Search

Abstract Mental health issues have increased substantially since the onset of the COVID-19 pandemic. However, health policymakers do not have adequate data and tools to predict mental health demand, especially amid a crisis. Using time-series data collected in Singapore, this study examines if and how algorithmically measured emotion indicators from Twitter posts can help forecast emergency mental health needs. We measured the mental health needs during 549 days from 1 July 2020 to 31 December 2021 using the public’s daily visits to the emergency room of the country’s largest psychiatric hospital and the number of users with “crisis” state assessed through a government-initiated online mental health self-help portal. Pairwise Granger-causality tests covering lag length from 1 day to 5 days indicated that forecast models using Twitter joy, anger and sadness emotions as predictors perform significantly better than baseline models using past mental health needs data alone (e.g., Joy Intensity on IMH Visits, χ2 = 14·9, P < ·001***; Sadness Count on Mindline Crisis, χ2 = 4·6, P = ·031*, with a one-day lag length). The findings highlight the potential of new early indicators for tracking emerging public mental health needs.

Abstract Purpose To explore the predictive potential of intratumoral and multiregion peritumoral radiomics features extracted from multiparametric MRI for predicting pathological differentiation in hepatocellular carcinoma (HCC) patients. Methods A total of 265 patients with 277 HCCs (training cohort n = 193, validation cohort n = 84) who underwent preoperative MRI were retrospectively analyzed. The risk factors identified through stepwise regression analysis were utilized to construct a clinical model. Radiomics models based on MRI (arterial phase, portal venous phase, delayed phase) across various regions (entire tumor, Peri_5mm, Peri_10mm, Peri_20mm) were developed using the LASSO approach. The features obtained from the intratumoral region and the optimal peritumoral region were combined to design the IntraPeri fusion model. Model performance was assessed using the area under the curve (AUC). Results Larger size, non-smooth margins, and mosaic architecture were risk factors for poorly differentiated HCC (pHCC). The clinical model achieved AUCs of 0.77 and 0.73 in the training and validation cohorts, respectively, while the intratumoral model achieved corresponding AUC values of 0.92 and 0.82. The Peri_10mm model demonstrated superior performance to the Peri_5mm and Peri_20mm models, with AUC values of 0.87 vs. 0.84 vs. 0.73 in the training cohort and 0.80 vs. 0.77 vs. 0.68 in the validation cohort, respectively. The IntraPeri model exhibited remarkable AUC values of 0.95 and 0.86 in predicting pHCC in the training and validation cohorts, respectively. Conclusions Our study highlights the potential of a multiparametric MRI-based radiomic model that integrates intratumoral and peritumoral features as a tool for predicting HCC differentiation. Critical relevance statement Both clinical and multiparametric MRI-based radiomic models, particularly the intratumoral radiomic model, are non-invasive tools for predicting HCC differentiation. Importantly, the IntraPeri fusion model exhibited remarkable predictiveness for individualized HCC differentiation. Key points • Both the intratumoral radiomics model and clinical features were useful for predicting HCC differentiation. • The Peri_10mm radiomics model demonstrated better diagnostic ability than other peritumoral region-based models. • The IntraPeri radiomics fusion model outperformed the other models for predicting HCC differentiation. Graphical Abstract

BackgroundSingapore, like the rest of Asia, faces persistent challenges to mental health promotion, including stigma around unwellness and seeking treatment and a lack of trained mental health personnel. The COVID-19 pandemic, which created a surge in mental health care needs and simultaneously accelerated the adoption of digital health solutions, revealed a new opportunity to quickly scale innovative solutions in the region. ObjectiveIn June 2020, the Singaporean government launched mindline.sg, an anonymous digital mental health resource website that has grown to include >500 curated local mental health resources, a clinically validated self-assessment tool for depression and anxiety, an artificial intelligence (AI) chatbot from Wysa designed to deliver digital therapeutic exercises, and a tailored version of the website for working adults called mindline at work. The goal of the platform is to empower Singapore residents to take charge of their own mental health and to be able to offer basic support to those around them through the ease and convenience of a barrier-free digital solution. MethodsWebsite use is measured through click-level data analytics captured via Google Analytics and custom application programming interfaces, which in turn drive a customized analytics infrastructure based on the open-source platforms Titanium Database and Metabase. Unique, nonbounced (users that do not immediately navigate away from the site), engaged, and return users are reported. ResultsIn the 2 years following launch (July 1, 2020, through June 30, 2022), the website received >447,000 visitors (approximately 15% of the target population of 3 million), 62.02% (277,727/447,783) of whom explored the site or engaged with resources (referred to as nonbounced visitors); 10.54% (29,271/277,727) of those nonbounced visitors returned. The most popular features on the platform were the dialogue-based therapeutic exercises delivered by the chatbot and the self-assessment tool, which were used by 25.54% (67,626/264,758) and 11.69% (32,469/277,727) of nonbounced visitors. On mindline at work, the rates of nonbounced visitors who engaged extensively (ie, spent ≥40 seconds exploring resources) and who returned were 51.56% (22,474/43,588) and 13.43% (5,853/43,588) over a year, respectively, compared to 30.9% (42,829/138,626) and 9.97% (13,822/138,626), respectively, on the generic mindline.sg site in the same year. ConclusionsThe site has achieved desired reach and has seen a strong growth rate in the number of visitors, which required substantial and sustained digital marketing campaigns and strategic outreach partnerships. The site was careful to preserve anonymity, limiting the detail of analytics. The good levels of overall adoption encourage us to believe that mild to moderate mental health conditions and the social factors that underly them are amenable to digital interventions. While mindline.sg was primarily used in Singapore, we believe that similar solutions with local customization are widely and globally applicable.

Objective: In order to improve the situation that existing fruit recognition and classification methods rely on manual operation and complex equipment. Methods: A lightweight model YOLO-FFD (YOLO with fruit and freshen detection) was proposed, which based on the YOLOv5 framework. Firstly, LightweightC3 was designed as the basic unit of the backbone feature extraction network based on the depth separable convolution and GELU activation function, which reduced the number of model parameters and computation, and speeds up the convergence of the model. Secondly, EnhancedC3, a large kernel depth separable convolution module, was used to improve the neck of the original model, suppressed information loss and enhance the feature fusion ability of the model, so as to improve the detection accuracy of the model. Finally, GSConv was used to replace the common convolution in the feature fusion network to further lighten the model. Results: The experimental results showed that the average accuracy of the proposed model reached 96.12%, the FPS on RTX 3090 was 172, and the speed on the embedded Jetson TX2 was 20 frames per second. Compared with the original YOLOv5 model, the mAP was improved by 2.21%, the calculation amount was reduced by 26%, and the speed was increased by two times. Conclusion: YOLO-FFD can meet the requirement of identifying fruit varieties and freshness, and improve the falsely detection and missing detection in complex scenes.

Abstract Following the Materials Genome Initiative project, materials research has embarked a new research paradigm centered around material repositories, significantly accelerating the discovery of novel materials, such as thermoelectrics. Thermoelectric materials, capable of directly converting heat into electricity, are garnering increasing attention in applications like waste heat recovery and refrigeration. To facilitate research in this emerging paradigm, we have established the Materials Hub with Three‐Dimensional Structures (MatHub‐3d) repository, which serves as the foundation for high‐throughput (HTP) calculations, property analysis, and the design of thermoelectric materials. In this review, we summarize recent advancements in thermoelectric materials powered by the MatHub‐3d, specifically HTP calculations of transport properties and material design on key factors. For HTP calculations, we develop the electrical transport package for HTP purpose, and utilize it for materials screening. In some works, we investigate the relationship between transport properties and chemical bonds for particular types of thermoelectric compounds based on HTP results, enhancing the fundamental understanding about interested compounds. In our work associated with material design, we primarily utilize key factors beyond transport properties to further expedite materials screening and speedily identify specific materials for further theoretical/experimental analyses. Finally, we discuss the future developments of the MatHub‐3d and the evolving directions of database‐driven thermoelectric research.

Abstract Background Several previous studies demonstrated that the combination of self-expandable metallic stents (SEMS) and 125I seed implantation might prolong stent patency and obtain survival benefits for malignant obstructive jaundice (MOJ) patients. However, these studies rarely mentioned a comparison between CT-guided intratumoral 125I seed implantation and intraluminal 125I seed strand insertion combined with stenting for the management of MOJ. This study aimed to further evaluate the safety and efficacy of SEMS combined with 125I brachytherapy in the management of unresectable MOJ. Methods Fifty-nine patients with unresectable MOJ were retrospectively included from March 2018 to June 2021. The main therapeutic outcomes were evaluated in terms of stent patency, and overall survival. Cumulative stent patency and overall survival rates were calculated by Kaplan–Meier survival analysis. Both clinical and treatment factors associated with survival were analyzed. Results Technical success was achieved in all patients. The clinical success rate was 94% (32/34) in the seeds group and 92% (23/25) in the control group, no significant difference was found (p =1.000). The median duration of stent patency was significantly longer in the 125I brachytherapy group compared with the control group (289 days vs. 88 days, respectively, p =0.001). The 125I brachytherapy group demonstrated a significantly better median overall survival rate than the control group (221 days vs. 78 days, respectively, p =0.001). In multivariate analysis, stents with 125I brachytherapy (p =0.004) was a significant favorable prognostic factor that affected patient survival. No significant difference was observed between CT-guided 125I seed implantation and 125I seed strand insertion in stent patency (p =0.268), and overall survival (p =0.483). Conclusion SEMS combined with 125I brachytherapy is safe and effective for treating MOJ. 125I brachytherapy may help to maintain stent patency and prolong overall survival. There was no significant difference between CT-guided 125I seed implantation with SEMS and 125I seed strand insertion with SEMS in stent patency and overall survival.

Infrared radiation can reflect the damage of coal and rock under load, and can be used to monitor and prevent the dynamic disaster of coal and rock. But the infrared thermal image generated by the infrared thermal imager has low pixel resolution and large noise, which leads to the detection result being greatly affected by subjective factors. Therefore, the damaged area of the coal body cannot be accurately identified. It has become a trend to combine deep learning with infrared thermal imaging for nondestructive testing. But the research on the identification and detection of coal damage under load by combining deep learning and infrared thermal imaging is relatively few. In order to solve the above problems, a segmentation method of the abnormal area of coal infrared thermal image based on multi-scale channel attention module (MS-CAM) U-Net model is proposed. The MS-CAM is introduced into the encoder of the traditional U-Net model, and the U-Net model structure based on MS-CAM is designed. The model not only pays attention to the major characteristics of the coal infrared thermal image abnormal area, but also pays attention to the small target characteristics of the abnormal area, so as to improve the segmentation accuracy of the abnormal area. In order to reduce the influence of the lack of coal infrared thermal image data set on the accuracy and applicability of the model, the data enhancement operation is carried out on the created coal infrared thermal image data set. The MS-CAM-based U-Net model is pre-trained by using the MS COCO data set. Then the coal infrared thermal image data set is used for training to obtain the final network weight. The experimental result shows that the method can effectively segment the abnormal areas of the infrared thermal image of the coal body. The accuracy rate, the F1 score, the Dice coefficient and the average cross-combination ratio are 94.75%, 94.94%, 94.65%, and 90. 03% respectively. The results are superior to the Deeplab model, the U-Net model and the U-Net model based on the attention mechanism of the SENet.

BackgroundThe website mindline.sg is a stress management and coping website that can be accessed anonymously in Singapore for free. Although designed to serve individuals who are well or have mild depression and anxiety symptoms, mindline.sg may potentially be used by clinicians as an adjunct therapeutic aid for patients with clinically diagnosed mental disorders. ObjectiveThis study aims to determine the perceived usability, acceptability, and usefulness of mindline.sg among individuals with diagnosed mental disorders in a clinical setting. MethodsA cross-sectional study with 173 participants was conducted in the waiting room of a psychiatrist’s office at the National University Hospital in Singapore. Participants waiting for an appointment were given 30 minutes and a simple set of instructions to use three features of mindline.sg. They subsequently answered a set of web-based survey questions via their smartphones, including a 16-item subset of the Post-Study System Usability Questionnaire (PSSUQ) for usability measurement and 5 questions designed to understand the perceived usefulness and acceptability of mindline.sg. Multiple linear regression is used to determine the associated demographic factors with overall PSSUQ score. A chi-square test is performed to investigate associations of psychiatric condition with users’ responses on acceptability and perceived usefulness of mindline.sg. For this study, P

Heavy metals in soils can migrate into the food chain and affect human health. In particular, they can be released into water supplies through interactions between soils and water. It is therefore important to study the concentrations of heavy metals in soils surrounding sources of drinking water, but there is a lack of research in this area. A total of 7656 topsoil samples surrounding the core water source of Danjiangkou Reservoir in China were collected and analyzed for As, Hg and Pb. Moran’s I index and semivariograms were used to analyze the spatial correlation and variation of these heavy metals. The potential ecological risk index was used to evaluate heavy metal pollution. Fifteen natural and human factors were selected to explore the sources of heavy metal pollution using the GeoDetector model. The positive matrix factorization (PMF) model verified the reasonableness of the main factors identified by the GeoDetector model and further quantified two main sources of soil heavy metals. As, Hg and Pb were enriched to varying degrees in the soils. The potential ecological risk of Hg in soils was the most serious, with 24.67% of the area at high or very high risk. As and Pb both had a low potential ecological risk. The results of GeoDetector model and PMF model showed that the contributions of factor 1 (fertilizer application and automobile exhaust emissions) and factor 2(industrial waste) of soil heavy metal pollution were 49.8% and 50.2%, respectively. At last, the zoning control strategies were proposed in order to provide scientific reference for the management of soil heavy metal pollution.

The application of machine learning (ML)-based methods to the study of thermoelectric (TE) materials is promising. Although conventional ML algorithms can achieve high prediction performance, their lack of interpretability severely obstructs researchers from extracting material-oriented insights from ML models. In this work, high ML-based prediction performance was achieved with respect to TE power factors (PFs), and the results were well understood by the SHapley Additive exPlanations (SHAP), a method to identify the correlations between targets and descriptors. We designed a robust PF prediction model for diamond-like compounds via a stacking technique, and the model achieved a coefficient of determination value above 0.95 on the test set. From the SHAP analysis, the PFs were negatively correlated with electronegativity and positively correlated with the descriptor “volume per atom” based on the previously reported dataset. TE domain knowledge was adopted to understand these correlations. This work shows that ML models can achieve high accuracy while exhibiting good interpretability, making them useful for materials scientists.

Certificateless public key cryptosystem combines the advantages of identity-based cryptosystem and traditional PKI public key cryptosystem,overcomes the key escrow problem of identity-based public key cryptosystem and the certificate management problem of PKI system,and has obvious advantages.By analysing the security of a strongly secure certificateless signature scheme proposed by Hassouna,et al,it shows that the scheme cannot resist the attack of falsifying messages and do not use private key generated by system master key to sign.So it is not a certificateless signature scheme.On this basis,an improved certificateless signature scheme is proposed and it proves the scheme can resist the attack of the first class of strong adversaries and the second class of adversaries.In the random oracle model and under the assumption of the Diffie-Hellman problem of the elliptic curve,the improved scheme satisfies the existential forgery.

Measurement(s) structural entity • relaxed crystal structure • density of states • band structure • electrical transport property • equation of states Technology Type(s) density functional theory • computational modeling technique Factor Type(s) material Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.15164577

Background: It is of great importance to predict the early recurrence (ER) of hepatocellular carcinoma (HCC) after hepatectomy using preoperative imaging modalities. Nevertheless, no comparative studies have been conducted to determine which modality, CT or MRI with radiomics analysis, is more effective. Methods: We retrospectively enrolled 119 HCC patients who underwent preoperative CT and MRI. A total of 3776 CT features and 4720 MRI features were extracted from the whole tumor. The minimum redundancy and maximum relevance algorithm (MRMR) and least absolute shrinkage and selection operator (LASSO) regression were applied for feature selection, then support vector machines (SVMs) were applied for model construction. Multivariable logistic regression analysis was employed to construct combined models that integrate clinical–radiological–pathological (CRP) traits and radscore. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used to compare the efficacy of CT, MRI, and CT and MRI models in the test cohort. Results: The CT model and MRI model showed no significant difference in the prediction of ER in HCC patients (p = 0.911). RadiomicsCT&MRI demonstrated a superior predictive performance than either RadiomicsCT or RadiomicsMRI alone (p = 0.032, 0.039). The combined CT and MRI model can significantly stratify patients at high risk of ER (area under the curve (AUC) of 0.951 in the training set and 0.955 in the test set) than the CT model (AUC of 0.894 and 0.784) and the MRI model (AUC of 0.856 and 0.787). DCA demonstrated that the CT and MRI model provided a greater net benefit than the models without radiomics analysis. Conclusions: No significant difference was found in predicting the ER of HCC between CT models and MRI models. However, the multimodal radiomics model derived from CT and MRI can significantly improve the prediction of ER in HCC patients after resection.

Objectives: To assess whether the extension of the flushing interval will increase risks of complications associated with totally implantable venous access port (TIVAP) in the off-treatment period. Methods: A retrospective single-center observational study was performed. Patients with a TIVAP in the off-treatment period that underwent regular flushing in our clinic were included. Data concerning patients and their TIVAPs were recorded. Patient baseline characteristics and TIVAP-related complications were analyzed. Continuous variables were analyzed by ANOVA or the Kruskal-Wallis H test. To compare the occurrence of TIVAP-related complications, the chi-square test was used; if needed, Fisher’s exact test was used. Results: Totally 607 patients were reviewed, and 563 patients were finally included. Thirteen complications were recorded, including 11 cases of catheter occlusion (1.95%), one case of port cannula rotation (0.18%), and one case of catheter tip malposition (0.18%). No device-related infection or venous thrombosis was recorded. Among these patients, the average flushing interval was 35.27 ± 13.09 days. Patients were divided into three groups according to the flushing interval: every 28 days or less (Group 1, n = 133); every 29–44 days (Group 2, n = 350); and every 45 days or more (Group 3, n = 80). No significant difference in catheter-related complications was found among the three groups (P > 0.05). Conclusions: In the TIVAP off-treatment period, patients without any history of TIVAP-related complications during approximately one year can attempt to prolong the flushing interval to more than 4 weeks; we further suggest that 5–6 weeks may be an appropriate option for these patients.

Materials genome methods have played an essential role in accelerating the discovery of high-performance novel materials, and include high-throughput calculation, database construction, and machine learning. Over the past decades, these approaches have been increasingly used in lithium battery materials, solar cells, transparent conductors, and thermoelectrics. Thermoelectrics are functional materials that can directly convert electricity into heat and vice versa, offering new ideas for conventional power generation and refrigeration. The application of high-throughput methods can achieve more efficient screening of new thermoelectric materials and accelerate experimental development. This review summarizes the recent progress in the application of materials genome methods for different thermoelectric materials, such as half-Heuslers, diamond-like structures, oxides, and other materials. Finally, current advances in machine learning for thermoelectrics are discussed. The progress of the theoretical design of thermoelectrics has driven the development of high-performance thermoelectrics.

Based on the hourly monitoring data including meteorological elements and PM2.5 mass concentration in Yancheng from 2017 to 2021, PM2.5 mass concentration variations, influencing factors and source apportionment were studied by the Kolmogorov–Zurbenko filter and Potential Source Contribution Function Analysis (PSCF) method. The results showed that the mass concentration of PM2.5 in Yancheng showed a decreasing trend from 2017 to 2021, with a decline rate of about 33.8% (2017, 44.79 ± 31.22 μg/m3; 2021, 29.66 ± 21.69 μg/m3); the visibility increased by 18.4% (2017, 11.69 ± 6.46 km; 2021,13.8 ± 6.24 km), which is mainly related to emission reduction measures in China. The mass concentration of PM2.5 has significant seasonal variation characteristics, with the highest in winter, reaching 60.61 μg/m3, and the lowest in summer, only 23.11 μg/m3. The diurnal variation of PM2.5 showed a unimodal distribution, and concentration difference is obvious under the influence of land–sea breeze (36.60 μg/m3, easterly wind; 43.57 μg/m3, westerly wind). Meteorological factors have an important impact on the mass concentration of PM2.5, which fluctuates with seasons. It is calculated to have a good fitting relationship between the visibility and PM2.5 concentration, and the correlation decreases with the increase in humidity (−0.71 ~ −0.41). The relatively clean atmosphere under high humidity conditions is also prone to the obstruction to vision. The corresponding PM2.5 concentration varies significantly under different wind directions and wind speeds in Yancheng, and high values mainly come from the northwest–southeast–southwest direction. The potential source regions in autumn are mainly distributed in southwestern Jiangsu and northwestern Zhejiang; the potential source regions in winter are mainly located in southwestern Jiangsu, southern Anhui and northern Jiangxi.

SARS-CoV-2 and influenza have caused substantial health threats. SARS-CoV-2 had caused >0.7 billion reported cases and 6.9 million deaths globally by May 2023, when the World Health Organization (WHO) declared [...]

Most crystalline materials follow the guidelines of T−1 temperature-dependent lattice thermal conductivity (κL) at elevated temperatures. Here, we observe a weak temperature dependence of κL in Mg3Sb2, T−0.48 from theory and T−0.57 from measurements, based on a comprehensive study combining ab initio molecular dynamics calculations and experimental measurements on single crystal Mg3Sb2. These results can be understood in terms of the so-called “phonon renormalization” effects due to the strong temperature dependence of the interatomic force constants (IFCs). The increasing temperature leads to the frequency upshifting for those low-frequency phonons dominating heat transport, and more importantly, the phonon-phonon interactions are weakened. In-depth analysis reveals that the phenomenon is closely related to the temperature-induced asymmetric movements of Mg atoms within MgSb4 tetrahedron. With increasing temperature, these Mg atoms tend to locate at the areas with relatively low force in the force profile, leading to reduced effective 3rd-order IFCs. The locally asymmetrical atomic movements at elevated temperatures can be further treated as an indicator of temperature-induced variations of IFCs and thus relatively strong phonon renormalization. The present work sheds light on the fundamental origins of anomalous temperature dependence of κL in thermoelectrics.

This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1186/s13046-019-1114-2.

Objective. To compare outcomes between laparoscopic spleen-preserving distal pancreatectomy (LSPDP) and open spleen-preserving distal pancreatectomy (OSPDP) for treatment of benign and low-grade malignant tumors of the pancreas and evaluate feasibility and safety of LSPDP. Methods. The clinical data of 53 cases of LSPDP and 44 cases of OSPDP performed between January 2008 and August 2018 were retrospectively analyzed. The clinical outcomes between the two groups were compared. Results. There was no significant difference in preoperative data between the two groups. However, the LSPDP group had statistically significant shorter operative time (145.3±55.9 versus 184.7±33.5, P=0.03) and lesser intraoperative blood loss (150.6±180.8 versus 253.5±76.2, P=0.03) than that of the OSPDP group. Moreover, the LSPDP group also had statistically significant earlier passing of first flatus (2.2±1.4 versus 3.1±1.9, P=0.01), earlier diet intake (2.3±1.8 versus 3.4±2.0, P=0.01), and shorter hospital stay (6.2±7.2 versus 8.8±9.3, 0.04) than that of the OSPDP group. However, postoperative pancreatic fistula (P=0.64) and total postoperative complications (P=0.59) were not significantly different between the groups. The rate of pancreatic fistula and total postoperative complications occurred in 62.5% and 64.5%, respectively, in LSPDP group and, similarly, 70% and 70.0%, respectively, in OSPDP group. Conclusion. This study confirms that LSPDP is safe, feasible, and superior to OSPDP in terms of operative time, intraoperative blood loss, hospital stay, and postoperative recovery. Hence, it is worth popularizing LSPDP for benign and low-grade malignant tumors of the pancreas.

This paper presents the design of a handheld pseudo random coded Ultra-WideBand (UWB) radar for human sensing. The main tasks of the radar are to track the moving human object and extract the human respiratory frequency. In order to achieve perfect penetrability and good range resolution, m sequence with a carrier of 800 MHz is chosen as the transmitting signal. The modulated m-sequence can be generated directly by the high-speed DAC and FPGA to reduce the size of the radar system, and the mean power of the transmitting signal is 5 dBm. The receiver has two receiving channels based on hybrid sampling, the first receiving channel is to sample the reference signal and the second receiving channel is to obtain the radar echo. The real-time pulse compression is computed in parallel with a group of on-chip DSP48E slices in FPGA to improve the scanning rate of the radar system. Additionally, the algorithms of moving target tracking and life detection are implemented using Intel’s micro-processor, and the detection results are sent to the micro displayer fixed on the helmet. The experimental results show that the moving target located at less than 16 m far away from the wall can be tracked, and the respiratory frequency of the static human at less than 14 m far away from the wall can be extracted.

The poor quality and low productivity of cultivated liquorice (Glycyrrhiza uralensis) continues to put pressure on wild plant populations. As arbuscular mycorrhizal fungi are known to support plant growth and in some cases even to enhance the accumulation of valuable molecules in the plant, the effect of Glomus mosseae on the growth and active ingredient contents was evaluated in liquorice plants grown under nutrient deficiency. We created a nutrient-deficient environment by mixing paddy soil, washed river sand, and pumice at a ratio of 1:5:1. Our results showed that the inoculation of pot-grown liquorice plants with G. mosseae significantly increased the shoot and root biomass (by 25- and 17-folds, respectively) and the contents of glycyrrhizic acid, liquiritin, isoliquiritin, and isoliquiritigenin in the main root (by 1.6-, 4.8-, 6.5-, and 4.4-folds, respectively). Both isoliquiritin and isoliquiritigenin were detectable in the lateral roots of the plants inoculated with G. mosseae, but not in plants without G. mosseae inoculation. G. mosseae inoculation improved the features of the root system and increased photosynthetic efficiency of liquorice. The uptake of P and K by liquorice increased when G. mosseae was inoculated, leading to the depletion of these macronutrients in the soil; G. mosseae also improved the availability of Mg, Cu, Zn, and Mn. Based on these results, we concluded that the inoculation of liquorice plants with G. mosseae is beneficial, particularly for those grown in nutrient-deficient soil, and such positive effect is related to the improvement of the root system and an increased photosynthetic efficiency.

Compared with solid solution (SS) Hf0.5Zr0.5O2, HfO2–ZrO2 superlattice (SL) ferroelectric films exhibit enhanced endurance and reduced leakage. However, so far, the underlying physical mechanism is still missing. In this work, first-principle calculations reveal that the superior reliability arises from the precise control in the spatial profile of oxygen vacancy with the stacked structure in SL in which oxygen vacancies (Vo) exhibit different formation energies and different energy profiles in Zr- and Hf-layers. However, Vo have the tendency to migrate and its suppression become critical to maintain the superiority of SL. A low annealing temperature is, therefore, suggested and validated with our fabricated SL- and SS-ferroelectric films with different annealing temperatures. This understanding can pave ways for the optimization in SL ferroelectric films. [ABSTRACT FROM AUTHOR]

Despite the extensive research on HfO2-based thin films, the ferroelectric orthorhombic phase formation remains unclear. This work proposes a physical picture throughout the entire annealing process to describe the phase transition. Subsequently, the phase evolution at various doping and annealing temperatures is illustrated based on a kinetic model formalized from the classical nucleation theory. It is found that the formation of the ferroelectric orthorhombic phase depends not only on a modest doping concentration but also on the thermal activation of the t-to-o phase transition provided by a sufficient annealing temperature. In addition, phase transition rates correlated to the monoclinic phase formation are effectively suppressed by doping. The exploration of combined effects of annealing parameters indicates a more decisive role of the annealing temperature rather than the keeping time for induced ferroelectricity, and the doping impact becomes significant when a critical annealing temperature is reached. This work provides an understanding for exploring the kinetic effect on the phase transition in HfO2-based thin films, which helps improve ferroelectricity in doped HfO2 ferroelectric films. [ABSTRACT FROM AUTHOR]

The electromagnetic interference (EMI) shielding effectiveness (SE) of carbon nanotube (CNT) macro-film that is adhered to common cloth to maintain the light weight, silk-like quality, and smooth surface of the material for EMI shielding is investigated. The results show that a high and stable EMI SE of 48 dB to 57 dB at 40 GHz to 60 GHz was obtained by the macro-film with a thickness of only ∼4 μm. The composite CNT macro-film is easily manipulated, and its EMI property is significantly different from that of traditional electromagnetic shielding materials that show a lower EMI SE with increasing frequency. For example, the EMI SE of Cu foils decrease from 75 dB to 35 dB as frequency increases from 25 GHz to 60 GHz. Considering their stable and outstanding EMI SE and easy manipulation, the composite CNT macro-films are expected to have potential applications in shielding against millimeter waves.