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Phyllospadix spp. play a crucial role in the supply of ecosystem services in rocky shores, but they have been rapidly reduced because of natural and anthropogenic causes. Since Phyllospadix spp. are attached to rocks in the surf zone with a strong hydrodynamic condition, their transplanted shoots easily disappear due to the high current velocity, resulting in the failure of transplantation. We described a leaf trimming method for transplanting shoots of surfgrass Phyllospadix iwatensis and evaluated the method’s establishment success for potential use in large-scale restoration projects. A 30-day laboratory experiment was conducted to determine the effect of leaf trimming on shoot survival, growth, and physiology. Successful establishment of new patches from shoots transplanted with the leaf trimming method was assessed through a shoot-transplanting field experiment over 15 months. The survival of P. iwatensis shoots was not significantly affected by the leaf trimming proportion of 10%–60%. The leaf elongation rate and total leaf area of the shoots exposed to 10%–50% leaf trimming reached or exceeded those of the control at the end of the laboratory experiment; however, the growth of the shoots under 60% leaf trimming was significantly lower than those under the control (p < 0.05). The soluble sugar and starch contents of the shoots also displayed a similar trend to the growth, with the lowest values attained at 60% of leaf trimming. The survival rate of shoots exposed to 50% leaf trimming treatment was 70% after 15 months following transplantation, which was 1.23 times higher than that of shoots in the control (p < 0.05). The shoot height in the 50% leaf trimming treatment was 1.02 times higher than that of shoots in the control at the end of the field experiment. There were no significant differences in photosynthetic pigment contents of P. iwatensis shoots between the leaf trimming treatment and the control (p > 0.05). Our study suggested that the leaf trimming method is an efficient restoration technique for the transplantation of P. iwatensis shoots, and is potentially useful in facilitating large-scale restoration projects.

Additional file 1: Supplemental Table 1. Comparison of baseline characteristics stratifiedby low or high FAR. Supplemental Table 2. Comparison of baselinecharacteristics of participants and non-participants due to exclusioncriteria. Supplemental Table 3. Correlation analysis between CACS and FAR inpatients with MACCE, Non-MACCE and whole. Supplemental Figure 1. linear regressionwith scatter dots about FAR and CACS.

BACKGROUND Well-differentiated liposarcoma is the second most common pathologic type of retroperitoneal sarcoma. It is characterized by a huge mass, but multiple organ invasions are common. Surgery is the only treatment option for potential cure. Hyper-accuracy three-dimensional (3D) reconstruction is widely used in robotic partly nephrectomy owing to its ability to visualize overlapping anatomy. CASE SUMMARY A 54-year-old man was admitted for progressive abdominal distension over the preceding 2 mo. Computed tomography revealed a 32 cm × 21 cm × 12 cm lipomatous mass. Hyper-accuracy 3D reconstruction was performed because of the complex relationship between the mass and nearby tissue. The patient underwent surgical resection, and the tumor did not recur for over 16 mo. CONCLUSION Hyper-accuracy 3D reconstruction is useful for operative planning owing to its intuitiveness and precise determination of anatomical structures in both tumors and nearby tissues.

Aim To compare the safety and effects of unrestricted visiting policies (UVPs) and restricted visiting policies (RVPs) in intensive care units (ICUs) with respect to outcomes related to delirium, infection, and mortality. Methods MEDLINE, Cochrane Library, Embase, Web of Science, CINAHL, CBMdisc, CNKI, Wanfang, and VIP database records generated from their inception to 22 January 2022 were searched. Randomized controlled trials and quasi-experimental studies were included. The main outcomes investigated were delirium, ICU-acquired infection, ICU mortality, and length of ICU stay. Two reviewers independently screened studies, extracted data, and assessed risks of bias. Random‑effects and fixed-effects meta‑analyses were conducted to obtain pooled estimates, due to heterogeneity. Meta-analyses were performed using RevMan 5.3 software. The results were analyzed using odds ratios (ORs), 95% confidence intervals (CIs), and standardized mean differences (SMDs). Results Eleven studies including a total of 3741 patients that compared UVPs and RVPs in ICUs were included in the analyses. Random effects modeling indicated that UVPs were associated with a reduced incidence of delirium (OR = 0.4, 95% CI 0.25–0.63, I2 = 71%, p = 0.0005). Fixed-effects modeling indicated that UVPs did not increase the incidences of ICU-acquired infections, including ventilator-associated pneumonia (OR = 0.96, 95% CI 0.71–1.30, I2 = 0%, p = 0.49), catheter-associated urinary tract infection (OR 0.97, 95% CI 0.52–1.80, I2 = 0%, p = 0.55), and catheter-related blood stream infection (OR = 1.15, 95% CI 0.72–1.84, I2 = 0%, p = 0.66), or ICU mortality (OR = 1.03, 95% CI 0.83–1.28, I2 = 49%, p = 0.12). Forest plotting indicated that UVPs could reduce the lengths of ICU stays (SMD = − 0.97, 95% CI − 1.61 to 0.32, p = 0.003). Conclusion The current meta-analysis indicates that adopting a UVP may significantly reduce the incidence of delirium in ICU patients, without increasing the risks of ICU-acquired infection or mortality. Further large-scale, multicenter studies are needed to confirm these indications.

This paper addresses policy learning in non-stationary environments and games with continuous actions. Rather than the classical reward maximization mechanism, inspired by the ideas of follow-the-regularized-leader (FTRL) and mirror descent (MD) update, we propose a no-regret style reinforcement learning algorithm PORL for continuous action tasks. We prove that PORL has a last-iterate convergence guarantee, which is important for adversarial and cooperative games. Empirical studies show that, in stationary environments such as MuJoCo locomotion controlling tasks, PORL performs equally well as, if not better than, the soft actor-critic (SAC) algorithm; in non-stationary environments including dynamical environments, adversarial training, and competitive games, PORL is superior to SAC in both a better final policy performance and a more stable training process.

Reinforcement learning (RL) solves sequential decision-making problems via a trial-and-error process interacting with the environment. While RL achieves outstanding success in playing complex video games that allow huge trial-and-error, making errors is always undesired in the real world. To improve the sample efficiency and thus reduce the errors, model-based reinforcement learning (MBRL) is believed to be a promising direction, which builds environment models in which the trial-and-errors can take place without real costs. In this survey, we take a review of MBRL with a focus on the recent progress in deep RL. For non-tabular environments, there is always a generalization error between the learned environment model and the real environment. As such, it is of great importance to analyze the discrepancy between policy training in the environment model and that in the real environment, which in turn guides the algorithm design for better model learning, model usage, and policy training. Besides, we also discuss the recent advances of model-based techniques in other forms of RL, including offline RL, goal-conditioned RL, multi-agent RL, and meta-RL. Moreover, we discuss the applicability and advantages of MBRL in real-world tasks. Finally, we end this survey by discussing the promising prospects for the future development of MBRL. We think that MBRL has great potential and advantages in real-world applications that were overlooked, and we hope this survey could attract more research on MBRL.

Inverse reinforcement learning (IRL) recovers the underlying reward function from expert demonstrations. A generalizable reward function is even desired as it captures the fundamental motivation of the expert. However, classical IRL methods can only recover reward functions coupled with the training dynamics, thus are hard to generalize to a changed environment. Previous dynamics-agnostic reward learning methods have strict assumptions, such as that the reward function has to be state-only. This work proposes a general approach to learn transferable reward functions, Dynamics-Agnostic Discriminator-Ensemble Reward Learning (DARL). Following the adversarial imitation learning (AIL) framework, DARL learns a dynamics-agnostic discriminator on a latent space mapped from the original state-action space. The latent space is learned to contain the least information of the dynamics. Moreover, to reduce the reliance of the discriminator on policies, the reward function is represented as an ensemble of the discriminators during training. We assess DARL in four MuJoCo tasks with dynamics transfer. Empirical results compared with the state-of-the-art AIL methods show that DARL can learn a reward that is more consistent with the true reward, thus obtaining higher environment returns.

With the rapid development of live streaming industry, live streaming has increasingly become an important tool and strategy for brand communication and product promotion. Through questionnaires, this paper explores the influencing mechanism of consumers' brand live streaming experience including information experience, entertainment experience and interactive experience that created by enterprises on brand communication. This paper constructs a theoretical model that can reflect the relationship between live streaming experience and brand communication, and further explains the critical path of brand communication in live streaming. Through 374 questionnaires, this study tests research hypotheses with SPSS. The research indicates the positive effect of brand live streaming experience on brand communication, and analyzes the mediating role of online word-of-mouth and consumer engagement. According to the research results, we provide relevant suggestions for enterprise brand construction in the context of online live streaming.

Layikeleke copper deposit is a large-scale porphyry copper polymetallic buried deposit, which has been discovered recently in the eastern Junggar area of Xinjiang. Mineralization occurred in the Late Silurian and Early Devonian with the copper body mainly confined to tonalite. To find new ore bodies, it is necessary to map the 3D spatial distribution of the tonalite. For this reason, we deployed audio-magnetotelluric (AMT) sounding in the research area, collected 26 profiles and 1198 measuring points, carried out 3D inversion calculations of off-diagonal elements in the impedance tensor data using the nonlinear conjugate gradient method, and obtained a 3D electrical structure model. The electrical structure reveals two groups of NW-SE trending middle and middle low resistivity anomaly zones, which intersect the high resistivity bedrock area in the northwest of the study area. Based on the electrical data, it can be inferred that the medium low resistance tonalite in the northern part of the study area is the host rock of the porphyry copper polymetallic deposit, which has been verified by borehole data. The results of 3D AMT inversion depict the spatial distribution and depth variation characteristics of the tonalite electrical structure model, providing a basis for further prospecting and exploration. Therefore, this method of identifying lithology by 3D inversion can provide an important basis for mineral exploration and mining of buried rock masses, and is an effective prospecting method.

Wavefield separation is one critical step in the three-component (3C) vertical seismic profiling (VSP) data processing. The conventional 3C VSP wavefield separation method exhibits low precision polarization angle and cannot obtain desirable results. This letter proposed the right-hand rule 3C VSP wavefield separation method which has many advantages over the conventional 3C VSP wavefield separation method—particularly the polarization angle precision and wavefields continuity. Analysis of real 3C VSP data demonstrates that the right-hand rule 3C VSP wavefield separation method can enhance polarization angle precision and show a very desirable ability to produce high-continuity wavefields.

Seasonal climate variability is an important component of the climate system, and has a significant impact on ecosystems and social systems. However, the temporal resolution of most proxy-based paleoclimate records is limiting to fully understand the past seasonal changes. Here we used high-precision monthly resolution Sr/Ca records of three Tridacna squamosa from northern SCS to reconstruct the SST seasonality during three-time windows of the middle Holocene. The results suggested that the SST seasonality in northern SCS during the middle Holocene (3.21 ± 0.98℃) was smaller than that for recent decades (1994-2004 AD, 4.32 ± 0.59℃). The analysis of modern instrumental data showed that the SST seasonality in northern SCS was dominated by the winter SST, which was deeply influenced by the intensity of EAWM. Strong EAWM usually resulted in cooler winter SST and a larger SST seasonality in northern SCS. The reconstructed Holocene EAWM records showed that the EAWM strengthened from the middle to late Holocene, which could be demonstrated by our reconstruction of a smaller SST seasonality during the middle Holocene in northern SCS. This study highlighted that the Sr/Ca ratios of Tridacna shells can be used as a potential high-resolution indicator of past seasonal climate changes.

Aiming at the problems of low screening efficiency, high energy consumption and low grouping rate of decommissioned power batteries at this stage, a fast screening and recombinant method based on short-time pulse discharge and electrochemical impedance spectroscopy (EIS) for decommissioned power batteries is proposed. More than 200 decommissioned lithium iron phosphate power batteries of the same type and different batches were tested and analyzed by short-time pulse discharge and EIS. Then, the obtained pulse voltage difference, DC internal resistance, EIS curve shape characteristics and EIS equivalent circuit model parameters are used as screening indexes, and a mathematical model is established to realize the rapid and effective sorting and reorganization of decommissioned power batteries. The experimental results show that this method has low energy consumption, the average test time of single cell is less than 20 min, and the consistency index is good after grouping, so it has great practical value in engineering.

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Tehnike otkrivanja i poboljšanja rubova podataka potencijalnih polja (gravitacijski i magnetski podaci) korisni su alati za pronalaženje mjesta anomalija u dubini. Nedavno su ove metode, uključujući filtre na bazi derivata, lokalne fazne filtre i tehnike temeljene na statistikama, sve više naširoko se koristi u rješavanju geoloških problema, poput identificiranja podzemnih rasjeda, kontakata i drugih tektonskih značajki. Ipak, opće metode možda neće pružiti značajne rezultate za potencijalne terenske podatke s jakom bukom. Da bismo prevladali ove nedostatke, predstavljamo novu metodu pod nazivom Varimax Norm (VariNorm) s pomičnim prozorom za procjenu mjesta potencijalnih podataka polja. Ispitivanja izvedena na sintetičkim i poljskim podacima u rudnom području Tonling pokazuju da metoda ne zahtijeva vodoravne ili okomite izračune izvedenih derivata bilo kojeg reda, odolijeva buci u prirodi i nadmašuje ostale tradicionalne metode u jakom okruženju buke., Edges detection and enhancement techniques of potential field data (gravity and magnetic data) are useful tools for finding the locations of anomalies at depth. Recently, these methods, including derivative-based filters, local phase filters and statistics-based techniques, have been increasingly widely used in solving geology problems, such as identifying subsurface faults, contacts, and other tectonic features. Nevertheless, general methods may not provide meaningful results for potential field data with heavy noise. To overcome these disadvantages, we present a new method named Varimax Norm (VariNorm) with a moving window to estimate the location of potential field data. Tests performed on the synthetic and field data in Tonling ore district show that the method does not require horizontal or vertical derivative calculations of any order, resists noise in nature and outperforms other traditional methods in a strong noise environment.

Synchrosqueezing transform (SST) has been used to address the problems in many diverse disciplines. However, the calculated instantaneous frequency (CIF) precision by SST decreases with the increase in time-sample interval and actual instantaneous frequency. This will lead to an incorrect time–frequency distribution. To eliminate the impact of the time-sample interval and to enhance the CIF precision and SST resolution, we propose an adaptive time-resampled high-resolution SST, in which the time-resampled interval of the time–frequency spectrum for instantaneous frequency calculation is adapted to the highest frequency in its effective frequency band and the desired CIF precision. A synthetic signal example shows that the adaptive time-resampled high-resolution SST can eliminate the impact of the time-sample interval and achieve correct and desired high-resolution time–frequency distribution. A real 3-D seismic data application demonstrates that the proposed approach is a good potential technique for high-precision signal processing and interpretation.

The commonly used stable factor methods for the inverse [Formula: see text]-filter achieve good performance in seismic data processing; however, the constant gain-limit assumption in these methods is not associated with the effective frequency band of seismic data and cannot obtain desirable results with high resolution and high signal-to-noise ratio (S/N). Our extended stable factor method for the inverse [Formula: see text]-filter extends these methods by introducing two parameters and constant or self-adaptive gain limit to achieve the desirable high-resolution and high-S/N result. The extended stable factor method for the inverse [Formula: see text]-filter can be implemented in the frequency or time-frequency domain; the latter implementation achieves a higher S/N. Analysis of synthetic signals and field seismic data application illustrate that our method can produce a desirable high-resolution and high-S/N result.

Hemicellulose is the second most abundant biomass in the world. Because of its unique chemical structure, hemicellulose has attracted more and more research and industry application under the background of fossil resource shortage and drawbacks. Hemicellulose is tended to be modified with esterification, etherification, cross-linkage and so on. These reactions change hemicellulose properties, so that it could be applied in many fields such as medical field, films, hydrogels, conductive polymers. Herein, we reviewed structure, isolation, reaction and applications of hemicellulose. Especially the useful pathways to change the hydrophilic character of hemicelluloses to hydrophobic are reviewed and several applications of these materials are discussed.

Human values and affective traits were found to predict attitudes toward the use of different types of knowledge-based theory through creative climate. In this study (N =329), we aimed to gain a more comprehensive understanding of those predictors toward use in a structural equation model (SEM), providied a better overview of a possible structural path that drives to such antecedents for Small and Medium Enterprises (SMEs) in Bangladesh. Precisely, we predicted and found that the relations between the variables and impact of different variables were modeled and tested by applying SEM. Based on the questionnaires survey on SMEs in Bangladesh, this empirical study indicates that all the predictor variables significantly influence the endogenous variables except knowledge management (KM) and employee resilience (ER), and creative climate (CC) and organizational resilience (OR). The study provides several theoretical and practical implications for further research.

Purpose Given that individual creativity is a critical element to achieving organizational competitiveness, the purpose of this study is to attempt to investigate how transformational leadership (TL) drives employee creative process engagement (CPE) by improving their creative self-efficacy (CSE). Design/methodology/approach Analysis has been performed based on 194 responses from information and communication technology firms using a cross-sectional survey design. The study follows a deductive research approach to test the hypotheses. It uses SmartPLS2 and IBM SPSS 21 for a structural equation model. Findings The investigation finds that TL significantly predicts CPE, and CSE partially mediates the TL–CPE relationship. The result demonstrates that TL shapes an organizational climate conducive to the employees’ CPE by building employees’ self-efficacy. Research limitations/implications The study sample was drawn from a single sector of the Bangladeshi economy. The sampling design represents a limitation, for which the findings cannot be broadly generalized. Replications and augmentations of the study in various industrial areas will help test the robustness and generalizability of the discoveries. Practical implications TL and CPE are desirable organizational outcomes across all cultures. From a practical standpoint, the outcomes demonstrate that TL is linked to CPE and CSE among information and communication technology employees. This study extends the appropriateness of CSE into Asian countries. Notably, it provides additional insight into a contemporary TL model that can unequivocally impact leadership development in the Bangladeshi information and communication technology firms. Managers or chief executive officers in the small and medium enterprises are expected to exhibit TL attributes by designing a supportive organizational climate that will motivate employees to exhibit creative activities. Social implications TL transforms employees’ psychological state to get them to engage in creative processes, benefiting the organizational stakeholders by their unconventional creative behavior. The TL-driven innovative outcome through employees’ CPE contributes to the development of social well-being. Originality/value This paper adds significance to the extant literature regarding the determinants of the mediating impact of CSE on TL and CPE from the viewpoints of information and communication technology firms, particularly from developing countries, such as Bangladesh. It also contributes to reconcile the findings of the previous studies around the globe in both developed and developing countries.

The Hilbert transform (HT) has been widely used in seismic data processing and interpretation. However, HT results exhibit lower noise robustness and resolution. This paper extends HT by introducing three orders greater than or equal to 0 and the sign function in frequency domain and propose an extended Hilbert transform (EHT) which has many advantages over the HT—particularly noise robustness, resolution, and a variety of applications. The output of EHT depends on the choice of the three orders and the sign function. Analysis of synthetic cosine signal and hypothetical channel model shows that EHT helps to retain the desired characteristics of HT while overcoming its shortcomings and exhibits better noise robustness and higher resolution than HT. Analysis of real 3‐D seismic data application demonstrates that EHT shows a very desirable ability to capture subtle geologic features and can be well used for seismic attributes and other fields involving digital data processing.

Adopting a multi-level research approach, this study aims to investigate the impact of employee engagement on team performance. It further explores the mediating effects of employee commitment and organizational citizenship behaviour on the employee engagement–team performance relationship.,The study follows a quantitative method. Data were collected through a self-administered questionnaire survey using snowball and convenience sampling. Descriptive statistics and bi-variate correlation analyses were conducted using SmartPLS 2 and SPSS 20 software, and subsequently, a structural equation model was developed.,The study suggests that better employee engagement could improve team performance in organizational contexts. Organizational commitment and citizenship behaviour played a mediating role in the employee engagement–team performance relationship. Further research on the meditating effects of demographic factors is suggested to advance knowledge in the employee engagement domain.,Based on premises of the social exchange theory and the employee stewardship theory, the study integrates multi-level variables to impact of individual employee engagement on organizational team performance. The findings of the study contribute to the existing literature by providing empirical evidence of the impact of individual-level variables on team-level performance. It reiterates the need for multi-level modelling of organizational behavioural research.,The study used a multi-theoretical approach to investigate team performance in organizational contexts, i.e. individual employee engagement, organizational commitment and organizational citizenship behaviour. This integrated model using predictors from multiple levels demonstrates that team performance could be enhanced from interactions of different factors of individual behaviour.

PurposeUsing a multi-level perspective, the purpose of this paper is to investigate impact of transformational leadership on employees’ creative process engagement and mediating roles of intrinsic motivation, task complexity and innovation support in the process of influence.Design/methodology/approachThis study follows a quantitative method. Using a multi-item survey instrument, a total of 400 questionnaires were distributed among employees of small and medium enterprises registered with the Chittagong Chamber of Commerce and Industry in Bangladesh. Collected data were analyzed using structural equation model as well as factor analysis and path analysis to test the hypotheses and to assess the moderating and mediating effects of the variables.FindingsThe findings reveal that transformational leadership has a significant impact on employees’ creative process engagement. The study further shows that task complexity and support for innovation moderate the relationship between transformational leadership and employees’ creative process engagement.Research limitations/implicationsBased on the premises of interactionist perspectives on creativity, this study integrates multi-level variables to investigate leaders’ influences on followers’ creative process engagement. This study contributes to the existing literature by providing empirical evidence on influence of transformational leadership on employees’ creative process engagement as well as the impact of both individual- and organizational-level variables.Originality/valueThe study adopts a distinct model comprising five different variables to investigate creative process engagement from a multi-level perspective, i.e., creative process engagement and intrinsic motivation at the individual level, task complexity at the unit level, and support for innovation and leadership at the organizational level. This integrated model of using predictors from multiple levels supports the theoretical assumptions that creative process engagement results from the interaction of individual-, group- and organizational-level factors.

This research investigated the link between employee-orientated human resource management (EOHRM) counterproductive work behaviors targeted at individual members and organization in Ethiopia. Relaying on social exchange theory, organizational support theory, signaling theory, and relevant literature we examined how employee-oriented HRM practice affects counterproductive work behaviors by using perceived organizational support as a mediator. Data had been obtained from 555 workers and 150 supervisors from eight companies in Ethiopia. Partial least squares structural equation modeling (PLS-SEM) methods via SmartPLS has been used to determine the hypothesized links pertaining to employee-oriented HRM and counterproductive work behavior directed towards individual members and the organization. Final results confirmed that perceived organizational support fully mediated the relationship between employee-oriented HRM and counterproductive work behaviors. The impact of employee-oriented HRM on counterproductive work behavior-organizational via perceived organizational support were stronger than the impact of employee-oriented HRM on counterproductive work behavior – individual (interpersonal). The findings suggest that organizations may minimize (reduce) employees’ counterproductive work behavior by putting into action employee-oriented HRM practices that would uplift perceived organizational support that finally prevents the tendency to act against the organization and its members.

Although deep convolutional neural networks have made breakthroughs in the accuracy and speed of single-image super-resolution, there are still many unsolved problems: firstly, How to refine the texture problem when performing super-resolution processing at a larger magnification ratio. Secondly, the existing convolutional neural network image super-resolution algorithms are prone to overfitting and insufficient convergence of the loss function. Aiming at two problems, an image super-resolution method based on generative adversarial network is proposed. The feature map is spatially transformed on the network to solve the problem of refined texture, combined with CycleGAN and SRGAN, the network structure is improved and the loss function is optimized, and the SRCICGAN algorithm is proposed to restore the four times down-sampled image to solve the loss function problem. The experiment is compared with the latest six methods on three data sets. The PSNR and SSIM indicators are 1.92% and 5.49% higher in the Flickr2K data set, respectively, and better visual effects can be obtained in terms of detailed texture.

This research reports the role of disaster policy implementation achieving disaster risk reduction (DRR) and sustainable development (SD) in Sierra Leone. The factors were highlighted to help policymakers measure disaster risk perception (DRP), disaster adaptation (DA), community participation (CP), and disaster policy implementation (DPI) towards achieving disaster risk reduction and sustainable development. A questionnaire was administered to collect data from the respondents in six disaster-prone communities (Dwarzarck, Portee-Rokupa, Kroobay, Susan’s Bay, Moyiba, and Colbot) in Freetown, Sierra Leone. Employing the structural equation model approach, we found that all the disaster risk reduction factors (DRP, CP, DA, and DPI) directly influence SD. Furthermore, disaster policy implementation serves as a channel through which disaster risk reduction influences sustainable development. This study suggests to policymakers to use the factors mentioned earlier to design effective disaster policy implementation to achieve disaster risk reduction and sustainable development in Sierra Leone.

MT data

Additional file 1: Figure S1. Hematoxylin–eosin (HE) staining of all 15 NPC cell lines (× 20). Scale bars: 50 μm.

Additional file 1. Supplementary Methods and Table S1–6.

We propose a deep learning architecture and test three other machine learning models to automatically detect individuals that will attempt suicide within (1) 30 days and (2) six months, using their social media post data provided in the CLPsych 2021 shared task. Additionally, we create and extract three sets of handcrafted features for suicide risk detection based on the three-stage theory of suicide and prior work on emotions and the use of pronouns among persons exhibiting suicidal ideations. Extensive experimentations show that some of the traditional machine learning methods outperform the baseline with an F1 score of 0.741 and F2 score of 0.833 on subtask 1 (prediction of a suicide attempt 30 days prior). However, the proposed deep learning method outperforms the baseline with F1 score of 0.737 and F2 score of 0.843 on subtask 2 (prediction of suicide 6 months prior)., Comment: This work is accepted to CLPsych 2021, to be held in conjunction with NAACL 2021

Alzheimer`s disease (AD)-related global healthcare cost is estimated to be $1 trillion by 2050. Currently, there is no cure for this disease; however, clinical studies show that early diagnosis and intervention helps to extend the quality of life and inform technologies for personalized mental healthcare. Clinical research indicates that the onset and progression of Alzheimer`s disease lead to dementia and other mental health issues. As a result, the language capabilities of patient start to decline. In this paper, we show that machine learning-based unsupervised clustering of and anomaly detection with linguistic biomarkers are promising approaches for intuitive visualization and personalized early stage detection of Alzheimer`s disease. We demonstrate this approach on 10 year`s (1980 to 1989) of President Ronald Reagan`s speech data set. Key linguistic biomarkers that indicate early-stage AD are identified. Experimental results show that Reagan had early onset of Alzheimer`s sometime between 1983 and 1987. This finding is corroborated by prior work that analyzed his interviews using a statistical technique. The proposed technique also identifies the exact speeches that reflect linguistic biomarkers for early stage AD.

The past few decades showed inadequate discussion of the impact of employees&rsquo, knowledge sharing and its diffusion on advancing banks&rsquo, long-term sustainability. The objective of the study is to examine the role of employees&rsquo, knowledge sharing on the sustainable performance of the banks operating in Bangladesh. Furthermore, this study tested the &ldquo, moderated mediation model&rdquo, of knowledge hiding and employees&rsquo, ambidexterity on the association above. The researchers applied the deductive reasoning method through the application of quantitative techniques, using structural equation modeling. Finally, 287 respondents from different banks were chosen through a self-administered questionnaire survey in the capital city of Dhaka. The findings indicated that all the predictor variables significantly explain the outcome variable, except the influence of knowledge sharing. Mediation analysis showed that employees&rsquo, ambidexterity mediated the association between knowledge sharing and sustainable performance. Surprisingly, moderation analysis revealed that the influence of knowledge sharing on employees&rsquo, ambidexterity is not affected by knowledge hiding. This study adds to the existing literature by demonstrating the importance of knowledge hiding, along with explaining how knowledge sharing can motivate and influence employees to achieve sustainable performances. In addition, the main contribution of this study is to advance knowledge and add values in the forms of knowledge creation, preservation, and dissemination among practitioners, banking professionals, and academics for utilizing their domain-specific areas to increase long-term sustainability.

In order to solve the problems of long time-consuming, low accuracy and high energy consumption in detecting the state of health (SOH) of retired power batteries, a rapid prediction method of SOH based on electrochemical impedance spectroscopy (EIS) is proposed. This method realizes the rapid estimation of the SOH of retired power batteries through the mathematical model established by the constant phase element parameters in the constructed electrochemical impedance spectroscopy equivalent circuit model and the battery SOC and SOH. The verification experiment results show that using this method can greatly reduce the test time, save energy, and achieve rapid estimation of the unknown state of charge and health of the battery, and the prediction error is less than 2%.

Bamboo forests have an efficient carbon sequestration capacity and play an important role in responding to global climate change. However, the current estimation of bamboo carbon storage has some errors, leading to uncertainty in the spatiotemporal pattern of bamboo forest carbon storage. This study simulated aboveground carbon storage of Zhejiang Province, China, during 1984-2014 based on the combination of an improved BIOME-BGC (biogeochemical cycles) model and remote sensing data, with the accuracy being verified with forest resource inventory data. The spatio-temporal distribution and environmental factors of aboveground carbon storage were analyzed. The results showed that the simulated carbon storage was accurate, with average correlation coefficient (r), root mean square error (RMSE) and relative bias (rBIAS) being 0.75, 7.24 Mg C·hm竹林具有高效的固碳能力,在应对全球气候变化中扮演重要角色.然而,目前大尺度竹林碳储量估算误差大,导致竹林碳储量时空格局存在较大的不确定性.本研究以浙江省为例,耦合遥感数据和BIOME-BGC生态系统过程模型模拟1984—2014年浙江省竹林地上碳储量,并利用森林资源清查数据进行精度验证,分析浙江省竹林地上碳储量时空格局以及环境因子对竹林地上碳储量的影响.结果表明: 模拟得到的竹林地上碳储量精度较高,平均相关系数(

Supplementary Materials and Methods. (DOCX 2775 kb)

Supplemental material, Supplemental_Data_2_Supplemental_Table_and_Figure_changes_marked_yellow for Pemetrexed/carboplatin plus gefitinib as a first-line treatment for EGFR-mutant advanced nonsmall cell lung cancer: a Bayesian network meta-analysis by Zhonghan Zhang, Kangmei Zeng, Shen Zhao, Yuanyuan Zhao, Xue Hou, Fan Luo, Feiteng Lu, Yaxiong Zhang, Ting Zhou, Yuxiang Ma, Yunpeng Yang, Wenfeng Fang, Yan Huang, Li Zhang and Hongyun Zhao in Therapeutic Advances in Medical Oncology

Additional file 1: Table S1. shRNAs for vectors. Table S2. Primers for vector construction. (DOCX 18 kb)

The load characteristic model based on demand response and the load optimization control method in three different scenarios are studied in this paper. Firstly, by decoupling rigid load and flexible load, according to different degree that flexible load participates in demand response, considering the influence of different control variables, three types of load characteristics models of electricity price load, direct control load and interruptible load are constructed. Secondly, based on the established the load characteristic model proposes a reasonable load control strategy optimization control method under the condition of different practical power supply gap constraints. Finally, through three cases of scenarios, we explored the control variables are direct control load and interruptible load control, the objective function is when the deviation between the actual load reduction amount and the power supply gap is the smallest, and the constraint condition considers the demand response contract. The feasibility of the constructed model and the optimization method is verified, which provides a reference for the promotion of user-side demand response in China.

Aims and objectives To prospectively identify the effect of the nonswallow procedure of nasogastric tube insertion. Background Nasogastric intubation is one of the most important and basic skills in treatment and nursing. Patients generally experience discomfort and encounter complications during this procedure. Thus, practitioners need a more convenient, effective, quicker and safer method to improve the performance of this procedure. Design This prospective randomised controlled trial was conducted from March to May 2014 in the four units of Gansun Province Hospital in Lanzhou, China. Method A total of 80 participants were randomly assigned to an experimental group (n = 40) and a control group (n = 40). Participants in the experimental group underwent a nonswallow procedure for nasogastric tube insertion. Results There were statistically significant differences in nasogastric tube insertion between the study groups. A marked increase in the success rate at first intubation as well as a markedly reduced occurrence of nausea, tearing, mucosal injury and changes in vital signs (i.e. heart rate, breath, systolic pressure) were observed compared with the control group. No differences in the success rates at second and third intubation were observed between the groups. Conclusions The nonswallow procedure of nasogastric tube intubation relieves discomfort and ensures the safety of patients. Relevance to clinical practice Patients subjected to nasogastric intubation are more likely to benefit from the nonswallow procedure when nasogastric tube insertion is performed.

This study investigates the failure and aftermath of state owned enterprises (SOEs) of an emerging economy, Bangladesh. Failure of SOEs of emerging economy has been investigated by many researchers during the last few decades. This study is an extension of previous research. Through the comparative case study, this study tries to explore the scenario of failure of SOEs, the causal factors of failure, remedial actions and aftermath in SOEs. The findings indicate that different authorities from the policy maker to the operating level employees cannot avoid the responsibilities for failure. Even proper restructuring within the ownership of government can drive the firm positively. It is expected that the comparative case study will help to make the decision for the concerned authorities of Bangladesh as well as the authorities of other countries of the world who are in the same position.

A series of novel thiosemicarbazone derivatives were synthesized and evaluated for their antiproliferative activity against several selected tumor cell lines of different origins using the MTT assay. The preliminary results indicated that the MGC-803 cell line was remarkably sensitive to all the synthesized compounds. Among this series, compound

Article history: Received September 18, 2014 Accepted 15 December 2014 Available online December 18 2014 The safety of civil aviation will be more secured if the errors in all the facets can be reduced. Like the other industrial sectors, human resource is one of the most complex and sensitive resources for the civil aviation. The error of human resources can cause fatal disasters. In these days, a good volume of researches have been conducted on the disaster of civil aviation. The researchers have identified the causes of the civil aviation disasters from various perspectives. They identified the areas where more concern is needed to reduce the disastrous impacts. This paper aims to find out the critical factors of human error in civil aviation in a developing country (Bangladesh) as it is accepted that human error is one of main causes of civil aviation disasters. The paper reviews the previous research to find out the critical factors conceptually. Fuzzy analytical hierarchy process (FAHP) has been used to find out the critical factors systematically. Analyses indicate that the concentration on precondition for unsafe acts (including sub-factors) is required to ensure the aviation safety. Growing Science Ltd. All rights reserved. 5 © 201