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This paper proposed a user-friendly and adaptive home intelligent agent with self-learning capability for optimal scheduling of smart home energy systems. The intelligent agent autonomously identifies model parameters based on system operation data, eliminating the need for manual input and making it more user-friendly and practical to implement. It can also self-learn the latest energy consumption information from an updated dataset and adaptively adjust model parameters to accommodate changing conditions. Utilizing these determined models as input, the intelligent agent performs day-ahead optimal scheduling using the proposed many-objective integer nonlinear optimization model and automatically controls system operation. Experimental studies were conducted on a laboratory-based smart home energy system to verify the effectiveness of the developed intelligent agent in different scenarios. The results consistently demonstrate Mean Absolute Percentage Errors below -12.7 % across all three scenarios, indicating the accuracy of the intelligent agent. Furthermore, the optimal scheduling significantly enhances system performances. After optimization, daily operational costs, peak-valley differences, and CO2 emissions were reduced by 34.1 % to 81.6 %, 29.2 % to 36.7 %, and 19.6 % to 43.2 %, respectively. Moreover, the PV generation self-consumption rate and self-sufficiency rate improved by 29.6 % to 38.0 % and 40.5 % to 49.4 %, respectively. The proposed intelligent agent provides invaluable guidance for optimal dispatch of smart home energy systems in real-world settings.

Abstract Background For patients with locally advanced rectal cancer (LARC), total neoadjuvant therapy (TNT), namely, intensifying preoperative treatment through the integration of radiotherapy and systemic chemotherapy before surgery, was commonly recommended as the standard treatment. However, the risk of distant metastasis at 3 years remained higher than 20%, and the complete response (CR) rate was less than 30%. Several clinical trials had suggested a higher complete response rate when combining single-agent immunotherapy with short-course radiotherapy (SCRT). The CheckMate 142 study had shown encouraging outcomes of dual immunotherapy and seemingly comparable toxicity for CRC compared with single-agent immunotherapy in historical results. Therefore, dual immunotherapy might be more feasible in conjunction with the TNT paradigm of SCRT. We performed a phase II study to investigate whether the addition of a dual immune checkpoint inhibitor bispecific antibody, Cadonilimab, to SCRT combined with chemotherapy might further increase the clinical benefit and prognosis for LARC patients. Methods This single-arm, multicenter, prospective, phase II study included patients with pathologically confirmed cT3-T4N0 or cT2-4N + rectal adenocarcinoma with an ECOG performance score of 0 or 1. Bispecific antibody immunotherapy was added to SCRT combined with chemotherapy. Patients enrolled would be treated with SCRT (25 Gy in five fractions over 1 week) for the pelvic cavity, followed by 4 cycles of CAPOX or 6 cycles of mFOLFOX and Cadonilimab. The primary endpoint was the CR rate, which was the ratio of the pathological CR rate plus the clinical CR rate. The secondary endpoints included local–regional control, distant metastasis, disease-free survival, overall survival, toxicity profile, quality of life and functional outcome of the rectum. To detect an increase in the complete remission rate from 21.8% to 40% with 80% power, 50 patients were needed. Discussion This study would provide evidence on the efficacy and safety of SCRT plus bispecific antibody immunotherapy combined with chemotherapy as neoadjuvant therapy for patients with LARC, which might be used as a candidate potential therapy in the future. Trial registration This phase II trial was prospectively registered at ClinicalTrials.gov, under the identifier NCT05794750.

Abstract Background Radiation pneumonitis (RP) is one of the common side effects after adjuvant radiotherapy in breast cancer. Irradiation dose to normal lung was related to RP. We aimed to propose an organ features based on deep learning (DL) model and to evaluate the correlation between normal lung dose and organ features. Methods Patients with pathology-confirmed invasive breast cancer treated with adjuvant radiotherapy following breast-conserving surgery in four centers were included. From 2019 to 2020, a total of 230 patients from four nationwide centers in China were screened, of whom 208 were enrolled for DL modeling, and 22 patients from another three centers formed the external testing cohort. The subset of the internal testing cohort (n = 42) formed the internal correlation testing cohort for correlation analysis. The outline of the ipsilateral breast was marked with a lead wire before the scanning. Then, a DL model based on the High-Resolution Net was developed to detect the lead wire marker in each slice of the CT images automatically, and an in-house model was applied to segment the ipsilateral lung region. The mean and standard deviation of the distance error, the average precision, and average recall were used to measure the performance of the lead wire marker detection model. Based on these DL model results, we proposed an organ feature, and the Pearson correlation coefficient was calculated between the proposed organ feature and ipsilateral lung volume receiving 20 Gray (Gy) or more (V20). Results For the lead wire marker detection model, the mean and standard deviation of the distance error, AP (5 mm) and AR (5 mm) reached 3.415 ± 4.529, 0.860, 0.883, and 4.189 ± 8.390, 0.848, 0.830 in the internal testing cohort and external testing cohort, respectively. The proposed organ feature calculated from the detected marker correlated with ipsilateral lung V20 (Pearson correlation coefficient, 0.542 with p

The optimal scheduling of home energy systems is influenced by the benefits of different stakeholders, with the hierarchical nature of user's needs being particularly significant. However, previous studies have largely neglected these factors. To bridge the research gaps, a many-objective optimal dispatch framework for home energy systems, which was inspired by Maslow's hierarchy of needs, was proposed. In the framework, user's needs for the optimal dispatch of home energy systems were categorized into various hierarchies referring to the Maslow's theory, which were fulfilled in a specific sequence during the scheduling optimization. In addition to the user's needs, the benefits of grid operators and policymakers were considered in the developed many-objective nonlinear optimal model, which includes six objective functions that capture the interests of end-users, grid operators, and policymakers. Simulation results obtained across the home energy systems with various configurations verified the effectiveness of the proposed framework. Results indicate that user's needs can be fully satisfied and a tradeoff among the benefits of end-users, grid operators, and policymakers was achieved. For various home energy systems, the optimal scheduling demonstrated reductions of 22.33 %-81.05 % in daily operation costs, 14.39 %-25.68 % in CO2 emissions, and 15.58 %-17.49 % in peak-valley differences, associated with increment of 5.37 %-15.51 % in self-consumption rate and 8.91 %-27.29 % in self-sufficiency rate, compared with the benchmark. The proposed framework provides valuable guidance for the optimal scheduling of various home energy systems in practical applications.

This paper focused on the impact of window shades’ physical characteristics and opening modes on annual air conditioning energy consumption of residential buildings in China. Three building models with different window layouts were proposed initially, and then validated by the dimensionless indicator annual energy performance (AEP) to determine the final building model adopted in this study. Harbin, Beijing, Guangzhou, Changsha and Kunming were selected to represent five different climate zones in China. The shading model has taken six physical characteristics of window shades, viz. outer emissivity, inner emissivity, solar transmittance, solar reflectance, thermal infrared transmittance, conductivity and two opening modes, viz. up & down mode as well as left & right mode, into consideration. Besides, the window shades operation schedule was summarized through 949 valid questionnaires. The annual air conditioning energy consumption was calculated via EnergyPlus software, and then the impact of the above different opening modes and parameters on energy use were investigated. The analysis results indicated that the top & bottom opening mode is better than the left & right mode when used in Harbin, and the effect of two different modes in air conditioning energy consumption in Kunming is similar. But in the other three cities, the left and right mode is preferred. Besides, the analysis results of the impact of different physical characteristics on air conditioning energy use in different climate zones could help improve the energy performance of window shades.

miR-29a/b1 was reportedly involved in the regulation of the reproductive function in female mice, but the underlying molecular mechanisms are not clear. In this study, female mice lacking miR-29a/b1 showed a delay in vaginal opening, irregular estrous cycles, ovulation disorder and subfertility. The level of luteinizing hormone (LH) was significantly lower in plasma but higher in pituitary of mutant mice. However, egg development was normal in mutant mice and the ovulation disorder could be rescued by the superovulation treatment. These results suggested that the LH secretion was impaired in mutant mice. Further studies showed that deficiency of miR-29a/b1 in mice resulted in an abnormal expression of a number of proteins involved in vesicular transport and exocytosis in the pituitary, indicating the mutant mice had insufficient LH secretion. However, the detailed mechanism needs more research.

Construction business involves people from different employers who have to work together in one project, thus a project manager needs to apply scientific principles to understand and to utilize those common psychological phenomena such as Hedgehog Effect, Butterfly Effect, Pygmalion Effect, Boiled Frog Syndrome, Parkinson’s Law, and Bandwagon Effect in completing work well and keeping people satisfied. The aim of this study is to develop a fuzzy mapping to assist project managers in implementing significant psychological phenomena in construction management through reflections on common psychological phenomena in the construction management. Through a structured interview survey among construction managers, the inferential association among gender, working experience, and the six psychological phenomena were plotted based on the Partial Least Square Structural Equation Modelling. Through the pairwise comparison technique, a fuzzy mapping of psychological phenomena in time, cost, and quality management was developed to facilitate the managerial efficiency in construction.

The significance of innovation management in triggering and sustaining increase in corporations of distinct size, age or enterprise type, is receiving growing attention, yet scant empirical research have been carried out in project-oriented service firms, in particular small-scaled enterprises. This study aims to identify how innovation management in small construction firms could enable them to pursue innovation and achieve greater business performance. Data collection comprises 157 empirical surveys leading to a conceptual framework modelled using the structural equation modelling approach. The findings show that entrepreneurship and networking have a direct and considerable influence on both technological and non-technological innovation, which consequently improves firm performance.

As China's population ages and the notion of contemporary people evolves, an increasing number of elderly people opt to spend their final years in a nursing home. Recently, there have been more fires in nursing facilities for the elderly. As a result, using computer simulation technology, this paper creates an evacuation micro-simulation model for the elderly and nursing staff, investigates the impact of psychological characteristics and evacuation behavior of the elderly and nursing staff on fire escape during the fire evacuation process, and designs fire evacuation for nursing homes. Based on the nursing home's regular evacuation paradigm, the study examines the behavioral elements. To simulate the three models and the influence of various behavioral and psychological features on fire evacuation, the authors utilized the MATLAB software, which is based on Agent theory and cellular automata. The simulation results show that the three models proposed in this study are capable of accurately describing reality.

Abstract Background Chimeric antigen receptor T‐cell (CAR‐T) therapy for acute myeloid leukaemia (AML) has thus far been elusive, in part due to target restriction and phenotypic heterogeneity of AML cells. Mutations of the FMS‐like tyrosine kinase 3 (FLT3) and DNA methyltransferase 3A (DNMT3A) genes are common driver mutations that present with a poor prognosis in AML patients. We found that AML patients with FLT3 or DNMT3A mutations had higher expression of CD44 isoform 6 (CD44v6) compared to normal specimens. Therefore, we intended to demonstrate CD44v6 could be a specific option for AML with FLT3 or DNMT3A mutations. Methods Internal tandem duplication (ITD) mutations of FLT3 (FLT3/ITD) knock‐in clone and DNMT3A‐R882H mutant clones of SKM‐1 cells were generated using CRISPR/Cas9 and lentiviral transfection, respectively. CD44v6 CAR‐T cells were constructed by transfecting T cells with lentivirus containing CD44v6 CAR. CD44v6 expression in AML cell lines, AML patients and healthy donors was evaluated by flow cytometry. DNA methylation assays were used to analyse the mechanisms of FLT3 and DNMT3A mutations affecting CD44v6 expression. Results Aberrant overexpression of CD44v6 was observed in AML cell lines with FLT3 or DNMT3A mutations compared to the wild‐type SKM‐1 or K562 cells. AML patients with FLT3 or DNMT3A mutations had higher expression of CD44v6 compared to normal specimens. Then we constructed CD44v6 CAR‐T cells and found that CD44v6 CAR‐T specifically lysed CD44v6+ cells, accompanied by cytokines release. No significant killing effect was observed from CD44v6‐ AML cells and normal cells after co‐culture with CD44v6 CAR‐T. These results were also observed in vivo. Furthermore, we found that FLT3 or DNMT3A mutations induced CD44v6 overexpression by downregulating the CpG methylation of CD44 promoter. Conclusions Collectively, CD44v6 is a promising target of CAR‐T for AML patients with FLT3 or DNMT3A mutations.

Emergency evacuation simulation is significant for architectural design and emergency plan implementation. To explore the influence of evacuees’ physical behavior and evacuees’ decisions on the evacuation process, as well as to address the problems of traditional emergency evacuation models with insufficient detail of the situation (realism), low reusability, poor operability, and lack of subsequent scalability, this paper first analyzed pedestrian characteristics in emergencies. To describe pedestrian decision-making in an emergent evacuation situation, a multi-agent design based on decision theory was proposed, solving the multi-agent decision-making problem in an emergency evacuation environment by the A* algorithm. Then the designed multi-agent was embedded into the social force model by AnyLogic software. Finally, the model reproduces the pedestrian evacuation process in an emergency evacuation situation on the built platform, depicting three kinds of typical behaviors: pedestrian partnering, obstacle avoidance, and exit competition. In addition, this study also analyzed a large student apartment building by example and proposed corresponding optimization solutions to improve its evacuation capacity through simulation results.

Acute myeloid leukemia (AML) patients who develop hematological relapse (HR) after allogeneic hematopoietic stem cell transplantation (allo-HSCT) generally have dismal clinical outcomes. Measurable residual disease (MRD)-directed preemptive interventions are effective approaches to prevent disease progression and improve prognosis for molecular relapsed patients with warning signs of impending HR. In this situation, boosting the graft-vs-leukemia (GVL) effect with immune checkpoint inhibitors (ICIs) might be a promising prevention strategy, despite the potential for causing severe graft-vs-host disease (GVHD). In the present study, we reported for the first time an AML patient with RUNX1-RUNX1T1 who underwent preemptive treatment with the combined application of tislelizumab (an anti-PD-1 antibody) and azacitidine to avoid HR following allo-HSCT. On day +81, molecular relapse with MRD depicted by RUNX1-RUN1T1-positivity as well as mixed donor chimerism occurred in the patient. On day +95, with no signs of GVHD and an excellent eastern cooperative oncology group performance status (ECOG PS), the patient thus was administered with 100 mg of tislelizumab on day 1 and 100 mg of azacitidine on days 1-7. After the combination therapy, complete remission was successfully achieved with significant improvement in hematologic response, and the MRD marker RUNX1-RUNX1T1 turned negative, along with a complete donor chimerism in bone marrow. Meanwhile, the patient experienced moderate GVHD and immune-related adverse events (irAEs), successively involving the lung, liver, lower digestive tract and urinary system, which were well controlled by immunosuppressive therapies. As far as we know, this case is the first one to report the use of tislelizumab in combination with azacitidine to prevent post-transplant relapse in AML. In summary, the application of ICIs in MRD positive patients might be an attractive strategy for immune modulation in the future to reduce the incidence of HR in the post-transplant setting, but safer clinical application schedules need to be explored.

Most relapsed chronic myeloid leukemia (CML) patients after tyrosine kinase inhibitor (TKI) discontinuation are in a chronic phase and could achieve remission through restarting the TKI treatment. Here we reported a case of sudden lymphoid blast crisis after 67 months of TKI discontinuation and depicted the patient by DNA and RNA sequencing to investigate intrinsic molecular features. The mutations of TGFBR2 and PCNT and the dysregulations of TGF-β and other pathways might accelerate the B cell transformation, which may serve as a blast crisis risk indicator of CML. Single-cell transcriptome data revealed that several clusters of immature B cells and late pro-B cells presented clone evolution during the treatment. After failing multiple lines of TKIs, conditioning chemotherapies and chimeric antigen receptor T cells (CAR-T) targeting CD19 and CD22 were performed to achieve remission. In conclusion, we report the first case of a CML patient with sudden lymphoid blast crisis after a long treatment-free remission and additional gene abnormalities other than BCR-ABL1 might participate in the progression, which need to be closely monitored, and CAR-T could be a solution to the chemoresistant progression.

In order to accurately analyze the building energy consumption and identify the problem of building energy consumption in advance, this study carries out the energy consumption analysis based on BIM (Building Information Modeling). The research object is a four-story college student dormitory in Beijing, and this set of BIM-based energy consumption simulation data was obtained using standard operating procedures (SOP). This operating procedure can start energy consumption analysis in the conceptual design stage, and developers can participate in real-time through the use of a three-dimensional information model, without additional design required. Then, comparing this study with the traditional energy consumption analysis, we see that the SOP of this research result has the following advantages: SOP function analysis is more professional, and the visual display method is more popular and intuitive; due to the flexible file format of the SOP, when data exchange is required between different software, the SOP can realize more convenient operation, and users can identify problems in the early stage of design through the SOP, correcting the scheme according to the simulation results, which is conducive to the development of the construction process. Finally, this study puts forward the analysis and estimation of energy consumption in different stages of the building life cycle, so as to provide researchers with ideas for improvement.

The safety inspection capability of construction sites before typhoons could be improved using a UAV, which has a rapid identification capability. However, the main safety inspection items need construction experience and technical safety specifications. This study aimed to obtain the influencing factors of typhoon and their weight proportion through the knowledge of disaster theory and the analytic hierarchy process (AHP). The effectiveness of this method was verified by collecting and analyzing the field data at the construction site. A set of construction site early warning flows and disaster prevention and mitigation measures for typhoons are proposed. The results show that UAVs can be used as a tool in this scenario, helping to improve disaster prevention and enhancing the capability of construction site management to evaluate typhoon risk. The research provides a much-needed common ground for collecting and analyzing advances in UAVs and immersive technologies, as well as their influence on building projects. Furthermore, this article provides a new horizon for beginner researchers working on digitalized construction research.