Reservoir volume optimization and performance evaluation of rooftop catchment systems in arid regions: A case study of Birjand,Iran

This study evaluated the performance of rooftop catchment systems in securing non-potable water supply in Birjand, located in an arid area in southeastern Iran. The rooftop catchment systems at seven study sites of different residential buildings were simulated for dry, normal, and wet water years, using 31-year rainfall records. The trial and error approach and mass diagram method were employed to optimize the volume of reservoirs in five different operation scenarios. Results showed that, during the dry water year from 2000 to 2001, for reservoirs with volumes of 200–20000 L, the proportion of days that could be secured for non-portable water supply was on average computed to be 16.4%–32.6% across all study sites. During the normal water year from 2009 to 2010 and the wet water year from 1995 to 1996, for reservoirs with volumes of 200–20000 L, the proportions were 20.8%–69.6% and 26.8%–80.3%, respectively. Therefore, a rooftop catchment system showed a high potential to meet a significant portion of non-potable water demand in the Birjand climatic region. Reservoir volume optimization using the mass diagram method produced results consistent with those obtained with the trial and error approach, except at sites #1, #2, and #5. At these sites, the trial and error approach performed better than the mass diagram method due to relatively high water consumption. It is concluded that the rooftop catchment system is applicable under the same climatic conditions as the study area, and it can be used as a drought mitigation strategy as well.     

IoT-Enabled Autonomous System Collaboration for Disaster-Area Management

Timely investigating post-disaster situations to locate survivors and secure hazardous sources is critical, but also very challenging and risky. Despite first responders putting their lives at risk in saving others, human-physical limits cause delays in response time, resulting in fatality and property damage. In this paper, we proposed and implemented a framework intended for creating collaboration between heterogeneous unmanned vehicles and first responders to make search and rescue operations safer and faster. The framework consists of unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), a cloud-based remote control station (RCS). A light-weight message queuing telemetry transport (MQTT) based communication is adopted for facilitating collaboration between autonomous systems. To effectively work under unfavorable disaster conditions, antenna tracker is developed as a tool to extend network coverage to distant areas, and mobile charging points for the UAVs are also implemented. The proposed framework’s performance is evaluated in terms of end-to-end delay and analyzed using architectural analysis and design language (AADL). Experimental measurements and simulation results show that the adopted communication protocol performs more efficiently than other conventional communication protocols, and the implemented UAV control mechanisms are functioning properly. Several scenarios are implemented to validate the overall effectiveness of the proposed framework and demonstrate possible use cases.      

A robust neural network model for fault detection in the presence of mislabelled data

Several data-driven methodologies for process monitoring and detection of faults or abnormalities have been developed for the safety of processing systems. The effectiveness of data-based models, however, is impacted by the volume and quality of training data. This work presents a robust neural network model for addressing the mislabelled and low-quality data in detecting faults and process abnormalities. The approach is based on harnessing data quality features along with supervisory labels in the network training. The data quality has been computed using the Mahalanobis distances and trusted centres of each class of data such as normal and faulty data. The method has been examined for detecting abnormalities in two case studies; a continuous stirred tank heater problem for detecting leaks and the Tennessee Eastman chemical process for detecting step and sticking faults. The performance of the proposed robust artificial neural networks (ANN) model is evaluated in terms of accuracy, fault detection rate, false alarm rate, and classification index at varying extents of mislabelling, namely, 1%, 5%, and 10% mislabelled data. The proposed model demonstrates higher detection performance, especially at increased labels of mislabelled data where the performance of the conventional ANN is severely impacted. The proposed methodology can be advantageous in handling mislabelled and low-quality data issues which are crucial in the data-driven modelling of processing systems.     

Impact of climate change on hydropower generation in Rio Jubones Basin,Ecuador

This study attempted to use the soil and water assessment tool(SWAT), integrated with geographic information systems(GIS), for assessment of climate change impacts on hydropower generation. This methodology of climate change impact modeling was developed and demonstrated through application to a hydropower plant in the Rio Jubones Basin in Ecuador. ArcSWAT 2012 was used to develop a model for simulating the river flow. The model parameters were calibrated and validated on a monthly scale with respect to the hydro-meteorological inputs observed from 1985 to 1991 and from 1992 to 1998, respectively. Statistical analyses produced Nash-Sutcliffe efficiencies(NSEs) of 0.66 and 0.61 for model calibration and validation, respectively, which were considered acceptable. Numerical simulation with the model indicated that climate change could alter the seasonal flow regime of the basin, and the hydropower potential could change due to the changing climate in the future.Scenario analysis indicates that, though the hydropower generation will increase in the wet season, the plant will face a significant power shortage during the dry season, up to 13.14% from the reference scenario, as a consequence of a 17% reduction of streamflow under an assumption of a 2.9℃ increase in temperature and a 15% decrease in rainfall. Overall, this study showed that hydrological processes are realistically modeled with SWAT and the model can be a useful tool for predicting the impact of climate change.     

Silk Fibroin as an Efficient Biomaterial for Drug Delivery,Gene Therapy,and Wound Healing

Silk fibroin (SF), an organic material obtained from the cocoons of a silkworm Bombyx mori, is used in several applications and has a proven track record in biomedicine owing to its superior compatibility with the human body, superb mechanical characteristics, and its controllable propensity to decay. Due to its robust biocompatibility, less immunogenic, non-toxic, non-carcinogenic, and biodegradable properties, it has been widely used in biological and biomedical fields, including wound healing. The key strategies for building diverse SF-based drug delivery systems are discussed in this review, as well as the most recent ways for developing functionalized SF for controlled or redirected medicines, gene therapy, and wound healing. Understanding the features of SF and the various ways to manipulate its physicochemical and mechanical properties enables the development of more effective drug delivery devices. Drugs are encapsulated in SF-based drug delivery systems to extend their shelf life and control their release, allowing them to travel further across the bloodstream and thus extend their range of operation. Furthermore, due to their tunable properties, SF-based drug delivery systems open up new possibilities for drug delivery, gene therapy, and wound healing.     

Activation of Piezo1 Increases Na,K-ATPase-Mediated Ion Transport in Mouse Lens

Lens ion homeostasis depends on Na,K-ATPase and NKCC1. TRPV4 and TRPV1 channels, which are mechanosensitive, play important roles in mechanisms that regulate the activity of these transporters. Here, we examined another mechanosensitive channel, piezo1, which is also expressed in the lens. The purpose of the study was to examine piezo1 function. Recognizing that activation of TRPV4 and TRPV1 causes changes in lens ion transport mechanisms, we carried out studies to determine whether piezo1 activation changes either Na,K-ATPase-mediated or NKCC1-mediated ion transport. We also examined channel function of piezo1 by measuring calcium entry. Rb uptake was measured as an index of inwardly directed potassium transport by intact mouse lenses. Intracellular calcium concentration was measured in Fura-2 loaded cells by a ratiometric imaging technique. Piezo1 immunolocalization was most evident in the lens epithelium. Potassium (Rb) uptake was increased in intact lenses as well as in cultured lens epithelium exposed to Yoda1, a piezo1 agonist. The majority of Rb uptake is Na,K-ATPase-dependent, although there also is a significant NKCC-dependent component. In the presence of ouabain, an Na,K-ATPase inhibitor, Yoda1 did not increase Rb uptake. In contrast, Yoda1 increased Rb uptake to a similar degree in the presence or absence of 1 µM bumetanide, an NKCC inhibitor. The Rb uptake response to Yoda1 was inhibited by the selective piezo1 antagonist GsMTx4, and also by the nonselective antagonists ruthenium red and gadolinium. In parallel studies, Yoda1 was observed to increase cytoplasmic calcium concentration in cells loaded with Fura-2. The calcium response to Yoda1 was abolished by gadolinium or ruthenium red. The calcium and Rb uptake responses to Yoda1 were absent in calcium-free bathing solution, consistent with calcium entry when piezo1 is activated. Taken together, these findings point to stimulation of Na,K-ATPase, but not NKCC, when piezo1 is activated. Na,K-ATPase is the principal mechanism responsible for ion and water homeostasis in the lens. The functional role of lens piezo1 is a topic for further study.     

Nontoxic and Naturally Occurring Active Compounds as Potential Inhibitors of Biological Targets in Liriomyza trifolii

In recent years, novel strategies to control insects have been based on protease inhibitors (PIs). In this regard, molecular docking and molecular dynamics simulations have been extensively used to investigate insect gut proteases and the interactions of PIs for the development of resistance against insects. We, herein, report an in silico study of (disodium 5′-inosinate and petunidin 3-glucoside), (calcium 5′-guanylate and chlorogenic acid), chlorogenic acid alone, (kaempferol-3,7-di-O-glucoside with hyperoside and delphinidin 3-glucoside), and (myricetin 3′-glucoside and hyperoside) as potential inhibitors of acetylcholinesterase receptors, actin, α-tubulin, arginine kinase, and histone receptor III subtypes, respectively. The study demonstrated that the inhibitors are capable of forming stable complexes with the corresponding proteins while also showing great potential for inhibitory activity in the proposed protein-inhibitor combinations.     

Effect of Humic Acid on Soil Physical and Chemical Properties,Microbial Community Structure,and Metabolites of Decline Diseased Bayberry

In recent years, bayberry decline disease has caused significant damage to the bayberry industry. In order to evaluate whether humic acid can be used to effectively control the disease, this research examined the nutritional growth and fruit quality of bayberry, soil physical and chemical properties, soil microbial community structure, and metabolites. Results indicated that the application of humic acid not only improved the vigor and fruit quality of diseased trees, but also increased the diversity of microbial communities in the rhizosphere soil. A great increase was observed in the relative abundance of bacterial genus Mycobacterium and Crossiella; fungal genus Fusarium and Coniosporium. In contrast, a significant decrease was observed in the relative abundance of bacterial genus Acidothermus, Bryobacter, Acidibacter, fungal genus of Geminibasidium and Mycena. Analysis of redundancies (RDA) for microbial communities and soil characteristics showed that the main four variables, including available nitrogen, phosphorus, potassium, and calcium, had a great effect on the composition of bacterial and fungal communities in bayberry rhizosphere soil at the genus level. The main four variables had a greater effect on bacterial communities than on fungal communities. In addition, ABC transporter, arginine and proline metabolism, galactose metabolism, and glutathione metabolism were significantly affected by humic acid, which changed the content of 81 metabolites including 58 significantly down-regulated metabolites such as isohexonic acid and carinitine, and 23 significantly up-regulated metabolites such as acidic acid, guaninosuccinate, lyxose, 2-monoolein, epicatechin, and pentonolactone. These metabolites also significantly correlated with rhizosphere soil microbiota at the phylum, order, and genus levels. In conclusion, the results demonstrated the role of humic acid on plant growth and fruit quality, as well as rhizosphere soil characteristics, microbiota, and secondary metabolites, which provides novel insights into the control of bayberry decline disease.     

交通量持续增长下大跨桥梁时变极值外推分析

随着交通运输行业的迅速发展,持续增长的交通荷载逐步成为威胁既有桥梁运营安全的重要因素。为了研究现有交通荷载持续增长对大跨桥梁安全水平的影响,提出考虑交通量区间增长的车载效应极值外推方法,采用基于\