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Wind energy is regarded as one of nature's cleanest, safest, and most durable sources of energy among renewable energy sources. Energy consumption is rising quickly in Bangladesh due to population increases and economic expansion. The article focuses on locating prospective wind energy harvesting sites in Bangladesh and investigating potential applications for them. Hence, the article utilizes 21 years of wind velocity data collected from Asia-Pacific Data-Research Center (APDRC), which website is widely used for research purposes. This study reveals that the average wind velocity at potential sites varies from 3 to 5 m/s, which is deemed appropriate for energy harvesting. Two extreme value distribution models, the Generalized Extreme Value Distribution (GEVD) and Generalized Pareto Distribution (GPD), have been applied to estimate the extreme wind velocities. These distributions make it easier to simulate the behavior of extreme situations, such as 6–14 m/s, which are crucial for wind energy production. For the chosen sites, a wind rose diagram has also been used to study the directional dispersion of the wind. During the monsoon season, the majority of the wind will blow from the southeast direction with an average frequency of 23 %. Displaying the frequency and direction of the wind for each location in this graphic is critical for designing wind turbines capable of harvesting the maximum possible energy. In addition, the study has employed machine learning (ML) methods (facebook prophet and N-HiTS) and statistical models (ARIMA and exponential smoothing) to forecast wind speed behavior to predict future wind energy harvesting. Utilizing wind energy technology offers enormous potential for meeting the energy needs of emerging nations like Bangladesh. The study offers crucial insights into locating possible wind energy production sites and investigating their effective utilization.

The Visible Difference Predictors are a class of data driven, white box, efficiently implemented image or video difference metrics. They model important aspects of perception like spatial and temporal vision, foveation, and more, and are calibrated on datasets relevant for display and graphics applications. In this paper, we present a historic retrospective of VDPs, and a high‐level technical overview and comparison to other metrics in the literature. Finally, we put forward a practical guide for selecting the appropriate metric for a given engineering problem and discuss how metrics can be effectively combined with subjective testing for high‐confidence assessments.

Commercial-Off-The-Shelf (COTS) embedded devices rely on vendor-specific firmware to perform essential tasks. These firmware have been under active analysis by researchers to check security features and identify possible vendor backdoors. However, consistently unpacking newly created filesystem formats has been exceptionally challenging. To thwart attempts at unpacking, vendors frequently use encryption and obfuscation methods. On the other hand, when handling encrypted, obfuscated, big endian cramfs, or custom filesystem formats found in firmware under test, the available literature and tools are insufficient. This study introduces DUDE, an automated framework that provides novel functionalities, outperforming cutting-edge tools in the decryption, unpacking, deobfuscation, and endian conversion of firmware. For big endian compressed romfs filesystem formats, DUDE supports endian conversion. It also supports deobfuscating obfuscated signatures for successful unpacking. Moreover, decryption support for encrypted binaries from the D-Link and MOXA series has also been added, allowing for easier analysis and access to the contents of these firmware files. Additionally, the framework offers unpacking assistance by supporting the extraction of special filesystem formats commonly found in firmware samples from various vendors. A remarkable 78% (1424 out of 1814) firmware binaries from different vendors were successfully unpacked using the suggested framework. This performance surpasses the capabilities of commercially available tools combined on a single platform.

High-frequency, up to 10 MHz, switching of normally-on GaN trench CAVETs was demonstrated using an on-wafer double pulse test (DPT) system, along with high-temperature switching up to 300 °C reported for the first time. By innovatively inserting a low-temperature (LT) GaN interfacial layer to inhibit Mg out-diffusion from p-GaN, a record-high field effect mobility of 1821 cm2/( $\text{V}\cdot \text{s}$ ) in a regrown AlGaN/GaN channel was confirmed from device transconductance characteristics, which enabled low-loss high-frequency switching capability of the fabricated device. CAVETs were effectively scaled up to 3-finger structures with reduced specific on-resistance ( $\text{R}_{\text {on,sp}})$ to 0.98 $\text{m}\Omega \cdot $ cm2. The device was switched using DPT, showing low turn-off/on times of 2.6/4.8 ns at 1 MHz and 4.5/7.0 ns at 10 MHz switching frequency. The high channel mobility of CAVET not only facilitates robust 10-MHz switching at room temperature but also ensures effective switching functionality even under high-temperature conditions reaching up to 300 °C.

BackgroundComplex regional pain syndrome type 1 (CRPS-1) is a rare, disabling and sometimes chronic disorder usually arising after a trauma. This exploratory study examined whether patients with chronic CRPS-1 have a different genetic profile compared with those who do not have the condition.MethodsExome sequencing was performed to seek altered non-synonymous SNP allele frequencies in a discovery cohort of well-characterised patients with chronic CRPS-1 (n=34) compared with population databases. Identified SNP alleles were confirmed by Sanger sequencing and sought in a replication cohort (n=50). Gene expression of peripheral blood macrophages was assessed.ResultsIn the discovery cohort, the rare allele frequencies of four non-synonymous SNPs were statistically increased. The replication cohort confirmed this finding. In a chronic pain cohort, these alleles were not overexpressed. In total, 25 out of 84 (29.8%) patients with CRPS-1 expressed a rare allele. The SNPs were rs41289586 in ANO10, rs28360457 in P2RX7, rs1126930 in PRKAG1and rs80308281 in SLC12A9. Males were more likely than females to have a rare SNP allele, 8 out of 14 (57.1%) vs 17 out of 70 (24.3%) (Fisher’s p=0.023). ANO10, P2RX7, PRKAG1and SLC12A9were all expressed in macrophages from healthy human controls.ConclusionA single SNP in each of the genes ANO10, P2RX7, PRKAG1and SLC12A9was associated with developing chronic CRPS-1, with more males than females expressing these rare alleles. Our work suggests the possibility that a permissive genetic background is an important factor in the development of CRPS-1.

Continual global energy scarcity and its future challenges, as well as environmental disasters, are causing global devastation. Additionally, a substantial quantity of food is being wasted regularly. Therefore, the adoption of circular bioeconomy principles and the bioconversion of wasted food appears to be both highly advantageous and urgently required. However, previous studies have placed limited emphasis on the technological progress and circular bioeconomy aspects associated with the bioconversion of wasted food. The present review thus investigates how mass-generated food waste can be used to produce valuable bioproducts through bioconversion techniques such as oleaginous metabolism, anaerobic fermentation, and solventogenesis. These techniques have attracted considerable interest due to their eco-friendly and resource-recycling capacities, as well as their efficiency and sustainability. The paper also discusses approaches to integrate biorefineries within existing economies to establish a circular bioeconomy and analyses the challenges as well as the techno-economic, environmental and life cycle scenarios of these approaches. Analysis of the techno-economic and environmental effects reveals that food waste biorefineries can be lucrative if certain pathways are maintained. The environmental impact of bioconversion methods that produce valuable bioproducts is also found to be substantially lower than that of conventional methods. Integrating bioconversion processes further improves the efficiency of the process and sustainably recovers resources. Developing a circular bioeconomy requires the adoption of a biorefinery strategy with an integrated approach.

Hill tract plant Tetrastigma bracteolatum(Wall.) (Family-Vitaceae) is traditionally used for headache, indigestion and stomach disorder by the tribal people in Bangladesh. In this study, the ethanolic leaves extract of TB was investigated for screening its phytochemical constituents and assessing the antioxidant, analgesic, antidiarrheal and antihyperglycemic potential. In DPPH free radical scavenging assay, the extract showed good radical scavenging potential with SC50(concentration for 50% scavenging) value of 56 µg/ml. Analgesic activity test was performed by acetic acid-induced writhing method, where the extract inhibited writhing by 28.8% and 51.5% at the doses of 250 and 500 mg/kg bw, respectively. The extract inhibited defecation by 36.2% and 60.3% at the doses of 250 and 500 mg/kg bw in castor oil-induced diarrheal mice. In the evaluation of antihyperglycemic activity by oral glucose tolerance test (OGTT), the extract reduced blood glucose levels in a dose-dependent manner after 90 min, compared to the control group. The extract was also assessed for its in vitroα-glucosidase inhibition capacity but no demonstrable effect was observed. Fourteen chemical compounds were identified through GC–MS analysis of the extract with the highest amount of 1,2,3,4,4a,5,8,9,12,12a-decahydro-1,4-methanobenzocyclodecene (5.46%). Few compounds displayed better binding affinity with the active site of NADPH oxidase, nitric oxide synthase, M3 muscarinic acetylcholine receptor and sulfonylurea receptor than standard drugs in molecular docking studies. Therefore, the extract of TB may be used as a potential source of drug leads for various ailments.