Miracle-dz/UniFAR-FTUs huggingface dataset:
Exchanges Call for Contributions Newsletter of the Climate Variability and Predictability Programme

CLIVAR is an international research programme dealing with climate variability and predictability on timescales from months to centuries. We would like to invite the CLIVAR community to submit papers to CLIVAR Exchanges for issue 33. The overarching topic will be on science related to Asian Monsoon. The deadline for this issue will be January 31st 2005. Efforts to improve climate prediction are at the heart of CLIVAR. In TOGA, and in the first phase of CLIVAR, much attention was focused on the problem of forecasting ENSO and its climate impacts, particularly those in the Indo-Pacific region. Rather less attention has been addressed to forecasting the climate of the Atlantic region, although a number of centres do now routinely issue seasonal forecasts for various aspects of Atlantic climate. Moreover, significant progress has been made both in identifying potentially predictable phenomena in the Atlantic region, and in developing statistical and dynamical prediction systems. It was to give focus to the challenges of Atlantic Sector climate prediction that a workshop was organised at the University of Reading in April of this year. The specific aims of the workshop were: 1. To provide an up to date assessment of the state of knowledge concerning the predictability of climate in the Atlantic Sector, with particular emphasis on the role of the Atlantic Ocean. 2. To improve communication between the operational prediction centres and regional fora and the research community concerning the predictability of Atlantic Sector climate. It is now over 3 months since the 1 st International CLIVAR Science Conference in which many of you will have participated. The Conference, held in Baltimore USA from June 21-25 2004, was, by any measure, an enormously informative, enjoyable and successful event. It provided a comprehensive overview of progress with CLIVAR science over the past 5 years, a host of new results expressed in a wide variety of talks and posters, and directional pointers for the future progress of our science. The Conference attracted over 640 registered attendees from 56 countries. More than 650 posters were displayed on all aspects of CLIVAR science and we were pleased to present 16 awards for student posters at 2 " breakfast " events. 35 multi-author oral presentations were made and 9 individuals led end of day discussions. In addition 4 press briefings involving 17 panelists and 4 moderators were held with several stories going to print. On page 18 you can …
Trichromatic Online Matching in Real-Time Spatial Crowdsourcing

The prevalence of mobile Internet techniques and Online-To-Offline (O2O) business models has led the emergence of various spatial crowdsourcing (SC) platforms in our daily life. A core issue of SC is to assign real-time tasks to suitable crowd workers. Existing approaches usually focus on the matching of two types of objects, tasks and workers, or assume the static offline scenarios, where the spatio-temporal information of all the tasks and workers is known in advance. Recently, some new emerging O2O applications incur new challenges: SC platforms need to assign three types of objects, tasks, workers and workplaces, and support dynamic real-time online scenarios, where the existing solutions cannot handle. In this paper, based on the aforementioned challenges, we formally define a novel dynamic online task assignment problem, called the trichromatic online matching in real-time spatial crowdsourcing (TOM) problem, which is proven to be NP-hard. Thus, we first devise an efficient greedy online algorithm. However, the greedy algorithm can be trapped into local optimal solutions easily. We then present a threshold-based randomized algorithm that not only guarantees a tighter competitive ratio but also includes an adaptive optimization technique, which can quickly learn the optimal threshold for the randomized algorithm. Finally, we verify the effectiveness and efficiency of the proposed methods through extensive experiments on real and synthetic datasets.
The Process of Direct Foreign Investment

A considerable amount of the economic literature concerning direct foreign investment (DFI) has been devoted to the question of why firms choose to become multinational. This question has occupied both theorists of multinational enterprises (MNE's) [1; 6; 7; 9; 11] and those who have done statistical studies of MNE's [2; 3; 8]. Certainly a firm's decision to invest directly abroad-rather than export goods produced at a single location-is a central question in the analysis of MNE's. As the number of MNE's continues to rise, though, it becomes increasingly useful to investigate the behavior of firms that are already multinational. Is it true, for example, that the factors that initially make a firm more likely to become a multinational also cause the firm to increase the size of its foreign investment? Kogut has argued that "[t]here is . a fallacy of explanation of genesis in failing to distinguish between the initial investment decision and the subsequent incremental investment flows [10, 38]. " He argues that DFI should be analyzed as a flow and that the MNE engages in this flow of foreign investment in order to capitalize on the flexibility inherent in the firm's multinationality. Thus, DFI should be studied as a "process" and not as a onetime decision. This paper formally develops this idea in the context of a model of international trade developed by Helpman that incorporates MNE's [6]. The rest of this paper is organized as follows: Section II contains a brief summary of the model that Helpman has developed. As an extension of Helpman, the model is used to develop the distinction between the decision to become multinational and the decision to add incremental flows to the direct foreign investment. Section III discusses a method for testing whether there is a distinction between the decision to become a multinational and the decision to continue flows of incremental investment. Section IV presents the results of such a test, using a sample of U.S. multinational firms. Conclusions are presented in section V.
Clinical innovation for neurodegenerative diseases

Neurodegenerative diseases, including Alzheimer’s disease (AD), Parkinson’s disease, amyotrophic lateral sclerosis and Huntington’s disease, are devastating diseases, with huge unmet medical needs. Although it has been estimated that the pharmaceutical industry has already spent billions of US dollars on developing a treatment for AD, the output so far has been dismal. We, like many others, hope that this long history of failures will soon be replaced by success. Whilst symptomatic treatments are valuable, especially those with clearly observable functional outcomes (e.g., l-DOPA in Parkinson’s disease), disease modification in terms of halting, slowing or preventing the evolution of neurodegenerative disorders remains the Holy Grail and no disease modifier product has yet been approved in any neurodegenerative disorder – with the possible exception of riluzole for amyotrophic lateral sclerosis. High cost, long timelines and low probability of success have led to reluctance by the pharmaceutical industry to invest in this area, despite the huge rewards that a successful treatments would reap [1]. Some companies have already opted to leave this area; others have decided to ‘reef the sail’. In contrast, publically funded efforts are growing. During the first decade of the 21st century, AD national plans were launched in a variety of different European countries. The US President signed the National AD Project Act in January 2011. The first European-wide Neurodegenerative Disease Research was launched in 2012. In 2013 the NIH total expenditure on AD research will reach an all-time high of US $529 million. A common belief is that public–private partnerships (PPPs) will generate breakthroughs in preclinical and clinical areas [2]. The Innovative Medicine Initiative (IMI) represents one such collaboration, which joins European governments and pharmaceutical companies together to speed up the development of better and safer medicines for patients. The IMI PharmaCog project was launched in 2010 and is already reporting data related to improved early preclinical and clinical experimental designs for predicting the cognitive properties of new drug candidates [101].
Serum immunoglobulins (IgG, IgA, IgM) in chronic hepatitis C. A comparison with non-cirrhotic alcoholic liver disease.

BACKGROUND/AIMS Serum immunoglobulin concentrations are commonly elevated in patients with liver cirrhosis. Immunoglobulin class increase may vary depending on the cause of liver disease. Hepatitis C virus is, together with alcohol, a leading cause of chronic liver disease. The present study aimed to evaluate serum IgG, IgA and IgM levels in chronic hepatitis C. Results were compared with those of patients with non-cirrhotic alcoholic liver disease and healthy controls. Special attention was given to cases with minimal liver disease, as an approach to evaluate if the causing agent, independently of liver damage, influences serum immunoglobulin levels. METHODOLOGY A total of 274 patients with histologically-proven chronic hepatitis C, 121 alcoholics with non-cirrhotic liver disease (steatosis or alcoholic hepatitis), and 75 healthy controls were studied. Serum IgG, IgA, and IgM were assayed by nephelometry. RESULTS Serum IgG was increased in patients with chronic hepatitis C with respect to both alcoholics (p < 0.001) and healthy controls (p < 0.001). IgG levels were similar in alcoholics and in controls. IgA was increased in patients with non-cirrhotic alcoholic liver disease with respect to both chronic hepatitis C patients (p < 0.001) and controls (p < 0.001). IgA values were similar in subjects with chronic hepatitis C and controls. Selective IgG or IgA alteration was present in cases with minimal liver disease (chronic hepatitis C with a Knodell index equal or lower than 3, and alcoholics with liver steatosis, respectively). CONCLUSIONS Hepatitis C virus and alcohol are linked to a selective increase of serum IgG and IgA, respectively, even in cases with mild or minimal liver disease.
Nuclear medical inpatient treatment in Germany

Summary All public licensed hospitals of Germany are obligated since 2004 to establish and to publish a structured biennial quality report. The aim of this study was to analyse the quality reports from 2008 of clinics with nuclear-medicine therapy ward and to investigate developments for the inpatient nuclear-medicine therapy by comparing the results with the quality reports of the years 2004 and 2006. Methods: All available structured quality reports of clinics with a nuclear-medicine therapy ward of the years 2004, 2006 and 2008 were evaluated. Results: The total number of inpatient treatment cases in 2008 amounted to 54 190 (2006: 54 884; 2004: 57 366). This corresponds to a decrease of 5.5% in comparison to 2004. The number of the therapy wards decreased at the same time to currently 117 (2006: 120; 2004: 124). Remarkable changes were found in the spectrum of the main diagnosis. Thus, the most frequent diagnosis with the ICD-code E05 (hyperthyroidism) decreased continuously from 37 747 treatments in 2004 and 34 764 in 2006 to 31 756 in the year 2008. In contrast, the ICD-diagnoses for thyroid cancer (C73, Z08) with 14 761 cases in 2008 increased with time (2006: 13 426; 2004: 12 581). Conclusions: In analogy to the observations from Europe after introduction of an iodine prophylaxis the improved iodine supply in Germany has led to a decline of the radioiodine therapy due to hyperthyroidism.
A Fast and Fuzzy Functional Simulator of Inexact Arithmetic Operators for Approximate Computing Systems

Inexact operators are developed to exploit the tolerance of an application to imprecisions. These operators aim at reducing system energy consumption and memory footprint. In order to integrate the appropriate inexact operators in a complex system, the Quality of Service of the approximate system must be thoroughly studied through simulation. However, when simulating on a PC or workstation, the custom bit-level structures of inexact operators are not implemented in the instruction set of the simulating architecture. Consequently, the simulation requires a costly emulation, leading to expensive bit-level simulations. This paper proposes a new "Fast and Fuzzy" functional simulation method for inexact operators whose probabilistic behavior is correlated with the Most Significant Bits of the input operands. The proposed method processes real signal data and simplifies the error model for inexact operators, accelerating the simulation of the system. The modelization accuracy of the error can be controlled by a parameter called fuzzyness degree F. Using the proposed method, the bit-accurate logic-level simulation of inexact operators is replaced by an exact operator to which a pseudo-random error variable is added. Experiments on 16-bit operators show that the proposed simulation method, when compared to a bit-accurate logic level simulation, is up to 44 times faster.
Evaluating Predictive Knowledge

Predictive Knowledge (PK) is a group of approaches to machine perception and knowledgability using large collections of predictions made online in real-time through interaction with the environment. Determining how well a collection of predictions captures the relevant dynamics of the environment remains an open challenge. In this paper, we introduce specifications for sensorimotor baselines and robustness-totransfer metrics for evaluation of PK. We illustrate the use of these metrics by comparing variant architectures of General Value Function (GVF) networks. Predictive Knowledge A key challenge for machine intelligence is that of representation: a system’s performance is tied to its ability to perceive and represent its environment. Predictive knowledge representations use large collections of predictions to model the environment. An agent continually anticipates its sensation from its environment by making many predictions about the dynamics of its environment with respect to its behaviour (Modayil, White, and Sutton 2014). These predictions about expected sensation can then be used to inform an agent’s internal representation of its environment (Littman and Sutton 2002). Other proposals describe inter-relations of predictions, similar to TD Networks (Tanner and Sutton 2005; Makino and Takagi 2008) to enable abstract, conceptual representations by making predictions of predictions (Schapire and Rivest 1988). In this paper we discuss the subtleties of evaluation predictive representation and propose two complimentary techniques. We specifically consider PK methods that 1) are able to expand their representations by proposing new predictions, 2) are able to self-verify their predictions through interaction with their environment, and 3) are able continually learn their predictions on-line. To examine these evaluation metrics we use the General Value Function framework for predictive representations (White 2015). GVFs estimate the expected discounted return of a signal C defined as Gt = P1 k=0( Qk j=1( t+j))Ct+k+1. Value is estimated with respect to a specific policy ⇡, discount function , and cumulant c: v(s;⇡, , c) = E⇡[Gt|St = s]. The parameters c, ⇡, and are the question parameters which specify what a GVF is about; the answer paramEnvironment How many
Solution NMR structure of the BRCT domain from Thermus thermophilus DNA ligase

3 Introduction . 3 I. STRUCTURE-BASED FUNCTIONAL GENOMICS. 3 Overview.3 Determining three -dimensional protein structure . 4 II. SOLUTION NMR STRUCTURE DETERMINATION . 6 Overview.6 Recording NMR spectra . 6 Processing NMR spectra . 7 III. T HE BRCT DOMAIN . 9 Methods.11 SAMPLE PREPARATION. 11 RECORDING/PROCESSING NMR SPECTRA.12 SEQUENTIAL RESONANCE ASSIGNMENTS.13 COLLECTION OF STRUCTURAL CONSTRAINTS. 14 Results. 15 SEQUENTIAL RESONANCE ASSIGNMENTS.15 NMR STRUCTURE CALCULATION.17 STRUCTURE DESCRIPTION. 17 COMPARISON WITH PREVI OUS STRUCTURE DETERMINATION.19 STRUCTURAL RELEVANCE. 20 Conclusion.22 CMap Connectivity Image. 23 Table 1.24 Table 2.25 Table 3.26 Acknowledgements.27 Works Cited . 28 TABLE OF CONTENTS
Combining HW/SW Mechanisms to Improve NUMA Performance of Multi-GPU Systems

Historically, improvement in GPU performance has been tightly coupled with transistor scaling. As Moore's Law slows down, performance of single GPUs may ultimately plateau. To continue GPU performance scaling, multiple GPUs can be connected using system-level interconnects. However, limited inter-GPU interconnect bandwidth (e.g., 64GB/s) can hurt multi-GPU performance when there are frequent remote GPU memory accesses. Traditional GPUs rely on page migration to service the memory accesses from local memory instead. Page migration fails when the page is simultaneously shared between multiple GPUs in the system. As such, recent proposals enhance the software runtime system to replicate read-only shared pages in local memory. Unfortunately, such practice fails when there are frequent remote memory accesses to read-write shared pages. To address this problem, recent proposals cache remote shared data in the GPU last-level-cache (LLC). Unfortunately, remote data caching also fails when the shared-data working-set exceeds the available GPU LLC size. This paper conducts a combined performance analysis of state-of-the-art software and hardware mechanisms to improve NUMA performance of multi-GPU systems. Our evaluations on a 4-node multi-GPU system reveal that the combination of work scheduling, page placement, page migration, page replication, and caching remote data still incurs a 47% slowdown relative to an ideal NUMA-GPU system. This is because the shared memory footprint tends to be significantly larger than the GPU LLC size and can not be replicated by software because the shared footprint has read-write property. Thus, we show that existing NUMA-aware software solutions require hardware support to address the NUMA bandwidth bottleneck. We propose Caching Remote Data in Video Memory (CARVE), a hardware mechanism that stores recently accessed remote shared data in a dedicated region of the GPU memory. CARVE outperforms state-of-the-art NUMA mechanisms and is within 6% the performance of an ideal NUMA-GPU system. A design space analysis on supporting cache coherence is also investigated. Overall, we show that dedicating only 3% of GPU memory eliminates NUMA bandwidth bottlenecks while incurring negligible performance overheads due to the reduced GPU memory capacity.
4 Environmental Friendly Corrosion Inhibitors for Magnesium Alloys

Magnesium is an important engineering material because of its light weight and excellent properties. Its density is 1.74 g⋅cm-3, only 2/3 that of aluminum and 1/4 that of iron. Moreover, it also has many advantageous properties such as good castability, hot formability, excellent machinability, good electromagnetic shielding characteristics, good biocompatibility, and recyclability (Cao et al, 2006; Staiger et al, 2006). Therefore, magnesium and its alloys have the potential to replace steel and aluminum in many applications. They have already been used in aerospace, aircraft, automotive, mobile electronics, biomaterials and other fields (Zhang & Zhang, 2004). However, there are some challenges for applications of magnesium and its alloys in a larger scale. The most important one is improving their poor corrosion resistance. Magnesium is a very active metal, and the standard potential of Mg2+/Mg is -2.356V (vs. N.H.E. at 25°C) (Bard & Faulkner, 2001). Therefore, magnesium and its alloys are extremely susceptible to corrosion, which can cause the decreased mechanical stability and unattractive appearance (Gray & Luan, 2002). To protect magnesium and its alloys from being corroded, the following techniques are frequently used (Zhang & Zhang, 2004): Conversion surface treatments, as chromating, phosphating, etc., Anodizing, Electroplating and electroless plating, Adding corrosion inhibitors. A great number of scientific studies have been devoted to the subjects of the first 3 techniques above (Song, 2005). But the last one, adding corrosion inhibitors has been seldom involved. Inhibitors are chemicals that react with a metallic surface, or the environment this surface is exposed to, giving the surface a certain level of protection (Roberge, 2000). For the metals widely employed in the industry such as iron, copper, zinc and aluminum, adding corrosion inhibitors is an effective and convenient method to decrease the corrosion rate. For magnesium and its alloys, there are very few publications on their corrosion inhibitors and only few inhibitors such as the salts of F(Song, 2005), Cr2O72(Song, 2006), 8hydroxyquinoline (Galio et al, 2010), and so on, are involved. Since Fand Cr2O72pollute the environment seriously, it is quite necessary to pay more attention to develop the environmental friendly corrosion inhibitors for magnesium and its alloys.
12 VARIATION IN REPRODUCTION AND PATHOGENICITY OF GEOGRAPHIC ISOLATES OF ROTYLENCHULUS RENIFORMIS ON SOYBEAN

McGawley, E. C. , C. Overstreet and M. J. Pontif. 2011. Variation in reproduction and pathogenicity of geographic isolates of Rotylenchulus reniformis on soybean. Nematropica 41:12-22. Known incidence of Rotylenchulus reniformis in Louisiana increased from 3 parishes in 1961 to 11 parishes in 1985 to all 21 of the major soybean producing parishes in 2010. Comparative reproduction and pathogenicity of isolates of Rotylenchulus reniformis from Alabama, Arkansas, Hawaii, Louisiana, Mississippi and Texas on soybean was evaluated in microplot trials. Prior to initiation of microplot trials, ten populations of each geographic isolate were derived. Reproduction of the single egg-mass (SEM) populations of each geographic isolate were evaluated in greenhouse studies with Deltapine 4331 soybean by assessing the numbers of vermiform stages in soil and eggs per gram of root tissue 60 days after inoculation. On the basis of these trials, each repeated once, one SEM population of each of the six isolates was selected for use in microplot trials. Averaged over the two trials, SEM populations selected for use in microplot trials and their respective reproduction values (R, where R = Pf/Pi) and numbers of eggs per gram of root were: AL-7 (R = 3.5, eggs = 1,082); AR-4 (R = 26.7, eggs = 2,186); HI-1 (R = 30.2, eggs = 1,624); LA-3 (R = 30.2, eggs = 1,656); MS-2 (R = 43.9, eggs = 5,215) and TX-5 (R = 55.4, eggs = 4,329). Data from full-season (126 day) microplot trials, averaged over 2 years, showed significant differences (Tukey’s HSD test (P ≤ 0.05%)) among isolates of reniform nematode in both reproduction and pathogenicity. Dry plant weight at harvest averaged 273.3 g for the non-inoculated control. All isolates except the ones from HI and TX produced root weights at harvest that were reduced significantly below that of the control. With the exception of the MS-2 isolate, harvest weights for plants inoculated with AR-4 were significantly lower than those from the other four geographic regions. Relative to the control, numbers and dry weights of pods per plant at harvest were reduced significantly by all reniform nematode isolates except those from AL and HI.