Light Changes Research Articles

Quantification of losses in agriculture production in eastern Ukraine due to the Russia-Ukraine war

The ongoing war in Ukraine has seriously impacted the agricultural sector, yet its exact effects on agricultural production are not well understood. Here we combine satellite imagery, machine learning, and statistical regression approaches to present a spatially detailed assessment of agricultural losses for five high-risk provinces in eastern Ukraine (Crimea, Donets’k, Kherson, Luhans’k, and Zaporizhzhya). Our findings indicated that approximately 18.11 ± 2.47% of croplands were left unplanted following the war. Among the cultivated areas, wheat, sunflower, and rapeseed experienced average production losses of 36.39–37.19% in 2022 compared to pre-war levels during 2019–2021. Economically, the indirect losses resulting from decreased production, corresponding to $520.36 ± 22.52, $427.59 ± 24.62, and $205.02 ± 11.53 million USD for wheat, sunflower, and rapeseed crops, respectively, were 1.31–2.16 times higher than direct losses due to unplanted. We also found that reductions in crop production were primarily affected by war intensity indicated by changes in nighttime lights. This methodology offers a comprehensive framework for quantifying agricultural damages from wars, which can be applicable beyond the Russia-Ukraine context.

Research on a Human Moving Object Detection Method Based on Gaussian Model and Deep Learning

In order to understand human motion object detection methods, the author proposes a research on human motion object detection method based on Gaussian model. Firstly, traditional Gaussian models are unable to detect complex scenes or slow moving targets. Therefore, an improved Gaussian model based moving object detection algorithm is proposed. Secondly, multiple Gaussian models are used to represent the features of each pixel in the moving target image, and based on the matching of each pixel in the image with the Gaussian model, it is considered as a background point. Conversely, it is based on the principle of the foreground, and the Gaussian model is updated. Finally, by updating the foreground model and calculating short-term stability indicators, the detection effect of moving targets is improved. By determining the Gaussian distribution and pixel relationship, new parameters are set to construct the background model and eliminate the impact caused by sudden changes in lighting. The experimental analysis results show that this method can effectively detect and track moving targets, with good noise resistance, high clarity, and an accuracy rate of up to 99%. Compared with traditional Gaussian model methods, the improved method can more effectively detect moving targets and has better robustness.

Dynamics of Phytoplankton Communities and Environmental Drivers in Chinese Mitten Crab Aquaculture Ponds: Highlighting the Need for Cyanobacteria Control

Pond culture is the primary method for cultivating Chinese mitten crab (Eriocheir sinensis), with phytoplankton significantly influencing their growth. Green algae benefit crab growth by serving as supplementary food, while cyanobacteria, particularly during blooms, hinder it and pose health risks. Environmental changes in nutrient levels, temperature, and light significantly affect phytoplankton communities in ponds, impacting both ecosystem stability and crab growth. However, there is a limited understanding regarding the patterns of phytoplankton changes within adult Chinese mitten crab culture ponds. This study conducted monthly collection and analysis of phytoplankton throughout the culture cycle in typical adult Chinese mitten crab culture ponds, concurrently measuring physical and chemical water parameters to explore the correlation between phytoplankton changes and environmental factors. The results revealed distinct seasonal variations in phytoplankton composition. Chlorophyta and Bacillariophyta, such as Chlorella, Pediastrum, and Cocconeis, predominated in spring, while Chlorophyta and cyanobacteria, such as Volvox, Anabaena, and Microcystis, dominated in summer, and cyanobacteria and Bacillariophyta, such as Microcystis, Dolichospermum, and Cocconeis, prevailed in autumn. Total phytoplankton density consistently increased throughout the culture period. Microcystis constituted the majority of cyanobacteria biomass throughout most months. Although the total phytoplankton biomass fluctuated, cyanobacteria biomass consistently rose each month, reaching a peak of 61.7 mg/L in October. Water temperature and pH emerged as the primary environmental drivers influencing changes in phytoplankton community structure. Cyanobacteria density reached its peak between 18 and 26 °C and at a pH range of 7.5–8.5. These findings highlight the need for environmental regulation and cyanobacteria control in Chinese mitten crab culture ponds, thus promoting the health and sustainability of the Chinese mitten crab culture.

NCS-catalyzed synthesis of 2,4,5-triaryl-1H-imidazole and its selective detection of iron ions

In this study, an efficient synthesis of 2,4,5-trisubstituted imidazoles was developed via cyclocondensation starting from o-dione, substituted aromatic aldehyde and ammonium acetate using catalyst NCS, and was characterized by HR-MS, FT-IR, 1H and 13C NMR spectroscopy. A novel fluorescence sensor 4-(1H-phenanthro[9,10-d]imidazol-2-yl)-N, N-diphenylaniline (3bd) was discovered for the detection of Fe3+ ions. The probe 3bd exhibited strong blue radiation in solution. In the presence of Fe3+ ions, a significant fluorescence change of blue light to green light was observed in the EtOH/H2O (4/1, v/v) solution of 3bd (Ag+, Al3+, Ba2+, Ca2+, Cd2+, Co2+, Cr3+, Cu2+, Fe2+, Fe3+, Hg2+, Mg2+, Mn2+, Pb2+, Sr2+, Zn2+). The limits of detection of probe 3bd for Fe3+ ions was calculated to be as low as 0.70 μM, and it had excellent anti-interference ability. The probe 3bd complexed with Fe3+ ions at 1:1, and the complexation constant was 3.93 × 104 M−1. The probe 3bd realized the detection of Fe2+ oxidation to Fe3+, and the pH showed fine stability in the environment between 4.0–7.0, which ensured its potential application prospects. It also showed good reversibility upon addition of EDTA. Furthermore, the viability of 3bd to Fe3+ had practical application in live cell imaging.

Sonar Fish School Detection and Counting Method Based on Improved YOLOv8 and BoT-SORT

Fish object detection and counting in pelagic fisheries face many challenges in complex environments. Sonar imaging technology offers a solution because it generates high-resolution images underwater. In this paper, we propose a sonar-based fish object detection and counting method using an improved YOLOv8 combined with BoT-SORT to address issues such as missed detection, false detection, and low accuracy caused by complex factors such as equipment motion, light changes, and background noise in pelagic environments. The algorithm utilizes the techniques of lightweight upsampling operator CARAFE, generalized feature pyramid network GFPN, and partial convolution. It integrates with the BoT-SORT tracking algorithm to propose a new region detection method that detects and tracks the schools of fish, providing stable real-time fish counts in the designated area. The experimental results indicate that while focusing on maintaining a lightweight design, the improved algorithm achieved a 3.8% increase in recall and a 2.4% increase in mAP0.5 compared to the original algorithm. This significantly impacts scientific and rational fishery planning, marine resource protection, and improved productivity. At the same time, it provides important data support for marine ecological monitoring, environmental protection, and fishery management, contributing to sustainable fishery development and marine ecology preservation.

Night-time light loss during the 2022 Kyiv offensive revealed through VIIRS DNB

ABSTRACT The satellite low-light imagers can detect changes in nighttime lights caused by ground military conflict. The Kyiv Offensive in Kyiv, Ukraine, which lasted less than 40 days during the Russia – Ukraine conflict, began on 24 February 2022. In addition to the monthly light product, we included a daily light product to analyse the number and average intensity of light pixels in the area around Kyiv over time. The changing trends of two parameters are similar. From February to March, the number of light pixels dropped by 65.2%, and average intensity by 24.5%. To account for daily fluctuations, the relative light ratio was introduced, comparing Kyiv to Moscow, Gomel, and Warsaw. This parameter showed a significant decrease in both the number and intensity of light pixels between days 411 and 423 since January 1, 2021, aligning with the conflict’s start. The relative light ratio revealed a 70.6%, 63.5%, and 57.3% drop in light pixel numbers, and a 9.5%, 24.2%, and 48.4% drop in their average intensity for the respective city pairs. However, unusual fluctuations in the reference cities, such as in Gomel during Christmas and in Moscow at the conflict’s onset, present some problems in using the relative light ratio.

Color-appearance-matched data in high-dynamic-range luminance conditions

We report color-appearance-matched data under high-dynamic-range luminance conditions. The experimental method and apparatus proposed in a previous study [J. Opt. Soc. Am. A 36, 1940 (2019)JOAOD60740-323210.1364/JOSAA.36.001940] were used to measure perceptual color shifts in the R, G, B, Y, RB, BG, GY, and YR groups of 16 samples under four dual-illumination conditions at luminance levels of (300 and 4500cd/m2), (20 and 300cd/m2), (80 and 4500cd/m2), and (20 and 4,500cd/m2). We observed a decrease in lightness for all samples, and hue shifts toward blue in R, red in reddish YR, and green in BG samples when the luminance changed from low to high. Correlated changes in lightness and chroma, that is, an increase in lightness change and a decrease in chroma change under the highest luminance contrast (20 and 4500cd/m2), were observed for the Y, GY, and YR samples.

Spatiotemporal Dynamics of COVID‐19 Pandemic City Lockdown: Insights From Nighttime Light Remote Sensing

AbstractThe global COVID‐19 outbreak severely hampered the growth of the global economy, prompting the implementation of the strictest prevention policies in China. Establishing a significant relationship between changes in nighttime light and COVID‐19 lockdowns from a geospatial perspective is essential. In light of nighttime light remote sensing, we evaluated the spatiotemporal dynamic effects of COVID‐19 city lockdowns on human activity intensity in the Zhengzhou region. Prior to the COVID‐19 outbreak, nighttime light in the Zhengzhou region maintained a significant growth trend, even under regular control measures. However, following the October 2022 COVID‐19 lockdown, nighttime light experienced a substantial decrease. In the central area of Zhengzhou, nighttime light decreased by at least 18% compared to pre‐lockdown levels, while in the sub‐center, the decrease was around 14%. The areas where nighttime light decreased the most in the central region were primarily within a 15 km radius, while in the sub‐center, the decrease was concentrated within a 5 km radius. These changes in both statistical data and nighttime light underscored the significant impact of the COVID‐19 lockdown on economic activities in the Zhengzhou region.

Towards medical imaging of drug photoactivation: Development of light responsive magnetic resonance imaging and chemical exchange saturation transfer contrast agents

AbstractIn recent years, the use of light to selectively and precisely activate drugs has been developed along the fundamental concepts of photopharmacology. One of the key methods in this field relies on transiently silencing the drug activity with photocleavable protecting groups (PPGs). To effectively utilize light‐activated drugs in future medical applications, physicians will require a reliable method to assess whether light penetrates deep enough into the tissues to activate the photoresponsive theragnostic agents. Here, we describe the development and evaluation of magnetic resonance (MR) imaging agents that allow for the detection of light penetration and drug activation in the tissues using non‐invasive whole‐body magnetic resonance imaging (MRI) and chemical exchange saturation transfer (CEST)‐MRI modalities. The approach relies on the use of PPG‐protected MR contrast agents, which upon irradiation with light change their imaging signal. A Gadolinium(III)‐based MRI contrast agent is presented that undergoes a significant change in relaxivity (25%) upon uncaging, providing a reliable indicator of light‐induced cargo release. Additionally, we introduce the first light‐responsive CEST‐MRI imaging agent, enabling positive signal enhancement (off‐to‐on) upon light activation, offering a novel approach to visualize the activation of photoactive agents in living tissues. This research provides a proof‐of‐principle for the non‐invasive, whole‐body imaging of light penetration and drug activation with high temporal resolution characteristic of MR methods.

High-performance Smart Home System based on Optimization Algorithm

Background: With the recent COVID-19 pandemic, people have become increasingly concerned about their physical health. Therefore, the ability to monitor changes in the surrounding environment in real-time and automatically improve the environment has become a current hot topic to improve the overall health level. Objective: This article describes the design of a high-performance intelligent home system that can simultaneously perform monitoring and automatic adjustment functions. Methods: The ESP8266 was used as the core controller, and the DHT11 and G12-04 sensors were used to collect data, such as temperature, humidity, and ambient light intensity. The sampling frequency was increased and the sampled data were processed to improve data accuracy. The sampled data were wirelessly transmitted to a PC or mobile terminal for real-time display. When the sampled data underwent sudden changes, an alert message was sent via the mobile terminal. Based on the real-time changes in ambient light, an improved lighting brightness adjustment algorithm combining bang-bang and single neuron adaptive PID control was used to adjust the lighting brightness. Results: After testing the system designed in this paper and analyzing the errors compared to standard values, the temperature measurement error ranged from 0% to 0.01107%, and the humidity measurement error ranged from 0% to 0.03797%. The improved algorithm was simulated and tested using MATLAB software and compared with traditional PID algorithms and single-neuron adaptive PID algorithms. The improved algorithm did not overshoot during adjustment, and the system reached a steady state much faster than traditional algorithms. Conclusion: The system showed good performance in real-time, stability, and accuracy, fully demonstrating the effectiveness of the devices and algorithms used in the system. This provides ideas for the design and improvement of future smart homes.

Fluctuations in the “static” atmosphere and their effects on tropospheric ozone distribution

Atmospheric fluctuation can be seen everywhere. This study focuses on the record-breaking increase of O3 concentration during the summer in some sensitive areas in recent years. The findings indicate that in the vicinity of the East Asian continent near western Pacific ocean, when the atmospheric conditions are stable or neutral, it is conducive to the maintenance and propagation of atmospheric oscillations near the height of the pollutant mixed layer (H_PML). Accompanied by the "peak-trough" effect of external gravity wave oscillations, due to the abundant water vapor of the cloud system (there are low pressure or typhoon disturbances in summer) near the large-scale cloud belt at the edge of the subtropical high in the western Pacific, the bright temperature at cloud top shows "light and dark changes" on satellite images, forming a wave-like cloud system. The novelty of this study lies in the fact that atmospheric fluctuations near the H_PML is not only related to the known aggravation of heavy rainfall, but also leads to the additional value-added effect of aerosols. Under static atmospheric conditions, the impact of atmospheric fluctuations near the H_PML on additional rise of O3 concentration helps us to deepen our understanding of the so-called "entrained ozone (EZ) effect" in the atmosphere. Due to the external gravity waves, the concentration of O3 increased further. Diurnal variations of solar zenith angle and H_PML are key meteorological factors influencing the significant increase in near-surface O3 concentration entrainment. The formation mechanism of solar photochemical O3 is further deepened and supplemented by analyzing the record-breaking increase of O3 concentration in summer observed in recent years.

Effects of Changes in Lighting on Color Perception of 3D Objects

Effects of Changes in Lighting on Color Perception of 3D Objects

Assessment of post-pandemic economic recovery in Beijing, China, using night-time light data

ABSTRACT The coronavirus disease 2019 (COVID-19) pandemic posed a significant impact on human society, resulting in substantial changes in night-time light (NTL). This study developed a novel NTL index to estimate the quarterly Gross Domestic Product (GDP) at the county level in Beijing. This study aimed to investigate the economic recovery status in Beijing by establishing regression models of economic development before and after the pandemic. The estimated quarterly GDP at the county level was found to have a strong correlation with actual quarterly GDP statistics, with an average coefficient of determination (R 2) of 0.790. The regression models of the economic development of Beijing county-level districts before and after the pandemic were established after seasonal decomposition of the quarterly GDP. Based on the economic recovery framework for the pandemic in Beijing, most districts in the city had exhibited low economic resilience in terms of resistance and recoverability before and after the pandemic. Although the economy of Beijing is recovering gradually, it has not yet restored to pre-pandemic normal levels. These findings imply that NTL data can help assess the impact of emergency events on the disturbance of economic activity.

Improvement of Climate Resource Utilization in the Southwestern Hilly Region through the Construction of a New Multi-Maturing Cropping System

The construction of an appropriate cropping pattern is crucial for the improvement of regional agricultural economic efficiency and sustainable development. Despite previous efforts, there remains a gap in optimizing cropping patterns that fully leverage climate resources to enhance production efficiency. This study addresses this gap by systematically comparing the differences in climate resource allocation, production efficiency and crop response among models by constructing four new triple-maturing cropping models at typical ecological sites in the hilly areas of southwest China. To solve the above problems, we constructed eight cropping patterns and classified them to three as follows: the Traditional Double Cropping System, the Traditional Triple Cropping System, the Novel Triple Cropping System. The results showed that the new multi-maturing planting pattern was significantly better than the traditional two-maturing netting pattern and the traditional three-maturing planting pattern in terms of light, temperature and water productivity. Compared with the traditional two-maturity net cropping model and the traditional three-maturity cropping model, the new cropping model increased light energy productivity by 97.88% and 50.00%, respectively; light energy use by an average of 0.48% and 0.31%; cumulative temperature productivity by an average of 84.70% and 49.14%; and rainfall productivity by an average of 101.04% and 49.61%. An assessment of the light, temperature and water meteorological resource use efficiency of the different treatments showed that the resource use efficiency of the new multi-maturing planting pattern was on average 111.58% and 74.78% higher than that of the traditional two-maturing net planting pattern and the traditional three-maturing planting pattern, with the T6 pattern having the highest resource use efficiency. The new multi-ripening cropping pattern has demonstrated production stability in response to changes in light, temperature and water resources, better adapting to weekly climate changes, stabilizing yields and improving efficiency. In summary, the results of this study can provide a theoretical basis for optimizing cropping patterns and promoting the use of climate resources in agriculture and sustainable development. Future research should focus on further refining these models, exploring their adaptability to various climatic conditions, and evaluating their long-term economic and environmental impacts.

A Robust CoS-PVNet Pose Estimation Network in Complex Scenarios

Object 6D pose estimation, as a key technology in applications such as augmented reality (AR), virtual reality (VR), robotics, and autonomous driving, requires the prediction of the 3D position and 3D pose of objects robustly from complex scene images. However, complex environmental factors such as occlusion, noise, weak texture, and lighting changes may affect the accuracy and robustness of object 6D pose estimation. We propose a robust CoS-PVNet (complex scenarios pixel-wise voting network) pose estimation network for complex scenes. By adding a pixel-weight layer based on the PVNet network, more accurate pixel point vectors are selected, and dilated convolution and adaptive weighting strategies are used to capture local and global contextual information of the input feature map. At the same time, the perspective-n-point localization algorithm is used to accurately locate 2D key points to solve the pose of 6D objects, and then, the transformation relationship matrix of 6D pose projection is solved. The research results indicate that on the LineMod and Occlusion LineMod datasets, CoS-PVNet has high accuracy and can achieve stable and robust 6D pose estimation even in complex scenes.

TESS light curve modeling and period study of four eclipsing binaries

Abstract We reported the light curves and orbital period variations of four short-period eclipsing binaries in the Southern Hemisphere. From short-cadence time-series observations of the TESS, the intrinsic light changes rapidly with time. Δmmax and Δmmin exhibit random wave-like variations or quasi-periodicities. We deduced 14 sets of photometric solutions from the truncated light curves using the W-D program. The results imply that V757 Cen and BC Gru are near-contact binaries, whose one or two components almost fill the Roche lobes with $f>98{{\%}}$. Meanwhile, V535 Ara and AQ Tuc are A-subtype contact binaries. The asymmetric light curves were modelled by a cool spot assumed on a more massive component, which was used to track the stellar longitudes of starspots. Based on all available eclipsing times (ETs), including 1495 ones from TESS light curves (LCs), the orbital period variations of four binaries were analysed. The (O − C) curves are coincidentally demonstrated by the light-time effect (LITE) via the presence of the third bodies. The modulation periods approximate to 50 ∼ 60 years. In the coplanar orbit with the central binaries, the third companions’ masses are 0.105 M⊙ for V757 Cen, 0.340 M⊙ for BC Gru, 0.238 M⊙ for V535 Ara, and 0.343 M⊙ for AQ Tuc, whose systems are stable according to Harrington’s criterion. Therefore, the four short-period eclipsing binaries, V757 Cen, BC Gru, V535 Ara and AQ Tuc are hierarchical triple stellar systems.

Photoperiod and temperature synergistically regulate heading date and regional adaptation in rice.

Plants must accurately integrate external environmental signals with their own development to initiate flowering at the appropriate time for reproductive success. Photoperiod and temperature are key external signals that determine flowering time; both are cyclical and periodic, and they are closely related. In this review, we describe photoperiod-sensitive genes that simultaneously respond to temperature signals in rice (Oryza sativa). We introduce the mechanisms by which photoperiod and temperature synergistically regulate heading date and regional adaptation in rice. We also discuss the prospects for designing different combinations of heading date genes and other cold tolerance or thermo-tolerance genes to help rice better adapt to changes in light and temperature via molecular breeding to enhance yield in the future.

Morphological changes and color development during cookie baking-Kinetic, heat, and mass transfer considerations.

Color and shape are important quality attributes in baked goods, particularly cookies. Composition and processing conditions determine and influence color development and morphological changes in these baked goods. The objective of this study was to systematically evaluate the evolution of color and shape during baking to determine useful correlations that can be implemented during the assessment and modeling of the baking process. Cookies (AACC-I standard protocol 10-53.01) were baked at 185, 205, and 225°C. Moisture content, water activity, surface temperature, characteristic dimensions (radius and thickness), and color indexes (lightness, redness, blueness, and browning index [BI]) were monitored at different locations on the cookie surface and baking times. Relationships among the tested conditions were explored using correlation analysis. The cookies' dimensions and color indexes were strongly correlated with changes in moisture content over time, and those relationships were characterized using empirical models. The temperature dependence of the kinetic parameters of the changes in lightness and BI was also described and deemed independent of the location on the cookie surface. This study provides insights into the influence of heat and mass transfer on the physical and physicochemical changes of cookies during baking. The kinetic and secondary models developed in this study can serve as important components for establishing a comprehensive approach for coupling heat transfer, mass transfer, and reaction kinetics to estimate and optimize cookie-baking processes. PRACTICAL APPLICATION: The findings from this study provide valuable information for better understanding the morphological changes and color developments during the cookie-baking process. The quantitative data and models generated in this study will allow identifying baking conditions for better quality development.

Light and Displacement Compensation-Based iPPG for Heart-Rate Measurement in Complex Detection Conditions.

A light and displacement-compensation-based iPPG algorithm is proposed in this paper for heart-rate measurement in complex detection conditions. Two compensation sub-algorithms, including light compensation and displacement compensation, are designed and integrated into the iPPG algorithm for more accurate heart-rate measurement. In the light-compensation sub-algorithm, the measurement deviation caused by the ambient light change is compensated by the mean filter-based light adjustment strategy. In the displacement-compensation sub-algorithm, the measurement deviation caused by the subject motion is compensated by the optical flow-based displacement calculation strategy. A series of heart-rate measurement experiments are conducted to verify the effectiveness of the proposed method. Compared with conventional iPPG, the average measurement accuracy increases by 3.8% under different detection distances and 5.0% under different light intensities.

Physicochemical, functional, and antinutritional properties of fermented Bambara groundnut and sorghum flours at different times

This study investigated the effect of fermentation at different times (24 and 48 h) on the proximate composition, physicochemical, antinutritional, and functional properties of fermented Bambara groundnut and sorghum flours. The results showed that fermentation improved the crude protein and crude fibre of the flours, with a decrease in crude fat and ash content. An increase in the mineral contents (potassium, magnesium, phosphorus, zinc, and iron), water absorption capacity, and foam stability were also observed. The oil absorption capacity of the fermented flour samples decreased after 24 h of fermentation, with an increase thereafter. A decrease in foam, emulsification capacity, and antinutritional factors were observed. The redness and yellowness values increased with an increase in fermentation time, while the lightness and total change in colour decreased. In conclusion, this study shows that fermented Bambara groundnut and sorghum flours could be useful ingredients or serve as an alternative for commercial and industrial purposes. Subsequent use of fermented Bambara groundnut and sorghum flours may also help mitigate nutritional issues, particularly in developing nations.