bluuebunny/crossref_metadata_2025 huggingface dataset:
Rice seeds biofortification using biogenic ıron oxide nanoparticles synthesized by using Glycyrrhiza glabra: a study on growth and yield ımprovement
Authors: Ahmad Sidra , Ahmad Nayab , Islam Md. Shahinoor , Ahmad Mian Afaq , Ercisli Sezai , Ullah Riaz , Bari Ahmed , Munir Iqbal
Published: May 2024

Iron, a crucial micronutrient, is an integral element of biotic vitality. The scarcity of iron in the soil creates agronomic challenges and has a detrimental impact on crop vigour and chlorophyll formation. Utilizing iron oxide nanoparticles (IONPs) via nanopriming emerges as an innovative method to enhance agricultural efficiency and crop health. The objective of this study was to synthesize biogenic IONPs fromGlycyrrhiza glabra(G. glabra) plant extract using green chemistry and to evaluate their nanopriming effects on rice seed iron levels and growth. The synthesized IONPs were analyzed using UV–Vis spectroscopy, Fourier-transform infrared spectroscopy (FTIR), Scanning electron microscope (SEM), Transmission electron microscopy (TEM), and Energy-dispersive X-ray (EDX) techniques. The UV–Vis peak at 280 nm revealed the formation of IONPs. SEM and TEM showed that the nanoparticles were spherical and had an average diameter of 23.8 nm. Nanopriming resulted in a substantial enhancement in growth, as seen by a 9.25% and 22.8% increase in shoot lengths for the 50 ppm and 100 ppm treatments, respectively. The yield metrics showed a positive correlation with the concentrations of IONPs. The 1000-grain weight and spike length observed a maximum increase of 193.75% and 97.73%, respectively, at the highest concentration of IONPs. The study indicates thatG. glabrasynthesized IONPs as a nanopriming agent significantly increased rice seeds' growth and iron content. This suggests that there is a relationship between the dosage of IONPs and their potential for improving agricultural biofortification.
Investigation of the trend and related factors of suicide attempts and suicide deaths in southeast Iran during 2018–2022
Authors: Rezaeian Mohsen , Jamali Zahra , Javadi Zahra , Taherifard Alireza , Khalili Parvin
Published: May 2024

Suicide is a major public health challenge worldwide with an increasing trend. Identifying risk factors for suicide attempts and suicide deaths may help find useful ways to prevent suicide. We aimed to determine the trend and related factors of suicide attempts and suicide deaths in Rafsanjan. This retrospective study included all suicide cases from 2018 to 2022 in Rafsanjan, a city in the southeast of Iran. The information was extracted from the suicide registration system of Rafsanjan University of Medical Sciences. Univariable and multivariable logistics regression models were used to investigate factors affecting suicide death. A total of 2039 cases of suicide, including 1932 cases (94.75%) of suicide attempts and 107 cases (5.25%) of suicide deaths were recorded during the study period. The frequency of suicide deaths and suicide attempts per 100,000 people increased in 2022 compared to 2018 in both genders. In the adjusted model, the odds of suicide deaths in males was 6.48 (95% CI 3.39–12.42) times higher than in females. Also, the odds of suicide deaths in unemployed subjects and housewives were 2.64 (95% CI 1.50–4.67) and 7.45 (95% CI 3.08–18.07) times higher than employed subjects respectively. Finally, people with education less than a diploma had 10.85 (95% CI 1.48–79.54) times higher odds of suicide deaths compared to people with university education. The present research showed that the pattern of suicide has been increasing since 2018, and we may see an upward trend in the coming years, which requires further investigation and preventive measures. Male gender, low education level, unemployment, and being a housewife were associated with the highest frequency of suicide death.
Anti-metastasis activity of 5,4’-dihydroxy 6,8-dimethoxy 7-O-rhamnosyl flavone from Indigofera aspalathoides Vahl on breast cancer cells
Authors: Al-Saeedi Fatma , Rajendran Peramaiyan
Published: May 2024

Breast cancer presents a significant challenge due to its high rates of illness and mortality, necessitating more effective treatment approaches. While traditional treatments offer some benefits, they often lack precision in targeting cancer cells and can inadvertently harm healthy tissues. This study aims to investigate the cytotoxic effects and molecular mechanism of 5,4’-dihydroxy-6,8-dimethoxy-7-O-rhamnosyl flavone (DDR), extracted from Indigofera aspalathoides Vahl, on breast cancer cells (MDA-MB-231). Through various in vitro assays including wound healing, invasion, Western blotting, and immunofluorescence, the impact of DDR on epithelial-mesenchymal transition (EMT) and metastasis was evaluated. Treatment of MDA-MB-231 cells with different DDR concentrations (0–10 µg/mL) resulted in a significant decrease in invasion and migration, accompanied by the downregulation of metastasis-related proteins including VEGF, uPAR, uPA, and MMP-9. DDR treatment also hindered EMT by upregulating E-cadherin and downregulating N-cadherin, Slug, Twist, and Vimentin. Additionally, inhibition of the PI3K/AKT signaling pathway and downregulation of the NF-кB pathway were observed. These findings highlight the potential of DDR as a valuable source of natural compounds with promising anticancer properties, offering opportunities for the development of novel cancer therapies.
The spillover effects of China’s carbon trading policy on coordinated emission efficiency
Authors: Cui Hao , Liu Zengbing
Published: May 2024

The significance of carbon trading policy (CTP) for China’s carbon reduction goals cannot be overstated. Examining the practical impacts and inherent features of this policy is crucial for fostering its healthy development and effectiveness. This study utilizes the directional SBM super-efficiency model to calculate the combined emission efficiency (CEE) of greenhouse gases and atmospheric pollutants across 30 provinces and cities in China from 2005 to 2020. Through spatiotemporal analysis of the CEE evolution using hotspot analysis, it is evident that hotspots gradually shift towards the southeast coastal areas over time, while cold spots shift towards the northwest. Additionally, employing the differences-in-differences (DID) model and conducting robustness tests, the study finds that the CTP significantly enhances the CEE development. Spatial econometric analysis reveals that the CEE primarily follows a distribution pattern characterized by low-low (LL) and high-high (HH) regions, with positive spatial spillover effects. However, due to the incomplete state of early green development in China, the CTP temporarily exhibits negative spatial spillover effects. Finally, considering the current state of China's carbon trading policy, corresponding policy recommendations are proposed in this paper.
Effects of maturation on myotonometric parameters and their predictors of athletic performance in elite youth soccer players
Authors: García-Santamaría Alberto , Abelairas-Gómez Cristian , Carrera Samuel , Padrón-Cabo Alexis , Rey Ezequiel
Published: May 2024

The aim of the present study was to investigate the variations in individual muscle stiffness across different maturation stages (i.e., peak height velocity [PHV]) in elite youth soccer players and to explore the associations between lower limb muscle stiffness and performance in sprinting (10, 20, and 40 m sprint), maneuverability (9–3-6–3-9 m sprint test), and jumping (countermovement jump [CMJ]). A total of 131 elite youth soccer players aged 12–18 years, volunteered to participate in the study and were divided into pre-PHV (n = 21), mid-PHV (n = 33), and post-PHV (n = 80). Muscle stiffness of the rectus femoris (RF) and biceps femoris (BF) muscles was assessed using a MyotonPRO. Results showed that players in the pre-PHV stage had lower stiffness in the BF and RF muscles compared to mid-PHV (p < 0.001; effect size [ES] = moderate to large) and post-PHV players (p < 0.001; ES = moderate to large). It was also observed that the mid-PHV group had lower stiffness levels in their RF muscle compared to the post-PHV group (p < 0.001; ES = small). Significant correlations were found between BF and RF stiffness and sprint (p < 0.001) and maneuverability (p < 0.001) performance. RF stiffness showed a significant positive correlation with CMJ (p < 0.05), suggesting that greater lower body stiffness is beneficial for athletic performance in youth soccer players. The findings highlighting the importance of considering training methods that increase muscular stiffness, particularly in relation to the RF muscle, to optimize athletic performance.
Conditional disruption of Nr5a1 directed by Sox9-Cre impairs adrenal development
Authors: Tagami Ayako , Ikeda Yayoi , Ishizuka Kyoko , Maekawa Mamiko
Published: May 2024

The current study aimed to investigate the effect of Sox9-Cre-directed Nr5a1-conditional knockout (Sox9-Cre;Nr5a1flox/flox) on adrenal development. We showed that SOX9 is expressed by adrenocortical cells at E10.5–E11.5 but is extinguished no later than E12.5. The number of adrenocortical cells significantly reduced in Sox9-Cre;Nr5a1flox/flox mice while the number of cleaved caspase 3-positive cells increased compared to that in the controls at E11.5–E12.5, when the adrenal primordium (AP) is about to expand. This indicated that fetal adrenocortical cells are lost via apoptosis due to Nr5a1 ablation by E12.5. Both medulla formation and encapsulation were perturbed, accompanied by a smaller AP size, in Sox9-Cre;Nr5a1flox/flox mice during embryonic development. Adult Sox9-Cre;Nr5a1flox/flox adrenals were hypoplastic and exhibited irregular organization of the medulla with aberrant sex differentiation in the X zone. Additionally, there were histologically eosin-negative vacuolated cells, which were negative for both the X-zone marker 20αHSD and the steroidogenesis marker 3βHSD at the innermost cortex of Sox9-Cre;Nr5a1flox/flox adrenals. Although Nr5a1+/− adrenals were hypoplastic, a small number of chromaffin cells were properly located in the center, having normal sex differences in the X-zone. The results collectively provided in-vivo evidence that Nr5a1 plays a critical role in AP expansion and subsequent adrenal development.
Green and shape-tunable synthesis of ellagic acid crystalline particles by tannic acid for neuroprotection against oxidative stress
Authors: Ha Wei , Ma Rui , Kang Jing-Yan , Iradukunda Yves , Shi Yan-Ping
Published: May 2024

We demonstrate a new method to transform tannic acid into tailorable shaped ellagic acid crystalline particles with significant neuroprotective effect.
Leveraging dual‐blockchain collaboration for logistics supply chain supervision
Authors: Lin Licheng , Pan Senshan , Jing Pujie , Song Xiangmei
Published: May 2024

Logistics supply chain (LSC), a chain structure that integrates and coordinates all logistics transactions, has become an essential component of the modern logistics industry. By using blockchain, trusted logistics services enable participants to effectively record and track transactions during the logistics process. Current blockchain‐based LSC features distributed structure and data privacy requirements, hindering the supervision of logistics transactions. Leveraging emerging dual‐blockchain architecture to separate logistics transactions from supervision is a promising direction. However, the dual‐blockchain collaboration restricts supervision due to its cross‐chain privacy and efficiency. To address these issues, a logistics supply chain supervision scheme based on dual‐blockchain collaboration (DBC) is proposed. First, an independent supervision blockchain is constructed to balance the contradiction between distributed structure and supervision requirements. Second, two mechanisms are designed to enhance the privacy and performance of collaborative supervision. The hybrid access control mechanism enables fine‐grained supervision for different participants, and the aggregated transaction verification method supports efficient collaboration for logistics transactions. Security analysis and performance evaluation demonstrate the feasibility of DBC in enhancing the security and supervision of logistics data on the dual‐blockchain architecture. Experimental results show that the cross‐chain supervision overhead of DBC is reduced to of the baseline schemes.
Adaptive non‐invasive ventilation treatment for sleep apnea
Authors: Tehrani Fleur T. , Roum James H.
Published: May 2024

The purpose of this study was to investigate the effectiveness of two non‐invasive mechanical ventilation (NIV) modalities to treat sleep apnea: (1) Average Volume Assured Pressure Support (AVAPS) NIV, and (2) Pressure Support (PS) NIV with Continuously Calculated Average Required Ventilation (CCARV). Two detailed (previously developed and tested) simulation models were used to assess the effectiveness of the NIV modalities. One simulated subjects without chronic obstructive pulmonary disease (COPD), and the other simulated patients with COPD. Sleep apnea was simulated in each model (COPD and Non‐COPD), and the ability of each NIV modality to normalize breathing was measured. In both NIV modalities, a low level continuous positive airway pressure was used and a backup respiratory rate was added to the algorithm in order to minimize the respiratory work rate. Both modalities could help normalize breathing in response to an episode of sleep apnea within about 5 min (during which time blood gases were within safe limits). AVAPS NIV and PS NIV with CCARV have potential value to be used for treatment of sleep apnea. Clinical evaluations are needed to fully assess the effectiveness of these NIV modalities.
A fixed‐frequency control method for wireless power transmission battery chargers using a dual‐function compensator
Authors: Bajelvand Sina , Babaki Amir , Jafari‐Natanzi Alireza , Yazdian Varjani Ali , Vaez‐Zadeh Sadegh
Published: May 2024

High efficiency and unity power factor (PF) are the most important requirements of a wireless charger system simultaneous with the output voltage regulation. Achieving all above‐mentioned criteria in a wide range of the load is challenging in the system. This paper presents a novel control approach applied to series‐series wireless power transmission converter by using a dual‐function compensator to achieve unity PF and maximum efficiency during the constant power‐constant voltage (CP‐CV) charging scenarios. A semi‐active rectifier with impedance matching capability along with a switch‐controlled capacitor constitutes the dual‐function compensator on the secondary side. Meanwhile, the primary side inverter executes the CP‐CV charging scenario for the battery with various charging characteristics at a fixed‐switching frequency. Besides that, all secondary side switches experience soft switching condition throughout the battery charging. Finally, a prototype with a power of 200 W and roughly regulated efficiency of 90% is presented in order to verify the proposed control method.
Deep learning model for enhanced power loss prediction in the frequency domain for magnetic materials
Authors: Sapkota Dixant Bikal , Neupane Puskar , Joshi Mecon , Khan Shahabuddin
Published: May 2024

This paper outlines the methodology for predicting power loss in magnetic materials. It starts by introducing the concept of core loss and the complexity of modelling it. Steinmetz's equation is presented to calculate power loss based on frequency and magnetic flux density, but its limitations are highlighted. As an alternative, a neural network‐based method is introduced. The proposed methodology adopts a long short‐term memory network, expressing the core loss as a function of magnetic flux density, frequency, temperature, and wave classification. Fast Fourier transform was implemented to reduce the data points of the sampled flux density waveform while preserving its characteristics. Analyzing in the frequency domain enabled streamlining the training of the model. The input features were arranged as required, and the network architecture was designed with appropriate layers and optimal activation functions. Through extensive training using the datasets, the model assimilated intricate relationships between input variables and known power loss. Evaluation and validation metrics were subsequently employed to gauge the performance of the trained network. This innovative methodology aims to significantly augment the precision of power loss predictions, providing valuable insights into the nuanced behaviour of magnetic materials.
A novel WDOB‐based strategy endows droop‐controlled grid‐forming converters better dynamic and static performance in DC microgrids
Authors: Xie Wenqiang , Zheng Xian , Shi Mingming , Sun Tiankui
Published: May 2024

The droop control strategy is popularly employed in DC microgrids. However, its virtual resistance will cause voltage deviation and reduce transient response. The DOB‐based method is proven to improve transient response in literature. However, it is analyzed in this study that this method will negatively influence the current sharing when employed in droop control. A weakened disturbance observation (WDOB) is proposed in this work to improve the drawbacks. To employ the proposed method, the equivalent models of the droop controller and the physical system are separately established, and several transformations are conducted. An auxiliary compensation is added and the current loop is considered as a whole to be transmitted into the control plant, making the traditional DOB method successfully adopted. It is obvious that the dynamic performance is improved, but it disabled virtual resistance in the steady‐state. And the current sharing cannot be achieved in a multi‐converter parallel system. The reason for this problem is analyzed from the control process and transfer function, and the WDOB solution is finally proposed. Through the proposed method, both aims of improving dynamic response and current sharing can be achieved, and the steady voltage deviation is much less than that of the traditional droop controller.
Retrofitting of Thermally Affected Structural Compression Member Using Basalt FRP Laminates
Authors: S Venkat Raman , S Naveen Kumar , Anusha G. , S Jegan , K Kailash Krishnan
Published: May 2024

Concrete structures exposed to high temperatures often experience thermal damage, which can significantly reduce their structural integrity. Fiber-Reinforced Polymer (FRP) wrapping is a common retrofitting technique used to restore the strength and durability of thermally affected concrete. This study investigates the effectiveness of Basalt Fiber-reinforced Polymer wrapping on different concrete specimens with varying orientations of wrapping. This study mainly focuses on various parameters as fiber orientation and wrapping methodology. A series of 15 columns of dimension 150mm x 150mm with a length of 700mm are cast and subjected to axial compression loading in a pre-heated condition until the initial cracking occurs. These cracked columns are made to strengthen using Basalt Fiber with different patterns of orientation of laminates. The retrofitted columns are subjected to axial compression loading to determine their maximum load-bearing capacities. The test results of this experiment is assessed and compared with conventional RC columns of same grade. The strength of retrofitted columns versus conventional ones are compared and analyzed. The maximum load bearing capacity for a particular pattern of wrapping is determined.
Experimental Investigation on Beam with Composite Reinforcement Using Mild Steel Tube In-Filled with Crumb Rubber
Authors: Balasubramaniam N. , Kavinkumar V. , Santhoshkumar T.
Published: May 2024

In today developing consequence, innovative alternates are being familiarized from recycled wastages used in concrete construction. This study concentrates on alternate reinforcement in the structural elements. The conventional reinforcement is replaced by the rubber composite reinforcement using in-filled tubes. The bond relation among the mild steel tube and concrete is simply good. The performance of the composite reinforcement using rubber in-filled tubes are comparing to the conventional reinforcement. The composite reinforcement is made by in-filling the mild steel tubes with cement slurry and crumb rubber. And the crumb rubber gained from the cracker mill. This crumb rubber institutes to the solid waste management. The scrap tires are prepared into crumb rubber and mixed with water – cement in a mortar ratio of 1:1:2 (water: cement: sand) to attain the colloidal consistency. 40% of 177-micron size crumb rubber sieves replaced instead of sand. This crumb rubber constitutes to the solid waste management and light weight. Hence these composite reinforcements will reduce weight of steel in reinforced concrete along with the decrease in cost of construction. This idea inspects the flexural strength of concrete beam with composite reinforcement, Mild steel pipe reinforcement and ordinary reinforcement by third point loading.
Experimental Investigation on Plastic Aggregate and Silica Fume In Concrete
Authors: Kumar S. Pream , Sankar K. Vijay , Nandhini U. , Priyanka M. , Rahul J. Rabiun , Mohanraj S.
Published: May 2024

Plastic consumption is increasing on a daily basis, despite efforts to minimize it. On the other hand, the management of waste plastic was a significant issue in several countries around the world. A healthy and sustainable reuse of plastics has numerous benefits. The acceptability and benefits of recycled plastics as Coarse aggregate in concrete are explored here. Plastic aggregate parameters such as density and specific gravity were determined through tests. Because complete replacement of natural Coarse aggregate with plastic Coarse aggregate is impractical, partial replacement at various percentages was investigated. In addition to that silica fume is added as a binding material at a constant of 10%. The substitution of 15 Percent Plastic aggregate resulted in high compressive, splitting tensile, and flexural strength.
Advancements in Soil Stabilization: The Efficacy of Fly Ash and GGBS
Authors: Raman Ravi Shankar , Lavanya C. , Manjunatha  , Pal Thethi H. , Parmar Ashish , Mohammad Laith H.Q. , Arora Sethi Vandana
Published: May 2024

Engineered soil qualities can be modified mechanically, chemically, or biologically to achieve soil stabilisation. Soil stabilisation is a method used in civil engineering to enhance and enhance a soil’s structural qualities. Mechanical strength, permeation, compressibility, resilience, and plasticity are some of these attributes. The systematic investigation of soil stabilization with fly ash and ground granulated blast furnace slag (GGBS) as binders is presented in this work. The goal of using geopolymer technology is to enhance the mechanical qualities of clay soils for the building of road pavement by substituting conventional cementitious materials. The ideal ratio of Fly Ash to GGBS is found using a Taguchi experimental design technique, more precisely a L9 Orthogonal Array, with the goal of improving soil liquid limit, plastic limit, and plasticity index. The effectiveness of various Fly Ash and GGBS ratios is assessed, as well as their influence on soil behavior. In order to develop models for predicting soil parameters, regression analysis is used. Diagnostic plots show a reasonable fit but also highlight small amounts of unexplained variability. These discoveries have important ramifications for sustainable construction methods and are essential for improving soil stabilizing procedures, especially when it comes to road pavement engineering.
Experimental Study on Rubberized Geopolymer Concrete with Sugarcane Bagasse Ash
Authors: Theres N Kurian Salini , Dominic Jiss
Published: May 2024

The purpose of this experimental investigation is to determine whether it is feasible and effective to use sugarcane bagasse ash (SCBA) in place of some of the cement in rubberized geopolymer concrete. Rubber particles are added to the concrete to improve its ductility and energy absorption capability, while SBA is added as an additional cementitious material to lessen its environmental impact Sugarcane bagasse ash, a byproduct of the sugarcane industry, has the potential to be utilized as an extra cementitious element due to its pozzolanic properties. To improve the concrete mix’s ductility and ability to absorb energy, waste rubber particles are added. Rubberized geopolymer concrete is evaluated in numerous curing circumstances through extensive laboratory testing, which includes compressive strength, flexural strength, and split tensile strength. The study’s findings shed light on whether using SCBA in rubberized geopolymer concrete is feasible and present environmentally friendly options for building applications. The study helps to promote circular economy concepts and environmental sustainability in the building industry by lowering cement usage and utilizing waste rubber resources. The design and optimization of rubberized geopolymer concrete mixes for improved mechanical qualities and durability are among the practical implications that may be applied to promote the use of environmentally friendly building materials. The mechanical characteristics of rubberized geopolymer concrete were assessed through experimental research. This paper is a scientific approach for complying the performance evaluation of strength studies such as Flexural strength, Compressive strength, Split tensile Strength, effect of NaOH molarities and the effect of curing method in rubberized geopolymer concrete that contains SCBA.
Biodegradable Polymer Biomaterials for Tissue Engineering Applications: A Critical Review
Authors: Aishwarya B.K. , V Revathi , Singh Navdeep , Mathew Lijosh , Dhamija Koushal , Fallah Mohammed H. , Kalra Ravi
Published: May 2024

This critical review explores the application of biodegradable polymer biomaterials in tissue engineering, highlighting their potential to revolutionize regenerative medicine and tissue substitute. Biodegradable polymers, due to their ability to mimic the extracellular matrix, offer a sustainable alternative for the development of tissue scaffolds that degrade at a rate matching new tissue formation. This review systematically covers the evolution, types, and applications of those materials, addressing both natural and synthetic polymers. Special attention is given to the fabrication techniques, along with 3-d bioprinting and nano-fabrication, that allow the introduction of scaffolds tailored for unique tissue engineering packages. The evaluation discusses the contemporary demanding situations, together with the balance among mechanical properties and biodegradability, and the mixing of scaffolds with host tissues. furthermore, it delves into future directions, including the development of hybrid biomaterials and the incorporation of bioactive molecules to enhance tissue regeneration. The advancements in biodegradable polymer biomaterials constitute a massive step in the direction of the development of more effective and personalised processes to tissue engineering.
Experimental Analysis of Alternate Refrigerant Mixtures in Refrigeration System
Authors: R Ragavendiran , A Gowrishankar , Hussaini M Mohammadha , G Ravivarman , K N Gunasekaran , Uday Kiran Kasi , R Girimurugan
Published: May 2024

This study focuses on conducting experimental analyses to assess the impact of alternative refrigerant blends within a vapor compression refrigeration system, with the aim of replacing the existing R134a refrigerant. These refrigerant blends are formulated by combining R600a, R1270, and R290 in four distinct mixing ratios. The assessment considers a range of output parameters for these hydrocarbon mixtures, in addition to their environmental implications related to potential global warming and depletion of ozone layer. Based on the comprehensive evaluation of various factors, it has been determined that the refrigerant blends of R290/R600a/R1270 at proportions of 10% R290 / 20% R600a / 70% R1270 by weight and 20% R290 / 20% R600a / 60% R1270 by weight emerge as the most viable alternatives among the tested refrigerant mixing ratios, surpassing R134a in terms of suitability.
A generative approach to explore residential urban form potential based on environmental performance for energy efficiency
Authors: Bhavsar Foram , Gajjar Vibha , Sharma Utpal , Kapadia Darshi
Published: May 2024

The United Nations predicts that by 2050, 70% of people will live in cities, which will bring significant environmental challenges, including climate change and resource depletion. In India, the residential sector account for 30% of total energy consumption. Therefore, it is crucial to optimize energy use in residential structures to address urban population growth, density, and energy efficiency. This study explores the use of genetic algorithms for multi-objective optimization in the design of energy efficient residential urban forms linking urban population growth and environmental concerns. Urban form significantly influences energy consumption within neighborhoods. However, introducing genetic algorithms into urban planning, a field not typically associated with such computational methods, presents considerable challenges. This research addresses complexities such as simulating and optimizing energy use by focusing on the control of solar radiation and the enhancement of natural daylight within residential neighborhoods. It further seeks to enhance the quality of life in open spaces by improving the sky view factor and the sense of spaciousness, adding another layer of complexity to the optimization. In response to these complexities, a framework is developed using the Biomorpher plugin, integrating genetic algorithms in Grasshopper. This research, carried out in Ahmedabad, India, progresses in two primary phases. The experiment progresses in two phases: first, developing prototypes considering factors like Floor Space Index and building types; and second, refining these through multiple design iterations based on environmental criteria. The study generates a diverse range of optimized scenarios, such as low-rise, mid-rise, and high-rise densities, to understand the relationship between residential form and energy consumption. The research identifies energy-efficient configurations through analysis, offering adaptable solutions tailored to specific environmental and spatial contexts.Additionally, it offers a replicable methodology for urban designers and policymakers.
Remediation of waste water through natural coagulants such as lemon and banana peel
Authors: M Haritha , Raju Greeshma , Jacob Anila Mary , Thampi Geethu
Published: May 2024

Water is not only necessary for survival, but it also adds significantly to the quality of our lives. The rapid increase in population, economic expansion, and industrialization in developing nations has led to an unexpected need for water in cities. The capacity for water uses and wastewater generation in residential sectors has significantly risen during the past few decades. Wastewater treatment is an essential procedure in the sanitation system. Reusing resources and adhering to environmental regulations require efficient treatment and pollution management of municipal wastewater resources. The most preferred method for treating wastewater among the many options currently available is the coagulation and flocculation processes. People widely use this treatment due to its low energy consumption, reliability, affordability, and ease of use. This study evaluated the use of banana and lemon peels as coagulants in water treatment using coagulation-flocculation procedures as a potential substitute for alum. We determined the pH and coagulant dose for both banana and lemon peel combinations. The results of this experiment show that lemon peel works well as a coagulant to absorb biological oxygen demand. It has been discovered that the dehydration procedure works better with peels from bananas and lemons. The ideal duration of contact between lemon and banana peels is 90 minutes. For peels of bananas and lemons, the optimal particle size is 300μm, and the ideal dosage of adsorbent is 0.3g.
IoT based solar powered air purifier with air quality monitoring system
Authors: Jose Aparna , Abraham C. , K Soman Akhil , T J Ajumal , Anandakrishna  , Shibu Abison
Published: May 2024

The cornerstone of combating indoor air pollution sustainably lies in integrating solar electricity into air purification systems. This not only
addresses airborne pollutants but also reduces reliance on traditional power sources, promoting environmental preservation and cost savings. The system's effectiveness hinges on real-time AQM and advanced filtering techniques, powered by solar energy. By leveraging solar power, it operates ecoconsciously while maximizing indoor air quality impact. Its design emphasizes energy efficiency without compromising purification efficacy, effectively eliminating allergens, pollutants, and Real-time monitoring empowers users to make informed environmental adjustments by tracking various metrics simultaneously. This comprehensive approach fosters sustainability, efficiency, and real-time control, crucial for enhancing indoor air quality. Additionally, its reliance on solar energy aligns with global efforts towards renewable energy adoption, reducing its ecological footprint. In summary, this solar-powered air filtration system signifies a paradigm shift in combating indoor air pollution, embodying the fusion of sustainability, innovation, and health-conscious design for a healthier indoor environment.
Multicriteria generalized regressive neural federated learning for cloud computing task scheduling and resource allocation
Authors: George Neema , B K Anoop , P Vijayan Vinodh
Published: May 2024

Cloud computing has arisen as a shrewd and well known worldview for people and associations to work with the entrance and use of registering assets through the web.With the rapid growth of cloud computing technology, efficiently running big data applications within minimal time has become a significant challenge. In this dynamic and scalable environment, effective resource allocation and task scheduling of big data applications play pivotal roles in optimizing performance, enhancing efficiency, and ensuring cost-effectiveness. In environments involving remote computing, task scheduling is a crucial consideration. In order to effectively accomplish resource-optimal task scheduling and minimize overall task execution time, a novel technique called Multicriteria Generalized Regressive Neural Federated Learning (MGRNFL) is developed to address the particular issues in cloud systems. Tasks from several users arrive at the cloud server at the start of the procedure. The cloud server's job scheduler then uses Multicriteria Federated Learning to carry out resource-optimal task scheduling. A decentralized machine learning technique called federated learning (FL) enables model training across several tasks that are gathered from cloud computing customers. This decentralized approach primarily focuses on learning from datasets to obtain a global model by aggregating the results of local models. The proposed techniques involve two different steps: local training models and global aggregation models. In the local training model, the task scheduler determines the resource-optimal virtual machine in the cloud server using a Generalized Regression Neural Network (GRNN) based on multicriteria functions of the virtual machine, such as energy, memory, CPU, and bandwidth. Based on these objective functions, resource-efficient virtual machines are determined to schedule multiple user tasks. The locally updated models are then combined and fed into the global aggregation model. Calculated within the global aggregation model is the weighted total of locally updated findings. The algorithm iterates through this process till the maximum number of times. In order to schedule incoming tasks, the resource-optimal virtual machine is found. Various quantitative criteria are used for the experimental evaluation, including makespan, throughput in relation to the number of tasks, and task scheduling efficiency.
The performance of Adsorbing and Removing gaseous acetic acid by activate carbon
Authors: Hsu Chen-Fu , Chen Yu-Tsung , Tseng Chao-Heng
Published: May 2024

Currently, gaseous molecular contaminants (acetic acid) is one of the main factors that cause defects in semiconductors and wafers, reduce product yields in high-tech process plants. Propylene Glycol Monomethyl Ethyl Ether Acetate (PGMEA) is a versatile solvent with many applications. Solvents used in the solder mask process in the manufacture of printed circuit boards (PCBs). The diluent in photoresist and edge bead removers used in semiconductor and wafer fabrication is PGMEA, which forms acetate contaminants through an acid-catalyzed hydrolysis reaction. The concentration standard of acetic acid pollutants in clean rooms is 1ppb.In order to protect the expensive optical components, the acetic acid generated by PGMEA needs to be controlled.For this purpose, the activated carbon filter in the intake filter prevents acetic acid from contaminating the components and corroding the material. In this study, we used the commercially available activated carbon fabricated filter to adsorption of acetic acid. The effect of adsorption under different face velocity (0.03/0.06/0.09 m/s) and initial acetic acid concentrations (4/6/8/10 ppm) were measured according to the principle of ASHRAE 145.1standard. The experimental data are also evaluated for adsorption performance, adsorption capacity, kinetic model of acetic acid adsorption process, and isothermal model of acetic acid adsorption process.The results of the acetic acid adsorption experiment show that MM3000 activated carbon has the highest adsorption capacity and the longest adsorption saturation time than KPL activated carbon. The higher the inlet acetic acid concentration at a fixed wind speed, the shorter the saturation time and the higher the adsorption capacity; the faster the wind speed at a fixed acetic acid concentration, the shorter the saturation time and the higher the adsorption capacity.The Langmuir (R2) of the MM3000 sample is higher than the Freundlich’s coefficient of determination (R2), which indicates that the adsorption phenomenon of the MM3000 sample is more suitable to be described by the Langmuir isothermal adsorption mode, which is the adsorption of a single molecular layer on a homogeneous surface. The Freundlich R2 of the KPL sample is higher than the Langmuir’s coefficient of determination (R2), which means that the adsorption phenomenon of this KPL sample is more suitable to be described by the Freundlich isothermal adsorption mode, and it is a case of adsorption of multiple layers on an inhomogeneous surface. The adsorption of MM3000 activated carbon and KPL activated carbon is more suitable to be described by the proposed second-order adsorption kinetic model, which is a phenomenon of chemisorption.
Establishing the Potential Rice Loss Prediction Model of Climate and Nature Disaster Factors Based on Machine Learning Theory
Authors: Hsu Yun-Ju , Chen Yu-Keng , Tseng Chao-Heng
Published: May 2024

The United Nations points out that extreme climate events are frequent and widespread in the 21st century and have become a global security issue. Artificial intelligence and machine learning have attracted much attention in environmental applications. This study aims at applying machine learning (ML) to rice disaster prediction, and uses SPSS to analyze environmental impact factors. After model training and evaluation, four models are provided, among which short-term prediction results show high accuracy on a single event, which are suitable for water damage, cold damage, and plant diseases and insect pests respectively. In terms of longterm prediction, using future meteorological prediction values to predict potential rice losses is better, especially within a specific time period. Ultimately, relevant units such as the Council of Agriculture or the AgriFood and Food Administration can choose a suitable model based on different purposes (short-term or long-term forecasting).
Hydrogen Integration for Achieving Net-Zero Emissions with Plug-in Fuel Cell Hybrid Electric Vehicles
Authors: Cortez Luis D. , Tapia-Bastidas C.V. , Alava Eduardo , Hidalgo’Crespo José , Amaya Rivas Jorge L.
Published: May 2024

Currently, to achieve net-zero emissions, the transport sector is going through a decarbonization process, with Battery Electric Vehicles (BEVs) leading the race. However, these vehicles present a limited range and high charging time as barriers to replacing 100% of the transport sector. Also, BEVs cannot achieve net-zero emissions given that the electric rechargeable stations are powered by the local grid electricity. Thus, even though electric vehicles do not produce greenhouse gas (GHG) emissions directly; there are indirect emissions linked to the electricity used, relying on the balance between renewable and non-renewable energy sources in the local network. In this study, green Hydrogen is assessed as a possible solution to reach net-zero emissions with Fuel Cell Plug-in Hybrid Electric Vehicles (FC-PHEVs) that count with a greater range. A specific model of a cradle-to-grave life cycle is developed, allowing the assessment of its environmental impacts. Consequently, 3 scenarios are implemented to be assessed and compared using the model. The analysis shows that a considerable part of GHG emissions of Hydrogen implementation is found in its transportation, although research is being carried out on alternative solutions to mitigate this drawback.
Better or worse? Revealing the impact of common institutional ownership on annual report readability
Authors: Jiang Zhenyu , Hu Lingshan , Wang Zongjun
Published: May 2024

Based on the data on Chinese listed companies over the period from 2007–2021, the relationship between common institutional ownership (CIO) and annual report readability (ARR) is revealed in this paper. The results show that CIO reduces ARR. After a series of robustness tests, this conclusion continues to hold. Further analyses indicate that in situations where analyst attention, industry concentration, and media coverage are high, the above negative relationship is more significant. In addition, operational risks play a mediating role between CIO and ARR. This study enriches the evidence supporting the collusive manipulation effect of CIO.
Deciphering of the morpho-physiological traits of two native grasses from Argentina with contrasting drought resistance strategies
Authors: Cenzano Ana M. , Arslan Idris , Furlan Ana , Varela M. Celeste , Reginato Mariana
Published: May 2024

Context Semiarid environments, such as the Patagonian shrublands, are characterised by having shrubby patches surrounded by grasses with different ecophysiological strategies to tolerate long dry periods. Aims We hypothesised that coexisting grasses of the Patagonian rangeland, already classified as drought-escaping or drought-tolerant, have different traits according to the season and the annual rainfall events. Methods Two dominant native grasses were selected: Pappostipa speciosa (evergreen) and Poa ligularis (deciduous). Samples were collected in the four seasons for the term of 1 year. Rainfall events and soil water content of each season were determined. Spring was the wettest season and autumn the driest. Physiological (relative water content, pigments, hormones), biochemical (polyphenols, antioxidant activity) and morphological traits were measured in the four seasons. Key results P. speciosa was characterised by keeping evergreen leaves with high production of polyphenols as secondary metabolites with high antioxidant capacity during the dry autumn and winter seasons. P. ligularis was characterised by high contents of gibberellin (GA1), auxin (IAA), total phenols, total flavonoids and tartaric acid esters, and high antioxidant capacity in roots during the autumn dry season. In addition, P. ligularis leaves had higher content of carotenoids and polyphenols than P. speciosa during the summer dry season. Conclusions The major adaptive strategy to tolerate dry periods is the high activity of the secondary metabolism, mainly in leaves in P. speciosa (a drought-tolerant grass) and in roots in P. ligularis (a drought-escaping grass). Implications Rainfall variations during a year can affect the phenological growth stages and the metabolism of two native grasses from Argentina characterised by different drought resistance mechanisms.
Prebiotic chemical reactivity in solution with quantum accuracy and microsecond sampling using neural network potentials
Authors: Benayad Zakarya , David Rolf , Stirnemann Guillaume
Published: May 2024

While RNA appears as a good candidate for the first autocatalytic systems preceding the emergence of modern life, the synthesis of RNA oligonucleotides without enzymes remains challenging. Because the uncatalyzed reaction is extremely slow, experimental studies bring limited and indirect information on the reaction mechanism, the nature of which remains debated. Here, we develop neural network potentials (NNPs) to study the phosphoester bond formation in water. While NNPs are becoming routinely applied to nonreactive systems or simple reactions, we demonstrate how they can systematically be trained to explore the reaction phase space for complex reactions involving several proton transfers and exchanges of heavy atoms. We then propagate at moderate computational cost hundreds of nanoseconds of a variety of enhanced sampling simulations with quantum accuracy in explicit solvent conditions. The thermodynamically preferred reaction pathway is a concerted, dissociative mechanism, with the transient formation of a metaphosphate transition state and direct participation of water solvent molecules that facilitate the exchange of protons through the nonbridging phosphate oxygens. Associative–dissociative pathways, characterized by a much tighter pentacoordinated phosphate, are higher in free energy. Our simulations also suggest that diprotonated phosphate, whose reactivity is never directly assessed in the experiments, is significantly less reactive than the monoprotonated species, suggesting that it is probably never the reactive species in normal pH conditions. These observations rationalize unexplained experimental results and the temperature dependence of the reaction rate, and they pave the way for the design of more efficient abiotic catalysts and activating groups.