Miracle-dz/UniFAR-FTUs huggingface dataset:
Segmentation of Moving Objects using Cue Integration

The ability to extract independently moving objects in a video is an essential requirement for a vision system to be able to learn about objects in an unsupervised manner. But the focus of most motion segmentation algorithms has been to group pixels with similar motion characteristics into regions, and usually ignore static cues. In this paper we pro-pose a segmentation process that will extract, using both dynamic and static visual cues, only the regions corresponding to the moving objects. Instead of grouping pixels into regions, the proposed process groups edge pixels into the closed boundaries of the moving objects in the video. The grouping of the edge pixels is accomplished using [16] that ﬁnds the closed boundary around a given point in an image without being affected by the size of the boundary. We propose a strategy to select the points inside the moving objects and use [16] to generate closed boundaries for the selected points. Following segmentation, a novel process selects a subset of the closed boundaries corresponding to the moving objects. We evaluate quantitatively the performance of our proposed system in extracting moving objects from videos and the results show its usefulness in generating the closed boundaries (or regions) for high-level visual processing such as object recognition.
A MECHANISTIC INSIGHT OF NATURAL PRODUCTS FOR ECZEMA TREATMENT (PART I)

Eczema is termed as a chronic relapsing atopic dermatitis which is a chronic, inflammatory dermatosis mediated by immune system and is characterized by Thelper 2 immune response phenotype. Eczema is associated with disturbance in sleep and it also affects the quality of life. Emollient, antimicrobial agents, corticosteroid or immune-modulating agents are used for treatment of eczema. Pathogenesis of eczema involves complex interactions between susceptible genes, immunological factor, defects in skin barriers, neuro-endocrine factors and factors related to environment like change in weather, food and aeroallergens. Because there is no cure till date for eczema, Chinese medicines which are part of dietary therapies are being adopted by the Asian patients. In the treatment of skin disorders and wounds a tremendous role has been played by Herbal extracts and isolated plant compounds. Recently a lot of new herbal drugs have been developed that were tested in controlled clinical or preclinical studies. St. John’s wort, licorice, tormentil, bitter substances, evening primrose and many more biomedicines, topical agents: coconut oil, colloidal oatmeal, sunflower oil, mustard oil, glycerin, and oral Chinese herbal therapy are used to treat AD. Probiotics, and vitamins are also used as oral agents in treatment of AD and all these bioagents have shown good results in treatment of atopic dermatitis. Wind, dampness and heat are the three main pathogenic factors of eczema. Various Chinese herb such as cortex moutan radix (danpi), radix paeoniae alba (bai shao), potentilla chinensis ser (weilingcai) and radix glycyrrhizae (gan cao) are common treatments for eczema allergy. It is being indicated in pharmacological studies that these herbs have anti-allergic, anti-inflammatory and sedative action for itchiness. These studied medicinal plants were found to be effective in eczema therapy, further mechanistic and clinical studies are required to establish this claim.
Full Research Paper Classification of Parus strawberry fruit by combining image processing techniques and intelligent methods

Nowadays, in modern agriculture, the combination of image processing techniques and intelligent methods has been used to replace humans by smart machine. There is no international or domestic standard classification for Parus variety. In this study, an artificial image processing and artificial neural network (ANN) method was used to classify strawberry fruit of Parus variety. In the first step, the fruit was divided into 6 classes (ANN outputs) by the expert, and 100 samples were randomly collected from each class. In the next step, the images of the samples were captured and three geometric properties with twelve color properties (as ANN inputs) were extracted. Morphological and color characteristics of the area of the fruit were extracted using the functions defined in Matlab software. Optimum artificial neural network structures (15-18-6) considering root mean squared error (RMSE) and correlation coefficient (R 2 ) were investigated to classifiy the strawberry samples. Finally, the perceptron neural network with a structure of 6-18-15 was selected with the classification rate of 83.83%. The results obtained by ANN showed that the lowest and highest accuracy was related to small ripe (about 65%) and small raw (about 100%). Based on the accuracy of the results and economic aspects, ANN method is considered a proper method to classify strawberry fruit.
Spherical World in Miniature: Exploring the Tiny Planets Metaphor for Discrete Locomotion in Virtual Reality

We explore the concept of a Spherical World in Miniature (SWIM) for discrete locomotion in Virtual Reality (VR). A SWIM wraps a planar WIM around a physically embodied sphere and thereby implements the metaphor of a tangible Tiny Planet that can be rotated and moved, enabling scrolling, scaling, and avatar teleportation. The scaling factor is set according to the sphere's distance from the head-mounted display (HMD), while rotation moves the current viewing window. Teleportation is triggered with a dwell time when looking at the sphere and keeping it still. In a lab study (N=20), we compare our SWIM implementation to a planar WIM with an established VR controller technique using physical buttons. We test both concepts in a navigation task and also investigate the effects of two different screen sizes. Our results show that the SWIM, despite its less direct geometrical transformation, performed superior in most evaluations. It outperformed the planar WIM not only in terms of task completion time (TCT) and accuracy but also in subjective ratings.
Clinical Radiology 3-Tesla Magnetic Resonance Imaging and Computed Tomography accurately identify T3c disease in colon cancer

Abstract: Aim: To compare the preoperative staging accuracy of CT and 3T MRI in colon cancer, and to investigate the prognostic significance of identified risk factors. Materials and methods: 58 patients undergoing primary resection of their colon cancer were prospectively recruited, with 53 patients included for final analysis. Accuracy of CT and MRI were compared for two readers, using postoperative histology as the gold standard. Patients were followed-up for a median of 39 months. Risk factors were compared by modality and reader in terms of metachronous metastases and DFS, stratified for adjuvant chemotherapy. Results: Accuracy for the identification of T3c+ disease was non-significantly greater on MRI (75% and 79%) than CT (70% and 77%). Differences in the accuracy of MRI and CT for identification of T3+ disease (MRI 75% and 57%, CT 72% and 66%) and N+ disease (MRI 62% and 63%, CT 62% and 56%) were also non-significant. Identification of EMVI+ disease was significantly greater on MRI (75% and 75%) than CT (79% and 54%) for one reader (p=0.029). T3c+ disease on histopathology was the only risk factor which demonstrated a significant difference in rate of metachronous metastases (OR 8.6, p=0.0044) and DFS stratified for adjuvant therapy (OR 4, p=0.048). Conclusion: T3c or greater disease is the strongest risk factor for predicting DFS in colon cancer,
An occurrence of avian malaria in domestic pigeons in Tamil Nadu, India

Plasmodium relictum is an invasive blood protozoan, which causes malaria in various species of birds worldwide and often leads to heavy mortality in naive birds. The aim of this study is to report the occurrence of P. relictum in the domestic pigeons with flock size of 150 birds and its gross pathological features in the various organs of the affected birds. Postmortem changes in dead birds showed enlargement and discoloration of the liver, serofibrinous pericarditis, hazy air sacs and swollen congested Kidneys. Organ impressions revealed various stages of P. relictum. This study concludes the first report of occurrence of P. relictum in domestic pigeons of Tamil Nadu.
Development of selective Inhibitors of crucial drug target Phosphoethanolamine methyltransferase of Plasmodium falciparum based on Chemo informatics and in vitro experiments

The chemo informatics and simulation approaches are highly preferred to develop drug candidate, applied in the study to develop a combinatorial library to meet, the need of new potent antimalarial. Combinatorial library was developed based on information of competitive inhibitors of Plasmodium falciparum phosphoethanolamine methyltransferase essential for membrane development for rapid multiplication of parasite. Combinatorial library was developed using LeadGrow (vLifeMDS4.6 software) by replacing the substitution sites (R1 and R2) with different aromatic and hetero-aromatic rings, and R3 with Oxygen and Sulfur. Library was screened based on druglike properties, ADMET using Discovery Studio 3.2 and also binding affinity from Schrodinger v9.6. The best scored analogs were got synthesized for in vitro testing. The thermodynamic stability was studied through dynamic simulation using Desmond. Among the druglike analogs aromatic (benzoic acid) ring at R1interacted through one hydrogen bond acceptor and donor. At position R2 hetero aromatic rings (Pyrimidine, Pyrazine and Imidazole) containing two hetero atoms could score better, actively participated in non-covalent interactions within the binding site. All the synthesized three analogs showed Schizonticidal and gametocidal activity but Comp.1 could show better IC50 3.4 μM and LD50 192. 91μM with ten folds higher (56.73) selectivity index. Comp.1 inhibited protein with EC50 2.1 μM was also found thermodynamically stable till 30ns.The Comp.1 has better affinity and drug-score as well; it may have the possibilities of potent antimalarial. In-vitro observations and the thermodynamic stability of Comp.1inhibitor also established the target (PfPMT) specificity. Hence; theComp.1 may further be optimized and validated for being potent antimalarial candidate. Identified Comp.1 and other two analogs may also further be served as lead for further rational drug designing for more potent antimalarial.
Project of PhD thesis in Computer Science: “Learning clinical decision processes from EHR: application to common condition diagnosis”

A clinical guideline (or CPG for Clinical Practice Guideline) is a document with the aim of guiding decisions and criteria regarding diagnosis, management, and treatment in specific areas of healthcare. In the case of diagnostics, guidelines may have the form of an algorithm with a set of questions to answer to be able to diagnose a patient with a specific condition. Classically, guidelines were established based on the medical literature, expert consensus, but also evidence from molecular biology or data-driven studies such as randomized clinical trials or observational studies. However, CPG are rarely available in machine-actionable forms that would allow their integration in decision support systems and then provide recommendations along the care flow. Previous works developed formal representation of clinical guidelines, such as those done with the GLIF3 standard to produce what is named Computer-Interpretable Guidelines (or CIGs) [2, 12]. These CIGs may be obtained manually, following for instance cognitive approaches involving either medical expert, knowledge engineer or both [13]; or obtained partially automatically from narrative guidelines or the medical literature [16, 15, 11]. So far, only a few works have focused on data-driven approaches that would learn CIGs from patient data. Most of them rely on unsupervised approaches, such as process mining [5], or sequence mining [3, 18] that were leveraged to learn
Tcl in the Middle

Tcl has long been recognized as an excellent language to glue existing components together to create new applications. Tcl is just as useful when interjected into the middle of functioning N-tier “enterprise” systems. SockSpy[1] is probably the best known[2] example of a “man in the middle” Tcl application. What may not be as widely appreciated, however, is that Tcl's strong TCP sockets and event-driveI/Omakeconstructionofcustom“maninthemiddlesolutions”(orproxies)quitestraight-forward. These custom solutions solve real business problems often at a fraction of the cost of other potential solutions. This paper will look at a handful of examples where Tcl has been employed in this manner at Intermountain Healthcare.
Locally Varying Hubble Parameter in Terms of Reduced Friedmann Equation

Assessment of the Hubble parameter as an indicator of the expansion rate of the universe holds a central position in the field of astronomy. From its initial estimate of about 500 km⋅sec-1⋅parsc-1, this value had been steadily amended as the observational tools became more accurate and precise. Despite this, a gap remains between the value of observations relating to local and nonlocal estimations of the Hubble parameter that gave rise to what became known as the Hubble tension. This tension is addressed here while dealing with space fabric as a cosmological fluid that undergoes transition.
Shifting Paradigms in Islamic Higher Education in Europe: The Case Study of Leiden University

slamic higher education finds itself at the cross-roads of a variety of developments: it oscillates between the ‘teaching into’ approach of Theology and the ‘teaching about’ approach of Religious Studies, between the security-driven need for a ‘European Islam’ and a European Muslim-driven need for a high-quality education in ‘Islam in Europe’, between traditional one-way knowledge dissemination and innovative two-way knowledge sharing, and between Islam as defined and discussed by scholars and Islam as defined and discussed by the public. This myriad of dynamics is challenging and a source of tensions among all parties involved, in particular between lecturers and students. In this article, a qualitative self-study research based on personal experiences with various Islamic higher education programs at Leiden University will be used to reflect on the broader developments in Islamic higher education programs in Europe. It argues that thinking about Islamic higher education is not a process of finding solutions to problems but is a process of educational opportunities and innovation.
Measuring Conference Attendees’ Satisfaction: An Insight from Libya

Background and objectives: Even with the widespread repetition of organizing events and conferences by hosting organizations, little is known about the influence of such meeting on attendee’s satisfaction. However, up to our knowledge, there is no exploratory survey measured the satisfaction of conference attendees in Libya. Hence, this study sought to reveal the that impact of the effectiveness of conference messages on the attendee's satisfaction. Methods: A self-report survey designed to assess satisfaction with conference attributes was completed by 78 attendees following their participation in the 3rd Libyan conference on medical and pharmaceutical sciences held in Libya. The questionnaires were circulated through personal contact with respondents at the conference. Results: Based on data analysis, the lowest mean values ranging between “Poor satisfaction” and “fair” (from 2.8 to 3.4) have the attributes: networking, venue of the conference, and the new knowledge. Furthermore, the highest rating was assigned to the conference organization and quality of service, technical support, and conference program. Generally, it is obvious that the attendees are not completely satisfied with the conference in general and specifically with some conference attributes, which are related to the networking and the conference venue. Conclusion: The results of this study suggest that the organizer should pay more attention to the venue selection process, as it affects overall quality of the conference. Further comparable studies, regarding conference satisfaction should be conducted in other conference venues and settings in Libya, in order to raise the quality of services destination attractiveness.
A Model of Antecedents of Knolwege Sharing

This paper looks at how organisations can become more sophisticated at supporting knowledge sharing, by identifying antecedents of knowledge sharing. The paper contributes to the literature in two ways: it develops a comprehensive model of antecedents of knowledge sharing that differentiates between three categories of antecedents: people infrastructure, organisational infrastructure and knowledge values. Secondly, the paper examines the relationship between perception of knowledge ownership and knowledge sharing in light of all other variables. The paper represents work in progress. The final version of the proposed model will be tested in technology parks in Australia and Malaysia.
Electronic Properties of Graphene Ribbons and Their Adducts Using Density Function Theory

In this research, we study the electronic properties of two pure graphene ribbon and their adducts by adding the Al / N compound. We showed that the electronic softness of the pure Graphene Ribbon was increased with increasing the thickness of the Ribbon, adding the Al / N atoms leads to decrease the electronic softness. The electrochemical hardness has inversely behavior to the softness. Increasing the thickness of the Graphene Ribbon leads to decrease the forbidden energy gap of the Ribbon, but the energy gap is increase due to the addition of the Al / N atoms in the Ribbon
Salivary Electrolytes in Patients with Periodontal Disease.

It is well known that periodontal disease is among others consequence of bacterial invasion of the host periodontal tissues. Saliva has an important role in antibacterial defence within oral cavity and even further on. Some of these antibacterial activities are probably dependent on certain salivary electrolytes such as copper, magnesium, etc. Therefore the aim of this study was to determine levels of salivary phosphate, copper, chloride, potassium and sodium in subjects with and without periodontal disease in order to explore its potential diagnostic implications. This study included 35 patients with periodontal disease and 41 controls. The levels of sodium, potassium and chloride were determined by indirect potentiometry, copper was determined by atomic absorption spectrophotometry, and levels of magnesium were determined by spectrophotometric method with xylidil blue. Parametric statistics was used for data analysis. No significant difference in any of the measured periodontal clinical parameters was found between patients with chronic and aggressive periodontitis. No significant difference in salivary phosphate, sodium, potassium, and chloride between patients and controls were found. Conclusions: Patients with periodontitis had significantly higher salivary copper concentration compared to the control group which might reflect either increased antimicrobial activity or ineffective enzymatic activity various copper containing enzymes.
Long Noncoding RNA ENST00000581794.1 in Peripher- al Blood Mononuclear Cells Acts as a Novel Biomarker in Patients with Acute Myocardial Infarction

The aim of this investigation is to investigate the long noncoding ribonucleic acid and mRNA expression profiles of acute myocardial infarction patients and matched healthy controls particularly the higherranked long noncoding ribonucleic acid ENST00000581794.1 in co-expression. This study group found that ENST00000581794.1 was up-regulated in acute myocardial infarction patients in pre-experiment. It is suggested that ENST00000581794.1 may be a potential biomarker of acute myocardial infarction. Fifty eight patients with acute myocardial infarction and 58 healthy controls were included in this study from September 2017 to February 2018. Venous blood samples were collected from patients within 6 h from the onset of chest pain and RT-qPCR measured the expression levels of long noncoding ribonucleic acid in peripheral blood mononuclear cells. All patients were followed for 12±1 mo. The expression levels of ENST00000581794.1 were significantly different between the two groups. The receiver operating characteristic curve showed that long noncoding ribonucleic acid ENST00000581794.1 (area under the curve = 0.744, 95 % confidence interval: 0.61~0.88, p=0.004) had a predictive effect on major adverse cardiovascular events. Survival curve analysis demonstrated that the incidence of major adverse cardiovascular events became significantly higher in patients with high expression of ENST00000581794.1 as the observation time increased. Multivariate regression analysis indicated that ENST00000581794.1 was an independent predictor of major adverse cardiovascular events in patients with acute myocardial infarction (hazard ratio: 1.17, 95 % confidence interval: 1.00~1.37, p=0.048). Highly expressed ENST00000581794.1 in peripheral blood mononuclear cells may be used as a biomarker for diagnosis and prognosis of acute myocardial infarction.
The Index of Cognitive Activity Predicts Cognitive Processing Load in Linguistic Task

The Index of Cognitive Activity (ICA) has been shown to index cognitive processing load in language processing tasks in previous work. However, the effect has so far only been shown as an aggregate effect across many subjects and trials. The feasibility and reliability of using ICA as a predictor of language-related cognitive processing load in a single-trial setting have not yet been assessed. Therefore, in this study, we compare the single-trial performance of various classification models, including Support Vector Machine (SVM), k-Nearest Neighbors (k-NN), Random Forest, and Gradient Boosting on two sentence-reading experiments. These algorithms were trained on ICA values to predict semantic and syntactic violations of the sentences read by the participants. The results showed that all trained classifiers performed above the 50% chance level. Of these classifiers, Gradient Boosting showed the best performance with an accuracy of 74.48% for semantic violation detection and 71.61% for syntactic violation detection, respectively. Our results indicate that the ICA is a viable measure for detecting cognitive processing load caused by language violation on a single-trial basis.