Miracle-dz/UniFAR-FTUs huggingface dataset:
Typed Adapton: Refinement types for nominal memoization

Nominal memoization combines memoized functional programming with a controlled form of imperative cache eﬀects. By leveraging these imperative eﬀects, nominal memoization can dramatically out-perform traditional (“structural”) memoization. However, the nominal memoization programming model is error-prone: when the programmer unintentionally misuses names, their incremental program ceases to correspond to its purely functional semantics. This paper develops a reﬁnement type system for nominal memoization that enforces a program’s correspondence with its purely functional semantics. Our type system employs set-indexed types in the style of DML (Xi and Pfenning 1999), extended with polymorphism over kinds and index functions. We prove that our type system enforces the dynamic side conditions required by Hammer et al. (2015). Past work shows that these conditions suﬃce for realistic uses of nominal memoization while also guaranteeing from-scratch consistency of the incremental programs. Furthermore, we propose a decidable form of name-level computations for expressing generic naming strategies in type-generic incremental code.
Holistic approach of Trigonella foenum-graecum in Phytochemistry and Pharmacology- A Review

India is a country of herbs where a lot of varieties are cultivated, and their formulation developed and used for preventing, mitigating and curing of diseases and other health problems. Trigonella foenumgraecum (Fenugreek) is one of them. Its origin is in India and Northern Africa. The plant contains a variety of components i.e. alkaloids, glycoside, polyphenols, steroids, amino acids and volatile components etc. It is used as anti-diabetic, anti-fertility, anti-microbial, antiparasitic and hypocholesterolaemic, antiepileptic, antibronchitis, carminative, aphrodisiac, analgesic, antipyretic, anticancer, antioxidant, immunomodulator, in phlegm disorders, and recently in balancing the blood sugar level. In India, fenugreek powder is also used as a lactation stimulant and protective against ethanol toxicity etc. Due to its versatile activities and holistic approach in pharmacology, it is a drug of choice for health related problems of the general person, patient and researchers also. Research is going on for developing various formulations for various activities of fenugreek. This review gives an account about the recent uses of the T. foenum-graecum. Keyword Anti-diabetic, Fenugreek, Immunomodulator, Pharmacology, Phytochemistry, Trigonella foenum-
Network Performance Optimization: A Case Study of Enterprise Network Simulated in OPNET

Designing an efficient network to achieve desirable performance is a challenging task and it becomes more demanding if the network to be optimized for performance is already deployed and operational. In this paper, a case study of a campus network which is operational has been considered to enhance the network performance. Campus network of COMSATS Institute of Information Technology Islamabad, Pakistan has been analyzed which provides local and internet connectivity to approximately 1200 nodes, the problems in the existing network has been identified with the aim to enhance network performance without incorporating additional hardware cost. OPNET Modeler 14.5 simulator has been used to first implement the entire network infrastructure and then a new design for CIIT network has been proposed which provides better performance. The simulation results of both the existing and proposed networks have been compared, it could be observed that the proposed design significantly performs better especially in terms of aggregated throughput of Wireless Local Area Network. The proposed network design also outperforms the existing approach in different parameters such as Ethernet delay and WLAN load by approximately 26% and 19% respectively.
Learning how to reach various goals by autonomous interaction with the environment: uniﬁcation and comparison of exploration strategies

In the field of developmental robotics, we are particularly interested in the exploration strategies which can drive an agent to learn how to reach a wide variety of goals. In this paper, we unify and compare such strategies, recently shown to be efficient to learn complex non-linear redundant sensorimotor mappings. They combine two main principles. The first one concerns the space in which the learning agent chooses points to explore (motor space vs. goal space). Previous works have shown that learning redundant inverse models could be achieved more efficiently if exploration was driven by goal babbling, triggering reaching, rather than direct motor babbling. Goal babbling is especially efficient to learn highly redundant mappings (e.g the inverse kinematics of a arm). At each time step, the agent chooses a goal in a goal space (e.g uniformly), uses the current knowledge of an inverse model to infer a motor command to reach that goal, observes the corresponding consequence and updates its inverse model according to this new experience. This exploration strategy allows the agent to cover the goal space more efficiently, avoiding to waste time in redundant parts of the sensorimotor space (e.g executing many motor commands that actually reach the same goal). The second principle comes from the field of active learning, where exploration strategies are conceived as an optimization process. Samples in the input space (i.e motor space) are collected in order to minimize a given property of the learning process, e.g the uncertainty or the prediction error of the model. This allows the agent to focus on parts of the sensorimotor space in which exploration is supposed to improve the quality of the model.
An overview of reservoir computing: theory, applications and implementations

Training recurrent neural networks is hard. Recently it has however been discovered that it is possible to just construct a random recurrent topology, and only train a single linear readout layer. State-of- the-art performance can easily be achieved with this setup, called Reservoir Computing. The idea can even be broadened by stating that any high di- mensional, driven dynamic system, operated in the correct dynamic regime can be used as a temporal 'kernel' which makes it possible to solve complex tasks using just linear post-processing techniques. This tutorial will give an overview of current research on theory, applica- tion and implementations of Reservoir Computing.
QUICKXPLAIN: Preferred Explanations and Relaxations for Over-Constrained Problems

Over-constrained problems can have an exponential number of conflicts, which explain the failure, and an exponential number of relaxations, which restore the consistency. A user of an interactive application, however, desires explanations and relaxations containing the most important constraints. To address this need, we define preferred explanations and relaxations based on user preferences between constraints and we compute them by a generic method which works for arbitrary CP, SAT, or DL solvers. We significantly accelerate the basic method by a divide-and-conquer strategy and thus provide the technological basis for the explanation facility of a principal industrial constraint programming tool, which is, for example, used in numerous configuration applications.
Communications infrastructure generation for modular FPGA reconfiguration

Modules that are swapped dynamically at run-time on an FPGA have varying communication needs over time. In order to support this, we aim to generate a wiring infrastructure that caters for the dynamically-changing module interfaces. This, however, imposes a regular structure for laying out modules on a device, which may result in longer inter-module wiring paths as compared to traditional methods where the netlists are flattened. This paper studies placing modules within a structured layout to compare resulting circuit speeds with those obtained by traditional methods. Our results indicate that the difference in critical path delay is high at very low utilisation, but that the overhead is absorbed as the number of modules and interconnection density increases to realistic levels. The authors conclude that implementing such a wiring infrastructure has manageable overheads while having the added advantage of being amenable to dynamic reconfiguration
A trace model for system requirements changes on embedded systems

ABSTRACT Technical systems play an important role in our daily lives. Most systems have to be changed during their lifetime, but cost estimates of changes are often inaccurate and implementation of changes is time consuming and cost intensive. Planning and performing changes can be supported by precise impact analysis. Traditionally, impact analysis has been something that software professionals do intuitively, after some cursory examination of code and documentation. But, empirical investigation shows that even experienced software professionals predict incomplete sets of change impacts. This paper introduces an approach that focuses on impact analysis of system requirements changes and that is suited for embedded control systems. The approach is based on a fine-grained trace model. Empirical studies show that the approach allows a more effective impact analysis of changes on embedded systems.
The Automated Music Transcription Problem

Automated transcription of polyphonic music is a difficult task which has been attempted over the last 30 years by a number of researchers with only partial success. The problem is highly complex and is not simple even for humans. In fact, for humans transcription is a specialised task which can generally only be undertaken successfully after years of musical training. One facet of this paper concerns a study of 19 musicians who responded to a survey as to how they transcribed music. Differences were found but a consistent pattern could be seen. The results placed within the context of music psychology and the point is made that transcription does not sit well in this environment transcription is in fact the breaking down of the overall musical scene to examine individual elements, which is not a normal listening task. After reviewing existing automated transcription methods, a scheme motivated by the human approach is proposed. This first examines more global musical features and uses these to build up a musical context to aid the resolution of more detailed and possibly ambiguous structures. While the details of implementation of each individual process are beyond the scope of this paper, some issues surrounding it are also discussed.
Single Trial Classification of Motor Imagination Using 6 Dry EEG Electrodes

Background Brain computer interfaces (BCI) based on electro-encephalography (EEG) have been shown to detect mental states accurately and non-invasively, but the equipment required so far is cumbersome and the resulting signal is difficult to analyze. BCI requires accurate classification of small amplitude brain signal components in single trials from recordings which can be compromised by currents induced by muscle activity. Methodology/Principal Findings A novel EEG cap based on dry electrodes was developed which does not need time-consuming gel application and uses far fewer electrodes than on a standard EEG cap set-up. After optimizing the placement of the 6 dry electrodes through off-line analysis of standard cap experiments, dry cap performance was tested in the context of a well established BCI cursor control paradigm in 5 healthy subjects using analysis methods which do not necessitate user training. The resulting information transfer rate was on average about 30% slower than the standard cap. The potential contribution of involuntary muscle activity artifact to the BCI control signal was found to be inconsequential, while the detected signal was consistent with brain activity originating near the motor cortex. Conclusions/Significance Our study shows that a surprisingly simple and convenient method of brain activity imaging is possible, and that simple and robust analysis techniques exist which discriminate among mental states in single trials. Within 15 minutes the dry BCI device is set-up, calibrated and ready to use. Peak performance matched reported EEG BCI state of the art in one subject. The results promise a practical non-invasive BCI solution for severely paralyzed patients, without the bottleneck of setup effort and limited recording duration that hampers current EEG recording technique. The presented recording method itself, BCI not considered, could significantly widen the use of EEG for emerging applications requiring long-term brain activity and mental state monitoring.
Associative processors for video coding applications

Associative processors are single-instruction multiple-data-based architectures that provide huge parallelism which can be very useful for processing video in real time. This paper describes architectural requirements for video and shows that associative processors are ideally suited for applications involving video. Some routines like discrete cosine transforms (DCTs) lack required parallelism and their implementation becomes critical for the overall performance of the processor for video. We present three different approaches for computing two-dimensional DCT on associative processors and discuss their implementation details. Many methods like conditional execution of DCT, have been suggested in literature for power efficiency. In this paper, we discuss integration of these techniques in our implementation. Finally, performance of Associative processors is compared with that of RISC and DSP processor and show that associative processors are better suited for processing video both in terms of speed and power.
Stochastic Back-propagation and Variational Inference in Deep Latent Gaussian Models

We marry ideas from deep neural networks and approximate Bayesian inference to derive a generalised class of deep, directed generative models, endowed with a new algorithm for scalable inference and learning. Our algorithm introduces a recognition model to represent approximate posterior distributions, and that acts as a stochastic encoder of the data. We develop stochastic back-propagation -- rules for back-propagation through stochastic variables -- and use this to develop an algorithm that allows for joint optimisation of the parameters of both the generative and recognition model. We demonstrate on several real-world data sets that the model generates realistic samples, provides accurate imputations of missing data and is a useful tool for high-dimensional data visualisation.
Novel Ion Trap Design for Strong Ion-Cavity Coupling

We present a novel ion trap design which facilitates the integration of an optical fiber cavity into the trap structure. The optical fibers are confined inside hollow electrodes in such a way that tight shielding and free movement of the fibers are simultaneously achievable. The latter enables in situ optimization of the overlap between the trapped ions and the cavity field. Through numerical simulations, we systematically analyze the effects of the electrode geometry on the trapping characteristics such as trap depths, secular frequencies and the optical access angle. Additionally, we simulate the effects of the presence of the fibers and confirm the robustness of the trapping potential. Based on these simulations and other technical considerations, we devise a practical trap configuration that isviable to achieve strong coupling of a single ion.
Some initial findings regarding first language influence on playing brass instruments

This paper presents some initial findings regarding the influence of First Language on playing brass instruments. Using ultrasound imaging of the tongue, vowel production and sustained trombone notes were compared for a New Zealand English and a Tongan speaker. It is suggested that, during trombone playing, the tongue shapes used by the Tongan participant pattern with the back vowel /o/ while those used by the New Zealand English player pattern with the centralized KIT vowel (/9/) and schwa (/@/). It is argued that these findings provide preliminary evidence of First Language influence on brass playing.
Clustering players for load balancing in virtual worlds

In current Massively Multiplayer Online Games (MMOGs) the distribution of load is not distributed dynamically. But players tend to concentrate in certain regions of the game world and cause overload conditions. Therefore we propose the use of structured Peer-to-Peer technology for the server infrastructure of the MMOGs to improve the reliability and scalability. Previous work segmented the game work into rectangular areas but often split a group of players to different servers. This work presents a cluster-based P2P approach, which is able to dynamically adapt to the current state of the game and handle uneven distributions of players. We show through simulation, also with traces from real online games, that the cluster-based approach performs better than the previous P2P-based system.
Aging, Secular Stagnation, and the Business Cycle

Abstract By the end of 2019, U.S. output was 14% below the level predicted by its pre-2008 trend. To understand why, I develop and estimate a model of the United States with demographics, real and monetary shocks, and the occasionally binding zero lower bound on nominal rates. Demographic shocks generate slow-moving trends in interest rates, employment, and productivity. Demographics alone can explain about 40% of the gap between log output per capita and its linear trend by 2019. By lowering interest rates, demographic changes caused the zero lower bound to bind after the Great Recession, contributing to the slow recovery.
Integrating software development security activities with agile methodologies

Because of several vulnerabilities in software products and high amount of damage caused by them, software developers are enforced to produce more secure systems. Software grows up through its life cycle, so software development methodologies should pay special attention to security aspects of the product. This paper focuses on agile methodologies in order to equip them with security activities. We can restrain reduction of agile nature of organization's current process by means of agility measurement and applying an efficient activity integration algorithm with a tunable parameter named agility reduction tolerance (ART). Using this approach, method engineer of the project can enhance his agile software development process with security features to increase product's trustworthiness.
Time‐varied characteristics of acupuncture effects in fMRI studies

When studying the neural responses to acupuncture with a block‐designed paradigm, its temporal dynamics predicted by the general linear model (GLM) conforms to typical “on‐off” variations during a limited period of the experiment manipulation. Despite a lack of direct evidence associating its psychophysiological response, numerous clinical reports suggest that acupuncture can provide pain relief beyond a needling session. Therefore, a typical GLM analysis may be insensitive or inappropriate for identifying altered neural responses resulting from acupuncture. We developed a new approach to investigate the dynamics underlying sustained effects of acupuncture. Specifically, we designed two separate models to evaluate the baseline activities (prior to stimulation) and neural activities in sequential epochs, using three block‐designed functional runs: acupuncture at acupoint ST36, nonmeridian point (NMP) stimulation, and a visual task. We found that the activity patterns during rest were associated with the stimulus types and that the resting activities might be even higher than that of stimulation phases. Such effects of the elevated activity during rest may reduce or eliminate the activity during stimulus conditions or even reverse the sign of brain activation using conventional GLM analysis. Moreover, such sustained responses, followed by acupuncture at ST36 and NMP, exhibited distinct patterns in wide brain structures, particularly in the limbic system and brainstem. These findings may pose great implications for the design and interpretation of a range of acupuncture neuroimaging studies. Hum Brain Mapp, 2009. © 2009 Wiley‐Liss, Inc.
Tapping into Recovery: Exploring Experiences of Emotional Freedom Techniques (EFT)

This thesis explores users' experiences of utilising a contemporary therapeutic intervention, called Emotional Freedom Techniques (EFT) for supporting physical chronic disease healthcare. Eight chronic disease patients and eight EFT practitioners were interviewed for this study. An in-depth exploration of the sixteen participants' experiences of using EFT to support chronic disease healthcare was undertaken using a qualitative research methodology. Findings of this study suggest that chronic disease patients may benefit from a holistic healthcare approach, which incorporates psychological and social support in addition to biomedical support. The findings of the study have been synthesised in an original healthcare model that views the patient as a 'whole-person', and guides patient healthcare in accordance with patients' unique life circumstances and experiences.
Recombination and the immortality of the germ line

Asexual populations irreversibly accumulate mildly deleterious mutations through the occasional stochastic loss of their least‐loaded line, a process known as “Muller's Ratchet”. This paper explores the dynamics of this process, and the role of recombination in halting the Ratchet. Simulation studies show that an optimal class comprising no individuals is lost in about 10no generations, implying that adaptedness may deteriorate rather rapidly in geological time. Asexual organisms will persist only if they are very numerous, or if they have very small genomes, or if there is extensive negative interaction among nonallelic mutations. Otherwise, long‐term persistence requires that unloaded genomes be continually generated by recombination. An approximate expression for the rate of recombination needed to halt the Ratchet is developed, and shows that substantial recombination is necessary in populations of fewer than about 1010 individuals. A further complication is introduced by mutations in sequences which specify proofreading enzymes. Since these will reduce the fidelity of their own replication, a process of positive feedback leading to an ever‐accelerating loss of function is conceivable.