Miracle-dz/UniFAR-FTUs huggingface dataset:
Switching From Glargine to Degludec: The Effect on Metabolic Control and Safety During 1-Year of Real Clinical Practice in Children and Adolescents With Type 1 Diabetes

Background/Objective: Insulin degludec (IDeg) is an ultra-long-acting analog with less daily variability compared to other basal insulins. In this retrospective study we examined 1-year efficacy and safety of IDeg in youth with type 1 diabetes (T1D). Subjects/Methods: Thirty-seven patients [11.7 ± 4.22 years; T1D duration 4.97 ± 3.63 years; once-daily glargine (IGlar) by at least 1 year] were switched to once-daily IDeg because of glycosylated hemoglobin (HbA1c) >7.5% and/or reported physical pain at IGlar injection. Changes in HbA1c, 30-day mean fasting plasma glucose (mean FPG), daily insulin dose, and severe hypoglycemia rates were collected at basal insulin switch (T0), 3-months (T1), 6-months (T2), and 12-months (T3) after IDeg was started. Results: In patients with HbA1c >7.5% at T0 we found a decrease in HbA1c values (%) from 8.46 ± 0.53 to 7.89 ± 0.72 at T1 (p = 0.008) and 7.97 ± 0.89 at T2 (p = 0.035). At T3, 38.9% of patients had HbA1c ≤ 7.5%. Mean FPG levels significantly decreased at T2 (p = 0.043). In the overall study population, we documented an increase in IDeg dose (+12.5% at T3; p < 0.001) and a decrease in mealtime insulin dose (−11.6% at T3; p = 0.001) after switch. HbA1c levels were unchanged. No episode of severe hypoglycemia was reported. Conclusions: Our data in children and adolescents with T1D suggest that IDeg dose should be increased by 12% and mealtime insulin doses should be lowered by 11% for patients who previously received IGlar. IDeg might be considered useful and well tolerated and it seems to improve the glycemic control compared to IGlar, mainly in patients with poor glycemic control.
PrivLBS: uma Abordagem para Preservação de Privacidade de Dados em Serviços baseados em Localização

Serviços baseados em localização têm sido integrados às atividades diárias das pessoas. Entretanto, alguns desses serviços podem não ser confiáveis e levar a sérios riscos de violação de privacidade. Este trabalho propõe uma nova técnica de preservação de privacidade de dados, denominada PrivLBS, capaz de assegurar que as localizações dos indivíduos não serão facilmente reidentificadas por serviços mal intencionados. Resultados de avaliação experimental demonstram que, para ataques baseados em distância euclidiana, a probabilidade de reidentificação das localizações de um indivíduo, após utilização do PrivLBS, é em torno de 11.4%, enquanto que, em trabalhos já existentes na literatura, essa probabilidade chega a 59.2%.
Surfacing the arctic: politics of participation in infrastructuring

The1 ongoing adoption of sensor networks, algorithms, and digital data comes with the promise of opening up participation in knowledge production. However, the dynamics of the participatory design (PD) processes in these infrastructuring endeavors remain underspecified. This short paper draws on a study of an oil company's project to design an open digital platform to produce knowledge about the Arctic marine environment. Fraught with political controversies, this effort encompasses several stakeholders with contrasting agendas. Leveraging the relational quality of infrastructure, we propose to revitalize the political roots of PD by problematizing simultaneously the roles of human and non-human participants, foregrounding both digital technology and the monitored natural ecosystems. We discuss how infrastructuring aimed at letting humans visualize the inaccessible, also shapes participation by creating spaces of (in)visibility and concentrating control over knowledge creation in the hands of the most powerful stakeholders.
Intravenous Vitamin C for Cancer Therapy – Identifying the Current Gaps in Our Knowledge

The use of intravenous vitamin C (IVC) for cancer therapy has long been an area of intense controversy. Despite this, high dose IVC has been administered for decades by complementary health care practitioners and physicians, with little evidence base resulting in inconsistent clinical practice. In this review we pose a series of questions of relevance to both researchers and clinicians, and also patients themselves, in order to identify current gaps in our knowledge. These questions include: Do oncology patients have compromised vitamin C status? Is intravenous the optimal route of vitamin C administration? Is IVC safe? Does IVC interfere with chemotherapy or radiotherapy? Does IVC decrease the toxic side effects of chemotherapy and improve quality of life? What are the relevant mechanisms of action of IVC? What are the optimal doses, frequency, and duration of IVC therapy? Researchers have made massive strides over the last 20 years and have addressed many of these important aspects, such as the best route for administration, safety, interactions with chemotherapy, quality of life, and potential mechanisms of action. However, we still do not know the answers to a number of fundamental questions around best clinical practice, such as how much, how often and for how long to administer IVC to oncology patients. These questions point the way forward for both basic research and future clinical trials.
Multi-Array 5G V2V Relative Positioning: Performance Bounds

We study the performance bounds of vehicle-to-vehicle (V2V) relative positioning for vehicles with multiple antenna arrays. The Cramér-Rao bound for the estimtion of the relative position and the orientation of the Tx vehicle is derived, when angle of arrival (AOA) measurements with or without time-difference of arrival (TDOA) measurements are used. In addition, geometrically intuitive expressions for the corresponding Fisher information are provided. The derived bounds are numerically evaluated for different carrier frequencies, bandwidths and array configurations under different V2V scenarios, i.e. overtaking and platooning. The significance of the AOA and TDOA measurements for position estimation is investigated. The achievable positioning accuracy is then compared with the present requirements of the 3rd Generation Partnership Project (3GPP) 5G New Radio (NR) vehicle-to-everything (V2X) standardization.
Multimodal Assessment of Parkinson's Disease: A Deep Learning Approach

Parkinson's disease is a neurodegenerative disorder characterized by a variety of motor symptoms. Particularly, difficulties to start/stop movements have been observed in patients. From a technical/diagnostic point of view, these movement changes can be assessed by modeling the transitions between voiced and unvoiced segments in speech, the movement when the patient starts or stops a new stroke in handwriting, or the movement when the patient starts or stops the walking process. This study proposes a methodology to model such difficulties to start or to stop movements considering information from speech, handwriting, and gait. We used those transitions to train convolutional neural networks to classify patients and healthy subjects. The neurological state of the patients was also evaluated according to different stages of the disease (initial, intermediate, and advanced). In addition, we evaluated the robustness of the proposed approach when considering speech signals in three different languages: Spanish, German, and Czech. According to the results, the fusion of information from the three modalities is highly accurate to classify patients and healthy subjects, and it shows to be suitable to assess the neurological state of the patients in several stages of the disease. We also aimed to interpret the feature maps obtained from the deep learning architectures with respect to the presence or absence of the disease and the neurological state of the patients. As far as we know, this is one of the first works that considers multimodal information to assess Parkinson's disease following a deep learning approach.
Periodontitis and platelet count: A new potential link with cardiovascular and other systemic inflammatory diseases

AIM As an infection-driven inflammatory disease, periodontitis could lead to a reactive increase in platelet count. This mechanism could partially mediate the well-documented association between periodontitis and atherosclerotic cardiovascular disease. The aim of this cross-sectional study was to test the presence of an association between periodontitis and platelet count in a representative sample of the South Korea population. MATERIALS AND METHODS A total of 5,197 subjects representative of 34.9 million of adults were examined. Multivariate regression analyses were applied controlling for age, gender, smoking status, educational level, body mass index, alcoholism, diabetes and hypertension status, vitamin D serum levels and total cholesterol, triglycerides, HDL and LDL blood levels. RESULTS Compared to the non-severe periodontitis group, subjects with severe periodontitis (CPI = 4) displayed 13,048.93 more platelets for μl of blood (95% CI: 3,296.26-22,801.61, p = 0.009) in the fully-adjusted model. The association between severe periodontitis and platelet count has shown to be highlighted in subjects aged more than 60 years, females, non-smokers and with normal HDL blood levels. A systemic inflammatory biomarker (white blood cell count) explained the 19.25% of this association. CONCLUSIONS Within the limitations of this study, periodontitis-especially severe-is independently associated with a considerable increase in platelet count which is explained, at least in part, by an increase in the systemic inflammation.
Avoiding bias in robot speech

speak to one of these systems today, it is most likely that another human has literally and quite mechanically typed out the words that the AI is saying back to you. The “intelligence” here is in understanding what we are saying, and in matching our words to a set of possible intents. The responses are “dumb” in the sense that they are not generated dynamically: They are scripted beforehand by a human. A little bit closer to artificial intelligence are systems that use machine learning to train themselves on huge corpora of text in order to “understand” the meaning of words, the different contexts in which those words can be used, and the syntax that can be used to order those words. Then, based upon this understanding, they answer our questions in a variety of contexts. Here, it is our questions that are more heavily scripted and We humans are teaching our robots how to speak. But when humans speak to each other, we can be pretty terrible. The words we use express our biases and prejudices, our stereotypes about each other, and the inequalities of our society. Do we want our robots to replicate all of that? Or should we hold them to a higher standard? If the latter, is there any chance that they can teach us, over time, to be better people? We are at a middle point in AI speech development, where the computers are speaking to us in two different ways. In consumer-oriented digital assistants, natural language processing has developed enough for them to convert human speech to text with high accuracy. Statistical methods match that text to probable intents and the systems return programmed responses. This describes what’s happening with chatbots, and with Insights → Bias and stereotypes are embedded in everyday language in ways that most people don’t realize. → At this stage in chatbot and Alexa-type AI development, designers have a lot of control over the language that AIs use with customers. → If we train our AIs to use unbiased language, they might one day take on the role of identifying and moderating bias in humans’ everyday language. Avoiding Bias in Robot Speech Charles Hannon, Washington & Jefferson College
Beefing Up Biosecurity: Survey of Ticks (Acari: Ixodidae) Currently Threatening the Tennessee Beef Cattle Industry, and a Proposed Monitoring Strategy for Invasive Ticks

Abstract Tick-borne diseases are poised to devastate the North American cattle industry if infected ticks invade the country either by importation of an infested-animal or with natural host migration. Our research objectives were to identify sources for invasive-tick monitoring and use those sources to describe seasonal and regional impacts on infestation prevalence and burden of ticks on beef cattle.Throughout the state of Tennessee, we sampled 25% of the total herd size (or 10 animals) at three university-operated research and education centers (RECs) (sentinel sites), six livestock auctions (check-stations), and nine Extension agents at 21 producer locations (tick scouts) from 2015 to 2016. From 1,817 sampled cattle 740 ticks (Acari: Ixodidae) were collected including 573 Amblyomma americanum (L.) (77.4%), 125 A. maculatum Koch (16.9%), 35 Dermacentor variabilis (Say) (4.7%), and 3 Ixodes scapularis (Say) (0.4%). Western and middle Tennessee were significantly different in infestation prevalence and burden of A. maculatum. For A. maculatum and the species total, infestation prevalence and burden were greater in spring than fall. Auctions (check stations) and RECs (sentinels) had the greatest infestation prevalence of A. maculatum, and the greatest burden of A. maculatum and D. variabilis. High-risk locations clustered in western and middle Tennessee, with low-risk locations in middle and easternTennessee. Results from this study provide knowledge necessary to initiate control measures, including seasonal phenology and regional distribution of current tick threats. Use of RECs as sentinel sites and routine tick surveillance at livestock auctions serving as check stations should be used for mitigating invasive tick threats.
Cultural Effects Rather Than a Bilingual Advantage in Cognition: A Review and an Empirical Study

The bilingual advantage hypothesis contends that the management of two languages in the brain is carried out through domain-general mechanisms, and that bilinguals possess a performance advantage over monolinguals on (nonlinguistic) tasks that tap these processes. Presently, there is evidence both for and against such an advantage. Interestingly, the evidence in favor has been thought strongest in children and older adults, leading some researchers to argue that young adults might be at peak performance levels, and therefore bilingualism is unable to confer an improvement. We conducted a large-scale review of the extant literature and found that the weight of research pointed to an absence of positive evidence for a bilingual advantage at any age. We next gave a large number of young adult participants a task designed to test the bilingual advantage hypothesis. Reasoning from the literature that young adults from an East Asian (Korean) culture would likely outperform those from a Western (British) culture, we also compared participants on this factor. We found no evidence for a bilingual advantage but did find evidence for enhanced performance in the Korean group. We interpret these results as further evidence against the bilingual advantage hypotheses.
NFAT5 Isoform C Controls Biomechanical Stress Responses of Vascular Smooth Muscle Cells

Vascular cells are continuously exposed to mechanical stress that may wreak havoc if exceeding physiological levels. Consequently, mechanisms facing such a challenge are indispensable and contribute to the adaptation of the cellular phenotype. To this end, vascular smooth muscle cells (VSMCs) activate mechanoresponsive transcription factors promoting their proliferation and migration to initiate remodeling the arterial wall. In mechanostimulated VSMCs, we identified nuclear factor of activated T-cells 5 (NFAT5) as transcriptional regulator protein and intended to unravel mechanisms controlling its expression and nuclear translocation. In cultured human VSMCs, blocking RNA synthesis diminished both baseline and stretch-induced NFAT5 mRNA expression while inhibition of the proteasome promoted accumulation of the NFAT5 protein. Detailed PCR analyses indicated a decrease in expression of NFAT5 isoform A and an increase in isoform C in mechanoactivated VSMCs. Upon overexpression, only NFAT5c was capable to enter the nucleus in control- and stretch-stimulated VSMCs. As evidenced by analyses of NFAT5c mutants, nuclear translocation required palmitoylation, phosphorylation at Y143 and was inhibited by phosphorylation at S1197. On the functional level, overexpression of NFAT5c forces its accumulation in the nucleus as well as transcriptional activity and stimulated VSMC proliferation and migration. These findings suggest that NFAT5 is continuously expressed and degraded in resting VSMCs while expression and accumulation of isoform C in the nucleus is facilitated during biomechanical stress to promote an activated VSMC phenotype.
Data objects for hasselt elections

Design-led activism seeks to create a counter-narrative to motivate social, institutional, environmental or economic change. This `Situated Action' proposes to do design-led activism in the cities of Hasselt and Genk using Data Objects - a new type of physical and functional object whose form and function encodes data to aid decision making. A series of objects which encode data will be designed and deployed in Z33 with the support of city representatives. The intention is to support voter deliberation and decision making in the 2018 regional election.
High-Fat Diet and Alcohol Intake Promotes Inflammation and Impairs Skin Wound Healing in Wistar Rats

The wound-healing process is complex and remains a challenging process under the influence of several factors, including eating habits. As improper diets may lead to disorders such as dyslipidemia, insulin resistance, and chronic inflammation, potentially affecting the tissue ability to heal, we decided to investigate the effect of a high-fat diet and alcohol intake on the inflammatory process and skin wound healing in Wistar rats. Male rats (n = 30) were individually housed in cages with food and water ad libitum (registration number 213/2014). After anesthesia, at day 40, three circular wounds (12 mm diameter) were made on the back of each animal, which were then randomly assorted into five treatment groups: C1 (control 1)—water via gavage and standard chow diet; C2 (control 2)—water (no gavage) and standard chow diet; AL (alcohol)—water (no gavage) and alcohol (40%) via gavage and standard chow diet; HF (high fat)—water (no gavage) and high-fat diet (50%); and HF + AL (alcohol/high fat)—water (no gavage), alcohol (40%) via gavage, and high-fat diet. Animals were treated for 61 days. Every seven days, the area and the rate of wound contraction were evaluated. Tissue samples were removed for histopathological analysis and biochemical analyses. Our results showed that wound contraction was not complete in the HF + AL rats. Two specific indices of wound-healing impairment (total cell number and levels of the inflammatory cytokine TGF-β) were increased in the HF + AL rats. We also observed decreased type I and III collagen fibers in the HF, AL, and HF + AL groups and increased oxidative stress markers in the same groups. We suggest that a high-fat diet combined with alcohol intake contributed to delayed skin wound healing through increase of the inflammatory phase and promoting oxidative stress, which may have led to morphological alterations and impaired matrix remodeling.
On Adopting Linters to Deal with Performance Concerns in Android Apps

With millions of applications (apps) distributed through mobile markets, engaging and retaining end-users challenge Android developers to deliver a nearly perfect user experience. As mobile apps run in resource-limited devices, performance is a critical criterion for the quality of experience. Therefore, developers are expected to pay much attention to limit performance bad practices. On the one hand, many studies already identified such performance bad practices and showed that they can heavily impact app performance. Hence, many static analysers, a.k. a. linters, have been proposed to detect and fix these bad practices. On the other hand, other studies have shown that Android developers tend to deal with performance reactively and they rarely build on linters to detect and fix performance bad practices. In this paper, we therefore perform a qualitative study to investigate this gap between research and development community. In particular, we performed interviews with 14 experienced Android developers to identify the perceived benefits and constraints of using linters to identify performance bad practices in Android apps. Our observations can have a direct impact on developers and the research community. Specifically, we describe why and how developers leverage static source code analysers to improve the performance of their apps. On top of that, we bring to light important challenges faced by developers when it comes to adopting static analysis for performance purposes.
Towards Automating Disambiguation of Regulations: Using the Wisdom of Crowds

Compliant software is a critical need of all modern businesses. Disambiguating regulations to derive requirements is therefore an important software engineering activity. Regulations however are ridden with ambiguities that make their comprehension a challenge, seemingly surmountable only by legal experts. Since legal experts' involvement in every project is expensive, approaches to automate the disambiguation need to be explored. These approaches however require a large amount of annotated data. Collecting data exclusively from experts is not a scalable and affordable solution. In this paper, we present the results of a crowd sourcing experiment to collect annotations on ambiguities in regulations from professional software engineers. We discuss an approach to automate the arduous and critical step of identifying ground truth labels by employing crowd consensus using Expectation Maximization (EM). We demonstrate that the annotations reaching a consensus match those of experts with an accuracy of 87%.
Correlation of neurochemical and imaging markers in migraine

Objective To examine whether interictal plasma pituitary adenylate cyclase-activating peptide 38-like immunoreactivity (PACAP38-LI) shows correlation with the microstructural integrity of the white matter in migraine. Methods Interictal plasma PACAP38-LI was measured by radioimmunoassay in 26 patients with migraine (24 women) who underwent diffusion tensor imaging afterward using a 1.5-tesla magnetic resonance scanner. Data were analyzed using tract-based spatial statistics included in FMRIB's Software Library. Results Interictal plasma PACAP38-LI showed significant correlation with mean diffusivity (p < 0.0179) mostly in the bilateral occipital white matter spreading into parietal and temporal white matter. Axial and radial diffusivity showed positive correlation with interictal PACAP38-LI (p < 0.0432 and p < 0.0418, respectively) in the left optic radiation and left posterior corpus callosum. Fractional anisotropy did not correlate significantly with PACAP38-LI. With disease duration as a nuisance regressor in the model, PACAP38-LI correlated with axial and mean diffusivity in the left thalamus (p < 0.01). Conclusion We report a link between PACAP38, a pathobiologically important neurochemical biomarker, and imaging markers of the disease that may bolster further research into the role of PACAP38 in migraine.