bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamics of Ethnocontact Zones in the Turkic Republics of the Ural-Volga Region in the Post-Soviet Period
Authors: Manakov Andrei G. , Terenina Natalia K. , Ivanov Ivan A.
Published: March 2024

Introduction. The interest of world science in assessing the ethnic diversity of countries and regions predetermines the development of the concept of ethnocontact zones. To test new methods within the framework of the concept, there is a need to conduct research not only at the regional, but also at the intraregional levels. The purpose of the study is to classify the municipalities of Chuvashia, Tatarstan and Bashkortostan according to ethnic dynamics in the post-Soviet period using the methodology developed by the authors in accordance with the concept of ethno-contact zones.

Materials and Methods. The empirical basis of the study is ethnic statistics at the level of municipalities of the republics based on the results of the population censuses of 1989, 2002 and 2010. The authorsʼ method of identifying the phases of development of ethnocontact zones, which was first applied at the municipal level, is presented.

Results. The general trend of ethnic processes in the last decade of the 20th century was the titularization of the population of the republics (with the exception of Chuvashia), and in the first decade of the 21st century – detitularisation of the population (except for Tatarstan). The processes of titularisation and detitularisation at the level of municipalities are determined both by the general trend in the change in the share of the titular population of the republics, and by ethnogeographic features associated with the different proportion of titular peoples in municipalities, which is largely due to their central, semi-peripheral or peripheral position within the republics.

Discussion and Conclusion. The spatial patterns of ethnic dynamics revealed in the course of the study, corresponding to certain phases of development of ethnocontact zones, make it possible to forecast ethnic processes at the intraregional level. However, such a forecast is possible only if the general trend of ethnic processes at the level of national formations is known. For this reason, the new task in the course of developing the concept of ethnocontact zones was to study the dynamics of ethnocontact zones on a regional scale over a long time interval, which will allow us to proceed to predicting the development of these ethnocontact zones in the medium and long term.
THE „GLASS INITIAL“ PROJECT STEAM WORKSHOPS
Authors: Chehlarova Koya , Chehlarova Neda
Published: March 2024

Some results of creative workshops held with students, teachers, parents, art lovers on the "Glass Initial" project are presented. The aim of Glass Initial project is to popularize two techniques of glass material and silk painting technique among art lovers and attract new members of amateur art.
SUSTAINABLE URBAN DEVELOPMENT - THE 20 YEARS OF THE 21ST CENTURY - OPPORTUNITIES AND CHALLENGES
Authors: Gaydardzhieva V.
Published: March 2024

Well-developed cities give people the opportunity for socio-economic progress as well as security in crisis situations. In the conditions of ecological, energy and pandemic crisis, the challenges of developing sustainable public relations during an unsustainable environment in large urban centers stand out even more strongly. A change in the priorities that municipalities follow is necessary. They should focus on the quality of life, safety and health of the residents, but with the use of smart technologies adequate to modern achievements. The facts accompanying urbanization are a serious argument for the search for long-term solutions for a sustainable urban living environment, especially in large cities. The purpose of the research is to emphasize the main policies and challenges affecting the quality of life in cities, as well as the opportunities for their improvement through smart technologies. City management should be transformed into an integrated management of the social, economic and environmental aspects of city life. Activities in the municipality can be understood as a partnership between politicians, administration, business and interested citizens. Integration can also be aimed in partnership with other cities in the country and in Europe. Sustainable financing oriented to long-term projects that contribute to overall economic development in a given area or region is needed.
Polyphenolic compounds in the combat of foodborne infections – An update on recent evidence
Authors: Menikheim Carolin B. , Mousavi Soraya , Bereswill Stefan , Heimesaat Markus M.
Published: March 2024

In recent years, the incidence of food-borne bacterial enteric diseases has increased worldwide causing significant health care and socioeconomic burdens. According to the World Health Organization, there are an estimated 600 million cases of foodborne illnesses worldwide each year, resulting in 420,000 deaths. Despite intensive efforts to tackle this problem, foodborne pathogenic microorganisms continue to be spread further. Therefore, there is an urgent need to find novel anti-microbial non-toxic compounds for food preservation. One way to tackle this issue may be the usage of polyphenols, which have received increasing attention in the recent years given their pleotropic health-promoting properties. This prompted us to perform a literature search summarizing studies from the past 10 years regarding the potential anti-microbial and disease-alleviating effects of plant-derived phenolic compounds against foodborne bacterial pathogens. The included 16 studies provide evidence that polyphenols show pronounced anti-bacterial and anti-oxidant effects against both Gram-positive and Gram-negative bacterial species. In addition, synergistic anti-microbial effects in combination with synthetic antibiotics were observed. In conclusion, phenolic compounds may be useful as natural anti-microbial agents in the food, agricultural, and pharmaceutical industries in the combat of foodborne infections.
Evaluation of heat-induced changes and 5-hydroxymethylfurfural formation in mare milk - a comparative study to cow milk
Authors:   University of Zagreb, Faculty of Food Technology and Biotechnology, Pierottijeva 6, 10000 Zagreb, Croatia, Barukčić Jurina Irena
Published: March 2024

Mare milk is known for therapeutic properties due to the presence of bioactive components that are sensitive to thermal treatments and tend to lose their activity. Accordingly, mare milk is consumed raw or frozen, but for food safety reasons recent studies suggest mandatory pasteurization of mare milk before consumption. The aim of this study was to examine the effects of different heat treatments on mare milk quality and compare those to heat induced changes in cow milk. In all milk samples, the total dissolved solids (TDS), electrical conductivity (EC), antioxidant capacity (AC) by the DPPH and FRAP methods, changes in colour (ΔE*), concentration of 5-hydroxymethylfurfural (HMF) and the total phenols (TPC) were determined. Heat induced protein denaturation was monitored by SDS-PAGE, while NIR was applied for qualitative analysis of structural changes. In-bottle sterilization at 116 °C/16ʹ and 120 °C/5ʹ showed to be inappropriate for mare milk processing, since they resulted in the most intense colour changes (ΔE*>5), the highest free and total HMF concentrations (40.70 μmol/L free, 70.26 μmol/L total HMF at 116 °C/16ʹ; 35.49 μmol/L free, 58.12 μmol/L total HMF at 120 °C/5ʹ) and the most intense protein denaturation. On contrary, the applied HTST regimes (72 °C/20”, 85 °C/30”, 90 °C/5ʹ) and thermisation at 63 °C/15” were appropriate for mare milk processing considering the studied qualitative changes. Thereby, the HMF concentration, FRAP, TPC and ΔE* value, combined with NIR analysis showed a good potential to be used as rapid and useful tools for monitoring the intensity of heat induced changes in mare milk.
Effect of dietary cold-pressed hempseed cake on the fatty acid profile of semi-hard cheese made from goat milk
Authors:   Josip Juraj Strossmayer University of Osijek, Faculty of Agrobiotechnical Sciences Osijek, Department for Animal Production and Biotechnology, V. Preloga 1, 31000 Osijek, Croatia, Klir Šalavardić Željka
Published: March 2024

Recently, many feedstuffs have been introduced to animal diets to increase the content of beneficial fatty acids in dairy products. Therefore, this study aimed to research the effect of including hempseed cake in dairy goats concentrate mixtures on the chemical composition and fatty acid profile of semi-hard goat cheese that is traditionally produced on family farm. The feeding of goats was based on meadow hay ad libitum and 1200 g/day/head of concentrate mixture. In the first experimental group, 60 g/kg DM of hempseed cake (HSC-60) was administered; meanwhile, in the second experimental group, 120 g/kg DM of hempseed cake (HSC-120) was included in the diet. The chemical composition of cheese was mostly unaffected by enriching the goats’ nutrition with hempseed cakes. Dietary HSC-120 increased C18:1 n-9 and C18:3 n-6 compared to the control, and increased C22:6 n-3 in cheese compared to HSC- 60, although both HSC-120 and HSC-60 lowered n-6/n-3 ratios in cheese. Feeding goats with HSC-120 may have contributed to the development of the functional properties of semi-hard goat cheese made on family farm, as compared to the cheese produced by goats fed with commercial concentrate mixtures.
Exploration and Identification of Ectomycorrhizal Fungi at IPB University Campus Forest
Authors: Adawiah Adilah , Mufidah Dinda Rista , Putra Ivan Permana
Published: March 2024

The exploration of ectomycorrhizal fungi diversity around the campus could provide insights into the presence and distribution of these symbiotic fungi in the area. This study aimed to observe, identify, and provide information regarding ectomycorrhizal fungi diversity in the IPB University Campus Forest. The sampling sites represent various tree species including forests, parks, and green spaces. The exploration was done using opportunistic sampling method. The obtained basidiomata were examined for macromorphological and micromorphological examination to identify the ectomycorrhizal fungi. The identification results based on the morphological characteristics confirmed our specimens as Inocybe cf. squarrosolutea (Corner & E. Horak) Garrido and Suillus bovinus (L.) Roussel. The Inocybe was characterized by having small to medium-sized, pileus squamules, dry surface, light brown to yellowish cap, lamellae crowded, cylindrical or attenuated stipe towards the apex, clavate basidia, and hemispheric knobs basidiospores. The Suillus was distinguished by having a cap that is convex in shape with a slightly brownish yellow color and the surface texture of the cap is smooth, lamella in the form of pores that are quite large and angular, brownish yellow in color, yellow tubular stipe, clavate basidia, and oval spores. These two macrofungi are new records in the sampling area and I. cf. squarrosolutea could be the new information for Indonesia. Our finding provides valuable information for ecological studies and contributes to the additional data on Indonesian ectomycorrhizal fungi diversity.
Phenolic Content and Antioxidant Activity Water and Ethanol Extracts of Sungkai Leaves (Peronema canescens Jack)
Authors: Maretha Delima Engga , Yani Dwi Fitri , Silvana Lili , Masri Mashuri
Published: March 2024

Sungkai (Peronema canescens Jack) is a plant that has phenolic content as an antioxidant that can enhance the immune system (immunomodulator). This study aimed to determine the phenolic content and antioxidant activity of Sungkai leaves (Peronema canescens Jack). The method  of antioxidant with invitro using of the DPPH where the ability of a compound to inhibit DPPH radicals is calculated from the absorbance value using UV-Vis spectroscopy. And Determination of total phenolic content was carried out using UV VIS spectroscopy at a wavelength of 745 nm with the help of Folin Ciocalteu reagentand a nd gallic acid standard curve . The test results showed that the water and ethanol extracts with a concentration of 0.1% had a phenolic content of 0.002% and 0.007%, their antioxidant activity (IC50) with a concentration of 0.02; 0.04; 0.06; 0.08; and 0.1% in the water and ethanol extracts of Sungkai leaves have values of 0.025% and 0.03% respectively. Therefore the best antioxidant activity (IC50) was extracts ethanol of sungkai leaves with phenolic content  of 0.007% and IC50  of 0.03%.
Detection of Plantaricin-Encoding Gene and Its Partial Purification in Lactobacillus plantarum BP102
Authors: Suryani Elsa Mega , Jatmiko Yoga Dwi , Mustafa Irfan
Published: March 2024

Lactobacillus plantarum BP102 isolated from garlic bulb tissue has probiotic properties, including producing bacteriocin called plantaricin. This study aimed to detect the gene encoding bacteriocin produced by Lactobacillus plantarum BP102, and to evaluate the bacteriocin activity at each stage of partial purification. After the end of the log phase of L. plantarum BP102 was determined, and the bacteriocin-encoding genes were checked by PCR technique. Partial purification of bacteriocin was elucidated including pH-neutralized cell-free-supernatant (CFS), precipitation using 80% of ammonium sulfate, and dialysis (cut-off 10 kDa), then the bacteriocin activity in every partial purification stage was evaluated. The molecular weight of plantaricin was estimated using SDS-PAGE analysis. Lactobacillus plantarum BP102 harbored the gene encoding plantaricin (pln) biosynthesis, namely plnEF and plnK genes. The activity of crude bacteriocin was inactivated by the presence of proteinase-K enzyme. The protein concentration was gradually decreased along with the purification process. The bacteriocin activity was demonstrated at each step of the purification process (CFS, precipitation, and dialysis) against Bacillus cereus by 9.23 ± 0.20 mm, 7.86 ± 0.15 mm, and 7.6 ± 0.10 mm, respectively; while, Escherichia coli by 10.3 ± 0.55 mm, 7.4 ± 0.1 mm, and 6.86 ± 0.45, respectively. The molecular weight of partially purified bacteriocin BP102 was found to be approximately 15.9 kDa. The overlaid part of the gel showed a slight inhibition against E. coli due to a low protein concentration. This bacteriocin purification process should be further optimized to improve the bacteriocin activity that could be useful for food preservation.
The dispersing of the Lubomirski Collection from Przeworsk
Authors: Wolska Agata
Published: March 2024

This article concerns the post-war fate of elements of historical furnishings of the Lubomirski family palace in Przeworsk owned by successive Tenants-in-Possession, who were also literary curators of the Ossolineum. The ownership structure of the collections stored in the palace and outbuildings was uneven. Some items belonged to the Przeworsk Entailed Estate, and some were personal property of Andrzej Lubomirski. A significant share belonged to his wife, Eleonora née Hussarzewska and originated from her family’s collection, and from a donation her husband made in 1932. The outbreak of the Second World War initiated the process of dispersing items that had survived in the Przeworsk residence of the Lubomirski family until the autumn of 1939. After the looting perpetrated by the Nazis, land reform proved equally painful in its consequences. As a result, the so-called Museum Storehouse was set up in the Lubomirski residence in Przeworsk to house its nationalised equipment. It was a temporary repository for the remaining elements of the Tenants-in-Possession and family collection in Przeworsk. The decision by the communist central authorities led to the dispersion of the most valuable items, distributed among museums in Warsaw (antiquities), Łańcut (paintings, graphics, furniture and artistic craftsmanship) and Rzeszów (jewellery for the Polish costume). The pieces considered useful were left in place. This text, along with its accompanying tables, represents an attempt to wrap up the existing knowledge regarding the post-war fate of the items that remained in the Przeworsk Palace until 1944 and can serve as a starting point for further detailed investigations. This text could also serve as a starting point for deeper reflection on the political and administrative mechanisms of dispersal of the land owners’ and aristocrats’ collections and the establishment of new museum collections after the Second World War.
Symbioautothanatosis: Science as Symbiont in the Work of Lynn Margulis
Authors: Basile Jonathan
Published: March 2024

Lynn Margulis’s writing about symbiosis has profoundly influenced contemporary evolutionary theory, as well as continental and analytic philosophy of science, the materialist turn, and new materialism. Nonetheless, her work, and all symbiosis or evolution, is founded on a paradox: symbiosis fictionalizes customary accounts of the origin and evolution of species, yet it is impossible to speak of symbiosis (cross-species association) unless species-boundaries have been posited in advance. Thus, a tension is legible throughout Margulis’s work between the drive to surpass the limits of species-definitions as they have been traditionally understood, and a need to maintain them in order that there can be “symbiosis” at all. Margulis criticized neo-Darwinian accounts of evolution in part because she saw symbiogenesis as debunking the theory that life was defined by individualistic competition. More recently, Myra Hird has suggested that the gift, such as it has been theorized by certain anthropologists and philosophers, could adequately figure symbiosis and the ethical relations founded on it. I turn to Derrida’s writing on the gift to suggest that, if a gift worthy of the name chances to happen, it necessarily exceeds scientific, theoretical, and philosophical knowledge.
Du rien-pour-nous que la mort: Derrida Épicure
Authors: Lezra Jacques
Published: March 2024

Le séminaire “La vie la mort” de Derrida opère, comme d’avance motivé par ses suites et comme contresigné par ce nom qui n’apparaît pas—le nom d’Épicure—un virage vers un matérialisme non productif, non représentationnel, dépourvu en quelque sorte de statut ontologique, voire non ontologisable, triomphant, normatif, voué à une économie de la cause. Nietzsche, lecteur antagonique d’Épicure (Lettre à Ménécée: “Accoutume-toi à considérer que la mort n'est rien pour nous”)—constitue son écran-substitut. Nietzsche, dont la lecture sert à fermer-ouvrir les grandes boucles du séminaire de Derrida. Il s’agit donc de fouiller “La vie la mort” à la recherche des traces de la rencontre Nietzsche-Épicure—une rencontre définitive, elle, bien qu’invisible et silencieuse, bien que presqu’illisible dans le texte de Derrida, au sujet du rapport “la vie la mort.”
Assessment of prostate tissue remodeling in rats exposed to bisphenol A and the phytoestrogens genistein and indole-3-carbinol during the perinatal period
Authors: Bueno Éricka Stéphanny Brandão , Vieira Neto Carlos Domingos , Rodrigues Alessandro , Sousa Thaina Cavalleri , Hinokuma Karianne Delalibera , Aquino Ariana Musa de , Scarano Wellerson Rodrigo , Brandt Joyce Zalotti , Mendes Leonardo de Oliveira
Published: March 2024

ABSTRACT: Bisphenol A (BPA) is a compound known for its direct action on the prostate. Prostatic morphogenesis is a critical period when interference by any compound could permanently damage the organ. As such, the present study evaluated the morphological aspects resulting from gestational and lactational administration of BPA, indole-3-carbinol (I3C) and genistein (GEN) in prepubescent male rats. Pregnant Sprague Dawley females were allocated into 4 experimental groups and received the following: C: Control (no treatment); B: BPA (10 µg/Kg); BG: BPA+GEN (5 mg/Kg); BI: BPA+I3C (20 mg/Kg) from gestation day (GD) 17 to postnatal day (PND) 21. After euthanasia on PND22, the prostate was collected and processed. When administered alone, BPA reduced the stromal compartment when compared to group C (P = 0.039). This decline was reversed in the groups submitted to GEN (P = 0.019) or I3C (P = 0.017). The groups treated with BPA (P < 0.0001) and the phytoestrogens (P < 0.0001) exhibited decreased epithelial height in relation to the control group. These changes were observed in stereological and morphometric analyses, but not in fractal analysis (P = 0.569). The area occupied by collagen increased in groups treated with BPA (P < 0.0001) and phytoestrogens (P < 0.0001) in relation to controls, while collagen distribution values were higher in all the treated groups (P < 0.0001), according to fractal analysis. Thus, BPA induced prostrate stroma remodeling with no influence from the phytoestrogens, which may affect glandular development and cause histopathological changes in adulthood.
Feasibility of replacing the viral isolation technique in mice with RT-qPCR for the diagnosis of rabies
Authors: Marinho Karina Miranda , Magalhães Júnior Cássio Alexandre Costa , Amorim Júnior Lúcio André , Vianna Lucas Alves , Tobias Fernando Luiz , Langoni Hélio , Braga Fabio Ribeiro , Rossi Gabriel Augusto Marques , Vieira Luiz Fernando Pereira
Published: March 2024

ABSTRACT: Rabies is a viral encephalitis that affects mammals, including humans. Rapid and effective laboratory diagnosis of the rabies virus is critical for public health. This study evaluated the operational, technical, and financial viability of the RT-qPCR in replacement of inoculation in mice for diagnosing rabies in the laboratory routine. A total of 316 samples of mammalian brains were analyzed, 121 positives and 195 negatives, previously diagnosed by direct immunofluorescence (DIF) and mouse inoculation test (MIT). The samples were submitted to the duplex TaqMan RT-qPCR technique. The accuracy, sensitivity, and specificity of RT-qPCR were analyzed. We analyzed the costs for performing the RT-qPCR technique and compared it with the cost of MIT. The results showed 99.37% accuracy, 99.17% sensitivity, and 99.49% specificity by RT-qPCR when related to DIF and MIT results, which proved to be a robust and repeatable technique. The minimum time for a positive diagnosis was reduced in RT-qPCR (1 day) if compared to MIT (9.64 days), with a 17.7% reduction in the cost of the molecular technique. The present study demonstrated that the molecular biology technique is an efficient tool to diagnose rabies in the laboratory routine, being able to replace MIT.
Confinement and semi confinement of lambs in an integrated production system: impacts on production performance, infection by gastrointestinal nematodes, and selected blood analytes
Authors: Schmidt Elizabeth Moreira dos Santos , Fachiolli Daniele Floriano , Meirelles Paulo Roberto de Lima , Soutello Ricardo Velludo Gomes de , Pariz Cristiano Magalhães , Castilhos André Michel de , Amarante Alessandro Francisco Talamini do , Almeida Fabiana Alves de , Souza Daniel Martins de , Barros Juliana da Silva , Costa Ciniro
Published: March 2024

ABSTRACT: This trial evaluated the production performance, gastrointestinal nematode infection (GIN), and selected blood analytes, in Corriedale lambs during the finishing phase in an integrated crop-livestock system (ICLS) with 2 stocking rates. Fifty-two Corriedale lambs were divided into 4 groups: a semi confinement system with a low stocking rate (T1) for 70 days; a semi confinement system with a high stocking rate (T2) for 70 days; confinement for 28 days, followed by semi confinement with a low stocking rate (T3) for 42 days; and confinement for 28 days, followed by semi confinement with a high stocking rate (T4) for 42 days. Body weight, dry matter intake, blood collection, and faecal analysis of nematode eggs were performed for each animal. The stocking rates did not influence body weight gain for the semiconfined lambs (T1 and T2) or for the confined/semiconfined lambs (T3 and T4). All treatments had lower EPG counts at the end of the experimental period. The nematode genera identified during the experiment trial were Haemonchus and Trichostrongylus. There were no significant differences (P > 0.05) for packed cell volume, total plasma protein, and eosinophil means between treatments. These results suggested that the confinement followed by semi confinement in an ICLS, was an option for lamb production during the finishing phase which could be useful in reducing GIN without affecting the production performance.
Caracterização da bacia leiteira do município de Juína – MT, Brasil
Authors: Rocha Josemir Paiva , Silva João dos Santos Vila da
Published: March 2024

Resumo Este estudo foi realizado na bacia leiteira do município de Juína, Mato Grosso, Brasil, com área aproximada de 300 mil ha, 216 produtores que, segundo dados do Instituto Brasileiro de Geografia e Estatística – IBGE, produziu 10,5 milhões de litros de leite, em 2019. O objetivo é regionalizar e caracterizar esta bacia leiteira. Para tanto, 60 produtores foram entrevistados com aplicação de questionário. Os dados coletados foram compilados e organizados em gráficos, textos e mapas produzidos no software QGIS. A análise desses dados permitiu regionalizar a bacia em seis Zonas Produtivas, apoiada na aglutinação pretérita dos produtores. Evidenciou-se as disparidades entre essas zonas, tanto no que tange à produção, quanto no que diz respeito aos índices de produtividade. Diante do aspecto de maior preocupação levantado identificou-se: baixa produtividade, fruto de um quadro que envolve a precária situação das pastagens; falta de suplementação alimentar; baixo padrão genético do rebanho; e principalmente, falta de assistência técnica. Faz-se necessária intervenção das agências de fomento públicas e privadas a esse tipo de atividade de forma urgente e efetiva. Assim, esta pesquisa poderá subsidiar intervenções e apoiar o desenvolvimento e sustentabilidade da bacia leiteira, servindo como arcabouço científico à tomada de decisões.
Cassava flour production, COVID-19 and Food Security: the repercussions for family farmers in the Recôncavo Baiano Region
Authors: Duarte Bianca Ferreira , Pena Lara Conceição Campos , Braga Tereza Cristina Vieira , Cardoso Ryzia de Cássia Vieira
Published: March 2024

Abstract The pandemic generated one of the biggest crises in the world, with a reduction in the population's purchasing power and difficulties in accessing food. In this context, this study aimed to analyze the conditions of flour production and its relation with the food security of family farmers in the cassava chain, in the Recôncavo Baiano Region, during the COVID-19 pandemic. A cross-sectional study was carried out, with data collection using a questionnaire and treatment using descriptive statistics and association tests. Of the total number of participants (n=86), 64% indicated changes in flour production volume and income. There was a reduction in monthly production, in the number of workers and hours worked in the flour houses, in addition to a reduction in the diversity of buyers. The increase in income from flour was associated with small number of more experienced producers (p=0.047). Despite the maintenance of fairs in the cities studied, there were changes in customer behavior. Online commerce and delivery were not very representative. Of those interviewed, 50% reported concern that food would run out. Government measures to support family farmers did not have a satisfactory reach among the participants. Most received emergency aid, and were also beneficiaries of social programs, which highlights vulnerabilities in the sector.
Hemodiafiltration: a synergy yet to be convincing
Authors: Thangarajah Brammah Rajarajeswaran
Published: March 2024

ABSTRACT The desperate attempt to improve mortality, morbidity, quality of life and patient-reported outcomes in patients on hemodialysis has led to multiple attempts to improve the different modes, frequencies, and durations of dialysis sessions in the last few decades. Nothing has been more appealing than the combination of diffusion and convection in the form of hemodiafiltration. Despite the concrete evidence of better clearance of middle weight molecules and better hemodynamic stability, tangible evidence to support the universal adoption is still at a distance. Survival benefits seen in selected groups who are likely to tolerate hemodiafiltration with better vascular access and with lower comorbid burden, need to be extended to real life dialysis patients who are older than the population studied and have significantly higher comorbid burden. Technical demands of initiation hemodiafiltration, the associated costs, and the incremental benefits targeted, along with patient-reported outcomes, need to be explored further before recommending hemodiafiltration as the mode of choice.
The Action of Centripetal and Centrifugal Forces in Religious Discourse about People with Disabilities: Reflections Based on Bakhtin and the Circle
Authors: Costa Dennis Souza da , Teixeira Ivana Siqueira
Published: March 2024

ABSTRACT This article analyzes the action of centripetal and centrifugal forces in utterances from the religious sphere, which reveal worldviews of the evangelical Christian segment regarding disability. For that, we selected a video available on YouTube, containing utterances by the hosts Tito Rocha and Leandro Quadros regarding disabilities, as well as the response of an internet user about the positioning of these individuals. The theoretical and methodological reflection is based on the dialogical orientation of language, considering dialogic relations, voices, and centripetal and centrifugal forces. Additionally, we drew upon studies on worldviews, the inclusion of people with disabilities, religious discourse, and Christian theology. The results reveal that the discourses of the hosts reflect and refract a Christian worldview that unifies the understanding of disability due to divine punishment caused by sin. While the internet user’s comment presents movements of centralization and dispersion of this Christian perspective.
Scale Optimization Using Evolutionary Reinforcement Learning for Object Detection on Drone Imagery
Authors: Zhang Jialu , Yang Xiaoying , He Wentao , Ren Jianfeng , Zhang Qian , Zhao Yitian , Bai Ruibin , He Xiangjian , Liu Jiang
Published: March 2024

Object detection in aerial imagery presents a significant challenge due to large scale variations among objects. This paper proposes an evolutionary reinforcement learning agent, integrated within a coarse-to-fine object detection framework, to optimize the scale for more effective detection of objects in such images. Specifically, a set of patches potentially containing objects are first generated. A set of rewards measuring the localization accuracy, the accuracy of predicted labels, and the scale consistency among nearby patches are designed in the agent to guide the scale optimization. The proposed scale-consistency reward ensures similar scales for neighboring objects of the same category. Furthermore, a spatial-semantic attention mechanism is designed to exploit the spatial semantic relations between patches. The agent employs the proximal policy optimization strategy in conjunction with the evolutionary strategy, effectively utilizing both the current patch status and historical experience embedded in the agent. The proposed model is compared with state-of-the-art methods on two benchmark datasets for object detection on drone imagery. It significantly outperforms all the compared methods. Code is available at https://github.com/UNNC-CV/EvOD/.
Operationalizing Essential Characteristics of Creativity in a Computational System for Music Composition
Authors: Bodily Paul M. , Ventura Dan
Published: March 2024

We address the problem of building and evaluating a computational system whose primary objective is creativity. We illustrate seven characteristics for computational creativity in the context of a system that autonomously composes Western lyrical music. We conduct an external evaluation of the system in which respondents rated the system with regard to each characteristic as well as with regard to overall creativity. Average scores for overall creativity exceeded the ratings for any single characteristic, suggesting that creativity may be an emergent property and that unique research opportunities exist for building CC systems whose design attempts to comprehend all known characteristics of creativity.
Bootstrapping Cognitive Agents with a Large Language Model
Authors: Zhu Feiyu , Simmons Reid
Published: March 2024

Large language models contain noisy general knowledge of the world, yet are hard to train or fine-tune. In contrast cognitive architectures have excellent interpretability and are flexible to update but require a lot of manual work to instantiate. In this work, we combine the best of both worlds: bootstrapping a cognitive-based model with the noisy knowledge encoded in large language models. Through an embodied agent doing kitchen tasks, we show that our proposed framework yields better efficiency compared to an agent entirely based on large language models. Our experiments also indicate that the cognitive agent bootstrapped using this framework can generalize to novel environments and be scaled to complex tasks.
Data Augmented Graph Neural Networks for Personality Detection
Authors: Zhu Yangfu , Xia Yue , Li Meiling , Zhang Tingting , Wu Bin
Published: March 2024

Personality detection is a fundamental task for user psychology research. One of the biggest challenges in personality detection lies in the quantitative limitation of labeled data collected by completing the personality questionnaire, which is very time-consuming and labor-intensive. Most of the existing works are mainly devoted to learning the rich representations of posts based on labeled data. However, they still suffer from the inherent weakness of the amount limitation of labels, which potentially restricts the capability of the model to deal with unseen data. In this paper, we construct a heterogeneous personality graph for each labeled and unlabeled user and develop a novel psycholinguistic augmented graph neural network to detect personality in a semi-supervised manner, namely Semi-PerGCN. Specifically, our model first explores a supervised Personality Graph Neural Network (PGNN) to refine labeled user representation on the heterogeneous graph. For the remaining massive unlabeled users, we utilize the empirical psychological knowledge of the Linguistic Inquiry and Word Count (LIWC) lexicon for multi-view graph augmentation and perform unsupervised graph consistent constraints on the parameters shared PGNN. During the learning process of finite labeled users, noise-invariant learning on a large scale of unlabeled users is combined to enhance the generalization ability. Extensive experiments on three real-world datasets, Youtube, PAN2015, and MyPersonality demonstrate the effectiveness of our Semi-PerGCN in personality detection, especially in scenarios with limited labeled users.
FairTrade: Achieving Pareto-Optimal Trade-Offs between Balanced Accuracy and Fairness in Federated Learning
Authors: Badar Maryam , Sikdar Sandipan , Nejdl Wolfgang , Fisichella Marco
Published: March 2024

As Federated Learning (FL) gains prominence in distributed machine learning applications, achieving fairness without compromising predictive performance becomes paramount. The data being gathered from distributed clients in an FL environment often leads to class imbalance. In such scenarios, balanced accuracy rather than accuracy is the true representation of model performance. However, most state-of-the-art fair FL methods report accuracy as the measure of performance, which can lead to misguided interpretations of the model's effectiveness to mitigate discrimination. To the best of our knowledge, this work presents the first attempt towards achieving Pareto-optimal trade-offs between balanced accuracy and fairness in a federated environment (FairTrade). By utilizing multi-objective optimization, the framework negotiates the intricate balance between model's balanced accuracy and fairness. The framework's agnostic design adeptly accommodates both statistical and causal fairness notions, ensuring its adaptability across diverse FL contexts. We provide empirical evidence of our framework's efficacy through extensive experiments on five real-world datasets and comparisons with six baselines. The empirical results underscore the potential of our framework in improving the trade-off between fairness and balanced accuracy in FL applications.
SpikingBERT: Distilling BERT to Train Spiking Language Models Using Implicit Differentiation
Authors: Bal Malyaban , Sengupta Abhronil
Published: March 2024

Large language Models (LLMs), though growing exceedingly powerful, comprises of orders of magnitude less neurons and synapses than the human brain. However, it requires significantly more power/energy to operate. In this work, we propose a novel bio-inspired spiking language model (LM) which aims to reduce the computational cost of conventional LMs by drawing motivation from the synaptic information flow in the brain. In this paper, we demonstrate a framework that leverages the average spiking rate of neurons at equilibrium to train a neuromorphic spiking LM using implicit differentiation technique, thereby overcoming the non-differentiability problem of spiking neural network (SNN) based algorithms without using any type of surrogate gradient. The steady-state convergence of the spiking neurons also allows us to design a spiking attention mechanism, which is critical in developing a scalable spiking LM. Moreover, the convergence of average spiking rate of neurons at equilibrium is utilized to develop a novel ANN-SNN knowledge distillation based technique wherein we use a pre-trained BERT model as “teacher” to train our “student” spiking architecture. While the primary architecture proposed in this paper is motivated by BERT, the technique can be potentially extended to different kinds of LLMs. Our work is the first one to demonstrate the performance of an operational spiking LM architecture on multiple different tasks in the GLUE benchmark. Our implementation source code is available at https://github.com/NeuroCompLab-psu/SpikingBERT.
Disentangled Partial Label Learning
Authors: Bao Wei-Xuan , Rui Yong , Zhang Min-Ling
Published: March 2024

Partial label learning (PLL) induces a multi-class classifier from training examples each associated with a set of candidate labels, among which only one is valid. The formation of real-world data typically arises from heterogeneous entanglement of series latent explanatory factors, which are considered intrinsic properties for discriminating between different patterns. Though learning disentangled representation is expected to facilitate label disambiguation for partial-label (PL) examples, few existing works were dedicated to addressing this issue. In this paper, we make the first attempt towards disentangled PLL and propose a novel approach named TERIAL, which makes predictions according to derived disentangled representation of instances and label embeddings. The TERIAL approach formulates the PL examples as an undirected bipartite graph where instances are only connected with their candidate labels, and employs a tailored neighborhood routing mechanism to yield disentangled representation of nodes in the graph. Specifically, the proposed routing mechanism progressively infers the explanatory factors that contribute to the edge between adjacent nodes and augments the representation of the central node with factor-aware embedding information propagated from specific neighbors simultaneously via iteratively analyzing the promising subspace clusters formed by the node and its neighbors. The estimated labeling confidence matrix is also introduced to accommodate unreliable links owing to the inherent ambiguity of PLL. Moreover, we theoretically prove that the neighborhood routing mechanism will converge to the point estimate that maximizes the marginal likelihood of observed PL training examples. Comprehensive experiments over various datasets demonstrate that our approach outperforms the state-of-the-art counterparts.
Constraint Latent Space Matters: An Anti-anomalous Waveform Transformation Solution from Photoplethysmography to Arterial Blood Pressure
Authors: Bian Cheng , Li Xiaoyu , Bi Qi , Zhu Guangpu , Lyu Jiegeng , Zhang Weile , Li Yelei , Zeng Zijing
Published: March 2024

Arterial blood pressure (ABP) holds substantial promise for proactive cardiovascular health management. Notwithstanding its potential, the invasive nature of ABP measurements confines their utility primarily to clinical environments, limiting their applicability for continuous monitoring beyond medical facilities. The conversion of photoplethysmography (PPG) signals into ABP equivalents has garnered significant attention due to its potential in revolutionizing cardiovascular disease management. Recent strides in PPG-to-ABP prediction encompass the integration of generative and discriminative models. Despite these advances, the efficacy of these models is curtailed by the latent space shift predicament, stemming from alterations in PPG data distribution across disparate hardware and individuals, potentially leading to distorted ABP waveforms. To tackle this problem, we present an innovative solution named the Latent Space Constraint Transformer (LSCT), leveraging a quantized codebook to yield robust latent spaces by employing multiple discretizing bases. To facilitate improved reconstruction, the Correlation-boosted Attention Module (CAM) is introduced to systematically query pertinent bases on a global scale. Furthermore, to enhance expressive capacity, we propose the Multi-Spectrum Enhancement Knowledge (MSEK), which fosters local information flow within the channels of latent code and provides additional embedding for reconstruction. Through comprehensive experimentation on both publicly available datasets and a private downstream task dataset, the proposed approach demonstrates noteworthy performance enhancements compared to existing methods. Extensive ablation studies further substantiate the effectiveness of each introduced module.
Variable Importance in High-Dimensional Settings Requires Grouping
Authors: Chamma Ahmad , Thirion Bertrand , Engemann Denis
Published: March 2024

Explaining the decision process of machine learning algorithms is nowadays crucial for both model’s performance enhancement and human comprehension. This can be achieved by assessing the variable importance of single variables, even for high-capacity non-linear methods, e.g. Deep Neural Networks (DNNs). While only removal-based approaches, such as Permutation Importance (PI), can bring statistical validity, they return misleading results when variables are correlated. Conditional Permutation Importance (CPI) bypasses PI’s limitations in such cases. However, in high-dimensional settings, where high correlations between the variables cancel their conditional importance, the use of CPI as well as other methods leads to unreliable results, besides prohibitive computation costs. Grouping variables statistically via clustering or some prior knowledge gains some power back and leads to better interpretations. In this work, we introduce BCPI (Block-Based Conditional Permutation Importance), a new generic framework for variable importance computation with statistical guarantees handling both single and group cases. Furthermore, as handling groups with high cardinality (such as a set of observations of a given modality) are both time-consuming and resource-intensive, we also introduce a new stacking approach extending the DNN architecture with sub-linear layers adapted to the group structure. We show that the ensuing approach extended with stacking controls the type-I error even with highly-correlated groups and shows top accuracy across benchmarks. Furthermore, we perform a real-world data analysis in a large-scale medical dataset where we aim to show the consistency between our results and the literature for a biomarker prediction.
Incomplete Contrastive Multi-View Clustering with High-Confidence Guiding
Authors: Chao Guoqing , Jiang Yi , Chu Dianhui
Published: March 2024

Incomplete multi-view clustering becomes an important research problem, since multi-view data with missing values are ubiquitous in real-world applications. Although great efforts have been made for incomplete multi-view clustering, there are still some challenges: 1) most existing methods didn't make full use of multi-view information to deal with missing values; 2) most methods just employ the consistent information within multi-view data but ignore the complementary information; 3) For the existing incomplete multi-view clustering methods, incomplete multi-view representation learning and clustering are treated as independent processes, which leads to performance gap. In this work, we proposed a novel Incomplete Contrastive Multi-View Clustering method with high-confidence guiding (ICMVC). Firstly, we proposed a multi-view consistency relation transfer plus graph convolutional network to tackle missing values problem. Secondly, instance-level attention fusion and high-confidence guiding are proposed to exploit the complementary information while instance-level contrastive learning for latent representation is designed to employ the consistent information. Thirdly, an end-to-end framework is proposed to integrate multi-view missing values handling, multi-view representation learning and clustering assignment for joint optimization. Experiments compared with state-of-the-art approaches demonstrated the effectiveness and superiority of our method. Our code is publicly available at https://github.com/liunian-Jay/ICMVC. The version with supplementary material can be found at http://arxiv.org/abs/2312.08697.
Accelerate Multi-Agent Reinforcement Learning in Zero-Sum Games with Subgame Curriculum Learning
Authors: Chen Jiayu , Xu Zelai , Li Yunfei , Yu Chao , Song Jiaming , Yang Huazhong , Fang Fei , Wang Yu , Wu Yi
Published: March 2024

Learning Nash equilibrium (NE) in complex zero-sum games with multi-agent reinforcement learning (MARL) can be extremely computationally expensive. Curriculum learning is an effective way to accelerate learning, but an under-explored dimension for generating a curriculum is the difficulty-to-learn of the subgames –games induced by starting from a specific state. In this work, we present a novel subgame curriculum learning framework for zero-sum games. It adopts an adaptive initial state distribution by resetting agents to some previously visited states where they can quickly learn to improve performance. Building upon this framework, we derive a subgame selection metric that approximates the squared distance to NE values and further adopt a particle-based state sampler for subgame generation. Integrating these techniques leads to our new algorithm, Subgame Automatic Curriculum Learning (SACL), which is a realization of the subgame curriculum learning framework. SACL can be combined with any MARL algorithm such as MAPPO. Experiments in the particle-world environment and Google Research Football environment show SACL produces much stronger policies than baselines. In the challenging hide-and-seek quadrant environment, SACL produces all four emergent stages and uses only half the samples of MAPPO with self-play. The project website is at https://sites.google.com/view/sacl-neurips.