Miracle-dz/UniFAR-FTUs huggingface dataset:
Tactile sensing for robotic applications

Robotic devices – limited to the structured environment of manufacturing plants until few years ago – are slowly making way into human life, which has led to the emergence of interaction and learning issues in robots. Such issues are important for future robot to be able to learn autonomously and to interact safely with the environment i.e. without causing any harm to it or to the objects with which it is interacting. In this context, it becomes important to study the ways and means of robot’s interaction with the environment. Humans interact and explore the environment through five main sense modalities viz. touch, vision, hearing, olfaction and taste. Loss of any of these modalities will result in the incomplete information about the environment. Irrespective of their importance with respect to each other, the study of their individual contribution in collecting information from environment is important for improving the sensing capabilities of any future robotic system. This chapter provides an overview of tactile sensing in robotics. This chapter is an attempt to answer three basic questions: • What is meant by Tactile Sensing? • Why Tactile Sensing is important? • How Tactile Sensing is achieved? The chapter is organized to sequentially provide the answers to above basic questions. Tactile sensing has often been considered as force sensing, which is not wholly true. In order to clarify such misconceptions about tactile sensing, it is defined in section 2. Why tactile section is important for robotics and what parameters are needed to be measured by tactile sensors to successfully perform various tasks, are discussed in section 3. An overview of `How tactile sensing has been achieved’ is given in section 4, where a number of technologies and transduction methods, that have been used to improve the tactile sensing capability of robotic devices, are discussed. Lack of any tactile analog to Complementary Metal Oxide Semiconductor (CMOS) or Charge Coupled Devices (CCD) optical arrays has often been cited as one of the reasons for the slow development of tactile sensing vis-a-vis other sense modalities like vision sensing. Our own contribution – development of tactile sensing arrays using piezoelectric polymers and involving silicon micromachining is an attempt in the direction of achieving tactile analog of CMOS optical arrays. The first phase implementation of these tactile sensing arrays is discussed in section 5. Section 6 concludes the chapter with a brief discussion on the present status of tactile sensing and the challenges that remain to be solved. O pe n A cc es s D at ab as e w w w . in te ch w eb . o rg
Exploration du concept d ’ Infrastructures en tant que Services avec HIPerNET

With the expansion and convergence of communication and computing, dynamic provisioning of customized networking and processing infrastructures, as well as resource virtualization, are appealing concepts and technologies. Therefore, new models and tools are needed to allow users to create, trust and enjoy such on-demand virtual infrastructures within a wide area context. This research report presents the HIPerNET framework that we are designing and developing for creating, managing and controlling virtual infrastructures in the context of high-speed Internet. The key idea of this proposal is the combination of networkand system-virtualization associated with controlled resource reservation to provide fully isolated environments. HIPerNET’s motivations and design principles are presented. We then examine specifically how this framework handles the virtual infrastructures, called Virtual Private eXecution Infrastructures (VPXI). To help specifying customized isolated infrastructures, HIPerNET relies on VXDL, a language for VPXI description and modeling which considers end-host resource as well as the virtual network topology interconnecting them, including virtual routers. We exemplify the VPXI specification, allocation and execution using a real large-scale distributed medical application. Experimental results obtained within the Grid’5000 testbed are presented and analyzed. Key-words: HIPerNET, Virtual Infrastructures, IaaS, Network Virtualization, VXDL, VPXI, Provisioning, Isolation Exploring the Virtual Infrastructures as a Service concept with HIPerNET 3
How to Live with Uncertainties: Exploiting the Performance Benefits of Self-Timed Logic In Synchronous Design

Ultra low power digital systems are key for any future wireless sensor nodes but also inside nomadic embedded systems (such as inside the digital front end of software defined radios). These systems require the highest possible energy efficiency of logic, which can only be achieved by operating in moderate inversion. Unfortunately, when operating near the threshold voltage, transistors become highly sensitive to process variations, thereby increasing leakage currents and complicating timing closure. Rather than pursuing a worst-case design approach for dealing with these uncertainties, we present a hybrid self-timed/synchronous approach. It will be demonstrated on the VEX VLIW core designed for ultra low-power operations. Experimental results of our approach demonstrate performance benefits up to 2times and significant energy savings at low throughput rates.
Split Personalities: Tax Law and Critical Race Theory

Unmasking racial and ethnic issues in the federal tax laws is a difficult and arduous task. Very few scholars have attempted to publish in this area. I understand why that phenomenon has occurred. First, tax law has a myth about it that suggests that it is different than other areas of the law. My tax colleague at Cincinnati, Professor Paul Caron, has eloquently referred to this phenomenon as "tax myopia," and observed that there are "serious consequences caused by the.myth that tax law is somehow different from other areas of the law. "' One such consequence is perpetuating the myth that tax law is neutral and objective. To the extent that tax law is assumed to be different, it is not examined the way other areas of the law have been examined through racial and ethnic lenses. To the extent that tax law is assumed to be different, any disparate impact based upon race or ethnicity will continue unabated. My scholarship is dedicated to forever eradicating the belief that tax law is somehow different, that it has no differing impact based upon race, ethnicity, or any other characteristic.
An Integrated Framework for Assessment of Hybrid Water Supply Systems

Urban water managers around the world are adopting decentralized water supply systems, often in combination with centralized systems. While increasing demand for water arising from population growth is one of the primary reasons for this increased adoption of alternative technologies, factors such as climate change, increased frequency of extreme weather events and rapid urbanization also contribute to an increased rate of adoption of these technologies. This combination of centralized-decentralized water systems approach is referred to as “hybrid water supply systems” and is based on the premise that the provision of alternative water sources at local scales can both extend the capacity of existing centralized water supply infrastructures, and improve resilience to variable climatic conditions. It is important to understand, however, that decentralized water production and reuse may change the flow and composition of wastewater and stormwater, thereby potentially also having negative impacts on its effectiveness and performance. This paper describes a framework to assess the interactions between decentralized water supply systems and existing centralized water servicing approaches using several analytical tools, including water balance modelling, contaminant balance modelling and multi-criteria decision analysis. The framework enables the evaluation of impacts due to change in quantity and quality of wastewater and stormwater on the existing centralized system arising from the implementation of hybrid water supply systems. The framework consists of two parts: (1) Physical system analysis for various potential scenarios and (2) Ranking of Scenarios. This paper includes the demonstration of the first part of the framework for an area of Melbourne, Australia by comparing centralized water supply scenario with a combination of centralized water supply and reuse of treated waste water supply scenario.
Mixed-Mode simulation of single event upsets in modern SiGe BiCMOS mixed-signal circuits

The latest enhancements to CFDRC NanoTCAD mixed-mode simulator, combining 3D physics-based device models and advanced circuit compact models (VBIC, Mextram) for advanced bipolar devices, as well as unique mixed-mode coupling of 3D TCAD models with the Cadence Spectre circuit simulator, have enabled simulations and in-operation analysis of ionizing radiation single event effects (SEEs) in modern high-speed SiGe BiCMOS technologies and integrated circuits. An example of simulation of SEEs affecting digital output of a 7.2GHz mixed-signal circuit are presented. Our mixed-mode modeling results compare very well with experimental data.
Developmental Origins of Chronic Kidney Disease: Should We Focus on Early Life?

Chronic kidney disease (CKD) is becoming a global burden, despite recent advances in management. CKD can begin in early life by so-called “developmental programming” or “developmental origins of health and disease” (DOHaD). Early-life insults cause structural and functional changes in the developing kidney, which is called renal programming. Epidemiological and experimental evidence supports the proposition that early-life adverse events lead to renal programming and make subjects vulnerable to developing CKD and its comorbidities in later life. In addition to low nephron endowment, several mechanisms have been proposed for renal programming. The DOHaD concept opens a new window to offset the programming process in early life to prevent the development of adult kidney disease, namely reprogramming. Here, we review the key themes on the developmental origins of CKD. We have particularly focused on the following areas: evidence from human studies support fetal programming of kidney disease; insight from animal models of renal programming; hypothetical mechanisms of renal programming; alterations of renal transcriptome in response to early-life insults; and the application of reprogramming interventions to prevent the programming of kidney disease.
Microbial production of scleroglucan and downstream processing

Synthetic petroleum-based polymers and natural plant polymers have the disadvantage of restricted sources, in addition to the non-biodegradability of the former ones. In contrast, eco-sustainable microbial polysaccharides, of low-cost and standardized production, represent an alternative to address this situation. With a strong global market, they attracted worldwide attention because of their novel and unique physico-chemical properties as well as varied industrial applications, and many of them are promptly becoming economically competitive. Scleroglucan, a β-1,3-β-1,6-glucan secreted by Sclerotium fungi, exhibits high potential for commercialization and may show different branching frequency, side-chain length, and/or molecular weight depending on the producing strain or culture conditions. Water-solubility, viscosifying ability and wide stability over temperature, pH and salinity make scleroglucan useful for different biotechnological (enhanced oil recovery, food additives, drug delivery, cosmetic and pharmaceutical products, biocompatible materials, etc.), and biomedical (immunoceutical, antitumor, etc.) applications. It can be copiously produced at bioreactor scale under standardized conditions, where a high exopolysaccharide concentration normally governs the process optimization. Operative and nutritional conditions, as well as the incidence of scleroglucan downstream processing will be discussed in this chapter. The relevance of using standardized inocula from selected strains and experiences concerning the intricate scleroglucan scaling-up will be also herein outlined.
The Frequency of Difficult Instances for MaxClique Approximation Algorithms

The MaxClique optimization problem cannot be approximated in polynomial-time within a ratio of n if NP 6= ZPP or within n if P 6= NP (H̊astad, 1999). We investigate the frequency with which approximation algorithms cannot achieve these ratios. Our results include the following for any ǫ > 0. 1. If NP 6= RP, then any polynomial-time approximation algorithm fails to approximate within n on a nonsparse set of instances. 2. If NP has positive p-dimension, then for some δ > 0, any 2 δ -time approximation algorithm fails to approximate within n on an exponentially dense set of instances. 3. If NP has positive p-dimension and strong pseudorandom generators exist, then for some δ > 0, any 2 δ -time approximation algorithm fails to approximate within n on an exponentially dense set of instances.
Unaccountable: How the Accounting Profession Forfeited a Public Trust

This is a vivid snapshot of the role of accounting firms in the twenty first century. The pitfalls of the flawed U.S. auditing system crystallized in the Enron/Andersen debacle and other audit failures have prompted the nation's investors to ask, time and time again: Where were the auditors? In "Unaccountable", business journalist Mike Brewster explores the fascinating transformation of CPAs from independent voices on behalf of the shareholder to Corporate America's best friend. He examines the implications of this shift for investors, the industry, and the economy. Brewster's brash style and his incisive examination of the key issues facing the profession make for fascinating reading as he explains how the profession became one of the most universally respected in the Western world, only to throw away this public trust for double digit growth and power. Brewster questions the dubious practices of the nation's leading accounting firms, including: their history of providing consulting services to the same firms they audit; their push in the 1990s to open investment banks and law firms; their unprecedented political and lobbying power; and their tremendous influence in the boardroom. "Unaccountable" turns the heat on an already beleaguered profession, but also shows how the best and brightest within the profession can still save the day by implementing reform and serving not their paymaster, but the investing public. Mike Brewster (New York, NY) is the coauthor of "King of Capital: Sandy Weill and the Making of Citigroup" (0 471 21416 7) and a respected writer, editor, and financial services professional. Formerly the editor of "LeadersOnline", Brewster spent seven years as the communications director at KPMG.
Early sensing of Yersinia pestis airway infection by bone marrow cells

Bacterial infection of the lungs triggers a swift innate immune response that involves the production of cytokines and chemokines that promote recruitment of immune cells from the bone marrow (BM) into the infected tissue and limit the ability of the pathogen to replicate. Recent in vivo studies of pneumonic plague in animal models indicate that the pulmonary pro-inflammatory response to airway infection with Yersinia pestis is substantially delayed in comparison to other pathogens. Consequently, uncontrolled proliferation of the pathogen in the lungs is observed, followed by dissemination to internal organs and death. While the lack of an adequate early immune response in the lung is well described, the response of BM-derived cells is poorly understood. In this study, we show that intranasal (i.n.) infection of mice with a fully virulent Y. pestis strain is sensed early by the BM compartment, resulting in a reduction in CXCR4 levels on BM neutrophils and their subsequent release into the blood 12 hours (h) post infection. In addition, increased levels of BM-derived hematopoietic stem and progenitor cells (HSPC) were detected in the blood early after infection. Mobilization of both immature and mature cells was accompanied by the reduction of BM SDF-1 (CXCL-12) levels and the reciprocal elevation of SDF-1 in the blood 24 h post infection. RT-PCR analysis of RNA collected from total BM cells revealed an early induction of myeloid-associated genes, suggesting a prompt commitment to myeloid lineage differentiation. These findings indicate that lung infection by Y. pestis is sensed by BM cells early after infection, although bacterial colonization of the BM occurs at late disease stages, and point on a potential cross-talk between the lung and the BM at early stages of pneumonic plague.
Theory of the Conditional Affine Term Risk of Jumps: an Analytical Single Event Q-Jump Distribution is Derived and Tested

A new transition probability function, the Q-jump, is derived and developed for the pricing of term risk due to jumps. The dynamic of the risk depends on the single jump with dispersion in the autocorrelation over conditional intertemporal variations in the time direction. The new Q-distribution is found by Fourier analysis, definition of marginals in frequency, and a new Nikon Radodym scaling in log time. The Q-jump model is first tested by an evaluation of its properties, then application to the term risk properties of yield curves and credit spreads. Q-jump models are shown capable of providing the required economic insights required of term risk if it is to justify the market risk (systematic risk over time) in jumps. As a single jump model, the Q-jump model solves the incomplete markets problem in Lévy processes, and avoids the need for the use, generally in current models, of arbitrary modelling assumptions (mean reversion and square root diffusion, etc). Unlike current models, the amounts and patterns of risk premiums are commensurate with large market premiums in term risk. Finally, it is noted that the Q-jump model measures risk orthogonally to Gaussian risk, in the time direction. The model is well suited to pricing conditional intertemporal variations, essentially in underlyings that are rates, as a class. In combination with the Gaussian Wiener models, therefore, it should cover the full range of market risks.
Cortical gray matter loss in treatment-naïve alcohol dependent individuals.

BACKGROUND Most studies of the impact of alcohol dependence on the brain have examined individuals in treatment. Such samples represent a small proportion of alcoholics in the general population. Such samples may embody a bias (Berkson's fallacy) if the association between variables (for example, alcoholism and cortical gray matter loss) differs between the population of alcoholics in treatment and alcoholics in the general population. Our objective was to determine if treatment-naïve alcoholics show structural brain changes versus controls and to compare our findings with reports evaluating alcoholic samples drawn from treatment populations. METHODS Structural MRI was used to assess whole brain and regional volumes of cortical gray matter and white matter in 24 young to middle-aged treatment-naïve alcohol-dependent males versus 17 controls. RESULTS Cortical gray matter volumes in alcohol-dependent individuals were negatively associated with age and lifetime duration of alcohol use (which were highly confounded). These subjects showed reduced whole brain (p < 0.05), prefrontal (p < 0.01), and parietal (p < 0.05) cortical gray matter compared with controls. White matter and temporal cortex, tissues that usually show volume reductions in samples drawn from treatment, did not differ between treatment-naïve alcoholics and controls (all p > 0.40). CONCLUSIONS Our findings are consistent with the hypothesis that structural brain changes in treatment-naïve alcoholics are less severe than those reported in clinical samples of alcoholics, perhaps due to less concomitant psychopathology and a reduced severity of alcoholism in treatment-naïve alcoholics. However, caution must be taken when comparing our findings with results from clinical samples, as we did not directly compare treatment-naïve alcoholics with treated alcoholics and our treatment-naïve sample tended to be younger than the (clinical) samples reported in the literature. Nevertheless, we suggest that most of the reports of the central nervous system consequences of alcoholism may not accurately describe the majority of alcoholic-dependent individuals.
TOWARDS AUTOMATIC GENERATION OF PLANS FOR AUTOMATED ASSEMBLY

The present CAD/CAM systems still lack the appropriate CAE component that would allow more efficient assembly planning in the effort to integrate the product design, assembly system design, assembly device programming and assembly execution. The problem is related to both the complexity and incompleteness of the planning methodology, and the lack of the algorithmized planning elements. The previous explorations often concentrated on particular planning elements such as assembly sequence, neglecting the urge of integral and a more general approach. Furthermore, they sometimes pose tedious requirements on the user, causing him/her to focus more on the planning method than on the planning goal. The paper presents a CAD-based prototyping system for the generation of plans for automated assembly. It uses many relevant well-established concepts in the assembly planning field and proposes a few new ones (especially regarding assembly process space structuring), trying to achieve the highest possible level of aut.
Optimized Kernel Machine for Cancer Classification Using Gene Expression Data

— The cancer classification using gene expression data has shown to be very useful for cancer diagnose and prediction. However, the nature of very high dimensionality and relatively small sample size associated with the gene expression data make the tasks of classification quite challenging. In this paper, we present a new approach, which is based on optimizing the kernel function, to improve the performances of the classifiers in classifying gene expression data. Aiming to increase the class separability of the data, we utilize a more flexible kernel function model, the data-dependent kernel, as the objective kernel to be optimized. The experimental results show that using the optimized kernel usually results in a substantial improvement for the K-nearest-neighbor (KNN) and support vector machine (SVM) in classifying gene expression data.