A controllable and reproducible synthesis of highly ordered two‐dimensional hexagonal mesoporous, crystalline bismuth‐doped TiO2 nanocomposites with variable Bi ratios is reported here. Analyses by ...transmission electron microscopy, X‐ray diffraction, Raman, and X‐ray photoelectron spectroscopy reveal that the well‐ordered mesostructure is doped with Bi, which exists as Bi3+ and Bi(3+x+). The Bi‐doped mesoporous TiO2 (ms‐TiO2) samples exhibit improved photocatalytic activities for simultaneous phenol oxidation and chromium reduction in aqueous suspension under visible and UV light over the pure ms‐TiO2, P‐25, and conventional Bi‐doped titania. The high catalytic activity is due to both the unique structural characteristics and the Bi doping. This new material extends the spectral response from UV to the visible region, and reduces electron–hole recombination, which renders the 2.0 % Bi‐doped ms‐TiO2 photocatalyst highly responsive to visible light.
Bismuth cleans up: Highly ordered 2D hexagonal mesoporous (ms) crystalline Bi‐doped TiO2 nanocomposites that are active catalysts in the visible region have been synthesized (see figure). The photocatalytic activity of 2.0 % Bi‐doped ms‐TiO2 is far superior to other TiO2 catalysts for the simultaneous degradation of phenol and reduction of chromium under visible illumination.
Statin therapy is the gold standard for hypercholesterolemia. However, a significant number of patients cannot achieve their target low-density lipoprotein (LDL) levels despite a maximal dose of ...statin therapy, and some cannot tolerate statins at all. Approval of proprotein convertase subtilisin/kexin type 9 inhibitors has been revolutionary for those patients. However, the need for frequent injections limits patient compliance with their use. Recently, a twice-yearly injection of inclisiran, a small interfering RNA, has been shown to inhibit hepatic synthesis of proprotein convertase subtilisin/kexin type 9. However, patient randomized clinical trial has been underpowered for clinical end points, necessitating a meta-analysis of those trials. The weighted mean difference was used to describe continuous variables, and pooled risk ratios, calculated using a random effects model, were used to describe discrete variables. Data from 3 randomized clinical trials comprising 3,660 patients showed that inclisiran decreased LDL cholesterol levels by 51% (95% Confidence Interval, 48 to 53%; p < 0.001) compared with placebo. It was associated with a 24% lower major adverse cardiovascular events rate (risk ratios = 0.76; 95% Confidence Interval, 0.61 to 0.92). It also significantly decreased total cholesterol by 37%, apolipoprotein B by 41%, and non high-density lipoprotein (HDL) cholesterol by 45% (all p < 0.001). No differences were found in adverse events, abnormalities in liver function tests, or creatine kinase levels between the treatment strategies. However, a mild injection site reaction occurred more frequently in the inclisiran group. In conclusions, in patients with hypercholesterolemia, inclisiran decreased LDL level by 51% without significant adverse effects. Additionally, it was associated with a lower major adverse cardiovascular event rate.
Large population-based studies examining differences in ICI-associated cardiotoxicity across cancer types and agents are limited. Data of 5518 cancer patients who received at least one cycle of ICIs ...were extracted from a large network of health care organizations. ICI treatment groups were classified by the first ICI agent(s) (ipilimumab, nivolumab, pembrolizumab, cemiplimab, avelumab, atezolizumab, or durvalumab) or its class (PD-1 inhibitors, PD-L1 inhibitors, CTLA4-inhibitors, or their combination (ipilimumab + nivolumab)). Time to first cardiac adverse event (CAE) (arrhythmia, acute myocardial infarction, myocarditis, cardiomyopathy, or pericarditis) developed within one year after ICI initiation was analyzed using a competing-risks regression model adjusting for ICI treatment groups, patient demographic and clinical characteristics, and cancer sites. By month 12, 12.5% developed cardiotoxicity. The most common cardiotoxicity was arrhythmia (9.3%) and 2.1% developed myocarditis. After adjusting for patient characteristics and cancer sites, patients who initiated on monotherapy with ipilimumab (adjusted Hazard Ratio (aHR): 2.00; 95% CI: 1.49−2.70; p < 0.001) or pembrolizumab (aHR: 1.21; 95% CI: 1.01−1.46; p = 0.040) had a higher risk of developing CAEs within one year compared to nivolumab monotherapy. Ipilimumab and pembrolizumab use may increase the risk of cardiotoxicity compared to other agents. Avelumab also estimated a highly elevated risk (aHR: 1.92; 95% CI: 0.85−4.34; p = 0.117) compared to nivolumab and other PD-L1 agents, although the estimate did not reach statistical significance, warranting future studies.
Fault tolerance, performance, and throughput have been major areas of research and development since the evolution of large-scale networks. Internet-based applications are rapidly growing, including ...large-scale computations, search engines, high-definition video streaming, e-commerce, and video on demand. In recent years, energy efficiency and fault tolerance have gained significant importance in data center networks and various studies directed the attention towards green computing. Data centers consume a huge amount of energy and various architectures and techniques have been proposed to improve the energy efficiency of data centers. However, there is a tradeoff between energy efficiency and fault tolerance. The objective of this study is to highlight a better tradeoff between the two extremes: (
) high energy efficiency and (
) ensuring high availability through fault tolerance and redundancy. The main objective of the proposed Energy-Aware Fault-Tolerant (EAFT) approach is to keep one level of redundancy for fault tolerance while scheduling resources for energy efficiency. The resultant energy-efficient data center network provides availability as well as fault tolerance at reduced operating cost. The main contributions of this article are: (
) we propose an Energy-Aware Fault-Tolerant (EAFT) data center network scheduler; (
) we compare EAFT with energy efficient resource scheduling techniques to provide analysis of parameters such as, workload distribution, average task per servers, and energy consumption; and (
) we highlight effects of energy efficiency techniques on the network performance of the data center.
Interest in individual‐level outcomes of corporate social responsibility (CSR) is gaining momentum in academic and managerial circles. This study investigated whether employees attributed different ...motives to CSR efforts and if these motives influenced employee's extra‐role behaviors (proactivity, knowledge sharing, creativity, and adaptivity). We also tested the moderating role of interpersonal trust and ethical corporate identity on the link between CSR attributions and employee's extra‐role behaviors. Data were collected from 360 employees and 117 supervisors from the hotel industry of Pakistan. Using hierarchical regression analyses, results show that CSR attributions affected employee's extra‐role behaviors. Moreover, interpersonal trust and ethical corporate identity were found to moderate the relationship between CSR attributions and extra‐role behaviors. Directions for future research and implications for practice are discussed.
The intelligent reflecting surface (IRS) is a cutting-edge technology for cost-effectively achieving future spectrum- and energy-efficient wireless communication. In particular, an IRS comprises many ...low-cost passive devices that can independently reflect the incident signal with a configurable phase shift to produce three-dimensional (3D) passive beamforming without transmitting Radio-Frequency (RF) chains. Thus, the IRS can be utilized to greatly improve wireless channel conditions and increase the dependability of communication systems. This article proposes a scheme for an IRS-equipped GEO satellite signal with proper channel modeling and system characterization. Gabor filter networks (GFNs) are jointly proposed for the extraction of distinct features and the classification of these features. Hybrid optimal functions are used to solve the estimated classification problem, and a simulation setup was designed along with proper channel modeling. The experimental results show that the proposed IRS-based methodology provides higher classification accuracy than the benchmark without the IRS methodology.
Cloud computing has emerged as the leading paradigm for information technology businesses. Cloud computing provides a platform to manage and deliver computing services around the world over the ...Internet. Cloud services have helped businesses utilize computing services on demand with no upfront investments. The cloud computing paradigm has sustained its growth, which has led to increase in size and number of data centers. Data centers with thousands of computing devices are deployed as back end to provide cloud services. Computing devices are deployed redundantly in data centers to ensure 24/7 availability. However, many studies have pointed out that data centers consume large amount of electricity, thus calling for energy-efficiency measures. In this survey, we discuss research issues related to conflicting requirements of maximizing quality of services (QoSs) (availability, reliability, etc.) delivered by the cloud services while minimizing energy consumption of the data center resources. In this paper, we present the concept of inception of data center energy-efficiency controller that can consolidate data center resources with minimal effect on QoS requirements. We discuss software- and hardware-based techniques and architectures for data center resources such as server, memory, and network devices that can be manipulated by the data center controller to achieve energy efficiency.
Automatic modulation recognition (AMR) is used in various domains—from general-purpose communication to many military applications—thanks to the growing popularity of the Internet of Things (IoT) and ...related communication technologies. In this research article, we propose an innovative idea of combining the classical mathematical technique of computing linear combinations (LCs) of cumulants with a genetic algorithm (GA) to create super-cumulants. These super-cumulants are further used to classify five digital modulation schemes on fading channels using the K-nearest neighbor (KNN). Our proposed classifier significantly improves the percentage recognition accuracy at lower SNRs when using smaller sample sizes. A comparison with existing techniques manifests the supremacy of our proposed classifier.
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