Significant enhancement of anticancer effect of iridium (III) complexes encapsulated in liposomes.

In this study, the ligand EIPP (5-ethoxy-2-(1H-imidazo[4,5-f] [1,10] phenanthrolin-2-yl)phenol) and [Ir(ppy)(EIPP)](PF)] (5a, ppy = 2-phenylpyridine) and [Ir(piq)(EIPP)](PF)] (5b, piq = 1-phenylisoquinoline) were synthesized and they were entrapped into liposomes to produce 5alipo and 5blipo. 5a and 5b were characterized via HRMS, NMR, UV-vis and IR. The cytotoxicity of 5a, 5b, 5alipo and 5blipo on cancer and non-cancer cells was estimated using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT).

Digital economy's role in shaping carbon emissions in the construction field: Insights from Chinese cities.

Achieving net-zero greenhouse gas emissions in the construction sector is essential to sustainable development policy. Previous studies have ignored the impact of the digital economy on carbon emissions in the construction industry. Using relevant city-level data from China from 2011 to 2021 and employing ArcGIS and Stata software, this study examines the current status of carbon emissions from the construction industry and investigates the impact of the digital economy on these emissions.

Association between fat and fat-free body mass indices on shock attenuation during running.

High amplitudes of shock during running have been thought to be associated with an increased injury risk. This study aimed to quantify the association between dual-energy X-ray absorptiometry (DEXA) quantified body composition, and shock attenuation across the time and frequency domains. Twenty-four active adults participated.

Smooth and accurate predictions of joint contact force time-series in gait using over parameterised deep neural networks.

Alterations in joint contact forces (JCFs) are thought to be important mechanisms for the onset and progression of many musculoskeletal and orthopaedic pain disorders. Computational approaches to JCFs assessment represent the only non-invasive means of estimating forces; but this cannot be undertaken in free-living environments. Here, we used deep neural networks to train models to predict JCFs, using only joint angles as predictors.

Monocular 3D Human Pose Markerless Systems for Gait Assessment.

Gait analysis plays an important role in the fields of healthcare and sports sciences. Conventional gait analysis relies on costly equipment such as optical motion capture cameras and wearable sensors, some of which require trained assessors for data collection and processing. With the recent developments in computer vision and deep neural networks, using monocular RGB cameras for 3D human pose estimation has shown tremendous promise as a cost-effective and efficient solution for clinical gait analysis.

Expanding window compressed sensing for non-uniform compressible signals.

Many practical compressible signals like image signals or the networked data in wireless sensor networks have non-uniform support distribution in their sparse representation domain. Utilizing this prior information, a novel compressed sensing (CS) scheme with unequal protection capability is proposed in this paper by introducing a windowing strategy called expanding window compressed sensing (EW-CS). According to the importance of different parts of the signal, the signal is divided into several nested subsets, i.

Distributed joint source-channel coding in wireless sensor networks.

Considering the fact that sensors are energy-limited and the wireless channel conditions in wireless sensor networks, there is an urgent need for a low-complexity coding method with high compression ratio and noise-resisted features. This paper reviews the progress made in distributed joint source-channel coding which can address this issue. The main existing deployments, from the theory to practice, of distributed joint source-channel coding over the independent channels, the multiple access channels and the broadcast channels are introduced, respectively.