nils-herrmann/clean_scirepeval huggingface dataset:
Enzyme-assisted extraction of flavorings and colorants from plant materials.

From times immemorial, colorants, and flavorings have been used in foods. Color and flavor are the major attributes to the quality of a food product, affecting the appearance and acceptance of the product. As a consequence of the increased demand of natural flavoring and colorant from industries, there is a renewed interest in the research on the composition and recovery of natural food flavors and colors. Over the years, numerous procedures have been proposed for the isolation of aromatic compounds and colors from plant materials. Generally, the methods of extraction followed for aroma and pigment from plant materials are solvent extraction, hydro-distillation, steam distillation, and super critical carbon dioxide extraction. The application of enzymes in the extraction of oil from oil seeds like sunflower, corn, coconut, olives, avocado etc. are reported in literature. There is a great potential for this enzyme-based extraction technology with the selection of appropriate enzymes with optimized operating conditions. Various enzyme combinations are used to loosen the structural integrity of botanical material thereby enhancing the extraction of the desired flavor and color components. Recently enzymes have been used for the extraction of flavor and color from plant materials, as a pre-treatment of the raw material before subjecting the plant material to hydro distillation/solvent extraction. A deep knowledge of enzymes, their mode of action, conditions for optimum activity, and selection of the right type of enzymes are essential to use them effectively for extraction. Although the enzyme hydrolases such as lipases, proteases (chymotrypsin, subtilisin, thermolysin, and papain), esterases use water as a substrate for the reaction, they are also able to accept other nucleophiles such as alcohols, amines, thio-esters, and oximes. Advantages of enzyme-assisted extraction of flavor and color in some of the plant materials in comparison with conventional methods are dealt with in this reveiw.
Region-Based Quality Estimation Network for Large-Scale Person Re-Identification

One of the major restrictions on the performance of videobased person re-id is partial noise caused by occlusion, blur and illumination. Since different spatial regions of a single frame have various quality, and the quality of the same region also varies across frames in a tracklet, a good way to address the problem is to effectively aggregate complementary information from all frames in a sequence, using better regions from other frames to compensate the influence of an image region with poor quality. To achieve this, we propose a novel Region-based Quality Estimation Network (RQEN), in which an ingenious training mechanism enables the effective learning to extract the complementary region-based information between different frames. Compared with other feature extraction methods, we achieved comparable results of 92.4%, 76.1% and 77.83% on the PRID 2011, iLIDS-VID and MARS, respectively. In addition, to alleviate the lack of clean large-scale person re-id datasets for the community, this paper also contributes a new high-quality dataset, named “Labeled Pedestrian in the Wild (LPW)” which contains 7,694 tracklets with over 590,000 images. Despite its relatively large scale, the annotations also possess high cleanliness. Moreover, it’s more challenging in the following aspects: the age of characters varies from childhood to elderhood; the postures of people are diverse, including running and cycling in addition to the normal walking state.
Systematic Error Analysis of the Stanford Question Answering Dataset

We analyzed the outputs of multiple question answering (QA) models applied to the Stanford Question Answering Dataset (SQuAD) to identify the core challenges for QA systems on this data set. Through an iterative process, challenging aspects were hypothesized through qualitative analysis of the common error cases. A classifier was then constructed to predict whether SQuAD test examples were likely to be difficult for systems to answer based on features associated with the hypothesized aspects. The classifier’s performance was used to accept or reject each aspect as an indicator of difficulty. With this approach, we ensured that our hypotheses were systematically tested and not simply accepted based on our pre-existing biases. Our explanations are not accepted based on human evaluation of individual examples. This process also enabled us to identify the primary QA strategy learned by the models, i.e., systems determined the acceptable answer type for a question and then selected the acceptable answer span of that type containing the highest density of words present in the question within its local vicinity in the passage.
Facial Action Coding System

The Facial Action Coding System (FACS) is a widely used protocol for recognizing and labelling facial expression by describing the movement of muscles of the face. FACS is used to objectively measure the frequency and intensity of facial expressions without assigning any emotional meaning to those muscle movements. Instead FACS breaks down facial expressions into their smallest discriminable movements called Action Units. Each Action Unit creates a distinct change in facial appearance, such as an eyebrow lift or nose wrinkle. FACS coders can identify the Action Units which are present on the face when viewing still images or videos. Psychological research has used FACS to examine a variety of research questions including social-emotional development, neuropsychiatric disorders, and deception. In the course of this report we provide an overview of FACS and the Action Units, its reliability as a measure, and how it has been applied in some key areas of psychological research.
Concept Hierarchy Extraction from Textbooks

Concept hierarchies have been useful tools for presenting and organizing knowledge. With the rapid growth in the number of online knowledge resources, automatic concept hierarchy extraction is increasingly attractive. Here, we focus on concept extraction from textbooks based on the knowledge in Wikipedia. Given a book, we extract important concepts in each book chapter using Wikipedia as a resource and from this construct a concept hierarchy for that book. We define local and global features that capture both the local relatedness and global coherence embedded in that textbook. In order to evaluate the proposed features and extracted concept hierarchies, we manually construct concept hierarchies for three well used textbooks by labeling important concepts for each book chapter. Experiments show that our proposed local and global features achieve better performance than using only keyphrases to construct the concept hierarchies. Moreover, we observe that incorporating global features can improve the concept ranking precision and reaffirms the global coherence in the book.
Social Isolation and Loneliness in Old Age : Review and Model Refinement

This paper reviews the empirical literature on social isolation and loneliness and identifies a wide range of published correlates. Using data from a study conducted in North Wales, which included many of the same correlated variables, a statistical modelling technique is used to refine models of isolation and loneliness by controlling for co-variance. The resulting models indicate that the critical factors for isolation are: marital status, network type and social class; and, for loneliness: network type, household composition and health.
Social news, citizen journalism and democracy

This article aims to contribute to a critical research agenda for investigating the democratic implications of citizen journalism and social news. The article calls for a broad conception of ‘citizen journalism’ which is (1) not an exclusively online phenomenon, (2) not confined to explicitly ‘alternative’ news sources, and (3) includes ‘metajournalism’ as well as the practices of journalism itself. A case is made for seeing democratic implications not simply in the horizontal or ‘peer-to-peer’ public sphere of citizen journalism networks, but also in the possibility of a more ‘reflexive’ culture of news consumption through citizen participation. The article calls for a research agenda that investigates new forms of gatekeeping and agendasetting power within social news and citizen journalism networks and, drawing on the example of three sites, highlights the importance of both formal and informal status differentials and of the software ‘code’ structuring these new modes of news
Pet in the therapy room: an attachment perspective on Animal-Assisted Therapy.

John Bowlby's ( 1973, 1980, 1982) attachment theory is one of the most influential theories in personality and developmental psychology and provides insights into adjustment and psychopathology across the lifespan. The theory is also helpful in defining the target of change in psychotherapy, understanding the processes by which change occurs, and conceptualizing cases and planning treatment (Daniel, 2006; Obegi & Berant, 2008; Sable, 2004 ; Wallin, 2007). Here, we propose a model of Animal-Assisted Therapy (AAT) based on attachment theory and on the unique characteristics of human-pet relationships. The model includes clients' unmet attachment needs, individual differences in attachment insecurity, coping, and responsiveness to therapy. It also suggests ways to foster the development of more adaptive patterns of attachment and healthier modes of relating to others.
Defend Deep Neural Networks Against Adversarial Examples via Fixed andDynamic Quantized Activation Functions

Recent studies have shown that deep neural networks (DNNs) are vulnerable to adversarial attacks. To this end, many defense approaches that attempt to improve the robustness of DNNs have been proposed. In a separate and yet related area, recent works have explored to quantize neural network weights and activation functions into low bit-width to compress model size and reduce computational complexity. In this work, we find that these two different tracks, namely the pursuit of network compactness and robustness, can be merged into one and give rise to networks of both advantages. To the best of our knowledge, this is the first work that uses quantization of activation functions to defend against adversarial examples. We also propose to train robust neural networks by using adaptive quantization techniques for the activation functions. Our proposed Dynamic Quantized Activation (DQA) is verified through a wide range of experiments with the MNIST and CIFAR-10 datasets under different white-box attack methods, including FGSM, PGD, and C&W attacks. Furthermore, Zeroth Order Optimization and substitute model based black-box attacks are also considered in this work. The experimental results clearly show that the robustness of DNNs could be greatly improved using the proposed DQA.
Temporomandibular disorders. Part 2: conservative management.

Appropriate management of temporomandibular disorders (TMD) requires an understanding of the underlying dysfunction associated with the temporomandibular joint (TMJ) and surrounding structures. A comprehensive examination process, as described in part 1 of this series, can reveal underlying clinical findings that assist in the delivery of comprehensive physical therapy services for patients with TMD. Part 2 of this series focuses on management strategies for TMD. Physical therapy is the preferred conservative management approach for TMD. Physical therapists are professionally well-positioned to step into the void and provide clinical services for patients with TMD. Clinicians should utilize examination findings to design rehabilitation programs that focus on addressing patient-specific impairments. Potentially appropriate plan of care components include joint and soft tissue mobilization, trigger point dry needling, friction massage, therapeutic exercise, patient education, modalities, and outside referral. Management options should address both symptom reduction and oral function. Satisfactory results can often be achieved when management focuses on patient-specific clinical variables.
Infrastructure Cost Comparison of Running Web Applications in the Cloud Using AWS Lambda and Monolithic and Microservice Architectures

Large Internet companies like Amazon, Netflix, and LinkedIn are using the microservice architecture pattern to deploy large applications in the cloud as a set of small services that can be developed, tested, deployed, scaled, operated and upgraded independently. However, aside from gaining agility, independent development, and scalability, infrastructure costs are a major concern for companies adopting this pattern. This paper presents a cost comparison of a web application developed and deployed using the same scalable scenarios with three different approaches: 1) a monolithic architecture, 2) a microservice architecture operated by the cloud customer, and 3) a microservice architecture operated by the cloud provider. Test results show that microservices can help reduce infrastructure costs in comparison to standard monolithic architectures. Moreover, the use of services specifically designed to deploy and scale microservices reduces infrastructure costs by 70% or more. Lastly, we also describe the challenges we faced while implementing and deploying microservice applications.
An Enhanced Security for Government Base on Multifactor Biometric Authentication

This paper is demonstrating to create a system of multifactor authentication based on biometric verification. Our system use iris for the first factor and fingerprint for the second factor. Once an attacker attempts to attack the system, there must have two factors. If one of them is compromised or broken, the attacker still has at least one more barrier to breach before successfully breaking into the target. Furthermore, this system will be implemented to enhance security for accessing control login government system.
ACS Surgery: Principles and Practice

Historically, the control of wound infection depended on antiseptic and aseptic techniques directed at coping with the infecting organism. In the 19th century and the early part of the 20th century, wound infections had devastating consequences and a measurable mortality. Even in the 1960s, before the correct use of antibiotics and the advent of modern preoperative and postoperative care, as much as one quarter of a surgical ward might have been occupied by patients with wound complications. As a result, wound management, in itself, became an important component of ward care and of medical education. It is fortunate that many factors have intervened so that the so-called wound rounds have become a practice of the past.The epidemiology of wound infection has changed as surgeons have learned to control bacteria and the inoculum as well as to focus increasingly on the patient (the host) for measures that will continue to provide improved results. The following three factors are the determinants of any infectious process:
Antennas in Cellular Phones for Mobile Communications

The mobile industry has experienced a dramatic growth; it evolves from analog to digital 2G (GSM), then to high date rate cellular wireless communication such as 3G (WCDMA), and further to packet optimized 3.5G (HSPA) and 4G (LTE and LTE advanced) systems. Today, the main design challenges of mobile phone antenna are the requirements of small size, built-in structure, and multisystems in multibands, including all cellular 2G, 3G, 4G, and other noncellular radio-frequency (RF) bands, and moreover the need for a nice appearance and meeting all standards and requirements such as specific absorption rates (SARs), hearing aid compatibility (HAC), and over the air (OTA). This paper gives an overview of some important antenna designs and progress in mobile phones in the last 15 years, and presents the recent development on new antenna technology for LTE and compact multiple-input-multiple-output (MIMO) terminals.
The Pleasure Principle as a Tool for Scientific Forecasting of Human Self-Evolution

The pleasure principle (PP) may be a verifiable fundamental law of the living matter in the universe, and this law might then be used for forecasting human self-evolution. I do not pretend to “prove” PP, but argue that it must be regarded as a scientific hypothesis. Accordingly, I formulate verifiable and falsifiable postulates of PP. Their confirmation would allow the construction of a new scientific discipline, hedodynamics, that would be able to forecast the future development of human civilization and even the probable structure and psychology of other rational beings within the universe. I suggest basic hedodynamical scenarios for human (posthuman) civilization and argue that the discovery of the neural correlate of pleasure would provide more detailed forecasts. In particular, I demonstrate how the studies of pleasure mechanisms might predict the degree of aggression in future societies. I conclude that PP may become a scientific basis for fundamental, not phenomenological (based on extrapolations), future forecasting on large timescales.
The Sedona Effect : Correlations between Geomagnetic Anomalies , EEG Brainwaves & Schumann Resonance

Evidence of Sedona magnetic anomaly and brainwave EEG synchronization can be demonstrated with portable equipment on site in the field, during sudden magnetic events. Previously, we have demonstrated magnetic anomaly charts recorded in both known and unrecognized Sedona vortex activity locations. We have also shown a correlation or amplification of vortex phenomena with Schumann Resonance. Adding the third measurable parameter of brain wave activity, we demonstrate resonance and amplification among them. We suggest tiny magnetic crystals, biogenic magnetite, make human beings highly sensitive to ELF field fluctuations. Biological Magnetite could act as a transducer of both low frequency magnetic fields and RF fields.
Preliminary mechanical design of NU-Wrist: A 3-DOF self-aligning Wrist rehabilitation robot

The use of robotics in rehabilitation area provides a quantifying outcomes on treatment of after stroke patients. This paper presents the preliminary design of a novel exoskeleton robot, called NU-Wrist, for human wrist and forearm rehabilitation. The proposed robot design provides rotation within the anatomical range of human wrist and forearm motions. A novel compliant robot handle link ensures dynamic passive self-alignment of human-robot axes during therapy exercising. The proof-of-concept wrist robot prototype has been manufactured using 3D printing technology for experimental design evaluation. It is shown the proposed NU-Wrist robot design is satisfied to the specified rehabilitation system requirements.
Story and Narrative Structures in Computer Games 1

Computer games can involve narrative and story elements integrating different forms of interactivity and using different strategies for combining interaction with non-interactive story and narrative elements. While some forms of interactive narrative involve simple selection between fixed narrative sequences, computer games more typically involve the integration of narrative with game play based upon a simulation substrate. These three forms, simulation, game play and narrative, involve pre-authored time structures at different levels of time scale. Simulation involves the lowest levels of time structure, with authored principles specifying how time develops from frame to frame based upon physics, the representation of game objects and their behaviour, and discrete event simulation. Games involve pre-designed game moves, types of actions that may be realized as abstractions over patterns of low level changes at the frame level. Linear and interactive narratives form the highest level of predesigned time structure, framing low-level simulation processes and intermediate level game moves within a high level structure typically based upon classic models of narrative form. Computer games may emphasise one or more of these primary forms as the focus of meaning in the play experience. Story construction within computer games is a function of how these different levels of time structure interact in the play experience, being the result of pre-designed narrative content, story potential and the actual unfolding story created by the actions of the player. There are many strategies for integrating these forms. However, a crucial issue in the design of story content is the relationship between how the resulting game experience relates to user play preferences. In particular, categories of play style can be extended to include preferences for how story content is experienced, based upon audience, performance and immersionist orientations to story. Perceived tensions within computer game form, such as the tension between game play and narrative, are explained, not as fundamental formal issues, but issues of player preferences and how these are satisfied or not by different strategies for story content within a game system.
Emergent Logical Structure in Vector Representations of Neural Readers

Reading comprehension is a question answering task where the answer is to be found in a given passage about entities and events not mentioned in general knowledge sources. A significant number of neural architectures for this task (neural readers) have recently been developed and evaluated on large cloze-style datasets. We present experiments supporting the existence of logical structure in the hidden state vectors of “aggregation readers” such as the Attentive Reader and Stanford Reader. The logical structure of aggregation readers reflects the architecture of “explicit reference readers” such as the Attention-Sum Reader, the GatedAttention Reader and the Attention-over-Attention Reader. This relationship between aggregation readers and explicit reference readers presents a case study in emergent logical structure. In an independent contribution, we show that the addition of linguistics features to the input to existing neural readers significantly boosts performance yielding the best results to date on Who-did-What datasets1.