Photodegradation of polychlorinated biphenyls (PCBs) on suspended particles from the Yellow River under sunlight irradiation: QSAR model and mechanism analysis.

Polychlorinated biphenyls (PCBs), as a class of hydrophobic organic pollutants, are widely found in river sediments and suspended particles, and the environmental fate of different PCBs can be better understood by investigating their photochemical transformation process. In this study, the quantitative structure-activity relationship (QSAR) model between the photodegradation rate constants of 17 PCBs adsorbed on Yellow River suspended particles in water (as a typical heterogeneous photodegradation system) and the physicochemical parameters of PCBs was constructed by SPSS and machine learning. The model showed that the more hydrophobicity of the molecule, the more positive charge carried by the aromatic C atoms, and the presence of chlorine atoms adjacent to the carbon bridge could all enhance the photochemical activity of PCBs. From the combined analysis of rate constants, quenching experiments and theoretical calculations, it was revealed for the first time that in natural suspended particle containing organic matter, the higher concentration of •O2- and 1O2 in the hydrophobic zone contributed more to the more hydrophobic PCBs, while •OH in the hydrophilic zone played a major role in the degradation of the less hydrophobic PCBs. Findings of this study would deepen the understanding of the degradation mechanism of hydrophobic pollutants by active species in complex environments.

Assessing the predictive value of intraductal carcinoma of the prostate (IDC-P) in determining abiraterone efficacy for metastatic hormone-sensitive prostate cancer (mHSPC) patients.

BACKGROUND: This study explored the value of intraductal carcinoma of the prostate (IDC-P) in predicting the efficacy of abiraterone treatment in metastatic hormone-sensitive prostate cancer (mHSPC) patients. METHODS: A retrospective study of 925 patients who underwent prostate biopsies to detect IDC-P was conducted, with participants divided into two cohorts. The first cohort of 165 mHSPC patients receiving abiraterone treatment was analyzed to compare therapeutic effectiveness between IDC-P positive and negative cases. Utilizing propensity score matching (PSM) to reduce bias, outcomes such as PSA response, progression-free survival (PSA-PFS), radiographic progression-free survival (rPFS), and overall survival were assessed. Additionally, the second cohort of 760 mHSPC patients compared the efficacy of abiraterone with conventional hormone therapy, focusing on differences between IDC-P positive and negative individuals. RESULTS: After PSM, our first cohort included 108 patients with similar baseline characteristics. Among them, 50% (54/108) were diagnosed with IDC-P, with 22.2% (12/54) having IDC-P pattern 1 and 77.8% (42/54) with IDC-P pattern 2. While no notable difference was seen in PSA responses between IDC-P positive and negative patients, IDC-P presence linked to worse clinical outcomes (PSA-PFS: 18.6 months vs. not reached [NR], p = 0.009; rPFS: 23.6 months vs. NR, p = 0.020). Further analysis showed comparable outcomes for IDC-P pattern 1 but significantly worse prognosis for IDC-P pattern 2 (PSA-PFS: 18.6 months vs. NR, p = 0.002; rPFS: 22.4 months vs. NR, p = 0.010). Subgroup analysis revealed IDC-P pattern 2 consistently predicted poorer outcomes across patient subgroups. Remarkably, both IDC-P positive and negative patients gained more from androgen deprivation therapy with abiraterone than conventional treatment, with IDC-P negative patients showing a more significant survival advantage, supported by better hazard ratios (0.47 and 0.66). CONCLUSION: This study found that IDC-P, especially pattern 2, predicts poor prognosis in mHSPC patients on abiraterone therapy. Also, abiraterone's advantage over hormone therapy is reduced in cases with IDC-P compared to those without.

Big data development and agricultural carbon emissions: Exacerbation or suppression? A quasi-natural experiment based on the establishment of the National Big Data Comprehensive Pilot Zone.

As a strategic resource, big data has become a key force affecting carbon emission reduction in agriculture. However, its impacts remain controversial, and relevant empirical evidence remains to be explored. Based on quasi-natural experimental analysis, this study explored the impact and mechanism of the construction of the National Big Data Comprehensive Pilot Zone (NBDCPZ) on agricultural carbon emissions (ACE) in China and adopted a difference-in-difference (DID) model using China's provincial panel data from 2003 to 2020. The results showed that the ACE in the NBDCPZ establishment area was significantly reduced by 11.91%, a finding that remained robust following the parallel trend test and the placebo test, among others. Mechanism analysis showed that the ACE was reduced through industrial upgrading and technological innovation. Heterogeneity analysis showed that more pronounced policy gains were achieved in China's central-eastern regions as well as in non-major grain-producing areas compared to western and major grain-producing areas. This research provided supporting evidence for the prospect of big data application in ACE and provided useful guidance regarding the promotion of green and sustainable agricultural development.

Epigenetic modification of PHLDA2 is associated with tumor microenvironment and unfavorable outcome of immune checkpoint inhibitor-based therapies in clear cell renal cell carcinoma.

BACKGROUND: A substantial proportion of patients with metastatic clear cell renal cell carcinoma (ccRCC) cannot derive benefit from immune checkpoint inhibitor (ICI) plus anti-angiogenic agent combination therapy, making identification of predictive biomarkers an urgent need. The members of pleckstrin homology-like domain family A (PHLDA) play critical roles in multiple cancers, whereas their roles in ccRCC remain unknown. METHODS: Transcriptomic, clinical, genetic alteration and DNA methylation data were obtained for integrated analyses from TCGA database. RNA sequencing was performed on 117 primary tumors and 79 normal kidney tissues from our center. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis, gene set enrichment analysis were performed to explore transcriptomic features. Data from three randomized controlled trials (RCT), including CheckMate025, IMmotion151, JAVELIN101, were obtained for validation. RESULTS: Members of PHLDA family were dysregulated in pan-cancer. Elevated PHLDA2 expression was associated with adverse clinicopathologic parameters and worse prognosis in ccRCC. Aberrant DNA hypomethylation contributed to up-regulation of PHLDA2. An immunosuppressive microenvironment featured by high infiltrates of Tregs and cancer-associated fibroblasts, was observed in ccRCC with higher PHLDA2 expression. Utilizing data from three RCTs, the association of elevated PHLDA2 expression with poor therapeutic efficacy of ICI plus anti-angiogenic combination therapy was confirmed. CONCLUSIONS: Our study revealed that elevated PHLDA2 expression regulated by DNA hypomethylation was correlated with poor prognosis and immunosuppressive microenvironment, and highlighted the role of PHLDA2 as a robust biomarker for predicting therapeutic efficacy of ICI plus anti-angiogenic agent combination therapy in ccRCC, which expand the dimension of precision medicine.

Predicting abiraterone efficacy in advanced prostate cancer: Insights from marker of proliferation Ki67.

BACKGROUND: KI67 is a well-known biomarker reflecting cell proliferation. We aim to elucidate the predictive role of KI67 in the efficacy of abiraterone for patients with advanced prostate cancer (PCa). METHODS: Clinicopathological data of 152 men with metastatic PCa, who received abiraterone therapy were retrospectively collected. The KI67 positivity was examined by immunohistochemistry using the prostate biopsy specimen. The predictive value of KI67 on the therapeutic efficacy of abiraterone was explored using Kaplan-Meier curve and Cox regression analysis. The endpoints included prostate-specific antigen (PSA) progression-free survival (PSA-PFS), radiographic PFS (rPFS), and overall survival (OS). RESULTS: In total, 85/152 (55.9%) and 67/152 (44.1%) cases, respectively, received abiraterone at metastatic hormone-sensitive (mHSPC) and castration-resistant PCa (mCRPC) stage. The median KI67 positivity was 20% (interquartile range: 10%-30%). Overall, KI67 rate was not correlated with PSA response. Notably, an elevated KI67-positive rate strongly correlated with unfavorable abiraterone efficacy, with KI67 ≥ 30% and KI67 ≥ 20% identified as the optimal cutoffs for prognosis differentiation in mHSPC (median PSA-PFS: 11.43 Mo vs. 26.43 Mo, p < 0.001; median rPFS: 16.63 Mo vs. 31.90 Mo, p = 0.003; median OS: 21.77 Mo vs. not reach, p = 0.005) and mCRPC (median PSA-PFS: 7.17 Mo vs. 12.20 Mo, p = 0.029; median rPFS: 11.67 Mo vs. 16.47 Mo, p = 0.012; median OS: 21.67 Mo vs. not reach, p = 0.073) patients, respectively. Multivariate analysis supported the independent predictive value of KI67 on abiraterone efficacy. In subgroup analysis, an elevated KI67 expression was consistently associated with unfavorable outcomes in the majority of subgroups. Furthermore, data from another cohort of 79 PCa patients with RNA information showed that those with KI67 RNA levels above the median had a significantly shorter OS than those below the median (17.71 vs. 30.72 Mo, p = 0.035). CONCLUSIONS: This study highlights KI67 positivity in prostate biopsy as a strong predictor of abiraterone efficacy in advanced PCa. These insights will assist clinicians in anticipating clinical outcomes and refining treatment decisions for PCa patients.

Fates of Terrigenous Dissolved Organic Carbon in the Gulf of Maine.

A significant amount of organic carbon is transported in dissolved form from soils to coastal oceans via inland water systems, bridging land and ocean carbon reservoirs. However, it has been discovered that the presence of terrigenous dissolved organic carbon (tDOC) in oceans is relatively limited. Therefore, understanding the fates of tDOC in coastal oceans is essential to account for carbon sequestration through land ecosystems and ensure accurate regional carbon budgeting. In this study, we developed a state-of-the-art modeling approach by coupling a land-to-ocean tDOC flux simulation model and a coastal tDOC tracking model to determine the potential fates of tDOC exported from three primary drainage basins in the Gulf of Maine (GoM). According to our findings, over half a year in the GoM, 56.4% of tDOC was mineralized. Biomineralization was responsible for 90% of that amount, with the remainder attributed to photomineralization. Additionally, 37% of the tDOC remained suspended in the GoM, and 6.6% was buried in the marine sediment.

Emergent Intrinsic Ferromagnetism in Two-Dimensional Trigonal Rhodium Oxide.

Two-dimensional (2D) van der Waals single crystals with long-range magnetic order are the precondition and urgent task for developing a 2D spintronics device. In contrast to graphene and transition metal dichalcogenides, the study of 2D single-crystal metal oxides with intrinsic ferromagnetic properties remains a huge challenge. Here, we report a large-size trigonal single-crystal rhodium oxide (SC-Tri-RhO2), with crystal parameters of a = b = 3.074 Å, c = 6.116 Å, and a space group of P3̅m1 (164), exhibiting strong ferromagnetism (FM) at a rather high temperature. Furthermore, theoretical calculations suggest that the ferromagnetism in SC-Tri-RhO2 originates from spin splitting near the Fermi level, and the total magnetic moment is contributed mainly by the Rh atom.

A Regularized Regression Thermal Error Modeling Method for CNC Machine Tools under Different Ambient Temperatures and Spindle Speeds.

Establishing a mathematical model to predict and compensate for the thermal error of CNC machine tools is a commonly used approach. Most existing methods, especially those based on deep learning algorithms, have complicated models that need huge amounts of training data and lack interpretability. Therefore, this paper proposes a regularized regression algorithm for thermal error modeling, which has a simple structure that can be easily implemented in practice and has good interpretability. In addition, automatic temperature-sensitive variable selection is realized. Specifically, the least absolute regression method combined with two regularization techniques is used to establish the thermal error prediction model. The prediction effects are compared with state-of-the-art algorithms, including deep-learning-based algorithms. Comparison of the results shows that the proposed method has the best prediction accuracy and robustness. Finally, compensation experiments with the established model are conducted and prove the effectiveness of the proposed modeling method.

Transcriptomic and Metabolomic Profiling Uncovers Response Mechanisms of Alicyclobacillus acidoterrestris DSM 3922T to Acid Stress.

Alicyclobacillus acidoterrestris, which has strong acidophilic and heat-resistant properties, can cause spoilage of pasteurized acidic juice. The current study determined the physiological performance of A. acidoterrestris under acidic stress (pH 3.0) for 1 h. Metabolomic analysis was carried out to investigate the metabolic responses of A. acidoterrestris to acid stress, and integrative analysis with transcriptome data was also performed. Acid stress inhibited the growth of A. acidoterrestris and altered its metabolic profiles. In total, 63 differential metabolites, mainly enriched in amino acid metabolism, nucleotide metabolism, and energy metabolism, were identified between acid-stressed cells and the control. Integrated transcriptomic and metabolomic analysis revealed that A. acidoterrestris maintains intracellular pH (pHi) homeostasis by enhancing amino acids decarboxylation, urea hydrolysis, and energy supply, which was verified using real-time quantitative PCR and pHi measurement. Additionally, two-component systems, ABC transporters, and unsaturated fatty acid synthesis also play crucial roles in resisting acid stress. Finally, a model of the responses of A. acidoterrestris to acid stress was proposed. IMPORTANCE Fruit juice spoilage caused by A. acidoterrestris contamination has become a major concern and challenge in the food industry, and this bacterium has been suggested as a target microbe in the design of the pasteurization process. However, the response mechanisms of A. acidoterrestris to acid stress still remain unknown. In this study, integrative transcriptomic, metabolomic, and physiological approaches were used to uncover the global responses of A. acidoterrestris to acid stress for the first time. The obtained results can provide new insights into the acid stress responses of A. acidoterrestris, which will point out future possible directions for the effective control and application of A. acidoterrestris.

The acceleration on decolorization of azo dyes by magnetic lignin-based materials via enhancing the extracellular electron transfer.

Two novel and eco-friendly redox mediators (RMs), magnetic oxidative vanillin (MOV) and magnetic oxidative syringaldehyde (MOS), both derived from lignin, were prepared to improve the decolorization of the methyl orange (MO) dye. The Decolorization Efficiency (DE) of MO in the batch experiments with MOV and MOS were increased by more than 60% and 22%, respectively, when compared to the control experiment without magnetic RMs. Moreover, the two magnetic RMs could maintain stable DE of MO in sequenced batch reactors (SBRs), and negligible leaching of the oxidized lignin monomers was observed under various environmental conditions. Density Function Theory (DFT) calculations were used to propose three potential biodegradation mechanisms for azo dyes, and the key intermediates were confirmed using high-performance liquid chromatography. This study proposed a feasible strategy for functional utilization of lignin resource, as well as a practical method for effectively treating azo dye-containing wastewater.

Characters of KRT80 and its roles in neoplasms diseases.

BACKGROUND: KRT80 is a human epithelial intermediate filament type II gene; its expression product is a component of intracellular intermediate filaments (IFs) and is involved in the assembly of the cytoskeleton. There is evidence that IFs form a dense network mainly in the perinuclear area, but they can also reach the cortex. They are essential for mechanical cushioning of cells, organelle positioning, cell apoptosis, migration, adhesion, and interactions with other cytoskeletal components. Humans possess 54 functional keratin genes, and KRT80 is one of the more unique genes. It is widely expressed in almost all epithelial cells, although it is structurally more similar to type II hair keratins than to type II epithelial keratins. AIM: In this review, we summarize the basic facts about the keratin family and KRT80, the essential role of KRT80 in neoplasms, and its potential as a therapeutic target. We hope that this review will inspire researchers to at least partially focus on this area. RESULT: In many neoplastic diseases, the high expression status of KRT80 and its role in regulating the biological functions of cancer cells have been well established. KRT80 can effectively enhance the proliferation, invasiveness and migration of cancer cells. However, the effects of KRT80 on prognosis and clinically relevant indices in patients with various cancers have not been extensively studied, and even opposite conclusions have been reached in different studies of the same cancer. Based on this, we should add more clinically relevant studies to clarify the prospect of clinical application of KRT80. Many researchers have made great progress in studying the mechanism of action of KRT80. However, their studies should be extended to more cancers to find common regulators and signaling pathways of KRT80 in different cancers. KRT80 may have far-reaching effects on the human body, and this marker may play a crucial role in the function of cancer cells and the prognosis of cancer patients, so it has a promising future in the field of neoplasms. CONCLUSION: In neoplastic diseases, KRT80 is overexpressed in many cancers and plays an essential role in promoting proliferation, migration, invasiveness and poor prognosis. The mechanisms of KRT80 functions in cancer have been partially elucidated, suggesting that KRT80 is a potentially useful cancer therapeutic target. However, more systematic, in-depth and comprehensive studies are still needed in this field.

Contribution of amino acids to Alicyclobacillus acidoterrestris DSM 3922T resistance towards acid stress.

Spoilage of juice and beverages by a thermo-acidophilic bacterium, Alicyclobacillus acidoterrestris, has been considered to be a major and widespread concern for juice industry. Acid-resistant property of A. acidoterrestris supports its survival and multiplication in acidic juice and challenges the development of corresponding control measures. In this study, intracellular amino acid differences caused by acid stress (pH 3.0, 1 h) were determined by targeted metabolomics. The effect of exogenous amino acids on acid resistance of A. acidoterrestris and the related mechanisms were also investigated. The results showed that acid stress affected the amino acid metabolism of A. acidoterrestris, and the selected glutamate, arginine, and lysine contributed to its survival under acid stress. Exogenous glutamate, arginine, and lysine significantly increased the intracellular pH and ATP level, alleviated cell membrane damage, reduced surface roughness, and suppressed deformation caused by acid stress. Additionally, the up-regulated gadA and speA genes and the enhanced enzymatic activity confirmed that glutamate and arginine decarboxylase systems played a crucial role in maintaining pH homeostasis of A. acidoterrestris under acid stress. Our research reveals an important factor contributing to acid resistance of A. acidoterrestris, which provides an alternative target for effectively controlling this contaminant in fruit juices.

Integrating terrestrial and aquatic ecosystems to constrain estimates of land-atmosphere carbon exchange.

In this Perspective, we put forward an integrative framework to improve estimates of land-atmosphere carbon exchange based on the accumulation of carbon in the landscape as constrained by its lateral export through rivers. The framework uses the watershed as the fundamental spatial unit and integrates all terrestrial and aquatic ecosystems as well as their hydrologic carbon exchanges. Application of the framework should help bridge the existing gap between land and atmosphere-based approaches and offers a platform to increase communication and synergy among the terrestrial, aquatic, and atmospheric research communities that is paramount to advance landscape carbon budget assessments.

A life cycle and product type based estimator for quantifying the carbon stored in wood products.

BACKGROUND: Timber harvesting and industrial wood processing laterally transfer the carbon stored in forest sectors to wood products creating a wood products carbon pool. The carbon stored in wood products is allocated to end-use wood products (e.g., paper, furniture), landfill, and charcoal. Wood products can store substantial amounts of carbon and contribute to the mitigation of greenhouse effects. Therefore, accurate accounts for the size of wood products carbon pools for different regions are essential to estimating the land-atmosphere carbon exchange by using the bottom-up approach of carbon stock change. RESULTS: To quantify the carbon stored in wood products, we developed a state-of-the-art estimator (Wood Products Carbon Storage Estimator, WPsCS Estimator) that includes the wood products disposal, recycling, and waste wood decomposition processes. The wood products carbon pool in this estimator has three subpools: (1) end-use wood products, (2) landfill, and (3) charcoal carbon. In addition, it has a user-friendly interface, which can be used to easily parameterize and calibrate an estimation. To evaluate its performance, we applied this estimator to account for the carbon stored in wood products made from the timber harvested in Maine, USA, and the carbon storage of wood products consumed in the United States. CONCLUSION: The WPsCS Estimator can efficiently and easily quantify the carbon stored in harvested wood products for a given region over a specific period, which was demonstrated with two illustrative examples. In addition, WPsCS Estimator has a user-friendly interface, and all parameters can be easily modified.

Response mechanisms to acid stress of acid-resistant bacteria and biotechnological applications in the food industry.

Acid-resistant bacteria are more and more widely used in industrial production due to their unique acid-resistant properties. In order to survive in various acidic environments, acid-resistant bacteria have developed diverse protective mechanisms such as sensing acid stress and signal transduction, maintaining intracellular pH homeostasis by controlling the flow of H+, protecting and repairing biological macromolecules, metabolic modification, and cross-protection. Acid-resistant bacteria have broad biotechnological application prospects in the food field. The production of fermented foods with high acidity and acidophilic enzymes are the main applications of this kind of bacteria in the food industry. Their acid resistance modules can also be used to construct acid-resistant recombinant engineering strains for special purposes. However, they can also cause negative effects on foods, such as spoilage and toxicity. Herein, the aim of this paper is to summarize the research progress of molecular mechanisms against acid stress of acid-resistant bacteria. Moreover, their effects on the food industry were also discussed. It is useful to lay a foundation for broadening our understanding of the physiological metabolism of acid-resistant bacteria and better serving the food industry.

Effect of inorganic and organic nitrogen supplementation on volatile components and aroma profile of cider.

To investigate the impact of inorganic and organic nitrogen on volatile compounds of cider, various levels (60, 150 and 240 mg N/L) of diammonium hydrogen phosphate (DAP) and amino acids mixture were added to apple juice before fermentation, respectively. The qualitative and quantitative of volatile substances were carried out by GC-MS. Further, sensory and electronic nose analysis was performed to analyze the aroma profile of cider. Both DAP and amino acids mixture promoted fermentation, significantly affected volatile compositions and increased perceived aromas of cider. Adding 60 mg N/L DAP significantly increased volatile compounds content, especially medium-chain fatty acid ethyl esters (MCFAEEs) and fatty acids (FAs), whereas higher alcohols and acetate esters concentrations were remarkably increased with 150 mg N/L amino acids supplementation. Partial least-squares (PLS) regression analysis suggested that MCFAEEs contributed the most to tropical fruity aroma. The study provides a theoretical foundation for high-quality cider brewing.

Antiosteoporosis and bone protective effect of nimbolide in steroid-induced osteoporosis rats.

BACKGROUND: Osteoporosis is a metabolic, hereditary, progressive disease characterized by unusual bone production across the skeleton and a loss the bone tissue microstructure and mass. In this experimental study, we scrutinized the antiosteoporosis effect of nimbolide against glucocorticoid (GCs) induced osteoporosis in rats. METHODS: Swiss albino female rats were employed for the current experiment study and the rats were divided into different groups. Dexamethasone (0.1 mg/kg/day) was used for induction the osteoporosis and the rats were received the different doses of nimbolide (2.5, 5, and 7.5 mg/kg) for the estimation of bone protective effects. The body weight was estimated (initially and finally). Hormones, bone metabolic markers, bone turnover markers, bone structure, biomechanical, histomorphometric dynamic, biochemical markers, and histomorphometric static parameters were analyzed. RESULTS: The body weight of GCs group rats considerably suppressed and nimbolide treatment remarkably improved the body weight. Nimbolide treated group exhibited the enhancement of bone metabolic, bone structure markers, and histomophometric dynamic markers, which was suppressed during the GCs-induced osteoporosis. GCs-induced osteoporosis rats exhibited the enhancement of procollagen type 1 C-terminal propeptide (P1CP), carboxy-terminal crosslinked telopeptide of type 1 collagen (CTX-1), Dickkopf-1 (DKK1), tartrate-resistant acid phosphatase 5b (TRACP 5b), and suppressed the level of bone alkaline phosphatase (BAP), which was reversed by the nimbolide treatment. Nimbolide treatment remarkably improved the level of estradiol and suppressed the level of parathyroid hormone (PTH), which was altered during the osteoporosis. Nimbolide treatment significantly (p < 0.001) improved the level of calcium, magnesium, and phosphorus in the serum and bone tissue. Nimbolide treatment also altered the level of bone metabolic markers and suppressed the level of inflammatory cytokines. CONCLUSION: Based on the findings, we may conclude that nimbolide has antiosteoporosis properties via balancing the bone mass and improving vitamin and hormone levels.

Year-Round Thermal Error Modeling and Compensation for the Spindle of Machine Tools Based on Ambient Temperature Intervals.

The modeling and compensation method is a common method for reducing the influence of thermal error on the accuracy of machine tools. The prediction accuracy and robustness of the thermal error model are two key performance measures for evaluating the compensation effect. However, it is difficult to maintain the prediction accuracy and robustness at the desired level when the ambient temperature exhibits strong seasonal variations. Therefore, a year-round thermal error modeling and compensation method for the spindle of machine tools based on ambient temperature intervals (ATIs) is proposed in this paper. First, the ATIs applicable to the thermal error prediction models (TEPMs) under different ambient temperatures are investigated, where the C-Means clustering algorithm is utilized to determine ATIs. Furthermore, the prediction effect of different numbers of ATIs is analyzed to obtain the optimal number of ATIs. Then, the TEPMs corresponding to different ATIs in the annual ambient temperature range are established. Finally, the established TEPMs of ATIs are used to predict the experimental data of the entire year, and the prediction accuracy and robustness of the proposed ATI model are analyzed and compared with those of the low and high ambient temperature models. The prediction accuracies of the ATI model are 20.6% and 41.7% higher than those of the low and high ambient temperature models, respectively, and the robustness is improved by 48.8% and 62.0%, respectively. This indicates that the proposed ATI method can achieve high prediction accuracy and robustness regardless of the seasonal temperature variations throughout the year.