Miracle-dz/UniFAR-FTUs huggingface dataset:
An in silico integrative analysis of hepatocellular carcinoma omics databases shows the dual regulatory role of microRNAs either as tumor suppressors or as oncomirs

MicroRNAs are well known as short RNAs bases, 22 nucleotides, binding directly to 3'untranslated region (3'UTR) of the messenger RNA to repress their functions. Recently, microRNAs have been widely used as a therapeutic approach for various types of Cancer. MicroRNA is categorized into tumor suppressor and oncomirs. Tumor suppressor microRNAs can repress the pathologically causative oncogenes of the hallmarks of Cancer. However, based on the fact that miRNA has no proper fidelity to bind specific mRNAs due to binding to off-targets, it results in a kind of inverse biological activity. Here, we have executed an in-silico integrative analysis of GEO/TCGA-LIHC of genes/microRNAs expression analysis in HCC, including (446 HCC vs. 146 normal specimens for miRNAs expression ) ad 488 specimens for genes expression. It virtually shows that microRNAs could have an ability to target both oncogenes and tumor suppressor genes that contribute to its dual activity role as a tumor suppressor and oncomirs via miRNA-lncRNA-TFs-PPI Crosstalk. Seven resultant microRNAs show a putative dual role in HCC. It enhances our concluded suggestion of using combination therapy of tumor suppressor genes activators with microRNAs.
LUCAS: A highly accurate yet simple risk calculator that predicts survival of COVID-19 patients using rapid routine tests

There is an urgent need to develop a simplified risk tool that enables rapid triaging of SARS CoV-2 positive patients during hospital admission, which complements current practice. Many predictive tools developed to date are complex, rely on multiple blood results and past medical history, do not include chest X ray results and rely on Artificial Intelligence rather than simplified algorithms. Our aim was to develop a simplified risk-tool based on five parameters and CXR image data that predicts the 60-day survival of adult SARS CoV-2 positive patients at hospital admission. Methods We analysed the NCCID database of patient blood variables and CXR images from 19 hospitals across the UK contributed clinical data on SARS CoV-2 positive patients using multivariable logistic regression. The initial dataset was non-randomly split between development and internal validation dataset with 1434 and 310 SARS CoV-2 positive patients, respectively. External validation of final model conducted on 741 Accident and Emergency admissions with suspected SARS CoV-2 infection from a separate NHS Trust which was not part of the initial NCCID data set. Findings The LUCAS mortality score included five strongest predictors (lymphocyte count, urea, CRP, age, sex), which are available at any point of care with rapid turnaround of results. Our simple multivariable logistic model showed high discrimination for fatal outcome with the AUC-ROC in development cohort 0.765 (95% confidence interval (CI): 0.738 - 0.790), in internal validation cohort 0.744 (CI: 0.673 - 0.808), and in external validation cohort 0.752 (CI: 0.713 - 0.787). The discriminatory power of LUCAS mortality score was increased slightly when including the CXR image data (for normal versus abnormal): internal validation AUC-ROC 0.770 (CI: 0.695 - 0.836) and external validation AUC-ROC 0.791 (CI: 0.746 - 0.833). The discriminatory power of LUCAS and LUCAS + CXR performed in the upper quartile of pre-existing risk stratification scores with the added advantage of using only 5 predictors. Interpretation This simplified prognostic tool derived from objective parameters can be used to obtain valid predictions of mortality in patients within 60 days SARS CoV-2 RT-PCR results. This free-to-use simplified tool can be used to assist the triage of patients into low, moderate, high or very high risk of fatality and is available at https://mdscore.net/.
Mapping the plague through natural language processing

Plague has caused three major pandemics with millions of casualties in the past centuries. There is a substantial amount of historical and modern primary and secondary literature about the spatial and temporal extent of epidemics, circumstances of transmission or symptoms and treatments. Many quantitative analyses rely on structured data, but the extraction of specific information such as the time and place of outbreaks is a tedious process. Machine learning algorithms for natural language processing (NLP) can potentially facilitate the establishment of datasets, but their use in plague research has not been explored much yet. We investigated the performance of five pre-trained NLP libraries (Google NLP, Stanford CoreNLP, spaCy, germaNER and Geoparser.io) for the extraction of location data from a German plague treatise published in 1908 compared to the gold standard of manual annotation. Of all tested algorithms, we found that Stanford CoreNLP had the best overall performance but spaCy showed the highest sensitivity. Moreover, we demonstrate how word associations can be extracted and displayed with simple text mining techniques in order to gain a quick insight into salient topics. Finally, we compared our newly digitised plague dataset to a re-digitised version of the famous Biraben plague list and update the spatio-temporal extent of the second pandemic plague mentions. We conclude that all NLP tools have their limitations, but they are potentially useful to accelerate the collection of data and the generation of a global plague outbreak database.
Biomass and Carbon Stored Estimated in the forest ecosystem of the Nova Canaã Farm (Porciúncula/RJ)

Global warming has become international concern, culminating with the ratification of the Kyoto Protocol which includes definitions and objectives of the sustainable development mechanisms and features that make it easier for the industrialized countries to jointly compensate for their polluting greenhouse gas emissions. Porciúncula is a city known for its agricultural development and the lack of characterization of ecosystems associated with the Atlantic Forest biome. Facing this chaotic scenario is Nova Canaã farm located in the Ribeirão da Perdição Environmental Preservation Area its forest ecosystem provides a series of environmental services such as carbon storage and CO2 sequestration. The team of researchers from OM Consultoria Ambiental performed the quantification of the biomass (Bwood) of the bole which resulted in estimates of 398.4753 t.ha-1 corresponding to 199.2377 tC.ha-1. The estimates obtained for the forest ecosystem of the farm can be used as a reference for the establishment of forest restoration projects under the under the sustainable development mechanism established the Kyoto Protocol.
Research on the Pricing of Convertible bonds in China---Migration risk based on credit rating

At present, further research and exploration on credit risks are being carried out in the global field, and increasingly profound modern credit risks are exposed to the bond market. This requires that we cannot ignore the impact of credit rating migration risk on bond pricing, so as to adapt to the sustainable and healthy development of the bond market under the new normal of China's economy. The innovation point of this paper is to try to analyze the pricing of Convertible bonds in China from the perspective of credit rating migration risk. Tsiveriotis and Fernandes(1998) model is selected, and the credit risk in the model is assumed to be caused by the credit rating migration risk, and the credit spread is used to measure the credit rating migration risk. The research conclusion of this paper is as follows: First, it is valid to consider the risk of credit rating migration in the TF(1998) model. The market price of convertible bonds is on average 1.22% higher than the theoretical value of the model. In general, the theoretical value obtained from the model has little deviation from the market price, and has a good fitting degree. Second, from the Angle of credit rating, the selection of 32 samples of convertible bonds only empirical research shows that the credit rating of AA - convertible bonds average deviation rate is negative, suggest that the credit rating of AA - the phenomenon of convertible bonds value is underestimated, and AAA credit rating to AA, AA +, the average deviation rate of convertible bonds is positive, that credit rating AA (containing AA) more convertible bond value is overrated phenomenon, and the higher the credit rating of the average deviation rate of convertible bond, the greater the overvalued levels. It has certain guiding significance for participants in the convertible bond market.
Treatment of aqueous selenocyanate (SeCN-) using combined TiO2 photocatalysis and 2-line ferrihydrite adsorption

The presence of selenocyanate (SeCN–) species in some specific industrial wastewater streams including those from the crude oil refineries and mining industries, pose a risk to human and animal health. The present work thus investigated the treatment of selenocyanate contaminated water using combined TiO2 photocatalysis and 2 line ferrihydrite (2LFh) adsorption system. The X-ray diffraction findings indicated the synthesized 2LFh to be in the amorphous state, whereas the Fourier transform infrared results showed several Feand O-based groups onto the 2LFh surface. During selenocyanate removal using the above-mentioned combined system, the TiO2 photocatalysis initiated the selenocyanate complex degradation with selenite and selenate species appearing over 360 min reaction time. This was followed by the adsorption of released selenium species onto 2LFh. Results from the respective TiO2 photocatalysis and 2LFh adsorption studies showed that the combination of the two systems through efficient, but was affected by the process control variables including pH. A complete selenium removal was noted at pH 5, whereas the selenium removal decreased significantly with an increase in the process pH. This was attributed to lower adsorption of released selenium species onto 2LFh. The response surface methodology (RSM) modeling also showed reasonable estimates for the aqueous phase selenocyanate removal under a varying set of operational conditions.
Research Article: Molecular phylogeny of bivalve families (Arcidae, Chamidae, Margaritidae, Ostreidae, Veneridae) in the Persian Gulf

Bivalvia is one of the least studied classes of the Persian Gulf. A survey and molecular analysis was conducted to determine bivalve species diversity in the Persian Gulf. To the best of our knowledge, this is the first report of barcoding data on bivalves of the Persian Gulf. We examined 40 individuals representing 8 species, 6 genera and 5 families. We collected samples from Hengam, Larak and Qeshm Islands and Bandar Lengeh in Persian Gulf, Iran. After DNA extraction, mitochondrial 16S ribosomal DNA (16SrDNA) and Cytochrome Oxidase subunit I were amplified by polymerase chain reaction (PCR). Based on obtained 16SrDNA and COI gene sequences and maximum parsimony, neighbor joining and maximum likelihood trees of these genes there was no overlap between maximum Kimura 2- parameter distance among conspecifics. Most species formed agglutinate sequence units with a small amount of changes. Eventually, comparison of the 8 selected studied species with metadata from India, Brazil, Japan, China, and America exposed that these species in Persian Gulf are classified in sister clades with high bootstraps except Pinctada. Since there is not much work on bivalves identification in the Persian Gulf, larger sampling and more research is needed to investigate mollusc diversity in this area.
DETERMINANT OF HALAL INDUSTRY PRODUCT SELECTION

This paper aims to analyze the determinants of Malang people's perceptions in choosing the halal industry. In this study, using product knowledge, accessibility, and information/promotion as exogenous variables, while religious and the perception of the halal industry as an endogenous variable and also halal Certification as a moderating variable. The government has prepared a masterplan to develop the halal industry. One of the goals of the government in making a masterplan is to foster public perceptions of the halal industry. So that is expected to be able to encourage the growth and development of the halal industry market in Indonesia, which is meant by the halal industry, including halal tourism, halal culinary, and halal hotels. Data's collected through a questionnaire of 160 respondents. This research uses the Partial Least Square (PLS) method based on variants approach. The results showed that all exogenous variables influence the endogenous variable, except information that does not significantly influence the religious and product knowledge also does not significantly influence the perception of the halal industry. While the halal certification variable as a moderating does not have a weakening or strengthening effect on the other variables.
Master of Information Systems: Digital Business Systems

Gamification is a rising trend in academia and an exciting concept for practitioners across different industries. There are many promising effects related to gamification, but all are related to increased engagement. One specific domain that is intriguing is in project management, as there are many routines and processes related to projects that might be considered tedious. Regardless, task performance has to be high in order to reach goals on time. This thesis has examined if gamification could boost engagement and subsequently task performance. With the help from a case company in the construction industry, gamification behaviours were explored through a between-group experiment in a natural setting. Intentional data was gathered and analyzed as well, in order to test both the actual and perceived effects of gamification. In parallel, an experiment in a more controlled setting was also conducted in relation to the COVID-19 pandemic, where a group of participants were recruited to do tasks related to official guidelines and advice on hygienic and personal well-being in state of emergency. This study aims to examine the grand promise of gamification; increased engagement. Being able to examine from two vastly different settings gave unique insight of what engagement can be inflicted by gamification, and how to design good gamified systems. A technical checklist process application was developed with the ability to switch on and off gamification elements to collect data. Despite a small dataset, the findings showed a tendency that there are indeed more engaged users in gamification in contrast to users not not being exposed to gamification. Therefore, applying gamification to combat tedious aspects of work life is proven to be a promising future avenue.
DEEP REINFORCEMENT LEARNING WITH SPARSE DISTRIBUTED MEMORY FOR “WATER WORLD” PROBLEM SOLVING

Context. Machine learning is one of the actively developing areas of data processing. Reinforcement learning is a class of machine learning methods where the problem involves mapping the sequence of environmental states to agent’s actions. Significant progress in this area has been achieved using DQN-algorithms, which became one of the first classes of stable algorithms for learning using deep neural networks. The main disadvantage of this approach is the rapid growth of RAM in real-world tasks. The approach proposed in this paper can partially solve this problem. Objective. The aim is to develop a method of forming the structure and nature of access to the sparse distributed memory with increased information content to improve reinforcement learning without additional memory. Method. A method of forming the structure and modification of sparse distributed memory for storing previous transitions of the actor in the form of prototypes is proposed. The method allows increasing the informativeness of the stored data and, as a result, to improve the process of creating a model of the studied process by intensifying the learning of the deep neural network. Increasing the informativeness of the stored data is the result of this sequence of actions. First, we compare the new transition and the last saved transition. To perform this comparison, this method introduces a rate estimate for the distance between transitions. If the distance between the new transition and the last saved transition is smaller than the specified threshold, the new transition is written in place of the previous one without increasing the amount of memory. Otherwise, we create a new prototype in memory while deleting the prototype that has been stored in memory the longest. Results. The work of the proposed method was studied during the solution of the popular “Water World” test problem. The results showed a 1.5-times increase in the actor’s survival time in a hostile environment. This result was achieved by increasing the informativeness of the stored data without increasing the amount of RAM. Conclusions. The proposed method of forming and modifying the structure of sparse distributed memory allowed to increase the informativeness of the stored data. As a result of this approach, improved reinforcement learning parameters on the example of the “Water World” problem by increasing the accuracy of the model of the physical process represented by a deep neural network.
Substrate Integrated Waveguide Directional Coupler in Ku and Ka Bands

Four port substrate integrated waveguide (SIW) directional couplers for Ku and Ka bands are concei ved. Initial design directional coupler -3 db follow substrate integrated waveguide selection and aperture couplin g theory as known from standard air-filled waveguide compone nts. The simulation results using HFSS and CST software demonstrate that this design approach is satisfacto ry for many applications. Tapered microstrip ports are use d as interfaces to the SIW couplers. Performances of design models of -3dB 90° SIW couplers described in this p a er are analyzed.
Data Communication Security Design on IoT Based Systems with the Port Knocking Method

Technology is a familiar thing among the people and the internet is something that is always used in everyday life to help with work. With technology and the internet, IoT (internet of things) can be realized in every device available to build a Smart City. However, there are still people who use the internet to commit crimes. To prevent it is not enough with a firewall, there needs to be a more security system. In this article, discussing how to tap on a port will be able to help manage the IoT-based system. The success rate of previous studies that support SSH by using port knocking is very good but in the author's study only to the design design only.
Eliciting Fairness in Multiplayer Bargaining through Network-Based Role Assignment

From employment contracts to climate agreements, individuals often engage in groups that must reach decisions with varying levels of fairness. These dilemmas also pervade AI, e.g. in automated negotiation, conflict resolution or resource allocation. As evidenced by the Ultimatum Game, payoff maximization is frequently at odds with fairness. Eliciting equality in populations of self-regarding agents thus requires judicious interventions. Here we use knowledge about agents’ social networks to implement fairness mechanisms, in the context of Multiplayer Ultimatum Games. We show that preferentially attributing the role of Proposer to low-connected nodes enhances fairness. We further show that, when high-degree must be the Proposers, stricter voting rules (i.e., requiring consensus for collectives to accept a proposal) reduce unfairness.
The impact of obesity and income on happiness: Evidence from EU countries

The World Happiness Report 2018 ranks 156 countries by their happiness levels, and revealed a link between happiness and obesity. Despite the importance of this link, few studies have analyzed this relationship. Moreover, it may be the case that the relationship between happiness and obesity is non-linear. The relationship between happiness and income, however, has been studied by several researchers, particularly after the publication of Easterlin (1974). In his famous paradox, Easterlin found that after reaching a certain level, the further increase of material wealth no longer promotes happiness. Here, we investigate whether there is a quadratic relationship between happiness & obesity and happiness & income, for a panel of EU countries for the period 2005-2016, using the system GMM method. The empirical results suggest an inverse U-shaped relationship between happiness & obesity and happiness & income, implying that as obesity (income), represented by body mass index, increases, happiness first increases then stabilizes and finally decreases. Hence, the existence of an inverted U-shaped relationship between happiness and income supports the validity of the Kuznets curve hypothesis. Some control variables were also included in the regressions in order to solve omitted variable bias problems. The results indicate that income inequality and unemployment have a significantly negative impact on happiness. Keywords: Happiness, Obesity, Income, Kuznets Curve, EU countries. JEL: D60, I31, J35.
Ecotourism and sustainable development. Prospects for Ukraine

The paper analyzes ecotourism's impact on the social, economic, and environmental components of sustainable development. A systematic review of the scientific literature on the topic reveals that the major problem in assessing ecotourism's impact is a lack of a unified approach to methods of measurement and certification in this field. Even approximate estimates show the high economic potential of ecotourism. Processing the data provided by mobile operators, using BigData technologies and the use of electronic visit permits, proves to be the most promising means to record the number of tourist arrivals. This data allows scientists to measure the level of tourism influence on the ecosystem. Studying foreign experience, eco-certification does not cover all objects of ecotourism. Although some countries, notably Australia, already have significant experience in implementing and using national eco-certification programs. In Ukraine, only several hotels and beaches have received eco-certification. Research on the impact of ecotourism on ecology has provided mixed results. We do not practice if ecotourism with caution; it jeopardizes the ecosystems on which its development depends. To promptly identify and prevent all negative consequences of the tourism in Ukraine, it is necessary to create (using foreign experience) tourist observatories. It should integrate the operation of such observatories into the national system of environmental and fiscal monitoring. Further development of this type of tourism in Ukraine requires more investments and support from the government. Therefore, it is necessary 1) to develop and implement a system of tax incentives for small businesses in ecotourism; 2) to enhance fiscal decentralization so that the environmental tax remains at the disposal of local communities and consequently local ecosystems; 3) to adjust the tourist tax base. The paper provides a generalization of the overseas experience, studies by scientists dedicated to the impact of ecotourism on the level of ecological culture of tourists and a local population. It presents conclusions regarding significant potential and opportunities for further successful development of ecotourism in Ukraine.