Diverse Environmental Settings Research Articles

Dual role of pyrogenic carbon in mediating electron transfer from clay minerals to chromium in aqueous and solid media

Clay minerals (CMs) and pyrogenic carbons (PCs) often co-exist in the environment and participate in the redox cycling of pollutants. This study unveiled the dual role of PCs in CM-dominated chromium transformation in both aqueous and agar solidification media. The findings showed that CMs and PCs adsorbed minimal Cr(VI), while reduced CMs and PCs displayed a substantial difference by directly reducing Cr(VI) to solid/dissolved Cr(III) through reactive structural Fe(II) and functional groups, respectively. Moreover, dissolved PCs were found to mediate electron transfer from reduced CMs to Cr(VI) in aqueous and solid media. Interestingly, the effect of solid PCs on Cr(VI) reduction by reduced CMs was concentration-dependent. At lower concentrations, solid PCs dispersed reduced CMs, acting as electron mediators and facilitating both direct and indirect Cr(VI) reduction, resulting in solid Cr(III) rather than dissolved Cr(III). Conversely, at higher concentrations, solid PCs served as redox buffers, storing electrons transferred from reduced CMs to Cr(VI). In either case, the transformed chromium was primarily immobilized on the surface of CMs rather than PCs. These findings offer valuable insights into pollutant transformations associated with CMs and PCs, deepening our understanding of their geochemical processes. Environmental ImplicationThe natural transformation of chromium (Cr), a ubiquitous environmental pollutant, is intricately linked to redox-active species like clay minerals (CMs) and pyrogenic carbon (PC). In this pioneering study, we explored the impact of the interaction between CMs and PCs on the transformation of Cr in both aqueous and solid systems. Our discoveries offer valuable insights into the dynamics of Cr associated with varying concentrations of natural redox-active species across diverse environmental settings.

Farnesol repurposing for prevention and treatment of Acinetobacter baumannii biofilms

Acinetobacter baumannii has emerged as a multidrug-resistant (MDR) superbug by causing severe infections, with high mortality rates. The ability of A. baumannii to form biofilms significantly contributes to its persistence in diverse environmental and hospital settings. Here we report that farnesol, an FDA-approved commercial cosmetic and flavoring agent, demonstrates efficacy for both inhibition of biofilm formation, and disruption of established A. baumannii biofilms. Moreover, no resistance to farnesol was observed even after prolonged culture in the presence of sub-inhibitory farnesol doses. Farnesol combats A. baumannii biofilms by direct killing, while also facilitating biofilm detachment. Furthermore, farnesol was safe, and effective, for both prevention and treatment of A. baumannii biofilms in an ex vivo burned human skin model. Since current treatment options for A. baumannii biofilm infections were mainly counted on the combination therapy of last-resort antibiotics, and clearly non-sustainable due to robust MDR phenotype of A. baumannii, we propose that farnesol alone can be repurposed as a highly effective agent for both preventing and treating life-threating biofilm-associated infections of A. baumannii due to its proven safety, convenient topical delivery, and excellent efficiency, plus its superiority of evading resistance development.

Perspectives on AI-based recommendations for mask-wearing and COVID-19 vaccination for transplant recipients in the post-COVID-19 era

In the aftermath of the COVID-19 pandemic, the ongoing necessity for preventive measures such as mask-wearing and vaccination remains particularly critical for organ transplant recipients, a group highly susceptible to infections due to immunosuppressive therapy. Given that many individuals nowadays increasingly utilize Artificial Intelligence (AI), understanding AI perspectives is important. Thus, this study utilizes AI, specifically ChatGPT 4.0, to assess its perspectives in offering precise health recommendations for mask-wearing and COVID-19 vaccination tailored to this vulnerable population. Through a series of scenarios reflecting diverse environmental settings and health statuses in December 2023, we evaluated the AI’s responses to gauge its precision, adaptability, and potential biases in advising high-risk patient groups. Our findings reveal that ChatGPT 4.0 consistently recommends mask-wearing in crowded and indoor environments for transplant recipients, underscoring their elevated risk. In contrast, for settings with fewer transmission risks, such as outdoor areas where social distancing is possible, the AI suggests that mask-wearing might be less imperative. Regarding vaccination guidance, the AI strongly advocates for the COVID-19 vaccine across most scenarios for kidney transplant recipients. However, it recommends a personalized consultation with healthcare providers in cases where patients express concerns about vaccine-related side effects, demonstrating an ability to adapt recommendations based on individual health considerations. While this study provides valuable insights into the current AI perspective on these important topics, it is crucial to note that the findings do not directly reflect or influence health policy. Nevertheless, given the increasing utilization of AI in various domains, understanding AI’s viewpoints on such critical matters is essential for informed decision-making and future research.

Peptide-Decorated Microneedles for the Detection of Microplastics.

The escalating utilization of plastics in daily life has resulted in pervasive environmental pollution and consequent health hazards. The challenge of detecting and capturing microplastics, which are imperceptible to the naked eye, is exacerbated by their diminutive size, hydrophobic surface properties, and capacity to absorb organic compounds. This study focuses on the application of peptides, constituted of specific amino acid sequences, and microneedles for the rapid and selective identification of microplastics. Peptides, due to their smaller size and greater environmental stability compared with antibodies, emerge as a potent solution to overcome the limitations inherent in existing detection methodologies. To immobilize peptides onto microneedles, this study employed microneedles embedded with gold nanorods, augmenting them with sulfhydryl (SH) groups at the peptides' termini. The sensor developed through this methodology exhibited efficient peptide binding to the microneedle tips, thereby facilitating the capture of microplastics. Raman spectroscopy was employed for the detection of microplastics, with the results demonstrating successful attachment to the microneedles. This novel approach not only facilitates localized analysis but also presents a viable strategy for the detection of microplastics across diverse environmental settings.

Enhancing drought tolerance in cauliflower (Brassica oleracea var. botrytis) by targeting LFY transcription factor modulation via the ethylene precursor, ACCA: an innovative computational approach.

Brassica oleracea var. botrytis is an annual or biennial herbaceous vegetable plant in the Brassicaceae family notable for its edible blossom head. A lot of effort has gone into finding defense-associated proteins in order to better understand how cauliflower and pathogens interact. Endophytes are organisms that live within the host plant and reproduce. Endophytes are bacteria and fungi that reside in plant tissues and can either help or harm the plant. Several species have aided molecular biologists and plant biotechnologists in various ways. Water is essential for a healthy cauliflower bloom. When the weather is hot, this plant dries up, and nitrogen scarcity can be detrimental to cauliflower growth. The study sought to discern plant growth promoting (PGP) compounds that can amplify drought resilience and boost productivity in cauliflower. Investigations were centered on endophytes, microorganisms existing within plant tissues. The dual role of beneficial and detrimental Agrobacterium was scrutinized, particularly emphasizing the ethylene precursor compound, 1-amino-cyclopropane-1-carboxylic acid (ACCA). ACCA possessed salient PGP traits, particularly demonstrating a pronounced enhancement of drought resistance in cauliflower plants. Specifically, during the pivotal marketable curd maturity phase, which necessitates defense against various threats, ACCA showcased a binding energy of -8.74 kcal/mol. ACCA holds a significant promise in agricultural productivity, with its potential to boost drought resistance and cauliflower yield. This could be particularly impactful for regions grappling with high temperatures and possible nitrogen shortages. Future research should explore ACCA's performance under diverse environmental settings and its applicability in other crops.

Spatial, Geographical, Climatic, and Edaphic Influences on Moss Community Structure: A Case Study from Qinhuangdao, China

In the realms of ecology and biogeography, the interaction between biodiversity and environmental factors is a critical area of research. This intersection highlights how biological communities, especially among groups like bryophytes, are influenced and shaped by their surrounding environmental conditions. This study presents a pioneering investigation into the diversity and community structure of mosses in Qinhuangdao, Hubei Province, China, a region marked by its diverse topography and climate. Employing extensive field surveys across 30 plots, we gathered and analyzed the relationship between moss species distribution and environmental variables, including topographical, climatic, and soil factors. Utilizing a range of analytical techniques, such as cluster analysis, canonical correspondence analysis (CCA), and partial least squares path modeling (PLS-PM), we characterized the intricate relationships between moss biodiversity and environmental gradients. The research has documented 84 species distributed among 36 genera and 13 families. Solar radiation has a great impact on moss diversity. There were significant differences between Form. Entodon compressus and Form. Plagiobryum demissum. Climate has a great impact on the community structure of mosses. Geographical factors were also identified as key secondary influences, affecting moss community structures both directly and indirectly by creating suitable microenvironments and influencing climate and soil properties. Additionally, the study highlights the indirect impact of spatial factors on these environmental variables, which in turn shape the structure of biological communities. The findings indicate that the annual temperature range is a key factor influencing the distribution and formation of moss community structures. The findings provide new insights into the ecological adaptation of mosses in diverse environmental settings and lay a crucial foundation for biodiversity conservation and ecosystem management in the Qinhuangdao area.

From reflection to absorption: Improving light harvesting of dye sensitized solar cells with Cu nanowires as reflectors

Back reflectors have emerged as an effective approach to improve the light harvesting ability of photoanodes, which is considered as an obstacle to high performing photovoltaic (PV) devices. Considering the light scattering phenomenon of one dimensional (1D) material playing significant role in back-reflection, the present work demonstrated the use of 1D copper nanowires (Cu NWs) as light reflectors in dye sensitized solar cells (DSSCs) towards improving their PV performance. Cu NWs were synthesized using solvothermal method and characterized using X-ray diffraction (XRD), scanning electron microscope (SEM), and energy dispersive X-ray spectroscopy (EDX) mapping. The criteria behind using Cu NWs reflectors is to utilize the unabsorbed incident light, which is usually transmitted through the platinum (Pt) counter electrode (CE) in a typical DSSC, to enhance the light harvesting ability of photoanodes and hence their PV performance. We have observed a 10.2% enhancement in the power conversion efficiency (PCE) of Cu reflector based DSSCs (6.69%) relative to reference DSSCs (6.07%). The improved PV performance of Cu reflector based DSSCs is supported by the reduced charge transfer resistances at different interfacial layers obtained from the electrochemical impedance spectroscopy (EIS) measurements. By demonstrating the remarkable cost-effectiveness of Cu NWs, our findings pave the way for the widespread implementation of reflectors in next-generation photovoltaic devices, enabling enhanced performance across diverse environmental settings.

Response of zooplankton to warming in a low-salinity, eutrophic bay

Warming and eutrophication are universal threats to bay ecosystems. However, the response of zooplankton varies due to diverse environmental settings and species composition. As a long and narrow semi-enclosed bay with low salinity (18–27) in the East China Sea, Xiangshan Bay (XSB) is jointly affected by global warming and the thermal drainage, which makes it an appropriate region for ascertaining the response of zooplankton to warming under low-salinity background. We examined the long-term changes in the abundance, biomass and dominant species of large mesozooplankton (LMZ; >505 μm) over four decades in XSB, and found downward trends in the annual abundance and biomass, and the biomass peak shifting from summer to spring since 2010. In addition, the relative abundance of cold-temperate species decreased, while that of warm-temperate/warm-water species and small-sized zooplankton increased. The decreased LMZ abundance and biomass in XSB were supposed to be related to low gelatinization compared with the other semi-enclosed bays in China, Jiaozhou Bay (JZB) in the Yellow Sea and Daya Bay (DYB) in the South China Sea, where the LMZ biomass and abundance increased or fluctuated mainly linked to the increase in gelatinous zooplankton. Salinity, temperature, and nutrient concentration are important factors affecting gelatinization. By comparing the background salinity and magnitudes of temperature and nutrient increases among the three bays, we speculated that the lower salinity (XSB: 18–27, JZB: 30–32, DYB: 30–34) influenced by freshwater input of the Changjiang River might be a potential factor causing the low gelatinization in XSB, as the similar upward trends in both nutrient concentration and temperature were observed in the three bays. This study suggests that miniaturization with low gelatinization and a decrease in cold-temperate species were the main responses of zooplankton to warming in the low-salinity bay in the East China Sea, which may lead to a specific pelagic ecosystem evolution.

Cyanobacteria as a potential bioasset for restoring degraded land

AbstractDegradation and pollution of land resources is a severe issue worldwide. Rapid urbanization and increased food demand have necessitated the restoration of degraded and highly contaminated land resources in a sustainable manner. The role of soil microorganism in maintaining nutrient balance, texture, fertility, and soil health is widely acknowledged. Cyanobacteria, one of the major components of soil microbiota, have been explored for their role as biofertilizers in improving plant growth and increasing soil fertility; however, less attention has been paid to their potential in restoring degraded lands. Cyanobacteria aids in nutrient cycling, production of plant growth‐promoting substances, desalination, and degradation of diverse organic as well as inorganic contaminants. They use diverse mechanisms for bioremediation (such as biosorption, bioaccumulation, and biotransformation) of contaminants in addition to the specific mechanism employed. They occur in symbiotic relationships with various hosts in natural as well as anthropogenically disturbed environments. Therefore, their use in restoration of highly degraded lands is justified and needs to be recognized worldwide. Identifying and exploring cyanobacterial species thriving in stress conditions and multiomics approaches would help in reconnoitering the complex plant–soil‐cyanobacteria interactions and enable scientists to design robust and well‐integrated biotechnological tools for soil remediation. Nevertheless, several technical challenges need to be addressed for rendering cyanobacteria as a realistic and viable bioasset. In this article, we summarize the role of cyanobacteria in addressing the reclamation of various types of degraded and polluted soils. And, it also examines the remaining knowledge gaps that limit its applicability in diverse environmental settings in a sustainable manner.

Comprehensive analysis of solar cell behavior: effects of light intensity, temperature, and operational modes

This study investigates the current-voltage characteristics of a solar cell under varying light intensities, temperatures, and operational conditions to comprehensively assess its performance. The experimental approach involves measuring short-circuit current and open-circuit voltage at different light intensities and constructing current-voltage curves to analyze the solar cell's response to changing illumination levels. The dependence of open-circuit voltage and short-circuit current on temperature is also estimated to understand thermal influences on the solar cell's electrical properties. Additionally, the solar cell's behavior is examined under different operational modes, including cooling with a blower, operation without cooling, and light filtration through a glass plate. The corresponding current-voltage characteristics are plotted to evaluate the impact of thermal management and light modulation on the solar cell's efficiency and stability. Furthermore, the characteristic curve of the solar cell is determined under natural sunlight illumination to simulate real-world conditions. The findings provide valuable insights into optimizing solar cell performance for practical applications and sustainable energy systems. This research contributes to advancing our understanding of solar cell behavior under diverse environmental and operational settings, with implications for enhancing solar energy utilization and promoting renewable energy technologies. Future studies will focus on refining solar cell design and operation based on these insights to maximize efficiency and reliability in solar power generation.

Trace Fossils and Sedimentary Depositional Environment: A Case Study from Early Permian Barakar Formation, Raniganj Basin, India

Behavioral responses of organisms with respect to changing environment have a wide area of research possibility. For a palaeontologist it is a challenge to interpret the organism-sediment interaction from the study of the trace fossils preserved in the ancient rock record. The ethological significance which is derived out of different intentional or accidental activities of the organisms may be preserved within the rock and is largely controlled by the substrate stability, grain size of the sediments, energy and rate of sedimentation of the driving process, types of nutrients and its supply, salinity, temperature and oxic/sub-oxic/an-oxic conditions etc. So, the viability of this study in sensu stricto depends on the preservation potential of the organism as a whole or in parts or its activities (indirect evidences) on or within the substrate upon which they have survived thousands and millions of years ago. The indirect evidences of the organism’s activities may be its locomotory/respiration/feeding/resting/dwelling/predating traces etc. which have different nomenclature based on their morphological classification. The study area encompassing the major river section of the Barakar, Khudia, Ajoy holds partly enriched and partly impoverished trace fossils within the sedimentary rocks hosting huge reserves of coal. There are several concepts regarding the depositional setting of the studied basin like formerly interpreted fluvio-lacustrine depositional model to recently reinterpreted fluvio-tide-wave dominated depositional model. Several invertebrate traces have been recorded from the study area namely Planolites, Thalassinoides, Ophiomorpha, Palaeophycus, Cylindrichnus, Diplocraterion which indicates diverse environmental settings ranging from supratidal/intertidal/subtidal to continental shelves whereas other solo/uniform traces observed like Chondrites, Skolithos, Rhizocorallium etc. are indicator of shallow subtidal to marine quite water setting. Here the additional challenges include the lack of ample exposures, weathered exposed rock sections, inaccessible mine cut sections, absence of body fossils and controversial identification of trace fossils in differential erosive surfaces. This chapter in short has tried to mitigate these problems by the integrated sedimentary and ichnological facies association studies in delineating the depositional environment of the studied basin.

Long-term trends in settlement persistence in Southwest Asia: Implications for sustainable urbanism, past, present and future

Southwest Asia saw the emergence of large settlements in the Early Holocene, and the world’s first urban communities around 6000 years ago, with cities a feature of the region ever since. These developed in diverse environmental settings, including the dry-farming plains of Northern Mesopotamia, the irrigated alluvium of Southern Mesopotamia and the more variegated landscapes of the Levant. In this paper we use a dataset of several hundred sites dating from the earliest large sites around 12,000 years ago to the Classical period (2000 BP), to examine trends in settlement sustainability through time. We use persistence of occupation as a proxy for sustainability and compare settlement trajectories in different land use zones. Comparing cities and settlements at these spatial and temporal scales allows us to address a key question in the New Urban Agendas framework: how urban development can best be supported by sustainable use of land. We find that the highest levels of persistence were not uniformly associated with high agricultural productivity regions, and some of the longest-lived settlements are located in marginal environments, likely at critical points in transport networks. We also find that persistence is enhanced in landscapes which do not require large-scale capital investment or specific forms of economic and social organisation to maintain high levels of agricultural productivity, and that sustainability is inversely correlated with social complexity. Our results show that the millennial timescales available through archaeology can enable us to identify the political, social and ecological conditions required for large centres to persist through time.

The inevitability of arbuscular mycorrhiza for sustainability in organic agriculture—A critical review

The arbuscular mycorrhizal fungi (AMF) are significant fertility-promoting microbes in soils. They enable soil fertility, soil-health and boost crop productivity. There are generalist and specialist groups among AMF in natural soils. Optimized use of specific AMF concerning crops and soils can improve agricultural sustainability. Thus, AMF is becoming an inevitable biological tool for improving crop productivity and soil health. Especially in the context of chemicalized agriculture undermining the sustainability of food security, safety, and human and ecosystem health, alternative agricultural means have become inevitable. Therefore, AMF has become essential in nature-friendly, organic agriculture. Of such farm fields, natural biological activity is enhanced to sustain soil fertility. Crops show increased innate immunity against pests and diseases in many such systems. Moreover, ecosystems remain healthy, and the soil is teeming with life in such farms. The primary goal of the review was a thorough critical analysis of the literature on AMF in organic agriculture to assess its efficiency as an ecotechnological tool in sustainable agricultural productivity. The novelty is that this is the first comprehensive review of literature on AMF concerning all aspects of organic agriculture. A vital systematic approach to the exhaustive literature collected using regular databases on the theme is followed for synthesizing the review. The review revealed the essentiality of utilizing specific mycorrhizal species, individually or in consortia, in diverse environmental settings to ensure sustainable organic crop production. However, for the exact usage of specific AMF in sustainable organic agriculture, extensive exploration of them in traditional pockets of specific crop cultivations of both chemical and organic fields and wild environments is required. Moreover, intensive experimentations are also necessary to assess them individually, in combinations, and associated with diverse beneficial soil bacteria.

Discovery of Highly Trimethoprim-Resistant DfrB Dihydrofolate Reductases in Diverse Environmental Settings Suggests an Evolutionary Advantage Unrelated to Antibiotic Resistance.

Type B dihydrofolate reductases (DfrB) are intrinsically highly resistant to the widely used antibiotic trimethoprim, posing a threat to global public health. The ten known DfrB family members have been strongly associated with genetic material related to the application of antibiotics. Several dfrB genes were associated with multidrug resistance contexts and mobile genetic elements, integrated both in chromosomes and plasmids. However, little is known regarding their presence in other environments. Here, we investigated the presence of dfrB beyond the traditional areas of enquiry by conducting metagenomic database searches from environmental settings where antibiotics are not prevalent. Thirty putative DfrB homologues that share 62 to 95% identity with characterized DfrB were identified. Expression of ten representative homologues verified trimethoprim resistance in all and dihydrofolate reductase activity in most. Contrary to samples associated with the use of antibiotics, the newly identified dfrB were rarely associated with mobile genetic elements or antibiotic resistance genes. Instead, association with metabolic enzymes was observed, suggesting an evolutionary advantage unrelated to antibiotic resistance. Our results are consistent with the hypothesis that multiple dfrB exist in diverse environments from which dfrB were mobilized into the clinically relevant resistome. Our observations reinforce the need to closely monitor their progression.

Interpretable Deep Learning Applied to Rip Current Detection and Localization

A rip current is a strong, localized current of water which moves along and away from the shore. Recent studies have suggested that drownings due to rip currents are still a major threat to beach safety. Identification of rip currents is important for lifeguards when making decisions on where to designate patrolled areas. The public also require information while deciding where to swim when lifeguards are not on patrol. In the present study we present an artificial intelligence (AI) algorithm that both identifies whether a rip current exists in images/video, and also localizes where that rip current occurs. While there have been some significant advances in AI for rip current detection and localization, there is a lack of research ensuring that an AI algorithm can generalize well to a diverse range of coastal environments and marine conditions. The present study made use of an interpretable AI method, gradient-weighted class-activation maps (Grad-CAM), which is a novel approach for amorphous rip current detection. The training data/images were diverse and encompass rip currents in a wide variety of environmental settings, ensuring model generalization. An open-access aerial catalogue of rip currents were used for model training. Here, the aerial imagery was also augmented by applying a wide variety of randomized image transformations (e.g., perspective, rotational transforms, and additive noise), which dramatically improves model performance through generalization. To account for diverse environmental settings, a synthetically generated training set, containing fog, shadows, and rain, was also added to the rip current images, thus increased the training dataset approximately 10-fold. Interpretable AI has dramatically improved the accuracy of unbounded rip current detection, which can correctly classify and localize rip currents about 89% of the time when validated on independent videos from surf-cameras at oblique angles. The novelty also lies in the ability to capture some shape characteristics of the amorphous rip current structure without the need of a predefined bounding box, therefore enabling the use of remote technology like drones. A comparison with well-established coastal image processing techniques is also presented via a short discussion and easy reference table. The strengths and weaknesses of both methods are highlighted and discussed.

Highly Stable and End‐group Tuneable Metal–Organic Framework/Polymer Composite for Superior Triboelectric Nanogenerator Application

AbstractTriboelectric nanogenerators (TENGs) are receiving significant attention lately as efficient mechanical energy harvesting devices. They are finding multiple uses in numerous low‐power applications. Current TENG designs, although innovative, fall short on practical demands like performance tunability, modulatory, and stability. This invites further research in the use of new materials for TENGs. Metal‐organic frameworks (MOFs) offer a unique feature of molecular tunability to optimize energy conversion which has been exploited in this study. Prototypal hybridization strategy is deployed on underexplored isoreticular subfamily UiO‐66(Zr) MOFs through UiO‐66‐X/PVDF (X = H or Br) composites for TENG output tuning and amplification. UiO‐66‐X/PVDF exhibits good aquatic and thermal stability accompanying substantial boost in TENG power. Functionalized H2BDC linker improved surface roughness and potential. UiO‐66‐Br encased in PVDF matrix boosted charge and TENG performance by enhancing electrification. Computational details support observations. Device captures waste energy in a vertical contact‐separation mode and functions consistently amidst diverse environmental settings. Functionalized TENG‐2 delivers a Vp–p of 110.41 V, which is 2.92 times and 14.12 times higher than unfunctionalized TENG‐1 and PVDF film, respectively. Findings reveal maiden example of ligand‐mediated functional group‐driven performance tuning of TENG and mechanistic insight using isoreticular MOFs/PVDF composites.

Measuring intrinsic human activity information using WiFi-based attention model

In this work, we have proposed the first WiFi-based attention model for intrinsic human activity information measuring. First, both convolutional layers and time-recurrent layers are integrated in a one-off manner for joint feature learning. Based on this, a temporal attention module is introduced to capture activity moments and reduce lengthy data collections. In addition, a channel-spatial attention module is further designed to retrieve the activity feature of interest, without requiring any additional supervision. Extensive experiments were conducted for performance comparison under diverse environmental settings. The results showed that our model can achieve the best overall accuracy of 94.62%, 94.36% and 91.04% in three datasets with minimal manual efforts involved, and consistently outperforms other baselines under diverse parameter settings.

Enabling efficient WiFi-based occupant behavior recognition using insufficient samples

To launch energy-efficient and occupant-centric services in smart buildings, understanding occupant behavior is becoming an essential underpinning. Prevailing approaches mainly adopt ambient sensors, wearables or vision cameras, which suffer from insensitive perception, arduous deployment or privacy-leakage risks. Recently developed WiFi-based methods circumvent the above limitations, however, most of them require sufficient training samples and computational resources for a comprehensive understanding of behavior patterns. This scenario requires occupant cooperation and considerable energy consumption. In this paper, we propose the use of LT-WiOB, which is a lightweight triplet framework for WiFi-based occupant behavior recognition, that provides a cost-efficient and user-friendly solution. Technically, the novelties of LT-WiOB are threefold. For the insufficient data problem, an efficient triplet framework is presented to measure the embedding dependencies; it attempts to avoid the ambiguity of new samples from each class and allows only a few samples to be entered. Regarding inefficient computation, a lightweight convolutional module is specifically designed and implemented to reduce the model complexity. For unstable training, the triplet architecture is further enhanced by employing a novel triplet sampling strategy that creates useful triplet candidates. Extensive experiments were conducted for performance comparison under diverse environmental settings. The results showed that LT-WiOB realizes the best overall accuracy of 96.1% and achieves over 90% and 85% accuracy in the five-shot and one-shot conditions, respectively, with almost half of the computation cost being saved. These results verify the efficiency and feasibility of the proposed LT-WiOB model.

Evaluation of low-cost particulate matter sensors OPC N2 and PM Nova for aerosol monitoring

Low-cost sensors have the potential to revolutionize air pollution research by providing high spatial resolution data. However, data accuracy from the low-cost sensors remains a major concern. Therefore, it is necessary to evaluate the performance of the low-cost sensors. The current study evaluated the performance of two such low cost PM (particulate matter) sensors viz. OPC N2 (∼400 USD) and PM Nova sensor (∼20 USD) for four different uncontrolled test environments i.e. (a) Indoor (b) Indoor with incense stick (c) Ambient air (outdoor) and (d) Traffic, using an aerosol spectrometer (GRIMM 1.108) as the reference instrument. The results showed that both OPC N2 and PM Nova can record the airborne PM concentration with good accuracy as demonstrated through linear regression with Grimm (OPC N2, R2 = 0.954–0.987 and PM Nova, R2 = 0.872–0.981). The performance of the sensors was better for the finer particles (PM1 and PM2.5) than coarser particles (PM10). Meteorological parameters such as wind speed, temperature and RH did not have any significant impact on the sensor performance. Using a sampling tube did not have an impact on sensor performance. A modified python script for data retrieval from the sensors in a user-friendly format has been developed. More evaluations of used sensors and in diverse environmental settings can further increase the understanding about the sensor performance.

Bacterial pathogens identified from houseflies in different human and animal settings: A systematic review and meta-analysis.

Housefly (Musca domestica) is an excellent candidate for the distribution of susceptible and resistant bacterial strains that potentially threaten public health. To date, there is a paucity of information on the global distribution of pathogenic bacteria of medical and veterinary importance from diverse environmental settings. Therefore, this study was undertaken to conduct a systemic review and meta‐analysis to estimate occurrence of various bacterial species of medical and veterinary importance harboured by houseflies around the world. Published articles from 1980 to 2020 were retrieved from electronic databases and assessed for eligibility according to Preferred Reporting Items for Systemic Reviews and Meta‐Analysis guidelines. Seventy‐eight studies were included in the review with only 44 studies being eligible for meta‐analysis. Results indicated that eligible studies used in this review were from four continents, i.e., Asia (47.4%) America (23.1%), Africa (20.5%) and Europe (8.9%). The majority of the studies (56.4%) used the culture method for the identification of bacterial pathogens, while 30.7% used both culture and PCR techniques. For meta‐analysis, we focused on five pathogenic bacterial species including Escherichia coli, Enterococcus faecium, Klebsiella pneumoniae, Pseudomonas aeruginosa and Staphylococcus aureus. High heterogeneity was found among studies investigating different pathogens including E. coli (Q = 10,739.55; I 2 = 99.60; Q‐p 0.0001), E. faecium (Q = 317.61; I 2 = 86.46; Q‐p < 0.0001), K. pneumonia (Q = 1,576.61; I 2 = 97.27; Q‐p < 0.0001), S. aureus (Q = 2,439.12; I 2 = 98.24; Q‐p < 0.0001) and P. aeruginosa (Q = 1,283.0; I 2 = 96.65; Q‐p < 0.0001). Furthermore, it was observed that houseflies carried a considerable number of susceptible and antibiotic‐resistant bacterial strains that pose considerable threats to public health. Findings from this study have provided more insight on the vectoral potential of houseflies in the transmission of significant bacterial pathogens from different regions across the world. Further investigation is required to quantify the bacterial contamination and dissemination by houseflies.