bluuebunny/crossref_metadata_2025_split huggingface dataset:
Understanding the impact of bridge structure on river morphology through geospatial techniques: case on Teesta River, Bangladesh
Authors: Uddin Md. Jahir , Shakik Ahmed , Mim Fauzia Barrah 
Published: July 2024

AbstractThe primary priority of bridge construction over a waterway is to support and confirm constant communication. Conversely, it may locally disrupt the health of the river which will have an adverse influence on the hydrological as well as morphological behavior of nearby regions by way of the river’s narrowing. The current study evaluated the effect of bridge structure on river morphological characteristics for Teesta River. Hence to do, this work robbed two approaches. Firstly, the Landsat images from a pre-road bridge (2001 and 2006) and post-road bridge construction (2011, 2016, and 2021) are processed and used for bar formation and bank line shifting. Secondly, the bar properties, differences in channel width, and changes in river bank were evaluated using geospatial technology. The outcomes revealed a recurrent change of bar area and channel width at the upstream side of the bridges and likewise dominating at the downstream side. Throughout the post-road bridge period, the average bar area has increased noticeably by 32.45 sq.km which is 7.75% of the total river area and the downstream bar area has also increased considerably. Besides, both bank lines of the river were dominated by erosion in the post-road bridge construction era. Accordingly, the Teesta Road bridge’s existence has had a significant impact on the morphological modification in recent years. The study also reveals that the bars and islands of Teesta River undergo a drastic change and the river can be treated as a braided one, and also showed the minor trend of meandering. The findings of this research may be supportive for sustainable and long-term planning and development of the rivers and neighboring floodplains in Bangladesh.
On the speed of convergence of discrete Pickands constants to continuous ones
Authors: Bisewski Krzysztof , Jasnovidov Grigori 
Published: July 2024

AbstractIn this manuscript, we address open questions raised by Dieker and Yakir (2014), who proposed a novel method of estimating (discrete) Pickands constants
$\mathcal{H}^\delta_\alpha$
using a family of estimators
$\xi^\delta_\alpha(T)$
,
$T>0$
, where
$\alpha\in(0,2]$
is the Hurst parameter, and
$\delta\geq0$
is the step size of the regular discretization grid. We derive an upper bound for the discretization error
$\mathcal{H}_\alpha^0 - \mathcal{H}_\alpha^\delta$
, whose rate of convergence agrees with Conjecture 1 of Dieker and Yakir (2014) in the case
$\alpha\in(0,1]$
and agrees up to logarithmic terms for
$\alpha\in(1,2)$
. Moreover, we show that all moments of
$\xi_\alpha^\delta(T)$
are uniformly bounded and the bias of the estimator decays no slower than
$\exp\{-\mathcal CT^{\alpha}\}$
, as T becomes large.
Validierung des Dispositionalen Selbstaffirmationsmaßes (DSAM)
Authors: Montagna Melissa , Wenker Theresa , Dickhäuser Oliver 
Published: July 2024

Zusammenfassung: Bislang existierte im deutschen Sprachraum keine Skala, welche die Tendenz von Individuen erfasst, zentrale Aspekte des Selbst zu bestärken (z. B. eigene wichtige Werte). Das Ziel der vorliegenden Studie war es, eine deutsche Version des Spontaneous Self-Affirmation Measure zu validieren ( Harris et al., 2019 ): das Dispositionale Selbstaffirmationsmaß (DSAM). Hierfür führten wir eine querschnittliche Untersuchung an einer Stichprobe von Studierenden ( N = 219) und eine weitere an einer Stichprobe von Arbeitnehmenden ( N = 229) durch. Die Ergebnisse beider Studien sprechen für eine hohe Reliabilität der Skala und deuten darauf hin, dass (1) der Skala eine Bifaktor-S-1-Struktur zugrunde liegt mit einem Self-Affirmation-Generalfaktor und zwei spezifischen Inhaltsfaktoren (Affirmation durch Stärken und soziale Beziehungen). Darüber hinaus (2) sprechen die Zusammenhänge des DSAM mit anderen Selbstbestärkungsstrategien, mit Selbstintegrität und Selbstwirksamkeit für die konvergente und divergente Validität der Skala. Entgegen den Erwartungen zeigte sich jedoch kein signifikanter Zusammenhang mit Defensivität. Mit dem DSAM steht dem deutschsprachigen Raum erstmals ein validiertes Messinstrument zur Erfassung der dispositionalen Selbstaffirmation zur Verfügung.
Formation Mechanism of Fingers That Protrude Eastward From the Io Plasma Disk During the Interchange Instability
Authors: Tanaka T. , Ebihara Y. , Watanabe M. , Fujita S. , Kataoka R. 
Published: July 2024

AbstractThe solar wind‐magnetosphere‐ionosphere interaction at Jupiter is reproduced numerically adopting the nine‐component magnetohydrodynamic simulation. Calculations take into account the magnetosphere‐ionosphere coupling, Jovian rotation, and Io plasma source. High‐speed rotating plasma inside restricted magnetospheric space causes expansion and contraction of magnetic field, forming super‐rotation at radial distance 20∼30 Rj and co‐rotation breakdown further outside. Field‐perpendicular current that restores co‐rotational delay beyond 30 Rj is connected via field‐aligned current to the main oval in the ionosphere. Inside 20 Rj, there is almost co‐rotation region (deviation from co‐rotation less than 20 km/s). Particularly within 10 Rj, the deviation from co‐rotation is less than 2 km/s. In the nearly co‐rotating region, the Io plasma forms a disk structure through field‐aligned redistribution. The interchange instability occurs near the outer wall of the Io plasma disk, and instability flow develops to vortex. Through this instability, a part of the centrifugal drift current supporting the Io plasma disk is connected to low‐latitude field‐aligned current that generates beads‐like spots on the lower latitude side of the main oval. Resulting interchange instability comes to satisfy the structure of convection and enables further development of vortex. The Coriolis force acting on eastward flow inside the developing vortex makes this flow protrude further outward, forming eastward bending fingers. Inside 10 Rj, Io plasma transport by the interchange instability becomes slower, despite the center of the disk. Io plasma escapes from the inner magnetosphere with a time constant of 20 days if this slow transport is taken into account.
Longitudinal study on hippocampal subfields and glucose metabolism in early psychosis
Authors: Armio Reetta-Liina , Laurikainen Heikki , Ilonen Tuula , Walta Maija , Sormunen Elina , Tolvanen Arvi , Salokangas Raimo K. R. , Koutsouleris Nikolaos , Tuominen Lauri , Hietala Jarmo 
Published: July 2024

AbstractAltered hippocampal morphology and metabolic pathology, but also hippocampal circuit dysfunction, are established phenomena seen in psychotic disorders. Thus, we tested whether hippocampal subfield volume deficits link with deviations in glucose metabolism commonly seen in early psychosis, and whether the glucose parameters or subfield volumes change during follow-up period using one-year longitudinal study design of 78 first-episode psychosis patients (FEP), 48 clinical high-risk patients (CHR) and 83 controls (CTR). We also tested whether hippocampal morphology and glucose metabolism relate to clinical outcome. Hippocampus subfields were segmented with Freesurfer from 3T MRI images and parameters of glucose metabolism were determined in fasting plasma samples. Hippocampal subfield volumes were consistently lower in FEPs, and findings were more robust in non-affective psychoses, with strongest decreases in CA1, molecular layer and hippocampal tail, and in hippocampal tail of CHRs, compared to CTRs. These morphometric differences remained stable at one-year follow-up. Both non-diabetic CHRs and FEPs had worse glucose parameters compared to CTRs at baseline. We found that, insulin levels and insulin resistance increased during the follow-up period only in CHR, effect being largest in the CHRs converting to psychosis, independent of exposure to antipsychotics. The worsening of insulin resistance was associated with deterioration of function and symptoms in CHR. The smaller volume of hippocampal tail was associated with higher plasma insulin and insulin resistance in FEPs, at the one-year follow-up. Our longitudinal study supports the view that temporospatial hippocampal subfield volume deficits are stable near the onset of first psychosis, being more robust in non-affective psychoses, but less prominent in the CHR group. Specific subfield defects were related to worsening glucose metabolism during the progression of psychosis, suggesting that hippocampus is part of the circuits regulating aberrant glucose metabolism in early psychosis. Worsening of glucose metabolism in CHR group was associated with worse clinical outcome measures indicating a need for heightened clinical attention to metabolic problems already in CHR.
Personalized rehabilitation approach for reaching movement using reinforcement learning
Authors: Pelosi Avishag Deborah , Roth Navit , Yehoshua Tal , Itah Dorit , Braun Benyamin Orit , Dahan Anat 
Published: July 2024

AbstractMusculoskeletal disorders challenge significantly the performance of many daily life activities, thus impacting the quality of life. The efficiency of the traditional physical therapy programs is limited by ecological parameters such as intervention duration and frequency, number of caregivers, geographic accessibility, as well as by subjective factors such as patient’s motivation and perseverance in training. The implementation of VR rehabilitation systems may address these limitations, but the technology still needs to be improved and clinically validated. Furthermore, current applications generally lack flexibility and personalization. A VR rehabilitation game simulation is developed, which focuses on the upper-limb movement of reaching, an essential movement involved in numerous daily life activities. Its novelty consists in the integration of a machine learning algorithm, enabling highly adaptive and patient-customized therapeutic intervention. An immersive VR system for the rehabilitation of reaching movement using a bubble popping game is proposed. In the virtual space, the patient is presented with bubbles appearing at different locations and is asked to reach the bubble with the injured limb and pop it. The implementation of a Q-learning algorithm enables the game to adjust the location of the next bubble according to the performance of the patient, represented by his kinematic characteristics. Two test cases simulate the performance of the patient during a training program of 10 days/sessions, in order to validate the effectiveness of the algorithm, demonstrated by the spatial and temporal distribution of the bubbles in each evolving scenario. The results show that the algorithm learns the patient’s capabilities and successfully adapts to them, following the reward policy dictated by the therapist; moreover, the algorithm is highly responsive to kinematic features’ variation, while demanding a reasonable number of iterations. A novel approach for upper limb rehabilitation is presented, making use of immersive VR and reinforcement learning. The simulation suggests that the algorithm offers adaptive capabilities and high flexibility, needed in the comprehensive personalization of a rehabilitation process. Future work will demonstrate the concept in clinical trials.
Digital twin and fuzzy framework for supply chain sustainability risk assessment and management in supplier selection
Authors: Hezam Ibrahim M. , Ali Ahmed M. , Sallam Karam , Hameed Ibrahim A. , Abdel-Basset Mohamed 
Published: July 2024

AbstractRisks in the supply chain can damage many companies and organizations due to sustainability risk factors. This study evaluates the supply chain risk assessment and management and then selects the best supplier in a gas company in Egypt. A comprehensive methodology can use the experts' opinions who use the linguistic variables in the spherical fuzzy numbers (SFNs) to evaluate the criteria and suppliers in this study based on their views. Selecting the best supplier is a complex task due to various criteria related to supply chain risk assessment, such as supply risks, environmental risks, financial risks, regularity risks, political risk, ethical risks, and technology risks and their sub-criteria. This study suggested a new combined model with multi-criteria decision-making (MCDM) under a spherical fuzzy set (SFS) environment to overcome uncertainty and incomplete data in the assessment process. The MCDM methodology has two methods: the Entropy and COmbinative Distance-based Assessment (CODAS) methods. The SFS-Entropy is used to compute supply chain risk assessment and management criteria weights. The SFS-CODAS method is used to rank the supplier. The main results show that supply risks have the highest importance, followed by financial and environmental risks, and ethical risks have the lowest risk importance. The criteria weights were changed under sensitivity analysis to show the stability and validation of the results obtained from the suggested methodology. The comparative analysis is implemented with other MCDM methods named TOPSIS, VIKOR, MARCOS, COPRAS, WASPAS, and MULTIMOORA methods under the SFS environment. This study can help managers and organizations select the best supplier with the lowest sustainability risks.
Estimation methods based on ranked set sampling for the power logarithmic distribution
Authors: Alsadat Najwan , Hassan Amal S. , Elgarhy Mohammed , Johannssen Arne , Gemeay Ahmed M. 
Published: July 2024

AbstractThe sample strategy employed in statistical parameter estimation issues has a major impact on the accuracy of the parameter estimates. Ranked set sampling (RSS) is a highly helpful technique for gathering data when it is difficult or impossible to quantify the units in a population. A bounded power logarithmic distribution (PLD) has been proposed recently, and it may be used to describe many real-world bounded data sets. In the current work, the three parameters of the PLD are estimated using the RSS technique. A number of conventional estimators using maximum likelihood, minimum spacing absolute log-distance, minimum spacing square distance, Anderson-Darling, minimum spacing absolute distance, maximum product of spacings, least squares, Cramer-von-Mises, minimum spacing square log distance, and minimum spacing Linex distance are investigated. The different estimates via RSS are compared with their simple random sampling (SRS) counterparts. We found that the maximum product spacing estimate appears to be the best option based on our simulation results for the SRS and RSS data sets. Estimates generated from SRS data sets are less efficient than those derived from RSS data sets. The usefulness of the RSS estimators is also investigated by means of a real data example.
Particulate matter hinders the development and reproduction of predatory mites of Euseius finlandicus (Acariformes: Phytoseiidae)
Authors: Puchalska E. , Przybysz A. , Nowak A. , Wójcik-Gront E. , Askarova G. , Lewandowski M. , Moniuszko H. 
Published: July 2024

AbstractThe foliage of the small-leaved lime (Tilia cordata) is characterised by the nerve axils being grown by non-glandular trichomes, which trait contributes to the enhanced retention of the particulate matter (PM). This fact may disturb the ecological service of T. cordata related to the structure of its leaves, which is to provide acarodomatia (micro-shelters) for the predatory mites of the Phytoseiidae family. Phytoseiids are natural enemies of a variety of plant pests, widely applied in integrated pest management (IPM). Their occurrence is largely related to acarodomatia in which these mites hide, feed, reproduce, and develop. For the first time, the influence of PM deposition within spaces typically occupied by phytoseiids is investigated. Experimental populations of Euseius finlandicus were reared on T. cordata leaves in the progressive PM-pollution. The results showed that the values of life table parameters of the predator depended significantly on the level of PM deposition on leaves. Contrary to clean leaves from the control, the medium and high contamination intensities significantly reduced the daily (by 47% and 70%, respectively) and the total fecundity (by 62% and 77%, respectively) of females which, in turn, resulted in a decreased net reproductive rate (by 67% and 81%, respectively), intrinsic rate of increase (by 40% and 55%, respectively) and finite rate of increase (by 8% and 10%, respectively) of E. finlandicus. The pre-ovipositional period was prolonged, while the oviposition duration was shortened and the mites matured longer. In high pollution level the mortality of phytoseiids was boosted by 19% and some females were observed with pollutant lumps adhered to the idiosoma. Also, significant shares of juvenile forms (13%) and adult females (25%) made attempts to escape from highly contaminated experimental arenas. The implications of PM retention on the shelter vegetation are discussed in the context of IPM and ecological services.
The SARIFA biomarker in the context of basic research of lipid-driven cancers
Authors: Märkl Bruno , Reitsam Nic G. , Grochowski Przemyslaw , Waidhauser Johanna , Grosser Bianca 
Published: July 2024

AbstractSARIFA was very recently introduced as a histomorphological biomarker with strong prognostic power for colorectal, gastric, prostate, and pancreatic cancer. It is characterized by the direct contact between tumor cells and adipocytes due to a lack of stromal reaction. This can be easily evaluated on routinely available H&E-slides with high interobserver agreement. SARIFA also reflects a specific tumor biology driven by metabolic reprogramming. Tumor cells in SARIFA-positive tumors benefit from direct interaction with adipocytes as an external source of lipids. Numerous studies have shown that lipid metabolism is crucial in carcinogenesis and cancer progression. We found that the interaction between tumor cells and adipocytes was not triggered by obesity, as previously assumed. Instead, we believe that this is due to an immunological mechanism. Knowledge about lipid metabolism in cancer from basic experiments can be transferred to develop strategies targeting this reprogramed metabolism.
Research on gravity compensation control of BPNN upper limb rehabilitation robot based on particle swarm optimization
Authors: Pang Zaixiang , Deng Xiaomeng , Gong Linan , Guo Danqiu , Wang Nan , Li Ye 
Published: July 2024

AbstractA four‐degree‐of‐freedom upper limb exoskeleton rehabilitation robot system with a gravity compensation device is constructed. The objective is to address the rehabilitation training needs of patients with upper limb motor dysfunction. A BP neural network adaptive control method based on particle swarm optimization is proposed. First, the degrees of freedom of the human body are analyzed, and a Lagrange method is employed to construct a dynamic model. Second, a particle swarm optimization back propagation neural network adaptive control algorithm based on particle swarm optimization is presented. Subsequently, the range of motion of the upper limbs is analyzed with reference to muscle anatomy and a three‐dimensional motion capture system. And the robot structure design is analyzed in detail. Finally, simulation experiments were conducted, and the results demonstrated that the proposed method exhibited high effectiveness and accuracy.
System error analysis and target localization of distributed pulse radars
Authors: Su Yihan , Wang Lei , Wang Zongyu , Liu Yimin , Wang Xiqin 
Published: July 2024

AbstractTarget localization for distributed radars requires precise knowledge of the calibration errors in time, frequency, and space. Previous studies focus on the sensor location error and sensor directional error in space. This paper concentrates on the system errors in time and frequency which directly affect the targets estimation of range and velocity. Based on linear frequency modulation waveform, the impact of the system errors including sample interval, pulse repetition interval, and centre frequency are analysed. An alternating optimization algorithm is proposed to achieve the target localization, velocity estimation and system errors estimation simultaneously. Simulation shows the effectiveness of the algorithm and the influence on localization due to varying number of targets and radars.
Quantum communications for image transmission over error‐prone channels
Authors: Jayasinghe Udara , Samarathunga Prabhath , Ganearachchi Yasith , Fernando Thanuj , Fernando Anil 
Published: July 2024

AbstractThe introduction of quantum communications, enabled by advancements in quantum computing, is expected to play a significant role in the field of communications. Inherent properties of quantum objects, such as superposition and entanglement, have the potential to provide novel solutions to overcome the challenges encountered by classical communication systems in bandwidth‐intensive applications such as media transmission. This research explores the performance of a quantum communication system in image transmission using quantum superposition and investigates its performance using a simple quantum channel model. With an increase in channel noise, there are significant gains in the rate distortion performance of images transmitted over the quantum channel compared to an ideal classical channel. This novel attempt at constructing a quantum communication‐based image transmission system indicates the potential of the approach to be applied to satisfy the ever‐increasing demands of high‐quality media transmission applications.
Delay aware resource allocation in ORAN through network optimization
Authors: Khalaf Basit N. , Ali Wisam Hasan , Alhumaima Raad S. , Alshamary Haider Ali Jasim 
Published: July 2024

AbstractA multi variable resource allocation problem is investigated in network environments, specifically focusing on the consideration of quality of service in open radio access network. The main objective is to minimise the combined latency of various servers while complying with network limitations. The delay of each server is represented by a non‐linear function that has exponentially based. This characteristic inherently brings non‐convexity into the objective function. In contrast, the constraints comprise various linear combinations of network variables, including resource block allocations, power consumption, and number of virtual machines. The purpose of these constraints is to guarantee that the allocation of resources adheres to practical limitations and upholds fairness among servers. Nevertheless, the inclusion of a non‐convex objective function significantly adds complexity to the optimisation problem and non‐convex behaviour, requiring specialised algorithms and techniques to identify solutions. Subsequently, the Lagrange multiplier method has been used to solve this problem mathematically. Numerically, three algorithms have been utilised and compared to solve the problem, these are active‐set, interior point and sequential quadratic programming. Note that the total delay as an objective function is based on the total power consumption of the servers. Previous to optimising the total delay, a delay model is proposed and compared with two research works that are based on experimental and real time data. The proposed model shows data matching with the other works and permits for more adaptation/integration with any other works that uses different servers’ characteristics and network parameters.