COVID-19 is a newly emerging infectious disease, which is generally susceptible to human beings and has caused huge losses to people's health. Acute respiratory distress syndrome (ARDS) is one of the ...common clinical manifestations of severe COVID-19 and it is also responsible for the current shortage of ventilators worldwide. This study aims to analyze the clinical characteristics of COVID-19 ARDS patients and establish a diagnostic system based on artificial intelligence (AI) method to predict the probability of ARDS in COVID-19 patients. We collected clinical data of 659 COVID-19 patients from 11 regions in China. The clinical characteristics of the ARDS group and no-ARDS group of COVID-19 patients were elaborately compared and both traditional machine learning algorithms and deep learning-based method were used to build the prediction models. Results indicated that the median age of ARDS patients was 56.5 years old, which was significantly older than those with non-ARDS by 7.5 years. Male and patients with BMI > 25 were more likely to develop ARDS. The clinical features of ARDS patients included cough (80.3%), polypnea (59.2%), lung consolidation (53.9%), secondary bacterial infection (30.3%), and comorbidities such as hypertension (48.7%). Abnormal biochemical indicators such as lymphocyte count, CK, NLR, AST, LDH, and CRP were all strongly related to the aggravation of ARDS. Furthermore, through various AI methods for modeling and prediction effect evaluation based on the above risk factors, decision tree achieved the best AUC, accuracy, sensitivity and specificity in identifying the mild patients who were easy to develop ARDS, which undoubtedly helped to deliver proper care and optimize use of limited resources.
Additive manufacturing provides great geometrical freedom for fabricating structures with complex or customized architecture. One of the applications benefiting from this technology is the ...fabrication of functionally graded materials with high degree of control of internal architecture which can be strategic application in advanced energy absorption. This study aims to explore the mechanical properties of functionally graded lattice structures fabricated by an additive manufacturing technique namely, selective laser melting (SLM), with Ti-6Al-4V as the building material. Both cubic lattice and honeycomb lattice structures with varied strut diameter and density were designed and manufactured, and their physical characteristics, deformation behavior and compressive properties were investigated. The collapse of structure always started from least dense layer to the denser layers. In contrast, samples with uniform density showed abrupt shear failure with diagonal cracking across the whole structure. The plateau stress and specific energy absorption of density graded samples were higher than for uniform density samples for three out of four designs by up to 67% and 72%, respectively. In addition, density graded lattices showed distinct energy absorption behavior with cumulative energy absorption increasing as a power of strain function while uniform density lattices showed a near-linear relationship.
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•New designs of functionally graded material with continuous density change were investigated.•The designs were opposed to those reported in literature with abrupt change.•The designed structures were shown to have novel deformation behavior than homogenous counterparts under compression.•Plateau stress and specific energy absorption of the structures were higher than homogenous counterparts for most designs.
Here, a Sn–C composite material prepared from bulk precursors (tin metal, graphite, and melamine) using ball milling and annealing is reported. The composite (58 wt% Sn and 42 wt% N‐doped carbon) ...shows a capacity up to 445 mAh gSn+C−1 and an excellent cycle life (1000 cycles). For the graphite, the ball milling leads to graphene nanoplatelets (GnP) for which the storage mechanism changes from solvent co‐intercalation to conventional intercalation. The final composite (Sn at nitrogen‐doped graphite nanoplatelets (SnNGnP)) is obtained by combining the GnPs with Sn and melamine as the nitrogen source. Rate‐dependent measurements and in situ X‐ray diffraction are used to study the asymmetric storage behavior of Sn, which shows a more sloping potential profile during sodiation and more defined steps during desodiation. The disappearance of two redox plateaus during desodiation is linked to the preceding sodiation current density (memory effect). The asymmetric behavior is also found by in situ electrochemical dilatometry. This method also shows that the effective electrode expansion during sodiation is much smaller (about +14%) compared to what is expected from Sn (+420%), which gives a reasonable explanation for the excellent cycle life for the SnNGnP (and likely other nanocomposites in general). Next to the advantages, challenges, which result from the nanocomposite approach, are also discussed.
Tin supported by nitrogen‐doped graphene nanoplatelets is found to be an efficient anode for sodium‐ion batteries. Rate‐dependent measurements and in situ diffraction reveal the asymmetric storage behavior of tin within a cycle as well as a memory effect. The in situ electrochemical dilatometry study shows the active role of the support in mitigating the large volume changes of tin during (de)sodiation.
The study of cognitive processes in English teaching methods from the perspective of HPM (History and Pedagogy of Mathematics) provides valuable insights into how students learn and understand the ...English language. Cognitive research in language learning focuses on the mental processes involved in acquiring, processing, and using language skills. By incorporating the principles of HPM, which examines the historical development and pedagogical approaches in mathematics education, researchers can draw parallels and apply similar methodologies to English language instruction. This paper constructed Bloom's taxonomy Fuzzy Decision Support System (BTF-DSS). Bloom's taxonomy provides information about the teacher's understanding towards the teaching. Through BTF-DSS model offers teachers provides the knowledge and expertise for effective teaching with the fuzzy model. The BTF-DSS model uses the fuzzy logic decision support system for the appropriate significant teaching and learning experience. The simulation analysis of the BTF-DSS model expressed that the fuzzy model exhibits significant performance for the English teaching method in China through the HPM process.
The prevalence of overweight and obesity is on the rise around the world. Common comorbidities associated with obesity, particularly diabetes, hypertension, and heart disease have an impact on social ...and financial systems. Appropriate lifestyle and behavior interventions are still the crucial cornerstone to weight loss success, but maintaining such a healthy lifestyle is extremely challenging. Abundant natural materials have been explored for their obesity treatment potential and widely used to promote the development of anti-obesity products. The weight loss segment is one of the major contributors to the overall revenue of the dietary supplements market. In this review, the anti-obesity effects of different dietary or herbal products, and their active ingredients and mechanisms of action against obesity will be discussed.
•An enhanced particle shifting technique (PST) is presented to overcome the deficiencies of traditional PSTs.•The volume-non-conservation issue is tackled by introducing a corrective cohesion force ...between particles.•The non-physical gap issue is alleviated by introducing a different free-surface treatment.•Four benchmarks are implemented to validate the effectiveness and stability of the present scheme.•Satisfactory numerical results are obtained in WCSPH simulations of violent free-surface flows.
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The non-conservation of total fluid volume, caused by the accumulating errors on the potential energy of the fluid, has been a serious numerical issue in a Weakly-Compressible SPH (WCSPH) simulation when transitional Particle Shifting Techniques (PSTs) are employed to prevent disordered particle distribution and the tensile instability from negative pressures. This paper is dedicated to, within the framework of WCSPH, developing an enhanced version that remedies the aforementioned deficiency of the traditional PSTs, and meanwhile improves the quality of the particle distribution in the vicinity of a free-surface region. To this end, a Corrective Cohesion Force (CCF) between a target particle and its interacting particles is introduced to provide adaptive compensation corresponding to the particle repositioning. Four classical benchmarks are implemented to validate the effectiveness and stability of the present PST. It is demonstrated that the new PST incorporating with the CCF shows satisfactory performance to improve the conservation of total fluid volume, and to obtain more uniform particle distribution in the proximity of the free-surface. In addition, the newly-developed PST also maintains the accuracy and stability inherited from the traditional versions, suggesting that it can be treated as an ideal alternative with regard to the traditional PSTs in a WCSPH simulation, especially for a long-term-duration case with violent free-surface evolutions.
Alcoholic liver disease (ALD) refers to the damages to the liver and its functions due to alcohol overconsumption. It consists of fatty liver/steatosis, alcoholic hepatitis, steatohepatitis, chronic ...hepatitis with liver fibrosis or cirrhosis, and hepatocellular carcinoma. However, the mechanisms behind the pathogenesis of alcoholic liver disease are extremely complicated due to the involvement of immune cells, adipose tissues, and genetic diversity. Clinically, the diagnosis of ALD is not yet well developed. Therefore, the number of patients in advanced stages has increased due to the failure of proper early detection and treatment. At present, abstinence and nutritional therapy remain the conventional therapeutic interventions for ALD. Moreover, the therapies which target the TNF receptor superfamily, hormones, antioxidant signals, and MicroRNAs are used as treatments for ALD. In particular, mesenchymal stem cells (MSCs) are gaining attention as a potential therapeutic target of ALD. Therefore, in this review, we have summarized the current understandings of the pathogenesis and diagnosis of ALD. Moreover, we also discuss the various existing treatment strategies while focusing on promising therapeutic approaches for ALD.
This paper presents a scaling friendly mostly digital voltage-controlled-oscillator (VCO)-based 0-1 multistage noise shaping (MASH) analog-to-digital converter. A novel background calibration ...technique corrects conversion errors due to VCO linear gain drift, residue generating digital-to-analog converter mismatches, and nonlinearity of the VCO voltage-to-frequency conversion. The proposed architecture minimally modifies the basic 0-1 MASH architecture and directly calibrates the main VCOs without relying on replica matching. A redundant first-stage coarse quantizer enables fast error estimation in the digital domain. A 12-b prototype implemented in 180-nm CMOS achieves 12-b ENOB over 2.5 MHz and consumes 4.8 mW from a 1.8 V supply.
This paper presents a high dynamic range (DR) power-efficient voltage-controlled oscillator (VCO)-based continuous-time ΔΣ modulator. It introduces a robust and low-power fully-digital phase extended ...quantizer that doubles the VCO quantizer resolution compared to a conventional XOR-based phase detector. A tri-level resistor digital-to-analog converter is also introduced as complementary to the new quantizer, enabling high DR while creating a dynamic power saving mechanism for the proposed design. Fabricated in 130-nm CMOS, the analog-to-digital converter achieved peak Schreier Figure-of-Merit (FoM) of 174.3 dB with a high DR of 89 dB over 0.4-MHz BW, consuming only 1 mW under 1.2-V power supply. It also reaches a peak Walden FoM of 59 fJ/conv with 74.7-dB signal-to-noise-and-distortion ratio over 2-MHz BW.
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