bluuebunny/crossref_metadata_2025 huggingface dataset:
Buddhismus,queer-gedacht
Authors: Scherer Bee
Published: September 2022

Dieser Beitrag untersucht die Schnittstelle zwischen queeren Subjektivitäten und psychischer Gesundheit und Suizidalität; der angeblich positive Einfluss von Religiosität auf psychische Gesundheit und buddhistische Antworten und Wege zu Befreiungspraktiken werden diskutiert. Ausgehend vom Freitod des 26-jährigen schwulen Burmesen Kyaw Zin Win wird untersucht, wie Buddhistische Traditionen konzeptionell und sozial-systemisch zu queerem Leiden und Suizidalität beigetragen haben. Durch kritische Hermeneutik werden Möglichkeiten für engagierte buddhistische inklusive Praktiken für soziale Gerechtigkeit aufgezeigt; buddhistische Perspektiven auf queere Diskriminierung und Suizidalität können so hinterfragt und überdacht werden.
Der politische Aushandlungsprozess um die Ehe für alle zwischen Konservatismus und Moderne
Authors: Exner-Krikorian Sabine
Published: September 2022

2021 jährte sich zum zwanzigsten Mal die Einführung des Lebenspartnerschaftsgesetzes und damit der Eingetragenen Lebenspartnerschaft als das erste Rechtsinstitut für gleichgeschlechtliche Paare. 2017 löste die Ehe die Lebenspartnerschaft ab, allerdings nicht mit allen Rechten einer Ehe wie zwischen heterosexuellen Personen. Der Aushandlungsprozess zur sogenannten Ehe für alle ist insbesondere für religionswissenschaftliche Fragestellungen erkenntnisreich. Am Beispiel des Diskurses um die Einführung der gleichgeschlechtliche Ehe in Deutschland 2015 und dem Referendum in Irland als diskursivem Ereignis zeigt die Autorin, wie politische Akteur*innen in einem zeitgenössischen Deutungskampf um die Bedeutung von Ehe wetteifern und dabei mit der Diskursprämisse einer angenommenen Moderne die Dichotomie von religiös vs. säkular sowie weitere Narrative von und über Religion(en) zur Selbst- und Fremdpositionierungen sowie für ihre Koalitions- und Oppositionsbildungen einsetzen. Die Analyse verwendet einen zeit-, akteurs- und arenaspezifischen Ansatz und verknüpft methodologisch die Wissenssoziologische Diskursanalyse (WDA) mit einem religionswissenschaftlichen Erkenntnisinteresse.
Die aktuelle Situation der Frauen in Afrika
Authors: Medoux Irma Julienne Angue
Published: September 2022

Diese Situation wird als eine Kumulation aller Ungleichheiten beschrieben, die einen Menschen treffen können: soziale Klassenungleichheit, sexuelle Ungleichheit und Ungleichheit aufgrund der Rasse. Durch die Zuspitzung dieser Ungleichheiten lässt sich die große Zahl afrikanischer Migrantinnen erklären. Die Suche nach sozialer, ziviler und bürgerlicher Gleichheit, die nach dem Modell der von Männern propagierten und zur Schau gestellten Selbstbeherrschung gedacht ist, kann in dem Maße nicht erfolgreich sein, wie sie versucht, sich einem Macho-Modell zu unterwerfen, das der Natur des Menschen widerspricht. Weil die zeitgenössische Anthropologie uns lehrt, dass dieser die Sprache erfinden musste, um sich das Leben zu ermöglichen und es jedes Mal neu zu harmonisieren, wenn er in eine Sackgasse gerät, weil die dialogische Vorstellungskraft, die den Dialog der Seele mit sich selbst antreibt, den Platon entdeckt hatte, durch das Gesetz der Wahrheit geregelt wird, müssen afrikanische Frauen erkennen, dass sie die Objektivität der ihnen auferlegten und der von ihnen selbst erfundenen Lebensbedingungen beurteilen müssen, um ihre Wahrheitsurteile mit ihren männlichen Partnern teilen zu können und um sich von jeglicher Herrschaft zu emanzipieren, unabhängig von ihrer Geschlechtszugehörigkeit.
An der Schwelle zum Dritten Weltkrieg – Welche Risiken darf der Westen im Ukraine-Krieg eingehen?
Authors: Krause Joachim
Published: September 2022

Kurzfassung

Die führenden westlichen Mächte USA, Großbritannien, Frankreich und Deutschland liefern zwar Waffen an die Ukraine, konditionieren aber stark das Ausmaß der Lieferungen sowie das sonstige Niveau ihrer Unterstützung. Hauptsächlich gelte es einen Weltkrieg mit nuklearer Eskalation zu vermeiden. Experten und frühere hochrangige Generäle kritisieren zunehmend diese Restriktionen, die sich an Konzepten der Rüstungskontrolle aus den 60er Jahren orientieren. Sie argumentieren, dass Russland weder die Absicht habe noch die Mittel besitze, den Krieg zu eskalieren – es sei denn, es wolle einen selbstmörderischen Nuklearkrieg beginnen. Außerdem lasse Russland keine Anzeichen von Restriktionen erkennen. Die derzeitige Fokussierung auf das Vermeiden eines Dritten Weltkriegs dürfte die Ukraine in absehbarer Zeit in eine unhaltbare Lage bringen. Dann bliebe den westlichen Staaten nur die sehr kostspielige Option, die Ukraine dauerhaft wirtschaftlich und militärisch über Wasser zu halten oder ihr einen Waffenstillstand aufzuzwingen, der bestenfalls eine militärische Pause bis zum nächsten russischen Angriff darstellen wird. Die Gefahr eines Weltkriegs könnte durch die westliche Politik der Vorsicht eher zu- denn abnehmen.
A Modular Smart Vision System for Industrial Inspection and Control of Conformity
Authors: El Helou Marwan , Benfriha Khaled , Al-Ahmari Abdulrahman M. , Wardle Peter , Talhi Esma , Loubère Stéphane , El Zant Chawki , Charrier Quentin
Published: September 2022

In manufacturing systems, there are several essential tasks to perform before and after the production process. In traditional systems, these tasks were done manually, which can lead to more resource consumption and the risk of human error; however, advanced manufacturing systems and Industry 4.0 tend toward a more autonomous manner. To ensure the compliance of the machining process and the safety of the personnel as well as the machines at the shop floor, the inspection of the overall factory prior to any machining process and the control of conformity of the manufactured parts are necessary in order to know the status of the manufacturing line. This paper proposes a novel modular smart vision system for machine inspection and conformity control of machined parts. Our system uses smart vision technologies embedded in industrial robots and enhanced with image processing and analysis capabilities. The solution also integrates a user interface for human–machine interactions that has been developed with a modular approach, and is designed, launched, and controlled by the manufacturing execution system, allowing agile and customized configuration. By this new approach, the robot inspects all the machines in the factory to check the status before launching the production plan. After the machining process, the system interprets the in situ dimensional analysis for the machined parts and makes decisions about whether the parts are acceptable or require additional machining.
Investigation of Blockchain Technology Integration within Food Supply Chain Management
Authors: Ali Taş Mehmet , Latif Aylak Batin
Published: September 2022

Blockchain technologies (BT) began to be used in many areas because of the many advantages they offer. In this respect, BT applications take place in different types of supply chains. One of the areas where blockchain is used is the food supply chain (FSC). FSC is a general concept that also covers different types such as agri-FSC and cold chain. These supply chains need the advantages of modern BT for crucial reasons such as the products’ time-dependent nature and direct impact on human health. We evaluate the use of blockchain applications in the field of FSC in order to provide a deep understanding of problems inherent to the FSC and present insights to companies into developing and implementing their own blockchain-driven solutions to address the FSC performance challenges. As the FSC is a complex and dynamic system, where multi-stakeholders are involved, a systematic approach should be established to reveal the BT integration behavior of the FSC. An extensive literature review was conducted within the scope of the study. A critical review of the studies shows which BT applications are used in the FSC chain to drive supply chain performance, their application areas, and main problems in various aspects in the applications. Using the causal loop diagram (CLD) as a system dynamics approach, the interrelationship of causes and effects is visualized and prescriptive information is generated to guide researchers and practitioners in the field of new technology adoption in FSCs in general and BT integration in particular. This study is intended to encourage the use of BT in FSC applications.
Measuring Nonapoptotic Caspase Activity with a Transgenic Reporter in Mice
Authors: Nicholls P. J. , Pack Thomas F. , Urs Nikhil M. , Kumar Sunil , Zhou Yang , Ichim Gabriel , Ginzel Joshua D. , Turu Gabor , Calabrese Evan , Roberts Wendy L. , Fan Ping , Ostapchenko Valeriy G. , Guzman Lenis Monica S. , Beraldo Flavio , Hatina Jiri , Prado Vania F. , Prado Marco A. M. , Spasojevic Ivan , Snyder Joshua C. , Dzirasa Kafui , Johnson G. Allan , Caron Marc G.
Published: September 2022

The protease caspase-3 is a key mediator of apoptotic programmed cell death. But weak or transient caspase activity can contribute to neuronal differentiation, axonal pathfinding, and synaptic long-term depression. Despite the importance of sublethal, or nonapoptotic, caspase activity in neurodevelopment and neural plasticity, there has been no simple method for mapping and quantifying nonapoptotic caspase activity (NACA) in rodent brains. We therefore generated a transgenic mouse expressing a highly sensitive and specific fluorescent reporter of caspase activity, with peak signal localized to the nucleus. As a proof of concept, we first obtained evidence that NACA influences neurophysiology in an amygdalar circuit. Then focusing on the amygdala, we were able to quantify a sex-specific persistent elevation in caspase activity in females after restraint stress. This simplein vivocaspase activity reporter will facilitate systems-level studies of apoptotic and nonapoptotic phenomena in behavioral and pathologic models.
Evaluation of the influence of SrTiO3 and CoO nanofillers on the structural and electrical polymer blend characteristics for electronic devices
Authors:   University of Babylon, College of Education for Pure Sciences, Department of Physics, Iraq, Mahdi S. M. , Habeeb M. A. ,   University of Babylon, College of Education for Pure Sciences, Department of Physics, Iraq
Published: September 2022

Using the casting method, the films of nanocomposites (NCs) are made from a (PEOPVA) mixture with varying ratios of SrTio3 and CoO nanoparticles (NPs). The results show that increasing the ratio of (SrTiO3-CoO) NPs improved the electrical and structural characteristics of (PEO-PVA-SrTio3-CoO) NCs. The scanning electron microscopy results demonstrate that morphology on surface of the (PEO-PVA-SrTiO3-CoO) NCs is homogeneous and coherent, with several groupings or pieces distributing on the top of the surface at random. According to the dielectric characteristics, dielectric constant and dielectric loss of the NCs reduce with increasing the frequency of the applied electric field and increases with increasing concentration of (SrTiO3-CoO) nanoparticles. As the concentration of (SrTiO3-CoO) and frequency are increased, conductivity increases. The results of structural and electrical characteristics show that the (PEO-PVA-SrTiO3-CoO) NCs may be used for various electronics fields.
A Study on Obstacle Detection For IoT Based Automated Guided Vehicle (AGV)
Authors: Osman Zahid Muhammed Nafis , Hao Loh Jit
Published: September 2022

In modern manufacturing industry context, Automated Guided Vehicles (AGVs) are mobile robots used in aiding the process of material handling from one point to a desired location in the workplace. Development on AGVs is a trending discussion among researchers due to its wide usage and the implementation of the Industrial 4.0. The performance of the AGVs is one of the spotlight issues in order to compete with the rising technologies and demanding workload in the industry. Current concern on obstacle detection in AGVs has become more subjective due to the uprising issue on the congested environment in the workplace. Therefore, an IoT system is developed to allow a flexible wireless communication among mobile robots in an indoor industrial environment. An AGV prototype is designed for obstacle detection and the performance is analyzed. In order to improve obstacle detection in the AGV prototype, Kalman Filtering (KF) algorithm is used in the signal filtering for the HC-SR04 Ultrasonic Sensor data acquisition. Furthermore, the communication verification is diagnosed for the Wi-Fi connection broadcast traffic and network latency. The study produced several significant results related to obstacle detection of AGV with IoT based technology. Experiment results show the vehicle movement reaction in dealing with obstacles. Next, the KF programming algorithm managed to diminish the measurement noise including the Main bang and flaw echo of the ultrasonic sensor. Moreover, the IoT system allows ease of accessibility and user-friendly GUI. Results proved that Wi-Fi is a reliable communication medium in obstacle detection and is comparable to ZigBee and Bluetooth connection. The communication delay for wireless connectivity on the AGV prototype surpassed the requirements of latency test, which is less than 20 ms. The research concludes that the IoT-based AGV prototype is competent and reliable in handling the obstacle detection in fixed route with indoor environment workplace.
Literackie kreacje świata reklamy w wybranych utworach autorów urodzonych na przełomie lat 1970–1980
Authors:   Wydział Filologiczny, Uniwersytet w Białymstoku, Łozowski Maciej
Published: September 2022

The aim of the article is to discuss the ways in which the world of advertising is created in selected works by writers born in the late 1970s and early 1980s who had a background in marketing. The author presents the socio-economic situation of young aspiring writers in Poland at the beginning of the 21st century. He points out the reasons why they decided to work in advertising agencies and how it translated into their literary work. The author analyzes the novels Copyfighter by Łukasz Krakowiak, Nie żyję, więc jestem [I’m Dead, Therefore I Am] by Katarzyna Byzia and Małż [Mollusk] by Marta Dzido, focusing on the ways of creating the presented world, protagonists and language.
Służące domowe we współczesnej literaturze popularnonaukowej
Authors:   Wydział Historyczny, Uniwersytet im. Adama Mickiewicza w Poznaniu, Wesołowska Julia
Published: September 2022

The article offers a critical reading of two popular science works about domestic servants Służące do wszystkiego [Servants for Everything]by Joanna Kuciel-Frydryszak and Instrukcja nadużycia [Instruction on Abuse] by Alicja Urbanik-Kopeć. According to the author, until recently domestic servants in Poland were exclusively the subject of academic consideration. At present, the subject has been taken up by popular science literature, which offers the reader a portrait of an archetypal female servant – a young (about 20–25 years old) and uneducated single woman, tormented by life and exploited by “masters”. The author of the review ponders the question to what extent such a portrait genuinely reflects historical reality. She believes that the books under discussion deploy certain historical and literary tropes, which are intended to portray the history of servants and employers in a certain way. This raises the question of why exactly this way of narrating the subject has gained an audience, and whether it really fulfills the need to give voice to servants.
Determinación de Helicobacter spp. en mucosa gástrica glandular de mulas a través de la prueba de la actividad de la ureasa e histopatología
Authors: Calixto L. C. , Martínez J. R.
Published: September 2022

La información sobre la presentación y los factores predisponentes del síndrome de úlcera gástrica en mulas (SUGM) es escasa en comparación con el síndrome de úlcera gástrica en equinos (SUGE) y asnales. Debido a la naturaleza multifactorial de este síndrome, la helicobacteriosis ha sido estudiada en otras especies. El objetivo fue establecer la presencia de Helicobacter spp. en mucosa gástrica de mulas a través de la prueba rápida de la ureasa (PRU) y de análisis histopatológico. Menos del 27% de las muestras reaccionaron a la PRU, con tiempos prolongados de reacción, y al Agar Urea (prueba de oro), con menor porcentaje de positividad. La histopatología reveló procesos inflamatorios crónicos, sin presencia de bacterias curvoespiraladas. Las PRU no fueron conclusivas en la determinación de Helicobacter spp., comportamiento similar reportado en equinos. Se requieren exámenes diagnósticos específicos y procedimientos complementarios que explore regiones del estómago en consideración del número de muestras representativas.
Iron nanoparticles for plant nutrition: Synthesis, transformation, and utilization by the roots of Cucumis sativus
Authors: Gracheva Maria , Klencsár Zoltán , Kis Viktória Kovács , Béres Kende Attila , May Zoltán , Halasy Viktória , Singh Amarjeet , Fodor Ferenc , Solti Ádám , Kiss László Ferenc , Tolnai Gyula , Homonnay Zoltán , Kovács Krisztina
Published: September 2022

Nanotechnology has been evolving in the past decades as an alternative to conventional fertilizers. Ferrihydrite nanoparticles that model the available Fe pool of soils are proposed to be used to recover Fe deficiency of plants. Nevertheless, ferrihydrite aqueous suspensions are known to undergo slow transformation to a mixture of goethite and hematite, which may influence its biological availability. Several nanocolloid suspensions differing in the surfactant type were prepared for plant treatment and fully characterized by transmission electron microscopy and 57Fe Mössbauer spectroscopy supported by magnetic measurements. The rate of transformation and the final mineral composition were revealed for all the applied surfactants. Nanomaterials at different stages of transformations were the subject of plant physiological experiments aiming at comparing the behavior and plant accessibility of the manufactured suspensions of nanoscale iron(III) oxide and oxide–hydroxide particles.

Graphical abstract
Endoscopic resection of bladder urothelial neoplasm in a child: a case report
Authors:   Communal Institution Zhytomyr Oblast Children’s Clinical Hospital of Zhytomyr Oblast State Administration, Ukraine, Shevchuk Dmytro ,   Zhytomyr Ivan Franko State University of the MES of Ukraine,   Shupyk National Healthcare University of Ukraine, Kyiv, Zaremba Vitalii ,   Communal Institution Zhytomyr Oblast Children’s Clinical Hospital of Zhytomyr Oblast State Administration, Ukraine, Vasianovych Andrii ,   Zhytomyr Oblast Morbid Anatomy Department of Zhytomyr Oblast State Administration, Ukraine
Published: September 2022

Bladder tumour, especially urothelial neoplasm, is a very rare condition in paediatric age. That is why true and accurate information on biological grade of malignancy and, correspondingly, the surgical management is absent. However, the majority of physicians take the view that this type of tumour has a low grade of malignization and recurrence, even after the endoscopic excision of neoplasm in paediatric patients. Purpose - to describe a clinical case of surgical management of the bladder urothelial neoplasm in a child by means of minimally invasive equipment. Clinical case. Endoscopic methods of surgical treatment are widely used in paediatric patients with the urinary tract conditions in our clinic. The transcutaneous surgical treatment of bladder conditions has been employed in paediatric patients since 2010. For example, it was used for the removal of ureterolith impacted in the bladder neck and foreign bodies of the bladder, as well as the bladder urothelial neoplasm excision. We also tried to use it for visualisation of the posterior urethra rupture length through a cystoscope, which was put into the epicystostomic hole of the posterior urethra together with the simultaneous urethroscopy (for the purpose of the directed illumination during the urethroscopy). However, due to the long length of the posttraumatic urethrostenosis, it was impossible to achieve the illumination and catheterisation of the urethra during the urethroscopy in the site of damage. The clinical case of the minimally invasive resection of the bladder urothelial neoplasm in a child is presented in the article. Minimally invasive techniques give the opportunity to perform even the radical operations with the perfect cosmetic result and minimal injury that is very important in the paediatric patients. The research was carried out in accordance with the principles of the Helsinki Declaration. The informed consent of the patient was obtained for conducting the studies. No conflict of interests was declared by the authors. Key words: bladder neoplasm, transcutaneous cystoscopy, neuromuscular bladder dysfunction, children.
On the role of voice and prosody in argumentation among pre-school children
Authors: Bose Ines , Hannken-Illjes Kati
Published: September 2022

This paper focuses on the role of voice and prosody in children’s argumentation and its relation to framing argumentation as more or less cooperative. Theoretically the project draws from rhetoric, argumentation studies, child studies and linguistics. After a brief overview of the current state in children’s argumentation we shall discuss the notion of multimodality in argumentation studies, specifically the role of voice and prosody in argumentation. The paper analyses two instances of child–child argumentation that show striking similarities and differences: Both deal with the same quaestio – that is the same controversial standpoint – and employ similar topoi – that is formal and material resources for arguments. However, they differ with respect to the cooperative framing – that relates in part to the framing of the interaction as fictional or factual – and with respect to the interaction tension. Methodologically, the paper takes a sequential perspective, grounded in conversation analysis and auditory phonetics. We work with longitudinal corpora of authentic child–child communication (3.0–7.0) in play. We argue that other-than-verbal means like voice and prosody play a crucial role in framing the interaction, thereby mediating the degree of cooperativity. This mediation has consequences for the elaboration of argumentative sequences by the children. Thus, voice and prosody we argue, can play a substantial role in argumentation.
From flat propositions to deep co-constructed and modalized argumentations
Authors: Luginbühl Martin , Kreuz Judith
Published: September 2022

Drawing on a corpus of 180 peer discussions of second, fourth and sixth graders in German-speaking Swiss elementary schools (ages 7–12), we comment on three aspects of oral argumentative competence: (1) giving reasons, (2) argumentative complexity and co-constructions, and (3) modalization of arguments. We combine qualitative and quantitative analyses, both based in the approach of conversation analysis, and show that, as children get older, they not only give more reasons for their arguments, but also match them to their partner’s perspective, modalize their different standpoints to a greater extent, and produce arguments that are more complex and co-constructed. We observe a bigger change in these argumentative practices between the second and fourth grades than between the fourth and sixth.
Anais do XXIII Congresso Nacional de Engenharia de Segurança no Trabalho - CONEST
Authors: Barreto Clarice
Published: September 2022

A Associação Nacional de Engenharia de Segurança do Trabalho (ANEST) em conjunto com a Associação dos Engenheiros de Segurança do Trabalho de Londrina - PR (ASENGEST), realizou nos dias 24, 25 e 26 de novembro de 2021, o “23º CONEST – Congresso Nacional de Engenharia de Segurança do Trabalho”. Evento Técnico-científico destinado a atualização e troca de experiências, abordando como tema central: DESAFIOS PROFISSIONAIS NO MUNDO EM TRANSFORMAÇÃO, com a participação de renomados palestrantes nacionais e internacionais. Os diversos temas selecionados foram abordados em conferências, painéis e mini- cursos, utilizando-se de protocolos restritos e medidas preventivas rigorosas de saúde e segurança, tendo em vista o estado pandêmico em COVID-19 que o mundo se encontra.
Changes in the prevalence of atrial fibrillation in the Russian population over a 13-year follow-up
Authors: Shapkina M. Yu. , Mazdorova E. V. , Avdeeva E. M. , Shcherbakova L. V. , Ryabikov A. N. , Hubachek J. A. , Bobak M. , Malyutina S. K.
Published: September 2022

Aim. To study the prevalence of atrial fibrillation (AF) in the Russian urban population cohort aged 45-69 years and its changes over 13-year follow-up during aging.

Material and methods. This cross-sectional long-term prospective study included random population sample of men and women 45-69 years (n=9360, HAPIEE project, Novosibirsk), which was examined in 2003-2005 and was re-examined twice and followed up for about 13±1,00 years in men and 13,1±2,17 years in women. The incidence of AF was assessed for individuals without AF or cardiovascular disease (CVD) at the baseline examination. Statistical analysis was performed using the SPSS software package (v.13.0).

Results. In a population sample over a 13-year follow-up, AF prevalence increased from 1,6% (1,1% among women and 2,1% among men) at the age of 45-69 years to 4,2% (3,0% among women and 6,1% among men) aged 55-84 years according to screening rest ECG examinations. The prevalence of new AF cases over a 13-year followup in the cohort of 45-69 years old without previous CVD and AF was 5,6%, of which 40% were paroxysmal. The mean age at the time of first registered AF was 69±6,93 years, and was 2 years higher in women (70,0±6,83) than in men (68±6,93). The average period before the AF onset among people aged 45-69 years without baseline CVD and AF was 7,5±3,83 years for men and 8,1±4,02 years for women. The total prevalence of AF in the population sample was 8,3%. The highest AF prevalence was registered at the age of 65-69 years (11,4%) for men and 5 years later for women (12,0%) (p80 years decreased and amounted to 4,1% among men and 5,7% among women.

Conclusion. In the Russian population sample (Novosibirsk) aged 45-69, the AF prevalence increased from 1,6 to 8,3% over 13 years of follow-up. In addition, 473 new AF cases were identified, ~40% of which were paroxysmal AF. The prevalence of AF in the Siberian population sample for the 45-60 years age group is comparable with the large Russian and North American studies, but higher for persons aged 60-74 years and lower for older age group, for both men and women.
High normal blood pressure and left ventricular structural and functional disorders in young adults
Authors: Shavarova E. K. , Khomova I. A. , Kobalava Zh. D. , Kirpichnikova E. I. , Ezhova N. E. , Bazdyreva E. I.
Published: September 2022

Aim. To evaluate the association of a high normal blood pressure (BP) with the risk of early hypertension-mediated organ damage (HMOD) in young adults.

Material and methods. Medical screening of population aged 18-45 years (n=987) revealed that in 173 persons, office BP corresponded to a high normal level or hypertension (HTN). Echocardiography (GE Healthcare Vivid 9, using EchoPAC Software) was performed when HTN was confirmed by office BP measurement and/or according to 24-hour ambulatory BP monitoring (ABPM) (n=127). In addition, creatinine and albumin-to-creatinine ratio in spot urine were measured.

Results. The median age was 23 [21; 25] years. The median systolic (SBP) and diastolic BP (DBP) was 129 [121; 137] and 75±12 mm Hg, respectively. The detection rate of LV geometry abnormalities was 3,3 times higher in the high normal BP group [95% CI, 1,06-6,28, p=0,02], and 10,7 times higher in the HTN group [95% CI, 2,32-16,49, p=0,04] compared with the optimal+normal BP group. In a multivariate analysis, the independence of associations with the LV mass index (LVMI) was confirmed only for the mean nighttime DBP, left atrial volume index, and the ratio of LV peak early diastolic velocity to the average septal and lateral peak early diastolic mitral annular velocity.

Conclusion. In young people, the prevalance of HMOD is comparable in the groups with high normal BP and HTN, while significant differences were found between the group with optimal+normal BP levels and patients with HTN and high normal BP. An independent association of elevated LVMI with mean nighttime DBP was found.
The co-evolution of life and biogeochemical cycles in our planet
Authors: Martinelli Luiz Antonio , Augusto Fernanda Gaudio
Published: September 2022

Abstract The Earth has undergone numerous geological and biological changes over billions of years. The evolution of plants and animals had a direct relationship with the elements’ changes in the atmosphere and the development of the biogeochemical cycles on Earth. The Anthropocene is the age of the Homo sapiens leaves its geological signature on the planet. Human domination and/or interference in the biogeochemical cycles results in an environmental change that affects not only ecosystems, in general, but also the biota and global biodiversity. In this way, we are creating another mass extinction event, the “sixth extinction wave” as well as transforming the ecosystems’ functions and services.
Elaboração e Validação de Conteúdo de um instrumento sobre as atividades dos Agentes Comunitários de Saúde
Authors: Fernandes Tatiana Fróes , Pinho Lucinéia de , Brito Maria Fernanda Santos Figueiredo , Lima Clara Cynthia Melo e , Caldeira Antônio Prates
Published: September 2022

Resumo Objetivo elaborar e conduzir a validação de conteúdo e de aparência de um instrumento para identificação das atividades desempenhadas pelos agentes comunitários de saúde na Estratégia Saúde da Família. Método trata-se de um estudo metodológico composto por três etapas: a primeira foi a elaboração do instrumento a partir da revisão de literatura; a segunda foi constituída pela validação de conteúdo por 10 juízes experts; e a terceira pela validação aparente pela população-alvo. Para a análise, calculou-se o Índice de Validade de Conteúdo. Resultados inicialmente, o instrumento foi composto por 45 itens dispostos em 10 dimensões. Os especialistas analisaram e sugeriram a modificação de termos e o acréscimo e o desmembramento de itens. Todas as sugestões foram acolhidas e a versão final do instrumento foi composta por 60 itens. O Índice de Validade de Conteúdo foi ≥ 0,90 para todos os itens. O instrumento abrangeu as atividades preconizadas pelas normativas ministeriais e pelas atribuições que fogem do escopo de atuação, mas que estão presentes na prática dos profissionais. Conclusão e implicações para a prática o instrumento apresentou validade satisfatória e refletiu a realidade do trabalho dos agentes comunitários de saúde, sendo seus itens compostos pela ampla gama de atividades desenvolvidas por esses profissionais.
A Bottom-Up DAG Structure Extraction Model for Math Word Problems
Authors: Cao Yixuan , Hong Feng , Li Hongwei , Luo Ping
Published: September 2022

Research on automatically solving mathematical word problems (MWP) has a long history. Most recent works adopt Seq2Seq approach to predict the result equations as a sequence of quantities and operators. Although result equations can be written as a sequence, it is essentially a structure. More precisely, it is a Direct Acyclic Graph (DAG) whose leaf nodes are the quantities, and internal and root nodes are arithmetic or comparison operators. In this paper, we propose a novel Seq2DAG approach to extract the equation set directly as a DAG structure. It is extracted in a bottom-up fashion by aggregating quantities and sub-expressions layer by layer iteratively. The advantages of our approach approach are three-fold: it is intrinsically suitable to solve multivariate problems, it always outputs valid structure, and its computation satisfies commutative law for +, x and =. Experimental results on Math23K and DRAW1K demonstrate that our model outperforms state-of-the-art deep learning methods. We also conduct detailed analysis on the results to show the strengths and limitations of our approach.
Modeling the Momentum Spillover Effect for Stock Prediction via Attribute-Driven Graph Attention Networks
Authors: Cheng Rui , Li Qing
Published: September 2022

In finance, the momentum spillovers of listed firms is well acknowledged. Only few studies predicted the trend of one firm in terms of its relevant firms. A common strategy of the pilot work is to adopt graph convolution networks (GCNs) with some predefined firm relations. However, momentum spillovers are propagated via a variety of firm relations, of which the bridging importance varies with time. Restricting to several predefined relations inevitably makes noise and thus misleads stock predictions. In addition, traditional GCNs transfer and aggregate the peer influences without considering the states of both connected firms once a connection is built. Such non-attribute sensibility makes traditional GCNs inappropriate to deal with the attribute-sensitive momentum spillovers of listed firms wherein the abnormal price drop of one firm may not spill over if the trade volume of this decreasing price is small or the prices of the linked firms are undervalued. In this study, we propose an attribute-driven graph attention network (AD-GAT) to address both problems in modeling momentum spillovers. This is achieved by element-wisely multiplying the nonlinear transformation of the attributes of the connected firms with the attributes of the source firm to consider its attribute-sensitive momentum spillovers, and applying the unmasked attention mechanism to infer the general dynamic firm relation from observed market signals fused by a novel tensor-based feature extractor. Experiments on the three-year data of the S&P 500 demonstrate the superiority of the proposed framework over stateof-the-art algorithms, including GCN, eLSTM, and TGC.
Compound Word Transformer: Learning to Compose Full-Song Music over Dynamic Directed Hypergraphs
Authors: Hsiao Wen-Yi , Liu Jen-Yu , Yeh Yin-Cheng , Yang Yi-Hsuan
Published: September 2022

To apply neural sequence models such as the Transformers to music generation tasks, one has to represent a piece of music by a sequence of tokens drawn from a finite set of pre-defined vocabulary. Such a vocabulary usually involves tokens of various types. For example, to describe a musical note, one needs separate tokens to indicate the note’s pitch, duration, velocity (dynamics), and placement (onset time) along the time grid. While different types of tokens may possess different properties, existing models usually treat them equally, in the same way as modeling words in natural languages. In this paper, we present a conceptually different approach that explicitly takes into account the type of the tokens, such as note types and metric types. And, we propose a new Transformer decoder architecture that uses different feed-forward heads to model tokens of different types. With an expansion-compression trick, we convert a piece of music to a sequence of compound words by grouping neighboring tokens, greatly reducing the length of the token sequences. We show that the resulting model can be viewed as a learner over dynamic directed hypergraphs. And, we employ it to learn to compose expressive Pop piano music of full-song length (involving up to 10K individual tokens per song), both conditionally and unconditionally. Our experiment shows that, compared to state-of-the-art models, the proposed model converges 5 to 10 times faster at training (i.e., within a day on a single GPU with 11 GB memory), and with comparable quality in the generated music
Estimating Calibrated Individualized Survival Curves with Deep Learning
Authors: Kamran Fahad , Wiens Jenna
Published: September 2022

In survival analysis, deep learning approaches have been proposed for estimating an individual's probability of survival over some time horizon. Such approaches can capture complex non-linear relationships, without relying on restrictive assumptions regarding the relationship between an individual's characteristics and their underlying survival process. To date, however, these methods have focused primarily on optimizing discriminative performance and have ignored model calibration. Well-calibrated survival curves present realistic and meaningful probabilistic estimates of the true underlying survival process for an individual. However, due to the lack of ground-truth regarding the underlying stochastic process of survival for an individual, optimizing and measuring calibration in survival analysis is an inherently difficult task. In this work, we i) highlight the shortcomings of existing approaches in terms of calibration and ii) propose a new training scheme for optimizing deep survival analysis models that maximizes discriminative performance, subject to good calibration. Compared to state-of-the-art approaches across two publicly available datasets, our proposed training scheme leads to significant improvements in calibration, while maintaining good discriminative performance.
Predicting Livelihood Indicators from Community-Generated Street-Level Imagery
Authors: Lee Jihyeon , Grosz Dylan , Uzkent Burak , Zeng Sicheng , Burke Marshall , Lobell David , Ermon Stefano
Published: September 2022

Major decisions from governments and other large organizations rely on measurements of the populace's well-being, but making such measurements at a broad scale is expensive and thus infrequent in much of the developing world. We propose an inexpensive, scalable, and interpretable approach to predict key livelihood indicators from public crowd-sourced street-level imagery. Such imagery can be cheaply collected and more frequently updated compared to traditional surveying methods, while containing plausibly relevant information for a range of livelihood indicators. We propose two approaches to learn from the street-level imagery: (1) a method that creates multi-household cluster representations by detecting informative objects and (2) a graph-based approach that captures the relationships between images. By visualizing what features are important to a model and how they are used, we can help end-user organizations understand the models and offer an alternate approach for index estimation that uses cheaply obtained roadway features. By comparing our results against ground data collected in nationally-representative household surveys, we demonstrate the performance of our approach in accurately predicting indicators of poverty, population, and health and its scalability by testing in two different countries, India and Kenya. Our code is available at https://github.com/sustainlab-group/mapillarygcn.
MeInGame: Create a Game Character Face from a Single Portrait
Authors: Lin Jiangke , Yuan Yi , Zou Zhengxia
Published: September 2022

Many deep learning based 3D face reconstruction methods have been proposed recently, however, few of them have applications in games. Current game character customization systems either require players to manually adjust considerable face attributes to obtain the desired face, or have limited freedom of facial shape and texture. In this paper, we propose an automatic character face creation method that predicts both facial shape and texture from a single portrait, and it can be integrated into most existing 3D games. Although 3D Morphable Face Model (3DMM) based methods can restore accurate 3D faces from single images, the topology of 3DMM mesh is different from the meshes used in most games. To acquire fidelity texture, existing methods require a large amount of face texture data for training, while building such datasets is time-consuming and laborious. Besides, such a dataset collected under laboratory conditions may not generalized well to in-the-wild situations. To tackle these problems, we propose 1) a low-cost facial texture acquisition method, 2) a shape transfer algorithm that can transform the shape of a 3DMM mesh to games, and 3) a new pipeline for training 3D game face reconstruction networks. The proposed method not only can produce detailed and vivid game characters similar to the input portrait, but can also eliminate the influence of lighting and occlusions. Experiments show that our method outperforms state-of-the-art methods used in games. Code and dataset are available at https://github.com/FuxiCV/MeInGame.
DeepPseudo: Pseudo Value Based Deep Learning Models for Competing Risk Analysis
Authors: Rahman Md Mahmudur , Matsuo Koji , Matsuzaki Shinya , Purushotham Sanjay
Published: September 2022

Competing Risk Analysis (CRA) aims at the correct estimation of the marginal probability of occurrence of an event in the presence of competing events. Many of the statistical approaches developed for CRA are limited by strong assumptions about the underlying stochastic processes. To overcome these issues and to handle censoring, machine learning approaches for CRA have designed specialized cost functions. However, these approaches are not generalizable, and are computationally expensive. This paper formulates CRA as a cause-specific regression problem and proposes DeepPseudo models, which use simple and effective feed-forward deep neural networks, to predict the cumulative incidence function (CIF) using Aalen-Johansen estimator-based pseudo values. DeepPseudo models capture the time-varying covariate effect on CIF while handling the censored observations. We show how DeepPseudo models can address co-variate dependent censoring by using modified pseudo values. Experiments on real and synthetic datasets demonstrate that our proposed models obtain promising and statistically significant results compared to the state-of-the-art CRA approaches. Furthermore, we show that explainable methods such as Layer-wise Relevance Propagation can be used to interpret the predictions of our DeepPseudo models.
Sketch Generation with Drawing Process Guided by Vector Flow and Grayscale
Authors: Tong Zhengyan , Chen Xuanhong , Ni Bingbing , Wang Xiaohang
Published: September 2022

We propose a novel image-to-pencil translation method that could not only generate high-quality pencil sketches but also offer the drawing process. Existing pencil sketch algorithms are based on texture rendering rather than the direct imitation of strokes, making them unable to show the drawing process but only a final result. To address this challenge, we first establish a pencil stroke imitation mechanism. Next, we develop a framework with three branches to guide stroke drawing: the first branch guides the direction of the strokes, the second branch determines the shade of the strokes, and the third branch enhances the details further. Under this framework's guidance, we can produce a pencil sketch by drawing one stroke every time. Our method is fully interpretable. Comparison with existing pencil drawing algorithms shows that our method is superior to others in terms of texture quality, style, and user evaluation. Our code and supplementary material are now available at: https://github.com/TZYSJTU/Sketch-Generation-withDrawing-Process-Guided-by-Vector-Flow-and-Grayscale
Commission Fee is not Enough: A Hierarchical Reinforced Framework for Portfolio Management
Authors: Wang Rundong , Wei Hongxin , An Bo , Feng Zhouyan , Yao Jun
Published: September 2022

Portfolio management via reinforcement learning is at the forefront of fintech research, which explores how to optimally reallocate a fund into different financial assets over the long term by trial-and-error. Existing methods are impractical since they usually assume each reallocation can be finished immediately and thus ignoring the price slippage as part of the trading cost. To address these issues, we propose a hierarchical reinforced stock trading system for portfolio management (HRPM). Concretely, we decompose the trading process into a hierarchy of portfolio management over trade execution and train the corresponding policies. The high-level policy gives portfolio weights at a lower frequency to maximize the long-term profit and invokes the low-level policy to sell or buy the corresponding shares within a short time window at a higher frequency to minimize the trading cost. We train two levels of policies via a pre-training scheme and an iterative training scheme for data efficiency. Extensive experimental results in the U.S. market and the China market demonstrate that HRPM achieves significant improvement against many state-of-the-art approaches.
Towards a Better Understanding of VR Sickness: Physical Symptom Prediction for VR Contents
Authors: Kim Hak Gu , Lee Sangmin , Kim Seongyeop , Lim Heoun-taek , Ro Yong Man
Published: September 2022

We address the black-box issue of VR sickness assessment (VRSA) by evaluating the level of physical symptoms of VR sickness. For the VR contents inducing the similar VR sickness level, the physical symptoms can vary depending on the characteristics of the contents. Most of existing VRSA methods focused on assessing the overall VR sickness score. To make better understanding of VR sickness, it is required to predict and provide the level of major symptoms of VR sickness rather than overall degree of VR sickness. In this paper, we predict the degrees of main physical symptoms affecting the overall degree of VR sickness, which are disorientation, nausea, and oculomotor. In addition, we introduce a new large-scale dataset for VRSA including 360 videos with various frame rates, physiological signals, and subjective scores. On VRSA benchmark and our newly collected dataset, our approach shows a potential to not only achieve the highest correlation with subjective scores, but also to better understand which symptoms are the main causes of VR sickness.
Learning Graph Neural Networks with Approximate Gradient Descent
Authors: Li Qunwei , Zou Shaofeng , Zhong Wenliang
Published: September 2022

The first provably efficient algorithm for learning graph neural networks (GNNs) with one hidden layer for node information convolution is provided in this paper. Two types of GNNs are investigated, depending on whether labels are attached to nodes or graphs. A comprehensive framework for designing and analyzing convergence of GNN training algorithms is developed. The algorithm proposed is applicable to a wide range of activation functions including ReLU, Leaky ReLU, Sigmod, Softplus and Swish. It is shown that the proposed algorithm guarantees a linear convergence rate to the underlying true parameters of GNNs. For both types of GNNs, sample complexity in terms of the number of nodes or the number of graphs is characterized. The impact of feature dimension and GNN structure on the convergence rate is also theoretically characterized. Numerical experiments are further provided to validate our theoretical analysis.
Hierarchical Multiple Kernel Clustering
Authors: Liu Jiyuan , Liu Xinwang , Wang Siwei , Zhou Sihang , Yang Yuexiang
Published: September 2022

Current multiple kernel clustering algorithms compute a partition with the consensus kernel or graph learned from the pre-specified ones, while the emerging late fusion methods firstly construct multiple partitions from each kernel separately, and then obtain a consensus one with them. However, both of them directly distill the clustering information from kernels or graphs to partition matrices, where the sudden dimension drop would result in loss of advantageous details for clustering. In this paper, we provide a brief insight of the aforementioned issue and propose a hierarchical approach to perform clustering while preserving advantageous details maximumly. Specifically, we gradually group samples into fewer clusters, together with generating a sequence of intermediary matrices of descending sizes. The consensus partition with is simultaneously learned and conversely guides the construction of intermediary matrices. Nevertheless, this cyclic process is modeled into an unified objective and an alternative algorithm is designed to solve it. In addition, the proposed method is validated and compared with other representative multiple kernel clustering algorithms on benchmark datasets, demonstrating state-of-the-art performance by a large margin.