nils-herrmann/clean_scirepeval huggingface dataset:
Per-Input Control-Flow Integrity

Control-Flow Integrity (CFI) is an effective approach to mitigating control-flow hijacking attacks. Conventional CFI techniques statically extract a control-flow graph (CFG) from a program and instrument the program to enforce that CFG. The statically generated CFG includes all edges for all possible inputs; however, for a concrete input, the CFG may include many unnecessary edges.
 We present Per-Input Control-Flow Integrity (PICFI), which is a new CFI technique that can enforce a CFG computed for each concrete input. PICFI starts executing a program with the empty CFG and lets the program itself lazily add edges to the enforced CFG if such edges are required for the concrete input. The edge addition is performed by PICFI-inserted instrumentation code. To prevent attackers from arbitrarily adding edges, PICFI uses a statically computed all-input CFG to constrain what edges can be added at runtime. To minimize performance overhead, operations for adding edges are designed to be idempotent, so they can be patched to no-ops after their first execution. As our evaluation shows, PICFI provides better security than conventional fine-grained CFI with comparable performance overhead.
Temporo-parietal Junction Activity in Theory-of-Mind Tasks: Falseness, Beliefs, or Attention

By combining the false belief (FB) and photo (PH) vignettes to identify theory-of-mind areas with the false sign (FS) vignettes, we re-establish the functional asymmetry between the left and right temporo-parietal junction (TPJ). The right TPJ (TPJ-R) is specially sensitive to processing belief information, whereas the left TPJ (TPJ-L) is equally responsible for FBs as well as FSs. Measuring BOLD at two time points in each vignette, at the time the FB-inducing information (or lack of information) is presented and at the time the test question is processed, made clear that the FB is processed spontaneously as soon as the relevant information is presented and not on demand for answering the question in contrast to extant behavioral data. Finally, a fourth, true belief vignette (TB) required teleological reasoning, that is, prediction of a rational action without any doubts being raised about the adequacy of the actor's information about reality. Activation by this vignette supported claims that the TPJ-R is activated by TBs as well as FBs.
A Real Time Autonomous Soldier Health Monitoring and Reporting System Using COTS Available Entities

Perturbed by the numerous instances of soldiers going untraced in action or killed in action, this paper suggests a qualitative approach to render an aid to the defense services by ensuring the safety, whereabouts and dignity of army personnel. The proposed system enables to detect the pulse (heartbeat rate) and position of the army personnel whenever required, thus vouching that timely support is provided to the needy ones. The transmitter equipped with pulse sensor and GPS Module is programmed with certain conditions to examine the healthiness of the soldier and accordingly to communicate with the receiver at some remote location. This paper presents framework of the design by utilizing the IEEE 802.15.4 standard and multifarious wireless sensor networks. The initial performance of the system has been evaluated with two personal computers. Also, the real time functioning of this design encourages extending this mechanism for a wireless health monitor network for the masses.
A fourth criterion for transient entrainment: the electrogram equivalent of progressive fusion.

Prior data pertaining to transient entrainment and associated phenomena have been best explained by pacing capture of a reentrant circuit. On this basis, we hypothesized that rapid pacing from a single site of two different constant pacing rates could constantly capture an appropriately selected bipolar electrogram recording site from one direction with a constant stimulus-to-electrogram interval during pacing at one rate, yet be constantly captured from another direction with a different constant stimulus-to-electrogram interval when pacing at a different constant pacing rate. To test this hypothesis, we studied a group of patients, each with a representative tachycardia (ventricular tachycardia, circus-movement tachycardia involving an atrioventricular bypass pathway, atrial tachycardia, and atrial flutter). For each tachycardia, pacing was performed from a single site for at least two different constant rates faster than the spontaneous rate of the tachycardia. We observed in these patients that a local bipolar recording site was constantly captured from different directions at two different pacing rates without interrupting the tachycardia at pacing termination. The evidence that the same site was captured from a different direction at two different pacing rates was supported by demonstrating a change in conduction time to that site associated with a change in the bipolar electrogram morphology at that site when comparing pacing at each rate. The mean conduction time (stimulus-to-recording site electrogram interval) was 319 +/- 69 msec while pacing at a mean cycle length of 265 +/- 50 msec, yet only 81 +/- 38 msec while pacing at a second mean cycle length of 233 +/- 51 msec, a mean change in conduction time of 238 +/- 56 msec. Remarkably, the faster pacing rate resulted in a shorter conduction time. The fact that the same electrode recording site was activated from different directions without interruption of the spontaneous tachycardia at pacing termination is difficult to explain on any mechanistic basis other than reentry. Also, these changes in conduction time and electrogram morphology occurred in parallel with the demonstration of progressive fusion beats on the electrocardiogram, the latter being an established criterion for transient entrainment.(ABSTRACT TRUNCATED AT 400
The physiology of salivary secretion.

Saliva in the mouth is a biofluid produced mainly by three pairs of major salivary glands--the submandibular, parotid and sublingual glands--along with secretions from many minor submucosal salivary glands. Salivary gland secretion is a nerve-mediated reflex and the volume of saliva secreted is dependent on the intensity and type of taste and on chemosensory, masticatory or tactile stimulation. Long periods of low (resting or unstimulated) flow are broken by short periods of high flow, which is stimulated by taste and mastication. The nerve-mediated salivary reflex is modulated by nerve signals from other centers in the central nervous system, which is most obvious as hyposalivation at times of anxiety. An example of other neurohormonal influences on the salivary reflex is the circadian rhythm, which affects salivary flow and ionic composition. Cholinergic parasympathetic and adrenergic sympathetic autonomic nerves evoke salivary secretion, signaling through muscarinic M3 and adrenoceptors on salivary acinar cells and leading to secretion of fluid and salivary proteins. Saliva gland acinar cells are chloride and sodium secreting, and the isotonic fluid produced is rendered hypotonic by salivary gland duct cells as it flows to the mouth. The major proteins present in saliva are secreted by salivary glands, creating viscoelasticity and enabling the coating of oral surfaces with saliva. Salivary films are essential for maintaining oral health and regulating the oral microbiome. Saliva in the mouth contains a range of validated and potential disease biomarkers derived from epithelial cells, neutrophils, the microbiome, gingival crevicular fluid and serum. For example, cortisol levels are used in the assessment of stress, matrix metalloproteinases-8 and -9 appear to be promising markers of caries and periodontal disease, and a panel of mRNA and proteins has been proposed as a marker of oral squamous cell carcinoma. Understanding the mechanisms by which components enter saliva is an important aspect of validating their use as biomarkers of health and disease.
Borrowed-virtual-time (BVT) scheduling: supporting latency-sensitive threads in a general-purpose schedular

Systems need to run a larger and more diverse set of applications, from real-time to interactive to batch, on uniprocessor and multiprocessor platforms. However, most schedulers either do not address latency requirements or are specialized to complex real-time paradigms, limiting their applicability to general-purpose systems.In this paper, we present Borrowed-Virtual-Time (BVT) Scheduling, showing that it provides low-latency for real-time and interactive applications yet weighted sharing of the CPU across applications according to system policy, even with thread failure at the real-time level, all with a low-overhead implementation on multiprocessors as well as uniprocessors. It makes minimal demands on application developers, and can be used with a reservation or admission control module for hard real-time applications.
Improving the robustness of convolutional networks to appearance variability in biomedical images

While convolutional neural networks (CNN) produce state-of-the-art results in many applications including biomedical image analysis, they are not robust to variability in the data that is not well represented by the training set. An important source of variability in biomedical images is the appearance of objects such as contrast and texture due to different imaging settings. We introduce the neighborhood similarity layer (NSL) which can be used in a CNN to improve robustness to changes in the appearance of objects that are not well represented by the training data. The proposed NSL transforms its input feature map at a given pixel by computing its similarity to the surrounding neighborhood. This transformation is spatially varying, hence not a convolution. It is differentiable; therefore, networks including the proposed layer can be trained in an end-to-end manner. We demonstrate the advantages of the NSL for the vasculature segmentation and cell detection problems.
Modeling and Control of a Multiport Power Electronic Transformer (PET) for Electric Traction Applications

This paper proposes a multiport power electronic transformer (PET) topology with multiwinding medium-frequency transformer (MW-MFT) isolation along with the associated modeling analysis and control scheme. The power balance at different ports can be controlled using the multiwinding transformer's common flux linkage. The potential applications of the proposed multiport PET are high-power traction systems for locomotives and electric multiple units, marine propulsion, wind power generation, and utility grid distribution applications. The complementary polygon equivalent circuit modeling of an MW-MFT is presented. The current and power characteristics of the virtual circuit branches and the multiports with general-phase-shift control are described. The general current and power analysis for the multiple active bridge (MAB) isolation units is investigated. Power decoupling methods, including nonlinear solution for power balancing are proposed. The zero-voltage-switching conditions for the MAB are discussed. Control strategies including soft-switching-phase-shift control and voltage balancing control based on the power decoupling calculations are described. Simulations and experiments are presented to verify the performance of the proposed topology and control algorithms.
A network project course based on network processors

A difficult problem in networking courses is to find hands-on projects that have the right balance between the level of realism and complexity. This is especially true for projects that focus on the internal functionality of routers and other network devices. We developed a capstone course called "Network Design and Evaluation" that uses a network processor-based platform for networking projects. This platform is more realistic than traditional approaches based on software emulation environments or PC-based routers running Unix, but it is significantly less complex to work with than real commercial routers or even PC-based routers. We are currently teaching this course for the third year, and our experience has been extremely positive. Students enjoy the realism of the platform and not only learn a lot about the internal operation of the network, but also about network configuration and management.
A Large Antenna Array for Ka-Band Satcom-on-the-Move Applications—Accurate Modeling and Experimental Characterization

We present the accurate modeling and analysis, followed by experimental validation, of a 1024-element (64-by-16) antenna array. This fixed-beam array radiates linear polarization in Ka-band (19.7–20.2 GHz). It acts as a first step in the design and modeling of future antenna arrays for satcom-on-the-move applications. Accurate prediction of the behavior of such a large array is a challenging task since full-wave simulation of the entire structure cannot be considered. By taking advantage of existing formalisms on periodic arrays and by using appropriate methods to efficiently exploit such formulations, it is possible to accurately define the performances of all building blocks, from the feeding circuits to the radiating elements, over a frequency range. Such a detailed design also allows an accurate physical analysis. It has been successfully used to guarantee the measured performances.
Smart Coffee Vending Machine Using RFID

The vending machine which provides the beverage like snacks, cold drink, it is also used for ticketing. These systems are operated on either coin or note or manually switch operated. This paper presents system which operates not on coin or note, it operates on RFID system. This system gives the access through only RFID which avoid the misuse of machine. A small RFID reader is fitted on the machine. The identity card which contains RFID tag is given to each employee. According to estimation the numbers of cups per day as per client’s requirement are programmed. Then an employee goes to vending machine show his card to the reader then the drink is dispensed. But when employee wants more coffees than fixed number, that person is allow for that but that employee has to pay for extra cups and amount is cut from the salary account. KeywordsRFID, Arduino, Vending machine.
Computational methods for the image segmentation of pigmented skin lesions: A review

Because skin cancer affects millions of people worldwide, computational methods for the segmentation of pigmented skin lesions in images have been developed in order to assist dermatologists in their diagnosis. This paper aims to present a review of the current methods, and outline a comparative analysis with regards to several of the fundamental steps of image processing, such as image acquisition, pre-processing and segmentation.



Techniques that have been proposed to achieve these tasks were identified and reviewed. As to the image segmentation task, the techniques were classified according to their principle.



The techniques employed in each step are explained, and their strengths and weaknesses are identified. In addition, several of the reviewed techniques are applied to macroscopic and dermoscopy images in order to exemplify their results.



The image segmentation of skin lesions has been addressed successfully in many studies; however, there is a demand for new methodologies in order to improve the efficiency.
Gene 33/Mig6 inhibits hexavalent chromium-induced DNA damage and cell transformation in human lung epithelial cells

Hexavalent Chromium [Cr(VI)] compounds are human lung carcinogens and environmental/occupational hazards. The molecular mechanisms of Cr(VI) carcinogenesis appear to be complex and are poorly defined. In this study, we investigated the potential role of Gene 33 (ERRFI1, Mig6), a multifunctional adaptor protein, in Cr(VI)-mediated lung carcinogenesis. We show that the level of Gene 33 protein is suppressed by both acute and chronic Cr(VI) treatments in a dose- and time-dependent fashion in BEAS-2B lung epithelial cells. The inhibition also occurs in A549 lung bronchial carcinoma cells. Cr(VI) suppresses Gene 33 expression mainly through post-transcriptional mechanisms, although the mRNA level of gene 33 also tends to be lower upon Cr(VI) treatments. Cr(VI)-induced DNA damage appears primarily in the S phases of the cell cycle despite the high basal DNA damage signals at the G2M phase. Knockdown of Gene 33 with siRNA significantly elevates Cr(VI)-induced DNA damage in both BEAS-2B and A549 cells. Depletion of Gene 33 also promotes Cr(VI)-induced micronucleus (MN) formation and cell transformation in BEAS-2B cells. Our results reveal a novel function of Gene 33 in Cr(VI)-induced DNA damage and lung epithelial cell transformation. We propose that in addition to its role in the canonical EGFR signaling pathway and other signaling pathways, Gene 33 may also inhibit Cr(VI)-induced lung carcinogenesis by reducing DNA damage triggered by Cr(VI).
SynPAnal: Software for Rapid Quantification of the Density and Intensity of Protein Puncta from Fluorescence Microscopy Images of Neurons

Continuous modification of the protein composition at synapses is a driving force for the plastic changes of synaptic strength, and provides the fundamental molecular mechanism of synaptic plasticity and information storage in the brain. Studying synaptic protein turnover is not only important for understanding learning and memory, but also has direct implication for understanding pathological conditions like aging, neurodegenerative diseases, and psychiatric disorders. Proteins involved in synaptic transmission and synaptic plasticity are typically concentrated at synapses of neurons and thus appear as puncta (clusters) in immunofluorescence microscopy images. Quantitative measurement of the changes in puncta density, intensity, and sizes of specific proteins provide valuable information on their function in synaptic transmission, circuit development, synaptic plasticity, and synaptopathy. Unfortunately, puncta quantification is very labor intensive and time consuming. In this article, we describe a software tool designed for the rapid semi-automatic detection and quantification of synaptic protein puncta from 2D immunofluorescence images generated by confocal laser scanning microscopy. The software, dubbed as SynPAnal (for Synaptic Puncta Analysis), streamlines data quantification for puncta density and average intensity, thereby increases data analysis throughput compared to a manual method. SynPAnal is stand-alone software written using the JAVA programming language, and thus is portable and platform-free.
Scale-Space Theory in Computer Vision

The presentation starts with a philosophical discussion about computer vision in general. The aim is to put the scope of the book into its wider context, and to emphasize why the notion of scale is crucial when dealing with measured signals, such as image data. An overview of different approaches to multi-scale representation is presented, and a number of special properties of scale-space are pointed out. Then, it is shown how a mathematical theory can be formulated for describing image structures at different scales. By starting from a set of axioms imposed on the first stages of processing, it is possible to derive a set of canonical operators, which turn out to be derivatives of Gaussian kernels at different scales. The problem of applying this theory computationally is extensively treated. A scale-space theory is formulated for discrete signals, and it demonstrated how this representation can be used as a basis for expressing a large number of visual operations. Examples are smoothed derivatives in general, as well as different types of detectors for image features, such as edges, blobs, and junctions. In fact, the resulting scheme for feature detection induced by the presented theory is very simple, both conceptually and in terms of practical implementations. Typically, an object contains structures at many different scales, but locally it is not unusual that some of these "stand out" and seem to be more significant than others. A problem that we give special attention to concerns how to find such locally stable scales, or rather how to generate hypotheses about interesting structures for further processing. It is shown how the scale-space theory, based on a representation called the scale-space primal sketch, allows us to extract regions of interest from an image without prior information about what the image can be expected to contain. Such regions, combined with knowledge about the scales at which they occur constitute qualitative information, which can be used for guiding and simplifying other low-level processes. Experiments on different types of real and synthetic images demonstrate how the suggested approach can be used for different visual tasks, such as image segmentation, edge detection, junction detection, and focusof-attention. This work is complemented by a mathematical treatment showing how the behaviour of different types of image structures in scalespace can be analysed theoretically.
A Compact a-IGZO TFT Model Based on MOSFET SPICE ${\rm Level}=3$ Template for Analog/RF Circuit Designs

This letter presents a compact model for flexible analog/RF circuits design with amorphous indium-gallium-zinc oxide thin-film transistors (TFTs). The model is based on the MOSFET LEVEL=3 SPICE model template, where parameters are fitted to measurements for both dc and ac characteristics. The proposed TFT compact model shows good scalability of the drain current for device channel lengths ranging from 50 to 3.6 μm. The compact model is validated by comparing measurements and simulations of various TFT amplifier circuits. These include a two-stage cascode amplifier showing 10 dB of voltage gain and 2.9 MHz of bandwidth.
Teaching Recommender Systems at Large Scale: Evaluation and Lessons Learned from a Hybrid MOOC

In the fall of 2013, we offered an open online Introduction to Recommender Systems through Coursera, while simultaneously offering a for-credit version of the course on-campus using the Coursera platform and a flipped classroom instruction model. As the goal of offering this course was to experiment with this type of instruction, we performed extensive evaluation including surveys of demographics, self-assessed skills, and learning intent; we also designed a knowledge-assessment tool specifically for the subject matter in this course, administering it before and after the course to measure learning, and again 5 months later to measure retention. We also tracked students through the course, including separating out students enrolled for credit from those enrolled only for the free, open course.
 Students had significant knowledge gains across all levels of prior knowledge and across all demographic categories. The main predictor of knowledge gain was effort expended in the course. Students also had significant knowledge retention after the course. Both of these results are limited to the sample of students who chose to complete our knowledge tests. Student completion of the course was hard to predict, with few factors contributing predictive power; the main predictor of completion was intent to complete. Students who chose a concepts-only track with hand exercises achieved the same level of knowledge of recommender systems concepts as those who chose a programming track and its added assignments, though the programming students gained additional programming knowledge. Based on the limited data we were able to gather, face-to-face students performed as well as the online-only students or better; they preferred this format to traditional lecture for reasons ranging from pure convenience to the desire to watch videos at a different pace (slower for English language learners; faster for some native English speakers). This article also includes our qualitative observations, lessons learned, and future directions.