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كسارة البندق
يفسح الواقع بالتدريج مجالا للخيالات الشبيهة بالأحلام والحكايات الخرافية داخل \"كسارة البندق\" التي تعد واحدة من أحسن القصص المؤلفة عن الكريسماس. ويتم من خلال هذه النسخة من \"السلسلة العالمية للروائع الأدبية\"-والتي يستعان فيها بالصور بشكل مبتكر-الكشف عن الخلفية التاريخية المبهرة التي تقوم عليها هذه الحكاية الرائعة. وقد أسهمت رسومات \"جيمس مايهو\" التي تتسم بالثراء في إثارة المعاني، إلى جانب إعادة الرواية بشكل مفعم بالحيوية لـ \"ديفيد كليمينت\" في إعادة كل ما كان يتمتع به النص الأصلي من طاقة وإثارة وخيال-الأمر الذي يجعل قصة \"كسارة البندق\" تتناسب مع كل الأعمار. إن الصور والحقائق التاريخية تضع القصة في سياق عصري ؛ لتسمح للقراء بالدخول كلية في عالم الحكاية الشبيه بالأحلام.
Book
WNT signalling pathway and diabetes mellitus
The WNT signalling pathway is involved in many physiological and pathophysiological activities. WNT ligands bind to Frizzled receptors and co-receptors (LDL receptor-related protein 5/6), triggering a cascade of signalling events. The major effector of the canonical WNT signalling pathway is the bipartite transcription factor β-catenin/T cell transcription factor (β-cat/TCF), formed by free β-cat and one of the four TCFs. The WNT pathway is involved in lipid metabolism and glucose homeostasis, and mutations in LRP5 may lead to the development of diabetes and obesity. β-Cat/TCF is also involved in the production of the incretin hormone glucagon-like peptide-1 in the intestinal endocrine L cells. More recently, genome-wide association studies have identified TCF7L2 as a diabetes susceptibility gene, and individuals carrying certain TCF7L2 single nucleotide polymorphisms could be more susceptible to the development of type 2 diabetes. Furthermore, β-cat is able to interact with forkhead box transcription factor subgroup O (FOXO) proteins. Since FOXO and TCF proteins compete for a limited pool of β-cat, enhanced FOXO activity during ageing and oxidative stress may attenuate WNT-mediated activities. These observations shed new light on the pathogenesis of type 2 diabetes as an age-dependent disease.
Journal Article
Highly compressible 3D periodic graphene aerogel microlattices
Graphene is a two-dimensional material that offers a unique combination of low density, exceptional mechanical properties, large surface area and excellent electrical conductivity. Recent progress has produced bulk 3D assemblies of graphene, such as graphene aerogels, but they possess purely stochastic porous networks, which limit their performance compared with the potential of an engineered architecture. Here we report the fabrication of periodic graphene aerogel microlattices, possessing an engineered architecture via a 3D printing technique known as direct ink writing. The 3D printed graphene aerogels are lightweight, highly conductive and exhibit supercompressibility (up to 90% compressive strain). Moreover, the Young’s moduli of the 3D printed graphene aerogels show an order of magnitude improvement over bulk graphene materials with comparable geometric density and possess large surface areas. Adapting the 3D printing technique to graphene aerogels realizes the possibility of fabricating a myriad of complex aerogel architectures for a broad range of applications.
Aerogels are ultra-lightweight porous materials that possess some remarkable properties. Here, the authors use a 3D printing technique to fabricate just such a material out of graphene, exhibiting large surface area, high conductivity and supercompressibility while maintaining good structural integrity.
Journal Article
Explainable machine learning in materials science
Machine learning models are increasingly used in materials studies because of their exceptional accuracy. However, the most accurate machine learning models are usually difficult to explain. Remedies to this problem lie in explainable artificial intelligence (XAI), an emerging research field that addresses the explainability of complicated machine learning models like deep neural networks (DNNs). This article attempts to provide an entry point to XAI for materials scientists. Concepts are defined to clarify what explain means in the context of materials science. Example works are reviewed to show how XAI helps materials science research. Challenges and opportunities are also discussed.
Journal Article
Reliable and explainable machine-learning methods for accelerated material discovery
Despite ML’s impressive performance in commercial applications, several unique challenges exist when applying ML in materials science applications. In such a context, the contributions of this work are twofold. First, we identify common pitfalls of existing ML techniques when learning from underrepresented/imbalanced material data. Specifically, we show that with imbalanced data, standard methods for assessing quality of ML models break down and lead to misleading conclusions. Furthermore, we find that the model’s own confidence score cannot be trusted and model introspection methods (using simpler models) do not help as they result in loss of predictive performance (reliability-explainability trade-off). Second, to overcome these challenges, we propose a general-purpose explainable and reliable machine-learning framework. Specifically, we propose a generic pipeline that employs an ensemble of simpler models to reliably predict material properties. We also propose a transfer learning technique and show that the performance loss due to models’ simplicity can be overcome by exploiting correlations among different material properties. A new evaluation metric and a trust score to better quantify the confidence in the predictions are also proposed. To improve the interpretability, we add a rationale generator component to our framework which provides both model-level and decision-level explanations. Finally, we demonstrate the versatility of our technique on two applications: (1) predicting properties of crystalline compounds and (2) identifying potentially stable solar cell materials. We also point to some outstanding issues yet to be resolved for a successful application of ML in material science.
Journal Article
Nano-Enhanced Drug Delivery and Therapeutic Ultrasound for Cancer Treatment and Beyond
While ultrasound is most widely known for its use in diagnostic imaging, the energy carried by ultrasound waves can be utilized to influence cell function and drug delivery. Consequently, our ability to use ultrasound energy at a given intensity unlocks the opportunity to use the ultrasound for therapeutic applications. Indeed, in the last decade ultrasound-based therapies have emerged with promising treatment modalities for several medical conditions. More recently, ultrasound in combination with nanomedicines, i.e., nanoparticles, has been shown to have substantial potential to enhance the efficacy of many treatments including cancer, Alzheimer disease or osteoarthritis. The concept of ultrasound combined with drug delivery is still in its infancy and more research is needed to unfold the mechanisms and interactions of ultrasound with different nanoparticles types and with various cell types. Here we present the state-of-art in ultrasound and ultrasound-assisted drug delivery with a particular focus on cancer treatments. Notably, this review discusses the application of high intensity focus ultrasound for non-invasive tumor ablation and immunomodulatory effects of ultrasound, as well as the efficacy of nanoparticle-enhanced ultrasound therapies for different medical conditions. Furthermore, this review presents safety considerations related to ultrasound technology and gives recommendations in the context of system design and operation.
Journal Article
Progress in treatment of neuromyelitis optica spectrum disorders (NMOSD): Novel insights into therapeutic possibilities in NMOSD
Neuromyelitis optica spectrum disorder (NMOSD) is a rare autoimmune inflammatory demyelinating disorder of the central nervous system (CNS), which is a severely disabling disorder leading to devastating sequelae or even death. Repeated acute attacks and the presence of aquaporin‐4 immunoglobulin G (AQP4‐IgG) antibody are the typical characteristics of NMOSD. Recently, the phase III trials of the newly developed biologicals therapies have shown their effectiveness and good tolerance to a certain extent when compared with the traditional therapy with the first‐ and second‐line drugs. However, there is still a lack of large sample, double‐blind, randomized, clinical studies to confirm their efficacy, safety, and tolerability. Especially, these drugs have no clear effect on NMOSD patients without AQP4‐IgG and refractory patients. Therefore, it is of strong demand to further conduct large sample, double‐blind, randomized, clinical trials, and novel therapeutic possibilities in NMOSD are discussed briefly here. Several drugs with different mechanisms and targets have been applied in clinic for therapy of NMOSD patients, included first‐line, second‐line, and new biologicals therapies. Other novel insights into therapeutic possibilities in NMOSD include targeting Th17 cells and blocking IL23/IL17/Th17 pathway and stem cell therapies, etc.
Journal Article
Low temperature difference thermoacoustic prime mover with asymmetric multi-stage loop configuration
Environmentally friendly and low-cost technologies to recover low-grade heat source into usable energy can contribute to ease the energy shortage. Thermoacoustic technology is expected as one promising approach in this ascendant field. In this work, the multi-stage looped thermoacoustic prime movers with asymmetric configuration, which can provide travelling-wave resonator and appropriate acoustic field for efficient regenerator, have been proposed and experimentally studied. The presented looped thermoacoustic prime movers can start to oscillate with quite low temperature difference along the regenerator. The lowest onset temperature difference obtained in the experiments is only 17 °C (the corresponding heating temperature is 29 °C), which can be achieved in both three-stage and four-stage looped thermoacoustic prime movers, with CO
2
of 1 MPa or 1.5 MPa as the working fluid. An electric generator driven by a three-stage looped thermoacoustic prime mover with low heating temperature was tested to achieve the acoustic to electric conversion.
Journal Article
Planning performance based contracts considering reliability and uncertain system usage
This paper investigates a novel quantitative approach for planning and contracting performance-based logistics in the presence of uncertain system usage. Our efforts focus on an integrated service delivery environment where the manufacturer develops capital-intensive systems and also provides after-sales support. We propose an analytical model to characterize system operational availability by comprehending five performance drivers: inherent failure rate, usage rate, spare parts inventory, repair time, and the fleet size. This analytical insight into the system performance allows the service supplier to minimize the total cost across system design, production, maintenance, and repair. Two contracting schemes are investigated under cost minimization and profit maximization schemes. For the first time in literature, reliability design and service parts logistics are seamlessly integrated into one decision support model for improving operational availability while lowering the lifecycle cost. Numerical examples are provided to demonstrate the applicability and the effectiveness of the proposed decision support tool.
Journal Article
Hydrologic feasibility of artificial forestation in the semi-arid Loess Plateau of China
Hydrologic viability, in terms of moisture availability, is fundamental to ecosystem sustainability in arid and semi-arid regions. In this study, we examine the spatial distribution and after-planting variations of soil moisture content (SMC) in black locust tree (Robinia pseudoacacia L.) plantings in the Loess Plateau of China at a regional scale. Thirty sites (5 to 45 yr old) were selected, spanning an area of 300 km by 190 km in the northern region of the Shaanxi Province. The SMC was measured to a depth of 100 cm at intervals of 10 cm. Geographical, topographic and vegetation information was recorded, and soil organic matter was evaluated. The results show that, at the regional scale, SMC spatial variability was most highly correlated with rainfall. The negative relationship between the SMC at a depth of 20–50 cm and the stand age was stronger than at other depths, although this relationship was not significant at a 5 % level. Watershed analysis shows that the after-planting SMC variation differed depending upon precipitation. The SMC of plantings in areas receiving sufficient precipitation (e.g., mean annual precipitation (MAP) of 617 mm) may increase with stand age due to improvements in soil water-holding capacity and water-retention abilities after planting. For areas experiencing water shortages (e.g., MAP = 509 mm), evapotranspiration may cause planting soils to dry within the first 20 yr of growth. It is expected that, as arid and semi-arid plantings age, evapotranspiration will decrease, and the soil profile may gradually recover. In extremely dry areas (e.g., MAP = 352 mm), the variation in after-planting SMC with stand age was found to be negligible. The MAP can be used as an index to divide the study area into different ecological regions. Afforestation may sequentially exert positive, negative and negligible effects on SMCs with a decrease in the MAP. Therefore, future restoration measures should correspond to the local climate conditions, and the MAP should be a major consideration for the Loess Plateau. Large-scale and long-term research on the effects of restoration projects on SMCs is needed to support more effective restoration policies. The interaction between afforestation and local environmental conditions, particularly water availability to plants, should be taken into account in afforestation campaigns in arid and semi-arid areas.
Journal Article