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Printing functional devices on flexible substrates requires printing of high conductivity metallic patterns. To prevent deformation and damage of the polymeric substrate, the processing (printing) and post-processing (annealing) temperature of the metal patterns must be lower than the glass transition temperature of the substrate. Here, a hybrid process including deposition of a sacrificial blanket thin film, followed by room environment nozzle-based electrodeposition, and subsequent etching of the blanket film is demonstrated to print pure and nanocrystalline metallic (Ni and Cu) patterns on flexible substrates (PI and PET). Microscopy and spectroscopy showed that the printed metal is nanocrystalline, solid with no porosity and with low impurities. Electrical resistivity close to the bulk (~2-time) was obtained without any thermal annealing. Mechanical characterization confirmed excellent cyclic strength of the deposited metal, with limited degradation under high cyclic flexure. Several devices including radio frequency identification (RFID) tag, heater, strain gauge, and temperature sensor are demonstrated.

Acoustic transducers are the crucial interface between acoustic signals and electrical signals, playing a pivotal role in converting and manipulating sound waves for a wide range of applications across industries and healthcare, such as non-destructive evaluation, range finding, proximity sensing, ultrasonic actuation and sensors, medical imaging probes, therapeutic ultrasound, microphones, and micro speakers. Such applications require transducers operating at frequencies spanning from tens of hertz to hundreds of megahertz. For most of the applications, generating strong acoustical signal is the most important design parameter. Achieving strong acoustic signals and heightened sensitivity demands a high output pressure per transducer unit area. To generate high output pressure per transducer unit area, higher vibration amplitude is required. When a transducer vibrates with a large vibrational amplitude, it can generate high output pressure per surface area even at a lower frequency. For example, when an acoustic membrane generates high output pressure per surface area, it would enable the membrane to produce enough audible sound at low frequency and works as a low frequency speakers or hearing aid instruments. Over the past century, acoustic transducer technology has evolved from piezoelectric crystals to contemporarycapacitive micromachined ultrasonic transducer (CMUT) or piezoelectric micromachined ultrasonic transducer (PMUT). However, current piezoelectric or electrostatic micromachined transducer face design and fabrication limitations for generating substantial vibration amplitudes.The main objective of this work is to demonstrate a novel approach that transforms the electrostatic transduction that is conventionally performed by a closely spaced electrode next to the vibrating membrane to an array of electrostatic cells embedded within the membrane. The air gap between the fixed electrode and moveable membrane of the conventional electrostatic acoustic transducers limits the vibration amplitude in the range of tens of nm to few microns. Expanding this gap further is restricted by concerns related to reliability, difficulties in fabrication, and the need for higher operating voltages. The array structures of this research can bypass all the above-mentioned issues and enable the realization of ultrasonic transducers and micro speakers with large out-of-plane displacement, resulting in high sound pressure output per unit area at moderate operating voltage. Extremely narrow air gaps can be made in the vertical electrostatic cells which allows the devices to be operated at low operating voltage while generating high electrostatic force and energy per unit area. Electrostatic cells embedded within the membrane also facilitate the membrane to vibrate with much larger vibration amplitude compared to the conventional devices.Using this novel approach, an acoustic membrane operating in the audible range has shown almost 5 times higher output pressure per surface area per volt compared to the state-of-the-art. Smaller membrane with a resonance frequency in the ultrasonic range would have much higher output pressure per surface area compared to the conventional CMUT and PMUT. This approach can also be used to design a much stronger MEMS micropump for drug delivery, and other MEMS devices where vibrating membrane is the crucial part.

There are lot of engineering fields where deployable structures are very important. Among them some applications require to develop a structure and deployment mech- anism that unfolds from a compact, folded form to a large at array. Initially, exible materials have been explored as a potential solution for deployable structures. While they have some positive aspects, they also have some negative aspects as well. Then, Origami, the Japanese art of paper folding, has been explored as a great source to these engineering designs. Among various origami patterns, the \"asher\" pattern (an origami base that folds into a 3D structure that can be radially deployed into a 2D surface) has been recognized for its potential application in the deployment of large structures from relatively small volumes. Accurate and practical dynamic models are essential in order to successfully design these deployable structures. In this analysis, a dynamic model of a asher is created using multibody dynamic (MBD) simulation software. The MBD model is created automatically by a series of scripts that transform a crease pattern into a fully defined engineering model. Such a structure can be internally deployed (by smart materials or stored strain energy) or externally (by actuators or inertial forces). This analysis focuses on the strain energy deployment method. The primary focus is to investigate the deployment time, the force and torque distributions throughout the structure, the bending angle of the panels, reaction torque at the center, kinetic energy of the panels, the trajectory of different vertices during the deployment, and the rigid foldability of the asher pattern. Parametric studies of the asher pattern were performed in two ways. Initially, the effects of various design parameters like the stiffness of panel joints, density of panel materials, the edge length of the center polygon, and the thickness of the panel on the dynamic performance were investigated. Parametric studies of various asher folding patterns were also performed by varying three basic geometric parameters: (1) the number of sides of the center polygon, (2) the number of rings comprising the array, and (3) the number of radially-distributed elements of each ring. In this analysis, the effect of these three parameters on the dynamic performance of the asher are studied using multibody dynamic (MBD) simulation software. As a basis for comparison, all the designs are held to the same surface area in the deployed at state. Each MBD model is created automatically by the aforementioned scripts. The primary focus is to investigate the variation of (a) the deployment time, (b) reaction torque at the center of the asher, (c) force and torque distribution in the entire structure, (d) bending angle of the panels, and (e) rigid foldability as a result of changes in the previously mentioned three basic geometric parameters. The overall effort provides insight to force and torque distribution within the structure, which can guide the placement of integrated smart material actuators or similarly compatible actuation system. Reaction torque measurement may help to design holding structure with proper strength. The results also help in asher design parameter decisions by giving insight into their effect on future applications such as star occulter designs, solar arrays, solar re ectors, sunshields, smallsat antennas, and solar sails. Furthermore, the method used is general and creates a groundwork for dynamic analysis of other origami structures.

Tobacco products are widely recognized as a major contributor to death. Cigarette smoke contains several toxic chemicals including heavy metals particulate causing high health risks. However, limited information has been available on the health risks associated with the heavy metals in cigarettes commonly sold in the Bangladeshi market. This study evaluated the concentrations and potential health risks posed by ten concerned heavy metals in ten widely consumed cigarette brands in Bangladesh using an atomic absorption spectrometer. The concentration (mg/kg) ranges of heavy metals Pb, Cd, Cr, As, Co, Ni, Mn, Fe, Cu, and Zn vary between 0.46–1.05, 0.55–1.03, 0.80–1.2, 0.22–0.40, 0.46–0.78, 2.59–3.03, 436.8–762.7, 115.8–184.4, 146.6–217.7, and 34.0–42.7, respectively. We assume that the heavy metals content among cigarette brands is varied due to the differences in the source of tobacco they use for cigarette preparation. The carcinogenic risks posed by heavy metals follow the order of Cr > Co > Cd > As > Ni > Pb, while the non-carcinogenic risks for Cu, Zn, Fe, and Mn were greater than unity (HQ > 1), except for Fe. The existence of toxic heavy metals in cigarette tobacco may thus introduce noticeable non-carcinogenic and carcinogenic health impacts accompanying inhalation exposure. This study provides the first comprehensive report so far on heavy metal concentration and associated health risks in branded cigarettes commonly sold in Bangladesh. Hence, this data and the information provided can serve as a baseline as well as a reference for future research and have potential implications for policy and legislation in Bangladesh. Graphical Abstract

Tobacco products are widely recognized as a major contributor to death. Cigarette smoke contains several toxic chemicals including heavy metals particulate causing high health risks. However, limited information has been available on the health risks associated with the heavy metals in cigarettes commonly sold in the Bangladeshi market. This study evaluated the concentrations and potential health risks posed by ten concerned heavy metals in ten widely consumed cigarette brands in Bangladesh using an atomic absorption spectrometer. The concentration (mg/kg) ranges of heavy metals Pb, Cd, Cr, As, Co, Ni, Mn, Fe, Cu, and Zn vary between 0.46–1.05, 0.55–1.03, 0.80–1.2, 0.22–0.40, 0.46–0.78, 2.59–3.03, 436.8–762.7, 115.8–184.4, 146.6–217.7, and 34.0–42.7, respectively. We assume that the heavy metals content among cigarette brands is varied due to the differences in the source of tobacco they use for cigarette preparation. The carcinogenic risks posed by heavy metals follow the order of Cr > Co > Cd > As > Ni > Pb, while the non-carcinogenic risks for Cu, Zn, Fe, and Mn were greater than unity (HQ > 1), except for Fe. The existence of toxic heavy metals in cigarette tobacco may thus introduce noticeable non-carcinogenic and carcinogenic health impacts accompanying inhalation exposure. This study provides the first comprehensive report so far on heavy metal concentration and associated health risks in branded cigarettes commonly sold in Bangladesh. Hence, this data and the information provided can serve as a baseline as well as a reference for future research and have potential implications for policy and legislation in Bangladesh.

The growing prevalence of malware in the digital landscape presents significant risks to the security and integrity of computer networks and devices. Malicious software, designed with harmful intent, can disrupt operations, compromise sensitive data, and undermine critical processes. To counter these ongoing threats, enhanced cyber threat detection systems are essential to identify and mitigate emerging risks proactively. One promising approach to improving cybersecurity involves applying Machine Learning (ML) techniques, which allow systems to detect patterns and make informed predictions. In this paper, we examined the effectiveness of ML in cyber threat detection, focusing on the classification of dangerous and benign entities within digital ecosystems. We tested four ML algorithms: Support Vector Machine (SVM), Decision Tree (DT), K-Nearest Neighbors (KNN), and Random Forest (RF). The dataset, sourced from Kaggle, was carefully pre-processed to ensure accurate malware and benign data classification. We used k-fold cross-validation for splitting the dataset and manually tuned hyper-parameters to refine model performance, reducing bias and variance. Our results revealed distinct performance metrics among the models, with RF emerging as the top performer with an impressive accuracy rate of 100%. To further enhance the interpretability of the RF model’s predictions, we employed Local Interpretable Model-Agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP) as the Explainable AI (XAI) techniques. These approaches ensure that static_prio, nivcsw, vm_truncate_count, shared_vm, and millisecond are the most significant features for validating and trusting ML-based cybersecurity solutions. The interaction-aware technique, Partial Dependence Plot (PDP), is utilized in LIME to demonstrate the impact of individual features on model predictions. We assessed LIME and SHAP, applying optimization techniques to minimize performance overhead. This research also incorporated opinions from cybersecurity experts and employed the Chi-Squared test to validate the explanations of XAI. These results reinforce the importance of ML in bolstering cybersecurity by enhancing cyber defense systems against malware and other threats. Ultimately, our research aims to strengthen computer network resilience and protect digital assets, ensuring the integrity and security of digital ecosystems amid evolving cyber threats.

Bangladesh is one of the sugarcane-producing countries in the South Asian region. The present sugar production accounts for approximately 4.5%, and jaggery production accounts for 20.5% of overall consumption. In the 2020–2021 cropping season, the country produced 7.37 million tons of sugarcane in a harvest area of 0.17 million hectares. The average sugarcane yield is around 70 t/ha, with a sugar yield of 5.49 t/ha. Due to the competition for cereals and other short-duration crops, the area under cane cultivation is decreasing substantially, resulting in the reduction in total sugarcane production. In recent decades, Bangladesh has made great strides in producing new sugarcane varieties through controlled crossbreeding, with the majority of current commercial varieties coming from regional breeding programs. The main goals of the sugarcane breeding program in Bangladesh are high productivity with high sugar content, early maturity, good ratooning ability, resilience, and resistance to the biotic and abiotic challenges of sugarcane. Improved sugarcane varieties have significantly increased sugar recovery from 12.43 to 13.89% and production from 83 t/ha in 1963 to 106 t/ha in 2022–2023. Micropropagation aimed at improving sugarcane varieties has enabled rapid propagation and accelerated acceptance of new varieties. This article provides a brief overview of the development of sugarcane in Bangladesh over time, as well as a discussion of current research difficulties and methodological methods, such as introgression-based, biotechnological, and molecular genetic breeding techniques.

This paper aims to illustrate the relationship between the constructs of social cognitive theory and social exchange theory with regard to the knowledge-sharing behaviour of students on Facebook. This research was conducted on 123 students using self-administrative survey questionnaires. The technique of structural equation modelling was employed to examine the hypothesized relationships between the variables. The findings of this study indicate that affiliation and innovativeness significantly the knowledge-sharing behaviour of students. Overall, perceived reciprocal benefit, perceived enjoyment, knowledge power, and affiliation and outcome expectations are found to be strong predictors of such behaviour. Previous research mostly examined the knowledge sharing attitude or intention in the industry setting. This study has been conducted in the educational setting and particularly focuses on the influence of the educational climate and expectation outcome on the knowledge sharing attitude of students.

The use of Internet and Internet-based services on PCs, Laptops, Net Pads, Mobile Phones, PDAs etc have not only changed the global economy but also the way people communicate and their life styles. It also has evolved people from different origins, cultures, beliefs across the national boundaries. As a result it has become an absolute necessity to address the cross-cultural issues of information systems (IS) reflecting the user behaviours and influencing the way the mobile broadband technology is being accepted as well as the way it is changing the life styles of different groups of people. This paper reports on an on-going research effort which studies the impacts of culture and socio-economic circumstances on users' behavior and mobile broadband technology diffusion trends.