Miracle-dz/UniFAR-FTUs huggingface dataset:
Technical Note: Trend estimation from irregularly sampled, correlated data

Abstract. Estimation of a trend of an atmospheric state variable is usually performed by fitting a linear regression line to a set of data of this variable sampled at different times. Often these data are irregularly sampled in space and time and clustered in a sense that error correlations among data points cause a similar error of data points sampled at similar times. Since this can affect the estimated trend, we suggest to take the full error covariance matrix of the data into account. Superimposed periodic variations can be jointly fitted in a straightforward manner, even if the shape of the periodic function is not known. Global data sets, particularly satellite data, can form the basis to estimate the error correlations. State-dependent amplitudes of superimposed periodic corrections result in a non-linear optimization problem which is solved iteratively.
A System for Handwritten and Printed Text Classification

An optical character recognition (OCR) system recognizes either printed or handwritten text. Hence it is required to seperate machine printed text from handwritten text in scanned documents before feeding it to a OCR system. We can discriminate these two types of text word images by their visual impression and shape structures. The intensity values distribution features gives us the visual impression and the shapes can be represented by the structural features. This paper proposes an approach for machine print and handwritten text classification at word level using intensity and shape structural features of scanned text. The proposed method achieved impressive classification efficiency on IAM dataset.
HEDEA: A Python Tool for Extracting and Analysing Semi-structured Information from Medical Records

Objectives One of the most important functions for a medical practitioner while treating a patient is to study the patient's complete medical history by going through all records, from test results to doctor's notes. With the increasing use of technology in medicine, these records are mostly digital, alleviating the problem of looking through a stack of papers, which are easily misplaced, but some of these are in an unstructured form. Large parts of clinical reports are in written text form and are tedious to use directly without appropriate pre-processing. In medical research, such health records may be a good, convenient source of medical data; however, lack of structure means that the data is unfit for statistical evaluation. In this paper, we introduce a system to extract, store, retrieve, and analyse information from health records, with a focus on the Indian healthcare scene. Methods A Python-based tool, Healthcare Data Extraction and Analysis (HEDEA), has been designed to extract structured information from various medical records using a regular expression-based approach. Results The HEDEA system is working, covering a large set of formats, to extract and analyse health information. Conclusions This tool can be used to generate analysis report and charts using the central database. This information is only provided after prior approval has been received from the patient for medical research purposes.
What’s Wrong, Python? – A Visual Differ and Graph Library for NLP in Python

The correct analysis of the output of a program based on supervised learning is inevitable in order to be able to identify the errors it produced and characterise its error types. This task is fairly difﬁcult without a proper tool, especially if one works with complex data structures such as parse trees or sentence alignments. In this paper, we present a library that allows the user to interactively visualise and compare the output of any program that yields a well-known data format. Our goal is to create a tool granting the total control of the visualisation to the user, including extensions, but also have the common primitives and data-formats implemented for typical cases. We describe the common features of the common NLP tasks from the viewpoint of visualisation in order to specify the essential primitive functions. We enumerate many popular off-the-shelf NLP visualisation programs to compare with our implementation, which uniﬁes all of the proﬁtable features of the existing programs adding extendibility as a crucial feature to them.
End-to-end optimization of optics and image processing for achromatic extended depth of field and super-resolution imaging

In typical cameras the optical system is designed first; once it is fixed, the parameters in the image processing algorithm are tuned to get good image reproduction. In contrast to this sequential design approach, we consider joint optimization of an optical system (for example, the physical shape of the lens) together with the parameters of the reconstruction algorithm. We build a fully-differentiable simulation model that maps the true source image to the reconstructed one. The model includes diffractive light propagation, depth and wavelength-dependent effects, noise and nonlinearities, and the image post-processing. We jointly optimize the optical parameters and the image processing algorithm parameters so as to minimize the deviation between the true and reconstructed image, over a large set of images. We implement our joint optimization method using autodifferentiation to efficiently compute parameter gradients in a stochastic optimization algorithm. We demonstrate the efficacy of this approach by applying it to achromatic extended depth of field and snapshot super-resolution imaging.
A fiskális politika jelzőszámai [Indicators of fiscal policy]

A hagyomanyos statisztikai hianykategoriak alkalmazhatosaga szamos feltetelhez kotődik, peldaul ahhoz, hogy az arszintemelkedes merteke nem jelentős, vagy ha megis, akkor a gazdasagi elet szereplőit nem befolyasolja a penzilluzio. Ehhez kepest egy analitikus jelzőszam realisabb feltetelezeseken alapulo modellekre epulhet, azonban a modell osszetettsege az osszehasonlithatosag rovasara mehet. A tanulmany az osszevethetőseg biztositasa erdekeben a nemzetkozileg szelesebb korben ismert analitikus mutatokat tekinti at, roviden bemutatva azokat az elmeleti kereteket, amelyekben ezek a jelzőszamok ertelmezhetők.
Likelihood-based inference for the power half-normal distribution

In this paper we consider an extension of the half-normal distribution based on the distribution of the maximum of a random sample. It is shown that this distribution belongs to the family of beta generalized half-normal distributions. Properties of its density are investigated, maximum likelihood estimation is discussed and the Fisher information matrix is derived. A real data illustration is presented, and comparisons with alternative extensions of the half-normal distribution reveal good performance of the proposed model.
Improving abdomen tumor low-dose CT images using a fast dictionary learning based processing

In abdomen computed tomography (CT), repeated radiation exposures are often inevitable for cancer patients who receive surgery or radiotherapy guided by CT images. Low-dose scans should thus be considered in order to avoid the harm of accumulative x-ray radiation. This work is aimed at improving abdomen tumor CT images from low-dose scans by using a fast dictionary learning (DL) based processing. Stemming from sparse representation theory, the proposed patch-based DL approach allows effective suppression of both mottled noise and streak artifacts. The experiments carried out on clinical data show that the proposed method brings encouraging improvements in abdomen low-dose CT images with tumors.
Analysis of Images in Iranian High School EFL Course Books

Although images are abundant and play significant aesthetic and pedagogical roles in today’s EFL course books, they are still one of the less explored areas of research. The present study is an attempt to examine the role and function of images in Iranian high school EFL course books; it also aims to cast a critical eye over their suitability and efficiency. To this end, Kress and Van Leeuwen’s (2006) model of visual grammar was adopted. The findings revealed that although the informative and/or illustrative functions of the images make them important resources in Iranian high school EFL course books, their full potential for language learning does not seem to be adequately exploited. This relates to flaws at the representational mode of meaning making, such as outdated portrayal of objects, gender stereotyping, and overdramatizing national identity as well as shortcomings at the interactive mode, such as poor modality due to grayscale printing and plain graphics with no contextualization or pictorial detail. These flaws make the images seem out of today’s world and hardly credible for high school students who are already adept at new technology. Since these shortcomings may sacrifice pedagogical objectives, the study calls for changes in both technical quality and underlying messages of images in the course books.
Optimal allocation of HIV prevention funds for state health departments

Objective To estimate the optimal allocation of Centers for Disease Control and Prevention (CDC) HIV prevention funds for health departments in 52 jurisdictions, incorporating Health Resources and Services Administration (HRSA) Ryan White HIV/AIDS Program funds, to improve outcomes along the HIV care continuum and prevent infections. Methods Using surveillance data from 2010 to 2012 and budgetary data from 2012, we divided the 52 health departments into 5 groups varying by number of persons living with diagnosed HIV (PLWDH), median annual CDC HIV prevention budget, and median annual HRSA expenditures supporting linkage to care, retention in care, and adherence to antiretroviral therapy. Using an optimization and a Bernoulli process model, we solved for the optimal CDC prevention budget allocation for each health department group. The optimal allocation distributed the funds across prevention interventions and populations at risk for HIV to prevent the greatest number of new HIV cases annually. Results Both the HIV prevention interventions funded by the optimal allocation of CDC HIV prevention funds and the proportions of the budget allocated were similar across health department groups, particularly those representing the large majority of PLWDH. Consistently funded interventions included testing, partner services and linkage to care and interventions for men who have sex with men (MSM). Sensitivity analyses showed that the optimal allocation shifted when there were differences in transmission category proportions and progress along the HIV care continuum. Conclusion The robustness of the results suggests that most health departments can use these analyses to guide the investment of CDC HIV prevention funds into strategies to prevent the most new cases of HIV.
Effects of Alkalinity and pH on Survival, Growth, and Enzyme Activities in Juveniles of the Razor Clam, Sinonovacula constricta

In order to clarify the possibility of rearing razor clams (Sinonovacula constricta) in inland saline water (ISW) and to facilitate their breeding under these stressful conditions, we performed semi-static acute and chronic toxicity tests to determine the effects of carbonate alkalinity (CA) and pH on the survival and growth rate, and critical metabolic enzyme activity in juvenile of S. constricta (JSC). (1) Acute toxicity test. As the water CA increased from 1.22 to 45.00 mmol L-1, the survival rate decreased significantly, which was exacerbated by the increase in the pH. When the water CA was set at 2.5 mmol L-1, the 48 h lethal concentration 50% (LC50) for JSCs with respect to pH was 9.86. When the water pH was 9.0, 9.5, and 10.0, the 48 h LC50 values for JSCs with respect to CA were 10.38, 8.79, and 3.11 mmol L-1, respectively. (2) Chronic toxicity test. Four experimental groups comprising the control, CAS, pHS, and CA-pHS were designated according to the target ISW data. After 3 months of stress, the JSC survival rate in each group exceeded 85%, but survival was significantly lower in the CA-pHS group than the control group (p < 0.05) in the first month. For the JSCs in various groups, the shell length growth rate (SGR) and weight gain (WG) rate were significantly lower in the CA-pHS group than the other groups (p < 0.05 for SGR; p < 0.001 for WG) in the first month. However, the difference in the growth rate among groups decreased in the next 2 months. For the JSCs in the CA-pHS group, the oxygen consumption, ammonia-N excretion, Na+/K+-ATPase, aspartate aminotransferase, and superoxide dismutase levels were significantly higher than those in the other groups during the first month, but there were no significant differences between the groups subsequently. The acetylcholinesterase and lysozyme levels did not differ significantly among groups during stress for 3 months. The integrated biomarker response index showed that stressors comprising high pH and CA could be tolerated well by JSCs over long periods of stress. These results indicate that water CA and pH together affect the survival, growth, and physiological activity of JSCs. S. constricta is suitable for culture in ISW.
Public Attitudes Toward Guided Internet-Based Therapies: Web-Based Survey Study

Background Internet interventions have been proposed to improve the accessibility and use of evidence-based psychological treatments. However, little is known about attitudes toward such treatments, which can be an important barrier to their use. Objective This study aimed to (1) determine attitudes toward guided internet interventions, (2) assess its acceptability compared with other internet-based formats, and (3) explore predictors of acceptance. Methods A convenience-sample Web-based survey (N=646) assessed attitudes toward guided internet therapies (ie, perceived usefulness and helpfulness, and advantage relative to face-to-face therapy), preferences for delivery modes (ie, e-preference: guided internet interventions, unguided internet interventions, or videoconferencing psychotherapy), and potential predictors of attitudes and preferences: sociodemographics, help-seeking–related variables, attachment style, and perceived stress. Results Although most participants perceived internet interventions as useful or helpful (426/646, 65.9%), a few indicated their advantage relative to face-to-face therapy (56/646, 8.7%). Most participants preferred guided internet interventions (252/646, 39.0%) over videoconferencing psychotherapy (147/646, 22.8%), unguided internet interventions (124/646, 19.2%), and not using internet interventions (121/646, 18.8%; missing data: 1/646, 0.2%). Attachment avoidance and stress were related to e-preference (all P<.05). Moreover, preference for therapist-guided internet interventions was higher for individuals who were aware of internet-based treatment (χ26=12.8; P=.046). Conclusions Participants assessed therapist-guided internet interventions as helpful, but not equivalent to face-to-face therapies. The vast majority (523/646, 81.0%) of the participants were potentially willing to use internet-based approaches. In lieu of providing patients with only one specific low-intensity treatment, implementation concepts should offer several options, including guided internet interventions, but not limited to them. Conversely, our results also indicate that efforts should focus on increasing public knowledge about internet interventions, including information about their effectiveness, to promote acceptance and uptake.
A Social Network Environment Based Analysis for Construction of Cancer Care

: Social media provides rich sources of personal information and community interaction which can be linked to aspect of mental health. In this paper we investigate manifest properties of textual messages, including latent topics, psycholinguistic features, and authors’ health, of a large corpus of blog posts, to analyze the aspect of social capital in social media communities. Using data collected from Live Journal, we find that bloggers with lower social capital have fewer positive moods and more negative moods than those with higher social capital. It is also found that people with low social capital have more random mood swings over time than the people with high social capital. Significant differences are found between low and high social capital groups when characterized by a set of latent topics and psycholinguistic features derived from blogposts, suggesting discriminative features, proved to be useful for classification tasks. Good prediction is achieved when classifying among social capital groups using topic and linguistic features, with linguistic features are found to have greater predictive power than latent topics. The significance of our work lies in the importance of online social capital to potential construction of automatic healthcare monitoring systems. We further establish the link between health and social capital in online communities, suggesting the foundation of new systems to monitor online mental well-being.
Instructions for Patient Health Questionnaire (PHQ) and GAD-7 Measures

The Primary Care Evaluation of Mental Disorders (PRIME-MD) was an instrument developed and validated in the early 1990s to efficiently diagnose five of the most common types of mental disorders presenting in medical populations: depressive, anxiety, somatoform, alcohol, and eating disorders. [1] Patients first completed a one-page 27-item screener and, for those disorders for which they screened positive, were asked additional questions by the clinician using a structured interview guide. However, this 2-stage process took an average of 5-6 minutes of clinician time in patients without a mental disorder diagnosis and 11-12 minutes in patients with a diagnosis. This proved to be a barrier to use given the competing demands in busy clinical practice settings.
Design of an Energy Management Strategy for a Parallel Hybrid Electric Bus Based on an IDP-ANFIS Scheme

A critical challenge in the energy management of hybrid electric vehicles is how to intelligently distribute the power between engine and electric motor with a significant reduction in fuel consumption and emissions. In this paper, iterative dynamic programming (IDP) and adaptive neurofuzzy inference system (ANFIS)-based energy management strategy was proposed for a parallel hybrid electric bus. First, IDP was used to obtain the optimal control trajectories for a specific driving cycle. During the iterative process, a modified gear-shifting strategy was introduced to achieve a good tradeoff between the fuel economy and the drivability performance. Next, multi-ANFIS networks were designed and trained to learn the control law from the available optimal trajectories. Finally, the real-time energy management controller based on the IDP-ANFIS was built to coordinate the output of the two power sources, which reduces the fuel consumption and emissions. The simulation and experimental results reveal that the IDP-ANFIS is feasible, and the performance is superior to that of the equivalent consumption minimization strategy and rule-based method.
Continuity and Change in Japanese Management

The system of manpower management developed in the 1960s and 1970s that has served Japan so well is currently undergoing a transformation. This article assesses the magnitude and direction of the changes in the employment and promotion systems inside Japanese companies. The Japanese company of the future will be a hybrid that effectively combines the advantages of lifetime employment practices with some of the flexibilities of a Western-style horizontal labor market.
Probabilistic description of ice-supersaturated layers in low resolution profiles of relative humidity

Abstract. The global observation, assimilation and prediction in numerical models of ice super-saturated (ISS) regions (ISSR) are crucial if the climate impact of aircraft condensation trails (contrails) is to be fully understood, and if, for example, contrail formation is to be avoided through aircraft operational measures. Given their small scales compared to typical atmospheric model grid sizes, statistical representations of the spatial scales of ISSR are required, in both horizontal and vertical dimensions, if global occurrence of ISSR is to be adequately represented in climate models. This paper uses radiosonde launches made by the UK Meteorological Office, from the British Isles, Gibraltar, St. Helena and the Falkland Islands between January 2002 and December 2006, to investigate the probabilistic occurrence of ISSR. Each radiosonde profile is divided into 50- and 100-hPa pressure layers, to emulate the coarse vertical resolution of some atmospheric models. Then the high resolution observations contained within each thick pressure layer are used to calculate an average relative humidity and an ISS fraction for each individual thick pressure layer. These relative humidity pressure layer descriptions are then linked through a probability function to produce an s-shaped curve which empirically describes the ISS fraction in any average relative humidity pressure layer. Using this empirical understanding of the s-shaped relationship a mathematical model was developed to represent the ISS fraction within any arbitrary thick pressure layer. Two models were developed to represent both 50- and 100-hPa pressure layers with each reconstructing their respective s-shapes within 8–10% of the empirical curves. These new models can be used, to represent the small scale structures of ISS events, in modelled data where only low vertical resolution is available. This will be useful in understanding, and improving the global distribution, both observed and forecasted, of ice super-saturation.
Lighten up the dark: metazoan parasites as indicators for the ecology of Antarctic crocodile icefish (Channichthyidae) from the north-west Antarctic Peninsula

Due to its remote and isolated location, Antarctica is home to a unique diversity of species. The harsh conditions have shaped a primarily highly adapted endemic fauna. This includes the notothenioid family Channichthyidae. Their exceptional physiological adaptations have made this family of icefish the focus of many studies. However, studies on their ecology, especially on their parasite fauna, are comparatively rare. Parasites, directly linked to the food chain, can function as biological indicators and provide valuable information on host ecology (e.g., trophic interactions) even in remote habitats with limited accessibility, such as the Southern Ocean. In the present study, channichthyid fish (Champsocephalus gunnari: n = 25, Chaenodraco wilsoni: n = 33, Neopagetopsis ionah: n = 3, Pagetopsis macropterus: n = 4, Pseudochaenichthys georgianus: n = 15) were collected off South Shetland Island, Elephant Island, and the tip of the Antarctic Peninsula (CCAML statistical subarea 48.1). The parasite fauna consisted of 14 genera and 15 species, belonging to the six taxonomic groups including Digenea (four species), Nematoda (four), Cestoda (two), Acanthocephala (one), Hirudinea (three), and Copepoda (one). The stomach contents were less diverse with only Crustacea (Euphausiacea, Amphipoda) recovered from all examined fishes. Overall, 15 new parasite-host records could be established, and possibly a undescribed genotype or even species might exist among the nematodes.