Miracle-dz/UniFAR-FTUs huggingface dataset:
Saroglitazar for the treatment of hypertrig-lyceridemia in patients with type 2 diabetes: current evidence

Diabetes mellitus (DM) is one of the most dreaded metabolic disorders in the world today. It is the leading cause of morbidity and mortality, and plays a cardinal role in quality of life and health economics. DM is associated with a high prevalence of microvascular and macrovascular complications. DM is a very important cardiovascular (CV) risk factor. Cardiovascular disease (CVD) has been implicated as the prime cause of mortality and morbidity in patients with DM. Hence, treatment of DM goes beyond glycemic control, and demands a multidisciplinary approach that comprehensively targets risk factors inherent in CV events. Lipid abnormalities are undoubtedly common in patients with DM, and they contribute to an increased risk of CVD. A high-risk lipid profile, termed atherogenic dyslipidemia of diabetes (ADD), is known to occur in patients with DM. The use of lipid-lowering agents, a quintessential part of the multifactorial risk factor approach, is a crucial intervention to minimize diabetes-related complications. In this article, we discuss the role of peroxisome proliferator activator receptor (PPAR) alpha/gamma (α/γ) agonist, saroglitazar, in the management of ADD. While statins are irrefutably the first line of drugs for dyslipidemia management in patients with residual CV risk while on a statin, PPAR α/γ agonists have been found to be of substantial benefit. Data from the PRESS I–VI clinical trials testify to the fact that saroglitazar and fibrates have similar efficacy in reducing triglycerides and improving high-density lipoprotein. The ancillary benefit of improved glycemic control, without the weight gain of PPAR γ agonists, is an added advantage. Reduction in ADD, improved glycemic control, efficacy at par with fibrates, and an acceptable safety profile form the grounds on which this group of PPAR α/γ agonists, with their novel mechanism, holds a promising future in the management of diabetic dyslipidemia.
Symptomatology and management of acute grief

At first glance, acute grief would not seem to be a medical or psychiatric disorder in the strict sense of the word but rather a normal reaction to a distressing situation. However, the understanding of reactions to traumatic experiences whether or not they represent clear-cut neuroses has become of ever-increasing importance to the psychiatrist. Bereavement or the sudden cessation of social interaction seems to be of special interest because it is often cited among the alleged psychogenic factors in psychosomatic disorders. The enormous increase in grief reactions due to war casualties, furthermore, demands an evaluation of their probable effect on the mental and physical health of our population. The points to be made in this paper are as follows: i. Acute grief is a definite syndrome with psychological and somatic symptomatology. 2. This syndrome may appear immediately after a crisis; it may be delayed; it may be exaggerated or apparently al)sent. 3. In place of the typical syndrome there may appear distorted pictures, each of which represents one special aspect of the grief syndrome. 4. By appropriate techniques these distorted pictures can be successfully transformed into a normal grief reaction with resolution. Our observations comprise tot patients. Included are (i) psychoneurotic patients who lost a relative during the course of treatment, (2) relatives of patients who uied in the hospital, (3) bereaved disaster victims (Cocoanut Grove Fire) and their close relatives, ( ) relatives of members of the armed forces.
Renewable Energy-Aware Joint Caching and Routing for Green Communication Networks

The Internet is one of the fastest increasing contributors to carbon emission. Content distribution as video on demand constitutes the majority of the Internet traffic. In order to reduce the Internet’s carbon footprint, we propose greener mechanisms for content delivery that utilize the use of renewable energy and content caching concept. If renewable energy is not enough to satisfy a given user’s demand, we use brown energy to satisfy the demand. Specifically, we consider the joint routing and caching problem with the objective of minimizing the brown energy usage while satisfying the users’ requests. We formulate the problem as a mixed integer-linear program (MILP) and prove that it is NP-hard. Accordingly, we present two relaxation techniques to find an efficient solution in a polynomial time (within 10% of the optimal). The first technique is based on relaxation and rounding. The other one is a near-optimal solution based on sequential fixing, where the binary variables are determined iteratively by solving a sequence of linear programs. Then, we develop a gradient-based distributed algorithm that can adapt to the changes in traffic and renewable energy conditions. Finally, we show that by utilizing network coding, the problem can be formulated using linear programming, which has polynomial-time complexity. Simulation results are provided, which verify the effectiveness of our optimization framework and demonstrate the significant energy saving achieved (up to 90%) over the nonenergy-aware shortest path-routing method.
FoldX accurate structural protein–DNA binding prediction using PADA1 (Protein Assisted DNA Assembly 1)

Abstract The speed at which new genomes are being sequenced highlights the need for genome-wide methods capable of predicting protein–DNA interactions. Here, we present PADA1, a generic algorithm that accurately models structural complexes and predicts the DNA-binding regions of resolved protein structures. PADA1 relies on a library of protein and double-stranded DNA fragment pairs obtained from a training set of 2103 DNA–protein complexes. It includes a fast statistical force field computed from atom-atom distances, to evaluate and filter the 3D docking models. Using published benchmark validation sets and 212 DNA–protein structures published after 2016 we predicted the DNA-binding regions with an RMSD of <1.8 Å per residue in >95% of the cases. We show that the quality of the docked templates is compatible with FoldX protein design tool suite to identify the crystallized DNA molecule sequence as the most energetically favorable in 80% of the cases. We highlighted the biological potential of PADA1 by reconstituting DNA and protein conformational changes upon protein mutagenesis of a meganuclease and its variants, and by predicting DNA-binding regions and nucleotide sequences in proteins crystallized without DNA. These results opens up new perspectives for the engineering of DNA–protein interfaces.
An Overview of Global Flavonoid Intake and its Food Sources

Dietary patterns and food availability differ greatly between regions and countries around the world. As a result, there is a large variability in the intake of total flavonoids and flavonoid subclasses, and subsequently in their major food sources. However, we need to be aware of certain methodological issues when we compare studies on flavonoid intake. In order to evaluate the intake of flavonoids, the different potential dietary assessment methodologies (dietary questionnaires and biomarkers) will be presented. Advantages and limitations of using of the two main food composition databases on flavonoids (US Department of Agriculture and Phenol-Explorer databases) will be discussed. The intake of total flavonoid and flavonoid subclasses in the various studies around the world will be comprehensively reviewed. The major food sources of flavonoids by region/country will be described. The main determinants of the intake of flavonoids will be explained as well. Calculating the intake of flavonoids is the first step before estimating their potential protective effects against chronic diseases and is an essential step for developing future dietary guidelines on flavonoids.
Armillaria mexicana, a newly described species from Mexico

ABSTRACT Armillaria mexicana (Agaricales, Physalacriaceae) is described as a new species based on morphology, DNA sequence data, and phylogenetic analyses. It clearly differs from previously reported Armillaria species in North, Central, and South America. It is characterized by the absence of fibulae in the basidioma, abundant cheilocystidia, and ellipsoidal, hyaline basidiospores that are apparently smooth under light microscope, but slightly to moderately rugulose under scanning electron microscope. It is differentiated from other Armillaria species by macromorphological characters, including annulus structure, pileus and stipe coloration, and other structures. DNA sequence data (nuc rDNA internal transcribed spacers [ITS1-5.8S-ITS2 = ITS], 28S D-domain, 3′ end of 28S intergenic spacer 1, and translation elongation factor 1-α [TEF1]) show that A. mexicana sequences are quite distinct from sequences of analogous Armillaria species in GenBank. In addition, sequences of ITS of the A. mexicana ex-type culture reveal an ITS1 of 1299 bp and an ITS2 of 582 bp, the longest ITS regions reported thus far in fungi. Phylogenetic analysis based on TEF1 sequences place A. mexicana in a well-separated, monophyletic clade basal to the polyphyletic A. mellea complex.
TIME—Tunable Inductors Using MEmristors

Memristors have proven to be an attractive feature for memory, logic-in-memory, and neuromorphic computing. Recently, radio-frequency memristive switches (RFMSs) have exhibited promising high-frequency performance, opening the possibility of their use in radio-frequency integrated circuit applications. In this paper, we present two novel topologies of Tunable Inductors using MEmristors, the memristive–via the switched tunable inductor and the multi-layer stacked inductor switched by an RFMS single-pole double-throw. The two inductor topologies are fully passive and are tuned by electrochemical metallization memristors. Memristive devices improve the performance of tunable inductors, as they provide low-area overhead, low-energy switching, and non-volatility, resulting in more compact and energy-efficient devices. The topologies are implemented and simulated in a momentum 3-D planar electromagnetic simulator. Simulation results show a maximum tunability of 296%, a quality factor of 18 at 5 GHz, and self-resonant frequency above 8.4 GHz.
Characterization and clinical evaluation of a novel IMRT quality assurance system

Intensity‐modulated radiation therapy (IMRT) is a complex procedure that involves the delivery of complex intensity patterns from various gantry angles. Due to the complexity of the treatment plans, the standard care is to perform measurement‐based, patient‐specific quality assurance (QA). IMRT QA is traditionally done with film for relative dose in a plane and with an ion chamber for absolute dose. This is a laborious and time‐consuming process. In this work, we characterized, commissioned, and evaluated the QA capabilities of a novel commercial IMRT device, Delta4, (ScandiDos, Uppsala, Sweden). This device consists of diode matrices in two orthogonal planes inserted in a cylindrical acrylic phantom that is 22 cm in diameter. Although the system has detectors in only two planes, it provides a novel interpolation algorithm that is capable of estimating doses at points where no detectors are present. Each diode is sampled per beam pulse so that the dose distribution can be evaluated on segment‐by‐segment, beam‐by‐beam, or as a composite plan from a single set of measurements. The end user can calibrate the system to perform absolute dosimetry, eliminating the need for additional ion chamber measurements. The patient's IMRT plan is imported into the device over the hospital LAN and the results of the measurements can be displayed as gamma profiles, distance‐to‐agreement maps, dose difference maps, or the measured dose distribution can be superimposed on the patient's anatomy to display an as‐delivered plan. We evaluated the system's reproducibility, stability, pulse‐rate dependence, dose‐rate dependence, angular dependence, linearity of dose response, and energy response using carefully planned measurements. We also validated the system's interpolation algorithm by measuring a complex dose distribution from an IMRT treatment. Several simple and complex isodose distributions planned using a treatment planning system were delivered to the QA device; the planned and measured dose distributions were then compared and analyzed. In addition, the dose distributions measured by conventional IMRT QA, which uses an ion chamber and film, were compared. We found that the Delta4 device is accurate and reproducible and that its interpolation algorithm is valid. In addition, the supplied software and network interface allow a streamlined IMRT QA process. PACS number: 87.56Fc
Anticancer and apoptosis-inducing effects of quercetin in vitro and in vivo

The present study focused on the elucidation of the putative anticancer potential of quercetin. The anticancer activity of quercetin at 10, 20, 40, 80 and 120 µM was assessed in vitro by MMT assay in 9 tumor cell lines (colon carcinoma CT-26 cells, prostate adenocarcinoma LNCaP cells, human prostate PC3 cells, pheocromocytoma PC12 cells, estrogen receptor-positive breast cancer MCF-7 cells, acute lymphoblastic leukemia MOLT-4 T-cells, human myeloma U266B1 cells, human lymphoid Raji cells and ovarian cancer CHO cells). Quercetin was found to induce the apoptosis of all the tested cancer cell lines at the utilized concentrations. Moreover, quercetin significantly induced the apoptosis of the CT-26, LNCaP, MOLT-4 and Raji cell lines, as compared to control group (P<0.001), as demonstrated by Annexin V/PI staining. In in vivo experiments, mice bearing MCF-7 and CT-26 tumors exhibited a significant reduction in tumor volume in the quercetin-treated group as compared to the control group (P<0.001). Taken together, quercetin, a naturally occurring compound, exhibits anticancer properties both in vivo and in vitro.
SRR loaded and CB-CPW fed octagonal shape antenna for wearable applications

The SRR loaded circular ring encircled by an octagonal patch shaped conductor backed coplanar wave guide fed with miniaturizarised antenna is outstandingly necessary part for wearable device module for electroencephalogram (EEG) and healthcare monitoring. This antenna designed to fine-tune at resonating frequency of 2.41GHz and 3.6GHz. The simulated results for the magnitude of reflection coefficients are −13.3dB at 2.47GHz and −31dB at 3.6GHz for SRR loaded proposed antenna, −30.6dB at 2.41GHz and for non-SRR loaded proposed antenna respectively. These values are more suitable for standard ISM and WLAN communication.
Uplink training for pilot decontamination in a multiceli massive MIMO system

In this paper, we investigate pilot contamination in a multiceli massive multiple-input multiple-output (MIMO) system, in which the estimated channel state information (CSI) suffers a crucial difference from the real CSI. Pilot contamination is an obstacle to the achievable rate for users. We propose an uplink training strategy to limit the effect of intercell pilot contamination on channel estimation with low complexity. As a result, the downlink data rate through the reciprocity channels is significantly improved, which is verified by numerical results.
NVQuery: Efficient Query Processing in Nonvolatile Memory

Today’s computing systems use a huge amount of energy and time to process basic queries in database. A large part of it is spent in data movement between the memory and processing cores, owing to the limited cache capacity and memory bandwidth of traditional computers. In this paper, we propose a nonvolatile memory-based query accelerator, called NVQuery, which performs several basic query functions in memory including aggregation, prediction, bit-wise operations, join operations, as well as exact and nearest distance search queries. NVQuery is implemented on a content addressable memory and exploits the analog characteristic of nonvolatile memory in order to enable in-memory processing. To implement nearest distance search in memory, we introduce a novel bitline driving scheme to give weights to the indices of the bits during the search operation. To further improve the energy efficiency, our design supports configurable approximation by adaptively putting memory blocks under voltage overscaling. Our experimental evaluation shows that a NVQuery can provide <inline-formula> <tex-math notation="LaTeX">$49.3{\boldsymbol \times }$ </tex-math></inline-formula> performance speedup and <inline-formula> <tex-math notation="LaTeX">$32.9{\boldsymbol \times }$ </tex-math></inline-formula> energy savings as compared to running the same query on traditional processor. Approximation improves the energy-delay product (EDP) of NVQuery by <inline-formula> <tex-math notation="LaTeX">$7.3{\boldsymbol \times }$ </tex-math></inline-formula>, while providing acceptable accuracy. In addition, NVQuery can achieve <inline-formula> <tex-math notation="LaTeX">$30.1{\boldsymbol \times }$ </tex-math></inline-formula> EDP improvement as compared to the state-of-the-art query accelerators.
The Study of Evaluation and Rehabilitation of Patients With Different Cognitive Impairment Phases Based on Virtual Reality and EEG

The evaluation and rehabilitation (EAR) of patients with different cognitive impairment phases (PDCIP), including subjective cognitive decline (SCD) (Jessen et al., 2014; Innes et al., 2016a,b, 2017), mild cognitive impairment (MCI) (Weniger et al., 2011) and Alzheimer's disease (AD) (Serino et al., 2015), become a rapidly growing research field. Virtual reality (VR) has been reported to re-activate and/or improve multiple cortical functions (Baumann et al., 2003; Lin et al., 2008; Schedlbauer et al., 2014; Carrieri et al., 2016) and help optimize the coding efficiency of the sensory cortex (Ansuini et al., 2006; Keller et al., 2012; Ravassard et al., 2013; Schindler and Bartels, 2013; Sofroniew et al., 2015). Therefore, many researchers have started applying the VR technology to the EAR of PDCIP (Buss, 2009), including spatial memory (Allison et al., 2016), episodic memory (Valladares-Rodriguez et al., 2017), activities of daily living (Seo et al., 2017), language (Montenegro and Argyriou, 2017), executive function (Tost et al., 2014), short-term and working memory (Burdea et al., 2013), attention (Kalova et al., 2005), movement and balance (McEwen et al., 2014), and outdoor activities (Van Schaik et al., 2008). For EAR of PDCIP, the advantages of using VR over conventional approaches, such as electroencephalogram (EEG), functional magnetic resonance imaging (fMRI), and neuropsychological tasks, have been reported (Tarnanas et al., 2014a,b, 2015a). However, these studies did not record EEG during the course of evaluation and training within a VR environment, nor took full advantages of the EEG recordings to objectively explore the brain states of PDCIP in (near) real time, despite the combination of VR and EEG has been used in the EAR of other diseases, including stroke (I Badia et al., 2013; Lechner et al., 2014; Vourvopoulos and I Badia, 2016), paraplegic (Donati et al., 2016), autism (Amaral et al., 2017), attention deficit hyperactivity disorder (Rohani and Puthusserypady, 2015) and so on. The neuroimaging research for the EAR of PDCIP within a VR environment is still in its infancy, and more works need to be done before conclusions can be confidently drawn. This study will review the literature related to the EAR of PDCIP from the perspectives of VR and EEG, and discuss the potential advantages of the combined use of VR and EEG. It is expected that the analysis may provide useful suggestions to the field of the EAR of PDCIP.
Fault Estimation Filter Design With Guaranteed Stability Using Markov Parameters

For additive actuator and sensor faults, we propose a systematic method to design a state-space fault estimation filter directly from Markov parameters identified from fault-free data. We address this problem by parameterizing a system-inversion-based fault estimation filter with the identified Markov parameters. Even without building an explicit state-space plant model, our novel approach still allows the filter gain design for stabilization and $\mathcal {H}_2$ estimation performance. This design freedom cannot be achieved by other existing data-driven fault estimation filter designs so far. Simulation results using a continuous stirred tank reactor illustrate the effectiveness of the proposed new method.
A deep learning approach towards autonomous flight in forest environments

Nowadays unmanned aerial vehicles (UAV's) are increasingly considered in several engineering and safety applications to explore unknown environments. Forest environments are among these environments of interest where autonomous exploration and navigation is desirable with the caveat that GPS may not be accessible for localization of the drone. Motivated by the latter, in this paper we present a methodology for autonomous navigation of UAV in forest environments, paying particular attention to competences desired in autonomous navigation, namely detection and evasion of trees. Obstacle detection is performed using a deep neural network approach trained with a limited database but that exploits transferred learning from a well-known network architecture called Alexnet. In addition to the detection of a tree, a direction of avoidance is also recognized, this is, evasion to the left or to the right is obtained with the same learning scheme. Our approached was assessed in simulation by using the simulator Gazebo and also in a real outdoors scenario populated with trees.
ParBiBit: Parallel tool for binary biclustering on modern distributed-memory systems

Biclustering techniques are gaining attention in the analysis of large-scale datasets as they identify two-dimensional submatrices where both rows and columns are correlated. In this work we present ParBiBit, a parallel tool to accelerate the search of interesting biclusters on binary datasets, which are very popular on different fields such as genetics, marketing or text mining. It is based on the state-of-the-art sequential Java tool BiBit, which has been proved accurate by several studies, especially on scenarios that result on many large biclusters. ParBiBit uses the same methodology as BiBit (grouping the binary information into patterns) and provides the same results. Nevertheless, our tool significantly improves performance thanks to an efficient implementation based on C++11 that includes support for threads and MPI processes in order to exploit the compute capabilities of modern distributed-memory systems, which provide several multicore CPU nodes interconnected through a network. Our performance evaluation with 18 representative input datasets on two different eight-node systems shows that our tool is significantly faster than the original BiBit. Source code in C++ and MPI running on Linux systems as well as a reference manual are available at https://sourceforge.net/projects/parbibit/.