nils-herrmann/clean_scirepeval huggingface dataset:
Administration-route and gender-independent long-term therapeutic correction of phenylketonuria (PKU) in a mouse model by recombinant adeno-associated virus 8 pseudotyped vector-mediated gene transfer

Phenylketonuria (PKU) is an inborn error of metabolism caused by deficiency of the hepatic enzyme phenylalanine hydroxylase (PAH) which leads to high blood phenylalanine (Phe) levels and consequent damage of the developing brain with severe mental retardation if left untreated in early infancy. The current dietary Phe restriction treatment has certain clinical limitations. To explore a long-term nondietary restriction treatment, a somatic gene transfer approach in a PKU mouse model (C57Bl/6-Pahenu2) was employed to examine its preclinical feasibility. A recombinant adeno-associated virus (rAAV) vector containing the murine Pah-cDNA was generated, pseudotyped with capsids from AAV serotype 8, and delivered into the liver of PKU mice via single intraportal or tail vein injections. The blood Phe concentrations decreased to normal levels (⩽100 μM or 1.7 mg/dl) 2 weeks after vector application, independent of the sex of the PKU animals and the route of application. In particular, the therapeutic long-term correction in females was also dramatic, which had previously been shown to be difficult to achieve. Therapeutic ranges of Phe were accompanied by the phenotypic reversion from brown to black hair. In treated mice, PAH enzyme activity in whole liver extracts reversed to normal and neither hepatic toxicity nor immunogenicity was observed. In contrast, a lentiviral vector expressing the murine Pah-cDNA, delivered via intraportal vein injection into PKU mice, did not result in therapeutic levels of blood Phe. This study demonstrates the complete correction of hyperphenylalaninemia in both males and females with a rAAV serotype 8 vector. More importantly, the feasibility of a single intravenous injection may pave the way to develop a clinical gene therapy procedure for PKU patients.
Modelling Slotted-ALOHA Simulator Using Computational Spreadsheet Based e-Forms

This paper demonstrates models that were designed and implemented to simulate slotted ALOHA multiple access computer network protocol. The models are spreadsheet-based simulating e-forms that were designed for students use in college level data communication and networking courses. Specifically, three models for simulating this protocol are fully implemented using spreadsheets. The features of these models are simplicity and quickness of implementation compared with other implementation techniques. These models assisted instructors to develop educational objects that in turn will help students for better understanding and exploring of the scientific concepts related to computer protocols by the aid of visual and interactive spreadsheet-based e-forms. Moreover, advanced spreadsheet techniques such as imagery integration, hyperlinks, conditional structures, conditional formats, and charts insetting, to simulate scientific notions that are taught to undergraduate students were exploited in these models. The models designing technique is characterized by simplicity, flexibility, and affordability. The technique can be applied and used in many disciplines of education, business, science, and technology. Generally, the developed computational e-forms can be used by instructors to illustrate topics in attractive fashions. In addition, students and learners can use the developed educational objects without instructor supervision in self-education or e-learning environments.
Automatic visual tracking and firing system for anti aircraft machine gun

Visual tracking is one of the most important field of computer vision. It has immense number of applications ranging from surveillance to hi-fi military applications. This paper is based on the application developed for automatic visual tracking and fire control system for anti-aircraft machine gun (AAMG). Our system mainly consists of camera, as visual sensor; mounted on a 2D-moving platform attached with 2GHz embedded system through RS-232 and AAMG mounted on the same moving platform. Camera and AAMG are both bore-sighted. Correlation based template matching algorithm has been used for automatic visual tracking. This is the algorithm used in civilian and military automatic target recognition, surveillance and tracking systems. The algorithm does not give robust performance in different environments, especially in clutter and obscured background, during tracking. So, motion and prediction algorithms have been integrated with it to achieve robustness and better performance for real-time tracking. Visual tracking is also used to calculate lead angle, which is a vital component of such fire control systems. Lead is angular correction needed to compensate for the target motion during the time of flight of the projectile, to accurately hit the target. Although at present lead computation is not robust due to some limitation as lead calculation mostly relies on gunner intuition. Even then by the integrated implementation of lead angle with visual tracking and control algorithm for moving platform, we have been able to develop a system which detects tracks and destroys the target of interest.
Power MOSFET Basics : Understanding MOSFET Characteristics Associated With The Figure of Merit

Power MOSFETs have become the standard choice as the main switching device for low-voltage (<200 V) switchmode power-supply (SMPS) converter applications. However using manufacturers’ datasheets to choose or size the correct device for a specific circuit topology is becoming increasingly difficult. The main criteria for MOSFET selection are the power loss associated with the MOSFET (related to the overall efficiency of the SMPS) and the power-dissipation capability of the MOSFET (related to the maximum junction temperature and thermal performance of the package). This application note focuses on the basic characteristics and understanding of the MOSFET.
Control Improvisation with Application to Music

We introduce the concept of control improvisation, the process of generating a random sequence of control events guided by a reference sequence and satisfying a given specification. We propose a formal definition of the control improvisation problem and an empirical solution applied to the domain of music. More specifically, we consider the scenario of generating a monophonic Jazz melody (solo) on a given song harmonization. The music is encoded symbolically, with the improviser generating a sequence of note symbols comprising pairs of pitches (frequencies) and discrete durations. Our approach can be decomposed roughly into two phases: a generalization phase, that learns from a training sequence (e.g., obtained from a human improviser) an automaton generating similar sequences, and a supervision phase that enforces a specification on the generated sequence, imposing constraints on the music in both the pitch and rhythmic domains. The supervision uses a measure adapted from Normalized Compression Distances (NCD) to estimate the divergence between generated melodies and the training melody and employs strategies to bound this divergence. An empirical evaluation is presented on a sample set of Jazz music.
Extreme learning machine and its applications

Recently, a novel learning algorithm for single-hidden-layer feedforward neural networks (SLFNs) named extreme learning machine (ELM) was proposed by Huang et al. The essence of ELM is that the learning parameters of hidden nodes, including input weights and biases, are randomly assigned and need not be tuned while the output weights can be analytically determined by the simple generalized inverse operation. The only parameter needed to be defined is the number of hidden nodes. Compared with other traditional learning algorithms for SLFNs, ELM provides extremely faster learning speed, better generalization performance and with least human intervention. This paper firstly introduces a brief review of ELM, describing the principle and algorithm of ELM. Then, we put emphasis on the improved methods or the typical variants of ELM, especially on incremental ELM, pruning ELM, error-minimized ELM, two-stage ELM, online sequential ELM, evolutionary ELM, voting-based ELM, ordinal ELM, fully complex ELM, and symmetric ELM. Next, the paper summarized the applications of ELM on classification, regression, function approximation, pattern recognition, forecasting and diagnosis, and so on. In the last, the paper discussed several open issues of ELM, which may be worthy of exploring in the future.
Acceleration induced head injury in the monkey.I. The model, its mechanical and physiological correlates.

A system has been developed which is capable of inducing brain injuries of graded severity from mild concussion to instantaneous death. A pneumatic shock tester subjects a monkey to a non-impact controlled single sagittal rotation which displaces the head 60 degrees in 10-20 msec. Results derived from 53 experiments show that a good correlation exists between acceleration delivered to the head, the resultant neurological status and the brain pathology. A simple experimental trauma severity (ETS) scale is offered based on changes in the heart rate, respiratory rate, corneal reflex and survivability. ETS grades 1 and 2 show heart rate or respiratory changes but no behavioral or pathological abnormality. ETS grades 3 and 4 have temporary corneal reflex abolition, behavioral unconsciousness, and post-traumatic behavioral abnormalities. Occasional subdural haematomas are seen. Larger forces cause death (ETS 5) from primary apnea or from large subdural haematomas. At the extreme range, instantaneous death (ETS 6) occurs because of pontomedullary lacerations. This model and the ETS scale offer the ability to study a broad spectrum of types of experimental head injury and underscore the importance of angular acceleration as a mechanism of head injury.
Project management and IT governance. Integrating PRINCE2 and ISO 38500

IT governance is becoming a critical area for the improvement and business continuity in organizations. The value of the services, as a product of IT projects, must be improved. A good definition of IT projects, according to business needs, helps to improve product value. For this purpose, some frameworks and standards have been developed by internationally recognized institutions. Among them project management framework “PRINCE2” and the IT governance standard ISO/IEC 38500 are highlighted. The application of these frameworks and standards has meant figures have improved, but they are far from covering the expectations of organizations. A IT project approach that integrates the needs of business and technology that supports it is a key to achieve the expected success for IT projects in organizations. This paper presents a summary of the study performed to find out how PRINCE2 meets the expectations of IT governance according to ISO/IEC 38500. The study could help knowing and improving and expectations of success in PRINCE 2 projects.
Advanced manufacturing equipment: a vertical batch furnace for 300-mm wafer processing

Industry analysts expect volume production of integrated circuits on 300-mm wafers to start in 2001 or 2002. At that time, appropriate production equipment must be available. To meet this need, the MEDEA Project has supported us at ASM Europe in developing an advanced vertical batch furnace system for 300-mm wafers. Vertical furnaces are widely used for many steps in the production of integrated circuits. In volume production, these batch furnaces achieve a lower cost per production step than single-wafer processing methods. Applications for vertical furnaces are extensive, including the processing of low-pressure chemical vapor deposition (LPCVD) layers such as deposited oxides, polysilicon, and nitride. Furthermore, the furnaces can be used for oxidation and annealing treatments. As the complexity of IC technology increases, production equipment must meet the technology guidelines summarized in Table 1 from the Semiconductor Industry Association’s Roadmap. The table shows that the minimal feature size will sharply decrease, and likewise the particle size and level will decrease. The challenge in designing a new generation of furnaces for 300-mm wafers was to improve productivity as measured in throughput (number of wafers processed per hour), clean-room footprint, and capital cost. Therefore, we created a completely new design rather than simply upscaling the existing 200mm equipment.
LECTOR: a technique for leakage reduction in CMOS circuits

In CMOS circuits, the reduction of the threshold voltage due to voltage scaling leads to increase in subthreshold leakage current and hence static power dissipation. We propose a novel technique called LECTOR for designing CMOS gates which significantly cuts down the leakage current without increasing the dynamic power dissipation. In the proposed technique, we introduce two leakage control transistors (a p-type and a n-type) within the logic gate for which the gate terminal of each leakage control transistor (LCT) is controlled by the source of the other. In this arrangement, one of the LCTs is always "near its cutoff voltage" for any input combination. This increases the resistance of the path from V/sub dd/ to ground, leading to significant decrease in leakage currents. The gate-level netlist of the given circuit is first converted into a static CMOS complex gate implementation and then LCTs are introduced to obtain a leakage-controlled circuit. The significant feature of LECTOR is that it works effectively in both active and idle states of the circuit, resulting in better leakage reduction compared to other techniques. Further, the proposed technique overcomes the limitations posed by other existing methods for leakage reduction. Experimental results indicate an average leakage reduction of 79.4% for MCNC'91 benchmark circuits.
Adaptive encrypted traffic fingerprinting with bi-directional dependence

Recently, network traffic analysis has been increasingly used in various applications including security, targeted advertisements, and network management. However, data encryption performed on network traffic poses a challenge to these analysis techniques. In this paper, we present a novel method to extract characteristics from encrypted traffic by utilizing data dependencies that occur over sequential transmissions of network packets. Furthermore, we explore the temporal nature of encrypted traffic and introduce an adaptive model that considers changes in data content over time. We evaluate our analysis on two packet encrypted applications: website fingerprinting and mobile application (app) fingerprinting. Our evaluation shows how the proposed approach outperforms previous works especially in the open-world scenario and when defense mechanisms are considered.
Semantic Tagging of Mathematical Expressions

Semantic tagging of mathematical expressions (STME) gives semantic meanings to tokens in mathematical expressions. In this work, we propose a novel STME approach that relies on neither text along with expressions, nor labelled training data. Instead, our method only requires a mathematical grammar set. We point out that, besides the grammar of mathematics, the special property of variables and user habits of writing expressions help us understand the implicit intents of the user. We build a system that considers both restrictions from the grammar and variable properties, and then apply an unsupervised method to our probabilistic model to learn the user habits. To evaluate our system, we build large-scale training and test datasets automatically from a public math forum. The results demonstrate the significant improvement of our method, compared to the maximum-frequency baseline. We also create statistics to reveal the properties of mathematics language.
An Experiment on "Free Generation" from Single RDF Triples

This paper introduces our domain independent approach to “free generation” from single RDF triples without using any domain dependent knowledge. Our approach is developed based on our argument that RDF representations carry rich linguistic information, which can be used to achieve readable domain independent generation. In order to examine to what extent our argument is realistic, we carry out an evaluation experiment, which is the first evaluation of this kind of domain independent generation in the field.
Attention and Localization based on a Deep Convolutional Recurrent Model for Weakly Supervised Audio Tagging

Audio tagging aims to perform multi-label classification on audio chunks and it is a newly proposed task in the Detection and Classification of Acoustic Scenes and Events 2016 (DCASE 2016) challenge. This task encourages research efforts to better analyze and understand the content of the huge amounts of audio data on the web. The difficulty in audio tagging is that it only has a chunk-level label without a frame-level label. This paper presents a weakly supervised method to not only predict the tags but also indicate the temporal locations of the occurred acoustic events. The attention scheme is found to be effective in identifying the important frames while ignoring the unrelated frames. The proposed framework is a deep convolutional recurrent model with two auxiliary modules: an attention module and a localization module. The proposed algorithm was evaluated on the Task 4 of DCASE 2016 challenge. State-of-the-art performance was achieved on the evaluation set with equal error rate (EER) reduced from 0.13 to 0.11, compared with the convolutional recurrent baseline system.
i FEM : AN INNOVATIVE FINITE ELEMENT METHOD PACKAGE IN MATLAB

Sparse matrixlization, an innovative programming style for MATLAB, is introduced and used to develop an efficient software package, iFEM, on adaptive finite element methods. In this novel coding style, the sparse matrix and its operation is used extensively in the data structure and algorithms. Our main algorithms are written in one page long with compact data structure following the style “Ten digit, five seconds, and one page” proposed by Trefethen. The resulting code is simple, readable, and efficient. A unique strength of iFEM is the ability to perform three dimensional local mesh refinement and two dimensional mesh coarsening which are not available in existing MATLAB packages. Numerical examples indicate that iFEM can solve problems with size 105 unknowns in few seconds in a standard laptop. iFEM can let researchers considerably reduce development time than traditional programming methods.
Towards Security and Privacy for Multi-user Augmented Reality: Foundations with End Users

Immersive augmented reality (AR) technologies are becoming a reality. Prior works have identified security and privacy risks raised by these technologies, primarily considering individual users or AR devices. However, we make two key observations: (1) users will not always use AR in isolation, but also in ecosystems of other users, and (2) since immersive AR devices have only recently become available, the risks of AR have been largely hypothetical to date. To provide a foundation for understanding and addressing the security and privacy challenges of emerging AR technologies, grounded in the experiences of real users, we conduct a qualitative lab study with an immersive AR headset, the Microsoft HoloLens. We conduct our study in pairs - 22 participants across 11 pairs - wherein participants engage in paired and individual (but physically co-located) HoloLens activities. Through semi-structured interviews, we explore participants' security, privacy, and other concerns, raising key findings. For example, we find that despite the HoloLens's limitations, participants were easily immersed, treating virtual objects as real (e.g., stepping around them for fear of tripping). We also uncover numerous security, privacy, and safety concerns unique to AR (e.g., deceptive virtual objects misleading users about the real world), and a need for access control among users to manage shared physical spaces and virtual content embedded in those spaces. Our findings give us the opportunity to identify broader lessons and key challenges to inform the design of emerging single-and multi-user AR technologies.
DEMOCRACY ‘ WITH ADJECTIVES ’ : Conceptual Innovation in Comparative Research

The recent trend toward democratization in countries throughout the globe has challenged scholars to pursue two potentially contradictory goals: to develop a differentiated conceptualization of democracy that captures the diverse experiences of these countries; and to extend the analysis to this broad range of cases without ‘stretching’ the concept. This paper argues that this dual challenge has led to a proliferation of conceptual innovations, including hundreds of subtypes of democracy—i.e., democracy ‘with adjectives.’ The paper explores the strengths and weaknesses of three important strategies of innovation that have emerged: ‘precising’ the definition of democracy; shifting the overarching concept with which democracy is associated; and generating various forms of subtypes. Given the complex structure of meaning produced by these strategies for refining the concept of democracy, we conclude by offering an old piece of advice with renewed urgency: It is imperative that scholars situate themselves in relation to this structure of meaning by clearly defining and explicating the conception of democracy they are employing.
Architectural criteria for website evaluation - conceptual framework and empirical validation

With the rapid development of the Internet, many types of websites have been developed. This variety of websites makes it necessary to adopt systemized evaluation criteria with a strong theoretical basis. This study proposes a set of evaluation criteria derived from an architectural perspective which has been used for over a 1000 years in the evaluation of buildings. The six evaluation criteria are internal reliability and external security for structural robustness, useful content and usable navigation for functional utility, and system interface and communication interface for aesthetic appeal. The impacts of the six criteria on user satisfaction and loyalty have been investigated through a large-scale survey. The study results indicate that the six criteria have different impacts on user satisfaction for different types of websites, which can be classified along two dimensions: users’ goals and users’ activity levels.
COMPLEX ADAPTIVE SYSTEMS: EXPLORING THE KNOWN, THE UNKNOWN AND THE UNKNOWABLE

The study of complex adaptive systems, from cells to societies, is a study of the interplay among processes operating at diverse scales of space, time and organizational complexity. The key to such a study is an understanding of the interrelationships between microscopic processes and macroscopic patterns, and the evolutionary forces that shape systems. In particular, for ecosystems and socioeconomic systems, much interest is focused on broad scale features such as diversity and resiliency, while evolution operates most powerfully at the level of individual agents. Understanding the evolution and development of complex adaptive systems thus involves understanding how cooperation, coalitions and networks of interaction emerge from individual behaviors and feed back to influence those behaviors. In this paper, some of the mathematical challenges are discussed.
On harmonic and biharmonic Bézier surfaces

We present a new method of surface generation from presc ribed boundaries based on the elliptic partial differential operators. In particular, we focus on the study of the so-called harmonic and biharmonic Bézier surfa The main result we report here is that any biharmonic Bézier surface is fully determined by the boundary points. We compare the new method, by way of practical examples, with some related methods such as su generation using discretisation masks and functional minimisations.