Global responses of wetland methane emissions to extreme temperature and precipitation.

As global warming continues, events of extreme heat or heavy precipitation will become more frequent, while events of extreme cold will become less so. How wetlands around the globe will react to these extreme events is unclear yet critical, because they are among the greatest natural sources of methane(CH4). Here we use seven indices of extreme climate and the rate of methane emission from global wetlands(WME) during 2000-2019 simulated by 12 published models as input data. Our analyses suggest that extreme cold (particularly extreme low temperatures) inhibits WME, whereas extreme heat (particularly extreme high temperatures) accelerates WME. Our results also suggest that daily precipitation >10 mm accelerates WME, while much higher daily precipitation levels can slow WME. The correlation of extreme high temperature and precipitation with rate of WME became stronger during the study period, while the correlation between extreme low temperature and WME rate became weaker.

Favorable Outcomes of Liver Transplantation for Hepatopulmonary Syndrome.

BACKGROUND: Hepatopulmonary syndrome (HPS) is a pulmonary vascular complication of chronic liver disease, which develops insidiously as a result of chronic liver disease. The prognosis for untreated patients with HPS is extremely poor, and liver transplantation (LT) serves as the only effective means for treating this condition. Here, we performed a retrospective analysis to evaluate the efficacy of LT on the survival and long-term prognosis of patients with HPS. METHODS: Clinical data, including survival and postoperative efficacy, from patients with HPS from records as obtained over the period from January 1 to December 31, 2022. All records were from a waiting list for LT at the Beijing Friendship Hospital Affiliated with Capital Medical University. RESULTS: Among the 274 patients on the LT waiting list, 37 were diagnosed with HPS (13.50%) and were enrolled. Survival rates of patients with HPS receiving an LT were greater, whereas a statistically significant difference was obtained between patients with LT vs non-LT with moderate to severe HPS (P = .003). The overall time until death without LT was 4-72 days after their initial HPS diagnosis. Patients with HPS receiving an LT showed a significant improvement in the state of oxygenation after surgery (P = .001). CONCLUSION: Comprehensive preoperative screening of patients on the waiting list for LT is critical to identify those patients with HPS who would maximally benefit from LT. Survival rates of patients with moderate to severe HPS are significantly increased after LT, a procedure that should be performed as soon as possible in these patients with HPS.

Body Composition Indicators Jointly Predict Metabolic Unhealthy Phenotypes in Young and Middle-Aged Obese Individuals: A Cross-Sectional Quantitative Computed Tomography Study.

Purpose: The main aim of this study is to analyze the relationship between body composition indices and metabolic unhealthy phenotypes in young and middle-aged obese patients and to assess their joint predictive ability. Patients and Methods: A cross-sectional study method was used to select 207 patients who were proposed to undergo weight loss surgery for morbid obesity from March to November 2022. Total adipose tissue (TAT), visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), liver fat content (LFC), cross-sectional area (CSAmuscle), and intermuscular adipose tissue (CSAIMAT) of paraspinal muscles were measured using quantitative computed tomography. Participants were categorized into two groups: metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO). The receiver operating characteristic curve comprised body composition variables that correlated with MUO, and the area under the curve (AUC) was calculated to compare their prediction capacity for MUO. Results: There were 71 patients with MHO (34.3%) and 136 patients with MUO (65.7%). The VAT, VAT/TAT ratio, LFC, and CSAmuscle was higher in MUO patients than in MHO (all P < 0.001), and SAT was lower than in MHO (P = 0.008). And all of these metrics were correlated with MUO (all P < 0.05). Inclusion of these body composition metrics in the ROC analysis showed that the AUC values for SAT, VAT, VAT/TAT ratio, LFC and CSAmuscle were 0.615, 0.663, 0.727, 0.694, 0.671, respectively, and the combination of the VAT/TAT ratio and the LFC had the ability to predict MUO best (AUC=0.746, P = 0.025). Conclusion: The combined use of VAT/TAT ratio and LFC is superior to the use of these two metrics alone in terms of their ability to predict the MUO, providing a more accurate approach to the management and prevention of obesity-related metabolic risk.

One-pot reaction for the preparation of diatom hemostatic particles with effective hemostasis and economic benefits.

Effective hemostatic materials have been in demand for rapid pre-hospital hemostasis in emergency situations, which can significantly reduce accidental deaths. The development of emergency hemostatic materials with rapid hemostasis, biosafety, and economical preparation is a great challenge. In this study, Ca(OH)2-complexed diatom powder hemostatic particles (Ca(OH)2-Php) were prepared based on a one-pot reaction by directly mixing various raw materials and by rotary granulation. High-temperature calcination was able to carbonate and consume the organic matter in the hemostatic particles. The crosslinked hydrogen bonds in those particles were converted to silica-oxygen bonds, the particles became more stable, and the porous structure of diatom biosilica (DBs) was exposed. Ca(OH)2-Php has high porosity, can quickly adsorb the water in blood (water absorption: 75.85 ± 6.93%), and exhibits rapid hemostasis capacity (clotting time was shortened by 43% compared with that of the control group), good biocompatibility (hemolysis rate <7%, no cytotoxicity), and simplicity of handling (conveniently debride, no residues, no tissue inflammation). This study provides a new idea for the preparation of emergency hemostatic materials, and Ca(OH)2-Php prepared by one-pot reaction has various high-quality characteristics including rapid hemostasis, wide applicability, economical preparation, and potential for large-scale production.

Resource-Efficient Direct Characterization of General Density Matrix.

Sequential weak measurements allow for the direct extraction of individual density-matrix elements, rather than relying on global reconstruction of the entire density matrix, which opens a new avenue for the characterization of quantum systems. Nevertheless, extending the sequential scheme to multiqudit quantum systems is challenging due to the requirement of multiple coupling processes for each qudit and the lack of appropriate precision evaluation. To address these issues, we propose a resource-efficient scheme (RES) that directly characterizes the density matrix of general multiqudit systems while optimizing measurements and establishing a feasible estimation analysis. In the RES, an efficient observable of the quantum system is constructed such that a single meter state coupled to each qudit is sufficient to extract the corresponding density-matrix element. An appropriate model based on the statistical distribution of errors is utilized to evaluate the precision and feasibility of the scheme. We have experimentally applied the RES to the direct characterization of general single-photon qutrit states and two-photon entangled states. The results show that the RES outperforms sequential schemes in terms of efficiency and precision in both weak- and strong-coupling scenarios. This Letter sheds new light on the practical characterization of large-scale quantum systems and the investigation of their nonclassical properties.

Worldwide trends in mortality for hypertensive heart disease from 1990 to 2019 with projection to 2034: data from the Global Burden of Disease 2019 study.

AIMS: This study aims to analyse the worldwide trends in hypertensive heart disease (HHD) mortality and associations with age, period, and birth cohort and predict the future burden of HHD deaths. METHODS AND RESULTS: Mortality estimates were obtained from Global Burden of Disease 2019 study. We used age-period-cohort (APC) model to examine the age, period, and cohort effects on HHD mortality between 1990 and 2019. Bayesian APC model was utilized to predict HHD deaths to 2034. The global HHD deaths were 1.16 million in 2019 and were projected to increase to 1.57 million in 2034, with the largest increment in low- and middle-income countries (LMICs). Between 1990 and 2019, middle/high-middle socio-demographic index (SDI) countries had the largest mortality reductions (annual percentage change = -2.06%), whereas low SDI countries saw a lagging performance (annual percentage change = -1.09%). There was a prominent transition in the age distribution of deaths towards old-age population in middle/high-middle SDI countries, while the proportion of premature deaths (aged under 60 years) remained at 24% in low SDI countries in 2019. Amongst LMICs, Brazil, China, and Ethiopia showed typically improving trends both over time and in recent birth cohorts, whereas 63 countries including Indonesia, the Philippines, and Pakistan had unfavourable or worsening risks for recent periods and birth cohorts. CONCLUSION: The HHD death burden in 2019 is vast and is expected to increase rapidly in the next decade, particularly for LMICs. Limited progress in HHD management together with high premature mortality would exact huge human and medical costs in low SDI countries. The examples from Brazil, China, and Ethiopia suggest that efficient health systems with action on improving hypertension care can reduce HHD mortality effectively in LMICs.

This study provides the first comprehensive analysis of the age, period, and cohort trends in mortality for hypertensive heart disease (HHD) across 204 countries and territories from 1990 to 2019, with projection to 2034. The death burden of HHD is substantial and growing rapidly in most of the world, particularly in low- and middle-income countries (LMICs). Wide disparities exist within LMICs in HHD management, with most low socio-demographic index countries showing little progress in reducing HHD mortality. The examples from Brazil, China, and Ethiopia suggest that prevention policies for HHD can reduce risks for younger birth cohorts and shift the risks for all age groups over time.

Collateral vessels on preoperative enhanced computed tomography for predicting pathological grade of clear cell renal cell carcinoma: A retrospective study.

OBJECTIVES: To retrospectively evaluate the association between the presence of collateral vessels and grade of clear cell renal cell carcinoma (ccRCC) and whether the presence of collateral vessels could serve as a predictor to differentiate high- and low-grade ccRCC. MATERIALS AND METHODS: From May 2018 to September 2022, a total of 160 ccRCC patients with pathological diagnosis were enrolled in this study. Patients were divided into a high-grade group and a low-grade group according to World Health Organization/International Society of Urological Pathology (WHO/ISUP) grading system. The significant variables were extracted based on the univariate analyses using Student t test, Mann-Whitney U test, Chi-square test or Fisher's exact test. Multivariate logistic regression analyses were performed to determine independent factors among extracted variables. We calculated the sensitivity, specificity and their 95% confidence intervals (CI) of collateral vessels for predicting high WHO/ISUP grade to quantify its predictive performance. Furthermore, to investigate the additional predictive contribution of collateral vessels, a primary model and a control model were constructed to predict WHO/ISUP grade. The primary model included all extracted significant variables and the control model included significant variables except collateral vessels. RESULTS: The proportion of ccRCC patients with collateral vessels was significantly larger in high-grade ccRCC than those in low-grade ccRCC (87.5 % vs. 26.8 %, P < 0.001). Multivariate logistic regression analyses showed that the presence of collateral vessels was an independent predictor for high WHO/ISUP grade (P < 0.001). The sensitivity and specificity of the presence of collateral vessels for differentiating high- and low-grade ccRCC were 87.5 % (95 % CI 0.753-0.941) and 73.2 % (95 % CI 0.643-0.806) respectively. Including collateral vessels in predictive model improves predictive performance for WHO/ISUP grade, increasing the area under the curve (AUC) value from 0.889 to 0.914. CONCLUSION: The presence of collateral vessels has high sensitivity and specificity for differentiating high- and low-grade ccRCC and can improve the predictive performance for high WHO/ISUP grade.

Predictive models for starting dose of gonadotropin in controlled ovarian hyperstimulation: review and progress update.

Controlled ovarian hyperstimulation (COH) is an essential for in vitro fertilization-embryo transfer (IVF-ET) and an important aspect of assisted reproductive technology (ART). Individual starting doses of gonadotropin (Gn) is a critical decision in the process of COH. It has a crucial impact on the number of retrieved oocytes, the cancelling rate of ART cycles, and complications such as ovarian hyperstimulation syndrome (OHSS), as well as pregnancy outcomes. How to make clinical team more standardized and accurate in determining the starting dose of Gn is an important issue in reproductive medicine. In the past 20 years, research teams worldwide have explored prediction models for Gn starting doses. With the integration of artificial intelligence (AI) and deep learning, it is hoped that there will be more suitable predictive model for Gn starting dose in the future.

Study on the Biomolecular Competitive Mechanism of Polybrominated Diphenyl Ethers and Their Derivatives on Thyroid Hormones.

Polybrominated diphenyl ethers (PBDEs) are widely used brominated flame retardants. PBDEs and their derivatives, hydroxylated PBDEs (OH-PBDEs), can bind to hormone receptors and impact hormone secretion, transportation, and metabolism, leading to endocrine disruption and the development of various diseases. They have particularly strong interference effects on thyroid hormones. This study used decabromodiphenyl ether (BDE-209); 2,2',4,4'-tetrabromodiphenyl ether (BDE-47); and 6-OH-BDE-47 as representative compounds of PBDEs and their derivatives, OH-PBDEs. A fluorescence probe, fluorescein-isothiocyanate-L-thyroxine (FITC-T4, F-T4), specific for binding to transthyretin (TTR), a thyroid transport protein, was prepared. The binding capacity of PBDEs and their derivatives, OH-PBDEs, to TTR was quantitatively measured using fluorescence spectroscopy. The principle of quenching the fluorescence intensity of F-T4 after binding to TTR was used to analyze the competitive interaction between the probe and BDE-209, BDE-47, and 6-OH-BDE-47, thereby evaluating the toxic effects of PBDEs and their derivatives on the thyroid system. Additionally, AutoDock molecular docking software (1.5.6) was used to further analyze the interference mechanism of OH-PBDEs on T4. The results of the study are as follows: (1) Different types of PBDEs and OH-PBDEs exhibit varying degrees of interference with T4. Both the degree of bromination and hydroxylation affect their ability to competitively bind to TTR. Higher bromination and hydroxylation degrees result in stronger competitive substitution. (2) The competitive substitution ability of the same disruptor varies at different concentrations. Higher concentrations lead to stronger substitution ability, but there is a threshold beyond which the substitution ability no longer increases. (3) When OH-PBDEs have four or more bromine atoms and exhibit the most structural similarity to T4, their binding affinity to TTR is stronger than that of T4.

Negative serum (1,3) -ß-D-glucan has a low power to exclude Pneumocystis jirovecii pneumonia (PJP) in HIV-uninfected patients with positive qPCR.

OBJECTIVE: The current study evaluated the diagnostic performance of serum (1,3)-beta-D Glucan (BDG) in differentiating PJP from P. jirovecii-colonization in HIV-uninfected patients with P. jirovecii PCR-positive results. METHODS: This was a single-center retrospective study between 2019 and 2021. The diagnosis of PJP was based on the following criteria: detection of P. jirovecii in sputum or BAL specimen by qPCR or microscopy; Meet at least two of the three criteria: (1) have respiratory symptoms of cough and/or dyspnea, hypoxia; (2) typical radiological picture findings; (3) receiving a complete PJP treatment. After exclusion, the participants were divided into derivation and validation cohorts. The derivation cohort defined the cut-off value of serum BDG. Then, it was verified using the validation cohort. RESULTS: Two hundred and thirteen HIV-uninfected patients were enrolled, with 159 PJP and 54 P. jirovecii-colonized patients. BDG had outstanding specificity, LR, and PPV for PJP in both the derivation (90.00%, 8.900, and 96.43%) and the validation (91.67%, 9.176, and 96.30%) cohorts at ≥ 117.7 pg/mL. However, it had lower sensitivity and NPV in the derivation cohort (89.01% and 72.97%), which was even lower in the validation cohort (76.47% and 57.89%). Of note, BDG ≥ 117.7 pg/mL has insufficient diagnostic efficacy for PJP in patients with lung cancer, interstitial lung disease (ILD) and nephrotic syndrome. And although lymphocytes, B cells, and CD4+ T cells in PJP patients were significantly lower than those in P. jirovecii-colonized patients, the number and proportion of peripheral blood lymphocytes did not affect the diagnostic efficacy of serum BDG. CONCLUSIONS: Serum BDG ≥ 117.7 pg/mL could effectively distinguish P. jirovecii-colonization from infection in qPCR-positive HIV-uninfected patients with infectious diseases, solid tumors (excluding lung cancer), autoimmune or inflammatory disorders, and hematological malignancies. Of note, for patients with lung cancer, ILD, and nephrotic diseases, PJP should be cautiously excluded at BDG < 117.7 pg/mL.

Changes in Bone Mineral Density and Related Influencing Factors Assessed by Quantitative Computed Tomography in Maintenance Dialysis Patients.

OBJECTIVE: To investigate the changes in volumetric bone mineral density (vBMD) assessed by quantitative computed tomography (QCT) in chronic kidney disease (CKD) patients on maintenance dialysis. STUDY DESIGN: Descriptive study. Place and Duration of the Study: Department of Radiology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China, from March to July 2022. METHODOLOGY: Maintenance dialysis patients were selected for this study, and parameters related to renal function and bone metabolism markers were recorded. Patients undergoing routine physical examination were age-matched with maintenance dialysis patients to serve as the control group. vBMD scans of the lumbar spine (L1-3) were obtained by QCT for all participants. RESULTS: Among the 141 maintenance dialysis patients, there were 67 patients with secondary hyperparathyroidism (SHPT) and 74 patients with non-secondary hyperparathyroidism (non-SHPT) with mean vBMDs of 145.99±55.13 mg/cm3 and 129.10±44.20 mg/cm3, respectively. The 159 individuals in the control group had mean age of 52.77±11.66 years and mean vBMD of 129.62±36.36 mg/cm3. The vBMD of the SHPT group was greater than that of both the non-SHPT group and the control group (all p<0.05). For dialysis patients, vBMD was positively correlated with calcium-phosphorus product and intact parathyroid hormone (iPTH) levels (r = 0.181, 0.214, respectively, p<0.05); vBMD was inversely correlated with age (r = -0.555, p<0.05). After adjusting for the covariates, vBMD remained positively correlated with iPTH (r = 0.184, p<0.05). CONCLUSION: Increased lumbar vertebral vBMD in maintenance dialysis patients may be associated with high iPTH, providing clinicians with a new understanding of the changes in bone mineral density in maintenance dialysis patients. KEY WORDS: Bone mineral density, Quantitative computed tomography, Chronic kidney disease, Maintenance dialysis.

Research on classification method of high myopic maculopathy based on retinal fundus images and optimized ALFA-Mix active learning algorithm.

AIM: To conduct a classification study of high myopic maculopathy (HMM) using limited datasets, including tessellated fundus, diffuse chorioretinal atrophy, patchy chorioretinal atrophy, and macular atrophy, and minimize annotation costs, and to optimize the ALFA-Mix active learning algorithm and apply it to HMM classification. METHODS: The optimized ALFA-Mix algorithm (ALFA-Mix+) was compared with five algorithms, including ALFA-Mix. Four models, including ResNet18, were established. Each algorithm was combined with four models for experiments on the HMM dataset. Each experiment consisted of 20 active learning rounds, with 100 images selected per round. The algorithm was evaluated by comparing the number of rounds in which ALFA-Mix+ outperformed other algorithms. Finally, this study employed six models, including EfficientFormer, to classify HMM. The best-performing model among these models was selected as the baseline model and combined with the ALFA-Mix+ algorithm to achieve satisfactory classification results with a small dataset. RESULTS: ALFA-Mix+ outperforms other algorithms with an average superiority of 16.6, 14.75, 16.8, and 16.7 rounds in terms of accuracy, sensitivity, specificity, and Kappa value, respectively. This study conducted experiments on classifying HMM using several advanced deep learning models with a complete training set of 4252 images. The EfficientFormer achieved the best results with an accuracy, sensitivity, specificity, and Kappa value of 0.8821, 0.8334, 0.9693, and 0.8339, respectively. Therefore, by combining ALFA-Mix+ with EfficientFormer, this study achieved results with an accuracy, sensitivity, specificity, and Kappa value of 0.8964, 0.8643, 0.9721, and 0.8537, respectively. CONCLUSION: The ALFA-Mix+ algorithm reduces the required samples without compromising accuracy. Compared to other algorithms, ALFA-Mix+ outperforms in more rounds of experiments. It effectively selects valuable samples compared to other algorithms. In HMM classification, combining ALFA-Mix+ with EfficientFormer enhances model performance, further demonstrating the effectiveness of ALFA-Mix+.

Targeting PTGES/PGE2 axis enhances sensitivity of colorectal cancer cells to 5-fluorouracil.

Insensitivity and resistance to 5-fluorouracil (5FU) remain as major hurdles for effective and durable 5FU-based chemotherapy in colorectal cancer (CRC) patients. In this study, we identified prostaglandin E synthase (PTGES)/prostaglandin E2 (PGE2) axis as an important regulator for 5FU sensitivity in CRC cells. We found that PTGES expression and PGE2 production are elevated in CRC cells in comparison to normal colorectal epithelial cells. Depletion of PTGES significantly enhanced the inhibitory effect of 5FU on CRC cell viability that was fully reverted by exogenous supplement of PGE2. Inhibition of PTGES enzymatic function, by either inducing loss-of-function mutant or treatment with selective inhibitors, phenocopied the PTGES depletion in terms of 5FU sensitization. Mechanistically, PTGES/PGE2 axis modulates glycolysis in CRC cells, thereby regulating the 5FU sensitivity. Importantly, high PTGES expression is correlated with poor prognosis in 5FU-treated CRC patients. Thus, our study defines PTGES/PGE2 axis as a novel therapeutic target for enhancing the efficacy of 5FU-based chemotherapy in CRC.

Modeling knot features using branch scars from Mongolian oak (Quercus mongolica).

Wood quality is an important indicator for modern sawmills. Internal wood characteristics can be derived from their correlations with external appearances. In this study, we developed linear regression models to predict knot size from surface features of Mongolian oak (Quercus mongolica) using data collected from 53 trees. For this, manual measurements and X-ray computed tomography scanning technology was respectively used to obtain internal and external features of 1,297 knots. Our results showed that Mongolian oak knots were generally concentrated in the middle part of oak stems, with fewer knots observed at the top and base. The parameters of knot and scar showed significant correlations (P < 0.01), where length and diameter of the corresponding external scar increase with increasing the length and diameter of a knot. The corresponding external scar can be used as an effective indicator to predict the internal value of oak logs. The accuracy of our constructed model is more than 95% when assessed against independent test samples. These models thus can be applied to improve the practical production of oak timber and reduce commercial loss caused by knots. These additional data can improve the estimation of the influence of knots on wood quality and provide a theoretical foundation for investigating the characteristics of hardwood knots.

Genome-Wide Identification and Expression Analysis of the bHLH Transcription Factor Family and Its Response to Abiotic Stress in Mongolian Oak (Quercus mongolica).

The basic helix-loop-helix (bHLH) family, one of the largest families of transcription factors in plants, is extensively involved in the growth, development, and stress response of several woody plants. However, no systematic analysis of the bHLH gene family in Quercus mongolica has been reported. We characterize QmbHLH genes and identify the functions of QmbHLH proteins in Q. mongolica. We used bioinformatics approaches, qRT-PCR analysis, and RNA sequencing data to examine chromosomal distributions, gene structures, and conserved patterns, and identified 89 QmbHLH genes, which were divided into 21 subgroups based on the phylogenetic analysis of bHLH genes in Arabidopsis thaliana. Segmental replication played a more prominent role than tandem duplication in the expansion of the QmbHLH gene family. Based on patterns of tissue-specific expression, protein interactions, and cis-element analysis, QmbHLH genes may be extensively involved in the growth and development of Q. mongolica. In leaves, stems, and roots, 12 selected QmbHLH genes exhibited responsiveness to abiotic stresses (salt, cold, weak light, and drought). Our study facilitates follow-up functional investigations of the bHLH gene family in Q. mongolica and provides novel insights into bHLH superfamilies in woody plants.

Machine learning for hydrothermal treatment of biomass: A review.

Hydrothermal treatment (HTT) (i.e., hydrothermal carbonization, liquefaction, and gasification) is a promising technology for biomass valorization. However, diverse variables, including biomass compositions and hydrothermal processes parameters, have impeded in-depth mechanistic understanding on the reaction and engineering in HTT. Recently, machine learning (ML) has been widely employed to predict and optimize the production of biofuels, chemicals, and materials from HTT by feeding experimental data. This review comprehensively analyzed the application of ML for HTT of biomass and systematically illustrated basic ML procedure and descriptors for inputs and outputs of ML models (e.g., biomass compositions, operation conditions, yield and physicochemical properties of derived products) that could be applied in HTT. Moreover, this review summarized ML-aided HTT prediction of yield, compositions, and physicochemical properties of HTT hydrochar or biochar, bio-oil, syngas, and aqueous phase. Ultimately, future prospects were proposed to enhance predictive performance, mechanistic interpretation, process optimization, data sharing, and model application during ML-aided HTT.

Large-capacity and long-distance distributed acoustic sensing based on an ultra-weak fiber Bragg grating array with an optimized pulsed optical power arrangement.

A large-capacity, long-distance distributed acoustic sensing (DAS) system without inline optical amplification was proposed and experimentally demonstrated using an ultra-weak fiber Bragg grating (UWFBG) array and coherent detection. The effect of the finite extinction ratio of an acousto-optic modulator and the Stokes signal of stimulated Brillouin scattering (SBS) in UWFBGs on the performance of DAS was simulated and revealed. A high extinction ratio and a balanced input pulsed optical power can improve the capacity and distance of the DAS. The dynamic acoustic signal can be well reconstructed for a serial array of 10828 near-identical UWFBG with a length of 54.14 km. An acoustic signal sensitivity of 189.54 pɛ/√Hz and a signal SNR of 40.01 dB with a spatial resolution of 5 m can be achieved at the far end.

Computational Intelligence Powered Performance Analysis on Phase Change Heat Storage Air Source Heat Pump System.

Aiming at the performance deterioration of air source heat pump at low temperature in cold area, an air source heat pump system with sodium chloride aqueous solution as low temperature phase change heat storage material was proposed to increase the air inlet temperature of the unit under low temperature conditions and improve the low temperature performance of the heat pump unit. The system form, unit energy consumption model, and economic model were given, and the operating economy of the traditional electric auxiliary heat air source heat pump system and the phase change heat storage air source heat pump system were compared through computational intelligence powered methods. On this basis, the operation economy of the heat pump system using different concentrations of sodium chloride solution as the heat storage material was simulated and optimized, and the operation efficiency and energy-saving performance of the system were analyzed by taking an actual residential building in a cold area as an example. The simulation results showed that the Heating Seasonal Performance Factor (HSPF) of the heat pump system using 8.5% sodium chloride aqueous solution as the heat storage material is 2.24, and the HSPF of the traditional electric auxiliary heat pump system is 1.83. Compared with the traditional electric auxiliary heat pump system, the phase change heat storage heat pump system saves heating energy consumption by 19.6% and defrosting energy consumption by 38.8%. The heat pump system using 10% sodium chloride aqueous solution as the heat storage material has the best operating economy, and the system HSPF is 2.33, which saves heating energy consumption by 23.2% and defrosting energy consumption by 34% compared with the traditional heat pump system. The operation condition of phase change heat storage air source heat pump system is stable, and the system performance is significantly improved.

Machine learning prediction of nitrogen heterocycles in bio-oil produced from hydrothermal liquefaction of biomass.

Hydrothermal liquefaction (HTL) of high-moisture biomass or biowaste to produce bio-oil is a promising technology. However, nitrogen-heterocycles (NH) presence in bio-oil is a bottleneck to the upgrading and utilization of bio-oil. The present study applied the machine learning (ML) method (random forest) to predict and help control the bio-oil NH, bio-oil yield, and N content of bio-oil (N_oil). The results indicated that the predictive performance of the yield and N_oil were better than previous studies, achieving test R2 of 0.92 and 0.95, respectively. Acceptable predictive performance (test R2 of 0.82 and RMSE of 7.60) for the prediction of NH was also achieved. The feature importance analysis, partial dependence, and Shapely value were used to interpret the prediction models and study the NH formation mechanisms and behavior. Then, forward optimization of NH was implemented based on optimal predictive models, indicating the high potential of ML-aided bio-oil production and engineering.