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We developed a disposable paper battery aiming to reduce the environmental impact of single-use electronics for applications such as point of care diagnosis, smart packaging and environmental sensing. The battery uses Zinc as a biodegradable metal anode, graphite as a nontoxic cathode material and paper as a biodegradable substrate. To facilitate additive manufacturing, we developed electrodes and current collector inks that can be stencil printed on paper to create water-activated batteries of arbitrary shape and size. The battery remains inactive until water is provided and absorbed by the paper substrate, taking advantage of its natural wicking behavior. Once activated, a single cell provides an open circuit potential of 1.2 V and a peak power density of 150 µW/cm2 at 0.5 mA. As a proof of concept, we fabricated a two cell battery and used it to power an alarm clock and its liquid crystal display. [ABSTRACT FROM AUTHOR]

However, the use of artificial intelligence (AI) tools like ChatGPT has generated significant concern among researchers about their potential misuse and ethical implications (Curtis [1]). The artificial abstracts produced by ChatGPT and the original abstracts were passed through AI output detector, and also reviewed by blinded human reviewers. B Commentary b ChatGPT, is an artificial intelligence language model developed by OpenAI, is a well-known technology that requires no introduction in today's world. [Extracted from the article]

For the last two decades, the amount of genomic data produced by scientific and medical applications has been growing at a rapid pace. To enable software solutions that analyze, process, and transmit these data in an efficient and interoperable way, ISO and IEC released the first version of the compression standard MPEG-G in 2019. However, non-proprietary implementations of the standard are not openly available so far, limiting fair scientific assessment of the standard and, therefore, hindering its broad adoption. In this paper, we present Genie, to the best of our knowledge the first open-source encoder that compresses genomic data according to the MPEG-G standard. We demonstrate that Genie reaches state-of-the-art compression ratios while offering interoperability with any other standard-compliant decoder independent from its manufacturer. Finally, the ISO/IEC ecosystem ensures the long-term sustainability and decodability of the compressed data through the ISO/IEC-supported reference decoder. Genie, an open-source encoder compliant with ISO/IEC's MPEG-G standard, delivers state-of-the-art genomic data compression ratios and guarantees long-term data sustainability and decodability through interoperability. [ABSTRACT FROM AUTHOR]

The humidity has often been measured through a single point sensor. Where, the humidity could be varied at different locations as well as depending on environmental conditions. The present paper developed the dual point humidity measuring sensor by using a polymer optical fiber (POF) based on a single illuminating fiber. The sensor's basic structure is to twist two fibers and bend them at a certain radius. However, the dual point sensor is developed through the cascading of twisted micro bend (TMB-1 and TMB-2). The twisting of fibers couples the light from one fiber to another fiber through the side coupling method. An increase in the humidity level leads to a change in the reflective index, which helps to get variation in coupled light intensity. To measure the humidity, the dual point sensors are placed into the control humidity chamber at two random positions. The power reading variation is significantly linear when the humidity level increases from 30 to 80%. The sensor has a fast response of about 1 s and a recovery time of about 4 s. Furthermore, the chemical coating is applied to improve the sensor's sensitivity. Between 30 and 80% range of humidity, the both sensors of dual point TMB-1 and TMB-2 have appropriate sensitivity and detection limits, which is about 680.8 nW/% and 763.9 nW/% and 1.37% and 1.98%, respectively. To measure the humidity at variable positions, the present dual points humidity sensor is well-stable, easy, and straightforward, which uses a less expensive method. [ABSTRACT FROM AUTHOR]

Robotic automation is proving itself indispensable in the modern Chemistry laboratory, but adoption is slowed down by the technical challenges of implementing such systems. This paper reports on a novel adaptive gripper mechanism that can easily and reliably grasp cylindrical and prismatic objects of various sizes with limited clearance required. The proposed design exploits the inherent compliance of a cable that is driven to fully envelope the target object. The cable is run through a rigid finger, allowing the loop to be placed around objects with minimal clearance required and to provide support for the object once the grip is complete. Thanks to the compliant nature of the mechanism, the gripper requires minimal control effort to complete a gasping task. A prototype of the gripper has been designed and built for chemistry automation tasks, where it showed very high grasp reliability with ≤ 1 % grasp failures. [ABSTRACT FROM AUTHOR]

In many biomechanical analyses, the forces acting on a body during dynamic and static activities are often simplified as point loads. However, it is usually more accurate to characterize these forces as distributed loads, varying in magnitude and direction, over a given contact area. Evaluating these pressure distributions while they are applied to different parts of the body can provide effective insights for clinicians and researchers when studying health and disease conditions, for example when investigating the biomechanical factors that may lead to plantar ulceration in diabetic foot disease. At present, most processing and analysis for pressure data is performed using proprietary software, limiting reproducibility, transparency, and consistency across different studies. This paper describes an open-source software package, 'pressuRe', which is built in the freely available R statistical computing environment and is designed to process, analyze, and visualize pressure data collected on a range of different hardware systems in a standardized manner. We demonstrate the use of the package on pressure dataset from patients with diabetic foot disease, comparing pressure variables between those with longer and shorter durations of the disease. The results matched closely with those from commercially available software, and individuals with longer duration of diabetes were found to have higher forefoot pressures than those with shorter duration. By utilizing R's powerful and openly available tools for statistical analysis and user customization, this package may be a useful tool for researchers and clinicians studying plantar pressures and other pressure sensor array based biomechanical measurements. With regular updates intended, this package allows for continued improvement and we welcome feedback and future contributions to extend its scope. In this article, we detail the package's features and functionality. [ABSTRACT FROM AUTHOR]