Analysis of Porcine Gelatin DNA in a Commercial Capsule Shell Using Real-Time Polymerase Chain Reaction for Halal Authentication

The presence of pig derivatives, such as porcine gelatin, in any products is prohibited to be consumed by Muslim community. This study is intended to develop a specific primer from mytochondrial D-loop capable of amplifying DNA from porcine gelatin in commercial capsule shells. Two pairs of primers designed from mitochondrial D-loop region were tested in order to confirm the primer specificity in gelatin sources (pork, beef, and catfish) and fresh tissue (pig, cows, goat, chickens, and rat). Primers were then used to perform sensitivity test of six dilution series (1000, 200, 100, 10, 5, and 1 pg/µL) of porcine gelatin and porcine capsule shell. The amplification was also performed on capsule shell from porcine-bovine mixture gelatin at 0, 10, 20, 30, 40, 50, and 100% concentration. The repeatability test was performed by measuring amplification capsule shells from porcine–bovine gelatin mixture. Real time polymerase chain reaction method using primers designed was further applied to analyze capsule shells purchased from markets. From two primers have been designed specifically, only primer D-Loop 108 (forward: 5’-CGT ATG CAA AAA ACC ACG CCA-3’; reverse: 5’-CTT ACT ATA GGG AGC TGC ATG-3’) had the capability to identify the presence of porcine DNA in fresh tissue and gelatin sources at optimum annealing temperature of 58.4ºC. Sensitivity of the developed method expressed as limit of detection of DNA in gelatin and capsule shells is 5 pg.     

A Review of Guidance Approaches in Visual Data Analysis: A Multifocal Perspective

Visual data analysis can be envisioned as a collaboration of the user and the computational system with the aim of completing a given task. Pursuing an effective system‐user integration, in which the system actively helps the user to reach his/her analysis goal has been focus of visualization research for quite some time. However, this problem is still largely unsolved. As a result, users might be overwhelmed by powerful but complex visual analysis systems which also limits their ability to produce insightful results. In this context, guidance is a promising step towards enabling an effective mixed‐initiative collaboration to promote the visual analysis. However, the way how guidance should be put into practice is still to be unravelled. Thus, we conducted a comprehensive literature research and provide an overview of how guidance is tackled by different approaches in visual analysis systems. We distinguish between guidance that is provided by the system to support the user, and guidance that is provided by the user to support the system. By identifying open problems, we highlight promising research directions and point to missing factors that are needed to enable the envisioned human‐computer collaboration, and thus, promote a more effective visual data analysis.     

Dielectric Properties of Ultrathin CaF2 Ionic Crystals

Mechanically exfoliated 2D hexagonal boron nitride (h-BN) is currently the preferred dielectric material to interact with graphene and 2D transition metal dichalcogenides in nanoelectronic devices, as they form a clean van der Waals interface. However, h-BN has a low dielectric constant (≈3.9), which in ultrascaled devices results in high leakage current and premature dielectric breakdown. Furthermore, the synthesis of h-BN using scalable methods, such as chemical vapor deposition, requires very high temperatures (>900 °C) , and the resulting h-BN stacks contain abundant few-atoms-wide amorphous regions that decrease its homogeneity and dielectric strength. Here it is shown that ultrathin calcium fluoride (CaF₂) ionic crystals could be an excellent solution to mitigate these problems. By applying >3000 ramped voltage stresses and several current maps at different locations of the samples via conductive atomic force microscopy, it is statistically demonstrated that ultrathin CaF₂ shows much better dielectric performance (i.e., homogeneity, leakage current, and dielectric strength) than SiO₂, TiO₂, and h-BN. The main reason behind this behavior is that the cubic crystalline structure of CaF₂ is continuous and free of defects over large regions, which prevents the formation of electrically weak spots.     

Guide Me in Analysis: A Framework for Guidance Designers

Guidance is an emerging topic in the field of visual analytics. Guidance can support users in pursuing their analytical goals more efficiently and help in making the analysis successful. However, it is not clear how guidance approaches should be designed and what specific factors should be considered for effective support. In this paper, we approach this problem from the perspective of guidance designers. We present a framework comprising requirements and a set of specific phases designers should go through when designing guidance for visual analytics. We relate this process with a set of quality criteria we aim to support with our framework, that are necessary for obtaining a suitable and effective guidance solution. To demonstrate the practical usability of our methodology, we apply our framework to the design of guidance in three analysis scenarios and a design walk-through session. Moreover, we list the emerging challenges and report how the framework can be used to design guidance solutions that mitigate these issues.     

Abwasserreinigung mit Schilf in einer mobilen Wurzelraumkläranlage

A mobile root‐zone wastewater treatment system with a reaction zone consisting solely of reed roots as the growth surface for microorganisms was tested for temporary applications in the treatment of municipal wastewater. Pretreated municipal wastewater from a large‐scale wastewater treatment plant was fed to this system during the 2016 vegetation period. The outlet limit values for chemical oxygen demand and biochemical oxygen demand were adhered to reliably at an inlet volumetric flow rate of 1200 L d^?1. Short‐term loading peaks of up to 1800 L d^?1 did not lead to overloading of the system.     

NEVA: Visual Analytics to Identify Fraudulent Networks

Trust-ability, reputation, security and quality are the main concerns for public and private financial institutions. To detect fraudulent behaviour, several techniques are applied pursuing different goals. For well-defined problems, analytical methods are applicable to examine the history of customer transactions. However, fraudulent behaviour is constantly changing, which results in ill-defined problems. Furthermore, analysing the behaviour of individual customers is not sufficient to detect more complex structures such as networks of fraudulent actors. We propose NEVA (Network dEtection with Visual Analytics), a Visual Analytics exploration environment to support the analysis of customer networks in order to reduce false-negative and false-positive alarms of frauds. Multiple coordinated views allow for exploring complex relations and dependencies of the data. A guidance-enriched component for network pattern generation, detection and filtering support exploring and analysing the relationships of nodes on different levels of complexity. In six expert interviews, we illustrate the applicability and usability of NEVA.