ALBERT

Description: Fault tolerance in IoT systems is challenging to overcome due to its complexity, dynamicity, and heterogeneity. IoT systems are typically designed and constructed in layers. Every layer has its requirements and fault tolerance strategies. However, errors in one layer can propagate and cause effects on others. Thus, it is impractical to consider a centralized fault tolerance approach for an entire system. Consequently, it is vital to consider multiple layers in order to enable collaboration and information exchange when addressing fault tolerance. The purpose of this study is to propose a multi-layer fault tolerance approach, granting interconnection among IoT system layers, allowing information exchange and collaboration in order to attain the property of dependability. Therefore, we define an event-driven framework called FaTEMa (Fault Tolerance Event Manager) that creates a dedicated fault-related communication channel in order to propagate events across the levels of the system. The implemented framework assist with error detection and continued service. Additionally, it offers extension points to support heterogeneous communication protocols and evolve new capabilities. Our empirical results show that introducing FaTEMa provided improvements to the error detection and error resolution time, consequently improving system availability. In addition, the use of Fatema provided a reliability improvement and a reduction in the number of failures produced.

Description: This study presents a 2-D lidar odometry based on an ICP (iterative closest point) variant used in a simple and straightforward platform that achieves real-time and low-drift performance. With a designated multi-scale feature extraction procedure, the lidar cloud information can be utilized at multiple levels and the speed of data association can be accelerated according to the multi-scale data structure, thereby achieving robust feature extraction and fast scan-matching algorithms. First, on a large scale, the lidar point cloud data are classified according to the curvature into two parts: smooth collection and rough collection. Then, on a small scale, noise and unstable points in the smooth or rough collection are filtered, and edge points and corner points are extracted. Then, the proposed tangent-vector-pairs based on edge and corner points are applied to evaluate the rotation term, which is significant for producing a stable solution in motion estimation. We compare our performance with two excellent open-source SLAM algorithms, Cartographer and Hector SLAM, using collected and open-access datasets in structured indoor environments. The results indicate that our method can achieve better accuracy.

Description: A simple one-pot approach was developed for the synthesis of furan-2(5H)-one derivative containing indole fragments. This method includes the telescoped multicomponent reaction of indole, 4-methoxyphenylglyoxal, and Meldrum’s acid. The synthetic utility of the prepared furan-2(5H)-one was demonstrated by condensation with 4-methoxybenzaldehyde. The advantages of this method include the employment of readily accessible starting materials, atom economy, process simplicity, and the easy isolation of the target products. The structure of the synthesized furanones was confirmed by 1H and 13C-NMR spectroscopy and high-resolution mass spectrometry with electrospray ionization (ESI-HRMS).

Description: In the single-polyelectrolyte aqueous phase separation (APS) approach, membranes are prepared by precipitating a weak polyelectrolyte from a concentrated aqueous solution using a pH switch. This has proven to be a versatile and more sustainable method compared to conventional approaches as it significantly reduces the use of organic solvents. Poly(styrene-alt-maleic acid) (PSaMA) is a polymer that has been extensively investigated for APS and has been the basis for both open and dense membranes with good performances. These membranes are chemically crosslinked and, in this work, we further investigated ultrafiltration (UF) and nanofiltration (NF) membranes prepared with PSaMA for their stability in various organic solvents and under different pH conditions. It was shown that these membranes had stable performances in both isopropanol (IPA) and toluene, and a slightly reduced performance in N-methyl-2-pyrollidone (NMP). However, PSaMA did not perform well as a selective layer in these solvents, indicating that the real opportunity would be to use the UF-type PSaMA membranes as solvent-stable support membranes. Additionally, the membranes proved to be stable in an acidic-to-neutral pH regime (pH 2–7); and, due to the pH-responsive nature of PSaMA, for the NF membranes, a pH-dependent retention of Mg2+ and SO42− ions was observed and, for the UF membranes, a strong responsive behavior was observed, where the pH can be used to control the membrane permeability. However, long-term exposure to elevated pH conditions (pH 8–10) resulted in severe swelling of the NF membranes, resulting in defect formation, and compaction of the UF membranes. For the UF membranes, this compaction did prove to be reversible for some but not all of the membrane samples measured. These results showed that in aqueous systems, membranes prepared with PSaMA had interesting responsive behaviors but performed best at neutral and acidic pH values. Moreover, the membranes exhibited excellent stability in the organic solvents IPA and toluene

Description: Volcanic ash fall-out represents a serious hazard for air and road traffic. The forecasting models used to predict its time–space evolution require information about the core characteristics of volcanic particles, such as their granulometry. Typically, such information is gained by the spot direct observation of the ash collected at the ground or by using expensive instrumentation. In this paper, a vision-based methodology aimed at the estimation of ash granulometry is presented. A dedicated image processing paradigm was developed and implemented in LabVIEW™. The methodology was validated experimentally using digital reference images resembling different operating conditions. The outcome of the assessment procedure was very encouraging, showing an accuracy of the image processing algorithm of 1.76%.

Description: Hypoxia is known to impair mitochondrial and endoplasmic reticulum (ER) homeostasis. Post-hypoxic perturbations of the ER proteostasis result in the accumulation of misfolded/unfolded proteins leading to the activation of the Unfolded Protein Response (UPR). Mitochondrial chaperone TNF receptor-associated protein 1 (TRAP1) is reported to preserve mitochondrial membrane potential and to impede reactive oxygen species (ROS) production thereby protecting cells from ER stress as well as oxidative stress. The first-line antidiabetic drug Metformin has been attributed a neuroprotective role after hypoxia. Interestingly, Metformin has been reported to rescue mitochondrial deficits in fibroblasts derived from a patient carrying a homozygous TRAP1 loss-of-function mutation. We sought to investigate a putative link between Metformin, TRAP1, and the UPR after hypoxia. We assessed post-hypoxic/reperfusion longevity, mortality, negative geotaxis, ROS production, metabolic activity, gene expression of antioxidant proteins, and activation of the UPR in Trap1-deficient flies. Following hypoxia, Trap1 deficiency caused higher mortality and greater impairments in negative geotaxis compared to controls. Similarly, post-hypoxic production of ROS and UPR activation was significantly higher in Trap1-deficient compared to control flies. Metformin counteracted the deleterious effects of hypoxia in Trap1-deficient flies but had no protective effect in wild-type flies. We provide evidence that TRAP1 is crucially involved in the post-hypoxic regulation of mitochondrial/ER stress and the activation of the UPR. Metformin appears to rescue Trap1-deficiency after hypoxia mitigating ROS production and downregulating the pro-apoptotic PERK (protein kinase R-like ER kinase) arm of the UPR.

Description: Real-time PCR is widely used to study the relative abundance of mRNA due to its specificity, sensitivity, and repeatability quantification. However, relative quantification requires a reference gene, which should be stable in its expression, showing lower variation by experimental conditions or tissues. The aim of this study was to evaluate the stability of the expression of five commonly used reference genes (actb, ywhaz, b2m, sdha, and 18s rRNA) at different physiological stages (alert and emergency) in three different cattle breeds. In this study, five genes (actb, ywhaz, b2m, sdha, and 18s rRNA) were selected as candidate reference genes for expression studies in the whole blood from three cattle breeds (Romosinuano, Gyr, and Brahman) under heat stress conditions. The transcription stability of the candidate reference genes was evaluated using geNorm and NormFinder. The results showed that actb, 18SrRNA, and b2m expression were the most stable reference genes for whole blood of Gyr and Brahman breeds under two states of livestock weather safety (alert and emergency). Meanwhile, actb, b2m, and ywhaz were the most stable reference genes for the Romosinuano breed.

Description: Food processing systematically aims at meeting the needs of consumers who are looking for total high quality and perfect food safety. As the various thermal and non-thermal food preservation technologies often affect the natural properties in terms of sensation, flavor, texture, etc., instant controlled pressure drop (DIC) has been conceived as a relevant, innovative process in this field. DIC uses high saturated steam pressure and short duration to provide a new way to expand biological matrices, improve drying, decontaminate, and extract biologically active compounds, among other attributes. Therefore, this review focuses on describing the applications of DIC technology on a wide range of products such as foods and by-products that have been processed both in the laboratory and on an industrial scale. The application of DIC has shown the possibility of a significant leap in quality improvement and cost reduction in the food industry. DIC reduces the drying time of fruits and vegetables, and improves the extraction of essential oils, vegetable oils, and antioxidant components. It also provides strong decontamination, eliminates vegetative microorganisms and spores, and reduces non-nutritional and allergenic components. Over the past 33 years, this technology has continued to expand its food applications and improve its characteristics on an industrial scale. But there are still many food unit operations that can be taken to the next level with DIC.

Description: This paper investigates the hybrid source localization problem using differential received signal strength (DRSS) and angle of arrival (AOA) measurements. The main advantage of hybrid measurements is to improve the localization accuracy with respect to a single sensor modality. For sufficiently short wavelengths, AOA sensors can be constructed with size, weight, power and cost (SWAP-C) requirements in mind, making the proposed hybrid DRSS-AOA sensing feasible at a low cost. Firstly the maximum likelihood estimation solution is derived, which is computationally expensive and likely to become unstable for large noise levels. Then a novel closed-form pseudolinear estimation method is developed by incorporating the AOA measurements into a linearized form of DRSS equations. This method eliminates the nuisance parameter associated with linearized DRSS equations, hence improving the estimation performance. The estimation bias arising from the injection of measurement noise into the pseudolinear data matrix is examined. The method of instrumental variables is employed to reduce this bias. As the performance of the resulting weighted instrumental variable (WIV) estimator depends on the correlation between the IV matrix and data matrix, a selected-hybrid-measurement WIV (SHM-WIV) estimator is proposed to maintain a strong correlation. The superior bias and mean-squared error performance of the new SHM-WIV estimator is illustrated with simulation examples.

Description: Cadmium (Cd) is one of the most injurious heavy metals, affecting plant growth and development. Melatonin (N-acetyl-5-methoxytryptamine) was discovered in plants in 1995, and it is since known to act as a multifunctional molecule to alleviate abiotic and biotic stresses, especially Cd stress. Endogenously triggered or exogenously applied melatonin re-establishes the redox homeostasis by the improvement of the antioxidant defense system. It can also affect the Cd transportation and sequestration by regulating the transcripts of genes related to the major metal transport system, as well as the increase in glutathione (GSH) and phytochelatins (PCs). Melatonin activates several downstream signals, such as nitric oxide (NO), hydrogen peroxide (H2O2), and salicylic acid (SA), which are required for plant Cd tolerance. Similar to the physiological functions of NO, hydrogen sulfide (H2S) is also involved in the abiotic stress-related processes in plants. Moreover, exogenous melatonin induces H2S generation in plants under salinity or heat stress. However, the involvement of H2S action in melatonin-induced Cd tolerance is still largely unknown. In this review, we summarize the progresses in various physiological and molecular mechanisms regulated by melatonin in plants under Cd stress. The complex interactions between melatonin and H2S in acquisition of Cd stress tolerance are also discussed.