bluuebunny/crossref_metadata_2025 huggingface dataset:
Anticancer Effects of Weizmannia coagulans MZY531 Postbiotics in CT26 Colorectal Tumor-Bearing Mice by Regulating Apoptosis and Autophagy
Authors: Zhong Bao , Zhao Yujuan , Gao Lei , Yang Ge , Gao Yansong , Li Fenglin , Li Shengyu
Published: October 2024

Weizmannia coagulans has been shown to have anticancer properties. However, there is limited research on the effects of postbiotic W. coagulans on colorectal cancer cell proliferation. Additionally, the exact mechanisms through which it influences apoptosis- and autophagy-related signaling pathways are yet to be thoroughly elucidated. This study explored the role of W. coagulans MZY531 as a postbiotic in inhibiting tumor growth by modulating apoptosis and autophagy in tumor cells. During the experimental period in the model group, tumors proliferated, tumor markers increased significantly, and immunofluorescence results showed that caspase-3 and terminal deoxynucleotidyl transferase dUTP nick-end labeling were significantly decreased. Conversely, supplementation with W. coagulans MZY531 postbiotics significantly reduced the levels of tumor markers carcinoembryonic antigen, colon cancer antigen, and extracellular protein kinase A and promoted cell apoptosis by increasing the caspase-3-positive count and terminal deoxynucleotidyl transferase dUTP nick-end labeling-positive cells in tumor tissue. Mechanistically, W. coagulans MZY531 postbiotics inhibit tumor growth through the modulation of the Bax/Bcl-2/caspase-3 and JAK2/STAT3 apoptosis pathways and PI3K/AKT/mTOR and TGF-β/SMAD4 cell autophagy pathways. W. coagulans MZY531 postbiotics had a more significant effect than that of W. coagulans MZY531 alone. Probiotics are expected to become effective natural functional foods for the treatment of colorectal cancer.
Evaluating Quality of Life Changes over 12 Months Among Opiate Users from Romania and Associated Worsening Factors
Authors: Bratu Melania Lavinia , Sandesc Dorel , Anghel Teodora , Bratosin Felix , Vlad Silviu Valentin , Terzi Artiom , Streian Caius Glad
Published: October 2024

This study aimed to evaluate the changes in quality of life (QoL) over a 12-month period among opiate users in Romania, identifying factors that contribute to a worsening of their condition. By examining these dynamics, the research intended to inform targeted interventions and support mechanisms to mitigate the negative outcomes associated with opiate use. Conducted as a longitudinal cohort analysis, this study enrolled 74 participants diagnosed with opioid use disorders from multiple healthcare settings in Romania. The WHOQOL-BREF instrument was utilized to assess QoL, with data collection spanning from 1 January 2023 to 31 December 2023. Ethical compliance with the Declaration of Helsinki was maintained, and participants provided informed consent. Statistical analysis was performed using SPSS, focusing on the impact of demographic and behavioral variables on QoL. Over the 12-month period, significant improvements were observed in all QoL domains: physical (51.68 to 58.39, p < 0.001), psychological (49.34 to 55.32, p < 0.001), social (46.21 to 53.66, p < 0.001), and environmental (47.85 to 54.17, p < 0.001). Methadone compliance significantly influenced positive outcomes across all domains. Compliant participants exhibited higher mean scores compared to non-compliant users, with respective increases in the physical domain from 52.47 to 60.21 (p < 0.001), psychological from 50.93 to 58.32 (p < 0.001), social from 48.36 to 57.14 (p < 0.001), and environmental from 47.82 to 55.79 (p < 0.001). Additionally, education showed a protective effect, particularly enhancing environmental QoL (estimate = 0.33, p = 0.013). Methadone compliance and higher education levels were identified as significant predictors of improved QoL among opiate users, demonstrating the critical importance of adherence to treatment protocols and the supportive role of education in enhancing life quality. These findings highlight the necessity for integrated treatment programs and educational interventions to improve the well-being of individuals battling opioid addiction, advocating for policy enhancements and supportive measures tailored to this demographic.
Short Lysine-Containing Tripeptide as Analgesic Substance: The Possible Mechanism of Ligand–Receptor Binding to the Slow Sodium Channel
Authors: Plakhova Vera B. , Kalinina Arina D. , Boichenko Nadezhda A. , Samosvat Dmitriy M. , Zegrya Georgy G. , Butkevich Irina P. , Mikhailenko Viktor A. , Penniyaynen Valentina A. , Podzorova Svetlana A. , Yagudina Roza I. , Krylov Boris V. , Rogachevskii Ilya V.
Published: October 2024

A possible molecular mechanism of the ligand–receptor binding of Ac-Lys-Lys-Lys-NH2 (Ac-KKK-NH2) to the NaV1.8 channel that is responsible for nociceptive signal coding in the peripheral nervous system is investigated by a number of experimental and theoretical techniques. Upon Ac-KKK-NH2 application at 100 nM, a significant decrease in the effective charge carried by the NaV1.8 channel activation gating system Zeff is demonstrated in the patch-clamp experiments. A strong Ac-KKK-NH2 analgesic effect at both the spinal and supraspinal levels is detected in vivo in the formalin test. The distances between the positively charged amino groups in the Ac-KKK-NH2 molecule upon binding to the NaV1.8 channel are 11–12 Å, as revealed by the conformational analysis. The blind docking with the NaV1.8 channel has made it possible to locate the Ac-KKK-NH2 binding site on the extracellular side of the voltage-sensing domain VSDI. The Ac-KKK-NH2 amino groups are shown to form ionic bonds with Asp151 and Glu157 and a hydrogen bond with Thr161, which affects the coordinated movement of the voltage sensor up and down, thus modulating the Zeff value. According to the results presented, Ac-KKK-NH2 is a promising candidate for the role of an analgesic medicinal substance that can be applied for pain relief in humans.
Research Progress on the Biological Activity of Ganoderic Acids in Ganoderma lucidum over the Last Five Years
Authors: Wang Siyi , Wang Longyu , Shangguan Jiaolei , Jiang Ailiang , Ren Ang
Published: October 2024

Ganoderma lucidum (G. lucidum) is a traditional edible and medicinal mushroom in China. The main bioactive components in G. lucidum include triterpenoids, polysaccharides, steroids, and sterols. Ganoderic acids (GAs) are one of the most abundant triterpenoids found in G. lucidum, garnering significant attention from researchers in the fields of medicine and health care. We summarize the extensive studies on the physiological function of GAs in anti-cancer, anti-inflammatory, radiation protection, anti-aging, liver protection, anti-microbial, and neuroprotection areas, among others. This review provides a comprehensive overview of the recent advances in the bioactivities and pharmacological mechanisms of GAs, aiming to delineate the current research directions and the state of the art in this field. This analysis helps to rapidly identify new bioactivities of GAs and understand their mechanisms, leading to more effective treatments for various diseases.
The Potential Role of Polyphenol Supplementation in Preventing and Managing Depression: A Review of Current Research
Authors: Farhan Mohd , Faisal Mohd
Published: October 2024

Depression is a common mental illness that affects 5% of the adult population globally. The most common symptoms of depression are low mood, lack of pleasure from different activities, poor concentration, and reduced energy levels for an extended period, and it affects the emotions, behaviors, and overall well-being of an individual. The complex pathophysiology of depression presents challenges for current therapeutic options involving a biopsychosocial treatment plan. These treatments may have a delayed onset, low remission and response rates, and undesirable side effects. Researchers in nutrition and food science are increasingly addressing depression, which is a significant public health concern due to the association of depression with the increased incidence of cardiovascular diseases and premature mortality. Polyphenols present in our diet may significantly impact the prevention and treatment of depression. The primary mechanisms include reducing inflammation and oxidative stress, regulating monoamine neurotransmitter levels, and modulating the microbiota–gut–brain axis and hyperactivity of the hypothalamic–pituitary–adrenal (HPA) axis. This review summarizes recent advances in understanding the effects of dietary polyphenols on depression and explores the underlying mechanisms of these effects for the benefit of human health. It also highlights studies that are looking at clinical trials to help future researchers incorporate these substances into functional diets, nutritional supplements, or adjunctive therapy to prevent and treat depression.
Development of a Residual Biomass Supply Chain Simulation Model Using AnyLogistix: A Methodical Approach
Authors: Chidozie Bernardine , Ramos Ana , Vasconcelos José , Ferreira Luis Pinto
Published: October 2024

Background: In the pursuit of sustainable energy sources, residual biomass has emerged as a promising renewable resource. However, efficiently managing residual biomass poses significant challenges, particularly in optimizing supply chain operations. Advanced modeling approaches are necessary to address these complexities. This study aims to develop a comprehensive methodological framework for creating simulation models tailored to agroforestry residual biomass supply chains. Methods: The study employs a hybrid simulation approach, integrating geographic information system mapping with a case study analysis. The simulation was conducted over a 365-day period, using the anyLogistix software (version 2.15.3.202209061204) to model various supply chain dynamics. The framework also accounts for financial, operational, customer satisfaction, and environmental metrics. Results: The simulation results showed a total expenditure of EUR 5,219,411.3, with transportation being the primary cost driver, involving 5678 trips and a peak capacity of 67.16 m3. CO2 emissions were measured at 487.7 kg/m3. The model performed as expected, highlighting the need for sustainable logistics strategies to reduce costs, lower losses, and improve productivity. Conclusions: This study presents one of the first detailed methodological frameworks for simulating agroforestry residual biomass supply chains. It provides valuable managerial insights into the financial, operational, and environmental aspects of supply chain management. The findings may stakeholders make informed decisions to enhance the sustainability of biomass utilization in energy production.
Facile Synthesis, Sintering, and Optical Properties of Single-Nanometer-Scale SnO2 Particles with a Pyrrolidone Derivative for Photovoltaic Applications
Authors: Hendra Wingki Mey , Nagaya Naohide , Hibi Yuto , Yoshida Norimitsu , Sugiura Takashi , Vafaei Saeid , Manseki Kazuhiro
Published: October 2024

We investigate the preparation of mesoscopic SnO2 nanoparticulate films using a Sn(IV) hydrate salt combined with a liquid pyrrolidone derivative to form a homogeneous precursor mixture for functional SnO2 nanomaterials. We demonstrate that N-methyl-2-pyrrolidone (NMP) plays a crucial role in forming uniform SnO2 films by both stabilizing the hydrolysis products of Sn(IV) sources and acting as a base liquid during nanoparticle growth. The hydrolysis of Sn(IV) was controlled by adjusting the reaction temperature to as low as 110 °C for 48 h. High-resolution TEM analysis revealed that highly crystalline SnO2 nanoparticles, approximately 3–5 nm in size, were formed. The SnO2 nanoparticles were deposited onto F-doped SnO2 glass and converted into dense particle films through heat treatments at 400 °C and 500 °C. This pyrrolidone-based nanoparticle synthesis enabled the production of not only crystallized SnO2 but also transparent and uniform films, most importantly by controlling the slow hydrolysis of Sn(IV) and polycondensation only with those two chemicals. These findings offer valuable insights for developing stable and uniform electron transport layers of SnO2 in mesoscopic solar cells, such as perovskite solar cells.
Bioactive Self-Polymerizing Resin with Surface Pre-Reacted Glass Ionomer Fillers for Suppressed Enamel Demineralization
Authors: Kaga Naoyuki , Kaga Masayuki , Morita Sho , Nagano-Takebe Futami , Nezu Takashi , Endo Kazuhiko , Matsuura Takashi
Published: October 2024

The treatment of damaged enamel surfaces involves modification of the enamel surface with artificial materials or the development of a pseudo-enamel, with research focusing on bioactive and biomimetic materials. In this study, a bioactive auto-polymerizing resin (APR) was developed by adding surface-pre-reacted glass ionomer (S-PRG) fillers of different quantities to APR. Its bioactive effects were evaluated via pH neutralization, ion release, and inhibition of enamel demineralization studies. The pH and fluoride ion release were measured using ion-specific electrodes, revealing that the APR disk with the S-PRG filler immediately neutralized the lactic acid solution (pH 4.0) through ion release. Inductively coupled plasma atomic emission spectrometry revealed that the Sr ion release peaked on the first day, with the other ions following the order F > B > Si > Al > Na, exhibiting a weekly decrease in the same order. Scanning electron microscopy was used to examine the enamel block morphology of the disks after 7 d of incubation, revealing enamel demineralization in disks without the S-PRG filler, whereas no demineralization occurred in disks with the S-PRG filler. APR containing the S-PRG filler demonstrated acid buffering suppressed enamel demineralization and bioactive properties.
Exploring the Potential of Cold Sintering for Proton-Conducting Ceramics: A Review
Authors: Bartoletti Andrea , Mercadelli Elisa , Gondolini Angela , Sanson Alessandra
Published: October 2024

Proton-conducting ceramic materials have emerged as effective candidates for improving the performance of solid oxide cells (SOCs) and electrolyzers (SOEs) at intermediate temperatures. BaCeO3 and BaZrO3 perovskites doped with rare-earth elements such as Y2O3 (BCZY) are well known for their high proton conductivity, low operating temperature, and chemical stability, which lead to SOCs’ improved performance. However, the high sintering temperature and extended processing time needed to obtain dense BCZY-type electrolytes (typically > 1350 °C) to be used as SOC electrolytes can cause severe barium evaporation, altering the stoichiometry of the system and consequently reducing the performance of the final device. The cold sintering process (CSP) is a novel sintering technique that allows a drastic reduction in the sintering temperature needed to obtain dense ceramics. Using the CSP, materials can be sintered in a short time using an appropriate amount of a liquid phase at temperatures < 300 °C under a few hundred MPa of uniaxial pressure. For these reasons, cold sintering is considered one of the most promising ways to obtain ceramic proton conductors in mild conditions. This review aims to collect novel insights into the application of the CSP with a focus on BCZY-type materials, highlighting the opportunities and challenges and giving a vision of future trends and perspectives.
Second Life for Recycled Concrete and Other Construction and Demolition Waste in Mortars for Masonry: Full Scope of Material Properties, Performance, and Environmental Aspects
Authors: Grigorjev Vadim , Azenha Miguel , De Belie Nele
Published: October 2024

This review presents the scope of current efforts to utilize recycled construction and demolition waste in mortars for masonry. More than 100 articles are divided into groups pertaining to the type of mortar, different binder systems, the type of construction and demolition waste (CDW), and its utilization specifics. Cement-based mortars dominate this research domain, whereas recycled concrete is the main material employed to replace virgin aggregates, followed by recycled masonry and recycled mixed waste aggregates. Such application in cement-based mortars could increase water demand by 20–34% and reduce strength by 11–50%, with recycled concrete aggregates being the most favorable. Natural aggregate substitution is disadvantageous in strong mortars, whereas weaker ones, such as lime-based mortars, could benefit from this incorporation. The extent of this topic also suggests possibilities for different recycled material use cases in mortars for masonry, although the available literature is largely insufficient to infer meaningful trends. Nonetheless, the most relevant knowledge synthesized in this review offers promising and environment-conscious utilization pathways for recycled concrete and other construction and demolition waste, which brings opportunities for further research on their use in mortars for masonry and industrial-scale applications.
Recycled Aggregates Influence on the Mechanical Properties of Cement Lime-Based Mortars
Authors: Catalin Saitis , Daniela Manea Lucia , Moldovan Marioara , Monica Plesa Luminita , Borodi Gheorghe , Petean Ioan , Sorin Letiu
Published: October 2024

The current framework for managing construction waste, guided by European Union regulations, calls for an integrated waste management system. However, the reuse of old plaster waste, particularly from deteriorated facades, remains underexplored. This study investigates the potential of repurposing old plaster waste as a substitute for aggregates and cement in mortars, with the aim of promoting environmental sustainability and resource efficiency. Three mortar mixes were analyzed: a control mix, a mix with 45% waste replacing aggregates, and a mix with 10% waste replacing cement. Results show that replacing 45% of aggregates with plaster waste led to a 30% reduction in flexural strength, while the 10% cement replacement increased flexural strength by 6%. Compressive strength dropped by 27% and 38% for cement and aggregate replacements, respectively. Despite these reductions, the waste replacement remained within acceptable limits for structural integrity. Further microscopic analysis revealed that the incomplete integration of portlandite particles from the waste contributed to non-uniform bonding and crystal formation, weakening the mortar’s structure. This research demonstrates the feasibility of reusing old plaster waste, offering a novel approach to reducing construction waste and promoting a circular economy. It contributes to filling the knowledge gap on the reuse of plaster mortars while aligning with sustainable construction goals.
High Performance of Mn2O3 Electrodes for Hydrogen Evolution Using Natural Bischofite Salt from Atacama Desert: A Novel Application for Solar Saline Water Splitting
Authors: Galleguillos-Madrid Felipe M. , Salazar-Avalos Sebastian , Fuentealba Edward , Leiva-Guajardo Susana , Cáceres Luis , Portillo Carlos , Sepúlveda Felipe , Brito Iván , Cobos-Murcia José Ángel , Rojas-Moreno Omar F. , Jimenez-Arevalo Víctor , Schott Eduardo , Soliz Alvaro
Published: October 2024

Solar saline water splitting is a promising approach to sustainable hydrogen production, harnessing abundant solar energy and the availability of brine resources, especially in the Atacama Desert. Bischofite salt (MgCl2·6H2O) has garnered significant attention due to its wide range of industrial applications. Efficient hydrogen production in arid or hyper arid locations using bischofite solutions is a novel and revolutionary idea. This work studied the electrochemical performance of Mn2O3 electrodes using a superposition model based on mixed potential theory and evaluated the superficial performance of this electrode in contact with a 0.5 M bischofite salt solution focusing on the hydrogen evolution reaction (HER) and oxygen reduction reaction (ORR) that occur during saline water splitting. The application of the non-linear superposition model provides valuable electrochemical kinetic parameters that complement the understanding of Mn2O3, this being one of the novelties of this work.
State-of-the-Art Flocking Strategies for the Collective Motion of Multi-Robots
Authors: Ali Zain Anwar , Alkhammash Eman H. , Hasan Raza
Published: October 2024

The technological revolution has transformed the area of labor with reference to automation and robotization in various domains. The employment of robots automates these disciplines, rendering beneficial impacts as robots are cost-effective, reliable, accurate, productive, flexible, and safe. Usually, single robots are deployed to accomplish specific tasks. The purpose of this study is to focus on the next step in robot research, collaborative multi-robot systems, through flocking control in particular, improving their self-adaptive and self-learning abilities. This review is conducted to gain extensive knowledge related to swarming, or cluster flocking. The evolution of flocking laws from inception is delineated, swarming/cluster flocking is conceptualized, and the flocking phenomenon in multi-robots is evaluated. The taxonomy of flocking control based on different schemes, structures, and strategies is presented. Flocking control based on traditional and trending approaches, as well as hybrid control paradigms, is observed to elevate the robustness and performance of multi-robot systems for collective motion. Opportunities for deploying robots with flocking control in various domains are also discussed. Some challenges are also explored, requiring future considerations. Finally, the flocking problem is defined and an abstraction of flocking control-based multiple UAVs is presented by leveraging the potentials of various methods. The significance of this review is to inspire academics and practitioners to adopt multi-robot systems with flocking control for swiftly performing tasks and saving energy.
Existence and Stability for Fractional Differential Equations with a ψ–Hilfer Fractional Derivative in the Caputo Sense
Authors: He Wenchang , Jin Yuhang , Wang Luyao , Cai Ning , Mu Jia
Published: October 2024

This article aims to explore the existence and stability of solutions to differential equations involving a ψ-Hilfer fractional derivative in the Caputo sense, which, compared to classical ψ-Hilfer fractional derivatives (in the Riemann–Liouville sense), provide a clear physical interpretation when dealing with initial conditions. We discovered that the ψ-Hilfer fractional derivative in the Caputo sense can be represented as the inverse operation of the ψ-Riemann–Liouville fractional integral, and used this property to prove the existence of solutions for linear differential equations with a ψ-Hilfer fractional derivative in the Caputo sense. Additionally, we applied Mönch’s fixed-point theorem and knowledge of non-compactness measures to demonstrate the existence of solutions for nonlinear differential equations with a ψ-Hilfer fractional derivative in the Caputo sense, and further discussed the Ulam–Hyers–Rassias stability and semi-Ulam–Hyers–Rassias stability of these solutions. Finally, we illustrated our results through case studies.
TetraFEM: Numerical Solution of Partial Differential Equations Using Tensor Train Finite Element Method
Authors: Kornev Egor , Dolgov Sergey , Perelshtein Michael , Melnikov Artem
Published: October 2024

In this paper, we present a methodology for the numerical solving of partial differential equations in 2D geometries with piecewise smooth boundaries via finite element method (FEM) using a Quantized Tensor Train (QTT) format. During the calculations, all the operators and data are assembled and represented in a compressed tensor format. We introduce an efficient assembly procedure of FEM matrices in the QTT format for curvilinear domains. The features of our approach include efficiency in terms of memory consumption and potential expansion to quantum computers. We demonstrate the correctness and advantages of the method by solving a number of problems, including nonlinear incompressible Navier–Stokes flow, in differently shaped domains.
Transfer Learning-Based Physics-Informed Convolutional Neural Network for Simulating Flow in Porous Media with Time-Varying Controls
Authors: Chen Jungang , Gildin Eduardo , Killough John E.
Published: October 2024

A physics-informed convolutional neural network (PICNN) is proposed to simulate two-phase flow in porous media with time-varying well controls. While most PICNNs in the existing literature worked on parameter-to-state mapping, our proposed network parameterizes the solutions with time-varying controls to establish a control-to-state regression. Firstly, a finite volume scheme is adopted to discretize flow equations and formulate a loss function that respects mass conservation laws. Neumann boundary conditions are seamlessly incorporated into the semi-discretized equations so no additional loss term is needed. The network architecture comprises two parallel U-Net structures, with network inputs being well controls and outputs being the system states (e.g., oil pressure and water saturation). To capture the time-dependent relationship between inputs and outputs, the network is well designed to mimic discretized state-space equations. We train the network progressively for every time step, enabling it to simultaneously predict oil pressure and water saturation at each timestep. After training the network for one timestep, we leverage transfer learning techniques to expedite the training process for a subsequent time step. The proposed model is used to simulate oil–water porous flow scenarios with varying reservoir model dimensionality, and aspects including computation efficiency and accuracy are compared against corresponding numerical approaches. The comparison with numerical methods demonstrates that a PICNN is highly efficient yet preserves decent accuracy.
Driver Distraction Detection Based on Fusion Enhancement and Global Saliency Optimization
Authors: Huang Xueda , Gu Shuangshuang , Li Yuanyuan , Qi Guanqiu , Zhu Zhiqin , An Yiyao
Published: October 2024

Driver distraction detection not only effectively prevents traffic accidents but also promotes the development of intelligent transportation systems. In recent years, thanks to the powerful feature learning capabilities of deep learning algorithms, driver distraction detection methods based on deep learning have increased significantly. However, for resource-constrained onboard devices, real-time lightweight models are crucial. Most existing methods tend to focus solely on lightweight model design, neglecting the loss in detection performance for small targets. To achieve a balance between detection accuracy and network lightweighting, this paper proposes a driver distraction detection method that combines enhancement and global saliency optimization. The method mainly consists of three modules: context fusion enhancement module (CFEM), channel optimization feedback module (COFM), and channel saliency distillation module (CSDM). In the CFEM module, one-dimensional convolution is used to capture information between distant pixels, and an injection mechanism is adopted to further integrate high-level semantic information with low-level detail information, enhancing feature fusion capabilities. The COFM module incorporates a feedback mechanism to consider the impact of inter-layer and intra-layer channel relationships on model compression performance, achieving joint pruning of global channels. The CSDM module guides the student network to learn the salient feature information from the teacher network, effectively balancing the model’s real-time performance and accuracy. Experimental results show that this method outperforms the state-of-the-art methods in driver distraction detection tasks, demonstrating good performance and potential application prospects.
Applying Multi-Task Deep Learning Methods in Electricity Load Forecasting Using Meteorological Factors
Authors: Huang Kai-Bin , Lee Tian-Shyug , Lee Jonathan , Wu Jy-Ping , Lee Leemen , Lee Hsiu-Mei
Published: October 2024

The steady rise in carbon emissions has significantly exacerbated the global climate crisis, posing a severe threat to ecosystems due to the greenhouse gas effect. As one of the most pressing challenges of our time, the need for an immediate transition to renewable energy is imperative to meet the carbon reduction targets set by the Paris Agreement. Buildings, as major contributors to global energy consumption, play a pivotal role in climate change. This study diverges from previous research by employing multi-task deep learning techniques to develop a predictive model for electricity load in commercial buildings, incorporating auxiliary tasks such as temperature and cloud coverage. Using real data from a commercial building in Taiwan, this study explores the effects of varying batch sizes (100, 125, 150, and 200) on the model’s performance. The findings reveal that the multi-task deep learning model consistently surpasses single-task models in predicting electricity load, demonstrating superior accuracy and stability. These insights are crucial for companies aiming to enhance energy efficiency and formulate effective renewable energy procurement strategies, contributing to broader sustainability efforts and aligning with global climate action goals.
Fast Color Image Encryption Algorithm Based on DNA Coding and Multi-Chaotic Systems
Authors: Wang Shaofang , Pan Jingguo , Cui Yanrong , Chen Zhongju , Zhan Wei
Published: October 2024

At present, there is a growing emphasis on safeguarding image data, yet conventional encryption methods are full of numerous limitations. In order to tackle the limitations of conventional color image encryption methodologies, such as inefficiency and insufficient security, this paper designs an expedited encryption method for color images that uses DNA coding in conjunction with multiple chaotic systems. The encryption algorithm proposed in this paper is based on three-dimensional permutation, global scrambling, one-dimensional diffusion and DNA coding. First of all, the encryption algorithm uses three-dimensional permutation algorithms to scramble the image, which disrupts the high correlation among the image pixels. Second, the RSA algorithm and the SHA-256 hashing algorithm are utilized to derive the starting value necessary for the chaotic system to produce the key. Third, the image is encrypted by using global scrambling and one-dimensional diffusion. Finally, DNA coding rules are used to perform DNA computing. The experimental results indicate that the encryption scheme exhibits a relatively weak inter-pixel correlation, uniform histogram distribution, and an information entropy value approaching eight. This shows that the proposed algorithm is able to protect the image safely and efficiently.
Bio-Calcium from Skipjack Tuna Frame Attenuates Bone Loss in Ovariectomy-Induced Osteoporosis Rats
Authors: Saetang Jirakrit , Issuriya Acharaporn , Suyapoh Watcharapol , Sornying Peerapon , Nilsuwan Krisana , Benjakul Soottawat
Published: October 2024

Bio-calcium derived from fish frames may offer several advantages for osteoporosis prevention. This study aimed to evaluate the effects of bio-calcium derived from skipjack tuna frames on bone loss in ovariectomized rats. Tuna bio-calcium was prepared through enzymatic hydrolysis, defatting, bleaching, and grinding processes. The bioavailability of calcium was tested using the Caco-2 cell monolayer model, showing that 13% of tuna bio-calcium was absorbed, compared to 10% for calcium carbonate. Rats were divided into the five following groups: (1) OVX, (2) sham-operated, (3), OVX + estrogen-treated (4) OVX + calcium carbonate-treated, and (5) OVX + tuna bio-calcium-treated. All groups were raised for eight weeks. Tuna bio-calcium was able to increase BV/TV by 26% in the femur and 29% in the tibia, compared to 13% and 17% in the OVX group, respectively. Trabecular thickness in the femur upsurged to 360 µm in the tuna group, while a thickness of 290 µm was observed in the control. Additionally, osteoclast numbers were reduced to 5 N.Oc/mm in the femur and 6 N.Oc/mm in the tibia in the tuna group, compared to 35 and 45 N.Oc/mm in the control. Overall, tuna bio-calcium effectively prevented bone loss and can serve as a promising natural alternative for managing osteoporosis.
Discovery of Anti-Inflammatory Alkaloids from Sponge Stylissa massa Suggests New Biosynthetic Pathways for Pyrrole–Imidazole Alkaloids
Authors: Liu Xiaojing , Wang Qi , Zhang Yun , Zhang Hanting
Published: October 2024

Pyrrole–imidazole alkaloids (PIAs) are a class of marine sponge derived natural products which have complex carbon frameworks and broad bioactivities. In this study, four new alkaloids, stylimassalins A–B (1–2), 3, and 5, together with two known compounds (4 and 6), were isolated from Stylissa massa. Compounds 2, 4, and 6 are the C-2 brominated analogues of 1, 3, and 5, respectively. Their structures display three different scaffolds, of which scaffold 1 (compounds 1,2) is new. A new biosynthetic pathway from oroidin, through spongiacidin, to latonduine and scaffold 1 was proposed by our group, in which the C12-N13-cleavaged compounds of spongiacidin (scaffold 2), dubbed seco-spongiacidins (3 and 4), are recognized as a key bridged scaffold, to afford PIA analogues (1,2 and 5,6). An anti-inflammatory evaluation in a zebrafish inflammation model induced by copper sulphate (CuSO4) demonstrated that stylimassalins A and B (1 and 2) could serve as a promising lead scaffold for treating inflammation.
Unveiling the Intricacies: Exploring Stepwise Initiation of Peritoneal Dialysis in a Single-Center Setting
Authors: Hsiao Ping-Kun , Wong Wei-Je , Hsieh Su-I , Lin Hsiu-Ying , Chen Tzay-Jinn , Cheng Chung-Yi
Published: October 2024

Background and Objectives: Chronic kidney disease (CKD) poses a significant global health challenge, necessitating effective renal replacement therapies. Peritoneal dialysis (PD) offers a patient-friendly, home-based alternative to hemodialysis. The Stepwise Initiation of Peritoneal Dialysis (SIPD) method, used in the SPD group and involving a gradual introduction of PD, presents a potential advantage over traditional protocols, yet the scientific literature on its efficacy and safety is limited. Materials and Methods: We conducted a retrospective analysis of 39 end-stage renal disease patients undergoing SIPD and 78 patients receiving conventional PD (CPD) at a single center from 1 January 2010 to 31 December 2023. Patients were matched for age and sex. Surgical techniques, early and late complications, infection rates, and catheter survival were evaluated. Data were analyzed using statistical methods, including the chi-square test, t-test, and negative binomial regression. Results: The mean break-in period was significantly more extended for the SPD group (176.05 ± 154.39 days) compared to the CPD group (26.87 ± 58.45 days). Early complications were similar between groups, but late complications, including peritonitis, were significantly higher in the CPD group. The SPD group experienced fewer infection events (28 vs. 80, p = 0.043). Median catheter survival times were 1486 days for SPD and 1774 days for CPD, with no statistical difference. Age was a significant factor in peritonitis incidence, increasing with age in both groups. Conclusions: Our study suggests that SPD may reduce the incidence of catheter-related infections and peritonitis compared to CPD. The extended break-in period in SPD could enhance tissue healing and reduce biofilm formation, thereby contributing to fewer infectious complications. Despite these findings, no significant difference in overall catheter survival was observed. Further multi-center studies with larger sample sizes are recommended to confirm these results and explore the economic impact of SPD vs. CPD.
Predicting Invasiveness in Lepidic Pattern Adenocarcinoma of Lung: Analysis of Visual Semantic and Radiomic Features
Authors: Johnson Sean F. , Tabatabaei Seyed Mohammad Hossein , Kim Grace Hyun J. , Villegas Bianca E. , Brown Matthew , Genshaft Scott , Suh Robert D. , Barjaktarevic Igor , Wallace William Dean , Abtin Fereidoun
Published: October 2024

Objectives: To differentiate invasive lepidic predominant adenocarcinoma (iLPA) from adenocarcinoma in situ (AIS)/minimally invasive adenocarcinoma (MIA) of lung utilizing visual semantic and computer-aided detection (CAD)-based texture features on subjects initially diagnosed as AIS or MIA with CT-guided biopsy. Materials and Methods: From 2011 to 2017, all patients with CT-guided biopsy results of AIS or MIA who subsequently underwent resection were identified. CT scan before the biopsy was used to assess visual semantic and CAD texture features, totaling 23 semantic and 95 CAD-based quantitative texture variables. The least absolute shrinkage and selection operator (LASSO) method or forward selection was used to select the most predictive feature and combination of semantic and texture features for detection of invasive lung adenocarcinoma. Results: Among the 33 core needle-biopsied patients with AIS/MIA pathology, 24 (72.7%) had invasive LPA and 9 (27.3%) had AIS/MIA on resection. On CT, visual semantic features included 21 (63.6%) part-solid, 5 (15.2%) pure ground glass, and 7 (21.2%) solid nodules. LASSO selected seven variables for the model, but all were not statistically significant. “Volume” was found to be statistically significant when assessing the correlation between independent variables using the backward selection technique. The LASSO selected “tumor_Perc95”, “nodule surround”, “small cyst-like spaces”, and “volume” when assessing the correlation between independent variables. Conclusions: Lung biopsy results showing noninvasive LPA underestimate invasiveness. Although statistically non-significant, some semantic features showed potential for predicting invasiveness, with septal stretching absent in all noninvasive cases, and solid consistency present in a significant portion of invasive cases.
Center-Punching Mechanical Clinching Process for Aluminum Alloy and Ultra-High-Strength Steel Sheets
Authors: Qiu Ping , Lu Xiaoxin , Dai Xuewei , Deng Boran , Xiao Hong
Published: October 2024

In recent years, with the rapid advancement of automotive lightweight technology, the mechanical clinching process between aluminum alloy and ultra-high-strength steel sheets has received extensive attention. However, the low ductility of ultra-high-strength steel sheets often results in conventional mechanical clinching processes producing joints that either fail to establish effective interlocks or cause the steel sheets to fracture. To address this issue, a novel mechanical clinching process is presented, called center-punching mechanical clinching (CPMC). This innovative process employs a method of punching, flanging, and bulging gradation to achieve the mechanical clinching of aluminum alloy and ultra-high-strength steel sheets in a single step. In order to determine the effects of different parameters on the quality and strength of the joint, an experimental study was carried out for various die depths and diameters based on the condition of constant punch size. Based on tensile and shear tests, the static strength and failure modes of CPMC joints were analyzed. The results indicated that the CPMC process significantly enhances the connectivity of joints for AA5052 aluminum alloy and DP980 ultra-high-strength steel. Optimal tensile and shear strengths of 1264 and 2249 N, respectively, were achieved at a die depth of 2.2 mm and a diameter of 10.4 mm. The CPMC process provides new ideas for the mechanical clinching of aluminum alloy and ultra-high-strength steels.
Machine-Learning-Driven Design of High-Elastocaloric NiTi-Based Shape Memory Alloys
Authors: Gao Yingyu , Hu Yunfeng , Zhao Xinpeng , Liu Yang , Huang Haiyou , Su Yanjing
Published: October 2024

In recent years, the detrimental impact of traditional gas–liquid refrigerants on the environment has prompted a shift towards sustainable solid-state refrigeration technology. The elastocaloric effect, particularly in NiTi-based shape memory alloys (SMAs), presents a promising alternative due to its high coefficient of performance. However, conventional methods for alloy development are inefficient, often failing to meet the stringent requirements for practical applications. This study employed machine learning (ML) to accelerate the design of NiTi-based SMAs with an enhanced elastocaloric effect. Through active learning across four iterations, we identified nine novel NiTi-based SMAs exhibiting phase-transformation-induced entropy changes (ΔS) greater than 90 J/kg·K−1, surpassing most existing alloys. Our ML model demonstrates robust interpretability, revealing key relationships between material features and performance. This work not only establishes a more efficient pathway for alloy discovery but also aims to contribute significantly to the advancement of sustainable refrigeration technologies.
Current Challenges in Corrosion Research
Authors: Díaz Belén , Grgur Branimir , Wang Jianqiang
Published: October 2024

Corrosion is a degradation phenomenon with huge economic consequences and severe security implications [...]
Comparative Study on the Effect of External Magnetic Field on Aluminum Alloy 6061 and 7075 Resistance Spot-Welding Joints
Authors: Wei Shitian , Zhang Rui , Liu Xiuli , Zhang Yu
Published: October 2024

This study investigates the effects of the external magnetic field on the microstructure and mechanical property aluminum alloy 6061-T6 and 7075-T651 resistance spot welding joints. The melting behavior of 6061 and 7075 was analyzed via the calculation of the phase diagram (CALPHAD) technique. The CALPHAD results indicate that, for the 6061 aluminum alloy, the liquid fraction shows a minimal increase at the beginning stage during the solid–liquid phase transition process but with a sharp rise at the ending stage (near the liquidus). In contrast, for the 7075 aluminum alloy, the liquid fraction gradually increases throughout the entire solid–liquid phase transition process. The differences in melting behavior between the 6061 and 7075 alloys lead to different liquation crack morphologies in their spot-welded joints. In the 6061 alloy, the cracks tend to be “eyebrow-shaped”, allowing the liquid metal in the nugget to feed the gaps, and this does not significantly compromise the mechanical properties of the joint. In contrast, the 7075 alloy develops slender cracks that extend through the partially melted zone (PMZ), making it difficult for the liquid metal to feed these gaps, thereby significantly deteriorating the joint’s mechanical strength. Compared to conventional resistance spot-welding joints, the heat exchange between the nugget and the workpiece is enhanced under the external magnetic field, leading to a wider PMZ. This exacerbates the detrimental effects of liquation cracks on the mechanical properties of the 7075 joints. Lap-shear tests indicate that the mechanical properties of the 6061 aluminum alloy joints are improved under electromagnetic stirring. For 7075 aluminum alloy joints, the mechanical properties improve when the welding current is below 34 kA. However, when the welding current exceeds 34 kA, because the widening of the PMZ increases the tendency for liquation cracks, the joint’s mechanical property is deteriorated.
A First-Principles Study of the Structural and Thermo-Mechanical Properties of Tungsten-Based Plasma-Facing Materials
Authors: Peng Jie , Qian Yichen , Cereceda David
Published: October 2024

Tungsten (W) and tungsten alloys are being considered as leading candidates for structural and functional materials in future fusion energy devices. The most attractive properties of tungsten for the design of magnetic and inertial fusion energy reactors are its high melting point, high thermal conductivity, low sputtering yield, and low long-term disposal radioactive footprint. Despite these relevant features, there is a lack of understanding of how the structural and mechanical properties of W-based alloys are affected by the temperature in fusion power plants. In this work, we present a study on the thermo-mechanical properties of five W-based plasma-facing materials. First-principles density functional theory (DFT) calculations are combined with the quasi-harmonic approximation (QHA) theory to investigate the electronic, structural, mechanical, and thermal properties of these W-based alloys as a function of temperature. The coefficient of thermal expansion, temperature-dependent elastic constants, and several elastic parameters, including bulk and Young’s modulus, are calculated. Our work advances the understanding of the structural and thermo-mechanical behavior of W-based materials, thus providing insights into the design and selection of candidate plasma-facing materials in fusion energy devices.
Multi-Modal Investigation of Metabolism in Murine Breast Cancer Cell Lines Using Fluorescence Lifetime Microscopy and Hyperpolarized 13C-Pyruvate Magnetic Resonance Spectroscopy
Authors: Erickson-Bhatt Sarah , Cox Benjamin L. , Macdonald Erin , Chacko Jenu V. , Begovatz Paul , Keely Patricia J. , Ponik Suzanne M. , Eliceiri Kevin W. , Fain Sean B.
Published: October 2024

Background/Objectives: Despite the role of metabolism in breast cancer metastasis, we still cannot predict which breast tumors will progress to distal metastatic lesions or remain dormant. This work uses metabolic imaging to study breast cancer cell lines (4T1, 4T07, and 67NR) with differing metastatic potential in a 3D collagen gel bioreactor system. Methods: Within the bioreactor, hyperpolarized magnetic resonance spectroscopy (HP-MRS) is used to image lactate/pyruvate ratios, while fluorescence lifetime imaging microscopy (FLIM) of endogenous metabolites measures metabolism at the cellular scale. Results: HP-MRS results showed no lactate peak for 67NR and a comparatively large lactate/pyruvate ratio for both 4T1 and 4T07 cell lines, suggestive of greater pyruvate utilization with greater metastatic potential. Similar patterns were observed using FLIM with significant increases in FAD intensity, redox ratio, and NAD(P)H lifetime. The lactate/pyruvate ratio was strongly correlated to NAD(P)H lifetime, consistent with the role of NADH as an electron donor for the glycolytic pathway, suggestive of an overall upregulation of metabolism (both glycolytic and oxidative), for the 4T07 and 4T1 cell lines compared to the non-metastatic 67NR cell line. Conclusions: These findings support a complementary role for HP-MRS and FLIM enabled by a novel collagen gel bioreactor system to investigate metastatic potential and cancer metabolism.