Miracle-dz/UniFAR-FTUs huggingface dataset:
Isolation, Morphological & Molecular Characterization of Aspergillus Species producing α-L-Rhamnosidase from Agro- Industrial Waste

An α-L-rhamnosidase enzyme [E.C. 3.2. 1.40] has potential application in food and pharmaceutical industry. Naringin is the dominant flavanoid bitter compound found in citrus fruit juices of the objective of present study was to isolate α-Lrhamnosidase producing fungus, study their morphological and molecular characteristics. A total twelve fungal strains were isolated from agro-industrial waste of lemon and sweet lemon peels for α-L-rhamnosidase enzyme production. Of these, only 4 isolates were capable of producing the α-L-rhamnosidase enzyme to hydrolyze naringin for removal of bitter taste from juices. Fungal isolates were selected according to their higher α-L-rhamnosidase enzyme activities (3.481 IU mL-1). For morphological studies, macroscopic features like colony colour, texture, elevation, growth and margins as well as microscopic characteristics such as the size of conidia and conidiophores, and their arrangements were examined for species differentiation. DNA was isolated from the best α-L-rhamnosidase producing fungal strain, and amplification of 18S rRNA gene, using specific primers ITS-1 and ITS-4 was done. This gene was subsequently sequenced and phylogenetic affiliations was accordingly assigned. Fungal isolate was identified as Aspergillus flavus.
APPLICATION OF ADDITIVE MANUFACTURING TECHNOLOGY FOR MANUFACTURING MEDICAL IMPLANTS: A REVIEW

With the advancement of technology every field of work is becoming more and more interrelated and inter-dependant. So the fields of CAD/CAM and healthcare are no exception to this. As it is said that human body is a machine, with every passing day, its wear and tear takes place and also due to some trauma/accidents it is necessary to have certain bones/limbs to be replaced, or there can be birth defects. A large number and variety of medical implants, prostheses, and surgical instruments are required to reconstruct or correct lost, damaged, deformed, and degenerated limbs, tissues and teeth. So CAD/CAM can be effectively used for the above purpose in the field of Orthopedics (medical field dealing with bones, limbs etc), dentistry. Orthodontic and maxillofacial implants, as well as distraction osteogenesis devices are used for correcting facial and oral deformities. The range of implants extends to auricular, ocular, cardiovascular, spinal, pelvic, and various joints: shoulder, elbow, wrist, hip, knee, and ankle. In India, the number of knee and hip replacements alone is estimated to be around 40,000 per year, most of them using imported implants. The number is nearly doubling every year, owing to better awareness and increasing affordability. Implants and instruments need to be developed considering the target population of patients and the consulting surgeons. The implants may be standard (suitable for a large population), modular (to provide intra-operative flexibility), or customized (patient-specific). Anatomical measurements of the target group or individual are carried out establish the geometric requirements. Now with the help of new CAD/CAM technology it is very easier to model and manufacture the implants to very accurate shape, size & dimensions according to patient’s requirements. This paper explores the scope of additive manufacturing technology for manufacturing implants, work progress going on in this field, challenges, future scope. INTERNATIONAL JOURNAL OF MECHANICAL ENGINEERING AND
Metabolic Living

The popular narrative of "globesity" posits that the adoption of Western diets is intensifying obesity and diabetes in the Global South and that disordered metabolisms are the embodied consequence of globalization and excess. In Metabolic Living Harris Solomon recasts these narratives by examining how people in Mumbai, India, experience the porosity between food, fat, the body, and the city. Solomon contends that obesity and diabetes pose a problem of absorption between body and environment. Drawing on ethnographic fieldwork carried out in Mumbai's home kitchens, metabolic disorder clinics, food companies, markets, and social services, he details the absorption of everything from snack foods and mangoes to insulin, stress, and pollutants. As these substances pass between the city and the body and blur the two domains, the onset and treatment of metabolic illness raise questions about who has the power to decide what goes into bodies and when food means life. Evoking metabolism as a condition of contemporary urban life and a vital political analytic, Solomon illuminates the lived predicaments of obesity and diabetes, and reorients our understanding of chronic illness in India and beyond.
Distance based Attribute Reduction in Set-Valued Decision Tables

Rough set based attribute reduction is an important problem in pre-processing step in data mining. However, most rough set based attribute reduction methods perform on single-value decision tables. In this paper, we solve attribute reduction problems in set-valued decision tables. Our method uses the distance measure which constructed between a conditional attribute set and decision attribute. General Terms Rough set, decision table, set-valued decision table, attribute reduction.
Market by Hybrid Intellige Short Term Electricity Price Forecasting in a Competitive nt Approach

In this paper a hybrid intelligent methodology is presented for short term electricity price forecasting in a competitive deregulated market. This approach is based on a hybrid methodology which is following several algorithm of artificial neural network. In this artificial network two most common techniques are used for forecasting the price and minimizing the error. By combining these two techniques a hybrid approach came which shows excellent results of price forecasting in electricity industry. Data for half hour demand and price is being collected for one year along with this data temperature, humidity and fuel prices is also collected. With the help of MATLAB the data is used to forecast the electricity price. This forecasting is done with several algorithms and it is also done with different techniques and comparison is made between the algorithm and between the techniques.
PRODUCTION AND CHARACTERIZATION OF BIODIESEL FROM CHICKEN FEATHER

From waste to energy generation is considered as potential approach to resolve the challenges associated with waste management and energy crisis. Currently waste to energy contributes about 114.08 MW of power capacity, which is far less in compare to other renewable sources. The present article reports the experimental work on the comparative evaluation of two bio-feeds i.e. waste chicken feather and Ghee (Clarified butter) for biodiesel production. Parameters such as percentage yield, specific gravity, acid value, saponification value, peroxide value, melting point were evaluated for biodiesel obtained from both biofeeds i.e. Chicken feather and Clarified butter. Present study revealed that oil obtained from CF contained higher acid value (8.64 meq/g), saponification value (110.78), peroxide value (7.89 meq/kg) and melting point (37°C) than the Clarified butter. Similarly, free fatty acid such as Oleic acid, Lauric acid, Ricinoleic acid, Palmitic acid was also found higher in CF than CF. Significant reduction in acid value, peroxide value, melting point was observed in methyl ester obtained from selected bio-feeds. Free fatty acid composition of CF based methyl ester showed close value as obtained in commercial biodiesel; on the other hand present study suggested that CF could be a potential biodiesel feedstock if impurities and saponification number reduced during processing.
A Novel Approach to Driving Licence Test using Wireless Sensor Network

: For eliminating the process of illegal driver’s license we have innovated a unique approach for granting a license to who actually deserve. This approach can be implemented with the help of wireless sensor network (WSN) using Bayesian logic classification algorithm along with the help of multi sensor fusion based detection approach. In this approach global positioning system (GPS) is being used for the purpose of comparing test data through map management system. For communication purpose ZIGBEE is used as a gateway. The proposed system is the elimination process of existing scenario to issue Indian driving license. For the test the applicant will be provided with a vehicle which is embedded with various sensors such as gyro sensor and RPM ( Revolutions per minute) sensor. Result analysis is done by comparing standard data with the applicants received data.
Performance Analysis of Optimal Scheduling Based Firefly algorithm in MIMO system

: In MIMO system, there are several number of users to communicate in a network. This may include signal noise and traffic in that network in channel usage. For channel allocation, there are several methods to predict available channel and to select optimal usage of channel to users. For this process, optimization algorithms like, PSO, ACO, etc. were used for selection of channel to the user for communication. In this process, there are many users communicate at a time which can combine these signal by multiplexing it and demultiplexing at receiving. But while during communication process this may effect in mixing of signals. This may add noise at receiver stage and may result in BER rate and due to mismatching of sender and receiver state, throughput will be reduced. To improve the performance level in MIMO communication system algorithm is proposed to implement optimization technique for selection of antenna according to communication parameters.Hence various scheduling technique to increase through-put parameter by allocating sleeping time to communicate source and destination enabling time implement are. In this technique, spectrum management is implemented to handle minimum delay for communicating source with destination. By using both configuration of optimization of antenna selection and scheduling technique, level of performance rate is improved. This will result in enhancing our communication performance. This proposal method can be compare with existing system for the parameters of transmission time, Bit error rate, Through-put, MMSE value, CIR and SNR
An Enhanced Query Processing Algorithm for Distributed Database Systems

— The growth of the web and the unlimited use of database management systems have brought to the forefront and integrated interconnection of diverse and large numbers of information sources known as distributed databases. The major problem in such an environment is the time taken to responds to query and the cost of transmission across the distributed site. This paper aimed at developing an enhanced query processing algorithm for distributed database systems, the proposed architecture and algorithm, uses the Iterative Dichotomizer 3 (ID3) as query optimizer that forms a decision tree, which decides the rules, patterns and the best execution plan to execute query at the barest minimum time. The applications of this work in organization, will automate the administration of operations, by providing user interactive platform for all stations to make queries and update their records. The object oriented analysis and design methodology was used in the study and the application was developed using MySQL, PHP and XAMP sever. The result shows that due to train dataset in the design of the database, the execution time of the algorithm in search, updating and querying of databases information in distributed sites, was less when compare to system search engine running time.
Exploration of Traumatic brain-inflammatory alterations in Alzheimer?s disease pateint

Since the expansive affiliation concentrates on in Alzheimer's illness have highlighted inflammation as a driver of the sickness as opposed to a result of the progressing neurodegeneration, various studies have been performed to recognize particular safe profiles connected with solid, maturing, or sick cerebrum. In any case, these studies have been performed basically in vitro or creature models, which reiterate just a few parts of the pathophysiology of human Alzheimer's illness. In this survey, we examine the accessibility of human after post-mortem tissue through cerebrum banks, the confinements connected with its utilization, the specialized instruments accessible, and the neuroimmune angles to investigate to accept in the human mind the test perceptions emerging from animal models.
Software Defined Network for Qos Enhancement in Mobile Wi-Fi Network

Wi-FI has become one of the dominant technology for direct access to the Internet due to its expanded services offering, its simplicity and its high-bandwidth provisioning that gives a capacity to support high traffic. Software-defined network (SDN) architecture simplified network management through an automatically programmed network. It provides a separation between the control plan (Controller) and the data plan (Switch) functions of the networks, this allows network optimization and fast response to network changes without the need to manually reconfigure existing infrastructure or purchase new hardware. In this paper, we have proceeded by studying the exchanges during a mobility within a WI-FI-based SDN network, then a network performance evaluation has been performed in order to analyze the impact of introducing the SDN concept on the performance of a mobile Wi-Fi network. For all proposed scenarios, we notice that the Wi-Fi-Based SDN architecture gives better results than in the case of the traditional Wi-Fi network.
SELF-CURE ACRYLIC RESIN SUSPECTED AS A CAUSATIVE AGENT FOR MANDIBULAR INTRA-OSSEOUS CARCINOMA: A CASE REPORT

1 Professor, Department of Oral Pathology and Microbiology, D.J.College of Dental Sciences and Research, Ajit Mahal, Niwari Road, Modinagar 201204, Ghaziabad, Uttar Pradesh, India. 2 Senior Lecturer, Department of Oral Pathology and Microbiology, 4 Reader, Department of Prosthodontics, Genesis Institute of Dental Sciences and Research, Ferozepur, India. 3 Reader, Department of Oral Pathology and Microbiology, ITS Dental College, Greater Noida, India.
Salient Motion Detection in a Video Signals

: In a video signals the detection of salient motion involves determining which motion is attended or presented by the human visual system in presence of complex background motion that are constantly changing. When the video sequence is represented as a linear dynamical system, then the salient motion detection is achieved from the output pixel. Salient motion is detected by comparing predictability to the more complex unpredictable background motion. The pixel saliency map is supported by two region based saliency map. It consists of different spatiotemporal patches in a video with the salient region in a global as well as local scene.
Statistical Assessment of New Coordinated Design of PSSs and SVC via Hybrid Algorithm

647  Abstract— The assessment of new coordinated design of Power System Stabilizers (PSSs) and Static Var Compensator (SVC) in a multimachine power system via statistical method is proposed in this paper. The coordinated design problem of PSSs and SVC over a wide range of loading conditions is formulated as an optimization problem. The Bacterial Swarming Optimization (BSO), which synergistically couples the Bacterial Foraging (BF) with the Particle Swarm Optimization (PSO), is employed to search for optimal controllers parameters. By minimizing the proposed objective function, in which the speed deviations between generators are involved; stability performance of the system is improved. To compare the capability of PSS and SVC, both are designed independently, and then in a coordinated manner. Simultaneous tuning of the BSO based coordinated controller gives robust damping performance over wide range of operating conditions and large disturbance in compare to optimized PSS controller based on BSO (BSOPSS) and optimized SVC controller based on BSO (BSOSVC). Moreover, a statistical T test is performed to ensure the effectiveness of coordinated controller versus uncoordinated one.
SECTUBIM: Automatic Segmentation And Classification of Tumeric Brain MRI Images using FHS (FCM, HWT and SVM)

: Abnormal development in any form fluid-fill or solid form of the tissue is termed as tumor. Gliomas are the Brain Tumors that are categorized into Malignant and Benign tumors. Benign tumors are less harmful than the Malignant tumor as benign are not having the capability of spreading by its own to other parts of the body. Whereas on the other hand Malignant tumors are cancerous tumors and are suspected to grow unconditionally. Gliomas are of two grades Low Grade Gliomas (LGG) and High Grade Gliomas (HGG). HGG are more harmful and destructive then LGG. Four stages are there to detect the tumor namely pre-processing, feature extraction, segmentation and classification. The proposed algorithm is combination make use of the FCM clustering and SVM classifier for classification of the tumor along with BCFCM for bias field correction and HAAR wavelet transform for feature extraction.
Adaptive Spatial Prediction For Lifting Scheme in Image Adaptive Spatial Prediction For Lifting Scheme in Image Adaptive Spatial Prediction For Lifting Scheme in Image Adaptive Spatial Prediction For Lifting Scheme in Image Compression Compression Compression Compression

Summary Wavelet transform has demonstrated excellent compression performance with Natural images. However the performance suffers in the neighborhood of oriented edges. Under these conditions the Lifting –style implementation of wavelets are widely used in image coders. The framework of lifting offers the flexibility for developing adaptive wavelet transforms. In this paper adaptive prediction techniques based on the local properties of the image are proposed. This adaptive lifting transform appears promising for image compression .
BUILDING NAMED ENTITY RECOGNITION AND CLASSIFICATION SYSTEM FOR RESOURCE POOR LANGUAGES USING PARALLEL CORPUS: ENGLISH-URDU AS CASE STUDY

: In this pape,r we propose an Urdu Named Entity Recognition and Classification (NERC) system and annotate an untagged Urdu corpus using alignment mapping technique given English-Urdu parallel corpus. First four probable alignments have been considered which produce accuracies of 57%, 18%, 7% and 4% respectively.
Psychosocial beliefs, physical activity and quality of life among shanghai teachers

Understanding psychosocial factors that influence physical activity and quality of life in working teachers may have important implications for future interventions aimed at improving their health. Participants were 238 working teachers (Mage=51.6±5.6) living in Shanghai, China. They completed previously validated questionnaires assessing their perceptions of stress, social support, self-efficacy, physical activity, and quality of life. The results suggest lower stress, higher social support, and more physical activity may directly increase quality of life. The mediating roles of self-efficacy and PA should be taken into account in managing stress and social support in order to promote quality of life among Shanghai teachers.
A Survey on Neural Network based Automatic Segmentation of Brain Magnetic Resonance Images

Medical Images are used as an important tool for determination of Pathological condition of the vital organs of the body like brain, lungs, liver, etc. Segmentation is the first step towards automatic processing for analysis and evaluation of medical images. Especially, image segmentation is a prerequisite process for image content understanding in brain MRI for the development of a computer aided diagnosis (CAD) system. It is a technique, which partitions an image into units, which are homogeneous with respect to one or more characteristics. Automatic Segmentation of brain MRI is used as a diagnostic tool in neuro medicine. Abnormal growth of brain tissues can be detected with the help of segmentation techniques. Changes in volumetric growth of brain tissues such as White Matter (WM), Gray Matter (GM) and Cerebrospinal fluid (CSF) can help in the early detection of neural disorders like epilepsy Alzheimer’s disease, parenchymal bleeds, etc. Even though several automated methods are available for segmentation of Brain MRI, there is no clear differentiation between these techniques about the suitability for various neural disorders. We presented a review of the methods used in brain segmentation. The review covers imaging techniques, magnetic resonance imaging and methods for segmentation and how a known Neural Network with fixed structure and training procedure could be applied to resolve medical imaging problem pertaining to Brain image segmentation.
Thresholded and Morphological Operations Based Brain Image Segmentation

— Skull Stripping is an inevitable computer-assisted medical brain mage pre-processing mechanism thataims to segregate the non-designated regions, in order to extract the designated brain regions. Those resultant brain region images arefurther subjected to diagnostic analysis to discover the brain diseases/ disorders. This paper presents an efficient method named, Threshold and Morphological Operations based Segmentation, (TMOS) for skull stripping is, exclusively designed for MRI brain images (Magnetic Resonance Images). It has two phases: the first phase localizes the brain region using Region of Interest (RoI) and in the second phase, morphological operations are applied to precisely extract the brain region by stripping out the skull. The performance of TMOS is validated using Minimal Interval Resonance Image in Alzheimer Disease (MIRIAD) dataset. The accuracy of TMOS is visually confirmed.
The Efficacy of Mannitol Therapy in the Management of Moderate and Severe Forms of Ovarian Hyperstimulation Syndrome: A New Application

Background & Aims: Ovarian hyperstimulation syndrome-(OHSS) is an important complication of ART. Based on the disease pathophysiology and the mechanism of the effects of the drug, we selected “Mannitol” as an alternative for “Albumin”. This study was designed to evaluate the efficacy of mannitol therapy in OHSS management. Materials & methods: This interventional non-experimental study was conducted on patients with moderate-severe OHSS over a period of 19 years (1994-2013). All patients at risk for OHSS received a preventive dose of mannitol. If the patients developed signs of moderate/severe OHSS, they entered the study based on the Rizk-Aboulghar classification. Mannitol therapy was started daily or twice a day (adjusted between 1-1.5 g/kg/dose). Patients were monitored according to the standard protocols. Results: Of 6970 women who entered the ovarian stimulation protocol for IVF, 1737 developed OHSS (24.92%), which was mild in 1360 (78.30%), moderate in 339 (19.46%), and severe in 39 (2.24%) patients. Weight loss (P=0.024), the correction of mean intake/output balance (P=0.009) after mannitol therapy, the decrease in the mean duration of hospitalization to 4.72±2.92 days, and the 0.0% mortality rate were the major outcomes. Conclusion: The results of this study showed the efficacy of mannitol therapy on controlling the signs and symptoms of OHSS.