Miracle-dz/UniFAR-FTUs huggingface dataset:
Long-term frequency aging for unpowered space-class oscillators

Very little data exists regarding the long-term aging performance of space-rated oscillators in the non-operating mode. This paper provides empirical evidence that may be used to estimate the performance of unpowered oscillators for long-term space missions, as well as an aid in validating the worst-case analyses that are routinely performed on these oscillators. The proper operation of any space vehicle is dependent on the performance of the onboard master oscillator. For maximum reliability, the onboard clock is often provided as a dual-or triple-redundant ensemble, with one active oscillator. The backup oscillator(s) are usually powered off and may be off for a significant percentage of the mission. A significant parameter of importance for oscillator performance is the aging rate. Papers have been presented on the aging performance of active oscillators in space, but very little data exists regarding the long-term aging performance of oscillators in the nonoperating mode. The aging rate data are extremely important for predicting the expected performance of these backup oscillators after 10 or 15 years in of non-operation in space. This paper presents performance data derived from temperature controlled crystal oscillators and oven controlled crystal oscillators that have been dormant for decades.
The absence of macrophage Nrf2 promotes early atherogenesis.

AIMS The loss of nuclear factor E2-related factor 2 (Nrf2) has been shown to protect against atherogenesis in apoE-deficient mice. The mechanism by which Nrf2 deficiency affords atheroprotection in this model is currently unknown, but combined systemic and local vascular effects on lesion macrophages have been proposed. We investigated the effect of bone marrow-specific loss of Nrf2 on early atherogenesis in low-density lipoprotein (LDL) receptor-deficient (LDLR(-/-)) mice, and assessed the effect of Nrf2 on cellular accumulation of modified LDLs and the expression of inflammatory markers in macrophages. METHODS AND RESULTS The effect of bone marrow-specific loss of Nrf2 on atherogenesis was studied using bone marrow transplantation of wild-type (WT) or Nrf2(-/-) bone marrow to LDLR(-/-) mice. Mice transplanted with Nrf2(-/-) bone marrow and fed a high-fat diet for 6 weeks exhibited significantly larger atherosclerotic lesions than WT bone marrow transplanted mice. Moreover, in thioglycollate-elicited Nrf2(-/-) macrophages, the uptake of acetylated and malondialdehyde-modified LDLs was increased in comparison with WT controls, with the concomitant increase in the expression of scavenger receptor A and toll-like receptor 4. In addition, the expression of pro-inflammatory monocyte chemoattractant protein-1 and interleukin-6 were increased in Nrf2(-/-) vs. WT macrophages. CONCLUSION Nrf2 deficiency specific to bone marrow-derived cells aggravates atherosclerosis in LDLR(-/-) mice. Furthermore, the loss of Nrf2 in macrophages enhances foam cell formation and promotes the pro-inflammatory phenotype.
Particle Swarm Optimization with a Novel Multi-Parent Crossover Operator

Particle swarm optimization (PSO) shares many similarities with evolutionary algorithms (EAs), while the standard PSO does not use any evolution operators such as crossover and mutation. This paper presents a hybrid PSO algorithm to inherit some excellent characteristics of advanced evolutionary computation techniques. The proposed method employs a novel multi-parent crossover operator and a self-adaptive Cauchy mutation operator to help escape from local optima. Experimental results on a suit of well-known benchmark functions with many local minima have shown that the proposed method could successfully deal with those difficult multimodal optimization problems.
Interactive Cost Configuration Over Decision Diagrams

In many AI domains such as product configuration, a user should interactively specify a solution that must satisfy a set of constraints. In such scenarios, offline compilation of feasible solutions into a tractable representation is an important approach to delivering efficient backtrack-free user interaction online. In particular, binary decision diagrams (BDDs) have been successfully used as a compilation target for product and service configuration. In this paper we discuss how to extend BDD-based configuration to scenarios involving cost functions which express user preferences. We first show that an efficient, robust and easy to implement extension is possible if the cost function is additive, and feasible solutions are represented using multi-valued decision diagrams (MDDs). We also discuss the effect on MDD size if the cost function is non-additive or if it is encoded explicitly into MDD. We then discuss interactive configuration in the presence of multiple cost functions. We prove that even in its simplest form, multiple-cost configuration is NP-hard in the input MDD. However, for solving two-cost configuration we develop a pseudo-polynomial scheme and a fully polynomial approximation scheme. The applicability of our approach is demonstrated through experiments over real-world configuration models and product-catalogue datasets. Response times are generally within a fraction of a second even for very large instances.
Abstraction and Representation of Continuous Variables in Connectionist Networks

A method is presented for using connectionist networks of simple computing elements to discover a particular type of constraint in multidimensional data. Suppose that some data source provides samples consisting of n-dimensional feature-vectors, but that this data all happens to lie on an m-dimensional surface embedded in the n-dimensional feature space. Then occurrences of data can be more concisely described by specifying an m-dimensional location on the embedded surface than by reciting all n components of the feature vector. The recoding of data in such a way is a form of abstraction. This paper describes a method for performing this type of abstraction in connectionist networks of simple computing elements. We present a scheme for representing the values of continuous (scalar) variables in subsets of units. The backpropagation weight updating method for training connectionist networks is extended by the use of auxiliary pressure in order to coax hidden units into the prescribed representation for scalar-valued variables.
Detecting Trojans Through Leakage Current Analysis Using Multiple Supply Pad ${I}_{\rm DDQ}$s

Hardware Trojans have emerged as a new threat to the security and trust of computing systems. Hardware Trojans are deliberate and malicious modifications to the logic function implemented within digital and mixed signal chips. In contrast to software Trojans, it is not possible to simply "scan the hard drive" to eradicate a hardware Trojan. Hardware Trojans can be designed to shutdown the chip at some predetermined time and/or when some specific signal or data pattern is received. They may also be designed to remain hidden while leaking confidential information covertly to the adversary. Determining whether a hardware Trojan has been inserted into a chip is extremely difficult for a variety of reasons, e.g., nanometer feature sizes and chip design complexity combine to make optical inspection difficult or impossible. This paper presents experimental results demonstrating the effectiveness of a Trojan detection method that is based on the analysis of a chip's Jddqs (steady-state current), which are measured simultaneously from multiple places on the chip. The proposed method also incorporates a technique for virtually eliminating process and test environment variations effects which act to reduce detection sensitivity of traditional testing approaches. Used together, resolution enhancements of up to a 1000 x are possible over conventional single power supply current measurement techniques. A regression-based statistical technique is applied to the data collected from a set of chips fabricated in a 65-nm process to illustrate the detection capabilities and limitations of this type of approach.
High cyclin‐dependent kinase inhibitors in Bcl‐2 and Bcl‐xL‐expressing CD34+‐proliferating haematopoietic progenitors

We have previously described the isolation of primitive, slow‐proliferating progenitors from normal, circulating CD34+ cells by using the fluorescent dye 5‐6‐carboxyfluorescein diacetate succinimidyl ester (CFDA‐SE). CFDA‐SEbright (primitive) and CFDA‐SEdim (differentiating) cells were isolated following cytokine stimulation on the basis of their different proliferation rates. In the present work we analysed the expression levels of a number of proteins involved with differentiation, proliferation and survival/apoptosis in CFDA‐SEbright/CD34+/slow‐proliferating cells that were previously defined as progenitors capable of differentiating into different lineages. The aim of this work was to gain a better understanding of our model system in order to define some of the important parameters that regulate differentiation in haematopoietic progenitors. GATA‐1 and PU.1 RNA levels were similar in freshly isolated (d 0) CD34+ and in CFDA‐SEbright (bright) cells, whereas they increased in CFDA‐SEdim (dim) cells. Accordingly, Nm23 was expressed at higher levels in bright cells. Moreover, bright cells had higher p21WAF1/CIP1, p27KIP1 and p16Ink4 protein levels than dim cells. Consistently, Cdc2 and Cdk2 kinase activity was much higher in the dim than in the slower proliferating bright cells. C‐myc and p53 levels were higher in bright cells than in d 0 CD34+ and dim cells, and so was Bcl‐xL, which followed the trend we have previously described for Bcl‐2. Thus, bright cells, despite having a higher proliferation rate than the starting d 0 CD34+ population, have strikingly elevated levels of cyclin‐dependent kinase inhibitors, which are likely to also act as inhibitors of differentiation.
Obtaining Accurate Probabilistic Causal Inference by Post-Processing Calibration

Discovery of an accurate causal Bayesian network structure from observational data can be useful in many areas of science. Often the discoveries are made under uncertainty, which can be expressed as probabilities. To guide the use of such discoveries, including directing further investigation, it is important that those probabilities be well-calibrated. In this paper, we introduce a novel framework to derive calibrated probabilities of causal relationships from observational data. The framework consists of three components: (1) an approximate method for generating initial probability estimates of the edge types for each pair of variables, (2) the availability of a relatively small number of the causal relationships in the network for which the truth status is known, which we call a calibration training set, and (3) a calibration method for using the approximate probability estimates and the calibration training set to generate calibrated probabilities for the many remaining pairs of variables. We also introduce a new calibration method based on a shallow neural network. Our experiments on simulated data support that the proposed approach improves the calibration of causal edge predictions. The results also support that the approach often improves the precision and recall of predictions.
Classification of RS data using Decision Tree Approach

The traditional hard classification techniques are parametric in nature and they expect data to follow a Gaussian distribution, they have been found to be performing poorly on high resolution satellite images, as classes in these images tend to exhibit extensive overlapping in spectral space. This produces spectral confusion among the classes and results in inaccurate classified images. A major drawback of such classifiers lies in the difficulty of integrating ancillary data, which follows a non Gaussian distribution nature. Ancillary data provides extra spectral and spatial knowledge, which improves the classification accuracy. Classification done using such knowledge is known as knowledge base classification. The present study explores a non-parametric decision tree classifier to extract knowledge from the spatial data in the form of classification rules. The classified image overall accuracy was found to be 86.66% using the Decision Tree method and with kappa values . 8133 respectively.
Practical verified computation with streaming interactive proofs

When delegating computation to a service provider, as in the cloud computing paradigm, we seek some reassurance that the output is correct and complete. Yet recomputing the output as a check is inefficient and expensive, and it may not even be feasible to store all the data locally. We are therefore interested in what can be validated by a streaming (sublinear space) user, who cannot store the full input, or perform the full computation herself. Our aim in this work is to advance a recent line of work on "proof systems" in which the service provider proves the correctness of its output to a user. The goal is to minimize the time and space costs of both parties in generating and checking the proof. Only very recently have there been attempts to implement such proof systems, and thus far these have been quite limited in functionality. Here, our approach is two-fold. First, we describe a carefully chosen instantiation of one of the most efficient general-purpose constructions for arbitrary computations (streaming or otherwise), due to Goldwasser, Kalai, and Rothblum [19]. This requires several new insights and enhancements to move the methodology from a theoretical result to a practical possibility. Our main contribution is in achieving a prover that runs in time O(S(n) log S(n)), where S(n) is the size of an arithmetic circuit computing the function of interest; this compares favorably to the poly(S(n)) runtime for the prover promised in [19]. Our experimental results demonstrate that a practical general-purpose protocol for verifiable computation may be significantly closer to reality than previously realized. Second, we describe a set of techniques that achieve genuine scalability for protocols fine-tuned for specific important problems in streaming and database processing. Focusing in particular on non-interactive protocols for problems ranging from matrix-vector multiplication to bipartite perfect matching, we build on prior work [8, 5] to achieve a prover that runs in nearly linear-time, while obtaining optimal tradeoffs between communication cost and the user's working memory. Existing techniques required (substantially) superlinear time for the prover. Finally, we develop improved interactive protocols for specific problems based on a linearization technique originally due to Shen [33]. We argue that even if general-purpose methods improve, fine-tuned protocols will remain valuable in real-world settings for key problems, and hence special attention to specific problems is warranted.
The changing meaning of family support among older Chinese and Korean immigrants.

OBJECTIVE Our objective in this study was to examine how family social-support expectations have changed among older Chinese and Korean U.S. immigrants. METHODS Fifty-two Cantonese- and Korean-speaking immigrants older than 60 years participated in eight focus groups. Transcripts were translated into English. Themes were developed based on a coding structure and compared to past research. RESULT Participants discussed changed perspectives of family social support and the need to integrate both American and Chinese or Korean culture, thus becoming bicultural. Three distinct perspectives of family emerged: (1) participants felt they had become peripheral family members, (2) parents were no longer authority figures in families, and (3) participants were more independent. Finally, participants described how factors such as a changed economic environment, living alone, and extending their social network beyond family, promoted a move to biculturalism. DISCUSSION These results suggest that the integration of two cultures, or biculturalism, is an indicator of successful adaptation to immigration later in life; older Chinese and Korean immigrants are adjusting to living in the United States and blending multiple cultures simultaneously. Thus, acculturation frameworks implying a linear process may not be theoretically valid as ethnic identity, particularly for those who immigrate to different countries, changes over the life course.
Brain edema and inflammatory activation in bile duct ligated rats with diet‐induced hyperammonemia: A model of hepatic encephalopathy in cirrhosis

Studies of the pathogenesis of hepatic encephalopathy are hampered by the lack of a satisfactory animal model. We examined the neurological features of rats after bile duct ligation fed a hyperammonemic diet (BDL+HD). Six groups were studied: sham, sham pair‐fed, hyperammonemic, bile duct ligation (BDL), BDL pair fed, and BDL+HD. The BDL+HD rats were made hyperammonemic via an ammonia‐containing diet that began 2 weeks after operation. One week later, the animals were sacrificed. BDL+HD rats displayed an increased level of cerebral ammonia and neuroanatomical characteristics of hepatic encephalopathy (HE), including the presence of type II Alzheimer astrocytes. Both BDL and BDL+HD rats showed activation of the inflammatory system. BDL+HD rats showed an increased amount of brain glutamine, a decreased amount of brain myo‐inositol, and a significant increase in the level of brain water. In coordination tests, BDL+HD rats showed severe impairment of motor activity and performance as opposed to BDL rats, whose results seemed only mildly affected. In conclusion, the BDL+HD rats displayed similar neuroanatomical and neurochemical characteristics to human HE in liver cirrhosis. Brain edema and inflammatory activation can be detected under these circumstances. (HEPATOLOGY 2006;43:1257–1266.)
Oral and laryngeal muscle coordination during swallowing

The objective of this experiment was to determine the relative contributions and patterns of activity of different muscles involved during the oral phase of swallowing. Electromyographic (EMG) signals were recorded from the orbicularis oris inferior, masseter, palatal elevator, anterior and posterior genioglossus, mylohyoid, anterior belly of the digastric, and vocalis muscles of 12 normal adult subjects. Each subject swallowed 15 mL of water, under normal and bite block conditions, 15 to 20 times. The integrated EMG signals for each subject's swallows were ensemble averaged. The results of the analyses showed that swallowing function varies from individual to individual in terms of the specific muscles used and how the various muscle activity patterns are coordinated. These results suggest that swallowing is a highly complex adaptive motor activity which probably relies more on higher‐level control mechanisms than previously believed.
Alcohol screening questionnaires in women: a critical review.

OBJECTIVE To describe the performance of alcohol screening questionnaires in female patients. DATA SOURCES We searched MEDLINE from 1966 to July 1997 for alcoholism or alcohol-drinking and for CAGE, AUDIT, BMAST, TWEAK, T-ACE, MAST, SMAST, or SAAST; Citations Indexes for newer screening questionnaires and those without acronyms; and MEDLINE from 1996 to July 1997 for alcoholism or alcohol-drinking and screening. STUDY SELECTION AND DATA EXTRACTION Reviewed studies presented data for women comparing brief alcohol screening questionnaires with valid criterion standards for heavy drinking (> or =2 drinks per day) or alcohol abuse or dependence in US general clinical populations. Sensitivities, specificities, and areas under receiver operating characteristic curves (AUROCs) were extracted. DATA SYNTHESIS Thirteen articles (9 studies) were reviewed. The CAGE questionnaire had AUROCs of 0.84 to 0.92 for alcohol abuse and dependence in predominantly black populations of women, but using the traditional cut point of 2 or more resulted in low sensitivities (38%-50%) in predominantly white female populations. The TWEAK and Alcohol Use Disorders Identification Test (AUDIT) questionnaires had high AUROCs (0.87-0.93) for past-year alcohol abuse or dependence in black or white women, but had sensitivities less than 80% at traditional cut points. For detecting heavy drinking, the AUDIT questionnaire had AUROCs of at least 0.87 in female primary care patients. The TWEAK and T-ACE questionnaires had higher AUROCs (0.84-0.87) than the CAGE questionnaire (0.76-0.78) for detecting heavy drinking before pregnancy was recognized in black obstetric patients. CONCLUSIONS The CAGE questionnaire was relatively insensitive in predominantly white female populations. The TWEAK and AUDIT questionnaires have performed adequately in black or white women, using lower cut points than usual.
Harmonic impacts of inverter-based distributed generations in low voltage distribution network

With the high penetration of distributed generations (DG) in low voltage (LV) distribution network, some power quality problems, such as harmonic impacts due to power electronics converters, are unavoidable. This paper analyzes the harmonic influence caused by DG inverters to the connection points and to other nodes in the network. The LV distribution network model with DG inverters is established by MATLAB/Simulink. And simulation results verify the analysis. Power quality issues of connection point when multiple DG inverters connected to LV network are presented in field measurements and some related problems are discussed.
Semantic-directed clumping of disjunctive abstract states

To infer complex structural invariants, shape analyses rely on expressive families of logical properties. Many such analyses manipulate abstract memory states that consist of separating conjunctions of basic predicates describing atomic blocks or summaries. Moreover, they use finite disjunctions of abstract memory states in order to account for dissimilar shapes. Disjunctions should be kept small for the sake of scalability, though precision often requires to keep additional case splits. In this context, deciding when and how to merge case splits and to replace them with summaries is critical both for the precision and for the efficiency. Existing techniques use sets of syntactic rules, which are tedious to design and prone to failure. In this paper, we design a semantic criterion to clump abstract states based on their silhouette which applies not only to the conservative union of disjuncts, but also to the weakening of separating conjunction of memory predicates into inductive summaries. Our approach allows to define union and widening operators that aim at preserving the case splits that are required for the analysis to succeed. We implement this approach in the MemCAD analyzer, and evaluate it on real-world C codes from existing libraries, including programs dealing with doubly linked lists, red-black trees and AVL-trees.