Addressing Criticality Levels in Critical Infrastructure System

Abstract-Modern society depends on the operations of critical infrastructure system (CIs), such as transportation, energy, telecommunications, and water. Characterized by direct and transitive interdependencies, these systems have become so interconnected that disruption of one may lead to disruptions in all. The levels in critical infrastructures must firstly be classified in order to make a systemic perspective for critical infrastructure system protection). This paper discusses critical infrastructure interdependencies by highlighting some examples of cascading failure phenomena from references and experts. By utilizing the Interpretive Structural Modeling (ISM) methodology, we analyze the interactions of eight critical infrastructures according to their mutual influences, thereby we identify those driving infrastructures, which can aggravate a few more infrastructure and those dependent infrastructures, which are most influenced by driving infrastructure. It can be also observed that there are some infrastructures, which have both high driving power and dependency, thus needing more attention. The approach taken in this research can form the basis for the analysis of the system of systems that represents the CIs

A Review of the Role of Tendon Stem Cells in Tendon-Bone Regeneration

Tendon-bone injuries are a prevalent health concern associated with sports and other physically demanding activities. These injuries have a limited innate healing ability, often leading to the formation of scar tissue rather than the regeneration of healthy tendon tissue. This scar tissue results from excessive fibrosis during the early healing process and often leads to reduced tendon function and an increased risk of reinjury. Traditionally, surgical reconstruction has been the primary treatment for tendon-bone injuries. However, restoring the natural structure and mechanical properties of tendons after surgical reconstruction presents a considerable challenge. Recently, the potential of stem cell therapy has been explored as an alternative treatment approach. In particular, a new type of pluripotent stem cell known as tendon stem cells (TDSCs) has been identified within tendon tissue. These cells exhibit the potential for self-renewal and multidirectional differentiation, meaning they can differentiate into fibroblasts and chondrocytes. These differentiated cells can aid in the repair and regeneration of new tissues by producing collagen and other matrix molecules that provide structural support. TDSCs have become a focal point in research for treating tendon-bone injuries and related conditions. The potential use of these cells provides a basis for both basic research and clinical applications, particularly in understanding the tendon-bone healing process and identifying factors that affect the ability of TDSCs to promote this healing. This review article aims to analyze the role of TDSCs in tendon-bone healing, understanding their therapeutic potential and contributing to the development of effective treatment strategies for tendon-bone injuries

Application and Evaluation of an Explicit Prognostic Cloud Cover Scheme in GRAPES Global Forecast System

An explicit prognostic cloud‐cover scheme (PROGCS) is implemented into the Global/Regional Assimilation and Prediction System (GRAPES) for global middle‐range numerical weather predication system (GRAPES_GFS) to improve the model performance in simulating cloud cover and radiation. Unlike the previous diagnostic cloud‐cover scheme (DIAGCS), PROGCS considers the formation and dissipation of cloud cover by physically connecting it to the cumulus convection and large‐scale stratiform condensation processes. Our simulation results show that clouds in mid‐high latitudes arise mainly from large‐scale stratiform condensation processes, while cumulus convection and large‐scale condensation processes jointly determine cloud cover in low latitudes. Compared with DIAGCS, PROGCS captures more consistent vertical distributions of cloud cover with the observations from Atmospheric Radiation Measurements (ARM) program at the Southern Great Plains (SGP) site and simulates more realistic diurnal cycle of marine stratocumulus with the ERA‐Interim reanalysis data. The low, high, and total cloud covers that are determined via PROGCS appear to be more realistic than those simulated via DIAGCS when both are compared with satellite retrievals though the former maintains slight negative biases. In addition, the simulations of outgoing longwave radiation (OLR) at the top of the atmosphere (TOA) from PROGCS runs have been considerably improved as well, resulting in less biases in radiative heating rates at heights below 850 hPa and above 400 hPa of GRAPES_GFS. Our results indicate that a prognostic method of cloud‐cover calculation has significant advantage over the conventional diagnostic one, and it should be adopted in both weather and climate simulation and forecast

Warming effect of dust aerosols modulated by overlapping clouds below

Due to the substantial warming effect of dust aerosols overlying clouds and its poor representation in climate models, it is imperative to accurately quantify the direct radiative forcing (DRF) of above-cloud dust aerosols. When absorbing aerosol layers are located above clouds, the warming effect of aerosols strongly depends on the cloud macro- and micro-physical properties underneath, such as cloud optical depth and cloud fraction at visible wavelength. A larger aerosol-cloud overlap is believed to cause a larger warming effect of absorbing aerosols, but the influence of overlapping cloud fraction and cloud optical depth remains to be explored. In this study, the impact of overlapping cloud properties on the shortwave all-sky DRF due to springtime above-cloud dust aerosols is quantified over northern Pacific Ocean based on 10-year satellite measurements. On average, the DRF is roughly 0.62 Wm^(−2). Furthermore, the warming effect of dust aerosols linearly increases with both overlapping cloud fraction and cloud optical depth. An increase of 1% in overlapping cloud fraction will amplify this warming effect by 1.11 Wm^(−2)τ^(−1). For the springtime northern Pacific Ocean, top-of-atmosphere cooling by dust aerosols turns into warming when overlapping cloud fraction is beyond 0.20. The variation of critical cloud optical depth beyond which dust aerosols switch from exerting a net cooling to a net warming effect depends on the concurrent overlapping cloud fraction. When the overlapping cloud coverage range increases from 0.2 to –0.4 to 0.6–0.8, the corresponding critical cloud optical depth reduces from 6.92 to 1.16. Our results demonstrate the importance of overlapping cloud properties for determining the springtime warming effect of dust aerosols

The role of C-peptide in diabetes and its complications: an updated review

Worldwide, diabetes and its complications have seriously affected people’s quality of life and become a serious public health problem. C-peptide is not only an indicator of pancreatic β-cell function, but also a biologically active peptide that can bind to cell membrane surface signaling molecules and activate downstream signaling pathways to play antioxidant, anti-apoptotic and inflammatory roles, or regulate cellular transcription through internalization. It is complex how C-peptide is related to diabetic complications. Both deficiencies and overproduction can lead to complications, but their mechanisms of action may be different. C-peptide replacement therapy has shown beneficial effects on diabetic complications in animal models when C-peptide is deficient, but results from clinical trials have been unsatisfactory. The complex pattern of the relationship between C-peptide and diabetic chronic complications has not yet been fully understood. Future basic and clinical studies of C-peptide replacement therapies will need to focus on baseline levels of C-peptide in addition to more attention also needs to be paid to post-treatment C-peptide levels to explore the optimal range of fasting C-peptide and postprandial C-peptide maintenance

Analysis of multidrug-resistant bacteria in 3223 patients with hospital-acquired infections (HAI) from a tertiary general hospital in China

The frequency of antimicrobial resistance has increased globally due to misuse and overuse of antibiotics, and multi-drug resistant (MDR) bacteria are now recognized as a major cause of hospital-acquired infections (HAI). Our aim was to investigate the prevalence, distribution, and antimicrobial susceptibility rates of MDR bacteria in patients with HAI from a tertiary hospital in China. We retrospectively evaluated all patients with a confirmed diagnosis of bacterial infection at a tertiary general hospital in Jining, for the period between January 2012 and December 2014. The following clinical and demographic data were collected: age, sex, specimens, treatment, microbiology results, and antibiotic resistance patterns of isolates. Bacterial identification and susceptibility testing were performed using VITEK 2 COMPACT system. We screened a total of 15,588 patients, out of which 7579 (48.6%) had an HAI. MDR showed 3223 out of 7579 isolates (42.5%). The most frequently isolated MDR bacteria in patients with HAI were extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli (n = 1216/3223, 37.7%), MDR Pseudomonas aeruginosa (n = 627/3223, 19.5%) and MDR Acinetobacter baumannii (n = 588/3223, 18.2%). MDR-HAI were more common in males (2074/3223, 64.4%) and in elderly patients (≥60 years; 1196/3223, 37.1%). Sputum was the main source of MDR isolates (2056/3223, 63.8%). Patients with MDR-HAI were predominantly distributed in different types of intensive care units. MDR strains in our study showed resistance to most current antibiotics. Overall, patients with HAI infections attributed to MDR bacteria were widely distributed in our hospital. Enhanced surveillance of MDR bacteria is critical for guiding the rational use of antibiotics and reducing the incidence of HAI

Application and Evaluation of an Explicit Prognostic Cloud Cover Scheme in GRAPES Global Forecast System

An explicit prognostic cloud‐cover scheme (PROGCS) is implemented into the Global/Regional Assimilation and Prediction System (GRAPES) for global middle‐range numerical weather predication system (GRAPES_GFS) to improve the model performance in simulating cloud cover and radiation. Unlike the previous diagnostic cloud‐cover scheme (DIAGCS), PROGCS considers the formation and dissipation of cloud cover by physically connecting it to the cumulus convection and large‐scale stratiform condensation processes. Our simulation results show that clouds in mid‐high latitudes arise mainly from large‐scale stratiform condensation processes, while cumulus convection and large‐scale condensation processes jointly determine cloud cover in low latitudes. Compared with DIAGCS, PROGCS captures more consistent vertical distributions of cloud cover with the observations from Atmospheric Radiation Measurements (ARM) program at the Southern Great Plains (SGP) site and simulates more realistic diurnal cycle of marine stratocumulus with the ERA‐Interim reanalysis data. The low, high, and total cloud covers that are determined via PROGCS appear to be more realistic than those simulated via DIAGCS when both are compared with satellite retrievals though the former maintains slight negative biases. In addition, the simulations of outgoing longwave radiation (OLR) at the top of the atmosphere (TOA) from PROGCS runs have been considerably improved as well, resulting in less biases in radiative heating rates at heights below 850 hPa and above 400 hPa of GRAPES_GFS. Our results indicate that a prognostic method of cloud‐cover calculation has significant advantage over the conventional diagnostic one, and it should be adopted in both weather and climate simulation and forecast

East Asian Study of Tropospheric Aerosols and their Impact on Regional Clouds, Precipitation, and Climate (EAST-AIR_(CPC))

Aerosols have significant and complex impacts on regional climate in East Asia. Cloud‐aerosol‐precipitation interactions (CAPI) remain most challenging in climate studies. The quantitative understanding of CAPI requires good knowledge of aerosols, ranging from their formation, composition, transport, and their radiative, hygroscopic, and microphysical properties. A comprehensive review is presented here centered on the CAPI based chiefly, but not limited to, publications in the special section named EAST‐AIRcpc concerning (1) observations of aerosol loading and properties, (2) relationships between aerosols and meteorological variables affecting CAPI, (3) mechanisms behind CAPI, and (4) quantification of CAPI and their impact on climate. Heavy aerosol loading in East Asia has significant radiative effects by reducing surface radiation, increasing the air temperature, and lowering the boundary layer height. A key factor is aerosol absorption, which is particularly strong in central China. This absorption can have a wide range of impacts such as creating an imbalance of aerosol radiative forcing at the top and bottom of the atmosphere, leading to inconsistent retrievals of cloud variables from space‐borne and ground‐based instruments. Aerosol radiative forcing can delay or suppress the initiation and development of convective clouds whose microphysics can be further altered by the microphysical effect of aerosols. For the same cloud thickness, the likelihood of precipitation is influenced by aerosols: suppressing light rain and enhancing heavy rain, delaying but intensifying thunderstorms, and reducing the onset of isolated showers in most parts of China. Rainfall has become more inhomogeneous and more extreme in the heavily polluted urban regions