Miracle-dz/UniFAR-FTUs huggingface dataset:
Power aware node selection in multicast routing for mobile ad hoc networks

Mobile ad hoc network is an infrastructure less self-configuring network, where nodes organize themselves arbitrarily. In this paper, a new multicast algorithm is proposed to increase the life time of the node and network in the mobile ad hoc network with increased packet delivery ratio. To do multicasting, the source node selects a nearest neighbor with maximum residual battery capacity. The proposed algorithm is simulated using network simulator 2.34 and is tested under various conditions and compared with the existing algorithm. Simulation results show that the proposed algorithm outperforms the existing algorithm in terms of packet delivery ratio, throughput, delay, dropping ratio, average energy consumption and life time of network.
Programming Support for a Delay-Tolerant Web of Things. (Support de programmation pour un Web des objets tolérant les délais)

The Internet of Things (IoT) is usually presented as a set of THINGS interconnected through a network that is, in practice, Internet. However, there exist many contexts in which the connectivity is intermittent due to short-range wireless communication means or energy constraints. The Delay Tolerant Networking (DTN) architecture and the Bundle Protocol (BP) are known to overcome this communication challenge as they provide communication means by relying on a store-carry-and- forward mechanism. This thesis aims to provide programming supports adapted to both IoT and DTN contexts. For this, both DTN and IoT (DT-IoT) challenges are studied and several design principles are proposed. These principles aim to optimize reactivity and efficiency of applications targeting the DT-IoT context. The first contribution is the definition of a resource-oriented programming support, named BoaP, to enable a DT-IoT. It provides a protocol based on request/response thanks to a transposition of CoAP (Contrained Application Protocol). This transposition consists of fundamental adjustments and enhancements to use BP as the underlying transport protocol. BoaP has been implemented and tested in a small physical network. A method to evaluate middleware systems in DTNs is presented. A tool implementing this method has been developed. It relies on a virtualization platform that simulates network contacts and emulates network devices. This tool was used to run experimentations that assessed the validity of BoaP. Finally, another programming support is investigated. It follows a service-oriented approach and respects REST (Representational State Transfer) constraints. It is built on top of BoaP with IoT in mind and is adapted to DTN environments. Its discovery/advertisement exploits a publish/subscribe interface. Service descriptors contain specific fields to inform on the availability of the service providers. %Finally, requests are extended with some options to enforce conditions on geographic or time context.
New Ways of Being a Man

Connell’s concept of hegemonic masculinity is often reduced to a singular construct, consisting of “toxic” traits viewed as detrimental to well-being. However, the concept allows for variation in hegemony, including the possibility of forms more conducive to well-being. Through in-depth interviews with thirty male meditators in the United Kingdom, we explored the social dimensions of meditation practice to examine its potential implications for well-being. Most participants became involved with “communities of practice” centered on meditation that promoted new local hegemonies, and these included ideals experienced as conducive to well-being, like abstinence. However, social processes associated with hegemony, like hierarchy and marginalization, were not overturned. Moreover, participants faced challenges enacting new practices in relation to the broader system of hegemonic masculinity—outside these communities—reporting censure. Our findings are cautionary for professionals seeking to encourage well-being behaviors: that is, there is potential for adaptation in men, yet complex social processes influence this change.
Coordination of Regulated and Merchant Energy Storage Investments

Distributed transmission-scale energy storage is becoming economically feasible due to the growing share of renewable generation and cost reduction of specific storage technologies, primarily batteries. Under these circumstances, independent merchants may start investing in storage facilities. On the other hand, system operators, besides investing in transmission lines, may, under certain conditions, invest in storage units as well. This paper formulates a trilevel model where the upper-level problem optimizes the system operator's transmission line and energy storage investments, the middle-level problem determines merchant energy storage investment decisions, while the lower level problem simulates market clearing process for representative days. After replacing the lower level problem with its primal dual equivalent conditions, the middle- and lower level problems are merged into a mixed-integer problem with equilibrium constraints. The resulting bilevel structure is iteratively solved using a cutting plane algorithm. The proposed formulation is first applied to a six-bus system to present the mechanics of the model and then to the IEEE RTS-96 test system. The results show that even at the low cost of energy storage, the system operator (SO) still prefers line investments, while merchant investments are driven by the volatility of LMPs. Both the SO and merchant investments increase the social welfare, although this increase is mostly driven by the SO investments.
An Ensemble Forecasting Method for the Aggregated Load With Subprofiles

With the prevalence of smart meters, fine-grained subprofiles reveal more information about the aggregated load and further help improve the forecasting accuracy. Ensemble is an effective approach for load forecasting. It either generates multiple training datasets or applies multiple forecasting models to produce multiple forecasts. In this letter, a novel ensemble method is proposed to forecast the aggregated load with subprofiles where the multiple forecasts are produced by different groupings of subprofiles. Specifically, the subprofiles are first clustered into different groups and forecasting is conducted on the grouped load profiles individually. Thus, these forecasts can be summed to form the aggregated load forecast. In this way, different aggregated load forecasts can be obtained by varying the number of clusters. Finally, an optimal weighted ensemble approach is employed to combine these forecasts and provide the final forecasting result. Case studies are conducted on two open datasets and verify the effectiveness and superiority of the proposed method.
Epigenetic mechanism of FMR 1 inactivation in Fragile X syndrome

Fragile X syndrome is the most frequent cause of inherited intellectual disability. The primary molecular defect in this disease is the expansion of a CGG repeat in the 5’ region of the fragile X mental retardation1 (FMR1) gene, leading to de novo methylation of the promoter and inactivation of this otherwise normal gene, but little is known about how these epigenetic changes occur during development. In order to gain insight into the nature of this process, we have used cell fusion technology to recapitulate the events that occur during early embryogenesis. These experiments suggest that the naturally occurring Fragile XFMR1 5’ region undergoes inactivation post implantation in a Dicer/Ago-dependent targeted process which involves local SUV39H-mediated tri-methylation of histone H3K9. It thus appears that Fragile X syndrome may come about through inadvertent siRNA-mediated heterochromatinization.
Fog computing and security issues: A review

The paradigm of fog computing has set new trends and heights in the modern world networking and have overcome the major technical complexities of cloud computing. It is not a replacement of cloud computing technology but it just adds feasible advanced characteristics to existing cloud computing paradigm.fog computing not only provide storage, networking and computing services but also provide a platform for IoT (internet of things). However, the fog computing technology also arise the threat to privacy and security of the data and services. The existing security and privacy mechanisms of the cloud computing cannot be applied to the fog computing directly due to its basic characteristics of large-scale geo-distribution, mobility and heterogeneity. This article provides an overview of the present existing issues and challenges in fog computing.
NEW META-HEURISTIC OPTIMIZATION ALGORITHM USING NEURONAL COMMUNICATION

A new meta-heuristic method, based on Neuronal Communication (NC), is introduced in this article. The neuronal communication illustrates how data is exchanged between neurons in neural system. Actually, this pattern works efficiently in the nature. The present paper shows it is the same to find the global minimum. In addition, since few numbers of neurons participate in each step of the method, the cost of calculation is less than the other comparable meta-heuristic methods. Besides, gradient calculation and a continuous domain are not necessary for the process of the algorithm. In this article, some new weighting functions are introduced to improve the convergence of the algorithm. In the end, various benchmark functions and engineering problems are examined and the results are illustrated to show the capability, efficiency of the method. It is valuable to note that the average number of iterations for fifty independent runs of functions have been decreased by using Neuronal Communication algorithm in comparison to a majority of methods.
ISOLATION AND IDENTIFICATION OF FLAVONOIDS FROM CYPERUS ROTUNDUS LINN. IN VIVO AND IN VITRO

Cyperus rotundus (Linn.) is an important medicinal plant belonging to family Cyperaceae. Four Flavonoids such as quercetin, kaempferol, catechin and myricetin were isolated from in vivo (leaf and root) and in vitro callus of this species. These compounds are extensively used in Ayurvedic preparation of medicines and are highly in demand in pharmaceutical industries. The present study therefore was undertaken to determine and compare the production of these flavonoids from in vitro callus culture and in vivo plant parts of C. rotundus . Quantification data revealed that the total flavonoid content (free + bound) was higher in tissue culture than in plant parts. The maximum amount of total flavonoid was found in six weeks old callus tissue (1.96mg/g.d.w) and minimum (0.28mg/g.d.w) in two week old callus tissue. In vivo studies showed higher flavonoids content in leaf in free form (0.58mg/g.d.w.) and bound form (0.48mg/g.d.w.) when compared to root in free form (0.19mg/g.d.w) and bound form (0.11mg/g.d.w). Keywords: Cyperus rotundus , Callus culture, Flavonoids
Using drones in a warehouse with minimum energy consumption

In this paper we analyze the feasibility of using drones in a manufacturing factory that requires multiple transports from the warehouse to the workstations. Considering low cost drones it is understood that they have little autonomy and low load capacity. To minimize energy consumption a mathematical model of vehicle routing type is used, in three dimensions, which is solved using a heuristic method based on the structure of the problem. The problem is complex because the routes must be planned in order to avoid collisions, therefore they must follow time windows in the deliveries.
A Contract Game for Direct Energy Trading in Smart Grid

Direct trading is a promising approach to simultaneously achieve trading benefits and reduce transmission line losses in smart grid. However, due to the selfish nature, small-scale electricity suppliers (SESs) and electricity consumers (ECs) will not participate direct trading if the trading does not bring them benefits. Therefore, how to provide proper economic incentives for these two parties to take part in direct trading is an essential issue. Nevertheless, the asymmetry trading information between them makes the problem challenging. In this paper, we propose a contract-based direct trading framework to tackle this challenge, in which the decision making process of ECs and SESs in the presence of asymmetric information is modeled as a contract game. In the proposed game, the EC designs a contract which contains its trading strategies toward all types of SESs. Through the contract, the EC not only attracts SESs to sell electricity but also maximizes its own revenue. The SESs, on the other hand, get maximal benefits if they truthfully select the contract items of their own types. We derive theoretically the optimal contract for the short-term market where the supply of SESs is deterministic. Then we extend our study to the long-term market where the supply of SESs is encountering significant uncertainty. Finally, simulation results are shown to verify the effectiveness of the proposed scheme.
Biochemical effects of methomyl on experimental animals

Received: 15 December 2013 Accepted: 24 January 2014 Published: 20 February 2014 Genotoxic effects of agricultural chemicals are of special concern because of their generally irreversible effects and the long latency associated with their manifestation. These effects include heritable genetic diseases, carcinogenesis, reproductive dysfunction and birth defects. The present study was carried out to investigate the effect of the insecticide "Methomyl" on male albino mice. The mice were treated for 30 days with three different doses of Methomyl (1/20 LD50, 1/40 LD50 and 1/80 LD50). Xenobiotic enzymes genotype were selected for this study because they are known to participate in metabolism of suspected or established carcinogens, and because polymorphism of these genes have been associated with an increased cancer risk in adults. Thus the major objectives of the present study was to evaluate the toxicological (cytogenic and mutagenic) effects of tested pesticide include polymorphism of glutathione-S-transferase T1 (GSTT1) and glutathione-S-transferase M1 (GSTM1). The genotoxic effect of the pesticide was evaluated by using polymorphism of glutathione S-transferase (GST) by polymerase chain reaction (PCR). Polymorphism of both (GSTM1 and (GSTT1) showed positive genotype in all doses. The (GSTM1) polymorphism showed positive genotype in the high and medium doses (1/20 LD50 and 1/40 LD50) but not in the low dose (1/80 LD50). From these results we concluded that tested pesticides exert mutagenic effects in male albino mice. © 2014 PSCI Publisher All rights reserved.
Computational analysis of hybrid high efficiency video encoders

With the evolution of technology, it has become necessary to make transmission more competitive. By using new state-of-the-art coding technology HEVC (H.265), one will be able to broadcast more programs, using HDTV instead of SD, accompanied by further improvements in audio and data services. Moreover, enhancement in broadcasting video-on-demand services and live streaming is possible with faster rate and low cost. The aim of this new standard is to transmit high resolution video in low bandwidth. This article focus on performance comparison between HEVC and H.264 video compression standards in terms of encoding time and PSNR and bit rate. Four different test sequences in random access configuration were used for HM software(HEVC test model) and same configuration was maintained for JM reference software (H.264 test model) as well in order to carry out the experimentation. It was been observed that HM obtains more compression ratio than JM in turn it can deliver the video at half the bit rate as compared to earlier codec standard JM but this is achieved at the cost of increase in encoding time.
Multi-Layer Ensembling Techniques for Multilingual Intent Classification

In this paper we determine how multi-layer ensembling improves performance on multilingual intent classification. We develop a novel multi-layer ensembling approach that ensembles both different model initializations and different model architectures. We also introduce a new banking domain dataset and compare results against the standard ATIS dataset and the Chinese SMP2017 dataset to determine ensembling performance in multilingual and multi-domain contexts. We run ensemble experiments across all three datasets, and conclude that ensembling provides significant performance increases, and that multi-layer ensembling is a no-risk way to improve performance on intent classification. We also find that a diverse ensemble of simple models can reach perform comparable to much more sophisticated state-of-the-art models. Our best F 1 scores on ATIS, Banking, and SMP are 97.54%, 91.79%, and 93.55% respectively, which compare well with the state-of-the-art on ATIS and best submission to the SMP2017 competition. The total ensembling performance increases we achieve are 0.23%, 1.96%, and 4.04% F 1 respectively.
The Safety and Utility of Phenobarbital Use for the Treatment of Severe Alcohol Withdrawal Syndrome in the Medical Intensive Care Unit

Background: Alcohol withdrawal syndrome (AWS) is a common reason for admission to a medical intensive care unit (MICU) and requires significant hospital resource utilization. Benzodiazepines are first-line therapy for AWS in many intensive care units. We propose the use of symptom-triggered phenobarbital for the treatment of AWS as a safe alternative to benzodiazepines. Methods: This was a retrospective observational study of a 4-year period, 2011 to 2015, of all patients with AWS admitted to the MICU of 1 tertiary care hospital and treated with phenobarbital. A symptom-triggered protocol was used. Resolution of AWS was assessed with the Richmond Agitation Sedation Scale to goal score of 0 to −1. The Charlson Comorbidity Index was used as an index of patient illness severity. Complications associated with phenobarbital use and/or the AWS admission were analyzed. Results: Data of 86 AWS patient encounters were analyzed. The mean Clinical Institute Withdrawal Assessment for Alcohol–Revised score of patients admitted to the MICU with AWS was 19 ± 9. The mean phenobarbital dose administered during the MICU stay was 1977.5 ± 1531.5 mg. There were a total of 17 (20%) intubations. The most frequent cause of mechanical ventilation in patients with AWS was loss of airway clearance, followed by hemodynamic instability secondary to upper gastrointestinal bleeding and the corresponding need for endoscopy. Conclusions: Sole use of phenobarbital use for control of AWS may be a safe alternative to benzodiazepines. Further study is needed to correlate phenobarbital serum levels with clinical control of AWS.
Understanding and clustering hashtags according to their word distributions

The purpose of our study is to understanding hashtags used in Twitter and clustering hashtags according to their word distribution, so that we can discover the public trend of user's topic in real time and bring benefit to marketing management. We extract the most frequent hashtags from sample tweets and then collect sample tweets related to these hashtags. We create a list of the word with frequent and probability and sort it by most frequent word. When looking through this word list, we can realize what is the meaning represented by each hashtag. Furthermore we cluster hashtags to several groups according to Jensen-Shannon divergence between any two hashtags and represent the results with dendrogram, which provides the hierarchical structure of all hashtags. As a result, it can be expected to deliver advertisements to Twitter users more precisely according to their interests.
PM 2 . 5 exacerbate allergic asthma involved in autophagy signaling pathway in mice

Epidemiological studies indicate an association between high levels of ambient particulate matter and increased incidence of asthma disorders. Asthmatics experience a physiologic airway disturbance, many forms of which are caused by chronic airway inflammatory processes. We previously demonstrated that particulate matter 2.5 (PM2.5) toxicology induces autophagy via inhibition of the PI3K/Akt/mTOR-kinase signaling pathway in human bronchial epithelial cells. PM2.5 also exacerbates asthma in a murine model of allergen-induced asthma, but its mechanism remains elusive. We used a mouse model (6-8 week-old SPF female BALB/c mouse sensitized with Ovalbumin (OVA)) to investigate the effect of PM2.5 on allergic inflammatory asthma. We evaluated PM2.5-induced inflammation and bronchial hyperreactivity and analyzed the correlation between these factors and autophagy. Mice were sensitized at day 1, 8, 15 and challenged at day 16, 19, 22 with OVA or OVA+PM2.5 or PM2.5 only. Mice were sacrificed one day following the last OVA challenge. Bronchial hyperreactivity was assessed with methacholine. Levels of inflammatory cytokines were measured by enzyme-linked immuno sorbent assay (ELISA) or real-time quantitative PCR (QPCR) respectively. The expression of autophagy genes was detected by RT-qPCR or western blot; LC3-positive vesicles were revealed by immunofluorescence microscopy. We found that the total number of cells and the number of eosinophils, neutrophils and macrophages from bronchial alveolar lavage fluid (BALF) in the OVA-sensitization/OVA + PM2.5-challenge (AP) group were significantly higher than in the control (NC) group and OVA-sensitization + OVA-challenge (AC) group. We observed some correlation between autophagy and inflammatory factors in the PM2.5-exacerbated mouse asthma model. Our data demonstrated that elevated inflammatory levels were strongly associated with reduced autophagy related factors in the OVA/PM2.5-exacerbated mouse allergic inflammatory asthma model. PM2.5 exacerbated inflammation and decreased autophagy in this mouse allergic inflammatory asthma model. However, PM2.5 alone did not along trigger asthmatic responses in the absence of concurrent OVA challenge. The present findings support the role of PM2.5 in augmenting allergic inflammatory asthma.
Optimized delta compression in live migration of virtual machines

Live migration becomes an essential feature for any popular hypervisor under consideration. But in many situations, because of huge amount of data transfer between servers, live migration is a challenging task at real time scenario. Ideally during live migration, the major performance matrices like down time, total migration time and amount of data transferred should be the minimum to keep all running applications in virtual machines uninterrupted. To achieve this, we analyze delta compression method to compress the VM snapshots while performing live migration between servers as a modification in KVM hypervisor. Delta compression drastically reduce the amount of data transferred and improve overall performance of live migration. Here we use LZ4 algorithm for delta compression instead of existing XBRLE. As per the experiments conducted for various workloads and input files LZ4 algorithm gives better results in terms of amount of data transferred, down time and total migration time and compression ratio as compared with XBRLE. In addition to this, to overcome the cache churning issue we suggest a four way set associative mapping for cache performance improvement.