Low-cost Solution Research Articles

Single-tube colorimetric loop-mediated isothermal amplification (LAMP) assay for high-sensitivity detection of SLCMV in cassava from southern India

Sri Lankan cassava mosaic virus (SLCMV) is a major cause for mosaic infections in cassava leaves, resulting in significant economic losses in southern India. SLCMV leads to growth retardation, leaf curl, and chlorosis in the host, with rapid transmission through whitefly insect vectors. Detecting SLCMV promptly is crucial, and the study introduces a novel and efficient colorimetric Loop-mediated isothermal amplification (LAMP) assay for successful detection in 60 min. Three primer sets were designed to target the conserved region of the SLCMV genome, specifically the coat protein gene, making the assay highly specific. The LAMP assay offers rapid and sensitive detection, completing within 60 min in a temperature-controlled water bath or thermal cycler. Compared to PCR techniques, it demonstrates 100 times superior sensitivity. The visual inspection of LAMP tube results using a nucleic acid dye and observing ladder-like pattern bands in a 2 % agarose gel confirms the presence of SLCMV. The assay is specific to SLCMV, showing no false positives or contaminations when tested against other virus. The standardized SLCMV LAMP assay proves technically efficient, providing a rapid, specific, simple, and low-cost solution, streamlining the detection and management of SLCMV.

DESIGN A CIRCUIT FOR HUMIDITY PREDICTION USING CMOS TECHNOLOGY AND IMPLEMENTING ANN

This research paper presents the knowledge about Humidity prediction model based on Arduino Uno, DHT11 Sensor and 16*2 LCD display. The model combines real-time data acquisition with predictive machine learning algorithm to estimate future humidity levels. The microcontroller of Arduino processes from the DHT sensor and shows the predicted and actual humidity data in the LCD display. This system gives a low-cost and user-friendly solution for humidity monitoring in various environments. Keyword: Arduino UNO, DHT-11, 16*2 LCD

Luminescence properties of Tb3+ -doped sodium phosphate glasses for green laser and X-ray imaging application

Tb3+ doped sodium-gadolinium-aluminum-phosphate glass samples (PGNA) with chemical compositions 30Na2CO3:8Gd2O3:5Al2O3:(57- x)P2O5: x Tb4O7 (where x=0, 0.25, 0.5, 1.0, 2.0, 3.0, 4.0, and 5 mol. %) were manufactured by using adopting the conventional melt quenching technique. The PXRD study of the prepared samples was used to confirm the amorphous structure. FE-SEM, EDS, and FTIR studies were carried out to analyze the elemental and structural characteristics of synthesized glasses. The X-ray induced luminescence spectra were obtained at room temperature and the emission peak at 311 nm corresponding to Gd3+ transition was observed decreasing with the increase of Tb4O7 concentrations, while emission peak intensities corresponding to Tb3+ electronic transitions increased with the concentrations of Tb4O7. The results from the photoluminescence (PL) studies in the UV–Vis–NIR region showed the glasses emitting intense green light with the highest peak at 544 nm under excitations at 220, 272, and 311 nm. The PL emission intensities were found reasonably high under characteristic excitations of both Gd3+ and Tb3+, peaking at 380, 414, 437, 489, 544, 584, and 623 nm, which corresponding to 5D3→7F6,5D3→7F5, 5D3→7F4, 5D4→7F6, 5D4→7F5, 5D4→7F5, 5D4→7F4, 5D4→7F3 transitions, respectively. The decay time of Tb3+ ions has been observed to decrease when the concentration of Tb4O7 increases. The energy transfer from Gd3+ to Tb3+ was found increased with increasing of Tb3+ concentrations. The CIE 1931 chromaticity coordinates of Tb doped PGNA glasses were found to be in the green range, indicating a strong potential for green laser application. The results from X-ray imaging showed that Tb-doped glass scintillators promise of efficient and low-cost solution for X-ray imaging applications.

Printable silicate and RuO2 composite with wide-range linear PTC for high-temperature sensors

3D printing has revolutionised the design and manufacturing of high-temperature thin/thick-film sensors (TFSs). However, existing printable high-temperature materials face cost-performance trade-offs. This study proposes a silicate and RuO2 composite for the 3D printing of TFSs. A silicate compound (SiO2–Al2O3–CaO, SAC) was used as a sintering aid to reduce the sintering temperature of RuO2, forming a silicate glass phase that enhanced film density and substrate adhesion. The SAC also minimised RuO2 particle volatilisation at high temperatures, thus enhancing the stability of the SAC/RuO2 composite. The SAC/RuO2 TFSs demonstrated exceptional performance, with a positive temperature coefficient (502 ppm/°C) from room temperature to 800 °C, high linearity, and stability (resistance drift rate of 0.1 %/h at 800 °C), extending the application temperature of RuO2 by nearly 200 °C from the previous application temperature of 600 °C. Therefore, the SAC/RuO2 composite offers a new low-cost and high-performance solution for using 3D printing technology in harsh environmental sensors such as turbine blades.

#1559 Using nephrology clinic data to emulate cohorts: a comparison between an electronic health records service and Chronic Renal Insufficiency Cohort

Abstract Background and Aims The amount of data contributed to evidence-synthesis is inequitably distributed among various countries in a way that most of the data is emerged from developed and/or upper middle and high income countries. One efficient and low-cost solution can be the implementation of scattered electronic health records (EHR) sources in those countries into emulated cohort studies. We aim to compare the characteristics of a custom-built nephrology clinic electronic health records (CBNC-EHR) service that is in practice for more than 13 years with Chronic Renal Insufficiency Cohort (CRIC) study which has approximately the same span and enrollment to find out about the feasibility, strengths, and challenges of the proposition. Method We compared measured variables of baseline characteristics and follow-up strategy of CRIC study with the data provided by CBNC-EHR to estimate if the care-centered database is capable of emulating a cohort study. Results Among variables of socioeconomic information at CRIC study, CBNC-EHR provides 33% at full, 33% are “partially available or easily accessible” (PAEA), and 33% are not available. 71% of variables of medical history are fully available for all patients, while only 14% are PAEA, and 14% are not available. For kidney function measures, CBNC-EHR provides 55% of variables completely, while the remaining 45% are PAEA. Obviously, no blood or urine sample were collected during ambulatory care, and no questionnaire on different aspects of health were used to gather supplementary data, contrary to CRIC study. Compared to follow-up strategy of CRIC study, which indicated Annual visits and laboratory tests and 6-month telephone follow-ups, CBNC-EHR yields data only upon personally-decided attention of patients for follow-up care, which varies widely from one patient to another. Nevertheless, the majority of patients have at least one office visit in a year, accompanied by relevant laboratory tests. CBNC-EHR provides a complete list of risk factors and comorbidities of each patient, which makes it suitable for subgrouping, as was designed in CRIC study regard the diabetes status of patients. CBNC-EHR currently has data of 6481 individuals with renal failure, compared to 3000 enrollment goal of CRIC study. However, much higher rates of dropout (estimated to be approximately 20%) and utilization of inclusion and exclusion criteria will contribute to the actual available cases to emulate a cohort study. Conclusion Implementing a care-centered database into emulation of a cohort study, is challenging and complicated. Lack of consistency, high dropout rates, imperfect baseline and complementary information, and need for extensive data cleaning are all difficulties. However, contribution to equitability of data share in evidence-synthesis, extremely lower cost of conduction, and less heterogeneity are strengths of this procedure which can have a remarkable effect on transforming medical data from less-developed countries (which understandably prioritize healthcare to research due to scarcity of resources) to effective research studies. In this paper, we compared a renowned nephrology cohort with a private nephrology clinic EHR in a developing country and showed virtual availability of data to emulate a cohort study based on the care-centered database.

Green synthesized silver nanoparticles in two stages: Box Behnken Design to machine learning

In order to solve the modeling issues due to data scarcity problems in the disciplines utilizing statistical approximations, a novel two-stage idea is proposed. As a use case, nanoparticle biosynthesis was selected, for which an environmentally friendly process is of vital importance. First, Box Behnken Design was used for experimental setup, quadratic model formulation and data generation. The second stage consists of Machine Learning, in which the data generated in the previous stage were fed into a Neural Network to determine the relationship between the parameters. Obtained results showed that the proposed combined strategy provided better nanoparticle size estimations than the statistical approach alone. In the absence of publicly available databases, data generation using experimental design and machine learning, as proposed here, could be a faster, lower-cost, and greener solution. Our proposed method can be applied to a wide range of biotechnology and bioengineering applications with significant advanced knowledge.

3D printed sub-terahertz photonic crystal for wireless passive biosensing

Monitoring pathogens has become a major challenge for society and research in recent years. Of great interest are refractive index sensors, which are based on the interaction between analytes and electromagnetic waves and allow label-free and fast detection. In addition, the electromagnetic waves can be exploited for wireless communication. However, current refractive index biosensors can only be read from a few centimeters. Here, we demonstrate an innovative concept of a passive wireless sensor based on a sub-terahertz photonic crystal resonator. The fabricated sensors have a reading range of up to 0.9 m and elevation and azimuth acceptance angles of around 90°. We demonstrate the stand-off detection of sub-µm thin-film proteins as test analytes. The proposed wireless sensor opens the door to a non-electronic, compact, and low-cost solution and can be extended to a wireless sensor network monitoring airborne pathogen, which may provide a pre-infection detection to prevent their spread efficiently.

Capturing urban green view with mobile crowd sensing

Urban green spaces are beneficial to ecosystems and the health of people. The Green View Index (GVI) is an essential metric for assessing urban green spaces from a human perspective. However, measuring GVI at an urban scale requires extensive collection and processing of sensing data, posing challenges in terms of high resource consumption, difficulty in implementation, and lack of user participation. Mobile crowd Sensing (MCS) is an emerging large-scale, low-cost solution for sensing data collection. To address the aforementioned issues, this study proposes an MCS system called GreenCam to measure the GVI with smartphone sensors. GreenCam guides users to capture photos of urban green spaces from human perspective. The system employs a Transformer-based model, which is trained on a customized dataset of 1200 carefully-labeled urban green images, to extract the greenery from the captured photos and calculate GVI. With widespread participation from urban users, the photos captured by users with GreenCam can cover various streets and areas of the city, enabling the measurement of GVI at an urban scale. Additionally, these photos reflect people's preferences towards specific urban landscapes, and analyzing the distribution and characteristics of popular landscapes contributes to the enhancement of urban ecosystems and landscapes.

A numerical approach to optimize the efficiency of a novel HTL-free Sr3Ti2S7 Ruddlesden-Popper perovskite solar cell

The exceptional environmental and structural stability of two-dimensional Ruddlesden-Popper perovskites has made them appealing candidates for high-performance perovskite solar cells. Besides, Ruddlesden-Popper perovskites can be synthesized using low-cost solution processing and have tunable bandgaps as compared to their conventional three-dimensional counterparts. Therefore, a Ruddlesden–Popper perovskite solar cell has been reported in this investigation and the SCAPS program has been used to theoretically study the device performance of the proposed lead-free, environmentally friendly perovskite solar cell. A novel Sr3Ti2S7 material has been utilized as the light absorber for the first time in such a theoretical study. Two different configurations, employing WS2 and C60 electron transport layers have been presented and device simulations have been performed to optimize the solar cell. The utilization of C60 as an electron transport material did not prove to be beneficial for the solar cell as it suffered from major recombination losses. It was also found that higher doping concentration of the electron transport materials could help these cells achieve improved fill factor. The diffusion length of the electrons and holes with respect to absorber defect density was also determined. Mott-Schottky analysis proved that the ITO/C60/Sr3Ti2S7/Au structure had a lower flatband potential compared to ITO/WS2/Sr3Ti2S7/Au. Additionally, from the impedance spectroscopy results, the recombination lifetime of the ITO/WS2/Sr3Ti2S7/Au configuration was found to be 46.7 μs compared to only 12.9 μs for the ITO/C60/Sr3Ti2S7/Au architecture. It was also established that if the thickness of the absorber and the bulk defect concentration were optimized the ITO/WS2/Sr3Ti2S7/Au and ITO/C60/Sr3Ti2S7/Au solar cells could achieve conversion efficiencies close to 11.0 % and 10.0 % respectively.

Energy Efficiency Optimisation of Joint Computational Task Offloading and Resource Allocation Using Particle Swarm Optimisation Approach in Vehicular Edge Networks.

With the progression of smart vehicles, i.e., connected autonomous vehicles (CAVs), and wireless technologies, there has been an increased need for substantial computational operations for tasks such as path planning, scene recognition, and vision-based object detection. Managing these intensive computational applications is concerned with significant energy consumption. Hence, for this article, a low-cost and sustainable solution using computational offloading and efficient resource allocation at edge devices within the Internet of Vehicles (IoV) framework has been utilised. To address the quality of service (QoS) among vehicles, a trade-off between energy consumption and computational time has been taken into consideration while deciding on the offloading process and resource allocation. The offloading process has been assigned at a minimum wireless resource block level to adapt to the beyond 5G (B5G) network. The novel approach of joint optimisation of computational resources and task offloading decisions uses the meta-heuristic particle swarm optimisation (PSO) algorithm and decision analysis (DA) to find the near-optimal solution. Subsequently, a comparison is made with other proposed algorithms, namely CTORA, CODO, and Heuristics, in terms of computational efficiency and latency. The performance analysis reveals that the numerical results outperform existing algorithms, demonstrating an 8% and a 5% increase in energy efficiency.

Optical Flow-Based Obstacle Detection for Mid-Air Collision Avoidance.

The sky may seem big enough for two flying vehicles to collide, but the facts show that mid-air collisions still occur occasionally and are a significant concern. Pilots learn manual tactics to avoid collisions, such as see-and-avoid, but these rules have limitations. Automated solutions have reduced collisions, but these technologies are not mandatory in all countries or airspaces, and they are expensive. These problems have prompted researchers to continue the search for low-cost solutions. One attractive solution is to use computer vision to detect obstacles in the air due to its reduced cost and weight. A well-trained deep learning solution is appealing because object detection is fast in most cases, but it relies entirely on the training data set. The algorithm chosen for this study is optical flow. The optical flow vectors can help us to separate the motion caused by camera motion from the motion caused by incoming objects without relying on training data. This paper describes the development of an optical flow-based airborne obstacle detection algorithm to avoid mid-air collisions. The approach uses the visual information from a monocular camera and detects the obstacles using morphological filters, optical flow, focus of expansion, and a data clustering algorithm. The proposal was evaluated using realistic vision data obtained with a self-developed simulator. The simulator provides different environments, trajectories, and altitudes of flying objects. The results showed that the optical flow-based algorithm detected all incoming obstacles along their trajectories in the experiments. The results showed an F-score greater than 75% and a good balance between precision and recall.

Stabilization of micaceous residual soil with industrial and agricultural byproducts: Perspectives from hydrophobicity, water stability, and durability enhancement

Micaceous residual soil is prevalent in the tropical regions of southern China. However, it is generally deemed unsuitable as a construction material in earthen structures due to its inferior engineering properties. Despite previous research into stabilizing micaceous soils, there remains an urgent demand for sustainable alternatives to traditional stabilizers to achieve circularity. Furthermore, uncertainties regarding the long-term performance of stabilized soils under hydraulic conditions complicated their use in flood-susceptible areas. To provide a sustainable and low-cost solution for creating stabilized soil for earthen structures in waterlogged regions, this study explores the impact of coir fiber and fly ash, agricultural and industrial byproducts, on the hydrophobicity, durability, and water stability of micaceous residual soil from Hainan, China. The study commenced with the preliminary mechanical tests to ascertain the optimal dosage of coir fiber and fly ash, which were determined to be 1% and 15%, respectively. Then, hydrophobicity, durability, and disintegration tests are conducted on fiber-reinforced fly-ash-treated soil under various stabilization conditions. The microstructural evolution of the soil fabric in response to the stabilization process was meticulously traced using scanning electron microscopy and energy-dispersive spectroscopy. Results indicated that the addition of fly ash could impart severe and persistent water repellency to the studied soil, with the contact angle improving from 16.7° to 102.9°, and the water drop penetration time significantly extending from 3.6 s to approximately 600 s. While incorporating coir fibers into the cemented soil presented negligible improvement on soil hydrophobicity, it markedly enhanced the soil’s durability, mitigated moisture-related deterioration and decelerated disintegration. Notably, the strength residual ratio of fiber-reinforced cemented sample maintained higher than 90% even after 20-day water immersion, and the disintegration rate decreased by 57% compared to unreinforced sample. Microstructural analysis revealed that bonding, friction, and interlocking among fibers, hydration products, and soil particles are the main contributors to the stable and robust matrix, ensuring improved mechanical behavior and longevity of micaceous residual soil. This study provides an innovative method for utilizing waste byproducts in stabilizing micaceous residual soil, as a viable option for earthworks in rain-soaked or flood-prone areas.

Spatial and temporal detection of root exudates with a paper-based microfluidic device

Root exudates control critical processes in the rhizosphere, retaining water, selecting for beneficial microorganisms or solubilising nutrients prior to uptake by the plant. Analysing root exudation patterns however is challenging because existing methods are often destructive and unable to resolve spatial and temporal variations in the production of root exudates. Here, we present a paper-based microfluidic device with integrated colorimetric sensors for the continuous extraction and analysis of root exudates along plant roots. The microfluidic device used standard filter paper wax printer to create channels for water to carry the exudates towards the sensors. TiO2 nanotubes/alginate hydrogel-based sensors were used to analyse the glucose content of the root exudates of living plants. The study shows that the paper microfluidic substrate successfully extracts the released glucose from the root, and transfers it to the hydrogel-based sensor to be colorimetrically detected from independent sections of the root at different times, up to 7 days. This method was tested on two different wheat varieties Triticum aestivum (rgt Tocayo and Filon varieties), where significant differences in exudation patterns were recorded. This research demonstrates the feasibility of low-cost technological solution for high precision screening and diagnostic of the biochemical composition of root exudates.

Time-bin entanglement at telecom wavelengths from a hybrid photonic integrated circuit

Mass-deployable implementations for quantum communication require compact, reliable, and low-cost hardware solutions for photon generation, control and analysis. We present a fiber-pigtailed hybrid photonic circuit comprising nonlinear waveguides for photon-pair generation and a polymer interposer reaching 68dB\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${68}\\,\\hbox {dB}$$\\end{document} of pump suppression and photon separation based on a polarizing beam splitter with >25dB\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$>{25}\\,\\hbox {dB}$$\\end{document} polarization extinction ratio. The optical stability of the hybrid assembly enhances the quality of the entanglement, and the efficient background suppression and photon routing further reduce accidental coincidences. We thus achieve a 96-8+3%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\left( 96_{-8}^{+3}\\right) \\%$$\\end{document} concurrence and a 96-5+2%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\left( 96_{-5}^{+2}\\right) \\%$$\\end{document} fidelity to a Bell state. The generated telecom-wavelength, time-bin entangled photon pairs are ideally suited for distributing Bell pairs over fiber networks with low dispersion.

Design of an RFID-Based Self-Jamming Identification and Sensing Platform

Commodity RFID tags backscatter stored electronic product code (EPC) to the reader, but do not have sensing capability. Existing works have made much effort on designing RFID-based sensing platform. But most of them either need intricate hardware design or rely on modification of the tag, which increases the cost or constrains the sensing capability. In this paper, we design a self-jamming identification and sensing platform (SJISP) consisting of SJISP nodes and a commodity RFID reader. A subtle design of the SJISP node is the adoption of a jammer radio module with the same frequency as the reader, controlled by the micro control unit (MCU) to decide whether to interfere with the query process of the RFID reader. The RFID tag is not readable if the jammer is turned on to generate interference signals. Otherwise, it is readable when the jammer is turned off. The sensing data is thus modulated by switching the jammer on and off for transmitting bit 0 and bit 1, respectively. The reader demodulates the data through the compatible EPC UHF Gen2 air interface protocol. To further save the energy of the SJISP node, we propose a prefix codebook based data delivery scheme, which leverages the difference of energy consumption (DEC) between transmitting bit 0 and bit 1. Our proposed scheme can save more than 50 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> of the energy than common communication without codebook. Experimental results based on our prototyped system show that the designed SJISP can achieve an average packet reception rate (PRR) of over 99 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> and is quite robust to environmental disturbance. Our designed platform provides a low-cost and compatible solution to extend the sensing capability of RFID system. A demo application with a temperature sensor and a light sensor embedded in two SJISP nodes respectively are developed to demonstrate how SJISP applies in real world scenario.

The Critical Ambient Temperature Threshold for Safe Fan Use in Young Adults During Extreme Heat Exposure

Introduction: The electric fan may be an effective, low-cost heat resilience solution during extreme heat. Fans have been shown to attenuate the rise in cardiovascular and thermal strain relative to still air in young adults, particularly during exposure to more humid conditions. When ambient temperature exceeds skin temperature, a fan improves sweat evaporation from the skin surface, which counterbalances the increased rate of convective heat gain. However, at higher air temperatures, the increased convective heat gain may exceed the rate of evaporative heat loss resulting in net heat gain and increasing physiological strain. The purpose of the present study was to identify the critical ambient temperature limit, where increased physiological strain will be observed, with a fan in comparison to still air. Method: To date, 6 participants (4 females; 24±9 y; 72.8±17.8 kg; 1.8±0.2 m) have completed two 180-minute temperature ramp heat-exposures (37°C to 47°C at ~0.05°C/min, 25%RH) on separate days. Wearing standardized t-shirts and shorts, the participants remained seated while either i) facing an electric fan (5.3±0.9 m/s) or ii) in still air (0.1±0.0 m/s). Rectal and skin temperature, heart rate, blood pressure, whole-body sweat loss, thermal comfort, and thermal sensation were measured every 10 minutes. Results: Rectal temperature was similar between fan and still air up to 43°C (P&gt;0.92), however was greater with a fan from 44°C onwards (p&lt;0.05). Skin temperature was higher with a fan compared to still air throughout the exposure (p&lt;0.001). Heart rate was similar between fan and still air until 44°C (P&gt;0.61), after which heart rate was higher with a fan (p&lt;0.05). Mean arterial pressure was not different between fan and still air at any air temperature (P=0.53). The rate pressure product was higher with a fan compared to still air when the ambient temperature exceeded 44°C (p&lt;0.05). Whole-body sweat losses were greater with a fan (1215±250 g) compared to still air (675±103 g, P=0.006). No differences between fan and still air were observed for thermal comfort (P=0.22) or thermal sensation (P=0.73) throughout the temperature ramp protocol. Conclusion: When ambient temperature exceeds 43°C, electric fan use results in greater physiological strain at rest in young healthy adults relative to still air. This research was supported by Dr. Ravanelli’s Natural Sciences and Engineering Research Council of Canada Discovery Grant (PIN#2022-05096). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Non-invasive paper-based sensors containing rare-earth-doped nanoparticles for the detection of D-glucose

Today, diabetes mellitus is one of the most common diseases that affects the population on a worldwide scale. Patients suffering from this disease are required to control their blood-glucose levels several times a day through invasive methods such as piercing their fingers. Our NaGdF4: 5% Er3+, 3% Nd3+ nanoparticles demonstrate a remarkable ability to detect D-glucose levels by analysing alterations in their red-to-green ratio, since this sensitivity arises from the interaction between the nanoparticles and the OH groups present in the D-glucose molecules, resulting in discernible changes in the emission of the green and red bands. These luminescent sensors were implemented and tested on paper substrates, offering a portable, low-cost and enzyme-free solution for D-glucose detection in aqueous solutions with a limit of detection of 22 mg/dL. With this, our study contributes to the development of non-invasive D-glucose sensors, holding promising implications for managing diabetes and improving overall patient well-being with possible future applications in D-glucose sensing through tear fluid.

Automatic Spontaneous Speech Analysis for the Detection of Cognitive Functional Decline in Older Adults: Multilanguage Cross-Sectional Study.

The rise in life expectancy is associated with an increase in long-term and gradual cognitive decline. Treatment effectiveness is enhanced at the early stage of the disease. Therefore, there is a need to find low-cost and ecological solutions for mass screening of community-dwelling older adults. This work aims to exploit automatic analysis of free speech to identify signs of cognitive function decline. A sample of 266 participants older than 65 years were recruited in Italy and Spain and were divided into 3 groups according to their Mini-Mental Status Examination (MMSE) scores. People were asked to tell a story and describe a picture, and voice recordings were used to extract high-level features on different time scales automatically. Based on these features, machine learning algorithms were trained to solve binary and multiclass classification problems by using both mono- and cross-lingual approaches. The algorithms were enriched using Shapley Additive Explanations for model explainability. In the Italian data set, healthy participants (MMSE score≥27) were automatically discriminated from participants with mildly impaired cognitive function (20≤MMSE score≤26) and from those with moderate to severe impairment of cognitive function (11≤MMSE score≤19) with accuracy of 80% and 86%, respectively. Slightly lower performance was achieved in the Spanish and multilanguage data sets. This work proposes a transparent and unobtrusive assessment method, which might be included in a mobile app for large-scale monitoring of cognitive functionality in older adults. Voice is confirmed to be an important biomarker of cognitive decline due to its noninvasive and easily accessible nature.

A Ka-band 27.6-dBm power amplifier with a compression-state large-signal matching approach in 130-nm CMOS SOI technology

This paper presents a Ka-band power amplifier with a compression-state large-signal matching approach in 130-nm CMOS SOI technology. The amplifier employs a quad-branch topology based on zero-degree power combiners/splitters, with each branch comprising two differential stages, each containing four stacked FETs. With a compression-state large-signal matching approach, this design achieves the saturated output power (Psat) of 27.6 dBm with 14.1 % peak power added efficiency (PAE), output 1-dB compression point (OP1dB) of 20.1 dBm at 35 GHz, according to electromagnetic simulation (EM) results. Additionally, it exhibits a peak gain of 39.2 dB at 33 GHz and a 3-dB bandwidth across 32–38 GHz. Offering a low-cost solution suitable for phased array radars and satellite communications.

A smartphone-based solution for fluorescence-powered protein aggregate detection

The level of protein aggregates can be used as an indicator of some diseases, including neurodegenerative disorders such as Alzheimer’s disease, and may be closely related to the efficacy of anti-cancer treatments. Moreover, strict control over protein aggregate levels is essential in pharmaceutical manufacturing to prevent potential side effects in the human body. In this study, we present a low-cost solution to evaluate protein aggregate levels in liquid samples using a smartphone-based fluorescence detection device. Initially, protein aggregate levels were assessed in bovine serum albumin samples. Then, this analysis was conducted using total protein extracts from breast cancer cells. The results obtained with the device were consistent with commercial spectrometer measurements, resulting in mean absolute errors of 0.098for bovine serum albumin samples and 0.152 for the proteins extracted from cancer cells, corresponding to differences of 9.8 % and 15.2 % between the commercial spectrometer and the developed device in the considered scales.