Research Outcomes Research Articles

Enhancing Recovery of Ultra-Fine Magnetite from Low-Iron-Grade Cyanidation Tailings by Optimizing Flow Field Parameters of Low-Intensity Magnetic Separation (LIMS)

The characteristics of iron minerals in cyanidation tailings with a low iron grade were determined via chemical composition analysis, iron phase analysis, and mineral liberation analysis (MLA). The results showed that the cyanidation tailings contained 15.68% iron, mainly occurring in the form of magnetite (19.66%) and limonite (79.91%), in which 16.52% magnetite and 65.90% limonite particles were fully liberated. Most ultra-fine magnetite grains were adjacent and wrapped with limonite to form complex intergrowths, which resulted in low-efficiency magnetite recovery in low-intensity magnetic separation (LIMS) and adversely affected the downstream high-gradient magnetic separation (HGMS) process. Thus, in this work, the optimization of the flow field was proposed to enhance the separation of ultra-fine magnetite from the cyanidation tailings using pilot-scale LIMS separation, and the controllable parameters (including feed flow, separation gap, drum rotating speed, and solid weight) affecting ultra-fine magnetite capture were investigated. Under optimized conditions, a high-grade magnetite concentrate assaying 63.31% Fe with 86.46% magnetite recovery was produced, which, respectively, increased by 0.76% and 15.22%, compared with those obtained from industrial production. In addition, from the flow dynamics simulation, it was found that the magnetite particles in the −6 µm ultra-fine fraction were lost much more easily than those of coarser fractions due to the relatively enhanced hydrodynamic drag force acting on the particles compared with the magnetic force. However, this loss would be effectively reduced with the regulation and control of the flow field. The iron recoveries in the −16~+6 µm and −6 µm fractions of magnetite concentrate increased by 3.66% and 4.42%, respectively, under optimized hydrodynamic conditions. This research outcome provides a valuable reference for the economic and effective utilization of iron resources from such solid wastes.

Novel Biocomposite of Starch and Flax Fiber Modified with Tannic Acid with Biocidal Properties.

The purpose of this paper was to develop novel biocomposites with biocidal properties in microorganisms, with enhanced mechanical strength and hydrophobicity as well as with increased biodegradation rates. The main idea and the novelty of this work was to use cross-linking compounds and, at the same time, biocidal compounds-natural compounds of plant origin with biocidal properties. The authors assumed that the modification of flax fiber by natural plant compound will reduce the hydrophilicity of novel biocompositie. Biopolymer based on thermoplastic starch reinforced with flax fibres modified with tannic acid (TA) was prepared by extrusion and injection molding processes. The effects of TA modification on the mechanical and structural properties of biocomposites were analyzed through DMA, tensile tests, DSC, and TG. The biocidal and wettability properties of the biocomposites were investigated. The article also discusses the outcomes of research conducted on the structural characteristics and rates of the biodegradation of biocomposites.

The effect of the COVID-19 pandemic on TOM in the housing market

Purpose The COVID-19 pandemic, a sudden and disruptive external shock to the USA and global economy, profoundly affected various operations. Thus, it becomes imperative to investigate the repercussions of this pandemic on the US housing market. This study investigates the impact of the COVID-19 pandemic on a crucial facet of the real estate market: the Time on the Market (TOM). Therefore, this study aims to ascertain the net effect of this unprecedented event after controlling for economic influences and real estate market variations. Design/methodology/approach Monthly time series data were collected for the period of January 2010 through December 2022 for statistical analysis. Given the temporal nature of the data, we conducted the Durbin–Watson test on the OLS residuals to ascertain the presence of autocorrelation. Subsequently, we used the generalized regression model to mitigate any identified issues of autocorrelation. However, it is important to note that the response variable derived from count data (specifically, the median number of months), which may not conform to the normality assumption associated with standard regression models. To better accommodate this, we opted to use Poisson regression as an alternative approach. Additionally, recognizing the possibility of overdispersion in the count data, we also explored the application of the negative binomial model as a means to address this concern, if present. Findings This study’s findings offer an insightful perspective on the housing market’s resilience in the face of COVID-19 external shock, aligning with previous research outcomes. Although TOM showed a decrease of around 10 days with standard regression and 27% with Poisson regression during the COVID-19 pandemic, it is noteworthy that this reduction lacked statistical significance in both models. As such, the impact of COVID-19 on TOM, and consequently on the housing market, appears less dramatic than initially anticipated. Originality/value This research deepens our understanding of the complex lead–lag relationships between key factors, ultimately facilitating an early indication of housing price movements. It extends the existing literature by scrutinizing the impact of the COVID-19 pandemic on the TOM. From a pragmatic viewpoint, this research carries valuable implications for real estate professionals and policymakers. It equips them with the tools to assess the prevailing conditions of the real estate market and to prepare for potential shifts in market dynamics. Specifically, both investors and policymakers are urged to remain vigilant in monitoring changes in the inventory of houses for sale. This vigilant approach can serve as an early warning system for upcoming market changes, helping stakeholders make well-informed decisions.

Evaluation of GIScience Exercise Using Online Educational Materials for Japanese University Students

GIScience is essential to geography education. Different curriculums and textbooks have been developed to teach GIScience in classrooms through lectures and exercises corresponding to the educational situation of each country. We developed e-learning materials based on existing research outcomes for GIScience education in Japan, such as the Japanese GIS core curriculum for university education. Using the materials, we held a three-day intensive GIScience class at the University of Tokyo from 2018 to 2022 with questionnaire surveys to investigate the educational effects of the materials and factors influencing GIScience learning. The attending students browsed the materials and studied GIScience by themselves but asked questions of teachers if necessary. The questionnaire survey results indicate that most students felt geospatial data processing is somewhat complex, but they were satisfied with the opportunity of GIScience learning. Whether the students thought the exercise was simple and easy depended on their confidence in computer knowledge and operation and their preferred learning style at their own pace. The students’ satisfaction level and ease in using the material correlate with their motivation level, the number of questions they asked the others, and their preferred style for learning at their own pace.

Assessing meat quality and textural properties of broiler chickens: the impact of voltage and frequency in reversible electrical water-bath stunning

The implementation of the head-only electrical stunning procedure in poultry processing has been aimed at enhancing eating, ethical, and religious quality. However, inconsistencies in voltage and frequency standardization, along with variations in previous research outcomes, have led to numerous cases of both under-stunned and over-stunned birds. Thus, this study aimed to comprehensively evaluate the effects of varying voltages and frequencies during electrical water bath stunning on carcass quality, meat attributes, and textural properties in broiler chickens. A cohort of 240 healthy female broilers (Cobb 500, 42-days-old, 2 kg ± 0.1 kg) was meticulously selected from a commercial farm. The birds underwent exposure to different stunning voltages (2.5, 10.5, 30, and 40 V) and frequencies (50 and 300 Hz). Subsequent analyses were conducted on meat samples to assess physicochemical properties, carcass quality, and textural attributes. The findings revealed a higher incidence of petechial hemorrhage (P < 0.05) in birds stunned at 10.5 V compared to other voltage. Notably, no broken bones were recorded in birds subjected to high voltages (30 and 40 V). Low frequency (50 Hz) significantly increased the occurrence of petechial hemorrhage and simultaneously resulted in pectoralis major muscle with decreased redness (a*). Birds subjected to the 10.5 V stunning treatment exhibited a lower cooking loss percentage. Significant interactions between voltage and ageing (V × A) were observed. Birds stunned at 30 V and aged for 7 d displayed highest drip loss compared to a one-day ageing period across different voltage levels. This interaction also impacted pH values, with birds subjected to 10.5 V showing significantly lower (P < 0.05) pH at d 7 of ageing. The meat hardness was influenced by the V × A interaction, wherein birds stunned at 10.5 V exhibited lower hardness after one day of ageing compared to other voltage levels. Red wing tips, lightness (L*), adhesiveness, and resilience were also significantly impacted (P < 0.05) by the interaction between frequency and voltage. A notable 3-way interaction was observed for gumminess and chewiness (F × V × A), where the 2-way interaction between frequency and voltage (F × V) affected both parameters differently at various ageing periods. Additionally, there was a significant interaction (P < 0.05) between frequency and voltage influencing shear strength and yellowness.

Multi-metric evaluation of the optimal intensity measure for mainshock-aftershock fragility analysis of transmission towers

Identifying the optimal intensity measure (IM) contributes to reducing uncertainties in probabilistic seismic demand models (PSDM) and enhancing confidence of their results. Although many studies have discussed appropriate IMs for mainshocks, relatively less attention is paid to the potential aftershock effect. In particularly, the optimal IMs for developing PSDM of transmission towers subjected to sequential earthquakes has not been well studied previously. Therefore, this paper conducts a multi-metric evaluation to identify the optimal IM in the context of mainshock-aftershock (MSAS) fragility analysis of transmission towers. This evaluation process includes collecting a set of ground motions recorded with varying magnitudes and fault distances to construct MSAS sequences, followed by comprehensive discussions on their seismic characteristics by comparing thirty-six potential IMs candidates. Additionally, a finite element model of a transmission tower is established to numerically investigate different engineering demand parameters (EDP) of the tower under the selected MSAS sequences. The optimal PSDM of the transmission tower is determined by evaluating each couple of IM−EDP on a logarithmic space using multiple evaluation metrics. Through this analysis, the first-mode spectral acceleration Sa(T1,ξ) is identified as the optimal IM as it exhibits excellent correlation, efficiency, practicality and proficiency with the EDPs of the transmission tower, especially with the inter-segment displacement ratio. Consequently, seismic fragility curves of the transmission tower are developed using the optimal IM. The research outcome can contribute to improving the understanding of the probabilistic assessment of transmission towers in the MSAS scenario.

Exploring the Influence of Dynamic Indicators in Urban Spaces on Residents’ Environmental Behavior: A Case Study in Shanghai Utilizing Mixed-Methods Approach and Artificial Neural Network (ANN) Modeling

The main aim of this article is to evaluate the impact of dynamic indicators associated with urban spaces on the environmental behavior of residents in Shanghai, China. With the city experiencing rapid urbanization and increasing environmental concerns, it is crucial to understand how the design and management of urban spaces can encourage pro-environmental attitudes and actions among the population. The study specifically focuses on dynamic indicators, namely vitality, accessibility, quality, and walkability, to develop a comprehensive understanding of the utilization and experience of urban spaces. The research outcomes will make valuable contributions towards Shanghai’s objectives of achieving environmental sustainability, while also providing insights that have broader relevance to sustainable urban development globally. As the built environment significantly influences energy consumption, resource utilization, pollution generation, and overall human wellbeing, attaining urban sustainability is of paramount importance. The findings of this study will aid in informing strategies and policies that promote sustainable practices, not only benefiting Shanghai but also serving as a valuable resource for urban development initiatives worldwide. Sustainable urban design principles, including compactness, density, mixed land use, greening, and walkability, have been associated with pro-environmental behaviors, including reduced reliance on automobiles, increased walking and cycling, and heightened environmental consciousness. Nevertheless, the relationship between the built environment and sustainability behaviors is intricate and is influenced by multiple factors. Consequently, further research is necessary to comprehend how specific spatial and temporal dynamics impact environmental behaviors within urban settings. In this study, an artificial neural network (ANN) was developed to estimate the quality and walkability of an area and environmental behaviors by considering the augmented vitality and accessibility factors. The ANN’s predictions demonstrate that higher levels of vitality and accessibility positively contribute to improved walkability and environmental behaviors. The accuracy of the ANN’s predictions was assessed using linear regression, which yielded acceptable error rates when compared with experimental results.

Non-Destructive Testing and Synergistic Investigation of a Historic Tower

This paper focuses on the reliability of a synergistic procedure, involving dynamic tests complemented by documentary and architectural research, for the structural assessment of heritage towers. The reliability of the presented method is exemplified in a relevant case study, the Zuccaro’s Tower in Mantua. As is known, historic buildings require addressed procedures in order to consider past building transformation and eventual damage/decay, which can affect the masonry properties and, more generally, the structural behavior. The proposed investigation procedure is based on multidisciplinary information (i.e., merging data) from historical and document studies, direct inspections, surveys of geometry and front surfaces, and dynamic tests in operational conditions. The processed information allowed the development and the calibration of a simplified numerical model, useful in driving the seismic/structural assessment of the tower. The results of past investigations, found during the archival research, contributed to the structural evaluation. This paper describes the main research outcomes and the model tuning with a special focus on the key role of the synergy between the applied methods for the assessment of a historic building.

Electro-induced biochar-embedded-SIPN hydrogel as discrete bipolar electrodes for selective oxidation and enrichment of trace thallium(Ι)

Electrochemical techniques for thallium (Tl) treatment face a substantial challenge linked to the concentration of Tl(I), hindering the efficient removal and recovery of trace Tl(I) (μg L−1). In response, we synthesized hydrogel particles incorporating biochar (BC) within semi-interpenetrating polymer networks (SIPN), showcasing robust selectivity for Tl(I). These biochar-embedded-SIPN hydrogel particles (BC-SIPN particles), employed as dispersed electrodes, facilitated the targeted oxidation and enrichment of Tl(I) through electro-induction. Research outcomes elucidate the adept mitigation of the “efficiency-dependent concentration” behavior by electro-induced BC-SIPN particles during the reaction process. Under optimized conditions (pH 12, 2 V cm−1, 30 min), Tl(I) removal efficiency surpassed 98 % at an initial concentration of 100 μg L−1. The SIPN structure enhanced particle stability, and after seven cycles of enrichment in a 100 μg L−1 Tl(I) environment, BC-SIPN particles achieved a Tl content of 0.073 %, meeting Tl mineral content standards and promoting the recovery of scarce Tl resources. First-principles calculations underscore the pivotal role of hydrogen bond-electrostatic interactions between TlOH(aq) and particles in driving selective Tl(I) adsorption. Insights from quenching and capture reactions reveal a predominant direct oxidation pathway of Tl(I) to Tl(Ⅲ), complemented by indirect oxidation driven by reactive oxygen species, including OH, O- 2 and 1O2. This study presents an innovative approach for trace Tl(I) wastewater treatment, simultaneously mitigating the “efficiency-dependent concentration” phenomenon, and underscores the transformative potential of electro-induced BC-SIPN hydrogel particles in offering sustainable solutions for Tl(I) removal and resource recovery in environmental stewardship.

The role of incentive policies and personal innovativeness in consumers' carbon footprint tracking apps adoption in China

The annual global greenhouse gas emissions are predicted to increase by 124% in 2030, higher than what is required to decrease the global temperature. China is the leading source of carbon emissions related to consumption and has become the focal point of worldwide efforts to lower carbon emissions. Using applications that monitor individual consumption and offer emissions reports will aid consumers in effectively controlling and mitigating their carbon footprint. There is a dearth of consumer understanding regarding the consequences of their everyday consumption-related carbon emissions. This paper uses Shanghai as the study area to assess the variables that encourage consumers to use carbon footprint monitoring applications in China. The integrated technology acceptance model (TAM) and theory of planned behaviour (TPB) were expanded to include personal innovativeness and incentive policies to achieve this aim. In total, 571 responses to legitimate questionnaires were collected. An empirical assessment was conducted using a structural equation modeling to examine the variables impacting consumers' usage of carbon footprint monitoring applications. The results suggest that personal innovativeness, incentive policies, attitude, subjective norm, perceived behavioural control, perceived usefulness, and perceived ease-of-use influence consumers' usage of carbon footprint monitoring applications positively and significantly. The research outcomes provide complete insight into consumer behaviour concerning adopting carbon footprint tracking apps. Besides, the study offers policy implications for decision-makers and potential stakeholders.

Exploring the Dynamics of Japanese Research Culture: A Case Study on Postgraduate Studies

The research culture in Japan shapes the country's academic landscape and scientific output quality. This study examines the unique characteristics and challenges of Japanese research culture among postgraduate studies by exploring research practices, institutional frameworks, mentor-student relationships, collaboration patterns, publication norms, and funding mechanisms. The findings contribute to existing knowledge, inform policymakers and educators, and emphasize the importance of understanding Japanese research culture for fostering collaboration, interdisciplinary research, and international engagement. The case study approach, with interviews from subject matter experts, provides in-depth insights and acknowledges limitations while adhering to ethical guidelines. The research highlights the prioritization of precision and fundamental research, supported by institutional frameworks, collaborative environments, and publication norms that value timely dissemination of research outcomes. These insights offer a comprehensive understanding of Japanese research culture and serve as a foundation for future initiatives aimed at enhancing research practices both in Japan and globally.

Housing-industry transformation development and rural revitalization path based on complex adaptive system in Three Gorges Reservoir Area of China

The core of dual circulation in the Three Gorges Reservoir Area (TGRA) and the greening Yangtze River is sustainable development. Reservoir housing-industry coordinate sustainable is extremely important to ensuring a more sustainable TGRA. Here, we investigate the overall characteristics of housing-industry transformation development and rural revitalization path in the TGRA at microscopic perspective. Taking Wutu village (WTV), a historical and cultural rural in the TGRA, as case study area, we also analyze the evolution, stage characteristics, and trends of housing-industry system (HIS) using theoretical analysis and empirical research from the perspective of spatio-temporal-development and complex adaptability system model. The findings reveal that: (1) In the traditional housing-industry separation stage(1978–1998), the development of villagers' self-organization and the positive and correct leadership of the village party branch are the dominant forces for the evolution of HIS in WTV. The adaptive behavior of the main body and the strength of the housing-industry effect are limited, and the evolution of the HIS is in the accumulation stage of quantitative change. (2) In the stage of cooperative transformation of housing-industry (1999–2018), the positive and correct leadership of the village party branch is the dominant force of the evolution of HIS in WTV, and the government's policy support is the main force of the evolution of HIS in WTV. (3) In the stage of modern housing-industry integration (2019 to present), the interaction of multiple subjects is the dominant force in the evolution of HIS in WTV. Multiple entities further adapt to various changes in the external environment, and the system structure and level have taken a qualitative leap. Overall, the evolution of HIS in WTV is a dynamic and continuous process. Based on the evolution stage and driving mechanism of HIS, it is necessary to improve the self-organization and adaptive response and ability of the complex adaptive system in WTV, adapt to the general law of system evolution, and effectively regulate the transformation and upgrading of HIS in WTV. Our research outcomes offer valuable insights for fostering rural transformation, enhancing the housing-industry environment, and ultimately propelling the TGRA towards a more sustainable and prosperous future.

Cryoanalgesia as the Essential Element of Enhanced Recovery after Surgery (ERAS) in Children Undergoing Thoracic Surgery-Scoping Review.

This article aims to present cryoanalgesia as an inventive strategy for pain alleviation among pediatric patients. It underlines the tremendous need to align pain management with the principles of the enhanced recovery after surgery (ERAS) approach. The aim of the study was to review the patient outcomes of nerve cryoanalgesia during surgery reported with regard to ERAS in the literature. The literature search was performed using PubMed and Embase to identify articles on the use of cryoanalgesia in children. It excluded editorials, reviews, meta-analyses, and non-English articles. The analysis focused on the study methods, data analysis, patient selection, and patient follow-up. This review includes a total of 25 articles. Three of the articles report the results of cryoanalgesia implemented in ERAS protocol in children. The research outcome indicates shortened hospital stay, potential reduction in opioid dosage, and significant progress in physical rehabilitation. This paper also describes the first intraoperative utilization of intercostal nerve cryoanalgesia during the Nuss procedure in Poland, highlighting its effectiveness in pain management. Adding the cryoanalgesia procedure to multimodal analgesia protocol may facilitate the implementation of the ERAS protocol in pediatric patients.

Rating Patients in Different Languages: Reliability and Validity.

Research outcomes in mental health disciplines are usually assessed using rating instruments that were developed as English language versions. However, in countries such as India, English is not the native language, and patients at even a single research center may speak in different regional tongues. It is permissible to assess such patients using rater-administered English language instruments designed to be scored after an unstructured interview conducted in the patient's preferred language. For many reasons, related to reliability and validity, it is not permissible to assess such patients in their preferred language by translating, impromptu, from English language versions of instruments that were designed to be self-administered or administered as a structured interview. In such situations, standardized, local language versions of the instruments should be used; that is, local language versions with established reliability and validity.

Endocan: A biomarker for endothelial dysfunction and inflammation, linking maternal obesity and pediatric obesity in a cohort of preterm neonates

ObjectivesNumerous animal and epidemiologic studies have demonstrated a positive association between maternal obesity in pregnancy and obesity in offspring. The biologic mechanisms of this association remain under investigation. One proposed mechanism includes fetoplacental endothelial dysfunction secondary to inflammation. Endocan is a relatively new biomarker for endothelial dysfunction and inflammation. Our objectives were to examine (1) the association between maternal obesity and neonatal serum endocan at birth, and (2) the association between neonatal serum endocan at birth and pediatric obesity at 24–36 months of age. Study DesignThis was a secondary analysis of a prospective cohort of neonates born < 33 weeks gestation. Serum endocan was collected within 48 hours of birth. Serum endocan levels were compared in neonates born to obese mothers vs. those born to non-obese mothers. BMI data were retrospectively collected from cohort neonates between 24 and 36 months of age. ResultsThe analysis included 120 mother/neonate dyads. Neonates born to obese mothers had higher median serum endocan at birth compared to neonates born to non-obese mothers (299 ng/L [205–586] vs. 251 ng/L [164–339], p = 0.045). In a linear regression modeled on neonatal serum endocan level, maternal obesity had a statistically significant positive association (p = 0.021). Higher mean serum endocan level at birth was associated with pediatric obesity between 24 and 36 months (obese vs. non-obese offspring; 574 ng/L (222) vs. 321 ng/L (166), p = 0.005). ConclusionsIn our cohort of preterm neonates, elevated serum endocan at birth was associated with both maternal obesity and downstream pediatric obesity. More research is needed to understand intergenerational transmission of obesity. A large focus has been on epigenetic modification. Endothelial dysfunction and inflammation may play important roles in these pathways. Effective biomarkers, including endocan, may also serve as intermediate outcomes in future pregnancy research.

THE IMPACT OF ALBEDO, CLOUD COVERS AND GLOBAL SOLAR RADIATION ON GLOBAL WARMING USING UYO COUNTY DATA, NIGERIA

Ways of countering the causes global warming is the world involve all researchers. The impact of albedo, cloud covers and global solar radiation on global warming have been studied using atmospheric data from Uyo. The data was obtained from NIMET. The outcomes were achieved using Microsoft Excel and SPSS packages. The result obtained showed that albedo varies directly with cloud covers and indirectly with the surface temperature and global solar radiation. The mean values of albedo, cloud cover and global solar radiation are 0.5823 (about 58), 72.25 and 15.22358 MJmday. The challenge of low performance of the solar energy systems from April to October is possible. Uyo may be seen as an unvegetated land, devoid of snow according to this research outcome. Making Uyo a fully forested land, global solar radiation would increase, leading to a decrease in cloud cover. This practice would add to the possible way of resolving the challenge of global warming.

Designing Sustainability Today: An Analytical Framework for a Design for Sustainability Model in European Fashion and Furniture Industries

The proposed article addresses pressing sustainability challenges, advocating for a profound transformation of existing development models, particularly emphasizing sustainable production and lifestyles. Utilizing a research method grounded in a comprehensive international knowledge base, the study explores the evolution of design for sustainability (DfS) approaches. Its significant contribution lies in systematically investigating connections among diverse DfS approaches, providing an initial framework for situating practices within the fashion and furniture industries. The research outcomes obtained iteratively involve mapping design-driven sustainability practices in European fashion and furniture companies. This mapping reveals a transition from a product-centric to an organization-centered design perspective, calling for a holistic ecosystemic framework to revolutionize business operations. The article analyzes contemporary design-driven practices, proposing an interpretative model that identifies ongoing practices fostering incremental changes toward sustainability guided by design. Furthermore, the article outlines a three-stage design-driven sustainability continuum, synthesizing potential future trajectories. Beyond contributing to the understanding of current practices, the research provides insights into future possibilities, highlighting the transformative role of design in reshaping consumeristic systems. Ultimately, the study offers valuable insights into the transformative power of design, paving the way for sustainable business practices in the fashion and furniture industries.

Enhancing Aboveground Biomass Prediction through Integration of the SCDR Paradigm into the U-Like Hierarchical Residual Fusion Model.

Deep learning methodologies employed for biomass prediction often neglect the intricate relationships between labels and samples, resulting in suboptimal predictive performance. This paper introduces an advanced supervised contrastive learning technique, termed Improved Supervised Contrastive Deep Regression (SCDR), which is adept at effectively capturing the nuanced relationships between samples and labels in the feature space, thereby mitigating this limitation. Simultaneously, we propose the U-like Hierarchical Residual Fusion Network (BioUMixer), a bespoke biomass prediction network tailored for image data. BioUMixer enhances feature extraction from biomass image data, facilitating information exchange and fusion while considering both global and local features within the images. The efficacy of the proposed method is validated on the Pepper_Biomass dataset, which encompasses over 600 original images paired with corresponding biomass labels. The results demonstrate a noteworthy enhancement in deep regression tasks, as evidenced by performance metrics on the Pepper_Biomass dataset, including RMSE = 252.18, MAE = 201.98, and MAPE = 0.107. Additionally, assessment on the publicly accessible GrassClover dataset yields metrics of RMSE = 47.92, MAE = 31.74, and MAPE = 0.192. This study not only introduces a novel approach but also provides compelling empirical evidence supporting the digitization and precision improvement of agricultural technology. The research outcomes align closely with the identified problem and research statement, underscoring the significance of the proposed methodologies in advancing the field of biomass prediction through state-of-the-art deep learning techniques.

How Satellite Imaging and Deep Learning are Influenced by Tensor Decompositions: A Review

This study focuses on examining various approaches for Tensor decomposition (TDs) and their potential applications in satellite imaging (SI) and deep learning (DL). The research highlights how these decompositions can contribute to the advancement of SI and DL, providing valuable insights for future utilization of TDs in research. It explores how these techniques contribute to the advancement of SI and DL methods, providing insights into their potential applications and suggesting future research directions. The study aims to enhance the use of TDs techniques to further advance research efforts in these fields. More importantly, the current investigation offers a thorough analysis of the potential advantages and reasons for employing TDs techniques in different domains, including satellite imaging and deep learning. The aim is to enhance research outcomes by utilizing TDs. The review also identifies unresolved issues and proposes future directions for further investigation in this field. Fundamentally, these proposed open problems will open new grounds to the research community to articulate, innovate, and provide more real-life applications to improve the current state of the art by delving into a wider vision for a higher-level performance of both satellite imaging (SI) and deep learning (DL). Looking at the bigger scenario, this also suggests that TDs could be potentially employed to revolutionize existing machine learning technologies as well as the current space AI industry

SHOWING UP AND OPENING UP: CONDUCTING RESEARCH WITH AND ABOUT REFUGEE RESETTLEMENT ORGANIZATIONS

ABSTRACT This article uses research conducted with and about refugee resettlement agencies in traditional and nontraditional destinations to critically assess the opportunities and constraints that social scientists encounter when conducting research on refugee incorporation experiences. Drawing on ethnographic field notes and reflections from two qualitative research projects in the U.S. Northeast and Midwest examining refugee incorporation postresettlement, we analyze how the geographic and institutional contexts in the case studies impacted research outcomes and differences in refugee participants’ showing up and opening up during data collection. We describe how the priorities of refugee resettlement agencies, along with the social locations and positionality of researchers, shaped our relationships and negotiations with institutional gatekeepers, as well as how refugee participants responded to the research. We show how conducting community-based research can introduce overlapping and conflicting reciprocal moral obligations between researchers, refugee participants, and refugee-serving organizations that ultimately shape the research process, decisions, and outcomes.