Growth simulation and yield prediction for perennial jujube fruit tree by integrating age into the WOFOST model

peer reviewedMathematical models have been widely employed for the simulation of growth dynamics of annual crops, thereby performing yield prediction, but not for fruit tree species such as jujube tree (Zizyphus jujuba). The objectives of this study were to investigate the potential use of a modified WOFOST model for predicting jujube yield by introducing tree age as a key parameter. The model was established using data collected from dedicated field experiments performed in 2016–2018. Simulated growth dynamics of dry weights of leaves, stems, fruits, total biomass and leaf area index (LAI) agreed well with measured values, showing root mean square error (RMSE) values of 0.143, 0.333, 0.366, 0.624 t ha−1 and 0.19, and R2 values of 0.947, 0.976, 0.985, 0.986 and 0.95, respectively. Simulated phenological development stages for emergence, anthesis and maturity were 2, 3 and 3 days earlier than the observed values, respectively. In addition, in order to predict the yields of trees with different ages, the weight of new organs (initial buds and roots) in each growing season was introduced as the initial total dry weight (TDWI), which was calculated as averaged, fitted and optimized values of trees with the same age. The results showed the evolution of the simulated LAI and yields profiled in response to the changes in TDWI. The modelling performance was significantly improved when it considered TDWI integrated with tree age, showing good global (R2≥0.856, RMSE≤0.68 t ha−1) and local accuracies (mean R2≥0.43, RMSE≤0.70 t ha−1). Furthermore, the optimized TDWI exhibited the highest precision, with globally validated R2 of 0.891 and RMSE of 0.591 t ha−1, and local mean R2 of 0.57 and RMSE of 0.66 t ha−1, respectively. The proposed model was not only verified with the confidence to accurately predict yields of jujube, but it can also provide a fundamental strategy for simulating the growth of other fruit trees

Applying a Comprehensive Action Determination Model to Examine the Recycling Behavior of Taipei City Residents

With the occurrence of rapid global economic growth concerns about waste and its related effects on the environment are on the rise. There has been an increasing focus towards sustainable development and waste recycling as part of environmental sustainability strategies, and the encouraging of recycling behavior has received considerable attention from various environmental stakeholders. While numerous studies have used grounded theories such as the theory of planned behaviors and the norm activation model to examine environmental behaviors, a lack of consideration of other important variables in these studies has been revealed. This study aimed to address this gap by adopting the comprehensive action determination model, which comprises a wider group of influencing variables related to norms, intentions, situations, and habits. This model was tested using structural equation modelling with a sample of 386 valid questionnaires collected from Taipei City residents in the domain of recycling behaviors. Results indicated that awareness had a positive influence on personal norms towards recycling behaviors; social norms had a positive influence on personal norms towards recycling behaviors; attitudes had a positive influence on recycling intentions; social norms had a positive influence on recycling intentions; personal norms had a positive influence on recycling intentions; perceived behavior control had a positive influence on recycling intentions; recycling intentions had a positive influence on recycling behavior; and recycling habits had a positive influence on recycling behavior. However, findings did not support the positive impact of perceived behavioral control on recycling behavior

Field demonstration of distributed quantum sensing without post-selection

Distributed quantum sensing can provide quantum-enhanced sensitivity beyond the shot-noise limit (SNL) for sensing spatially distributed parameters. To date, distributed quantum sensing experiments have been mostly accomplished in laboratory environments without a real space separation for the sensors. In addition, the post-selection is normally assumed to demonstrate the sensitivity advantage over the SNL. Here, we demonstrate distributed quantum sensing in field and show the unconditional violation (without post-selection) of SNL up to 0.916 dB for the field distance of 240 m. The achievement is based on a loophole free Bell test setup with entangled photon pairs at the averaged heralding efficiency of 73.88%. Moreover, to test quantum sensing in real life, we demonstrate the experiment for long distances (with 10-km fiber) together with the sensing of a completely random and unknown parameter. The results represent an important step towards a practical quantum sensing network for widespread applications.Comment: 8 pages, 5 figure

Surface passivation effect by fluorine plasma treatment on ZnO for efficiency and lifetime improvement of inverted polymer solar cells

Zinc oxide (ZnO) is an important material for polymer solar cells (PSCs) where the characteristics of the interface can dominate both the efficiency and lifetime of the device. In this work we study the effect of fluorine (SF6) plasma surface treatment of ZnO films on the performance of PSCs with an inverted structure. The interaction between fluorine species present in the SF6 plasma and the ZnO surface is also investigated in detail. We provide fundamental insights into the passivation effect of fluorine by analyzing our experimental results and theoretical calculations and we propose a mechanism according to which a fluorine atom substitutes an oxygen atom or occupies an oxygen vacancy site eliminating an electron trap while it may also attract hydrogen atoms thus favoring hydrogen doping. These multiple fluorine roles can reduce both the recombination losses and the electron extraction barrier at the ZnO/fullerene interface improving the selectivity of the cathode contact. Therefore, the fabricated devices using the fluorine plasma treated ZnO show high efficiency and stable characteristics, irrespective of the donor : acceptor combinations in the photoactive blend. Inverted polymer solar cells, consisting of the P3HT:PC71BM blend, exhibited increased lifetime and high power conversion efficiency (PCE) of 4.6%, while the ones with the PCDTBT:PC71BM blend exhibited a PCE of 6.9%. Our champion devices with the PTB7:PC71BM blends reached a high PCE of 8.0% and simultaneously showed exceptional environmental stability when using the fluorine passivated ZnO cathode interlayers

An improved method for predicting truncated multiple recursive generators with unknown parameters

Multiple recursive generators are an important class of pseudorandom number generators which are widely used in cryptography. The predictability of truncated sequences that predict the whole sequences by the truncated high-order bits of the sequences is not only a crucial aspect of evaluating the security of pseudorandom number generators but also serves an important role in the design of pseudorandom number generators. This paper improves the work of Sun et al on the predictability of truncated multiple recursive generators with unknown parameters. Given a few truncated digits of high-order bits output by a multiple recursive generator, we adopt the resultant, the Chinese Remainder Theorem and the idea of recovering $p$-adic coordinates of the coefficients layer by layer, and Kannan\u27s embedding technique to recover the modulus, the coefficients and the initial state, respectively. Experimental results show that our new method is superior to that of the work of Sun et al, no matter in terms of the running time or the number of truncated digits required

Applying Factor Analysis Combined with Kriging and Information Entropy Theory for Mapping and Evaluating the Stability of Groundwater Quality Variation in Taiwan

In Taiwan many factors, whether geological parent materials, human activities, and climate change, can affect the groundwater quality and its stability. This work combines factor analysis and kriging with information entropy theory to interpret the stability of groundwater quality variation in Taiwan between 2005 and 2007. Groundwater quality demonstrated apparent differences between the northern and southern areas of Taiwan when divided by the Wu River. Approximately 52% of the monitoring wells in southern Taiwan suffered from progressing seawater intrusion, causing unstable groundwater quality. Industrial and livestock wastewaters also polluted 59.6% of the monitoring wells, resulting in elevated EC and TOC concentrations in the groundwater. In northern Taiwan, domestic wastewaters polluted city groundwater, resulting in higher NH3-N concentration and groundwater quality instability was apparent among 10.3% of the monitoring wells. The method proposed in this study for analyzing groundwater quality inspects common stability factors, identifies potential areas influenced by common factors, and assists in elevating and reinforcing information in support of an overall groundwater management strategy