Multiple Environments Research Articles

Atmospheric new particle formation identifier using longitudinal global particle number size distribution data.

Atmospheric new particle formation (NPF) is a naturally occurring phenomenon, during which high concentrations of sub-10 nm particles are created through gas to particle conversion. The NPF is observed in multiple environments around the world. Although it has observable influence onto annual total and ultrafine particle number concentrations (PNC and UFP, respectively), only limited epidemiological studies have investigated whether these particles are associated with adverse health effects. One plausible reason for this limitation may be related to the absence of NPF identifiers available in UFP and PNC data sets. Until recently, the regional NPF events were usually identified manually from particle number size distribution contour plots. Identification of NPF across multi-annual and multiple station data sets remained a tedious task. In this work, we introduce a regional NPF identifier, created using an automated, machine learning based algorithm. The regional NPF event tag was created for 65 measurement sites globally, covering the period from 1996 to 2023. The discussed data set can be used in future studies related to regional NPF.

Transforming Software Development Through Generative AI : A Systematic Analysis of Automated Development Practices

This article presents a comprehensive analysis of the transformative impact of Generative Artificial Intelligence (GenAI) on software development practices. Through systematic evaluation of implementations across multiple development environments, this article demonstrates how GenAI technologies significantly enhance four critical areas of the software development lifecycle: code generation, automated testing, intelligent code review, and predictive failure analysis. The findings indicate a 45% reduction in initial code development time through automated code generation, 60% improvement in test coverage through AI-driven test case creation, and 30% decrease in post-deployment issues through predictive failure analysis. The article employs a mixed-methods approach, combining quantitative analysis of development metrics from 50 software projects with qualitative assessments from 200 professional developers across diverse organizational contexts. Results reveal that organizations implementing GenAI-assisted development workflows experience a mean productivity increase of 37% while maintaining or improving code quality metrics. Additionally, the article identifies key integration challenges and provides a framework for effective GenAI adoption in software development environments. These findings contribute to the growing body of knowledge on AI-assisted software development and offer practical insights for organizations seeking to optimize their development processes through GenAI integration.

Bioinspired cooperation in a heterogeneous robot swarm using ferrofluid artificial pheromones for uncontrolled environments

This article presents a novel bioinspired technology for the cooperation and coordination of heterogeneous robot swarms in uncontrolled environments, utilizing an artificial pheromone composed of magnetized ferrofluids. Communication between different types of robots is achieved indirectly through stigmergy, where messages are inherently associated with specific locations. This approach is advantageous for swarm experimentation outside controlled laboratory spaces, where localization is typically managed through centralized camera systems (e.g. infrared, RGB). Applying pheromone principles has also proven beneficial for various swarm behaviors. We introduce a detection methodology for the artificial ferrofluid pheromone using low-cost magnetic sensors, along with signal processing and parameter characterization. Experiments involved a heterogeneous swarm consisting of two types of robots: one equipped with camera and image processing capabilities and the other with basic sensor technologies. Validation in multiple uncontrolled environments (with varying floor surfaces, wind, and light conditions) demonstrated successful cooperation among robots with differing technological complexities using the proposed technology.

Spectral density modulation and universal Markovian closure of fermionic environments.

The combination of chain-mapping and tensor-network techniques provides a powerful tool for the numerically exact simulation of open quantum systems interacting with structured environments. However, these methods suffer from a quadratic scaling with the physical simulation time, and therefore, they become challenging in the presence of multiple environments. This is particularly true when fermionic environments, well-known to be highly correlated, are considered. In this work, we first illustrate how a thermo-chemical modulation of the spectral density allows replacing the original fermionic environments with equivalent, but simpler, ones. Moreover, we show how this procedure reduces the number of chains needed to model multiple environments. We then provide a derivation of the fermionic Markovian closure construction, consisting of a small collection of damped fermionic modes undergoing a Lindblad-type dynamics and mimicking a continuum of bath modes. We describe, in particular, how the use of the Markovian closure allows for a polynomial reduction of the time complexity of chain-mapping based algorithms when long-time dynamics are needed.

Optimizing the Allocation of Trials to Sub-regions in Crop Variety Testing with Multiple Years and Locations

AbstractField experiments in crop variety testing are conducted in multiple environments. When the targeted growing area can be stratified into sub-regions (zones), a design problem arises regarding the number of trials to be performed in each sub-region. We propose an analytical solution and a computational approach for optimal allocation of trials to sub-regions in multi-environment crop variety testing for multi-year experiments. For our purpose, we use a linear mixed model and we determine allocations that are optimal for the prediction of pairwise linear contrasts of genotype effects. For computations, we use the OptimalDesign package. The analytical results are illustrated by a real data example.

Dynamic Multiobjective Optimization Based on Multi-Environment Knowledge Selection and Transfer

Background: Dynamic multiobjective optimization problems (DMOPs) involve multiple conflicting and time-varying objectives, and dynamic multiobjective algorithms (DMOAs) aim to find Pareto optima that are closer to the real one in the new environment as soon as possible. In particular, the introduction of transfer learning in DMOAs has led to good results in solving DMOPs. However, the selection of valuable historical knowledge and the mitigation of negative transfer remain important problems in existing transfer learning-based DMOAs. Method: A DMOA based on multi-environment knowledge selection and transfer (MST-DMOA) is proposed in this article. First, by clustering historical Pareto optima, some representative solutions that can reflect the main evolutionary information are selected as knowledge of the environment. Second, the similarity between the historical and current environments is evaluated, and then the knowledge of multiple similar environments is selected as valuable historical knowledge to construct the source domain. Third, solutions with high quality in the new environment are obtained to form the target domain, which can better help historical knowledge to adapt to the current environment, thus effectively alleviating negative transfer. Conclusions: We compare the proposed MST-DMOA with five state-of-the-art DMOAs on fourteen benchmark test problems, and the experimental results verify the excellent performance of MST-DMOA in solving DMOPs.

Migración de serverbox hacia un sistema de microservicios aplicando arquitectura vertical

Efficient data management is essential in public administration for the effective operation of municipal cadastral systems. In 2010, the Multifinality Cadastral Modernization Program was implemented, a partnership between the Puebla municipality government and Sistemas de Información Geográfica S.A. de C.V. (SIGSA), which included the ServerBox platform. Over time, the monolithic architecture of ServerBox showed limitations in maintenance, updates, and change deployment. This project hypothesizes that migrating ServerBox to a distributed microservices architecture, using a vertical approach, can overcome these challenges and improve operational areas of the system. The proposed design establishes a modular and scalable structure that facilitates system maintenance and evolution. The implementation includes the development of TagHelpers in ASP.NET Core to simplify HTML element creation and the use of snippets to streamline coding. Additionally, a JSON configuration file is defined to manage multiple deployment environments. This strategic approach to migrating ServerBox to a distributed and vertical architecture offers significant advantages in terms of scalability, maintenance, and software development efficiency, and can serve as a guide for similar projects in public administration.

SERAV Deep-MAD: Deep Learning-Based Security–Reliability–Availability Aware Multiple D2D Environment

The tremendous growth of internet-connected devices can lead to network congestion, making it essential to incorporate new technologies to optimize performance. Thus, Device to Device(D2D) communication has been deemed as an emerging technology that can be used to communicate efficiently. However, establishing a secure and reliable mechanism for Device-to-Device (D2D) communication that ensures security, reliability, and availability poses a significant challenge. To tackle these issues a novel deep learning-based security-reliability-availability aware multiple D2D environment (SERAV Deep-MAD) has been proposed for Secure D-2-D Communication in a Fog environment. The proposed method utilizes a Fully Homomorphic Quantum Diffie Hellman Encryption (FHQDHE) to secure the data while transmitting. The proposed method utilizes the novel secure Quantum Diffie Hellman key exchange (QDHKE) technique for sharing the key to transform the plain data into cipher data, then applies FH operations on the encrypted data before transferring it to the Fog environment. Whenever a client requests data from the Fog, the Fog provider verifies the client's access rights. Moreover, the Attention-based Bi-GRU model is utilized to categorize whether the device is non-attack or attack, if the data is attacked then the proposed model classifies multiple attacks. The NS2 Simulator is used to verify and validate the proposed SERAV Deep-MAD model, and resiliency analysis is done to assess performance. The proposed techniques attain a higher accuracy of 98.18% which is 1.58%, 2.02%, and 2.41% better than MECC, MIMO, andAAKA-D2D respectively.

Connect, care, create: practical framework for physical environment design for person-centred palliative care.

This article aims to explore architectural-rich insights derived from users' experiences within everyday practice in palliative environments and provides a practical framework for healthcare organisations, architects and researchers involved in (re)designing palliative environments for person-centred care. An ethnographic study involving participatory observation was undertaken to gain insight into the influence of palliative environments on the diverse users' subjective experiences. This immersive research took place across multiple palliative environments, encompassing a palliative care unit, a day care centre for palliative care and a hospice located in Belgium. Also, informal conversations and photo-elicitation interviews were conducted with residents, family members, healthcare professionals, volunteers and maintenance staff. Analysing the subjective experiences yielded a practical framework of four architectural atmospheres (proximity, support, engagement, comfort) intended to serve as guiding principles for designing palliative environments. To shape these atmospheres, this article elaborates on 17 spatial aspects and aligns them with real-life experiences of users within palliative environments, thereby enriching and contextualising these insights. This study presents a practical framework encompassing atmospheres, spatial aspects and overarching insights. It is augmented by supplemental material featuring real-life user experiences, all directed towards guiding the design of palliative environments in pursuit of person-centred palliative care. This article advocates for a collaborative, interdisciplinary, holistic design approach that acknowledges these considerations' interconnectedness and considers the users' multiple perspectives. Ultimately, this approach serves as a means of bridging design intentions and actual experiences encountered by users in their real-life contexts to assist healthcare organisations and architects in creating environments for person-centred palliative care.

Governing the Slovenian National Cancer Control Programme - Key Lessons Learnt

Abstract Issue Strategic documents addressing major public health concerns should extend beyond health sector. Cancer control is commonly perceived only as a health issue, thus involving diverse stakeholders is challenging. Description of the problem The inclusion of stakeholders within and beyond the health sector is crucial in the preparation, and through implementation of National Cancer Control Programmes (NCCP). Lessons learned on how to involve and maintain fruitful collaboration with diverse stakeholders in Slovenian NCCP are presented. Results Over the past 14 years Slovenia’s NCCP has built a reliable and reputable partnership with diverse stakeholders, a collaboration that continues to evolve. Efforts extend across multiple sectors, encompassing health, education, employment, research, environment, technology, and non-governmental organizations. NCCP has set up multistakeholder governance structures: an advisory board, board of experts, specialised expert groups, and a group of representatives of cancer hospitals. These groups engage a diverse range of experts and institutions nationwide. Whenever feasible, representatives of patient organizations are included. All these structures hold regular meetings, complemented by an annual event that convenes all stakeholders and also provides an invaluable platform for informal networking. To ensure seamless coordination of all activities, a dedicated team is essential. Our approach has evolved to embrace a dual leadership, comprising both a public health specialist and a clinical expert. Additionally, we benefit from the expertise of communication experts, who offer valuable insights into effectively reaching diverse audiences. Lessons Governing Slovenia’s NCCP by involving diverse stakeholders in planning and implementation activities has demonstrated its effectiveness. Furthermore, we are witnessing an increasing number of new stakeholders actively seeking out to participate in the NCCP. Key messages • Slovenia’s NCCP is recognized for its credibility and strategic approach. • Involving diverse stakeholders in cancer control endeavours has proven effective, fostering trust and partnerships.

Genetic loci associated with sorghum drought tolerance in multiple environments and their sensitivity to environmental covariables.

Climate change can limit yields of naturally resilient crops, like sorghum, challenging global food security. Agriculture under an erratic climate requires tapping into a reservoir of flexible adaptive loci that can lead to lasting yield stability under multiple abiotic stress conditions. Domesticated in the hot and dry regions of Africa, sorghum is considered a harsh crop, which is adapted to important stress factors closely related to climate change. To investigate the genetic basis of drought stress adaptation in sorghum, we used a multi-environment multi-locus genome-wide association study (MEML-GWAS) in a subset of a diverse sorghum association panel (SAP) phenotyped for performance both under well-watered and water stress conditions. We selected environments in Brazil that foreshadow agriculture where both drought and temperature stresses coincide as in many tropical agricultural frontiers. Drought reduced average grain yield (Gy) by up to 50% and also affected flowering time (Ft) and plant height (Ph). We found 15 markers associated with Gy on all sorghum chromosomes except for chromosomes 7 and 9, in addition to loci associated with phenology traits. Loci associated with Gy strongly interacted with the environment in a complex way, while loci associated with phenology traits were less affected by G × E. Studying environmental covariables potentially underpinning G × E, increases in relative humidity and evapotranspiration favored and disfavored grain yield, respectively. High temperatures influenced G × E and reduced sorghum yields, with a ~ 100kgha-1 average decrease in grain yield for each unit increase in maximum temperature between 29 and 38°C. Extreme G × E for sorghum stress resilience poses an additional challenge to breed crops for moving, erratic weather conditions.

Punjab Tar-1: A New Short Duration, High Yielding and Disease Resistance Long Melon Variety (Cucumis melo) Released in Pakistan.

The development of new crop varieties with favorable features is a continuing effort. With the passage of time, a cultivated variety becomes subjected to various biotic and abiotic plant stresses. This article describes development of an innovative and imaginative long melon cultivar called "Punjab Tar-1."This article discusses creation of a novel and inventive long melon variety known as "Punjab Tar-1." Current long melon varieties in Pakistan are sensitive to climatic conditions and susceptible to pest and disease attack. A New Short Duration, High Yielding and Disease Resistance Long Melon Variety (Cucumis melo) is released in Pakistan to address these current issues of long melon varieties A high yielding and early maturing variety of long melon “Punjab Tar-1” has been developed by Vegetable Research Institute, Faisalabad, Pakistan through mass selection. Plants were selected from an open pollinated indigenous source population with main emphasis on earliness, fruit shape, color and taste and yield. Selection intensity was 15% in 1st three selection cycles and 30% in subsequent four selection cycles whereas yield trials were started from 8th selection cycle. The fruit of this variety has a strong longitudinal rib that makes it difficult for eating by caterpillars. This variety has wide adaptability and exhibits stable yield across multiple environments. Notably, "Punjab Tar-1" contains 10.59 % crude protein and 1.08% crude fat content. Genetic uniformity and distinctiveness of this variety was confirmed through SSR polymorphism. Punjab Tar-1 variety has been approved by Punjab Seed Council in its meeting held on 2021 and was recommended for general cultivation in Punjab, Pakistan. Its certified seed is available for farmers at Vegetable Research Institute, Faisalabad. This newly approved variety will aid to save the precious foreign reserves by reducing vegetable seed import bill. In Pakistan, seed market of long melon is occupied by improved varieties. In multi-location evaluation, one said variety has exhibited high yield and stability than exotic germplasm. This is the first variety developed in Pakistan having good taste, early maturity, long shape, and high yield potential. DNA fingerprinting has further confirmed that it is distinct from local material, having novelty and diversity.

Semi-Supervised Online Continual Learning for 3D Object Detection in Mobile Robotics

Continual learning addresses the challenge of acquiring and retaining knowledge over time across multiple tasks and environments. Previous research primarily focuses on offline settings where models learn through increasing tasks from samples paired with ground truth annotations. In this work, we focus on an unsolved, challenging, yet practical scenario, specifically, the semi-supervised online continual learning in autonomous driving and mobile robotics. In our settings, models are tasked with learning new distributions from streaming unlabeled samples and performing 3D object detection as soon as the LiDAR point cloud arrives. Additionally, we conducted experiments on both the KITTI dataset, our newly built IUSL dataset and Canadian Adverse Driving Conditions (CADC) Dataset. The results indicate that our method achieves a balance between rapid adaptation and knowledge retention, showcasing its effectiveness in the dynamic and complex environment of autonomous driving and mobile robotics. The developed ROS packages and IUSL dataset will be publicly available at: https://github.com/npu-ius-lab/OCL3D.

Considerations on time resolution of neutron irradited single pixel 3D structures at fuences up to 1017 neq/cm2 using 120 GeV SPS pion beams

The proven radiation hardness of silicon 3D devices up to fluences of 1 × 1017 neq/cm2 makes them an excellent choice for next generation trackers, providing <10 μm position resolution at a high multiplicity environment. The anticipated pile-up increase at HL-LHC conditions and beyond, requires the addition of <50 ps per hit timing information to successfully resolve displaced and primary vertices. In this study, the timing performance, uniformity and efficiency of neutron and proton irradiated single pixel 3D devices is discussed. Fluences up to 1 × 1017 neq/cm2 in three different geometrical implementations are evaluated using 120 GeV SPS pion beams. A MIMOSA-26 type telescope is used to provide detailed tracking information with a ∼5 μm position resolution. Productions with single- and double-sided processes, yielding active thicknesses of 130 and 230 μm respectively, are examined with varied pixel sizes from 55 × 55 μm2 to 25 × 100 μm2 and a comparative study of field uniformity is presented with respect to electrode geometry. The question of electronics bandwidth is extensively addressed with respect to achievable time resolution, efficiency and collected charge, forming a 3D phase space to which an appropriate operating point can be selected depending on the application requirements.

Exploring Built Environment Visual Interactions: A SoftBIM Data-Driven Approach for a Database About the Outdoor View

Windows and glazed facades provide outdoor views, serving as vital sources of visual information that aid navigation and interaction within buildings. These views can trigger psychological and physiological responses, affecting individual well-being. However, optimizing outdoor view quality is challenging due to the complex interplay of factors influencing the building’s experience of vision. Managing the complexity of optimizing outdoor view quality within current digital frameworks for building design presents significant challenges. A key issue lies in the ambiguity of certain visual metrics, which are often difficult to translate into explicit descriptors of spatial configurations. Even when such metrics are available, their practical use as guiding tools in the design process is frequently obstructed by complex data interoperability procedures. These procedures are necessary to enable seamless data transfer across the multiple software environments involved in the design process. This study advocates for the softBIM paradigm, which optimizes workflows by embedding visual analysis results into target geometries. Supported by this process, the calculation of a metric to measure the impact of existing and planned visual obstructions on the vision of the targeted landmarks is proposed and analysed. This metric is specifically applied to assess the visual information incoming to the vertical facades of building envelopes, a context of application that denotes criteria of assessment different from the ones usually applied in the most established frameworks for visual analysis (e.g., isovist analysis). SoftBIM enables effective automation strategies to aid the metric computation and the processing of the results to implement seamless export and data implementation. The visual metric is built upon implementing the Ladybug suite and addresses the different limitations in the target-based visibility calculation supported by the tool.

Yr29 combined with QYr.nwafu-4BL.3 confers durable resistance to stripe rust in wheat cultivar Jing 411.

The combination of a QTL on chromosome arm 4BL and Yr29 provides durable resistance with no significant yield penalty. Wheat stripe rust or yellow rust (YR), caused by Puccinia striiformis f. sp. tritici (Pst), causes substantial yield reductions globally, but losses can be minimized by using resistance genes. Chinese wheat cultivar Jing 411 (J411) has continued to display an acceptable level of adult-plant resistance (APR) to YR in varied field conditions since its release in the 1990s. A recombinant inbred line (RIL) population comprising 187 lines developed from a cross of J411 and Kenong 9204 (KN9204) was evaluated in multiple environments to identify genomic regions carrying genes for YR resistance. A total of five quantitative trait loci (QTL) on chromosome arm 1BL, 3BS, 4BL, 6BS, and 7BL from J411 and two QTL on 3DS and 7DL from KN9204 were detected using inclusive composite interval mapping with the wheat 660K SNP array. QYr.nwafu-1BL.5 and QYr.nwafu-4BL.3 from J411 were robust and showed similar effects in all environments. QYr.nwafu-1BL.5 was likely the pleiotropic gene of Yr29/Lr46. QYr.nwafu-4BL.3 was located within a 1.0cM interval delimited by KASP markers AX-111609222 and AX-89755491. Based on haplotype analysis, Yr29 and QYr.nwafu-4BL.3 were identified as genetic components of quantitative resistance in a number of wheat cultivars. Moreover, RILs with Yr29 and QYr.nwafu-4BL.3 individually or when combined showed higher resistance to YR in rust nurseries compared with RILs without them, and there was no negative effect of their presence on agronomic traits under rust-free conditions. These results suggest that effective polymerization strategy is important for breeding high yielding and durable resistance cultivars.

Microstructured Reflective Coatings on Commodity Textiles for Passive Personal Cooling.

As the effects of climate change become more severe and widespread, maintaining personal thermal homeostasis becomes necessary for survival. In principle, advanced textiles and garments have the ability to leverage light absorption, transmission and/or reflection, in addition to straightforward convection, to heat or cool bodies in extreme temperature conditions. For cooling, in particular, surfaces adept at selectively reflecting or refracting high-energy incident light (200 nm-2.5 mm) from the sun while transmitting or emitting infrared light (8-13 mm) from radiant body heat boast the ability to maintain cooler body temperatures, even when exposed to direct sunlight and the open sky. Here, we present a strategy to transform common clothing into implements for passive personal cooling. As confirmed by Mie scattering calculations, cheap and biocompatible calcium carbonate and barium sulfate micro/nanoparticles are found to serve as suitable reflectors for radiative cooling. Finite-difference time domain simulations reveal, surprisingly, that higher reflectance is achieved with surface coatings containing these materials, as compared to extruded metamaterial fibers containing CaCO3 and BaSO4 particles embedded within a polymer matrix. A stepwise process involving photoinitiated chemical vapor deposition and ion-exchange driven crystal growth is used to create a lamellar composite coating comprised of alternating CaCO3 and BaSO4 nano/microparticle layers directly on the surface of common fabrics. A polyester poplin fabric coated in this manner shows a cooling ability of up to 8 °C compared to an uncoated sample, achieving a maximum cooling of 6 °C below ambient temperature. Wash and durability testing of the lamellar coating reveal no mechanical degradation and no evident attenuation in the material's performance, affirming its resilience and long-term effectiveness as a functional textile coating for personal cooling. We also assess the performance of our coated fabrics in multiple outdoor environments to conclude that we can achieve up to 3.4 °C of sub-ambient cooling in optically complex built environments.

Age trends of genetic parameters and genotype-by-environment interactions for growth traits of Eucalyptus urophylla clones in South-China.

Eucalyptus urophylla S.T. Blake, an important economic tree species, is widely cultivated as a raw material source for pulpwood, veneer plywood, and sawlog timber in southern China. As a tree in multiple environments, tree-breeding programs can assess genotype by environment (G×E) interactions and identify the suitable genotype for a specific environment. G×E interactions related to growth traits and soil factors have not been adequately studied for clones of Eucalyptus urophylla and its hybrids. To examine this important question, trials containing 20 clones of E. urophylla and its hybrids were established at three sites in southern China: Shankou (SK), Tiantang (TT), and Xiniujiao (XNJ). These sites each have different soil conditions but similar geographical and climatic conditions. With the data across nearly eight years, average phenotypic trends and broad sense repeatability (H2) were modeled, G×E interactions between clones and diverse soil environments were estimated, genetic gains of clones were calculated, and the adaptabilities of E. urophylla clones in different soil environments were compared. Average survival trends for clones tended to show a moderate decrease while growth traits tended to show sharp increases with age. At the same age, sites were ordered for average survival and growth traits as TT>SK>XNJ while H2 values for growth traits by site followed the basic order TT>SK>XNJ. The H2 values for growth traits at SK tended to increase at first, platform, and then smooth with age. The H2 values for growth traits at TT were high and stable across ages, and those at XNJ tended to undulate largely at a relatively low level across ages. Genetic correlations for growth traits between any pair of sites tended to increase at first and then decrease. A genetic correlation was strong between SK and TT, intermediate between SK and XNJ, and weak between TT and XNJ. It was concluded that: (1) clones tended to be adapted better to an environment with acidic and loamy soil with a clay content of about 45.6%, the soil depth from the surface to parent material about 1.5 m, and the previous vegetation of Eucalypts. (2) The G×E interactions between clones and sites are weaker if the environmental conditions between the sites are similar, and which are stronger if the environmental conditions between the sites are different. (3) The optimum selection age for clones ranged from 1.5 to 3.5 years old, while the optimum selection growth trait is individual tree volume.

Identification of Climate-Smart Bread Wheat (Triticum aestivum L.) Germplasm for Optimum Moisture Areas of Ethiopia

Ethiopia's Bread Wheat Breeding Program conducts annual multi-environment yield trials to develop advanced wheat genotypes for Ethiopian wheat cultivation, ensuring a steady supply of new and improved varieties to meet production and marketing challenges. The objective of this research was to assess potential yield and the interactions between genotype and environment in wheat across multiple environments, as every cultivar has a distinct response to soil and climate. The BLUP analysis reveals that the 22AA and 22KU trials in 2022, along with 21KU trials in 2021 yielded high grain production, indicating optimal testing locations for distinguishing bread wheat genotypes and agroecologies. The study found that seven out of sixteen trials exhibited a higher genetic variance for yield, indicating high genotype discriminating power, with estimates ranging from 0.043 to 0.989 for genetic variance, 0.084 to 1.147 for error variance, and 72.7 to 96.4 for heritability. EBW202471 and EBW202473 are stable genotypes with good yield performance across correlated locations, with EBW202471 showing the highest yield (4.98 t/ha) and Deka showing a lower yield (4.07 t/ha). Three wheat genotypes, EBW202471, EBW202472, and EBW202473, were found to be moderately resistant to moderately susceptible to stem and yellow rust among 20 wheat genotypes. Finally, the two genotypes, EBW202471 and EBW202473, were advanced to National Performance Trials to evaluate their performance alongside top genotypes from regional federal research centers and to be released as new varieties.

Joint Decoding Technique for Collision Resolution in Non-orthogonal Multiple Access Environment

Multiple access technologies have grown hand in hand from the first generation to the 5th Generation (5G) with both performance and quality improvement. Non-Orthogonal Multiple Access (NOMA) is the recent multiple access technology adopted in the 5G communication technology. Capacity requirements of wireless networks have grown to a large extent with the penetration of ultra-high-definition video transmission, Internet of Things (IoT), and virtual reality applications taking ground in the recent future. This paper develops the Physical Layer Network Coding (PNC) for collision resolution in a NOMA environment with two users. Traditionally NOMA uses Successive Interference Cancellation (SIC) for collision resolution. While additionally a decoding algorithm is added along with SIC to improve the performance of the collision resolution. MATLAB-based simulation is developed on the NOMA environment with two users using Viterbi coding, Low-Density Parity Check (LDPC), and Turbo coding. Performance parameters of Bit Error Rate (BER) and throughput are compared for these three algorithms. It is observed that the Turbo coding performed better among these three algorithms both in the BER and throughput. The BER obtained from the SIC- Turbo is found to be performing well with an increase of about 14% from the ordinary SIC implementation. The performance of the collision resolution has increased by 13% to 14% when joint decoding techniques are used and thus increasing the throughput of the NOMA paradigm.