bluuebunny/crossref_metadata_2025 huggingface dataset:
MEG in MRI-Negative Patients with Focal Epilepsy
Authors: Kreidenhuber Rudolf , Poppert Kai-Nicolas , Mauritz Matthias , Hamer Hajo M. , Delev Daniel , Schnell Oliver , Rampp Stefan
Published: September 2024

Objectives: To review the evidence on the clinical value of magnetic source imaging (MSI) in patients with refractory focal epilepsy without evidence for an epileptogenic lesion on magnetic resonance imaging (“MRI-negative” or “non-lesional MRI”). Methods: We conducted a systematic literature search on PUBMED, which was extended by researchrabbit.ai using predefined criteria to identify studies that applied MSI in MRI-negative patients with epilepsy. We extracted data on patient characteristics, MSI methods, localization results, surgical outcomes, and correlation with other modalities. Results: We included 23 studies with a total of 512 non-lesional epilepsy patients who underwent MSI. Most studies used equivalent current dipole (ECD) models to estimate the sources of interictal epileptic discharges (IEDs). MEG detected IEDs in 32–100% of patients. MSI results were concordant with other modalities, such as EEG, PET, and SPECT, in 3892% of cases. If MSI concordant surgery was performed, 52–89% of patients achieved seizure freedom. MSI contributed to the decision-making process in 28–75% of cases and altered the surgical plan in 5–33% of cases. Conclusions: MSI is a valuable diagnostic tool for MRI-negative patients with epilepsy, as it can detect and localize IEDs with high accuracy and sensitivity, and provides useful information for surgical planning and predicts outcomes. MSI can also complement and refine the results of other modalities, such as EEG and PET, and optimize the use of invasive recordings. MSI should be considered as part of the presurgical evaluation, especially in patients with non-lesional refractory epilepsy.
Are Fibrous Cortical Defects (FCDs) and Non-Ossifying Fibromas (NOFs) Only Radiological Findings? The Relationship between Radiological/Clinical Findings and Physical Activity in Children and Adolescents: A Cross-Sectional Study
Authors: Berk Erhan , Aydogan Baykara Rabia
Published: September 2024

Background: Fibrous cortical defect (FCD) and non-ossifying fibroma (NOF) are incidentally recognised and benign developmental lesions. The objective of this study was to ascertain the clinical manifestations and symptoms of FCDs/NOFs in children and adolescent patients, to characterise the lesions radiologically using X-ray and MRI techniques, and to determine the relationship between physical activity and the condition. Methods: The study included patients under the age of 18 with radiological lesions on their extremities. The lesions were classified as FCD or NOF in accordance with the distinctive imaging features. For each lesion, the bone involved, the site involved, the size of the lesion, and the type of lesion (according to the Ritschl classification) were recorded. In the anamnesis, the patient’s presenting complaint, the character of the pain, if any, and the level of activity were investigated. Pain was quantified using the visual analogue scale (VAS) and the 21-Numbered Circle VAS (21-NCVAS). The 21-Numbered Circle Activity Scale (21-NCAS) and the International Physical Activity Questionnaire (IPAQ) were employed for the assessment of physical activity. Results: The study included 34 lesions in 28 children (14 girls/14 boys). There was no difference in age between girls and boys (p = 0.45). According to Ritschl’s classification, 18 (52.9%) lesions were stage A, 9 (26.5%) were stage B, and 7 (20.6%) were stage C. The lesion size increased with increasing Ritschl stage (p < 0.02). The main presenting complaint was pain (n = 13, 49.9%). In 21.4% of the children (n = 6), lesions were detected incidentally on radiographs. According to IPAQ, 39.3% of the children were physically inactive. There was a significant negative correlation between 21-NCAS and Ritschl stage (r = −0.51, p < 0.05). Activity decreased as the Ritschl stage increased. There was a significant negative correlation between 21-NCAS and VAS (r = −0.69, p < 0.05). Conclusions: Spontaneous pain was observed in 49.9% of patients diagnosed with FCD/NOF. No correlation was identified between lesion size and the presence or severity of pain. As the severity of pain and Ritschl stage increased, there was a corresponding decrease in physical activity.
Validation of a Paralimbic-Related Subcortical Brain Dysmaturation MRI Score in Infants with Congenital Heart Disease
Authors: Reynolds William T. , Votava-Smith Jodie K. , Gabriel George , Lee Vincent K. , Rajagopalan Vidya , Wu Yijen , Liu Xiaoqin , Yagi Hisato , Slabicki Ruby , Gibbs Brian , Tran Nhu N. , Weisert Molly , Cabral Laura , Subramanian Subramanian , Wallace Julia , del Castillo Sylvia , Baust Tracy , Weinberg Jacqueline G. , Lorenzi Quigley Lauren , Gaesser Jenna , O’Neil Sharon H. , Schmithorst Vanessa , Panigrahy Ashok , Ceschin Rafael , Lo Cecilia W.
Published: September 2024

Background: Brain magnetic resonance imaging (MRI) of infants with congenital heart disease (CHD) shows brain immaturity assessed via a cortical-based semi-quantitative score. Our primary aim was to develop an infant paralimbic-related subcortical-based semi-quantitative dysmaturation score, termed brain dysplasia score (BDS), to detect abnormalities in CHD infants compared to healthy controls and secondarily to predict clinical outcomes. We also validated our BDS in a preclinical mouse model of hypoplastic left heart syndrome. Methods: A paralimbic-related subcortical BDS, derived from structural MRIs of infants with CHD, was compared to healthy controls and correlated with clinical risk factors, regional cerebral volumes, feeding, and 18-month neurodevelopmental outcomes. The BDS was validated in a known CHD mouse model named Ohia with two disease-causing genes, Sap130 and Pchda9. To relate clinical findings, RNA-Seq was completed on Ohia animals. Findings: BDS showed high incidence of paralimbic-related subcortical abnormalities (including olfactory, cerebellar, and hippocampal abnormalities) in CHD infants (n = 215) compared to healthy controls (n = 92). BDS correlated with reduced cortical maturation, developmental delay, poor language and feeding outcomes, and increased length of stay. Ohia animals (n = 63) showed similar BDS findings, and RNA-Seq analysis showed altered neurodevelopmental and feeding pathways. Sap130 mutants correlated with a more severe BDS, whereas Pcdha9 correlated with a milder phenotype. Conclusions: Our BDS is sensitive to dysmaturational differences between CHD and healthy controls and predictive of poor outcomes. A similar spectrum of paralimbic and subcortical abnormalities exists between human and Ohia mutants, suggesting a common genetic mechanistic etiology.
Reply to Kovacs, F.M.; Seco-Calvo, J. Limitations of a Cross-Sectional Correlation Study. Comment on “Elabd et al. Prediction of Back Disability Using Clinical, Functional, and Biomechanical Variables in Adults with Chronic Nonspecific Low Back Pain. J. Clin. Med. 2024, 13, 3980”
Authors: Elabd Omar M. , Oakley Paul A. , Elabd Aliaa M.
Published: September 2024

Herein, we reply to comments made by Kovacs and Seco-Calvo [...]
Political Listening and Podcasting: The Case of Tunisia
Authors: Snoussi Thouraya , Hatamleh Islam Habis Mohammad , Barkho Leon , Abusamra Noura
Published: September 2024

This paper examines the dynamics of political listening, news processing, and podcasting in North African countries through the case study of Tunisia. The analysis centers on Tunisian President Kais Saied’s speech on 25 July 2021, in which he dissolved the Parliament and assumed full control, following widespread public protests against the country’s deteriorating conditions. By leveraging the concept of political listening, this study investigates the methods podcasters employ to foster political engagement in Tunisia. The content analysis encompasses five podcasts produced between 25 July and 31 December 2021. The findings reveal that podcasters address the constitutional legitimacy of Saied’s actions and criticize the Ennahda party for its power monopoly attempts. The use of interview-based narratives, coupled with emotional elements such as humor and sarcasm, enhances the linguistic impact, conveys optimism, and garners support for the president. This approach signifies the emergence of an alternative public sphere, purposefully crafted to attract political listening, enrich public knowledge, foster cohesion, and encourage civic participation.
Implementing the Risk Stratification and Clinical Management of Breast Cancer Families Using Polygenic Risk Score Evaluation: A Pilot Study
Authors: Rizzacasa Barbara , Nicolì Vanessa , Tancredi Chantal , Conte Chiara , Salehi Leila B. , Carriero Miriam Lucia , Longo Giuliana , Cirigliano Vincenzo , Lopez Luis Izquierdo , Palao Bibiana , Portarena Ilaria , Buonomo Oreste Claudio , Novelli Giuseppe , Biancolella Michela
Published: September 2024

Background: The identification of women at high risk of breast cancer (BC) is crucial for personalized screening strategies. Pathogenic and likely pathogenic variants (PVs/LPVs) in susceptibility risk genes explain part of the individual risk. Moreover, a polygenic background, summarized as a polygenic risk score (PRS), contributes to the risk of BC and may modify the individual risk in carrier and non-carrier members of BC families. Methods: We performed a retrospective pilot study evaluating PRS in women from a subset of high- (BRCA1 and BRCA2) and moderate-risk (PALB2 and ATM) BC families. We included PVs/LPVs carriers and non-carriers and evaluated a PRS based on 577,113 BC-associated variants. Using BOADICEA, we calculated the adjusted lifetime BC risk. Results: Our data showed that in BRCA1/BRCA2 carriers, PVs have a major role in stratifying the lifetime risk, while PRS improves risk estimation in non-carriers of these families. A different scenario may be observed in PALB2 and ATM families where PRS combined with PV/LPV carrier status gives a more informative lifetime risk. Conclusions: This study showed that in BC families, the PRS might help to quantify the weight of the genetic familial background, improving the individual risk stratification and contributing to personalized clinical management for carrier and non-carrier women.
The Emerging Phenomenon of Shopstreaming: Gaining a More Nuanced Understanding of the Factors Which Drive It
Authors: Mutambik Ibrahim
Published: September 2024

Over the past decade, the concept and practice of shopstreaming (also known as livestream shopping) have grown significantly within the e-business world, as it integrates live streaming technology with e-commerce. However, the relationship between the perceived benefits of this shopping mode and the intention to use it is not fully understood. This research seeks to enhance the current understanding of this relationship by studying the association in the context of fashion and personal care (FPC) goods. Uniquely, the study bases its core model on a combination of the theory of planned behaviour (TPB) and some elements of the enhanced stimulus–organism–response (ESOR) theory, which incorporates cognitive, emotional and physiological processes within the organism component. This enables the development of a framework which facilitates the examination of the relationship between perceived benefits and intention to purchase within a shopstreaming environment, moderated by attitude (organism). The uniqueness of the study is further enhanced by the inclusion and analysis of perceived platform quality and the streamer’s (seller’s) influence as moderating constructs. These analyses were carried out using data from 901 respondents to a structured questionnaire, collected over a 4-month period. The results of the study showed that the seller has a significant moderating effect on the mediation of intention to purchase by attitude, though the mediation between perceived benefits and attitude was not affected by perceived platform quality. The study therefore offers significant insights to Saudi FPC brands, streamers and marketing agencies to develop and optimise sales and content strategy.
Unraveling the Influential Mechanisms of Smart Interactions on Stickiness Intention: A Privacy Calculus Perspective
Authors: He Jinyi , Liang Xinjian , Xue Jiaolong
Published: September 2024

Artificial intelligence (AI) technologies are changing the ways of interaction between humans and machines, and smart interactions have become one of the hot topics of artificial intelligent in-home voice assistants (AVAs) by connecting humans, machines, content, and AVAs. Based on the privacy calculus theory (PCT), the authors conducted an online questionnaire-based survey to investigate the influential mechanisms of smart interactions on stickiness intention (SI), demonstrated the positive (negative) effects of smart interactions on benefits and risks, and verified the moderating role of susceptibility to normative influence (SNI). The results show that smart interactions positively impact SI via utilitarian benefit and hedonic benefit; humanness has a U-shaped effect on privacy risk; personalization, connectivity, and linkage positively impact privacy risk; multimodal control negatively impacts privacy risk; and SNI positively moderates the effects of smart interactions on stickiness intention. The study enriched and expanded the literature on smart interactions in the context of AIoT and offered practical implications for AVA service providers and developers to design or optimize smart interactions for AI interactive services. By examining the double-edged sword effects of personalization and humanness, our findings offer novel insights into the privacy calculus in smart interactions.
Assessment of Landscape Ecological Risk and Its Driving Factors for the Ebinur Lake Basin from 1985 to 2022
Authors: Adili Ayinigaer , Wu Biao , Chen Jiayu , Wu Na , Ge Yongxiao , Abuduwaili Jilili
Published: September 2024

The Ebinur Lake Basin (ELB), which is a typical watershed in an arid region, has an extremely delicate natural ecosystem. Rapid urbanisation and economic growth have triggered substantial ecological and environmental transformations in this key economic hub of Xinjiang. However, a comprehensive and systematic knowledge of the evolving ecological conditions in the ELB remains limited. Therefore, this study modelled the landscape ecological risk index (LERI) using land use/land cover (LULC) data from 1985 to 2022 and assessed the drivers of landscape ecological risk (LER) using a geographical detector model (GDM). The findings revealed that (1) from 1985 to 2022, the construction land, cropland, and forestland areas in the ELB increased, whereas those of water bodies, grasslands, and barren land decreased. (2) Between 1985 and 2022, LER in the ELB showed a downward trend. Spatially, LER was predominantly characterised by lower and lowest risk levels. The higher and highest risk status has been around Ebinur lake and has continued to improve each year. (3) Climatic factors, particularly temperature and precipitation, were identified as the most significant drivers of the LER change from 1985 to 2022. The findings provide crucial scientific knowledge for advancing sustainable development and maintaining ecological security in the ELB.
A Case Study of Story Mapping, Neighborhood Change, and Community Assets of Ballpark, Salt Lake City
Authors: García Ivis , Biamont Anthony , Klopfenstein Jacob
Published: September 2024

Gentrification and displacement of low-income and minority families is a frequently discussed phenomenon when it comes to community planning. To best address and redistribute resources for these neighborhoods, needs assessments are often conducted to identify the problem areas, such as crime, poverty, and abandoned infrastructure. Although needs assessments are a great starting point, they often neglect the hand of valuable community assets that should be preserved when engaging with gentrifying neighborhoods. To engage in these neighborhoods, researchers, governments, non-profits, and redevelopment corporations are more often turning to an asset-based community development approach (ABCD) pioneered by Kretzmann and McKnight (1993). This ABCD approach utilizes an asset mapping technique to identify and better understand the present strengths of a community. This was an approach taken by researchers to assist in the Salt Lake City’s (SLC) initiatives to document the city’s transformation and potentially preserve assets for their plan, called “Thriving in Place: A SLC Anti-displacement Strategy”. Asset mapping includes surveying and plotting resources both physical and non-physical, such as sustainable food sources, churches, schools, relationships, social networks, and individuals. The product of the asset map was an ArcGIS StoryMap—which is a GIS-based map that can be used for storytelling.
Effects of Land Cover Changes on Shallow Landslide Susceptibility Using SlideforMAP Software (Mt. Nerone, Italy)
Authors: Murgia Ilenia , Vitali Alessandro , Giadrossich Filippo , Tonelli Enrico , Baglioni Lorena , Cohen Denis , Schwarz Massimiliano , Urbinati Carlo
Published: September 2024

Land cover changes in mountainous areas due to silvo-pastoral abandonment can affect soil stability, especially on steep slopes. In addition, the increase in rainfall intensity in recent decades requires re-assessing landslide susceptibility and vegetation management for soil protection. This study was carried out using the software SlideforMAP in the Mt. Nerone massif (central Italy) to assess (i) the effects of land cover changes on slope stability over the past 70 years (1954–2021) and (ii) the role of actual vegetation cover during intense rainfall events. The study area has undergone a significant change in vegetation cover over the years, with a reduction in mainly pastures (−80%) and croplands (−22%) land cover classes in favor of broadleaf forests (+64%). We simulated twelve scenarios, combining land cover conditions and rainfall intensities, and analyzed the landslide failure probability results. Vegetation cover significantly increased the slope stability, up to three to four times compared to the unvegetated areas (29%, 68%, and 89%, respectively, in the no cover, 1954, and 2021 scenarios). The current land cover provided protection against landslide susceptibility, even during extreme rainfall events, for different return periods. The 30-year return period was a critical condition for a significant stability reduction. In addition, forest species provide different mitigation effects due to their root system features. The results showed that species with deep root systems, such as oaks, provide more effective slope stability than other species, such as pines. This study helps to quantify the mitigation effects of vegetation cover and suggests that physically based probabilistic models can be used at the regional scale to detect the areas prone to failure and the triggering of rainfall-induced shallow landslides. This approach can be important in land planning and management to mitigate risks in mountainous regions.
A Tribological Study of ta-C, ta-C:N, and ta-C:B Coatings on Plastic Substrates under Dry Sliding Conditions
Authors: Neubauer Paul , Kaulfuss Frank , Weihnacht Volker
Published: September 2024

In this study, we analyze the extent to which thin hard coatings can serve as tribological protective layers for the selected plastic substrate materials PA12 (polyamide 12) und PEEK (polyetheretherketone), with and without fiber reinforcement. The approximately 1 µm thick coating variants ta-C, ta-C:N, and ta-C:B, which were applied using the laser arc process, are investigated. In oscillating sliding wear tests against a steel ball in an air atmosphere without lubricant, the wear of the coating and counter body is compared to analogous coating variants applied in parallel to AISI 52100 steel. The ta-C-based coatings show good adhesion strength and basic suitability as wear protection layers on the plastic substrates in the tribological tests. However, there are variations depending on the coating type and substrate material. The use of a Cr interlayer and its thickness also plays an important role. It is demonstrated that by coating under conditions where the uncoated plastic substrate would normally fail, a similarly good performance as with analogously coated steel substrates can be achieved by ta-C:N.
Influence of Fiber Volume Fraction on the Predictability of UD FRP Ply Behavior: A Validated Micromechanical Virtual Testing Approach
Authors: Alhaddad Wael , He Minjuan , Halabi Yahia , Almajhali Khalil Yahya Mohammed
Published: September 2024

Enhancing the understanding of the behavior, optimizing the design, and improving the predictability and reliability of manufactured unidirectional (UD) FRP plies, which serve as primary building blocks for structural FRP laminates and components, are crucial to achieving a safe and cost-effective design. This research investigated the influence of fiber volume fraction (vf) on the predictability and reliability of the homogenized elastic properties and damage initiation strengths of two different types of UD FRP plies using validated micromechanical virtual testing for representative volume element (RVE) models. Several sources of uncertainties were included in the RVE models. This study also proposed a modified algorithm for microstructure generation and explored the effect of vf on the optimal sizes of the RVE in terms of fiber number. Virtual tests were systematically conducted using full factorial DOE coupled with Monte Carlo simulation. The modified algorithm demonstrated exceptional performance in terms of convergence speed and jamming limit, significantly reducing the time required to generate microstructures. The developed RVE models accurately predicted failure modes, loci, homogenized elastic properties, and damage initiation strengths with a mean error of less than 5%. Also, it was found that increasing vf led to a concurrent increase in the optimal size of the RVE. While it was found that the vf had a direct influence on homogenized elastic properties and damage initiation strengths, it did not significantly affect the reliability and predictability of these properties, as indicated by low correlation coefficients and fluctuations in the coefficient of variation of normalized properties.
Flexure Performance of Textile-Reinforced Cementitious Composites with Novel Inclined Reinforcements
Authors: Kocaman Esat Selim , Henzel Thomas , Aydogan Olcay Gurabi , Yucel Can Gurer
Published: September 2024

Textile-reinforced cementitious composites have great potential to offer novel design opportunities for thin-section structures thanks to their superior material capabilities. In this work, new cementitious composites with novel reinforcement configurations are developed, which have superior mechanical properties. The cementitious composites contain inclined through-the-thickness reinforcements, and their enhanced performance on thin-section material hardening under flexural loading is demonstrated. Furthermore, a new practical FE modeling approach is proposed that involves the combined use of multiple cohesive regions and 1D reinforcement elements that pass through these regions with a bilinear material law. This approach provides a new computationally efficient modelling framework whereby reinforcement pull-out during hardening is readily captured without resorting to computationally demanding interface laws between the reinforcement and the cementititous matrix. The model can model enhanced hardening of new configurations and provides comparable results with the experimental findings. The model can be used in the modelling and design of novel cementitious composites with engineered reinforcement configurations. Overall, this study aims to open up new avenues for the smart material design of cementitious composites with novel structural reinforcements.
Predicting the Compressive Strength of Sustainable Portland Cement–Fly Ash Mortar Using Explainable Boosting Machine Learning Techniques
Authors: Wang Hongwei , Ding Yuanbo , Kong Yu , Sun Daoyuan , Shi Ying , Cai Xin
Published: September 2024

Unconfined compressive strength (UCS) is a critical property for assessing the engineering performances of sustainable materials, such as cement–fly ash mortar (CFAM), in the design of construction engineering projects. The experimental determination of UCS is time-consuming and expensive. Therefore, the present study aims to model the UCS of CFAM with boosting machine learning methods. First, an extensive database consisting of 395 experimental data points derived from the literature was developed. Then, three typical boosting machine learning models were employed to model the UCS based on the database, including gradient boosting regressor (GBR), light gradient boosting machine (LGBM), and Ada-Boost regressor (ABR). Additionally, the importance of different input parameters was quantitatively analyzed using the SHapley Additive exPlanations (SHAP) approach. Finally, the best boosting machine learning model’s prediction accuracy was compared to ten other commonly used machine learning models. The results indicate that the GBR model outperformed the LGBM and ABR models in predicting the UCS of the CFAM. The GBR model demonstrated significant accuracy, with no significant difference between the measured and predicted UCS values. The SHAP interpretations revealed that the curing time (T) was the most critical feature influencing the UCS values. At the same time, the chemical composition of the fly ash, particularly Al2O3, was more influential than the fly-ash dosage (FAD) or water-to-binder ratio (W/B) in determining the UCS values. Overall, this study demonstrates that SHAP boosting machine learning technology can be a useful tool for modeling and predicting UCS values of CFAM with good accuracy. It could also be helpful for CFAM design by saving time and costs on experimental tests.
Fabrication and Tribological Properties of Epoxy Nanocomposites Reinforced by MoS2 Nanosheets and Aligned MWCNTs
Authors: Tong Zhe , Du Jiaxuan , Li Xiangmeng , Liu Zeyu , Yan Chao , Lei Wenxing
Published: September 2024

The epoxy nanocomposites reinforced by MoS2 nanosheets and aligned multi-walled carbon nanotubes (MWCNTs) were fabricated by DC electric field inducement. The epoxy nanocomposites achieved improvement in the tribological properties with the addition of randomly dispersed MoS2 and MWCNTs compared to the pure epoxy. Furthermore, the epoxy nanocomposites exhibit anisotropic tribological and mechanical properties when the MWCNTs are aligned in the composites. The tribological properties of epoxy nanocomposites containing 1 wt% MoS2 and aligned 1.2 wt% MWCNTs achieved the maximum improvement when the sliding direction is perpendicular to the axial direction of MWCNTs. Compared to random MoS2 nanosheets and random MWCNTs reinforced epoxy nanocomposites, the friction coefficient and wear rate of random MoS2 and aligned MWCNTs reinforced epoxy nanocomposites decreased by 11.3 and 66.7% under a load of 5 N, respectively. The increased thermal conductivity and mechanical properties, higher surface content of nanoparticles, as well as unique alignment mode of MWCNTs are considered to be the main reasons for the improvement of tribological properties of epoxy nanocomposites.
Quantitative Study of Predicting the Effect of the Initial Gap on Mechanical Behavior in Resistance Spot Welding Based on L-BFGS-B
Authors: Su Yulong , Song Kai , Du Zhanpeng , Yu Kangchen , Hu Zhaohui , Jin Hao
Published: September 2024

The initial gap (IG) is frequently occurring in the process of resistance spot welding (RSW) for automotive body-in-white structures. It is an inevitable challenge that the RSW with IG can negatively impact the welding quality, subsequently reducing the structural integrity and safety of the vehicle. This research aims to study the influence of the IG on RSW mechanical behaviors based on the refined finite element model (FEM) of RSW with different IGs under tensile shear load. The influence of six types of IGs on the peak load and fracture modes of RSW of plates with similar thicknesses of 1.0 mm and 1.5 mm is investigated through FEM and experiments. To quantify the influence of the IG on the RSW’s deformational behavior, a prediction model is introduced to predict the peak load of RSW with different IGs. The prediction model is locally optimized through the Limited memory Broyden Fletcher Goldfarb Shanno (L-BFGS-B) optimization algorithm. Based on the prediction model, the relationship among the peak load values of the tensile shear specimens, the IG, and the mechanical behavior of the RSW is revealed. The results show that the IG has an obvious influence on the peak load values of RSW under tensile shear load, and the fracture modes are both the pull-out fracture (PF) mode. The peak load values of the RSW’s tensile shear specimens are decreased with the increment in the IG. Finally, the prediction model can accurately predict the peak load for various IGs, with errors of no more than 3%.
Adsorption, Adhesion, and Wettability of Commercially Available Cleansers at Dental Polymer (PMMA) Surfaces
Authors: Pogorzelski Stanisław , Janowicz Paulina , Dorywalski Krzysztof , Boniewicz-Szmyt Katarzyna , Rochowski Paweł
Published: September 2024

This study aims to evaluate the adsorptive, adhesive, and wetting energetic properties of five commercially available cleansers in contact with model dental polymer (PMMA). It was assumed that the selected parameters allow for determining the optimal concentration and place of key component accumulation for antibacterial activity in the bulk liquid phase and prevention of oral plaque formation at the prosthetic material surface. The adsorptive (Gibbs’ excesses ΓLV, critical micellar concentration) and thermal (entropy and enthalpy) surface characteristics originated from surface tension γLV(T) and γLV(C) dependences. The surface wetting properties were quantified upon the contact angle hysteresis formalism on the advancing ΘA, receding ΘR contact angles, and γLV as the input data, which yield a set of wettability parameters: 2D adsorptive film pressure, surface free energy with its dispersive and polar components, work of adhesion, and adhesional tension, considered as interfacial interaction indicators. In particular, molecular partitioning Kp and ΓLV are indicators of the efficiency of particular active substance accumulation in the volume phase, while γSV, a = ΓSL/ΓLV, and WA point to the degree of its accumulation at the immersed polymer surface. Finally, the liquid penetration coefficient PC and the Marangoni temperature gradient-driven liquid flow speed were estimated.
Effects of Scanning Speed on the Microstructure and Wear Properties of Rockit 606 Coating Layer by Disk Laser Cladding
Authors: Li Tianqing , Bi Zhiwei , Lei Yucheng
Published: September 2024

Improving the wear resistance and corrosion resistance of 60Si2Mn steel is an important issue in agricultural machinery. A Rockit 606 coating layer may exhibit excellent performance in wear resistance and corrosion resistance. However, there are very a few public reports and articles involving the topic of a Rockit 606 laser cladding layer on a steel 60Si2Mn surface. It is of great importance to research Rockit 606 laser cladding layers. This work focuses on studying the microstructure and properties of Rockit 606 coating layers with different scanning speeds by disk laser cladding. Firstly, the laser cladding platform was designed and set up. Secondly, the laser cladding parameters were designed, and then the laser cladding experiment was conducted, and the Rockit 606 coating layers were obtained. And finally, the microstructure, phase distribution, corrosion resistance, surface hardness, and wear resistance of the coating layers were measured and analyzed. A scanning electron microscope (SEM), X-ray diffractometer (XRD), electrochemical workstation, and microhardness tester were used in this work. It was found that the microstructure Rockit 606 alloy coating consists of γ-Fe, V8C7, and Cr7C3. The microhardness of the Rockit 606 alloy coatings decreased with an increase in the scanning speed. When the scanning speed was 4 mm/s, the highest microhardness value reached 867.2 HV, which is about three times of that of the substrate. The average coefficients of friction (COFs) of the coatings decreased with an increase in the scanning speed, which led to the corresponding decrease of the wear rate. When the scanning speed was 4 mm/s, the wear behavior of the coating was mainly oxidative wear and a small amount of adhesive wear. The self-corrosion current density of the coatings prepared by laser cladding in a 3.5 wt.% NaCl solution is one order of magnitude lower than that of the substrate, indicating that the coatings have better corrosion resistance properties.
Numerical Analysis in Double-Sided Polishing: Mechanism Exploration of Edge Roll-Off
Authors: Chen Jiayu , Liu Yiran , Wang Ding , Yu Wenjie , Zhu Lei
Published: September 2024

Understanding the mechanism of stress concentration effects on the surface of semiconductor substrate materials—silicon wafers—in Double-Sided Polishing (DSP) is particularly important for improving polishing quality. In this study, a two-dimensional finite element model is established to study the effect of contact state and stress concentration during polishing on edge roll-off (ERO) and polishing rate uniformity. The variation in this contact state is influenced by changes in wafer thickness and the gap between it and the carrier. The model is validated by experiments and helps to further analyze and interpret the experimental results, identifying six stages of contact states during the polishing process. The research indicates that the phenomenon of stress concentration at the edge of a wafer is caused by the pads creating a large amount of compression at the edge of the wafer. Additionally, there appears to be a threshold value during the polishing process, below which the stress concentration on the wafer changes, thereby altering the magnitude of edge roll-off and, ultimately, affecting overall flatness. This study provides a basis for optimizing the process design.
Experimental Investigation of the Effects of Coolant Temperature on Cutting Tool Wear in the Machining Process
Authors: Şahin Osman , Karayel Durmuş , Ertürk Mustafa Ali , Nart Ergün , Seçgin Ömer
Published: September 2024

In machining processes, the heat generated in the cutting zone varies depending on cutting parameters such as depth of cut, cutting speed and feed rate. On the other hand, in most existing machine tools, the flow rate of the coolant sent to the cutting zone is constant, and there is no additional cooling system in the tank. Therefore, the temperature of the coolant circulating in the closed circuit in the system is constantly increasing, which negatively affects cutting performance. This study aims to investigate the effect of coolant temperature on tool wear in the machining process and to control the coolant temperature. For this purpose, a comprehensive coolant temperature control system was developed and integrated into the CNC machine tool. Thanks to this system, it was possible to automatically control the temperature of the cutting fluid (coolant) and maintain it within a constant temperature range throughout the cutting process. Thus, experiments were conducted at different temperatures with different cutting parameters and coolant emulsion ratios using the developed system. Since the cutting parameters interact with each other, the Taguchi method was used to observe the effect of each parameter and to determine the optimum cutting parameters. As a result, it was observed that tool wear was reduced, tool life was extended and unnecessary coolant use was prevented, especially at low temperatures. In addition, the amount of coolant used is expected to reduce negative environmental impacts.
Construction Waste Transportation Planning under Uncertainty: Mathematical Models and Numerical Experiments
Authors: Yi Wen , Lim Ying Terk , Wang Huiwen , Zhen Lu , Zhou Xin
Published: September 2024

Annually, over 10 billion tons of construction and demolition waste is transported globally from sites to reception facilities. Optimal and effective planning of waste transportation holds the potential to mitigate cost and carbon emissions, and alleviate road congestion. A major challenge for developing an effective transportation plan is the uncertainty of the precise volume of waste at each site during the planning stage. However, the existing studies have assumed known demand in planning models but the assumption does not reflect real-world volatility. Taking advantage of the problem structure, this study adopts the stochastic programming methodology to approach the construction waste planning problem. An integer programming model is developed that adeptly addresses the uncertainty of the amount of waste in an elegant manner. The proposed stochastic programming model can efficiently handle practical scale problems. Our numerical experiments amass a comprehensive dataset comprising nearly 4300 records of the actual amount of construction waste generated in Hong Kong. The results demonstrate that incorporating demand uncertainty can reduce the transportation cost by 1% correlating with an increase in profit of 14% compared to those that do not consider the demand uncertainty.
Dynamical Sphere Regrouping Particle Swarm Optimization Programming: An Automatic Programming Algorithm Avoiding Premature Convergence
Authors: Montes Rivera Martín , Guerrero-Mendez Carlos , Lopez-Betancur Daniela , Saucedo-Anaya Tonatiuh
Published: September 2024

Symbolic regression plays a crucial role in machine learning and data science by allowing the extraction of meaningful mathematical models directly from data without imposing a specific structure. This level of adaptability is especially beneficial in scientific and engineering fields, where comprehending and articulating the underlying data relationships is just as important as making accurate predictions. Genetic Programming (GP) has been extensively utilized for symbolic regression and has demonstrated remarkable success in diverse domains. However, GP’s heavy reliance on evolutionary mechanisms makes it computationally intensive and challenging to handle. On the other hand, Particle Swarm Optimization (PSO) has demonstrated remarkable performance in numerical optimization with parallelism, simplicity, and rapid convergence. These attributes position PSO as a compelling option for Automatic Programming (AP), which focuses on the automatic generation of programs or mathematical models. Particle Swarm Programming (PSP) has emerged as an alternative to Genetic Programming (GP), with a specific emphasis on harnessing the efficiency of PSO for symbolic regression. However, PSP remains unsolved due to the high-dimensional search spaces and local optimal regions in AP, where traditional PSO can encounter issues such as premature convergence and stagnation. To tackle these challenges, we introduce Dynamical Sphere Regrouping PSO Programming (DSRegPSOP), an innovative PSP implementation that integrates DSRegPSO’s dynamical sphere regrouping and momentum conservation mechanisms. DSRegPSOP is specifically developed to deal with large-scale, high-dimensional search spaces featuring numerous local optima, thus proving effective behavior for symbolic regression tasks. We assess DSRegPSOP by generating 10 mathematical expressions for mapping points from functions with varying complexity, including noise in position and cost evaluation. Moreover, we also evaluate its performance using real-world datasets. Our results show that DSRegPSOP effectively addresses the shortcomings of PSO in PSP by producing mathematical models entirely generated by AP that achieve accuracy similar to other machine learning algorithms optimized for regression tasks involving numerical structures. Additionally, DSRegPSOP combines the benefits of symbolic regression with the efficiency of PSO.
Plastic-Degrading Enzymes from Marine Microorganisms and Their Potential Value in Recycling Technologies
Authors: Ruginescu Robert , Purcarea Cristina
Published: September 2024

Since the 2005 discovery of the first enzyme capable of depolymerizing polyethylene terephthalate (PET), an aromatic polyester once thought to be enzymatically inert, extensive research has been undertaken to identify and engineer new biocatalysts for plastic degradation. This effort was directed toward developing efficient enzymatic recycling technologies that could overcome the limitations of mechanical and chemical methods. These enzymes are versatile molecules obtained from microorganisms living in various environments, including soil, compost, surface seawater, and extreme habitats such as hot springs, hydrothermal vents, deep-sea regions, and Antarctic seawater. Among various plastics, PET and polylactic acid (PLA) have been the primary focus of enzymatic depolymerization research, greatly enhancing our knowledge of enzymes that degrade these specific polymers. They often display unique catalytic properties that reflect their particular ecological niches. This review explores recent advancements in marine-derived enzymes that can depolymerize synthetic plastic polymers, emphasizing their structural and functional features that influence the efficiency of these catalysts in biorecycling processes. Current status and future perspectives of enzymatic plastic depolymerization are also discussed, with a focus on the underexplored marine enzymatic resources.
Nanostructured Affinity Membrane to Isolate Extracellular Vesicles from Body Fluids for Diagnostics and Regenerative Medicine
Authors: Torsello Monica , Animini Margherita , Gualandi Chiara , Perut Francesca , Pollicino Antonino , Boi Cristiana , Focarete Maria Letizia
Published: September 2024

Electrospun regenerated cellulose (RC) nanofiber membranes were prepared starting from cellulose acetate (CA) with different degrees of substitution. The process was optimized to obtain continuous and uniformly sized CA fibers. After electrospinning, the CA membranes were heat-treated to increase their tensile strength before deacetylation to obtain regenerated cellulose (RC). Affinity membranes were obtained by functionalization, exploiting the hydroxyl groups on the cellulose backbone. 1,4-Butanediol-diglycidyl ether was used to introduce epoxy groups onto the membrane, which was further bioconjugated with the anti-CD63 antibody targeting the tetraspanin CD63 on the extracellular vesicle membrane surface. The highest ligand density was obtained with an anti-CD63 antibody concentration of 6.4 µg/mL when bioconjugation was performed in carbonate buffer. The resulting affinity membrane was tested for the adsorption of extracellular vesicles (EVs) from human platelet lysate, yielding a very promising binding capacity above 10 mg/mL and demonstrating the suitability of this approach.
Microfluidic Applications in Prostate Cancer Research
Authors: Szewczyk Kailie , Jiang Linan , Khawaja Hunain , Miranti Cindy K. , Zohar Yitshak
Published: September 2024

Prostate cancer is a disease in which cells in the prostate, a gland in the male reproductive system below the bladder, grow out of control and, among men, it is the second-most frequently diagnosed cancer (other than skin cancer). In recent years, prostate cancer death rate has stabilized and, currently, it is the second-most frequent cause of cancer death in men (after lung cancer). Most deaths occur due to metastasis, as cancer cells from the original tumor establish secondary tumors in distant organs. For a long time, classical cell cultures and animal models have been utilized in basic and applied scientific research, including clinical applications for many diseases, such as prostate cancer, since no better alternatives were available. Although helpful in dissecting cellular mechanisms, these models are poor predictors of physiological behavior mainly because of the lack of appropriate microenvironments. Microfluidics has emerged in the last two decades as a technology that could lead to a paradigm shift in life sciences and, in particular, controlling cancer. Microfluidic systems, such as organ-on-chips, have been assembled to mimic the critical functions of human organs. These microphysiological systems enable the long-term maintenance of cellular co-cultures in vitro to reconstitute in vivo tissue-level microenvironments, bridging the gap between traditional cell cultures and animal models. Several reviews on microfluidics for prostate cancer studies have been published focusing on technology advancement and disease progression. As metastatic castration-resistant prostate cancer remains a clinically challenging late-stage cancer, with no curative treatments, we expanded this review to cover recent microfluidic applications related to prostate cancer research. The review includes discussions of the roles of microfluidics in modeling the human prostate, prostate cancer initiation and development, as well as prostate cancer detection and therapy, highlighting potentially major contributions of microfluidics in the continuous march toward eradicating prostate cancer.
Effects of Mo Addition on Microstructure and Corrosion Resistance of Cr25-xCo25Ni25Fe25Mox High-Entropy Alloys via Directed Energy Deposition
Authors: Kim Han-Eol , Kim Jae-Hyun , Jeong Ho-In , Cho Young-Tae , Salem Osama , Jung Dong-Won , Lee Choon-Man
Published: September 2024

Highly entropy alloys (HEAs) are novel materials that have great potential for application in aerospace and marine engineering due to their superior mechanical properties and benefits over conventional materials. NiCrCoFe, also referred to as Ni-based HEA, has exceptional low-temperature strength and microstructural stability. However, HEAs have limited corrosion resistance in some environments, such as a 3.5 wt% sodium chloride (NaCl) solution. Adding corrosion-resistant elements such as molybdenum (Mo) to HEAs is expected to increase their corrosion resistance in a variety of corrosive environments. Metal additive manufacturing reduces production times compared to casting and eliminates shrinkage issues, making it ideal for producing homogeneous HEA. This study used directed energy deposition (DED) to create Cr25-xCo25Ni25Fe25Mox (x = 0, 5, 10%) HEAs. Tensile strength and potentiodynamic polarization tests were used to assess the materials’ mechanical properties and corrosion resistance. The mechanical tests revealed that adding 5% Mo increased yield strength (YS) by 20.1% and ultimate tensile strength (UTS) by 9.5% when compared to 0% Mo. Adding 10% Mo led to a 32.5% increase in YS and a 20.4% increase in UTS. Potentiodynamic polarization tests were used to assess corrosion resistance in a 3.5-weight percent NaCl solution. The results showed that adding Mo significantly increased initial corrosion resistance. The alloy with 5% Mo had a higher corrosion potential (Ecorr) and a lower current density (Icorr) than the alloy with 0% Mo, indicating improved initial corrosion resistance. The alloy containing 10% Mo had the highest corrosion potential and the lowest current density, indicating the slowest corrosion rate and the best initial corrosion resistance. Finally, Cr25-xCo25Ni25Fe25Mox (x = 0, 5, 10%) HEAs produced by DED exhibited excellent mechanical properties and corrosion resistance, which can be attributed to the presence of Mo.