bluuebunny/crossref_metadata_2025 huggingface dataset:
Holoplankton and meroplankton communities in surf zone waters of a temperate SW Atlantic sandy beach: Seasonal patterns
Authors: Menéndez M. Clara , Baleani Carla A. , Acha E. Marcelo , Piccolo M. Cintia
Published: April 2023

Sandy beaches and their associated surf zones are the most common type of open shoreline, with significant ecological and socio‐economic importance. In this study, we explored the seasonal fluctuations of the surf zone holo‐ and meroplankton communities to understand the underlying environmental variables driving the temporal dynamics of each community. We also defined a surf‐zooplankton community on a temperate sandy beach (Monte Hermoso, Argentina) and related the organisms to those reported in a nearby estuary for a better understanding of the connection between adjacent coastal ecosystems. Holoplankton was very abundant (13.52–11070.4 ind m−3) and showed a strong seasonality, mainly related to the specific pattern of the two most abundant species: Acartia tonsa (>autumn) and Paracalanus parvus (>winter). This community was affected by seasonal changes in water temperature and salinity and variations in the velocity of currents, which showed that hydrodynamic forces were more significant on a short‐term time scale than seasonal ones. Meroplankton abundances (1.3–48.05 ind m−3) were significantly lower than those recorded for the holoplankton and were mainly dominated by Medusae and larvae of Bivalvia and Decapoda. This fraction also showed a clear seasonal pattern (>abundances in summer), primarily related to the seasonal changes in temperature. The abundances of the main surf‐zooplanktonic taxa were high and constant, emphasizing the importance of these waters as habitats for well‐established communities rather than being used as a transient area. Consequently, we proposed a “specific” surf‐zooplankton community for a temperate sandy beach, considering resident and non‐resident taxa. Finally, the comparison of the surf and estuarine communities indicated a faunal relationship between seascapes, highlighting the ecological role of coastal waters in planktonic life.
c‐di‐GMP regulates activity of the PlzA RNA chaperone from the Lyme disease spirochete
Authors: Van Gundy Taylor , Patel Dhara , Bowler Bruce E. , Rothfuss Michael T. , Hall Allie J. , Davies Christopher , Hall Laura S. , Drecktrah Dan , Marconi Richard T. , Samuels D. Scott , Lybecker Meghan C.
Published: April 2023

PlzA is a c‐di‐GMP‐binding protein crucial for adaptation of the Lyme disease spirochete Borrelia (Borreliella) burgdorferi during its enzootic life cycle. Unliganded apo‐PlzA is important for vertebrate infection, while liganded holo‐PlzA is important for survival in the tick; however, the biological function of PlzA has remained enigmatic. Here, we report that PlzA has RNA chaperone activity that is inhibited by c‐di‐GMP binding. Holo‐ and apo‐PlzA bind RNA and accelerate RNA annealing, while only apo‐PlzA can strand displace and unwind double‐stranded RNA. Guided by the crystal structure of PlzA, we identified several key aromatic amino acids protruding from the N‐ and C‐terminal domains that are required for RNA‐binding and unwinding activity. Our findings illuminate c‐di‐GMP as a switch controlling the RNA chaperone activity of PlzA, and we propose that complex RNA‐mediated modulatory mechanisms allow PlzA to regulate gene expression during both the vector and host phases of the B. burgdorferi life cycle.
Risk factor for progression to kidney failure with replacement therapy in elderly patients with chronic kidney disease: A retrospective single‐centre cohort study
Authors: Nagae Hiroshi , Ueno Yuki , Shojima Masumi , Takae Keita , Kuroki Yusuke , Katafuchi Ritsuko
Published: April 2023

Background

Although the number of elderly patients with chronic kidney disease (CKD) has increased, few studies have examined their prognosis.

Methods

The study design was a retrospective cohort study at a single centre. We evaluated 301 patients aged ≥75 years old with CKD stage G3a to G5. The primary endpoint was kidney failure with replacement therapy (KFRT) and secondary endpoints were all‐cause mortality and annual decline rates of estimated glomerular filtration rate (eGFR). The incidence of KFRT was estimated using the cumulative incidence method considering the competing risk of death. To identify the independent risk factors related to KFRT, multivariate Fine‐Gray regression model analysis were performed.

Results

The median age of the patients was 79 years and the median eGFR was 24.0 mL/min/1.73 m2 at baseline. Urinary protein was positive in 70% of patients. With a median follow‐up of 24.5 months, 35% of the patients developed KFRT and 9% died. Kidney survival significantly decreased according to the CKD stage at baseline. In patients without proteinuria, the cumulative incidence of KFRT increased in CKD stage G5 patients, while in patients with proteinuria, the incidence of KFRT increased from patients with CKD stage G3b. Multivariate Fine‐Gray regression model revealed that less aged, CKD stage G5, baseline data such as proteinuria, hypoalbuminemia, hyperphosphatemia, and hyperuricemia were independent risk factors for KFRT.

Conclusion

Elderly CKD patients with proteinuria need to be carefully monitored even at an early CKD stage because of the risk of developing KFRT.
B7‐H3 drives immunosuppression and Co‐targeting with CD47 is a new therapeutic strategy in β‐catenin activated melanomas
Authors: Hsu Min , Martin Tiphaine C. , Vyas Nikki S. , Desman Garrett , Mendelson Karen , Horst Basil , Parsons Ramon E. , Celebi Julide Tok
Published: April 2023

In melanoma, immune cell infiltration into the tumor is associated with better patient outcomes and response to immunotherapy. T‐cell non‐inflamed tumors (cold tumors) are associated with tumor cell‐intrinsic Wnt/β‐catenin activation, and are typically resistant to anti‐PD‐1 alone or in combination with anti‐CTLA‐4 therapy. Reversal of the ‘cold tumor’ phenotype and identifying new effective immunotherapies are challenges. We sought to investigate the role of a newer immunotherapy agent, B7‐H3, in this setting. RNA sequencing was used to identify co‐targeting strategies upon B7‐H3 inhibition in a well‐defined preclinical melanoma model driven by β‐catenin. We found that immune checkpoint molecule B7‐H3 confers a suppressive tumor microenvironment by modulating antiviral signals and innate immunity. B7‐H3 inhibition led to an inflamed microenvironment, up‐regulation of CD47/SIRPa signaling, and together with blockade of the macrophage checkpoint CD47 resulted in additive antitumor responses. We found that the antitumor effects of the B7‐H3/CD47 antibody combination were dependent on cytokine signaling pathways (CCR5/CCL5 and IL4).
Our experience with propranolol for infantile hemangioma
Authors: Wu Yao , Zhao Piaoping , Song Wei , Lu Wenmin , Dai Ting , Wang Liuhui
Published: April 2023

Background/objectives

The most frequent benign vascular tumor in children is infantile hemangioma (IH). For severe IHs, propranolol has become the first‐line Treatment. Despite the fact that several studies have comprehensive therapy regimens, including the best time to start Treatment, dosage, visit frequency, and treatment duration, there is still controversy about the best time to start and stop propranolol medication.

Methods

Between January 2016 and February 2019, dermatologists experienced hemangioma treatment and recommended propranolol treatment for 232 IHs. A total of 90 patients completed the treatment process after undergoing a color Doppler ultrasound test.

Results

Propranolol uniquely affects each IH. Ninety patients were divided into two groups in this study: entire regression (n = 40) and partial regression (n = 50). The entire regression group's initial treatment period (4.3 ± 2.97 months) was substantially shorter than the partial regression group's (5.2 ± 4.57 months) (p < 0.05). Between the entire regression group (23.4 ± 12.8 months) and the partial regression group (24.5 ± 16.6 months), there was no significant difference in time to reduce propranolol. The partial regression group (32.9 ± 25.3month) had a lengthier treatment course than the entire regression group (23.4 ± 13.7 months) (p < 0.05). The partial regression group (22%), like the entire regression group, had a higher recurrence rate (5%). The overall proportion of hemangiomas on the face (particularly periocular hemangioma) in the regression group was greater than in the control group.

Conclusion

The entire regression group's initial treatment time was significantly shorter than the partial regression group's. As a result, as soon as a hemangioma is discovered, it should be treated. To determine the appropriate time to reduce propranolol, we must evaluate the patient's age and the percentage of tumor regression. Periocular hemangioma may have a better prognosis than other types. Given the small number of patients in our study, we will need to do more research in the future to confirm our findings.
Absence of GSTT1 and polymorphisms in GSTP1 and TP53 are associated with the incidence of acne vulgaris
Authors: Ullah Rehmat , Afgan Sher , Akhtar Mariyam , Asif Muhammad , Latif Muhammad , Mehmood Rashid , Naeem Muhammad , Zahra Kiran , Farooq Muhammad , Ben Said Mourad , Iqbal Furhan
Published: April 2023

Backgrounds

Acne vulgaris is a chronic inflammatory skin disease of the pilosebaceous unit affecting most teenagers and numerous adults throughout the world. The present study was designed to assess the association of the presence or absence of GSTM1, GSTT1, and single nucleotide polymorphisms rs1695 in GSTP1 and rs1042522 in TP53 gene with acne vulgaris.

Methods

The cross‐sectional case–control study was conducted at the Institute of Zoology from May 2020 to March 2021 and included acne vulgaris patients (N = 100) and controls (N = 100) enrolled in Dera Ghazi Khan district, Pakistan. Multiplex and tetra‐primer amplification refractory mutation system‐polymerase chain reactions were applied to investigate the genotype in analyzed genes. The association of rs1695 and rs1042522 with acne vulgaris was studied either individually or in various combinations with GATM1 and T1.

Results

A significant association of absence of GSTT1 and mutant genotype at rs1695 (GG) and at rs1042522 (CC) in GSTP1 and TP53, respectively, was found to be associated with acne vulgaris in enrolled subjects. Subjects aged 10–25 years and smokers were more susceptible to acne vulgaris.

Conclusion

Our results suggest that genotypes of glutathione S‐transferases (GSTs) and TP53 are involved in protection against oxidative stress and may influence disease progression in acne vulgaris.
Sellars, practical reality, and practical truth
Authors: Dach Stefanie
Published: April 2023

Wilfrid Sellars is usually read as claiming that only the unobservable, theoretical objects which science would postulate at the ideal end of inquiry are real. Against this, Willem deVries has suggested that we can develop a notion of practical reality in the context of Sellars's philosophy which would pertain primarily to commonsense objects. I use deVries's suggestion as a foil to clarify Sellars's own commitments about the practical. I show that the notion of practical reality is not necessary to secure the ultimate legitimacy of practical concepts. We can retreat to the less committed notion of practical truth. I argue that the notion of practical truth may not be sufficient to ensure that ultimately legitimate practical concepts are commonsense concepts in Sellars's framework. Nevertheless, deVries's suggestion highlights that Sellars's vision of an ultimate conceptual system may have been richer than is often thought.
Conceptualizing Human–Nature Relationships: Implications of Human Exceptionalist Thinking for Sustainability and Conservation
Authors: Kim Joan J. H. , Betz Nicole , Helmuth Brian , Coley John D.
Published: April 2023

The ways in which people conceptualize the human–nature relationship have significant implications for proenvironmental values and attitudes, sustainable behavior, and environmental policy measures. Human exceptionalism (HE) is one such conceptual framework, involving the belief that humans and human societies exist independently of the ecosystems in which they are embedded, promoting a sharp ontological boundary between humans and the rest of the natural world. In this paper, we introduce HE in more depth, exploring the impact of HE on perceptions of the human–nature relationship, the role of culture in HE, and speculating on the origins of HE. We consider potential implications for environmental decision‐making, conservation and environmental science, and promoting proenvironmental behavior. We present empirical evidence on the pervasiveness and consequences of HE in WEIRD (Western, Educated, Industrialized, Rich and Democratic) populations, and potential interventions. Finally, we close with implications of human‐exceptionalist thinking on other sustainability‐related fields, including conservation practices, nature management, climate change adaptation, and environmental science. Understanding the cognitive and social drivers of this disconnect is vital on a planet now dominated by environmental change, as not only are humans increasingly impacted by natural disasters, but the choices they make can have ever more dire consequences for the sustainability of ecosystems.
Sustainability and Semantic Diversity: A View from the Malayan Rainforest
Authors: Burenhult Niclas
Published: April 2023

Sustainable development goals assume that basic notions, such ashealth,life, andwater, can be universally and easily expressed and understood across diverse communities and stakeholders. Yet, there is growing evidence pointing to considerable semantic diversity in how humans represent the world in language. In this paper, I discuss such semantic diversity in the context of key notions of sustainability. Focusing on an environmental term of broad relevance to sustainability goals,forest, I explore how this notion compares with assumed equivalent notions in a non‐Western lesser‐known speech community. Specifically, I analyze representations of treed environments in the language of the Jahai, a forager community inhabiting the rainforests of the Malay Peninsula. The results show that an understanding of local indigenous systems of representation can be crucial to the communication and implementation of sustainability goals.
What Makes Us Smart?
Authors: Henrich Joseph , Muthukrishna Michael
Published: April 2023

How did humans become clever enough to live in nearly every major ecosystem on earth, create vaccines against deadly plagues, explore the oceans depths, and routinely traverse the globe at 30,000 feet in aluminum tubes while nibbling on roasted almonds? Drawing on recent developments in our understanding of human evolution, we consider what makes us distinctively smarter than other animals. Contrary to conventional wisdom, human brilliance emerges not from our innate brainpower or raw computational capacities, but from the sharing of information in communities and networks over generations. We review how larger, more diverse, and more optimally interconnected networks of minds give rise to faster innovation and how the cognitive products of this cumulative cultural evolutionary process feedback to make us individually “smarter”—in the sense of being better at meeting the challenges and problems posed by our societies and socioecologies. Here, we consider not only how cultural evolution supplies us with “thinking tools” (like counting systems and fractions) but also how it has shaped our ontologies (e.g., do germs and witches exist?) and epistemologies, including our notions of what constitutes a “good reason” or “good evidence” (e.g., are dreams a source of evidence?). Building on this, we consider how cultural evolution has organized and distributed cultural knowledge and cognitive tasks among subpopulations, effectively shifting both thinking and production to the level of the community, population, or network, resulting in collective information processing and group decisions. Cultural evolution can turn mindless mobs into wise crowds by facilitating and constraining cognition through a wide variety of epistemic institutions—political, legal, and scientific. These institutions process information and aid better decision‐making by suppressing or encouraging the use of different cultural epistemologies and ontologies.
Análisis de las demandas y recursos laborales en una organización del Estado peruano, prestadora de servicios de atención durante la crisis sanitaria por la COVID-19
Authors: Vera Ruiz Angela , Guevara Rojas Luis Alberto , Espinosa Pezzia Agustín , Calderón Prada Alicia , Mego Vasquez Marisol , Ticona Quispe Sofía
Published: April 2023

Este estudio analiza las demandas y recursos laborales presentes en una entidad gubernamental, que ha prestado servicios de atención frente a la pandemia, siendo previamente prestadora de servicios deportivos, para proponer un modelo de análisis complejo. Desde una metodología descriptiva-correlacional, se identificaron los recursos y demandas laborales que afectan el desempeño de los trabajadores en el contexto particular de crisis sanitaria, siendo el apoyo organizacional, las oportunidades de desarrollo, y la esperanza, resiliencia y optimismo, los recursos organizacionales y psicológicos que los protegen del agotamiento y/o potencian su engagement, y las demandas de confusión de rol y dificultades en el trabajo, las que pueden ponerlos en riesgo de agotamiento. Los resultados ponen en evidencia variables claves para el afrontamiento de eventos críticos en el sector público.
Establishment of Prediction Model for Cavitation Surge Frequency and Onset in an Inducer Considering Dynamic Characteristics of Cavitation Compliance and Mass Flow Gain Factor
Authors: Yamamoto Keita , Ukai Satoshi , Fukuda Taro , Kawasaki Satoshi , Negishi Hideyo
Published: April 2023

An accurate prediction method of cavitation surge is desired to design a reliable turbopump for rocket engines that allow complex operational sequences such as controlled reentry and landing. Therefore, the paper aims to develop a novel model that enables accurate predictions of both frequency and onset of cavitation surge by considering dynamic characteristics of cavitation compliance K and mass flow gain factor M. The paper conducts both experimental and numerical studies in an inducer known to cause cavitation surge. First, characteristics of cavitation surge including frequency and occurrence conditions are experimentally surveyed. Secondary, K and M for the studied inducer are numerically obtained by steady RANS simulations. Then, the one-dimensional model is initially established based on the premises acquired by performed experiments and applied to cavitation surge predictions using quasi-statically evaluated K and M. As a result of comparisons with experiments, the cavitation surge frequency is adequately evaluated by the established model, whereas the cavitation surge onset fails to be estimated only using quasi-static parameters. The new model is thus proposed by including dynamic characteristics of K and M, and it is mathematically clarified that phase properties of K and M may play a key role to trigger cavitation surge. By presuming adequate values of dynamic characteristics based on past literatures, consequently, the developed model succeeds in accurate predictions of the cavitation surge onset in the experiment. This evidences that dynamic characteristics of K and M are essential to predict cavitation surge quantitatively.
Improving Ambient Contrast Ratio of Display Device at Oblique Angle Using a Fe3O4-Magnetic Particle Chained Pillar Array Structure
Authors: Li Zong-Tao , Wu Jun-Hao , Liang Guan-Wei , Yang Ren-peng , Yang Zhihui , Li Jia-Sheng
Published: April 2023

A high ambient contrast ratio (ACR) is essential for achieving a high dynamic range in advanced display applications, but reported ACR enhancement strategies always result in reduced optical efficiency of light-emitting diode (LED) display devices. In this study, an Fe3O4-magnetic particle-chained pillar array (Fe3O4-MPCP) structure was introduced to improve the ACR of LED display devices with low optical loss. The results indicated that the MPCP structure achieved high ACR at an oblique angle using surface pillar array to suppress ambient light reflections, and its internal magnetic particle chain improved the transmissivity to maintain high device efficiency. Compared with the commercial graphite-coated device at typical viewing angles (i.e., 0 deg and 60 deg), the ACR of the optimal MPCP device increased by 217 and 140%, while the device efficiency increased by 25 and 12%, respectively. Therefore, the proposed method provides a novel approach for significantly improving ACR at all oblique angles while maintaining high device efficiency, which can be easily integrated into various LED display devices and has significant potential in advanced display applications.
Multi-Level Embedded Three-Dimensional Manifold Microchannel Heat Sink of Aluminum Nitride Direct Bonded Copper for the High-Power Electronic Module
Authors: Lin Yujui , Wei Tiwei , Moy Wyatt Jason , Chen Hao , Gupta Man Prakash , Degner Michael , Asheghi Mehdi , Mantooth H. Alan , Goodson Kenneth E.
Published: April 2023

Better thermal management is a key enabler of higher power density in traction inverter power modules. For the first time, we successfully fabricated and tested a microchannel with a three-dimensional (3D) manifold cooler (MMC) using aluminum nitride (AlN)-based directed bonded copper (DBC) substrates. The microchannels (width ∼300 μm and height ∼450 μm) and 3D manifold fluidic passages (width ∼300 μm and height ∼600 μm) were fabricated in two DBC substrates using the femtosecond laser and subsequently bonded using transition liquid phase (TLP) bonding. In this study, the hydraulic and thermal performance of the 3D MMC is measured and validated with numerical simulation. The proposed 3D MMC is capable of removing heat at 600 W/cm2 with a 10 kPa pressured drop at the thermal thermal resistance of 0.2 cm2 K/W. The optimized designs via geometric and layout rearrangement were conducted, which indicates the pressure drop can be further reduced by 10× while maintaining the same thermal performance.
Strong Resonance Bifurcations in a Discrete-Time In-Host Model With a Saturating Infection Rate
Authors: Salman Sanaa Moussa
Published: April 2023

Viral blips are a recurrent pattern observed in many persistent infections such as the human immunodeficiency virus (HIV). The main goal of this research is to present a comprehensive analytical study of a two-dimensional discrete-time in-host infection model, that exhibits viral blips, with a saturating infection rate. We examine the interactions between the population densities of infected and uninfected CD4+ T cells by discussing the model's dynamics in the long run. The local asymptotic stability of fixed points of the model is investigated. The model undergoes both flip and Neimark–Sacker bifurcations. Moreover, codimension-two bifurcations of the endemic fixed point are discussed using bifurcation theory and normal forms. The model exhibits 1:2, 1:3, and 1:4 strong resonances. Numerical simulations are performed to verify our analysis. In addition, bifurcations of higher iterations are extracted from the numerical continuation.
Damage Assessment of Similar Martensitic Welds Under Creep, Fatigue, and Creep-Fatigue Loading
Authors: Bender Thorben , Klenk Andreas , Weihe Stefan
Published: April 2023

For the assessment of welds under high-temperature conditions in the creep or creep-fatigue regimes, the knowledge of the damage location and its temporal evolution is of high importance. The local failure behavior of weld joints is not reflected in design guidelines using weld reduction factors or in typical assessment approaches. The evaluation of local strains and stresses in the heat affected zone (HAZ) is essential for a more detailed consideration of weld behavior and has a high potential for improvement of design and inspection guidelines. In this paper, an overview of current developments in the assessment of weld joints is given. Uni-axial creep, component tests, low cycle fatigue (LCF), and creep-fatigue experiments with base material, weld joints and microstructure simulated HAZ material are presented. The use of test results of microstructure simulated HAZ material allows the parameter identification of numerical material models for the HAZ and improves the simulation of the local stress and strain behavior of weld joints. Two assessment methods, one for creep and one for fatigue/creep-fatigue were presented, based on the local behavior determined by the numerical simulations. The assessment approach for pure creep loads was validated using several uni-axial creep tests and two component tests. The approach for the fatigue/creep-fatigue loads is still in the developmental stage but the first results were presented and further areas for improvement were identified.
Taxonomic contribution to the knowledge of the oribatid mite genus Schalleria (Acari, Oribatida, Microzetidae), with description of a new species from Cuba
Authors: Ermilov Sergey G.
Published: April 2023

A new species of Schalleria (Oribatida, Microzetidae)—S. (Paraschalleria) engelbrechti sp. nov.—is described from leaf litter of mixed forest in Cuba; it is similar to S. (P.) forceps in presence of bacilliform basal prodorsal apophysis, but differs by smaller body size, the morphology of the first lobed structure, lamella, bothridial seta, epimeral setae 3c, 4c, distal part of prodorsal apophysis, and the length and morphology of interlamellar seta. A new generic diagnosis of Schalleria is presented. An identification key to known species of the genus is provided.
Functional and numerical responses are influenced by the feeding experience of Neoseiulus cucumeris (Acari: Phytoseiidae)
Authors: Yazdanpanah Shima , Fathipour Yaghoub
Published: April 2023

Neoseiulus cucumeris (Oudemans) is a commercially available biocontrol agent against various pests. This generalist predator was reared on cattail pollen for 10 generations (G10) and its quality was evaluated using functional and numerical responses to Tetranychus urticae Koch nymph densities as prey. The experiments were conducted by offering a range of prey densities (2, 4, 8, 16, 32, 64, and 128 nymphs) under standard conditions (25 ± 1ºC, 60 ± 5% RH, and a photoperiod of L16:D8 h). The predator exhibited a type III functional response after ten generations of rearing on cattail pollen (G10), while it was type II when the predator had no experience with pollen (G0). The highest estimated maximum predation rate (T/Th) was in G0 (127 prey/day), and the lowest was in G10 (85 prey/day); while, the observed maximum predation rate (OMPR) in the mentioned generations was 67 and 84 prey/day, respectively. The number of prey consumed and the number of eggs laid by the predator in G10 was significantly more than G0. The effects of predator’s generation, prey density, and their interaction on predation and oviposition rate (on T. urticae) were statistically significant. Therefore, because of the higher predation and oviposition rate, and efficient quality of mass-reared predators on cattail pollen, it is proposed that this pollen can be an appropriate food source for mass rearing of N. cucumeris.
Relationship between food grinding and gut microbiota in Brandt's voles
Authors: Shen Qiu-Yi , Shi Jia-Yi , Gu Ke-Han , Wei Wan-Hong , Yang Sheng-Mei , Dai Xin
Published: April 2023

Food grinding is an abnormal behavior in rodents and its influencing factors are unknown. Our study investigated the potential relationships between gut microbiota and food grinding in Brandt's voles ( Lasiopodomys brandtii (Radde, 1861)) by comparing the differences between groups with different degrees of food grinding. The strong food-grinding group showed more relative food ground, higher ratio of ground food to food consumption, and lower percentage of time spent in the central area. The structure of fecal microbiota community differed between the strong and weak food-grinding groups. Strong and weak food-grinding voles showed higher abundances of Alistipes and Aerococcus and Atopostipes, Paenalcaligenes, Un—s-Clostridiaceae bacterium GM1, and Streptococcus, respectively. Strong correlations between the food ground to consumption ratio and abundances of fecal microbiota were found in Streptococcus and Paenalcaligenes. Fecal acetate and isobutyrate contents were higher in strong food-grinding voles and positively correlated with relative ground food and food ground to consumption ratio. Our study suggests that gut microbiota and short-chain fatty acids may contribute to the regulation of food-grinding behavior.
Succinct Data Structures for SP, Block-Cactus and 3-Leaf Power Graphs
Authors: Chakraborty Sankardeep , Jo Seungbum , Sadakane Kunihiko , Satti Srinivasa Rao
Published: April 2023

We design succinct encodings of series-parallel, block-cactus and 3-leaf power graphs while supporting the basic navigational queries such as degree, adjacency and neighborhood optimally in the RAM model with logarithmic word size. One salient feature of our representation is that it can achieve optimal space even though the exact space lower bound for these graph classes is not known. For these graph classes, we provide succinct data structures with optimal query support for the first time in the literature. For series-parallel multigraphs, our work also extends the works of Uno et al. (Disc. Math. Alg. and Appl., 2013) and Blelloch and Farzan (CPM, 2010) to produce optimal bounds.
Weierstrass 1-forms and nondicritical generalized curve foliations
Authors: García Barroso Evelia R. , Hernandes Marcelo Escudeiro , Iglesias Mauro Fernando Hernández
Published: April 2023

In this paper, we introduce a distinguished expression for a given 1-form with respect to a polynomial [Formula: see text], called Weierstrass form. We will use this form and the properties of plane analytical curves to give new characterizations of nondicritical generalized curve foliations.
Pinakas: A Methodology for Deep Analysis of Tables in Technical Documents
Authors: Alexiou Michail S. , Bourbakis Nikolaos G.
Published: April 2023

The holistic understanding of the information contained in technical documents depends on the understanding of the document’s individual modalities. These modalities are tables, graphics, diagrams, formulas, etc. and each of them is a standalone research topic that requires a different way of processing and understanding. These modalities, processed and combined with the document text, can introduce new techniques for visual question answering in documents. Thus, in this paper we present Pinakas, a methodology for automatic analysis of the internal tabular information that appears in technical documents and its modeling to stochastic Petri-net graphs. We focus only on tables that strictly abide by the IEEE format rules. The methodology presented here is divided into the following steps: (1) table detection, (2) table recognition, (3) table understanding. Qualitative results of Pinakas are demonstrated as proof of concept for the accurate extraction of information from three different types of tables.
Extracting Pseudocode from Digital Block Diagram in Technical Documents
Authors: Gkorgkolis Nikolaos , Bourbakis Nikolaos G.
Published: April 2023

The technical document is an entity that consists of several essential and interconnected parts, often referred to as modalities. Despite the extensive attention that certain modalities have already received, say per the textual information, there are several aspects that get disproportional attention throughout the bibliography. An instance of such a modality is the block diagrams found in the technical document, as they can provide crucial information about the functionality and the technical details of both their related parts and the technical document as a whole. This paper deals with the automatic understanding of block diagrams and the extraction of pseudocode associated with the functionality of a given diagram. In particular we present a complete methodology for the formal modelling of digital block diagrams and their elements, then we develop a generative framework and three novel annotated datasets on diagrams classification and captioning. After mapping the initial problem to a block diagram description task, we present several original predictive setups derived from image segmentation, analyze the inference capabilities, and we offer illustrative examples justifying our approach.
Efficient Prediction of Seasonal Infectious Diseases Using Hybrid Machine Learning Algorithms with Feature Selection Techniques
Authors: Indhumathi K. , Kumar K. Sathesh
Published: April 2023

Early seasonal disease risk identification is the most challenging task in the medical industry. The capacity to detect patients at risk of improvement throughout their hospital stay is critical for effective patient allocation and care among patients with seasonal diseases. Patient risk factor prediction is the most important issue in reducing victim mortality. Machine learning plays a vital role in identifying the risk level of patients. In this research, we consider four seasonal diseases such as dengue, malaria, typhoid, and pneumonia. In this research, the researcher finds the dangerous symptoms of victims based on their age group. The real-time dataset was used in this study. The dataset for this study was gathered from hospitals in the Madurai district between 2019 and 2020. Feature selection is the prime element of patient risk recognition. It is used to pick the most accurate attributes for prediction. The dataset is divided into 70% training data and 30% testing data. This research proposes the feature selection method Boruta-XGBoost for improving accuracy. In this research, we discuss various attribute selection algorithms, including the Boruta algorithm, the XGBoost algorithm, the recursive feature elimination method (RFE), and the PRF-BXGBoost (Patient Risk Factor-Boruta-XGBoost) algorithm. The proposed method provides greater accuracy when compared to other variable selection methods. The time complexity of the proposed method is low when compared to other algorithms.
OPTIMAL TREATMENT STRATEGIES USING DENDRITIC CELL VACCINATION FOR A TUMOR MODEL WITH PARAMETER IDENTIFIABILITY
Authors: KHAJANCHI SUBHAS , MONDAL JAYANTA , TIWARI PANKAJ KUMAR
Published: April 2023

Immunotherapy has become a rapidly developing approach in the treatment of cancer. Cancer immunotherapy aims at promoting the immune system response to react against the tumor. In view of this, we develop a mathematical model for immune–tumor interplays with immunotherapeutic drug, and strategies for optimally administering treatment. The tumor–immune dynamics are given by a system of five coupled nonlinear ordinary differential equations which represent the interaction among tumor-specific CD4+T cells, tumor-specific CD8+T cells, tumor cells, dendritic cells and the immuno-stimulatory cytokine interleukin-2 (IL-2), extended through the addition of a control function describing the application of a dendritic cell vaccination. Dynamical behavior of the system is studied from the analytical as well as numerical points of view. The main aim is to investigate the treatment regimens which minimize the tumor cell burden and the toxicity of dendritic cell vaccination. Our numerical simulations demonstrate that the optimal treatment strategies using dendritic cell vaccination reduce the tumor cell burden and increase the cell count of CD4+T cells, CD8+T cells, dendritic cells and IL-2. The most influential parameters having significant impacts on the tumor cells are identified by employing the approach of global sensitivity analysis.
Energy-Efficient Data Aggregation and Cluster-Based Routing in Wireless Sensor Networks Using Tasmanian Fully Recurrent Deep Learning Network with Pelican Variable Marine Predators Algorithm
Authors: Yadawad Shreedhar , Joshi S. M.
Published: April 2023

One of the major significant problems in the existing techniques in Wireless Sensor Networks (WSNs) is Energy Efficiency (EE) because sensor nodes are battery-powered devices. The energy-efficient data transmission and routing to the sink are critical challenges because WSNs have inherent resource limitations. On the other hand, the clustering process is a crucial strategy that can rapidly increase network lifetime. As a result, WSNs require an energy-efficient routing strategy with optimum route election. These issues are overcome by using Tasmanian Fully Recurrent Deep Learning Network with Pelican Variable Marine Predators Algorithm for Data Aggregation and Cluster-Based Routing in WSN (TFR-DLN-PMPOA-WSN) which is proposed to expand the network lifetime. Initially, Tasmanian Fully Recurrent Deep Learning Network (TFR-DLN) is proposed to elect the Optimal Cluster Head (OCH). After OCH selection, the three parameters, trust, connectivity, and QoS, are optimized for secure routing with the help of the Pelican Variable Marine Predators Optimization Algorithm (PMPOA). Finally, the proposed method finds the minimum distance among the nodes and selects the best routing to increase energy efficiency. The proposed approach will be activated in MATLAB. The efficacy of the TFR-DLN- PMPOA-WSN approach is assessed in terms of several performances. It achieves higher throughput, higher packet delivery ratio, higher detection rate, lower delay, lower energy utilization, and higher network lifespan than the existing methods.
Additional Estrogen Administration to Avoid Poor Outcomes Associated with a Thin Endometrium in Frozen Embryo Transfer
Authors: Takahashi Kyoko , Takehara Isao , Nakamura Fumihiro , Nakai Nanako , Matsukawa Jun , Matsuo Koki , Kawagoe Jun , Igarashi Hideki , Nagase Satoru
Published: April 2023

Background: During hormone replacement therapy (HRT) to optimize endometrial growth for thawed-frozen embryo transfer (FET), patients normally undergo estrogen administration for 14 days (day 14 group). However, if optimal endometrial thickness is not achieved in 14 days, estrogen treatment is continued for seven more days at a higher dose (day 21 group). This study aimed to determine the effects of this extended estrogen administration regimen on pregnancy outcomes.

Methods: A retrospective analysis was performed using our patient database from November 2016 to March 2018. We analyzed 303 cycles of blastocyst-FET and compared patient background characteristics and pregnancy outcomes between day 14 and day 21 groups.

Results: In day 21 group, the pregnancy rate tended to be lower while the miscarriage rate and ectopic pregnancy rate were higher than those in day 14 group. However, the differences between the groups were not statistically significant.

Conclusions: Delayed endometrial growth resulted in poorer pregnancy outcomes in FET, but the differences were not statistically significant. Thus, it could be meaningful to add estrogen administration for 7 days to avoid the poor outcomes caused by a thin endometrium.
Automatic Keyword Extraction Algorithm for Chinese Text based on Word Clustering
Authors: Pan Rui
Published: April 2023

There are some problems in automatic keyword extraction of Chinese text, such as large feature extraction error, low precision of extracted keywords, and poor real-time performance. Therefore, an automatic keyword extraction algorithm for Chinese text based on word clustering is designed. Calculate keyword frequency, document frequency and inverse document frequency features through statistical algorithm, measure the degree of interdependence between keywords with the help of point mutual information, and construct keyword feature item quantification matrix with the help of vector space model corresponding to keywords and feature items to complete keyword feature quantification and realize keyword feature extraction of Chinese text. Calculate the average semantic similarity of keyword words, determine the similarity of keyword features, and eliminate the keyword features with high similarity; Set the comprehensive feature value of the importance of single word words in Chinese text, determine the importance of single word words in the text, remove the single word words with low importance, and use Bayesian framework to reduce the dimension of high-dimensional keyword feature data to realize preprocessing research. The mapping results of keyword vector space model are determined by word clustering algorithm, the text clusters of keyword space clustering results are calculated by clustering algorithm, and the keywords are classified by DBN method. On this basis, the automatic keyword extraction model of Chinese text is designed to realize the automatic keyword extraction of Chinese text. The experimental results show that the design algorithm can effectively reduce the feature extraction error and improve the extraction efficiency.
Data Provenance in Security and Privacy
Authors: Pan Bofeng , Stakhanova Natalia , Ray Suprio
Published: April 2023

Provenance information corresponds to essential metadata that describes the entities, users, and processes involved in the history and evolution of a data object. The benefits of tracking provenance information have been widely understood in a variety of domains; however, only recently have provenance solutions gained interest in the security community. Indeed, on the one hand, provenance allows for a reliable historical analysis enabling security-related applications such as forensic analysis and attribution of malicious activity. On the other hand, the unprecedented changes in the threat landscape place demands for securing provenance information to facilitate its trustworthiness.

With the recent growth of provenance studies in security, in this work we examine the role of data provenance in security and privacy. To set this work in context, we outline fundamental principles and models of data provenance and explore how the existing studies achieve security principles. We further review the existing schemes for securing data provenance collection and manipulation known as secure provenance and the role of data provenance for security and privacy, which we refer to as threat provenance.
MSA Speech Rhythm Pattern in a Multilingual Setting
Authors: Droua-Hamdani Ghania
Published: April 2023

This study examines variation in rhythm metrics in a multilingual setting by focusing on between-speaker differences. The investigation analyzes speech rhythm patterns of segmental durations in the speech of 77 Algerian speakers belonging to three educational background classes and three age groups. The experiment focuses on speech rhythm variability according to the level of educational background of the speakers and the language used in daily life. The gender and age of speakers are also analyzed. Results show that five vocalic rhythm metrics reflect the contrast between long and short vowels that was observed from the acoustic measurements. The statistical analysis reveals that rhythm metrics are sensitive to differences between groups of speakers, such as age and educational background. The outcomes also show that the lack of practice of Modern Standard Arabic by some speaker groups considerably affects vowel quantity.
XCoS: Explainable Code Search Based on Query Scoping and Knowledge Graph
Authors: Wang Chong , Peng Xin , Xing Zhenchang , Zhang Yue , Liu Mingwei , Luo Rong , Meng Xiujie
Published: April 2023

When searching code, developers may express additional constraints (e.g., functional constraints and nonfunctional constraints) on the implementations of desired functionalities in the queries. Existing code search tools treat the queries as a whole and ignore the different implications of different parts of the queries. Moreover, these tools usually return a ranked list of candidate code snippets without any explanations. Therefore, the developers often find it hard to choose the desired results and build confidence on them. In this article, we conduct a developer survey to better understand and address these issues and induct some insights from the survey results. Based on the insights, we propose XCoS, an explainable code search approach based on query scoping and knowledge graph. XCoS extracts a background knowledge graph from general knowledge bases like Wikidata and Wikipedia. Given a code search query, XCoS identifies different parts (i.e., functionalities, functional constraints, nonfunctional constraints) from it and use the expressions of functionalities and functional constraints to search the codebase. It then links both the query and the candidate code snippets to the concepts in the background knowledge graph and generates explanations based on the association paths between these two parts of concepts together with relevant descriptions. XCoS uses an interactive user interface that allows the user to better understand the associations between candidate code snippets and the query from different aspects and choose the desired results. Our evaluation shows that the quality of the extracted background knowledge and the concept linkings in codebase is generally high. Furthermore, the generated explanations are considered complete, concise, and readable, and the approach can help developers find the desired code snippets more accurately and confidently.
Analyzing Differences in Diagnostic Accuracy of a Pigmented Lesion Assay for Melanoma
Authors: Ludzik Joanna , Lee Claudia , Latour Emile , Witkowski Alexander
Published: April 2023

Background. Standard protocol to detect melanoma relies on visual assessment in which the sensitivity and specificity are low for early melanomas. Pigmented lesion assay (PLA) offers objective metrics to aid in determining suspicious lesions; however, the literature on the diagnostic accuracy is controversial. Methods. To assess the performance of PLA, we retrospectively assessed the diagnostic accuracy using two different cohorts, total (n = 426) and biopsied (n = 96), modifying the definition of true negative for each. Sensitivity, specificity, negative predictive value, positive predictive value, prevalence, and Cohen’s kappa were calculated. Results. 370 PLA (−) lesions and 56 in the PLA (+). Of the 40 PLA (−) lesions that were biopsied, 5 (12.5%) were diagnosed as melanoma and 16 (40.0%) were atypical melanocytic nevus. Of the 56 PLA (+) lesions, 14 (25.0%) were melanoma, of which 10 (71.4%) were double positive, 3 (21.4%) were PRAME only, and 1 (7.1%) was LINC only. For the total cohort (n = 426), sensitivity of 73.7%, specificity of 89.7%, NPV of 98.6%, PPV of 25.0%, prevalence of 4.5%, accuracy of 89.0%, and kappa agreement of 0.329 were calculated. The biopsied cohort revealed the same sensitivity and PPV; however, specificity was 45.5%, accuracy was 51.0%, NPV was 87.5%), and kappa agreement was 0.110. Conclusion. There differences in our study seen between cohorts highlight the importance to recognize that neither findings are perfect. The real value likely falls in between, but further studies are needed.
Length-Weight Relationships of Four Fish Species of the Upper Yangtze River, Sichuan, China
Authors: Song Mingjiang , Chen Yeyu , Wu Xiaoyun , Liu Ya , Gong Quan , Li Feiyang , Li Pengcheng , Ou Jun , Zou Qiaolin , Lai Jiansheng
Published: April 2023

In this study, the length-weight relationships were determined for four fish species of the upper Yangtze River, Sichuan province, China. The fish were collected by drift net (mesh size: 4 cm × 4 cm) and ground bamboo cages (1 cm × 1 cm) from Yalong River, Laixi River, Pingtung River, and Baoxing River. Samples were collected from March 2017 to December 2022. According to the length-weight function equation (

W
=
a

L

b

), r2 values ranged from 0.960 to 0.991 and the b values of LWRs ranged from 2.916 (Megalobrama pellegrini) to 3.095 (Claea dabryi).