Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of six novel microsatellite markers for the Chilean red alga Pyropia orbicularis

Mariculture of edible Porphyra/Pyropia species, which are cosmopolitan red foliose algae, represent an important source of income for the pharmaceutical and food industries. In Chile, the most common alga of this complex is Pyropia orbicularis (Bangiales, Rhodophyta). Here we report 6 microsatellite markers obtained from P. orbicularis through a genomic library from 10 individuals of the gametophytic phase by next generation (Illumina) sequencing. Polymorphism analyses were done from 10 individuals of the conchocelis phase, revealing an allelic diversity ranging from three to six alleles per locus, and observed heterozygosity (HO) and expected heterozygosity (HE) ranging from 0.200 to 0.995, and 0.250 to 0.610, respectively. A large proportion of genetic variance (61%) in P. orbicularis was among individuals within population, and 39% genetic variance was among populations. Nonetheless, these results should be interpreted with caution; further research using larger sample sizes is required. These polymorphic markers could be useful in future studies on population genetic structure, for conservation and applied purposes.
Assessment of an APP to measure lift velocity during bench press exercises : preliminary results

Introducción: Cada vez es más frecuente encontrar aplicaciones móviles relacionadas con el deporte de fácil acceso y uso. Sin embargo, su precisión general de medida tiene aún mucho margen de mejora. El objetivo de este estudio fue determinar la precisión de una Aplicación móvil (APP) Android y del acelerómetro del teléfono móvil, para medir la velocidad media de un levantamiento de Press Banca (PB). Material y método: Participaron en el estudio 5 sujetos (edad 23,8 ± 2,94 años), con una experiencia mínima de un año en el entrenamiento con resistencias en PB. Todos realizaron 3 repeticiones con un 70% y 90% del valor estimado de 1 Repetición Máxima (1RM). En cada repetición se midió y comparó la velocidad media simultáneamente con un Encoder lineal validado y la APP. Resultados: Observamos una correlación positiva fuerte de la velocidad media entre el Encoder lineal y la APP (r= 0,685, p<0.001, SEE=0,09 m • s−1). El coeficiente de correlación intraclase (ICC= 0,707) mostró un buen acuerdo entre ambos dispositivos. La APP mostró diferencias significativas en las velocidades medias de levantamientos del 90% 1RM (APP= 0,44±0,08 m • s−1; Encoder= 0,30 ± 0,03 m • s−1), no encontrando diferencias significativas en velocidades medias con cargas del 70% 1RM (APP= 0,54±0,13 m • s−1; Encoder= 0,51 ± 0,10 m • s−1). Discusión: La APP no es por el momento totalmente válida y fiable a bajas velocidades de ejecución. Sin embargo, con filtros de señal específicos puede llegar a ser una herramienta de medición suficientemente precisa, accesible, fácil de usar, y que permitirá estimar la velocidad de los levantamientos de forma cómoda y adecuada. Palabras clave: Acelerómetro. Teléfono móvil. Resistencias. Entrenamiento. Tecnología. Fuerza. APP. Test. Summary
Reproductive Incompatibility Between Univoltine Males and Multivoltine Females of the Plum Curculio

Multivoltine female plum curculios, Conotrachelus nenuphar (Herbst) (Coleoptera: Curculionidae), were mated with univoltine and multivoltine males. The fecundity and fertility resulting from each mating were correlated with histological changes in the spermatheca and sperm degeneration therein. Matings with univoltine males resulted in reduced oviposition and egg hatch. Reduction in oviposition was associated with early degeneration of spermatozoa in the spermathecae. Accelerated sperm degeneration subsequent to mating between strains was accompanied by a disruptive reaction in the spermathecal gland, suggesting a postmating isolating mechanism. The reaction also occurred with low frequency in females mated to multivoltine males.
INVESTIGATION ON DISTRIBUTION, ECOLOGICAL FEATURE AND MALARIA TRANSMISSION EFFECT OF ANOPHELES IN GUANGDONG PROVINCE

Objective To investigate the distribution, ecological feature and malaria transmission effect of Anopheles in Guangdong Province. Methods The investigation methods of mosquito vector and ecological feature were conducted in malaria epidemic regions in Guangdong Province. Results Anopheles anthropophagus was found in 12 Cities and Counties in Guangdong. It fed mainly on human and on cattle sometimes. The peak season of An. anthropophagus in nature was from September to October each year, which was in accordance with the malaria peak incidence. An. sinensis, An. minimus and An. cndoidiensis were found in most Cities and Counties in Guangdong respectively. They mainly fed on cattle and on human sometimes. The positive sporozoite with four species of Anopheles had been found widely. The positive sporozoite rate were by 0.35%-0.54% for An. anthropophagus , by 0.15%-0.93% for An. sinensis , 0.23%-5.94% for An. minimus and 0.05% for An. candidiensis respectively. Conclusion An. anthropophagus, An. sinensis, An. minimus and An. candidiensis were the malaria transmission vectors in Guangdong Province, but An. anthropophagus and An. minimus were the chief malarial vector in malaria epidemic regions, An. sinensis and An. candidiensis were the secondary vectors in malaria epidemic regions.
Provenance Framework for the Cloud Infrastructure: Why and How?

—Provenance is an important aspect in the veriﬁcation, audit trails, reproducibility, privacy and security, trust, and reliability in distributed computing, in-silico experiment and generally in e-science. On the other hand, Cloud computing is the business model of distributed computing and is considered the next generation of computing and storage platforms. Cloud computing requires an extension of the architecture of distributed and parallel systems by using virtualization techniques. Key to this extensible architecture is to support properties such as compute on-demand and pay-as-you-go model. Many research domains have already adopted Cloud paradigm into their existing computational and storage platforms and, thus, a shift of technology is in progress. In this paper, we give an overview of Cloud architecture and the importance of provenance in Cloud computing. We provide the mechanism for the collection of the provenance data while addressing the challenges offered by this new paradigm. These challenges include mainly the abstraction, high scalability and the inability to modify or extend the Cloud services. We provide a framework that requires minimal knowledge and understanding of underlying services and architecture of a Cloud. We assure trust by augmenting a Cloud infrastructure with provenance collection in a structured way. Then, we present the architectural overview of the provenance framework and the performance results of the extended architecture. The experimental results show that our provenance framework has a very low computation overhead (less than milliseconds), which makes it a good ﬁt for the Cloud infrastructure.
Eﬃcient constant-time hashing to elliptic curves y 2 = x 3 + b provided that b is a quadratic residue

Let F q be a ﬁnite ﬁeld and E b : y 20 = x 30 + b be an ordinary elliptic F q -curve of j -invariant 0 such that √ b ∈ F q . In particular, this condition is fulﬁlled for the curve BLS12-381 and for one of sextic twists of the curve BW6-761 (in both cases b = 4). These curves are very popular in pairing-based cryptography. The article provides an eﬃcient constant-time hashing h : F q → E b ( F q ) of an absolutely new type for which at worst #Im( h ) ≈ q/ 6. The main idea of our hashing consists in extracting in F q a cubic root instead of a square root as in the well known (universal) SWU hashing and in its simpliﬁed analogue. Besides, the new hashing can be implemented without quadratic and cubic residuosity tests (as well as without inversions) in F q . Thus in addition to the protection against timing attacks, h is much more eﬃcient than the SWU hashing, which generally requires to perform two quadratic residuosity tests in F q . For instance, in the case of BW6-761 this allows to avoid at least approximately 2 · 761 ≈ 1500 ﬁeld multiplications.
Examination of the causes of mortality in non-beak-trimmed pure line laying hens with special regard to aggression

The experiment was started with 1,508 Rhode Island Red (RIR) and 1,820 Rhode Island White (RIW) type non-beak-trimmed day-old pullets, which were originated from 58 RIR and 70 RIW different pedigree cocks, respectively. From all of the 128 cocks 26 half sibling offspring were tested. The pure line pullets were raised up to 18 weeks of age in a closed building, in deep litter pens and moved to the laying house and placed into three types of keeping systems [furnished cage, alternative pen (litter and floor) and conventional cage] thereafter. The number of dead birds and the cause of mortality were recorded daily during the whole rearing and egg-laying period, up to 72 weeks of age. During the rearing period the most frequent cause of mortality was wasting, which accounted for nearly 36% of the total mortality. Aggression was responsible for 28.3% of the total mortality. Depending on the type of the pullets (RIR or RIW), differences were observed in the frequency of occurrence of mortality causes. For example, oedema and beak deformation occurred only in the RIR, whereas technological injury and aggression only in the RIW pullets during the rearing period. During the egg-laying period aggression was the most common cause of mortality. Its lowest occurrence was observed in the alternative pens. In both of the examined types there were found cocks, whose offspring died exclusively by aggression, and cocks, whose offspring did not show any loss due to aggression. The ratio of these cocks differed significantly (P<0.05) between the two types examined. Based on the results it was established that the genetic background has significant effect on the mortality caused by aggression in non-beak-trimmed laying hens.
A comparative study of IE Techniques and their algorithms

— Information extraction from databases is a key research area and this area is familiar among the researcher. Data mining having great importance for the organization and it provides the reason to increase the profit of the organization. So data mining is an interesting field for the researcher. Many application are using to provide the facilities for data mining . hence data mining techniques are needed to determine the customer habits, according to business point of view, these techniques are used for the improvement in applications that provide the facilities for data mining, these applications may be internet online services and data where housing etc. These applications provide the new openings for the business and also increase its profit. Due to such demand this article is written on one information extraction technique clustering with its algorithm comparison and information extraction mechanism is presented.
Ship Trajectory Reconstruction from AIS Sensory Data via Data Quality Control and Prediction

Accurate ship trajectory plays an important role for maritime traffic control and management, and ship trajectory prediction with Automatic Identification System (AIS) data has attracted considerable research attentions in maritime traffic community. The raw AIS data may be contaminated by noises, which limits its usage in maritime traffic management applications in real world. To address the issue, we proposed an ensemble ship trajectory reconstruction framework combining data quality control procedure and prediction module. More specifically, the proposed framework implemented the data quality control procedure in three steps: trajectory separation, data denoising, and normalization. In greater detail, the data quality control procedure firstly identified outliers from the raw ship AIS data sample, which were further cleansed with the moving average model. Then, the denoised data were normalized into evenly distributed data series (in terms of time interval). After that, the proposed framework predicted ship trajectory with the artificial neural network. We verified the proposed model performance with two ship trajectories downloaded from public accessible AIS data base.
Systemic Absorption of Topical Tacrolimus in Metastatic Crohn Disease With Skin Ulcers

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A Review on Region of Interest Segmentation Based on Clustering Techniques for Breast Cancer Ultrasound Images

The most prevalent cancer amongst women is woman breast cancer. Ultrasound imaging is a widely employed method for identifying and diagnosing breast abnormalities. Computer-aided diagnosis technologies have lately been developed with ultrasound images to help radiologists enhance the accuracy of the diagnosis. This paper presents several ultrasound image segmentation techniques, mainly focus on eight clustering methods over the last 10 years, and it shows the advantages and disadvantages of these approaches. Breast ultrasound image segmentation is, therefore, still an accessible and challenging issue due to numerous ultrasound artifacts introduced in the imaging process, including high speckle noise, poor contrast, blurry edges, weak signal-to-noise ratio, and intensity inhomogeneity.
Toward Palmprint Recognition Methodology Based Machine Learning Techniques

The presented paper proposes an algorithm for palmprint recognition using seven different machine learning algorithms. First of all, we have proposed a region of interest (ROI) extraction methodology which is a two key points technique. Secondly, we have performed some image enhancement techniques such as edge detection and morphological operations in order to make the ROI image more suitable for the Hough transform. In addition, we have applied the Hough transform in order to extract all the possible principle lines on the ROI images. We have extracted the most salient morphological features of those lines; slope and length. Furthermore, we have applied the invariant moments algorithm in order to produce 7 appropriate hues of interest. Finally, after performing a complete hybrid feature vectors, we have applied different machine learning algorithms in order to recognize palmprints effectively. Recognition accuracy have been tested by calculating precision, sensitivity, specificity, accuracy, dice, Jaccard coefficients, correlation coefficients, and training time. Seven different supervised machine learning algorithms have been implemented and utilized. The effect of forming the proposed hybrid feature vectors between Hough transform and Invariant moment have been utilized and tested. Experimental results show that the feed forward neural network with back propagation has achieved about 99.99% recognition accuracy among all tested machine learning techniques.
Determination of bioactive constituents of Spondias mombin leaves by GC-MS analysis

The therapeutic capabilities of abundant herbal products have been known. However, further researches are required to properly screen, isolate and probably characterize their various active components. In this study, an attempt was made to identify the compounds present in the ethanol and n-hexane extracts of S. mombin leaves using gas chromatography and mass spectrometry (GC-MS) technique. Spondias mombin leaves were collected, air dried and pulverized into powdery form and extracted with ethanol and n-hexane at room temperature. The ethanol and n-hexane extracts of S. mombin leaves were analyzed by GC-MS. The GC-MS analysis of the ethanol extract of S. mombin leaves showed twenty-five (25) compounds, while twenty-nine (29) compounds were identified in n-hexane extract of S. mombin leaves. However, both extracts had ten compounds in common: n-Hexadecanoic acids, Phytol, Phenol 3-pentadecyl-, Phenol 3-methyl-, Phenol 2-methyl-, 2H-1-Benzopyran-6-ol, Gamma-Tocopherol, Vitamin E, Lup-20(29)-en-3-one and Stigmast-4-en-3-one. The percentage proportion of these compounds differed in each extract. In view of this, the possible biological properties of these identified compounds suggested that S. mombin might possibly be potential therapeutic agents.
Smart Firewall Using Machine Learning

— In today’s modern world no system currently available in the world is 100% secure. In addition, we always can notice that there are huge Attack scenarios. Generally, if a new signature is found on the database, then the behavior will be considered as an attack. Vulnerabilities in most computer systems and, it can be exploited by either non-authorized or authorized users. We propose fuzzy based prevention techniques. In which we have the advantage of automatic intrusion prevention system by having a trained data set of previous attack patterns. Having said that, several tools are being designed and implemented for a variety of exploitation in the diverse range of security attacks. Among these tools firewall is the one which allow us to monitor a range of computer systems: an information system, a network or a cloud computing. The objective of this-project is detecting the different types of attacks with varying parameters using predictive learning. In addition, we will include the attacks like XSS, DNS and Cookie poisoning are used by the attackers to exploit the client-based system, these types of attacks will be prevented using machine learning approaches.
2D inverse heat transfer measurements by IR thermography in hypersonic flows

The purpose of this work is to develop a data reduction technique for the measurement of heat fluxes in hypersonic flows. When dealing with inverse heat transfer problems in which temperature gradients in the solid are high enough (e.g. in case of temperature distributions due Gӧrtler vortices that can have high spatial frequency), tangential conduction is not negligible. The heat flux is estimated by solving a 2-D inverse heat transfer problem. The heat flux distribution is represented by discrete Fourier series, to reduce the computational cost.The data reduction technique has been numerically validated and then applied to experimental tests performed in an hypersonic wind tunnel at Mach number equal to 7.5 on a compression ramp where the instability is generated using a comb-like strip. The heat flux obtained solving the 2-D inverse heat transfer problem is compared with the one obtained solving the 1-D problem to evaluate the effect of the tangential conduction. Results show that the convective heat flux coefficient distribution obtained by the 2-D solution is higher than the one obtained from the 1-D case and that, using the two dimensional approach, a higher resolution of the result is obtained.
SMART CRITICAL PATH METHOD AS A MODIFIED DETAILED SCHEDULING TECHNIQUE

Now more Construction managers depends on scheduling tools based Critical Path Method (CPM) to can obtain total project duration plus activities’ float that leads to more efficiency for controlling and planning the studied construction projects. CPM was the best tool for construction projects time schedule but nowadays researchers were focused on drawbacks that loose its use as a decision making technique. This paper shows most of CPM drawbacks and discusses a modified tool for CPM model that is named Critical Path Segments (CPS). This CPS scheduling technique solves CPM drawbacks by three main ways: (1) Dividing duration of project activity into separated time segments; (2) All activities relationships were switched into sequential relation as finish to start and (3) Calculations and analysis were done by using forward path. Sample cases of studies were included to focus on CPM shortages and CPS detailed calculations and analysis were illustrated showing this CPS technique can handle the schedules by best way.
A Synthesis, Properties and Application as a Possible Drug Delivery Systems Dendrimers – A Review

Dendrimer is derived from the Greek word “dendron” which is used for tree and from the Greek suffix “mer” (segment) which describes the synthetic, three-dimensional molecules having branching parts. “A dendrimer is generally described as a macromolecule, which is characterized by its dendritic and hyper branched 3D structure that offers a high degree of surface functionality and versatility. ” Dendrimers possess three distinguishable architectural components i.e. an interior core, interior layer(generations) composed of repeating units radially attached to the interior core, and exterior (terminal functionality) attached to outermost interior generation (Fig. 1). The higher generation dendrimers, due to their globular structure, occupy a smaller hydrodynamic volume compared to the corresponding linear polymers. The dendritic structure is characterized by layer between each generation.Dendrimers are generally prepared using either a divergent method or a convergent one. There is a fundamental difference between these two construction concepts. Dendrimers shows the various properties such as structure, shape, aqueous solubility, non-polar solubility, &architecture. Dendrimer can be classification on the basis of their shape, structure, branching, solubility, chirality and attachment. Dendrimer can be differentiated on the basis of their shape, end functional groups and internal cavities.
Bergenia ciliata as antibacterial agent

The search for alternatives to combat antibiotics has been increased due to the upsurge in cases of antibiotic-resistant pathogens that has become a global phenomenon which threatens the human health. Medicinal plants provide multiple health benefits because these plants contain bioactive phytochemicals that are used in medicines as alternatives to various ailments of human beings. Bergenia ciliata is a perennial herb belongs to the family Saxifragaceae that consists of about 30 genera and 580 species worldwide. It has large, evergreen and leathery leaves with the pink to dark purple flowers and has various traditional and modern medical uses. This plant is considered is one of the most effective antibacterial agents. The present review emphasizes the antibacterial potential of Bergenia ciliata by compiling various researches and fragmented information. The most important phytochemicals derived from Bergenia ciliata launched on the pharmaceutical market are also discussed. This attempt will help the researchers to develop and synthesize new antibacterial drugs from Bergenia ciliata against drug-resistive pathogens.