Miracle-dz/UniFAR-FTUs huggingface dataset:
Cybersecurity, Computer Networks Phishing, Malware, Ransomware, and Social Engineering Anti-Piracy Reviews

With the rapid development of technology, connection to the internet is an indispensable element of life. With the Covid-19 Pandemic outbreak, online education with a computer and tablet mobile phone has become mandatory due to the remote training. The security of these tools used for connectivity has become critical. In this process, online shopping from homes has increased considerably. Due to this use among users for the first time and due to fast service, security vulnerabilities expose users to a difficult situation and cyberbullying. The fact that the devices are on the internet as wired or wireless makes it inevitable that they are vulnerable. The exposure of such devices in your home to cyberattacks means a violation of your privacy, along with many of your personal data. Nowadays, even the fine details of such technologies are trying to steal personal data by using the need to believe, such as phone fraud or pandemic vaccines. It is becoming increasingly important to inform end users of internet technology and security weaknesses in this field and to create awareness. If these are increased, the number of people exposed to cyber attacks will decrease. The first method for this is to reach these people and education
A Modified Large Dynamic Weak DSSS Signal Acquisition Algorithm Based on DBZP

In order to solve the problem of fast acquisition of weak direct sequence spread spectrum (DSSS) signals under the condition of large dynamic, this paper proposes a modified DSSS signal acquisition algorithm based on the double block zero padding algorithm. The proposed algorithm realizes segmented Doppler search by frequency compensation of the baseband signal, then the code Doppler of partial correlation result is corrected by pre-compensating local pseudo-code and the Keystone transform. In addition, the computational cost of the algorithm is reduced by introducing the sparse fourier transform. Theoretical analysis and simulation results show that the proposed algorithm can effectively eliminate the influence of large dynamic on long-term accumulation of the weak DSSS signals. Compared with the representative algorithm, the proposed algorithm, which reduces the computational cost by 48.9% when the coherent accumulation time is 5ms, has higher computational efficiency.
Autonomous Mobile Robots: Refining the Computational Landscape

Within distributed computing, the study of distributed systems of identical mobile computational entities, called robots, operating in a Euclidean space is rather extensive. When a robot is activated, it executes a Look-Compute-Move cycle: it takes a snapshot of the environment (Look); with this input, it computes its destination (Compute); and then it moves towards that destination (Move). The choice of the times a robot is activated and how long its cycle lasts is made by a fair (but adversarial) scheduler; three schedulers are usually considered: fully synchronous (Fsync), semi-synchronous (Ssync), and asynchronous (Async). Extensive investigations have been carried out, under all those schedulers, within four models, corresponding to different levels of computational and communication powers of the robots: $\mathcal{O}\mathcal{B}\mathcal{L}\mathcal{O}\mathcal{T}$ (the weakest), $\mathcal{L}\mathcal{U}\mathcal{M}\mathcal{I}$ (the strongest), and two intermediate models $\mathcal{F}\mathcal{S}\mathcal{T}\mathcal{A}$ and $\mathcal{F}\mathcal{C}\mathcal{O}\mathcal{M}$. The many results for specific problems have provided insights on the relationships between the models and with respect to the activation schedulers. Recently, a comprehensive characterization of these relationships has been provided with respect to the Fsync and Ssync schedulers; however, in several cases, the results were obtained under some restrictive assumptions (chirality and/or rigidity). In this paper, we improve the characterization by removing those assumptions, providing a refined map of the computational landscape for those robots. We also establish some preliminary results with respect to the Async scheduler.
Formation of Cyclodextrin-Drug Inclusion Compounds and Polymeric Drug Delivery Systems using Supercritical Carbon Dioxide

New methods for the preparation of porous biomedical scaffolds have been explored for applications in tissue engineering and drug delivery. Scaffolds with controlled pore morphologies have been generated which incorporate cyclodextrin-drug inclusion complexes as the drug delivery component. Supercritical CO2 was explored as the main processing fluid in the complex formation and in the foaming of the polymer scaffold. The co-solvents, ethanol, ethyl acetate and acetone, were explored in each stage, as needed, to improve the solvent power of CO2. The first goal was to promote cyclodextrin-drug complex formation. Complex formation by traditional methods was compared with complex formation driven by processing in supercritical CO2. Complex formation was promoted by melting the drug in supercritical CO2 or in CO2 + cosolvent mixtures while in the presence of cyclodextrin. Some drugs, such as piroxicam, are prone to degradation near the drug’s ambient melting temperature. However, this approach using CO2 was found to circumvent drug thermal degradation, since drug melting temperatures were depressed in the presence of CO2.
STUDY OF EFFECTS OF DIFFERENT LEVELS OF NITROGEN AND POTASSIUM ON YIELD AND YIELD COMPONENTS OF RAIN-FED LENTIL

In order to study the effects of nitrogen and potassium fertilizers on yield and yield components of lentil under rain-fed conditions, an experiment was carried out in Agriculture Research Center of Ardabil, Iran in 2008. A factorial experiment based on a complete randomized block design with three replications was used. Nitrogen treatments included three levels (0, 25 and 50 kg.ha), potassium treatments included three levels (0, 30 and 60 kg.ha) and there were two cultivars (a local and a new cultivar named ILL180). Traits including plant height, number of branches/plant, number of filled pod/plant, pod number, seed number/plant, 100-seed weight and grain yield per unit area were measured. Analysis of variance showed that cultivars were not statistically significant regarding grain yield. Application of 50 kg N.ha fertilizer significantly increased the number of secondary branches/plant, number of filled pod/plant, total number of pod, seed number/plant and seed yield. Maximum seed yield was achieved when 50 kg N.ha fertilizer was applied. Potassium fertilizer had no significant effect on the above-mentioned traits.
Impact of regional analgesia techniques on the long-term clinical outcomes following thoracic surgery

Continuous monitoring of clinical outcomes after thoracotomy is very important to improve medical services and to reduce complications. The use of regional analgesia techniques for thoracotomy offers several advantages in the perioperative period including effective pain control, reduced opioid consumption and associated side effects, enhanced recovery, and improved patient satisfaction. Postthoracotomy complications, such as chronic postthoracotomy pain syndrome, postthoracotomy ipsilateral shoulder pain, pulmonary complications, recurrence, and unplanned admission to the intensive care unit are frequent and may be associated with poor outcomes and mortality. The role of regional techniques to reduce the incidence of these complications is questionable. This narrative review aims to investigate the impact of regional analgesia on the long-term clinical outcomes after thoracotomy.
Research Article: Lipid and fatty acid profile variations in Perna indica and Perna viridis of Kanyakumari district, South east and west coast of India

Variations of lipid and fatty acid profile of Perna viridis and Perna indica were assessed from Kanyakumari district. Lipid compositions varied and were measured as 8.92±0.03% in P. viridis and 6.73±0.01% in P. indica. The percentage composition of individual fatty acids as a ratio of total muscle lipids of P. viridis ranged from 0.11±0.01% to 25.09±0.03% whereas in P. indica it ranged from 0.10±0.01% to 33.2±0.05%. Highest proportions of fatty acids were of palmitic acid which was present in both species. The ratio of Omega-3 and Omega-6 fatty acids was 0.35±0.05 3.09±0.04 in P. viridis while in P. indica it was less than 1. Both the mussel species contained essential fatty acids particularly eicosapentaenoic acid and docosahexaenoic acid for promoting good health, as well as prevention and healing of diseases in humans. P. viridis and P. indica were recommended for human beings due to the presence of high content of unsaturated fatty acids.
Nasal Carriage of Staphylococcus aureus in Preclinical and Clinical Dental Students of Tabriz University of Medical Sciences and Identification of Methicillin-Resistant Isolates in 2019

Introduction Bacterial infection is a global problem. In many cases, bacterial resistance to antimicrobial agents could complicate treatments. Several strains of infectious agents have developed resistance to most of the available antibiotics and therefore, global monitoring has increased to examine antimicrobial resistances. This is particularly true for Methicillin-resistant Staphylococcus aureus (MRSA) which is one of the most important hospitaland community-related pathogens. Methicillin is a semisynthetic penicillin derivative produced in 1959 and is resistant to beta-lactamase resulting in significant decrease in infections related to penicillin-resistant strains. According to the definition proposed by the Center for Disease Control and Prevention, MRSA means resistance to methicillin and other common antibiotics. It has been reported to be found occasionally among people who refer to healthcare systems or have contact with MRSA patients. MRSA colonization is estimated to be around 1.5% in human population one-sixth of which is community-acquired MRSA (CA-MRSA) (1,2). Over the last 45 years, hospital-acquired MRSA (HA-MRSA) and CA-MRSA clones have spread across the world, and there is a high risk of related epidemies. Taking into account the importance of CA-MRSA and HA-MRSA strains, it is vital to identify them and determine their antibiotic resistance patterns in each region in order for helping doctors prescribe effective antibiotics (3). Given the lack of a comprehensive research in East Azerbaijan as well as considering dental students’ close contact with patients and the importance of MRSA strain, the present study aimed to identify the nasal carriage of S. aureus in preclinical and clinical students of dentistry at Tabriz University of Medical Sciences.
Production of a pasteurized functional drink containing wheatgrass and apple juice

Hasani, A. , Kongoli, R. , Laze, A. , Popovska, O. & Rexhepi, E. (2021). Production of a pasteurized functional drink containing wheatgrass and apple juice. Bulg. J. Agric. Sci., 27 (3), 615–624 The novelty in this investigation is the development of a new product, production of a pasteurized functional drink containing wheatgrass. The aim of this research was to develop a pasteurized functional drink containing wheatgrass and apple juice and to give some concrete data on the changes of nutritional values of the fruit juice as well as after adding wheatgrass in its recipes. It also aims to determine the most appropriate pasteurization scheme that ensures the food safety of the product and that minimally denaturizes the valuable health promoting phytochemicals. The raw materials and the produced juices have undergone quantitative chemical analyses for Chlorophyll, Vitamin C, total polyphenols, antioxidant activity, and minerals (P, Ca, Mg, Fe, Na, and Zn). Microbiological analyses for the presence of pathogens: E. coli, Salmonella and L. monocytogenes were conducted as well. Also, through this research, the identification of functional ingredients of wheatgrass is done; which is added to fruit juice thereby producing a stable functional beverage, which is safe in terms of food safety and that enriches the nutritional value of fruit juice.
Design, Aggregation and Analysis of Power Consumption Data using the Jump Process

This work aims to seek a pragmatic approach to assess electricity consumption at the level of households, buildings and neighborhoods. The main concern consists in proposing aggregation methods based on jump process according to a customer environment that is intrinsically linked to the implementation of a centralized system. The aim of the approach is to present data aggregations that derive their basis from a data model in order to facilitate the processing of electricity data at different scales of analysis. Such a smart meter data management process merits the design of an aggregated database that can store data for a house, a building and a neighborhood. The advantage of this system lies in the facilitation of data interpretation and the ability to guide decision-makers in the management of electricity consumption. An analysis of the behavior of electricity consumption is also proposed based on the monitoring of the electricity consumption of the various devices connected to a smart meter. Keywords—Design; aggregation; analysis; jump process; electricity consumption; smart meter
Examination of Preservice Teachers’ Views on Peer Learning

This study aimed to examine the preservice teachers’ views on the process after entering Code.org and block-based programming (Scratch) training programs, which are carried out by the peer learning method. The study group of the research consists of 41 preservice teachers at the Computer Education and Instructional Technologies departments of a state university and took the Special Teaching Methods 2 course in the spring semester of the 2017-2018 academic year. Considering the criteria determined by the researcher, 7 preservice teachers were selected as educators. As students, 34 preservice teachers participated in the study. In this study, a qualitative research method was used to determine the opinions of preservice teachers on the Code.org and Scratch training programs, which are carried out by the peer learning method. As a data collection tool, the opinion form for the Code.org training programs, the structure of opinion determination on the Scratch training programs, and the personal information form were used. The total duration of the study consists of eight weeks. Data from the preservice teachers were collected weekly using data collection tools and a content analysis technique used in the analysis of the data. At the end of the study, the opinions of the preservice teachers on the study conducted with the peer learning method were determined. It can be said that preservice teacher generally has positive views on peer learning and are satisfied with the peer learning method.
NCI Imaging Data Commons

This study introduces NCI Imaging Data Commons, a new repository of the NCI Cancer Research Data Commons, which will support cancer imaging research on the cloud. The National Cancer Institute (NCI) Cancer Research Data Commons (CRDC) aims to establish a national cloud-based data science infrastructure. Imaging Data Commons (IDC) is a new component of CRDC supported by the Cancer Moonshot. The goal of IDC is to enable a broad spectrum of cancer researchers, with and without imaging expertise, to easily access and explore the value of deidentified imaging data and to support integrated analyses with nonimaging data. We achieve this goal by colocating versatile imaging collections with cloud-based computing resources and data exploration, visualization, and analysis tools. The IDC pilot was released in October 2020 and is being continuously populated with radiology and histopathology collections. IDC provides access to curated imaging collections, accompanied by documentation, a user forum, and a growing number of analysis use cases that aim to demonstrate the value of a data commons framework applied to cancer imaging research. Significance: This study introduces NCI Imaging Data Commons, a new repository of the NCI Cancer Research Data Commons, which will support cancer imaging research on the cloud.
Executive functions in patients with different types of headaches.

Patients suffering from headache complain of the appearance of cognitive symptoms, although there is not much research in this regard, so the objective of the study was to analyze the deterioration in executive functions in patients with different types of headaches. The executive functions are processes related to the planning of the behaviour oriented to the achievement of a goal. A cross-sectional study was carried out, with a sample of 48 participants; 18 with vascular headache, 14 with tension headache, 16 with migraine. Significant differences have been found in the capacity for abstraction, which has discriminated between patients with vascular headache and tension headache, as well as between these and patients with migraine. Similarly, overall cognitive performance is different in patients with migraine compared with patients with vascular headache and tension headache. The type of headache and global cognitive impairment moderately affect the variability of abstraction capacity. Finally, the existence of a directly proportional relation of positive nature that indicates a dependent between the variables has been evidenced. It can be concluded that global cognitive deterioration affects the performance of abstraction capacity.
Food System Resilience Towards a Joint Understanding and Implications for Policy

The COVID-19 crisis is just one in a series of shocks and stressors that exemplify the importance of building resilient food systems. To ensure that desired food system outcomes are less fluctuating, policy makers and other important stakeholders need a common narrative on food system resilience. The purpose of this paper is to work towards a joint understanding of food system resilience and its implications for policy making. The delivery of desired outcomes depends on the ability of food systems to anticipate , prevent , absorb , and adapt to the impacts of shocks and stressors. Based on our literature review we found four properties of food systems that enhance their resilience. We refer to these as the A B C D of resilience building: Agency, Buffering, Connectivity and Diversity. Over time, many food systems have lost levels of agency, buffering capacity, connectivity or diversity. One of the principal causes of this is attributed to the governance of food systems. Governance is inherently political: as a result of conflicting interests and power imbalances, food systems fail to deliver equitable and just access to food. Moreover, the impacts of shocks and stressors are not evenly distributed across actors in the food system. This paper has highlighted the importance of more inclusive governance to direct food system transformation towards such higher levels of resilience. We conclude that we cannot leave this to the market, but that democratic and before all independent, credible institutions are needed to create the necessary transparency between actors as to their interests, power and influence. on its capacity to deal with natural and man-made disturbances: shocks and stressors. Shocks refer to a sudden event that impacts on the functions of a system and its components, as seen for example with COVID-19 and locust plagues. A stressor can be defined as a long-term trend that undermines the functioning and increases the vulnerability of a system. The most acute stressor threatening the current global food system is climate change, which in turn leads to a variety of shocks, such as extreme weather events or crop diseases.
Facile and Eco-Friendly Method for Synthesis of Calcium Oxide (CaO) Nanoparticles and its Potential Application in Agriculture

The regular techniques used to incorporate organic and inorganic compounds are experiencing significant expense, not environmental friendly, low proficient and not progressively reasonable in huge scope activities. As of late, we need a productive and eco-friendly manufactured way to deal with blend some significant inorganic or organic compounds in nano scales. Green procedures have the minimization of hurtful synthetic compounds and instrumentations, ease, basic, no unsafe concoction ages and high proficiency. In nano-scale, the capability of the compounds altogether increments and the green synthesis methodologies in engineered science are better other options and effective over customary techniques. In the current investigation, we have synthesized calcium oxide (CaO) nanoparticles by utilizing the leaf extract of Ocimum tenuiflorum. Calcium oxide nanoparticles are discovered important in adsorption, antimicrobial activities, catalysis and absorption. The newly synthesized CaO nanoparticles (CaONP) have been described by various systematic techniques, for example, UV-Visible, DLS, XRD, SEM and EDX. The CaO nanoparticles are pertinent in the antimicrobial activity against gram positive (Bacillus subtilis, Staphylococcus aureus) and gram negative bacteria (Pseudomonas aeruginosa, Escherichia coli) and huge zone of inhibition found over these microorganisms in the following order, S. aureus < B. subtilis < E. coli < P. aeruginosa. CaONP also test for agricultural application as macro nutrient. Plant growth was measured using growth analysis parameters i.e. % germination, relative growth rate (RGR), net assimilation rate (NAR), leaf area ratio (LAR), leaf weight ratio (LWR), specific leaf area (SLA), specific leaf weight (SLW), leaf area duration (LAD), the physiological response to particular mineral stress calculated by measuring % phytotoxicity, % inhibition, tolerance indices, seed vigor index. The biochemical response to particular CaNP stress calculated by measuring total carbohydrates, total protein, chlorophyll pigment concentrations and peroxidase enzyme activity.
Optimal Power System Stabilizers Design for Multimachine Power System via Hybrid Approach

A novel hybrid approach involving Particle Swarm Optimization (PSO) and Bacterial Foraging Optimization Algorithm (BFOA) called Bacterial Swarm Optimization (BSO) is illustrated for designing Power System Stabilizers (PSSs) in a multimachine power system. In BSO, the search directions of tumble behaviour for each bacterium are oriented by the individual’s best location and the global best location of PSO. The proposed hybrid algorithm has been extensively compared with the original BFOA algorithm and the PSO algorithm. Simulations results have shown the validity of the proposed BSO in tuning PSSs compared with BFOA and PSO. Moreover, the results are presented to demonstrate the effectiveness of the proposed controller to improve the power system stability over a wide range of loading conditions. Key-Words: PSSs; Multimachine Power System; Particle Swarm Optimization; Bacteria Foraging.