Search Results (1,593)

A two-factor experiment was conducted using the cultivar ‘Xin you No. 2’ (Citrullus lanatus) to identify an efficient and green production model for drip-irrigated watermelon under plastic mulch in Southern Xinjiang. A basal organic fertilizer was applied at 2250 kg·ha⁻¹. The experimental design comprised three irrigation levels, maintaining soil moisture at 60–70% (W1), 70–80% (W2), and 80–90% (W3) of field capacity, and three nitrogen application rates: 180 (N1), 240 (N2), and 300 (N3) kg·ha⁻¹. This study systematically investigated the effects of water–nitrogen coupling on watermelon yield, quality, water use efficiency, and nitrogen partial factor productivity. The W2N2 treatment achieved the highest yield of 64,617.59 kg·ha⁻¹. Vine length, stem diameter, and dry matter accumulation increased with increasing nitrogen application under the W1 and W2 irrigation levels, but exhibited an initial increase followed by a decrease under the W3 condition. Water restriction combined with increased nitrogen application significantly enhanced the central sugar content, with the W1N3 treatment increasing it by 15.69% compared to CK. Conversely, the W1N1 treatment was most conducive to vitamin C accumulation, showing a 49.88% increase over CK. The total water consumption across the different treatments ranged from 362.12 to 493.92 mm. Both water use efficiency and irrigation water use efficiency reached their maximum values under the W1N3 treatment, at 21.94 kg·m⁻³ and 35.05 kg·m⁻³, respectively. In contrast, the highest partial factor productivity of nitrogen (NPFP) was observed under W3N1, reaching 239.33 kg·kg⁻¹. A comprehensive multi-index evaluation using the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method indicated that the W1N3 treatment achieved the highest relative closeness (0.669), identifying it as the optimal water–nitrogen combination. Full article

Dynamic network conditions in precision agriculture motivate a scalable, privacy preserving federated learning architecture that tightly integrates ground-based edge intelligence with a space-assisted hierarchical aggregation layer. In Phase 1, heterogeneous tractors act as intelligent farm nodes that train local models, form capability- and task-aware clusters, and employ Network Quality Index (NQI)-driven scheduling, similarity-based check pointing, and compressed transmissions to cope with highly variable 3G/4G/5G connectivity. In Phase 2, cluster drivers synchronize with Low Earth Orbit (LEO) and Geostationary Earth Orbit (GEO) satellites that perform regional and global aggregation using staleness- and fairness-aware weighting, while end-to-end Salsa20 + MAC encryption preserves the confidentiality and integrity of all model updates. Across two representative tasks—nutrient prediction and crop health assessment—our full hierarchical system matches or exceeds centralized performance (e.g., AUC 0.92 vs. 0.91 for crop health) while reducing uplink traffic by ∼90% relative to vanilla FedAvg and cutting the communication energy proxy by more than 4×. The proposed fairness-aware GEO aggregation substantially narrows regional performance gaps (standard deviation of AUC across regions reduced from 0.058 to 0.017) and delivers the largest gains in low-connectivity areas (AUC 0.74 → 0.88). These results demonstrate that coupling on-farm intelligence with multi-orbit federated aggregation enables near-centralized model quality, strong privacy guarantees, and communication efficiency suitable for large-scale, connectivity-challenged agricultural deployments. Full article

Maintaining color constancy in polymer extrusion processes is a key difficulty in manufacturing applications, as fluctuations in processing parameters greatly influence pigment dispersion and the quality of the finished product. Preliminary historical data mining analysis was conducted in 2009. This work concentrates on Opaque PC Grade 5, which constituted 2.43% of the pigment; it contained 10 PPH of resin2 with a Melt Flow Index (MFI) of 6.5 g/10 min and 90 PPH of resin1. It also employs a fixed resin composition with an MFI of 25 g/10 min. This research identified the significant processing parameters (PPs) contributing to the lowest color deviation. Interactions between processing parameters, for the same color formulation, were analyzed using statistical methods under various processing conditions. A principle-driven General Trends (GT) diagnostic procedure was applied, wherein each parameter was individually varied across five levels while holding others constant. Particle size distribution (PSD) and colorimetric data (CIE Lab*) were systematically measured and analyzed. To complete this, correlations for the impact of temperature (Temp) on viscosity, particle characteristics, and color quality were studied by characterizing viscosity, Digital Optical Microscopy (DOM), and particle size distribution at various speeds. The samples were characterized for viscosity at three temperatures (230, 255, 280 °C) and particle size distribution at three speeds: 700, 750, 800 rpm. This study investigates particle processing features, such as screw speed and pigment size distribution. The average pigment diameter and the fraction of small particles were influenced by the speed of 700–775 rpm. At 700 rpm, the mean particle size was 2.4 µm, with 61.3% constituting particle numbers. The mean particle size diminished to 2 µm at 775 rpm; however, the particle count proportion escalated to 66% at 800 rpm. This research ultimately quantifies the relative influence of particle size on the reaction, resulting in a color value of 1.36. The mean particle size and particle counts are positively correlated; thus, reduced pigment size at increased speed influences color response and quality. The weighted contributions of the particles, 51.4% at 700 rpm and 48.6% at 800 rpm, substantiate the hypothesis. Further studies will broaden the GT analysis to encompass multi-parameter interactions through design experiments and will test the diagnostic assessment procedure across various polymer grades and colorants to create robust models of prediction for industrial growth. The global quality of mixing polycarbonate compounding constituents ensured consistent and smooth pigment dispersion, minimizing color streaks and resulting in a significant improvement in color matching for opaque grades. Full article

In order to screen high-quality processed tomato germplasm resources, the present research measured the content of quality indicators—lycopene, soluble solids, total acidity, total sugar, and vitamin C—in mature fruits of 113 processed tomato high-generation inbred lines. Comprehensive evaluations of germplasm quality were conducted through genetic diversity analysis, correlation analysis, principal component analysis, and cluster analysis. The results indicated that the variability of the five quality traits in the materials under test was relatively high, with a range of variation from 12.21% to 39.04%. Total sugar exhibited the greatest variation, while soluble solids content showed the least variation. The genetic diversity index ranged from 1.899 to 2.064, with total sugar, vitamin C, and lycopene showing high genetic variation. Soluble solids content was significantly positively correlated with lycopene, total sugar, and total acidity, while lycopene content was significantly positively correlated with total sugar. Vitamin C showed weaker correlations with other traits, but exhibited a significant negative correlation with total sugar. Total acidity had relatively simple correlations with other traits, being significantly correlated only with soluble solids. The three principal components extracted from the principal component analysis all had eigenvalues above 0.8%, contributing to a cumulative contribution rate of 77.435%. Through cluster analysis, the tested materials were divided into six major groups at an Euclidean distance of 15. Group I serves as candidate materials for breeding varieties with good basic quality and high vitamin C content. Group II stood out in terms of high sugar and lycopene content, suitable for developing tomato sauce or juice products with high vibrancy and sweetness. Group III had a high nutritional value and vibrant color, serving as core germplasm resources for breeding high-end processing-specific varieties. Group IV had high soluble solids content, making it a parent source for improving the viscosity and flavor of sauce tomatoes. Group V was suitable for specific formulations requiring high acidity or as breeding materials for high-acidity characteristics. Group VI had limited processing potential and should be used cautiously in breeding. The comprehensive evaluation results showed that the top five germplasm resources in terms of score were W119, 61, 82, 83, and W144. This study enriched the high-quality processed tomato germplasm resources and provided parental resources for quality breeding of processed tomatoes. Full article

Background: Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity, mortality, and healthcare utilization. Lung volume reduction surgery improves outcomes in a select cohort but portends high morbidity. Bronchoscopic lung volume reduction (BLVR) is a less invasive, reversible manner of lung volume reduction, using one-way valves to improve lung function, quality of life, and exercise capacity. Nevertheless, knowledge gaps persist regarding factors that predict procedural success. Methods: We retrospectively reviewed 142 patients who underwent BLVR at the University of Chicago between December 2018 and July 2024 to assess the relationship between comorbidities and procedural outcomes. Using logistic and multinomial regression, we determined odds ratios (ORs) for a binary outcome of success and failure and relative risk ratios (RRRs) for failure sub-categories relative to procedural success. Results: We observed a procedural success rate of 48.1% and pneumothorax prevalence of 21.8%. After adjusting for age, sex, race, and body mass index (BMI), comorbidities associated with procedural failure included chronic kidney disease (CKD), congestive heart failure (CHF), anemia, and a BMI, Obstruction, Dyspnea and Exercise (BODE) Index of 5 or greater. Obstructive sleep apnea (OSA) was associated with procedural success. Conclusions: Comorbidities associated with dyspnea appear to have a significant effect on procedural success in BLVR. Full article

The Finite State Model Predictive Control (FSMPC) of variable speed drives is the subject of many works in the recent literature. Many variants of FSMPC exist, each aiming at an aspect such as the complexity of the cost function, switching frequency, current quality, etc. In the case of multiphase drives, two popular variants are the monovector and multivector techniques. Despite past efforts to compare different techniques, the field must still reach a consensus regarding the relative merits of each one. This paper presents a new method to compare two families of FSMPC. The method is based on a reduced set of figures of merit using the current modulation index as the variable. The comparison is made for the equal usage of the power converter in terms of commutations. The results point to better values for the figures of merit for the monovector that, in addition, portrays more flexibility and better DC link usage. Full article

Background: Plantar fasciitis is a prevalent musculoskeletal disease characterized by heel pain and functional impairment. Both high-intensity laser therapy (HILT) and extracorporeal shockwave therapy (ESWT) have demonstrated efficacy in managing plantar fasciitis; however, their relative effectiveness remains unclear. Purpose: This systematic review and meta-analysis aimed to compare the effects of HILT and ESWT for treating plantar fasciitis. Methods: A comprehensive literature search of PubMed, the Cochrane Library, EMBASE, and Scopus was conducted from inception to 13 July 2025 to identify randomized controlled trials (RCTs) investigating both interventions. Two reviewers independently extracted data and assessed the methodological quality of the trials using the Physiotherapy Evidence Database (PEDro) scale. The certainty of evidence was evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. The primary outcomes of this study were pain intensity and foot function. The visual analog scale (VAS) was used for pain assessment. Foot function was evaluated by the total scores of the Foot Function Index (FFI) and American Orthopedic Foot & Ankle Society Scale (AOFAS) and the activities of daily living (ADL) subscale scores of the Foot and Ankle Ability Measure (FAAM). Outcomes were assessed at the end of treatment and during short-, medium-, and long-term follow-ups. The meta-analysis utilized standardized mean differences (SMDs), assessed heterogeneity using the I² test, applied the inverse variance method for pooling continuous variables, and employed a random-effects model because of the variable study methods used across the included articles. Results with p < 0.05 were considered statistically significant. The I² test was used to objectively measure statistical heterogeneity, with I² ≥ 50% indicating significant heterogeneity. Results: Five RCTs met the inclusion criteria, with methodological quality scores ranging from 6 to 7 on the 10-point PEDro scale. In total, 120 participants received HILT and 116 received ESWT. Regarding pain intensity (VAS), no statistically significant differences were detected between HILT and ESWT at any time point, including short-term morning pain (SMD = −0.11, 95% CI −0.42 to 0.19, p = 0.40), resting pain (SMD = 0.01, 95% CI −0.48 to 0.49, p = 0.05), and activity pain (SMD = −0.08, 95% CI −0.41 to 0.26, p = 0.89), as well as medium-term morning, resting, and activity pain (all p > 0.05). For foot function (FFI), the pooled analysis of all studies showed no significant short-term difference (SMD = 0.37, 95% CI −0.22 to 0.95, p = 0.01; I² = 73%); however, a subsequent sensitivity analysis, which excluded one studyreduced heterogeneity to 0% and revealed a significant short-term advantage of ESWT (SMD = 0.64, 95% CI 0.32 to 0.95, p < 0.01). Medium-term FFI also favored ESWT (SMD = 0.53, 95% CI 0.14 to 0.92, p < 0.01). Overall, the certainty of evidence ranged from moderate to low, mainly due to risk of bias and heterogeneity, as assessed by the GRADE approach. Conclusions: While the pooled results suggested a trend toward greater functional improvement with ESWT than with HILT in the short- and medium-term, the effect sizes were small. No significant between-group differences were observed in pain-related outcomes. Given the limited number of available trials and variability in treatment protocols, current evidence remains insufficient to draw definitive conclusions about the comparative efficacy of ESWT and HILT. Further high-quality, large-scale randomized controlled trials with standardized methodologies are needed to better inform clinical decision-making. Full article

This study examines the relationship between national open educational resource (OER) policies and Sustainable Development Goal 4 (SDG4) outcomes across 187 countries between 2015 and 2024, with particular attention to the moderating role of artificial intelligence (AI) readiness. Despite widespread optimism about digital technologies as catalysts for universal education, systematic evidence linking formal OER policy frameworks to measurable improvements in educational access and completion remains limited. The analysis employs fixed effects and difference-in-differences estimation strategies using an unbalanced panel dataset comprising 435 country-year observations. The research investigates how OER policies associate with primary completion rates and out-of-school rates while testing whether these relationships depend on countries’ technological and institutional capacity for advanced technology deployment. The findings reveal that AI readiness demonstrates consistent positive associations with educational outcomes, with a ten-point increase in the readiness index corresponding to approximately 0.46 percentage point improvements in primary completion rates and 0.31 percentage point reductions in out-of-school rates across fixed effects specifications. The difference-in-differences analysis indicates that OER-adopting countries experienced completion rate increases averaging 0.52 percentage points relative to non-adopting countries in the post-2020 period, though this estimate remains statistically imprecise (p equals 0.440), preventing definitive causal conclusions. Interaction effects between policies and readiness yield consistently positive coefficients across specifications, but these associations similarly fail to achieve conventional significance thresholds given sample size constraints and limited within-country variation. While the directional patterns align with theoretical expectations that policy effectiveness depends on digital capacity, the evidence should be characterized as suggestive rather than conclusive. These findings represent preliminary assessment of policies in early implementation stages. Most frameworks were adopted between 2019 and 2022, providing observation windows of two to five years before data collection ended in 2024. This timeline proves insufficient for educational system transformations to fully materialize in aggregate indicators, as primary education cycles span six to eight years and implementation processes operate gradually through sequential stages of content development, teacher training, and institutional adaptation. The analysis captures policy impacts during formation rather than at equilibrium, establishing baseline patterns that require extended longitudinal observation for definitive evaluation. High-income countries demonstrate interaction coefficients between policies and readiness that approach marginal statistical significance (p less than 0.10), while low-income subsamples show coefficients near zero with wide confidence intervals. These patterns suggest that OER frameworks function as complementary interventions whose effectiveness depends critically on enabling infrastructure including digital connectivity, governance quality, technical workforce capacity, and innovation ecosystems. The results carry important implications for how countries sequence educational technology reforms and how international development organizations design technical assistance programs. The evidence cautions against uniform policy recommendations across diverse contexts, indicating that countries at different stages of digital development require fundamentally different strategies that coordinate policy adoption with foundational capacity building. However, the modest short-term effects and statistical imprecision observed here should not be interpreted as evidence of policy ineffectiveness, but rather as confirmation that immediate transformation is unlikely given implementation complexities and temporal constraints. The study contributes systematic cross-national evidence on aggregate policy associations while highlighting the conditional nature of educational technology effectiveness and establishing the need for continued longitudinal research as policies mature beyond the early implementation phase captured in this analysis. Full article

Melasma management is challenged by heterogeneity in patient presentation, particularly among individuals with darker skin tones. This study applied k-means clustering, an unsupervised machine learning algorithm that partitions data into k distinct clusters based on feature similarity, to identify patient subgroups that could provide a hypothesis-generating framework for future precision strategies. We analysed clinical and demographic data from 150 South African women with melasma using k-means clustering. The optimal number of clusters was determined using the Elbow Method and Bayesian Information Criterion (BIC), with t-distributed stochastic neighbour embedding (t-SNE) visualization for assessment. The k-Means algorithm identified seven exploratory patient clusters explaining 52.6% of the data variability (R² = 0.526), with model evaluation metrics including BIC = 951.630 indicating optimal model fit and a Silhouette Score of 0.200 suggesting limited separation between clusters consistent with overlapping clinical phenotypes, while the Calinski-Harabasz index of 26.422 confirmed relatively well-defined clusters that were characterized by distinct profiles including “The Moderately Sun Exposed Young Women”, “Elderly Women with Long-Term Melasma”, and “Younger Women with Severe Melasma”, with key differentiators being age distribution and menopausal status, melasma severity and duration patterns, sun exposure behaviours, and quality of life impact profiles that collectively define the unique clinical characteristics of each subgroup. This study demonstrates how machine learning can identify clinically relevant patient subgroups in melasma. Aligning interventions with the characteristics of specific clusters can potentially improve treatment efficacy. Full article

A well-designed layout for urban parks plays a crucial role in constructing livable cities and enhancing residents’ well-being. The provision of age-friendly park access is fundamental to building an elderly-friendly city. However, previous studies have lacked comprehensive analyses that integrate the distribution of the elderly population, park accessibility, park quality, environmental characteristics, and social equity within a unified framework. Specifically, the supply–demand imbalance mechanism underlying the spatial variations in accessibility has not been adequately addressed. This study employs an improved two-step floating catchment area (2SFCA) method, combined with Lorenz curves and urban park-adapted Gini coefficients, to examine the supply–demand relationship and allocation differences between the elderly population and parks at the neighborhood and community levels. The analysis highlights issues related to equity and accessibility and explores their spatial disparity and influencing factors. The key findings are as follows: (1) The classic 2SFCA model exhibits significant biases in evaluating park supply–demand relationships, accessibility, and equity at a fine-grained scale, indicating the necessity of high-precision modeling. (2) Park accessibility in the Old City of Nanjing follows a dual-ring pattern of high accessibility, contrasted with clustered areas of low accessibility, while accessibility equity shows a central–peripheral gradient. Overall equity is relatively low, with good walking accessibility within only about one-third of communities. (3) Park supply levels, neighborhood construction year, and plot ratios are the primary factors influencing park accessibility for elderly residents. The comprehensive aging index is positively correlated with the equity in park layout, whereas housing prices and neighborhood size do not exhibit a simple linear relationship with park accessibility or equity for elderly residents. These findings provide a comprehensive and realistic perspective for understanding elderly park accessibility and equity, offering decision-making references for enhancing urban livability, managing an aging society, and formulating spatial equity policies in the future. Full article

Predicting internal quality parameters, such as Brix and water content, of apples, is essential for quality control. Existing near-infrared (NIR) and hyperspectral imaging (HSI)-based techniques have limited applicability due to their dependence on equipment and environmental sensitivity. In this study, a transportable quality assessment system was proposed using spatiotemporal domain analysis with long-wave infrared (LWIR)-based thermal diffusion phenomics, enabling non-destructive prediction of the internal Brix of apples during transport. After cooling, the thermal gradient of the apple surface during the cooling-to-equilibrium interval was extracted. This gradient was used as an input variable for multiple linear regression, Ridge, and Lasso models, and the prediction performance was assessed. Overall, 492 specimens of 5 cultivars of apple (Hongro, Arisoo, Sinano Gold, Stored Fuji, and Fuji) were included in the experiment. The thermal diffusion response of each specimen was imaged at a sampling frequency of 8.9 Hz using LWIR-based thermal imaging, and the temperature changes over time were compared. In cross-validation of the integrated model for all cultivars, the coefficient of determination (R²_cv) was 0.80, and the RMSEcv was 0.86 °Brix, demonstrating stable prediction accuracy within ±1 °Brix. In terms of cultivar, Arisoo (Cultivar 2) and Fuji (Cultivar 5) showed high prediction reliability (R²_cv = 0.74–0.77), while Hongro (Cultivar 1) and Stored Fuji (Cultivar 4) showed relatively weak correlations. This is thought to be due to differences in thermal diffusion characteristics between cultivars, depending on their tissue density and water content. The LWIR-based thermal diffusion analysis presented in this study is less sensitive to changes in reflectance and illuminance compared to conventional NIR and visible light spectrophotometry, as it enables real-time measurements during transport without requiring a separate light source. Surface heat distribution phenomics due to external heat sources serves as an index that proximally reflects changes in the internal Brix of apples. Later, this could be developed into a reliable commercial screening system to obtain extensive data accounting for diversity between cultivars and to elucidate the effects of interference using external environmental factors. Full article

Non-destructive evaluation techniques are increasingly recognised as effective alternatives to destructive testing for estimating the compressive strength of lightweight aggregate concrete (LWAC). Among these, ultrasonic pulse velocity (UPV) is a well-established and widely employed method, characterised by its speed, non-invasiveness, and relative simplicity of implementation. In this study, an experimental dataset comprising 640 core segments from 160 cylindrical specimens, provided for analysis, was investigated. Each segment was described by physical and processing variables or features, including lightweight aggregate (LWA) and concrete densities, casting and vibration times, experimental dry density, and P-wave velocity obtained through UPV testing. A segregation index, derived from UPV measurements and defined as the ratio of local to mean P-wave velocity within each specimen, was also considered, following approaches previously suggested in the literature. A range of machine learning techniques was applied to assess the predictive capacity of local P-wave velocity and segregation index. Most ensemble-based methods and support vector regression (SVR) achieved the highest predictive performance when the segregation index was excluded, suggesting that its inclusion did not improve the predictive ability of the models. By contrast, Gaussian process regression (GPR) showed slight improvements when the segregation index was included. The results confirmed that the P-wave velocity measured by UPV testing is a reliable non-destructive predictor of compressive strength in LWAC. At the same time, the added value of the segregation index remained negligible under conditions of low segregation, as reflected by segregation index values above 0.8. These findings highlight the practical potential of integrating UPV-based measurements with data-driven modelling to enhance the reliability of concrete characterisation and quality control. Full article

Background/Objectives: Chrononutrition—the temporal organization of food intake relative to circadian rhythms—has emerged as an important factor in cardiometabolic health. While meal timing is typically analyzed as an isolated variable, limited research has examined integrated meal timing patterns, and no study has systematically compared clustering approaches for their identification. This cross-sectional study compared four clustering techniques—traditional (K-means, Hierarchical) and non-traditional (Gaussian Mixture Models (GMM), Spectral)—to identify meal timing patterns from habitual breakfast, lunch, and dinner times. Methods: The sample included 388 Mexican university students (72.8% female). Patterns were characterized using sociodemographic, anthropometric, food intake quality, and chronotype data. Clustering method concordance was assessed via Adjusted Rand Index (ARI). Results: We identified five patterns (Early, Early–Intermediate, Late–Intermediate, Late, and Late with early breakfast). No differences were observed in BMI, waist circumference, or age among clusters. Chronotype aligned with patterns (morning types overrepresented in early clusters). Food intake quality differed significantly, with more early eaters showing healthy intake than late eaters. Concordance across clustering methods was moderate (mean ARI = 0.376), with the highest agreement between the traditional and non-traditional techniques (Hierarchical–Spectral = 0.485 and K-means-GMM = 0.408). Conclusions: These findings suggest that, while traditional and non-traditional clustering techniques did not identify identical patterns, they identified similar core structures, supporting complementary pattern detection across algorithmic families. These results highlight the importance of comparing multiple methods and transparently reporting clustering approaches in chrononutrition research. Future studies should generate meal timing patterns in university students from other contexts and investigate whether these patterns are associated with eating patterns and cardiometabolic outcomes. Full article

Silicon–nitride (SiN) waveguides have emerged as fundamental building blocks in silicon photonic integrated circuits (Si-PICs), offering advantages that compensate for the intrinsic limitations of silicon-on-insulator (SOI) and silica-on-silicon (SOS) platforms. In this work, two sizes of single-mode SiN strip waveguides are investigated: (i) 600 nm wide strip waveguide cores on a 400 nm thick Si₃N₄ film and (ii) 1.0 µm wide strip waveguide cores on a 1.0 µm thick Si₃N₄ film. First, we design two AWG architectures and develop a generalized theoretical model for one of the key specifications—polarization mode dispersion (PMD)—by considering a pair of orthogonal polarization states in these two waveguides. Then, as the two-size SiN waveguides are generally fabricated via multiple operating processes of coating, photolithography, and etching, we investigate the dependences of PMD performances on the device errors of the two AWG architectures caused by the coating/manufacturing qualities and accuracies, and the dependences of PMD performance on the refractive index errors of the waveguide core. As a consequence, the softwaretool simulations for the two AWG architectures of 40-channel 0.8 nm channelspacing show that the average PMDs of the above two waveguide sizes are <0.50 ps and <0.35 ps, respectively, and the PMD responses to the ±10% fabrication error are < ±0.20 ps and ±10% fluctuation, respectively, but the ±2.5% variations have no obvious impacts upon the PMD performance. Therefore, it turns out that the PMD performance of a smaller waveguide has a relatively strong error sensitivity to the AWG architecture, while the larger waveguide size has a relatively weak error sensitivity to the AWG architecture. Full article

Alfalfa cultivation is an effective way to achieve soil improvement while utilizing saline soils. Irrigation and drainage, as physical measures to leach salts, can effectively reduce the soil salt content, while application of organic fertilizer fermented with an effective microorganism (EM) may further enhance the improvement effect of saline–alkaline soil by improving soil fertility and microbial community structure. However, there is still a lack of systematic assessment on the effects of applying these three measures on the saline soil–plant system. In this study, we used alfalfa as the plant material and set three water depths of 8 mm (IR1), 16 mm (IR2), and 24 mm (IR3) under the condition of irrigating every 10 days with remote-controlled timed and quantitative irrigation, which is the most acceptable to farmers in the era of smart agriculture. EM organic fertilizer dosage was designed as 0 kg/ha (CK), 1500 kg/ha (OF1), 3000 kg/ha (OF2), 4500 kg/ha (OF3), and 6000 kg/ha (OF4). The multiple-crop alfalfa yield, quality (crude protein (CP), neutral detergent fiber (NDF), and acid detergent fiber (ADF)), and soil electrical conductivity (EC) were observed. The results showed that after the application of EM organic fertilizer, the soil’s EC value of fertilized treatments was higher than that of CK, but this difference became smaller with the prolongation of alfalfa’s growing period, implying that EM organic fertilizer could absorb more soil salts by promoting alfalfa’s growth; the water depth was obviously negatively correlated with the soil’s EC value, demonstrating that the increase in the water depth had a stronger ability to reduce the soil salts. By the end of the experiment, the soil’s EC values were reduced by 21.4–43.7% for the treatments. The alfalfa yield was significantly increased by EM organic fertilizer application, and the three alfalfa yields were increased by 63.3–69.1%, 65.4–83.6%, and 52.6–56.2%, respectively, when fertilizer application was elevated from CK to OF4. The highest alfalfa yields were all found at IR2OF4, reaching 1164.7, 2637.3 and 2519.7 t/ha, corresponding to the first, second, and third alfalfa crops, respectively. The analysis of alfalfa quality indexes revealed that higher CP values were found in the IR2 treatments, and increasing fertilizer application from OF1–OF4 resulted in an increase in CP values by 2.4–9.1%, 1.5–7.4%, and 0.8–6.7% for the three alfalfa crops. Relatively low NDF and ADF values were observed for alfalfa under IR2 conditions; however, the application of EM organic fertilizer reduced the NDF and ADF values within a certain range. According to the results of the entropy weight evaluation model, IR3OF4, IR3OF2, and IR3OF3 were the top three treatments with the best overall benefits, respectively, with relative closeness values of 0.71, 0.70, and 0.68, in that order, which suggests that the appropriate water depth is 24 mm, while the appropriate EM organic fertilizer dosage is in the range of 3000–6000 kg/ha. There was a pattern observed in our study, in which the treatments with better overall benefits were better distributed at high water depths, which emphasizes the critical role of the irrigation volume in ameliorating saline soils. The conclusions of the study are intended to provide a practical basis for the comprehensive utilization and sustainable development of saline soils. Full article