Idiopathic Pulmonary Fibrosis
Authors: Xu Yahan , Lan Peixiang , Wang Tao
Published: November 2023

Idiopathic pulmonary fibrosis (IPF) is a devastating disease of unknown etiology with limited treatment options. The role of the immune system in IPF has received increasing attention. Uncontrolled immune responses drive the onset and progression of IPF. This article provides an overview of the role of innate immune cells (including macrophages, neutrophils, mast cells, eosinophils, dendritic cells, nature killer cells, nature kill cells and γδ T cells) and adaptive immune cells (including Th1 cells, Th2 cells, Th9 cells, Th17 cells, Th22 cells, cytotoxic T cells, B lymphocytes and Treg cells) in IPF. In addition, we review the current status of pharmacological treatments for IPF and new developments in immunotherapy. A deeper comprehension of the immune system’s function in IPF may contribute to the development of targeted immunomodulatory therapies that can alter the course of the disease.
Research on the Performance of Self-Made Open-Cathode Fuel Cell Stacks under Different Operating Conditions
Authors: Bai Qiang , Liu Zhenghong , Hsieh Chuangyu
Published: November 2023

The traditional fuel cell power system requires external ventilation and humidification systems for both the anode and cathode, which not only increases the application cost but also restrict its widespread use. In order to further enhance the applicability and reduce the operating costs of fuel cell power systems, this paper investigates the open-cathode proton exchange membrane fuel cell power system. This approach not only lowers the cost but also reduces the weight of the power system, enabling its potential application in a wider range of vehicles. In this study, two versions of the open-cathode fuel cell stacks were developed and performance and stability tests were conducted under various operating conditions. Additionally, tests were carried out with different materials of carbon paper to find a balance between performance and stability. Through the research presented in this paper, the application scope of fuel cells has been expanded, providing valuable insights for their further development.
Facile Route to Achieve a Hierarchical CuO/Nickel-Cobalt-Sulfide Electrode for Energy Storage
Authors: Lv Sa , Cheng Zhifei , Chi Yaodan , Wang Huan , Chu Xuefeng , Zhao Yang , Wu Boqi , Wang Runsheng , Zhang Zhiwen , Wang Chao , Yang Jia , Yang Xiaotian
Published: November 2023

Herein, a novel self-supporting CuO/nickel-cobalt-sulfide (NCS) electrode was designed in a two-step electrodeposition technique followed by a calcination process. Three-dimensional copper foam (CF) was exploited as the current collector and spontaneous source for the in situ preparation of the CuO nanostructures, which ensured sufficient deposition space for the subsequent NCS layer, thus forming abundant electrochemical active sites. Such a hierarchical structure is conducive to providing a smooth path for promoting electronic transmission. Therefore, the optimized CuO/NCS electrode exhibits outstanding energy storage capability with extremely superior specific capacitance (Cs) of 7.08 F cm−2 at 4 mA cm−2 and coulombic efficiency of up to 94.83%, as well as excellent cycling stability with capacitance retention of 83.33% after 5000 cycles. The results presented in this work extend our horizons to fabricate novel hierarchical structured electrodes applied to energy storage devices.
Comparative Study of Intestinal Microbiome in Patients with Ulcerative Colitis and Healthy Controls in Korea
Authors: Do Kyung-Hyo , Ko Seung-Hyun , Kim Ki Bae , Seo Kwangwon , Lee Wan-Kyu
Published: November 2023

Ulcerative colitis (UC) poses a contemporary medical challenge, with its exact cause still eluding researchers. This is due to various factors, such as the rising incidence, diagnostic complexities, and difficulties associated with its management. We compared the intestinal microbiome of patients with UC to that of healthy controls to determine the qualitative and quantitative changes associated with UC that occur in the intestinal microbiota. The intestinal bacterial abundance in 40 Korean patients with UC and 25 healthy controls was assayed using via next-generation sequencing. There were five major phyla in both groups: Firmicutes (UC patients: 51.12%; healthy controls: 46.90%), Bacteroidota (UC patients: 37.04%; healthy controls: 40.34%), Proteobacteria (UC patients: 6.01%; healthy controls: 11.05%), Actinobacteriota (UC patients: 5.71%; healthy controls: 1.56%), and Desulfobacteriota (UC patients: 0.13%; healthy controls: 0.14%). Firmicutes was more prevalent in patients with UC (51.12%) compared to that of healthy controls (46.90%). Otherwise, Bacteroidota was more prevalent in healthy controls (40.34%) compared to patients with UC (37.04%). Although there was no significant difference, our results showed a substantially lower gut microbiome diversity in patients with UC (mean: 16.5; 95% confidence interval (CI) = 14.956–18.044) than in healthy controls (mean: 17.84; 95% CI = 15.989–19.691), the beta diversity and the flora structure of the microbiome in patients with UC differed from those in healthy controls. This will be helpful for the development of new treatment options and lay the groundwork for future research on UC. To understand the disease mechanism, it is essential to define the different types of microbes in the guts of patients with UC.
Transcriptome and Secretome Analyses of Endophyte Methylobacterium mesophilicum and Pathogen Xylella fastidiosa Interacting Show Nutrient Competition
Authors: Dourado Manuella Nobrega , Pierry Paulo Marques , Feitosa-Junior Oseias Rodrigues , Uceda-Campos Guillermo , Barbosa Deibs , Zaini Paulo A. , Dandekar Abhaya M. , da Silva Aline Maria , Araújo Welington Luiz
Published: November 2023

Xylella fastidiosa is the causal agent of several plant diseases affecting fruit and nut crops. Methylobacterium mesophilicum strain SR1.6/6 was isolated from Citrus sinensis and shown to promote plant growth by producing phytohormones, providing nutrients, inhibiting X. fastidiosa, and preventing Citrus Variegated Chlorosis. However, the molecular mechanisms involved in the interaction among these microbes are still unclear. The present work aimed to analyze physiological and molecular aspects of M. mesophilicum SR1.6/6 and X. fastidiosa 9a5c in co-culture. The transcriptome and secretome analyses indicated that X. fastidiosa down-regulates cell division and transport genes and up-regulates stress via induction of chaperones and pathogenicity-related genes including, the lipase-esterase LesA, a protease, as well as an oligopeptidase in response to M. mesophilicum competition. On the other hand, M. mesophilicum also down-regulated transport genes, except for iron uptake, which was up-regulated. Secretome analysis identified four proteins in M. mesophilicum exclusively produced in co-culture with X. fastidiosa, among these, three are related to phosphorous uptake. These results suggest that M. mesophilicum inhibits X. fastidiosa growth mainly due to nutrient competition for iron and phosphorous, thus promoting X. fastidiosa starvation, besides producing enzymes that degrade X. fastidiosa cell wall, mainly hydrolases. The understanding of these interactions provides a direction for control and management of the phytopathogen X. fastidiosa, and consequently, helps to improve citrus growth and productivity.
Natural Pyrite as a Catalyst for a Fenton Reaction to Enhance Xanthate Degradation in Flotation Tailings Wastewater
Authors: Gong Xiang , Li Suqi , Yuan Jiaqiao , Ding Zhan , Yu Anmei , Wen Shuming , Bai Shaojun
Published: November 2023

The efficient treatment of mineral-processing wastewater has attracted soaring interest recently. This study’s objective was to degrade xanthate from flotation tailings wastewater using a pyrite-catalyzed Fenton system. A sodium butyl xanthate (SBX) removal rate of more than 96% was achieved via the method under optimal conditions (a H2O2 concentration of 0.5 mM, a FeS2 concentration of 0.5 g/L, an initial SBX concentration of 100 mg/L, and a natural pH of 9.36 ± 0.5), which is 12.85% higher than with a H2O2 system. An appropriate concentration of natural pyrite can act as a catalyst to significantly improve the oxidation capacity of H2O2. Additionally, the results of electron paramagnetic resonance and quenching measurements suggest that hydroxyl radicals (•OH) are the main active species in the H2O2-FeS2 system. The possible reaction mechanism is proposed. The H2O2 adsorbs onto the pyrite surfaces and reacts with Fe2+, triggering the formation of •OH and Fe3+. The •OH most likely attacks the SBX that adsorbs on the pyrite surface or exists in the solution and promotes the transformation of the SBX anion (C4H9OCS2−) into the intermediate butyl xanthate peroxide (BPX, C4H9OCS2O−). Finally, BPX intermediates are likely further oxidized to smaller products such as SO42−, CO2, and H2O under the ongoing attack of •OH.
Predictive Mapping of Prospectivity for Gold in the Central Portion of the Tapajós Mineral Province, Brazil
Authors: Souza Gaia Sulsiene Machado de , Souza Filho Carlos Roberto de
Published: November 2023

This work aims to model mineral prospectivity for intrusion–related gold deposits in the central portion of the Tapajós Mineral Province (TMP), southwestern Pará state. The scope includes experimentation and evaluation of knowledge and data-driven methods applied to multisource data to predict potential targets for gold mineralization. The radiometric data processing allowed to identify a hydrothermal alteration footprint of known gold deposits, providing information in regions with little or no field data available. The aeromagnetic data analysis prompted the identification of high magnetic zones, which are probably related to hydrothermal fluid transport. Linear features extracted from digital elevation data revealed an NNW–SSE general trend, which is consistent with the main structural control of deposits. The data were integrated through three modeling techniques—fuzzy logic (knowledge-driven), weights of evidence (WofE, data-driven), and a machine learning algorithm (SVM, data-driven)—resulting in three prospective models. In all models, the majority of indicated prospective regions coincide with the known deposits. The results obtained in the models were combined to generate an agreement map, which mapped the overlapping of their highest prospective scores, indicating new areas of prospective interest in the central portion of the TMP.
Experimental Investigation into the Proportion of Cemented Aeolian Sand-Coal Gangue-Fly Ash Backfill on Mechanical and Rheological Properties
Authors: Zheng Zhijun , Yang Baogui , Gu Chengjin , Yang Faguang , Liu Hao
Published: November 2023

Aiming at the problems of large water secretion, poor suspensibility and low strength of cemented aeolian sand (AS)-fly ash (FA) backfill (CAFB) mixtures, CAFB was doped with fine coal gangue (CG) particles crushed to less than 4 mm and configured as cemented aeolian sand-coal gangue-fly ash backfill (CACFB) mixtures, in which coal gangue accounted for 8% of the mass ratio of the slurry. Through UCS and rheological experiments, using the response surface methodology and an orthogonal design, the following conclusions were drawn: (1) With the increase in ordinary Portland cement (PO) and slurry concentration, the UCS of the CACFB increased. (2) With the increase in the FA dosage, the UCS of the CACFB decreased first and then increased due to the gradual increase in FA dosage, destroying the reasonable ratio of the material and leading to the reduction in the material’s UCS, and with the growth in time, the volcanic ash effect of the FA caused the UCS of the material to increase. (3) With the increases in slurry concentration, the yield stress and viscosity coefficient of the slurry increased. (4) Reasonable proportions for CACFB should ensure the strength characteristics and rheological properties of the material. Through theoretical and experimental research, the final reasonable proportions were as follows: the concentrations of slurry, AS, CG, FA and PO were 77.5%, 42%, 8%, 17.5% and 10%, respectively. This ensured that the UCSs of the CACFB at 3 d, 7 d and 28 d were 1.2 MPa, 2.5 MPa and 4.3 MPa, respectively; the yield stress of the CACFB was 495 Pa, and the viscosity coefficient was 3.97 Pa·s. These reasonable proportions of the CACFB can meet the strength index and flow property of material industrial experiments.
Short-Term Effects of Weight-Loss Meal Replacement Programs with Various Macronutrient Distributions on Gut Microbiome and Metabolic Parameters: A Pilot Study
Authors: Song Seungmin , Shon Jinyoung , Yang Woo-ri , Kang Han-Bit , Kim Keun-Ha , Park Ju-Yeon , Lee Sanghoo , Baik Sae Yun , Lee Kyoung-Ryul , Park Yoon Jung
Published: November 2023

It has emerged the gut microbiome is crucially linked to metabolic health and obesity. Macronutrient distribution has been discussed as a key parameter in weight-loss programs, but little is known about its impact on the gut microbiome. We investigated the effects of weight-loss meal replacement programs with different macronutrient ratios on the gut microbiota and metabolic parameters in subjects with overweight and obesity. Three low-calorie meal replacement programs with different ratios of carbohydrates, proteins, and lipids were designed: a balanced diet (Group B, 60:15:30), a high-lipid−low-carbohydrate diet (Group F, 35:20:55), and a protein-enriched diet (Group P, 40:25:35). Sixty overweight or obese participants were provided with the meals twice daily for 3 weeks. In all groups, diet intervention resulted in reduced body weight and BMI. The relative abundance of Bacteroidetes and Firmicutes phyla decreased and increased, respectively, which increased the Firmicutes/Bacteroidetes (F/B) ratio in all subjects, particularly in Groups B and P. Alpha- and beta-diversity were augmented at the phylum level in Group P. In conclusion, short-term interventions with weight-loss meal replacement programs increased butyrate-producing bacteria and the F/B ratio. Moreover, the protein-enriched diet significantly increased alpha- and beta-diversity compared to the balanced diet and the high-lipid−low-carbohydrate diet.
Bioactive Ingredients from Dairy-Based Lactic Acid Bacterial Fermentations for Functional Food Production and Their Health Effects
Authors: Sørensen Helena Mylise , Rochfort Keith D. , Maye Susan , MacLeod George , Loscher Christine , Brabazon Dermot , Freeland Brian
Published: November 2023

Lactic acid bacteria are traditionally applied in a variety of fermented food products, and they have the ability to produce a wide range of bioactive ingredients during fermentation, including vitamins, bacteriocins, bioactive peptides, and bioactive compounds. The bioactivity and health benefits associated with these ingredients have garnered interest in applications in the functional dairy market and have relevance both as components produced in situ and as functional additives. This review provides a brief description of the regulations regarding the functional food market in the European Union, as well as an overview of some of the functional dairy products currently available in the Irish and European markets. A better understanding of the production of these ingredients excreted by lactic acid bacteria can further drive the development and innovation of the continuously growing functional food market.