Miracle-dz/UniFAR-FTUs huggingface dataset:
K-means clustering with manifold

K-means clustering is a popular conventional clustering algorithm. As it does not use the structure information of data sets, sometime the clustering result will be dissatisfied. Manifold learning algorithms can reveal the low-dimensional geometry structure of the data sets. In this paper, we combine K-means clustering algorithm with manifold learning algorithms into a coherent framework. We show the proposed algorithms KCM(K-means clustering with manifold) approaches can obtain good clustering results on UCI data sets. We also illustrate that the KCM clustering algorithms can be naturally extended to semi-supervised clustering. Experimental results also show the effectiveness of the semi-supervised clustering approaches.
What You Will Gain By Rounding: Theory and Algorithms for Rounding Rank

When factorizing binary matrices, we often have to make a choice between using expensive combinatorial methods that retain the discrete nature of the data and using continuous methods that can be more efficient but destroy the discrete structure. Alternatively, we can first compute a continuous factorization and subsequently apply a rounding procedure to obtain a discrete representation. But what will we gain by rounding? Will this yield lower reconstruction errors? Is it easy to find a low-rank matrix that rounds to a given binary matrix? Does it matter which threshold we use for rounding? Does it matter if we allow for only non-negative factorizations? In this paper, we approach these and further questions by presenting and studying the concept of rounding rank. We show that rounding rank is related to linear classification, dimensionality reduction, and nested matrices. We also report on an extensive experimental study that compares different algorithms for finding good factorizations under the rounding rank model.
Work disability and employment status among advanced chronic kidney disease patients

Introduction Chronic kidney disease (CKD) is a major public health issue with significant socioeconomic impacts. In Malaysia, the prevalence of CKD in 2018 was 15%. Complications of CKD such as anaemia, mineral bone disease, and infections led to frequent hospitalizations resulting in work disability and unemployment. To date, there is no data of employment status of CKD patients in Malaysia. Methods A cross-sectional study of patients with advanced CKD (stage 4 and 5 non-dialysis) treated in our centre. We interviewed those aged 18 to 60 years old who were selected based on random sampling of their employment status and associated factors. Work disabilities and quality of life were assessed using work productivity and activity impairment (WPAI-GH) questionnaire and kidney disease and quality of life (KDQOL-36) questionnaire. These questionnaires were assisted by the main investigators to aid participants in facilitating their response process. Result A total of 318 patients recruited, 53.5% were males, with a mean age of 49.0 ± 9.0 years old. The main cause of CKD was diabetes (67.0%) followed by hypertension (11.3%). Majority of them were obese (55.3%) with a mean body mass index of 28.81 ± 6.3 kg/m2. The mean household income was RM 4669.50 ± 3034.75 (USD1006.27 ± 653.99). The employment rate was 50% (n = 159). 86% of the unemployed patients were in B40 income category. Multiple Logistic Regression was performed on the significant factors affecting employment status showed one year increase in age increased 6.5% odds to be unemployed. Female and dyslipidaemia had 2.24- and 2.58-times higher odds respectively to be unemployed. Meanwhile, patients with tertiary level of education were 81% less odds to be unemployed. Patients with advanced CKD had a mean percentage of 24.35 ± 15.23 work impairment and 13.36 ± 32.34 mean percentages of face absenteeism due to the disease burden. Furthermore, patients who were unemployed had significant perceived symptoms and problem lists, effects, and burden of kidney disease (p<0.01) and showed poor mental and physical composites (p<0.01) as compared with those who were employed. Conclusion The employment rate of advanced CKD patients was low with half of patients lost their jobs due to the disease burden and had poor mental and physical composites of quality of life. This raises the concern for financial support for long term renal replacement therapy.
The Experiences of Multiple Sclerosis Patients ’ Family Caregivers at the First Hospitalization of Their Patients: A Qualitative Study Patient Preference and Adherence

Background and Aim: Being diagnosed with multiple sclerosis is usually accompanied by emotional trauma for patients and their families. The chronic, progressive, and unpredictable nature of the disease spells the patients ’ long-term need for care from their families. As soon as a diagnosis is made, family caregivers are faced with many challenges. The present study aims to identify family caregivers ’ experiences at the ﬁ rst hospitalization of their patients. Materials and Methods: The present study is a work of qualitative research and uses the conventional content analysis approach. It lasted from July 2019 to March 2020. The subjects were selected via purposeful sampling. To collect data, the researchers conducted in-depth, semi-structured interviews with 18 family caregivers of patients with multiple sclerosis. The collected data were analyzed using MAXQDA 2007. Results: Analysis of the data yielded three themes: peaceful environment, need for continuing full support, and religion-based coping strategies. Conclusion: The ﬁ ndings of the present study can be used to develop support programs that address family caregivers ’ problems and needs to assist them in accepting and coping with the conditions of their patients, thereby increasing the quality of care provided to patients with multiple
Organization and formation of the tight junction system in human epidermis and cultured keratinocytes.

Occludin and several proteins of the claudin family have been identiried in simple epithelia and in endothelia as major and structure-determining transmembrane proteins clustered in the barrier-forming tight junctions (TJ), where they are associated with a variety of TJ plaque proteins, including protein ZO-1. To examine whether TJ also occur in the squamous stratified epithelium of the interfollicular human epidermis we have applied several microscopic and biochemical techniques. Using RT-PCR techniques, we have identiried mRNAs encoding protein ZO-1, occludin and claudins 1, 4, 7, 8, 11, 12, and 17 in both tissues, skin and cultured keratinocytes, whereas claudins i and 10 have only been detected in skin tissue. By immunocytochemistry we have localized claudin-1, occludin and protein ZO-1 in distinct plasma membrane structures representing cell-cell attachment zones. While claudin-1 occurs in plasma membranes of all living cell layers, protein ZO-1 is concentrated in or even restricted to the uppermost layers, and occludin is often detected only in the stratum granulosum. Using electron microscopy, typical TJ structures ("kissing points") as well as some other apparently related junctional structures have been detected in the stratum granulosum, interspersed between desmosomes. Modes and patterns of TJ formation have also been studied in experimental model systems, e.g., during wound healing and stratification as well as in keratinocyte cultures during Ca2+-induced stratification. We conclude that the epidermis contains in the stratum granulosum a continuous zonula occludens-equivalent structure with typical TJ morphology and molecular composition, characterized by colocalization of occludin, claudins and TJ plaque proteins. In addition, cell-cell contact structures and certain TJ proteins can also be detected in other epidermal cell layers in specific cell contacts. The pattern of formation and possible functions of epidermal TJ and related structures are discussed.
Severity scoring index for Crimean-Congo hemorrhagic fever and the impact of ribavirin and corticosteroids on fatality.

BACKGROUND Patients infected with Crimean-Congo hemorrhagic fever (CCHF) virus present with a wide clinical spectrum. In observational studies, the effects of therapeutic agents are confounded by severity. We describe use of a clinical severity scoring index (SSI) for CCHF patients and assess the effect of ribavirin and corticosteroid therapy on the case-fatality rate, stratified by SSI. METHODS The study group included hospitalized patients who received a diagnosis of CCHF at the Infectious Diseases and Clinical Microbiology Clinic of Ankara Numune Education and Research Hospital between 2004 and 2011. The SSI included platelet count, bleeding, fibrinogen level, activated partial thromboplastin time, and somnolence. The effects of ribavirin and corticosteroid on the case-fatality rate were studied by univariate and multivariate analysis, stratified by SSI. RESULTS Two hundred eighty-one confirmed cases of CCHF were included in the study. Of 281 patients, 23 (8%) died. The mean age (±SD) of the patients was 47 ± 16 years. Forty-nine percent were female. The mean duration of stay at our clinic after onset of symptoms was 4.4 days, with a range of 1-14 days. In multivariate analysis of factors for the prediction of death, the SSI (odds ratio [OR], 3.27; 95% confidence interval [CI], 2.09-5.13) and ribavirin use (OR, 0.04; 95% CI, .004-.48) were found to be statistically significant factors. CONCLUSION The SSI is an accurate predictor of death and will therefore be a useful tool for case management and for drug-assessment studies. After stratification of cases by SSI, ribavirin was found to be effective in reducing the case-fatality rate, especially among moderately ill patients, whereas steroids were found to be beneficial particularly among patients with severe disease.
Optimizing the High-Pass Filter Addition Technique for Image Fusion

Pixel-level image fusion combines complementary image data, most commonly low spectral-high spatial resolution data with high spectral-low spatial resolution optical data. The presented study aims at refining and improving the High-Pass Filter Additive (HPFA) fusion method towards a tunable and versatile, yet standardized image fusion tool. HPFA is an image fusion method in the spatial domain, which inserts structural and textural details of the higher resolution image into the lower resolution image, whose spectral properties are thereby largely retained. Using various input image pairs, workable sets of HPFA parameters have been derived with regard to high-pass filter properties and injection weights. Improvements are the standardization of the HPFA parameters over a wide range of image resolution ratios and the controlled trade-off between resulting image sharpness and spectral properties. The results are evaluated visually and by spectral and spatial metrics in comparison with wavelet-based image fusion results as a benchmark.
In Vitro Interactions of Echinocandins with Triazoles Against Multidrug-Resistant Candida auris

ABSTRACT We determined the in vitro interactions between echinocandins and azoles against 10 multidrug-resistant Candida auris strains by use of a microdilution checkerboard technique. Our results suggest synergistic interactions between micafungin and voriconazole with fractional inhibitory concentration index (FICI) values of 0.15 to 0.5, and we observed indifferent interactions when micafungin was combined with fluconazole (FICI, 0.62 to 1.5). Combinations of caspofungin with fluconazole or voriconazole exhibited indifferent interactions. No antagonism was observed for any combination.
Progress and challenges in achieving tuberculosis elimination in India by 2025: A systematic review and meta-analysis

Background Tuberculosis (TB) continues to pose a significant public health challenge in India, which is home to one of the highest TB burdens worldwide. This systematic review and meta-analysis will aim to synthesize the anticipated progress and potential challenges in achieving TB elimination in India by 2025. Methods A comprehensive search will be conducted across multiple databases, including PubMed, Scopus, and Web of Science, to identify relevant studies. The eligibility criteria will encompass individuals diagnosed with TB in India, interventions targeting TB treatment, prevention, or control, and various comparator groups. Outcomes of interest will include incidence reduction, mortality rate, treatment success rate, barriers to TB care, and more. Both quantitative and qualitative data will be synthesized, and the risk of bias will be assessed using established tools. Outcomes The review is expected to provide a holistic understanding of the TB landscape in India, highlighting the effective interventions and potential challenges in the journey towards TB elimination. Conclusions While it is anticipated that significant progress will be made in the fight against TB in India, challenges are likely to persist. This review will offer a comprehensive roadmap for researchers, policymakers, and healthcare professionals, emphasizing the importance of continued efforts, innovative strategies, and a multi-pronged approach in achieving the goal of TB elimination in India by 2025.
Proliferation and Differentiation of Hematopoietic Cells and Preservation of Immune Functions

A limited number of pluripotent stem cells are mainly located in the bone marrow, and give rise to all blood cell 1ineages. Because of their relatively short lifespan, circulating cells must be continually replaced in living body throughout the life. The task performed by hematopoietic stem cells is shared in two main features, that is, the capacity of regeneration which prevents depletion of the cells and the ability of preservation of blood homeostasis. The mechanisms behind the critical choice between lineage-commitment and maintenance of the stem-cell pool involve a number of complex interactions between hematopoietic progenitor cells at different stages of maturation, stromal cells and their extracellular matrix, as well as a variety of stimulatory or inhibitory cytokines provided by the microenvironment.
FAQ: Questions Asked Frequently

We define and study the Functional Aggregate Query (FAQ) problem, which encompasses many frequently asked questions in constraint satisfaction, databases, matrix operations, probabilistic graphical models and logic. This is our main conceptual contribution. We then present a simple algorithm called "InsideOut" to solve this general problem. InsideOut is a variation of the traditional dynamic programming approach for constraint programming based on variable elimination. Our variation adds a couple of simple twists to basic variable elimination in order to deal with the generality of FAQ, to take full advantage of Grohe and Marx's fractional edge cover framework, and of the analysis of recent worst-case optimal relational join algorithms. As is the case with constraint programming and graphical model inference, to make InsideOut run efficiently we need to solve an optimization problem to compute an appropriate variable ordering. The main technical contribution of this work is a precise characterization of when a variable ordering is `semantically equivalent' to the variable ordering given by the input FAQ expression. Then, we design an approximation algorithm to find an equivalent variable ordering that has the best `fractional FAQ-width'. Our results imply a host of known and a few new results in graphical model inference, matrix operations, relational joins, and logic. We also briefly explain how recent algorithms on beyond worst-case analysis for joins and those for solving SAT and #SAT can be viewed as variable elimination to solve FAQ over compactly represented input functions.
Special section on automated verification of critical systems Some current topics in model checking

Model checking is a particular approach to property verification of systems. One describes a system in a mathematical model, expresses the properties one wishes to verify for the system in a formal language, and then checks whether the model satisfies the formal property. Invented 25 years ago, this approach is fully automatic and has therefore gained wide acceptance and is increasingly being used in commercial research & development units. Impediments remain on the road to successful technology transfer. For one, the size of models often increases exponentially in the number of variables or sub-models, preventing scalable automation. Abstracting a model to reduce its size can be a cost-effective way of addressing this. For another, systems and models may be subject to change, e.g. in an incremental design process. One then seeks cost-effective means of ascertaining that property verifications remain to be valid as models evolve. This special section presents current research on such abstraction and change management of model checking.
An empirically based alternative to DSM‐5's disruptive mood dysregulation disorder for ICD‐11

The World Health Organization (WHO)'s priorities for the development of the classification of mental and behavioural disorders in the ICD-11 include increasing its clinical utility in global mental health settings (1) and improving the identification and diagnosis of mental disorders among children and adolescents (2). An issue that has been hotly debated in the area of childhood psychopathology is the assessment, diagnosis and treatment of children with severe irritability and anger (3,4). Although virtually all children display irritable and angry behaviours at times, some children exhibit them more frequently and more intensely, to the extent that they become an impairing form of emotional dysregulation. Recent findings indicate that these children with chronic and severe irritability/anger have not been adequately identified through existing classification systems, are at an increased risk for particular negative outcomes, and have not received appropriate treatment. To the extent that ICD-11 can help clarify the clinical picture of irritability/anger, children and families will benefit from more accurate diagnoses, more useful prognoses, and more effective interventions. This paper provides a brief overview of the issue, followed by several possible options and the current proposal for the classification of childhood irritability/anger in ICD-11. This proposal represents a markedly different – but we believe more scientifically justifiable – solution to the problems in this area than that selected for DSM-5 (5).
C HAPTER 8 Using Cultural Models of Decision Making to Develop and Assess Cultural Sensemaking Competence

In this chapter we outline a theoretical framework for cultural sensemaking that connects high level metacognitive skills to region-specific knowledge. We also describe a novel instructional analysis and design approach, specifically developed to identify learning objectives and content for cultural sensemaking training. This approach leverages cultural models of decision making in the development and assessment of cultural competence. The cultural sensemaking framework describes a possible avenue through which culture-specific learning can contribute to culture-
Mining top-K high utility itemsets

Mining high utility itemsets from databases is an emerging topic in data mining, which refers to the discovery of itemsets with utilities higher than a user-specified minimum utility threshold min_util. Although several studies have been carried out on this topic, setting an appropriate minimum utility threshold is a difficult problem for users. If min_util is set too low, too many high utility itemsets will be generated, which may cause the mining algorithms to become inefficient or even run out of memory. On the other hand, if min_util is set too high, no high utility itemset will be found. Setting appropriate minimum utility thresholds by trial and error is a tedious process for users. In this paper, we address this problem by proposing a new framework named top-k high utility itemset mining, where k is the desired number of high utility itemsets to be mined. An efficient algorithm named TKU (Top-K Utility itemsets mining) is proposed for mining such itemsets without setting min_util. Several features were designed in TKU to solve the new challenges raised in this problem, like the absence of anti-monotone property and the requirement of lossless results. Moreover, TKU incorporates several novel strategies for pruning the search space to achieve high efficiency. Results on real and synthetic datasets show that TKU has excellent performance and scalability.
Probabilistic QoS and Soft Contracts for Transaction-Based Web Services Orchestrations

Service level agreements (SLAs), or contracts, have an important role in Web services. They define the obligations and rights between the provider of a Web service and its client, about the function and the quality of the service (QoS). For composite services like orchestrations, contracts are deduced by a process called QoS contract composition, based on contracts established between the orchestration and the called Web services. Contracts are typically stated as hard guarantees (e.g., response time always less than 5 msec). Using hard bounds is not realistic, however, and more statistical approaches are needed. In this paper we propose using soft probabilistic contracts instead, which consist of a probability distribution for the considered QoS parameter-in this paper, we focus on timing. We show how to compose such contracts, to yield a global probabilistic contract for the orchestration. Our approach is implemented by the TOrQuE tool. Experiments on TOrQuE show that overly pessimistic contracts can be avoided and significant room for safe overbooking exists. An essential component of SLA management is then the continuous monitoring of the performance of called Web services, to check for violations of the SLA. We propose a statistical technique for run-time monitoring of soft contracts.
Continuous Microfluidic Antisolvent Crystallization as a Bottom-Up Solution for the Development of Long-Acting Injectable Formulations

A bottom-up approach was investigated to produce long-acting injectable (LAI) suspension-based formulations to overcome specific limitations of top-down manufacturing methods by tailoring drug characteristics while making the methods more sustainable and cost-efficient. A Secoya microfluidic crystallization technology-based continuous liquid antisolvent crystallization (SCT-CLASC) process was optimized and afterward compared to an earlier developed microchannel reactor-based continuous liquid antisolvent crystallization (MCR-CLASC) setup, using itraconazole (ITZ) as the model drug. After operating parameter optimization and downstream processing (i.e., concentrating the suspensions), stable microsuspensions were generated with a final solid loading of 300 mg ITZ/g suspension. The optimized post-precipitation feed suspension consisted of 40 mg ITZ/g suspension with a drug-to-excipient ratio of 53:1. Compared to the MCR-CLASC setup, where the post-precipitation feed suspensions contained 10 mg ITZ/g suspension and had a drug-to-excipient ratio of 2:1, a higher drug concentration and lower excipient use were successfully achieved to produce LAI microsuspensions using the SCT-CLASC setup. To ensure stability during drug crystallization and storage, the suspensions’ quality was monitored for particle size distribution (PSD), solid-state form, and particle morphology. The PSD of the ITZ crystals in suspension was maintained within the target range of 1–10 µm, while the crystals displayed an elongated plate-shaped morphology and the solid state was confirmed to be form I, which is the most thermodynamically stable form of ITZ. In conclusion, this work lays the foundation for the SCT-CLASC process as an energy-efficient, robust, and reproducible bottom-up approach for the manufacture of LAI microsuspensions using ITZ at an industrial scale.