Miracle-dz/UniFAR-FTUs huggingface dataset:
RECENT TRENDS IN NEMATODE MANAGEMENT PRACTICES: THE INDIAN CONTEXT

Human existence has depended heavily on the ability of plants to harness energy from sunlight and fix it into carbohydrates and to produce oxygen and organic matter. Today, agriculture is a global business and a necessity for the fulfillment of human needs of food, fiber, medicines and drugs, drinks etc. Plants dominate our lives and economy, just as they have in all civilizations. Humankind is not alone in need of plants for survival, microbes do exist which derive their nutrition from plants, either as saprophytes or as parasites. Plants are in a continuous battle to defend themselves from these pathogens and understanding these responses will ensure good agricultural outcomes. Of these pathogens, nematodes are emerging as a serious concern in agriculture, horticulture and forestry. Nematodes pose a serious threat to the production of economically important crops, vegetables and, a lesser extend to some tree species also. Some estimates suggest they cause 77 billion dollars of damage worldwide each year. In order to banish this limiting factor in agricultural production, it is essential to accurately identify the nematode infestation and to understand their biology. Although nematicides have emerged as an effective and economically feasible tool against nematode infestation in plants, but they have also raised environmental, resistance development and health concerns during the last decade. A gradual shift of interest towards developing more sustainable methods for nematode management has been noted in recent years. Current work summarizes the recently developed approaches for the control of nematode populations through genetic manipulations of host plants, design of cropping systems, integrated pest management, development of naturally occurring nematicides and employing biological control methods. Since these alternatives are more target specific and of biological origins, they will better respect the diversity and environment and hence, priorities must be urgently established for research and development in field of applied nematology.
Synthesis of Hydroxyapatite nanorods as heavy metal adsorbent via L-Arginine assisted ultrasonicated route

Hydroxyapatite, Ca10 (PO4)6(OH)2, a main inorganic component of bone material is widely used in various biomedical applications due to its excellent bioactivity and biocompatibility. It has been established that the existence of biomolecules like peptides or amino acids during the synthesis of bone affects the biomineralization process differently in “in vitro” systems. In order to comprehend the role of a given amino acid on the morphology of the Hydroxyapatite formed, L-arginine assisted synthesis of hydroxyapatite by ultrasound irradiation has been attempted and comparison has been made with that of chemical precipitation technique. The samples prepared were characterized by various techniques such as FT-IR, XRD, and FE-SEM. XRD peaks were attributed to the stoichiometric hydroxyapatite and no other calcium phosphate peaks were detected. Formation of apatite in both the cases was confirmed by the observed fundamental vibrational modes of the phosphate and hydroxide peaks . FE-SEM images indicate that hydroxyapatite synthesis using L-arginine by ultra sound irradiation technique reduced the agglomeration apart from enhancing the c-axis growth of the crystals. Heavy metal adsorption studies have been carried out using hydroxyapatite thus synthesized as an adsorbent and a suitable adsorption isotherm has been proposed.
Effectiveness of Dialectical Behavior Therapy (Distress Tolerance Skills, the Mindfulness and Regulation of Emotions) on the Self- esteem of high School Students

The purpose of this study was to investigate the efficacy of dialectical behavior therapy intervention, with the help of three skills of distress tolerance, the mindfulness, and regulation of emotion on the reduction of test anxiety symptoms among high school girls. This study was a quasi-experimental study with pretest and posttest and a control group. Among 412 high school girls out of five educational districts of Tabriz were sampled and 66 of them with high anxiety symptoms were put in two groups of experiment and control group (each group including 33). Eight sessions of group counseling based on dialectical behavior therapy (distress tolerance skills, mindfulness, regulation of emotions) were performed once a week for experiment group. Demographic characteristics questionnaires and test anxiety inventory (TAI) were used for data collection. Analysis of covariance using SPSS software was implemented to the results of experimental group and the control group for data analysis. The findings of the study showed that the intervention of dialectical behavior therapy (distress tolerance skills, mindfulness and regulation of emotions), was effective in reducing the level of test anxiety. According to the results, this study can be found useful in preventive programs, empowering youth and therapeutic interventions.
Dietary Patterns as a Predictive Factor for Overweight and Obesity Among Secondary School Children in Mashhad, Iran

This cross-sectional study was carried out to determine the prevalence of overweight and obesity among secondary school children in the city of Mashhad, Iran and its association with dietary patterns. A total of 1189 secondary school children (579 males and 610 females) aged 12- 14 years old were selected through a stratified multistage random sampling. All adolescents were measured for weight and height. Household socio-demographic information were self-reported by parents. Adolescents were classified as overweight or obese based on BMI-for age Z-score. Dietary patterns were assessed using a validated Iranian food frequency questionnaire (FFQ) included 121 food items. The principal component factor analysis (PCA) was applied to derive dietary patterns, and Logistic Regression (LR) was applied to examine the association between dietary pattern and adolescents BMI. The overall prevalence of overweight and obesity among the study population was 17.2% and 11.9%, respectively. The PCA analysis revealed the presence of two dietary patterns that were labeled as ‘Healthy dietary pattern’ (HP), and ‘Unhealthy dietary pattern’ (UP). LR analysis showed that HP was significantly associated with BMI (OR: 1.28, 95% CI: 1.124-1.47). Similarly, UP was significantly associated with BMI (OR: 0.861, 95% CI: .725-.968). In Iran, nutritional transition has taken place in the context of urbanization and has changed lifestyle, and dietary patterns. Policies must be formulated and circulated in the society to reach every family in the form of healthy dietary pattern.
A Comparative Survey on the Influence of Machine Learning Techniques on Intrusion Detection System (IDS)

--With the enormous growth of computer networks and content usage of users, there is a need for secure and reliable networks. As it is observed that the different types of network attacks are raised over a period of time, it is necessary to make the availability of effective automatic tools in order to identify the attack detection scenarios. Intrusion Detection System is one of the attack detection systems that detect intrusions coming from the Internet. Several approaches were observed in the literature for intrusion detection over the network. In the recent past, mining techniques were prevalent in order to check the intrusion detection. The characteristics of incoming intrusions were identified by using the mined knowledge over the data present in the network. Whenever a matching is found in the characteristics of the mined data then it is declared as an intrusion. Based on this criterion various intrusion detection models were developed in the recent research and the accuracy is improved. In this paper, a brief review is carried out over the earlier approaches. The complete approaches are divided into data preprocessing approaches and detection approaches. Further, the data preprocessing approaches are divided into Feature extraction and feature transformation models based on working methodology over the features. Similarly, the detection approaches are categorized as machine learning and evolutionary approaches. The complete details about the advantages and disadvantages of all the mentioned approaches are also described in this paper. A comparative analysis is also carried out between the approaches based on their working methodology.
Effects of Level and Type of Energy on the Plasma Lipid Components in Broiler Chickens

In a completely randomized design, 600 Cobb male broiler chicks were divided into five treatment groups and four replicates involve 30 chicks per each. The effect of level and source of energy on the blood components were measured at the day 28 of age. Chicks were assigned to receive five different types of rations. Dietary treatments were: T1) as control, main energy come from corn and it was according to the standard catalog of Cobb, T2) main energy come from corn and it was 3 percent energy less than the Cobb nutritional requirements, T3) main energy come from corn and it was 6 percent energy lesser than the Cobb nutritional requirements, T4) main energy satisfied according to standard catalogue of Cobb and come from corn and lipid source and T5) main energy come from corn and lipid source and it prepare 3 percent energy more than the Cobb nutrient requirements. There was no significant difference among treatments in very low-density lipoprotein cholesterol (VLDL), while the significant differences were observed in high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), albumin, cholesterol, triglyceride, total antioxidant and total protein content for all treatments (P<0.05). The lowest and highest amounts of total antioxidant were found in T1and T4, respectively. Minimum level of LDL was allocated to T1and T4, whereas the maximum belongs to T3. The lowest level of HDL was for T3and the most was for T1. The least amount of cholesterol related to T2, while the greatest amount belongs to T5. It was concluded that energy level and type can be effective on changing blood lipid metabolites such as cholesterol and triglyceride.
Performance Analysis of Computationally Efficient Model based Object Detection and Recognition Techniques

Object detection and recognition is one of the vital fields in Machine Learning and Computer Vision. Objects are of innumerable sizes and shapes. The pinnacle of success for any object recognition algorithm is to identify the object that is present in the image or a video sequence irrespective of any parameter like shape, size, color etc. This paper gives a detailed discussion of the computationally efficient object detection and recognition techniques such as Scale Invariant Feature Transform, Speeded-Up Robust Features and Features from Accelerated Segment Test. One more technique, Oriented FAST and rotated BRIEF, is considered as a combination of FAST algorithm along with BRIEF that additionally boasts of properties such as Orientation and rotation invariance. Some techniques which are dedicated for particular type of object such as Haar cascade and Histogram of Oriented Gradients are also glanced briefly upon. The performance parameters accuracy and recognition time are taken into consideration.
Phase I study of SCH 900105 (SC), an anti-hepatocyte growth factor (HGF) monoclonal antibody (MAb), as a single agent and in combination with erlotinib (E) in patients (pts) with advanced solid tumors.

2525 Background: SC is a humanized anti-HGF IgG1 MAb with potent antitumor effects in vitro and in xenograft models. The HGF/c-Met pathway mediates cell proliferation, angiogenesis, survival, migration, and invasion. Preclinical studies indicate potent additivity when combined with EGFR inhibitors. Methods: A phase I study (3+3 design) evaluated the safety, tolerability, recommended phase II dose (RP2D), pharmacokinetics (PK), and pharmacodynamics (PD) of SC. Monotherapy SC was given IV over 30-60 min, at 2, 5, 10, or 20 mg/kg once every 2 weeks. At the RP2D of SC, E at a dose of 150 mg/d was evaluated. At RP2D, cohorts were expanded to a total of 12 pts. Results: 37 pts (15M/22F, median age 63, range 18-87, ECOG PS 0/1/2: 10/26/1) have been enrolled. 24 pts with monotherapy SC were treated at 2 (n=3), 5 (n=3), 10 (n=3), or 20 mg/kg (n=15). 13 pts received the combination of SC 20mg/kg and E 150 mg/d. Most common tumors were sarcoma (6), ovarian (4), mesothelioma (3), and GBM (3). There were no dose-limit.
AUTOMATIC MATERIAL IDENTIFICATION TECHNIQUE USING DIGITAL IMAGE PROCESSING

-The material identification and its classification is one of the important processes in the manufacturing industries. The prominent methods used for material identification are Microscopy and X-Ray Fluorescence. These two methods have several drawbacks. In Microscopy process preliminary preparation of the specimen is necessary whereas the X-Ray Fluorescence method requires an XRF gun which uses Fluorescence rays for individual atoms to determine the composition of the material and it is a time-consuming process. Both methods are costlier. In this paper we have presented new technique for material identification and its classification using digital image processing i.e. Automatic Material Identification Technique (AMIT). This technique is efficient in saving time and money, avoids practical errors, gives accurate result and it requires less human effort. It is also easy to carry and can be programmed as per our requirement. The MATLAB software is used for image processing and performing the experiment.
To Study the Data Mining Applications in Higher educational System

Data analysis plays an important role for decision support irrespective of type of industry like any manufacturing unit and educations system. There are many domains in which data mining techniques plays an important role. This paper proposes the use of data mining techniques to improve the efficiency of higher education institution. If data mining techniques such as clustering, decision tree and association are applied to higher education processes, it would help to improve students' performance, their life cycle management, selection of courses, to measure their retention rate and the grant fund management of an institution. This is an approach to examine the effect of using data mining techniques in higher education. Keywords: ERP; Decision Support; Data Warehousing; OLAP; Data Mining; Applications in Higher education.
Namibian nurses experience of patients adherence to the treatment plan : an empirical study of nurses work related to patients diagnosed with multi drug resistant Tuberculosis

Background: A low adherence is one of the reasons for the development of drug resistant Tuberculosis. One of the identified factors connected to adherence is the relations between health care personal and patient. Nurses all over the world daily work close to the patient supporting them to achieve a high adherence to their treatment plan. Still there is an underrepresentation in a scientific view of exploring and evaluating this preformed work.Aim: The aim of this study wad to explore how the Namibian nurses experienced adherence to treatment in patients diagnosed with multidrug-resistant tuberculosis. Method: A qualitative research technic was used to collect data. The interview questions were constructed in a semi-structure with partly opened questions. The data was analysed with Graneheim and Lundman (2004) analysis model.Result: Strategies that was used by the nurses to enable a high adherence was providing information, counselling and education to the patient together with a practical support of delegating DOTS and providing the patient with medicine. There was a divided opinion on how to communicate with the patient depending on the nurse fundamental view of adherence. A doctor centred view resulted in a one way communication by informing the patient. A patient centred view of adherence resulted in a two way communication when the nurse aimed to learn about the patient own point of views. Conclusion: To enable a high adherence there has to be a two way communication which demands high communicational skills from the nurse.
NN/BRT BASED MODEL FOR EVALUATING IMPACT OF TQM ON HIGHER TECHNICAL EDUCATION

The prime aim of this study is to propose a novel model for evaluating the impact of Total Quality Standard in the area of higher technical education system. The secondary purpose of the work is to analyze various models and then depict a new model based on neural network and bagged regression tree (NN/BTR) to analyze the data and model accomplished after training the network with extremely low computational cost. Based on theoretical considerations, a model is proposed associating the TQM parameters to the educational establishment and its performance factors. Investigative and Positive factor analyses empirically verified and validated the underlying dimensions of TQM and educational establishment for higher technical studies. The accomplished result is considered for minimized value of maximum average peak ratio (MAPR) in every iteration. The accomplished result shows better throughput and positive indication that if TQM is properly implemented with the proposed consideration, the educational establishment has better feasibility of redefining their quality for higher technical education. Keywords; Total Quality Management, Higher Technical Education, MAPR, Neural network, Bagged Regression Tree
Text Query Based Indexing For Efficient Video Retrieval Using Hashing

- In recent years, e-lecturing is becoming more and more popular. Different research organizations put their e-lectures over World Wide Web. With help of which students or researchers can have access to these lecture videos without any restrictions of time and space. As a result of which, video data over World Wide Web is increasing very rapidly. Thus retrieval and access of video from large video archives is nearly inefficient. Text in the e-lecture videos provide appropriate clue that can be used as search index for video retrieval. We have proposed more efficient technique of hashing for faster retrieval of query text in videos. For query text retrieval open source OCR package can be used. After storing extracted text from videos, we are using hashing technique over texts to generate hash codes. This secures the structural information of each video frame with its extracted text and this will take minimum time to search videos from large databases and retrieve videos faster. As a result, we can retrieve lecture videos efficiently from big video datasets.
Pregnancy associated Urinary Tract Infection: Prevalence and Screening

Urinary tract infections (UTI) are an important global health problem prevailing in all age groups. They are one of the commonest infective sequel during pregnancy & is of great importance due to the serious impact it has on the mother and the foetus. This study was taken up to determine the prevalence of UTI in pregnant women, to identify the common uropathogen causing UTI, comparison of various screening methods with bacteriological culture & to document the prevailing antibiogram pattern of the common uropathogens causing UTI. Materials and methods: The study involved 500 pregnant women attending the antenatal clinic of the Department of OBG at Mahatma Gandhi Medical College & Research Institute (MGMCRI), Pondicherry. A brief history( presenting illness, past history & personal history)was taken from the patient and 5ml urine sample was then collected under strict aseptic precautions, transported at the earliest to the Microbiology lab at MGMCRI for processing & identification. The sample was first subjected to a wet mount examination, a Dipstick testing: A10 REAGENT STRIPS, RAPHA(for detection of urinary leucocytes & detection of urinary nitrites) & urine culture on CLED agar & 5% sheep blood agar. Any growth if present was then identified by routine preliminary tests & biochemical tests. Antibiotic sensitivity testing was then done as per CLSI guidelines. Results & Discussion: Prevalence of UTI among pregnant women was 45 % (n=219), this high prevalence could be attributed to the low income state of the patient & anaemia. Higher prevalence of UTI in pregnancy of 44%(n=97/219)was observed in the age group of 2125yrs,this could be due to the high sexual activity or higher prevalence of anaemia among this group. Detection of urinary nitrite was positive in 172/219 cases positive by urine culture, accounting for 78.5%. This could be due to the variability in the kit manufacturer or the time delay in the appearance of nitrites in the urine giving false negatives. Urine culture remained the gold standard for diagnosis of UTI. In our study Enterococcus emerged as the third most common isolate, following E.coli and Klebsiella. This may be attributed to the ablution practices following defecation in women.Gram negative bacilli showed increased sensitivity to Amikacin, Nitrofurantoin & Imipenem.Gram positive cocci showed 60% sensitivity to Amoxyclav, Gentamicin, Tetracycline, Linezolid & Teicoplanin and 80% sensitivity to Vancomycin. However, on account of teratogenicity of Amikacin, Nitrofurantoin may be a better alternative. K e y w o r d s
Empirical Evaluation of Software Component

Many information-based legacy systems contain similar or even identical things, which are developed from scratch again and again. From the scratch, development is more expensive and can take a long time to complete. Critical applications with strict time limits may loose the market due to the delay in the development process. This has led to the evolution of a new approach, called component- based development (CBD), which uses the concept of reusability in the application development. Component-based development is the process of assembling existing software components in an application such that they satisfy a predefined functionality. Reduced development time, effort and cost are few merits of CBD. Component based development mainly involves the reuse of already developed components. The selection of best quality component is of prime concern for developing an overall quality product. The present paper presents an empirical evaluation of some software component metrics used for reusability.
Exposure Of Fake Reviews In Mass Media

: Today the main aim of everyone is to trust on the matter of social media such as feedback and also opinion upon the topic or product. Spammers compose a spam survey about product for liability that everyone takes off about products and services for `issue by researchers and number of studies state that there is a narrow difference between spammer and its features. Here recent investigation states a new method names as NET spam that uses spam importance for demonstrating review datasets as unmatched information network for designing, detecting, and classifying such networks. Spam types supports to acquire improved effects regarding dissimilar metrics on reviewed datasets. This result gives the ultimate outcome of Net spam for existing methods between 4 categories such as reviewed and user behaviour and linguistic type of features but under that features only first type gives better performance than other categories. The contribution work is when user search query it will display all top-k products as well as recommendation of the product.