Development of a novel design approach for rigid landslide debris-resisting barriers

Natural terrain landslides pose a global threat as they often cause casualties and economic losses. Potential impacts of climate change could further aggravate the landslide risk and robust mitigation measures such as rigid debris-resisting barriers are particularly important in protecting lives and properties. Traditionally, rigid barriers are designed based on empirical approaches which generally oversimplify the dynamic nature of debris-barrier interaction. This often results in overlyconservative designs where the barrier structures are not only bulky and environmentally intrusive, but also difficult to construct. There is thus a pressing need to optimise the design approach. In this regard, the Geotechnical Engineering Office has been endeavouring to enhance the process efficiency, in collaboration with top-notch experts, by capitalising on the latest advancement in computational simulations and physical testing, and improving the understanding of the physical process. A technical breakthrough has been achieved with respect to an improved knowledge in the debris flow dynamic and the complex debris-barrier interaction. A novel design method covering geotechnical and structural aspects has been developed for use in Hong Kong. This would bring about more cost-effective barrier designs, with enhanced design reliability and robustness.

Antibody-free profiling of transcription factor occupancy during early embryogenesis by FitCUT&RUN

Key transcription factors (TFs) play critical roles in zygotic genome activation (ZGA) during early embryogenesis, while genome-wide occupancies of only a few factors have been profiled during ZGA due to the limitation of cell numbers or the lack of high-quality antibodies. Here, we present FitCUT&RUN, a modified CUT&RUN method, in which an Fc fragment of immunoglobulin G is used for tagging, to profile TF occupancy in an antibody-free manner and demonstrate its reliability and robustness using as few as five thousand K562 cells. We applied FitCUT&RUN to zebrafish undergoing embryogenesis to generate reliable occupancy profiles of three known activators of zebrafish ZGA: Nanog, Pou5f3 and Sox19b. By profiling the time-series occupancy of Nanog during zebrafish ZGA, we observed a clear trend toward a gradual increase in Nanog occupancy and found that Nanog occupancy prior to the major phase of ZGA is critical for the activation of a significant proportion of early transcribed genes. Our results further suggested that the sequential binding of Nanog may be controlled by replication timing and the presence of Nanog motifs.

The Adaptive Damping Technique: Improving the Simulation Accuracy of Hydraulic Transients

Hydraulic surges are transient events frequently observed in various industrial and laboratory flow situations. Understanding surge physics and its accurate numerical prediction is crucial to the safety of flow systems. The maximum accuracy achievable for transient surge simulations is limited by the inefficiencies in the mathematical models used. In this work, we propose a mathematical model that incorporates an adaptive damping technique for the accurate prediction of hydraulic surges. This model also takes the compressibility effects in the liquid during the surge process into account. The novel approach of using the local pressure fluctuation data from the flow to adjust the unsteady friction for controlling the dissipation is introduced in this paper. The adaptive-dissipation is actualized through a unique 'variable pressure wave damping coefficient' function definition. Numerical simulation of three different valve-induced surge experiments demonstrates the reliability and robustness of the mathematical model. Numerical results from the proposed model show an excellent match with the experimental data by closely reproducing both the frequency and the amplitude of transient pressure oscillations. A comparative study explains the improvement in the simulation accuracy achieved by replacing the constant damping coefficient with the proposed variable coefficient. The superiority of the new model with the adaptive damping capability over the similar models in literature and those used in commercial software packages is also well established through this study.

Potential distribution of invasive boxwood blight pathogen (Calonectria pseudonaviculata) as predicted by process-based and correlative models

Boxwood blight, caused by the ascomycete fungi Calonectria pseudonaviculata and C. henricotiae, is an emerging plant disease of boxwood (Buxus spp.) that has had devastating impacts on the health and productivity of boxwood in both the horticultural sector and native ecosystems. In this study, we predicted the potential distribution of C. pseudonaviculata at regional and global scales and explored how climatic factors shape its known range limits. Our workflow combined multiple modeling algorithms to enhance the reliability and robustness of predictions. We produced a process-based climatic suitability model in the CLIMEX program and combined outputs of six different correlative modeling algorithms to generate an ensemble correlative model. All models were fit and validated using an occurrence record dataset (N = 292 records from 24 countries) comprised of positive detections of C. pseudonaviculata from across its entire known invaded range. Evaluations of model performance provided validation of good model fit for all models. A consensus map of CLIMEX and ensemble correlative model predictions indicated that not-yet-invaded areas in eastern and southern Europe and in the southeastern, midwestern, and Pacific coast regions of North America are climatically suitable for establishment. Most regions of the world where Buxus and its congeners are native are also at risk of establishment, which suggests that C. pseudonaviculata should be able to significantly expand its range globally if susceptible hosts exist. Our findings provide the first insight into the global invasion threat of boxwood blight, and are valuable to stakeholders who need to know where to focus surveillance efforts for early detection and rapid response measures to prevent or slow the spread of the disease.

An investigation of latent fingerprinting techniques

Background Latent fingerprints are the unintentional impressions that are left at crime scenes, which are considered to be highly significant in forensic analysis and authenticity verification. It is an extremely crucial tool used by law enforcement and forensic agencies for the conviction of criminals. However, due to the accidental nature of these impressions, the quality of prints uplifted is generally inferior. Main body In order to improve the overall fingerprint recognition performance, there is an insistent need to design novel methods to improve the reliability and robustness of the existing techniques. Therefore, a systematic review is presented to study the existing methods for latent fingerprint acquisition, enhancement, reconstruction, and matching, along with various benchmark datasets available for research purposes. Conclusion The paper highlights multiple challenges and research gaps using comparative analysis of existing enhancement, reconstruction and matching approaches in order to augment the research in this direction that has become imperative in this digital era.

A Comparative Numerical Study and Stability Analysis for a Fractional-Order SIR Model of Childhood Diseases

The objective of this work is to examine the dynamics of a fractional-order susceptible-infectious-recovered (SIR) model that simulate epidemiological diseases such as childhood diseases. An effective numerical scheme based on Grünwald–Letnikov fractional derivative is suggested to solve the considered model. A stability analysis is performed to qualitatively examine the dynamics of the SIR model. The reliability and robustness of the proposed scheme is demonstrated by comparing obtained results with results obtained from a fourth order Runge–Kutta built-in Maple syntax when considering derivatives of integer order. Graphical illustrations of the numerical results are given. The inaccuracy of some results presented in two studies exist in the literature have been clearly explained. Generalizing of the cases examined in another study, by considering a model with fraction-order derivatives, is another objective of this work as well.

Quality-of-care comparison of stroke: The reliability and robustness of ranking by process or outcome measures

Background and aim Discussion on the most rational types of performance measures for care quality comparisons has received increasing attention. The important consideration is to what extent will the measure detect a genuine difference in the underlying quality. In this study, we aimed to compare the ranking of hospitals on the performance of individual indicators, composite scores (CS, that were calculated by the method of opportunity-based score on patient-level), and in-hospital outcome of acute ischemic stroke across hospitals, and determined the reliability and robustness of the three types of ranking. Methods We analyzed data from 15,090 patients diagnosed with acute ischemic stroke who were treated at 184 large tertiary hospitals from January 2014 to May 2017. We ranked the hospital effects of recombinant tissue plasminogen activator (rt-PA) and CS and independence (modified Rankin Scale ≤2) at discharge based on fixed- and random-effects regression models before and after case-mix adjustment. We assessed the time-robustness of the hospital effects and calculated the rankability by relating the uncertainty within the hospital and the total hospital variation “beyond chance.” Results After case-mix and reliability adjustment, we estimated that 84.03% of the variance in CS between hospitals was due to true quality differences. The uncertainty within hospitals caused a poor (49.51%) rankability in rt-PA and moderate rankability (63.34%) in independence at discharge. The hospital rankings of CS were more robust across years compared with rt-PA and independence. Conclusions Our data indicated that CS is the optimal measure to indicate the quality-of-care variation of acute ischemic stroke between hospitals.

Reliability-Based Robust Design Optimization of Lithium-Ion Battery Cells for Maximizing the Energy Density by Increasing Reliability and Robustness

Lithium-ion batteries (LIBs) are increasingly employed in electric vehicles (EVs) owing to their advantages, such as low weight, and high energy and power densities. However, the uncertainty encountered in the manufacturing of LIB cells increases the failure rate and causes cell-to-cell variations, thereby degrading the battery capacity and lifetime. In this study, the reliability and robustness of LIB cells were improved using the design of experiments (DOE), and the reliability-based robust design optimization (RBRDO) approaches. First, design factors sensitive to the energy density and power density were selected as design variables through sensitivity analysis using the DOE. RBRDO was performed to maximize the energy density while reducing the failure rate and cell-to-cell variations. To verify the superiority of the reliability and robustness offered by RBRDO, the obtained results were compared with those from conventional deterministic design optimization (DDO), and reliability-based design optimization (RBDO). RBRDO increased the mean of the energy density by 33.5% compared to the initial value and reduced the failure rate by 98.9%, due to improved reliability, compared to DDO. Moreover, RBRDO reduced the standard deviation in the energy density (i.e., cell-to-cell variations) by 30.0% due to the improved robustness compared to RBDO.

Improved library preparation protocols for amplicon sequencing-based noninvasive fetal genotyping for RHD-positive D antigen-negative alleles

Objective We aimed to simplify our fetal RHD genotyping protocol by changing the method to attach Illumina’s sequencing adaptors to PCR products from the ligation-based method to a PCR-based method, and to improve its reliability and robustness by introducing unique molecular indexes, which allow us to count the numbers of DNA fragments used as PCR templates and to minimize the effects of PCR and sequencing errors. Results Both of the newly established protocols reduced time and cost compared with our conventional protocol. Removal of PCR duplicates using UMIs reduced the frequencies of erroneously mapped sequences reads likely generated by PCR and sequencing errors. The modified protocols will help us facilitate implementing fetal RHD genotyping for East Asian populations into clinical practice.