Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of anthropogenic emissions of carbon monoxide in East Asia derived from the observations of atmospheric radon-222 over the western North Pacific

We used the observed CO/ 222 Rn ratio in the Asian outflows at Minamitorishima (MNM), Yonagunijima (YON), and Ryori (RYO) in the western North Pacific from 2007 to 2011, together with a three-dimensional chemical transport model (STAG), in order to estimate anthropogenic emissions of CO in East Asia. The measurements captured high-frequency synoptic variations of enhanced 222 Rn (ERN) events associated with the long-range transport of continental air masses. 222 Rn and CO showed high correlation during the ERN events observed at MNM and YON in the winter and spring, but not at RYO. The STAG transport model reproduced well the concentrations of observed 222 Rn when forced with a constant and uniform flux density of 1.0 atom cm −2 s −1 , but underestimated the associated enhancement of synoptically variable CO caused by the underestimated flux values in the EDGAR ver. 4.1 emission database used in the model for East Asia. Better estimates for the East Asian emission were derived using a radon tracer method based on the difference in the enhancement ratio of CO/ 222 Rn between the observation and the model. The anthropogenic emissions of CO for China, Japan, and Korea were estimated to be 203 Tg CO yr −1 , 91% of which originated in China. When compared with other estimated emissions of CO, our estimated result showed consistency with those of the inverse method, whereas the emission database of EDGAR was about 45% smaller than our anthropogenic estimation for China.
A cloud-based collaborative video story authoring and sharing platform

The growing ubiquity of Internet and cloud computing is having significant impact on mediarelated industries. These industries are using the Internet and cloud as a medium to enable creation, search, management, and consumption of their content. Rich web pages, software downloads, interactive communications, and ever-expanding universe of digital media require a new approach to multimedia (e.g., audio, video, images, etc.) content sharing and management. Size and volume of multimedia content is growing exponentially. Though there are many online videohosting services (YouTube, flickr, dailymotion, etc.) for storing and viewing multimedia content, there is clear lack of software platforms that can help end-users in content authoring and sharing activities in a social setting. This paper introduces the principle concepts of multimedia content sharing in a social setting and presents a novel platform that supports cloud-based collaborative video story authoring and telling. The platform leverages social networks for video search and recommendation for the purpose of story telling. The Social Content Authoring and Sharing Platform (SCASP) leverages MediaWise Cloud Content Orchestrator (MCCO) that supports do-it-yourself creation, search, management, and consumption of multimedia content. MCCO supports dynamic content delivery using CPU and storage services available in the public cloud. The platform exploits flexible content distribution capabilities of MCCO for a group of possibly geographically distributed end-users who collaborate on a specific task such as video story telling.
Nanothermoforming of hierarchical optical components utilizing shape memory polymers as active molds

We utilize shape memory polymers as active mold inserts for the thermoforming of complex, hierarchical nano- and microstructured optical components with undercuts on large scales. Our approach combines nanoimprint/hot embossing and thermoforming with the unique features of shape memory polymers. As examples for this nano- and microthermo-forming process, we demonstrate the fabrication of hierarchical photonic structures inspired by the blue Morpho butterfly as well as diffractive optical elements with nm- and μm-size structures.
Improving Publication Pipeline with Automated Biological Entity Detection and Validation Service

Abstract With the increasing amount of digital journal submissions, there is a need to deploy new scalable computational methods to improve information accessibilities. One common task is to identify useful information and named entity from text documents such as journal article submission. However, there are many technical challenges to limit applicability of the general methods and lack of general tools. In this paper, we present domain informational vocabulary extraction (DIVE) project, which aims to enrich digital publications through detection of entity and key informational words and by adding additional annotations. In a first of its kind to our knowledge, our system engages authors of the peer-reviewed articles and the journal publishers by integrating DIVE implementation in the manuscript proofing and publication process. The system implements multiple strategies for biological entity detection, including using regular expression rules, ontology, and a keyword dictionary. These extracted entities are then stored in a database and made accessible through an interactive web application for curation and evaluation by authors. Through the web interface, the authors can make additional annotations and corrections to the current results. The updates can then be used to improve the entity detection in subsequent processed articles in the future. We describe our framework and deployment in details. In a pilot program, we have deployed the first phase of development as a service integrated with the journals Plant Physiology and The Plant cell published by the American Society of Plant Biologists (ASPB). We present usage statistics to date since its production on April 2018. We compare automated recognition results from DIVE with results from author curation and show the service achieved on average 80% recall and 70% precision per article. In contrast, an existing biological entity extraction tool, a biomedical named entity recognizer (ABNER), can only achieve 47% recall and return a much larger candidate set.
ATLASGAL - Kinematic distances and the dense gas mass distribution of the inner Galaxy

The formation of high mass stars and clusters occurs in giant molecular clouds. Objects in evolved stages of massive star formation such as protostars, hot molecular cores, and ultracompact HII regions have been studied in more detail than earlier, colder objects. Further progress thus requires the analysis of the time before massive protostellar objects can be probed by their infrared emission. With this in mind, the APEX Telescope Large Area Survey of the whole inner Galactic plane at 870 ? m (ATLASGAL) has been carried out to provide a global view of cold dust and star formation at submillimetre wavelengths. Aims. We derive kinematic distances to a large sample of massive cold dust clumps from their measured line velocities. We estimate masses and sizes of ATLASGAL sources, for which the kinematic distance ambiguity is resolved. Methods. The ATLASGAL sample is divided into groups of sources, which are located close together, mostly within a radius of 2 pc, and have velocities in a similar range with a median velocity dispersion of ~1 km s-1. We use NH3, N2H+, and CS velocities to calculate near and far kinematic distances to those groups. Results. We obtain 296 groups of ATLASGAL sources in the first quadrant and 393 groups in the fourth quadrant, which are coherent in space and velocity. We analyse HI self-absorption and HI absorption to resolve the kinematic distance ambiguity to 689 complexes of submm clumps. They are associated with 12CO emission probing large-scale structure and 13CO (1–0) line as well as the 870 ? m dust continuum on a smaller scale. We obtain a scale height of ~28 ± 2 pc and displacement below the Galactic midplane of ~? 7 ± 1 pc. Within distances from 2 to 18 kpc ATLASGAL clumps have a broad range of gas masses with a median of 1050 M? as well as a wide distribution of radii with a median of 0.4 pc. Their distribution in galactocentric radii is correlated with spiral arms. Conclusions. Using a statistically significant ATLASGAL sample we derive a power-law exponent of ? 2.2 ± 0.1 of the clump mass function. This is consistent with the slope derived for clusters and with that of the stellar initial mass function. Examining the power-law index for different galactocentric distances and various source samples shows that it is independent of environment and evolutionary phase. Fitting the mass-size relationship by a power law gives a slope of 1.76 ± 0.01 for cold sources such as IRDCs and warm clumps associated with HII regions.
Maria e Spiridione Petrettini: Contributi allo studio della cultura italo-greca tra fine del dominio veneto e restaurazione

The lives of the Petrettini siblings, Maria Anastasia and Spiridione, unfold in the pre and post-revolutionary climate of troubled Corfu, a territory then owned by the Serenissima Republica of Venice, and in a decadent Venice. The artistic and historic reconstruction of the time and the analysis of the literary relationship between Venice and Corfu is followed by the reconstruction of the early years of the two authors. Their education process started Corfu and was completed in Italy, travelling repeatedly across the Adriatic Sea, during years in which Napoleon was replaced by the Russians and the English in Corfu and the Austro-Hungarians in Venice.
Reducing Chemotoxic Stomatitis in Cancer Patients With a Self-Care Oral Hygiene Protocol

A Pretest-Posttest Control Group design was used to examine the effectiveness of a self-care management approach to reduce the severity of chemotoxic stomatitis. Orem's nursing model. Levin's self-care theory, and Magoon's constructivist research methodology were employed as the theoretical framework. Subjects, 24 short-stay or out-patient oncology clients, were all beginning treatment with known stomatotoxic agents. Buccal cultures were taken to determine changes in normal oral flora during stomatitis. The experimental group received information and direction for a systematic oral hygiene protocol. Post-chemotherapy oral assessment score means of the experimental group were significantly better (p<.01) than those of the control group. Candida was cultured from half of the sample subjects in the pre-chemotherapy specimens; oral cultures taken when stomatitis occurred were similar to initial cultures.
Regionalization of the nervous system requires axial allocation prior to neural lineage commitment

Summary Neural induction in vertebrates generates a central nervous system that extends the rostral-caudal length of the body. The prevailing view is that neural cells are initially induced with anterior (forebrain) identity, with caudalising signals then converting a proportion to posterior fates (spinal cord). To test this model, we used chromatin accessibility assays to define how cells adopt region-specific neural fates. Together with genetic and biochemical perturbations this identified a developmental time window in which genome-wide chromatin remodeling events preconfigure epiblast cells for neural induction. Contrary to the established model, this revealed that cells commit to a regional identity before acquiring neural identity. This “primary regionalization” allocates cells to anterior or posterior regions of the nervous system, explaining how cranial and spinal neurons are generated at appropriate axial positions. These findings prompt a revision to models of neural induction and support the proposed dual evolutionary origin of the vertebrate central nervous system.
A Survey on Clustering Algorithms for Data Streams

Data stream mining is an emerging area for extracting useful information from continuous arriving data. Web click stream, weather monitoring, network traffic, shopping history, web log are some key resources of generating data stream. Clustering is one of the most useful technique for analsing stream data, as it does not require any predefined class labeling. Data stream mining is challanging as the data is massive and arriving continuously. The traditional clustering algorithms cannot be directly applied on the data streams. Data stream mining needs one scan algorithms to extract rich data in the form of data streams. In this paper we discuss various data stream clustering algorithms with their limitations and required data structures. This paper also provides a comparative study of these algorithms. Real world applications of data streams, data resources and publicly available softwares are also discussed.
A general bound for oscillatory integrals with a polynomial phase of degree k

Let f ∈ R[X1, . , Xn] be a polynomial of degree k > 2. We consider the oscillatory integral I(λ) = R φ(x)eiλf(x)dx, where φ is a C1 function with compact support. A classical result due to E.M. Stein implies that I(λ) = O(λ−1/k), as λ→ +∞. The exponent 1/k is best possible, as shown by the example f(x) = f(x0)±L(x−x0), where x0 is any point in R and L is any nonzero linear form on R. In this paper, we show that, if f is precisely not of the above form, then the stronger bound I(λ) = O(λ−1/(k−1)) holds, and the exponent −1/(k − 1) is best possible. 1. Statement of the result We consider a polynomial f ∈ R[X1, . , Xn] of total degree k, i.e. f(x) = ∑ α aαx , with α =(α1, ., αn), such that |α| = α1 + . + αn 6 k, for each α in the summation, and such that there exists at least one α with |α| = k and aα 6= 0 ; here, as usual, we have set x = x1 1 . x αn n . Let us denote by C 1 c (Ω) the set of all functions φ which are C with compact support contained in the open set Ω. Let ∆ denote the largest size of those |aα| for which |α| = k. Then for any φ ∈ C c (R), the general bound of Stein’s Lemma (cf Lemma 1 below) applies here in the following form : (1.1) ∣∣∣∣∫ φ(x)eiλf(x)dx∣∣∣∣ 6 C1(k)(∆λ)(‖φ‖L∞ + ‖φ‖L1), for all λ > 0 where C1(k) is a positive constant that depends only on the degree k. Such a bound is quite uniform. Our aim is to improve the exponent −1/k in −1/(k − 1), providing that f cannot be written as (1.2) f(x) = f(x0)± L(x− x0), for some x0 ∈ R and some linear form L on R. If so it is, we shall say that f satisfies the hypothesis Hk,n. Our analog of (1.1) is as follows. Theorem 1. We suppose that f satisfies the hypothesis Hk,n and that Ω is a bounded open set in R. We then have, for any φ ∈ C c (Ω), (1.3) ∣∣∣∣∫ φ(x)eiλf(x)dx∣∣∣∣ 6 C2(f,Ω) ‖φ‖1 λ−1/(k−1), for all λ > 0 where C2(f,Ω) is a positive constant which depends only on f and Ω, and where we have set ‖φ‖1 = ‖φ‖L∞ + ‖φ ‖L∞ . Received by the editors January 12, 2005.
Expression of CD 44 s in Advanced Stage Esophageal Squamous Cell Carcinomas and Other Clinicopathological Prognostic Factors

CD44s is an adhesion molecule which is a member of the cell adhesion molecules family hyaladherins. CD44s has some effects including tumor-endothel interaction, cell motility and migration, cell adhesion and tumor invasion, tumor progression, and metastasing. In this study, we aimed to evaluate the CD44s expression and some other prognostic factors in patients with esophageal squamous cell carcinoma. Between 1999 and 2004, pathological specimens of 35 patients were examined by the Yuzuncu Yil University (YYU) Medical Faculty, Pathology Department and other clinical and laboratory findings were collected from Oncology Department patient files. CD44s staining was positive in 32 patients and negative in 3. The intensity of stained CD44s was positive in 30 and negative in 5 patients. Thirteen patients were well-differentiated, 18 were mid-differentiated, and 4 were poorly differentiated. Inflamatuary reactions were observed in 23 cases. The median survival was 5.3 months and the one year, two year and five year survival rates were 34.2%, 8.6% and 2.9% respectively. Treatment modality, clinical stage and tumour size at the diagnosis time was significant at univariate analysis and only treatment modality was significant in multivariate analysis. Very high CD44s expression was observed in sq cell osephageal cancer patients. CD44s may be an important marker in prognosis. Treatment modality was found as an independent factor on prognosis of osephageal cancer.
Personalizing HIV Therapy, Mission Impossible?

Sustained HIV suppression depends on a number of factors including therapy adherence, management of side effects, viral resistance and individual characteristics of patients and therapeutic settings. Treatment response rates range up to 90% in therapy naive patients but decline to approximately 50% in patients who received several antiretrovirals during treatment history. Furthermore, HIV protease inhibitors (PI) and non nucleoside reverse transcriptase inhibitors (NNRTI) plasma concentrations display high inter- and intra individual variability and the therapeutic window is comparably narrow. In this therapeutic setting the personalization of dosing regimens has been suggested in many cases to tailor the ARV plasma concentrations with the intention to maximize therapy success and minimize side effects in the individual. However, personalizing therapy by modifying the dosing regimen bears the danger of losing therapeutic efficacy, increasing side effects or causing viral resistance. This topical review identifies pharmacokinetic and pharmacodynamic models of antiretroviral therapy appraising the potential application to HIV therapy and discusses its future in the light of new drug classes and fix-dose combinations.
INTRUSION DETECTION SYSTEM USING BIG DATA

In the enormous stream of network traffic, there is no way to identify which packet is benign and which is an anomaly packet. Hence, we intend to develop a new network intrusion detection model using apache-spark to improve the performance and to detect the intrusions while handling the colossal stream of network traffic in IDS. The model can detect known intrusion effectively using real-time analytics and hence identify unknown data schema compared with traditional IDS. The objective of the model addresses the following capabilities: Deep Packet Inspection (DPI) by inspecting the network traffic and examining the properties that describe the intrusion characteristics. Collaborating the vulnerability assessment with human intervention, using C.45 decision tree algorithm, optimizes pattern matching to boost detection rate. The clustered hosts are grouped based on their number of visits in an unique IP. The intrusion classifiers are developed by investigating each IP groups which reflects different properties used for prediction. The prediction model is built over Amrita Big Data Apache-Spark framework as a sequence of workflows. The above workflow is implemented in Amrita Big Data Framework (ABDF) to improve the detection time and performance, the model output provides effective results in detecting DOS attacks and port scanning attacks.
DEVELOPMENT OF A POINT-OF-CARE BOVINE LIVE STOCK HEALTH CONTROL SYSTEM USING ACOUSTOPHORESIS

A microfluidic chip for acoustophoretic raw milk sample preparation, eliminating the need for chemical pretreatment linked to somatic cell counting, was developed. This opens the route to an on-farm platform for live stock health status analysis in the dairy industry. Our previous work has shown the benefits of using acoustophoresis for raw milk analysis [1]. This work presents a combination of acoustophoresis and Coulter Counting to provide a simple point-of-care diagnostic tool to measure somatic cell count (SCC) levels, which indicate udder health [2]. Shorter treatment response times using this system will minimize health hazards for live stock and consumers.
Particle verbs are heads and phrases

One of the most intriguing questions about particle verbs concerns the observation that they sometimes look like phrases and sometimes like heads. In this paper I suggest that particle verbs can in fact be represented by two different structures they can appear either as complex Vs consisting of the particle and the verb or alternatively as V’or VP-nodes consisting of the verb and a phrasal particle complement. Different aspects of grammar highlight different sides of the hybrid character of particle verbs. Table 1 lists some of the phenomena that illustrate the ambiguous behavior of the verb-particle construction:
Nab Technology : A Drug Delivery Platform Utilising Endothelial gp 60 Receptor-based Transport and Tumour-derived SPARC for Targeting I

Vlce Pnsldent o f Research and Development Abraxls BloScience, UG 11755 Wllshln Blvd, Sulte 2000, Lor Angeles, CA 90025. US RI: +I H O 883 1300, Fax: +1 310 998 8553, Emall: ndwalOabraxlsbio.com NeII Desal is Vice President of Research and Development at Abraxis Bioscience, Inc. (ABI), in Los Angeles. CA. Dr Desai is an inventor of Abraxis' nanotechnology and nanoparticle-albumin bound (nab") drug deiivery platform and discovered itr novel targeted biological pathway. He was primarily responsible for the development of the nanotechnology drug Abraxane*, which was apprwed by the FDA in January 2005 as the first n a new c ass of nanotnerapeut cs for the treatment of metastatic breast cancer Pr or to lo n na ABI. Dr Desa~ was Sen or Dlrector of B ooolvmer Research a V voRx. ,nc. wnere ne oeve.owd novel , , , . encapsulation systems for living cells and was part of the team that performed the worid'sfim su~cessfui encapsulated islet cell transplant in a diabetic patient. Dr Desai has more than 17 years' experience in the research and development of nwei drug delivery systems and blommpatibie polymers. He holds over 60 issued US and foreign patents and has authored wer 40 peer-reviewed publications. Dr Desai hdds an MS and a PhD in Chemical Engineering from the University of Texas at Austin and a 8S in Chemical Engineering from the University of Bombay.
Consumption, the persistence of shocks, and asset pricing puzzles

This paper studies an equilibrium asset pricing model in which the endowment is the sum of two components: one permanent, the other transitory. Permanent shocks are assumed to be rare events and are modeled as realizations of a Poisson process. The transitory component is modeled as a diffusion. Empirical support is offered to justify this decomposition. It is shown analytically that there is a direct relation between the predictability of dividends and the volatility of returns, and that excess volatility is essentially an intertemporal substitution phenomenon. Moreover, in the presence of transitory shocks, intertemporal substitution explains most of the volatility of returns. With the permanent component modeled as a pure jump process, jump risk contributes to increase the equity premium, and fundamentally to reduce the risk-free interest rate, but it has no role in explaining returns volatility beyond the volatility of consumption growth. Numerical results show that the model developed in this paper is able to generate equity premium, volatility of returns and volatility of the risk-free rate in line with the data for levels of risk aversion lower than nine, and rate of intertemporal preference higher than zero. JEL Classification: G12,E21,C22 * This paper is an essay from my dissertation, written when I was a graduate student at the Department of Economics of the University of Maryland. I thank Michael Binder, Fernando Broner, and Dilip Madan for insightful comments and suggestions. I am also grateful to John Haltiwanger, and seminar participants at the University of Maryland and Eurandom. All remaining errors are mine. Address for correspondence: Eurandom, P.O Box 513, 5600 MB, Eindhoven, The Netherlands. Email: rodriguez@eurandom.tue.nl.