Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy efficient E-Textile based portable keyboard

We have created sensor architecture, data collection and processing techniques for an E-Textile wireless keyboard. We leverage the inherent properties of E-Textiles to produce optimized architecture for energy efficient sensing. Novel techniques such as one where each sensor senses several events (activations of different keys) and each event is sensed by three sensors and flexible interleaved sensing and data processing result in up to a factor of 30 energy reduction over the system where each key is sensed by exactly one sensor. We build the keyboard and test it on multiple subjects.
Zygomycotic Mediastinal Lymphadenitis in Beef Cattle with Ruminal Tympany

ABSTRACT A 9-month-old steer was autopsied due to recurrent ruminal tympany. A macroscopic examination found an enlarged caudal mediastinal lymph node, and a section of the lymph node revealed necrosis with marked calcification, similar to tuberculous lymphadenitis. Histopathologically, the lesion consisted of multiple coagulative necrotic foci and fibrosis with macrophage, lymphocyte, eosinophil and multinucleated giant cell infiltration. Non-uniform width hyphae were detected in the necrotic area and within the cytoplasm of the multinucleated giant cells, and they were found to be anti-Rhizopus arrhizus antibody positive in an immunohistochemical examination. Therefore, the steer was diagnosed with necrotic caudal mediastinal lymphadenitis due to zygomycetes infection, and inhibition of eructation by the enlarged lymph node was the likely cause of the ruminal tympany.
Applicability of simple power analysis to stream ciphers constructed using multiple LFSRs

In recent years, the hardware implementation of stream ciphers has attracted the interest of many designers, mainly due to their low implementation area on a chip. However, to date, in comparison with block ciphers, side channel attacks have not been extensively analyzed for their applicability to stream cipher hardware implementations. However it has been shown that simple power analysis (SPA) attacks are applicable to stream ciphers based on one linear feedback shift register. In this paper, we extend the SPA method to stream ciphers with multiple linear feedback shift registers and multiple linear feedback shift registers with irregular clocking. Then we apply the proposed method to the well-known stream ciphers E0 and LILI-128.
Inductively coupled plasma deep etching of InP/InGaAsP in Cl2/CH4/H2 based chemistries with the electrode at 20 °C

A Cl2/CH4/H2 inductively coupled plasma process without additional heating or wafer bonding is developed for the InP/InGaAsP material system. Vertical and smooth sidewalls can be observed in the scanning electron microscope images. The main factors of etch rate, selectivity, and sidewall roughness are analyzed relative to the gas concentration in a full factorial design of the experimental procedure. Under optimized conditions, an etch depth of more than 3 μm with smooth and vertical sidewalls can be obtained. A strong indication of a passivation effect of CH4 is obtained.
Micro- and Nanoengineering Approaches to Developing Gradient Biomaterials Suitable for Interface Tissue Engineering

This chapter discusses various techniques such as micro- and nanotechnologies, used in the fabrication of gradient biomaterials or scaffolds suitable for engineering tissue interfaces and how the gradient features of the biomaterials influence cellular behaviors such as adhesion, migration, differentiation, and heterotypic interactions during tissue organization. In addition, an overview of various gradient biomaterials and their physical, chemical, and biological classifications is provided. Finally, potential challenges and future directions of the emerging field of interface tissue engineering (ITE) are discussed.
How Did We Get Into This Mess? Isolating Fault- Inducing Inputs to SDN Control Software

Software bugs are inevitable in software-defined networking (SDN) control planes, and troubleshooting is a tedious, time-consuming task. In this paper we discuss how one might improve SDN network troubleshooting by presenting a technique, retrospective causal inference, for automatically identifying a minimal sequence of inputs responsible for triggering a given bug in the control software. Retrospective causal inference works by iteratively pruning inputs from the history of the execution, and coping with divergent histories by reasoning about the functional equivalence of events. We apply retrospective causal inference to three open source SDN control platforms—Floodlight, POX, and NOX—and illustrate how our technique found minimal causal sequences for the bugs we encountered.
Introduction Live Cell Imaging of Yeast

The development of cloning vectors for green fluorescent protein (GFP) and the simplicity of yeast reverse genetics allow straightforward labeling of yeast proteins in living cells. Budding and fission yeast are therefore attractive organisms in which to study dynamic cellular processes such as growth, cell division, and morphogenesis using live cell fluorescence microscopy. This article focuses on methods to culture, mount, and observe budding yeast cells using three-dimensional (3D) microscopy, but themethods are broadly applicable to other types of cells and other imaging techniques. The emphasis is on 3D imaging, because yeast cells are roughly spherical, andmost organelles in yeast move in three dimensions. Three-dimensional imaging also makes it possible to apply image restorationmethods (e.g., deconvolution) to obtain sharper images with better definition. This is important, because yeast cells are small (haploid Saccharomyces cerevisiae cells have a diameter of ~4–5 μm) relative to the resolution of even the best optical microscope (~0.25 μm).
Tunable terahertz plasmonic filter based on a substrate of photo-induced phase-transition vanadium dioxide film

A tunable terahertz (THz) filter is reported, which was based on surface plasmonic effects from a subwavelength copper hole array, and the tunability was made possible by a substrate of phase-transition vanadium dioxide (VO2) film. The phase transition of the VO2 film was induced by femtosecond laser pulses and the modulation depth of the THz pulse peak by the VO2 film was measured by THz time-domain spectroscopy to be 80% under optimal fabrication conditions. The change of the conductivity of the substrate film could lead to a shift of the center resonance frequency from 1.33 to 0.92 THz, a relative shift of 30.8%. This tunable THz filter holds great promise for various applications.
Development of Welding Distortion Analysis Method Using Residual Strain as Boundary Condition

There are two ways of conventional thermal distortion analysis. One is thermal elastoplastic analysis and the other is equivalent forces method based on inherent strain. The former needs exorbitant analysis time, while the latter cannot obtain stress results and requires more time with loads modeling on curved plates. To solve those time-consuming problems, a new kind of thermal distortion analysis method was developed. In this method, inherent strains are devised to be used as direct input factors as boundary conditions. Suggested analysis method was already adopted at welding distortion analysis of large hull block, which was considered as impossible.
Austenitic-ferritic stainless steel containing niobium

The austenitic-ferritic stainless steels present a better combination of mechanical properties and stress corrosion resistance than the ferritic or austenitic ones. The microstructures of these steels depend on the chemical compositions and heat treatments. In these steels, solidification starts at about 1450oC with the formation of ferrite, austenite at about 1300oC and sigma phase in the range of 600 to 950oC.The latter undertakes the corrosion resistance and the toughness of these steels. According to literature, niobium has a great influence in the transformation phase of austenitic-ferritic stainless steels. This study evaluated the effect of niobium in the microstructure, microhardness and charge transfer resistance of one austenitic-ferritic stainless steel. The samples were annealed at 1050oC and aged at 850oC to promote formation of the sigma phase. The corrosion testes were carried out in artificial saliva solution. The addition of 0.5% Nb in the steel led to the formation of the Laves phase.This phase, associated with the sigma phase, increases the hardness of the steel, although with a reduction in the values of the charge transfer resistance.
Symbiotic Evolution of Neural Networks in Sequential Decision Tasks

Sequential decision tasks appear in many practical situations ranging from robot navigation to stock market trading. Because of the complexity of such tasks, it is often difficult to perceive the direct consequences of individual decisions and even harder to generate examples of correct behavior. Consequently, difficult decision problems such as routing traffic, autonomous control, and resource allocation are often unautomated or are only semi-automated using "rule-of-thumb" strategies or simple heuristics. This dissertation proposes a general methodology for automating these tasks using techniques from machine learning. Specifically, this research studies the combination of evolutionary algorithms and artificial neural networks to learn and perform difficult decision tasks. Evolutionary algorithms provide an efficient search engine for building decision strategies and require only minimal reinforcement or direction from the environment. Neural networks provide an efficient storage mechanism for the decision policy and can generalize experiences from one situation to another. The learning system developed in this dissertation called SANE contains an evolutionary algorithm specifically tailored to sequential decision learning. Populations evolve faster than previous methods and rarely converge on suboptimal solutions. SANE is extensively evaluated and compared to existing decision learning systems and other evolutionary algorithms. SANE is shown to be significantly faster, more robust, and more adaptive in almost every situation. Moreover, SANE's efficient searches return more profitable decision strategies. The flexibility and scope of SANE is demonstrated in two real-world applications. First, SANE significantly improves the play of a world champion Othello program. Second, SANE successfully forms neural networks that guide a robot arm to target objects while avoiding randomly placed obstacles. The contributions of this research are twofold: a novel integration of evolutionary algorithms and neural networks and an efficient system for learning decision strategies in complex problems.
On J. Goodman's comment to "Language Trees and Zipping"

Motivated by the recent submission to cond-mat archives by J. Goodman (cond-mat/0202383) whose results apparently discredit the approach we have proposed in a recent paper (Phys. Rev. Lett., 88, 048702 (2002), cond-mat/0108530), we report the results of the same experiment performed by Goodman using three different data compression schemes. As a matter of fact the three zippers display the same efficiency Goodman obtained using Naive Bayesian Methods and not, as Goodman claimed, an efficiency three times smaller. We point out the question of the extreme generality of approaches based on data compression techniques and we list a large range of potential applications, including those of interest for the physics community.
Optical properties of Saharan dust aerosol and contribution from the coarse mode as measured during the Fennec 2011 aircraft campaign

Abstract. New in-situ aircraft measurements of Saharan dust originating from Mali, Mauritania and Algeria taken during the Fennec 2011 aircraft campaign over a remote part of the Sahara Desert are presented. Size distributions extending to 300 μm are shown, representing measurements extending further into the coarse mode than previously published for airborne Saharan dust. A significant coarse mode was present in the size distribution measurements with effective diameter ( d eff ) from 2.3 to 19.4 μm and coarse mode volume median diameter ( d vc ) from 5.8 to 45.3 μm. The mean size distribution had a larger relative proportion of coarse mode particles than previous aircraft measurements. The largest particles (with d eff > 12 μm, or d vc > 25 μm) were only encountered within 1 km of the ground. Number concentration, mass loading and extinction coefficient showed inverse relationships to dust age since uplift. Dust particle size showed a weak exponential relationship to dust age. Two cases of freshly uplifted dust showed quite different characteristics of size distribution and number concentration. Single Scattering Albed (SSA) values at 550 nm calculated from the measured size distributions revealed high absorption ranging from 0.70 to 0.97 depending on the refractive index. SSA was found to be strongly related to d eff . New instrumentation revealed that direct measurements, behind Rosemount inlets, overestimate SSA by up to 0.11 when d eff is greater than 2 μm. This is caused by aircraft inlet inefficiencies and sampling losses. Previous measurements of SSA from aircraft measurements may also have been overestimates for this reason. Radiative transfer calculations indicate that the range of SSAs during Fennec 2011 can lead to underestimates in shortwave atmospheric heating rates by 2.0 to 3.0 times if the coarse mode is neglected. This will have an impact on Saharan atmospheric dynamics and circulation, which should be taken into account by numerical weather prediction and climate models.
Transmitting Hierarchical Aggregation Information Using RTCP Protocol

Summary The current state of the RFC 3550 RTP/RTCP standard is not optimal for large-scale streaming sessions employing sourcespecific multicast and is currently the subject of research in many research laboratories. The most promising optimization for the RTP/RTCP protocol seems to be hierarchical aggregation [2], [3], [5], [6], [10], [11]. However, hierarchical aggregation has not yet completely solved the problem of hierarchical structure organization. The answer can be a Tree Transmission Protocol (TTP), which seems to be flexible and powerful but quite demanding to implement. This text deals with a different approach that tries to maximally utilize the features of current standards.
How Safe Is It to Transplant Organs from Deceased Donors with Primary Intracranial Malignancy? An Analysis of UK Registry Data

Patients dying from primary intracranial malignancy are a potential source of organs for transplantation. However, a perceived risk of tumor transfer to the organ recipient has limited their use. We evaluated the risk of tumor transmission by reviewing the incidence in patients transplanted in the UK. Information from the UK Transplant Registry was combined with that from the national cancer registries of England, Wales and Northern Ireland to identify all organ donors between 1985 and 2001 inclusive with a primary intracranial malignancy and to identify the occurrence of posttransplant malignancy in the recipients of the organs transplanted. Of 11 799 organ donors in the study period, 179 were identified as having had a primary intracranial malignancy, including 33 with high‐grade malignancy (24 grade IV gliomas and 9 medulloblastomas). A total of 448 recipients of 495 organs from 177 of these donors were identified. No transmission of donor intracranial malignancy occurred. Organs from patients dying from primary intracranial malignancy, including those with high‐grade tumors, should be considered for transplantation and the small risk of tumor transmission should be balanced against the likely mortality for potential recipients who remain on the transplant waiting list.
Automated gating of flow cytometry data via robust model‐based clustering

The capability of flow cytometry to offer rapid quantification of multidimensional characteristics for millions of cells has made this technology indispensable for health research, medical diagnosis, and treatment. However, the lack of statistical and bioinformatics tools to parallel recent high‐throughput technological advancements has hindered this technology from reaching its full potential. We propose a flexible statistical model‐based clustering approach for identifying cell populations in flow cytometry data based on t‐mixture models with a Box–Cox transformation. This approach generalizes the popular Gaussian mixture models to account for outliers and allow for nonelliptical clusters. We describe an Expectation‐Maximization (EM) algorithm to simultaneously handle parameter estimation and transformation selection. Using two publicly available datasets, we demonstrate that our proposed methodology provides enough flexibility and robustness to mimic manual gating results performed by an expert researcher. In addition, we present results from a simulation study, which show that this new clustering framework gives better results in terms of robustness to model misspecification and estimation of the number of clusters, compared to the popular mixture models. The proposed clustering methodology is well adapted to automated analysis of flow cytometry data. It tends to give more reproducible results, and helps reduce the significant subjectivity and human time cost encountered in manual gating analysis. © 2008 International Society for Analytical Cytology
A Trainable Document Summarizer Using Bayesian Classifier Approach

This paper presents an investigation into machine learning approach for document summarization. A major challenge related to document summarization is selection of features and learning patterns of these features which determines what information in source should be included in the summary. Instead of selecting and combining these features in ad hoc manner which would require readjustment for each new genre, natural choice is to use machine learning techniques. This is the basis for trainable machine learning approach to summarization. We briefly discuss design, implementation and performance of Bayesian classifier approach for document summarization.
LPS-Enhanced Glucose-Stimulated Insulin Secretion Is Normalized by Resveratrol

Low-grade inflammation is seen with obesity and is suggested to be a mediator of insulin resistance. The eliciting factor of low-grade inflammation is unknown but increased permeability of gut bacteria-derived lipopolysaccharides (LPS) resulting in endotoxemia could be a candidate. Here we test the effect of LPS and the anti-inflammatory compound resveratrol on glucose homeostasis, insulin levels and inflammation. Mice were subcutaneously implanted with osmotic mini pumps infusing either low-dose LPS or saline for 28 days. Half of the mice were treated with resveratrol delivered through the diet. LPS caused increased inflammation of the liver and adipose tissue (epididymal and subcutaneous) together with enlarged spleens and increased number of leukocytes in the blood. Resveratrol specifically reduced the inflammatory status in epididymal fat (reduced expression of TNFa and Il1b, whereas the increased macrophage infiltration was unaltered) without affecting the other tissues investigated. By LC-MS, we were able to quantitate resveratrol metabolites in epididymal but not subcutaneous adipose tissue. LPS induced insulin resistance as the glucose-stimulated insulin secretion during an oral glucose tolerance test was increased despite similar plasma glucose level resulting in an increase in the insulinogenic index (IGI; delta0-15insulin / delta0-15glucose) from 13.73 to 22.40 pmol/mmol (P < 0.001). This aberration in insulin and glucose homeostasis was normalized by resveratrol. In conclusion: Low-dose LPS enhanced the glucose-stimulated insulin secretion without affecting the blood glucose suggesting increased insulin resistance. Resveratrol restored LPS-induced alteration of the insulin secretion and demonstrated anti-inflammatory effects specifically in epididymal adipose tissue possibly due to preferential accumulation of resveratrol metabolites pointing towards a possible important involvement of this tissue for the effects on insulin resistance and insulin secretion.
THE CHEMISTRY AND BIOLOGY OF GOLD NANOPARTICLE-MEDIATED PHOTOTHERMAL THERAPY: PROMISES AND CHALLENGES

Under laser radiation, cells labeled with gold nanoparticles (AuNPs) are believed to suffer thermal damage due to the transfer of the absorbed light from the AuNPs to the cells. This process, which involves complex mechanisms such as the rapid electron–phonon decay in the AuNPs, followed by phonon–phonon relaxation, culminates in the localized heating of both the AuNPs and the cells, setting the rational for the use of these nanostructures, under laser light, in cancer photothermal therapy (PTT). Here, we discuss the chemical and biological aspects of this promising new therapeutic approach, including the advantages over conventional cancer therapies and the challenges that scientists still need to overcome to progress toward translation research.
Peer-to-peer architecture for real-time strategy MMOGs with intelligent cheater detection

Massively multi-player online games (MMOGs) are having increasing success, because they allow players to explore huge virtual worlds and to interact in many different ways, either cooperating or competing. To implement MMOGs that support several million users, a decentralized communication infrastructure is much better than a centralized one. Unfortunately, decentralization introduces many security problems, allowing dishonest players to apply cheating strategies, if appropriate countermeasures are not implemented. In this paper we illustrate our framework for real-time strategy MMOGs, called PATROL, focusing on the AI-based strategies it adopts to detect cheating attempts.
A SIP of CoFee : A Sample of Interesting Productions of Conversational Feedback

Feedback utterances are among the most frequent in dialogue. Feedback is also a crucial aspect of linguistic theories that take social interaction, involving lan- guage, into account. This paper introduces the corpora and datasets of a project scru- tinizing this kind of feedback utterances in French. We present the genesis of the cor- pora (for a total of about 16 hours of tran- scribed and phone force-aligned speech) involved in the project. We introduce the resulting datasets and discuss how they are being used in on-going work with focus on the form-function relationship of conver- sational feedback. All the corpora created and the datasets produced in the frame- work of this project will be made available for research purposes.