Point2Volume: A vision-based dietary assessment approach using view synthesis

Dietary assessment is an important tool for nutritional epidemiology studies. To assess the dietary intake, the common approach is to carry out 24-h dietary recall (24HR), a structured interview conducted by experienced dietitians. Due to the unconscious biases in such self-reporting methods, many research works have proposed the use of vision-based approaches to provide accurate and objective assessments. In this article, a novel vision-based method based on real-time three-dimensional (3-D) reconstruction and deep learning view synthesis is proposed to enable accurate portion size estimation of food items consumed. A point completion neural network is developed to complete partial point cloud of food items based on a single depth image or video captured from any convenient viewing position. Once 3-D models of food items are reconstructed, the food volume can be estimated through meshing. Compared to previous methods, our method has addressed several major challenges in vision-based dietary assessment, such as view occlusion and scale ambiguity, and it outperforms previous approaches in accurate portion size estimation

Biomineralization mediated by anaerobic methane-consuming cell consortia

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Physical Characteristic and Palatability of Market Vegetable Waste Wafer for Sheep

Vegetable waste is a part of vegetables or vegetables that are discarded. This vegetable market wastes are perishable, voluminous (bulky) and the availability was fluctuated so the processing technology is needed to make this vegetable waste become durable, easy to be stored and could be given to the animal. To solve this problem, vegetable waste could be formed into a wafer. The objective of this experiment was to determine the physical characteristic and palatability of vegetable market waste after formed into a wafer. The experimental design used in this research was Completely Randomized Design with 5 treatments and 4 replicates. The treatments were the composition of raw materials used: 100% corn husk  (R1); 75% corn husk  +25% mungbean waste (R2); 50% corn husk  + 25% mungbean waste + 25% cauliflower leaf  (R3); 25%  corn husk +50% mungbean waste + 25% cauliflower leaf  (R4); 25% corn husk  + 25% mungbean waste  +50%  cauliflower leaf (R5).  Variables measured were water activity, water absorption, density and palatability. The results of this research indicated that treatments significantly affected water activity (P<0.08) and wafer palatability (P<0.05). The highly significant difference in water absorption and wafer density (P<0.01) were found among treatments. Based on physical characteristic, R1 had the highest water absorption.  R5 had the lowest water activity, whereas R3 had the highest wafer density. Wafer of R4 was the most palatable for the experimental sheep compare to other treatments. (Animal Production 12(1): 29-33 (2010)Key Words : physical characteristic,  palatability, wafer and vegetable wast

Nucleation mechanism for the direct graphite-to-diamond phase transition

Graphite and diamond have comparable free energies, yet forming diamond from graphite is far from easy. In the absence of a catalyst, pressures that are significantly higher than the equilibrium coexistence pressures are required to induce the graphite-to-diamond transition. Furthermore, the formation of the metastable hexagonal polymorph of diamond instead of the more stable cubic diamond is favored at lower temperatures. The concerted mechanism suggested in previous theoretical studies cannot explain these phenomena. Using an ab initio quality neural-network potential we performed a large-scale study of the graphite-to-diamond transition assuming that it occurs via nucleation. The nucleation mechanism accounts for the observed phenomenology and reveals its microscopic origins. We demonstrated that the large lattice distortions that accompany the formation of the diamond nuclei inhibit the phase transition at low pressure and direct it towards the hexagonal diamond phase at higher pressure. The nucleation mechanism proposed in this work is an important step towards a better understanding of structural transformations in a wide range of complex systems such as amorphous carbon and carbon nanomaterials

Physical Characteristic and Palatability of Market Vegetable Waste Wafer for Sheep

Vegetable waste is a part of vegetables or vegetables that are discarded. This vegetable market wastes are perishable, voluminous (bulky) and the availability was fluctuated so the processing technology is needed to make this vegetable waste become durable, easy to be stored and could be given to the animal. To solve this problem, vegetable waste could be formed into a wafer. The objective of this experiment was to determine the physical characteristic and palatability of vegetable market waste after formed into a wafer. The experimental design used in this research was Completely Randomized Design with 5 treatments and 4 replicates. The treatments were the composition of raw materials used: 100% corn husk (R1); 75% corn husk +25% mungbean waste (R2); 50% corn husk + 25% mungbean waste + 25% cauliflower leaf (R3); 25% corn husk +50% mungbean waste + 25% cauliflower leaf (R4); 25% corn husk + 25% mungbean waste +50% cauliflower leaf (R5). Variables measured were water activity, water absorption, density and palatability. The results of this research indicated that treatments significantly affected water activity (P<0.08) and wafer palatability (P<0.05). The highly significant difference in water absorption and wafer density (P<0.01) were found among treatments. Based on physical characteristic, R1 had the highest water absorption. R5 had the lowest water activity, whereas R3 had the highest wafer density. Wafer of R4 was the most palatable for the experimental sheep compare to other treatments. (Animal Production 12(1): 29-33 (2010

Sulfur-Modulated Tin Sites Enable Highly Selective Electrochemical Reduction of CO2 to Formate

Electrochemical reduction of carbon dioxide (CO2RR) to formate provides an avenue to the synthesis of value-added carbon-based fuels and feedstocks powered using renewable electricity. Here, we hypothesized that the presence of sulfur atoms in the catalyst surface could promote undercoordinated sites, and thereby improve the electrochemical reduction of CO2 to formate. We explored, using density functional theory, how the incorporation of sulfur into tin may favor formate generation. We used atomic layer deposition of SnSx followed by a reduction process to synthesize sulfur-modulated tin (Sn(S)) catalysts. X-ray absorption near-edge structure (XANES) studies reveal higher oxidation states in Sn(S) compared with that of tin in Sn nanoparticles. Sn(S)/Au accelerates CO2RR at geometric current densities of 55 mA cm−2 at −0.75 V versus reversible hydrogen electrode with a Faradaic efficiency of 93%. Furthermore, Sn(S) catalysts show excellent stability without deactivation (&lt;2% productivity change) following more than 40 hours of operation. With rapid advances in the efficient and cost-effective conversion of sunlight to electrical power, the development of storage technologies for renewable energy is even more urgent. Using renewable electricity to convert CO2 into formate simultaneously addresses the need for storage of intermittent renewable energy sources and the need to reduce greenhouse gas emissions. We report an increase of greater than 4-fold in the current density (hence the rate of reaction) in formate electrosynthesis compared with relevant controls. Our catalysts also show excellent stability without deactivation (&lt;2% productivity change) following more than 40 hours of operation. The electrochemical reduction of carbon dioxide (CO2RR) offers a compelling route to energy storage and high-value chemical manufacture. The presence of sulfur atoms in catalyst surfaces promotes undercoordinated sites, thereby improving the electrochemical reduction of CO2 to formate. The resulting sulfur-modulated tin catalysts accelerate CO2RR at geometric current densities of 55 mA cm−2 at −0.75 V versus RHE with a Faradaic efficiency of 93%

Investigation of Critical Body Residues and Modes of Toxic Action Based on Injection and Aquatic Exposure in Fish

The internal concentration represented by the critical body residue (CBR) is an ideal indicator to reflect the intrinsic toxicity of a chemical. Whilst some studies have been performed on CBR, the effect of exposure route on internal toxicity has not been investigated for fish. In this paper, acute toxicity data to fish comprising LC50 and LD50 values were used to investigate CBR. The results showed that exposure route can significantly affect the internal concentration. LD50 and CBR calculated from LC50 and BCF both vary independently of hydrophobicity as expressed by log Kow; conversely, LC50 is related to log Kow. A poor relationship was observed between LC50 and LD50, but the relationship can be improved significantly by introduction of log Kow because log CBR is positively related to log LD50. The parallel relationship of log CBR-log Kow and log LD50-log Kow indicates that LD50 does not reflect the actual internal concentration. The average LD50 is close to the average CBR for less inert and reactive compounds, but greater than the average CBR for baseline compounds. This difference is due to the lipid fraction being the major storage site for most of the baseline compounds. Investigation on the calculated and observed CBRs shows that calculated CBRs are close to observed CBRs for most of compounds. However, systemic deviations of calculated CBRs have been observed for some compounds. The reasons for these systemic deviations may be attributed to BCF, equilibrium time and experimental error of LC50. These factors are important and should be considered in the calculation of CBRs

Daytime napping, sleep duration and increased 8-year risk of type 2 diabetes in a British population.

BACKGROUND AND AIMS: Few studies have prospectively examined the relationship between daytime napping and risk of type 2 diabetes. We aimed to study the effects of daytime napping and the joint effects of napping and sleep duration in predicting type 2 diabetes risk in a middle- to older-aged British population. METHODS AND RESULTS: In 1998-2000, 13 465 individuals with no known diabetes participating in the European Prospective Investigation into Cancer-Norfolk study reported daytime napping habit and 24-h sleep duration. Incident type 2 diabetes cases were identified through multiple data sources until 31 July 2006. After adjustment for age and sex, daytime napping was associated with a 58% higher diabetes risk. Further adjustment for education, marital status, smoking, alcohol intake, physical activity, comorbidities and hypnotic drug use had little influence on the association, but additional adjustment for BMI and Waist Circumference attenuated the Odds ratio (OR) (95% CI) to 1.30 (1.01, 1.69). The adjusted ORs (95% CI) associated with short and long sleep duration were 1.46 (1.10, 1.90) and 1.64 (1.16, 2.32), respectively. When sleep duration and daytime napping were examined together, the risk of developing diabetes more than doubled for those who took day naps and had less than 6 h of sleep, compared to those who did not nap and had 6-8 h of sleep. CONCLUSION: Daytime napping was associated with an increased risk of type 2 diabetes, particularly when combined with short sleep duration. Further physiological studies are needed to confirm the interaction between different domains of sleep in relation to diabetes risk.The design and conduct of the EPIC-Norfolk study and collection and management of the data was supported by programme grants from the Medical Research Council UK (G9502233, G0300128) and Cancer Research UK (C865/A2883). Funding sources did not have a role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript.This is the final version of the article. It first appeared from Elsevier at http://dx.doi.org/10.1016/j.numecd.2016.06.006

Indoor future person localization from an egocentric wearable camera

Accurate prediction of future person location and movement trajectory from an egocentric wearable camera can benefit a wide range of applications, such as assisting visually impaired people in navigation, and the development of mobility assistance for people with disability. In this work, a new egocentric dataset was constructed using a wearable camera, with 8,250 short clips of a targeted person either walking 1) toward, 2) away, or 3) across the camera wearer in indoor environments, or 4) staying still in the scene, and 13,817 person bounding boxes were manually labelled. Apart from the bounding boxes, the dataset also contains the estimated pose of the targeted person as well as the IMU signal of the wearable camera at each time point. An LSTM-based encoder-decoder framework was designed to predict the future location and movement trajectory of the targeted person in this egocentric setting. Extensive experiments have been conducted on the new dataset, and have shown that the proposed method is able to reliably and better predict future person location and trajectory in egocentric videos captured by the wearable camera compared to three baselines