Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges

Artificial General Intelligence (AGI), possessing the capacity to comprehend, learn, and execute tasks with human cognitive abilities, engenders significant anticipation and intrigue across scientific, commercial, and societal arenas. This fascination extends particularly to the Internet of Things (IoT), a landscape characterized by the interconnection of countless devices, sensors, and systems, collectively gathering and sharing data to enable intelligent decision-making and automation. This research embarks on an exploration of the opportunities and challenges towards achieving AGI in the context of the IoT. Specifically, it starts by outlining the fundamental principles of IoT and the critical role of Artificial Intelligence (AI) in IoT systems. Subsequently, it delves into AGI fundamentals, culminating in the formulation of a conceptual framework for AGI's seamless integration within IoT. The application spectrum for AGI-infused IoT is broad, encompassing domains ranging from smart grids, residential environments, manufacturing, and transportation to environmental monitoring, agriculture, healthcare, and education. However, adapting AGI to resource-constrained IoT settings necessitates dedicated research efforts. Furthermore, the paper addresses constraints imposed by limited computing resources, intricacies associated with large-scale IoT communication, as well as the critical concerns pertaining to security and privacy

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

Synthesis, characterization and thermal properties of novel nanoencapsulated phase change materials for thermal energy storage

In this paper, nanocapsules containing n-octadecane with an average 50 nm thick shell of poly(ethyl methacrylate) (PEMA) and poly(methyl methacrylate) (PMMA), and a core/shell weight ratio of 80/20 were synthesized by the direct miniemulsion method, respectively. The average size of the capsules is 140 nm and 119 nm, respectively. The chemical structure of the sample was analyzed using Fourier Transformed Infrared Spectroscopy (FTIR). Crystallography of nanocapsules was investigated by X-ray diffractometer. The surface morphology was studied by Scanning Electron Microscopy (SEM) and Transmission Electron Microscopy (TEM). The thermal properties and thermal stability of the sample were obtained from Differential Scanning Calorimeter (DSC) and Thermal Gravimetric Analysis (TGA). The temperatures and latent heats of melting and crystallizing of PEMA nanocapsule were determined as 32.7 and 29.8 °C, 198.5 and −197.1 kJ/kg, respectively. TGA analysis indicated that PEMA/octadecane nanocapsule had good thermal stability. The nanocapsules prepared in this work had a much higher encapsulation ratio (89.5%) and encapsulation efficiency (89.5%). Therefore, the findings of the work lead to the conclusion that the present work provides a novel method for fabricating nanoencapsulated phase change material, and it has a better potential for thermal energy storage

Molecular mapping of the hybrid necrosis gene NetJingY176 in Aegilops tauschii using microsatellite markers

The rich genetic variation preserved in collections of Aegilops tauschii can be readily exploited to improve common wheat using synthetic hexaploid wheat lines. However, hybrid necrosis, which is characterized by progressive death of leaves or plants, has been observed in certain interspecific crosses between tetraploid wheat and Ae. tauschii. The aim of this study was to construct a fine genetic map of a gene (temporarily named NetJingY176) conferring hybrid necrosis in Ae. tauschii accession Jing Y176. A triploid F1 population derived from distant hybridization between Ae. tauschii and tetraploid wheat was used to map the gene with microsatellite markers. The newly developed markers XsdauK539 and XsdauK561 co-segregated with NetJingY176 on chromosome arm 2DS. The tightly linked markers developed in this study were used to genotype 91 Ae. tauschii accessions. The marker genotype analysis suggested that 49.45% of the Ae. tauschii accessions carry NetJingY176. Interestingly, hybrid necrosis genotypes tended to appear more commonly in Ae. tauschii ssp. tauschii than in Ae. tauschii ssp. strangulata

Integrated plant diversity hotspots and long-term stable conservation strategies in the unique karst area of southern China under global climate change

The Karst Areas in Southern China are known for their abundant plant diversity and high endemism, but confronted with unprecedented challenges in biodiversity conservation. To identify hotspots and evaluate conservation effectiveness and gaps of the areas we built an occurrence database containing 16,073 species with 344,179 distribution points. We identified plant diversity hotspots by employing the top 5% richness algorithm, complementary algorithm and spatial phylogenetics, and evaluated the conservation effectiveness and gaps of hotspots under current conservation network by consideration spatial distribution ranges of both. Then, we conducted correlation analysis of distribution patterns and predicted suitable habitat areas of threatened species. Hotspots identified in this study are of high value in conservation priority for 75 hotspot grid cells scattered in 9 periphery regions of the karst areas and harboured 78.70% species only with 5% area. Conservation effectiveness analysis indicated that there were 38, 27 and 48 hotspot grid cells protected by either national nature reserves (NNRs), provincial nature reserves (PNRs), or both. These protected cells contained 59.28%, 49.08% and 64.76% of all species, respectively. However, conservation gaps analysis showed that 37, 48 and 27 hotspot grid cells were located outside of the conservation networks of NNRs, PNRs, or both, as they contained only 65.63%, 70.98% and 59.53% of all species. Further analysis of the conservation status of different taxa showed a high proportion of regional endemic and threatened species shared by hotspots and conservation gaps, which may be due to high percentage of narrow-ranged species occurring in both. More attentions should be paid to strengthen conservation networks and create new conservation areas to address the apparent gaps. Targeted conservation planning should also focus on hotspot distribution patterns of specific plant taxa to address the mismatches of distribution patterns of different taxa as indicated by different algorithms. Other countermeasures, for example, dynamic monitoring and rearrangement of the conservation network, should be envisaged in the future. The current and future suitable habitat areas are mostly confined to the heartland of karst areas, while the identified hotspots of plant diversity are much more limited, and especially under climate change scenarios the karst biodiversity will face huge challenges