bluuebunny/crossref_metadata_2025_split huggingface dataset:
Jaguar (Panthera onca) population dynamics in an “isolated” national park in the Cerrado biome, Brazil
Authors: Alves Giselle Bastos , Tôrres Natália Mundim , Jácomo Anah Tereza de Almeida , Finnegan Shannon Patrícia , Trinca Cristiano Trapé , Moreira Renato , Sanz-Pérez Ana , Sollmann Rahel , Silveira Leandro 
Published: January 2024

Abstract

The jaguar (Panthera onca) is endangered along all its geographical distribution, including Brazil. Assessments of jaguar population dynamics are scarce despite their relevance to efficiently design conservation measures and acknowledge the demographic health of jaguar populations. This study uses camera trap data from 4 surveys spanning 8 years to gain knowledge on jaguar population dynamics in Emas National Park (ENP), one of the largest Conservation Units in the Brazilian Cerrado biome. ENP is located within a major grain cropland area and provides refuge for species that occur in its interior and surroundings. We used spatially explicit capture-recapture models (SCR) to estimate jaguar population density and population trends, and Cormack-Jolly Seber models (CJS) to estimate survival. We derived recruitment into the adult population from estimates of population trends and survival. Across all surveys, we identified 26 individuals, 9 female (F), 13 male (M), and 4 with unidentified sex (NI). The estimated sex ratio was not statistically different from even. Distance to river positively affected jaguar detection rates; baseline detection rates were higher for males than females and on-road than off-road. The movement parameter σ was higher for males than females. Survey specific density estimates ranged from 1.87 to 2.42 ind./100km², leading to an average annual population growth rate of 0.99, i.e., a stable population. Survival was high (0.87), and some individuals remained in the population for over 10 years, pointing towards a healthy population with low turn-over rates. But recruitment into the adult population was low (0.16), possibly suggesting a somewhat isolated and saturated population. Such population stability supports the role of ENP in local-scale jaguar conservation. Therefore, population management strategies should be adopted to prevent population decline from anthropogenic pressures and stochastic factors.
In vivo expression of anti-CD19/CD3 BiTE by liver-targeted AAV for the treatment of B cell malignancies
Authors: Yang Jianmin , Song Zhiqiang , Liu Ping , Zhang Dongliang , Wang Tao , Yue Wenqin , Geng Yuke , Liu Na , Wang Yang 
Published: January 2024

Abstract
Anti-CD19/CD3 bispecific T-cell engagers (CD19BiTE) has shown promising efficacy in patients with relapsed or refractory (r/r) B-cell malignancies. However, the short half-life of CD19BiTE necessitates long-term repeated administration with rest period, which not only increases the costs but also compromises the efficacy. Long-term and stable expression of CD19BiTE is crucial for achieving durable responses of B-cell malignancies. Adeno-associated virus (AAV)-mediated gene therapy has been demonstrated to achieve long-term efficacy for multiple diseases. Here, we generated liver-targeted AAV encoding CD19BiTE (AAV-CD19BiTE) and achieved sustained expression of CD19BiTE for more than six months. The results indicated that AAV-CD19BiTE could significantly reduce the tumor burdens in CD19+ B-cell malignancies xenograft model via a single injection of AAV-CD19BiTE. Meanwhile, more CD3+, CD4+, CD8+T, and activated CD8+T cells were observed in lymphoma microenvironment after therapy with AAV-CD19BiTE. In addition, AAV-CD19BiTE was also proved to have a strong antitumor activity in patient-derived xenograft (PDX) model of B-cell lymphoma. Altogether, in vivo expression of CD19BiTE circumvents the problem of short half-life and may hold promise as a new therapeutical strategy for CD19+ B-cell malignancies via a single injection of AAV.
Grating-Based Phase-Contrast Breast ComputedTomography at an Inverse Compton Source
Authors: Berthe Daniel , Heck Lisa , Resch Sandra , Dierolf Martin , Brantl Johannes , Benedikt Guenter , Petrich Christian , Achterhold Klaus , Pfeiffer Franz , Grandl Susanne , Hellerhoff Karin , Herzen Julia 
Published: January 2024

Abstract

The introduction of mammography screening programs has significantly reduced breast cancer mortality rates. Nevertheless, some lesions remain undetected, especially in dense breast tissue. Studies have shown that phase-contrast imaging can improve breast cancer diagnosis by increasing soft tissue contrast. Furthermore, grating-based phase-contrast imaging enables the simultaneous acquisition of absorption-, phase-contrast, and scattering, so-called dark-field images. The latter allows the classification of microcalcifications. In addition, breast computed tomography (BCT) systems can identify and discriminate overlapping but clinically relevant structures. This study investigates the benefit of combining grating-based phase-contrast with BCT. For this task, two Photon counting detector (PCD)s are used, and their performance is compared to a flat panel detector in terms of their resolution. The results demonstrate a resolution advantage of PCDs over flat panel detectors. Furthermore, we explore the potential of grating-based phase-contrast breast computed tomography (gbpc-BCT) with a breast phantom and a freshly dissected fibroadenoma. Improved image contrast could be achieved with radiation doses comparable to those used inclinical mammography.
Design and Implementation of Blockchain-Enabled Immutability Mechanism for Enhanced Machine Visual Data Integrity
Authors: Umar Hafiz Gulfam Ahmad , Jatoi Muhammad Uzair , Abid Muhammad Shoaib , Sulaman Muhammad , Iqbal Kashif 
Published: January 2024

Abstract

In the realm of Machine Vision, the progress in cinematography and image processing has empowered computers to comprehend images and videos. Cameras and infrared (IR) technology have become nearly omnipresent, facilitating the acquisition of crucial information about individuals and their surroundings. They are applied across various sectors, including high-security access, biometric cards, and modern surveillance systems embedded in the Internet of Things (IoT) ecosystem. However, an issue arises with the surge in information and its dissemination, raising concerns regarding safety, confidentiality, and secure storage as these systems interact with others, potentially leading to problems. To tackle these challenges, experts in computer vision are exploring the integration of blockchain technology. This article presents an overview of blockchain applications in computer vision, encompassing biometrics, video surveillance, and the sharing of image and video data. The objective is to demonstrate how blockchain could augment the safety, privacy, and reliability of these applications. The paper also delves into the tools and methodologies contributing to these goals, shedding light on prospective developments. Essentially, this review seeks to furnish clear insights into the collaboration between blockchain and computer vision. It achieves this by examining the latest advancements, existing challenges, and opportunities for leveraging visual data in a blockchain-driven environment. Ultimately, the focus is on understanding how these technologies can harmonize to influence the future landscape of Machine Vision.
Association between HOMA2 based beta-cell function or insulin resistance and long-term outcomes in kidney transplant recipients with type 2 diabetes
Authors: Maanaoui Mehdi , Debillon Florence , Lenain Rémi , Defrance Frédérique , Vantyghem Marie-Christine , Triempont Marine Van , Provôt François , Chetboun Mikael , Kerr-Conte Julie , Hamroun Aghiles , Frimat Marie , Raverdy Violeta , Pattou François , Hazzan Marc , Glowacki François 
Published: January 2024

Abstract

Type 2 diabetes (T2D) is a common comorbidity in kidney transplant recipients, representing a significant proportion of the candidate pool. Post-kidney transplantation management of T2D remains challenging, leading to inferior long-term outcomes compared to non-diabetic recipients. This study aimed to assess the association between Homeostatic Model Assessment 2 (HOMA2) derived insulin resistance and beta-cell function on kidney graft outcomes in T2D kidney transplant recipients. We conducted a monocentric retrospective study at the University Hospital of Lille, including all consecutive adult T2D patients who underwent kidney transplantation between January 2007 and December 2018. HOMA2 indexes (HOMA2 IR for insulin resistance and HOMA2 B for beta-cell function) were calculated at one-year post-transplantation. Primary endpoint was patient-graft survival and secondary endpoints were death-censored graft survival, patient survival and post-transplant metabolic control. Among 1620 kidney transplant recipients, 138 patients with T2D were included, with a median follow-up of 1189 days [688–2038]. HOMA2 IR was significantly associated with an increased risk of kidney graft failure or death (HR per unit = 1.10 (1.01–1.21)). Beta-cell function was not associated with graft prognosis, but decreased beta-cell function was associated with poorer metabolic control over time. This study highlights the significance of insulin resistance as a potential determinant of long-term outcomes in T2D kidney transplant recipients.
Community shifts in the coral Oculina patagonica holobiont in response to confinement, temperature and vibrio infections
Authors: Martin-Cuadrado Ana-Belen , Rubio-Portillo Esther , Antón Josefa 
Published: January 2024

Abstract

Background Extensive research on the diversity and functional roles of the microorganisms associated with reef-building corals has been promoted as a consequence of the rapid global decline of coral reefs attributed to climate change. Several studies have highlighted the importance of coral-associated algae (Symbiodinium) and bacteria and their potential roles in promoting coral host fitness and survival. However, the complex coral holobiont extends beyond these components to encompass other entities such as protists, fungi, and viruses. While each constituent has been individually investigated in corals, a comprehensive understanding of their collective roles is imperative for a holistic comprehension of coral health and resilience.Results A metagenomic analysis was performed to investigate the entire microbiome of the coral Oculina patagonica under various stress conditions, including aquaria confinement, heat stress, and Vibrio infections. Results revealed significant shifts in the abundances and richness of dominant bacterial phyla within the microbiome. In general, aquaria confinement led to an increase in Rhodobacteraceae, Flavobacteraceae, and Vibrionaceae families, accompanied by a decrease in Streptomycetaceae. Concurrently, it was observed that both the abundance and richness of microeukaryotic species significantly declined. Some fungi such as Aspergillus, Fusarium and Rhizofagus genera decrease (or increased, in the case of Saccharomyces). Furthermore, our analysis also identified a reduction in genes associated with antimicrobial compound production by the coral itself, as well as by Symbiodinium and fungi.Conclusion Our findings suggest that the interplay between microeukaryotic and prokaryotic components of the coral holobiont may be disrupted by stress conditions, such as confinement, increase of seawater temperature or Vibrio infection, leading to a dysbiosis in the global microbial community that may increase coral susceptibility to diseases. Further, microeukaryotic community seems to exert influence on the prokaryotic community dynamics, possibly through predation or the production of secondary metabolites with anti-bacterial activity.
Cognitive differences between two zebra species - the role of fission-fusion dynamics
Authors: Schaffer Alina , Caicoya Alvaro L. , Vadillo Iker Loidi , Widdig Anja , Holland Ruben , Amici Federica 
Published: January 2024

Abstract

In animals, high fission-fusion dynamics characterize groups in which individuals frequently split into subgroups of different size and composition, and may be linked to the enhancement of cognitive skills. However, this hypothesis has rarely been tested. Here, we compared two zebra species with different levels of fission-fusion dynamics, Chapman’s zebras (Equus burchelli chapmanni) and Grévy’s zebras (Equus grevyi), to assess potential differences in their cognitive skills. We tested 8 individuals of each species in experimental tasks assessing their object permanence, short-term memory, inference and quantity discrimination skills. Our results showed that Grévy’s zebras, which are characterized by higher levels of fission-fusion dynamics, performed better than Chapman’s zebras in tasks requiring inference and quantity discrimination skills. These findings provide preliminary support to the hypothesis that high fission-fusion dynamics are linked to the enhancement of specific cognitive skills also in taxa other than primates.
Quantum Ostrowski type inequalities for qa-differentiable strongly convex functions
Authors: Sahatsathatsana Chanokgan , Luangboon Waewta , Nonlaopon Kamsing 
Published: January 2024

Abstract
In this paper, we study some new quantum Ostrowski type inequalities for strongly convex functions by applying the notion of qa-differentiable. Moreover, we present the relationship between the newly established and already known inequalities. The newly established results are also proven to be generalizations of some existing results in the area of integral inequalities. Some numerical examples are provided to explain the result.
Chromium-free parenteral nutrition and their effects on chromium levels in very low birth weight infants
Authors: Tejedor María , Vetter-Laracy Susanne , Cobo Pilar , Bauça Josep Miquel , Robles Juan , Forteza Francisca , Beltran Eva 
Published: January 2024

Abstract
Background
As Chromium (Cr) is known to contaminate components of parenteral nutrition (PN), Cr-free PN is recommended for preterm infants. Exposure to Cr by PN in preterm infants is scarcely investigated.
Objective
To describe Cr levels in plasma (Crp) and urine (Cru) during the first month of life in premature newborns ≤ 1500 g of birthweight (BW) receiving PN and to evaluate the impact on postnatal clinical parameters.
Methods
A prospective observational study. Cr-free PN was administered at day 1 of life and continued until full enteral feeding with fortified breastmilk began. Crp levels at day 15 and 30 and Cru at day 30 of life were assessed according to demographic factors, biochemical markers and postnatal morbidity.
Results
97 infants had a median gestational age (GA) of 29.9 weeks, and median BW of 1205g. Medium Crp remained at 1.0 µg/L at 15 and 30 days (IQR 0.7–1.4 and 0.7–1.3 respectively). Premature babies < 26 weeks had a significantly higher Crp at one month than the remainder (P = 0.043) and a higher Cr elimination in urine (P = .026). Crp increased with prolonged PN (P < 0.001), even after adjusting for gestational age (P = .001). Laboratory parameters were not influenced by Crp or Cru, nor was morbidity.
Conclusion
Crp increases with days of PN even when a trace mineral supplement without Cr is used and the level reached maintains during the first month of life with the introduction of Cr supplemented breastmilk feeding. No relation to morbidity was observed.
Application of artificial intelligence-based modelling for the prediction of crop water stress index
Authors: Kumar Navsal , Shankar Vijay 
Published: January 2024

Abstract
The study evaluates the performance of three artificial intelligence (AI) techniques viz. support vector regression (SVR), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) for predicting the crop water stress index (CWSI) using relative humidity, air temperature, and canopy temperature. Field crop experiments were conducted on Wheat (during 2018, 2019) and Indian mustard (during 2017, 2018) to observe the canopy temperature in different irrigation levels. The experimentally obtained empirical CWSI was considered as the reference CWSI. Different configurations of ANN, SVR and ANFIS models were developed and validated with the empirical CWSI. The most optimal model structures for predicting CWSI were ANN5 (ANN with 5 hidden neurons), SVRQ (SVR with Quadratic kernel) and ANFIS2 (ANFIS with 2 membership functions) in Wheat; and ANN3 (ANN with 3 hidden neurons), SVRQ and ANFIS2 in Indian mustard. Based on the values of error statistics during validation, all three models presented a satisfactory performance, however, the efficacy of the models was relatively better in the case of Wheat. The model predictions at low CWSI values indicate deviations in the case of both crops. Overall, the study results indicate that data-driven-based AI techniques can be used as potential and reliable alternatives for predicting CWSI since the performance of the models is reliable for CWSI values commonly encountered in irrigation scheduling.
The effects of a Virtual Fracture Care review protocol on secondary healthcare utilization in trauma patients requiring non operative treatment: a retrospective cohort study
Authors: Willinge Gijs , Salentijn Dorien , Spierings Jelle , Twigt Bas , Goslings Carel , Veen Ruben van 
Published: January 2024

Abstract
Background The strain on healthcare resources in the Dutch trauma care system is rising. In response, a Dutch adaptation of the Virtual Fracture Care (VFC) review protocol, designed to optimize trauma care quality within resource constraint, has been implemented to sustain high-quality trauma care. This study aimed to evaluate the influence of the VFC review protocol on the utilization of secondary healthcare resources in adult trauma patients who received non-operative treatment for musculoskeletal extremity injuries.Methods This retrospective cohort study assessed the impact of a VFC review protocol on secondary healthcare utilization in adult trauma patients treated non-operatively for a musculoskeletal extremity injury. Patients treated between July 1, 2018 – December 31, 2019 (pre-VFC group), and January 1, 2021 – June 30, 2022 (VFC group) were included. Outcomes included follow-up appointments and involved healthcare professionals, radiographic imaging, and emergency department (ED) reattendances.Results A total of 3791 patients were included, comprising 1819 pre-VFC patients and 1972 VFC patients. Following VFC review, the number of follow-up appointments was reduced by 8% and a shift towards remote delivery of care occurred. Furthermore, VFC review led to a 9% reduction in follow-up radiographs and a 29% decrease in ED reattendances.Conclusion Utilization of a VFC review protocol for management of adult patients with a musculoskeletal extremity injury requiring non-operative treatment improves reduces secondary healthcare utilization compared to traditional treatment protocols. This protocol results in a reduction of follow-up appointments, a transition from face-to-face to remote care delivery, fewer follow-up radiographs, and a reduction of ED reattendances.
Star-Shaped Small Donor Molecules Based on Benzotriindole for Efficient Organic Solar Cells: A DFT Study
Authors: Shafiq Faiza , Mubarik Adeel , Rafiq Mahira , Alshehri Saad M. 
Published: January 2024

Abstract
Context
The purpose of the S01-S05 series of end-capped modified donor chromophores is to amplify the energy conversion efficiency of organic solar cells. Using quantum chemical modeling, the photophysical and photoelectric characteristics of the S01-S05 geometries are examined.
Method
The influence of side chain replacement on multiple parameters, including the density of states (DOS), molecular orbital analysis (FMOS), Exciton binding energy (Eb), Molecular electrostatic potential analysis, Dipole moment (µ), and photovoltaic characteristics including open circuit voltage (VOC), and PCE at minimal energy state geometries, has been investigated employing density functional theory along with TD-DFT analysis. The molar absorption coefficient (λmax) of all the proposed compounds (S01-S05) were efficiently enhanced by the terminal acceptor alteration technique, as demonstrated by their scaling up with the reference molecule (SR). Among all molecules, S04 has shown better absorption properties with a red shift in absorption having λmax at 845 nm in CHCl3 solvent and narrow energy gap (EG) 1.83 eV with least excitation energy (Ex) of 1.4657 eV. All created donors exhibited improved FF and VOC than the SR, which significantly raised PCE and revealed their great efficiency as OSC. Consequently, the results recommended these star-shaped molecules as easily attainable candidates for constructing extremely efficient OSCs.
A YOLOv5 landslide detection model based on multi-scale feature fusion
Authors: Wu YinLong , Shi Longlong , Xu Danchao , Wang Hongming 
Published: January 2024

Abstract

The fast, accurate identification of landslide areas is an important task in the context of big data from high-resolution remote sensing images. convolutional neural network (CNN), as the most commonly used feature extractor for identification of landslide areas in deep learning, still has many shortcomings. An important point is that CNN has to accumulate multiple layers before it can associate the whole image with different parts of the region because the convolutional kernel acts on the local field of perception. Compared with the continuous stacking of convolutions, the non-local operation of Transform directly calculates the relationship between two positions to capture long-range dependencies quickly. This paper combines the non-local information statistical operation operator with CNN, and the non-local operation operator with the global information acquisition capability in CNN. In addition, on the basis of ASPP (Atrous Spatial Pyramid Pooling), we replace the dilated convolution with a large convolution kernel and introduce the depthwise separable convolution (DSconv), which realizes the multi-scale fusion of convolution layers without increasing the amount of calculation. A non-local information statistical attention YOLOv5 model (NLA-YOLOv5) for landslide detection is proposed. Experimental results show that the NLA-YOLOv5 landslide detection accuracy reaches 80\% average precision (AP). Compared with the basic network YOLOv5, the precision, recall, and AP are increased by 7\%, 2\%, and 5\% respectively. The model detection speed reaches 69 f/s, which effectively improves the landslide detection ability to ensure the real-time detection of the model.