Search results for: spectrum sensing

Authors: Zhijie Li, Wenhui Peng, Zelong Yuan, Jianchun Wang

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Turbulence is a complex phenomenon that plays a crucial role in various fields, such as engineering, atmospheric science, and fluid dynamics. Predicting and understanding its behavior over long time scales have been challenging tasks. Traditional methods, such as large-eddy simulation (LES), have provided valuable insights but are computationally expensive. In the past few years, machine learning methods have experienced rapid development, leading to significant improvements in computational speed. However, ensuring stable and accurate long-term predictions remains a challenging task for these methods. In this study, we introduce the implicit U-net enhanced Fourier neural operator (IU-FNO) as a solution for stable and efficient long-term predictions of the nonlinear dynamics in three-dimensional (3D) turbulence. The IU-FNO model combines implicit re-current Fourier layers to deepen the network and incorporates the U-Net architecture to accurately capture small-scale flow structures. We evaluate the performance of the IU-FNO model through extensive large-eddy simulations of three types of 3D turbulence: forced homogeneous isotropic turbulence (HIT), temporally evolving turbulent mixing layer, and decaying homogeneous isotropic turbulence. The results demonstrate that the IU-FNO model outperforms other FNO-based models, including vanilla FNO, implicit FNO (IFNO), and U-net enhanced FNO (U-FNO), as well as the dynamic Smagorinsky model (DSM), in predicting various turbulence statistics. Specifically, the IU-FNO model exhibits improved accuracy in predicting the velocity spectrum, probability density functions (PDFs) of vorticity and velocity increments, and instantaneous spatial structures of the flow field. Furthermore, the IU-FNO model addresses the stability issues encountered in long-term predictions, which were limitations of previous FNO models. In addition to its superior performance, the IU-FNO model offers faster computational speed compared to traditional large-eddy simulations using the DSM model. It also demonstrates generalization capabilities to higher Taylor-Reynolds numbers and unseen flow regimes, such as decaying turbulence. Overall, the IU-FNO model presents a promising approach for long-term dynamics prediction in 3D turbulence, providing improved accuracy, stability, and computational efficiency compared to existing methods.

Keywords: data-driven, Fourier neural operator, large eddy simulation, fluid dynamics

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Authors: Ranjita Ghoshmoulick, Aswathi Madhavan, Subhavna Juneja, Prasenjit Sen, Jaydeep Bhattacharya

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Type 2 diabetes mellitus (T2DM) is a very complex and multifactorial metabolic disease where the blood sugar level goes up. One of the major consequence of this elevated blood sugar is the formation of AGE (Advance Glycation Endproducts), from a series of chemical or biochemical reactions. AGE are detrimental because it leads to severe pathogenic complications. They are a group of structurally diverse chemical compounds formed from nonenzymatic reactions between the free amino groups (-NH2) of proteins and carbonyl groups (>C=O) of reducing sugars. The reaction is known as Maillard Reaction. It starts with the formation of reversible schiff’s base linkage which after sometime rearranges itself to form Amadori Product along with dicarbonyl compounds. Amadori products are very unstable hence rearrangement goes on until stable products are formed. During the course of the reaction a lot of chemically unknown intermediates and reactive byproducts are formed that can be termed as Early Glycation Products. And when the reaction completes, structurally stable chemical compounds are formed which is termed as Advanced Glycation Endproducts. Though all glycation products have not been characterized well, some fluorescence compounds e.g pentosidine, Malondialdehyde (MDA) or carboxymethyllysine (CML) etc as AGE and α-dicarbonyls or oxoaldehydes such as 3-deoxyglucosone (3-DG) etc as the intermediates have been identified. In this work Gold NanoParticle (GNP) was used as an optical indicator of glycation products. To achieve faster glycation kinetics and high AGE accumulation, fructose was used instead of glucose. Hemoglobin A0 (HbA0) was fructosylated by in-vitro method. AGE formation was measured fluorimetrically by recording emission at 450nm upon excitation at 350nm. Thereafter this fructosylated HbA0 was fractionated by column chromatography. Fractionation separated the proteinaceous substance from the AGEs. Presence of protein part in the fractions was confirmed by measuring the intrinsic protein fluorescence and Bradford reaction. GNPs were synthesized using the templates of chromatographically separated fractions of fructosylated HbA0. Each fractions gave rise to GNPs of varying color, indicating the presence of distinct set of glycation products differing structurally and chemically. Clear solution appeared due to settling down of particles in some vials. The reactive groups of the intermediates kept the GNP formation mechanism on and did not lead to a stable particle formation till Day 10. Whereas SPR of GNP showed monotonous colour for the fractions collected in case of non fructosylated HbA0. Our findings accentuate the use of GNPs as a simple colorimetric sensing platform for the identification of intermediates of glycation reaction which could be implicated in the prognosis of the associated health risk due to T2DM and others.

Keywords: advance glycation endproducts, glycation, gold nano particle, sensor

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Authors: Ogemdi Chinwendu Anika, Anna Strzelecka, Yadira Bajón-Fernández, Raffaella Villa

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Anaerobic digestion (AD) has been used since time in memorial to take care of organic wastes in the environment, especially for sewage and wastewater treatments. Recently, the rising demand/need to increase renewable energy from organic matter has caused the AD substrates spectrum to expand and include a wider variety of organic materials such as agricultural residues and farm manure which is annually generated at around 140 billion metric tons globally. The problem, however, is that agricultural wastes are composed of materials that are heterogeneous and too difficult to degrade -particularly lignin, that make up about 0–40% of the total lignocellulose content. This study aimed to evaluate the impact of varying concentrations of lignin on biogas yields and their subsequent response to a commercial yeast-based bioadditive in batch anaerobic digesters. The experiments were carried out in batches for a retention time of 56 days with different lignin concentrations (200 mg, 300 mg, 400 mg, 500 mg, and 600 mg) treated to different conditions to first determine the concentration of the bioadditive that was most optimal for overall process improvement and yields increase. The batch experiments were set up using 130 mL bottles with a working volume of 60mL, maintained at 38°C in an incubator shaker (150rpm). Digestate obtained from a local plant operating at mesophilic conditions was used as the starting inoculum, and commercial kraft lignin was used as feedstock. Biogas measurements were carried out using the displacement method and were corrected to standard temperature and pressure using standard gas equations. Furthermore, the modified Gompertz equation model was used to non-linearly regress the resulting data to estimate gas production potential, production rates, and the duration of lag phases as indicatives of degrees of lignin inhibition. The results showed that lignin had a strong inhibitory effect on the AD process, and the higher the lignin concentration, the more the inhibition. Also, the modelling showed that the rates of gas production were influenced by the concentrations of the lignin substrate added to the system – the higher the lignin concentrations in mg (0, 200, 300, 400, 500, and 600) the lower the respective rate of gas production in ml/gVS.day (3.3, 2.2, 2.3, 1.6, 1.3, and 1.1), although the 300 mg increased by 0.1 ml/gVS.day over that of the 200 mg. The impact of the yeast-based bioaddition on the rate of production was most significant in the 400 mg and 500 mg as the rate was improved by 0.1 ml/gVS.day and 0.2 ml/gVS.day respectively. This indicates that agricultural residues with higher lignin content may be more responsive to inhibition alleviation by yeast-based bioadditive; therefore, further study on its application to the AD of agricultural residues of high lignin content will be the next step in this research.

Keywords: anaerobic digestion, renewable energy, lignin valorisation, biogas

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Authors: M. Kowalik, J. Masternak, K. Kazimierczuk, O. V. Khavryuchenko, B. Kupcewicz, B. Barszcz

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Recently, the growing interest of chemists in metal-organic coordination polymers (MOCPs) is primarily derived from their intriguing structures and potential applications in catalysis, gas storage, molecular sensing, ion exchanges, nonlinear optics, luminescence, etc. Currently, we are devoting considerable effort to finding the proper method of synthesizing new coordination polymers containing S- or N-heteroaromatic carboxylates as linkers and characterizing the obtained Pb(II) compounds according to their structural diversity, luminescence, and thermal properties. The choice of Pb(II) as the central ion of MOCPs was motivated by several reasons mentioned in the literature: i) a large ionic radius allowing for a wide range of coordination numbers, ii) the stereoactivity of the 6s2 lone electron pair leading to a hemidirected or holodirected geometry, iii) a flexible coordination environment, and iv) the possibility to form secondary bonds and unusual non-covalent interactions, such as classic hydrogen bonds and π···π stacking interactions, as well as nonconventional hydrogen bonds and rarely reported tetrel bonds, Pb(lone pair)···π interactions, C–H···Pb agostic-type interactions or hydrogen bonds, and chelate ring stacking interactions. Moreover, the construction of coordination polymers requires the selection of proper ligands acting as linkers, because we are looking for materials exhibiting different network topologies and fluorescence properties, which point to potential applications. The reaction of Pb(NO₃)₂ with 1H-pyrrole-2-carboxylic acid (2prCOOH) leads to the formation of a new four-nuclear Pb(II) polymer, [Pb4(2prCOO)₈(H₂O)]ₙ, which has been characterized by CHN, FT-IR, TG, PL and single-crystal X-ray diffraction methods. In view of the primary Pb–O bonds, Pb1 and Pb2 show hemidirected pentagonal pyramidal geometries, while Pb2 and Pb4 display hemidirected octahedral geometries. The topology of the strongest Pb–O bonds was determined as the (4·8²) fes topology. Taking the secondary Pb–O bonds into account, the coordination number of Pb centres increased, Pb1 exhibited a hemidirected monocapped pentagonal pyramidal geometry, Pb2 and Pb4 exhibited a holodirected tricapped trigonal prismatic geometry, and Pb3 exhibited a holodirected bicapped trigonal prismatic geometry. Moreover, the Pb(II) lone pair stereoactivity was confirmed by DFT calculations. The 2D structure was expanded into 3D by the existence of non-covalent O/C–H···π and Pb···π interactions, which was confirmed by the Hirshfeld surface analysis. The above mentioned interactions improve the rigidity of the structure and facilitate the charge and energy transfer between metal centres, making the polymer a promising luminescent compound.

Keywords: coordination polymers, fluorescence properties, lead(II), lone electron pair stereoactivity, non-covalent interactions

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Authors: Shashi Bhushan, Sucharita Sen

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In India, forest and people are inextricably linked since millions of people live adjacent to or within protected areas and harvest forest products. Indian forest has their own legacy to sustain by its own climatic nature with several social, economic and cultural activities. People surrounding forest areas are not only dependent on this resource for their livelihoods but also for the other source, like religious ceremonies, social customs and herbal medicines, which are determined by the forest like agricultural land, groundwater level, and soil fertility. The assumption that fuelwood and fodder extraction, which is the part of local livelihood leads to deforestation, has so far been the dominant mainstream views in deforestation discourses. Given the occupational division across social groups in Kaimur reserve forest, the differential nature of dependence of forest resources is important to understand. This paper attempts to assess the nature of dependence and impact of forest degradation on rural households across various social groups. Also, an additional element that is added to the enquiry is the way degradation of forests leading to scarcity of forest-based resources impacts the patterns of dependence across various social groups. Change in forest area calculated through land use land cover analysis using remote sensing technique and examination of different economic activities carried out by the households that are forest-based was collected by primary survey in Kaimur reserve forest of state of Bihar in India. The general finding indicates that the Scheduled Tribe and Scheduled Caste communities, the most socially and economically deprived sections of the rural society are involved in a significant way in collection of fuelwood, fodder, and fruits, both for self-consumption and sale in the market while other groups of society uses fuelwood, fruit, and fodder for self-use only. Depending on the local forest resources for fuelwood consumption was the primary need for all social groups due to easy accessibility and lack of alternative energy source. In last four decades, degradation of forest made a direct impact on rural community mediated through the socio-economic structure, resulting in a shift from forest-based occupations to cultivation and manual labour in agricultural and non-agricultural activities. Thus there is a need to review the policies with respect to the ‘community forest management’ since this study clearly throws up the fact that engagement with and dependence on forest resources is socially differentiated. Thus tying the degree of dependence and forest management becomes extremely important from the view of ‘sustainable’ forest resource management. The statization of forest resources also has to keep in view the intrinsic way in which the forest-dependent population interacts with the forest.

Keywords: forest degradation, livelihood, social groups, tribal community

Procedia PDF Downloads 131

Authors: Claudia Norambuena, Myissa Weiss, Maria Ruiz Maya, Matthew Straley, Elijah Hammond, Benjamin Chesebrough, David Grow

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The purpose of this project is to develop a low-cost, portable sensor device that can be used at home for long-term analysis of gait and balance abnormalities. One area of particular concern involves the asymmetries in movement and balance that can accompany certain types of injuries and/or the associated devices used in the repair and rehabilitation process (e.g. the use of splints and casts) which can often increase chances of falls and additional injuries. This device has the capacity to monitor a patient during the rehabilitation process after injury or operation, increasing the patient’s access to healthcare while decreasing the number of visits to the patient’s clinician. The sensor device may thereby improve the quality of the patient’s care, particularly in rural areas where access to the clinician could be limited, while simultaneously decreasing the overall cost associated with the patient’s care. The device consists of nine interconnected accelerometer/ gyroscope/compass chips (9-DOF IMU, Adafruit, New York, NY). The sensors attach to and are used to determine the orientation and acceleration of the patient’s lower abdomen, C7 vertebra (lower neck), L1 vertebra (middle back), anterior side of each thigh and tibia, and dorsal side of each foot. In addition, pressure sensors are embedded in shoe inserts with one sensor (ESS301, Tekscan, Boston, MA) beneath the heel and three sensors (Interlink 402, Interlink Electronics, Westlake Village, CA) beneath the metatarsal bones of each foot. These sensors measure the distribution of the weight applied to each foot as well as stride duration. A small microntroller (Arduino Mega, Arduino, Ivrea, Italy) is used to collect data from these sensors in a CSV file. MATLAB is then used to analyze the data and output the hip, knee, ankle, and trunk angles projected on the sagittal plane. An open-source program Processing is then used to generate an animation of the patient’s gait. The accuracy of the sensors was validated through comparison to goniometric measurements (±2° error). The sensor device was also shown to have sufficient sensitivity to observe various gait abnormalities. Several patients used the sensor device, and the data collected from each represented the patient’s movements. Further, the sensors were found to have the ability to observe gait abnormalities caused by the addition of a small amount of weight (4.5 - 9.1 kg) to one side of the patient. The user-friendly interface and portability of the sensor device will help to construct a bridge between patients and their clinicians with fewer necessary inpatient visits.

Keywords: biomedical sensing, gait analysis, outpatient, rehabilitation

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Authors: Jessica A. Hellings, Piyushkumar Jani

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Background: Systemic autoimmune disorders are increasingly implicated in neuropsychiatric illness, especially in the setting of treatment resistance in individuals of all ages. Gluten allergy in fullest extent results in celiac disease, affecting multiple organs including central nervous system (CNS). Clinicians often lack awareness of the association between neuropsychiatric illness and gluten allergy, partly since many such research studies are published in immunology and gastroenterology journals. Methods: Following a Pubmed literature search and online searches on celiac disease websites, 40 articles are critically reviewed in detail. This work reviews celiac disease, gluten intolerance and current evidence of their relationship to neuropsychiatric and systemic illnesses. The review also covers current work-up and diagnosis, as well as dietary interventions, gluten restriction outcomes, and future research directions. Results: Gluten allergy in susceptible individuals damages the small intestine, producing a leaky gut and malabsorption state, as well as allowing antibodies into the bloodstream, which attack major organs. Lack of amino acid precursors for neurotransmitter synthesis together with antibody-associated brain changes and hypoperfusion may result in neuropsychiatric illness. This is well documented; however, studies in neuropsychiatry are often small. In the large CATIE trial, subjects with schizophrenia had significantly increased antibodies to tissue transglutaminase (TTG), and antigliadin antibodies, both significantly greater gluten antibodies than in control subjects. On later follow up, TTG-6 antibodies were identified in these subjects’ brains but not in their intestines. Significant evidence mostly from small studies also exists for gluten allergy and celiac-related depression, anxiety disorders, attention-deficit/hyperactivity disorder, autism spectrum disorders, ataxia, and epilepsy. Dietary restriction of gluten resulted in remission in several published cases, including for treatment-resistant schizophrenia. Conclusions: Ongoing and larger studies are needed of the diagnosis and treatment efficacy of the gluten-free diet in neuropsychiatric illness. Clinicians should ask about the patient history of anemia, hypothyroidism, irritable bowel syndrome and family history of benefit from the gluten-free diet, not limited to but especially in cases of treatment resistance. Obtaining gluten antibodies by a simple blood test, and referral for gastrointestinal work-up in positive cases should be considered.

Keywords: celiac, gluten, neuropsychiatric, translational

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Authors: Deybith Venegas-Rojas, Sercan Keskin, Svenja Riekeberg, Sana Azim, Stephanie Manz, R. J. Dwayne Miller, Hoc Khiem Trieu

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Liquid Transmission Electron Microscopy (TEM) is a growing area with a broad range of applications from physics and chemistry to material engineering and biology, in which it is possible to image in-situ unseen phenomena. For this, a nanofluidic device is used to insert the nanoflow with the sample inside the microscope in order to keep the liquid encapsulated because of the high vacuum. In the last years, Si3N4 windows have been widely used because of its mechanical stability and low imaging contrast. Nevertheless, the pressure difference between the inside fluid and the outside vacuum in the TEM generates bulging in the windows. This increases the imaged fluid volume, which decreases the signal to noise ratio (SNR), limiting the achievable spatial resolution. With the proposed device, the membrane is fortified with a microstructure capable of stand higher pressure differences, and almost removing completely the bulging. A theoretical study is presented with Finite Element Method (FEM) simulations which provide a deep understanding of the membrane mechanical conditions and proves the effectiveness of this novel concept. Bulging and von Mises Stress were studied for different membrane dimensions, geometries, materials, and thicknesses. The microfabrication of the device was made with a thin wafer coated with thin layers of SiO2 and Si3N4. After the lithography process, these layers were etched (reactive ion etching and buffered oxide etch (BOE) respectively). After that, the microstructure was etched (deep reactive ion etching). Then the back side SiO2 was etched (BOE) and the array of free-standing micro-windows was obtained. Additionally, a Pyrex wafer was patterned with windows, and inlets/outlets, and bonded (anodic bonding) to the Si side to facilitate the thin wafer handling. Later, a thin spacer is sputtered and patterned with microchannels and trenches to guide the nanoflow with the samples. This approach reduces considerably the common bulging problem of the window, improving the SNR, contrast and spatial resolution, increasing substantially the mechanical stability of the windows, allowing a larger viewing area. These developments lead to a wider range of applications of liquid TEM, expanding the spectrum of possible experiments in the field.

Keywords: liquid cell, liquid transmission electron microscopy, nanofluidics, nanofluidic cell, thin films

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Authors: Dmitry Kukushkin

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Lineaments form complex grids on Earth's surface. Currently, one particular object of study for many researchers is the analysis and geological interpretation of maps of lineament density in an attempt to locate various geological structures. But lineament grids are made up of global, regional and local components, and this superimposition of lineament grids of various scales (global, regional, and local) renders this method less effective. Besides, the erosion processes and the erosional resistance of rocks lying on the surface play a significant role in the formation of lineament grids. Therefore, specific lineament density map is characterized by poor contrast (most anomalies do not exceed the average values by more than 30%) and unstable relation with local geological structures. Our method allows to confidently determine the location and boundaries of local geological structures that are likely to contain mineral deposits. Maps of the fields of lineament distortion (residual specific density) created by our method are characterized by high contrast with anomalies exceeding the average by upward of 200%, and stable correlation to local geological structures containing mineral deposits. Our method considers a lineament grid as a general lineaments field – surface manifestation of stress and strain fields of Earth associated with geological structures of global, regional and local scales. Each of these structures has its own field of brittle dislocations that appears on the surface of its lineament field. Our method allows singling out local components by suppressing global and regional components of the general lineaments field. The remaining local lineament field is an indicator of local geological structures.The following are some of the examples of the method application: 1. Srednevilyuiskoye gas condensate field (Yakutia) - a direct proof of the effectiveness of methodology; 2. Structure of Astronomy (Taimyr) - confirmed by the seismic survey; 3. Active gold mine of Kadara (Chita Region) – confirmed by geochemistry; 4. Active gold mine of Davenda (Yakutia) - determined the boundaries of the granite massif that controls mineralization; 5. Object, promising to search for hydrocarbons in the north of Algeria - correlated with the results of geological, geochemical and geophysical surveys. For both Kadara and Davenda, the method demonstrated that the intensive anomalies of the local lineament fields are consistent with the geochemical anomalies and indicate the presence of the gold content at commercial levels. Our method of suppression of global and regional components results in isolating a local lineament field. In early stages of a geological exploration for oil and gas, this allows determining boundaries of various geological structures with very high reliability. Therefore, our method allows optimization of placement of seismic profile and exploratory drilling equipment, and this leads to a reduction of costs of prospecting and exploration of deposits, as well as acceleration of its commissioning.

Keywords: lineaments, mineral exploration, oil and gas, remote sensing

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Authors: Muhammad Irfan

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The rise of radicalization within Islam has spawned a new era of global terror. The battlefield Successes of ISIS and the Taliban are fuelled by an ideological war waged, largely and successfully, in the media arena. This research will examine how Islamic extremist groups are using media modalities and populist narratives to influence migrant Muslim populations in Europe towards extremism. In 2014, ISIS shocked the world in exporting horrifically graphic forms of violence on social media. Their Muslim support base was largely disgusted and reviled. In response, they reconfigured their narrative by introducing populist 'hooks', astutely portraying the Muslim populous as oppressed and exploited by unjust, corrupt autocratic regimes and Western power structures. Within this crucible of real and perceived oppression, hundreds of thousands of the most desperate, vulnerable and abused migrants left their homelands, risking their lives in the hope of finding peace, justice, and prosperity in Europe. Instead, many encountered social stigmatization, detention and/or discrimination for being illegal migrants, for lacking resources and for simply being Muslim. This research will examine how Islamic extremist groups are exploiting the disenfranchisement of these migrant populations and using populist messaging on social media to influence them towards violent extremism. ISIS, in particular, formulates specific encoded messages for newly-arriving Muslims in Europe, preying upon their vulnerability. Violence is posited, as a populist response, to the tyranny of European oppression. This research will analyze the factors and indicators which propel Muslim migrants along the spectrum from resilience to violence extremism. Expected outcomes are identification of factors which influence vulnerability towards violent extremism; an early-warning detection framework; predictive analysis models; and de-radicalization frameworks. This research will provide valuable tools (practical and policy level) for European governments, security stakeholders, communities, policy-makers, and educators; it is anticipated to contribute to a de-escalation of Islamic extremism globally.

Keywords: populism, radicalization, de-radicalization, social media, ISIS, Taliban, shariah, jihad, Islam, Europe, political communication, terrorism, migrants, refugees, extremism, global terror, predictive analysis, early warning detection, models, strategic communication, populist narratives, Islamic extremism

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Authors: Eliane G. Tótoli, Hérida Regina N. Salgado

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Daptomycin is an important antimicrobial agent used in clinical practice nowadays, since it is very active against some Gram-positive bacteria that are particularly challenges for the medicine, such as methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococci (VRE). The importance of environmental preservation has receiving special attention since last years. Considering the evident need to protect the natural environment and the introduction of strict quality requirements regarding analytical procedures used in pharmaceutical analysis, the industries must seek environmentally friendly alternatives in relation to the analytical methods and other processes that they follow in their routine. In view of these factors, green analytical chemistry is prevalent and encouraged nowadays. In this context, infrared spectroscopy stands out. This is a method that does not use organic solvents and, although it is formally accepted for the identification of individual compounds, also allows the quantitation of substances. Considering that there are few green analytical methods described in literature for the analysis of daptomycin, the aim of this work was the development and validation of a green analytical method for the quantification of this drug in lyophilized powder for injectable solution, by Fourier-transform infrared spectroscopy (FT-IR). Method: Translucent potassium bromide pellets containing predetermined amounts of the drug were prepared and subjected to spectrophotometric analysis in the mid-infrared region. After obtaining the infrared spectrum and with the assistance of the IR Solution software, quantitative analysis was carried out in the spectral region between 1575 and 1700 cm-1, related to a carbonyl band of the daptomycin molecule, and this band had its height analyzed in terms of absorbance. The method was validated according to ICH guidelines regarding linearity, precision (repeatability and intermediate precision), accuracy and robustness. Results and discussion: The method showed to be linear (r = 0.9999), precise (RSD% < 2.0), accurate and robust, over a concentration range from 0.2 to 0.6 mg/pellet. In addition, this technique does not use organic solvents, which is one great advantage over the most common analytical methods. This fact contributes to minimize the generation of organic solvent waste by the industry and thereby reduces the impact of its activities on the environment. Conclusion: The validated method proved to be adequate to quantify daptomycin in lyophilized powder for injectable solution and can be used for its routine analysis in quality control. In addition, the proposed method is environmentally friendly, which is in line with the global trend.

Keywords: daptomycin, Fourier-transform infrared spectroscopy, green analytical chemistry, quality control, spectrometry in IR region

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Authors: Sara Ignoto, Elena M. Scalisi, Carmen Sica, Martina Contino, Greta Ferruggia, Antonio Salvaggio, Santi C. Pavone, Gino Sorbello, Loreto Di Donato, Roberta Pecoraro, Maria V. Brundo

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The new fifth generation technology (5G), which should favor high data-rate connections (1Gbps) and latency times lower than the current ones (<1ms), has the characteristic of working on different frequency bands of the radio wave spectrum (700 MHz, 3.6-3.8 GHz and 26.5-27.5 GHz), thus also exploiting higher frequencies than previous mobile radio generations (1G-4G). The higher frequency waves, however, have a lower capacity to propagate in free space and therefore, in order to guarantee the capillary coverage of the territory for high reliability applications, it will be necessary to install a large number of repeaters. Following the introduction of this new technology, there has been growing concern in recent years about the possible harmful effects on human health and several studies were published using several animal models. This study aimed to observe the possible short-term effects induced by 5G-millimeter waves on heartbeat of early life stages of Danio rerio using DanioScope software (Noldus). DanioScope is the complete toolbox for measurements on zebrafish embryos and larvae. The effect of substances can be measured on the developing zebrafish embryo by a range of parameters: earliest activity of the embryo’s tail, activity of the developing heart, speed of blood flowing through the vein, length and diameters of body parts. Activity measurements, cardiovascular data, blood flow data and morphometric parameters can be combined in one single tool. Obtained data are elaborate and provided by the software both numerical as well as graphical. The experiments were performed at 27 GHz by a no commercial high gain pyramidal horn antenna. According to OECD guidelines, exposure to 5G-millimeter waves was tested by fish embryo toxicity test within 96 hours post fertilization, Observations were recorded every 24h, until the end of the short-term test (96h). The results have showed an increase of heartbeat rate on exposed embryos at 48h hpf than control group, but this increase has not been shown at 72-96 h hpf. Nowadays, there is a scant of literature data about this topic, so these results could be useful to approach new studies and also to evaluate potential cardiotoxic effects of mobile radiofrequency.

Keywords: Danio rerio, DanioScope, cardiotoxicity, millimeter waves.

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Authors: Kevin De Castro Cogle, Mirian Kubo, Maria Anastasiadi, Fady Mohareb, Claire Rossi

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Background: The bioaccessibility of bioactive compounds is a critical determinant of the nutritional quality of various food products. Despite its importance, there is a limited number of comprehensive studies aimed at assessing how the composition of a food matrix influences the bioaccessibility of a compound of interest. This knowledge gap has prompted a growing need to investigate the intricate relationship between food matrix formulations and the bioaccessibility of bioactive compounds. One such class of bioactive compounds that has attracted considerable attention is curcuminoids. These naturally occurring phytochemicals, extracted from the roots of Curcuma longa, have gained popularity owing to their purported health benefits and also well known for their poor bioaccessibility Project aim: The primary objective of this research project is to systematically assess the influence of matrix composition on the bioaccessibility of curcuminoids. Additionally, this study aimed to develop a series of predictive models for bioaccessibility, providing valuable insights for optimising the formula for functional foods and provide more descriptive nutritional information to potential consumers. Methods: Food formulations enriched with curcuminoids were subjected to in vitro digestion simulation, and their bioaccessibility was characterized with chromatographic and spectrophotometric techniques. The resulting data served as the foundation for the development of predictive models capable of estimating bioaccessibility based on specific physicochemical properties of the food matrices. Results: One striking finding of this study was the strong correlation observed between the concentration of macronutrients within the food formulations and the bioaccessibility of curcuminoids. In fact, macronutrient content emerged as a very informative explanatory variable of bioaccessibility and was used, alongside other variables, as predictors in a Bayesian hierarchical model that predicted curcuminoid bioaccessibility accurately (optimisation performance of 0.97 R2) for the majority of cross-validated test formulations (LOOCV of 0.92 R2). These preliminary results open the door to further exploration, enabling researchers to investigate a broader spectrum of food matrix types and additional properties that may influence bioaccessibility. Conclusions: This research sheds light on the intricate interplay between food matrix composition and the bioaccessibility of curcuminoids. This study lays a foundation for future investigations, offering a promising avenue for advancing our understanding of bioactive compound bioaccessibility and its implications for the food industry and informed consumer choices.

Keywords: bioactive bioaccessibility, food formulation, food matrix, machine learning, probabilistic modelling

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Authors: Mehwish Jamil Noor

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Morphological features of pollen (sculpturing) were useful for identification of different floral taxa. In this study 49 pollen grains, types belonging to 25 families were studied using Scanning Electron Microscope. Shape and sculpturing of pollen ranging from Psilate, scabrate to reticulate, bireticulate and echinolophate. Honey pollen was identified using morphological features, number and arrangement of pore and colpi, size and shape. It presents the first attempt from Pakistan involving extraction of pollen from honey, its identification and taxonomic analysis. Among pollen studied diversity in shape and sculpturing has been observed ranging from Psilate, scabrate to reticulate to bireticulate and echinolophate condition. Pollen has been identified with the help of morphological feature, number and arrangement of pore and colpi, size and shape, reference slides, light microscopic data and previous literature have been consulted for pollen identification. Pollen of closely related species resemble each other therefore pollen identification of airborne and honey pollen is not possible till species level. Survey of flora was carried in parallel to keep the record about the allergenic and melliferous preference of specific sites through surveys and interviews. Their pollination season and geographical distribution were recorded. Two hundred and five including wild and cultivated taxa were identified belonging to sixty-seven families. Major bee attracting wild shrub and trees includes Justicia adhatoda, Acacia nilotica, Ziziphus jujuba, Taraxicum officinalis, Artemisia dubia, Casuarina sp., Ulmus sp., Broussonetia papyrifera, Cupressus sp. or Pinus roxburghii etc. Cultivated crops like Pennisetum typhoides, Nigella sativa, Triticum sativum along with fruit trees of Pyrus, Prunus, Eryobotria, Citrus etc. are popular melliferous floras. Exotic/ introduced species like Eucalyptus or Parthenium hysterophorus, are also frequently visited by bees indicating the significance of those plants in the honey industry. It is concluded that different microscopic analysis techniques give more clear and authentic pictures of and melliferous pollen identification which is well supported by the floral calendar. The diversity of pollen are observed in case of melliferous pollen, and most of the windborne pollen were found less sculptured or psilate expressing the adaptation to the specific mode of pollination. Pollen morphology and sculpturing would serve as a reference for future studies.

Keywords: pollen, allergenic flora, sem, pollen key, Scanning Electron Microscopy (SEM)

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Authors: Vincent Andrew Cappellano

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In the early phases of critical infrastructure system design, translating distributed computing requirements to an architecture has risk given the multitude of approaches (e.g., cloud, edge, fog). In many systems, a single requirement for system uptime / availability is used to encompass the system’s intended operations. However, when architected systems may perform to those availability requirements only during normal operations and not during component failure, or during outages caused by adversary attacks on critical infrastructure (e.g., physical, cyber). System designers lack a structured method to evaluate availability requirements against candidate system architectures through deep degradation scenarios (i.e., normal ops all the way down to significant damage of communications or physical nodes). This increases risk of poor selection of a candidate architecture due to the absence of insight into true performance for systems that must operate as a piece of critical infrastructure. This research effort proposes a process to analyze critical infrastructure system availability requirements and a candidate set of systems architectures, producing a metric assessing these architectures over a spectrum of degradations to aid in selecting appropriate resilient architectures. To accomplish this effort, a set of simulation and evaluation efforts are undertaken that will process, in an automated way, a set of sample requirements into a set of potential architectures where system functions and capabilities are distributed across nodes. Nodes and links will have specific characteristics and based on sampled requirements, contribute to the overall system functionality, such that as they are impacted/degraded, the impacted functional availability of a system can be determined. A machine learning reinforcement-based agent will structurally impact the nodes, links, and characteristics (e.g., bandwidth, latency) of a given architecture to provide an assessment of system functional uptime/availability under these scenarios. By varying the intensity of the attack and related aspects, we can create a structured method of evaluating the performance of candidate architectures against each other to create a metric rating its resilience to these attack types/strategies. Through multiple simulation iterations, sufficient data will exist to compare this availability metric, and an architectural recommendation against the baseline requirements, in comparison to existing multi-factor computing architectural selection processes. It is intended that this additional data will create an improvement in the matching of resilient critical infrastructure system requirements to the correct architectures and implementations that will support improved operation during times of system degradation due to failures and infrastructure attacks.

Keywords: architecture, resiliency, availability, cyber-attack

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Authors: Ameni Mejri, Moufida Hajjaj, Salem Hasnaoui, Ridha Bouallegue

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The technology advances have most lately made the millimeter wave (mmWave) communication possible. Due to the huge amount of spectrum that is available in MmWave frequency bands, this promising candidate is considered as a key technology for the deployment of 5G cellular networks. In order to enhance system capacity and achieve spectral efficiency, very large antenna arrays are employed at mmWave systems by exploiting array gain. However, it has been shown that conventional beamforming strategies are not suitable for mmWave hardware implementation. Therefore, new features are required for mmWave cellular applications. Unlike traditional multiple-input-multiple-output (MIMO) systems for which only digital precoders are essential to accomplish precoding, MIMO technology seems to be different at mmWave because of digital precoding limitations. Moreover, precoding implements a greater number of radio frequency (RF) chains supporting more signal mixers and analog-to-digital converters. As RF chain cost and power consumption is increasing, we need to resort to another alternative. Although the hybrid precoding architecture has been regarded as the best solution based on a combination between a baseband precoder and an RF precoder, we still do not get the optimal design of hybrid precoders. According to the mapping strategies from RF chains to the different antenna elements, there are two main categories of hybrid precoding architecture. Given as a hybrid precoding sub-array architecture, the partially-connected structure reduces hardware complexity by using a less number of phase shifters, whereas it sacrifices some beamforming gain. In this paper, we treat the hybrid precoder design in mmWave MIMO systems as a problem of matrix factorization. Thus, we adopt the alternating minimization principle in order to solve the design problem. Further, we present our proposed algorithm for the partially-connected structure, which is based on the iterative hard thresholding method. Through simulation results, we show that our hybrid precoding algorithm provides significant performance gains over existing algorithms. We also show that the proposed approach reduces significantly the computational complexity. Furthermore, valuable design insights are provided when we use the proposed algorithm to make simulation comparisons between the hybrid precoding partially-connected structure and the fully-connected structure.

Keywords: alternating minimization, hybrid precoding, iterative hard thresholding, low-complexity, millimeter wave communication, partially-connected structure

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Authors: Rafael Castilho Carvalho, Edjair de Souza Mota

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As the largest contributor to the biogeochemical functioning of the Earth system, the Amazon Rainforest has the greatest biodiversity on the planet, harboring about 15% of all the world's flora. Recognition and preservation are the focus of research that seeks to mitigate drastic changes, especially anthropic ones, which irreversibly affect this biome. Functional and low-cost monitoring alternatives to reduce these impacts are a priority, such as those using technologies such as Low Power Wide Area Networks (LPWAN). Promising, reliable, secure and with low energy consumption, LPWAN can connect thousands of IoT devices, and in particular, LoRa is considered one of the most successful solutions to facilitate forest monitoring applications. Despite this, the forest environment, in particular the Amazon Rainforest, is a challenge for these technologies, requiring work to identify and validate the use of technology in a real environment. To investigate the feasibility of deploying LPWAN in remote water quality monitoring of rivers in the Amazon Region, a LoRa-based test bed consisting of a Lora transmitter and a LoRa receiver was set up, both parts were implemented with Arduino and the LoRa chip SX1276. The experiment was carried out at the Federal University of Amazonas, which contains one of the largest urban forests in Brazil. There are several springs inside the forest, and the main goal is to collect water quality parameters and transmit the data through the forest in real time to the gateway at the uni. In all, there are nine water quality parameters of interest. Even with a high collection frequency, the amount of information that must be sent to the gateway is small. However, for this application, the battery of the transmitter device is a concern since, in the real application, the device must run without maintenance for long periods of time. With these constraints in mind, parameters such as Spreading Factor (SF) and Coding Rate (CR), different antenna heights, and distances were tuned to better the connectivity quality, measured with RSSI and loss rate. A handheld spectrum analyzer RF Explorer was used to get the RSSI values. Distances exceeding 200 m have soon proven difficult to establish communication due to the dense foliage and high humidity. The optimal combinations of SF-CR values were 8-5 and 9-5, showing the lowest packet loss rates, 5% and 17%, respectively, with a signal strength of approximately -120 dBm, these being the best settings for this study so far. The rains and climate changes imposed limitations on the equipment, and more tests are already being conducted. Subsequently, the range of the LoRa configuration must be extended using a mesh topology, especially because at least three different collection points in the same water body are required.

Keywords: IoT, LPWAN, LoRa, coverage, loss rate, forest

Procedia PDF Downloads 52

Authors: Dana R. Thomson, Catherine Linard, Sabine Vanhuysse, Jessica E. Steele, Michal Shimoni, Jose Siri, Waleska Caiaffa, Megumi Rosenberg, Eleonore Wolff, Tais Grippa, Stefanos Georganos, Helen Elsey

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The Sustainable Development Goals (SDGs) and Urban Health Equity Assessment and Response Tool (Urban HEART) identify dozens of key indicators to help local decision-makers prioritize and track inequalities in health outcomes. However, presentations and discussions at the International Conference on Urban Health (ICUH) 2017 suggested that additional indicators are needed to make decisions and policies. A local decision-maker may realize that malaria or road accidents are a top priority. However, s/he needs additional health determinant indicators, for example about standing water or traffic, to address the priority and reduce inequalities. Health determinants reflect the physical and social environments that influence health outcomes often at community- and societal-levels and include such indicators as access to quality health facilities, access to safe parks, traffic density, location of slum areas, air pollution, social exclusion, and social networks. Indicator identification and disaggregation are necessarily constrained by available datasets – typically collected about households and individuals in surveys, censuses, and administrative records. Continued advancements in earth observation, data storage, computing and mobile technologies mean that new sources of health determinants indicators derived from 'big data' are becoming available at fine geographic scale. Big data includes high-resolution satellite imagery and aggregated, anonymized mobile phone data. While big data are themselves not representative of the population (e.g., satellite images depict the physical environment), they can provide information about population density, wealth, mobility, and social environments with tremendous detail and accuracy when combined with population-representative survey, census, administrative and health system data. The aim of this paper is to (1) flag to data scientists important indicators needed by health decision-makers at the city and sub-city scale - ideally free and publicly available, and (2) summarize for local decision-makers new datasets that can be generated from big data, with layperson descriptions of difficulties in generating them. We include SDGs and Urban HEART indicators, as well as indicators mentioned by decision-makers attending ICUH 2017.

Keywords: health determinant, health outcome, mobile phone, remote sensing, satellite imagery, SDG, urban HEART

Procedia PDF Downloads 178

Authors: Ramin Mehdiabadi, Neda Menbari, Mohammad Nazir Menbari

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As a pressing public health concern, breast cancer stands as the predominant oncological diagnosis and principal cause of cancer-related mortality among women globally, accounting for 11.7% of new cancer incidences and 6.9% of cancer-related deaths. The annual figures indicate that approximately 230,480 women are diagnosed with breast cancer in the United States alone, with 39,520 succumbing to the disease. While developed economies have reported a deceleration in both incidence and mortality rates across various forms of cancer, including breast cancer, emerging and low-income economies manifest a contrary escalation, largely attributable to lifestyle-mediated risk factors such as tobacco usage, physical inactivity, and high caloric intake. Breast cancer is distinctly characterized by molecular heterogeneity, manifesting in specific subtypes delineated by biomarkers—Estrogen Receptors (ER), Progesterone Receptors (PR), and Human Epidermal Growth Factor Receptor 2 (HER2). These subtypes, comprising Luminal A, Luminal B, HER2-enriched, triple-negative/basal-like, and normal-like, necessitate nuanced, subtype-specific therapeutic regimens, thereby challenging the applicability of generalized treatment protocols. Within this molecular complexity, the transcription factor Forkhead Box M1 (FoxM1) has garnered attention as a significant driver of cellular proliferation, tumorigenesis, metastatic progression, and treatment resistance in a spectrum of human malignancies, including breast cancer. Concurrently, microRNAs (miRs), specifically miR-216b-5p, have been identified as post-transcriptional gene expression regulators and potential tumor suppressors. The overarching objective of this academic investigation is to explicate the multifaceted interrelationship between FoxM1 and miR-216b-5p across the disparate molecular subtypes of breast cancer. Employing a methodologically rigorous, interdisciplinary research design that incorporates cutting-edge molecular biology techniques, sophisticated bioinformatics analytics, and exhaustive meta-analyses of extant clinical data, this scholarly endeavor aims to unveil novel biomarker-specific therapeutic pathways. By doing so, this research is positioned to make a seminal contribution to the advancement of personalized, efficacious, and minimally toxic treatment paradigms, thus profoundly impacting the global efforts to ameliorate the burden of breast cancer.

Keywords: breast cancer, fox m1, microRNAs, mir-216b-5p, gene expression

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Authors: Anne Giles

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Humans naturally wish they could forget traumatic experiences. To help prevent future harm, however, the human brain has evolved to retain data about experiences of threat, alarm, or violation. When given compassionate support and assistance with thinking helpfully and realistically about traumatic events, most people can adjust to experiencing hardships, albeit with residual sad, unfortunate memories. Persistent, recurrent, intrusive memories, difficulty sleeping, emotion dysregulation, and avoidance of reminders, however, may be symptoms of Post-traumatic Stress Disorder (PTSD). Brain scans show that PTSD affects brain functioning. We currently have no physical means of restoring the system of brain structures and functions involved with PTSD. Medications may ease some symptoms but not others. However, forms of "talk therapy" with cognitive components have been found by researchers to reduce, even resolve, a broad spectrum of trauma symptoms. Many cultures have taboos against talking about hardships. Individuals may present themselves to mental health care professionals with severe, disabling trauma symptoms but, because of cultural norms, be unable to speak about them. In China, for example, relationship expectations may include the belief, "Bad things happening in the family should stay in the family (jiāchǒu bùkě wàiyán 家丑不可外扬)." The concept of "family (jiā 家)" may include partnerships, close and extended families, communities, companies, and the nation itself. In contrast to many trauma therapies, Cognitive Processing Therapy (CPT) for Post-traumatic Stress Disorder asks its participants to focus not on "what" happened but on "why" they think the trauma(s) occurred. The question "why" activates and exercises cognitive functioning. Brain scans of individuals with PTSD reveal executive functioning portions of the brain inadequately active, with emotion centers overly active. CPT conceptualizes PTSD as a network of cognitive distortions that keep an individual "stuck" in this under-functioning and over-functioning dynamic. Through asking participants forms of the question "why," plus offering a protocol for examining answers and relinquishing unhelpful beliefs, CPT assists individuals in consciously reactivating the cognitive, executive functions of their brains, thus restoring normal functioning and reducing distressing trauma symptoms. The culturally sensitive components of CPT that allow people to "talk about it without talking about it" may offer the possibility for worldwide relief from symptoms of trauma.

Keywords: cognitive processing therapy (CPT), cultural norms, post-traumatic stress disorder (PTSD), trauma recovery

Procedia PDF Downloads 177

Authors: A. Alyaaria, b, J. P. Wignerona, A. Ducharneb, Y. Kerrc, P. de Rosnayd, R. de Jeue, A. Govinda, A. Al Bitarc, C. Albergeld, J. Sabaterd, C. Moisya, P. Richaumec, A. Mialonc

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Global Level-3 surface soil moisture (SSM) maps from the passive microwave soil moisture and Ocean Salinity satellite (SMOSL3) have been released. To further improve the Level-3 retrieval algorithm, evaluation of the accuracy of the spatio-temporal variability of the SMOS Level 3 products (referred to here as SMOSL3) is necessary. In this study, a comparative analysis of SMOSL3 with a SSM product derived from the observations of the Advanced Microwave Scanning Radiometer (AMSR-E) computed by implementing the Land Parameter Retrieval Model (LPRM) algorithm, referred to here as AMSRM, is presented. The comparison of both products (SMSL3 and AMSRM) were made against SSM products produced by a numerical weather prediction system (SM-DAS-2) at ECMWF (European Centre for Medium-Range Weather Forecasts) for the 03/2010-09/2011 period at global scale. The latter product was considered here a 'reference' product for the inter-comparison of the SMOSL3 and AMSRM products. Three statistical criteria were used for the evaluation, the correlation coefficient (R), the root-mean-squared difference (RMSD), and the bias. Global maps of these criteria were computed, taking into account vegetation information in terms of biome types and Leaf Area Index (LAI). We found that both the SMOSL3 and AMSRM products captured well the spatio-temporal variability of the SM-DAS-2 SSM products in most of the biomes. In general, the AMSRM products overestimated (i.e., wet bias) while the SMOSL3 products underestimated (i.e., dry bias) SSM in comparison to the SM-DAS-2 SSM products. In term of correlation values, the SMOSL3 products were found to better capture the SSM temporal dynamics in highly vegetated biomes ('Tropical humid', 'Temperate Humid', etc.) while best results for AMSRM were obtained over arid and semi-arid biomes ('Desert temperate', 'Desert tropical', etc.). When removing the seasonal cycles in the SSM time variations to compute anomaly values, better correlation with the SM-DAS-2 SSM anomalies were obtained with SMOSL3 than with AMSRM, in most of the biomes with the exception of desert regions. Eventually, we showed that the accuracy of the remotely sensed SSM products is strongly related to LAI. Both the SMOSL3 and AMSRM (slightly better) SSM products correlate well with the SM-DAS2 products over regions with sparse vegetation for values of LAI < 1 (these regions represent almost 50% of the pixels considered in this global study). In regions where LAI>1, SMOSL3 outperformed AMSRM with respect to SM-DAS-2: SMOSL3 had almost consistent performances up to LAI = 6, whereas AMSRM performance deteriorated rapidly with increasing values of LAI.

Keywords: remote sensing, microwave, soil moisture, AMSR-E, SMOS

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Authors: Yunhan Zhang, Xiaopeng Li, Zhongxiao Peng

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Additive manufacturing (AM) possesses several key characteristics, including high design freedom, energy-efficient manufacturing process, reduced material waste, high resolution of finished products, and excellent performance of finished products. These advantages have garnered widespread attention and fueled rapid development in recent decades. AM has significantly broadened the spectrum of available materials in the manufacturing industry and is gradually replacing some traditionally manufactured parts. Similar to components produced via traditional methods, products manufactured through AM are susceptible to degradation caused by wear during their service life. Given the prevalence of 316L stainless steel (SS) parts and the limited research on the tribological behavior of 316L SS samples or products fabricated using AM technology, this study aims to investigate the degradation process and wear mechanisms of 316L SS disks fabricated using AM technology. The wear mechanisms and tribological performance of these AM-manufactured samples are compared with commercial 316L SS samples made using conventional methods. Additionally, methods to enhance the tribological performance of additive-manufactured SS samples are explored. Four disk samples with a diameter of 75 mm and a thickness of 10 mm are prepared. Two of them (Group A) are prepared from a purchased SS bar using a milling method. The other two disks (Group B), with the same dimensions, are made of Gas Atomized 316L Stainless Steel (size range: 15-45 µm) purchased from Carpenter Additive and produced using Laser Powder Bed Fusion (LPBF). Pin-on-disk tests are conducted on these disks, which have similar surface roughness and hardness levels. Multiple tests are carried out under various operating conditions, including varying loads and/or speeds, and the friction coefficients are measured during these tests. In addition, the evolution of the surface degradation processes is monitored by creating moulds of the wear tracks and quantitatively analyzing the surface morphologies of the mould images. This analysis involves quantifying the depth and width of the wear tracks and analyzing the wear debris generated during the wear processes. The wear mechanisms and wear performance of these two groups of SS samples are compared. The effects of load and speed on the friction coefficient and wear rate are investigated. The ultimate goal is to gain a better understanding of the surface degradation of additive-manufactured SS samples. This knowledge is crucial for enhancing their anti-wear performance and extending their service life.

Keywords: degradation process, additive manufacturing, stainless steel, surface features

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Authors: Kyohei Yoshino, Masahiko Matsumiya, Yuji Sasaki

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Recently, studies have been conducted on Au(III) extraction using ionic liquids (ILs) as extractants or diluents. ILs such as piperidinium, pyrrolidinium, and pyridinium have been studied as extractants for noble metal extractions. Furthermore, the polarity, hydrophobicity, and solvent miscibility of these ILs can be adjusted depending on their intended use. Therefore, the unique properties of ILs make them functional extraction media. The extraction mechanism of Au(III) using phosphonium-based ILs and relevant thermodynamic studies are yet to be reported. In the present work, we focused on the mechanism of Au(III) extraction and related thermodynamic analyses using phosphonium-based ILs. Triethyl-n-pentyl, triethyl-n-octyl, and triethyl-n-dodecyl phosphonium bis(trifluoromethyl-sulfonyl)amide, [P₂₂₂ₓ][NTf₂], (X = 5, 8, and 12) were investigated for Au(III) extraction. The IL–Au complex was identified as [P₂₂₂₅][AuCl₄] using UV–Vis–NIR and Raman spectroscopic analyses. The extraction behavior of Au(III) was investigated with a change in the [P₂₂₂ₓ][NTf₂]IL concentration from 1.0 × 10–4 to 1.0 × 10–1 mol dm−3. The results indicate that Au(III) can be easily extracted by the anion-exchange reaction in the [P₂₂₂ₓ][NTf₂]IL. The slope range 0.96–1.01 on the plot of log D vs log[P₂₂₂ₓ][NTf2]IL indicates the association of one mole of IL with one mole of [AuCl4−] during extraction. Consequently, [P₂₂₂ₓ][NTf₂] is an anion-exchange extractant for the extraction of Au(III) in the form of anions from chloride media. Thus, this type of phosphonium-based IL proceeds via an anion exchange reaction with Au(III). In order to evaluate the thermodynamic parameters on the Au(III) extraction, the equilibrium constant (logKₑₓ’) was determined from the temperature dependence. The plot of the natural logarithm of Kₑₓ’ vs the inverse of the absolute temperature (T–1) yields a slope proportional to the enthalpy (ΔH). By plotting T–1 vs lnKₑₓ’, a line with a slope range 1.129–1.421 was obtained. Thus, the result indicated that the extraction reaction of Au(III) using the [P₂₂₂ₓ][NTf₂]IL (X=5, 8, and 12) was exothermic (ΔH=-9.39〜-11.81 kJ mol-1). The negative value of TΔS (-4.20〜-5.27 kJ mol-1) indicates that microscopic randomness is preferred in the [P₂₂₂₅][NTf₂]IL extraction system over [P₂₂₂₁₂][NTf₂]IL. The total negative alternation in Gibbs energy (-5.19〜-6.55 kJ mol-1) for the extraction reaction would thus be relatively influenced by the TΔS value on the number of carbon atoms in the alkyl side length, even if the efficiency of ΔH is significantly influenced by the total negative alternations in Gibbs energy. Electrochemical analysis revealed that extracted Au(III) can be reduced in two steps: (i) Au(III)/Au(I) and (ii) Au(I)/Au(0). The diffusion coefficients of the extracted Au(III) species in [P₂₂₂ₓ][NTf₂] (X = 5, 8, and 12) were evaluated from 323 to 373 K using semi-integral and semi-differential analyses. Because of the viscosity of the IL medium, the diffusion coefficient of the extracted Au(III) increases with increasing alkyl chain length. The 4f7/2 spectrum based on X-ray photoelectron spectroscopy revealed that the Au electrodeposits obtained after 10 cycles of continuous extraction and electrodeposition were in the metallic state.

Keywords: au(III), electrodeposition, phosphonium-based ionic liquids, solvent extraction

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Authors: Zheng Wang, Zhenhong Li, Jon Mills

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Ground-based synthetic aperture radar (GBSAR) represents a powerful remote sensing tool for deformation monitoring towards various geohazards, e.g. landslides, mudflows, avalanches, infrastructure failures, and the subsidence of residential areas. Unlike spaceborne SAR with a fixed revisit period, GBSAR data can be acquired with an adjustable temporal resolution through either continuous or discontinuous operation. However, challenges arise from processing high temporal-resolution continuous GBSAR data, including the extreme cost of computational random-access-memory (RAM), the delay of displacement maps, and the loss of temporal evolution. Moreover, repositioning errors between discontinuous campaigns impede the accurate measurement of surface displacements. Therefore, a versatile package with two complete chains is developed in this study in order to process both continuous and discontinuous GBSAR data and address the aforementioned issues. The first chain is based on a small-baseline subset concept and it processes continuous GBSAR images unit by unit. Images within a window form a basic unit. By taking this strategy, the RAM requirement is reduced to only one unit of images and the chain can theoretically process an infinite number of images. The evolution of surface displacements can be detected as it keeps temporarily-coherent pixels which are present only in some certain units but not in the whole observation period. The chain supports real-time processing of the continuous data and the delay of creating displacement maps can be shortened without waiting for the entire dataset. The other chain aims to measure deformation between discontinuous campaigns. Temporal averaging is carried out on a stack of images in a single campaign in order to improve the signal-to-noise ratio of discontinuous data and minimise the loss of coherence. The temporal-averaged images are then processed by a particular interferometry procedure integrated with advanced interferometric SAR algorithms such as robust coherence estimation, non-local filtering, and selection of partially-coherent pixels. Experiments are conducted using both synthetic and real-world GBSAR data. Displacement time series at the level of a few sub-millimetres are achieved in several applications (e.g. a coastal cliff, a sand dune, a bridge, and a residential area), indicating the feasibility of the developed GBSAR data processing package for deformation monitoring of a wide range of scientific and practical applications.

Keywords: ground-based synthetic aperture radar, interferometry, small baseline subset algorithm, deformation monitoring

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Authors: Sulalit Bandyopadhyay, Muhammad Awais Ashfaq Alvi, Anuvansh Sharma, Wilhelm R. Glomm

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Release of drugs from nanogels and nanogel-based systems can occur under the influence of external stimuli like temperature, pH, magnetic fields and so on. pNIPAm-AAc nanogels respond to the combined action of both temperature and pH, the former being mostly determined by hydrophilic-to-hydrophobic transitions above the volume phase transition temperature (VPTT), while the latter is controlled by the degree of protonation of the carboxylic acid groups. These nanogels based systems are promising candidates in the field of drug delivery. Combining nanogels with magneto-plasmonic nanoparticles (NPs) introduce imaging and targeting modalities along with stimuli-response in one hybrid system, thereby incorporating multifunctionality. Fe@Au core-shell NPs possess optical signature in the visible spectrum owing to localized surface plasmon resonance (LSPR) of the Au shell, and superparamagnetic properties stemming from the Fe core. Although there exist several synthesis methods to control the size and physico-chemical properties of pNIPAm-AAc nanogels, yet, there is no comprehensive study that highlights the dependence of incorporation of one or more layers of NPs to these nanogels. In addition, effective determination of volume phase transition temperature (VPTT) of the nanogels is a challenge which complicates their uses in biological applications. Here, we have modified the swelling-collapse properties of pNIPAm-AAc nanogels, by combining with Fe@Au NPs using different solution based methods. The hydrophilic-hydrophobic transition of the nanogels above the VPTT has been confirmed to be reversible. Further, an analytical method has been developed to deduce the average VPTT which is found to be 37.3°C for the nanogels and 39.3°C for nanogel coated Fe@Au NPs. An opposite swelling –collapse behaviour is observed for the latter where the Fe@Au NPs act as bridge molecules pulling together the gelling units. Thereafter, Cyt C, a model protein drug and L-Dopa, a drug used in the clinical treatment of Parkinson’s disease were loaded separately into the nanogels and nanogel coated Fe@Au NPs, using a modified breathing-in mechanism. This gave high loading and encapsulation efficiencies (L Dopa: ~9% and 70µg/mg of nanogels, Cyt C: ~30% and 10µg/mg of nanogels respectively for both the drugs. The release kinetics of L-Dopa, monitored using UV-vis spectrophotometry was observed to be rather slow (over several hours) with highest release happening under a combination of high temperature (above VPTT) and acidic conditions. However, the release of L-Dopa from nanogel coated Fe@Au NPs was the fastest, accounting for release of almost 87% of the initially loaded drug in ~30 hours. The chemical structure of the drug, drug incorporation method, location of the drug and presence of Fe@Au NPs largely alter the drug release mechanism and the kinetics of these nanogels and Fe@Au NPs coated with nanogels.

Keywords: controlled release, nanogels, volume phase transition temperature, l-dopa

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Authors: Elena Maria Scalisi, Roberta Pecoraro, Martina Contino, Sara Ignoto, Carmelo Iaria, Santi Concetto Pavone, Gino Sorbello, Loreto Di Donato, Maria Violetta Brundo

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5G Technology is evolving to satisfy a variety of service requirements that may allow high data-rate connections (1Gbps) and lower latency times than current (<1ms). In order to support a high data transmission speed and a high traffic service for eMBB (enhanced mobile broadband) use cases, 5G systems have the characteristic of using different frequency bands of the radio wave spectrum (700 MHz, 3.6-3.8 GHz and 26.5-27.5 GHz), thus taking advantage of higher frequencies than previous mobile radio generations (1G-4G). However, waves at higher frequencies have a lower capacity to propagate in free space and therefore, in order to guarantee the capillary coverage of the territory for high reliability applications, it will be necessary to install a large number of repeaters. Following the introduction of this new technology, there has been growing concern over the past few months about possible harmful effects on human health. The aim of this preliminary study is to evaluate possible short term effects induced by 5G-millimeter waves on embryonic development and early life stages of Danio rerio by Z-FET. We exposed developing zebrafish at frequency of 27 GHz, with a standard pyramidal horn antenna placed at 15 cm far from the samples holder ensuring an incident power density of 10 mW/cm2. During the exposure cycle, from 6 h post fertilization (hpf) to 96 hpf, we measured a different morphological endpoints every 24 hours. Zebrafish embryo toxicity test (Z-FET) is a short term test, carried out on fertilized eggs of zebrafish and it represents an effective alternative to acute test with adult fish (OECD, 2013). We have observed that 5G did not reveal significant impacts on mortality nor on morphology because exposed larvae showed a normal detachment of the tail, presence of heartbeat, well-organized somites, therefore hatching rate was lower than untreated larvae even at 48 h of exposure. Moreover, the immunohistochemical analysis performed on larvae showed a negativity to the HSP-70 expression used as a biomarkers. This is a preliminary study on evaluation of potential toxicity induced by 5G and it seems appropriate to underline the importance that further studies would take, aimed at clarifying the probable real risk of exposure to electromagnetic fields.

Keywords: Biomarker of exposure, embryonic development, 5G waves, zebrafish embryo toxicity test

Procedia PDF Downloads 96

Authors: M. Chukhryaeva, R. Skhalyakho, J. Kagazegeva, E. Pocheshkhova, L. Yepiskopossyan, O. Balanovsky, E. Balanovska

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The Middle East is crossroad of different populations at different times. The Kurds are of particular interest in this region. Historical sources suggested that the origin of the Kurds is associated with Medes. Therefore, it was especially interesting to compare gene pool of Kurds with other supposed descendants of Medes-Tats. Yezidis are ethno confessional group of Kurds. Yezidism as a confessional teaching was formed in the XI-XIII centuries in Iraq. Yezidism has caused reproductively isolation of Yezidis from neighboring populations for centuries. Also, isolation helps to retain Yezidian caste system. It is unknown how the history of Yezidis affected its genу pool because it has never been the object of researching. We have examined the Y-chromosome variation in Yezidis and Kurdish males to understand their gene pool. We collected DNA samples from 90 Yezidi males and 24 Kurdish males together with their pedigrees. We performed Y-STR analysis of 17 loci in the samples collected (Yfiler system from Applied Biosystems) and analysis of 42 Y-SNPs by real-time PCR. We compared our data with published data from other Kurdish groups and from European, Caucasian, and West Asian populations. We found that gene pool of Yezidis contains haplogroups common in the Middle East (J-M172(xM67,M12)- 24%, E-M35(xM78)- 9%) and in South Western Asia (R-M124- 8%) and variant with wide distribution area - R-M198(xM458- 9%). The gene pool of Kurdish has higher genetic diversity than Yezidis. Their dominants haplogroups are R-M198- 20,3 %, E-M35- 9%, J-M172- 9%. Multidimensional scaling also shows that the Kurds and Yezidis are part of the same frontier Asian cluster, which, in addition, included Armenians, Iranians, Turks, and Greeks. At the same time, the peoples of the Caucasus and Europe form isolated clusters that do not overlap with the Asian clusters. It is noteworthy that Kurds from our study gravitate towards Tats, which indicates that most likely these two populations are descendants of ancient Medes population. Multidimensional scaling also reveals similarity between gene pool of Yezidis, Kurds with Armenians and Iranians. The analysis of Yezidis pedigrees and their STR variability did not reveal a reliable connection between genetic diversity and caste system. This indicates that the Yezidis caste system is a social division and not a biological one. Thus, we showed that, despite many years of isolation, the gene pool of Yezidis retained a common layer with the gene pool of Kurds, these populations have common spectrum of haplogroups, but Yezidis have lower genetic diversity than Kurds. This study received primary support from the RSF grant No. 16-36-00122 to MC and grant No. 16-06-00364 to EP.

Keywords: gene pool, haplogroup, Kurds, SNP and STR markers, Yezidis

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Authors: Irina Veselova, Maria Makedonskaya, Olga Eremina, Alexandr Sidorov, Eugene Goodilin, Tatyana Shekhovtsova

Abstract:

Such catecholamines as dopamine, norepinephrine, and epinephrine are the principal neurotransmitters in the sympathetic nervous system. Catecholamines and their metabolites are considered to be important markers of socially significant diseases such as atherosclerosis, diabetes, coronary heart disease, carcinogenesis, Alzheimer's and Parkinson's diseases. Currently, neurotransmitters can be studied via electrochemical and chromatographic techniques that allow their characterizing and quantification, although these techniques can only provide crude spatial information. Besides, the difficulty of catecholamine determination in biological materials is associated with their low normal concentrations (~ 1 nM) in biomaterials, which may become even one more order lower because of some disorders. In addition, in blood they are rapidly oxidized by monoaminooxidases from thrombocytes and, for this reason, the determination of neurotransmitter metabolism indicators in an organism should be very rapid (15—30 min), especially in critical states. Unfortunately, modern instrumental analysis does not offer a complex solution of this problem: despite its high sensitivity and selectivity, HPLC-MS cannot provide sufficiently rapid analysis, while enzymatic biosensors and immunoassays for the determination of the considered analytes lack sufficient sensitivity and reproducibility. Fluorescent and SERS-sensors remain a compelling technology for approaching the general problem of selective neurotransmitter detection. In recent years, a number of catecholamine sensors have been reported including RNA aptamers, fluorescent ribonucleopeptide (RNP) complexes, and boronic acid based synthetic receptors and the sensor operated in a turn-off mode. In this work we present the fluorescent and SERS turn-on sensor systems based on the bio- or chemorecognizing nanostructured films {chitosan/collagen-Tb/Eu/Cu-nanoparticles-indicator reagents} that provide the selective recognition, visualization, and sensing of the above mentioned catecholamines on the level of nanomolar concentrations in biomaterials (cell cultures, tissue etc.). We have (1) developed optically transparent porous films and gels of chitosan/collagen; (2) ensured functionalization of the surface by molecules-'recognizers' (by impregnation and immobilization of components of the indicator systems: biorecognizing and auxiliary reagents); (3) performed computer simulation for theoretical prediction and interpretation of some properties of the developed materials and obtained analytical signals in biomaterials. We are grateful for the financial support of this research from Russian Foundation for Basic Research (grants no. 15-03-05064 a, and 15-29-01330 ofi_m).

Keywords: biomaterials, fluorescent and SERS-recognition, neurotransmitters, solid-phase turn-on sensor system

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Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

Abstract:

To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

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Authors: Muhammad Ather Nadeem, Bilal Ahmad Khan, Hussam F. Najeeb Alawadi, Athar Mahmood, Aneela Nijabat, Tasawer Abbas, Muhammad Habib, Abdullah

Abstract:

The global prevalence of Avena fatua infestation poses a significant challenge to wheat sustainability. While chemical control stands out as an efficient and rapid way to control weeds, concerns over developing resistance in weeds and environmental pollution have led to criticisms of herbicide use. Consequently, this study was designed to address these challenges through the chemical synthesis, characterization, and optimization of chitosan-based nanoparticles containing clodinofop Propargyl and fenoxaprop-P-ethyl for the effective management of A. fatua. Utilizing the ionic gelification technique, chitosan-based nanoparticles of clodinofop Propargyl and fenoxaprop-P-ethyl were prepared. These nanoparticles were applied at the 3-4 leaf stage of Phalaris minor weed, applying seven altered doses. These nanoparticles were applied at the 3-4 leaf stage of Phalaris minor weed, applying seven altered doses (D0 (Check weeds), D1 (Recommended dose of traditional-herbicide (TH), D2 (Recommended dose of Nano-herbicide (NPs-H)), D3 (NPs-H with 05-fold lower dose), D4 ((NPs-H) with 10-fold lower dose), D5 (NPs-H with 15-fold lower dose), and D6 (NPs-H with 20-fold lower dose)). Characterization of the chitosan-containing herbicide nanoparticles (CHT-NPs) was conducted using FT-IR analysis, demonstrating a perfect match with standard parameters. UV–visible spectrum further revealed absorption peaks at 310 nm for NPs of clodinofop propargyl and at 330 nm for NPs of fenoxaprop-p-ethyl. This research aims to contribute to sustainable weed management practices by addressing the challenges associated with chemical herbicide use. The application of chitosan-based nanoparticles (CHT-NPs) containing fenoxaprop-P-ethyl and clodinofop-propargyl at the recommended dose of the standard herbicide resulted in 100% mortality and visible injury to weeds. Surprisingly, when applied at a lower dose with 5-folds, these chitosan-containing nanoparticles of clodinofop Propargyl and fenoxaprop-P-ethyl demonstrated extreme control efficacy. Furthermore, at a 10-fold lower dose compared to standard herbicides and the recommended dose of clodinofop-propargyl and fenoxaprop-P-ethyl, the chitosan-based nanoparticles exhibited comparable effects on chlorophyll content, visual injury (%), mortality (%), plant height (cm), fresh weight (g), and dry weight (g) of A. fatua. This study indicates that chitosan/tripolyphosphate-loaded nanoparticles containing clodinofop-propargyl and fenoxaprop-P-ethyl can be effectively utilized for the management of A. fatua at a 10-fold lower dose, highlighting their potential for sustainable and efficient weed control.

Keywords: mortality, chitosan-based nanoparticles, visual injury, chlorophyl contents, 5-fold lower dose.

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