Light Intensity Research Articles

Response of blueberry photosynthetic physiology to light intensity during different stages of fruit development.

To investigate the response of blueberry photosynthetic physiology to different light intensities during different stages of fruit development. In this study, four light intensity treatments (25%, 50%, 75% and 100% of full light) were set up to study the change rule of photosynthetic pigment content and photosynthetic characteristics of 'O'Neal' southern highbush blueberry leaves during the white fruiting stage (S1), purple fruiting stage (S2) and blue fruiting stage (S3) under different light intensity environments, and to explore the light demand and light adaptability of blueberry during different developmental stages of the fruit. The results showed that the chlorophyll and carotenoid contents of blueberry leaves showed an increasing trend with decreasing light intensity at all three stages of fruit development. The total chlorophyll content of blueberry leaves at 25% light intensity increased by 76.4% compared with CK during the blue fruiting stage; the maximum net photosynthetic rate (Pmax), light compensation point (LCP), light saturation point (LSP), rate of dark respirations (Rd), inter-cellular CO2 concentration (Ci), stomatal conductance (Gs), transpiration rate (Tr), net photosynthesis rate (Pn), and chlorophyll a/b showed a decreasing trend with decreasing light intensity. The Pn of blueberry leaves was highest under full light conditions at all three stages, and the Pn at 25% light intensity decreased by 68.5% compared with CK during the white fruiting stage Reflecting the fact that blueberries can adapt to low-light environments through increases in chlorophyll and carotenoids, but reduced light intensity significantly inhibited their photosynthesis. The photosynthetic physiology of blueberry showed a consistent pattern at all three stages, but there were some differences in the changes of photosynthetic parameters at different stages. The results of the study can provide theoretical references for the selection of sites and density regulation in blueberry production.

Association between physical activity performed at different intensities and cardiovascular health in patients with peripheral artery disease: an observational study.

We examined the sedentary behavior and physical activity of 260 patients with peripheral artery disease. Women engaged in more light physical activity than men did. Light physical activity was associated with lower arterial stiffness in men only, while no significant associations were found between sedentary behavior, moderate-vigorous physical activity, and cardiovascular outcomes. ◼ Women with peripheral artery disease exhibited higher blood pressure and arterial stiffness than men. ◼ Low levels of physical activity, particularly moderate to vigorous activity, were observed in individuals with peripheral artery disease. To analyze the association between the time spent in sedentary behavior and physical activity of different intensities with cardiovascular health in men and women with peripheral artery disease. Two hundred and sixty patients with peripheral artery disease and claudication symptoms (65.7% men; 66±1 years; ankle brachial index 0.57±0.18) were evaluated. Physical activity and sedentary behavior were assessed using an accelerometer. Physical activity was classified into light and moderate-vigorous intensities. The cardiovascular outcomes included blood pressure (oscillometric method), cardiac autonomic modulation (heart rate variability), and arterial stiffness (pulse wave velocity). Women spent more time engaged in light physical activity than men (341±14 min/day versus 306±9 min/day; p=0.040, respectively). There was no significant difference in the time spent on sedentary behavior and moderate-vigorous physical activity. Women had a higher systolic blood pressure (p=0.025), higher augmentation index (p<0.001), and lower sympathovagal balance (p=0.047) than men. Pulse wave velocity was only negatively associated with light physical activity (β= -4.66; 95%CI= -8.57; -0.76) in men. Light and moderate-vigorous physical activity and sedentary behavior were not associated with other cardiovascular outcomes. Higher levels of light physical activity were associated with lower arterial stiffness in men with peripheral artery disease.

Model based optimization for refractive index mismatched light sheet imaging

Selective plane illumination microscopy (SPIM) is an optical sectioning imaging approach based on orthogonal light pathways for excitation and detection. The excitation pathway has an inverse relation between the optical sectioning strength and the effective field of view (FOV). Multiple approaches exist to extend the effective FOV, and here we focus on remote focusing to axially scan the light sheet, synchronized with a CMOS camera’s rolling shutter. A typical axially scanned SPIM configuration for imaging large samples utilizes a tunable optic for remote focusing, paired with air objectives focused into higher refractive index media. To quantitatively explore the effect of remote focus choices and sample space refractive index mismatch on light sheet intensity distributions, we developed an open-source computational approach for integrating ray tracing and field propagation. We validate our model’s performance against experimental light sheet profiles for various SPIM configurations. Our findings indicate that optimizing the position of the sample chamber relative to the excitation optics can enhance image quality by balancing aberrations induced by refractive index mismatch. We validate this prediction using a home-built, large sample axially scanned SPIM configuration and calibration samples. Our open-source, extensible modeling software can easily extend to explore optimal imaging configurations in diverse light sheet imaging settings.

Flexible intelligent fabric composed of pinecone-like microstructure Co-cMOFs/CoZnAl-LDH composite nanomaterial for various types of sensor signals to guide personalized health activities

Multifunctional interfacing is a key aspect of flexible sensor development that facilitates enhanced interaction with the natural environment. However, challenges faced by contemporary multifunctional flexible sensors are structural complexity and high cost. Herein, inspired by the specific structure of pinecone in nature and the microstructured neural networks randomly distributed within human skin, we fabricated Co-cMOFs/CoZnAl-LDH composite nanomaterials with pinecone-like microstructure. Through the mutual verification of finite element simulation and experimental data, the mechanism of high sensitivity of the sensor is dynamically revealed from the structural point of view. The prepared pressure sensors exhibit a detection range (0–120 kPa), high sensitivity (2.35 × 109 kPa−1) and fast response. The photoelectric sensor shows enhanced photoelectric energy conversion, which shows great potential in the detection of sunlight intensity (20–100 mW cm−2). Simultaneously, building a hybrid pressure, acoustic and optical sensing platform and validating its superior performance in human movement and health monitoring applications. Furthermore, a strategy of light intensity feedback system to guide personalized health activities is put forward, so that doctors can guide patients/elderly health activities remotely.

Exploring the impact and influence of melanin on frequency-domain near-infrared spectroscopy measurements.

Near-infrared spectroscopy (NIRS) is a non-invasive optical method that measures changes in hemoglobin concentration and oxygenation. The measured light intensity is susceptible to reduced signal quality due to the presence of melanin. We quantify the influence of melanin concentration on NIRS measurements taken with a frequency-domain near-infrared spectroscopy system using 690 and 830nm. Using a forehead NIRS probe, we measured 35 healthy participants and investigated the correlation between melanin concentration indices, which were determined using a colorimeter, and several key metrics from the NIRS signal. These metrics include signal-to-noise ratio (SNR), two measurements of oxygen saturation (arterial oxygen saturation, , and tissue oxygen saturation, ), and optical properties represented by the absorption coefficient ( ) and the reduced scattering coefficient ( ). We found a significant negative correlation between the melanin index and the SNR estimated in oxy-hemoglobin signals ( , ) and levels ( , ). However, no significant changes were observed in the optical properties and ( , ). We found that estimated SNR and values show a significant decline and dependence on the melanin index, whereas and optical properties do not show any correlation with the melanin index.

Internet of Things Based Water Quality Control System

Fish incubation, which involves the hatching of fish eggs, represents the process of embryogenesis until the embryo emerges from its protective shell. This intricate developmental journey is influenced by a combination of internal and external factors. External factors can be influenced by water quality that is not suitable for hatching fish eggs. Water quality, which includes temperature, dissolved oxygen, light intensity, salinity, and pH, is an important and limiting factor for living creatures that live in water, including chemical, biological, and physical factors. Poor water quality can prevent fish eggs from hatching and even cause death. The primary objective here is the creation of an Internet of Things (IoT)-based system designed for controlling water quality during fish incubation. This system is intended to aid fish farmers in effectively control the environmental conditions within their incubation ponds. The method used in designing IoT device is research and development, and it uses the Arduino Mega microcontroller as the main device to run pH sensors, turbidity sensors, oxygen sensors, temperature sensors, and relay modules. Water Quality Control System The fish incubation was successful. The average time needed to change the water temperature from 28.5 to 29 degrees Celsius is 4 minutes and 7 seconds; change the dissolved oxygen level from 11 to 11.5 is 3 minutes and 33 seconds; change the pH value of the water from 6.9 to 7.1; and maintain turbidity below 5 with an average time of 5 minutes and 58 seconds. Controlling water quality can speed up the fish egg incubation process for 8 hours.

Maximum power point tracking controller for photovoltaic system based on chaos quantum particle swarm optimization – moth-flame optimization hybrid model

To convert photovoltaic arrays to solar energy in a more efficient way, this paper has proposed a maximum power point tracking controller model based on the chaotic quantum particle swarm-mothballing hybrid algorithm. First, the optimization of the particle swarm algorithm is designed to solve defects, such as premature maturity by using the quantum and chaotic strategies. The mothballing algorithm is introduced to help the model find global optimization-seeking more quickly. After that, further optimization was made to operate the tracking model in both offline and real-time parameters. The conductivity increment method and the perturbation observation method were adopted to effectively track the model under different temperatures and light intensities. Finally, the simulation and analysis experiments were carried out on the Simulink platform. The study’s proposed maximum power point tracking controller achieved a steady-state accuracy η2 of 99.84%. In summary, the study has proposed a hybrid intelligent algorithm with extraction of internal parameters. The maximum power point tracker based on the proposed method is proved to be both effective and accurate.

Vertical farming goes dynamic: optimizing resource use efficiency, product quality, and energy costs

Vertical farming is considered to be a key enabler for transforming agrifood systems, especially in or nearby urbanized areas. Vertical farming systems (VFS) are advanced indoor cropping systems that allow for highly intensified and standardized plant production. The close control of environmental parameters makes crop production stable and repeatable, ensuring year-round uniform product quality and quantity irrespective of location. However, due to continuous changes in plant physiology and development, as well as frequent changes in electricity prices, the optimum conditions for crop production and its associated costs can change within days or even minutes. This makes it beneficial to dynamically adjust setpoints for light (intensity, spectrum, pattern, and daylength), CO2, temperature, humidity, air flow, and water and nutrient availability. In this review, we highlight the beneficial effects that dynamic growth conditions can have on key plant processes, including improvements in photosynthetic gas exchange, transpiration, organ growth, development, light interception, flowering, and product quality. Our novel findings based on modeling and experimentation demonstrate that a dynamic daily light intensity pattern that responds to frequent changes in electricity prices can save costs without reducing biomass. Further, we argue that a smart, dynamic VFS climate management requires feedback mechanisms: several mobile and immobile sensors could work in combination to continuously monitor the crop, generating data that feeds into crop growth models, which, in turn, generate climate setpoints. In addition, we posit that breeding for the VFS environment is at a very early stage and highlight traits for breeding for this specialized environment. We envision a continuous feedback loop between dynamic crop management, crop monitoring, and trait selection for genotypes that are specialized for these conditions.

Dual-Mode Semiconductor Device Enabling Optoelectronic Detection and Neuromorphic Processing with Extended Spectral Responsivity.

High-performance semiconductor devices capable of multiple functions are pivotal in meeting the challenges of miniaturization and integration in advanced technologies. Despite the inherent difficulties of incorporating dual functionality within a single device, a high-performance, dual-mode device is reported. This device integrates an ultra-thin Al2O3 passivation layer with a PbS/Si hybrid heterojunction, which can simultaneously enable optoelectronic detection and neuromorphic operation. In mode 1, the device efficiently separates photo-generated electron-hole pairs, exhibiting an ultra-wide spectral response from ultraviolet (265nm) to near-infrared (1650nm) wavelengths. It also reproduces high-quality images of 256×256 pixels, achieving a Q-value as low as 0.00437µWcm- 2 at a light intensity of 8.58µWcm- 2. Meanwhile, when in mode 2, the as-assembled device with typical persistent photoconductivity (PPC) behavior can act as a neuromorphic device, which can achieve 96.5% accuracy in classifying standard digits underscoring its efficacy in temporal information processing. It is believed that the present dual-function devices potentially advance the multifunctionality and miniaturization of chips for intelligence applications.

Highly stable and self-powered ultraviolet photodetector based on Dion-Jacobson phase lead-free double perovskite

Metal halide perovskite materials present a wide array of opportunities for the development of high-performance optoelectronic devices, owing to their outstanding photoelectric properties. Compared with the lead-containing perovskites, stable and non-toxic organic-inorganic hybrid perovskites exhibit enhanced potential for future commercial applications. In this work, we developed a self-powered UV photodetector based on 2D Dion−Jacobson (DJ) phase lead-free double perovskite HAAg0.5Bi0.5Br4 (HA2+ = histammonium) perovskite with an on-off ratio up to 2.66 × 106, excellent specific detectivity of 6 × 1012 Jones, and response speed of 1.32 ms/118.4 μs. The light intensity related pyro-phototronic effect on 2D perovskite is thoroughly investigated. Temperature and light detection are realized through multi-energy coupling, which greatly improves the detection performance. Coupled pyro-phototronic current is calculated nearly 75 folds higher than that from the photoelectronic merely. As-prepared photodetector film shows excellent stability in normal environment, maintaining a value of 90 % to the initial performance after 500 cycles and 90 days. This work provides a new self-powered, stable and non-toxic candidate for the future UV photodetectors.

Smart Farm Control System Using IoT

This paper presents a way to do smart agriculture by using the advances in technology and information today, especially the Internet of Things (IoT) to help control the environment to change according to the needs of plants automatically. Which this research used the method of making a closed house or Greenhouse size 6m x 9m x 4m in number of 2 houses and using various types of sensor equipment. To detect parameters that affect the environment such as: Temperature sensor, Humidity sensor, Soil moisture sensor, pH sensor and Light sensor. To bring those values ​​forward to the microcontroller to process and order the electrical equipment to work, such as solenoid valves or water pumps; As well as send the parameter value to display the results to the application on the smartphone and the website through the wireless Internet system (WiFi) using the Blynk platform or Blynk cloud. From the results of the design and experiment, it was found that the system can control electrical equipment in the farm system, such as solenoid valves, water pump, and read various values ​​according to the set goals and objectives. We can order control Turn on and off the water system or the fog system anywhere at any time according to the conditions of the internet connection or direct control through the control box at any place or choose to have the system work automatically such as watering and misting according to the conditions we want and the system can also monitor or check the temperature, touch moisture, soil moisture, light intensity and pH value of the water at any time through the platform of the brand that can be used on both smartphones and computers.

ProDiVis: a method to normalize fluorescence signal localization in 3D specimens.

A common problem in confocal microscopy is the decrease in intensity of excitation light and emission signal from fluorophores as they travel through 3D specimens, resulting in decreased signal detected as a function of depth. Here, we report a visualization program compatible with widely used fluorophores in cell biology to facilitate image interpretation of differential protein disposition in 3D specimens. Glioblastoma cell clusters were fluorescently labeled for mitochondrial complex I (COXI), P2X7 receptor (P2X7R), β-Actin, Ki-67, and DAPI. Each cell cluster was imaged using a laser scanning confocal microscope. We observed up to ∼70% loss in fluorescence signal across the depth in Z-stacks. This progressive underrepresentation of fluorescence intensity as the focal plane deepens hinders an accurate representation of signal location within a 3D structure. To address these challenges, we developed ProDiVis: a program that adjusts apparent fluorescent signals by normalizing one fluorescent signal to a reference signal at each focal plane. ProDiVis serves as a free and accessible, unbiased visualization tool to use in conjunction with fluorescence microscopy images and imaging software.

Multicolor and multimode luminescent lanthanide-doped Cs2NaInCl6:Sb3+ from visible to near infrared for versatile applications

Double halide perovskites have shown admirable potential in promising optoelectronic applications due to simple synthesis, good stability and high structural tolerance. However, the poor optical properties caused by the parity-forbidden transitions posts a stringent limitation on their potential applications. Herein, we dope the lanthanide (Ln3+) ions with abundant energy levels into the Cs2NaInCl6:Sb3+ single crystals, which not only achieve multicolor visible emissions spectra from blue to red light, but also expand to the near infrared region from 800 to 1900 nm. In addition, the phosphors enable the multimode emissions with the up-conversion and down-conversion photoluminescence. Intriguingly, the excitation source, and the excitation light intensity also endow the multicolor emissions. Thus, combining with the multicolor and multimode luminescent properties, Cs2NaInCl6:Sb3+/Ln3+ could be applied to night vision imaging, substance detection, optical thermometry, white-light-emitting diodes (WLEDs) and anti-counterfeiting. The maximum value of relative temperature sensitivity reaches as high as 1.207 % K−1, which is relatively higher than those of most metal halide perovskites. Moreover, the single-source WLED displays Commission Internationale de L'Eclairage color coordinates (0.32, 0.31), a correlated color temperature of 6673 K, and color rendering index of 81.7. These results demonstrate the potential applications in the multifunctional photoelectric applications.

Multi-environment robust polarization navigation sensor and the parameter adaptive prediction method

As a type of photosensitive sensor, the polarization navigation sensor is susceptible to variations in external optical information. Experiments have demonstrated that light intensity is one of the factors influencing solution parameters. Considering that traditional polarization navigation sensor cannot detect light intensity effectively, a polarization sensor with light intensity detection capability is designed. Additionally, a neural network-based adaptive parameter method is proposed. By utilizing a neural network for the real-time solution degree of linear polarization (DLOP) and combining the light intensity information with polarization information from the new sensor, the method finally realizes the prediction of external solution parameters, thus enabling the solution model to adapt to the environmental variations. Finally, the effectiveness of the adaptive prediction method is verified by experiments. The results of outdoor experiments show that the adaptive prediction method reduces the mean square error (MSE) of angle of polarization (AOP) by approximately 42.11%, 44.78%, and 52.83% compared to the convention solution method under sunny, cloudy, and overcast conditions.

Illumination optimization strategies to enhance hydrogen productivity and light conversion efficiency for photo-fermentation by Rhodobacter sphaeroides KKU-PS1 using a concentrated multi-substrate feedstock

With the use of biotechnology, hydrogen can be produced from wastewater rich in short-chain fatty acids. A previous study revealed the ability of Rhodobacter sphaeroides KKU-PS1 to produce biohydrogen from substrates mimicking succinate fermentation effluent. However, the process still requires optimization. Before illumination optimization, due to high concentration of the effluent, various effluent dilution factors ranging from 10 to 100 were compared, and the optimal dilution factor was determined to be 50. Light-emitting diode (LED) setups consisting of bands and tubes were compared, and various illuminated surface-to-volume ratios (S/V) were obtained. LED tubes were subsequently used for light intensity optimization in the range of 5–23 klux, revealing optimum light intensity at 15 klux, yielding 2202 mL H2/L and 13.8 mL H2/L/h as the cumulative hydrogen and maximum output rate, respectively. The lighting protocol at 15 klux and with a 6h–6h light-dark cycle improved the total light conversion efficiency by up to 3.1%. The study successfully optimized the process, with results rivalling those of a previous study using malate.

High light intensity improves yield of specialized metabolites in medicinal cannabis (Cannabis sativa L.), resulting from both higher inflorescence mass and concentrations of metabolites

Medicinal cannabis (Cannabis sativa L.) contains various plant specialized metabolites, such as cannabinoids and terpenoids. These metabolites are mainly accumulated in inflorescences and are the primary focus of cultivation. Medicinal cannabis is often cultivated in indoor farming with electrical light, which allows for light intensities to optimize quantity and quality of production. Although it is known that an increase in light intensity results in increased inflorescence yield in cannabis, its impact on specialized metabolites remains unclear. We aim to quantify the effects of light intensity on the yield of specialized metabolites, and to elucidate which plant traits explain these effects, using a yield component analysis. Hereto, we conducted an experiment in a climate-controlled chamber using broad-band white LEDs at three light intensities: 600, 800, and 1000 µmol m−2 s−1 photosynthetic photon flux density (PPFD), applied during the generative phase (8 weeks with a 12-h photoperiod) in cannabis cv. ‘Critical CBD’. Yield of specialized metabolites, including cannabinoids and terpenoids, strongly increased with increasing PPFD due to increases in both their concentrations and inflorescence yield. The inflorescence yield showed a proportional increase with PPFD, resulting in a constant light use efficiency. The higher inflorescence dry mass was mainly caused by an increase in total plant dry matter production, and to a lesser extent a larger fraction of dry mass partitioned to the inflorescences. Leaf photosynthesis was higher for plants grown at higher PPFD. This study shows that cannabis can use very high light intensity, resulting in high yield of specialized metabolites due to high inflorescence mass and metabolite concentrations.

Effects of root zone temperature and light intensity on plant growth, flowering and fruit quality of plant factory ‘festival’ strawberry (Fragaria × ananassa Duch.)

Effects of root zone temperature and light intensity on plant growth, flowering and fruit quality of plant factory ‘festival’ strawberry (Fragaria × ananassa Duch.)

Analisis Efektivitas Sistem Kendali Otomatis PJU Berbasis IoT Menggunakan Mikrokontroler ESP32 dengan Metode Regresi Linier

Public street lighting (PJU) is essential infrastructure for nighttime security. This research develops an automatic PJU control system based on IoT using light and motion sensors with an ESP32 microcontroller. The system allows for PJU lamp control via a website, providing high flexibility for users. The ESP32 microcontroller is connected to a PIR sensor to detect motion. When the sensor detects movement, the intensity of the PJU lamps is increased, and when no movement is detected, the light intensity is reduced to save energy. Users can control the PJU lamps from any internet-connected device. Testing results show an increase in energy efficiency, with an average power consumption reduction of 13.77 watts and an efficiency increase of 42.67%. An R-squared value of 0.629 indicates that the model is quite good at explaining the variability in power consumption data. This system can automatically turn on street lights and be monitored in real-time, And hopes to contribute to the development of smarter and more efficient street lighting systems.

Optimasi Deteksi Tumor Otak Menggunakan Adaptive Multiscale Retinex dan YOLOV10 Pada Citra Digital

The incidence of brain tumors in Indonesia continues to rise annually, affecting both adults and children. Therefore, an effective detection system is required to differentiate MRI images showing the presence of brain tumors from those that do not. This distinction is crucial in the analysis and diagnosis of medical images. This study aims to optimize brain tumor detection in digital images by combining the Adaptive Multiscale Retinex (AMSR) method with the YOLOv10 algorithm. AMSR enhances the quality and contrast of brain images, making critical details more visible. The method adjusts the scale and intensity of image lighting to address uneven illumination and improve the visibility of brain structures. YOLOv10 is recognized for its speed and accuracy in real-time object detection. This algorithm employs deep learning techniques to identify and classify objects with high precision on enhanced brain image datasets. The model's performance was evaluated using metrics such as accuracy, sensitivity, specificity, and computation time. Results indicate that the combination of AMSR and YOLOv10 improves the accuracy and efficiency of brain tumor detection compared to conventional methods. The YOLOv10 model achieved a detection accuracy of 92%. This study provides significant contributions to early brain tumor detection technology, with important implications for the healthcare sector.

Comparative Analysis of Phytohormone Biosynthesis Genes Responses to Long-Term High Light in Tolerant and Sensitive Wheat Cultivars.

Phytohormones are vital for developmental processes, from organ initiation to senescence, and are key regulators of growth, development, and photosynthesis. In natural environments, plants often experience high light (HL) intensities coupled with elevated temperatures, which pose significant threats to agricultural production. However, the response of phytohormone-related genes to long-term HL exposure remains unclear. Here, we examined the expression levels of genes involved in the biosynthesis of ten phytohormones, including gibberellins, cytokinins, salicylic acid, jasmonic acid, abscisic acid, brassinosteroids, indole-3-acetic acid, strigolactones, nitric oxide, and ethylene, in two winter wheat cultivars, Xiaoyan 54 (XY54, HL tolerant) and Jing 411 (J411, HL sensitive), when transferred from low light to HL for 2-8 days. Under HL, most genes were markedly inhibited, while a few, such as TaGA2ox, TaAAO3, TaLOG1, and TaPAL2, were induced in both varieties. Interestingly, TaGA2ox2 and TaAAO3 expression positively correlated with sugar content but negatively with chlorophyll content and TaAGP expression. In addition, we observed that both varieties experienced a sharp decline in chlorophyll content and photosynthesis performance after prolonged HL exposure, with J411 showing significantly more sensitivity than XY54. Hierarchical clustering analysis classified the phytohormone genes into the following three groups: Group 1 included six genes highly expressed in J411; Group 2 contained 25 genes drastically suppressed by HL in both varieties; and Group 3 contained three genes highly expressed in XY54. Notably, abscisic acid (ABA), and jasmonic acid (JA) biosynthesis genes and their content were significantly higher, while gibberellins (GA) content was lower in XY54 than J411. Together, these results suggest that the differential expression and content of GA, ABA, and JA play crucial roles in the contrasting responses of tolerant and sensitive wheat cultivars to leaf senescence induced by long-term HL. This study enhances our understanding of the mechanisms underlying HL tolerance in wheat and can guide the development of more resilient wheat varieties.