Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Endoscope Design Using Spiral Technique for Robotic-Assisted Endoscopy Insertion

Gastrointestinal (GI) endoscopy is a conventional and prevalent procedure used to diagnose and treat diseases in the digestive tract. This procedure requires inserting an endoscope equipped with a camera and instruments inside a patient to the target of interest. To manoeuvre the endoscope, an endoscopist would rotate the knob at the handle to change the direction of the distal tip and apply the feeding force to advance the endoscope. However, due to the nature of the design, this often causes a looping problem during insertion making it difficult to be further advanced to the deeper section of the tract such as the transverse and ascending colon. To this end, in this paper, we propose a novel robotic endoscope which is covered by a rotating screw-like sheath and uses a spiral insertion technique to generate ’pull’ forces at the distal tip of the endoscope to facilitate insertion. The whole shaft of the endoscope can be actively rotated, providing the crawling ability from the attached spiral sheath. With the redundant control on a spring-like continuum joint, the bending tip is capable of maintaining its orientation to assist endoscope navigation. To test its functions and feasibility to address the looping problem, three experiments were carried out. The first two experiments were to analyse the kinematic of the device and test the ability of the device to hold its distal tip at different orientation angles during spiral insertion. In the third experiment, we inserted the device in the bent colon phantom to evaluate the effectiveness of the proposed design against looping when advancing through a curved section of a colon. Results show the moving ability using spiral technique and verify its potential of clinical application.
Comparison of selected psychological variables among different levels of table tennis players

Objective: The objective of the study is to know the psychological state i.e. Personality Trait and Competitive State Anxiety among State Level and University Level table tennis players. Methods: To serve the purpose of the investigation, 30 male table tennis players were selected i.e. 15 players from Madhya Pradesh State level table tennis players and 15 players from University participated levels at the age group between 19 to 24 years. The Big five Inventory Personality Traits developed by John, O. P., & Srivastava, S. (1999) and Competitive State Anxiety developed by Martens, Vealey, and Burton (1990) were used to assess the personality and state anxiety level of the selected subjects. The descriptive statistics and One Way Analysis of Variance (ANOVA) with SPSS software 20 version was also used to analyze the data at . 05 level of confidence. Results: The mean and standard deviation of the factors of personality traits of State Level and University Level players are as follows; Extraversion (24.87±4.97) & (28.07±4.43), Agreeableness (31.13±4.96) & (29.87±3.60), Conscientiousness (30.67±5.60) & (30.67±4.98), Neuroticism (22.60±5.93) & (23.40±5.14) and Openness (34.40±5.83) & (33.80±6.61). There were no significant difference was found on factors of personality trait between the two levels of players, as the calculated ‘fvalue’ of Extraversion (2.94), Agreeableness (0.01), Consciousness (0.00), Neuroticism (0.03) and Openness (0.30) were less than the tabulated ‘f-value’ (4.20). And the mean and standard deviations of state level and university levels table tennis players of Competitive State Anxiety are as follows; Cognitive State Anxiety (22.00±5.90) & (21.87±5.41), Somatic state anxiety (20.40±4.26) & (19.27±6.83) and Self-confidence (24.67±6.06) & (23.53±5.89). There were no significant difference was found on factors of Competitive Anxiety between the two levels of players, as the calculated ‘f-value’ of Cognitive state anxiety (0.00), somatic state anxiety (0.29) and Self-confidence (0.27) were less than the tabulated ‘f-value’ (4.20). Conclusion: the present study shows that the players of the state and university level have similar level of competitive state anxiety and personality trait. Further it also recommend that same study could be done with the elite level players or by increasing the sample size or comparison with the beginners to get better knowledge regarding the similarities exists in the present study.
Mapping OACs to Grounded Symbolic LDEC Plan Representations

The core focus of WP4 is the formalization of Object Action Complexes (OACs). As part of WP4.3 (Action Description Language) this deliverable reports on the translation of OACs into explicit symbolic representations, using a formal language like the Linear Dynamic Event Calculus (LDEC)
Evaluation of the Weather-Influenza Pattern  with a Regression Model Approximation to Causality

Review Article Once at a time, this author starts a research in the relations between Australia’s number of case in influenza and weather. The outcome has been hypothesised with a structural equation model (SEM). In this paper, the author tries to evaluate the model. It is true that one can apply the evaluation to both of the formative measurement model and structural model through certain suitable procedures. At the same time, this author approximates the model by linear regression method. The result is one can apply the regression to the Hayes’ Process model and find out the wanted model with mediation and moderation effects. In addition, one can also use the Granger Causality Test to examine all of the hypothesised causal relationships between those independent variables such as temperature, wettest_1, concentration of carbon dioxide, strongest wind and coolest and the number case of influenza infected etc. The final outcome is that Hayes’ model 91 is the best mediated one with carbon dioxide as the moderated factor. This author will also explain in details why we have the above prescribed Hayes’ model 91 as the proposed regression model approximation to causality from the SPSS data analysis.
Opportunities for, and limitations of, near infrared reflectance spectroscopy applications in soil analysis: a review.

Near infrared reflectance spectroscopy (NIRS) is a cost- and time-effective and environmentally friendly technique that could be an alternative to conventional soil analysis methods. In this review, we focussed on factors that hamper the potential application of NIRS in soil analysis. The reported studies differed in many aspects, including sample preparation, reference methods, spectrum acquisition and pre-treatments, and regression methods. The most significant opportunities provided by NIRS in soil analysis include its potential use in situ, the determination of various biological, chemical, and physical properties using a single spectrum per sample, and an estimated reduction of analytical cost of at least 50%. Contradictory results among studies on NIRS utilisation in soil analysis are partly related to variations in sample preparation and reference methods. The following calibration statistics appear to be most appropriate for comparing NIRS performance across soil attributes: (i) coefficient of det.
Anonymization: A Method To Protect Sensitive Data In Cloud

— Cloud computing is a model that enables Convenient and On-demand network access to a shared pool of configurable computing resources where millions of users share an infrastructure. Privacy and Security are significant obstacle that is preventing the extensive adoption of the public cloud in the Industry. Researchers have developed privacy models such as k-anonymity, l-diversity, t-closeness. However, even though these privacy models are applied, an attacker may still be able to access some confidential data if same sensitive labels are used by a group of nodes. Publishing data about individuals without revealing sensitive information about them is an important problem. Data Anonymization is a method that makes data worthless to anyone except the owner of the data. It is one of the methods for transforming the data that it prevents identification of key information from an unauthorized person. Data can also be anonymized by using techniques such as, Hashing, Hiding, Permutation, Shifting, Truncation, Prefix-preserving, Enumeration, etc. We survey the existing methods of anonymization to protect sensitive information stored in cloud.
Automated Generation of Graphs from Relational Sources to Optimise Queries for Collaborative Filtering

—Graph abstraction is an intuitive and effective approach for collaborative ﬁltering as used in, for example, recommender engines. However, for many collaborative ﬁltering applications, the transactional data is kept in a relational database and, through bespoke processes, is Exported, Transformed and Loaded (ETL) into a graph database where collaborative ﬁltering algorithms can be applied. However, the ETL process requires knowledge of the source relational database, the target graph database and the application domain. The ETL process, therefore, tends to be expensive, non-optimised for graph queries and relies heavily on application domain knowledge and understanding of the property graph engine for the graph database. In this paper, a mechanism is presented whereby data in a relational format, which is normalised to 5 th normal form, can be automatically converted to a graph database format, through an automated process. The presented evaluation demonstrates, using the recommendation engine application domain as an example, that the proposed mechanism is more efﬁcient than comparable approaches to reduce the execution time required for collaborative ﬁltering.
Routing order pickers in warehouses considering congestion and aisle width

Due to the importance of routing order pickers, there has been extensive research in the area of routing in warehouses. Still, there are some prominent factors that should receive more attention, as they may provide unsatisfactory services and incur considerable operational costs if ignored. In real-world applications, warehouse configuration, width of aisles, and controlling the vehicle congestion in the aisles greatly influence the efficiency of the routing process. Therefore, this paper proposes a mixed-integer programming model. The model aims to minimize maximum delivery time by finding the shortest pickup and delivery routes of all goods for all vehicles. Since the problem is NP-hard, a Simulated Annealing metaheuristic approach is designed to solve the model in large-size problems. This research contributes to picker routing literature by considering dynamic congestion, narrow and wide aisles, and pickup times and proposing a metaheuristic algorithm. The validation and efficiency of our proposed model are proved by solving some various generated benchmark problems. In summary, the developed route planning mathematical model works effectively for any two-dimensional rectangular layout, and the collision prevention constraints are incorporated in the mathematical model.
The Assembly of Bacteriophage Functional Enzymatic Models in Association with E. coli Proteins’ Profiles

Introduction: The invasion of bacteriophage on the associated host bacterium depends on their receptors’ orientation that adsorb them to cell surface. During phage replication a valuable number of proteins acts as lytic enzymes for host puncher at the beginning of the infection and other for burst after lytic cycle compilation. Accordingly, the proteomic relationship among phage and bacterium proteins could easily be studied by their protein profi les analysis.
Citizen science facilitates phylogenetic placement of old species of non-lichenised Pezizomycotina based on newly collected material.

1 Department of Botany, Faculty of Science, Charles University, Benátská 2, CZ-128 01 Praha 2, Czech Republic; ondrej.koukol@natur.cuni. cz 2 Václava III. 10, CZ-771 00 Olomouc, Czech Republic 3 Department of Botany, Faculty of Science, Palacký University Olomouc, Šlechtitelů 27, CZ-783 71 Olomouc, Czech Republic 4 Pezinská 14, SK-903 01 Senec, Slovakia 5 Mycological Department, National Museum, Cirkusová 1740, CZ-193 00 Praha 9, Czech Republic 6 Resslova 26, CZ-400 01 Ústí nad Labem, Czech Republic
ORGANIZATION AND CONSTRAINTS OF A RECOMMENDER SYSTEM FOR MOOCS

Recommender Systems (RSs) are software tools providing suggestions for users about items likely to be of interest for them. MOOCs (Massive Open Online Courses) offer a vast amount of learning items to millions of users. Users face a challenging task of finding the suitable learning content, learning path and peer-learners for collaborative activities. Poor selections lead to very low completion rates, typically under 10%. The paper assumes that a better decision-making process is likely to lead to a higher completion rate and discusses the organization and constraints of a Recommender Systems in a MOOCs context. As the organization of a Learning Recommender System and the choice of algorithms represent the first two architecture design criteria for meaningful results, attention is given to this factors. The paper argues that an effective Recommender System must focus on MOOCs specific type of items (learning items) and user behavior in MOOCs context and consequently, a number of particularities and constraints are identified and discussed. In this paper, the term organization is used to describe how different components work together to form a system and the term architecture is used to describe a blue-print of how to actually build such a system.
INERTIA AND CHANGE IN TRANSFORMATION OF THE IT- FUNCTION IN LARGE ORGANIZATIONS: A PATH THEORY LENS

Digitalization and digital transformation of large incumbent organizations, more often than not, require substantial changes to how the IT-function conducts and sources software development. This, however, often involves battling strong organizational and technical inertia making radical changes hard to implement. Yet, radical changes are often a prerequisite for digitally transforming the firm. In this regard, we present a longitudinal case study of a large governmental organization that over a relatively short period managed to radically change their IT-function in spite of strong inertia related to its software development methods and practices, sourcing arrangements, and legacy systems. In explaining this, the paper presents two contributions. First, we build on path theory to explain how IT organizations can develop organizational inertia in terms of path dependence related to software development methods, souring models, software delivery routines, and legacy systems. Second, we identify three interdependent mechanisms of breaking out of such path dependency: use of digital platforms for software development, attracting and securing competence, and establishment of cross-disciplinary software development teams. The paper concludes by giving some directions to further Information Systems (IS) research on this topic.
By: Vivek Koshta

The commercial sterilization of milk finds its origin from the beginning of the 20 th century derived from the work of Nicholas Appert. The continous-flow sterilizer constructed to heat milk at temperature 130 – 140 o C had been first patented in the early 20 th century. More practical solutions were developed by Jonas Nielson in 1908. (Burton, 1988). Since then, the UHT applications were adopted for market milk, cream, Pea soup, ice-cream mix, etc.( Scott, 2008). In 1957, an experiment done by Feliciotti and Esselen showed the advantage of high-temperature –short –time processing for retention of Vitamin B1 (Thiamine). Subsequently it was shown that many quality factors, including colour and flavour, show the same temperature dependence as the vitamins. (Lund, 2018). In 1961, the first commercial UHT system with aseptic packaging line was developed for milk (Robertson, 2016).
Clustering of Quantitative Survey Data based on Marking Patterns

Clustering of quantitative survey data is done in-order to identify the divergent and dominant behaviors of the respondents. It is intended to explore the general tendencies of the respondent groups. Popular clustering methods working on value based similarity are inappropriate for survey data due to its distinct properties. Since marking patterns in survey data represents respondent’s behavior, hence separating the responses on the basis of marking patterns is an effective approach to identify the dominant behaviors. Thus, in this paper, we propose a specialized clustering method for quantitative survey data that combines the features of both, value based as well as pattern based approaches in order to obtain meaningful results. The proposed method does not require presetting of the clustering parameters while it makes use of group labels for selecting features and guiding the centroids at positions, which best describe divergent marking habits. We apply the proposed method over an educational survey dataset and compare its results with K-means clustering with respect to the benchmark stakeholder theory. Comparison results show that the proposed method is more appropriate for quantitative survey data.
Detection of Dichloromethane in Superfund Sites

There are more than a thousand Superfund sites in the United States, and many of them are located near or in neighborhoods or areas prone to earthquakes, flooding, or erosion. Superfund sites are hazardous waste dumps that have been identified by the Environmental Protection Agency (EPA) as posing an unacceptable risk to human health and the health of other organisms. The EPA has identified several chemical substances present in Superfund sites, ranging from hazardous metals to harmful organic compounds. Our team decided to focus on dichloromethane (DCM), a widely used synthetic haloalkane that is present in high concentrations at a Superfund site close to our school. DCM has wide-ranging and serious health effects; it is carcinogenic, neurotoxic, and hepatotoxic. Our goal is to create a biosensor for the detection of DCM. We are utilizing synthetic biology to design a biological system that will display red fluorescence when DCM is detected. Our system uses Escherichia coli as the chassis and is composed of two connected devices: a DCM sensor and a DCM reporter. For the DCM sensor, we are using the dcmR gene, which was first identified in the genome of Methylobacterium extorquens, a methylotrophic bacterium capable of degrading DCM. The dcmR gene, which is regulated by a constitutive promoter, produces the DcmR protein, a transcriptional repressor for the Red Fluorescent Protein (RFP) gene. When DCM is present in the samples tested, it will bind to the DcmR protein and change its conformation, derepressing the RFP gene and triggering visible red fluorescence. We are adding a tuner in order to link the intensity of the red fluorescence to the varying DCM concentration. Compared with the conventional analytical methods for DCM detection, this biological system provides an inexpensive and easy-to-use DCM biosensor for testing water and soil samples from Superfund sites.
Literature Survey: Text Segmentation

Text Segmentation is an application of Natural Language Processing used for splitting a piece of text into small meaningful paragraphs. Since it is hard to deﬁne criteria on which the segmentation can be done, researchers have come up with many approaches. Discourse phenomena, Cohesion and Coherence are ma-jorly used to detect potential positions in text. But there are works that utilize patterns for text segmentation. This report is a brief introduction to the major works in the ﬁeld of text segmentation.
Intermittent Transport and Relaxation Oscillations of Nonlinear Reduced Models for Fusion Plasmas

Generation of sheared flows and their effects on turbulent transport are studied for ion temperature gradient (ITG) driven instability and resistive drift instability. With the use of low degree-of-freedom models as well as the full partial differential equation (PDE) models, the minimum mode structures have been identified that are required for the generation of intermittent transport and relaxation oscillations. Generation of turbulence due to magnetohydrodynamic (MHD) instabilities and their roles in the control of stellarator and tokamak plasmas are also discussed.
On the Performance Analysis of Full-Duplex Incremental Cooperative NOMA

—A full-duplex incremental cooperative non-orthogonal multiple access (FD-ICN) scheme is proposed for a two user downlink network. Based on a pilot signal from the far user, the base station decides between transmitting in direct transmission mode or using cooperation via the near user. We evaluate the proposed scheme in terms of the pair outage probability, in order to guarantee a feasible service for both users. The results show that the proposed scheme presents better performance in terms of outage probability, when compared with the half-duplex incremental cooperative non-orthogonal multiple access scheme as well as with the conventional cooperative non-orthogonal multiple access schemes.
Development of the Scheme of the Installation for Mechanical Wastewater Treatment

The paper presents the schemes of various equipment for the mechanical treatment of the industrial and domestic wastewater, which allows removing it from the main part of the pollution. An examination of the shortcomings of the known equipment with the aim of its improvement was conducted. As a result, an installation scheme for continuous high-performance mechanical wastewater treatment was proposed. In contrast to the known equipment, the proposed installation provides a three-staged treatment of wastewater with the help of the two pairs of gratings – for preliminary treatment (removal of large-size pollutions) and by filtration through the two metallic sieves – for normal and fine treatment (removal of small-size mechanical pollutions). The installation consists of highly-efficient appliances for the cleaning of filtering elements in the course of realization of the working process, which provides stable high productivity of treatment. The installation has simple reliable design and low energy expenses. The paper contains the formulas for determining of main operational parameters of the installation: the change of the cross-sectional area of the filtering elements and productivity of the working process, periodicity of cleaning of gratings and sieves, the necessary electric power of installations drives. These formulas can be a basis for further research of installation and for elaboration of a method of its design calculation.
I Want It, Too: A Correlational Study on the Link Between Youth Celebrity Idolization and Materialism

Online social media usage among youth has been on the rise, and concerns about its impact have accompanied it (O'Keeffe & Clarke-Pearson, 2011; Rideout, 2018). Upon reviewing the existing literature, it appears that a multitude of studies detail the negative internal and interpersonal effects of materialism, and others assert that advertising viewing is positively correlated with materialism. However, few studies directly focus on advertisements with celebrity product endorsement in particular. This study attempted to bridge these various gaps through the following research question: In 2020, how does the viewing of Instagram celebrity product endorsement correspond with levels of materialism (with a focus on its relationship to well-being and generosity) in middle schoolers in Southern California? Quantitative data from a cross-sectional survey led to the conclusion that the level of celebrity idolization was the most conclusive factor in determining the middle schooler’s final level of materialism. And the more time spent on Instagram–and likely, the more exposure to this type of advertising–the more materialistic and less generous students were. Thus, students feeling particularly detached from their values may consider scrutinizing their list of followed celebrities on social media. The discouragement of celebrity idolization is expected to decrease materialism.