bluuebunny/crossref_metadata_2025 huggingface dataset:
Rethinking Formal Models of Partially Observable Multiagent Decision Making (Extended Abstract)
Authors: Kovařík Vojtěch , Schmid Martin , Burch Neil , Bowling Michael , Lisý Viliam
Published: August 2023

Multiagent decision-making in partially observable environments is usually modelled as either an extensive-form game (EFG) in game theory or a partially observable stochastic game (POSG) in multiagent reinforcement learning (MARL). One issue with the current situation is that while most practical problems can be modelled in both formalisms, the relationship of the two models is unclear, which hinders the transfer of ideas between the two communities. A second issue is that while EFGs have recently seen significant algorithmic progress, their classical formalization is unsuitable for efficient presentation of the underlying ideas, such as those around decomposition.

To solve the first issue, we introduce factored-observation stochastic games (FOSGs), a minor modification of the POSG formalism which distinguishes between private and public observation and thereby greatly simplifies decomposition. To remedy the second issue, we show that FOSGs and POSGs are naturally connected to EFGs: by "unrolling" a FOSG into its tree form, we obtain an EFG. Conversely, any perfect-recall timeable EFG corresponds to some underlying FOSG in this manner. Moreover, this relationship justifies several minor modifications to the classical EFG formalization that recently appeared as an implicit response to the model's issues with decomposition. Finally, we illustrate the transfer of ideas between EFGs and MARL by presenting three key EFG techniques -- counterfactual regret minimization, sequence form, and decomposition -- in the FOSG framework.
Learning to Design Fair and Private Voting Rules (Extended Abstract)
Authors: Mohsin Farhad , Liu Ao , Chen Pin-Yu , Rossi Francesca , Xia Lirong
Published: August 2023

Voting is used widely to aggregate preferences to make a collective decision. In this paper, we focus on evaluating and designing voting rules that support both the privacy of the voting agents and a notion of fairness over such agents. First, we introduce a novel notion of group fairness and adopt the existing notion of local differential privacy. We then evaluate the level of group fairness in several existing voting rules, as well as the trade-offs between fairness and privacy, showing that it is not possible to always obtain maximal economic efficiency with high fairness.

Then, we present both a machine learning and a constrained optimization approach to design new voting rules that are fair while maintaining a high level of economic efficiency. Finally, we empirically examine the effect of adding noise to create local differentially private voting rules and discuss the three-way trade-off between economic efficiency, fairness, and privacy.
Proofs and Certificates for Max-SAT (Extended Abstract)
Authors: Py Matthieu , Cherif Mohamed Sami , Habet Djamal
Published: August 2023

In this paper, we present a tool, called MS-Builder, which generates certificates for the Max-SAT problem in the particular form of a sequence of equivalence-preserving transformations. To generate a certificate, MS-Builder iteratively calls a SAT oracle to get a SAT resolution refutation which is handled and adapted into a sound refutation for Max-SAT. In particular, the size of the computed Max-SAT refutation is linear with respect to the size of the initial refutation if it is semi-read-once, tree-like regular, tree-like or semi-tree-like. Additionally, we propose an extendable tool, called MS-Checker, able to verify the validity of any Max-SAT certificate using Max-SAT inference rules.
A Survey of Methods for Automated Algorithm Configuration (Extended Abstract)
Authors: Schede Elias , Brandt Jasmin , Tornede Alexander , Wever Marcel , Bengs Viktor , Hüllermeier Eyke , Tierney Kevin
Published: August 2023

Algorithm configuration (AC) is concerned with the automated search of the most suitable parameter configuration of a parametrized algorithm. There are currently a wide variety of AC problem variants and methods proposed in the literature. Existing reviews do not take into account all derivatives of the AC problem, nor do they offer a complete classification scheme. To this end, we introduce taxonomies to describe the AC problem and features of configuration methods, respectively. Existing AC literature is classified and characterized by the provided taxonomies.
Motion Planning Under Uncertainty with Complex Agents and Environments via Hybrid Search (Extended Abstract)
Authors: Strawser Daniel , Williams Brian
Published: August 2023

As autonomous systems tackle more real-world situations, mission success oftentimes cannot be guaranteed and the planner must reason about the probability of failure. Unfortunately, computing a trajectory that satisfies mission goals while constraining the probability of failure is difficult because of the need to reason about complex, multidimensional probability distributions. Recent methods have seen success using chance-constrained, model-based planning. We argue there are two main drawbacks to these approaches. First, current methods suffer from an inability to deal with expressive environment models such as 3D non-convex obstacles. Second, most planners rely on considerable simplifications when computing trajectory risk including approximating the agent's dynamics, geometry, and uncertainty. We apply hybrid search to the risk-bound, goal-directed planning problem. The hybrid search consists of a region planner and a trajectory planner. The region planner makes discrete choices by reasoning about geometric regions that the agent should visit in order to accomplish its mission. In formulating the region planner, we propose landmark regions that help produce obstacle-free paths. The region planner passes paths through the environment to a trajectory planner; the task of the trajectory planner is to optimize trajectories that respect the agent's dynamics and the user's desired risk of mission failure. We discuss three approaches to modeling trajectory risk: a CDF-based approach, a sampling-based collocation method, and an algorithm named Shooting Method Monte Carlo. A variety of 2D and 3D test cases are presented in the full paper including a linear case, a Dubins car model, and an underwater autonomous vehicle. The method is shown to outperform other methods in terms of speed and utility of the solution. Additionally, the models of trajectory risk are shown to better approximate risk in simulation.
Pushing the Limits of Fairness in Algorithmic Decision-Making
Authors: Shah Nisarg
Published: August 2023

Designing provably fair decision-making algorithms is a task of growing interest and importance. In this article, I argue that preference-based notions of fairness proposed decades ago in the economics literature and subsequently explored in-depth within computer science (specifically, within the field of computational social choice) are aptly suited for a wide range of modern decision-making systems, from conference peer review to recommender systems to participatory budgeting.
Fairness and Stability in Complex Domains
Authors: Chingoma Julian
Published: August 2023

Fairness and stability are normative concepts that have been investigated for many social choice domains. Recently, increasing attention has fallen on richer, and more complex, settings and we look to develop, and study in depth, these fairness and stability notions in a variety of such complex domains.
Human-Centred Multimodal Deep Learning Models for Chest X-Ray Diagnosis
Authors: Hsieh Chihcheng
Published: August 2023

My thesis consists of investigating how chest X-ray images, radiologists' eye movements and patients' clinical data can be used to teach a machine how radiologists read and classify images with the goal of creating human-centric AI architectures that can (1) capture radiologists' search behavioural patterns using their eye-movements in order to improve classification in DL systems, and (2) automatically detect lesions in medical images using clinical data and eye tracking data. Heterogeneous data sources such as chest X-rays, radiologists' eye movements, and patients' clinical data can contribute to novel multimodal DL architectures that, instead of learning directly from images' pixels, will learn human classification patterns encoded in both the eye movements of the images' regions and patients' medical history. In addition to a quantitative evaluation, I plan to conduct questionnaires with expert radiologists to understand the effectiveness of the proposed multimodal DL architecture.
Fedstellar: A Platform for Training Models in a Privacy-preserving and Decentralized Fashion
Authors: Martínez Beltrán Enrique Tomás , Sánchez Sánchez Pedro Miguel , López Bernal Sergio , Bovet Gérôme , Gil Pérez Manuel , Martínez Pérez Gregorio , Huertas Celdrán Alberto
Published: August 2023

This paper presents Fedstellar, a platform for training decentralized Federated Learning (FL) models in heterogeneous topologies in terms of the number of federation participants and their connections. Fedstellar allows users to build custom topologies, enabling them to control the aggregation of model parameters in a decentralized manner. The platform offers a Web application for creating, managing, and connecting nodes to ensure data privacy and provides tools to measure, monitor, and analyze the performance of the nodes. The paper describes the functionalities of Fedstellar and its potential applications. To demonstrate the applicability of the platform, different use cases are presented in which decentralized, semi-decentralized, and centralized architectures are compared in terms of model performance, convergence time, and network overhead when collaboratively classifying hand-written digits using the MNIST dataset.
Plansformer Tool: Demonstrating Generation of Symbolic Plans Using Transformers
Authors: Pallagani Vishal , Muppasani Bharath , Srivastava Biplav , Rossi Francesca , Horesh Lior , Murugesan Keerthiram , Loreggia Andrea , Fabiano Francesco , Joseph Rony , Kethepalli Yathin
Published: August 2023

Plansformer is a novel tool that utilizes a fine-tuned language model based on transformer architecture to generate symbolic plans. Transformers are a type of neural network architecture that have been shown to be highly effective in a range of natural language processing tasks. Unlike traditional planning systems that use heuristic-based search strategies, Plansformer is fine-tuned on specific classical planning domains to generate high-quality plans that are both fluent and feasible. Plansformer takes the domain and problem files as input (in PDDL) and outputs a sequence of actions that can be executed to solve the problem. We demonstrate the effectiveness of Plansformer on a variety of benchmark problems and provide both qualitative and quantitative results obtained during our evaluation, including its limitations. Plansformer has the potential to significantly improve the efficiency and effectiveness of planning in various domains, from logistics and scheduling to natural language processing and human-computer interaction. In addition, we provide public access to Plansformer via a website as well as an API endpoint; this enables other researchers to utilize our tool for planning and execution. The demo video is available at https://youtu.be/_1rlctCGsrk
BPNet: Bézier Primitive Segmentation on 3D Point Clouds
Authors: Fu Rao , Wen Cheng , Li Qian , Xiao Xiao , Alliez Pierre
Published: August 2023

This paper proposes BPNet, a novel end-to-end deep learning framework to learn Bézier primitive segmentation on 3D point clouds. The existing works treat different primitive types separately, thus limiting them to finite shape categories. To address this issue, we seek a generalized primitive segmentation on point clouds. Taking inspiration from Bézier decomposition on NURBS models, we transfer it to guide point cloud segmentation casting off primitive types. A joint optimization framework is proposed to learn Bézier primitive segmentation and geometric fitting simultaneously on a cascaded architecture. Specifically, we introduce a soft voting regularizer to improve primitive segmentation and propose an auto-weight embedding module to cluster point features, making the network more robust and generic. We also introduce a reconstruction module where we successfully process multiple CAD models with different primitives simultaneously. We conducted extensive experiments on the synthetic ABC dataset and real-scan datasets to validate and compare our approach with different baseline methods. Experiments show superior performance over previous work in terms of segmentation, with a substantially faster inference speed.
Humming2Music: Being A Composer As Long As You Can Humming
Authors: Qiu Yao , Zhang Jinchao , Ren Huiying , Shan Yong , Zhou Jie
Published: August 2023

Creating a piece of music is difficult for people who have never been trained to compose. We present an automatic music generation system to lower the threshold of creating music. The system takes the user's humming as input and creates full music based on the humming melody. The system consists of five modules: 1) humming transcription, 2) melody generation, 3) broken chord generation, 4) accompaniment generation, and 5) audio synthesis. The first module transcribes the user's humming audio to a score, and then the melody generation module composes a complete melody based on the user's humming melody. After that, the third module will generate a broken chord track to accompany the full melody, and the fourth module will create more accompanying tracks. Finally, the audio synthesis module mixes all the tracks to generate the music. Through the user experiment, our system can generate high-quality music with natural expression based on the user's humming input.
LingGe: An Automatic Ancient Chinese Poem-to-Song Generation System
Authors: Shan Yong , Zhang Jinchao , Ren Huiying , Qiu Yao , Zhou Jie
Published: August 2023

This paper presents a novel system, named LingGe ("伶歌" in Chinese), to generate songs for ancient Chinese poems automatically. LingGe takes the poem as the lyric, composes music conditioned on the lyric, and finally outputs a full song including the singing and the accompaniment. It consists of four modules: rhythm recognition, melody generation, accompaniment generation, and audio synthesis. Firstly, the rhythm recognition module analyzes the song structure and rhythm according to the poem. Secondly, the melody generation module assembles the rhythm into the template and then generates the melody. Thirdly, the accompaniment generation module predicts the accompaniment in harmony with the melody. Finally, the audio synthesis module generates singing and accompaniment audio and then mixes them to obtain songs. The results show that LingGe can generate high-quality and expressive songs for ancient Chinese poems, both in harmony and rhythm.
Matting Moments: A Unified Data-Driven Matting Engine for Mobile AIGC in Photo Gallery
Authors: Zhang Yanhao , Wang Fanyi , Sun Weixuan , Su Jingwen , Liu Peng , Li Yaqian , Feng Xinjie , Zou Zhengxia
Published: August 2023

Image matting is a fundamental technique in visual understanding and has become one of the most significant capabilities in mobile phones. Despite the development of mobile storage and computing power, achieving diverse mobile Artificial Intelligence Generated Content (AIGC) applications remains a great challenge. To address this issue, we present an innovative demonstration of an automatic system called "Matting Moments" that enables automatic image editing based on matting models in different scenarios. Coupled with accurate and refined matting subjects, our system provides visual element editing abilities and backend services for distribution and recommendation that respond to emotional expressions. Our system comprises three components: 1) photo content structuring, 2) data-driven matting engine, and 3) AIGC functions for generation, which automatically achieve diverse photo beautification in the gallery. This system offers a unified framework that guides consumers to obtain intelligent recommendations with beautifully generated contents, helping them enjoy the moments and memories of their present life.
Joint-MAE: 2D-3D Joint Masked Autoencoders for 3D Point Cloud Pre-training
Authors: Guo Ziyu , Zhang Renrui , Qiu Longtian , Li Xianzhi , Heng Pheng-Ann
Published: August 2023

Masked Autoencoders (MAE) have shown promising performance in self-supervised learning for both 2D and 3D computer vision. However, existing MAE-style methods can only learn from the data of a single modality, i.e., either images or point clouds, which neglect the implicit semantic and geometric correlation between 2D and 3D. In this paper, we explore how the 2D modality can benefit 3D masked autoencoding, and propose Joint-MAE, a 2D-3D joint MAE framework for self-supervised 3D point cloud pre-training. Joint-MAE randomly masks an input 3D point cloud and its projected 2D images, and then reconstructs the masked information of the two modalities. For better cross-modal interaction, we construct our JointMAE by two hierarchical 2D-3D embedding modules, a joint encoder, and a joint decoder with modal-shared and model-specific decoders. On top of this, we further introduce two cross-modal strategies to boost the 3D representation learning, which are local-aligned attention mechanisms for 2D-3D semantic cues, and a cross-reconstruction loss for 2D-3D geometric constraints. By our pre-training paradigm, Joint-MAE achieves superior performance on multiple downstream tasks, e.g., 92.4% accuracy for linear SVM on ModelNet40 and 86.07% accuracy on the hardest split of ScanObjectNN.
DAMO-StreamNet: Optimizing Streaming Perception in Autonomous Driving
Authors: He Jun-Yan , Cheng Zhi-Qi , Li Chenyang , Xiang Wangmeng , Chen Binghui , Luo Bin , Geng Yifeng , Xie Xuansong
Published: August 2023

In the realm of autonomous driving, real-time perception or streaming perception remains under-explored. This research introduces DAMO-StreamNet, a novel framework that merges the cutting-edge elements of the YOLO series with a detailed examination of spatial and temporal perception techniques. DAMO-StreamNet's main inventions include: (1) a robust neck structure employing deformable convolution, bolstering receptive field and feature alignment capabilities; (2) a dual-branch structure synthesizing short-path semantic features and long-path temporal features, enhancing the accuracy of motion state prediction; (3) logits-level distillation facilitating efficient optimization, which aligns the logits of teacher and student networks in semantic space; and (4) a real-time prediction mechanism that updates the features of support frames with the current frame, providing smooth streaming perception during inference. Our testing shows that DAMO-StreamNet surpasses current state-of-the-art methodologies, achieving 37.8% (normal size (600, 960)) and 43.3% (large size (1200, 1920)) sAP without requiring additional data. This study not only establishes a new standard for real-time perception but also offers valuable insights for future research. The source code is at https://github.com/zhiqic/DAMO-StreamNet.
Enriching Phrases with Coupled Pixel and Object Contexts for Panoptic Narrative Grounding
Authors: Hui Tianrui , Ding Zihan , Huang Junshi , Wei Xiaoming , Wei Xiaolin , Dai Jiao , Han Jizhong , Liu Si
Published: August 2023

Panoptic narrative grounding (PNG) aims to segment things and stuff objects in an image described by noun phrases of a narrative caption. As a multimodal task, an essential aspect of PNG is the visual-linguistic interaction between image and caption. The previous two-stage method aggregates visual contexts from offline-generated mask proposals to phrase features, which tend to be noisy and fragmentary. The recent one-stage method aggregates only pixel contexts from image features to phrase features, which may incur semantic misalignment due to lacking object priors. To realize more comprehensive visual-linguistic interaction, we propose to enrich phrases with coupled pixel and object contexts by designing a Phrase-Pixel-Object Transformer Decoder (PPO-TD), where both fine-grained part details and coarse-grained entity clues are aggregated to phrase features. In addition, we also propose a Phrase-Object Contrastive Loss (POCL) to pull closer the matched phrase-object pairs and push away unmatched ones for aggregating more precise object contexts from more phrase-relevant object tokens. Extensive experiments on the PNG benchmark show our method achieves new state-of-the-art performance with large margins.
PENGARUH SISTEM INFORMASI MANAJEMEN TERHADAP EFEKTIFITAS KERJA (Suatu Studi Pada Pegawai Kecamatan Rajadesa)
Authors: Puspitasari Endah , Nursolih Enjang , Rustendi Enang
Published: August 2023

Penelitian ini difokuskan pada pengaruh sistem informasi manajemen terhadap efektifitas kerja (Suatu Studi Pada Pegawai Pegawai Kecamatan Rajadesa).

Permasalahan yang dihadapi dalam penelitian ini meliputi : 1] Bagaimana Sistem Informasi Manajemen pada Kantor Kecamatan Rajadesa?; 2] Bagaimana Efektivitas Pengelolaan Sumber Daya Manusia pada Kantor Kecamatan Rajadesa?; 3] Bagaimana pengaruh Sistem Informasi Manajemen Terhadap Efektivitas Kerja pada Kantor Kecamatan Rajadesa?. Adapun tujuan penelitian ini adalah untuk mengetahui 1] Bagaimana Sistem Informasi Manajemen pada Kantor Kecamatan Rajadesa; 2] Bagaimana Efektivitas Pengelolaan Sumber Daya Manusia pada Kantor Kecamatan Rajadesa 3] Pengaruh Sistem Informasi Manajemen Terhadap Efektivitas Kerja pada Kantor Kecamatan Rajadesa. Metode yang digunakan dalam penelitian adalah metode survey dengan pendekatan kuantitatif yaitu hasil penelitian yang kemudian diolah dan dianalisis untuk diambil kesimpulannya. Sedangkan untuk menganalisis data yang diperoleh digunakanan analisis koefisien korelasi spearment rank, determinasi, uji Hipotesis menggunakan Uji signifikansi (Uji t) dan regresi linier sederhana. Hasil penelitian membuktikan bahwa Sistem Informasi Manajemen berpengaruh terhadap efektifitas kerja pada pegawai Kecamatan Rajadesa. Artinya semakin baik sistem informasi manajemen maka efektifitas kerja akan meningkat. Sebaiknya atasan menerpakan sistem apresiasi dan penghargaan yang diberikan secara teratur sehingga akan memberikan insentif kepada karyawan untuk melakukan yang terbaik dan pencapaian tujuan akan berjalan dengan baik.
Selection of Dry Port Locations Using PROMETHEE Approach: Case for Türkiye
Authors: KAYMAZ Yunus , ÇİÇEKLİ Ural Gökay
Published: August 2023

The aim of this study is to determine the most suitable location for a possible dry port in the Aegean Region of Türkiye based on various criteria. The concept of dry port, which is highly discussed especially in foreign literature, and accordingly, dry port location selection is examined as a multi-criteria decision making (MCDM) problem that requires various evaluation criteria. In this context, the PROMETHEE method, which is one of the MCDM methods, is used for dry port selection. As a result of the analyses, it can be said that in an environment where port congestion is increasing, dry ports can decrease this congestion, in this context, Türkiye is in an advantageous position and considering the global crisis events such as the pandemic called Covid-19, such applications will contribute to the overall efforts to strengthen Türkiye's logistics infrastructure. In the study, 10 locations were evaluated based on a total of 13 criteria. Among these locations, the location with the highest score can be considered as the most suitable dry port area.
Effects of Parental Support Group on Perceived Stress and Self-Esteem among Parents of Children with Special Needs
Authors: Pallavi Abdi  , Subodh Kumar
Published: August 2023

Parents are the fundamental and most important connection in the care, education, and supervision of children with special needs. When parenting a special child, they face many challenges, including tremendous physical and psychological concerns associated with child care and unprecedented stress. The present study aims to assess the effects of parental support groups on the self-esteem and perceived stress of parents of children with special needs. A cross-sectional study was conducted, and data from 100 parents of children with special needs was collected through convenience sampling using Perceived Stress Scale (PSS; Cohen, et al., 1983) and Rosenberg Self-Esteem Scale (SES; Rosenberg, 1989). The results showed that parents who were a part of parental support groups had better self-esteem but higher perceived stress. t-test showed a significant difference in self-esteem in relation to membership of parental support groups (t=2.127, p=0.03). However, there was no significant difference in perceived stress in reference to membership of parental support groups (t=1.575, p=0.119). Pearson’s correlation showed a statistically significant association (r=0.611) between self-esteem and perceived stress at 0.01 levels. There is an urgent need for medical, psychological, and educational professionals to provide family-based interventions to assist parents raising a child with a disability.
Cognitive Offloading: Systematic Review of a Decade
Authors: Prachi Pandey  , Tara Singh  , Subodh Kumar
Published: August 2023

Cognitive offloading refers to the use of physical action to alter information processing requirement of the given task. Offloading can be done either internally or externally. We have been included cognitive offloading through external tools related papers. Cognitive offloading is applied aspect of Extended Mind Thesis (EMT). EMT is applicable to human beings, technological & cognitive artefacts and self & group. Deliberation points on EMT has been found: what is cognitive and how to differentiate causal coupling from constitutive. Necessary deliberations either acceptance or rejections till date has been included (from 2009 onwards) in this paper. EMT can also be applied to the web, known as web based cognitive offloading where web is collection of external representations. Interaction of mind with artefact is also included in this paper till date to enrich knowledge as mind artefact interaction is one of the forms of cognitive offloading. Empirical studies of cognitive offloading found in literature which revolve around the questions of why one engages in cognitive offloading despite of good memory. For poor memory or brain damage, external tools are good compensatory tool. This paper specifically deals with advances in technological & cognitive artifacts and at the end, future directions in cognitive offloading has been suggested.
O lugar da Carta de Tiago no cânon bíblico
Authors: Malzoni Claudio Vianney
Published: August 2023

O objeto do presente estudo é a Carta de Tiago e seu lugar no cânon bíblico. A Carta se situa entre aqueles escritos do Novo Testamento que tiverem mais dificuldade em ver aceita sua canonicidade, tendo sido novamente posta sob suspeita à época da Reforma. Uma vez que a definição de cânon não se restringe à lista dos escritos que compõem a Bíblia, mas também indica a regra de fé expressa por esses escritos, pode-se perguntar se a aporofobia, atitude comum na atualidade, inclusive entre cristãos, não implica tacitamente em novo rechaço à Carta de Tiago, pelo desprezo de seu ensinamento em relação aos pobres. A metodologia usada na investigação foi essencialmente a da pesquisa bibliográfica. Realizado o percurso da apresentação do tema, chegou-se à conclusão de que a Carta de Tiago comporta tal grandeza em seus ensinamentos de modo a sair-se vitoriosa dos percalços pelos quais passou. Passam os problemas, a Carta de Tiago permanece.
Autotransplante dentário de terceiro molar superior como alternativa à extração dentária sem substituição: relato de caso
Authors: Tenório Miguel Dias , Almeida Lucas Farias de , Damião Cecília Wéllida Laurentino , Oliveira Hugo Franklin Lima de , Liberatti Camila Marzone , Santos Júnior Elinaldo Borges dos , Santos Thayana da Silva , Correia Thiago Leopoldino da Silva , Moura Rafaella Ferreira , Lessa Samara Verçosa
Published: August 2023

Objetivo: Relatar o caso clínico de um paciente submetido a um transplante dentário autógeno do dente 28, conhecido como dente siso. Detalhamento do caso: Paciente do gênero masculino, 16 anos, apresentando fratura radicular com comprometimento total de furca, teve indicação de extração do dente 36 (primeiro molar inferior). Neste relato de caso foi realizado um autotransplante com transferência do elemento dentário 28 (dente siso), para a loja alveolar do elemento 36 (primeiro molar inferior). O indivíduo jovem reabilitado com prótese tem a necessidade de trocar a próte­se periodicamente, pois a falta de adaptação decorrente do desenvol­vimento dos maxilares do paciente jovem inviabiliza o seu uso, assim o autotransplante é o tratamento indicado para casos de extração sem substituição. Considerações finais: Garantir através dos resultados obtidos o sucesso do transplante de dente autólogo e o tratamento eficaz do plano cirúrgico e dotam melhor estética e função, bem como as condições necessárias para a manutenção da saúde bucal.
Cerebral infarction following administration of andexanet alfa for anticoagulant reversal in a patient with traumatic acute subdural hematoma
Authors: Nagai Arata , Karibe Hiroshi , Narisawa Ayumi , Kameyama Motonobu , Ishikawa Shuichi , Iwabuchi Naoya , Tominaga Teiji
Published: August 2023

Background:

Anticoagulants prevent thrombosis in patients with atrial fibrillation (AF) and venous thromboembolism but increase the risk of hemorrhagic complications. If severe bleeding occurs with anticoagulant use, discontinuation and rapid reversal are essential. However, the optimal timing for resuming anticoagulants after using reversal agents remains unclear. Here, we report early cerebral infarction following the use of andexanet alfa (AA), a specific reversal agent for factor Xa inhibitors, in a patient with traumatic acute subdural hematoma (ASDH). The possible causes of thromboembolic complication and the optimal timing for anticoagulant resumption are discussed.

Case Description:

An 84-year-old woman receiving rivaroxaban for AF presented with impaired consciousness after a head injury. Computed tomography (CT) revealed right ASDH. The patient was administered AA and underwent craniotomy. Although the hematoma was entirely removed, she developed multiple cerebral infarctions 10 h after the surgery. These infarctions were considered cardiogenic cerebral embolisms and rivaroxaban was therefore resumed on the same day. This case indicates the possibility of early cerebral infarction after using a specific reversal agent for factor Xa inhibitors.

Conclusion:

Most studies suggest that the safest time for resuming anticoagulants after using reversal agents is between 7 and 12 days. The present case showed that embolic complications may develop much earlier than expected. Early readministration of anticoagulant may allow for adequate prevention of the acute thrombotic syndromes.
Surgical treatment of epilepsy in a patient with bilateral periventricular nodular heterotopia: A case report
Authors: Kim Sergey Afanasievich , Ivanov Anton Olegovich , Halepa Anastasia Anatolievna , Sysoeva Anna Alexeevna , Gunenko Galina Alexandrovna
Published: August 2023

Background:

Periventricular nodular heterotopia (PNH) is a rare pathological condition characterized by the presence of nodules of gray matter located along the lateral ventricles of the brain. The condition typically presents with seizures and other neurological symptoms, and various methods of surgical treatment and postoperative outcomes have been described in the literature.

Case Description:

We present a case study of a 17-year-old patient who has been experiencing seizures since the age of 13. The patient reported episodes of loss of consciousness and periodic freezing with preservation of posture. Two years later, the patient experienced his first generalized tonic-clonic seizure during nocturnal sleep and was subsequently admitted to a neurological department. A magnetic resonance imaging scan of the brain with an epilepsy protocol (3 Tesla) confirmed the presence of an extended bilateral subependymal nodular heterotopy at the level of the temporal and occipital horns of the lateral ventricles, which was larger on the left side, and a focal subcortical heterotopy of the right cerebellar hemisphere. The patient underwent a posterior quadrant disconnection surgery, which aimed to isolate the extensive epileptogenic zone in the left temporal, parietal, and occipital lobes using standard techniques. As of today, 6 months have passed since the surgery and there have been no registered epileptic seizures during this period following the surgical treatment.

Conclusion:

Although PNHs can be extensive and located bilaterally, surgical intervention may still be an effective way to achieve seizure control in selected cases.
Computational and AI-Assisted Design of Dual-Metal Single-Atom Catalyst for Oxygen Reduction Reaction
Authors: Xie Evan , Wang Xijun
Published: August 2023

The electrocatalytic oxygen reduction reaction (ORR) plays a crucial role in numerous energy and sustainability systems, such as fuel cells, metal-air batteries, and water electrolysers. It holds significant potential for renewable energy generation, transportation, and storage, heralding a cleaner and more sustainable future. Recent trends have shown increased use of single-atom catalysts (SACs), particularly metal-N4 moieties grown on graphene-based 2D materials, for enhancing ORR efficiency. However, the rational design of SAC for high-performance ORR faces challenges due to unclear structure-property relationships and the limits of conventional experimental trial-and-error approaches. In this study, we harnessed the power of the density functional theory (DFT) calculations, combined with cutting-edge machine learning (ML) techniques, to explore 144 SACs featuring dual interacting M1-N4 and M2-N4 moieties (M1, M2 = Mn, Fe, Co, Ni, Cu, Ru, Rh, Pd, Ag Ir, Pt, Au), denoted as M1-M2, grown on graphene. Of all the catalysts we examined, emerged as the top performer, achieving an impressive overpotential of 0.980 V in alkaline conditions — outperforming most previously reported SACs. Even more striking, 25 of the evaluated SACs surpassed the renowned Fe-N4 SAC in catalytic efficiency, including more economically viable alternatives like Fe-Ag. Venturing further into innovation, we developed three ML models that accurately predict the overpotentials of various M1-M2 SACs, showing their strong ability to capture the relationship between single-atom metal site properties and overpotential. These models provide useful navigation toolkits for the rational design of effective electrocatalysts. Our study sheds light on the path toward achieving efficient SAC-catalyzed ORR, contributing to a more sustainable and energy-efficient future.
Group I Alkoxides and Amylates as Highly Efficient Radical Precatalysts for Silicon–Nitrogen Heterodehydrocoupling
Authors: Reuter Matthew , Javier-Jimenez Diego , Bushey Claire , Waterman Rory
Published: August 2023

Group I alkoxides are highly active precatalysts in the heterodehydrocoupling of silanes and amines. The broadly soluble and commercially available KOtAmyl was utilized as the benchmark precatalyst for this transformation. Challenging substrates such as anilines were found to readily couple primary, secondary, and tertiary silanes in high conversions (> 90%) after only 2 h at 40 °C. Traditionally challenging silanes such as Ph3SiH were also easily coupled to simple primary and secondary amines under mild conditions, with reactivity that rivals many rare earth and transition-metal catalysts for this transformation. Preliminary evidence suggests the formation of hypervalent intermediates, but radicals were detected under catalytic conditions, indicating a mechanism that is rare for Si–N bond formation.
Cations Mediate Lithium Polysulfide Adsorption in Metal-Organic Framework Coatings for Lithium-Sulfur Batteries
Authors: Jarrín Roberto A. , Bennett Kevin , Thoi V. Sara , Bukowski Brandon C.
Published: August 2023

Lithium-sulfur (Li-S) batteries are one promising alternative to Li-ion batteries due to their higher theoretical specific capacity and energy density. However, several technical challenges such as polysulfide shuttling remain. As liquid polysulfide diffusion into the electrolyte causes a loss of capacity, different material classes have been explored to anchor lithium polysulfides and reduce active material loss. The metal-organic framework (MOF) UiO-66 has been identified as one candidate material due to its porosity, high surface area, and zirconium oxide nodes that could anchor liquid polysulfides. MOFs also allow for post-synthetic modifications that can increase their adsorption specificity towards liquid polysulfides and reduce shuttling. In this work, we combined atomistic simulations and experimental characterization to probe the molecular interactions between lithium polysulfides and functionalized UiO-66 nodes. We explored how lithium polysulfides adsorb to open sites caused by missing linker defects, as well as sites functionalized with alkali cations. Our results demonstrate that lithium polysulfides adsorb favorably to UiO-66 through Li-O electrostatic interactions. In addition, we found that nodes functionalized with alkali metals demonstrated stronger adsorption of long chain lithium polysulfides (Li2S4-8) by facilitating charge transfer to the nodes. Experimental UV-Vis and 7Li-NMR measurements on Zr polyoxometallates and UiO-66 provided further evidence that lithiation favors adsorption of long chain polysulfides. Our findings show how UiO-66 functionalization may inhibit the shuttle effect through polysulfide adsorption, and consequently im-prove Li-S battery performance. The fundamental insights into polysulfide adsorption shown here provide quantitative principles to design functionalized moieties and further inhibit polysulfide shuttling.
Synthesis of Palladium Nanoparticles by Electrode-Respiring Geobacter sulfurreducens Biofilms
Authors: Chavez Marko , MacLean Magdalene , El-Naggar Mohamed
Published: August 2023

The electroactive microorganism Geobacter sulfurreducens can couple organic electron donor oxidation to the respiration of electrode surfaces, colonizing them in the process. These microbes can also reduce soluble metal ions, such as soluble Pd, resulting in metallic nanoparticle (NP) synthesis. Such NPs are valuable catalysts for industrially relevant chemical production; however, their chemical and solid-state synthesis are often energy intensive and result in hazardous biproducts. Utilizing electroactive microbes for precious metal NP synthesis has the advantage of operating under more sustainable conditions. By combining G. sulfurreducens’ ability to colonize electrodes and synthesize NPs, we performed electrode cultivation ahead of biogenic Pd(0) NP synthesis for the self-assembled fabrication of a biohybrid cell-Pd material. G. sulfurreducens biofilms were grown in electrochemical reactors with added Pd(II), and electrochemistry, spectroscopy, and electron microscopy were used to confirm (1) metabolic current production before and after Pd(II) addition, (2) simultaneous electrode respiration and soluble Pd reduction over time, and (3) biofilm-localized Pd NP synthesis. Utilizing electroactive microbes for the controlled synthesis of NPs can enable the self-assembly of novel cell-nanoparticle biohybrid materials with unique electron transport and catalytic properties.
VELIKIYE LUKI AS AN INTERDISTRICT CENTERAN
Authors: Жолобова Е.Э. , Смирнова А.А.
Published: August 2023

Данная статья посвящена особой категории городов – межрайонным центрам. В качестве примера такого населенного пункта рассмотрен город Великие Луки, который по выполняемым им функциям является значимым межрайонным центром на юге Псковской области. В силу периферийного положения Великие Луки оказывают существенное влияние и на соседние районы Тверской области, что было продемонстрировано по данным социальной сети «ВКонтакте». Были выбраны крупные виртуальные городские сообщества и проанализирована география их подписчиков. На основе этих данных были выделены группы районов, различающиеся по степени тяготения к межрайонному центру. Полученные результаты были сопоставлены с информацией о количестве автобусных маршрутов, связывающих Великие Луки с другими пунктами. В результате сопоставления «виртуальных» и «транспортных» данных была выделена зона значительного влияния Великих Лук как межрайонного центра.

This article is devoted to a special category of cities – inter-district centers. As an example of such a settlement, the city of Velikiye Luki is considered, which, according to the data on the functions performed by it, is a significant interdistrict center in the south of the Pskov region. Due to the peripheral position of Velikiye Luki, they also have a significant impact on the neighboring districts of the Tver region, which was demonstrated according to the VKontakte social network. Large virtual urban communities were selected and the geography of their subscribers was analyzed. Based on these data, groups of districts were identified that differ in the degree of attraction to the interdistrict center. The results obtained were compared with information on the number of bus routes connecting Velikiye Luki with other points. As a result of the comparison of «virtual» and «transport» data, the zone of significant influence of Velikiye Luki as an interdistrict center was identified.
SPATIAL ANALYSIS OF THE ECOLOGICAL FRAMEWORK OF THE CITY OF TVER
Authors: Сергеев А.Р. , Сукманова Н.Ю. , Прокофьева Н.Б.
Published: August 2023

В работе рассмотрены особенности формирования и функционирования «зелёного каркаса» как части экологического каркаса города Твери. Выявлены главные элементы зелёного каркаса (ядра, коридоры, центры и т.д.). Основное внимание уделено анализу пространственной динамики зелёных насаждений. Картографический, геоинформационный и визуальный анализ позволил выделить новые элементы территориальной структуры зелёного пространства Твери на трех уровнях, с вариантами решения проблемной ситуации.

The paper considers the features of the formation and functioning of the "green frame" as part of the ecological frame of the city of Tver. The main elements of green spaces (cores, corridors, centers, etc.) have been identified. The main attention is paid to the analysis of the spatial dynamics of green spaces. Cartographic, geoinformational and visual analysis made it possible to identify new elements of the territorial structure of the green space of Tver at three levels, with options for solving the current situation.
UNIVERSAL METHODOLOGICAL SCHEME FOR STUDYING THE SUBJECT AS AN ELEMENT OF ACHIEVING THE QUALITY OF EDUCATION
Authors: Григорович М.А.
Published: August 2023

Представлены авторские методические разработки для школьного курса географии: алгоритм универсальной схемы преподавания и универсальной схемы урока. Универсальные схемы – результат многолетнего опыта школьного учителя географии. Их назначение – разработка единых «правил» построения урока, нацеленного на результат. Универсальные схемы рассматриваются как элементы управления качеством образования.

The author's methodological developments for the school geography course are presented: the algorithm of the universal teaching scheme and the universal lesson scheme. Universal schemes are the result of many years of experience as a school geography teacher. Their purpose is to develop uniform “rules” for constructing a result-oriented lesson. Universal schemes are considered as elements of education quality management.
ADMINISTRATIVE COMPULSION IN AVIATION SECURITY
Authors: Зайкова С.Н.
Published: August 2023

Введение: механизм обеспечения авиационной безопасности основан на применении мер государственного принуждения. Целью исследования стала попытка определения сущностных признаков, особенностей и проблем в правом регулировании и применении отдельных мер административного принуждения на авиационном транспорте. Методологическая основа представлена совокупностью общенаучных и частнонаучных (логико-юридический, сравнительно-правовой) методов познания. Результаты: автором установлены противоречия между правовыми нормами, регулирующими порядок применения на воздушном транспорте различных видов досмотров, установленных Воздушным кодексом РФ и Федеральным законом «О транспортной безопасности». Выводы: административное принуждение в области обеспечения авиационной безопасности представляет собой применение уполномоченными федеральными органами исполнительной власти мер административного воздействия в установленных нормами административного права процессуальных формах, влекущее для субъектов инфраструктуры воздушного транспорта, эксплуатантов, авиационного персонала, пассажиров, физических лиц, находящихся на территории объектов инфраструктуры воздушного транспорта, а также иных лиц, осуществляющих свою деятельность на территории объектов инфраструктуры воздушного транспорта, правовые последствия.

Introduction: The mechanism used to ensure aviation security is based on state coercive measures’ application. The research goal was an attempt to determine the essential features, characteristics and gaps that could exist in legal regulation and application of specific administrative coercion measures in air transport field. The methodological basis is a set of general scientific and particular scientific (logical-legal, comparative-legal) knowledge methods. Results are as follows. The author has found out contradictions of the legal norms governing the application of various types of inspections for air transport established by the Air Code of the Russian Federation and the Federal Law "On Transport Security". Conclusions say that administrative coercion in aviation security field shall be considered as application by authorized federal executive authorities of administrative measures in the procedural forms established by administrative law rules, which entails some legal effects for air transport infrastructure entities, operators, aviation personnel, passengers, individuals located as well as other persons operating on the territory of air transport infrastructure.