Abstract Jute is classified as a bast fibre crop which is one of the most important natural fibre crops. Jute fibre is both economical and environmentally friendly and it can be utilized for minimizing the use of synthetic fibres. For the quality improvement of jute fibre, the molecular study of the genes linked with the fibre biogenesis is crucial. RNA isolation is a fundamental step for gene expression and transcriptomic studies of jute fibre. RNA isolation is restricted from jute especially from the well-developed bark tissues because it is rich in mucilage, polysaccharides, and phenolic compounds. In this study, a new method was optimized for extracting the total RNA from the field-grown bark tissues of two tossa jute varieties at 30 and 60 Days-After-Germination (DAG). Two-times use of CTAB extraction buffer with SDS and later addition of TRIZOL made the protocol simple, cost effective and minimal time consuming as compared to other methods. The A260/A280 value ranged between 1.99 ± 0.05 to 2.10 ± 0.02 which determined the purity of RNA. The range of the mean yield of the RNA was 232.38 ± 5.01 to 419.49 ± 9.43 µg/ gm of tissue which is abundant for further molecular analysis. For validation of the protocol, the RNA was converted into cDNA which was further amplified by semi quantitative-real-time-PCR using Cellulose synthase gene specific primers. The results indicated that the proposed RNA isolation method will be helpful in further downstream processing for the betterment of jute fibre quality. crops fibres crucial welldeveloped well developed mucilage polysaccharides compounds fieldgrown field grown 3 6 DaysAfterGermination Days After Germination DAG. DAG . (DAG) Twotimes Two times simple methods A260A280 AA A260 A280 A A260/A28 199 1 99 1.9 005 0 05 0.0 210 2 10 2.1 002 02 23238 232 38 232.3 501 5 01 5.0 41949 419 49 419.4 943 9 43 9.4 µg analysis quantitativerealtimePCR quantitative real PCR primers (DAG A260A28 A26 A28 A260/A2 19 1. 00 0. 21 2. 2323 23 232. 50 5. 4194 41 4 419. 94 9. A260A2 A2 A260/A A260A

Abstract in Brazil, the development of a strong technical foundation for soil and water conservation has made no-tillage (NT) the leading method for preparing land for temporary crops. Despite this, there's insufficient information regarding the extent to which farmers have adopted NT and conservation agriculture (CA) and the distribution and evolution of these practices within Paraná-a state at the forefront of NT and CA implementation. This study investigates the adoption rates of NT and CA among Paraná's farmers, focusing on temporary crops. It utilizes specialized data from the Brazilian Institute of Geography and Statistics' agricultural censuses of 2006 and 2017. Adoption rates for NT and CA were determined by comparing their proportions in both the number of farming properties and the overall land area devoted to temporary crops across various microregions. Findings indicate a rise in the adoption of NT from 68.5% to 78.9% and CA from 14.6% to 27.7% over the 2006 to 2017 period. Moreover, adoption rates varied across the 39 microregions, with the highest rates in regions dominated by temporary crops, particularly soybeans, maize, and wheat. Conversely, the lowest adoption rates were found in microregions where permanent crops and pastures prevailed, and sugarcane, cassava, and rice were the primary temporary crops. Brazil notillage no tillage (NT this theres there s (CA Paranáa Paraná implementation Paranás Statistics 200 685 68 5 68.5 789 78 9 78.9 146 14 6 14.6 277 27 7 27.7 201 period Moreover 3 soybeans maize wheat Conversely prevailed sugarcane cassava 20 68. 78. 1 14. 2 27.

Abstract Phytoliths are plant micro-remains found in soils and sediments. Their durability, abundance and diagnostic morphologies make them reliable environmental proxies, especially when associated with other biological, chemical, or physical indicators. However, in some cases, phytoliths are the only biological proxy available on the soil for paleoenvironmental studies, therefore, it requires extra attention to taphonomic processes affecting these silica bodies’ assemblage. The preservation and conservation of this markers in the soil is directly linked to the edaphic conditions to which it is subjected over time. Hence, the application of this proxy requires care in order to avoid misinterpretations, since phytoliths are subject to degradation and movement within the soil due to soil-plant-water interactions, soil hydrological processes a/nd bioturbation. In this article we examine the diversity and taphonomic evidence found in an Oxisol’s phytolith assemblage in search to better our understanding of this silica bodies preservation in tropical soils. The result shows that the assembly found is very resistant to tropical edaphic conditions, displaying taphonomic signs such as breakage and corrosion across the profile, with significant increase with depth, pointing to the phytolith’s early deposition. Also, results suggest that Grass Silica Short Cell Phytolith tend to present more breakage than corrosion due to its smaller size when compared to bigger morphotypes, which have corrosion features more often. microremains micro remains sediments durability proxies chemical indicators However cases studies therefore time Hence misinterpretations soilplantwater water interactions a nd bioturbation Oxisols Oxisol s profile depth deposition Also morphotypes often

Abstract Energy efficiency in the industrial sector aims to produce goods with lower energy consumption, using efficient practices and technologies throughout the production process, bringing economic, environmental, and social benefits. Taking this into consideration, the objective of this study was to evaluate energy efficiency in a furniture industry, employing the production of a dresser made of wood as the object of analysis. Data were collected through on-site measurements and records in the company's database. Voltage and current measurements were utilized to calculate the electrical energy consumption of each machine in the production of a dresser. Electric energy consumption was analyzed at each stage of the production process, and fractions of consumed energy, mechanical power, and operation time for each machine were determined. Utilizing energy efficiency indicators, energy consumption was compared with similar studies, and strategies were proposed to improve energy efficiency. The results showed that the CNC Machining Center machine is the one that consumes the most energy, representing 58% of the total energy, and that the specific energy consumption (SEC) indicator can be reduced from 143.71 MJ to 99.91 MJ if the suggested strategies are adopted in the production of the dresser. This research introduced the Economic Indicator (EC) as a measure directly related to SEC, in this sense, strategies were proposed that result in savings of R$5.93 per dresser produced. By emphasizing the cumulative impact of adopting multiple energy efficiency strategies and quantifying potential energy savings, this research underscores the importance of such endeavors. process economic environmental benefits consideration industry analysis onsite on site companys company s database power determined indicators studies 58 SEC (SEC 14371 143 71 143.7 9991 99 91 99.9 EC (EC sense R593 R 5 93 R$5.9 produced endeavors 1437 14 7 143. 999 9 99. R59 R$5. 1 R5 R$5 R$

Abstract The aims of this study were to investigate the use of the peach palm by-products - PPBs (shell and sheaths) as substrate to Pleurotus ostreatus cultivation, evaluate its composition, and the antioxidant properties. The cultivation conditions were defined varying the C:N ratio and moisture content, using as substrate PPBs, and for comparison, a control medium of sawdust was used. P. ostreatus produced in these substrates and a commercial sample were evaluated as composition and antioxidant properties; in these last analyzes it was previous defined how to extract the highest content of phenolic compounds (TPC). The highest yield of P. ostreatus (24.47% wet basis, w.b.) was obtained using the PPB with C:N of 69.14 and moisture of 86.2% (w w-1); yield higher than that found in the control medium (17.15% w.b.). The protein content of commercial mushroom (28 g 100 g-1, dry basis - d.b.) was higher than the cultivated samples (16 g 100 g-1, d.b). In the mushroom samples the contents of ashes, lipids and dietary fibers ranged between 6.09 and 6.92 g 100g-1, d.b, 1.22 to 1.72 g 100g-1, d.b and 39.46 and 43.24 g 100g-1, d.b, respectively. The best condition for TPC extraction was: 38.8 min, using 29.4% (v v-1) of ethanol. P. ostreatus cultivated in PPBs showed the highest contents of TPC, phenolic acids (gallic, vanillic, trans-cinnamic, ferulic and coumaric), and antioxidant activity. Therefore, PPB is a low-cost alternative to mushrooms cultivation with high nutritional value, avoiding environmental problems of its incorrect disposal. byproducts by products shell sheaths properties CN C N comparison used P TPC. . (TPC) 24.47% 2447 24 47 (24.47 w.b. wb w b 6914 69 14 69.1 862 86 2 86.2 w1 1 w-1) 17.15% 1715 17 15 (17.15 w.b.. 28 (2 10 g1, g1 1, g-1 d.b. db d 16 (1 d.b) ashes 609 6 09 6.0 692 92 6.9 100g1, 100g1 100g 100g-1 122 22 1.2 172 72 1.7 3946 39 46 39.4 4324 43 43.2 respectively 388 38 8 38. min 294 29 4 29.4 v v1 v-1 ethanol gallic, gallic (gallic vanillic transcinnamic, transcinnamic trans cinnamic, cinnamic trans-cinnamic coumaric, coumaric , coumaric) activity Therefore lowcost low cost value disposal (TPC 24.47 244 (24.4 w.b 691 69. 86. w-1 17.15 171 (17.1 ( g- 60 0 6. 9 100g- 12 1. 7 394 3 39. 432 43. 29. v- 24.4 (24. w- 17.1 (17. 24. (24 17. (17

Abstract In this work, we studied 46 bacterial isolates to determine their potential for polyethylene terephthalate (PET) degradation. Only eight lipase-positive isolates were pre-selected to continue analysis. The isolates belonged to the genera Micrococcus, Acinetobacter, Pseudomonas, Bacillus, and Pseudochrobactrum. In addition to lipase, other enzymatic activities such as protease, carboxymethyl cellulase, xylanase, and chitinase were detected. PET sheets were pretreated with temperature, UV light, HNO3, and Stenotrophomonas pavanii. All isolates were tested against pretreated PET for 60 days. All isolates displayed lipase activity, and some hydrolase activities. The chemical changes of PET sheets were determined using Fourier-transform infrared spectroscopy. Peaks observed at 3000-3500 cm-1 corresponding to hydroxyl group suggested degradation. The physical changes of PET observed with the naked eye and with SEM consisted of erosion, bubbles, scales, bumps, pits, and a shiny surface. Pseudomonas soli was selected as the best PET degrader, according to the notable changes in the infrared spectrum and macroscopic changes compared to the other genera and the control. In addition, this isolate did not show xylanase activity and it lacks the chitinase gene too. It is possible that not only lipase activity could be associated with the PET degradation, but also another enzymatic activity not detected in this study. Although the genus Pseudomonas has been reported as a plastic degrader, the P. soli species is novel in the degradation of PET, as well as the other genera mentioned here. Finally, these findings contribute to the knowledge of bacterial species for PET degradation. work 4 (PET lipasepositive positive preselected pre analysis Micrococcus Acinetobacter Bacillus Pseudochrobactrum protease cellulase temperature light HNO3 HNO pavanii 6 days Fouriertransform Fourier transform spectroscopy 30003500 3000 3500 3000-350 cm1 cm 1 cm- erosion bubbles scales bumps pits surface degrader control too study P here Finally 3000350 300 350 3000-35 300035 30 35 3000-3 30003 3 3000-

Abstract The Internet of Things (IoT) has experienced rapid development in area-specific applications, including smart transportation systems, healthcare, industries, and smart agriculture, to enhance socio-economic development over the past few years. This IoT system includes different actuators, interconnected sensors, and network-enabled devices that exchange various data through private networks and the Internet infrastructure. The intrusion detection system (IDS) is deployed with preventive security mechanisms, namely access control and authentication. The usual behaviors of the mechanism distinguish malicious and normal activities based on specific patterns or rules of IDSs. Therefore, this article focuses on developing IDS using Double Adaptive Weighting Arithmetic Optimization Algorithm with Deep Learning (DAWAOA-DL) approach in the IoT environment. The DAWAOA-DL methodology's objective is to recognise and classify intrusions in the IoT platform accurately. To execute this, the presented DAWAOA-DL approach involves the design of the DAWAOA technique for the feature selection procedure. Next, the convolutional neural network-gated recurrent unit (CNN-GRU) technique is used for the intrusion detection task. Finally, the Adam optimizer is exploited as a hyperparameter optimizer of the CNN-GRU methodology. A series of simulations were performed on the BoT-IoT dataset to exhibit the effectual detection performance of the DAWAOA-DL method. A widespread experimental validation demonstrated the betterment of the DAWAOA-DL method over other recent models under several metrics. (IoT areaspecific area applications systems healthcare industries agriculture socioeconomic socio economic years actuators sensors networkenabled network enabled infrastructure (IDS mechanisms authentication IDSs Therefore DAWAOADL DL (DAWAOA-DL environment methodologys methodology s accurately procedure Next networkgated gated CNNGRU CNN GRU (CNN-GRU task Finally BoTIoT BoT metrics

Abstract The calculated or experimental physical-chemical Properties are important for choosing substances that will be used in the treatment of several diseases by different administration routes. Chloroquine, for example, is a drug with several biological activities that has been constantly investigated as an alternative to drug repurposing in different diseases. With respect to leishmaniasis, there are few treatment options, which are invasive and have several adverse effects. Another point is the identification of important drug molecular targets, understand their functions, and thus discovering new therapeutic alternatives. Thus, this work aimed at: performing an in analysis of the pharmacokinetic profile of chloroquine as an option for the treatment of cutaneous leishmaniasis by dermal route; evaluating the interaction of the drug with the enzyme Trypanothione reductase, responsible for the parasite’s redox balance. The melting point was obtained in the PUBCHEM database. Analysis showed that chloroquine presented a partition coefficient, molecular weight, and melting point within the established proper range of parameters. The skin permeability coefficient also presented a satisfactory value, as well as the values for total polar surface area, number of rotatable bonds, and sp3 Carbon Fraction. In molecular docking simulations, chloroquine showed interactions with the enzyme TRLb, with a calculated Ki lower than that of the reference compound. This study reinforces the theoretical prediction and good solubility and permeability of chloroquine. The results justify further investigations on the inhibition of TRLb as an important alternative for the treatment of leishmaniasis. physicalchemical physical chemical routes Chloroquine example options effects targets functions alternatives Thus at route reductase parasites parasite s balance database weight parameters value area bonds sp Fraction simulations compound

Abstract Variable renewable energies are leading the energy transition and power system flexibility has become a global priority. Incorporating short-term assessment into long-term planning is essential to capture the operational characteristics of generation and address flexibility issues. This paper presents a novel model for generation and transmission expansion planning with economic dispatch. In the generation expansion planning, the capacity expansion is optimized. In the economic dispatch problem, power plant operation, hydropower generation, and line transmission power flow are optimized. The model is a mixed-integer linear programming problem solved in MATLAB using Gurobi toolbox. A model is proposed to optimize the reservoir of hydropower systems and run-of-river. A case study for supplying Brazilian demand in 2050 is presented. A scenario with greenhouse gas emission costs and no deficit is proposed. This study has shown that the current penalty cost for loss of load is not sufficient to avoid a deficit. It is possible to supply 2050 demand, without large reservoirs or deficits, with a 5.5% curtailment, using 13% of total storage capacity, however; peaking power plants are required. priority shortterm short term longterm long issues optimized operation mixedinteger mixed integer toolbox runofriver. runofriver run river. river run-of-river 205 presented deficits 55 5 5.5 curtailment 13 however required 20 5. 1 2

Abstract Mung beans are a nutrient-dense dietary option since they are low in fat and high in fiber, protein, and vitamins. Estimating the amount of pod shells is important because it gives information about the amount of seeds contained in the pods and indirectly about the yield. The study aimed to predict the pod shell rate of mung bean genotypes and cultivars in pod and seed sizes by using curving fitting and artificial neural networks. The produced equation for predicting of shell weight rate of the genotypes and varieties was formulized as SWR = (-1.349e-13) + (0.999 x TW) + (0.999 x SIW) + (1.416e-18 x TW2) - [1.908e-17 x (TW x SIW)] where SWR is shell weight rate, TW is total weight, and SIW is seed internal weight. On the other hand, this research discusses the use of an artificial neural network (ANN) model to predict the shell rate of legumes based on various input parameters such as pod length, pod width, pod thickness, seed length, seed width, and seed thickness. The R2 values obtained from the ANN analysis indicate that the model predicts shell rate with 87% accuracy. nutrientdense nutrient dense fiber protein vitamins yield networks 1.349e13 1349e13 e 1.349e 13 1 349e (-1.349e-13 0.999 0999 0 999 (0.99 1.416e18 1416e18 1.416e 18 416e (1.416e-1 TW2 1.908e17 1908e17 1.908e 17 908e [1.908e-1 hand (ANN length width thickness R 87 accuracy 349e13 1.349e1 1349e1 1349e (-1.349e-1 0.99 099 99 (0.9 416e18 1.416e1 1416e1 1416e (1.416e- 908e17 1.908e1 1908e1 1908e [1.908e- 8 349e1 (-1.349e- 0.9 09 9 (0. 416e1 (1.416e 908e1 [1.908e (-1.349e 0. (0 (

Abstract The paper proposes design and investigates controllers for infusion pump systems to actuate air control flow with improved performance. The actuator is realized with a permanent magnet brushless DC motor controlled by a self-tune PID controller replaced self-tune fuzzy-PID controller. Using the nonlinear model of the infusion pump system includes the motor driver, fuzzy-PID controller, and gear head as the load connected to the analysis of experimental results. The proposed control topology will improve transient responses such as rise time and steady-state error of the infusion pump system. The actuation system needs an efficient actuator with a controller for tracking desired response with self-tuning depending on linear and nonlinear conditions. The complete electromechanical actuator for fin control is modeled in MATLAB/SIMULINK environment. The simulation results show a better transient response and fewer torque ripples in the proposed system and a comparison study is performed for fuzzy-PID and conventional PID controllers. performance selftune self tune fuzzyPID fuzzy driver steadystate steady state selftuning tuning conditions MATLABSIMULINK MATLAB SIMULINK environment

Abstract Smart Transformer (ST)-based Meshed Hybrid AC/DC Microgrids (MHM) present advantages concerning the performance of conventional AC/DC microgrids (MG). Despite this, MHMs present challenges in managing and controlling electronic converters associated with the ST and Distributed Energy Resources (DER), a scenario that makes it complex to achieve optimal system performance. Additionally, the high penetration of DER would impact the voltage profile, reduce the reactive compensation, and increase the losses in the distribution lines at a high cost in operation. This work proposes an optimal power management computational model for the day-ahead optimal operation planning of ST-based MHM. The management algorithm delivers the optimal operating points of each of the converters of the MG so that it allows the control of active power on both the AC and DC sides; likewise, it will enable reactive power injection control according to the availability of the solar photovoltaic resource and Battery Energy Storage Systems (BESS). According to the tests performed under different operation scenarios with varying degrees of penetration of Photovoltaic Generator (PVG), the benefits of implementing the ST as an energy router according to the operating set points by the optimization algorithm are evidenced. Integrating the ST in MHM and optimization algorithms is a suitable alternative for managing microgrids with high penetration of distributed energy resources. This allows for improving the voltage profile in the MHM, reducing losses in the lines and energy exchange costs with the distribution network. STbased based ACDC (MHM MG. . (MG) this DER, , (DER) Additionally compensation dayahead day ahead sides likewise BESS. BESS (BESS) PVG, PVG (PVG) evidenced resources network (MG (DER (BESS (PVG

Abstract Real-time monitoring of crop growth has become indispensable in modern agriculture, facilitating prompt detection of crop stress, diseases, and nutrient deficiencies by farmers. This study investigates the feasibility of leveraging unmanned aerial vehicles (UAVs) and deep learning algorithms for the real-time monitoring of Vicia faba L. crop growth stages, aimed at informing decisions related to irrigation, fertilization, and pest management. The study introduces a cutting-edge deep learning model tailored for accurate real-time monitoring of diverse growth stages based on neural architecture search (NAS). This model is benchmarked against seven other rigorously trained models using a diverse dataset of 2530 UAV-captured images, encompassing varied and complex lighting and background conditions. We meticulously fine-tuned the training parameters, closely examining and comparing the substantial performance of each model. Notably, the NAS-based architecture model proved outstanding results, achieving a precision rate of 95.80%, a recall rate of 98.80%, and a mAP@0.5_0.95 value of 71.30%. It strikes an optimal balance between precision, speed, and model size compared to alternative neural network models. The mean average precision (mAP) stands at 95.50%, and it maintains a refresh rate of 24.8 frames per second (FPS), all within a compact model size of 256 megabytes (MB). This chosen model achieves an impressive inference speed of 40.32 milliseconds per frame during testing with new images. This performance is underpinned by the current technology of the NVIDIA Quadro P1000, recognized for its high performance and significant pipelines/CUDA cores. Realtime Real time agriculture stress diseases farmers UAVs (UAVs realtime real L irrigation fertilization management cuttingedge cutting edge NAS. NAS . (NAS) 253 UAVcaptured UAV captured images conditions finetuned fine tuned parameters Notably NASbased results 9580 95 80 95.80% 9880 98 98.80% mAP05095 mAP 0 5 mAP@0.5_0.9 7130 71 30 71.30% (mAP 9550 50 95.50% 248 24 8 24. FPS, FPS , (FPS) 25 MB. MB (MB) 4032 40 32 40.3 P1000 P pipelinesCUDA pipelines CUDA cores (NAS 958 9 95.80 988 98.80 mAP0509 mAP@0.5_0. 713 7 3 71.30 955 95.50 2 (FPS (MB 403 4 40. P100 95.8 98.8 mAP050 mAP@0.5_0 71.3 95.5 P10 95. 98. mAP05 mAP@0.5_ 71. P1 mAP0 mAP@0.5 mAP@0. mAP@0 mAP@