Miracle-dz/UniFAR-FTUs huggingface dataset:
PTGS2 Over-Expression: A Colorectal Carcinoma Initiator not an Invasive Factor.

Background Cyclooxygenase-2 (COX-2) main product is Prostaglandin E2 (PGE2) which cause mitogenesis and inflammation. COX-2 is the product of prostaglandin-endoperoxide synthase 2 (PTGS2) gene expression. COX-2 dysregulation can cause angiogenesis, differentiation, and promotion of cancer and its suppression related to control of the tumor's size, number, and cell shape. This study focused on the association of COX-2 expression with colorectal carcinoma (CRC) among Iranian patients on mRNA level and in the Cancer Genome Atlas Program (TCGA) colon and rectum RNAseq dataset, and its relation with pathological features. Methods PTGS2 expression was assayed by quantitative-PCR method from 90 tissue samples collected from 45 participants. The control samples come from the non-tumor area of the same patients. The data analyzed based on ΔΔCq. The PTGS2-RNAseq data extracted and analyzed by UCSC Xena browser, and its association assessed the occurrence of CRC and invasive-features. Results PTGS2 showed very significant over-expression in tumor tissues (p< 0.0001) with an N-fold expression of 2.25. But, there was not any significant association between PTGS2 and CRC invasive-pathological features such as Lymphatic, vascular and perineural invasion, the Grades of cancer, and Pathologic-M in both parts of this study. Conclusion The increase in PTGS2 is related to the occurrence of CRC among patient samples. But in both part of this study, PTGS2 is not an invasive factor, and it does not affect the cell differentiation of tumors and metastasis. Based on the high N-fold for patient samples, it can be a strong candidate as a CRC initiator biomarker.
Development of an Intelligent Decision Support System for Smart Viticulture

 Abstract — The Internet of Things (IoT) represents the best option for smart vineyard applications, even if it is necessary to integrate the technologies required for the development. This article is based on the research and the results obtained in the DISAVIT project. For Smart Agriculture, the project aims to provide a trustworthy, intelligent, integrated vineyard management solution that is based on the IoT. To have interoperability through the use of a multiprotocol technology (being the future connected wireless IoT) it is necessary to adopt an agnostic approach, providing a reliable environment to address cyber security, IoT-based threats and traceability through blockchain-based design, but also creating a concept for long-term implementations (modular, scalable). The ones described above represent the main innovative technical aspects of this project. The DISAVIT project studies and promotes the incorporation of better management tools based on objective data-based decisions, which are necessary for agriculture adapted and more resistant to climate change. It also exploits the opportunities generated by the digital services market for smart agriculture management stakeholders. The project's final result aims to improve decision-making, performance, and viticulturally infrastructure and increase real-time data accuracy and interoperability. Innovative aspects such as end-to-end solutions, adaptability, scalability, security and traceability, place our product in a favorable situation over competitors. None of the solutions in the market meet every one of these requirements by a unique product being innovative.
Multichannel 3D Microphone Arrays: A Review

Along with the recent advance of multichannel 3D audio technologies, a number of new microphone techniques for 3D sound recording have been proposed over the years. To choose a technique that is most suitable for the intended goal of a recording, it is first necessary to understand the design principles, pros, and cons of different techniques. This paper first categorizes existing 3D microphone arrays according to their physical configurations, design philosophies, and purposes, followed by an overview of each array. Studies that have subjectively or objectively evaluated different microphone arrays are also reviewed. Different approaches in the configuration of upper microphone layer are discussed, aiming to provide theoretical and practical insights into how they can contribute to creating an immersive auditory experience. Finally, limitations of previous studies and future research topics in 3D sound recording are identified.
Machine Learning in Artificial Intelligence

Machine Learning is the core argument and artificial aspect classification of problem learning and decision making. Scientists therefore introduce machine learning, often used in the artificial mind. A significant method to automate a wide variety of activity like human brain is the artificial intelligence preparation framework. Machine Learning techniques require a planning program to gain search control of information for different applications automatically. Machine Learning plays an important role in the field of robotics. It contributes to decision-making and improves machine efficiency. Machine learning is applied in a large amount of application. It is the principle concept of intelligence system that helps to introduce artificial intelligence ingeniously and it also make artificial intelligence very advanced.
AN INVESTIGATION OF BRUCELLOSIS KNOWLEDGE, ATTITUDE AND PRACTICE AMONG LIVESTOCK (SHEEP AND GOAT) OWNERS IN WEST BANK PART OF PALESTINE

Brucellosis is endemic in Palestine and therefore since 1998 a national program of brucellosis control has been launched. In the traditional breeding area of small ruminants, brucellosis is often reported in humans, mainly as a food borne disease. Any control strategy requires a well-functioning surveillance system, the co-operation with owners and a sustainable financial support. The aim of this study is sizing up of the current situation of knowledge, of the attitude and practice (KAP) regarding brucellosis, among sheep and goat farmers. A cross-sectional survey was conducted in 118 participants through an anonymous questionnaire to assess to which extent the flock owners are familiar with the knowledge and practices related to brucellosis of small ruminants. The designs of the questionnaire consider the implementation of KAP. Results shown that farmers, independent on their education, heard about brucellosis (100%) and all of them consider the washing of hands as necessary after close contact with animals or their products, and animal vaccination as being necessary to prevent brucellosis. Despite the educational level, almost all owners are aware about the risk of exposure of their family to animals infected with Brucella: they are considering the heating of cheese at boiling point and the use of gloves, as appropriate practices to reduce the exposure to Brucella. Great majorities of the participants (89.8%) have good knowledge about the transmission of Brucella from animals to humans, but only 37.3% correctly answered about the transmission of brucellosis by drinking raw milk, eating unpasteurized cheese, eating raw meat, liver, spleen and kidney or by contact with an aborted foetus and placenta fluid. Referring to the brucellosis’ prevention, 83% answered that boiling of milk and cheese and wearing of gloves when handling an aborted foetus could prevent it: these answers fit with the level of knowledge. From the questioned owners, 28.8% knew that boiling the milk affect his nutritive value; 84.7% think that owners of animals and their families are more exposed to brucellosis and 11.9% of their families have been diseased. Relative good general knowledge of owners about brucellosis was recorded, but high-risk behaviors still exist. Awareness campaigns on the control and prevention of the brucellosis are success stories, and government agencies should continue the public education. UDC Classification: 614.9; DOI: http://dx.doi. org/10.12955/cbup.v5. 1068
The Role of Total Antioxidant Status in Cerebral Vasoreactivity of Chronic Obstructive Pulmonary Disease Patients

Introduction: Chronic obstructive pulmonary disease (COPD) is associated with an oxidant-antioxidant imbalance. COPD patients have impaired cerebral vasoreactivity (CVR). Impaired CVR could be correlated with total antioxidant status (TAS) in plasma. Aim: Determine the role of systemic TAS in CVR of COPD patients. Materials and Methods: In this cross-sectional observational study, we included 120 participants (mean age 67±7.9, 87 males), 90 COPD patients divided according to airway limitation severity in mild, moderate, severe/very severe and 30 age and sex-matched controls. We analyzed baseline mean flow velocities (MFV) of middle cerebral artery (MCA) and basilar artery (BA), mean breath-holding index (BHI m ) of those arteries (BHI m MCA and BHI m BA) by transcranial Doppler ultrasound and TAS in plasma. The level of significance was set to α=0.05. Results: In COPD, we found a significant negative correlation between TAS and BHI m BA (Rho=−0.327, P=0.002). In mild COPD we found a significant negative correlation between TAS and BHI m BA (Rho=−0.445, P=0.01). In COPD, baseline MFV BA is in a significant positive correlation with BHI m MCA and BHI m BA (Rho=0.336, P=0.001 and Rho=0.647, P<0.001). In COPD, we found a significant positive correlation between baseline MFV BA and BHI m BA: in mild (Rho = 0.731, P<0.001), moderate (Rho=0.574, P=0.001) and severe/very severe (Rho=0.398, P=0.03). Conclusions: Systemic TAS was not correlated with the CVR in all COPD groups. However, perfusion in BA of COPD was in a significant positive correlation with the anterior and posterior CVR. The analysis of perfusion in the basal cerebral arteries should be part of a future study of CVR in COPD patients.
Long Short-Term Session Search: Joint Personalized Reranking and Next Query Prediction

DR and next query prediction (NQP) are two core tasks in session search. They are often driven by the same search intent and, hence, it is natural to jointly optimize both tasks. So far, most models proposed for jointly optimizing document reranking (DR) and NQP have focused on users’ short-term intent in an ongoing search session. Because of this limitation, these models fail to account for users’ long-term intent as captured in their historical search sessions. In contrast, we consider a personalized mechanism for learning a user’s profile from their long-term and short-term behavior to simultaneously enhance the performance of DR and NQP in an ongoing search session. We propose a personalized session search model, called Long short-term session search, Network (LostNet), that jointly learns to rerank documents for the current query and predict the next query. LostNet consists of three modules: The hierarchical session-based attention mechanism tracks the fine-grained short-term intent in an ongoing session. The personalized multi-hop memory network tracks a user’s dynamic profile information from their prior search sessions so as to infer their personal search intent. Jointly learning of DR and NQP is aimed at simultaneously reranking documents and predicting the next query based on outputs from the above two modules. We conduct experiments on two large-scale session search benchmark datasets. The results show that LostNet achieves significant improvements over state-of-the-art baselines.
Inactivation of Bacillus Spores by Ultraviolet or Gamma Radiation

Bacillus anthracis spores represent an important bioterrorism agent that can be dispersed in air or water. Existing decontamination practices based on these spores have focused on chemical disinfectants; however, the basic characteristics of radiation-based disinfectants suggest potential advantages in their application for control of Bacillus spores. Experiments were conducted to examine the effectiveness of ultraviolet ( UV254 ) radiation and γ radiation for inactivation of Bacillus spores. Spores of Bacillus cereus were used for most experiments because of their similarity to B. anthracis. A limited number of experiments were also conducted using B. anthracis Sterne spores. In aqueous suspension, B. anthracis Sterne spores were observed to be slightly more resistant to UV254 than the spores of B. cereus. For the conditions of culture and assay used in these experiments, both spore types were more sensitive to UV254 radiation in aqueous suspension than the spores of B. subtilis, which are commonly used .
Expression of Endothelial Protein C Receptor in Prostate Cancer

Prostate cancer is the second leading cause of cancer deaths in men in the United States (Siegel 2019). This honors thesis quantified the expression of Endothelial Protein C Receptor (EPCR) in the serum of patients with varying stages of prostate cancer and determined its expression in the prostate cancer cell line, PC3. EPCR and its ligand, protein C, play an important role in the anticoagulation cascade that prevents thrombosis from occurring at the sight of a vascular injury (Esmon 1992). Previous research regarding tumor metastasis and the coagulation cascade in ovarian cancer has shown that there is also an association between the expression of EPCR and the metastasis of cancer cells, as cells that expressed EPCR were more prone to survive, divide, and eventually become metastatic (Ducros et al. 2012). The expression of EPCR on breast tumor cells promotes their metastasis by activating the cytoprotective mechanisms of Activated Protein C (APC) and allowing them to invade the circulatory system and avoid immune detection by the host organism (Griffin 2012). Researchers have investigated the use of EPCR concentration in patient serum samples and in ovarian cancer cell lines as a potential biomarker for ovarian cancer. These researchers found that there was a correlation between the stage of ovarian cancer and the concentration of EPCR found in the patient serum (Ducros et al. 2012). Since previous research has shown that EPCR is expressed in breast cancer and ovarian cancer cells, this study investigated if EPCR is also present in prostate cancer cells. The expression of EPCR in serum samples may be used to confirm the diagnosis of prostate cancer and may also be used to determine the stage of prostate cancer. EPCR expression
SARS-CoV-2 specific immune-signature in direct contacts of COVID-19 cases protect them from contracting disease: A Retrospective Study

The response to SARS-CoV-2 is largely impacted by the level of exposure and the status of immunity. The nature of protection shown by direct contacts of COVID-19 positive patients is quite intriguing to note. We aimed to study the immune differences reinforcing contact individuals in circumventing the disease. Our observation showed direct contacts of PCR positive patients developed elevated neutralizing antibody titres and cytokine levels. On the other hand, single cell data revealed differential usage of V(D)J genes and unique BCR clonotypes imparting protective immune signatures.
Analysis of Machine Learning in Intrusion Detection Systems The Machine Learning Approach to Detecting Cyber Intrusions

With the rapid expansion of computers and the networks connecting them, there has been an equally rapid need for security. Intrusion detection systems (IDS) are an integral part of keeping computer systems secure. IDS help administrators keep tabs on unusual activity on a network or device. The problem with IDS, in their current state, is they are not able to adapt to the constantly growing networks and the changing world of malicious activity. With the introduction of machine learning in IDS it may be possible for these systems to be more accurate, efficient, and flexible, allowing them to catch new and unforeseen attacks. With implementing new technologies come new challenges, especially with developing an accurate and dynamic IDS. This paper presents a brief introduction into this topic, including the NSL-KDD Dataset, a comparison and analysis of machine learning techniques applied to IDS, a preliminary attempt to make an intelligent IDS, and a look at the current commercial market.
Preparation of Long-Chain Fatty Acyl-Grafted Chitosan in an Ionic Liquid and Their Self-Assembled Micelles in Water

Controllable synthesis of self-associating lauroyl-grafted chitosan with high molecular weight was realized in ionic liquid reacting media. The obtained lauroyl chitosan with different grafting degrees was characterized by FT-IR and 1H-NMR spectra. The chitosan derivatives were able to self-assemble into spherical polymeric micelles in water. The onset of micellization or critical micelle concentration (CMC) was estimated by fluorescence spectroscopy. The hydrodynamic diameters of various lauroyl chitosan micelles, determined by dynamic light scattering, were in the range of 122–295 nm. The morphology of the micelles was observed by scanning electron microscopy. The self-assembly behavior and the size of the assembled micelles of lauroyl chitosan were affected by the grafting degree of lauroyl groups. Generally, higher grafting degree resulted in lower CMC and smaller micelle size. These lauroyl chitosan nano-micelles may have potential applications in biological and medical fields.
Concomitant effects of late fetal growth restriction and intra-cytoplasmatic sperm injection on fetal cardiac remodelling: a case report

3Prenatal Cardiology Division of work: Vita Zidere (ORCID: 0000-0001-7505-6621): research concept and design, collection and/or assembly of data, data analysis and interpretation, writing the article, critical revision of the article, final approval of the article Trisha Vigneswaran (ORCID: 0000-0002-4084-4203): research concept and design, collection and/or assembly of data, data analysis and interpretation, writing the article, critical revision of the article, final approval of the article David F.A. Lloyd (ORCID iD: 0000-0003-1759-6106): data analysis and interpretation, critical revision of the article, final approval of the article Meekai To (ORCID: 0000-0001-6568-9193): collection and/or assembly of data, critical revision of the article, final approval of the article Kuberan Pushparajah (ORCID: 0000-0003-1541-1155): collection and/or assembly of data, data analysis and interpretation, critical revision of the article, final approval of article Conal Austin (ORCID: 0000-0003-4417-7310): collection and/or assembly of data, critical revision of the article, final approval of the article Figure 3. Surgical approach via a medium sternotomy with the patient on cardiopulmonary bypass is shown. The forceps on the left (asterisk) point to the large aortopulmonary window before repair
Isolation and Identification of Fungi from Clinical Samples of Diabetic Patients and Studying the Anti-Fungal Activity of Some Natural Oils on Isolated Fungi

Isolation of fungi was performed from February to July, 2019. One hundred clinical specimens were collected from King Abdullah Hospital (KAH) Bisha, Saudi Arabia. Samples were collected from twenty patients of different ages (30 - 70 years old) ten males and ten females. The samples were collected from patients with the two types of diabetics. Specimens included blood, hair, nail, oral swabs and skin. Specimens were inoculated on Sabourauds Dextrose agar containing chloramphenicol. Thirteen fungal species were isolated and identified. The isolated species were: Aspergillus flavus, A. niger, A. terrus, A. nidulans, A. fumigatus, Candida albicans, C. krusei, C. parapsilosis, C. Tropicalis, Curvularia lunata, Fusarium solani, Penicillium marneffei and Saccharomyces cerevisiae. Identification of molds was carried out morphologically and microscopically using available methods and books of identification, while identification of yeasts was carried out using API system. C. albicans recorded the highest isolated number where 31 colonies were isolated from 18 patients, representing relative density of 22.5%. (R. D.: is the number of a certain fungal species divided by the total number of fungi). Other isolated fungal species recorded relative density less than 16 %. The most common isolated fungus Candida albicans was molecularly identified using the 5.8S and flanking ITS regions. The antifungal activity of some natural essential oils (cinnamon, thyme, coconut, almond and clove) was assayed against isolated fungi using disk diffusion method. The used concentration was 5 µl / plate. The MIC values were also determined using different oil concentrations (1, 2.5, 5, 10, 20 and 40 µl / disc).
Learning by Ignoring

Learning by ignoring, which identifies less important things and excludes them from the learning process, is broadly practiced in human learning and has shown ubiquitous effectiveness. There has been psychological studies showing that learning to ignore certain things is a powerful tool for helping people focus. In this paper, we explore whether this useful human learning methodology can be borrowed to improve machine learning. We propose a novel machine learning framework referred to as learning by ignoring (LBI). Our framework automatically identifies pretraining data examples that have large domain shift from the target distribution by learning an ignoring variable for each example and excludes them from the pretraining process. We formulate LBI as a three-level optimization framework where three learning stages are involved: pretraining by minimizing the losses weighed by ignoring variables; finetuning; updating the ignoring variables by minimizing the validation loss. A gradient-based algorithm is developed to efficiently solve the three-level optimization problem in LBI. Experiments on various datasets demonstrate the effectiveness of our framework.
Aerosol formation and growth in atmospheric aromatic hydrocarbon photooxidation

An experimental study of aerosol formation in aromatic hydrocarbon/NO_x systems has been conducted in an outdoor smog chamber. Aerosol size distributions were measured as a function of time in toluene, m-xylene, ethylbenzene, or 1,3,5-trimethylbenzene photooxidations to determine the rates of new particle formation and the effects of initial particles on aerosol formation and growth. Aerosol yields from the aromatic gas-phase photooxidations were found to be approximately 2-5% by mass of the starting aromatic species. Simulations of the aerosol behavior in these experiments have been carried out using an integral model that includes a vapor source, homogeneous nucleation, condensational growth, and particle loss by deposition. Predictions from the model are in relatively good agreement with the experimental observations. Results indicate that the nucleation mechanism in these systems is still not completely understood.