nils-herrmann/clean_scirepeval huggingface dataset:
Emotion hacking VR (EH-VR): amplifying scary VR experience by accelerating real heart rate using false vibrotactile biofeedback

Emotion hacking virtual reality (EH-VR) system is an interactive system that hacks one's heartbeat and controls it to accelerate scary VR experience. The EH-VR system provides vibrotactile biofeedback, which resembles a heartbeat, from the floor. The system determines false heartbeat frequency by detecting user's heart rate in real time and calculates false heart rate, which is faster than the one observed according to the quadric equation model. With the system, we demonstrate "Pressure of unknown" which is a CG VR space originally created to express the metaphor of scare. A user experiences this space by using a wheel chair as a controller to walk through a VR world displayed via HMD while receiving vibrotac-tile feedback of false heartbeat calculated from its own heart rate from the floor.
TrueNorth: Design and Tool Flow of a 65 mW 1 Million Neuron Programmable Neurosynaptic Chip

The new era of cognitive computing brings forth the grand challenge of developing systems capable of processing massive amounts of noisy multisensory data. This type of intelligent computing poses a set of constraints, including real-time operation, low-power consumption and scalability, which require a radical departure from conventional system design. Brain-inspired architectures offer tremendous promise in this area. To this end, we developed TrueNorth, a 65 mW real-time neurosynaptic processor that implements a non-von Neumann, low-power, highly-parallel, scalable, and defect-tolerant architecture. With 4096 neurosynaptic cores, the TrueNorth chip contains 1 million digital neurons and 256 million synapses tightly interconnected by an event-driven routing infrastructure. The fully digital 5.4 billion transistor implementation leverages existing CMOS scaling trends, while ensuring one-to-one correspondence between hardware and software. With such aggressive design metrics and the TrueNorth architecture breaking path with prevailing architectures, it is clear that conventional computer-aided design (CAD) tools could not be used for the design. As a result, we developed a novel design methodology that includes mixed asynchronous-synchronous circuits and a complete tool flow for building an event-driven, low-power neurosynaptic chip. The TrueNorth chip is fully configurable in terms of connectivity and neural parameters to allow custom configurations for a wide range of cognitive and sensory perception applications. To reduce the system's communication energy, we have adapted existing application-agnostic very large-scale integration CAD placement tools for mapping logical neural networks to the physical neurosynaptic core locations on the TrueNorth chips. With that, we have successfully demonstrated the use of TrueNorth-based systems in multiple applications, including visual object recognition, with higher performance and orders of magnitude lower power consumption than the same algorithms run on von Neumann architectures. The TrueNorth chip and its tool flow serve as building blocks for future cognitive systems, and give designers an opportunity to develop novel brain-inspired architectures and systems based on the knowledge obtained from this paper.
On Unexpectedness in Recommender Systems: Or How to Better Expect the Unexpected

Although the broad social and business success of recommender systems has been achieved across several domains, there is still a long way to go in terms of user satisfaction. One of the key dimensions for significant improvement is the concept of unexpectedness. In this article, we propose a method to improve user satisfaction by generating unexpected recommendations based on the utility theory of economics. In particular, we propose a new concept of unexpectedness as recommending to users those items that depart from what they would expect from the system - the consideration set of each user. We define and formalize the concept of unexpectedness and discuss how it differs from the related notions of novelty, serendipity, and diversity. In addition, we suggest several mechanisms for specifying the users’ expectations and propose specific performance metrics to measure the unexpectedness of recommendation lists. We also take into consideration the quality of recommendations using certain utility functions and present an algorithm for providing users with unexpected recommendations of high quality that are hard to discover but fairly match their interests. Finally, we conduct several experiments on “real-world” datasets and compare our recommendation results with other methods. The proposed approach outperforms these baseline methods in terms of unexpectedness and other important metrics, such as coverage, aggregate diversity and dispersion, while avoiding any accuracy loss.
Vehicle Routing And Scheduling Models, Simulation And City Logistics

Taniguchi defines City Logistics as “the process of totally optimising the logistics and transport activities by private companies in urban areas while considering the traffic environment, traffic congestion and energy consumption within the framework of a market economy”. The distribution of goods based on road services in urban areas contribute to traffic congestion, generates environmental impacts and in some cases incurs in high logistics costs. On the other hand the various stakeholders involved in the applications may have possibly conflicting objectives. Industrial firms, shippers, freight carriers, have individually established to meet consumer demands looking to maximize the company effectiveness and as a consequence from a social point of view the resulting logistics system is inefficient from the point of view of the social costs and environmental impacts. As a consequence the design and evaluation of City Logistics applications requires an integrated framework in which all components could work together. Therefore City Logistics models must be models that, further than including the main components of City Logistics applications, as vehicle routing and fleet management models, should be able of including also the dynamic aspects of the underlying road network, namely if ICT applications are taken into account. Some of the methodological proposals made so far are based on an integration of vehicle routing models and, dynamic traffic simulation models that emulate the actual traffic conditions providing at each time interval the estimates of the current travel times, queues, etc. on each link of the road network, that is, the information that will be used by the logistic model (i.e. a fleet management system identifying in real-time the positions of each vehicle in the fleet and its operational conditions type of load, available capacity, etc. – to determine the optimal dynamic routing and scheduling of the vehicle.
TSP: Mining Top-K Closed Sequential Patterns

Sequential pattern mining has been studied extensively in data mining community. Most previous studies require the specification of a minimum support threshold to perform the mining. However, it is difficult for users to provide an appropriate threshold in practice. To overcome this difficulty, we propose an alternative task: mining topfrequent closed sequential patterns of length no less than , where is the desired number of closed sequential patterns to be mined, and is the minimum length of each pattern. We mine closed patterns since they are compact representations of frequent patterns. We developed an efficient algorithm, called TSP, which makes use of the length constraint and the properties of topclosed sequential patterns to perform dynamic supportraising and projected database-pruning. Our extensive performance study shows that TSP outperforms the closed sequential pattern mining algorithm even when the latter is running with the best tuned minimum support threshold.
Noise Reduction of Speech Signal using Wavelet Transform with Modified Universal Threshold

In this paper, Discrete-wavelet transform (DWT) based algorithm are used for speech signal denoising. Here both hard and soft thresholding are used for denoising. Analysis is done on noisy speech signal corrupted by babble noise at 0dB, 5dB, 10dB and 15dB SNR levels. Simulation & results are performed in MATLAB 7.10.0 (R2010a). Output SNR (Signal to Noise Ratio) and MSE (Mean Square Error) is calculated & compared using both types of thresholding methods. Soft thresholding method performs better than hard thresholding at all input SNR levels. Hard thresholding shows a maximum of 21.79 dB improvement whereas soft thresholding shows a maximum of 35.16 dB improvement in output SNR. General Terms Thresholding, multi-resolution analysis, wavelet.
Effects of Tramadol on Fertility Hormones (Follicle Stimulating Hormone, Leutinizing Hormone, Prolactin, Testosterone, Estrogen and β-HCG) in Laboratory Rabbits.

Drug abuse in Nigeria has been indicated to be on the rise in recent years. The use of hard drugs and misuse of prescription drugs for nonmedical purposes cuts across all strata, especially the youths. Tramadol (2[(Dimethylamin) methyl]-1-(3-methoxyphenyl)cyclohexanol) is known for its analgesic potentials. This potent opioid pain killer is misused by Nigerian youths, owing to its suspicion as sexual performance drug. This study therefore is aimed at determining the effect of tramadol on hormone levels its improved libido properties and possibly fertility. Twenty seven (27) European rabbits weighing 1.0 to 2.0 kg were used. Animals were divided into four major groups consisting of male and female control, and male and female tramadol treated groups. Treated groups were further divided into oral and intramuscular (IM) administered groups. Oral groups were administered 25 mg/kg b.w. of tramadol per day while the IM groups received 15 mg/kg b.w. per Original Research Article Osadolor and Omo-Erhabor; BJMMR, 14(8): 1-11, 2016; Article no.BJMMR.24620 2 day over a period of thirty days. Blood samples were collected at the end of the experiment for progesterone, testosterone, estrogen (E2), luteinizing hormone, follicle stimulating hormone (FSH), β-human chorionic gonadotropin and prolactin estimation. Tramadol treated groups were compared with control groups at the end of the study, as well as within group comparison was done. From the results, FSH was found to be significantly reduced (p<0.05) while LH increased significantly (p<0.05). A decrease was observed for testosterone (p<0.001), and estrogen, FSH, progesterone also decreased (p<0.05). Significant changes weren’t observed when IM groups were compared with oral groups. This study does not support an improvement of libido by tramadol, though its possible usefulness in the treatment of premature ejaculation may have been established, but its capabilities to induce male and female infertility is still in doubt.
Fully convolutional neural networks for polyp segmentation in colonoscopy

Colorectal cancer (CRC) is one of the most common and deadliest forms of cancer, accounting for nearly 10% of all forms of cancer in the world. Even though colonoscopy is considered the most effective method for screening and diagnosis, the success of the procedure is highly dependent on the operator skills and level of hand-eye coordination. In this work, we propose to adapt fully convolution neural networks (FCN), to identify and segment polyps in colonoscopy images. We converted three established networks into a fully convolution architecture and fine-tuned their learned representations to the polyp segmentation task. We validate our framework on the 2015 MICCAI polyp detection challenge dataset, surpassing the state-of-the-art in automated polyp detection. Our method obtained high segmentation accuracy and a detection precision and recall of 73.61% and 86.31%, respectively.
Magnetic- Visual Sensor Fusion-based Dense 3D Reconstruction and Localization for Endoscopic Capsule Robots

Reliable and real-time 3D reconstruction and localization functionality is a crucial prerequisite for the navigation of actively controlled capsule endoscopic robots as an emerging, minimally invasive diagnostic and therapeutic technology for use in the gastrointestinal (GI) tract. In this study, we propose a fully dense, non-rigidly deformable, strictly real-time, intraoperative map fusion approach for actively controlled endoscopic capsule robot applications which combines magnetic and vision-based localization, with non-rigid deformations based frame-to-model map fusion. The performance of the proposed method is evaluated using four different ex-vivo porcine stomach models. Across different trajectories of varying speed and complexity, and four different endoscopic cameras, the root mean square surface reconstruction errors vary from 1.58 to 2.17 cm.
Speciation in the dark: diversification and biogeography of the deep‐sea gastropod genus Scaphander in the Atlantic Ocean

The aim of this work was to improve understanding about the mode, geography and tempo of diversification in deep-sea organisms, using a time-calibrated molecular phylogeny of the heterobranch gastropod genus Scaphander.


LOCATION
Atlantic and Indo-West Pacific (IWP) oceans.



Two mitochondrial gene markers (COI and 16S) and one nuclear ribosomal gene (28S) from six Atlantic species of Scaphander, and four IWP species were used to generate a multilocus phylogenetic hypothesis using uncorrelated relaxed-clock Bayesian methods implemented in beast and calibrated with the first occurrence of Scaphander in the fossil record (58.7-55.8 Ma).



Two main clades were supported: clade A, with sister relationships between species and subclades from the Atlantic and IWP; and clade B, with two western Atlantic sister species. Our estimates indicate that the two earliest divergences in clade A occurred between the middle Eocene and late Miocene and the most recent speciation occurred within the middle Miocene to Pleistocene. The divergence between the two western Atlantic species in clade B was estimated at late Oligocene-Pliocene.



The prevailing mode of speciation in Scaphander was allopatric, but one possible case of sympatric speciation was detected between two western Atlantic species. Sister relationships between IWP and Atlantic lineages suggest the occurrence both of vicariance events caused by the closure of the Tethyan Seaway and of dispersal between the two ocean basins, probably around South Africa during episodic disruptions of the deep-sea regional current system caused by glacial-interglacial cycles. Cladogenetic estimates do not support comparatively older diversification of deep-sea faunas, but corroborate the hypothesis of a pulse of diversification centred in the Oligocene and Miocene epochs. Amphi-Atlantic species were found to occur at deeper depths (bathyal-abyssal) and we hypothesize that trans-Atlantic connectivity is maintained by dispersal between neighbouring reproductive populations inhabiting the abyssal sea floor and by dispersal across the shelf and slope of Arctic and sub-Arctic regions.
Enterprise Architecture as Information Technology Strategy

Many organizations adopt cyclical processes to articulate and engineer technological responses to their business needs. Their objective is to increase competitive advantage and add value to the organization's processes, services and deliverables, in line with the organization's vision and strategy. The major challenges in achieving these objectives include the rapid changes in the business and technology environments themselves, such as changes to business processes, organizational structure, architectural requirements, technology infrastructure and information needs. No activity or process is permanent in the organization. To achieve their objectives, some organizations have adopted an Enterprise Architecture (EA) approach, others an Information Technology (IT) strategy approach, and yet others have adopted both EA and IT strategy for the same primary objectives. The deployment of EA and IT strategy for the same aims and objectives raises question whether there is conflict in adopting both approaches. The paper and case study presented here, aimed at both academics and practitioners, examines how EA could be employed as IT strategy to address both business and IT needs and challenges.
Comparative fluorescence analysis of the bovine sperm using IVA-520 (anti-CD46 antibody) and lectins: probable localisation of CD46 on bovine sperm membrane.

Membrane cofactor protein (CD46) is complement regulatory protein with probable function in the reproduction process. Expression of CD46 on human, mice, rat and guinea pig spermatozoa is restricted to the inner acrosomal membrane. In spite of the presence of anti-sperm antibodies and other potential complement activating agents in follicular fluid, CD46 is not expressed on the plasma membrane of spermatozoa as the other complement regulatory proteins (DAF and CD59) in human. Using dual immunofluorescence labelling with mAb IVA-520 (anti-bovine CD46) and various lectins with different binding pattern or monoclonal antibody ACR.4, targeted against intra-acrosomal protein, we excluded the expression of CD46 on the inner acrosomal membrane as well as in the acrosomal content but, we suggested the localization of this molecule on the outer acrosomal membrane and possibly on the plasma membrane of bovine sperm.
Fang: A Firewall Analysis Engine

Today, even a moderately sized corporate intranet contains multiple firewalls and routers, which are all used to enforce various aspects of the global corporate security policy. Configuring these devices to work in unison is difficult, especially if they are made by different vendors. Even testing or reverse-engineering an existing configuration (say, when a new security administrator takes over) is hard. Firewall configuration files are written in low-level formalisms, whose readability is comparable to assembly code, and the global policy is spread over all the firewalls that are involved. To alleviate some of these difficulties, we designed and implemented a novel firewall analysis tool. Our software allows the administrator to easily discover and test the global firewall policy (either a deployed policy or a planned one). Our tool uses a minimal description of the network topology, and directly parses the various vendor-specific lowlevel configuration files. It interacts with the user through a query-and-answer session, which is conducted at a much higher level of abstraction. A typical question our tool can answer is “from which machines can our DMZ be reached, and with which services?”. Thus, our tool complements existing vulnerability analysis tools, as it can be used before a policy is actually deployed, it operates on a more understandable level of abstraction, and it deals with all the firewalls at once.
Behind closed doors: measurement and analysis of CryptoLocker ransoms in Bitcoin

Bitcoin, a decentralized cryptographic currency that has experienced proliferating popularity over the past few years, is the common denominator in a wide variety of cybercrime. We perform a measurement analysis of CryptoLocker, a family of ransomware that encrypts a victim's files until a ransom is paid, within the Bitcoin ecosystem from September 5, 2013 through  2014. Using information collected from online fora, such as reddit and BitcoinTalk, as an initial starting point, we generate a cluster of 968 Bitcoin addresses belonging to CryptoLocker. We provide a lower bound for CryptoLocker's economy in Bitcoin and identify 795 ransom payments totalling 1,128.40 BTC ($310,472.38), but show that the proceeds could have been worth upwards of $1.1 million at peak valuation. By analyzing ransom payment timestamps both longitudinally across CryptoLocker's operating period and transversely across times of day, we detect changes in distributions and form conjectures on CryptoLocker that corroborate information from previous efforts. Additionally, we construct a network topology to detail CryptoLocker's financial infrastructure and obtain auxiliary information on the CryptoLocker operation. Most notably, we find evidence that suggests connections to popular Bitcoin services, such as Bitcoin Fog and BTC-e, and subtle links to other cybercrimes surrounding Bitcoin, such as the Sheep Marketplace scam of 2013. We use our study to underscore the value of measurement analyses and threat intelligence in understanding the erratic cybercrime landscape.
Neural-based Natural Language Generation in Dialogue using RNN Encoder-Decoder with Semantic Aggregation

Natural language generation (NLG) is an important component in spoken dialogue systems. This paper presents a model called Encoder-Aggregator-Decoder which is an extension of an Recurrent Neural Network based Encoder-Decoder architecture. The proposed Semantic Aggregator consists of two components: an Aligner and a Refiner. The Aligner is a conventional attention calculated over the encoded input information, while the Refiner is another attention or gating mechanism stacked over the attentive Aligner in order to further select and aggregate the semantic elements. The proposed model can be jointly trained both sentence planning and surface realization to produce natural language utterances. The model was extensively assessed on four different NLG domains, in which the experimental results showed that the proposed generator consistently outperforms the previous methods on all the NLG domains.
Monotonic Wide-Range Digitally Controlled Oscillator Compensated for Supply Voltage Variation

A digitally controlled oscillator (DCO) to be used in an all-digital phase-locked loop (PLL) is presented which offers a wide operating frequency range, a monotonic gain curve, and compensation for instantaneous supply voltage variation. The monotonic and wide oscillation frequency is achieved by interpolating at the fine tuning block between two nodes selected from a coarse delay line. Supply voltage compensation is obtained by dynamically adjusting the strength of the feedback latch of the delay cell in response to the change of the supply voltage.
Ergonomics Principles Associated With Laparoscopic Surgeon Injury/Illness

This study sought to investigate the prevalence of laparoscopic surgeon injury/illness symptoms and evaluate associations between symptoms and operating room ergonomics.



Although laparoscopic procedures significantly benefit patients in terms of decreased recovery times and improved outcomes, they contribute to mental fatigue and musculoskeletal problems among surgeons. A variety of ergonomic interventions and applications are implemented by surgeons to reduce health problems. Currently, there is a gap in knowledge regarding a surgeon's individual assessment of the operating room, an assessment that, in turn, would prompt the implementation of these interventions.



A new survey instrument solicited information from surgeons (N = 61) regarding surgeon demographics, perception, frequency of operating room equipment adjustment, and self-reported symptoms. Surgeons responded to questions addressing safety, ergonomics, and fatigue in the operating room, using a 5-point Likert-type scale that included the option undecided.



Surgeons who responded undecided were more likely to experience symptoms of injury/illness than respondents who were able to assess the features of their operating rooms. Symptoms were experienced by 100% of participants. The most prevalent symptoms were neck stiffness, back stiffness, and back pain.



This study supports hypotheses that surgeons are experiencing body part discomfort and indicators of fatigue that may be associated with performing laparoscopy. Results suggest that awareness, knowledge, and utilization of ergonomic principles could protect surgeons against symptoms that lead to occupational injury.



The purpose of this brief report is to convey the importance of ergonomic principles in the operating room, specific to laparoscopic surgery and surgeon injury/illness symptoms.