bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of the effectiveness and efficiency of clear aligners and fixed appliances in the pre-surgical orthodontic treatment of skeletal class III: a retrospective cohort study
Authors: Wei Zhi , Liu Linan , Gao Yanzi , Wu Zhouqiang , Wang Yan , Lai Wenli 
Published: June 2023

Abstract
Objective
This retrospective cohort study aims to compare the performance of clear aligners (CAs) with fixed appliances (FAs) in pre-surgical orthodontics of skeletal class III malocclusion patients.
Materials and Methods
Ninety-five patients were included in the study, and were divided into four groups: extraction with CA, extraction with FA, non-extraction with CA, and non-extraction with FA. The effectiveness of the treatments was measured using several parameters, including the PAR index, arch width coordination, incisor up-righting, root parallelism, root resorption, and bone dehiscence. The efficiency of the treatments was evaluated by comparing the duration of pre-surgical treatment and the number of follow-up visits.
Results
CAs were found to be as effective as FAs in the pre-surgical orthodontics of skeletal class III malocclusion. However, there are significant differences in treatment duration and follow-up visits between the two groups. The treatment duration was significantly shorter in CA groups than that in FA groups (409.21 ± 172.01 vs. 548.29 ± 208.14 days, P = 0.015 for non-extractions while 536.16 ± 195.78 vs. 768.32 ± 316.83 days, P = 0.009 for extractions). Similarly, the number of follow-up visits were statistically lower in the CA groups as well (7.58 ± 3.24 vs. 16.08 ± 5.28 visits, P = 0.001 for non-extractions, while 9.37 ± 3.73 vs. 22.39 ± 10.08 visits, P = 0.001 for extractions). Furthermore, the non-extraction with CA group showed better U1-SN reduction than the non-extraction with FA group (1.46 ± 5.57 VS -2.52 ± 6.11 degrees, P = 0.023).
Conclusions
CAs are an effective alternative to FAs for pre-surgical orthodontic treatment of skeletal class III malocclusion patients. Moreover, they offer high efficiency by shortening treatment duration and reducing the number of follow-up visits.
Clinical relevance
CAs can be a highly efficient and effective option in pre-surgical orthodontic of skeletal class III malocclusion.
Decreased filamentous actin and tight junction protein expression, and paracellular permeability in Frataxin-deficient human brain microvascular endothelial cells – implications for blood-brain barrier integrity in Friedreich's Ataxia
Authors: Smith Frances M. , Kosman Daniel J. 
Published: June 2023

Abstract
Background Friedreich’s Ataxia (FRDA) is the most prevalent inherited ataxia. FRDA results from loss of Frataxin (FXN), an essential mitochondrial iron trafficking protein. FRDA starts with an early burst of neurodegeneration of the dorsal root ganglion and cerebellar dentate nuclei, followed by progressive brain iron accumulation in the latter. End stage disease includes cardiac fibrosis that contributes to hypertrophic cardiomyopathy. The microvasculature plays an essential barrier role in both brain and heart homeostasis, thus an investigation of this tissue system in FRDA is essential to the delineation of the cellular dysfunction in this genetic disorder. Here, we investigate brain microvascular endothelial cell integrity in FRDA in a model of the blood-brain barrier (BBB).Methods We used lentiviral delivery of shRNA to knockdown FXN in a novel FRDA model in immortalized human brain microvascular endothelial cells (hBMVEC), which compose the microcapillaries of the BBB. We investigated known cellular pathophysiologies of FXN knockdown including energy metabolism, actin glutathionylation, and cell size. Furthermore, we investigated cytoskeletal architecture including the abundance and organization of filamentous actin (F-actin) and tight junction proteins, and quantified barrier physiology via transendothelial electrical resistance and fluorescent tracer flux.Results shFXN hBMVEC display the known FRDA cell morbidities including decreased energy metabolism, increased actin glutathionylation, and increased cell size. We also quantify a total loss of F-actin, and decreased abundance of F-actin at the cell membrane and in the cortical actin ring of shFXN hBMVEC. Furthermore, our model demonstrates a decreased production of the transmembrane tight junction proteins Claudin-5 and Occludin. Consistent with these phenotypes, we have identified increased paracellular permeability of a shFXN barrier system. These cells start with only 67% barrier integrity of the controls, and flux a paracellular tracer at 800% of physiological levels.Conclusion We identified that insufficient FXN levels in the hBMVEC BBB model causes changes in cytoskeletal architecture and tight junction protein abundance, co-incident with increased barrier permeability. Changes in the integrity of the BBB may be related to patient brain iron accumulation, neuroinflammation, neurodegeneration, and stroke. Furthermore, our findings implicate other barrier cells, e.g., the cardiac microvasculature, likely contributory also to disease pathology in FRDA.
Conservation Laws, Solitary Wave Solutions, and Lie Analysis for the Nonlinear Chains of Atoms
Authors: Rehman Muhammad Junaid U , Awrejcewicz Jan , Kudra Grzegorz 
Published: June 2023

Abstract
Nonlinear chains of atoms(NCA) are complex systems with rich dynamics, influencing various scientific disciplines. Lie symmetry approach is considered to analyze the NCA. The Lie symmetry method is a powerful mathematical tool for analyzing and solving differential equations with symmetries, facilitating the reduction of complexity and obtaining solutions. After getting the entire vector field by using the Lie scheme, we find the optimal system of symmetries. Using the optimal system we have converted assumed PDE into nonlinear ODE. The new auxiliary scheme introduces novel approaches to complement existing techniques, enhancing accuracy and simplifying computations. Travelling wave solutions describe wave-like propagation in systems, while graphical behavior visually represents relationships and patterns in data or mathematical models. The multiplier method enables the identification of conservation laws, fundamental principles in physics that assert certain quantities remain constant over time. Understanding these concepts contributes to a deeper comprehension of nonlinear chains of atoms and their dynamics, fostering advancements in related fields.
Simplifying Multimodal Composition: A Novel Zero-shot Framework to Visual Question Answering and Image Captioning
Authors: Liu Ethan 
Published: June 2023

Abstract
In this work, we perform zero-shot image captioning and visual question answering on images using a simple model composition framework, composing the dense image captioning capabilities of a visual language model with the powerful reasoning abilities of a large language model, ChatGPT. The proposed method utilizes zero-shot learning to enable cross-modal integration of vision and language in order to create a comprehensive visual language model. We achieve zero-shot state-of-the-art performance on VQAv2, demonstrating its effectiveness and high accuracy. The method's simplicity makes it highly scalable and adaptable to a wide range of applications, including integration from OpenAI’s multimodal model, GPT-4, with audio language models in the future. The results demonstrate the vast potential of this simple zero-shot framework in improving the accuracy and relevance of vision and language applications, constituting an effective approach to image captioning and visual question answering, as well as future multimodal composition.
Reparameterized Multiobjective Control of BCG Immunotherapy
Authors: Yue Rongting , Dutta Abhishek 
Published: June 2023

Abstract
Bladder cancer is a cancerous disease that mainly affects elder men and women. The immunotherapy that uses Bacillus of Calmette and Guerin (BCG) effectively treats bladder cancer by stimulating the immune response of patients. The therapeutic performance of BCG relies on drug dosing, and the design of an optimal BCG regimen is an open question. In this study, we propose the Reparameterized Multiobjective Control (RMC) approach for seeking an optimal drug dosing regimen and apply it to the design of BCG treatment. This approach utilizes constrained optimization based on a nonlinear bladder cancer model with impulsive drug instillation. We compare the performance of RMC with Koopman Model Predictive Control (MPC) and validate the efficacy of optimal BCG dosing regimens through numerical simulations, demonstrating the efficient elimination of cancerous cells. The proposed control framework holds the potential for generalization to other model-based treatment designs.
Neutrophil extracellular traps melt Peyer’s patches following stroke and myocardial infarction
Authors: Tuz Ali , Ghosh Susmita , Gallert Markus , Ttoouli Dimitris , Sata Sai , Ulusoy Özgür , Kraus Andreas , Zwirnlein Franziska , Kaygusuz Viola , Lakovic Vivian , Beer Alexander , Qefalia Altea , Cibir Zülal , Antler Medina , Korste Sebastian , Michel Lars , Rassaf Tienush , Kaltwasser Britta , Abdelrahman Hossam , Mohamud-Yusuf Ayan , Wang Chen , Haeusler Lars , Lueong Smiths , Stenzel Martin , Soehnlein Oliver , Frank Benedikt , Köhrmann Martin Köhrmann , Siveke Jens , Totzeck Matthias , Hoffmann Daniel , Grüneboom Anika , Hagemann Nina , Hasenberg Anja , Sickmann Albert , Chen Jianxu , Hermann Dirk , Gunzer Matthias , Singh Vikramjeet 
Published: June 2023

Abstract

Sterile tissue injury after stroke causes lymphocyte contraction in lymphoid tissues and may decrease circulating IgA-levels. Intestinal Peyer’s patches (PP) harbor large numbers of IgA+ B cell precursors and plasma cells. Whether and how tissue injury triggers PP-B cell death, thereby mediating IgA-loss, is unknown. We found decreased circulating IgA levels in stroke and myocardial infarction patients. Experimental stroke and myocardial infarction in mice phenocopied the human situation. Decreased plasma and fecal IgA were accompanied by rapid and macroscopic shrinkage of PP caused by substantial losses of PP-resident IgA+ precursors and plasma cells in mice. Tissue injury induced neutrophil activation endowed with the release of toxic neutrophil extracellular traps (NETs). Antibody-mediated or genetically-induced neutrophil loss, digestion of NETs, or inhibition of their release by the Gasdermin D blockade completely prevented lymphocyte loss and PP shrinkage. We also identified NETs in the plasma of stroke and myocardial infarction patients. Hence, tissue injury induces systemic NET-release, which might be targeted to maintain immune homeostasis at mucosal barriers.
Dissipative Control for Nonlinear Singularly Perturbed Systems with Dynamic Quantization and Actuator Failure
Authors: Chang Xiao-Heng , Jin Xue 
Published: June 2023

Abstract
The manuscript discusses the dissipative control of nonlinear singularly perturbed systems (SPSs) with dynamic quantization and actuator faults. The nonlinear singularly perturbed plant is described by a class of fuzzy SPSs with using Takagi–Sugeno (T–S) fuzzy model. Considering the impact of quantization and actuator failures may occur in the networked communication channel, the asymptotic stability and dissipativity for quantized closed-loop system are analyzed, and some sufficient conditions are given to synchronously design the -independent state feedback controller and the dynamic parameter. Furthermore, the maximum stability bound ¯ is found by giving a new short search algorithm. Finally, a tunnel diode circuit system is simulated in order to prove the feasibility and effectiveness of the proposed method.
Broadening the genetic base of peanut breeding using incompatible wild species
Authors: Jiang Chun Jiao , Li Jia Kai , Sun Hao Jie , Wang Zhi Wei , Yang Zhen , Wang Chuan Tang 
Published: June 2023

Abstract
The cultivated peanut is a major edible oilseed crop. Remarkable success has been achieved in breeding new peanut varieties. The narrow genetic base of the cultivated peanut, as the result of a series of six bottlenecks in evolution, however, makes it increasingly difficult to develop breakthrough varieties solely by intraspecific hybridization. For this reason, research has been carried out to exploit incompatible wild Arachis species. In this paper, we report for the first time a genetic diversity assessment of 30 progenies from intersectional crosses between high-oleic peanut cultivar Huayu 665 and two wild species, A. paraguariensis or A. appresipilla, together with 32 cultivar materials, and 29 wild accessions using transposon element markers. The hybrids had higher genetic diversity than the cultivars, broadening the genetic base of peanut breeding. Hybrid progenies with improved insect pest resistance and both high oleic acid and high oil/protein were obtained. Hopefully, peanut varieties with high and stable yield and quality will be bred using crop wild relatives in the near future.
ACNN: Arbitrary Traces Attack based on LeakageArea Detection
Authors: Xiao Chong , Tang Ming 
Published: June 2023

Abstract
Deep Learning-based Profiled Side-Channel Analysis (DL-PSCA) has become an important research method in the field of Side-Channel Analysis (SCA). The current research of DL-PSCA is based on publicly available datasets. Both the training set and attack set are derived from the same batch of collected data and are well-organized, resulting in the disregard of differences arising from the condition of trace measurement that exists in actual attack scenarios. Specifically, the timing of measurement is inconsistent due to the fact that attackers have different levels of control in terms of profiling and attacking devices. To bridge the gap, we assert that it is necessary for a network to explicitly identify areas of leakage and subsequently predict the leaked values. By decomposing conventional DL-PSCA into tasks of finer granularity, we have been able to restructure DL-PSCA as a regression task that operates in asliding window manner. Therefore, we present Arbitrary Convolutional Neural Network (ACNN) that is composed of a feature extractor and a regressor, which scans the input trace of arbitrary length for leakage localization and leakage value prediction in a sliding window way. We use the public datasets DPAv4.2 and ASCAD respectively to simulate variable traces and verify the effectiveness of our approach on unmasked and masked devices. The experiments show that no matter if the implementation is protected with masking scheme, the network can accurately identify the leakage areas and predict the leaked values. In terms of key recovery performance, our architecture is on par with state-of-the-art.
Design of All Digital Phase Locked Loop with Digitally Controlled Oscillator Using 45nm for Low Power Consumption
Authors: Yadav Lalita , Duhan Manoj 
Published: June 2023

Abstract
A low-power consuming device All Digital Phase Locked Loop (ADPLL) has grown more appealing due to improved verifiability, flexibility, reliability, and portability over various processes as well as improved noise resistance. ADPLL is a negative feedback system that creates a high-frequency clock signal in the phase relationship to a low-frequency reference signal. In this proposed work, an ADPLL was developed using 45 nm CMOS technology with a Digital Control Oscillator (DCO) to fulfill the requirements of system implementation because the DCO can attain both better resolution and a large bandwidth spectrum. The Cadence Virtuoso software is employed for verification and simulation to affirm its features and functions. Control bits created by the Digital Loop Filter (DLF) are utilized to electronically regulate the DCO output frequency range. The loop is deemed to be held at 12ns once the reference signal and divided output clock frequency have been associated. The simulation results showed that the designed ADPLL achieves a (peak-to-peak) p2p jitter of 60 ps between 880 MHz − 1 GHz and a root means square (RMS) value of 1ps. The layout area estimated is 1.188 mm2. The DCO consumes 288 \(\mu\)W and the overall energy consumption is 2.66 mW with a power source of 1.2 V.
Discovery and clinical characteristics of obesity and non-obesity obstructive sleep apnoea hypertension syndromes
Authors: Hu Chunsong , Li Juxiang , Wu Yanqing , Wang Menghong , Tkebuchava Tengiz , Wu Qinghua 
Published: June 2023

Abstract
Background Obesity, obstructive sleep apnoea (OSA), and hypertension are major clinical risk factors. The tripartite coexistence was referred to as OOH syndrome (OOHS) and that of non-obesity as NOOHS.
Objective This study reported the discovery and clinical characteristics of OOHS and NOOHS.
Methods A total of 163 patients, aged 23-74 years, were randomly enrolled at the outpatients department who were either obese or non-obese, suffered OSA and hypertension. Subjects with a body mass index (BMI) of ³25 (Chinese criteria), of ³27 (criteria of this study), and of ³30 (WHO criteria) were defined as obese or non-obese, respectively. Cases with snoring were classified as mild, moderate and severe OSA by using the apnoea-hypopnoea Index where mild is 5-15, moderate is 15-30, and severe is >30. Daytime blood pressure (BP) was measured to assess any correlation. And analysis of long-term follow-up outcomes.
Results Seven typical cases with OOHS and NOOHS were assessed and presented. 163 cases with OOHS and NOOHS have similar or different clinical characteristics. Both potentially suffer from major adverse cardiocerebrovascular events (MACCE), which are associated with increased BMI, OSA, and BP. Long-term follow-up showed the clinical outcomes consistently linked to patients’ lifestyle and adherence to treatment.
Conclusion This study suggested that both OOHS and NOOHS are high risk conditions in MACCE. There is an urgent need for early healthy lifestyle interventions and treatments. But whether these patients are easy to suffer from cardiovascular aging, heart failure, neurodegenerative diseases, or cardiovascular, diabetes, and cancer strips, it needs a longer-term follow-up.
Rural Households’ Vulnerability to Climate Variability and Adaptation Strategies In the case of Begemdir District, Amhara Region, Ethiopia.
Authors: mencho Birhanu , Tefera Endeshaw Yeshiwas , Terefe Baye 
Published: June 2023

Abstract

Vulnerability to climate change has become the greatest challenge in our world due to its adverse impacts on ecosystems, economies, and societies. Thus, these studies assessed rural households’ vulnerability to climate variability and adaptation responses in Guna Begemdir District. Primary data was collected from three kebeles by selecting 120 sample households using the systematic random sampling method. Moreover, farmers’ perceptions, adaptation strategies, and socioeconomic and institutional factors were determined through household surveys, key informant interviews, and secondary data collected through document analysis. Monthly, seasonal, and annual rainfall and temperature data were collected for two metrological stations for the period 1983–2018 to assess climate variability and identify climate-related risks. To assess farmers’ perceptions and adaptation strategies being used by farmers. Finally, a logistic regression model was employed to identify factors that affect farmers’ decisions to adapt and implement given adaptation strategies to tackle the impacts of climate variability. Results from the study showed the presence of significant rainfall variability during Belg months (March–May months) compared to Kiremt months (June–August). The rainfall series for the annual time scale showed mixed trends (increase and decrease). However, the majority of farmers in Guna Begemdir District perceived that the rainfall had been decreasing for the last 36 years. They also perceived an increase in temperature, a delay in rainfall onset during the growing season, rainfall occurrence during harvesting time, an early end to rainfall during the growing season, pest occurrence, and a rainfall shortage. The overall LVI and IPCC-LVI score in this study is 0.49, which implies that the study area is vulnerable to the impacts of climate variability. In response to the perceived climate risks (water shortage, flood risks, and soil erosion), farmers in the study area adopted many types of soil and water conservation strategies. Thus, the study identified gender of household heads, size of active household members, household distance from farmland and market, access to credit, extension support, and agroclimate zone type as significant determinant factors that affect farmers’ adoption of climate change and variability.
Self-supervised Re-identification for Online Joint Multi-object Tracking
Authors: Li Shuman , Yang Longqi , Tan Huibin , Wang Binglin , Huang Wanrong , Liu Hengzhu , Yang Wenjing , Lan Long 
Published: June 2023

Abstract

Recently, the bottleneck of multi-object tracking is shifting from detection performance to association performance. However, research on association algorithms requires a large number of identity labels, which are more expensive than detection labels. To circumvent the need for identity labels, we propose a Self-supervised Re-ID module for online joint Multi-Object Tracking (SR-MOT). Specifically, we design an appearance discriminator to judge identities with only the readily detection hypotheses and then associate the same identity to the final trajectory. To train the discriminator without using identity labels, we construct negative pairs by the detections appear in the same video frame as they definitely belong to different identities, the positive pairs are naturally constructed by several useful data augmentation methods. In addition, our proposed method balances the conflicting tasks of detection and re-ID by using different output features and we dynamically adjust the loss weights of detection and re-ID based on the information content of the loss distribution to promote balance between the two tasks from the feature level and optimization methods.In our evaluation on the MOT Challenge benchmark, we show that our SR-MOT performs comparably to supervised methods and is significantly superior to other unsupervised methods. Our proposed method provides a practical solution for multi-object tracking without the need for identity labels, making it more accessible for real-world applications.
Multiscale aware classification of COVID-19 from Chest X-Ray using a spatially weighted atrous spatial pyramid pooling CNN
Authors: Fetoh Mahmoud Z. , Amin Khalid M. , Hamad Ahmed M. 
Published: June 2023

Abstract
COVID-19 is a severe respiratory tract infections which can range from mild to lethal. COVID-19 caused by SARS-CoV-2 can readily spread through direct or indirect contact with an infected person. This high spread rate pressure on the health care systems and requires non time-consuming methods for diagnosing. Convolutional Neural Networks (CNN) show a great success for various computer vision tasks. However, CNN like many computer vision models is a scale-variant model and requires expensive computation. In this paper, a novel micro architecture is proposed for multiscale feature extraction and classification. Proposed CNN learns multiscale features using a pyramid of shared convolution kernels with different dilation, atrous, rates. Proposed CNN is an attention based mechanism that is used to guide and select correct scale for each input. Proposed CNN is an end-to-end trainable Network. It achieved a 0.9929 for F1-score tested on QaTa-Cov19 benchmark dataset with a total of 5,040,571 trainable parameters.