Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing Severity of Patients with Community-Acquired Pneumonia

Abstract Despite all advances in its management, community-acquired pneumonia (CAP) is still an important cause of morbidity and mortality requiring a great consumption of health, social, and economic resources. An early and adequate severity assessment is of paramount importance to provide optimized care to these patients. In the last 2 decades, this issue has been the subject of extensive research. Based on 30 day mortality, several prediction rules have been proposed to aid clinicians in deciding on the appropriate site of care. In spite of being well validated, their sensitivity and specificity vary, which limits their widespread use. The utility of biomarkers to overcome this problem has been investigated. At this moment, their full clinical value remains undetermined, and no single biomarker is consistently ideal for assessing CAP severity. Biomarkers should be seen as a complement rather than superseding clinical judgment or validated clinical scores. The search for a gold standard is not over, and new tools, like bacterial DNA load, are in the pipeline. Until then, CAP severity assessment should be based in three key points: a pneumonia-specific score, biomarkers, and clinical judgment.
Essays on economic dynamics under heterogeneity

This thesis consists of three essays studding the influence of heterogeneity upon the economic dynamics. In the first model of R&D-based economic growth the agents have heterogeneous preferences over a growing continuum of consumption goods. In the second model a monopolist firm or an industry distributes investments in physical capital among a growing set of technologies the payoff of which is heterogeneous. In the third model of solving territorial disputes between countries the income from the land use of a country is not equally (heterogeneously) distributed among the citizens.
Intracellular Potassium Stabilizes Human Ether-à-go-go-Related Gene Channels for Export from Endoplasmic Reticulum

Several therapeutic compounds have been identified that prolong the QT interval on the electrocardiogram and cause torsade de pointes arrhythmias not by direct block of the cardiac potassium channel human ether-à-go-go-related gene (hERG) but via disruption of hERG trafficking to the cell surface membrane. One example of a clinically important compound class that potently inhibits hERG trafficking are cardiac glycosides. We have shown previously that inhibition of hERG trafficking by cardiac glycosides is initiated via direct block of Na+/K+ pumps and not via off-target interactions with hERG or any other protein. However, it was not known how pump inhibition at the cell surface is coupled to hERG processing in the endoplasmic reticulum. Here, we show that depletion of intracellular K+—either indirectly after long-term exposure to cardiac glycosides or directly after exposure to gramicidin in low sodium media—is sufficient to disrupt hERG trafficking. In K+-depleted cells, hERG trafficking can be restored by permeating K+ or Rb+ ions, incubation at low temperature, exposure to the pharmacological chaperone astemizole, or specific mutations in the selectivity filter of hERG. Our data suggest a novel mechanism for drug-induced trafficking inhibition in which cardiac glycosides produce a [K+]i-mediated conformational defect directly in the hERG channel protein.
Association of reversed Robin Hood syndrome with risk of stroke recurrence

Background: Reversed Robin Hood syndrome (RRHS) has recently been identified as one of the mechanisms of early neurologic deterioration in acute ischemic stroke (AIS) patients related to arterial blood flow steal from ischemic to nonaffected brain. We sought to investigate the association of RRHS with risk of stroke recurrence in a single-center cohort study. Methods: Consecutive patients with AIS or TIA affecting the anterior circulation were prospectively evaluated with serial NIH Stroke Scale assessments and bilateral transcranial Doppler monitoring with breath-holding test. RRHS was defined according to previously validated criteria. Results: A total of 360 patients (51% women, mean age 62 ± 15 years) had an ischemic stroke (81%) or TIA (19%) in the anterior circulation, and 30 (8%) of them had RRHS. During a mean follow-up period of 6 months (range 1–24), a total of 16 (4%) recurrent strokes (15 ischemic and 1 hemorrhagic) were documented. The cumulative recurrence rate was higher in patients with RRHS (19%; 95% confidence interval [CI] 1–37) compared to the rest (15%; 95% CI 0–30; p = 0.022 by log-rank test). All recurrent strokes in patients with RRHS were cerebral infarcts that occurred in the ipsilateral to the index event anterior circulation vascular territory. After adjusting for demographic characteristics, vascular risk factors, and secondary prevention therapies, RRHS was independently associated with a higher stroke recurrence risk (hazard ratio 7.31; 95% CI 2.12–25.22; p = 0.002). Conclusions: Patients with AIS and RRHS appear to have a higher risk of recurrent strokes that are of ischemic origin and occur in the same arterial territory distribution to the index event. Further independent validation of this association is required in a multicenter setting.
Selective Reminding Test: Demographic Predictors of Performance and Normative Data for the Greek Population

The Buschke Selective Reminding Test (SRT) measures verbal learning and memory during a multiple-trial list-learning task, which allows for analysis of encoding, storage, and retrieval data. This study of 443 healthy participants (ages 18 to 83 years with 3 to 18 years of education) presents normative data for the Greek population. Statistical analysis indicated that age and educational level were correlated with all the variables as well as sex, although to a considerably lesser extent. Performance on most of the measures decreased with increasing age and lower education, whereas sex differences favored women over men. Based on these results, the sample was stratified into six age groups and three levels of education, with mean and standard deviation for each group. Current norms for the Selective Reminding Test represent a useful neuropsychological tool in clinical practice for patients with memory dysfunction, irrespective of etiology.
Psychopathological and emotional deficits in myotonic dystrophy

OBJECTIVE To evaluate psychopathological disturbances in patients with myotonic dystrophy (MD) and compare patients with MD to both patients with facioscapulohumeral dystrophy (FSHD) and healthy control subjects. METHODS A semistructured interview was used to determine DSM III-R criteria for major depressive episodes, dysthymic episodes, and generalised anxiety. The Montgomery and Asberg and the Hamilton depressive scales, the Covi and Tyrer anxiety scales, the Abrams and Taylor scale for emotional blunting, and the depressive mood scale were all used in the study. Subjects were also asked to complete questionnaires for physical and social anhedonia. RESULTS Fifteen patients with MD, 11 patients with FSHD, and 14 healthy subjects were studied. Patients with MD were not more depressed or anxious than healthy controls. Patients with FSHD were the most depressed and most anxious. However, patients with MD had significantly lower scores for expressiveness and significantly higher scores for anhedonia than the other two groups. CONCLUSION Patients with MD did not present significant depressive or anxious symptomatology but rather an emotional deficit. This emotional deficit may be an adaptive reaction to the threatening implications of the disease, or the effect of the CNS lesions which occur with MD, or both.
MalHunter: Automatic generation of multiple behavioral signatures for polymorphic malware detection

Malicious software, also called malware, is one of the major threats on the Internet today. Despite various antivirus programs, thousands of Internet hosts are daily infected with malware, such as viruses, worms, and Trojan horses. Due to using a variety of obfuscation techniques, polymorphic malware can easily evade signature-based detection techniques by continually changing their appearance or patterns. However, all polymorphic malware samples in the same malware family often follow the same behavioral pattern that can be used to generate a behavioral signature. In this paper, we propose MalHunter, a novel method based on sequence clustering and sequence alignment to automatic generation of behavioral signatures for polymorphic malware detection. We first generate a set of behavioral sequences for different samples of a polymorphic malware, each of which represents a thread's behavior. We then group similar behavioral sequences into the same cluster and generate an alignment pattern for each cluster. We finally build a multiple behavioral signature for the polymorphic malware. MalHunter stores fewer signatures in the signature database due to the generation of a multiple behavioral signature for different samples of each polymorphic malware. The experimental results on a malware collection suggest that MalHunter is both precise and succinct for effective matching and detection of polymorphic malware.
A population‐based study of severity of comorbidity among patients with non‐Hodgkin's lymphoma: prognostic impact independent of International Prognostic Index

Over 60% of patients aged over 70 years, diagnosed with non‐Hodgkin's lymphoma (NHL) in the Netherlands have serious comorbidity. We studied the independent influence of comorbidity on choice of treatment, dose reductions, treatment‐related toxicity and prognosis, using data from a random sample of 381 patients from the population‐based Eindhoven Cancer Registry. About 45% of patients over 60 years of age with NHL had high impact comorbidity at the time of cancer diagnosis. The proportion of patients with aggressive NHL who received chemotherapy decreased from 85% in patients aged 40–60 years to 70% in those over 60 years. About 65% of systematically treated patients with aggressive NHL suffered from treatment‐related toxicity. Toxicity appeared to be more common among females and those with high‐intermediate or high International Prognostic Index (IPI) risk. Among patients with aggressive NHL, the chance of dying for those with high impact comorbidity was twice as high compared with those without comorbidity. This was independent of the IPI risk. Dose reductions are frequently unavoidable for patients with severe comorbidity, poor performance status or chemotherapy‐related toxicity. Whether the less frequent prescription of (full dose) chemotherapy for patients with advanced age and/or with comorbidity is justified remains a question for debate.
Parallel implementation of an adaptive generalized predictive control algorithm

The Adaptive Generalized Predictive Control (AGPC) algorithm can be speeded up using parallel processing. Since the AGPC algorithm needs to be fed with knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here. Also a parallel implementation of Gauss-Jordan elimination method to handle matrix inversion is presented. The parallel algorithm is implemented over a small network of T805 transputers so that it can afterwards be mapped to an equivalent DSP processor network. Execution times and efficiency results are presented to show the performance of the parallel algorithm.
Gentrification and Grassroots Resistance in San Francisco's Tenderloin

Since World War II, San Francisco has been transformed by the high-rise postindustrial restructuring of central cities and by corresponding gentrification pressures. In one low-income inner-city district, the Tenderloin, residents organized and fought successful battles against the gentrifying growth regime through the 1980s. Moving beyond being a reactionary antigrowth movement, Tenderloin activists have advanced a proactive, neighborhood-sensitive regime, with a social-production capacity of its own, represented by the neighborhood's nonprofit housing movement. Their example teaches about the neighborhood-responsive progressive forces that characterize San Francisco and about the potential of grassroots mobilization as a response to international economic restructuring.
On Predicting Stock Returns with Nearly Integrated Explanatory Variables

Statistical inference in predictive regressions depends critically on the stochastic properties of the posited explanatory variable, in particular, its order of integration. Confidence intervals computed for the largest autoregressive root of many explanatory variables commonly used in predictive regressions, including the dividend yield, the book-to-market ratio, the short-term rate of interest, and the term and default spreads, confirm uncertainty surrounding these variables' order of integration. We investigate the effects of this uncertainty on inferences drawn in predictive regressions. Once this uncertainty is accounted for, contrary to previous evidence, we find reliable evidence of predictability at shorter rather than at longer horizons.
Reversal of Domain Wall Motion in Perpendicular Magnetized Tb-Fe-Co Nanowires

We studied the motion of magnetic domain walls (DWs) in SiO2/TbFeCo/Pt (asymmetric) and Pt/TbFeCo/Pt (symmetric) nanowires. The reversed DW motion was observed in the asymmetric wire at zero field and room temperature. The reversed DW motion was attributed to the structural inversion asymmetry-induced spin-orbit torques from Pt/TbFeCo interface and Pt layer of the asymmetric wire. The DW velocity sign was again reversed when the current density is larger than 1.52 × 1011 A/m2 which corresponds to threshold of Walker-breakdown current density.
Nearest neighbor search : the old, the new, and the impossible

Over the last decade, an immense amount of data has become available. From collections of photos, to genetic data, and to network tra c statistics, modern technologies and cheap storage have made it possible to accumulate huge datasets. But how can we e ectively use all this data? The ever growing sizes of the datasets make it imperative to design new algorithms capable of sifting through this data with extreme e ciency. A fundamental computational primitive for dealing with massive dataset is the Nearest Neighbor (NN) problem. In the NN problem, the goal is to preprocess a set of objects, so that later, given a query object, one can nd e ciently the data object most similar to the query. This problem has a broad set of applications in data processing and analysis. For instance, it forms the basis of a widely used classi cation method in machine learning: to give a label for a new object, nd the most similar labeled object and copy its label. Other applications include information retrieval, searching image databases, nding duplicate les and web pages, vector quantization, and many others. To represent the objects and the similarity measures, one often uses geometric notions. For example, a black-and-white image may be modeled by a high-dimensional vector, with one coordinate per pixel, whereas the similarity measure may be the standard Euclidean distance between the resulting vectors. Many other, more elaborate ways of representing objects by high-dimensional feature vectors have been studied. In this thesis, we study the NN problem, as well as other related problems that occur frequently when dealing with the massive datasets. Our contribution is two-fold: we signi cantly improve the algorithms within the classical approaches to NN, as well as propose new approaches where the classical ones fail. We focus on several key distances and similarity measures, including the Euclidean distance, string edit distance and the Earth-Mover Distance (a popular method for comparing images). We also give a number of impossibility results, pointing out the limits of the NN algorithms. The high-level structure of our thesis is summarized as follows. New algorithms via the classical approaches. We give a new algorithm for the approximate NN problem in the d-dimensional Euclidean space. For an approximation factor c > 1, our algorithm achieves dnρ query time and dn1+ρ space for ρ = 1/c2+o(1). This greatly improves on the previous algorithms that achieved ρ that was only slightly smaller than 1/c. The same technique also yields an algorithm with dnO(ρ) query time and space near-linear in n. Furthermore, our algorithm is near-optimal in the class of hashing algorithms. Failure of the classical approaches for some hard distances. We give an evidence that the classical approaches to NN under certain hard distances, such as the string edit
Important for clinical practice Efficacy and safety of long-term continuous growth hormone treatment in children with Prader-Willi syndrome

This collection of articles aims to provide a wide spectrum of studies on the subject of growth and growth factors, particularly focusing on those with direct or potential clinical implications. Of course, given the limited number of papers to be selected, the choice of articles has been fully arbitrary and, inevitably, other equally valuable studies have been neglected. Among experimental studies, I favored those with major clinical implications. In the last 12 months, the research in the field of growth factors has provided important achievements. Molecular biology, applied to single clinical cases or large cohorts of patients, has elucidated the mechanisms underlying some conditions characterized by severe short stature. New therapeutic tools for treating growth impairment have been tested in phase 1 and 2 clinical trials. New relationships between the IGF system and predisposition to cardiovascular disease have been described. Finally, pharmacological modulation of IGF system has been attempted to inhibit cancer growth. Although most of these papers have not yet yielded conclusive results, they nonetheless provide the basis for further clinical and experimental research. Wishing you a good reading, I would like to wrap up this short introduction quoting a sentence written on the office door of James Muorilyan Tanner, the founder of modern auxology: ‘the appetite comes reading’.
Dynamic Markets with Competitive Bidding

The model features a dynamic market in steady state in which prices are determined in first-price auctions. It combines competition over time familiar from the pairwise meeting models with instantaneous bidding competition. It inquires how different properties of the model determine the relative importance of these two aspects of the competition and, in particular, how the non-market-clearing price result of the matching and bargaining models is affected by the introduction of instantaneous bidding competition. It turns out, for example, that if there is some heterogeneity in buyers' valuations of the traded goods, then when the market is frictionless enough in the sense that the common discount factor is close to 1, the instantaneous bidding competition effectively disappears and the non-market-clearing price result can obtain.
Assessing the Success of the Sale of Social Housing in the UK

This article evaluates whether the sale of social housing in the UK during the past three decades has been a success. It explores the avenues available to obtain homeownership, starting with the Right to Buy in 1980. It considers from multiple perspectives the impact of the right to purchase social housing. The article concludes that the drive to increase homeownership has produced a rather hazy picture in terms of ‘success’. From a policy perspective, the goal of increasing homeownership has been successful in the sense that the number of homeowners has steadily increased since the 1980s. However, from a social and individual perspective, it is evident that there has been limited success, with both winners and losers from this process. For example, the sale of social housing has led to a polarisation between the tenures and a process of residualisation. Also, while some individuals have benefited from acquiring a property at a discount, and have thus acquired some capital wealth, others have found themselves in debt and with a property that they cannot sell.
Viability of introducing milk futures contracts in Brazil: a multiple criteria decision analysis

The viability of introducing milk futures contracts in Brazil was assessed through a combination of multiple criteria decision analysis and the application of traditional principles from the theory of success and failure of futures trading. Commodity-specific attributes and market-related aspects were analyzed for chilled raw milk, ultra high temperature (UHT) milk, and milk powder. The analytic hierarchy process methodology was used to rank the commodities in terms of their feasibility prospects. Among them, it was ascertained that chilled raw milk is the most suitable for futures trading. Major reasons for this result are the product's high price volatility, the competitive nature of its markets, the absence of competing risk-management tools, and the impossibility of cross-hedging. Complementing the analysis, interviews were conducted with the 100 largest milk producers in the country to assess their perceptions regarding futures trading. Approximately 92% of these farmers expressed an interest in adopting milk futures contracts as price risk management tools. In conclusion, the analysis indicated that the introduction of a milk futures contract in Brazil has a high probability of success. lEconLit citations: Q130, C610, 0220r. © 2008 Wiley Periodicals, Inc.
Adsorbent Derived from Sewage Sludge and Its Application in Dye Wastewater Treatment

This paper presents sewage sludge to produce an adsorbent for Direct Fast Brown M removal. The optimal conditions for a larger surface area adsorbent were 4 M ZnCl2immersed sludge pyrolyzed at 550°C for 60 min, the highest BET surface area and micropore area achieves 174 m2/g, and 95 m2/g, respectively. The experiment to adsorb the Direct Fast Brown M waste water was carried out. It is noteworthy to point out that more than 80% reduction in COD value has occurred for wastewater sample. Experimental results demonstrate that sewage sludge, a waste material in abundant supply, is a viable source of activated adsorbents.
Design the size reduction patch antenna based on complementary split ring resonators

A size reduction microstrip patch antenna is designed and fabricated. The presence of the negative effective permittivity and permeability produced by the complementary split ring resonator array etched on the ground plane leads the antenna size reduction. The numerical and measurement result show that 35 percent patch size reduction can be achieved between the antenna with CSRR as well as comparison the one without it.
Huawei's leadership role in IMS standards development and in its own proprietary Softswitch

Purpose – The purpose of this paper is to provide a case study of Huawei's leadership role in the Internet Protocol Multi‐media Subsystem (IMS) international standards effort while it developed its own proprietary Softswitch solution. This strategy of leading the standards bodies, developing proprietary standards, and being the low‐cost provider is helping Huawei to become the number one telecom company in the world.Design/methodology/approach – For this case study over 20 industry experts, both outside of Huawei and within were interviewed, and web resources utilized. The big challenge was the nebulous name IMS which combined technical standards with a vision for the future of the telecommunications.Findings – It is a common assumption that China is a copier of technology and not one of the world's leaders in terms of technical innovation. China's Huawei Technologies Company Ltd (Huawei Jishu Youxian Gongsi) is rapidly becoming one of the world's largest telecom manufacturers and one of the key innovator.