nils-herrmann/clean_scirepeval huggingface dataset:
Human interaction discovery in smartphone proximity networks

Since humans are fundamentally social beings and interact frequently with others in their daily life, understanding social context is of primary importance in building context-aware applications. In this paper, using smartphone Bluetooth as a proximity sensor to create social networks, we present a probabilistic approach to mine human interaction types in real life. Our analysis is conducted on Bluetooth data continuously sensed with smartphones for over one year from 40 individuals who are professionally or personally related. The results show that the model can automatically discover a variety of social contexts. We objectively validated our model by studying its predictive and retrieval performance.
Correct estimation of parameters for ultrasound nuchal translucency screening.

Johnson, S. (1996). Down’s syndrome screening in the UK, Lancet, 347, 906–907. Pandya, P.P., Snijders, R.J.M., Johnson, S.P., de Loudes Brizot, M., Nicolaides, K.H. (1995). Screening for fetal trisomies by maternal age and fetal nuchal translucency thickness at 10 to 14 weeks of gestation, Br. . Schuchter, K., Wald, N.J., Hackshaw, A.K., Hafner, E., Liebhardt, E. (1998). The distribution of nuchal translucency at 10–13 weeks of pregnancy, Prenat. Diagn., 18, 281–286. Wald, N.J., George, L., Smith, D., Densem, J.W., Petterson, K. (1996). On behalf of the International Prenatal Screening Research Group. Serum screening for Down’s syndrome between 8 and 14 weeks of pregnancy, Br.  Wald, N.J., Hackshaw, A.K. (1997). Combining ultrasound and biochemistry in first-trimester screening for Down’s syndrome, Prenat. Diagn., 17, 821–829. Wald, N.J., Kennard, A., Hackshaw, A., McGuire, A. (1997). Antenatal screening for Down’s syndrome,  Barkai, G., Brambati, B., Teisner, B., Fuhrmann, W. (1992). First trimester concentrations of PAPP-A and placental protein 14 in Down’s syndrome, BMJ, 305, 28.
Wireless Sensor Networks: a Survey on Environmental Monitoring

Traditionally, environmental monitoring is achieved by a small number of expensive and high precision sensing unities. Collected data are retrieved directly from the equipment at the end of the experiment and after the unit is recovered. The implementation of a wireless sensor network provides an alternative solution by deploying a larger number of disposable sensor nodes. Nodes are equipped with sensors with less precision, however, the network as a whole provides better spatial resolution of the area and the users can have access to the data immediately. This paper surveys a comprehensive review of the available solutions to support wireless sensor network environmental monitoring applications.
Vaginal Leech Infestation: A Rare Cause of Hypovolumic Shock In Postmenopausal Woman

Human leech infestation is a disease of the poor who live in rural areas and use water contaminated with leeches. Like any other body orifices, vagina can also be infested by leech when females use contaminated water for bathing and/or douching. Although this condition is very rare in postmenopausal women, it causes morbidities and mortalities.



A 70 year old Para X (all alive) abortion I mother, postmenopausal for the last 20 years, presented with vaginal bleeding of 3 weeks duration to Gimbie Adventist Hospital, Western Ethiopia. On examination, she had deranged vital signs and there was a dark moving worm attached to the cervical os. She was admitted with the diagnosis of hypovolumic shock and severe anemia secondary to postmenopausal vaginal bleeding. After the patient was stabilized with intravenous crystalloids, the leech was removed from the vagina. She was then transfused with two units of whole blood and discharged with good condition on the 3(rd) post procedure day with ferrous sulphate.



Vaginal leech infestation in postmenopausal woman can cause hypovolumic shock and severe anemia. Therefore, in order to decrease morbidities from failure or delay in making the diagnosis, health care providers should consider the possibility of vaginal leech infestation in postmenopausal woman from rural areas and those who use river water for drinking, bathing and/or douching and presented with vaginal bleeding. In addition, the importance of using clean water and improving access to safe water should be emphasized.
Neural mechanisms involved in the comprehension of metaphoric and literal sentences: An fMRI study

In this study, we investigated the neural substrate involved in the comprehension of novel metaphoric sentences by comparing the findings to those obtained with literal and anomalous sentences using event-related functional magnetic resonance imaging (fMRI). Stimuli consisted of 63 copula sentences ("An A is a B") in Japanese with metaphorical, literal, or anomalous meanings. Thirteen normal participants read these sentences silently and responded as to whether or not they could understand the meaning of each sentence. When participants read metaphoric sentences in contrast to literal sentences, higher activation was seen in the left medial frontal cortex (MeFC: Brodmann's area (BA) 9/10), the left superior frontal cortex (SFC: BA 9), and the left inferior frontal cortex (IFC: BA 45). The opposite contrast (literal sentences in contrast to metaphoric sentences) gave higher activation in the precuneus (BA 7) and the right middle and SFC (BA 8/9). These findings suggest that metaphor comprehension is involved in specific neural mechanisms of semantic and pragmatic processing which differ from those in literal comprehension. Especially, our results suggest that activation in the left IFC reflects the semantic processing and that activation in the MeFC reflects the process of inference for metaphorical interpretation to establish semantic coherence.
Temporal Action Localization by Structured Maximal Sums

We address the problem of temporal action localization in videos. We pose action localization as a structured prediction over arbitrary-length temporal windows, where each window is scored as the sum of frame-wise classification scores. Additionally, our model classifies the start, middle, and end of each action as separate components, allowing our system to explicitly model each actions temporal evolution and take advantage of informative temporal dependencies present in that structure. In this framework, we localize actions by searching for the structured maximal sum, a problem for which we develop a novel, provably-efficient algorithmic solution. The frame-wise classification scores are computed using features from a deep Convolutional Neural Network (CNN), which are trained end-to-end to directly optimize for a novel structured objective. We evaluate our system on the THUMOS 14 action detection benchmark and achieve competitive performance.
The Rademacher Complexity of Linear Transformation Classes

Bounds are given for the empirical and expected Rademacher complexity of classes of linear transformations from a Hilbert space H to a nite dimensional space. The results imply generalization guarantees for graph regularization and multi-task subspace learning. 1  Rademacher averages have been introduced to learning theory as an e¢ cient complexity measure for function classes, motivated by tight, sample or distribution dependent generalization bounds (, ). Both the denition of Rademacher complexity and the generalization bounds extend easily from realvalued function classes to function classes with values in R, as they are relevant to multi-task learning (, ). There has been an increasing interest in multi-task learning which has shown to be very e¤ective in experiments ([7], ), and there have been some general studies of its generalisation performance (, ). For a large collection of tasks there are usually more data available than for a single task and these data may be put to a coherent use by some constraint of relatedness. A practically interesting case is linear multi-task learning, extending linear large margin classiers to vector valued large-margin classiers. Di¤erent types of constraints have been proposed: Evgeniou et al (, ) propose graph regularization, where the vectors dening the classiers of related tasks have to be near each other. They also show that their scheme can be implemented in the framework of kernel machines. Ando and Zhang  on the other hand require the classiers to be members of a common low dimensional subspace. They also give generalization bounds using Rademacher complexity, but these bounds increase with the dimension of the input space. This paper gives dimension free bounds which apply to both approaches. 1.1 Multi-task generalization and Rademacher complexity Suppose we have m classication tasks, represented by m independent random variables X ; Y l taking values in X f 1; 1g, where X l models the random
Implementing situation-aware and user-adaptive music recommendation service in semantic web and real-time multimedia computing environment

With the advent of the ubiquitous era, many studies have been devoted to various situation-aware services in the semantic web environment. One of the most challenging studies involves implementing a situation-aware personalized music recommendation service which considers the user’s situation and preferences. Situation-aware music recommendation requires multidisciplinary efforts including low-level feature extraction and analysis, music mood classification and human emotion prediction. In this paper, we propose a new scheme for a situation-aware/user-adaptive music recommendation service in the semantic web environment. To do this, we first discuss utilizing knowledge for analyzing and retrieving music contents semantically, and a user adaptive music recommendation scheme based on semantic web technologies that facilitates the development of domain knowledge and a rule set. Based on this discussion, we describe our Context-based Music Recommendation (COMUS) ontology for modeling the user’s musical preferences and contexts, and supporting reasoning about the user’s desired emotions and preferences. Basically, COMUS defines an upper music ontology that captures concepts on the general properties of music such as titles, artists and genres. In addition, it provides functionality for adding domain-specific ontologies, such as music features, moods and situations, in a hierarchical manner, for extensibility. Using this context ontology, we believe that logical reasoning rules can be inferred based on high-level (implicit) knowledge such as situations from low-level (explicit) knowledge. As an innovation, our ontology can express detailed and complicated relations among music clips, moods and situations, which enables users to find appropriate music. We present some of the experiments we performed as a case-study for music recommendation.
Semi-custom design of adiabatic adder circuits

The paper presents the design, evaluation and performance comparison of cell based, low power adiabatic adder circuits operated by two-phase sinusoidal power clock signals, as against the literatures providing the operation of various adiabatic circuits, focusing on inverter circuits and logic gates, powered by ramp, three phase and four phase clock signals. The cells are designed for the quasi-adiabatic families, namely, 2N2P, 2N2N2P, PFAL, ADSL and IPGL for configuring complex adder circuits. A family of adiabatic cell based designs for carry lookahead adders and tree adders were designed. The simulations prove that the cell based design of tree adder circuits can save energy ranging from 2 to 100 over a frequency range of operation of 2MHz to 200MHz against the static CMOS circuit implementation. The schematic edit and T-Spice of Tanner tools formed the simulation environment.
Perceiving and Reasoning about a Changing World

A rational agent (artificial or otherwise) residing in a complex changing environment must gather information perceptually, update that information as the world changes, and combine that information with causal information to reason about the changing world. Using the system of defeasible reasoning that is incorporated into the OSCAR architecture for rational agents, a set of reason-schemas is proposed for enabling an agent to perform some of the requisite reasoning. Along the way, solutions are proposed for the Frame Problem, the Qualification Problem, and the Ramification Problem. The principles and reasoning described have all been implemented in OSCAR.  defeasible reasoning, nonmonotonic logic, perception, causes, causation, time, temporal This work was supported in part by NSF grant no. IRI-9634106. An early version of some of this material appears in Pollock (1996), but it has undergone substantial change in the present paper. projection, frame problem, qualification problem, ramification problem, OSCAR.
2 What Have We Been Calling Integration ?

The word integration has been used with different meanings in the ontology field. This article aims at clarifying the meaning of the word “integration” and presenting some of the relevant work done in integration. We identify three meanings of ontology “integration”: when building a new ontology reusing (by assembling, extending, specializing or adapting) other ontologies already available; when building an ontology by merging several ontologies into a single one that unifies all of them; when building an application using one or more ontologies. We discuss the different meanings of “integration”, identify the main characteristics of the three different processes and propose This work was partially supported by JNICT grant No. PRAXIS XXI/BD/11202/97 (Sub-Programa Ciência e Tecnologia do Segundo Quadro Comunitário de Apoio) and project PRAXIS XXI/1568/95. The copyright of this paper belongs to the papers authors. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage. Proceedings of the IJCAI-99 workshop on Ontologies and Problem-Solving Methods (KRR5) Stockholm, Sweden, August 2, 1999 (V.R. Benjamins, B. Chandrasekaran, A. Gomez-Perez, N. Guarino, M. Uschold, eds.) http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-18/ three words to distinguish among those meanings: integration, merge and use.
The architecture of a digital forensic readiness management system

A coordinated approach to digital forensic readiness (DFR) in a large organisation requires the management and monitoring of a wide variety of resources, both human and technical. The resources involved in DFR in large organisations typically include staff from multiple departments and business units, as well as network infrastructure and computing platforms. The state of DFR within large organisations may therefore be adversely affected if the myriad human and technical resources involved are not managed in an optimal manner. This paper contributes to DFR by proposing the novel concept of a digital forensic readiness management system (DFRMS). The purpose of a DFRMS is to assist large organisations in achieving an optimal level of management for DFR. In addition to this, we offer an architecture for a DFRMS. This architecture is based on requirements for DFR that we ascertained from an exhaustive review of the DFR literature. We describe the architecture in detail and show that it meets the requirements set out in the DFR literature. The merits and disadvantages of the architecture are also discussed. Finally, we describe and explain an early prototype of a DFRMS.
Sim4CV: A Photo-Realistic Simulator for Computer Vision Applications

We present a photo-realistic training and evaluation simulator (Sim4CV) (http://www.sim4cv.org) with extensive applications across various fields of computer vision. Built on top of the Unreal Engine, the simulator integrates full featured physics based cars, unmanned aerial vehicles (UAVs), and animated human actors in diverse urban and suburban 3D environments. We demonstrate the versatility of the simulator with two case studies: autonomous UAV-based tracking of moving objects and autonomous driving using supervised learning. The simulator fully integrates both several state-of-the-art tracking algorithms with a benchmark evaluation tool and a deep neural network architecture for training vehicles to drive autonomously. It generates synthetic photo-realistic datasets with automatic ground truth annotations to easily extend existing real-world datasets and provides extensive synthetic data variety through its ability to reconfigure synthetic worlds on the fly using an automatic world generation tool.
GPFS: A Shared-Disk File System for Large Computing Clusters

GPFS is a distributed file system run on some of the largest supercomputers and clusters. Through it's deployment, the authors have been able to gain a number of key insights into the methodology of developing a distributed file system which can reliably scale and maintain POSIX semantics. Achieving the necessary throughput requires parallel access for reading, writing and updating metadata. It is a process that is accomplished mostly through distributed locking.
Real-time 3D video system based on FPGA

With the higher demand of the three dimensional (3D) imaging, a high definition real-time 3D video system based on FPGA is proposed. The system is made up of CMOS image sensors, DDR2 SDRAM, High Definition Multimedia Interface (HDMI) transmitter and Field Programmable Gate Array (FPGA). CMOS image sensor produces digital video streaming. DDR2 SDRAM buffers large amount of video data. FPGA processes the video streaming and realizes 3D data format conversion. HDMI transmitter is utilized to transmit 3D format data. Using the active 3D display device and shutter glasses, the system can achieve the living effect of real-time 3D high definition imaging. The resolution of the system is 720p@60Hz in 3D mode.
De novo design of a hyperstable non-natural protein-ligand complex with sub-Å accuracy.

Protein catalysis requires the atomic-level orchestration of side chains, substrates and cofactors, and yet the ability to design a small-molecule-binding protein entirely from first principles with a precisely predetermined structure has not been demonstrated. Here we report the design of a novel protein, PS1, that binds a highly electron-deficient non-natural porphyrin at temperatures up to 100 °C. The high-resolution structure of holo-PS1 is in sub-Å agreement with the design. The structure of apo-PS1 retains the remote core packing of the holoprotein, with a flexible binding region that is predisposed to ligand binding with the desired geometry. Our results illustrate the unification of core packing and binding-site definition as a central principle of ligand-binding protein design.
Why are A(2B) receptors low-affinity adenosine receptors? Mutation of Asn273 to Tyr increases affinity of human A(2B) receptor for 2-(1-Hexynyl)adenosine.

Adenosine A(2B) receptors are known as low-affinity receptors due to their modest-to-negligible affinity for adenosine and prototypic agonists. Despite numerous synthetic efforts, 5'-N-ethylcarboxamidoadenosine (NECA) still is the reference agonist, albeit nonselective for this receptor. In our search for higher affinity agonists, we developed decision schemes to select amino acids for mutation to the corresponding residues in the most homologous, higher affinity, human A(2A) receptor. One scheme exploited knowledge on sequence alignments and modeling data and yielded three residues, V11, L58, and F59, mutation of which did not affect agonist affinity. The second scheme combined knowledge on sequence alignments and mutation data and pointed to Ala12 and Asn273. Mutation of Ala12 to threonine did not affect the affinity for NECA, (R)-N(6)-(phenylisopropyl)adenosine (R-PIA), and 2Cl Ado. The affinity of the N273Y mutant for NECA and R-PIA and for the antagonists xanthine amine congener (XAC), ZM241385, and SCH58261 was also unaltered. However, this mutant had a slightly increased affinity for a 2-substituted adenosine derivative, CGS21680. This prompted us to investigate other 2-substituted adenosines, with selectivity and high affinity for A(2A) receptors. All four compounds tested had improved affinity for the N273Y receptor. Of these, 2-(1-hexynyl)adenosine had submicromolar affinity for the N273Y receptor, 0.18 +/- 0.10 microM, with a 61-fold affinity gain over the wt receptor. In addition, the non-NECA analog (S)-PHP adenosine had an affinity of 1.7 +/- 0.5 microM for the wt receptor. The high affinity of (S)-PHP adenosine for the wt receptor suggests that further modifications at the 2-position may yield agonists with even higher affinity for A(2B) receptors.
Do Normalization Layers in a Deep ConvNet Really Need to Be Distinct?

Yes, they do. This work investigates a perspective for deep learning: whether different normalization layers in a ConvNet require different normalizers. This is the first step towards understanding this phenomenon. We allow each convolutional layer to be stacked before a switchable normalization (SN) that learns to choose a normalizer from a pool of normalization methods. Through systematic experiments in ImageNet, COCO, Cityscapes, and ADE20K, we answer three questions: (a) Is it useful to allow each normalization layer to select its own normalizer? (b) What impacts the choices of normalizers? (c) Do different tasks and datasets prefer different normalizers? Our results suggest that (1) using distinct normalizers improves both learning and generalization of a ConvNet; (2) the choices of normalizers are more related to depth and batch size, but less relevant to parameter initialization, learning rate decay, and solver; (3) different tasks and datasets have different behaviors when learning to select normalizers.
Color to gray and back: color embedding into textured gray images

We have developed a reversible method to convert color graphics and pictures to gray images. The method is based on mapping colors to low-visibility high-frequency textures that are applied onto the gray image. After receiving a monochrome textured image, the decoder can identify the textures and recover the color information. More specifically, the image is textured by carrying a subband (wavelet) transform and replacing bandpass subbands by the chrominance signals. The low-pass subband is the same as that of the luminance signal. The decoder performs a wavelet transform on the received gray image and recovers the chrominance channels. The intent is to print color images with black and white printers and to be able to recover the color information afterwards. Registration problems are discussed and examples are presented.
EE-LEACH: development of energy-efficient LEACH Protocol for data gathering in WSN

A wireless sensor network (WSN) consists of a huge number of sensor nodes that are inadequate in energy, storage and processing power. One of the major tasks of the sensor nodes is the collection of data and forwarding the gathered data to the base station (BS). Hence, the network lifetime becomes the major criteria for effective design of the data gathering schemes in WSN. In this paper, an energy-efficient LEACH (EE-LEACH) Protocol for data gathering is introduced. It offers an energy-efficient routing in WSN based on the effective data ensemble and optimal clustering. In this system, a cluster head is elected for each clusters to minimize the energy dissipation of the sensor nodes and to optimize the resource utilization. The energy-efficient routing can be obtained by nodes which have the maximum residual energy. Hence, the highest residual energy nodes are selected to forward the data to BS. It helps to provide better packet delivery ratio with lesser energy utilization. The experimental results shows that the proposed EE-LEACH yields better performance than the existing energy-balanced routing protocol (EBRP) and LEACH Protocol in terms of better packet delivery ratio, lesser end-to-end delay and energy consumption. It is obviously proves that the proposed EE-LEACH can improve the network lifetime.