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Abstract The development of a wearable, easy-to-fabricate, and stable intelligent minisystem is highly desired for the closed-loop management of diabetes. Conventional systems always suffer from large size, high cost, low stability, or complex fabrication. Here, we show for the first time a wearable, rapidly manufacturable, stability-enhancing microneedle patch for diabetes management. The patch consists of a graphene composite ink-printed sensor on hollow microneedles, a polyethylene glycol (PEG)-functionalized electroosmotic micropump integrated with the microneedles, and a printed circuit board for precise and intelligent control of the sensor and pump to detect interstitial glucose and deliver insulin through the hollow channels. Via synthesizing and printing the graphene composite ink, the sensor fabrication process is fast and the sensing electrodes are stable. The PEG functionalization enables the micropump a significantly higher stability in delivering insulin, extending its lifetime from days to weeks. The patch successfully demonstrated excellent blood glucose control in diabetic rats. This work may introduce a new paradigm for building new closed-loop systems and shows great promise for widespread use in patients with diabetes.

Objective: Liquid black garlic was prepared from fresh garlic and the effect of Streptococcus thermophilus on the quality of liquid black garlic was studied. Methods: Fresh garlic was inactivated with alliinase at 180 ℃, then broken and added with Streptococcus thermophilus. Using the inactivated garlic without Streptococcus thermophilus (blank) as reference, the effects of Streptococcus thermophilus ratio, different alliinase inactivation time and their coexistence time on the quality of liquid black garlic were studied. Results: The optimal time for inactivating allinase in garlic at high temperature was 9 min, the optimal proportion of Streptococcus thermophilus was 5%, the optimal coexistence time of Streptococcus thermophilus and inactivated crushed garlic was 32 h, and the fermentation time required in a constant temperature and humidity fermentation tank at 80 ℃ was 15 d. All quality indexes reached the fermentation standard of black garlic. Compared with blank black garlic, the total phenol content of liquid black garlic was 2 times, the total acid content was 1.9 times, the reducing sugar content was 1.3 times, the DPPH· clearance and ·OH clearance were 1.5 times and 1.46 times, respectively. Conclusion: Streptococcus thermophilus can promote the fermentation of black garlic, improve its quality indicators, shorten fermentation time and have great application prospects.

ObjectiveTo assess the positional reproducibility of sedated and non-sedated pediatric tumor patients during radiotherapy through a retrospective analysis of cone-beam computed tomography (CBCT) and planned computed tomography (CT) scan data.MethodsThe positional reproducibility of 40 pediatric tumor patients, aged 2 to 17 years with a median age of 4.5 years, who received radiotherapy under sedated and non-sedated states was retrospectively compared. The first CBCT images obtained during CT-based treatment planning were analyzed. The analysis encompassed six-dimensional positional changes, including vertical (Vrt), longitudinal (Lng), lateral (Lat), rotational (Rtn), pitch, and roll directions. Kolmogorov-Smirnov Z nonparametric rank-sum testing was employed to evaluate the positional deviations, considering absolute values regardless of directionality. Data were further stratified based on different fixation methods used during treatment.ResultsSedated patients exhibited significantly smaller positional deviations in Vrt, Lng, Lat, and Rtn directions in the body membrane group compared with their non-sedated counterparts (P

In this paper, a new design method of E-plane waveguide bandpass filter (BPF) using high-order modes of spoof surface plasmon polaritons (SSPPs) is proposed. The high-order modes of the double-layer SSPP (DL-SSPP) unit cell can be effectively manipulated by adjusting the dimensions of grounded metallic patterns in SSPP array, which mainly determines the filtering characteristics of E-plane waveguide BPFs. For improving the out-of-band rejection, two extra transmission zeros (TZs) are designed at the upper and lower stopbands of E-plane waveguide BPF, and then the operating mechanism of TZs is clearly investigated. Moreover, the filtering characteristics of the E-plane waveguide BPF with different transition parts are discussed to demonstrate the generalization of proposed design method. To verify the design feasibility, two examples of E-plane waveguide BPF are fabricated and measured. Good agreement between measurements and simulations shows that the proposed design method possesses good potential for the applications of high-performance E-plane waveguide BPF design.

Abstract Human cancer cell lines have long served as tools for cancer research and drug discovery, but the presence and the source of intra-cell-line heterogeneity remain elusive. Here, we perform single-cell RNA-sequencing and ATAC-sequencing on 42 and 39 human cell lines, respectively, to illustrate both transcriptomic and epigenetic heterogeneity within individual cell lines. Our data reveal that transcriptomic heterogeneity is frequently observed in cancer cell lines of different tissue origins, often driven by multiple common transcriptional programs. Copy number variation, as well as epigenetic variation and extrachromosomal DNA distribution all contribute to the detected intra-cell-line heterogeneity. Using hypoxia treatment as an example, we demonstrate that transcriptomic heterogeneity could be reshaped by environmental stress. Overall, our study performs single-cell multi-omics of commonly used human cancer cell lines and offers mechanistic insights into the intra-cell-line heterogeneity and its dynamics, which would serve as an important resource for future cancer cell line-based studies.

This study investigates the genesis of analcite in black shale from continental lakes and its implications for hydrocarbon enrichment, with a case study of the Permian Pingdiquan Formation in the Junggar Basin, Xinjiang, China. As an alkaline mineral, analcite is extensively developed in China’s lacustrine black shale hydrocarbon source rocks and is linked to hydrocarbon distribution. However, the mechanisms of its formation and its impact on hydrocarbon generation and accumulation remain insufficiently understood. This paper employs a multi-analytical approach, including petrological observations, geochemical analysis, and X-ray diffraction, to characterize analcite and its association with hydrocarbon source rocks. The study identifies a hydrothermal sedimentary origin for analcite, suggesting that it forms under conditions of alkaline lake water and volcanic activity, which are conducive to organic matter enrichment. The analcite content in the studied samples exhibits a significant variation, with higher contents associated with hydrocarbon accumulation zones, suggesting its role in hydrocarbon generation and accumulation. This paper reports that analcite-bearing rocks display characteristics of high-quality reservoirs, enhancing the permeability and porosity of the rock, which is essential for hydrocarbon storage and migration. In conclusion, this paper underscores the importance of analcite as a key mineral indicator for hydrocarbon potential in black shale formations and provides valuable insights for further geological and hydrocarbon exploration in similar settings.

Surface treatment processes such as mass finishing play a crucial role in enhancing the quality of machined parts across industries. However, accurate measurement of the velocity field of granular media in mass finishing presents significant challenges. Existing measurement methods suffer from issues such as complex and expensive equipment, limited to single-point measurements, interference with the flow field, and lack of universality in different scenarios. This study addresses these issues by proposing a single-camera-based method with deep learning to measure the three-dimensional velocity field of granular flow. We constructed a complete measurement system and analyzed the accuracy and performance of the proposed method by comparing the measurement results with those of the traditional DIC algorithm. The results show that the proposed method is very accurate in measuring spatial displacement, with an average error of less than 0.07 mm and a calculation speed that is 1291.67% of the traditional DIC algorithm under the same conditions. Additionally, experiments in a bowl-type vibratory finishing machine demonstrate the feasibility of the proposed method in capturing the three-dimensional flow of granular media. This research not only proposed a novel method for three-dimensional reconstruction and velocity field measurement using a single-color camera, but also demonstrated a way to combine deep learning with traditional optical techniques. It is of great significance to introduce deep learning to improve traditional optical techniques and apply them to practical engineering measurements.

Commercial nanofiltration (NF) membranes based on polyamides may experience a decline in permeation performance after prolonged operation. The short lifespan of NF membranes will lead to waste and additional carbon emissions. Thus, rejuvenating membranes and extending their lifespan seem more meaningful than investigating new materials. In this paper, polyamide NF membranes were modified with various polyphenol monomers to improve their permeation performance. The effects of different polyphenols on pore size, surface morphology, and permeation performance of the NF membranes were thoroughly investigated. After modification with tannic acid, the NF membrane exhibits improved salt rejection while experiencing an acceptable decrease in water flux. It should be noted that the commercial NF membrane element fabricated by Koch can recover its Na2SO4 rejection from 83.0% to 94.2% and demonstrate long-term stability after rejuvenation with tannic acid. Combined with the environmental friendliness of polyphenols, this straightforward modification method has the potential for prolonging the operational lifespan of industrial NF membrane products.

Background: Endometriosis (EMs) is a common chronic inflammatory disease which is characterized by multiple clinical symptoms and high recurrence rate due to the absence of effective therapies. Huayu Jiedu Formula (HYJDF), is a traditional Chinese medicine prescription with five major herbs. It has been used as traditional medicine to treat EMs for more than twenty years and exerted a good therapeutic effect. However, the underlying mechanism is unclear. Here we aim to observe the effects of HYJDF on EMs and investigate the therapeutic mechanism. Methods: The extract components of HYJDF were identified and quantified by an UHPLC-QE-MS method. Network pharmacology was used to obtain the core targets of HYJDF for the treatment of EMs and the specific biologic processes involved. A total of 68 EMs cases were randomly divided into control (gestrinone) and observation (HYJDF) groups. The overall effectiveness, pain scores, cyst-size changes, serum CA125 levels, quality-of-life scores, safety, and adverse events were evaluated before and after treatment. For the mechanism research, DNA methylation-chip analysis was performed to determine the differential genes. EMs mice models and human ectopic stromal cells (ESCs) were treated with HYJDF and its pharmaceutical serum, respectively. The ectopic foci was measured via H&E staining while the expressions of the target genes were verified by real-time PCR and Western blot analysis. The inflammatory cytokine levels in the peritoneal fluid of mice were detected by ELISA. The proliferative potential of cells was analyzed by MTS whereas the apoptosis and cell cycle were determined through flow analysis. Results: The total number of components detected in positive and negative ion modes was 839 and 597, respectively. Network pharmacology suggested that HYJDF treated EMs through DNA methylation. We found that HYJDF and gestrinone exerted good therapeutic effect with no obvious difference, but the HYJDF treatment group had fewer side effects. GATA 6, which was hypomethylated and abundant in endometriotic cells, potently induced inflammatory response. This finding indicated the important role of GATA 6 in EMs development. Moreover, HYJDF ameliorated inflammatory response (i.e., reduced the levels of IL-1β and PGE2 in peritoneal fluid), suppressed ESCs proliferation, and increased cell apoptosis by down-regulating GATA 6 expression. Conclusion: We demonstrated that HYJDF has anti-inflammation activity and increased cell apoptosis through the reduction of GATA 6 expression in ectopic tissues, which showed good therapeutic effect without any obvious side effects. These findings suggest that HYJDF may be a new and efficient traditional Chinese medicine for the treatment of EMs.

The research field of Information Retrieval (IR) has evolved significantly, expanding beyond traditional search to meet diverse user information needs. Recently, Large Language Models (LLMs) have demonstrated exceptional capabilities in text understanding, generation, and knowledge inference, opening up exciting avenues for IR research. LLMs not only facilitate generative retrieval but also offer improved solutions for user understanding, model evaluation, and user-system interactions. More importantly, the synergistic relationship among IR models, LLMs, and humans forms a new technical paradigm that is more powerful for information seeking. IR models provide real-time and relevant information, LLMs contribute internal knowledge, and humans play a central role of demanders and evaluators to the reliability of information services. Nevertheless, significant challenges exist, including computational costs, credibility concerns, domain-specific limitations, and ethical considerations. To thoroughly discuss the transformative impact of LLMs on IR research, the Chinese IR community conducted a strategic workshop in April 2023, yielding valuable insights. This paper provides a summary of the workshop’s outcomes, including the rethinking of IR’s core values, the mutual enhancement of LLMs and IR, the proposal of a novel IR technical paradigm, and open challenges.

Diabetes mellitus is a chronic heterogeneous metabolic disease characterized primarily by hyperglycemia due to impaired insulin secretion or impaired insulin efficacy. In recent years, a number of novel point-of-care platforms have been developed for sustained and controlled drug delivery. These platforms allow the patients to ingest insulin via transbuccal, nasal, inhalation, transdermal or subcutaneous routes, thereby effectively releasing insulin molecules the need for inconvenient and frequent needle injections. There are several issues needed to be addressed in developing such as platform: How many routes of administration are available for a point-of-care medication platform? What device components and configurations are available? What is the status of their application? This review will highlight our early attempts to address these questions. It is expected this review could provide a comprehensive overview of the medication platforms for diabetes, as well as open new avenues for developing the next-generation drug delivery devices for patients with diabetes.

The development of simple sensing platforms for evaluating the oral conditions has attracted great attentions for healthcare. Saliva or toothpaste contains various analytes that can indicate health conditions. A salivary glucose sensing platform can provide a convenient and non-invasive alternative detection approach for diabetic patients. Toothbrush is used every day, and it has an easy access to saliva biomarker and toothpaste residues. Here, we demonstrate for the first time an amperometric biosensor on a toothbrush, using glucose as a typical analyte. The carbon graphite ink and the Ag/AgCl ink are painted on a toothbrush as the sensing electrodes, followed by the enzyme immobilization. The sensor shows an excellent detection performance for glucose with a concentration ranging from 0.18 mM to 5.22 mM and a short detection time of less than 5 min. The sensor is promising for the non-invasive monitoring of salivary glucose levels in diabetic patients when they brush their teeth. We anticipate that these results would open up exciting opportunities for developing new toothbrush sensors, as well as advance related healthcare applications.

BackgroundAs rare diseases (RDs) receive increasing attention, obtaining accurate RD incidence estimates has become an essential concern in public health. Since RDs are difficult to diagnose, include diverse types, and have scarce cases, traditional epidemiological methods are costly in RD registries. With the development of the internet, users have become accustomed to searching for disease-related information through search engines before seeking medical treatment. Therefore, online search data provide a new source for estimating RD incidences. ObjectiveThe aim of this study was to estimate the incidences of multiple RDs in distinct regions of China with online search data. MethodsOur research scale included 15 RDs in China from 2016 to 2019. The online search data were obtained from Sogou, one of the top 3 commercial search engines in China. By matching to multilevel keywords related to 15 RDs during the 4 years, we retrieved keyword-matched RD-related queries. The queries used before and after the keyword-matched queries formed the basis of the RD-related search sessions. A two-step method was developed to estimate RD incidences with users’ intents conveyed by the sessions. In the first step, a combination of long short-term memory and multilayer perceptron algorithms was used to predict whether the intents of search sessions were RD-concerned, news-concerned, or others. The second step utilized a linear regression (LR) model to estimate the incidences of multiple RDs in distinct regions based on the RD- and news-concerned session numbers. For evaluation, the estimated incidences were compared with RD incidences collected from China’s national multicenter clinical database of RDs. The root mean square error (RMSE) and relative error rate (RER) were used as the evaluation metrics. ResultsThe RD-related online data included 2,749,257 queries and 1,769,986 sessions from 1,380,186 users from 2016 to 2019. The best LR model with sessions as the input estimated the RD incidences with an RMSE of 0.017 (95% CI 0.016-0.017) and an RER of 0.365 (95% CI 0.341-0.388). The best LR model with queries as input had an RMSE of 0.023 (95% CI 0.017-0.029) and an RER of 0.511 (95% CI 0.377-0.645). Compared with queries, using session intents achieved an error decrease of 28.57% in terms of the RER (P=.01). Analysis of different RDs and regions showed that session input was more suitable for estimating the incidences of most diseases (14 of 15 RDs). Moreover, examples focusing on two RDs showed that news-concerned session intents reflected news of an outbreak and helped correct the overestimation of incidences. Experiments on RD types further indicated that type had no significant influence on the RD estimation task. ConclusionsThis work sheds light on a novel method for rapid estimation of RD incidences in the internet era, and demonstrates that search session intents were especially helpful for the estimation. The proposed two-step estimation method could be a valuable supplement to the traditional registry for understanding RDs, planning policies, and allocating medical resources. The utilization of search sessions in disease detection and estimation could be transferred to infoveillance of large-scale epidemics or chronic diseases.

Traumatic brain injury (TBI) is the main cause of driver death in electric two-wheeler accidents in China. Traumatic brain injury not only brings great threat to people's life safety, but also causes great economic losses in the process of national economic and social development. In this study, a head fluid–structure coupling finite element model was combined with a multi-rigid dummy body to form a finite element and multi-rigid body coupling model of an electric two-wheeler driver. Moreover, a human–vehicle-to-road combined system model was established that included a multi-rigid body two-wheeler model, a multi-rigid body vehicle model, and a road model, which is verified by an actual accident information. According to some simulation tests, moderate and severe nerve injuries may have happened to the driver although the HIC(Head Injury Criteria, common used in vehcile collision injury) is less than 1000. The result shows that the maximum pressure of the simulation result is 455.27 kPa, which exceeds the critical value of brain contusion. The overall relative error between simulation results and actual accident results is less than 10%. The driver model, especially the head model, can accurately simulate the bicyclist head injury and thereby provide a theoretical basis for the traffic injury assessment.

A compact on-chip dual-band bandpass filter (BPF) at millimeter-wave frequencies is proposed in 0.15- ${\mu }\text{m}$ GaAs technology. To understand the working mechanism of the BPF, an LC equivalent circuit model is presented and analyzed for position estimation of the transmission zeros and poles. For demonstration, an on-chip BPF example is fabricated and tested, whose simulation and measurement are in good agreement. There are two frequency bands at 60.2 and 79.7 GHz with bandwidths of 9% and 6.8%, respectively. The chip, excluding the feedings, is only 0.304 mm $\times0.464$ mm.

In this study, a multi-layer pervaporation composite membrane was prepared by spray-coating a hydrophilic layer consisting of poly(allylamine hydrochloride) (PAH)/polyvinyl alcohol (PVA)/trimesic acid (BTA) onto a polyethersulfone (PES) porous substrate. The presence of amine groups facilitated the transport of water molecules, enabling the composite membrane to exhibit excellent water/ethanol separation properties. When a feed solution consisting of 90 ​wt% ethanol and 10 ​wt% water was dehydrated using the PV membrane at 70 ​°C, a flux of 1.46 ​kg ​m−2 ​h−1 with a water/ethanol separation factor of 3300 was realized. In addition, after coating a 267 ​nm silicone rubber layer on top of the membrane, the separation factor was further increased by 70.79 % to 5285, while the flux was slightly decreased by 12.33 % to 1.28 ​kg ​m−2 ​h−1. This was because the hydrophobic silicone rubber layer reduced the water swelling effect of the selective layer and hindered the permeation of ethanol-water coupling molecules, resulting in a reduction in the ethanol flux of the composite membrane and an improvement in the separation factor. This simple but effective method to improve dehydration properties was very useful for fabricating PV composite membranes.

The oxygen octahedral rotation (OOR) forms fundamental atomic distortions and symmetries in perovskite oxides and definitely determines their properties and functionalities. Therefore, epitaxial strain and interfacial structural coupling engineering have been developed to modulate the OOR patterns and explore novel properties, but it is difficult to distinguish the 2 mechanisms. Here, different symmetries are induced in Na0.5Bi0.5TiO3 (NBT) epitaxial films by interfacial oxygen octahedral coupling rather than epitaxial strain. The NBT film grown on the Nb:SrTiO3 substrate exhibits a paraelectric tetragonal phase, while with La0.5Sr0.5MnO3 as a buffer layer, a monoclinic phase and robust ferroelectricity are obtained, with a remanent polarization of 42 μC cm−2 and a breakdown strength of 7.89 MV cm−1, which are the highest record among NBT-based films. Moreover, the interfacial oxygen octahedral coupling effect is demonstrated to propagate to the entire thickness of the film, suggesting an intriguing long-range effect. This work provides a deep insight into understanding the structure modulation in perovskite heterostructures and an important avenue for achieving unique functionalities.

Nanofiltration has gained increasing attention in lithium extraction from salt lake brine with high Mg2+/Li+ ratio. However, conventional nanofiltration membranes with negatively charged surfaces suffer from low Mg2+/Li+ selectivity. Herein, positive nanofiltration membranes with high charge density were fabricated via a two-step charge enhancement strategy. High concentration of polyethylenimine was used as the aqueous monomer to ensure the abundant amino groups on the membrane surface. To further enhance the electro-positivity, 2, 3-epoxypropyl trimethyl ammonium chloride was grafted through ring-opening reactions. The as-obtained membranes demonstrated positive zeta potentials over a large pH range (3-10), leading to significantly strengthened Donnan exclusion for Mg2+. The membrane rejection to MgCl2 was up to 99.3% while the rejection to LiCl was only ∼30%. The Mg2+/Li ​+ ​separation factor was 167 when filtration simulated brine with a Mg2+/Li+ ratio of 20 (2000 ​ppm MgCl2 and LiCl mixture), which is the highest value achieved among polyamide-based nanofiltration membranes. In addition, the membranes exhibited good stability in 40 ​h’ continuous testing. The modification strategy proposed in the present work is highly compatible with current industrial membrane preparation processes and easy to scale up with cost effectiveness.

Titanium nitride (TiN), with its tunable work function, serves as an electrode metal in the scaling fin-type field-effect transistor and plays the key role for low threshold operation. Measuring the effective work function of thin TiN films is desirable for rapid evaluation before device fabrication. In this work, Kelvin probe force microscopy is applied to study the impact of various factors on the surface potential of TiN films with an uncertainty below 30 mV. By scraping and gauging the potential evolvement of TiN in different circumstances, it is revealed that the surface effect is the major obstacle to determine the work function of the as-deposited TiN. For thick films, the potential drops over 530 mV for a fresh TiN surface relative to that of an aged one. For TiN films thinner than 5 nm, the potential changes by 290 mV due to surface oxidation. This enables a quantitative assessment on the effective work function as well as the surface charge density of TiN films.

Abstract Because few well-preserved hydrothermal chimneys have been found in terrestrial sedimentary rocks, research on paleo-thermal vents in geological history is relatively sparse. In this study, we present our original discovery of “hydrothermal chimneys” from the Chang 7 source rocks of the Triassic Yanchang Formation in the Ordos Basin, China, and provide the best evidence for deciphering hydrothermal activity preserved in the geological record (i.e., sedimentary rocks). Three possible chimney samples (i.e., samples 1551.6, 1551.6–2 and 1574.4) were collected for this study; they were interbedded with mudstones and oil shales, indicative of a deep-lake sedimentary environment. All three samples consist mainly of anhydrite, pyrite, and dolomite with the formation of mineral zoning across the walls of these structures, suggesting a sulfate-dominated stage and a carbonate-sulfide replacement stage. Moreover, their in situ geochemistry is characterized by high Eu, U, Th, Sr, Mn and U/Th ratios, which are typical indicators of hydrothermal vents. In addition, their S isotopes range from 7.89% to 10.88%, near the values of magma sulfur, implying a possible magmatic trigger for these hydrothermal vents. All this evidence shows that the Triassic sedimentary rocks of the Ordos Basin probably contain hydrothermal chimneys. Comparing ancient hydrothermal chimneys to modern hydrothermal chimneys, we should note the important implications of ancient chimneys; their formation mechanism may have been related to oil production, and they are possible indicators for future oil investigations. Further, they have great significance for studying the hydrothermal properties of primary dolomite.

Abstract Diabetes is a prevalent chronic metabolic disease with multiple clinical manifestations and complications, and it is among the leading causes of death. Painless and continuous monitoring of interstitial glucose is highly desirable for diabetes management. Here we unprecedentedly show continuous monitoring of diabetes with an integrated microneedle biosensing device. The device was manufactured with a 3D printing process, a microfabrication process, an electroplating process, and an enzyme immobilization step. The device was inserted into the dermis layer of mouse skin and showed accurate sensing performance for monitoring subcutaneous glucose levels in normal or diabetic mice. The detection results were highly correlated with those obtained from a commercial blood glucose meter. We anticipate that the study could open exciting avenues for monitoring and managing diabetes, alongside fundamental studies of subcutaneous electronic devices.

Diabetes is a highly prevalent and chronic metabolic disease with a multifactorial etiology and various clinical manifestations. The point-of-care sensing platforms, as miniaturized devices being portable or worn on the body, are ideal approaches for monitoring diabetes, and can significantly improve the life qualities of diabetes patients with great convenience and comfort. In recent years, there have been many attempts for developing these miniaturized platforms. To successfully develop a point-of-care sensing platform for diabetes, there are several interesting questions: What are the mechanisms for sensing diabetes? How many biofluids are there for monitoring diabetes? Which type of biofluids could provide an accurate detection? What are the configurations of the sensing devices for each type of biofluid? Which is the current status for the development of the sensing devices? Which are the commercial devices for monitoring diabetes? This review will highlight our early attempts for addressing these questions. We believe this review could open up exciting opportunities for the development of the next-generation sensing devices for monitoring diabetes, as well as providing the diagnosis and monitoring methods for diabetes patients.

ObjectiveTo observe the impact of insufficient exogenous and/or endogenous serine on selenoprotein expression and health of pregnant rats and their offspring.MethodExperiment 1 was conducted in male rats, in which the dose-dependent effects of serine on selenoprotein expression and thyroid hormones (T3, T4 and TSH) were investigated by feeding either a serine adequate diet (20C), serine-deprived diet (20CSD) or 20CSD with different serine levels (0.5, 1.0, and 2.0 times the amount of serine in 20C). In experiment 2, a PHGDH inhibitor was administrated to pregnant rats fed either 20C or 20CSD. Blood and organ tissues of pregnant rats and offspring were subjected to the analyses of thyroid hormone, serine and homocysteine and GPx3 and SELENOP in plasma and expression of GPx1 and DIO1, 2 in tissues respectively.ResultIn experiment 1, plasma SELENOP and GPx3 levels in adult male rats increased with the increasing dose of serine. Immunohistochemical results showed that GPx1 expression in liver and kidney of male rats also increased with increasing serine supplementation. Amongst all diet groups, only male rats fed 20CSD had significantly lower plasma TSH and T4 levels (P < 0.05). In experiment 2, GPx1 and DIO2 expression in the liver and kidney were suppressed in pregnant rats administered with a PHGDH compared to those who were not (P < 0.05). There were no significant differences in plasma T4 and T3 amongst all diet groups (P > 0.05). Also, offspring born to pregnant rats administered with a PHGDH inhibitor exhibited slower growth rates and hyperhomocysteinemia compared to offspring from mothers not administered with the inhibitor (P < 0.05). Conclusions: Insufficient exogenous serine through the diet decreased selenoprotein synthesis in adult male rats. However, this was not observed in pregnant rats, whereby exogenous or endogenous serine deficiency had no effect on the selenoprotein levels. A possible explanation is that dams may have an adaptive mechanism to limit maternal serine utilization and ensure adequate supply to the fetus.

The exploration of the ocean is essential for the exploitation of marine resources and the sustainable development of human society. In order to assess both the health and the resources of the marine environment, a variety of chemical and biological sampling is needed. Traditionally, marine samples are collected on site and transported to a laboratory for analysis. Analytical methods are often tedious, and it is difficult to know the in situ real-time status. This review provides a comprehensive summary of the development of in situ chemical and biological sensors for the typical compounds in the ocean, including methane, radon, ferrous ion, carbon dioxide, microorganisms, pollutants, nutrients and seafood. Different types of sensors for each compound are highlighted, such as novel electrochemical and optical sensors. Commercial status of different sensors is introduced, and performance of representative sensors is compared and discussed deeply. The advantages and disadvantages of each sensing technique are analyzed and evaluated in detail. Finally, future prospects and work directions are presented, such as the deployment of these in situ sensors on fixed and/or moving platforms, development of microfluidic sensors and exploration of new antifouling materials and methods. This paper could serve as a resource for developing more advanced in situ chemical sensors and biosensors for marine scientific research, as well as related practical applications for monitoring marine resource exploration and exploitation and for environmental protection.

The causes of oil and natural gas formation have long been controversial about organic and inorganic causes. In recent years, the discovery of hydrothermal genesis in different oceans around the world has further provided new thinking for the exploration of oil and gas genesis. On the basis of reviewing the basic theory of organic oil-producing hypothesis, inorganic oil-producing hypothesis and the dispute between the two, authors focused on the characteristics and research progress of hydrothermally derived petroleum and its organic matter. Then combined with the study of hydrothermal jet deposition in the source rocks of Santanghu Basin and Ordos Basin, the following important insights were obtained: ①The organic matter derived from hydrothermal oil is derived from terrestrial higher plants and lower ocean organisms, the latter being thermophilic, poisonous, and high temperature resistant organisms living around hydrothermal vents. ②Hydrothermal oil does not need to be buried to continuously provide heat, and submarine hydrothermal activities provide material and heat for it. ③In the process of physicochemical interaction between organic matter and deep-source thermal material fluid, organic matter is "instantaneously" (short time) pyrolyzed into oil and partially converted into petroleum-like products. The study of hydrothermally oil and its organic matter can not only deepen people's understanding of the causes of oil and gas, but also have great significance for the exploration and development of unconventional oil.

Search engines are widely used in our daily life. Batch evaluation of the performance of search systems to their users has always been an essential issue in the field of information retrieval. However, batch evaluation, which usually compares different search systems based on offline collections, cannot directly take the perception of users to the systems into consideration. Recently, substantial studies have focused on proposing effective evaluation metrics that model user behavior to bring human factors in the loop of Web search evaluation. In this survey, we comprehensively review the development of user behavior modeling for Web search evaluation and related works of different model-based evaluation metrics. From the overview of these metrics, we can see how the assumptions and modeling methods of user behavior have evolved with time. We also show the methods to compare the performances of model-based evaluation metrics in terms of modeling user behavior and measuring user satisfaction. Finally, we briefly discuss some potential future research directions in this field.

Diabetes is a chronic metabolic disease with a high blood glucose level, leading to both seriously acute and chronic complications. The closed-loop system is an ideal system for diabetes management. However, the large size and high cost of the commercial systems restrict their widespread uses. Here, we present for the first time a microtube-based wearable closed-loop minisystem for diabetes management. The closed-loop minisystem includes a biosensing device, an electroosmotic micropump, and a printed circuit board (PCB) with an algorithm. The microtube-based sensing device coated on the outer surface of the microtube is inserted into subcutaneous tissue for detecting interstitial glucose; the current signal for sensing glucose is processed by the PCB to power the electroosmotic micropump intelligently for the delivery of insulin into the subcutaneous tissue via the microtube channel. The closed-loop minisystem worn on a diabetic SD rat can successfully maintain its blood glucose level within a safe level. It is expected that this new closed-loop paradigm could open up new prospects for clinical diabetes management.

The development of a low-cost and portable integrated sensing system for hydrogen peroxide could offer exciting opportunities for the diagnosis of diseases, and environmental monitoring. Arduino is a popular platform with integrated software and hardware, and a large number of open source sensor libraries. Here, we show the development of a new homemade Arduino-based potentiostat and its sensing of hydrogen peroxide. The Arduino-based potentiostat are made with a low cost, and a great flexibility. The new system can successfully perform the chronoamperometry and cyclic voltammetry functions. The system shows an accurate and precise sensing of hydrogen peroxide, and the detection performance of this system is almost the same as that from a commercial potentiostat. We anticipate that the study can open new routes for constructing a variety of electrochemical sensing systems, and towards advanced medical and environmental applications.

This paper intends to provide design selections of hybrid powertrain architectures in 48 V mild hybrid electric vehicles. Based on the location of the electric machine in the driveline, the hybrid powertrain architectures can be categorized into five groups, P0, P1, P2, P3, and P4. This paper uses simulation software to investigate the fuel economy improvements and emission reduction of 48 V mild hybrid electric vehicles with P0, P1, and P2 architectures. A baseline conventional and a 12 V start/stop vehicle models based on the production vehicle are built for comparison. The 48 V battery pack model is based on experimental data including open-circuit voltage and internal resistance of a 20 Ah lithium polymer battery cell. Four standard driving cycles are used to assess the fuel economy and emissions of the vehicle models. With features of engine idle elimination, electric power assist, and regenerative braking, the 48 V P0 and P1 respectively gains average 13.5% and 15.5% simulated fuel economy compared to baseline vehicle. The 48 V P2 enables feature of electric launch/driving and improves the fuel economy by average 18.5% better than baseline vehicle. The 48 V mild hybrid system seems to be one of the promising techniques to meet future fuel economy standards and emission regulations.

For lithium-ion battery thermal management system for electric vehicles, the insertion of metal plates with channels on both sides of a lithium-ion battery is an effective method for a high-temperature cooling. Inspired by the nature spider-web structure, we propose a cold plate with a bionic spider-web channel inside. Based on the heat generation characteristics of the pouch lithium-ion battery at an extreme discharge rate of 12 C, we used an orthogonal experimental design to study the cooling performance of the spider web-channel structure for a lithium-ion battery. Numerical simulation results showed that, among the structural parameters of the spider-web channel, the channel width had the largest influence on the cooling performance of the cold plate, while the channel angle had the smallest influence. The increase in the channel width could not indefinitely enhance the cooling performance of the cold plate. The most suitable structure was obtained at a width of 3 mm. When the channel angle was 120°, the pouch lithium-ion battery could provide the best thermal balance.

Self-awareness is an essential concept in physiology and psychology. Accurate overall self-awareness benefits the development and well being of an individual. The previous research studies on self-awareness mainly collect and analyze data in the laboratory environment through questionnaires, user study, or field research study. However, these methods are usually not real-time and unavailable for daily life applications. Therefore, we propose a new direction of utilizing lifelog for self-awareness. Lifelog records about daily activities are used for analysis, prediction, and intervention on individual physical and psychological status, which can be automatically processed in real-time. With the help of lifelog, ordinary people are able to understand their condition more precisely, get effective personal advice about health, and even discover physical and mental abnormalities at an early stage. As the first step on using lifelog for self-awareness, we learn from the traditional machine learning problems, and summarize a schema on data collection, feature extraction, label tagging, and model learning in the lifelog scenario. The schema provides a flexible and privacy-protected method for lifelog applications. Following the schema, four topics were conducted: sleep quality prediction, personality detection, mood detection and prediction, and depression detection. Experiments on real datasets show encouraging results on these topics, revealing the significant relation between daily activity records and physical and psychological self-awareness. In the end, we discuss the experiment results and limitations in detail and propose an application, Lifelog Recorder, for multi-dimensional self-awareness lifelog data collection.

TikTok is one of the world's most attractive and fastest-growing social media platforms. It has more than 2.6 billion downloads globally and over 100 million users in the US. The “secret weapon” is its unique methodology of discovering and delivering content.On the “For You” feed, TikTok mixes videos of both internet celebrities and newcomers, encourages high-quality creative content according to page views, and promotes new bloggers to share videos with users. The unique aspect is that anyone has the opportunity to spring into fame on the feed. Through TikTok's recommendation algorithm, videos are continuously recommended to users with similar interests or attributes as video bloggers, thus allowing high-quality creative content to be disseminated quickly. The TikTok recommendation algorithm does not take video blogger's fanbase or popularity into major consideration. In addition to the candidate video title, audio, and tags, the algorithm integrates the content of the user's uploaded videos, and the categories of videos liked by the user. TikTok's skills at enhancing user loyalty are impressive, which can not only accurately recommend videos of interest to users, but also assist them in expanding into new intersecting areas.①① Original source in Chinese: M. Zhang, Y. Liu, TikTok recommendation algorithms, Bulletin of National Natural Science Foundation of China. 35 (3) (2021) 415-416.

The nail penetration test has been widely adopted as a battery safety test for reproducing internal short-circuits. In this paper, the effects of cell initial State-of-Charge (SOC) and penetration location on variations in cell temperature and terminal voltage during penetration tests are investigated. Three different initial SOCs (10%, 50%, and 90%) and three different penetration locations (one is at the center of the cell, the other two are close to the edge of the cell) are used in the tests. Once the steel cone starts to penetrate the cell, the cell terminal voltage starts to drop due to the internal short-circuit. The penetration tests with higher initial cell SOCs have larger cell surface temperature increases during the tests. Also, the penetration location always has the highest temperature increment during all penetration tests, which means the heat source is always at the penetration location. The absolute temperature increment at the penetration location is always higher when the penetration is close to the edge of the cell, compared to when the penetration is at the center of the cell. The heat generated at the edges of the cell is more difficult to dissipate. Additionally, a battery cell internal short-circuit model with different penetration locations is built in ANSYS Fluent, based on the specifications and experimental data of the tested battery cells. The model is validated with an acceptable discrepancy range by using the experimental data. Simulated data shows that the temperature gradually reduces from penetration locations to their surroundings. The gradients of the temperature distributions are much larger closer to the penetration locations. Overall, this paper provides detailed information on the temperature and terminal voltage variations of a lithium-ion polymer battery cell with large capacity and high power under penetration tests. The presented information can be used for assessing the safety of the onboard battery pack of electric vehicles.

Based on core and thin section observation, and combined with X-ray diffraction, electron probe and geochemical analysis, the characteristics and origin of tuff tight oil of the Permian Lucaogou Formation in the Jimusaer depression, Junggar Basin were examined. There are tuff, tuffite and tuffaceous dolomite interlaid in the sedimentary rocks of the Lucaogou Formation. The alkali feldspar and quartz in the tuff are rich in strontium, which, according to mineral geochemical analysis, are originated from alkaline-peralkaline magmatic rocks. The Sr isotope ratio (87Sr/86Sr) of dolomite is similar to that of mantle, which shows minerals of tuff were formed in volcanism-related hydrothermal environments. High Sr/Ba and δ13C of dolomite, and occurrence of halite under microscope suggest that the Lucaogou Formation was deposited in high salinity environment. High content of magnesium and iron ions related to volcanism and hydrotherm, and high salinity environment contributed to the precipitation of dolomite. The distribution of tight oil, organic matter abundance of source rock and reservoir physical properties show that it is the rich nutrients provided by volcanic activity that controlled the formation of high abundance source rock; tuff, tuffaceous dolomite with plenty of residual inter-granular pores and dissolved pores are favorable reservoir sections; and tuff controls the formation and distribution of tight oil. Key words: Junggar Basin, Jimusaer Depression, tuff, tight oil, geological characteristics

In some hazardous or inaccessible applications, such as earthquake rescue, as a substitute for mankind, robots are expected to perform missions reliably. Unfortunately, the failure of components is difficult to avoid due to the complexity of robot composition and the interference of the environment. Thus, improving the reliability of robots is a crucial problem. The hexapod robot has redundant degrees of freedom due to its multiple joints, making it possible to tolerate the failure of one leg. In this paper, the Fault-Tolerant Tripod (F-TT) gait dealing with the failure of one leg is researched. The Denavit–Hartenberg (D-H) method is exploited to establish a kinematic model for the hexapod robot, the Jacobian matrix is analyzed, and it is proved that the body can be controlled when three legs are supported. Then, an F-TT gait phase sequence planning method based on a stability margin is established, and a method to improve stability is proposed. The trajectory for the center of gravity (COG) and foot is studied. Finally, a simulation model and prototype robot experiments are developed, and the effectiveness of the proposed method is verified.

Modelling, simulation, and validation of the 12-volt battery pack using a 20 Ah lithium−nickel−manganese−cobalt−oxide cell is presented in this paper. The cell characteristics influenced by thermal effects are also considered in the modelling. The parameters normalized directly from a single cell experiment are foundations of the model. This approach provides a systematic integration of actual cell monitoring with a module model that contains four cells connected in series. The validated battery module model then is utilized to form a high fidelity 80 Ah 12-volt battery pack with 14.4 V nominal voltage. The battery cell thermal effectiveness and battery module management system functions are constructed in the MATLAB/Simulink platform. The experimental tests are carried out in an industry-scale setup with cycler unit, temperature control chamber, and computer-controlled software for battery testing. As the 12-volt lithium-ion battery packs might be ready for mainstream adoption in automotive starting−lighting−ignition (SLI), stop−start engine idling elimination, and stationary energy storage applications, this paper investigates the influence of ambient temperature and charging/discharging currents on the battery performance in terms of discharging voltage and usable capacity. The proposed simulation model provides design guidelines for lithium-ion polymer batteries in electrified vehicles and stationary electric energy storage applications.

In order to meet the demands of small race car dynamics simulation, a new method of parameter identification in the Magic Formula tire model is presented in this work, based on an analysis of the Magic Formula tire model structure. A high-precision tire model used for vehicle dynamics simulation is established via this method. It is difficult for students to build a high-precision tire model because of the complexity of widely used tire models such as Magic Formula and UniTire. At a pure side slip condition, building a lateral force model is an example, which illustrate the utilization of a multilayer feed-forward neural network to build an intelligent tire model conveniently. In order to fully understand the difference between the two models, a two-degrees-of-freedom (2 DOF) vehicle model is established. The advantages, disadvantages, and applicable scope of the two tire models are discussed after comparing the simulation results of the 2 DOF model with the Magic Formula and intelligent tire model.

This study firstly analyses the driver’s manipulation behaviour and relates the different components of the driver model. Then, a model controlling the driver directions is built according to the prediction-follower theory with the aim of improving the point search algorithm. A model of the driving system of an electric vehicle is used to establish the longitudinal speed control model of the driver by using a feedforward-PID feedback control strategy. Our approach is to release the coupling between direction and speed control and build an integrated model that includes the direction and speed for an arbitrary path. Finally, the characteristics of an actual racing track are considered to establish the fastest driver control model. We simulated the typical operating conditions of our driver operation model. The simulation confirmed the effectiveness of the improved predictive point search algorithm and the integrated driver model to control the direction and speed for an arbitrary path.

The development of new bioelectronic platforms for direct interactions with oral fluid could open up significant opportunities for healthcare monitoring. A tongue depressor is a widely used medical tool that is inserted into the mouth, where it comes into close contact with saliva. Glucose is a typical salivary biomarker. Herein, we report—for the first time—a tongue depressor-based biosensor for the detection of glucose in both phosphate buffer and real human saliva. Carbon nanotubes (CNTs) are attractive electronic materials, with excellent electrochemical properties. The sensor is constructed by printing CNTs and silver/silver chloride (Ag/AgCl) to form three electrodes in an electrochemical cell: Working, reference, and counter electrodes. The enzyme glucose oxidase (GOD) is immobilized on the working electrode. The glucose detection performance of the sensor is excellent, with a detection range of 7.3 μM to 6 mM. The glucose detection time is about 3 min. The discretion between healthy people’s and simulated diabetic patients’ salivary samples is clear and easy to tell. We anticipate that the biosensor could open up new opportunities for the monitoring of salivary biomarkers and advance healthcare applications.