Search Results (1,008)

This study investigates the engineering characteristics of a newly commissioned higher education building through the Bioharmological Conformity Assessment (BCA) method, specifically using the 2020vEB version. The BCA is a novel evaluation approach that assesses whether a building aligns with the identity of its users and its intended function. The engineering attributes of the structure were assessed across 12 core criteria, encompassing a total of 600 individual parameters. Findings from the BCA inspection indicate that the newly completed building falls into the category of “Near-Standard Building/Minor Modifications Required.” The BCA score was calculated as 398.73, corresponding to a deficiency rate of 25.50%. Notably, significant shortcomings were observed in categories such as user identity and intended use, Physical Characteristics of the Space, and Ecological and Seismological Suitability. Consequently, targeted improvements are necessary to align the building with bioharmological principles, requiring only minor adjustments to rectify the identified deficiencies. Full article

Breast cancer detection through non-invasive and accurate techniques remains a critical challenge in medical diagnostics. This study introduces a deep learning-based framework that leverages a microwave radar system equipped with an arc-shaped array of six antennas to estimate key tumor parameters, including position, size, and depth. This research begins with the evolutionary design of an ultra-wideband octagram ring patch antenna optimized for enhanced tumor detection sensitivity in directional near-field coupling scenarios. The antenna is fabricated and experimentally evaluated, with its performance validated through S-parameter measurements, far-field radiation characterization, and efficiency analysis to ensure effective signal propagation and interaction with breast tissue. Specific Absorption Rate (SAR) distributions within breast tissues are comprehensively assessed, and power adjustment strategies are implemented to comply with electromagnetic exposure safety limits. The dataset for the deep learning model comprises simulated self and mutual S-parameters capturing tumor-induced variations over a broad frequency spectrum. A core innovation of this work is the development of the Attention-Based Feature Separation (ABFS) model, which dynamically identifies optimal frequency sub-bands and disentangles discriminative features tailored to each tumor parameter. A multi-branch neural network processes these features to achieve precise tumor localization and size estimation. Compared to conventional attention mechanisms, the proposed ABFS architecture demonstrates superior prediction accuracy and interpretability. The proposed approach achieves high estimation accuracy and computational efficiency in simulation studies, underscoring the promise of integrating deep learning with conformal microwave imaging for safe, effective, and non-invasive breast cancer detection. Full article

Detection of surface defects can significantly elongate mechanical service time and mitigate potential risks during safety management. Traditional defect detection methods predominantly rely on manual inspection, which suffers from low efficiency and high costs. Some machine learning algorithms and artificial intelligence models for defect detection, such as Convolutional Neural Networks (CNNs), present outstanding performance, but they are often data-dependent and cannot provide guarantees for new test samples. To this end, we construct a detection model by combining Mask R-CNN, selected for its strong baseline performance in pixel-level segmentation, with Conformal Risk Control. The former evaluates the distribution that discriminates defects from all samples based on probability. The detection model is improved by retraining with calibration data that is assumed to be independent and identically distributed (i.i.d) with the test data. The latter constructs a prediction set on which a given guarantee for detection will be obtained. First, we define a loss function for each calibration sample to quantify detection error rates. Subsequently, we derive a statistically rigorous threshold by optimization of error rates and a given guarantee significance as the risk level. With the threshold, defective pixels with high probability in test images are extracted to construct prediction sets. This methodology ensures that the expected error rate on the test set remains strictly bounded by the predefined risk level. Furthermore, our model shows robust and efficient control over the expected test set error rate when calibration-to-test partitioning ratios vary. Full article

Bacillus species have shown the potential to recover rare earth elements (REEs), but strains with adsorption selectivity for terbium(III) remain understudied. In this study, six Bacillus strains with the capability for efficient adsorption of Tb(III) were screened from an ionic rare earth mine and were identified based on 16S rRNA gene sequencing. Adsorption experiments showed that Bacillus sp. DW011 exhibited exceptional Tb(III) adsorption efficiency, with an adsorption rate of 90.45% and adsorption selectivity for heavy rare earth elements. Notably, strain DW011 was also found to be tolerant against Tb(III) with the 24 h 50% lethal concentration (LC₅₀) of 2.62 mM. The biosorption mechanisms of DW011 were investigated using adsorption kinetics, SEM-EDS, and FTIR. The results indicated that the adsorption of strain DW011 conforms to the second-order kinetic model, and the teichoic acid–peptidoglycan network (phosphate-dominated) serves as the primary site for heavy REE adsorption, while carboxyl/amino groups in the biomembrane matrix provide secondary sites for LREEs. This study provides new information that Bacillus strains isolated from ionic rare earth mine deposits have potential as green adsorbents and have high selectivity for the adsorption of heavy REEs, providing a sustainable strategy for REE recovery from wastewaters. Full article

Background: During food processing and storage, traditional protein-based delivery systems encounter significant challenges in maintaining the structural and functional integrity of bioactive compounds, primarily due to their temporal instability. Methods: In this study, a nanocomposite hydrogel was prepared through the co-assembly of a self-assembling peptide, 9-Fluorenylmethoxycarbonyl-phenylalanine-arginine-glycine-aspartic acid-phenylalanine (Fmoc-FRGDF), and hyaluronic acid (HA). The stability of this hydrogel as a quercetin (Que) delivery carrier was systematically investigated. Furthermore, the impact of Que co-assembly on the microstructural evolution and physicochemical properties of the hydrogel was characterized. Concurrently, the encapsulation efficiency (EE%) and controlled release kinetics of Que were quantitatively evaluated. Results: The findings indicated that HA significantly reduced the storage modulus (G′) from 256.5 Pa for Fmoc-FRGDF to 21.1 Pa with the addition of 0.1 mg/mL HA. Despite this reduction, HA effectively slowed degradation rates; specifically, residue rates of 5.5% were observed for Fmoc-FRGDF alone compared to 14.1% with 0.5 mg/mL HA present. Notably, Que enhanced G′ within the ternary complex, increasing it from 256.5 Pa in Fmoc-FRGDF to an impressive 7527.0 Pa in the Que/HA/Fmoc-FRGDF hydrogel containing 0.1 mg/mL HA. The interactions among Que, HA, and Fmoc-FRGDF involved hydrogen bonding, electrostatic forces, and hydrophobic interactions; furthermore, the co-assembly process strengthened the β-sheet structure while significantly promoting supramolecular ordering. Interestingly, the release profile of Que adhered to the Korsmeyer–Peppas pharmacokinetic equations. Conclusions: Overall, this study examines the impact of polyphenol on the rheological properties, microstructural features, secondary structure conformation, and supramolecular ordering within peptide–polysaccharide–polyphenol ternary complexes, and the Fmoc-FRGDF/HA hydrogel system demonstrates a superior performance as a delivery vehicle for maintaining quercetin’s bioactivity, thereby establishing a multifunctional platform for bioactive agent encapsulation and controlled release. Full article

Stainless steel dust (SSD) is a by-product generated during the smelting process of stainless steel, which is rich in valuable metals such as Fe, Cr, Ni, and Mn. To optimize the carbothermic reduction process of SSD, this study first conducted the thermodynamic analysis of the carbothermic reduction of SSD and then employed walnut shell biochar as a reductant with non-isothermal thermogravimetric analysis with linear heating rates of 5 °C/min, 10 °C/min, 15 °C/min, and 20 °C/min. The activation energies of the carbothermic reduction reactions were calculated using the FWO method, KAS method, and Friedman method, respectively. Subsequently, the corresponding kinetic models were fitted and matched using the Málek method. The results indicate that before 600 °C, the direct reduction of SSD by carbon plays a dominant role. As the temperature increases, the indirect reduction becomes the main reduction reaction for SSD due to the generation of CO. The activation energies calculated by the Flynn–Wall–Ozawa (FWO) method, Kissinger–Akahira–Sunose (KAS) method, and Friedman method are 412.120 kJ/mol, 416.930 kJ/mol, and 411.778 kJ/mol, respectively, showing close values and a general trend of increasing activation energy as the conversion rate increased from 10% to 90%. Moreover, the reduction reaction is staged. In the conversion range of 10% to 50%, the carbothermic reduction reaction conforms to the shrinking core model within phase boundary reactions, coded as R1/4. In the conversion range of 50% to 60%, it conforms to the shrinking core model within phase boundary reactions, coded as R1/2; in the conversion range of 60% to 90%, the carbothermic reduction reaction follows the second-order chemical reaction model, coded as F2. Full article

Grasping objects with a high degree of anthropomorphism is a critical component in the field of highly anthropomorphic robotic grasping. However, the accuracy of contact maps and the irrationality of the grasping gesture become challenges for grasp generation. In this paper, we propose a reasonably improved generation scheme, called Diffangle-Grasp, consisting of two parts: contact map generation based on a conditional variational autoencoder (CVAE), sharing the potential space with the diffusion model, and optimized grasping generation, conforming to the physical laws and the natural pose. The experimental findings demonstrate that the proposed method effectively reduces the loss in contact map reconstruction by 9.59% in comparison with the base model. Additionally, it enhances the naturalness by 2.15%, elevates the success rate of grasping by 3.27%, reduces the penetration volume by 11.06%, and maintains the grasping simulation displacement. The comprehensive comparison and qualitative analysis with mainstream schemes also corroborate the rationality of the improvement. In this paper, we provide a comprehensive account of our contributions to enhancing the accuracy of contact maps and the naturalness of grasping gestures. We also offer a detailed technical feasibility analysis for robotic human grasping. Full article

Every year, a large amount of antibiotics enter aquatic environments globally through discharging of pharmaceutical wastewater and domestic sewage, emissions from agriculture, and livestock, posing a severe threat to ecosystems and human health. Therefore, it is essential to develop efficient adsorption materials for rapid removal of antibiotics in water. In this study, abundant and renewable wetland plants (lotus leaves, Arundo donax, and canna lilies) were utilized as raw materials to prepare biochar through slow pyrolysis combined with KOH chemical activation. The prepared biochar was employed to adsorb typical tetracycline (TC) antibiotics (TC-HCl, CTC-HCl, OTC-HCl) from water. The results showed that the optimum biochar (LBC-600 (1:3)) was prepared at a pyrolysis temperature of 600 °C with the mass ratio of KOH to lotus leaf of 1:3. The optimum pH for the adsorption of the three antibiotics were 5, 4, and 3, respectively. The highest adsorption rates reached 93.32%, 81.44%, and 83.76% for TC-HCl, CTC-HCl, and OTC-HCl with 0.6 g/L of biochar, respectively. At an initial antibiotic concentration of 80 mg·L⁻¹, the maximum adsorption capacities achieved 40.17, 27.76, and 24.6 mg·g⁻¹ for TC-HCl, CTC-HCl, and OTC-HCl, respectively. The adsorption process conformed to the pseudo-second-order kinetic and Langmuir isotherm models, indicating that it was a spontaneous endothermic process and primarily involved monolayer chemical adsorption. This study transformed wetland plant waste into adsorbent and applied it for antibiotic removal, providing a valuable resource utilization strategy and technical support for recycling wetland plant residues and antibiotic removal from water environments. Full article

In this study, MIL-101 (Cr) was synthesized and characterized in terms of its physical properties. The adsorption breakthrough curves for toluene were measured and compared to those of conventional adsorbents (i.e., silica gel and activated carbon) at typical indoor concentrations of toluene. The results show that MIL-101 (Cr) exhibits a 5–8 times higher adsorption capacity for toluene compared to silica gel at low concentrations. The adsorption isotherm of MIL-101 (Cr) for toluene conforms to the Langmuir model. Increasing temperature reduces the adsorption breakthrough time and saturation time, but it leads to a significant decrease in the adsorption capacity. During the breakthrough experiment, flow rate had little effect on adsorption capacity, but higher flow rates notably decreased the breakthrough and saturation times. The negative values of ΔG, ΔH, and ΔS indicate that the adsorption of toluene on MIL-101 (Cr) is a spontaneous and exothermic process. Compared to traditional adsorbents, MIL-101 (Cr) exhibits desirable performance in toluene adsorption in indoor environments. It shows significant potential for indoor air purification applications. Full article

This study explored the effects of adding a newly developed type of polydextrose on the appearance, sensory score, and textural parameters of steamed bread and the microstructure of dough, as well as the pasting, thermal, and thermal mechanical properties of high-gluten wheat flours. The results revealed that, compared with a control sample, 3–10% of polydextrose addition significantly increased the hardness, adhesiveness, gumminess, and chewiness of steamed bread, but other textural parameters like springiness, cohesiveness, and resilience remained basically the same. Further, in contrast to the control sample, 3–10% polydextrose addition significantly reduced the specific volume and width/height ratio of steamed bread but increased the brightness index, yellowish color, and color difference; improved the internal structure; and maintained the other sensory parameters and total score. Polydextrose addition decreased the peak, trough, final, breakdown, and setback viscosity of the pasting of wheat flour suspension solutions but increased the pasting temperature. Polydextrose additions significantly reduced the enthalpy of gelatinization and the aging rate of flour paste but increased the peak temperature of gelatinization. A Mixolab revealed that, with increases in the amount of added polydextrose, the dough’s development time and heating rate increased, but the proteins weakened, and the peak torque of gelatinization, starch breakdown, and starch setback torque all decreased. Polydextrose additions increased the crystalline regions of starch, the interaction between proteins and starch, and the β-sheet percentage of wheat dough without yeast and of steamed bread. The amorphous regions of starch were increased in dough through adding polydextrose, but they were decreased in steamed bread. Further, 3–10%of polydextrose addition decreased the random coils, α-helixes, and β-turns in dough, but the 3–7% polydextrose addition maintained or increased these conformations in steamed bread, while 10% polydextrose decreased them. In unfermented dough, as a hydrogel, the 5–7% polydextrose addition resulted in the formation of a continuous three-dimensional network structure with certain adhesiveness and elasticity, with increases in the porosity and gas-holding capacity of the product. Moreover, the 10% polydextrose addition further increased the viscosity, freshness, and looseness of the dough, with smaller and more numerous holes and indistinct boundaries between starch granules. These results indicate that the 3–10% polydextrose addition increases the chewiness and freshness of steamed bread by improving the gluten network structure. This study will promote the addition of polydextrose in steamed bread to improve shelf-life and dietary fiber contents. Full article

The development of metallic coatings as Ni-Co alloys, with particular emphasis on their homogeneity, processability, and sustainability, is of the utmost significance. To address these challenges, the utilization of phenylsalicylimines (PSIs) as additives within deep eutectic solvents (DES) was investigated, assessing their influence on the electrodeposition process of these metals at an intermediate temperature of 60 °C, while circumventing aqueous reaction conditions. The findings demonstrated that the incorporation of PSIs markedly enhances coating uniformity, resulting in an optimal cobalt content of 37% and an average thickness of 24 µm. Electrochemical evaluations revealed improvements in charge and mass transfer, thereby optimizing process efficiency. Moreover, computational studies confirmed that PSIs form stable complexes with Co (II), modulating the electrochemical characteristics of the system through the introduction of the diethylamino electron-donating group, which significantly stabilizes the coordinated forms with both components of the DES. Additionally, the coatings displayed exceptional corrosion resistance, with a rate of 0.781 µm per year, and achieved an optimal hardness of 38 N HRC, conforming to ASTM B994 standards. This research contributes to the development of electroplating bath designs for metallic coating deposition and lays the groundwork for the advancement of sophisticated technologies in functional coatings that augment corrosion resistance and mechanical properties. Full article

This research takes the Suzhou Gardens, a World Cultural Heritage Site, as the object of study and investigates a rapid scheme generation approach for garden restoration and expansion projects, assisting designers in making scientific decisions. Considering the limitations of current garden design, which is inefficient and relies on human experience, this study proposes an intelligent generation framework based on a conditional generative adversarial network (CGAN). In constructing the CGAN model, we determine the spatial characteristics of the Suzhou Gardens and, combined with historical floor plan data, train the network. We then design an optimization strategy for the model training process and finally test and verify the generative space scheme. The research results indicate the following: (1) The CGAN model can effectively capture the key elements of the garden space and generate a planar scheme that conforms to the traditional space with an accuracy rate reaching 91.08%. (2) This model can be applied to projects ranging from 200 to 1000 square meters. The generated results can provide multiple scheme comparisons for update decisions, helping managers to efficiently select the optimal solution. (3) Decision-makers can conduct space utilization analyses and evaluations based on the generated results. In conclusion, this study can help decision-makers to efficiently generate and evaluate the feasibility of different design schemes, providing intelligent support for decision-making in urban renewal plans. Full article

See-through augmented reality glasses, such as HoloLens 2, are increasingly adopted in medical settings; however, their efficacy as medical display devices remains unclear, as current evaluation protocols are designed for traditional monitors. This study examined whether the established display-evaluation techniques apply to HoloLens 2 and whether it meets standards for primary and secondary medical displays. HoloLens 2 was assessed for overall image quality, luminance, grayscale consistency, and color uniformity. Five participants rated the TG18-OIQ pattern under ambient lighting conditions of 2.4 and 138.7 lx. Minimum and maximum luminance were measured using the TG18-LN12-03 and -18 patterns, targeting ≥ 300 cd/m² and a luminance ratio ≥ 250. Grayscale conformity to the standard grayscale display function allowed deviations of 10% for primary and 20% for secondary displays. Color uniformity was measured at five screen positions for red, green, and blue, with a chromaticity limit of 0.01 for primary displays. HoloLens 2 satisfied four of the ten primary and four of the seven secondary overall-quality criteria, achieving a maximum luminance of 2366 cd/m² and a luminance ratio of 1478.75. Grayscale uniformity was within tolerance for 10 of the 15 primary and 13 of the 15 secondary measurements, while 25 of the 30 color uniformity values exceeded the threshold. The adapted evaluation methods facilitate a systematic assessment of HoloLens 2 as a medical display. Owing to inadequate grayscale and color representation, the headset is unsuitable as a primary diagnostic display; for secondary use, requirements must be assessed based on specific application requirements. Full article

Continuous monitoring of vital signs could improve patient care in veterinary hospitals by identifying changes earlier and reducing patient stress from repeated handling. This study aimed to assess the agreement between a wireless harness device and manual measurement of heart rate, respiratory rate, and body temperature in hospitalized dogs. Nineteen client-owned dogs wore the harness throughout hospitalization and paired manual and harness measurements were collected every 4–8 h. Linear regression and Bland–Altman analysis were used to assess agreement. The device demonstrated strong correlation with manual measurements for heart rate and respiratory rate; however, the limits of agreement (LoA) exceeded predefined clinical thresholds, indicating high variability in individual readings. Temperature measurements showed a mean difference of 1.34 °F (manual minus harness), indicating underestimation by the harness. The LoA for temperature also exceeded predefined clinical thresholds, particularly in dogs with long fur. Fur length significantly influenced respiratory rate and temperature measurements, but not heart rate. Chest conformation also impacted respiratory rate and temperature accuracy. Heart rate was the most consistent parameter across all body types. Overall, the device tracked trends in heart rate and respiratory rate, supporting its potential as a supplemental monitoring tool. However, measurements should be confirmed manually prior to clinical decision-making. Full article

Background/Objectives: Prostate cancer (PCa) remains a major contributor to cancer-related morbidity and mortality worldwide. Current diagnostic strategies, largely based on PSA screening, lack specificity and sensitivity, leading to unnecessary invasive procedures and elevated healthcare costs. This real-world study evaluated the EpiSwitch^® PSE assay, a blood-based test analyzing 3D genome conformation signatures, ability to avoid unnecessary biopsies and the resulting clinical and economical benefits. Methods: 187 patients undergoing evaluation for PCa were tested with the EpiSwitch^® PSE assay. Biopsy confirmation was available for 53 patients, while predictive modeling assessed 134 patients using EpiSwitch PSE results and clinical variables. Results: Among the 187 patients evaluated, predictive modeling showed that up to 79.1% (106/134) of patients could safely defer biopsy based on a low-likelihood EpiSwitch PSE result, while an alternative model showed a 66.4% (89/134) biopsy avoidance rate. The PSE result demonstrated strong concordance with biopsy-confirmed diagnoses and was the most influential predictor in multivariate analysis, followed by PI-RADS score. The test achieved a 100% technical success rate, with an average turnaround time of 4.4 days. Conclusions: Incorporating the EpiSwitch PSE assay into clinical workflows enhances decision-making efficiency, reduces unnecessary biopsies, and improves healthcare resource utilization. These findings support the assay’s strong clinical utility and economic value, highlighting its potential for broader adoption as a minimally invasive reflex test and a pre-biopsy triage tool for the early and accurate detection of prostate cancer. Future studies should include prospective, multicenter trials to confirm these results across broader populations and evaluate longitudinal outcomes of patients managed with PSE-guided care. Full article