Miracle-dz/UniFAR-FTUs huggingface dataset:
Sparse Deep Neural Networks for Embedded Intelligence

Deep learning is becoming more widespread due to its power in solving complex classification problems. However, deep learning models often require large memory and energy consumption, which may prevent them from being deployed effectively on embedded platforms, limiting their application. This work addresses the problem of memory requirements by proposing a regularization approach to compress the memory footprint of the models. It is shown that the sparsity-inducing regularization problem can be solved effectively using an enhanced stochastic variance reduced gradient optimization approach. Experimental evaluation of our approach shows that it can reduce the memory requirements both in the convolutional and fully connected layers by up to 300X without affecting overall test accuracy.
Design, synthesis, and biologic evaluation of novel galloyl derivatives as HIV‐1 RNase H inhibitors

Human immunodeficiency virus (HIV) reverse transcriptase (RT)‐associated ribonuclease H (RNase H) remains as the only enzyme encoded within the viral genome not targeted by current antiviral drugs. In this work, we report the design, synthesis, and biologic evaluation of a novel series of galloyl derivatives with HIV‐1 RNase H inhibitory activity. Most of them showed IC50s at sub‐ to low‐micromolar concentrations in enzymatic assays. The most potent compound was II‐25 that showed an IC50 of 0.72 ± 0.07 μM in RNase H inhibition assays carried out with the HIV‐1BH10 RT. II‐25 was 2.8 times more potent than β‐thujaplicinol in these assays. Interestingly, II‐25 and other galloyl derivatives were also found to inhibit the HIV IN strand transfer activity in vitro. Structure–activity relationships (SAR) studies and molecular modeling analysis predict key interactions with RT residues His539 and Arg557, while providing helpful insight for further optimization of selected compounds.
6. Glycemic Targets: Standards of Medical Care in Diabetes—2019

The American Diabetes Association (ADA) “Standards of Medical Care in Diabetes” includes ADA’s current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA’s clinical practice recommendations, please refer to the Standards of Care Introduction. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes. org/SOC.
Analysis of the Mediating Role of Self-Efficacy and Self-Esteem on the Effect of Workload on Burnout’s Influence on Nurses’ Plans to Work Longer

At the present time, we know that there is a positive relationship between self-efficacy and self-esteem in which positive beliefs about one’s own efficacy increase one’s sense of self-worth as stressful situations of a heavy workload are coped with successfully, and this, in turn, affects the nurses’ plans to work longer. Analyze the mediating role of self-efficacy and self-esteem in the effect of workload, measured as the number of users attended to during a workday, on burnout in nursing professionals. A sample of 1307 nurses aged 22 to 60 years who were administered the Brief Burnout Questionnaire, the General Self-Efficacy Scale, and the Rosenberg Self-Esteem Scale, and workload, measured as the number of users attended to during the workday. The results show that professionals with high levels of self-efficacy also scored higher on global self-esteem. Burnout correlated negatively with both variables (self-efficacy and self-esteem). Three clusters were found with the variables (self-efficacy, self-esteem, and workload) showing significant differences in burnout scores among clusters. Self-efficacy and self-esteem function as buffers of the negative effects of workload on burnout. Organizations should design interventions for promoting the personal resources of their workers through training activities and organizational resources (e.g., redesigning job positions) to promote satisfaction and wellbeing of employees, making their stay at work greater.
Industry funding effect on positive results of probiotic use in the management of acute diarrhea: a systematized review

Several investigations have found that industry-funded studies tend to inform results favoring the sponsored products. The pressure to demonstrate that a drug or a product causes a favorable outcome may result in investigation biases from industry-funded research. One example of this could be found in the probiotic research funded by the industry. The aim of this study was to assess the effect of industry funding on positive outcomes of the use of probiotics in the management of acute diarrhea. A systematized review of clinical trials on the use of probiotics in the management of acute diarrhea was performed. The associations between the source of funding, clinical outcomes, probiotic genus, and quality of the study were assessed using the &khgr;2-test and Fisher’s exact test. Sixty-six clinical trials were included; 27 were industry funded, 18 were nonindustry funded, and 21 did not disclose their funding source. There were 48 positive and 30 negative clinical outcomes. There was no significant association between the source of funding and clinical outcomes (P=0.491). No association between the rest of the studied variables and outcomes was observed either (P>0.05). In clinical trials on the use of probiotics in the management of acute diarrhea, the source of funding has no influence on positive clinical outcomes.
To What Extent Do Practitioners Need to Treat Stereotypy During Academic Tasks?

Researchers frequently argue that a child’s engagement in stereotypy may compete with his ability to acquire academic skills, engage in appropriate social interactions, or both; however, few studies have directly tested these suppositions. We used a five-phase assessment to evaluate the extent to which behavioral interventions with a progressively greater number of components were necessary to decrease stereotypy and increase correct responding during academic instructions for five children diagnosed with autism spectrum disorders. For one participant, stereotypy decreased when instructors provided standard instruction without specific intervention for stereotypy. For two participants, stereotypy decreased when instructors provided standard instruction plus antecedent intervention for stereotypy with continuous music. For another participant, stereotypy decreased when instructors provided enhanced consequences for correct responding during standard instruction without either antecedent or consequent intervention for stereotypy. For the final participant, stereotypy decreased and correct responding increased when instructors provided standard instruction and consequent intervention for stereotypy.
Optimization of the Extraction Conditions and Biological Evaluation of Dendropanax morbifera H. Lev as an Anti-Hyperuricemic Source

Dendropanax morbifera H. Levis a medicinal plant native to South Korea, East Asia, and South America. Among some 75 species, one species grows in Korea. In previous studies, D. morbifera extracts with anti-oxidant, anti-inflammatory, anti-complementary and anti-cancer activities were reported. The present study aims to investigate optimization of extraction and evaluation of anti-hyperuricemic effects of D. morbifera leaf and the phytochemicals contained therein. Ethanol and hexane extract were found to display the best xanthine oxidase inhibition among six types of solvent and water extract. The antioxidant effect of the ethanol extract was superior to that of the hexane extract. The DPPH radical scavenging effect of the ethanol and hexane extracts were 81.52 ± 1.57% and 2.69 ± 0.16. The reducing power of the ethanol and hexane extracts were 9.71 ± 0.15 and 0.89 ± 0.01 mg/g equivalent of gallic acid. Total phenols of the ethanol and hexane extracts were 6.53 ± 0.16 and 0.63 ± 0.001 mg/g equivalent of gallic acid. In addition, we compared the two marker compounds from D. morbifera, chlorogenic acid and rutin, which were determined in the ethanol extract at 0.80 ± 0.03% and 0.52 ± 0.01%, respectively. We found that the ethanol extracts showed better xanthine oxidase inhibition than hexane extracts. Especially, ethanol extracts showed higher antioxidant activity than hexane extracts. Based on these results, we selected the ethanol extract as an effective xanthine oxidase inhibitor and confirmed whether ethanol extracts showed xanthine oxidase inhibition in animal experiments. The in vivo mouse study demonstrated that ethanol extract of D. morbifera leaf at the dose of 300 mg/kg could inhibit blood/hepatic xanthine oxidase activity and this result shows that the xanthine oxidase inhibitory activity in vitro is reproduced in vivo. The present study showed that ethanol extract was optimal xanthine oxidase inhibitor which can be applied to prevent diseases related to hyperuricemia.
Functional network interactions at rest underlie individual differences in memory ability

Intrinsic network interactions may underlie individual differences in the ability to remember. The default mode network (DMN) comprises subnetworks implicated in memory, and interactions between the DMN and frontoparietal network (FPN) were shown to support mnemonic processing. However, it is unclear if such interactions during resting-state predict episodic memory ability. We investigated whether intrinsic network interactions within and between the DMN and FPN are related to individual differences in memory performance. Resting-state activity was measured using functional MRI in healthy young adults followed by a memory test for object–location associations that were studied 3 d earlier. We identified two subnetworks within the DMN, the main-DMN and the medial temporal lobe, retrosplenial cortex (MTL_RSC)-DMN. Further, we found regions forming the FPN. Memory performance was associated with lower connectivity within the MTL_RSC-DMN, and stronger connectivity between the main-DMN and FPN. Exploratory whole-brain analysis revealed stronger MTL connectivity with the left posterior parietal cortex that was related to better memory performance. Furthermore, we found increased task-evoked activation during successful retrieval within the main-DMN and FPN, but not within the MTL_RSC-DMN. In sum, lower intrinsic connectivity within the MTL_RSC-DMN, combined with stronger connectivity between the main-DMN and FPN, explain individual differences in memory ability.
The effect of Dr Google on doctor–patient encounters in primary care: a quantitative, observational, cross-sectional study

Background Two-thirds of all patients search the internet prior to a health consultation. Aim To explore how searching for online health information before visiting a doctor influences patients’ behaviour during the consultation. Design & setting A quantitative, observational, and cross-sectional study of 18–75-year-old patients who used the internet. Method Patients were recruited by social media for the quantitative study. This was followed by a qualitiative study of GPs who were questioned in focus groups. Two questions were addressed: What is the effect of searching online health information on the behaviour of the patients? How does the GP handle this information? Results Almost half of all responders (total n = 963) usually went to the doctor after the online information search but two-thirds were not reassured by the internet search. More than half of responders had more confidence in their GP after searching online. The older the responders, the more they went to the doctor after their internet search and the younger the responders, the more they were worried. The more frequently people consulted the internet for specific complaints, the more likely they reported reassurance. Discussion Patients usually made an appointment with their GP after the internet search. New symptoms are rarely noticed and the search usually did not lead patients to distrust their GP. The majority of GPs described positive effects of the online search behaviour on the consultation. Conclusion The emerging use of the internet for searching health information, commonly referred to as 'Dr Google', is not seen as a threat by GPs and leads to a better mutual understanding of symptoms and diagnosis.
Weighted Harvest-Then-Transmit: UAV-Enabled Wireless Powered Communication Networks

This paper proposes an unmanned aerial vehicle (UAV)-enabled wireless-powered communication network (WPCN), which consists of a hybrid access point (H-AP), a UAV, and nodes. The H-AP broadcasts energy to all nodes, and the nodes harvest and use the energy for information transmission. However, far-apart nodes from the H-AP hardly harvest the energy and they require more energy for the same throughput as near-apart nodes due to distance-dependent signal attenuation, which is called the doubly near–far problem. To overcome the doubly near–far problem, we propose a weighted harvest-then-transmit protocol. In the proposed protocol, we consider that the channel power gain changes according to the location of nodes, whereas it has remained constant in most conventional WPCNs. The UAV acts as a mobile H-AP, where the UAV performs weighted energy transfer and receives information to/from all encountering far-apart nodes with the better channel power gain. For the UAV, we consider the flight path optimization by implementing a regression algorithm in terms of energy efficiency. Under these considerations, we aim to maximize the sum-throughput of all nodes based on the weighted harvest-then-transmit protocol, by using convex optimization techniques. The optimal time allocation is investigated for far-apart nodes and near-apart nodes sequentially, to solve the doubly near–far problem. Simulation results show that the proposed UAV-enabled WPCN outperforms the conventional WPCN with a fixed H-AP in terms of the sum-throughput maximization.
Full-Wave Modal Analysis of a Novel Dielectrometer for Accurate Measurement of Complex Permittivity of High-Loss Liquids at Microwave Frequencies

A novel dielectrometer to measure the complex permittivity of high-loss liquids is presented. The geometry consists of a reentrant cavity with insertion holes, where the holder filled with liquid can be introduced readily. Radii of the insertion holes are large enough for a convenient pouring of the liquid. The electromagnetic analysis has been performed by a mixed mode-matching and circuit technique with the purpose of taking the high accuracy and fast convergence of the mode-matching and the flexibility and versatility of the circuit method. The convergence of the method is studied, and a procedure to estimate the result for an infinite number of modes is proposed. A calibration procedure is presented to minimize the error introduced by the numerical method. Mode charts are shown to analyze the behavior of resonant parameters for every mode. Some reference liquids are measured at different resonant frequencies, and the results are compared with those provided by other models of the literature.
The Sin of Missing Data: Is All Forgiven by Way of Imputation?

Missing data can seriously compromise inferences from clinical research studies. One method for handling missing data is to substitute each missing value with a reasonable guess, and then carry out the analysis as if there were no missing values (imputation). Single imputation replaces a missing value based on a predefined rule and includes last observation carried forward, worst observation carried forward, and simple mean imputation. In general, single imputation methods are not recommended. Multiple imputation is a statistical technique that creates multiple complete datasets, substituting missing with imputed values. The datasets are analyzed separately, and the results pooled into a final result. Whether to use multiple imputation for missing data depends on the missing data mechanism (reason for missing data). To properly use multiple imputation, the missing data should be MAR.
The effect of diet on primary dysmenorrhea in university students: A randomized controlled clinical trial

Objective: To evaluate the effect of diet therapy on primary dysmenorrhea in female university students. Methods: A randomized controlled pre and post-test design was used to verify the effects of diet therapy on primary dysmenorrhea. The study was conducted on 67 female students who were suffering from primary dysmenorrhea. The participants were divided into diet and control groups. The intensity of dysmenorrhea was determined using Visual Analogue Scale and a modified questionnaire assessing several symptoms of dysmenorrhea. The intervention group received the diet therapy for three months. The assessments were made before intervention and three months later. Results: Before the intervention, the mean intensity of dysmenorrhea was found to be 7.14 ± 1.3, 7.09 ± 1.4, in diet groups and control groups, respectively, but the difference was not statistically significant. After the diet therapy, a significant difference was found among the two groups regarding the mean intensity of dysmenorrhea after three months and the average score of pain score of diet group was significantly lower (Diet group:5.15±1.15, Control group: 6.74±1.97). Conclusion: Diet therapy was found to be effective in reducing pain in female university students with primary dysmenorrhea complaints.
Fast Recognition of Human Actions Using Autocorrelation Sequence

Recent state-of-the-art systems for human action recognition are computationally intensive due to the use of full-length videos and complex network structures. This study aims to develop sampling strategies as well as simple network structure to boost inference time of recognition. Especially, auto-correlation sequence, which shows the similarity between a video and a lagged version of itself, is adopted to extract the most essential segment of the video without information loss. The proposed method considerably reduces inference time while keeping comparable recognition accuracy.
AGEP overlap induced by hydroxychloroquine: a case report and literature review

ABSTRACT Acute Generalized Exanthematous Pustulosis (AGEP) is a rare drug reaction manifesting as pustular lesions with surrounding erythema following exposure. The disease is often self-limited and treatment is supportive. It may present in an atypical variant with vesicles that desquamate into erosions, which classifies the disease as an AGEP/SJS Overlap. This overlap syndrome can carry a substantial mortality rate and necessitate elevation in the level of care. Hydroxychloroquine has been implicated in cases of AGEP, and we present a case of AGEP/SJS overlap attributed to this common medication. Given the prevalence of drug eruptions, it is critical for the physicians to recognize and not overlook this rare and potentially fatal dermatological emergency.
Preoperative assessment of CD44‐mediated depth of invasion as predictor of occult metastases in early oral squamous cell carcinoma

Epithelial–mesenchymal transition and cancer stem‐like cells (CSC) have been linked to increased metastatic potential. We evaluated the prognostic impact of CD44, a CSC biomarker, on depth of invasion (DOI) and outcome in oral squamous cell carcinoma (OSCC).
Differentiation of multiple myeloma and metastases: Use of axial diffusion-weighted MR imaging in addition to standard MR imaging at 3T

Background Metastasis and multiple myeloma are common malignant bone marrow lesions which may be difficult to distinguish because of similar imaging findings. The purpose of this study was to determine the value of adding diffusion-weighted imaging (DWI) to standard MR imaging to differentiate multiple myeloma from metastasis. Methods 25 patients with metastasis and 18 patients with multiple myeloma underwent 3T MR imaging with DWI (b = 0, 800 s/mm2) were enrolled. They all had pathologically confirmed bone lesions and were in a treatment naïve state. Two readers who were blind of final diagnosis measured the average ADC (ADCav) and minimum ADC (ADCmin) on the DWI. They then estimated the diagnosis, based on the standard MR imaging and measured ADC values. Another reader performed histogram analysis on the whole tumor volume and obtained mean ADC (ADCvol), standard deviation (SDvol), skewness, and kurtosis. Comparison of the obtained values from DWI was performed by the t-test or Mann-Whitney U test. The receiver operating characteristic (ROC) curve with areas under the curve (AUC) was used to obtain the cut off values and to evaluate the diagnostic performance of the two readers. Results ADCav, ADCmin, and ADCvol of multiple myeloma were significantly lower than those of metastasis: ADCav, 752 μm2/sec versus 1081 μm2/sec; ADCmin, 704 μm2/sec vs 835 μm2/sec; ADCvol 761 μm2/sec vs 1184 μm2/sec (p < .001). In histogram analysis, ADC values of multiple myeloma showed narrow distribution than metastasis: SDvol, 144 vs 257 (p < .001). Areas under the receiver operating characteristic curve was significantly higher with additive DWI than standard MR alone: 0.762 vs 0.953; 0.706 vs 0.950 (p < .05) for two readers. Conclusions This study suggested that the addition of axial DWI to standard MR imaging can be helpful to diagnose multiple myeloma from metastasis at 3T.
Impact of Mode Decision Delay on Estimation Error in Continuous-Time Controlled System

For highly maneuvering target interception in terminal guidance, the maximal admissible mode decision delay (MAMDD) and the least required mode sojourn time (LRMST) are calculated in continuous-time controlled system. The lateral acceleration command of the evader is modeled as a jump-Markov process. Suppose that the mode switches are observable and the evader’s motion mode is correctly identified by a separate mode decision-maker with a fixed time delay, then the error model of the state estimation is derived. By limiting the state estimation error to a certain range, MAMDD and LRMST are calculated. The derivation is validated by a typical instance of tactical ballistic missile interception. The results in this paper provide a useful tool for guiding the design of the mode decision-maker and evaluating the performance of the logic-based integrated estimation and guidance system.
Joint Relay Selection and Power Allocation for Energy-Limited Networks with Cloud Computing

We consider a energy-limited network where a source node communicates with a destination node with help of relay node. Appropriate relay node is a good way for solving communication between source and destination and reducing energy consuming. The conventional methods adopt simple and tractable criterion to achieve goal as of tough computation. Cloud computing (CC) technology brings novel ideas that the application of Auto-Regressive and Moving Average (ARMA) model in energy-limited networks for our intention. A source selects an appropriate relay node to assisted communication before predicting historical energy information of potential relay nodes through ARMA model. Then, the Lagrange Multiplier is used to optimize the power allocation of nodes to improving network energy. The results show our relay selection algorithm and power allocation method could effectively reduce network energy consumption.