Miracle-dz/UniFAR-FTUs huggingface dataset:
Implications of the autoantibodies in the diagnosis of rheumatic diseases

Choroby reumatyczne to roznorodna pod wzgledem objawow klinicznych grupa schorzen, w patogenezie ktorych istotną role odgrywają procesy autimmunologiczne. Ich przejawem jest miedzy innymi obecnośc autoprzeciwcial w plynach ustrojowych, a w szczegolności w surowicy krwi. W pracy przedstawiono znaczenie poszczegolnych autoprzeciwcial w rozpozniu chorob reumatycznych. Omowiono glownie udzial przeciwcial przeciwjądrowych w diagnostyce chorob reumatycznych. Ponadto przedstawiono role innych autoprzeciwcial, w tym przeciw cyklicznie cytrulinowanemu peptydowi i czynnikowi reumatoidalnemu w rozpoznaniu reumatoidalnego zapalenia stawow, przeciwcial przeciw fosfolipidom w rozpoznaniu zespolu antyfosfolipidowego oraz przeciwcial przeciw cytoplazmie granulocytow obojetnochlonnych (ANCA) dla diagnozy zapalen naczyn.
Eff ectiveness of interspinous implant surgery: a systematic review and meta-analysis

Background: Despite an increasing implantation rate of interspinous process distraction devices (IPD) devices in the treatment of intermittent neurogenic claudication (INC), definitive evidence on the clinical effectiveness of implants is lacking. The main objective of this review was to perform a meta-analysis of all systematic reviews, randomized clinical trials and prospective cohort series to quantify the effectiveness of IPDs and to evaluate the potential side-effects. Methods: Data from all studies prospectively describing clinical results based on validated outcome scales and reporting complications of treatment of patients with INC with IPD placement. We searched MEDLINE, EMBASE, Web of Science, Cochrane (CENTRAL), CINAHL, Academic Search Premier, Science Direct up to July 2010. Studies describing patients with INC caused by lumbar stenosis, reporting complication rate and reporting based on validated outcome scores, were eligible. Studies with only instrumented IPD results were excluded. Results: Eleven studies eligible studies were identified. Two independently RCTs and eight prospective cohorts were available. In total 563 patients were treated with IPDs. All studies showed improvement in validated outcome scores after six weeks and one year. Pooled data based on the Zurich Claudication Questionnaire of the RCTs were more in favor of IPD treatment compared with conservative treatment (pooled estimate 23.2, SD 18.5-27.8). Statistical heterogeneity after pooled data was low (I-squared 0.0, p=0.930). Overall complication rate was 7%. Conclusions: As the evidence is relatively low and the costs are high, more thorough (cost-) effectiveness studies should be performed before worldwide implementation is introduced. interspinous implant surgery, interspinous implants, interspinous distraction devices, interspinous decompression interspinous process decompression, intermittent neurogenic neurogenic
Role of Interleukins and New Perspectives in Mechanisms of Resistance to Chemotherapy in Gastric Cancer

Gastric cancer (GC) is the fourth most common cancer in the world in terms of incidence and second in terms of mortality. Chemotherapy is the main treatment for GC. The greatest challenge and major cause of GC treatment failure is resistance to chemotherapy. As such, research is ongoing into molecular evaluation, investigating mechanisms, and screening therapeutic targets. Several mechanisms related to both the tumor cells and the tumor microenvironment (TME) are involved in resistance to chemotherapy. TME promotes the secretion of various inflammatory cytokines. Recent studies have revealed that inflammatory cytokines affect not only tumor growth, but also chemoresistance. Cytokines in TME can be detected in blood circulation and TME cells. Inflammatory cytokines could serve as potential biomarkers in the assessment of chemoresistance and influence the management of therapeutics in GC. This review presents recent data concerning research on inflammatory cytokines involved in the mechanisms of chemoresistance and provides new clues in GC treatment.
Curriculum development methodologies for English for occupational purposes in tourism management : a case study from a South African university of technology

The development of English for Occupational Purposes (EOP) curricula for universities of technology has become increasingly important. These institutions aim to produce graduates who can function effectively, upon entry into the occupational world. Since English is regarded as the global lingua franca, the demand for EOP is growing worldwide, so that, universally, employees can function in their fields of specialisation. Therefore, EOP wants and needs analyses have become imperative. This implies that the methodologies used to gather data from stakeholders in the development of EOP curricula should be effective. This paper takes a closer look at such methodologies, by exploring the perceptions of stakeholders on some of them, and the value that stakeholders could add to EOP curriculum development for Tourism Management at a South African university of technology.
Experimental Study on Microbial Induced Calcium Carbonate Precipitation to Enhance Reservoir Recovery

Background: Bacillus subtilis can produce urease in the presence of urea as the main carbon source and induce mineralization in the presence of precipitable cations. Objectives: The objective of our study was to demonstrate that Bacillus subtilis catabolizes glucose first in the presence of both glucose and urea carbon sources. Using its feature of catabolizing glucose first to delay the mineralization time, it proved its potential application in enhancing the recovery of heterogeneous reservoirs. Material and Methods: The metabolic process of Bacillus subtilis was monitored by changing the glucose content in the bacterial medium by UV spectrophotometer and pH meter. Using a non-homogeneous physical model, experiments were conducted to improve reservoir recovery by microbial mineralization after polymer oil drive. Results: The higher the glucose content in the medium, the longer the time for the pH of the bacterial solution to reach 7 and the longer the end of the logarithmic phase of growth. the glucose content of the 48 h medium was significantly correlated with the consumption of the bacteria and the quality of the precipitation. In the oil drive experiment the permeability of the high permeability model was reduced from 1200 md to 136 md with a reduction rate of 88.6 %, and the permeability of the low permeability model was reduced by 22 md, and the crude oil recovery was increased by 7.9 %. Conclusions: It was demonstrated that the addition of glucose to the culture medium retarded the mineralization of bacteria. Only 0.2 times the pore volume of the bacterial solution and the cementing solution is required to form an effective seal, thus improving the recovery of crude oil.
W&M ScholarWorks W

Technology integration in K-12 classrooms resembles the “hammer in search of a nail” phenomenon. While increasingly powerful and accessible technology tools certainly offer promising potential to impact teaching and learning, their implementation can often be contrived or incongruent with classroom practice and discipline-specific pedagogy. Digital moviemaking provides a unique opportunity to connect powerful, yet accessible, technology integration with core content and pedagogical practice within specific academic disciplines. This paper explores the digital disconnect between student use of technology in and out of school, the typical problems with integrating technology in K-12 schools, the potential of digital moviemaking, an examination of a digital documentary project in the social studies, and a discussion of next steps.
Soluble urokinase plasminogen activator receptor and decline in kidney function among patients without kidney disease

ABSTRACT Background Hospitalized patients are at an increased risk of developing kidney disease after discharge, often despite the absence of any clinical indicators during hospitalization. Soluble urokinase plasminogen activator receptor (suPAR) is a marker of systemic chronic inflammation that can be measured from routine blood samples. We determined whether elevated suPAR during hospitalization is associated with a decline in estimated glomerular filtration rate (eGFR) after discharge. Methods This was a retrospective longitudinal cohort study of patients without detectable kidney disease presenting to the emergency department on two separate occasions during a 3-year period. The association between suPAR and a decline in eGFR was assessed by linear mixed models for repeated measures adjusting for age, sex, C-reactive protein, sodium, diabetes, hypertension and cardiovascular disease. Results In total, 5124 patients (median age 65.9 years, 51.0% female) were included. The median suPAR was 2.9 ng/mL, the median time to readmission was 144 days and the expected rate of eGFR decline over this period was 5.1 mL/min/1.73 m2/year. Adjusting for other risk factors, patients with suPAR <3, 3–6 or ≥6 ng/mL had an expected eGFR decline of 4.3, 5.2 or 9.0 mL/min/1.73 m2/year, respectively. Similarly, patients with suPAR in the lowest (<2.4 ng/mL), middle (2.4–3.6 ng/mL) or highest (≥3.6 ng/mL) tertile had an expected eGFR decline of 4.2, 4.6 or 6.5 mL/min/1.73 m2/year, respectively. In both cases, a higher suPAR level was significantly and independently associated with a higher rate of eGFR decline (P < .001). Conclusions A higher suPAR level was associated with accelerated eGFR decline among patients presenting to the emergency department, suggesting that routine suPAR measurements may have utility for the early detection of kidney disease.
Collaborative Three-Tier Architecture Noncontact Respiratory Rate Monitoring Using Target Tracking and False Peaks Eliminating Algorithms

Monitoring respiratory rate (RR) is crucial for helping identify respiratory disorders. Devices for conventional respiratory monitoring are inconvenient and scarcely available. Recent research has demonstrated the ability of noncontact technologies, such as photoplethysmography and infrared thermography, to gather respiratory signals from the face and monitor breathing. However, current noncontact respiratory monitoring techniques have poor accuracy because they are sensitive to environmental influences like lighting and motion artifacts. Furthermore, frequent contact between users and the cloud in real-world medical application settings might cause service request delays and potentially the loss of personal data. We proposed a noncontact RR monitoring system with a cooperative three-layer design to increase the precision of respiratory monitoring and decrease data transmission latency. To reduce data transmission and network latency, our three-tier architecture layer-by-layer decomposes the computing tasks of respiration monitoring. Moreover, we improved the accuracy of respiratory monitoring by designing a target tracking algorithm and an algorithm for eliminating false peaks to extract high-quality respiratory signals. By gathering the data and choosing several regions of interest on the face, we were able to extract the respiration signal and investigate how different regions affected the monitoring of respiration. The results of the experiment indicate that when the nasal region is used to extract the respiratory signal, it performs experimentally best. Our approach performs better than baseline approaches while transferring fewer data.
A Brezis-Oswald approach for mixed local and nonlocal operator

In this paper we provide necessary and suﬃcient conditions for the existence of a unique positive weak solution for some sublinear Dirichlet problems driven by the sum of a quasilinear local and a nonlocal operator, i.e., L p,s = − ∆ p + ( − ∆) sp . Our main result is resemblant to the celebrated work by Brezis–Oswald [11]. In addition, we prove a regularity result of independent interest.
SSIVD-Net: A Novel Salient Super Image Classification&Detection Technique for Weaponized Violence

Detection of violence and weaponized violence in closed-circuit television (CCTV) footage requires a comprehensive approach. In this work, we introduce the \emph{Smart-City CCTV Violence Detection (SCVD)} dataset, specifically designed to facilitate the learning of weapon distribution in surveillance videos. To tackle the complexities of analyzing 3D surveillance video for violence recognition tasks, we propose a novel technique called, \emph{SSIVD-Net} (\textbf{S}alient-\textbf{S}uper-\textbf{I}mage for \textbf{V}iolence \textbf{D}etection). Our method reduces 3D video data complexity, dimensionality, and information loss while improving inference, performance, and explainability through the use of Salient-Super-Image representations. Considering the scalability and sustainability requirements of futuristic smart cities, the authors introduce the \emph{Salient-Classifier}, a novel architecture combining a kernelized approach with a residual learning strategy. We evaluate variations of SSIVD-Net and Salient Classifier on our SCVD dataset and benchmark against state-of-the-art (SOTA) models commonly employed in violence detection. Our approach exhibits significant improvements in detecting both weaponized and non-weaponized violence instances. By advancing the SOTA in violence detection, our work offers a practical and scalable solution suitable for real-world applications. The proposed methodology not only addresses the challenges of violence detection in CCTV footage but also contributes to the understanding of weapon distribution in smart surveillance. Ultimately, our research findings should enable smarter and more secure cities, as well as enhance public safety measures.
Implementing the Comparison-Based External Sort

In the age of big data, sorting is an indispensable operation for DBMSes and similar systems. Having data sorted can help produce query plans with significantly lower run times. It also can provide other benefits like having non-blocking operators which will produce data steadily (without bursts), or operators with reduced memory footprint. Sorting may be required on any step of query processing, i.e., be it source data or intermediate results. At the same time, the data to be sorted may not fit into main memory. In this case, an external sort operator, which writes intermediate results to disk, should be used. In this paper we consider an external sort operator of the comparison-based sort type. We discuss its implementation and describe related design decisions. Our aim is to study the impact on performance of a data structure used on the merge step. For this, we have experimentally evaluated three data structures implemented inside a DBMS. Results have shown that it is worthwhile to make an effort to implement an efficient data structure for run merging, even on modern commodity computers which are usually disk-bound. Moreover, we demonstrated that using a loser tree is a more efficient approach than both the naive approach and the heap-based one.
Non-reciprocal Wave Transmission In Integrated Waveguide Array Isolators

iii ACKNOWLEDGMENTS . v TABLE OF CONTENTS . vi LIST OF FIGURES . viii LIST OF TABLES . xii CHAPTER ONE: INTRODUCTION . 1 CHAPTER TWO: DEVICE DESIGN AND SIMULATION . 9 2.1 Design Consideration . 9 2.2 Wafer Epitaxial Structure . 11 2.3 Numerical Simulations. 13 2.4 Beam Propagation Simulations . 20 CHAPTER THREE: DEVICE FABRICATION . 32 CHAPTER FOUR: SAMPLE CHARACTERIZATION . 40 4.1 Measurements of the Loss and Internal Quantum Efficiency . 40 4.2 Measurements of the Optical Modal Gain and Differential Gain . 49 4.3 Measurements of the Linewidth Enhancement Factor . 55 CHAPTER FIVE: ALL-OPTICAL ISOLATOR SWITCH . 58
Quantitatively Visualizing Bipartite Datasets

As experiments continue to increase in size and scope, a fundamental challenge of subsequent analyses is to recast the wealth of information into an intuitive and readily-interpretable form. Often, each measurement only conveys the relationship between a pair of entries, and it is difficult to integrate these local interactions across a dataset to form a cohesive global picture. The classic localization problem tackles this question, transforming local measurements into a global map that reveals the underlying structure of a system. Here, we examine the more challenging bipartite localization problem, where pairwise distances are only available for bipartite data comprising two classes of entries (such as antibody-virus interactions, drug-cell potency, or user-rating profiles). We modify previous algorithms to solve bipartite localization and examine how each method behaves in the presence of noise, outliers, and partially-observed data. As a proof of concept, we apply these algorithms to antibody-virus neutralization measurements to create a basis set of antibody behaviors, formalize how potently inhibiting some viruses necessitates weakly inhibiting other viruses, and quantify how often combinations of antibodies exhibit degenerate behavior.
Efficient protocol for solving combinatorial graph problems on neutral-atom quantum processors

On neutral atom platforms, preparing specific quantum states is usually achieved by pulse shaping, i.e., by optimizing the time-dependence of the Hamiltonian related to the system. This process can be extremely costly, as it requires sampling of the final state in the quantum processor many times. Hence, determining a good pulse, as well as a good embedding, to solve specific combinatorial graph problems is one of the most important bottlenecks of the analog approach. In this work, we propose a novel protocol for solving hard combinatorial graph problems that combines variational analog quantum computing and machine learning. Our numerical simulations show that the proposed protocol can reduce dramatically the number of iterations to be run on the quantum device. Finally, we assess the quality of the proposed approach by estimating the related Q-score, a recently proposed metric aimed at benchmarking QPUs.
Relaxing strong compatibility at atomistic-continuum interface: Introduction to consistent linear coupling method

The most essential concept in concurrent multiscale methods involving atomistic-continuum coupling is how to define the relation between atomistic and continuum regions. A well-known coupling method that has been frequently employed in different concurrent multiscale methods such as quasicontinuum is the strong compatibility coupling (SCC). Although the SCC is a highly accurate coupling method, it constrains the mesh generation and restricts the reduction of computational cost. In this paper, first, we explain the notion of coupling models through the interface in the context of continuum mechanics for quasistatic problems. Then, the SCC is relaxed to overcome the downsides in the following approaches: a surface approximation approach and a force approximation approach. Based on the latter, we develop a brand new coupling method called consistent linear coupling (CLC). Overall, six different coupling schemes are introduced in line with the surface and force approximation approaches. The schemes are compared in terms of solving quasi-static 3D elastic nanoscale contact between an aluminum substrate and a diamond semi-sphere. Numerical results reveal that the CLC-based schemes are more accurate when compared with the surface approximation schemes. Furthermore, we demonstrate that by decreasing the size of interface elements, the accuracy of the CLC converges to and even exceeds the accuracy of SCC, but nevertheless with significantly less computational cost. In other words, in contrast to the SCC, the accuracy of the CLC is tunable, and it can be optimized proportional to the computational cost and accuracy. Finally, we sketch the idea of how the CLC can make the consistency near the atomisticcontinuum interface by eliminating ‘‘ghost forces. ” The energy of a one-dimensional atomic chain with a finite range of interaction is relaxed to validate the CLC method.
A Guide to Image and Video based Small Object Detection using Deep Learning : Case Study of Maritime Surveillance

Small object detection (SOD) in optical images and videos is a challenging problem that even state-of-the-art generic object detection methods fail to accurately localize and identify such objects. Typically, small objects appear in real-world due to large camera-object distance. Because small objects occupy only a small area in the input image (e.g., less than 10%), the information extracted from such a small area is not always rich enough to support decision making. Multidisciplinary strategies are being developed by researchers working at the interface of deep learning and computer vision to enhance the performance of SOD deep learning based methods. In this paper, we provide a comprehensive review of over 160 research papers published between 2017 and 2022 in order to survey this growing subject. This paper summarizes the existing literature and provide a taxonomy that illustrates the broad picture of current research. We investigate how to improve the performance of small object detection in maritime environments, where increasing performance is critical. By establishing a connection between generic and maritime SOD research, future directions have been identified. In addition, the popular datasets that have been used for SOD for generic and maritime applications are discussed, and also well-known evaluation metrics for the state-of-the-art methods on some of the datasets are provided.
Quenching in the Right Place at the Right Time: Tracing the Shared History of Starbursts, Active Galactic Nuclei, and Poststarburst Galaxies Using Their Structures and Multiscale Environments

This work uses multiscale environments and the structures of galaxies in the Sloan Digital Sky Survey as consistency checks on the evolution from starburst to quiescence at redshift z < 0.2. The environmental indicators include fixed-aperture mass overdensities (δ xMpc, x ∈ {0.5, 1, 2, 4, 8} h −1 Mpc), k-nearest neighbor distances, the tidal parameter, halo mass (M h ), and satellite/central classification. The residuals of the specific star formation rates (Δ SSFRs) are used to select starbursts (ΔSSFR > 0.6 dex, N ≈ 8600). Quenched poststarbursts (QPSBs) are selected using Hα < 3 Å emission and Hδ A > 4 Å absorption (N ≈ 750). The environments of starbursts and QPSBs are compared with those of active galactic nuclei (AGNs) and inactive galaxies of varying ΔSSFR. The environments of starbursts, AGNs, and QPSBs are unlike the environments of most quiescent galaxies (QGs). About 70%–90% of starbursts, AGNs with Hδ A > 4 Å, and QPSBs are centrals; ∼80%–90% have M h < 1013 M ⊙, and only ∼2%–4% have M h > 1014 M ⊙ or live in clusters. Their M h and satellite fractions are also different from those of QGs. All QPSBs are matched to some SFGs, starbursts, AGNs, and QGs of similar M ⋆, environments, concentration indices, and velocity dispersions. A significant fraction (∼20%–30%) of starbursts cannot be matched to QPSBs or QGs. The implications are that: (1) some starbursts do not quench rapidly; (2) the satellite-quenching mechanisms operating in high-density environments cannot account for most QPSBs; (3) the evolution from starbursts to QPSBs to QGs is not the dominant path at z < 0.2; and (4) starbursts are not mainly triggered by tidal interactions.