bluuebunny/crossref_metadata_2025 huggingface dataset:
Acquiring Knowledge of Affective Events from Blogs Using Label Propagation
Authors: Ding Haibo , Riloff Ellen
Published: June 2022

Many common events in our daily life affect us in positive and negative ways. For example, going on vacation is typically an enjoyable event, while being rushed to the hospital is an undesirable event. In narrative stories and personal conversations, recognizing that some events have a strong affective polarity is essential to understand the discourse and the emotional states of the affected people. However, current NLP systems mainly depend on sentiment analysis tools, which fail to recognize many events that are implicitly affective based on human knowledge about the event itself and cultural norms. Our goal is to automatically acquire knowledge of stereotypically positive and negative events from personal blogs. Our research creates an event context graph from a large collection of blog posts and uses a sentiment classifier and semi-supervised label propagation algorithm to discover affective events. We explore several graph configurations that propagate affective polarity across edges using local context, discourse proximity, and event-event co-occurrence. We then harvest highly affective events from the graph and evaluate the agreement of the polarities with human judgements.
Labeling the Semantic Roles of Commas
Authors: Arivazhagan Naveen , Christodoulopoulos Christos , Roth Dan
Published: June 2022

Commas and the surrounding sentence structure often express relations that are essential to understanding the meaning of the sentence. This paper proposes a set of relations commas participate in, expanding on previous work in this area, and develops a new dataset annotated with this set of labels. We identify features that are important to achieve a good performance on comma labeling and then develop a machine learning method that achieves high accuracy on identifying comma relations, improving over previous work. Finally, we discuss a variety of possible uses, both as syntactic and discourse-oriented features and constraints for downstream tasks.
Distance Minimization for Reward Learning from Scored Trajectories
Authors: Burchfiel Benjamin , Tomasi Carlo , Parr Ronald
Published: June 2022

Many planning methods rely on the use of an immediate reward function as a portable and succinct representation of desired behavior. Rewards are often inferred from demonstrated behavior that is assumed to be near-optimal. We examine a framework, Distance Minimization IRL (DM-IRL), for learning reward functions from scores an expert assigns to possibly suboptimal demonstrations. By changing the expert’s role from a demonstrator to a judge, DM-IRL relaxes some of the assumptions present in IRL, enabling learning from the scoring of arbitrary demonstration trajectories with unknown transition functions. DM-IRL complements existing IRL approaches by addressing different assumptions about the expert. We show that DM-IRL is robust to expert scoring error and prove that finding a policy that produces maximally informative trajectories for an expert to score is strongly NP-hard. Experimentally, we demonstrate that the reward function DM-IRL learns from an MDP with an unknown transition model can transfer to an agent with known characteristics in a novel environment, and we achieve successful learning with limited available training data.
Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks
Authors: Ondruska Peter , Posner Ingmar
Published: June 2022

This paper presents to the best of our knowledge the first end-to-end object tracking approach which directly maps from raw sensor input to object tracks in sensor space without requiring any feature engineering or system identification in the form of plant or sensor models. Specifically, our system accepts a stream of raw sensor data at one end and, in real-time, produces an estimate of the entire environment state at the output including even occluded objects. We achieve this by framing the problem as a deep learning task and exploit sequence models in the form of recurrent neural networks to learn a mapping from sensor measurements to object tracks. In particular, we propose a learning method based on a form of input dropout which allows learning in an unsupervised manner, only based on raw, occluded sensor data without access to ground-truth annotations. We demonstrate our approach using a synthetic dataset designed to mimic the task of tracking objects in 2D laser data — as commonly encountered in robotics applications — and show that it learns to track many dynamic objects despite occlusions and the presence of sensor noise.
Component Caching in Hybrid Domains with Piecewise Polynomial Densities
Authors: Belle Vaishak , Van den Broeck Guy , Passerini Andrea
Published: June 2022

Counting the models of a propositional formula is an important problem: for example, it serves as the backbone of probabilistic inference by weighted model counting. A key algorithmic insight is component caching (CC), in which disjoint components of a formula, generated dynamically during a DPLL search, are cached so that they only have to be solved once. In the recent years, driven by SMT technology and probabilistic inference in hybrid domains, there is an increasing interest in counting the models of linear arithmetic sentences. To date, however, solvers for these are block-clause implementations, which are nonviable on large problem instances. In this paper, as a first step in extending CC to hybrid domains, we show how propositional CC systems can be leveraged when limited to piecewise polynomial densities. Our experiments demonstrate a large gap in performance when compared to existing approaches based on a variety of block-clause strategies.
Concepts Not Alone: Exploring Pairwise Relationships for Zero-Shot Video Activity Recognition
Authors: Gan Chuang , Lin Ming , Yang Yi , Melo Gerard , G. Hauptmann Alexander
Published: June 2022

Vast quantities of videos are now being captured at astonishing rates, but the majority of these are not labelled. To cope with such data, we consider the task of content-based activity recognition in videos without any manually labelled examples, also known as zero-shot video recognition. To achieve this, videos are represented in terms of detected visual concepts, which are then scored as relevant or irrelevant according to their similarity with a given textual query. In this paper, we propose a more robust approach for scoring concepts in order to alleviate many of the brittleness and low precision problems of previous work. Not only do we jointly consider semantic relatedness, visual reliability, and discriminative power. To handle noise and non-linearities in the ranking scores of the selected concepts, we propose a novel pairwise order matrix approach for score aggregation. Extensive experiments on the large-scale TRECVID Multimedia Event Detection data show the superiority of our approach.
Labeling the Features Not the Samples: Efficient Video Classification with Minimal Supervision
Authors: Leordeanu Marius , Radu Alexandra , Baluja Shumeet , Sukthankar Rahul
Published: June 2022

Feature selection is essential for effective visual recognition. We propose an efficient joint classifier learning and feature selection method that discovers sparse, compact representations of input features from a vast sea of candidates, with an almost unsupervised formulation. Our method requires only the following knowledge, which we call the feature sign - whether or not a particular feature has on average stronger values over positive samples than over negatives. We show how this can be estimated using as few as a single labeled training sample per class. Then, using these feature signs, we extend an initial supervised learning problem into an (almost) unsupervised clustering formulation that can incorporate new data without requiring ground truth labels. Our method works both as a feature selection mechanism and as a fully competitive classifier. It has important properties, low computational cost annd excellent accuracy, especially in difficult cases of very limited training data. We experiment on large-scale recognition in video and show superior speed and performance to established feature selection approaches such as AdaBoost, Lasso, greedy forward-backward selection, and powerful classifiers such as SVM.
Robust Complex Behaviour Modeling at 90Hz
Authors: Kong Xiangyu , Wang Yizhou , Xiang Tao
Published: June 2022

Modeling complex crowd behaviour for tasks such as rare event detection has received increasing interest. However, existing methods are limited because (1) they are sensitive to noise often resulting in a large number of false alarms; and (2) they rely on elaborate models leading to high computational cost thus unsuitable for processing a large number of video inputs in real-time. In this paper, we overcome these limitations by introducing a novel complex behaviour modeling framework, which consists of a Binarized Cumulative Directional (BCD) feature as representation, novel spatial and temporal context modeling via an iterative correlation maximization, and a set of behaviour models, each being a simple Bernoulli distribution. Despite its simplicity, our experiments on three benchmark datasets show that it significantly outperforms the state-of-the-art for both temporal video segmentation and rare event detection. Importantly, it is extremely efficient — reaches 90Hz on a normal PC platform using MATLAB.
Look, Listen and Learn — A Multimodal LSTM for Speaker Identification
Authors: Ren Jimmy , Hu Yongtao , Tai Yu-Wing , Wang Chuan , Xu Li , Sun Wenxiu , Yan Qiong
Published: June 2022

Speaker identification refers to the task of localizing the face of a person who has the same identity as the ongoing voice in a video. This task not only requires collective perception over both visual and auditory signals, the robustness to handle severe quality degradations and unconstrained content variations are also indispensable. In this paper, we describe a novel multimodal Long Short-Term Memory (LSTM) architecture which seamlessly unifies both visual and auditory modalities from the beginning of each sequence input. The key idea is to extend the conventional LSTM by not only sharing weights across time steps, but also sharing weights across modalities. We show that modeling the temporal dependency across face and voice can significantly improve the robustness to content quality degradations and variations. We also found that our multimodal LSTM is robustness to distractors, namely the non-speaking identities. We applied our multimodal LSTM to The Big Bang Theory dataset and showed that our system outperforms the state-of-the-art systems in speaker identification with lower false alarm rate and higher recognition accuracy.
Understanding Dominant Factors for Precipitation over the Great Lakes Region
Authors: Chatterjee Soumyadeep , Liess Stefan , Banerjee Arindam , Kumar Vipin
Published: June 2022

Statistical modeling of local precipitation involves understanding local, regional and global factors informative of precipitation variability in a region. Modern machine learning methods for feature selection can potentially be explored for identifying statistically significant features from pool of potential predictors of precipitation. In this work, we consider sparse regression, which simultaneously performs feature selection and regression, followed by random permutation tests for selecting dominant factors. We consider average winter precipitation over Great Lakes Region in order to identify its dominant influencing factors.Experiments show that global climate indices, computed at different temporal lags, offer predictive information for winter precipitation. Further, among the dominant factors identified using randomized permutation tests, multiple climate indices indicate the influence of geopotential height patterns on winter precipitation.Using composite analysis, we illustrate that certain patterns are indeed typical in high and low precipitation years, and offer plausible scientific reasons for variations in precipitation.Thus, feature selection methods can be useful in identifying influential climate processes and variables, and thereby provide useful hypotheses over physical mechanisms affecting local precipitation.
Trust and Distrust Across Coalitions: Shapley Value Based Centrality Measures for Signed Networks (Student Abstract Version)
Authors: Gangal Varun , Narwekar Abhishek , Ravindran Balaraman , Narayanam Ramasuri
Published: June 2022

We propose Shapley Value based centrality measures for signed social networks. We also demonstrate that they lead to improved precision for the troll detection task.
Automated Regression Testing Using Constraint Programming
Authors: Gotlieb Arnaud , Carlsson Mats , Liaaen Marius , Marijan Dusica , Pétillon Alexandre
Published: June 2022

In software validation, regression testing aims to check the absence of regression faults in new releases of a software system. Typically, test cases used in regression testing are executed during a limited amount of time and are selected to check a given set of user requirements. When testing large systems, the number of regression tests grows quickly over the years, and yet the available time slot stays limited. In order to overcome this problem, an approach known as test suite reduction (TSR), has been developed in software engineering to select a smallest subset of test cases, so that each requirement remains covered at least once. However solving the TSR problem is difficult as the underlying optimization problem is NP-hard, but it is also crucial for vendors interested in reducing the time to market of new software releases. In this paper, we address regression testing and TSR with Constraint Programming (CP). More specifically, we propose new CP models to solve TSR that exploit global constraints, namely NVALUE and GCC. We reuse a set of preprocessing rules to reduce a priori each instance, and we introduce a structureaware search heuristic. We evaluated our CP models and proposed improvements against existing approaches, including a simple greedy approach and MINTS, the state-of-theart tool of the software engineering community. Our experiments show that CP outperforms both the greedy approach and MINTS when it is interfaced with MiniSAT, in terms of percentage of reduction and execution time. When MINTS is interfaced with CPLEX, we show that our CP model performs better only on percentage of reduction. Finally, by working closely with validation engineers from Cisco Systems, Norway, we integrated our CP model into an industrial regression testing process.
Phase-Mapper: An AI Platform to Accelerate High Throughput Materials Discovery
Authors: Xue Yexiang , Bai Junwen , Le Bras Ronan , Bernstein Richard , Bjorck Johan , Liane Longpre Liane Longpre , Suram Santosh , Van Dover Robert , Gregoire John , Gomes Carla
Published: June 2022

High-throughput materials discovery involves the rapid synthesis, measurement, and characterization of many different but structurally related materials. A central problem in materials discovery, the phase map identification problem, involves the determination of the crystal structure of materials from materials composition and structural characterization data. We present Phase-Mapper, a novel solution platform that allows humans to interact with both the data and products of AI algorithms, including the incorporation of human feedback to constrain or initialize solutions. Phase-Mapper is compatible with any spectral demixing algorithm, including our novel solver, AgileFD, which is based on convolutive non-negative matrix factorization. AgileFD allows materials scientists to rapidly interpret XRD patterns, and can incorporate constraints to capture the physics of the materials as well as human feedback. We compare three solver variants with previously proposed methods in a large-scale experiment involving 20 synthetic systems, demonstrating the efficacy of imposing physical constraints using AgileFD. Since the deployment of Phase-Mapper at the Department of Energy’s Joint Center for Artificial Photosynthesis (JCAP), thousands of X-ray diffraction patterns have been processed and the results are yielding discovery of new materials for energy applications, as exemplified by the discovery of a new family of metal oxide solar light absorbers, among the previously unsolved Nb-Mn-V oxide system, which is provided here as an illustrative example. Phase-Mapper is also being deployed at the Stanford Synchrotron Radiation Lightsource (SSRL) to enable phase mapping on datasets in real time.
Real-Time Indoor Localization in Smart Homes Using Semi-Supervised Learning
Authors: Ghourchian Negar , Allegue-Martinez Michel , Precup Doina
Published: June 2022

Long-term automated monitoring of residential or small in- dustrial properties is an important task within the broader scope of human activity recognition. We present a device- free wifi-based localization system for smart indoor spaces, developed in a collaboration between McGill University and Aerˆıal Technologies. The system relies on existing wifi net- work signals and semi-supervised learning, in order to au- tomatically detect entrance into a residential unit, and track the location of a moving subject within the sensing area. The implemented real-time monitoring platform works by detect- ing changes in the characteristics of the wifi signals collected via existing off-the-shelf wifi-enabled devices in the environ- ment. This platform has been deployed in several apartments in the Montreal area, and the results obtained show the poten- tial of this technology to turn any regular home with an ex- isting wifi network into a smart home equipped with intruder alarm and room-level location detector. The machine learn- ing component has been devised so as to minimize the need for user annotation and overcome temporal instabilities in the input signals. We use a semi-supervised learning framework which works in two phases. First, we build a base learner for mapping wifi signals to different physical locations in the en- vironment from a small amount of labeled data; during its lifetime, the learner automatically re-trains when the uncer- tainty level rises significantly, without the need for further supervision. This paper describes the technical and practical issues arising in the design and implementation of such a sys- tem for real residential units, and illustrates its performance during on-going deployment.
Determining Relative Airport Threats from News and Social Media
Authors: Khandpur Rupinder , Ji Taoran , Ning Yue , Zhao Liang , Lu Chang-Tien , Smith Erik , Adams Christopher , Ramakrishnan Naren
Published: June 2022

Airports are a prime target for terrorist organizations, drug traffickers, smugglers, and other nefarious groups. Traditional forms of security assessment are not real-time and often do not exist for each airport and port of entry. Thus, homeland security professionals must rely on measures of attractiveness of an airport as a target for attacks. We present an open source indicators approach, using news and social media, to conduct relative threat assessment, i.e., estimating if one airport is under greater threat than another. The three ingredients of our approach are a dynamic query expansion algorithm for tracking emerging threat-related chatter, news-Twitter reciprocity modeling for capturing interactions between social and traditional media, and a ranking scheme to provide an ordered assessment of airport threats. Case studies based on actual aviation incidents are presented.
Tree stratum alteration decreases C use efficiency and the stability of litter decomposition in a sacred fir ( Abies religiosa ) forest
Authors: Choreño-Parra Eduardo M. , Ángeles-Pérez Gregorio , Villegas-Ríos Margarita , Beltrán-Paz Ofelia , Pérez-Pazos Eduardo , Quintero-Gradilla Shatya , Chávez-Vergara Bruno
Published: June 2022

Background: There is limited information to predict the direction in which canopy modification affects the microbial carbon use efficiency (CUE) and, consequently, the magnitude and stability of litter decomposition in monodominant sacred fir ( Abies religiosa ) forests.
Questions: What is the effect of tree stratum alteration on CUE and stability of litter decomposition in an A. religiosa forest?
Study sites and dates: Two conditions inside a sacred fir forest were selected: A) a naturally monodominant homogeneous condition, and B) a heterogeneous condition with a non-monospecific tree stratum derived from local disturbances (wildfire and reforestation) occurred on a single occasion 18 years ago.
Methods: In each condition (homogeneous and heterogeneous), the Importance Value Index (IVI) was calculated in the tree stratum, while chemical composition, microbial carbon (C) concentration, enzyme activities and C mineralization were measured in litter samples. The specific enzymatic activity and the metabolic quotient were calculated as CUE indicators, and the coefficient of variation as a proxy for litter decomposition stability.
Results: A change in tree species composition and an increase in tree species richness in the heterogeneous condition was found, which decreased litter phosphorous (P) concentration. This promoted a high microbial activity and low CUE, favoring C mineralization. Furthermore,  low stability during litter decomposition was observed as tree species richness increased.
Conclusions: Tree stratum heterogeneity, as a consequence of past disturbances, decreases CUE and the stability of litter decomposition in an A. religiosa forest.
Analisis Koefisien Reaktivitas Teras RSG-GAS pada Kondisi Hot Full Power (HFP)
Authors: Panggabean Jonny Haratua
Published: June 2022

Analisis koefisien reaktivitas teras RSG-GAS pada kondisi Hot Full Power  (HFP) telah dilakukan karena sangat berhubungan dengan keselamatan operasi. Perhitungan parameter ini belum pernah dilakukan, saat ini dilakukan dengan menggunakan dengan program komputer WIMSD-5B dan Batan-2DIFF. Program WIMSD-5B menggunakan data nuklir ENDFB-VIII.0 dengan muatan 250gram digunakan untuk menggenerasi tampang lintang makroskopik material teras dan program Batan-2DIFF digunakan untuk perhitungan teras. Tujuan penelitian ini adalah untuk mengetahui besaran parameter neutronik koefisien reaktivitas pada teras RSG-GAS dengan kondisi hot full power. Hasil perhitungan koefisien reaktivitas temperatur moderator dan temperature bahan bakar pada kondisi HFP adalah negatif dan nilainya tidak sama untuk setiap temperatur. Dari hasil perhitungan dapat disimpulkan bahwa teras reaktor bersifat undermoderated dan sesuai dengan harapan.  Kata kunci : koefisien reaktivitas, teras RSG-GAS, WIMSD-5B,  Batan-2DIFF, hot full power
Association Between Sleep Parameters and Postural Control: A Literature Review
Authors: Tanwar Tarushi , Veqar Zubia
Published: June 2022

Background and Objective The purpose of the review was to explore the association between sleep parameters and postural control.Methods The PubMed, Science Direct, and EBSCO were searched using the keywords ‘sleep’ including either sleep quality, sleep deprivation, poor sleep quality; and ‘postural control’ including either dynamic balance, static balance, postural balance, and balance control. Related studies published till December 2017 were selected.Results Acute sleep deprivation resulted in an impairment in postural control. Chronic sleep deprivation and postural control were also found to be related in a similar way to that of total sleep deprivation, thus affecting postural control negatively. Time of day was found to influence the postural control such that the postural control was better in the morning than in the latter part of the day. A study of the impact of aging on the effects of sleep deprivation on postural control revealed that loss of sleep had a more disturbing effect on postural control in the olderadult group than in younger participants, thus indicating a high risk of fall among the elderly.Conclusions Despite various limitations and methodological differences, this review has identified a negative influence on postural control due to impaired sleep in a wide range of populations, indicating the need for a more focused approach to sleep when assessing and measuring postural control.
Four Useful Concepts When Treating Patients With Insomnia: Possibility of Sleep Index-Based Cognitive Behavioral Therapy for Insomnia
Authors: Chung Seockhoon
Published: June 2022

Cognitive behavioral therapy for insomnia (CBT-I) is one of the most common treatments for insomnia and is considered as the first-line treatment. People who struggle to fall asleep or stay asleep or those who do not find sleep refreshing can benefit over four to six sessions of CBT-I. Although CBT-I has many benefits, it does have some drawbacks. Therefore, a brief version needs to be developed for use in clinical practice. This study proposes the following concepts that can be readily applied in clinical practice: 1) Concept 1, 17 hours of activity and 7 hours of sleep; 2) Concept 2, discrepancy between desired time in bed and desired total sleep time; 3) Concept 3, time in bed during 24 hours; and 4) Concept 4, taking sleeping pills 7 hours before the waking up time. These concepts based on sleep indices could easily help patients with insomnia and may serve as a foundation for the development of Sleep Index-based CBT-I.
Verification for Diagnosis of Sleep-Related Hypoventilation and Carbon Dioxide Partial Pressure During Sleep in Children Using End-Tidal Carbon Dioxide
Authors: Han Jang Gyu , Park Hannah , Yang Ji Sun , Kim Ji Su , Park Bumhee , Park Do-Yang , Kim Hyun Jun
Published: June 2022

Background and Objective From the past, several researchers have studied and measured the partial pressure of carbon dioxide during sleep in normal children to establish diagnostic criteria for hypoventilation in children. Here we tried to verify the existing definition of sleep-related hypoventilation in Asian by evaluating and analyzing the carbon dioxide partial pressure in pediatric subjects who underwent polysomnography.Methods We retrospectively analyzed clinical information of 196 children who underwent polysomnography at our hospital from Feb 2011 to Apr 2021. Among Asian pediatric subjects, those with serious chronic or genetic diseases, craniofacial deformities, and hypoventilation confirmed by polysomnography were excluded. We evaluated partial pressure of carbon dioxide in target group by end-tidal carbon dioxide (EtCO2) measured with a stream capnometer through nasal cannula. The target group was classified by apnea-hypopnea index and analyzed.Results The mean value of the time with EtCO2 ≥ 45 mm Hg in total sleep time was 47.00% which is higher than previous studies. The mean value of the time with EtCO2 ≥ 50 mm Hg in total sleep time was 2.77% which is similar to previous studies. Also, our subjects showed the highest mean EtCO2 value in non-rapid eye movement (NREM) stage and lowest mean EtCO2 value when wake.Conclusions In this study, the diagnostic criteria for sleep-related hypoventilation at the American Academy of Sleep Medicine (AASM) in 2017 established by measuring the EtCO2 in western children seems appropriate to apply to Asian children to define hypoventilation.
Complement C1QC as a potential prognostic marker and therapeutic target in colon carcinoma based on single-cell RNA sequencing and immunohistochemical analysis
Authors: Deng Huiming , Chen Yan , Liu Yong , Liu Li , Xu Ronghua
Published: June 2022

Immune cell infiltration plays an essential role in the occurrence and development of colon cancer. However, the main tumor-associated immune cell infiltration and its gene regulation in colon cancer still need to be further clarified in order to provide a new perspective for diagnosing and treating this disease. For this study, single-cell RNA sequencing (scRNA-seq) expression profiles and TCGA colon cancer data sets were first acquired from the GEO database. Then, Seurat, Monocle, LIMMA, Clusterprofile, GSVA and GSEABase algorithms were used to systematically examine the data. Potential target drugs corresponding to target genes were analyzed in the Drugbank database and detected by molecular docking. Immunohistochemistry was used to assess the level of C1QC expression in the tissue microarray. Single cell analysis suggested that neutrophil activation might be the critical regulatory pathway in colon cancer and that macrophages were the main cell population involved. Subsequent functional enrichment analysis on differential genes in macrophages suggested that C1QC may be a critical regulatory factor in the occurrence and progression of colon cancer, and was closely related to the survival of patients. According to the drug target prediction, palivizumab is a targeted drug for C1QC, and molecular docking demonstrated that palivizumab binds to C1QC. Additionally, tissue-microarray based immunohistochemical analysis showed that C1QC was highly expressed in colon cancer tissue, and the prognosis of colon cancer patients with high C1QC expression was worse, closely related to age, lymphatic metastasis and the TNM stage (Tumor, Nodes and Metastases). Our findings suggest that C1QC may regulate the macrophages in colon cancer immune infiltration, which is expected to be a potential immunotherapy target for colon cancer, and beneficial for the diagnosis and prognosis of colon cancer patients.
Anforderungen an modulare Elektrolyseanlagen
Authors: Scholz Lena , Markaj Artan , Fay Alexander , Erdmann Daniel , Beisswenger Lucien , Lorenzen Lukas , Urbas Leon , Bittorf Lukas
Published: June 2022

Um die Energiewende in Deutschland zu beschleunigen, sind Wasserstofftechnologien ein entscheidender Faktor. Mit der Nationalen Wasserstoffstrategie hat die Bunderegierung einen Grundstein für die Implementierung dieser Technologien gesetzt. In diesem Beitrag werden Vorgehen und erste Ergebnisse aus dem H2Giga-Projekt eModule vorgestellt. Es wird gezeigt, wie mithilfe des Requirements Engineerings Anforderungen an modulare Elektrolyseanlagen und deren automatisierten Betrieberhoben und aufgestellt werden können. Neben  Anforderungen werden Nutzungs- und Betriebsszenarien für modulare Elektrolyseanlagen definiert. Es werden ausgewählte exemplarische Ergebnisse dargestellt und erläutert. Diese Ergebnisse bilden die Basis für die Modellierung, Simulation und Steuerung von modular aufgebauten Elektrolyseanlagen.
Integrierte, modulare Demonstrationsanlage zur Biowachsherstellung
Authors: Lorenz Julius , Reichelt Erik , Näke Ralf , Zschiesche Christopher , Kureti Sven , Mädler Jonathan , Viedt Isabell , Klose Anselm , Urbas Leon
Published: June 2022

In einem auf erneuerbaren Energiequellen basierenden, sektorgekoppelten Energie- und Rohstoffsystem besteht die Notwendigkeit zur Speicherung fluktuierend anfallender elektrischer Energie. Die Speicherung in Form von chemischen Wertprodukten erfordert flexible, modulare Verfahrens- und Anlagenkonzepte. Im Forschungsprojekt ProRegional wurde eine integriertemodulare Demonstrationsanlage für die Erzeugung von synthethischem Rohöl und Wachs aus Biogas und erneuerbaren Energien untersucht, wobei die Automatisierung mit dem Module Type Package (MTP) bereits vorgedacht und anhand der virtuellenAnlage untersucht wurde.
The Right to Participate in Political and Decision-Making Process under the Maputo Protocol: Normative Masculinity and Nigerian Women
Authors: Eni Onyekachi , Nnam Macpherson Uchenna , Udu Eseni Azu
Published: June 2022

The birth of the Protocol on the Rights of Women in Africa otherwise known as Maputo Protocol was meant to overcome the shortcomings of the African Charter on Human Rights. Despite Nigeria’s ratification of the protocol, little concrete achievements have been recorded. This study situates the right of Nigerian women to participate in political and decision-making process under the Maputo Protocol in the context of normative and hegemonic barriers in the country. Using analytical methodology, the paper argues that the underrepresentation of Nigerian women in public governance is a negation of human rights. The domestication of the Protocol is recommended.
Correlation of Administrative Definitions of Refugees and Internally Displaced Persons: Compliance with International Standards
Authors: Gerasymenko Yevgen , Zadyraka Nataliia , Georgiievska Viktoriia , Kovalenko Nataliia , Leheza Yulia
Published: June 2022

The purpose of this study is to investigate the correlation of administrative definitions of refugees and internally displaced persons, as well as compliance of these definitions with international standards. The methodological framework of the study included analytical, legal, and statistical methods of analysis. The study employed general scientific and special methods of cognition. The paper investigates the main provisions of the legislative framework at the international and national levels. The applied methods allowed obtaining reliable and reasonable conclusions and results. Therefore, it is necessary to legislatively regulate the situation of persons who have been in Ukraine for a long time in violation of the law. The specified non-conformity of the legislation of Ukraine should be eliminated in two parallel ways. The specified non-conformity of the legislation of Ukraine should be eliminated in two parallel ways. On the one hand, any restrictions on the circle of persons to whom it applies should be excluded from the definition of IDPs in Article 1 of the Law of Ukraine “On Ensuring the Rights and Freedoms of Internally Displaced Persons”, primarily regarding the presence of stateless persons on the territory of Ukraine on legal grounds and the right to permanent residence in Ukraine. On the other hand, the corresponding law approves the procedure for determining a person as stateless, or apatride. This paper presents the criteria for the correlation between the terms “refugee” and “internally displaced person”. The practical value of this study lies in the fact that the investigation of the correlation of administrative definitions of refugees and internally displaced persons and their compliance with international standards is essential for practitioners and theorists in legal science.
Trans-Visibilities and Sexual Politics: Temporary Passages in Spanish Popular Cultures
Authors: Sabuco i Cantò Assumpta
Published: June 2022

This article aims to review the models that historically have shaped technologies of gender through popular representations in Spanish culture. First, an anthropological view will be cast on the naturalised Catholic-Francoist models that exalted heterosexual dichotomies and reproductive marriage. This includes an analysis of how, although the criminalization of transsexuals aggravated their situation, resistance movements generated a wide range of cultural references and possibilities for inclusion. Second, the article will review the models associated with Spain’s transition to democracy and their evolution moving on to the beginning of the 21st century. Finally, it will draw an outline of the trans models produced during the past two decades and their popular expressions.
Resolución de Tipos de Problemas y Niveles del Razonamiento Proporcional en Formación Inicial de Profesores de Matemática
Authors: Díaz Verónica , Aravena María
Published: June 2022

Este artículo tiene como objetivos determinar y analizar el desempeño de los futuros profesores de matemática de enseñanza secundaria en la resolución de tipos de problemas y los niveles del razonamiento proporcional. La investigación es descriptiva con metodología cuantitativa con una muestra de veinticinco estudiantes de una Universidad en Chile. Los datos se recopilan a través de una prueba de problemas de respuesta abierta sobre aplicaciones de la proporcionalidad. Los resultados develan capacidad de los estudiantes para resolver problemas rutinarios, preferentemente de contexto puramente matemático y en menor grado, fantasista, pero con alta dificultad en la resolución de problemas no rutinarios y de contexto real. La categoría de nivel aditivo es la mayormente utilizada, lo que demuestra la prevalencia del razonamiento pre-proporcional sin lograr alcanzar la categoría de nivel proporcional que incluye el desempeño de los estudiantes que usan relaciones proporcionales entre todos los datos para obtener la respuesta correcta.
Comparative analysis of minimally invasive methods of treatment of localized prostate cancer
Authors: Chinenov D. V. , Shpot E. V. , Chernov Ya. N. , Tsukkiev Z. K. , Votyakov A. Yu. , Kurbanov A. A. , Ismailov H. M. , Lerner Yu. V. , Rapoport L. M.
Published: June 2022

The purpose of this work is to study the functional and oncological results of minimally invasive methods in patients with verified prostate cancer.

Materials and methods. In our study, 160 patients with identified prostate cancer were presented, treatment was carried out with minimally invasive methods (methods of cryoablation (n = 53), brachytherapy (n = 52) and HIFU therapy (n = 55)). A qualitative assessment of the oncological outcome revealed high levels of prostate-specific antigen (PSA) and the results of repeated transrectal prostate biopsies. The evaluation of functional indicators and quality of life was carried out according to the results of the IIEF-5 (International Index of Erectile Function), IPSS (International Prostate Symptom Score), QoL (Quality of Life), Qmax (maximum urination rate of function).

Results. The results of oncological control according to the data of positive repeated biopsies were worse in patients after cryoablation (7.54 %), the best indicators of oncological results were observed in patients after brachytherapy. Looking at the IPSS results, it is possible to detect statistical signs of higher scores in the brachytherapy group when various signs are found in the postoperative period, however, these differences do not reach statistical signs in the late period in patients of group brachytherapy and cryoablation. Patients of the cryoablation group showed higher levels of the IIEF-5 in the postoperative period, in the late period of observation of erectile function in patients  of the cryoablation group, the statistical data did not differ from those in patients after brachytherapy. Patients after HIFU therapy showed a decrease in de novo erectile dysfunction over a 3-year follow-up period, above average IIEF5 scores, below IPSS scores, and better QoL results.

Conclusion. Long-term oncological results are, in general, revisions, however, the recurrence rate is slightly higher in patients after cryoablation. Prostate cancer recurrence was detected in patients of the ISUP 3 group. In patients after HIFU therapy, the quality of urination is higher than in patients of other groups, which can be associated with the laser enucleation of prostate hyperplasia performed by him. The advantage in patients after HIFU therapy was observed in the detection of IIEF-5, thus HIFU therapy had a better effect on the quality of life of patients with pathological prostate cancer.
Efficacy and safety of bovhyaluronidase azoximer in patients undergoing transurethral resection of the prostate
Authors: Shatylko T.  V. , Safiullin R. I. , Gamidov S. I. , Popova A. Yu. , Izhbaev S. H. , Mazitova A. F.
Published: June 2022

Introduction. Inflammation and fibrosis may have a significant role in pathogenesis of benign prostatic hyperplasia and associated lower urinary tract symptoms. Moreover, those factors may compromise the outcomes of surgical interventions for bladder outlet obstructions, such as transurethral resection of the prostate (TURP). Additional measures, such as administration of anti-fibrotic agents, may decrease the incidence of certain complications (e.g. bladder neck stenosis, urethral stricture) and improve overall outcomes of TURP. Bovhyaluronidase azoximer is an enzyme combined with high molecular mass copolymer which may inhibit surgery-related tissue remodeling and prevent excessive fibrosis.

Materials and methods. Sixty-five patients undergoing monopolar TURP were enrolled in this prospective randomized open-label study. Patients in Group 1 (n = 34) received 5 intramuscular injections of bovhyaluronidase azoximer (3000 IU) on days 3, 6, 9, 12 and 15 after TURP in addition to standard therapy. Patients in Group 2 (n = 31) received conventional peri-operative therapy. All patients routinely underwent uroflowmetry and post-void residual volume measurement on follow-up 3 months after TURP. Incidence of fibrosis-associated complications was compared using Fisher’s exact test. Uroflowmetric parameters were compared using Mann-Whitney U-test.

Results. One patient in Group 1 was excluded from the study due to mild allergic reaction after second injection of bovhyaluronidase azoximer. There were three cases of clinically significant fibrosis-associated complications in Group 2 which were confirmed on imaging (9.7 %). One case of stricture in bulbar urethra was later successfully managed with anastomotic urethroplasty, and two cases of bladder neck stenosis were managed with transurethral incision. No such complications were observed in Group 1 (0 %). However, the difference was not statistically significant (p = 0.1079). Otherwise, there were no adverse events in both groups. Median Qmax in Groups 1 and 2 was 24 ml/s and 22 ml/s, respectively (p = 0.08). Median Qave in Groups 1 and 2 was 15 ml/s and 9 ml/s, respectively (p <0.00001). Median of post-void residual volume in Groups 1 and 2 was 25 ml and 40 ml, respectively (p = 0.00438).

Conclusion. This study was underpowered to demonstrate significant difference in incidence of fibrosis-related complications of TURP, though there was a trend towards lower risk in patients treated with bovhyaluronidase azoximer. There was also a statistically significant difference in Qave and post-void residual volume in favor of Group 1, which may demonstrate lower rates of subclinical fibrosis. Overall, treatment with bovhyaluronidase azoximer was safe. Robust studies with longer follow-up are required to confirm efficacy of bovhyaluronidase preparations in post-TURP setting.
Urethral strictures in boys after hypospadias treatment: two-staged buccal urethroplasty
Authors: Ladygina E. A. , Demin N. V. , Nikolaev V. V.
Published: June 2022

Introduction. The most common cause of urethral strictures in boys is a complication of hypospadias treatment. Extended and complicated strictures represent the most difficult segment of the problem and the choice of the method of surgical correction.

The study objective is to review the technique and results of replacement urethroplasty with buccal graft in urethral strictures that occurred after treatment of hypospadias in childhood.

Materials and methods. A retrospective study conducted at the Clinical and Research Institute of Emergency Pediatric Surgery and Trauma from 2017 to 2020. Cases of 34 patients who underwent staged replacement buccal urethroplasty for complicated urethral stricture were studied. The examination revealed complications such as: Lichen sclerosus, short urethra, fistulas, diverticula, multiple (double) and extended strictures.

Results. Complications occurred in 3 (8.8 %) patients: cutaneous urethral fistula developed in two, partial scarring of the free graft occurred in one child. Long-term results were assessed after an average of 16 months. Our experience of treating 34 pediatric and adolescent patients with p after-hypospadias strictures showed that the leading cause of stricture formation after hypospadias treatment is Lichen sclerosus, which occurred in 16 patients.

Conclusion. During the last century, many donor tissues have been proposed for free urethroplasty, but it is the buccal graft that has won the largest number of supporters, and two-staged urethroplasty has become the method of choice for strictures of the anterior urethra. The surgeon’s considerable experience in performing buccal urethroplasty, adherence to the nuances of the technique and methodology of postoperative management, both at the first and second stages, allows you to obtain a good cosmetic and functional result even after a number of unsuccessful operations.
Combination of plastic surgery of the pyeloureteral junction with kidney transposition and nephropexy in hydronephrosis of a dystopic kidney
Authors: Laletin D. I. , Firsov M. A. , Bodyagin V. Y. , Bezrukov E. A. , Simonov P. A.
Published: June 2022

Introduction. Obstruction of the pyeloureteral junction is the most common anomaly of the upper urinary tract. Irrespective of the causes, narrowing of the ureteropelvic junction leads to abnormal urine outflux, increased intrarenal pressure, gradual sclerosis of renal parenchyma, loss of kidney function. In some cases, obstruction of the ureteropelvic junction can be accompanied by dystopic kidney, nephroptosis, abnormal location of the main and accessory renal vessels which requires correction of the standard surgical treatment.

The study objective is to evaluate the effectiveness of combination of laparoscopic pyeloplasty with kidney transposition and nephropexy in obstruction of the pyeloureteral junction of a dystopic kidney.

Materials and methods. Medical records of 8 patients who underwent surgery in the Kracnoyarsk Regional Clinical Hospital between 2017 and 2021 were analyzed. Obstruction of the pyeloureteral junction was confirmed clinically by ultrasound of the kidneys, excretory retrograde pyelography, contrast-enhanced spiral computed tomography.

Results. In all of the 8 patients, lumbar dystopia of the affected kidney was diagnosed, in 25 % pathology was accompanied by nephroptosis, in 50 % of cases by abnormal location of the main and accessory renal vessels. All patients underwent laparoscopic plastic surgery of the pyeloureteral junction per Anderson–Hynes with antegrade ureter stenting, kidney transposition, nephropexy. Mean operative time was 190 ± 39 min, no intraoperative blood loss was observed. Ureteral catheter was removed at day (6.3 ± 2.2). Hospital length of stay was 9.3 ± 3.7 days. In 1 patient, postoperative period was complicated by suture breakage in the posterior wall of the pyeloureteral anastomosis which required repeat laparoscopy to correct suture defect. Time of ureteral stent implantation was 34.6 ± 8.5 days. Control examination showed full remission of pain syndrome. Excretory urography showed full outflow of the contrast agent after examination with furosemide in 100 % of cases.

Conclusion. Combination of laparoscopic plastic surgery of the pyeloureteral segment with kidney transposition and nephropexy is an effective minimally invasive operation for treatment of ureteropelvic junction stricture of a dystopic kidney.