bluuebunny/crossref_metadata_2025 huggingface dataset:
Ultrasensitive Lateral Flow Immunoassay of Fluoroquinolone Antibiotic Gatifloxacin Using Au@Ag Nanoparticles as a Signal-Enhancing Label
Authors: Hendrickson Olga D. , Byzova Nadezhda A. , Panferov Vasily G. , Zvereva Elena A. , Xing Shen , Zherdev Anatoly V. , Liu Juewen , Lei Hongtao , Dzantiev Boris B.
Published: December 2024

Gatifloxacin (GAT), an antibiotic belonging to the fluoroquinolone (FQ) class, is a toxicant that may contaminate food products. In this study, a method of ultrasensitive immunochromatographic detection of GAT was developed for the first time. An indirect format of the lateral flow immunoassay (LFIA) was performed. GAT-specific monoclonal antibodies and labeled anti-species antibodies were used in the LFIA. Bimetallic core@shell Au@Ag nanoparticles (Au@Ag NPs) were synthesized as a new label. Peroxidase-mimic properties of Au@Ag NPs allowed for the catalytic enhancement of the signal on test strips, increasing the assay sensitivity. A mechanism of Au@Ag NPs-mediated catalysis was deduced. Signal amplification was achieved through the oxidative etching of Au@Ag NPs by hydrogen peroxide. This resulted in the formation of gold nanoparticles and Ag+ ions, which catalyzed the oxidation of the peroxidase substrate. Such “chemical enhancement” allowed for reaching the instrumental limit of detection (LOD, calculated by Three Sigma approach) and cutoff of 0.8 and 20 pg/mL, respectively. The enhanced assay procedure can be completed in 21 min. The enhanced LFIA was tested for GAT detection in raw meat samples, and the recoveries from meat were 78.1–114.8%. This method can be recommended as a promising instrument for the sensitive detection of various toxicants.
Native and Non-Native Speakers’ Recognition of Chinese Two-Character Words in Audio Sentence Comprehension
Authors: Ma Wenling , Li Degao , Dong Xiuling
Published: December 2024

Two experiments were conducted to examine native and non-native speakers’ recognition of Chinese two-character words (2C-words) in the context of audio sentence comprehension. The recording was played of a sentence, in which a collocation composed of a number word, a sortal classifier, and a noun (NCN) was embedded. When the participants were about to hear the noun of the NCN (Noun), the playing stopped, and a target was visually presented, which was the Noun, the character-transposed word of the Noun (NounT), or a control word (NounC), or was a homophone nonword for Noun, NounT, or NounC. The participants were required to make a lexical decision on the target before they resumed listening. The results showed that both native and non-native speakers were able to take visually presented 2C-word targets as semantic whole entities in the context of audio sentence comprehension, which was mediated by their Chinese proficiency. Native speakers readily processed visually presented 2C-words both as wholes and according to their constituent characters, but non-native speakers were not likely to process the 2C-words according to their constituent characters.
Analyzing the Effect of Factors on Individuals’ Subjective Well-Being with Quantile Bayesian Structural Equation Modeling Approach
Authors: Çiçek Zübeyde , Bayram Arlı Nuran
Published: December 2024

This study investigates factors influencing individuals’ levels of subjective well-being by examining fundamental variables, called life domains, such as satisfaction with health, education, marriage, housing district, work life, social life, relationships, and public services. The aim is to understand how these domains affect various quantile values of subjective well-being. To achieve this, the Life Satisfaction Survey dataset for 2020, obtained from the Turkish Statistical Institute, was utilized, and Bayesian Quantile Structural Equation Modeling and Bayesian Structural Equation Modeling methods were applied. The empirical study indicates that all life domains were found to have a positive impact on subjective well-being, except for housing-district satisfaction and education satisfaction. In particular, for individuals with low subjective well-being, satisfaction with work life, relationships, and public services has a stronger effect on subjective well-being compared to those in higher quantiles. Conversely, marriage satisfaction has a stronger effect on subjective well-being among individuals in the higher quantiles. This study’s unique contribution is that examining subjective well-being according to quantile values provides detailed information on how the factors influencing individuals’ subjective well-being vary across different levels.
Urban Architectural Color Evaluation: A Cognitive Framework Combining Machine Learning and Human Perception
Authors: Li Xu , Qin Jianan , Long Yixiang
Published: December 2024

Architectural color significantly impacts the quality of built environments and is closely related to the physical and mental health of residents. Previous studies have conducted numerous valuable explorations in this field; however, the challenge of quantitatively measuring the characteristics of architectural colors in depth and examining the complex relationship between these colors and human perception remains an unresolved issue. To this end, this study builds upon recent advancements in data technology and emotion analysis to develop a comprehensive cognitive framework for urban architectural color evaluation. It combines machine learning techniques and perception scales, utilizing both objective and subjective data. By acquiring and recognizing numerous street-view images of the Changsha Central District, we quantitatively examined the hue, saturation, value, color complexity index and color harmony index of urban architectural colors and investigated the complex relationships between human perception and architectural colors through large-scale participant ratings and correlation analyses. The results show that the architectural colors of the study area are warm, with low saturation and moderate value. Most areas exhibit a high color complexity index, whereas the overall color harmony score is low. Human-perception evaluations indicate that people are generally satisfied with the urban architectural colors of the Changsha Central District. For further optimization, the saturation and color harmony scores need to be enhanced. This study provides a comprehensive evaluation of urban architectural color quality, visualizing the complex relationship between urban architectural color and human perception. It offers new perspectives for improving the built environments and supporting sustainable development, with practical application value.
Retrofit Analysis of Exterior Windows for Large Office Buildings in Different Climate Zones of China
Authors: Liu Sai , Ghazali Farid E. Mohamed , Yang Jingjing , Guo Zongkang , Zeng Kejun , Chen Yixing
Published: December 2024

In the energy-saving retrofit of existing buildings, investors are particularly concerned about the energy-saving performance of exterior windows and the payback period of additional costs. This study evaluates representative cities in four different climate zones in China to simulate the energy consumption of large office buildings after replacing different glass windows and conducting energy-saving and economic feasibility assessments. The research method includes the following steps: First, a baseline model of large office buildings in four cities was established using AutoBPS and OpenStudio. Then, the baseline and retrofit models of replacing glass windows were simulated using the EnergyPlus V9.3.0 to obtain multiple hourly energy consumption results. The commercial electricity and gas prices in the four cities were adjusted to calculate the total cost within 20 years after replacing different types of windows. Using the discounted payback period (DPP), net present value (NPV), and profitability index (PI) as evaluation indicators, a feasibility analysis was conducted in the four regions to evaluate the economic feasibility of replacing building windows. The simulation results show that considering economic feasibility and meeting energy-saving standards, it is more economical to choose windows with moderate U-value and SHGC value in the four regions than to choose windows with the smallest U-value and SHGC value, and that both energy savings and economic benefits are closely related to building age, with older buildings (especially those in Changsha and Shenzhen) showing greater benefits. Furthermore, the optimal window types in the four cities determined in this study can recover the investment cost within the window life, with Harbin (SC), Beijing (C), Changsha (HC), and Shenzhen (HW) with the payback period of 6.60, 15.66, 10.16, and 11.42 years, respectively. The research model established in this study provides a useful evaluation path for selecting windows for the energy-saving retrofit of large office buildings in cities in different climate zones and provides data support for the decision making of energy-saving retrofit investors.
Sustainable Management of Cities with a Focus on the Spread of Pollution in the Built Environment Using Information Modeling
Authors: Szeligova Natalie , Faltejsek Michal , Teichmann Marek
Published: December 2024

The sustainable development of settlements is increasingly linked to the development of information technologies, which can help identify critical and risky locations based on already detected information. By properly utilizing the advantages of individual systems, effective simulations can be created that will help municipal administrators ensure the expected quality of the environment or mitigate the impacts of the negative effects of the external environment. This article presents an example of the synthesis of several systems used in building information modeling and uses them for modeling and simulating external factors in the built environment. By appropriate application of the methods, places of interest that are affected by the negative effects of air flow, or the spread of pollution through the built environment, were illustratively visualized. The presented study was created based on publicly available data on air pollution in the territory of Ostrava city.
Investigation of Passive Controlled Post-Tensioning System on the Structural Behaviour of Precast Reinforced Concrete Beam–Column Connections
Authors: Pekgokgoz Recep Kadir , Yakut Ihsan
Published: December 2024

Precast structures are widely used in many parts of the world. This construction technique is more commonly preferred for low-rise industrial buildings than multi-story structures. The most commonly used column–beam connection in precast buildings is the dowel connection (DC). Past earthquakes in various parts of the world have shown that these connections do not provide sufficient resistance. The main deficiencies of such connections are that they are sheared or stripped due to the shear force demand from the in-plane effects of large earthquakes, and that they do not provide sufficient resistance to the overturning moments from the out-of-plane effects of the earthquakes. Correspondingly, many prefabricated buildings have collapsed during earthquakes, causing loss of life and property. This study proposes using post-tensioning tendon (PT) systems and systems created by adding steel springs (PTS) to eliminate the weaknesses in column–beam connections in precast structures. To this end, real-sized column and beam specimens used in precast buildings were produced, and experiments were conducted under the cyclic loads defined by the American Concrete Institute (ACI) Committee, Report 374, simulating earthquake effects for three different connection types (DC, PT, and PTS). It was observed that the proposed PTS connection type dissipated approximately one-third of the energy transferred to the joint through elastic deformation in the springs, compared to the DC and PT connection types. This indicates that the PTS specimens transferred significantly less energy to the column–beam connection region. Consequently, the PTS system exhibited much less damage in the column foundation and especially the column–beam connection areas than other test specimens. In conclusion, it can be stated that the use of the PTS connection type in prefabricated structures has high potential to reduce damages due to dynamic loads such as earthquakes.
Layout Optimization of Residential Buildings to Improve the Outdoor Microclimate of Neighborhoods Along an Urban Bay: A Case Study of Shantou’s Inner Bay, China
Authors: Liu Wenqing , Miao Chang , Xiao Lei , Mai Junhang , Wang Yingzi
Published: December 2024

In summer, the urban heat island effect causes unbearable warmth in Shantou City, especially in the urban areas along the Inner Bay with densely populated neighborhoods. An investigation of the layout patterns of 100 residential neighborhoods along Shantou’s Inner Bay was conducted, leading to the establishment of four types and nine sub-types of idealized residential neighborhood models. Their wind speed, relative humidity, and air temperature were simulated in the ENVI-met software (version No.5.0.1). The simulation results show that high-rise buildings in the front areas play a decisive role in the overall microclimate environment. Accordingly, three principal drawbacks regarding neighborhood layout for thermal climate adaptation were extracted. Furthermore, by comparing the simulation results before and after modifying the layout of high-rise buildings, three spatial strategies to strengthen the humidification and cooling effect of sea–land breezes to optimize the outdoor microclimatic environment of neighborhoods were proposed, and these strategies were subsequently verified in the Golden-Harbor neighborhood.
Practical Repair Cost Assessment of Steel Office Buildings with Diverse Beam-to-Column Connection Types in Japan
Authors: Takaya Kazuki , Jin Jialiang , Nagae Takuya
Published: December 2024

This study investigates the seismic performance of beam-to-column connections in Japanese steel office buildings and evaluates their impact on repair costs as part of practical seismic loss assessment. Repair cost analysis is conducted following FEMA P-58 guidelines, utilizing a probabilistic seismic performance approach. Additionally, this study incorporates the damage and loss of non-structural components, accounting for uncertainties arising from various factors. By applying story loss functions and the Capacity Spectrum Method within the assessment framework of this study, the applicability of these methods in Japanese design practices is validated. A numerical model of a typical steel building is established based on prior experimental data, and a series of numerical analyses are conducted to quantitatively assess variations in building response distribution and fragility resulting from different beam-to-column connection types. Analysis results indicate that, within the range up to maximum strength, differences in connection performance contribute more to variations in fragility than to building response. Component fragility is particularly influenced by connection type and dimensions that affect inter-story drift ratios. This approach highlights the potential cost differences driven by structural specifications and emphasizes the importance of connection-specific fragility in accurately estimating seismic repair costs in practical design. Furthermore, improvements in structural performance have limited effects in reducing non-structural damage, underscoring the necessity of directly enhancing non-structural component performance.
Acute Promyelocytic Leukemia in the Real World: Understanding Outcome Differences and How We Can Improve Them
Authors: Bidikian Aram , Bewersdorf Jan Philipp , Kewan Tariq , Stahl Maximilian , Zeidan Amer M.
Published: December 2024

The advent of all-trans retinoic acid (ATRA) and arsenic trioxide (ATO) has revolutionized the treatment of acute promyelocytic leukemia (APL), resulting in excellent rates of remission and long-term survival. However, real-world outcomes often fall short of those observed in clinical trials due to various factors related to patient demographics and clinical practices. This review examines APL treatment outcomes in real-world settings and highlights the phenomenon of APL clusters. Clinical trials frequently exclude older patients and individuals with significant comorbidities, yet these groups represent a substantial portion of patients in clinical practice. Early mortality remains high in real-world settings, compounded by delayed diagnosis and treatment initiation, as well as the inexperience of some community providers and limited resources of their centers in managing APL and its associated complications. High rates of disease and induction-related complications further exacerbate early mortality. Continuous education and collaboration between community healthcare centers and expert institutions are essential, and international partnerships between resource-limited settings and expert centers can improve global APL outcomes. Ongoing monitoring for measurable residual disease (MRD) recurrence and long-term treatment toxicity, coupled with comprehensive patient evaluations, and experienced management, can enhance long-term outcomes. The clustered incidence of APL, while frequently reported, remains poorly understood. Regular reporting of these clusters could provide valuable insights into disease pathology and aid in developing predictive models for APL incidence, which would guide future resource allocation.
Senescence and Stress Signaling Pathways in Corneal Cells After Nitrogen Mustard Injury
Authors: Anwar Khandaker N. , Soleimani Mohammad , Ashraf Mohammad Javad , Moghtader Amirhossein , Koganti Raghuram , Ghalibafan Seyyedehfatemeh , Baharnoori Mahbod , Arabpour Zohreh , Cheraqpour Kasra , Sebhat Aron M. , Abtahi Mansour , Yao Xincheng , Ghassemi Mahmood , Djalilian Ali R.
Published: December 2024

Mustard gas keratopathy (MGK), a complication of exposure to sulfur mustard, is a blinding ocular surface disease involving key cellular pathways, including apoptosis, oxidative stress, and inflammation. Recent studies indicate that cellular senescence contributes to the pathophysiology of mustard gas toxicity. This study aimed to assess senescence and stress-related pathways—particularly mitogen-activated protein kinase (MAPK) signaling—in nitrogen mustard (NM)-induced corneal injury. In vitro, primary human corneal epithelial (P-HCECs), primary human corneal mesenchymal stromal cells (hcMSCs), and human corneal–limbal epithelial cell (HCLE) lines were exposed to varying concentrations of NM. The results demonstrated a dose-dependent increase in cellular senescence, characterized by reduced Ki67 expression, elevated p16, and p21 mRNA levels, as well as activation of the MAPK pathway activation. Treatment with a selective p38-MAPK inhibitor significantly reduced senescence markers and improved cell proliferation following exposure to NM. Overall, these studies indicate that NM exposure triggers cellular senescence and stress-related MAPK signaling, while p38-MAPK inhibition mitigates these effects, suggesting a potential therapeutic strategy.
8-(Pyridin-2-yl)quinolin-7-ol and Beyond: Theoretical Design of Tautomeric Molecular Switches with Pyridine as a Proton Crane Unit
Authors: Zaharieva Lidia , Nedeltcheva-Antonova Daniela , Antonov Liudmil
Published: December 2024

Long-range proton transfer in several conjugated proton cranes, originating from 7-hydroxy quinoline as a proton transfer platform, has been investigated theoretically by means of DFT and TD-DFT methodology. Major emphasis was given to their applicability to provide clean switching upon irradiation. The border conditions require the existence of a single enol tautomer in the ground state, which under excitation through a series of consecutive exited and ground state intramolecular proton transfer steps is transferred to the keto tautomer. It was shown that the most suitable candidates are based on using iso-quinoline, pyrimidine and 4-nitropyridine as proton crane units. Their suitability is a function of aromaticity changes, the basicity of the nitrogen atom from the proton crane unit and the structural effects originating from their conjugation with 7-hydroxy quinoline.
The Impact of the Interactive Floor Device and Aerobic Training on Executive Functions in Children
Authors: Rymarczyk Krystyna , Makowska Iwona , Hyniewska Sylwia
Published: December 2024

Background/Objectives: Considering the importance of physical activity on the development of cognitive functions in children, the aim of this study was to assess the effects of a ten-week training program using the Interactive Floor device (© Funtronic), i.e., a kinesthetic educational game, and aerobic activity training on executive functions in 9-year-old children. Given current knowledge of the advantages of gamification and on-task switching, stronger improvement was expected for the Interactive Floor device than aerobic exercise activities. Methods: Sixty-four children (29 boys/35 girls) were randomly assigned to the Interactive Floor (n = 22), Aerobic Training (n = 22), or Control groups (n = 20). The participants had their cognitive abilities assessed twice (pre- and post-intervention) using computer tests from the Vienna Test System (VTS) and subtests from the Wechsler Intelligence Scale for Children® Fifth Edition (WISC®-V). From VTS, the Stroop Test was used to measure inhibition and attentional control, while the Corsi Block test assessed visuospatial short-term working memory. To assess auditory working memory, the Digit Span subtest from the WISC®-V was applied. Additionally, fluid intelligence was estimated using Raven’s Progressive Matrices. Results: Repeated-measures mixed ANOVA and post hoc tests with Bonferroni correction for multiple comparisons showed that all intervention program groups improved in terms of intelligence and non-verbal abstract reasoning. The second significant finding in this study was that especially children from the Interactive Floor group developed their executive functions, i.e., inhibition and attentional control as well as their spatial short-term memory capacity. Conclusions: The results suggest that a combination of both physical exercise and cognitive games in the Interactive Floor group resulted in greater improvement in cognitive abilities in children than aerobic exercise or physical education lessons. It seems that a multidisciplinary approach combining physical and cognitive stimulation effectively promotes child development. Future programs aiming to improve cognitive skills in children should consider incorporating interactive and engaging activities that stimulate both the body and the mind.
The Dose Rate of Corpuscular Ionizing Radiation Strongly Influences the Severity of DNA Damage, Cell Cycle Progression and Cellular Senescence in Human Epidermoid Carcinoma Cells
Authors: Soroko Sergey S. , Skamnitskiy Dmitry V. , Gorshkova Ekaterina N. , Kutova Olga M. , Seriev Ismail R. , Maslennikova Anna V. , Guryev Evgeniy L. , Gudkov Sergey V. , Vodeneev Vladimir A. , Balalaeva Irina V. , Shilyagina Natalia Yu
Published: December 2024

Modern radiotherapy utilizes a broad range of sources of ionizing radiation, both low-dose-rate (LDR) and high-dose-rate (HDR). However, the mechanisms underlying specific dose-rate effects remain unclear, especially for corpuscular radiation. To address this issue, we have irradiated human epidermoid carcinoma A431 cells under LDR and HDR regimes. Reducing the dose rate has lower lethality at equal doses with HDR irradiation. The half-lethal dose after HDR irradiation was three times less than after LDR irradiation. The study of mechanisms showed that under HDR irradiation, the radiation-induced halt of mitosis with the accompanying emergence of giant cells was recorded. No such changes were recorded after LDR irradiation. The level of DNA damage is significantly greater after HDR irradiation, which may be the main reason for the different mechanisms of action of HDR and LDR irradiations. Comparing the mechanisms of cell response to LDR and HDR irradiations may shed light on the mechanisms of tumor cell response to ionizing radiation and answer the question of whether different dose rates within the same dose range can cause different clinical effects.
Cell-Free Carbonic Anhydrase IX mRNA in Urine as Biomarker for Urogenital Cancers: The Relationship Between Urinary Extracellular RNA and Tumor-Cell-Associated RNA
Authors: Malentacchi Francesca , Mancini Irene , Villari Donata , Forster Michael , Marzocco Andrea , Galli Ilaria Camilla , Viola Lorenzo , Masieri Lorenzo , Nesi Gabriella , Pinzani Pamela
Published: December 2024

Circulating tumor cells and cell-free nucleic acids are novel diagnostic, prognostic and predictive tools for non-invasive and cost-effective cancer detection in liquid biopsy. Carbonic anhydrase IX (CAIX) has been proposed as a biomarker in urogenital tumors and urine sediment. Our aim was to evaluate CAIX full-length percentage (CAIX FL%) in urine-cell-free RNA (cfRNA) and its relationship with tumor-cell-associated RNA (TC-RNA). CAIX FL% was quantified by reverse transcription quantitative polymerase chain reaction (RT-qPCR) in patients with prostate, kidney or bladder carcinoma. When cfRNA and TC-RNA were analyzed, CAIX FL% was significantly higher in urine samples from cancer patients than from controls. Using a 10% cutoff for CAIX FL%, specificity, sensitivity, positive and negative predictive values, as well as accuracy for TC-RNA were higher than for cfRNA in all urogenital cancers, but varied according to tumor type. CAIX FL% distribution in TC-RNA differed significantly (p < 0.001) between control and tumor samples (37.5% and 96.2%, respectively); similar results were obtained for each tumor type. Additionally, the 10% cutoff showed a 77.9% concordance between TC-RNA and cfRNA. In conclusion, urine is proposed as an alternative biofluid for investigating CAIX FL% in urogenital cancers, and this parameter can be reliably measured as cfRNA and TC-RNA with different predictive capabilities depending on tumor type.
Correction: Liu et al. Enhanced Osteogenic Activity and Antibacterial Properties of Graphene Oxide-Poly(Lactic Acid) Films for the Repair of Cranial Defects in Rats. Coatings 2024, 14, 223
Authors: Liu Kai , Lai Wen , Wu Jianyong , Lu Yongjian
Published: December 2024

In the original publication [...]
The Influence of the Assembly Unit of CO2-Cured Secondary Aluminum Ash and CO2-Cured Iron Tailings on High Performance Concrete’s Properties
Authors: Yu Hongrun , Chen Baolong , Zhang Zixuan , Wang Hui
Published: December 2024

This paper aims to study the influence of the assembly units of CO2-cured iron tailings (IOT) and CO2-cured secondary aluminum ash (SAA) on the fresh high-performance concrete’s (HPC’s) slump flow and setting time. The mechanical properties including the flexural strength, compressive strength, the bonding strength and the dry shrinkage rate of the hardened HPC are measured. The amount of leached Cr and Zn after immersing in deionized water for 1 month~6 months is measured. The influence of the basalt fibers’ volume ratio and the aspect ratio of the high-performance concrete’s performance is considered. The scanning electron microscopy energy spectrums (SEM-EDS) are obtained. The results show that the slump flow and the setting time of fresh HPC are increased by the added CO2-cured SAA and IOT. The fresh HPC with 10% CO2-cured IOT and 20% CO2-cured SAA had the highest slump flow. The slump flow decreases in the form of cubic function with the placing time. The mechanical strengths and the dry shrinkage rate of HPC during the early curing ages (cured for 0.5 day~7 days) are decreased by the CO2-cured SAA and CO2-cured IOT, while the mechanical strengths at later curing ages (14 days~90 days) are increased by the added CO2-cured SAA and CO2-cured IOT. HPC with 10% CO2-cured SAA and 20% CO2-cured IOT shows the highest mechanical strengths. The amount of leached Cr and Zn is decreased by the CO2 cured SAA and IOT. The relationship between the mechanical strengths and the curing time coincides with the cubic equation. The basalt fibers with a volume ratio of 2% and aspect ratio of 1000 show the highest mechanical strengths, the lowest dry shrinkage rate and the least amount of leached Cr and Zn. CO2-cured SAA and IOT can improve the compactness of HPC’s hydration products. HPC with 10% CO2-cured SAA and 20% CO2-cured IOT shows the highest compact hydration products.
Enhancing the Efficiency of Solar Cells Based on TiO2 and ZnO Photoanodes Through Copper Oxide: A Comparative Study Using Vitis labrusca Extract and N3 Ruthenium Dye
Authors: da Cunha Higor Oliveira , Leite Arcano Matheus Bragança , Babu Rajendran Suresh , Gama Filho Hamilton Santos , dos Santos Ramon Silva , dos Anjos Marcelino José , de Barros Ana Lucia Ferreira
Published: December 2024

This study investigates the effects of varying CuO doping concentrations on the performance of titanium dioxide (TiO2)-based or zinc oxide (ZnO)-based dye-sensitized solar cells (DSSCs). TiO2 or ZnO mixed with CuO at different weight percentages (0–50 wt %) was employed as photoanodes in DSSCs, prepared via mechanical mixing. X-ray diffraction analysis revealed the structural changes, showing that as the CuO content increased in the hybrid, the CuO peaks (notably at 35.5° and 38.7°) became more prominent. Morphological and elemental characterizations were conducted using SEM and XRF, respectively. The solar cells were photosensitized by Vitis lasbrusca (V.L.) extract and N3 dye. The presence of anthocyanin molecules in the extracted V.L. was confirmed using UV-VIS and FTIR spectroscopy. The electrochemical characterization demonstrated optimal solar conversion efficiencies at a 20% doping level for both photosensitizers. Specifically, in the V.L. dye, TiO2-CuO achieved a conversion efficiency of 7.18%, and ZnO-CuO reached 5.77%. In the N3 dye, TiO2-CuO showed an efficiency of 11.34%, and ZnO-CuO, 9.55%. Notably, undoped photoanodes displayed a significantly lower photovoltaic performance: for V.L. dye, TiO2 showed 1.12% and ZnO 0.87%; for N3 dye, TiO2 showed 6.02% and ZnO 4.39%. Doping was therefore effective, yielding up to a seven-fold increase in performance in the case of V.L. with TiO2, compared to undoped DSSCs. The results demonstrate that using the hybrid photoanode led to a considerable increase in performance compared to using only TiO2 or ZnO photoanodes, highlighting the potential of DSSCs as sustainable energy sources.
Integrative Machine Learning, Virtual Screening, and Molecular Modeling for BacA-Targeted Anti-Biofilm Drug Discovery Against Staphylococcal Infections
Authors: Almatroudi Ahmad
Published: December 2024

The rise in antibiotic-resistant Staphylococcal infections necessitates innovative approaches to identify new therapeutic agents. This study investigates the application of machine learning models to identify potential phytochemical inhibitors against BacA, a target related to Staphylococcal infections. Active compounds were retrieved from BindingDB while the decoy was generated from DUDE. The RDKit was utilized for feature engineering. Machine learning models such as k-nearest neighbors (KNN), the support vector machine (SVM), random forest (RF), and naive Bayes (NB) were trained on an initial dataset consisting of 226 active chemicals and 2550 inert compounds. Accompanied by an MCC of 0.93 and an accuracy of 96%, the RF performed better. Utilizing the RF model, a library of 9000 phytochemicals was screened, identifying 300 potentially active compounds, of which 192 exhibited drug-like properties and were further analyzed through molecular docking studies. Molecular docking results identified Ergotamine, Withanolide E, and DOPPA as top inhibitors of the BacA protein, accompanied by interaction affinities of −8.8, −8.1, and −7.9 kcal/mol, respectively. Molecular dynamics (MD) was applied for 100 ns to these top hits to evaluate their stability and dynamic behavior. RMSD, RMSF, SASA, and Rg analyses showed that all complexes remained stable throughout the simulation period. Binding energy calculations using MMGBSA analysis revealed that the BacA_Withanolide E complex exhibited the most favorable binding energy profile with significant van der Waals interactions and a substantial reduction in gas-phase energy. It also revealed that van der Waals interactions contributed significantly to the binding stability of Withanolide E, while electrostatic interactions played a secondary role. The integration of machine learning models with molecular docking and MD simulations proved effective in identifying promising phytochemical inhibitors, with Withanolide E emerging as a potent candidate. These findings provide a pathway for developing new antibacterial agents against Staphylococcal infections, pending further experimental validation and optimization.
Peripheral Neuropathy Instruments for Individuals with Cancer: A COSMIN-Based Systematic Review of Measurement Properties
Authors: Belloni Silvia , Magon Arianna , Giacon Chiara , Savioni Francesca , Conte Gianluca , Caruso Rosario , Arrigoni Cristina
Published: December 2024

Although the literature on patient-reported outcomes (PROMs) continues to expand, challenges persist in selecting reliable and valid instruments for assessing peripheral neuropathy (PN) in patients with cancer. This systematic review aimed to identify all validated self-report PN scales and critically appraise their measurement properties. This review was conducted using the COSMIN methodology for PROMs and the PRISMA statement. Five databases were searched from inception to August 2024, identifying 46 eligible studies and 16 PROMs. Evidence quality ranged from “very low” to “moderate”, with notable inconsistencies in the content and structural validity phases of most instruments. Instruments such as the Chemotherapy-induced peripheral neuropathy assessment tool and the Functional Assessment of Cancer Therapy/Gynecologic Oncology Group–Neurotoxicity demonstrated moderate quality and potential utility in clinical practice, while others, including the Location-based assessment of sensory symptoms in cancer and the Measure of Ovarian Symptoms and Treatment, had insufficient evidence to support their use. Importantly, all PROMs focused on chemotherapy-induced peripheral neuropathy, highlighting a significant gap in instruments addressing other PN causes, such as radiotherapy or tumor-related nerve damage. Further research should prioritize developing and validating instruments for distinct cancer populations, ensuring robust psychometric properties and clinical applicability.
Nearest-Better Network-Assisted Fitness Landscape Analysis of Contaminant Source Identification in Water Distribution Network
Authors: Diao Yiya , Li Changhe , Zeng Sanyou , Yang Shengxiang
Published: December 2024

Contaminant Source Identification in Water Distribution Network (CSWIDN) is critical for ensuring public health, and optimization algorithms are commonly used to solve this complex problem. However, these algorithms are highly sensitive to the problem’s landscape features, which has limited their effectiveness in practice. Despite this, there has been little experimental analysis of the fitness landscape for CSWIDN, particularly given its mixed-encoding nature. This study addresses this gap by conducting a comprehensive fitness landscape analysis of CSWIDN using the Nearest-Better Network (NBN), the only applicable method for mixed-encoding problems. Our analysis reveals for the first time that CSWIDN exhibits the landscape features, including neutrality, ruggedness, modality, dynamic change, and separability. These findings not only deepen our understanding of the problem’s inherent landscape features but also provide quantitative insights into how these features influence algorithm performance. Additionally, based on these insights, we propose specific algorithm design recommendations that are better suited to the unique challenges of the CSWIDN problem. This work advances the knowledge of CSWIDN optimization by both qualitatively characterizing its landscape and quantitatively linking these features to algorithms’ behaviors.
Late Enhancement Computed Tomography for Left Atrial Fibrosis Imaging: A Pilot “Proof-of-Concept” Study
Authors: Lacaita Pietro G. , Beyer Christoph , Plank Fabian , Stühlinger Markus , Feuchtner Gudrun M.
Published: December 2024

Background/Objective: Left atrial (LA) fibrosis imaging improves the guidance of LA catheter ablation. Cardiac computed tomography (CT) may be a reasonable alternative to CMR. The aim was to evaluate late enhancement (LE) fibrosis mapping by CT, and to correlate the results with low-voltage areas on electroanatomical mapping (EAM). Methods: In patients with atrial fibrillation who underwent 128-slice dual-source CT angiography (CTA) prior to LA catheter ablation, an additional LE-CT scan was performed 7 min after CTA. (1) Left atrial wall thickness (LAWT) was measured at three sites along the LA ridge. (2) Late enhancement (LE) was quantified co-axially aligned to LAWT and compared with low-voltage areas (LVA) on EAM. Results: Of 137 patients (age: 59.8 years; 27.7% females), 108 were included. The prevalence of LE was higher in patients with LAWT > 2 mm compared with 1.5 mm, with 78 (91.7%) vs. 77 (80.2%) (p = 0.022). Of 78 patients with LE, 60 (77.1%) had focal, 13 (16.5%) had diffuse, and 5 (6.3%) had mixed LE patterns. The CT density of focal LE was not different from that of diffuse patterns (104.2 +/− 21 HU vs. 98.9 +/− 18 HU; p = 0.360). Increasing LAWT and LE-HU were weakly correlated (r = 0.229; p = 0.041). LA wall artifacts had higher CT density compared with LE (154.1 HU vs. 114.2 HU; p = 0.002). The effective radiation dose was 0.95 mSv (range, 0.52–1.2 mSv) for LE-CT. The agreement of LE-CT was 80% for LVA < 0.5 mV and 86.6% for LVA < 0.7 mV in a subset of 30 patients. Conclusions: Left atrial fibrosis mapping by LE-CT is feasible. Late enhancement was found more frequently in LAWTs of more than 2 mm, and LE was correlated with increasing LA remodeling and low-voltage areas.
Adapting SAM2 Model from Natural Images for Tooth Segmentation in Dental Panoramic X-Ray Images
Authors: Li Zifeng , Tang Wenzhong , Gao Shijun , Wang Yanyang , Wang Shuai
Published: December 2024

Dental panoramic X-ray imaging, due to its high cost-effectiveness and low radiation dose, has become a widely used diagnostic tool in dentistry. Accurate tooth segmentation is crucial for lesion analysis and treatment planning, helping dentists to quickly and precisely assess the condition of teeth. However, dental X-ray images often suffer from noise, low contrast, and overlapping anatomical structures, coupled with limited available datasets, leading traditional deep learning models to experience overfitting, which affects generalization ability. In addition, high-precision deep models typically require significant computational resources for inference, making deployment in real-world applications challenging. To address these challenges, this paper proposes a tooth segmentation method based on the pre-trained SAM2 model. We employ adapter modules to fine-tune the SAM2 model and introduce ScConv modules and gated attention mechanisms to enhance the model’s semantic understanding and multi-scale feature extraction capabilities for medical images. In terms of efficiency, we utilize knowledge distillation, using the fine-tuned SAM2 model as the teacher model for distilling knowledge to a smaller model named LightUNet. Experimental results on the UFBA-UESC dataset show that, in terms of performance, our model significantly outperforms the traditional UNet model in multiple metrics such as IoU, effectively improving segmentation accuracy and model robustness, particularly with limited sample datasets. In terms of efficiency, LightUNet achieves comparable performance to UNet, but with only 1.6% of its parameters and 24.0% of the inference time, demonstrating its feasibility for deployment on edge devices.
Interplay of Spin Nernst Effect and Entanglement Negativity in Layered Ferrimagnets: A Study via Exact Diagonalization
Authors: Lima Leonardo S.
Published: December 2024

In this paper, we analyzed the influence of the spin Nernst effect on quantum correlation in a layered ferrimagnetic model. In the study of three-dimensional ferrimagnets, the focus is on materials with a specific arrangement of spins, where the neighboring spins are parallel and the others are antiparallel. The anisotropic nature of these materials means that the interactions between spins depend on their relative orientations in different directions. We analyzed the effect of magnon bands induced by the coupling parameters on entanglement negativity. The influence of the coupling parameters of the topologic phase transition on quantum entanglement is investigated as well. Numerical simulations using the Lanczos algorithm and exact diagonalization for different lattice sizes are compared with the results of spin wave theory.
Research on Distributed Secure Storage Framework of Industrial Internet of Things Data Based on Blockchain
Authors: Tian Hongliang , Huang Guangtao
Published: December 2024

The conventional centralized Industrial Internet of Things (IIoT) framework is plagued by issues like subpar security performance and challenges related to storage expansion. This paper proposes a two-tier distributed secure storage framework based on blockchain for IIoT data. The authors first introduce the two-layer framework, which includes the edge network layer and the blockchain storage layer. The nodes in the edge network layer are classified into administrator nodes and ordinary nodes. It provides a lower latency network environment compared to cloud computing to preprocess raw industrial data. The blockchain storage layer provides storage space to keep data secure and traceable. Secondly, the authors propose a differentiated storage solution. Based on the timestamps of industrial data and the specific media access control (MAC) address, the Universally Unique Identifier (UUID) of the raw data is generated and uploaded to the blockchain for secure storage. Encrypt the corresponding raw data using the elliptic curve cryptography algorithm, and then upload it to InterPlanetary File System (IPFS) to expand the storage capacity of the blockchain. Deploy a smart contract on the blockchain to compare UUIDs for consistency in an automated, lightweight method to determine data integrity. Finally, we analyze the advantages brought by the integration of blockchain and IIoT. Additionally, the authors design comparative tests on different storage methods. The results prove that the security of this paper’s scheme is improved, and the storage performance is extended. Noteworthy enhancements include heightened throughput of data uploaded to the blockchain and minimized delay overhead.
Enhanced Solar Power Prediction Using Attention-Based DiPLS-BiLSTM Model
Authors: Zhong Yuanchang , He Tengfei , Mao Zhongyuan
Published: December 2024

The data for solar power generation contain a huge amount of data with a large number of features which are difficult to extract effectively. It is important for the grid management and operational efficiency of the solar farm to accurately predict the solar power. The existing prediction models utilize historical data but often fail to capture critical latent features. This limitation leads to overlooked complex dependencies or temporal relationships, reducing prediction accuracy, especially in load and generation forecasting. An attention-based dynamic inner partial least squares (DiPLS) model and a bidirectional long short-term memory (BiLSTM) model were used for solar power prediction. First, DiPLS is used to dynamically extract features, and then, an attention process is used to predict the importance of these features. Finally, the raw sets are input to the BiLSTM model to make predictions of solar power in the future. The proposed method improves prediction accuracy, achieving an R2 value of 0.965 for training and 0.961 for testing, compared to conventional models. Additionally, the method demonstrated lower root mean squared error (RMSE), indicating enhanced stability and accuracy for solar power forecasting.
A SiC Photo-Conductive Switch-Based Pulse Generator with Nanoseconds and High Voltage for Liver Cancer Cells Ablation Therapy
Authors: Yin Haocheng , Zhang Zeyu , Liu Yapeng , Wang Yutian , Guo Hui , Zhang Yuming
Published: December 2024

Electroporation ablation, as an innovative cancer treatment, not only preserves the structure and function of affected organs but also significantly reduces surgical risks, offers patients a safer and more effective therapeutic option, and demonstrates immense potential in the field of oncology. This paper presents the innovative design of a high-voltage nanosecond pulse generator triggered by a silicon carbide (SiC) photoconductive switch. The generator is capable of stably outputting adjustable voltages ranging from 10 kV to 15 kV, with pulse widths precisely controlled between 10 and 15 nanoseconds, and an operating frequency adjustable from 1 Hz to 10 Hz. This device enables instant activation and deactivation of the pulse generator during ablation, enhancing the efficiency of strong electric field applications and preventing overtreatment due to delayed shutdown. This paper introduces the structure and basic principles of this novel SiC photoconductive switch-triggered pulse device and reports on the impact of device-related pulse parameters on the ablation effect of hepatocellular carcinoma cells through cell experiments. Under optimal ablation parameters, the CCK8 results show that the number of viable cells is only 0.7% of that in the untreated control group after 12 h of subculture following ablation. These findings hold significant importance for expanding the application areas of SiC devices.
Revealing Occult Malignancies in Mammograms Through GAN-Driven Breast Density Transformation
Authors: Anyfantis Dionysios , Koutras Athanasios , Apostolopoulos George , Christoyianni Ioanna
Published: December 2024

Breast cancer remains one of the primary causes of cancer-related deaths among women globally. Early detection via mammography is essential for improving prognosis and survival rates. However, mammogram diagnostic accuracy is severely hindered by dense breast tissue, which can obstruct potential malignancies, complicating early detection. To tackle this pressing issue, this study introduces an innovative approach that leverages Generative Adversarial Networks (GANs), specifically CycleGAN and GANHopper, to transform breast density in mammograms. The aim is to diminish the masking effect of dense tissue, thus enhancing the visibility of underlying malignancies. The method uses unsupervised image-to-image translation to gradually alter breast density (from high (ACR-D) to low (ACR-A)) in mammographic images, detecting obscured lesions while preserving original diagnostic features. We applied this approach to multiple mammographic datasets, demonstrating its effectiveness in diverse contexts. Experimental results exhibit substantial improvements in detecting potential malignancies concealed by dense breast tissue. The method significantly improved precision, recall, and F1-score metrics across all datasets, revealing previously obscured malignancies and image quality assessments confirmed the diagnostic relevance of transformed images. The study introduces a novel mammogram analysis method using advanced machine-learning techniques, enhancing diagnostic accuracy in dense breasts and potentially improving early breast cancer detection and patient outcomes.