Miracle-dz/UniFAR-FTUs huggingface dataset:
Global Trade and the Dollar

We document that it is not bilateral exchange rates but the dollar exchange rate that drives global trade prices and volumes. Using a newly constructed data set of bilateral price and volume indices for more than 2,500 country pairs, we establish the following facts: 1) The dollar exchange rate quantitatively dominates the bilateral exchange rate in price pass-through and trade elasticity regressions. U.S. monetary policy induced dollar fluctuations have high pass-through into bilateral import prices. 2) Bilateral non-commodities terms of trade are essentially uncorrelated with bilateral exchange rates. 3) The cross-sectional heterogeneity in pass-through/elasticity across country pairs is related to the share of imports invoiced in dollars. Our results derive from fixed effects panel regressions as well as a Bayesian semiparametric hierarchical panel data model. Unlike standard panel regressions, the Bayesian approach allows us to quantify the cross-sectional heterogeneity of exchange rate pass-through/elasticities and the relation of this heterogeneity to dollar invoicing. Our findings strongly support the dominant currency paradigm as opposed to the traditional Mundell-Fleming pricing paradigms.
Improvement of gastric motility by hemodialysis in patients with chronic renal failure.

BACKGROUND Gastrointestinal (GI) symptoms are common in patients with chronic renal failure (CRF). We have previously demonstrated that patients with predialysis end-stage renal disease showed a high prevalence of GI symptoms and gastric hypomotility, and that gastric hypomotility appears to be an important factor in generating GI symptoms. However, it is not clear whether impaired gastric motor function would improve after hemodialytic treatment. AIMS To examine the relationship between gastric motor function and GI symptoms in CRF patients on hemodialysis. METHODS The study was performed in 19 patients with CRF treated with hemodialysis for more than six months and in 12 matched healthy controls. GI symptom severity was quantified in all patients. Gastric motility was evaluated with cutaneously recorded electrogastrography (EGG) and gastric emptying of semi-solid meals using the (13)C-acetic acid breath test. RESULTS Six patients had no symptoms, and 11 had slight GI symptoms with a total symptom score of less than 5. Compared with controls, CRF patients revealed no differences in gastric motility parameters, with the exception of a lower percentage of normogastria in EGG at fasting state. Eleven patients had normal gastric motor function (Group A), and eight showed abnormalities of either gastric myoelectrical activity or gastric emptying (Group B). There was no difference in symptom score between Group A and Group B. CONCLUSIONS More than half of the patients with CRF on hemodialysis demonstrated normal gastric motility, and no or slight GI symptoms. Hemodialytic treatment may improve impaired gastric motility and reduce GI symptoms in patients with CRF.
Peer Group Analysis in Identity and Access Management to Identify Anomalies

: Nowadays companies need to manage user accesses across multiple channels such as mobile, social and cloud. Business is always about delivering value to customers, and Identity and Access Management is very essential part of ensuring that employees are both empowered to deliver that value and prohibited from damaging the security, business reputation. Organization can use Identity and Access data to detect the attacks within the organization. Data Analytics techniques can be used to identify the anomalies in the identity and Access Data, out of that Peer group Analysis is one technique. Peer Group Analysis focuses on the local pattern rather than the global models; anomaly may not be present when compared with whole data but there may be some outliers present when compared with its peer groups. Context anomaly is the data points that considered abnormal when compared with its peer group. In this research we are doing peer group analysis on Identity and Access Data using the various outlier detection algorithms. Various context anomaly detection algorithms are used to identify the abnormal user behaviour which gives the risk insights the organization. We are proposing peer group analysis which can able to locate entitlements that can be exclusive than other users of same group, which gives the risk of the user access.
E-business for the electricity retail market a business to client perspective

In the new deregulated market of the electricity industry the communication and e-Business infrastructure plays a main role for the efficiency of all the entities present in the electricity sector. From generation to the final client there are two markets, the wholesale and the retail market. Specific characteristics of the electricity industry make the communication support a fundamental tool to reflect the changes made by one of the intervenients in the whole value chain. When prices change at the wholesale market it is necessary to reflect them at the final consumers. Without a bidirectional and reliable communication systems several problems could occur, from spikes in the electricity prices that could take retail companies to bankruptcy, to huge blackouts that happened in Europe and in the United States. The goal of this paper is to present a model for the electricity retail market. Several studies have been done about the electricity markets, the grand majority focus their attention on the wholesale market. Our proposal is to analyse the e-Business communication structure in a Business-to-Client perspective.
Maintenance and Drift of Attention in Human-Robot Communication

We describe an attention based human-robot communication system called ACS. Here, an attention refers to an arbitrary policy for selecting behaviors. Attention is usually defined a priori by the designers of the robots, which prevents communication between humans and robots. The reason is that the reactions of such robots are fixed for specific situations so that humans are easy to predict the robots reactions. We therefore developed ACS to enable robots to generate their own attentions without predefined settings. We propose Feature Drift, which enables the system to dynamically maintains its attention based according to environmental objects. In particular, Feature Drift can change the attention spontaneously in over time, which solves the problem of fixed reaction. We implemented ACS in a communication robot, Robovie, and evaluated it. The results showed that the robot could maintain its own attention and react to human utterances according to this attention.
Role of BacA in Lipopolysaccharide Synthesis, Peptide Transport, and Nodulation by Rhizobium sp. Strain NGR234

ABSTRACT BacA of Sinorhizobium meliloti plays an essential role in the establishment of nitrogen-fixing symbioses with Medicago plants, where it is involved in peptide import and in the addition of very-long-chain fatty acids (VLCFA) to lipid A of lipopolysaccharide (LPS). We investigated the role of BacA in Rhizobium species strain NGR234 by mutating the bacA gene. In the NGR234 bacA mutant, peptide import was impaired, but no effect on VLCFA addition was observed. More importantly, the symbiotic ability of the mutant was comparable to that of the wild type for a variety of legume species. Concurrently, an acpXL mutant of NGR234 was created and assayed. In rhizobia, AcpXL is a dedicated acyl carrier protein necessary for the addition of VLCFA to lipid A. LPS extracted from the NGR234 mutant lacked VLCFA, and this mutant was severely impaired in the ability to form functional nodules with the majority of legumes tested. Our work demonstrates the importance of VLCFA in the NGR234-legume symbiosis and also shows that the necessity of BacA for bacteroid differentiation is restricted to specific legume-Rhizobium interactions.
Violence and schizophrenia: examining the evidence.

BACKGROUND It is now accepted that people with schizophrenia are significantly more likely to be violent than other members of the general population. A less acknowledged fact is that the proportion of societal violence attributable to schizophrenia is small. AIMS To critically examine the epidemiological evidence for the association between violence and schizophrenia and estimate the impact of this association on society. METHOD A selective review of the key literature on the epidemiology of violence and schizophrenia. Population-attributable risks for violence in schizophrenia are calculated from population-based studies. RESULTS Most studies confirm the association between violence and schizophrenia. Recent good evidence supports a small but independent association. Comorbid substance abuse considerably increases this risk. The proportion of violent crime in society attributable to schizophrenia consistently falls below 10%. CONCLUSIONS Less focus on the relative risk and more on the absolute risk of violence posed to society by people with schizophrenia would serve to reduce the associated stigma. Strategies aimed at reducing this small risk require further attention, in particular treatment for substance misuse.
Five-year follow-up results of the PROFHER trial comparing operative and non-operative treatment of adults with a displaced fracture of the proximal humerus

Aims The PROximal Fracture of the Humerus Evaluation by Randomisation (PROFHER) randomised clinical trial compared the operative and non‐operative treatment of adults with a displaced fracture of the proximal humerus involving the surgical neck. The aim of this study was to determine the long‐term treatment effects beyond the two‐year follow‐up. Patients and Methods Of the original 250 trial participants, 176 consented to extended follow‐up and were sent postal questionnaires at three, four and five years after recruitment to the trial. The Oxford Shoulder Score (OSS; the primary outcome), EuroQol 5D‐3L (EQ‐5D‐3L), and any recent shoulder operations and fracture data were collected. Statistical and economic analyses, consistent with those of the main trial were applied. Results OSS data were available for 164, 155 and 149 participants at three, four and five years, respectively. There were no statistically or clinically significant differences between operative and non‐operative treatment at each follow‐up point. No participant had secondary shoulder surgery for a new complication. Analyses of EQ‐5D‐3L data showed no significant between‐group differences in quality of life over time. Conclusion These results confirm that the main findings of the PROFHER trial over two years are unchanged at five years.
The anti-angiogenic and antibacterial effect of Tinomiscium philippinense Miers. (Menispermaceae) leaf extract

Sheryl Rena-Aguila, Mario A. Tan, Oliver B. Villaflores The Graduate School, University of Santo Tomas, Manila, Philippines College of Science, University of Santo Tomas, Manila, Philippines Research Center for the Natural and Applied Sciences, University of Santo Tomas, Manila, Philippines College of Nursing, University of Santo Tomas, Manila, Philippines Journal of Coastal Life Medicine 2016; 4(1): 61-68
LearnIR: WSDM 2018 Workshop on Learning from User Interactions

While users interact with online services(e.g. search engines, recommender systems, conversational agents), they leave behind fine grained traces of interaction patterns. The ability to understand user behavior, record and interpret user interaction signals, gauge user satisfaction and incorporate user feedback gives online systems a vast treasure trove of insights for improvement and experimentation. More generally, the ability to learn from user interactions promises pathways for solving a number of problems and improving user engagement and satisfaction. Understanding and learning from user interactions involves a number of different aspects - from understanding user intent and tasks, to developing user models and personalization services. A user's understanding of their need and the overall task develop as they interact with the system. Supporting the various stages of the task involves many aspects of the system, e.g. interface features, presentation of information, retrieving and ranking. Often, online systems are not specifically designed to support users in successfully accomplishing the tasks which motivated them to interact with the system in the first place. Beyond understanding user needs, learning from user interactions involves developing the right metrics and expiermentation systems, understanding user interaction processes, their usage context and designing interfaces capable of helping users. Learning from user interactions becomes more important as new and novel ways of user interactions surface. There is a gradual shift towards searching and presenting the information in a conversational form. Chatbots, personal assistants in our phones and eyes-free devices are being used increasingly more for different purposes, including information retrieval and exploration. With improved speech recognition and information retrieval systems, more and more users are increasingly relying on such digital assistants to fulfill their information needs and complete their tasks. Such systems rely heavily on quickly learning from past interactions and incorporating implicit feedback signals into their models for rapid development.
Manipulating Superparamagnetic Microparticles with an Electromagnetic Needle

Selective, precise, and high‐throughput manipulation of individual superparamagnetic microparticles has profound applications in performing location‐tailored in vitro biomedical studies. The current techniques for manipulation of microparticles allow only a single particle in the manipulation workspace, or simultaneous transportation of multiple microparticles in batches. In this work, a method based on a robotized electromagnetic needle for manipulation of individual superparamagnetic microparticles within a microparticle population is introduced. By automatically controlling the highly localized magnetic field of the needle, a single microparticle is selectively picked when its neighboring particle is few micrometers away. Supported by the nanometer resolution of the robotic positioner, particles are placed at sub‐micrometer precision. This manipulation technique allows the creating of arbitrary patterns, sorting of microparticles based on size and morphology, and transporting of individual microparticles in 3D space. Therefore, this approach has the potential to enable more deterministic and quantitative microanalysis and microsynthesis using superparamagnetic microparticles.
Source parameters of a M4.8 and its accompanying repeating earthquakes off Kamaishi, NE Japan: Implications for the hierarchical structure of asperities and earthquake cycle

We determine the source parameters of a M4.9 ± 0.1 ‘characteristic earthquake’ sequence and its accompanying microearthquakes at ∼50 km depth on the subduction plate boundary offshore of Kamaishi, NE Japan. The microearthquakes tend to occur more frequently in the latter half of the recurrence intervals of the M4.9 ± 0.1 events. Our results show that the microearthquakes are repeating events and they are located not only around but also within the slip area for the 2001 M4.8 event. From the hierarchical structure of slip areas and smaller stress drops for the microearthquakes compared to the M4.8 event, we infer the small repeating earthquakes rupture relatively weak patches in and around the slip area for the M4.8 event and their activity reflects a stress concentration process and/or change in frictional property (healing) at the area. We also infer the patches for the M4.9 ± 0.1 and other repeating earthquakes undergo aseismic slip during their interseismic period.
Systematic, Multimethod Assessment of Adaptations Across Four Diverse Health Systems Interventions

Background Many health outcomes and implementation science studies have demonstrated the importance of tailoring evidence-based care interventions to local context to improve fit. By adapting to local culture, history, resources, characteristics, and priorities, interventions are more likely to lead to improved outcomes. However, it is unclear how best to adapt evidence-based programs and promising innovations. There are few guides or examples of how to best categorize or assess health-care adaptations, and even fewer that are brief and practical for use by non-researchers. Materials and methods This study describes the importance and potential of assessing adaptations before, during, and after the implementation of health systems interventions. We present a promising multilevel and multimethod approach developed and being applied across four different health systems interventions. Finally, we discuss implications and opportunities for future research. Results The four case studies are diverse in the conditions addressed, interventions, and implementation strategies. They include two nurse coordinator-based transition of care interventions, a data and training-driven multimodal pain management project, and a cardiovascular patient-reported outcomes project, all of which are using audit and feedback. We used the same modified adaptation framework to document changes made to the interventions and implementation strategies. To create the modified framework, we started with the adaptation and modification model developed by Stirman and colleagues and expanded it by adding concepts from the RE-AIM framework. Our assessments address the intuitive domains of Who, How, When, What, and Why to classify and organize adaptations. For each case study, we discuss how the modified framework was operationalized, the multiple methods used to collect data, results to date and approaches utilized for data analysis. These methods include a real-time tracking system and structured interviews at key times during the intervention. We provide descriptive data on the types and categories of adaptations made and discuss lessons learned. Conclusion The multimethod approaches demonstrate utility across diverse health systems interventions. The modified adaptations model adequately captures adaptations across the various projects and content areas. We recommend systematic documentation of adaptations in future clinical and public health research and have made our assessment materials publicly available.
Upper limits from the LIGO and TAMA detectors on the rate of gravitational-wave bursts

We report on the first joint search for gravitational waves by the TAMA and LIGO collaborations. We looked for millisecond-duration unmodelled gravitational-wave bursts in 473 hr of coincident data collected during early 2003. No candidate signals were found. We set an upper limit of 0.12 events per day on the rate of detectable gravitational-wave bursts, at 90% confidence level. From simulations, we estimate that our detector network was sensitive to bursts with root-sum-square strain amplitude above approximately 1-3x10^{-19} Hz^{-1/2} in the frequency band 700-2000 Hz. We describe the details of this collaborative search, with particular emphasis on its advantages and disadvantages compared to searches by LIGO and TAMA separately using the same data. Benefits include a lower background and longer observation time, at some cost in sensitivity and bandwidth. We also demonstrate techniques for performing coincidence searches with a heterogeneous network of detectors with different noise spectra and orientations. These techniques include using coordinated signal injections to estimate the network sensitivity, and tuning the analysis to maximize the sensitivity and the livetime, subject to constraints on the background.
Testbed Experiments for Improving the Cost-Effectiveness of the Conservation Reserve Program

The Conservation Reserve Program (CRP), the world’s largest conservation program, pays farmers to voluntarily establish conservation cover on approximately 30 million acres of environmentally sensitive cropland. We conduct a laboratory study of several auction alternatives for the CRP and test their performance in terms of efficiency and cost-effectiveness. We focus on (i) the current price cap format studying the impact of different degrees of price-cap tightness, and (ii) on comparing the price-cap auctions with two alternative formats based on reference prices—one in which the reference is determined exogenously and another in which it is determined endogenously. We find that, as expected, excessive tightening of price caps forces participants out, damaging efficiency and cost effectiveness. Second, substantial relaxation of the price cap does not hurt efficiency nor participation, but it does hurt cost-effectiveness by allowing higher rents. On balance, relaxing price caps is preferable to tightening them in terms of cost effectiveness. Third, the exogenous reference price format allows medium-cost bidders to submit offers that are competitive against low-cost bidders. Both efficiency and costeffectiveness are hurt. The endogenous reference price, outperforms the exogenous reference price in terms of cost-effectiveness by increasing participation and reducing rents.
Disruptive change and the reconfiguration of innovation ecosystems

This conceptual paper extends the traditional view of disruptive change, which considers the effects of rivalry between an incumbent and new entrant firm, by examining the impact of disruption upon the ‘innovation ecosystem’ in its entirety – the group of organisations that collaborate in creating a holistic value proposition for the end-user. Following Adner’s “ecosystem-as-structure” perspective, we develop propositions that anticipate structural differences between incumbent and disruptive innovation ecosystems, and then review these propositions in the context of three historical, disruptive innovation cases; Bakelite (a synthetic plastic), microwave oven, and photocopier. Through these cases, we illustrate that the manner of innovation ecosystem reconfiguration is likely to depend on the design attributes of the product, as well as the type of disruption experienced. We conclude by reflecting upon contemporary cases of disruption enabled through digital technologies, and proposing a framework that can guide future research.
Interactions between donor Agreeableness and recipient characteristics in predicting charitable donation and positive social evaluation

Agreeable people are more likely to display prosocial attitudes and helpful behavior in a broad range of situations. Here we show that this tendency interacts with the personal characteristics of interaction partners. In an online study (n = 284), participants were given the opportunity to report attitudes toward and make monetary donations to needy individuals who were described in dynamically generated biographies. Using a machine learning and multilevel modeling framework, we tested three potential explanations for the facilitatory influence of Agreeableness on charitable behavior. We find that Agreeableness preferentially increased donations and prosocial attitudes toward targets normatively rated as being more deserving. Our results advance understanding of person-by-situation interactions in the context of charitable behavior and prosocial attitudes.