nils-herrmann/clean_scirepeval huggingface dataset:
BloomStore: Bloom-Filter based memory-efficient key-value store for indexing of data deduplication on flash

Due to its better scalability, Key-Value (KV) store has superseded traditional relational databases for many applications, such as data deduplication, on-line multi-player gaming, and Internet services like Amazon and Facebook. The KV store efficiently supports two operations (key lookup and KV pair insertion) through an index structure that maps keys to their associated values. The KV store is also commonly used to implement the chunk index in data deduplication, where a chunk ID (SHA1 value computed based on the chunk's content) is a key and its associative chunk metadata (e.g., physical storage location, stream ID) is the value. For a deduplication system, typically the number of chunks is too large to store the KV store solely in RAM. Thus, the KV store maintains a large (hash-table based) index structure in RAM to index all KV pairs stored on secondary storage. Hence, its available RAM space limits the maximum number of KV pairs that can be stored. Moving the index data structure from RAM to flash can possibly overcome the space limitation. In this paper, we propose efficient KV store on flash with a Bloom Filter based index structure called BloomStore. The unique features of the BloomStore include (1) no index structure is required to be stored in RAM so that a small RAM space can support a large number of KV pairs and (2) both index structure and KV pairs are stored compactly on flash memory to improve its performance. Compared with the state-of-the-art KV store designs, the BloomStore achieves a significantly better key lookup performance and roughly the same insertion performance with multiple times less RAM usage based on our experiments with deduplication workloads.
Complete genome sequence of Treponema pallidum, the syphilis spirochete.

The complete genome sequence of Treponema pallidum was determined and shown to be 1,138,006 base pairs containing 1041 predicted coding sequences (open reading frames). Systems for DNA replication, transcription, translation, and repair are intact, but catabolic and biosynthetic activities are minimized. The number of identifiable transporters is small, and no phosphoenolpyruvate:phosphotransferase carbohydrate transporters were found. Potential virulence factors include a family of 12 potential membrane proteins and several putative hemolysins. Comparison of the T. pallidum genome sequence with that of another pathogenic spirochete, Borrelia burgdorferi, the agent of Lyme disease, identified unique and common genes and substantiates the considerable diversity observed among pathogenic spirochetes.
Shape tracking of extended objects and group targets with star-convex RHMs

This paper is about tracking an extended object or a group target, which gives rise to a varying number of measurements from different measurement sources. For this purpose, the shape of the target is tracked in addition to its kinematics. The target extent is modeled with a new approach called Random Hypersurface Model (RHM) that assumes varying measurement sources to lie on scaled versions of the shape boundaries. In this paper, a star-convex RHM is introduced for tracking star-convex shape approximations of targets. Bayesian inference for star-convex RHMs is performed by means of a Gaussian-assumed state estimator allowing for an efficient recursive closed-form measurement update. Simulations demonstrate the performance of this approach for typical extended object and group tracking scenarios.
A game theoretic approach to provide incentive and service differentiation in P2P networks

Traditional peer-to-peer (P2P) networks do not provide service differentiation and incentive for users. Consequently, users can obtain services without themselves contributing any information or service to a P2P community. This leads to the "free-riding" and "tragedy of the commons" problems, in which the majority of information requests are directed towards a small number of P2P nodes willing to share their resources. The objective of this work is to enable service differentiation in a P2P network based on the amount of services each node has provided to its community, thereby encouraging all network nodes to share resources. We first introduce a resource distribution mechanism between all information sharing nodes. The mechanism is driven by a distributed algorithm which has linear time complexity and guarantees Pareto-optimal resource allocation. Besides giving incentive, the mechanism distributes resources in a way that increases the aggregate utility of the whole network. Second, we model the whole resource request and distribution process as a competition game between the competing nodes. We show that this game has a Nash equilibrium and is collusion-proof. To realize the game, we propose a protocol in which all competing nodes interact with the information providing node to reach Nash equilibrium in a dynamic and efficient manner. Experimental results are reported to illustrate that the protocol achieves its service differentiation objective and can induce productive information sharing by rational network nodes. Finally, we show that our protocol can properly adapt to different node arrival and departure events, and to different forms of network congestion.
Isolated Mode Antenna Technology for 4 G

The challenges of 4G are multifaceted. First, 4G requires multiple-input, multiple-output (MIMO) technology, and mobile devices supporting MIMO typically have multiple antennas. To obtain the benefits of MIMO communications systems, antennas typically must be properly configured to take advantage of the independent signal paths that can exist in the communications channel environment.  With proper design, one antenna’s radiation is prevented from traveling into the neighboring antenna and being absorbed by the opposite load circuitry. Typically, a combination of antenna separation and polarization is used to achieve the required signal isolation and independence. However, when the area inside devices such as smartphones, USB modems, and tablets is extremely limited, this approach often is not effective in meeting industrial design and performance criteria. Second, new LTE networks are expected to operate alongside all the existing services, such as 3G voice/data, Wi-Fi, Bluetooth, etc. Third, this problem gets even harder in the 700 MHz LTE band because the typical handset is not large enough to properly resonate at that frequency.
Melanoma Brain Metastasis: Mechanisms, Models, and Medicine

The development of brain metastases in patients with advanced stage melanoma is common, but the molecular mechanisms responsible for their development are poorly understood. Melanoma brain metastases cause significant morbidity and mortality and confer a poor prognosis; traditional therapies including whole brain radiation, stereotactic radiotherapy, or chemotherapy yield only modest increases in overall survival (OS) for these patients. While recently approved therapies have significantly improved OS in melanoma patients, only a small number of studies have investigated their efficacy in patients with brain metastases. Preliminary data suggest that some responses have been observed in intracranial lesions, which has sparked new clinical trials designed to evaluate the efficacy in melanoma patients with brain metastases. Simultaneously, recent advances in our understanding of the mechanisms of melanoma cell dissemination to the brain have revealed novel and potentially therapeutic targets. In this review, we provide an overview of newly discovered mechanisms of melanoma spread to the brain, discuss preclinical models that are being used to further our understanding of this deadly disease and provide an update of the current clinical trials for melanoma patients with brain metastases.
A Calibrated Phase/Frequency Detector for Reference Spur Reduction in Charge-Pump PLLs

This brief presents a new technique for minimizing reference spurs in a charge-pump phase-locked loop (PLL) while maintaining dead-zone-free operation. The proposed circuitry uses a phase/frequency detector with a variable delay element in its reset path, with the delay length controlled by feedback from the charge-pump. Simulations have been performed with several PLLs to compare the proposed circuitry with previously reported techniques. The proposed approach shows improvements over previously reported techniques of 12 and 16 dB in the two closest reference spurs
Incorporating Nesterov Momentum into

When attempting to improve the performance of a deep learning system, there are more or less three approaches one can take: the first is to improve the structure of the model, perhaps adding another layer, switching from simple recurrent units to LSTM cells , or–in the realm of NLP–taking advantage of syntactic parses (e.g. as in [13, et seq.]); another approach is to improve the initialization of the model, guaranteeing that the early-stage gradients have certain beneficial properties , or building in large amounts of sparsity [6], or taking advantage of principles of linear algebra ; the final approach is to try a more powerful learning algorithm, such as including a decaying sum over the previous gradients in the update , by dividing each parameter update by the L2 norm of the previous updates for that parameter , or even by foregoing first-order algorithms for more powerful but more computationally costly second order algorithms . This paper has as its goal the third option—improving the quality of the final solution by using a faster, more powerful learning algorithm.
Digital Image Based Identification of Rice Variety Using Image Processing and Neural Network

The consumer concern on the originality of rice variety and the quality of rice leads to originality certification of rice by existing institutions. Technology helps human to perform evaluations of food grains using images of objects. This study developed a system as a tool to identify rice varieties. Identification process was performed by analyzing rice images using image processing. The analyzed features for identification consist of six color features, four morphological features, and two texture features. Classifier used LVQ neural network algorithm. Identification results using a combination of all features gave average accuracy of 70.3% with the highest classification accuracy level of 96.6% for Mentik Wangi and the lowest classification accuracy of 30% for Cilosari.
A fast algorithm for skew detection of document images using morphology

Any paper document when converted to electronic form through standard digitizing devices, like scanners, is subject to a small tilt or skew. Meanwhile, a de-skewed document allows a more compact representation of its components, particularly text objects, such as words, lines, and paragraphs, where they can be represented by their rectilinear bounding boxes. This simplified representation leads to more efficient, robust, as well as simpler algorithms for document image analysis including optical character recognition (OCR). This paper presents a new method for automatic detection of skew in a document image using mathematical morphology. The proposed algorithm is extremely fast as well as independent of script forms.
A 0.18µm pipelined 8B10B encoder for a high-speed SerDes

This paper presented a pipelined 8B10B encoder for a high speed SerDes. To overcome the drawback of the speed limitation due to the conventional architecture, a pipelined encoding architecture is proposed. By splitting the longer path into two shorter paths with registers, the delay of the critical path is shortened greatly. Based on the pipelined architecture, a high-speed 8B10B encoder is implemented using 0.18 µm CMOS technology and standard cell library. Post-simulation results show that the encoder can work up to the rate of 7Gbps with a core are of 76.86 µm × 76.86 µm and the power consumption is 5.0317 mW under a 1.8V power supply voltage.
Intuitionistic computability logic I

Computability logic (CL) is a systematic formal theory of computational tasks and resources, which, in a sense, can be seen as a semantics-based alternative to (the syntactically introduced) linear logic. With its expressive and flexible language, where formulas represent computational problems and “truth” is understood as algorithmic solvability, CL potentially offers a comprehensive logical basis for constructive applied theories and computing systems inherently requiring constructive and computationally meaningful underlying logics. Among the best known constructivistic logics is Heyting’s intuitionistic calculus INT, whose language can be seen as a special fragment of that of CL. The constructivistic philosophy of INT, however, just like the resource philosophy of linear logic, has never really found an intuitively convincing and mathematically strict semantical justification. CL has good claims to provide such a justification and hence a materialization of Kolmogorov’s known thesis “INT = logic of problems”. The present paper contains a soundness proof for INT with respect to the CL semantics. It is expected to constitute part 1 of a two-piece series on the intuitionistic fragment of CL, with part 2 containing an anticipated completeness proof.
Universal Style Transfer via Feature Transforms

Universal style transfer aims to transfer arbitrary visual styles to content images. Existing feed-forward based methods, while enjoying the inference efficiency, are mainly limited by inability of generalizing to unseen styles or compromised visual quality. In this paper, we present a simple yet effective method that tackles these limitations without training on any pre-defined styles. The key ingredient of our method is a pair of feature transforms, whitening and coloring, that are embedded to an image reconstruction network. The whitening and coloring transforms reflect a direct matching of feature covariance of the content image to a given style image, which shares similar spirits with the optimization of Gram matrix based cost in neural style transfer. We demonstrate the effectiveness of our algorithm by generating high-quality stylized images with comparisons to a number of recent methods. We also analyze our method by visualizing the whitened features and synthesizing textures via simple feature coloring.
Droplet-trace-based array partitioning and a pin assignment algorithm for the automated design of digital microfluidic biochips

Microfluidics-based biochips combine electronics with biology to open new application areas such as point-of-care medical diagnostics, on-chip DNA analysis, and automated drug discovery. Bioassays are mapped to microfluidic arrays using synthesis tools, and they are executed through the manipulation of sample and reagent droplets by electrical means. Most prior work on CAD for biochips has assumed independent control of electrodes using a large number of (electrical) input pins. Such solutions are not feasible for low-cost disposable biochips that are envisaged for many field applications. A more promising design strategy is to divide the microfluidic array into smaller partitions and use a small number of electrodes to control the electrodes in each partition. We propose a partitioning algorithm based on the concept of "droplet trace", which is extracted from the scheduling and droplet routing results produced by a synthesis tool. An efficient pin assignment method, referred to as the "Connect-5 algorithm", is combined with the array partitioning technique based on droplet traces. The array partitioning and pin assignment methods are evaluated using a set of multiplexed bioassays.
Research on NFE Model of Multi-Sensor Information Fusion

To study information fusion method under complex environment, a highly intelligent information fusion model is put forward- the NFE model. This model is an organic combination of neural network, fuzzy reasoning and expert system. Considering various factors which influence the performance of sensor, the NFE confidence estimator is presented from the engineering application point of view. This paper presents principles, frameworks as well as key algorithms of the NFE model, and makes a comparison between the NFE model and traditional fuzzy neural network model. Simulation experiments prove that the NFE model can realize target recognition more effectively against sensor failures and strong interference, and the results are more reliable.
Trust and Credibility in Web-Based Health Information: A Review and Agenda for Future Research

Internet sources are becoming increasingly important in seeking health information, such that they may have a significant effect on health care decisions and outcomes. Hence, given the wide range of different sources of Web-based health information (WHI) from different organizations and individuals, it is important to understand how information seekers evaluate and select the sources that they use, and more specifically, how they assess their credibility and trustworthiness.



The aim of this study was to review empirical studies on trust and credibility in the use of WHI. The article seeks to present a profile of the research conducted on trust and credibility in WHI seeking, to identify the factors that impact judgments of trustworthiness and credibility, and to explore the role of demographic factors affecting trust formation. On this basis, it aimed to identify the gaps in current knowledge and to propose an agenda for future research.



A systematic literature review was conducted. Searches were conducted using a variety of combinations of the terms WHI, trust, credibility, and their variants in four multi-disciplinary and four health-oriented databases. Articles selected were published in English from 2000 onwards; this process generated 3827 unique records. After the application of the exclusion criteria, 73 were analyzed fully.



Interest in this topic has persisted over the last 15 years, with articles being published in medicine, social science, and computer science and originating mostly from the United States and the United Kingdom. Documents in the final dataset fell into 3 categories: (1) those using trust or credibility as a dependent variable, (2) those using trust or credibility as an independent variable, and (3) studies of the demographic factors that influence the role of trust or credibility in WHI seeking. There is a consensus that website design, clear layout, interactive features, and the authority of the owner have a positive effect on trust or credibility, whereas advertising has a negative effect. With regard to content features, authority of the author, ease of use, and content have a positive effect on trust or credibility formation. Demographic factors influencing trust formation are age, gender, and perceived health status.



There is considerable scope for further research. This includes increased clarity of the interaction between the variables associated with health information seeking, increased consistency on the measurement of trust and credibility, a greater focus on specific WHI sources, and enhanced understanding of the impact of demographic variables on trust and credibility judgments.
Video Inpainting of Complex Scenes

We propose an automatic video inpainting algorithm which relies on the optimisation of a global, patch-based functional. Our algorithm is able to deal with a variety of challenging situations which naturally arise in video inpainting, such as the correct reconstruction of dynamic textures, multiple moving objects and moving background. Furthermore, we achieve this in an order of magnitude less execution time with respect to the state-of-the-art. We are also able to achieve good quality results on high definition videos. Finally, we provide specific algorithmic details to make implementation of our algorithm as easy as possible. The resulting algorithm requires no segmentation or manual input other than the definition of the inpainting mask, and can deal with a wider variety of situations than is handled by previous work.
FET Journey Continues Efficient Power Conversion Corporation High Power Fully Regulated Eighth-brick DC-DC Converter with GaN FETs

The recently introduced family of fourth generation eGaN® FET power devices provides significant improvements in electrical performance figures of merit, reductions in device onresistance, and larger die, enabling improved performance in high frequency, high current applications. These new devices provide a path to approximately double the power density of brick-type standard converters. This paper describes the development of an eighth-brick (Ebrick) demonstration converter which uses the latest generation eGaN FETs. This converter is capable of output power greater than 500 W with an output of 12 V and 42 A and achieves a peak efficiency of 96.7% with 52 V input voltage.
Staple : Complementary Learners for Real-Time Tracking Supplementary material

We show here all the results provided by the vot-toolkit [9]. We use the latest version available at the time of writing (commit d3b2b1d of the 11 Sep 2015). For completeness, we present both reports generated by the toolkit. The analysis of report challenge pools the performance per attribute, considering camera motion, illumination change, occlusion, size change and motion change. Instead, the analysis of report article groups the results per sequence. Tables 1 and 2 report the final rankings provided by the two analyses. Staple ranks first in both, but the order of the remaining trackers varies significantly between the two tables. The Accuracy-Robustness plot of Figure 1 gives a more intuitive visualization of the relative performance of the trackers by showing their accuracy and robustness ranks on a 2D grid. Tables 3, 4, 5 and 6 provide a more in-depth analysis by showing the raw values of, respectively, accuracy per attribute, robustness per attribute, accuracy per sequence and robustness per sequence. Finally, Figures 2, 3 and 4 complete the plots of Sections 4.3, 4.4 and 4.5 of the main article.
ORec: An Opinion-Based Point-of-Interest Recommendation Framework

As location-based social networks (LBSNs) rapidly grow, it is a timely topic to study how to recommend users with interesting locations, known as points-of-interest (POIs). Most existing POI recommendation techniques only employ the check-in data of users in LBSNs to learn their preferences on POIs by assuming a user's check-in frequency to a POI explicitly reflects the level of her preference on the POI. However, in reality users usually visit POIs only once, so the users' check-ins may not be sufficient to derive their preferences using their check-in frequencies only. Actually, the preferences of users are exactly implied in their opinions in text-based tips commenting on POIs. In this paper, we propose an opinion-based POI recommendation framework called ORec to take full advantage of the user opinions on POIs expressed as tips. In ORec, there are two main challenges: (i) detecting the polarities of tips (positive, neutral or negative), and (ii) integrating them with check-in data including social links between users and geographical information of POIs. To address these two challenges, (1) we develop a supervised aspect-dependent approach to detect the polarity of a tip, and (2) we devise a method to fuse tip polarities with social links and geographical information into a unified POI recommendation framework. Finally, we conduct a comprehensive performance evaluation for ORec using two large-scale real data sets collected from Foursquare and Yelp. Experimental results show that ORec achieves significantly superior polarity detection and POI recommendation accuracy compared to other state-of-the-art polarity detection and POI recommendation techniques.