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Background: Congenital scoliosis is often associated with costal deformities, of which a bilateral bifid intrathoracic rib is very rare. The aim of this study was to retrospectively summarize the clinical manifestations, imaging characteristics, treatment strategies, and postoperative outcomes of five patients with bilateral bifid intrathoracic rib. Methods: We retrospectively reviewed the imaging findings and medical records of five pediatric patients (two girls, three boys) with bilateral bifid intrathoracic rib who were surgically treated for congenital kyphoscoliosis (mean age = 8 years). The clinical manifestations, imaging characteristics, treatment strategies, and postoperative outcome were summarized. Results: Four of five patients showed abnormalities from birth. All five patients presented with kyphoscoliosis and a fused vertebral body or lamina. The bilateral bifid intrathoracic rib was located at T2–3 in three patients, T7 in one patient, and T10 in one patient. Various congenital spinal deformities and multiple system malformations were present in all five patients. Three patients had preoperative neurological deficits. For corrective surgery, one patient received a traditional growing rod implantation, one patient underwent resection of a bony septum, and three patients underwent spinal osteotomy. One patient suffered complete paralysis of the lower limbs after surgery. Conclusion: Bilateral bifid intrathoracic rib is a rare anomaly that typically occurs in patients with serious kyphoscoliosis. Bilateral bifid intrathoracic rib patients show similar clinical and radiological characteristics and are likely to exhibit neurological deficits before or following corrective surgery. Spinal surgeons should be aware of the high risk of permanent neurological complications related to surgery in these patients. Level of evidence: level IV. [ABSTRACT FROM AUTHOR]

The gut microbiota is a complex community of microorganisms inhabiting the intestinal tract, which plays a vital role in human health. It is intricately involved in the metabolism, and it also affects diverse physiological processes. The gut–lung axis is a bidirectional pathway between the gastrointestinal tract and the lungs. Recent research has shown that the gut microbiome plays a crucial role in immune response regulation in the lungs and the development of lung diseases. In this review, we present the interrelated factors concerning gut microbiota and the associated metabolites in pulmonary hypertension (PH), a lethal disease characterized by elevated pulmonary vascular pressure and resistance. Our research team explored the role of gut‐microbiota‐derived metabolites in cardiovascular diseases and established the correlation between metabolites such as putrescine, succinate, trimethylamine N‐oxide (TMAO), and N, N, N‐trimethyl‐5‐aminovaleric acid with the diseases. Furthermore, we found that specific metabolites, such as TMAO and betaine, have significant clinical value in PH, suggesting their potential as biomarkers in disease management. In detailing the interplay between the gut microbiota, their metabolites, and PH, we underscored the potential therapeutic approaches modulating this microbiota. Ultimately, we endeavor to alleviate the substantial socioeconomic burden associated with this disease. This review presents a unique exploratory analysis of the link between gut microbiota and PH, intending to propel further investigations in the gut–lung axis. Highlights: The significant development in gut microbiota has brought an unprecedented paradigm for pulmonary hypertension (PH) management in recent years, which has delighted researchers and clinicians in precise disease control.The gut–lung axis is the bidirectional interaction between the gut and lung, which occurs through circulation, the nervous system, and other physiological processes, ultimately affecting the health of both the gut and the lung.We provided a comprehensive landscape of gut microbiota and its associated metabolites in PH, emphasizing the interplay between microorganisms and hosts in modulating PH.With the rapid development of technologies, including metagenomic and metabolomics on gut microbiota, the association of microorganisms and the human body will be untangled eventually, which will bring the dawn for disease cure followed by prognosis improvement among patients with PH. [ABSTRACT FROM AUTHOR]

The current motion interaction model has the problems of insufficient motion fidelity and lack of self-adaptation to complex environments. To address this problem, this study proposed to construct a human motion control model based on the muscle force model and stage particle swarm, and based on this, this study utilized the deep deterministic gradient strategy algorithm to construct a motion interaction control model based on the muscle force model and the deep reinforcement strategy. Empirical analysis of the human motion control model proposed in this study revealed that the joint trajectory correlation and muscle activity correlation of the model were higher than those of other comparative models, and its joint trajectory correlation was up to 0.90, and its muscle activity correlation was up to 0.84. In addition, this study validated the effectiveness of the motion interaction control model using the depth reinforcement strategy and found that in the mixed-obstacle environment, the model's desired results were obtained by training 1.1 × 103 times, and the walking distance was 423 m, which was better than other models. In summary, the proposed motor interaction control model using the muscle force model and deep reinforcement strategy has higher motion fidelity and can realize autonomous decision making and adaptive control in the face of complex environments. It can provide a theoretical reference for improving the effect of motion control and realizing intelligent motion interaction. [ABSTRACT FROM AUTHOR]

In this paper, we formulate high-type intelligent control as a multi-objective problem and apply evolutionary algorithms to search for optimal solutions. Specifically, we consider the metrics of the system in both the frequency domain and the time domain. Integrated time and absolute error is used as a performance metric in the time domain, while bandwidth is used as a measure in the frequency domain. Simultaneously, the amplitude margin and phase margin are used as constraints to ensure the stability of the high-type control system. Then, we adopt evolutionary algorithms to solve the formulated multi-objective problem. Unlike most of the existing approaches, we formulate intelligent high type control as a multi-objective optimization problem based on our knowledge about the control system. Furthermore, evolutionary algorithms are adopted to search for optimal solutions to real-world controlling systems. Extensive experiments are conducted to evaluate the effectiveness of our proposed approach. Compared to the Z-N method and the extending symmetrical optimum criterion, our proposed method achieves an improvement in bandwidth of more than 126.6%, while reducing the overshoot by more than 56.8% and the settling time by more than 48.4% for all controlled objects used in the experiments. At the same time, the tracking errors of the ramp and parabolic signals are significantly reduced, which means this method effectively improves the system performance. [ABSTRACT FROM AUTHOR]

Basal crevasses are macroscopic structural discontinuities at the base of ice sheets and glaciers that arise by fracture. Motivated by observations and by the mechanics of elastic fracture, we hypothesise that spatial variations in basal stress (in the presence of basal water pressure) can promote and localise basal crevassing. We quantify this process in the theoretical context of linear elastic fracture mechanics. We develop a model evaluating the effect of shear-stress variation on the growth of basal crevasses. Our results indicate that sticky patches promote the propagation of basal crevasses, increase their length of propagation into the ice and, under some conditions, give them curved trajectories that incline upstream. A detailed exploration of the parameter space is conducted to gain a better understanding of the conditions under which sticky-patch-induced basal crevassing is expected beneath ice sheets and glaciers. [ABSTRACT FROM AUTHOR]

The quasi‐2D Ruddlesden–Popper layered perovskites with single‐phase multiferroicity have attracted much attention in recent magnetoelectric memory applications. We have systematically investigated the optical and magnetic properties of Ru‐doped hybrid improper perovskite Ca3Mn2O7 both experimentally and using first‐principles calculations. The Ca3RuxMn2−xO7 (x = 0, 0.02, 0.06, 0.10) powders were successfully synthesized using the sol–gel method. Ru doping enhanced the ferromagnetism of Ca3Mn2O7. The quasi‐2D antiferromagnetic (AFM) fluctuation effect was observed in Ca3Mn2O7 and in certain doped samples. We also found that the optical bandgaps of the doped samples were reduced after doping, agreeing with the results of the first‐principles calculations. Infrared absorption spectra indicated the distortion of the Mn–O bonds was possibly due to the Jahn–Teller effect. To analyze the electronic structures and to understand the detailed atomic contributions of magnetic moments, the Crystal Orbital Hamilton Population (COHP) and Integrated COHP of the (Mn,Ru)O6 octahedra were also calculated. The Ru‐doped materials with the coexistence of ferromagnetic and AFM orderings are expected to be excellent candidates for magnetoelectric devices. [ABSTRACT FROM AUTHOR]

Background: 44Sc/47Sc is an attractive theranostic pair for targeted in vivo positron emission tomographic (PET) imaging and beta-particle treatment of cancer. The 44Ti/44Sc generator allows daily onsite production of this diagnostic isotope, which may provide an attractive alternative for PET facilities that lack in-house irradiation capabilities. Early animal and patient studies have demonstrated the utility of 44Sc. In our current study, we built and evaluated a novel clinical-scale 44Ti/44Sc generator, explored the pharmacokinetic profiles of 44ScCl3, [44Sc]-citrate and [44Sc]-NODAGA (1,4,7-triazacyclononane,1-glutaric acid-4,7-acetic acid) in naïve mice, and estimated the radiation burden of 44ScCl3 in humans. Methods: 44Ti/44Sc (101.2 MBq) in 6 M HCl solution was utilized to assemble a modular ZR resin containing generator. After assembly, 44Sc was eluted with 0.05 M HCl for further PET imaging and biodistribution studies in female Swiss Webster mice. Based on the biodistribution data, absorbed doses of 44/47ScCl3 in human adults were calculated for 18 organs and tissues using the IDAC-Dose software. Results: 44Ti in 6 M HCl was loaded onto the organic resin generator with a yield of 99.97%. After loading and initial stabilization, 44ScCl3 was eluted with 0.05 M HCl in typical yields of 82.9 ± 5.3% (N = 16), which was normalized to the estimated generator capacity. Estimated generator capacity was computed based on elution time interval and the total amount of 44Ti loaded on the generator. Run in forward and reverse directions, the 44Sc/44Ti ratio from a primary column was significantly improved from 1038 ± 440 to 3557 ± 680 (Bq/Bq) when a secondary, replaceable, ZR resin cartridge was employed at the flow outlet. In vivo imaging and ex vivo distribution studies of the reversible modular generator for 44ScCl3, [44Sc]-citrate and [44Sc]-NODAGA show that free 44Sc remained in the circulation significantly longer than the chelated 44Sc. The dose estimation of 44ScCl3 reveals that the radiation burden is 0.146 mSv/MBq for a 70 kg adult male and 0.179 mSv/MBq for a 57 kg adult female. Liver, spleen and heart wall will receive the highest absorbed dose: 0.524, 0.502, and 0.303 mGy/MBq, respectively, for the adult male. Conclusions: A clinical-scale 44Ti/44Sc generator system with a modular design was developed to supply 44ScCl3 in 0.05 M HCl, which is suitable for further radiolabeling and in vivo use. Our data demonstrated that free 44ScCl3 remained in the circulation for extended periods, which resulted in approximately 10 times greater radiation burden than stably chelated 44Sc. Stable 44Sc/47Sc-complexation will be more favorable for in vivo use and for clinical utility. [ABSTRACT FROM AUTHOR]

Post-stroke fatigue (PSF) is a common complication of stroke that has a negative impact on prognosis and recovery. We aimed to investigate the relationship between PSF and demographics, mood disorders, sleep disorders, and other clinical characteristics of patients with stroke. In this exploratory cross-sectional study, we collected data on sociodemographic characteristics, biological indicators, and imaging features and evaluated patients using neuropsychological scales. Patients were assessed using the Fatigue Severity Scale, Hamilton Depression Rating Scale, Hamilton Anxiety Scale, and Pittsburgh Sleep Quality Index. Magnetic resonance imaging scans were primarily used to evaluate infarctions and white matter lesions. The correlation between the PSF of patients with stroke and clinical indicators was obtained by logistic regression analysis and power analysis. We observed an independent association between fatigue severity and female sex (odds ratio [OR], 2.12; 95% confidence interval [CI], 1.14–3.94), depressive state (OR, 1.50; 95% CI, 1.01–1.73), and sleep disorders (OR, 1.58; 95% CI, 1.01–1.98). High levels of blood glucose, serum uric acid, and homocysteine and low levels of serum triiodothyronine were strongly associated with poor functional outcomes in patients with stroke. Further studies are needed to elucidate how specific structural lesions and anxiety symptoms are related to early PSF. [ABSTRACT FROM AUTHOR]

Attempts have been made to incorporate remote sensing techniques and in situ observations for enhanced water quality assessments. Estimations of nonoptical indicators sensitive to water environment changes, however, have not been fully studied, mainly due to complex nonlinear relationships between the observed values and surface reflectance. In this study, we applied a novel deep learning approach driven by a range of spectral properties to retrieve 6-year changes in water quality variables, i.e., Chl-a, BOD, TN, CODMn, NH3-N, and TP, on a monthly basis between 2013 and 2018 at Dongping Lake, an impounded lake located in the Yellow River in China. Band arithmetic was used to compute 26 predictors from Landsat 8 OLI imagery for model inputs. The results showed generally strong agreement between in situ and ConvLSTM-derived lake variables, generating R2 of 0.92, 0.88, 0.84, 0.80, 0.83, and 0.77 for TN, NH3-N, CODMn, Chl-a, TP, and BOD, which suggest good performance of the developed model. We then used statistical analysis to identify the spatial and temporal heterogeneity. The framework established in this study has applications in effective water quality monitoring and serves as an alarming tool for water-environment management in the complex inland lake waters. [ABSTRACT FROM AUTHOR]

Hepatic ischemia-reperfusion injury(HIRI) remains to be an unsolved risk factor that contributes to organ failure after liver surgery. Our clinical retrospective study showed that lower donor liver CX3-C chemokine receptor-1(CX3CR1) mRNA expression level were correlated with upregulated pro-resolved macrophage receptor MERTK, as well as promoted restoration efficiency of allograft injury in liver transplant. To further characterize roles of CX3CR1 in regulating resolution of HIRI, we employed murine liver partial warm ischemia-reperfusion model by Wt & Cx3cr1 −/− mice and the reperfusion time was prolonged from 6 h to 4–7 days. Kupffer cells(KCs) were depleted by clodronate liposome(CL) in advance to focus on infiltrating macrophages, and repopulation kinetics were determined by FACS, IF and RNA-Seq. CX3CR1 antagonist AZD8797 was injected i.p. to interrogate potential pharmacological therapeutic strategies. In vitro primary bone marrow macrophages(BMMs) culture by LXR agonist DMHCA, as well as molecular and functional studies, were undertaken to dissect roles of CX3CR1 in modulating macrophages cytobiological development and resolutive functions. We observed that deficiency or pharmacological inhibition of CX3CR1 facilitated HIRI resolution via promoted macrophages migration in CCR1/CCR5 manner, as well as enhanced MerTK-mediated efferocytosis. Our study demonstrated the critical roles of CX3CR1 in progression of HIRI and identified it as a potential therapeutic target in clinical liver transplantation. [Display omitted] • Low donor CX3CR1 expression is correlated with accelerated recovery after LT. • CX3CR1 deficiency promotes recovery of HIRI in CL-pretreated mice. • CX3CR1 deficiency enhances infiltrating macrophages efferocytosis by hepatic specific reprogramming. • Enhanced macrophages reprogramming and migration favours liver homeostasis. • Inhibition of CX3CR1 by AZD8797 promotes HIRI resolution. [ABSTRACT FROM AUTHOR]

The growing interest and clinical translation of alpha particle (α) therapies brings with it new challenges to assess target cell engagement and to monitor therapeutic effect. Noninvasive imaging has great potential to guide α-treatment and to harness the potential of these agents in the complex environment of disseminated disease. Poly(ADP) ribose polymerase 1 (PARP-1) is among the most abundantly expressed DNA repair enzymes with key roles in multiple repair pathways—such as those induced by irradiation. Here, we used a third-generation PARP1-specific radiotracer, [18F]-PARPZ, to delineate castrate resistant prostate cancer xenografts. Following treatment with the clinically applied [225Ac]-PSMA-617, positron emission tomography was performed and correlative autoradiography and histology acquired. [18F]-PARPZ was able to distinguish treated from control (saline) xenografts by increased uptake. Kinetic analysis of tracer accumulation also suggests that the localization of the agent to sites of increased PARP-1 expression is a consequence of DNA damage response. Together, these data support expanded investigation of [18F]-PARPZ to facilitate clinical translation in the ⍺-therapy space. [ABSTRACT FROM AUTHOR]

Efficient, accurate molecular characterization of genetically modified (GM) organisms is challenging, especially for those transgenic events transferred with genes/elements of recipient species. Herein, we decipher the comprehensive molecular characterization of one novel GM rice event G281 which was transferred with native promoters and an RNA interference (RNAi) expression cassette using paired-end whole genome sequencing (PE-WGS) and modified TranSeq approach. Our results show that transgenes integrate at rice chromosome 3 locus 16,439,674 included a 36 bp deletion of rice genomic DNA, and the whole integration contains two copies of the complete transfer DNA (T-DNA) in a head-to-head arrangement. No unintended insertion or backbone sequence of the transformed plasmid is observed at the whole genome level. Molecular characterization of the G281 event will assist risk assessment and application for a commercial license. In addition, we speculate that our approach could be further used for identifying the transgene integration of cisgenesis/intragenesis crops since both ends of T-DNA in G281 rice were from native gene or elements which is similar with that of cisgenesis/intrasgenesis. Our results from the in silico mimicking cisgenesis event confirm that the mimic rice Gt1 gene insertion and its flanking sequences are successfully identified, demonstrating the applicability of PE-WGS for molecular characterization of cisgenesis/intragenesis crops. Coupling paired-end whole-genome sequencing with droplet digital PCR enabled precise identification of a transgene insertion in the genetically modified rice event G281 on chromosome 3 and the potential for exploring the native gene integration. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is a prevalent neurodegenerative aging disorder that manifests as motor and non-motor symptoms, and its etiopathogenesis is influenced by non-coding RNAs (ncRNAs). Signal pathway and gene sequence studies have proposed that alteration of ncRNAs is relevant to the occurrence and development of PD. Furthermore, many studies on brain tissues and body fluids from patients with PD indicate that variations in ncRNAs and their target genes could trigger or exacerbate neurodegenerative pathogenesis and serve as potential non-invasive biomarkers of PD. Numerous ncRNAs have been considered regulators of apoptosis, α-syn misfolding and aggregation, mitochondrial dysfunction, autophagy, and neuroinflammation in PD etiology, and evidence is mounting for the determination of the role of competing endogenous RNA (ceRNA) mechanisms in disease development. In this review, we discuss the current knowledge regarding the regulation and function of ncRNAs as well as ceRNA networks in PD pathogenesis, focusing on microRNAs, long ncRNAs, and circular RNAs to increase the understanding of the disease and propose potential target identification and treatment in the early stages of PD. [ABSTRACT FROM AUTHOR]

Due to the forecasted fast increasing cellular traffic and the already highly congested licensed spectrum, it is critical to exploit and utilize the unlicensed spectrum resources for the fifth-generation (5G) and beyond networks. A challenging problem is the coexistence of 5G and other networks with fair, reliable, and efficient sharing of the unlicensed spectrum. In this paper, we propose a blockchain-enhanced distributed spectrum sharing scheme for coexisting multiple operators and multiple WiFi APs. We design a novel lightweight and efficient consensus mechanism, named Proof of Strategy (PoG). In this consensus mechanism, the problem of spectrum sharing is used as a consensus puzzle, and the part of the unlicensed spectrum is used as the ‘fee’ of miners. With such a design, the computing overhead of the consensus process is expected to be reduced significantly. We develop a non-cooperative game to analyze the behavior of the miners and obtain a symmetric Bayesian Nash equilibrium under the uniform distribution of mining cost estimation. It can be found mathematically and experimentally that the strategy of the winner tends to maximize the system revenue by sharing the unlicensed spectrum resource. Furthermore, to reduce the impact of heavy interactions on system throughput, the operation of WiFi APs in the proposed scheme can be adaptively switched between ‘contention mode’ and ‘blockchain mode’ according to the network traffic load. The dynamic behavior is constructed as an evolutionary game, and the existence and uniqueness of equilibrium points are proved by theoretical analysis. Simulations demonstrated the fairness and effectiveness of the proposed blockchain-based scheme and the mode switching method for distributed spectrum sharing by heterogeneous wireless networks. [ABSTRACT FROM AUTHOR]

Nowadays, the increasingly complex and changeable marine environment makes the signals received by the underwater sensing equipment not only contain the weak signals radiated by underwater targets but also accompanied by marine solid background noise, which leads to the degradation and distortion of underwater acoustic signals and the decline of underwater communication quality. Under the severe influence of ocean noise, the underwater acoustic sensing and acquisition system will have the problems of high SNR ratio threshold, minimal sensing bandwidth, and unable to sense the signal with unknown frequency effectively. The Lévy noise model has been selected to describe the marine noise environment and explain its scientificity in this paper. A parameter estimation method for Lévy noise is proposed. Under the condition of characteristic index α = 1.5 and noise intensity D = 0.1 of the Lévy noise model, the estimated mean values of parameters are 1.5026 and 1.1664. The estimated variances are 0.0034 and 0.0046, which proves the effectiveness and applicability of the estimation method. Then, an improved dual-coupled Duffing oscillator sensing system is proposed to sense the weak signals with unknown frequency under Lévy noise. Under the background of Lévy with characteristic index α = 1.5 , deflection parameter β = 0 and noise intensity D = 0.1 , the sensing error rate of our system with unknown frequency is 0.054 % , the lowest sensing signal amplitude is A = 0.010 , the lowest sensing SNR ratio is − 23.9254 dB, and the frequency of multi-frequency weak signals to be measured can be obtained. The estimation error of frequency sensing is 0.33 % . [ABSTRACT FROM AUTHOR]

Summary: Molecular characterization of genetically modified organisms (GMOs) yields basic information on exogenous DNA integration, including integration sites, entire inserted sequences and structures, flanking sequences and copy number, providing key data for biosafety assessment. However, there are few effective methods for deciphering transgene integration, especially for large DNA fragment integration with complex rearrangement, inversion and tandem repeats. Herein, we developed a universal Large Integrated DNA Fragments Enrichment strategy combined with PacBio Sequencing (LIFE‐Seq) for deciphering transgene integration in GMOs. Universal tilling DNA probes targeting transgenic elements and exogenous genes facilitate specific enrichment of large inserted DNA fragments associated with transgenes from plant genomes, followed by PacBio sequencing. LIFE‐Seq were evaluated using six GM events and four crop species. Target DNA fragments averaging ~6275 bp were enriched and sequenced, generating ~26 352 high fidelity reads for each sample. Transgene integration structures were determined with high repeatability and sensitivity. Compared with next‐generation whole‐genome sequencing, LIFE‐Seq achieved better data integrity and accuracy, greater universality and lower cost, especially for transgenic crops with complex inserted DNA structures. LIFE‐Seq could be applied in molecular characterization of transgenic crops and animals, and complex DNA structure analysis in genetics research. [ABSTRACT FROM AUTHOR]

Energy consumption has dramatically increased in buildings over the past decade. A synthetic urban building energy consumption dataset can be used to estimate energy demand and anthropogenic carbon emission, which overcomes the constraints of real-world datasets, including difficulties in the collection of energy uses from different sources, expense, and time. In this study, a 24-h building energy consumption dataset was designed and established in a hot and humid subtropical region, based on ENVI-met, Energyplus™ and Access software. The dataset considers 72 conditions from three aspects including six built-up local climate zones, seven building categories (five public and two residential buildings), and four widely-used air conditioning systems. A total of 17,400 building energy consumption data were collected. We analyzed the hourly variations of building energy consumption under different conditions, and the factors influencing the building energy consumption. Finally, based on the dataset, taking Tianhe District in Guangzhou as an example, we further explored the hourly spatio-temporal distribution patterns of building energy consumption and daily total building energy consumption distribution using ArcGIS software. This study provides a method for establishing an urban building energy consumption dataset from a local-scale view, which shows a new light on developing the National Building Energy Consumption Database response to global low-carbon action. [Display omitted] • Propose a bottom-up building energy consumption (BEC) accounting method • Establish a LCZ-based BEC dataset based on a series of coupling factors • Present spatio-temporal visualization maps of local-scale BEC • A LCZ-based BEC dataset contributes to design "smart energy network" • The established BEC dataset can be applied to guide smart urban planning [ABSTRACT FROM AUTHOR]

The Australian wildfires in 2019–2020 have brought suffering to the Australian people. It is essential to use models to help the Victorian government monitor and predict the occurrence and development of fires to the greatest extent possible under the principles of safety and economy to facilitate rapid response. Through the idea of K -means algorithm and greedy algorithm, we, respectively, analyzed cities and rural areas at different altitudes and combined the altitude with the obtained clusters; the analysis from the established model shows that, for cities, cluster areas with smaller clusters with an altitude of less than 1600 meters and areas with smaller clusters with an altitude of greater than or equal to 1800 meters are covered by an EOC; for areas with larger clusters less than or equal to 600 meters above the sea level and areas with larger clusters greater than or equal to 1000 meters above the sea level, we use two EOCs for coverage; for rural areas, all areas with smaller clusters are covered by one EOC, while for areas with larger clusters where the altitude is less than or equal to 1000 meters and the altitude is greater than or equal to 1600 meters, we use two EOCs for coverage; also, obtained through greedy algorithm analysis, one EOC corresponds to 14 SSA UAVs and 8 repeater UAVs, and two EOCs correspond to 12 repeater UAVs and 26 SSA UAVs. We have a reason to believe that, through our mathematical model and the leaps in drone technology, it will have a long-term and profound impact on Australia's wildfire control. [ABSTRACT FROM AUTHOR]

Rapid progress has been made to identify and study the causative agent leading to coronavirus disease 2019 (COVID‐19) but many questions including who is most susceptible and what determines severity remain unanswered. Angiotensin‐converting enzyme 2 (ACE2) is a key factor in the infection process of severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2). In this study, molecularly specific positron emission tomography imaging agents for targeting ACE2 are first developed, and these novel agents are evaluated in vitro, in preclinical model systems, and in a first‐in‐human translational ACE2 imaging of healthy volunteers and a SARS‐CoV‐2 recovered patient (NCT04422457). ACE2 expression levels in different organs in live subjects are quantitatively delineated and observable differences are measured in the patient recovered from COVID‐19. Surprising sites of uptake in the breast, reproductive system and very low uptake in pulmonary tissues are reported. This novel method can add a unique tool to facilitate SARS‐CoV‐2 related research and improve understanding of this enigmatic disease. Molecular imaging provides quantitative annotation of ACE2, the SARS‐CoV‐2 entry receptor, to noninvasively monitor organs impacted by the COVID‐19. [ABSTRACT FROM AUTHOR]

Rapid progress has been made to identify and study the causative agent leading to coronavirus disease 2019 (COVID‐19) but many questions including who is most susceptible and what determines severity remain unanswered. Angiotensin‐converting enzyme 2 (ACE2) is a key factor in the infection process of severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2). In this study, molecularly specific positron emission tomography imaging agents for targeting ACE2 are first developed, and these novel agents are evaluated in vitro, in preclinical model systems, and in a first‐in‐human translational ACE2 imaging of healthy volunteers and a SARS‐CoV‐2 recovered patient (NCT04422457). ACE2 expression levels in different organs in live subjects are quantitatively delineated and observable differences are measured in the patient recovered from COVID‐19. Surprising sites of uptake in the breast, reproductive system and very low uptake in pulmonary tissues are reported. This novel method can add a unique tool to facilitate SARS‐CoV‐2 related research and improve understanding of this enigmatic disease. Molecular imaging provides quantitative annotation of ACE2, the SARS‐CoV‐2 entry receptor, to noninvasively monitor organs impacted by the COVID‐19. [ABSTRACT FROM AUTHOR]

Remaining useful life (RUL) prediction is critical for health management of industrial equipment. It has been widely noted that degradation modeling is a core step for RUL prediction where the Brownian motion (BM)-based models attract much attention. However, the existing BM-based degradation models still have some impractical assumptions, where the increments of a BM are independent and stationary. To extend the application of the degradation models, a bifractional Brownian motion (biFBM)-based degradation model is developed in this article. The biFBM is a process with dependent and nonstationary increments, which includes the BM and fractional Brownian motion (FBM) as special cases. For the proposed degradation model, the estimation of parameters and degradation states as well as the prediction of RUL is further considered. To address the non-Markovian degradation processes, an improved particle filter is designed for degradation state estimation and RUL prediction. The proposed degradation model and RUL prediction method are validated by case studies of turbine engines and a blast furnace wall. [ABSTRACT FROM AUTHOR]

Background: To investigate the influence of different risk factors on central lymph node metastasis (CLNM) in the cervical region in patients with papillary thyroid carcinoma (PTC). Methods: This retrospective study included 2586 PTC patients. Potential risk factors were identified by univariate analysis, and the relationships between these factors and CLNM were ascertained by multivariable analysis. A scoring system was constructed, and the optimal cut-off value was determined. Results: On univariate analysis, sex, age, tumor diameter, multifocality, capsule invasion, vascular invasion, total number of lymph nodes in the central region, and serum thyroid peroxidase antibody (TPOAb) concentration were identified as potential risk factors for CLNM in the cervical region, whereas nerve invasion, thyroid-stimulating hormone concentration, and thyroglobulin antibody (TgAb) concentration were not. Multivariable analysis indicated that male sex, young age, large tumor diameter, multifocality, vascular invasion, a large number of central lymph nodes, and a low TPOAb concentration were significant risk factors. From these factors, a preoperative CLNM risk assessment scale was constructed for predicting CLNM in the cervical region for PTC patients. Conclusion: Male sex, young age, large tumor diameter, multifocality, vascular invasion, a large number of central lymph nodes, and a low TPOAb concentration were positively correlated with CLNM in the cervical region in PTC patients. The preoperative CLNM risk assessment scale based on these risk factors is expected to offer accurate preoperative assessment of central lymph node status in PTC patients. [ABSTRACT FROM AUTHOR]

Current advances of molecular-targeting therapies for hepatocellular carcinoma (HCC) have improved the overall survival significantly, whereas the results still remain unsatisfied. Recently, much attention has been focused on organelles, such as the mitochondria, to reveal novel strategies to control the cancers. The mitochondria are vital organelles which supply energy and maintain metabolism in most of the eukaryotic cells. They not only execute critical bioenergetic and biosynthetic functions but also regulate ROS homeostasis and apoptosis. Existing in a dynamic equilibrium state, mitochondria constantly undergo the fission and fusion processes in normal situation. Increasing evidences have showed that mitochondrial fission is highly related to the diseases and cancers. Distinctive works have proved the significant effects of mitochondrial fission on HCC behaviors and the crosstalks with other molecular pathways. Here, we provide an overview of the mitochondrial fission and the link with HCC, emphasizing on the underlying molecular pathways and several novel materials that modulate HCC behaviors. [ABSTRACT FROM AUTHOR]

To solve the problem brought from enormous policy documents and complex management in the social security domain, the article uses ontology as the way of representing and storing knowledge. The article first constructs the framework of ontology through manual work so that it can ensure the relative accuracy of the ontology structure. Then it achieves the automatic ontology expansion based on the inclusion relationship of property sets or operational object sets. The article uses a semi-automatic method that extracts hierarchical concepts and non-hierarchical concepts from domain thesaurus by using the method combining statistics with rules to construct the ontology. Besides constructing the ontology, the article proposes the concepts of concept phrase vector model and high frequency characteristics phrase vector model. The experiment result indicates that ontology semi-automatic construction process can help experts to construct the social security ontology effectively oriented on massive policy documents and is a considerable reference for the construction of ontology in other domains. [ABSTRACT FROM AUTHOR]

For some practical industrial systems or components, such as blast furnaces and Li-ion batteries, there are two important factors to model the degradation processes. One is the long-range dependence, which can reflect the non-Markovian nature of the degradation processes. The other factor is the existence of multiple modes, because the operating conditions and external environments inevitably change during the whole lifetime of these systems. In this paper, we first propose a fractional Brownian motion (FBM) based degradation model with long-range dependence and multiple modes, and then consider the prediction of remaining useful life. To identify the multiple modes in the degradation process, we propose a two-step method, including change-points detection and linear segments clustering. In each degradation mode, the degradation rate is assumed to be normally distributed. The means and variances of these distributions can be obtained by the maximum likelihood estimation. To describe the switching between different modes, the continuous-time Markov chain is applied, and its transition rate matrix can be estimated by the historical switching time. An approximation of the first passage time with a predefined threshold can be obtained by a weak convergence theorem and a time-space transformation. A numerical simulation and a practical case of a blast furnace wall are provided to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The magnetoelectric multiferroic materials with ferroelectric and magnetic orders have great attributed attention in the field of magnetoelectric memories and magnetic resonance devices. Here, we systematically investigated the optical and multiferroic properties of Fe-doped hybrid improper ferroelectricity Ca 3 Ti 2 O 7 prepared by sol-gel method. The distortion of TiO 6 octahedron changes with the content of oxygen vacancy introduced by Fe doping, thus realizing the adjustment of remnant ferroelectric polarization of the samples. The slight blue shift of the Raman band at 667 cm−1 reflected the introduces of oxygen vacancies by Fe doping. The optical bandgaps of the doped samples were reduced after doping, agreeing with the results of the first-principles calculations. With the introduction of Fe3+, the magnetism increases gradually. The first-principles calculation shows that magnetism origins from the Fe-3 d and their surrounding O-2 p orbitals. The Fe-doping Ca 3 Ti 2 O 7 materials realizing the introduction of magnetic properties while regulating its ferroelectric properties are expected to be applied in magnetoelectric memories, optoelectronic devices spintronics and magnetic response devices. [Display omitted] • The Fe-doped Ca 3 Ti 2 O 7 prepared with sol-gel possesses shows low coercivity field and large ferroelectric polarization. • The magnetism increases due to the introduces of Fe3+ in the doped samples, which is attributed to the spin splitting of Fe-3 d and their surrounding O atoms analyzed though first-principles calculations. • The slight blue shift of the Raman band upon Fe doping is attributed to the introduce oxygen vacancies, which also leads to a decrease of the bandgaps. • The O atom has the tendency to get more charge in Fe–O octahedral compared with that in Ti–O octahedral, leading to an enhanced electronegativity in doped Ca 3 Ti 2 O 7. [ABSTRACT FROM AUTHOR]

In this study the fuel retention and erosion of different reduced-activation ferritic martensitic (RAFM) steels exposed to deuterium (D) plasma were investigated. D plasma exposure was performed in a linear experimental plasma system (LEPS) with the incident ion energy between 30 and 180 eV per D, fluence from 1023 to 1025 D/m2 and sample temperature between 300 and 500 K. After D plasma exposure, erosion structure development of surface topography was observed, but no significant difference was seen among various RAFM steels within the examined conditions. W-enriched surface is formed for all investigated RAFM steels with little difference. RAFM steels exhibited similarities in D erosion and dependence on D plasma energy or fluence. Thermal desorption spectroscopy reveals in all steel samples only one broaden releasing peak from 450 to 800 K and total D inventory of 1018–1020 D/m2. Similar D retention behavior of five RAFM steels was found that it decreases with increasing incident fluence or ion energy. Moreover, different cutting treatment along rolling direction leads to different erosion structure and D releasing behaviors. [ABSTRACT FROM AUTHOR]

[Display omitted] • MXene-rGO aerogel greatly improves conductivity for sodium storage. • Na 3.5 MnTi(PO 4) 3 in situ grows on MXene-rGO with large specific surface area. • N 3.5 MTP@MXene-rGO exhibits high power density long cycle life over 5000 cycles. • N 3.5 MTP@MXene-rGO performs good specific capacity at low temperature of −30 °C. Sodium superionic conductor (NASICON) structured polyanionic materials have recently attracted great attention for robust crystal structures. However, inherent properties of NASICON presents poor electrical conductivity and low energy density. Herein, non-stoichiometric synthesized strategy is used for acquiring N 3.5 MTP, effectively suppressing voltage hysteresis. Besides, as-fabricated N 3.5 MTP grains in-situ grow on MXene-rGO aerogels by sol–gel synthesis approach obtaining N 3.5 MTP@MXene-rGO. MXene-rGO aerogel as an excellent conductive matrix can effectively avoid agglomeration of Na 3.5 MnTi(PO 4) 3 particles and alleviate volume change of the lattice during sodium ion intercalation/deintercalation. Moreover, cross-linked network of N 3.5 MTP@MXene-rGO provides fast electron transfer and ion transport rates. The above synergistic effect and contribution of pseudocapacitance make it an excellent discharge capacity of 189 mA h g−1 at 50 mA g−1 for N 3.5 MTP@MXene-rGO, long cycles of 5000 cycles, as well as 98 mA g−1 at −30 °C (50 mA g−1). Prospectively, this study provides an effective strategy for improving electrochemical performance of NASICON-type cathode for sodium batteries. [ABSTRACT FROM AUTHOR]

Background: Adolescent idiopathic scoliosis (AIS) is often accompanied by osteopenia and osteoporosis, which can cause serious complications. The aim of this study was to determine the specific bone mineral density (BMD) of each vertebral body in patients with AIS using biomechanical finite element modeling based on three-dimensional (3D) reconstruction. Methods: This retrospective study involved 56 patients with AIS. Computed tomography (CT) and radiography were performed. Spinal vertebrae were segmented from the spinal CT images of patients with AIS to reconstruct 3D vertebral models. The vertebral models were meshed into tetrahedral finite elements to assess the BMD. Results: The mean main curve Cobb angle was 88.6 ± 36.7°, and the mean kyphosis angle was 36.8 ± 31.5°. The mean BMD of the global spine was 0.83 ± 0.15 g/cm2. The highest BMD was measured on the concave side of the apex (0.98 ± 0.16 g/cm2). Apical vertebral BMD was negatively correlated with age and height (r = − 0.490, p = 0.009 and r = − 0.478, p = 0.043, respectively). There were no significant differences in BMD values between the concave and convex sides (p > 0.05). Conclusions: The 3D finite element modeling of BMD in patients with AIS is a reliable and accurate BMD measurement method. Using this method, the overall BMD of patients with AIS was shown to gradually decrease from the top to the bottom of the spine. Our findings provide valuable insights for surgical planning, choice of screw trajectories, and additional biomechanical analyzes using finite element models in the context of scoliosis. [ABSTRACT FROM AUTHOR]

The mixed linear model has been widely used in genome-wide association studies (GWAS), but its application to multi-locus GWAS analysis has not been explored and assessed. Here, we implemented a fast multi-locus random-SNP-effect EMMA (FASTmrEMMA) model for GWAS. The model is built on random single nucleotide polymorphism (SNP) effects and a new algorithm. This algorithm whitens the covariance matrix of the polygenic matrix K and environmental noise, and specifies the number of nonzero eigenvalues as one. The model first chooses all putative quantitative trait nucleotides (QTNs) with ≤ 0.005 P -values and then includes them in a multi-locus model for true QTN detection. Owing to the multi-locus feature, the Bonferroni correction is replaced by a less stringent selection criterion. Results from analyses of both simulated and real data showed that FASTmrEMMA is more powerful in QTN detection and model fit, has less bias in QTN effect estimation and requires a less running time than existing single- and multi-locus methods, such as empirical Bayes, settlement of mixed linear model under progressively exclusive relationship (SUPER), efficient mixed model association (EMMA), compressed MLM (CMLM) and enriched CMLM (ECMLM). FASTmrEMMA provides an alternative for multi-locus GWAS. [ABSTRACT FROM AUTHOR]

A prerequisite for the existing remaining useful life prediction methods based on stochastic processes is the assumption of independent increments. However, this is in sharp contrast to some practical systems including batteries and blast furnace walls, in which the degradation processes have the property of long-range dependence. Based on the fractional Brownian motion, we adopt a degradation process with long-range dependence to predict the remaining useful life of the above systems. Because the degradation process with long-range dependence is neither a Markovian process nor a semimartingale, the exact analytical first passage time is difficult to derive directly. To address this problem, a weak convergence theorem is first adopted to approximately transform a fractional Brownian motion-based degradation process into a Brownian motion-based one with a time-varying coefficient. Then, with a space-time transformation, the first passage time of the degradation process with long-range dependence can be obtained in a closed form. Unknown parameters in the degradation model can be identified using discrete dyadic wavelet transform and maximum likelihood estimation. Numerical simulations and a practical example of a blast furnace wall are given to verify the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

In the present work, The L1 2 -strengthened CoCrFeNiTi 0.2 (at.%) high-entropy alloy (HEA) exhibit excellent tensile mechanical properties both at room temperature (293 K) and liquid nitrogen temperature (77 K). Especially at 77 K, the yield strength and ultimate tensile strength are about 900 MPa and 1500 MPa, respectively, and the elongation is markedly increased to 50%, realizing the most exceptional strength-plasticity synergy. Dislocation slips dominate at 293 K, whlie at 77 K, stacking faults assist plastic deformation. This strengthening strategy of coherent L1 2 precipitates provides the basic guidance for the development of high-performance alloys. • An excellent strength-plasticity synergy achieved in the L1 2 -strengthened high-entropy alloy both at room and liquid nitrogen temperatures. • The origins of the macroscopic mechanical behaviors at different temperatures are analyzed and discussed. Dislocation slips dominate at 293 K, whlie at 77 K, stacking faults assist plastic deformation. • The reason why nano scale precipitates inhibit the formation of twins is explained. [ABSTRACT FROM AUTHOR]

Phosphatase and tensin homolog (PTEN) loss tightly correlates with prostate cancer (PCa) progression and metastasis. Inactivation of PTEN leads to abnormal activation of PI3K/AKT pathway. However, results from clinical trials with AKT inhibitors in PCa have been largely disappointing. Identification of novel regulators of PTEN in PTEN-dysfunctional PCa is urgently needed. Here we demonstrated that the expression level of PTEN is inversely correlated with the signature score of unfolded protein response (UPR) in PCa. Importantly, PTEN suppresses the activity of ATF6α, via interacting to de-phosphorylate ATF6α and consequently inhibiting its nuclear translocation. Conversely, ATF6α promotes the ubiquitination and degradation of PTEN by inducing CHIP expression. Thus, ATF6α and PTEN forms a negative feedback loop during PCa progression. Combination of ATF6α inhibitor with AKT inhibitor suppresses tumor cell proliferation and xenograft growth. Importantly, this study highlighted ATF6α as a therapeutic vulnerability in PTEN dysfunctional PCa. [ABSTRACT FROM AUTHOR]

It is now common knowledge that many water resources stresses relate to access to water within a basin. Yi River Basin, a typical river basin characterized by intensive agricultural processes, significant population growth, and water management, has been undergoing grave water problems. In this paper, the long-term trend of precipitation and streamflow in Yi River Basin, from 1964 to 2010, was investigated via Mann-Kendall test. The change point occurred in the year 1965 dividing the long-term series into two periods. Climate elasticity method and linear regression method were implemented to quantify the impact of precipitation and human activities on runoff and presented basically consistent results of the percentage change in an annual runoff for the postchange period. The results reveal that the decline of annual runoff in postchange period is mainly attributed to precipitation variability of 53.66–58.25% and human activities of 46.34–41.74%, as estimated by climate elasticity method and linear regression method, respectively. This study detected the changes in the precipitation-streamflow relationship and investigated the possible causes in the Yi River, which will be helpful for providing a reference for the management of regional water resources. [ABSTRACT FROM AUTHOR]

The potential risk caused by the leakage of toxic and hazardous substances during air pollution accidents poses a great threat to local environmental safety, human heath, and even property security. Uncertainties and causalities are important components that should not be ignored in risk assessment. Compared with traditional non-probabilistic methods, Bayesian networks (BNs) are well suited to solving problems with high complexity and uncertainties. To utilize these advantages, a BN-based approach, coupled with diffusion simulation of risk substances, was proposed to estimate the risk of air pollution accidents in a probabilistic way at the local scale. This method was applied to analyze the risk levels of 24 risk sources and 24 risk subregions in Daya Bay, a national economic and technological development zone with a large petrochemical industry in Huizhou, Guangdong province. The results indicated that the Daya Bay area suffered a relatively low risk of accidental air pollution. Only five risk sources (20.8%) and two risk subregions (8.3%) were found to have high danger or risk. Ammonia, styrene, and sulfur dioxide were the most threatening substances in order. Acute exposure was the most sensitive factor, and made the highest contribution to risk level. This research provides an effective approach that can be used to characterize the air pollution accident risk quantitatively, probabilistically, and graphically. Probabilistic risk assessment can provide substantial support to local risk prevention, control, and emergency response for accidental air pollution, as well as to future risk management and policy decisions. [Display omitted] • A BN-based formal probabilistic approach is proposed for accidental air pollution risk analysis at the local scale. • Uncertainties and causalities in risk assessment are well expressed. • Dispersion models are introduced to enhance quantitative exposure estimation. • Daya Bay suffers a relatively low risk of accidental air pollution, acute exposure is the key driver of the risk level. • The results provide more detailed support to local accidental air pollution risk management. [ABSTRACT FROM AUTHOR]

In this paper, the calibration approach is revisited in order to allow new calibration weights that are subject to the restriction of multiple calibration equations on a vector of ratios, means and proportions. The classical approach is extended in such a way that the calibration equations are not based on a vector of totals, but on a vector of other nonlinear parameters. We stated some properties of the resulting estimators and carry out some empirical simulations in order to asses the performance of this approach. We found that this methodology is suitable for some practical situations like vote intention estimation, estimation of labor force, and retrospective stud- ies. The methodology is applied in the context of the Presidential elections held in Colombia in 2014 for which we estimated the vote intention in the second round using information from an election poll, taking the results from the first round as auxiliary information [ABSTRACT FROM AUTHOR]

This paper considers the modeling of the threshold autoregressive (TAR) process, which is driven by a noise process that follows a Student's t -dis- tribution. The analysis is done in the presence of missing data in both the threshold process f Z t g and the interest process f X t g . We develop a three-stage procedure based on the Gibbs sampler in order to identify and estimate the model. Additionally, the estimation of the missing data and the forecasting procedure are provided. The proposed methodology is illustrated with simulated and real-life data. [ABSTRACT FROM AUTHOR]

Magnetic-liquid double-suspension bearing (MLDSB) is composed of an electromagnetic supporting system and a hydrostatic supporting system. Due to its greater supporting capacity and stiffness, it is appropriate for middle-speed applications, overloading, and frequent starting. However, because it contains two sets of systems, its structure and rotor support system are more complex. It contains strong nonlinear links. When the parameters of the system change, the bearing rotor may feature Hopf bifurcation, resulting in system flutter and reducing the operational stability of the magnetic fluid double-suspension bearing rotor, which has become one of the key problems restricting its development and application. As key parameters of MLDSB, the coil current and oil film thickness exert a major impact on Hopf bifurcation. Therefore, the mathematical model of MLDSB is established in this paper, and the border and direction of Hopf bifurcation, period, and amplitude of limit cycle are analyzed. The calculation, simulation, and experimental results show that when the coil current and oil film thickness of the bearing system are greater than the boundary value of the Hopf bifurcation, Hopf bifurcation will occur, resulting in the vibration of the bearing rotor and affecting the stability of the system. In addition, when analyzing the combined effects of coil current and oil film thickness on the Hopf bifurcation of the system, it was found that the boundary value of Hopf bifurcation in the system is reduced compared with when it is are affected solely due to the coupling of the two parameters. The period, amplitude and vibration speed of limit cycle increase with increases in the coil current and oil film thickness. Hopf bifurcation experiment was conducted on MLDSB testing system. The results show that Hopf bifurcation does not occur when i0 < 0.5 A, the bearing rotor operates stably in the balanced position, i0 > 1.0 A, Hopf bifurcation occurs in the system, and the bearing rotor vibrates with equal amplitude, which reduces the stability of operation. The research in this paper can provide a theoretical reference for the Hopf bifurcation analysis of MLDSB. [ABSTRACT FROM AUTHOR]

Magnetic-Liquid Double Suspension Bearing (MLDSB) is composed of an electromagnetic supporting and a hydrostatic supporting system. Due to greater supporting capacity and static stiffness, it is appropriate for occasions of middle speed, overloading, and frequent starting. Because of the complicated structure of the supporting system, the probability and degree of static bifurcation of MLDSB can be increased by the coupling of hydrostatic force and electromagnetism force, and then the supporting capacity and operation stability are reduced. As the key part of MLDSB, the controller makes an important impact on its supporting capacity, operation stability, and reliability. Firstly, the mathematical model of MLDSB is established in the paper. Secondly, the static bifurcation point of MLDSB is determined, and the influence of parameters of the controller on singular point characteristics is analyzed. Finally, the influence of parameters of the controller on phase trajectories and basin of attraction is analyzed. The result showed that the pitchfork bifurcation will occur as proportional feedback coefficient Kp increases, and the static bifurcation point is Kp = −60.55. When Kp < −60.55, the supporting system only has one stable node (0, 0). When Kp > −60.55, the supporting system has one unstable saddle (0, 0) and two stable non-null focuses or nodes. The shape of the basin of attraction changed greatly as Kp increases from −60.55 to 30, while the outline of the basin of attraction is basically fixed as Kp increases from 30 to 80. Differential feedback coefficient Kd has no effect on the static bifurcation of MLDSB. The rotor phase trajectory obtained from theoretical simulation and experimental tests are basically consistent, and the error is due to the leakage and damping effect of the hydrostatic system within the allowable range of the engineering. The research in the paper can provide theoretical reference for static bifurcation analysis of MLDSB. [ABSTRACT FROM AUTHOR]

Researchers have made advances in reducing the metabolic rate of both walking and running by modulating mono-articular energy with exoskeletons. However, how to modulate multiarticular energy with exoskeletons to improve the energy economy of both walking and running is still a challenging problem, due to the lack of understanding of energy transfer among human lower-limb joints. Based on the study of the energy recycling and energy transfer function of biarticular muscles, we proposed a hip–knee unpowered exoskeleton that emulates and reinforces the function of the hamstrings and rectus femoris in different gait phases. The biarticular exo-tendon of the exoskeleton assists hamstrings to recycle the kinetic energy of the leg swing while providing hip extension torque in the swing phase. In the following stance phase, the exo-tendon releases the stored energy to assist the co-contraction of gluteus maximus and rectus femoris for both hip extension and knee extension, thus realizing the phased modulation of hip and knee joint energy. The metabolic rate of both walking (1.5 m/s) and running (2.5 m/s) can be reduced by 6.2% and 4.0% with the multiarticular energy modulation of a hip–knee unpowered exoskeleton, compared to that of walking and running without an exoskeleton. The bio-inspired design method of this study may inspire people to develop devices that assist multiple gaits in the future. [ABSTRACT FROM AUTHOR]

Targeting neuroendocrine tumors expressing somatostatin receptor subtypes (sst) with radiolabeled somatostatin agonists is an established diagnostic and therapeutic approach in oncology. While agonists readily internalize into tumor cells, permitting accumulation of radioactivity, radiolabeled antagonists do not, and they have not been considered for tumor targeting. The macrocyclic chelator 1,4,7,10-tetraazacyclododecane-l,4,7,10-tetraacetic acid (DOTA) was coupled to two potent somatostatin receptor-selective peptide antagonists [NH2-CO-c(DCys-Phe-Tyr-DAgl8(Me,2-naphthoyl)-Lys-Thr-Phe-Cys)-OH (sst3-ODN-8) and a sst2-selective antagonist (sst2-ANT)], for labeling with 111/natIn. 111/natIn-DOTA-sst3-ODN-8 and 111/natIn-DOTA-[4-NO2-Phe-c(DCys-Tyr-DTrp-Lys-Thr-Cys)-DTyr-N H2] (111/natIn-DOTA-sst2-ANT) showed high sst3- and sst2-binding affinity, respectively. They did not trigger sst3 or sst2 internalization but prevented agonist-stimulated internalization. 111In-DOTA-sst3-ODN-8 and 111In-DOTA-sst2-ANT were injected intravenously into mice bearing sst3- and sst2-expressing tumors, and their biodistribution was monitored. In the sst3-expressing tumors, strong accumulation of 111In-DOTA-sst3-ODN-8 was observed, peaking at I h with 60% injected radioactivity per gram of tissue and remaining at a high level for >72 h. Excess of sst3-ODN-8 blocked uptake. As a control, the potent agonist 111In-DOTA-[1-Nal³]-octreotide, with strong sst3-binding and internalization properties showed a much lower and shorter-lasting uptake in sst3-expressing tumors. Similarly, 111In-DOTA-sst2-ANT was injected into mice bearing sst2-expressing tumors. Tumor uptake was considerably higher than with the highly potent sst2-selective agonist 111In-diethylenetriaminepentaacetic acid-[Tyr³,Thr8]-octreotide (111In-DTPA-TATE). Scatchard plots showed that antagonists labeled many more sites than agonists. Somatostatin antagonist radiotracers therefore are preferable over agonists for the in vivo targeting of sst3- or sst2-expressing tumors. Antagonist radioligands for other peptide receptors need to be evaluated in nuclear oncology as a result of this paradigm shift. [ABSTRACT FROM AUTHOR]

Cold-formed steel (CFS) structures constructed by screw connections are commonly used in low-rise or mid-rise dwellings. Being a critical role affecting the strength and robustness of the structure, the configuration of joist-to-stud joints should be emphasized. However, the design method given by the existing specifications is incapable of covering screwed CFS joint with complex configuration. Therefore, further investigations are required for revealing the resistance and failure behaviour of CFS joist-to-stud screw joint under varying load modes. In this paper, laboratory tests of screw connections were conducted with the loading cases involving shear, tension, and combined tension and shear. This study concerns the behaviour of each connection in the elastic, plastic and failure stages. Finite element method (FEM) based on bushing connector elements was developed to simulate the performance of the screw connections in the physical experiment. Modelling details are given and a close correlation can be noticed when comparing numerical results against experimental outcomes. Moreover, a series of empirical design equations are proposed to predict the stiffness and resistance of the CFS joints. [Display omitted] • Investigation is conducted for revealing the resistance and failure mode of CFS joist-to-stud joint under varying load modes. • Tests of screw connections are conducted with the loading cases involving shear, tension, and combined tension and shear. • Numerical models based on bushing connector elements are presented to simulate the performance of the screw connections. • A series of empirical design equations are proposed to predict the stiffness and resistance of the CFS joints. [ABSTRACT FROM AUTHOR]

The blast furnace reactor has a large volume, and smelting occurs at high temperatures and high-pressure environments. The blast furnace reactor has a large volume, and smelting occurs at high temperatures and high-pressure environments. Considering the small samples of fault data and non-stationarity of the production process with a considerable time lag, it is difficult to diagnose and eliminate the faults timely. This paper proposes for the first time a data and knowledge collaborative-driven framework to identify fault and perform self-healing control. Following the adaptive two-scale sequence division method, the prior knowledge matrix refined K2 algorithm is used to construct Bayesian networks to model the control process. When a new abnormal condition arises, the most similar historical sequence will be found, and inference on the corresponding Bayesian network can lead to fault identification results and self-healing control action. The proposed framework has achieved satisfactory results in simulation experiments and real data experiments. In the simulation data, the Bayesian network (BN) modeling achieved an accuracy of 98.75%, and the time required for structure learning of the BN was reduced by over 75.69%. In real data, the accuracy of identifying blast furnace faults reached 97.1%, and the results of self-healing control reasoning surpassed those of traditional BN reasoning methods in terms of correctness, order, completeness, and necessity. • A self-healing control framework for blast furnace is proposed. • Introducing prior knowledge into industry can efficiently benefit process modeling. • Put forward an adaptive sequence division method for non-stationary data. • The method is suitable for non-stationary and high safety requirements situations. [ABSTRACT FROM AUTHOR]

Background: Endocrine resistance driven by sustained activation of androgen receptor (AR) signaling pathway in advanced prostate cancer (PCa) is fatal. Characterization of mechanisms underlying aberrant AR pathway activation to search for potential therapeutic strategy is particularly important. Rac GTPase-activating protein 1 (RACGAP1) is one of the specific GTPase-activating proteins. As a novel tumor proto-oncogene, overexpression of RACGAP1 was related to the occurrence of various tumors. Methods: Bioinformatics methods were used to analyze the relationship of expression level between RACGAP1 and AR as well as AR pathway activation. qRT-PCR and western blotting assays were performed to assess the expression of AR/AR-V7 and RACGAP1 in PCa cells. Immunoprecipitation and immunofluorescence experiments were conducted to detect the interaction and co-localization between RACGAP1 and AR/AR-V7. Gain- and loss-of-function analyses were conducted to investigate the biological roles of RACGAP1 in PCa cells, using MTS and colony formation assays. In vivo experiments were conducted to evaluate the effect of RACGAP1 inhibition on the tumor growth. Results: RACGAP1 was a gene activated by AR, which was markedly upregulated in PCa patients with CRPC and enzalutamide resistance. AR transcriptionally activated RACGAP1 expression by binding to its promoter region. Reciprocally, nuclear RACGAP1 bound to the N-terminal domain (NTD) of both AR and AR-V7, blocking their interaction with the E3 ubiquitin ligase MDM2. Consequently, this prevented the degradation of AR/AR-V7 in a ubiquitin-proteasome-dependent pathway. Notably, the positive feedback loop between RACGAP1 and AR/AR-V7 contributed to endocrine therapy resistance of CRPC. Combination of enzalutamide and in vivo cholesterol-conjugated RIG-I siRNA drugs targeting RACGAP1 induced potent inhibition of xenograft tumor growth of PCa. Conclusion: In summary, our results reveal that reciprocal regulation between RACGAP1 and AR/AR-V7 contributes to the endocrine resistance in PCa. These findings highlight the therapeutic potential of combined RACGAP1 inhibition and enzalutamide in treatment of advanced PCa. [ABSTRACT FROM AUTHOR]

Simple Summary: Protozoa are the most abundant phagotrophic group in the biosphere and play an important ecological role in aquatic ecosystems. However, the effects of environmental stressors such as temperature changes, eutrophication, and pesticide pollution, on the protozoan communities in fresh waters remain poorly understood. The results of our study show that warming and eutrophication considerably promote an increase in protozoan biomass, and the combination of warming and pesticides can remarkably reduce the abundance, biomass and diversity of protozoa. Warming, eutrophication, and pesticide pollution affect protozoan diversity, community structure, and functional groups, either independently or interactively. To explore the impacts of multiple environmental stressors on animal communities in aquatic ecosystems, we selected protozoa—a highly sensitive group of organisms—to assess the effect of environmental change. To conduct this simulation we conducted a three-factor, outdoor, mesocosm experiment from March to November 2021. Changes in the community structure and functional group composition of protozoan communities under the separate and combined effects of these three environmental stressors were investigated by warming and the addition of nitrogen, phosphorus, and pesticides. The results were as follows: (1) Both eutrophication and pesticides had a considerable promotional effect on the abundance and biomass of protozoa; the effect of warming was not considerable. When warming was combined with eutrophication and pesticides, there was a synergistic effect and antagonistic effect, respectively. (2) Eutrophication promoted α diversity of protozoa and affected their species richness and dominant species composition; the combination of warming and pesticides remarkably reduced the α diversity of protozoa. (3) Warming, eutrophication, and pesticides were important factors affecting the functional groups of protozoa. Interaction among different environmental factors could complicate changes in the aquatic ecological environment and its protozoan communities. Indeed, in the context of climate change, it might be more difficult to predict future trends in the protozoan community. Therefore, our results provide a scientific basis for the protection and restoration of shallow lake ecosystems; they also offer valuable insights in predicting changes in shallow lakes. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM) is a devastating brain cancer for which new effective therapies are urgently needed. GBM, after an initial response to current treatment regimens, develops therapeutic resistance, leading to rapid patient demise. Cancer cells exhibit an inherent elevation of endoplasmic reticulum (ER) stress due to uncontrolled growth and an unfavorable microenvironment, including hypoxia and nutrient deprivation. Cancer cells utilize the unfolded protein response (UPR) to maintain ER homeostasis, and failure of this response promotes cell death. In this study, as integrins are upregulated in cancer, we have evaluated the therapeutic potential of individually targeting all αβ1 integrin subunits using RNA interference. We found that GBM cells are uniquely susceptible to silencing of integrin α3. Knockdown of α3-induced proapoptotic markers such as PARP cleavage and caspase 3 and 8 activation. Remarkably, we discovered a non-canonical function for α3 in mediating the maturation of integrin β1. In its absence, generation of full length β1 was reduced, immature β1 accumulated, and the cells underwent elevated ER stress with upregulation of death receptor 5 (DR5) expression. Targeting α3 sensitized TRAIL-resistant GBM cancer cells to TRAIL-mediated apoptosis and led to growth inhibition. Our findings offer key new insights into integrin α3's role in GBM survival via the regulation of ER homeostasis and its value as a therapeutic target. [ABSTRACT FROM AUTHOR]

Drought is a major natural disaster that seriously affects agricultural production, especially for winter wheat in boreal China. As functional proteins, the functions and mechanisms of glyceraldehyde-3-phosphate dehydrogenase in cytoplasm (GAPCs) have remained little investigated in wheat subjected to adverse environmental conditions. In this study, we cloned and characterized a GAPC isoform TaGAPC2 in wheat. Over-expression of TaGApC2-6D in Arabidopsis led to enhanced root length, reduced reactive oxygen species (ROS) production, and elevated drought tolerance. In addition, the dual-luciferase assays showed that TaWRKY28/33/40/47 could positively regulate the expression of TaGApC2-6A and TaGApC2-6D. Further results of the yeast two-hybrid system and bimolecular fluorescence complementation assay (BiFC) demonstrate that TaPLDδ, an enzyme producing phosphatidic acid (PA), could interact with TaGAPC2-6D in plants. These results demonstrate that TaGAPC2 regulated by TaWRKY28/33/40/47 plays a crucial role in drought tolerance, which may influence the drought stress conditions via interaction with TaPLDδ. In conclusion, our results establish a new positive regulation mechanism of TaGAPC2 that helps wheat fine-tune its drought response. [ABSTRACT FROM AUTHOR]

Air pollution problems have a severe effect on the natural environment and public health. The application of machine learning to air pollutant data can result in a better understanding of environmental quality. Of these methods, the deep learning method has proven to be a very efficient and accurate method to forecast complex air quality data. This paper proposes a deep learning model based on an auto-encoder and bidirectional long short-term memory (Bi-LSTM) to forecast PM 2.5 concentrations to reveal the correlation between PM 2.5 and multiple climate variables. The model comprises several aspects, including data preprocessing, auto-encoder layer, and Bi-LSTM layer. The performance of the proposed model was verified based on a real-world air pollution dataset, and the results indicated this model can improve the prediction accuracy in an experimental scenario. • The deep learning neural network is introduced in constructing prediction model for PM2.5 concentration. • The proposed model is based on combining auto-encoder with Bi-LSTM neural networks, namely AE-Bi-LSTM model. • The Auto-encoder layer of the proposed model aims to extract the internal features of pollution data. • The Bi-LSTM layer of the proposed model aims to predict the PM2.5 concentration as a time series problem. [ABSTRACT FROM AUTHOR]