Miracle-dz/UniFAR-FTUs huggingface dataset:
World Wide ICS Honeypots: A Study into the Deployment of Conpot Honeypots

Honeypots are a well-known concept used for threat intelligence and are becoming more ordinary within ICS environments. A well-known ICS honeypot, Conpot, is popular and has been deployed on a large scale. These deployments are not always correctly configured and have odd characteristics compared to a real industrial control system. This paper explores several common Conpot signatures and deployments found through internet search engines such as Shodan. We identify that the default deployment of Conpot is not enough when deploying a honeypot. Afterwards, we explore the behaviour of a real PLC when conducting the same reconnaissance operations. To verify these red flags, we deploy three honeypots with a different configuration, have them scanned by Shodan and evaluate the traffic they get. Our experiments indicate that Shodan leverages CIP for ICS classification. We conclude that proper deployment of a low-interaction honeypot, such as Conpot, requires time and resources to entirely obfuscate the device and fool the attacker to a limited level. However, small changes to the default configuration does increase the performance of Conpot and results in more returning traffic.
PROPOSAL FOR LIPID-BASED DRUG DELIVERY SYSTEM: DEFINITION, RECOMMENDATIONS, FORMULATION STRATEGIES, FEATURES AND FUTURE ASPECTS

The principle objective of formulation of lipid-based drugs is to reinforce their bioavailability. the utilization of lipids in drug delivery is not any more a replacement trend now but remains the promising concept. Lipid-based drug delivery systems are one of the emerging strategies designed to deal with challenges just like the solubility and bioavailability of poorly water-soluble drugs. These formulations are synthesized to meet a huge range of product specifications largely determined by sign of disease, route of administration, cost consideration, product security, toxicity and effectiveness. These formulations also are a commercially viable strategy to formulate pharmaceuticals, for topical, oral, pulmonary, or parenteral delivery. Additionally, lipid-based formulations are shown to scale back the toxicity of varied drugs by changing the biodistribution of the drug faraway from sensitive organs. However, the amount of applications for lipid-based formulations has expanded because the nature and sort of active drugs under investigation became more varied. This paper mainly focuses on novel lipid-based formulations, namely, emulsions, vesicular systems, and lipid particulate systems and their subcategories also as on their prominent applications in pharmaceutical drug delivery.
ENTEROPATHOGEN SURVIVAL IN SOIL FROM 4 DIFFERENT LAND-USES IS PREDOMINANTLY 5 REGULATED BY MICROBIAL COMMUNITY 6 COMPOSITION 7

Microbial enteropathogens can enter the environment via landspreading of animal slurries and manures. Biotic interactions with the soil microbial community can contribute to their subsequent decay. This study aimed to determine the impact of microbial community structure associated with soils derived from 12 contrasting land-uses on model enteropathogen survival. The phenotypic profiles of these soil microbial communities were determined by phospholipid fatty acid (PLFA) profiling, and soils were also characterized for 49 a range of physicochemical properties. The persistence of Salmonella Dublin, Listeria 50 monocytogenes, and Escherichia coli was measured over 110 days within soil microcosms. 51 Physicochemical and biotic data were used in stepwise regression analysis to determine the 52 predominant factor related to pathogen-specific death rates. Phenotypic structure, associated 53 with a diverse range of constituent PLFAs, was identified as the most significant factor in 54 pathogen decay for S. Dublin, L. monocytogenes, non-toxigenic E. coli O157 but not for 55 environmentally-persistent E. coli . This demonstrates the importance of entire community 56 interactions in pathogen suppression, which are context-specific. 57 58
Nonpositive Hopfield Neural Network with Self-Feedback and its Application to Maximum Clique Problems

In this paper, we propose a nonpositive Hopfield neural network (NHNN) with self-feedback for maximum clique problem. By introducing a negative self-feedback to the NHNN, the NHNN can escape from local minima and therefore get better solutions. A number of instances have been simulated to verify the proposed algorithm.
Recent Applications of Deep Learning Algorithms in Medical Image Analysis

Advances in deep learning have enabled researchers in the field of medical imaging to employ such techniques for various applications, including early diagnosis of different diseases. Deep learning techniques such as convolutional neural networks offer the capability of extracting invariant features from images that can improve the performance of most predictive models in medical and diagnostic imaging. This work concentrates on reviewing deep learning architectures along with medical imaging modalities where the crucial applications of such algorithms, including image classification and segmentation, are discussed. Also, brain imaging as a branch of medical imaging which allows scientists to explore the structure and function of the brain is explored, and the applications of deep learning to early diagnose Alzheimer‟s Disease, and Autism as the most critical brain disorders are studied. Moreover, the recent research findings revealed that employing deep learning-based semantic segmentation techniques could significantly improve the accuracy of models developed for brain tumor detection. Such advances in early diagnosis of disorders and tumors encourage medical imaging practitioners to implement software applications assisting them to improve their decision-making process.
T Cells + CD4Lymphoblastoid B Cell Lines to Stimulate Herpes Simplex Inhibits the Capacity of

HSV establish a lifelong persistent infection in their host even among immunocompetent persons. The viruses use a variety of immune evasion strategies, presumably to assist persistent replication in the human host. We have observed that infection of human B lymphoblastoid cells (B-LCL) by HSV resulted in a strong inhibition of their ability to induce CD4 1 T cell clone proliferation and cytokine secretion. This inhibitory effect occurs in a variety of both HSV- and HIV-speciﬁc clones from three different patients. The inhibition is observed when the Ag is provided either as a soluble protein or as a synthetic peptide and is not associated with detectable down-modulation of the MHC class II molecules or costimulatory molecules. Expression of the HSV-1 unique sequence 1 gene ( US1 ) is necessary and sufﬁcient to induce this inhibition of APC function. US1 gene expression also made B-LCL less susceptible to CD4 1 T cell-mediated lysis. These data indicate a novel immune evasion strategy by HSV-1 in which Ag-processing cells that become infected by HSV-1 are inhibited in their ability to induce subsequent CD4 1 T cell activation. The Journal of Immunology, 2001, 166: 6242–6249.
Edinburgh Research Explorer Estimation of sex from the upper limb in modern cretans with the aid of ROC-analysis

Discriminant function analysis is one of the most popular methods employed for grouping specimens according to optimal combination of linear measurements. Many studies have used this method with the objective of producing population specific formulae for sex estimation from different skeletal parts of the skeleton. This study focuses on the long bones of the upper limb using Receiving operation characteristics (ROC) curves. A total of 173 well preserved skeletons of Cretan origin were used. A total of 12 measurements are taken from the bones of the upper limn. The diagnostic value of the single variables was evaluated using the Area Under the Curve (AUC). The cut-off values and the diagnostic characteristics of each variable (Sensitivity, Specificity, Positive and Negative predictive values) are presented. The correlation of normally distributed the variables will be tested with the method Pearson correlation coefficient. The level of statistical significance is set to p<0.05 (a-error). Means, standard deviations and F-ratios for all single dimensions are calculated by performing ANOVA with SPSS 13.0. All measurements are found statistically significant at the level of 0.0001. The best discriminatory variables was found to be radius length (91.3%) followed by humerus head vertical diameter (90.2%) and ulnar length (89%). Comparison with published standards for mainland Greece reaffirms a scope for developing additional standards for modern Cretans. Traditional methods use discriminant function analysis to study sexual dimorphism. Herein a different approach is proposed. ROC curves, known to be very effective in medical decision making, are employed in the evaluation of several variables as effective markers for sex identification. The method should complement multivariate statistical analyses.
An Autonomous Internet of Things (IoT) pipeline network for Image acquisition in Agricultural Applications

Agriculture is considered to be a self-sufficient component of the country's economy. In terms of agricultural output, India is second only to the United States in terms of production. Irrigation, fertiliser, and crop rotation are three of the most significant elements in agricultural production. The usage of the Internet of Things can make crop production predictions and other components that contribute to high yielding crops more accurate and efficient (IoT). In the past, a pipeline for making predictions was created. A solution based on the Internet of Things (IoT) is being developed and designed to address this problem (IoT). When operating in a Wireless Sensor Network (WSN), sensor nodes are required to perform tasks such as observation, data collection, and transaction processing in order to exhaust their energy. Farmers saving time and money by collecting this information on their own is a win-win situation. To make advantage of this network, you must have a wireless sensor network (WSN), which must be capable of transmitting large amounts of data at a low rate while also consuming little power and communicating over short distances.
STUDIES ON ZARAIBI GOAT’S MILK IN SEMI- INTENSIVE PRODUCTION SYSTEM

The study was conducted to determine the influence of stages of lactation on milk yield and the chemical composition of Zaraibi goats milk in semi-intensive system. The analysis involved a total of 23 milk samples in various stages of lactation (early, midpoint, late). The results indicated that the total yield was (81.6±3.96 kg) in lactation period of 120 days, the daily yield (0.555±0.027 kg), the peak yield (0.78±0.10 kg) in the fifth week, and milk analysis included determination of average (12.81± 0.14 %) total solids, (4.66±0.14%) fat, (3.17±0.07%) protein, (4.18±0.05%) lactose,( 8.12±0.08%) solids-non-fat and (0.80±0.02%) ash.
Light-induced microfluidic chip based on shape memory gold nanoparticles/poly (vinyl alcohol) nanocomposites

A shape memory light-induced microfluidic technology is applied in preprogrammed microfluidic chip based on shape memory gold nanoparticles/poly (vinyl alcohol) nanocomposites. The shape memory gold nanoparticles/poly (vinyl alcohol) nanocomposites display excellent light-induced shape memory property with recovery ratio of nearly 100% in visible light. The crosslinked network of light-induced shape memory gold nanoparticles/poly (vinyl alcohol) nanocomposites forms by aldol reaction, esterification, and/or hydrogen bonding of poly (vinyl alcohol), glutaraldehyde, and gold nanoparticles. The light-induced shape memory mechanism of shape memory gold nanoparticles/poly (vinyl alcohol) nanocomposites is based on photothermal effect of gold nanoparticles and shape memory effect of poly (vinyl alcohol)-based shape memory polymer (SMP). In this report, a light-induced microfluidic microvalve is demonstrated based on the shape memory gold nanoparticles/poly (vinyl alcohol) nanocomposites. This research presents demonstration of the shape memory light-induced intelligent microfluidic chip. The light-induced SMP microfluidic microvalve would yield practical, physical, and technological advantages for disposable integrated microfluidic chip laboratories.
Research on the Linear Prediction Model of Financial Financing Reliability under Earnings Management

: Aiming to reduce the risk of financial financing and improve the reliability of financial financing, the research on the linear prediction model of financial financing reliability under earnings management model is summarized. A linear prediction model of financial financing reliability is proposed based on earnings management model. Taking the ratio of assets and liabilities and the interval of social capital financing as the constraint index, the empirical analysis model of enterprise financing decision is established, and the earnings management analysis of enterprise financial financing is carried out by using financial leverage. The linear prediction model of financial financing reliability is established by using AHP and the least square fitting method is used to realize the reliability evaluation and quantitative prediction of financial financing risk. The empirical results show that the model is reliable and accurate.
A ﬀ ective Pathﬁnding in Video Games

To allow player submerge in created environment of a video game, agents called Non-Player Characters (NPCs) should act believably. One of the most vital aspect, in case of NPCs is pathﬁnding. There are a few meth-ods that allow change path ﬁnding algorithms to become more human-like. Yet, those are not considering many vital aspects of human decisions regarding path choosing. The main purpose of this paper is to present known approaches and show example of a new approach that wider considers psychological aspects of decision making in case of choosing a path.
BENEFITS OF VOLUNTARY REPORTING OF MEDICATION ERRORS IN A HOSPITAL SETTING

Context: Medication errors remain the most common type of medical incidents reported in hospitals. Reducing medication errors significantly improves patient safety and the quality use of medicines. Identification of medication error is a main target in improving clinical practice errors, in order to prevent adverse events. The major method for detecting medication errors and associated adverse drug-related events are computerized monitoring system for order entry and reporting medication errors, patient chart review, using direct observation, incident reporting and patient monitoring. Objective: To evaluate the impact of reporting medications errors on patient’s safety and required action plan for preventing reoccurrence. Method: It is a retrospective study. 1550 medication errors were collected and analyzed from government hospital in Abu-Dhabi for 2 years by using patient safety net (PSN). Results: The highest medication errors incidents were in quarter 4 2014 (20%) and declined to (7%) in quarter 4 2015. However some types of errors that were related to hospital system increased in 2015 like missing doses in inpatient pharmacy from 5% to 17.6%. While, all errors related to physician prescribing were dropped down from 89% in 2014 to 51.4% in 2015. Near miss an error occurred but did not reach the patient were the highest incidents among all categories, it was 95% in 2014 and slightly decreased to 88% in 2015. Event reached the patient, but no harm was evident was 3% in 2014 and slightly increased to 9% in 2015 while errors categories 4 to 9 were Zero for 2 years. Conclusion: Voluntary medication error reporting can provide useful information about systems contributing to errors, strategies for prevention, and evidence-based information about patient safety concepts. This information is important for hospitals to consider both when analysing medication errors and when implementing systems to improve safety.
Capacity Development Programmes: Developing Positive Human Capital Capacity for Socio-Economic transformation in South Africa

This paper explores capacity development programmes as one of the indispensable tools towards developing dimensions of positive human capital capacity for socio-economic transformation in South Africa. The South African ruling party or consecutive governments have been emphasising on the commitment to implementing radical socio-economic transformation policies and programmes to meet the hopes and aspirations of all South Africans, especially the Black African majority who had been marginalised, exploited, dehumanised, and excluded by the apartheid system. Unfortunately, the radical socio-economic transformation narrative emerged as an ideological proxy battle by the ruling party for the control of Soul of South Africa. The vision for radical socio-economic transformation seems to be an unreachable agenda because the application process may take many years, as the country is still critically confronting various intractable challenges of endemic corruption, poverty, unemployment, inequality, etc., which in major part are caused by people in leadership or in different managerial levels, which are lacking administrative integrity and moral ethics. The lack of best practice of administrative (political) integrity and moral ethics are amongst the key challenges affecting socio-economic transformation in the country. In other words developing administrative integrity and moral ethics capacities (and other attributes of the dimensions of positive human capital capacity) for good governance, sustainable governance and development, and socio-economic transformation constitute a strong vaccine towards fulfilling effectively and efficiently administrative tasks, functions or responsibilities in order to influence positively the growth of socio-economic activities in the country. This paper intends to awake, alert and intensify vigorously the awareness of leaders from public and private institutions on the necessity of initiating and promoting programmes of capacity development that support the development of positive human capital capacity as a foremost key factor in tackling all forms of mismanagement (unprofessional success/positive actions. Therefore, developing dimensions of positive human capital capacity could be a sine qua non condition or an essential key factor for socio-economic transformation. Thus, it was recommended that more efforts, resources and increased awareness campaigns, actions, and interventions should be invested towards promoting programmes that support the development of positive human capital capacity in the country.
Combining Machine Learning and Semantic Analysis for Efficient Misinformation Detection of Arabic Covid-19 Tweets

With the spread of social media platforms and the proliferation of misleading news, misinformation detection within microblogging platforms has become a real challenge. During the Covid-19 pandemic, many fake news and rumors were broadcasted and shared daily on social media. In order to filter out these fake news, many works have been done on misinformation detection using machine learning and sentiment analysis in the English language. However, misinformation detection research in the Arabic language on social media is limited. This paper introduces a misinformation verification system for Arabic COVID-19 related news using an Arabic rumors dataset on Twitter. We explored the dataset and prepared it using multiple phases of preprocessing techniques before applying different machine learning classification algorithms combined with a semantic analysis method. The model was applied on 3.6k annotated tweets achieving 93% best overall accuracy of the model in detecting misinformation. We further build another dataset of Covid-19 related claims in Arabic to examine how our model performs with this new set of claims. Results show that the combination of machine learning techniques and linguistic analysis achieves the best scores reaching 92% best accuracy in detecting the veracity of sentences of the new dataset.
The 3M Company (3M) appreciates the opportunity to review and comment on the EFSA’s draft scientific opinion on the “Risk to human health related to the presence of perfluoroalkyl

The EFSA Scientific Panel on Contaminants in the Food Chain (CONTAM Panel) has previously performed risk assessments for PFOA and PFOS in 2008 and 2012. Based on the experimental toxicology data from laboratory animals actually exposed to high doses of PFOA and/or PFOS, the previous CONTAM panels concluded that “it is unlikely that adverse effects of PFOS or PFOA are occurring in the general population. ” The total daily intake (TDI) set by EFSA in 2008 and 2012 were the identical 1500 ng/kg b.w. and 150 ng/kg b.w. for PFOA and PFOS, respectively.
PCDHB17P/miR-145-3p/MELK/NF-κB Feedback Loop Promotes Metastasis and Angiogenesis of Breast Cancer

Li Zhu The First Medical Center of PLA General Hospital Yan-Jun Zhang The First Medical Center of PLA General Hospital Bin Wang The Second Medical Center of PLA General Hospital Li Yang Beijing Shunyi Hospital Yi-Qiong Zheng The First Medical Center of PLA General Hospital Lin-De Sun The First Medical Center of PLA General Hospital Lin Tian The First Medical Center of PLA General Hospital Jian-Dong Wang (  jiandongwang55@163.com ) The First Medical Center of PLA General Hospital Tao Chen The First Medical Center of PLA General Hospital
Fast motion estimation algorithm using multilevel distortion search in Walshâ•fiHadamard domain

Block-matching motion estimation (BME) can efficiently reduce the temporal redundancy between the successive video sequences in video compression coding system. In this study, a fast BME algorithm using multilevel distortion search in Walsh–Hadamard domain is proposed to reduce the computational burden and speed up coding process. First, the proposed algorithm divides the block into several sub-blocks. Then, the Walsh–Hadamard transform is applied to these sub-blocks. Finally, the proposed algorithm calculates the partial block matching distortion by utilising a novel back diagonal search scheme which can quickly reject unnecessary candidate block in a multilevel manner. Experimental results show that the proposed algorithm effectively reduces the number of operations in block distortion calculation meanwhile maintains the best motion estimation matching quality. Compared with the full search, the proposed algorithm can reduce 87.19% computational complexity without any degradation of the peak signal to noise ratio. In addition, compared with the partial distortion search algorithm, successive elimination algorithm, multilevel successive elimination algorithm and the transform-domain successive elimination algorithm, the proposed algorithm can also save 68.27, 70.09, 37.81 and 37.44% computational complexity, respectively. Moreover, the proposed algorithm can also be easily incorporated into any block-based template search motion estimation algorithm.
FOREIGN INVESTMENT IN AFRICA A LOOK INTO FDI DETERMINANTS

Foreign Direct Investment is seen as a critical source of capital inflow and a stimulant of economic growth in many developing nations. It brings with it benefits such as job creation, technology and knowledge transfers just to mention a few. Thus many African countries are keen in finding ways of attracting FDI. The main objective of this paper is to empirically examine the determinants of foreign direct investment (FDI) by incorporating an econometric method based on cross-sectional data from 41 African countries over the period 2002-2007. More precisely, this research intends to answer the following question: what are the relevant determinants that promote FDI inflows in Africa? Among the several determinants of FDI, the finding suggests that market size and natural resource predominance are the main determinants of FDI into Africa.