Miracle-dz/UniFAR-FTUs huggingface dataset:
Programmable SoC for an XTEA Encryption Algorithm Using a Co-Design Environment Replication Performance Approach

With the rapid development of wired and wireless networks, the security needs within network systems are becoming increasingly intensive owing to the continuous development of new applications. Existing cryptography algorithms differ from each other in many ways including their security complexity, size of the key and words operated on, and processing time. Nevertheless, the main factors that prioritize an encryption algorithm over others are its ability to secure and protect data against attacks and its speed and efficiency. In this study, a reconfigurable Co-Design multi-purpose security design with very low complexity, weight, and cost, has been developed using Extended Tiny Encryption Algorithm (XTEA) data encryption standards. The paper aims to discuss issues and present solutions associated with this system, as well as compare the Co-Design implementation approach with Full-Hardware and Full-Software solutions. The main contribution that this paper offers is the profiling of XTEA cryptographic algorithm to reach more satisfactory understanding of its computation structure that leads to fully software, fully hardware, beside the co-design implementations all together, of this light weight encryption algorithm.
Classification Model Based on Deep Learning

Text classification is of importance in natural language processing, as the massive text information containing huge amounts of value needs to be classified into different categories for further use. In order to better classify text, our paper tries to build a deep learning model which achieves better classification results in Chinese text than those of other researchers’ models. After comparing different methods, long short-term memory (LSTM) and convolutional neural network (CNN) methods were selected as deep learning methods to classify Chinese text. LSTM is a special kind of recurrent neural network (RNN), which is capable of processing serialized information through its recurrent structure. By contrast, CNN has shown its ability to extract features from visual imagery. Therefore, two layers of LSTM and one layer of CNN were integrated to our new model: the BLSTM-C model (BLSTM stands for bi-directional long short-term memory while C stands for CNN.) LSTM was responsible for obtaining a sequence output based on past and future contexts, which was then input to the convolutional layer for extracting features. In our experiments, the proposed BLSTM-C model was evaluated in several ways. In the results, the model exhibited remarkable performance in text classification, especially in Chinese texts.
OF APPROACHES FOR VARIABLE SPEED LIMIT CONTROL

Urban motorways serve the traffic demand from adjacent dense populated urban regions and transit traffic. Combinations of these two traffic demand types generate periodically traffic congestions during the peak hours. The capacity drop effect is the most common cause of congestions. It occurs when the current traffic flow reached its maximal capacity of the observed urban motorway section. In order to alleviate the capacity drop effect and enable better level of service on motorways new traffic control methods are introduced. One of the used traffic control methods is variable speed limit control (VSLC). VSLC conducts homogenization and reduction of vehicle speeds what consequently decreases time needed to create a critical shockwave, which will induce the capacity drop. This paper presents a short overview of the latest VSLC algorithms originally designed for mitigation of traffic congestions and their effects on the motorway mainline. Firstly, simple reactive VSLC algorithms are introduced. Then approaches based on model based optimization are described. Possible coordination between VSLC and other motorway management strategies is also described in this paper.
Daily and 3‐hourly variability in global fire emissions and consequences for atmospheric model predictions of carbon monoxide

Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic- and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We disaggregated monthly GFED3 emissions during 2003–2009 to a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) Wildfire Automated Biomass Burning Algorithm (WF_ABBA) active fire observations. Daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of burning in savannas. These patterns were consistent with earlier field and modeling work characterizing fire behavior dynamics in different ecosystems. On diurnal timescales, our analysis of the GOES WF_ABBA active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top-down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates.
Flow and sound fields of temporal subsonic round jets

Two temporally-developing isothermal round jets at a Mach number of 0.9 and diameter-based Reynolds numbers Re D of 3125 and 12500 are simulated in order to investigate their flow and acoustic fields. The simulations are carried out using high-order finitedifference schemes on a grid of 940 million points extending up to 120 jet radii in the axial direction. For each case, ten runs are performed, and their results are ensemble averaged. The jet at ReD = 12500 develops more rapidly, exhibits more fine turbulent scales, and generates more high-frequency acoustic waves than the jet at ReD = 3125. For both Reynolds numbers, however, a strong intermittency of the velocity field and high convection velocities are found on the jet axis at the time of the jet potential-core closing. At that time, low-frequency acoustic waves spaced by about 15 jet radii are also emitted in the downstream direction, as observed at the end of the potential core of spatially-developing jets. These results suggest the presence of the same sound source on the axis of temporally-developing and spatially-developing jets.
An Archaeal Photosignal-Transducing Module Mediates Phototaxis in Escherichia coli

ABSTRACT Halophilic archaea, such as Halobacterium salinarumand Natronobacterium pharaonis, alter their swimming behavior by phototaxis responses to changes in light intensity and color using visual pigment-like sensory rhodopsins (SRs). In N. pharaonis, SRII (NpSRII) mediates photorepellent responses through its transducer protein, NpHtrII. Here we report the expression of fusions of NpSRII and NpHtrII and fusion hybrids with eubacterial cytoplasmic domains and analyze their function in vivo in haloarchaea and in eubacteria. A fusion in which the C terminus of NpSRII is connected by a short flexible linker to NpHtrII is active in phototaxis signaling for H. salinarum, showing that the fusion does not inhibit functional receptor-transducer interactions. We replaced the cytoplasmic portions of this fusion protein with the cytoplasmic domains of Tar and Tsr, chemotaxis transducers from enteric eubacteria. Purification of the fusion protein from H. salinarum and Tar fusion chimera from Escherichia coli membranes shows that the proteins are not cleaved and exhibit absorption spectra characteristic of wild-type membranes. Their photochemical reaction cycles in H. salinarum and E. coli membranes, respectively, are similar to those of native NpSRII in N. pharaonis. These fusion chimeras mediate retinal-dependent phototaxis responses by Escherichia coli, establishing that the nine-helix membrane portion of the receptor-transducer complex is a modular functional unit able to signal in heterologous membranes. This result confirms a current model for SR-Htr signal transduction in which the Htr transducers are proposed to interact physically and functionally with their cognate sensory rhodopsins via helix-helix contacts between their transmembrane segments.
MicroRNA-155 induces protection against cerebral ischemia/reperfusion injury through regulation of the Notch pathway in vivo

microRNA (miR)-155 has been demonstrated to participate in the regulation of endothelium during cerebral ischemia. In the present study, it was aimed to investigate the molecular mechanism of miR-155 in the regulation of cerebral ischemia/reperfusion (I/R) injury with middle cerebral artery occlusion (MCAO) in mice. The MCAO model was established in C57BL/6 mice. Transfection of miR-155 mimics and miR-155 inhibitors was performed to alter the expression of miR-155. The level of miR-155 was measured by RT-qPCR analysis. The western blotting results demonstrated that deletion of miR-155 increased the expression of Notch1, intracellular Notch receptor domain (NICD) and hairy and enhancer of split-1 (Hes1) levels. In addition, the percentage of terminal deoxynucleotidyl-transferase-mediated dUTP nick end labeling-positive cells and caspase-3 levels were decreased following treatment with a miR-155 inhibitor compared with the Pre-IR group. Notably, disrupting miR-155 also increased nitric oxide (NO) production and the expression of endothelial NO synthase (eNOS), leading to downregulation of brain water content and Evans blue levels. However, overexpression of miR-155 restored all these changes to similar levels observed in the cerebral I/R injury group. The expressions of Notch1, NICD and Hes1 were also decreased to the cerebral I/R injury condition. In conclusion, a novel mechanism was identified for abrogating normal NO production and eNOS expression via the aberrant expression of the Notch signaling pathway, a mechanism that may be modulated by miR-155. Together, these results reveal important functions of miR-155 in regulating the Notch signaling pathway of the nervous system, and a potential role for miR-155 as a crucial therapy target for cerebral stroke.
Data-driven Sales Operations Management

In this paper, we present a data-driven approach for the allocation of sales resources at DAW, a large, German-based manufacturer of building paint. DAW’s product portfolio mainly focuses on paint and coating solutions for the professional business and is sold via two main distribution channels: The first one comprises the wholesale business where DAW markets their products to paint wholesalers and the specialist trade. The second channel, which is the one we are focusing on in this work, comprises direct sales to large building sites. In the latter business, the company collaborates directly with potential painters and processors to win these objects and supply their products. Evidently, good customer relations are key in this business however, the capacity of the sales team is limited and DAW needs to decide how to allocate these scarce resources. Despite the very particular setting in the paint manufacturing industry, the company faces a problem which is very common for a lot of enterprises and which can be abstracted from the concrete application: The company’s potential customers are dispersed over a large area and as a consequence, the company needs to plan which customer to visit in order to optimize the selling potential. So far, the decision of which customer to visit is completely made by the sales agents based on their own assessment, without providing them with any information about success probabilities for specific sales opportunities. The main reason why this approach will typically lead to suboptimal decisions is that sales agents tend to contact potential customers where a successful sale is very likely. However, these are generally not the sales opportunities where an additional contact by a sales agent yields the highest increase in winning chances, which would be the better criterion. In contrast to the hands-on approach currently in practice in many companies, we propose a new, fully data-driven method to support and improve sales operations planning. Starting with a raw data set received from DAW we obtain 1200 instances of won and lost contracts after some
Poplar Culture for Speedy Carbon Sequestration in India : A Case Study from Terai Region of Uttarakhand

Kyoto Protocol recognizes forestry as an acceptable mean of carbon sequestration, and the sector offers possibilities for significant climate change mitigation. During the Seventh Meeting of Conference of Parties (CoP 7) held at Marrakesh (Morocco) in 2001, it was decided that only afforestation and reforestation (A and R) project activities would be eligible under LULUCF sector of the clean development mechanism (CDM). The A and R project activities eligible under CDM include agroforestry, farm forestry, plantations of mixed species, and orchards. There are enough evidences to show that individuals and communities can use tree plantations sustainably to support livelihoods besides carrying out agricultural and horticultural production. However, the studies on the amount of carbon stored and trading of this carbon in international markets to provide considerable income and overall sustainable development of area are lacking. Intensive field investigations are also required to assess the suitability of different plantation models, which the individuals and communities may like to plant on different lands under CDM forestry projects. Such studies would not only provide valuable information on the scope of CDM A and R projects for sustainable livelihoods, but also encourage the marginal communities to contribute to mitigate global carbon emissions and expanding forest and tree cover (Ravindranath and Murthy, 2003). The progress on preparation of A and R CDM projects in the recent past had been much below the expected levels as the methodologies and the procedures applicable to such forestry projects are seen as complex by the project developers. Limited demand for carbon credits emanating from forestry sector has further restricted the scope of forestry CDM projects. Despite these limitations, by now, ten large-scale, two consolidated, seven small-scale methodologies and a number of tools are available for this sector to assist in project development. Besides, 40 forestry projects have already been registered by the Executive Board of CDM (UNFCCC, 2012). The Kyoto Protocol’s continuation up to 2020 is likely to further benefit the development of CDM forestry projects in future. Populus deltoides, commonly called eastern cottonwood and referred as poplar hereafter is an important agroforestry tree species, especially in the northern alluvial belt of India. It is very commonly seen along with Eucalyptus spp. on The countries like India that has chosen the lower limit of 15 per cent as crown cover could potentially include more agroforestry systems into the REDD-plus mechanism
Evaluation of Speech Recognition by a Person with Articulation Disorder in Operation for Home Information Appliances

ECU (environmental control unit) takes an important role in self-support for developmentally-disabled individual. Some ECU use speech recognition for operation. It is important for a crippled-disabled person to use speech recognition. However, it is very difficult for a person with articulation disorder to use the ECU with speech interface since conventional ECU targets non-articulation disorder as user. Our subject is to build the ECU which can recognize articulation disorder’s speech. In this paper, we built an acoustic model for a person with articulation disorder and evaluated speech recogniton in the task of operation for home information appliances. We used two different speech data as test data. One is recorded under a familiar environment. The other is recorded under an unfamiliar environment. In the experiment for speech data which recorded under the unfamiliar environment, the word-recognition rate of 56.4% was obtained. The speaking style of a person with cerebral palsy tends to fluctuate by the change of environments. Therefore, we carried out speaker adaptation in the test environment, and the word-recognition rate improved to 83.9%.
An enzyme regulating triacylglycerol composition is encoded by the ROD1 gene of Arabidopsis

The polyunsaturated fatty acids (PUFAs) linoleic acid (18:2) and α-linolenic acid (18:3) in triacylglycerols (TAG) are major factors affecting the quality of plant oils for human health, as well as for biofuels and other renewable applications. These PUFAs are essential fatty acids for animals and plants, but also are the source of unhealthy trans fats during the processing of many foodstuffs. PUFAs 18:2 and 18:3 are synthesized in developing seeds by the desaturation of oleic acid (18:1) esterified on the membrane lipid phosphatidylcholine (PC) on the endoplasmic reticulum. The reactions and fluxes involved in this metabolism are incompletely understood, however. Here we show that a previously unrecognized enzyme, phosphatidylcholine:diacylglycerol cholinephosphotransferase (PDCT), encoded by the Arabidopsis ROD1 gene, is a major reaction for the transfer of 18:1 into PC for desaturation and also for the reverse transfer of 18:2 and 18:3 into the TAG synthesis pathway. The PDCT enzyme catalyzes transfer of the phosphocholine headgroup from PC to diacylglycerol, and mutation of rod1 reduces 18:2 and 18:3 accumulation in seed TAG by 40%. Our discovery of PDCT is important for understanding glycerolipid metabolism in plants and other organisms, and provides tools to modify the fatty acid compositions of plant oils for improved nutrition, biofuel, and other purposes.
Evolutionary history of the genus Trisopterus q

The group of small poor cods and pouts from the genus Trisopterus, belonging to the Gadidae family, comprises four described benthopelagic species that occur across the North-eastern Atlantic, from the Baltic Sea to the coast of Morocco, and the Mediterranean. Here, we combined molecular data from mitochondrial (cytochrome b) and nuclear (rhodopsin) genes to confirm the taxonomic status of the described species and to disentangle the evolutionary history of the genus. Our analyses supported the monophyly of the genus Trisopterus and confirmed the recently described species Trisopterus capelanus. A relaxed molecular clock analysis estimated an Oligocene origin for the group ( 30 million years ago; mya) indicating this genus as one of the most ancestral within the Gadidae family. The closure and re-opening of the Strait of Gibraltar after the Messinian Salinity Crisis (MSC) probably triggered the speciation process that resulted in the recently described T. capelanus. 2011 Elsevier Inc. All rights reserved.
Applications of Artificial Neural Network Modeling in Drug Discovery

Copyright: © 2012 Cheng F, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Artificial Neural Networks (ANNs) modeling is a group of computer algorithms for modeling and pattern recognition, functioning similarly to the neurons of the brain. The brain learns from its experience. In the brain, a biological neuron receives inputs from many external resources, combines them, performs a non-linear operation, and then makes a decision based on the final results. The ANNs are a type of mathematical model that simulates the biological nervous system and draws on analogues of adaptive biological neurons. A major advantage of ANNs compared to statistical modeling is that they do not require rigidly structured experimental designs and can map functions using historical or incomplete data. ANNs are good recognizers of patterns and robust classifiers, with the ability to generate when making decisions based on imprecise input data.
Pharm acogenom ics BeadArray TM-based solutions for enabling the promise of pharmacogenomics

INDIVIDUAL DIFFERENCES, INDIVIDUAL OUTCOMES Therapeutic treatments rarely, if ever, work for all patients. Even blockbuster drugs are efficacious in just 40%–60% of the patients to whom they are administered. And many patients suffer adverse drug reactions (ADRs), so much so that ADRs are a leading cause of death among Americans. After all, people are different. Pharmacogenomics (PGx) aims to understand and then take advantage of those differences. Genetic variation, however, affects far more than drug response. Increasingly, scientists and clinical researchers are studying individual differences at the molecular level to understand how genetic variation directly impacts differential disease predisposition, symptomatic development, and clinical outcomes in addition to drug response.
Assessing drivers for organizational commitment towards the security controls implementation in the Malaysian online service in computer-based accounting system 1

The objective of this study is to determine the accessing drivers for organizational commitment towards security controls implementation in the Malaysian online service in computer based accounting system. Based on survey, data was collected from 63 firms in hotel/resort, financial and transportation industry, and suggested that firm size, managerial awareness, regulatory support, as well as vendor support were found to have a positive significant influence towards organizational commitment in security controls implementation. Also, the commitment to implement security controls first comes from the management itself especially senior and top management through managerial awareness as well as the need to safeguard the organization’s reputation. Moreover, regulatory support from government to encourage security controls implementation among organizations are important as it was proven that they have a significant influence towards organizational commitment in security controls implementation.