Miracle-dz/UniFAR-FTUs huggingface dataset:
FIE on Firmware: Finding Vulnerabilities in Embedded Systems Using Symbolic Execution

Embedded systems increasingly use software-driven low-power microprocessors for security-critical settings, surfacing a need for tools that can audit the security of the software (often called firmware) running on such devices. Despite the fact that firmware programs are often written in C, existing source-code analysis tools do not work well for this setting because of the specific architectural features of low-power platforms. We therefore design and implement a new tool, called FIE, that builds off the KLEE symbolic execution engine in order to provide an extensible platform for detecting bugs in firmware programs for the popular MSP430 family of microcontrollers. FIE incorporates new techniques for symbolic execution that enable it to verify security properties of the simple firmwares often found in practice. We demonstrate FIE's utility by applying it to a corpus of 99 open-source firmware programs that altogether use 13 different models of the MSP430. We are able to verify memory safety for the majority of programs in this corpus and elsewhere discover 21 bugs.
Engineering Support Vector Machine Kerneis That Recognize Translation Initialion Sites

MOTIVATION In order to extract protein sequences from nucleotide sequences, it is an important step to recognize points at which regions start that code for proteins. These points are called translation initiation sites (TIS). RESULTS The task of finding TIS can be modeled as a classification problem. We demonstrate the applicability of support vector machines for this task, and show how to incorporate prior biological knowledge by engineering an appropriate kernel function. With the described techniques the recognition performance can be improved by 26% over leading existing approaches. We provide evidence that existing related methods (e.g. ESTScan) could profit from advanced TIS recognition.
Limited access alcohol drinking in high- and low-alcohol preferring selected lines of mice.

BACKGROUND Selection studies and genetic analyses of drinking behavior in rodents often involved unlimited access to alcohol over a period of weeks, with water and food freely available. Most studies investigating the pharmacology of alcohol drinking, on the other hand, use procedures in which access to alcohol is limited to a particular time each day. Reconciliation of findings between these two conditions likely depends on their sharing common genetic mechanisms as indicated, for example, by covariation in response to selection. To this end, high- and low-alcohol preferring (HAP and LAP, respectively) mice, selected for differences in 24-hr access alcohol drinking over a 4-week period, were subjected to a limited access alcohol drinking protocol. METHODS During 2-hr sessions, mice had access to various concentrations of alcohol (7-15%, v/v) in the home cage for 2 hr a day, with ad libitum access to food and water. Additional sessions were conducted with no food present. RESULTS Although both strains consumed alcohol and water during these sessions, HAP mice drank far more alcohol than did LAP mice. HAP but not LAP mice drank alcohol at a high rate early in the session compared with later in the session. Additionally, HAP mice responded to changes in alcohol concentration, whereas LAP mice did not. Removal of food did not influence alcohol drinking, although water drinking decreased following food removal. HAP mice reached appreciable blood alcohol concentrations after limited access. CONCLUSIONS These findings indicate that in these selectively bred mice, alcohol drinking during limited and unlimited access may be genetically related, and that drinking during limited access sessions in HAP mice is likely for the pharmacological properties of alcohol.
Year-class differences in the reproductive system, plasma prolactin and corticosterone concentrations, and onset of prebasic molt in male dark-eyed juncos (Junco hyemalis) during the breeding period.

Year-class differences in reproductive function were investigated in a free-living population of adult male Dark-eyed Juncos, Junco hyemalis, breeding in interior Alaska. Second-year males (SY, entering their first breeding season) were compared with after-second-year males (ASY, entering at least their second breeding season). We measured body mass, size of the cloacal protuberance (CP), testis mass, onset of prebasic molt, and concentrations of plasma luteinizing hormone (LH), testosterone (T), corticosterone (CORT), and prolactin (PRL) throughout the reproductive season (April to mid-July). There were no differences in SY and ASY body weights but SY males had smaller CPs and testis masses than ASY males during gonadal recrudescence and at the end of the breeding season. Plasma LH was elevated from April until mid-June and then decreased in the same way in both year classes. In contrast, plasma T was high from April until mid-May and was lower in SY than in ASY juncos shortly after they arrived on their breeding grounds at the end of April, but not at other times. In July, SY males started to molt earlier, suggesting that they became photorefractory earlier than ASY males. Plasma PRL increased progressively in both year classes between April and early June and decreased in early July. At this time, plasma PRL decreased earlier in SY than in ASY males. Plasma CORT changed seasonally, but did not differ between SY and ASY juncos. Thus, year-class differences in CP sizes and testis mass apparently did not result from SY males secreting less LH or more PRL or CORT than ASY males. It is suggested that differences in reproductive condition in SY and ASY juncos are mediated by interactions with conspecific birds and do not result from an intrinsic effect of age.
Sensitivity Measures for Oscillating Systems: Application to Mammalian Circadian Gene Network

Vital physiological behaviors exhibited daily by bacteria, plants, and animals are governed by endogenous oscillators called circadian clocks. The most salient feature of the circadian clock is its ability to change its internal time (phase) to match that of the external environment. The circadian clock, like many oscillators in nature, is regulated at the cellular level by a complex network of interacting components. As a complementary approach to traditional biological investigation, we utilize mathematical models and systems-theoretic tools to elucidate these mechanisms. The models are systems of ordinary differential equations exhibiting stable limit cycle behavior. To study the robustness of circadian phase behavior, we use sensitivity analysis. As the standard set of sensitivity tools are not suitable for the study of phase behavior, we introduce a novel tool, the parametric impulse phase response curve.
Resource Optimization for Program Committee Members: A Subreview Article

This paper formalizes a resource-allocation problem that is all too familiar to the seasoned program-committee member. For each submission j that the PC member has the honor of reviewing, there is a choice. The PC member can spend the time to review submission j in detail on his/her own at a cost of Cj. Alternatively, the PC member can spend the time to identify and contact peers, hoping to recruit them as subreviewers, at a cost of 1 per subreviewer. These potential subreviewers have a certain probability of rejecting each review request, and this probability increases as time goes on. Once the PC member runs out of time or unasked experts, he/she is forced to review the paper without outside assistance. This paper gives optimal solutions to several variations of the scheduling-reviewers problem. Most of the solutions from this paper are based on an iterated log function of Cj. In particular, with k rounds, the optimal solution sends the k-iterated log of Cj requests in the first round, the (k − 1)-iterated log in the second round, and so forth. One of the contributions of this paper is solving this problem exactly, even when rejection probabilities may increase. Naturally, PC members must make an integral number of subreview requests. This paper gives, as an intermediate result, a linear-time algorithm to transform the artificial problem in which one can send fractional requests into the less-artificial problem in which one sends an integral number of requests. Finally, this paper considers the case where the PC member knows nothing about the probability that a potential subreviewer agrees to review the paper. This paper gives an approximation algorithm for this case, whose bounds improve as the number of rounds increases.
Triangle listing in massive networks and its applications

Triangle listing is one of the fundamental algorithmic problems whose solution has numerous applications especially in the analysis of complex networks, such as the computation of clustering coefficient, transitivity, triangular connectivity, etc. Existing algorithms for triangle listing are mainly in-memory algorithms, whose performance cannot scale with the massive volume of today's fast growing networks. When the input graph cannot fit into main memory, triangle listing requires random disk accesses that can incur prohibitively large I/O cost. Some streaming and sampling algorithms have been proposed but these are approximation algorithms. We propose an I/O-efficient algorithm for triangle listing. Our algorithm is exact and avoids random disk access. Our results show that our algorithm is scalable and outperforms the state-of-the-art local triangle estimation algorithm.
Assessing interactions in the brain with exact low-resolution electromagnetic tomography

Scalp electric potentials (electroencephalogram; EEG) are contingent to the impressed current density unleashed by cortical pyramidal neurons undergoing post-synaptic processes. EEG neuroimaging consists of estimating the cortical current density from scalp recordings. We report a solution to this inverse problem that attains exact localization: exact low-resolution brain electromagnetic tomography (eLORETA). This non-invasive method yields high time-resolution intracranial signals that can be used for assessing functional dynamic connectivity in the brain, quantified by coherence and phase synchronization. However, these measures are non-physiologically high because of volume conduction and low spatial resolution. We present a new method to solve this problem by decomposing them into instantaneous and lagged components, with the lagged part having almost pure physiological origin.
Development of Hybrid Classification Methodology for Mining Skewed Data Sets - A Case Study of Indian Customs Data

At present, detecting customs declaration frauds with limited examination of imported goods by available scarce resources is posing considerable challenge to the customs authorities world over. Data mining techniques could be utilized to sift through the past data and develop predictive model for examination of limited goods with higher probability of fraud. However, this requires handling large, skewed data sets with variable error of each misclassification. Literature suggests various data level and algorithm level interventions for addressing these issues. Successive application of combination of both the types of interventions on the classification tree technique is devised in this paper to improve the predictive accuracy of the model. Furthermore, the predictions of this classification tree model are then fed into an artificial neural classification model, which gives the flexibility to modulate the predictive accuracy of a particular class label to suit the end objective. This methodology can be effectively applied to other similar situations such as detecting insurance fraud, credit card fraud, telecom churning and frauds etc.
Multi-faceted contextual model for person identification in news video

Person identification is very important in the domain of multimedia news as it is often the focus of events in news stories and interest of searchers. However, this detection is impeded by the imprecise audio/visual analysis tools. In this paper, we describe a multimodal and multi-faceted approach to person-x detection in news video. We make use of multimodal features extracted from text, visual and audio inherent in news video. We also incorporate multiple external sources of news from Web and parallel news archives to extract location and temporal profile of the persons. We call this second source of information the multi-faceted context. The multimodal, multi-faceted information is then fused using a rank boosting approach. Experiments on TRECVID 2003 and 2004 search queries demonstrate that our approach is effective
Mold accessibility via Gauss map analysis

In manufacturing processes like injection molding or die casting, a 2-piece mold is required to be separable, that is, having both pieces of the molds removed in opposite directions while interfering neither with the mold nor with each other. The fundamental problem is to find a viewing (i.e. separating) direction, from which a valid partition line (i.e. the contact curves of the two mold pieces) exists. While previous research work on this problem exists for polyhedral models, verifying and finding such a partition line for general freeform shapes, represented by NURBS surfaces, is still an open question. This paper shows that such a valid partition exists for a compact surface of genus g, if and only if there is a viewing direction from which the silhouette consists of exactly g + 1 nonsingular disjoint loops. Hence, the 2-piece mold separability problem is essentially reduced to the topological analysis of silhouettes. It follows that the aspect graph, which gives all topologically distinct silhouettes, allows one to determine the existence of a valid partition as well as to find such a partition when it exists. We present an aspect graph computation technique for compact free-form objects represented as NURBS surfaces. All the vision event curves (parabolic curves, flecnodal curves, and bitangency curves) relevant to mold separability are computed by symbolic techniques based on the NURBS representation, combined with numerical processing. An image dilation technique is then used for robust aspect graph cell decomposition on the sphere of viewing directions. Thus, an exact solution to the 2-piece mold separability problem is given for such models.
Effects of functional electrical stimulation on trunk control in children with diplegic cerebral palsy

Purpose: This study aimed to investigate the efficiency of FES application on the abdomen-posterior back muscles in children with CP that were enrolled into physical therapy and rehabilitation (PTR) program. Method: The study included 55 spastic diplegic children that were hospitalized for rehabilitation. Those with deformities that could disrupt the balance in sitting and cause problems in evaluations were excluded. The patients were randomly divided into two equal groups according to their time of presentation. Thirty-two children completed the study. The control group received PTR program only for 4 weeks. The children in the FES group received PTR in addition to electrical stimulation. Electrical stimulation was applied 5 days a week for 4 weeks to abdomen-posterior back muscles in 30-minute-long sessions. To evaluate the balance in sitting, sitting score of gross motor function measurement (GMFM) and to evaluate the trunk asymmetry in sitting, radiographic measurements were used. Thus, kyphosis, Cobb and sacral angles were measured. Results: The comparisons of the measurements of the two groups before and after the treatment showed that the GMFM sitting score and the sacral angle were statistically significantly increased, and the kyphotic and Cobb angles were statistically significantly decreased. After the treatment, both groups demonstrated an increase in the GMFM score, but the increase in the FES group was statistically significantly higher than that in the control group. With respect to radiological measurements, the changes observed in both the kyphotic and Cobb angles after the treatment were statistically significantly higher in the FES group than in the control group. The rates of the changes in the sacral angle did not differ among the groups. Conclusion: We believe to provide balance in sitting for children with CP, FES applied on abdomen-back muscles along with conventional therapy to maintain trunk control is more effective than conventional therapy alone. Implications for Rehabilitation FES is used to increase the muscle strength and improve functions. When used in children with CP, FES application on the abdomen-posterior muscles reduces cobb and kyphosis angles and increases sitting balance. It is well-tolerated by children with CP and offers positive contributions to rehabilitation program.
Stable Deterministic Multithreading through Schedule Memoization

A deterministic multithreading (DMT) system eliminates nondeterminism in thread scheduling, simplifying the development of multithreaded programs. However, existing DMT systems are unstable; they may force a program to (ad)venture into vastly different schedules even for slightly different inputs or execution environments, defeating many benefits of determinism. Moreover, few existing DMT systems work with server programs whose inputs arrive continuously and nondeterministically. TERN is a stable DMT system. The key novelty in TERN is the idea of schedule memoization that memoizes past working schedules and reuses them on future inputs, making program behaviors stable across different inputs. A second novelty in TERN is the idea of windowing that extends schedule memoization to server programs by splitting continuous request streams into windows of requests. Our TERN implementation runs on Linux. It operates as user-space schedulers, requiring no changes to the OS and only a few lines of changes to the application programs. We evaluated TERN on a diverse set of 14 programs (e.g., Apache and MySQL) with real and synthetic workloads. Our results show that TERN is easy to use, makes programs more deterministic and stable, and has reasonable overhead.
Characterization of a Novel Humanized Anti-CD20 Antibody with Potent Anti-Tumor Activity against Non-Hodgkin's Lymphoma

Background: Rituximab, a mouse Fab and human Fc chimeric antibody, has been widely used to treat Non-Hodgkin's lymphoma (NHL). However, only 48% of patients respond to the treatment and complete response rate is below 10%. Also, immunogenicity was reported in 17-20% patients receiving the treatment, making it unsuitable for long term diseases such as autoimmune disorders. It has been a hot research field to “humanize” rituximab toward improved efficacy and reduced immunogenicity. Methods: In this study, an advanced antibody humanization technology was applied to the sequence of the anti-CD20 antibody 2B8, its sequence of which was based on the original murine monoclonal antibody of rituximab in Roche. The complementarity-determining regions (CDRs) of the humanized antibodies were further optimized through computer-aided molecular dock. Results: Five novel humanized anti-CD20 antibodies 1-5(1635, 1534, 3637, 1634 and 1536) were generated and their immunogenicity was significantly decreased when compared to rituximab. The novel humanized anti-CD20 antibodies 1-5 retained the binding activity of their murine counterpart, as demonstrated by the fluorescence-activated cell-sorting analysis (FACS). When compared to rituximab, the humanized antibodies still have the similar properties on both complement-dependent cytotoxicity (CDC) and antibody-dependent cell-mediated cytotoxicity (ADCC). Furthermore, its anti-tumor efficacy in xenograft model is comparable to that of rituximab. Conclusion: The humanized anti-CD20 antibodies 1-5 have lower immunogenicity than rituximab. And at the same time, they still retain the anti-tumor effect both in vitro and vivo.
Investigation of Some Technical Indexes in Stock Forecasting Using Neural Networks

Training neural networks to capture an intrinsic property of a large volume of high dimensional data is a difficult task, as the training process is computationally expensive. Input attributes should be carefully selected to keep the dimensionality of input vectors relatively small. Technical indexes commonly used for stock market prediction using neural networks are investigated to determine its effectiveness as inputs. The feed forward neural network of Levenberg-Marquardt algorithm is applied to perform one step ahead forecasting of NASDAQ and Dow stock prices. Keywords—Stock Market Prediction, Neural Networks, Levenberg-Marquadt Algorithm, Technical Indexes
GobyWeb: Simplified Management and Analysis of Gene Expression and DNA Methylation Sequencing Data

We present GobyWeb, a web-based system that facilitates the management and analysis of high-throughput sequencing (HTS) projects. The software provides integrated support for a broad set of HTS analyses and offers a simple plugin extension mechanism. Analyses currently supported include quantification of gene expression for messenger and small RNA sequencing, estimation of DNA methylation (i.e., reduced bisulfite sequencing and whole genome methyl-seq), or the detection of pathogens in sequenced data. In contrast to previous analysis pipelines developed for analysis of HTS data, GobyWeb requires significantly less storage space, runs analyses efficiently on a parallel grid, scales gracefully to process tens or hundreds of multi-gigabyte samples, yet can be used effectively by researchers who are comfortable using a web browser. We conducted performance evaluations of the software and found it to either outperform or have similar performance to analysis programs developed for specialized analyses of HTS data. We found that most biologists who took a one-hour GobyWeb training session were readily able to analyze RNA-Seq data with state of the art analysis tools. GobyWeb can be obtained at http://gobyweb.campagnelab. org and is freely available for non-commercial use. GobyWeb plugins are distributed in source code and licensed under the open source LGPL3 license to facilitate code inspection, reuse and independent extensions http://github.com/CampagneLaboratory/gobyweb2-plugins.
Generalization and a framework for query modification

The rigidity and limited expressiveness of relational queries often require that a query be iteratively modified. An initial query is posed, and once it is discovered that the answer does not meet the additional constraints, which are not expressed in the relational query, it is necessary to modify the query in a way such that those constraints are satisfied. The aim of this work is to capture this iterative process by extending the query model. Extended queries, which express additional constraints on the answer set and designate some of the conditions in the relational query as flexible, are defined. The query modification operators modify flexible constraints to satisfy an extended query. The query modification operation, generalization, is described. The conditions under which generalization is applicable are identified. Rules of generalization are proposed, and an algorithm for picking a minimal generalization is suggested. <<ETX>>
Filament winding of aramid/PA6 commingled yarns with in situ consolidation

The in situ consolidation of commingled yarns during filament winding is demonstrated on an aramid fibre-reinforced polyamide 6 material. This article is a systematic experimental investigation of the filament winding processing parameters, namely, the heat gun temperature, line speed, fibre tension, compaction force and preheater temperature. Optimizing the processing parameters in this filament winding process produced a fully consolidated material with a void content of ∼0.25% which is comparable to the material quality achieved by means of compression moulding using the same intermediate materials.