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Nanoscale building blocks are individually exceptionally strong because they are close to ideal, defect-free materials. It is, however, difficult to retain the ideal properties in macroscale composites. Bottom-up assembly of a clay/polymer nanocomposite allowed for the preparation of a homogeneous, optically transparent material with planar orientation of the alumosilicate nanosheets. The stiffness and tensile strength of these multilayer composites are one order of magnitude greater than those of analogous nanocomposites at a processing temperature that is much lower than those of ceramic or polymer materials with similar characteristics. A high level of ordering of the nanoscale building blocks, combined with dense covalent and hydrogen bonding and stiffening of the polymer chains, leads to highly effective load transfer between nanosheets and the polymer.

Kumarasamy Thangaraj, David Reich and colleagues identify 81 South Asian groups descended from extreme founder events, including 14 with a census size of over 1 million people, thus providing an opportunity to test for and decrease the burden of recessive genetic diseases in these populations. The more than 1.5 billion people who live in South Asia are correctly viewed not as a single large population but as many small endogamous groups. We assembled genome-wide data from over 2,800 individuals from over 260 distinct South Asian groups. We identified 81 unique groups, 14 of which had estimated census sizes of more than 1 million, that descend from founder events more extreme than those in Ashkenazi Jews and Finns, both of which have high rates of recessive disease due to founder events. We identified multiple examples of recessive diseases in South Asia that are the result of such founder events. This study highlights an underappreciated opportunity for decreasing disease burden among South Asians through discovery of and testing for recessive disease-associated genes.

Accelerated learning programmes (ALPs) provide a fast-track second-chance opportunity to complete formal education, enabling disadvantaged children and youth to catch up with their peers. In 2005, after a preliminary pilot phase, the Government of Iraq, in partnership with the United Nations Children’s Fund (UNICEF) implemented an ALP initially in 10 of Iraq’s 18 governorates with the intention of providing an estimated 50,000 out-of-school, often traumatised and disenfranchised children aged 12–18 years with an opportunity to complete the six-year primary cycle in three years. This experience generated some insights which may still be of practical use today in other conflict-ridden countries and regions. In order to highlight how the lessons learned just over 10 years ago are relevant to similar situations elsewhere today, this article discusses the findings of an independent evaluation of the programme in 2008. The available evaluation data imply that this ALP addressed a significant need and was appreciated by the target group, with 75 % of learners stating that they liked the ALP very much. Around 90 % of ALP graduates continued either in secondary education, or studying in other programmes, joined an apprenticeship scheme or found employment. Both survey and interview data suggest that this ALP did more than create educational opportunities for young persons; it also helped young people obtain a confident perspective for their own future. Consequently, this made them less vulnerable to participation in subversive activities (such as, for example, being recruited into militias). This is a lesson not just relevant to Iraq at the time, but to a wide range of unstable contexts across the world. Le potentiel des programmes d’apprentissage accéléré (PAA ou ALP/Accelerated Learning Programmes) pour les pays et régions déchirés par des conflits: les enseignements tirés d’une expérience en Irak – Les programmes d’apprentissage accéléré offrent une seconde chance à des enfants et des jeunes défavorisés de terminer rapidement leur scolarité formelle, leur permettant ainsi de rattraper le retard qu’ils ont pris sur leurs pairs. En 2005, au terme d’une phase expérimentale, le gouvernement irakien, en partenariat avec le Fonds des Nations unies pour l’enfance (UNICEF), mettait en place un programme d’apprentissage accéléré, initialement dans 10 des 18 gouvernorats du pays, en vue de permettre à quelque 50 000 enfants âgés de 12 à 18 ans, souvent traumatisés, privés de leurs droits et en rupture de scolarité de suivre le cycle d’études primaires en trois ans au lieu de six. Cette expérience a fourni quelques éléments peut-être encore utiles aujourd’hui sur le terrain dans des pays et régions secoués par des conflits. Afin de montrer dans quelle mesure les leçons qui en ont été tirées il y a un peu plus de 10 ans restent pertinentes ailleurs actuellement dans des situations comparables, cet article se penche sur les résultats d’une évaluation indépendante du programme, réalisée en 2008. Les données d’évaluation disponibles indiquent que le programme d’apprentissage accéléré dont il est ici question répondait à un besoin important et que le groupe cible l’a apprécié, 75 % des apprenants ayant indiqué qu’ils l’aimaient beaucoup. Quelque 90 % des diplômés du programme ont poursuivi leur scolarité dans le secondaire, ou dans le cadre d’autres programmes, ont commencé un apprentissage ou trouvé du travail. Les données ressortant de l’enquête et des interviews indiquent que le programme n’a pas simplement offert à des jeunes des possibilités de s’instruire, il les a aussi aidés à avoir confiance dans leur propre avenir, ce qui les rend moins susceptibles de se livrer à des activités subversives (par exemple en se laissant recruter par des milices). Cette leçon ne vaut pas uniquement pour l’Irak de l’époque, elle peut également s’appliquer à un vaste ensemble de situations instables dans le monde entier.

Over the past decade, there has been a dramatic increase in the use of various technologies in the Architecture, Engineering, and Construction sector. Artificial intelligence has played a significant role throughout the different phases of the design and construction process. A growing body of literature recognizes the importance of artificial neural network applications in numerous areas of the construction industry and the built environment, presenting a need to explore the main research themes, attributes, benefits, and challenges. A three-step extensive research method was utilized by conducting a bibliometric search of English language articles and conducting quantitative and qualitative analyses. The bibliometric analysis aimed to identify the current research directions and gaps forming future research areas. The scientometric analysis of keywords revealed diverse areas within the construction industry linked to ANNs. The qualitative analysis of the selected literature revealed that energy management in buildings and construction cost predictions were the leading research topics in the study area. These findings recommend directions for further research in the field, for example, broadening the application ranges of ANNs in the current Construction 4.0 technologies, such as robotics, 3D printing, digital twins, and VR applications.

The Wireless sensor network has been highly focused research area in recent times due to its wide applications and adaptability to different environments. The energy-constrained sensor nodes are always under consideration to increase their lifetime. In this paper we have used the advantages of two approaches i.e. fuzzy c-means clustering and neural network to make an energy efficient network by prolonging the lifetime of network. The cluster formation is done using FCM to form equally sized clusters in network and the decision of choosing cluster head is done using neural network having input distance from basestation, heterogeneity and energy of the node. Our Approach has successfully increased the lifetime and data capacity of the network and outperformed different approaches applied to the network present in literature.

We present further study of a subset of carbapenems, arising from a previously reported machine learning approach, with regard to their mouse pharmacokinetic profiling and subsequent study in a mouse model of sub-acute Mycobacterium tuberculosis infection. Pharmacokinetic metrics for such small molecules were compared to those for meropenem and biapenem, resulting in the selection of two carbapenems to be assessed for their ability to reduce M . tuberculosis bacterial loads in the lungs of infected mice. The original syntheses of these two carbapenems were optimized to provide multigram quantities of each compound. One of the two experimental carbapenems, JSF-2204, exhibited efficacy equivalent to that of meropenem, while both were inferior to rifampin. The lessons learned in this study point toward the need to further enhance the pharmacokinetic profiles of experimental carbapenems to positively impact in vivo efficacy performance.

The worldwide construction sector is moving towards digitization due to the development of Industry 4.0. However, when it comes to digitizing building techniques, structural health monitoring, or SHM, it is still one factor that needs to be considered. Artificial Intelligence (AI) is a remarkable invention in the construction sector. Artificial Intelligence can improve structural health monitoring and provide better solutions. Evaluating previous studies and current developments in AI-based structural health monitoring is essential to achieving this. Through a thorough Patentometric study using the industry-leading databases Espacenet and The Lens, the research seeks to present an analysis of AI in structural health monitoring. For analysis, patent information covering 2019 to 2023 is taken into account. The chosen data is evaluated for patents by nation and year, and the IPC and CPC codes for patents in artificial intelligence for structural health monitoring are also covered. The United States is currently at the forefront of patenting artificial intelligence AI-based structural health monitoring systems. This report presents an in-depth Patentometric analysis that enumerates state-of-the-art innovations. In addition to highlighting the previous art, it offers a route for strategic patenting with higher odds of publication and patent award.

The natural environment is often contaminated with hydrophobic pollutants such as long-chain hydrocarbons, petrochemicals, oil spills, pesticides, and heavy metals. Hydrophobic pollutants with a toxic nature, slow degradation rates, and low solubility pose serious threats to the environment and human health. Decontamination based on conventional chemical surfactants has been found to be toxic, thereby limiting its application in pharmaceutical and cosmetic industries. In contrast, biosurfactants synthesized by various microbial species have been considered superior to chemical counterparts due to their non-toxic and economical nature. Some biosurfactants can withstand a wide range of fluctuations in temperature and pH. Recently, biosurfactants have emerged as innovative biomolecules not only for solubilization but also for the biodegradation of environmental pollutants such as heavy metals, pesticides, petroleum hydrocarbons, and oil spills. Biosurfactants have been well documented to function as emulsifiers, dispersion stabilizers, and wetting agents. The amphiphilic nature of biosurfactants has the potential to enhance the solubility of hydrophobic pollutants such as petroleum hydrocarbons and oil spills by reducing interfacial surface tension after distribution in two immiscible surfaces. However, the remediation of contaminants using biosurfactants is affected considerably by temperature, pH, media composition, stirring rate, and microorganisms selected for biosurfactant production. The present review has briefly discussed the current advancements in microbially synthesized biosurfactants, factors affecting production, and their application in the remediation of environmental contaminants of a hydrophobic nature. In addition, the latest aspect of the circular bioeconomy is discussed in terms of generating biosurfactants from waste and the global economic aspects of biosurfactant production.

An unusually high blood glucose level is a hallmark of diabetes mellitus, with an imbalance between insulin levels and insulin sensitivity leading to an insulin functional deficit. Since it serves as both a risk indicator and a gauge of long-term glycemic control, the HbA1c concentration is a crucial component of standard diabetes treatment. The use of the HbA1c concentration in the diagnosis of diabetes is expanding as the test's accuracy increases. Dyslipidemic profiles can appear before type 2 diabetes manifests itself and are independent risk factors for the disease. Additionally, dyslipidemia, especially in diabetics, might affect pancreatic beta-cell survival and activity. This study was undertaken with the aim to find out any correlation between HbA1c and lipid profile among diabetics, prediabetics, and non-diabetics. A total of 1,000 individuals with age 18-60 years were included in the study (non-diabetics = 186, prediabetics = 238, diabetics = 576). HbA1c was estimated by capillary electrophoresis and a lipid profile was done using a fully automatic chemistry analyzer. Diabetes was found to be significantly associated with dyslipidemia. In diabetics, a statistically significant increase in the level of triglyceride and very low-density lipoprotein (VLDL) was seen as compared to prediabetics. Diabetic women were found to be significantly more dyslipidemic as compared to diabetic males. The mean HbA1c among diabetics was found to be 8.3. In hyperglycemia-induced dyslipidemia, raised triglyceride and VLDL were the most common findings, and combined lipid abnormalities were more commonly seen as compared to a single abnormality in the lipid profile. Patients with poor glycemic control more commonly develop dyslipidemia, which may be a reason for an increased incidence of cardiovascular catastrophes in such patients.