Miracle-dz/UniFAR-FTUs huggingface dataset:
Biopolymer Xanthan: A New Adjuvant for DNA Vaccines

: DNA vaccines have been evaluated as an option to prevent several diseases. In this study, the capacity of the xanthan biopolymer to improve the DNA vaccines immune response, administered intramuscularly, was evaluated. The experimental vaccines consisted of genes encoding fragments of the proteins LigA and LigB of Leptospira interrogans serogroup Icterohaemorrhagiae serovar Copenhageni strain Fiocruz L1-130. The humoral immune response was evaluated by indirect ELISA. Cytokine expression levels were determined by RT-qPCR. Compared to the control group, the IgG antibody levels of animals immunized with pTARGET/ ligAni and pTARGET/ ligBrep plasmids associated with xanthan biopolymer were significantly higher than the control group. Additionally, there was a significant increase in IL-17 expression in animals vaccinated with pTARGET/ ligBrep and xanthan.
An Extensive Survey on Metamaterial Based Antenna Design for Breast Cancer Detection

The Threats To Human Life Due To Cancer Is Growing Faster And Early Detection And Easy Diagnostic Methods Are In Demand. This Paper Provides A Detailed Survey On Metamaterials And Analysis Of Various Antenna Structures To Detect Breast Cancer At The Earliest. The Cancer In The Breast Can Be Effectively Diagnosed And Screened Using Microwave Imaging Technique. This Can Be Achieved By Designing A Medical Imaging System Using Microwave Antenna. Metamaterial Antennas Improve The Performance Of Miniaturized Antenna Systems With Efficient Power And Acceptable Bandwidth. One Among The Most Widely Investigated Detection Mechanism Is Using Microwave Imaging In The Field Of Medicine.
The need to employ reliable and reproducible species identifications in coralline algal research

Coralline algae perform important ecological roles in nearshore marine ecosystems globally by promoting the settlement of invertebrate larvae and enhancing biodiversity by creating habitat. However, these roles are severely threatened by global environmental changes. Most coralline algae are extremely difficult to identify, and DNA sequencing has revealed rampant inaccuracy of morpho-anatomical approaches to distinguish species, and even genera. If appropriate identification methods are not reported, or even used, we will be left with an uninterpretable body of literature where the species-specific biology of coralline algae cannot be validated. This will make it difficult to determine the impact a changing ocean may have on these ecologically important species. We reveal the magnitude of the issue in coralline algal research — both the identification methods used and the reporting of identification protocols. An analysis of 341 articles over the past decade revealed that only 7.6% used molecular methods, with over 70% not reporting any details of how species were identified. While many coralline algal taxonomists understand that the majority of species cannot be identified morphologically, this message has not disseminated to the ecological and physiological community. We provide a series of guidelines for conducting DNA-based identifications and strongly recommend the use of these methods over less informative morpho-anatomical techniques. Most importantly, the methods of identification should be adequately reported. Without following these guidelines, research on coralline algae runs the risk of collecting uninterpretable data, and conducting irreproducible science, slowing our ability to determine how these important species will respond to future ocean conditions.
Chemical Kinetic Study of Toluene Oxidation Under Premixed and Nonpremixed Conditions

A study was performed to elucidate the chemical-kinetic mechanism of combustion of toluene. A detailed chemical-kinetic mechanism for toluene was improved by adding a more accurate description of the phenyl + O{sub 2} reaction channels, toluene decomposition reactions and the benzyl + O reaction. Results of the chemical kinetic mechanism are compared with experimental data obtained from premixed and non-premixed systems. Under premixed conditions, predicted ignition delay times are compared with new experimental data obtained in shock tube. Also, calculated species concentration histories are compared to experimental flow reactor data from the literature. Under non-premixed conditions, critical conditions of extinction and autoignition were measured in strained laminar flows in the counterflow configuration. Numerical calculations are performed using the chemical-kinetic mechanism at conditions corresponding to those in the experiments. Critical conditions of extinction and autoignition are predicted and compared with the experimental data. Comparisons between the model predictions and experimental results of ignition delay times in shock tube, and extinction and autoignition in non-premixed systems show that the chemical-kinetic mechanism predicts that toluene/air is overall less reactive than observed in the experiments. For both premixed and non-premixed systems, sensitivity analysis was used to identify the reaction rate constants that control themore » overall rate of oxidation in each of the systems considered. Under shock tube conditions, the reactions that influence ignition delay time are H + O{sub 2} chain branching, the toluene decomposition reaction to give an H atom, and the toluene + H abstraction reaction. The reactions that influence autoignition in non-premixed systems involve the benzyl + HO{sub 2} reaction and the phenyl + O{sub 2} reaction. « less
IMPROVE SCHEDULING AND ENERGY EFFICIENCY OF WSN USING OPTIMAL CLUSTERSCHEME

Cluster heads nearby base station (BS) reduce their energy very rapidly in Multihop method, due to the large inter-cluster relay load, which causes the problem of the hot spot. Therefore, both energy capable with liability accepting be required for a clustering protocol. This paper provides an unpredictable and fault tolerant clustering with a TDMA process system known as PSO-UFC-TDMA dependent particle swarm optimization (PSO). Here, the network connection is restored in PSO-UFC protocol via the sudden failure of the MCH by selecting an additional CH called Surrogate Cluster Head. TDMA allocates timescales to save energy when transmitting data. The results of the simulation show that the PSO-UFC-TDMA approach extends the lifespan of the network against protocols like PSO-UFC, EBUC, PSO-C and LEACH-C.
Computational Geometric Tools for Modeling Inherent Variability in Animal Behavior

A fundamental challenge for behavioral neuroscientists is to represent inherent variability among animals accurately without compromising the ability to quantify differences between conditions. We developed two new methods that apply curve and shape alignment techniques to address this issue. As a proof-of-concept we applied these methods to compare normal or alarmed behavior in pairs of medaka (Oryzias latipes). The curve alignment method we call Behavioral Distortion Distance (BDD) revealed that alarmed fish display less predictable swimming over time, even if individuals incorporate the same action patterns like immobility, sudden changes in swimming trajectory, or changing their position in the water column. The Conformal Spatiotemporal Distance (CSD) technique on the other hand revealed that, in spite of the unpredictability, alarmed individuals share an overall swim pattern, possibly accounting for the widely held notion of “stereotypy” in alarm responses. More generally, we propose that these new applications of known computational geometric techniques are useful in combination to represent, compare, and quantify complex behaviors consisting of common action patterns that differ in duration, sequence, or frequency.
Development of liquid rhizobial inoculants and pre-inoculation of alfalfa seeds

Application of liquid microbial inoculants on legume seeds is a sustainable agricultural practice that can improve plant nutrient uptake and increase crop productivity. Inoculants should provide long-term survival of rhizobia in the final product and after application, to legume seeds. Ten different medium formulations of microbial inoculants were examined (yeast mannitol broth with the addition of agar, sodium-alginate, calcium chloride, glycerol or ferric chloride and combinations thereof) for the survival of the efficient nitrogen-fixing rhizobium, Sinorhizobium (Ensifer) meliloti L3Si strain. The most suitable liquid inoculant for survival of L3Si during a storage time of 150 days was the medium formulation containing glycerol in combination with agar or sodium-alginate. Alfalfa seeds were pre-inoculated with four formulations (yeast mannitol broth (YMB), YMB with agar (1 g L-1), YMB with 1 or 5 g L-1 sodium-alginate) for up to three months. Seeds pre-inoculated and stored for one month produced successful alfalfa plants. The nitrogen content in alfalfa obtained from pre-inoculated seeds one month before sowing was adequate and ranged from 3.72-4.19%. Using S. meliloti-based liquid inoculants for alfalfa and application of the pre-inoculation technique can increase the quality of alfalfa crops and reduce cultivation cost.
Anthropometric and physical performance profiles of Sabah youth netball players

Anthropometric and physical performance profiles of youth netball players have not been studied frequently. There have been limited studies focused on physical performances among youth netball players. Thus, this study aimed to evaluate the height, weight, body mass index (BMI), and physical performances of Sabah youth netball players by position. A total of ninety-one female netball players aged between 17 to 20 years old have participated in this study. Anthropometric (height, weight, and body mass index) and physical fitness performance (speed, agility, power, flexibility, and aerobic endurance) were collected. For anthropometric result showed that there was a significant difference between positions in height and weight (p.05). For physical fitness, the performance showed that there was no significant difference between the players’ positions in all fitness components (p>.05). These findings demonstrate that the height and body weight is different between positions in female netball players. This physical performance profiles may help coaches to improve athlete performance before a competition.
Epileptic Signal Classification Based on Synthetic Minority Oversampling and Blending Algorithm

The scalp electroencephalogram (EEG) has been extensively studied for epileptic signal classification in the past, but little attention has been paid to the data imbalance among different epileptic states. It is well known that, in general, the duration of seizure onset is less than several minutes or even shorter. This will result in an imbalance problem when comparing to the durations of the preictal and interictal states. In this article, a novel epileptic classification and seizure detection algorithm for imbalanced data is proposed. The wavelet packet decomposition (WPD)-based statistical features (SFs) of multichannel EEGs are first extracted for representation. Then, the $K$ -means synthetic minority oversampling technique ( $K$ -means SMOTE) is applied for data balancing. A blending algorithm that consists of random forests (RFs), extremely randomized trees (Extra-Trees), and gradient boosting decision trees (GBDTs) is finally adopted for feature learning and epileptic signal classification. The developed algorithm provides an average accuracy of 89.49% and 83.90% on the Children’s Hospital Boston (CHB)-MIT and iNeuro databases, respectively. For the patient-specific classification experiment on the iNeuro database, the proposed algorithm achieves the highest average accuracy of 92.68%.
Generation and analysis of driving scenario trajectories for safety verification of Autonomous Drive

Autonomous vehicles are often considered to be the future of transportation. However, many believe fully-autonomous vehicles are still far away from being realized. One of the main reasons is the lack of con dence from a safety level standpoint. While car manufacturers such as Volvo Cars have made great e orts to prove that developed algorithms are safe enough, it is just not feasible to test each new feature in the elds. Luckily, virtual environments address this issue by reproducing tra c situations scenarios. But even with virtual environments, a lot of data still has to be collected to cover the whole spectrum of possible scenarios. This can be addressed with simulated scenarios. Another approach that is investigated in this thesis is generating scenarios based on real ones. We considered two approaches: Recurrent Conditional Generative Adversarial Nets and a Recurrent Autoencoder with Generative Adversarial Nets. The latter also shows useful properties for scenario analysis. The second problem that we try to tackle in this thesis is the evaluation of our developed models.
Facilitating the Detection of ASD in Ultrasound Video using RHOOF and SVM

In the medical field various motion tracking techniques like block matching, optical flow, and histogram of oriented optical flow (HOOF) are being experimented for the abnormality detection. The information furnished by the existing techniques is inadequate for medical diagnosis. This technique has an inherent drawback, as the entire image is considered for motion vector calculation, increasing the time complexity. Also, the motion vectors of unwanted objects are getting accounted during abnormality detection, leading to misidentification / misdiagnosis. In this research, our main objective is to focus more on the region of abnormality by avoiding the unwanted motion vectors from the rest of the portion of the heart, allowing better time complexity. Proposed a region-based HOOF (RHOOF) for blood motion tracking and estimation; after experimentation, it is observed that RHOOF is four times faster than HOOF. The performance of supervised machine learning techniques was evaluated based on accuracy, precision, sensitivity, specificity, and area under the curve. In the medical field more importance is given to the sensitivity than accuracy. Support vector machine (SVM) has outperformed other technique on sensitivity and time complexity, hence chosen for abnormality classification in this work. An algorithm has been devised to use combination of RHOOF and SVM for the detection of atrial septal defect (ASD).
Effect of Imbrasia belina (Westwood) or Vigna subterranea (L) Verde or Tylosema esculentum (Burchell) Schreiber as protein sources in diets fed to Tswana hens on egg quality

A 90 days study was conducted to compare the effects of feeding Tswana hens reared under intensive system and fed diets formulated from Imbrasia belina (Westwood), Vigna subterranea (L) Verde and Tylosema esculentum (Burchell) Schreiber as sources of protein on egg quality. Four isonitrogenous and isocaloric diets were formulated by totally replacing soybean meal (SBM) with I. belina, V. subterranea and T. esculentum as protein sources while commercial layer diet was used as control diet. Twelve eggs from each pen were collected at 28, 33 and 38 weeks of age for egg quality analysis in a completely randomized design. Egg weight (EW), shell weight (SW), shell thickness (ST), shell index (SI), shell percentage (SP), egg surface area (ESA), egg volume (EV), egg contents (EC) and Haugh units (HU) were measured. Repeated measure analysis showed significant (P 0.05) of dietary treatments was observed on overall ST, SP and HU. The inclusion of I. belina and V. subterranea on layer diet had no adverse effects on egg quality while the totally replacement of SBM with T. esculentum as protein source impaired egg quality. These results, suggest that I. belina and V. subterranea could completely replace SBM as protein source in the layer diets without any detrimental effects on egg quality.
Comparison of UAV LiDAR and Digital Aerial Photogrammetry Point Clouds for Estimating Forest Structural Attributes in Subtropical Planted Forests

Estimating forest structural attributes of planted forests plays a key role in managing forest resources, monitoring carbon stocks, and mitigating climate change. High-resolution and low-cost remote-sensing data are increasingly available to measure three-dimensional (3D) canopy structure and model forest structural attributes. In this study, we compared two suites of point cloud metrics and the accuracies of predictive models of forest structural attributes using unmanned aerial vehicle (UAV) light detection and ranging (LiDAR) and digital aerial photogrammetry (DAP) data, in a subtropical coastal planted forest of East China. A comparison between UAV-LiDAR and UAV-DAP metrics was performed across plots among different tree species, heights, and stem densities. The results showed that a higher similarity between the UAV-LiDAR and UAV-DAP metrics appeared in the dawn redwood plots with greater height and lower stem density. The comparison between the UAV-LiDAR and DAP metrics showed that the metrics of the upper percentiles (r for dawn redwood = 0.95–0.96, poplar = 0.94–0.95) showed a stronger correlation than the lower percentiles (r = 0.92–0.93, 0.90–0.92), whereas the metrics of upper canopy return density (r = 0.21–0.24, 0.14–0.15) showed a weaker correlation than those of lower canopy return density (r = 0.32–0.68, 0.31–0.52). The Weibull α parameter indicated a higher correlation (r = 0.70–0.72) than that of the Weibull β parameter (r = 0.07–0.60) for both dawn redwood and poplar plots. The accuracies of UAV-LiDAR (adjusted (Adj)R2 = 0.58–0.91, relative root-mean-square error (rRMSE) = 9.03%–24.29%) predicted forest structural attributes were higher than UAV-DAP (Adj-R2 = 0.52–0.83, rRMSE = 12.20%–25.84%). In addition, by comparing the forest structural attributes between UAV-LiDAR and UAV-DAP predictive models, the greatest difference was found for volume (△Adj-R2 = 0.09, △rRMSE = 4.20%), whereas the lowest difference was for basal area (△Adj-R2 = 0.03, △rRMSE = 0.86%). This study proved that the UAV-DAP data are useful and comparable to LiDAR for forest inventory and sustainable forest management in planted forests, by providing accurate estimations of forest structural attributes.
Multiple pharmacological approaches on hydroalcoholic extracts from different parts of Cynoglossum creticum Mill. (Boraginaceae)

Abstract Cynoglossum creticum Mill (Boraginaceae) is used traditionally as a remedy to manage several human ailments. In this context, the present study aimed to perform multiple pharmacological investigations on the hydroalcoholic extracts prepared from Cynoglossum roots and aerial parts (leaves and flowers). We evaluated the antioxidant and enzyme inhibitory (against cholinesterases, α-glucosidase, α-amylase, lipase and tyrosinase) activity of the extracts. The protective effect(s) of the extracts on cardiomyocyte C2C12 and intestinal HCT116 cell lines challenged with hydrogen peroxide (H2O2) was studied. We found that the aerial parts harbored the highest amount of phenolic compounds. Generally, aerial parts showed significant antioxidant and enzyme inhibitory effects. Leaves exhibited the best lipase inhibitory activity (173.15 mgOE/g extract), followed by flowers and roots. The root and aerial extracts were equally able to blunt intracellular H2O2 induced reactive oxygen species production from both C2C12 and HCT116 cell lines. Both cells lines could be treated with scalar concentrations of root and flower extracts in the range 50–300 μg/mL without interferences on cell viability. In conclusion, the present study showed protective effects exerted by Cynoglossum extracts, which could serve as a foundation for the development of pharmaceuticals and nutraceuticals derived from Cynoglossum.
Variants of Golomb Coding and the n-ary Versions

Golomb coding is a type of entropy encoding scheme for geometric distributions. It consists of two parts, and both parts are coded with variable-length coding, which requires a higher computational effort than fixed-length coding schemes. To solve this issue, the first part of this article presents a variant of Golomb coding that uses fixed-length coding to code the first part. The simulations show that the proposed coding scheme has a higher throughput than Golomb coding, due to the reduction of arithmetic complexity. In the second part, we discuss the <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula>-ary versions of Golomb coding and the proposed coding scheme.
Caracterização estrutural in silico de proteinas recombinantes Neuraminidase-RFP

Segundo a Organizacao Mundial de Saude – OMS (2018), os virus Influenza causam infeccoes respiratorias que acometem entre 5 e 10% da populacao mundial, sendo um problema de saude publica. O virus Influenza A e pertencente a familia Orthomyxoviridae e apresenta em sua superficie a glicoproteina neuraminidase, que esta associada ao processo de infeccao pelo virus. Considerando a complexidade de suas estruturas, os virus influenza constituem uma interessante plataforma para a geracao de virus recombinantes para a expressao de proteinas heterologas. Dessa forma, o presente estudo buscou realizar a caracterizacao in silico de tres proteinas heterologas, que consistiam em diferentes porcoes da neuraminidase acopladas a RFP. Foi feita a analise das propriedades fisico-quimicas e estrutura 2D das mesmas. Tambem foi realizada a modelagem das estruturas 3D por threading . Os resultados demonstraram que a conservacao de diferentes porcoes da neuraminidase altera as propriedades fisico-quimicas da molecula tais como pI, indice de hidropatia e coeficiente de extincao. Esses parâmetros tambem influenciam os ângulos diedros, as sobreposicoes estereoquimicas e, consequentemente o enovelamento da proteina e sua superficie. Contudo, mais estudos envolvendo modelagem com minimizacao de energia e dinâmica molecular sao necessarios para a obtencao de modelos 3D de melhor qualidade. Alem disso, a validacao experimental desses achados e de suma importância para uma melhor compreensao do papel funcional das estruturas modeladas in silico .
A New Calculation Method of the Lightning Electromagnetic Field Considering Variable Return Stroke Velocity

The article proposes an improved method for the calculation of the electromagnetic field radiated by a lightning return stroke over a perfectly conducting ground. Specifically, the proposed time domain expressions allow a closed-form solution for the field produced by an impulse-current propagating upward along a vertical path with a given velocity. The expressions are valid for a wide class of engineering return stroke models and can be adopted also in case the return stroke velocity varies along the channel. The solution for an arbitrary current waveform can be obtained by the convolution of the current at the channel base with the electromagnetic field due to the impulse-current along the channel. The accuracy and advantages of the method are assessed by the comparison with those obtained by a finite-element method computer model. The expressions are implemented in the LIOV-EMTP-RV code for the calculation of the induced voltages in an overhead distribution line.