Miracle-dz/UniFAR-FTUs huggingface dataset:
Science and Technology of Shape-Memory Alloys: New Developments

The martensitic (also called displacive or diffusionless) transformation is a classical cooperative phenomenon in solids similar to ferromagnetism. Although the displacement of each atom is not large, the transformation results in a macroscopic change in shape, since all of the atoms move in the same direction in a domain or variant. As a result, unique properties arise, such as the shape-memory effect and superelasticity, whose characteristics are quite distinct from those of normal metals and alloys. Because of these unique properties, shape-memory alloys (SMAs) have been used as new functional materials for applications such as couplings, sensors, actuators, and antennas for cellular phones. In this issue of MRS Bulletin , we present an overview of recent progress in this field. In this introductory article, we discuss fundamental notions, such as the mechanism of the shape-memory effect, the martensitic transformation, and superelasticity, along with examples of applications and other important recent topics not treated in the following articles. It will be shown that progress in the science and technology of shape-memory alloys has been achieved by the side-by-side development of fundamentals and applications.
A PPM Gaussian pulse generator for ultra-wideband communications

A Gaussian pulse generator incorporating a pulse position modulator for use in an ultra-wideband or impulse radio system is described. The pulse generator is preceded by a programmable pulse-position modulator and consists of a cascade of complex first-order systems, which, in turn, are made up of differential pairs employing partial positive feedback. The resulting PPM Gaussian pulse generator has been designed to be implemented in AMS 0.35/spl mu/m CMOS IC technology. Simulations predict the correct operation of the circuit for supply voltages of 3.3Vand a power consumption of 95mW. The output monocycle indeed approximates a Gaussian monocycle very well and has a pulse duration of about 230ps. Proper modulation of the pulse in time is confirmed.
Label Dependencies using a Tree-structured Hierarchy

While topic models can discover patterns of word usage in large corpora, it is difficult to meld this unsupervised structure with noisy, human-provided labels, especially when the label space is large. In this paper, we present a model—Label to Hierarchy (L2H)—that can induce a hierarchy of user-generated labels and the topics associated with those labels from a set of multi-labeled documents. The model is robust enough to account for missing labels from untrained, disparate annotators and provide an interpretable summary of an otherwise unwieldy label set. We show empirically the effectiveness of L2H in predicting held-out words and labels for unseen documents. 1 Understanding Large Text Corpora through Label Annotations Probabilistic topic models [4] discover the thematic structure of documents from news, blogs, and web pages. Typical unsupervised topic models such as latent Dirichlet allocation [7, LDA] uncover topics from unannotated documents. In many settings, however, documents are also associated with additional data, which provide a foundation for joint models of text with continuous response variables [6, 48, 27], categorical labels [37, 18, 46, 26] or link structure [9]. This paper focuses on additional information in the form of multi-labeled data, where each document is tagged with a set of labels. These data are ubiquitous. Web pages are tagged with multiple directories,1 books are labeled with different categories or political speeches are annotated with multiple issues.2 Previous topic models on multi-labeled data focus on a small set of relatively independent labels [25, 36, 46]. Unfortunately, in many real-world examples, the number of labels— from hundreds to thousands—is incompatible with the independence assumptions of these models. In this paper, we capture the dependence among the labels using a learned tree-structured hierarchy. Our proposed model, L2H—Label to Hierarchy—learns from label co-occurrence and word usage to discover a hierarchy of topics associated with user-generated labels. We show empirically that L2H can improve over relevant baselines in predicting words or missing labels in two prediction tasks. L2H is designed to explicitly capture the relationships among labels to discover a highly interpretable hierarchy from multi-labeled data. This interpretable hierarchy helps improve prediction performance and also provides an effective way to search, browse and understand multi-labeled data [17, 10, 8, 12]. ∗Part of this work was done while the first author interned at Facebook. Open Directory Project (http://www.dmoz.org/) Policy Agenda Codebook (http://policyagendas.org/)
A 32x32-pixel array with in-pixel photon counting and arrival time measurement in the analog domain

A Time-to-Amplitude Converter (TAC) with embedded analog-to-digital conversion is implemented in a 130-nm CMOS imaging technology. The proposed module is conceived for Single-Photon Avalanche Diode imagers and can operate both as a TAC or as an analog counter, thus allowing both time-correlated or time-uncorrelated imaging operation. A single-ramp, 8-bit ADC with two memory banks to allow high-speed, time-interleaved operation is also included within each module. A 32x32-TACs array has been fabricated with a 50-µm pitch in order prove the highly parallel operation and to test uniformity and power consumption issues. The measured time resolution (LSB) is of 160 ps on a 20-ns time range with a uniformity across the array within ±2LSBs, while DNL and INL are 0.7LSB and 1.9LSB respectively. The average power consumption is below 300µW/pixel when running at 500k measurements per second.
Factor V Leiden and Prothrombin Gene G20210A Mutation in Children with Venous Thromboembolism

Summary To determine whether factor V Leiden (FVL) and/or prothrombin gene G20210A mutation (PT20210A) are risk factors for venous thromboembolism (VTE) in Argentinean children. One hundred and thirty consecutive children with VTE were prospectively assisted at a single centre. Blood samples were available from 110 of them for detailed haematological analysis. The prevalence of both mutations was compared with a control group. The odds ratio for VTE was significantly increased in patients with FVL (OR 3.64; 95% CI: 1.14-11.6, p <0.029) whereas odds ratio for VTE was not significantly increased in patients with PT20210A (OR 1.06; 95% CI: 0.24-4.73, p = 0.938). Combined disorders were found in 5 of the 10 children with the aforementioned mutations. In 21 children (19%) without these mutations other inherited and acquired disorders were detected. Our data show that FVL is a risk factor for VTE whereas PT20210A does not seem to be a risk factor in our paediatric population.
A critical appraisal of 98.6 degrees F, the upper limit of the normal body temperature, and other legacies of Carl Reinhold August Wunderlich.

OBJECTIVE To evaluate critically Carl Wunderlich's axioms on clinical thermometry. DESIGN Descriptive analysis of baseline oral temperature data from volunteers participating in Shigella vaccine trials conducted at the University of Maryland Center for Vaccine Development, Baltimore. SETTING Inpatient clinical research unit. PARTICIPANTS One hundred forty-eight healthy men and women aged 18 through 40 years. MAIN MEASUREMENTS Oral temperatures were measured one to four times daily for 3 consecutive days using an electronic digital thermometer. RESULTS Our findings conflicted with Wunderlich's in that 36.8 degrees C (98.2 degrees F) rather than 37.0 degrees C (98.6 degrees F) was the mean oral temperature of our subjects; 37.7 degrees C (99.9 degrees F) rather than 38.0 degrees C (100.4 degrees F) was the upper limit of the normal temperature range; maximum temperatures, like mean temperatures, varied with time of day; and men and women exhibited comparable thermal variability. Our data corroborated Wunderlich's in that mean temperature varied diurnally, with a 6 AM nadir, a 4 to 6 PM zenith, and a mean amplitude of variability of 0.5 degrees C (0.9 degrees F); women had slightly higher normal temperatures than men; and there was a trend toward higher temperatures among black than among white subjects. CONCLUSIONS Thirty-seven degrees centigrade (98.6 degrees F) should be abandoned as a concept relevant to clinical thermometry; 37.2 degrees C (98.9 degrees F) in the early morning and 37.7 degrees C (99.9 degrees F) overall should be regarded as the upper limit of the normal oral temperature range in healthy adults aged 40 years or younger, and several of Wunderlich's other cherished dictums should be revised.
Preperitoneal postcesarean section bupivacaine analgesia: Comparison between dexamethasone and dexmedetomidine as adjuvants

Background: The peritoneal wound is frequently neglected during laparotomy. The preperitoneal local anesthetics and many adjuvants were effective for postcesarean analgesia. Analgesia may involve somatic and autonomic components. The preperitoneal bupivacaine and the promising adjuvants dexamethasone or dexmedetomidine were compared in this study. Patients and Methods: Sixty patients subjected to a cesarean section (CS) under general anesthesia divided into two groups using a bolus of preperitoneal bupivacaine 0.7 mg/kg with either 1ug/kg dexmedetomidine (Group P) or 8 mg dexamethasone (Group D). The time to the first analgesic request was the primary outcome. Results: There was a significantly prolonged time to the first analgesic request in the Group P than the Group D and less required preperitoneal injections in the Group P, also pain assessed by Numerical Rating Scale (NRS) was lower in the Group P than the Group D after 6 h postoperatively up to 24 h. Conclusions: Dexmedetomidine provided better analgesia than dexamethasone as an adjuvant to preperitoneal bupivacaine post-CS.
Iterative and Participative Action Research a designers approach to Research through Design

During a two-year period we studied practitioners in creative group meetings and introduced new tools into their design process. In this paper we describe how we employed iterative and participative action research cycles in a Research through Design process. We report on two cases in which we varied the research design of the action research cycles: iterations within a single company and between companies. The multiple iterations allowed us to understand domain specific design constraints and provided insights into governing variables that drove the direction of our research. We therefore explain our approach as a double loop learning process.
Hierarchical Model-Based Clustering for Relational Data

Relational data mining deals with datasets containing multiple types of objects and relationships that are presented in relational formats, e.g. relational databases that have multiple tables. This paper proposes a propositional hierarchical model-based method for clustering relational data. We first define an object-relational star schema to model composite objects, and present a method of flattening composite objects into aggregate objects by introducing a new type of aggregates – frequency aggregate, which can be used to record not only the observed values but also the distribution of the values of an attribute. A hierarchical agglomerative clustering algorithm with log-likelihood distance is then applied to cluster the aggregated data tentatively. After stopping at a coarse estimate of the number of clusters, a mixture model-based method with the EM algorithm is developed to perform a further relocation clustering, in which Bayes Information Criterion is used to determine the optimal number of clusters. Finally we evaluate our approach on a real-world dataset.
The mid-infrared spectra characteristic of the transformer oil-paper insulation in thermal ageing process

Transformer oil and insulation paper are the research objects,accelerated aging experiments in laboratory are performed.The infrared spectrums of samples of different aging time are obtained by the FT-RI apparatus.The absorption intensity of insulation paper's stretching vibration of O-H at the wave number of 3 346 cm-1 is weaken with the ageing time,so it can be the characteristic quantity of ageing and it can also be the basis for the on-line monitoring of insulation paper in practical transformers.Transformer oil has C=C and C=O group absorption peak at the wave number of 3006 and 1740 cm-1,and the intensity of the absorption peak became stronger with the aging time.The mid-infrared spectra characteristic of the transformer oil-paper is analyzed.The process and mechanism of transformer oil-paper insulation ageing is explored from perspective of microscopic functional groups.
Author ' s personal copy Resource management policies for fixed relays in cellular networks q

Mobile stations in the cell boundary experience poor spectral efficiency due to the path loss and interference from adjacent cells. Therefore, satisfying QoS requirements of each MS at the cell boundary has been an important issue. To resolve this spectral efficiency problem at the cell boundary, deploying fixed relay stations has been actively considered. In this paper, we consider radio resource management policies concerned with fixed relays that include path selection rules, frequency reuse pattern matching, and frame transmission pattern matching among cells. We evaluate performance of each policy by varying parameter values such as relay station’s position and frequency reuse factor. Through Monte Carlo simulations and mathematical analysis, we suggest some optimal parameter values for each policy and discuss some implementation issues that need to be considered in practical deployment of relay stations. 2008 Elsevier B.V. All rights reserved.
Atopic dermatitis: Interaction between genetic variants of GSTP1, TNF, TLR2, and TLR4 and air pollution in early life

Associations between traffic‐related air pollution (TRAP) and childhood atopic dermatitis (AD) remain inconsistent, possibly due to unexplored gene‐environment interactions. The aim of this study was to examine whether a potential effect of TRAP on AD prevalence in children is modified by selected single nucleotide polymorphisms (SNPs) related to oxidative stress and inflammation.
Cardiovascular risk factors in childhood and carotid artery intima-media thickness in adulthood: the Cardiovascular Risk in Young Finns Study.

CONTEXT Exposure to cardiovascular risk factors during childhood and adolescence may be associated with the development of atherosclerosis later in life. OBJECTIVE To study the relationship between cardiovascular risk factors measured in childhood and adolescence and common carotid artery intima-media thickness (IMT), a marker of preclinical atherosclerosis, measured in adulthood. DESIGN, SETTING, AND PARTICIPANTS Population-based, prospective cohort study conducted at 5 centers in Finland among 2229 white adults aged 24 to 39 years who were examined in childhood and adolescence at ages 3 to 18 years in 1980 and reexamined 21 years later, between September 2001 and January 2002. MAIN OUTCOME MEASURES Association between cardiovascular risk variables (levels of low-density lipoprotein cholesterol [LDL-C], high-density lipoprotein cholesterol [HDL-C], and triglycerides; LDL-C/HDL-C ratio; systolic and diastolic blood pressure; body mass index; smoking) measured in childhood and adulthood and common carotid artery IMT measured in adulthood. RESULTS In multivariable models adjusted for age and sex, IMT in adulthood was significantly associated with childhood LDL-C levels (P =.001), systolic blood pressure (P<.001), body mass index (P =.007), and smoking (P =.02), and with adult systolic blood pressure (P<.001), body mass index (P<.001), and smoking (P =.004). The number of risk factors measured in 12- to 18-year-old adolescents, including high levels (ie, extreme age- and sex-specific 80th percentile) of LDL-C, systolic blood pressure, body mass index, and cigarette smoking, were directly related to carotid IMT measured in young adults at ages 33 through 39 years (P<.001 for both men and women), and remained significant after adjustment for contemporaneous risk variables. The number of risk factors measured at ages 3 to 9 years demonstrated a weak direct relationship with carotid IMT at ages 24 to 30 years in men (P =.02) but not in women (P =.63). CONCLUSIONS Risk factor profile assessed in 12- to 18-year-old adolescents predicts adult common carotid artery IMT independently of contemporaneous risk factors. These findings suggest that exposure to cardiovascular risk factors early in life may induce changes in arteries that contribute to the development of atherosclerosis.
Active sensing for motion planning in uncertain environments via mutual information policies

This paper addresses path planning with real-time reaction to environmental uncertainty. The environment is represented as a robotic roadmap, or graph, and is uncertain in that the edges of the graph are unknown to the robot a priori. Instead, the robot’s prior information consists of a distribution over candidate edge sets, modeling the likelihood of certain obstacles in the environment. The robot can locally sense the environment, and at a vertex, can determine the presence or absence of some subset of edges. Within this model, the reactive planning problem provides the robot with a start location and a goal location and asks it to compute a policy that minimizes the expected travel and observation cost. In contrast to computing paths that maximize the probability of success, we focus on complete policies (i.e., policies that are guaranteed to navigate the robot to the goal or determine no such path exists). We prove that the problem is NP-hard and provide a suboptimal, but computationally efficient solution. This solution, based on mutual information, returns a complete policy and a bound on the gap between the policy’s expected cost and the optimal. We test the performance of the policy and the lower bound against that of the optimal policy and explore the effects of errors in the robot’s prior information on performance. Simulations are run on a flexible factory scenario to demonstrate the scalability of the proposed approach. Finally, we present a method to extend this solution to robots with faulty sensors.
Phosphoproteome profiling provides insight into the mechanism of action for carvedilol‐mediated cancer prevention

Recent studies suggest that the β‐blocker drug carvedilol prevents skin carcinogenesis but the mechanism is unknown. Carvedilol is one of a few β‐blockers identified as biased agonist based on an ability to promote β‐arrestin‐mediated processes such as ERK phosphorylation. To understand the role of phosphoproteomic signaling in carvedilol's anticancer activity, the mouse epidermal JB6 P+ cells treated with EGF, carvedilol, or their combination were analyzed using the Phospho Explorer Antibody Array containing 1318 site‐specific and phospho‐specific antibodies of over 30 signaling pathways. The array data indicated that both EGF and carvedilol increased phosphorylation of ERK's cytosolic target P70S6 K while its nuclear target ELK‐1 were activated only by EGF; Furthermore, EGF‐induced phosphorylation of ELK‐1 and c‐Jun was attenuated by carvedilol. Subcellular fractionation analysis indicated that ERK nuclear translocation induced by EGF was blocked by co‐treatment with carvedilol. Western blot and luciferase reporter assays confirmed that the biased β‐blockers carvedilol and alprenolol blocked EGF‐induced phosphorylation and activation of c‐Jun/AP‐1 and ELK‐1. Consistently, both carvedilol and alprenolol strongly prevented EGF‐induced neoplastic transformation of JB6 P+ cells. Remarkably, oral carvedilol treatment significantly inhibited the growth of A375 melanoma xenograft in SCID mice. As nuclear translocation of ERK is a key step in carcinogenesis, inhibition of this event is proposed as a novel anticancer mechanism for biased β‐blockers such as carvedilol.
Automatic Detection Technique for Speech Recognition based on Neural Networks Inter-Disciplinary

Automatic speech recognition allows the machine to understand and process information provided orally by a human user. It consists of using matching techniques to compare a sound wave to a set of samples, usually composed of words but also of phonemes. This field uses the knowledge of several sciences: anatomy, phonetics, signal processing, linguistics, computer science, artificial intelligence and statistics. The latest acoustic modeling methods provide deep neural networks for speech recognition. In particular, recurrent neural networks (RNNs) have several characteristics that make them a model of choice for automatic speech processing. They can keep and take into account in their decisions past and future contextual information. This paper specifically studies the behavior of Long Short-Term Memory (LSTM)-based neural networks on a specific task of automatic speech processing: speech detection. LSTM model were compared to two neural models: Multi-Layer Perceptron (MLP) and Elman’s Recurrent Neural Network (RNN). Tests on five speech detection tasks show the efficiency of the Long Short-Term Memory (LSTM) model.
Interleukin 10‐deficient colitis: new similarities to human inflammatory bowel disease

Interleukin (IL) 10 is a potent anti‐inflammatory cytokine. Disruption of the IL‐10 gene in C57/Black6 mice results in enterocolitis in the presence of intestinal bacteria. This study investigated gut mucosal barrier function sequentially during the development of colitis in this model.
Modelling of strategies for genetic control of scrapie in sheep: The importance of population structure

Scrapie is a transmissible spongiform encephalopathy in sheep and an example of a disease that may be controlled through breeding for disease resistance. Member states of the European Union have introduced strategies for breeding against scrapie based on the selection of genetically resistant breeding rams. An ambitious strategy adopted in The Netherlands consisted of selecting resistant rams for breeding throughout both breeding and production sectors. Mathematical modelling of the effect of a breeding program on the spreading capacity of scrapie in a national flock is needed for making assessments on how long a breeding strategy needs to be maintained to achieve disease control. Here we describe such a model applied to the Dutch situation, with the use of data on the genetic content of the Dutch sheep population as well as on scrapie occurrence in this population. We show that the time needed for obtaining scrapie control depends crucially on two parameters measuring sheep population structure: the between-flock heterogeneity in genotype frequencies, and the heterogeneity of mixing (contact rates) between sheep flocks. Estimating the first parameter from Dutch genetic survey data and assuming scenario values for the second one, enables model prediction of the time needed to achieve scrapie control in The Netherlands.
Numerical identification of parameters for a model of sedimentation processes

In this paper we present the identification of parameters in the flux and diffusion functions for a quasilinear strongly degenerate parabolic equation which models the physical phenomenon of flocculated sedimentation. We formulate the identification problem as a minimization of a suitable cost function and we derive its formal gradient by means of an adjoint equation which is a backward linear degenerate parabolic equation with discontinuous coefficients. For the numerical approach, we start with the discrete Lagrangian formulation and assuming that the direct problem is discretized by the Engquist–Osher scheme obtain a discrete adjoint state associated with this scheme. The conjugate gradient method allows us to find numerical values of the physical parameters. It also allows us to identify the critical concentration level at which solid flocs begin to touch each other and determine the change of parabolic to hyperbolic behaviour in the model equation.