Mesembryanthemum crystallinum is an annual succulent plant that is being used as an emerging healthy leafy vegetable. To investigate the growth and physiological response of M. crystallinum to artificial lighting, five different light treatments were applied at 150 µmol(photon) m-2 s-1, which were white (W), different rations of red/blue (B) (15, 40, and 70%B), and blue (100%B), respectively. Our results showed that plants could gain as much as edible leaf area and dry mass with a certain ratio of blue (40%) in comparison with W. Plants grown under 100%B resulted in reduced photosynthetic rate, leaf area, and fresh mass compared with W. Adding blue fraction in the light regime enhanced the photosynthetic performance by influencing the amount of chlorophyll (Chl), Chl a/b, and specific leaf area. Under red/blue treatments, the electron transport rate and effective quantum yield of both PSII and PSI increased, while the nitrate content was reduced and flavonoids and total antioxidant capacity were unaffected.
The adult human brain represents only 2 % of the body's total weight, however it is one of the most metabolically active organs in the mammalian body. Its high metabolic activity necessitates an efficacious waste clearance system. Besides the blood, there are two fluids closely linked to the brain and spinal cord drainage system: interstitial fluid (ISF) and cerebrospinal fluid (CSF). The aim of this review is to summarize the latest research clarifying the channels of metabolite removal by fluids from brain tissue, subarachnoid space (SAS) and brain dura (BD). Special attention is focused on lymphatic vascular structures in the brain dura, their localizations within the meninges, morphological properties and topographic anatomy. The review ends with an account of the consequences of brain lymphatic drainage failure. Knowledge of the physiological state of the clearance system is crucial in order to understand the changes related to impaired brain drainage.
Agriculture faces several challenges to use the available resources in a more environmentally sustainable manner. One of the most significant is to develop sustainable water management. The modern Internet of Things (IoT) techniques with real-time data collection and visualisation can play an important role in monitoring the readily available moisture in the soil. An automated Arduino-based low-cost capacitive soil moisture sensor has been calibrated and developed for data acquisition. A sensor- and soil-specific calibration was performed for the soil moisture sensors (SKU:SEN0193 - DFROBOT, Shanghai, China). A Repeatability and Reproducibility study was conducted by range of mean methods on clay loam, sandy loam and silt loam soil textures. The calibration process was based on the data provided by the capacitive sensors and the continuously and parallelly measured soil moisture content by the thermo-gravimetric method. It can be stated that the response of the sensors to changes in soil moisture differs from each other, which was also greatly influenced by different soil textures. Therefore, the calibration according to soil texture was required to ensure adequate measurement accuracy. After the calibration, it was found that a polynomial calibration function (R2 ≥ 0.89) was the most appropriate way for modelling the behaviour of the sensors at different soil textures.