Comparing open data benchmarks: Which metrics and methodologies determine countries’ positions in the ranking lists?

An understanding of the similar and divergent metrics and methodologies underlying open government data benchmarks can reduce the risks of the potential misinterpretation and misuse of benchmarking outcomes by policymakers, politicians, and researchers. Hence, this study aims to compare the metrics and methodologies used to measure, benchmark, and rank governments' progress in open government data initiatives. Using a critical meta-analysis approach, we compare nine benchmarks with reference to meta-data, meta-methods, and meta-theories. This study finds that both existing open government data benchmarks and academic open data progress models use a great variety of metrics and methodologies, although open data impact is not usually measured. While several benchmarks’ methods have changed over time, and variables measured have been adjusted, we did not identify a similar pattern for academic open data progress models. This study contributes to open data research in three ways: 1) it reveals the strengths and weaknesses of existing open government data benchmarks and academic open data progress models; 2) it reveals that the selected open data benchmarks employ relatively similar measures as the theoretical open data progress models; and 3) it provides an updated overview of the different approaches used to measure open government data initiatives’ progress. Finally, this study offers two practical contributions: 1) it provides the basis for combining the strengths of benchmarks to create more comprehensive approaches for measuring governments’ progress in open data initiatives; and 2) it explains why particular countries are ranked in a certain way. This information is essential for governments and researchers to identify and propose effective measures to improve their open data initiatives.     

Magnetically Guidable Proteinaceous Adhesive Microbots for Targeted Locoregional Therapeutics Delivery in the Highly Dynamic Environment of the Esophagus

The esophagus is a tubular-shaped muscular organ where swallowed fluids and muscular contractions constitute a highly dynamic environment. The turbulent, coordinated processes that occur through the oropharyngeal conduit can often compromise targeted administration of therapeutic drugs to a lesion, significantly reducing therapeutic efficacy. Here, magnetically guidable drug vehicles capable of strongly adhering to target sites using a bioengineered mussel adhesive protein (MAP) to achieve localized delivery of therapeutic drugs against the hydrodynamic physiological conditions are proposed. A suite of highly uniform microparticles embedded with iron oxide (IO) nanoparticles (MAP@IO MPs) is microfluidically fabricated using the genipin-mediated covalent cross-linking of bioengineered MAP. The MAP@IO MPs are successfully targeted to a specific region and prolongedly retained in the tubular-structured passageway. In particular, orally administered MAP@IO MPs are effectively captured in the esophagus in vivo in a magnetically guidable manner. Moreover, doxorubicin (DOX)-loaded MAP@IO MPs exhibit a sustainable DOX release profile, effective anticancer therapeutic activity, and excellent biocompatibility. Thus, the magnetically guidable locomotion and robust underwater adhesive properties of the proteinaceous soft microbots can provide an intelligent modular approach for targeted locoregional therapeutics delivery to a specific lesion site in dynamic fluid-associated tubular organs such as the esophagus.     

Recent Advances in Design of Functional Biocompatible Hydrogels for Bone Tissue Engineering

Bone related diseases have caused serious threats to human health owing to their complexity and specificity. Fortunately, owing to the unique 3D network structure with high aqueous content and functional properties, emerging hydrogels are regarded as one of the most promising candidates for bone tissue engineering, such as repairing cartilage injury, skull defect, and arthritis. Herein, various design strategies and synthesis methods (e.g., 3D-printing technology and nanoparticle composite strategy) are introduced to prepare implanted hydrogel scaffolds with tunable mechanical strength, favorable biocompatibility, and excellent bioactivity for applying in bone regeneration. Injectable hydrogels based on biocompatible materials (e.g., collagen, hyaluronic acid, chitosan, polyethylene glycol, etc.) possess many advantages in minimally invasive surgery, including adjustable physicochemical properties, filling irregular shapes of defect sites, and on-demand release drugs or growth factors in response to different stimuli (e.g., pH, temperature, redox, enzyme, light, magnetic, etc.). In addition, drug delivery systems based on micro/nanogels are discussed, and its numerous promising designs used in the application of bone diseases (e.g., rheumatoid arthritis, osteoarthritis, cartilage defect) are also briefed in this review. Particularly, several key factors of hydrogel scaffolds (e.g., mechanical property, pore size, and release behavior of active factors) that can induce bone tissue regeneration are also summarized in this review. It is anticipated that advanced approaches and innovative ideas of bioactive hydrogels will be exploited in the clinical field and increase the life quality of patients with the bone injury.     

Enzyme-Activated Prodrug-Based Smart Liposomes Specifically Enhance Tumor Hemoperfusion with Efficient Drug Delivery to Pancreatic Cancer Cells and Stellate Cells

Tumor-specific enhanced delivery of chemotherapeutics and modulators to tumor cells and activated pancreatic stellate cells (aPSCs), respectively, represents safer and more effective therapy for pancreatic cancer. Herein, a membrane type 1-matrix metalloproteinase (MT1-MMP)-cleavable spacer is used to assemble low-density cRGDfK onto thermosensitive liposomes loaded with phosphorylated calcipotriol (PCAL) and doxorubicin (DOX), yielding MR-T-PD. The liposome-linked cRGDfK prodrug on MR-T-PD surface is first activated by MT1-MMP, which is selectively expressed on tumor endothelial cells, to release cRGDfK. The free cRGDfK specifically promotes tumor angiogenesis, leading to 3.4-fold higher accumulation and a wider distribution of MR-T-PD in tumors. Furthermore, MR-T-PD rapidly releases PCAL and DOX into the interstitium under heat treatment. The released DOX enters tumor cells to induce apoptosis, whereas the PCAL prodrug is converted to CAL by alkaline phosphatase on the surface of aPSCs; CAL can then enter aPSCs to induce quiescence and promote the antitumor effect of DOX. Finally, by enhancing the exposure of DOX and CAL to tumor cells and aPSCs, respectively, in a tumor-specific manner, MR-T-PD exerts superior efficacy (a 5.9-fold decrease in tumor weight) without causing additional side effects. Overall, this prodrug-based smart liposome system represents a promising paradigm for pancreatic cancer therapy.     

Hepatitis B Virus-Like Particle: Targeted Delivery of Plasmid Expressing Short Hairpin RNA for Silencing the Bcl-2 Gene in Cervical Cancer Cells

Gene therapy research has advanced to clinical trials, but it is hampered by unstable nucleic acids packaged inside carriers and there is a lack of specificity towards targeted sites in the body. This study aims to address gene therapy limitations by encapsidating a plasmid synthesizing a short hairpin RNA (shRNA) that targets the anti-apoptotic Bcl-2 gene using truncated hepatitis B core antigen (tHBcAg) virus-like particle (VLP). A shRNA sequence targeting anti-apoptotic Bcl-2 was synthesized and cloned into the pSilencer 2.0-U6 vector. The recombinant plasmid, namely PshRNA, was encapsidated inside tHBcAg VLP and conjugated with folic acid (FA) to produce FA-tHBcAg-PshRNA VLP. Electron microscopy revealed that the FA-tHBcAg-PshRNA VLP has an icosahedral structure that is similar to the unmodified tHBcAg VLP. Delivery of FA-tHBcAg-PshRNA VLP into HeLa cells overexpressing the folate receptor significantly downregulated the expression of anti-apoptotic Bcl-2 at 48 and 72 h post-transfection. The 3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide (MTT) assay demonstrated that the cells’ viability was significantly reduced from 89.46% at 24 h to 64.52% and 60.63%, respectively, at 48 and 72 h post-transfection. As a conclusion, tHBcAg VLP can be used as a carrier for a receptor-mediated targeted delivery of a therapeutic plasmid encoding shRNA for gene silencing in cancer cells.     

基于K-means和SOM的水下传感器数据采集方法

随着海洋资源勘探和海洋污染物监控工作的开展，水文数据的监测和采集等已经成为重要的研究方向。其中，水下无线传感器网络在水文数据采集过程中起着举足轻重的作用。本文研究的是水下无线传感器二维监测网络模型中，传感器节点数据采集的问题，其设计方法是通过自组织映射（Self-organizing mapping，SOM）对传感器节点进行路径最优化处理，结合优化的路径图形和K-means算法找到路径内部聚合点，利用聚合点和传感器的节点得到传感器通信半径内的数据采集点，最后通过SOM得到水下机器人（Autonomous underwater vehicle，AUV）到各个数据采集点采集数据的最优路径。经过实验验证，在水下1 200 m×1 750 m范围内布置52个传感器节点的情景下，数据采集点相比于传感器节点路径规划采用相同的采集顺序得到的路径优化了6.7%；对数据采集点重新进行自组织路径规划得到的路径比传感器结点路径的最优解提高了12.2%。增加传感器节点的数量，其结果也大致相同，因此采用该方法可以提高水下机器人采集数据的效率。     

Perception of Artificial Intelligence in Spain

This paper analyses the perception of Artificial Intelligence (AI) by individuals in Spain and the factors associated with it. It uses data from 6308 individuals from a 2018 Spanish survey. A binary logit regression model is formulated and estimated for the attitude towards robots and AI and its possible determinants. As main results are that a gender gap is detected, and that people have a negative attitude if they are not interested in scientific discoveries and technological developments and if AI and robots are not useful at work.     

A novel multi-objective optimization method: Input values effect on responses (IVER)

In this study, a novel multi-objective optimization method based on the best effect of unique input (independent variable) values on responses (dependent variables) was proposed. The proposed method was compared with optimization using Derringer & Suich function that is still the most used. The comparison was made using the response values measured in real experiments and available in the literature. The advantages of the proposed method such as not needing the polynomial model aiming to predict the response values, no parameter selection problem, being able to offer optimum range instead of single optimum value, being suitable for use with existing experimental designs and being simple and interpretable were demonstrated as a result of comparison. It was also suggested how the proposed method will be effective according to experimental designs, and application for the users' application was presented.     

Adaptive Discretization for Computerized Tomography

Two adaptive discretization frameworks are tested for computerized tomography (CT) data reconstruction. Removal of inactive pixels is primary motivation. Efficient and user independent entropy optimized masking is employed for spatial filtering purposes. Density of nodes at high gradient of reconstructed physical property is used as adaptation criterion. An alternative option, independent from noisy projection data and nature of the physical properties, is also discussed. Sensitivity analysis between the uniform and nonuniform (evolved via adaptive route) reconstruction grid reveals the utility of nonuniform grids. Iterative and transform based reconstruction techniques are used. Outcomes are tested successfully on three real world projection data from two different compact CT setups and one commercial high-resolution micro-CT scanner.