Miracle-dz/UniFAR-FTUs huggingface dataset:
Screening the estrogenic potency of nonylphenol in rats: in vivo and in silico approaches

The aim of the present study is evaluation of the effect of intraperitoneal administration of nonylphenol (N P) on sex hormones in male rats and i silico analysis for interaction between rat estrogen receptor and nonylphenol. Healthy adult male albino rats were divided into 4 groups with 8 animals each. Animals in f i r s t group served as control, second, third and fourth groups were administered with NP at doses of 1, 10 and 100 μg/kg bw every alternative day for 55 days. After the treatment, animals were sacrificed an collected blood and separated the serum. The circulatory levels of testosterone, FSH and LH were estimated in serum. Testosterone was significantly (p < 0.05) decreased in a dose dependent manner w hereas the levels of FSH and LH were significantly (p < 0. 05) increased in dose dependent manner when compared with controls. In in silico analysis, estradiol showed the strongest binding affinity with 9.62 kcal.mol −1 energy with estrogen receptor. NP fit within the binding d omain of estrogen receptor, thereby showed the moderate binding capacity w i t h −6.18 kcal mol−1 affinity, and hence it can be regarded as estrogenic effectors. H ence the present study revealed that intraperitoneal administration of NP alters the concentrations of testosterone, FSH and LH; docking studies revealed that NP binds to estrogen receptor. Citation: Ganga U.K., Munikumar M. , Sainath S.B. , Umamaheswar i A. , Kishori B. , Reddy P.S. 2016. Screening the estrogen ic potency of nonylphenol in rats: in vivo and in silico approaches. The Journal for Endocrinology and Metabolism. Photon 10 6, 213221 All Rights Reserved with Photon. Photon Ignitor: ISJN57438481D825615102016
MASARYKOVA UNIVERZITA Přı́rodovědecká fakulta

The thesis analyses the behaviour of the Czech economy during the dramatic economic events which have started in 2008. The analysis is conducted using a dynamic stochastic general equilibrium model (DSGE). The model is identified using historical data. The analysis of the behaviour of the model is done using the methods of recursive estimation, impulse responses and shock decomposition. The model is then used to produce conditional forecasts of a further development of the Czech economy.
G protein β3 subunit gene polymorphism in Turkish hypertensives Hipertansif Türklerde G protein β3 subunit gen polimorfizmi

Objective: G protein is one of the most important regulators of intracellular signaling pathways. C825T polymorphism of G protein β3 subunit is associated with increased intracellular signal transduction. The 825T allele has been found associated with a variety of cardiovascular risk factors, including hypertension. The aim of the present study was to investigate the association between the C825T polymorphism of the G protein β3 subunit and essential hypertension in Turkish population. Methods: This cross-sectional, case-controlled study included 209 patients with essential hypertension (Patient group) and 82 subjects with normal blood pressure (Control group). The G protein β3 subunit C825T gene polymorphism was determined by polymerase chain reaction. Hypertension was defined according to JNC VII criteria. Statistical analysis was performed using Chi square and unpaired t tests. Logistic regression analysis was used to study association between hypertension and genotypes. Results: We found that the frequencies of the G protein β3 subunit C825T polymorphism in hypertensive and control groups were 17.7%, 59.3%, 23.0% and 32.9%, 48.8%, 18.3%, (CC, CT, TT) respectively (χ2=7.963, p=0.019). In the multivariate logistic regression analysis CT genotype had 2.2 (OR=2.262, 95% CI 1.228-4.167, p=0.009), and TT genotype had 2.3 times (OR=2.335, 95% CI 1.089-5.008, p=0.029) greater risk of hypertension compared to CC genotype. Conclusion: It seems that the G protein β3 subunit C825T gene polymorphism is associated with systolic and diastolic blood pressure. Furthermore, the study indicates that the G protein β3 subunit may be a susceptible gene to essential hypertension. (Anadolu Kardiyol Derg 2008; 8: 331-5)
NATIONAL BIOSAFETY AUTHORITY APPLICATION SUMMARY AS PROVIDED BY THE APPLICANT TITLE: THE APPLICATION FOR ENVIRONMENTAL RELEASE AND PLACING ON THE MARKET OF MON 15985 AND ALL COTTON DERIVED FROM THIS EVENT FOR OPEN FIELD CULTIVATION AND FOOD/FEED USES IN KENYA

This document is protected under national and international copyright law and treaties. This document and any accompanying material are for use only by the regulatory authority to which it has been submitted by Monsanto Company and only in support of actions requested by Monsanto Company. Any other use, copying, or transmission of this document and the materials described in or accompanying this document, without prior consent of Monsanto, is strictly prohibited; except that Monsanto hereby grants such consent to the regulatory authority where required under applicable law or regulation. The intellectual property, information and materials described in or accompanying this document are owned by Monsanto Company, which has filed for or been granted patents on those materials. By submitting this document and any accompanying materials, Monsanto does not grant any party or entity any right or license to the information, material or intellectual property described or contained in this submission. NATIONAL BIOSAFETY AUTHORITY
AUTHENTICATION METHOD IN SOFTWARE-DEFINED NETWORK BASED ON CIPHERTEXT-POLICY ATTRIBUTES ENCRYPTION

The controller of Software-Defined Networks (SDN) is lacking well-established authentication controls for accessing terminals to protected networks. This gap may lead to several network attacks gaining full access to the network or revealing sensitive traffic details. In order to resolve this problem, a secure authentication method in SDN is designed and implemented. The design of the authentication method utilizes the concept of Ciphertext-Policy Attributes Based Encryption (CP-ABE). We aim to satisfy the credibility theory by allowing authenticated users with authenticated platforms to fully gain their privileged access. On the other hand, our method allows limited access for authenticated users of unauthenticated platforms. Experimental results show that our authentication method is secure with an acceptable range of access delay and CPU utilization.
Tempered Fractional Equations for Quantum Transport in Mesoscopic One-Dimensional Systems with Fractal Disorder

New aspects of electron transport in quantum wires with Lévy-type disorder are described. We study the weak scattering and the incoherent sequential tunneling in one-dimensional quantum systems characterized by a tempered Lévy stable distribution of spacing between scatterers or tunneling barriers. The generalized Dorokhov–Mello–Pereyra–Kumar equation contains the tempered fractional derivative on wire length. The solution describes the evolution from the anomalous conductance distribution to the Dorokhov function for a long wire. For sequential tunneling, average values and relative fluctuations of conductance and resistance are calculated for different parameters of spatial distributions. A tempered Lévy stable distribution of spacing between barriers leads to a transition in conductance scaling.
Influence of Irrigation Frequency on Radicchio (Cichorium Intybus L.) Yield

Red chicory (radicchio) plants produce leafy heads that are of great commercial interest and they require a proper irrigation technique to achieve satisfactory productivity. The use of mini-sprinklers with high-frequency irrigation schedules may increase radicchio productivity, provide better growing conditions due to timely intervention, and save water, but so far little research has been carried out on this topic. This experiment aims at evaluating the effect of two mini-sprinkler irrigation schedules (high- and low-frequency) on radicchio yield and growing conditions over a 5-year cultivation period. Marketable radicchio head production was on average 12% greater with the high-frequency schedule (26.5 t ha−1) than with the low-frequency schedule (23.6 t ha−1), mainly due to greater head weight. The number of underweight, pre-flowering, rotten, and missing plants was significantly different between the two schedules when these variables were considered separately, but the overall number of marketable plants was greater in the high-frequency schedule during certain years. In general, the high-frequency schedule permitted to increase both radicchio yield and to reduce irrigation water use on average by 14% (−24 mm in volume), improving the irrigation water productivity by 19% (from 0.18 t mm−1 of the low-frequency schedule to 0.22 t mm−1 of the high-frequency schedule). Reducing the irrigation interval permits a timely adaptation to the weather course and improves radicchio growing conditions, presenting itself as a valid strategy that could be adopted by the farmers, upon appropriate consideration of energy and management costs.
Determination of Heavy Metals in 16 Bleaching Creams and 3 Mixtures of Bleaching Creams from Local Market of Jeddah

EAVY metals on bleaching cream products easy cased many . types of skin problems and deleterious effects to the human health. Many consumers are using mixture of bleaching creams simultaneously to get a double activity (shiny and faster) on their skins. They are at risk of toxicity and adverse interactions due to their multiplicative contamination with heavy metals and uncertain mixing of different components. 16 bleaching creams and 3 mixtures of bleaching creams were digested with high pressure microwave technique followed by injection on Inductive Coupled Plasma Optical Emission Spectrometer (ICP-OES) for determining (Hg, Cd, Ti, Bi, Pd, As and Tl) elements. The obtained results showed that, the highest concentration for (Hg, Bi, Ti and Pb) on samples were 5739.16, 7013.53, 21407.73, 456.70 ppm, respectively, other metals less than 28.99 ppm. One of the mixtures sample has high concentrations of Hg and Bi were 13338.50, 619.23 ppm, respectively, so creams and its mixtures which contain heavy metals above the permissible limit must be blind. Detection limits are achieved at the level of 2.5-50 μg/g, RSD were less than 14.72%, the recoveries for cosmetics were in the range of 88.52% to 99.62%. Good results show that the method is quick, accurate and convenient.
AUDITORY FACTORS IN THE EMERGENCE OF PREPALATAL AFFRICATES IN POLISH∗

The idea that auditory factors play a role in phonology besides articulation has gained more and more attention in recent years (cf. Steriade, e.g. 1997, 2001, Flemming, 1995/2002, Boersma 1998, Padgett 2001a, 2001b, Hume and Johnson 2001, and references therein; NiChiosain and Padgett 2001, Ćavar 2003, and many others). The standard assumption for Polish so far has been that the emergence of prepalatal affricates is of articulatory nature and accounts have been offered in terms of articulatory features (e.g. Rubach 1984, Szpyra 1995,Ćavar 1997). I will argue that, though articulatory factors may play here some role, the driving force is of auditory background. Two parameters will be investigated separately, namely, place of articulation, and stridency. Arguments from the typology of consonantal inventories, and from the phonology of standard Polish and Polish dialects will be presented to support this view.
Image Quantification Learning Technique through Content based Image Retrieval

This paper proposes a Radial basis functionality incorporation in learning the quantification of images using Content based Image Retrieval (CBIR). The approach is trying to find out the effectiveness of Multi-Layer Perceptron (MLP) namely Radial Basis Function (RBF) through Content Based Image Retrieval. Extract the features of an image, the numeric values of each pixel is framed in to a definite input data set of image to that the neural networks MLP gives the accuracy of the prediction of that particular Image data set. This paper put forward us with new idea of neural networks structure efficiency in the accuracy of output data set which got increased by the adjustment of the weighted neurons through a Perceptron called Radial Basis Function promoting by applying k means clustering to form clusters which are parameterized with Gaussian function application. Finally compare the actual output with observed output promoting the weighted neurons adjustment for getting the actual accurate output. A new dimension, in work enhancement of neural networks technology with that of image processing.
Urban infiltration in cold climate Infiltration urbaine en climat froid

The implementation of Sustainable Urban Drainage Systems (SUDS) in the northern hemisphere is confronted with the problem of decreased infiltration during winter because of frozen soils. The goal of this research was to assess the winter infiltration capacity of a grass swale and natural vegetation cover during frequent freeze-thaw cycles. Infiltration was measured with eight single-ring infiltrometers, and by analysing continuous water content measurements in the soil at different depths in the steep (1316%), BREEAM certified neighbourhood Urriðaholt. Results suggest that frost formation and infiltration capacity were influenced by vegetation cover: dense grass cover performed equally on a seasonal basis, while infiltration through less dense vegetation covers decreased by 11-54% during winter as compared to summer. Frost was measured for a few days at 5 cm depth in the soil, and concrete frost completely inhibiting infiltration did not form. The results presented are part of an ongoing research.
ICLR 2020 Convolutional   Features Convolutional   Backbone Primary   Capsules Convolution   + LayerNorm Routing Routing Convolutional   Capsules Fully-Connected   Capsules Class   Capsules Classifier

We introduce a new routing algorithm for capsule networks, in which a child capsule is routed to a parent based only on agreement between the parent’s state and the child’s vote. The new mechanism 1) designs routing via inverted dot-product attention; 2) imposes Layer Normalization as normalization; and 3) replaces sequential iterative routing with concurrent iterative routing. When compared to previously proposed routing algorithms, our method improves performance on benchmark datasets such as CIFAR-10 and CIFAR-100, and it performs at-par with a powerful CNN (ResNet-18) with 4× fewer parameters. On a different task of recognizing digits from overlayed digit images, the proposed capsule model performs favorably against CNNs given the same number of layers and neurons per layer. We believe that our work raises the possibility of applying capsule networks to complex real-world tasks.
Graph-based Recurrent Retriever Machine reading Reasoning Path reranking Hidden states of recurrent neural network Reasoning Path Retrieval

Answering questions that require multi-hop reasoning at Web-scale requires retrieving multiple evidence documents, one of which often has little lexical or semantic relationship to the question. This paper introduces a new graphbased recurrent retrieval approach that learns to retrieve reasoning paths over the Wikipedia graph to answer multi-hop open-domain questions. Our retriever trains a recurrent neural network that learns to sequentially retrieve evidence documents in the reasoning path by conditioning on the previously retrieved documents. Our reader ranks the reasoning paths and extracts the answer span included in the best reasoning path. Experimental results show state-of-the-art results in three opendomain QA datasets, showcasing the effectiveness and robustness of our method. Notably, our method achieves significant improvement in HotpotQA, outperforming the previous best model by more than 14 points.1
Towards an Approximated Accurate Measure of Links on the Data Web and a Scalable Generation Method for Dynamic LOD Cloud Diagrams

The Web of Linked Data is growing and it becomes increasingly necessary to discover the relationship between different datasets. This paper proposes an approach for accurate link counting which uses Bloom filters (BF) to compare and approximately count links between datasets, solving the problem of lack of up-to-date meta-data about linksets. We compare the performance to classical approaches such as binary search tree (BST) and hash tables (HT). The results show that Bloom filter is 12x more efficient regarding of memory usage with adequate query speed performance. BF maintains a low level of false positives and a precision level quite close to 100%. In addition, we created a small cloud comparing all English DBpedia datasets and vocabularies available in Linked Open Vocabularies (LOV). The whole process took only 1h45min. Moreover, we developed a GUI that uses the generated meta-data and creates a visualization of datasets and distributions, making it possible to apply real time filters. DataID files can also be enriched with VoID linksets based on statistical data generated by our approach.
Discourse of Nrima Ing Pandum in Novel Langit Mendhung Sajroning Pangangen by Tulus Setiyadi

The Langit Mendhung Sajroning Pangangen (LMSP) novel one of the contains moral values about the acceptance of whatever God gives that are conceptually the inheritance of Javanese ancestors. In the Javanese culture, that attitude is known as nrima ing pandum which is almost the same as the sepi ing pamrih attitude 'unconditional' for the purpose of living of memayu hayuning bawana 'beautify the life of the universe'. Therefore, the nrima ing pandum attitudes is very important to be studied, since such attitudes have relevance in the present. This article aims to uncover the discourse of nrima ing pandum in the LMSP novel with uses the anthropological and Javanese religious perspective for the read of text in the Javanese anthroporeligio context. The result is reveals that the discourse of nrima ing pandum contained in the LMSP novel is described based on the three attitudes that make a person nrima ing pandum, namely rila, nrima, and patient as inseparable attitudes. The conclusion is proves that the value of Javanese culture, especially value of nrima ing pandum, still maintained by the supporting community and still very relevant to be used in everyday life and can be realized in the life of today's society.
ICLR 2020 Concatenated Nodes Features GraphSAGE Sparse Representation Adjacency Matrix Node Feature : Ops Type Output Shape Input Ops Aggregator 1 Aggregator 2 Segment 1 Segment 2 Transformer

Runtime and scalability of large neural networks can be significantly affected by the placement of operations in their dataflow graphs on suitable devices. With increasingly complex neural network architectures and heterogeneous device characteristics, finding a reasonable placement is extremely challenging even for domain experts. Most existing automated device placement approaches are impractical due to the significant amount of compute required and their inability to generalize to new, previously held-out graphs. To address both limitations, we propose an efficient end-to-end method based on a scalable sequential attention mechanism over a graph neural network that is transferable to new graphs. On a diverse set of representative deep learning models, including Inception-v3, AmoebaNet, Transformer-XL, and WaveNet, our method on average achieves 16% improvement over human experts and 9.2% improvement over the prior art with 15× faster convergence. To further reduce the computation cost, we pre-train the policy network on a set of dataflow graphs and use a superposition network to fine-tune it on each individual graph, achieving state-of-the-art performance on large hold-out graphs with over 50k nodes, such as an 8-layer GNMT.
New methods in veriﬁcation of multi-agent systems and e-voting protocols

Multi-agent systems describe interactions of multiple entities called agents, often assumed to be intelligent and autonomous. Alternating-time temporal logic ATL∗ and its fragment ATL [1] are logics which allow for reasoning about strategic interactions in such systems, by extending the framework of temporal logic with the game-theoretic notion of strategic ability. Hence, ATL∗ enables to express statements about what agents (or groups of agents) can achieve. Such properties can be useful for specification, verification, and reasoning about interaction in agent systems and security and usability in e-voting protocols. They have become especially relevant due to active development of algorithms and tools for verification where the “correctness” property is given in terms of strategic ability [4]. However, there are several obstacles First, most of the tools and algorithmic solutions focus on agents with perfect information, i.e., agents who at any point of the game know exactly the global state of the game, which is clearly unrealistic in all but the simplest multi-agent scenarios. The imperfect information semantics of ATL does not admit alternation-free fixpoint characterizations [3], which makes incremental synthesis of strategies impossible, or at least difficult to achieve. Secondly, the semantics of strategic logics are almost exclusively based on synchronous concurrent game models. That is, one implicitly assumes the existence of a global clock that triggers subsequent global events in the system. However, many real-life systems are inherently asynchronous, and do not operate on a global clock that perfectly synchronizes the atomic steps of all the components. The aim of the project is to develop a new methodology for verification of agents with imperfect information, using strategy logics interpreted on asynchronous models [2]. As far as the applications are concerned, the main focus will be on voting procedures and protocols, and in particular on their essential features like confidentiality, coercion-resistance, and voter-verifiability. More specifically, the verification methods will include:
Assessment of the Biomass Productivity Decline in the Lower Mekong Basin

This study aimed to delineate the geographic hotspots of negative trends in biomass productivity in the Lower Mekong Basin countries (Vietnam, Cambodia, Laos, and Thailand) and identify correlated regional environmental and anthropogenic factors. A long-term time-series (1982–2015) of Normalized Difference Vegetation Index at a resolution of approximately 9.16 km × 9.16 km was used to specify the areas with significant decline or increase in productivity. The relationships between vegetation changes and land attributes, such as climate, population density, soil/terrain conditions, and land-cover types, were examined. Rainfall time-series maps were used to identify areas that might have been affected by land degradation from those correlated with rainfall. Most of the detected potentially degraded areas were found in Cambodia, the Northwest and the Highland of Vietnam, the Northern Mountains of Thailand and Laos, and the mountainous border between Laos, Vietnam, and Cambodia. About 15% of the total land area of these four countries experienced a reduction in biomass productivity during the 34-year study period. The map of hotspots of changes in productivity can be used to direct further studies, including those at finer spatial resolution that may support policy makers and researchers in targeting the strategies for combating land degradation.