bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evolution of research related to how a sedentary lifestyle influences the aging process: a bibliometric review
Authors: Cabo Carolina A. , Hernández-Beltrán Víctor , Gamonales José M. , Parraca José A. , Fernandes Orlando , Espada Mario C. 
Published: July 2024

Abstract
Aim
The world’s population suffers greatly from sedentary lifestyles, which are becoming more common as a result of factors such as a lack of easily accessible places to exercise, a rise in sedentary work practices such as office work, and the pervasive use of television and video devices. Consequently, associated health problems are escalating. The primary goal of this study was to examine the state and features of current trends in international publications regarding the effects of sedentary behavior on the elderly.

Subject and methods
A bibliometric analysis spanning the years 1994–2022, identifying a total of 311 documents, was carried out using the Web of Science Core Collection.

Results
The findings showed an exponential increase of 79% from 1997 to the present. The most productive journal categories, authors, and countries were Geriatrics & Gerontology and Public, Environmental & Occupational Health; authors S. Amagasa, N. Fukushima, S. Inoue, and H. Kikuchi; and the United States, respectively. Considerable variation was found in the keywords; “aging” and “sedentary lifestyle” were the most frequent terms, with 97 and 37 instances, respectively.

Conclusion
Maximum investment in programs promoting physical activity is necessary to improve quality of life as people age. Participants’ mental health will improve as a result of these programs, and their risk of illness will decrease.
A flexible multiscale algorithm based on an improved smoothed particle hydrodynamics method for complex viscoelastic flows
Authors: Ren Jinlian , Lu Peirong , Jiang Tao , Liu Jianfeng , Lu Weigang 
Published: July 2024

AbstractViscoelastic flows play an important role in numerous engineering fields, and the multiscale algorithms for simulating viscoelastic flows have received significant attention in order to deepen our understanding of the nonlinear dynamic behaviors of viscoelastic fluids. However, traditional grid-based multiscale methods are confined to simple viscoelastic flows with short relaxation time, and there is a lack of uniform multiscale scheme available for coupling different solvers in the simulations of viscoelastic fluids. In this paper, a universal multiscale method coupling an improved smoothed particle hydrodynamics (SPH) and multiscale universal interface (MUI) library is presented for viscoelastic flows. The proposed multiscale method builds on an improved SPH method and leverages the MUI library to facilitate the exchange of information among different solvers in the overlapping domain. We test the capability and flexibility of the presented multiscale method to deal with complex viscoelastic flows by solving different multiscale problems of viscoelastic flows. In the first example, the simulation of a viscoelastic Poiseuille flow is carried out by two coupled improved SPH methods with different spatial resolutions. The effects of exchanging different physical quantities on the numerical results in both the upper and lower domains are also investigated as well as the absolute errors in the overlapping domain. In the second example, the complex Wannier flow with different Weissenberg numbers is further simulated by two improved SPH methods and coupling the improved SPH method and the dissipative particle dynamics (DPD) method. The numerical results show that the physical quantities for viscoelastic flows obtained by the presented multiscale method are in consistence with those obtained by a single solver in the overlapping domain. Moreover, transferring different physical quantities has an important effect on the numerical results.
Theoretical Investigation of Propylene Epoxidation Using H2 and O2 Over Titanosilicate-Supported Au Catalysts
Authors: Hamada Yasutaka , Yonemori Tomohisa , Ishimaru Yuhki , Kawakami Takashi , Yamanaka Shusuke , Okumura Mitsutaka 
Published: July 2024

AbstractTitanosilicate-supported Au-cluster catalysts can be used to selectively synthesize propylene oxide from propylene using O2 and H2. However, the details of the catalytic reaction mechanism have not yet been elucidated. Thus, the reaction mechanism was investigated using density functional theory calculations. The calculation results revealed that active Ti-OOH forms on the surface Ti site, which is active as an oxidant and acts as an anchorage site for Au nanoclusters. The rate-determining step of propylene oxide synthesis on Au/titanosilicate is O insertion into propylene, with an activation energy of 1.37 eV. The propylene involved in this reaction is activated by adsorption on Au nanoclusters. Moreover, it was also found that the formation of Ti-OOH on Au/titanosilicate requires an activation energy of 0.48 eV, while it is barrierless on Au/anatase-TiO2. However, the decomposition energy of Ti-OOH on Au/titanosilicate is −0.16 eV, which is smaller than that on Au/anatase-TiO2 (−1.12 eV). The results indicate that Ti-OOH decomposes more readily on Au/titanosilicate than on Au/anatase-TiO2 but is easily regenerated because the reaction energy is significantly smaller than that on Au/anatase-TiO2. Therefore, these calculations are qualitatively in good agreement with the experimental results for Au/titanosilicate, which exhibited high catalytic activity at high temperatures.
Graphical Abstract
The SSIS SEL Brief Scales – Student Form: Examining the Structural Validity of a Portuguese Version
Authors: Ganicho Ana , Magalhães Sofia , Limpo Teresa , Lemos Marina S. , Alves Diana 
Published: July 2024

Abstract

Background
Despite the increased use of social and emotional learning (SEL) programs, empirical research is hindered by lengthy assessment options, difficult to fit into educational contexts. To cover these needs, the Social Skills Improvement System SEL Brief Scales – Student Form (SSIS SELb-S) was developed. Although it has been translated into several languages, a Portuguese version with sound psychometric properties is still missing.

Objective
This study aimed to develop the Portuguese version (SSIS SELb-Spt) and to examine its psychometric properties. METHODS: After translating the original SSIS SELb-S to Portuguese, the instrument was administered to 200 5th graders, along with self- and hetero-report measures of school well-being and involvement, peer acceptance, and academic achievement. We examined the SSIS SELb-Spt factorial validity and reliability, tested its correlations with external correlates, and examined the instruments’ predictive validity.

Results
Results supported a three-factor structure of the scale, which included the dimensions of intrapersonal and interpersonal skills, and responsible decision-making. Correlations with external correlates were in the expected direction. Moreover, the scale predicted school involvement and later academic achievement.

Conclusion
This study seems to corroborate and extend previous knowledge about the validity of SSIS SELb-S, offering validity and reliability evidence on the scale’s three-factor structure.
Explainable and interpretable machine learning and data mining
Authors: Atzmueller Martin , Fürnkranz Johannes , Kliegr Tomáš , Schmid Ute 
Published: July 2024

AbstractThe growing number of applications of machine learning and data mining in many domains—from agriculture to business, education, industrial manufacturing, and medicine—gave rise to new requirements for how to inspect and control the learned models. The research domain of explainable artificial intelligence (XAI) has been newly established with a strong focus on methods being applied post-hoc on black-box models. As an alternative, the use of interpretable machine learning methods has been considered—where the learned models are white-box ones. Black-box models can be characterized as representing implicit knowledge—typically resulting from statistical and neural approaches of machine learning, while white-box models are explicit representations of knowledge—typically resulting from rule-learning approaches. In this introduction to the special issue on ‘Explainable and Interpretable Machine Learning and Data Mining’ we propose to bring together both perspectives, pointing out commonalities and discussing possibilities to integrate them.
Anchoring as a Structural Bias of Deliberation
Authors: Braun Sebastian Till , Rad Soroush Rafiee , Roy Olivier 
Published: July 2024

AbstractWe study the anchoring effect in a computational model of group deliberation on preference rankings. Anchoring is a form of path-dependence through which the opinions of those who speak early have a stronger influence on the outcome of deliberation than the opinions of those who speak later. We show that anchoring can occur even among fully rational agents. We then compare the respective effects of anchoring and three other determinants of the deliberative outcome: the relative weight or social influence of the speakers, the popularity of a given speaker’s opinion, and the homogeneity of the group. We find that, on average, anchoring has the strongest effect among these. We finally show that anchoring is often correlated with increases in proximity to single-plateauedness. We conclude that anchoring can constitute a structural bias that might hinder some of the otherwise positive effects of group deliberation.
Mechanical and Microstructural Characterization of a Nano-stabilized Sandy Soil
Authors: Jafari Kermanipour Mojtaba , Bagheripour Mohammad Hossein , Yaghoubi Ehsan 
Published: July 2024

AbstractThis research investigates the potential of using nanoparticles, Poly Aluminum Silicate and Poly Calcium Silicate, and industrial by-products, Recycled Glass Powder (RGP) and Ground Granulated Ballast Furnace Slag (GGBS) to enhance the durability and strength of a sandy soil, particularly in wet or saturated conditions where water table is close to building foundations. The study aims to determine the optimal content and concentration of additives and assess their influence on the compressive strength and the failure strain. The optimal content and concentration of dry additives and alkaline solutions were determined. Uniaxial compressive strength tests were conducted on various stabilized geopolymers, considering factors such as alkaline activator type, nanoparticle type and percentage, and degree of saturation. Scanning electron microscopy images were taken and analyzed to verify geomechanical testing outcomes. Mixtures with nanomaterials exhibited greater strength than untreated soil, with some exhibiting up to a tenfold increase. GGBS-based samples displayed a twofold increase in strength with nanomaterial addition, while RGP-based samples experienced reduced strength. However, both nanomaterials addressed the durability concerns in wet conditions. The addition of 2% nanomaterials to GGBS-based mixtures led to significant strength gains, with some showing a 20% increase after saturation. This research indicated the potential of nanoparticles and industrial by-products in resolving a major concern regarding geopolymers which is the lack of durability in wet or saturated conditions. These findings have implications for eco-friendly geoconstruction materials and practices.
Leveraging Greenhouse Gas Emissions Traceability in the Groundnut Supply Chain: Blockchain-Enabled Off-Chain Machine Learning as a Driver of Sustainability
Authors: El Hathat Zakaria , Venkatesh V. G. , Sreedharan V. Raja , Zouadi Tarik , Manimuthu Arunmozhi , Shi Yangyan , Srinivas S. Srivatsa 
Published: July 2024

Abstract
As emphasized in multiple United Nations (UN) reports, sustainable agriculture, a key goal in the UN Sustainable Development Goals (SDGs), calls for dedicated efforts and innovative solutions. In this study, greenhouse gas (GHG) emissions in the groundnut supply chain from the region of Diourbel & Niakhar, Senegal, to the port of Dakar are investigated. The groundnut supply chain is divided into three steps: cultivation, harvesting, and processing/shipping. This work adheres to UN guidelines, addressing the imperative for sustainable agriculture by applying machine learning-based predictive modeling (MLPMs) utilizing the FAOSTAT and EDGAR databases. Additionally, it provides a novel approach using blockchain-enabled off-chain machine learning through smart contracts built on Hyperledger Fabric to secure GHG emissions storage and machine learning’s predictive analytics from fraud and enhance transparency and data security. This study also develops a decision-making dashboard to provide actionable insights for GHG emissions reduction strategies across the groundnut supply chain.
Robust bilevel optimization for near-optimal lower-level solutions
Authors: Besançon Mathieu , Anjos Miguel F. , Brotcorne Luce 
Published: July 2024

AbstractBilevel optimization problems embed the optimality of a subproblem as a constraint of another optimization problem. We introduce the concept of near-optimality robustness for bilevel optimization, protecting the upper-level solution feasibility from limited deviations from the optimal solution at the lower level. General properties and necessary conditions for the existence of solutions are derived for near-optimal robust versions of general bilevel optimization problems. A duality-based solution method is defined when the lower level is convex, leveraging the methodology from the robust and bilevel literature. Numerical results assess the efficiency of exact and heuristic methods and the impact of valid inequalities on the solution time.
Age-independent benefits of postoperative rehabilitation during chemoradiotherapy on functional outcomes and survival in patients with glioblastoma
Authors: Natsume Keisuke , Yoshida Akira , Sakakima Harutoshi , Yonezawa Hajime , Kawamura Kentaro , Akihiro Shintaro , Hanaya Ryosuke , Shimodozono Megumi 
Published: July 2024

Abstract
Purpose
To investigate the impact of early and continuous postoperative inpatient rehabilitation during chemoradiotherapy on functional outcomes and overall survival (OS) in patients with glioblastoma (GBM), particularly in different age groups.

Methods
This retrospective cohort study at a university hospital (2011–2016) included 75 of 119 consecutive patients newly diagnosed with GBM who underwent standardized treatment and postoperative rehabilitation. Patients were divided into older (≥ 65 years, n = 45) and younger (< 65 years, n = 30) groups, engaging in a 50-day rehabilitation program. We assessed rehabilitation progress, Barthel Index (BI), Brunnstrom Recovery Stage (BRS), adverse events, and OS. BI at discharge and survival were analyzed using multivariate and Cox regression models, respectively.

Results
The mean age was 72.5 ± 6.3 and 52.4 ± 7.8 years in the older and younger groups, respectively. Both groups demonstrated significant improvements in BI and BRS. Despite more adverse events in the older group, no significant difference existed in median OS (older group: 18.7 months vs. younger group: 18.3 months, p = 0.87). Early walking training, reduced fatigue during chemoradiotherapy, and high Karnofsky Performance Status at admission significantly impacted the BI at discharge. Cox regression analysis identified the BI at discharge as a significant predictor of survival (hazard ratio [HR] 0.98, 95% confidence interval [CI] 0.97–0.99, p = 0.008).

Conclusion
Integrated rehabilitation improves functional outcomes, and enhanced ADL at discharge is associated with improved survival outcomes in patients with GBM, regardless of age. This highlights the need for personalized rehabilitation in treatment protocols. Further prospective studies are warranted to confirm these findings.
Nonuniformity of diffractive splitting and receiver-transmitter alignment for large-field-of-view hundred-beam-scale LiDAR
Authors: Jia Hou , Zhonghao Zhao , Genghua Huang , Ziqing Jiang , Zhiqiang Peng , Zhiping He 
Published: July 2024

AbstractTo meet the spatial perception requirements for autonomous ship navigation in common scenarios such as ocean navigation, port entry and exit, and lock passage, commercial vehicle-mounted LiDAR technology falls short of demands in aspects such as sensing distance, field of view, angular resolution, and spatial sampling density. This paper proposes a hundred-beam-scale LiDAR scheme based on large-field-of-view diffractive beam splitting and a fiber array for echo reception and presents an in-depth investigation of the angular nonuniformity of diffractive beam splitting and the microradian-scale alignment for such hundred-beam-scale large-field-of-view LiDAR. This paper considers a combination of split-beam transmission based on a high-order diffractive optical element (DOE) and echo reception based on a high-precision fiber-optic line array. The nonlinear angular characteristics of the DOE are deduced and analyzed for a large field of view. The units of the receiving fiber-optic array are designed to offset the influence of the angular nonlinearity of the DOE, ensuring high-precision receiver–transmitter alignment of the hundred-beam-scale LiDAR for beams at any order of diffraction and helping to reduce system errors. The above-described LiDAR system has undergone laboratory testing and practical engineering verification, and it provides a new optical solution for LiDAR systems at the hundred-beam scale with a large field of view, a small divergence angle, and high sampling density. The presented system achieves a registration accuracy of 66.5 μrad with 128 beams and a 10-degree field of view, greatly improving signal reception efficiency. Such LiDAR systems have a wide range of applications, including space docking, target identification, lunar and planetary exploration, and ground-based vehicle-mounted LiDAR.
A bidirectional free space optical link for last-mile terrestrial access links employing a novel wavelength shift keying technique
Authors: Qu Changjia , Ghafoor Salman , Ahmad Arsalan , Mirza Jawad , Aljohani Abdulah Jeza , Aziz Imran 
Published: July 2024

AbstractIn this study, we propose a novel wavelength shift keying (WSK) technique that is combined with the conventional intensity modulation scheme for the transmission of point-to-point bidirectional data at the rate of 10 Gbps in each direction. We observe that WSK technique has not been investigated for implementation in point-to-point free space optical (FSO) links. Therefore, to the best of our knowledge, our study is the first one to perform this investigation. Our proposed link uses WSK in the downlink direction while we re-use the optical carriers for the transmission of uplink data. The use of WSK in the downlink direction enables us to perform balanced detection at the receiver, resulting in 3 dB improvement in receiver sensitivity compared to simple direct detection. We present bit error rate (BER) results for the signals transmitted in both the directions under different turbulence conditions and FSO link lengths. It was observed that the downlink signals generally perform better compared to the uplink due to the use of balanced detection and higher intensity fluctuations induced over the re-used optical carrier transmitted in the uplink direction.Please check and confirm that all the author names (given name, family name) and initials are correctly identified. The author names and initials are CORRECT.
Measurement invariance of the PROMIS emotional distress and subjective well-being domains among autistic and General Population adolescents
Authors: Kaplan-Kahn Elizabeth A. , Benecke Rachel M. , Guthrie Whitney , Yerys Benjamin E. , Holmes Laura Graham , Miller Judith S. 
Published: July 2024

Abstract
Purpose
Quality of life (QoL) is identified as a clinical and research priority by the autistic community. Researchers have the responsibility to ensure that instruments used to measure QoL do so reliably and accurately among autistic participants.

Methods
Our study evaluated measurement invariance of Emotional Distress (Depression, Anxiety, Anger, Psychological Stress) and Subjective Well-Being (Life Satisfaction, Positive Affect, and Meaning & Purpose) scales of the Patient-Reported Outcomes Measurement Information System (PROMIS) among groups of autistic (N=140, n per scale=132–140) and general population (N=1,224, n per scale=406–411) teenagers (14–17 years). These scales were included in the PROMIS Autism Battery-Lifespan, which uses PROMIS scales to measure QoL domains most relevant for autistic people.

Results
Multi-group confirmatory factor analyses using permutation tests demonstrated that Depression and Positive Affect scales exhibited scalar invariance between groups, indicating that scores can be meaningfully compared across autistic and general population teens. Anger and Psychological Stress scales demonstrated metric invariance between groups, indicating that these scales measure the same latent trait in both groups, but group comparisons are not supported.

Conclusion
We provide guidance as to how these scales can be used in psychometrically supported ways to capture constructs relevant for understanding QoL among autistic teens.
Temperature dependence of feeding activity in the invasive freshwater snail Pomacea canaliculata: implications for its response to climate warming
Authors: Miyata Yudai , Nakatsubo Takayuki 
Published: July 2024

AbstractPomacea canaliculata, a freshwater snail native to South America, has become widely naturalised in many countries, causing serious damage to agricultural and native ecosystems. Although climate warming is likely to expand the distribution of this species, limited information exists regarding its impact on feeding activities. In this study, we examined the effects of temperature on the feeding activity of this species and estimated the impact of climate warming on its feeding potential. The feeding activity was determined by measuring the amount of standard food (Japanese mustard spinach, komatsuna) ingested at different temperatures. It tended to increase from 15 to 25 °C but became almost stable from 25 to 35 °C. The respiration rate determined by the O2 consumption rate, showed a similar response to temperature. Based on these findings, we constructed a simple model to estimate the relative feeding activity using climatic data recorded at meteorological stations throughout the Japanese Archipelago. The model estimated that, with warming of + 2 °C, annual feeding potential (relative value) increased by 21.1% at the present northern distribution limit of this species. The effect of warming on percentage increase in feeding potential was estimated to be smaller at the southern distribution limit (9.9%), although the absolute feeding potential was larger than that at the northern sites. The model also suggested that if this species expanded its northern distribution range as a result of climate warming, it would have a high feeding potential comparable to that of the southern regions.