Rapid Growth Research Articles

Attention is All They Need: Exploring the Media Archaeology of the Computer Vision Research Paper

Research papers, in addition to textual documents, are a designed interface through which researchers communicate. Recently, rapid growth has transformed that interface in many fields of computing. In this work, we examine the effects of this growth from a media archaeology perspective, through the changes to figures and tables in research papers. Specifically, we study these changes in computer vision over the past decade, as the deep learning revolution has driven unprecedented growth in the discipline. We ground our investigation through interviews with veteran researchers spanning computer vision, graphics, and visualization. Our analysis focuses on the research attention economy: how research paper elements contribute towards advertising, measuring, and disseminating an increasingly commodified "contribution." Through this work, we seek to motivate future discussion surrounding the design of both the research paper itself as well as the larger sociotechnical research publishing system, including tools for finding, reading, and writing research papers.

Sunwoda's Financial Analysis Based on The Harvard Analytical Framework

In order to comply with the strategy of sustainable development, China hopes to further accelerate the rapid development of the new energy vehicle industry and supporting industries. Power battery is the core component of new energy vehicles, and the selection of sunwoda in the battery industry for financial analysis can provide a useful reference for the same type of enterprises.This paper selects sunwoda as an analysis case, applies the Harvard analytical framework to sunwoda's financial analysis, and conducts in-depth discussion and analysis of sunwoda's financial status and existing problems. The analysis found that sunwoda is currently in the growth period,adopting a growth-oriented development strategy to gradually expand the scale of the enterprise, with many projects underconstruction and rapid growth in scale. However, behind the seemingly perfect financial data, there are problems such as low profitability, intensified market competition,and insufficient future development capabilities.In view of these problems,corresponding improvement suggestions are put forward,hoping to help the development of sunwoda.

Functionalization Strategies of Iron Sulfides for High-Performance Supercapacitors

AbstractSupercapacitors have emerged as a promising class of energy storage technologies, renowned for their impressive specific capacities and reliable cycling performance. These attributes are increasingly significant amid the growing environmental challenges stemming from rapid global economic growth and increased fossil fuel consumption. The electrochemical performance of supercapacitors largely depends on the properties of the electrode materials used. Among these, iron-based sulfide (IBS) materials have attracted significant attention for use as anode materials owing to their high specific capacity, eco-friendliness, and cost-effectiveness. Despite these advantages, IBS electrode materials often face challenges such as poor electrical conductivity, compromised chemical stability, and large volume changes during charge–discharge cycles. This review article comprehensively examines recent research efforts aiming at improving the performance of IBS materials, focusing on three main approaches: nanostructure design (including 0D nanoparticles, 1D nanowires, 2D nanosheets, and 3D structures), composite development (including carbonaceous materials, metal compounds, and polymers), and material defect engineering (through doping and vacancy introduction). The article sheds light on novel concepts and methodologies designed to address the inherent limitations of IBS electrode materials in supercapacitors. These conceptual frameworks and strategic interventions are expected to be applied to other nanomaterials, driving advancements in electrochemical energy conversion.

Technical Analysis of the Indonesian Stock Market with Gated Recurrent Unit and Temporal Convolutional Network

Big data is essential in the age of 4.0 industry as it becomes the basis of decision making. Deep learning research in the last few years has been proven effective in understanding complex big data patterns, especially in the finance sector. The rapid growth of the Indonesian stock market in the last 20 years, which was driven by globalization, prompted fluctuation in the Bursa Efek Jakarta (JKSE) which was influenced by stock prices, commodity prices, and exchange rate. This study identifies the main indicators of Indonesian stock market crisis, applies and compares deep learning models, particularly Gated Recurrent Unit (GRU) and Temporal Convolutional Network (TCN), in predicting stock prices. This study identified 20 JKSE crisis points between the 2002-2023 period with average return value at around -6%. All variables correlated positively with JKSE, with SET.BK as the highest correlated variable in lag 0. The American and European stock market, commodity price, and exchange rate tend to show a pattern opposite to the JKSE crisis. Predictor variables such as STI, HIS, KLSE, KS11, SET.BK, PSEI.PS, RUT, and USDIDR are chosen based on significant cross correlation and average return plot. Hyperparameter tuning and cross validation within a 3 years window concluded that the GRU model is accurate and efficient, with RMSE value at 43.35568 and MAE value at 33.66909 in the validation data.

Making sense of generative AI for assessments: Contrasting student claims and assessor evaluations

The rapid growth of generative AI usage in higher education has left educators looking urgently for insights into student usage and guidance on good practice. This case study examines an experiential exercise involving 118 postgraduate management students at a UK business school, where students were asked to write a 500-word reflection on their use of AI for a 2500-word essay-style assessment. Using sensemaking as a theoretical lens, we compare students' claims with assessors' evaluations of students' AI usage. Our findings indicate that students predominantly use generative AI for writing, paraphrasing, and rephrasing, rather than for fostering critical thinking or engaging in the more advanced stages of sensemaking, a level achieved by only one-tenth of the cohort. The consistency between this study's findings and pre-generative AI research suggests that higher education has yet to adapt adequately in ways to integrate AI to mitigate, rather than exacerbate, current sector deficiencies. We call on university leaders to develop institutional strategies that allow for effective and responsible integration of generative AI, and on educators to develop students' critical evaluation and academic writing skills that build on generative AI's affordances, with several specific recommendations made in this article.

Enhancement of the quality of mc-Si ingot grown by vacuum directional solidification furnace with growth rate increase reducing the cost of the wafer for PV application: Carbon and oxygen analysis

In this paper, we propose a numerical model to investigate the dissolution of oxygen atoms from the porous silica crucible, SiO gas formation, back diffusion of CO gas and segregation of carbon and oxygen during the growth of multi-crystalline silicon (mc-Si) by vacuum directional solidification (VDS) at different growth rates (3, 6 and 9 mm/h) by silt valve opening rate. The dissolution of oxygen decreases during the rapid growth of ingot because the reaction between the molten silicon and the porous silica crucible is constrained. This limitation on oxygen dissolution from the porous silica crucible further diminishes chemical reaction inside the VDS furnace. Consequently, the segregation pattern of the carbon and oxygen is affected at higher growth rate. During the VDS mc-Si growth, a growth rate of 9mm/h yields better quality of the VDS grown mc-Si ingots compared to other growth rates, this rate reduces SiC precipitation and SiO2 cluster formation due to lower concentration of carbon and oxygen. The obtained carbon concentration minimizes the wire saw defects. Based on these numerical results (9 mm/h), we have implemented experimental work. Prepared samples are analyzed using FTIR spectra and minority carrier lifetime measurements. The effect of oxygen concentration in the samples is analyzed in the minority carrier lifetime measurements. The oxygen and carbon concentrations are calculated by FTIR spectra and their results are compared with the numerical simulation.

The development of supplemental multimedia learning modules and their impact on student learning in food biotechnology courses.

The rapid growth of online education has created opportunities to integrate multimedia learning tools into complex scientific disciplines like food biotechnology. This study aimed to develop and evaluate supplementary online course modules on gene expression analysis, protein engineering tools, and fermentation genomics for undergraduate food biotechnology education. Based on cognitive load theory and multimedia learning principles, the modules incorporated focused visual media and interactive knowledge checks. The study involved 85 students in an introductory food microbiology course and 25 students in an upper-level food biochemistry elective at a large public university. Module implementation included tracking student usage through learning management system analytics, collecting qualitative feedback, and assessing learning outcomes via exam performance. Results showed that 73%-76% of students voluntarily accessed the modules, with average engagement times of 5-8 min per module. Student feedback highlighted the modules' effectiveness in clarifying textbook content through replayable examples and real-world scenarios. Comparison of exam scores revealed a 6%-10% improvement in performance on module-related items compared to overall exam averages. Qualitative feedback indicated that students found the visual representations and interactive elements helpful for clarifying complex concepts. This study demonstrates the potential of well-designed multimedia modules to support student learning in food biotechnology education, providing a model for expanding such resources in food science curricula.

Chromosome-level genome assembly of the ivory shell Babylonia areolata

The ivory shell Babylonia areolata is an economically important marine benthic gastropod known for its rapid growth and high nutritional value. B. areolata is distributed in Southeast Asia and the southeast coastal areas of China. In this study, we constructed a high-quality genome for B. areolata using PacBio, Illumina, and Hi-C sequencing technologies. The genome assembly comprised 35 chromosomal sequences with a total length of 1.65 Gb. The scaffold and contig N50 lengths were 53.17 Mb and 2.64 Mb, respectively, with repeat sequences constituting 64.46% of the genome. Furthermore, 26,130 protein-coding genes and 96.75% of the genome’s BUSCOs were identified. This inaugural report of a B. areolata genome provides crucial foundational information for further investigations into the biology, genomics, and genetic improvement of economic traits of this species.

Pegaruh Kepercayaan Konsumen Terhadap Keputusan Pembelian di Tokopedia Melalui Electronic Word of Mouth Sebagai Variabel Intervening

With rapid growth, researchers are intrigued to investigate the factors influencing consumer purchasing decisions on this platform. Through data collection and analysis, this research aims to provide deeper insights into how electronic word of mouth (e-WOM) influences purchasing decisions on Tokopedia. As a popular e-commerce platform, further understanding of these factors is expected to contribute to the development of marketing strategies and enhancement of consumer experiences on Tokopedia. This study utilizes purposive sampling and non-probability sampling techniques, involving 200 respondents from the community of Tangerang City who use Tokopedia for daily shopping. Data collection is carried out through G-form tools and manual methods with a questionnaire of statements using a 5-point Likert scale. The research employs Partial Least Squares Structural Equation Modeling (PLS-SEM) techniques for hypothesis testing and data validity. From the discussion of each hypothesis, some hypotheses are rejected as they surpass the theoretical significance value. The variable rejected is the consumer trust variable in purchasing decisions. This rejection aligns with prior research on Scarlett products, finding that consumer trust has a positive and significant impact on purchasing decisions, while brand image and brand ambassadors do not significantly influence purchasing decisions (Putri & Harti, 2022). The results of this study indicate that the role of electronic word of mouth (e-WOM) mediates the influence of consumer trust on purchasing decisions among Tokopedia users in Tangerang City.

Pengaruh Faktor-Faktor Perilaku Konsumen terhadap Keputusan Pembelian Produk Frozen Food di Adam Frozen Food Kabupaten Bekasi

Bekasi Regency is one of the metropolitan areas in Indonesia with rapid population and urban growth. The majority of Bekasi Regency residents have a busy lifestyle with a busy work routine. This time limitation makes Bekasi Regency residents need practical food products such as frozen food. Frozen food products are the right choice because they are easy to store, durable, and quick to serve. One of the frozen food stores in Bekasi Regency is Adam Frozen Food, which sells frozen food products as a solution to meet food needs without spending excessive time and energy. Competition in the frozen food industry is getting tighter with many offering similar products with competitive quality and prices. With this condition, research is needed to understand the factors of consumer behavior in purchasing frozen food products at Adam Frozen Food, Bekasi Regency. The purpose of this research is to analyze the influence of cultural factors, social factors, personal factors and psychological factors on purchasing decisions for frozen food products at Adam Frozen Food. The sampling method used the Lemeshow formula with 100 respondents. The data analysis used is multiple linear regression. The results showed that cultural factors, social factors, personal factors and psychological factors simultaneously influenced the variable purchasing decisions for frozen food products at Adam Frozen Food. Social factors, personal factors and psychological factors partially influence the decision to purchase frozen food products at Adam Frozen Food. Meanwhile, cultural factors partially have no effect on purchasing decisions for frozen food products at Adam Frozen Food.

Analysis of Building Distribution and Accessibility of Kanigoro Urban Roads

The Kanigoro Settlement Area's land is mostly utilized for residential and agricultural purposes. Modifications to the city's construction and development are necessary to turn Kanigoro into a sustainable urban region, particularly in the field of urban morphological pattern development. City or area morphology may be analyzed using three primary components: building density, land use patterns, and road network patterns. This research aims to investigate the urban morphology pattern in Kanigoro Urban Area, focusing on road accessibility and building dispersion. In order to accomplish this goal, land use and building distribution were identified using satellite image data from 2011, 2015, 2019 and 2023, along with questionnaire data on residential location selection. The findings demonstrate that elongated patterns dominate settlement patterns in Kanigoro, with group patterns and the main road network following closely behind. Kinship and historical factors also play a role in this pattern. During the study, there was a notable increase in settlement growth, particularly on main transportation routes. The population density analysis shows that there is a concentration of population in the city center and some rapidly developing residential areas as a result of this rapid settlement growth. According to the road accessibility analysis, most areas are served by arterial roads, but there are still some areas with limited accessibility, especially with regard to collector roads. Based on the research results, there is a need for sustainable integrated spatial planning, adequate infrastructure, improving the quality of the collector road network and developing integrated public transportation.

Sustainable Biopolymers in Eco-Friendly Triboelectric Energy Harvesting.

Biopolymer-based triboelectric nanogenerators (B-TENGs) represent an innovative fusion of eco-friendly, sustainable energy-harvesting technology with renewable and environmentally benign biopolymer material. This integration not only introduces novel pathways for advancing green energy solutions but also offers a critical approach to addressing contemporary environmental challenges and fostering sustainable progress. Over the past few years, B-TENGs have seen rapid and remarkable growth in the realm of biopolymers, device architecture, and their applications (e.g., implantable power source, electronic medicine, human anatomical and physiological movements monitoring sensors, etc.). In this review article, the promising developments in harnessing triboelectric biopolymers are encapsulated, enumerate their representative applications, evaluate the pros and cons of these biopolymers, highlight key challenges for future research, and offer strategic recommendations for innovating and realizing advanced B-TENGs.

Modeling Lymphoma Angiogenesis, Lymphangiogenesis, and Vessel Co-Option, and the Effects of Inhibition of Lymphoma–Vessel Interactions with an αCD20-EndoP125A Antibody Fusion Protein

Lymphoma growth, progression, and dissemination require tumor cell interaction with supporting vessels and are facilitated through tumor-promoted angiogenesis, lymphangiogenesis, and/or lymphoma vessel co-option. Vessel co-option has been shown to be responsible for tumor initiation, metastasis, and resistance to anti-angiogenic treatment but is largely uncharacterized in the setting of lymphoma. We developed an in vitro model to study lymphoma–vessel interactions and found that mantle cell lymphoma (MCL) cells co-cultured on Matrigel with human umbilical vein (HUVEC) or human lymphatic (HLEC) endothelial cells migrate to and anneal with newly formed capillary-like (CLS) or lymphatic-like (LLS) structures, consistent with lymphoma–vessel co-option. To inhibit this interaction, we constructed an antibody fusion protein, αCD20-EndoP125A, linking mutant anti-angiogenic endostatin (EndoP125A) to an αCD20-IgG1-targeting antibody. αCD20-EndoP125A inhibited both CLS and LLS formation, as well as MCL migration and vessel co-option. Lymphoma vessel co-option requires cell migration, which is regulated by chemokine–chemokine receptor interactions. CXCL12 and its receptor, CXCR4, are highly expressed by both endothelial cells forming CLS and by MCL cells during vessel co-option. αCD20-EndoP125A suppressed expression of both CXCL12 and CXCR4, which were required to facilitate CLS assembly and vessel co-option. We also tested αCD20-EndoP125A effects in vivo using an aggressive murine B cell lymphoma model, 38c13-hCD20, which demonstrated rapid growth and dissemination to tumor-draining lymph nodes (TDLNs) and the spleen, lung, and brain. The pattern of lymphoma distribution and growth within the lung was consistent with vessel co-option. As predicted by our in vitro model, αCD20-EndoP125A treatment inhibited primary tumor growth, angiogenesis, and lymphangiogenesis, and markedly reduced the number of circulating tumor cells and lymphoma dissemination to TDLNs and the lungs, spleen, and brain. αCD20-EndoP125A inhibited lymphoma vessel co-option within the lung. Marked inhibition of MCL primary tumor growth and dissemination were also seen using an MCL xenograft model. The ability of αCD20-EndoP125A to inhibit angiogenesis, lymphangiogenesis, and lymphoma vessel co-option provides a novel therapeutic approach for inhibition of lymphoma progression and dissemination.

Transformer Based Ship Detector: An Improvement on Feature Map and Tiny Training Set

The exponential increment of commodity exchange has raised the need for maritime border security in recent years. One of the most critical tasks for naval border security is ship detection inside and outside the territorial sea. Conventionally, the task requires a substantial human workload. Fortunately, with the rapid growth of the digital camera and deep-learning technique, computer programs can handle object detection tasks well enough to replace human labor. Therefore, this paper studies how to apply recent state-of-the-art deep-learning networks to the ship detection task. We found that with a suitable number of object queries, the Deformable-DETR method will improve the performance compared to the state-of-the-art ship detector. Moreover, comprehensive experiments on different scale datasets prove that the technique can significantly improve the results when the training sample is limited. Last but not least, feature maps given by the method will focus well on key objects in the image.

Traffic Accidents: A Historical and Socio-Legal Analysis of Road Safety Challenges

Abstract This article examines the socio-legal aspects of the formation of the concept of a traffic accident, exploring its evolution from the late 19th century to the present day. The rapid growth of motor vehicles and the increasing complexity of road systems have necessitated the development of legal frameworks and safety regulations to address the risks posed by traffic accidents. The study highlights key legal milestones, such as the official introduction of the term “traffic accident” at the 1949 Geneva Conference, and analyzes the role of societal attitudes toward road safety and personal responsibility. It also delves into the cultural factors influencing traffic behavior, emphasizing the need for a comprehensive safety culture that involves drivers, pedestrians, and state regulation. By assessing the socio-legal dynamics, the article provides insights into the challenges of ensuring road safety and reducing the social and economic consequences of traffic accidents.

Competition and coordination between traditional and internet hospitals

AbstractMotivated by the recent emergence and rapid growth of online healthcare platforms, this paper investigates its impacts on the healthcare ecosystem by taking into consideration of heterogeneous patients, homogeneous service providers and profit-driven hospitals. A game-theoretical model with a queueing framework is developed, and two healthcare systems are considered, including a monopolistic system with either an offline, traditional hospital, or an online, Internet hospital, and a duopolistic system with both kinds of hospitals. Our study finds that in both systems a large population of patients always increases the healthcare supply and demand and the hospital utilization, which leads to an improvement not only in the hospital profitability, but also in the welfare of both patients and service providers. When considering a monopolistic system only, our study suggests that the monopolistic Internet hospital outperforms its counterpart in hospital utilization only when the wait cost is not high (i.e., patients are less sensitive to wait time), especially when the wait cost is medium and the patient-provider ratio is small. When considering a duopolistic system, this study concludes that the decisions of patients, service providers, and hospital managers of both hospitals are interrelated, and that a large population of service providers increases its hospital’s supply, demand, and wage rate, while decreases its wait times. When comparing the two monopolistic with the duopolistic system, the latter outperforms and improves every entity’s utility (i.e., patients, hospital, and society) when there is abundance of service providers with more being allocated to the Internet hospital, whereas the monopolistic system dominates when the patient population is large, and more providers are allocated to the traditional hospital.

New approaches and performance analysis of on-demand delivery systems using buses

With the rapid growth of on-demand delivery, traditional third-party delivery services using electric bicycles face increasing challenges, including increased labor costs and safety issues. To address these issues, we propose two modes for on-demand delivery systems using buses. One is the “bus terminal + professional crowd shippers” (B&P) mode, which involves consolidating parcels from various origins at the bus transfer hub. From there, they are grouped and delivered by buses. The other is the “bus stop + crowdsourced passenger” (B&C) mode, which transports parcels directly from the origin to the destination by passengers without the need for consolidation and sorting at bus transfer hubs. Both modes fully utilize the surplus capacity of buses and employ resources from retail stores and third-party shippers. We evaluated these modes using key performance indicators (KPIs) such as labor costs, cost increases from en-route destination changes, and average delivery time per kilometer. This analysis was based on 18,349 delivery cases in downtown Ningbo, China. Through this evaluation, we identified the strengths, weaknesses, opportunities, and threats associated with each mode. Our findings reveal that both the B&P and B&C modes effectively reduce delivery costs and external impacts while maintaining a user experience and efficiency level comparable to traditional third-party delivery services for mid-to-long-distance (3–10 km) deliveries. However, the use of public transportation may limit the flexibility of the delivery mode. Based on these insights, we provide strategic recommendations for the further development and implementation of B&P and B&C modes.

Productive and morphological features of females and calves of domestic deer of the Evenk and Nenets breeds during the calving period

Purpose: to conduct a comparative description of the productive and morphological characteristics of domestic reindeer of the Nenets and Evenki breeds.Materials and methods. Study of the morphological, behavioral and reproductive characteristics of domestic reindeer of the Nenets and Evenki breeds, kept in various natural and climatic conditions of the tundra and northern taiga, during the calving and dairy periods. Experimental data were collected from clinically healthy animals. The research was carried out in accordance with the basic methods of zootechnical research (observation, examination). Their gender (visually) and age were determined (using ear tags and animal registration data, and, if necessary, based on the degree of tooth wear); An assessment of the exterior of the reindeer herd was carried out before the rut to select males and females for mating. Methods of visual assessment, linear measurements of animals, and field chronometry of calving were used.Results. The Evenki breed of deer is distinguished by its large size, height, high load-carrying capacity and endurance when transporting goods and people. It has been established that the dynamics of calving of domestic reindeer of the Evenki breed is identical to the dynamics of calving of Nenets reindeer, but there are some peculiarities. In the tundra zone, calving takes 3—5 days longer, and the initial phase begins (on average) 7-10 days earlier than in the taiga zone. The live weight of Evenki breed calves at birth is 0.8 kg higher than that of Nenets breed calves. The intensity of growth up to 3 months of age is higher in the early, mass and late periods of calving. It has been established that calves of the early calving period exceed in live weight at birth and its growth the calves of the mass period, and those, in turn, exceed the calves of the late calving period. This pattern can be traced up to 6 months of age. Calves of early and mass calving periods, having the potential for rapid growth, find themselves in more favorable nutritional conditions in the first months of life than late calves. This is expressed in the ability to receive green pasture food 15-25 days earlier and be stronger by the time the blood-sucking dipterous insects appear. Early calving Nenets calves are more active at night, since there is still a lot of snow in the tundra zone during this period and the temperature sometimes drops below 0ºC.

The proportion of weight gain due to change in fat mass in infants with vs without rapid growth.

There is extensive evidence that rapid infant weight gain increases the risk of childhood obesity, but this is normally based on childhood body mass index (BMI) only and whether or not this is because infants with rapid weight gain accrue greater fat mass is unknown. The primary objective of our study was to test whether the proportion of infant weight gain due to concurrent increases in fat mass is greater in infants with rapid weight gain as compared to those with normal growth. Body composition was assessed by (1) air-displacement plethysmography (ADP) at 0 and 6 months in 342 infants from Australia, India, and South Africa and (2) deuterium dilution (DD) at 3 and 24 months in 555 infants from Brazil, Pakistan, South Africa, and Sri Lanka. Weight gain and length growth were each categorized as slow, normal, or rapid using cut-offs of <-0.67 or >+0.67 Z-scores. Regression was used to estimate and contrast the percentages of weight change due to fat mass change. Approximately 40% of the average weight gain between 0 and 6 months and 20% of the average weight gain between 3 and 24 months was due to increase in fat mass. In both samples, compared to the normal group, the proportion of weight gain due to fat mass was higher on average among infants with rapid weight gain and lower among infants with slow weight gain, with considerable individual variability. Conversely, slow and rapid length growth was not associated with differential gains in fat mass. Pediatricians should monitor infant growth with the understanding that, while crossing upward through the weight centiles generally is accompanied by greater adiposity gains (not just higher BMI), upward crossing through the length centiles is not.

Trends in the dynamic evolution of blockchain and circular economy: A literature review and bibliometric analysis

AbstractThe intersection of blockchain technology and circular economy (CE) practices holds significant potential for enhancing sustainability, transparency, and efficiency. This study conducts a comprehensive bibliometric analysis to explore the current research landscape in this domain. Key findings indicate a rapid growth in publications, highlighting a burgeoning interest in leveraging blockchain for CE initiatives. The analysis identifies critical approaches such as enhancing supply chain transparency, improving resource management, and facilitating product lifecycle tracking. However, the integration of blockchain into CE practices presents challenges, including technical complexities, scalability issues, and regulatory hurdles. Addressing these challenges requires interdisciplinary and cross‐sectoral collaboration, as well as continuous research and innovation. Future research should focus on the integration of emerging technologies with blockchain, longitudinal studies on long‐term impacts, socio‐economic implications, and the development of regulatory frameworks. This study contributes to the existing body of knowledge by providing unique insights and outlining potential research directions at the intersection of blockchain and CE.