Miracle-dz/UniFAR-FTUs huggingface dataset:
Excitatory, Inhibitory, and Structural Plasticity Produce Correlated Connectivity in Random Networks Trained to Solve Paired-Stimulus Tasks

The pattern of connections among cortical excitatory cells with overlapping arbors is non-random. In particular, correlations among connections produce clustering – cells in cliques connect to each other with high probability, but with lower probability to cells in other spatially intertwined cliques. In this study, we model initially randomly connected sparse recurrent networks of spiking neurons with random, overlapping inputs, to investigate what functional and structural synaptic plasticity mechanisms sculpt network connections into the patterns measured in vitro. Our Hebbian implementation of structural plasticity causes a removal of connections between uncorrelated excitatory cells, followed by their random replacement. To model a biconditional discrimination task, we stimulate the network via pairs (A + B, C + D, A + D, and C + B) of four inputs (A, B, C, and D). We find networks that produce neurons most responsive to specific paired inputs – a building block of computation and essential role for cortex – contain the excessive clustering of excitatory synaptic connections observed in cortical slices. The same networks produce the best performance in a behavioral readout of the networks’ ability to complete the task. A plasticity mechanism operating on inhibitory connections, long-term potentiation of inhibition, when combined with structural plasticity, indirectly enhances clustering of excitatory cells via excitatory connections. A rate-dependent (triplet) form of spike-timing-dependent plasticity (STDP) between excitatory cells is less effective and basic STDP is detrimental. Clustering also arises in networks stimulated with single stimuli and in networks undergoing raised levels of spontaneous activity when structural plasticity is combined with functional plasticity. In conclusion, spatially intertwined clusters or cliques of connected excitatory cells can arise via a Hebbian form of structural plasticity operating in initially randomly connected networks.
Efficient computation of minimal perturbation sets in gene regulatory networks

In the last few decades, technological and experimental advancements have enabled a more precise understanding of the mode of action of drugs with respect to human cell signaling pathways and have positively influenced the design of new drug compounds. However, as the design of compounds has become increasingly target-specific, the overall effects of a drug on adjacent cellular signaling pathways remain difficult to predict because of the complexity of the interactions involved. Off-target effects of drugs are known to influence their efficacy and safety. Similarly, drugs which are more target-specific also suffer from lack of efficacy because their scope might be too limited in the context of cellular signaling. Even in situations where the signaling pathways targeted by a drug are known, the presence of point mutations in some of the components of the pathways can render a therapy ineffective in a considerable target subpopulation. Some of these issues can be addressed by predicting Minimal Intervention Sets (MIS) of elements of the signaling pathways that when perturbed give rise to a pre-defined cellular phenotype. These minimal gene perturbation sets can then be further used to screen a library of drug compounds in order to discover effective drug therapies. This manuscript describes algorithms that can be used to discover MIS in a gene regulatory network that can lead to a defined cellular phenotype. Algorithms are implemented in our Boolean modeling toolbox, GenYsis. The software binaries of GenYsis are available for download from http://www.vital-it.ch/software/genYsis/.
If Words Could Dance: Moving from Body to Data through Kinesthetic Evaluation

The value of integrating the body and experience into technology has become an important goal in third wave HCI. One challenge in using experiential design methodologies is understanding how to transmit and apply the fullness of an experience into a computational system. We explore the relationship and meaning that can be created between kinesthetic experiences, words, and sensor data through the design of an interactive system that generates poetry from movement data. POEME (Portrayal of Ephemeral Movement Experiences) combines words into insightful, whimsical, and witty poetry that interprets one's movement. We refined our design of POEME through kinesthetically evaluating sensor data with the aid of visual analytic tools and confirmed the utility of these results through incorporating them into an effective machine learning system. Through this combination of visual analytics and kinesthetic evaluation, we contribute to the exploration of innovative design practices that both embody and evaluate movement interaction design strategies.
Free to Touch: A Portable Tactile Display For 3D Surface Texture Exploration

The development of successful tactile displays can be assisted by the capacity to assess their performance in integrated virtual reality applications. The design of single tactor or desktop tactile displays has been useful for scientific analysis of the mechanisms of touch. Nevertheless, it does not provide useful information about the quality of immersion in VR environments integrated with tactile feedback where user mobility and comfort are paramount. The present work introduces a new wireless portable tactile display for the finger. This new device demonstrates excellent levels of force output combined with good bandwidth in a configuration of a wearable 4times4 array of vertically moving tactors. The focus of this design is small size, comfort, mobility and ultimately integration into a complete Virtual Reality system for tactile surface texture exploration with 6DOF in the finger's work envelope
Characterization of CD4+ memory T cell responses directed against common respiratory pathogens in peripheral blood and lung.

BACKGROUND We investigated CD4(+) memory T cell responses to influenza virus (FLU), respiratory syncytial virus (RSV), and nontypeable Haemophilus influenzae (NTHi). METHODS The precursor frequencies of antigen-specific CD4(+) cells were determined by in vitro expansion of peripheral blood mononuclear cells from healthy individuals (n=9) and patients with chronic obstructive pulmonary disease (COPD; n=16). The expression of CD27 and CCR7 and the production of interferon (IFN)- gamma and interleukin-2 was measured directly ex vivo. Furthermore, the phenotypic and functional properties of CD4(+) T cells residing in the lung were analyzed and compared with those of circulating CD4(+)memory cells from the same donors (n=8). RESULTS FLU-, RSV-, and NTHi-specific CD4(+) memory T cells circulated at low frequencies in the peripheral blood of healthy individuals and patients. RSV- and NTHi-specific CD4(+) T cells had a memory phenotype with moderate to high CD27 and CCR7 expression. In contrast to the low frequencies of circulating FLU-specific CD4(+) T cells, we found an enrichment of differentiated CD4(+) FLU-specific cells and high IFN- gamma expression in CD4(+) memory cells in lung tissue. CONCLUSION No gross defects were found in circulating CD4(+) memory cells specific for pathogens associated with COPD. However, the large differentiated CD4(+) memory T cell pool residing in the lung may contribute to a large extent to local antiviral immunological protection.
Interactive Integrated Exploration and Management of Visualization Parameters

Visualization algorithms are parameterized to offer universality in terms of handling various data types, showing different aspects of the visualized data, or producing results useful for domain experts from different fields. Hence, input parameters are an important aspect of the visualization process. Their exploration and management are tasks which enable the visualization reusability, portability, and interdisciplinary communication. With increasing availability of visualization systems, which are suitable for a great variety of tasks, their complexity increases as well. This usually involves many input parameters necessary for the meaningful visualization of data. Multiple input parameters form parameter spaces which are too large to be explored by brute-force. Knowing the properties of a parameter space is often beneficial for improving data visualization. Therefore, it is important for domain experts utilizing data visualization to have tools for automatic parameter specification and for aiding the manual parameter setting. In this thesis, we review existing approaches for parameter-space visualization, exploration, and management. These approaches are used with a great variety of underlying algorithms. We focus on their applicability to visualization algorithms. We propose three methods solving specific problems arising from the fact that the output of a visualization algorithm is an image, which is challenging to process automatically and often needs to be analyzed by a human. First, we propose a method for the exploration of parameter-spaces of visualization algorithms. The method is used to understand effects of combinations of parameters and parts of the internal structure of the visualization algorithms on the final image result. The exploration is carried out by specifying semantics for localized parts of the visualization images in the form of positive and negative examples influenced by a set of input parameters or parts of the visualization algorithm itself. After specifying the localized semantics, global effects of the specified components of the visualization algorithm can be observed. The method itself is independent from the underlying algorithm. Subsequently, we present a method for managing image-space selections in visualizations and automatically link them with the context in which they were created. The context is described by the values of the visualization parameters influencing the output image. The method contains a mechanism for linking additional views to the selections, allowing the user an effective management of the visualization parameters whose effects are localized to certain areas of the visualizations. We present various applications for the method, as well as an implementation in the form of a library, which is ready to be used in existing visualization systems. Our third method is designed to integrate dynamic parameters stored during a multiplayer video game session by the individual participating players. For each player, the changing pa-
A software tool for automatic generation of neural hardware

Natural neural networks greatly benefit from their parallel structure that makes them fault tolerant and fast in processing the inputs. Their artificial counterpart, artificial neural networks, proved difficult to implement in hardware where they could have a similar structure. Although, many circuits have been developed, they usually present problems regarding accuracy, are application specific, difficult to produce and difficult to adapt to new applications. It is expected that developing a software tool that allows automatic generation of neural hardware while using high accuracy solves this problem and make artificial neural networks a step closer to the natural version. This paper presents a tool to respond to this need: A software tool for automatic generation of neural hardware. The software gives the user freedom to specify the number of bits used in each part of the neural network and programs the selected FPGA with the network. The paper also presents tests to evaluate the accuracy of the implementation of an automatically built neural network against Matlab.
Umami: a delicious flavor formed by convergence of taste and olfactory pathways in the human brain

Umami taste is produced by glutamate acting on a fifth taste system. However, glutamate presented alone as a taste stimulus is not highly pleasant, and does not act synergistically with other tastes (sweet, salt, bitter and sour). We show here that when glutamate is given in combination with a consonant, savory, odour (vegetable), the resulting flavor can be much more pleasant. Moreover, we showed using functional brain imaging with fMRI that the glutamate taste and savory odour combination produced much greater activation of the medial orbitofrontal cortex and pregenual cingulate cortex than the sum of the activations by the taste and olfactory components presented separately. Supralinear effects were much less (and significantly less) evident for sodium chloride and vegetable odour. Further, activations in these brain regions were correlated with the pleasantness and fullness of the flavor, and with the consonance of the taste and olfactory components. Supralinear effects of glutamate taste and savory odour were not found in the insular primary taste cortex. We thus propose that glutamate acts by the nonlinear effects it can produce when combined with a consonant odour in multimodal cortical taste‐olfactory convergence regions. We propose the concept that umami can be thought of as a rich and delicious flavor that is produced by a combination of glutamate taste and a consonant savory odour. Glutamate is thus a flavor enhancer because of the way that it can combine supralinearly with consonant odours in cortical areas where the taste and olfactory pathways converge far beyond the receptors.
Design Study on Green Sports Building Based on BIM

Under the background of sustainable development, the energy-consuming equipment and application mode of building system have changed to some degree. BIM's green building is the priority in design currently. BIM reintegrates the process of buildings design and the involved life cycle management of building is focused and affected by green build- ing design. Building information model covers the information of geometry, physics and topology. Geometrical informa- tion directly reflects the shape of buildings in three-dimensional space and physical information describes the physical property of various components, such as thermal coefficient, etc. And topological information includes the correlation among various components. However, due to the influence of multiple elements and lack of the support of appropriate platform, this method faces some difficulties and obstacles, such as weak compatibility and expandability, low integration level of information, etc., which results in many problems in sports building design. This paper will analyze design pattern in detail by studying the key points that BIM technology combines green building design.
Vertical Accuracy and Use of Topographic LIDAR Data in Coastal Marshes

Abstract Coastal marsh habitat and its associated vegetation are strongly linked to substrate elevation and local drainage patterns. As such, accurate representations of both the vegetation height and the surface elevations are requisite components for systematic analysis and temporal monitoring of the habitat. Topographic Light Detection and Ranging (LIDAR) data can provide high-resolution, high-accuracy elevation measurements of features both aboveground and at the surface. However, because of poor penetration of the laser pulse through the marsh vegetation, bare-earth LIDAR elevations can be markedly less accurate when compared with adjacent upland habitats. Consequently, LIDAR ground-elevation errors (i.e., standard deviation [SD] and bias) can vary significantly from the standard upland land-cover classes quoted in a typical data provider's quality-assurance report. Custom digital elevation model (DEM) generation techniques and point classification processes can be used to improve estimates of ground elevations in coastal marshes. The simplest of these methods is minimum bin gridding, which extracts the lowest elevation value included within a user-specified search window and assigns that value to the appropriate DEM grid cell. More complex point-to-point classification can be accomplished by enforcing stricter slope limits and increasing the level of smoothing. Despite lowering the spatial resolution of the DEM, the application of these techniques significantly improves the vertical accuracy of the LIDAR-derived bare-earth surfaces. By employing the minimum bin technique to the bare-earth classified LIDAR data, the overall bias in the resultant surface was reduced by 12 cm, and the vertical accuracy was improved by 8 cm when compared with the “as-received” data.
Fast Precomputed Ambient Occlusion for Proximity Shadows

Ambient occlusion is used widely for improving the realism of real-time lighting simulations. We present a new method for precomputed ambient occlusion where we store and retrieve unprocessed ambient-occlusion values in a three-dimensional grid. Our method is very easy to implement, has a reasonable memory cost, and has a rendering time independent of the complexity of the occluder or the receiving scene. This makes the algorithm highly suitable for games and other real-time applications.
Substitution Biases in Price Indexes during Transition

The rapidly changing environment of the transition may create special problems for calculation of index numbers that require a fixed basket of goods and retail outlets. Using referent-level data we find that fixed- weight Laspeyres index on average overstated cost of living increases by approximately 5 per cent a year when compared with a superlative index in the Czech Republic. This difference is smaller than might be expected given the large changes in relative prices that occurred during transition and suggests that consumer substitution impacts may have been largely offset by other factors, especially rising prices combined with increased consumption of some goods as artificial shortages under communism were removed. Indeed, in the period of greatest supply response to price liberalization, the Laspeyres index appears to understate increases in the cost of living.
WSD based on three short context methods

This article describes three methods for Word Sense Disambiguation using short context information. The first one is based on Semantic Classification Trees and the second and the third ones are a pattern-matching-like method. Their application within the SENSEVAL evaluation is shown here. Our participation in the ROMANSEVAL evaluation is described at the end of the article.
Estimating and rating the quality of optically character recognised text

The focus of this paper is on the quality of historical text digitised through optical character recognition (OCR) and how it affects text mining. We study the effect OCR errors have on named entity recognition (NER) and show that in a random sample of documents picked from several historical text collections, 30.6% of false negative commodity and location mentions and 13.3% of all manually annotated commodity and location mentions contain OCR errors. We introduce a simple method for estimating text quality of OCRed text and examine how well human raters can evaluate it. We also illustrate how automatic text quality estimation compares to manual rating with the aim of determining a quality threshold below which documents could potentially be discarded or would require extensive correction first. This work was conducted during the Trading Consequences project which focussed on text mining and visualisation of historical documents for the study of nineteenth century trade.
Epidemiology of occupational injury among cleaners in the healthcare sector.

BACKGROUND The cleaning profession has been associated with multiple ergonomic and chemical hazards which elevate the risk for occupational injury. AIMS This study investigated the epidemiology of occupational injury among cleaners in healthcare work settings in the Canadian province of British Columbia. METHODS Incidents of occupational injury among cleaners, resulting in lost time from work or medical care, over a period of 1 year in two healthcare regions were extracted from a standardized operational database and with person-years obtained from payroll data. Detailed analysis was conducted using Poisson regression modeling. RESULTS A total of 145 injuries were identified among cleaners, with an annual incidence rate of 32.1 per 100 person-years. After adjustment for age, gender, subsector, facility, experience and employment status, Poisson regression models demonstrated that a significantly higher relative risk (RR) of all injury, musculoskeletal injury and cuts was associated with cleaning work in acute care facilities, compared with long-term care facilities. Female cleaners were at a higher RR of all injuries and contusions than male cleaners. A lower risk of all injury and allergy and irritation incidents among part-time or casual workers was found. Cleaners with >10 years of experience were at significantly lower risk for all injury, contusion and allergy and irritation incidents. CONCLUSION Cleaners were found to be at an elevated risk of all injury categories compared with healthcare workers in general.
The Lived Experience of Nationally Certified Counselors who Attended an Eight-Day Native American Cultural Immersion Institute

iii ACKNOWLEDGEMENTS . iv DEDICATION . vi LIST OF TABLES . viii CHAPTER ONE: INTRODUCTION . 1 CHAPTER TWO: LITERATURE REVIEW . 21 CHAPTER THREE: METHODS . 39 CHAPTER FOUR: FINDINGS . 54 CHAPTER FIVE: DISCUSSION/IMPLICATIONS . 69 REFERENCES . 83
The use of supplementary immunisation activities to improve uptake of current and future vaccines in low-income and middle-income countries: a systematic review protocol

Introduction Immunisation coverage data in low-income and middle-income countries (LMICs) suggest that more strategies need to be implemented to achieve and sustain optimal vaccine uptake. Among possible strategies to improve immunisation coverage are supplementary immunisation activities (SIAs). We are therefore interested in conducting a systematic review to assess whether SIAs complement routine immunisation programmes to improve vaccination coverage and prevent disease outbreaks. Methods Our systematic review will focus on studies conducted in LMICs. With the help of an information specialist, we will search for eligible studies in PubMed, Web of Science, Scopus, Africa-Wide, Cochrane Library, WHOLIS, CINAHL, PDQ-Evidence as well as reference lists of relevant publications. Additionally, we will contact relevant organisations such as WHO and GAVI. Two authors will independently extract data from eligible studies and independently assess risk of bias by assessing the adequacy of study characteristics. The primary meta-analysis will use random effects models due to expected interstudies heterogeneity. Dichotomous data will be analysed using relative risk and continuous data using weighted mean differences (or standardised mean differences), both with 95% CIs. Discussion The findings from this systematic review will be discussed in the context of strengthening routine childhood immunisation services, routine adolescent immunisation services and introduction of future vaccines against tuberculosis and HIV/AIDS. Study strengths Unbiased selection of many studies conducted in different settings. This will strengthen the validity of the review results. Study limitations Heterogeneity of the study settings of the low-income, lower-middle-income and upper-middle-income countries as well as heterogeneity in study designs.