bluuebunny/crossref_metadata_2025_split huggingface dataset:
Implicit Cooperative Trajectory Planning with Learned Rewards Under Uncertainty
Authors: Kurzer Karl , Stegmaier Philipp , Polley Nikolai , Zöllner J. Marius 
Published: August 2024

AbstractUrban traffic scenarios often require high interaction between traffic participants to ensure safety and efficiency. While the capabilities of automated driving systems have made remarkable progress in the past decade, they lack two critical abilities: anticipation and provision of cooperation between traffic participants without communication, i.e., implicit cooperation. Observing the behavior of other traffic participants, humans infer the need to cooperate and act accordingly. Our work presents a system that utilizes a sampling-based cooperative trajectory planner that accounts for all possible actions of other traffic participants, enabling cooperation. Further, we extend the planner employing learned reward models based on expert trajectories to demonstrate its ability to adapt to a desired human driving style for smooth integration into today’s traffic. Lastly, we address the issue of measurement uncertainties to robustify the decision-making process in real-world environments utilizing return distributions over start states according to a belief. We exemplify the effectiveness of our solutions on 15 challenging multi-agent scenarios.
Learning Cooperative Trajectories at Intersections in Mixed Traffic
Authors: Yan Shengchao , Welschehold Tim , Büscher Daniel , Burger Christoph , Stiller Christoph , Burgard Wolfram 
Published: August 2024

AbstractIntersections are a significant bottleneck in traffic and have been a topic of much research. Optimization approaches incorporating traffic models are often limited by the intractable complexity resulting from the combinatorial explosion associated with increasing numbers of vehicles. Learning cooperative maneuver policies with deep neural networks from traffic data is a promising approach to address this issue. This chapter presents two approaches for managing traffic at intersections using deep reinforcement learning. The first approach learns an adaptive traffic signal controller, serving as a trajectory planner for all vehicles at the intersection. For smaller intersections with less traffic and fewer lanes, traffic signs are preferred over traffic lights due to their lower cost and higher efficiency. The second approach uses a centralized control unit to optimize efficiency and equity by ordering automated vehicles to yield to vehicles on conflicting routes with lower priorities. Self-driving cars have the potential to improve traffic flow in mixed environments with human-driven vehicles. The chapter evaluates the approaches using a traffic simulator with simulated and real-world traffic data. The approaches achieve state-of-the-art performance in terms of traffic efficiency and equity compared to non-learning and other learning-based methods. The chapter concludes with a discussion of possible future work on learning cooperative trajectories in mixed traffic.
Cooperative Hub for Cooperative Research on Cooperatively Interacting Vehicles: Use Cases, Design and Interaction Patterns
Authors: Flemisch Frank , Herzberger Nicolas , Usai Marcel , Baltzer Marcel , Schwalm Maximilian , Voß Gudrun , Krems Josef , Quante Laura , Trommler Daniel , Strelau Nadine , Burger Christoph , Stiller Christoph 
Published: August 2024

AbstractThis chapter describes central cooperative activities in the research priority program Cooperatively Interacting Vehicles (CoInCar). If the whole research program CoInCar can be seen as a wheel, which is turning research questions into answers, knowledge and hopefully progress for society, the individual research projects described in the other chapters could be seen as spokes of the wheel, and the aspects described in this chapter as an informal cooperative hub of the wheel. Starting with common essential definitions, a use case catalogue was derived and documented. Based on that, cooperation and interaction pattern were sketched and documented into a pattern database. While the details of the research hub described here are specific for this DFG priority program, the general principles of a research hub could be transferred to any other research and development activity.
Detecting Intentions of Vulnerable Road Users Based on Collective Intelligence as a Basis for Automated Driving
Authors: Zernetsch Stefan , Kress Viktor , Bieshaar Maarten , Schneegans Jan , Reitberger Günther , Fuchs Erich , Sick Bernhard , Doll Konrad 
Published: August 2024

AbstractThe project Detecting Intentions of Vulnerable Road Users Based on Collective Intelligence as a Basis for Automated Driving (DeCoInt$$^2$$

2

) focuses on detecting the intentions of vulnerable road users (VRUs) in automated driving using cooperative technologies. Especially in urban areas, VRUs, e.g., pedestrians and cyclists, will continue to play an essential role in mixed traffic. For an accident-free and highly efficient traffic flow with automated vehicles, it is vital to perceive VRUs and their intentions and analyze them similarly to humans when driving and forecasting VRU trajectories. Doing this reliably and robustly with a multimodal sensor system (e.g., cameras, LiDARs, accelerometers, and gyroscopes in mobile devices) in real-time is a big challenge. We follow a holistic, cooperative approach to recognize humans’ movements and forecast their trajectories. Heterogeneous open sets of agents, i.e., collaboratively interacting vehicles, infrastructure, and VRUs equipped with mobile devices, exchange information to determine individual models of their surrounding environment, allowing an accurate and reliable forecast of VRU basic movements and trajectories. The collective intelligence of cooperating agents resolves occlusions, implausibilities, and inconsistencies. We developed new methods by considering and combining novel signal processing and modeling techniques with machine learning-based pattern recognition approaches. The cooperation between agents happens on several levels: the VRU perception level, the level of recognized trajectories, or the level of already detected intentions.
The “Zero Tolerance Policy” to Separate Migrant Families: Context and Discursive Strategies to Foster Exclusion
Authors: Díaz de León Alejandra , Yrizar Barbosa Guillermo 
Published: August 2024

AbstractDuring April and May of 2018, the Trump administration promoted and implemented a family separation approach designed to discourage irregular migration flows along the southern border, also known as the “Zero Tolerance Policy” (ZTP). Prior to its termination on 20th June of that same year, at least 2700 children had been separated from their parents. According to different sources, the parents of over 600 children had been “lost” or were still missing by the end of 2020. In this chapter, we contextualize this “zero tolerance” approach to immigration in the wider setting of the U.S.-Mexico border and the deterrence practices deployed by the Trump administration. We analyze how the Trump administration justified and reacted to reporting of the family separation policy in the media and explore its stated aims. We show how the administration changed the discourse it used and its justification for the policy on an almost daily basis when reacting to protests, the news cycle, and statements from politicians. From a human rights perspective, by analyzing this family separation policy, we identify how elements of racism and the criminalization of immigration seriously undermine not only people’s dignity but also the protection of the right to family life.
“It Is Not the Netherlands Here.” How Parents of LGB Migrants Experience Everyday Bordering Against Nonheterosexual Belonging in CEE
Authors: Vuckovic Juros Tanja 
Published: August 2024

AbstractThis chapter explores everyday bordering against nonheterosexual belonging in the case of CEE parents of LGB migrants who emigrated to Belgium or the Netherlands—two countries reputed for their “LGB-friendliness”—from five countries characterized by a homonegative public opinion, exclusionary LGBT legal framework and recent anti-gender mobilizations. The analysis is based on in-depth interviews with eight CEE parents—the “stayers” who are embedded in the transnational social field with their migrant children, but still firmly situated in their CEE home countries. In this analysis, the chapter focuses on how the “others”—representing the wider imagined community of their CEE societies—were continually inserted in the narratives of parents discussing the nonheterosexuality of their migrant children. In these narratives, the parents highlight the experiences and expectations of the personal cost of societal homonegativity—both for their children and themselves. The analysis shows how these experiences and expectations are embedded in a wider heteronationalist discourse that places nonheterosexual belonging outside CEE collectivities and is reinforced and amplified by the anti-gender actors and their nationalistic, right-wing allies in CEE, who use it to support and sustain the construct of the European West–East divide.
TNF reduces osteogenic cell fate in PDL cells at transcriptional and functional levels without alteration of periodontal proliferative capacity
Authors: Knaup Isabel , Kramann Rafael , Sasula Martha-Julia , Mack Paula , Bastos Craveiro Rogério , Niederau Christian , Coenen Franziska , Neuss Sabine , Jankowski Joachim , Wolf Michael 
Published: August 2024

Abstract
Aims
To investigate the effect of tumor necrosis factor (TNF) on the growth of human periodontal ligament (PDL) cells, their osteogenic differentiation and modulation of their matrix secretion in vitro.

Methods
The influence of 10 ng/ml TNF on proliferation and metabolic activity of PDL cells was analyzed by cell counting (DAPI [4’,6-diamidino-2-phenylindole] staining) and the MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium) assay. In addition, cells were cultured under control conditions and osteogenic conditions (media containing 10 mM β-glycerophosphate). Quantitative expression analysis of genes encoding the osteogenic markers alkaline phosphatase (ALP), collagen type I alpha 1 chain (COL1A1), osteoprotegerin (OPG), and osteopontin (OPN) was performed after 7 and 14 days of cultivation. Calcium deposits were stained with alizarin red.

Results
Our studies showed that 10 ng/ml TNF did not affect the survival and metabolic activity of PDL cells. Quantitative expression analysis revealed that long-term cultures with TNF impaired osteogenic cell fate at early and late developmental stages. Furthermore, TNF significantly reduced matrix secretion in PDL cells.

Conclusion
The present data confirm TNF as a regulatory factor of proinflammatory remodeling that influences the differentiation behavior but not the metabolism and cell proliferation of the periodontium. Therefore, TNF represents an interesting target for the regulation of orthodontic remodeling processes in the periodontium.
Evaluation of score-based tertiary triage policies during the COVID-19 pandemic: simulation study with real-world intensive care data
Authors: Bartenschlager Christina C. , Brunner Jens O. , Kubiciel Michael , Heller Axel R. 
Published: August 2024

Abstract
Objective
The explicit prohibition of discontinuing intensive care unit (ICU) treatment that has already begun by the newly established German Triage Act in favor of new patients with better prognoses (tertiary triage) under crisis conditions may prevent saving as many patients as possible and therefore may violate the international well-accepted premise of undertaking the “best for the most” patients. During the COVID-19 pandemic, authorities set up lockdown measures and infection-prevention strategies to avoid an overburdened health-care system. In cases of situational overload of ICU resources, when transporting options are exhausted, the question of a tertiary triage of patients arises.

Methods
We provide data-driven analyses of score- and non-score-based tertiary triage policies using simulation and real-world electronic health record data in a COVID-19 setting. Ten different triage policies, for example, based on the Simplified Acute Physiology Score (SAPS II), are compared based on the resulting mortality in the ICU and inferential statistics.

Results
Our study shows that score-based tertiary triage policies outperform non-score-based tertiary triage policies including compliance with the German Triage Act. Based on our simulation model, a SAPS II score-based tertiary triage policy reduces mortality in the ICU by up to 18 percentage points. The longer the queue of critical care patients waiting for ICU treatment and the larger the maximum number of patients subject to tertiary triage, the greater the effect on the reduction of mortality in the ICU.

Conclusion
A SAPS II score-based tertiary triage policy was superior in our simulation model. Random allocation or “first come, first served” policies yield the lowest survival rates, as will adherence to the new German Triage Act. An interdisciplinary discussion including an ethical and legal perspective is important for the social interpretation of our data-driven results.
Nanosecond pulse electric field treatment initiates mitochondrial apoptosis pathway by inducing mitochondrial morphological changes in myocardial cells
Authors: Fan Aqing , Liu Gengliang , Wu Xiaodong 
Published: August 2024

Abstract
Background
As an emerging myocardial ablation technique, the mechanism of nanosecond pulse electric field (nsPEF) ablation is currently less studied. Mitochondria are one of the important membrane structure organelles in cells, participating in numerous life activities within the cell. This study aimed to explore the morphological changes of mitochondria in living cells following nsPEF treatment.

Methods
Myocardial cells were treated with a self-made solid-state LTD high-voltage nanosecond pulse generator with a pulse width of 100 ns for 80 times. The changes in mitochondrial membrane potential and cell apoptosis in rat myocardial cells after nsPEFs were investigated using JC-1 assay kit, apoptosis double staining assay kit, and mitochondrial fluorescence probe.

Results
The results showed that after nsPEF treatment, the mitochondrial membrane potential decreased, apoptosis increased, and the average mitochondrial area decreased from 0.48 µm2 in live myocardial cells to 0.16 µm2. The average circumference ranges from 3.17 µm dropped to 1.60 µm. The shape factor decreased from 1.92 to 1.41. The aspect ratio has decreased from 2.16 to 1.59. nsPEF treatment induces changes in the morphology of myocardial cell mitochondria.

Conclusions
Based on the results of mitochondrial membrane potential and apoptosis, it can be inferred that under this equipment and parameter conditions, nsPEF treatment first causes changes in mitochondrial morphology, and then initiates the mitochondrial apoptosis pathway, which may provide experimental basis for investigating the potential mechanism of nsPEF ablation of myocardial cells.

Graphical Abstract
Research on concept drift algorithm based on evolutionary computation
Authors: Kou Ai-Jun , Huang Xu , Sun Wen-Xue 
Published: August 2024

AbstractConcept drift (CD) in data streams can significantly impact the performance and stability of data stream classification algorithms, diminishing the generalization capabilities of integrated learning models. This paper addresses CD issues in dichotomous data streams by introducing a novel modeling approach that leverages evolutionary computation techniques. The method entails grouping base learners based on their performance within a sliding window and then evolving the base learning periods using evolutionary techniques. Furthermore, the concept of “gene flow” is introduced to enhance diversity among base learners and improve CD prediction performance. Experimental results on real and artificial datasets demonstrate the superior comprehensive performance of the proposed method. Specifically, the BCDECA algorithm outperforms other similar methods, excelling in accuracy, diversity, convergence rate, and robustness on a range of datasets.
Proper application of anticoagulation therapy on cancer-associated venous thrombosis
Authors: Yhim Ho-Young 
Published: August 2024

AbstractCancer-associated venous thromboembolism (VTE) significantly impacts morbidity and mortality. The introduction of direct oral anticoagulants over the past decade has revolutionized VTE treatment in patients with active cancer, offering potential advantages over traditional therapies. However, uncertainties persist regarding the optimal selection and dosage of anticoagulants, particularly in patients with specific risk factors for bleeding, such as certain cancer types (e.g., upper gastrointestinal cancer, genitourinary cancer, primary or metastatic brain tumor, and hematologic malignancies) and specific patient characteristics (e.g., renal dysfunction and thrombocytopenia). Recent data on the thrombotic risk associated with low thrombotic burden VTE, such as subsegmental pulmonary embolism and isolated distal deep vein thrombosis, underscore the need for updated management strategies in daily clinical practice. This review aims to explore these issues and highlight the evolving landscape of cancer-associated VTE management.
Mineralization of alkaline waste for CCUS
Authors: Walker Irene , Bell Robert , Rippy Kerry 
Published: August 2024

AbstractEx-situ mineralization processes leverage the reaction of alkaline materials with CO2 to form solid carbonate minerals for carbon capture, utilization, and storage. Annually, enough alkaline waste is generated to reduce global CO2 emissions by a significant percentage via mineralization. However, while the reaction is thermodynamically favorable and occurs spontaneously, it is kinetically limited. Thus, a number of techniques have emerged to increase the efficiency of mineralization to achieve a scalable process. In this review, we discuss mineralization of waste streams with significant potential to scale to high levels of CO2 sequestration. Focus is placed on the effect of operating parameters on carbonation kinetics and efficiency, methods, cost, and current scale of technologies.
Patients with ulcerative colitis who have normalized histology are clinically stable after de-escalation of therapy
Authors: Akiyama Shintaro , St-Pierre Joëlle , Traboulsi Cindy , Silfen Alexa , Rai Victoria , Rodriguez Tina G. , Erondu Amarachi I. , Steinberg Joshua M. , Shaffer Seth R. , Christensen Britt , Rubin David T. 
Published: August 2024

AbstractWe have previously demonstrated that histological normalization in ulcerative colitis (UC) is associated with superior maintenance of remission outcomes. This single-center, retrospective case-control study assessed outcomes after the therapeutic de-escalation in UC patients who have achieved histologic normalization. A total of 111 patients were included, of which 24 underwent de-escalation, and 87 patients without therapeutic changes. The most commonly withdrawn therapy was aminosalicylates (50%), followed by immunomodulators (37.5%), and biologics (12.5%). Fourteen patients remained on therapies after de-escalation, including aminosalicylate (9/14), immunomodulators (3/14), and biologics (3/14), while 10 patients were not on any therapy immediately after withdrawal. Median follow-up was 43 months in the de-escalation group and 47 months in the control. The rates of clinical, endoscopic, and histologic recurrence were not significantly different between the two groups, nor was the proportion of patients who subsequently required additional therapies after withdrawal (P = 0.133). Clinical and endo-histologic recurrence rates were the lowest in patients who withdrew immunomodulators (0% and 14.3%, respectively). We demonstrate the clinical stability of therapeutic withdrawal in UC patients with histologic normalization.
Scalable data management in global health crises: Leveraging blockchain technology
Authors: Al Jobaid Sakib , Kabir Upama , Jahan Mosarrat 
Published: August 2024

AbstractEffective data management is crucial in navigating any health crisis. With proper data management protocols in place, stakeholders can swiftly adapt to evolving circumstances during challenging times. A recent event like the COVID‐19 pandemic has unequivocally revealed its significance. It is essential to conduct disease surveillance, practice preventive measures, and devise policies to contain the situation. As the process involves massive data growth, it demands an acute level of oversight and control. Monitoring this vast sensitive data faces multifaceted limitations, namely data tampering, breach of privacy, and centralized data stewardship. In response to these challenges, we propose an innovative blockchain‐enabled scalable data management scheme in light of the COVID‐19 scenario. However, blockchain cannot scale in a large ecosystem due to storing all contents in every participating node. This work addresses this shortcoming by proposing a lightweight solution that groups nodes into clusters, resulting in less memory and processing overhead. Moreover, it adopts an off‐chaining technique to reduce the memory load of every node and, thereby, the entire network. The experimental results demonstrate that it attains approximately 85% and 94% storage reduction per node and the whole network, respectively, and an 87% reduction in transaction processing time.
Exact partition function of the Potts model on the Sierpinski gasket and the Hanoi lattice
Authors: Alvarez P D 
Published: August 2024

Abstract
We present an analytic study of the Potts model partition function on the Sierpinski and Hanoi lattices, which are self-similar lattices of triangular shape with non integer Hausdorff dimension. Both lattices are examples of non-trivial thermodynamics in less than two dimensions, where mean field theory does not apply. We used and explain a method based on ideas of graph theory and renormalization group theory to derive exact equations for appropriate variables that are similar to the restricted partition functions. We benchmark our method with Metropolis Monte Carlo simulations. The analysis of fixed points reveals information of location of the Fisher zeros and we provide a conjecture about the location of zeros in terms of the boundary of the basins of attraction.
72269 - Ten-year results after primary gastric bypass for severe obesity: results from the Scandinavian Obesity Registry (SOReg)
Authors: Sundbom Magnus , Näslund Erik , Ottosson Johan , Stenberg Erik ,   the SOReg Study Group
Published: August 2024

Abstract

Introduction
Metabolic and bariatric surgery (MBS) is part of routine care for patients with severe obesity (BMI &gt;35 kg/m2). In Sweden, the Scandinavian Obesity Registry (SOReg) collects data on all MBS with follow-up at 1, 2, 5 and 10 years. Long-term results (≥10 years) are scarce, especially in larger cohorts.

Method
Patients who underwent a primary Roux-en-Y gastric bypass (RYGB) in 2007-2012 were studied. SOReg was used for weight, laboratory data, and sleep apnoea, defined as CPAP-treatment (continuous positive airway pressure). Data on metabolic comorbidities, defined as active pharmacological treatment, was obtained from the Prescribed drugs registry. Preoperatively, 14.5% were treated for type 2 diabetes (T2D), 31.3% for hypertension, and 12.3% for dyslipidaemia.

Result
29,578 patients (BMI 42.7 kg/m2, age 41.0 years, and 75.6% women) were included. Ten years after surgery, we had access to SOReg-data in 9966 (33.7%) patients and current pharmacological treatment in 28,233 (95.4%) patients. Mean total body weight loss was 24.6%, corresponding to an excess body weight loss of 62.4%. The following rates of complete remission was seen: T2D 30.0%, hypertension 15.8%, and dyslipidaemia 8.9%. A similar result was seen in laboratory values. The use of CPAP for sleep apnoea was reduced from 9.8% to 4.1% at 10 years.

Discussion
Despite gradual weight regain, large weight loss and substantial remission in comorbid diseases was seen 10 years after primary gastric bypass. The successive weight regain should be noted and addressed.