bluuebunny/crossref_metadata_2025_split huggingface dataset:
Whole-field density measurements by digital image correlation
Authors: van Oers Alexander M. , Kat Roeland de , Maas Leo R. M. 
Published: October 2023

AbstractA novel application of Synthetic Schlieren in a laboratory set-up yields a quantitative measurement of the density field of two-dimensional, stratified or homogeneous, transparent fluids in a laboratory set-up using a single camera. This application obtains local values of the density without the need for tomographic reconstruction algorithms that require images taken from different directions through the fluid nor does the application require regularization. This is achieved by placing the camera at a large oblique angle with respect to the experimental set-up. This step is motivated by a fallacy observed when applying ray tracing in a classical configuration, in which the camera’s optical axis is perpendicular to the flat surface of a fluid container. The application is illustrated by the optical determination of static density fields of linearly and nonlinearly stratified fluids, as well as of multi-layered fluids. The application is validated by comparing with density profiles obtained from probe measurements of conductivity and temperature. Our application yields similar density and density gradient profiles as the probe while also providing a whole-field measurement without disturbing the fluid, and allowing the determination of dynamical density fields.
DMF-TONN: Direct Mesh-free Topology Optimization using Neural Networks
Authors: Joglekar Aditya , Chen Hongrui , Kara Levent Burak 
Published: October 2023

AbstractWe propose a direct mesh-free method for performing topology optimization by integrating a density field approximation neural network with a displacement field approximation neural network. We show that this direct integration approach can give comparable results to conventional topology optimization techniques, with an added advantage of enabling seamless integration with post-processing software, and a potential of topology optimization with objectives where meshing and Finite Element Analysis (FEA) may be expensive or not suitable. Our approach (DMF-TONN) takes in as inputs the boundary conditions and domain coordinates and finds the optimum density field for minimizing the loss function of compliance and volume fraction constraint violation. The mesh-free nature is enabled by a physics-informed displacement field approximation neural network to solve the linear elasticity partial differential equation and replace the FEA conventionally used for calculating the compliance. We show that using a suitable Fourier Features neural network architecture and hyperparameters, the density field approximation neural network can learn the weights to represent the optimal density field for the given domain and boundary conditions, by directly backpropagating the loss gradient through the displacement field approximation neural network, and unlike prior work there is no requirement of a sensitivity filter, optimality criterion method, or a separate training of density network in each topology optimization iteration.
Does statin suppress oxaliplatin-induced peripheral neuropathy in patients with colorectal cancer? A single-center observational study
Authors: Okamoto Kazuaki , Nozawa Hiroaki , Emoto Shigenobu , Murono Koji , Sasaki Kazuhito , Ishihara Soichiro 
Published: October 2023

Abstract
Background
Oxaliplatin-induced peripheral neuropathy (OIPN) is a common and dose-limiting toxicity that markedly limits the use of oxaliplatin and affects quality of life. Statins have been shown to exert neuroprotective effects in preclinical settings. The aim of the present study was to clarify whether statins prevented OIPN in patients with colorectal cancer (CRC) receiving adjuvant CAPOX therapy.

Methods
We examined 224 patients who received adjuvant CAPOX therapy for CRC between July 2010 and December 2021 at our hospital. Patients were divided into “Statin” and “Non-statin” groups based on statin use. Details on and the adverse events of adjuvant CAPOX therapy were examined in association with statin use.

Results
Thirty-one patients (14%) were treated with statins. There were no intergroup differences in the relative dose intensity or number of CAPOX cycles between the Statin and Non-statin groups. In total, 94% of patients in the Statin group and 95% of those in the Non-statin group developed OIPN (p=0.67). The severity of OIPN was similar between the two groups (p=0.89). The frequency of treatment delays in CAPOX did not significantly differ between the Statin and Non-statin groups (16% vs. 11%, p=0.45).

Conclusions
The efficacy of statins to attenuate OIPN during adjuvant CAPOX therapy was not apparent in the current study. Further studies are needed to confirm the present results.
Constipation and pain in Parkinson’s disease: a clinical analysis
Authors: Al-Wardat Mohammad , Grillo Piergiorgio , Schirinzi Tommaso , Pavese Chiara , Salimei Chiara , Pisani Antonio , Natoli Silvia 
Published: October 2023

AbstractParkinson’s Disease (PD) is a neurodegenerative disorder characterized by both motor and non-motor symptoms (NMS). Among NMS, constipation and pain are both highly prevalent and debilitating affecting up to 80% of PD patients and impairing their quality of life. Here, we investigated the relationship between constipation and pain in PD patients. This is a retrospective study assessing the relationship between pain and constipation in a PD patient population from a clinical database of patients attending the outpatient clinic of the movement disorders division, Neurology Unit of Policlinico Tor Vergata, in Rome. Subjects were assessed with the Unified Parkinson’s Disease Rating Scale (UPDRS) part III, Hoehn and Yahr (H&Y) stage, King’s Parkinson’s Disease Pain Scale (KPPS), Brief Pain Inventory (BPI), Non-Motor Symptoms Scale (NMSS) and Beck Depression Inventory (BDI). Patients were further divided in two groups (Group 1, 32 patients with constipation and Group 2, 35 PD patients without constipation) ANOVA and ANCOVA analysis were used to compare the two groups. PD patients with constipation had significantly higher pain severity and pain interference, as measured by the BPI scale and higher total KPPS score, fluctuation-related pain, nocturnal pain, and radicular pain when compared to PD patients without constipation. This study highlights for the first time a possible interplay between constipation and pain in PD that deserves further investigations.
A study on the implementation of nonlinear Kalman filter applying MMG model
Authors: Koike Hiroaki , Dostal Leo , Sawada Ryohei , Miyauchi Yoshiki , Maki Atsuo 
Published: October 2023

AbstractMany technologies need to be established to realize autonomous ships. In particular, accurate state estimation in real time is one of the most important technologies. In the ship and ocean engineering fields, there have been many studies on state estimation using nonlinear Kalman filters. Several methods have been proposed for nonlinear Kalman filters. However, there is insufficient verification on the selection of which filter should be applied among them. Therefore, this study aims to validate the filter selection to provide a guideline for filter selection. The effects of modeling error, observation noise, and type of maneuvers on the estimation accuracy of the unscented Kalman filter () and ensemble Kalman filter () used in this study were investigated. In addition, it was verified whether filtering could be performed in real time. The results show that modeling error significantly impacts the estimation accuracy of the and . However, the observation noise and types of maneuvers did not have an impact like the modeling error. Thus, we obtained the guideline that and should be used differently depending on the required computation time. We also obtained that keeping the modeling error sufficiently small is essential to improving the estimation accuracy.
Co-regulation of biofilm formation and antimicrobial resistance in Acinetobacter baumannii: from mechanisms to therapeutic strategies
Authors: Mendes Sérgio G. , Combo Sofia I. , Allain Thibault , Domingues Sara , Buret Andre G. , Da Silva Gabriela J. 
Published: October 2023

AbstractIn recent years, multidrug-resistant Acinetobacter baumannii has emerged globally as a major threat to the healthcare system. It is now listed by the World Health Organization as a priority one for the need of new therapeutic agents. A. baumannii has the capacity to develop robust biofilms on biotic and abiotic surfaces. Biofilm development allows these bacteria to resist various environmental stressors, including antibiotics and lack of nutrients or water, which in turn allows the persistence of A. baumannii in the hospital environment and further outbreaks. Investigation into therapeutic alternatives that will act on both biofilm formation and antimicrobial resistance (AMR) is sorely needed. The aim of the present review is to critically discuss the various mechanisms by which AMR and biofilm formation may be co-regulated in A. baumannii in an attempt to shed light on paths towards novel therapeutic opportunities. After discussing the clinical importance of A. baumannii, this critical review highlights biofilm-formation genes that may be associated with the co-regulation of AMR. Particularly worthy of consideration are genes regulating the quorum sensing system AbaI/AbaR, AbOmpA (OmpA protein), Bap (biofilm-associated protein), the two-component regulatory system BfmRS, the PER-1 β-lactamase, EpsA, and PTK. Finally, this review discusses ongoing experimental therapeutic strategies to fight A. baumannii infections, namely vaccine development, quorum sensing interference, nanoparticles, metal ions, natural products, antimicrobial peptides, and phage therapy. A better understanding of the mechanisms that co-regulate biofilm formation and AMR will help identify new therapeutic targets, as combined approaches may confer synergistic benefits for effective and safer treatments.
A rolling horizon planning approach for short-term demand supply matching
Authors: Herding Raphael , Mönch Lars 
Published: October 2023

AbstractDemand fulfillment and order management are important functions in semiconductor supply chains to interact with customers. In this paper, an iterative short-term demand supply matching (STDSM) algorithm based on mixed-integer linear programming (MILP) is proposed. This approach repromises orders taking into account the finite capacity of the shop floor. Decomposition is used to obtain computationally tractable subproblems. The STDSM approach is applied together with master planning and allocation planning in a rolling horizon setting. A simulation model of a simplified semiconductor supply chain is used for the rolling horizon experiments. The experiments demonstrate that the proposed STDSM scheme outperforms conventional business rule-based heuristics with respect to several delivery performance-related measures and with respect to stability.
Climate change and its impacts on glaciers and glacial lakes in Nepal Himalayas
Authors: Khadka Nitesh , Chen Xiaoqing , Sharma Shankar , Shrestha Bhaskar 
Published: October 2023

AbstractNepal, a Himalayan country, is often chosen by global scientists to study climate change and its impact on the Himalayan environment. The changes in temperature, precipitation, glaciers, and glacial lakes over Nepal are comprehensively reviewed based on published literature and compared with regional studies. Furthermore, the published glacier datasets were used to calculate and analyze the changes in area, equilibrium line of altitude (ELA) and ice reserves to show the response of glaciers to climate change. We find that the warming trend (0.02 to 0.16 °C yr−1) is being more pronounced over Nepal, and heterogeneous changes in precipitation amount, pattern, and frequency are observed with no significant trend. Concurrently, the glaciers are found to be responding with heterogeneous shrinkage in area (− 1 to − 5 km2 yr−1), possessing negative mass balance (− 0.3 to − 0.8 m w.e. yr−1), decrease in ice volume (− 4.29 km3 yr−1) and upward shift of the ELA (~ 20.66 m decade−1). The total decrease in ice reserve (− 128.84 km3) of Nepal has resulted in ~ 0.32 mm of sea level rise in past 30 years. Moreover, the formation and surface area expansion (0.83 % yr−1) of glacial lakes over Nepal have been accelerated. Additionally, we note that Nepal is highly susceptible to glacial lake outburst flood (GLOF) events and document a total of 45 reliable reported and unreported historical GLOF events from 39 glacial lakes across Nepal. This review will facilitate a comprehensive understanding of the current state of climate change and the identification of existing knowledge gaps in Nepal.
Older adults’ user experience with introvert and extravert humanoid robot personalities
Authors: Zedda Eleonora , Manca Marco , Paternò Fabio , Santoro Carmen 
Published: October 2023

AbstractHumanoid robots can be an effective tool for the cognitive training of older adults. For this purpose, it is important that their interaction be engaging. In this study, we investigate whether proposing robots exhibiting extraverted or introverted personalities can improve user experience. In particular, we have designed and implemented a set of multi-modal cues for such personality traits, which have been exploited in an application proposing typical exercises for cognitive training through a Pepper robot. We report on a user test with 24 older adults (65 +), which provided interesting and positive feedback regarding how the robot personalities have been exhibited and their impact on the experience of such users.
Large Eddy Simulation of a Low-Pressure Turbine Cascade with Turbulent End Wall Boundary Layers
Authors: Morsbach Christian , Bergmann Michael , Tosun Adem , Klose Bjoern F. , Kügeler Edmund , Franke Matthias 
Published: October 2023

AbstractWe present results of implicit large eddy simulation (LES) and different Reynolds-averaged Navier–Stokes (RANS) models of the MTU 161 low pressure turbine at an exit Reynolds number of $$90\,000$$

90

000

and exit Mach number of 0.6. The LES results are based on a high-order discontinuous Galerkin method and the RANS is computed using a classical finite-volume approach. The paper discusses the steps taken to create realistic inflow boundary conditions in terms of end wall boundary layer thickness and freestream turbulence intensity. This is achieved by tailoring the input distribution of total pressure and temperature, Reynolds stresses and turbulence length scale to a Fourier series based synthetic turbulence generator. With this procedure, excellent agreement with the experiment can be achieved in terms of blade loading at midspan and wake total pressure losses at midspan and over the channel height. Based on the validated setup, we focus on the discussion of secondary flow structures emerging due to the interaction of the incoming boundary layer and the turbine blade and compare the LES to two commonly used RANS models. Since we are able to create consistent setups for both LES and RANS, all discrepancies can be directly attributed to physical modelling problems. We show that both a linear eddy viscosity model and a differential Reynolds stress model coupled with a state-of-the-art correlation-based transition model fail, in this case, to predict the separation induced transition process around midspan. Moreover, their prediction of secondary flow losses leaves room for improvement as shown by a detailed discussion of turbulence kinetic energy and anisotropy fields.
First evidence of mouse predation killing adult great albatrosses
Authors: Connan Maëlle , Jones Christopher W. , Risi Michelle M. , Smyth Lucy K. , Oppel Steffen , Perold Vonica , Stevens Kim L. , Daling Roelf , Ryan Peter G. 
Published: October 2023

AbstractInvasive rodents threaten native species in numerous ecosystems, especially oceanic islands. The House Mouse Mus musculus is the only introduced mammal species on sub-Antarctic Gough and Marion Islands. Ample evidence exists of mice preying upon seabird chicks on these two islands, but there have been only a few reports of attacks on adult seabirds, none of which has been fatal. We report the first deaths of adult great albatrosses due to mouse attacks. On Gough Island, three Tristan Albatrosses Diomedea dabbenena (Critically Endangered) brooding small chicks were observed with wounds typical of mouse attacks in March–April 2021; two likely abandoned their chick, causing breeding failure, and the third was found dead eight days after discovery with large blowfly larvae in the wound. On Marion Island, two wounded and eight dead adult Wandering Albatrosses D. exulans (Vulnerable) were found in April 2023. Inspection of the wounded individuals, as well as the injuries on the fresh carcasses strongly suggest that mouse predation was the cause of death. Gough Island is home to virtually all Tristan Albatrosses, and Marion Island is the single most important breeding site for Wandering Albatrosses, home to about a quarter of all breeding birds. The death of breeding adults of these long-lived species emphasizes the urgent need to eradicate introduced mice from these islands.
Energy efficiency of the Visitor Pattern: contrasting Java and C++ implementations
Authors: Connolly Bree Déaglán , Ó Cinnéide Mel 
Published: October 2023

AbstractDesign patterns are applied frequently during software evolution in order to make the software more flexible and amenable to extension. One little-studied aspect of design patterns is their propensity to increase run-time energy consumption due to the indirection and additional structure they introduce. In this paper we study the impact of the Visitor pattern on energy efficiency. The Visitor pattern separates an algorithm from the objects it acts upon and improves maintainability by placing each algorithm within a single visitor class. This is at the cost of increased indirection due to the double dispatch required when the algorithm is invoked. We experimentally investigate the energy impact of varying the implementation of this pattern, and of removing the pattern entirely from software written in Java and C++. In our results we observe energy consumption reductions greater than 7% in a Java-based textbook example when the pattern is implemented using reflective dispatch, and reductions of over 10% when experimenting with an open source Java project, JavaParser. The complete removal of the pattern yields more complex results, with little impact in the textbook example but reductions of over 7% in the JavaParser study. To explore the generalisability of our findings, we subsequently apply the same transformations to the C++ based CppParser. Total pattern removal here sees energy consumption reductions of over 66% while the reflective dispatch approach increases energy consumption by up to 2012%. Our results highlight the energy savings that can be achieved when the Visitor pattern is removed both in Java and C++ implementations, and also show that some language specific features can allow for further energy savings when the implementation of the pattern is varied.
Multi-task learning for X-vector based speaker recognition
Authors: Zhang Yingjie , Liu Liu 
Published: October 2023

AbstractIn this paper, we propose a speaker recognition system that leverages multi-task learning and features integration (MTFI), to improve the performance of x-vector based speaker recognition models. It is important to integrate complementary information from different features such as MFCC, Fbank, spectrogram and LPCC, as often a single feature usually cannot cover all information about a speaker and generalization is insufficient. Since the x-vector model outputs affine transformation values with the penultimate hidden layer in the trained model, the parameter distribution of this layer should be stable and should not be affected by tasks that are not current branches when switching tasks. Therefore, we propose a shared unit (SU) in multi-task learning, which is useful for sharing common representations and other auxiliary tasks. Then, an attention mechanism is designed to calculate the frame weight in the statistical pooling layer, so as to enhance the key frame information. The proposed system had an EER of 0.98% in voxceleb1 and the average score fusion obtained the EER of 0.65%.
Screening for Attention Deficit Hyperactivity Disorder in Young Autistic Adults: The Diagnostic Accuracy of Three Commonly Used Questionnaires
Authors: Palmer Melanie , Fang Zhaonan , Hollocks Matthew J , Charman Tony , Pickles Andrew , Baird Gillian , Simonoff Emily 
Published: October 2023

Abstract
Objective
Attention Deficit Hyperactivity Disorder (ADHD) is a common co-occurring condition in autistic individuals. ADHD is sometimes first recognised in young adulthood because ADHD symptoms may be misattributed to autism due to superficial overlap in presentation and diagnostic overshadowing. It should be investigated whether ADHD questionnaires are accurate in screening symptoms in young adults with autism. The current study examined this.

Methods
Participants were autistic young adults (N = 119) who took part in the Special Needs and Autism Project (SNAP), a population-based cohort. ADHD research diagnoses were obtained through the parent-informed Young Adult Psychiatric Assessment. Parents and young adults (self-report sample N = 71) completed ADHD questionnaires (Aberrant Behavior Checklist hyperactivity/non-compliance subscale, Conners Adult ADHD Rating Scales ADHD Index, and Strengths and Difficulties Questionnaire ADHD subscale). Receiver operating characteristic analyses were conducted to explore if the questionnaires discriminated ADHD cases from non-cases. To assess whether results varied by intellectual functioning, subgroup analyses were completed for those with an IQ ≥ 70 vs. <70.

Results
Weighted ADHD rates were high. Overall although the measures were performing at or close to adequate levels (area under the curve was 0.66 to 0.79 for parent-report and 0.70 to 0.65 for self-report), no single measure met adequate thresholds for sensitivity and specificity simultaneously. Tool performance was not different for those with an IQ ≥ 70 vs. <70.

Conclusion
No single measure reported adequate performance for distinguishing ADHD from non-ADHD cases in this sample of young autistic adults. Use of current thresholds may lead to under-diagnosis.