Miracle-dz/UniFAR-FTUs huggingface dataset:
Chemical Characterization of Atlantic Cod (Gadus morhua) Collagen Hydrolyzed Using Enzyme Preparation Derived from Red King Crab (Paralithodes camtschaticus) and Its Potential as a Core Component of Bacterial Culture Medium

The Atlantic cod (Gadus morhua) and red king crab (Paralithodes camtschaticus) processing wastes are massive and unutilized in the Murmansk region of Russia. The samples of skin-containing waste of Atlantic cod fillets production were hydrolyzed using enzyme preparations derived from red king crab hepatopancreases, porcine pancreases, and Bacillus subtilis bacteria. The activity of enzymes from crab hepatopancreases was significantly higher than the activity of enzymes derived from other sources. The optimal conditions of the hydrolysis process have been figured out. The samples of cod processing waste hydrolysate were analyzed for amino acid composition and molecular weight distribution. The samples of hydrolysate were used as core components for bacterial culture medium samples. The efficiency of the medium samples was tested for Escherichia coli growth rate; the most efficient sample had an efficiency of 95.3% of that of a commercially available medium based on fish meal. Substitution of medium components with those derived from industrial by-products is one of the ways to decrease a cost of a culture medium in biopharmaceutical drug production.
Energy Efficient, Protocols for Wireless Sensor Network: A Survey and Review

— Wireless sensor network (WSN) is emerging as most promising technology. WSN has numerous applications such as scientific exploration, disaster prevention and monitoring, healthcare, military surveillance, etc. WSN has limited resources with traditional data collection technique. One of the biggest limitation of Wireless Sensor Network is its nodes have limited energy resources. Maximize the energy efficiency in WSN is the biggest challenge. In this paper, we discuss about different studies in this area. By summarizing we found some pros and cons and trying to eliminate those drawback that belongs regarding our work, we also draw attention to possible research for future work.
Amphibians and reptiles from the Parque Nacional da Tijuca, Brazil, one of the world’s largest urban forests

Abstract: The Parque Nacional da Tijuca in Rio de Janeiro, Brazil, is considered to be one of the world’s largest urban forests, however no systematic inventory of its herpetofauna is available. In the present study, we surveyed the amphibians and reptiles of this park to assess its species composition (including secondary data) and obtain estimates of species richness and abundance. We conducted active searches (460 hours) between January 2013 and December 2015. We identified the taxa endemic to either the Atlantic Forest or Rio de Janeiro state, and verified the conservation status of each species in the international, Brazilian, and state red lists. We also estimated the species richness and sampling sufficiency by rarefaction curves and Bootstrap richness estimator, and analyzed the distribution of the species abundance in Whittaker plots. We recorded 3,288 individuals over 36 months, representing 24 species of amphibians and 25 reptiles. The cumulative species curves, rarefaction, and the richness estimated indicated that sampling effort was adequate. Species abundance adjusted to the log-series model in both amphibians and reptiles. The four most abundant amphibians represented 70% of the individuals recorded in this group, while the two most abundant reptiles represented 60% of the total individuals. The inclusion of the secondary data raised the number of amphibian species to 38, and the number of reptiles to 36. Approximately 80% of the amphibian species and 28% of the reptile species recorded are endemic to the Atlantic Forest, and six of the amphibian species are endemic to Rio de Janeiro state. Six amphibian species and one reptile species are classified under some threat of extinction, and two reptile species were exotic. The considerable diversity of the herpetofauna of the Parque Nacional da Tijuca, which includes endemic and threatened species, reflects the effectiveness of the reforestation of this protected area and emphasizes the importance of its conservation.
The Amounts of Water Adsorbed to the Surface of Clay Minerals at the Plastic Limit

Abstract The paper presents results of a study on the amount of water associated with the solid phase of the clay water system at the plastic limit. Two model monomineral clays, namely kaolinite, and montmorillonite, were used in the study. The latter was obtained by gravitational sedimentation of Na-bentonite (Wyoming). The calculated mean number of water molecule layers on the external surface of montmorillonite was 14.4, and water in interlayer spaces constituted 0.3 of the water mass at the plastic limit. The number of water layers on the external surface of kaolinite particles was 63, which was related to the higher density of the surface electrical charge of kaolinite compared to that of montmorillonite. The calculations were made on the basis of the external surface area of clays and the basal spacing at the plastic limit measured by an X-ray diffraction test. The external surface area of clays was estimated by measuring sorption at a relative humidity p/p0 = 0.5.
Social Networks and Job Referrals in Recruitment

This paper investigates whether using recommendations for recruitment reduce information asymmetries or allow the exchange of favors in the labor market of board directors. I use data on all directors of large listed US companies between 2004 and 2008. These are linked with extensive information on their social networks and detailed information on the referrals underpinning new independent board appointments. Compared to non-connected new directors, connected directors are 14% more likely to be referred by current board members with whom they share employment history. Predictions of a theoretical model allow me to further discriminate between information provision and favoritism in the use of such referrals for recruitment. Results show that referrals help select directors with higher ability, in particular the type of ability that is partially observed at the time of hiring. JEL codes: M51, J44, D82
Mining Relevant Arguments At Web Scale Master's Thesis

With the goal of developing an argument search engine, a novel approach to estimate the relevance of the arguments on the Web is proposed. Argument relevance is a quality criterion which indicates how much an argument contributes to a speci c discussion. We model an argument as a conclusion and a set of premises which support or attack the conclusion, all called argument units. The approach relies on constructing an argument graph which represents the arguments and their relations on the Web. PageRank is then used to score the argument units in the graph according to the attention they get as premises. The relevance of an argument is then estimated using the PageRank scores of their units. We use AIFdb to construct a ground-truth argument graph and apply our approach to rank the arguments in it. Then, we evaluate the rankings of a set of arguments by comparing them to rankings which are generated by experts. The experiment reveals a positive Kendall's correlation of 0.28. Starting from these results, we bring our approach to the Web by developing a cross-domain argument mining approach. A cross-domain argument web corpus is constructed to represent three di erent web domains. A domain is any set of documents on the Web which share the same source or the topic. The corpus is used to develop and evaluate the ability of the cross-domain argument mining approach to carry their knowledge over di erent collections of documents on the Web. To evaluate the ability of the cross-domain approach to generalize over domains, We develop an in-domain approach which is trained and tested on the same corpus. The e ectiveness of both approaches is found to be relatively close with regard to a minority baseline but indicates the need for improvements.
UNIVERSIDADE FEDERAL FLUMINENSE FACULDADE DE VETERINÁRIA HIGIENE VETERINÁRIA E PROCESSAMENTO TECNOLÓGICO DE PRODUTOS DE ORIGEM ANIMAL

The aim of this study was evaluate the behavior of biogenic amines in fermented cow’s and goat’s milks with probiotic bacteria and an overall acceptance test. Initial elevated tyramine levels were observed in both products, which increased throughout the storage period. The highest production of biogenic amines occurred between the first and fifth day of storage, decreasing in the content of such compounds occurred thereafter. A higher overall acceptance of the fermented cow’s milk was observed. The results suggested that the content of biogenic amines may be a criterion for selecting lactic acid bacteria to develop fermented milks.
A Survey on Improved Brain Tumor Segmentation and Detection Using EM and FCM Algorithm

: This paper deals with the implementation of Simple Algorithm for detection of range and shape of tumor in brain MR images and predicts the disease risk details from the given area of tumor. Tumor is an uncontrolled growth of tissues in any part of the body. Tumors are of different types and they have different Characteristics and different treatment. As it is known, brain tumor is inherently serious and life-threatening because of its character in the limited space of the intracranial cavity (space formed inside the skull). Most Research in developed countries show that the number of people who have brain tumors were died due to the fact of inaccurate detection. Generally, CT scan or MRI that is directed into intracranial cavity produces a complete image of brain. After researching a lot statistical analysis which is based on those people whose are affected in brain tumor some general Risk factors and Symptoms have been discovered. The development of technology in science day night tries to develop new methods of treatment. This image is visually examined by the physician for detection & diagnosis of brain tumor. However this method accurate determines the accurate of stage & size of tumor and also predicts the disease details from the area of tumor. This work uses segmentation of brain tumor based on the k-means and fuzzy c-means algorithms. This method allows the segmentation of tumor tissue with accuracy and reproducibility comparable to manual segmentation. In addition, it also reduces the time for analysis and predicts the disease details from the given area of tumor. Finally implement a system using java to predict Brain tumor risk level which is easier, cost reducible and time savable
University of Groningen The effect of product diversification on Corporate Social Performance in the non-renewable energy industry Jongsma, Renske; Pennink, Bartjan

Aim: Building upon stakeholder and institutional theory, this paper investigates the relationship between product diversification and corporate social performance (CSP), thereby attempting to make essential contributions to the current literature. Based on an extensive literature review, it was expected that related, unrelated and total product diversification are positively related to CSP. Moreover, it was hypothesized that the exposure to weak institutional host country environments negatively affects the relationship between diversification and CSP, and that the Sustainable Development Goals (SDGs) have a positive effect on the relationship. Design / Research methods: The sample selected for this research is the non-renewable energy industry, since the industry shows great divergence in terms of corporate social responsibility (CSR) performance. In addition, the industry is highly susceptible to regulatory changes, while the Sustainable Development Goals have an enormous focus on the reliability and sustainability of energy, making it a highly relevant industry to study. This study analyzed 40 a 40 non-renewable energy firms over a time frame of seven years, by using OLS regression. Conclusions / findings: The results reveal that unrelated diversification is positively related to CSP, while the other forms of diversification show insignificant results. Contrary to expectations, the Sustainable Development Goals negatively affect the relationship between product diversification and CSP, while the moderating effect of exposure to weak institutional environments is insignificant. Originality / value of the article: Research on the relationship between product diversification on corporate financial performance is well-established, but the way in which product diversification influences a firm’s behavior towards stakeholder demands and social concerns remains largely unexplored. Accordingly, the results of this study challenge existing theories while adding more context to the existing relationship, and in turn provide promising avenues for future research.
A CHARACTERIZATION OF TRAFFIC VARIABILITY FOR SPC SYSTEMS

Recent data indicate that the traffic offered to a local SPC switching system such as No. 1 ESS may not be adequately· characterized by a station ary Poisson process, even for intervals as short as 15 minutes. The use of a simple measure of traffic variability such as a sample variance to-mean ratio of 10 second counts has the diffi culty of not uniquely characterizing the traffic. Using a simple model of an SPC system, a traffic pattern is determined which upper bounds the real time capacity of such systems. A good approxi mation to this "worst case" pattern is a two level Poisson process. This pattern is similar to that seen in field data and is shown to pro duce a good approximation to system performance.
Integrating scientific knowledge into machine learning using interactive decision trees

Decision Trees (DT) is a machine learning method that has been widely used in the environmental sciences to automatically extract patterns from complex and high dimensional data. However, like any data-based method, is hindered by data limitations and potentially physically unrealistic results. We develop interactive DT (iDT) that put the human in the loop and integrate the power of experts’ scientific knowledge with the power of the algorithms to automatically learn patterns from large data. We created a toolbox that contains methods and visualization techniques that allow users to interact with the DT. Users can create new composite variables, manually change the variable and threshold to split, manually prune and group variables based on physical meaning. We demonstrate with three case studies that iDT help experts incorporate their knowledge in the DT models achieving higher interpretability and realism in a physical sense.
THE IMPACT OF GEOMETRY ON EFFECTIVE MODELS OF NUTRIENT UPTAKE BY ROOT HAIRS

Full-geometry numerical simulations of nutrient uptake by plant roots covered with root hairs can be computationally challenging and time-consuming. Multiscale methods such as homogenisation offer a desirable alternative, allowing for the determination of effective macroscopic equations which capture microscale geometric details but are substantially easier to analyse. Here, we will show how to extend homogenisation of the root hair uptake problem to the limit of very sparse root hairs, and then consider the effects of the root hair length on sink terms representing the nutrient uptake in the effective equation. Finally, we demonstrate the validity of these asymptotic results by comparing them with the corresponding full-geometry numerical simulations.
Staphylococcus aureus (MRSA) and Mycobacterium tuberculosis (Mtb). Moreover, through the misuse, mismanagement and delay in the diagnosis of TB, the disease can potentially progress to multidrug-resistant tuberculosis (MDR-TB) and extensively drug-resistant tuberculosis (XDR

A series of aryl and alkyl pyrimido[1,2-a]benzimidazole derivatives was synthesized according to published procedures. All synthesized compounds were fully characterized by spectral and microanalytical data. The compounds (1a, 1b, 2a, 2b and 2c) were screened for their antimicrobial activity against Gram-positive and Gram-negative bacteria and only compound 2b showed moderate to good activity with respect to minimum inhibitory concentrations and by disc diffusion assays. Apart from Proteus vulgaris, which showed resistance against all the compounds, Enterobacter cloacae, Escherichia coli and Proteus mirabilis were the most susceptible Gram-negative bacteria with MIC of 1 μg/ml, 4 μg/ml and 2 μg/ml respectively. On the other hand, Staphylococcus epidermis, Staphylococcus aureus, Bacillus cereus, Bacillus subtilis, Enterococcus faecalis and Mycobacterium smegmatis all showed susceptibility with MIC’s of 15.62 μg/ml, 31.25 μg/ml, 62.5 μg/ml, 3.9 μg/ml, 62.5 μg/ml and 7.81 μg/ml respectively. Keywords—2-aminobenzimidazole, antibacterial, double Michael addition, pyrimido[1, 2-a] benzimidazole,.
Performance of Prediction-Based Dynamic Bandwidth Provisioning

: Future data networks are required to support different types of traffic with distinct QoS requirements. An attractive approach to meet this requirement is to use virtual networks to provide traffic segregation and resource partitioning in the network. Because of the bursty nature of network traffic, in order to reduce the cost of operating the virtual links of a virtual network, as well as to improve the efficiency of the underlying network, the bandwidth of the virtual links needs to be dynamically adjusted. In this paper, the performance of Autoregressive Moving Average (ARMA) and Fractional Autoregressive Integrated Moving Average (fARIMA) predictors in prediction-based dynamic bandwidth provisioning is studied. The analysis and simulation results show that the performance of prediction-based dynamic bandwidth provisioning depends not only on the accuracy of the predictor, but more importantly on the autocorrelation structure of the prediction error. This dependence has not been noticed in previous research. In addition, our results show that error compensation is a powerful technique to decorrelate the predictor error, and simple predictors, such as ARMA predictor, with error compensation are more suitable in prediction-based dynamic bandwidth provisioning themes than computationally complex fARIMA predictors.
Blockchain based RDF Management Ing .

As Structured open data sees a growth in popularity evidenced by the size of networks such as the Linked Open Data LOD cloud, aspects of its lifecycle management and scalability have yet to be adressed. At the time of writing, implementations of change tracking and provenance do not guarantee integrity and availability, and depend upon individual domain owners to be deployed and maintained. This represents a threat to the stability of a system in which data is composed of cross-domain URI references such as the Semantic Web’s de-facto model: RDF. In this paper we explore the advantages and capabilities a solution based on Blockchain can provide when used as a support for RDF. We provide the design, implementation, testing, and evaluation of a Proof of Concept Distributed Ledger which addresses the use-cases of Create, Read, Update, Delete (CRUD) operations, Linked Data Notifications, and Publish/Subscribe Observer pattern. Our solution provides mutually distrusting parties a support for traceability and provenance of versioned RDF statements, leveraging integrity and availability with decentralization.
QUEEN: Neural Query Rewriting in E-commerce

Query rewriting (QR), which aims to improve the shopping experience by reformulating ambiguous customer input queries into well-formed queries, is a critical component of modern e-commerce search engines. In this work, we present a practical deep learning solution, named as Query Understanding EnhancEd mechaNism (QUEEN), to the large-scale query rewriting problem in e-commerce search engines. QUEEN incorporates query annotations, the by-product of query processing pipelines in most e-commerce search engines, to model ambiguous product search queries. The empirical study is based on 38.5 million anonymous product search queries. Compared to other SOTA baselines, QUEEN improves the sentence-level recall by 6% (relatively).
Glacial Dust Surpasses Both Volcanic Ash and Desert Dust in Its Iron Fertilization Potential

The subarctic Pacific Ocean and Bering Sea comprise the second‐largest high nitrate, low chlorophyll region in the world, where primary production is limited by the availability of iron (Fe). To estimate the potential impact of different terrestrial aerosol Fe sources on marine ecosystems, we performed a suite of laboratory assessments following established protocols, including: (1) leaching with Milli‐Q water, (2) sequential extractions, (3) complete acid digestions, (4) X‐ray diffraction, and (5) grain size analysis. Measurements were performed on 20 fine‐grained (<5 μm) glacier‐derived sediments from Alaska and the Yukon, two fresh, never‐wetted volcanic ashes (Redoubt 2009 and Pavlof 2016), and six weathered ashes (Redoubt and Augustine) which span the past ∼8,700 years. We compared results to published data on Asian desert‐derived sediments, finding that the glacier‐derived sediments have five times higher easily reducible Fe (median 2.3 ± 0.6 wt.%) than desert‐derived samples (0.49 ± 0.1 wt.%) and fourteen times higher easily reducible Fe than fresh ash (0.16 ± 0.1 wt.%). In addition, fractional Fe solubility was higher in glacial sediment (median cumulative 0.31 ± 0.11% FeS) than volcanic ash (0.04 ± 0.02% FeS). Glacial sediments contained higher concentrations of other bioactive metals including Co, Ni, Cu, Zn, Mo, Cd, and Pb. Results suggest that glacier‐derived dust may provide the subarctic Pacific with more bioavailable iron per unit mass than either volcanic ash or Asian desert‐derived dust.
Antihelmintic Effect of Embelia Tsjeriam-Cottam

Manjusha Suresh Nikam, Md. Rageeb Md. Usman, Gautam P. Vadnere Department of Pharmacognosy, Smt. Sharadchandrika Suresh Patil College of Pharmacy, Chopda, Maharashtra, India ABSTRACT The present study was undertaken to investigate the anthelmintic activity of extract of Embeliatsjeriam-cottam using earthworm. Different concentrations of standard drug (Albendazole) and extract of Embeliatsjeriam-cottam fruits were employed and the average time required for paralysis and death was noted. It was found that the Paralysis time & Death time was lowest for 5% concentration of Ethanolic extract and Death time was slightly better than Albendazole Standard solution. Though Ethanolic Extract can be compared to the Standard hence establishing the pharmacological antihelminthic activity of Embelia tsjeriamcottam.