Miracle-dz/UniFAR-FTUs huggingface dataset:
SpotMal: A hybrid malware detection framework with privacy protection for BYOD

The proliferation of mobile devices coupled with their increased computing capabilities has made them perfectly fit in the business environment. Bring Your Own Device (BYOD) is the phenomenon where individuals bring their own portable devices for connectivity and use in the workplace. BYODs introduce several benefits such as increased productivity and employee motivation but also a range of security challenges. Hackers have developed multifaceted malware targeting these BYODs. Research has been done on mobile malware detection however, because of their resource-constraint, the adoption of PC-based malware detection methods such as signature and behavior-based detection techniques has proved to be challenging. Users have cited privacy concerns when these virus detection techniques are remotely applied on the BYOD for example cloud-based detection since these devices are used for both personal and work data storage. This paper examines the threat of mobile malware to organizations that have adopted BYOD and current solutions to this threat. Additionally, a hybrid malware detection framework with privacy protection for BYOD and smart-work environments is proposed to detect malware without compromising the privacy and confidentiality of personal sensitive data.
The Future Is Now: The Formation of Single Low-Mass White Dwarfs in the Solar Neighborhood

Low-mass helium-core white dwarfs (M < 0.45 M☉) can be produced from interacting binary systems, and traditionally all of them have been attributed to this channel. However, a low-mass white dwarf could also result from a single star that experiences severe mass loss on the first ascent giant branch. A large population of low-mass He-core white dwarfs has been discovered in the old metal-rich cluster NGC 6791. There is therefore a mechanism in clusters to produce low-mass white dwarfs without requiring binary star interactions, and we search for evidence of a similar population in field white dwarfs. We argue that there is a significant field population (of order half of the detected systems) that arises from old metal-rich stars which truncate their evolution prior to the helium flash from severe mass loss. There is a consistent absence of evidence for nearby companions in a large fraction of low-mass white dwarfs. The number of old metal-rich field dwarfs is also comparable with the apparently single low-mass white dwarf population, and our revised estimate for the space density of low-mass white dwarfs produced from binary interactions is also compatible with theoretical expectations. This indicates that this channel of stellar evolution, hitherto thought hypothetical only, has been in operation in our own Galaxy for many billions of years. One strong implication of our model is that single low-mass white dwarfs should be good targets for planet searches because they are likely to arise from metal-rich progenitors. We also discuss other observational tests and implications, including the potential impact on SNIa rates and the frequency of planetary nebulae.
An Elliptical Boundary Model for Skin Color Detection

Automatic skin detection has been intensively studied for human-related recognition systems. A Gaussian model for skin detection is a well-known approach with its simplicity and generality. In this paper, we discuss limitations of the Gaussian model and suggest a new statistical color model for skin detection, called an elliptical boundary model. The suggested model overcomes the limitations of the Gaussian model with better performance. From the experiment performed on six chrominance spaces, it gives the much higher correct detection ratio than a single Gaussian model. As compared to the mixture of Gaussian model suggested to improve the correct detection ratio of a single Gaussian at the expense of slower speed, the elliptical boundary model still gives the better correct detection ratio with faster speed.
Src Family Kinase Activity Is Up-Regulated in Hormone-Refractory Prostate Cancer

Purpose: Although Src family kinase (SFK) inhibitors are now in clinical trials for the treatment of androgen-independent prostate cancer (AIPC), there are no studies relating SFK activation to patient survival. This study was designed to determine if SFK activation was up-regulated with the development of AIPC and if patients could be selected who were more likely to respond to therapy. Experimental Design: A unique cohort of matched prostate tumor samples, taken before hormone deprivation therapy and following hormone relapse, was used to determine by immunohistochemistry on an individual patient basis if SFK activity changed with progression to AIPC and whether this related to patient outcome measures. Using matched, hormone-sensitive and hormone-refractory cell lines, we determined if hormone status affected the way prostate cancer cells respond to suppression of SFK activity by the small-molecule inhibitor dasatinib. Results: In the current study, 28% of patients with AIPC exhibited an increase in SFK activity in prostate cancer tissue, these patients had significantly shorter overall survival (P<0.0001), and activated SFK expression correlated with the presence of distant metastases. Dasatinib inhibited phosphorylation of Src and Lyn and the downstream substrate FAK in hormone-sensitive and hormone-refractory cell lines. Although migration was reduced by dasatinib in both cell lines, proliferation of hormone-refractory cells only was inhibited. Conclusion: Appropriate patient selection may allow better targeting of prostate cancer patients who are likely to respond to the treatment with SFK inhibitors at the same time improving the outcome of clinical trials.
Time-frequency signal decomposition using energy mixture models

We address the problem of signal decomposition. We specify signal components by the property that their energies are localised and disjoint in the time-frequency plane. Rather than modelling the signal directly, we represent the time-frequency energy of the signal using a finite mixture model. This model is used to develop a partitioning of the time-frequency plane, allowing the application of time-frequency filtering to isolate components. Modelling energy rather than specifying a dictionary of allowable waveforms imposes fewer constraints on what a component may be. We demonstrate how the approach can be applied in the context of vibration analysis, where we wish to isolate the structure of individual bending waves travelling through a beam.
Physical Exercise-Induced Adult Neurogenesis: A Good Strategy to Prevent Cognitive Decline in Neurodegenerative Diseases?

Cumulative evidence has indicated that there is an important role for adult hippocampal neurogenesis in cognitive function. With the increasing prevalence of cognitive decline associated with neurodegenerative diseases among the ageing population, physical exercise, a potent enhancer of adult hippocampal neurogenesis, has emerged as a potential preventative strategy/treatment to reduce cognitive decline. Here we review the functional role of adult hippocampal neurogenesis in learning and memory, and how this form of structural plasticity is altered in neurodegenerative diseases known to involve cognitive impairment. We further discuss how physical exercise may contribute to cognitive improvement in the ageing brain by preserving adult neurogenesis, and review the recent approaches for measuring changes in neurogenesis in the live human brain.
Exploiting multiuser diversity in reservation random access

In this paper, we study the uplink of a cellular network where reservation random access schemes such as reservation slotted ALOHA and reservation slotted nonpersistent ISMA are used for multiple access. When channel state information is not available to users when they contend for channel access, we find that capture effect inherent in wireless communications can exploit the channel variations and reserve users with favorable channels for data transmission. We investigate two channel models where in the first model, channel variations come from time-varying Nakagami-m fading and in the second model, mobile users have both time-varying fading and path loss
Power-Aware spatial multiplexing with unilateral Antenna cooperation

This thesis offers a power aware solution to the problem of spatial multiplexing of independent data streams in a multi-antenna system, assuming that either the transmit antennas or the receive antennas are not allowed to cooperate and a sum power constraint is imposed. Cooperation is achieved by using spatial linear filters (beamformers), which are optimized jointly with the power allocation. To this end, the spatial channel characteristics must be known at the cooperating side. The design goal is to achieve individual signal-to-interference-plus-noise ratios (SINR) with minimal power consumption. This problem occurs, e.g., in a cellular wireless communication system, where a multi-antenna base station communicates simultaneously with several decentralized mobile terminals, each equipped with a single antenna. Downlink and uplink correspond to cooperating transmit and receive antennas, respectively. As a first approach to this optimization problem, the beamformers are assumed to be fixed. This allows for a characterization of the global optimum, which will prove useful for the following analysis. It turns out that there is a fundamental duality between uplink and downlink spatial multiplexing. In particular, the same SINR values can be achieved in both channels under the same power constraint. Hence, a solution of the downlink problem, which has a complicated analytical structure, can be found by solving the “smoother” uplink problem instead. A second important step towards a general solution is the investigation of joint beamforming in the absence of noise, as proposed by Gerlach and Paulraj [10]. This problem consists of minimizing a non-differentiable `∞ objective function. A key step in finding a global solution is to formulate an equivalent eigenvalue optimization problem and to show that each local minimum is a global minimum. Also, there is an interesting relation between optimal `∞ optimization and the alternative `1 objective proposed by [10]. The analytical results of this study lead to the development of globally convergent algorithms with strictly monotone iteration sequences. Typically, only a few iteration steps are required. The insight gained from studying interference balancing in the absence of noise is used to derive a power aware strategy for SINR balancing with minimal power consumption. This new algorithm has the same excellent convergence behavior as the one derived for the noiseless case. By choosing individual target thresholds, arbitrary SINR levels can be achieved as long as the problem is feasible. Necessary
Kahler manifolds and supersymmetry

Supersymmetric field theories of scalars and fermions in 4-D space-time can be cast in the formalism of Kahler geometry. In these lectures I review Kahler geometry and its application to the construction and analysis of supersymmetric models on Kahler coset manifolds. It is shown that anomalies can be eliminated by the introduction of line-bundle representations of the coset symmetry groups. Such anomaly-free models can be gauged consistently and used to construct alternatives to the usual MSSM and supersymmetric GUTs.
Kinesin-8 effects on mitotic microtubule dynamics contribute to spindle function in fission yeast

Kinesin-8 motor proteins destabilize microtubules and increase chromosome loss in mitosis. In fission yeast, aberrant microtubule-driven kinetochore pushing movements, tripolar mitotic spindles, and fluctuations in metaphase spindle length occurred in kinesin-8–deletion mutants. A mathematical model can explain these results.
IDS Alert Correlation in the Wild With EDGe

Intrusion detection systems (IDSs) produce a large number of alerts, which overwhelm their operators, e.g., a deployment of the popular Snort IDS in the campus network of ETH Zurich (which includes more than 40 thousand hosts) produces on average 3 million alerts per day. In this paper, we introduce an IDS alert correlator, which we call Extrusion Detection Guard (EDGe), to detect infected hosts within a monitored network from IDS alerts. EDGe detects several malware that exhibit a multi-stage behavior and it can identify the family and even variant of certain malware, which helps to remediate and prioritize incidents. Our validation based on manual real-time analysis of a sample of detected incidents shows that only 15% of the detected infections are false positives. In addition, we compare EDGe with a state-of-the-art previous work and show that EDGe finds 60% more infections and has a lower number of false positives. A large part of this paper focuses on characterizing 4,358 infections (13.4 new infections per day) detected with EDGe from a unique dataset of 832 million IDS alerts collected from an operational network over a period of 9 months. Our characterization shows that infections exhibit spatial correlations and attract many further inbound attacks. Moreover, we investigate attack heavy hitters and show that client infections are significantly more bursty compared to server infections. Finally, we compare the alerts produced by different malware families and highlight key differences in their volume, aliveness, fanout, and severity.
Dynamic analysis of the demolding process for PDMS microstructures with high aspect ratio

This study aims to investigate several peel demolding schemes through numerical simulations for demolding of the PDMS film with high aspect ratio microstructures. Motivated by the need to improve the yield rate of our first generation, rotating arm based peel demolding system, numerical models based on the explicit dynamic finite element method are developed in order to identify a minimum stress design of the process which can minimize the maximum stress of microstructures during demolding. A scale-up approach is proposed to reduce computational time for the micro-scale problems. The experimental tests are also carried out to verify the findings from numerical simulations. From this study, the roller based demolding system is identified as the optimal scheme in our analysis cases and is developed as our next generation automatic demolding system (the maximum pillar stress can reduce 20% comparing to the rotating arm scheme).
Convolutional codes under a minimal trellis complexity measure

We conduct a code search, restricted to the recently introduced class of generalized punctured convolutional codes, under the minimal trellis complexity measure defined by McEliece and Lin. For the same decoding complexity and the same code rate, new codes are compared to well-known existing classes of convolutional codes. Some of the best convolutional codes (in a distance spectrum sense) of existing and new trellis complexities are tabulated.
A Failure Detection and Prediction Mechanism for Enhancing Dependability of Data Centers

 Abstract—Modern data centers continue to grow in their scale and complexity. They are changing dynamically as well due to the addition and removal of system components, changing execution environments, frequent updates and upgrades, online repairs and more. Classical reliability theory and conventional methods do rarely consider the actual state of a system and are therefore not capable to reflect the dynamics of runtime systems and failure processes. In this paper, we present an unsupervised failure detection and prediction method using an ensemble of Bayesian models. It characterizes normal execution states of the system and detects anomalous behaviors. We implement a prototype of our failure detection and prediction mechanism and evaluate its performance on a data center test platform. Experimental results show that our proposed method can forecast failure dynamics with high accuracy.
Divalent transition metal cations counteract potassium-induced quadruplex assembly of oligo(dG) sequences.

Nucleic acids containing tracts of contiguous guanines tend to self-associate into four-stranded (quadruplex) structures, based on reciprocal non-Watson-Crick (G*G*G*G) hydrogen bonds. The quadruplex structure is induced/stabilized by monovalent cations, particularly potassium. Using circular dichroism, we have determined that the induction/stabilization of quadruplex structure by K+is specifically counteracted by low concentrations of Mn2+(4-10 mM), Co2+(0.3-2 mM) or Ni2+(0.3-0.8 mM). G-Tract-containing single strands are also capable of sequence-specific non-Watson-Crick interaction with d(G. C)-tract-containing (target) sequences within double-stranded DNA. The assembly of these G*G.C-based triple helical structures is supported by magnesium, but is potently inhibited by potassium due to sequestration of the G-tract single strand into quadruplex structure. We have used DNase I protection assays to demonstrate that competition between quadruplex self-association and triplex assembly is altered in the presence of Mn2+, Co2+or Ni2+. By specifically counteracting the induction/stabilization of quadruplex structure by potassium, these divalent transition metal cations allow triplex formation in the presence of K+and shift the position of equilibrium so that a very high proportion of triplex target sites are bound. Thus, variation of the cation environment can differentially promote the assembly of multistranded nucleic acid structural alternatives.
The effect of glucocorticoids on tendon cell viability in human tendon explants

Background and purpose Previous studies on the culture of human tenocytes have shown that dexamethasone and triamcino-lone reduce cell viability, suppress cell proliferation, and reduce collagen synthesis. However, such cell cultures lack the extracellular matrix and three-dimensional structure of normal tendons, which affects their response to stimuli. We established a human tendon explant culture system and tested the effects of dexamethasone and triamcinolone on cell viability. Methods Primary human tendon explant cultures were prepared from healthy hamstring tendons. Tendon strips were harvested from hamstring tendons and cultured in 24-well plates in Dulbecco’s modification of Eagle’s Medium (DMEM) supplemented with 2% fetal calf serum. The tendon explants were treated with 0 μM (control), 10 μM, or 100 μM dexamethasone sodium phosphate or 0 μM (control), 10 μM, or 100 μM triamcinolone acetonide in DMEM for 96 h. Cell viability was measured by Alamar blue assay before and after glucocorticoid treatment. Results Incubation with 10 μM and 100 μM dexamethasone reduced cell viability in human tendon explants by 35% and 45%, respectively, as compared to a 6% increase in the controls (p = 0.01, mixed-effects ANOVA). Triamcinolone at 10 μM and 100 μM reduced cell viability by 33% and 36%, respectively, as compared to a 9% increase in the controls (p = 0.07, mixed-effects ANOVA). Interpretation Human tendon explant cultures can be used to study the effects of glucocorticoids on human tendon. Dexamethasone and triamcinolone suppress the cell viability of human tendon in its natural 3-dimensional environment with matrix anchorage. Human tendon explant cultures provide a species-specific model for further investigation of the effects of glucocorticoids on the metabolism of the extracellular matrix of human tendon, and on its mechanical properties.
Comparison of Oxidative Stress Status in Dogs Undergoing Laparoscopic and Open Ovariectomy

ABSTRACT The present study evaluated and compared the oxidative stress status of dogs undergoing laparoscopic or open ovariectomy. Twelve healthy female dogs were divided into two groups according to the type of the surgical procedure, laparoscopic or open ovariectomy. Plasma total oxidant status (TOS), total antioxidant status (TAS) and oxidative stress index (OSI) levels for the evaluation of oxidative stress were determined. Increases in plasma TOS and OSI levels and decreases in TAS levels were observed in both groups after surgery. The TOS level was significantly lower in the laparoscopic ovariectomy group compared with the open surgery group. Laparoscopic ovariectomy is a safe and beneficial surgical alternative to traditional ovariectomy with respect to oxidative stress status in dogs.
The Variable-Star Population in Phoenix: Coexistence of Anomalous and Short-Period Classical Cepheids and Detection of RR Lyrae Variables

We present the results of a search for variable stars in the Local Group dwarf galaxy Phoenix. Nineteen Cepheids, six candidate long-period variables, one candidate eclipsing binary, and a large number of candidate RR Lyrae stars have been identified. Periods and light curves have been obtained for all the Cepheid variables. Their distribution in the period-luminosity diagram reveals that both anomalous Cepheids (ACs) and short-period classical Cepheids (s-pCC's) are found in our sample. This is the first time that both types of variable stars are identified in the same system even though they likely coexist, but have gone unnoticed so far, in other low-metallicity galaxies such as Leo A and Sextans A. We argue that the conditions for the existence of both types of variable stars in the same galaxy are a low metallicity at all ages and the presence of both young and intermediate-age (or old, depending on the nature of AC) stars. The RR Lyrae candidates trace, together with the well-developed horizontal branch, the existence of an important old population in Phoenix. The different spatial distributions of s-pCC's, ACs, and RR Lyrae variables in the Phoenix field are consistent with the stellar population gradients found in Phoenix, in the sense that the younger population is concentrated in the central part of the galaxy. The gradients in the distribution of the young population within the central part of Phoenix, which seem to indicate a propagation of the recent star formation, are also reflected in the spatial distribution of the s-pCC's.
A Method to Annotate Programs with High-Level Knowledge of Computation

When programming in languages such as C, Java, etc., it is difficult to reconstruct the programmer's ideas only from the program code. This occurs mainly because, much of the programmer's ideas behind the implementation are not recorded in the code during implementation. For example, physical aspects of computation such as spatial structures, activities, and meaning of variables are not required as instructions to the computer and are often excluded. This makes the future reconstruction of the original ideas difficult. AIDA, which is a multimedia programming language based on the cyberFilm model, can solve these problems allowing to describe ideas behind programs using advanced annotation methods as a natural extension to programming. In this paper, a development environment that implements the AIDA language is presented with a focus on the annotation methods. In particular, an actual scientific numerical computation code is created and the effects of the annotation methods are analyzed. Keywords—cyberFilm, development environment, knowledge engineering, multimedia programming language