bluuebunny/crossref_metadata_2025 huggingface dataset:
Identity and Temporal Fragmentation in Borderline Personality Disorder: A Systematic Review
Authors: Faggioli Ilaria , Esposito Cecilia Maria , Stanghellini Giovanni
Published: December 2024

Background: Borderline Personality Disorder (BPD) is a prevalent psychopathological condition, affecting 0.7–2.7% of the general population. Given the known link between identity formation and the temporal, metacognitive, and narrative processes that contribute to its coherence, the aim of the present systematic review is to synthesize the current literature about the relationship between identity diffusion and lived time in adult patients with BPD. This would enhance knowledge and treatments, leading to a better understanding of the implications of time processes on identity diffusion in BPD. Methods: According to PRISMA guidelines, the main databases were consulted, and specific eligibility criteria were applied. The selection leads to the inclusion of 15 articles, investigating through integrated techniques the lived time, memory, self-reported narratives, and metacognition in BPD subjects. Results: A general agreement among researchers was found, confirming greater difficulty for BPD subjects in producing autobiographical stories, logically and temporally integrated, characterized by positive content. Functional and structural alterations were detected to explain narrative incoherence, as well as symptoms such as emotional dysregulation and cognitive biases. Conclusions: The difficulty for BPD subjects in producing a coherent personal narrative has been interpreted as a correlation of anomalies in autobiographical memories and consequently identities, which were equally compromised by the experience of discontinuity in the temporal structure. This would confirm the hypothesis of the temporal fragmentation of the self in BPD. Although some limitations have been encountered, we suggest that the understanding of identity diffusion and lived time in BPD subjects could represent a useful guide for further research.
At the Frontiers of Neurorehabilitation, Series II: Advancing Neurorehabilitation Through Patient-Centered Undogmatic Innovative Approaches
Authors: Viruega Hélène , Gaviria Manuel
Published: December 2024

At the Frontiers of Neurorehabilitation: Series II [...]
Numerical Simulation of the Distribution Patterns of Particle Deposition on the Vertical Wall Behind Near-Wall Heat Source
Authors: Chen Xi , Wang Peng , Li Jiangyi , Yang Liu , Liu Yang , Xia Jialing
Published: December 2024

Near-wall heat sources have a crucial part to play in the process of particle deposition. Thus, this study investigates the impact of the near-wall heat source on the distribution patterns of particle deposition on the vertical wall behind the heat source, taking into account the variability in heat source temperatures and distances from the vertical wall. A model based on the Eulerian–Lagrangian method was established for tracking the motion trajectories of 1000 particles with a density of 1400 kg/m3 and a particle size range of 0.01–10.0 μm. The temperature field, airflow field, and particle deposition distribution in six cases were analyzed. It was shown that the heat source temperature significantly affectis the temperature field, airflow field, and particle deposition distribution on the vertical wall behind the heat source. This study demonstrated that as the temperature rises, the quantity of particles deposited in the upper-right region of the vertical wall decreases more noticeably. The quantity of particles deposited onto the vertical wall is inversely related to the distance between the near-wall heat source and the vertical wall. On one hand, the deposition distribution law serves as a foundation for advancing the technology aimed at removing suspended particles via thermal plumes. On the other hand, it provides critical insights for addressing the challenges associated with harmful particle deposition linked to the attachment effects of thermal plumes.
Impact of the Aging Process on the Ability of Decorative Materials Containing Biocides to Support Fungal Growth
Authors: Zine Filali Nouha , Braish Tamara , Locoge Nadine , Andres Yves
Published: December 2024

Building and finishing materials are among the main sources of indoor air pollution and can provide ideal substrates for microbial growth. Environmental factors can induce physico-chemical aging of these materials, altering their composition and increasing their vulnerability to microbial growth. To mitigate this risk, manufacturers are increasingly adding biocidal agents to these materials to prevent microbial contamination. The aim of this project was to study the sensitivity of two different acrylic paints to fungal growth, before and after an aging process, and to assess the impact of aging on the effectiveness of the biocides contained in these materials. To do this, two paints (antifungal and normal paint) were applied to a wall covering (polyester-cellulose) before being subjected to accelerated aging. The later process was based on the addition of detergent or water and exposing the material to a visible light spectrum, moderate temperature (38 ± 6 °C), and ambient relative humidity (25 ± 17%). Prior to 30 days of incubation, the aged and unaged (“native”) materials were inoculated with fungal spores using a dry aerosolization system. Fungi behavior was then evaluated by the culture method. The results showed that the native and water-aged normal acrylic paint supported fungal growth at 95 ± 5% relative humidity. However, the use of the cleaning product during the aging process provided additional resistance of the materials against fungal growth. On the other hand, the antifungal paint showed no visible growth due to its biocide content. The accelerated aging and incubation processes led to the depletion of the biocides and thus a decrease in their effectiveness against mold development.
Leveraging Machine Learning to Forecast Neighborhood Energy Use in Early Design Stages: A Preliminary Application
Authors: di Stefano Andrea Giuseppe , Ruta Matteo , Masera Gabriele , Hoque Simi
Published: December 2024

The need for energy efficiency in neighborhood-scale architectural design is driven by environmental imperatives and escalating energy costs. This study identifies three key phases in a design process framework where machine learning can be applied to optimize energy consumption in early design stages. The overall framework integrates machine learning tools into the design workflow, enhancing design exploration from concept level and enabling targeted energy assessments. This paper focuses on the first phase (Phase 1) of the framework, which employs machine learning for building energy forecasting using only the few inputs available in a business-as-usual early-stage design workflow. The CatBoost model was selected for its high accuracy in predicting energy consumption using minimal input data. A preliminary application to a case study in New York City showed high predictive accuracy while reducing the input needed, with R2 scores of 0.88 for both cross-validation and test datasets. Shapely additive explanation analysis validated the selection of key influencing parameters such as building area, principal building activity, and climate zones. The test demonstrated discrepancies between the test data-driven model and a physics-based energy model values ranging from −8.69% to 11.04%, which can be considered an acceptable result in early-stage design. The remaining two phases, though outside the scope of this study, are introduced at a conceptual level to provide an overview of the full framework. Phase 2 will analyze building shape and elevation, assessing the total energy use intensity, while Phase 3 will apply district-level energy optimization across interconnected buildings. The findings from Phase 1 underscore the potential of machine learning to integrate energy efficiency considerations into neighborhood-scale design from the earliest stages, providing reliable predictions that can inform sustainable design.
Diabetes Mellitus and Prostate Cancer Risk—A Systematic Review and Meta-Analysis
Authors: Drab Agnieszka , Wdowiak Krystian , Kanadys Wiesław , Zajączkowski Krzysztof , Koczkodaj Paweł , Religioni Urszula , Borowska Mariola , Łoś Magdalena , Lozano-Lorca Macarena
Published: December 2024

Introduction: Prostate cancer is the second most commonly diagnosed malignant tumor worldwide and poses a significant challenge to public health. This systematic review and meta-analysis aims to investigate the association between diabetes mellitus and the risk of developing prostate cancer. Methods: We conducted a search of PubMed, Embase, and the Cochrane Library from 1998 to 2024. The risk of bias within the included studies was assessed using the Newcastle–Ottawa Scale. The DerSimonian–Laird random-effect model was employed for the meta-analysis. Heterogeneity was evaluated using a forest plot and statistically assessed via the Q test, I2 index, and p-values. Results: Forty-three studies involving a total of 3,746,769 patients were included. Both case–control (pOR = 0.68, 95% CI: 0.61–0.97; I2 = 92.24%) and cohort studies (pRR = 0.71, 95% CI: 0.59–0.99; I2 = 85.41%) suggest that diabetes mellitus is associated with a reduced risk of prostate cancer, though with significant heterogeneity (p < 0.05). Subgroup analysis revealed that the risk of developing prostate cancer was significantly higher in patients with a family history of prostate cancer (pRR = 1.25, 95% CI: 1.16–1.35; I2 = 69.51%). Conclusions: Our meta-analysis of recent observational studies indicates that diabetes mellitus is associated with a reduced risk of developing prostate cancer.
FoxP3+ Regulatory T-Cell Quantities in Nodal T-Follicular Helper Cell Lymphomas and Peripheral T-Cell Lymphomas Not Otherwise Specified and Their Impact on Overall Survival
Authors: Erzar Eva , Tzankov Alexandar , Ocvirk Janja , Grčar Kuzmanov Biljana , Boltežar Lučka , Prevodnik Veronika Kloboves , Gašljević Gorana
Published: December 2024

Background/Objectives: The tumour microenvironment (TME) plays an important role in the development and progression of cancer and it differs among lymphomas, both with respect to the composition and quantity of specific tumour-infiltrating immune cells (TICs), such as FoxP3+ regulatory T cells (Tregs). The role of FoxP3+ Tregs in the TME of peripheral T-cell lymphomas (PTCLs) is complex, and their impact on overall survival (OS) remains unclear. Consequently, we aim to evaluate and compare the FoxP3+ cell quantity in nodal PTCLs and reactive lymph nodes (LNs), with a focus on investigating their impact on OS. Methods: excisional lymph node (LN) biopsies from 105 nodal PTCLs and 17 reactive LNs are immunohistochemically stained for FoxP3. Visual scoring of FoxP3+ cells is performed, and different cut-off values are used to evaluate the impact of FoxP3+ cell quantity on OS. Results: FoxP3+ cells are present in the TME of all cases, except for four cases where FoxP3+ is expressed in lymphoma cells. Lower FoxP3+ cell quantities are observed in certain nodal PTCL subtypes compared to reactive LNs. Patients with high FoxP3+ cell quantities show improved OS. However, the FoxP3+ cell quantity is not confirmed as an independent prognostic biomarker. Conclusions: these findings underscore the promise of FoxP3+ cell quantities as added value in prognosis and highlight the potential benefits of Treg-stimulating therapies in PTCLs.
Challenges for the Implementation of Primary Standard Dosimetry in Proton Minibeam Radiation Therapy
Authors: Cotterill John , Flynn Samuel , Thomas Russell , Subiel Anna , Lee Nigel , Homer Michael , Palmans Hugo , De Marzi Ludovic , Prezado Yolanda , Shipley David , Lourenço Ana
Published: December 2024

Background/Objectives: Spatial fractionation of proton fields as sub-millimeter beamlets to treat cancer has shown better sparing of healthy tissue whilst maintaining the same tumor control. It is critical to ensure primary standard dosimetry is accurate and ready to support the modality’s clinical implementation. Methods: This work provided a proof-of-concept, using the National Physical Laboratory’s Primary Standard Proton Calorimeter (PSPC) to measure average absorbed dose-to-water in a pMBRT field. A 100 MeV mono-energetic field and a 2 cm wide SOBP were produced with a spot-scanned proton beam incident on a collimator comprising 15 slits of 400 µm width, each 5 cm long and separated by a center-to-center distance of 4 mm. Results: The results showed the uncertainty on the absorbed dose-to-water in the mono-energetic beam was dominated by contributions of 1.4% and 1.1% (k = 1) for the NPL PSPC and PTW Roos chambers, respectively, originating from the achievable positioning accuracy of the devices. In comparison, the uncertainty due to positioning in the SOBP for both the NPL PSPC and PTW Roos chambers were 0.4%. Conclusions: These results highlight that it may be more accurate and reliable to perform reference dosimetry measuring the Dose-Area Product or in an SOBP for spatially fractionated fields.
Executive Functions Assessment in a Child with Autism: A Pilot Single-Case Study from a Longitudinal and Mixed Methods Approach
Authors: Acero-Ferrero Marian , Escolano-Pérez Elena
Published: December 2024

Although the literature confirms executive deficits in individuals with autism spectrum disorder (ASD) that hinder adaptation, evidence-based intervention programs targeting this area are scarce, and even fewer have evaluated their effectiveness. Objectives: This study aimed to assess a pilot program designed to improve the executive functions of a child five years and nine months in age with ASD. Methods: To evaluate the effects of the intervention, observational methodology was used, which is considered a mixed method in itself as it integrates both qualitative and quantitative elements in its various phases. Specifically, an idiographic, longitudinal, and multidimensional design was followed. A lag sequential analysis was conducted using GSEQ software Version 5.1, enabling us to study changes in the executive functions of a child before, during, and after the intervention, including whether its effects are sustained over time. Results: The sequential patterns obtained indicate more appropriate and complex executive functioning after the three-month intervention, specifically increased cognitive flexibility, improved self-regulation, more accurate evaluation, and progress in inhibitory processes. However, these improvements do not persist over time. Conclusion: This study contributes to the scarcely explored field of executive function interventions in children with ASD, although it is necessary to consider the generalization of the results to other contexts, such as family and school, during interaction with peers.
The Role of Caregivers in Promoting Connectedness in Youth with Mental Health Concerns
Authors: Andrews Brody , Krishnamoorthy Govind , Dallinger Vicki C. , Maybery Darryl
Published: December 2024

Background/Objectives: Mental health concerns among youth represent a critical global public health issue. Research has found that youth with mental health concerns are often reliant on their caregivers while being isolated from peers. Guided by the recovery model of mental health care, this study investigates the often-overlooked role of caregivers in fostering ‘connectedness’ in youth; Methods: Semi-structured interviews were conducted with nine caregivers of youth with mental health issue; Results: Thematic analysis underscored three tasks in the role of caregivers in promoting connectedness in youth: (a) understanding the nature and quality of social networks, (b) supporting readiness to engage in social relationships, and (c) promoting their youth’s social problem solving and self-efficacy; Discussion: These tasks highlight the complex dialectics faced by caregivers in supporting youth recovery. The findings hold key implications for developing interventions, resources and policies designed for caregivers.
Association Between Low Tongue Pressure and Physical Abnormalities in Adolescent and Young Adult Women: A Cross-Sectional Study
Authors: Fujita Yuko , Masuda Shutaro , Takeshima Tomohito , Fujimoto Mai
Published: December 2024

Background: We examined the factors associated with low tongue pressure to clarify its association with physical abnormalities in adolescent and young adult women. Methods: This study enrolled 92 women aged 10–20 years. Following the collection of anthropometric data, measurements were performed, including grip strength, maximum occlusal force, maximum tongue pressure, and masticatory performance. Based on the Rohrer index and body mass index (BMI), the participants were divided into normal weight, underweight, and overweight/obese groups. Low tongue pressure was defined as the bottom 20th percentile of maximum tongue pressure. After univariate analyses, factors associated with low tongue pressure were identified using multivariate binomial logistic regression analysis. Results: In the bivariate analysis, maximum tongue pressure was significantly positively correlated with grip strength (r = 0.407, p < 0.05). Binomial logistic regression analysis revealed that factors associated with low tongue pressure included being underweight (odds ratio [OR] = 7.451, p = 0.005, 95% confidence interval [CI] = 1.857–29.898), being overweight/obese (OR = 18.384, p = 0.004, 95% CI = 2.483–136.112), and having lower grip strength (OR = 0.864, p = 0.015, 95% CI = 0.768–0.972). Conclusions: Low tongue pressure is closely associated with being underweight, being overweight, and having lower grip strength among young women.
Modification of Microstructure and Properties of Cold-Sprayed AlSi10Mg+TiB2 Composite by Friction Stir Process
Authors: Jing Yufei , Xie Xinliang , Li Rengeng
Published: December 2024

This study investigates the influence of friction stir processing (FSP) on the microstructure, microhardness, and tribological properties of cold-sprayed AlSi10Mg+TiB2 composite coatings on Al substrates. Due to the limitation of particle deformation during cold spraying, there were still some porosities and poorly bonded regions in the as-deposited AlSi10Mg+TiB2 composite coating, which decreased the mechanical performance. Applying FSP to the composite coating significantly reduced the porosity and improved metallurgical bonding. Further, the FSP process induced severe plastic deformation, leading to a more uniform distribution of TiB2 particles and a homogenized microstructure in the composite coating. The microhardness decreases progressively from the unaffected region through the heat-affected zone and thermomechanical-affected zone, and ultimately reaches its lowest value in the stir zone. The decreased microhardness is primarily attributed to the removal of the work-hardening effect. The FSP treatment seems to have little impact on the wear performance for both the pure AlSi10Mg and AlSi10Mg+TiB2 composite samples, as the coefficient of friction values and wear rates remain essentially unchanged after the FSP treatments.
The Effect of σ Phase Content on the Hot Working Properties of Super Austenitic Stainless Steel Containing 7Mo-0.42N
Authors: Li Yanguo , Wang Wanshuai , Wang Zhuyu , Chen Chen , Yang Zhinan
Published: December 2024

In the present study, super austenitic stainless steel containing 7Mo-0.42N was isothermally treated at 1100 °C, 1200 °C, and 1250 °C for different times, in order to obtain the samples with different σ precipitate content of 7%, 1.4%, and 0.7%. The effect of σ phase content on the hot working properties of the specimens was investigated under hot compression conditions at 900~1200 °C and strain rates of 0.01~5 s−1. Results show that, with the increase in σ content, the recrystallized grains increase gradually, and the internal stress decreases firstly and then increases. Therefore, the σ phase has two roles in the thermal deformation process. One is that the σ phase promotes recrystallization and the other is that the σ phase hinders dislocation motion. In the hot working diagram of super austenitic stainless steel with different σ phase contents, the distribution of high power consumption and instability regions is significantly different. The sample containing 1.4% σ phase does not show the region where the power dissipation coefficient η is negative, and there is a large number of dynamic recrystallized grains in the high power region, showing good hot working performance. However, the local rheology and cracking in samples containing 0.7% and 7% σ phase after deformation are more serious. Combined with the constitutive equation, hot working diagram, and microstructure, it is found that the optimum hot working property of the super austenitic stainless steel containing 7Mo-0.42N could be obtained when it is deformed at a temperature of 1200 °C with a strain rate of 5 s−1 when the content of σ phase is 1.4%.
Study on the Microstructure and Properties of Al Alloy/Steel CMT Welding–Brazing Joints Under Different Pulse Magnetic Field Intensities
Authors: Pu Juan , Chen Tingmu , Rao Jiawei , Sun Yubo , Chen Yunxia , Jiang Changhua , Sun Huawei
Published: December 2024

Butt welding experiments on 6061 Al alloy and Q235B steel of 2 mm thickness were conducted using an ER4047F flux-cored wire as the filler metal, after adding a pulsed magnetic field into the process of cold metal transfer (CMT) welding. The effect of the pulsed magnetic field intensity on the macro morphology, microstructure, tensile strength and corrosion resistance of the welding–brazing joint was analyzed. The results showed that when the pulsed magnetic field intensity increased from 0 to 60 mT, the wettability and spreadability of the liquid metal were improved. As a result, the appearance of the Al alloy/steel joint was nice. However, when the pulsed magnetic field intensity was 80 mT, the stability of the arc and the forming quality of the joint decreased, which resulted in a deterioration in the appearance of the joint. A pulsed magnetic field with different intensities did not alter the microstructure of the joint. All of the joint was composed of θ-Fe2(Al,Si)5 and τ5-Al7.2Fe1.8Si at the interface and Al-Si eutectic phase and α-Al solid solution at the weld seam zone. Actually, with the pulsed magnetic field intensity increasing from 0 mT to 60 mT, the IMC thickness in the interfacial layer gradually reduced under the action of electromagnetic stirring. Also, the grain in the weld seam was refined, and elements were distributed uniformly. But when the pulsed magnetic field intensity was 80 mT, the grain in the weld seam began to coarsen, and the intermetallic compound (IMC) thickness was too small, which was unfavorable for the metallurgical bonding of Al alloy and steel. Therefore, with the increase in pulsed magnetic field intensity, the tensile strength of the joints first increased and then decreased, and it reached its maximum of 187.7 MPa with a pulsed magnetic field intensity of 60 mT. Similarly, the corrosion resistance of the joint first increased and then decreased, and it was best when the pulse magnetic field intensity was 60 mT. The Nyquist plot and Bode plot confirmed this result. The addition of a pulsed magnetic field caused less fluctuation in the anode current density, resulting in less localized corrosion of the joint using the scanning vibrating electrode technique (SVET). The XPS analysis showed the Al-Fe-Si compounds replacing the Fe-Al compounds in the joint was the main reason for improving its corrosion resistance under the action of a pulsed magnetic field.
Facile Preparation of Composite Coatings with Incorporated 13X Zeolite and CeO2
Authors: Mojsilović Kristina , Tadić Nenad , Stojanović Srna , Damjanović-Vasilić Ljiljana , Vasilić Rastko
Published: December 2024

One-step methods for the formation of efficient thin-film catalysts for wastewater treatment under the sunlight spectrum is a topic of interest for many research groups. This article reports on the facile preparation of photocatalytic coatings by plasma electrolytic oxidation processing from 0.01 M sodium tungstate electrolyte solution containing both 13X zeolite and CeO2. Obtained coatings are characterized with respect to their surface morphology, chemical and phase composition, and possible application as photocatalysts in photodegradation of organic pollutants. All prepared coatings contain elements originating from both substrate and electrolyte solution. Addition of 1 g/L of 13X zeolite and CeO2 in various concentrations to electrolyte solution results in increased photodecomposition of model organic pollutant. The highest photodegradation under simulated sunlight is observed for coatings formed in 0.01 M sodium tungstate with addition of 1 g/L of 13X zeolite and 1 g/L of CeO2, reaching 50% after 6 h of irradiation.
Narrow-Pulse-Width, Straight-Type-Cavity, All-Solid-State Laser at 228.5 nm
Authors: Shen Weihan , Xu Can , Fan Lixiang , Xu Dongxin , Sun Kangxun , Zhao Zhibin , Li Zaijin , Chen Hao , Qiao Zhongliang , Qu Yi
Published: December 2024

Deep-ultraviolet (DUV) lasers operating at a wavelength of 228 nm offer distinct advantages in Raman spectroscopy and analysis, demonstrating significant potential in the field of surgical medicine. This paper details the development of a high-repetition-rate, narrow-pulse-width, short-cavity laser system functioning at 228.5 nm, which is based on Barium Borate (BBO) electro-optic Q-switching. The system utilizes a double-concave resonator structure and a pressure-applied electro-optic Q-switching technique, incorporating Lithium Borate (LBO) and BBO as frequency-doubling crystals. A low-concentration Nd:YVO4 crystal, measuring 4 mm × 4 mm × 5 mm, serves as the gain medium, with a high-reflectivity coating applied to its left end face to function as the total reflection mirror within the resonant cavity. Upon achieving a pump power of 37 W at a repetition rate of 12 kHz, the system produced a maximum average power of 32 mW, with a pulse width varying from 2.48 ns to 2.70 ns and a central wavelength of 228.5 nm, which is effectively applicable for deep-ultraviolet spectral detection.
Surface Modification of Anodized Titanium Surfaces with Chitosan/ε-Polylysine Coating, Aiming for Improved Bioactivity, Biocompatibility, and Anti-Bacterial Properties for Orthopedic Applications
Authors: Jalali Dehkordi Mahshid , Bahrami Abbas , Abbasi Mohammad Saeid , Mokhtari Mohammad Amin , Heidari Laybidi Farnaz , Roosefid Ali , Hosseini-Abari Afrouzossadat , Yazdan Mehr Maryam
Published: December 2024

The increasidng demand for implants due to the aging populations highlights the necessity for applying highly functional coatings on the surface of implants. This study investigates the implications of applying a chitosan/polylysine composite coating on anodized titanium surfaces, aiming for improved biocompatibility, bioactivity, and anti-bacterial properties. Titanium substrates were anodized at 40 volts for a duration of two hours, followed by dip coating with the chitosan/polylysine composite. Fourier-transform infrared (FTIR) analysis was employed to characterize the polymer structure, while field emission scanning electron microscopy (FESEM) and energy-dispersive X-ray spectroscopy (EDS) techniques were utilized to evaluate nanotube morphology and the coating structure. Results showed that samples containing 1.5% polylysine exhibited noticeable anti-bacterial properties and cell viability above fifty percent. Subsequent immersion in simulated body fluid (SBF) for a duration of two weeks revealed the formation of apatite crystals on the coated samples, indicating that the samples are bioactive. Furthermore, polylysine contributed to enhanced resistance against degradation in phosphate-buffered saline (PBS) solution. Overall, the chitosan/polylysine composite coating exhibited promising mechanical and biomedical characteristics, suggesting its potential for applications in orthopedic implants.
Effects of Physical Cooling on the Temperature and Performance of Newly Laid Porous Asphalt Mixtures
Authors: Li Jun , Li Mingliang , Zhang Yi , Ren Wanyan , Li Renfei
Published: December 2024

Porous asphalt pavements need to be cured for 24 h~48 h before they can be opened to traffic. In an emergency, physical cooling methods, such as water sprinkling and air blowing, can be used to accelerate cooling, but the effects of the two methods on the mechanical properties and durability of porous asphalt mixtures are still unclear. In this research, firstly, the dropping and rising temperatures of the pavement surface during the water sprinkling process of newly laid porous asphalt mixtures in real projects were analyzed. The effects of the two conditions of water immersion and water sprinkling on the mechanical properties of porous asphalt mixtures were clarified, and water sprinkling technology for porous asphalt mixtures was proposed. Secondly, the effects of air blowing on the temperature reduction and strength loss of porous asphalt mixtures was analyzed, and the pavement surface temperature control standard that was suitable for air blowing was proposed. Finally, a seven-year observation was carried out on the water sprinkling cooling test section in the actual project. The research results show that water immersion or the sprinkling of water repeatedly during the curing period of porous asphalt pavements reduces the strength of the mixture. It is recommended to use a water amount of 0.3 kg/m2 once and sprinkling four times before painting road markings and two times after painting road markings; this was the best water sprinkling cooling process for porous asphalt pavements. The use of air blowing can accelerate the temperature reduction of porous asphalt mixtures, but the mechanical properties of the mixtures are attenuated after air blowing. Air blowing can be carried out when the pavement surface temperature is lower than 70 °C. Compared with the road section without water sprinkling for cooling, the use of the determined process to cool the newly laid porous asphalt mixtures by water sprinkling does not have a significant adverse effect on their durability. There is also no significant difference in the performances of the two road surfaces within a seven-year service. In an emergency, physical cooling methods, such as water sprinkling or air blowing, can be used to accelerate the temperature reduction of the newly laid porous asphalt mixtures, so as to achieve the purpose of quickly opening to traffic.
Quantum Mechanics/Molecular Mechanics Simulations for Chiral-Selective Aminoacylation: Unraveling the Nature of Life
Authors: Ando Tadashi , Tamura Koji
Published: December 2024

Biological phenomena are chemical reactions, which are inherently non-stopping or “flowing” in nature. Molecular dynamics (MD) is used to analyze the dynamics and energetics of interacting atoms, but it cannot handle chemical reactions involving bond formation and breaking. Quantum mechanics/molecular mechanics (QM/MM) umbrella sampling MD simulations gives us a significant clue about transition states of chemical reactions and their energy levels, which are the pivotal points in understanding the nature of life. To demonstrate the importance of this method, we present here the results of our application of it to the elucidation of the mechanism of chiral-selective aminoacylation of an RNA minihelix considered to be a primitive form of tRNA. The QM/MM MD simulation, for the first time, elucidated the “flowing” atomistic mechanisms of the reaction and indicated that the L-Ala moiety stabilizes the transition state more than D-Ala, resulting in L-Ala preference in the aminoacylation reaction in the RNA. The QM/MM method not only provides important clues to the elucidation of the origin of homochirality of biological systems, but also is expected to become an important tool that will play a critical role in the analysis of biomolecular reactions, combined with the development of artificial intelligence.
Accurate Range-Free Localization Using Cuckoo Search Optimization in IoT and Wireless Sensor Networks
Authors: Hadir Abdelali , Kaabouch Naima
Published: December 2024

Precise positioning of sensors is critical for the performance of various applications in the Internet of Things and wireless sensor networks. The efficiency of these networks heavily depends on the precision of sensor node locations. Among various localization approaches, DV-Hop is highly recommended for its simplicity and robustness. However, despite its popularity, DV-Hop suffers from significant accuracy issues, primarily due to its reliance on average hop size for distance estimation. This limitation often results in substantial localization errors, compromising the overall network effectiveness. To address this gap, we developed an enhanced DV-Hop approach that integrates the cuckoo search algorithm (CS). Our solution improves the accuracy of node localization by introducing a normalized average hop size calculation and leveraging the optimization capabilities of CS. This hybrid approach refines the distance estimation process, significantly reducing the errors inherent in traditional DV-Hop. Findings from simulations reveal that the developed approach surpasses the accuracy of both the original DV-Hop and multiple other current localization methods, providing a more precise and reliable localization method for IoT and WSN applications.
α-Halogenated Curcumins
Authors: Pham Phuong-Truc T. , Bader Mamoun M.
Published: December 2024

α- or 4-Substituted curcumin analogues are scarce. We describe herein the syntheses and crystal structures of the first α-halogenated curcumin derivatives: (1E,6E)-1,7-bis (4-hydroxy-3-methoxyphenyl)-4-bromo-5-hydroxy-1,3,6-heptatriene-3-one or (4-bromocurcumin) (1) and (1E,6E)-1,7-bis (4-hydroxy-3-methoxyphenyl)-4-chloro-5-hydroxy-1,3,6-heptatriene-3-one or (4-chlorocurcumin) (2). We note that the key step in the successful synthesis of the bromo-analog is the use of slightly acidic media to favor the diketo form of curcumin prior to carrying out the reaction. Both newly prepared compounds assume the keto–enol form in the solid state and crystallize in the monoclinic space group P21/c with four molecules in the unit cell each with slightly different dimensions. Inter- and intra- molecular hydrogen bonds were observed in the two structures. Most significant observed features were the inter-molecular O…O distances of 2.842 and 2.840 Å and intra-molecular O…O distances of 2.460 and 2.451 Å for bromo-or (1) and chloro- or (2) derivatives, respectively. No close halogen…halogen contacts were observed in either of the two structures. Both molecules are nearly planar with torsion angles of 0.54 and 1.16 °C between the planes of two terminal phenyl groups for (1) and (2), respectively. π-Stacks were observed in both structures with interplanar distances of 3.367 and 3.454 Å for the bromo- and chloro- compounds, respectively. Hirshfeld surface analysis confirms quantitively a picture of the inter- and intra-molecular interactions in both compounds compared with polymorph I (the most common form) of curcumin. UV–Vis absorption spectra are shifted to higher wavelengths with lmax of 475 and 477 nm for compounds 1 and 2, respectively, compared with 442 nm in dichloromethane solutions. The newly synthesized molecules will open the door for numerous possible synthetic modifications of the α-carbon to prepare valuable analogues of curcumin with more favorable solubility profiles.
Investigation of AI Algorithms for Photometric Online Analysis in a Draft Tube Baffle Crystallizer
Authors: Marsollek Laura , Lamprecht Julius , Kockmann Norbert
Published: December 2024

The rapid advancement of AI algorithms presents new opportunities for sensing technologies based on image recognition, such as real-time crystallization monitoring. This work investigates the use of computer vision to detect and size crystals in a lab scale draft tube baffle crystallizer (DTBC). A specially developed analytical bypass was implemented on the DTBC to enable a low-influence analysis without invasive intrusion into the process. By utilizing AI models such as YouOnlyLookOnce version 8 (YOLOv8), YOLOv8 Segmentation (YOLO8seg), and the convolutional network for biomedical image segmentation U-Net, this study assesses their effectiveness in determining crystal size distributions from photometric images. While U-Net was deemed unsuitable due to computational demands and accuracy issues, YOLOv8 and YOLO8seg performed better in terms of efficiency and precision. YOLO8seg, specifically, achieved the highest accuracy, with a mean average precision (mAP) of 82.3%, and excelling in detecting larger crystals, but underperforming with crystals smaller than 90 µm. Despite this limitation, YOLO8seg was able to compete with the manual methods and was superior to the state-of-the-art algorithm mask region convolutional neural network (Mask R-CNN) in terms of accuracy. The study suggests that specific training and adaptation of the imaging conditions could further improve the crystal detection performance.
Heterogeneous to Homogeneous Melting Transition Observed During a Single Process
Authors: Lv Xue-Qi , Cong Shi-Xin , Li Xiong-Ying , Xia Chun-Ming
Published: December 2024

The melting mechanism at medium heating rates is unclear, owing to the lack of accurate characterizations of structural changes in poly-directional melting conditions. Here, a particular multilayered nanostructure was selected to control the propagation of melting in a single direction. We predicted the heterogeneous to homogeneous melting (HeM to HoM) transition during a single melting process at medium heating rates of 10–400 K/ps by molecular dynamics (MD) simulations, without a change in heating rates. The information on structural changes for the HeM to HoM transition, including the loss of crystallinity and long- and short-range order, are clearly provided by both a single direction and the radial distribution functions. These results contribute to a more comprehensive understanding of the HeM to HoM transition induced by heating rates.
Longitudinal Study of Patients with Connective Tissue Disease–Interstitial Lung Disease and Response to Mycophenolate Mofetil and Rituximab
Authors: Li Yan , Mumtaz Sehreen , Baig Hassan Z. , Mira-Avendano Isabel , Wang Benjamin , Rojas Carlos A. , Stowell Justin T. , Lesser Elizabeth R. , Borkar Shalmali R. , Majithia Vikas , Abril Andy
Published: December 2024

Background/Objective: To investigate the effect of mycophenolate mofetil (MMF) and rituximab (RTX) on pulmonary function test (PFT) results in a mixed cohort of patients with connective tissue disease-associated interstitial lung disease (CTD-ILD), longitudinally followed up for 1 year in a single academic center. Methods: Patients with CTD-ILD were identified in electronic medical records from 1 January 2009 to 30 April 2019. Prescribed MMF and RTX doses, dosage changes, and therapy plans were analyzed individually with improvement in PFT outcomes determined using multivariable linear regression models during 12-month follow-up. Results: Forty-seven patients with CTD-ILD, treated with MMF, RTX, or both, were included. Patients on combined MMF and RTX had worse PFT outcomes at baseline compared with patients on monotherapy. Substantial improvement was observed among all PFT outcomes from baseline to 12 months, regardless of medication dosage or therapy plans. The diffusing capacity of the lungs for carbon monoxide (DLCO) worsened by an average of 7.21 mL/(min*mmHg) (95% CI, 4.08–10.33; p < 0.001) among patients on RTX compared to combined therapy. Patients on higher doses of MMF at baseline experienced an average increase of 0.93 (95% CI, 0.04–1.82) units in DLCO from baseline to 6 months (p = 0.04) and a 2.79% (95% CI, 0.61–4.97%) increase in DLCO from 6 to 12 months (p = 0.02) within patients on concurrent RTX at 6-month follow-up. Conclusions: The treatment of CTD-ILD with MMF and/or RTX was associated with overall improvement in PFT outcomes. Combined therapy resulted in significant improvements in DLCO compared with monotherapy. Higher doses of MMF also provided greater improvements in DLCO.
Minimum and Maximum Pattern-Based Self-Organized Feature Engineering: Fibromyalgia Detection Using Electrocardiogram Signals
Authors: Cambay Veysel Yusuf , Hafeez Baig Abdul , Aydemir Emrah , Tuncer Turker , Dogan Sengul
Published: December 2024

Background: The primary objective of this research is to propose a new, simple, and effective feature extraction function and to investigate its classification ability using electrocardiogram (ECG) signals. Methods: In this research, we present a new and simple feature extraction function named the minimum and maximum pattern (MinMaxPat). In the proposed MinMaxPat, the signal is divided into overlapping blocks with a length of 16, and the indexes of the minimum and maximum values are identified. Then, using the computed indices, a feature map is calculated in base 16, and the histogram of the generated map is extracted to obtain the feature vector. The length of the generated feature vector is 256. To evaluate the classification ability of this feature extraction function, we present a new feature engineering model with three main phases: (i) feature extraction using MinMaxPat, (ii) cumulative weight-based iterative neighborhood component analysis (CWINCA)-based feature selection, and (iii) classification using a t-algorithm-based k-nearest neighbors (tkNN) classifier. Results: To obtain results, we applied the proposed MinMaxPat-based feature engineering model to a publicly available ECG fibromyalgia dataset. Using this dataset, three cases were analyzed, and the proposed MinMaxPat-based model achieved over 80% classification accuracy with both leave-one-record-out (LORO) cross-validation (CV) and 10-fold CV. Conclusions: These results clearly demonstrate that this simple model achieved high classification performance. Therefore, this model is surprisingly effective for ECG signal classification.
A Hybrid Deep Learning Model with Data Augmentation to Improve Tumor Classification Using MRI Images
Authors: Younis Eman M. G. , Mahmoud Mahmoud N. , Albarrak Abdullah M. , Ibrahim Ibrahim A.
Published: December 2024

Background: Cancer ranks second among the causes of mortality worldwide, following cardiovascular diseases. Brain cancer, in particular, has the lowest survival rate of any form of cancer. Brain tumors vary in their morphology, texture, and location, which determine their classification. The accurate diagnosis of tumors enables physicians to select the optimal treatment strategies and potentially prolong patients’ lives. Researchers who have implemented deep learning models for the diagnosis of diseases in recent years have largely focused on deep neural network optimization to enhance their performance. This involves implementing models with the best performance and incorporating various network architectures by configuring their hyperparameters. Methods: This paper presents a novel hybrid approach for improved brain tumor classification by combining CNNs and EfficientNetV2B3 for feature extraction, followed by K-nearest neighbors (KNN) for classification, which has been described as one of the simplest machine learning algorithms based on supervised learning techniques. The KNN algorithm assumes similarities between new cases and available cases and assigns new cases to the category that most closely resembles the available categories. Results: To evaluate the recommended method’s efficacy, two widely known benchmark MRI datasets were utilized in the experiments. The initial dataset consisted of 3064 MRI images depicting meningiomas, gliomas, and pituitary tumors. Images from two classes, consisting of healthy brains and brain tumors, were included in the second dataset, which was obtained from Kaggle. Conclusions: In order to enhance the performance even further, this study concatenated the CNN and EfficientNetV2B3’s flattened outputs before feeding them into the KNN classifier. The proposed framework was run on these two different datasets and demonstrated outstanding performance, with accuracy of 99.51% and 99.8%, respectively.
Sex-Specific Differences in Peripheral Nerve Properties: A Comparative Analysis of Conduction Velocity and Cross-Sectional Area in Upper and Lower Limbs
Authors: Nobue Ayaka , Ishikawa Masaki
Published: December 2024

Background/Objectives: Peripheral nerve conduction velocity (NCV) and nerve cross-sectional area (nCSA) are crucial parameters in neurophysiological assessments, yet their sex-specific differences are not fully understood. This study investigated sex-based variations in NCV and nCSA between upper and lower limbs. Methods: Twenty participants (ten males and ten females) were recruited for this study. The NCV and nCSA of the ulnar and tibial nerves were measured in both the upper and lower limbs. NCV was measured using supramaximal electric stimulation, and nCSA was assessed using peripheral nerve ultrasonography at three regions for each nerve. Supramaximal electric stimulations were applied superficially to the ulnar and tibial nerves at each measurement point. Action potentials were recorded from the abductor digiti minimi and soleus muscles for the ulnar and tibial nerves, respectively. Results: The ulnar nCSA of the upper limbs was significantly greater in males than in females (p < 0.05). However, ulnar NCV was significantly higher in females than in males (p < 0.05). In the lower limbs, no sex differences were observed in tibial NCV or nCSA. Conclusions: These findings reveal sex-specific differences in upper limb peripheral nerve characteristics that may have important implications for clinical assessments and treatment strategies. The contrasting patterns between upper and lower limbs suggest that both developmental and functional factors influence peripheral nerve properties.
Random Walk on T-Fractal with Stochastic Resetting
Authors: Sun Xiaohan , Li Anlin , Zhu Shaoxiang , Zhu Feng
Published: December 2024

In this study, we explore the impact of stochastic resetting on the dynamics of random walks on a T-fractal network. By employing the generating function technique, we establish a recursive relation between the generating function of the first passage time (FPT) and derive the relationship between the mean first passage time (MFPT) with resetting and the generating function of the FPT without resetting. Our analysis covers various scenarios for a random walker reaching a target site from the starting position; for each case, we determine the optimal resetting probability γ* that minimizes the MFPT. We compare the results with the MFPT without resetting and find that the inclusion of resetting significantly enhances the search efficiency, particularly as the size of the network increases. Our findings highlight the potential of stochastic resetting as an effective strategy for the optimization of search processes in complex networks, offering valuable insights for applications in various fields in which efficient search strategies are crucial.
Exploring the Trade-Off in the Variational Information Bottleneck for Regression with a Single Training Run
Authors: Kudo Sota , Ono Naoaki , Kanaya Shigehiko , Huang Ming
Published: December 2024

An information bottleneck (IB) enables the acquisition of useful representations from data by retaining necessary information while reducing unnecessary information. In its objective function, the Lagrange multiplier β controls the trade-off between retention and reduction. This study analyzes the Variational Information Bottleneck (VIB), a standard IB method in deep learning, in the settings of regression problems and derives its optimal solution. Based on this analysis, we propose a framework for regression problems that can obtain the optimal solution of the VIB for all β values with a single training run. This is in contrast to conventional methods that require one training run for each β. The optimization performance of this framework is theoretically discussed and experimentally demonstrated. Our approach not only enhances the efficiency of exploring β in regression problems but also deepens the understanding of the IB’s behavior and its effects in this setting.