Miracle-dz/UniFAR-FTUs huggingface dataset:
PGPM_A_271516 87..99

1Department of Cardiothoracic Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325035, People’s Republic of China; 2Department of Laboratory Medicine, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325027, People’s Republic of China Background: LARGE1 plays a pivotal role in glycosylation of alpha-Dystroglycan (α-DG) and is aberrantly downregulated in cell lines originating from epithelium-derived cancers including lung cancer. However, the expression of LARGE1 and its clinical significance in NSCLC are not clear. Materials and Methods: The data were collected from the TCGA database to investigate LARGE1 expression in stage I–III NSCLC and explore its associations with clinicopathological parameters and overall survival of patients. The prognostic role of LARGE1 was examined in subgroups according to clinical features and treatments. The results were validated in external cohorts from the NCBI GEO database. Gene Set Enrichment Analysis (GSEA) was performed to investigate the potential molecular mechanisms during LARGE1 alteration in NSCLC. Results: LARGE1 was aberrantly downregulated in NSCLC compared with adjacent tissues and normal lung tissues and in tumors with advanced stage compared with early stage. There was only a trend of association between high LARGE1 with OS in multivariate analysis. Surprisingly, high LARGE1 was significantly associated with improved OS in a subgroup of the patients with adjuvant chemotherapy (ACT) and a significant interaction between LARGE1 expression and ACT was found. Improved OS after ACT was also found in patients with high LARGE1 compared to those with low LARGE1. When combining LARGE1 expression and ACT, compared with patients with non-ACT, HR of low LARGE1/ACT was 0.592 (95% CI=0.432–0.813, P=0.0012), and HR of high LARGE1/ACT was 0.124 (95% CI=0.031–0.505, P=0.0036). The results were verified in two external cohorts from the GEO database. GSEA indicated that LARGE1 might downregulate cell cycle pathway to improve ACT sensitivity and subsequently the prognosis in NSCLC. Conclusion: High LARGE1 can be used to identify the patients with resected stage I–III NSCLC most likely to benefit from adjuvant chemotherapy.
Digitization of the construction industry in the Czech Republic

The work is focused on the issue of innovation in construction, which is associated with the gradual digitization of the entire sector to streamline work processes, save time and costs. The work addresses in more detail the issue of BIM implementation and the overall transformation of the construction industry based on the approved innovation strategy of the construction industry in the Czech Republic 2019-2030. From the point of view of introducing digitization into the construction industry, construction companies in the Czech Republic receive support mainly from subsidy programs, thanks to which construction companies can obtain a contribution for the purchase of new software and hardware solutions. The BIM method is analyzed in more detail from the point of view of implementation in a construction company and the implementation process itself is divided into several steps. Currently, the issue of BIM implementation is a very current topic, especially regarding the impending obligation to award above-limit public contracts in the Czech Republic for construction work, including contracts for related pre-project and project services in the above-limit regime using the BIM method.
PARTY BASED SENTIMENT ANALYSIS OF LEGAL OPINION TEXTS

Factual scenario analysis of previous court cases holds a significant importance to lawyers and legal officers whenever they are handling a new legal court case. Legal officials are required to analyse previous court cases and statutes to find arguments and evidence before they represent a client at a trial. As the number of legal cases increases, legal professionals typically endure heavy workloads on a daily basis, and they may be overwhelmed and may be unable to obtain quality analysis. In this analysis process, identifying advantageous and disadvantageous relevant to legal parties can be considered a critical and time consuming task. By automating this task, legal officers will be able to reduce their workload significantly. Our ultimate goal of this research is to introduce a system to predict sentiment value of sentences in legal documents in relation to its legal parties. To achieve this task, we use a fine-grained sentiment analysis technique called Aspect-Based Sentiment Analysis(ABSA). To the best of our knowledge, this would be the first study that brings the concepts of Aspect Based Sentiment Analysis to the legal domain. To the best of our knowledge, there is no publicly available dataset for the aspect (party)based sentiment analysis for legal opinion texts. Hence, we created a dataset(SigmaLaw-ABSA) which consists 2000 legal opinion text fetched from court cases in order to train the models and to conduct the experiments. Then we developed a rule-based model which is primarily built around a phrase-level sentiment annotator and using rationally built rules to perform Party-Based Sentiment Analysis. The complexity of the structure of the sentences in legal texts has prompted to develop first a rule-based approach over other approaches. Developing this model, we got a much understanding on the legal domain, complex structure of the legal texts and many other benefits for the future works. But in the evaluation process, we experienced some major limitations as it’s significantly depends on the phrase level sentiment annotator and
An Improved Firefly Algorithm Integrated with Recurrent Neural Network (RNN) for Face Recognition

Background: Face recognition (FR) is a promising biometric trait widely used for authentication in several applications like finance, military, security, surveillance and so on in daily life. Deep learning involves several processing layers for learning data representations with feature extraction at multiple levels. Hence, deep FR techniques with hierarchical architecture which puts pixels together to represent invariant face has drastically improved the recognition performance and promoted real-time applications successfully. Objective: In this research, an Improved FireFly (IFF) algorithm is developed to recognize face whose performance is estimated by the integration of RNN network. Method: Based on the selected dataset, RNN involved in analysis of facial features with inclusion of improved firefly algorithm (RnnIFF). Result: The results stated that proposed approach provides higher value of accuracy, precision and sensitivity expressing 90%, 90% and 91% respectively. Also, Mean Square Error (MSE) and Peak Signal to Noise ratio (PSNR) is evaluated and comparatively examined with existing techniques. The simulation results illustrated that proposed RnnIFF exhibits significant performance for recognition of faces.
Use of ludic design to fight disinformation: newsgames as a tool to raise awareness about hoaxes

The rise of social media, together with a particularly convulsive political situation, has fostered the spread of fake news and other information disorders. In this context, several media outlets and non-profit institutions have launched different verification initiatives with the objective of empowering individuals to critically evaluate fake news. The objective of this research is to explore the potential of five newsgames designed to educate users against disinformation. The methodological proposal is based on an exploratory content analysis of the newsgames, to identify the mechanics, dynamics, and narrative formulas used in its design. Our findings reveal that the correct choice of mechanics and dynamics allows complex arguments to be created in a way that is consistent with news standards. Thus, the intersection of journalism, education, and gaming facilitates “information-driven media” in which news content is constructed through interaction with the game system and is not included just as an accessory element.
THE EFFECT OFEDUCATION PRICE AND SERVICE QUALITY ONSTUDENT EDUCATION SELECTION DECISION AND ITS IMPACT ON STUDENT SATISFACTION :STUDY IN ACEHMALAHAYATI SHIPPING POLYTECHNIC

This study intends to examine the effect of price and service quality on student decision in choosing education and training and its impact on the satisfaction of training students at shipping polytechnics in Aceh. This research was conducted on training participants (students) of the Aceh Malahayati Shipping Polytechnic training program throughout 2019 with a population of 16,917 people. The sampling technique used was the probability sampling technique, which was the stratified random sampling in order to obtain a sample of 200 students. Data were analyzed using Structural Equation Modeling (SEM) with the help of Amos software. The research found that the price of education and the quality of service were the factors that influenced the student education selection decision. Furthermore, the price of education, quality of service, and student education selection decisionare factors that affect student satisfaction. The results of the mediation test found that student education selection decision significantly mediates the effect of education price on student satisfaction, and are proven to function as a partial mediator. Meanwhile, student education selection decision cannot significantly mediate the effect of service quality on student satisfaction at the Aceh MalahayatiShipping Polytechnic. The novelty of this research lies in the combination of previous theories regarding the effects of direct causality and the effects of mediating causality, as well as new research object. The next researchers are expected to form a new model as a result of the development of this research model that has been tested, by combining it with other variables such as brand image, trust, and E-WOM, and gender in the multigroup moderation model will provide a more complete picture. Keyword:education price, service quality, student education selection decision, satisfaction.
POPULATION DYNAMICS AND FISHERY MANAGEMENT OF CIRRHINUS MRIGALA (HAMILTON, 1822) IN PAKISTAN

The study of environmental resources usually gets meagre attention particularly in developing countries. This is the first-attempt to study population dynamics and fishery management parameters of a very important aquatic environmental resource Cirrhinus mrigala (Mrigal carp) in Pakistan. For this, six monthly surveys, January to June 2020, collected 720 samples numbers (n), ranging (R) in size from 14 to 37 centimeters (cm) (22±5.445) and weighing from 30 to 527 grams (g) (148±110.673). Collected data was statistically analysed by FAO-ICLARM Stock Assessment Tools II (FiSAT-II). Length-weight relationship (LWR) for Mrigal carp was measured as W=0.014 L having goodness of fit (R) value of 0.987. Computed values of asymptotic length (L∞) and growth coefficient (K) were 38.85 cm and 0.180 years. Other fishery parameters, viz., theoretical age at which length is zero (to), growth performance index (GPI), total mortality (Z), natural mortality (M) and fishing mortality (F) were estimated at -0.056, Φ'= 2.434 year, Φ= 1.130 year, 1.170 years, 0.493 years and 0.677 years, correspondingly. Moreover, target reference point (TRP) for maximum sustainable yield (MSY) was calculated as 92160 g. Thus, considering obtained results, it can be concluded that Mrigal carp fishery is degrading and biologically overfished at Chashma Barrage. Therefore, it is strongly recommended that catch should be reduced according to the TRP and conservation management policies should be implemented immediately.
Transcatheter mitral valve replacement for degenerated mitral bioprostheses: a systematic review.

Background Treatment of degenerated mitral bioprostheses with transcatheter mitral valve-in-valve (MVIV) implantation is increasingly used. The goal of this review was to evaluate the one-year outcomes of this therapy using the most recent evidence. Methods A MEDLINE, Cochrane database and SCOPUS search was performed of published observational studies involving patients undergoing transcatheter MVIV for degenerated bioprosthesis to determine procedural success, thirty-day and one-year survival. Results A total of 2,684 patients undergoing transcatheter MVIV were identified from five studies with mean age of 73-75 years, 57-63% female and Society for Thoracic Surgery (STS) risk score ranging from 9-13%. Procedural technical success ranged from 94-98%, with 1-3% rates of periprocedural death, 0-2% stroke and 1-5% risk of left ventricular outflow tract (LVOT) obstruction. Thirty-day post-procedure mean mitral prosthetic gradient ranged from 6-7 mmHg and residual mitral regurgitation was mild or less in 96-100% of patients. Thirty-day survival and one-year survival ranged from 93-97% and 83-89% respectively. Conclusions Transcatheter MVIV is an effective treatment for structural degeneration of biologic mitral valve replacement with low complication rates and favorable one-year outcomes. Accordingly, MVIV should be considered as a reasonable alternative to re-do surgical mitral valve replacement in high risk patients with comorbidities. Further study of long-term outcomes of this treatment is needed.
Application of “Face Recognition” Technology for Attendance Management System

The attendance management system is a system that needed for learning activity in a University. In some University, the attendance management system has been used tapping system which using NFC technology. Actually, that attendance management system is effective for managing each of attendance information. However, until now we can still see many cheats for this attendance system. For example, leave their cards to their classmates and tell them to tap for them. For that, one of the many effective solutions to resolve that problem is to add face recognition technology in the current attendance system. In our experiment, we know that to add face recognition to the current attendance management system surely need a camera and also face dataset for the system. At the beginning, we need at least 9 images with different emotions and face positions to let the system recognizes one’s face. To make this system more accurate at recognizing one's face, we would update the face dataset in every face recognizing process.
A Porcine Model for Repair of Long Bone Non-Union Defects Using Three-Dimensionally Printed Scaffolds

Background: Approximately 5-10% of bone injuries in the United States result in non-union, costing an estimated $10.4-26.1 billion annually for treatment. While several orthopedic strategies to address non-unions in long bones are available, all have drawbacks and risks of complications. A possible alternative is the recent advances in tissue engineering treatments that are improvements over current treatment options. Methods and Findings: We have developed a porcine long bone segmental defect model for testing osseous non-union repair using 3D-printed biodegradable scaffolds. We generated a 3.5 cm mid-diaphyseal defect in the right radius of a six-month-old pig. A Polycaprolactone (PCL) scaffold implant designed from radius Computed Tomography (CT) scans and produced using solid form fabrication was implanted into the defect and stabilized with a stainless-steel plate. The animal could stand and place weight on the limb at six hours post-surgery and ambulating without a noticeable limp by four weeks. CT imaging post-surgery show bone fill in the defect space by two weeks, significant defect closure by eight weeks and complete union by 24 weeks.
Estimation procedures on Type-II censored data from a scaled Muth distribution

In the present paper, we consider the estimation problem for the scaled Muth distribution under Type-II censoring scheme. In order to estimate the model parameters α and β, the maximum likelihood, the least-squares, and the maximum spacing estimators are derived. To show estimation efficiencies of the estimators obtained with this paper, we present an exten- sive Monte-Carlo simulation study in which the estimators are compared according to bias and mean squared error criteria. Furthermore, we evaluate the applicability of the scaled Muth distribution by taking into account both full and Type-II censored data situations by an anal- ysis conducted on a real-life dataset.
Evaluation of the Adulteration of Edible and Cosmetic Sunflower Oils by GC-FID and ESI-MS

Sunflower oil has several properties that are valuable to the human skin and health; however, they are target of adulterations. In this study, in order to evaluate the authenticity of edible and cosmetics based on sunflower oils, the triacylglycerol (TAG) profiles using direct infusion electrospray ionization mass spectrometry (ESI-MS), the fatty acid (FA) composition by gas chromatography with flame ionization detection (GC-FID) and principal component analysis, of seven commercial samples were determined and the results obtained were compared with the pure sunflower and soybean oils. Of the seven brands analyzed, just one sample presented only sunflower oil in its composition; two stated in the label soybean addition; and four did not present the real composition of the product in the label. Therefore, GC-FID and ESI-MS analysis in conjunction with principal component analysis (PCA) demonstrated that they are complementary techniques and could be applied in food industries to assess the quality of vegetable oils, since results showed the need for stricter quality control for this product.
Physical Properties of Different Local Glutinous Rice Cultivar ( Susu and Siding ) and Commercial Thai Cultivar ( Susu )

: Glutinous rice (Oryza sativa var. glutinosa) is known as waxy rice or sticky rice and it has an opaque and small size grain cultivar distinct from common white rice. In outlining the equipment for processing, storage, sorting, sizing and other post-harvest equipment, the physical properties are very important. Two different cultivars of Malaysian local glutinous rice known as Susu and Siding were evaluated in this study. The objective of this study is to compare the physical properties of two different local cultivars in designing the rice processing equipment. For Susu cultivar, the average of length, width and thickness were 6.63 mm, 1.88 mm and 1.50 mm, respectively. The corresponding values were 6.24 mm, 1.98 mm and 1.48 mm for Siding cultivar. For Susu cultivar, the average of aspect ratio, sphericity, volume, surface area, bulk density, true density, porosity, 1000 weight kernel and angle of repose were 0.28, 0.40%, 9.81 mm 3 , 19.02 mm 2 , 800.54 kg/m 3 , 1500.36 kg/m 3 , 46.65%, 18.88 g and 39.45 ° , respectively. The corresponding values were 0.32, 0.42%, 10.25 mm 3 , 19.45 mm 2 , 772.73 kg/m 3 , 1229.51 kg/m 3 , 37.15%, 17.04 g and 40.08 ° for Siding cultivar. The physical properties of the same cultivar ( Susu ) showed no significant difference, but apparently Siding was higher in bulk density, which requires a larger-sized silo compared to Susu cultivar in term of equipment design.
Reduce the Memory Used in Key Management for Security Systems

– Nowadays, most of the applications are distributed and require two or more parties to establish a secure communication channel over an open network. Key management is one of the major security issues in such applications. A good security system should reduce more complex problems related to the proper key management and secure-saving of a little number of secret keys at every endpoint. So it is difficult to save one key secretly, and the difficulty will be more and more if the number of secret keys increased. In the literature, many schemes have been proposed for key distribution and management. Although, such schemes have reduced the number of secret keys stored at the users to only one key, Key Distribution Center (KDC), known here as Key Managing Center (KMC), still maintains a shared secret key with each user in the network. In this paper, we propose a method to reduce the number of secret keys stored at the KDC to only one key, regardless of the network size. In the proposed method, the KMC will store a unique stuff data for every user. The user's secret key will be generated by taking the stuff data, adding the lifetime of the secret key, and then hashing the resulting string using the manager secret key. The output digest will be used as the user's secret key. By this way, KMC will only store one key called the manager secret key. Furthermore, we will combine the proposed method with our previous work to build an efficient key management model. Analysis and experimental results indicate that the developed model is highly secure, practical and efficient.
Modelling and Optimization of Robotic Manipulator Mechanism for Computed Tomography Guided Medical Procedure

Although industrial robots are common, a higher degree of manipulability might be required to expand the applications of manipulators in the field of medicine. Modifying the mechanical design of a robot as per the workspace can be perceived as an optimization problem. Hence, a novel spatial manipulator is designed for a diagnostic apparatus using different optimization algorithms. Standard Genetic Algorithm (SGA) and GA (Genetic Algorithm) with hybrid functions like pattern search (PS) and fmincon are proposed to optimize the link lengths of a 3degrees of freedom (DOF), 6-DOF, and novel 9-DOF hybrid redundant manipulator. A 9-DOF robot is designed to manipulate a needle in CT machine environment. The fitness function for all the manipulators is formulated using forward kinematic equations according to their workspace. Limits and constraints of each link are decided beforehand. A comparative study between all the hybrid GA functions is performed. MATLAB is used to solve and train the proposed GA method for optimizing the link lengths. Results show that GA with PS provide better-optimized link lengths for a 3-DOF and 9-DOF manipulator while fmincon is well suited for a 6-DOF robot manipulator. Workspace and dead zone analysis is also performed using the optimized link lengths obtained.
Current Aspects of Using Artificial Intelligence in Digital Games and Computer Graphics Content Control

: The extraordinary size and influence of gaming industry on contemporary (digital) markets creates a vast pool of resources (material and abstract) that is constantly refilled and used in order to make modern digital games of all kinds and genres as attractive and performant as possible. A key component of almost every complex digital game that is developed today is its artificial intelligence module. Due to the variety of problems that can be and are solved by using artificial intelligence in digital games its functionality is practically essential. The paper describes the application of artificial intelligence methods, its implementation in the content generation process, as well as modelling the gameplay. The game design directly conditions the complexity and performance of artificial intelligence module. It should be noted that the digital games that so far used mode advanced artificial intelligence techniques had variable success, which implies that this area of application still needs to be fully defined, and that the future technological/software progress will further determine the level of freedom that game designers will have in their creativity.