Miracle-dz/UniFAR-FTUs huggingface dataset:
Dissecting ghost clicks: ad fraud via misdirected human clicks

FBI's Operation Ghost Click, the largest cybercriminal takedown in history, recently took down an ad fraud infrastructure that affected 4 million users and made its owners 14 million USD over a period of four years. The attackers hijacked clicks and ad impressions on victim machines infected by a DNS changer malware to earn ad revenue fraudulently. We experimented with the attack infrastructure when it was in operation and present a detailed account of the attackers' modus operandi. We also study the impact of this attack on real-world users and find that 37 subscriber lines were impacted in our data set. Also, 20 ad networks and 257 legitimate Web content publishers lost ad revenue while the attackers earned revenue convincing a dozen other ad networks that their ads were served on websites with real visitors. Our work expands the understanding of modalities of ad fraud and could help guide appropriate defense strategies.
SAL: Scaling data centers using Smart Address Learning

Multi-tenant data centers provide a cost-effective many-server infrastructure for hosting large-scale applications. These data centers can run multiple virtual machines (VMs) for each tenant, and potentially place any of these VMs on any of the servers. Therefore, for inter-VM communication, they also need to provide a VM resolution method that can quickly determine the server location of any VM. Unfortunately, existing methods suffer from a scalability bottleneck in the network load of the address resolution messages and/or in the size of the resolution tables. In this paper, we propose Smart Address Learning (SAL), a novel approach that expands the scalability of both the network load and the resolution table sizes, making it implementable on faster memory devices. The key property of the approach is to selectively learn the addresses in the resolution tables, by using the fact that the VMs of different tenants do not communicate. We further compare the various resolution methods and analyze the tradeoff between network load and table sizes. We also evaluate our results using real-life trace simulations. Our analysis shows that SAL can reduce both the network load and the resolution table sizes by several orders of magnitude.
A Variable Conversion Gain Star Mixer for Ka-Band Applications

A variable conversion gain star mixer for Ka-band applications has been presented. This monolithic microwave integrated circuit was implemented on AlGaAs/InGaAs/GaAs pseudomorphic high-electron-mobility transistor process with a chip size of 1.7times1. 7 mm2. The mixer is modified from conventional star mixer to apply dc bias. The conversion gain of the mixer, controlled by the voltage of the diodes, could be applied to meet gain compensation requirements in communication systems. From the measured results, the circuit can provide 11.9 dB conversion gain and 9.3 dB gain adjustment by controlling voltage from 0 to 0.7 V at 30 GHz.
“Redox Imaging” to Distinguish Cells with Different Proliferative Indexes: Superoxide, Hydroperoxides, and Their Ratio as Potential Biomarkers

The present study was directed to the development of EPR methodology for distinguishing cells with different proliferative activities, using “redox imaging. ” Three nitroxide radicals were used as redox sensors: (a) mito-TEMPO—cell-penetrating and localized mainly in the mitochondria; (b) methoxy-TEMPO—cell-penetrating and randomly distributed between the cytoplasm and the intracellular organelles; and (c) carboxy-PROXYL—nonpenetrating in living cells and evenly distributed in the extracellular environment. The experiments were conducted on eleven cell lines with different proliferative activities and oxidative capacities, confirmed by conventional analytical tests. The data suggest that cancer cells and noncancer cells are characterized by a completely different redox status. This can be analyzed by EPR spectroscopy using mito-TEMPO and methoxy-TEMPO, but not carboxy-PROXYL. The correlation analysis shows that the EPR signal intensity of mito-TEMPO in cell suspensions is closely related to the superoxide level. The described methodology allows the detection of overproduction of superoxide in living cells and their identification based on the intracellular redox status. The experimental data provide evidences about the role of superoxide and hydroperoxides in cell proliferation and malignancy.
Simplifying RDF Data for Graph-Based Machine Learning

From the perspective of machine learning and data mining applications, expressing data in RDF rather than a domain-specific for- mat can add complexity and obfuscate the internal structure. We in- vestigate and illustrate this issue with an example where bio-molecular graph datasets are expressed in RDF. We use this example to inspire pre- processing techniques which reverse some of the complications of adding semantic annotations, exposing those patterns in the data that are most relevant to machine learning. We test these methods in a number of clas- sification experiments and show that they can improve performance both for our example datasets and real-world RDF datasets.
Identification of Host Kinase Genes Required for Influenza Virus Replication and the Regulatory Role of MicroRNAs

Human protein kinases (HPKs) have profound effects on cellular responses. To better understand the role of HPKs and the signaling networks that influence influenza virus replication, a small interfering RNA (siRNA) screen of 720 HPKs was performed. From the screen, 17 HPKs (NPR2, MAP3K1, DYRK3, EPHA6, TPK1, PDK2, EXOSC10, NEK8, PLK4, SGK3, NEK3, PANK4, ITPKB, CDC2L5 (CDK13), CALM2, PKN3, and HK2) were validated as essential for A/WSN/33 influenza virus replication, and 6 HPKs (CDK13, HK2, NEK8, PANK4, PLK4 and SGK3) were identified as vital for both A/WSN/33 and A/New Caledonia/20/99 influenza virus replication. These HPKs were found to affect multiple host pathways and regulated by miRNAs induced during infection. Using a panel of miRNA agonists and antagonists, miR-149* was found to regulate NEK8 expression, miR-548d-3p was found to regulate MAPK1 transcript expression, and miRs -1228 and -138 to regulate CDK13 expression. Up-regulation of miR-34c induced PLK4 transcript and protein expression and enhanced influenza virus replication, while miR-34c inhibition reduced viral replication. These findings identify HPKs important for influenza viral replication and show the miRNAs that govern their expression.
Improving Classifier Performance by Autonomously Collecting Background Knowledge from the Web

Many websites allow users to tag data items to make them easier to find. In this paper we consider the problem of classifying tagged data according to user-specified interests. We present an approach for aggregating background knowledge from the Web to improve the performance of a classier. In previous work, researchers have developed technology for extracting knowledge, in the form of relational tables, from semi-structured websites. In this paper we integrate this extraction technology with generic machine learning algorithms, showing that knowledge extracted from the Web can significantly benefit the learning process. Specifically, the knowledge can lead to better generalizations, reduce the number of samples required for supervised learning, and eliminate the need to retrain the system when the environment changes. We validate the approach with an application that classifies tagged Fickr data.
31-Year-Old Female Shows Marked Improvement in Depression, Agitation, and Panic Attacks after Genetic Testing Was Used to Inform Treatment

This case describes a 31-year-old female Caucasian patient with complaints of ongoing depression, agitation, and severe panic attacks. The patient was untreated until a recent unsuccessful trial of citalopram followed by venlafaxine which produced a partial response. Genetic testing was performed to assist in treatment decisions and revealed the patient to be heterozygous for polymorphisms in 5HT2C, ANK3, and MTHFR and homozygous for a polymorphism in SLC6A4 and the low activity (Met/Met) COMT allele. In response to genetic results and clinical presentation, venlafaxine was maintained and lamotrigine was added leading to remission of agitation and depression.
Gradient Boosting on Stochastic Data Streams

Boosting is a popular ensemble algorithm that generates more powerful learners by linearly combining base models from a simpler hypothesis class. In this work, we investigate the problem of adapting batch gradient boosting for minimizing convex loss functions to online setting where the loss at each iteration is i.i. d sampled from an unknown distribution. To generalize from batch to online, we first introduce the definition of online weak learning edge with which for strongly convex and smooth loss functions, we present an algorithm, Streaming Gradient Boosting (SGB) with exponential shrinkage guarantees in the number of weak learners. We further present an adaptation of SGB to optimize non-smooth loss functions, for which we derive a O(ln N/N) convergence rate. We also show that our analysis can extend to adversarial online learning setting under a stronger assumption that the online weak learning edge will hold in adversarial setting. We finally demonstrate experimental results showing that in practice our algorithms can achieve competitive results as classic gradient boosting while using less computation.
A distributed and conflict-aware measurement method using local information exchange in overlay networks

Network resource information, including available bandwidth, propagation delay and packet loss ratio, should be obtained by measurements for maintaining effectiveness of overlay network services. Although measurement accuracy can be enhanced by frequent measurements, performing measurements with high frequency can cause measurement conflict problem, that increases the network load and degrades measurement accuracy. In this report, we propose a distributed and conflict-aware measurement method which can reduce measurement conflicts and obtain high measurement accuracy. The main idea is that overlay nodes exchanges the route information and measurement results only with neighboring overlay nodes, while decreasing the measurement frequency. Simulation results show that the relative error of measurement results of our method is less than half of that of an existing method when the total measurement overhead of both methods are equal. We also confirm that exchanging of measurement results contributes more to the enhancement of measurement accuracy than performing measurements.
Study on Text Similarity Measure Algorithms For English Language

In this modern era Text Similarity Measurement is one of the most vital concerns. We are constantly driven to improve our system to minimize human error by achieving high accuracy and Machine Learning algorithm is serving the same purpose in many aspects like plagiarism checking, answer script checking, optimized search engine etc. Over last decade there have been significant improvements in this era. This paper is focused to develop a text similarity system which will allow teachers to check a script by comparing with a standard answer registered in the system. The objective is not only limited to reduce the time but also eradicates the possibility of biasness. The book describes the algorithm process and accuracy checking with several examples to ensure a clear understanding.
Importance of CXC Chemokine Receptor 2 in the Homing of Human Peripheral Blood Endothelial Progenitor Cells to Sites of Arterial Injury

Circulating endothelial progenitor cells (EPCs) may contribute to endothelial regeneration; however, the exact mechanisms of their arterial homing remain elusive. We examined the role of the angiogenic chemokine receptor CXCR2 in the homing of human EPCs. Isolated EPCs expressed CXCR2 together with kinase insert domain–containing receptor, CD31, vascular endothelial cadherin, and CXCR4. Adhesion assays under flow conditions showed that EPCs preferentially adhered to &bgr;2-integrin ligands, that firm arrest on fibronectin or fibrinogen was enhanced by the CXCR2 ligands CXCL1 or CXCL7, and that blockade of CXCR2 significantly reduced EPC adhesion on platelet-coated endothelial matrix. This was corroborated by the involvement of CXCR2 in EPC recruitment to denuded areas of murine carotid arteries ex vivo and in vivo. Notably, blocking CXCR2 inhibited the incorporation of human EPCs expressing CXCR2 at sites of arterial injury in athymic nude mice. Immunoreactivity for the &bgr;-thromboglobulin isoform CXCL7 was observed in murine platelets and denuded smooth muscle cells (SMCs) early after wire injury, and transcripts for CXCL7 and CXCL1 were detected in isolated human arterial SMCs. Human KDR+CXCR2+ cells showed better in situ adhesion to injured murine carotid arteries than KDR+CXCR2− cells, were predominantly CD14+, and improved CXCR2-dependent endothelial recovery after injury in nude mice. In conclusion, our data clearly demonstrate the importance of CXCR2 for the homing of circulating EPCs to sites of arterial injury and for endothelial recovery in vivo.
Heat transfer enhancement in flow past triangular turbulence promoters in closed channels

Abstract The global competitiveness has led industries to investigate innovative strategies to increase heat transfer. This work is inserted within this context and focuses on heat transfer enhancement in plane channels using triangular turbulence promoters. The SST turbulence model is adopted owing to its improved capacity to simulate flows with adverse pressure gradients. Verification and validation are performed by comparing numerical results against theoretical/experimental/numerical data for a plane channel and backward facing step. The location of the turbulence promoters was investigated and the best performance (minimum pressure drop/maximum heat transfer rate) was achieved when the turbulence promoters are aligned and positioned close to one of the channel walls.
Cancer Treatment-Related Infertility: A Critical Review of the Evidence

Abstract Cancer treatments may compromise the fertility of children, adolescents, and young adults, and treatment-related infertility represents an important survivorship issue that should be addressed at diagnosis and in follow-up to ensure optimal decision-making, including consideration of pursuing fertility preservation. Risk of infertility varies substantially with patient and treatment factors. The ability to accurately assess fertility risk for many patients is hampered by limitations of the current literature, including heterogeneity in patient populations, treatments, and outcome measures. In this article, we review and synthesize the available data to estimate fertility risks from modern cancer treatments for both children and adult cancer survivors to enable clinicians to counsel patients about future fertility.
Locally efficient on-line strategies for routing packets along fixed paths

Most of the work done in the area of static routing concentrates on minimizing the runtime of the whole schedule rather than minimizing the runtime of individual packets, using global parameters such as the congestion and dilation of a path collection. In this paper, we study the problem of minimizing the routing time of individual packets, using local parameters. In fact, we present the first nearly optimal, truly on-line routing protocols for the following problems: l Packet switching: Assume that a fixed collection of paths is given. For every path p in this collection, let cP denote the maximum number of paths that share an edge with p, and let d, denote the length of p. Find a schedule such that the routing time of a packet following a path p merely depends on c, and dP. l Virtual circuit switching: Assume that a fixed set of sessions is given. For every session i, packets are injected at a rate 7; to follow a predetermined path of length di. If the sum of rates of the sessions using an edge is sufficiently small, find a schedule such that the routing time of a packet from session i merely depends on Ti and di. We also consider dynamic versions of the two problems together with a wide range of (stochastical and adversarial) injection models.
Smooth interpolation of orientations with angular velocity constraints using quaternions

In this paper we present methods to smoothly interpolate orientations, given N rotational key frames of an object along a trajectory. The methods allow the user to impose constraints on the rotational path, such as the angular velocity at the endpoints of the trajectory. We convert the rotations to quaternions, and then spline in that non-Euclidean space. Analogous to the mathematical foundations of flat-space spline curves, we minimize the net “tangential acceleration” of the quaternion path. We replace the flat-space quantities with curved-space quantities, and numerically solve the resulting equation with finite difference and optimization methods.
Mitochondrial intermediate peptidase is a novel regulator of sirtuin‐3 activation by caloric restriction

Sirtuin‐3 (SIRT3) regulates mitochondrial quality and is involved in the anti‐ageing and pro‐longevity actions of caloric restriction (CR). Here, we show that CR upregulates the mature form of SIRT3 and mitochondrial intermediate peptidase (MIPEP), a mitochondrial signal peptidase (MtSPase), in white adipose tissue. We also demonstrate that upregulation of mature SIRT3 is dependent on MIPEP in 3T3‐L1 cells, suggesting that MIPEP may contribute to the maintenance of mitochondrial quality during CRvia activation of SIRT3. This novel mechanism of SIRT3 activation through MIPEP facilitates the elucidation of additional molecular pathways of CR.
Anthocyanins and intestinal barrier function: a review

Chronic intestinal inflammation, occurring in inflammatory bowel diseases (IBD), is associated with compromised intestinal barrier function. Inflammatory cytokines disrupt tight junctions and increase paracellular permeability of luminal antigens. Thus, chronic intestinal barrier dysfunction hinders the resolution of inflammation. Dietary approaches may help mitigate intestinal barrier dysfunction and chronic inflammation. A growing body of work in rodent models of colitis has demonstrated that berry consumption inhibits chronic intestinal inflammation. Berries are a rich dietary source of polyphenolic compounds, particularly anthocyanins. However, berry anthocyanins have limited bioavailability and are extensively metabolized by the gut microbiota and host tissue. This review summarizes the literature regarding the beneficial functions of anthocyanin-rich berries in treating and preventing IBD. Here, we will establish the role of barrier function in the pathogenesis of IBD and how dietary anthocyanins and their known microbial catabolites modulate intestinal barrier function.
A 3D Graphical Based Password Security

In this paper, we propose and evaluate a scheme which is based on a virtual three-dimensional environment. Passwords provide security mechanism for authentication and protection services against unwanted access to resources. A graphical based password is one promising alternatives of textual passwords. According to human psychology, humans are able to remember pictures easily. In this paper, we have proposed a new hybrid graphical password based system, which is a combination of recognition and recall based techniques that offers many advantages over the existing systems and may be more convenient for the user. Our scheme is resistant to shoulder surfing attack and many other attacks on graphical passwords. This scheme is proposed for smart mobile devices (like smart phones i.e. ipod, iphone, PDAs etc).
Exploring the Ambivalent Effects of Control Modes on Project Performance Dimensions in Software Development Outsourcing

Although software development outsourcing (SDO) market continuously grows and various types of SDO are available, the control performance of SDOs is still complicated. Not only positive effects but also no effects and even negative effects of control have been reported. This study focuses on these mixed results and classifies control by modes and SDO project performance by sub-dimensions. The paper presents a theory and research model on the duality between each control mode and SDO performance sub-dimensions. The study results suggest that it is not the amount of control exercised, but rather the amount of individual control mode appropriate to the specific SDO goals to enhance SDO performance. It also provides realistic suggestions and guidelines to companies and organizations that need to improve SDO performance in practice.
Anaesthesia for patient with chronic obstructive pulmonary disease

The chronic obstructive pulmonary disease has become a disease of public health importance. Among the various risk factors, smoking remains the main culprit. In addition to airway obstruction, the presence of intrinsic positive end expiratory pressure, respiratory muscle dysfunction contributes to the symptoms of the patient. Perioperative management of these patients includes identification of modifiable risk factors and their optimisation. Use of regional anaesthesia alone or in combination with general anaesthesia improves pulmonary functions and reduces the incidence of post-operative pulmonary complications.
An intrinsic reward for affordance exploration

In this paper, we present preliminary results demonstrating how a robot can learn environmental affordances in terms of the features that predict successful control and interaction. We extend previous work in which we proposed a learning framework that allows a robot to develop a series of hierarchical, closed-loop manipulation behaviors. Here, we examine a complementary process where the robot builds probabilistic models about the conditions under which these behaviors are likely to succeed. To accomplish this, we present an intrinsic reward function that directs the robot's exploratory behavior towards gaining confidence in these models. We demonstrate how this single intrinsic motivator can lead to artifacts of behavior such as “novelty,” “habituation,” and “surprise. ” We present results using the bimanual robot Dexter, and explore these results further in simulation.
The Non-Muscle Myosin Heavy Chain 9 Gene (MYH9) Is Not Associated with Lupus Nephritis in African Americans

Background: African Americans (AA) disproportionately develop lupus nephritis (LN) relative to European Americans and familial clustering supports causative genes. Since MYH9 underlies approximately 40% of end-stage renal disease (ESRD) in AA, we tested for genetic association with LN. Methods: Seven MYH9 single nucleotide polymorphisms (SNPs) and the E1 risk haplotype were tested for association with LN in three cohorts of AA. Results: A preliminary analysis revealed that the MYH9 E1 risk haplotype was associated with ESRD in 25 cases with presumed systemic lupus erythematosus (SLE)-associated ESRD, compared to 735 non-SLE controls (odds ratio 3.1; p = 0.010 recessive). Replication analyses were performed in 583 AA with SLE in the PROFILE cohort (318 with LN; 265 with SLE but without nephropathy) and 60 AA from the NIH (39 with LN; 21 with SLE but without nephropathy). Analysis of the NIH and larger PROFILE cohorts, as well as a combined analysis, did not support this association. Conclusions: These results suggest that AA with ESRD and coincident SLE who were recruited from dialysis clinics more likely have kidney diseases in the MYH9-associated spectrum of focal segmental glomerulosclerosis. PROFILE and NIH participants, recruited from rheumatology practices, demonstrate that MYH9 does not contribute substantially to the development of LN in AA.