NUTRACEUTICAL PROPERTIES OF GLUTEN-FREE CUPCAKES PREPARED BY GLUTEN-FREE COMPOSITE FLOUR

Objective: The present study was aimed to evaluate the nutritional, phytochemical and antioxidant properties of all ratios of gluten-free composite flour-based cupcakes. Methods: Composite flour was the blend of teff millet flour (TF), navy bean flour (NF) and watermelon seeds flour (WF). The variations of three composite flours were prepared as, A being (TF: NF: WF=45:45:10), B being (TF: NF: WF=55:35:10) and C being (TF: NF: WF=65:25:10) respectively. Moisture, ash, fat, fiber, protein and carbohydrate were analyzed in this study. Minerals like calcium, iron, phosphorus and zinc were also analyzed. Results: The result of macronutrient and micronutrient of C ratio was moisture (28.1±0.2), ash (2.5±0.0), protein (12.2±0.3), fat (24.5±0.0), fiber (2.8±0.1) and carbohydrate (32.2±0.1 g/100g) respectively. Calcium (36.9±0.1), iron (7.5±0.0), zinc (3.8±0.2) and phosphorus (235.0±0.4 mg/100g) were also present in gluten-free Cupcakes. On the basis of the present study, it was found that gluten-free cupcakes contain different macro as well as micronutrients. It also has some phytochemicals such as flavonoids, saponins, tannin, glycocides and steroids. Conclusion: The study result revealed that gluten-free Cupcakes had higher phenols content as well as antioxidant activity. The overall good amount of all nutrients found in the C ratio. The sensory evaluation of Cupcakes on a 9 point hedonic scale revealed that a ratio was more acceptable than the B and C ratio. Therefore, it can be beneficial for celiac diseases, hypertension, anemia, diabetes and cancer condition

Sensors for Desert Surveillance

Various types of sensors-visible, passive night vision, infrared, synthetic aperture radar, etc can be used for desert surveillance. The surveillance capability of these sensors depends to a large extent, on various atmospheric effects, viz., absorption, scattering, aerosol, turbulence, and optical mirage. In this paper, effects of various atmospheric phenomena on the transmission of signals, merits and demerits of different means of surveillance under desert environmental conditions are discussed. Advanced surveillance techniques, ie, multisensor fusion, multi and hyperspectral imaging, having special significance for desert surveillance, have also been discussed

The Parallel Persistent Memory Model

We consider a parallel computational model that consists of $P$ processors, each with a fast local ephemeral memory of limited size, and sharing a large persistent memory. The model allows for each processor to fault with bounded probability, and possibly restart. On faulting all processor state and local ephemeral memory are lost, but the persistent memory remains. This model is motivated by upcoming non-volatile memories that are as fast as existing random access memory, are accessible at the granularity of cache lines, and have the capability of surviving power outages. It is further motivated by the observation that in large parallel systems, failure of processors and their caches is not unusual. Within the model we develop a framework for developing locality efficient parallel algorithms that are resilient to failures. There are several challenges, including the need to recover from failures, the desire to do this in an asynchronous setting (i.e., not blocking other processors when one fails), and the need for synchronization primitives that are robust to failures. We describe approaches to solve these challenges based on breaking computations into what we call capsules, which have certain properties, and developing a work-stealing scheduler that functions properly within the context of failures. The scheduler guarantees a time bound of $O(W/P_A + D(P/P_A) \lceil\log_{1/f} W\rceil)$ in expectation, where $W$ and $D$ are the work and depth of the computation (in the absence of failures), $P_A$ is the average number of processors available during the computation, and $f \le 1/2$ is the probability that a capsule fails. Within the model and using the proposed methods, we develop efficient algorithms for parallel sorting and other primitives.Comment: This paper is the full version of a paper at SPAA 2018 with the same nam

Effect of labile inorganic phosphate status and organic carbon additions on the microbial uptake of phosphorus in soils

Includes bibliographical references (pages 384-385).Abstract in English and French.The effect of labile inorganic phosphate (Pi) status of the soil on the decomposition of added cellulose and on the immobilization, mineralization, and redistribution of native and added P in soils was studied in a greenhouse incubation experiment. Cellulose was added at 765 μg C∙g−1 soil with and without P (9 μg∙g−1 soil) every 30 days under adequate N, H2O, and constant tempreature to two soils of different available P status. Lack of P eventually slowed down decomposition of added C, but this effect was partially compensated for by increased mineralization of organic P (Po) forms. Added P was redistributed to both P, (58–69%) and Po (42–31%) forms; higher amounts of Po were found in the soil with the highest Pi status. The correlation between microbial P uptake and solution P values was significant, and microbial C:P ratios ranged from 12:1 under high available P conditions to 45:1 where P was in low supply

Effect of carbon additions on soil labile inorganic, organic and microbially held phosphate

Includes bibliographical references (page 396).Investigations of the rate of P movement between soil inorganic, organic and biomass P compartments were carried out to clarify aspects of P cycling in soil systems. Organic carbon, as dried grass (33% C, 0.11% P) and cellulose (43% C), was added at a rate equivalent to 4000 kg organic material (OM)∙ha−1 every 30 days for 9 mo to the Ap horizon of a Chernozemic Black soil kept at field capacity moisture content and 24 ± 2 °C. In a third treatment, cellulose was added at the same rate with P (20 kg∙ha−1) at KH2PO4. Approximately 39% and 22% of the P added in grass and with cellulose, respectively, was found in organic P forms after 9 mo incubation. The remainder was found in NH4Cl-, NH4F- and NaOH-NaCl-extractable P forms which constituted part of the labile inorganic P pool and could be extracted by an anion exchange resin. Increases of biomass P during the first 4 or 5 days of each incubation period after residue addition were found to average 12 μg P∙g−1 in the first 3 mo incubation period. After this period, there was a smaller response in microbial P attributable to additions of grass or cellulose

Camera-Based Visual Feedback Learning Aid for Recovering Sense of Smell and Taste in COVID-19 Survivors: A Proof-of-Concept Study

Introduction: A significant proportion of people report persistent COVID 19-related anosmia, hyposmia or parosmia, often accompanied with ageusia, hypogeusia or dysgeusia. Here, we present a proof-of-concept study that assessed the feasibility and acceptability of a new Camera-Based Visual Feedback Learning Aid (CVFLA) and explored its potential to restore or improve persistent COVID-19-related smell and/or taste impairment. Methods: Fifteen adult participants with persistent smell and/or taste impairment were randomly allocated to 7-, 14-, or 21-days baseline of symptom monitoring before receiving the intervention in up to 10 sessions (length and frequency determined by participant’s preference and progress) using a specialised CVFLA apparatus (patent no. 10186160). Smell and taste were assessed pre- and post intervention subjectively, and also objectively using the ODOFIN Taste Strips and Sniffin Sticks. Participant feedback about their experience of receiving CVFLA was obtained via a semi-structured interview conducted by someone not involved in delivering the intervention. Results: The intervention was extremely well received, with no dropouts related to the intervention. There was also a significant improvement in smell and taste from pre- to post-CVFLA intervention (mean number of sessions = 7.46, SD = 2.55; total duration = 389.96 min, SD = 150.93) both in subjective and objective measures. All participants, except one, reported experiencing some improvement from the 2nd or 3rd session. Discussion: This new CVFLA intervention shows promise in improving COVID-19 related impairment in smell and taste with a very high level of acceptability. Further studies with larger samples are required to confirm its potential in restoring, improving or correcting smell and/or taste impairment in relevant clinical and non-clinical groups.Brunel University London, and the European Research Development Fund (EDRF) and Learning JBE Ltd. via Anglia Ruskin University. Learning JBE Ltd. owns the patent on the camera-based feedback learning technique used in the study. Learning JBE Ltd. was not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication

KamLAND Bounds on Solar Antineutrinos and neutrino transition magnetic moments

We investigate the possibility of detecting solar electron antineutrinos with the KamLAND experiment. These electron antineutrinos are predicted by spin-flavor oscillations at a significant rate even if this mechanism is not the leading solution to the SNP. KamLAND is sensitive to antineutrinos originated from solar ${}^8$B neutrinos. From KamLAND negative results after 145 days of data taking, we obtain model independent limits on the total flux of solar electron antineutrinos $\Phi({}^8 B)< 1.1-3.5\times 10^4 cm^{-2}\ s^{-1}$, more than one order of magnitude smaller than existing limits, and on their appearance probability$P<0.15%$(95antineutrino production by spin-flavor precession, this upper bound implies an upper limit on the product of the intrinsic neutrino magnetic moment and the value of the solar magnetic field$\mu B< 2.3\times 10^{-21}$MeV 95LMA$(\Delta m^2, \tan^2\theta)$values). Limits on neutrino transition moments are also obtained. For realistic values of other astrophysical solar parameters these upper limits would imply that the neutrino magnetic moment is constrained to be, in the most conservative case,$\mu\lsim 3.9\times 10^{-12} \mu_B$(95CL) for a relatively small field$B= 50$kG. For higher values of the magnetic field we obtain:$\mu\lsim 9.0\times 10^{-13} \mu_B$for field$B= 200$kG and$\mu\lsim 2.0\times 10^{-13} \mu_B$for field$B= 1000$ kG at the same statistical significance.Comment: 13 pages, 2 figure

Muscle vitamin E and retail colour of meat from lambs fed lucerne or grain-based diets at two antioxidant levels

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Non-Invasive Sheep Biometrics Obtained by Computer Vision Algorithms and Machine Learning Modeling Using Integrated Visible/Infrared Thermal Cameras

Live sheep export has become a public concern. This study aimed to test a non-contact biometric system based on artificial intelligence to assess heat stress of sheep to be potentially used as automated animal welfare assessment in farms and while in transport. Skin temperature (°C) from head features were extracted from infrared thermal videos (IRTV) using automated tracking algorithms. Two parameter engineering procedures from RGB videos were performed to assess Heart Rate (HR) in beats per minute (BPM) and respiration rate (RR) in breaths per minute (BrPM): (i) using changes in luminosity of the green (G) channel and (ii) changes in the green to red (a) from the CIELAB color scale. A supervised machine learning (ML) classification model was developed using raw RR parameters as inputs to classify cutoff frequencies for low, medium, and high respiration rate (Model 1). A supervised ML regression model was developed using raw HR and RR parameters from Model 1 (Model 2). Results showed that Models 1 and 2 were highly accurate in the estimation of RR frequency level with 96% overall accuracy (Model 1), and HR and RR with R = 0.94 and slope = 0.76 (Model 2) without statistical signs of overfitting