Light Environment Research Articles

The Impacts of Planting Patterns Combined with Irrigation Management Practices on Watermelon Growth, Photosynthesis, and Yield.

(1) Background: Crop yields in China's arid and semi-arid regions are limited by water shortages. Exploring the interactions and resource utilization among agroforestry species is key to maintaining diversified agricultural production. (2) Objective: An apple-watermelon agroforestry system and watermelon sole-cropping system were compared to quantify how resource availability (light, water) and watermelon performance (leaf photosynthetic rate, growth, and yield) change with irrigation strategies. (3) Methods: A three-year apple and watermelon field experiment was conducted in a young apple orchard in the arid area of central Ningxia to test the effect of light competition and irrigation systems on light environment, leaf photosynthetic rate, plant growth, and yield in watermelon. The experiment encompassed two planting patterns: (i) apple-watermelon agroforestry (AF) and watermelon sole-cropping (SC) and (ii) three irrigation quotas (W1: 105 mm, W2: 210 mm, and W3: 315 mm). (4) Results: The results show that the agroforestry planting pattern extended the growth period of watermelon and increased the leaf area index. Mean daily shade intensity increased by 16.02% from 2020 to 2022. The land equivalent ratio (LER) was >1 in 2021 and 2022. The SWC, leaf photosynthetic rate, LAI, and yield of watermelon in an agroforestry planting pattern were lower than when in a sole-cropping planting pattern. However, under the W1 irrigation strategy, the total soluble solids of the agroforestry planting pattern were 2.27% higher than those of the sole-cropping pattern, and the yield of the agroforestry planting pattern was 2.59% higher than that of the sole-cropping pattern. Under the W3 irrigation strategy, the average watermelon weight in the agroforestry planting pattern was 2.85% higher than that of the sole-cropping pattern. A path analysis showed that the agroforestry planting pattern can increase the yield by increasing soil water content, which is different from the sole-cropping pattern. (5) Conclusions: The results confirm that the apple-watermelon agroforestry planting pattern reduced watermelon yields. However, the LER of the agroforestry system was greater than 1.0. It is reasonable to plant watermelons in young apple forests.

Can environmental traffic light warning labels reduce meat meal selection? A randomised experimental study with UK meat consumers

An important area for tackling climate change and health improvement is reducing population meat consumption. Traffic light labelling has successfully been implemented to reduce the consumption of unhealthy foods and sugary drinks. The present research extends this work to meat selection. We tested 1,300 adult UK meat consumers (with quotas for age and gender to approximate a nationally representative sample). Participants were randomised into one of four experimental groups: (1) a red traffic light label with the text ‘High Climate Impact’ displayed on meat meal options only; (2) a green traffic light label with the text ‘Low Climate Impact’ displayed on vegetarian and vegan meal options only; (3) red/orange/green (ROG) traffic light labels displayed on relevant meals; and (4) control (no label present). Participants made meal selections within their randomised group across 20 meal trials. A beta-regression was performed to ascertain the change in primary outcome (proportion of meat meals selected across the 20 trials) across the different groups. The red-only label and ROG labels significantly reduced the proportion of meat meals selected compared to the unlabelled control group, by 9.2% and 9.8% respectively. The green-only label did not differ from control. Negatively framed traffic light labels seem to be effective at discouraging meat selection. The labels appeared to be moderately acceptable to meat eaters, who did not think the labels impacted the appeal of the products. These encouraging findings require replication in real-life settings.

ВИКОРИСТАННЯ МЕТОДІВ ВІРТУАЛЬНОЇ РЕАЛЬНОСТІ ДЛЯ ОТРИМАННЯ ПРАКТИЧНИХ НАВИКІВ З ВИПРОБУВАНЬ БУДІВЕЛЬНИХ МАТЕРІАЛІВ

Introduction. Current developments that are being implemented by modern organizations must include not only initial methodological complexes of disciplines (modules), but also security programs aimed at mastering professional competencies. The optimal way to develop competencies is through virtual laboratories, which are modeled in an electronic lighting environment on real-world objects. Problem Statement. The problem of this article is the need to promote current technologies of virtual modeling, which is considered as a tool for increasing the brightness of engineering lighting. Purpose. development and implementation of virtual 3D laboratories to obtain practical skills from testing real-life materials. Materials and methods. 3D graphics editor, software Unity 2022.3.4. Results. We also have an analysis of programs for 3D modeling, which can be used not only for the purpose of displaying on printed products or on the computer screen, but also for the development of entire elements. In addition to software products, the authors propose an approach to creating a virtual technological laboratory, which allows industry professionals to learn practical skills from testing real-life materials.

PIF transcription factors-versatile plant epigenome landscapers

Plants are exquisitely responsive to their local light and temperature environment utilizing these environmental cues to modulate their developmental pathways and adjust growth patterns. This responsiveness is primarily achieved by the intricate interplay between the photoreceptor phyB (phytochrome B) and PIF (PHYTOCHROME INTERACTING FACTORs) transcription factors (TFs), forming a pivotal signaling nexus. phyB and PIFs co-associate in photobodies (PBs) and depending on environmental conditions, PIFs can dissociate from PBs to orchestrate gene expression. Until recently, the mechanisms governing epigenome modifications subsequent to PIF binding to target genes remained elusive. This mini review sheds light on the emerging role of PIFs in mediating epigenome reprogramming by recruiting chromatin regulators (CRs). The formation of numerous different PIF-CR complexes enables precise temporal and spatial control over the gene regulatory networks (GRNs) governing plant-environment interactions. We refer to PIFs as epigenome landscapers, as while they do not directly reprogram the epigenome, they act as critical sequence-specific recruitment platforms for CRs. Intriguingly, in the absence of PIFs, the efficacy of epigenome reprogramming is largely compromised in light and temperature-controlled processes. We have thoroughly examined the composition and function of known PIF-CR complexes and will explore also unanswered questions regarding the precise of locations PIF-mediated epigenome reprogramming within genes, nuclei, and plants.

Quantification of Arbutin and its degradation products, hydroquinone and p-Benzoquinone, in hyperpigmentation topical formulation: Effect of extraction procedure and interference assessment

The utilization of Hydroquinone (HQ) in over-the-counter skincare items is subject to restrictions. Consequently, Arbutin (AR) serves as a reliable alternative for addressing hyperpigmentation in non-prescription topical formulations. Nevertheless, AR undergoes decomposition into HQ and p-Benzoquinone (BZ) when exposed to temperature stress, ultraviolet light, or dilution in an acidic environment, all of which can induce skin toxicity. The intention of this paper is to investigate the effect of extraction procedure on the conversion of AR to HQ and or BZ and to evaluate kinetics of AR hydrolysis to HQ. Meanwhile this study aims to evaluate AR and BZ interference with the United States Pharmacopoeia (USP) identification and assessment method for HQ Hydrolytic stress during extraction conditions underwent optimization through systematic screening tests. Subsequent assessment of the residual drug and its degradation products were achieved by HPLC method. The resulting data were meticulously fitted to various kinetic models. To analyze the potential interference of AR in HQ measurement using USP method, the standard concentrations of AR and HQ were analyzed through UV–VIS spectrophotometry. For enhanced certainty, a validated HPLC method analysis was also conducted. Notably, the acid hydrolysis of AR exhibited independence from its initial concentration. So, the hydrolytic degradation of AR exhibited a Zero-order kinetic profile. Furthermore, the proven interference of AR in the UV–VIS spectrophotometry method was identified within the context of the USP method. This study successfully utilized an adopted HPLC method for the concurrent quantification of AR, HQ, and BZ. The potential interference of AR in the UV–VIS spectrophotometric assay for HQ may lead to false results especially for regulatory purposes.

Changes induced by parental neighboring touch in the clonal plant Glechoma longituba depend on the light environment.

Touch by neighboring plants is a common but overlooked environmental variable for plants, especially in dense vegetation. In addition, shade is inevitable for understory plants. The growth performance of clonal plant to the interaction between thigmomorphogenesis and shade response, and their impact on light adaptability is still unknown. At the present study, parental ramets of Glechoma longituba were exposed to two conditions (neighboring touch and shade), and their offspring ramets were in ambient or shaded environment. The phenotype and growth of parental and offspring ramets were analyzed. The results showed that neighboring touch of parental ramets regulated the performance of offspring ramets, while the effect depended on the light environment. The parental neighboring touch occurring in ambient environment suppressed the expansion of leaf organ, showed as a shorter petiole and smaller leaf area. Moreover, G. longituba exhibited both shade avoidance and shade tolerance characters to shaded environment, such as increased leaf area ratio and leaf mass ratio, longer specific petiole length and specific stolon length. It was notable that these characters of shade response could be promoted by parental neighboring touch to some extent. Additionally, parental light environment plays an important role in offspring growth, parent with ambient light always had well-grown offspring whatever the light condition of offspring, but the growth of offspring whose parent in shaded environment was inhibited. Finally, for the offspring with shaded environment, the touch between parental ramets in shade environment showed a disadvantage on their growth, but the influence of the touch between parental ramets in ambient environment was slight. Overall, the interaction of parental neighboring touch and shade environment complicate the growth of understory plants, the performance of plants is the integrated effect of both. These findings are conducive to an in-depth understanding of the environmental adaptation of plants.

Study on the photodegradation behaviors of thermal-aged silk

In museums, silk cultural relics are highly sensitive to light. However, lighting is inevitable due to the exhibition needs, despite any light would pose irreversible damage to silk. Although the solution of eliminating UV radiation was widely achieved in museum lighting environment, long-time accumulation of other light sources still would induce photodegradation of silk. This work therefore established the simulated light ageing experiments to assess the degradation behaviors of silk samples with different ageing degrees. The variation of color values and structure transformation of each sample group were determined by the means of scanning electron microscopy (SEM), colorimeter, Fourier Transform infrared spectroscopy (FTIR) and 13C CPMAS NMR. The results indicated that silk samples with different initial ageing degrees presented different discoloration tendency and structural variation in experimental lighting environment, suggesting the higher disordered structure makes the silk more vulnerable to light damage. It is of great significance to understand the long-time impacts of illumination on degraded silk and further provide methodology for predicting the duration of exhibited silk cultural relics.

Recommendations for light-dosimetry field studies based on a meta-analysis of personal light levels of office workers

Daytime light levels are important for human physiology. Office workers spend most of their daytime inside buildings where it is unclear whether they receive healthy light levels. A recent publication presented recommendations for the minimum daytime light level for optimal human health, expressed in melanopic equivalent daylight illuminance (EDI). The current paper assesses whether this recommended daytime light level is achieved by office workers through a meta-analysis of personal light levels of office workers, obtained from light-dosimetry field studies. From our literature search, we identified nine eligible papers. These papers comprised data from studies in one or multiple office buildings, over one or more seasons, from 1 to 62 participants, and for 19 to 564 workdays. After analysing the data, we found that in none of the offices the recommended minimum light level of 250 melanopic EDI was met for the entire day. Only 1 out of 6 median and 6 out of 13 mean reported personal light levels were above this recommended value. Unfortunately, these conclusions are less groundbreaking than we hoped for, due to large differences between study protocols. This resulted in a large variety of (unreported) study characteristics (i.e. light data, light-dosimeter, participant, building and environment) which complicated a fair comparison between the different studies. To facilitate meta-analyses of light-dosimetry field studies, we introduce recommendations for data collection and reporting in light-dosimetry field studies. We based these recommendations on the gaps identified from our meta-analysis, supplemented by recommendations from other papers.

Natural variations of heterosis-related allele-specific expression genes in promoter regions lead to allele-specific expression in maize

BackgroundHeterosis has successfully enhanced maize productivity and quality. Although significant progress has been made in delineating the genetic basis of heterosis, the molecular mechanisms underlying its genetic components remain less explored. Allele-specific expression (ASE), the imbalanced expression between two parental alleles in hybrids, is increasingly being recognized as a factor contributing to heterosis. ASE is a complex process regulated by both epigenetic and genetic variations in response to developmental and environmental conditions.ResultsIn this study, we explored the differential characteristics of ASE by analyzing the transcriptome data of two maize hybrids and their parents under four light conditions. On the basis of allele expression patterns in different hybrids under various conditions, ASE genes were divided into three categories: bias-consistent genes involved in basal metabolic processes in a functionally complementary manner, bias-reversal genes adapting to the light environment, and bias-specific genes maintaining cell homeostasis. We observed that 758 ASE genes (ASEGs) were significantly overlapped with heterosis quantitative trait loci (QTLs), and high-frequency variations in the promoter regions of heterosis-related ASEGs were identified between parents. In addition, 10 heterosis-related ASEGs participating in yield heterosis were selected during domestication.ConclusionsThe comprehensive analysis of ASEGs offers a distinctive perspective on how light quality influences gene expression patterns and gene-environment interactions, with implications for the identification of heterosis-related ASEGs to enhance maize yield.

Effects of combined ecological restoration measures on water quality and underwater light environment of Qingshan Lake, an urban eutrophic lake in China

Ecological restoration is vital in the management of eutrophic lakes. However, the effect of combined ecological restoration measures on the improvement of water quality and the light environment of urban eutrophic lakes requires further exploration. This study considered Qingshan Lake, a typical urban eutrophic lake in the middle reaches of the Yangtze River in China and explored the changes in the water quality and light environment before and after the implementation of combined ecological restoration measures from 2021 to 2022. The results showed that: (1) Ecological restoration significantly improved the transparency of Qingshan Lake (P < 0.05), with transparency increased from 33.1 cm to 96.0 cm. Total phosphorus, total nitrogen, chlorophyll a, permanganate index, suspended solids and turbidity decreased by 52.11 %, 65.47 %, 73.84 %, 92.11 %, 83.11 % and 77.52 %; respectively (P < 0.05). (2) Following ecological restoration, Qingshan Lake converted from severe eutrophication to mesotrophication, and the trophic level index decreased from 75.29 to 49.65 (P < 0.05). (3) Ecological restoration had a significant effect on improving underwater light environments. After ecological restoration, the light attenuation coefficient changed between 1.61–3.12 m−1, and the annual mean value decreased by 61.96 % (P < 0.05). The euphotic zone depth changed from 1.85 to 6.19 m, an increase of 167.68 %. (4) Ecological restoration reduced the attenuation of blue light, which reduced the red-blue ratio (R/B) of water. In general, turbidity had the greatest impact on light attenuation and R/B of Qingshan Lake, and ecological restoration combined with multiple measures had a positive effect on the management of eutrophic lakes.

Accurate Blood Pressure Measurement Using Smartphone's Built-in Accelerometer

Efficient blood pressure (BP) monitoring in everyday contexts stands as a substantial public health challenge that has garnered considerable attention from both industry and academia. Commercial mobile phones have emerged as a promising tool for BP measurement, benefitting from their widespread popularity, portability, and ease of use. Most mobile phone-based systems leverage a combination of the built-in camera and LED to capture photoplethysmography (PPG) signals, which can be used to infer BP by analyzing the blood flow characteristics. However, due to low Signal-to-Noise (SNR), various factors such as finger motion, improper finger placement, skin tattoos, or fluctuations in environmental lighting can distort the PPG signal. These distortions consequentially affect the performance of BP estimation. In this paper, we introduce a novel sensing system that utilizes the built-in accelerometer of a mobile phone to capture seismocardiography (SCG) signals, enabling accurate BP measurement. Our system surpasses previous mobile phone-based BP measurement systems, offering advantages such as high SNR, ease of use, and power efficiency. We propose a triple-stage noise reduction scheme, integrating improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), recursive least squares (RLS) adaptive filter, and soft-thresholding, to effectively reconstruct high-quality heartbeat waveforms from initially contaminated raw SCG signals. Moreover, we introduce a data augmentation technique encompassing normalization coupled with temporal-sliding, effectively augmenting the diversity of the training sample set. To enable battery efficiency on smartphone, we propose a resource-efficient deep learning model that incorporates resource-efficient convolution, shortcut connections, and Huber loss. We conduct extensive experiments with 70 volunteers, comprising 35 healthy individuals and 35 individuals diagnosed with hypertension, under a user-independent setting. The excellent performance of our system demonstrates its capacity for robust and accurate daily BP measurement.

Improved YOLOv8 and SAHI Model for the Collaborative Detection of Small Targets at the Micro Scale: A Case Study of Pest Detection in Tea

Pest target identification in agricultural production environments is challenging due to the dense distribution, small size, and high density of pests. Additionally, changeable environmental lighting and complex backgrounds further complicate the detection process. This study focuses on enhancing the recognition performance of tea pests by introducing a lightweight pest image recognition model based on the improved YOLOv8 architecture. First, slicing-aided fine-tuning and slicing-aided hyper inference (SAHI) are proposed to partition input images for enhanced model performance on low-resolution images and small-target detection. Then, based on an ELAN, a generalized efficient layer aggregation network (GELAN) is designed to replace the C2f module in the backbone network, enhance its feature extraction ability, and construct a lightweight model. Additionally, the MS structure is integrated into the neck network of YOLOv8 for feature fusion, enhancing the extraction of fine-grained and coarse-grained semantic information. Furthermore, the BiFormer attention mechanism, based on the Transformer architecture, is introduced to amplify target characteristics of tea pests. Finally, the inner-MPDIoU, based on auxiliary borders, is utilized as a replacement for the original loss function to enhance its learning capacity for complex pest samples. Our experimental results demonstrate that the enhanced YOLOv8 model achieves a precision of 96.32% and a recall of 97.95%, surpassing those of the original YOLOv8 model. Moreover, it attains an mAP@50 score of 98.17%. Compared to Faster R-CNN, SSD, YOLOv5, YOLOv7, and YOLOv8, its average accuracy is 17.04, 11.23, 5.78, 3.75, and 2.71 percentage points higher, respectively. The overall performance of YOLOv8 outperforms that of current mainstream detection models, with a detection speed of 95 FPS. This model effectively balances lightweight design with high accuracy and speed in detecting small targets such as tea pests. It can serve as a valuable reference for the identification and classification of various insect pests in tea gardens within complex production environments, effectively addressing practical application needs and offering guidance for the future monitoring and scientific control of tea insect pests.

Low–carbon regulation method for greenhouse light environment based on multi–objective optimization

Controlled environment agriculture is uniquely positioned to contribute to the decarbonization of cities due to its low carbon emissions and high energy efficiency in the food supply process. The energy consumed by the horticultural industry to supplemental lighting is enormous, but improvements in the light environment of greenhouse plants are essential. To make light regulation compatible with low carbon and environmentally friendly while improving photosynthetic production, experiments on tomato plant measurements with nested light intensity, spectra, carbon dioxide concentration and temperature were carried out in a solar greenhouse based on an infrared gas analyzer and machine learning. Based on the photosynthetic response to the photosynthetic photon flux density and red–blue ratio under multi–environmental conditions, the photosynthesis prediction model was developed using the least squares support vector regression, and model hyperparameter optimization was achieved by genetic algorithm nested cross–validation. A calculation method of carbon emissions from supplemental lighting was proposed, and the low–carbon light regulation was abstracted into multi–objective optimization for the solution. Based on the comprehensive objective evaluation method, low–carbon targets for light regulation were obtained through decision–making. The results showed that the developed prediction model with root mean square error of 1.069 and determination coefficient of 0.976, which is both accurate and fast, realizes the description and expression of the net photosynthetic rate in response to the environments. The optimal targets contain two–dimensional information of light intensity and spectra, and reduces carbon emissions by a maximum of 14.85% compared to the light saturation objective based on single–objective optimization at 95.49 % of the net photosynthetic rate. The method is energy efficient and suitable for supporting multi–spectral light environment regulation applications and guiding the greenhouse environment management under the demand of carbon reduction.

Light-Adaptive Human Body Key Point Detection Algorithm Based on Multi-Source Information Fusion.

The identification of key points in the human body is vital for sports rehabilitation, medical diagnosis, human-computer interaction, and related fields. Currently, depth cameras provide more precise depth information on these crucial points. However, human motion can lead to variations in the positions of these key points. While the Mediapipe algorithm demonstrates effective anti-shake capabilities for these points, its accuracy can be easily affected by changes in lighting conditions. To address these challenges, this study proposes an illumination-adaptive algorithm for detecting human key points through the fusion of multi-source information. By integrating key point data from the depth camera and Mediapipe, an illumination change model is established to simulate environmental lighting variations. Subsequently, the fitting function of the relationship between lighting conditions and adaptive weights is solved to achieve lighting adaptation for human key point detection. Experimental verification and similarity analysis with benchmark data yielded R2 results of 0.96 and 0.93, and cosine similarity results of 0.92 and 0.90. With a threshold range of 8, the joint accuracy rates for the two rehabilitation actions were found to be 89% and 88%. The experimental results demonstrate the stability of the proposed method in detecting key points in the human body under changing illumination conditions, its anti-shake ability for human movement, and its high detection accuracy. This method shows promise for applications in human-computer interaction, sports rehabilitation, and virtual reality.

Multi-Target Feeding-Behavior Recognition Method for Cows Based on Improved RefineMask.

Within the current process of large-scale dairy-cattle breeding, to address the problems of low recognition-accuracy and significant recognition-error associated with existing visual methods, we propose a method for recognizing the feeding behavior of dairy cows, one based on an improved RefineMask instance-segmentation model, and using high-quality detection and segmentation results to realize the recognition of the feeding behavior of dairy cows. Firstly, the input features are better extracted by incorporating the convolutional block attention module into the residual module of the feature extraction network. Secondly, an efficient channel attention module is incorporated into the neck design to achieve efficient integration of feature extraction while avoiding the surge of parameter volume computation. Subsequently, the GIoU loss function is used to increase the area of the prediction frame to optimize the convergence speed of the loss function, thus improving the regression accuracy. Finally, the logic of using mask information to recognize foraging behavior was designed, and the accurate recognition of foraging behavior was achieved according to the segmentation results of the model. We constructed, trained, and tested a cow dataset consisting of 1000 images from 50 different individual cows at peak feeding times. The method's effectiveness, robustness, and accuracy were verified by comparing it with example segmentation algorithms such as MSRCNN, Point_Rend, Cascade_Mask, and ConvNet_V2. The experimental results show that the accuracy of the improved RefineMask algorithm in recognizing the bounding box and accurately determining the segmentation mask is 98.3%, which is higher than that of the benchmark model by 0.7 percentage points; for this, the model parameter count size was 49.96 M, which meets the practical needs of local deployment. In addition, the technologies under study performed well in a variety of scenarios and adapted to various light environments; this research can provide technical support for the analysis of the relationship between cow feeding behavior and feed intake during peak feeding periods.

Is celebration of New Year and other festivals worth their environmental impact?

AbstractThe global tradition of fireworks at festivals causes significant environmental harm, including air, water, noise and light pollution, and impacts on human health. Diwali and the Chinese New Year fireworks can spike the Air Quality Index and elevate particulate matter (PM2.5) concentrations in capitals during and after celebrations. This commentary examines evidence for the detrimental effects of fireworks on the environment, human health and wildlife. Alternatives like drone displays, laser shows and eco‐friendly decorations are proposed, along with stricter regulations to curb firework impacts.

Patterns of tree regeneration and their implications for succession in Himalayan pine-oak forests, India

Factors affecting successional processes are critical determinants of the structural and compositional changes in a plant community. The present study examines the role of plant traits, such as seed size and dispersal mode, habitat factors such as canopy closure, leaf litter, soil moisture, disturbance, fire frequency, and landscape forest cover, in arrival and establishment of tree species in the oak-pine forests of the Western Himalayas. For this, we compared the regeneration, abundance, and composition of tree species in pine forests (pioneer stage) with that in oak-dominated hardwood forests (climax stage). The microsite factors and landscape forest cover varied significantly between the two stages. While species diversity was comparable across seedling, sapling, and pole stages, density of regenerating individuals was relatively lower in oak forest sites. The extent of overlap in species composition between oak and pine forest sites was also found to be low for both regeneration and adult stages. The amount of forest cover surrounding the study sites (landscape forest cover) did not significantly impact regeneration. Instead, factors related to establishment were determined to be more important. Regeneration density decreased with an increase in canopy closure (light environment) and litter depth, implying their crucial role in driving the successional trajectories. When plant traits were considered, all three regeneration stages of large-seeded and animal-dispersed species were of comparable densities in pine and oak forests, suggesting an absence of dispersal or arrival limitation. However, anthropogenic disturbance was found to negatively impact density of zoochorous species while fire frequency negatively influenced the diversity of large-seeded species. Control of extractive pressures, reducing incidence of fire, and retention of protected oak stands may be necessary to enable regeneration of zoochorous and of large-seeded species and thereby, natural succession to oak-dominated hardwood forest in this human-dominated landscape.

Fullerene derivatives barrier layer for efficient and stable perovskite solar cells through interfacial modification and removal of superoxide radicals

Superoxide radicals(O2•–)-induced decomposition of perovskite, which seriously impairs the photovoltaic performance and stability of perovskite solar cells (PSCs). Both TiO2 and perovskite produce O2•– that accelerates the rate of catalytic degradation at the interface and inherently poor interfacial contact, exacerbating charge recombination and efficiency loss. Adding fullerene phenol derivative (C60HTB) to the perovskite/TiO2 interface absorbs O2•– and improves poor interfacial communication. The PSCs' power conversion efficiency (PCE) is improved from 20.54 % to 21.63 %. The target devices retained 91.20 %, 94.86 %, and 89.36 % of their initial power conversion efficiencies after 48 h of aging under full-spectrum illumination, 240 h of aging under ultraviolet illumination, and dark storage in air for 500 h, respectively. In this work, efficient and stable TiO2-based-PSCs were realized by scavenging O2•–, which opens a new way to enhance the stability of PSCs in light and O2 environments (light/oxygen).

Comparative study of the removal of sulfate by UASB in light and dark environment.

At present, the application of sewage treatment technologies is restricted by high sulfate concentrations. In the present work, the sulfate removal was biologically treated using an upflow anaerobic sludge blanket (UASB) in the absence/presence of light. First, the start-up of UASB for the sulfate removal was studied in terms of COD degradation, sulfate removal, and effluent pH. Second, the impacts of different operation parameters (i.e., COD/SO42- ratio, temperature and illumination time) on the UASB performance were explored. Third, the properties of sludge derived from the UASB at different time were analyzed. Results show that after 28days of start-up, the COD removal efficiencies in both the photoreactor and non-photoreactor could reach a range of 85-90% while such reactors could achieve > 90% of sulfate being removed. Besides, higher illumination time could facilitate the removal of pollutants in the photoreactor. To sum up, the present study can provide technical support for the clean removal of sulfate from wastewater using photoreactors.

Regulation of Green Fluorescent Proteins by Sea Anemones (Anthopleura spp.) in Response to Light.

Green Fluorescent Proteins (GFPs) are a family of proteins with a disjunct systematic distribution; their biological functions remain speculative for the most part. Here we report studies of 3 closely related species of green sea anemones (Anthopleura) that express GFPs throughout their ectoderm. Individuals of these species maintain facultative symbiosis with zooxanthellae in their endoderm and inhabit the rocky intertidal or shallow subtidal. Thus, they depend on exposure to light to maintain photosynthesis of their symbionts, and simultaneously need to manage stresses associated with this exposure. We present experimental evidence that these sea anemones regulate the amount of GFP in their bodies in response to the surrounding light environment: they increase or reduce GFP when exposed to brighter or dimmer light, respectively, yet they maintain some GFP while in darkness, for surprisingly long periods.