Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Implementation of Tree-transformations in Ensemble Ucb Cs Honors Program Project Report

Tree transformations ooer a convenient method to describe various manipulations that are commonly performed by compilers and language-based editors. Many of the compiler stages, such as semantic analysis, code optimization, and code generation Pelegri-Llopart 1988], are frequently speciied as a sequence of tree transformations that transform parse tree into output representation (e.g. machine language). Similarly , structured-document environments, such as Ensemble Dennis et al. 1995], can beneet from the use of tree transformations to convert parse trees to abstract syntax trees (and vice versa, given suucient information for the reverse transformation), compute presentation-trees, etc. In this paper, we describe design and implementation of tree transformation subsystem in Ensemble environment. Ensemble (presently a research prototype) provides to the user a number of document services (including incremental analysis, revision management, presentation, etc.), simplifying the task of software construction and maintenance. We extend this set of document services to include tree transformation facilities that provide functionality to translate between programming languages, rearrange source code, perform code generation, etc. by means of applying tree transformations to document trees.
Privacy-Preserving Tuple Matching in Distributed Databases

We address the problems of privacy-preserving duplicate tuple matching (PPDTM) and privacy-preserving threshold attributes matching (PPTAM) in the scenario of a horizontally partitioned database among N parties, where each party holds a private share of the database's tuples and all tuples have the same set of attributes. In PPDTM, each party determines whether its tuples have any duplicate on other parties' private databases. In PPTAM, each party determines whether all attribute values of each tuple appear at least a threshold number of times in the attribute unions. We propose protocols for the two problems using additive homomorphic cryptosystem based on the subgroup membership assumption, e.g., Paillier's and ElGamal's schemes. By analysis on the total numbers of modular exponentiations, modular multiplications and communication bits, with a reduced computation cost which dominates the total cost, by trading off communication cost, our PPDTM protocol for the semihonest model is superior to the solution derivable from existing techniques in total cost. Our PPTAM protocol is superior in both computation and communication costs. The efficiency improvements are achieved mainly by using random numbers instead of random polynomials as existing techniques for perturbation, without causing successful attacks by polynomial interpolations. We also give detailed constructions on the required zero-knowledge proofs and extend our two protocols to the malicious model, which were previously unknown.
Non-Gaussian Analysis of Diffusion Weighted Imaging in Head and Neck at 3T: A Pilot Study in Patients with Nasopharyngeal Carcinoma

Purpose To technically investigate the non-Gaussian diffusion of head and neck diffusion weighted imaging (DWI) at 3 Tesla and compare advanced non-Gaussian diffusion models, including diffusion kurtosis imaging (DKI), stretched-exponential model (SEM), intravoxel incoherent motion (IVIM) and statistical model in the patients with nasopharyngeal carcinoma (NPC). Materials and Methods After ethics approval was granted, 16 patients with NPC were examined using DWI performed at 3T employing an extended b-value range from 0 to 1500 s/mm2. DWI signals were fitted to the mono-exponential and non-Gaussian diffusion models on primary tumor, metastatic node, spinal cord and muscle. Non-Gaussian parameter maps were generated and compared to apparent diffusion coefficient (ADC) maps in NPC. Results Diffusion in NPC exhibited non-Gaussian behavior at the extended b-value range. Non-Gaussian models achieved significantly better fitting of DWI signal than the mono-exponential model. Non-Gaussian diffusion coefficients were substantially different from mono-exponential ADC both in magnitude and histogram distribution. Conclusion Non-Gaussian diffusivity in head and neck tissues and NPC lesions could be assessed by using non-Gaussian diffusion models. Non-Gaussian DWI analysis may reveal additional tissue properties beyond ADC and holds potentials to be used as a complementary tool for NPC characterization.
G Protein Regulation of Neuronal Calcium Channels: Back to the Future

Neuronal voltage-gated calcium channels have evolved as one of the most important players for calcium entry into presynaptic endings responsible for the release of neurotransmitters. In turn, and to fine-tune synaptic activity and neuronal communication, numerous neurotransmitters exert a potent negative feedback over the calcium signal provided by G protein–coupled receptors. This regulation pathway of physiologic importance is also extensively exploited for therapeutic purposes, for instance in the treatment of neuropathic pain by morphine and other μ-opioid receptor agonists. However, despite more than three decades of intensive research, important questions remain unsolved regarding the molecular and cellular mechanisms of direct G protein inhibition of voltage-gated calcium channels. In this study, we revisit this particular regulation and explore new considerations.
Saliency preprocessing for person re-identification images

In this paper, we propose a preprocessing strategy for refining the pedestrian images in person re-identification(re-id). The accomplishment of the person re-id task depends on the features extracted from pedestrian appearances. The best image matches are verified based on these features as identification results. The saliency information in image scenes is often exploited for feature selection in high-level vision tasks. Inspired by the pre-attentive mechanism in human visual system, we utilize the saliency information in the re-identification data to refine the person appearance in a preprocessing step. We first obtain the eye-fixation-predicting map based on the saliency analysis of image. Then this map is used to spatially weight the image features for a better appearance. Finally, we apply these processed images to the feature extraction in a standard re-identification procedure. Experiments on the widely-used VIPeR dataset show that the proposed method improves the final performance of re-identification task.
Education, Epistemology and Critical Realism

@contents: 1. Introduction and Initial Thoughts 2. Critical Realism and Empirical Research Methods in Education 3. Resolving the Quantitative-Qualitative Divide 4. Epistemic Relativism, Ontological Realism, and the Possibility of Judgemental Rationality 5. Educational Judgements: Epistemic, Parasitic and External Criteria 6. Judgemental Rationality 7. Empirical Indicators and Causal Narratives 8. Structure and Agency - Key Ontological Concepts 9. Educational Critique 10. Arbitrary and Non-Arbitrary Knowledge
Serum Alpha-Fetoprotein Predicts Treatment Outcome in Chronic Hepatitis C Patients Regardless of HCV Genotype

We examined the association between serum alpha-fetoprotein (AFP) level and sustained virological response (SVR) in 93 chronic hepatitis C patients. The SVR rate was much higher among patients with serum AFP levels below rather than above the median value (5.7 ng/ml) (58.7% and 19.2%, respectively; P<0.0001). Serum AFP should be added to the list of factors predictive of treatment response in chronic hepatitis C.
ZMap: Fast Internet-wide Scanning and Its Security Applications

Internet-wide network scanning has numerous security applications, including exposing new vulnerabilities and tracking the adoption of defensive mechanisms, but probing the entire public address space with existing tools is both difficult and slow. We introduce ZMap, a modular, open-source network scanner specifically architected to perform Internet-wide scans and capable of surveying the entire IPv4 address space in under 45 minutes from user space on a single machine, approaching the theoretical maximum speed of gigabit Ethernet. We present the scanner architecture, experimentally characterize its performance and accuracy, and explore the security implications of high speed Internet-scale network surveys, both offensive and defensive. We also discuss best practices for good Internet citizenship when performing Internet-wide surveys, informed by our own experiences conducting a long-term research survey over the past year.
Real-time Monocular Tracking of View Frustum for Large Screen Human-Computer Interaction

This paper introduces a novel approach towards direct interaction with large display systems. Monocular computer vision is utilised to avoid restraints imposed by input devices. Tracking the user's head and determining the view frustum in real-time is one of the key processes in our proposed human-computer interaction system. We also proposed using a view frustum to model the user's interaction volume allowing flexible interaction with the display. Finally, we demonstrate the feasibility of this new concept and provide an accuracy analysis of our prototype system.
Uncertainty modeling of gate delay considering multiple input switching

With the continual advancement in manufacturing technologies and the resultant process variations, delay variability is becoming increasingly significant. Statistical models have become mandatory to model the delay variability. It has also been experimentally proved that ignoring multiple input switching and approximating it by single input switching results in significant error. We propose a new gate delay model that considers the impact of both process variations and multiple input switching. The proposed model uses an orthogonal polynomial based probabilistic collocation method to construct a delay analytical equation from a circuit's output response. The obtained analytical equation is used to evaluate the output delay distribution. Experimental results show that our approach gives a mean delay error less than 0.1% and a standard deviation error less than 2% when compared with Monte Carlo analysis.
Schools at home : parental support for learning Mandarin as a second or foreign language

This study examined how parents of various backgrounds supported their children learning Mandarin as a second or foreign language. It addresses two questions which have previously rarely been addressed in the literature. 1. Whether and if so in what ways do parents of different backgrounds support their children in learning Mandarin as a second or a foreign language? 2. How is this affected by social, cultural as well as the parents’ own educational experience? Here the most relevant socio-cultural theories of learning: prolepsis; guided participation; syncretism; synergy and funds of knowledge have been studied. Ethnographic research was conducted on six families chosen from three categories: families in which both parents had Chinese heritage; one parent had Chinese heritage and those in which neither parent had a Chinese background. Data were collected through participant observation and interviews. The method of multi-layering was applied to analyze these data: the outer layer- social and cultural background, the middle layer- supporting strategies and the inner layer- the pedagogic methods used by the parents. The results reveal that these parents were determined to assist their children’s learning and employed different methods: both direct (teaching) and indirect (providing access to resources, cultural activities and events). All parents set aside time for formal, serious, regular (school-like) learning sessions. The support they provided was affected significantly by their social, cultural and educational background. All enhanced their children’s motivation and learning achievement.
The Fatty Acid Receptor GPR40 Plays a Role in Insulin Secretion In Vivo After High-Fat Feeding

OBJECTIVE—The G-protein–coupled receptor GPR40 is expressed in pancreatic β-cells and is activated by long-chain fatty acids. Gene deletion studies have shown that GPR40 mediates, at least in part, fatty acid–amplification of glucose-induced insulin secretion (GSIS) but is not implicated in GSIS itself. However, the role of GPR40 in the long-term effects of fatty acids on insulin secretion remains controversial. This study aimed to test the hypothesis that GPR40 plays a role in insulin secretion after high-fat feeding. RESEARCH DESIGN AND METHODS—GPR40 knockout (KO) mice on a C57BL/6 background and their wild-type (WT) littermates were fed a high-fat diet (HFD) for 11 weeks. Glucose tolerance, insulin tolerance, and insulin secretion in response to glucose and Intralipid were assessed during the course of the diet period. RESULTS—GPR40 KO mice had fasting hyperglycemia. They became as obese, glucose intolerant, and insulin resistant as their WT littermates given HFD and developed a similar degree of liver steatosis. Their fasting blood glucose levels increased earlier than those of control mice during the course of the HFD. The remarkable increase in insulin secretory responses to intravenous glucose and Intralipid seen in WT mice after HFD was of much lower magnitude in GPR40 KO mice. CONCLUSIONS—GPR40 plays a role not only in fatty acid modulation of insulin secretion, but also in GSIS after high-fat feeding. These observations raise doubts on the validity of a therapeutic approach based on GPR40 antagonism for the treatment of type 2 diabetes.
Graph regularized Non-negative Tensor Completion for spatio-temporal data analysis

We propose a pattern discovery method for analyzing spatio-temporal counting data collected by sensor monitoring systems, such as the number of vehicles passed a cite, where the data include a large number of missing values. Our method is based on the Non-negative Tensor Completion method that simultaneously infers missing values and decomposes a non-negative tensor into latent factor matrices. To deal with the large number of missing values, we extend this method to utilize spatial and temporal auxiliary information, such as the temporal continuity and topological similarity of data attributes, when estimating factor matrices. We employ a graph-based regularizer to make latent factors represent the spatial and temporal structures and combine them with NTC. We also incorporate the generalized Kullback-Leibler divergence into NTC, which is suitable for modeling counting values. To estimate the latent factors of our method, we derive a computationally efficient algorithm that only needs to solve linear equations. We apply our proposed method to a problem that consists of analyzing real-world traffic flow data. We show that our proposed method improved quantitative performance with regards inferring missing values from existing methods, and reasonably interpretable latent patterns were discovered with our proposed method.
A flexible instruction generation framework for extending embedded processors

Modern platform-based design involves the domain-specific extension of embedded processors to fit customer requirements. To accomplish this task, the possibilities offered by recent extensible processors for their instruction set and microarchitectural customization have to be exploited. In this paper, a design approach that encapsulates automated workload characterization and highly-controllable instruction and application-specific functional unit (AFU) generation is utilized for fast extension space exploration of embedded processors. It is proved that a relatively small number of unique AFUs is needed in order to support embedded applications from the MiBench and Powerstone suites. It is possible to achieve 1.8times to 6.8times performance improvements although further possibilities such as subword parallelization are not currently regarded
An emotional voice generation and extraction system using soft computing technique

Recently, researchers have paid close attention to intelligent human-machine interfaces. The future intelligent computing system will need to have human-centered designs instead of the traditional computer-centered designs. Dealing with emotional information is one of such approaches. In the symbiotic generation of human beings and machines, exchanging emotional information will become very important. Therefore, we propose an emotional voice generation and extraction system using soft computing technique. The system generates emotional voice using genetic algorithm, and evaluates the generated emotional voice using fuzzy inference. In this paper, we describe the system and discuss about an experimental result using a neutral voice.
Worst-case temperature analysis for different resource models

The rapid increase in heat dissipation in real-time systems imposes various thermal issues. For instance, real-time constraints cannot be guaranteed if a certain threshold temperature is exceeded, as it would immediately reduce the system reliability and performance. Dynamic thermal management techniques are promising methods to prevent a system from overheating. However, when designing real-time systems that make use of such thermal management techniques, the designer has to be aware of their effect on both real-time constraints and worst-case peak temperature. In particular, the worst-case peak temperature of a real-time system with non-deterministic workload is the maximum possible temperature under all feasible scenarios of task arrivals. This study proposes an analytic framework to calculate the worst-case peak temperature of a system with general resource availabilities, which means that computing power might not be fully available for certain time intervals. The event and resource models are based on real-time and network calculus, and therefore, our analysis method is able to handle a broad range of uncertainties in terms of task arrivals and available computing power. Finally, we propose an indicator for the quality of the resource model with respect to worst-case peak temperature and schedulability.
CONSIDERATION OF A MOVING MASS EFFECT ON DYNAMIC BEHAVIOUR OF A JIB CRANE STRUCTURE

The moving load problem is considered as a special topic in structural dynamics. Structures subjected to moving bodies have been analysed ever since the first railway bridges were built in the early 19th century. Since then, the moving load problem has become more dynamic in character mainly due to increased vehicle speeds and structural flexibility. A large number of studies dealing with the moving load problem refer to the excellent monograph by Fryba [1]. Irrespective of many viewpoints and analytical methods proposing to solve the dynamic problems, the majority of research can be grouped into two categories: the moving force problem and the moving mass problem. The additional approach is moving oscillator model which is only reasonable to be used in some special structures because of its complexity. The basic understanding of the moving force phenomena is given in [2]. In most moving force models the magnitude of the contact force is constant in time which implies that the inertia forces of a moving body are neglected. Even so, the moving force models are simple to use and yield reasonable structural results in some cases [3]. The moving mass problem implies the existence of an interaction force between the moving mass and the structure during the time the mass travels along the structure, to which the following factors contribute: the inertia of the mass, the centrifugal force, the Coriolis force and the timevarying speed-dependent forces. Hence, the speed of the moving mass, structural flexibility and the ratio of the moving mass and structure mass are important factors that contribute to the creation of the interaction force. Michaltsos et al. [4] have studied the effect of a moving mass and other parameters, such as magnitude and speed of the moving mass, on the dynamic response of a simply
Potassium Uptake Supporting Plant Growth in the Absence of AKT1 Channel Activity

A transferred-DNA insertion mutant of Arabidopsis that lacks AKT1 inward-rectifying K+ channel activity in root cells was obtained previously by a reverse-genetic strategy, enabling a dissection of the K+-uptake apparatus of the root into AKT1 and non-AKT1 components. Membrane potential measurements in root cells demonstrated that the AKT1 component of the wild-type K+ permeability was between 55 and 63% when external [K+] was between 10 and 1,000 μM, and NH4 + was absent. NH4 + specifically inhibited the non-AKT1 component, apparently by competing for K+ binding sites on the transporter(s). This inhibition by NH4 + had significant consequences for akt1 plants: K+ permeability, 86Rb+ fluxes into roots, seed germination, and seedling growth rate of the mutant were each similarly inhibited by NH4 +. Wild-type plants were much more resistant to NH4 +. Thus, AKT1 channels conduct the K+ influx necessary for the growth of Arabidopsis embryos and seedlings in conditions that block the non-AKT1 mechanism. In contrast to the effects of NH4 +, Na+ and H+ significantly stimulated the non-AKT1 portion of the K+ permeability. Stimulation of akt1 growth rate by Na+, a predicted consequence of the previous result, was observed when external [K+] was 10 μM. Collectively, these results indicate that the AKT1 channel is an important component of the K+ uptake apparatus supporting growth, even in the “high-affinity” range of K+ concentrations. In the absence of AKT1 channel activity, an NH4 +-sensitive, Na+/H+-stimulated mechanism can suffice.
Exploring the use of hand-to-face input for interacting with head-worn displays

We propose the use of Hand-to-Face input, a method to interact with head-worn displays (HWDs) that involves contact with the face. We explore Hand-to-Face interaction to find suitable techniques for common mobile tasks. We evaluate this form of interaction with document navigation tasks and examine its social acceptability. In a first study, users identify the cheek and forehead as predominant areas for interaction and agree on gestures for tasks involving continuous input, such as document navigation. These results guide the design of several Hand-to-Face navigation techniques and reveal that gestures performed on the cheek are more efficient and less tiring than interactions directly on the HWD. Initial results on the social acceptability of Hand-to-Face input allow us to further refine our design choices, and reveal unforeseen results: some gestures are considered culturally inappropriate and gender plays a role in selection of specific Hand-to-Face interactions. From our overall results, we provide a set of guidelines for developing effective Hand-to-Face interaction techniques.