Miracle-dz/UniFAR-FTUs huggingface dataset:
Hybrid throughput aware variable puncture rate coding for PHY-FEC in video processing

: It is attractive to be able to alter the coding rate, and hence the error correcting power, of a forward error correcting coder/decoder (codec) to provide a codec whose error correction capability can be matched to the requirements of the data communication system in which it is used. Punctured coding applied to convolutional encoding/Viterbi decoding offers a method of achieving this. And adoptive multi beam-forming alongside with MIMO diversity gain is used for considerable QOS enhancement in their Open Network Intermediate Data Rate system. This paper discusses the modification of a QoS constraint length 7, 1/2-rate codec to operate with punctured coding at rates up to 7/8. Following a brief discussion of the requirements for variable rate coding in communication systems the practical implementation of a prototype codec and considerations relating to performance characterization are discussed. Experimental results at various coding rates and MIMO are given, together with simulation of performance to demonstrate the sensitivity of performance to path history length at higher coding rates. It is concluded that the method is very suitable to provide variable coding rates and not suffers from increasingly severe practical limitations over high speed networks.
Narrow Band Imaging- A New Imaging Technology in Early Detection of Head and Neck Cancer

Narrow band imaging (NBI) is a novel method of imaging that increases the diagnostic potential of conventional endoscopy. It highlights abnormalities in the superficial vasculature of mucosal lesions so that precancerous or cancerous lesions can be identified more easily. Initially developed for the gastrointestinal tract, and widely used in other branches of medicine, it is now being used for the assessment of patients with malignancy in the head and neck. We review current published papers relating to NBI and discuss its benefits for early detection of cancer of the head and neck.
PREDICTION AND VALIDATION OF PHYSICAL QUALITIES OF OFADA RICE AS AFFECTED BY STORAGE DURATION AND PROCESSING CONDITIONS USING RESPONSE SURFACE METHODOLOGY

The objective of the study was to produce optimum physical qualities of Ofada rice with varying independent variables of storage duration and processing conditions using response surface D-Optimal. The experimental design independent variables were storage duration (1 9 months) and processing conditions (soaking, 1-5 days; parboiling, 80-120 C; drying, 30 -70 C) and responses were size characteristics, head rice yield, brokenness, chalkiness and colour value. The experimental results were evaluated, optimised and modelled using response surface methodology. The result revealed that storage duration and processing parameters affected physical quality of Ofada rice. The predicted R 2 ranged between 0.9148 and 0.7373 which confirmed the fitness of the model. Coefficient of the quadratic model showed the effect of soaking time influence positively size characteristics, brokenness, chalkiness and colour value. Parboiling and drying temperature determined head rice yield, parboiling positively influence colour value of Ofada rice while the effect of paddy storage was more felt on lightness. The best optimum solution for storage and processing conditions as predicted include storage of paddy for 1 month, soaking in water for 1 day, parboiling at 119.92°C and drying at
Plastic Embeddment of Dry-Processed Tissue1

Seed tissue is extremely difficult, if not impossible, to embed in plastic when fixed and processed dry; on the other hand, if it is fixed with aqueous fixatives and dehydrated by solvent exchange, seed tissue can be embedded readily. Earlier, I hypothesized that cell walls exclude resin monomers from dry-processed peanut (Arachis hypogaea L.) seed tissues. Now I show that seed tissues whose cellular contents have been digested away by a proteolytic enzyme, still are difficult to embed in plastic if air-dried and processed dry. I submit, therefore, that since these specimens consist only of cell walls, air-dried cell walls are indeed the factor that bars passage of resin monomers into seed tissues processed dry.
The synergistic cytotoxic effects of doxorubicin and Viola odorata extract on human breast cancer cell line T47-D

Background: Breast cancer accounts for one-third of cancer cases in women. Doxorubicin (Dox) is one of the chemotherapeutical compounds widely used to treat breast cancer. Chemical drugs have several side effects and their continuous administration leads to drug resistance in patients. To decrease such side effects in cancer treatment, combination therapy as well as application of natural and herbal compounds has been taken into consideration. The aim of this study was to investigate the cytotoxic effect of Viola odorata (Vo) extract on T47-D human breast cancer cells, alone and in combination with Dox. Materials and Methods: The cytotoxic effects of V. odorata and Dox were studied by morphological examination and 3,(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Flowcytometric analysis was performed to determine the type of cell death. Moreover, scratch healing assay was conducted to investigate antimigration effect of V. odorata. Results: The results of MTT assay showed that V. odorata and Dox-induced cell death in T47-D cells in a dose- and time-dependent manner. Morphological analysis revealed that V. odorata and Dox-induced features of apoptotic cell death in T47-D cells. These results were confirmed by flow cytometry analysis. Scratch healing assay revealed that migration rate was reduced in the V. odorata- treated cells. Conclusions: Our findings suggest that components of V. odorata exert antitumor effects on human breast cancer and could be administered with lower doses of antitumor agent Dox, in combination therapy, to decrease its side effects.
The Vital Role of Advanced Generation Anti-PSMA having Special CAR-T of PSMA in Cancer of Prostate having Immunotherapy Analysis

s: CAR T cell therapy havean extraction from designed T cells (dTc) locomotive engineered of chimeric antigen receptors (CARs) for tumoricidal action correspond potency having elevation of specific role for the management of cancer. In this study, the first generation dTc are adapted with chimeric immunoglobulin T cell receptor while the second generation dTc are engineered with an immunoglobulin CD28 T cell receptor which integrated a CD28 costimulatory signal for optimal T cell stimulation. It determines the cognition of chimeric T cell receptors (CTR) load-bearing T cells to recognize humanlike prostate specific membrane antigen (hPSMA) on epithelium targets in both vitro and vivo. The CAR T cells are created using the antiPSMA, and the intracellular signaling domains, CD3ζ and CD28. T cells supporting the third generation antihPSMA CAR, P28BBζ, were capable to recognize and kill off the primary human endothelial cell separate from gynecological carcinoma. While4 th generation CAR having an extra unique feature by releasing cytokine transgene.Current review is focus on the 1 st , 2 nd , 3 rd and 4 th generation’s antiprostate specific membrane antigen (PSMA) CARs and their applications for combating prostate carcinoma. Conclusions: This research demonstrate that Ist ,2 nd ,3 rd and 4 th generation of the anti-PSMA designer T cells exhibit superior antitumor function versus first generation, also providing the prostate cancer immunotherapy. CAR-T cell therapy is mainly achieved in the treatment of hematologic malignancies a breakthrough in the stage of its tumor research in the field has great potential value. But in the treatment of solid tumors is not mature, failed to produce excepted effect. By finding the appropriate tumor surface antigens, overcome tumor immunosuppressive microenvironment, optimization of co-stimulatory molecules, and construction. The fourth generation of Cars, design suicide gene, to reduce adverse reactions after reinfusion should be such as to enhance the anticancer activity of toxic, has become a hot research in this field.
Solving Least Squares with LSRN

In this paper we will present the LSRN iterative algorithm for solving the Linear Least Squares Problem. Linear Least Squares finds a linear regressor for a data set which minimizes the squared residual. Most frequently it appears in statistics, data science, and machine learning though the techniques are put to use in nearly any field using data. Typically, Linear Least Squares is written as the following optimization problem:
Measuring the Impact of the GDPR on Data Sharing in Ad Networks

The European General Data Protection Regulation (GDPR), which went into effect in May 2018, brought new rules for the processing of personal data that affect many business models, including online advertising. The regulation's definition of personal data applies to every company that collects data from European Internet users. This includes tracking services that, until then, argued that they were collecting anonymous information and data protection requirements would not apply to their businesses. Previous studies have analyzed the impact of the GDPR on the prevalence of online tracking, with mixed results. In this paper, we go beyond the analysis of the number of third parties and focus on the underlying information sharing networks between online advertising companies in terms of client-side cookie syncing. Using graph analysis, our measurement shows that the number of ID syncing connections decreased by around 40% around the time the GDPR went into effect, but a long-term analysis shows a slight rebound since then. While we can show a decrease in information sharing between third parties, which is likely related to the legislation, the data also shows that the amount of tracking, as well as the general structure of cooperation, was not affected. Consolidation in the ecosystem led to a more centralized infrastructure that might actually have negative effects on user privacy, as fewer companies perform tracking on more sites.
Impact of CPEC on Pakistan Stock Exchange

The paper is written to find out the Impact on Pakistan stock exchange due to the investment of China in Pakistan with Exchange Rate. Chinese policy makers are trying to mold investor’s perception towards its own region. China Pakistan Economic Corridor is the pathway of their objective. The change in the Pakistan Stock Exchange will reflect impact of the foreign direct investment. It is proved by the study that capitalization in Pakistan Stock Exchange has increased. Its reason is very clear; the policy makers focused power-sector, infrastructure, developing programs in agriculture and industry zone. Not only the investors of this region are interested and affected by the investment in the region but also other international markets are affected by this. For example, America started Sino-US trading war. As this investigation have also its limitations. The study conducted for a specific time period. The Variations in the Exchange Rates is due to monetary policy. Controlling over Exchange rate might give more favorable results. This investigation will be beneficial for the Government of Pakistan and for national and international investors.
Optimised Environmental Data Acquitisation Technique for Monitoring Air Quality and Crop Plantation for Developing a Smart City Using LoRa Network

Movements in low power and simplicity estimation and correspondence development have gotten a disturbed remote distinguishing and checking applications. Starting at now, there are many battling checks and advances trying to take a hold of WSN, especially the zone of remote identifying and correspondence development. LoRa Network is one of these progressions getting omnipresence in the utilization of Wireless Sensor Networks (WSNs). The limit of LoRa Network to develop correspondence interfaces over long detachments with by and large essential centers; irrelevant establishment, low power requirements and use of license free ISM gatherings give it a broad edge of its adversaries. Notwithstanding the way that a lot of research work has been done about the ampleness of LoRa Network for low power remote sensor frameworks, there are still openings in the expounding on the sensible pieces of structure and execution of such systems. This endeavor revolves around issue of realizing a constrained sensor arrange for a sharp air quality examination and yield domain system for a splendid city application using LoRa Network as the central correspondence development. A structure for checking air nature of the earth and yield bequest is executed using negligible exertion game plans available in the market. This task likewise has application in yield ranch. Soil dampness, temperature, mugginess of the dirt is noted so that if soil's water level goes down or ends up overabundance it will hurt the yields. So to keep up the water prerequisite sensors are set in soil and lora innovation is utilized for information transmission.
The Effect of Political Socialization through Opinion Leader toward Political Participation of Borderline Citizens in 2019 General Election (Raihat-Atambua District Border District)

In socializing politics in border region is quite difficult, the limitations of media entering the border areas and the limitations in the use of Indonesian have the public struggle to obtain information about the election. This condition is getting worse with the unstable internal political upheaval in the border region. Therefore, it takes the presence of an opinion leader figure to bridge the information gap between outsiders and rural. The purpose of this study was to determine the effect of political socialization in the election process through opinion leaders on community participation in the border region of the Republic of Indonesia-Timor Leste, Raihat District, NTT in the 2019 elections. This research was a quantitative study using an explanatory approach. The results of the research that have been done show that political socialization, through opinion leaders has a significant influence on political participation.
A Survey on Machine Learning Algorithms

: Machine Learning is a logical procedure where the PCs figure out how to take care of an issue, without unequivocally program them. Profound learning is at present driving the ML race fueled by better calculations, calculation force and huge information. Still ML old style calculations have their solid situation in the field.It is difficult to choose appropriate algorithm for a particular dataset which will help the developer to develop a productive approach. Our project will solve this difficulty by considering a few of the parameters like accuracy, time taken etc. of the algorithm for a particular dataset and compare each algorithm on the basis of these parameters and then predict that which out of these algorithms is the best used in the given scenario. We have done a comparative study over different machine learning supervised and unsupervised techniques like Linear Regression, Logistic Regression, K nearest neighbors and Decision Trees in this project. This project is implemented using python. Thus, we had used JupyterLab(Which is an IDE for Python) for implementing this project. In this project we have used different datasets such as pima-India-diabetes dataset for supervised learning, The Oxford-IIIT Pet Dataset for image classification algorithms etc. This paper center’s around clarifying the idea and advancement of Machine Learning, a portion of the famous Machine Learning calculations and attempt to analyses most well-known calculations dependent on some essential ideas. In this project different machine learning algorithms are compared on the basis of some parameters such as Confusion matrix, accuracy, Area Under ROC Curve etc.
Large-Scale Phosphorylation Analysis of -Factor-Arrested Saccharomyces cerevisiae

Journal of Proteome Research is published by the American Chemical Society. 1155 Sixteenth Street N.W. , Washington, DC 20036 Article Large-Scale Phosphorylation Analysis of -Factor-Arrested Saccharomyces cerevisiae Xue Li, Scott A. Gerber, Adam D. Rudner, Sean A. Beausoleil, Wilhelm Haas, Judit Villn, Joshua E. Elias, and Steve P. Gygi J. Proteome Res., 2007, 6 (3), 1190-1197• DOI: 10.1021/pr060559j • Publication Date (Web): 17 January 2007 Downloaded from http://pubs.acs. org on February 27, 2009
Activity Report 2019 Team CHORALE Collaborative and HeterOgeneous Robots interActing in Live Environment

: CrowdBot will enable mobile robots to navigate autonomously and assist humans in crowded areas. Today’s robots are programmed to stop when a human, or any obstacle is too close, to avoid coming into contact while moving. This prevents robots from entering densely frequented areas and performing effectively in these high dynamic environments. CrowdBot aims to ﬁll in the gap in knowledge on close interactions between robots and humans during navigation tasks
Spatial and temporal variation in hippoboscid parasitism by Ornithomya chloropus on house sparrows (Passer domesticus) and its effect on survival

1. I examined how the Hippoboscidae Ornithomya chloropus is spatially and temporally distributed in an insular metapopulation of house sparrows in northern Norway from 2004-2011, whether there were demographic differences in abundance as well the relationship between abundance and morphology, and abundance and survival in juvenile house sparrows. 2. I found a handling effect on the abundance of O. chloropus which reduced the number of flies found on individuals from their first to their second catch. 3. There was considerable variation in abundance between years and islands as well as within seasons, and abundance of O. chloropus differed between age-classes. 4. There was a negative relationship between abundance and the three morphological traits; body condition index, body mass and tarsus length. There was also a positive effect of age on these morphological traits and a negative effect of late hatch days. 5. There was a positive relationship between juvenile survival and body condition index, and survival and tarsus length. 6. These results indicate a relationship between the abundance of O. chloropus and the fitness of juvenile house sparrows with morphology while there was no clear relationship between juvenile survival and abundance.
A Systematic Review of Blockchain-based Services for Security Upgradation of a Smart City

The concept of smart city has gained popularity in recent years. The elementary concept refers to promoting the uninterrupted sharing of data and services within and across communities by the application of emerging technologies. Smart cities strive for cost reduction, optimal use of resources and the development of a more sustainable environment. Considerable advances in modern technologies such as IoT and wireless communication have enabled sharing of data between remote devices which are geared with open data, hence a smart city is susceptible to a number of security threats. It is important to identify these threats, analyze IoT data to improve privacy and security and identify the corresponding consequences. Blockchain has emerged as a promising solution to resolve these challenges. Blockchain is a peer-to-peer shared database technology that cannot be modified once a transaction is recorded and validated. This study explores the contribution of blockchain to smart cities in terms of decentralized security, immutability, transparency and privacy to provide intelligent, customized and context-aware services to smart city dwellers. A brief overview of this novel technology has been given along with its deployment in a smart city setting, the open issues discussed and prospective scope of blockchain application has been presented.
Ontology-Based Approach to Validation of Learning Outcomes for Information Security Domain

Validation of non-formal and informal learning results is an effective way to solve a number of socioeconomic problems in various spheres. Recognition of learning outcomes in dynamic domains requires the use of background knowledge acquired from open information resources. Need in such background knowledge causes the interest to ontological representation of learning domain and ontology-based methods of knowledge analysis. Now unstructured natural language texts constitute considerable part of the Web available content. The large data volume necessitates scalable means of analysis, and more efficient and rapid processing can be ensured through the use of task-specific the-sauri based on domain ontologies. The approach proposed by the authors to recognize non-formal and informal learning outcomes is exemplified by information security domain. The referencing to this domain is determined by the heterogeneity and dynamics of its information sources, the complex hierarchy of knowledge as well as the growing need for information security specialists in the context of the digitalization of society.
Cornucopia: Temporal Safety for CHERI Heaps

Use-after-free violations of temporal memory safety continue to plague software systems, underpinning many high-impact exploits. The CHERI capability system shows great promise in achieving C and C++ language spatial memory safety, preventing out-of-bounds accesses. Enforcing language-level temporal safety on CHERI requires capability revocation, traditionally achieved either via table lookups (avoided for performance in the CHERI design) or by identifying capabilities in memory to revoke them (similar to a garbage-collector sweep). CHERIvoke, a prior feasibility study, suggested that CHERI’s tagged capabilities could make this latter strategy viable, but modeled only architectural limits and did not consider the full implementation or evaluation of the approach.Cornucopia is a lightweight capability revocation system for CHERI that implements non-probabilistic C/C++ temporal memory safety for standard heap allocations. It extends the CheriBSD virtual-memory subsystem to track capability flow through memory and provides a concurrent kernel-resident revocation service that is amenable to multi-processor and hardware acceleration. We demonstrate an average overhead of less than 2% and a worst-case of 8.9% for concurrent revocation on compatible SPEC CPU2006 benchmarks on a multi-core CHERI CPU on FPGA, and we validate Cornucopia against the Juliet test suite’s corpus of temporally unsafe programs. We test its compatibility with a large corpus of C programs by using a revoking allocator as the system allocator while booting multi-user CheriBSD. Cornucopia is a viable strategy for always-on temporal heap memory safety, suitable for production environments.
Outcome of Single Level Microdiscectomy in Different Herniation Type and Level: A Prospective Study

Aim:To report on a young, active population with symptomatic lumbar disc herniations who had failed a reasonable trial of non-operative care and then underwent micro-discectomy. Validated outcome measures, patient satisfaction, and return to duty were correlated with type and level of herniation to determine clinical success.Materials and methods: 36 patients with clinically diagnosed disc herniationswho were subjected to micro-discectomy were analyzed for the outcome using VAS (Visual analogue score) and OPDS (Oswestry Disability Index scoring) pre and postoperatively. Results: There was a significant difference in type of disc herniation (p=0.008). However there was no significant difference with respect to level of herniation (p=0.167). There was a significant improvement in both VAS and OPDS of patients at post-operative stage (p<0.001). Conclusion:We found that surgical outcomes were significantly influenced by disc herniation type. Sequestered discs were associated with the best outcome scores, significantly better than those associated with extruded and contained disc herniations. Patients with disc herniations at the L5–S1 level had significantly better outcomes by VAS and OPDS score than did those with herniations at the L4–L5 level.