Pengaruh Perbedaan Konsentrasi Ekstrak Bit Merah dan Gelatin terhadap Sifat Fisikokimia dan Organoleptik Marshmallow Beet

Marshmallow was known as snack food made from sugar, glucose syrup, gelatin and coloring with addition of high air contain that produce soft texture and melting sensation when it chewe. Thus, use of betalain pigment from red beet extract as natural colorant is attempted for marshmallow. The use of beet extract give pectin component and affect gelatin which act as foaming agent to form marshmallow texture. The differences of red beet extract and gelatin concentration will give some effect to the physicochemical properties and organoleptic of marshmallow beet. Red beet extract obtained from red beet bandung and commercial gelatin is used. The research design will be used is two factor Randomized Block Design, red beet extract concentration (5%, 10%, 15%) and gelatin concentration (3%, 4%, 5%) with three replications. The test results are analyzed by varians test (ANOVA) at α = 5% and Duncan's Multiple Range Test at α = 5% if there is real influence. The result of the analysis: water content (21,41-24,35%), water activity (0,807-0,817), pH (7,09-7,32), density (0,4484-0,5401 gram/mL), texture (hardness (773,98-1599,25 g) and chewiness (774,04-1508,77 g)) color (lightness (46,2-60,4), redness (28,2-35,7) and yellowness (5,1-6,6)) and organoleptic (color (4,79-6,13), taste (4,92-6,06) and texture (4,36-6,30)).The best treatment of beet marshmallow is G3B1 treatment (5% gelatin concentration and 5% beet extract concentration), which has 21,41% water content, 0,811 water activity, 0,4790 g/mL density, 1599,25 g hardness, 1508,77 g chewiness, 6,04 lightness, 28,2 redness, 6,6 yellowness and the organoleptic 5,87; 5,84 6,30 for color, taste and texture

Investigating the role of the fusiform face area and occipital face area using multifocal transcranial direct current stimulation.

The functional role of the occipital face area (OFA) and the fusiform face area (FFA) in face recognition is inconclusive to date. While some research has shown that the OFA and FFA are involved in early (i.e., featural processing) and late (i.e., holistic processing) stages of face recognition respectively, other research suggests that both regions are involved in both early and late stages of face recognition. Thus, the current study aims to further examine the role of the OFA and the FFA using multifocal transcranial direct current stimulation (tDCS). In Experiment 1, we used computer-generated faces. Thirty-five participants completed whole face and facial features (i.e., eyes, nose, mouth) recognition tasks after OFA and FFA stimulation in a within-subject design. No difference was found in recognition performance after either OFA or FFA stimulation. In Experiment 2 with 60 participants, we used real faces, provided stimulation following a between-subjects design and included a sham control group. Results showed that FFA stimulation led to enhanced efficiency of facial features recognition. Additionally, no effect of OFA stimulation was found for either facial feature or whole face recognition. These results suggest the involvement of FFA in the recognition of facial features

A unified approach for the solution of the Fokker-Planck equation

This paper explores the use of a discrete singular convolution algorithm as a unified approach for numerical integration of the Fokker-Planck equation. The unified features of the discrete singular convolution algorithm are discussed. It is demonstrated that different implementations of the present algorithm, such as global, local, Galerkin, collocation, and finite difference, can be deduced from a single starting point. Three benchmark stochastic systems, the repulsive Wong process, the Black-Scholes equation and a genuine nonlinear model, are employed to illustrate the robustness and to test accuracy of the present approach for the solution of the Fokker-Planck equation via a time-dependent method. An additional example, the incompressible Euler equation, is used to further validate the present approach for more difficult problems. Numerical results indicate that the present unified approach is robust and accurate for solving the Fokker-Planck equation.Comment: 19 page

Architecting the IoT Paradigm: A Middleware for Autonomous Distributed Sensor Networks

Actualizing Internet of Things undoubtedly constitutes a major challenge of modern computing and is a promising next step in realizing the unification of all seamlessly interacting entities, either human users or participating machines, under a shared, coherent architecture. While it has now become common belief that the related solutions should be based on compatible network infrastructure employing widely accepted communication schemes, the specifics of the intermediate system that would act as global interface for all involved “things” are yet to be determined. A rising trend to define such machine-based entities is through cyber-physical systems, in terms of collaborating elements with physical input and output. Certainly, sensor networks constitute the most representative realization of such systems. Taking these issues and opportunities under consideration, this work proposes a bioinspired distributed architecture for an Internet of Things that exhibits self-organization properties to enable efficient interaction between entities modeled as cyber-physical systems, mainly focusing on sensor networks. Furthermore, a middleware has been implemented according to the proposed architecture, which serves the role of the backbone of this network as a multiagent and autonomous distributed system. The evaluation results demonstrate the self-optimization properties of the introduced scheme and indicate global network convergence

Quantitative model for inferring dynamic regulation of the tumour suppressor gene p53

Background: The availability of various "omics" datasets creates a prospect of performing the study of genome-wide genetic regulatory networks. However, one of the major challenges of using mathematical models to infer genetic regulation from microarray datasets is the lack of information for protein concentrations and activities. Most of the previous researches were based on an assumption that the mRNA levels of a gene are consistent with its protein activities, though it is not always the case. Therefore, a more sophisticated modelling framework together with the corresponding inference methods is needed to accurately estimate genetic regulation from "omics" datasets. Results: This work developed a novel approach, which is based on a nonlinear mathematical model, to infer genetic regulation from microarray gene expression data. By using the p53 network as a test system, we used the nonlinear model to estimate the activities of transcription factor (TF) p53 from the expression levels of its target genes, and to identify the activation/inhibition status of p53 to its target genes. The predicted top 317 putative p53 target genes were supported by DNA sequence analysis. A comparison between our prediction and the other published predictions of p53 targets suggests that most of putative p53 targets may share a common depleted or enriched sequence signal on their upstream non-coding region. Conclusions: The proposed quantitative model can not only be used to infer the regulatory relationship between TF and its down-stream genes, but also be applied to estimate the protein activities of TF from the expression levels of its target genes

Transcriptome-scale similarities between mouse and human skeletal muscles with normal and myopathic phenotypes

BACKGROUND: Mouse and human skeletal muscle transcriptome profiles vary by muscle type, raising the question of which mouse muscle groups have the greatest molecular similarities to human skeletal muscle. METHODS: Orthologous (whole, sub-) transcriptome profiles were compared among four mouse-human transcriptome datasets: (M) six muscle groups obtained from three mouse strains (wildtype, mdx, mdx(5cv)); (H1) biopsied human quadriceps from controls and Duchenne muscular dystrophy patients; (H2) four different control human muscle types obtained at autopsy; and (H3) 12 different control human tissues (ten non-muscle). RESULTS: Of the six mouse muscles examined, mouse soleus bore the greatest molecular similarities to human skeletal muscles, independent of the latters' anatomic location/muscle type, disease state, age and sampling method (autopsy versus biopsy). Significant similarity to any one mouse muscle group was not observed for non-muscle human tissues (dataset H3), indicating this finding to be muscle specific. CONCLUSION: This observation may be partly explained by the higher type I fiber content of soleus relative to the other mouse muscles sampled

Bio-anthropological Studies on Human Skeletons from the 6th Century Tomb of Ancient Silla Kingdom in South Korea

In November and December 2013, unidentified human skeletal remains buried in a mokgwakmyo (a traditional wooden coffin) were unearthed while conducting an archaeological investigation near Gyeongju, which was the capital of the Silla Kingdom (57 BCE– 660 CE) of ancient Korea. The human skeletal remains were preserved in relatively intact condition. In an attempt to obtain biological information on the skeleton, physical anthropological, mitochondrial DNA, stable isotope and craniofacial analyses were carried out. The results indicated that the individual was a female from the Silla period, of 155 ± 5 cm height, who died in her late thirties. The maternal lineage belonged to the haplogroup F1b1a, typical for East Asia, and the diet had been more C3- (wheat, rice and potatoes) than C4-based (maize, millet and other tropical grains). Finally, the face of the individual was reconstructed utilizing the skull (restored from osseous fragments) and three-dimensional computerized modelling system. This study, applying multi-dimensional approaches within an overall bio-anthropological analysis, was the first attempt to collect holistic biological information on human skeletal remains dating to the Silla Kingdom period of ancient Korea

Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity.

Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels