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The development of polyaniline (PANI)/biomaterial composites as humidity sensor materials represents an emerging area of advanced materials with promising applications. The increasing attention to biopolymer materials as desiccants for humidity sensor components can be explained by their sustainability and propensity to absorb water. This review represents a literature survey, covering the last decade, which is focused on the interrelationship between the core properties and moisture responsiveness of multicomponent polymer/biomaterial composites. This contribution provides an overview of humidity-sensing materials and the corresponding sensors that emphasize the resistive (impedance) type of PANI devices. The key physicochemical properties that affect moisture sensitivity include the following: swelling, water vapor adsorption capacity, porosity, electrical conductivity, and enthalpies of adsorption and vaporization. Some key features of humidity-sensing materials involve the response time, recovery time, and hysteresis error. This work presents a discussion on various types of humidity-responsive composite materials that contain PANI and biopolymers, such as cellulose, chitosan and structurally related systems, along with a brief overview of carbonaceous and ceramic materials. The effect of additive components, such as polyvinyl alcohol (PVA), for film fabrication and their adsorption properties are also discussed. The mechanisms of hydration and proton transfer, as well as the relationship with conductivity is discussed. The literature survey on hydration reveals that the textural properties (surface area and pore structure) of a material, along with the hydrophile–lipophile balance (HLB) play a crucial role. The role of HLB is important in PANI/biopolymer materials for understanding hydration phenomena and hydrophobic effects. Fundamental aspects of hydration studies that are relevant to humidity sensor materials are reviewed. The experimental design of humidity sensor materials is described, and their relevant physicochemical characterization methods are covered, along with some perspectives on future directions in research on PANI-based humidity sensors.

Climatic extremes have adverse concurrent and lagged effects on terrestrial carbon cycles. Here, a concurrent effect refers to the occurrence of a latent impact during climate extremes, and a lagged effect appears sometime thereafter. Nevertheless, the uncertainties of these extreme drought effects on net carbon uptake and the recovery processes of vegetation in different Tibetan Plateau (TP) ecosystems are poorly understood. In this study, we calculated the Standardised Precipitation–Evapotranspiration Index (SPEI) based on meteorological datasets with an improved spatial resolution, and we adopted the Carnegie–Ames–Stanford approach model to develop a net primary production (NPP) dataset based on multiple datasets across the TP during 1982–2015. On this basis, we quantised the net reduction in vegetation carbon uptake (NRVCU) on the TP, investigated the spatiotemporal variability of the NPP, NRVCU and SPEI, and analysed the NRVCUs that are caused by the concurrent and lagged effects of extreme drought and the recovery times in different ecosystems. According to our results, the Qaidam Basin and most forest regions possessed a significant trend towards drought during 1982–2015 (with Slope of SPEI < 0, P < 0.05), and the highest frequency of extreme drought events was principally distributed in the Qaidam Basin, with three to six events. The annual total net reduction in vegetation carbon uptake on the TP experienced a significant downward trend from 1982 to 2015 (−0.0018 ± 0.0002 PgC year−1, P < 0.001), which was negatively correlated with annual total precipitation and annual mean temperature (P < 0.05). In spatial scale, the NRVCU decrement was widely spread (approximately 55% of grids) with 17.86% of the area displaying significant declining trends (P < 0.05), and the sharpest declining trend (Slope ≤ −2) was mainly concentrated in southeastern TP. For the alpine steppe and alpine meadow ecosystems, the concurrent and lagged effects of extreme drought induced a significant difference in NRVCU (P < 0.05), while forests presented the opposite results. The recovery time comparisons from extreme drought suggest that forests require more time (27.62% of grids ≥ 6 years) to recover their net carbon uptakes compared to grasslands. Therefore, our results emphasise that extreme drought events have stronger lagged effects on forests than on grasslands on the TP. The improved resilience of forests in coping with extreme drought should also be considered in future research.

Background Multidrug-resistant tuberculosis (MDR-TB) is caused by bacteria that are resistant to the most effective anti-tuberculosis drug. The MDR-TB is an increasing global problem and the spread of MDR-TB has different recovery time for different patients. Therefore, this study aimed to investigate the recovery time of MDR-TB patients in Amhara region, Ethiopia. Method A retrospective study was carried out in seven hospitals having MDR-TB treatment center of Amhara region, Ethiopia from September 2015 to February 2018. An accelerated failure time and parametric shared frailty models were employed. Results The study revealed that the recovery time of MDR-TB patients in Amhara region was 21 months. Out of the total MDR-TB patients, 110 (35.4%) censored and 201 (64.6%) cured of MDR-TB. The clustering effect of frailty model was hospitals and the Weibull-gamma shared frailty model was selected among all and hence used for this study. The study showed that extra pulmonary MDR-TB patients had longer recovery time than that of seamier pulmonary MDR-TB patients in Amhara region, Ethiopia. According to this study, male MDR-TB patients, MDR-TB patients with co-morbidity and clinical complication were experiencing longer recovery time than that of the counter groups. This study also showed that MDR-TB patients with poor adherence had longer recovery time than those with good adherence MDR-TB patients. Conclusion Among different factors considered in this study, MDR-TB type, clinical complication, adherence, co-morbidities, sex, and smoking status had a significant effect on recovery time of MDR-TB patients in Amhara region, Ethiopia. In conclusion, the Regional and Federal Government of Ethiopia should take immediate steps to address causes of recovery time of MDR-TB patients in Amhara region through encouraging adherence, early case detection, and proper handling of drug-susceptibility according to WHO guidelines.

Among other approaches, camera trap distance sampling (CTDS) is used to estimate animal abundance from unmarked populations. It was formulated for videos and observation distances are measured at predetermined ‘snapshot moments’. Surveys recording still images with passive infrared motion sensors suffer from frequent periods where animals are not photographed, either because of technical delays before the camera can be triggered again (i.e. ‘camera recovery time’) or because they remain stationary and do not immediately retrigger the camera following camera recovery time (i.e. ‘retrigger delays’). These effects need to be considered when calculating temporal survey effort to avoid downwardly biased abundance estimates. Here, we extend the CTDS model for passive infrared motion sensor recording of single images or short photo series. We propose estimating ‘mean time intervals between triggers’ as combined mean camera recovery time and mean retrigger delays from the time interval distribution of pairs of consecutive pictures, using a Gamma and Exponential function, respectively. We apply the approach to survey data on red deer, roe deer and wild boar. Mean time intervals between triggers were very similar when estimated empirically and when derived from the model‐based approach. Depending on truncation times (i.e. the time interval between consecutive pictures beyond which data are discarded) and species, we estimated mean time intervals between retriggers between 8.28 and 15.05 s. Using a predefined snapshot interval, not accounting for these intervals, would lead to underestimated density by up to 96% due to overestimated temporal survey effort. The proposed approach is applicable to any taxa surveyed with camera traps. As programming of cameras to record still images is often preferred over video recording due to reduced consumption of energy and memory, we expect this approach to find broad application, also for other camera trap methods than CTDS.

Background Increased intracranial pressure (ICP) in patients with hypertensive intracerebral hemorrhage (HICH) has been associated with poor prognosis. The transsylvian insular approach (TIA) and the transcortical (TCA) approach are applied for patients with HICH. We aimed to compare the postoperative ICP parameters of TIA and TCA to identify which procedure yields better short-term outcomes in patients with basal ganglia hematoma volumes ranging from 30 to 50 mL. Methods Eighty patients with basal ganglia hematomas 30–50 mL were enrolled in this study. Patients were implanted with ICP probes and divided into TIA and TCA groups according to the procedure. The ICP values were continuously recorded for five days at four-hour intervals. Short-term outcomes were evaluated using the length of hospitalization and postoperative consciousness recovery time. Results No statistically significant differences were found in age, sex, GCS score at admission, hematoma volume, and hematoma clearance rate (p > 0.05). The results showed that postoperative initial ICP, ICP on the first postoperative day, mean ICP, DICP20 mmHg × 4 h, postoperative consciousness recovery time, the length of hospitalization, mannitol utilization rate and the mannitol dosage were lower in the TIA group than in the TCA group (p < 0.05). Postoperative consciousness recovery time was positively correlated with ICP on the first postoperative day, and the length of hospitalization was positively correlated with mean ICP. Conclusions TIA is more effective than TCA in improving the short-term outcomes of patients with basal ganglia hematoma volumes ranging from 30 to 50 mL according to comparisons of postoperative ICP parameters.

In modern corporate environments, having a disaster recovery solution is no longer a luxury but a business necessity. The adoption of a disaster recovery solution, however, can be costly and often only affordable by large enterprises. Disaster-Recovery-as-a-Service (DRaaS) is a cloud-based solution that small and medium-sized businesses have been adopting to guarantee availability even in catastrophic situations. It offers lower acquisition and operational costs than traditional solutions. This work presents availability models for evaluating a DRaaS solution taking into account crucial disaster recovery metrics, such as downtime, costs, recovery time objective, and transaction loss. Furthermore, we performed sensitivity analysis on the DRaaS model to determine the parameters that cause the greatest impact on the system availability. Based on these analyses, disaster recovery coordinators can determine the optimum point to recover the damaged system by balancing the cost of system downtime against the cost of resources required for restoring the system. Our numerical results show the effectiveness of a DRaaS solution in terms of downtime, cost, and transition loss.

Drought imposes severe, long-term effects on global environments and ecosystems. A better understanding of how long it takes a region to recover to pre-drought conditions after drought is essential for addressing future ecology risks. In this study, drought-related variables were obtained using remote sensing and reanalysis products for 2003 to 2016. The meteorological drought index [standardized precipitation evapotranspiration index (SPEI)] and agricultural drought index [vegetation condition index (VCI)] were employed to estimate drought duration time (DDT) and drought recovery time (DRT). To the basin’s west, decreasing rainfall and increasing potential evapotranspiration led to decreasing SPEI. On the east side, decreasing soil moisture from each depth effects vegetation condition, which results in a decreasing gross primary productivity and VCI. Extreme meteorological drought events are likely to occur in the basin’s northeastern and middle western areas, while the southern basin is more likely to suffer from extreme agricultural drought events. The mean SPEI-based DDT (2.45 months) was smaller than the VCI-based DDT (2.97 months); the average SPEI-based DRT (2.02 months) was larger than the VCI-based DRT (1.63 months). Most of the area needs 1 or 2 months to recover from drought except for the basin’s northwestern area, where the DRT is more than 8 months. DDT is the most important parameter in determining DRT. These results provide useful information about regional drought recovery that will help local governments looking to mitigate potential environmental risks and formulate appropriate agricultural policies in Lake Victoria Basin.

Performance of an electronic device relies heavily on the availability of a suitable functional material. One of the simple, easy, and cost-effective ways to obtain novel functional materials with improved properties for desired applications is to make composites of selected materials. In this work, a novel composite of transparent n-type zinc oxide (ZnO) with a wide bandgap and a unique structure of graphene in the form of a graphene flower (GrF) is synthesized and used as the functional layer of a humidity sensor. The (GrF/ZnO) composite was synthesized by a simple sol–gel method. Morphological, elemental, and structural characterizations of GrF/ZnO composite were performed by a field emission scanning electron microscope (FESEM), energy-dispersive spectroscopy (EDS), and an x-ray diffractometer (XRD), respectively, to fully understand the properties of this newly synthesized functional material. The proposed humidity sensor was tested in the relative humidity (RH) range of 15% RH% to 86% RH%. The demonstrated sensor illustrated a highly sensitive response to humidity with an average current change of 7.77 μA/RH%. Other prominent characteristics shown by this device include but were not limited to high stability, repeatable results, fast response, and quick recovery time. The proposed humidity sensor was highly sensitive to human breathing, thus making it a promising candidate for various applications related to health monitoring.

It is shown that capacitance–frequency characterization can help to derive the optimization limits for radiation optimization of the transient properties of the rectifiers. Measurements of the current–voltage, capacitance–voltage, capacitance–frequency characteristics, and reverse recovery profiling were provided for silicon-based rectifiers. p – n -junction rectifiers were irradiated by 5 MeV electrons with fluences from 10 14 to 10 15 cm –2 . It is shown that reverse-recovery time decreases after 5 MeV electron irradiation and this decreasing changes monotonously with irradiation dose (from 2.2 ms to 15 µs for 10 15 cm –2 ). At the same time, series resistance increases dramatically (from 0.5 to 90 Ω); it indicates strong degradation of the high-frequency properties. Next criteria for optimal radiation dose can be used: the irradiation level associated with the maximum of boundary frequency indicates the optimum in terms of switching speed. Before this dose, maximum frequency is limited by reverse-recovery time of diode. After this dose, the limiting factor is the relaxation time of RC -circuit, where R is the series resistance of the diode and C is the capacitance of the SRC -region.

This paper analyzed the factors that influence the seismic resilience of urban building groups and studied the laws that influence internal factors and external factors. Based on the data from the first national comprehensive risk survey of natural disasters, a refined classification study of urban building groups was carried out. Based on the existing evaluation methods of seismic resilience of individual buildings, the recovery time was selected as the resilience evaluation index to calculate the effect of internal factors on the seismic resilience of urban building groups. Then, we studied the quantitative relationship between external factors (i.e., disaster relief capacity, population density, and economic level) and the evaluation indicators of seismic resilience of urban building groups, and we proposed the kilometer grid coefficient. Based on that, we proposed a calculation method of the effect of external factors on the seismic resilience of urban building groups. Considering the influence of internal and external factors, the evaluation model for the seismic resilience of urban building groups was established. And the model was applied in a typical city. This paper proposes a method to evaluate the seismic resilience of urban building groups, which can master the functional recovery time of urban building groups after an earthquake. Based on the proposed model, we can optimize the functional recovery path and emergency rescue path of the disaster area, as well as improve the resilience of urban building systems and the construction of resilient cities.