Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of Degradation Using Reflectance Spectroscopy (Postprint)

Abstract : A semi-classical model of the reflectance of a complex material is modeled. Model selection techniques using this reflectance model are developed to detect molecular vibration modes measured using infrared spectroscopy. An inverse problem methodology is then used to ascertain the underlying vibrational modes associated with varying concentrations of different chemical species. These two techniques are developed to characterize the extent of material degradation through the detection of spectra associated with the chemical processes underlying the degradation process. These methods are validated using data from samples of ceramic matrix composites. The samples considered were exposed to varying amounts of thermal treatment to ascertain the effectiveness of these methods to detect degradation.
On The Development of Low-power MAC Protocol for WBANs

Current advances in wireless communication, microelectronics, semiconductor technologies, and intelligent sensors have contributed to the development of unobtrusive WBANs. These networks provide long term health monitoring of patients without any constraint in their normal activities. Traditional MAC protocols do not accommodate the assorted WBAN traffic requirements in a power efficient manner. In this paper, we present a brief discussion on the development process of a low power MAC protocol for WBANs. We observe the behavior of a beacon-enabled IEEE 802.15. 4 for on-body sensor networks. We further propose a low power technique called traffic based wakeup mechanism for a WBAN that exploits the traffic patterns of the BAN Nodes to ensure power efficient and reliable communication.
Coordinating the Interruption of People in Human-Computer Interaction

People have cognitive limitations that make them sensitive to interruption. These limitations can cause people to make serious mistakes when they are interrupted. Unfortunately, interruption of people is a side effect of systems that allow users to delegate tasks to active background processes, like intelligent software agents. Delegation carries the costs of supervision, and that often includes being interrupted by subordinates. User interfaces for these kinds of computer systems must be designed to accommodate people’s limitations relative to being interrupted. A theory-based taxonomy of human interruption was used to identify the four known methods for deciding when to interrupt people. An experiment was conducted with 36 subjects to compare these four different design approaches within a common context. The results show important differences between the four user interface design solutions to the problem of interrupting people in human-computer interaction (HCI).
Furosemide effect on isolated perfused tubules.

BURG, MI. , L. STONER, J. CARDINAL, AND N. GREEN. Furosemide effect on isolated perfused tubules. Am. J. Physiol. 225(l): 119-124. 1973 . -Proximal convoluted tubules, thick ascending limbs of Henle’s loop, and cortical collecting tubules were dissected from rabbit kidneys, and perfused in vitro. The effect of the diuretic agent furosemide on electrolyte transport and electrical potential difference (PD) in these segments was determined. Furosemide in the lumen (lo-” to lOA M) inhibited active Cl transport in the thick ascending limbs of Henle’s loop with resultant decrease in net NaCl absorption and electrical PD. Concentrations of furosemide as high as 10 -4 M in the bath had little effect. Furosemide at low4 M also had no definite effect on proximal convoluted tubules and cortical collecting tubules whether placed in the bath and/or the lumen. We conclude that the principal renal action of this drug is to inhibit active Cl transport in the thick ascending limb of Henle’s loop.
Stepwise re-engineering and development of object-oriented database schemata

We present a general approach for re-engineering of object-oriented database schemata. The approach consists of four dependent steps: (1) description of the data within the underlying basic data format, (2) application of a powerful semantic data model in order to construct a semantic database schema, (3) translation of the achieved schema into a general object model, and (4) implementation of the object schema in a concrete object-oriented database system. As an instantiation of this general procedure we report on a case study carried out in an industrial context where an extended entity-relationship model was used as the semantic data model and ObjectStore as the implementation platform.
Asynchronous gate-diffusion-input (GDI) circuits

Novel gate-diffusion input (GDI) circuits are applied to asynchronous design. A variety of GDI implementations are compared with typical CMOS asynchronous circuits. Dynamic GDI state holding elements are 2/spl times/ smaller than CMOS C-elements, 30% faster, and consume 85% less power, but certain CMOS elements are preferred when static storage is called for. A GDI bundled controller outperforms CMOS on all accounts, having 1/3 the delay and requiring less than half the area while consuming the same power. A combination CMOS-GDI circuit provides the optimal solution for qDI combinational logic, saving 1/3 the power, half the area, and 10% in delay relative to a CMOS implementation. GDI circuits also provide some measure of enhanced hazard tolerance.
A mixture Cox-Logistic model for feature selection from survival and classification data

This paper presents an original approach for jointly fitting survival times and classifying samples into subgroups. The Coxlogit model is a generalized linear model with a common set of selected features for both tasks. Survival times and class labels are here assumed to be conditioned by a common risk score which depends on those features. Learning is then naturally expressed as maximizing the joint probability of subgroup labels and the ordering of survival events, conditioned to a common weight vector. The model is estimated by minimizing a regularized log-likelihood through a coordinate descent algorithm. Validation on synthetic and breast cancer data shows that the proposed approach outperforms a standard Cox model or logistic regression when both predicting the survival times and classifying new samples into subgroups. It is also better at selecting informative features for both tasks.
A Hybrid Choice Model that Uses Actual and Ordered Attribute Value Information

In the usual multinomial choice model, consumers choose to use “actual value” information; that is, utilities are continuous functions of product attributes (e.g., choices depend on actual magnitudes of price differences). The authors propose an alternative model in which consumers use only “ordered value” information; that is, utilities are functions only of the relative orderings of the attributes' values across alternatives (e.g., choices depend only on the price ordering and not on actual prices). The ordered value model is attractive because it fits well with psychological evidence that consumers often favor decision mechanisms that are cognitively less demanding. Using a supermarket shopper panel data set, the authors evaluate four models in which (1) all consumers use actual values; (2) all consumers use ordered values; (3) some consumers use actual values all the time, and some consumers use ordered values all the time; and (4) all consumers use both actual values and ordered values but with different propensities. In the analysis, the ordered value model finds stronger support than the actual value model: Model 1 outperforms Model 2; in the two hybrid choice models (Models 3 and 4), ordered value processing is more prevalent than actual value processing. These results suggest that consumers in some product categories engage more heavily in ordered value processing than in actual value processing.
Liowsn Project: An Operating System Remastered for Works with Simulation of Wireless Sensor Networks

Since the last decade, the area of Wireless Sensor Networks (WSN) is a field search on the rise. Due to its high mobility and scalability in several areas, acting on functions of sensing, monitoring, tracking, control and maintenance, WSNs are increasingly attracting researchers for the study. With the advent of computer simulations, it has been eliminated, in part by the necessity of obtaining real sensors, which because of its implementation cost, eventually disabling the initial analysis and further tests with these networks. Considering that most of these simulator programs are native from GNU/Linux, expertises are needed to implement these tools in the operating system, which can be a problem. This paper presents the Liowsn project, which is a GNU/Linux operating system remastered with several classic tools of literature already installed and configured, and it has been proposed in order to achieve a higher speed in the implementation process of the simulation environment to study this type of network.
In Vitro Endothelial Differentiation of Long‐Term Cultured Murine Embryonic Yolk Sac Cells Induced by Matrigel

The yolk sac of an early mammalian embryo contains progenitors of hematopoietic cells and vascular endothelial cells. We established a cell line, YS4, from murine embryonic yolk sac 10 years ago. The line has been successfully cultured since then. To determine whether these long‐term cultured yolk sac cells still have the potential to differentiate into endothelial cells, an in vitro model of yolk sac cell differentiation into tube‐forming endothelial cells was established in the present study by culturing the yolk sac cells on basement membrane proteins (Matrigel). The results indicate that upon plating onto Matrigel, YS4 cells attach quickly, align in tandem, and form a complete network of capillary structures within 12 h. By using antibodies against the known components of Matrigel in a tube formation inhibition assay, we found that extracellular matrix proteins such as laminin, collagen IV, vitronectin, and fibronectin are the most important components in the Matrigel which induce the yolk sac cells to undergo endothelial differentiation. New basement membrane proteins are also required for the endothelial differentiation process, as indicated by the fact that base membrane protein synthesis inhibitor, D609, can block the differentiation process. Furthermore, our experiments revealed the involvement of several signal transduction pathways, such as protein kinase A, C and protein tyrosine kinase in this differentiation process.
Reducing livestock emissions from Cattle farming Mini-paper – Precision Livestock Farming

While livestock production forms one of the pillars of the EU food industry it faces many societal challenges, not least from the rising demand for meat protein, increasingly stringent environmental regulations, coupled with the falling numbers of young farmers entering the industry. Environmental degradation as a result of the releases of harmful substances in the atmosphere can ultimately lead to regional tensions and violence, affecting economic policies and farmers’ income.
Tumorgrafts as In Vivo Surrogates for Women with Ovarian Cancer

Purpose: Ovarian cancer has a high recurrence and mortality rate. A barrier to improved outcomes includes a lack of accurate models for preclinical testing of novel therapeutics. Experimental Design: Clinically relevant, patient-derived tumorgraft models were generated from sequential patients and the first 168 engrafted models are described. Fresh ovarian, primary peritoneal, and fallopian tube carcinomas were collected at the time of debulking surgery and injected intraperitoneally into severe combined immunodeficient mice. Results: Tumorgrafts demonstrated a 74% engraftment rate with microscopic fidelity of primary tumor characteristics. Low-passage tumorgrafts also showed comparable genomic aberrations with the corresponding primary tumor and exhibit gene set enrichment of multiple ovarian cancer molecular subtypes, similar to patient tumors. Importantly, each of these tumorgraft models is annotated with clinical data and for those that have been tested, response to platinum chemotherapy correlates with the source patient. Conclusions: Presented herein is the largest known living tumor bank of patient-derived, ovarian tumorgraft models that can be applied to the development of personalized cancer treatment. Clin Cancer Res; 20(5); 1288–97. ©2014 AACR.
Use of the Magnetic Field for Improving Gyroscopes' Biases Estimation

An accurate orientation is crucial to a satisfactory position in pedestrian navigation. The orientation estimation, however, is greatly affected by errors like the biases of gyroscopes. In order to minimize the error in the orientation, the biases of gyroscopes must be estimated and subtracted. In the state of the art it has been proposed, but not proved, that the estimation of the biases can be accomplished using magnetic field measurements. The objective of this work is to evaluate the effectiveness of using magnetic field measurements to estimate the biases of medium-cost micro-electromechanical sensors (MEMS) gyroscopes. We carry out the evaluation with experiments that cover both, quasi-error-free turn rate and magnetic measurements and medium-cost MEMS turn rate and magnetic measurements. The impact of different homogeneous magnetic field distributions and magnetically perturbed environments is analyzed. Additionally, the effect of the successful biases subtraction on the orientation and the estimated trajectory is detailed. Our results show that the use of magnetic field measurements is beneficial to the correct biases estimation. Further, we show that different magnetic field distributions affect differently the biases estimation process. Moreover, the biases are likewise correctly estimated under perturbed magnetic fields. However, for indoor and urban scenarios the biases estimation process is very slow.
Joint feature selection and hierarchical classifier design

This work presents a method for improving classifier accuracy through joint feature selection and hierarchical classifier design with genetic algorithms. The hierarchical classifier divides the classification problem into a set of smaller problems using multiple feature-selected classifiers in a tree configuration to separate the data into progressively smaller groups of classes. This allows the use of more specific feature sets for each set of classes. Several existing performance measures for evaluating the feature sets are investigated, and a new measure, count-based RELIEF is proposed. The joint feature selection and hierarchical classifier design method is tested on two artificial data sets. Results indicate that the feature selected hierarchical classifiers are able to achieve better accuracy than a non-hierarchical classifier using feature selection alone. The newly proposed performance measure is also tested and shown to provide a better indication of classifier performance than existing methods.
On Demand Response Management Performance Optimization for Microgrids Under Imperfect Communication Constraints

A perfect bidirectional communication network is a common assumption in smart grids. However, it is unrealistic, especially in the neighborhood area network of microgrids. Due to the channel fading, large volumes of transmission data, and considerable communication cost, the imperfect communications affect the system performance directly. In this paper, we consider the uncertainty of imperfect communications in both supply and demand sides, which affects the microgrid system performance in terms of the packet loss ratio of the power demand data transmission and the forecasting accuracy ratio of the renewable energy generation. We analyze the impacts of imperfect communications on the demand response management (DRM) performance under the real-time pricing scheme. An optimization problem is formulated first to maximize the DRM performance of the microgrid system. As these impacts can be mitigated by using sufficient spectrum resources, we then propose a spectrum resource allocation scheme that considers different characteristics of transmission data and system communication cost to balance the tradeoff between the DRM performance and the incurred communication cost. We introduce a joint optimization problem that not only maximizes the DRM performance but also minimizes the communication cost. Simulation results reveal the impacts of imperfect communications on the DRM performance and power price, and the efficiency of the proposed optimization problems.
Elimination of Aggressive Behavior in Male Mice Lacking Endothelial Nitric Oxide Synthase

Male mice with targeted deletion of the gene encoding the neuronal isoform of nitric oxide synthase (nNOS(-/-)) display increased aggressive behavior compared with wild-type (WT) mice. Specific pharmacological inhibition of nNOS with 7-nitroindazole also augments aggressive behavior. We report here that male mice with targeted deletion of the gene encoding endothelial NOS (eNOS(-/-)) display dramatic reductions in aggression. The effects are selective, because an extensive battery of behavioral tests reveals no other deficits. In the resident-intruder model of aggression, resident eNOS(-/-) males show virtually no aggression. Latency for aggression onset is 25-30 times longer in eNOS(-/-) males compared with WT males in the rare instances of aggressive behaviors. Similarly, a striking lack of aggression is noted in tests of aggression among groups of four mice monitored in neutral cages. Although eNOS(-/-) mice are hypertensive ( approximately 14 mmHg blood pressure elevation), hypertension does not appear responsible for the diminished aggression. Reduction of hypertension with hydralazine does not change the prevalence of aggression in eNOS(-/-) mice. Extensive examination of brains from eNOS(-/-) male mice reveals no obvious neural damage from chronic hypertension. In situ hybridization in WT animals reveals eNOS mRNA in the brain associated exclusively with blood vessels and no neuronal localizations. Accordingly, vascular eNOS in the brain appears capable of influencing behavior with considerable selectivity.
Discovering word senses from text

Inventories of manually compiled dictionaries usually serve as a source for word senses. However, they often include many rare senses while missing corpus/domain-specific senses. We present a clustering algorithm called CBC (Clustering By Committee) that automatically discovers word senses from text. It initially discovers a set of tight clusters called committees that are well scattered in the similarity space. The centroid of the members of a committee is used as the feature vector of the cluster. We proceed by assigning words to their most similar clusters. After assigning an element to a cluster, we remove their overlapping features from the element. This allows CBC to discover the less frequent senses of a word and to avoid discovering duplicate senses. Each cluster that a word belongs to represents one of its senses. We also present an evaluation methodology for automatically measuring the precision and recall of discovered senses.
Effects of LWR environments on fatigue life of carbon and low-alloy steels

SME Boiler and Pressure Vessel Code provides construction of nuclear power plant components. Figure I-90 Appendix I to Section III of the Code specifies fatigue design curves for structural materials. While effects of environments are not explicitly addressed by the design curves, test data suggest that the Code fatigue curves may not always be adequate in coolant environments. This paper reports the results of recent fatigue tests that examine the effects of steel type, strain rate, dissolved oxygen level, strain range, loading waveform, and surface morphology on the fatigue life of A 106-Gr B carbon steel and A533-Gr B low-alloy steel in water.
A Novel Automated Microscopy Platform for Multiresolution Multispectral Early Detection of Lung Cancer Cells in Bronchoalveolar Lavage Samples

Lung cancer is the deadliest form of cancer mainly because of the absence of reliable early diagnostic protocols. Therefore, there is increasing interest in the development of novel diagnostic noninvasive technologies that may improve the early detection of the disease. Bronchoscope-guided bronchoalveolar lavage (BAL) is a minimally invasive diagnostic technique that is based on the extraction and analysis of cellular material from the bronchial epithelium of patients that present suspicious lung masses on low-dose screening X-ray-computed tomography images. Together with a novel staining technique that combines immunophenotyping of a lung cancer biomarker with fluorescent in situ hybridization of genetically abnormal DNA loci, BAL promises a powerful early diagnostic tool for lung carcinomas. The sensitivity of this method, however, is highly dependent on the pathologist's ability to reliably and repeatedly examine thousands of cells under the microscope. This is an extremely labor-intensive and error-prone task. We have developed a multiscale multidimensional integrated microscopy computer-aided detection platform that autonomously scans and analyzes BAL samples. In this paper, we describe its software architecture and validate the specific image analysis protocols that are developed for this particular application.
Shareholder Risk and Returns in Union and Nonunion Firms

This study examines shareholder risk and rates of return in union and nonunion companies in 1973–87. Shareholder risk declined with the extent of union coverage in the 1970s, and returns were lower among highly unionized companies than among other companies during the late 1970s and early 1980s. Union-nonunion differences in risk were small and insignificant by the mid-1980s, however, and there was no systematic relationship between union coverage and shareholder returns in the mid-1970s or mid-1980s. Finally, firms with relatively low rates of return to investors in 1977–82 tended to experience larger than average declines in firm-level union coverage between 1977 and 1987. As a partial explanation for these findings, the authors posit a relationship between shareholder risk and the differential use of COLAs across industries and time.
Interferometric Techniques for Investigating Growth and Dissolution of Crystals in Solutions

Although conventional optical interferometry has lower resolution for the observation of crystal surfaces than scanning probe microscopy (SPM) such as AFM or STM, new advanced interferometers have attained nearly the same resolution as scanning microscopes. The advantages of using optical interferometers can be summarized as follows: (1) they can be used not only at room temperature but also at elevated temperatures as high as 1800K; (2) their ability to resolve time is much better, making them more suitable for observing rapidly growing crystals; and (3) they observe surfaces non‐destructively, making in situ observation possible if the solution or the melt is transparent. In this lecture, the key points of observing growth steps and measuring growth rate will be introduced together with recently developed interferometry such as Laser Confocal Phase‐Shift Interferometry (LCPSI). Using this technique, mono‐molecular growth steps of proteins and some other crystals can be observed with accurate step height.
A test generation tool for specifications in the form of state machines

This paper describes a software tool, TAG (test automatic generation), that automatically generates test cases for an FSM specification. It implements the so-called transition identification approach for test derivation, and may output test cases in the form of an SDL skeleton. The description focuses on the functions of the tool and the methods implemented in the tool, especially, the heuristic solution to the minimization of state identification sequences.