nils-herrmann/clean_scirepeval huggingface dataset:
Parasitic mites of medical and veterinary importance--is there a common research agenda?

There are an estimated 0.5-1 million mite species on earth. Among the many mites that are known to affect humans and animals, only a subset are parasitic but these can cause significant disease. We aim here to provide an overview of the most recent work in this field in order to identify common biological features of these parasites and to inform common strategies for future research. There is a critical need for diagnostic tools to allow for better surveillance and for drugs tailored specifically to the respective parasites. Multi-'omics' approaches represent a logical and timely strategy to identify the appropriate mite molecules. Recent advances in sequencing technology enable us to generate de novo genome sequence data, even from limited DNA resources. Consequently, the field of mite genomics has recently emerged and will now rapidly expand, which is a particular advantage for parasitic mites that cannot be cultured in vitro. Investigations of the microbiota associated with mites will elucidate the link between parasites and pathogens, and define the role of the mite in transmission and pathogenesis. The databases generated will provide the crucial knowledge essential to design novel diagnostic tools, control measures, prophylaxes, drugs and immunotherapies against the mites and associated secondary infections.
Share First, Save Later: Performance of Self through Snapchat Stories

As the third most popular social network among millennials, Snapchat is well known for its picture and video messaging system that deletes content after it is viewed. However, the Stories feature of Snapchat offers a different perspective of ephemeral content sharing, with pictures and videos that are available for friends to watch an unlimited number of times for 24 hours. We conduct-ed an in-depth qualitative investigation by interviewing 18 participants and reviewing 14 days of their Stories posts. We identify five themes focused on how participants perceive and use the Stories feature, and apply a Goffmanesque metaphor to our analysis. We relate the Stories medium to other research on self-presentation and identity curation in social media.
Automated Neural Image Caption Generator for Visually Impaired People

Being able to automatically describe the content of an image using properly formed English sentences is a challenging task, but it could have great impact by helping visually impaired people better understand their surroundings. Most modern mobile phones are able to capture photographs, making it possible for the visually impaired to make images of their environments. These images can then be used to generate captions that can be read out loud to the visually impaired, so that they can get a better sense of what is happening around them. In this paper, we present a deep recurrent architecture that automatically generates brief explanations of images. Our models use a convolutional neural network (CNN) to extract features from an image. These features are then fed into a vanilla recurrent neural network (RNN) or a Long Short-Term Memory (LSTM) network to generate a description of the image in valid English. Our models achieve comparable to state of the art performance, and generate highly descriptive captions that can potentially greatly improve the lives of visually impaired people.
Can Beach Cleans Do More Than Clean-Up Litter? Comparing Beach Cleans to Other Coastal Activities

Coastal visits not only provide psychological benefits but can also contribute to the accumulation of rubbish. Volunteer beach cleans help address this issue, but may only have limited, local impact. Consequently, it is important to study any broader benefits associated with beach cleans. This article examines the well-being and educational value of beach cleans, as well as their impacts on individuals' behavioral intentions. We conducted an experimental study that allocated students (n = 90) to a beach cleaning, rock pooling, or walking activity. All three coastal activities were associated with positive mood and pro-environmental intentions. Beach cleaning and rock pooling were associated with higher marine awareness. The unique impacts of beach cleaning were that they were rated as most meaningful but linked to lower restorativeness ratings of the environment compared with the other activities. This research highlights the interplay between environment and activities, raising questions for future research on the complexities of person-environment interactions.
3D Head Pose Normalization with Face Geometry Analysis, Genetic Algorithms and PCA

In this paper, a software toolchain is presented for the fully automatic alignment of a 3D human face model. Beginning from a point cloud of a human head (previously segmented from its background), pose normalization is obtained using an innovative and purely geometrical approach. In order to solve the six degrees of freedom raised by this problem, we first exploit the human face’s natural mirror symmetry; secondly, we analyze the frontal profile shape; and finally, we align the model’s bounding box according to the position of the tip of the nose. The whole procedure is considered as a two-fold, multivariable optimization problem which is addressed by the use of multi-level, genetic algorithms and a greedy search stage, with the latter being compared against standard PCA. Experiments were conducted utilizing a GavabDB database and took into account proper preprocessing stages for noise filtering and head model reconstruction. Outcome results reveal strong validity in this approach, however, at the price of high computational complexity.
Topical Medical Cannabis: A New Treatment for Wound Pain-Three Cases of Pyoderma Gangrenosum.

Pain associated with integumentary wounds is highly prevalent, yet it remains an area of significant unmet need within health care. Currently, systemically administered opioids are the mainstay of treatment. However, recent publications are casting opioids in a negative light given their high side effect profile, inhibition of wound healing, and association with accidental overdose, incidents that are frequently fatal. Thus, novel analgesic strategies for wound-related pain need to be investigated. The ideal methods of pain relief for wound patients are modalities that are topical, lack systemic side effects, noninvasive, self-administered, and display rapid onset of analgesia. Extracts derived from the cannabis plant have been applied to wounds for thousands of years. The discovery of the human endocannabinoid system and its dominant presence throughout the integumentary system provides a valid and logical scientific platform to consider the use of topical cannabinoids for wounds. We are reporting a prospective case series of three patients with pyoderma gangrenosum that were treated with topical medical cannabis compounded in nongenetically modified organic sunflower oil. Clinically significant analgesia that was associated with reduced opioid utilization was noted in all three cases. Topical medical cannabis has the potential to improve pain management in patients suffering from wounds of all classes.
A mathematic model for relating the drug sensitivity of tumors to their spontaneous mutation rate.

A mathematic model has been developed relating the drug sensitivity of a tumor to its own spontaneous mutation rate towards phenotypic drug resistance. The proportion as well as the absolute numbers of resistant cells will increase with time and the fraction of resistant cells within tumor colonies of the same size with vary depending on whether mutation occurs as an early or late event. Analysis of the model indicates that the probability of the appearance of a resistant phenotype increases with the mutation rate. Furthermore, for any population of tumors with a non-zero mutation rate the likelihood of there being at least one resistant cell will go from a condition of low to high probability over a very short interval in the tumor's biologic history.
Understanding environmental influences on walking; Review and research agenda.

Understanding how environmental attributes can influence particular physical activity behaviors is a public health research priority. Walking is the most common physical activity behavior of adults; environmental innovations may be able to influence rates of participation.



Review of studies on relationships of objectively assessed and perceived environmental attributes with walking. Associations with environmental attributes were examined separately for exercise and recreational walking, walking to get to and from places, and total walking.



Eighteen studies were identified. Aesthetic attributes, convenience of facilities for walking (sidewalks, trails); accessibility of destinations (stores, park, beach); and perceptions about traffic and busy roads were found to be associated with walking for particular purposes. Attributes associated with walking for exercise were different from those associated with walking to get to and from places.



While few studies have examined specific environment-walking relationships, early evidence is promising. Key elements of the research agenda are developing reliable and valid measures of environmental attributes and walking behaviors, determining whether environment-behavior relationships are causal, and developing theoretical models that account for environmental influences and their interactions with other determinants.
Near-Duplicate Video Retrieval with Deep Metric Learning

This work addresses the problem of Near-Duplicate Video Retrieval (NDVR). We propose an effective video-level NDVR scheme based on deep metric learning that leverages Convolutional Neural Network (CNN) features from intermediate layers to generate discriminative global video representations in tandem with a Deep Metric Learning (DML) framework with two fusion variations, trained to approximate an embedding function for accurate distance calculation between two near-duplicate videos. In contrast to most state-of-the-art methods, which exploit information deriving from the same source of data for both development and evaluation (which usually results to dataset-specific solutions), the proposed model is fed during training with sampled triplets generated from an independent dataset and is thoroughly tested on the widely used CC_WEB_VIDEO dataset, using two popular deep CNN architectures (AlexNet, GoogleNet). We demonstrate that the proposed approach achieves outstanding performance against the state-of-the-art, either with or without access to the evaluation dataset.
A role for presynaptic mechanisms in the actions of nomifensine and haloperidol

Psychomotor stimulants and neuroleptics exert multiple effects on dopaminergic signaling and produce the dopamine (DA)-related behaviors of motor activation and catalepsy, respectively. However, a clear relationship between dopaminergic activity and behavior has been very difficult to demonstrate in the awake animal, thus challenging existing notions about the mechanism of these drugs. The present study examined whether the drug-induced behaviors are linked to a presynaptic site of action, the DA transporter (DAT) for psychomotor stimulants and the DA autoreceptor for neuroleptics. Doses of nomifensine (7 mg/kg i.p.), a DA uptake inhibitor, and haloperidol (0.5 mg/kg i.p.), a dopaminergic antagonist, were selected to examine characteristic behavioral patterns for each drug: stimulant-induced motor activation in the case of nomifensine and neuroleptic-induced catalepsy in the case of haloperidol. Presynaptic mechanisms were quantified in situ from extracellular DA dynamics evoked by electrical stimulation and recorded by voltammetry in the freely moving animal. In the first experiment, the maximal concentration of electrically evoked DA ([DA](max)) measured in the caudate-putamen was found to reflect the local, instantaneous change in presynaptic DAT or DA autoreceptor activity according to the ascribed action of the drug injected. A positive temporal association was found between [DA](max) and motor activation following nomifensine (r=0.99) and a negative correlation was found between [DA](max) and catalepsy following haloperidol (r=-0.96) in the second experiment. Taken together, the results suggest that a dopaminergic presynaptic site is a target of systemically applied psychomotor stimulants and regulates the postsynaptic action of neuroleptics during behavior. This finding was made possible by a voltammetric microprobe with millisecond temporal resolution and its use in the awake animal to assess release and uptake, two key mechanisms of dopaminergic neurotransmission. Moreover, the results indicate that presynaptic mechanisms may play a more important role in DA-behavior relationships than is currently thought.
Sex, attachment, and the development of reproductive strategies.

This target article presents an integrated evolutionary model of the development of attachment and human reproductive strategies. It is argued that sex differences in attachment emerge in middle childhood, have adaptive significance in both children and adults, and are part of sex-specific life history strategies. Early psychosocial stress and insecure attachment act as cues of environmental risk, and tend to switch development towards reproductive strategies favoring current reproduction and higher mating effort. However, due to sex differences in life history trade-offs between mating and parenting, insecure males tend to adopt avoidant strategies, whereas insecure females tend to adopt anxious/ambivalent strategies, which maximize investment from kin and mates. Females are expected to shift to avoidant patterns when environmental risk is more severe. Avoidant and ambivalent attachment patterns also have different adaptive values for boys and girls, in the context of same-sex competition in the peer group: in particular, the competitive and aggressive traits related to avoidant attachment can be favored as a status-seeking strategy for males. Finally, adrenarche is proposed as the endocrine mechanism underlying the reorganization of attachment in middle childhood, and the implications for the relationship between attachment and sexual development are explored. Sex differences in the development of attachment can be fruitfully integrated within the broader framework of adaptive plasticity in life history strategies, thus contributing to a coherent evolutionary theory of human development.
Design and Research on Private Cloud Computing Architecture to Support Smart Grid

In recent years, State Grid Corporation of China has been vigorously promoting smart grid construction, and cloud computing is developing rapidly. Trend of the electric power enterprise informatization construction will be the private cloud computing, which will become the comprehensive platform of smart grid. Comparing private cloud with public cloud, this paper lists differences between them and puts forward an architecture of private cloud computing to support smart gird, expounds structure of each layer, and presents concept of private cloud computing operating system and network virtualization. It provides the theoretical reference to build the private cloud computing, thus promotes the construction of the smart grid.
Personal PIN Leakage from Wearable Devices

The proliferation of wearable devices, e.g., smartwatches and activity trackers, with embedded sensors has already shown its great potential on monitoring and inferring human daily activities. This paper reveals a serious security breach of wearable devices in the context of divulging secret information (i.e., key entries) while people are accessing key-based security systems. Existing methods of obtaining such secret information rely on installations of dedicated hardware (e.g., video camera or fake keypad), or training with labeled data from body sensors, which restrict use cases in practical adversary scenarios. In this work, we show that a wearable device can be exploited to discriminate mm-level distances and directions of the user’s fine-grained hand movements, which enable attackers to reproduce the trajectories of the user’s hand and further to recover the secret key entries. In particular, our system confirms the possibility of using embedded sensors in wearable devices, i.e., accelerometers, gyroscopes, and magnetometers, to derive the moving distance of the user’s hand between consecutive key entries regardless of the pose of the hand. Our Backward PIN-Sequence Inference algorithm exploits the inherent physical constraints between key entries to infer the complete user key entry sequence. Extensive experiments are conducted with over 7,000 key entry traces collected from 20 adults for key-based security systems (i.e., ATM keypads and regular keyboards) through testing on different kinds of wearables. Results demonstrate that such a technique can achieve 80 percent accuracy with only one try and more than 90 percent accuracy with three tries. Moreover, the performance of our system is consistently good even under low sampling rate and when inferring long PIN sequences. To the best of our knowledge, this is the first technique that reveals personal PINs leveraging wearable devices without the need for labeled training data and contextual information.
A VNF-as-a-service design through micro-services disassembling the IMS

With the evolution of Telco systems towards 5G, new requirements emerge for delivering services. Network services are expected to be designed to allow greater flexibility. In order to cope with the new users' requirements, Telcos should rethink their complex and monolithic network architectures into more agile architectures. Adoption of NFV as well as micro-services patterns are opportunities promising such an evolution. However, to gain in flexibility, it is crucial to satisfy structural requirements for the design of VNFs as services. We present in this paper an approach for designing VNF-asa-Service. With this approach, we define design requirements for the service architecture and the service logic of VNFs. As Telcos have adopted IMS as the de facto platform for service delivery in 3G and even 4G systems, it is interesting to study its evolution for 5G towards a microservices-based architecture with an optimal design. Therefore, we consider IMS as a case of study to illustrate the proposed approach. We present new functional entities for IMS-as-a-Service through a functional decomposition of legacy network functions. We have developed and implemented IMS-as-a-Service with respect to the proposed requirements. We consider a service scenario where we focus on authentication and authorization procedures. We evaluate the involved microservices comparing to the state-of-the-art. Finally, we discuss our results and highlight the advantages of our approach.
A Multilingual Datasets Repository of the Hadith Content

Knowledge extraction from unstructured data is a challenging research problem in research domain of Natural Language Processing (NLP). It requires complex NLP tasks like entity extraction and Information Extraction (IE), but one of the most challenging tasks is to extract all the required entities of data in the form of structured format so that data analysis can be applied. Our focus is to explain how the data is extracted in the form of datasets or conventional database so that further text and data analysis can be carried out. This paper presents a framework for Hadith data extraction from the Hadith authentic sources. Hadith is the collection of sayings of Holy Prophet Muhammad, who is the last holy prophet according to Islamic teachings. This paper discusses the preparation of the dataset repository and highlights issues in the relevant research domain. The research problem and their solutions of data extraction, preprocessing and data analysis are elaborated. The results have been evaluated using the standard performance evaluation measures. The dataset is available in multiple languages, multiple formats and is available free of cost for research purposes. Data extraction; preprocessing; regex; Hadith; text analysis;
Covert Communications Versus Physical Layer Security

This letter studies and compares the physical-layer security approach and the covert communication approach for a wiretap channel with a transmitter, an intended receiver and an eavesdropper. In order to make the comparison, we investigate the power allocation problems for maximizing the secrecy/covert rate subject to the transmit power constraint. Simulation results illustrate that if the eavesdropper is not noisy or it is near to the transmitter, covert communication is more preferable.
The Internet of Things (IoT): A Study of Architectural Elements

The Internet of Things(IoT) is a technology which is currently emerging and it can be viewed as a network of objects connected via. Internet, which aims to increase the availability of Internet at anyplace and any time(the state or capacity of being everywhere, especially at the same time) through integration of the physical objects (embedded with software, sensors, actuators etc.) into the information network which enables these objects to collect data and exchange it. IoT paradigm when applied to Cultural Heritage (CH) encompasses a very wide range of technologies, hence a single reference architecture won't be enough for all possible implementations. IoT's basic model is a 5-layered architecture comprising of Business, Application, Service Management, Object Abstraction and Objects layers. With the evident fact that IoT is still in its formative stages, the main objective of this paper is to reflect that the IoT architecture is growing in an evolutionary fashion. An area of overlap exists between several reference architectures and this study of 5-layer model shows how architecture in this context means a framework for the specifications of physical objects, their organization, communication principles, operational methods and data formats used in their operations. This model provides a definitive goal for rethinking CH in terms of sustainability along with development of new activities that generate economic returns.