bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Comparative Analysis of Sensory Properties, Flavour Profiles, and Fatty Acids in Three Popular Turkish Rice Varieties
Authors: Pirnia Aida , Dağıstan Hazal , Sarıkaya Ebru , Demir Sinem , Doğan Nuray , Tireki Suzan , Demirkoz Aslı Barla 
Published: June 2024

Abstract

Rice dish is a complex food item with different dimensions affected by variety, cooking technique, and presence of other ingredients together with their interactions. In this study, rice dishes were prepared with Baldo, Osmancik, and Cammeo rice varieties, and with butter, olive oil, margarine, and sunflower oil by Salma and Pilaf cooking techniques. Samples prepared with Osmancik-Salma method-olive oil (O-S-O), Baldo-Pilaf method-olive oil (B-P-O), and Cammeo-Salma method-olive oil (C-S-O) were the top three dishes in terms of overall acceptability scores. Squalene, limonene, isopropyl myristate, cyclotetradecane, acetic acid, acetol, and nonanal were detected volatiles in rice dishes. Methyl oleate, methyl palmitate, methyl linoleate, methyl stearate, methyl palmitoleate, methyl linolenate, and methyl eicosanate were the common fatty acid components in rice dishes and olive oil. Methyl benzoate and benzaldehyde were quantified in the samples with Salma technique but not in the sample cooked with Pilaf method. Complicated chemical reactions among rice components like Maillard reaction, caramelization reaction, lipid oxidation, thermal degradation, enzymatic/non-enzymatic hydrolysis are closely associated to the cooked rice aroma development. This study is the first study to investigate volatiles, and fatty acid derived compounds of rice dishes cooked with Baldo, Osmancik, and Cammeo varieties with Salma and Pilaf procedure accompanied with sensory evaluation.
Competing stochastic thresholds: The green transition as a race between “the good” and “the ugly”
Authors: Lorentzen Linnea , Strøm Steinar , Vislie Jon 
Published: June 2024

Abstract

We study a highly aggregated fossil-based world economy with two competing stochastic thresholds or tipping points. Current production generates emissions that add to a stock of GHGs that affect the probability distribution of hitting a climate threshold with severe consequences (the “ugly” scenario). The fossil-intensive output is used either for current consumption or as R&D-investment in knowledge production, with the stock of knowledge affecting the probability distribution for hitting a “good” threshold or having a technological breakthrough (the “good” scenario) providing a clean emission-free substitute to fossil energy. We characterize an optimal strategy for allocating resources over time, given that no threshold has been hit, with the strategy or decision rules being continuously revised due to the induced changes in the derived probability distribution. To avoid the ugly scenario, while pushing for the good one, we find that the conditional expected marginal benefit or willingness-to-pay for knowledge will be increasing over time, with a non-decreasing rate of R&D investment and a non-increasing rate of consumption. Implementation of this strategy requires a global organization with coercive power, equipped with instruments so as to tax the negative stock externality and to subsidize the provision of the public good or stock of knowledge. An important task for the global planner is continuously to update the hazard rates for hitting the two thresholds.
JEL Classification C02, H23, H41, Q54, Q55
Use of Artificial Intelligence tools in supporting decision-making in hospital management
Authors: Alves Maurício , Seringa Joana , Silvestre Tatiana , Magalhães Teresa 
Published: June 2024

Abstract

Background
The integration of Artificial Intelligence (AI) tools in hospital management holds potential for enhancing decision-making processes. This study investigates the current state of decision-making in hospital management, explores the potential benefits of AI integration, and examines hospital managers' perceptions of AI as a decision-support tool.
Methods
A descriptive and exploratory study was conducted using a qualitative approach. Data were collected through semi-structured interviews with 15 hospital managers from various departments and institutions. The interviews were transcribed, anonymized, and analyzed using thematic coding to identify key themes and patterns in the responses.
Results
Hospital managers highlighted the current inefficiencies in decision-making processes, often characterized by poor communication, isolated decision-making, and limited data access. The use of traditional tools like spreadsheet applications and business intelligence systems remains prevalent, but there is a clear need for more advanced, integrated solutions. Managers expressed both optimism and skepticism about AI, acknowledging its potential to improve efficiency and decision-making while raising concerns about data privacy, ethical issues, and the loss of human empathy. The study identified key challenges, including the variability in technical skills, data fragmentation, and resistance to change. Managers emphasized the importance of robust data infrastructure and adequate training to ensure successful AI integration.
Conclusions
The study reveals a complex landscape where the potential benefits of AI in hospital management are balanced with significant challenges and concerns. Effective integration of AI requires addressing technical, ethical, and cultural issues, with a focus on maintaining human elements in decision-making. AI is seen as a powerful tool to support, not replace, human judgment in hospital management, promising improvements in efficiency, data accessibility, and analytical capacity. Preparing healthcare institutions with the necessary infrastructure and providing specialized training for managers are crucial for maximizing the benefits of AI while mitigating associated risks.
Risky lane-changing behavior recognition based on Stacking ensemble learning on snowy and icy surfaces
Authors: DU Xuejing , Zhao Wei 
Published: June 2024

Abstract

Risky lane-changing (LC) behavior adversely affects traffic safety, especially on snowy and icy surfaces. However, due to the particularity of the snowy and icy surfaces and the scarcity of data, research on risky lane-changing behavior (RLCB) under extreme scenarios is insufficient. Therefore, this study presents a novel research framework aimed at selecting key risk characterisation indicators (RCIs) and identifying RLCB on highways using driving simulation data on snowy and icy surfaces. A highway LC scenario was established on snowy and icy surfaces using a driving simulator, and 1200 sets of LC sample data were extracted. From the perspectives of parameter importance and correlation, 12 key RCIs with high importance and low inter-correlation were selected using the C4.5 decision tree algorithm and Pearson correlation analysis method. The RLCB recognition model was developed using the Stacking ensemble learning method and then compared with traditional recognition algorithms. The results show that the accuracy of the recognition model based on the Stacking ensemble learning model is significantly better than that of traditional algorithms, with a recognition accuracy of 98.33%. This finding can provide the basis for developing LC warning systems for intelligent connected vehicles on snowy and icy surfaces.
Potential common molecular mechanisms between inflammatory bowel disease and erectile dysfunction in men: genetic screening and in vivo validation
Authors: Wang Ya-jie , Xiao Lin , Pan Yi-sheng 
Published: June 2024

Abstract

Purpose: To explore Potential common molecular mechanisms between inflammatory bowel disease and erectile dysfunction in men.
Method: First, differentially expressed genes in GSE10804 dataset and GSE191234 dataset were identified. qRT-PCR to verify the expression of differential genes. Enrichment analysis was performed in GO, KEGG and PPI.
Result: From public GEO datasets of IBD and ED, we mined 15 genes that work together on both diseases and validated them in mice with inflammatory bowel disease, finding the importance of several genes. Among them, the common KEGG pathway of the DEGs in the two datasets includes calcium signaling pathway and cell adhesion molecules, cytoskeleton in muscle cells, protein digestion and absorption, and tyrosine metabolism. In vivo, ABAC8, ADGRF5, CLGN, GRM1, NUAK1, PDE1A, SLC39A8 were verified by statistical difference.
Conclusion: Potential common genes interaction between inflammatory bowel disease and erectile dysfunction may be related to ABAC8, ADGRF5, CLGN, GRM1, NUAK1, PDE1A, SLC39A. calcium signaling pathway and cell adhesion molecules, cytoskeleton in muscle cells, protein digestion and absorption, and tyrosine metabolism may be the potential mechanism.
Automated Robotic-Assisted Patient Positioning for Boron Neutron Capture Therapy: Integration with NeuMANTA Treatment Planning System and Dosimetric Impact Analysis
Authors: Chen Jiang , Shu Di-Yun , Gong Qiu-Ping , Teng Yi-Chiao , Liu Yuan-Hao 
Published: June 2024

Abstract

Boron Neutron Capture Therapy (BNCT) represents a revolutionary approach in targeted radiation treatment for cancer. While the therapy's potential in precise targeting is well-recognized, a critical bottleneck remains in the accurate positioning of patients for treatment delivery. This study proposes a novel automated robotic-assisted patient positioning system specifically engineered for BNCT applications. The system utilizes high-precision industrial robotics and is fully integrated with NeuMANTA, a proprietary treatment planning system designed for BNCT. Through a systematic workflow, the robotic arm algorithmically calculates and executes the patient's positioning based on the treatment plan, thus enhancing the accuracy and efficacy of the treatment. We validate the positioning system using an anthropomorphic phantom and evaluate the dosimetric impact of positional deviations. The results indicate that the system achieves high accuracy, with a maximum observational deviation of 3 mm in Source-to-Skin Distance (SSD) and 2 mm along the surface. Dosimetric analysis reveals that the resulting dose changes are less than 1% in surface orientation deviations and greater than 5% in SSD orientation deviations. The study concludes that the robotic patient positioning system substantially advances in BNCT treatment delivery. This work not only sets a new benchmark for patient positioning in BNCT, but also provides a comprehensive framework for integrating advanced robotics into radiotherapy, paving the way for more precise and effective cancer treatments.
A low-cost low-viscosity refractive-index-matching pair -- PIV error measurement and sensitivity analysis
Authors: Akutina Yulia , Pengning Sun , Eiff Olivier 
Published: June 2024

Abstract

Refractive-index matching (RIM) techniques are often employed in order to perform optical flow measurements around solid bodies: the RI of a transparent solid object is matched with that of the working fluid. The solid becomes "invisible" and full optical access inside or behind the object is granted free of distortions. In this paper, a low-cost and low-viscosity RIM pair is proposed. It combines the polymer THV (tetrafluoroethylene, hexafluoropropylene and vinylidene fluoride), which is commercially available and manufactured in various shapes, with NaCl (table salt) added to water for the working fluid. The low cost of table salt combined with the viscosity of the solution close to water allows this RIM pair to be extended for large scale, high Reynolds number experiments, such as open-channel flows. Here, a set of validation experiments is presented which was designed to analyse the errors and matching sensitivity of PIV measurements in an actual flow rather than using a still target pattern -- the common testing method. The flow -- a dipole impacting a patch of vertical tubes -- is measured simultaneously by two PIV systems, where one camera takes images through a patch of THV tubes while the other camera has a free optical path to the same measurement laser plane. Comparing the results between the two cameras gives an estimate of the PIV measurement error.
To further analyse the PIV errors and their dependence on the tubes' geometry and their sensitivity to slight differences in the refractive indices between the solid and the fluid, a mathematical model of light refraction is employed. The higher thickness of the tube is found to increase the PIV error less than expected and sometimes even decrease it for a given resolution. It is found that the PIV error is inversely proportional to the PIV correlation box size relative to the tube size. This conclusion is also valid for other geometries, where edges or curved surfaces are present. That is, close-up measurements (higher resolution) around objects require higher precision of the RI matching.
The cryptic complex rearrangements involving the DMD gene causing completely opposite manifestations: etiologic clues revealed by optical genome mapping
Authors: Ma Yunting , Gui Chunrong , Shi Meizhen , Wei Lilin , He Junfang , Xie Bobo , Zheng Haiyang , Lei Xiaoyun , Wei Xianda , Cheng Zifeng , Zhou Xu , Chen Shaoke , Luo Jiefeng , Huang Yan , Gui Baoheng 
Published: June 2024

Abstract

Background: Deletion or duplication of DMD is one of the most common causes of Duchenne and Becker muscular dystrophy (DMD/BMD). However, the pathogenicity of complex rearrangements involving DMD, especially segmental duplications with unknown breakpoints, is not well understood. This study aimed to evaluate the structure, pattern, and potential impact of rearrangements involving DMD duplication.
Methods: Two families with DMD segmental duplications exhibiting opposite manifestations were recruited. Optical genome mapping (OGM) was used to explore the cryptic pattern of the rearrangements. Breakpoints were validated using long-range polymerase chain reaction combined with next-generation sequencing and Sanger sequencing.
Results: A multi-copy duplication involving exons 64–79 of DMD was identified in Family A without obvious clinical symptoms. Family B exhibited typical DMD neuromuscular manifestations and presented a duplication involving exons 10–13 of DMD. The rearrangement in Family A involved complex in-cis tandem repeats shown by OGM but retained a complete copy (reading frame) of DMDinferred from breakpoint validation. A reversed insertion with a segmental repeat was identified in Family B by OGM, which was predicted to disrupt the normal structure and reading frame of DMD after confirming the breakpoints.
Conclusions: Validating breakpoint and rearranged pattern is crucial for the functional annotation and pathogenic classification of genomic structural variations. OGM provides valuable insights into etiological analysis of DMD/BMD and enhances our understanding for cryptic effects of complex rearrangements.
Evaluation of Community Emergency Governance Resilience Based on Improved TOPSIS Method with Probabilistic Linguistic Term Sets
Authors: Li Hongying , Kaili Lu , Yanan Wang 
Published: June 2024

Abstract

Community emergency management serves as a crucial safeguard in preventing and mitigating significant security risks and safeguarding the lives of community members. To thoroughly and scientifically assess the capacity of community emergency management, a multi-attribute decision-making approach is proposed, which builds upon an enhanced TOPSIS method utilizing probabilistic linguistic term sets. Firstly, adopting the resilience theory perspective, a comprehensive evaluation system for community emergency management resilience is established, encompassing five dimensions: organization, physical elements, individuals, institutions, and technology. Secondly, to ensure a comprehensive reflection of expert preferences and evaluation information, as well as enhance the rationality of evaluation outcomes, an improved TOPSIS evaluation model based on probabilistic linguistic term sets is developed. Lastly, the feasibility and effectiveness of the model are validated through practical case studies, thereby providing valuable insights for the evaluation and enhancement of community emergency management capabilities.
Intelligent Vehicle Lateral Control Strategy Research based on Feedforward + Predictive LQR Algorithm with GA optimisation and PID compensation
Authors: Zheng Zhu-an , Ye Zimo , Zheng Xiangyu 
Published: June 2024

Abstract

Targeting the lateral motion control problem in the intelligent vehicle autopilot structural system, this paper proposes a feedforward + predictive LQR algorithm for lateral motion control based on Genetic Algorithm (GA) parameter optimisation and PID steering angle compensation. Firstly, based on the vehicle dynamics tracking error model, the intelligent vehicle LQR lateral motion controller as well as the feedforward controller are designed, and upon which the predictive controller is added to eliminate the system lag.Subsequently, exploiting the advantage that the PID algorithm is not model-based, a PID steering angle compensation controller that can directly control and correct the lateral error is designed. Second, a LQR controller based on path tracking deviation is designed by using the parameter rectification method of genetic algorithm (GA), which optimizes the control parameters of the lateral motion controller and improves the adaptivity of the control accuracy. Finally, the simulation verification and analysis are carried out through the Carsim-Simulink joint simulation platform. The simulation outcomes demonstrate that, under the premise that the vehicle is capable of tracking the path in real time, compared with the feedforward+LQR control and the LQR controller, The lateral controller proposed in this paper can enhance the accuracy of lateral distance error control and heading error control effectively.
Seismic Vulnerability Assessment of Reinforced Concrete Haunch Beam By Nonlinear Static and Incremental Dynamic Analyses
Authors: Haque Md. Foisal , Hoque Md. Mozammel 
Published: June 2024

Abstract

This research presents a novel technique of the seismic vulnerability assessment of the reinforced concrete haunch beams in terms of the probability of exceedance of the plastic hinge rotations. For this reason, the nonlinear static and incremental dynamic analyses of various structures with bays have been conducted by the ETABS. The plastic hinge rotation is controlled by the collapse prevention and life safety performance levels of beams and joints, respectively. The roof displacement controls the probability of exceedance of the plastic hinge rotations of beams and joints based on the nonlinear static analysis, which is a new insight of this research. The numerical analysis of ETABS is validated with the previously published work to obtain a good agreement of validation results. The 15-storied structure with 3 bays shows a higher vulnerability and the 4-storied structure shows a lower vulnerability according to the numerical analysis. The ranges of the normalized roof displacement and the peak ground acceleration for higher vulnerability are found to be (0.38 ~ 0.56) and (0.05 ~ 0.09) g, respectively, based on the nonlinear static and incremental dynamic analyses.
OntoReD: Requirements debt Ontology
Authors: Bonfim Viviane Duarte , Benitti Fabiane Barreto Vavassori 
Published: June 2024

Abstract

The practices proposed in agile methods to speed up software development, although they are beneficial to the organization, can affect the way in which requirements engineering activities are conducted as these practices are not explicit. These activities, when not carried out properly, can result in poorly understood, omitted and poorly specified requirements, leading to requirements debt and can compromise other stages of software development. However, requirements debts are little explored and, on many occasions, are unknown, not monitored or managed efficiently, which causes high maintenance costs over time. The objective of this article is to propose an Ontology focused on requirements debt in the agile context. The research was conducted through an investigation of the state of practice supported by \textit{grounded theory}, unifying the result with information obtained in two systematic studies of the literature: a systematic mapping of the literature that consists of identifying the causes, consequences and practices aimed at debts of requirements and a tertiary study focused on debt management, supporting the knowledge obtained about requirements debt and serving as input for the construction of an ontology, called “OntoReD”.
An application of SQUARE cryptanalysis to symmetric block cipher O'zDST 1105:2009 to retrieve secret parameters
Authors: Ikramov Alisher 
Published: June 2024

Abstract

We studied the symmetric block data encryption algorithm O'zDST 1105:2009 and demonstrated the process of retrieving of secret parameters $ R, d $ using integral analysis (SQUARE-analysis). These parameters are based on the secret key and are used to construct substitution tables of the algorithm. We attacked a truncated version of the algorithm exploiting its vulnerabilities.
We demonstrated the importance of a thorough examination of the mutual influence of operations in encryption algorithms.
Restoration of early postnatal synaptic dysregulation rescues polyglutamine-mediated motor neuron degeneration in mice
Authors: Katsuno Masahisa , Hirunagi Tomoki , Sahashi Kentaro , Iida Madoka , Ogura Yusuke , Tohnai Genki , Sakakibara Kenji , Maeda Kentaro , Bennett C. Frank 
Published: June 2024

Abstract

Spinal and bulbar muscular atrophy (SBMA) is an adult-onset neurodegenerative disorder caused by the expansion of a polyglutamine tract in the androgen receptor (AR). Here, we show that polyglutamine-expanded AR accumulates in the nucleus of motor neurons and induces aberrant up-regulation of glutamatergic synaptic genes, mediated by a master transcriptional repressor, Rest, during early postnatal development in a mouse model of SBMA. Further analysis indicates that the up-regulation of Rest-target synaptic genes is caused by an increased expression of Rest4, a neuron-specific isoform of Rest that derepresses the promoter activity of Rest-binding lesions. In addition, calcium imaging shows that induced pluripotent stem cell-derived motor neurons expressing polyglutamine-expanded AR are hyperexcitable compared to those expressing wild-type AR. Reducing neonatal AR or switching Rest4 to Rest using antisense oligonucleotides attenuates the up-regulation of the synaptic genes and ameliorates the disease phenotype and histopathology in SBMA mice. The late-onset neurodegeneration in SBMA is attributable to the synaptic defects and resulting hyperexcitability of motor neurons at early postnatal stages, which would be therapeutically targeted.