Miracle-dz/UniFAR-FTUs huggingface dataset:
Translational Value of the Transdermal Administration of Bergamot Essential Oil and of Its Fractions

The essential oil of bergamot (BEO) has consistently proven antinociceptive and antiallodynic properties. Accordingly, the analgesic efficacy of the decolored essential oil (DEC), with higher levels of limonene, and the deterpenated (DET) fraction, with higher levels of linalool and linalyl acetate, was investigated using a formalin test after inhalation. The present study was aimed at characterizing the effects of BEO, its components with the highest pharmacological activity (represented by linalool, limonene, and linalyl acetate), and its DEC and DET fractions on the formalin test after transdermal administration relevant to clinical translation through topical application. To this aim, the schedule of intervention involved administration immediately after formalin injection or as a 5 min pretreatment followed by washout in ddY-strain mice. This study demonstrates, for the first time, the significant analgesic effect of all three constituents in the first and second phases, accounting for the efficacy of the essential oil in the formalin test. While all fractions revealed equal activity toward the phytocomplex in the early phase, the reduction in time of licking/biting during the late phase was more markedly induced by DEC. Moreover, pretreatment with BEO and its fractions followed by washout did not produce a significant reduction in licking/biting time in both phases of formalin-induced nociceptive response.
Network Analysis of Reconnaissance and Intrusion of an Industrial Control System

Abstract : This report describes the results of an experiment assessing 5 security configurations in order to increase the amount of security for an industrial control system (ICS). The first objective was to evaluate how network topology affects the information learned by an attacker to conduct passive reconnaissance of an ICS. The second objective was to identify useful methods to detect network intrusion. The testbed experiment demonstrated that network segregation and technical controls can reduce the attack surface of an ICS network. The experiment also revealed that whitelisting techniques can detect an attacker since ICS network hosts rarely change. In addition, we describe general methods for characterizing baseline Modbus traffic that could be used for detecting anomalous ICS traffic from an attacker.
Fusion of Multiple Audio Representations for Music Genre Classiﬁcation

Music classiﬁcation is one of the most studied tasks in music information retrieval. Notably, one of the targets with high interest in this task is the music genre. In this scenario, the use of deep neural networks has led to the current state-of-the-art results. Research en-deavors in this knowledge domain focus on a single feature to represent the audio in the input for the classiﬁcation model. Due to this task’s nature, researchers usually rely on time-frequency-based features, especially those designed to make timbre more explicit. However, the audio processing literature presents many strategies to build representations that reveal diverse characteristics of music, such as key and tempo, which may contribute with relevant information for the classiﬁcation of genres. We showed an exploratory study on different neural network model fusion techniques for music genre classiﬁcation with multiple features as input. Our results demonstrate that Multi-Feature Fusion Networks consistently improve the classi-ﬁcation accuracy for suitable choices of input representations.
HVAC control loop performance assessment: A critical review (1587-RP)

This article presents a comprehensive review of control loop performance assessments in the context of building HVAC controls. Few studies are available for assessing HVAC control loop performance using a single control quality factor. A control quality factor should be an objective and quantitative metric with simple-to-interpret criteria and should only use data available from the actual control system, such as the control output. The authors systematically reviewed 34 indices and the associated methods of evaluating control loop performance and cataloged the drawbacks and merits of the different indices. Most of these performance assessment indices are currently used in process control industry applications. There were 14 of the 34 indices selected for further review, due to their particular suitability for implementation in HVAC control loop performance assessment. Finally, the selected 14 indices are implemented for assessments of three regulatory control loops with proportional-integral controllers: a heating coil outlet air temperature control loop and variable air volume room air temperature control loop using simulated data from a dynamic Modelica model, and variable air volume room air temperature control loop in a heating mode from real field data. Based on the review and preliminary results, the Normalized Harris Index and exponentially weighted moving averages based index are proposed as potential candidates for control quality factor, and further investigation of the use of them in HVAC control loop performance assessment is recommended.
The Role of the Nucleotides in the Insertion of the bis-Molybdopterin Guanine Dinucleotide Cofactor into apo-Molybdoenzymes

The role of the GMP nucleotides of the bis-molybdopterin guanine dinucleotide (bis-MGD) cofactor of the DMSO reductase family has long been a subject of discussion. The recent characterization of the bis-molybdopterin (bis-Mo-MPT) cofactor present in the E. coli YdhV protein, which differs from bis-MGD solely by the absence of the nucleotides, now enables studying the role of the nucleotides of bis-MGD and bis-MPT cofactors in Moco insertion and the activity of molybdoenzymes in direct comparison. Using the well-known E. coli TMAO reductase TorA as a model enzyme for cofactor insertion, we were able to show that the GMP nucleotides of bis-MGD are crucial for the insertion of the bis-MGD cofactor into apo-TorA.
Observers of a nonlinear neutral system modelling a musical brass instrument

A model of a trumpet-like instrument is described by a nonlinear neutral system controlled by the mouth pressure. The output is the pressure at the end of the pipe. A nonlinear state observer of this system is built. Local asymptotic stability of the error estimation is proved using a Lyapunov-based analysis and illustrated by simulations.
Modeifed artificial bee colony algorithm for gene selection in classifying cancer

Development of cancer diagnostic models by utilizing microarray data has become a topic of great interest in the field of bioinformatics and medicine. Only a small number of gene expression data compared to the total number of genes explored possess a significant correlation with a certain phenotype. Gene selection enables researchers to obtain substantial insight into the genetic nature of the disease and the mechanisms responsible for it. Besides improvement of the performance of cancer classification, it can also cut down the time and cost of medical diagnosis. This study presents a modified Artificial Bee Colony Algorithm (ABC) to select a minimum number of genes that are deemed to be significant for cancer along with improvement of predictive accuracy. The search equation of ABC is said to be good at exploration but poor at exploitation. To overcome this limitation we have modified the ABC algorithm by incorporating pheromone which is one of the major components of Ant Colony Optimization (ACO) algorithm and introduced a new operation in which successive bees communicate to share their findings. The proposed algorithm is evaluated using a suite of ten publicly available datasets after the parameters are scientifically tuned with one of the datasets. The obtained results are compared to other works which used the same datasets. The performance of the proposed method has been proved to be superior. The method presented in this paper can provide a subset of genes leading to more accurate classification results while the number of selected genes is smaller. The proposed modified ABC Algorithm could conceivably be applied to problems in other areas.
Gestión energética mediante procesos estocásticos para la respuesta a la demanda

Population increase and industrial development have forced a greater energy demand, this forces the generating companies to increase their infrastructure of energy production, which is very expensive; for this reason, is sought to implement Demand Response Policies, including Distributed Generation, on this way, consumption will be achieved more efficient, like transferring non-representative loads of peak hours to other time periods. Also, it’s possible to implement Energy Management Systems, in other words, adopt policies where is necessary to plan an optimal consumption and applying to general or industrial electrical system. These policies will help to energy company improving its competitiveness, it includes reduction of energy consumption using more efficient equipment. It should be considered that improving equipment technology is not enough in fact to have energy efficiency, this should be accompanied by an optimal use of energy resources and their optimal use with skillful and precise ways. To solve the problem of energy consumption, it has been used stochastic processes, where an optimization of consumption is done through Demand Response Policies, then, through economic dispatch, it’s possible to find the lowest generation cost, using cheaper and less polluting generators, since it will be left aside part of thermal generation, reducing the costs of electrical production and also contributing to the reduction of environmental pollution with less CO2 emissions.
Lift of a Rotating Circular Cylinder In Unsteady Flows

A cylinder rotating in steady current experiences a lift known as the Magnus effect. In the present study, the effect of waves on the Magnus effect has been investigated. This situation is experienced with the novel, floating offshore vertical axis wind turbine (VAWT) concept called the DEEPWIND concept, which incorporates a rotating spar buoy and thereby utilizes seawater as a roller bearing. The a priori assumption and the results suggest that the lift in waves, to a first approximation, may be represented by a formulation similar to the well-known Morison formulation. The force coefficients are experimentally found to depend primarily on the ratio between the surface speed of the cylinder and the outer flow velocity.
Active self-diagnosis in telecommunication networks

While modern networks and services are continuously growing in scale, complexity and heterogeneity, the management of such systems is reaching the limits of human capabilities. Technically and economically, more automation of the classical management tasks is needed. This has triggered a significant research effort, gathered under the terms self-management and autonomic networking. The aim of this thesis is to contribute to the realization of some self-management properties in telecommunication networks. We propose an approach to automatize the management of faults, covering the different segments of a network, and the end-to-end services deployed over them. This is a model-based approach addressing the two weaknesses of model-based diagnosis namely: a) how to derive such a model, suited to a given network at a given time, in particular if one wishes to capture several network layers and segments and b) how to reason a potentially huge model, if one wishes to manage a nation-wide network for example. To address the first point, we propose a new concept called self-modeling that formulates off-line generic patterns of the model, and identifies on-line the instances of these patterns that are deployed in the managed network. The second point is addressed by an active self-diagnosis engine, based on a Bayesian network formalism, that consists in reasoning on a progressively growing fragment of the network model, relying on the self-modeling ability: more observations are collected and new tests are performed until the faults are localized with sufficient confidence. This active diagnosis approach has been experimented to perform cross-layer and cross-segment alarm management on an IMS network.
Forwarding Strategies Effect on Named Data Network Traffic Load. Case Study : Simulation with Mini NDN

NDN is a new network architecture where packets no longer carry information in the form of source and destination addresses but carry the name of data. FIB (Forwarding Information Base) is one of the structures in the NDN routers used for packet forwarding in the network. The FIB contains the information needed for decision-making on where the packet of interest will be forwarded. NDN forwarding process has many strategies such as best route, multicast, access, broadcast, etc. This study discusses the comparison between best-route and multicast forwarding strategies and their effect on traffic load. The simulation is performed on Mini-NDN using a topology consisting of five fully-mesh nodes and two nodes connected to the mesh via a single link. Two single-link nodes are used as producer and consumer. The traffic load parameters used to compare the performance of the best-route and multicast forwarding strategies are average delay of the packet, throughput in the consumer node, and average packets drop. In addition, the simulation is carried out by varying the frequency of interest from the consumer then observing its effect on delay of packet and packet drop.
Silicon-on-insulator 'gate-all-around device'

Describes the process fabrication and the electrical characteristics of an SOI (silicon-on-insulator) MOSFET with gate oxide and a gate electrode not only on top of the active silicon film but also underneath it. Device fabrication is simple and necessitates only a single additional mask and etch step, compared to standard SOI processing. The device shows evidence of volume inversion (inversion is observed not only in surface channels, but through the entire thickness of the silicon film). Because of the presence of two channels and because of reduced carrier scattering within the bulk of the silicon film, the transconductance of the 'gate-all-around' device is more than twice that of a conventional SOI device, and its subthreshold slope is nearly 60 mV/decade at room temperature. <<ETX>>
Occurrence of Toxoplasma gondii and Neospora caninum antibodies and risk factors in domiciliated dogs of Manaus, Amazonas, Brazil

Abstract The presence of antibodies anti-Toxoplasma gondii and Neospora caninum have been described in dogs from virtually all Brazilian states, however in the state of Amazonas, there are few studies on these coccidia. In this study the occurrence of antibodies against T. gondii and N. caninum and risk factors were determined in domiciliated dogs of Manaus, AM. Blood samples were collected from 154 dogs and, during the harvest, a questionnaire was applied with questions related to the animals. The samples were analyzed, for the presence of anti-T. gondii and N. caninum antibodies, by indirect fluorescence antibody test, with cutoff of 16 and 50, respectively. Associations between the variables studied and the presence of antibodies were made by chi-square test, fisher's exact test or G test (p<0.05). Of the 154 samples, 19 (12.3% 95% CI = 7.1% - 17.5%) were reagents to T. gondii, and association (p <0.05) was observed between the presence of antibodies and contact with other dogs. The occurrence of dogs reactive to N. caninum was 1.9% (95% CI = 0.4% - 5.6%) with 3 of the 154 dogs positives, and no association (p>0.05) was observed between the presence of N. caninum antibodies, and the variables studied.
Nanoemulsified Formulation of Cedrela odorata Essential Oil and Its Larvicidal Effect against Spodoptera frugiperda (J.E. Smith)

Cedrela odorata L. is a plant species from the Meliaceae family that is cultivated for timber production. Although the C. odorata essential oil (EO) contains mainly sesquiterpenes, its insecticidal potential is unknown. The lipophilic properties and high degradation capacity of EOs have limited their application for use in pest control. However, the currently available knowledge on the nanoemulsification of EOs, in addition to the possibility of improving their dispersion, would allow them to prolong their permanence in the field. The objective of the present work was to develop a nanoemulsion of the C. odorata EO and to evaluate its larvicidal activity against Spodoptera frugiperda. The EO was obtained by the hydrodistillation of C. odorata dehydrated leaves, and the nanoemulsion was prepared with non-ionic surfactants (Tween 80 and Span 80) using a combined method of agitation and dispersion with ultrasound. The stability of the nanoemulsion with a droplet diameter of <200 nm was verified in samples stored at 5 °C and 25 °C for 90 days. Both the C. odorata EO and its corresponding nanoemulsion presented lethal properties against S. frugiperda. The results obtained provide guidelines for the use of wood waste to produce sustainable and effective insecticides in the fight against S. frugiperda. In addition, considering that a phytochemical complex mixture allows the simultaneous activation of different action mechanisms, the development of resistance in insects is slower.
A mechanistic study on graphene-based nonvolatile ReRAM devices

Nonvolatile resistive switching random access memory (ReRAM) devices have been of critical importance in the recent information technology industry. A resistive switching memory cell in ReRAM is generally based on simple three-dimensional stacked structures composed of an insulating material sandwiched between two electrodes. Recently, graphene-based 2D materials have been actively employed as either active dielectric layers or electrodes in ReRAM devices. It is noted, however, that the working mechanism of the devices with a focus on the role of graphene-based materials has not yet been systematically discussed. Therefore, in this review article, we first overview the operation mechanism of the devices employing graphene oxide (GO), reduced graphene oxide (rGO), hybrid GO, and hybrid rGO as dielectric layers. Next, the mechanism of the cells based on graphene electrodes is summarized. We systematically discuss the operation principle in terms of the constitution and architecture of the cells. The comprehensive review is finalized with concluding remarks and a prospective for future study.
Torque Ripple Reduction for BLDC Permanent Magnet Motor Drive Using DC-Link Voltage and Current Modulation

This paper proposes a torque ripple reduction for brushless DC (BLDC) permanent magnetic (PM) motor drive based on the DC-link voltage pulse amplitude modulation (PAM). The proposed method improves torque ripple drawback for BLDC drives at low speed. BLDC drives have the better inverter efficiency and requires low position sensing resolution. However, both freewheeling current during diode conduction and discontinuous motor phase current cause high torque ripples. In this paper, a front-end DC converter is added to improve BLDC torque ripples. Although the integration of DC converter and BLDC drive has been reported, the DC voltage regulation for the BLDC torque ripple compensation is this paper novelty. On the basis, the DC bus is modulated during diode conduction to manipulate the DC current dynamically every BLDC commutation period. In addition considering the discontinuous six-step commutation, the DC current is also regulated with the 6th-order spatial harmonic to minimize the commutation reflected torque ripple. The proposed torque ripple compensation of BLDC drive is verified by simulation for different PM motor types. According to experimental results, around 40% torque ripple reduction on a PM motor is demonstrated using the proposed BLDC drive with DC voltage modulation.
Synthesis and characterization of hydrogel nanocomposite based on functional CNTs–copper sulfate-polymethyl methacrylate

abstract This work reports the preparation of hydrogel nanocomposites based on copolymerization of methyl methacrylate using ammonium persulfate as the initiator, methylene bisacrylic amide as the crosslinker & various amounts of functionalized CNT for inter-hydrogel binding. Functionalization of CNTs was performed by its oxidation at room temperature using nitric acid as the oxidizing agent, then acylation of carboxylic acid agent in CNTs by SOCl2 addition and finally esterification of CNTs by the addition of ethylene glycol to acylchloride. The swelling rate of the obtained composites was checked in deionized water where the composite containing more CNTs percent in the hydrogel structure showed a higher swelling rate (>50%). Then, for increase of chemical activity, the obtained hydrogel nanocomposites were impregnated by solution of CuSO4 with different concentrations and the resultant hydrogels as the activity filler were analyzed by FTIR, XRD and SEM.
A 21-Gb/s Duobinary Transceiver for GDDR Interfaces With an Adaptive Equalizer

In this article, we propose a duobinary transceiver for graphics double-data-rate (GDDR) memory interfaces. The proposed voltage-mode driver complies with the GDDR impedance specifications without sacrificing the ratio of level mismatch (RLM). The quarter-rate time-interleaved successive approximation duobinary receiver (Rx) reduces the forwarded clock frequency and minimizes the capacitive loading of the front-end analog equalizer (EQ). To compensate for the channel loss, the transmitter is composed of a three-tap feed-forward EQ, and the Rx employs a continuous-time linear EQ. Also, an EQ adaptation scheme applicable to duobinary signaling is proposed. The transceiver achieves a 10−12 bit error rate at 21 Gb/s with 1.42 mW/Gb.
Tree-KGQA: An Unsupervised Approach for Question Answering Over Knowledge Graphs

Most Knowledge Graph-based Question Answering (KGQA) systems rely on training data to reach their optimal performance. However, acquiring training data for supervised systems is both time-consuming and resource-intensive. To address this, in this paper, we propose Tree-KGQA, an unsupervised KGQA system leveraging pre-trained language models and tree-based algorithms. Entity and relation linking are essential components of any KGQA system. We employ several pre-trained language models in the entity linking task to recognize the entities mentioned in the question and obtain the contextual representation for indexing. Furthermore, for relation linking we incorporate a pre-trained language model previously trained for language inference task. Finally, we introduce a novel algorithm for extracting the answer entities from a KG, where we construct a forest of interpretations and introduce tree-walking and tree disambiguation techniques. Our algorithm uses the linked relation and predicts the tree branches that eventually lead to the potential answer entities. The proposed method achieves 4.5% and 7.1% gains in F1 score in entity linking tasks on LC-QuAD 2.0 and LC-QuAD 2.0 (KBpearl) datasets, respectively, and a 5.4% increase in the relation linking task on LC-QuAD 2.0 (KBpearl). The comprehensive evaluations demonstrate that our unsupervised KGQA approach outperforms other supervised state-of-the-art methods on the WebQSP-WD test set (1.4% increase in F1 score) - without training on the target dataset.