A New Species of Scymnus (Coleoptera, Coccinellidae) from Pakistan with Mitochondrial Genome and Its Phylogenetic Implications.

In this study, a new species of the subgenus Pullus belonging to the Scymnus genus from Pakistan, Scymnus (Pullus) cardi sp. nov., was described and illustrated, with information on its distribution, host plants, and prey. Additionally, the completed mitochondrial genome (mitogenome) of the new species using high-throughput sequencing technology was obtained. The genome contains the typical 37 genes (13 protein-coding genes, two ribosomal RNAs, and 22 transfer RNAs) and a non-coding control region, and is arranged in the same order as that of the putative ancestor of beetles. The AT content of the mitogenome is approximately 85.1%, with AT skew and GC skew of 0.05 and -0.43, respectively. The calculated values of relative synonymous codon usage (RSCU) determine that the codon UUA (L) has the highest frequency. Furthermore, we explored the phylogenetic relationship among 59 representatives of the Coccinellidae using Bayesian inference and maximum likelihood methods, the results of which strongly support the monophyly of Coccinellinae. The phylogenetic results positioned Scymnus (Pullus) cardi in a well-supported clade with Scymnus (Pullus) loewii and Scymnus (Pullus) rubricaudus within the genus Scymnus and the tribe Scymnini. The mitochondrial sequence of S. (P.) cardi will contribute to the mitochondrial genome database and provide helpful information for the identification and phylogeny of Coccinellidae.

Measuring the Capability of Biological Incident Rescue Teams in China: A Fuzzy Analytic Hierarchy Process Based Model - Tianjin Municipality, China, 2022-2023.

Introduction: The swift advancement of biotechnology has presented both opportunities and challenges to our society, thrusting biosafety to the forefront of concern. Consequently, the evaluation of rescue capabilities in the event of a bioterrorism incident becomes of paramount importance. Currently, there is a notable absence of specific measurement criteria and a comprehensive evaluation system. This paper aims to establish a systematic approach towards assessing emergency response capabilities in the context of bioterrorism incidents. Methods: We employed an enhanced Delphi methodology to establish an index evaluation framework. Subsequently, the weight of the judgment matrix was ascertained via the application of the fuzzy comprehensive evaluation approach. This led to the creation of a fuzzy comprehensive evaluation model for bioterrorism rescue capability. Results: A modified Delphi study was conducted involving 11 experts across two rounds, achieving a response rate of 100%. The Kendall coordination coefficients recorded in the first and second rounds were 0.303 and 0.632, respectively (P<0.05). Upon comprehensive analysis involving score, coefficient of variation, and full score ratio, we distinguished five primary indicators and 25 secondary indicators. Subsequently, an evaluation model was developed based on the Analytic Hierarchy Process (AHP) tailored to assess the response to a rescue from bioterrorism. Discussion: The expert panel confirmed consensus on all aspects of the model, validating its comprehensive content. The succeeding course of action involves converting the assessment model to a measurable scale, affirming its functionality, and implementing it in practical evaluation tasks to further enhance the capabilities of the biological incident rescue team.

Successful Large Hospital Evacuation With 11 350 Patients Transferred in the 2021 Zhengzhou Flood.

OBJECTIVES: This is a case report of a huge hospital evacuation with 11 350 inpatients in the 2021 Zhengzhou flood in China, using a mixed methods analysis. METHODS: The qualitative part was a content analysis of semi-structured interviews of 6 key hospital staff involved in evacuation management. The evacuation experience was reviewed according to the 4 stages of disaster management: prevention, preparation, response, and recovery. RESULTS: Because of unprecedented torrential rain, the flood exceeded expectations, and there was a lack of local preventive measures. In preparation, according to the alert, the evacuation was planned to reduce the workload on inpatients and to accept the surge of medical needs by the flood. In response, the prioritization of critically ill patients and large-scale collaboration of hospital staff, rescue teams, and accepting branch made it possible to successfully transfer all 11 350 inpatients. In recovery, restoring medical services and a series of activities to improve the hospital's vulnerability were carried out. CONCLUSIONS: A hospital evacuation is one of the strategies of the business continuity plan of a hospital. For the evacuation, leadership and collaboration were important. Challenges such as prolonged roadway flooding and the infrastructure issues were needed to be addressed throughout the evacuation process.

Novel cementitious materials with mechanoluminescence for the application of visible stress monitoring and recording.

The development of real-time and accurate visual stress detection is crucial for the field of building engineering. Herein, a new strategy is explored for the development of novel cementitious materials by hierarchical aggregation smart luminescent material and resin-based material. The cementitious material with such layered structure is inherently capable of visualization of stress monitoring and recording by converting the stress to visible light. The specimen fabricated by the novel cementitious material could repetitively emit green visible light under excitation of a mechanical pulse for 10 cycles, suggesting that the cementitious material shows highly reproducible performance. Moreover, the numerical simulations and analysis for the models of stress indicate that the luminescent time is synchronous with the stress and the emission intensity is proportional to the value of stress. To the best of our knowledge, this is the first study that the cementitious material realizes visible stress monitoring and recording, which supplies new insights for exploring modern multi-functional building materials.

CTV-Net: Complex-Valued TV-Driven Network With Nested Topology for 3-D SAR Imaging.

The regularization-based approaches offer promise in improving synthetic aperture radar (SAR) imaging quality while reducing system complexity. However, the widely applied l1 regularization model is hindered by their hypothesis of inherent sparsity, causing unreal estimations of surface-like targets. Inspired by the edge-preserving property of total variation (TV), we propose a new complex-valued TV (CTV)-driven interpretable neural network with nested topology, i.e., CTV-Net, for 3-D SAR imaging. In our scheme, based on the 2-D holography imaging operator, the CTV-driven optimization model is constructed to pursue precise estimations in weakly sparse scenarios. Subsequently, a nested algorithmic framework, i.e., complex-valued TV-driven fast iterative shrinkage thresholding (CTV-FIST), is derived from the theory of proximal gradient descent (PGD) and FIST algorithm, theoretically supporting the design of CTV-Net. In CTV-Net, the trainable weights are layer-varied and functionally relevant to the hyperparameters of CTV-FIST, which aims to constrain the algorithmic parameters to update in a well-conditioned tendency. All weights are learned by end-to-end training based on a two-term cost function, which bounds the measurement fidelity and TV norm simultaneously. Under the guidance of the SAR signal model, a reasonably sized training set is generated, by randomly selecting reference images from the MNIST set and consequently synthesizing complex-valued label signals. Finally, the methodology is validated, numerically and visually, by extensive SAR simulations and real-measured experiments, and the results demonstrate the viability and efficiency of the proposed CTV-Net in the cases of recovering 3-D SAR images from incomplete echoes.

TPSSI-Net: Fast and Enhanced Two-Path Iterative Network for 3D SAR Sparse Imaging.

The emerging field of combining compressed sensing (CS) and three-dimensional synthetic aperture radar (3D SAR) imaging has shown significant potential to reduce sampling rate and improve image quality. However, the conventional CS-driven algorithms are always limited by huge computational costs and non-trivial tuning of parameters. In this article, to address this problem, we propose a two-path iterative framework dubbed TPSSI-Net for 3D SAR sparse imaging. By mapping the AMP into a layer-fixed deep neural network, each layer of TPSSI-Net consists of four modules in cascade corresponding to four steps of the AMP optimization. Differently, the Onsager terms in TPSSI-Net are modified to be differentiable and scaled by learnable coefficients. Rather than manually choosing a sparsifying basis, a two-path convolutional neural network (CNN) is developed and embedded in TPSSI-Net for nonlinear sparse representation in the complex-valued domain. All parameters are layer-varied and optimized by end-to-end training based on a channel-wise loss function, bounding both symmetry constraint and measurement fidelity. Finally, extensive SAR imaging experiments, including simulations and real-measured tests, demonstrate the effectiveness and high efficiency of the proposed TPSSI-Net.

Removal of type-A, type-B, and borderline metals from contaminated soils using zero valent iron and magnetic separation technology: A predictive approach for metal resources recovery.

Despite the limitations reported on the efficiency of metals used as sorbents, recent advances in chemical and material sciences make it possible to use remediation technologies based on zero valent iron (ZVI) to restore the ecosystem services of metal-contaminated soils. In addition, recent studies showed that remediation by in situ immobilization could be avoided by taking advantage of the strong magnetic characteristics of ZVI. We combined these well-established concepts and conducted laboratory experiments to predict the removal efficiency of metals from contaminated soils based on their chemical classification into type-A, type-B and borderline metals. The Nieboer-Richardson separation of metal ions based on covalent and ionic indexes was used, and beryllium (Be2+), mercury (Hg2+) and lead (Pb2+) were selected as representative of type-A, type-B and borderline, respectively. The results showed a significant decrease in total metal concentrations of treated soils, with a removal efficiency of about 80% for Be, 90% for Pb and 97% for Hg. This ranking followed the increasing order of the covalent indexes, which are 1.11, 3.36, and 3.92 for Be, Pb and Hg, respectively. Therefore, the ability to form strong covalent bonds with oxygen atoms in maghemite (Fe2O3, γ-Fe2O3) identified on ZVI surfaces seems to drive metal recovery. Validation studies conducted on soil samples collected from sites contaminated with either Pb or Hg, confirmed the above trend. Overall, the results suggest that borderline and type-B metals can be successfully recovered from contaminated soils with rates ≥90%, while the performance would be much lower for type-A metals.

Experiences and Practices in the Current Prevention and Control of the Novel Coronavirus Pneumonia in China.

Since December 2019, several new infectious diseases, mainly lung diseases caused by novel coronavirus infections, have been discovered in Wuhan, Hubei Province. With the spread of the epidemic, cases in other regions of China and abroad have been confirmed. This sudden outbreak of a new type of infectious disease has seriously threatened people's health and safety, and China has adopted strong prevention and control measures in response. To provide a reference for international health emergency management workers, this article summarizes, from an academic perspective, the main prevention and control measures taken in China.

A new species of Phytodietus Gravenhorst, 1829 (Hymenoptera: Ichneumonidae: Tryphoninae) from China.

A new species in the genus Phytodietus Gravenhorst, 1829, P. xui Kostro-Ambroziak Reshchikov sp. n. is described from the Yunnan Province of China. An identification key for the eight species of Phytodietus currently recorded in Mainland China is provided. P. longicauda (Uchida, 1931) is recorded for the first time in China and P. spinipes (Cameron, 1905) is recorded in Guangdong and Hunan Provinces.