Conventional diagnostic techniques are based on utilization of analyte sampling, sensing and signalling on separate platforms for detection purposes, that must be evaded and integrated to a single step procedure in point of care (POC) testing devices. Therefore, the trend has been shifted towards utilization of microfluidic platforms for detection of analytes in biochemical, clinical and food technology due to its being expeditious. Microfluidic systems moulded with polymer substances or glass offer specific and sensitive detection of infectious and non-infectious diseases by providing innumerable benefits including less cost, good biological affinity, strong capillary action and simple process of fabrication. In the case of nucleic acid-based nanosensors, there are some challenges that need to be addressed such as cellular lysis, isolation and amplification of nucleic acid required to be accomplished prior to its detection. To avoid utilization of laborious steps for executing these steps, advances have been deployed in this perspective for on-chip sample preparation, amplification and detection which not only improves sensitivity and selectivity but also saves time and resources. This review emphasizes the significance of microfluidic technology for nucleic acid detection of infectious and non-infectious diseases. The implementation of isothermal amplification in concomitance with lateral flow assay greatly increases the binding efficiency of nanoparticles and biomolecules, improves limit of detection and sensitivity. Most importantly deployment of paper-based material made of cellulose reduces the overall cost. Microfluidic technology in nucleic acid testing has been discussed by explicating its applications in different fields. This review concludes with the prospects and proposes future directions in microfluidic based methods in disease diagnosis.

Marula seed cake (MSC) is a nutritionally-rich natural feed resource that can enhance the healthiness of animal-derived foods (ADFs) for human consumption. This study compared the health-related fatty acid (FA) profiles of MSC products from South Africa and Eswatini. Composite samples monthly collected from both countries were analysed for FAs. MSC products from both countries were found to be dominated by oleic acid (>70%), followed by palmitic, linoleic and stearic acids. Consequently, both products had their FA totals dominated by ƩMUFA followed by ƩSFA, ƩPUFA, Ʃn-6 PUFA and Ʃn-3 PUFA. Both oleic and stearic acids were higher (P < 0.01) whilst linoleic (P < 0.001), α-linolenic (P < 0.05), margaric (P < 0.05), palmitoleic (P < 0.05) and eicosatrienoic (P < 0.05) acids were lower in South African in comparison to Eswatini MSC. Consequently, South African MSC had higher ƩMUFA (P < 0.01) but lower ƩPUFA (P < 0.001), Ʃn-6 PUFA (P < 0.001) and Ʃn-3 PUFA (P < 0.05). Also, Eswatini MSC had higher n-6 : n-3 PUFA, PUFA : SFA (P = 0.001) and PUFA : MUFA (P < 0.05) ratios. Further, MSC products from both countries had similarly (P > 0.05) low atherogenicity and high desaturase indices. In conclusion, both country products are rich particularly in oleic acid and their incorporation into farm animal diets would increase content of the MUFA in ADFs and, consequently, improve health benefits to human consumers.

Background: The prognostic value of erythrocyte levels of the n-6 fatty acids (FAs) for total mortality and cardiovascular disease (CVD) outcomes remains an open question. Methods: We examined CV outcomes and death in 2500 individuals in the Framingham Heart Study Offspring cohort without prevalent CVD (mean age 66 years, 57% women) as a function of baseline levels of different length n-6 FAs (18 carbon, 20 carbon and 22 carbon) in the erythrocyte membranes. Clinical outcomes were monitored for up to 9.5 years (median follow up, 7.26 years). Cox proportional hazards models were adjusted for a variety of demographic characteristics, clinical status and RBC n-6 and long chain n-3 FA content. Results: There were 245 CV events, 119 CHD events, 105 ischemic strokes, 58 CVD deaths, and 350 deaths from all causes. Few associations between either mortality or CVD outcomes were observed for the n-6 FAs, with those that were observed becoming non-significant after adjusting for n-3 FA levels. Conclusions: Higher circulating levels of the marine n-3 FA levels are associated with reduced risk for incident CVD and ischemic stroke and for death from CHD and all-causes, however in the same sample, little evidence exists for association with n-6 FAs. Further work is needed to identify a full profile of FAs associated with cardiovascular risk and mortality.

Pentadecanoic acid (C15:0) and heptadecanoic acid (C17:0) have been described as dietary biomarkers of dairy-fat consumption with varying degrees of reliability between studies. It remains unclear how the total amount of dietary fat; one of the main confounding factors in these biomarker investigations, affects C15:0 and C17:0 circulating compositions independently to their relative intake. Additionally, it is unknown how changes in the dietary total-fat affects other fatty acids in circulation. Through two dietary studies with different total-fat levels but maintaining individual fatty acid compositions we were able to see how the dietary total-fat affects the fatty acids in circulation. We saw that there was a significant, proportionate, and robust decrease in the endogenous C15:0 levels with an increase in dietary total-fat. However, there was an increase in the circulating C17:0 compositions as the total-fat increased. To conclude, the dietary total-fat content and fat-type have a very complex influence on the relative compositions of circulating fatty acids, which are independent to the actual dietary fatty acid composition. Knowing how to manipulate circulating C15:0 and C17:0 composition is far-reaching in nutritional/pathological research as they highlight a dietary route to attenuate the development of metabolic disease (both by reducing risk and improving prognosis).

Incorrect sitting posture, characterized by asymmetrical or uneven positioning of the body, often leads to spinal misalignment and muscle tone imbalance. Prolonged maintenance of such postures can adversely impact well-being and contribute to the development of spinal deformities and musculoskeletal disorders. In response, smart-sensing chairs equipped with cutting-edge sensor technologies have been introduced as a viable solution for real-time detection, classification, and monitoring of sitting postures, aiming to mitigate the risk of musculoskeletal disorders and promote overall health. This comprehensive literature review evaluates the current body of research on smart-sensing chairs, with a specific focus on the strategies used for posture detection and classification, as well as the effectiveness of different sensor technologies. A meticulous search across MDPI, IEEE, and Google Scholar databases yielded 34 pertinent studies that utilize non-invasive methods for posture monitoring. The analysis reveals that Force Sensing Resistors (FSR) are the predominant sensors utilized for posture detection, whereas Convolutional Neural Networks (CNN) and Artificial Neural Networks (ANN) are the leading machine learning models for posture classification. However, it was observed that CNNs and ANNs do not outperform traditional statistical models in terms of classification accuracy, due to constrained size and lack of diversity within training datasets. These datasets often fail to comprehensively represent the array of human body shapes and musculoskeletal configurations. Moreover, this review identifies a significant gap in the evaluation of user feedback mechanisms, essential for alerting users to their sitting posture and facilitating corrective adjustments.

Light detection and ranging (LIDAR) sensors using a polarization-diverse receiver are able to capture polarimetric information about the target under measurement. This information can be used in a classifier to make an instantaneous assessment of the type of material present, enabling a shot-by-shot prediction of the material type and distance to the target.

Onchocerciasis, or river blindness, has historically been one of the most important causes of blindness worldwide, and a major cause of socio-economic disruption, particularly in sub-Saharan Africa. Its importance as a cause of morbidity and an impediment to economic development in some of the poorest countries in the world motivated the international community to implement several programs to control or eliminate this scourge. Initially, these involved reducing transmission of the causative agent Onchocerca volvulus through controlling the vector population. When ivermectin was found to be a very effective drug for treating onchocerciasis, the strategy shifted to mass drug administration (MDA) of endemic communities. In some countries, both vector control and ivermectin MDA have been used together. However, traditional vector control methods involve treating rivers in which the black fly vectors breed with insecticides, a process which is expensive, requires trained personnel to administer, and is ecologically harmful. In this review, we discuss recent research into alternatives to riverine insecticide treatment, which are inexpensive, ecologically less harmful and which can be implemented by the affected communities themselves. These can dramatically reduce vector densities and, when combined with ivermectin MDA, can accelerate the time to elimination when compared to MDA alone.

Numerous elements, such as the composition and characteristics of carbon nanomaterials, the composition and characteristics of the matrix material, moisture levels, temperature, and loading circumstances, influence the piezoresistive behaviour of self-sensing cementitious composites. While some past research has explored the impact of some of these factors on the performance of self-sensing cementitious composites, additional investigations need to be conducted to delve into how loading conditions affect the sensitivity of self-sensing cement-stabilized composites. Therefore, this study explores the influences of various loading conditions (i.e., location of loading regarding the location of recording electrodes, and loading level) on the electromechanical performance of self-sensing cement-stabilized sand. To this end, firstly, the evaluation of the percolation threshold based on 10% cement-stabilized sand specimens containing various multiwall carbon nanotubes (MWCNTs) and graphene nanoplatelets (GNPs) was performed. Then, 10% cement-stabilized sand containing 4% MWCNTs/GNPs was tested under various cyclic compressive stresses. The results suggested that the distance between the loading area and the electrode location used for recording the electrical resistance significantly impacts the sensitivity of cement-stabilized sand. Optimal sensitivity was achieved when the electrodes were positioned directly beneath the loading area. Moreover, the study yielded that the stress sensitivity of self-sensing cement-stabilized sand increases proportionally with the stress level. Examination through scanning electron microscopy (SEM) demonstrated that the loading condition influences the bridging characteristics of carbon nanomaterials in cement-stabilized sand, leading to diverse electromechanical behaviors based on the loading condition. This study underscores the importance of considering specific parameters when designing the application of self-sensing cement-stabilized sand for practical field use.

In the Lubumbashi charcoal production basin (LCPB) in south-eastern DR Congo, agricultural and charcoal production activities regularly give rise to fires that lead to considerable degradation of the miombo open forest. This study analyzes the drivers of the spatio-temporal distribution of active fires and burnt areas in the LCPB by processing MODIS and Landsat data. In addition, a Kernel density analysis method (KDE) was used to estimate fire risk, while the effect of the road network and dwellings on vegetation fires was highlighted in areas between 0-3000m radius. Obtained results revealed that fires in the LCPB generally occur between April and November mainly during the day, between 11am and 12pm. These fires are concentrated in the central and south-western part of the LCPB, more specifically in the savannahs and near roads. From 2002 to 2022, an average of 11,237 active fires and an average of 6,337 km2 of burnt areas were recorded in the LCPB. Each year, these fires peak in August, and despite their steady decline, the few fires that have affected the forests have caused more devastation (more than 2790 km2 / year) than those observed in the fields and savannah. These figures highlight the imperative need to put in place fire prevention and management measures in the LCPB, with particular emphasis on awareness, monitoring and fire-fighting measures.

The research on the distribution of rural buildings is one of the fundamental works of urban-rural development in Vietnam. Adopting Mask R-CNN deep learning framework and collecting sub-meter remote sensing images, this research used a remote sensing interpretation model of rural buildings trained based on East Asian characteristics of rural buildings and successfully recognized about 2.87 million rural buildings in 34 Vietnamese provincial administrative districts with a total area of rural buildings of 2,492 million square meters. The reliability of the identification results was verified by manual detection and quantitative statistics, and a multi-scale database of rural buildings in Vietnam based on individual rural buildings was created. Based on the database, this paper analyzes the distribution characteristics of rural buildings and summarizes characteristics of rural buildings distribution at the country, regional, and provincial scales. The identification results lay the foundation for the next study of urban-rural relations in Southeast Asia and the construction of a basic database on villages.

In this work, backscattering signatures of snow-covered lake ice and sea ice from X- and Ku-band synthetic aperture radar (SAR) data are investigated. The SAR data were acquired with the ESA airborne SnowSAR sensor in winter 2012 over Lake Orajärvi in northern Finland and over landfast ice in the Bay of Bothnia of the Baltic Sea. Co-incident with the SnowSAR acquisitions in-situ snow and ice data were measured. In addition, time series of TerraSAR-X images and ice mass balance buoy data were acquired for the Lake Orajärvi in 2011-12. The main objective of our study was to investigate relationships between SAR backscattering signatures and snow depth over lake and sea ice, with the ultimate objective of assessing the feasibility of retrieval of snow characteristics using X- and Ku-band dual-polarisation (VV and VH) SAR over freshwater or sea ice. This study constitutes the first comprehensive survey of snow backscattering signatures at these two combined frequencies over both lake and sea ice. For lake ice, we show that X-band VH-polarized backscattering coefficient (σo) and the Ku-band VV/VH-ratio exhibited the highest sensitivity to the snow depth. For sea ice, the highest sensitivity to the snow depth was found from the Ku-band VV-polarised σo and the Ku-band VV/VH-ratio. However, the observed relations were relatively weak, indicating that at least for the prevailing snow conditions, obtaining reliable estimates of snow depth over lake and sea ice would be challenging using only X- and Ku-band backscattering information.

The analysis of the land use dynamics of the Lac Télé Community Reserve (RCLT) using Landsat Thematic Mapper (TM) and (Enhance Thematic Mapper) ETM+ images highlight significant changes in the vegetation cover from 1980 to 2000 and 2018. Thus, the rate of forest area decreased by 21.41% for the entire LTCR in favor of savannahs which increased by 15.23%. The conversion of this forest area to savannah due to the practice of slash and burn agriculture facilitates the opening up of the forest area and contributes to greatly degrading the spawning grounds of fish species from the Likouala aux herbes river. For the mapping of fishing activity in general and the ecological characterization of the 151 identified spawning grounds in particular; the respective mean values of the physical and chemical water parameters; temperature (28.13°C), pH (4.23) and depth (3.34) did not vary significantly from one selected village to another between July and September 2019. The fish diversity unregistered during the study, in the 07 pilot villages would be due to the diversity of the microhabitats noted in the villages of the LTCR, especially from the villages; Botongo, Mossengue and Bouanela where the indices of ichthyological diversity were the highest.

The coastal zone faces an ever-growing risk associated with climate-driven change, including sea level rise and increased frequency of extreme natural hazards. Coastal processes are governed by the dynamic ocean and atmospheric factors with constantly changing conditions. Often the location and dynamism of coastal regions makes them a formidable environment to adequately study with in-situ methods. Remote sensing methods offer an alternative to in-situ monitoring. In this study we use Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) to make measurements of basic wave parameters and wave directionality in the Hawaiian Islands and North Carolina, USA. ICESat-2 has existing Level-3a data products, Ocean Surface Height (ATL12) and Inland Water Elevation (ATL13), providing some wave and ocean surface elevation data. ATL12 provides sparse global average measurements of the sea surface elevation, slope, and roughness along ICESat-2 tracks and ATL13 provides wave metrics at variable length scales out to ~7 km from the coast and does not maintain the 0.7m along-track resolution of the primary Level-2 data product (ATL03). Our goal was to leverage the full resolution data available in ATL03 to generate wave metrics out from shore up to ~25 km. Using a combination of statistical and signal processing methods we can use ICESat-2 to generate basic wave metrics, including significant wave heights with an accuracy of ±0.5m. In some profiles we can identify wave shoaling, which could be used to infer bathymetry. In areas with complex wave dynamics, the nature of how ICESat-2 measures elevations (parallel laser altimetry beams) can make extracting some wave parameters (e.g., wavelength and directionality) more challenging. These wave metrics can provide important data in support of validating wave and tidal models and may also prove useful in ICESat-2 bathymetric corrections and satellite derived bathymetry.

The study sheds light on the impact of urbanization on fragile ecosystems such as the western Himalayas. We use Haldwani in Uttarakhand as an example of human encroachment and loss of ecosystem services. Several environmental parameters such as Nighttime light (NTL), Land Surface Temperatures (LSTs), Aerosol Optical Depth (AOD) and forest cover are used based on satellite imagery to allow a bidecadal comparison (between 2000 and 2020) of the status of these parameters for the city based on these parameters shows a decline in ecosystem services. Significant statistical differences for LSTs and AOD (p < 0.001) can be found in the bidecadal comparison. Furthermore, a strong negative correlation was found between LST-NDVI (r = -0.69) and between NTL-NDVI (r = -0.58) in earlier and last decade intervals. In addition, long-term multi-spectral satellite imagery also shows a decline in tree cover in the reserved forest. Therefore, focusing on ecosystem services related to tree cover in reserved forest areas, particularly in the Indian Himalayan Region (IHR) must be part of a broader action plan to address these issues to further protect fragile Himalayan ecosystems.

Snow parameters have traditionally been retrieved using discontinuous, multi-band sensors; however, continuous hyperspectral sensor are now being developed as an alternative. In this paper we investigate the performance of various sensor configurations using machine learning neural networks trained on a simulated dataset. Our results show improvements in accuracy of retrievals of snow grain size and impurity concentration for continuous hyperspectral channel configurations. Retrieval accuracy of snow albedo was found to be similar for all channel configurations.

Chlorophyll-a (Chla) is a crucial pigment in phytoplankton, playing a vital role in determining phytoplankton biomass and water nutrient status. However, in optically complex water bodies, Chla concentration is no longer the primary factor influencing remote sensing spectral reflectance signals, leading to significant errors in traditional Chla concentration estimation methods. With advancements in in-situ measurements, synchronized satellite data, and computer technology, machine learning algorithms have become popular in Chla concentration retrieval. Nevertheless, when using machine learning methods to estimate Chla concentration, abrupt changes in Chla values can disrupt the spatiotemporal smoothness of the retrieval results. Therefore, this study proposes a two-stage approach to enhance the accuracy of Chla concentration estimation in optically complex water bodies. In the first stage, a one-dimensional convolutional neural network (1DCNN) is employed for precise Chla retrieval, and in the second stage, the regression layer of the 1DCNN is replaced with Support Vector Regression (SVR). The research findings are as follows: (1) In the first stage, the performance metrics (R², RMSE, RMLSE, Bias, MAE) of the 1DCNN outperform state-of-the-art algorithms (OCI, SVR, RFR) on the test dataset. (2) After the second stage, the performance further improves, with the metrics achieving values of 0.892, 11.243, 0.052, 1.056, and 1.444, respectively. (3) In mid-to-high latitude regions, the inversion performance of 1DCNN\SVR is superior to other algorithms, exhibiting richer details and higher noise tolerance in nearshore areas. (4) 1DCNN\SVR demonstrates high inversion capabilities in water bodies with medium to high nutrient levels.

Considering higher stability and lower cost of nanozymes than native enzymes, the nanozymatic systems had been utilized for several practical application, especially for sensing and detection. Most of common nanozymatic sensors are single-nanozyme based systems, however, recently a new generation of nanozyme-based systems called “multinanozyme system’ was introduced by Hormozi Jangi et al. (2020). Since the first report of multinanozyme systems, several multinaozyme systems have been developed and utilized for highly sensitive and selective sensing aims. The main advantages of multinaozyme systems compared of common nanozymatic sensors are their impact on simultaneous enhancing selectivity and sensitivity of sensor in a well-designed detection process. Since, the principles of design and detection mechanism of this new generation is not well-described in the literature, the aim of this article is the fast review of the principles of design of this new generation of nanozyme-based sensing and detection.

Sea ice extraction and segmentation of remote sensing images is the basis for sea ice monitoring. Machine learning-based image segmentation methods rely on manual sampling and require complex feature extraction. Deep-learning semantic segmentation methods have the advantages of high efficiency, intelligence, and automation. Sea ice segmentation using deep learning methods faces the following problems: in terms of datasets, the high cost of sea ice image label production leads to fewer datasets for sea ice segmentation; in terms of image quality, remote sensing image noise and Severe weather conditions affects image quality, which affects the ac-curacy of sea ice extraction. To address the quantity and quality of the dataset, this study used multiple data augmentation methods for data expansion. To improve the semantic segmentation accuracy, the SC-U2-Net network was constructed using multi-scale inflation convolution and a multi-layer Convolutional Block Attention Module (CBAM) attention mechanism for the U2-Net network. The experiments showed that (1) data augmentation solved the problem of an insuffi-cient number of training samples to a certain extent and improved the accuracy of image seg-mentation. (2) This study designed a multilevel Gaussian noise data augmentation scheme to improve the network's ability to resist noise interference and achieve a more accurate segmenta-tion of images with different degrees of noise pollution. (3) The inclusion of a multi-scale inflation perceptron and multi-layer CBAM attention mechanism improved the ability of U2-Net network feature extraction and enhanced the model accuracy and generalization ability.

Recently, the move from cost-tied to open-access data has led to the mushrooming of research in pursuit of algorithms for estimating aboveground grass biomass (AGGB). Nevertheless, a comprehensive synthesis or direction on the milestones archived or an overview of how these models perform is lacking. This study synthesises the research work from decades of experiments in order to point researchers in the direction of what was done, the challenges faced, as well as how the models perform. A pool of findings from 108 remote sensing-based AGGB studies published from 1972 to 2020 show that about 62% of the remote sensing-based algorithms were tested in the Steppe grasslands, mostly in the temperate climate zone. An uneven annual publication yield was observed with approximately 36% of the research output from Asia whereas countries in the global south yielded few publications (&lt;10%). Optical sensors, particularly MODIS, remain a major source of satellite data for AGGB studies, whilst studies in the global south rarely use active sensors such as Sentinel-1. Optical data tend to produce poor regression accuracies that are highly inconsistent across the studies compared to Radar. Vegetation indices, particularly the Normalised Difference Vegetation Index (NDVI), remain a major predictor variable. Predictor variables such as Sward height, Red edge position and Backscatter coefficients produced slightly consistent accuracies. Deciding on the optimal algorithm for estimating AGGB is daunting due to the lack of overlap in the grassland type, location, sensor types, and predictor variables, signalling the need for further studies around the transferability of remote sensing-based AGGB models.

After a time away from the classrooms and laboratories due to the global pandemic, the return to the teaching activities during the semester represented a challenge to both teachers and students. Our particular situation in a Microbial Physiology course was the necessity of imparting in a shorter time, laboratory practices that usually take longer. This article describes a two-week long laboratory exercise that covers several concepts in an interrelated way: conjugation as a gene transfer mechanism, regulation of microbial physiology, production of secondary metabolites, degradation of macromolecules and biofilm formation. Utilizing a Quorum Quenching (QQ) strategy, the Quorum Sensing (QS) system of Pseudomonas aeruginosa is first attenuated. Then, phenotypes regulated by QS are evidenced. QS is a regulatory mechanism of the microbial physiology that relays on signal molecules. QS is related in P. aeruginosa to several virulence factors, some of which are exploited in the laboratory practices presented in this work. QQ is phenomenon by which QS is interrupted or attenuated. We utilized a QQ approach based on the enzymatic degradation of the P. aeruginosa QS signals in order to put in evidence QS-regulated traits that are relevant for our Microbial Physiology course.

Aerosol Optical Thickness (AOT) is one of the critical factors for global atmospheric conditions, climate change, and air pollution. AOT has been exposed as a major component of air pollution in Bangladesh. This paper aims to map the seasonal distribution of AOT from 2002-2022 and to explore the internal relationship between AOT and ten air pollutants using remote sensing and machine learning tools. These ten air pollutants are Particulate matter (PM2.5), Methane (CH4), Carbon monoxide (CO), Nitrogen dioxide (NO2), Formaldehyde (HCHO), Ozone (O3), Sulfur dioxide (SO2), Aerosol Particulate Radius (APR), Nitrogen oxide (NOx) and Black carbon (BC). The results show that the concentrations of AOT were higher in December-January-February (mean value 0.50) and March-April-May (mean value 0.50) seasons, mostly in the central, western, and southern parts of Dhaka, Narayanganj, and Munshiganj districts. AOT was a bit less in June-July-August (mean value 0.33) and September-October-November (mean value 0.37). This paper also revealed that the AOT was correlated positively with PM2.5 (0.60), CH4 (0.80), NO (0.76), and BC (0.83) while correlated negatively with CO (-0.66), HCHO (-0.16), SO2 (-0.41), APR (-0.48), and NOx (-0.20). From the machine learning, the Rational quadratic GPR (RME-0.0024, MAE-0.0015, R2-0.96), Matern 5/2 GPR (RMSE-0.0023, MAE-0.0015, R2-0.96), and Squared Exponential GPR (RMSE-0.0015, MAE-0.0015, R2-0.96) were found good classifiers to predict AOT. UN agencies, government line departments, and local and regional development councils for air pollution mitigation and long-term protective measures may use the paper's key results.

Cannabidiol (CBD) is an active diterpenoid compound that is extracted from the leaves and stem of Cannabis sativa. Previous studies show that CBD is a non-psychotropic compound with significant anti-cancer effects. This study determines its cytotoxic effect on oral cancer cells and OECM1 cells and compares the outcomes with a chemotherapeutic drug, cisplatin. This study determines the effect of CBD on the viability, apoptosis, morphology and migration of OECM1 cells. Electric cell-substrate impedance sensing (ECIS) is used to measure the change in cell impedance for cells that are treated with a series concentration of CBD for 24 hours. AlamarBlue and annexin V/7-AAD staining assays show that CBD has a cytotoxic effect on cell viability and induces cell apoptosis. ECIS analysis shows that CBD decreases the overall resistance and morphological parameters at 4 kHz in a concentration-dependent manner. There is a significant reduction in the wound-healing recovery rate for cells that are treated with 30 μM CBD. This study demonstrates that ECIS can be used for in vitro screening of anticancer drugs and is more sensitive, functional and comprehensive than traditional biochemical assays. CBD also increases cytotoxicity on cell survival and the migration of oral cancer cells, so it may be a therapeutic drug for oral cancer

The Kashmir valley is prone to flooding due to its peculiar geomorphic setup compounded by the rapid anthropogenic land system changes and climate change. The study assesses the impact of land use and land cover (LULC) changes between 1980 and 2020 and extreme rainfall on peak discharge and sediment yield in the Upper Jhelum Basin (UJB), Kashmir Himalaya, India using KINEROS2 model. Analysis of LULC change revealed a notable shift from natural LULC to more intensive human-modified LULC, including a decrease in vegetative cover, deforestation, urbanization, and improper farming practices. The findings revealed a strong influence of the LULC changes on peak discharge, and sediment yield relative to the 2014 timeframe, which coincided with the catastrophic September 2014 flood event. The model predicted a peak discharge of 115101 cubic feet per second (cfs) and a sediment yield of 56.59 tons/ha during the September 2014 flooding, which is very close to the observed peak discharge of 115218 cfs indicating that the model is reliable for discharge prediction. The model predicted a peak discharge of 98965 cfs and a sediment yield of 49.11 tons/ha in 1980, which increased to 118366 cfs and, 58.92 tons/ha respectively in 2020, showing an increase in basin’s flood risk over time. In the future, it is anticipated that the ongoing LULC changes will make flood vulnerability worse, which could lead to another major flooding in the event of an extreme rainfall as predicted under climate change and, in turn compromise achievement of sustainable development goals (SDG). Therefore, regulating LULC in order to modulate various hydrological and land surface processes would ensure stability of runoff and reduction in sediment yield in the UJB, which is critical for achieving many SDGs.

The vulnerability of vegetation in the Middle East to meteorological conditions and climate change, especially those leading to drought, is high. Despite the importance of the Amu Darya and Kabul River Basins (ADB and KRB) as a region in which more than 15 million people live, and its vulnerability to global warming, only several studies addressed the issue of the linkage of meteorological parameters on vegetation for the eastern basins of Afghanistan. In this study, data from the Moderate Resolution Imaging Spectroradiometer (MODIS), Global Precipitation Measurement Mission (GPM), and Land Data Assimilation System (GLDAS) to examine the impact of meteorological parameters on vegetation for the eastern basins of Afghanistan for the period from 2000 to 2021. The study utilized several indices, such as Precipitation Condition Index (PCI), Temperature Condition Index (TCI), Soil Moisture Condition Index (SMCI), and Microwave Integrated Drought Index (MIDI). The relationships between meteorological quantities, drought conditions, and vegetation variations were examined by analyzing the anomalies and using regression methods. The results showed that the years 2000, 2001, and 2008 had the lowest vegetation coverage (VC) (56, 56, and 55% of the study area, respectively). On the other hand, the years 2010, 2013, 2016, and 2020 had the highest VC (71, 71, 72, and 72% of the study area, respectively). The trend of the VC for the eastern basins of Afghanistan for the period from 2000 to 2021 was upward. High correlations between VC and soil moisture (R = 0.70, p = 0.0004), and precipitation (R = 0.5, p = 0.008) were found, whereas no significant correlation was found between VC and drought index MIDI. It was revealed that soil moisture, precipitation, land surface temperature, and area under meteorological drought conditions explained 45% of annual VC variability.

Burn injury serves as an example of a condition with a robust inflammatory response. The elevation of circulating interleukins (IL)- 1 beta and -6 in children with severe burn injury up-regulate the parathyroid calcium sensing receptor (CaSR) resulting in hypocalcemic hypoparathyroidism with urinary calcium wasting. This effect protects the body from the hypercalcemia resulting from bone resorption liberating calcium into the circulation. Extracellular calcium can exacerbate and prolong the inflammatory response by stimulating mononuclear cell chemokine production as well as the NLRP3 inflammasome of the innate immune system, resulting in increased IL-1 production by monocytes and macrophages. Interestingly, the CaSR response to inflammatory cytokines disappears with age, potentially trapping calcium from bone resorption in the circulation and allowing it to contribute to increased inflammation and possibly increased calcium deposition in small arteries, , such as the coronaries, as conditions with increased chronic inflammation, such as spinal cord injury, osteoarthritis and rheumatoid arthritis have an incidence of cardiovascular disease and coronary artery calcium deposition significantly higher than the unaffected age-matched population.

Abstract: Early assessment of crop development is a key aspect of precision agriculture. Shortening the time of response before a deficit of irrigation, nutrients and damage by diseases is one of the usual concerns in agriculture. Early prediction of crop yields can increase profitability in the farmer's economy. In this study we aimed to predict the yield of four maize commercial hybrids (Dekalb7508, Advanta9313, MH_INIA619 and Exp_05PMLM) using remotely sensed spectral vegetation indices (VI). A total of 10 VI (NDVI, GNDVI, GCI, RVI, NDRE, CIRE, CVI, MCARI, SAVI, and CCCI) were considered for evaluating crop yield and plant cover at 31, 39, 42, 46 and 51 days after sowing (DAS). A multivariate analysis was applied using principal component analysis (PCA), linear regression, and r-Pearson correlation. In the present study, highly significant correlations were found between plant cover with VIs at 46 (GNDVI, GCI, RVI, NDRE, CIRE and CCCI) and 51 DAS (GNDVI, GCI, NDRE, CIRE, CVI, MCARI and CCCI). The PCA indicated a clear discrimination of the dates evaluated with VIs at 31, 39 and 51 DAS. The inclusion of the CIRE and NDRE in the prediction model contributed to estimate the performance, showing greater precision at 51 DAS. The use of RPAS to monitor crops allows optimizing resources and helps in making timely decisions in agriculture in Peru.

Molecular communication (MC) is a promising bio-inspired paradigm for exchanging molecule information among nanomachines. This paper proposes a synchronisation-assist photolysis MC system that aims to transmit the bio-sensing signal of the tumour microenvironment, facilitated by mitigating redundant molecules for improved bit error rate (BER) performance. Benefits from bio-compatible MC, biosensors could transmit bio-sensing signals of the tumour in $vivo$ instead of converting them to electrical signals. Due to diffusion motion's slow and stochastic nature, inter-symbol interference (ISI), resulting from previous symbols' residual information molecules, inevitably occurs in diffusion-based MC. ISI is one of the challenges in diffusion-based MC, which significantly impacts signal detection. Inspired by on-off keying (OOK) modulation, the proposed modulation implements a switch of molecules and light alternatively. The light emitted is triggered by a synchronisation signal, and the photolysis reactions could reduce the redundant molecules. An expression for the relevant channel impulse response (CIR) is derived from a hybrid channel model of diffusion and photolysis-reaction. This paper implements the maximum posterior estimation scheme to find the optimal decision threshold and analysis the BER performance in terms of different time intervals of the system. Numerical simulations demonstrate that the proposed method can improve the channel capacity and BER performance. We believe that our work may pave the way for MC application in bio-sensing.

Concrete condition assessing penetrometers need to be able to distinguish between making contact with a hard (concrete) surface as opposed to a semi-solid (corroded concrete) surface. If a hard surface is mistaken for a soft surface, concrete corrosion may be over-estimated, with the potential for triggering unnecessary remediation works. Unfortunately, the variably-angled surface of a concrete pipe can cause the tip of a force-sensing tactile penetrometer to slip and thus to make this mistake. We investigated whether different shaped tips of a cylindrical penetrometer were better than others at maintaining contact with concrete and not slipping. We designed a range of simple symmetric tip shapes, controlled by a single superellipse parameter. We performed a finite element analysis of these parametric models in SolidWorks before machining in stainless steel. We tested our penetrometer tips on a concrete paver cut to four angles at 20∘ increments. The results indicate that penetrometers with a squircle-shaped steel tip (a=b=1,n=4) have the least slip, in the context of concrete condition assessment.

Specific emissivity features of swamps and wetlands of Western Siberia were studied for changing seasonal conditions with the use of daily data of satellite microwave sounding. The research technique involved the analysis of brightness temperatures of the underlying surface at the test sites. Variations in seasonal dynamics of brightness temperatures were mainly caused by different rates of seasonal freezing of the upper waterlogged layer of the underlying surface and dielectric characteristics of water containing natural media (water body, soil, vegetation). We analyzed long-term trends in seasonal and annual dynamics of brightness temperatures of the underlying surface and estimated hydrological changes in the Arctic and Subarctic. The findings open up new possibilities for using satellite data in the microwave range for studying natural seasonal dynamic processes and predicting hazardous hydrological phenomena.

We compared two approaches to non-invasive proximal sensing of the early changes in fresh-cut lettuce leaf quality: hyperspectral imaging and imaging PAM-fluorometry of chlorophyll contained in the leaves. The assessments made by the imaging techniques were confronted with the quality assessments made by traditional biochemical assays: relative water content and foliar pigment (chlorophyll and carotenoid) composition. The hyperspectral imaging-based approach provided the highest sensitivity to the decline of fresh-cut lettuce leaf quality taking place within 24 h from cutting. Using of the imaging PAM was complicated by (i) weak correlation of the spatial distribution pattern of the Qy parameter with the actual physiological condition of the plant object and (ii) its high degree of heterogeneity. Accordingly, the imaging PAM-based approach was sensitive only to the manifestations of leaf quality degradation only at advanced stages of the process. Sealing the leaves in the polyethylene bags slowed down the leaf quality degradation at the initial stages (&lt; 3 days) but promoted its rate at more advanced stages, likely due to build-up of ethylene in the bags. An approach was developed to the processing of hyperspectral data for non-invasive monitoring of the lettuce leaves with a potential for implementation in greenhouses and packinghouses.

Wireless sensor networks are attractive largely because they need no wired infrastructure. But precisely this feature makes them energy constrained. Recent studies find that sensing behaviors that are otherwise deemed efficient consume comparable energy with communication. The duty cycle scheduling is perceived as contributing to achieving energy efficiency of sensing. Because of different research assumptions and objectives, various scheduling schemes have various emphases. This paper designed an adaptive sensing scheduling strategy. The objective function of the scheduling strategy includes minimizing average energy expenditure and maximizing sensing coverage (reducing event miss-rate), and it requires relatively loose assumptions. We determine the functional relationship between the variables of the objective function and the step-size parameters of the proposed strategy through the numerical fitting. We found that the objective function aggregated by the fitting functions is a bivariate multi-peak function that favors the Fibonacci tree optimization algorithm. Once the optimization of parameters is done, the strategy can be easily deployed and behaves consistently in the coming hours. We name the proposed strategy as “FTOS”. The experimental results show that the Fibonacci tree optimization algorithm gets a better optimistic effect than the comprehensive learning particle swarm optimization (CLPSO) algorithm and differential evolution (DE) algorithm. The FTOS strategy is superior to the fixed time scheduling strategy in achieving the scheduling objectives. It also outperforms other strategies with the same scheduling objectives such as LDAS, BS, DSS and PECAS.

Automatic ice charting can not be achieved using only SAR modalities. It is fundamental to combine information from other remote sensors with different characteristics for more reliable sea ice characterization. In this paper, we employ principal feature analysis (PFA) to select significant information from multimodal remote sensing data. PFA is a simple yet very effective approach that can be applied to several types of data without loss of physical interpretability. Considering that different homogeneous regions require different types of information, we perform the selection patch-wise. Accordingly, by exploiting the spatial information, we increase the robustness and accuracy of PFA.

This paper focuses on processing low oversampling echo data of staggered synthetic aperture radar (SAR). In staggered mode, the non-uniformly sampling and irregular loss of echo data cause azimuth ambiguity which severely degrades the imaging quality. To solve this problem, we propose a compressed sensing (CS) method in which the non-uniform fast Fourier transform (NUFFT) technique is adopted to obtain uniform azimuth spectrum, and the fast iterative shrinkage thresholding algorithm (FISTA) is utilized to efficiently reconstruct the ambiguity-free image from in-complete echo data. Simulation results demonstrate the proposed method can effectively suppress the azimuth ambiguity in the vicinity of targets.

Malaria is a disease spread by female mosquitos of the Anopheles genus. It is acutely prevalent in Sub-Saharan Africa, where 90% of malaria deaths occur annually. One Sub-Saharan African country historically impacted by malaria is Ethiopia. In the past twenty years, malaria prevalence has decreased throughout Sub-Saharan Africa; yet, anthropogenic environmental changes are changing the landscape of malaria. Scholarly literature has cited a positive relationship between hydroelectric dams and malaria in Sub-Saharan Africa. Ethiopia is currently expanding their hydroelectric infrastructure. The Gilgel Gibe III Dam is located on the Omo River in Southwestern Ethiopia. It began generating electricity in 2015 and its reservoir has a capacity of 14,700 million m3 of water. This research utilized Geographic Information Systems and Remote Sensing to identify populations at an increased risk of malaria due to Gilgel Gibe III Dam. Two different techniques were employed: the proximity approach and the remote sensing approach. The proximity approach was based on distance from the reservoir. It identified all populations living within three kilometers of the reservoir as being at an increased risk. The remote sensing approach evaluated the slope, elevation, water content, and land surface temperature of the study area to create a mosquito breeding habitat risk map. Then, populations living within three kilometers of the two main High-Risk areas were identified. This study suggests that mosquito breeding habitat risk is not equally distributed throughout the Gilgel Gibe III Reservoir. This causes certain populations to be at a heightened risk of malaria.

N-Acyl-homoserine lactones, the Quorum sensing signaling molecules predominantly found in gram-negative bacteria, which regulate several bacterial genes including virulence and antibiotic resistant genes. The study was aimed to identify and characterize QS and QQ bacteria from different samples. 5 samples with different ecological background were collected from soil and 10 samples from hospital setup. 31 different bacteria were isolated with either QS or QQ activities all together. CV026 and A136 biosensor strains were used for the detection of QS and QQ positive strains. QS activity was observed by cross streaking test of bacteria against CV026, it was affirmed that 13 isolates from the soil and 5 from hospital equipment’s showed positive QS activity. QQ activity of each isolate was tested by well diffusion assay, C6-HSL and C12-HSL were our candidate AHL molecules. The AHL molecule degradation was detected in 4 isolates of soil and none from the samples obtained from hospital setup. The total of 6 strongly positive QS and QQ isolates were identified and selected for 16S rRNA gene sequencing. The phylogenetic analysis revealed that these isolates were closely related to Pseudomonas, Bacillus and Exiguobacterium genera. In contrast, 1 Gram positive bacterial isolate was also purified with QS potential.

The European heatwave of 2018 led to record-breaking temperatures and extremely dry conditions in many parts of the continent resulting in widespread decrease in agricultural yield, early tree-leaf senescence, and increase in forest fires in Northern Europe. Our study aims to capture the impact of the 2018 European heatwave on terrestrial ecosystem through the lens of a high-resolution solar-induced fluorescence (SIF) data acquired from the Orbiting Carbon Observatory (OCO-2) satellite. SIF is proposed to be a direct proxy for gross primary productivity (GPP) and thus can be used to draw inferences about changes in photosynthetic activity in vegetation due to extreme events. We explore spatial and temporal SIF variation and anomaly during spring and summer months across different vegetation types (agriculture, broadleaved forest, coniferous forest, and mixed forest) during the European heatwave of 2018 and compare it to non-drought conditions (most of Southern Europe). About one-third of Europe’s land area experienced a consecutive spring and summer drought in 2018. Comparing 2018 to mean (2015-2017) conditions, we found a change in intra-spring season SIF dynamics for all vegetation types, with lower SIF during the start of spring followed by an increase in fluorescence from mid-April. Summer, however, showed a significant decrease in SIF. Our results show that particularly agricultural areas were severely affected by the hotter drought of 2018. Furthermore, the intense heat wave in Central Europe showed about 31% decrease in SIF values during July and August as compared to the mean over three previous years. Furthermore, our MODIS and OCO-2 comparative results indicate that especially for forests, OCO-2 SIF has a quicker response and possible higher sensitivity to drought in comparison to MODIS’s fPAR and NDVI when considering shorter reference periods, which highlights the added value of remotely sensed solar-induced fluorescence for studying the impact of drought on vegetation.

Precipitation and temperature are significant inputs for hydrological models. Currently, many satellite and reanalysis precipitation and air temperature datasets exist at different spatio-temporal resolutions at a global and quasi-global scale. This study evaluated the performances of three open-access precipitation datasets (gauge-adjusted research-grade Global Satellite Mapping of Precipitation (GSMaP_Gauge), Climate Hazards Group Infrared Precipitation with Station data (CHIRPS), Climate Forecast System Reanalysis(CFSR)) and CFSR air temperature dataset in driving the Soil and Water Assessment Tool (SWAT) model required for the monthly simulation of streamflow in the upper Shiyang River Basin of northwest China. After a thorough comparison of six model scenarios with different combinations of precipitation and air temperature inputs, the following conclusions were drawn: (1) Although the precipitation products had similar spatial patterns, however, CFSR differs significantly by showing an overestimation; (2) CFSR air temperature yielded almost identical performance in the streamflow simulation than the measured air temperature from gauge stations; (3) among the three open-access precipitation datasets, CHIRPS produced the best performance. These results suggested that the CHIRPS precipitation and CFSR air temperature datasets which are available at high spatial resolution (0.05), could be a promising alternative open-access data source for streamflow simulation in the case of limited access to desirable gauge data in the data-scarce area.

We discuss some of the fundamental practical limitations of the Fluctuation-Enhanced Sensing of odors and gases. We address resolution, measurement speed, reproducibility, memory and other problems such as humidity. Various techniques and ideas are presented to overcome these problems. Circuit solutions are also discussed.

An improved method for Fluctuation Enhanced Sensing (FES) is introduced. We enhanced the old binary fingerprinting method, where the fingerprint bit values were ± 1, by introducing ternary fingerprints utilizing a reference odor. In the ternary method, the fingerprint bit values are -1, 0, and +1 where the 0 value stands for the situation where the slope of the spectrum is identical to that of the reference odor. The application of the reference odor spectrum makes the fingerprint relative to the reference. This feature increases the information entropy of the fingerprints. The method is briefly illustrated by sensing bacterial odor in cow manure isolates.

Chiroptical responses have been an essential tool over the last decades for chemical structural elucidation due to their exceptional sensitivity to geometry and intermolecular interactions. In recent times, there has been an increasing interest for the search of more efficient sensing by the rational design of tailored chiroptical systems. In this Review article, advances on chiroptical systems towards their implementation in sensing applications are summarized. Strategies to generate chiroptical responses are illustrated. Theoretical approaches to assist in the design of these systems are discussed. Development of efficient chiroptical reporters in different states of matter, essential for the implementation in sensing devises, is reviewed. In the last part, remarkable examples of chiroptical sensing applications are highlighted.

In general, remote sensing has proven to be a powerful tool in the overall understanding of natural and anthropogenic phenomena. Satellites have become useful tools for tasks such as characterization, monitoring, and the continuous prospecting of natural resources. This research aims to analyze spatial dynamic and destructive on coral reefs area and correlation between live coral reduction and population on small islands. Landsat MSS, TM, ETM, and OLI-TIRS are used to spatial analyze of coral reef dynamics from 1972 to 2016. The image processing includes gap-filling, atmospheric correction, geometric correction, image composite (true color), water column correction, unsupervised classification, reclassification, accuracy assessment. The statistical analysis identifies the relationship between dynamic population data with a reduction of live coral, namely Principal Component Analysis (PCA) and Multiple Regression Analysis. The effect of the population shows a positive correlation with the reduction in the area of live coral, although it is significant. The fact is the practice of coral destruction on an island; it is usually not only caused or carried out by residents who live on the island but also carried out by other residents of different islands.

We discuss a topological method of storing and retrieving information from flash memory. We first present a sensing method where the threshold voltage level, as represented by a sensing time, is extracted in one sensing cycle. The sense time distribution from one set of flash cells, e.g. one physical row, is then processed in software to decode the digital state of each cell. The decoding method uses topological constraints but no rigid or predetermined voltage thresholds to digitize the distribution. The software defined nature of the topologically defined flash (TDF) allows greater flexibility for allocating cells to arbitrary number of digital states.

We apply deep convolutional neural networks (CNNs) to estimate wave breaking type from close-range monochrome infrared imagery of the surf zone. Image features are extracted using six popular CNN architectures developed for generic image feature extraction. Logistic regression on these features is then used to classify breaker type. The six CNN-based models are compared without and with augmentation, a process that creates larger training datasets using random image transformations. The simplest model performs optimally, achieving average classification accuracies of 89% and 93%, without and with image augmentation respectively. Without augmentation, average classification accuracies vary substantially with CNN model. With augmentation, sensitivity to model choice is minimized. A class activation analysis reveals the relative importance of image features to a given classification. During its passage, the front face and crest of a spilling breaker are more important than the back face. Whereas for a plunging breaker, the crest and back face of the wave are most important. This suggests that CNN-based models utilize the distinctive `streak' temperature patterns observed on the back face of plunging breakers for classification.

In past few years, unmanned aerial vehicles (UAV) or drones has been a hot topic encompassing technology, security issues, rules and regulations globally due to its remarkable advancements and uses in remote sensing and photogrammetry applications. This review paper highlights the evolution and development of UAV, classification and comparison of UAVs along with Hardware and software design challenges with diverse capabilities in civil and military applications. Further, safety and security issues with drones, existing regulations and guidelines to fly the drone, limitations and possible solutions have also been discussed.

In California, water is a perennial concern. As competition for water resources increases due to growth in population, California’s tree nut farmers are committed to improving the efficiency of water used for food production. There is an imminent need to have reliable methods that provide information about the temporal and spatial variability of crop water requirements, which allow farmers to make irrigation decisions at field scale. This study focuses on estimating the actual evapotranspiration and crop coefficients of an almond and pistachio orchard located in Central Valley (California) during an entire growing season by combining a simple crop evapotranspiration model with remote sensing data. A dataset of the vegetation index NDVI derived from Landsat-8 was used to facilitate the estimation of the basal crop coefficient (Kcb), or potential crop water use. The soil water evaporation coefficient (Ke) was measured from microlysimeters. The water stress coefficient (Ks) was derived from airborne remotely sensed canopy thermal-based methods, using seasonal regressions between the crop water stress index (CWSI) and stem water potential (Ystem). These regressions were statistically-significant for both crops, indicating clear seasonal differences in pistachios, but not in almonds. In almonds, the estimated maximum Kcb values ranged between 1.05 to 0.90, while for pistachios, it ranged between 0.89 to 0.80. The model indicated a difference of 97 mm in transpiration over the season between both crops. Soil evaporation accounted for an average of 16% and 13% of the total actual evapotranspiration for almonds and pistachios, respectively. Verification of the model-based daily crop evapotranspiration estimates was done using eddy-covariance and surface renewal data collected in the same orchards, yielding an r² >= 0.7 and average root mean square errors (RMSE) of 0.74 and 0.91 mm day^-1 for almond and pistachio, respectively. It is concluded that the combination of crop evapotranspiration models with remotely-sensed data is helpful for upscaling irrigation information from plant to field scale and thus may be used by farmers for making day-to-day irrigation management decisions.

In the oil palm industry, stands age is an important parameter to monitor the sustainability of cultivation, to develop the growth yield model, to identify the disease or stressed area, and to estimate the carbon storage capacity. This research is focused to estimate and distinguish oil palm stands age based on crown/ canopy density obtained using Forest Canopy Density (FCD) model derived from four indices as follows; Advanced Vegetation Index, Bare Soil Index, Shadow Index, and Thermal Index. FCD model employs multi temporal image analysis resulting four classes of oil palm stands age categorized as seed with FCD value of 29–56% (0 years), young with FCD value of 56–63% (1–9 years), teen with FCD value of 63–80% (10–15 years), and mature with FCD value of >80% (>15 years). Minimum canopy density value is 29% even in the zero years old indicates incomplete land clearance or the type of seed planted in the land.

Hybrid metal-halide perovskites have emerged as leading class of semiconductors for photovoltaic devices with remarkable light harvesting efficiencies. The formation of methylammonium lead iodide (CH₃NH₃PbI₃) perovskite into mesoporous titania (TiO₂) scaffold by a sequential deposition technique is known to offer better control over the perovskite morphology. The growth reactions at the mesoporous TiO₂ film depend on reactants concentration in the host matrix and the reaction activation energy. Here, we are characterizing formation of CH₃NH₃PbI₃ perovskite in mimic solar cell photoelectrodes utilizing the developed NanoPlasmonic Sensing (NPS) approach. Based on dielectric changes at the TiO₂ mesoporous film interface, the technique provides time-resolved spectral shifts of the localized surface plasmon resonance that varies widely depending on the different operating temperatures and methylammonium iodide (CH₃NH₃I) concentrations. Analytical studies included Ellipsometry, Scanning Electron Microscopy, and X-ray diffraction. The results show that perovskite conversion can be obtained at lower CH₃NH₃I concentrations if reaction activation energy is lowered. A significant finding is that the NPS response at 350 nm mesoporous TiO₂ can widely change from red shifts to blue shifts depending on extent of conversion and morphology of perovskite formed at given reaction conditions.

Passive microwave measurements have been available on satellites dating back to the 1970s on research satellites flown by the National Aeronautics and Space Administration (NASA). Since then, several other sensors have been flown to retrieve hydrological products for both operational weather applications (e.g., the Special Sensor Microwave/Imager–SSM/I; the Advanced Microwave Sounding Unit–AMSU) and climate applications (e.g., the Advanced Microwave Scanning Radiometer–AMSR; the Tropical Rainfall Measurement Mission Microwave Imager–TMI; the Global Precipitation Mission Microwave Imager–GMI). Here the focus is on measurements from the AMSU-A, AMSU-B and Microwave Humidity Sounder (MHS). These sensors have been in operation since 1998 with the launch of NOAA-15, and are also on board NOAA-16, -17, -18, -19 and the MetOp-A and -B satellites. A data set called the “Hydrological Bundle” is a Climate Data Record (CDR) that utilizes brightness temperatures from Fundamental CDRs to generate Thematic CDRs (TCDR). The TCDR’s include: Total Precipitable Water (TPW), Cloud Liquid Water (CLW), Sea-Ice concentration (SIC), Land surface temperature (LST), Land surface emissivity (LSE) for 23, 31, 50 GHz, rain rate (RR), snow cover (SC), ice water path (IWP), and snow water equivalent (SWE). The TCDR’s are shown to be in general good agreement with similar products from other sources such as the Global Precipitation Climatology Project (GPCP) and the Modern-Era Retrospective Analysis for Research and Applications (MERRA-2). Because of the careful intercalibration of the FCDR’s, little bias is found among the different TCDR’s produced from individual NOAA and MetOp satellites, except for normal diurnal cycle differences.

Many remote sensing analytical data products are most useful when they are in an appropriate regional or national projection, rather than globally based projections like Universal Transverse Mercator (UTM) or geographic coordinates, i.e., latitude and longitude. Furthermore, leaving data in the global systems can create problems, either due to misprojection of imagery because of UTM zone boundaries, or because said projections are not optimised for local use. We developed the open-source Irish Earth Observation (IEO) Python module to maintain a local remote sensing data library for Ireland. This pure Python module, in conjunction with the IEOtools Python scripts, utilises the Geospatial Data Abstraction Library (GDAL) for its geoprocessing functionality. At present, the module supports only Landsat TM/ETM+/OLI/TIRS data that have been corrected to surface reflectance using the USGS/ESPA LEDAPS/ LaSRC Collection 1 architecture. This module and the IEOtools catalogue available Landsat data from the USGS/EROS archive, and includes functions for the importation of imagery into a defined local projection and calculation of cloud-free vegetation indices. While this module is distributed with default values and data for Ireland, it can be adapted for other regions with simple modifications to the configuration files and geospatial data sets.

In winter 2008-2009, Lake Occhito, a strategic multiple-uses reservoir in South Italy, was affected by an extraordinary Planktothrix rubescens bloom. P. rubescens is a filamentous potentially toxic cyanobacterium which has recently colonized many environments in Europe. A number of studies is currently available on the use of remote sensing techniques to monitor different fresh water cyanobacteria species. By contrast no specific applications are available on the remote sensing monitoring of P. rubescens. In this paper we present a specific algorithm, based on Water Leaving Reflectances (WLR) from MERIS data, atmospherically corrected using the Aerosol Optical Thickness (AOT) retrieved by MODIS data, to detect P. rubescens blooms. The high accuracy in AOT data, provided by MOD09 surface reflectance product, at 1km spatial resolution, allowed obtaining a good correlation between the WLR and the P. rubescens chlorophyll-a concentrations measured in the field, through multiple stations fluorometric profiles. A modified Normalized Difference Chlorophyll index (NDCI) algorithm is presented. The performance of the proposed algorithm has been successfully compared with other specific algorithms for turbid productive waters. We demonstrated how important is to verify the spectral behaviour of bio-optical parameters in order to develop an ad hoc algorithm that better performs with respect to standard algorithms.

For applications in sensing and cavity-based quantum computing and metrology, open-access Fabry-Perot cavities – with an air or vacuum gap between a pair of high reflectance mirrors – offer important advantages compared to other types of microcavities. For example, they are inherently tunable using MEMS-based actuation strategies, and they enable atomic emitters or target analytes to be located at high field regions of the optical mode. Integration of curved-mirror Fabry-Perot cavities on chips containing electronic, optoelectronic, and optomechanical elements is a topic of emerging importance. Micro-fabrication techniques can be used to create mirrors with small radius-of-curvature, which is a prerequisite for cavities to support stable, small-volume modes. We review recent progress towards chip-based implementation of such cavities, and highlight their potential to address applications in sensing and cavity quantum electrodynamics.

Carbon nanotube (CNT) yarns are fiber-like materials that exhibit excellent mechanical, electrical and thermal properties. More importantly, they exhibit a piezoresistive response that can be tapped for sensing purposes. The objective of this study is to determine experimentally the piezoresistive response of CNT yarns that are embedded in a polymeric medium while subjected to either compression or tension, and compare it with that of the free or unconstrained CNT yarns. The rationale for this study is the need to know the response of the CNT yarn while in a medium, which provides a lateral constraint to the CNT yarn thus mimicking the response of integrated CNT yarn sensors. The experimental program will include the fabrication of samples and their electromechanical characterization. The CNT yarns are integrated in polymeric beams and subjected to four-point bending, allowing the determination of their response under tension and compression. The electrical resistance data from an Inductance-Capacitance-Resistance (LCR) device is used with the data acquired from the mechanical testing system to determine the piezoresistive response of the CNT yarns. This data and information will be used for future modeling efforts and to study the phenomena that occur when CNT yarns are integrated in polymeric and composite materials and structures.

A hydrophilic silica-based stationary phase with surface bound N-acetylglucosamine (GlcNAc-silica) was prepared in house and characterized physically via Fourier transform infrared (FTIR) and thermogravimetric analysis (TGA) and chromatographically over a wide range of mobile phase compositions. While both FTIR and TGA confirmed the attachment of the GlcNAc ligands to the silica surface, the chromatographic evaluation of the GlcNAc-silica with polar and slightly polar standard solutes (e.g., sugars, nucleic acid fragments, phenolic and benzoic acid derivatives) yielded the typical hydrophilic interaction liquid chromatography (HILIC) behaviors in the sense that retention increased with increased solute’s polarity and the organic content (i.e., acetonitrile) of the hydro-organic mobile phase (i.e., ACN-rich mobile phase). Sugars derivatized with 1-naphthylamine (1-NA) and 2-aminoanthrcene (2-AA) such as xylose, glucose and short chains maltooligosaccharides constituted the most polar species for HILIC retention evaluation, and in addition the maltooligosaccharides offered a polar homologous series for gauging the hydrophilicity of the GlcNAc-silica in analogy with alkylbenzene homologous series and other nonpolar homologous for evaluating the hydrophobicity of non-polar stationary phases. On the other hand, the benzoic acid and phenolic acid derivatives were the probe solutes for evaluating the HILIC retention dependence of ionizable solutes on the pH of the mobile phase. Similarly, the nucleobase and nucleoside weak basic solutes as well as some typical cyclic nucleotide acidic solutes allowed the examination of the dependence of solute retention on the pH of the mobile as well as the polarity of the species.

Due to the low content, few studies are focused on the essential oils (EOs) of Phlomoides rotata (Benth. ex Hook. f.) Mathiesen (syn. Lamiophlomis rotata (Benth.) Kudô. This plant has been used to treat rheumatic arthritis and grasserie in China. However, such EOs may have important pharmacological activities such as anti-cancer. To identify the chemical markers (CM) in the EOs and evaluate their antioxidant activities (AAs), we firstly conduct a thoroughly investigation on their chemicals and AAs, to the best of our knowledge. Light yellow EOs with fresh and elegant smell are obtained by hydro-distillation with average yield 0.11% (volume mL/weight g). The crystals are separated from the EOs through cryoprecipitation, respectively. A total of 81 components are qualified and quantified in the EOs, crystals and EOs removed crystals, in which 44 ones are first reported. As for content, the main compounds are long-chain fatty acids (FAs) and their esters. The most abundant one n-hexadecanoic acid (palmitic acid, PA) accounting for 43.15-54.8%, 58.49-64.57% and 15.9-41.1%, in the EOs, crystals and EOs removed crystals, respectively. Seven compounds including PA, tetradecanoic acid, linoleic acid, oleic acid, methyl hexadecanoate, hexahydrofarnesyl acetone and phytol can be chosen a the CMs in these EOs. The AAs are evaluated through in vitro assays. PA presents pro-oxidant activities in a concentration dependence manner. Usually, the EOs removed crystals demonstrate stronger AAs, and the crystals demonstrate weaker AAs compared with that of the corresponding EOs, which is related to the different content of PA in these samples. This study can give some hints for the utilization of such EOs which are abundant in FAs such as PA.

Some cancer cells rely heavily on non-essential biomolecules for survival, growth, and proliferation. Enzyme based therapeutics can eliminate these biomolecules, thus specifically targeting neoplastic cells; however, enzyme therapeutics are susceptible to immune clearance, exhibit short half-lives, and require frequent administration. Encapsulation of therapeutic cargo within biocompatible and biodegradable poly(lactic-co-glycolic acid) nanoparticles (PLGA NPs) is a strategy for controlled release. Unfortunately, PLGA NPs exhibit burst release of cargo shortly after delivery or upon introduction to aqueous environments where they decompose via hydrolysis. Here we show the generation of hybrid silica-coated PLGA (SiLGA) NPs as viable drug delivery vehicles exhibiting sub-200 nm diameters, a metastable Zeta potential, and high loading efficiency and content. Compared to uncoated PLGA NPs, SiLGA NPs offer greater retention of enzymatic activity and slow the burst release of cargo. Thus, SiLGA encapsulation of therapeutic enzymes, such as asparaginase, could reduce frequency of administration, increase half-life, and improve efficacy for patients with a range of diseases.

Marine sponges, a well documented prolific source of natural products, harbors numerous microbial communities believed to possess N-acyl homoserine lactones (AHLs) mediated Quorum sensing (QS) as one of the mechanisms of interaction. Bacteria and eukaryotic organisms are known to produce molecules that can interfere with QS signaling, thus affecting microbial genetic regulation and function. In the present study, we established the potential for production of both QS signal molecules as well as QS interfering molecules (QSI) in the same sponge species Sarcotragus spinosulus. A total of eighteen saturated acyl chain AHLs were identified along with six putative unsaturated acyl chain AHLs. Bioassay guided purification led to the isolation of two brominated metabolites with QS-interfering activity. The structures of these compounds were elucidated by comparative spectral analysis of 1HNMR and HR-MS data and was identified as 3-Br-N-methyltyramine (1) and 5,6-dibromo-N,N-dimethyltryptamine (2). The QSI activity of compounds 1 and 2 were evaluated using reporter gene assays for long- and short-chain signals (E. coli pSB1075 and E. coli pSB401) and was confirmed by measuring dose dependent inhibition of proteolytic activity and pyocyanin production in P. aeruginosa PAO1. The obtained results showed the co-existence of QS and QSI in S. spinosulus, a complex network which may mediate the orchestrated function of the microbiome within the sponge holobiont.

This study was performed to evaluate the efficacy of nicotinic acid against Streptococcus pneumoniae biofilm. The experimental results indicate that S. pneumoniae forms biofilms, particularly at the liquid-air interface, as evidenced by the pellicle assay. Nicotinic acid demonstrated significant inhibition of S. pneumoniae biofilm formation at 6 h and 18 h, with higher concentrations leading to lower biofilm biomass, suggesting a concentration-dependent response. However, minimal biofilm inhibition was observed at 12 h. Treatment with nicotinic acid induced FTIR spectral changes in protein biomolecules of S. pneumoniae biofilm at 6 h and 18 h, evidenced by alterations in spectral peaks at 750 cm-1, 906 cm-1, 1540 cm-1, 1548 cm-1, and 1644 cm-1. Notably, no FTIR spectral changes were detected in 12 h S. pneumoniae biofilm following exposure to nicotinic acid. These findings suggest that nicotinic acid inhibits biofilm formation in a time and concentration-dependent manner, possibly by altering the structure of protein biomolecules within the biofilm.

The occurrence and ability of Salmonella typhimurium to withstand the effects of various antibiotics has been extensively recorded. This highlights the necessity for alternative methods to combat Salmonella infections. The current investigation aimed to ascertain the impact of benzoic acid on the extent of surface coverage and biomass of S. typhimurium biofilm after 48 and 72 hours. The findings indicated that all the different doses of benzoic acid (ranging from 3.125% to 50%) resulted in a decrease in the extent of biofilm surface coverage. Benzoic acid exhibited a substantial inhibitory effect on the biofilm biomass at all concentrations. Higher concentrations of benzoic acid led to a decrease in biofilm biomass, suggesting a concentration-dependent response. This finding implies that benzoic acid is effective in managing Salmonella infections.

Elevated serum uric acid (sUA) is associated with risk of developing cardiovascular disease (CVD). Here, we examined the prognostic significance of sUA and exercise capacity in 411 Japanese adults (age, ≥65; mean, 81 years) hospitalized for worsening CVD. Mean sUA was significantly higher in the 23% of patients on an sUA-lowering agent than in those not. When the patients were stratified by sUA into three groups (7.0 mg/dL), the high sUA group had significantly worse peak VO2 and composite endpoint (rehospitalization due to worsening CVD and all-cause mortality) compared with low and moderate sUA groups (P < 0.001). When the patients were stratified by sUA into five groups (sUA 10.0 mg/dL), the incidence of the composite endpoint was significantly higher in the highest sUA group compared with that in the reference group, but only in women. Univariate Cox regression analysis, but not a multivariate analysis, indicated that sUA was significantly associated with the composite endpoint. Although sUA and exercise capacity may have some degree of prognostic significance in older patients with CVD, this significance may differ between men and women.

Primary biliary cholangitis (PBC) is a cholestatic liver disease characterized by immune-mediated injury to small bile ducts. Although PBC is an autoimmune disease, the results of traditional immunosuppressive therapy are disappointing. Nearly 40% of PBC patients do not respond to the first-line drug UDCA. Without appropriate intervention, PBC patients would eventually progress to liver cirrhosis and even death. There is an urgent need to develop new therapies. The gut-liver axis emphasizes the interconnection between the gut and the liver, and there is increasing evidence that gut microbiota and bile acids play an important role in cholestatic diseases. Dysbiosis of gut microbiota, imbalance of bile acids, and immune-mediated bile duct injury constitute the triad of pathophysiology in PBC. Understanding the gut microbiota-bile acid network and corresponding immune functions in PBC provides a new perspective for its treatment strategies. Therefore, we summarize the latest advancements in research of gut microbiota and bile acids in PBC and, for the first time, explore the potential of immune factors related to them as novel immunotherapy targets. This article discusses potential therapeutic approaches focusing on regulating gut microbiota, maintaining bile acid homeostasis, their interactions, and related immune factors.

Pain is unpleasant sensory and emotional experience accompanied by tissue injury. Often an indi-vidual experience, it can be influenced by different physiological, psychological, and social factors. Fibromyalgia, one of the most difficult-to-treat types of pain, is characterized by general muscle pain accompanied by obesity, fatigue, sleep, and memory and psychological concerns. Fibromyal-gia has increased nociceptive sensations via central sensitization in the brain and spinal cord level. We used intermittent cold stress to create a mouse fibromyalgia pain model (Day 0: 3.69  0.14 g; Day 5: 2.13  0.12 g). Mechanical pain could be reversed by eicosapentaenoic acid (EPA) admin-istration (Day 0: 3.72  0.14 g; Day 5: 3.69  0.13 g). A similar trend could be also observed for thermal hyperalgesia. The levels of elements in the transient receptor potential V1 (TRPV1) sig-naling pathway were increased in the ascending pain pathway, including the thalamus, medial prefrontal cortex, somatosensory cortex, anterior cingulate cortex, and cerebellum. EPA intake significantly attenuated this overexpression. Novel chemogenetics method was used to indeed in-hibit SSC to ACC activity presented an analgesic effect through TRPV1 downstream pathway. The present results provide insights as to the role of TRPV1 signaling pathway as in fibromyalgia and its potential as a clinical target.

This study deals with the preparation of adsorbents from a commercial xerogel by chemically modifying its surface with concentrated mineral acids and alkali metal chlorides, their physicochemical characterization, and their use as adsorbents for gallic acid in aqueous solution. The prepared adsorbents have a high specific surface area (347-563 m2 g-1), better pore development for samples treated with alkali metal chlorides than with mineral acids and are more acidic than the initial xerogel (p.z.c range 2.49-6.87 vs. 7.20). The adsorption properties of the commercial xerogel improved over a wide range of pH and temperature. The experimental results indicate that the adsorption process is thermodynamically favored.

Peas are among the most widely consumed legumes and are of great benefit for human nutrition. Sowing and cultivation techniques are known to affect the yield and the quality of the seeds. Existing studies investigating the nutritional properties of the seeds from plants cultivated using different methods are continue to be of significant value. However, changes in the climate in recent years are presumed to have affected the optimum sowing dates for grain yield and quality. This study in-vestigates the effects of sowing peas at different sowing dates on the yield of the seed and on its nutrient content, as determined by certain quality traits (parameters). The experiment was con-ducted at the Aydin Adnan Menderes University Faculty of Agriculture in Turkey during the 2021-2022 and 2022-2023 pea production seasons. Specifically, it examined the yield of the seed (fresh/dry), its saponin and phenolic matter content and its amino acid composition in the case of five pea cultivars (Deren, Misya, Irmak, Karina, Local) sown at three different sowing times (November 15, November 30, December 15). The study found that the effects of sowing date on grain yield and quality characteristics were significant. However, the varieties' reactions to sowing dates were found to be different. The highest fresh seed yield (3.27 t ha-1) was obtained from samples sown at the second sowing date, while the highest dry yield (1.85 t ha-1) came from samples sown at the third sowing date. The cultivars also had a statistically significant effect on the yields. The highest fresh seed yields were obtained from the Misya (2.88 t ha-1) and Local (2.81 t ha-1) varieties, while the highest dry yields were obtained from samples of Local (1.76 t ha-1) and Irmak (1.73 t ha-1). In terms of sowing dates, the highest protein (27.75%) was obtained from the first sowing date, and the protein content decreased in the following dates. Misya was the cultivar from which the highest protein content (28.77%) was obtained. In the study, higher yields were obtained from the second and third sowing dates, while the first sowing time resulted in higher protein and amino acid composition. Similar to the protein content, the composition of almost all amino acids increased on the first sowing date. In addition, it was established that the saponin and phenolic substance contents of seeds varied with the sowing date.

Introduction: We under took an in-use evaluation of a novel hypochlorous acid-based hand hygiene product with in vitro sporicidal efficacy in a NHS Older Persons inpatient ward setting. Methods: The novel hand hygiene product was implemented for a trial period of seven weeks commending in September 2023. Healthcare worker (HCW) hands were sampled before and after direct patient care, and after the application of either an alcohol-based handrub (ABHR) (n=50) or the novel product (n=50). Samples were cultured to quantify the total aerobic count (TAC) and presence or absence of MRSA, ESBLs, CREs, and C. difficile. Trends in weekly observational hand hygiene audit results were reviewed, and a survey of HCW views about the new product undertaken. Results: HCW hands had a significantly greater TAC after ABHR (p=0.01) but not after the novel product (p=0.11) compared with their respective baseline counts. 3% of 100 samples grew MRSA or ESBLs after application of the alcohol-based or novel hand hygiene products. No C. difficile was cultured from healthcare worker hands. There was no significant difference in observed hand hygiene compliance. The majority of HCW surveyed preferred the novel product to the alcohol-based hand hygiene product. Discussion: The novel hand hygiene product was more effective than ABHR at reducing the TAC on HCW hands. Poor hand hygiene technique may explain the identification of antibiotic-resistant bacteria on staff hands after ABHR or the novel product. We were not able to evaluate sporicidal efficacy since no C. difficile was cultured from hands.

Brassinosteroids (BR) are key phytohormones involved in the regulation of major processes of cell metabolism guiding plant growth. In the past decades, new evidence made it clear that BRs also play a key role in the orchestration of plant responses to many abiotic and biotic stresses. In the present work we analyzed the impact of foliar treatment with 24-epicastasterone (ECS) on the endogenous content of major phytohormones (auxins, salicylic acid, jasmonic acid, abscisic acid) and their intermediates in soybean leaves 7 days following the treatment. Changes in the endogenous content of phytohormones have been identified and quantified by LC/MS. Obtained results point to a clear role of ECS in the upregulation of auxin content (indole-3-acetic acid, IAA) and downregulation of salicylic, jasmonic, and abscisic acid levels. These data confirm that under optimal conditions ECS in tested concentrations of 0,25 µM and 1 µM might promote growth in soybean by inducing auxin contents. Benzoic acid (a precursor of salicylic acid (SA)), but not SA itself, has also been highly accumulated under ECS treatment which indicates an activation of the adaption strategies of cell metabolism to possible environmental challenges.

Fermented rice is known as a healthy food due to the presence of lactic acid bacteria as fermentative microorganisms. The study was carried out to discover and characterize the lactic acid bacteria (LAB) from white and red fermented rice (BG varieties). Fermentation was carried out naturally by soaking red, white, raw and cooked rice in water using an earthen pot. Species were confirmed based on 16S r DNA gene sequencing and studied for phenotypic characteristics including morphological, physiological (growth temperature, salt tolerance, milk coagulation) and biochemical characteristics (carbohydrate fermentation pattern) using API 50CH kits. Distinct clusters like cocci (48), diplo cocci (30) and rods (30) shaped bacteria were observed from fermented rice. Five species of lactic acid bacteria including Latilactobacillus curvatus GR Lb1,2 10 and 11 (predominant Bacillus species), Latilactobacillus graminis Lb8, Limosilactobacillus fermentum GRLb17, Weissella confuse GRLb4 and Pediococcus pentosaceus GRLc1 were identified. The base pair length of amplified DNA for the isolates was 1500 Bp. The beneficial physiological and biochemical properties of isolated Lactobacillus species from fermented rice revealed their potential applications in the food industry.

In this study, composite nanofiber films comprising polyvinyl alcohol, wheat gluten, and glucose (PWG) were fabricated using electrospinning, followed by cross-linking via the Maillard cross-linking. Various mass concentrations of ferulic acid (FA) were incorporated into the PWG films. The results indicate that the average diameter of the FA-PWG films decreased from 449 nm to 331 nm as the concentration of FA increased, until reaching a concentration of 12%, after which a significant increase in diameter was observed. Subsequent Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and differential scanning calorimetry (DSC) results suggested that FA was distributed in the sample films in an amorphous form through hydrogen and ester bonds. Additionally, release experiments and antimicrobial tests on FA-PWG sample films showed good con-trolled release of FA and excellent anti-Escherichia coli and Staphylococcus aureus activity of this film. These findings all indicate that the FA-PWG nanofiber film is a potential candidate for food active packaging.

With the objective of studying the influence of elicitors on growth, yield and quality of kalmegh we carried out an investigation for two consecutive years. Nine treatments with three replications were laid out in CRD design. Chitosan, Yeast extract, Jasmonic acid and Salicylic acid were evaluated at different concentrations. CHT 1000 ppm exhibited highest plant height (73.91 cm) and secondary branches (29.07) at the time of harvest. Primary branches and number of leaves per plant were highest in CHT 1000 ppm (26.36; 88.32) which were on par with SA 200 ppm (26.28; 81.51). Plant spread was highest in SA 200 ppm (35.46 cm2) which was on par with CHT 1000 ppm (35.11 cm2). CHT and SA sprays were recorded with on par results for yield parameters but highest fresh (42.34 g) and dry (18.30) herbage yield per plant were exhibited with SA 200 ppm. Highest total chlorophyll (4.459 mg g-1) and total andrographolides (3.494%) content were recorded in SA 200 ppm spray. Significant and positive improvement in growth, yield and quality of kalmegh was noticed with Salicylic acid spray @ 200 ppm at 30 and 60 DAS signifying its use in cultivation of kalmegh for high productivity, quality and better returns for farmers.

Pharmaceuticals including antibiotics are among hazardous micropollutants (HMP) of the environment. Incomplete degradation of the HMP leads to their persistence in water bodies causing a plethora of deleterious effects. Conventional wastewater treatment cannot remove HMP completely, and a promising alternative is comprised by biotechnologies based on microalgae. The use of immobilized microalgae in environmental biotechnology is advantageous since immobilized cultures allow recycling of the microalgal cells, support higher cell densities, and boost tolerance of microalgae to stresses including HMP. Here we report on a comparative study of HMP (exemplified by the antibiotic ceftriaxone) removal by suspended and chitosan-immobilized cells of Lobosphaera sp. IPPAS C-2047 unialgal culture. We also monitored the dynamics of photosynthetic pigments content and the physiological condition of the cells as reflected by the activity of their photosynthetic apparatus. Special attention was paid to the changes in the accumulation of valuable arachidonic acid (C20:4). In addition to this, we followed the changes in the culture microbiome induced the antibiotic exposure. Collectively, our results showed that both suspended and immobilized cultures took up ceftriaxone from the culture medium. In the case of immobilized culture, a significant amount of the antibiotic was adsorbed on the chitosan carrier itself. The dynamics of the taxonomic composition of the microbiome of the microalgae was more shifted by the immobilization on the chitosan than by exposure to 20 mg/L of ceftriaxone. The possibility and limitations of the using of chitosan-immobilized Lobosphaera sp. IPPAS C-2047 for HMP removal coupled with the production of valuable long-chain polyunsaturated fatty acids is discussed.

Cancer is a catchall term that refers to a collection of more than one chronic disease that can adversely affect the body, including the organs of the body. These diseases can be grouped together under the umbrella term "cancer." Cancer is a catch-all term that is used to refer to a number of different diseases. During the process of looking for new chemical entities, it was found that certain compounds with a basic nucleus of benzoic acid (BA) exhibit a remarkable anticancer potential. This was discovered while the researchers were looking for new chemical entities. In the sixteenth century, the aromatic chemical known as BA, which is also known as an aromatic carboxylic acid, was discovered. BA is also referred to as an aromatic carboxylic acid. When it comes to the chemical synthesis of a wide range of different active molecules, the utilization of a sizeable quantity of BA as a raw material is absolutely necessary. In addition to being present in a variety of other naturally occurring compounds, the BA moiety is the component that is responsible for the activity of the naturally occurring compounds vanillin, gallic acid, and syringic acid. In the synthesis of a wide variety of synthetic bioactive molecules, the BA scaffold is utilized as a building block. The drugs furosemide, bumetanide, benzocaine, tetracaine, and bexarotene are all examples of molecules that fall into this category. The scope of this review article allows for the discussion of a number of noteworthy and recent achievements of BA derivatives in terms of their effectiveness against cancer.

Over the years, chitosan has been the subject of numerous studies and has gained significant popularity as a biomaterial due to its various characteristics, including biocompatibility, biodegradability, and bioactivity. In this work, chitosan fibres surface was modified with ursolic acid to improve their antibacterial properties by wet impregnation method. Five specimens of chitosan fibres were immersed in ursolic acid (UA) solution for varying immersion times of 1, 2, 4, 6, and 8 hours. Characterization was carried out by means of FTIR, SEM, UV-Vis spectroscopy; the results indicated an ongoing chemical reaction between chitosan and ursolic acid resulting in changes to the chemical structure. After 2 hours, the absorbance ratio remained constant; suggesting that the reaction had reached completion and the chemical structure of the sample remained stable. Antibacterial tests were performed on the resulting chitosan fibres against two bacterial strains. The fibres without ursolic acid did not exhibit any noteworthy antibacterial activity against either strain. However, the chitosan fibres modified with ursolic acid showed significant and almost strong antibacterial activity against the Gram-positive strain, S. aureus. These results suggest that chitosan fibres modified with ursolic acid could have potential applications as antibacterial materials, particularly against Gram-positive bacteria.

Gamma-aminobutyric acid (GABA), a non-protein-producing amino acid, is extensively found in microorganisms, plants and vertebrates, and is abundantly expressed in the spinal cord and brain. To date, GABA is considered to be the major inhibitory neurotransmitter in the central nervous system. Its physiological effects are related to the regulation of synaptic transmission, the promotion of neuronal development and relaxation, and the prevention of insomnia and depres-sion. Mediated through its specific receptors, it plays a pivotal role in the control of neuronal ex-citability, which can serve as anovel target for developing analgesics for pain management. This review provides an update on the accumulating evidence of specific GABA receptors and their subtypes in the involvement of pain analgesia.

Desmin is a class III intermediate filament highly expressed in cardiac, smooth and striated muscle Autosomal dominant or recessive mutations in the desmin gene (DES) result in a variety of diseases, including cardiomyopathies and myofibrillar myopathy, collectively called desminopathies. Here we describe the clinical, histological and radiological features of a Greek patient with a myofibrillar myopathy and cardiomyopathy linked to the c.734A>G,p.(Glu245Gly) heterozygous variant in the DES gene. Moreover, through ribonucleic acid sequencing analysis in skeletal muscle we show that this variant provokes a defect in exon 3 splicing and thus should be considered clearly pathogenic

Objectives: One of the home-made herbal remedy being traditionally used against gout is evaluated to identify any new and characteristic marker compound which may be used as characteristic analytical marker to standardize this polyherbal remedy. Materials and method: A distinct and remarkable peak in the HPLC chromatogram of remedy was identified which was further isolated by fraction collector. This fraction was then evaporated and characterized for structure elucidation using set of various techniques such as RP-HPLC,UV, FTIR, TLC, EIMS and NMR. Results: The compound characterized was non polar compound, ester of betulin and palmitoleic acid. Although the remedy has been standardized using set of four markers as discussed in literature but this newly developed marker compound can be used to further standardize this remedy and other herbal preparations comprising of this marker compound.Conclusion: Hence the isolated compound can be used as novel analytical marker in the standardization of this herbal remedy and the other herbal preparations containing such marker compound

Cisplatin (CDDP) is widely used to treat several types of cancer. However, CDDP induces nephrotoxicity. This toxicity could be avoided, applying a lower cisplatin dose; however, it could induce a lesser therapeutic activity. In this paper, we present the cytotoxic activity against prostate human cancer cell line (PC-3) of the combination of CDDP with masticadienonic acid (MDA), a triterpene isolated from Amphypterygium adstringens.The combinations A (half of the IC₅₀), B (IC₅₀) and C (twice IC₅₀ of the compounds) in a radio 1:1 were evaluated. Our results showed that the B and C combinations presented synergism effect. However, B combination showed almost 100% inhibition of cell proliferative activity and increased apoptosis compared with those presented by each compound apart. A pretreatment of MDA 24 h to cells before the CDDP, AMD or B combination administration result in a resistance to the treatments. A xenograft study using PC-3 cells showed that the combination of 47.5 mM/kg (AMD) plus 4 mM/kg (CDDP) administered weekly for 3 weeks reducing the tumor volume in approximately 47 %. However, the combination of 47.5 mg/kg (AMD) plus 2 mg/kg (CDDP) administered every third day for 21 days reduce, approximately 82% of tumor compared with mice no treated.

Klebsiella pneumonia (K. pneumoniae) is a Gram-negative bacterium that causes nosocomial infections in the lung, bloodstream, and urinary tract. Therefore, detecting K. pneumoniae in early time is important in preventing severe infections. However, clinical detection of K. pneumoniae requires a long time of agar plate culture. Nucleic acid detection like qPCR is precise but requires expensive equipment. Recent research reveals that collateral cleavage activity of CRISPR-LbCas12a has been applied in nucleic acid detection. In this study, PCR combined with CRISPR-LbCas12a targeting the K. pneumoniae system was established. This system showed excellent detection specificity and sensitivity in both bench work and clinical samples. Due to its advantages, its application can meet different detection requirements in health centers where qPCR is not accessible.

Surface activity of humic acid (HA) and its six sub-fractions isolated from forest soil were characterized by surface tension measurements, dynamic light scattering, and laser doppler electrophoresis. The surface tension of HA sub-fractions decreased from 72.4 mN·m-1 to 36.8 mN·m-1 with the increasing concentration from 0 to 20000 mg·L-1. The critical micelle concentration (CMC) of HA and its sub-fractions ranged from 216 to 1024 mg·L-1 with the multiple linear regression equation of CMC = 18896–6.9×C–296×alkyl-C–331×aromatic-C–17019×H/C+4054×HB/HI (p &lt; 0.05). The Z-average particle size ranges from 108.2 nm to 186.9 nm. The maximum particle size was 5000 nm after filtered with a membrane of 0.45 μm, indicating HA and its sub-fractions progressed self-assembly during 2000 mg·L-1, pH = 6.86. The number-base particle size distribution of HA sub-fractions was identified as four peaks by Gaussian model, and the aggregate sizes were mainly in six clusters including 2 ± 1 nm, 5 ± 2 nm, 10 ± 3 nm, 21 ± 8 nm, 40 ± 10 nm, and &gt; 50 nm indicating multiple aggregations of different particle sizes in the HA fractions solution.

Keywords: lactic acid; ceramide; folate; nicotinamide; Alzheimer’s disease

The experiments were designed to know the function of ascorbic acid against salinity on germination, different biochemical and micronutrients concentrations of Solanum melongena. Ascorbic acid was applied as foliar spray on leaves and given in roots through irrigation at 100 and 200 ppm to the plants growed in non saline, 60mM and 100mM salt stress conditions. Different biochemical parameters i.e. chlorophyll, carotenoids, carbohydratrates, protein and micro nutrients concentrations of Solanum melongena were observed under different salt stress concentrations from control (non-saline), 60mM NaCl and 100mM NaCl solutions. The rates of different biochemical parameters and micro nutrients concentrations exhibited decrease in saline media in comparison with their respective control while ascorbic acid used as a foliar spray and through irrigation in roots at the concentration of 100 ppm and 200 ppm resulted promotion in non saline control as compared with salt concentrations media. It was determined that chlorophyll concentration was decreased considerably under salt stress. Amongst micro nutrients ionic composition of Na, K and Na/K ratio resulted that plants treated with different NaCl concentrations at 60mM NaCl and 100mM salt concentrations showed increase in Na and K ions and ascorbic acid were used as a foliar spray and in roots showed decrease in Na and K ions. Overall from the outcomes of the study it was observed that salinity stress significantly decrease vegetative and reproductive parameters that could be improved with the using of ascorbic acid. Best concentration found were 200 ppm ascorbic acid contributed towards an increase in growth irrespective of non-saline and saline conditions. Based on these findings, ascorbic acid treatment helps in alleviating the negative effects of salinity.

Catalytic hydrogenation of a biomass-derived molecule, levulinic acid (LA) to γ-valerolactone (GVL) has been getting a lot of attention from researchers across the globe recently. This is because GVL has been identified as one of the potential molecules for the replacement of fossil fuels. For instance, GVL can be catalytically converted into liquid alkenes in the molecular weight range close to that found in transportation fuels via a process that does not require an external hydrogen source. Noble and non-noble metals have been used as catalysts for the selective hydrogenation of LA to GVL. Of these, Ru has been reported to be the most active metal for this reaction. The type of metal supports and solvents has been proved to affect the activity, selectivity, and yields of GVL. Water has been identified as a potential, effective “green” solvent for the hydrogenation of LA to GVL. The use of different sources of H2 other than molecular hydrogen (such as formic acid) has also been explored. In a few instances, the product, GVL, is hydrogenated further to other useful products such as 1,4-pentanediol (PD) and methyl tetrahydrofuran (MTHF). This review selectively focuses on the potential of immobilized Ru catalysts as a potential superior catalyst for selective hydrogenation of LA to GVL.

Fructose in beverages has adverse effects on lipids, glucose and insulin sensitivity after acute and chronic ingestion. There is limited data showing that chronic consumption of fructose in solid foods has harmful effects. We hypothesized that a moderate amount of fructose compared with sucrose in solid food consumed for a month would not adversely influence fasting or postprandial lipids and glucose after an acute fat and carbohydrate load. Twenty-five men and women with prediabetes and/or obesity and overweight consumed in random order two acute test meals of muffins sweetened with either fructose or sucrose, followed by 4-week chronic consumption of 42g/day of either fructose or sucrose in low fat muffins after which the 2 meal tests were repeated. Subjects were randomised to sugar type in the chronic feeding period. Sugar type had no effect on the incremental area under the curve for triglyceride or uric acid at either time point (P=0.4 and P=0.9). There was no overall difference between meal tests at baseline and after 1 month and no effect of consuming sucrose or fructose muffins for 1 month. Fasting triglyceride increased after chronic consumption of fructose by 0.31±0.37 mmol/L compared with sucrose in people with IFG/IGT only (P=0.004). Fructose at a moderate intake of <10% of energy in solid food has no different effects on postprandial triglyceride and uric acid compared with sucrose although fasting triglyceride was increased in people with IFG/IGT after 1 month of fructose muffins suggesting the need for caution.

Osteoarthritis (OA) is a disease that currently has no cure. There are numerous studies showing that carnosine and hyaluronic acid (HA) have a positive pharmacological action during joint inflammation. For this reason, the goal of this research was to discover the protective effect of a new HA+Carnosine formulation (FidHycarn) on the inflammatory response and on the cartilage degradation in in vivo experimental model of OA. This model was induced by a single intra-articular (i.ar.) injection of 25µl normal saline having 1mg of monosodium iodoacetate solution (MIA) in the knee joint. MIA injection caused histological alterations and degradation of cartilage as well as behavioral changes. Oral treatment with FidHycarn ameliorated the macroscopic signs, improved thermal hyperalgesia and weight distribution of hind paw as well as decreased histological and radiographic alterations. The oxidative damage was analyzed by evaluating the levels of nitrotyrosine and inducible nitric oxide synthase (iNOS) that were significantly reduced in FidHycarn rats. Moreover, the levels of pro-inflammatory cytokines and chemokines were also significantly reduced by FidHycarn. However, interestingly, in more cases, the effects of FidHycarn were not statistically different to Naproxen used as positive control. Thus, the new formulation containing Carnosine and HA could represent an interesting therapeutic strategy to combat osteoarthritis.

Objective: Rheumatoid Arthritis (RA) is a chronic inflammatory disease affecting the synovium and articular cartilage that initiates joint damage. RA associates with a change in many inflammatory biomarkers. The present study aims to measure the levels of inflammatory adipocytokines (chemerin and visfatin) and their ratio in addition to some related biomarkers in RA patients group in comparison to healthy control group and find out their efficacy in diagnosis of RA.Methods: The study included 60 RA patients and 30 healthy control group. Serum visfatin and chemerin were measured by using ELISA technique, while other biomarkers were determined spectrophotometrically. Multivariate general linear model analysis and Receiver operating curve was used to study the opportunity of using chemerin and visfatin as diagnostic tools for RA.Results: The results indicated that there was a significant increase (p<0.05) in all lipid profile components, except HDLc that decreased, in RA patients in comparison with healthy control group; while significant decrease (p<0.001) in high density lipoprotein-cholesterol of RA patients in comparison with control group. Serum chemerin, visfatin, C-reactive protein, and uric acid levels were significantly higher (p<0.05) in RA patients than those of control group. The results showed a relatively good sensitivity and specificity of chemerin (sensitivity=88.1, specificity=75.9) at a concentration=187.88ng in diagnosis of RA.Conclusions: chemerin is able to diagnose RA efficiently but this diagnoses, due to relatively small specificity, may interfere with other inflammatory disorders. However, with adjuvant with other diagnostic parameters, chemerin may represent a useful addition in diagnosis of RA.

Chlorogenic acid or 5-Caffeoylquinic acid is a polyphenolic component present in coffee and its by-products. Chlorogenic acid has been shown to exert biological properties, particularly in relation to glucose and lipid metabolism, including antibacterial, antioxidant, anti-inflammatory activities, among others. Due to its importance, it is necessary to evaluate the reliability of the analytical method for its determination in complex matrices such as food. In this work, different methods of chlorogenic acid extraction in coffee Silverskin were studied, as well as its quantification by HPLC. The results showed that the method of extraction with a mixture of methanol:water (3:1 v/v) in an ultrasonic bath, favored the recovery of chlorogenic acid with a recovery of 77.44%. The instrument detection limit for chlorogenic acid was 3.311 µg/mL and the quantification limit was 11.037 µg/mL. For coffee Silverskin, the concentration obtained of chlorogenic acid by the three extraction methods evaluated was in the range of 57 to 224 mg/kg of coffee silverskin (dry basis).

This study investigated the relationship of acrosome reactions and fatty acid composition on fertility in boar sperm. The acrosome reaction of sperm was induced via methyl-beta-cyclodextrin (MBCD), and acrosome reaction, plasma membrane integrity, and fertility were analyzed. The fatty acid composition of the excess acrosome reacted sperm was determined via gas chromatography. The results showed that the acrosome reaction in sperm was induced over 85% of the time by 60 mM MBCD treatment, and the plasma membrane integrity was significantly decreased and was dependent on the MBCD level. The acrosome reacted sperm resulted in significantly higher saturated fatty acids (SFAs) and lower unsaturated fatty acids (PUFAs) than the non-acrosome reaction group. Moreover, the acrosome reacted sperm from 60 mM MBCD significantly decreased in vitro fertility and blastocyst formation relative to non-acrosome reacted sperm, and the acrosome reaction was positively correlated with SFAs and negatively correlated with PUFAs. Of these fatty acids, C22:5n-6 (docosapentaenoic acid [DPA]) and C22:6n-3 (docosahexaenoic acid [DHA]) were directly negatively correlated with the acrosome reaction (r = -0.982 and -0.947, respectively). In conclusion, the excessive acrosome reactions may occur by reducing the PUFAs, which may then dramatically decrease sperm fertility in pigs.

1-[5-(4-methylphenyl)-1,3,4-oxadiazol-2-yl]methanamine compound has been successfully synthesized by reacting p-Toluic hydrazide and glycine via polyphosphoric acid condensation route. The course of the reaction was found to be high yielding and the title compound was spectroscopically characterized by FT-IR, DSC, 13C/1H-NMR and Mass spectrometric techniques.

Poly(acrylic acid) (PAAc) hydrogels possess good bioadhesive properties and allow enhanced penetration of drugs. In addition, it is possible to localize the absorption site of the drug in the hydrogel and increase the drug residence time. As opposed to other cross-linking processes radiation-induced polymer cross-linking can be easily and rapidly carried out without the use of cross-linking agents and other chemical additives. In this study, we fabricated metronidazole (MD) containing PAAc hydrogel (MD/PAAc) with different MD contents (0.1, 0.25, 0.5 wt%) using varying radiation doses (25, 50, 75 kGy) by gamma-irradiation. The physical and thermal properties were determined by gel content analysis, swelling ratio measurements, compressive strength measurements, differential scanning calorimetery, and thermogravimetric analysis. The properties of the hydrogel degraded due to the crystalline nature of MD. The properties of the hydrogel degraded due to the crystalline nature of MD. Cumulative release observed after 50 min in the case of 0.5MD/PAAc and 0.1MD/PAAc was 50% and 10%, respectively. Our findings suggest that MD/PAAc could be a suitable drug delivery carrier for use with radiation-based techniques.

The health benefits of purple sweetpotato, which is used as an edible food in its natural state and in processed foods and as a natural color pigment, have been recognized. In Japan, sweetpotato has been economically produced in regions below 36°4′N latitude, however, cultivation areas are beginning to expand further north. The anthocyanin and polyphenolics in purple sweetpotatoes cultivated in different locations; I (42°92′ N, 143°04′ E), II (35°99′ N, 140°01′ E), and III (31°72′ N, 131°03′ E), were compared over two years. Total anthocyanin and polyphenolic contents in purple sweetpotatoes tended to be high in location I. Their contents significantly differed over the two years in locations I and III and was dependent on temperature during cultivation. The anthocyanin and polyphenolic compositions differed between locations. The peonidin/cyanidin ratios were higher in location III compared with I and II in all varieties. The relative amount of chlorogenic acid was higher in location I, while the amount of 3,4- and 4,5-dicaffeoyolquinic acids were higher in location III, suggesting that the variability of the anthocyanin and polyphenolic content and composition was dependent on cultivation conditions. This study suggested that northern areas in Japan are an alternative production area and may yield higher amounts of anthocyanin and polyphenolics.

Fumaric acid is a chemical building block with many applications, namely in the polymer industry. The fermentative production of fumaric acid from renewable feedstock is a promising and sustainable alternative to petroleum-based chemical synthesis. The use of existing industrial side-streams as raw-material within biorefineries potentially enable production costs competitive against current chemical processes, while preventing the use of refined sugars competing with food and feed uses and avoiding purposely grow crops requiring large areas of arable land. However, most industrial side streams contain a diversity of molecules that will add complexity to the purification of fumaric acid from the fermentation broth. A process for the recovery and purification of fumaric acid from complex fermentation medium containing spent sulfite liquor (SSL) as carbon source was developed and is herein described. A simple two-stage precipitation procedure involving separation unit operations, pH and temperature manipulation and polishing through the removal of contaminants with activated carbon allowed the recovery of fumaric acid with 68.3% recovery yield with specifications meeting the requirements of the polymer industry. Further, process integration opportunities were implemented that allowed minimizing the generation of waste streams containing fumaric acid which enabled increasing the yield to 81.4% while keeping the product specifications.

Ependymoma is responsible for 8–10% of all pediatric brain tumors and constitutes the third most common brain tumor in children. No robust molecular markers are yet in routine clinical use. Surgical resection and adjuvant radiotherapy cure approximately 40-70% of pediatric patients with ependymoma. In our centre, we have been using prophylactic valproic acid treatment for brain tumor patients. Initial observations indicated that valproate could have a beneficial effect in the survival of patients. Recent observations by other authors have shown that patients with glioblastoma benefited from the treatment with valproic acid, a histone deacetylase inhibitor. We have used random survival forest, a novel ensemble survival modelling method to study a single- center, small number cohort of pediatric patients with ependymoma. This analysis has confirmed surgery resection extent and treatment with radiotherapy as independent predictors of overall survival. Treatment with valproic acid was also a predictor of higher survival in this cohort. These results highlight the potential usefullness of the random survival forest model in gathering information from retrospective data. More data is needed about the possible influence of histone deacetylase inhibition by valproic acid in the survival of patients with ependymoma.

In this paper, carbon nanotubes modified screen-printed electrode (CNTs/SPE) was prepared and the CNTs/SPE was employed for the electrochemical determination of antioxidant substance Chlorogenic acids (CGAs). A pair of well-defined redox peak of CGA was observed at the CNTs/SPE in 0.10 mol∙L^-1 acetic acid-sodium acetate buffer (pH 6.2) and electrode process is adsorption-controlled. Cyclic voltammetry (CV) and differential pulse voltammetry (DPV) method for the determination of CGA were proposed based on the CNTs/SPE. Under the optimal conditions, the proposed method exhibited linear ranges from 4.73×10^-7 to 4.45×10^-5 mol∙L^-1, the linear regression equation was Ipa(µA) = 4.1993 C (mol∙L^-1)+1.1039 (r = 0.9976) and the detection limit for CGA could reach 3.25×10^-6 mol∙L^-1. The recovery of matrine was 94.74~106.65% (RSD = 2.92%) in coffe beans. The proposed method is quick, sensitive, reliable, and can be used for the determination of CGA.

A Staudinger reaction on solid phase between an electronodeficit organic azide such as sulfonyl azide, and the phosphite triester formed upon phosphoramidite coupling is a convenient method for chemical modification of oligonucleotides at the internucleotidic phosphate position. In this work, 4-carboxybenzenesulfonyl azide either with a free carboxy group or in the form of an activated ester such as pentafluorophenyl, 4-nitrophenyl, or pentafluorobenzyl ester were used to introduce a carboxylic acid function to the terminal or internal internucleotidic phosphate of an oligonucleotide via Staudinger reaction. A subsequent treatment with excess primary alkyl amine followed by usual work-up, after prior activation with a suitable peptide coupling agent such as HBTU/HOBt in the case of a free carboxyl, afforded amide-linked oligonucleotide conjugates in good yields including multiple conjugations of up to the exhaustive modification at each phosphate position for a weakly activated pentafluorobenzyl ester, whereas more strongly activated and, thus, more reactive aryl esters provided only single conjugations at the 5′-end. The conjugates synthesized include those with di- and polyamines that introduce a positively charged side-chain to potentially assist intracellular delivery of the oligonucleotide.

During the last trimester of gestation and for the first 18 months after birth, both docosahexaenoic acid,22:6n-3 (DHA) and arachidonic acid,20:4n-6 (ARA) are preferentially deposited within the cerebral cortex at a rapid rate. Although, the structural and functional roles of DHA in brain development are well investigated, similar roles of ARA are not well documented. The mode of action of these two fatty acids and their derivatives at different structural-functional roles and their levels in the gene expression and signaling pathways of the brain have been continuously emanating. In addition to DHA, importance of ARA has been much discussed in recent years for fetal and postnatal brain development and the maternal supply of ARA and DHA. These fatty acids are also involved in various brain developmental processes; however, their mechanistic cross talks are not clearly known yet. This review describes the importance of ARA, in addition to DHA to support the optimal brain development and growth and functional roles in the brain.

Cells receive external stimuli to incur structural and functional damages. On scanning acoustic microscopy (SAM), speed-of-sound (SOS), attenuation-of-sound (AOS), and thickness values are plotted on the screen to create cellular images, which are related to stiffness, viscosity, and cell size, respectively. The obtained digital data compared using statistical analysis. We aimed to investigate the effects of anticancer drugs, acidic fluids, and heat effects on the cells by using SAM. Anticancer drug cisplatin induced cancer cell apoptosis/necrosis and regeneration in culture, causing elevated SOS, reduced AOS, and thickness. During a more prolonged incubation, the SAM values fluctuated differently between the cisplatin-treated and untreated cells. The tannic and acetic acid and microwave stimuli induced SOS and AOS elevations. These stimuli altered the cell size, number, differentiation, viscosity, and stiffness, which corresponded well to the fluctuation of the SOS and AOS values after incubation. Different anticancer drugs interacted with cancer cells to induce the characteristic alterations of the SAM values. These structural and mechanical alterations induced in cells was difficult to observe on light microscopy. Cellular damages were statistically compared between different stimuli and time-lapse cellular changes were observed using a SAM analysis. SAM is a useful modality to evaluate cellular damage.

(1) Teeth, represent in humans the most resilient tissues. However, exposure to concentrated acids might lead to their obliteration, thus making human identification difficult. Teeth often contain dental restorations from materials that are even more resilient to acid impact. This paper introduces novel method of 3D reconstruction of dental patterns as a crucial step for digital identification with dental records.; (2) With combination of modern methods of Micro-Computer Tomography, Cone Beam Computer Tomography, Attenuated Total Reflection in conjunction with Fourier-Transform Infrared Spectroscopy and Artificial Intelligence Convolutional Neural Network algorithms, the paper presents the way of 3D dental pattern reconstruction and human remains identification. Research studies morphology of teeth, bone, and dental materials (Amalgam, Composite, Glass-ionomer cement) under different periods of exposure to 75% sulfuric acid; (3) Results reveal significant volume loss in bone, enamel, dentine, and as well glass-ionomer cement. Results also reveal significant resistance of composite and amalgam dental materials to sulfuric acid impact, thus serving as strong parts in the dental pattern mosaic. Paper also introduces probably first successful artificial intelligence application in automated forensic CBCT segmentation.; (4) Interdisciplinary cooperation utilizing mentioned technologies can solve problem of human remains identification with 3D reconstruction of dental patterns and their 2D projections over existing ante-mortem records.

Semantic segmentation of high-resolution remote sensing images provides detailed and precise feature information, playing a pivotal role in decision-making and analysis in sectors such as water management, agriculture, military, and environmental protection. However, most methods merely combine features from various branches directly, without a mechanism for spatial location feature screening, and treat all extracted features as equally important. To overcome these limitations, we introduce a novel spatially adaptive interaction network (SAINet) for dynamic interaction across different features in remote sensing semantic segmentation task. Specifically, we propose a spatial refined module that leverages local context information to filter spatial locations and extract salient regions. Following this, we introduce an innovative spatial interaction module that uses a spatial adaptive modulation mechanism to dynamically select and allocate spatial position weights. This facilitates interaction between local salient areas and global information, allowing the network to focus more on relevant regions. This flexible approach enables the network to capture more informative features, thereby enhancing segmentation accuracy. Experiments conducted on the DeepGlobe, Vaihingen, and Potsdam public datasets confirm the effectiveness and capability of SAINet. Our code and models will be publicly available

In this paper, we propose and demonstrate a network analysis optical frequency domain reflectometer (NA-OFDR) for distributed temperature measurements at high spatial (down to 3 cm) and temperature resolution. The system makes use of a frequency-stepped, continuous-wave (cw) laser, whose output light is modulated using a vector network analyzer. The latter is also used to demodulate the amplitude of the beat signal obtained by coherently mixing the Rayleigh backscattered light with a local oscillator. The system is capable of high measurand resolution (50 mK at 3-cm spatial resolution), thanks to the high sensitivity of coherent Rayleigh scattering to temperature. Furthermore, compared to the conventional optical-frequency domain reflectometry (OFDR), the proposed system does not rely on the use of a tunable laser, therefore it is less prone to limitations related to the laser coherence or sweep nonlinearity. Two configurations are analyzed, both numerically and experimentally, based on either a double sideband or single sideband modulated probe light. The results confirm the validity of the proposed approach.

Wang et al. (Nature 623, 340—350; 2023)¹ used satellite observations and phenological signatures to estimate the extent of planted rubber (Hevea brasiliensis Müll.Arg.) and associated deforestation for eight Southeast Asian countries. Their map implies that planted rubber has caused more than 4 Mha of deforestation since 1993 — a value greater than previously assumed. Unfortunately, their approach was flawed. Our assessment indicates that the actual extent of planted rubber is approximately half that reported by Wang et al., while the extent of associated deforestation is approximately one quarter.

Detecting the presence of explosives is important to protect human lives in military conflicts and peacetime. Gas-phase detection of explosives can make use of the change of material properties, which can be sensitive to environmental conditions such as temperature and humidity. This paper describes a remote-controlled automatic shutter method for environmental impact assessment of photoluminescence (PL) sensors under near-open conditions. Utilizing the remote-sensing method, we obtained environmental effects without being exposed to sensing vapor molecules, and explained how PL intensity was influenced by the temperature, humidity, and exposure time. We also developed a theoretical model including the effect of exciton diffusion for PL quenching, which worked well under limited molecular diffusions. Incomplete recovery of PL intensity, or degradation effect, was considered as an additional factor in the model.

This study explores the use of Bayesian Neural Networks (BNNs) for estimating chlorophyll-a concentration ([CHL-a]) from remotely sensed data. The BNN model enables uncertainty quantification, offering additional layers of information compared to traditional ocean colour models. An extensive in situ bio-optical dataset is utilized, generated by merging 27 data sources across the world’s oceans. The BNN model demonstrates remarkable capability in capturing mesoscale features and ocean circulation patterns, providing comprehensive insights into spatial and temporal variations in [CHL-a] across diverse marine ecosystems. In comparison to established ocean colour algorithms, such as Ocean Colour 4 (OC4), the BNN shows comparable performance in terms of correlation coefficients, errors, and biases when compared with the in situ data. The BNN, however, further provides critical information about the distribution of [CHL-a], which can be used to assess uncertainties in the prediction. Moreover, the BNN model’s ability to provide more information for coastal waters, especially with higher spatial resolution imagery, offers valuable advantages for marine research and management. By quantifying uncertainty, the model builds confidence in [CHL-a] predictions, even in regions with limited data coverage. This is reflected by the spread in the model predictions, where the BNN can detect a range of uncertainty bounds that reflect confidence in the retrievals. Introducing BNNs as probabilistic ocean colour models represents a significant advancement, enabling more accurate and reliable predictions of [CHL-a] in the global oceans.