A Review of Strategies to Improve Biomechanical Fixation in the Cervical Spine

Study Design Systematic review. Objectives Review the surgical techniques and construct options aimed at improving the biomechanical strength of cervical constructs. Methods A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A search of the MEDLINE, Embase, and Cochrane Library databases was performed to identify all studies examining biomechanical strategies utilized in the osteoporotic cervical spine. Screening was performed in duplicate for all stages of the review process. Results An initial search returned 3887 articles. After deletion of duplications and review of abstracts and full text, 39 articles met inclusion criteria. Overall, the surgical techniques reviewed aimed at obtaining rigid fixation in the setting of poor bone quality, or dispersing the forces at the bone-implant interface. We identified 6 key techniques to improve biomechanical fixation. These include bicortical fixation, appropriate screw selection (size and trajectory), PMMA augmentation, load sharing techniques, consideration of ancillary fixation around the occipitocervical junction, and supplementing the construct with post-operative collar or halo. Conclusion The summation of the literature highlights a framework of modalities available to surgeons to improve biomechanical fixation in the cervical spine. While these may improve construct strength in the setting of osteoporosis, there is a paucity of evidence available to make recommendations in this patient population.

Technology Status and Development Trend of Modular Moving System

With the development of technology, modular independent suspension technology has been widely applied on high-movement off-road platforms in the developed world because of the characteristics of offline assembly and full-body lifting. At the same time, after the breakthrough of key techniques such as the stiffness spiral springs, the high dissipation of the shock absorbers, the lightweight of double-wishbone steering mechanism and the non-maintenance bearing, the ability to carry the off-road mobility and armor protection of the military vehicles have been significantly increased. In this case, the application of the modular independent suspension and its current state around the world was explained, that the development of this technology is of great significance to the off-road maneuvering of our military equipment was also represented in this paper.

Quingo: A Programming Framework for Heterogeneous Quantum-Classical Computing with NISQ Features

The increasing control complexity of Noisy Intermediate-Scale Quantum (NISQ) systems underlines the necessity of integrating quantum hardware with quantum software. While mapping heterogeneous quantum-classical computing (HQCC) algorithms to NISQ hardware for execution, we observed a few dissatisfactions in quantum programming languages (QPLs), including difficult mapping to hardware, limited expressiveness, and counter-intuitive code. In addition, noisy qubits require repeatedly performed quantum experiments, which explicitly operate low-level configurations, such as pulses and timing of operations. This requirement is beyond the scope or capability of most existing QPLs. We summarize three execution models to depict the quantum-classical interaction of existing QPLs. Based on the refined HQCC model, we propose the Quingo framework to integrate and manage quantum-classical software and hardware to provide the programmability over HQCC applications and map them to NISQ hardware. We propose a six-phase quantum program life-cycle model matching the refined HQCC model, which is implemented by a runtime system. We also propose the Quingo programming language, an external domain-specific language highlighting timer-based timing control and opaque operation definition, which can be used to describe quantum experiments. We believe the Quingo framework could contribute to the clarification of key techniques in the design of future HQCC systems.

Image Segmentation for Review of Cerebral Apoplexy

Brain computed tomography (CT) provides a medical imaging tool for reviewing cerebral apoplexy. It is of strong clinical significance to study the key techniques for lesion segmentation and feature selection of cerebral apoplexy. Most of the previous research fail to fully utilized the other prior information, or apply to the changing feature analysis on multiple lesion images generated in the rehabilitation process. Therefore, this paper aims to develop an image segmentation method for review of cerebral apoplexy. Based on the correlation between image series, the authors proposed a segmentation method for CT images of cerebral apoplexy, and developed a way to extract and select the changing lesion features, which assists with the diagnosis of cerebral apoplexy rehabilitation. The image segmentation and feature selection results were obtained through experiments, revealing the effectiveness of our method.

Controlling the Chemistry of Nanoclusters: From Atomic Precision to Controlled Assembly

Metal nanoclusters have gained prominence in nanomaterials sciences, owing to their atomic precision, structural regularity, and unique chemical composition. Additionally, the ligands stabilizing the clusters provide great opportunities for linking the clusters in higher order dimensions, eventually leading to the formation of a repertoire of nanoarchitectures. This makes the chemistry of atomic clusters worth exploring. In this mini review, we aim to focus on the chemistry of nanoclusters. Firstly, we summarize the important strategies developed so far for the synthesis of atomic clusters. For each synthetic strategy, we highlight the chemistry governing the formation of nanoclusters. Next, we discuss the key techniques in the purification and separation of nanoclusters, as the chemical purity of clusters is deemed important for their further chemical processing. Thereafter which we provide an account of the chemical reactions of nanoclusters. Then, we summarize the chemical routes to the spatial organization of atomic clusters, highlighting the importance of assembly formation from an application point of view. Finally, we raise some fundamentally important questions with regard to the chemistry of atomic clusters, which, if addressed, may broaden the scope of research pertaining to atomic clusters.

The key enablers, techniques and benefits of managing stakeholders within BIM supported projects

Purpose Project managers still face challenges with managing stakeholders. Using building information modelling (BIM) has further increased these challenges. Meanwhile, there is a paucity of research specifically focussing on the techniques which organisations are adopting to manage stakeholders within BIM-implemented projects and the associated benefits which they can reap. Thus, this paper aims to identify the key techniques, enablers and benefits of managing stakeholders within BIM-implemented projects. Design/methodology/approach An exploratory approach was adopted due to the paucity of the variables on the topic. In total, 23 semi-structured interviews were conducted in the UK through purposive and snowball sampling. The data was analysed using content analysis and the “NVivo 11 Pro” software. Findings Two key techniques and two enablers required to manage stakeholders within BIM-implemented projects were identified. Nine benefits of managing stakeholders were identified which split into interim and eventual benefits. Originality This paper provides a richer understanding of the enablers and techniques which organisations should focus on while strategising for minimum resistance from stakeholders in their BIM implemented projects.

Deep Learning Model for Imbalanced Multi-label Surface Defect Classification

Automatic defect classification is vital to ensure product quality, especially for steel production. In the real world, the amount of collected samples with labels is limited due to high labor costs, and the gathered dataset is usually imbalanced, making accurate steel defect classification very challenging. In this paper, a novel deep learning model for imbalanced multi-label surface defect classification, named ImDeep, is proposed. It can be deployed easily in steel production lines to identify different defect types on the steel's surface. ImDeep incorporates three key techniques, i.e., Imbalanced Sampler, Fussy-FusionNet, and Transfer Learning. It improves the model's classification performance with multi-label and reduces the model's complexity over small datasets with low latency. The performance of different fusion strategies and three key techniques of ImDeep is verified. Simulation results prove that ImDeep accomplishes better performance than the state-of-the-art over the public dataset with varied sizes. Specifically, ImDeep achieves about 97% accuracy of steel surface defect classification over a small imbalanced dataset with a low latency, which improves about 10% compared with that of the state-of-the-art.

Research on the Methods and Key Techniques of Web Archive Oriented Social Media Information Collection

Social media information collection and preservation is a hot issue in the field of Web Archive. This paper makes a comparative analysis of the different social media information collection methods, deeply analyzes the key techniques of the three important parts-collection, evaluation and preservation in the information collection process, and provides the solutions for the problems in the key techniques. Through analysis, the collection method suitable for the social media information is found. In terms of the problem that social websites impose restrictions on the call frequency of API, the paper provides solutions, for example, use the multiplexing mechanism, use the naive Bayesian algorithm to solve the spam filtering problem, and use MongoDB Dbased distributed storage to store collected massive data.

Nanotech drug delivery system: The perfect physio-Chemical deal for biological command

The application of nanotechnology in drug delivery is offering several exhilarating possibilities not only in healthcare but also in agriculture. Nanoparticles combined with the therapeutic agents have a proven edge over problems associated with conventional therapy; however, some issues like side effects and toxicity are still under debate and are of prime concern in utilization in biological systems. Herein, we discuss the role of nanotech drug delivery system mostly in animal and plants- highlighting the comparative accounts of the key techniques for designing of drug in animals and plants, the challenges therein, the important nanoparticles being used in both the area and prospects of the field in the near future.