Rapid diagnosis of Toxoplasma gondii using loop-mediated isothermal amplification assay in camels and small ruminants

Background This study was conducted to detect the presence of T. gondii in milk and blood samples using three different assays: enzyme-linked immunosorbent assay (ELISA), polymerase chain reaction (PCR), and loop-mediated isothermal amplification assay (LAMP). Whole blood, serum, and milk samples were collected from goats (n = 156), sheep (n = 261), and camels (n = 108) in different governorates in Egypt from December 2019 to February 2021 and screened by ELISA for anti-Toxoplasma IgG antibodies before DNA extraction. The target T. gondii DNA gene was detected and evaluated using the LAMP assay compared to PCR. Results T. gondii antibodies were found in milk and serum samples at the rates of (29.26%) and (36.58%) in camels, (34.18%) and (35.89%) in sheep, and (33.7%) and (36.36%) in goats, respectively. Similar to PCR, the percentages of LAMP tests for the detection of the T. gondii DNA gene in milk and blood samples of camels, sheep, and goats were (4.8, 14.63), (6.83, 7.69), and (7.79, 9.09), respectively. LAMP's sensitivity for detecting T. gondii in milk and blood samples, which was identical to that of PCR, was 100%. Conclusions The findings clearly demonstrated that there were no variations in T. gondii detection capabilities in milk and blood samples from various animals using both PCR and LAMP tests. It provides a quick, precise, and sensitive method of detecting T. gondii in a variety of samples that may be used both in the field and in laboratory diagnosis.

Evaluating multi-purpose syndromic surveillance systems – a complex problem

Surveillance systems need to be evaluated to understand what the system can or cannot detect. The measures commonly used to quantify detection capabilities are sensitivity, positive predictive value and timeliness. However, the practical application of these measures to multi-purpose syndromic surveillance services is complex. Specifically, it is very difficult to link definitive lists of what the service is intended to detect and what was detected. First, we discuss issues arising from a multi-purpose system, which is designed to detect a wide range of health threats, and where individual indicators, e.g. ‘fever’, are also multi-purpose. Secondly, we discuss different methods of defining what can be detected, including historical events and simulations. Finally, we consider the additional complexity of evaluating a service which incorporates human decision-making alongside an automated detection algorithm. Understanding the complexities involved in evaluating multi-purpose systems helps design appropriate methods to describe their detection capabilities.

Neutron Detection in Mixed Neutron-Gamma Fields with Common NaI(Tl) Detectors

<p>Searching digitized detector signals for piled-up delayed components with distinct energy and delay time signatures is a smart method to provide common NaI(Tl) detectors with additional neutron detection capabilities at no extra cost. This technique nicely complements the idea of neutron detection by analyzing events with high energy depositions above the range of common gamma-ray energies. In combination, both approaches can provide half of the neutron sensitivity offered by a commercial ⁶Li co-doped NaI(Tl) (NaIL™) scintillator of the same size, at the price of higher and load-dependent background contributions. Delayed-coincidence techniques are most suitable for neutron monitoring or long-term measurements, where the statistics of the acquired delay-time distributions allows separate fitting of the effect and background contributions. In this case, the thermal neutron flux can be quantified in parallel to gamma-ray spectroscopy at overall detector loads exceeding 10 kcps.</p>

Neutron Detection in Mixed Neutron-Gamma Fields with Common NaI(Tl) Detectors

<p>Searching digitized detector signals for piled-up delayed components with distinct energy and delay time signatures is a smart method to provide common NaI(Tl) detectors with additional neutron detection capabilities at no extra cost. This technique nicely complements the idea of neutron detection by analyzing events with high energy depositions above the range of common gamma-ray energies. In combination, both approaches can provide half of the neutron sensitivity offered by a commercial ⁶Li co-doped NaI(Tl) (NaIL™) scintillator of the same size, at the price of higher and load-dependent background contributions. Delayed-coincidence techniques are most suitable for neutron monitoring or long-term measurements, where the statistics of the acquired delay-time distributions allows separate fitting of the effect and background contributions. In this case, the thermal neutron flux can be quantified in parallel to gamma-ray spectroscopy at overall detector loads exceeding 10 kcps.</p>

Assessment of real-time bioaerosol particle counters using reference chamber experiments

This study presents the first reference calibrations of three commercially available bioaerosol detectors. The Droplet Measurement Technologies WIBS-NEO (new version of the wideband integrated bioaerosol spectrometer), Plair Rapid-E, and Swisens Poleno were compared with a primary standard for particle number concentrations at the Federal Institute for Metrology (METAS). Polystyrene (PSL) spheres were used to assess absolute particle counts for diameters from 0.5 to 10 µm. For the three devices, counting efficiency was found to be strongly dependent on particle size. The results confirm the expected detection range for which the instruments were designed. While the WIBS-NEO achieves its highest efficiency with smaller particles, e.g. 90 % for 0.9 µm diameter, the Plair Rapid-E performs best for larger particles, with an efficiency of 58 % for particles with a diameter of 10 µm. The Swisens Poleno is also designed for larger particles but operates well from 2 µm. However, the exact counting efficiency of the Poleno could not be evaluated as the cut-off diameter range of the integrated concentrator unit was not completely covered. In further experiments, three different types of fluorescent particles were tested to investigate the fluorescent detection capabilities of the Plair Rapid-E and the Swisens Poleno. Both instruments showed good agreement with the reference data. While the challenge to produce known concentrations of larger particles above 10 µm or even fresh pollen particles remains, the approach presented in this paper provides a potential standardised validation method that can be used to assess counting efficiency and fluorescence measurements of automatic bioaerosol monitoring devices.

Exploitation Techniques for Data-oriented Attacks with Existing and Potential Defense Approaches

Data-oriented attacks manipulate non-control data to alter a program’s benign behavior without violating its control-flow integrity. It has been shown that such attacks can cause significant damage even in the presence of control-flow defense mechanisms. However, these threats have not been adequately addressed. In this survey article, we first map data-oriented exploits, including Data-Oriented Programming (DOP) and Block-Oriented Programming (BOP) attacks, to their assumptions/requirements and attack capabilities. Then, we compare known defenses against these attacks, in terms of approach, detection capabilities, overhead, and compatibility. It is generally believed that control flows may not be useful for data-oriented security. However, data-oriented attacks (especially DOP attacks) may generate side effects on control-flow behaviors in multiple dimensions (i.e., incompatible branch behaviors and frequency anomalies). We also characterize control-flow anomalies caused by data-oriented attacks. In the end, we discuss challenges for building deployable data-oriented defenses and open research questions.

Regional Morpho-Kinematic Inventory of Slope Movements in Northern Norway

Mountain slopes in periglacial environments are affected by frost- and gravity-driven processes that shape the landscape. Both rock glaciers and rockslides have been intensively inventoried worldwide. Although most inventories are traditionally based on morphologic criteria, kinematic approaches based on satellite remote sensing have more recently been used to identify moving landforms at the regional scale. In this study, we developed simplified Interferometric Synthetic Aperture Radar (InSAR) products to inventory ground velocity in a region in Northern Norway covering approximately 7,500 km2. We used a multiple temporal baseline InSAR stacking procedure based on 2015–2019 ascending and descending Sentinel-1 images to take advantage of a large set of interferograms and exploit different detection capabilities. First, moving areas are classified according to six velocity brackets, and morphologically associated to six landform types (rock glaciers, rockslides, glaciers/moraines, talus/scree deposits, solifluction/cryoturbation and composite landforms). The kinematic inventory shows that the velocity ranges and spatial distribution of the different types of slope processes vary greatly within the study area. Second, we exploit InSAR to update pre-existing inventories of rock glaciers and rockslides in the region. Landform delineations and divisions are refined, and newly detected landforms (54 rock glaciers and 20 rockslides) are incorporated into the databases. The updated inventories consist of 414 rock glacier units within 340 single- or multi-unit(s) systems and 117 rockslides. A kinematic attribute assigned to each inventoried landform documents the order of magnitude of the creep rate. Finally, we show that topo-climatic variables influence the spatial distribution of the rock glaciers. Their mean elevation increases toward the continental interior with a dominance of relict landforms close to the land-sea margin and an increased occurrence of active landforms further inland. Both rock glaciers and rockslides are mostly located on west-facing slopes and in areas characterised by strongly foliated rocks, which suggests the influence of geological preconditioning factors. The study demonstrates the value of semi-quantitative InSAR products to characterise kinematic information at large scale and exploit the results for periglacial research. It highlights the complementarity of both kinematic and morphologic approaches for inventorying slope processes.

Chained Digital Signature for the Improved Video Integrity Verification

The recorded videos from the surveillance cameras can be used as potential evidence in forensic applications. These videos can be easily manipulated or tampered with video editing tools without leaving visible clues. Hence integrity verification is essential before using the videos as evidence. Existing methods mostly depend on the analysis of video data stream and video container for tampering detection. This paper discusses an active video integrity verification method using Elliptic Curve Cryptography and blockchain. The method uses Elliptic Curve Digital Signature Algorithm for calculating digital signature for video content and previous block. The digital signature of the encoded video segment (video content with predetermined size) and that of previous block are kept in each block to form an unbreakable chain. Our method does not consider any coding or compression artifacts of the video file and can be used on any video type and is tested on public-available standard videos with varying sizes and types. The proposed integrity verification scheme has better detection capabilities towards different types of alterations like insertion, copy-paste and deletion and can detect any type of forgery. This method is faster and more resistant to brute force and collision attacks in comparison to existing recent blockchain method.

An object detection network based on YOLOv4 and improved spatial attention mechanism

In recent years, the research on object detection has been intensified. A large number of object detection results are applied to our daily life, which greatly facilitates our work and life. In this paper, we propose a more effective object detection neural network model ENHANCE_YOLOV4. We studied the effects of several attention mechanisms on YOLOV4, and finally concluded that spatial attention mechanism had the best effect on YOLOV4. Therefore, based on previous studies, this paper introduces Dilated Convolution and one-by-one convolution into the spatial attention mechanism to expand the receptive field and combine channel information. Compared with CBAM and BAM, which are composed of spatial attention and channel attention, this improved spatial attention module reduces model parameters and improves detection capabilities. We built a new network model by embedding improved spatial attention module in the appropriate place in YOLOV4. And this paper proves that the detection accuracy of this network structure on the VOC data set is increased by 0.8%, and the detection accuracy on the coco data set is increased by 7%when the calculation performance is increased a little.