Miracle-dz/UniFAR-FTUs huggingface dataset:
Drift-free dynamic height sensor using MEMS IMU aided by MEMS pressure sensor

We demonstrate a low-cost, low-power, and small form factor solution to drift-free high-resolution vertical positioning by fusing MEMS accelerometers with MEMS barometric altimeter. In this system, the highly responsive but drift-prone aspect of the MEMS accelerometers is stabilized by barometric altimeter and high-fidelity height tracking is achieved. Typical vertical human movements such as walking up or down a staircase can be tracked in real-time with this system. The height tracking performance is benchmarked against a reference system using a tactical-grade IMU and an error analysis is performed.
Smart proxies in Java RMI with dynamic aspect-oriented programming

Java RMI extends Java with distributed objects whose methods can be called from remote clients. This abstraction is supported using statically-generated proxy objects on the client to hide network communication. One limitation of Java RMI is that these proxies can only forward method calls from client to server. Many applications can benefit from smart proxies that shift some application responsibilities to the client. Normally, developers must manually implement such proxies. This paper describes an aspect-oriented approach to creating smart proxies. This approach allows a server to extend an existing proxy with new capabilities at runtime. This approach is demonstrated with two examples.
Unique Properties of NMDA Receptors Enhance Synaptic Excitation of Radiatum Giant Cells in Rat Hippocampus

In the hippocampus, fast excitatory synaptic transmission of principal projection neurons is mediated by non-NMDA glutamate receptors, whereas NMDA glutamate receptors serve a slower modulatory role. We used the whole-cell patch-clamp technique in adult hippocampal slices to assess the role of NMDA receptors in synaptic excitation of a recently discovered excitatory projection neuron, the CA1 radiatum giant cell (RGC). Glutamatergic synaptic activation, even after blocking non-NMDA receptors, fired an NMDA receptor-dependent burst of action potentials in RGCs. In contrast, the contribution of NMDA receptors to synaptic activation of pyramidal cells (PCs) was minimal. Stimulation of the same synaptic inputs evoked greater than threefold larger EPSCs in RGCs than in PCs. Isolated NMDA receptor-mediated EPSCs were significantly less sensitive to blockade by extracellular Mg2+ and had slower decay kinetics in RGCs than in PCs. Thus, unique properties of synaptic NMDA receptors underlie enhanced synaptic excitability in a newly discovered excitatory hippocampal projection neuron.
Finding and Testing Network Communities by Lumped Markov Chains

Identifying communities (or clusters), namely groups of nodes with comparatively strong internal connectivity, is a fundamental task for deeply understanding the structure and function of a network. Yet, there is a lack of formal criteria for defining communities and for testing their significance. We propose a sharp definition that is based on a quality threshold. By means of a lumped Markov chain model of a random walker, a quality measure called “persistence probability” is associated to a cluster, which is then defined as an “-community” if such a probability is not smaller than . Consistently, a partition composed of -communities is an “-partition. ” These definitions turn out to be very effective for finding and testing communities. If a set of candidate partitions is available, setting the desired -level allows one to immediately select the -partition with the finest decomposition. Simultaneously, the persistence probabilities quantify the quality of each single community. Given its ability in individually assessing each single cluster, this approach can also disclose single well-defined communities even in networks that overall do not possess a definite clusterized structure.
Extracting programs from type class proofs

Standard presentations of type class translation schemes exhibit some surprising problems when translating Haskell 98 programs. We suggests ways how to fix these problems based on a formal framework for extracting programs from type class proofs. Our description includes type improvement and recursive dictionaries -- something which has not been formally studied before. Thus, we are able to advance the state of art of translating type classes and open up the possibility for new type class applications.
Reconstructive surgery of the penis

Purpose of review Diseases of the penis are common, and the aim now is the preservation of function and cosmesis of the penis using modern penile reconstructive techniques. Penile cancer, Peyronie's disease and trauma are the three pathologies assessed. Recent findings Modern conservative organ-sparing surgery in penile cancer has shown that good oncological control can be gained by 2 mm margins that allow preservation of sexual function. Early intervention in the traumatic penis gives better results whereas the Nesbit operation is still the gold standard for Peyronie's disease as the quest for an alternative graft to saphenous vein continues. Summary The current operations of choice in penile reconstruction are glansectomy and skin grafting to fashion a neoglans in penile cancer and the Nesbit operation or saphenous grafting for Peyronie's disease.
On improving the successful decoding performance of MDD based LT codes for erasure channels

In this paper, the performance of Luby Transform (LT) codes with modified degree distribution (MDD) is investigated for packet erasure channels (PEC). In LT codes, the number of degree-1 encoded symbols at the receiver plays a vital role in the successful recovery of all information symbols. Hence, this work aims to determine the optimal number of received encoded symbols needed to be degree-1 at the decoder for maximizing the decoding performance of LT codes. Simulation results demonstrate that significant improvements in successful decoding probability could be achieved by varying the proportion of degree-1 encoded symbols using MDD.
Maximum-likelihood DOA estimation by data-supported grid search

After reviewing the main existing methods for determining the maximum-likelihood (ML) estimates of the direction-of-arrival (DOA) parameters in array signal processing applications, we introduce a new conceptually simple and computationally effective approach that consists of maximizing the likelihood function (LF) over a set of points derived from the data. We show that the data-supported grid search of the LF provides a performance similar to that achieved by a genetic algorithm, but at a significantly lower computational cost. We use an ESPRIT-like algorithm to obtain the grid points with support in the data, although our approach is not limited to this choice.
MOSAIC: A Multiscale Model of Osteogenesis and Sprouting Angiogenesis with Lateral Inhibition of Endothelial Cells

The healing of a fracture depends largely on the development of a new blood vessel network (angiogenesis) in the callus. During angiogenesis tip cells lead the developing sprout in response to extracellular signals, amongst which vascular endothelial growth factor (VEGF) is critical. In order to ensure a correct development of the vasculature, the balance between stalk and tip cell phenotypes must be tightly controlled, which is primarily achieved by the Dll4-Notch1 signaling pathway. This study presents a novel multiscale model of osteogenesis and sprouting angiogenesis, incorporating lateral inhibition of endothelial cells (further denoted MOSAIC model) through Dll4-Notch1 signaling, and applies it to fracture healing. The MOSAIC model correctly predicted the bone regeneration process and recapitulated many experimentally observed aspects of tip cell selection: the salt and pepper pattern seen for cell fates, an increased tip cell density due to the loss of Dll4 and an excessive number of tip cells in high VEGF environments. When VEGF concentration was even further increased, the MOSAIC model predicted the absence of a vascular network and fracture healing, thereby leading to a non-union, which is a direct consequence of the mutual inhibition of neighboring cells through Dll4-Notch1 signaling. This result was not retrieved for a more phenomenological model that only considers extracellular signals for tip cell migration, which illustrates the importance of implementing the actual signaling pathway rather than phenomenological rules. Finally, the MOSAIC model demonstrated the importance of a proper criterion for tip cell selection and the need for experimental data to further explore this. In conclusion, this study demonstrates that the MOSAIC model creates enhanced capabilities for investigating the influence of molecular mechanisms on angiogenesis and its relation to bone formation in a more mechanistic way and across different time and spatial scales.
Evaluating the searching capabilities of e-commerce web sites in a non-English language: A Greek case study

Purpose – The purpose of this work in progress is to build a methodology for evaluating the searching capabilities of e‐shops. The emphasis of the evaluation is on ease of use and on the characteristics THAT influence the retrieval of products in non‐English queries.Design/methodology/approach – Initially an evaluation model is built in the paper, based on previous studies and on the attributes of worldwide search engines. Next, this model is applied in the evaluation of the searching effectiveness of Greek e‐shops with the aid of real users who define the importance of each criterion of the model. The results of this review are then presented and analysed.Findings – The methodological evaluation revealed several inefficiencies of the local search engines related to interface issues and most importantly to their searching effectiveness. The evaluation showed that the search engines do not take account of the morphology of the queries, which is significant in a non‐English and non‐Latin language like Greek.
The Potential of Hyperspectral Patterns of Winter Wheat to Detect Changes in Soil Microbial Community Composition

Reliable information on soil status and crop health is crucial for detecting and mitigating disasters like pollution or minimizing impact from soil-borne diseases. While infestation with an aggressive soil pathogen can be detected via reflected light spectra, it is unknown to what extent hyperspectral reflectance could be used to detect overall changes in soil biodiversity. We tested the hypotheses that spectra can be used to (1) separate plants growing with microbial communities from different farms; (2) to separate plants growing in different microbial communities due to different land use; and (3) separate plants according to microbial species loss. We measured hyperspectral reflectance patterns of winter wheat plants growing in sterilized soils inoculated with microbial suspensions under controlled conditions. Microbial communities varied due to geographical distance, land use and microbial species loss caused by serial dilution. After 3 months of growth in the presence of microbes from the two different farms plant hyperspectral reflectance patterns differed significantly from each other, while within farms the effects of land use via microbes on plant reflectance spectra were weak. Species loss via dilution on the other hand affected a number of spectral indices for some of the soils. Spectral reflectance can be indicative of differences in microbial communities, with the Renormalized Difference Vegetation Index the most common responding index. Also, a positive correlation was found between the Normalized Difference Vegetation Index and the bacterial species richness, which suggests that plants perform better with higher microbial diversity. There is considerable variation between the soil origins and currently it is not possible yet to make sufficient reliable predictions about the soil microbial community based on the spectral reflectance. We conclude that measuring plant hyperspectral reflectance has potential for detecting changes in microbial communities yet due to its sensitivity high replication is necessary and a strict sampling design to exclude other ‘noise’ factors.
Sensory-Motor Interactions for Vocal Pitch Monitoring in Non-Primary Human Auditory Cortex

The neural mechanisms underlying processing of auditory feedback during self-vocalization are poorly understood. One technique used to study the role of auditory feedback involves shifting the pitch of the feedback that a speaker receives, known as pitch-shifted feedback. We utilized a pitch shift self-vocalization and playback paradigm to investigate the underlying neural mechanisms of audio-vocal interaction. High-resolution electrocorticography (ECoG) signals were recorded directly from auditory cortex of 10 human subjects while they vocalized and received brief downward (−100 cents) pitch perturbations in their voice auditory feedback (speaking task). ECoG was also recorded when subjects passively listened to playback of their own pitch-shifted vocalizations. Feedback pitch perturbations elicited average evoked potential (AEP) and event-related band power (ERBP) responses, primarily in the high gamma (70–150 Hz) range, in focal areas of non-primary auditory cortex on superior temporal gyrus (STG). The AEPs and high gamma responses were both modulated by speaking compared with playback in a subset of STG contacts. From these contacts, a majority showed significant enhancement of high gamma power and AEP responses during speaking while the remaining contacts showed attenuated response amplitudes. The speaking-induced enhancement effect suggests that engaging the vocal motor system can modulate auditory cortical processing of self-produced sounds in such a way as to increase neural sensitivity for feedback pitch error detection. It is likely that mechanisms such as efference copies may be involved in this process, and modulation of AEP and high gamma responses imply that such modulatory effects may affect different cortical generators within distinctive functional networks that drive voice production and control.
JCAT: a platform for the TAC market design competition

Auctions, when well designed, result in desirable economic out-comes and have been widely used in solving real-world resource allocation problems, and in structuring stock or futures exchanges. The field of auction mechanism design has drawn much attention in recent years from economists, mathematicians, and computer scientists. In traditional auction theory, auctions are viewed as games of incomplete information and traditional analytic methods from game theory have been successfully applied to some simple types of auctions. However, the assumption of prior common knowledge in the incomplete information approach may not hold in some auctions, and computing analytic solutions may be infeasible in other auctions. Both of these problems hold in the case of continuous double auctions.
Fine pitch 3D-TSV based high frequency components for RF MEMS applications

The development of interconnections suitable for radio-frequency (RF) and millimeter-wave (mm-wave) applications is of foremost importance for the feasibility of high-quality substrate-integrated devices. For this purpose, we introduce and validate the technology to implement fine-pitch high-aspect ratio tungsten-filled through-silicon vias (W-TSVs) adapted for high-frequency applications. The presented technology is optimized for integration with RF MEMS, for which we propose a compatible fabrication process flow. We designed and characterized RF test structures to assess the quality of the W-TSVs and their suitability for radio-frequency integrated circuits (RFIC) applications, showing low insertion loss for TSV in coplanar waveguides (CPW) and high-performance wideband mm-wave antennas.
Enclave-Based Privacy-Preserving Alignment of Raw Genomic Information: Information Leakage and Countermeasures

Recent breakthroughs in genomic sequencing led to an enormous increase of DNA sampling rates, which in turn favored the use of clouds to efficiently process huge amounts of genomic data. However, while allowing possible achievements in personalized medicine and related areas, cloud-based processing of genomic information also entails significant privacy risks, asking for increased protection. In this paper, we focus on the first, but also most data-intensive, processing step of the genomics information processing pipeline: the alignment of raw genomic data samples (called reads) to a synthetic human reference genome. Even though privacy-preserving alignment solutions (e.g., based on homomorphic encryption) have been proposed, their slow performance encourages alternatives based on trusted execution environments, such as Intel SGX, to speed up secure alignment. Such alternatives have to deal with data structures whose size by far exceeds secure enclave memory, requiring the alignment code to reach out into untrusted memory. We highlight how sensitive genomic information can be leaked when those enclave-external alignment data structures are accessed, and suggest countermeasures to prevent privacy breaches. The overhead of these countermeasures indicate that the competitiveness of a privacy-preserving enclave-based alignment has yet to be precisely evaluated.
Fabrication of discrete carbon nanotube based nano-scaled force sensors

We present a novel fabrication technique for discrete and released carbon nanotube based nano-mechanical force sensors. The simple fabrication technique involves pre-patterned coordinate markers used to align the device design to pre-deposited single walled carbon nanotubes (SWCNT): atomic force microscope (AFM) images are recorded to determine spatial orientation of each discrete nanotube to be integrated in a nano-scaled force sensor. Electron beam (e-beam) lithography is subsequently used to pattern the metallic electrodes for the nanoscale structures. Diluted HF etching followed by critical point drying finalizes the nano-sized device fabrication. We use discrete, highly purified and chemically stable CNT as active elements to reliably withstand HF release, rather than CNT grown by chemical vapor deposition (CVD). We show AFM and FESEM images to prove the successful realization and release of SWCNT embedded in true NEMS.
Innovation Clusters in Technological Systems: A Network Analysis of 15 OECD Countries for the Middle '90s

The paper aims at investigating how innovations cluster in different technological systems (TSs) when their “techno-economic", rather than “territorial" space is considered. Innovation clusters of economic sectors are identified by applying network analysis to the intersectoral R&D flows matrices of 15 OECD countries in the middle '90s. Different clusterization models are first tested in order to detect the way sectors group on the basis of the embodied R&D flows they exchange. Actual clusters are then mapped in the different TSs by looking for intersectoral relationships which can be qualified to constitute “reduced-TSs" (ReTSs). In all the 15 TSs investigated the technoeconomic space appears organized in hierarchies, along which its constitutive sectors group into clusters with different density and composition. Once ReTSs are looked for, the 15 TSs display highly heterogeneous structures, but with some interesting similarity on the basis of which different clusters of TSs can be identified in turn.
Knowledge Management Enablers, Processes, and Organizational Performance: An Integrative View and Empirical Examination

Knowledge is recognized as an important weapon for sustaining competitive advantage and many companies are beginning to manage organizational knowledge. Researchers have investigated knowledge management factors such as enablers, processes, and performance. However, most current empirical research has explored the relationships between these factors in isolation. To fill this gap, this paper develops a research model that interconnects knowledge management factors. The model includes seven enablers: collaboration, trust, learning, centralization, formalization, T-shaped skills, and information technology support. The emphasis is on knowledge creation processes such as socialization, externalization, combination, and internalization. To establish credibility between knowledge creation and performance, organizational creativity is incorporated into the model. Surveys collected from 58 firms were analyzed to test the model. The results confirmed the impact of trust on knowledge creation. The information technology support had a positive impact on knowledge combination only. Organizational creativity was found to be critical for improving performance; neglecting ideas can undermine a business. The results may be used as a stepping stone for further empirical research and can help formulate robust strategies that involve trade-offs between knowledge management enablers.
Short-term effects of wildfire on Patagonian headwater streams

In March–April 2015, the El Cristo fire burned 1228 ha of mixed Nothofagus forest in Los Alerces National Park (Argentine Patagonia). We compared physicochemical variables and community structure of burned and unburned headwater streams. Sampling began shortly after the fire was extinguished and comprised periodic water quality assessments and four visits to collect periphyton and invertebrate samples (May, August, October and December). Water temperature, total dissolved solids, total suspended solids and specific conductance were significantly higher in burned sites, whereas nutrient and oxygen concentrations exhibited no major differences. Chlorophyll a (used as a surrogate for autotrophic periphyton biomass) also did not differ significantly. Macroinvertebrate richness, abundance and diversity showed no differences across sites, but taxonomic composition and densities of sensitive taxa were markedly lower at burned streams. Oligochaetes and amphipods, however, were significantly more abundant in the disturbed reaches. Analysis of functional feeding groups revealed that the relative abundances of shredders and collector-filterers were lower at burned sites, possibly reflecting a shift in detrital input.
Improved decoding of attentional selection in a cocktail party environment with EEG via automatic selection of relevant independent components

Recently it has been shown to be possible to ascertain which speaker a subject is attending to in a cocktail party environment from single-trial (~60s) electroencephalography (EEG) data. The attentional selection of most of subjects could be decoded with a very high accuracy (>90%). However, the performance of many subjects fell below what would be required for a potential brain computer interface (BCI). One potential reason for this is that activity related to the stimuli may have a lower signal-to-noise ratio on the scalp for some subjects than others. Independent component analysis (ICA) is a commonly used method for denoising EEG data. However, its effective use often requires the subjective choice of the experimenter to determine which independent components (ICs) to retain and which to reject. Algorithms do exist to automatically determine the reliability of ICs, however they provide no information as to their relevance for the task at hand. Here we introduce a novel method for automatically selecting ICs which are relevant for decoding attentional selection. In doing so, we show a significant increase in classification accuracy at all test data durations from 60s to 10s. These findings have implications for the future development of naturalistic and user-friendly BCIs, as well as for smart hearing aids.