Miracle-dz/UniFAR-FTUs huggingface dataset:
GUI-Squatting Attack: Automated Generation of Android Phishing Apps

Mobile phishing attacks, such as mimic mobile browser pages, masquerade as legitimate applications by leveraging repackaging or clone techniques, have caused varied yet significant security concerns. Consequently, detection techniques have been receiving increasing attention. However, many such detection methods are not well tested and may therefore still be vulnerable to new types of phishing attacks. In this article, we propose a new attacking technique, named GUI-Squatting attack, which can generate phishing apps (phapps) automatically and effectively on the Android platform. Our method adopts image processing and deep learning algorithms, to enable powerful and large-scale attacks. We observe that a successful phishing attack requires two conditions, page confusion and logic deception during attacks synthesis. We directly optimize these two conditions to create a practical attack. Our experimental results reveal that existing phishing defenses are less effective against such emergent attacks and may, therefore, stimulate more efficient detection techniques. To further demonstrate that our generated phapps can not only bypass existing detection techniques, but also deceive real users, we conduct a human study and successfully steal users’ login information. The human study also shows that different response messages (e.g., “Crash” and “Server failed”) after pressing the login button mislead users to regard our phapps as functionality problems instead of security threats. Extensive experiments reveal that such newly proposed attacks still remain mostly undetected, and are worth further exploration.
Development of a Volume Of Fluid Method for Computing Interfacial Incompressible Fluid Flows

This study is aimed to develop a volume of fluid (VOF) method to capture the free surface flow. The incompressible two-phase flow is computed by second-order Adams-Bashforth algorithm with a uniform staggered Cartesian grid arrangement. The tangent of hyperbola for interface capturing (THINC) scheme and weighted linear interface calculation (WLIC) based geometrical reconstruction procedure have been implemented in the operator-splitting method for the VOF method. The proposed VOF method preserves mass well, and the interface normal vector can be easily estimated from the level set (LS) function. The LS function, which is a continuous signed distance function around the interface, is represented by solving the re-initialization equation. Numerical results using the present scheme are compared with experimental data and other numerical results in the Rayleigh-Taylor instability, dam-break flow, travelling solitary wave, Kelvin-Helmholtz instability, rising bubble and merging bubble problems. We also present numerical results in detail between computations made with the proposed VOF method and computations made with the conventional LS method. AMS subject classifications: 35Q30, 76D05, 76D27, 76M20
Highlights in Managing Monetary Policy of Vietnam in Post-Crisis Period

This paper focuses on assessing highlights in the managing monetary policy in post-crisis period from 2011 to present in Vietnam in order to identifies key messages which helped Vietnam overcome the financial crisis 2007-2008 and keep the growth rate stably at high level, to be one of highest growth rate in the world. The research used aggregated methods, descriptive statistics and analysis based on World Bank, International Monetary Fund, Central Bank of Vietnam data sources. The results shown that the monetary policy in Vietnam in this period had a flexible transition in its management objectives, coordinated in close with fiscal policy to achieve macro goals, besides changing the regulatory mechanism by volume to operating with interest rates and combined with other operating tools more diverse.
Laborem Exercens : A Tool for Promoting the Provision of Valuable Services by the Nigerian Civil and Public Servants

The contemporary services proffered by the Nigerian Civil and Public Servants appear to be characterized of lack of commitment in provision of valuable services. This work is geared towards challenging the Nigerian Civil and Public Servants with the tool of Laborem Exercens towards the provision of valuable services in their various specific areas of employment. The Social Learning Theory (SLT) and the Social Disorganization Theory (SDT) used in this work revealed to the fur that the lack of provision of valuable services by the Nigerian Civil and Public Servants and the right appreciation of workers is as a result of corruption endemic in the country. It was discovered that a corruption substructure that provides an opportunity to learn corruption and deviant activities is prevalent in Nigeria. Again, there is no down to earth laid down strict disciplinary measures for civil and public servants that engage in corrupt practices in Nigeria thereby making corruption persistence; this as a result perpetuates the provision of invaluable services by the civil and public servants in Nigeria. This work employed both the primary and secondary means of data collection. It streamlined all the gathered data via phenomenological approach.
DeepNano-blitz: A Fast Base Caller for MinION Nanopore Sequencers

Motivation Oxford Nanopore MinION is a portable DNA sequencer that is marketed as a device that can be deployed anywhere. Current base callers, however, require a powerful GPU to analyze data produced by MinION in real time, which hampers field applications. Results We have developed a fast base caller DeepNano-blitz that can analyze stream from up to two MinION runs in real time using a common laptop CPU (i7-7700HQ), with no GPU requirements. The base caller settings allow trading accuracy for speed and the results can be used for real time run monitoring (i.e. sample composition, barcode balance, species identification, etc.) or pre-filtering of results for more detailed analysis (i.e. filtering out human DNA from human–pathogen runs). Availability and Implementation DeepNano-blitz has been developed and tested on Linux and is available under MIT license at https://github.com/fmfi-compbio/deepnano-blitz Contact vladimir.boza@fmph.uniba. sk
From Material Objects to Social Objects: Researching the Material-Dialogic Spaces of Joint Attention in a School-based Makerspace

In this paper, we investigate the material-discursive spaces of joint attention between students and their teachers in a school-based makerspace. Drawing on sociocultural theorizing, Bakhtinian inspired notion of the “dialogic space”, and material-discursive ontoepistemology, we introduce the concept of social object to explain how material objects can turn into joint attention and meaning-making in ongoing interaction. Video recordings (75 hours) of 94 students’ aged 9 to 12 years old and their teachers’ interactions in the makerspace were analyzed. The study shows how the material objects of the makerspace were enacted into social objects via joint attention about the objects, around the objects and with the objects. The study demonstrates the need to rethink the meaning and role of material objects in novel educational makerspaces for establishing and negotiating joint attention, mediating learning opportunities and tensions.
A real gas-based throughflow method for the analysis of SCO2 centrifugal compressors

The supercritical carbon dioxide Brayton cycle is recognized as a promising candidate for the next generation of nuclear power and energy system. Among all the components in the cycle, the centrifugal compressor is one of the most important ones. This paper presents a streamline curvature throughflow method based on real gas properties and capable of dealing with condensation flows in the supercritical carbon dioxide compressors. A fluid thermodynamic property calculation method based on look-up tables is adopted to account for the real gas effects and fluid condensation and to reduce the computational time. For extending the simulation capability to the region below the saturation curve to assess the condensation possibility, the homogeneous equilibrium model is adopted. Finally, the real gas-based streamline curvature method is applied in the analysis of a supercritical carbon dioxide centrifugal compressor working near the critical point. Then, computational fluid dynamics calculations are performed to validate the method in detail. The results of the computational validation indicate that the real gas-based streamline curvature method presented in the paper can obtain an accurate enough flow field as that obtained by three-dimensional computational fluid dynamics simulations considering the coarse grid and the much less calculation time.
Heart Rate and Activity Monitoring

Continuous monitoring of the heart for various metrics is very important, this has led to at home and remote monitoring of events such as heart attacks or any other issues concerning the heart and reporting to the doctor and family members in case of emergency. This paper contains an intelligent pulse sensor and temperature sensor integrated with the arduino chip and GSM (Global System for Mobile communication) modem. The sensor measures the heart rate and room temperature and based on the readings, plots the ECG (Electrocardiogram) and displays the heart rate and room temperature. A special feature of detecting the mood of the person by using the heart rate is also deployed here. This is done by calculating the CPR (Cardiopulmonary Resuscitation) value using the heart rate. In case of any sudden variations in the heart rate, a message is sent to the doctor and family members using GSM modem for the immediate rescue of the person concerned. Keywords—Arduino, CPR (Cardiopulmonary Resuscitation), GSM (Global System for Mobile Communication), pulse sensor, temperature sensor.
Effect of supplemental serine-protease from Bacillus licheniformis on growth performance and physiological change of broiler chickens

ABSTRACT An experimental study was conducted to examine the effects of adding serine-protease from Bacillus licheniformis on performance and physiological parameters of broiler chickens under Egyptian condition. A total of 600 one-day-old chicks were randomly divided into four experimental treatments. The treatments consisted of the control diet with 0, 100, 200 and 300 mg/kg serine-protease. Protease supplementation increased (P < 0.05) body weights (BW). Feed conversion ratio (FCR) was improved (P < 0.05) due to 200 and 300 mg/kg protease supplementation. The dry matter and crude protein digestibilities were enhanced (P < 0.05) by both 200 and 300 mg/kg protease supplementation. Plasma albumin and high-density lipoprotein (HDL) concentrations were increased (P < 0.05), while plasma total cholesterol (CHO) and low-density lipoprotein (LDL) concentrations were decreased (P < 0.05) at 100, 200, and 300 mg/kg of protease. Liver malondialdehyde (MDA) levels were declined (P < 0.05) due to 200 and 300 mg /kg protease supplementation. Supplementing 100, 200, and 300 mg/kg of protease increased (P < 0.05) lysine, methionine, and threonine levels in breast muscle. In conclusion, exogenous serine-protease could be used as a feed additive in broiler nutrition and supplementing 200∼300 mg/kg was sufficient to improve growth performance, probably because of its mechanism to enhance protein digestibility.
Identification and analysis of a novel scavenger receptor-like protein conserved in Plasmodium species

In October 2002, the complete sequence of the genome of the human malaria parasite Plasmodium falciparum was published. The data showed that as many as 60% of all identified open reading frames were unique to the parasite, with no known homologues in other species. Identification and characterization of novel molecules that may provide targets for drug and vaccine design is crucial to fight malaria. The aim of this project has been to analyse a novel gene and protein in Plasmodium. A short nucleotide fragment was originally identified in Plasmodium chabaudi chabaudi (AS) and the complete sequence subsequently obtained using Vectorette PCR. A singleexon gene was identified and Southern analysis showed the presence of a single copy in the P. chabaudi genome. Analysis of the protein secondary structure revealed a multidomain molecule consisting of an N-terminal secretion signal, two Scavenger Receptor Cysteine-Rich (SRCR) domains, three Limulus factor C, Coch-5b2 and Lgl1 (LCCL) modules and an LH2/PLAT domain. These motifs all have adhesive properties, and the protein was subsequently named Plasmodium SRCR LCCL Adhesive-like Protein (PSLAP). Multiple sequence alignment established that PSLAP is highly conserved within Plasmodium and also identified a paralogue in Toxoplasma gondii, suggesting it may play a specific and vital role in apicomplexan biology. Results from indirect immunofluoresence assays showed a punctate expression pattern contained within the parasite, indicating that the protein is distributed in vesicles. Northern analysis and immunofluorescence co-localisation studies showed transcription and expression in blood-stage gametocytes, demonstrating that PSLAP is a sexual stage protein.
The Mediating Role Of Self-Efficacy In The Relationship Between Problem Solving And Hope

The current study aims to investigate the relationship among problem solving, hope, and self-efficacy and to test a model for determining the role of self-efficacy in the relationship between problem solving and hope. It adopted convenience sampling and consisted of 494 undergraduate students (369 females; 125 males). The Hope Scale, General Self-Efficacy Scale and Problem Solving Inventory were applied in order to collect the data. Pearson correlation analysis and two-step Structural Equation Modelling were used for data analysis. Findings revealed that while a high level of positive correlation existed among problem solving, self-efficacy and hope, a moderate positive relationship was found between self-efficacy and hope. As a result of Structural Equation Modelling, self-efficacy was found to be significantly predicted by problem solving whereas hope was observed to be significantly predicted by problem-solving and self-efficacy. In addition, mediation analysis demonstrated that the relationship between problem solving and hope emerged through the development of self-efficacy. As a result, this paper exhibited that individuals with developing problem solving ability had also developing self-efficacy, which in turn leads to an increase in hope. Therefore, it may be effective to take into account the components that will improve individuals' problem solving skills and perceptions about themselves while conducting the studies to raise the hope level, which is an important concept of psychological health.
Optimizing lung cancer MDT data for maximum clinical impact—a scoping literature review

Multidisciplinary care in is widely recommended as best practice for lung cancer in many countries and jurisdictions. A number of studies suggest multidisciplinary care benefits patient outcomes, with analyses based on a range of data sources including national, state and local registries as well as multidisciplinary team meeting (MDT)-based data collections, often focused on different questions depending on data sources. MDT data collection and linkage are not standardized and not routine although data collection and feedback are specifically recommended by at least one statutory body. We performed a scoping review of current evidence for lung cancer MDT data collection and analysis, to identify discrete strategies through illustrative examples and to make recommendations for future approaches. Thirteen studies were identified that presented lung cancer MDT-related clinical outcomes, three included MDTs from multiple tumour streams while 10 studies focussed on lung cancer MDT meetings. Eleven studies measured the effect of MDT discussion on clinical outcomes of which eight were positive. Data sources included MDT records (3 studies), medical or hospital records (3 studies), institutional registries (5 studies) and state or national administrative datasets (6 studies), with some overlap. Examples of studies based on different data sources (local MDT, institutional registry, national registry) exemplified the different types of clinical research questions appropriate for each data source. While MDT data collection is not well-defined, the importance of clinical audit and data feedback and the potential for real-time analysis to improve outcomes deserve further investigation. Optimized datasets and linkage strategies are likely to maximize benefits for patients.
Soluble selectins and highly fucosylated α1-antichymotrypsin in rheumatoid arthritis patients

Introduction. Fucosylation of acute phase proteins and serum soluble selectin levels is increased in rheumatoid arthritis (RA) patients and can influence leukocyte extravasation. Aim. The aim of this study was to evaluate the concentration and fucosylation of α1-antichymotrypsin (ACT) in relation to serum concentrations of soluble forms of selectins in RA patients. Material and methods. Serum samples of 70 RA patients and 30 healthy controls were examined using sandwich enzyme‑linked immunosorbent assay (ELISA). Results. ACT-FR was significantly increased in RA patients when compared to healthy controls (p < 0.001) and significantly correlated with serum concentrations of rheumatoid factor (RF) and antibodies against cyclic citrullinated peptides (ACPA) (p = 0.006, p = 0.04, respectively). Moreover, we found significant correlations between the serum levels of soluble (s)P- and sE-selectin and ACT-FR (p = 0.008 and p = 0.03, respectively) only in male RA patients. Conclusions. Fucosylation of ACT differs between male and female RA patients and is related to sP- and sE-selectin levels only in men.
Gene replacement therapy provides benefit in an adult mouse model of Leigh syndrome

Mutations in nuclear-encoded mitochondrial genes are responsible for a broad spectrum of disorders among which Leigh syndrome (LS) is the most common in infancy. No effective therapies are available for this severe disease mainly because of the limited capabilities of the standard adeno-associated viral (AAV) vectors to transduce both peripheral organs and the central nervous system (CNS) when injected systemically in adults. Here, we used the brain-penetrating AAV-PHP.B vector to reinstate gene expression in the Ndufs4 KO mouse model of LS. Intravenous delivery of an AAV.PHP.B-Ndufs4 vector in 1-month old KO mice restored mitochondrial complex I activity in several organs including the CNS. This gene replacement strategy extended lifespan, rescued metabolic parameters, provided behavioral improvement, and corrected the pathological phenotype in the brain, retina, and heart of Ndufs4 KO mice. These results provide a robust proof that gene therapy strategies targeting multiple organs can rescue fatal neurometabolic disorders with CNS involvement.
Use of Machine Learning to Automate the Identification of Basketball Strategies Using Whole Team Player Tracking Data

The use of machine learning to identify and classify offensive and defensive strategies in team sports through spatio-temporal tracking data has received significant interest recently in the literature and the global sport industry. This paper focuses on data-driven defensive strategy learning in basketball. Most research to date on basketball strategy learning has focused on offensive effectiveness and is based on the interaction between the on-ball player and principle on-ball defender, thereby ignoring the contribution of the remaining players. Furthermore, most sports analytical systems that provide play-by-play data is heavily biased towards offensive metrics such as passes, dribbles, and shots. The aim of the current study was to use machine learning to classify the different defensive strategies basketball players adopt when deviating from their initial defensive action. An analytical model was developed to recognise the one-on-one (matched) relationships of the players, which is utilised to automatically identify any change of defensive strategy. A classification model is developed based on a player and ball tracking dataset from National Basketball Association (NBA) game play to classify the adopted defensive strategy against pick-and-roll play. The methodology described is the first to analyse the defensive strategy of all in-game players (both on-ball players and off-ball players). The cross-validation results indicate that the proposed technique for automatic defensive strategy identification can achieve up to 69% accuracy of classification. Machine learning techniques, such as the one adopted here, have the potential to enable a deeper understanding of player decision making and defensive game strategies in basketball and other sports, by leveraging the player and ball tracking data.
FPGA Implementation of Real-Time Pedestrian Detection Using Normalization-Based Validation of Adaptive Features Clustering

Presently, many researchers and engineers have investigated autonomous driving, which has significantly influenced the revolution of artificial intelligence (AI). One of the critical challenges for autonomous driving is the inadequate precision of autonomous vehicles in detecting pedestrians, which is a major safety hazard to human beings. In this paper, a Field Programmable Gate Array (FPGA) demonstration system with a normalization-based validity index (NbVI) has been proposed for real-time pedestrian detection. The proposed algorithm can accurately detect pedestrians by calculating the Manhattan distance between the target histogram of oriented gradient (HOG) features and real-time pedestrian HOG features. In lieu of sophisticated circuit layout and substantial training burden with neuron computation circuit, the proposed detection system with adaptive features clustering is hardware-friendly and is capable of real-time pedestrian detection using fewer training images with high detection rate (up to <inline-formula><tex-math notation="LaTeX">$99.2\%$</tex-math></inline-formula>). Moreover, the function execution time of pedestrian detection is shortened by <inline-formula><tex-math notation="LaTeX">$25\%$</tex-math></inline-formula> using FPGA acceleration.