Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationship between Serum Soluble Klotho Protein and Coronary Artery Calcification and Prognosis in Patients on Maintenance Hemodialysis

Background: We aimed to investigate the relationship between serum soluble Klotho protein (sKlotho) level and coronary artery calcification (CAC) as well as prognosis in patients with maintenance hemodialysis (MHD). Methods: Overall, 128 adult patients with end-stage renal failure treated with MHD were collected in the Second Affiliated Hospital & Yuying Children’s Hospital of Wenzhou Medical University, Zhejiang Province, China in 2013. Serum sKlotho was detected by ELISA and coronary artery calcification was measured by multi-slice spiral computed tomography (MSCT). With 36 months’ follow-up, death notes such as cause of death and death time were recorded. Results: Patients were divided into low sKlotho group and high sKlotho group. Age, blood phosphorus level, hypertension incidence and incidence of diabetes mellitus of the patients in low sKlotho group was significantly higher than that of high sKlotho group (P<0.05). The coronary artery calcification score (CACs) of patients in high sKlotho group was significantly lower than that of low sKlotho group (P<0.001). Logistic regression showed that the decrease of sKlotho level (P<0.001) was an independent risk factor for CAC progression. The mortality of the patients in low sKlotho group was higher than that of high sKlotho group. Kaplan-Meier survival curve had shown that survival time of the patients in low sKlotho group was significantly lower than that of high sKlotho group (P<0.05). Conclusion: SKlotho can increase the degree of CAC. Although MHD patients with low sKlotho level had shorter survival time, sKlotho is not an independent risk factor in prediction of prognosis of MHD patients.
Healthcare utilisation and expenditure of overweight and non-overweight children

Background Quantification of the burden of overweight on the healthcare system is becoming increasingly urgent for health policy, but accurate estimates are hard to obtain. Methods In order to assess healthcare utilisation and expenditure of overweight and non-overweight children, we linked, on an individual basis, data on body mass index from a birth cohort study with administrative health insurance claims data. In children aged 14–15 years, we compared utilisation and expenditure on general practice care, dental care, hospital/specialist care, prescribed medication, allied healthcare and mental healthcare of overweight children (overweight at age 11 and 14, n=80) and non-overweight children (no overweight at age 11 and 14, n=1253). Results For overweight children, mean 1-year healthcare expenditure was €837 per child and for non-overweight children €616. This difference was mainly due to significant differences in utilisation of hospital care (49% vs 37%) and mental healthcare (14% vs 7%) and to a lesser extent to higher expenditure per user. Conclusion Our results indicate the potential value of linking survey data to claims data in order to obtain insight into the healthcare costs of childhood overweight. Further studies should elucidate whether the observed differences are causally related to overweight.
Effect of environmental changes on vegetable and legume yields and nutritional quality

Significance Environmental changes, including climate change, air pollution, and water scarcity and salinization, threaten global agricultural production, food security, and health. There is evidence that environmental change will reduce the yields of starchy staple crops, but impacts on (nonstaple) vegetables and legumes—important constituents of healthy diets—remain largely unknown. We systematically reviewed the available published evidence from experimental studies on the impact of environmental changes on yields and nutritional quality of (nonstaple) vegetables and legumes and found that environmental change would have a negative impact on yields without suitable responses from the agricultural sector. An enhanced understanding of the scale of environmental impacts on agricultural production is essential for the development of effective strategies to protect global population health. Environmental changes threaten agricultural production, food security, and health. Previous reviews suggest that environmental changes will substantially affect future yields of starchy dietary staples. To date, no comprehensive global analysis of the impacts of environmental change on (nonstaple) vegetables and legumes—important constituents of healthy diets—has been reported. We systematically searched for articles published between 1975 and 2016 on the effects of ambient temperature, tropospheric carbon dioxide (CO2), and ozone (O3) concentrations, water availability, and salinization on yields and nutritional quality of vegetables and legumes. We estimated mean effects of standardized environmental changes using observed exposure-response relationships and conducted meta-analyses where possible. We identified 174 relevant papers reporting 1,540 experiments. The mean (95% CI) reported yield changes for all vegetables and legumes combined were +22.0% (+11.6% to +32.5%) for a 250-ppm increase in CO2 concentration, −8.9% (−15.6% to −2.2%) for a 25% increase in O3 concentration,−34.7% (−44.6% to −24.9%) for a 50% reduction in water availability, and −2.3% (−3.7% to −0.9%) for a 25% increase in salinity. In papers with baseline temperatures >20 °C, a 4 °C increase in temperature reduced mean yields by −31.5% (−41.4% to −21.5%). Impacts of environmental changes on nutritional quality were mixed. In a business-as-usual scenario, predicted changes in environmental exposures would lead to reductions in yields of nonstaple vegetables and legumes. Where adaptation possibilities are limited, this may substantially change their global availability, affordability, and consumption in the mid to long term. Our results stress the importance of prioritizing agricultural developments, to minimize potential reductions in vegetable and legume yields and associated negative health effects.
Therapist-delivered and self-help interventions for gambling problems: A review of contents

Background and aims To date, no systematic approach to identifying the content and characteristics of psychological interventions used to reduce gambling or problem gambling has been developed. This study aimed to develop a reliable classification system capable of identifying intervention characteristics that could, potentially, account for greater or lesser effectiveness. Methods Intervention descriptions were content analyzed to identify common and differentiating characteristics. A coder manual was developed and applied by three independent coders to identify the presence or absence of defined characteristics in 46 psychological and self-help gambling interventions. Results The final classification taxonomy, entitled Gambling Intervention System of CharacTerization (GIST), included 35 categories of intervention characteristics. These were assigned to four groups: (a) types of change techniques (18 categories; e.g., cognitive restructuring and relapse prevention), (b) participant and study characteristics (6 categories; e.g., recruitment strategy and remuneration policy), and (c) characteristics of the delivery and conduct of interventions (11 categories; e.g., modality of delivery and therapist involvement), and (d) evaluation characteristics (e.g., type of control group). Interrater reliability of identification of defined characteristics was high (κ = 0.80–1.00). Discussion This research provides a tool that allows systematic identification of intervention characteristics, thereby enabling consideration, not only of whether interventions are effective or not, but also of which domain-relevant characteristics account for greater or lesser effectiveness. The taxonomy also facilitates standardized description of intervention content in a field in which many diverse interventions have been evaluated. Conclusion Application of this coding tool has the potential to accelerate the development of more efficient and effective therapist-delivered and self-directed interventions to reduce gambling problems.
Computation Rate Maximization in UAV-Enabled Wireless-Powered Mobile-Edge Computing Systems

Mobile-edge computing (MEC) and wireless power transfer are two promising techniques to enhance the computation capability and to prolong the operational time of low-power wireless devices that are ubiquitous in Internet of Things. However, the computation performance and the harvested energy are significantly impacted by the severe propagation loss. In order to address this issue, an unmanned aerial vehicle (UAV)-enabled MEC wireless-powered system is studied in this paper. The computation rate maximization problems in a UAV-enabled MEC wireless powered system are investigated under both partial and binary computation offloading modes, subject to the energy-harvesting causal constraint and the UAV’s speed constraint. These problems are non-convex and challenging to solve. A two-stage algorithm and a three-stage alternative algorithm are, respectively, proposed for solving the formulated problems. The closed-form expressions for the optimal central processing unit frequencies, user offloading time, and user transmit power are derived. The optimal selection scheme on whether users choose to locally compute or offload computation tasks is proposed for the binary computation offloading mode. Simulation results show that our proposed resource allocation schemes outperform other benchmark schemes. The results also demonstrate that the proposed schemes converge fast and have low computational complexity.
Key Tenets of Operational Success in International Animal Welfare Initiatives

Simple Summary With increasing frequency, animal welfare organisations are looking to operate in multiple countries. Apart from lessons learned by trial and error and personal experiences informally shared, little formal knowledge is available to support the challenging task of achieving success for the animal welfare movement beyond borders. Through gaining interview insights from leaders of some of the world’s biggest international animal welfare organisations, this study was able to conduct an analysis to find reoccurring themes and important concepts relating to both successful and unsuccessful initiatives, and investigate the reasons behind their success level. The prominent findings are presented and aim to be of use when looking to develop international animal welfare strategy. Abstract Animal welfare is an increasingly global initiative, which makes the intricate business of operating across borders of particular relevance to the movement. There is, however, a distinct absence of literature dedicated to investigating operational strategies that are more likely to result in the success of international animal welfare initiatives. In addition to this, opportunities exist to investigate the human aspects of animal welfare, parallel to the growing field of animal-based science. This study aimed to begin addressing these gaps by conducting semi structured interviews with 15 leaders of some of the largest international animal welfare charities. Leaders were asked to describe their experiences of successful and unsuccessful initiatives within the animal welfare movement. Thematic analysis was then conducted to identify recurring concepts and extrapolate potentially applicable information. Engaging stakeholders and communities in locally-led and culturally respectful ways were discussed, as was the importance of knowledge, moderation, flexibility, and mutual benefits. The dangers of attacking personal and cultural identity are also highlighted and discussed. Key quotes and examples are presented, supplemented with mind maps as a tool to more readily apply the findings of the study in strategy development.
Reduced order modelling applied to augmented reality

Augmented reality is one of the fields with greatest interest in technological research. Real time requirements force to use physics engines to approximate the behaviour of the objects. We propose the computation of the proper equations that govern the physics of deformable objects, and their interaction with users in real time, using dimensionality reduction techniques.
Influence of Pore Characteristics on the Fate and Distribution of Newly Added Carbon

Pores create a transportation network within a soil matrix, which controls the flow of air, water, and movement of microorganisms . The flow of air, water, and movement of microbes, in turn, control soil carbon dynamics. Computed microtomography (μCT) allows for the visualization of pore structure at micron scale, but quantitative information on contribution of pores to fate and protection of soil carbon, essential for modeling, is still lacking. This study uses the natural difference between carbon isotopes of C3 and C4 plants to determine how the presence of pores of different sizes affects spatial distribution patterns of newly added carbon immediately after plant termination and then after one-month incubation. We considered two contrasting soil structure scenarios: soil with the structure kept intact and soil for which the structure was destroyed via sieving. For the experiment, soil was collected from 0-15 cm depth from a 20-year continuous maize (Zea mays L., C4 plant) experiment into which cereal rye (Secale cereale L., C3 plant) was planted. Intact soil fragments (5-6 mm) were procured after 3 months rye growth in a greenhouse. Pore characteristics of the fragments were determined through μCT imaging. Each fragment was sectioned and total carbon, total nitrogen, δ13C, and δ15N were measured. The results indicate that, prior to incubation, greater presence of 40-90 μm pores was associated with higher levels of C3 carbon, pointing to the positive role of these pores in transport of new C inputs. Nevertheless, after incubation, the association became negative, indicating greater losses of newly added C in such pores. These trends were statistically significant in destroyed-structure soil and numerical in intact-structure soil. In soils of intact-structures, after incubation, higher levels of total carbon were associated with greater abundance of 6.5-15 and 15-40 μm pores, indicating a lower carbon loss associated with these pores. The results indicate that, in the studied soil, pores of 40-90 μm size range are associated with the fast influx of new C followed by its quick decomposition, while pores <40 μm tend to be associated with C protection.
A study of outer membrane protein (OMPs) genes for detection of salmonella organisms in poultry farms

Bacteriological examination of internal organs obtained from diseased layers, broilers and baby chicks revealed isolation of salmonellae with an incidence 5%, 2.5% and 7.1%, respectively. Eleven Salmonella isolates were recovered out of 250 poultry samples. The highest percentage rate was in liver 4%, followed by intestine 2.4% and finally spleen 0.8%. Salmonella organisms were recovered from ovary of layers with an incidence 3.33%. Serological identification of Salmonella isolates revealed that the most prevalent serovars was. Enteritidis (3) followed by. Gallinarum (2) and Rissen (2) then S. Kentukey, S. Florida, S. Lomita and S. Sontheim (one isolate for each). The goal of this study was to evaluate the suitability of the outer membrane genes OmpA and OmpF for detection of Genus Salmonella in clinical samples. OmpA gene was detected in 100% of the examined clinical samples while OmpF gene was detected in 14 clinical samples. Three samples were positive by OmpF.PCR more than cultural method. It was concluded that PCR protocol decrease the time needed for the detection of Salmonella OmpA gene couldn't discriminate genus Salmonella from other non-Salmonella organisms in clinical samples . AS it amplified OmpA in other Enterobacteriaceae. However, OmpF gene is promising tool for detection of Genus Salmonella.
Sensitive and Selective Detection of Tartrazine Based on TiO2-Electrochemically Reduced Graphene Oxide Composite-Modified Electrodes

TiO2-reduced graphene oxide composite-modified glassy carbon electrodes (TiO2–ErGO–GCE) for the sensitive detection of tartrazine were prepared by drop casting followed by electrochemical reduction. The as-prepared material was characterized by transmission electron microscopy (TEM) and X-ray diffraction (XRD). Cyclic voltammetry and second-order derivative linear scan voltammetry were performed to analyze the electrochemical sensing of tartrazine on different electrodes. The determination conditions (including pH, accumulation potential, and accumulation time) were optimized systematically. The results showed that the TiO2–ErGO composites increased the electrochemical active area of the electrode and enhanced the electrochemical responses to tartrazine significantly. Under the optimum detection conditions, the peak current was found to be linear for tartrazine concentrations in the range of 2.0 × 10−8–2.0 × 10−5 mol/L, with a lower detection limit of 8.0 × 10−9 mol/L (S/N = 3). Finally, the proposed TiO2–ErGO–GCEs were successfully applied for the detection of trace tartrazine in carbonated beverage samples.
Analyzing crowd workers' learning behavior to obtain more reliable labels

Crowdsourcing is a popular means to obtain high-quality labels for datasets at moderate costs. These crowdsourced datasets are then used for training supervised or semisupervised predictors. This implies that the performance of the resulting predictors depends on the quality/reliability of the labels that crowd workers assigned – low reliability usually leads to poorly performing predictors. In practice, label reliability in crowdsourced datasets varies substantially depending on multiple factors such as the difficulty of the labeling task at hand, the characteristics and motivation of the participating crowd workers, or the difficulty of the documents to be labeled. Different approaches exist to mitigate the effects of the aforementioned factors, for example by identifying spammers based on their annotation times and removing their submitted labels. To complement existing approaches for improving label reliability in crowdsourcing, this thesis explores label reliability from two perspectives: first, how the label reliability of crowd workers develops over time during an actual labeling task, and second how it is affected by the difficulty of the documents to be labeled. We find that label reliability of crowd workers increases after they labeled a certain number of documents. Motivated by our finding that the label reliability for more difficult documents is lower, we propose a new crowdsourcing methodology to improve label reliability: given an unlabeled dataset to be crowdsourced, we first train a difficulty predictor v on a small seed set and the predictor then estimates the difficulty level in the remaining unlabeled documents. This procedure might be repeated multiple times until the performance of the difficulty predictor is sufficient. Ultimately, difficult documents are separated from the rest, so that only the latter documents are crowdsourced. Our experiments demonstrate the feasibility of this method.
Direct observation and rational design of nucleation behavior in addressable self-assembly

Significance Current efforts aimed at constructing complex supramolecular structures often suffer from low yields or require long assembly protocols. We address these problems by demonstrating a facile strategy for optimizing the nucleation step of a multicomponent self-assembly reaction. By tracking the formation of multisubunit clusters in situ, our experiments show that modifying the critical nucleus required to initiate structure growth can broaden the range of conditions over which self-assembly occurs and, consequently, can dramatically improve the final yield of correctly formed structures. Since varying the design of only a small portion of the target structure optimizes its yield, this strategy provides a practical route to improve the speed and accuracy of self-assembly in biomolecular, colloidal, and nanoparticle systems. To optimize a self-assembly reaction, it is essential to understand the factors that govern its pathway. Here, we examine the influence of nucleation pathways in a model system for addressable, multicomponent self-assembly based on a prototypical “DNA-brick” structure. By combining temperature-dependent dynamic light scattering and atomic force microscopy with coarse-grained simulations, we show how subtle changes in the nucleation pathway profoundly affect the yield of the correctly formed structures. In particular, we can increase the range of conditions over which self-assembly occurs by using stable multisubunit clusters that lower the nucleation barrier for assembling subunits in the interior of the structure. Consequently, modifying only a small portion of a structure is sufficient to optimize its assembly. Due to the generality of our coarse-grained model and the excellent agreement that we find with our experimental results, the design principles reported here are likely to apply generically to addressable, multicomponent self-assembly.
A novel biliary cannulation method for difficult cannulation cases using a unique, uneven, double-lumen cannula (Uneven method)

The utility of pancreatic duct guidewire (P-GW) placement techniques, including the contrast-medium method and the contrast-free wire-guided cannulation method (i. e. the “double-guidewire method” [D-GW]), has been reported for selective biliary cannulation in patients in whom performing cannulation of the bile duct is difficult [1–5]. However, P-GW placement often disturbs the approach to the bile orifice. Moreover, it is sometimes difficult to insert the catheter or guidewire in the direction of the bile duct, which delays biliary cannulation. Herein, we report a novel biliary cannulation method using a unique, uneven, double-lumen cannula (UDLC; PIOLAX, Tokyo, Japan). The UDLC is a double-lumen catheter, with lumens measuring 0.025 and 0.035 inches in diameter, respectively. The orifice of each lumen is uneven, thereby forming a channel at the tip of the UDLC (▶Fig. 1). With such characteristics in mind, we applied the UDLC to develop a new method of selective biliary cannulation for difficult cannulation cases (UDLC method). We describe a case wherein the UDLC was successfully employed without complications (▶Video1). A 75-year-old man presented with pancreatic cancer and was admitted to our hospital for treatment of obstructive cholangitis. It was difficult to perform biliary cannulation as we could insert only the P-GW. Initially, the UDLC was used to intubate the papilla through the P-GW via the distal lumen. This straightened the pancreatic duct and the common channel, thereby effectively stabilizing the papilla (▶Fig. 2). Next, we performed biliary cannulation via the proximal lumen, as is done in the D-GW method (▶Fig. 3). By using this method, we were able to avoid the time delay in adjusting the catheter axis to comply with the bile duct direction, as required in the P-GW method. Thus, we easily initiated the biliary cannulation approach. Ultimately, we succeeded in performing selective biliary cannulation (▶Fig. 4). E-Videos