Search

One of the areas that show the most visible effects of human-induced land alterations is also the world's most essential resource: water. Decision-makers in arid regions face considerable difficulties in providing and maintaining sustainable water resource management. However, developing appropriate and straightforward approaches for quantifying water use in arid/hyper-arid regions is still a formidable challenge. Meanwhile, a better knowledge of the effects of land use land cover (LULC) changes on natural resources and environmental systems is required. The purpose of this study was to quantify the water consumption in a hyper-arid region (New Valley, Egypt) using two different approaches—LULC based on optical remote sensing data and groundwater storage changes based on Gravity Recovery Climate Experiment (GRACE) satellite data—and to compare and contrast the quantitative results of the two approaches. The LULC of the study area was constructed from 1986 to 2021 to identify the land cover changes and investigate the primary water consumption patterns. The analysis of groundwater storage changes utilized two GRACE mascon solutions from 2002 to 2021 in New Valley. The results showed an increase in agricultural areas in New Valley's oases. They also showed an increased in irrigation water usage and a continuous decrease in the groundwater storage of New Valley. The overall water usage in New Valley for domestic and irrigation was calculated as 18.62 km3 (0.93 km3/yr) based on the LULC estimates. Moreover, the groundwater storage changes of New Valley were extracted using GRACE and calculated to be 19.36 ± 7.96 km3 (0.97 ± 0.39 km3/yr). The results indicated that the water use calculated from LULC was consistent with the depletion in groundwater storage calculated by applying GRACE. This study provides an essential reference for regional sustainability and water resource management in arid/hyper-arid regions. [ABSTRACT FROM AUTHOR]

There is great demand for high-performance, low-cost electrode materials for anodes of lithium-ion batteries (LIBs). Herein, we report the recovery of carbon materials by treating waste tire rubber via a facile one-step carbonization process. Electrochemical studies revealed that the waste tire carbon anode had a higher reversible capacity than that of commercial graphite and shows the positive effect of ZnS in the waste tire carbon. When used as the anode for LIBs, waste tire carbon shows a high specific capacity of 510.6 mAh·g−1 at 100 mA·g−1 with almost 97% capacity retention after 100 cycles. Even at a high rate of 1 A·g−1, the carbon electrode presents an excellent cyclic capability of 255.1 mAh·g−1 after 3000 cycles. This high-performance carbon material has many potential applications in LIBs and provide an alternative avenue for the recycling of waste tires. [ABSTRACT FROM AUTHOR]

The further deployment of silicon-based anode materials is hindered by their poor rate and cycling abilities due to the inferior electrical conductivity and large volumetric changes. Herein, we report a silicon/carbon nanotube (Si/CNT) composite made of an externally grown flexible carbon nanotube (CNT) network to confine inner multiple Silicon (Si) nanoparticles (Si NPs). The in situ generated outer CNTs networks, not only accommodate the large volume changes of inside Si NPs but also to provide fast electronic/ionic diffusion pathways, resulting in a significantly improved cycling stability and rate performance. This Si/CNT composite demonstrated outstanding cycling performance, with 912.8 mAh g−1 maintained after 100 cycles at 100 mA g−1, and excellent rate ability of 650 mAh g−1 at 1 A g−1 after 1000 cycles. Furthermore, the facial and scalable preparation method created in this work will make this new Si-based anode material promising for practical application in the next generation Li-ion batteries. [ABSTRACT FROM AUTHOR]

PA66/surface-modified multi-walled carbon nanotubes (MWNTs) composite fibers with a better dispersion and a stronger interfacial interaction between MWNTs and polyamide 66 (PA66) matrix were fabricated via the method of ball milling and melt-spinning. The effects of unmodified (U-MWNTs), acid-modified (MWNTs-COOH) and sodium dodecyl benzenesulfonate-modified MWNTs (MWNTs-SDBS) on the physical mechanical and thermal properties of PA66 were investigated. The results show that, the surface modified nanotube can provide homogeneous dispersion and there is a strong interfacial bonding between PA66 and MWNTs-COOH. A homogeneous dispersion of MWNTs in PA66 matrices without agglomeration is obtained by a facile ball milling method, which can increase the utilization ratio of MWNTs, reduce the required amount of MWNTs and ultimately improve the mechanical properties at a lower filler loading. The tensile strength of composite fibers reaches a maximum which respectively improved by 27% and 24% than that of PA66 fibers, when the mass fraction of MWNTs-SDBS and MWNTs-COOH is 0.1%. It is helpful for decrease the producing cost of the composite fibers. Moreover, the incorporation of MWNTs into PA66 improves the crystallizing temperature, crystallinity and thermal stability. The research shows that a novel facile method is developed for the fabrication of polymer composite fiber. [ABSTRACT FROM AUTHOR]

Patients with terminal cancers commonly receive aggressive and sub-optimal treatment near the end of life, which may not be beneficial in terms of duration or quality of life. To improve end-of-life care, it is essential to develop methods that can accurately predict the short-term risk of death. However, most prediction models for patients with cancer are static in the sense that they only use patient features at a fixed time. We proposed a dynamic prediction model (DPM) that can incorporate time-dependent predictors. We apply this method to patients with advanced non-small-cell lung cancer from a real-world database. Inverse probability of censoring weighted AUC with bootstrap inference was used to compare predictions among models. We found that increasing ECOG performance status and decreasing albumin had negative prognostic associations with overall survival (OS). Moreover, the negative prognostic implications strengthened over the patient disease course. DPMs using both time-independent and time-dependent predictors substantially improved short-term prediction accuracy compared to Cox models using only predictors at a fixed time. The proposed model can be broadly applied for prediction based on longitudinal data, including an estimation of the dynamic effects of time-dependent features on OS and updating predictions at any follow-up time.