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Abstract In this paper we are concerned with an inverse problem with Robin boundary conditions, which states that, when the potential on [ 0 , 1 / 2 ] $[0,1/2]$ and the coefficient at the left end point are known a priori, a full spectrum uniquely determines its potential on the whole interval and the coefficient at the right end point. We shall give a new method for reconstructing the potential for this problem in terms of the Mittag-Leffler decomposition of entire functions associated with this problem. The new reconstructing method also deduces a necessary and sufficient condition for the existence issue.

A knowledge and data-synergized intelligent computation architecture for materials was proposed within the data science paradigm. As a vital operation, two digital ensemble descriptors implying chemical composition and structural trend for crystals were created using the features contained in the Periodic Table of elements without a priori assumption, which affords causal emergence and regulation principles for the mechanical response of covalent and ionic solids. In addition to a linear correlation among structural state/mechanical response parameters, causal analytic relations in an exponential form between structural and thermodynamic state/mechanical response parameters and a digital ensemble descriptor were unveiled through least squares regression, in which the coefficients are classified in accordance with symmetry principles on the atom and lattice. Thereafter, the underlying physicochemical mechanisms of chemical pressure and chemical bonding are found responsible for the mechanical responses of bulk modulus and hardness of solids. At last, a physical prediction model was established for crystalline solids and demonstrated the feasibility of the predictive design of novel superhard materials. It is believed that by constructing suitable digital ensemble descriptors, this intelligent computation architecture and consequent physical prediction models on the basis of causal analytic relations are able to generalize by depicting crystalline solids with covalent and ionic bonds in other crystallographic structures.

An electric wheel hybrid power system is designed for driving a large single-aisle passenger aircraft during the take-off and ground taxi phases, which consists of an APU, an energy storage system, and a motor. In the taxi phase, the electric wheel hybrid power system works alone, and the turbofan engine does not work, reducing fuel consumption and pollution emissions. During the take-off rolling phase, the electric wheel hybrid power system and turbofan engine work together to reduce the thrust requirement of the turbofan engine. This article establishes an aircraft kinematic model, hybrid power system model, and a mechanical wheel model. The feasibility of the collaborative work of the electric wheels and the turbofan engines is verified by simulations. By utilizing the established hybrid system of electric motor wheels, the fuel consumption can be reduced, and the emissions of CO, HC, and NOX can also be diminished to varying degrees. The input of motor power leads to lower turbine inlet temperature, thereby enhancing the turbofan engine’s service life by approximately 4.3% and saving operational costs.

PurposeThe purpose of this study is to assess the safety of progestin-primed ovarian stimulation (PPOS) protocol regarding the neonatal outcomes and congenital malformations in babies born after in vitro fertilization (IVF) and frozen embryo transfer (FET).MethodsIn this large retrospective cohort study, a total of 16,493 infants born between 1 September 2013 and 31 July 2021 from IVF and FET cycles after treatment with either PPOS (n = 15,245) or gonadotropin-releasing hormone antagonist (GnRH-ant) (n = 1,248) were finally enrolled. The primary outcome measure was the incidence of congenital malformations. The secondary outcome measures were rates of low birth weight (LBW), very low birth weight (VLBW), preterm birth (PTB), very preterm birth (VPTB), and early neonatal death.ResultsBirth characteristics for both singletons and twins regarding the sex of infants, gestational age, birth weight, and birth length were comparable between the PPOS group and the GnRH-ant group. Rates of LBW, VLBW, PTB, VPTB, and early neonatal death were also similar. The reanalysis using propensity score matching (PSM) and multivariable logistic regression indicated that the PPOS protocol could not increase the risk of adverse neonatal outcomes compared with the GnRH-ant protocol. Furthermore, no significant difference was observed in the overall incidence of congenital malformations in live-born babies. After PSM and controlling for all confounders, the results remained insignificant with an adjusted odds ratio of 0.66 [95% confidence interval (CI) 0.32–1.34] and 2.43 [95% CI 0.97–6.06], respectively, for singletons and twins.ConclusionsOur study suggests that compared with GnRH-ant treatment for IVF, the PPOS protocol could not produce a negative effect on the newborn population in terms of neonatal outcomes and congenital malformations.

Optical fiber sensors working at the dispersion turning point (DTP) have served as promising candidates for various sensing applications due to their ultrahigh sensitivity. In this review, recently developed ultrasensitive fiber sensors at the DTP, including fiber couplers, fiber gratings, and interferometers, are comprehensively analyzed. These three schemes are outlined in terms of operation principles, device structures, and sensing applications. We focus on sensitivity enhancement and optical transducers, we evaluate each sensing scheme based on the DTP principle, and we discuss relevant challenges, aiming to provide some clues for future research.

A steel-wire wound reinforced thermoplastic pipe (SWW-RTP) has been widely utilized in many industrial areas, and a soil landslide is an inevitable hazardous extreme condition for the SWW-RTP as it is usually buried underground. It is imperative to study the mechanical failure behavior and the failure criterion of the SWW-RTP under the combination of internal pressure and soil landslide conditions, and this paper is the first study to investigate the topic. In this paper, groups of stress–strain curves of high-density polyethylene (HDPE) and steel wires were obtained by uniaxial tensile tests at different strain rates, with the help of a Digital Image Correlation device (DIC). A rate-dependent constitutive model was employed to represent the mechanical behavior of the HDPE and to help deduce the stress–strain curve of the HDPE under the required strain rate, estimated from the static simplification of the dynamic soil landslide. Afterwards, a finite element model of the SWW-RTP, embedded in a cubic of soil, was established with the software ABAQUS. The SWW-RTP model was composed of HDPE solid elements, embedded with steel-wire truss elements, and the soil was characterized with the extended Drucker–Prager model. A quartic polynomial displacement distribution was applied to the soil model to represent the soil landslide. Then, the mechanical response of the SWW-RTP was analyzed. It was found that the failure criterion of the HDPE yield was more suitable for the pipe subjected to internal pressure and soil landslide conditions, instead of the steel-wire strength failure criterion always used in traditional research on the SWW-RTP. Further, the influence of landslide width, internal pressure and steel-wire number were discussed. The larger the width of the landslide area, the gentler the deformation of the pipeline; this resulted in an increase in the maximum landslide and a decrease in the maximum curvature with the width of the landslide area. The relatively high internal pressure was beneficial to the safety of the SWW-RTP under landslide, because the internal pressure could increase the stiffness of the pipeline. The number of steel wires had a limited influence on the maximum landslide required for the SWW-RTP’s failure. This work can be useful for the design and safe assessment of the SWW-RTP under internal pressure and soil landslide conditions.

To study the swelling characteristics of bentonite eroded by alkaline solutions, swelling deformation (δs) tests on the bentonite subjected to immersion conditions of NaOH and KOH solutions were conducted. It is found that the δs of bentonite decreases with the increase in the concentration of alkaline solution. The swelling deformation δs of bentonite eroded by NaOH solution exceeds than that in the KOH solution for the same level of concentration. Moreover, by performing XRD tests, it is revealed that the reduced swelling performance of bentonite in alkaline solutions is mainly attributed to the dissolution of the swelling mineral, i.e., montmorillonite (Mt.). The higher the concentration of alkali solution, the stronger the dissolution of Mt., thus leading to more significant attenuation of the swelling properties. Besides, the K+ exhibits low hydration energies, which tends to fit into the silicon-oxygen tetrahedral cavity of smectite, forming a stronger K-linkage which leads to closely spaced crystal layers. The e-pe fractal relation can be calculated using the δs of bentonite eroded by alkaline solution. The e-pe fitting relation of the experimental data depicts that the dissolution of Mt. minerals in alkaline solution reduces the swelling coefficient κ, however, it increases the surface fractal dimension (Ds).

Cervical cancer is one of the most common and deadliest cancers among women. Despite that, this cancer is entirely treatable if it is detected at a precancerous stage. Pap smear test is the most extensively performed screening method for early detection of cervical cancer. However, this hand-operated screening approach suffers from a high false-positive result because of human errors. To improve the accuracy and manual screening practice, computer-aided diagnosis methods based on deep learning is developed widely to segment and classify the cervical cytology images automatically. In this survey, we provide a comprehensive study of the state of the art approaches based on deep learning for the analysis of cervical cytology images. Firstly, we introduce deep learning and its simplified architectures that have been used in this field. Secondly, we discuss the publicly available cervical cytopathology datasets and evaluation metrics for segmentation and classification tasks. Then, a thorough review of the recent development of deep learning for the segmentation and classification of cervical cytology images is presented. Finally, we investigate the existing methodology along with the most suitable techniques for the analysis of pap smear cells.

In this paper, a novel multilayer hidden conditional random fields (MHCRFs)-based cervical histopathology image classification (CHIC) model is proposed to classify well, moderate and poorly differentiation stages of cervical cancer using a weakly supervised learning strategy. First, the color, texture, and deep learning features are extracted to represent the histopathological image patches. Then, based on the extracted features, artificial neural network, support vector machine, and random forest classifiers are designed to calculate the patch-level classification probabilities. Third, effective classifiers are selected to generate unary and binary potentials. At last, using the generated potentials, the final image-level classification results are predicted by our MHCRF model, and an overall accuracy around 77.32% is obtained on six practical cervical histopathological image datasets with more than 600 immunohistochemical (IHC) stained samples. Among the six test accuracies, the highest reaches 88%. Furthermore, we also test our MHCRF method with a gastric hematoxylin-eosin (HE) stained histopathological image dataset including 200 images for an extended experiment, and achieve an accuracy of 93%.

Ectopic pregnancy (EP) is increasingly found in women treated with in vitro fertilization and embryo transfer (IVF–ET). With the development of the freeze-all policy in reproductive medicine, it is controversial whether frozen embryo transfer (FET) could reduce the rate of EP. In this single-center, large-sample retrospective study, we analyzed 16,048 human chorionic gonadotrophin (hCG)-positive patients who underwent fresh embryo transfer (ET) or FET cycles between January 2013 and March 2022. Throughout the study, the total EP rate was 2.09% (336/16,048), 2.16% (82/3803) in the ET group, and 2.07% (254/12,245) in the FET group. After adjustment for age, infertility causes, and other confounding factors, logistic regression results showed no statistical difference in EP rates between FET and ET groups (odds ratio (OR) 0.93 (0.71–1.22), p > 0.05). However, among the 3808 patients who underwent fresh ET cycles, the OR for EP was significantly lower in the long agonist protocol group than in the gonadotropin-releasing hormone antagonist (GnRH-ant) protocol group (OR 0.45 (0.22–0.93), p < 0.05). Through a large retrospective study, we demonstrated a slightly lower EP rate in FET cycles than in fresh ET cycles, but there was no significant difference. The long agonist protocol in ET cycles had a significantly lower risk of EP than the GnRH-ant protocol.

In this paper, the characteristics of the vortex shedding and noise of the blunt trailing edge with different porous permeable segment are studied by numerical simulation. The permeability distribution is adjusted through continuously changing the viscous drag of porous region to achieve uniformity and non-uniformity. The simulation results firstly show that the porous trailing edge can stabilize the free shear layer in a certain range of viscous drag coefficient to suppress the vortex shedding and reduce the overall noise level significantly. The optimized non-uniform permeability can further reduce the noise by 3dB than that of uniform permeability for porous blunt trailing edge. The discrete strip-shaped porous blunt trailing edge is proposed for more practical engineering application. It is found that the noise level is increased by 2 dB rather than optimal function distribution. However, the discrete strip porous trailing edge still has significant noise reduction capacity with respect to solid blunt trailing edge. The three-dimensional simulation demonstrates further that the non-uniform permeable trailing edge behaves more potential than uniform permeable trailing edge and reveals the crucial spanwise synergy effects by porous treatment.

Abstract The term “geographical synthetic thinking” is taken from the latest Chinese version of the “Geography Curriculum Standards” (General High School 2017 edition, Compulsory Education 2022 edition) and is one of the four core competencies prioritized in the teaching of geography at the secondary-school level. This study proposes that using geographic subject mind maps improves students’ geographical synthetic thinking and develops a set of geographic subject mind map (GSMM) drawing standards for teachers and matching standards and suggestions for teaching applications. Seven geography teachers and their students from eight class sections in seven provinces and cities in China were recruited to participate in the study. The teachers taught students how to use geographic subject mind maps designed to develop students’ geographical synthetic thinking in the geography classroom. After 4–5 experimental lessons, the geographical synthetic thinking level of the 267 valid student participants showed a significant improvement, with a statistically significant difference between pretest and posttest scores. The teachers’ level of application of geographic subject mind maps in teaching was significantly and positively correlated with the students’ improvements in geographical synthetic thinking, demonstrating that the standardized use of geographic subject mind maps in accordance with teaching application standards can effectively improve students’ geographical synthetic thinking levels.

Abstract Apolipoprotein O (APOO) plays a critical intracellular role in regulating lipid metabolism. Here, we investigated the roles of APOO in metabolism and atherogenesis in mice. Hepatic APOO expression was increased in response to hyperlipidemia but was inhibited after simvastatin treatment. Using a novel APOO global knockout (Apoo −/− ) model, it was found that APOO depletion aggravated diet-induced obesity and elevated plasma cholesterol levels. Upon crossing with low-density lipoprotein receptor (LDLR) and apolipoprotein E (APOE) knockout hyperlipidemic mouse models, Apoo −/− Apoe −/− and Apoo −/− Ldlr −/− mice exhibited elevated plasma cholesterol levels, with more severe atherosclerotic lesions than littermate controls. This indicated the effects of APOO on cholesterol metabolism independent of LDLR and APOE. Moreover, APOO deficiency reduced cholesterol excretion through bile and feces while decreasing phospholipid unsaturation by inhibiting NRF2 and CYB5R3. Restoration of CYB5R3 expression in vivo by adeno-associated virus (AAV) injection reversed the reduced degree of phospholipid unsaturation while decreasing blood cholesterol levels. This represents the first in vivo experimental validation of the role of APOO in plasma cholesterol metabolism independent of LDLR and elucidates a previously unrecognized cholesterol metabolism pathway involving NRF2/CYB5R3. APOO may be a metabolic regulator of total-body cholesterol homeostasis and a target for atherosclerosis management. Apolipoprotein O (APOO) regulates plasma cholesterol levels and atherosclerosis through a pathway involving CYB5R3 that regulates biliary and fecal cholesterol excretion, independently of the LDL receptor. In addition, down-regulation of APOO may lead to impaired mitochondrial function, which in turn aggravates diet-induced obesity and fat accumulation.

Abstract Myeloid cells are abundant and plastic immune cell subsets in the liver, to which pro-tumorigenic, inflammatory and immunosuppressive roles have been assigned in the course of tumorigenesis. Yet several aspects underlying their dynamic alterations in hepatocellular carcinoma (HCC) progression remain elusive, including the impact of distinct genetic mutations in shaping a cancer-permissive tumor microenvironment (TME). Here, in newly generated, clinically-relevant somatic female HCC mouse models, we identify cancer genetics’ specific and stage-dependent alterations of the liver TME associated with distinct histopathological and malignant HCC features. Mitogen-activated protein kinase (MAPK)-activated, Nras G12D-driven tumors exhibit a mixed phenotype of prominent inflammation and immunosuppression in a T cell-excluded TME. Mechanistically, we report a Nras G12D cancer cell-driven, MEK-ERK1/2-SP1-dependent GM-CSF secretion enabling the accumulation of immunosuppressive and proinflammatory monocyte-derived Ly6Clow cells. GM-CSF blockade curbs the accumulation of these cells, reduces inflammation, induces cancer cell death and prolongs animal survival. Furthermore, GM-CSF neutralization synergizes with a vascular endothelial growth factor (VEGF) inhibitor to restrain HCC outgrowth. These findings underscore the profound alterations of the myeloid TME consequential to MAPK pathway activation intensity and the potential of GM-CSF inhibition as a myeloid-centric therapy tailored to subsets of HCC patients.

Abstract Argonaute (Ago) proteins are ubiquitous across all kingdoms of life. Eukaryotic Agos (eAgos) use small RNAs to recognize transcripts for RNA silencing in eukaryotes. In contrast, the functions of prokaryotic counterparts (pAgo) are less well known. Recently, short pAgos in conjunction with the associated TIR or Sir2 (SPARTA or SPARSA) were found to serve as antiviral systems to combat phage infections. Herein, we present the cryo-EM structures of nicotinamide adenine dinucleotide (NAD+)-bound SPARSA with and without nucleic acids at resolutions of 3.1 Å and 3.6 Å, respectively. Our results reveal that the APAZ (Analogue of PAZ) domain and the short pAgo form a featured architecture similar to the long pAgo to accommodate nucleic acids. We further identified the key residues for NAD+ binding and elucidated the structural basis for guide RNA and target DNA recognition. Using structural comparisons, molecular dynamics simulations, and biochemical experiments, we proposed a putative mechanism for NAD+ hydrolysis in which an H186 loop mediates nucleophilic attack by catalytic water molecules. Overall, our study provides mechanistic insight into the antiphage role of the SPARSA system.

In traditional wastewater treatment, ozone injection efficiency is low. There is a need for the quantitative preparation of ozone-based microfine bubbles to balance bubble stability and ozone reactivity. To address this, we developed coaxial and T-type ozone-based microfine bubble generators and conducted experiments to compare their bubble production effects. The more effective generator was then compared with the traditional aeration method. The results indicate the following: 1. The coaxial type is more effective in producing ozone-based microfine bubbles. 2. The bubbles produced by the coaxial type have an average diameter of 0.2–0.4 mm and a residence time of ∼2 min, meeting microfine bubble standards. Experimental data analysis shows compliance with the force process and bubble growth mechanism under coaxial flow, meeting the requirements for quantitative and controllable ozone-based microfine bubble production. 3. Ozone bubbles from the coaxial method surpass those from traditional aeration in volume and concentration. More than 99.73% are microfine bubbles, with an ozone concentration of ∼84.5%. 4. The coaxial method more effectively reduces COD values in water, contributing to efficient wastewater treatment. This research presents new avenues for efficient sewage treatment.

Demand fluctuates in actual production. When manufacturers face demand under their maximum capacity, suspension shifts are crucial for cost reduction and on-time delivery. In this case, suspension shifts are needed to minimize idle time and prevent inventory buildup. Thus, it is essential to integrate suspension shifts with scheduling under an uncertain production environment. This paper addresses the two-stage hybrid flow shop scheduling problem (THFSP) with suspension shifts under uncertain processing times, aiming to minimize the weighted sum of earliness and tardiness. We develop a stochastic integer programming model and validate it using the Gurobi solver. Additionally, we propose a dual-space co-evolutionary biased random key genetic algorithm (DCE-BRKGA) with parallel evolution of solutions and scenarios. Considering decision-makers’ risk preferences, we use both average and pessimistic criteria for fitness evaluation, generating two types of solutions and scenario populations. Testing with 28 datasets, we use the value of the stochastic solution (VSS) and the expected value of perfect information (EVPI) to quantify benefits. Compared to the average scenario, the VSS shows that the proposed algorithm achieves additional value gains of 0.9% to 69.9%. Furthermore, the EVPI indicates that after eliminating uncertainty, the algorithm yields potential improvements of 2.4% to 20.3%. These findings indicate that DCE-BRKGA effectively supports varying decision-making risk preferences, providing robust solutions even without known processing time distributions.

To enhance the performance of tubular microbubble generators, the Volume of Fluid (VOF) multiphase flow model in COMSOL Multiphysics was used to simulate the bubble fragmentation characteristics within a throttling hole microbubble generator. The effects of the inlet speed of the throttling hole pipe, the diameter of the throttling hole, and the length of the expansion section on bubble fragmentation performance were analyzed. The results indicated that an increase in the inlet speed of the throttling hole pipe gradually improved the bubble fragmentation performance. However, an increase in the throttling hole diameter significantly reduced the bubble fragmentation performance. Changes in the length of the expansion section had a minor impact on the bubble fragmentation performance. Experimental methods were used to verify the characteristics of bubble fragmentation, and it was found that the simulation and experimental results were consistent. This provides a theoretical basis and practical guidance for the design optimization of tubular microbubble generators.