Miracle-dz/UniFAR-FTUs huggingface dataset:
Lower gastrointestinal symptoms are associated with worse glycemic control and quality of life in type 1 diabetes mellitus

Objectives Lower gastrointestinal symptoms are not well characterized in people with type 1 diabetes, and the effects on quality of life and glycemic control are unknown. This study aimed to determine the prevalence of lower gastrointestinal symptoms and the effects on glycemic control and quality of life, and to investigate for underlying causes. Research design and methods This is a prospective, cohort study in secondary care. Patients with type 1 diabetes completed a gastrointestinal symptom questionnaire and the Short Form 36 V.2 quality of life questionnaire and had their hemoglobin A1c measured. Patients with diarrhea were offered reassessment and investigation as per the national guidelines. Controls without diabetes were used to compare symptom prevalence and quality of life scores. Results 706 with type 1 diabetes (mean age 41.9 years) and 604 controls (mean age 41.9 years) were enrolled. Gastrointestinal symptoms were significantly more frequent in type 1 diabetes compared with controls, in particular constipation (OR 2.4), diarrhea (OR 2.5), alternating bowel habit (OR 2.1), abdominal pain (OR 1.4), floating stools (OR 2.7), bloating (OR 1.4) and flatulence (OR 1.3) (all p<0.05). Previous pancreatitis was more frequent in type 1 diabetes (OR 4.6), but other gastrointestinal conditions were not. Gastrointestinal symptoms were associated with poorer glycemic control (p<0.01) and worse quality of life particularly in those with diarrhea. Investigation of those with diarrhea, including those with alternating bowel habit, (n=105), identified a cause in 72.3% with subsequent change in management. Conclusions Gastrointestinal symptoms are twice as common in type 1 diabetes and associated with poorer quality of life and glycemic control. Investigation of diarrhea in people with type 1 diabetes leads to a high yield of treatable conditions and a change in management in about three-quarters.
Autoencoders for music sound synthesis: a comparison of linear, shallow, deep and variational models

This study investigates the use of non-linear unsupervised dimensionality reduction techniques to compress a music dataset into a low-dimensional representation, and its use for the synthesis of new sounds. We systematically compare (shallow) autoencoders (AE) and deep autoencoders (DAE) with principal component analysis (PCA) for representing the high-resolution short-term amplitude spectrum of a large and dense dataset of music notes into a lower-dimensional vector (and then convert it back to a synthetic amplitude spectrum used for sound resynthesis). In addition, we report results obtained with variational autoencoders (VAE) which to our knowledge have never been considered for processing musical sounds. Our experiments were conducted on the publicly available multi-instrument and multi-pitch database NSynth. Interestingly and contrary to the recent literature on image processing, they showed that PCA systematically outperforms shallow AE and that only a deep architecture (DAE) can lead to a lower reconstruction error. The optimization criterion in deep VAE being the sum of the reconstruction error and a regularization term, it naturally leads to a lower reconstruction accuracy than DAE but we show that VAEs are still able to outperform PCA while providing a low-dimensional latent space with nice "usability" properties.
Grassroots Initiatives as Sustainability Transition Pioneers: Implications and Lessons for Urban Food Systems

This review explores the current evidence on the role and success factors of grassroots initiatives in sustainability transitions, with special attention given to social innovations and the transformation of urban food systems, a field that is still rather scantly dealt with in literature compared to technological innovations in other sectors such as energy. In addition to their contributions to get the necessary transformation towards sustainable futures off the ground, the preconditions for grassroots initiatives to thrive are presented—as well as limitations regarding their possibilities and the challenges they face. Increasingly, the importance of civil society and social movements in facilitating societal transformation is recognized by both researchers and policy makers. Within their radical niches, grassroots initiatives do not have to adhere to the logics of the wider systems in which they are embedded. This allows them to experiment with diverse solutions to sustainability challenges such as local food security and sovereignty. By means of democratic, inclusive and participatory processes, they create new pathways and pilot a change of course. Nevertheless, upscaling often comes at the loss of the transformative potential of grassroots initiatives.
Activity of beavers as an ecological factor that affects the benthos of small rivers - a case study in the Żylica River (Poland)

The Eurasian beaver (Castor fiber) has a greater impact on local ecosystems than other herbivores, and the affected area exceeds the range of its presence. Its activity may change or create new habitats by modifying the availability of the biotic and abiotic resources available not only to beavers, but also to other groups of animals. Our aim was to study how beaver activity affects the benthos composition in a small river and in a beaver pond. The way in which beavers function in the case of small rivers has received little attention. The study showed a lower density of benthos above the dam (beaver pond - 1467 ind./m2) compared to the river (3147 ind./m2). Below the dam, the diversity of Trichoptera and Coleoptera was greater, while Diptera were more abundant in the beaver pond. Betidae were a constant component in the benthos assemblages and were most abundant in the beaver pond. Collectors-gatherers and predators were the most numerous in the beaver pond. Decreasing percentages of collectors-gatherers were observed with an increased abundance of collectors-filterers and shredders in the river. All of the ratio values except the P/T FFG (Predators to total of all other groups) were lower in the beaver pond compared to the river. The % EPT (Ephemeroptera Plecoptera and Trichoptera) was also greater in the beaver pond. Small differences in the physicochemical properties of the water and organic matter content in the bottom sediments were found both above and below the beaver dam.
Processing Multiple-User Location-Based Keyword Queries

Geosocial networking allows users to interact with respect to their current locations, which enables a group of users to determine where to meet. This calls for techniques that support processing of Multiple-user Location-based Keyword (MULK) queries, which return a set of Point-of-Interests (POIs) that are ’close’ to the locations of the users in a group and can provide them with potential options at the lowest expense (e.g., minimizing travel distance). In this paper, we formalize the MULK query and propose a dynamic programming-based algorithm to find the optimal result set. Further, we design two approximation algorithms to improve MULK query processing efficiency. The experimental evaluations show that our solutions are feasible and efficient under various parameter settings. key words: multiple-user location-based query, location-based keyword query, query processing
The Association Between Dietary Quality and Overall and Cancer-Specific Mortality Among Cancer Survivors, NHANES III

Abstract Given the recent emphasis on the totality of the diet by national guidelines, we examined the relationship between the quality of diet and overall and cancer-specific mortality among cancer survivors. From the Third National Health and Nutrition Examination Survey (NHANES III), 1191 participants diagnosed with cancer were identified. Healthy Eating Index (HEI) scores were utilized; higher HEI score indicated better adherence to dietary recommendations. During a median follow-up of 17.2 years, a total of 607 cancer-specific deaths occurred. A high-quality diet (highest-quartile HEI score) was associated with decreased risk of overall (hazard ratio [HR] = 0.59, 95% confidence interval [CI] = 0.45 to 0.77) and cancer-specific (HR = 0.35, 95% CI = 0.19 to 0.63) mortality when compared with a poor-quality diet (lowest-quartile HEI score). Among individual dietary components, the highest-quartile score for saturated fat intake was associated decreased cancer-specific mortality (HR = 0.55, 95% CI = 0.36 to 0.86). Our results highlight the importance of a “total diet” approach to improving survival among cancer patients.
Optimizing sequential decisions in the drift-diffusion model

To make decisions organisms often accumulate information across multiple timescales. However, most experimental and modeling studies of decision-making focus on sequences of independent trials. On the other hand, natural environments are characterized by long temporal correlations, and evidence used to make a present choice is often relevant to future decisions. To understand decision-making under these conditions we analyze how a model ideal observer accumulates evidence to freely make choices across a sequence of correlated trials. We use principles of probabilistic inference to show that an ideal observer incorporates information obtained on one trial as an initial bias on the next. This bias decreases the time, but not the accuracy of the next decision. Furthermore, in finite sequences of trials the rate of reward is maximized when the observer deliberates longer for early decisions, but responds more quickly towards the end of the sequence. Our model also explains experimentally observed patterns in decision times and choices, thus providing a mathematically principled foundation for evidence-accumulation models of sequential decisions.
Learning to Estimate Indoor Lighting from 3D Objects

In this work, we propose a step towards a more accurate prediction of the environment light given a single picture of a known object. To achieve this, we develop a deep learning method that is able to encode the latent space of indoor lighting using few parameters that is trained on a database of environment maps. This latent space is then used to generate predictions of the light that are both more realistic and accurate than previous methods. Our first contribution is a deep autoencoder which is capable of learning the feature space that compactly models lighting. Our second contribution is a convolutional neural network that predicts the light from a single image of a known object. To train these networks, our third contribution is a novel dataset that contains 21,000 HDR indoor environment maps. Finally, we evaluate our method on a dataset of synthetic objects and find it to outperform the state-of-the-art techniques across a variety of materials and poses.
Background Subtraction for Moving Object Detection in RGBD Data: A Survey

The paper provides a specific perspective view on background subtraction for moving object detection, as a building block for many computer vision applications, being the first relevant step for subsequent recognition, classification, and activity analysis tasks. Since color information is not sufficient for dealing with problems like light switches or local gradual changes of illumination, shadows cast by the foreground objects, and color camouflage, new information needs to be caught to deal with these issues. Depth synchronized information acquired by low-cost RGBD sensors is considered in this paper to give evidence about which issues can be solved, but also to highlight new challenges and design opportunities in several applications and research areas.
Polyhedral auto-transformation with no integer linear programming

State-of-the-art algorithms used in automatic polyhedral transformation for parallelization and locality optimization typically rely on Integer Linear Programming (ILP). This poses a scalability issue when scaling to tens or hundreds of statements, and may be disconcerting in production compiler settings. In this work, we consider relaxing integrality in the ILP formulation of the Pluto algorithm, a popular algorithm used to find good affine transformations. We show that the rational solutions obtained from the relaxed LP formulation can easily be scaled to valid integral ones to obtain desired solutions, although with some caveats. We first present formal results connecting the solution of the relaxed LP to the original Pluto ILP. We then show that there are difficulties in realizing the above theoretical results in practice, and propose an alternate approach to overcome those while still leveraging linear programming. Our new approach obtains dramatic compile-time speedups for a range of large benchmarks. While achieving these compile-time improvements, we show that the performance of the transformed code is not sacrificed. Our approach to automatic transformation provides a mean compilation time improvement of 5.6× over state-of-the-art on relevant challenging benchmarks from the NAS PB, SPEC CPU 2006, and PolyBench suites. We also came across situations where prior frameworks failed to find a transformation in a reasonable amount of time, while our new approach did so instantaneously.
Examining the anatomy of last-mile distribution in e-commerce omnichannel retailing: A supply network configuration approach

Purpose The purpose of this paper is to investigate the interplay between configuration dimensions (network structure, network flow, relationship governance, and service architecture) of last-mile supply networks (LMSN) and the underlying mechanisms influencing omnichannel performance. Design/methodology/approach Based on mixed-method design incorporating a multiple embedded case study, mapping, survey, and archival records, this research involved undertaking in-depth within- and cross-case analyses to examine seven LMSNs, employing a configuration approach. Findings The existing literature in the operations management (OM) field was shown to provide limited understanding of LMSNs within the emerging omnichannel context. Case results suggest that particular configurations have intrinsic capabilities, and that these directly influence omnichannel performance. The study further proposes a taxonomy of LMSNs comprising six forms, with two hybrids, supporting the notion of equifinality in configuration theory. Propositions are developed to further explore interdependencies between configurational attributes, refining the relationship between LMSN types, and factors influencing omnichannel performance. Practical implications The findings provide retailers with a set of design parameters for the (re)configuration of LMSNs and facilitate performance evaluation using the concept of fit between configurational attributes. The developed model sheds light on the consequential effects when certain configurational attributes are altered, preempting managerial attention. Given the global trend in urbanization, improved LMSN performance would have positive societal impacts in terms of service and resource efficiency. Originality/value This is one of the first studies in the OM field to critically analyze LMSNs and their behaviors in omnichannel retailing. Additionally, the paper offers several important avenues for future research.
Eficiencia relativa en el servicio de distribución eléctrica en el Perú durante el período 1997-2000: un estudio de fronteras

Se desarrolla un conjunto de medidas de eficiencia, aplicando el metodo de analisis de fronteras, para comparar el desempeno de las empresas de distribucion electrica que operan en el Peru, tanto las que ya han sido privatizadas como las que aun permanecen en manos del Estado.
Numerical investigation of industrial continuous digesters

Digesters, either of batch or continuous type, are large chemical cooking vessels used to convert wood chips into fiber solution or pulp, from which paper products are eventually produced. In the continuous digesters, the complex liquor flow, which usually has a number of circulation loops, interacts with the downward moving wood chips through mass, momentum, and energy exchanges and therefore has a major effect on the chip motion and the cooking reactions. A set of comprehensive differential equations governing the two-phase flow, heat transfer, and chemical reaction is developed, with the purpose of computationally investigating the cooking process in continuous digesters. A new cooking reaction model is also derived, based on extensive experimental data. To model the chip phase motion, the chip phase is assumed to be a non-Newtonian fluid with a slip boundary condition on the digester walls. A number of sub-models are examined and used to account for the compressibility of chip column and the inter-phase friction force. Based on the governing equations and mathematical models, a general two-phase three-dimensional CFD code has been developed to calculate the flow fields for both phases, solid fraction, temperature, and the concentrations of chemicals. The developed CFD code also has the capability of solving many other potential multiphase reactive flow problems. Liquid flow in a laboratory digester filled with compacted chips is simulated by the developed code. The computations compare reasonably well with the experimental observations by ERT (Electrical Resistance Tomography). Currently, the code cannot predict the tracer motion. Therefore detailed comparison between CFD simulation and ERT images cannot be made. Simulations are also performed in a full-scale industrial digester. The predictions of yield and kappa number at the digester exit are accurate for various cooking conditions. The distributions of pressure and chip phase volume fraction are discussed, the chip
'score to Door Time', a Benchmarking Tool for Rapid Response Systems: a Pilot Multi-centre Service Evaluation

Introduction: Rapid Response Systems were created to minimise delays in recognition and treatment of deteriorating patients on general wards. Physiological 'track and trigger' systems are used to alert a team with critical care skills to stabilise patients and expedite admission to intensive care units. No benchmarking tool exists to facilitate comparison for quality assurance. This study was designed to create and test a tool to analyse the efficiency of intensive care admission processes. Methods: We conducted a pilot multicentre service evaluation of patients admitted to 17 intensive care units from the United Kingdom, Ireland, Denmark, United States of America and Australia. Physiological abnormalities were recorded via a standardised track and trigger score (VitalPAC™ Early Warning Score). The period between the time of initial physiological abnormality (Score) and admission to intensive care (Door) was recorded as 'Score to Door Time'. Participants subsequently suggested causes for admission delays. Results: Score to Door Time for 177 admissions was a median of 4:10 hours (interquartile range (IQR) 1:49 to 9:10). Time from physiological trigger to activation of a Rapid Response System was a median 0:47 hours (IQR 0:00 to 2:15). Time from call-out to intensive care admission was a median of 2:45 hours (IQR 1:19 to 6:32). A total of 127 (71%) admissions were deemed to have been delayed. Stepwise linear regression analysis yielded three significant predictors of longer Score to Door Time: being treated in a British centre, higher Acute Physiology and Chronic Health Evaluation (APACHE) II score and increasing age. Binary regression analysis demonstrated a significant association (P < 0.045) of APACHE II scores >20 with Score to Door Times greater than the median 4:10 hours. Conclusions: Score to Door Time seemed to be largely independent of illness severity and, when combined with qualitative feedback from centres, suggests that admission delays could be due to organisational issues, rather than patient factors. Score to Door Time could act as a suitable benchmarking tool for Rapid Response Systems and helps to delineate avoidable organisational delays in the care of patients at risk of catastrophic deterioration.
La ola de calor de agosto de 2003 en Navarra

The first fortnight of august, there was a strong heat wave that has been unique in the series of available records, due to its intensity and length. This article has as its aim to study such period, in order to know its climatic causes and features in the different areas of Navarre. To do so, we have analysed data provided by manual and automatic stations of Navarre which are well spread over the community.
Project-as-Practice: In Search of Project Management Research that Matters

Research on projects is not only an immature field of research, but it is also insubstantial when it comes to understanding what occurs in projects. This article contributes to making project management research matter to the academic as well as to the practitioner by developing a project-as-practice approach, in alignment with the ongoing debate in social science research. The article outlines a framework and argues that there are two major challenges to the researcher and also suggests how these challenges can be met. Underlying notions of the practice approach are outlined to ensure a development of the project-as-practice approach that makes project management research matter!
Leadership Skills Development for Engineers

Abstract: Leadership must be a key element advancing for the engineering profession to remain relevant and connected in an era of heightened outsourcing and global competition. Companies intent on maintaining a competitive edge are calling upon educators to produce engineers capable of leading multidisciplinary teams, combine technical ingenuity with business acumen, and produce graduates who have a passion for lifelong learning. Industry is also challenging universities to broaden curricula beyond the intellectual endeavors of design and scientific inquiry to the greater domain of professional leadership and entrepreneurship. Managers in industry are similarly challenged to cultivate key leadership attributes in junior engineers. This article explores the changing nature of engineering in a globally competitive environment and addresses why leadership must become a key issue in the career progression of engineers. We will present a literature review of leadership models along with some proposed solutions for cultivating leadership skills as part of the career development process. Lastly, we will present specific recommendations on how to cultivate leadership attributes throughout an engineering career.
The canonical solution operator to ∂ restricted to spaces of entire functions

Dans cet article, nous etudions l'operateur canonique de solution du ∂ dans les espaces L 2 (C n ,e -p ) a poids et discutons de ses proprietes de compacite et d'etre de Hilbert-Schmidt. Dans le cas d'une seule variable complexe, nous montrons que cet operateur solution n'est pas compact dans L 2 (C,e-|z| 2 ) meme si on se restreint au sous-espace correspondant de fonctions entieres. L'operateur solution est compact quand on le restreint au sous-espace des fonctions entieres pour les poids e -|z|m , m > 2, mais n'est pas Hilbert-Schmidt. Dans la seconde partie, nous montrons que, dans un contexte legerement different, nous obtenons la propriete d'etre de type Hilbert-Schmidt pour une classe tres large d'espaces a poids de fonctions entieres de plusieurs variables complexes.
Religion and Economic Performance

Studies on religion and economy have attract many researchers. This paper is aim to observe how religion influence economy by seeing from microeconomic and Islamic perspective. Moreover, it elaborates the role of religion for economic performance. The finding indicates that social phenomena in the community can be understood by seeing the individual behavior as part of microeconomic level. Individual consumer sees religious expression as an economic good that must compete with other goods. While from Islamic perspective, economic activities should provide a better concept according to the Quran, Sunnah and hadith. Religion has a role to enhance economy by shaping individual values and attitudes particularly in terms honesty, work ethic and trust.