bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating the Efficacy of Non-Invasive Mechanical Ventilation in Managing Acute Exacerbations of COPD in a Tertiary Care Centre Hapur Uttar Pradesh
Authors: khan Raja , Kaushik Ashish , Gupta Shubhendu , Garg Lalit
Published: August 2024

Background- COPD is currently ranked among the top 3 rd.leading leading cause of mortality globally, with ninety percent of .the. mortality concentrated .in under developed and developing nations COPD poses a huge healthcare issue that is either preventable or treatable (COPD) is a bigger cause of long-term illness and mortality globally. Numerous patients endure this condition for extended periods and experience premature death as a result of the disease itself or its associated complications. The implementation and extensive adoption of non- invasive mechanical ventilation (NIMV) have significantly transformed the management and survival outcomes for patients experiencing exacerbations of chronic obstructive pulmonary disease (COPD). This observational study aims to evaluate the outcomes of NIMV in AECOPD within our hospital setting.  Objective:- To monitor and analyze the outcomes of patients managed with .non-.invasive mechanical. ventilation, specifically focusing on the necessity for endo-tracheal intubation, .mechanical .ventilation, & improvements in .A.B.G levels & vital signs.  Material and Method:- This observational study was conducted on 100 patients with COPD. This study observed patients who underwent NIMV receiving pharmaceutical therapy for AECOPD. The evaluation of patients were depend upon clinical improvements, including reductions in .respiratory .rate and .heart .rate, as well as enhancements in arterial blood gas levels after initiating NIMV.  Results:- The primary outcome assessed was the need for intubation. Among the 100 patients, 88 (88%) showed an improved outcome, including enhancements in pH, PaCO2, respiratory rate, and heart rate after the first and fourth hours of starting NIMV. The study found a statistically significant difference between these values, indicating the efficacy of NIMV in managing acute exacerbations of COPD  Conclusion:- The study concludes that Non-Invasive Mechanical Ventilation (NIMV) shows promise as a treatment approach for managing acute exacerbations of Chronic Obstructive Pulmonary Disease (COPD). Timely implementation of NIMV results in rapid and significant change in arterial blood gas levels, thereby reducing the needed for endo-tracheal intubation in these patients.
Challenges and Consequences of IOL-Implantation in Children with Congenital Cataract before the Age of One Year
Authors: Gani Chowdhury Nasimul , Kumar Biswas Sujit , Khanam Afrina , Akter Chowdhury Farjana
Published: August 2024

Aim To evaluate the intra-operative challenges and post- operative consequences of IOL implantation in children before the age of one year.  Methods 40 eyes of 20 patients with congenital cataract underwent cataract surgeries under general anesthesia were included in this study. Mean age was 9±1 months (7 months to 1 year). All the cases were reviewed at 1 week, 1 month, 3 months and 6 months intervals. The cases completed at least 6 months follow up were included in this study. Intra-operative difficulties, post-operative complications and final visual outcome were recorded.  Results Small eyeball, anterior capsular calcification, thick posterior capsular plaque and pre-existing posterior capsular dehiscence are the major intra-operative challenges. Treatment incompliance, secondary membrane formation, increase intraocular pressure and it’s measurement, changes in refraction and amblyopia are the important concern of IOL implantation in children before the age of one year.  Conclusion Stimulus deprivation amblyopia is the main cause of decreased vision after IOL implantation in children before 1 year of age. Primary IOL implantation after 7 months is safe method to avoid amblyopia and obtain visual rehabilitation in small children.
Assessing Exoplanetary System Architectures with DYNAMITE Including Observational Upper Limits
Authors: Dietrich Jamie
Published: August 2024

The information gathered from observing planetary systems is not limited to the discovery of planets, but also includes the observational upper limits constraining the presence of any additional planets. Incorporating these upper limits into statistical analyses of individual systems can significantly improve our ability to find hidden planets in these systems by narrowing the parameter space in which to search. Here, I include radial velocity (RV), transit, and transit timing variation (TTV) upper limits on additional planets in known multiplanet systems into the Dynamite software package and test their impact on the predicted planets for these systems. The tests are run on systems with previous Dynamite analysis and with updated known planet parameters in the 2–3 yr since the original predictions. I find that the RV limits provide the strongest constraints on additional planets, lowering the likelihood of finding them within orbital periods of ∼10–100 days in the inner planetary systems, as well as truncating the likely planet size (radius and/or mass) distributions toward planets smaller than those currently observed. Transit and TTV limits also provide information on the size and inclination distributions of both the known and predicted planets in the system. Utilizing these limits on a wider range of systems in the near future will help determine which systems might be able to host temperate terrestrial planets and contribute to the search for extraterrestrial biosignatures.
Flux Density Stability and Temporal Changes in the Spectra of Millisecond Pulsars Using the GMRT
Authors: Sharan Rahul , Bhattacharyya Bhaswati , Kumari Sangita , Roy Jayanta , Ghosh Ankita
Published: August 2024

This paper presents an investigation of the spectral properties of 10 millisecond pulsars (MSPs) discovered by the uGMRT, observed from 2017 to 2023 using band 3 (300–500 MHz) and 4 (550–750 MHz) of the uGMRT. For these MSPs, we have reported a range of spectral indices from ∼0 to −4.8, while averaging the full observing band and all the observing epochs. For every MSP, we calculated the mean flux density across 7–8 subbands, each with approximately 25 MHz bandwidth spanning band 3 and band 4. We computed their modulation indices as well as average and maximum-to-median flux density within each subband. Using the temporal variations of the flux density we calculated the refractive scintillation timescales and estimated a structure function with a time lag for eight MSPs in the sample. We note a significant temporal evolution of the in-band spectra, classified into three categories based on the nature of the best-fit power-law spectra, having single positive spectral indices, multiple broken power laws, and single negative spectral indices. Additionally, indications of a low-frequency turnover and temporal variations of the turnover frequency (to the extent that turnover was observed for some of the epochs while not seen for the rest) were noted for all the MSPs. To the best of our knowledge, this is the first systematic investigation probing temporal changes in MSP spectra as well as in the turnover frequency. Future exploration with dense monitoring combined with the modeling of spectra can provide vital insight into the intrinsic emission properties of MSPs and interstellar medium properties.
Bayesian Constraints on the Ring Ellipticity of M87* 2017 Using Themis
Authors: Tiede Paul , Broderick Avery E.
Published: August 2024

Measuring the properties of black hole images has the potential to constrain deviations from general relativity on horizon scales. Of particular interest is the ellipticity of the ring that is sensitive to the underlying spacetime. In 2019, the Event Horizon Telescope (EHT) produced the first-ever image of a black hole on horizon scales. Here, we reanalyze the M87* EHT 2017 data using Bayesian imaging (BI) techniques, constructing a posterior of the ring shape. We find that BI recovers the true on-sky ring shape more reliably than the original imaging methods used in 2019. As a result, we find that M87*'s ring ellipticity is

0.09

−
0.06

+
0.07

and is consistent with the measured ellipticity from general relativistic magnetohydrodynamic simulations.
Stellar Mergers or Truly Young? Intermediate-age Stars on Highly Radial Orbits in the Milky Way’s Stellar Halo
Authors: Horta Danny , Lu Yuxi (Lucy) , Ness Melissa K. , Lisanti Mariangela , Price-Whelan Adrian M.
Published: August 2024

Reconstructing the mass assembly history of the Milky Way relies on obtaining detailed measurements of the properties of many stars in the galaxy, especially in the stellar halo. One of the most constraining quantities is stellar age, as it can shed light on the accretion time and quenching of star formation in merging satellites. However, obtaining reliable age estimates for large samples of halo stars is difficult. We report published ages of 120 subgiant halo stars with highly radial orbits that likely belong to the debris of the Gaia-Enceladus/Sausage (GES) galaxy. The majority of these halo stars are old, with an age distribution characterized by a median of 11.6 Gyr and a 16th (84th) percentile of 10.5 (12.7) Gyr. However, the distribution is skewed, with a tail of younger stars that span ages down to ∼6–9 Gyr. All highly radial halo stars have chemical and kinematic/orbital quantities that associate them with the GES debris. Initial results suggest that these intermediate-age stars are not a product of mass transfer and/or stellar mergers, which can bias their age determination low. If this conclusion is upheld by upcoming spectrophotometric studies, then the presence of these stars will pose an important challenge for constraining the properties of the GES merger and the accretion history of the galaxy.
Experimental Determination of the Unusual CH Stretch Frequency of Protonated Fullerenes
Authors: Finazzi Laura , Esposito Vincent J. , Palotás Julianna , Martens Jonathan , Peeters Els , Cami Jan , Berden Giel , Oomens Jos
Published: August 2024

We report experimental values for the CH stretch frequencies of the protonated fullerenes C60H+ and C70H+. Anharmonic frequency calculations at the B3LYP/6-31G level of theory, which are independent of empirical scaling factors, reproduce the experimental values to within approximately 5 cm−1. Scaling theoretical harmonic frequencies by applying factors derived for polycyclic aromatic hydrocarbons deviate significantly from the experimentally measured frequency. We attribute this deviation to the unusual hydrocarbon structure that affects the degree of anharmonicity of the CH stretch. This result allows us to propose an original, specific scaling factor of 0.9524 to correct harmonic frequencies of CH stretches of protonated fullerenes calculated at the B3LYP/6-311 + G(d,p) level of theory. The special spectral position of the protonated fullerene CH stretch bands makes it a diagnostic marker that may aid in their detection in the interstellar medium.
Updated Kinematics of the Radcliffe Wave: Nonsynchronous, Dipole-like Vertical Oscillations
Authors: Zhu Zhi-Kai , Fang Min , Lu Zu-Jia , Wang Junzhi , Li Guang-Xing , Zhang Shiyu , Pelkonen Veli-Matti , Padoan Paolo , Liang En-Wei
Published: August 2024

The kinematic information of the Radcliffe wave (RW) is essential for determining its existence and gaining insights into its origin and evolution. In this work, we present an accurate measurement of the vertical velocity (V

Z
) of the RW by incorporating the radial velocity (RV) measures through two methods, which is crucial but was neglected previously. First, the velocities are measured toward young stars, using their RV measurements from APOGEE-2 and proper motion measurements from Gaia DR3. Second, we combine RV measurements toward clouds with proper motion measurements of associated young stellar objects to determine the vertical velocities of the clouds. The results reveal that the oscillations in V

Z
are not synchronous with the vertical coordinate Z, which differs from the conclusions of previous studies. Instead, we find a 5 km s−1 kpc−1 gradient in V

Z
along the RW, exhibiting a dipole-like pattern. Consequently, the kinematic arrangement does not show a corresponding coherence with the spatial arrangement, bringing the RW model into question.
Extensive Intrusive Magmatism in the Lunar Farside Apollo and South Pole–Aitken Basins, Chang’e-6 Landing Site
Authors: Qian Yuqi , Head James , Michalski Joseph , Gong Shengxia , Yang Wei , Wang Zilong , Xiao Long , Li Xianhua , Zhao Guochun
Published: August 2024

Lunar igneous activities, including intrusive magmatism and extrusive volcanism, and their products contain significant information about the lunar interior and its thermal state. Their distribution is asymmetrical on the nearside and farside, reflecting the global dichotomy. Samples from the South Pole–Aitken (SPA) basin on the farside hold the key to disclosing the dichotomy conundrum and rebalancing the asymmetrical understandings of the Moon, in addition to previously returned nearside samples (Apollo, Luna, Chang’e-5). For the first time, the Chang’e-6 mission obtained ∼1935.5 g of lunar soils from the farside in the southern Apollo basin, northeast of SPA, opening a window to solve this long-standing question. However, compared with the well-known mare/cryptomare volcanism in SPA, intrusive activity has a much more obscure presence and origin, due to its unclear surface expression, thus impeding the ongoing Chang’e-6 sample analysis, which is therefore emphasized here. We found evidence that intrusive magmatism is extensive across SPA, including Mg-suite intrusions, floor-modified craters, and linear/ring dikes, consistent with its intermediate crustal thickness, where dike intrusion is favored. Intrusive magmatism is abundant in the Apollo basin, where Chang’e-6 landed. Two obscure craters were discovered (Apollo X and Q) with evidence for subsurface intrusions, strongly suggesting the intensive intrusion in the region. Plutonic materials are very likely to be obtained by Chang’e-6, especially the Mg-suite from the western peak ring of the Apollo basin that delivered and mixed in the soils by the Chaffee S crater, whose components might provide critical new insights into their petrogenesis, early lunar evolution, and the origin of dichotomy.
The Coronal Lines of the High-excitation, Fe ii-type Nova V2467 Cygni
Authors: Rudy Richard J. , Russell Ray W. , Sitko Michael L. , Lynch David K. , Woodward Charles E.
Published: August 2024

Optical and infrared spectra are presented for the nova V2467 Cygni from the period of its maximum excitation. The spectra indicate exceptionally high excitation for a Fe ii-type nova, exhibiting [Si x] 1.4305 μm and several emission lines that we associate with C vi. Along with numerous coronal features, V2467 Cygni also displayed low-excitation nebular lines. A CLOUDY analysis indicates a temperature of 5.5 × 105 for its exciting source, a very heterogeneous emission line region, and an ejected mass ≥1.5 × 10−4 L
☉.
Yushania dezhui (Poaceae, Bambusoideae), a new bamboo species from Yunnan, China
Authors: Zhang Yu-Xiao , Zhang Chao , Zhang Ru-Li , Zhao Hu-Gang
Published: August 2024

A new bamboo species, Yushania dezhui, from Kunming, Yunnan, China is described and illustrated in this paper. The new species used to be misidentified as Y. polytricha. Based on careful comparison of morphological features and molecular phylogeny evidence, we confirmed its identity as a new member of the genus Yushania. Yushania dezhui resembles Y. maculata, Y. polytricha and Y. weixiensis in several aspects, such as culm height and branch complement structure. However, the glabrous culm leaf sheaths and internodes, the absence of auricles and oral setae on most foliage leaves, except the one-year-old foliage leaves, the pubescence on the adaxial surface of the one-year-old foliage leaves and its limestone habitat preference can readily distinguish this new species from its related taxa. Moreover, we emphasise that individuals from various populations and molecular markers with different inheritance patterns for phylogeny reconstruction should be included in new species discovery, especially in plant groups with complex evolutionary histories.
Discovery of a new tarantula species from the Madrean Sky Islands and the first documented instance of syntopy between two montane endemics (Araneae, Theraphosidae, Aphonopelma): a case of prior mistaken identity
Authors: Hamilton Chris A. , Hendrixson Brent E. , Silvestre Bringas Karina
Published: August 2024

The Chiricahua Mountains in southeastern Arizona are renowned for their exceptional biodiversity and high levels of endemism. Morphological, genomic, behavioral, and distributional data were used to report the discovery of a remarkable new tarantula species from this range. Aphonopelma jacobiisp. nov. inhabits high-elevation mixed conifer forests in these mountains, but also co-occurs and shares its breeding period with A. chiricahua—a related member of the Marxi species group—in mid-elevation Madrean evergreen oak and pine-oak woodlands. This marks the first documented case of syntopy between two montane endemics in the Madrean Archipelago and adds to our knowledge of this threatened region’s unmatched tarantula diversity in the United States. An emended diagnosis and redescription for A. chiricahua are also provided based on several newly acquired and accurately identified specimens. Phylogenetic analyses of mitochondrial and genomic-scale data reveal that A. jacobiisp. nov. is more closely related to A. marxi, a species primarily distributed on the Colorado Plateau, than to A. chiricahua or the other Madrean Sky Island taxa. These data provide the evolutionary framework for better understanding the region’s complex biogeographic history (e.g., biotic assembly of the Chiricahua Mountains) and conservation of these spiders.
GastroFuse-Net: an ensemble deep learning framework designed for gastrointestinal abnormality detection in endoscopic images
Authors: Aggarwal Sonam , Gupta Isha , Kumar Ashok , Kautish Sandeep , Almazyad Abdulaziz S. , Wagdy Mohamed Ali , Werner Frank , Shokouhifar Mohammad
Published: August 2024

Convolutional Neural Networks (CNNs) have received substantial attention as a highly effective tool for analyzing medical images, notably in interpreting endoscopic images, due to their capacity to provide results equivalent to or exceeding those of medical specialists. This capability is particularly crucial in the realm of gastrointestinal disorders, where even experienced gastroenterologists find the automatic diagnosis of such conditions using endoscopic pictures to be a challenging endeavor. Currently, gastrointestinal findings in medical diagnosis are primarily determined by manual inspection by competent gastrointestinal endoscopists. This evaluation procedure is labor-intensive, time-consuming, and frequently results in high variability between laboratories. To address these challenges, we introduced a specialized CNN-based architecture called GastroFuse-Net, designed to recognize human gastrointestinal diseases from endoscopic images. GastroFuse-Net was developed by combining features extracted from two different CNN models with different numbers of layers, integrating shallow and deep representations to capture diverse aspects of the abnormalities. The Kvasir dataset was used to thoroughly test the proposed deep learning model. This dataset contained images that were classified according to structures (cecum, z-line, pylorus), diseases (ulcerative colitis, esophagitis, polyps), or surgical operations (dyed resection margins, dyed lifted polyps). The proposed model was evaluated using various measures, including specificity, recall, precision, F1-score, Mathew's Correlation Coefficient (MCC), and accuracy. The proposed model GastroFuse-Net exhibited exceptional performance, achieving a precision of 0.985, recall of 0.985, specificity of 0.984, F1-score of 0.997, MCC of 0.982, and an accuracy of 98.5%.
Spectral distribution and semigroup properties of a queueing model with exceptional service time
Authors: Yiming Nurehemaiti
Published: August 2024

In this paper, we studied the spectrum and semigroup properties of the M/G/1 queueing model with exceptional service time for the first customer in each busy period. First, we described the point spectrum of the system operator that corresponds to the model, and we prove that the system operator has an uncountable infinite number of eigenvalues on the left-half complex plane. Second, by using the spectrum analysis and semigroup theory, we obtained that the spectrum-determined growth (SDG) condition holds and the semigroup is not asymptotically stable, compact, eventually compact, or even quasi-compact. Finally, in order to clarify the results of spectral distribution, some numerical analysis were conducted.
An Exclusive Survey on Metamaterial-Based Fractal Antennas for Wireless Applications
Authors: Kalaiyarasan R. , Bibi Rasheeda , Nagarajan G.
Published: August 2024

Fractal geometry has emerged as a promising technique for optimizing microstrip patch antennas, meeting the increasing demand for compactness and efficiency in wireless communication systems. This involves incorporating fractal elements into conventional microstrip patch antenna designs, highlighting methods for achieving compact, multiband operation. When combined with fractal antennas, metamaterials enable unprecedented control over electromagnetic wave manipulation, improving control over the antenna's radiation pattern, polarization, and frequency response. The combination of fractal antennas and metamaterials presents an intriguing opportunity for advancing antenna design with the potential for enhanced performance, reduced size, and increased effectiveness. Metamaterials are artificially created materials that possess unique features that are not present in materials that occur naturally. These devices can be engineered to control electromagnetic waves in non-traditional manners resulting in a wide range of uses in antennas and other areas.
An Overview of Applications of Machine Learning Techniques in Antenna Design and Optimization
Authors: Palaniappan Rajkumar , Vijean Vikneswaran , Nabi Fizza Ghulam , Rushambwa Munyaradzi Charles
Published: August 2024

This chapter gives an overview of how machine learning algorithms can be employed in designing and optimizing antennas. Antenna design and optimization is a major factor that enhances the performance of any communication system, making it an important part of wireless systems. The traditional antenna design is mainly based on a trial-and-error approach, which is time consuming and has many challenges while designing and optimizing. The recent development in artificial intelligence has been instrumental in efficient antenna design and optimization. Machine learning techniques have emerged as a practical solution to these limitations and challenges by providing effective and automated antenna design and optimization. This chapter discusses several machine learning techniques used in antenna design, their advantages, disadvantages, and future possibilities for further work on antennas design.
Improving Power Distribution in Wearable Technology on Simultaneous Bidirectional Converter
Authors: Mohammed Ali H. , Kamal M. D. Raj , Paranthaman V. , Maranan Ramya
Published: August 2024

This research addresses the critical challenge of improving power distribution in wearable technology by introducing a novel simultaneous bidirectional converter designed for enhanced efficiency and better energy factors. The proposed converter architecture significantly reduces ac/dc power source wastage, commonly associated with harmonic difficulties and voltage level drops in wearable devices. The design features two key components: the first transformer operates as a dc/dc phase, adjusting the switching frequency to control the reference voltage, while the second serves as an ac/dc converter, focusing on transformer efficiency and distortion reduction. A key innovation in this architecture is the bidirectional inverting amplifier, which synchronizes voltage output with any output waveform by adjusting the multimeter settings and altering the interval, while keeping the switching on-time constant. This approach notably enhances frequency deviation, reducing output current drop by nearly 70%, and simultaneously lowers overall harmonic distortion, leading to cost savings.
Analyzing Renewable Power Integration in Edible Devices on Variable Rate Pumped Storage
Authors: Seeniappan Kaliappan , Krishnakumari A. , Shanmugapriya M. , Muthukannan M.
Published: August 2024

This study embarks on a novel exploration of integrating renewable power sources, particularly wind and solar energy, into edible devices, focusing on the Indian power grid's context. As the prevalence of renewable energy sources grows, the dynamics of power systems are rapidly evolving, presenting unique challenges such as network stability and fluctuating energy outputs. This research specifically addresses the variability inherent in renewable energy sources and investigates the potential of minimum variable rate pumped storage systems to provide fundamental consistency in power grids. Key issues such as network inertia minimization and the challenges posed by nano-grids are examined, with an emphasis on their impact on edible devices. The study also explores the use of rapid dispatchable generation (DG) units, like the Kenneth and configurable speed hydel charger, as viable solutions to the energy fluctuation issues typical in renewable-rich power systems.
Advancing to Sustainable Development
Authors: Shah Mushtaq Ahmad , Kumar Sanjeev , Talukder Mohammad Badruddoza
Published: August 2024

Sustainable economic growth necessitates efficient management of the growing environmental degradation and climate change problems. To address the climate catastrophe, more investments, research and development activities, and public education about the benefits of renewable energy sources are required. This comprehensive bibliometric study explores the complex relationships between green energy, green investment, and climate change research, with the purpose of giving an in-depth examination of the changing dynamics in these essential areas. Scopus, a comprehensive scientific database, serves as the primary source for this analysis. The timeframe under investigation spans from 2003 to 2023, encompassing a period of significant global focus on climate change and its economic consequences. Using quantitative approaches and visualization tools such as VOSviewer version 16.2 software, this study sheds light on the growing global interest in sustainable practices and renewable energy solutions. The study reveals a rising amount of literature focused on addressing environmental issues, lowering carbon emissions, and encouraging environmentally beneficial initiatives. It emphasizes the need of matching policies with green ideals in order to promote long-term environmental sustainability and economic stability. This study adds to the ongoing discussion by assessing significant trends, identifying central scientific clusters, and defining future research pathways, emphasizing the need of continuous innovation and cooperation in advancing sustainable development goals.
Towards Sustainable Cities
Authors: Singh Manvendra , Arora Vaishali , Kulshreshta Kushagra
Published: August 2024

Urban sustainability stands at the forefront of contemporary discourse, propelled by the urgent need to address the multifaceted challenges spurred by rapid urbanization, climate change, increasing population, resource depletion, and social inequality. To respond to these emerging issues, this research abstract delves into the foundational principles and strategic approaches of urban sustainability. It aims to furnish a comprehensive elucidation tailored for policymakers, urban planners, and stakeholders alike, recognizing the pivotal role they play in shaping the cities of tomorrow. At its heart, urban sustainability strives to strike a harmony between economic vibrancy, social inclusivity, and environmental stewardship. The United Nations has predicted that by 2050, the urban population will rise to nearly 70% all over the world. Urban sustainability emerges as a beacon of hope, offering a roadmap towards more inclusive, resilient, and environmentally conscious cities. It calls for a departure from conventional urban development paradigms towards holistic, long-term solutions that keep the well-being of both people and the planet on priority.
Unveiling the Critical Role of Artificial Intelligence in Energy Management
Authors: Manoharan Geetha , Ashtikar Sunitha Purushottam , Nivedha M.
Published: August 2024

Recently, the incorporation of artificial intelligence into energy management has emerged as a transformative approach to optimize energy consumption, enhance efficiency, and extenuate environmental impacts. The chapter indulges in understanding the applications, potential advantages, mitigating challenges, and innovative collaboration of artificial intelligence in energy management. Energy management and artificial intelligence can potentially address numerous business problems and lead to revolutionary new developments. The chapter explores how AI-driven approaches facilitate demand forecasting, load balancing, grid optimization, predictive maintenance, and renewable energy integration within diversified energy systems. Additionally, the significance of AI-enabled smart grids and energy-efficient buildings is that they are built with optimized energy usage and a reduced carbon footprint. AI could improve energy operations, efficiency, and renewable energy use, which are needed to build a resilient, sustainable, and collaborative energy environment that stimulates innovation.
Melding Artificial Intelligence and Remote Sensing Data for Real-Time Monitoring of Marine Biodiversity
Authors: Lal Sahil , Arora Manmeet Kaur , Riswandi Budi Agus , Singh Nishtha , Singh Bhupinder
Published: August 2024

The biodiversity of the oceans provides us with key ecosystem services, however marine life is facing a multitude of threats like pollution, climate change and over-exploitation. Action: Monitoring and conservation strategies need to be put in place to save these fragile ecosystems. The focus of this chapter is on marine biodiversity monitoring in real-time using remote sensing and artificial intelligence (AI). Advanced monitoring systems (such as the TOPAZ system) use an ensemble Kalman filter to assimilate satellite-measured sea-surface temperatures, sea-surface heights, and in-situ measurements from Argo profiling floats and XBTs. These systems render a three-dimensional (3D) comprehensive state picture of the ocean, which comprises temperature fields and current structures rather than just climate projections. This chapter focuses on melding artificial intelligence and remote sensing data for real-time monitoring marine biodiversity.
Through an Energy Lens
Authors: Arora Manmeet Kaur , Lal Sahil , Singh Bhupinder , Olyaee Mahsa
Published: August 2024

Energy must be at the core of impact if we are to address the 17 SDGs. The policy brief seeks to provide insights and suggest recommendations on some of the key levers that governments can use to align energy policies with SDG objectives, including recent cross-sectoral efforts, in order accelerate sustainable development across all three dimensions at higher pace towards 2030. The careful account of recent UN policy briefs and academic literature suggests several vital levers for shaping energy action as a driver for the SDGs. Unlocking this potential demands political will, multi-stakeholder partnerships, and a systems perspective to policy-making. The 2030 Agenda presents an unprecedented chance to integrate the cross-cutting nature of energy with mainstream sustainable development objectives.
The Role of Logistics in SDG 7 “Affordable and Clean Energy”
Authors: Tercan Irem , Özdemir Deniz Irem
Published: August 2024

In today's world, access to renewable energy is crucial for global sustainable development. This chapter highlights the vital role of logistics in achieving Sustainable Development Goal 7 (SDG 7), which aims for affordable and sustainable energy. It explores how logistics impacts economic development, job creation, green energy applications, and clean energy transportation, including the use of wind turbines and large-scale hydrogen batteries. The logistics sector offers opportunities to meet the growing demand for clean energy by developing infrastructure, distributing products, and managing transportation efficiently. This chapter emphasizes the potential for job creation and environmental benefits, transforming logistics into a driver of economic growth and sustainability. It also examines sustainable port development and the integration of renewable energy in logistics operations, showcasing how logistics can advance global efforts toward a sustainable future.
The Role of Logistics in Industry, Innovation, and Infrastructure
Authors: Terzi Altuğ , Kula Bora Berke
Published: August 2024

This chapter examines Sustainable Development Goal 9: Industry, Innovation, and Infrastructure with a focus on the essential functions of inclusive and sustainable industrialization, infrastructure development, and universal access to information and communications technology in promoting sustainable development. The examination commences by focusing on Industry 5.0, emphasizing its capacity to facilitate all-encompassing and eco-friendly industrial progress, in conjunction with sustainable manufacturing and efficient resource utilization. Subsequently, it analyzes the improvement of transportation infrastructure and the progress of logistics as pivotal factors in facilitating commerce and market accessibility. Moreover, the significance of resilient telecommunications infrastructure and fair access to information is highlighted. It also explores the transformative effects of ICT on enhancing sustainability and efficiency in logistics. It facilitates innovation, stimulates economic development, and advocates for environmental sustainability by Including these components.
The Role of Logistics in Sustainable Cities and Communities
Authors: Uzun Fevzi , Ergül Mustafa Yiğit
Published: August 2024

This chapter explores the critical role of logistics in achieving Sustainable Development Goal (SDG) 11, which focuses on making cities and communities inclusive, safe, resilient, and sustainable. By emphasizing green logistics, the chapter addresses the integration of environmentally friendly practices across supply chain operations. With the rapid growth of e-commerce and the increasing importance of express delivery sectors, particularly in China, the need for sustainable logistics solutions has become paramount. The chapter delves into the challenges and opportunities associated with implementing green supply chain management (GSCM), highlighting the importance of overcoming technological and informational barriers to achieve low-carbon and efficient logistics networks. By examining the evolution of green logistics, the chapter underscores the significance of sustainable production practices and the role of government policies and business strategies in promoting environmentally conscious logistics.
Sustainable Development Goals
Authors: Bursalı Caner , Ercis Yakup
Published: August 2024

This chapter investigates the pivotal role of logistics within the context of Sustainable Development Goal (SDG) 16, focusing on “Peace, Justice, and Strong Institutions.” SDG 16 serves as a cornerstone in the global pursuit of sustainable development, emphasizing the critical importance of governance, access to justice, and institutional integrity in fostering stable and inclusive societies. Despite the significant attention given to policy frameworks and institutional reforms within discussions surrounding SDG 16, the role of logistics, particularly in transportation and supply chain management, remains understudied. This chapter elucidates the intricate intersections between logistics and the overarching goals of SDG 16 through a multidisciplinary inquiry. Drawing upon theoretical frameworks from transportation studies, supply chain management, and international development, the chapter explores how logistical operations contribute to advancing peace, justice, and institutional resilience.
A Two-Stage Multi-Modal Multi-Label Emotion Recognition Decision System Based on GCN
Authors: Wu Weiwei , Chen Daomin , Li Qingping
Published: August 2024

Compared with single-modal methods, emotion recognition research is increasingly focusing on the use of multi-modal methods to improve accuracy. Despite the advantages of multimodality, challenges such as feature fusion and redundancy remain. In this study, we propose a multi-modal multi-label emotion recognition decision system based on graph convolution. Our approach utilizes text, speech, and video data for feature extraction, while combining tag attention to capture fine-grained modal dependencies. The two-stage feature reconstruction module facilitates complementary feature fusion while preserving mode-specific information. Emotional decisions are made using a fully connected layer to optimize performance without adding complexity to the model. Experimental results on IEMOCAP, CMU-MOSEI and MELD datasets show that our algorithm has higher accuracy than existing models, highlighting the effectiveness and innovation of our proposed algorithm.
A Review on Enabling Technologies of Industrial Virtual Training Systems
Authors: Singhaphandu Raveekiat , Pannakkong Warut
Published: August 2024

Industrial training increasingly uses computer technologies to boost efficiency, effectiveness, and safety. Virtual reality (VR), augmented reality (AR), and e-learning platforms have transformed traditional training methods. This review examines these technologies and highlights their applications in various sectors. The review addresses adoption challenges, including high costs, technical complexity, user acceptance, learning curves, simulation realism, and health concerns. It proposes strategies to mitigate these issues, such as cost-effective solutions, improved usability, enhanced realism, and robust assessment mechanisms. By analyzing multiple studies, the paper provides insights into the current state and future directions of technology-enabled industrial training, emphasizing ongoing innovation and adaptation to maximize these advanced tools' potential.
Elections Administration and Bimodal Voter Accreditation System (BVAS) Technology
Authors: Akah Augustine Ugar , Edino Ojonimi Ferdinand , Agbor Uno Ijim , Nwagboso Chris Iwejuo , Musa Andrawus , Adams John Anyabe , Ebegbulem Joseph , Eja Terrence Richard , Bassey Ugo Samuel , Ogar Joy Iyeumbe , Nwagboso Salome Nnenna , Ekpo Stella Odey
Published: August 2024

To mitigate electoral challenges in Nigeria, the Independent National Electoral Commission (INEC) deploys Smart Card Readers (SRC) to conduct the 2015, 2019 elections. However, the SCR had challenges, such as the inability to authenticate voter cards and verify biometric data. Hence, INEC introduced Bimodal Voter Accreditation System (BVAS) in 2023. Relying on data generated using the macro qualitative and eclectic approach (Technological Acceptance Model and Innovation Diffusion Theory), the paper assesses the acceptance, challenges of BVAS and the relative advantage, compatibility, complexity, trial-ability and the observability of BVAS during the 2023 presidential elections. The findings reveal that INEC's failure to upload the election results on the Result Viewing (IREV) portal in real-time was a significant setback, leading to doubt about the credibility of the elections. This failure was not only a breach of the 2022 Electoral Act but also of INEC's guidelines. Therefore, the paper recommends an effective way of administering elections in Nigeria using technology-based devices
Group Consensus-Driven Energy Consumption Assessment Using Social Network Analysis and Fuzzy Information Fusion
Authors: Wang Bingjie , Zhang Chao , Sangaiah Arun Kumar , Alenazi Mohammed J. F. , AlQahtani Salman A. , K. S. Sendhil Kumar
Published: August 2024

With industrial development deepening, the share of industrial energy in overall consumption has notably risen. To assess industrial energy consumption accurately, this paper proposes a method employing interval type-2 fuzzy sets (IT2FSs) to represent assessment information effectively. Additionally, it analyzes decision-makers (DMs) as a social network to alleviate individual biases. IT2FSs are chosen to handle uncertainties in assessing industrial energy consumption. Addressing biases in DMs' opinions, a group consensus model aids the consensus reaching process (CRP). Industrial energy consumption is assessed using the MULTIMOORA method, yielding three results. These are fused via D-S evidence theory (DSET) to obtain the final assessment. Finally, the model's effectiveness is verified with a case study on energy consumption in the steel industry. In conclusion, this paper not only deepens the understanding of uncertainties in the energy consumption assessment process, but also provides a robust tool for various industries to optimize energy use and economic outcomes.
“Under Pressure!”
Authors: Klumpp Matthias , Ruiner Caroline , Hagemann Vera , Meinecke Jonathan , Debbing Christina Elisabeth , Hesenius Marc
Published: August 2024

The use of digital technologies or applications can have positive and negative effects on workers: Digital technologies might support workers' decision-making by providing necessary information, but digital technologies might also lead to time pressure and mental strain. In this paper, the authors specifically analyze the characteristics of digital work and the link to mental strain to estimate the effects on work performance in industry. They report survey data from four German companies in the manufacturing, service, and logistics sector with N=279 participants. Results indicate that technology-based organizational and personal resources mitigate, while technology-based demands enhance mental stress and strain. Time pressure is the most important individual factor increasing mental stress and strain. Mental strain, in turn, negatively influences work performance. Considering such connections is crucial for human resource management in digital work contexts and specifically workers' use of and interaction with technologies beyond the analyzed specific manufacturing, service, and logistics industries.
Rapid screening for physical activities of daily living (pADL) in older adults in resource limited clinical settings
Authors: Lekamwasam Sarath , Rathnayake Nirmala , De Zoysa Warsha , Palangasinghe Dhammika , Abeygunasekara Thilina , Dias Harshani
Published: August 2024

We evaluated the validity of 3-item shorter versions of Barthel index (BI) in older adults. Sinhala versions of 10 item-BI (BI) and 6-item Katz index (KI) were administered among older adults (≥65 years and n=200). The per-formance of three shorter versions of BI (SV1, SV2 and SV3) was examined considering the 10-item BI and 6-item KI, which are widely used tools to assess the physical activities of daily living (pADL), as the reference standards. These, when compared with the 10-item BI, the sensitivity and specificity of SV1 were 0.28 and 0.87. The corresponding values of SV2 and SV3 were 0.72, 0.66 and 1.0, 0.58. Compared to KI, the sensitivity and specificity of SV1 were 0.21 and 0.80. The corresponding values of SV2 and SV3 were 0.73, 0.84 and 0.87, 0.61. SV2 and SV3, but not SV1, showed satisfactory psychometric properties that make them suitable tools to screen for pADL in older adults. bi fruits are useful in the evaluation of kidney injury.
Impact of Multiple Intelligences on Architectural Ability and Success: A Case Study of Pritzker Price Laureates (1979-2022)
Authors: Gayantha D.W.K.
Published: August 2024

The concept of Multiple Intelligences (MI) has been a popular area within the field of psychology and education since its introduction in 1983. MI is comprised of 09 autonomous intelligence types. As suggested by MI concepts, the making of an Architect involves a great deal of Visual-spatial Intelligence (VSI) out of the aforesaid ensemble.
This research seeks to identify the impact of other intelligences types apart from VSI – also referred to as Non Visual-spatial Intelligence (NVSI) – associated with the aforesaid phenomenon. The study adopts a qualitative research method and relies on multiple case studies as the strategy, using compiled data extant in literature. The biographies of the entire population of prestigious Pritzker Prize Laureate Architects (PPLAs) up to year 2022 is considered from the award’s inception in 1979, to study their subject abilities other than Architectural; marked by Extra Architectural Abilities (EAA). Further, an additional literature survey facilitates the mapping of EAA data, in order to assess NVSI traits possessed by each of the architects under review. The compiled data is analyzed (using tables initially, and subsequently MS Excel after being turned into numerical values) to test the hypothesis that a significant level of EAA backed by NVSI is possessed by high standard architectural practitioners. Therefore, this research opens up new trails for further studies to seek the relationship between MI and architectural abilities/success, which could be beneficial to the sphere of architectural education as well as the profession as a whole.
Translanguaging as a strategy for navigating multilingualism in peri-urban preschool classrooms
Authors: Mahan Sibongile J. , Phatudi Nkidi C. , Modise Matshediso R.
Published: August 2024

Background: Language discussions have historically focused on the power dynamics between dominant and indigenous languages. This has generated discontent and contention on which language should rule the educational sector. The national language policy of South Africa mandates the use of all languages in the educational system. Even though there are 12 recognised languages, English is preferred in education circles. This ignores the research that demonstrates the advantages of speaking one’s native language, especially in the early years of schooling.Aim: This study was conducted to determine how preschool practitioners assist the language development of learners in multilingual classrooms.Setting: Six early childhood education (ECE) practitioners from three preschools in Mamelodi township, South Africa were selected, based on choosing English as the language of communication, in multilingual classrooms in peri-urban areas.Methods: A qualitative approach and a case study research design were employed. It focused on purposive sampling of practitioners from three preschools in Mamelodi where the medium of communication was English. Interviews, observations, casual conversations and document and visual data analysis were data collection tools. A questionnaire was used to gather the geographical information of the participants. A fusion of the Bakhtinian philosophy of dialogism and social justice theory underpinned the study.Results: The results showed that despite English in their schools as a medium of instruction, practitioners used predominating home languages to assure understanding. This translanguaging approach was commonly used in every school. Learning in a single language was challenging because of diverse languages, hence the use of English First Additional Language.Conclusion: To promote language acquisition in multilingual preschools, translanguaging ought to be promoted.Contribution: This study proposes that early childhood teacher preparation programs ought to promote multilingualism by employing translanguaging strategies as a study unit.