Miracle-dz/UniFAR-FTUs huggingface dataset:
Cloud condensation nuclei (CCN) from fresh and aged air pollution in the megacity region of Beijing

Abstract. Atmospheric aerosol particles serving as cloud condensation nuclei (CCN) are key elements of the hydrological cycle and climate. CCN properties were measured and characterized during the CAREBeijing-2006 campaign at a regional site south of the megacity of Beijing, China. Size-resolved CCN efficiency spectra recorded for a supersaturation range of S=0.07% to 0.86% yielded average activation diameters in the range of 190 nm to 45 nm. The corresponding effective hygroscopicity parameters (κ) exhibited a strong size dependence ranging from ~0.25 in the Aitken size range to ~0.45 in the accumulation size range. The campaign average value (κ =0.3 ± 0.1) was similar to the values observed and modeled for other populated continental regions. The hygroscopicity parameters derived from the CCN measurements were consistent with chemical composition data recorded by an aerosol mass spectrometer (AMS) and thermo-optical measurements of apparent elemental and organic carbon (EC and OC). The CCN hygroscopicity and its size dependence could be parameterized as a function of only AMS based organic and inorganic mass fractions (forg, finorg) using the simple mixing rule κp ≈ 0.1 · forg + 0.7 · finorg. When the measured air masses originated from the north and passed rapidly over the center of Beijing (fresh city pollution), the average particle hygroscopicity was reduced (κ = 0.2 ± 0.1), which is consistent with enhanced mass fractions of organic compounds (~50%) and EC (~30%) in the fine particulate matter (PM1). Moreover, substantial fractions of externally mixed weakly CCN-active particles were observed at low supersaturation (S=0.07%), which can be explained by the presence of freshly emitted soot particles with very low hygroscopicity (κ
The Viewpoint Mechanism for Object-oriented Databases Modelling, Distribution and Evolution

During the past years, the most of research works dealing with the object multiple representation and evolution propose to enrich the monolithic vision of the classical object approach in which an object belongs to one hierarchy class. In particular, the viewpoint concept receives recently a widespread attention. Its integration to a data model gives flexibility for the conventional object-oriented data model and allows one to improve the modelling power of objects. The viewpoint paradigm can be used as a means for object multiple descriptions and as a means to master the complexity of the current database systems permitting a distributed manner to develop them. The motivation of this paper is twofold: to define an object data model integrating viewpoints in databases and to present a federated database system integrating multiple sources following a local-as-extended-view approach.
Experimental comparison of coherent versus incoherent sources in a four-user /spl lambda/-t OCDMA system at 1.25 Gb/s

In optical code-division multiple access (OCDMA), the optical bandwidth is accessed simultaneously by multiple users, leading to beat noise in photodetection. The choice of the optical source can have important impact on that noise. In this paper, we compare two optical sources, a broad-band erbium-doped fiber source and a multilaser source. Experimental results for a wavelength-time OCDMA system are presented for up to four simultaneous users. Bit-error-rate curves are measured at 1.25 Gb/s with a chip rate of 10 Gchip/s. It is shown that the multilaser source outperforms the broad-band source for the design parameters of this system.
Specifying WSN Applications through Agents Based on Events and States

Wireless sensor networks (WSNs) are emerging as powerful platforms for distributed embedded computing supporting a variety of high-impact applications such as disaster/crime prevention and military applications, environmental applications, health applications, and smart spaces. Programming WSNs is a complex task as system level code and application level code are often intertwined. Several programming paradigms have been to date proposed which provide programming abstractions and programming support for the development of WSN applications. In this paper we propose a specification language centered on the concept of lightweight agent based on events and states which distinctively integrates the advantages of three important paradigms and models for WSN programming: agent- based, event-driven and state-based programming. The proposed language is exemplified through a specification of the well-known EnviroTrack application.
Selection of classifier in acute abdominal pain diagnosis with decision tree model

The article presents the application of the decisio n tree classifier to the acute abdominal pain diagn osis. The recognition task model is based on a decision tree. In this model the decision tree structure is given by the experts. For the assumed structure of the decision tree the loca lly optimal strategy is considered. The problem dis cussed in the work shows a selection of different classifiers (paramet ers) to the internal nodes of the decision tree. Ex periments conducted for selected medical diagnosis problem shows that t he use of different parameters for k-NN classificat ion can improve the quality of classification in comparison with th e situation if it is used with the same parameter f or all internal nodes of the decision tree.
The Atlas supervisor

This paper gives a brief description of work originating in the Computer Group at Manchester University. Atlas is the name given to a large computing system which can include a variety of peripheral equipments, and an extensive store. All the activities of the system are controlled by a program called the supervisor. Several types of store are used, and the addressing system enables a virtually unlimited amount of each to be included. The primary store consists of magnetic cores with a cycle time of under two microseconds, which is effectively reduced by multiple selection mechanisms. The core store is divided into 512 word "pages"; this is also the size of the fixed blocks on drums and magnetic tapes. The core store and drum store are addressed identically, and drum transfers are performed automatically as described in Section 3. There is a fixed store which consists of a wire mesh into which ferrite slugs are inserted; it has a fast read-out time, and is used to hold common routines including routines of the supervisor. A subsidiary core store is used as working space for the supervisor. The V-store is a collective name given to various flip-flops throughout the computer, which can be read, set, and re-set by reading from or writing to particular store addresses.
Early Microglial Activation Precedes Neuronal Loss in the Brain of the Cstb−/− Mouse Model of Progressive Myoclonus Epilepsy, EPM1

Abstract Progressive myoclonus epilepsy of Unverricht-Lundborg type (EPM1) is a hereditary neurodegenerative disorder caused by mutations in the cystatin B (CSTB) gene encoding an inhibitor of cysteine proteases. Here, we provide the first detailed description of the onset and progression of pathologic changes in the CNS of Cstb-deficient (Cstb−/−) mice. Our data reveal early and localized glial activation in brain regions where neuron loss subsequently occurs. These changes are most pronounced in the thalamocortical system, with neuron loss occurring first within the cortex and only subsequently in the corresponding thalamic relay nucleus. Microglial activation precedes the emergence of myoclonia and is followed by successive astrocytosis and selective neuron loss. Neuron loss was not detected in thalamic relay nuclei that displayed no glial activation. Microglia showed morphologic changes during disease progression from that of phagocytic brain macrophages in young animals to having thickened branched processes in older animals. These novel data on the timing ofpathologic events in the CSTB-deficient brain highlight the potentialrole of glial activation at the initial stages of the disease. Determiningthe precise sequence of the neurodegenerative events in Cstb−/− mouse brains will lay the basis for understanding the pathophysiology of EPM1.
Modulation of TNF Release by Choline Requires α7 Subunit Nicotinic Acetylcholine Receptor-Mediated Signaling

The α7 subunit-containing nicotinic acetylcholine receptor (α7nAChR) is an essential component in the vagus nerve-based cholinergic anti-inflammatory pathway that regulates the levels of TNF, high mobility group box 1 (HMGB1), and other cytokines during inflammation. Choline is an essential nutrient, a cell membrane constituent, a precursor in the biosynthesis of acetylcholine, and a selective natural α7nAChR agonist. Here, we studied the anti-inflammatory potential of choline in murine endotoxemia and sepsis, and the role of the α7nAChR in mediating the suppressive effect of choline on TNF release. Choline (0.1–50 mM) dose-dependently suppressed TNF release from endotoxin-activated RAW macrophage-like cells, and this effect was associated with significant inhibition of NF-κB activation. Choline (50 mg/kg, intraperitoneally (i.p.)) treatment prior to endotoxin administration in mice significantly reduced systemic TNF levels. In contrast to its TNF suppressive effect in wild type mice, choline (50 mg/kg, i.p.) failed to inhibit systemic TNF levels in α7nAChR knockout mice during endotoxemia. Choline also failed to suppress TNF release from endotoxin-activated peritoneal macrophages isolated from α7nAChR knockout mice. Choline treatment prior to endotoxin resulted in a significantly improved survival rate as compared with saline-treated endotoxemic controls. Choline also suppressed HMGB1 release in vitro and in vivo, and choline treatment initiated 24 h after cecal ligation and puncture (CLP)-induced polymicrobial sepsis significantly improved survival in mice. In addition, choline suppressed TNF release from endotoxin-activated human whole blood and macrophages. Collectively, these data characterize the anti-inflammatory efficacy of choline and demonstrate that the modulation of TNF release by choline requires α7nAChR-mediated signaling.
Cache Resource Allocation in Large-Scale Chip Multiprocessors

To my parents, De Dzwo and Ellen Hsu ii ACKNOWLEDGEMENTS This dissertation marks the single most trying, thrilling, educational, and lengthy period of my life. Through the research and experiences that have led to finishing this work, I have grown, both intellectually and emotionally, into a person I am proud to be. I certainly could not have gone through this process alone — I have had the help of many wonderful people to guide me and support me through this doctoral process. First, I must acknowledge my parents, whom I feel lucky to have every single day. The level of friendship and trust I feel with my mother and father have enabled me to be myself and pursue my goals without fear of judgement. In the summer of 2005, I had an internship at Intel Corporation in Hillsboro, Oregon. I planned to drive from Michigan to Oregon so that I could have a car during the summer, and I asked my parents if they would join me on the road trip. When I tell people that I came up with this idea on my own, they think that I am the craziest person in the world. But I think this anecdote best represents how much I love and am loved by my parents. I am truly lucky. And, by the way, we had a wonderful time together. Next, I cannot express the gratitude I feel for having married the best husband I could ask for. My husband Tom is my biggest fan, always encouraging me to be the best I can be. He genuinely feels happy and proud when I accomplish something, and knowing I have him in my corner makes the world an easier place to live in. When I was working on deadlines, Tom would cook meals for me and bring them to my desk as I stared at my computer screen, encourage me to go outside for fresh air when I iii had closeted myself indoors for days, and give me unsolicited backrubs when I was at my most stressed. I am more grateful to him than he knows, and I am so glad he is my partner in life. Of course, I must also thank my little sister, Leslie, for her support these last few years. I am several years older than Leslie, and have always been accustomed to taking care of her. As she has …
Non-iterative compensation for software-defined radio quadrature front-end inaccuracies

The analog front-end of a software-defined radio (SDR) transceiver can have a critical impact on the accuracy of the transmitted and received signals. This paper proposes a digitally compensated direct-conversion front-end for both the transmission and reception stage. Quadrature mixing impairments are studied from first principles, and the exact relationships between quadrature front-end impairments and signal artefacts are derived. It is shown that these impairments may be substantially suppressed by simple digital techniques that directly estimate compensation parameters from measurements, allowing non-iterative compensation. Finally, these techniques are verified by practical experiments.
Early Childhood Teacher Preparation for Developmentally and Culturally Appropriate Practice (DCAP).

This paper presents Developmentally and Culturally Appropriate Practice (DCAP) as an extension of Developmentally Appropriate Practice (DAP) which combines the goals of multicultural and anti-bias education with those of early childhood education (ECE). The paper presents characteristics of multicultural pedagogical strategies, with the root of each strategy being the consideration of learners' individual cultural backgrounds. It illustrates how DCAP is driven from the notions of multicultural education, culturally congruent critical pedagogy, and antibias education. The paper contends that, in order to extend DAP to DCAP, teacher preparation must re-address, re-introduce, and restructure certain notions prevalent in ECE. Prospective teachers must be provided with a clear understanding of the bases for DCAP and opportunities to explore autobiographical self-awareness and to learn the major ethnic characteristics which combine to affect culturally congruent critical pedagogy. Prospective teachers should be offered a culturally diverse student teaching experience which incorporates inquiry-oriented, reflective, clinical supervision. (Contains approximately 80 references.) (JDD) *********************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. ********Yc********************************************************A***** The Penn State university Department of Curriculum and Instruction Early Childhood Teacher Preparation for Developmentally and Culturally Appropriate Practice (mu)) Eunsook H. Roh 144 Chambers Building Pennsylvania State Univ. University Park, PA 16801 Tel: 814-861-3768(Office) 814-2" -1552(Home) Fax: 814-8 7602 E-mail: EHK 2atpsu.edu U S DEPARTMENT OF EDUCATION ()owe OI Educational Research and Improvement EDUCATIONAL RE SOURCES INFORMATION CENTER {ERIC) This document has been reproduced as received from the person or organization Originating 4 I. Minor changes have been made In improve reproductron Quality Points of view 01 opinions stared in ! Ns dor u mesh do not necessairry represent villa rat GEMOOmhonorpohry "PERMISSION TO REPRODUCE THIS MATERIAL HAS BEEN GRANTED BY e4) 4 TO THE EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC{"
Data based kinematic model of a multi-flexible-link robot arm for varying payloads

Reducing weight and inertias of conventional robot arms with an elastic structure allows safer interactive cooperation between humans and robots. While the end effector pose of a rigid robot is determined by the forward kinematic chain, the pose of elastic arms results from a superposition of the rigid kinematics and the pose dependent deflection caused by gravity. This property complicates the computation of forward and inverse kinematics in particular in case of dynamic loads. This paper presents a machine learning approach to extract various nonlinear regression models of the forward and inverse kinematics of a three degrees of freedom (DOF) flexible-link robot arm with dynamic loads from experimental data. The forward model predicts the target pose, given the joint angles and the strain signals while the inverse kinematic model predicts the joint angles required to assume a target pose. The transformation of the original features onto suitable nonlinear features substantially improves the generalisation ability of the both forward and inverse kinematic model. The closed loop inverse kinematic controller archieves a pose accuracy of 3 mm and the results show that the learned model can solve the inverse kinematics problem of flexible robot arms with sufficient accuracy even with unknown payloads.
Implementing Parallel Data Mining Algorithm on High Performance Data Cloud

Cloud Computing technology has been emerged to manage large-scale data efficiently. And due to rapid growth of data, large scale data processing is becoming a focal point of information technique. To deal with this advancement in data collection and storage technologies, designing and implementing large-scale parallel algorithm for Data mining is gaining more interest. In this paper we design Association Rule based parallel data mining algorithm which deals with Hadoop cloud, a parallel store and computing platform. Moreover we have introduced cloud inter operation between Hadoop and Sector/Sphere Cloud which allows the same Hadoop MapReduce application to be run against data in either Hadoop Distributed File System or Sphere File System.
Curtailing the High Rate of Late-Stage Attrition of Investigational Therapeutics Against Unprecedented Targets in Patients with Lung and Other Malignancies

A greater understanding of the pathogenesis and biology of cancer coupled with major advances in biotechnology has resulted in the identification of rationally designed, target-based (RDTB) anticancer therapeutics, ushering in new therapeutic opportunities and high expectations for the future as well as developmental challenges. Because these agents appear to principally target malignant cells, it is expected that they will produce less toxicity at clinically effective doses than nonspecific cytotoxic agents, but their target requirements are likely to be much more stringent. The innate complexity of the networks that contain elements targeted by these agents also decreases the probability that any single therapeutic manipulation will result in robust clinical activity and success when used alone, particularly in patients with solid malignancies that have multiple relevant signaling aberrations. In contrast, proof of principle and robust antitumor activity may be most efficiently demonstrated in nonrandomized evaluations involving tumors that are principally driven by aberrations of the specific target. The predominant therapeutic manifestation of RDTB agents in preclinical studies is due to decreased tumor growth rates and will likely be similar in the clinic; however, such manifestations are not readily detectable and quantifiable using nonrandomized clinical evaluations. To curtail the increasing rate of late-stage attrition of RDTB agents, which, if maintained, will stymie progress in cancer therapy, the design of initial nonrandomized evaluations, particularly the selection of tumors and patients, must be guided by the principal biological features of the agents. Next, evaluations, some of which must be randomized, can be performed in a wide range of tumor types, depending on the presence and relevance of the target. To validate the concept of RDTB therapeutics and to realize their full potential, radically different development, evaluation, and regulatory paradigms must be adopted.
Multilevel Selection 1: Quantitative Genetics of Inheritance and Response to Selection

Interaction among individuals is universal, both in animals and in plants, and substantially affects evolution of natural populations and responses to artificial selection in agriculture. Although quantitative genetics has successfully been applied to many traits, it does not provide a general theory accounting for interaction among individuals and selection acting on multiple levels. Consequently, current quantitative genetic theory fails to explain why some traits do not respond to selection among individuals, but respond greatly to selection among groups. Understanding the full impacts of heritable interactions on the outcomes of selection requires a quantitative genetic framework including all levels of selection and relatedness. Here we present such a framework and provide expressions for the response to selection. Results show that interaction among individuals may create substantial heritable variation, which is hidden to classical analyses. Selection acting on higher levels of organization captures this hidden variation and therefore always yields positive response, whereas individual selection may yield response in the opposite direction. Our work provides testable predictions of response to multilevel selection and reduces to classical theory in the absence of interaction. Statistical methodology provided elsewhere enables empirical application of our work to both natural and domestic populations.
Prediction of Diabetes Based on Baseline Metabolic Characteristics in Individuals at High Risk

OBJECTIVE Individuals with impaired glucose tolerance (IGT) are at high risk for developing type 2 diabetes mellitus (T2DM). We examined which characteristics at baseline predicted the development of T2DM versus maintenance of IGT or conversion to normal glucose tolerance. RESEARCH DESIGN AND METHODS We studied 228 subjects at high risk with IGT who received treatment with placebo in ACT NOW and who underwent baseline anthropometric measures and oral glucose tolerance test (OGTT) at baseline and after a mean follow-up of 2.4 years. RESULTS In a univariate analysis, 45 of 228 (19.7%) IGT individuals developed diabetes. After adjusting for age, sex, and center, increased fasting plasma glucose, 2-h plasma glucose, ∆G0–120 during OGTT, HbA1c, adipocyte insulin resistance index, ln fasting plasma insulin, and ln ∆I0–120, as well as family history of diabetes and presence of metabolic syndrome, were associated with increased risk of diabetes. At baseline, higher insulin secretion (ln [∆I0–120/∆G0–120]) during the OGTT was associated with decreased risk of diabetes. Higher β-cell function (insulin secretion/insulin resistance or disposition index; ln [∆I0–120/∆G0–120 × Matsuda index of insulin sensitivity]; odds ratio 0.11; P < 0.0001) was the variable most closely associated with reduced risk of diabetes. CONCLUSIONS In a stepwise multiple-variable analysis, only HbA1c and β-cell function (ln insulin secretion/insulin resistance index) predicted the development of diabetes (r = 0.49; P < 0.0001).
Maximizing compression efficiency through block rotation

The Discrete Cosine Transform (DCT) is widely used in lossy image and video compression schemes, e.g., JPEG and MPEG. In this paper, we show that the compression efficiency of the DCT is dependent on the edge directions within a block. In particular, higher compression ratios are achieved when edges are aligned with the image axes. To maximize compression for general images, we propose a rotated block DCT method. It consists of rotating each block, before applying the DCT, by an angle that aligns the edges, and rotating back the block in the decompression stage. We show how to compute the rotation angle and analyze two alternative block rotation approaches. Our experiments show that our method enables both a perceptual improvement and a PSNR increase of up to 2dB, compared with the standard DCT, for low and medium bit rates.