Miracle-dz/UniFAR-FTUs huggingface dataset:
Our treatment methods in herpes zoster and postherpetic neuralgia: Retrospective analysis

Aim: The aim of this study is to investigate the effectiveness of our treatment methods applied in the pain management of patients with HZ, PHN and risk factors associated with the development of HZ and PHN . Materials and Methods: The study was conducted in our hospital pain medicine clinic. The demographic data of the patients, in which phase of the disease they admitted, in which dermatomes the disease was occurred, what medical treatments they received and type of interventional treatments were applied between the dates January 2019 – January 2023 were recorded. Also, pain reduction was evaluated as beneficial when there’s a reduction in the pain level equal or more than % 50, and below as useless. The dosage scheme and types of drugs used were recorded. The follow-up interval was determined as 6 weeks after the intervention. Results: While 131 (56.2 %) of 233 patients were diagnosed with HZ, 102 patients (43.8%) were diagnosed as PHN. The median age was significantly higher in the PHN group (p<0.001). Thoracic region (60.9%) is the most frequently involved dermatome for HZ and PHN, followed by lumbar, trigeminal nerve ophthalmic branch and cervical region. The most commonly used agents are pregabalin, tramadol and gabapentin, respectively. Interventional treatments, on the other hand, were generally effective regardless of the phase. Conclusion: It has been determined sympathetic blocks and epidural injections in acute and subacute periods are more effective, and peripheral nerve blocks are effective in both periods. While it was found to be effective the pulse radiofrequency in lumbar region, it was found to be effective in the chronic period while it was not effective in the facial dermatome in the acute period.
Rolling the DICE William Nordhaus’s Dubious Case for a Carbon Tax

T he 2007 Nobel Peace Prize awarded to Al Gore and the Intergovernmental Panel on Climate Change (IPCC) underscores the public’s growing awareness of and concern about anthropogenic (man-made) global warming. Many climatologists and other relevant scientists claim that emissions of greenhouse gases (GHGs) from human activity will lead to increases in the earth’s temperature, which in turn will spell potentially catastrophic hardship for future generations. If this forecast proves to be accurate, economists will recognize what former World Bank chief economist Nicholas Stern described in his famous report to the British government as “the greatest example of market failure we have ever seen” (2007, 1). With the science of global warming so stipulated, most economists’ standard reaction is to recommend a government policy to internalize the externality; the debate has largely revolved around the best mechanism to deal with carbon emissions (for example, “cap and trade” versus a carbon tax) and the appropriate magnitude of the corrective penalty on emissions. Although the most important implementation of emission curbs to date, the Kyoto Protocol, relies on tradable permits, increasingly more economists have concluded that a carbon tax can achieve a desired level of emissions more efficiently (Pizer 1997; Nordhaus 2008). It would seem that the “consensus” in the natural sciences on anthropogenic global warming has carried over into the social sciences in the form of an emerging consensus on a carbon tax as
Sector financiero y crecimiento liderado por las exportaciones. El caso de México, 1995‑2020

El objetivo de este trabajo es analizar el papel de la Inversión Extranjera Directa (IED) y el Crédito Bancario al Sector Industrial (CBSI) como factores de expansión del sector productivo en México durante el periodo 1995‑2020, en la transición de una economía con alta protección arancelaria a una economía abierta, bajo el postulado teórico generalmente aceptado de que la represión financiera impedía el libre flujo de la inversión; escenario desfavorable para una industria que empezaba a reconfigurarse en el marco de un modelo secundario exportador. Se empleó un modelo de cambio de régimen de Markov y un modelo de Vectores de Corrección de Error (VECM). Los modelos seleccionados no reflejan relación alguna de causalidad del sector financiero al sector real o viceversa.
Data imputation with a diagnostic purpose in building: Application to an oﬃce setting

In a building system, diagnoses are calculated from symptoms resulting from a set of tests; each deﬁned by a bunch of data, behavioral constraints and a set of possible explanations in case of anomaly. To make a test, data are required from diﬀerent sensors. However, missing data is a common issue in buildings. Because a detection test relies on several variables and that all the data should be available along a given time horizon, performing tests could become an issue. In the literature, many techniques have been proposed to impute missing data. However, detection tests could detect non-existing anomalies with usual types of imputation: it is indeed necessary that the imputed data do not generate alarms. It is all the more important for diagnosis from ﬁrst principle approach where detection of anomalies has a strong impact on the diagnosis. This paper discusses the issue of imputation with diagnostic purposes i.e generating data satisfying test constraints. The proposed imputation algo-rithm is based on a genetic algorithm which search iteratively for imputed data satisfying behavioral constraints while preserving as much as possible known statistical properties. The eﬃciency of the method is evaluated on measurements obtained from a real application: an oﬃce at G-SCOP laboratory with a large number of sensors and missing data.
PLACE OF HAPPINESS AND SUBJECTIVE INDICATORS OF WELL-BEING IN QUALITY OF LIFE ISSUES

Quality of life (QOL), a multidimensional construct, has in the last two and a half decades attracted attention in research and practice across the medical sciences, humanities and the social sciences. One major challenge is the conceptualization of QOL which has led to confusion with other terms. This paper is an attempt to conceptualise QOL and examine the point(s) of distinction with happiness and wellbeing. Evidence from literature established significant overlaps between happiness, wellbeing and QOL, with quality of life seen as an umbrella construct having happiness, wellbeing and other factors as sub-components. The composite quality of life is broadly categorized into objective and subjective components. The objective component has to do with established (societal) norms using observable and quantifiable socio-economic and health indicators. The subjective component, which is the thrust of this paper, has to do with the perception/personal self-evaluation of individuals about how good they feel, how happy they are, and general life satisfaction in order of importance to the individuals. Abraham Maslow’s theory of motivation, otherwise known as theory of needs, provides an effective framework in explaining quality of life from the subjective perspective. With the hierarchical nature of human needs and motivation dynamics, it becomes obvious that subjective quality of life is fluid and influenced by situational factors and prevailing circumstances, coupled with individual motivation. The implication is that individuals will evaluate their quality of life based on the needs that are
Indoor Positioning using the IEEE 802.11 Infrastructure

We propose a new indoor localization method which can be used to track a mobile node . Our method uses only the received signal strengths as input information . In addition our approach doesn't require any prior knowledge of the mobile node's motion and therefore doesn't use a cinematic motion model for tracking the mobile node. We discuss in detail the features of our approach and its resulting algorithm . We evaluate the performances of our algorithm using a real signal map.
The Use of Ensemble Classiﬁcation and Clustering Methods of Machine Learning in the Study of Internet Addiction of Students

: One of the relevant current vectors of study in machine learning is the analysis of the application peculiarities for methods of solving a speciﬁc problem. We will study this issue on the example of methods of solving the clustering and classiﬁcation problem. Currently, we have a considerable number of machine learning algorithms – e.g. Expectation Maximization, Farthest First, K-Means, Expectation-Maximization, Hierarchical Clustering, Support vector machines, K-nearest neighbor, Logistic regression, Random Forest etc. – which can be used for clustering and classiﬁcation. However, not all methods can be used for solving a speciﬁc task. The article describes the technology of empirical comparison of methods of clustering and classiﬁcation problems solving using WEKA free software for machine learning. Empirical comparison of data clustering methods was based on the results of a survey conducted among students majoring in Computer Studies and dedicated to detecting signs of Internet Addiction (IA) (Internet Addiction is a behavioural disorder that occurs due to Internet misuse). As a continuation of the study of Internet Addiction of students, a survey of students of other specialties was conducted. Ensemble methods of machine learning classiﬁcation were used to analyze these data. Empirical comparison of clustering algorithms (Expectation Maximization, Farthest First and K-Means) and ensemble classiﬁcation algorithms (AdaBoost, Bagging, Random Forest and Vote) with the application of the WEKA machine learning system had the following results: it described the peculiarities of application of these methods in feature clustering and classiﬁcation, the authors developed data instances’ clustering and classiﬁcation models to detect signs of Internet addiction among students, the study concludes that these meth-ods may be applicable to development of models detecting respondents with signs of IA related disorders and risk groups.
eBusiness patterns and strategic change

Within this paper we develop and explore the concept of a business pattern. The term business pattern is used to refer to a coherent and repeating sequence of action involving humans and technology appropriate to some domain of organisation. We demonstrate a way of visualising such patterns in a medium we refer to as pattern comics. We argue that such an approach to visualisation offers an innovative way of making sense of the issue of strategic change, particularly as it concerns the domains of electronic business (eBusiness) and electronic commerce (eCommerce). We utilise the developing domains of online retail in general and online grocery in particular to ground our theorisation.
Sorting On-line and On-time ∗

In this paper we provide novel evidence on the direction and strength of worker-ﬁrm sorting, using data from a Chilean job posting website. Our evidence is at the job application stage and relies on the fact that we observe several characteristics (including desired and paid wages) for both individuals and ﬁrms posting their ads. We ﬁnd strong, positive assortative matching between job seekers and job postings, both along observed dimensions and on unobserved characteristics, which we proxy using residual wages (from linear regressions). We further estimate the value job seekers assign to several dimensions of a job: our results show that positive sorting in terms of education levels and occupations are the most important variables explaining decisions to apply. We also show how individuals behave in the presence of under/over qualiﬁcation with respect to position requirements. Finally, we analyze how sorting ﬂuctuates with business cycle conditions: we ﬁnd that positive assortative matching is pro-cyclical (residual wage mismatch is counter-cyclical), and that this result is mainly driven by the counter-cyclicality of applications in which types of ﬁrms are higher than those of workers. several of a our results show that positive sorting in terms of educational levels and are the more important ones (they increase the likelihood of an application), and also show how individuals apply in the presence of under/over qualiﬁcation with respect to positions. show that the and For case of all
MODELLING THE TECHNICAL EFFICIENCY OF RICE PRODUCTION IN NIGERIA

Rice botanically known as Oryza sativa has become a household food item in Nigeria, prompting the adoption of measures to ensure self-sufficiency in its production thus the need to analyse its production efficiency. This study employed data drawn from selected Nigerian states which included 168 rice farms within a Cobb-Douglas stochastic production frontier framework. The technical efficiency mean value obtained implied that on average, rice farmers obtained only 63% of the optimal output from inputs used in the production process. This therefore suggests that when inputs are efficiently utilized, technical inefficiency should be 37%. Empirical results more specifically revealed a considerable need for increased efficiency to complement rice supply shortfalls. The study suggested among other policy thrusts the need to assist rice farmers with adequate finance in order to increase production efficiency.
Single maintenance and reliever therapy (SMART) of asthma: a critical appraisal

The use of a combination inhaler containing budesonide and formoterol as both maintenance and quick relief therapy (SMART) has been recommended as an improved method of using inhaled corticosteroid/long-acting β agonist (ICS/LABA) therapy. Published double-blind trials show that budesonide/formoterol therapy delivered in SMART fashion achieves better asthma outcomes than budesonide monotherapy or lower doses of budesonide/formoterol therapy delivered in constant dosage. Attempts to compare budesonide/formoterol SMART therapy with regular combination ICS/LABA dosing using other compounds have been confounded by a lack of blinding and unspecified dose adjustment strategies. The asthma control outcomes in SMART-treated patients are poor; it has been reported that only 17.1% of SMART-treated patients are controlled. In seven trials of 6–12 months duration, patients using SMART have used quick reliever daily (weighted average 0.92 inhalations/day), have awakened with asthma symptoms once every 7–10 days (weighted average 11.5% of nights), have suffered asthma symptoms more than half of days (weighted average 54.0% of days) and have had a severe exacerbation rate of one in five patients per year (weighted average 0.22 severe exacerbations/patient/year). These poor outcomes may reflect the recruitment of a skewed patient population. Although improvement from baseline has been attributed to these patients receiving additional ICS therapy at pivotal times, electronic monitoring has not been used to test this hypothesis nor the equally plausible hypothesis that patients who are non-compliant with maintenance medication have used budesonide/formoterol as needed for self-treatment of exacerbations. Although the long-term consequences of SMART therapy have not been studied, its use over 1 year has been associated with significant increases in sputum and biopsy eosinophilia. At present, there is no evidence that better asthma treatment outcomes can be obtained by moment-to-moment symptom-driven use of ICS/LABA therapy than conventional physician-monitored and adjusted ICS/LABA therapy.
'S PERSPECTIVE ON DEPRESSION AND ANXIETY IN

Abu Zayd Al-Balkhi was a Muslim polymath who made significant contributions to the field of psychology, particularly in his views on depression and anxiety. This research aimed to understand al-Balkhi's perspective on depression and anxiety in the context of Islam during his time and to contribute to the understanding of mental health that aligns with Islamic values. The study employed a literature research method to analyze his main work, “Masalih Al-Abdan Wa Al-Anfus”, and investigated Al-Balkhi's opinions on depression and anxiety. Researchers also classified different types of depression and the understanding of anxiety as proposed by Al-Balkhi. The research findings revealed that Al-Balkhi was one of the early pioneers in understanding mental disorders by categorizing psychological symptoms within a more modern framework. Furthermore, the study highlighted his views on the connection between physical and mental health and emphasized the significance of maintaining a balance between the two.
How Good Is QUIC Actually?

—The Internet Engineering Task Force (IETF) is currently ﬁnalizing the standardization of the QUIC core transport protocol and HTTP/3 (H3) with a target date of July 2019 for the ﬁnal speciﬁcation. The working group has deﬁned ﬁve key goals that should be improved on: connection establishment and transport latency, head-of-line blocking, secure transport, allowing future evolution, as well as multipath and forward error correction extensions. In this paper, we explain the problems QUIC tries to solve, discuss QUIC’s proposed solutions, and highlight their strengths and weaknesses.
Unsupervised-to-Supervised Sea Clutter Suppression via Adversarial Priori and Idempotent Generative Theorem

—Marine radar is widely employed in ocean monitoring systems. However, the presence of sea clutter and noise significantly hampers the detection performance of marine radar. In this paper, we propose an unsupervised-to-supervised sea clutter suppression and denoise framework. The unsupervised stage provides sufficiently high-quality pseudo-labels to the supervised stage, effectively addressing the challenge of obtaining clean labels in current supervised deep learning-based (DL-based) sea clutter suppression methods. The experiments demonstrate that our proposed method exhibits excellent adaptability in both single-target and multi-target scenarios, as well as under various pulse quantities, effectively suppressing sea clutter and noise in low signal-to-clutter ratio (SCR) and signal-to-noise ratio (SNR). In addition, we also verified that the proposed method does not lose clean signals at high SCR and SNR. To validate the widespread applicability of our unsupervised stage, we integrate it into other supervised DL-based clutter suppression methods, and the experiments show a noticeable improvement in the performance of these methods. To further verify the effectiveness of the proposed framework, we conduct validation on downstream applications of radar target detection. Our code will be released after possible acceptance.
ITRF2014 plate motion model

For various geodetic and geophysical applications, users need to have access to a Plate Motion Model (PMM) that is consistent with the ITRF2014 frame. The aim of this paper is to describe the approach used for determining a PMM from the horizontal velocities of a subset of the ITRF2014 sites away from plate boundaries, Glacial Isostatic Adjustment regions and other deformation zones. We show that it is necessary to include in the inversion model a translation rate vector between the ITRF2014 origin (long-term averaged center of mass of the Earth as sensed by SLR) and the center of tectonic plate motion. We additionally assess the impact of the site distribution (i.e. network effect) on both the estimated Euler poles and translation rate vector (called here Origin Rate Bias – ORB). The site selection finally adopted for the ITRF2014-PMM adjustment leads to a relatively small ORB (0.3 mm/yr in the Z-component). Nevertheless, in order to accommodate operational geodesy applications that require access to the ITRF2014 frame through pure plate rotation poles, we also provide an alternative model, without ORB, based on plate-by-plate rotation pole adjustments.
This paper is included in the Proceedings of the 32nd USENIX Security Symposium

WebGL is a set of standardized JavaScript APIs for GPU accelerated graphics. Security of the WebGL interface is paramount because it exposes remote and unsandboxed access to the underlying graphics stack (including the native GL libraries and GPU drivers) in the host OS. Unfortunately, applying state-of-the-art fuzzing techniques to the WebGL interface for vulnerability discovery is challenging because of (1) its huge input state space, and (2) the infeasibility of collecting code coverage across concurrent processes, closed-source libraries, and device drivers in the kernel. Our fuzzing technique, GLeeFuzz, guides input mutation by error messages instead of code coverage. Our key observation is that browsers emit meaningful error messages to aid developers in debugging their WebGL programs. Error messages indicate which part of the input fails (e.g., incomplete arguments, invalid arguments, or unsatisﬁed dependencies between API calls). Leveraging error messages as feedback, the fuzzer effectively expands coverage by focusing mutation on erroneous parts of the input . We analyze Chrome’s WebGL implementation to identify the dependencies between error-emitting statements and rejected parts of the input, and use this information to guide input mutation. We evaluate our GLeeFuzz prototype on Chrome, Firefox, and Safari on diverse desktop and mobile OSes. We discovered 7 vulnerabilities, 4 in Chrome, 2 in Safari, and 1 in Firefox. The Chrome vulnerabilities allow a remote attacker to freeze the GPU and possibly execute remote code at the browser privilege.
Pelvic Organ Prolapse.

OBSTETRICS & GYNECOLOGY Committee on Practice Bulletins—Gynecology and American Urogynecologic Society. This Practice Bulletin was developed by the Committee on Practice Bulletins—Gynecology and the American Urogynecologic Society in collaboration with Paul Tulikangas, MD. The information is designed to aid practitioners in making decisions about appropriate obstetric and gynecologic care. These guidelines should not be construed as dictating an exclusive course of treatment or procedure. Variations in practice may be warranted based on the needs of the individual patient, resources, and limitations unique to the institution or type of practice. Background Definition
Individual and partner’s level of occupation and the association with HbA1c levels in people with type 2 diabetes mellitus: the Dutch Diabetes Pearl cohort

Anne Rutte Simone P. Rauh Miranda T. Schram Giel Nijpels J. Hans DeVries Frits Holleman Hanno Pijl Olaf M. Dekkers Behiye Özcan Eric J. G. Sijbrands Cees J. Tack Evertine J. Abbink Harold W. de Valk Bianca Silvius Bruce H. R. Wolffenbuttel Coen D. A. Stehouwer Nicolaas C. Schaper Jacqueline M. Dekker Joline W. Beulens Petra J. M. Elders Femke Rutters on behalf of the Diabetes Pearl from the Parelsnoer Initiative
Application of Perturbation Theory for P-wave Eikonal Equation in Orthorhombic Media

The P-wave eikonal equation for orthorhombic media is the sixth-order PDE with complex and time-consuming numerical solution. We propose to approximate the solution of this equation by applying multi-parametric perturbation method. We also investigate the sensitivity of traveltime surface in orthorhombic media with respect to three anelliptic parameters. A simple moveout equation valid for orthorhombic media is derived.