Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of purple grape juice on the pharmacokinetics of digoxin: Results of a food-drug interaction study .

OBJECTIVE Digoxin is a glycosidic, cardiotonic plant extract with a narrow therapeutic window. The purpose of the study was to investigate the effects of purple grape juice on the pharmacokinetics of digoxin in rats. MATERIALS AND METHODS A randomized, controlled, single- and multiple-dose study was conducted to evaluate the pharmacokinetic profiles of orally and intravenously administered digoxin. The plasma concentration of digoxin was determined by radioimmunoassay using a gamma counter, and a Caco-2 cell transport model was used to investigate the potential mechanism by which purple grape juice affects the pharmacokinetics of digoxin. RESULTS The results show that multiple-dose purple grape juice caused a remarkable increase in the AUC, Cmax, and Ka of orally administered digoxin (p < 0.05); only a single dose increased the digoxin AUC0-∞ by 72.80% (p < 0.05). Other parameters were not significantly affected. The study of intravenously administered digoxin found no significant difference in the pharmacokinetic characteristics of the two dosing groups (p > 0.05). The Caco-2 transwell experiments indicated that both the pure purple grape juice and its ethyl acetate extract significantly inhibited digoxin basolateral-to-apical (B→A) transport at concentrations of 10%, 30%, and 50% with dose dependency. These results confirmed that the improvement in bioavailability of digoxin resulted from the inhibition of P-gp by purple grape juice at the level of the gastrointestinal wall. CONCLUSION Purple grape juice can increase the bioavailability of orally administered digoxin, especially with multiple doses. This information suggests that co-administration of oral digoxin and purple grape juice may require a dose adjustment.
Taxonogenomics description of Parabacteroides timonensis sp. nov. isolated from a human stool sample

Intensive efforts have been made to describe the human microbiome and its involvement in health and disease. Culturomics has been recently adapted to target formerly uncultured bacteria and other unclassified bacterial species. This approach enabled us to isolate in the current study a new bacterial species, Parabacteroides timonensis strain Marseille‐P3236T, from a stool sample of a healthy 39‐year‐old pygmy male. This strain, is an anaerobic, gram‐negative, nonspore‐forming motile rod. Its genome is made up of 6,483,434 bp with 43.41% G+C content, 5046 protein‐encoding genes, and 84 RNA genes. We herein provide the full description of Parabacteroides timonensis strain Marseille‐P3236T through the taxonogenomic approach.
Bayesian Optimisation of Exoskeleton Design Parameters

Exoskeletons are currently being developed and used as effective tools for rehabilitation. The ideal location and design of exoskeleton attachment points can vary due to factors such as the physical dimensions of the wearer, which muscles or joints are targeted for rehabilitation or assistance, or the presence of joint misalignment between the human subject and exoskeleton device. In this paper, we propose an approach for identifying the ideal exoskeleton cuff locations based on a human-in-the-Ioop optimisation process, and present an empirical validation of our method. The muscle activity of a subject was measured while walking with assistance from the XoR exoskeleton (ATR, Japan) over a range of cuff configurations. A Bayesian optimisation process was implemented and tested to identify the optimal configuration of the XoR cuffs which minimised the measured EMG activity. Using this process, the optimal design parameters for the XoR were identified more efficiently than via linear search.
Radiation Dose Optimization in Pediatric Chest CT: Major Indicators of Dose Exposure in 1695 CT Scans over Seven Years

Abstract Purpose To analyze possible influencing factors on radiation exposure in pediatric chest CT using different approaches for radiation dose optimization and to determine major indicators for dose development. Materials and Methods In this retrospective study at a clinic with maximum care facilities including pediatric radiology, 1695 chest CT examinations in 768 patients (median age: 10 years; range: 2 days to 17.9 years) were analyzed. Volume CT dose indices, effective dose, size-specific dose estimate, automatic dose modulation (AEC), and high-pitch protocols (pitch ≥ 3.0) were evaluated by univariate analysis. The image quality of low-dose examinations was compared to higher dose protocols by non-inferiority testing. Results Median dose-specific values annually decreased by an average of 12 %. High-pitch mode (n = 414) resulted in lower dose parameters (p < 0.001). In unenhanced CT, AEC delivered higher dose values compared to scans with fixed parameters (p < 0.001). In contrast-enhanced CT, the use of AEC yielded a significantly lower radiation dose only in patients older than 16 years (p = 0.04). In the age group 6 to 15 years, the values were higher (p < 0.001). The diagnostic image quality of low-dose scans was non-inferior to high-dose scans (2.18 vs. 2.14). Conclusion Radiation dose of chest CT was reduced without loss of image quality in the last decade. High-pitch scanning was an independent factor in this context. Dose reduction by AEC was limited and only relevant for patients over 16 years. Key Points The radiation dose of pediatric chest CT was reduced in the last decade. High-pitch scanning is an independent factor of dose optimization. Dose reduction by AEC is limited and only relevant for older children. Citation Format Esser M, Hess S, Teufel M et al. Radiation Dose Optimization in Pediatric Chest CT: Major Indicators of Dose Exposure in 1695 CT Scans over Seven Years. Fortschr Röntgenstr 2018; 190: 1131 – 1140
Detection and Assessment of Partial Shading Scenarios on Photovoltaic Strings

There has been growing interest in using photovoltaic (PV) energy harvesting technology to reduce reliance on mineral-based energy. Partial shading scenarios (PSS) significantly affect the electrical characteristics of a PV generator. However, a few studies have devoted to the detection and assessment of the PSS. In this paper, shading rate and shading strength are used to characterize the PSS. A shading pattern detection algorithm is proposed to estimate the number of shaded modules in a PV string and distinguish the PSS from uniform irradiation scenarios. A multiple-output support vector regression is applied to estimate the shading strength. In addition, the maximum power point voltage of the applied PV generation system can be predicted from measured data. Simulation and experimental validation show the feasibility of the proposed method in the face of various environmental conditions. It could be used as a preliminary step toward automatic supervision and monitoring PV generation system.
Molecular Cloning and Expression of MnGST-1 and MnGST-2 from Oriental River Prawn, Macrobrachium nipponense, in Response to Hypoxia and Reoxygenation

The glutathione-S-transferase (GST) superfamily includes seven classes, and different classes have different functions. GST superfamily members function in various processes including detoxification of xenobiotics, protection against oxidative damage, and intracellular transport of hormones, endogenous metabolites, and exogenous chemicals. Herein, to elucidate the tissue-specific expression pattern of GSTs in response to hypoxia stress, which induces cell death, we investigated the expression of GSTs in response to hypoxia and reoxygenation in oriental river prawn, Macrobrachium nipponense. Full-length cDNAs of two δ class GSTs were cloned from the hepatopancreas, and named MnGST-1 and MnGST-2 based on the established GST nomenclature system. Expression profiles of both GSTs in various tissues were different under acute and chronic experimental hypoxia stress conditions, suggesting that both respond strongly to hypoxia-induced oxidative stress. However, the intensity of responses to hypoxia and reoxygenation were different in different tissues. During acute hypoxia stress, MnGST-1 responds earlier than MnGST-2 in the hepatopancreas and gill, but more slowly in muscle. By contrast, during chronic hypoxia stress, MnGST-2 plays a more important role in the hepatopancreas and gill than MnGST-1.
Prometheus : Directly Learning Acyclic Directed Graph Structures for Sum-Product Networks

In this paper, we present Prometheus, a graph partitioning based algorithm that creates multiple variable decompositions efficiently for learning Sum-Product Network structures across both continuous and discrete domains. Prometheus proceeds by creating multiple candidate decompositions that are represented compactly with an acyclic directed graph in which common parts of different decompositions are shared. It eliminates the correlation threshold hyperparameter often used in other structure learning techniques, allowing Prometheus to learn structures that are robust in low data regimes. Prometheus outperforms other structure learning techniques in 30 discrete and continuous domains. We also describe a sampling based approximation of Prometheus that scales to high-dimensional domains such as images.
Disease progression in blepharospasm: a 5‐year longitudinal study

The clinical manifestation of dystonic spasms in blepharospasm (BSP) patients may be heterogeneous. Whether the varying phenomenology of eyelid spasms becomes manifest sequentially during the course of the disease or aggregates in separate clusters according to different disease courses is still unclear. For this purpose, the clinical features in BSP patients were evaluated longitudinally over a 5‐year period and also the blink reflex recovery cycle was tested in a subgroup of BSP patients.
Walmart's Sales Data Analysis - A Big Data Analytics Perspective

Information technology in this 21st century is reaching the skies with large-scale of data to be processed and studied to make sense of data where the traditional approach is no more effective. Now, retailers need a 360-degree view of their consumers, without which, they can miss competitive edge of the market. Retailers have to create effective promotions and offers to meet its sales and marketing goals, otherwise they will forgo the major opportunities that the current market offers. Many times it is hard for the retailers to comprehend the market condition since their retail stores are at various geographical locations. Big Data application enables these retail organizations to use prior year’s data to better forecast and predict the coming year’s sales. It also enables retailers with valuable and analytical insights, especially determining customers with desired products at desired time in a particular store at different geographical locations. In this paper, we analysed the data sets of world’s largest retailers, Walmart Store to determine the business drivers and predict which departments are affected by the different scenarios (such as temperature, fuel price and holidays) and their impact on sales at stores’ of different locations. We have made use of Scala and Python API of the Spark framework to gain new insights into the consumer behaviours and comprehend Walmart’s marketing efforts and their data-driven strategies through visual representation of the analysed data.
Congestion Control Mechanism in Software Defined Networking by Traffic Rerouting

Software defined networking enables the network administrator to have centralized control over the entire network by splitting the data plane from the control plane. Software Defined Network also enables the user to program the various network elements. With increasing amount of traffic in the current day network, congestion tends to be a vital problem to be solved. The congestion in the networks is caused by a heavy surge of packets at one particular region on the topology. The congestion can be avoided using the SDN framework with the shortest path algorithm where several shorter parts of similar lengths are found and the traffic is redirected based on the obtained traffic details. The obtained results show that the throughput and bandwidth values have increased considerably.
Computationally Efficient Implementation of Dynamic Matrix Control Algorithm for Very Fast Processes Using Programmable Logic Controller

This work reports implementation of the Dynamic Matrix Control (DMC) algorithm using a Programmable Logic Controller (PLC). In contrast to typical industrial implementations of the DMC algorithm with relatively long time constants (and sampling times), in this work very fast processes are considered, characterised by very short sampling times. The DMC algorithm is implemented in its most computationally efficient version in which the values of the manipulated variables are calculated from explicit formulas. Thanks to that it is shown that the DMC algorithm is able to successfully control a laboratory process with the sampling time equal to 5 ms. The first process configuration has one input and one output whereas the second one has two inputs and two outputs. The influence of the process horizon of dynamics on the algorithm execution time and PLC's memory usage is discussed.
An Empirical Evaluation of Flow Tagging Mechanisms and Service Function Platform Choices for NFV/SFC

In this research study, we discuss some design details of the NFV (Network Function Virtualization) architecture, especially under considerations of Softwaredefined Networking (SDN) technical supports. Two design issues of NFV/SFC are discussed in particularly: flow tagging mechanisms and service function platform choices. In the flow tagging mechanisms, we discuss three possible tagging mechanisms: mac-rewrite, VLAN ID, and MPLS label. For service function platform choices, we compare the difference between using KVM (Virtual Machine) and using Docker (Container). To investigate performance difference under different design considerations, we built a simplified NFV system. For each design issues concerned in this these work, we conducted different experiments under the simplified NFV system.
Comparative analysis of OMP and ROMP for sparse recovery of temporally correlated data in WSNs

Greedy algorithms have the advantages of low computational complexity and ease of implementation over the linear programming optimization techniques. A few greedy algorithms work on the principle of selecting a single column whereas, in others, multiple columns are selected in each iteration. In this paper, a comparison is performed on the experimental data which is collected using NI WSN test bed, to find out a more efficient algorithm for sparse signal recovery. Algorithms are compared on the basis of peak signal to noise ratio, root mean square error and speed of recovery. Based on the simulation results, ROMP is preferred over OMP in case of sparse signals with enough sparsity.
Coverage mandates and market dynamics: employer, insurer and patient responses to parity laws

Abstract Parity in coverage for mental health services has been a longstanding policy aim at the state and federal levels and is a regulatory feature of the Affordable Care Act. Despite the importance and legislative effort involved in these policies, evaluations of their effects on patients yield mixed results. I leverage the Employee Retirement Income Security Act and unique claims-level data that includes information on employers’ self-insurance status to shed new light in this area after the implementation of two state parity laws in 2007 and federal parity a few years later. My empirics reveal evidence of strategic avoidance on behalf of insurers in both states prior to the passage of state parity, as well as positive increases in mental health care utilization after parity laws are implemented – but context matters. Policy heterogeneity across states and strategic behaviors by employers and commercial insurers substantively shape the benefits that ultimately flow to patients. Insights from this research have broad relevance to ongoing health policy debates, particularly as states retain great discretion over many health coverage decisions and as federal policy continues to evolve.
An Operational Concept for Correcting Navigation Drift During Sonar Surveys of the Seafloor

The accumulation of navigation errors (drift) is a problem in many applications of autonomous underwater vehicles (AUVs), particularly during long-duration underwater surveys. Traditional methods for correcting drift require either surfacing of the vehicle for a global navigation satellite systemupdate or use of an independent acoustic positioning system. These methods may not be desirable or possible due to mission constraints. We propose a solution to this problem completely underwater and without the aid of external navigation systems. The approach is based on an operational concept that uses a modified paired-track survey pattern combined with through-the-sensor navigation corrections from a seafloor imaging sonar. We describe the operational concept, derive a model for its performance limits, validate this model, and demonstrate the concept with real experiments at sea. Using this approach, we provide an opportunity to use either coherent or incoherent through-the-sensor positioning corrections for a mission length increase of only the product of the intratrack spacing and the number of track pairs. We show results from a proof-of-principle experiment using data collected by the ${\text{300-kHz}}$ synthetic aperture sonar of the NATO Centre for Maritime Research and Experimentation's Minehunting Unmanned underwater vehicle for Shallow water Covert Littoral Expeditions.
Fucoxanthin-Containing Cream Prevents Epidermal Hyperplasia and UVB-Induced Skin Erythema in Mice

Microalgae represent a source of bio-active compounds such as carotenoids with potent anti-inflammatory and antioxidant properties. We aimed to investigate the effects of fucoxanthin (FX) in both in vitro and in vivo skin models. Firstly, its anti-inflammatory activity was evaluated in LPS-stimulated THP-1 macrophages and TNF-α-stimulated HaCaT keratinocytes, and its antioxidant activity in UVB-irradiated HaCaT cells. Next, in vitro and ex vivo permeation studies were developed to determine the most suitable formulation for in vivo FX topical application. Then, we evaluated the effects of a FX-containing cream on TPA-induced epidermal hyperplasia in mice, as well as on UVB-induced acute erythema in hairless mice. Our results confirmed the in vitro reduction of TNF-α, IL-6, ROS and LDH production. Since the permeation results showed that cream was the most favourable vehicle, FX-cream was elaborated. This formulation effectively ameliorated TPA-induced hyperplasia, by reducing skin edema, epidermal thickness, MPO activity and COX-2 expression. Moreover, FX-cream reduced UVB-induced erythema through down-regulation of COX-2 and iNOS as well as up-regulation of HO-1 protein via Nrf-2 pathway. In conclusion, FX, administered in a topical formulation, could be a novel natural adjuvant for preventing exacerbations associated with skin inflammatory pathologies as well as protecting skin against UV radiation.
Dietary Patterns and Attention Deficit Hyperactivity Disorder Among Iranian Children: A Case-Control Study

Abstract Objective: Associations between nutritional/dietary factors and mental disorders have been suggested. This study was conducted to assess the relation of major dietary patterns determined by factor analysis with attention-deficit/hyperactivity disorder (ADHD) in a group of Iranian preschool- and school-aged children. Methods: This case-control study was conducted with 500 preschool- and school-aged children (4–12 years old) matched by age and sex, in Isfahan, Iran. Dietary intake was identified by a 168-item questionnaire, and major dietary patterns were identified by factor analysis. The multivariable logistic regression is used for the association of dietary patterns with the diagnosis of ADHD. ADHD diagnosis was carried out with the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Results: Two major dietary patterns were identified: healthy and Western. The healthy dietary pattern was rich in fruits, vegetables, vegetable oils, whole grains, legumes, and dairy products. The Western pattern was rich in processed meat, red meat, pizza, eggs, snacks, animal fat, hydrogenated fat, and salt. After controlling for potential confounders, children in the top quintile of the Western dietary pattern score had greater odds having ADHD, compared with those in the lowest quintile (odds ratio [OR] = 3.45; 95% confidence interval [CI], 1.17–18.3; ptrend = 0.03). The healthy pattern was inversely associated with ADHD (OR = 0.46; 95% CI, 0.38–0.91; ptrend = 0.01). Conclusions: A significant independent association was found between the Western dietary pattern and the odds of ADHD. The healthy dietary pattern was associated with lower odds of having ADHD. Prospective studies are needed to confirm these findings.
Synergistic Effect of Laccase and Sugar Beet Pectin on the Properties of Concentrated Protein Emulsions and Its Application in Concentrated Coconut Milk

Concentrated coconut milk (CCM), a raw material from coconut products, is extremely unstable because of its high oil content (>30%). In this study, three model emulsions—primary emulsions stabilized by coconut proteins only, secondary emulsions stabilized by the conjugation of sugar beet pectin (SBP) and coconut protein, and laccase-treated secondary emulsions—were prepared to investigate the effects of different factors (coconut proteins, coconut proteins + SBP, laccase-treated emulsions) on the stability of model emulsions and the application of this method to real CCM. The stability of the emulsions was evaluated based on their interfacial tension, zeta potential, particle size distribution, rheological properties, and the assembly formation of SBP and coconut protein at the oil–water interface. Results showed that addition of SBP or laccase can increase the viscosity and reduce the interfacial tension of the emulsion, and the effect was concentration dependent. Zeta potential of the emulsion decreased with the increase of protein (from −16 to −32 mV) and addition of SBP (from −32 to −46 mV), and it was reduced when laccase was added (from −9.5 to −6.0 mV). The secondary emulsion exhibited the narrowest particle size distribution (from 0.1 to 20 μm); however, laccase-catalyzed secondary emulsions showed the best storage stability and no layering when the laccase content reached 10 U/100 g. Confocal laser scanning microscopy (CLSM) revealed that protein was adsorbed on the oil–water interface and SBP distributed in the continuous phase could undergo oxidative crosslinking by laccase. These results show that the stability of the concentrated emulsion can be effectively improved by adding SBP and laccase.
Continuous Modulation of Step Height and Length in Bipedal Walking, Combining Reflexes and a Central Pattern Generator

Deploying humanoid robots in complex and unstructured environments requires the development of efficient and adaptive locomotion controllers. Bio-inspiration holds promises in this perspective, since humans are known to have both an energy efficient gait, and the capacity to modulate it across several features like forward speed and step length and height. In this paper, we report the development of a bio-inspired controller for bipedal walking that can achieve controlled modulations of the step height and length over a large range. This controller builds upon our previous work where we combined both a Central Pattern Generator (CPG) and reflex-like modulations with a layer of virtual muscles providing human-like leg impedance. Here, we report first a sensitivity analysis that was performed to identify those among the many parameters of our controller that can actually modulate the step height and length. Then, we report experimental results illustrating such controlled modulations over a large parameter space.