Search Results (36)

In a rapidly changing era, education systems must empower learners as community innovators through Place-Based Education (PBE). While School–University partnerships are global drivers of reform, the specific administrative mechanisms required to support and scale these innovations within decentralized policy frameworks, such as Thailand’s Education Sandbox, remain underexplored. This Research and Development (R&D) study, integrated with a Design Thinking framework, investigated school-led administrative innovations across four diverse jurisdictions in the Songkhla Education Sandbox over 12 months. The study synthesized a collaborative administrative framework structured around four core pillars: Strategic Mentoring and Thinking Partnership, Place-Based Educational Ecosystems, Adaptive Governance and Resource Autonomy, and Collective Synergy and Iterative Development. Empirical findings indicate that this framework supported the development of “Innovative Co-creator” characteristics among students, generating high-value outcomes such as “Songkhla Mini Mango Coffee” and social innovations from water hyacinth. The study concludes that educational transformation thrives when administrative structures shift from compliance-driven mandates to flexible, context-responsive partnerships. By integrating university-led coaching with community assets, the framework offers a promising, contextually adaptable model for enhancing student learning outcomes while preserving local socio-cultural identity. This systematic approach supports the continuity of educational reform across diverse regional contexts. Full article

This study aimed to develop an automated irrigation system for substrate-grown strawberry plants and to evaluate whether irrigation and biostimulation levels influence yield and fruit quality. The system comprised two Arduino Pro Mini devices equipped with LoRa transceivers, substrate moisture sensors, and servomotors for valve control. Six biostimulants were assessed [control (without biostimulation), microalga Spirulina platensis (SP), mycorrhiza Scutellospora heterogama (SH), a mycorrhizal community (SJ CS), SP + SH, and SP + SJ CS] under four irrigation levels [reference tension of 5 kPa (moderate water deficit), 10% above the reference tension (severe water deficit), 10% below the reference tension (mild water deficit), and standard irrigation without restriction] defined by substrate water tension. Data were collected in real time and analyzed using the InfluxDB (version 3 Core) and Grafana (version 12.3.2) platforms. The automated system-controlled valve activation was based on moisture sensor readings, enabling the establishment of irrigation levels supported by energy-efficient technologies. Under standard irrigation, fruits exhibited lower acidity and improved flavor compared to those from plants under water deficit. Plants subjected to mild water deficit or standard irrigation achieved higher yields than those exposed to moderate or severe deficit. Fruits produced by plants treated with S. heterogama showed higher phytochemical concentrations. Overall, the findings support the use of automated irrigation and biostimulation as sustainable management strategies to enhance water use efficiency, productivity, and fruit quality in soilless strawberry cultivation. Full article

Hyperspectral reconstruction (SR) refers to the computational process of generating high-dimensional hyperspectral images (HSI) from low-dimensional observations. However, the superior performance of most supervised learning-based reconstruction algorithms is predicated on the availability of fully labeled three-dimensional data. In practice, this requirement demands complex optical paths with dual high-precision registrations and stringent calibration. To address this gap, we extend the fully supervised paradigm to a semi-supervised setting and propose SSHSR, a semi-supervised SR method for scenarios with limited spectral annotations. The core idea is to leverage spectrally aware mini-patches (SA-MP) as guidance and form region-level supervision from averaged spectra, so it can learn high-quality reconstruction without dense pixel-wise labels over the entire image. To improve reconstruction accuracy, we replace the conventional fixed-form Tikhonov physical layer with an optimizable version, which is then jointly trained with the deep network in an end-to-end manner. This enables the collaborative optimization of physical constraints and data-driven learning, thereby explicitly introducing learnable physical priors into the network. We also adopt a reconstruction network that combines spectral attention with spatial attention to strengthen spectral–spatial feature fusion and recover fine spectral details. Experimental results demonstrate that SSHSR outperforms existing state-of-the-art (SOTA) methods on several publicly available benchmark datasets, as well as on remote sensing and real-world scene data. On the GDFC remote sensing dataset, our method yields a 6.8% gain in PSNR and a 22.1% reduction in SAM. Furthermore, on our self-collected real-world scene dataset, our SSHSR achieves a 6.0% improvement in PSNR and a 11.9% decrease in SAM, confirming its effectiveness under practical conditions. Additionally, the model has only 1.59 M parameters, which makes it more lightweight than MST++ (1.62 M). This reduction in parameters lowers the deployment threshold while maintaining performance advantages, demonstrating its feasibility and practical value for real-world applications. Full article

High-entropy alloys (HEAs) present a vast compositional design space, characterized by four core effects—high configurational entropy, sluggish diffusion, severe lattice distortion, and the cocktail effect—which collectively underpin their exceptional potential for both structural and hydrogen storage applications. This mini-review synthesizes recent advances in the compositional design of HEAs with emphasis on structural materials and hydrogen storage. Firstly, it provides an overview of the definition of HEAs and the roles of principal alloying elements, then synthesizes solid solution formation rules based on representative descriptors—atomic size mismatch, electronegativity difference, valence electron concentration, mixing enthalpy, and mixing entropy—together with their applicability limits and common failure scenarios. A brief introduction is provided to the preparation methods of arc melting and powder metallurgy, which have a strong interaction with the composition. The design–structure–property links are then consolidated for structural materials (mechanical properties) and for hydrogen storage materials (hydrogen storage performance). Furthermore, the rules for the combined design of control systems for HEAs and the associated challenges were further discussed, and the future development prospects of HEAs in structural materials and hydrogen storage were also envisioned. Full article

Hand rehabilitation requires consistent, repetitive exercises that can often reduce patient motivation, especially in home-based therapy. This study introduces ReHAb Playground, a deep learning-based system that merges real-time gesture recognition with 3D hand tracking to create an engaging and adaptable rehabilitation experience built in the Unity Game Engine. The system utilizes a YOLOv10n model for hand gesture classification and MediaPipe Hands for 3D hand landmark extraction. Three mini-games were developed to target specific motor and cognitive functions: Cube Grab, Coin Collection, and Simon Says. Key gameplay parameters, namely repetitions, time limits, and gestures, can be tuned according to therapeutic protocols. Experiments with healthy participants were conducted to establish reference performance ranges based on average completion times and standard deviations. The results showed a consistent decrease in both task completion and gesture times across trials, indicating learning effects and improved control of gesture-based interactions. The most pronounced improvement was observed in the more complex Coin Collection task, confirming the system’s ability to support skill acquisition and engagement in rehabilitation-oriented activities. ReHAb Playground was conceived with modularity and scalability at its core, enabling the seamless integration of additional exercises, gesture libraries, and adaptive difficulty mechanisms. While preliminary, the findings highlight its promise as an accessible, low-cost rehabilitation platform suitable for home use, capable of monitoring motor progress over time and enhancing patient adherence through engaging, game-based interactions. Future developments will focus on clinical validation with patient populations and the implementation of adaptive feedback strategies to further personalize the rehabilitation process. Full article

An understanding of the textures (grain size, grain shape, porosity, etc.), composition (mineralogy), and distribution of constituent components of geological materials such as carbonate and siliciclastic sedimentary rocks is essential in their classification, interpretation, and significance in terms of their geomechanical strength and liquid/gas storage potential. In terms of scanning electron microscopy (SEM), this is limited to relatively flat areas of selected rough surfaces, or the analysis of polished thin sections. Here, we illustrate a new technique that can image large areas of the external surface of mini-cores (approximately 10 mm or smaller in diameter) drilled from carbonate and siliciclastic rock samples. The technique utilises a specially developed horizontal rotation stage within an SEM and allows the collection of high-resolution images that can be reconstructed into realistic surface representations of the mini-core surfaces. Elemental data (representative of mineralogy) can also be added using a combined backscattered electron and X-ray (BEX) detector. Currently, these reconstructions can be used as a useful tool for the analysis of both carbonate and siliciclastic geological materials. Further work may allow such reconstructions to aid in the improvement of resolution in micro-CT scans and the direct identification of mineral phases within such scans. Full article

(1) Background: This study aimed to investigate the changes in core temperature of Cyan-shank partridge chickens with continuously increased ambient temperature at different relative humidity (RH) levels. (2) Methods: Thirty birds were selected at the age of 35 days and randomly divided and housed in three artificial climate chambers. Each chamber was set at one of three different RH levels (50%, 65%, and 80%), and the ambient temperature was increased by 1.0 °C per 0.5 h from 24.0 to 34.0 °C. The core temperature was tested at 1.0 h intervals, and the ambient temperature in the chambers was recorded using mini temperature data loggers. Data were collected continuously for three days at the ages of 35, 42, and 49 days. The broken-line model (BLM) was used to calculate the inflection point temperature (IPT) and basal core temperature (constant). (3) Results: Both RH and age had no significant influence on the IPT. With increasing ambient temperature, the average IPT values of birds measured at the three ages were 26.52, 27.02, and 26.71 °C at the RH levels of 50%, 65%, and 80%, respectively. A significant downward trend in basal core temperature was observed as the birds aged from 35 to 42 days (p < 0.05). (4) Conclusions: the core temperature of the chicken gradually decreased as the age increased. During the hot summer months, it is better to keep the ambient temperature less than 26.5 °C to avoid the excessive increase in core temperature in Cyan-shank partridge chicken at the ages from 35 to 49 days. Full article

Background/Objectives: The Agenesis of maxillary lateral incisors occurs with a variable prevalence in different ethnic groups, and there is a need for a temporary replacement until maturity has been reached in patients for whom the replacement solution has been chosen. This study aims to analyze the scientific evidence available to date concerning the use of mini-screw implant (MSI)-supported pontics for the transitional management of permanent maxillary lateral incisors’ agenesis in developmental age subjects. Methods: Electronic research was conducted using four databases: PubMed, Clarivate Analytics/Web of Science Core Collection, Scopus, and the Wiley/Cochrane Library. Six studies were included in the final review. Data were extracted based on the first and second author, year of publication, study design, sample characteristics, mini-screw implant (MSI) characteristics, MSI insertion and loading protocol, characteristics of the prosthetic component, and outcomes during the follow-up time. Results: Clinical outcomes were proven positive in all studies. In only one study did MSIs show mobility and consequent failure after one month. Discoloration of the prosthetic part proved to be the main complication. Conclusions: The comparison with conventional removable prostheses and fixed dental prostheses revealed that MSI-supported pontics are a viable alternative and a promising temporary solution until the end of growth. Further studies to standardize protocols and assess long-term outcomes are needed. Full article

Background/Objectives: Cognitive impairment represents a core and prodromal clinical feature of cerebral amyloid angiopathy (CAA). We sought to assess specific cognitive domains which are mainly affected among patients with CAA and to investigate probable associations with neuroimaging markers and Cerebrospinal Fluid (CSF) biomarkers. Methods: Thirty-five patients fulfilling the Boston Criteria v1.5 or v2.0 for the diagnosis of probable/possible CAA were enrolled in this prospective cohort study. Brain Magnetic Resonance Imaging and CSF biomarker data were collected. Every eligible participant underwent a comprehensive neurocognitive assessment. Spearman’s rank correlation tests were used to identify possible relationships between the Addenbrooke’s Cognitive Examination—Revised (ACE-R) sub-scores and other neurocognitive test scores and the CSF biomarker and neuroimaging parameters among CAA patients. Moreover, linear regression analyses were used to investigate the effects of CSF biomarkers on the ACE-R total score and Mini-Mental State Examination (MMSE) score, based on the outcomes of univariate analyses. Results: Cognitive impairment was detected in 80% of patients, and 60% had a coexistent Alzheimer’s disease (AD) pathology based on CSF biomarker profiles. Notable correlations were identified between increased levels of total tau (t-tau) and phosphorylated tau (p-tau) and diminished performance in terms of overall cognitive function, especially memory. In contrast, neuroimaging indicators, including lobar cerebral microbleeds and superficial siderosis, had no significant associations with cognitive scores. Among the CAA patients, those without AD had superior neurocognitive test performance, with significant differences observed in their ACE-R total scores and memory sub-scores. Conclusions: The significance of tauopathy in cognitive impairment associated with CAA may be greater than previously imagined, underscoring the necessity for additional exploration of the non-hemorrhagic facets of the disease and new neuroimaging markers. Full article

Broomcorn millet (Panicum miliaceum L.) is a crop with a good ability to adapt to the environment. Over 8800 accessions have been collected in the national gene bank of China. The huge quantity of germplasms made it difficult for analysis and evaluation. Although a broomcorn millet core collection (CC) comprising 780 accessions was established, the number is still too large for researchers to explore in depth. In this study, the genetic diversity of 634 broomcorn millet accessions from the core collection was analyzed based on SSR markers. A mini-core collection (MC) containing 256 accessions was extracted. The mini-core collection accounted for less than half of the original core collection and only about 2.8% of the total resources but still provided a good representation. In addition, the results of this study validated that Shanxi is the origin of broomcorn millet, and accessions from the South region may contain novel genes. In conclusion, this study provides a comprehensive characterization of the genetic diversities of broomcorn millet core collection in China. Moreover, an MC may aid in reasonably and efficiently selecting materials for broomcorn millet breeding as researchers could screen for aimed genetic characters within a smaller scope. Full article

Drought is a destructive abiotic stress that affects all critical stages of peanut growth such as emergence, flowering, pegging, and pod filling. The development of a drought-tolerant variety is a sustainable strategy for long-term peanut production. The U.S. mini-core peanut germplasm collection was evaluated for drought tolerance to the middle-season drought treatment phenotyping for pod weight, pod count, relative water content (RWC), specific leaf area (SLA), leaf dry matter content (LDMC), and drought rating. A genome-wide association study (GWAS) was performed to identify minor and major QTLs. A total of 144 QTLs were identified, including 18 significant QTLs in proximity to 317 candidate genes. Ten significant QTLs on linkage groups (LGs) A03, A05, A06, A07, A08, B04, B05, B06, B09, and B10 were associated with pod weight and pod count. RWC stages 1 and 2 were correlated with pod weight, pod count, and drought rating. Six significant QTLs on LGs A04, A07, B03, and B04 were associated with RWC stages 1 and 2. Drought rating was negatively correlated with pod yield and pod count and was associated with a significant QTL on LG A06. Many QTLs identified in this research are novel for the evaluated traits, with verification that the pod weight shared a significant QTL on chromosome B06 identified in other research. Identified SNP markers and the associated candidate genes provide a resource for molecular marker development. Verification of candidate genes surrounding significant QTLs will facilitate the application of marker-assisted peanut breeding for drought tolerance. Full article

Sorghum (Sorghum bicolor L.) ranks fifth as the most crucial cereal crop globally, yet its seed morphology remains relatively unexplored. This study investigated seed morphology in sorghum based on 115 mini-core and 130 Senegalese germplasms. Eight seed morphology traits encompassing size, shape, and color parameters were assessed. Statistical analyses explored potential associations between these traits and resistance to three major sorghum diseases: anthracnose, head smut, and downy mildew. Furthermore, genome-wide association studies (GWAS) were conducted using phenotypic data from over 24,000 seeds and over 290,000 publicly available single nucleotide polymorphisms (SNPs) through the Genome Association and Prediction Integrated Tool (GAPIT) R package. Significant SNPs associated with various seed morphology traits were identified and mapped onto the reference sorghum genome to identify novel candidate defense genes. Full article

Peanut (Arachis hypogaea L.) plants respond to drought stress through changes in morpho-physiological and agronomic characteristics that breeders can use to improve the drought tolerance of this crop. Although agronomic traits, such as plant height, lateral growth, and yield, are easily measured, they may have low heritability due to environmental dependencies, including the soil type and rainfall distribution. Morpho-physiological characteristics, which may have high heritability, allow for optimal genetic gain. However, they are challenging to measure accurately at the field scale, hindering the confident selection of drought-tolerant genotypes. To this end, aerial imagery collected from unmanned aerial vehicles (UAVs) may provide confident phenotyping of drought tolerance. We selected a subset of 28 accessions from the U.S. peanut mini-core germplasm collection for in-depth evaluation under well-watered (rainfed) and water-restricted conditions in 2018 and 2019. We measured morpho-physiological and agronomic characteristics manually and estimated them from aerially collected vegetation indices. The peanut genotype and water regime significantly (p < 0.05) affected all the plant characteristics (RCC, SLA, yield, etc.). Manual and aerial measurements correlated with r values ranging from 0.02 to 0.94 (p < 0.05), but aerially estimated traits had a higher broad sense heritability (H²) than manual measurements. In particular, CO₂ assimilation, stomatal conductance, and transpiration rates were efficiently estimated (R² ranging from 0.76 to 0.86) from the vegetation indices, indicating that UAVs can be used to phenotype drought tolerance for genetic gains in peanut plants. Full article

Domestication and extensive selection in the development of modern, high-yielding commercial groundnut cultivars have resulted in the selection of an undesirable trait known as in situ germination, which is also referred to as the pre-harvest sprouting of seeds. This is particularly prevalent in regions where humid weather coincides with the harvest season. Delayed harvesting and pre-sprouting can cause production losses and increase the chances of aflatoxin contamination, thereby impeding the quality and kernel yield. Breeding early maturing groundnut cultivars with 2–3 weeks of fresh seed dormancy, particularly in Spanish-type cultivars, enhances the sustainability of agriculture. In this context, we conducted a comprehensive evaluation of a groundnut mini-core collection, a major resource for genetic diversity, for fresh seed dormancy using an in vitro germination assay for two seasons, viz., rainy 2022 and post-rainy 2022–2023 at ICRISAT (Hyderabad). To enhance the effectiveness and accuracy of traditional breeding methods via the use of markers for marker-assisted selection, we performed molecular screening of the mini-core accessions using two allele-specific markers. The GMFSD1 marker was successfully validated by effectively differentiating dormant and non-dormant genotypes. By employing phenotypic and marker data, we identified a set of accessions, viz., ICG 5827 (Virginia Runner), ICG 11457 (Virginia Runner), ICG 7000 (Virginia Bunch), and ICG 11322 (Virginia Bunch) of sub spp. hypogaea var. hypogaea and ICG 9809 (Spanish Bunch) of sub spp. fastigiata var. vulgaris that exhibited a fresh seed dormancy period ranging from 2 to 3 weeks. These identified accessions hold potential as donors in breeding programs that are designed to address the groundnut production needs in various cropping systems across different countries. The validated marker, particularly GMFSD1, demonstrated considerable potential for facilitating faster breeding of groundnut cultivars with the desired dormancy using marker-assisted selection. This research provides a foundation to expediting groundnut breeding programs and offers opportunities to mitigate pre-harvest sprouting, ultimately improving seed quality and productivity in groundnut-producing regions. Full article

Due to the rapid increase in private car ownership in China, most cities face the problem of insufficient parking spaces, leading to frequent occurrences of parking space conflicts. There is a wide variety of parking locks available on the market. However, most of them lack advanced intelligence and cannot cater to the growing diverse needs of people. The present study attempts to devise a smart parking lock to tackle this issue. Specifically, the smart parking lock uses a Raspberry Pi as the core controller, senses the vehicle with an ultrasonic ranging module, and collects the license plate image with a camera. In addition, algorithms for license plate recognition based on traditional image-processing methods typically require a high pixel resolution, but their recognition accuracy is often low. Therefore, we propose a new algorithm called UNET-GWO-SVM to achieve higher accuracy in embedded systems. Moreover, we developed a WeChat mini program to control the smart parking lock. Field tests were conducted on campus to evaluate the performance of the parking locks. The test results show that the corresponding effective unlocking rate is 99.0% when the recognition error is less than two license plate characters. The average time consumption is controlled at about 2 s. It can meet real-time requirements. Full article