Miracle-dz/UniFAR-FTUs huggingface dataset:
SecureESFS: Sharing Android External Storage Files in A Securer Way

As an essential component on Android devices, External Storage is frequently used for sharing files between different apps. Therefore, compared to Internal Storage, the access control on the External Storage is usually very loose. However, a lot of sensitive files might be stored on the External Storage, which makes it an attractive target for the attackers. Since Android 10, a security mechanism named Scoped Storage has been introduced to protect the sensitive files on the External Storage. However, this mechanism is mainly used to protect the app-specific files, and can't support the sharing of sensitive files between trusted apps in a secure and flexible way. In this paper, we present a secure External Storage sensitive file sharing solution named SecureESFS. It first extends a Linux kernel security mechanism named ACL on the SDCardFS filesystem to protect the External Storage. With different ACL policy settings, the user can dynamically share sensitive files between trusted apps according to specific business needs. We also enforce the integrity protection on the ACL policies by checking the hash message authentication codes (HMAC) of these policies. Moreover, we design a transparent encryption mechanism in SecureESFS to protect the sensitive files on the External Storage, when the Android devices are physically accessed by the attackers, such as removing the SD card. For versions lower than Android 10, SecureESFS can provide independent protection and secure sharing for the sensitive files on the External Storage. For versions higher than Android 10, SecureESFS can achieve the secure sharing of sensitive files while Scoped Storage provides protection for the app-specific files. SecureESFS may also be used to enhance the security of the Scoped Storage mechanism. Experiments conducted on a prototype show that SecureESFS works well and incurs acceptable overhead.
Trust and Believe - Should We? Evaluating the Trustworthiness of Twitter Users

Social networking and micro-blogging services, such as Twitter, play an important role in sharing digital information. Despite the popularity and usefulness of social media, they are regularly abused by corrupt users. One of these nefarious activities is so-called fake news - a virus that has been spreading rapidly thanks to the hospitable environment provided by social media platforms. The extensive spread of fake news is now becoming a major problem with far-reaching negative repercussions on both individuals and society. Hence, the identification of fake news on social media is a problem of utmost importance that has attracted the interest not only of the research community but most of the big players on both sides - such as Facebook, on the industry side, and political parties on the societal one. In this work, we create a model through which we hope to be able to offer a solution that will instill trust in social network communities. Our model analyses the behaviour of 50,000 politicians on Twitter and assigns an influence score for each evaluated user based on several collected and analysed features and attributes. Next, we classify political Twitter users as either trustworthy or untrustworthy using random forest and support vector machine classifiers. An active learning model has been used to classify any unlabeled ambiguous records from our dataset. Finally, to measure the performance of the proposed model, we used accuracy as the main evaluation metric.
An Arithmetic Differential Privacy Budget Allocation Method for the Partitioning and Publishing of Location Information

The rapid development of mobile Internet services and the wide application of intelligent terminals has accelerated the advent of the promising era of big data. A number of big data services based on location information bring convenience to users, however, it also results in serious leakage of personal privacy. The partitioning and publishing method combined with the differential privacy model can provide better range counting query results under the premise of ensuring the privacy of users' location. Nevertheless, most of the existing research studies only focus on the structural design during the partitioning process of location big data and ignore the impact of differential privacy budget allocation methods on the published results. This paper, therefore, proposes an efficient arithmetic privacy budget allocation strategy for the tree-based partitioning and publishing of location big data which satisfies the $\varepsilon$-differential privacy. Experimental results over a large number of real-world datasets prove that the proposed privacy budget allocation method is superior in contrast to the existing methods for improving the usability of the published data.
A Compliance Control Method Based on Viscoelastic Model for Position-Controlled Humanoid Robots

Compliance is important for humanoid robots, especially a position-controlled one, to perform tasks in complicated environments where unexpected or sudden contacts will result in large impacts which may cause instability or destroy the hardware of robots. This paper presents a compliance control method based on viscoelastic model for humanoid robots to survive on these conditions. The viscoelastic model is used to obtain the relationship between the differential of contact force/torque and linear/angular position. Thus a state equation of this model can be established and a state feedback controller adjusting the position to adapt to the contact force/torque can be designed to realize the compliant movement. The proposed compliance control method based on viscoelastic model has been employed in ankle compliance for stable walking on indefinite uneven terrain and arm compliance for falling protection on BHR-6P, a position-controlled humanoid robot, which validates its effectiveness.
Human Gait Phase Recognition using a Hidden Markov Model Framework*

Analysis of human daily living activities, particularly walking activity, is essential for health-care applications such as fall prevention, physical rehabilitation exercises, and gait monitoring. Studying the evolution of the gait cycle using wearable sensors is beneficial for the detection of any abnormal walking pattern. This paper proposes a novel discrete/continuous unsupervised Hidden Markov Model method that is able to recognize six gait phases of a typical human walking cycle through the use of two wearable Inertial Measurement Units (IMUs) mounted at both feet of the subject. The results obtained with the proposed approach were compared to those of well-known supervised and unsupervised segmentation approaches. The obtained results show the efficiency of the proposed approach in accurately recognizing the different gait phases of a human gait cycle. The proposed model allows the consideration of the sequential aspect of the walking gait phases while operating in an unsupervised context that avoids the process of data labeling, which is often tedious and time-consuming, particularly within a massive-data context.
Progress on n‐type doping of AlGaN alloys on AlN single crystal substrates for UV optoelectronic applications

As the building blocks of deep UV light emitting diode (LED) technology and high-power electronic devices, AlGaN alloys have attracted considerable attention. In this study, AlGaN films with varying compositions doped with Si were deposited on homoepitaxial AlN layers grown on AlN single crystal substrates. The room temperature resistivity of AlGaN alloys of different compositions grown on AlN and sapphire substrates with a constant Si doping level of 6x1018 cm-3 was compared. AlGaN films grown on AlN substrates consistently exhibited a lower n-type resistivity than those grown on sapphire. An n-type resistivity of 0.1 Ω cm was obtained for an AlGaN film with 80% Al content and a sheet resistance of 235 Ω/sq. for an AlGaN film with 70% Al content. The carrier activation energy as a function of Al content in AlGaN for these n-type films was measured. For compositions below 80% Al, the activation energy was around 15 meV due to impurity potential screening. For higher Al compositions, the carrier concentration was limited by a high compensation ratio, except for AlN, which has activation energy of 250 meV. (© 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Monitoring Mental Heal TH Using Physiological Signals

Some of the indicators of suicidal tendencies are mental health issues like Anxiety and Depression, ADHD, PTSD, etc. Even though there are doctors who help to stabilize these conditions, it is difficult for them to analyze the individual's daily emotional state and tendencies. This may lead to difficulties in diagnosis and may also affect the treatment of the individuals. To overcome this problem, a monitoring system which routinely monitors the mental state of the individual and also detects if there are any signs or symptoms of serious mental health issues is required. The Proposed system uses input peripheral data like GSR data, ECG signal of the individuals respectively. The ECG and GSR data are run through a regression system which predicts several indicators for classification like, valence, arousal, dominance, familiarity and liking. The original data along with the predicted data are collected and input into a classification algorithm like Support Vector Machine (SVM) algorithm. The obtained classified emotion is then sent to an inference engine which with each input of emotion infers if the individual has any mental health condition like Anxiety disorder and Depression.
Multiscale Computational Analysis of the Effect on Heart Rate of a HCN4 Gene Double Mutation: From the Single Channel to the Clinical Phenotype

This work aims to assess: I) the effects of the 1479V/A485E HCN4 channel double mutation (DM), II) the role of cellular coupling (p) and III) the role of cellular heterogeneity (σ) on systems of increasing complexity: ionic channel, single cell, 1D fibre and 2D tissue of the human SAN. The Fabbri et al. model was used to describe the human SAN cell and to build the 1D and 2D models, which are constituted of 100 and 2500 (50×50) cells, respectively. σ = 0.05, 0.1, 0.1873, 0.3, 0.4 and p = 10, 100, 1000, 10000 and ∞ MΩ. m were simulated, in order to test their effect on the heart rate (HR). The reduction of If current due to the heterozygous condition (gj(WT0.5 + DM) = 45% of gf(WT)) leads to an increase of the cycle length of the simulated action potential of a single cell (924 vs 814 ms; + 14%). This WT0.5+DM bradycardic effect is confirmed also by the 1D model (802 vs 690 ms; +14%) as well as by the 2D one (908 vs 794 ms; +14%). These results were obtained forσ = 0.1873 and p = 100 MΩ· m (50 MΩ. m in 1D). Other combinations of σ and p can provide changes in HR greater than 50%, highlighting the importance of these two parameters in the establishment of a physiologic pacing in the human SAN.
A Robotic Gripper Design and Integrated Solution Towards Tunnel Boring Construction Equipment

Creative design of grippers on their configurations, mechatronics control system, and multi-component collaborative algorithms is often utilized to realize complex operations in industrial applications, due to the environmental constraints or specific task requirements. Firstly, this paper introduces the background problems. As the main automatic equipment -- the shield machine -- in the field of tunnel boring construction, needs frequent tool (cutter) replacement during underground process, but has no practical automatic method yet, due to heavy payload, complex environment and work procedure. Thus, an integrated solution was proposed by developing a specific gripper and a snake-like manipulator to accomplish tool replacement in a cooperative way. Through simple and unique design of relative components, the solution realizes a fully automatic and precise approach including heavy load tool grasping and regrasping, posture adjustment, unlocking and disassembly, and installation and locking. Finally, this paper also describes the experimental process of tool replacement by the prototype under a real working condition, and discusses the feasibility of putting the scheme into practical application through comparison.
Formalization of Robot Skills with Descriptive and Operational Models

In this paper, we propose a formal language to specify robot skills, i.e. the elementary behaviours or functions provided by the robot platform in order to perform an autonomous mission. The advantage of the language we propose is that it integrates a wide range of elements that allows to define and provide automatic translation both to operational models, used online to control the skill execution, and descriptive models, allowing to reason about the expected skill execution, and then apply automated planning or model-checking taking skill models into account.
The Relationship between Job Stress and Job Satisfaction among Saudi Nurses: A Cross-Sectional Study

Background: The productivity of nurses and patient healthcare is highly influenced by nurses’ stress-related factors and job satisfaction. Nursing is the least preferred career opportunities for Saudi residents as compared to other options. Nurses’ perceptions of intention to quit contributes to their shortage in Saudi health care institutions.Purpose: The study aimed to examine the relationship between work-related stress and job satisfaction among Saudi nurses working at a public hospital.Methods: The research used a cross-sectional design that collected data from samples of 297 nurses working at a specified public hospital and aged over than 20 years old. Convenient sampling was employed to recruit the samples. Data were collected using the Expanded Nursing Stress Scale (ENSS) and Job Satisfaction Scale (JSS). The Statistical Package for Social Sciences (SPSS) version 20.0 was applied, and Pearson’s correlation test was to identify the relationship between variables.Results: The results indicated that the nurses at the hospital where the study took place experienced low levels of stress with a mean value of 2.1995. Besides, the nature of work indicated maximum job satisfaction with a mean value of 15.666, whereas minimum job satisfaction levels (11.569), were related to benefits provided to nurses. A positive correlation was found between the level of stress and satisfaction with a p-value of 0.041. Conclusion: The stress factors were highly correlated with job satisfaction. The identification of stress factors is important as it may create a negative impact on patients’ care and their well-being. It is suggested that changes in managerial affairs and policies are essential for implementing beneficial strategies that may assist in resolving the issue.
Modelling Health Process and System Requirements Engineering for Better e-Health Services in Saudi Arabia

This systematic review aimed to examine the published works on e-health modelling system requirements and suggest one applicable to Saudi Arabia. PRISMA method was adopted to search, screen and select the papers to be included in this review. Google Scholar was used as the search engine to collect relevant works. From an initial 74 works, 20 were selected after all screening procedures as per PRISMA flow diagram. The 20 selected works were discussed under various sections. The review revealed that goal setting is the first step. Using the goals, a model can be created based on which system requirements can be elicited. Different research used different approaches within this broad framework and applied the procedures to varying healthcare contexts. Based on the findings, an attempt has been made to set the goals and elicit the system requirements for a diabetes self-management model for the entire country in Saudi Arabian context. This is a preliminary model which needs to be tested, improved and then implemented.
Surface-enhanced Raman scattering

We present an introduction to surface-enhanced Raman scattering (SERS) which reviews the basic experimental facts and the essential features of the mechanisms which have been proposed to account for the observations. We then review very recent fundamental developments which include: SERS from single particles and single molecules; SERS from fractal clusters and surfaces; and new insights into the chemical enhancement mechanism of SERS.
Feasible rounding approaches for equality constrained mixed-integer optimization problems

A feasible rounding approach is a novel technique to compute good feasible points for mixed-integer optimization problems. The central idea of this approach is the construction of a continuously described inner parallel set for which any rounding of any of its elements is feasible in the original mixed-integer problem. It is known that this approach is promising for problems in which no equality constraints on integer variables appear. Yet, so far the potential of incorporating equality constraints with integer variables into this approach remained unclear. In this article, we close this gap by developing a reduction scheme that enables the application of feasible rounding approaches to problems in which such equality constraints occur. Our computational study on a large test bed of MIPLIB instances shows that this reduction is applicable to a relevant share of practical problems. Moreover, our results illustrate that a non-empty inner parallel set is possible, but less likely to occur for practical problems with equality constraints on integer variables. Finally, our results indicate that the application of a feasible rounding approach can be beneficial for the computation of good feasible points even under the occurrence of equality constraints on integer variables.
Combined Effects of Manganese, Iron, Copper, and Dopamine on Oxidative DNA Damage

Manganese (Mn) damages the central nervous system and causes Parkinson's disease (PD)-like syndrome called manganism. Abnormal accumulation of Mn and iron (Fe) is observed in the basal nuclei of patients with PD. Dopamine induces oxidative DNA damage in the presence of Fe or copper (Cu) in vitro. Therefore, an Mn-induced neural disorder may involve combined actions of Mn, Fe/Cu, and catecholamines. Here we investigated the combined effects of Mn(II) on the DNA damage induced by dopamine and either Fe(III) or Cu(II). Mn(II) enhanced the formation of 7,8-dihydro-8-oxo-2'-deoxyguanosine (8-oxodG) induced by dopamine and Fe(III)/Cu(II), whereas Mn(II) did not induce 8-oxodG formation in the absence of Fe(III)/Cu(II). Mn(II) accelerated hydrogen peroxide (H2O2) production in the dopamine-Fe(III)/Cu(II) system. Furthermore, Mn(II) decreased superoxide anion radicals (O2•-) generated in the xanthine-xanthine oxidase system. These results indicate that Mn(II)-mediated enhancement of DNA damage is caused by facilitated conversion of O2•- to H2O2. In addition, Mn(II) accelerated the formation of aminochrome, an oxidized dopamine product, in the presence of Cu(II). This reaction may have involved Mn(III) accompanied by H2O2 production from O2•-, suggesting a mechanism for Mn-induced oxidative stress on dopaminergic neurons through the combined actions of Mn, Fe, Cu, and dopamine.
Raman Study on the Structure of Cysteamine Monolayers on Silver

Cysteamine (2-aminoethanethiol) monolayers were spontaneously formed on silver surfaces by chemisorption from cysteamine and cystamine solutions. The present surface-enhanced Raman scattering investigation of such layers shows that the conformation of the adsorbed molecules clearly depends on the preparation procedure, surrounding liquids, pH, and applied potential. A majority of trans conformers were obtained directly after adsorption from more concentrated cysteamine solutions. Adsorption from more diluted cysteamine solutions and solutions of the corresponding disulfide, cystamine, and storage of layers containing mainly trans conformers in water lead to a predominance of gauche conformers. The portion of trans conformers could be increased by lowering the pH and applying negative potential and by the adsorption of additional cysteamine. Time-resolved analyses showed that the changes of conformations proceed with time constants of about 20 min. The slow rearrangement should be attributed to a reversibl.
– Supplementary Material – Fast Kernelized Correlation Filter without Boundary Effect

This supplementary material contains four parts. 1) The formal steps of ACSII and CCIM (Sec.1). 2) The implementation details of nBEKCF-D, its comparison to trackers with ImageNet pre-trained features, and comments on C-COT, ECO, and UPDT (Sec.2). 3) An illustration to explain how Algorithm 2, CCIM, works exactly (Sec.4). 4) Mathematical proof of the correctness of CCIM (Sec.5).
A geometrically-based mean-field theory of polydisperse hard-sphere mixtures

We present a mean-field description of a system of polydisperse hard-spheres. The theory is based on the postulate that the excess statistical properties of a general polydisperse mixture are a function of the number, the mean diameter, surface area, and volume of the constituent particles. Within this model a corresponding states relationship holds between a general polydisperse system and a suitably chosen two-component mixture. This equivalence is used to derive approximate expressions for the free energy and pressure of polydisperse crystal and fluid phases. Quantitative results are presented for the case of a Schultz distribution of diameters. These free energies are used to calculate the solid–fluid phase diagram as a function of diameter polydispersity. We find a terminal polydispersity of 8.3% above which the polydisperse fluid remains stable at all densities. In contrast with recent simulations we find no evidence for a substantial fractionation in diameters between the coexisting fluid and solid phases.
Crystal structure of potassium tetramolybdate, K2Mo4O13, and its relationship to the structures of other univalent metal polymolybdates

K2Mo4O13 crystallises in the triclinic system, space group P, with Z= 2 in a unit cell of dimensions a= 7·972, b= 8·352, c= 10·994 A, α= 119·4, β= 62·7, and γ= 109·8°. Its structure, determined by three-dimensional Patterson and Fourier methods and refined by least-squares techniques, contains subunits of eight distorted MoO6 octahedra sharing edges, joined by a common edge to form infinite chains, with adjacent chains having no common oxygen atoms. The potassium ions occupy irregular eight-co-ordinate interchain sites. Rb2Mo4O13 is isomorphous with K2Mo4O13. The tetramolybdate chain structure is compared with those of some other anhydrous polymolybdates(VI), and the similarity of the subunit of eight octahedra to the basic units found in a number of complex molybdates, and to the hepta- and octa-molybdate polyanions, is discussed. The possible existence of polyanions in molybdate melts is considered, and the ability to predict polymolybdate structures from i.r. absorption spectra critically assessed.
Site–site pair correlation functions of water from 25 to 400 °C: Revised analysis of new and old diffraction data

Recent controversy in the literature about the structure of water away from ambient conditions is manifested by significant differences between the site–site pair correlation functions of water as derived from neutron diffraction data and the same quantities obtained in computer simulations using an effective pairwise potential for the intermolecular interactions. One possible explanation of the discrepancies between computer models of water and neutron diffraction results near the critical point is that they arise from uncertainties in the inelasticity correction, which is particularly large for light water. To test out this idea, a new method of obtaining the pair correlations is described. This new analysis method is applied both to the earlier neutron data on non-ambient water and on recently reported data for a range of densities at 573 K. For this newer data the incident neutron spectrum is derived from an ambient water moderator instead of the liquid methane (100 K) moderator of previous work, and .