Miracle-dz/UniFAR-FTUs huggingface dataset:
Food and Applied Bioscience Journal

Plant extracts with various bioactive compounds have gained considerable attention especially when used as functional ingredient. The aims of the present study were to profile the bioactive and volatile compounds in different maturity stages of torch ginger (Etlingera elatior) and also to study the effect of drying methods on bioactive compounds of torch ginger (Etlingera elatior) extract. The bioactive compounds in unopened and opened torch ginger were identified using Gas Chromatography-Mass spectrometry (GCMS). Unopened torch ginger flower was sun-dried with mid-day temperature ranged from 35–40°C for almost 27 hours, overnight oven drying at 40°C and the torch ginger also be lyophilized for 48 hours in a vacuum flask at 0.125 mbar and -50°C in a freeze-dryer till moisture content reached 10±2% in weight. The total phenols, total flavonoids and antioxidant activity of unopened torch ginger extract were determined by using UV-vis spectrophotometer. The most abundant compounds in torch ginger included á-pinene, decanal, and 1-dodecanol. Freeze-dried unopened torch ginger flower resulted the highest level of total phenols content (485.50±3.24mg GAE/100g), total flavonoids (61.26±14.87 mg GAE/100g), ferric reducing assay power (1943.50±84.15mg GAE/100g) and scavenging activity (89.24±1.24%) respectively. The extract from torch ginger flower could be potentially used as a new source of natural antioxidant in functional ingredient.
Combination of the artificial neural network and advection-dispersion equation for modeling of methylene blue dye removal from aqueous solution using olive stones as reactive bed

In the present investigation, the propensity of olive stones (OS) to be utilized in the removal of methylene blue dye (MBD) from polluted water was analyzed. The three-layer artificial neural network (ANN) model has been used as an alternative method in fixing the relationship describing the sorption process accurately and matching with the experimental results. Therefore, 137 batch experiments were performed for characterizing the equilibrium sorption properties. Applying the ANN model proved that the contact time was the most influential parameter. Subsequently, the transport of methylene blue dye through the OS bed was described by integrating the ANN model with the advection–dispersion equation which describes the transport of contaminant in the porous medium resulting in a good agreement between expected and measured results with a correlation coefficient (R) greater than 0.9789.
Diagnostic potential of gut microbiota in Parkinson’s disease

Background. Nowadays many efforts are taken in searching for Parkinson’s disease biomarkers, especially for an early recognition of the disease. The gut microbiota is one of the potential sources of biomarkers, changes in the composition of which in PD are actively studied. The aim of this study is to identify microbiota biomarkers in the Parkinson’s disease with an estimated accuracy of the diagnostics, including differential diagnostics, relative to other neurological diseases for patients of the Russian population. Material and methods. One hundred ninety-two metagenomics profiles from patients with Parkinson’s disease (n = 93), people with other neurological diagnoses (n = 33), and healthy controls (n = 66) were included in this study. These profiles were obtained with amplicon sequencing of bacterial 16S rRNA genes. Classifying models were made using the naive Bayes classifier, the artificial neural network, support vector machine, generalized linear model, and partial least squares regression. As a result we established that an optimal classification by the composition of the gut microbiota on the validation sample (sensitivity 91.30%, specificity 91.67% at 91.49% accuracy) amid patients was demonstrated with a naive Bayes classifier using the representation of the following genera as predictors: Christensenella, Methanobrevibacter, Leuconostoc, Enterococcus, Catabacter, Desulfovibrio, Sphingomonas, Yokenella, Atopobium, Fusicatenibacter, Cloacibacillus, Bulleidia, Acetanaerobacterium, and Staphylococcus. Conclusions. Information of the gut microbiota taxonomic composition may be used in differential diagnosis of Parkinson’s disease.
Progression-free survival (PFS) and health-related quality of life (HRQoL) in AVAglio, a phase III study of bevacizumab (Bv), temozolomide (T), and radiotherapy (RT) in newly diagnosed glioblastoma (GBM).

2005^ Background: GBM has a high disease burden and poor prognosis, and impacts negatively on HRQoL. Symptomatic therapies for GBM, such as corticosteroids (CS), may impact patient status negatively Methods: AVAglio, a randomized, double-blind, placebo (P)-controlled trial in patients (pts) ≥18 yrs with newly diagnosed GBM, evaluated the addition of Bv or P (10mg/kg, q2w) to 6 wks of T (75mg/m2/d) + RT (2Gy, 5d/wk) followed by 28 treatment-free days, then 6 cycles of T (150–200 mg/m2/d, 5d q4w) with Bv or P (10 mg/kg, q2w), and then single-agent Bv or P (15 mg/kg, q3w) until disease progression (PD)/unacceptable toxicity. Co-primary endpoints were investigator-assessed PFS and overall survival. Secondary endpoints included HRQoL (EORTC QLQ-C30 and BN20, with 5 prespecified domains based on relevance in GBM). HRQoL time to definitive deterioration (TDD) was defined as time from randomization to ≥10 point deterioration from baseline with no subsequent improvement, PD, or death. Exploratory endpoints include.
Single mothers' contact frequency with family and non-family members

Existing studies on single mothers’ social contacts often examine small selective samples and are mostly cross-sectional. The lack of high-quality longitudinal survey data on this subject constrains the possibility to draw more generalizable conclusions. This paper exploits panel data to investigate whether transitions to single motherhood affect contact frequency. Fixed-effects models are used on the six waves of the German ‘Socio-economic Panel’ survey that contain social contact data (1990, 1995, 1998, 2003, 2008, 2013) for analyzing whether single motherhood is associated with changes in contact frequency with family and non-family members. Findings show that women transitioning to single motherhood maintain contact with family and non-family members. Single motherhood is unlikely to cause mothers’ structural isolation. However, the absence of a second parent in the household neither seems to be connected with an increase in contact frequency with others. Providing a more generalised account of single mothers’ social contacts over time than previous research, the present study does not find evidence for a disintegrative effect of single motherhood.
Microemulsions and Nanoparticles as Carriers for Dermal and Transdermal Drug Delivery

The major obstacle of dermal and transdermal therapeutics is the low penetration rate of xenobiotics through the skin due to the diffusional barrier of its upper layer, the stratum corneum. A wide array of techniques has been proposed thus far, however, recent developments in the application of nanosystems for topical drug administration have gained much interest and optimism. In this review, we provide a comprehensive overview of the main types of nanocarriers that have been studied and developed up-to-date. We conclude that the nanosystems may become a useful dosage form for a variety of dermally active principals by modulating drug transfer and serving as nontoxic penetration enhancers.
Reducing the Grid Dependency of Large Buildings Through Renewable Integrated Microgrids

In this paper, we investigate the possibilities of reducing the grid based conventional energy consumption in large buildings through the integration of a microgrid supplemented by renewable energy sources. An educational building, with an average annual consumption of 317.55 MWh was chosen for the study. Based on the daily energy consumption pattern of the building and renewable energy resource potential at the site, a microgrid has been optimally designed for minimizing the Cost of Energy. It could be seen that, 38.8 % of the total energy demand of the building can be met by wind energy, by installing a turbine of 40kW rated capacity, which would contribute 129.3 MWh per annum to the proposed microgrid. This can also reduce the cost of electricity from the current rate of 0.12 $/kWh to 0.107 $/kWh. Sensitivities of the Cost of Energy, renewable energy system capacity and excess renewable energy, on the renewable penetration levels are presented. The sensitivity of the Cost of Energy on different levels of emission reduction through increased renewable penetration is also discussed. The technical feasibility and economic viability of renewable integrated microgrids, in reducing the grid dependency of large buildings, has been established under this study. IndexTerms Microgrids, Cost of Energy, Life Cycle Emission, Net Present Cost, HOMER, Renewable Energy Fraction.
INFLUENCE OF PRESERVATIVE CHEMICALS AND GROWTH REGULATORS ON THE POST HARVEST PHYSICAL PARAMETERS OF GLADIOLUS SPIKES (Gladiolus grandiflorus L.) cv. AMERICAN BEAUTY

The present investigation on the “Influence of preservative chemicals and growth regulators on the post harvest physical parameters of gladiolus (Gladiolus grandiflorus L.) cv. American Beauty” was carried out in the Department of Horticulture, Faculty of Agriculture, Annamalai University, Annamalainagar. The experiment was conducted in a Completely Randomized Design with 13 treatments in three replications. The treatments consisted of two preservative chemicals viz., 8hydroxy quinoline sulphate @ 150, 300, 450 ppm and silver nitrate @ 25, 50, 75 ppm along with benzyl adenine (BA) @ 20, 40 and 60 ppm and gibberellic acid (GA3) @ 10, 25 and 40 ppm and a control (distilled water) was also maintained. The results of the experiment revealed that the best treatment was T2 (8-HQS 300 ppm + 4 % sucrose + BA 40 ppm) in terms of all the physical parameters viz., days taken for the basal floret to open in vase, longevity of florets, ornamental value and vase life. From the above results it has been concluded that the use of vase solution containing 8 HQS 300 ppm + sucrose 4 per cent + BA 40 ppm was found better for extending the vase life and maintaining quality of gladiolus cv. American Beauty.
Globalization beyond partitioning

In an ultra-globalized world, all existing firms service all markets (zero partitioning) and some may need to cross-subsidize. Especially, intense competition forces low productivity firms to compensate losses on the home market with profits made on foreign markets. Are there still gains from further trade liberalization in such a situation? We present a simple and tractable heterogeneous firms specification to address this question. The answer we find is: yes, even more. JEL: F12, F13, F15
BIOTECHNO 2017

— We established a new theory of discriminant analysis after R. Fisher. We developed two methods and four Optimal Linear Discriminant Functions (OLDFs) in order to solve five serious problems of discriminant analysis. Over than 30 years, many researchers could not select cancer genes from gene datasets such as microarray datasets (Problem 5). The Matryoshka feature selection method (Method 2) could separate the dataset to several linearly separable subspaces (Small Matryoshka, SM) and non-linearly separable subspace definitely. We consider genes including each SM are cancer genes because they can discriminate cancer patients versus normal patients completely. On the other hand, other genes cannot discriminate two classes correctly and are noise. Therefore, Method 2 can separate the dataset to several signal SMs and noise subspace naturally. In this study, we introduce how to analyze all SMs of six datasets using common statistical methods and propose malignancy indexes for cancer gene diagnosis. Because our standard statistical approach obtains almost the same successful results, we explain the results by Alon et al. dataset. Researchers can analyze their dataset by our approach.
SIGNAL PROCESSING BY MEANS OF “ CATERPILLAR ” – SSA METHOD

This paper deals with “Caterpillar”-SSA method - a new powerful method of time series analysis and forecasting, which was independently developed in Russia (under the name of “Caterpillar”) and also in UK and USA (under the name of SSA - Singular Spectrum Analysis). This model-free method intended to study the structure of the time series, combines the advantages of many other methods, such as Fourier analysis and regression analysis and at the same time it is characterized by clarity and controllability. The method can be successfully used for processing the signals from the vibrating structure elements and machine parts. Alongside with signal processing this method is successfully used to study the time series in many various areas: in medicine, meteorology, hydrology, sociology, economics, traffic analysis, wherever the trend or periodic behavior can present. This paper shows how SSA method may be realized in MATHCAD program, which is a convenient tool for the engineers.
Detecting the phishing websites with machine learning

:- Harmful URLs had been consistently used to mount remarkable programmed attacks consisting of spamming, phishing and malware. Divulgence of vindictive URLs and obvious confirmation of hazard organization are key to destroy those ambushes. Knowing the form of a opportunity connects with estimation of truth of the strike and gets a conceivable countermeasure. Existing strategies routinely cozy poisonous URLs of a solitary strike form. In this paper, we include device the utilization of contraption spotting how to isolate dangerous URLs of all a similar old snare company and notice strike a threatening URL endeavors to dispatch. Our strategy makes usage of a recreation plan of discriminative highlights which incorporate uncovered homes, be a piece of structures, web page substance, DNS assurances, and gadget side hobby. Huge amounts of these highlights are novel and spectacularly successful.
The Impact of Increased Openness and Structural Reforms

Firm productivity is affected by increased competition. Theoretical research shows that higher competition allows or compels firms to cut down managerial slack. Also, according to theoretical arguments, competition affects a company’s incentives to innovate. This effect, however, is contextual dependent. While increased competition induce firms close to the technology frontier to invest more in innovation, backward firms reduce innovation. In the present paper we empirically assess the impact of increased competition on firm productivity and the importance of the initial firm efficiency level using a financial panel data set of Czech companies for the period 1993-2005. After the collapse of the communist system in 1989 the Czech economy underwent a series of reforms that have lead to tougher competition in all its markets.
Improvement of Robustness Blind Image Restoration Method Using Failing Detection Process

—Blurring is one of the representative image degradation, and much research has been done on its restoration -. In these studies, the degradation process of the image is modeled by a point spread function (PSF: Point Spread Function) of blurring, and it is possible to recover from one input image by estimating its PSF. However, when noise is mixed into the image due to factors such as the characteristics of the camera, there is still a failure of the image due to PSF estimation error. In this paper, we introduce a ringing removal method using L 0 regularization. We propose a high-performance restoration method that can estimate clear images, and confirm its effectiveness by experiments.
Clinico-biochemical alternation in bovine ketosis

The study was aimed to study clinico-biochemical profile of bovine ketosis in Kashmir valley. During the study, 309 milk-cows of mixed population were screened for suspected ketosis out of which 28 were positive for clinical ketosis and 81 for subclinical ketosis and 08 animals were kept as healthy control. The body temperature, respiration rate and heart rate in affected animal was within the normal range, however rumen motility was decreased. The most consistent clinical signs were sudden drop in milk yield (100.00%) and selective feeding (75.00%). Wasting (35.71%), complete anorexia (25.00%), acetone smell in breath/milk (17.85%), depression (39.28%), constipation (14.28%), dry and scant faeces (21.42%), disinclination to move (3.57%) and nervous signs (3.57%) were observed in less than 50% of cases. The multi-diagnostic strip reaction (Siemens) in ketotic cows showed (+++) in eight cases, (++) in four cases and (+) in nine cases. Whereas urobilinogen, blood, specific gravity, bilirubin, nitrites and glucose were normal in all cases of ketosis in cattle, although presence of leucocytes (7/28), proteinurea (6/28) and lowered urine pH were seen in four cases. There was a significant decrease in blood glucose level in clinical ketosis compared to control group. The plasma NEFA and BHBA levels were significantly increased in both clinical and subclinical ketosis.
Revitalizing cultivation and strengthening the seed systems of fonio and Bambara groundnut in Mali through a community biodiversity management approach

Abstract Fonio (Digitaria exilis (Kippist) Stapf) and Bambara groundnut (Vigna subterranea (L.) Verdc. ) are native crops grown at a small scale in Mali that have potential to support agricultural productivity under climate change. A community biodiversity management approach was explored in this study as a means to reinforce the cultivation of these crops by increasing farmers' access to intraspecific diversity and developing capacities of community institutions for their management. The research involved six communities in Ségou and Sikasso regions. Multiple varieties of fonio (10–12) and Bambara groundnut (8–12) were established in diversity fields in each site over 2 years where farmers engaged in experiential learning over the crop cycle. Significant adoption of fonio and Bambara groundnut was detected in several study sites. The precise drivers of adoption cannot be definitively determined but likely include increased seed access and awareness gained through the diversity field fora, seed fairs and community seed banks. No significant yield advantage was detected for any of the varieties in the diversity fields, which showed variable performance by site and year. The number of varieties registered and managed by community seed banks in each site increased from 1–5 varieties of each crop to 11–12 varieties following the interventions. The number of Bambara groundnut varieties cultivated in farmers' fields also increased, while there was evidence of a slight decline in fonio diversity in some communities. The results of this study can inform efforts to strengthen seed systems and cultivation of neglected and underutilized species in Africa.
R&D offshoring: What determines the choice between FDI and international outsourcing?

We empirically analyse the determinants of firms’ choices between offshore R&D through companies that belong to the same business group (FDI), through external providers (international outsourcing), or through both sources (bi-sourcing). We use a newly available firm-level panel data set, which provides unique information on firms’ R&D imports by type of provider. We find that very R&D intensive companies offshore R&D through FDI. We also show that there is a complementarity between patents and international outsourcing. Our results suggest that the reason to import R&D through FDI channels is to avoid the vulnerability to technology leakage.
Identification of FOS as a Candidate Risk Gene for Liver Cancer by Integrated Bioinformatic Analysis

Liver cancer is a lethal disease that is associated with poor prognosis. In order to identify the functionally important genes associated with liver cancer that may reveal novel therapeutic avenues, we performed integrated analysis to profile miRNA and mRNA expression levels for liver tumors compared to normal samples in The Cancer Genome Atlas (TCGA) database. We identified 405 differentially expressed genes and 233 differentially expressed miRNAs in tumor samples compared with controls. In addition, we also performed the pathway analysis and found that mitogen-activated protein kinases (MAPKs) and G-protein coupled receptor (GPCR) pathway were two of the top significant pathway nodes dysregulated in liver cancer. Furthermore, by examining these signaling networks, we discovered that FOS (Fos proto-oncogene, AP-1 transcription factor subunit), LAMC2 (laminin subunit gamma 2), and CALML3 (calmodulin like 3) were the most significant gene nodes with high degrees involved in liver cancer. The expression and disease prediction accuracy of FOS, LAMC2, CALML3, and their interacting miRNAs were further performed using a HCC cohort. Finally, we investigated the prognostic significance of FOS in another HCC cohort. Patients with higher FOS expression displayed significantly shorter time to recurrence (TTR) and overall survival (OS) compared with patients with lower expression. Collectively, our study demonstrates that FOS is a potential prognostic marker for liver cancer that may reveal a novel therapeutic avenue in this lethal disease.
Maximizing Information Gain in Partially Observable Environments via Prediction Reward

Information gathering in a partially observable environment can be formulated as a reinforcement learning (RL), problem where the reward depends on the agent's uncertainty. For example, the reward can be the negative entropy of the agent's belief over an unknown (or hidden) variable. Typically, the rewards of an RL agent are defined as a function of the state-action pairs and not as a function of the belief of the agent; this hinders the direct application of deep RL methods for such tasks. This paper tackles the challenge of using belief-based rewards for a deep RL agent, by offering a simple insight that maximizing any convex function of the belief of the agent can be approximated by instead maximizing a prediction reward: a reward based on prediction accuracy. In particular, we derive the exact error between negative entropy and the expected prediction reward. This insight provides theoretical motivation for several fields using prediction rewards---namely visual attention, question answering systems, and intrinsic motivation---and highlights their connection to the usually distinct fields of active perception, active sensing, and sensor placement. Based on this insight we present deep anticipatory networks (DANs), which enables an agent to take actions to reduce its uncertainty without performing explicit belief inference. We present two applications of DANs: building a sensor selection system for tracking people in a shopping mall and learning discrete models of attention on fashion MNIST and MNIST digit classification.
DO REGIONAL ASYMMETRIES MATTER FOR THE TRADE- MIGRATION LINK?

Empirical evidence has shown that the arrival of foreign workers tend to enhance the bilateral trade between the source and the receiving country. However, the fact that immigrants are not uniformly distributed across regions in the host country has not been taken into account until very recently. Therefore, this increase in bilateral trade should be asymmetrical at the regional level. Under this assumption, we analyse the trade of the Spanish regions with the main source countries of immigration to Spain. In our study, we consider immigrant characteristics (such as the educational level and the type of jobs occupied), together with variables regarding country (and region) characteristics.