Miracle-dz/UniFAR-FTUs huggingface dataset:
Low level of galacto-oligosaccharide in infant formula stimulates growth of intestinal Bifidobacteria and Lactobacilli.

AIM To investigate the effect of a new infant formula supplemented with a low level (0.24 g/100 mL) of galacto-oligosaccharide (GOS) on intestinal micro-flora (Bifidobacteria, Lactobacilli and E. coli) and fermentation characteristics in term infants, compared with human milk and a standard infant formula without GOS. METHODS Term infants (n = 371) were approached in this study in three hospitals of China. All infants started breast-feeding. Those who changed to formula-feeding within 4 wk after birth were randomly assigned to one of the two formula groups. Growth and stool characteristics, and side effects that occurred in recruited infants were recorded in a 3-mo follow-up period. Fecal samples were collected from a subpopulation of recruited infants for analysis of intestinal bacteria (culture technique), acetic acid (gas chromatography) and pH (indicator strip). RESULTS After 3 mo, the intestinal Bifidobacteria, Lactobacilli, acetic acid and stool frequency were significantly increased, and fecal pH was decreased in infants fed with the GOS-formula or human milk, compared with those fed with the formula without GOS. No significant differences were observed between the GOS formula and human milk groups. Supplementation with GOS did not influence the incidence of crying, regurgitation and vomiting. CONCLUSION A low level of GOS (0.24 g/100 mL) in infant formula can improve stool frequency, decrease fecal pH, and stimulate intestinal Bifidobacteria and Lactobacilli as in those fed with human milk.
Multi-Resolution Forecast Aggregation for Time Series in Agri Datasets

A wide variety of phenomena are characterized by time dependent dynamics that can be analyzed using time series methods. Various time series analysis techniques have been presented, each addressing certain aspects of the data. In time series analysis, forecasting is a challenging problem when attempting to estimate extended time horizons which effectively encapsulate multi-step-ahead (MSA) predictions. Two original solutions to MSA are the direct and the recursive approaches. Recent studies have mainly focused on combining previous methods as an attempt to overcome the problem of discarding sequential correlation in the direct strategy or accumulation of error in the recursive strategy. This paper introduces a technique known as Multi-Resolution Forecast Aggregation (MRFA) which incorporates an additional concept known as Resolutions of Impact. MRFA is shown to have favourable prediction capabilities in comparison to a number of state of the art methods.
What Do Financial Market Data Tell Us about Monetary Policy Transparency

This paper attempts to discern from financial market data the impact of greater monetary policy transparency over the period since the late 1980s. We examine whether interest rate variability has changed, the degree to which financial markets anticipate policy moves and movements in the yield curve at the time of changes in monetary policy. Where possible, we compare the results for Australia with other countries. We find that interest rate volatility at the short end has fallen dramatically since the late 1980s. The extent to which market participants anticipate changes in the policy rate has gradually risen, as has the speed of reaction to interest rate announcements. Since the late 1990s, bill futures contract prices have responded to the Reserve Bank of Australia’s (RBA) commentaries on the economy. These results are consistent with an increase in the efficiency with which the market digests economic news. The results are quite similar across countries, and it is difficult to isolate from cross-country data any specific preferred model of monetary policy transparency.
Approximate Searching XML Elements Based on Semantic Restrictions

In last years, XML has become the standard for information representing, exchanging, and publishing. So, querying XML data is a well-explored topic in both database (DB) and information retrieval (IR) fields, which shows proximity search is well suited to XML documents, which are often modelled as labelled trees. Based on the observations that there are some semantic restrictions in userpsilas query, this paper first analysis query restrictions on elements and their values, and then proposes to approximately extract XML elements by using semantic restrictions.
Optical computing advances logically for image processing

A powerful application of optical computation, digital optical cellular image processing (DOCIP), is discussed. DOCIP uses digital optical computing techniques to perform cellular logic operations or extended array functions on images. Cellular logic is reviewed, and a binary image algebra (BlA) that serves as an analysis and synthesis tool for cellular image processing systems is described. Some DOCIP architectures that have been proposed or experimentally demonstrated are discussed and classified as image-algebra-type processors or symbolic-substitution-type processors. The optical and optoelectronic implementations of these architectures are also discussed. <<ETX>>
Engagement in a newly launched online support community for complex regional pain syndrome: membership growth, header analysis and introductory messages

Several studies have investigated forum engagement, with a small but growing body of research focusing on the number of people using a forum membership growth, how they use it header analysis and how they introduce themselves introductory messages. Most studies use established forums and little is known about newly launched forums. This study examines engagement in a newly launched forum for complex regional pain syndrome. Results showed that membership growth occurred in bursts that were closely linked to promotional strategies. Header analysis showed the forum was used throughout the day, evening and night, with a focus on providing support as well as receiving it. Introductory messages took the form of disease stories with six themes: personal details, precipitating event, symptoms, treatment, living with CRPS, and reasons for joining. Implications and areas for future research are discussed.
Consultas and Socially Responsible Investing in Guatemala: A Case Study Examining Maya Perspectives on the Indigenous Right to Free, Prior, and Informed Consent

Since 2005, more than 78 Maya communities representing approximately one million Guatemalans have held referendums called consultas comunitarias, which ask the community whether they are in agreement with mineral, hydroelectric, and/or other megaprojects in their traditional territory. Participation in the consultas is a form of resistance to the granting of mineral rights to corporate interests. In Canada, where much of the Guatemalan mining investment is based, “socially responsible investment firms” (SRIs) promote corporate respect for Indigenous rights. Based on interviews and participant observation, we highlight the perspectives of Maya consulta organizers in three communities that have undertaken consultas to resist the mining licenses of the Canadian mining company Goldcorp, Inc. We argue that a strict policy of corporate respect for the right to free, prior, and informed consent of affected communities is a minimum requirement for Maya acceptance of SRI legitimacy.
Depressive symptoms are independently associated with recurrent falls in community-dwelling older adults

ABSTRACT Background: Falls and depression are two major public health problems that affect millions of older people each year. Several factors associated with falls are also related to depressive symptoms such as medical conditions, sleep quality, use of medications, cognitive functioning, and physical capacities. To date, studies that investigated the association between falls and depressive symptoms did not control for all these shared factors. The current study addresses this issue by examining the relationship between falls and depression symptoms after controlling for several confounders. Methods: Eighty-two community-dwelling older adults were enrolled in this study. The Geriatric Depression Scale (GDS-30) was used to evaluate the presence of depressive symptoms, and the following question was used to assess falls: “Did you fall in the last 12 months, and if so, how many times? ” Results: Univariate analyses indicated that the number of falls was significantly correlated with gender (women), fractures, asthma, physical inactivity, presence of depressive symptoms, complaints about quality of sleep, use of antidepressant drugs, and low functional capacities. Multivariate analyses revealed that depressive symptoms were significantly and independently linked to recurrent falls after controlling for confounders. Conclusions: Results of the present study highlight the importance of assessing depressive symptoms during a fall risk assessment.
A three-phase four-wire grid-connected photovoltaic system using a dual unified power quality conditioner

This paper proposes a photovoltaic (PV) power generation system, which is implemented by means of multilevel converters. The PV system is connected to utility grid and operates as a unified power quality conditioner (UPQC). Thus, the PV-UPQC system injects active power into the there-phase grid and, simultaneously, performs active power-line filtering, in order to improve the power quality. By using dual compensating strategy, the proposed PV-UPQC system is implemented by means of two back-to-back NPC converters sharing the same dc-bus, which is directly connected to the PV array. Both voltage and current controllers are implemented in the synchronous rotating reference frame (dq0-axis), such that they operate interconnected with the maximum power point tracking algorithm, as well as the dc-bus voltage controller. Simulation results are presented to verify the static and dynamic performances of the grid-tied PV-UPQC system.
Anti-stalling pivot rules for the network simplex algorithm

Stalling in the simplex algorithm is defined as an exponentially long sequence of consecutive degenerate pivots without cycling. Pivot rules for the network simplex algorithm that prevent both cycling and stalling are considered. For several of these, the number of consecutive degenerate pivots is shown to be at most k (k + 1)/2, where k is the number of degenerate basic variables. The relationship between these pivot rules for the network simplex algorithm and strongly polynomial simplex variants for solving the shortest path problem is also discussed.
The Double-Cusp Map for the Forced Lorenz System

It is found that adding constant forcing terms to the Lorenz equations breaks the (x,y)→(-x,-y) symmetry of the system. As a result of the symmetry breaking the consecutive zmax return map (the cusp map) gets split into a double-cusp map. We investigate the double-cusp map for the forced Lorenz system using approximate invariant manifolds about the fixed points and use the double-cusp map to understand the stability of the attractor.
Computing the Shattering Coefficient of Supervised Learning Algorithms

The Statistical Learning Theory (SLT) provides the theoretical guarantees for supervised machine learning based on the Empirical Risk Minimization Principle (ERMP). Such principle defines an upper bound to ensure the uniform convergence of the empirical risk Remp(f), i.e., the error measured on a given data sample, to the expected value of risk R(f) (a.k.a. actual risk), which depends on the Joint Probability Distribution P(X x Y) mapping input examples x in X to class labels y in Y. The uniform convergence is only ensured when the Shattering coefficient N(F,2n) has a polynomial growing behavior. This paper proves the Shattering coefficient for any Hilbert space H containing the input space X and discusses its effects in terms of learning guarantees for supervised machine algorithms.
Medicine Radar - a Tool for Exploring Online Health Discussions

Research focusing on online health discussions provides valuable insights into the use of medicines, as well as health-related experiences and difficulties currently not well understood. We introduce Medicine Radar, a tool for exploring health-related online discussions obtained from the Finnish Suomi24 chat forum. The health subset of the entire Suomi24 data consists of 19 million messages written over a time span of 16 years. We outline the method, identify some challenges in analyzing Finnish texts and explain how we overcame them in this specific domain. In particular, we present a novel method for generating domain vocabularies from colloquial texts, which utilizes a combination of machine learning and human input. Medicine Radar is accessible as an open sourced web interface that we hope will inspire and facilitate further research.
On Target?: The International Experience with Achieving Inflation Targets

This paper examines the international experience with full-fledged inflation targeting monetary regimes. Stylized facts are brought together from a review of the institutional elements of inflation targeting frameworks, a comparison of actual and targeted inflation outcomes, and case studies of large inflation target misses. Inflation targets are missed about 40 percent of the time and often by substantial amounts and for prolonged periods, yet no country has dropped inflation targeting. The resilience of the inflation targeting regime is attributable to the flexibility of the framework, its high standards of transparency and accountability, and the lack of realistic alternatives.
Optimal Emissions Taxation Under Imperfect Competition in a Durable Good Industry

This paper investigates optimal emissions taxation under imperfect competition in a durable good industry where products are sold (instead of rented). As a benchmark, attention is paid to the special case of monopoly with exogenously given product durability. In line with previous literature, the optimal emission tax in this benchmark model falls short of marginal damage (underinternalization). Extending the benchmark model either to the case of an oligopolistic market structure andsor to the case of endogenous product durability then provides two cases in which the optimal emission tax overinternalizes marginal damage. Copyright Blackwell Publishers Ltd and the Board of Trustees of the Bulletin of Economic Research, 2004.
Orientation sensing using backscattered phase from multi-antenna tag at 5.8 GHz

Object localization is one of the most important applications of RFID technology. In this paper, we demonstrate how fine-scale orientation can be estimated from a multi-antenna backscatter tag. Three basic orientation changes - tag roll, pitch and yaw - were considered, where roll and pitch maneuvers were successfully identified from the direction of phase rotation. Moreover, an inclination of 5° in roll and pitch maneuvers was successfully identified by measuring the phase difference with 15% and 8% error respectively. The analysis can be extended to any amount of inclination.
Optical coherence tomography for retinal imaging in multiple sclerosis

Abstract Visual disturbances caused by inflammatory and demyelinating processes of the visual system, mainly in the optic nerve, are a common symptom in multiple sclerosis (MS). Optical coherence tomography (OCT) is a tool that is increasingly used for quantifying retinal damage in MS and other neurologic diseases. Based on spectral interferometry, it uses low-coherent infrared light to generate high-resolution spatial images of the retina. The retinal nerve fiber layer (RNFL) consists of unmyelinated axons that form the optic nerve, and thus represents a part of the central nervous system. OCT allows for noninvasive measurements of RNFL thickness in micrometer resolution. With the help of OCT, researchers have managed to demonstrate that eyes of MS patients show distinct RNFL thinning after an event of acute optic neuritis in MS, and even subclinical damage in eyes with no previous optic neuritis. OCT is also a useful tool in terms of providing a differential diagnosis of MS toward, for example, neuromyelitis optica, a disease that usually shows stronger retinal thinning, or Susac syndrome, which is characterized by distinct patchy thinning of the inner retinal layers. RNFL thinning is associated with magnetic resonance imaging-derived measurements of the brain, such as whole-brain atrophy, gray and white matter atrophy, and optic radiation damage. These features suggest that OCT-derived retinal measurements are a complement for measuring central nervous system neurodegeneration in the context of clinical trials – for example, with neuroprotective substances.
A novel framework for collaborative intrusion detection for M2M networks

The proliferation of sensor devices has introduced exciting possibilities such as the Internet of Things (IoT). Machine to Machine (M2M) communication underpins efficient interactions within such infrastructures. The resource constraints and ad-hoc nature of these networks have significant implications for security in general and with respect to intrusion detection in particular. Consequently, contemporary solutions mandating a stable infrastructure are inadequate to fulfill these defining characteristics of M2M networks. In this paper, we present COLIDE (COLlaborative Intrusion Detection Engine) a novel framework for effective intrusion detection in the M2M networks without incurring high energy and communication cost on the participating host and edge nodes. The framework is envisioned to address challenges such as flexibility, resource constraints, and the collaborative nature of the M2M networks. The paper presents a detailed system description along with its formal and empirical evaluation using Contiki OS. Our evaluation for different communication scenarios demonstrates that the proposed approach has limited overhead in terms of energy utilization and memory consumption.
How Does Financial Liberalization affect Economic Growth

This paper assesses the effects of international financial liberalization and banking crises on investments and productivity in a sample of 93 countries (at its largest) observed between 1975 and 1999. I provide empirical evidence that financial liberalization spurs productivity growth and marginally affects capital accumulation. Banking crises depress both investments and TFP. Both levels and growth rates of productivity respond to financial liberalization and banking crises. The paper also presents evidence of conditional convergence in productivity across countries. However, the speed of convergence is unaffected by financial liberalization. These results are robust to a number of econometric specifications.
Metabolic analysis of knee synovial fluid as a potential diagnostic approach for osteoarthritis

Osteoarthritis (OA) is a leading cause of chronic joint pain in the older human population. Diagnosis of OA at an earlier stage may enable the development of new treatments to one day effectively modify the progression and prognosis of the disease. In this work, we explore whether an integrated metabolomics approach could be utilized for the diagnosis of OA. Synovial fluid (SF) samples were collected from symptomatic chronic knee OA patients and normal human cadaveric knee joints. The samples were analyzed using 1H nuclear magnetic resonance (NMR) spectroscopy and gas chromatography‐mass spectrometry (GC‐MS) followed by multivariate statistical analysis. Based on the metabolic profiles, we were able to distinguish OA patients from the controls and validate the statistical models. Moreover, we have integrated the 1H NMR and GC‐MS results and we found that 11 metabolites were statistically important for the separation between OA and normal SF. Additionally, statistical analysis showed an excellent predictive ability of the constructed metabolomics model (area under the receiver operating characteristic curve = 1.0). Our findings indicate that metabolomics might serve as a promising approach for the diagnosis and prognosis of degenerative changes in the knee joint and should be further validated in clinical settings. © 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 33:1631–1638, 2015.
A novel knowledge reduction method based on rank correlation analysis

Dominance-based rough set approach has recently become a routine method to deal with preference-ordered data, and knowledge reduction method based on rough set theory has been proposed. However, the results obtained are usually short of statistical significance. In this paper, non- parametric methods in statistics are introduced to analyze ordered information systems and ordered decision tables. Spearman and Kendall rank correlation coefficient are respectively used as new measures of attribute sets correlation. Based on these measures, a new method of knowledge reduction of the ordered information systems and the ordered decision tables using nonparametric rank statistics is presented. It can be proved that there are some relationships between the rough set theory and the nonparametric statistical methods. The numerical experiments show that the approach proposed is feasible, and it can provide a statistical evidence for rough set method.
Progressive Taxation Contribute to Economic Development ?

Financial instability has increased for many economies in the face of greater capital mobility. Eliminating capital flows, especially portfolio investment flows, may reduce volatility, but it could also result in domestic capital constraints. To overcome this dilemma, policymakers may consider alternatives, such as progressive income taxation, that could raise domestic funds. In this paper, we combine several macro economic data sources to test the link between progressive taxation and economic stability, economic growth, inequality and fiscal policy. Based on data from 1981 to 2002, we find that progressive taxation provides policymakers with the ability to conduct countercyclical fiscal policies, which in turn contributes significantly to economic stability. In turn, we find no evidence that progressive taxation adversely affects economic stability by reducing growth. We find, though, that the possibility to raise the progressiveness is constrained by capital mobility and by the level of government spending. Finally, policymakers, who may consider consumption taxes, such as the value added taxes (VAT), when tax enforcement is ineffective, would see no additional gains in terms of economic stability from the implementation of a VAT in combination with progressive income taxation.
Food security and government interventions: A study of Indian grain markets

Abstract This study examines the future of Indian food security in light of possible liberalization of its agriculture sector. Demand for major food grains such as wheat and rice is projected after taking into account possible dietary changes due to income growth, urbanization and other demographic changes. Policy Analysis Matrix (PAM) indicators are constructed to predict changes in supply patterns in the case of reduced government intervention. The projected demand growth suggests faster increases in per capita wheat consumption due to strong income growth and urbanization whereas per capita rice consumption is projected to level off in the next few years and then will likely decline steadily for the remainder of the projection period. This indicates that Indian wheat production may need to grow at a much faster rate than rice production in order to remain self-sufficient in the future. Based on the PAM ranking, this may be possible under reduced or no government interventions because of the comparative advantage of wheat over rice in the major growing regions.