Factors Driving Changes in Vegetation in Mt. Qomolangma (Everest): Implications for the Management of Protected Areas

The Mt. Qomolangma (Everest) National Nature Preserve (QNNP) is among the highest natural reserves in the world. Monitoring the spatiotemporal changes in the vegetation in this complex vertical ecosystem can provide references for decision makers to formulate and adapt strategies. Vegetation growth in the reserve and the factors driving it remains unclear, especially in the last decade. This study uses the normalized difference vegetation index (NDVI) in a linear regression model and the Breaks for Additive Seasonal and Trend (BFAST) algorithm to detect the spatiotemporal patterns of the variations in vegetation in the reserve since 2000. To identify the factors driving the variations in the NDVI, the partial correlation coefficient and multiple linear regression were used to quantify the impact of climatic factors, and the effects of time lag and time accumulation were also considered. We then calculated the NDVI variations in different zones of the reserve to examine the impact of conservation on the vegetation. The results show that in the past 19 years, the NDVI in the QNNP has exhibited a greening trend (slope = 0.0008/yr, p < 0.05), where the points reflecting the transition from browning to greening (17.61%) had a much higher ratio than those reflecting the transition from greening to browning (1.72%). Shift points were detected in 2010, following which the NDVI tendencies of all the vegetation types and the entire preserve increased. Considering the effects of time lag and time accumulation, climatic factors can explain 44.04% of the variation in vegetation. No climatic variable recorded a change around 2010. Considering the human impact, we found that vegetation in the core zone and the buffer zone had generally grown better than the vegetation in the test zone in terms of the tendency of growth, the rate of change, and the proportions of different types of variations and shifts. A policy-induced reduction in livestock after 2010 might explain the changes in vegetation in the QNNP.

Biosynthesis of α-Fe2O3-CdO Nanocomposites for Electrochemical Detection of Chloridazon Herbicide

Biosynthesised α-Fe2O3-CdO electrochemical nanosensor attained from Coriandrum sativum leaves extract and fabricated on the screen-printed electrode to detect chloridazon (CLZ) herbicide in agricultural food samples. Scanning electron microscopy, energy dispersive x-ray analysis, X-ray diffraction spectroscopy, cyclic voltammetry, and differential pulse voltammetry were used to investigate the α-Fe2O3-CdO electrochemical nanosensor. The optimization factors of the effect of pH, accumulation time, accumulation potential, and foreign substances were elevated. The α-Fe2O3-CdO/SPE electrochemical nanosensor shows the significant voltammetric response for the CLZ detection. Foreign substances did not considerably influence pesticide detection. Dynamic linear CLZ plot for a standard solution of CLZ was obtained in the concentration range of 0.1 to 36.00 µg⸳mL-1 (R=0.995) with a limit of detection 0.059 µg⸳mL-1 and a quantification limit of 0.179 µg⸳mL-1. The proposed electrochemical nanosensor was used to detect CLZ in agricultural food samples and agreeable recovery results.

A Synchronization Acquisition Method for the Dual-Sequence-Frequency-Hopping Communication System Based on Software Defined Radio at Low SNR

The Dual-Sequence-Frequency-Hopping (DSFH) communication system based on software defined radio (SDR) system belongs to the field of information and communication security of software engineering. At very low signal-to-noise ratio (SNR), which is lower than -10dB, the DSFH fails to synchronize. Synchronization acquisition method via a combined multi-signal detection (SAMCMD) is proposed. The feature of a short sequence of frequency hopping (FH) frequency point is utilized to express the information of the time of date (TOD), and the time accumulation of several FH signals is used to extend the detection time. This method can not only be appropriate for DSFH but also greatly improve the synchronization performance at low SNR. Explain the principle and structure of the SAMCMD. And obtain the performance of this method of the SDR synchronization acquisition. The conclusions are as below: 1) the longer detection time is, the better the anti-jamming performance of SAMCMD is; 2) SAMCMD can gain about 22.5dB-24dB when the SNR is -20dB and the acquisition probability requirement is 96.31% due to the extension of the detection time, compared with the traditional FH synchronization acquisition method.

Accumulation of heavy metals (As, Cd, Pb, Hg) on brown algae, Padina australis, cultivated in Kima Bajo Waters, North Minahasa Regency

Although heavy metals have relatively low levels in water column and sediments, they will not be degraded and can even be absorbed and accumulated by marine algae. Research on accumulation of heavy metals on algae was done in Kima Bajo Waters, North Minahasa Regency. The research objective was to evaluate the accumulation of four heavy metals, i.e. arsenic (As), cadmium (Cd), plumbum (Pb), and mercury (Hg), on brown macroalgae Padina australis. The alga was introduced and cultivated in the research area using bottom method. The same method was also used in the experiment. One-week acclimatization process was done prior the experiment. Sampling of alga’s thallus was carried out every two weeks to measure the concentration of metals. The experiment was terminated after six weeks. Bottom sediment was also collected at the beginning of the experiment to measure the metal concentration. The results showed that the heavy metals (As, Cd, Pb, and Hg) were accumulated in the algae. The highest concentration of Cd, Pb, and Hg accumulated in the algae was 0.15 mg/kg wet weight, 3.5 mg/kg wet weight, and 0.009 mg/kg wet weight, respectively. All the concentrations were higher than the initial concentration of each metal. Accumulation of As was also occurred with the highest concentration (1,9 mg/kg wet weigh) occurred at fourth weeks; however, it was lower than the initial concentration. The accumulation varied according to type of metals and time; accumulation of Cd, Pb, and Hg were occurred on second weeks of cultivations and As on the fourth weeks. It can be concluded that cultivated alga can accumulate heavy metals.Indonesian title: Akumulasi logam berat (As, Cd, Pb, Hg) pada alga coklat, Padina australis, yang dibudidaya di Perairan Kima Bajo, Kabupaten Minahasa Utara

Pavlovian conditioning under partial reinforcement: The effects of non-reinforced trials versus cumulative CS duration

A core feature of associative models, such as those proposed by Allan Wagner (Rescorla &amp; Wagner, 1972; Wagner, 1981), is that conditioning proceeds in a trial-by-trial fashion, with increments and decrements in associative strength occurring on each occasion that the conditioned stimulus (CS) is present either with or without the unconditioned stimulus (US). A very different approach has been taken by theories that assume animals continuously accumulate information about the total length of time spent waiting for the US both during the CS and in the absence of the CS (e.g., Gallistel &amp; Gibbon, 2000). Here we describe three experiments using within-subject designs that tested between trial-based and time-accumulation accounts of the acquisition of conditioned responding using magazine approach conditioning in rats. We found that responding was affected by the total (cumulative) duration of exposure to the CS without the US rather than the number of trials on which the CS occurred without the US. We also found that exposure to the CS without the US had the same effect on conditioning whether that exposure occurred shortly (60 s) before each CS-US pairing or whether it occurred long (240 s) before each pairing. These findings are more consistent with time-accumulation models of conditioning than trial-based models like the Rescorla-Wagner model and Wagner’s (1981) Sometimes Opponent Process model. We discuss these findings in relation to other evidence that favours trial-based models rather than time-accumulation models.