Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effects of Sodium Chloride Stress on Proline Content and Morphological Characteristics in Wheat (Triticum aestivum L.)

Salinity is the most important abiotic stresses adversely affect the quality and quantity of crops, in which 20% of the world's irrigated agricultural lands are affected by salinity. Wheat is an oldest and the first crop used for bread making for human nutrition. To investigate the response of wheat root to NaCl stress, a susceptible, Arta, and resistance, Bam, wheat varieties were grown under both non-stress and stress conditions. Stress plants were exposed to 250 mM of NaCl based on a completely randomized design with four replications. After removing the roots from the soil and removing them from the shoot, the fresh and dry weight, length, volume, Numbers of main roots of each plant were recorded. Then the other roots were harvested and were immediately immersed in liquid nitrogen and stored at -80°C until used for proline measurement.
Overcoming Antibiotic Resistance in Hospitals

Understanding the mechanisms of antibiotic resistan ce is important in the development of strategies to olving the problem. Active efflux of drugs, alteration of target sites and enzymatic degradations are the str ategies by which pathogenic bacteria acquire or develop intrin sic resistance to antibiotics. Multi-drug resistanc e (MDR) pumps, capable of recognizing and expelling a varie ty of structurally unrelated compounds from the bac terial cell and conferring resistance to a wide range of a ntibiotics have since been characterized in many gr am positive and gram negative pathogens like Staphylococcus aur eus, Pseudomonas aeruginosa, Escherichia coli and, more recently, in mycobacteria. The ability of some chem ical compounds to modify the resistance phenotype i n bacteria by working synergistically with antibiotic s in vitro has since been observed. The search for such compounds which can be combined with antibiotics in the treatment of drug resistant infections may be an alternative to overcoming the problem of resistance i bacteria.
Local Octal Pattern: A Proficient Feature Extraction for Face Recognition

— This paper presents a novel and efficient face image representation based on Local Octal Pattern (LOP) texture features. The standard methods viz., the local binary pattern (LBP), the local ternary pattern (LTP) and the local tetra pattern (LTrP) are able to encode with a maximum of four distinct values about the relationship between the referenced pixel and its corresponding neighbors. The proposed method calculates the diagonal, horizontal and vertical directions of the pixels using first-order derivatives. Thereby, it encodes eight distinct values about the relationship between the referenced pixel and its neighbors. The performance of the proposed method is compared with the LBP, the LTP and the LTrP based on the results obtained in terms of average precision and average recall on PubFig image database.
Diagnosis of Periprosthetic Joint infection: from Novel Synovial Fluid Biomarkers to Identification of the Etiological Agent

Joint replacement surgery is a success story in orthopaedic surgery which brought clear clinical and economical benefits. As the prevalence of total joint arthroplasty continues to rise worldwide, the incidence of periprosthetic joint infection (PJI) is expected to increase [1]. Infection of the prosthesis is one of the most worrisome complications and has an overwhelming impact on patients and society. PJI is difficult to diagnose and treat as there remains no diagnostic ‘gold-standard’ method. A high index of suspicion is key due to the heterogeneous behaviour of the microorganisms involved and therefore the diverse clinical presentation [2]. Some of the patients submitted to an aseptic revision surgery might actually have PJI. Not every patient with a PJI meets the criteria of Musculoskeletal Infection Society (MSIS), which are the most used for diagnosing PJI and include 2 major and 5 minor criteria [3].
Report of a case of familial mediterranean fever with special emphasis on histopathologic characteristics

Infectious erysipelas is a common clinical diagnosis in daily practice that usually responds well to standard antibiotic treatment. In cases of non-responders to conventional anti-infective therapies, two things need to be done: antibiotic resistance must be ruled out and diagnosis has to be re-evaluated. Familial Mediterranean Fever (FMF) is the most common entity within the huge group of hereditary periodic fever syndromes. FMF is characterized by distinct clinical findings, especially the late clinical onset post-infancy and pathognomonic erysipelas-like eruptions. Against the background of autoinflammatory syndromes that may present with erysipelas-like eruptions, patient’s history has to be recorded very carefully and clinical and dermatopathologic findings have to be evaluated meticulously. Correspondence to: Cornelia S.L. Müller, MD, Saarland University Medical School, Department of Dermatology, D 66421 Homburg/Saar, Germany, Tel: 0049 6841-16 23814; Fax: 0049 6841-1613816; E-mail: cornelia.mueller@uks.eu
Adjacent Disc Degeneration In The Cervical Spine: Personal Data And A Critical Reappraisal Of The Literature

Objective: Anterior cervical discectomy with fusion (ACDF) is often performed. More recently, degeneration of the adjacent segment (ADD) has gained more attention, and it was thought to be related to an ACDF. Arthroplasty could prevent the occurrence of ADD. The often cited proof for the existence of newly formed ADD is critically reconsidered. , and especially its clinical relevance is questioned.Methods: Retrospectively, the data of 37 patients who were operated on between 1998 and 2002 were retrieved. Re-surgeries after ACDF with stand alone cages were noted. An independent investigator contacted the patients and asked previously determined questions. The literature was also reviewed, and articles frequently cited in the discussion about ADD are critically reviewed.Results: Thirty-four patients participated. The mean follow-up was 9.6 ± 1.2 years. At the last follow up, 74% of the patients had a good to excellent result, 24% a moderate result, and 2% a fair result. Six patients underwent a new surgery after the index surgery of whom only one due to a clinical symptomatic new ADD. The annual rate of ADD was 0.32 %. The number of articles dealing with ADD were strongly correlated with those about arthroplasty. Revision of the available data resulted in a lower annual rate that resembled the rate of ADD after arthroplasty. Conclusion: Our personal data confirmed the estimation of the annual rate of ADD after CADF of less than 1%. In one study it resembled the annual rate after arthroplasty. The clinical relevance of ADD should seriously be questioned.
SECURE AND EFFECTIVE FILE SHARING ON CLOUD

Cloud computing is a system whereby data storage, applications and to some degree processing power are freed from local constraints and are available via servers or computers elsewhere in the world. The need for huge local drives is negated, those space-hogging office suites no longer sit on local machines and the option of an extra power boost when needed is within our reach. There are certain problems in Existing cloud computing which is impending the fast growth of cloud computing technology, among them few causes are Data security, Data confidential and Fine-Grained data access. In this paper, we present a way to implement scalable and fine-grained access control systems based on Key Policy attribute-based encryption (KP-ABE). For the purpose of secure access control in cloud computing, the prevention of illegal key sharing among colluding users is missing from the existing access control systems based on KP-ABE. This paper addresses this challenging open issue by defining and enforcing access policies based on data attributes and implementing user accountability by using Proxy re-encryption and Lazy Revocation. Furthermore, both the user grant and revocation are efficiently supported by using the Lazy re-vocation technique. Extensive analysis shows that the proposed scheme is highly efficient and provably secures under existing security models.
The Role of NAD+ in Anti-Aging Therapies

The aging process involves accumulation of DNA damage, mitochondrial defects, progressive tissue degeneration and atrophy, and the development of metabolic dysfunction and weakness. Aging is also accompanied by decreased levels of nicotinamide adenine dinucleotide (NAD+), which can result in cell damage and even shorter life spans. NAD+ acts as an enzyme cofactor in many essential biological pathways and is a substrate for several regulatory proteins. Many studies have suggested that the upregulation of NAD+ precursors can increase levels of NAD+ in tissues or cells to delay aging. Clinical trials have been conducted on the safety and efficacy of NAD+. Here we provide a review of NAD+ metabolism and its role in aging-related therapy.
PWM-Based Multilevel Cascaded Inverters Under Unbalanced DC Sources

This paper proposes pulse width modulation technique to get balanenced line to line out put voltage. in linearly modulation range maximize the modulation indeex ,linearly varying out put voltage occurs. In the cascaded multilevel inverter(MLCI) operating under unbalanced dc link the linear modulation is reduced caused to voltage imbalance as voltage references increses. In order to analyze these effects, the voltage vector space for MLCI is evaluated in detail. From this analysis, the theory behind the output voltage imbalance is explained, and the maximum linear modulation range considering an unbalanced dc-link condition is evaluated. After that, a neutral voltage modulation strategy is proposed to achieve output voltage balancing as well as to extend the linear modulation range up to the maximum reachable point in theory. In the proposed method, too large of a dc-link imbalance precludes the balancing simulations and the experiments for a seven-level phase-shifted modulated MLCI for electric vehicle traction motor drive show that the proposed method is able to balance line-to-line output voltages as well as to maximize the linear modulation range under the unbalanced dc-link conditions.
Antibacterial Activities of Syzygium aromaticum oil Against Local Clinical Pathogenic Bacteria

Eighteen bacterial isolates gram negative and gram positive were collected from King Fahd central hospital, Jazan region, Saudi Arabia. Four of these isolates belonging to Pseudomonas aeruginosa, three to Acintobacter baumanni and Klebsiella Pneumonia, two to Methicillin-resistant Staphylococcus aureus (MRSA) and E. coli, and one isolate to Enterobacter sp. , E. aerogenes, Staphylococcus capitis and S. epidermis. Bacterial isolates were isolated from different sources e.g., blood, swab, throat, trachea, urine, wound. The antimicrobial activity of four plant oils; cloves (Syzygium aromaticum), ginger (Zingiber officinale), camphor (Cinnamomum camphora), and cinnamon (Cinnamomum verum) were obtained from the local market were evaluated on twelve sensitive and resistant isolates of the collected bacteria. Clove oil showed highest antimicrobial potential on different bacterial isolates (MICs ranged from 0.3125 to 3.75 μg/ml). The antimicrobial activity of clove oil was evaluated alone or incombination with 10g Gentamycin or 5g Rifampicin, antibiotics on both gram-negative and gram-positive bacteria. Association of antibiotics and clove oil showed synergistic antibacterial activity against tested bacteria.
Image Denoising & Metric Parameters Improvement using Dictionary Learning and Sparse Coding

: Digital image processing uses efficient computer algorithms for image denoising and to improve the image quality. Noisy image is produced due to various reasons in image acquisition, compression, preprocessing, segmentation etc. Over the last decade, various methods have shown promising results in removing zero mean Gaussian noise from images. Apart from different strategies implemented for noise reduction; this paper proposes a method for reducing noise and to improve metric parameters. Without using pre-chosen set of basis functions to represent the image, this paper discuss about performing image denoising using dictionary learning and sparse representation. Instead of removing coefficients of noise, shrinking sparse coefficients of noise is implemented to eliminate noise and it retains the image quality
RNA in Semen and Sperm: Importance and Transcriptome Analysis in Buck. Vet Sci Res 2018, 3(2): 000158

Mammalian sperm contains an array of RNAs including messenger RNAs (mRNAs), ribosomal RNAs (rRNAs) and small RNAs (sRNAs), largely representing remnant transcripts produced during spermatogenesis. Increasing evidence has indicated that ncRNAs, which control gene expression at transcriptional, post-transcriptional, and epigenetic levels, play critical roles in male germ cell development. Sperm transcribe their RNA,RNAs have different role, high fertile buck have more RNA yield /spermatozoon vs low fertile buck, transcripts such as miR-34c, BMP2, TRADD influence semen quality
Studies on Thermal Behaviour of DOPO-functionalized Mullite Reinforced Epoxy Nanocomposites

The present work describes the development of epoxy composites reinforced with varying weight percentages of DOPO functionalized mullite fibre and DGEBA (diglycidyl ether of bisphenol-A) epoxy resin cured with diamino diphenyl methane (DDM). The synthesised mullite fibre was surface modified with 9,10dihydro-9-oxa-10 phosphaphenanthrene-10-oxide (DOPO). The introduction of DOPO functionality into mullite fibre has been confirmed by FT-IR and TGA analysis. The data obtained from the thermal studies, states that theDOPO modified mullite(DM) had a significant impact on the resultant epoxy nanocomposites when compared to that of neat epoxy matrix.
Discovering the Most Influential Human Action Using Web Based Classifier

-Vision-based human action recognition is the process of tagging image sequences with action labels. The identification of movement can be performed at various levels of abstraction. In existing system, after collecting an preliminary image set for each action by querying the Web, fit a logistic regression classifier to distinguish the foreground features of the correlated action from the background. In the action recognition process, PbHOG features can be used, which are more robust to the background clutter and variance of the domain. Using the initial classifier, incrementally collect more action images and, at the same time improve the model. Use nonnegative matrix factorization on this set to find the diverse pose clusters for that action and train separate local action classifiers for each cluster of poses. In proposed system it can be done by event monitoring to discover the most influential ordered pair for the human specific action. To this end, it make use of already annotated motion capture datasets and prepare action segmentation as a weakly supervised temporal clustering problem for an unknown number of clusters. Use the annotations to learn a distance metric for skeleton motion using relative comparisons in the form of samples of the same action are more similar than they are to a different action. The learned distance metric is then used to cluster the test sequences. To this end, we employ a hierarchical Dirichlet process that also estimates the number of clusters.
CARBONACEOUS PARTICULATE CONCENTRATION DURING INDOOR BURNING

Wood, crop residue, cow dung is a primary cooking fuel for a large majority of Indian households. Similarly, the fuming materials i.e. incense and mosquito coil are also widely used in indoor environments. Their incomplete combu stion generates particulate matter of a complex chemical composition with high potential environmental and health risks. There are an estimated 1.8 million deaths per year due to toxic EC and other indoor air pollutants. Therefore, carbonaceous particulate (EC and OC) in PM10 during burning of materials i.e. fuels (i.e. LPG (liquefied petrole um gas), kerosene, coal, cow dung, wood and crop residues), incense and mosquito coil in September, 2013 in typical indoor environments at Raipur, Chhattisgarh, India is measured in the present work. The EC concentration was found in t he following order: wood kerosene crop residues cow dung incense coal mosquito coil LPG; OC was in the following order: wood crop residues incense cow dung coal mosquito coil kerosene LPG. The highest OC concentration was observed in all tested materials except for ker osene and camphor, shows OC is a predominant contributor to t he total carbon. The highest total carbon was observed during wood burning, indicates the harmful impact to the women and children who spent more time in indoor environment i.e. kitchen. The incense and mosquito coil were also found a signifi cant contributor of carbonaceous particulates. The OC/EC ratios and contribution of SOC are discussed.
Model for Information Extraction and Information Retrieval Based on Cascaded Support Vector Machine and Feature Vector Optimization

Information extraction and optimization play vital role in semantic web mining. Semantic web mining process proceeds the better way information retrieval over the ocean of internet database. In this paper design model of information optimization using feature vector optimization. The feature vector optimization process reduces the relational key constraints for the categorization of information for retrieval. Relative information categorization increases the hit ratio of retrieving data. For the better categorization of relative information used cascaded support vector machine. The cascaded support vector machine is two stages multi-kernel-based classification process. The two-stage support vector machine reduces the semantic gap between the search query and internet database. The design model removes the bottleneck of relational constraints of the post mining process. The feature vector optimization is used to find optimal attribute for the label of the cascaded support vector machine. The labeled class of support vector machine map the domain ontology database.
Triple Bottom Line performance of reverse logistics: Graph Theory Approach

Reverse logistics has gained importance because of growing attention towards circular economy and environmental concerns. Reverse logistics is an important component of circular economy and makes a significant contribution to sustainability. However, literature review indicates that there are very few studies related to incorporating reverse logistics into the concept of sustainability. Also, the performance evaluation models are mostly traditional focusing on its economic performance. The article is aimed at developing a performance measurement model based on economic, environmental, and social sustainability, known as triple bottom line concept. The model utilizes Graph Theory Approach for developing the frame work of performance measure model. A case of mobile manufacturing firm is considered for the illustration of the model. The permanent function value of the matrix developed is referred as reverse logistics performance index. The findings of the study and RL performance index will help the firm in evaluating the reverse logistics performance from triple bottom line perspectives. The model will help academicians, and industry for evaluating, and benchmarking the RL performance.
Determinants of the Passengers' Light Rail Transit Usage in the Klang Valley Malaysia

The study aims to examine the determinants that motivate passengers to use the Light Rail Transit in The Klang Valley, Malaysia. The factors identified in the study were traffic reduction, advantage of LRT, and attitude. This study used a questionnaire to gather the survey data. The convenience sampling technique was utilised in the study. SmartPLS Version 3 was used to test the hypotheses. The results of the study showed that traffic reduction, advantages of LRT and attitude have a positive influence towards the LRT usage. These significant variables can be used as a guide for the LRT operators to increase the LRT usage. Future research is suggested to include other potential factors that could stimulate more LRT usage and for it to become the preferred mode choice for travelling amongst the users.
Testability Assessment of Object Oriented Software Using Internal & External Factor Model and Analytic Hierarchy Process

— In this paper we have proposed a new testability assessment model for object oriented software based on existing software testability models. The model is based on those six important internal programming features of object oriented design and six external quality factors which are not used before together at the same time in-spite of being highlighted in some or other research. These design features are assessed using popular static object oriented metrics and their link with testability is established indirectly through the affected quality factors. The model is further analysed using Multi Criteria Decision Making (MCDM) approach. The model is validated using Analytic Hierarchy Process (AHP). The proposed model and evaluation technique helps software engineering practitioners to choose the best alternative amongst available options by analysing the Testability not only at internal level but also at external quality level too.
Schedulability Analysis for Rate Monotonic Algorithm in Distributed Real-Time System

 Abstract: Real-Time Monotonic algorithm (RMA) is a widely used static priority scheduling algorithm. For application of RMA at various systems, it is essential to determine the system’s feasibility first. The various existing algorithms perform the analysis by reducing the scheduling points in a given task set. In this paper we develop a algorithm to compute the RMA schedulability in a distributed real-time system. In today’s world all the high performance computation are done in some form of distributed systems. We look at the limitations of parallel system and show how a distributed system can overcome it and also propose a distributed algorithm for the Schedulability analysis.
Distributive Reprogramming of Wireless Sensor Nodes with Secure Data Transmission

— Wireless sensor networks have found their applications in numerous industrial fields. This is because they assist humans by ceaseless monitoring of impossible areas by sending timely updates to the base station. Once these sensors are set up, it is highly impossible for humans to manually reprogram such devices and hence a reprogramming protocol is a necessity here. Such a reprogramming process needs to be done in an energy efficient way. This paper we propose Distributive Reprogramming of sensor nodes with secure Data Transmission where the nodes are categorized into good and bad nodes during the forwarding process of the reprogramming code. Also a random key generation and exchange is proposed and used between the nodes in this work to further improve security. Also the allocation of the Users in SDRP is a significant task as the failure of the User Node might cause the failure of the entire group of nodes under that particular User. Considering the energy of each wireless sensor node the allocation of the users can be done to enhance the overall energy efficiency of the SDRP without altering the multi-authorization of the network. It is an enhancement over Secure and Distributive reprogramming protocol and has been proved through network simulator simulations to show greater quality of service on Energy, Packet loss, Delay and throughput than the existing scheme .