bluuebunny/crossref_metadata_2025 huggingface dataset:
Event-Related Desynchronization of MEG Alpha-Band Oscillations during Simultaneous Presentation of Audio and Visual Stimuli in Children with Autism Spectrum Disorder
Authors: Arutiunian Vardan , Arcara Giorgio , Buyanova Irina , Buivolova Olga , Davydova Elizaveta , Pereverzeva Darya , Sorokin Alexander , Tyushkevich Svetlana , Mamokhina Uliana , Danilina Kamilla , Dragoy Olga
Published: September 2023

Alpha-band (8–12 Hz) event-related desynchronization (ERD) or a decrease in alpha power in electro- and magnetoencephalography (EEG and MEG) reflects the involvement of a neural tissue in information processing. It is known that most children with autism spectrum disorder (ASD) have difficulties in information processing, and, thus, investigation of alpha oscillations is of particular interest in this population. Previous studies have demonstrated alterations in this neural activity in individuals with ASD; however, little is known about alpha ERD during simultaneous presentation of auditory and visual stimuli in children with and without ASD. As alpha oscillations are intimately related to attention, and attention deficit is one of the common co-occurring conditions of ASD, we predict that children with ASD can have altered alpha ERD in one of the sensory domains. In the present study, we used MEG to investigate alpha ERD in groups of 20 children with ASD and 20 age-matched typically developing controls. Simple amplitude-modulated tones were presented together with a fixation cross appearing on the screen. The results showed that children with ASD had a bilateral reduction in alpha-band ERD in the auditory but not visual cortex. Moreover, alterations in the auditory cortex were associated with a higher presence of autistic traits measured in behavioral assessment.
The Impact of Sustainable Exercise on Self-Efficacy and Life Satisfaction in Women before and after Menopause
Authors: Kulak Abdulaziz , Toros Turhan , Ogras Emre Bulent , Etiler Ibrahim Efe , Bagci Emre , Gokyurek Belgin , Bilgin Ulviye
Published: September 2023

The study aims at elucidating the association between sustainable exercise and its influence on self-efficacy and life satisfaction in women during their premenopausal and postmenopausal stages. A relational screening model was employed on a sample of 422 women, with 215 premenopausal and 207 postmenopausal participants, utilizing convenience sampling. Participants’ regularity of exercise and its duration was taken into consideration. Evaluation tools included the General Self-Efficacy Scale (GSES) and the Satisfaction with Life Scale (SWLS). Data were analyzed using a statistical software package with significance set at 0.05. Sustainable exercise demonstrated no significant difference in SWLS or GSES subdimensions among premenopausal women. However, postmenopausal women engaging in regular exercise reported significantly higher scores in SWLS and all GSES subdimensions. Moreover, positive correlations between age and SWLS scores, as well as between age and certain GSES subdimensions, were found in both pre- and postmenopausal periods. While sustainable exercise does not evidently impact the life satisfaction and self-efficacy of premenopausal women, it significantly enhances these parameters in postmenopausal women. Additionally, age appears to influence life satisfaction and specific self-efficacy subdimensions across both phases.
A Stress Measurement Method for Steel Strands Based on Spatially Self-Magnetic Flux Leakage Field
Authors: Liu Shangkai , Cheng Cheng , Zhao Ruiqiang , Zhou Jianting , Tong Kai
Published: September 2023

Metal Magnetic Memory (MMM) exhibits the advantage of not requiring embedded sensors or external excitation, making it suitable for inspecting ferromagnetic components in engineering structures. This study introduced MMM into stress detection of steel strands. Graded tensile tests were conducted on the steel strands to investigate the correlation between Self-Magnetic Flux Leakage (SMFL) signals and stress levels. Different spatial detection positions with varying Lift-Off Values (LOV) and Rotation Angle Values (RAV) were set to examine the distribution of spatial SMFL field under load. Furthermore, a magnetic characteristic parameter AN was proposed to assess the stress level of the steel strands. The results indicate that the rate of change in the middle region of the SMFL curve was lower than that at the beginning and the end. Additionally, with increased applied load, the SMFL curve exhibited systematic variations, and the dispersion of the normal component curve gradually decreased. By utilizing the magnetic characteristic parameter AN, the stress in the steel strands can be calculated, with the parameters determined based on LOV and RAV. This achievement expanded the nondestructive testing methods for steel strands and holds significant research value.
A Human Detection Approach for Intrusion in Hazardous Areas Using 4D-BIM-Based Spatial-Temporal Analysis and Computer Vision
Authors: Tran Si Van-Tien , Lee Doyeop , Bao Quy Lan , Yoo Taehan , Khan Muhammad , Jo Junhyeon , Park Chansik
Published: September 2023

Detecting intrusion in hazardous areas is one of the priorities and duties of safety enhancement. With the emergence of vision intelligence technology, hazardous-area-detection algorithms can support safety managers in predicting potential hazards and making decisions. However, because of the dynamic and complex nature of the jobsite, high-risk zones have a different geometry and can be changed following the schedule and workspace of activity. This leads to hazardous areas being annotated manually. Thus, this study proposes a computer vision and a 4D BIM-based approach for intrusion detection in hazardous areas, called IDC4D. IDC4D comprises three modules: (1) the 4D BIM-based safety planning (4BSP) module, which analyzes the hazardous area; (2) the hazardous area registration (HAR) module, which delivers the hazardous area from the BIM model to the camera’s first frame image; and (3) the hazardous-area-intrusion-detection module (HAID), which applies the computer vision algorithm to identify the correlation between workers and hazardous areas. The efficiency of the IDC4D approach is validated by testing a maintenance project on the construction site. IDC4D supports the planner in choosing the plan and detecting the event of workers entering hazardous areas while working. It showed an average precision of 93% and 94% in phase 1 and phase 2, respectively. These findings provide insight into how varying geometries of diverse hazard areas can be handled for enhancing intrusion detection.
A Comprehensive Review of the Improvement of the Thermal and Mechanical Properties of Unfired Clay Bricks by Incorporating Waste Materials
Authors: Lachheb Mohamed , Youssef Nicolas , Younsi Zohir
Published: September 2023

In recent years, the construction sector has significantly increased demand for new building materials that can reduce environmental impact and promote sustainable design strategies. In this context, the use of earth for construction purposes has received increasing attention in the last decade owing to its low environmental impact, local availability, and recyclability. The literature survey indicates that the incorporation of waste materials in the production of unfired earth bricks holds significant potential to partly substitute earth by satisfying specific requirements. Additionally, utilizing these waste materials for the development of unfired earth bricks provides a solution that conserves natural resources, reduces energy consumption, and contributes to efficient waste management. The aim of this paper is to present an overview of recent research focusing on the recycling of various types of waste into eco-friendly unfired earth bricks. Also, the effect of the incorporation of waste materials on the thermal and mechanical properties of unfired clay bricks is reviewed. The most common results, organized based on the type of additive (industrial or agricultural waste), are shown and discussed.
Developing Nomographs for the Unit Weight of Soils
Authors: Dungca Jonathan , Galupino Joenel
Published: September 2023

Engineers have created increasingly complex correlations based on laboratory and field tests. Over time, geotechnical engineering modeling techniques have evolved from simple analytical methods to complex numerical modeling techniques. Nomographs are traditional computational tools that have been widely employed in engineering. Combining nomographs with computational tools such as numerical models and machine learning algorithms can lead to better outcomes. Thus, this study aimed to develop a nomograph for geotechnical engineering that incorporates machine learning, specifically for the unit weight of soil. Four calibrated models were developed to determine the unit weight of soil: the moist unit weight of coarse-grained soil, the saturated unit weight of coarse-grained soil, the moist unit weight of fine-grained soil, and the saturated unit weight of fine-grained soil. An uncertainty test was conducted for the data used. Our results indicated a strong positive relationship to most of the models. The generated nomographs were tested in Malabon, a city in Metro Manila, where a low unit weight of soil was determined. This low unit weight was validated by the predominance of alluvial deposits and the shallow groundwater table, which soften and weaken the soil.
Identification of Damage in Planar Multistory Reinforced Concrete Frames Developing a Beam-Sway Plastic Mechanism Using the “M and P” Technique
Authors: Makarios Triantafyllos K. , Bakalis Athanasios P.
Published: September 2023

The effectiveness of a recently proposed methodology for the identification of damage in planar, multistory, reinforced concrete (RC) moment frames, which develop a plastic yield mechanism on their beams, is showcased here via the examining of a group of such existing multistory frames with three or more unequal spans. According to the methodology, the diagram of the instantaneous eigenfrequencies of the frame in the nonlinear regime is drawn as a function of the inelastic seismic roof displacement by the performance of a sequence of pushover and instantaneous modal analyses with gradually increasing target displacement. Using this key diagram, the locations of severe seismic damage in an existing moment frame can be evaluated if the instantaneous fundamental eigenfrequency of the damaged frame, at an analysis step within the nonlinear area, is known in advance by “the monitoring and the identification of frequencies” using a local network of uniaxial accelerometers. This is a hybrid technique because both procedures, the instrumental monitoring of the structure and the pushover analysis on the frame (M and P technique), are combined. A ductile, five-story, planar RC moment frame with three unequal spans is evaluated in this paper by the M and P technique. The results show that the seismic roof displacement, the lateral stiffness matrix, and, finally, the damage image of this existing frame, are fully compatible with the eigenfrequencies identified by the monitoring and are calculated with high accuracy.
Low-Field Nuclear Magnetic Resonance Investigation on Early Hydration Characterization of Cement Paste Mixed with Mineral Admixtures
Authors: Tang Yu-Juan , Shan Zi-Qi , Yin Guang-Ji , Miao Ling , Wang Sai-Sai , Zhang Zhen-Ya
Published: September 2023

Mineral admixtures (MA), like fly ash (FA), silica fume (SF), and slag (S), are usually added to cement-based materials to improve their compactness and further enhance their mechanical properties, permeability resistance, and durability. In this study, low-field nuclear magnetic resonance (LF-NMR) is adopted to explore the evolution of the early hydration characterization of cement-based materials with MA by testing the transverse relaxation time T2. Meanwhile, the effect of MA on mechanical properties is analyzed by measuring compressive and flexural strength. The results show that, in the early hydration (0–7 days), the T2 distribution shows a trend of gradually moving to a short relaxation time and changes from a double peak to a single main peak. The decrease in T2i (main peak vertex) means that the evaporated water is gradually distributed in smaller pores with more motion constraints. However, the type and content of MA have little effect on T2i. Porosity gradually decreases in the period of early hydration. The addition of MA causes the porosity to decrease, and the order influence is FA > S > SF, i.e., the porosities of cement paste with 0%MA, 10%FA + 10%SF, 10%FA + 10%S, and 20%FA at 7 days are 48%, 44.5%, 40.7%, and 40.2%, respectively. Additionally, the addition of MA to cement-based materials also decreases the early strength, and the influence order is FA > S > SF, i.e., the compression strength values of cement paste with 0%MA, 10%FA + 10%SF, 10%FA + 10%S, and 20%FA at 7 days are 47.8 MPa, 40.1 MPa, 38.6 MPa, and 37 MPa, respectively.
Experimental Study on the Seismic Performance of L-Shaped CFST Columns in Different Combinations
Authors: Han Dongji , Tao Zhong , Abdul Ghafar Wahab , Hasan Md Mehedi , Xiao Weichao , Wang Tao , Zhou Kun , Dai Hongye
Published: September 2023

L-shaped concrete-filled steel tubular (CFST) columns represent a valuable structural element with an L-shaped cross-section, primarily employed in the corner columns of framed structures. These columns offer several advantages, including space efficiency by avoiding column protrusion, robust mechanical properties, high load-bearing capacity, ductility, and efficient utilization of internal building space. This article presents the outcomes of an experimental investigation into the seismic behavior of L-shaped CFST columns. The experimental study investigated the seismic performance of nine L-shaped CFST columns while considering different cross-sectional dimensions, their combinations, and varying levels of confinement. The results obtained from this study indicate that L-shaped CFST columns possess favorable seismic performance characteristics. However, there exists the potential for significant improvement by modifying certain parameters. Enhancements in seismic performance were observed when increasing the cross-sectional dimensions of the column and the length of its legs. The use of steel tubes and the provision of adequate confinement also demonstrated notable benefits. Moreover, the better arrangement of steel tubes within the column positively influenced seismic performance. These findings can potentially inform and enhance the design of L-shaped CFST columns, rendering them more resilient to seismic forces.
A Radiomic-Based Machine Learning Model Predicts Endometrial Cancer Recurrence Using Preoperative CT Radiomic Features: A Pilot Study
Authors: Coada Camelia Alexandra , Santoro Miriam , Zybin Vladislav , Di Stanislao Marco , Paolani Giulia , Modolon Cecilia , Di Costanzo Stella , Genovesi Lucia , Tesei Marco , De Leo Antonio , Ravegnini Gloria , De Biase Dario , Morganti Alessio Giuseppe , Lovato Luigi , De Iaco Pierandrea , Strigari Lidia , Perrone Anna Myriam
Published: September 2023

Background: Current prognostic models lack the use of pre-operative CT images to predict recurrence in endometrial cancer (EC) patients. Our study aimed to investigate the potential of radiomic features extracted from pre-surgical CT scans to accurately predict disease-free survival (DFS) among EC patients. Methods: Contrast-Enhanced CT (CE-CT) scans from 81 EC cases were used to extract the radiomic features from semi-automatically contoured volumes of interest. We employed a 10-fold cross-validation approach with a 6:4 training to test set and utilized data augmentation and balancing techniques. Univariate analysis was applied for feature reduction leading to the development of three distinct machine learning (ML) models for the prediction of DFS: LASSO-Cox, CoxBoost and Random Forest (RFsrc). Results: In the training set, the ML models demonstrated AUCs ranging from 0.92 to 0.93, sensitivities from 0.96 to 1.00 and specificities from 0.77 to 0.89. In the test set, AUCs ranged from 0.86 to 0.90, sensitivities from 0.89 to 1.00 and specificities from 0.73 to 0.90. Patients classified as having a high recurrence risk prediction by ML models exhibited significantly worse DSF (p-value < 0.001) across all models. Conclusions: Our findings demonstrate the potential of radiomics in predicting EC recurrence. While further validation studies are needed, our results underscore the promising role of radiomics in forecasting EC outcomes.
MRI Radiomics-Based Machine Learning Models for Ki67 Expression and Gleason Grade Group Prediction in Prostate Cancer
Authors: Qiao Xiaofeng , Gu Xiling , Liu Yunfan , Shu Xin , Ai Guangyong , Qian Shuang , Liu Li , He Xiaojing , Zhang Jingjing
Published: September 2023

Purpose: The Ki67 index and the Gleason grade group (GGG) are vital prognostic indicators of prostate cancer (PCa). This study investigated the value of biparametric magnetic resonance imaging (bpMRI) radiomics feature-based machine learning (ML) models in predicting the Ki67 index and GGG of PCa. Methods: A total of 122 patients with pathologically proven PCa who had undergone preoperative MRI were retrospectively included. Radiomics features were extracted from T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and apparent diffusion coefficient (ADC) maps. Then, recursive feature elimination (RFE) was applied to remove redundant features. ML models for predicting Ki67 expression and GGG were constructed based on bpMRI and different algorithms, including logistic regression (LR), support vector machine (SVM), random forest (RF), and K-nearest neighbor (KNN). The performances of different models were evaluated with receiver operating characteristic (ROC) analysis. In addition, a joint analysis of Ki67 expression and GGG was performed by assessing their Spearman correlation and calculating the diagnostic accuracy for both indices. Results: The ML model based on LR and ADC + T2 (LR_ADC + T2, AUC = 0.8882) performed best in predicting Ki67 expression, and ADC_wavelet-LHH_firstorder_Maximum had the highest feature weighting. The SVM_DWI + T2 (AUC = 0.9248) performed best in predicting GGG, and DWI_wavelet HLL_glcm_SumAverage had the highest feature weighting. The Ki67 and GGG exhibited a weak positive correlation (r = 0.382, p < 0.001), and LR_ADC + DWI had the highest diagnostic accuracy in predicting both (0.6230). Conclusion: The proposed ML models are suitable for predicting both Ki67 expression and GGG in PCa. This algorithm could be used to identify indolent or invasive PCa with a noninvasive, repeatable, and accurate diagnostic method.
Silk Peptide Ameliorates Sarcopenia through the Regulation of Akt/mTOR/FoxO3a Signaling Pathways and the Inhibition of Low-Grade Chronic Inflammation in Aged Mice
Authors: Oh Hyun-Ji , Jin Heegu , Lee Jeong-Yong , Lee Boo-Yong
Published: September 2023

As populations around the world age, interest in healthy aging is growing. One of the first physical changes that occurs with aging is the loss of muscle mass and strength, termed sarcopenia. Sarcopenia limits the activity of older people, reduces their quality of life, and increases the likelihood of their developing disease. In the present study, we aimed to evaluate the effects of the ingestion of acid-hydrolyzed silk peptide (SP) on the muscle mass and strength of mice of >22 months of age with naturally occurring sarcopenia, and to identify the mechanisms involved. The daily administration of SP for 8 weeks increased the activation of the Akt/mTOR/FoxO3a signaling pathways and increased the muscle mass and strength of the old mice. In addition, SP inhibited oxidative stress and inflammation in muscle, which are direct causes of sarcopenia. Therefore, SP represents a promising potential treatment for sarcopenia that may improve the healthy lifespan and quality of life of older people.
Morphofunctional Investigation in a Transgenic Mouse Model of Alzheimer’s Disease: Non-Reactive Astrocytes Are Involved in Aβ Load and Reactive Astrocytes in Plaque Build-Up
Authors: Lana Daniele , Branca Jacopo Junio Valerio , Delfino Giovanni , Giovannini Maria Grazia , Casamenti Fiorella , Nardiello Pamela , Bucciantini Monica , Stefani Massimo , Zach Petr , Zecchi-Orlandini Sandra , Nosi Daniele
Published: September 2023

The term neuroinflammation defines the reactions of astrocytes and microglia to alterations in homeostasis in the diseased central nervous system (CNS), the exacerbation of which contributes to the neurodegenerative effects of Alzheimer’s disease (AD). Local environmental conditions, such as the presence of proinflammatory molecules, mechanical properties of the extracellular matrix (ECM), and local cell–cell interactions, are determinants of glial cell phenotypes. In AD, the load of the cytotoxic/proinflammatory amyloid β (Aβ) peptide is a microenvironmental component increasingly growing in the CNS, imposing time-evolving challenges on resident cells. This study aimed to investigate the temporal and spatial variations of the effects produced by this process on astrocytes and microglia, either directly or by interfering in their interactions. Ex vivo confocal analyses of hippocampal sections from the mouse model TgCRND8 at different ages have shown that overproduction of Aβ peptide induced early and time-persistent disassembly of functional astroglial syncytium and promoted a senile phenotype of reactive microglia, hindering Aβ clearance. In the late stages of the disease, these patterns were altered in the presence of Aβ-plaques, surrounded by typically reactive astrocytes and microglia. Morphofunctional characterization of peri-plaque gliosis revealed a direct contribution of astrocytes in plaque buildup that might result in shielding Aβ-peptide cytotoxicity and, as a side effect, in exacerbating neuroinflammation.
Nanoscale CAR Organization at the Immune Synapse Correlates with CAR-T Effector Functions
Authors: Sajman Julia , Yakovian Oren , Unger Deshet Naamit , Almog Shaked , Horn Galit , Waks Tova , Globerson Levin Anat , Sherman Eilon
Published: September 2023

T cells expressing chimeric antigen receptors (CARs) are at the forefront of clinical treatment of cancers. Still, the nanoscale organization of CARs at the interface of CAR-Ts with target cells, which is essential for TCR-mediated T cell activation, remains poorly understood. Here, we studied the nanoscale organization of CARs targeting CD138 proteoglycans in such fixed and live interfaces, generated optimally for single-molecule localization microscopy. CARs showed significant self-association in nanoclusters that was enhanced in interfaces with on-target cells (SKOV-3, CAG, FaDu) relative to negative cells (OVCAR-3). CARs also segregated more efficiently from the abundant membrane phosphatase CD45 in CAR-T cells forming such interfaces. CAR clustering and segregation from CD45 correlated with the effector functions of Ca++ influx and target cell killing. Our results shed new light on the nanoscale organization of CARs on the surfaces of CAR-Ts engaging on- and off-target cells, and its potential significance for CAR-Ts’ efficacy and safety.
Size Exclusion Chromatography–Mass Photometry: A New Method for Adeno-Associated Virus Product Characterization
Authors: Wu Di , Zhao Xiaonan , Jimenez Diego Antonio , Piszczek Grzegorz
Published: September 2023

Over the past decade, adeno-associated viruses (AAVs) have attained significant prominence in gene therapy and genome editing applications, necessitating the development of robust and precise methodologies to ensure the quality and purity of AAV products. Existing AAV characterization techniques have proven effective for the analysis of pure and homogeneous AAV samples. However, there is still a demand for a rapid and low-sample-consumption method suitable for the characterization of lower purity or heterogeneous AAV samples commonly encountered in AAV products. Addressing this challenge, we propose the SEC-MP method, which combines size exclusion chromatography (SEC) with mass photometry (MP). In this novel approach, SEC effectively separates monomeric AAV particles from impurities, while the UV detector determines the virus particle concentration. MP complements this process by estimating the fraction of fully packaged AAVs in the total population of AAV particles. This combined methodology enables accurate determination of the titer of effective, fully packaged AAVs in samples containing aggregates, incorrectly packaged AAVs with incomplete genomes, protein or DNA fragments, and other impurities. Our experimental results demonstrate that SEC-MP provides valuable guidance for sample quality control and subsequent applications in the field of AAV research.
How Does Climate Change Worry Influence the Relationship between Climate Change Anxiety and Eco-Paralysis? A Moderation Study
Authors: Innocenti Matteo , Perilli Alessio , Santarelli Gabriele , Carluccio Niccolò , Zjalic Doris , Acquadro Maran Daniela , Ciabini Lorenzo , Cadeddu Chiara
Published: September 2023

Climate change (CC) has a significant impact on human health, resulting in both physical and mental illnesses. Eco-anxiety—the excessive and pervasive fear about the consequences of CC—is the most studied psychoterratic state. This study presents the validation of Italian versions of Hogg’s Eco-Anxiety Scale (HEAS) and the Eco-Paralysis Scale. It also investigates the effects of worry on eco-anxiety and eco-paralysis. The study was conducted on 150 Italian individuals who responded to the two scales and to other questionnaires to make comparisons with the two above. Internal consistency and factorial structure were assessed through Cronbach’s alpha, Confirmatory Factor Analysis and Exploratory Factor Analysis. A median regression was used to assess the association between the EPS and the HEAS and Climate Change Worry Scale (CCWS) and their interaction. HEAS and EPS showed good psychometric properties: HEAS resulted in good internal consistency (Cronbach’s α = 0.986), and the Eco-Paralysis scale had good test-retest reliability (r = 0.988). In both cases, a one-factor structure was suggested to be retained. The interaction terms between HEAS and CCWS (β = −0.02; 95% CI: −0.03, −0.01; p < 0.001) and between HEAS and education (β = −0.05; 95% CI: −0.08, −0.02; p < 0.001) were significant. Therefore, the feeling of worry seems to act as a moderator between climate change anxiety and eco-paralysis since it may appear to influence individuals and their ability to transform anxiety into action. Education plays a role in reducing the risk of Eco-Paralysis in subjects affected by climate change anxiety. Thus, data suggest that working on reinforcing a more cognitive concern might result in more problem-solving-focused strategies to face climate change anxiety and eco-paralysis.
Research on the Microstructure and Properties of Al Alloy/Steel CMT Welding-Brazing Joints with Al–Si Flux-Cored Welding Wires
Authors: Liu Haodong , Pu Juan , Wu Mingfang , Zhang Chao , Rao Jiawei , Long Weimin , Shen Yuanxun
Published: September 2023

Al alloy/steel composite structures combine the advantage of a lightweight Al alloy and high-strength steel and are widely used in new energy vehicles, solar photovoltaic, and other fields. The main problems with the connection of an Al alloy and steel are poor weld formation and difficulty in controlling the thickness of the intermetallic compounds (IMCs) at the interface of the Al alloy and steel, which deteriorates the mechanical properties and corrosion resistance of the Al alloy/steel joints. Therefore, experiments on Al alloy/steel CMT (cold metal transfer, CMT) welding brazing were conducted by using AlSi5 and AlSi12 flux-cored welding wires as filler metals. The macro morphology, microstructure composition, tensile strength, and corrosion resistance of the Al alloy/steel joints were then analyzed. The mechanism of the Noclock flux on the wettability and spreadability of the Al–Si welding wire to a low-carbon steel surface was discussed and the formation behavior of the IMCs at the interface layer of the Al alloy/steel joints was clarified. The results showed that the NH4F and NH4AlF4 of the Noclock flux induced and accelerated the removal of oxide films on the surface of the Al alloy and Al–Si welding wire at a high temperature. It promoted the wettability and spreadability of the Al–Si welding wire, which resulted in the improvement of the Al alloy/steel joint formation. Under the CMT arc heat source, the Al–Si welding wire melted, and then a chemical metallurgical reaction occurred among the Al, Si, and Fe elements. The τ5-Al7.2Fe1.8Si phase formed preferentially near the Al alloy fusion zone while the θ-Fe (Al, Si)3 phase formed near the steel side. Actually, the interface reaction layer was composed of a double-layer compound including the τ5-Al7.2Fe1.8Si phase and θ-Fe (Al, Si)3 phase. Additionally, the IMC thickness of the Al alloy/steel joint with the AlSi12 flux-cored welding wire was 3.01 μm, which was less than that with the AlSi5 flux-cored welding wire, so its tensile strength was less but its corrosion resistance was superior. The main reason for the corrosion resistance of Al alloy/steel joints was the presence of a large amount of Al2O3, FeO, and Fe2O3 in the passive film.
Improved Numerical Modeling of Terahertz Wave Propagation in Epoxy Coating with the Finite-Difference Time-Domain Method
Authors: Tu Wanli , Zhong Shuncong , Zhang Qiukun , Huang Yi , Luo Manting
Published: September 2023

Electromagnetic theoretical analysis was usually used to investigate the pulsed terahertz wave interaction with the medium. For epoxy coatings, the material dispersion of the coating was often simplified or ignored in the traditional propagation model. It is difficult to elaborate on the propagation mechanism and to differentiate the coating deterioration as serving time increases. An improved propagation model based on the finite-difference time domain was established to characterize the propagation in the epoxy protective coating under broad-band terahertz radiation. Either an intact or defective coating structure was investigated, and the simulated results were compared with the experimental test. The dissipation mechanism was considered in the proposed model. The results indicated that the terahertz reflections varied with the change in optical and dielectric properties caused by coating aging, which influences the intrinsic impedance of the medium. Moreover, it could well elucidate the propagation mechanism of pulsed terahertz waves in rusted, defective coating structures.
The Effects of Ultrasonic Impact Modification on the Surface Quality of 20CrNiMo Carburized Steel
Authors: Jiang Qingshan , Zhu Li , Chen Junying , Chen Xiuyu , Weng Jianchun , Xu Zhilong , Zhao Zhenye
Published: September 2023

Ultra-high residual compressive stress can be introduced via the ultrasonic impact on the basis of transformation hardening, and further enhance the overall performance of 20CrNiMo carburized steel. In order to achieve the best surface quality of 20CrNiMo carburized steel, ultrasonic impact modification testing with varying static loads (900 N, 1200 N, and 1500 N) and rounds (1, 3, and 6) was conducted. By characterizing microhardness, microstructure, the surface roughness and residual compressive stress, the influence of ultrasonic impact modification parameters on its surface quality were analyzed. The experimental results indicated that the static loads and rounds of ultrasonic impact modification had a significant impact on the surface quality. The best surface quality could be obtained after six rounds of ultrasonic impact modification under a static load of 1200 N. In addition, the surface roughness decreased from 0.40 μm to 0.04 μm, the surface microhardness increased from 679 HV0.1 to 1086 HV0.1, and the maximum residual compressive stress of 1195.36 MPa was formed. Furthermore, the surface quality would deteriorate when the static load and ultrasonic impact rounds were increased.
Using an Interlayer to Toughen Flexible Colorless Polyimide-Based Cover Windows
Authors: Matsuda Yusuke , Cen Yinjie , Bu Luke , Zhang Jieqian , Kourtakis Kostantinos , Huang Tao , Song Yixuan , Yahyazadehfar Mobin , Caputo Derek , Podhiny John , Carbajal Leopoldo , Samadi-Dooki Aref
Published: September 2023

Colorless polyimide (PI)-based flexible cover windows are a critical component of flexible electronics to protect devices from unwanted chemical and mechanical damage. The integration of flexible colorless PI-based windows into electronics applications is limited by the embrittlement of some colorless PI films when they are coated with hard coats. Here, we investigate the embrittlement mechanism of hard-coated colorless PI films and the role of interlayers in toughening the colorless PI-based cover windows for flexible electronics applications. A fracture mechanics approach combined with finite element analysis (FEA) models is employed to compute fracture strain, εc, for different crack cases in the bilayer (hard coated colorless PI) and trilayer (with an additional interlayer) cover windows. For the model inputs and validation, the material properties of the cover windows are characterized. We show that the embrittlement is attributed to the fracture behavior of the cover windows, and placing a ductile interlayer increases the εc of colorless PI films. Using the fracture analysis as a design guide, we fabricate a trilayer cover window with an acrylic thermoset interlayer and demonstrate an improvement of the εc of the colorless PI cover window by ~42%. We believe our analysis provides insights into design guides for mechanically robust cover windows using colorless PI films and flexible HCs for emerging flexible electronics.
Multispectral Image Generation from RGB Based on WSL Color Representation: Wavelength, Saturation, and Lightness
Authors: Skala Vaclav
Published: September 2023

Image processing techniques are based nearly exclusively on RGB (red–green–blue) representation, which is significantly influenced by technological issues. The RGB triplet represents a mixture of the wavelength, saturation, and lightness values of light. It leads to unexpected chromaticity artifacts in processing. Therefore, processing based on the wavelength, saturation, and lightness should be more resistant to the introduction of color artifacts. The proposed process of converting RGB values to corresponding wavelengths is not straightforward. In this contribution, a novel simple and accurate method for extracting the wavelength, saturation, and lightness of a color represented by an RGB triplet is described. The conversion relies on the known RGB values of the rainbow spectrum and accommodates variations in color saturation.
Divisions and Square Roots with Tight Error Analysis from Newton–Raphson Iteration in Secure Fixed-Point Arithmetic
Authors: Korzilius Stan , Schoenmakers Berry
Published: September 2023

In this paper, we present new variants of Newton–Raphson-based protocols for the secure computation of the reciprocal and the (reciprocal) square root. The protocols rely on secure fixed-point arithmetic with arbitrary precision parameterized by the total bit length of the fixed-point numbers and the bit length of the fractional part. We perform a rigorous error analysis aiming for tight accuracy claims while minimizing the overall cost of the protocols. Due to the nature of secure fixed-point arithmetic, we perform the analysis in terms of absolute errors. Whenever possible, we allow for stochastic (or probabilistic) rounding as an efficient alternative to deterministic rounding. We also present a new protocol for secure integer division based on our protocol for secure fixed-point reciprocals. The resulting protocol is parameterized by the bit length of the inputs and yields exact results for the integral quotient and remainder. The protocol is very efficient, minimizing the number of secure comparisons. Similarly, we present a new protocol for integer square roots based on our protocol for secure fixed-point square roots. The quadratic convergence of the Newton–Raphson method implies a logarithmic number of iterations as a function of the required precision (independent of the input value). The standard error analysis of the Newton–Raphson method focuses on the termination condition for attaining the required precision, assuming sufficiently precise floating-point arithmetic. We perform an intricate error analysis assuming fixed-point arithmetic of minimal precision throughout and minimizing the number of iterations in the worst case.
Ionic Liquid Additives for Efficient and Durable Two-Step Perovskite Photovoltaic Devices
Authors: Wang Fei , Sun Yonggui , Wang Taomiao , Yang Guo , Li Qiannan , Li Yongjun , Lin Haoran , Wan Xuejuan , Li Gang , Hu Hanlin
Published: September 2023

Ionic liquids (ILs) have found widespread use in controlling the crystallization process of perovskites, optimizing the morphology and enhancing the device performance, especially in the one-step method. However, research regarding the effects of ionic liquids on perovskite devices prepared using the two-step method remains relatively scarce. Here, an IL 1-Hexyl-3-methylimidazolium Tetrafluoroborate (HMIMBF4) is selected as an additive in the perovskite precursor solution for the fabrication of PSCs using the two-step method. Our study involves a systematic exploration of the precise effects of ILs on the morphology of perovskite thin films, defect density, and photovoltaic performance. IL HMIMBF4 is convincingly shown to possess a robust chemical affinity with perovskite components, thereby establishing a basis for the inhibition of ion migration. Concurrently, ILs play a pivotal role in governing the morphology of perovskite while also facilitating the conversion of lead iodide into the perovskite structure. Benefiting from the regulation of the perovskite morphology and defect states by IL HMIMBF4, the devices with an efficiency exceeding 23% is ultimately achieved. Our research provides a comprehensive comprehension and contributes to advancing the utilization of ILs in two-step photovoltaic devices.
Hydrolithon farinosum and Lithophyllum epiphyticum sp. nov. (Corallinaceae, Corallinales, Rhodophyta), Two Epiphytic Crustose Coralline Algae from the Abrolhos Archipelago, Brazil, Southwestern Atlantic
Authors: Lyra Manoela B. , Bahia Ricardo G. , Jesionek Michel B. , Carvalho Rodrigo T. , Moraes Fernando C. , Harvey Adele S. , Pereira Renato C. , Salgueiro Fabiano , Salgado Leonardo T.
Published: September 2023

The aim of this study was to elucidate the taxonomy of the common but overlooked epiphytic coralline algae species from shallow reefs and seagrass meadows of the Abrolhos Archipelago, Brazil. Two thin (two vegetative cells thick) epiphytic coralline species were recorded: Lithophyllum epiphyticum sp. nov. and Hydrolithon farinosum. Molecular analysis from psbA genetic marker confirmed the position of L. epiphyticum into Lithophylloideae and revealed a phylogenetic relationship with an undescribed Lithophyllum from Italy. Thin thallus (2–3 cells thick) and cells lining the pore of tetrasporangial conceptacles protruding laterally occluding the canal, either partially or totally, are its main diagnostic characteristics. Hydrolithon farinosum is herein described in detail for Brazil, and its worldwide distribution is then discussed.
Fish Diversity in Relation to Littoral Habitats in Three Basins of Lake Kivu (East Africa)
Authors: Kisekelwa Tchalondawa , Alimasi Wilondja , Mazambi Lutete , Mwaijengo Grite N. , Hyangya Lwikitcha , Muzungu Heri , Joyeuse Mudagi , Lubala Amani , Kubota Musombwa , Wüest Alfred , Muvundja Amisi , Masilya Mulungula
Published: September 2023

In total, 28 of the 29 fish species reported from the Lake Kivu basin occur in the littoral zone of the lake, but information about their structure, occurrence, and the habitats affecting their distribution is largely lacking. The lake’s inshore area is poorly heterogenous, with rock and macrophyte habitats representing the major habitats. The lack of heterogeneity in the habitats is probably an important factor influencing species richness, abundance, and the association between the species and habitats. We evaluated the fish diversity, abundance, and habitat parameters across 14 sites representing the major habitats of the lake, using data collected between April 2018 and October 2019. We calculated Hull and Jaccard indices and applied uni- and multivariate statistical approaches to the collected data. We identified 18 fish species in the lake. In the north, 17 species were found, with high abundance in rocky sites but low abundance in sandy habitats. In the south, 15 species were reported. We identified 12 species in the Ishungu Basin where the site with rock substrate had high abundance and 13 species in the Bukavu Basin with weak species richness and low abundance across degraded sites. Lamprichthys tanganicanus, a non-native species, was abundant in rocky (north) and macrophyte sites (south). Sand, rock, conductivity, depth, dissolved oxygen, and water transparency were significant parameters that could explain the fish distribution in the north while dissolved oxygen, vegetation cover, depth, and conductivity were significant in the south. A monitoring programme of the fish fauna in Lake Kivu is needed.
Essential Oil Supplementation in Small Ruminants: A Review on Their Possible Role in Rumen Fermentation, Microbiota, and Animal Production
Authors: Caroprese Mariangela , Ciliberti Maria Giovanna , Marino Rosaria , Santillo Antonella , Sevi Agostino , Albenzio Marzia
Published: September 2023

Essential oils are bioactive compounds, originating from the secondary metabolism of plants, recognized for their ability to modify rumen fermentation, gut health, and to function as antioxidant molecules in small ruminants. Indeed, small ruminant-derived products, such as milk, dairy, and meat can benefit from the utilization of essential oils, that have demonstrated antimicrobial, antioxidant and anti-inflammatory affects, in the animals’ diet. This review reports on the findings that demonstrates the possible role of essential oils in controlling greenhouse gas emissions from ruminants through the modulation of ruminal microbial populations, in sustaining animal health and welfare by affecting the gut microbiota, and in ameliorating animals’ products through enhancement of their nutritional composition from a human diet perspective. However, the current review highlighting the inconclusive findings related to the use of essential oils in small ruminant nutrition, supports the need of further studies to better understand the administration of how essential oils and to explore their specific actions at the molecular level.
Update of Dietary Supplement Label Database Addressing on Coding in Italy
Authors: Perelli Giorgia , Bernini Roberta , Lucarini Massimo , Durazzo Alessandra
Published: September 2023

Harmonized composition data for foods and dietary supplements are needed for research and for policy decision making. For a correct assessment of dietary intake, the categorization and the classification of food products and dietary supplements are necessary. In recent decades, the marketing of dietary supplements has increased. A food supplements-based database has, as a principal feature, an intrinsic dynamism related to the continuous changes in formulations, which consequently leads to the need for constant monitoring of the market and for regular updates of the database. This study presents an update to the Dietary Supplement Label Database in Italy focused on dietary supplements coding. The updated dataset here, presented for the first time, consists of the codes of 216 dietary supplements currently on the market in Italy that have functional foods as their characterizing ingredients, throughout the two commonly most used description and classification systems: LanguaLTM and FoodEx2-. This update represents a unique tool and guideline for other compilers and users for applying classification coding systems to dietary supplements. Moreover, this updated dataset represents a valuable resource for several applications such as epidemiological investigations, exposure studies, and dietary assessment.
Clinical Usefulness of Speckle-Tracking Echocardiography in Patients with Heart Failure with Preserved Ejection Fraction
Authors: Lin Yixia , Zhang Li , Hu Xiaoqing , Gao Lang , Ji Mengmeng , He Qing , Xie Mingxing , Li Yuman
Published: September 2023

Heart failure with preserved ejection fraction (HFpEF) is defined as HF with left ventricular ejection fraction (LVEF) not less than 50%. HFpEF accounts for more than 50% of all HF patients, and its prevalence is increasing year to year with the aging population, with its prognosis worsening. The clinical assessment of cardiac function and prognosis in patients with HFpEF remains challenging due to the normal range of LVEF and the nonspecific symptoms and signs. In recent years, new echocardiographic techniques have been continuously developed, particularly speckle-tracking echocardiography (STE), which provides a sensitive and accurate method for the comprehensive assessment of cardiac function and prognosis in patients with HFpEF. Therefore, this article reviewed the clinical utility of STE in patients with HFpEF.
Dermo-Seg: ResNet-UNet Architecture and Hybrid Loss Function for Detection of Differential Patterns to Diagnose Pigmented Skin Lesions
Authors: Arshad Sannia , Amjad Tehmina , Hussain Ayyaz , Qureshi Imran , Abbas Qaisar
Published: September 2023

Convolutional neural network (CNN) models have been extensively applied to skin lesions segmentation due to their information discrimination capabilities. However, CNNs’ struggle to capture the connection between long-range contexts when extracting deep semantic features from lesion images, resulting in a semantic gap that causes segmentation distortion in skin lesions. Therefore, detecting the presence of differential structures such as pigment networks, globules, streaks, negative networks, and milia-like cysts becomes difficult. To resolve these issues, we have proposed an approach based on semantic-based segmentation (Dermo-Seg) to detect differential structures of lesions using a UNet model with a transfer-learning-based ResNet-50 architecture and a hybrid loss function. The Dermo-Seg model uses ResNet-50 backbone architecture as an encoder in the UNet model. We have applied a combination of focal Tversky loss and IOU loss functions to handle the dataset’s highly imbalanced class ratio. The obtained results prove that the intended model performs well compared to the existing models. The dataset was acquired from various sources, such as ISIC18, ISBI17, and HAM10000, to evaluate the Dermo-Seg model. We have dealt with the data imbalance present within each class at the pixel level using our hybrid loss function. The proposed model achieves a mean IOU score of 0.53 for streaks, 0.67 for pigment networks, 0.66 for globules, 0.58 for negative networks, and 0.53 for milia-like-cysts. Overall, the Dermo-Seg model is efficient in detecting different skin lesion structures and achieved 96.4% on the IOU index. Our Dermo-Seg system improves the IOU index compared to the most recent network.