bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fictitious-Positive Decision Dispute Resolution at PTUN For the Achieving Unity of Proceedings and Legal Certainty
Authors: Kupita Weda , Ardhanariswari Riris 
Published: April 2023

The Administrative Court (PTUN) has the authority to adjudicate ordinary state administrative disputes, namely disputes resulting from the issuance of written decisions by government officials, these disputes are classified as "ordinary state administrative disputes". The Administrative Court is also authorized to adjudicate "fictitious-positive decision disputes", namely disputes caused by legal events in the form of silence by government officials not issuing the requested decision, then the application is considered legally granted. Plaintiff (person or civil legal entity), before filing a lawsuit to the Administrative Court, it must first take an " Administrative Appeal ", it is determined if the authorized official does not respond (acts in silence) to Administrative Appeal, then "Administrative Appeal are deemed granted". Then there will be a juridical problem: "whether the dispute will be tried by PTUN as" Ordinary State Administrative Dispute "or as" Fictitious-Positive Decision Dispute? ". The approach method used is Normative Juridical, qualitative normative analysis method, and grammatical and systematic interpretation method. Based on normative studies, it is not yet clear whether the legal event will become an "Ordinary TUN Dispute" or a "Fictitious-Positive Decision Dispute", because it cannot be classified into the two types of disputes. Certainty is needed, because the procedural law are very different between the two types of disputes. The Article 77 and Article 78 of the UU-AP need to be amended by adding the provisions in the next paragraph which stipulates: "if the applicant for an administrative objection or appeal wishes to submit to the Administrative Court, then the TUN dispute is resolved in the Ordinary Procedure or is resolved as a fictitious decision dispute- positive". It is very important to emphasize in the provisions of the article in order to realize the unity of the proceedings and legal certainty
Mixture Culver Filter for Space Object Orbit Determination
Authors: Gilani Syed Amer Ahsan , Mihaylova Lyudmila S , Bhutta Maheen Fatima 
Published: April 2023

Exact sequential state estimation of orbiting objects in space can be found by predicting the state using Fokker Planck Kolmogorov Equation (FPKE) and measurement correction using Bayes’ conditional/posterior Probability Density Function (PDF). Posterior PDF can be expressed as Gaussian density expanded in terms of Hermite polynomials named as Gram Charlier Series (GCS). This research is an extension of an earlier work on second order linearized solution to nonlinear Bayesian filtering using Taylor series and third order GCS expansion of posterior PDF. In this new extension, Bayes’ posterior PDF is approximated by a mixture of GCS functions for which the parameters are propagated using linear propagation theory. The update of weights of different components of GCS mixture model uses the FPKE error as feedback to adapt for the amplitude of different GCS components while solving a quadratic programming problem earlier used for Gaussian Mixture Model (GMM) PDF. Proposed filtering method is applied on tracking of space debris. The simulation results for the filter shows performance is moderately better than single GCS filter, Extended Kalman Filter (EKF) and Gaussian Sum Filter (GSF) under space debris’ highly uncertain initial conditions and sparse measurement availability.
Special Issue on Navigation and Control Technologies for Autonomous Mobility
Authors: Minami Yuki , Okajima Hiroshi , Sawada Kenji , Sekiguchi Kazuma 
Published: April 2023

Autonomous mobility, as exemplified by self-driving cars, autonomous mobile robots, drones, etc., is essential to the acceleration and practical application of transportation services and the automation of delivery, guidance, security, and inspection. Therefore, in recent years, expectations have been building for autonomous mobility to grow as a technology that not only improves the convenience and comfort of transportation and the efficiency of logistics but also leads to solutions to various social problems. Various technological elements are required to ensure the safety and quality of autonomous mobility. For example, technology is needed to create environmental maps and automatically determine obstacles based on data acquired by cameras and sensors such as LiDAR. Technologies for planning appropriate routes and controlling robots safely and comfortably are also essential.
This special issue highlights 24 exciting papers, including 20 research papers, three letters, and one development report. They are related to “recognition,” “decision and planning,” and “control” technologies for autonomous mobile robots, such as self-driving cars and drones. The papers’ keywords are as follows:
• Collision avoidance, path planning, path tracking control
• Motion control, attitude control
• Measurement, position and posture estimation, modeling
• Point cloud processing
We would like to express our gratitude to all authors and reviewers, and we hope that this special issue contributes to future research and development in autonomous mobility.
​Weighted Rank Aggregation Based on Ranker Accuracies for Feature Selection
Authors: Abdolrazzagh-Nezahd Majid , Kherad Mahdi 
Published: April 2023

Abstract
Rank aggregation is the combination of several ranked lists from a set of candidates to achieve a better ranking by combining information from different sources. In feature selection problem, due to the heterogeneity of methods, there are some base rankers (Filter-based methods) that are of diverse quality and usually the ground truth of ratings is not available. Existing rank aggregation methods that take the diverse quality of base rankers into account do not have any explicit approach for appropriate weighting, require prior assumptions, and suffers from high computational complexity. In this paper, to overcome these challenges, an efficient unsupervised method is introduced for estimating the base rankers’ qualities and aggregating the rankers based on the estimated weights. We first compute the ratio of disagreement between base rankers in ordering different element pairs and then estimate the accuracies in a way that to minimize the discrepancy between these computed ratios and their analytical counterparts. We use the weighted majority voting method for obtaining the aggregated results. To resolve the probable inconsistencies in the final aggregation, the result is formed as a graph, and a greedy algorithm is used to find an acyclic subgraph with the highest weigh. To demonstrate the performance of the proposed method, nine standard UCI datasets are used. The experiments show the superiority of the proposed method compared to the existing baseline FS methods and rank aggregation-based multi-filter FS methods.
Faster functional performance recovery after individualized nutrition therapy combined with a patient-tailored physical rehabilitation program versus standard physiotherapy in patients with long COVID: a pilot study for a randomized, controlled single-center trial.
Authors: Roggeman Stijn , Garcia Berenice Jimenez , Leemans Lynn , Demol Joy , Geers Janne , De Smedt Ann , Putman Koen , Schiltz Marc , Beckwée David , De Waele Elisabeth 
Published: April 2023

Abstract
Background
Long COVID is suggested to be present in 14 to 43% of COVID 19-survivors. Literature on this new condition states a need for a multidisciplinary approach including physical exercise and nutrition. The aim of the current UNLOCK study is to investigate the feasibility of the proposed protocol to prepare for a randomized controlled study that addresses the effectiveness of a personalized multimodal treatment compared to standard physiotherapy.
Methods
This is a protocol of a pragmatic, single-center, randomized controlled pilot trial with two groups. Patients with persisting symptoms related to a proven SARS-CoV-2 infection will be recruited from the Universitair Ziekenhuis Brussel, Belgium. Patients will receive either standard physiotherapy or an individualized physical exercise program combined with nutritional counseling. They will be followed-up at 6, 12 and 18 weeks after randomization.
Discussion
a multidisciplinary approach for dealing with long COVID is needed. Because of the lack of clear data and the fact that this is a very heterogenic group, we aim to prepare and optimize a randomized controlled study that addresses the effectiveness of a personalized multimodal treatment.
Protocol version number and date
Version number: 2.0
Version date: 10 June 2022
Trial registration: ClinicalTrials.gov Identifier: NCT05254301 (since February 24, 2022)
High-Frequency Quantitative Trading of Digital Currencies Based on Deep Reinforcement Learning Models with Fusion Evolutionary Strategies
Authors: 贺 一峻 , Xu Bo , Su Xinpu 
Published: April 2023

Abstract
To address the emerging market of digital currencies where researchers have less applied deep reinforcement learning, this paper proposed deep evolutionary reinforcement learning (DERL) model, which is a deep reinforcement learning model based on an evolutionary strategy to extract trading information between users using Bitcoin K-line data as base data. Reinforcement learning is applied to data cleaning and factor extraction from a high-frequency, microscopic viewpoint to quantitatively explain the supply and demand imbalance and to create trading strategies. In order to determine whether the algorithm can successfully extract the significant hidden features in the factors when faced with large and complex high-frequency factors, this paper trains the agent in reinforcement learning using three different learning algorithms, including Q-learning, evolution strategy, and Policy Gradient. The experimental dataset, which contains data on sharp up, sharp down, and continuous oscillation situations, was chosen to test Bitcoin in January-February, September, and November 2022. According to the experimental results, the evolution strategy algorithm achieved returns of 59.18%, 25.14%, and 22.72%, respectively. The results also demonstrate that deep reinforcement learning based on the evolution strategy outperforms Q-learning and Policy Gradient concerning risk resistance and return capability.
Evolutionary relationship between DOF multigene transcription factors and the regulation of lipid biosynthesis in oilseeds
Authors: Zakavi Maryam , Farrokhi Naser 
Published: April 2023

Abstract

The Dofs (DNA binding with One Finger; a plant transcription factor family) encode single zinc finger proteins with essential roles in several biological processes. Although the lipid biosynthesis routes have been known for a while, the information about the corresponding regulatory elements including transcription factors have only recently started to emerge. Previous studies have shown that Dof transcription factors could regulate oil production. To test this subject matter, 162 unique exonic regions of Dof genes from oilseed plants including peanut, canola, soybean, cotton, sesame, corn, and oil palm were checked via phylogenic analyses that resulted in seven clads. A purifying selection was evident for the Dof family of genes in oil-producing plants. To compare the selection pattern of Dof in oilseed and non-oily plants, selection pressures acting on the Dof genes in cucumber (Cucumis sativus) and citrus (Citrus sinensis) were analyzed and showed to be different. Signatures of balancing selection were evident for the representatives of non-oily plants. Here and for the first time, the evolution of plant Dof members that are involved in oil production were put under scrutiny in order to elucidate their regulatory roles in oil biosynthesis.
Prevalence of The Risk Factors Associated with Pre-eclampsia and Eclampsia Disorders in a Tertiary Care Hospital of Lahore, a cross sectional study
Authors: Iqbal Sana , Ali Sibgha , Naeem Mah noor , Fida Tooba , abiddin Zain ul 
Published: April 2023

Abstract

Introduction: Pre-eclampsia (PE) is a multi-system hypertensive condition characterized by a blood pressure of greater than 140/90 mmHg recorded on two separate readings at least 4 hours apart and associated with proteinuria or end organ dysfunction. It is called Eclampsia when a patient with pre-eclampsia develops tonic-clonic seizures as well. It is thought to occur due to disordered trophoblastic invasion that causes uteroplacental hypoperfusion, leading to widespread endothelial dysfunction. Risk factors include PE in a previous pregnancy, Chronic kidney disease, diabetes mellitus, chronic hypertension or autoimmune diseases. Increased maternal age, high BMI and family history also play a role in its pathology. Pakistan has the third highest maternal mortality according to a recent global health analysis, 29% of this is contributed by hypertensive disorders. This study aims to study the predisposing risk factors in pre-eclampsia patients at a tertiary care hospital.
Methods: 82 selected cases of pre-eclampsia and eclampsia were included in this cross-sectional study. Informed consent was taken from all the patients and a pre-tested questionnaire was filled out by interviewing them during their antenatal visits.
Results: Most (61%) of the patients were in the third decade (20-29) of their life. The mean of the blood pressure checked at the time of interviewing was 153/95 mmHg. The majority (54.90%) of the patients were overweight (BMI=26-34.9). The most commonly identified risk factors include; raised diastolic BP at the booking visit (60%), history of pre-eclampsia in a previous pregnancy (41%), nulliparity (37%), obesity (37%) family history of pre-eclampsia (28%), GDM (21%) and chronic HTN (13%). Other less common risk factors include severe anemia (9%), a gap of more than 10 years (7%), multiple gestations (5%) and maternal age of more than 35 years (4%).
Conclusion: Pre-eclampsia is a significant threat to maternal as well as fetal life. And it has a higher incidence in the developing part of the world. Various risk factors are attributed to its pathophysiology. Prompt diagnosis and proper management and monitoring can reduce the morbidity and mortality associated with pre-eclampsia.
Machining error compensation based on a compliance error model reconstructed surface method
Authors: Chen Yueping , Yu Shifang , Tang Qingchun , Zeng Linan 
Published: April 2023

Abstract
To reduce the errors caused by the overall compliance of the system and the machine tool wear during the machining process for curved workpieces, and to improve the machining accuracies of curved workpieces, a machining error compensation method using a compliance error model to reconstruct the surface was adopted. During a process involving multiple cuts, on-machine measurement (OMM) was achieved by replacing the cutting tool with a touch probe. After the last semi-finishing cut, the error values were measured and compensated for using a compliance error model that predicted the change in the overall compliance of the system and estimated the error at the finishing cut depth based on the measured machining error at the previous cut depth. Finally, the machining errors before and after compensation of formula and free-form surface workpieces were verified experimentally. For the formula surface workpiece, the maximum value of the machining error was reduced from 0.057 mm to 0.0163 mm, and the average absolute value of the machining error was reduced from 0.047 mm to 0.0032 mm after compensation when using the method based on a compliance error model reconstructed surface. For the free-form surface workpiece, the maximum value of the machining error was reduced from 0.0586 mm to 0.0166 mm, and the average absolute value of the machining error was reduced from 0.0483 mm to 0.0057 mm after compensation using the compliance error model reconstructed surface method. It was verified that this method could effectively reduce machining errors and improve the machining accuracy of machine tools. This method can be used to predict and compensate for machining errors at different cut depths, which is of great research significance for machining various types of curved workpieces.
Single-cell analysis of white adipose tissue reveals the tumor-promoting adipocyte subtypes
Authors: Liu Si-Qing , Chen Ding-Yuan , Li Bei , Gao Zhi-Jie , Feng Hong-Fang , Yu Xin , Liu Zhou , Sun Si , Sun Sheng-Rong , Wu Qi 
Published: April 2023

Abstract
Background: The tumor-adipose microenvironment (TAME) is characterized by the enrichment of adipocytes, and is considered a special ecosystem that supports cancer progression. However, the heterogeneity and diversity of adipocytes in TAME remains poorly understood.
Methods: We conducted a single-cell RNA-seq analysis of adipocytes in mouse and human white adipose tissue (WAT). We analyzed several adipocyte subtypes to evaluate their relationship and potential as prognostic factors for overall survival (OS). The potential drugs are screened by using bioinformatics methods. The tumor-promoting effects of a typical adipocyte subtype in breast cancer are validated by performing in vitro functional assays and immunohistochemistry (IHC) in clinical samples.
Results: We profiled a comprehensive single-cell atlas of adipocyte in mouse and human WAT and described their characteristics, origins, development, functions and interactions with immune cells. Several cancer-associated adipocyte subtypes, namely DPP4+ adipose stem cells in visceral adipose and ADIPOQ+ adipocytes in subcutaneous adipose, are identified. We found that high levels of these subtypes are associated with unfavorable outcomes in four typical adipose-associated cancers. Some potential drugs including Trametinib, Selumetinib and Ulixertinib are discovered. Emphatically, knockdown of adiponectin receptor 1 (AdipoR1) and AdipoR2 impaired the proliferation and invasion of breast cancer cells. Patients with AdipoR2-high breast cancer display significantly shorter relapse-free survival (RFS) than those with AdipoR2-low breast cancer.
Conclusion: Our results provide a novel understanding of TAME at the single-cell level. Based on our findings, several adipocyte subtypes have negative impact on prognosis. These cancer-associated adipocytes may serve as key prognostic predictor and potential targets for treatment in the future.
Pre-operative psychological factors influence analgesic consumption and self-report of pain intensity following breast cancer surgery
Authors: Masaud Khaled , Galvin Audrey Dunn , Deloughry Gillian , Meachair Aisling O , Galea Sarah , Shorten George 
Published: April 2023

Abstract

Background: Psychological factors such as anxiety and mood appear to influence acute post-operative pain; however, the evidence on the relationship between pre-operative psychological parameters and the severity of post-operative pain is conflicting. Given the particularly stressful setting of initial surgery for breast cancer we conducted a prospective observational study of patients who were scheduled to undergo initial breast cancer surgery.Methods: The objectives were to examine the potential associations between pre-defined pre-operative psychological parameters with i. Self-reported pain scores at discharge from the post-operative acute care unit, ii. Cumulative perioperative opioid consumption at four hours post-operatively and iii. Measures of self-reported pain during the first seven days after surgery. Patients completed the following questionnaires during the three hours prior to surgery: Spielberger’s State Trait Anxiety Inventory (STAI State and Trait), Pain Catastrophizing Score (PCS), Cohen Stress Questionnaire (CSQ), Hospital Anxiety and Depression scale (HADS A and D), and the short form McGill Pain Questionnaire. Post-operative pain experience was assessed using patient self-report of pain (SF Magill Pain questionnaire on discharge from the post-anaesthesia care unit, and a pain diary for seven days postoperatively) and record of analgesic consumption.Results: A significant positive correlation was demonstrated between pre-operative state anxiety (STAI) and the most severe pain reported during the first seven days post-operatively. Patients who were categorized pre-operatively as “high value” for each of the psychological parameters studied (HADS A and D, STAI State and Trait and PCS), tended to have greater perioperative opioid consumption (up to four hours post-operatively ); this trend was statistically significant for HADS D and HADS A only. Using a linear regression model, state anxiety was found to be a significant predictor of post-operative pain based on self-report during the first seven post-operative days (standardized β = 0.271, t = 2.286, p = 0.025).Conclusion: Our findings that pre-operative state anxiety, in particular, is associated with the severity of the post-operative pain experience in women undergoing initial breast cancer surgery. Formal pre-operative assessment of anxiety may be warranted in this setting with a view to optimizing perioperative analgesia and wellbeing.
Correlation between the Fasciola hepatica infestation rate (number of parasites in the liver parenchyma) and the antibody titration, detected by ELISA assay
Authors: Samir Djemai , Ayadi Ouarda , Boubezari Mohammed Tahar , Djafar Zehaira Romeissa , Mekroud Abdeslam 
Published: April 2023

Abstract
This study aimed to demonstrate the existence of a possible correlation between the level of liver fluke infection in cattle caused by Fasciola hepatica and the titers of anti-parasite antibodies in the blood. 113 blood samples were taken from non-dewormed pasture cattle in the communal slaughterhouse of the Jijel city in order to determine the serological titration of anti-fluke antibodies by the ELISA method. After slaughtering the animals studied, a count of parasites present in the inspected livers was carried out in order to assess the level of parasitic infection. The prevalence of bovine fasciolosis (due to Fasciola hepatica) based on counting the number of flukes in the inspected livers was around 61.06%, while the seroprevalence obtained is 55.75%. The sensitivity and specificity of the ELISA test used in this study were, respectively, 91.3% and 100%. A very strong correlation (r = 0.93 to p < 0.0001) was statistically demonstrated between the antibody titers and the number of flukes in the inspected livers. According to the results of this study, there is a strong statistical correlation between serum antibody titers and the number of flukes present in the liver (the higher the number of parasites in the liver, the higher the level of anti-flukes antibodies in the blood).