Cost-effective Equipment Research Articles

Optimizing silt density index prediction in water treatment systems using pressure-based gradient boosting hybridized with Salp Swarm Algorithm

This study introduces a novel approach for predicting Silt Density Index (SDI) values in desalination systems by combining Gradient Boosting with the Salp Swarm Algorithm (GBSSA). The integration of GBSSA enhances predictive accuracy over a one-month period, addressing critical challenges related to water scarcity exacerbated by climate change. Data were collected from two desalination plants in western Algeria, specifically the Benisaf and El Mactaa plants, to train and validate the models. Pressure measurements were chosen as input features due to their ease of measurement and the use of simple, cost-effective equipment, minimizing the need for complex sensors and reducing manual intervention. The study compared the performance of three Gradient Boosting variants: the standard Gradient Boosting model (GB), Gradient Boosting optimized with Particle Swarm Optimization (GBPSO), and the proposed GBSSA model. Results demonstrated that the GBSSA model significantly outperformed both GB and GBPSO, achieving superior accuracy in predicting SDI values. This enhanced predictive capability is crucial for effective monitoring and management of fouling in desalination plants, facilitating better operational adjustments and maintenance decisions. The findings underscore the potential of combining advanced machine learning techniques with optimization algorithms to improve predictive modeling in critical environmental contexts.

Unsteady flow analysis in a pump as turbine impeller based on proper orthogonal decomposition and dynamic mode decomposition methods

Pump as turbine (PAT) is an efficient, simple, and cost-effective equipment combining pump and turbine and is one of the excellent energy recovery devices. It is helpful to master the flow characteristics of the key component impeller for the further optimization and design of the PAT. To analyze the unsteady flow features in the impeller of a double-suction pump operating as a turbine, numerical simulations were conducted using the shear stress transport (SST) k-ω turbulence model at the designed operating conditions. By utilizing proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) methods on the unsteady velocity field of a single cycle, the dominant modes up to the fourth order, along with their respective space–time information, can be extracted. The velocity field and vorticity field analysis were performed on the first four modes extracted using two different methods. Additionally, the vortex structures were extracted using the Ω method. The analysis demonstrates that the POD and DMD methods effectively decompose the intricate flow characteristics within the impeller into dynamic–static interference modes, fundamental modes, and dissipative modes. The dynamic–static interference mode is dominant, reflecting the flow characteristics influenced by the stationary components within the impeller. The vortex structure is mainly small tubular vortex and point vortex. The fundamental mode captures the steady flow field characteristics caused by the blade channel geometry. The vortex structure is mainly continuous tubular vortex and the diameter becomes larger. The dissipative mode reflects the flow separation generated on the blades by disturbances from the stationary components. The vortex structure is dominated by point vortex and discontinuous tubular vortex. Comparing the outcomes of the two modal analysis methods shows that the POD method has a distinct advantage in showcasing key changing nodes. In contrast, the DMD method is superior in isolating modes with a single frequency and in determining their stability.

Cost effective synthesis of sulfur and nitrogen co-doped graphene aerogel and application in binder free supercapacitor

Incorporating heteroatoms into graphene lattice results in enhanced electrical conductivity and electrochemically active sites and has significant importance in developing high-performance supercapacitors. In this study, sulfur and nitrogen co-doped graphene aerogel is synthesized via hydrothermal technique followed by a simple but effective freeze-thawing and ambient pressure drying process (referred to as SN-GA). The process requires low-cost raw materials and cost-effective equipment without the utilization of any special instrument that operates at ultra-low temperatures, under high pressure, or vacuum environment. Ammonium sulfate [(NH4)2SO4] and ethylenediamine are used as a source of sulfur and nitrogen and as a reducing agent. (NH4)2SO4 with different molarities (0, 12, 24, and 36 mM) are used to synthesize four different aerogel samples marked as GA, SN-GA1, SN-GA2, and SN-GA3. The electrode is prepared using an SN-GA2 sample, exhibiting an outstanding specific capacitance of 244 F g−1 at an applied current density of 1 A g−1 with almost 98.5% Coulomb efficiency. Furthermore, based on the SN-GA2 sample, the symmetrical supercapacitor is fabricated, displaying an energy density of 18.14 Wh kg−1 at a power density of 498.4 W kg−1. Hence, SN-GA2 renders a promising material for supercapacitor applications.

Progression in low-intensity ultrasound-induced tumor radiosensitization.

Radiotherapy (RT) is a widely utilized tumor treatment approach, while a significant obstacle in this treatment modality is the radioresistance exhibited by tumor cells. To enhance the effectiveness of RT, scientists have explored radiosensitization approaches, including the use of radiosensitizers and physical stimuli. Nevertheless, several approaches have exhibited disappointing results including adverse effects and limited efficacy. A safer and more effective method of radiosensitization involves low-intensity ultrasound (LIUS), which selectively targets tumor tissue and enhances the efficacy of radiation therapy. This review summarized the tumor radioresistance reasons and explored LIUS potential radiosensitization mechanisms. Moreover, it covered diverse LIUS application strategies in radiosensitization, including the use of LIUS alone, ultrasound-targeted intravascular microbubble destruction, ultrasound-mediated targeted radiosensitizers delivery, and sonodynamic therapy. Lastly, the review presented the limitations and prospects of employing LIUS-RT combined therapy in clinical settings, emphasizing the need to connect research findings with practical applications. LIUS employs cost-effective equipment to foster tumor radiosensitization, curtail radiation exposure, and elevate the quality of life for patients. This efficacy is attributed to LIUS's ability to utilize thermal, cavitation, and mechanical effects to overcome tumor cell resistance to RT. Multiple experimental analyses have underscored the effectiveness of LIUS in inducing tumor radiosensitization using diverse strategies. While initial studies have shown promising results, conducting more comprehensive clinical trials is crucial to confirm its safety and effectiveness in real-world situations.

Efficient trihalomethane quantification in drinking water for minimally-equipped water treatment plants labs

Chlorine is a common disinfectant used in water treatment. However, its reaction with organic matter can lead to the formation of harmful byproducts, such as trihalomethanes (THMs), which are potentially carcinogenic. To address this issue, the aim of this work was to enhance a colorimetric method capable of quantifying THMs in drinking water through UV/Vis Spectrophotometry, using cost-effective equipment, and validate this methodology for the first time according to established validation protocols. The method’s innovation involved replacing the solvent pentane with the more common hexane, along with adjusting the heating ramp, elucidating the mechanisms involved in the process. This method involves the reaction between THMs, pyridine, and NaOH to produce a colored compound, which is then monitored through molecular absorption spectroscopy in the visible region. The method was thoroughly validated, achieving a limit of detection of 13.41 μg L−1 and a limit of quantification of 40.65 μg L−1. Recovery assays ranged from 86.1 % to 90.7 %, demonstrating high accuracy. The quality of the linear fit for the analytical curve exceeded R2 > 0.98. The method was applied to real samples, revealing concentrations ranging from 13.58 to 55.46 μg L−1, all way below the legal limit in Brazil (Maximum Contaminant Levels (MCL) = 100 μg L−1). This cost-effective and straightforward method is suitable for integration into water treatment plant laboratories.

Paediatric airway foreign-body removal equipment availability in sub-Saharan Africa

Sub-Saharan Africa (SSA), home to over 1 billion people, has only one paediatric otolaryngology fellowship program and nine fellowship-trained paediatric Otolaryngology Head and Neck Surgery (OHNS) specialists covering seven countries. Seven of these specialists estimated an average of 40+ patients per month are in need of critical surgical airway management in their respective countries and that 2–25 deaths per year (mainly paediatric) occur in their country from lack of access to foreign body removal equipment. Investing in paediatric airway infrastructure and capacity would largely benefit the health system in SSA, where the current lack of equipment alone leads to unmeasured morbidity and mortality. As a region of the world with the largest paediatric populations, sub-Saharan Africa’s need is all the more pressing given the disproportionately low number of medical specialists, institutions and resources. Collaborative approaches in procurement and maintenance of high-quality, cost-effective equipment are crucially desirable factors in both low- and middle-income countries (LMICs) and high-income countries (HICs). We, as the Global OHNS Initiative, urge for multi-stakeholder engagement and collaboration to forge lasting change.

Asphalt Pavement Damage Detection through Deep Learning Technique and Cost-Effective Equipment: A Case Study in Urban Roads Crossed by Tramway Lines

Asphalt pavements are subject to regular inspection and maintenance activities over time. Many techniques have been suggested to evaluate pavement surface conditions, but most of these are either labour-intensive tasks or require costly instruments. This article describes a robust intelligent pavement distress inspection system that uses cost-effective equipment and the ‘you only look once’ detection algorithm (YOLOv3). A dataset for flexible pavement distress detection with around 13,135 images and 30,989 bounding boxes of damage was used during the neural network training, calibration, and validation phases. During the testing phase, the model achieved a mean average precision of up to 80%, depending on the type of pavement distress. The performance metrics (loss, precision, recall, and RMSE) that were applied to estimate the object detection accuracy demonstrate that the technique can distinguish between different types of asphalt pavement damage with remarkable accuracy and precision. Moreover, the confusion matrix obtained in the validation process shows a distress classification sensitivity of up to 98.7%. The suggested technique was successfully implemented in an inspection car. Measurements conducted on urban roads crossed by tramway lines in the city of Palermo proved the real-time ability and great efficacy of the detection system, with potentially remarkable advances in asphalt pavement examination efficacy due to the high rates of correct distress detection.

The Determination of Triacylglycerols and Tocopherols Using UHPLC-CAD/FLD Methods for Assessing the Authenticity of Coffee Beans.

The authenticity of coffee beans was addressed in this study using an analytical method with minimal sample preparation to achieve simple oil extraction and through the implementation of cost-effective equipment. For this purpose, methods using UHPLC with CAD and FLD detectors were applied to detect triglycerides and tocopherols in coffee, respectively. The coffee samples included two main varieties: Arabica from Brazil, Colombia, Ethiopia, and Uganda, as well as the Robusta variety from Cambodia, Guatemala, India, and Vietnam. The samples were either in their green state or subjected to different roasting levels. The used methods successfully distinguished the Arabica and Robusta variants targeted in this study based on their tocopherols and TAG profiles, with the latter being particularly effective for discriminating the origins of the Arabica coffee, while tocopherols excelled at differentiating the origin of the Robusta coffee. TAGs and tocopherols were not affected by the type of roasting, from medium to very dark, suggesting it is possible to distinguish between coffee varieties independently from their degree of roasting. The obtained results hold valuable implications for future research regarding coffee fraud and authenticity.

Fibrous Structures Produced Using the Solution Blow-Spinning Technique for Advanced Air Filtration Process.

This study proposes utilising the solution blow-spinning process (SBS) for manufacturing a biodegradable filtration structure that ensures high efficiency of particle filtration with an acceptable pressure drop. The concept of multi-layer filters was applied during the design of filters. Polylactic acid (PLA) was used to produce various layers, which may be mixed in different sequences, building structures with varying filtration properties. Changing the process parameters, one can create layers with diverse average fibre diameters and thicknesses. It enables the design and creation of optimal filtration materials prepared for aerosol particle filtration. The structures were numerically modelled using the lattice Boltzmann approach to obtain detailed production guidelines using the blow-spinning technique. The advantage of this method is the ability to blow fibres with diameters in the nanoscale, applying relatively simple and cost-effective equipment. For tested PLA solutions, i.e., 6% and 10%, the mean fibre diameter decreases as the concentration decreases. Therefore, the overall filtering efficiency decreases as the concentration of the used solution increases. The produced multi-layer filters have 96% overall filtration efficiency for particles ranging from 0.26 to 16.60 micrometres with a pressure drop of less than 160 Pa. Obtained results are auspicious and are a step in producing efficient, biodegradable air filters.

Evaluating Green Solvents for Bio-Oil Extraction: Advancements, Challenges, and Future Perspectives

The quest for sustainable and environmentally friendly fuel feedstocks has led to the exploration of green solvents for the extraction of bio-oil from various biomass sources. This review paper provides a comprehensive analysis of the challenges and future research outlooks for different categories of green extraction solvents, including bio-based solvents, water-based solvents, supercritical fluids, and deep eutectic solvents (DES). The background of each solvent category is discussed, highlighting their potential advantages and limitations. Challenges such as biomass feedstock sourcing, cost fluctuations, solvent properties variability, limited compatibility, solute solubility, high costs, and potential toxicity are identified and examined in detail. To overcome these challenges, future research should focus on alternative and abundant feedstock sources, the development of improved solubility and separation techniques, optimization of process parameters, cost-effective equipment design, standardization of DES compositions, and comprehensive toxicological studies. By addressing these challenges and advancing research in these areas, the potential of green extraction solvents can be further enhanced, promoting their widespread adoption and contributing to more sustainable and environmentally friendly industrial processes.

Advances in Natural Product Extraction Techniques, Electrospun Fiber Fabrication, and the Integration of Experimental Design: A Comprehensive Review.

The present review explores the growing interest in the techniques employed for extracting natural products. It emphasizes the limitations of conventional extraction methods and introduces superior non-conventional alternatives, particularly ultrasound-assisted extraction. Characterization and quantification of bioactive constituents through chromatography coupled with spectroscopy are recommended, while the importance of method development and validation for biomarker quantification is underscored. At present, electrospun fibers provide a versatile platform for incorporating bioactive extracts and have extensive potential in diverse fields due to their unique structural and functional characteristics. Thus, the review also highlights the fabrication of electrospun fibers containing bioactive extracts. The preparation of biologically active extracts under optimal conditions, including the selection of safe solvents and cost-effective equipment, holds promising potential in the pharmaceutical, food, and cosmetic industries. Integration of experimental design into extraction procedures and formulation development is essential for the efficient production of health products. The review explores potential applications of encapsulating natural product extracts in electrospun fibers, such as wound healing, antibacterial activity, and antioxidant properties, while acknowledging the need for further exploration and optimization in this field. The findings discussed in this review are anticipated to serve as a valuable resource for the processing industry, enabling the utilization of affordable and environmentally friendly, natural, and raw materials.

Mechanical Design of DNA Origami in the Classroom

DNA origami (DO) nanotechnology has strong potential for applications including molecular sensing, drug delivery, and nanorobotics that rely on nanoscale structural precision and the ability to tune mechanical and dynamic properties. Given these emerging applications, there is a need to broaden access to and training on DO concepts, which would also provide an avenue to demonstrate engineering concepts such as kinematic motion and mechanical deformation as applied to nanotechnology and molecular systems. However, broader use in educational settings is hindered by the excessive cost and time of fabrication and analysis. Compliant, or deformable, DO is especially difficult to design and characterize in a cost-effective manner, because analysis often relies on advanced imaging methods to quantify structure conformations. Building on recent work establishing classroom-ready methods for DO fabrication and analysis, we developed an experiment module for classroom implementation focused on a DO compliant hinge joint. The module consists of folding three distinct joint conformations that can be evaluated via gel electrophoresis using portable and cost-effective equipment within ~120 min. To highlight the mechanical design, we present two beam-based models for describing the deformation that controls the joint angle. We envision that this module can broaden access to and interest in the mechanical design of DO.

Measuring rock slope damage on rubble mound breakwater through digital photogrammetry

In coastal engineering, laboratory research is the primary way to investigate wave–structure interaction. Different techniques can be used to study the stability of coastal structures and the related damage level, among which, the most consolidated one exploits the laser profiling system, with costly and time-consuming procedures. The present research proposes an innovative method, based on photogrammetry, for the measurement of the damage of rock slope structures (i.e. depth and extension of the damaged area). The approach has been tested and validated during an experimental campaign carried out on a 2D-physical scaled model of a rubble mound breakwater at the EUMER Laboratory (University of Salento, Lecce, Italy). Photogrammetric outputs have been compared with the laser derived profiles, under different structures layouts and hydrodynamic conditions. Results have proven to be highly accurate (relative error lower than 5%), with time and cost-effective equipment (standard digital camera) and simple acquisition and processing procedures.

A Fuzzy BWM-TOPSIS Framework for Identifying and Prioritizing Measures to Overcome Obstacles to the Regionalization of Iranian Healthcare Services.

One of the most effective strategies to improve the access of community members to health services is to regionalize health services. The purpose of this study is to examine and prioritize measures that could help to counteract obstacles and problems in implementing the regionalization of healthcare in Iran. The study relied on a mixed research method, including qualitative and quantitative phases. First, by conducting semi-structured interviews and analyzing them through qualitative content analysis, the obstacles and measures were identified. In the quantitative phase, the obstacles identified were weighted using the fuzzy best-worst method (FBWM), and the measures were then prioritized through the fuzzy TOPSIS (FTOPSIS) method. The obstacles were categorized into four main dimensions: "infrastructural," "political," "human resources," and "managerial." Among the 15 obstacles identified, "absence of performance guarantees" was the most important obstacle, while "insufficient education" was the least important obstacle to the regionalization of healthcare services in Iran. Meanwhile, the following eight measures that could help to overcome the obstacles were extracted from the interviews: "conducting a needs assessment," "providing clinical guidelines," "employing specialized human resources," "reinforcing the referral system," and "preparing electronic health records," "enhancing education and information dissimilation," "building executive support," and "providing cost-effective equipment and technology." "Employing specialized human resources" was also the most effective measure to overcome the obstacles. Iranian healthcare policy-makers can use the empirical findings of this investigation to accelerate the implementation of Iran's regionalization plan to improve the access of community members to healthcare services.

Data driven-based model for predicting pump failures in the oil and gas industry

Equipment reliability is a critical aspect of the oil and gas industry because the failure of such equipment can lead to catastrophic outcomes on different levels. In these industries, the need for safe, accurate, and cost-effective equipment operation requires reliable failure estimation and identification in order to improve performance and ensure that the maintenance strategy is efficient and effective. Thus, failure prediction is vital in the oil and gas industries for extending part lifetime and reducing unexpected equipment failures, thereby avoiding costly plant shutdowns and equipment damage. This paper proposes a simple and easy-to-implement data-driven model based on multiple linear regression for predicting the failures of a seawater pump in the oil and gas industry. Real-world historical data from equipment and process sensors mounted on the selected pump is collected and analyzed to develop the proposed model. The factors used to build the proposed model have been identified through a review of the literature and expert interviews. In addition, the correlation between the input factors is investigated. The results revealed that the proposed model has the capability to predict pump failure with more than 97% accuracy. Furthermore, sensitivity analysis revealed that temperature and pressure are the most important factors influencing pump failure. The findings of the proposed model can assist maintenance managers and decision-makers in properly detecting and predicting failure. It also helps to monitor and control the input factor levels in order to prevent failures. This study contributes to the development of failure prediction alerts, which will serve as a maintenance decision support system for operatives to avoid potential incoming failures.

Cost-effective equipment for surface pre-treatment for cleaning and excitation of substrates in semiconductor technology

This article presents a cost-effective ultraviolet-ozone cleaner (UV/O3 Cleaner) for surface pre-treatment of substrates in the field of semiconductor technology. The cleaner consists of two chambers, the upper one contains the electronics, including the time counter. The lower chamber contains the two UV sterilisation lamps and a UV reflector of anodized aluminium, which confines the area of high Ozone concentration in the area of interest. The device is successfully used for surface cleaning and modification of different materials. To this end, the two important wavelengths 253.7 nm (excitation of organic residues) and 184.9 nm (production of ozone from the atmospheric environment as a strong oxidant) were first detected. The effectiveness of UV/O3 cleaning is demonstrated by improving the properties of indium tin oxide (ITO) for OLED fabrication. The contact angle of water to ITO could be reduced from 90° to 3° and for diiodomethane, it was reduced from 55° to 31° within the 10 min of irradiation. This greatly improved wettability for polar and non-polar liquids can increase the flexibility in further process control. In addition, an improvement in wettability is characterized by measuring the contact angles for titanium dioxide (TiO2) and polydimethylsiloxane (PDMS). The contact angle of water to TiO2 decreased from 70° to 10°, and that of diiodomethane to TiO2 from 54° to 31°. The wettability of PDMS was also greatly increased. Here, the contact angle of water was reduced from 109° to 24° and the contact angle to diiodomethane from 89° to 49°.Article HighlightsWe report a cost-effective dry-cleaning device for surface cleaning and modification based on ultraviolet-ozone irradiation.Contact angle measurements show an increase of wettability for different materials due to surface modification.The UVO3 pre-treatment improves layer formation and optoelectrical properties of OLEDs.

The Software Cache Optimization-Based Method for Decreasing Energy Consumption of Computational Clusters

Reducing the consumption of electricity by computing devices is currently an urgent task. Moreover, if earlier this problem belonged to the competence of hardware developers and the design of more cost-effective equipment, then more recently there has been an increased interest in this issue on the part of software developers. The issues of these studies are extensive. From energy efficiency issues of various programming languages to the development of energy-saving software for smartphones and other gadgets. However, to the best of our knowledge, no study has reported an analysis of the impact of cache optimizations on computing devices’ power consumption. Hence, this paper aims to provide an analysis of such impact on the software energy efficiency using the original software design procedure and computational experiments. The proposed Software Cache Optimization (SCO)-based Methodology was applied to one of the key linear algebra transformations. Experiments were carried out to determine software energy efficiency. RAPL (Running Average Power Limit) was used—an interface developed by Intel, which provides built-in counters of Central Processing Unit (CPU) energy consumption. Measurements have shown that optimized software versions reduce power consumption up to 4 times in relation to the basic transformation scheme. Experimental results confirm the effectiveness of the SCO-based Methodology used to reduce energy consumption and the applicability of this technique for software optimization.

(Invited) High Performance Fully Solution Processed Transistors Towards Flexible Sustainable Electronics

The shift towards a human-centered society promotes greater interconnectedness between people and the digital space. Modern devices such as displays and sensors in which thin-film transistors (TFT) are key materials have crucial roles in the next-generation society because displays are used as both information terminals and interface for human-device interactions while sensors gather data. Furthermore, there is growing interest in neuromorphic devices which aim to mimic the human brain’s efficiency in simultaneously processing and memorizing information to address the von Neumann bottleneck pervasive in modern computing architecture [1]. Amorphous oxide semiconductors (AOS) have gained attention as excellent materials for TFT [2], memory [3], sensing [4], and neuromorphic [5] applications for their superb combination of electrical performance and transparency. Currently, AOS devices are still mainly fabricated using vacuum process. To achieve high throughput and cost-effective production of numerous ubiquitous devices necessary in the next-generation society, an alternative fabrication process is needed.Solution process is an exceptional candidate because of its: (i) efficient production with cost-effective equipment, (ii) large material utilization (low waste) since it can be an additive process compared to vacuum process (high waste), and (iii) low temperature processability for flexible applications in healthcare, energy, and electronics. However, solution process still has major issues such as inferior performance and reliability compared with vacuum process. Several processes have been developed to address these issues but are mostly focused on improving performance and usually limited to a single solution processed device layer – the channel or gate insulator [6]. Thus, many still opt for vacuum process or a single solution processed layer as a compromise. For truly high throughput fabrication, all device layers should be fabricated by solution process. In reality, fully solution-processed TFTs are challenging to fabricate, have dismal performance (mobility (μ) < 1 cm2/Vs), and poor reliability. Therefore, high temperature (>400 °C) process and exotic materials are required for decent μ <10 cm2/Vs which precludes their use in high performance flexible device applications [7].Here, we present how photo-assisted methods through UV treatment and excimer laser annealing (ELA) can selectively transform AOS regions at low substrate temperatures [8]. Consequently, a single AOS film acts as both the semiconductor channel and conducting electrode to realize fully solution processed TFTs with μ of ~40 cm2/Vs (see Fig. 1) [9]. We also show how alternative methods can be used to enhance the performance and stability of fully solution processed TFTs on rigid/flexible substrates. In particular, how low temperature processes such as light, plasma, and material design of functional materials enable high throughput solution processing of flexible electronic devices. AcknowledgmentThis research was supported by JSPS Kakenhi Grant no. 22K14291.

The miEye: Bench-top super-resolution microscope with cost-effective equipment

Commercial super-resolution (SR) imaging systems require a high budget, while current more affordable open source microscopy systems lack modularity and sometimes are too complex or lack reliability. We present miEye – a cost-effective microscope designed for high-resolution wide-field fluorescence imaging. The build is constructed using a CNC milled aluminum microscope body and commercially available optomechanics, with open-source Python-based microscope control, data visualization, and analysis software integration. The data acquisition software works robustly with commonly used industrial-grade complementary metal oxide semiconductor (iCMOS) cameras, performs IR beam back-reflection-based automatic focus stabilization, and allows for laser control via an Arduino-based laser relay. The open-source nature of the design is aimed to facilitate adaptation by the community. The build can be constructed for a cost of roughly 50 k €. It contains SM-fiber and MM-fiber excitation paths that are easy to interchange and an adaptable emission path. Also, it ensures <5 nm/min stability of the sample on all axes, and allows achieving <30 nm lateral resolution for dSTORM and DNA-PAINT single-molecule localization microscopy (SMLM) experiments. Thus it serves as a cost-effective and adaptable addition to the open source microscopy community and potentially will allow high-quality SR imaging even for limited-budget research groups.

Design and Development of Multipurpose Agricultural Drone

Agriculture has been the most important aspect of human life. Especially in developing countries like India, the livelihood of over 70% of the rural people depends upon agriculture. The crops are affected by various diseases caused by pests and insects, which reduces productivity. Pesticides are used to kill the insects and pests in order to enhance the crop quality. The United Nations Food and Agriculture Organization (UN FAO) expects that food production must be raised by 70% throughout the following 40 years to meet increasing demand due to rising economic welfare and population growth. As the global labour force does not match the plant growth, the main focus of this project is to design an affordable multi-purpose agricultural drone. With increased precision in the spraying, it is possible to reduce the amount of pesticide used and improve the quality of agricultural products as well as mitigate the risk of environmental damage. In addition, to develop an Aerial Seeding mechanism which can be used to plant seeds in the agricultural field using drones to pace the process of seeding. The drone is designed in such a way that it can be affordable for farmers. The discussed system involves designing a prototype which use simple cost effective equipment like BLDC motor, Ardupilot - Flight Controller, ESC wires, etc.