Detection of gaps in sinusoids by frog auditory nerve fibers: importance in AM coding

Physiological studies were carried out in the frog (Rana pipiens pipiens) eighth nerve to determine: (i) whether the modulation rate or the silent gap was the salient feature that set the upper limit of time-locking to pulsed amplitude-modulated (PAM) stimuli, (ii) the gap detection capacity of individual eighth nerve fibers. Time-locked responses of 79 eighth nerve fibers to PAM stimuli (at the fiber's characteristic frequency) showed that the synchronization coefficient was a low-pass function of the modulation rate. In response to PAM stimuli having different pulse durations, a fiber gave rise to non-overlapping modulation transfer functions. The upper cut-off frequency of time locking was higher when tonepulses in PAM stimuli had shorter duration. The fact that the cut-off frequency was different for the different PAM series suggested that the AM rate was neither the sole, nor the main, determinant for the decay in time-locking at high AM rates. Gap detection capacity was determined for 69 eighth nerve fibers by assessing fiber's spiking activities to paired tone-pulses during an OFF-window and an ON-window. It was found that the minimum detectable gap of eighth nerve fibers ranged from 0.5 to 10 ms with an average of 1.23–2.16 ms depending on the duration of paired tone pulses. For each fiber, the minimum detectable gap was longer when the duration of tone pulses comprising the twin-pulse stimuli was more than four times longer. When the synchronization coefficient was plotted against the silent gap between tones pulses in the PAM stimuli, the gap response functions of a fiber as derived from multiple PAM series were equivalent to gap response functions deriving from twin-pulse series suggesting that it was the silent gap which primarily determined the upper limit of time-locking to PAM stimuli.Abbreviations MTF modulation transfer function - PAM pulse amplitude modulated - SAM sinusoidally amplitude modulated - SC synchronization coefficient - TW time window     

Bayesian signal extraction from noisy FT NMR spectra

Summary The statistical interpretation of the histogram representation of NMR spectra is described, leading to an estimation of the probability density function of the noise. The white-noise and Gaussian hypotheses are discussed, and a new estimator of the noise standard deviation is derived from the histogram strategy. The Bayesian approach to NMR signal detection is presented. This approach homogeneously combines prior knowledge, obtained from the histogram strategy, together with the posterior information resulting from the test of presence of a set of reference shapes in the neighbourhood of each data point. This scheme leads to a new strategy in the local detection of NMR signals in 2D and 3D spectra, which is illustrated by a complete peak-picking algorithm.     

Long-term changes in frequencies ofPythium iwayamai andP. paddicum in upland- and paddy-field soils

The long-term changes in the frequencies ofPythium iwayamai andP. paddicum in upland- and flooded paddy-field soils were compared. The frequencies of both species fell in both soils within the first 6 months after they had been buried. After 36 and 48 months,P. iwayamai showed higher frequency thanP. Paddicum in upland-field soil, whileP. paddicum showed higher frequency thanP. iwayamai in paddy-field soil. These findings indicate respectively higher colonization ability to organic matters ofP. iwayamai in upland-field soil andP. paddicum in paddy-field soil.This study was partly supported by a Grant-in-Aid (no. 63560048) from the Ministry of Education, Science and Culture, Japan.     

The Presence of (+)-S-Adenosyl-l-Methionine in the Rat Brain and Its Lack of Effect on Phenylethanolamine N-Methyltransferase Activity

Abstract: (+)-S-Adenosyl- l -methionine [(+)-SAM] was isolated from rat brain and was quantified by HPLC followed by UV spectrophotometric measurements and by ¹H-NMR. Its estimated ratio in brain is 3% of total SAM. Because of its commercial unavailability, (+)-SAM was also prepared from chemically synthesized SAM by separation of the two diastereoisomers on a preparative reverse-phase Nucleosil C8 column. The (+) diastereoisomer thus obtained was then assayed in vitro both as an inhibitor and a substrate of phenylethanolamine N -methyltransferase. Enzymatic activity was measured by HPLC analysis. It was shown that (+)-SAM has no effect on phenylethanolamine N -methyltransferase activity; therefore, it is unlikely that (+)-SAM plays any possible role in regulation of adrenaline synthesis in the brain.     

Object detection by honeybees: Why do they land on edges?

Behavioural experiments using a variety of experimental situations (Figs. 1, 3, 6, 7, 9) were conducted to investigate the visual cues which bees use in the task of object-ground discrimination. The bees' flight and landing behaviour was video-filmed throughout the experiments. The evaluation of the video data shows that bees trained to find a randomly textured figure raised above a similarly textured ground land mainly on the boundaries of the figure, facing its inner surface (Fig. 2a, b). Bees can also be trained to find a hole, i.e. a low texture viewed through a window cut in a raised texture, but these bees are not attracted to the edges of the hole (Fig. 5a, b). Bees trained to a single edge between a low and a raised random texture land at the edge mainly facing the raised side (Table 1). Bees approaching the edge from the high side cross the edge in most cases without landing on it (Table 1). Bees trained to an edge between 2 striped patterns, one raised above the other, again land on the edge facing the raised pattern, regardless of whether the stripes on the 2 patterns run parallel or perpendicular to each other or to the edge (Fig. 8). In this case, the bees acquire range information by flying in oblique directions with respect to the orientation of the stripes (Fig. 10). All of the results suggest that the edge elicits landings when the bee perceives a local increase in the speed of image motion, signalling an abrupt decrease in range. This is corroborated by the results of further experiments in which artificial motion was used to simulate range differences between the two sides of an edge (Table 2). We conclude that image speed is a powerful cue in range discrimination as well as object detection. Dedicated to G. Adrian Horridge on the occasion of his retirement     

Water conditions influence the detectability of Crossodactylus gaudichaudii (Anura,Hylodidae) in streams of the Atlantic Forest

Stream-dwelling amphibians' occurrence, behaviour and reproductive success are strongly influenced by dynamic abiotic factors, for example, water flow and spray. These factors can disproportionately affect these frogs due to their dependency on specific favourable conditions for development and incapacity to disperse from unfavourable environments. We analysed the influence of environmental covariates on the detectability of Crossodactylus gaudichaudii, an amphibian species endemic to streams in the Brazilian Atlantic Forest. We conducted sampling in the streams of the Duas Bocas Biological Reserve, Brazil, and we measured air and water temperature, air humidity and pH of water on each sampling occasion. We estimated the effects of variables on the detectability of the species using single-season occupancy models. Our results indicated that the detectability of the species increases on occasions with higher water temperatures (24–26°C) and lower pH (5.0–5.5). We investigated the influence of these covariates only on the detectability of adult frogs, but it is likely that the physiochemical properties of stream water are more important to aquatic larvae, and hence, the probability of their detection. Given this, further studies should examine the relevance of covariates on the detectability of adult frogs as well as larvae.     

Nanostructured material-based optical and electrochemical detection of amoxicillin antibiotic

The penicillin derivative amoxicillin (AMX) plays an important role in treating various types of infections caused by bacteria. However, excessive use of AMX may have negative health effects. Therefore, it is of utmost importance to detect and quantify the AMX in pharmaceutical drugs, biological fluids, and environmental samples with high sensitivity. Therefore, this review article provides valuable and up-to-date information on nanostructured material-based optical and electrochemical sensors to detect AMX in various biological and chemical samples. The role of using different nanostructured materials on the performance of important optical sensors such as colorimetric sensors, fluorescence sensors, surface-enhanced Raman scattering sensors, chemiluminescence/electroluminescence sensors, optical immunosensors, optical fibre-based sensors, and several important electrochemical sensors based on different electrode types have been discussed. Moreover, nanocomposites, polymer, and MXenes-based electrochemical sensors have also been discussed, in which such materials are being used to further enhance the sensitivity of these sensors. Furthermore, nanocomposite-based photo-electrochemical sensors and the market availability of biosensors including AMX have also been discussed briefly. Finally, the conclusion, challenges, and future perspectives of the above-mentioned sensing techniques for AMX detection are presented.     

Searching by parts: Towards fine-grained image retrieval respecting species correlation

Most of the existing works on fine-grained image categorization and retrieval focus on finding similar images from the same species and often give little importance to inter-species similarities. However, these similarities may carry species correlations such as the same ancestors or similar habits, which are helpful in taxonomy and understanding biological traits. In this paper, we devise a new fine-grained retrieval task that searches for similar instances from different species based on body parts. To this end, we propose a two-step strategy. In the first step, we search for visually similar parts to a query image using a deep convolutional neural network (CNN). To improve the quality of the retrieved candidates, structural cues are introduced into the CNN using a novel part-pooling layer, in which the receptive field of each part is adjusted automatically. In the second step, we re-rank the retrieved candidates to improve the species diversity. We achieve this by formulating a novel ranking function that balances between the similarity of the candidates to the queried parts, while decreasing the similarity to the query species. We provide experiments on the benchmark CUB200 dataset and Columbia Dogs dataset, and demonstrate clear benefits of our schemes.     

基于土地利用变化的东海区大陆海岸带生境质量时空演变研究

人类活动对生态环境的影响主要表现为土地利用方式的变化。土地利用变化影响下的生境质量时空格局演变,对优化区域国土生态布局具有重要意义。利用DEM数据、气象数据、社会经济数据与1980、1990、2000、2010、2018年5期土地利用数据,通过InVEST模型、景观格局指数、地理探测器评估、描述、分析东海区大陆海岸带生境质量时空演变特征。结果表明：(1)1980—2018年东海区大陆海岸带陆地面积增加,土地利用中林地所占比重最大,耕地、建设用地面积变化最明显,2000—2010年土地利用转化最显著。土地变化北部大于南部、东侧大于西侧。(2)1980—2018年生境质量均值为0.75,总体生境质量较好,但呈下降趋势,2000—2010年生境质量下降最明显,2010年后下降速度减缓。生境质量斑块趋于破碎化、多样化、均匀化。(3)生境质量总体上从沿海向内陆下降,受岸线性质与围垦影响,北部生境质量由陆向海退化,南部生境退化沿海向陆推进。低等生境质量区呈现点—面—带的扩张趋势。(4)建设用地指数、高程、夜间灯光亮度、土壤类型、坡度为影响生境质量分布的主要因素,38年间主导因素由高程变为建设用地指...     

构建全细胞生物传感器测定农田土壤中有机磷农药甲基对硫磷含量

土壤中污染物的生物有效性评估对于准确评价环境污染风险至关重要,而全细胞生物传感器是此类评估的重要工具之一。本研究旨在使用新型全细胞生物传感器建立土壤中甲基对硫磷(methyl parathion,MP)的检测方法。首先,使用筛选出的甲基对硫磷水解酶基因(methyl parathion degrading gene,mpd)和pUC19质粒骨架以及已有的特异性诱导元件pobR为材料,构建全细胞生物传感器。然后,以96孔的酶标板为载体和以5种全细胞生物传感器为指示细胞,建立了土壤提取液样品中甲基对硫磷的分析方法,并应用于实际测试和田间土壤样品中甲基对硫磷的检测。以检测性能的最佳大肠杆菌(Escherichia coli)DH5α/pMP-AmilCP为例,其检测限为6.21−6.66μg/L,线性范围为10−10000μg/L。E.coli DH5α/pMP-RFP和E.coli DH5α/pMP-AmilCP的方法用于分析土壤提取液样品中甲基对硫磷的浓度,具有较好的检测性能。这种全细胞生物传感器方法有助于快速评估土壤中甲基对硫磷的生物有效性强弱,从而有效判断有机磷农药甲基对硫磷对土壤的污染风险。