Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of a MEMS-Based Oscillator Using 180nm CMOS Technology

Micro-electro mechanical system (MEMS) based oscillators are revolutionizing the timing industry as a cost effective solution, enhanced with more features, superior performance and better reliability. The design of a sustaining amplifier was triggered primarily to replenish MEMS resonator’s high motion losses due to the possibility of their ‘system-on-chip’ integrated circuit solution. The design of a sustaining amplifier observing high gain and adequate phase shift for an electrostatic clamp-clamp (C-C) beam MEMS resonator, involves the use of an 180nm CMOS process with an unloaded Q of 1000 in realizing a fixed frequency oscillator. A net 122dBΩ transimpedance gain with adequate phase shift has ensured 17.22MHz resonant frequency oscillation with a layout area consumption of 0.121 mm2 in the integrated chip solution, the sustaining amplifier draws 6.3mW with a respective phase noise of -84dBc/Hz at 1kHz offset is achieved within a noise floor of -103dBC/Hz. In this work, a comparison is drawn among similar design studies on the basis of a defined figure of merit (FOM). A low phase noise of 1kHz, high figure of merit and the smaller size of the chip has accredited to the design’s applicability towards in the implementation of a clock generative integrated circuit. In addition to that, this complete silicon based MEMS oscillator in a monolithic solution has offered a cost effective solution for industrial or biomedical electronic applications.
Heteroscedastic Multilinear Discriminant Analysis for Face Recognition

There is a growing attention in subspace learning using tensor-based approaches in high dimensional spaces. In this paper we first indicate that these methods suffer from the Heteroscedastic problem and then propose a new approach called Heteroscedastic Multilinear Discriminant Analysis (HMDA). Our method can solve this problem by utilizing the pairwise chernoff distance between every pair of clusters with the same index in different classes. We also show that our method is a general form of Multilinear Discriminant Analysis (MDA) approach. Experimental results on CMU-PIE, AR and AT&T face databases demonstrate that the proposed method always perform better than MDA in term of classification accuracy.
Anticipation mappings for learning classifier systems

In this paper, we study the use of anticipation mappings in learning classifier systems. At first, we enrich the extended classifier system (XCS) with two types of anticipation mappings: one based on array of perceptrons array, one based on neural networks. We apply XCS with anticipation mappings (XCSAM) to several multistep problems taken from the literature and compare its anticipatory performance with that of the neural classifier system X-NCS which is based on a similar approach. Our results show that, although XCSAM is not a "true" anticipatory classifier system like ACS, MACS, or X-NCS, nevertheless XCSAM can provide accurate anticipatory predictions while requiring smaller populations than those needed by X-NCS.
Advanced spectroscopies of graphene and 2D materials

A full exploitation of the unique features of graphene and related 2D materials in micro and nano-scaled optoelectronic devices for high-data rate photonic systems calls for a deep understanding of their fundamental structural, electronic, photophysical properties and fast dynamics. We introduce some advanced spectroscopic techniques developed to this aim, while reviewing their specific potentialities and highlighting recent results. To provide absolute local nanoscale thickness metrology of as-grown 2D materials, Scanning Auger Electron Microspectroscopy has been calibrated. Results obtained for graphene and graphene oxide (GO) are reported, showing sub-monolayer resolution. Ultrafast optical transient absorption spectroscopy, with temporal resolution down to 10fs, unveils the relaxation dynamics of hot electrons in single layer graphene and the formation and radiative recombination via stimulated emission of biexcitons in ultra-narrow, structurally well-defined nanoribbons (GNRs). By recently developed ultrafast Time- and Angle-resolved Photo-Electron Spectroscopy (TR-ARPES) we investigate electronic states and spin dynamics close to the Dirac cone, in graphene and metal chalcogenide topological insulators (TI) under fs strong laser excitation, in view of spintronic applications.
Lessons Learned in Deploying a Multi-Agent Learning Support System: The I-Help Experience

In this paper we look at the lessons learned from several large-scale real world deployments of the I-Help agent-based peer-help learning support system. These lessons divide into two main categories: software engineering lessons and usage lessons. In the deployments of I-Help to date we have learned a number of important things about the technology needed to support widespread use of a distributed learning support system. In particular accessibility, dependability, and scalability are critical needs. We have also learned a number of things about how, why, and even whether students will use a system like I -Help. There are technical and social dimensions to the usage issue. The paper briefly overviews I-Help, and then describes the various deployments. The software engineering and usage lessons are then elaborated, drawing on data gathered by I-Help itself during its various deployments and on questionnaires handed out to student users at the end of two of the deployments. These lessons are, we believe, useful not just in the I-Help context, but for any AIED researchers who plan to deploy a complex system in a real world for a large number of users.
Choice and control for people ageing with intellectual disability in group homes

Abstract Background Many people ageing with intellectual disabilities (ID) age in place in group homes. Participation is a central concept in support and service to people with ID, but age is often a determining factor for participation among this group. Choice and control are dimensions of participation. Aim The aim of this article is to explore how choice and control in the everyday life of people ageing with ID is expressed and performed in the group home’s semi-private spaces. Material and methods Participant observations and interviews with residents and staff were conducted in four different group homes in Sweden that had older residents. Results Four categories were found that can be understood as aspects of choice and control in the group home’s semi-private spaces in the everyday life of people ageing with ID. These categories included aspects such as space and object, time and routines, privacy, and a person-centred approach. Conclusion and significance People ageing with ID are vulnerable when it comes to maintaining choice and control in various situations in the home’s semi-private spaces. It is argued that occupational therapists should include this occupational arena in their evaluations and interventions for people ageing with ID.
PERFORMANCE EVALUATION OF WIRELESS SENSOR NETWORKS FOR JOINT MOBILE SINK AND ROUTING PROTOCOLS

The durability of Wireless Sensor Networks (WSNs) is a major issue that impacts the application of such networks. While communication protocols are striving to save energy by acting on sensor nodes, recent results show that network lifetime can be extended by further involving sink mobility. As most proposals give their evidence of lifetime improvement through numerical simulations and field tests, a study which combines the sink mobility with the different existing routing protocols is still missing. In this work, we investigate how sensor networks perform when the sink node is mobile. We compare the simulation results for two cases: when the sink node is stationary and mobile, considering lattice and random topologies and using three routing protocols: AODV, DSDV, and DSR. The simulation results have shown that for the case of mobile sink, the depleted energy is half than what was consumed in the case of motionless sink. As well, the consumed energy of lattice topology is 4% to 9% low if compared to that of random topology. Finally, DSDV seems to have the best performance in terms of depleted energy (16% and 6%, of the total energy for stationary and mobile sink, respectively), yet it has the poorest packet delivery ratio (100% to 76,23%, for motionless and itinerant sink, respectively). KeywordsWSN; mobile sink; consumed energy; topology; packet delivery ratio, end-to-end delay; routing load
Spaces of connection and belonging: young people’s perspectives on the role of youth cafés in their lives

ABSTRACT A youth café is a relaxed, drug-free and alcohol-free meeting space for young people. The youth café model has become a prominent form of policy provision for young people in Ireland over the past decade, with in excess of 160 youth cafés now in operation. While the youth café model is not unique to Ireland, there has been little published research internationally on the perspectives of young people regarding the role of youth cafés in their lives. Drawing on qualitative research with 102 young people from 10 youth cafés in Ireland, this article presents findings in relation to six thematic areas: feeling supported; belonging and connection; personal and identity development; safety; alcohol and drugs; and education. The findings indicate that the attraction of the model for young people is that it respects their individualised preferences for engagement whilst providing them with a sense of ownership and connection. It is argued that the values and principles underpinning the model are instrumental in creating “care-full” spaces that enhance the well-being of children and young people.
Sources of strain among elite UK track athletes

Following the theoretical framework of Lazarus and Folkman (1984), recently adapted to sport (Fletcher, Hanton, & Mellalieu, 2006), 12 elite UK track athletes (M age = 22.7; SD = 2.4 years) participated in semistructured interviews to identify sources of strain. Inductive content analysis identified 11 general dimensions of sources of strain from 664 meaning units, which were subsequently categorized into competitive, organizational, and personal domains. Several sources of strain (e.g., competitive concerns, pressure to perform) were consistent with previous research supporting the suggestion that a core group of stressors may be evident across sports although several sources of strain appeared to be more pertinent to track athletes (e.g., social evaluation and self-presentation concerns) highlighting the need to consider group differences.
Dissolved oxygen fluxes and ecosystem metabolism in an eelgrass (Zostera marina) meadow measured with the eddy correlation technique

Dissolved oxygen (DO) fluxes were measured by eddy correlation to estimate net ecosystem metabolism (NEM) during summer in a restored eelgrass (Zostera marina) meadow and a nearby, unvegetated sediment. This technique measures benthic fluxes under true in situ light and hydrodynamic conditions, integrates over a large area (typically > 100 m2), and captures short‐term variations. DO fluxes measured through eight 24‐h periods showed pronounced temporal variation driven by light and local hydrodynamics on multiple scales: hour‐to‐hour, within each daily cycle, and between deployments. The magnitude of variation between hours during single deployments equaled that between deployments, indicating that short‐term variation must be included for metabolism estimates to be accurate. DO flux variability was significantly correlated to mean current velocity for the seagrass site and to significant wave height for the unvegetated site. Fluxes measured in low‐flow conditions analogous to many chamber and core incubations underestimated those measured in higher‐flow conditions typical of in situ conditions by a factor of 2–6. Rates of gross primary production (GPP), respiration (R), and NEM varied substantially between individual deployments, reflecting variations in light and hydrodynamic conditions, and daily values of GPP and R for individual deployments were tightly linked. Average daily NEM of the seagrass site was higher than that of the unvegetated site; the seagrass site was in metabolic balance, and the unvegetated site showed a tendency toward net heterotrophy during this midsummer period.
Design of Wearable Breathing Sound Monitoring System for Real-Time Wheeze Detection

In the clinic, the wheezing sound is usually considered as an indicator symptom to reflect the degree of airway obstruction. The auscultation approach is the most common way to diagnose wheezing sounds, but it subjectively depends on the experience of the physician. Several previous studies attempted to extract the features of breathing sounds to detect wheezing sounds automatically. However, there is still a lack of suitable monitoring systems for real-time wheeze detection in daily life. In this study, a wearable and wireless breathing sound monitoring system for real-time wheeze detection was proposed. Moreover, a breathing sounds analysis algorithm was designed to continuously extract and analyze the features of breathing sounds to provide the objectively quantitative information of breathing sounds to professional physicians. Here, normalized spectral integration (NSI) was also designed and applied in wheeze detection. The proposed algorithm required only short-term data of breathing sounds and lower computational complexity to perform real-time wheeze detection, and is suitable to be implemented in a commercial portable device, which contains relatively low computing power and memory. From the experimental results, the proposed system could provide good performance on wheeze detection exactly and might be a useful assisting tool for analysis of breathing sounds in clinical diagnosis.
Hope and Hopelessness: The Role of Hope in Buffering the Impact of Hopelessness on Suicidal Ideation

Objectives The present study investigated whether hope and hopelessness are better conceptualized as a single construct of bipolar spectrum or two distinct constructs and whether hope can moderate the relationship between hopelessness and suicidal ideation. Methods Hope, hopelessness, and suicidal ideation were measured in a community sample of 2106 participants through a population-based household survey. Results Confirmatory factor analyses showed that a measurement model with separate, correlated second-order factors of hope and hopelessness provided a good fit to the data and was significantly better than that of the model collapsing hope and hopelessness into a single second-order factor. Negative binomial regression showed that hope and hopelessness interacted such that the effect of hopelessness on suicidal ideation was lower in individuals with higher hope than individuals with lower hope. Conclusions Hope and hopelessness are two distinct but correlated constructs. Hope can act as a resilience factor that buffers the impact of hopelessness on suicidal ideation. Inducing hope in people may be a promising avenue for suicide prevention.
Sketched Symbol Recognition with a Latent-Dynamic Conditional Model

In this paper we present a recognizer of sketched symbols based on Latent-Dynamic Conditional Random Fields (LDCRF), a discriminative model for sequence classification. The LDCRF model classifies unsegmented sequences of strokes into domain symbols by taking into account contextual and temporal information. In particular, LDCRFs learn the extrinsic dynamics among strokes by modeling a continuous stream of symbol labels, and learn internal stroke sub-structure by using intermediate hidden states. The performance of our work is evaluated in the electric circuit domain.
FLUCTUATING CROSSTALK , GA SCALABILITY , AND THE DISRUPTION OF OPTIMA BY

The genetic algorithm (GA) is gaining increasing interest in both academia and industry in attempts to solve hard search problems quickly, accurately, and reliably. Various theories of what makes a problem difficult for the GA to solve have been put forward; yet, none of them has been completely confirmed experimentally. This thesis examines one theory of GA problem difficulty and investigates one facet of that theory that has received scant empirical attention and only passing theoretical consideration. The theory of problem difficulty assumed in this thesis is centered on the notion that GAs process building blocks in their search for optimal solutions. A source of difficulty commonly referred to in the literature is crosstalk, or nonlinear interactions among building blocks. The purpose of this thesis is to explore the effects of one type of crosstalk, fluctuating crosstalk, on population size, convergence time, and the number of function evaluations for boundedly difficult test functions. By modeling fluctuating crosstalk with Walsh coefficients, this thesis investigates fluctuating crosstalk effects on GA scalability by varying the order and magnitude of the crosstalk and the scaling of building blocks in the underlying fitness function. High-order fluctuating crosstalk induces scalability effects similar to exogenous noise, and can be modeled by known facetwise models of GA scalability that account for external noise until the strength of the crosstalk far exceeds the underlying fitness variance by a certain factor empirically observed. Additionally, for multiple small-order coefficients, the fluctuating crosstalk has the potential to disrupt the optimal solution. The results have implications for the relative performance of building block–wise mutation to crossover.
End-to-End Speech Recognition Models

For the past few decades, the bane of Automatic Speech Recognition (ASR) systems have been phonemes and Hidden Markov Models (HMMs). HMMs assume conditional independence between observations, and the reliance on explicit phonetic representations requires expensive handcrafted pronunciation dictionaries. Learning is often via detached proxy problems, and there especially exists a disconnect between acoustic model performance and actual speech recognition performance. Connectionist Temporal Classification (CTC) character models were recently proposed attempts to solve some of these issues, namely jointly learning the pronunciation model and acoustic model. However, HMM and CTC models still suffer from conditional independence assumptions and must rely heavily on language models during decoding. In this thesis, we question the traditional paradigm of ASR and highlight the limitations of HMM and CTC models. We propose a novel approach to ASR with neural attention models and we directly optimize speech transcriptions. Our proposed method is not only an end-toend trained system but also an end-to-end model. The end-to-end model jointly learns all the traditional components of a speech recognition system: the pronunciation model, acoustic model and language model. Our model can directly emit English/Chinese characters or even word pieces given the audio signal. There is no need for explicit phonetic representations, intermediate heuristic loss functions or conditional independence assumptions. We demonstrate our end-to-end speech recognition model on various ASR tasks. We show competitive
Construction of an in vivo System for Functional Analysis of the Genes Involved in Sex Pheromone Production in the Silkmoth, Bombyx mori

Moths produce species-specific sex pheromones to attract conspecific mates. The biochemical processes that comprise sex pheromone biosynthesis are precisely regulated and a number of gene products are involved in this biosynthesis and regulation. In recent years, at least 300 EST clones have been isolated from Bombyx mori pheromone gland (PG) specific cDNA libraries with some of those clones [i.e., B. mori PG-specific desaturase 1 (Bmpgdesat1), PG-specific fatty acyl reductase, PG-specific acyl-CoA-binding protein, B. mori fatty acid transport protein, B. mori lipid storage droplet protein-1] characterized and demonstrated to play a role in sex pheromone production. However, most of the EST clones have yet to be fully characterized and identified. To develop an efficient system for analyzing sex pheromone production-related genes, we investigated the feasibility of a novel gene analysis system using the upstream region of Bmpgdesat1 that should contain a PG-specific gene promoter in conjunction with piggyBac vector-mediated germ line transformation. As a result, we have been able to obtain expression of our reporter gene (enhanced green fluorescent protein) in the PG but not in other tissues of transgenic B. mori. Current results indicate that we have successfully constructed a novel in vivo gene analysis system for sex pheromone production in B. mori.
Adaptive Visualization of Text Documents Incorporating Domain Knowledge

We present a method for visualizing text corpora that are assumed to contain labeled and unlabeled documents. Our method aims at learning data mappings of labeled documents including the terms that are most relevant for label discrimination. We can use this information to visualize mapped unlabeled documents as well. We also show how this method allows the inclusion of user’s feedback. This feedback is supplied in an iterative process, so that the user can use the output of the method to provide its domain knowledge of the data. At the same time, this technique is well suited for providing a new low-dimensional space where traditional clustering or classification methods can be applied. Even though our approach is able to deal with document labels that are discrete classes, continuous values, or associated vectors, we confine the experiments of this article to labels that represent non-overlapped topics. This approach is evaluated using a set of short and noisy documents, which is considered as a challenging task in the text mining literature.
Characterization of the complex ion dynamics in lithium silicate glasses via computer simulations

We present results of molecular dynamics simulations on lithium metasilicate over a broad range of temperatures for which the silicate network is frozen but the lithium ions can still be equilibrated. The lithium dynamics is studied via the analysis of different correlation functions. The activation energy for the lithium mobility agrees very well with experimental data. The correlation of the dynamics of adjacent ions is weak. At low temperatures the dynamics can be separated into local vibrational dynamics and hopping events between adjacent lithium sites. The derivative of the mean square displacement displays several characteristic time regimes. They can be directly mapped onto respective frequency regimes for the conductivity. In particular it is possible to identify time regimes dominated by localized dynamics and long-range dynamics, respectively. The question of time–temperature superposition is discussed for the mean square displacement and the incoherent scattering function.
BLIND SOURCE SEPARATION BASED ON DUAL ADAPTIVE CONTROL

ABSTRACT This paper presents a new method for Blind Source Separation (BSS) based on dual adaptive control, which allows successful separation of linear mixtures of independent source signals. The method reformulates a BSS problem to get a dual adaptive control problem. Then a Sigmoid MLP neural network is used to approximate the widesence-mixing matrix defined in the BSS problem. By solving the dual adaptive control problem, in which unknown parameters of the neural network are estimated by applying the Extended Kalman Filter, we then obtain the widesense-mixing matrix. Experimental results show that individual source signals can be separated effectively from the known linear mixture signals using this method. And faster convergence speed as well as good performance can be achieved.