Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of a climate-niche model to evaluate spatiotemporal trends in Placopecten magellanicus distribution in the Gulf of Maine, USA

We developed a climate-niche species distribution model to evaluate spatiotemporal trends in Atlantic sea scallop (Placopecten magellanicus) along the coastal waters of the Gulf of Maine. We used a Tweedie-generalized additive model (GAM) to quantify the relationships between scallop abundance and key environmental variables. A boosted regression tree was used to identify significant interactions among environmental variables to integrate within the Tweedie GAM and a regional circulation model was incorporated with the Tweedie GAM to hindcast projections of scallop distribution and assess the impacts of environmental change on this species. Additionally, we evaluate two common model fitting and variable selection methods for GAMs to ensure high model performance. A classic backward variable selection procedure was compared to penalized thin plate regression splines. Projections from the climate-niche species distribution model show higher scallop density along inshore areas relative to those farther offshore. An increasing temporal trend in scallop density was observed along inshore areas and a decreasing temporal trend was observed in areas farther offshore. Additionally, we found that the GAM incorporating thin plate regression splines outperformed the widely used backwards stepwise procedure. This modeling framework will help to inform adaptive management strategies for the scallop fishery within the context of a changing Gulf of Maine ecosystem.
Qualitative and quantitative phytochemical analysis and in-vitro biological activity of Rheum ribes L. different parts

DOI : 10.26650/IstanbulJPharm.2019. 18012 The methanol extracts from different parts of Rheum ribes were subjected to qualitative and quantitative phytochemical and in vitro biological activity (antioxidant, anti-urease, anticholinesterase). Qualitative phytochemical tests were performed using standard analysis methods and these studies revealed the presence of phenolics and tannins. Following this, a quantitative determination of total phenolics and tannins contents was carried out. The antioxidant activity of the extracts were assayed using DPPH, FRAP, TEAC/ABTS and CUPRAC techniques. In addition, the anti-urease and anticholinesterase activity of the extracts were examined using indophenol and Ellman methods, respectively. In this study, it was determined that the macerated flowers extract contained higher total phenolic and tannins contents than the other extracts. According to the results obtained from the antioxidant experiment, the macerated extract of flowers showed the strongest ABTS. + scavenging and ferric reducing antioxidant power activity. The macerated leaves and Soxhlet radix extracts exhibited the strongest DPPH. scavenging and cupric reducing antioxidant activity, respectively. The young shoots extracts obtained using the Soxhlet methods showed the highest anticholinesterase activity. All extracts obtained from different parts of the plant were found to have very low anti-urease activity when compared to the anti-urease activity of standard compound. Therefore, methanol extracts from plant’s flowers, leaves and young shoots can be used as a natural antioxidant and anticholinesterase agent respectively, for the pharmaceutical and food industry in the future. Cite this article as : Taskin T, Bulut G (2019). Qualitative and quantitative phytochemical analysis and in-vitro biological activity of Rheum ribes L. different parts. Istanbul J Pharm 49 (1): 7-13.
The Consequences of Contention: Understanding the Aftereffects of Political Conflict and Violence

What are the political and economic consequences of contention (i.e., genocide, civil war, state repression/human rights violation, terrorism, and protest)? Despite a significant amount of interest as well as quantitative research, the literature on this subject remains underdeveloped and imbalanced across topic areas. To date, investigations have been focused on particular forms of contention and specific consequences. While this research has led to some important insights, substantial limitations—as well as opportunities for future development—remain. In particular, there is a need for simultaneously investigating a wider range of consequences (beyond democracy and economic development), a wider range of contentious activity (beyond civil war, protest, and terrorism), a wider range of units of analysis (beyond the nation year), and a wider range of empirical approaches in order to handle particular difficulties confronting this type of inquiry (beyond ordinary least-squares regression). Only then will we have a better and more comprehensive understanding of what contention does and does not do politically and economically. This review takes stock of existing research and lays out an approach for looking at the problem using a more comprehensive perspective.
Evaluation of total and inhalable samplers for the collection of carbon nanotube and carbon nanofiber aerosols

Abstract A growing number of carbon nanotubes and nanofibers (CNT/F) exposure and epidemiologic studies have utilized 25- and 37-mm open-faced cassettes (OFCs) to assess the inhalable aerosol fraction. It has been previously established that the 37-mm OFC undersamples particles >20 µm in diameter, but the size-selective characteristics of the 25-mm OFC have not yet been fully evaluated. This article describes an experimental study conducted to determine if the 25- and 37-mm OFCs performed with relative equivalence to a reference inhalable aerosol sampler when challenged with CNT/F particles. Side-by-side paired samples were collected within a small Venturi chamber using a 25-mm styrene OFC, 37-mm styrene OFC, 25-mm aluminum OFC, and button inhalable aerosol sampler. Three types of CNT/F materials and an Arizona road dust were used as challenge aerosols for the various sampler configurations. Repeated experiments were conducted for each sampler configuration and material. The OFC samplers operated at flow rates of 2 and 5 L/min. Results showed that the 25-mm OFC performed comparably to the button sampler when challenged with CNT/F aerosols, which was demonstrated in five of the six experimental scenarios with an average error of 21%. Overall, the results of this study indicate that the sampling efficiency of the 25- and 37-mm OFCs adequately followed the ISO/ACGIH/CEN inhalable sampling convention when challenged with CNT/F aerosols. Past exposure and epidemiologic studies that used these OFC samplers can directly compare their results to studies that have used other validated inhalable aerosol samplers.
Melodies as Maximally Disordered Systems under Macroscopic Constraints with Musical Meaning

One of the most relevant features of musical pieces is the selection and utilization of musical elements by composers. For connecting the musical properties of a melodic line as a whole with those of its constituent elements, we propose a representation for musical intervals based on physical quantities and a statistical model based on the minimization of relative entropy. The representation contains information about the size, location in the register, and level of tonal consonance of musical intervals. The statistical model involves expected values of relevant physical quantities that can be adopted as macroscopic constraints with musical meaning. We studied the occurrences of musical intervals in 20 melodic lines from seven masterpieces of Western tonal music. We found that all melodic lines are strictly ordered in terms of the physical quantities of the representation and that the formalism is suitable for approximately reproducing the final selection of musical intervals made by the composers, as well as for describing musical features as the asymmetry in the use of ascending and descending intervals, transposition processes, and the mean dissonance of a melodic line.
Assessment of Selected Nutrients and Toxic Chemicals in Ethiopian Khat

Heavy metal pollution is among the leading health concerns all over the world because of their long-term cumulative effects. khat (Catha edulisforsk), a plant used as a stimulant is grown in certain areas of East Africa and the Arab Peninsula this day it is a known cash crop in Ethiopia. Due to increased demand and value, many farmers have not only begun growing it but have also adopted modern farming methods which include application of fertilizers, pesticides, compost manure, and irrigation. Yet some of these agricultural practices such as application of fertilizers and pesticides are known to increase the concentration of heavy metals such as Cd, Pb, Zn and Cu in the soil. Some of these heavy metals such as Pband Cd are toxic even at low concentrations while Zn, Cu, Fe and Cr though essential in the body, are toxic at high levels This call for monitoring to make sure that the levels of heavy metals in khat do not exceed the threshold limits recommended by WHO due to their adverse health effects to man. This study therefore assesses selected chemical nutrients and toxic metal in khat that is available in Ethiopia. khat samples were collected from16 sits of the three main khat growing regions namely Oromiya, South Nation and Nationality and Amhara regional state Known weights of oven dried khat samples were digested using nitric andPerchloric acids. The digests were analyzed for selected heavy metals using flame atomic absorption spectrophotometer. The following concentration ranges in dry weight (μg/g) were obtained in khat: Zn (25.15-73.95), Cu (0.10-41.80), Cr (ND-39.50), Cd(ND-0.90) and Pb (0.50-13.00). Cd was only detected in khat samples from Oromiyaare more susceptible to adverse effects of Pb than adults. The results suggested that there was significant different (p 0.05) in the levels of heavy metals between khat from various regions. Levels of studied heavy metals in khat were below the maximum limits recommended by WHO except for Pb and Cr Therefore children should be discouraged from chewing khat since they are more susceptible to adverse effects of Pb than adults.
Musical Social Entrainment

Over the last decade, the concept of entrainment—emerging from the fields of physics and biology—has grown as a tool for investigating rhythmic adjustments among musicians, and between different groups of musicians. When combined with methods of audio data analysis, this approach has benefits for the assessment of musical behavior, previously limited to largely descriptive ethnomusicological research based on ethnographic data collected through field study. However, musical behavior is not only biophysically determined, but also a highly social activity. Therefore, this article focuses on “social entrainment”—a concept coined by the social scientists Joseph E. McGrath and Janice R. Kelly in 1986 which recently has been taken up in music research. Relating this concept to certain approaches in relevant current empirical studies on interpersonal coordination, the authors develop their own categories of social behavior, which are broader than those of social entrainment but can accordingly be applied to the social entrainment that may occur in musical practices. These categories range from basic behaviors that do not involve social cognition but are meaningful to interacting individuals and groups, to high-order social behaviors that require collective intentionality and can lead to sophisticated interaction involving music-specific phenomena such as a “groove. ” Consequently, a concept of entrainment which goes beyond both an adaptation of the established concept of physical and biological entrainment and McGrath and Kelly’s original concept of social entrainment is proposed: “musical social entrainment. ” The authors use this term to refer to intra-individual, inter-individual, intra-group, and inter-group entrainment to exogenous musical rhythms—including the rhythms of other musically acting individuals and groups—embedded in a social context and contributing to sociality. Finally, reviewing selected studies relevant to musical social entrainment, the authors discuss problems and open questions concerning music-related entrainment research, and potential contributions in the future of entrainment studies in general.
A Lagrangian relaxation approach for stochastic distribution network design

This paper addresses the design of a distribution network in which a single supplier ships products to a set of retailers facing random demands via a set of distribution centers. Distribution centers are not known a priori and are to be located at a set of retailer locations. Decisions include: retailer locations to be selected as distribution centers, assignment of retailers to the distribution centers, and inventory to keep at each distribution center. The goal is to minimize the total location, shipment, and inventory costs, while ensuring a given retailer service level. A Lagrangian relaxation heuristic is proposed. Computation results show the effectiveness of the proposed heuristic and the duality gap is less than 1.5% in all tested problem instances.
Stomatal conductance, leaf chlorophyll content, growth, and yield of sweet pepper in response to plant growth regulators

ABSTRACT The demand for sweet pepper (Capsicum annuum L.) is increasing because of nutrition and quality factors. Research to improve pepper yield using plant growth regulators (PGRs) has occurred, but results are not consistent. This study evaluated the effects of the PGRs naphthalene acetic acid (NAA), gibberellic acid (GA3), 4-chlorophenoxyacetic acid, Kelpak® (seaweed extract), and their combinations, on stomatal conductance, leaf chlorophyll content, and growth and yield of hydroponically grown sweet pepper. Seedling root plugs were soaked in Kelpak® at 10 mL L−1, 3 h before transplanting. Thereafter, solutions were applied to foliage with NAA at 20 mg L−1, GA3 at 15 mL L−1, and Kelpak® at 5 mL L−1 and their combinations at 15, 30, and 45 days after transplanting. PGR treatments benefitted stomatal conductance. Leaf chlorophyll content of untreated plants decreased with time compared to treated plants. Foliar application of GA3, alone, and in combination with Kelpak®, increased plant height, fresh and dry biomass, and yield compared to other treatments. Further investigation with application rates, and time of foliar application, on sweet pepper will provide a better understanding of how plants respond to PGRs.
A parallel patient treatment algorithm and it’s application in hospital queuing recommendation

A patient queue management system to minimize patient wait time, delays and patient overcrowding is one of the major challenges faced by hospitals. Redundant and bothersome waits for long periods result in substantial human resource and time wastage and increase the frustration endured by patients. Therefore, we recommend a Patient Treatment Time Prediction (PTTP) algorithm to predict the waiting time for each treatment task for a patient. Based on the predicted waiting time, a Hospital Queuing-Recommendation (HQR) system is developed. HQR calculates and predicts an efficient and suitable treatment plan recommended for the patient.
SENTATION USING ROBOTIC PRIORS

Our understanding of the world depends highly on how we represent it. Using background knowledge about its complex underlying physical rules, our brain can produce intuitive and simplified representations which it can easily use to solve problems. The approach of this paper aims to reproduce this simplification process using a neural network to produce a simple low dimensional state representation of the world from images acquired by a robot. As proposed in (Jonschkowski & Brock, 2015), we train the neural network in an unsupervised way, using the a priori knowledge we have about the world as loss functions called ”robotic priors” that we implemented through a siamese network. This approach has been used to learn a one dimension representation of a Baxter head position from raw images. The experiment resulted in a 97,7% correlation between the learned representation and the ground truth, and show that relevant visual features form the environment are learned.
Coverage Analysis for 2D/3D Millimeter Wave Peer-to-Peer Networks

This paper presents a theoretical analysis for estimating the coverage probability in two-dimensional (2D) and three-dimensional (3D) peer-to-peer (P2P) millimeter-wave (mmWave) wireless networks. The analysis is carried out by adopting suitable link state models and realistic propagation conditions, involving path-loss attenuation, angular dispersion, mid- and small-scale fading, which comply with recent channel measurements. The presented framework accounts in detail for the actual shape of the transmitting/receiving antenna patterns and for the spatial statistic that describes the node location, by considering the widely adopted Poisson point process, the uniform distribution, and the random waypoint mobility model. Analytical expressions for the statistic of the received power and simple integral formulas for the coverage probability in the presence of interference and noise are derived. The accuracy of the obtained estimations and of the introduced approximations is checked by independent Monte Carlo validations. As possible applications in the 3D mmWave context, the conceived mathematical theory is used to discuss the impact of the interference model on the reliability of the noise-limited approximation, and to estimate the average link capacity of an interfered P2P communication.
PHYTOCHEMICAL SCREENING OF POLYHERBAL COMPOSITION BASED ON Portulaca oleracea AND IT’S EFFECT ON MACROPHAGE OXIDATIVE METABOLISM

63 Use of complementary and alternative medicine, particularly herbal remedies is known as a beneficial approach for curing the different ailments. The growing number of studies report the anti-inflammatory, antioxidant, anticancer, antidiabetic, immunomodulatory and other effects of medicinal plants, which make them as a natural, innocuous and reliable remedy for treatment of wide spectrum of human diseases, as well as attractive objects for the biotechnology [1–3]. Portulaca oleracea is a medicinal plant with a broad range of therapeutic activities, and one of the most commonly used medicinal plants according to the World Health Organization [4]. The most common biologic effect of P. oleracea and its isolated constituents is the prevention and resolution of inflammation [5, 6]. In addition, P. oleracea extracts have an ability to restore suppressed immune reactivity in animal models [7]. Traditional anti-inflammatory effects of this plant can be implemented through the immunosuppressive or immune-stimulant effects and there are lack of obvious and clear characteristics of its impact on different effector cells of immune system, including phagocytes which are key players of majority immune responses [8, 9]. In most cases, P. oleracea based phytopreparations are used in the form of herbal remedies which are prepared from only this plant. Meanwhile, herbal mixtures containing a combination of different plant species have been reported to have better biological activities than monocomponent formulations because of synergistic effects of phytochemicals from UDC 571.27: 581.6 https://doi.org/10.15407/biotech12.02. 063
Tecnolengua Lingmotif at EmoInt-2017: A lexicon-based approach

In this paper we describe Tecnolengua Group’s participation in the shared task on emotion intensity at WASSA 2017. We used the Lingmotif tool and a new, complementary tool, Lingmotif Learn, which we developed for this occasion. We based our intensity predictions for the four test datasets entirely on Lingmotif’s TSS (text sentiment score) feature. We also developed mechanisms for dealing with the idiosyncrasies of Twitter text. Results were comparatively poor, but the experience meant a good opportunity for us to identify issues in our score calculation for short texts, a genre for which the Lingmotif tool was not originally designed.
A COMPREHENSIVE STUDY ON THE ROLE OF GHRELIN IN OBESITY AMONG LOCAL POPULATION OF PAKISTAN

Introduction: Obesity is a major public health problem as more than 10% of the global population is obese. The number of patients affected by this modern epidemic and the associated co-morbidities, such as diabetes mellitus, cardiovascular diseases and cancer, are constantly rising, along with the associated health costs, making the management of obesity one of paramount importance. Objectives of the study: The main objective of the study is to analyze the role of Ghrelin in obesity among local population of Pakistan. Methodology of the study: This cross sectional study was conducted in Health department of Punjab during April 2018 to October 2018. The data was collected from 100 patients. The age range for this study was 10 to 25 years. Subjects with known history of Diabetes mellitus, malignancy and major abdominal surgery and on any major Drug e.g metocloperamide will be excluded from participating in the study. A fasting venous blood sample with a total volume of 4 ml will be collected from each study participant. One ml of this will be used in for routine testing FBS and 1 ml for fasting lipid profile. Results: The data was collected from 100 patients of both genders. Mean age of hypertensive obese was 43.42 ± 10.466 years and mean age of normotensive was 35.28 ± 7.876 years. Mean ghrelin levels in hypertensive obese was 0.572±0.514 and mean ghrelin levels in normotensive obese was 0.387 ± 0.202. Statistically significant difference of mean fasting ghrelin levels between hypertensive obese and normotensive obese was noted with p value 0.013. Conclusion: It is concluded that Ghrelin was positively associated in obese patients and this association was inversely influenced by the increase of BMI.
A Data-Driven Semi-Supervised Soft-Sensor Method: Application on an Industrial Cracking Furnace

The cracking furnace is the key equipment of the ethylene unit. Coking in furnace tubes results from the generation of coke during cracking, which will compromise the heat transfer efficiency and lead to shape change of tubes. In order to keep the cracking furnace operating economically and safely, the engineers need to decoke according to the surface temperature of the furnace tube. However, the surface temperature of the furnace tube is difficult to obtain in practice. Due to redundant instrumentation and the high level of process control in cracking furnaces, a large number of operation data have been collected, which makes it possible to predict the surface temperature of furnace tubes based on autocorrelation and cross correlation within and among variables. Traditional prediction methods rely on labeled data samples for training, ignoring the process information contained in a vast amount of unlabeled data. In this work, a data-driven semi-supervised soft-sensor method is proposed. Considering the nonlinear and dynamic relationship among variables, long short-term memory network (LSTM) autoencoder (AE), a deep neural network suitable for the feature extraction of long-term nonlinear series, is used for pre-training to extract process data features from unlabeled and labeled data. Then, principal component analysis (PCA) and mutual information (MI) are applied to remove feature correlation and select features related to target variables, respectively. Finally, the selected data features are utilized to establish a soft-sensor model based on artificial neural network (ANN). Data from an industrial cracking furnace of an ethylene unit is considered to validate the performance of the proposed method. The results show that the prediction error of furnace tube surface temperature is about 1% and successfully aid engineers in determining the optimal time for decoking.