Miracle-dz/UniFAR-FTUs huggingface dataset:
Cellular signaling pathways regulating β-cell proliferation as a promising therapeutic target in the treatment of diabetes

It is established that a decrease in β-cell number and deficiency in the function of existing β-cells contribute to type 1 and type 2 diabetes mellitus. Therefore, a major focus of current research is to identify novel methods of improving the number and function of β-cells, so as to prevent and/or postpone the development of diabetes mellitus and potentially reverse diabetes mellitus. Based on prior knowledge of the above-mentioned causes, promising therapeutic approaches may include direct transplantation of islets, implantation and subsequent induced differentiation of progenitors/stem cells to β-cells, replication of pre-existing β-cells, or activation of endogenous β-cell progenitors. More recently, with regards to cell replacement and regenerative treatment for diabetes patients, the identification of cellular signaling pathways with related genes or corresponding proteins involved in diabetes has become a topic of interest. However, the majority of pathways and molecules associated with β-cells remain unresolved, and the specialized functions of known pathways remain unclear, particularly in humans. The current article has evaluated the progress of research on pivotal cellular signaling pathways involved with β-cell proliferation and survival, and their validity for therapeutic adult β-cell regeneration in diabetes. More efforts are required to elucidate the cellular events involved in human β-cell proliferation in terms of the underlying mechanisms and functions.
Detecting Depression Using K-Nearest Neighbors (KNN) Classification Technique

Social networks have developed as a promising point for everybody to communicate with their interested friend and share their opinions, photos, and videos. Also, it has been an upcoming research field and has picked an established position globally. In this paper, we considered depression problems among various Facebook users. Already, a number of researchers have studied and applied many techniques to detect depression, but still need to detect accurately from social network data. So, we investigate the possibility to utilize Facebook data and apply KNN (k-nearest neighbors) classification technique for detecting depressive emotions. We do believe that our investigation and approach might be helpful to raise consciousness in online social network users.
Fuzzy nearest mean reclustering of SAR pixel features: assessments on land use classification

This paper describes a non-parametric algorithm based on fuzzy-reasoning concepts and suitable for land use classification, either supervised or unsupervised, starting from pixel features derived from SAR observations. Pixel vectors composed by simple features calculated from the backscattering coefficient(s) in one or more bands and/or polarizations are iteratively clustered. At each iteration step, pixels in the scene are classified based on the minimum attained by a weighted Euclidean distance from the centroid representative of each cluster. Upgrade of centroids is iteratively obtained both from the previously obtained classification map and by thresholding a membership function of pixel vectors to each cluster. Such a function is inversely related to the weighted Euclidean distances from the centroid representative of each cluster. To yield the weighted distances from a pixel vector, its features are weighted by means of progressively refined coefficients, whose calculation still relies on the membership function through a least squares algorithm. Possible "a priori" knowledge coming from ground truth data may be used to initialize the procedure, but is not required. Experiments on MAC-91 NASA/JPL AIRSAR data on the Montespertoli test site show that a total of nine features derived from C-HV, L-HV, and P-HV observations are capable to discriminate seven agricultural cover classes with an overall pixel accuracy of 70%, with one tenth of the ground truth data used for training and the remaining nine tenths for testing the classification accuracy.
The Effect of White Rice and White Bread as Staple Foods on Gut Microbiota and Host Metabolism

The purpose of this study was to examine the influence of two kinds of major Japanese staple foods, white rice and white bread, on gut microbiota against the background in which participants eat common side dishes. Seven healthy subjects completed the dietary intervention with two 1-week test periods with a 1-week wash-out period in cross-over design (UMIN registration UMIN000023142). White bread or white rice and 21 frozen prepared side dishes were consumed during the test periods. At baseline and at the end of each period, fasting blood samples, breath samples, and fecal samples were collected. For fecal samples, 16S rRNA gene sequencing was used to analyze the gut microbiota. After the bread period, the abundance of fecal Bifidobacterium genus (19.2 ± 14.5 vs. 6.2 ± 6.6 (%), p = 0.03), fasting glucagon-like peptide 1 (GLP-1) (13.6 ± 2.0 vs. 10.5 ± 2.9 (pg/mL), p = 0.03), and breath hydrogen (23.4 ± 9.9 vs. 8.2 ± 5.5 (ppm), p = 0.02) were significantly higher than those of after the rice period. Plasma SCFAs also tended to be higher after the bread period. White bread contains more dietary fiber than refined short grain rice. These findings suggest that indigestible carbohydrate intake from short grain rice as a staple food may be smaller than that of white bread.
State Estimation of Distribution Network based on Historical Data Mining and APSO-BP algorithm

For the safety and stability of the distribution network, the distribution management system (DMS) requires high precision state estimation results as the basic information. If there are errors in line parameters, the precision of estimation results of Weighted Least Squares (WLS) state estimation method will be lower because the WLS model relies on line parameters. This paper presents a state estimation model based on historical data mining via multivariate linear regression. BP neural network is used to directly obtain the mapping between input and output, which would avoid the dependency on line parameters. Therefore, the proposed model would not be affected by the errors of parameters. At first, Recursive Least Squares (RLS) is used to establish a historical data model to calculate pseudo measurement. Then the pseudo measurement is taken as part of the inputs to BP neural network which is improved by Adaptive Particle Swarm Optimization algorithm (APSO-BP). Finally, the proposed method is simulated based on IEEE 33 nodes system. The results are evaluated through maximum absolute error and mean absolute error, which show that the proposed method has high precision and performances well in avoiding the influence of line parameters errors.
Optimum Mode Operation and Implementation of Class E Resonant Inverter for Wireless Power Transfer Application

This paper proposes the design of ZVS class E resonant inverter to be used in a wireless power transfer (WPT) system. Since the Class E inverter satisfies the zero voltage switching (ZVS) and zero derivative voltage switching (ZDS) condition, high conversion efficiency at high frequency can be achieved. All the components of the circuit are designed for optimum mode of operation and the inverter is made to operate at optimal switching conditions. The designed circuit is simulated in PSPICE environment and experimentally verified at a frequency of 333 kHz. The system is also tested for the WPT application and the transferred power is found out with different coupling coefficients.
UPA-seq: prediction of functional lncRNAs using differential sensitivity to UV crosslinking

While a large number of long noncoding RNAs (lncRNAs) are transcribed from the genome of higher eukaryotes, systematic prediction of their functionality has been challenging due to the lack of conserved sequence motifs or structures. Assuming that lncRNAs function as large ribonucleoprotein complexes and thus are easily crosslinked to proteins upon UV irradiation, we performed RNA-Seq analyses of RNAs recovered from the aqueous phase after UV irradiation and phenol-chloroform extraction (UPA-Seq). As expected, the numbers of UPA-Seq reads mapped to known functional lncRNAs were remarkably reduced upon UV irradiation. Comparison with ENCODE eCLIP data revealed that lncRNAs that exhibited greater decreases upon UV irradiation preferentially associated with proteins containing prion-like domains (PrLDs). Fluorescent in situ hybridization (FISH) analyses revealed the nuclear localization of novel functional lncRNA candidates, including one that accumulated at the site of transcription. We propose that UPA-Seq provides a useful tool for the selection of lncRNA candidates to be analyzed in depth in subsequent functional studies.
Facilitated permeation of insulin across TR146 cells by cholic acid derivatives-modified elastic bilosomes

Background Buccal delivery of insulin is still a challenging issue for the researchers due to the presence of permeability barrier (buccal mucosa) in the buccal cavity. The main objective of this study was to investigate the safety, effectiveness, and potential of various liposomes containing different bile salts to improve the permeation of insulin across in vitro TR146 buccal cell layers. Methods Elastic bilosomes containing soy lecithin and bile salt edge activators (sodium cholate [SC], sodium taurocholate [STC], sodium glycocholate [SGC], sodium deoxyglycocholate [SDGC], or sodium deoxytaurocholate [SDTC]) were fabricated by thin-film hydration method. The prepared liposomes were characterized, and in vitro permeation studies were performed. The fluorescein isothiocyanate-insulin-loaded elastic bilosomes were used to evaluate the quantitative and qualitative cellular uptake studies. Results The prepared elastic bilosomes had a particle size and an entrapment efficiency of ~140–150 nm and 66%–78%, respectively. SDGC-lipo (SDGC-incorporated liposome) was observed to be the most superior with an enhancement ratio (ER) of 5.24 (P<0.001). The SC-incorporated liposome (SC-lipo) and SDTC-incorporated liposome (SDTC-lipo) also led to a significant enhancement with ERs of 3.20 and 3.10 (P<0.05), respectively, compared with insulin solution. These results were further supported by quantitative and qualitative cellular uptake studies performed employing fluorescence-activated cell sorting analysis and confocal microscopy, respectively. The relative median fluorescence intensity values of elastic bilosomes were counted in the order of SDGC-lipo > SC-lipo > SDTC-lipo > SGC-incorporated liposome > STC-incorporated liposome, and similarity in the permeability profile of the employed elastic bilosomes was noted. Conclusion This study presents the employment of various derivatives of cholic acid-loaded elastic bilosomes as a promising strategy to enhance the permeation of insulin through buccal route.
A General Matched Filter Design for Reciprocity Calibration in Multiuser Massive MIMO Systems

In this paper, we propose a novel design of calibration matrix for time-division duplex multiuser multiple-input multiple-output with maximal ratio transmit beamforming, which maximizes the achievable sum rate in the presence of reciprocity mismatch induced by radio-frequency (RF) gain responses at base station side. We show that two conventional designs are equivalent to the asymptotic expressions of proposed design when signal-to-noise ratio (SNR) tends to infinity or zero, respectively, since the proposed calibration matrix behaves as a decorrelator that rejects RF gain mismatch for the former SNR region, or as a matched filter maximizing the power of useful signal for the latter. The robust version against the channel estimation error is also investigated. Simulation results illustrate the effectiveness of our proposed design.
Programmable Electronic AC Load Based on a Hybrid Multilevel Voltage Source Inverter

A programmable electronic load (PEL) solution is usually needed for comprehensive testing of power supplies. In this paper, a novel PEL based on a hybrid five-level voltage source inverter (VSI) is introduced to emulate a variety of static load behaviors, such as R, L, C loads, high-frequency harmonic loads, and unbalanced loads. Dynamic load behavior, for example, modulation loads, can also be achieved in this paper. A dedicated control structure is proposed for the emulation of different load behaviors and the detailed compensator design is presented to evaluate the system dynamic performance. The proposed PEL system has isolated active dc links to support multilevel converter topology, and it can either dump the energy to a passive load or recycle the energy back to the utility grid through another VSI. Simulation and experimental results are provided to validate the effectiveness of proposed control methods in terms of successfully achieving a variety of load profile functions.
The Pain Registry for Epidemiological, Clinical, and Interventional Studies and Innovation (PRECISION): registry overview and protocol for a propensity score-matched study of opioid prescribing in patients with low back pain

Background Low back pain is the leading cause of disability worldwide. Nonsteroidal anti-inflammatory drugs (NSAIDs) are recommended as the first-line pharmacologic therapy for subacute or chronic low back pain, with opioids reserved for patients who fail on NSAIDs. CYP2D6, CYP2C9, and CYP2C19 genes have variants that place patients using analgesics at risk for adverse events. However, precision medicine based on pharmacogenetically informed prescribing is becoming more feasible as genotyping costs decline. This study aims to compare opioids vs NSAIDs in treating adults with subacute or chronic low back pain under the alternative models of usual care and precision medicine. Methods An observational cohort study within the Pain Registry for Epidemiological, Clinical, and Interventional Studies and Innovation (PRECISION) will be used to simulate a randomized controlled trial. Patients using opioids and NSAIDs will be optimally matched at baseline using propensity scores. A saliva sample will also be collected to determine patient genotypes for drug metabolism based on CYP2D6 (single-gene model) and CYP2D6, CYP2C9, and CYP2C19 (multigene model). Prescribing that is concordant with pharmacogenetically informed care under these models will be considered “low risk”, whereas discordant prescribing will be considered “high risk”. Primary outcomes will be assessed over 6 months using a Numerical Rating Scale for pain, the Roland-Morris Disability Questionnaire, and the Drug Adverse Events Index. Secondary outcomes will be assessed using quality-of-life measures. An estimated 600 patients will be enrolled to acquire at least 400 patients after attrition and allowing for unmatched patients. This will achieve a statistical power of at least 80% in detecting the effect sizes ranging from 0.35 (small–medium effect) to 0.69 (medium–large effect). Discussion This PRECISION Pain Research Registry study builds on the concepts espoused in the Precision Medicine Initiative and addresses long-term goals established by the National Institutes of Health by assessing how precision medicine may prevent and treat chronic pain.
Design Optimization of an Energy Harvesting Platform for Self-Powered Wireless Devices in Monitoring of AC Power Lines

This paper presents the design optimization of a magnetic field energy harvesting platform for self-powered ac power line monitoring devices in smart grid applications. The designed platform can be used with any type of vibration-to-electricity energy conversion schemes including piezoelectric, electromagnetic, and electrostatic energy harvesters. The platform includes a cantilever beam with a miniaturized permanent magnet (PM) at the tip that vibrates due to the interaction with the magnetic field of the ac line. The proposed method analytically determines the optimum geometric orientations of the platform as well as the optimum dimensions of PM to maximize the applied magnetic force to the beam. The validity of the design procedure and its assumptions are verified numerically and experimentally using a piezoelectric energy harvesting platform. The numerical and experimental test results confirm the calculated optimum orientation angles and PM dimensions that maximize the magnetic force. The analysis shows that for a PM with vibration direction in a plane normal to the power line, the maximum force can be achieved at the multiples of $+$45 $^\circ$ with reference to the vibration direction. The optimum orientation angle also depends on the angles between the magnetization vector and the direction of the vibration.
Design and Static Tests of an All-Terrain Suspension System for Electric Wheelchair

The purpose of this article is to present the process of design and simulation, design, and testing of a Rocker-Bogie-like suspension system, for use in an all-terrain electric wheelchair. This suspension is a base of a six-wheel remote-controlled platform adapted to the rough-terrain conditions. The first stage of the designing process is to create a CAD model and perform the simulations for its configuration. After conducting analyses, the suspension model was made of plywood, MDF and 3D printed parts. This is the essential stage between CAD drownings and the aluminum model. The last step of the process of building Rocker-Bogie suspension is to make an aluminum structure and then conduct field tests under controlled conditions.
The Nationwide Health Information Network: The Case of the Expansion of Health Information Exchanges in the United States

The Nationwide Health Information Network (NHIN) implemented secure exchange of health records through utilization of the Internet. The NHIN has greatly assisted in achieving the goals of the Health Information Technology for Economic and Clinical Health Act by promoting the adoption of Meaningful Use. Epic introduced a Health Information Exchange platform, Care Everywhere, which has facilitated Health Information Exchange availability. The purpose of this research was to determine the impact of NHIN and Epic Care’s Care Everywhere on health care to determine whether their use in the emergency department (ED) has increased. The methodology for this study utilized a literature review. Twenty-eight sources were referenced for this study. With the NHIN implementation, repeated visits were decreased, visit times became faster, and charges were lower. Emergency department reported significant benefits with sharing clinical information. The NHIN implementation throughout the ED has increased the quality of health care; duplicated tests and drug usage were determined, and a reduction of the ED length of stay was also achieved.
Rhythmic Component Extraction from EEG Signal Using Data Adaptive Multiband Filtering

The rhythmic components of electroencephalography (EEG) signal illustrate the neural activities and effective to implement brain computer interface (BCI). This paper presents an efficient rhythmic component extraction (RCE) method from multi-channel EEG. It is based multivariate empirical mode decomposition (MEMD) which decomposes multichannel EEG signal into a finite set of subbands termed as intrinsic mode functions (IMFs). The decomposition is fully data adaptive and effective for non-stationary signal. The IMF is a time varying band limited signal. It is filtered using a Fourier transform based zero phase bandpass filter for a specific rhythmic component. Thus obtained rhythmic component of all IMFs of an EEG channel are summed up yielding the channel’s component. All the desired components of individual channels are extracted using the same method. The energies of different extracted rhythmic components are compared as a function of channels. The inter-channel correlation is taken into consideration during decomposition with MEMD hence it is very much effective for RCE from multichannel EEG signal.
Mineralocorticoid Receptor and Aldosterone-Related Biomarkers of End-Organ Damage in Cardiometabolic Disease

The mineralocorticoid receptor (MR) was first identified as a blood pressure regulator, modulating renal sodium handling in response to its principal ligand aldosterone. The mineralocorticoid receptor is also expressed in many tissues other than the kidney, such as adipose tissue, heart and vasculature. Recent studies have shown that MR plays a relevant role in the control of cardiovascular and metabolic function, as well as in adipogenesis. Dysregulation of aldosterone/MR signaling represents an important cause of disease as high plasma levels of aldosterone are associated with hypertension, obesity and increased cardiovascular risk. Aldosterone displays powerful vascular effects and acts as a potent pro-fibrotic agent in cardiovascular remodeling. Mineralocorticoid receptor activation regulates genes involved in vascular and cardiac fibrosis, calcification and inflammation. This review focuses on the role of novel potential biomarkers related to aldosterone/MR system that could help identify cardiovascular and metabolic detrimental conditions, as a result of altered MR activation. Specifically, we discuss: (1) how MR signaling regulates the number and function of different subpopulations of circulating and intra-tissue immune cells; (2) the role of aldosterone/MR system in mediating cardiometabolic diseases induced by obesity; and (3) the role of several MR downstream molecules as novel potential biomarkers of cardiometabolic diseases, end-organ damage and rehabilitation outcome.
Research on 3D Reconstruction Based on Multiple Views

The acquisition of 3D models is a fundamental research in the field of computer graphics and computer vision. However, it is very complicated and expensive to build 3D models manually by using modeling software, such as 3DMAX and Maya. Therefore, how to get 3D models directly and quickly from the real world is a hot research topic in this field. Multi-view based 3D reconstruction techniques include feature point extraction and matching, camera calibration, sparse point cloud reconstruction, dense point cloud reconstruction, Poisson surface reconstruction, texture mapping and many other techniques. This paper will focus on the main algorithms of 3D reconstruction algorithms - Structure from Motion, Multi-View Stereo and Poisson Surface Reconstruction. Based on the above research, this paper designed a 3D reconstruction system including the above algorithms. The system takes a variety of views of an object as input, and finally outputs the 3D model of the object. Finally, this paper verified the effectiveness and feasibility of the system through experimental analysis.
Preference Based Recommendation System for Apparel E-Commerce Sites

Preference Based Recommendation System for Apparel E-Commerce Sites is a new approach for e-commerce sites to come up with more accurate and personalized recommendation. The proposed system will use the reviews that given by users as the base of the system, by using natural language processing methods it will calculate the sentiment score, attributes more concerned and their corresponding values of each items. The outcome of the text mining will be used as input to the recommendation process. The recommendation approach is combination of both collaborative and content based methods. With considering user reviews the module will develop item feature and user preference matrixes from that ratings will be predicted by using Term Frequency-Document Inverse Frequency model.