LLukas22/scidocs huggingface dataset:
Ozonation of drinking water : Part I . Oxidation kinetics and product formation

The oxidation of organic and inorganic compounds during ozonation can occur via ozone or OH radicals or a combination thereof. The oxidation pathway is determined by the ratio of ozone and OH radical concentrations and the corresponding kinetics. A huge database with several hundred rate constants for ozone and a few thousand rate constants for OH radicals is available. Ozone is an electrophile with a high selectivity. The second-order rate constants for oxidation by ozone vary over 10 orders of magnitude, between o0.1M s 1 and about 7 10M s . The reactions of ozone with drinking-water relevant inorganic compounds are typically fast and occur by an oxygen atom transfer reaction. Organic micropollutants are oxidized with ozone selectively. Ozone reacts mainly with double bonds, activated aromatic systems and non-protonated amines. In general, electron-donating groups enhance the oxidation by ozone whereas electron-withdrawing groups reduce the reaction rates. Furthermore, the kinetics of direct ozone reactions depend strongly on the speciation (acid-base, metal complexation). The reaction of OH radicals with the majority of inorganic and organic compounds is nearly diffusion-controlled. The degree of oxidation by ozone and OH radicals is given by the corresponding kinetics. Product formation from the ozonation of organic micropollutants in aqueous systems has only been established for a few compounds. It is discussed for olefines, amines and aromatic compounds. r 2002 Elsevier Science Ltd. All rights reserved.
Safety of Gadoterate Meglumine (Gd-DOTA) as a Contrast Agent for Magnetic Resonance Imaging

BACKGROUND
Safety is a primary concern with contrast agents used for MRI. If precautions could be taken before the repeated administration of gadolinium-based contrast media, then the awareness and management of adverse reactions would be more efficient.


OBJECTIVES
To assess the safety and efficacy of gadoterate meglumine (Gd-DOTA) [Magnescope® in Japan, Dotarem® in other countries], a gadolinium-based contrast agent, in patients undergoing imaging of the brain/spinal cord and/or trunk/limbs, and to identify factors associated with the onset of adverse reactions.


METHODS
The study ran for 4 years and included 3444 cases. The study was conducted before it became known that gadolinium-based contrast agents could trigger the development of nephrogenic systemic fibrosis. Patients for whom the contrast agent was indicated and who underwent imaging of the brain/spinal cord and/or trunk/limbs by MRI were enrolled. There were 1300 inpatients who were followed up during hospitalization (for several days), and 2144 outpatients who were followed up for at least 2 hours on-site. After Gd-DOTA administration, 13 patient baseline characteristics were used to explore factors that might predict a greater likelihood of acute non-renal adverse reactions. The physician's appraisal of the efficacy of Gd-DOTA was also assessed.


RESULTS
A total of 40 adverse reactions were recorded in 32 patients, giving an overall incidence of adverse reactions of 0.93%. Gastrointestinal disorders were the most commonly reported adverse reactions (0.49%). Most adverse reactions reported were of mild intensity and no serious adverse reactions were reported. This study found that statistically significant risk factors for adverse reactions were general patient condition, liver disorder, kidney disorder, health complications, concomitant treatments, and Gd-DOTA dose (although the incidence of adverse reactions was not dose dependent). In the majority of cases (99.53%), the efficacy of Gd-DOTA was rated as 'effective' or 'very effective'; only the presence of kidney disorder was associated with a significantly greater likelihood of Gd-DOTA inefficacy.


CONCLUSION
Overall, this post-marketing surveillance study did not reveal any untoward or unexpected findings concerning the safety or efficacy of Gd-DOTA. The low incidence of adverse reactions (<1%) and the absence of serious adverse reactions reported during the survey period showed that Gd-DOTA was very well tolerated. The use of Gd-DOTA as an MRI-enhancing contrast medium in the clinical practice setting appears to be safe and effective.
A 72-week randomized study of the safety and efficacy of a stavudine to zidovudine switch at 24 weeks compared to zidovudine or tenofovir disoproxil fumarate when given with lamivudine and nevirapine.

BACKGROUND
Due to superior long-term toxicity profiles, zidovudine (AZT) and tenofovir disoproxil fumarate (TDF) are preferred over stavudine (d4T) for first-line antiretroviral regimens. However, short-term d4T use could be beneficial in avoiding AZT-induced anaemia.


METHODS
We randomized (1:1:1) 150 treatment-naive Thai HIV-infected adults with CD4(+) T-cell count <350 cells/mm(3) to arm 1 (24-week GPO-VIR S30(®) [d4T plus lamivudine (3TC) plus nevirapine (NVP)] followed by 48-week GPO-VIR Z250(®) [AZT plus 3TC plus NVP]), arm 2 (72-week GPO-VIR Z250(®)) or arm 3 (72-week TDF plus emtricitabine [FTC] plus NVP). Haemoglobin (Hb), dual energy x-ray absorptiometry, neuropathic signs, estimated glomerular filtration rate (eGFR), CD4(+) T-cell count, plasma HIV RNA and adherence were assessed.


RESULTS
In an intention-to-treat analysis, mean Hb decreased from baseline to week 24 in arm 2 compared with arm 1 (-0.19 versus 0.68 g/dl; P=0.001) and arm 3 (0.48 g/dl; P=0.010). Neuropathic signs were more common in arm 2 compared with arm 3 (20.4 versus 4.2%; P=0.028) at week 24. There were no differences in changes in peripheral fat and eGFR from baseline to weeks 24 and 72 among arms. CD4(+) T-cell count increased more in arm 1 than arms 2 and 3 from baseline to week 24 (168 versus 117 and 118 cells/mm(3); P=0.01 and 0.02, respectively) but the increase from baseline to week 72 was similar among arms.


CONCLUSIONS
A 24-week d4T lead-in therapy caused less anaemia and greater initial CD4(+) T-cell count increase than initiating treatment with AZT. This strategy could be considered in patients with baseline anaemia or low CD4(+) T-cell count. If confirmed in a larger study, this may guide global recommendations on antiretroviral initiation where AZT is more commonly used than TDF.
Effective Web Log Mining and Online Navigational Pattern Prediction: A Survey

The web has become the world's largest repository of knowledge. Web usage mining is the process of discovering knowledge from the interactions generated by the user in the form of access logs, cookies, and user sessions data. Web Mining consists of three different categories, namely Web Content Mining, Web Structure Mining, and Web Usage Mining (is the process of discovering knowledge from the interaction generated by the users in the form of access logs, browser logs, proxy-server logs, user session data, cookies). Accurate web log mining results and efficient online navigational pattern prediction are undeniably crucial for tuning up websites and consequently helping in visitors’ retention. Like any other data mining task, web log mining starts with data cleaning and preparation and it ends up discovering some hidden knowledge which cannot be extracted using conventional methods. After applying web mining on web sessions we will get navigation patterns which are important for web users such that appropriate actions can be adopted. Due to huge data in web, discovery of patterns and there analysis for further improvement in website becomes a real time necessity. The main focus of this paper is using of hybrid prediction engine to classify users on the basis of discovered patterns from web logs. Our proposed framework is to overcome the problem arise due to using of any single algorithm, we will give results based on comparison of two different algorithms like Longest Common Sequence (LCS) algorithm and Frequent Pattern (Growth) algorithm. Keywords— Web Usage Mining, Navigation Pattern, Frequent Pattern (Growth) Algorithm. ________________________________________________________________________________________________________
Growth performance of Cobb broilers given varying concentrations of Malunggay (Moringa oleifera Lam.) aqueous leaf extract.

A study was conducted to determine the growth performance of Cobb broilers supplemented with varying concentrations of Moringa oleifera Aqueous Leaf Extract (MoALE) via the drinking water. A total of four hundred day-old chicks were randomly distributed into four treatment groups, replicated four times with twenty-five broilers per replicate. The growth performance of broilers was evaluated based on their feed consumption, live weight, feed conversion ratio (FCR) and return of investment (ROI). Results of the study showed that at 90 mL MoALE (T3), the feed consumption of broilers was consistently lower than the control group (T0) and this was statistically significant (P<0.01). The live weight of broilers given 30 mL (T1), 60 mL (T2) and 90 mL (T3) MoALEs were significantly higher than the control group (T0) and this was also statistically significant (P<0.01). In terms of feed conversion ratio (FCR), the MoALE treated broilers (T1-T3) were more efficient converter of feeds into meat than the control group (T0) and this was statistically significant (P<0.01). Furthermore, the return of investment (ROI) of MoALE treated broilers (T1-T3) was significantly higher (P<0.01) than the control group (T0) with a revenue per peso invested of Php 0.62 in T1 and T2, and Php 0.63 in T3 compared to Php 0.50 in T0.
Low-energy ηd-resonance

Abstract: Elastic ηd-scattering is considered within the Alt-Grassberger-Sandhas (AGS) formalism for various ηN input data. A three-body resonant state is found close to the ηd threshold. This resonance is sustained for different choices of the two-body ηN-scattering length aηN. The position of the resonance moves towards the ηd threshold when ReaηN is increased, and turns into a quasi-bound state at ReaηN∼ 0.7-0.8 fm depending on the choice of ImaηN.
Service-Oriented Computing

The Internet of Things (IoT) paradigm refers to the network of physical objects or “things” embedded with electronics, software, sensors, and connectivity to enable objects to exchange data with servers, centralized systems, and/or other connected devices based on a variety of communication infrastructures. IoT makes it possible to sense and control objects creating opportunities for more direct integration between the physical world and computer-based systems. IoT will usher automation in a large number of application domains, ranging from manufacturing and energy management (e.g. SmartGrid), to healthcare management and urban life (e.g. SmartCity). However, because of its fine-grained, continuous and pervasive data acquisition and control capabilities, IoT raises concerns about the security and privacy of data. Deploying existing data security solutions to IoT is not straightforward because of device heterogeneity, highly dynamic and possibly unprotected environments, and large scale. In this talk, after outlining key challenges in data security and privacy, we present initial approaches to techniques and services for securing IoT data, including efficient and scalable encryption protocols, software protection techniques for small devices, and fine-grained data packet loss analysis for sensor networks. Bio: Elisa Bertino is professor of computer science at Purdue University, and serves as Director of Purdue Cyber Center and Research Director of the Center for Information and Research in Information Assurance and Security (CERIAS). She is also an adjunct professor of Computer Science & Info Tech at RMIT. Prior to joining Purdue in 2004, she was a professor and department head at the Department of Computer Science and Communication of the University of Milan. She has been a visiting researcher at the IBM Research Laboratory (now Almaden) in San Jose, at the Microelectronics and Computer Technology Corporation, at Rutgers University, at Telcordia Technologies. Her recent research focuses on data security and privacy, digital identity management, policy systems, and security for drones and embedded systems. She is a Fellow of ACM and of IEEE. She received the IEEE Computer Society 2002 Technical Achievement Award, the IEEE Computer Society 2005 Kanai Award and the 2014 ACM SIGSAC outstanding contributions award. She is currently serving as EiC of IEEE Transactions on Dependable and Secure Computing.
Heritable CRISPR/Cas9-Mediated Genome Editing in the Yellow Fever Mosquito, Aedes aegypti

In vivo targeted gene disruption is a powerful tool to study gene function. Thus far, two tools for genome editing in Aedes aegypti have been applied, zinc-finger nucleases (ZFN) and transcription activator-like effector nucleases (TALEN). As a promising alternative to ZFN and TALEN, which are difficult to produce and validate using standard molecular biological techniques, the clustered regularly interspaced short palindromic repeats/CRISPR-associated sequence 9 (CRISPR/Cas9) system has recently been discovered as a "do-it-yourself" genome editing tool. Here, we describe the use of CRISPR/Cas9 in the mosquito vector, Aedes aegypti. In a transgenic mosquito line expressing both Dsred and enhanced cyan fluorescent protein (ECFP) from the eye tissue-specific 3xP3 promoter in separated but tightly linked expression cassettes, we targeted the ECFP nucleotide sequence for disruption. When supplying the Cas9 enzyme and two sgRNAs targeting different regions of the ECFP gene as in vitro transcribed mRNAs for germline transformation, we recovered four different G1 pools (5.5% knockout efficiency) where individuals still expressed DsRed but no longer ECFP. PCR amplification, cloning, and sequencing of PCR amplicons revealed indels in the ECFP target gene ranging from 2-27 nucleotides. These results show for the first time that CRISPR/Cas9 mediated gene editing is achievable in Ae. aegypti, paving the way for further functional genomics related studies in this mosquito species.
"Anything as a Service" for 5G Mobile Systems

5G network architecture and its functions are yet to be defined. However, it is generally agreed that cloud computing, network function virtualization (NFV), and software defined networking (SDN) will be key enabling technologies for 5G. Indeed, putting all these technologies together ensures several advantages in terms of network configuration flexibility, scalability, and elasticity, which are highly needed to fulfill the numerous requirements of 5G. Furthermore, 5G network management procedures should be as simple as possible, allowing network operators to orchestrate and manage the lifecycle of their virtual network infrastructures (VNIs) and the corresponding virtual network functions (VNFs), in a cognitive and programmable fashion. To this end, we introduce the concept of “Anything as a Service” (ANYaaS), which allows a network operator to create and orchestrate 5G services on demand and in a dynamic way. ANYaaS relies on the reference ETSI NFV architecture to orchestrate and manage important services such as mobile Content Delivery Network as a Service (CDNaaS), Traffic Offload as a Service (TOFaaS), and Machine Type Communications as a Service (MTCaaS). Ultimately, ANYaaS aims for enabling dynamic creation and management of mobile services through agile approaches that handle 5G network resources and services.
Girona 500 AUV: From Survey to Intervention

This paper outlines the specifications and basic design approach taken on the development of the Girona 500, an autonomous underwater vehicle whose most remarkable characteristic is its capacity to reconfigure for different tasks. The capabilities of this new vehicle range from different forms of seafloor survey to inspection and intervention tasks.
Mood Detection : Implementing a facial expression recognition system

Facial expressions play a significant role in human dialogue. As a result, there has been considerable work done on the recognition of emotional expressions and the application of this research will be beneficial in improving human-machine dialogue. One can imagine the improvements to computer interfaces, automated clinical (psychological) research or even interactions between humans and autonomous robots.
Zero-Shot Recognition via Structured Prediction

• Test-time: For each image feature , identify max scoring source descriptor from a collection of (unseen) classes, and label the test image using the label of the source descriptor. This Paper : Transductive Zero-Shot Recognition • Problem: projection domain shift between source and target data leads to ZSR degradation. • Solution: Model domain shift as small distortion in predicted cluster centers based on seen classes. Then solve a structured matching problem to improve alignment between source and target domain.
Biodiesel Production from Azolla filiculoides (Water Fern)

Purpose: To assess the potential of Azolla filiculoides, total body collected from a rice farm in northern Iran as source for biodiesel production. Methods: Solvent extraction using Soxhlet apparatus with chloroform-methanol (2:1 v/v) solvent blend was used to obtain crude oil from freeze-dried the Azolla plant. Acid-catalyzed transesterification was used to convert fatty acids (FA), monoglycerides (MG), diglycerides (DG) and triglycerides (TG) in the extracts to fatty acid methyl esters (FAMEs) by acid-catalyzed methylation. Gas chromatography–mass spectrometry (GC–MS) was employed to analyze the FAMEs in the macroalgae biodiesel. Results: The presence of myristic acid (C14:0), palmitic acid (C16:0), palmitoleic acid (C16:1), myristic acid (C14:0), stearic acid (C18:3), oleic acid (C18:1) and linoleic acid 9C18:2), eicosenoic acid (C20:1), eicosapentaenoic acid (C20:5), erucic acid (C22:1) and docosahexaenoic acid (C22:6) in the macroalgae biodiesel was confirmed. Conclusion: The results indicate that biodiesel can be produced from macroalgae and that water fern is potentially an economical source of biodiesel due its ready availability and probable low cost.
Prospective analysis of long-term psychosocial outcomes in breast reconstruction: two-year postoperative results from the Michigan Breast Reconstruction Outcomes Study.

OBJECTIVE
To prospectively evaluate the psychosocial outcomes and body image of patients 2 years postmastectomy reconstruction using a multicenter, multisurgeon approach.


BACKGROUND
Although breast reconstruction has been shown to confer significant psychosocial benefits in breast cancer patients at year 1 postreconstruction, we considered the possibility that psychosocial outcomes may remain in a state of flux for years after surgery.


METHODS
Patients were recruited as part of the Michigan Breast Reconstruction Outcome Study, a 12 center, 23 surgeon prospective cohort study of mastectomy reconstruction patients. Two-sided paired sample t tests were used to compare change scores for the various psychosocial subscales. Multiple regression analysis was used to determine whether the magnitude of the change score varied by procedure type.


RESULTS
Preoperative and postoperative year 2 surveys were received from 173 patients; 116 with immediate and 57 with delayed reconstruction. For the immediate reconstruction cohort, significant improvements were observed in all psychosocial subscales except for body image. This occurred essentially independent of procedure type. In the cohort with delayed reconstruction, significant change scores were observed only in body image. Women with transverse rectus abdominis musculocutaneous flaps had significantly greater gains in body image scores (P = 0.003 and P = 0.034, respectively) when compared with expander/implants.


CONCLUSIONS
General psychosocial benefits and body image gains continued to manifest at 2 years postmastectomy reconstruction. In addition, procedure type had a surprisingly limited effect on psychosocial well being. With outcomes evolving beyond year 1, these data support the need for additional longitudinal breast reconstruction outcome studies.
Approximation by exponential sums revisited ✩

Article history: Received 15 May 2009 Accepted 15 August 2009 Available online 2 September 2009 Communicated by Ginette Saracco
ECLiPSe - from LP to CLP

ECLPS is a Prolog-based programming system, aimed at the development and deployment of constraint programming applications. It is also used for teaching most aspects of combinatorial problem solving, e.g. problem modelling, constraint programming, mathematical programming, and search techniques. It uses an extended Prolog as its high-level modelling and control language, complemented by several constraint solver libraries, interfaces to third-party solvers, an integrated development environment and interfaces for embedding into host environments. This paper discusses language extensions, implementation aspects, components and tools that we consider relevant on the way from Logic Programming to Constraint Logic Programming. To appear in Theory and Practice of Logic Programming (TPLP).
Stock time series pattern matching: Template-based vs. rule-based approaches

One of the major duties of financial analysts is technical analysis. It is necessary to locate the technical patterns in the stock price movement charts to analyze the market behavior. Indeed, there are two main problems: how to define those preferred patterns (technical patterns) for query and how to match the defined pattern templates in different resolutions. As we can see, defining the similarity between time series (or time series subsequences) is of fundamental importance. By identifying the perceptually important points (PIPs) directly from the time domain, time series and templates of different lengths can be compared. Three ways of distance measure, including Euclidean distance (PIP-ED), perpendicular distance (PIP-PD) and vertical distance (PIP-VD), for PIP identification are compared in this paper. After the PIP identification process, both templateand rule-based pattern-matching approaches are introduced. The proposed methods are distinctive in their intuitiveness, making them particularly user friendly to ordinary data analysts like stock market investors. As demonstrated by the experiments, the templateand the rule-based time series matching and subsequence searching approaches provide different directions to achieve the goal of pattern identification. r 2006 Elsevier Ltd. All rights reserved.
PPP-RTK: Results of CORS Network-Based PPP with Integer Ambiguity Resolution

During the last decade the technique of CORS-based Network RTK has been proven capable of providing cmlevel positioning accuracy for rovers receiving GNSS correction data from the CORS network. The technique relies on successful integer carrier-phase ambiguity resolution at both network and user level: at the level of the CORS network, ambiguity resolution is a prerequisite in order to determine very precise atmospheric corrections for (mobile) users, while these users need to resolve their integer ambiguities (with respect to a certain CORS network master reference station) to obtain precise cmlevel positioning accuracy. In case of Network RTK a user thus needs corrections from the network, plus the GNSS data of one of the CORS stations. In practice, there exists a variety of implementations of the Network RTK concept, of which VRS, FKP and MAC are best known [1], [2], [3], [4]. In this contribution we discuss a closely related concept, PPP-RTK, and show its performance on two CORS networks.
A Real-Time Approach to Process Control

Contents Preface xi Acknowledgements xiii Endorsement xv About the authors xvii 1 A brief history of control and simulation 1