nils-herrmann/clean_scirepeval huggingface dataset:
A Field Study of Run-Time Location Access Disclosures on Android Smartphones

Smartphone users are increasingly using apps that can access their location. Often these accesses can be without users knowledge and consent. For example, recent research has shown that installation-time capability disclosures are ineffective in informing people about their apps’ location access. In this paper, we present a four-week field study (N=22) on run-time location access disclosures. Towards this end, we implemented a novel method to disclose location accesses by location-enabled apps on participants’ smartphones. In particular, the method did not need any changes to participants’ phones beyond installing our study app. We randomly divided our participants to two groups: a Disclosure group (N=13), who received our disclosures and a No Disclosure group (N=9) who received no disclosures from us. Our results confirm that the Android platform’s location access disclosure method does not inform participants effectively. Almost all participants pointed out that their location was accessed by several apps they would have not expected to access their location. Further, several apps accessed their location more frequently than they expected. We conclude that our participants appreciated the transparency brought by our run-time disclosures and that because of the disclosures most of them had taken actions to manage their apps’ location access.
Hierarchical Active Transfer Learning

We describe a unified active transfer learning framework called Hierarchical Active Transfer Learning (HATL). HATL exploits cluster structure shared between different data domains to perform transfer learning by imputing labels for unlabeled target data and to generate effective label queries during active learning. The resulting framework is flexible enough to perform not only adaptive transfer learning and accelerated active learning but also unsupervised and semi-supervised transfer learning. We derive an intuitive and useful upper bound on HATL’s error when used to infer labels for unlabeled target points. We also present results on synthetic data that confirm both intuition and our analysis. Finally, we demonstrate HATL’s empirical effectiveness on a benchmark data set for sentiment classification.
Three Birds One Stone: A Unified Framework for Salient Object Segmentation, Edge Detection and Skeleton Extraction

In this paper, we aim at solving pixel-wise binary problems, including salient object segmentation, skeleton extraction, and edge detection, by introducing a unified architecture. Previous works have proposed tailored methods for solving each of the three tasks independently. Here, we show that these tasks share some similarities that can be exploited for developing a unified framework. In particular, we introduce a horizontal cascade, each component of which is densely connected to the outputs of previous component. Stringing these components together allows us to effectively exploit features across different levels hierarchically to effectively address the multiple pixel-wise binary regression tasks. To assess the performance of our proposed network on these tasks, we carry out exhaustive evaluations on multiple representative datasets. Although these tasks are inherently very different, we show that our unified approach performs very well on all of them and works far better than current single-purpose state-of-theart methods. All the code in this paper will be publicly available.
Simultaneous Localization and Mapping with Detection and Tracking of Moving Objects

Both simultaneous localization and mapping (SLAM) and detection and tracking of moving objects (DTMO) play key roles in robotics and automation. For certain constrained environments, SLAM and DTMO are becoming solved problems. But for robots working outdoors, and at high speeds, SLAM and DTMO are still incomplete. In earlier works, SLAM and DTMO are treated as two separate problems. In fact, they can be complementary to one another. In this paper, we present a new method to integrate SLAM and DTMO to solve both problems simultaneously for both indoor and outdoor applications. The results of experiments carried out with CMU Navlab8 and Navlab11 vehicles with the maximum speed of 45 mph in crowded urban and suburban areas verify the described work.
Probabilistic in-network caching for information-centric networks

In-network caching necessitates the transformation of centralised operations of traditional, overlay caching techniques to a decentralised and uncoordinated environment. Given that caching capacity in routers is relatively small in comparison to the amount of forwarded content, a key aspect is balanced distribution of content among the available caches. In this paper, we are concerned with decentralised, real-time distribution of content in router caches. Our goal is to reduce caching redundancy and in turn, make more efficient utilisation of available cache resources along a delivery path.
 Our in-network caching scheme, called ProbCache, approximates the caching capability of a path and caches contents probabilistically in order to: i) leave caching space for other flows sharing (part of) the same path, and ii) fairly multiplex contents of different flows among caches of a shared path.
 We compare our algorithm against universal caching and against schemes proposed in the past for Web-Caching architectures, such as Leave Copy Down (LCD). Our results show reduction of up to 20% in server hits, and up to 10% in the number of hops required to hit cached contents, but, most importantly, reduction of cache-evictions by an order of magnitude in comparison to universal caching.
Orchestration of IT/cloud and networks: From Inter-DC interconnection to SDN/NFV 5G services

The so-called 5G networks promise to be the foundations for the deployment of advanced services, conceived around the joint allocation and use of heterogeneous resources, including network, computing and storage. Resources are placed on remote locations constrained by the different service requirements, resulting in cloud infrastructures (as pool of resources) that need to be interconnected. The automation of the provisioning of such services relies on a generalized orchestration, defined as to the coherent coordination of heterogeneous systems, applied to common cases such as involving heterogeneous network domains in terms of control or data plane technologies, or cloud and network resources. Although cloud-computing platforms do take into account the need to interconnect remote virtual machine instances, mostly rely on managing L2 overlays over L3 (IP). The integration with transport networks is still not fully achieved, including leveraging the advances in software defined networks and transmission. We start with an overview of network orchestration, considering different models; we extend them to take into account cloud management while mentioning relevant existing initiatives and conclude with the NFV architecture.
Is beautiful really usable? Toward understanding the relation between usability, aesthetics, and affect in HCI

This paper analyzes the relation between usability and aesthetics. In a laboratory study, 80 participants used one of four different versions of the same online shop, differing in interface-aesthetics (low vs. high) and interface-usability (low vs. high). Participants had to find specific items and rate the shop before and after usage on perceived aesthetics and perceived usability, which were assessed using four validated instruments. Results show that aesthetics does not affect perceived usability. In contrast, usability has an effect on post-use perceived aesthetics. Our findings show that the “what is beautiful is usable” notion, which assumes that aesthetics enhances the perception of usability can be reversed under certain conditions (here: strong usability manipulation combined with a medium to large aesthetics manipulation). Furthermore, our results indicate that the user’s affective experience with the usability of the shop might serve as a mediator variable within the aestheticsusability relation: The frustration of poor usability lowers ratings on perceived aesthetics. The significance of the results is discussed in context of the existing research on the relation between aesthetics and usability.
Cleansing effect of acidic L-arginine on human oral biofilm.

Dental plaque formed on tooth surfaces is a complex ecosystem composed of diverse oral bacteria and salivary components. Accumulation of dental plaque is a risk factor for dental caries and periodontal diseases. L-arginine has been reported to decrease the risk for dental caries by elevating plaque pH through the activity of arginine deiminase in oral bacteria. Here we evaluated the potential of L-arginine to remove established oral biofilms.



Biofilms were formed using human saliva mixed with Brain Heart Infusion broth supplemented with 1 % sucrose in multi-well plates or on plastic discs. After washing the biofilms with saline, citrate (10 mM, pH3.5), or L-arginine (0.5 M, pH3.5), the retained biofilms were analyzed by crystal violet staining, scanning electron microscopy, and Illumina-based 16S rDNA sequencing.



Washing with acidic L-arginine detached oral biofilms more efficiently than saline and significantly reduced biofilm mass retained in multi-well plates or on plastic discs. Illumina-based microbiota analysis showed that citrate (pH3.5) preferentially washed out Streptococcus from mature oral biofilm, whereas acidic L-arginine prepared with 10 mM citrate buffer (pH3.5) non-specifically removed microbial components of the oral biofilm.



Acidic L-arginine prepared with citrate buffer (pH3.5) effectively destabilized and removed mature oral biofilms. The acidic L-arginine solution described here could be used as an additive that enhances the efficacy of mouth rinses used in oral hygiene.
Let me Join Two Worlds! Analyzing the Integration of Web and Native Technologies in Hybrid Mobile Apps

We can notice that security problems of inappropriate integration of native and web technologies in hybrid mobile applications (apps) have been covered in the related state-of-the-art research. However, analyzing hybrid mobile apps' unique behaviors has been seldom addressed. In this paper, we explore the influence of native and web technologies integration in hybrid mobile apps on the generated profile of mobile applications. Specifically, we analyze the type of Security Sensitive APIs (SS-APIs) exposed to web content and identify the corresponding usage patterns by systematically tracking function-call-graphs of a large number of hybrid and native mobile apps. Our investigations indicate that the generated profiles for hybrid and native mobile apps are considerably different. Using our proposed tool, called Hybrid-scanner, for tracking and analyzing internal behaviors of hybrid mobile apps, we show that there is more trace of API calling for triggering a specific SS-API in a hybrid mobile app in comparison with Android native mobile apps. In addition, we have found that almost 40% of SS-APIs in hybrid mobile apps are invoked by third-party libraries, e.g. advertisement libraries. This knowledge, however, is crucial for designing appropriate malware detection or vulnerability mitigation strategies. Based on our results, we discuss two main approaches in Android malware analysis field and enumerate some suggestions which should be considered in order to successfully detect malicious behaviors in such new type of apps.
The first de novo transcriptome of pepino (Solanum muricatum): assembly, comprehensive analysis and comparison with the closely related species S. caripense, potato and tomato

Solanum sect. Basarthrum is phylogenetically very close to potatoes (Solanum sect. Petota) and tomatoes (Solanum sect. Lycopersicon), two groups with great economic importance, and for which Solanum sect. Basarthrum represents a tertiary gene pool for breeding. This section includes the important regional cultigen, the pepino (Solanum muricatum), and several wild species. Among the wild species, S. caripense is prominent due to its major involvement in the origin of pepino and its wide geographical distribution. Despite the value of the pepino as an emerging crop, and the potential for gene transfer from both the pepino and S. caripense to potatoes and tomatoes, there has been virtually no genomic study of these species. Using Illumina HiSeq 2000, RNA-Seq was performed with a pool of three tissues (young leaf, flowers in pre-anthesis and mature fruits) from S. muricatum and S. caripense, generating almost 111,000,000 reads among the two species. A high quality de novo transcriptome was assembled from S. muricatum clean reads resulting in 75,832 unigenes with an average length of 704 bp. These unigenes were functionally annotated based on similarity of public databases. We used Blast2GO, to conduct an exhaustive study of the gene ontology, including GO terms, EC numbers and KEGG pathways. Pepino unigenes were compared to both potato and tomato genomes in order to determine their estimated relative position, and to infer gene prediction models. Candidate genes related to traits of interest in other Solanaceae were evaluated by presence or absence and compared with S. caripense transcripts. In addition, by studying five genes, the phylogeny of pepino and five other members of the family, Solanaceae, were studied. The comparison of S. caripense reads against S. muricatum assembled transcripts resulted in thousands of intra- and interspecific nucleotide-level variants. In addition, more than 1000 SSRs were identified in the pepino transcriptome. This study represents the first genomic resource for the pepino. We suggest that the data will be useful not only for improvement of the pepino, but also for potato and tomato breeding and gene transfer. The high quality of the transcriptome presented here also facilitates comparative studies in the genus Solanum. The accurate transcript annotation will enable us to figure out the gene function of particular traits of interest. The high number of markers (SSR and nucleotide-level variants) obtained will be useful for breeding programs, as well as studies of synteny, diversity evolution, and phylogeny.
Design of Multiway Power Divider by Using Stepped-Impedance Transformers

In this paper, the design of multiway power dividers by interconnecting power dividers with fewer output ports is studied by transforming them into multisection stepped-impedance transformers. By using this approach, it is easy to design multiway power dividers with required equal ripples of input reflection (S11 ) within a wide passband. The interconnecting lines can be used as additional matching sections to improve the input matching. General properties of this type of multiway power dividers can be easily obtained. Design of multiway power divider with required input reflection level can be readily performed by using the published data and tables of stepped-impedance transformer in the literature. Both even- and odd-mode analyses are performed to obtain the optimal isolation resistor values. A prototype of a wideband four-way power divider with a rhombic architecture is designed, fabricated, and measured. Simulation and measurement results are in good agreement and validate the proposed approach.
Piaget : Implications for Teaching

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Hand Gesture Recognition Based on Perceptual Shape Decomposition with a Kinect Camera

In this paper, we propose the Perceptual Shape Decomposition (PSD) to detect fingers for a Kinect-based hand gesture recognition system. The PSD is formulated as a discrete optimization problem by removing all negative minima with minimum cost. Experiments show that our PSD is perceptually relevant and robust against distortion and hand variations, and thus improves the recognition system performance. key words: Kinect camerta, hand gesture recognition, perceptual decomposition, finger detection
BlueSky: a cloud-backed file system for the enterprise

We present BlueSky, a network file system backed by cloud storage. BlueSky stores data persistently in a cloud storage provider such as Amazon S3 or Windows Azure, allowing users to take advantage of the reliability and large storage capacity of cloud providers and avoid the need for dedicated server hardware. Clients access the storage through a proxy running on-site, which caches data to provide lower-latency responses and additional opportunities for optimization. We describe some of the optimizations which are necessary to achieve good performance and low cost, including a log-structured design and a secure in-cloud log cleaner. BlueSky supports multiple protocols—both NFS and CIFS—and is portable to different providers.
Physical Primitive Decomposition

Objects are made of parts, each with distinct geometry, physics, functionality, and affordances. Developing such a distributed, physical, interpretable representation of objects will facilitate intelligent agents to better explore and interact with the world. In this paper, we study physical primitive decomposition—understanding an object through its components, each with physical and geometric attributes. As annotated data for object parts and physics are rare, we propose a novel formulation that learns physical primitives by explaining both an object’s appearance and its behaviors in physical events. Our model performs well on block towers and tools in both synthetic and real scenarios; we also demonstrate that visual and physical observations often provide complementary signals. We further present ablation and behavioral studies to better understand our model and contrast it with human performance.
Risk prediction models for hospital readmission: a systematic review.

Predicting hospital readmission risk is of great interest to identify which patients would benefit most from care transition interventions, as well as to risk-adjust readmission rates for the purposes of hospital comparison.



To summarize validated readmission risk prediction models, describe their performance, and assess suitability for clinical or administrative use.



The databases of MEDLINE, CINAHL, and the Cochrane Library were searched from inception through March 2011, the EMBASE database was searched through August 2011, and hand searches were performed of the retrieved reference lists. Dual review was conducted to identify studies published in the English language of prediction models tested with medical patients in both derivation and validation cohorts.



Data were extracted on the population, setting, sample size, follow-up interval, readmission rate, model discrimination and calibration, type of data used, and timing of data collection.



Of 7843 citations reviewed, 30 studies of 26 unique models met the inclusion criteria. The most common outcome used was 30-day readmission; only 1 model specifically addressed preventable readmissions. Fourteen models that relied on retrospective administrative data could be potentially used to risk-adjust readmission rates for hospital comparison; of these, 9 were tested in large US populations and had poor discriminative ability (c statistic range: 0.55-0.65). Seven models could potentially be used to identify high-risk patients for intervention early during a hospitalization (c statistic range: 0.56-0.72), and 5 could be used at hospital discharge (c statistic range: 0.68-0.83). Six studies compared different models in the same population and 2 of these found that functional and social variables improved model discrimination. Although most models incorporated variables for medical comorbidity and use of prior medical services, few examined variables associated with overall health and function, illness severity, or social determinants of health.



Most current readmission risk prediction models that were designed for either comparative or clinical purposes perform poorly. Although in certain settings such models may prove useful, efforts to improve their performance are needed as use becomes more widespread.
Millimeter-Wave Substrate Integrated Waveguide Multibeam Antenna Based on the Parabolic Reflector Principle

A novel substrate integrated waveguide (SIW) multibeam antenna based on the parabolic reflector principle is proposed and implemented at 37.5 GHz, which takes the advantages of low loss, low profile, high gain, and mass producible. A prototype of the proposed antenna with seven input ports generating a corresponding number of output beams is fabricated in a standard PCB process. The measurements are in good agreement with the simulations, and the results demonstrate that this type of printed multibeam antenna is a good choice for communications applications where mobility and high gain are simultaneously required.
A framework for analyzing semantic change of words across time

Recently, large amounts of historical texts have been digitized and made accessible to the public. Thanks to this, for the first time, it became possible to analyze evolution of language through the use of automatic approaches. In this paper, we show the results of an exploratory analysis aiming to investigate methods for studying and visualizing changes in word meaning over time. In particular, we propose a framework for exploring semantic change at the lexical level, at the contrastive-pair level, and at the sentiment orientation level. We demonstrate several kinds of NLP approaches that altogether give users deeper understanding of word evolution. We use two diachronic corpora that are currently the largest available historical language corpora. Our results indicate that the task is feasible and satisfactory outcomes can be already achieved by using simple approaches.
ParSym: Parallel symbolic execution

Scaling software analysis techniques based on source-code, such as symbolic execution and data flow analyses, remains a challenging problem for systematically checking software systems. The increasing availability of clusters of commodity machines provides novel opportunities to scale these techniques using parallel algorithms. This paper presents ParSym, a novel parallel algorithm for scaling symbolic execution using a parallel implementation. In every iteration ParSym explores multiple branches of a path condition in parallel by distributing them among available workers resulting in an efficient parallel version of symbolic execution. Experimental results show that symbolic execution is highly scalable using parallel algorithms: using 512 processors, more than two orders of magnitude speedup are observed.