Conversational recommender system (CRS) needs to be seamlessly integrated between the two modules of recommendation and dialog, aiming to recommend high-quality items to users through multiple rounds of interactive dialogs. Items can typically refer to goods, movies, news, etc. Through this form of interactive dialog, users can express their preferences in real time, and the system can fully understand the user’s thoughts and recommend corresponding items. Although mainstream dialog recommendation systems have improved the performance to some extent, there are still some key issues, such as insufficient consideration of the entity’s order in the dialog, the different contributions of items in the dialog history, and the low diversity of generated responses. To address these shortcomings, we propose an improved dialog context model based on time-series features. Firstly, we augment the semantic representation of words and items using two external knowledge graphs and align the semantic space using mutual information maximization techniques. Secondly, we add a retrieval model to the dialog recommendation system to provide auxiliary information for generating replies. We then utilize a deep timing network to serialize the dialog content and more accurately learn the feature relationship between users and items for recommendation. In this paper, the dialog recommendation system is divided into two components, and different evaluation indicators are used to evaluate the performance of the dialog component and the recommendation component. Experimental results on widely used benchmarks show that the proposed method is effective.

Routine blood examination is an easy way to examine infectious diseases. This study is aimed to develop a model to diagnose serious bacterial infections (SBI) in ICU neonates based on routine blood parameters. This was a cross-sectional study, and data were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III). SBI was defined as suffering from one of the following: pyelonephritis, bacteraemia, bacterial meningitis, sepsis, pneumonia, cellulitis, and osteomyelitis. Variables with statistical significance in the univariate logistic regression analysis and log systemic immune–inflammatory index (SII) were used to develop the model. The area under the curve (AUC) was calculated to assess the performance of the model. A total of 1,880 participants were finally included for analysis. Weight, haemoglobin, mean corpuscular volume, white blood cell, monocyte, premature delivery, and log SII were selected to develop the model. The developed model showed a good performance to diagnose SBI for ICU neonates, with an AUC of 0.812 (95% confidence interval (CI): 0.737–0.888). A nomogram was developed to make this model visualise. In conclusion, our model based on routine blood parameters performed well in the diagnosis of neonatal SBI, which may be helpful for clinicians to improve treatment recommendations.

HIV-1 molecular surveillance provides a new approach to explore transmission risks and targeted interventions. From January to June 2021, 663 newly reported HIV-1 cases were recruited in Zhaotong City, Yunnan Province, China. The distribution characteristics of HIV-1 subtypes and HIV-1 molecular network were analysed. Of 542 successfully subtyped samples, 12 HIV-1 strains were identified. The main strains were CRF08_BC (47.0%, 255/542), CRF01_AE (17.0%, 92/542), CRF07_BC (17.0%, 92/542), URFs (8.7%, 47/542), and CRF85_BC (6.5%, 35/542). CRF08_BC was commonly detected among Zhaotong natives, illiterates, and non-farmers and was mostly detected in Zhaoyang County. CRF01_AE was frequently detected among married and homosexual individuals and mostly detected in Weixin and Zhenxiong counties. Among the 516 pol sequences, 187 (36.2%) were clustered. Zhaotong natives, individuals aged ≥60 years, and illiterate individuals were more likely to be found in the network. Assortativity analysis showed that individuals were more likely to be genetically associated when stratified by age, education level, occupation, and reporting area. The genetic diversity of HIV-1 reflects the complexity of local HIV epidemics. Molecular network analyses revealed the subpopulations to focus on and the characteristics of the risk networks. The results will help optimise local prevention and control strategies.

N-enriched biochar can increase the accumulation of carbon (C), nitrogen (N), phosphorus (P), and biomass in rice plants. On the other hand, the biomass and C, N, and P contents of plant organs are important indicators to reflect plant C, N, and P storages. We established control, 4 t ha−1, and 8 t ha−1 N-enriched biochar treatment plots in a subtropical paddy field in China to investigate the effect of these treatments on C, N, and P storages, ecological stoichiometry in various rice plant organs, and their relationships with edaphic factors. The application of N-enriched biochar increased the biomass and storages of C, N, and P in rice roots, stems, leaves, and grains, mainly at 4 t ha−1. The application of N-enriched biochar decreased the C/N and C/P ratios of rice organs, but increased their N/P ratio. Changes in C/N were mainly due to the changes in storage, while N/P was positively correlated with N storage of stems, leaves, and grains and negatively correlated with P storage in roots. Pearson’s correlation analysis revealed that pH was negatively correlated, and soil N content was positively correlated with P storage in various organs of rice. In addition, soil P content and chlorophyll were positively correlated with N storage. In conclusion, we found that the application of N-enriched biochar improved plant N and P storage and stoichiometrical relations among rice organs.

Sleep apnea is one of the most common sleep disorders. The consequences of undiagnosed sleep apnea can be very serious, increasing the risk of high blood pressure, heart disease, stroke, and Alzheimer’s disease over a long period of time. However, many people are often unaware of their condition. The gold standard for diagnosing sleep apnea is nighttime polysomnography monitoring in a specialized sleep laboratory. However, these diagnoses are expensive and the number of beds is limited, and there is insufficient monitoring in terms of time dimension. Existing methods for automated detection use no more than three physiological signals, but all other signals are also associated with the patient’s sleep. In addition, the limited amount of medical real annotation data, especially abnormal samples, lead to weak model generalization capability. The gap between model generalization capability and medical field needs still exists. In this paper, we propose a method for integrating medical interpretation rules into a long short-term memory neural network based on self-attention with multichannel respiratory signals as input. We obtain attention weights through a token-level attention mechanism and then extract key rules of medical interpretation to assist the weights, improving model generalization and reducing the dependence on data volume. Compared with the best prediction performance of existing methods, the average improvements of our method in accuracy, precision, and f1-score are 3.26%, 7.03%, and 1.78%, respectively. The algorithm tested the performance of our model on the Sleep Heart Health Study data set and found that the model outperformed existing methods and could help physicians make decisions in their practices.

Given a graph $G$ and an integer $\ell \ge 2$ , we denote by $\alpha _{\ell }(G)$ the maximum size of a $K_{\ell }$ -free subset of vertices in $V(G)$ . A recent question of Nenadov and Pehova asks for determining the best possible minimum degree conditions forcing clique-factors in $n$ -vertex graphs $G$ with $\alpha _{\ell }(G) = o(n)$ , which can be seen as a Ramsey–Turán variant of the celebrated Hajnal–Szemerédi theorem. In this paper we find the asymptotical sharp minimum degree threshold for $K_r$ -factors in $n$ -vertex graphs $G$ with $\alpha _\ell (G)=n^{1-o(1)}$ for all $r\ge \ell \ge 2$ .

Nitrogen fertilizer and water are two major nutrients required for the optimal production of rice worldwide. The utilization of different irrigation techniques to save water and fertigation to maximize rice production has been the main focus. A field experiment was conducted to explore the responses of 16 rice varieties to different irrigation and nitrogen fertilizer regimes. Two nitrogen treatments, 270 kg ha−1 and 225 kg ha−1 (urea N ≥ 46.4%), and two irrigation regimes, 8.7 t ha−1 and 5.22 t ha−1, were applied three times. Plant height and the soil and plant analyser development (SPAD) values were measured throughout the growth period. The total yield and quality characteristics of the rice varieties were also determined. Based on the yield, the 16 rice varieties were divided into three groups: high yield (I), middle yield (II) and low yield (III) using cluster analysis. A positive correlation was found between the growth period and yield of these 16 rice varieties. In the water-deficient regime, the growth period of the 16 varieties was reduced by 1.68–2.93%. Furthermore, nitrogen- and water-deficient regimes had significant effects on the polishing rate, protein content and taste values of all varieties. At maturity stage under these regimes, plant height and chlorophyll SPAD values were decreased by 1.25–6.05% and 1.60–31.48%, respectively. Deficient nitrogen fertilization, along with appropriate irrigation, is an effective method for the efficient utilization of irrigation and fertilizer resources in rice-growing areas.

Suppose you need to complete a task of 5 steps, each of which has equal difficulty and pass rate. You somehow have a privilege that can ensure you pass one of the steps, but you need to decide which step to be privileged before you start the task. Which step do you want to privilege? Mathematically speaking, the effect of each step on the final outcome is identical, and so there seems to be no prima facie reason for a preference. Five studies were conducted to explore this issue. In Study 1, participants could place the privilege on any of steps 1–5. Participants were most inclined to privilege step 5. In Study 2, participants needed to pay some money to purchase the privilege for steps 1–5, respectively. Participants would pay most money for step 5. Study 3 directly reminded participants that the probability of success of the whole task is mathematically the same, no matter on which step the privilege is placed, but most of the participants still prefer to privilege the final step. Study 4 supposed that the outcomes of all steps were not announced until all steps were finished, and asked how painful participants would feel if they passed all steps but one. People thought they would feel most painful when they failed at the final step. In Study 5, an implicit association test showed that people associated the first step with easy and the final step with hard. These results demonstrated the phenomenon of the final step effect and suggested that both anticipated painfulness and stereotype may play a role in this phenomenon.

Objectives: Patients undergoing hemodialysis using a catheter are at significant risk of developing central venous catheter–related bloodstream infections (CRBSIs), especially with methicillin-resistant Staphylococcus aureus (MRSA), resulting in increased morbidity, mortality, and cost. In our 1,000-bed regional hospital, the average CRBSI (any bacteria) rate in patients dialyzing via dialysis catheters was 1.44 per 1,000 catheter days, and the average CRBSI (MRSA) rate was 0.56 per 1,000 catheter days. A quality improvement project was initiated to reduce the overall dialysis CRBSI and CRBSI-MRSA by 50%. Methods: Following the formation of a multidisciplinary team, the catheter-insertion protocols and catheter-care protocols were standardized throughout the hospital. We adopted a well-established scientific quality improvement method, plan–do–study–act (PDSA) cycle model for all interventions that were implemented. The patients and general ward nursing staff were provided education and training in dialysis catheter care. Results: The project was initiated in January 2016, and the initial improvement was seen from July 2017 onward. Analysis of the data since 2016 showed a steady improvement in the overall CRBSI rates, as well as CRBSI-MRSA rates. The average CRBSI rate improved to 0.76 per 1,000 catheter days, and the average CRBSI-MRSA rates improved to 0.15 per 100 catheter days in the calendar year 2021. Conclusions: Because the causes of these infections are multifactorial, emphasis should be placed on improving care processes from the patient preparation phase prior to catheter insertion to regular catheter care in the inpatient wards and dialysis units. We attribute the success of our project to involving all stakeholders and obtaining constant feedback from the staff. We successfully applied PDSA cycles to make relevant incremental changes.

One of the most common harmful mites in edible fungi is Histiostoma feroniarum Dufour (Acaridida: Histiostomatidae), a fungivorous astigmatid mite that feeds on hyphae and fruiting bodies, thereby transmitting pathogens. This study examined the effects of seven constant temperatures and 10 types of mushrooms on the growth and development of H. feroniarum, as well as its host preference. Developmental time for the total immature stages was significantly affected by the type of mushroom species, ranging from 4.3 ± 0.4 days (reared on Pleurotus eryngii var. tuoliensis Mou at 28°C) to 17.1 ± 2.3 days (reared on Auricularia polytricha Sacc. at 19°C). The temperature was a major factor in the formation of facultative heteromorphic deutonymphs (hypopi). The mite entered the hypopus stage when the temperature dropped to 16°C or rose above 31°C. The growth and development of this mite were significantly influenced by the type of species and variety of mushrooms. Moreover, the fungivorous astigmatid mite preferred to feed on the ‘Wuxiang No. 1’ strain of Lentinula edodes (Berk.) Pegler and the ‘Gaowenxiu’ strain of P. pulmonarius (Fr.) Quél., with a shorter development period compared with that of feeding on other strains. These results therefore quantify the effect of host type and temperature on fungivorous astigmatid mite growth and development rates, and provide a reference for applying mushroom cultivar resistance to biological pest control.

The present study aimed to investigate the relationship between dietary patterns and the risk of type 2 diabetes mellitus (T2DM) among Taiwanese individuals. Data were collected using a nationwide cohort study (2001–15) from the Triple-High Database. Dietary intake was assessed using the twenty-group food frequency questionnaire and used to calculate alternate Mediterranean diet (aMED) and Dietary Approaches to Stop Hypertension (DASH) scores. Principal component analysis (PCA) and partial least-squares (PLS) regression were used to derive dietary patterns, with incident T2DM as the outcome. Multivariable-adjusted hazard ratios and 95 % confidence intervals were calculated using time-dependent Cox proportional hazards (Cox PH) regression analysis, and subgroup analyses were performed. A total of 4705 participants were enrolled in the study, and 995 had newly developed T2DM during the median 5⋅28-year follow-up period (30⋅7 per 1000 person-years). Six dietary patterns were extracted (PCA: Western, prudent, dairy and plant-based; PLS: health-conscious, fish-vegetable and fruit-seafood). The highest aMED score quartile had a 25 % (hazard ratio 0⋅75; 95 % CI 0⋅61, 0⋅92; P = 0⋅039) lower risk of T2DM than the lowest quartile. This association remained significant after adjustment (adjusted hazard ratio 0⋅74; 95 % CI 0⋅60, 0⋅91; P = 0⋅010), and no effect modifier was found for aMED. The DASH scores, PCA and PLS dietary patterns were not significant after adjustment. In conclusion, high adherence to a MED-type dietary pattern by Taiwanese foods was associated with a lower risk of T2DM in the Taiwanese population, regardless of unhealthy lifestyle habits.

The Palaeo-Mesozoic geodynamic evolution of the Tangjia–Sumdo accretionary complex belt, which separates the North and South Lhasa Terrane, remains controversial. Moreover, the lack of geological records restricts the understanding of the evolution of the Sumdo Palaeo-Tethys Ocean from the middle Permian until the middle Triassic. Here we present zircon U–Pb geochronology, whole-rock geochemistry and Sr–Nd–Hf isotopic compositions of the Yeqing gabbro. Zircon U–Pb geochronology yields ages from 254 ± 1 to 249 ± 1 Ma. In situ Hf isotopic analyses yield ϵ Hf(t) values of −0.2 to +6.3. These samples have high TiO2 (3.69 wt %) and P2O5 (0.78 wt %) contents, with typical patterns like ocean island basalt (OIB). Besides, they are classified as high-Nb basalts (HNBs) based on the high content of Nb (45.3–113.5 ppm). Whole-rock Sr–Nd isotopic compositions are similar to OIB, with initial 87Sr/86Sr of 0.7047–0.7054, 143Nd/144Nd of 0.512526–0.512647 and ϵ Nd(t) of 0.3–2.7. These signatures suggest that the Yeqing gabbro is mainly derived from low-degree melting of the garnet lherzolite mantle. Based on field observations of HNBs intruding into the continental margin and their geochemical characteristics, we infer that the Yeqing gabbro was generated in a subduction environment. Combined with the regional geology of the subduction environment and the evolution of oceanic islands in the Sumdo Palaeo-Tethys Ocean, we propose that the Yeqing gabbro may represent a product of the asthenosphere upwelling through a slab window produced by subduction of seismic ridge in the Sumdo Palaeo-Tethys Ocean, called plume – subduction-zone interaction, during the late Permian to early Triassic.

Liriomyza trifolii is a significant pest of vegetable and ornamental crops across the globe. Microwave radiation has been used for controlling pests in stored products; however, there are few reports on the use of microwaves for eradicating agricultural pests such as L. trifolii, and its effects on pests at the molecular level is unclear. In this study, we show that microwave radiation inhibited the emergence of L. trifolii pupae. Transcriptomic studies of L. trifolii indicated significant enrichment of differentially expressed genes (DEGs) in ‘post-translational modification, protein turnover, chaperones’, ‘sensory perception of pain/transcription repressor complex/zinc ion binding’ and ‘insulin signaling pathway’ when analyzed with the Clusters of Orthologous Groups, Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes databases, respectively. The top DEGs were related to reproduction, immunity and development and were significantly expressed after microwave radiation. Interestingly, there was no significant difference in the expression of genes encoding heat shock proteins or antioxidant enzymes in L. trifolii treated with microwave radiation as compared to the untreated control. The expression of DEGs encoding cuticular protein and protein takeout were silenced by RNA interference, and the results showed that knockdown of these two DEGs reduced the survival of L. trifolii exposed to microwave radiation. The results of this study help elucidate the molecular response of L. trifolii exposed to microwave radiation and provide novel ideas for control.

In the era of rapid product update and intense competition, aesthetic design has been increasingly important in various fields, as aesthetic feelings of customers largely influence their purchase preferences. However, the quantification of aesthetic feeling is still a very subjective process due to vague evaluations. The determination of form parameters according to aesthetics is difficult hitherto. Aesthetic measure recently arises as a prominent tool for this purpose using formulas derived from aesthetic theory. But as revealed by existing studies, it needs to be customized with deterministic and objective methods to be reliable in practice use. To facilitate this application, this paper proposes an evolutionary form design method, integrating aesthetic dimension selection and parameter optimization. After summarizing initial aesthetic dimensions, aesthetic dimension selection based on expert decision-making and particle swarm optimization (PSO) is carried out. With filtered aesthetic dimensions, design parameters are optimized with NSGA-II (non-dominated sorting genetic algorithm). The quality of pareto solutions obtained to be design schemes is assessed by three criteria to conduct sensitivity analysis of cross and mutation probability and population size. Our experiment using bicycle form design shows that the proposed evolutionary form design method can generate numerous and variant aesthetic design schemes rapidly. This is very useful for both product redesign and innovative new product development.

Immune cells play a key role in maintaining renal dynamic balance and dealing with renal injury. The physiological and pathological functions of immune cells are intricately connected to their metabolic characteristics. However, immunometabolism in chronic kidney disease (CKD) is not fully understood. Pathophysiologically, disruption of kidney immune cells homeostasis causes inflammation and tissue damage via triggering metabolic reprogramming. The diverse metabolic characteristics of immune cells at different stages of CKD are strongly associated with their different pathological effect. In this work, we reviewed the metabolic characteristics of immune cells (macrophages, natural killer cells, T cells, natural killer T cells and B cells) and several non-immune cells, as well as potential treatments targeting immunometabolism in CKD. We attempt to elaborate on the metabolic signatures of immune cells and their intimate correlation with non-immune cells in CKD.

Recently, the collisionless pitch-angle scattering for relativistic runaway electrons (REs) in toroidal geometries such as tokamaks was discovered through a full orbit simulation approach (Liu et al., Nucl. Fusion, vol. 56, 2016, p. 064002), and it was then theoretically investigated that a new expression for the magnetic moment, including the second-order corrections, could essentially reproduce the so-called collisionless pitch-angle scattering process (Liu et al., Nucl. Fusion, vol. 58, 2018, p. 106018). In this paper, with synchrotron radiation, extensive numerical verification of the validity of the high-order guiding-centre theory is given for simulations involving REs by incorporating such an expression for the magnetic moment into our particle tracing code. A high-order guiding-centre simulation approach with synchrotron radiation (HGSA) is applied. Synchrotron radiation plays an essential role in the life cycle of REs. The energy of REs first increases and then becomes saturated until the electric field acceleration is balanced by the radiation dissipation. Unfortunately, the process cannot be simulated accurately with the standard guiding-centre model, i.e. the first-order guiding-centre model. Remarkably, it is found that the HGSA can effectively produce the fundamental process of REs. Since the time scale of the energy saturation of REs is close to seconds, the computational cost becomes significant. In order to save costs, it is necessary to estimate the time of energy saturation. An analytical estimate is derived for the time it takes for synchrotron drag to balance an accelerating electric field and the provided formula has been numerically verified. Test calculations reveal that HGSA is favourable for exploiting the dynamics of REs in tokamak plasmas.