Ambient Environmental Conditions Research Articles

Liquid solvent direct air capture’s cost and carbon dioxide removal vary with ambient environmental conditions

Emission trajectories produced by integrated assessment models increasingly suggest that gigatonnes of carbon removal will be required to stabilize atmospheric greenhouse gas concentrations at safe levels. This can be accomplished using the direct air capture of carbon dioxide, among other technologies. Process models of these systems assume that they would operate at standard ambient temperature and pressure, when capture rates vary with ambient conditions, including temperature, relative humidity, and other factors. Here, we build an open-source model of a liquid solvent direct air capture technology and analyze its capture performance as a function of hourly varying ambient environmental conditions across Canada. We find that, in the cool climate considered, capture performance is degraded due to both varying environmental conditions and the intermittent operation that could result. Our findings can be used to calibrate policy and investment decisions, and to support engineers in making operational design choices.

Subpicotesla Optomechanical Magnetometry.

High-sensitivity magnetometry has found important applications in fields ranging from basic science studies such as searching for dark matter and exotic particles to more practical tasks in geology, archaeology, navigation, and biomedicine. Currently, the performance of typical high-sensitivity magnetometers is limited by the required stringent operation environment, such as cryogenic conditions for superconducting quantum interference device magnetometers and near-zero-field environments for spin-exchange-relaxation-free atomic magnetometers. This Letter reports a high-sensitivity solid-state magnetometer based on a magnetostrictive gap-swing Fabry-Pérot cavity optomechanical system that is capable of benchmark performance at ambient environment conditions. Thanks to the strong resonance enhancement of the gap-swing mechanical mode, it achieves a sensitivity of 620 fT Hz^{-1/2} at room temperature and under the Earth's magnetic field, and is expected to approach the thermal-noise-limited sensitivity of 5.9 fT Hz^{-1/2} by controlling the optomechanical coupling. Our Letter opens the avenue toward the application of portable and low-maintenance high-sensitivity magnetometry in broad fields.

Sustainable catalytic pathways for biofuel precursors: quantitative conversion of glucose to gluconic acid using Pt-Zn biochar catalyst

Achieving quantitative conversion of biomass-derived feedstocks under ambient environmental conditions (20°C, atmospheric air, 0.1 MPa) is a critical milestone for sustainability in chemical processes. Herein, the quantitative conversion of glucose to gluconic acid was accomplished under ambient environmental conditions without any additives using a Pt-Zn intermetallic nanoparticle-supported biochar catalyst prepared from raw rice straw (Pt-Zn/strawC) via a straightforward one-pot solvothermal reaction with ethylene glycol solvent. Spectroscopic analyses verified the formation of the Pt-Zn intermetallic alloy and confirmed strong electronic metal-support interactions. The Pt-Zn/strawC catalyst (Pt:Zn molar ratio of 1:6) was highly selective for the conversion of glucose to gluconic acid, whereas yields as high as 99.9% (98.9% gluconic acid, 1.0% glucaric acid) were reached at 20 oC under base-free and additive-free conditions. Isotope measurements and density functional theory revealed synergistic interactions in the Pt-Zn alloy, wherein the alloy tended to absorb glucose and active O2 into superoxide radical (O2·). This work demonstrates a chemocatalytic method that is practical for environmental conditions and provides a new avenue for sustainable conversion of lignocellulosic biomass to chemical products.

Role of Halogen Elements in Conductivity and Electrochemical Stability of Sulfide Based Solid Electrolytes

All-solid-state batteries (ASSBs) are a promising candidate for future energy storage technology with better safety and higher energy density [1]. Safety of solid state batteries come from solid electrolytes used instead of organic liquid electrolytes in conventional Li-ion batteries. The various types of solid electrolytes have already been reported for SSBs which can be divided into oxides, sulfides, halides and polymers based on their properties, advantages and disadvantages [2]. Among them, sulfide based solid electrolytes have advantages over other due to high conductivity and ductile nature of sulfides [3]. The discovery of Li10GeP2S12 solid electrolyte called LGPS structured sulfide electrolyte have shown great potential to replace liquid electrolyte as ionic conductivity of LGPS was found 1.2×10-2 S cm-1 at room temperature comparable to the conductivity of organic liquid electrolyte [4]. However, Li10GeP2S12 electrolyte suffers with poor cyclability in solid state batteries due to reduction of Ge+4 ions to Ge0, and instable against lithium metal anode [5, 6].The solid electrolytes (SEs) with high conductivity and better stability against lithium metal are most important requirements for successful commercialization of solid state battery (SSB) technology. Therefore, in the search for new SEs with above mentioned qualities, halogen elements (Cl, Br, I) are explored in Li-P-S-O system to prepare Li10GeP2S12 (LGPS) structured SEs. In all prepared SEs, LPSOBr and LPSOI compositions show highest conductivities of 0.55 mS cm-1 and 0.67 mS cm-1 at 25 °C. The phase identification of newly synthesized solid electrolytes is done by X-ray diffractometer technique along with Rietveld refinement analysis. The conductivity of prepared solid electrolytes is determined by electrochemical impedance spectroscopy. These similar compounds also show superior stability against lithium metal in symmetric cells (Li/Ses/SE) as well as in full SSB cells (NCA/SEs/graphite) tested with LiNi0.8Co0.15Al0.05O2 cathode and graphite anode. These compounds also show 5 times higher stability in ambient environment conditions as compared to non-doped LPSO compound.

Contrasting aerosol effects on shallow and deep convections during the Mei-yu season in China

Convective clouds during the Mei-yu season contribute significantly to the total rainfall and related disasters over the middle and lower reaches of the Yangtze River in China. Studying the effects of aerosols on convective clouds is of great importance to weather and climate research. However, there are still many open questions to address. This study investigated the effects of aerosol on convections with different cloud geometrical thickness (CGT) bins during the 2018 Mei-yu season, which lasted for 17 days from 18 June to 5 July. Contrasting aerosol effects on shallow and deep convective clouds were revealed by means of anthropogenic aerosol experiments in the Weather Research and Forecasting model with Chemistry (WRF-Chem). Specifically, increased anthropogenic aerosols lead to a 9% reduction in total rainfall and a 7.17% decrease in convection occurrences during the Mei-yu season. After adopting a methodology that stratifies the convective clouds by fixing the CGT, we found that increasing aerosols suppress shallow convections with CGT <4 km and invigorate deep convections with CGT >4 km. Increased aerosols enhance the scattering of shortwave radiation, resulting in cooling of the surface air and increasing the stability of the regional lower atmosphere, potentially suppressing shallow convection. Meanwhile, in deep convection, with its stronger updraft and more latent heat, convective invigoration occurs under polluted conditions due to the aerosol-related microphysical and dynamical responses. Considering the high-humidity environment during the Mei-yu season, additional relative humidity tests show that the competing aerosol effects come from convective core invigoration and convective periphery processes which enhance evaporation and dissipation, demonstrating relative humidity is a critical factor in maintaining the net aerosol effects on convections. These results contribute to a better understanding of the effects of anthropogenic aerosols on convections during the Mei-yu season and the competing effects of aerosols depending on the ambient environmental conditions.

Peroxymonosulphate activation by ultra-small Ni@NiFe2O4/ZnO magnetic nanocomposites for solar photocatalytic degradation of β-lactam antibiotic - cefadroxil

In this study, ultra-small nickel nanoparticles on NiFe2O4 (Ni@NiFe2O4) and Ni@NiFe2O4/ZnO magnetic nanocomposites were synthesized and utilized for the solar light-driven photocatalytic degradation of cefadroxil. The drug cefadroxil is widely used to treat bacterial infections and cefadroxil is a non-biodegradable pharmaceutical compound detected in the groundwater sources because of its low removal efficiency. The Raman active phonon at 540 cm−1 confirms the presence of Ni nanoparticles at the surface of NiFe2O4/ZnO. DR-UV-Vis analysis exhibited surface plasmon resonance at 350 nm for ultra-small nickel nanoparticles. The observed optical bandgap values for Ni@NiFe2O4 and NiFe2O4/ZnO are 1.2 eV and 2.43 eV, respectively. Which indicates that these magnetic nanocomposites can be utilized for the mineralization of cefadroxil (β-lactam antibiotic) under ambient environmental conditions. The efficiency was determined by the direct solar light driven photocatalytic oxidation of cefadroxil in the presence and absence of peroxymonosulphate (PMS). The experimental findings exhibits that ∼95 % of cefadroxil (CDL) was eliminated by the ultra-small Ni@NiFe2O4/ZnO within 60 min (k = 7.5 × 10−4 s−1) of direct solar light irradiation. Further, the addition of PMS enhanced the photodegradation to achieve 100 % cefadroxil oxidation within 40 min (k = 25 × 10−4 s−1) of direct sunlight. The efficiency of the nanocatalyst was compared with controlled experiments and was found to be Fe2O3 < ZnO < TiO2 (P25) < Ni@NiFe2O4 < Ni@NiFe2O4/ZnO under absence and presence of PMS. Moreover, ultra-small Ni@NiFe2O4/ZnO nanophotocatalyst were stable up to 3 consecutive cycles.

Chemo-mechanical ageing of paper: effect of acidity, moisture and micro-structural features

A multi-scale modeling framework is proposed for the prediction of the chemo-mechanical degradation of paper, with the particular aim of uncovering the key factors affecting the degradation process. Paper is represented as a two-dimensional, periodic repetition of a fibrous network unit cell, where the fibers are characterized by a moisture-dependent chemo-hygro-mechanical constitutive behavior. The degradation of paper occurs primarily as a result of the hydrolysis of cellulose, which causes a reduction of the degree of polymerization and a consequent decrease of the effective mechanical properties, ultimately leading to fiber embrittlement and a loss of material integrity. The interplay between the acidity of the paper, the ambient environmental conditions, and its chemo-mechanical degradation behaviour is a complex process. In the model, these interactions are accounted for by determining the coupled temporal evolution of the degree of polymerization, the acidity of the paper, and the moisture content, from which the time-dependent tensile strength of the paper is calculated. The internal stresses developing in the fibrous network under a change in moisture content lead to brittle fiber fracture once they reach the fiber tensile strength. The successive breakage of individual fibers results in damage development in the fibrous network, altering its effective constitutive properties. The temporal evolution of the effective hygro-mechanical properties of the fibrous network is calculated by employing asymptotic homogenization. For obtaining accurate model input, the strength and stiffness properties of individual fibers and the degree of polymerization of paper samples are measured at different ageing times by carrying out dedicated experiments. Subsequently, a series of numerical simulations is performed to analyze the chemo-mechanical degradation process of paper, highlighting the influence of the time-evolving acidity and moisture content. The numerical study further considers the effects of micro-structural features (i.e., the anisotropy of the fibrous network orientation and the fiber longitudinal elastic modulus) on the macroscopic degradation response of paper. The results of this work may help conservators of cultural heritage institutions determining optimal environmental conditions to limit or delay the time-dependent degradation of valuable historical paper artefacts.

Efficacy of Three Antimicrobials Against two SARS-COV-2 Surrogates, Bovine Coronavirus and Human Coronavirus OC43, on Hard or Soft Nonporous Materials

The efficacy of three antimicrobials was evaluated against two severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) surrogates – bovine coronavirus (BCoV) and human coronavirus (HCoV) OC43 – on hard and soft nonporous materials. Three antimicrobials with three different active ingredients (chlorine, hydrogen peroxide, and quaternary ammonium compound + alcohol) were studied. Initially, a neutralization method was optimized for each antimicrobial. Then, we determined their efficacy against BCoV and HCoV OC43 in both suspension and on surfaces made with polyethylene terephthalate (PET) plastic and vinyl upholstery fabric. All tests were conducted under ambient environmental conditions with a soil load of 5% fetal bovine serum. After a 2-min exposure, all three antimicrobials achieved a >3.0 log10 reduction in viral titers in suspension. All three also reduced virus infectivity on both surface materials below the detection limit (0.6 log10 TCID50/carrier). Treatments in which the reduction in virus titer was <3.0 log10 were attributed to a decreased dynamic range on the carrier during drying prior to disinfection. The carrier data revealed that both surrogates were inactivated more rapidly (p <0.05) on vinyl or under conditions of high relative humidity. Three classes of antimicrobials were efficacious against both SARS-CoV-2 surrogate viruses, with BCoV demonstrating slightly less sensitivity compared to HCoV OC43. These findings also illustrate the importance of (1) optimizing the neutralization method and (2) considering relative humidity as a key factor for efficacy testing.

Radiocarbon-based ages and growth rates of cold-water bamboo corals in the South China Sea

Growth rates of cold-water bamboo corals are of crucial importance for establishing high-resolution chronology and reconstructing the development of these corals. However, due to the difficulty of sampling, their ages and growth rates as well as ecological indications are still fragmentary. In this study, radiocarbon analysis was performed on live-collected bamboo corals from the South China Sea (SCS) to investigate their growth and the controlling environmental factors. The obtained bomb 14C curve of organic nodes, which is formed by corals via consuming the surface-sourced sinking particulate organic material suggest that the organic nodes can document the upper ocean environmental conditions. The corals with ages up to 829 years have radial growth rates (RGRs) of 7.4–60.0 μm/year (average: 22.9 μm/year). These RGRs are among the lowest values of all the published RGRs of bamboo corals, representing the slow growth of corals in the SCS, and probably results from the low surface productivity. On the other hand, the relatively high coral RGRs at water depths of ∼1000 m and ∼2000 m probably results from the enhanced food availability caused by the strong bottom current at the water mass boundaries in the intermediate and deep waters. Although no significant correlation between the coral RGRs and the ambient environmental conditions were found, the relatively low RGRs of bamboo corals in the SCS clearly imply rather low ability to recover after damage. Further investigation of the environmental conditions controlling the growth of bamboo corals is needed.

Native freshwater lake microbial community response to an in situ experimental dilbit spill.

With the increase in crude oil transport throughout Canada, the potential for spills into freshwater ecosystems has increased and additional research is needed in these sensitive environments. Large enclosures erected in a lake were used as mesocosms for this controlled experimental dilbit (diluted bitumen) spill under ambient environmental conditions. The microbial response to dilbit, the efficacy of standard remediation protocols on different shoreline types commonly found in Canadian freshwater lakes, including a testing of a shoreline washing agent were all evaluated. We found that the native microbial community did not undergo any significant shifts in composition after exposure to dilbit or the ensuing remediation treatments. Regardless of the treatment, sample type (soil, sediment, or water), or type of associated shoreline, the community remained relatively consistent over a 3-month monitoring period. Following this, metagenomic analysis of polycyclic aromatic and alkane hydrocarbon degradation mechanisms also showed that while many key genes identified in PAH and alkane biodegradation were present, their abundance did not change significantly over the course of the experiment. These results showed that the native microbial community present in a pristine freshwater lake has the prerequisite mechanisms for hydrocarbon degradation in place, and combined with standard remediation practices in use in Canada, has the genetic potential and resilience to potentially undertake bioremediation.

Cellulose Diacetate Aerogels with Low Drying Shrinkage, High-Efficient Thermal Insulation, and Superior Mechanical Strength.

The inherent characteristics of cellulose-derived aerogels, such as their natural abundance and environmental friendliness, make them highly interesting. However, its significant shrinkage before and after the supercritical drying procedure and low mechanical strength limit its potential application. Here, we propose a strategy to prepare cellulose diacetate aerogels (CDAAs) with low drying shrinkage, exceptional thermal insulation, and superior mechanical strength. The low drying shrinkage (radial drying shrinkage of 1.4%) of CDAAs is attributed to their relative strong networking skeletons, which are greatly formed by tert-butanol solvent exchange in exerting the interaction of reducing the surface tension force. In this case, CDAAs are eventually endowed with the low bulk density of 0.069 g cm-3 as well. Additionally, as-prepared CDAAs possess an abundant three-dimensional networking structure whose pore size is concentrated in the diameter range of ~50 nm, and the result above is beneficial for improving the thermal insulation performance (thermal conductivity of 0.021 W m-1 K-1 at ambient environmental and pressure conditions). On the other hand, the optimal compressive stresses of CDAAs at 3% and 5% strain are 0.22 and 0.27 MPa respectively, indicating a mechanically well robustness. The above evidence demonstrates indeed the exceptional thermal insulation and superior compressive properties of CDAAs. This work may provide a new solution for developing a kind of high-performance cellulose-derived aerogel in the future.

Cellular patterning and cyto-architectural organization of the skin of electric catfish (Malapterurus electricus, Siluriformes) with a particular emphasis on its ampullary electroreceptor

The functional morphology of the skin of Malapteruridae is presumably evolved to cope with a diversified range of ambient physiological, environmental, and behavioral conditions. Herein, we firstly characterized the microstructures and intriguing patterning of the skin of twelve adult electric catfish (Malapterurus electricus, Malapteruridae) using histological, histochemical, immunofluorescent, and ELISA standard methodology. The skin comprises three sequentially–oriented layers: the epidermis, dermis, and hypodermis with a significantly increased thickness of the former. The epidermis contains four types of cells: the surface epithelial cells, mucous cells, granular cells, and club cells. We defined distinctive ampullary electroreceptors in the outer epidermis that possess flask-shaped sensory crypt containing electroreceptor cells together with vertical collagen rods. Dermis and hypodermis are composed of connective tissue; however, the former is much more coarse and dense with comparable reactivity for Masson–Goldner trichrome (MT). Placing our data in the context of the limited body of previous work, we showed subtle changes in the expression of mucin subunits together with cytoskeletal fractions of collagens, myosin, F-actin, keratins, and tubulins. Taken as a whole, our results convincingly showed that the skin of M. electricus shares some structural similarities to other Siluriformes, however, it has some functional modifications that are implicated in protection, defense, and foraging behavior.

Simultaneous increase in piezoelectric response and Curie point in BaTiO3 based Pb-free piezoceramic

Piezoelectric ceramics are used in wide-ranging applications as actuators, transducers, and sensors. For applications at ambient environmental conditions, it is desirable that the piezoelectric material exhibit large piezoelectric coefficient (d33) and possess Curie point well above room temperature. Among the lead-free piezoelectrics, the classical ferroelectric BaTiO3 exhibits Curie point and d33 ∼ 120 °C and 190 pC/N, respectively. Most attempts at improving the d33 of BaTiO3 via chemical modifications significantly reduces the Curie point (Tc). Here we show that it is possible to improve both the d33 and Tc of BaTiO3. We found this possibility while investigating a solid solution of BaTiO3 with BaAlO2.5. An optimum composition, 0.97 BaTiO3-0.03BaAlO2.5 of this solid solution exhibit d33 ∼356 pC/N, Curie point 125 °C, and good thermal stability of the piezo response.

Interface Engineering Enables Multilevel Resistive Switching in Ultra-Low-Power Chemobrionic Copper Silicate.

Memristor is assuming prominence due to its exceptionally low power consumption, adaptable, and parallel signal processing capabilities that address the limitations of the von Neumann architecture to meet the growing demand for advanced technologies such as artificial intelligence, Internet of Things (IoTs), and neuromorphic computation. In this work, we demonstrate resistive switching in copper silicate-based hollow tube-forming self-organized membrane structures belonging to the category of chemobrionics or chemical gardens to demonstrate cost-effective and highly efficient memristor devices. The device architecture is configured as ITO/PEDOT:PSS/active layer (copper silicate)/PMMA/Ag, an arrangement that serves to stabilize current-voltage hysteresis and exhibit a low SET voltage ∼0.2 V with a 0.8 nJ power consumption while manifesting robust data endurance and multilevel resistive switching. The inherent self-rectifying behavior, characterized by a high rectification ratio of 60, underscores the potential utility of these devices across a spectrum of electronic applications. To emulate the functionality of biological synapses, fundamental synaptic characteristics are assessed, including paired-pulse facilitation (PPF) and potentiation and depression (P&D). We validate the potential of copper silicate chemical garden-based memristor devices for applications that require real-time synaptic processing. Importantly, the fabrication of these devices was accomplished through a comprehensive solution-based, low-temperature process conducted under ambient environmental conditions, obviating the need for specialized glovebox facilities.

All‐Carbon‐Based Complementary Integrated Circuits

AbstractOwing to the growing global increase in electronic and electrical waste (e‐waste), significant challenges arise regarding the proper disposal of electronic devices. One potential solution that has gained attention is the development of disposable electronics, in which all components are designed to be for safe and environmentally friendly disposal. In this study, all‐carbon‐based complementary integrated circuits composed of printed single‐crystalline thin films of p‐ and n‐type organic semiconductors, graphite‐based carbon electrodes/wiring, and polymeric dielectrics/substrates are demonstrated. Elemental analysis reveals that the total amount of metallic element contaminants weighed &lt;50 parts per million (ppm). The demonstrated analog/digital integrated circuits with 64 p‐ and n‐type organic thin‐film transistors exhibit stable operation under ambient environmental conditions. These all‐carbon‐based complementary integrated circuits possess excellent element traceability, thus mitigating the potential environmental impacts throughout the device's life cycle. Consequently, this advancement represents a significant step toward addressing the global environmental challenges associated with e‐waste.

Performance enhancement of flat-plate and parabolic trough solar collector using nanofluid for water heating application

Flat plate solar collector (FPSC) and parabolic trough solar collector (PTSC) are widely used for residential solar water heating (SWH) applications. This work studied two different solar collector systems. Nanofluid and its influence on the residential solar water heating (SWH) systems were investigated. The two SWH systems were designed, installed, tested, and compared at varying mass flow rates (mf) of 0.47, 1.05, and 1.75 kg min−1 in ambient environmental conditions. The comparative study was conducted according to thermal efficiency (ηth), useful energy gain (QU), stored energy (QS), outlet hot water temperature (To), and difference temperature (ΔT) between the cold inlet and hot outlet water from the collectors. The analysis of outcomes showed that the PTSC was more efficient than FPSC. The FPSC and PTSC systems performance were investigated using two different types of nanofluids. Carbon nanotubes in water and ethylene glycol were utilized. A remarkable improvement in the average thermal efficiency 64.1 % and 80.6 % of FPSC and PTSC systems using ethylene glycol nanofluid were obtained respectively. The total reduction in CO2 emissions was 31.26 kg/day and 39.28 kg/day for the FPSCs and PTSCs, respectively in the presence of ethylene glycol nanofluid. A significant saving in CO2 release is owing to the renewable clean energy of solar collectors.

Clinical Manifestations.

Troubling behavioral symptoms such as mood changes or agitation are highly prevalent during the course of Alzheimer's disease and related dementias (ADRD). Effective management is dependent upon understanding the causes and precipitants of behavioral symptoms. The objective of our studies is to evaluate the role of the physical ambient environment in instigating symptoms. Participants are from two studies: 1) MOnitoring DEmentia-Related Agitation Using Technology Evaluation (MODERATE) which focuses on agitation in people with later-stage dementia, and 2) Monitoring Apathy, Depression and Anxiety Using Technology Evaluation (ADA) which focuses on apathy, depression and anxiety in older adults with or without cognitive decline. A commercially available, multifunction environmental sensor, Awair Omni, was deployed in the room where the participant sleeps, measuring levels of temperature, humidity, carbon dioxide (CO2), total volatile organic compounds (VOC), particulate matter 2.5 (PM2.5), noise and light every 5 minutes. Additionally, a multi-sensor array (bed pressure mats, motion sensors, and wearables) is deployed in homes to objectively measure participants' behaviors. Caregivers in MODERATE report agitation level/event experienced by their partners while participants in ADA self-report their level of symptoms via weekly online surveys. To date, 9 dyads (persons with cognitive decline and their caregivers) have enrolled in MODERATE and 9 participants are enrolled in ADA. 3135 days of data have been collected for MODERATE while 849 days of data have been collected for ADA. Mean participant characteristics: age = 75±8 years; 48% women; Blind MoCA = 13.2±7.96. For 4 weeks from 12/19/2022 to 1/15/2023, ambient environmental conditions identified (mean±SD): temperature = 21 ±2.0°C; humidity = 41±7.6%; VOC = 195±263 ppm; CO2 = 651±225 ppm; particulate matter 2.5 = 2.4±13 µg/m3; noise = 52±4.3 dBA; light = 9.5±40 Lux. The home environments are individually heterogeneous with high variability over time across multiple environmental conditions. Reports of behavioral symptoms show high week-to-week variability as well. Proposed methods of analyzing such data include generalized linear mixed model. This in situ environmental sensing approach provides more objective and timely data to enable identifying the relationship between physical environments and the behaviors of older adults at risk of or with ADRD. The knowledge generated will help prevent or mediate symptoms by prospectively modifying environmental conditions.

Analysis of Thermal Condition of Classrooms in Suburban Area During Corona Virus Desease using Adaptive Method

This article addresses the influence of a classroom’s thermal environment on the thermal comfort of the student when windows and vents are wide open during a pandemic, following Corona Virus Desease regulations. This research was conducted quantitatively by measuring the classrooms’ thermal environments from 08:00 to 13:00 at a suburban high school. The findings indicate that the classroom’s average air temperature (Ta) was 29.80°C, with an average relative humidity (RH) of 67.71%, an average airflow velocity (V) of 0.05m/s, an average Mean Radiant Temperature (MRT) of 29.67°C, and an average operating temperature (Top) of 29.72°C. An analysis was conducted using the web-based CBE Thermal Comfort Tool with the Adaptive Method, which can analyze the acceptance of thermal conditions based on operative temperature (Top). According to the analysis, it can be concluded that the thermal environment conditions in the morning in a “Comfortable” condition based on the ASHRAE-55 scale with the operative temperature (Top) are 27.37°C, the airflow speed (V) is 0.3m/s, and the prevailing mean outdoor temperature is 29.73°C. However, during the day, the ambient environmental conditions change, and the thermal comfort turns to “Too Warm” due to the operative temperature condition (Top), which is at the highest point of 31.46°C, with a prevailing mean outdoor temperature of 29.73°C, and an airflow speed (V) of 0.3m/s. It can be seen that the condition has not been able to meet the ASHRAE-55 standard, both in the 80% acceptability limit and the 90% acceptability limit range.

High dimensional Longitudinal Assessment of Ambient Home Environments and Their Association with Behaviors of People with Cognitive Decline

AbstractBackgroundTroubling behavioral symptoms such as mood changes or agitation are highly prevalent during the course of Alzheimer’s disease and related dementias (ADRD). Effective management is dependent upon understanding the causes and precipitants of behavioral symptoms. The objective of our studies is to evaluate the role of the physical ambient environment in instigating symptoms.MethodParticipants are from two studies: 1) MOnitoring DEmentia‐Related Agitation Using Technology Evaluation (MODERATE) which focuses on agitation in people with later‐stage dementia, and 2) Monitoring Apathy, Depression and Anxiety Using Technology Evaluation (ADA) which focuses on apathy, depression and anxiety in older adults with or without cognitive decline. A commercially available, multifunction environmental sensor, Awair Omni, was deployed in the room where the participant sleeps, measuring levels of temperature, humidity, carbon dioxide (CO2), total volatile organic compounds (VOC), particulate matter 2.5 (PM2.5), noise and light every 5 minutes. Additionally, a multi‐sensor array (bed pressure mats, motion sensors, and wearables) is deployed in homes to objectively measure participants’ behaviors. Caregivers in MODERATE report agitation level/event experienced by their partners while participants in ADA self‐report their level of symptoms via weekly online surveys.ResultTo date, 9 dyads (persons with cognitive decline and their caregivers) have enrolled in MODERATE and 9 participants are enrolled in ADA. 3135 days of data have been collected for MODERATE while 849 days of data have been collected for ADA. Mean participant characteristics: age = 75±8 years; 48% women; Blind MoCA = 13.2±7.96. For 4 weeks from 12/19/2022 to 1/15/2023, ambient environmental conditions identified (mean±SD): temperature = 21 ±2.0°C; humidity = 41±7.6%; VOC = 195±263 ppm; CO2 = 651±225 ppm; particulate matter 2.5 = 2.4±13 µg/m3; noise = 52±4.3 dBA; light = 9.5±40 Lux. The home environments are individually heterogeneous with high variability over time across multiple environmental conditions. Reports of behavioral symptoms show high week‐to‐week variability as well. Proposed methods of analyzing such data include generalized linear mixed model.ConclusionThis in situ environmental sensing approach provides more objective and timely data to enable identifying the relationship between physical environments and the behaviors of older adults at risk of or with ADRD. The knowledge generated will help prevent or mediate symptoms by prospectively modifying environmental conditions.

Tiny machine learning on the edge: A framework for transfer learning empowered unmanned aerial vehicle assisted smart farming

AbstractEmerging technologies are continually redefining the paradigms of smart farming and opening up avenues for more precise and informed farming practices. A tiny machine learning (TinyML)‐based framework is proposed for unmanned aerial vehicle (UAV)‐assisted smart farming applications. The practical deployment of such a framework on the UAV and bespoke internet of things (IoT) sensors which measure soil moisture and ambient environmental conditions is demonstrated. The key objective of this framework is to harness TinyML for implementing transfer learning (TL) using deep neural networks (DNNs) and long short‐term memory (LSTM) ML models. As a case study, this framework is employed to predict soil moisture content for smart agriculture applications, guiding optimal water utilisation for crops through time‐series forecasting models. To the best of authors’ knowledge, a framework which leverages UAV‐assisted TL for the edge internet of things using TinyML has not been investigated previously. The TL‐based framework employs a pre‐trained data model on different but similar applications and data domains. Not only do the authors demonstrate the practical deployment of the proposed framework but they also quantify its performance through real‐world deployment. This is accomplished by designing a custom sensor board for soil and environmental sensing which uses an ESP32 microcontroller unit. The inference metrics (i.e. inference time and accuracy) are measured for different ML model architectures on edge devices as well as other performance metrics (i.e. mean square error and coefficient of determination [R2]), while emphasising the need for balancing accuracy and processing complexity. In summary, the results show the practical feasibility of using drones to deliver TL for DNN and LSTM models to ultra‐low performance edge IoT devices for soil humidity prediction. But in general, this work also lays the foundation for further research into other applications of TinyML usage in many different aspects of smart farming.