Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Data Analytics to Improve Nursing Home Quality

Background: There exists an array of quality performance measures for nursing homes. They can confuse consumers, administrators, and government regulators. Our methodology provides a unified multidimensional evaluation. Objective: To present a methodology to perform a multidimensional assessment of each nursing home within any specified group of nursing homes to aid policy makers, administrators, and consumers with a clear, easy-to-interpret evaluation of a nursing home quality performance. Methods: We use data envelopment analysis (DEA) to integrate several quality measures into a comprehensive benchmarking model. We present statewide results comparing DEA performance scores with the Five-Star rating using data from New York State (NYS) Department of Health. Results: In total, 212 of the 526 nursing homes performed as well as possible. Public nursing homes are most likely to lie on the frontier and have the highest average performance scores. The relationship between the DEA-based performance scores and the NYS Five-Star quality ratings is very weak. Conclusion: DEA is a comprehensive methodology for measuring nursing home quality. The DEA factor performance scores provide detailed information for individual nursing homes, enabling administrators to benchmark their facility's quality performance and to focus quality improvement efforts more effectively.
Comprehensive Analysis on Intrusion Detection Using Neural Network

: Intrusion detection is the process of detecting intrusion in network which it compromises the confidentiality integrity and availability of a resource. In this paper we mainly focused on neural network algorithm applied for detecting intrusion. Aim of our research paper is to determine which neural network classifies the attacks with high detection rate and low false alarm rate. Five different types of algorithm are used in this paper multi layer perceptron, generalized feed forward, principle component analysis, self organizing feature map and radial basis function.
Age, cognitive status, and accuracy of ADL self-reports in adults living with HIV

ABSTRACT Determination of functional capacity in cognitively impaired persons living with HIV (PLHIV) is pivotal to the accurate diagnosis of HIV-associated neurocognitive disorders (HAND). Functional data is typically collected through self-report. Reliability concerns arise with memory and executive functioning impairments, which could compromise the integrity of self-report and result in inaccurate HAND diagnoses. The current study tested the accuracy of older PLHIV functional reports through examination of concordance rates between self-report and caregiver’s (CG) report. Cross-sectional cognitive, mood, and functional status data were sampled from the Manhattan HIV Brain Bank. Participants and caregivers independently completed an Activities of Daily Living (ADL) questionnaire, producing 78 participant-caregiver dyads. Functional report concordance was operationalized by calculating differences between participant and CG ADL total scores. Assessment pairs differing by 2 or more points were considered to be discordant. Analyses revealed that one-third of the patient sample was discordant in the ADL report. ANOVA revealed that PLHIV overestimating their functional impairments, were significantly older, more educated, and more depressed than other participants. Global cognitive functioning was not associated with concordance. Thus, the majority of PLHIV were consistent with their caregivers’ ADL report, and older age and increased depressive symptomatology, but not cognitive status, were factors associated with discordance.
Fabrication of human myocardium using multidimensional modelling of engineered tissues

Biofabrication of human tissues has seen a meteoric growth triggered by recent technical advancements such as human induced pluripotent stem cells (hiPSCs) and additive manufacturing. However, generation of cardiac tissue is still hampered by lack of adequate mechanical properties and crucially by the often unpredictable post-fabrication evolution of biological components. In this study we employ melt electrowriting (MEW) and hiPSC-derived cardiac cells to generate fibre-reinforced human cardiac minitissues. These are thoroughly characterized in order to build computational models and simulations able to predict their post-fabrication evolution. Our results show that MEW-based human minitissues display advanced maturation 28 post-generation, with a significant increase in the expression of cardiac genes such as MYL2, GJA5, SCN5A and the MYH7/MYH6 and MYL2/MYL7 ratios. Human iPSC-cardiomyocytes are significantly more aligned within the MEW-based 3D tissues, as compared to conventional 2D controls, and also display greater expression of C ×43. These are also correlated with a more mature functionality in the form of faster conduction velocity. We used these data to develop simulations capable of accurately reproducing the experimental performance. In-depth gauging of the structural disposition (cellular alignment) and intercellular connectivity (C ×43) allowed us to develop an improved computational model able to predict the relationship between cardiac cell alignment and functional performance. This study lays down the path for advancing in the development of in silico tools to predict cardiac biofabricated tissue evolution after generation, and maps the route towards more accurate and biomimetic tissue manufacture.
Meeting Older Adults’ Food Needs: Interviews with Area Agency on Aging Staff, Food Bank Staff, and Older Adults

Abstract Area Agencies on Aging (AAAs) and food banks provide nutritious food for in-need older adults. The objective of this study was to identify successes, challenges, and opportunities associated with meeting the food needs of older adults. We used semi-structured telephone interviews with AAA nutrition staff (n = 5), food bank program coordinators (n = 5) and executives (n = 6), and older adults (n = 60) in Iowa. AAAs and food banks identified providing healthy food and client satisfaction as successes and funding and staff/volunteer capacity as challenges. Before the pandemic, the relationships between these organizations were limited, but both saw opportunities for collaboration. Older adults described coordination between AAAs and food banks during the COVID-19 crisis. AAAs and food banks play an important role in meeting older adults’ food needs, but their effectiveness is limited by challenges related to funding and capacity. There is a need to identify feasible and sustainable strategies for collaboration past this crisis.
Dual-Modulated Release of a Cytotoxic Photosensitizer Using Photogenerated Reactive Oxygen Species and Glutathione.

Reversible thiol-disulfide exchange chemistry is of particular interest in drug delivery systems. However, high levels of glutathione (GSH) in cancer cells are hardly distinguished from GSH in normal cells, resulting in unmanageable cytotoxic drug release. This study investigates the spatiotemporally-controlled irreversible degradation of Ir-based photosensitizer (TIr3)-encapsulating nanogels (IrNG) through the hyperoxidation of resulting intracellular thiols using reactive oxygen species (ROS). A highly cytotoxic TIr3 was stably encapsulated within IrNG through hydrophobic interactions and reversible crosslinking between its disulfide bonds and thiols in the absence of light, resulting in high biocompatibility under normal cellular conditions. However, upon photoirradiation, TIr3 generated high levels of ROS, irreversibly oxidizing the thiols to induce electrostatic repulsion between the polymer molecules, resulting in the TIr3 release and induction of cancer cell apoptosis.
Ant colony optimization

Ant colony optimization (ACO) is a metaheuristic that was originally introduced for solving combinatorial optimization problems. In this chapter we present the general description of ACO, as well as its adaptation for the application to continuous optimization problems. We apply this adaptation of ACO to optimize the weights of feed-forward neural networks for the purpose of pattern classification. As test problems we choose three data sets from the well-known PROBEN1 medical database. The experimental results show that our algorithm is comparable to specialized algorithms for feed-forward neural network training. Furthermore, the results compare favourably to the results of other general-purpose methods such as genetic algorithms.
Determining baseline anatomy knowledge among professional allied health students

Health professional students often struggle with anatomy coursework despite undergraduate coursework in anatomy. Educators must identify early on whether students may struggle in order to target remediation. The purpose of the study was to elucidate whether an assessment tool administered before the start of a professional anatomy course correlated with allied health students' course performance. Students over four years were given a quiz covering anatomy knowledge they were expected to know upon matriculation to their professional program. A supplemental data form was administered at the course's conclusion to identify prior anatomy experience and topics in which students felt deficient. Pre‐quiz scores significantly correlated with examination performance throughout the course. Students reported feeling most deficient in neurobiology (54.9%) and anatomy terminology (39.1%). Videos were created to target these deficient knowledge areas; students who watched the videos did better in course assessments than those who did not. Most respondents (98.0%) recommended students take an undergraduate anatomy course prior to starting a health professional program. These results indicate that a quiz assessing anatomy knowledge among matriculating students may identify students with the potential to struggle in a professional anatomy course early on. Responses outlined areas in which students felt deficient, which allows educators to target topics early with intervention tools such as the review videos in this study. Finally, most respondents strongly recommended undergraduate coursework in anatomy prior to starting a professional health program, which outlines students' recognition that a solid foundation in anatomical knowledge is important to success in professional programs.
Enhanced Fuzzy Controller for Nonlinear Systems: Membership-Function-Dependent Stability Analysis Approach

Fuzzy-model-based (FMB) control approach provides a systematic and effective way to control nonlinear systems. It has been shown by various applications (Lam et al., 1998; Lian et al., 2006; (b)Tanaka et al., 1998) that FMB control approach performs superior to some traditional control approaches. Based on the T-S fuzzy model (Sugeno & Kang, 1988; Takagi & Sugeno, 1985) the system dynamics of the nonlinear can be represented by some local linear models in the form of linear state-space equations. With the fuzzy logic technique, the overall system dynamics of the nonlinear plant is a fuzzy combination of the local linear models. Consequently, the fuzzy model offers a systematic way and general framework to represent the nonlinear plants in the form of averaged weighted sum of local linear systems. This particular structure exhibits favourable property to facilitate the system analysis and control synthesis. In general, the stability analysis for FMB control systems can be classified into two categories, i.e., membership function (MF)-independent (Chen et al.,1993; Tanaka & Sugeno, 1992) and MF-dependent (Fang et al., 2006; Feng, 2006; Kim & Lee 2000; Liu & Zhang, 2003a; Liu & Zhang, 2003b; Tanaka et al., 1998a; Teixeira et al.,2003) stability analysis approaches. Under the MF-independent stability analysis, the membership functions of both fuzzy model and fuzzy controller are not considered during stability analysis. The system stability is guaranteed to be asymptotically stable if there exists a common positive definite matrix to a set of stability conditions in the form of Lyapunov inequalities (Chen et al.,1993; Tanaka & Sugeno, 1992). The main advantages under the MF-independent analysis approach are 1). The membership functions of the fuzzy controller can be designed freely. Some simple and easy-to-implement membership functions can be employed to realize the fuzzy controller to lower the implementation cost. 2). The grades of membership functions of the fuzzy model are not necessarily known which implies parameter uncertainties of the nonlinear plant are allowed. Consequently, the fuzzy controller exhibits an inherent robustness property for nonlinear plant subject to parameter uncertainties. However, the membership function mismatch (both fuzzy model and fuzzy controller do not share the same membership functions) leads to very conservative stability analysis results. Furthermore, it can be shown that the fuzzy controller designed based on the stability conditions in (Chen et al.,1993; Tanaka & Sugeno, 1992) can be replaced by a liner controller.
Efﬁcient Ego Lane Detection for Various Lane Types

In this work, we present an ego lane detector designed for the use in automotive vision systems for personal light electric vehicles like electric bicycles, tricycles or scoot-ers. The approach is based on a combination of gradient-based line detection, color-based segmentation and geometrical rules, making the ego lane detector fast, but also robust to different scenes, including curves. Qualitative evaluation on over ﬁfty trafﬁc scenes show that the lane detector is able to ﬁnd a suitable approximation of the road area with an IoU of 75.71%.
regulates RNA modification and host cell innate immune responses during SARS-CoV-2 infection.

It is urgent and important to understand the relationship of the widespread severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2) with host immune response and study the underlining molecular mechanism. N 6 -methylation of adenosine (m6A) in RNA regulates many physiological and disease pro-cesses. Here, we investigate m6A modiﬁcation of the SARS-CoV-2 gene in regulating the host cell innate immune response. Our data show that the SARS-CoV-2 virus has m6A modiﬁcations that are enriched in the 3 0 end of the viral genome. We ﬁnd that depletion of the host cell m6A methyltransferase METTL3 decreases m6A levels in SARS-CoV-2 and host genes, and m6A reduction in viral RNA increases RIG-I binding and subsequently enhances the downstream innate immune signaling pathway and inﬂammatory gene expression. METTL3 expression is reduced and inﬂammatory genes are induced in patients with severe coronavirus disease 2019 (COVID-19). These ﬁndings will aid in the understanding of COVID-19 pathogenesis and the design of future studies regulating innate immunity for COVID-19 treatment. METTL3 is depleted, m6A levels of viral RNA are reduced, and RIG-I-bound viral RNA is increased, leading to enhanced RIG-I sensing and activation, which is followed by downstream activation of the NF- k B pathway and inﬂammatory gene expression. In addition, METTL3 depletion alters gene expression and m6A levels of several proviral host factors upon SARS-CoV-2 infection. RIG-I Western fmol of [ 13 C 5 ]-2 0 - O -methyladenosine, 9.7 fmol [ 13 C 5 ]-2 0 - O -methylcytidine, 3.3 pmol [ 15 N 3 ]-cytidine, 5.5 pmol of [ 15 N 2 ]-uridine, 5.1 fmol [ 13 C 5 ]-5-methylcytidine, and 5.6 fmol 13 C 5 -5-methyluridine. The enzymes in the digestion mixture were then removed by chloroform extraction. The aqueous layer was subsequently dried and reconstituted in 100 m L of ddH 2 O/ acetonitrile (1/9, v/v) to precipitate residual salts in the digestion mixture. After incubation at (cid:3) 20 (cid:2) C for 20 min, the mixture was centri-fuged, and the supernatant was collected, dried by Speed-Vac, reconstituted in water, and subjected to LC-MS/MS and MS/MS/MS analyses. nLC-nESI-MS/MS/MS experiments in scheduled in SRM mode were performed on an LTQ-XL linear ion trap mass spectrometer coupled with an EASY-nLC II (Thermo Fisher Scientiﬁc, San Jose, CA). The mass spectrometer was operated in the positive-ion mode, with the electrospray, capillary, and tube lens voltages being 2.0 kV, 12 V, and 100 V, respectively. Samples were loaded onto a 5 cm in-house packed porous graphitic carbon (PGC, 5 m m in particle size, Thermo Fisher Scientiﬁc) trapping column (150 m m i.d). Analytes were eluted onto a 20-cm Zorbax SB-C18 (5 m m in particle size, 100 A˚ in pore size, Michrom BioResources) analytical column (75 m m i.d.) at a ﬂow rate of 300 nL/min. The gradient employed was 0%–16% B in 5 min, 16%–22% B in 23 min, 22%–50% B in 17 min, 50%–90% B in 5 min,
Age-Related Differences in Arithmetic Problem-Veriﬁcation Strategies

To test age-related differences in split and problem-difficulty effects, adults between the ages of 20 and 80 years ( N 5 138) performed a simple and a complex inequality verification task (e.g., 6 1 3 < 11, 271 1 182 < 458; true or false? ). Split effects in verification tasks (i.e., better performance for large-split than for small-split problems) reflect strategy selection between nonexhaustive verification (e.g., evaluation of plausibility; estimation) and exhaustive verification (e.g., retrieval; calculation). Problem-difficulty effects (i.e., better performance for easy than hard problems) reflect calculation processing. Results showed decreased split effects across age groups, particularly in the complex task. Moreover, problem-difficulty effects did not vary across age groups. Age-related changes were mostly mediated by age-related declines in processing speed.
A novel method using the level of mobility to predict mortality in patients admitted for decompensated cirrhosis: A prospective study

To the editor, Frailty is characterized by decreased physiologic reserve predisposing to adverse outcomes[1] and is a significant burden to patients with advanced chronic liver disease (AdvCLD) affecting approximately 25% of outpatients and about 60% of inpatients. [2,3] The assessment of frailty is crucial as it is associated with falls, hospitalization, waitlist dropout, posttransplantation complications, and mortality. [3,4] Recent research has focused on the validation of physical performance metrics to identify frailty and its response to rehabilitation in AdvCLD. Clinically available tools include the 6‐minute walk test (6MWT) and the liver frailty index (LFI). Their use is recommended to standardize the diagnosis of frailty in outpatient/liver transplantation clinics. In the case of LFI, longitudinal changes carry significant prognostic implications. [5] Little attention has been paid to the study of frailty in hospitalized patients; however, LFI was recently shown to predict nonhome discharge and mortality among inpatients with AdvCLD. [3] The Johns Hopkins Highest Level of Mobility (JH‐HLM) is a simple and efficient method to measure physical activity in hospitalized patients. JH‐HLM is an equipment‐ free tool allowing rapid mobility assessment (Figure 1) and can be performed by any member of the health care team. We conducted a prospective single‐center cohort study to assess the ability of inpatient JH‐HLM score to predict mortality in patients with decompensated AdvCLD.
Cholest-4-En-3-One- (cid:2) 1 -Dehydrogenase, a Flavoprotein Catalyzing the Second Step in Anoxic Cholesterol Metabolism (cid:1)

The anoxic metabolism of cholesterol was studied in the denitrifying bacterium Sterolibacterium denitriﬁcans , which was grown with cholesterol and nitrate. Cholest-4-en-3-one was identiﬁed before as the product of cholesterol dehydrogenase/isomerase, the ﬁrst enzyme of the pathway. The postulated second enzyme, cholest-4-en-3-one- (cid:1) 1 dehydrogenase, was partially puriﬁed, and its N-terminal amino acid sequence and tryptic peptide sequences were determined. Based on this information, the corresponding gene was ampliﬁed and cloned and the His-tagged recombinant protein was overproduced, puriﬁed, and characterized. The recombinant enzyme catalyzes the ex- pected (cid:1) 1 -desaturation (cholest-4-en-3-one to cholesta-1,4-dien-3-one) under anoxic conditions. It contains approx-imately one molecule of FAD per 62-kDa subunit and forms high molecular
(2020). Association of prenatal alcohol exposure and offspring depression: A negative control analysis of maternal and partner consumption. Alcoholism: Clinical and Experimental Research.

Background: Previous research has suggested that intrauterine alcohol exposure is associated with a variety of adverse outcomes in oﬀspring. However, few studies have investigated its association with oﬀspring internalizing disorders in late adolescence. Methods: Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC), we investigated the associations of maternal drinking in pregnancy with oﬀspring depression at age 18 and 24 ( n = 13,480). We also examined partner drinking as a negative control for intrauterine exposure for comparison. Results: Oﬀspring of mothers that consumed any alcohol at 18 weeks gestation were at increased risk of having a diagnosis of depression (fully adjusted model: OR 1.17, 95% CI 1.02 to 1.34), but there was no clear evidence of association between partners’ alcohol consumption at 18 weeks gestation during pregnancy and increased risk of oﬀspring depression (fully adjusted model: OR 0.87, 95% CI 0.74 to 1.01). Postestimation tests found a positive diﬀerence between the association of maternal and partner alcohol use on oﬀspring depression, showing a stronger association for maternal compared with partner alcohol use (OR 1.41, CI 1.07 to 1.84). Conclusions: Maternal drinking in pregnancy was associated with increased risk of oﬀspring depres- sion at age 18. Residual confounding may explain this association, but the negative control comparison of paternal drinking provides some evidence that it may be causal, and this warrants further investiga- tion.
Understanding drivers of influenza vaccine hesitancy among pregnant women in China: evidence from an extended theory of planned behavior

ABSTRACT Background Pregnant women’s influenza vaccination uptake was low, although being recommended as a priority. Research design and methods We conducted a cross-sectional questionnaire survey in China from June to July 2021. Hierarchical regression analysis and structural equation modeling were performed based on the extended theory of planned behavior, in which attitudes, subjective norms, perceived behavioral control, and intention each affect vaccine hesitancy; response efficacy, knowledge, vulnerability, and severity were added as extended dimensions; vaccination history played as a moderator. Results Totally, 1283 pregnant women participated in this study. The intention existed as a mediator between attitude [βindirect = 0.142 (95% confidence interval (CI): 0.084, 0.206), P < 0.001], subjective norms [βindirect = 0.568 (95%CI: 0.424, 0.754), P < 0.001], perceived behavioral control [βindirect = 0.070 (95%CI: 0.025, 0.118), P = 0.004] and vaccine hesitancy. Further, indirect effect differences between the two dimensions of attitude (P < 0.001), perceived behavioral control (P < 0.001), and subjective norms were each statistically significant. Vaccination history did not moderate the association between attitude (P = 0.679), subjective norms (P = 0.645), and hesitancy. Conclusions The subjective norms dimension has a strong association with influenza vaccine hesitancy. Vaccination history was limited to reduce hesitancy.