Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Classification System for Medical Diagnosis using SVM

Classification is a data mining and machine learning task aimed at building a classifier using some training instances for predicting classes for new instances . Building effective classification systems is one of the central tasks of data mining. Support Vector Machines (SVMs) are among the most popular and successful classification algorithms The SVM approach to machine learning is known to have both theoretical and practical advantages. The accuracy of an SVM model is largely dependent on the selection of the model parameters such as C, Gamma and P. There are a number of parameters such as C , Degree and Gamma that apply to the SVM model and the selected kernel function. Kernel techniques have long been used in SVM to handle linearly inseparable problems by transforming data to a high dimensional space. Selecting the optimal values can significantly impact the accuracy of the model. This paper aims to establish an accurate SVM classification model for Medical prediction, in order to make full use of the invaluable information in clinical data, especially which is usually ignored by most of the existing methods when they aim for high prediction accuracies. This paper presents a comparison among the different SVM kernels with different parameters on the three medical data sets. The empirical results demonstrate the ability to use more generalized kernel functions and it goes to prove that the polynomial and RBF kernel’s performance is consistently improved with suitable parameters like degree and gamma. Experimental results show that kernel selection greatly improves the quality of classification.
Comparative vegetative anatomy and systematics of the angraecoids (Vandeae, Orchidaceae) with an emphasis on the leafless habit

The vegetative anatomy and morphology of 142 species of the angraecoid orchids (Angraecinae + Aerangidinae) and 18 species of Aeridinae were examined using light and scanning electron microscopy. Leafless members of Vandeae were of particular interest because of their unique growth habit. Leafy and leafless members of Angraecinae and Aerangidinae were examined and compared with specimens of Aeridinae. Vandeae were homogeneous in both leaf and root anatomy. A foliar hypodermis and fibre bundles were generally absent. Stegmata with spherical silica bodies were found associated with sclerenchyma and restricted to leaves in almost all specimens examined. Distinct inner tangential wall thickenings of the endovelamen occurred in several vandaceous genera. Exodermal proliferations and aeration units commonly occurred in both leafy and leafless Vandeae. Cladistic analyses of Angraecinae and Aerangidinae with members of Aeridinae and Polystachyinae as outgroups using 26 structural characters resulted in 20 000+ equally parsimonious trees. Vandeae formed the only well-supported clade in bootstrap analyses and were characterized by having a monopodial growth habit, spherical stegmata, loss of mucilage, and loss of tilosomes. © 2006 The Linnean Society of London, Botanical Journal of the Linnean Society, 2006, 151, 165–218.
Frequency of Dynamic Spectrum Using Cognitive Radio in Wireless Ad-Hoc Networks

—T he users may use cognitive radio frequency (CR) in wireless communication systems which senses the radio frequency for data and message communication. The modern investigate gives the issues related to spectrum utilization is a function of time and space calls for dynamic access strategies that adapt to the electromagnetic environment. The usage of free spectrum sharing between primary users (licensed) and secondary users, being license-exempted and has been incontestable within the recent experimental trails supported TV whitespace networks. The technique of dynamically accessing unused spectrum victimization Dynamic Spectrum Access (DSA) is gaining momentum. Many experimental trails on dynamic spectrum networks are being disbursed within the TV-band spectrum to check the technology and enact rules. During this work, a summary of psychological feature radio i.e. spectrum sensing, spectrum sharing, spectrum management and spectrum quality
Revision of the Planthopper Genus Tambinia (Hemiptera: Fulgoromorpha: Tropiduchidae) from China, with Description of a New Species

ABSTRACT All 6 species of the genus Tambinia Stål, 1859 in China are reviewed, including 1 new species, T. sinuata sp. nov. from Yunnan Province. Morphological descriptions, illustrations, molecular characteristics of the mitochondrial COI gene and an identification key for Chinese Tambinia species are provided. Pairwise distances, calculated by the Kimura-2-parameter model among the Tambinia species examined, ranged from 0.0306 to 0.1072. Type specimens are deposited in the Entomological Museum, Northwest A & F University, Yangling, Shaanxi Province, China (NWAFU).
Successful In vitro and In vivo Development of Cryopreserved Mouse Oocytes Fertilized by Cryopreserved Mouse Epididymal Spermatozoa

We substantially improved the cryosurvival rate of unfertilized mouse oocytes by em-ploying a pre-vitrification 2-step equilibration with sucrose (0.25 M and 0.5 M for 5 min each) at room temperature. As a result, 96.4% of the oocytes vitrified in a DPS-1 solution (2.75 M dimethylsulphoxide, 2.75 M propylene glycol, and 1.0 M sucrose) were recovered normally after warming, and 85.2% of the recovered oocytes were successfully fertilized by fresh spermatozoa. The in vitro developmental rate of these fertilized eggs into the blastocysts was 81.4% which was comparable to that (83.0%) of its solution control. Using this technique, we next examined the developmental rate of vitrified mouse oocytes that were fertilized by frozen mouse epididymal spermatozoa. Though the in vitro fertilization rate was relatively low (55.8%), the in vitro develop-ment of these fertilized eggs into the 2-cell stage was 93.5%, comparable to the solution control (95.6%). The in vivo developmental rate after transfer into recipient females was 54.2%, which was also comparable to the rate (57.8%) of eggs derived from fertilization between fresh oocytes and spermatozoa. We successfully demonstrated that fetal development is possible from cryopreserved oocytes and spermatozoa in mice.
Data-Driven Precursor Detection Algorithm for Terminal Airspace Operations

—The air traffic management system is one of the most complex man-made systems, with stringent standards for safety and operational performance. Modern surveillance systems make available detailed flight and airport information, through on-board and ground recording systems. These recorded datasets can be used for detecting and/or predicting anomalies which hinder safe and efficient operations. The prediction of an anomaly is performed by identifying events that precede the occurrence of an anomaly, which are called precursors. In this paper, we propose a detection algorithm that can identify precursors for flight anomalies through data-driven models designed with surveillance data recorded in the terminal airspace. The proposed algorithm is demonstrated to detect precursors of flight anomalies in the terminal airspace around LaGuardia (LGA) airport in New York City using real traffic data obtained from the Airport Surface Detection Equipment - Model X (ASDE-X) and the Terminal Automation Information Service (TAIS) surveillance datasets.
An End User Development Approach for Failure Handling in Goal-oriented Conversational Agents

This chapter introduces an end user development (EUD) approach for handling common types of failures encountered by goal-oriented conversational agents. We start with identifying three common sources of failures in human-agent conversations: unknown concepts , out-of-domain tasks and wrong fulﬁllment means or level of generalization in task execution . To handle these failures, it is useful to enable the end user to program the agent and to “teach” the agent what to do as a fallback strategy. Showing examples for this approach, we walk through our two integrated systems: S UGILITE and L IA . S UGILITE uses the programming by demonstration (PBD) technique, allowing the user to program the agent by demonstrating new tasks or new means for completing a task using the GUIs of third-party smart-phone apps, while L IA learns new tasks from verbal instructions, enabling the user to teach the agent through breaking down the procedure verbally. L IA also supports the user to verbally deﬁne unknown concepts used in the commands and adds those concepts into the agent’s ontology. Both S UGILITE and L IA can generalize what they have learned from the user across related entities and perform a task with new parameters in a different context.
Management of early blight (Alternaria solani) in tomato by integration of fungicides and cultural practices.

Tomato (Lycopersicon esculentum Mill.) is one of the most popular and widely grown vegetables in the world. By virtues of its many attributes, wider adoptability and versatility, tomato is considered as a favourite crop for research. Diseases are one of the most limiting factors for production of tomato. It reduces the quantity as well as market value of the product. Fungal pathogens are often more wide spread and cause substantial damages. Alternaria blight of tomato, popularly known as early blight is caused by a fungus, Alternaria solani (Ell. and Martin) Jones and Grout. It is common disease wherever tomatoes are grown and is one of the most destructive diseases causing significant qualitative and quantitative losses at any stage of plant growth including fruit and seed production. The pathogen is also responsible for causing storage losses during transit. Disease is favoured by warm temperature and extended periods of leaf wetness from dew, rainfall and crowded plantation. The plants are more susceptible to infection by the disease during fruiting period ABSTRACT
Centromere detection of human metaphase chromosome images using a candidate based method [version 1; peer review: 2 approved with reservations]

Accurate detection of the human metaphase chromosome centromere is a critical element of cytogenetic diagnostic techniques, including chromosome enumeration, karyotyping and radiation biodosimetry. Existing centromere detection methods tends to perform poorly in the presence of irregular boundaries, shape variations and premature sister chromatid separation. We present a centromere detection algorithm that uses a novel contour partitioning technique to generate centromere candidates followed by a machine learning approach to select the best candidate that enhances the detection accuracy. The contour partitioning technique evaluates various combinations of salient points along the chromosome boundary using a novel feature set and is able to identify telomere regions as well as detect and correct for sister chromatid separation. This partitioning is used to generate a set of centromere candidates which are then evaluated based on a second set of proposed features. The proposed algorithm outperforms previously published algorithms and is shown to do so with a larger set of chromosome images. A highlight of the proposed algorithm is the ability to rank this set of centromere candidates and create a centromere confidence metric which may be used in post-detection analysis.
Functional Diversity Changes after Selective Thinning in a Tropical Mountain Forest in Southern Ecuador

Background: The impact of selective thinning on forest diversity has been extensively studied in temperate and boreal regions. However, in the tropics, knowledge is still poor regarding the impacts of this silvicultural treatment on functional diversity, especially in tropical mountain forests, which are considered to be highly biodiverse ecosystems and also endangered by human activities. By evaluating the changes on functional diversity by using different indicators, hypothesizing that selective thinning significantly affects (directly or indirectly) tropical mountain forests, this work promotes sustainable ecosystem use. Methods: A total of 52 permanent plots of 2500 m2 each were installed in a primary mountain forest in the San Francisco Biological Reserve to assess the impact of this silvicultural treatment. Selective thinning can be defined as a controlled process, in which trees that compete with ecologically and/or valuable timber species are progressively removed to stimulate the development of profitable ones, called potential crop trees (PCT). In doing so, the best specimens remain in the forest stand until their final harvest. After PCT selection, 30 plots were chosen for the intervention, while 22 plots served as control plots. The thinning intensity fluctuated between 4 and 56 trees ha−1 (average 18.8 ± 12.1 stems ha−1). Functional Diversity (FD) indices, including the community weighted mean (CWM), were determined based on six traits using the FD package implemented in R software. The difference between initial and final conditions of functional richness (FRic), functional divergence (FDiv), functional evenness (FEve), functional dispersion (FDis), and Rao quadratic entropy (RaoQ) was modeled using linear mixed models (LMM). As fixed factors, we used all the predictors inherent to structural and ecological forest conditions before and after the selective thinning and as a random variable, we used the membership to nested sampling units. Results: Functional Richness (FRic) showed significant changes after selective thinning, the other indexes (FEve, FDis, FDiv, RaoQ) were only influenced by predictors related to ecological conditions and characteristics of the community.
Isolation and Partial Characterization of an Adhesin from Candida albicans

SUMMARY: Candida albicans produces extracellular polymeric material (EP) which contains a mannoprotein adhesin. EP isolated from culture supernatants of C. albicans GDH 2346 consisted of a mixture of glycoprotein components and inhibited yeast adhesion to buccal epithelial cells by up to 60%. Partial purification of the adhesin was achieved by a two-step procedure involving chromatography of EP on concanavalin A-Sepharose and DEAE-cellulose. The purified adhesin inhibited adhesion to buccal cells 30 times more efficiently (on a weight basis) than unfractionated EP. Pretreatment of EP with heat, dithiothreitol or proteolytic enzymes either partially or completely destroyed its ability to inhibit adhesion, whereas pretreatment with sodium periodate or α-mannosidase had little or no effect. These results suggest that the protein portion of the mannoprotein adhesin is more important than the carbohydrate moiety in mediating yeast attachment to buccal epithelial cells.
A System to Clarify Unwanted Messages from OSN User Surface

: Today Online Social Networks (OSNs) are one of the most wanted and popular social networks where users can share, exchange and communicate with the large amount of information to each other. One basic issue in these OSNs is to give users a protected private space from the undesirable and unwanted messages displayed. So the main goal of the present work is to propose and experimentally evaluate Filtered Wall (FW) which is an automated system can filter noisy messages from OSN user space. This is possible through a flexible rule-based system that allows users to customize the filtering options to be used to their surfaces and a Machine Learning (ML) depended soft classifier involuntarily labeling messages in support of content-based filtering.
From Genes to Behavior

■ Abstract Modulation of fast neurotransmission by monoamines is critically involved in numerous physiological functions and pathological conditions. Plasma membrane monoamine transporters provide one of the most efficient mechanisms controlling functional extracellular monoamine concentrations. These transporters for dopamine (DAT), serotonin (SERT), and norepinephrine (NET), which are expressed selectively on the corresponding neurons, are established targets of many psychostimulants, antidepressants, and neurotoxins. Recently, genetic animal models with targeted disruption of these transporters have become available. These mice have provided opportunities to investigate the functional importance of transporters in homeostatic control of monoaminergic transmission and to evaluate, in an in vivo model system, their roles in physiology and pathology. The use of these mice as test subjects has been helpful in resolving several important issues on specificity and mechanisms of action of certain pharmacological agents. In the present review, we summarize recent advances in understanding the physiology and pharmacology of monoamine transporters gained in mice with targeted genetic deletion of DAT, SERT, and NET.
Design and Simulation of a Pressure Sensor Based on Optical Waveguides for Applications in Hydraulic Fracturing

In this work is presented the design and simulation of a pressure sensor for a high range from 4MPa to 83MPa. The purpose is to use Mach-Zehnder Interferometer (MZI) and optical waveguides for applications where corrosion and high temperature levels (up to 120° Celsius) are present. The sensor is designed for down-hole applications like petroleum wells. Keywords-Pressure; sensor; interferometer; waveguide
Evaluating Nitrogen and Carbon Differences in Standing Litter from Normal and Prematurely Senesced Bromus tectorum Plants

Evaluating Nitrogen and Carbon Differences in Standing Litter from Normal and Prematurely Senesced Bromus Tectorum Plants Alexa Lunt Jensen Department of Plant and Wildlife Sciences, BYU Master of Science Bromus tectorum, an invasive winter annual, has displaced native vegetation throughout the western United States. Bromus tectorum litter influences nutrient cycling near the soil surface as well as plant establishment. Failed seed production of B. tectorum occasionally occurs in the field, with plants exhibiting weak flowering culms that turn straw-colored in spring when normal plants are green or purple in color. Because annual grasses transport most soluble carbon (C) and nitrogen (N) to reproductive organs, seed production failure results in significantly different fates for these nutrients compared with normal plants. As part of larger efforts to understand events leading to large-scale seedling emergence failure (termed die-offs), occasionally observed in near mono-cultures of B. tectorum, we here test the hypothesis that prematurely senesced litter associated with seed production failure has higher soluble C and N than normal litter. C and N concentrations of aboveground biomass were compared for normal and prematurely senesced B. tectorum plants. Two methods were used to cause premature senescence: fungal pathogen infection with Clarireedia capillus-albis and glyphosate herbicide application. In a related experiment, field sampling of normal and prematurely senesced plants under natural conditions was conducted to compare C and N levels in-situ. Herbicide-induced senescence resulted in 1.5 to 2 times greater soluble C concentrations, but fungal infection had no effect on soluble C under experiment conditions. Prematurely senesced litter had increased total N concentrations, resulting in lower C:N ratios. The C:N ratio for prematurely senesced plants (averaged across all studies) was 68:1, whereas mature normal plants averaged 243:1. These findings illustrate failed seed production associated with premature senescence results in B. tectorum litter with significantly higher N concentrations and can result in increased soluble C concentrations. Altered nutrient status may contribute to changes in soil microbial activity, including activity of soilborne pathogens found in die-offs.
ANOMALY DETECTION USING NETWORK TRAFFIC CHARACTERIZATION

ANOMALY DETECTION USING NETWORK TRAFFIC CHARACTERIZATION Detecting suspicious traffic and anomaly sources are a general tendency about approaching the traffic analyzing. Since the necessity of detecting anomalies, different approaches are developed with their software candidates. Either event based or signature based anomaly detection mechanism can be applied to analyze network traffic. Signature based approaches require the detected signatures of the past anomalies though event based approaches propose a more flexible approach that is defining application level abnormal anomalies is possible. Both approach focus on the implementing and defining abnormal traffic. The problem about anomaly is that there is not a common definition of anomaly for all protocols or malicious attacks. In this thesis it is aimed to define the non-malicious traffic and extract it, so that the rest is marked as suspicious traffic for further traffic. To achieve this approach, a method and its software application to identify IP sessions, based on statistical metrics of the packet flows are presented. An adaptive network flow knowledge-base is derived. The knowledge-base is constructed using calculated flows attributes. A method to define known traffic is displayed by using the derived flow attributes. By using the attributes, analyzed flow is categorized as a known application level protocol. It is also explained a mathematical model to analyze the undefined traffic to display network traffic anomalies. The mathematical model is based on principle component analysis which is applied on the origindestination pair flows. By using metric based traffic characterization and principle component analysis it is observed that network traffic can be analyzed and some anomalies can be detected.
OOV Words Extension for Modular Neural Acoustics-to-Word Model

: The direct Acoustic-to-Word (A2W) End-to-End (E2E) model leads to a truly E2E speech recognition system, which gets rid of lexicons or sub-word models. Nevertheless, one of the challenges hampers the wide application of A2W models is the out-of-vocabulary (OOV) or vocabulary expansion problem. This work tries to solve the OOV problem by extending the adaptability of A2W E2E models. We follow the modular training framework of E2E systems and decouple the A2W E2E model into an acoustics-to-phoneme (A2P) module and a phoneme-to-word (P2W) module before joint optimization. Benefit from the modularization, the OOV modeling techniques can be explicitly applied in the latter part. We utilized the extra text corpus for OOV data augmentation. Words are transcribed into phonemes by a pronunciation lexicon or grapheme-to-phoneme transducer (G2P). After that, the augmented OOV P2W data can be used to fine-tune the pre-trained modular system with the extended vocabulary. To alleviate the augmented data mismatch, several methods of data synthesis and model training are investigated and compared. The proposed method is applied in both CTC and attention-based encoder-decoder models and shows significant and consistent improvements in both Switchboard telephone and WSJ reading speech.
Improvement of Open-Pollinated Spring Rapeseed (Brassica napus L.) Through Introgression of Genetic Diversity from Winter Rapeseed

aBs TRacT ThewinterandspringtypesofoilseedBrassica napusL. � belongtodistinctlydifferentgenetic� groups. � Hence,� itshouldbepossibletouse� wintertypesfortheimprovementofspringtype� B. napus. � Weinvestigatedtheeffectofintro- gressionofallelesfromwintertypeintoopen- pollinatedCanadianspringB. napuscultivars. � CrossesweremadebetweentwoEuropean� winterrapeseedcultivars,� AvisoandTequila,� aCanadianspringdoubled-haploid� (DH)� line,� A03-3NR,� andtwoDHpopulationsdeveloped� fromF 2 �plants. �Atotalof�134�simplesequence� repeat� (SSR)� markersfrom� 19� linkagegroups� wereevaluatedonthethreeparents,� ofwhich� 84�markerswerepolymorphic. �Basedonthese� markers,�geneticsimilaritybetweenthetwowin- terparentswasestimatedtobe�0.49,�whereas� itwasonly�0.27�betweenthespringandthetwo� winterparents. � Thirty-sevenselectedpolymor- phicmarkersweretestedonthetwoDHpop- ulations,� whichdetectedatotalof� 94� alleles. � Occurrenceoftheallelesfromthewinterparent� rangedfrom�17.0�to�59.9%�inDHpopulationof� Aviso�×�A03-3NR,�whereasinthepopulationof� Tequila�×�A03-3NRitrangedfrom�13.8�to�50.0%. �