Miracle-dz/UniFAR-FTUs huggingface dataset:
Digestive tract neural control and gastrointestinal disorders in cerebral palsy.

OBJECTIVES To examine the neural control of digestive tract and describe the main gastrointestinal disorders in cerebral palsy (CP), with attention to the importance of early diagnosis to an efficient interdisciplinary treatment. SOURCES Systematic review of literature from 1997 to 2012 from Medline, Lilacs, Scielo, and Cochrane Library databases. The study included 70 papers, such as relevant reviews, observational studies, controlled trials, and prevalence studies. Qualitative studies were excluded. The keywords used were: cerebral palsy, dysphagia, gastroesophageal reflux disease, constipation, recurrent respiratory infections, and gastrostomy. SUMMARY OF THE FINDINGS The appropriate control of the digestive system depends on the healthy functioning and integrity of the neural system. Since CP patients have structural abnormalities of the central and peripheral nervous system, they are more likely to develop eating disorders. These range from neurological immaturity to interference in the mood and capacity of caregivers. The disease has, therefore, a multifactorial etiology. The most prevalent digestive tract disorders are dysphagia, gastroesophageal reflux disease, and constipation, with consequent recurrent respiratory infections and deleterious impact on nutritional status. CONCLUSIONS Patients with CP can have neurological abnormalities of digestive system control; therefore, digestive problems are common. The issues raised in the present study are essential for professionals within the interdisciplinary teams that treat patients with CP, concerning the importance of comprehensive anamnesis and clinical examination, such as detailed investigation of gastrointestinal disorders. Early detection of these digestive problems may lead to more efficient rehabilitation measures in order to improve patients' quality of life.
Cross-border workers’ remittances: Transmission channels and measurement issues in India

The debate on appropriate measurement of workers’ remittances and the greater need for conceptual clarity about such statistics both for the compilers and the users raises certain important issues. First, lack of uniformity in properly identifying and measuring remittances of migrant workers constrains the scope of international comparability. For instance, in many countries translated in the form of transfers to residents as unrequited transfers. These country specific formats of remittance transfers and their inclusion in the remittance statistics need to be clearly recognized. Thus, the definitional issues need clarity to provide direction to the compiling counties to produce comparable statistics. Second, the experience of developing countries suggests that the survey method has its own limitations due to poor response of participants, particularly in a more liberalized environment. Even under the ITRS, the introduction of formats seeking disaggregated information does not ensure quality of data when respondents are either not cautious in classifying the detailed transactions or lack adequate skill to handle such information. Missing incentive systems for the reporting entities may also result in inadequate data quality. Third, is there a need for synthesizing statistics on remittances and the migration statistics? To what extent the migration statistics can keep pace with the requirements of compilation of remittances in terms of updated information, and attributes such as changing structure of migrant stocks, skill classification, average income levels, duration of stay etc. Possibility to develop an appropriate information system through coordinated efforts of migration authorities, immigration offices, the population census and the BoP compilers? The scope for sharing the host country statistics on immigration, which is presumably credible due to firm record of immigrants. Fourth, as many countries rely on the ITRS, it becomes extremely difficult to segregate between workers’ remittances and the compensation of employees by the reporting entities. The thin dividing line is conceptual rather than functional and more often the reporting entities do not have details on the period of stay.
TO A CONTRIBUTION TO THE CRITIQUE OF HEGEL ’ S PHILOSOPHY OF RIGHT

From McLellan: “[This manuscript] was written when Marx’s ideas were in a transient state: he had adopted the fundamental humanism of Feuerbach and, with it, Feuerbach’s reversal of subject and predicate in the Hegelian dialectic. He considered it plain that the task ahead was the recovery by man of the social dimension of his nature that had been lost ever since the French Revolution leveled all citizens in the political state and thus accentuated the individualism of bourgeois society. It was clear to Marx that private property must cease to be the basis of social organization, but it is not obvious that he was arguing for its abolition, nor did he make clear the various roles of classes in the social evolution. ” The selection reprinted below was first published in the Deutsch-Französische Jahrbücher (1844).
A Survey among Dog and Cat Owners on Pet Food Storage and Preservation in the Households

Simple Summary Proper dog and cat food preservation is fundamental to ensure the best quality of the diet right up to the moment of feeding, given that nutritional value, safety and sensory properties can be irreparably damaged by environment and time. To this end, a survey was conducted to explore how pet owners store both commercial and home-prepared diets. On the whole, despite the wide variability of practices adopted, most of the 2221 respondents implemented good storage management. Room temperature was the most overlooked parameter during storage, and this may be a cause of concern because exposure to warmth can enhance rancidity, especially in diet formulations rich in fats and oils. For this reason, veterinarians should provide precise instructions on storing perishable ingredients to those who feed home-prepared diets. Moreover, respondents of older generations appeared to distrust the use of preservatives in commercial pet foods and often deemed their inclusion harmful and unnecessary. Pet food manufacturers should discourage skepticism of the additives crucial to long-term commercial pet food conservation through better communication. Abstract Background: Pet food storage plays a crucial role in maintaining the nutritional and sensory properties of purchased products over time. Methods: An online survey was developed to collect data regarding owners’ storage habits for both commercial and home-made diets. Results: The questionnaire was completed by 1545 dog owners and 676 cat owners. Pet and owner age played roles in the choice of the type of diet (commercial vs. home-cooked vs. raw meat-based) adopted. Kibble feeders (75.7%) usually bought one (50.1%) or two (24.6%) packages at a time, and most pets (64.4%) took a minimum four weeks to consume an entire bag. Almost half of the owners (43.5%) used a container to store pet food (plastic bins for 79.5%). Pet food was commonly stored in the kitchen (45.1%) and not exposed to direct light (94.5%); 23.6% of the kibble feeders said it might be exposed to high temperatures. Most commercial pet food feeders (67.3%) considered preservatives a potential health risk for pets. Among homemade diet feeders, 38.6% stored fish oil at room temperature. Conclusions: Pet owners should be educated in proper food storage management when receiving feeding instructions from veterinarians. More comprehensive information on the nature and importance of additives in pet food should be promoted by manufacturers.
Pragmatic Analysis of Fruit Processing Models for Quality Evaluation from a Statistical Perspective

Fruits & other naturally occurring plant-based products change their temporal visual appearance & smell when separated from their parent trees. The temporal visual appearance is used by image processing analysts to evaluate its quality, and lifespan related parameters. In order to perform this task, various components are used, which include, pre-processing models, segmentation models, feature extraction & selection techniques, classification models, and post-processing techniques. Each of these micro models vary in terms of performance metrics like accuracy of detection, error rate, signal to noise ratio (SNR), computational complexity, delay of processing, cost of deployment, etc. Due to such a wide variation in performance, there is an ambiguity in method selection while designing an efficient fruit quality detection model. Due to this ambiguity, researchers need to validate individual model performance, and then interface them with their own architecture. This process is cumbersome, and increases deployment cost & time needed for bringing the product into market. In order to reduce this ambiguity, a review of recently proposed models for fruit quality detection is discussed in this text. These models are reviewed on the basis of their nuances, advantages, limitations, and future research scopes along with their scalability performance. This text also compares the reviewed fruit-image models in terms of processing delay, accuracy, precision, recall, computational complexity, and recommended application of use. These applications include quality analysis, artificial ripening detection, disease detection, and fruit grading applications. Based on this comparison, researchers can identify best performing model(s) and/or their combinations for application-specific deployments.
LATE-TIME NEAR-INFRARED OBSERVATIONS OF SN 2005df

We present late-time near-infrared (NIR) spectral evolution, at 200–400 days, for the Type Ia supernova SN 2005df. The spectra show numerous strong emission features of [Co ii], [Co iii], and [Fe ii] throughout the 0.8–1.8 μm region. As the spectrum ages, the cobalt features fade as would be expected from the decay of 56Co to 56Fe. We show that the strong and isolated [Fe ii] emission line at 1.644 &mgr; m ? > provides a unique tool to analyze NIR spectra of SNe Ia. Normalization of spectra to this line allows the separation of features produced by stable versus unstable isotopes of iron group elements. We develop a new method of determining the initial central density, &rgr; c ? > , and the magnetic field, B, of the white dwarf (WD) using the width of the 1.644 &mgr; m ? > line. The line width (LW) is sensitive because of electron capture in the early stages of burning, which increases as a function of density. The sensitivity of the LW to B increases with time, and the effects of the magnetic field shift toward later times with decreasing &rgr; c ? > . Through comparison with spherical models, the initial central density for SN 2005df is measured as &rgr; c = 0.9 ( ± 0.2 ) × 10 9 g cm − 3 ? > , which corresponds to a WD close to the Chandrasekhar mass, with M WD = 1.31 ( ± 0.03 ) M ☉ ? > and systematic error less than 0.04 M ☉ ? > . This error estimate is based on spherical models. We discuss the potential uncertainties due to multi-dimensional effects, mixing, and rotation. The latter two effects would increase the estimate of the WD mass. Within M Ch ? > explosions, however, the central density found for SN 2005df is very low for a H-accretor, possibly suggesting a helium star companion or a tidally disrupted WD companion. As an alternative, we suggest mixing of the central region. We find some support for high initial magnetic fields of strength 10 6 G ? > for SN 2005df, however, 0 G ? > cannot be ruled out because of noise in the spectra combined with low &rgr; c ? > . We discuss our findings in the context of mixing by Rayleigh–Taylor instabilities during deflagration burning and a wide variety of explosion scenarios. Observations strongly support a very limited amount of mixing during a deflagration phase and high central densities characteristic of a M Ch ? > WD.
SLIC: Self-Conditioned Adaptive Transform with Large-Scale Receptive Fields for Learned Image Compression

—Recently, learned image compression methods have achieved remarkable performance. Analysis and synthesis transform, play an important role in boosting the rate-distortion performance. Analysis transform converts the input image to a compact latent representation. The more compact the latent representation is, the fewer bits we need to compress an image. When designing better transform, some previous works adopt Swin-Transformer. However, the LayerNorm adopted in trans-formers is not suitable for image compression. The success of the Swin-Transformer in image compression can be attributed to the dynamic weights of self-attention, and large receptive ﬁeld. We ﬁnd CNN-based modules can also be dynamic and adaptive and have large receptive-ﬁelds. The CNN-based modules can also work with GDN / IGDN. To make the CNN-based modules dynamic and adaptive, we generate the weights of kernels conditioned on the input feature. We scale up the size of each kernel for larger receptive ﬁelds. To reduce complexity, we make the CNN-module channel-wise connected. We call this module Dynamic Depth-wise convolution. We replace the self-attention module with the proposed Dynamic Depth-wise convolution, replace the embedding layer with a depth-wise residual bottleneck for non-linearity and replace the FFN layer with an inverted residual bottleneck for more interactions in the spatial domain. The interactions among channels of dynamic depth-wise convolution are limited. We design the other block, which replaces the dynamic depth-wise convolution with channel attention. We equip the proposed modules in the analysis transform and the synthesis transform and receive a more compact latent representation and propose the learned image compression model SLIC, meaning Self-Conditioned Adaptive Transform with Large-Scale Receptive Fields for Learned Image Compression Learned Image Compression. Thanks to the proposed transform modules, we achieve state-of-the-art performance on the Kodak dataset. Our proposed SLIC achieves 6.35% BD-rate reduction over VVC when measured in PSNR.
Individual risk prediction and population-wide disease prevention.

Epidemiologists seem to be engaged in a ceaseless search for new risk factors for disease. An increasingly important consequence of this activity is the categorization of individuals according to personal disease risk. This search for risk factors is being conducted with the hope of more accurately isolating groups of high risk individuals; that is, the goal is to identify risk factors with high relative risks and with a correspondingly good ability to discriminate between diseased and nondiseased individuals. However, most known risk factors associated with chronic diseases (with the important exceptions of heavy smoking and certain occupational exposures, such as asbestos) have modest relative risks. At the individual level, most risk factors have poor discriminatory power, or poor positive predictive value. Some persons in the "low risk" or unexposed category will develop disease, while the majority of those who are exposed will remain healthy. One of the goals in the burgeoning field of genetic epidemiology is to extend the search for risk factors into the human genome, to uncover high risk individuals who were hitherto hidden within exposures defined by conventional lifestyle or environmental factors. Speculating on the future of genetic epidemiology, Feigelson et al. noted that "expanded knowledge in this area should lead to more refined definitions of 'high-risk' individuals. and, hopefully, lead us to be able to better define who may benefit from specific interventions based on underlying genetic susceptibility" (1, p. 20). In a similar vein, Khoury stated that "new gene discoveries, which occur on an almost daily basis, require that the public health community take a leadership role in translating the results of these dis-
Proper Reporting of Statistical Parameters in Clinical Trials Published in Indian Medical Journals. Is Inclusion of Statistician Play any Significant Role?

It is observed that the clinical trials published in various medical journals are poor in reporting of various methodological aspects, including sample size calculation and power. [1] It is difficult to generalize the results of clinical trials having poor reporting of statistics to the normal patient population and conducting these clinical trials raises ethical issues. [2] It is always advisable to take the help of a statistician both during the analysis of data and design of clinical trials. [3] Not associating a statistician while designing clinical trials is associated with the poor reporting of statistical parameters in clinical trials. [3] . Read more. ,
Sophie's World

Reviews: More praise for the international bestseller that has become “Europe’s oddball literary sensation of the decade” (New York Newsday) “A page-turner. ” —Entertainment Weekly “First, think of a beginner’s guide to philosophy, written by a schoolteacher . Next, imagine a fantasy novel— something like a modern-day version of Through the Looking Glass. Meld these disparate genres, and what do you get? Well, what you get is an improbable international bestseller . a runaway hit. [a] tour deforce. ” —Time
Towards efficient error detection in large-scale HPC systems

The need for computer systems to be reliable has increasingly become important as the dependence on their accurate functioning by users increases. The failure of these systems could very costly in terms of time and money. In as much as system's designers try to design fault-free systems, it is practically impossible to have such systems as different factors could affect them. In order to achieve system's reliability, fault tolerance methods are usually deployed; these methods help the system to produce acceptable results even in the presence of faults. Root cause analysis, a dependability method for which the causes of failures are diagnosed for the purpose of correction or prevention of future occurrence is less efficient. It is reactive and would not prevent the first failure from occurring. For this reason, methods with predictive capabilities are preferred; failure prediction methods are employed to predict the potential failures to enable preventive measures to be applied. Most of the predictive methods have been supervised, requiring accurate knowledge of the system's failures, errors and faults. However, with changing system components and system updates, supervised methods are ineffective. Error detection methods allows error patterns to be detected early to enable preventive methods to be applied. Performing this detection in an unsupervised way could be more effective as changes to systems or updates would less affect such a solution. In this thesis, we introduced an unsupervised approach to detecting error patterns in a system using its data. More specifically, the thesis investigates the use of both event logs and resource utilization data to detect error patterns. It addresses both the spatial and temporal aspects of achieving system dependability. The proposed unsupervised error detection method has been applied on real data from two different production systems. The results are positive; showing average detection F-measure of about 75%.
MashCache : Taming Flash Crowds by Using Their Good Features

This paper presents MashCache, a scalable client-side architecture for taming harsh effects of flash crowds. Like previous systems, MashCache extensively makes use of client resources to cache and share frequently accessed contents. To design MashCache, we carefully investigated the quantitative analysis of flash crowds in the wild and found out that flash crowds have three good features that can be used to simplify the overall design of MashCache. First, flash crowds start up very slowly. MashCache has enough time to prepare for the coming flash crowds. Second, flash crowds last for a short period. Since the accessed content is rarely updated in this short period, MashCache can employ a simple mechanism for cache consistency. Finally, the clients issue the same requests on the target web sites. This feature simplifies the cache management of MashCache because the cache explosion can be avoided. By using these good features of flash crowds, MashCache advances the state-of-the-art of P2P based caching systems for flash crowds; MashCache is a pure P2P system that combines 1) aggressive caching, 2) query-origin key, 3) two-phase delta consistency, and 4) carefully designed cache meta data. MashCache has another advantage. Since it works completely on client-side, MashCache can tolerate flash crowds even if the external services the mashup depends on are not equipped with flash-crowd-resistant mechanisms. In the experiments with up to 2,500 emulated clients, a prototype of MashCache reduces the number of requests to the original web servers by 98.2% with moderate overheads.
On the Industrial Applicability of Visual GUI Testing

There is constant pressure on the software development industry to improve software quality and deliver new and innovative software faster and more efficiently. These demands affect all aspects of software development, from requirements engineering to testing. Today, much testing is performed with costly, tedious and error-prone manual practices, especially on higher levels of system abstraction such as in system and acceptance testing. Increased test automation has been proposed as a key solution to help alleviate these test-related problems and has found increasing use. Automated tests typically consist of scripts that can be executed to give frequent feedback on the system's quality, ensure that previously correct functionality has not been negatively affected by changes, and also relieve resources e.g. human testers. However, as a system evolves, changes to the requirements also require maintenance of the tests, which can be costly. Furthermore, most automated test techniques approach testing from a lower level of system abstraction, e.g. testing the low-level components and functions, but their use for system testing has been questioned. Test techniques have been proposed that automate the interaction with the graphical user interface (GUI) of a system. For example, record and replay tools can be used to automate system testing by emulating a user interacting with the system. Existing literature have pointed out several shortcomings of these techniques, for example they are sensitive to GUI layout and code changes, require access to source code, are dependent on a specific platform or operating system access etc. In this thesis we evaluate if Visual GUI Testing (VGT), a novel technique that combines test scripts with image recognition, can be used to automate high-level, software testing. The strength of VGT lies in the use of image recognition that makes the technique robust in instances where previous GUIbased test techniques had limitations. Yet, VGT is only sparsely applied in industry and the academic body of knowledge on the technique is limited; there is a lack of empirical evaluation and experience reports from industrial use. To fill this gap in knowledge we have conducted three empirical case studies applying different VGT tools in industrial software projects at two Swedish companies. We have also conducted an industrial survey with participants from multiple companies. These studies provide evidence that VGT can be successfully applied in industrial software development projects, but also detail challenges, problems and limitations that need to be overcome for more widespread industrial adoption. Future work should focus on evaluating the long-term maintenance costs of VGT test scripts, since our studies only present initial evidence that these costs are manageable in relation to the benefits of the technique.