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Although the origin of brass-type deformation texture in low SFE alloys has been extensively investigated, the annealing textures of such materials have received less attention, mostly limited to brass and different austenitic steels. On the other hand, the annealing textures of low SFE HEAs have been investigated more intensively recently; however, a comprehensive insight into annealing texture formation from HEAs down to binary systems is missing. To bridge the gap, the annealing texture of FCC single-phase Cu-11.6 at%Al alloy with SFE ∼10 mJm−2 comparable to HEAs was first investigated as a model binary system and compared with selected low SFE binary, medium entropy (MEAs), and HEAs to understand the similarities and characteristic differences. The cold-rolled alloy showed massive nanostructure and a typical brass-type texture featured by a strong B ({110}) component expected for a low SFE alloy. Annealing resulted in ultrafine recrystallized microstructure but extensive grain growth at higher temperatures, like other binary alloys but unlike HEAs. The annealing texture showed the retention of deformation components, weak α-fiber (ND//) components and a high random fraction. These features were very similar to HEAs/MEAs and attributed to the absence of oriented nucleation (ON) or oriented growth (OG) mechanisms. However, striking differences such as strong BR ({236}) and D ({113}) components in the brass alloy, selective growth of the G ({110}) and G/B ({110}) in binary Ni-60wt%Co alloy, and strong retention of the {110} component in the annealing texture of (FCC+B2) dual-phase AlCrFe2Ni2 HEA were remarkable. These outcomes indicated underlying microstructural effects on annealing texture formation in low SFE binary to HEAs/MEAs and should motivate further research.

The storage and transportation of hydrogen gas, a non-polluting alternative to carbon-based fuels, have always been challenging due to its extreme flammability. In this regard, formic acid (FA) is a promising liquid organic hydrogen carrier (LOHC), and over the past decades, significant progress has been made in dehydrogenating FA through transition metal catalysis. In this review, our goal is to provide a detailed insight into the existing processes to expose various mechanistic challenges associated with FA dehydrogenation (FAD). Specifically, methodologies catalyzed by pincer-ligated metal complexes were chosen. Pincer ligands are preferred as they provide structural rigidity to the complexes, making the isolation and analysis of reaction intermediates less challenging and consequently providing a better mechanistic understanding. In this perspective, the catalytic activity of the reported pincer complexes in FAD was overviewed, and more importantly, the catalytic cycles were examined in detail. Further attention was given to the structural modifications, role of additives, reaction medium, and their crucial effects on the outcome.

Cloud-based IoT is a platform that connects smart devices to the cloud for real-time data analysis. Any device on the IoT platform can connect to the cloud through messaging. The integrated publish/subscribe and push/pull methods for a cloud-based IoT framework that is scalable for connecting IoT devices and processing the real-time data are proposed. The proposed framework uses a publish/subscribe messaging broker and a push-pull method for transmitting the data from the device to the cloud. The IoT devices publish the data via the broker, to which the cloud service providers subscribe. This publishing and transferring of data from the broker to the cloud is implemented with the help of a push-pull mechanism. In this mechanism, the broker makes the computations required to select the cloud service provider. Hence, the overhead of the device is reduced. All computations go in parallel, which reduces the latency of the system. The system is flexible for any number of devices, brokers, and cloud service providers, which shows that the system is scalable. The results demonstrated the effectiveness of the model, which was developed using a cloud-based IoT framework with a focus on scalability and latency.

Membrane processes are extensively used to provide purified water from various saline water bodies. Membrane distillation (MD), one such membrane process, is mainly used for desalinating highly saline feed waters and to provide clean water. The design of robust membranes recently received considerable attention to address wetting, scaling, and fouling issues that hampered performance in long-term MD process. The current review discusses the omniphobic membranes employed in MD process for desalinating highly saline feedwaters containing diverse low surface tension substances. Also, it summarizes the basic concepts, fabrication and modification methods involved in designing omniphobic membranes. The developed omniphobic membranes have re-entrant structures and low surface energy which effectively provided anti-wetting and anti-fouling ability against saline feedwaters containing various low-surface tension substances. Further, the review focused on future research directions for developing omniphobic membranes for MD desalination applications.

Cyber-attacks are increasing day by day. The generation of data by the population of the world is immensely escalated. The advancements in technology, are intern leading to more chances of vulnerabilities to individual’s personal data. Across the world it became a very big challenge to bring down the threats to data security. These threats are not only targeting the user data and also destroying the whole network infrastructure in the local or global level, the attacks could be hardware or software. Central objective of this paper is to design an intrusion detection system using ensemble learning specifically Decision Trees with distinctive feature selection univariate ANOVA-F test. Decision Trees has been the most popular among ensemble learning methods and it also outperforms among the other classification algorithm in various aspects. With the essence of different feature selection techniques, the performance found to be increased more, and the detection outcome will be less prone to false classification. Analysis of Variance (ANOVA) with F-statistics computations could be a reasonable criterion to choose distinctives features in the given network traffic data. The mentioned technique is applied and tested on NSL KDD network dataset. Various performance measures like accuracy, precision, F-score and Cross Validation curve have drawn to justify the ability of the method.

A new outburst of GX 339−4 in 2021 was monitored by the Hard X-ray Modulation Telescope (Insight-HXMT). By using the data of Insight-HXMT from 2021 February to March, we make an X-ray timing analysis of this new outburst. Based on the results of the count rates, hardness–intensity diagram, and power density spectrum (PDS), we confirm that the source exhibits spectral transitions from the low-hard state (LHS) to the hard-intermediate state (HIMS). During the transition from the LHS to the HIMS, low-frequency quasi-periodic oscillations (QPOs) are detected in the PDS. We found that these QPOs are all type C QPOs with centroid frequencies evolving from 0.1 to 0.6 Hz in the LHS and in the 1–3 Hz frequency range in HIMS. The QPO features above 50 keV are reported for the first time in this black hole by Insight-HXMT. The QPO rms stays stable with time but decreases with energy at a higher energy above ∼10 keV. We also find that the phase lag of the type C QPO is close to zero in the early outburst stage but becomes positive as the outburst evolves, with a hard lag of ∼0.6–1.2 rad in 50–100 keV. The implications of the phase lag in high energy bands and the possible physical mechanisms to explain those observations are also discussed.

Summary: Secretagogin (SCGN) is a β-cell enriched, secretory/cytosolic Ca2+-binding protein with unknown secretory regulation and functions. Recent findings suggest that SCGN deficiency correlates with compromised insulin response and diabetes. However, the (patho)physiological SCGN-insulin nexus remains unexplored. We here report that SCGN is an insulin-interacting protein. The protein-protein interaction between SCGN and insulin regulates insulin stability and increases insulin potency in vitro and in vivo. Mutagenesis studies suggest an indispensable role for N-terminal domain of SCGN in modulating insulin stability and function. SCGN supplementation in diabetogenic-diet-fed mice preserves physiological insulin responsiveness while relieving obesity and cardiovascular risk. SCGN-insulin interaction mediated alleviation of hyperinsulinemia by increased insulin internalization, which translates to reduced body fat and hepatic lipid accumulation, emerges as a plausible mechanism for the preservation of insulin responsiveness. These findings establish SCGN as a functional insulin-binding protein (InsBP) with therapeutic potential against diabetes. : Molecular Interaction; Endocrinology; Diabetology; Specialized Functions of Cells Subject Areas: Molecular Interaction, Endocrinology, Diabetology, Specialized Functions of Cells

Nickel (Ni) doped SnO2 powder samples were prepared using solid-state reaction with dopant concentrations in the range of 3 at.% to 15 at.%. The influence of Ni doping on structural, optical, and magnetic properties of the powder samples has been investigated. All the Ni doped powder samples exhibited tetragonal structure of SnO2. A decrease in optical band gap was observed with increase of Ni doping levels. The vibrating sample magnetometer measurements revealed that the Ni doped SnO2 powder samples were ferromagnetic at room temperature.

Focal epithelial hyperplasia is a rare contagious disease caused by human papilloma virus. Usually HPV involves either cutaneous or mucosal surfaces, whereas concomitant mucocutaneous involvement is extremely rare. We report such a unique case of multifocal epithelial hyperplasia involving multiple sites of oral cavity along with skin lesions in a 65-year-old female. We also discuss the probable multifactorial etiology and variable clinical presentations of the lesions, including evidence of HPV 16 expression, as detected by polymerase chain reaction. The present report illustrates the need for careful examination and prompt diagnosis of the disease, as it might be associated with high risk genotypes such as HPV 16 and 18.

Co doped CdTe powder samples were prepared by solid-state reaction method. In the present work effect of Co doping on structural, optical, and magnetic properties has been studied. X-ray diffraction studies confirm zinc blend structure for all the samples. The lattice parameter showed linear increase with the increase in Co content. The elemental constituents were characterized by EDAX. Optical studies showed the increase in band gap with increase in Co level. The samples were diluted magnetic semiconductors and exhibited clear hysteresis loop showing room temperature ferromagnetism as confirmed by vibrating sample magnetometer.