As a major approach for controlling electromagnetic (EM) waves, metamaterials have experienced an abundant and rapid development in the 21st century. They have provided flexible and powerful techniques for controlling EM waves and brought many unique applications that are difficult to realise with natural materials. With increasing demands on dynamic controls of the EM waves, many innovations have been conducted in both three-dimensional metamaterials and two-dimensional metasurfaces, in which the meta-atom has been gradually evolved from passive to active. In 2014, coding and digital mechanisms were initially introduced to the metamaterials, further advancing the appearance of digitally programmable metamaterials. The programmable metamaterials have shown great potentials in not only real-time manipulations of the EM waves, but also direct information processing on the EM wave level. In this article, we present an in-depth review of the programmable EM metamaterials and metasurfaces, focusing on the programmable features including theoretical concepts, implementing methods and applications in EM controls. We first give a short retrospect of traditional metamaterials and metasurfaces, followed by the concepts and detailed discussions of digital coding and field-programmable metamaterials. Then, we introduce space-domain, time-domain and space–time-domain programmable metamaterials and metasurfaces, mainly focusing on their theories, functionalities, experimental implementations, and system-level applications. Finally, we conclude the current advances of the programmable metamaterials and metasurfaces, and give a prospect for the future developments.

We conduct three-dimensional direct numerical simulations to investigate the mixing, entrainment and energy budgets of gravity currents emerging from two-layer stratified locks. Depending on the density and layer thickness ratios, we find that either the upper layer or lower layer fluid can propagate faster, and that the density structure of the overall gravity current can range from strongly stratified to near-complete mixing. We furthermore observe that intermediate values of the density ratio can maximise mixing between the gravity current layers. Based on the vorticity budget, we propose a theoretical model for predicting the overall gravity current height, along with the front velocity of the two layers, for situations in which the lower layer moves faster than the upper layer. The model identifies the role of the height and thickness ratios in determining the velocity structure of the current, and it clarifies the dynamics of the ambient counter-current. A detailed analysis of the energy budget quantifies the conversion of potential into kinetic energy as a function of the governing parameters, along with the energy transfer between the different layers of the gravity current and the ambient fluid. Depending on the values of the density and layer thickness ratios, we find that the lower lock layer can gain or lose energy, whereas the upper layer always loses energy.

According to Hamilton's rule, matrilineal-biased investment restrains men in matrilineal societies from maximising their inclusive fitness (the ‘matrilineal puzzle'). A recent hypothesis argues that when women breed communally and share household resources, a man should help his sisters' household, rather than his wife's household, as investment to the later but not the former would be diluted by other unrelated members (Wu et al., 2013). According to this hypothesis, a man is less likely to help on his wife's farm when there are more women reproducing in the wife's household, because on average he would be less related to his wife's household. We used a farm-work observational dataset, that we collected in the matrilineal Mosuo in southwest China, to test this hypothesis. As predicted, high levels of communal breeding by women in his wife's households do predict less effort spent by men on their wife's farm, and communal breeding in men's natal households do not affect whether men help on their natal farms. Thus, communal breeding by women dilutes the inclusive fitness benefits men receive from investment to their wife and children, and may drive the evolution of matrilineal-biased investment by men. These results can help solve the ‘matrilineal puzzle'.

The association between dietary Cu intake and mortality risk remains uncertain. We aimed to investigate the relationship of dietary Cu intake with all-cause mortality among Chinese adults. A total of 17 310 participants from the China Health and Nutrition Survey, a national ongoing open cohort of Chinese participants, were included in the analysis. Dietary intake was measured by three consecutive 24-h dietary recalls in combination with a weighing inventory over the same 3 d. The average intakes of the 3-d dietary macronutrients and micronutrients were calculated. The study outcome was all-cause mortality. During a median follow-up of 9·0 years, 1324 (7·6 %) participants died. After adjusting for sex, age, BMI, ever alcohol drinking, ever smoking, education levels, occupations, urban or rural residents, systolic blood pressure, diastolic blood pressure and the intakes of fat, protein and carbohydrate, the association between dietary Cu intake and all-cause mortality followed a J-shape (P for nonlinearity = 0·047). When dietary Cu intake was assessed as quartiles, compared with those in the first quartile (<1·60 mg/d), the adjusted hazard ratios for all-cause mortality were 0·87 (95 % CI (0·71, 1·07)), 0·98 (95 % CI (0·79, 1·21)) and 1·49 (95 % CI (1·19, 1·86)), respectively, in participants in the second (1·60–<1·83 mg/d), third (1·83–<2·09 mg/d) and fourth (≥2·09 mg/d) quartiles. A series of subgroup analyses and sensitivity analyses showed similar results. Overall, our findings emphasised the importance of maintaining optimal dietary Cu intake levels for prevention of premature death.

We investigate the submerged collapse of weakly polydisperse, loosely packed cohesive granular columns, as a function of aspect ratio and cohesive force strength, via grain-resolving direct numerical simulations. The cohesive forces act to prevent the detachment of individual particles from the main body of the collapsing column, reduce its front velocity, and yield a shorter and thicker final deposit. All of these effects can be captured accurately across a broad range of parameters by piecewise power-law relationships. The cohesive forces reduce significantly the amount of available potential energy released by the particles. For shallow columns, the particle and fluid kinetic energy decreases for stronger cohesion. For tall columns, on the other hand, moderate cohesive forces increase the maximum particle kinetic energy, since they accelerate the initial free-fall of the upper column section. Only for larger cohesive forces does the peak kinetic energy of the particles decrease. Computational particle tracking indicates that the cohesive forces reduce the mixing of particles within the collapsing column, and it identifies the regions of origin of those particles that travel the farthest. The simulations demonstrate that cohesion promotes aggregation and the formation of aggregates. Furthermore, they provide complete information on the temporally and spatially evolving network of cohesive and direct contact force bonds. While the normal contact forces are aligned primarily in the vertical direction, the cohesive bonds adjust their preferred spatial orientation throughout the collapse. They result in a net macroscopic stress that counteracts deformation and slows the spreading of the advancing particle front.

The pandemic caused by severe acute respiratory syndrome coronavirus 2 is sweeping the world, threatening millions of lives and drastically altering our ways of living. According to current studies, failure to either activate or eliminate inflammatory responses timely and properly at certain stages could result in the progression of the disease. In other words, robust immune responses to coronavirus disease 2019 (COVID-19) are critical. However, they do not theoretically present in some special groups of people, including the young, the aged, patients with autoimmunity or cancer. Differences also do occur between men and women. Our immune system evolves to ensure delicate coordination at different stages of life. The innate immune cells mainly consisted of myeloid lineage cells, including neutrophils, basophils, eosinophils, dendritic cells and mast cells; they possess phagocytic capacity to different degrees at different stages of life. They are firstly recruited upon infection and may activate the adaptive immunity when needed. The adaptive immune cells, on the other way, are comprised mainly of lymphoid lineages. As one grows up, the adaptive immunity matures and expands its memory repertoire, accompanied by an adjustment in quantity and quality. In this review, we would summarise and analyse the immunological characteristics of these groups from the perspective of the immune system ‘evolution’ as well as ‘revolution’ that has been studied and speculated so far, which would aid the comprehensive understanding of COVID-19 and personalised-treatment strategy.

We aimed to investigate the relationship between the neutrophil to lymphocyte ratio (NLR) and nutritional parameters in chronic kidney disease (CKD) patients. In this cross-sectional study, 187 non-dialysis CKD patients were enrolled. Daily dietary energy intake (DEI) and daily dietary protein intake (DPI) were assessed by 3-d dietary records. Protein-energy wasting (PEW) was defined as Subjective Global Assessment (SGA) class B and C. Spearman correlation analysis, logistic regression analysis and receiver operating characteristic (ROC) curve analysis were performed. The median NLR was 2·51 (1·83, 3·83). Patients with CKD stage 5 had the highest NLR level. A total of 19·3 % (n 36) of patients suffered from PEW. The NLR was positively correlated with SGA and serum P, and the NLR was negatively correlated with BMI, waist and hip circumference, triceps skinfold thickness, mid-arm muscle circumference, DPI and Hb. Multivariate logistic regression analysis adjusted for DPI, DEI, serum creatinine, blood urea nitrogen, uric acid and Hb showed that a high NLR was an independent risk factor for PEW (OR = 1·393, 95 % CI 1·078, 1·800, P = 0·011). ROC analysis showed that an NLR ≥ 2·62 had the ability to identify PEW among CKD patients, with a sensitivity of 77·8 %, a specificity of 62·3 % and an AUC of 0·71 (95 % CI 0·63, 0·81, P < 0·001). The NLR was closely associated with nutritional status. NLR may be an indicator of PEW in CKD patients.

In this article, we reviewed the current literature studies and our understanding of the parameters that affect the chimeric antigen receptor T cells (CAR-T's) activation, effector function, in vivo persistence, and antitumour effects. These factors include T cell subsets and their differentiation stages, the components of chimeric antigen receptors (CAR) design, the expression promoters and delivery vectors, and the CAR-T production process. The CAR signalling and CAR-T activation were also studied in comparison to TCR. The last section of the review gave special consideration of CAR design for solid tumours, focusing on strategies to improve CAR-T tumour infiltration and survival in the hostile tumour microenvironment. With several hundred clinical trials undergoing worldwide, the pace of CAR-T immunotherapy moves from bench to bedside is unprecedented. We hope that the article will provide readers a clear and comprehensive view of this rapidly evolving field and will help scientists and physician to design effective CAR-Ts immunotherapy for solid tumours.

We investigate the removal of a dense bottom layer by a gravity current, via Navier–Stokes simulations in the Boussinesq limit. The problem is governed by a dimensionless thickness parameter for the bottom layer, and by the ratio of the density differences between bottom layer, gravity current and ambient fluids. A quasisteady gravity current forms that propagates along the interface and displaces some of the dense bottom fluid, which accumulates ahead of the gravity current and forms an undular bore or a series of internal gravity waves. Depending on the ratio of the gravity current front velocity to the linear shallow-water wave velocity, we observe the existence of different regimes, characterized by small-amplitude waves or by a train of steep, nonlinear internal waves. We develop a semiempirical model that provides reasonable estimates of several important flow properties. We also formulate a more sophisticated, self-contained model based on the conservation principles for mass and vorticity that does not require empirical closure assumptions. This model is able to predict such quantities as the gravity current height and the internal wave or bore velocity as a function of the governing dimensionless parameters, generally to within approximately a 10 $\%$ accuracy. An energy budget analysis provides information on the rates at which potential energy is converted into kinetic energy and then dissipated, and on the processes by which energy is transferred from the gravity current fluid to the dense and ambient fluids. We observe that the energy content of thicker and denser bottom layers grows more rapidly.

Nicotine 3,5-dihydroxybenzoate dihydrate is a nicotine salt and can be used as compositions in tobacco products. X-ray powder diffraction data, unit-cell parameters, and space group for nicotine 3,5-dihydroxybenzoate, C10H15N2⋅C7H5O4⋅2H2O, are reported [a = 8.424(1) Å, b = 13.179(8) Å, c = 8.591(1) Å, α = 90°, β = 102.073(8)°, γ = 90°, unit-cell volume V = 932.765(3) Å3, Z = 2, ρcal = 1.256 g⋅cm−3, and space group P21] at room temperature. All measured lines were indexed and are consistent with the P21 space group.

For image recognition, an extensive number of subspace-learning methods have been proposed to overcome the high-dimensionality problem of the features being used. In this paper, we first give an overview of the most popular and state-of-the-art subspace-learning methods, and then, a novel manifold-learning method, named soft locality preserving map (SLPM), is presented. SLPM aims to control the level of spread of the different classes, which is closely connected to the generalizability of the learned subspace. We also do an overview of the extension of manifold learning methods to deep learning by formulating the loss functions for training, and further reformulate SLPM into a soft locality preserving (SLP) loss. These loss functions are applied as an additional regularization to the learning of deep neural networks. We evaluate these subspace-learning methods, as well as their deep-learning extensions, on facial expression recognition. Experiments on four commonly used databases show that SLPM effectively reduces the dimensionality of the feature vectors and enhances the discriminative power of the extracted features. Moreover, experimental results also demonstrate that the learned deep features regularized by SLP acquire a better discriminability and generalizability for facial expression recognition.

Lipopolysaccharides (LPS) could induce milk fat depression via regulating the body and blood fat metabolism. However, it is not completely clear how LPS might regulate triglyceride synthesis in dairy cow mammary epithelial cells (DCMECs). DCMECs were isolated and purified from dairy cow mammary tissue and treated with LPS. The level of triglyceride synthesis, the expression and activity of the liver X receptor α (LXRα), enzymes related to de novo fatty acid synthesis, and the expression of the fatty acid transporters were investigated. We found that LPS decreased the level of triglyceride synthesis via a down-regulation of the transcription, translation, and nuclear translocation level of the LXRα. The results also indicated that the transcription level of the LXRα target genes, sterol regulatory element binding protein 1 (SREBP1), fatty acid synthetase (FAS), acetyl-CoA carboxylase-1 (ACC1), were significantly down-regulated in DCMECs after LPS treatment. Our data may provide new insight into the mechanisms of milk fat depression caused by LPS.

Hydrothermal carbon microsphere (HTC) is a carbon-based fluorescent material, which can be synthesized by hydrothermal carbonization of glucose. In this article, a series of 4ZnO·B2O3·H2O:Ln3+/HTC (where Ln = Eu or Tb) composites were prepared under hydrothermal conditions. The effects of the glucose concentration on the morphology, photoluminescence (PL) intensity and emission color of Zn3.64:Eu0.24[B2O7]·H2O/HTCx and Zn3.55:Tb0.3[B2O7]·H2O/HTCy were investigated. The relationship between morphology and PL intensity of composites was discussed. The results revealed that the presence of HTC did not change the original emission color of 4ZnO·B2O3·H2O:Ln3+ (where Ln = Eu or Tb) materials, but greatly increased their PL intensity, the sphere-like morphology composites have the strongest PL intensity. The Zn3.64:Eu0.24[B2O7]·H2O/HTCx and Zn3.55:Tb0.3[B2O7]·H2O/HTCy emit bright red light and green light, respectively, under respective excitation wavelengths. The present research suggests that the 4ZnO·B2O3·H2O:Ln3+/HTC (where Ln = Eu or Tb) composites may be candidates of red and green phosphors for display and lighting applications.

We examine the role of relationship-based resource allocations during the approval process of seasoned equity offerings (SEOs) in the Chinese capital market. Our results show that guanxi-based relationships significantly increase the likelihood of SEO approvals, particularly for suspect SEO applicants with abnormal levels of earnings management (EM), related-party transactions (RPTs), and intercompany loans. More importantly, we find that guanxi-influenced SEO firms have significantly poorer performance in the post-SEO period, which indicates that it results in inefficient resource allocations. Overall, our evidence suggests that relationship-based resource allocations lead to negative spillover effects that impose social welfare losses.