bluuebunny/crossref_metadata_2025 huggingface dataset:
Flexible strain sensors based on carbon nanotubes/polydimethylsiloxane composites with a segregated structure prepared by sustainable emulsion method
Authors: Jia Bin , Liu Zhouyu , Xiang Dong , Liu Libing , Sun Haoming , Wu Yuanpeng , Mu Mulan , Wang Bin , Zhao Chunxia , Li Hui
Published: December 2024

Flexible strain sensors have been widely used in many fields because of their excellent adaptability and flexibility. Nonetheless, creating these sensors through simple methods that achieve a low percolation threshold and high sensitivity continues to pose a challenge. In this paper, a segregated structure was realized in a carbon nanotube/polydimethylsiloxane (CNT/PDMS‐S) strain sensor by a sustainable emulsion method that involved the mixing cellulose nanocrystals (CNCs), CNTs, PDMS and water. The incorporation of CNC improved the stability of CNTs in aqueous suspension. Consequently, The CNT@CNC nanocomposites were strategically placed in the gaps between the PDMS microspheres, creating a segregated structure. The segregated structure notably lowered the percolation threshold of the composite to 0.49 wt%. Moreover, we found that the CNT/PDMS‐S sensor containing 1.5 wt% CNTs showed excellent sensing performance, which not only had a wide strain measurement range and could adapt to the strain change from 0% to 70%, but also had high sensitivity with a gauge factor (GF) of 290 at 70% strain. Meanwhile, the sensor had an excellent linear response (R2 ≥ 0.96) and can monitor the minimum strain of 0.1%. The proposed sensor demonstrated excellent response when applied to sense wrist movement, facial movement and closure, and syllable recognition.

Highlights

Strain sensors with a segregated structure were realized by a sustainable method.

The segregated structure greatly reduces the percolation threshold of sensor.

The sensor has a high sensitivity, linearity, and wide strain detection range.

The sensor features high resolution for tiny deformations sensing.
Shrubs Strongly Influence Snow Properties in Two Subarctic Watersheds
Authors: Lathrop Emma , Thomas Lauren , Gasarch Eve , Bachand Claire , Bolton W. Robert , Busey Robert , Crumley Ryan L. , Dann Julian , Dillard Shannon L. , Bennett Katrina E.
Published: December 2024

Understanding changes in snow distribution in permafrost ecosystems is fundamental to predicting their response to future climate change. The expansion of tall shrubs into tundra ecosystems can trap snow and insulate permafrost ecosystems during the winter, but the overall insulation effect is dependent upon many ecosystem properties. To study shrub–snow–ground interactions, small temperature sensors were deployed at two research sites on the Seward Peninsula of Alaska, USA, during the 2019–2020 winter. Snow temperatures were used to extrapolate multiple metrics, including freezing n‐factors, the snow insulation effect, snow cover duration, and the length of the snowmelt period. Statistical and spatial analysis showed that shrub patches were a dominant control on all snow metrics. Within shrub patches, average ground temperatures were 2.1°C warmer, snow persisted 50 days longer, snow insulation was double, and a longer, later spring snowmelt period occurred compared to nonshrubby areas. Site‐level differences contributed relatively little to variation in snow metrics, indicating that shrub presence is an overarching driver of snow–ground interactions at the locations examined. Shrub expansion, which is anticipated under climate change, will strongly impact future permafrost distribution and Arctic energy, water, and carbon cycles through snow–shrub–ground feedbacks.
Single and dual RPA‐CRISPR/Cas assays for point‐of‐need detection of Stewart's wilt pathogen (Pantoea stewartii subsp. stewartii) of corn and Maize dwarf mosaic virus
Authors: Tian Qian , Zhou Hua , Zhao Zhenxing , Zhang Yongjiang , Zhao Wenjun , Cai Lulu , Guo Tao
Published: December 2024

BACKGROUND

Pantoea stewartii subsp. stewartii and Maize dwarf mosaic virus (MDMV) infections severely affect corn productivity worldwide. Rapid point‐of‐need diagnoses of quarantine pathogens P. stewartii subsp. stewartii and MDMV are required for early detection, timely disease management and ensuring phytosanitary regulations. Recombinase polymerase amplification (RPA) is an isothermal technique suitable for rapid diagnostics using minimally processed samples. Integrating CRISPR/Cas collateral activities with the RPA assays further enhances the specificity and sensitivity of molecular toolkits for diagnostic assays.

RESULTS

RPA‐CRISPR/Cas12a assay targeting the intergenic spacer region between capsular polysaccharide genes cpsA and cpsB of P. stewartii subsp. stewartii detected 1 × 10−6 ng DNA μL−1 using real‐time fluorescence and blue light observation methods, and 1 × 10−4 ng DNA μL−1 using the lateral flow dipstick (LFD). Likewise, RPA‐CRISPR/Cas13a assay detected MDMV coat protein (CP) gene with an ultrasensitive detection limit of 3.69 × 10−7 ng μL−1 using the real‐time fluorescence and blue light observation methods, and 3.69 × 10−5 ng μL−1 using the LFD. The dual RPA‐CRISPR/Cas assays detected both pathogens without compromising the speed and/or detection sensitivity of the single assays.

CONCLUSION

The validated assays provide a useful and sensitive molecular tool for detecting two quarantine pathogens of maize within a minimal resource framework suitable for fast‐tracking the containment strategies. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
Resilient Formation Tracking for Networked Swarm Systems Under Malicious Data Deception Attacks
Authors: Liu Yishi , Li Wenxin , Dong Xiwang , Ren Zhang
Published: December 2024

A distributed time‐varying formation tracking method for a leader‐following networked swarm system in the presence of malicious deception attacks is proposed in this paper. Both state and output equations are injected with false data by adversaries to prevent formation tracking information transmission. The real‐time attack estimations are provided by an anomaly estimator. To design an event‐triggered secure formation tracking protocol, a state predictor is utilized to provide neighboring states. The attack estimations and neighboring error are considered in the secure control protocol, which is adjusted using the Lyapunov stability theorem. A simulation result is shown to validate that the proposed method can accomplish the desired formation tracking under deception attacks.
Construction of Pt─O Sites on Pt Nanoclusters in Silicalite‐1 Zeolite for Efficient Catalytic Oxidation of Hydrogen Isotope Gases
Authors: Wei Guilin , Zhou Linsen , Wang Xianglin , Tang Ru , Chen Kelin , Luo Junhong , Song Jiangfeng , Shi Yan , Liu Ning , Feng Xingwen
Published: December 2024

The construction, use, and maintenance of tritium‐related equipment will inevitably produce tritium‐containing radioactive waste gas, and the production of efficient catalysts for tritium removal remains a difficult problem. Herein, silicalite‐1 zeolite with entrapped Pt nanoclusters is skillfully post‐oxidized at an appropriate temperature, building highly active Pt─O sites on the nanoclusters to achieve efficient oxidation of hydrogen isotopes at low temperatures. The designed Pt─O sites can directly participate in the oxidation reaction of hydrogen isotopes. Compared to the case without Pt─O sites, the presence of these sites significantly reduces the reaction energy barrier to 0.55 eV, enabling the catalyst to achieve a hydrogen conversion rate of 99% at a low temperature of 40 °C. Specifically, the O atoms consumed by the Pt─O sites in the reaction are replaced by O2 gas and this cycle repeats, which is consistent with the Mars‐van Krevelen (M–K) theory. This ensures efficient catalytic oxidation of hydrogen isotopes, and provides an astonishingly high conversion rate of 99% in the nearly 34 days restart performance test. The results of this study provide insights into the strategic design of efficient catalysts for hydrogen isotope oxidation.
In Situ Unravelling NiOOH Species on Flower‐Like NiFeCo LDH/Nb2CTx for Ameliorated Solar‐Powered Bifunctional Electrocatalytic Benzyl Alcohol Oxidation Coupled with Hydrogen Evolution
Authors: Loh Jian Yiing , Yap Feng Ming , Siang Tan Ji , Zeng Xianhai , Ong Wee‐Jun
Published: December 2024

Developing bifunctional electrocatalysts from earth‐abundant first‐row transition metals for large‐scale hydrogen production through water electrolysis is both promising and challenging. This study presents a ternary layered double hydroxide (LDH) as a bifunctional electrocatalyst for the hydrogen evolution reaction (HER) and benzyl alcohol oxidation (BAOR). The synergy between 2D NiFeCo LDH and non‐Ti‐based Nb2CTx MXene enhances electrochemical performance. The electrocatalyst achieves excellent results with a low potential of 1.5 V versus RHE at 100 mA cm⁻2 for BAOR, an overpotential of 320 mV at 50 mA cm⁻2 for HER, and stability over 100 h. A solar cell‐powered HER||BAOR system shows faradaic efficiency of ≈73.92% for benzaldehyde production and solar‐to‐hydrogen (STH) efficiency of ≈39.67%. In situ Raman analysis identifies the oxyhydroxide group as the real catalytic active site during BAOR. These findings offer valuable insights for linking fundamental research with technological innovation to address global challenges.
Traumatic lumbosacral instability: part 1 – proposing a definition and identifying underlying injury patterns
Authors: Lindtner Richard A. , Krappinger Dietmar , Lindahl Jan , Bellabarba Carlo
Published: December 2024

Traumatic lumbosacral instability (TLSI) generally refers to a traumatic disruption of the lumbopelvic junction. The ambiguous use of this term has contributed to confusion and limited understanding of injuries that can impact lumbosacral stability. As of now, TLSI lacks a clear definition, and the underlying injury patterns remain inadequately characterized. Therefore, the objectives of the first part of this two-part series are: (1) to establish a precise definition of TLSI, (2) to identify and systematically characterize the injury patterns underlying TLSI, and (3) to outline principles for diagnosing and classifying these underlying conditions.
High-power all-fiber tunable near-infrared 1.1 ~ 2.1 μm burst-mode supercontinuum laser
Authors: Liu Shuailin , Peng Xi , Zhang Bin , Bu Yuanzhuang , Yang Linyong , Hou Jing
Published: December 2024

In this paper, we demonstrate a high-power all-fiber tunable near-infrared (NIR) burst-mode supercontinuum (SC) based on passive fiber. By optimizing the seed pulse parameters, pump energy of the main amplifier and passive fiber length, the NIR burst-mode SC spectrum with a coverage range of 1.1 ~ 2.1 μm was obtained, the subpulse repetition rate can be continuously tuned from 0.5 GHz to 10 GHz, with the highest output energy of 1.24 mJ and the peak power of ~ 200 kW. This is a fresh experimental demonstration to reveal that passive fiber can emit high power all-fiber tunable NIR burst-mode SC, which is of key importance for applications such as spectral LiDAR, optical coherence tomography (OCT), as well as multi-color fluorescence imaging.
The Conversion of Sir Tobie Matthew: Homosocial Bonds and Affective Networks in Early Modern Catholicism
Authors: Santa Maria Thomas
Published: December 2024

This article offers an in-depth examination of Sir Tobie Matthew’s conversion as an attempt to understand not only the internal process of conversion for one individual, but also its meaning for the English Catholic community during the early seventeenth-century. Matthew was an extraordinary figure. He was both learned and extremely well-connected, with friends in the highest echelons of the Roman Catholic Church, and in English society, and this despite his conversion. He maintained those relationships to his benefit throughout his life. Officially he was at times an exile from England and at other times at court, nonetheless he was always at the centre of dynastic politics. He maintained loyalty to England throughout his life, but clearly felt a draw to Catholicism for its intellectual tradition, emotional appeal, his desire to travel; and, perhaps, also for reasons of sexuality. Sir Tobie’s conversion reveals just how complex the relationship between religious and national identity could be after the Reformations.
Surface-Based Morphometry Findings Reveal Structural Alterations of the Brain in Meige Syndrome
Authors: Tang Yunyu , Liu Ruen
Published: December 2024

Objective:

To compare structural alterations in the brains of Meige syndrome (MS) patients with those of healthy controls (HCs) by using surface-based morphometry (SBM) and compare structural differences between the brains of MS patients with sleep disorders and those of MS patients without sleep disorders.

Methods:

We investigated cortical surface parameters in 42 MS patients and 30 HCs. T1-weighted images were acquired and processed using CAT12 to perform vertexwise between-group comparisons of cortical thickness, gyrification, cortical complexity and sulcus depth with validated quality control protocols. We also performed SBM to analyze data from 19 patients with sleep disorders and 23 patients without sleep disorders.

Results:

Compared with HCs, MS patients had differences in large clusters of cortical regions, especially in postcentral, precentral, superior frontal and paracentral thickness. Differences were also observed in the parietal and occipital areas. Among MS patients with and without sleep disorders, altered cortical complexity and sulcal depth were observed.

Conclusions:

This study strongly suggested that MS patients have cortical structural abnormalities compared with HCs, thus elucidating the underlying pathophysiology of motor and nonmotor symptoms in MS patients.
Models of Field Hospital Emergency Departments: The Israeli Experience
Authors: Alpert Evan Avraham , Weiser Giora , Schul Shai , Mashiach Eran , Shaham Amit , Kobliner-Friedman Deganit
Published: December 2024

The World Health Organization has classified Emergency Medical Teams (EMTs) into 3 types for international disaster response. They range from those that operate as daytime clinic facilities to those that have complete hospital capabilities that can provide 24/7 inpatient care. The most complex EMT (Type 3) includes a full-scale emergency department (ED), operating rooms, a medical/surgical ward, an intensive care unit, and laboratory services. The Israel Defense Forces Field Hospital was the first to be officially designated as a Type 3 EMT. Two models have been used by the Israeli EMT depending on the disaster response: standalone and hybrid. The standalone model is where the ED and hospital are set up in tents independent of any existing health care facilities. The hybrid model is where the equipment and personnel are combined with existing structures. Pediatric patients are examined in either a designated area staffed by specialized pediatric emergency physicians and nurses or integrated into the general ED. Models of ED layout, staffing, scheduling, and equipment are also described. While the Israeli team is a Type 3 EMT, the different models of ED organization can also be applied to other types of field hospitals to maximize care in the disaster setting.
A Domino Theory of Disease
Authors: Fagerberg Harriet
Published: December 2024

This paper advances a theory of disease as domino dysfunction. It is often argued that diseases are biological dysfunctions. However, a theory of disease as biological dysfunction is complicated by some plausible cases of dysfunction, which seem clearly non-pathological. I argue that pathological conditions are not just dysfunctions but domino dysfunctions, and that domino dysfunctions can be distinguished on principled biological grounds from non-pathological dysfunctions. I then show how this theory can make sense of the problem cases; they are not diseases because they are not domino dysfunctions.
Yellow peril or model minority? Measuring Janus-faced prejudice toward Asians in the United States
Authors: Kim D.G. , Han Enze
Published: December 2024

There are two prominent but seemingly contradictory symbols of how Asians are racialized domestically within the United States: “yellow peril” and “model minority.” How do these two racial tropes relate to each other? What effects do they have on the formation of support for race-targeted public policy? In this paper, we propose and empirically test that racialized resentment toward Asian Americans and the congratulatory framing of them as a model minority are both salient in the minds of the American public, reflecting the complexity of prejudices toward Asians in American society. Utilizing two original survey-based measures of anti-Asian resentment and the model minority stereotype, we empirically demonstrate the interconnection between the two racial tropes and highlight the key demographic and dispositional correlates of these multi-faceted contemporary racial attitudes toward Asian Americans. We then show that the two racial tropes, both independently and by interacting with each other, significantly shape racial public policy preferences in the United States.
The Racial Geography of U.S. Public Opinion at the Punitive Turn
Authors: Fresh Adriane
Published: December 2024

A large literature considers the mid-century a key turning point in punitive public opinion in the United States. This article examines racial and geographic heterogeneity in changing public opinion during the mid-century using data on death penalty support from as early as 1953. I find that the punitive turn is characterized by divergence in death penalty support between Black and White people, and that White Southerners grew more supportive than Whites in the non-South from before to after the turn. Additional tests identify that this regional divergence is unlikely to have arisen by chance. Heterogeneity in partisanship and responsiveness to regional violent crime support is consistent with the idea that crime rates themselves were meaningful in punitive attitude formation only insofar as they were mediated by additional socio-political forces.
A Ticking Time Bomb: Restrictions on Abortion Rights and Physical Integrity Rights Abuses
Authors: AVDAN NAZLI , MURDIE AMANDA , ASAL VICTOR
Published: December 2024

Do abortion restrictions augur broader crackdowns on human rights? We examine the relationship between restrictions on abortion and future Physical Integrity Rights (PIR) abuses. We argue that abortion restrictions both directly and indirectly influence PIR. Directly, abortion restrictions serve as a testing ground for repressive policies and behaviors. Indirectly, restrictions worsen inequality across segments of society and winnow support for social and religious diversity. When abortion restrictions are enacted, regimes are better equipped to shift society and consolidate power, as a subdued public is discouraged from voicing collective grievances. Using a variety of time-series cross-sectional approaches, we show that significant retractions in abortion access foretell erosion of PIR.
Prevalence and genotypic characterization of zoonotic intestinal protozoan parasites in transboundary migratory Mongolian Gazelles (Procapra gutturosa): the first survey
Authors: Gao Sichao , Hu Bin , Li Gaojian , An Xing , Xing Yanan , Han Shuyi , Chun Yan , Han Lingling , Xi Du , Li Wenchao , He Hongxuan
Published: December 2024

The migration of Mongolian gazelles (Procapra gutturosa) poses a potential risk of outbreak for zoonotic intestinal protozoan parasite infections. This study aims to investigate the infection status of zoonotic intestinal protozoan parasites in these migratory Mongolian gazelles. We collected 120 fecal samples from Mongolian gazelles during their migration from Mongolia to China in December 2023. These samples were analysed using amplification and sequencing of partial SSU rRNA genes to detect the 4 presence of zoonotic intestinal protozoan parasites and characterize their genotypes. Our analysis revealed the presence of several zoonotic intestinal protozoan parasites in the sampled Mongolian gazelles. Cryptosporidium spp. was detected in 14.17% (17/120) of the samples, followed by Cystoisospora belli in 13.33% (16/120), Blastocystis sp. in 16.67% (20/120) and Cyclospora cayetanensis in 30.00% (36/120). Moreover, we identified novel host-adapted genotypes of Cryptosporidium spp. and C. belli, as well as the presence of ST2 and ST13 Blastocystis sp. subtypes, while distinct genotypes were found in Blastocystis sp. and C. cayetanensis. This study revealed the status of 4 prevalent zoonotic intestinal protozoan parasite infections in Mongolian gazelles and provided crucial insights into their characteristics. The prevalence of these parasites in the population highlights the potential risk of cross-border transmission of infectious diseases associated with long-distance migration. Furthermore, the identification of novel genotypes contributes to our understanding of the genetic diversity and adaptation of these parasites. These findings can inform the development of protective measures to mitigate the impact of these infections on the health and survival of Mongolian gazelles.
An Indian Jewish Commandant and a Muslim Begum
Authors: Weil Shalva
Published: December 2024

This article explores the oral narratives about Samuel Ezekiel Divekar (1730–97), an officer in the British army and a member of the Bene Israel Indian Jewish community, who was released from the prison of Tipu Sultan (1751–99) by the Muslim ruler’s mother, Begum Fatima Fakhr-un-Nisa. These foundational narratives are compared with non-native colonial and other sources, including manuscripts, books, letters and reports located in libraries and archives, in order to see whether there is any synchronicity between the different versions. Of particular interest is the gender dimension in which Divekar’s release from prison was facilitated by a Muslim woman, reminiscent of the biblical story of Joseph and Potiphar’s wife in Egypt. Although prominent in the Bene Israel communal narrative, the Begum’s role is reflected neither in colonial records nor in other accounts (notably, in Cochin Jewish letters). Finally, the question of whether Divekar brought a Torah scroll to the Gate of Mercy synagogue (so named to commemorate the compassion of the Begum) established in 1796 in Bombay is discussed. The article demonstrates that the analysis of subaltern oral narratives can enrich our understanding of history by giving a voice to marginalised groups, and focusing on suppressed narratives about gender.
Personality Revisited: A Posthumous Tribute to Albert Bandura and David Magnusson
Authors: Caprara Gian Vittorio
Published: December 2024

To honour the memory of Albert Bandura and David Magnusson, a few years after their deaths, the current status and perspectives of research on Personality is addressed. There is a growing demand for psychological knowledge to enable our societies to value their human capital. To this end, contemporary research on Personality moves beyond traditional rivalries among competing theories and addresses the whole personality by focusing on the unique properties that account for humans as agentic and moral beings, and for the social conditions that enable us to unveil and nurture the best of our humanity.
Nutritional characterization and identification of sweet tamarind (Tamarindus indica L.) accessions from the Bastar region of Chhattisgarh, India
Authors: Chaturvedi Kanupriya , G Karunakaran , Satisha G. C. , Singh Pritee , Nag S. K. , Kumar Prakash
Published: December 2024

This study aimed to explore the genetic variability present in tamarind fruits. A survey and collection of twenty-nine tamarind accessions from the Bastar region of Chhattisgarh was conducted, focusing on morphological traits, biochemical properties, and mineral content. The analysis revealed significant variation in fruit characteristics, including pod weight (91.1–528.3 g), pod length (4.11–15.39 cm), pulp weight (32.88–275.68 g), number of seeds (26–237), seed weight (23.14–214.08 g), pulp percentage (26.43–52.18%), vitamin C content (54.5–92 mg/100 g), phenolic content (51.53–296.4 mg GAE/g fw), flavonoid content (75.91–280.88 mg QE/ 100 g fw), acidity (5.3–12.60%), reducing sugars (24.67–68.29%), total sugars (24.89–78.87%), calcium (0.15–1.28%), and iron content (26.6–125.7 ppm) across different accessions. Based on the overall evaluation, five accessions B21, B26, B15, B25, and B7 with the best combination of desirable fruit traits, were identified as the most promising. Additionally, five sweet accessions with acidity levels below 6% were identified (B26, B21, B15, B12, B11). Principal component analysis (PCA) was applied, identifying five principal components that accounted for 86.73% of the total variability. Correlation analysis showed a significant positive relationship between pod weight and pulp weight (r = 0.93), shell weight (r = 0.70), number of seeds (r = 0.89), and seed weight (r = 0.89). The biplot of PC1 and PC2 illustrated the distribution of accessions across all four quadrants, with B27, B8, B26, B29, B14, B18, and B13 displaying distinct differences from one another.
Independent Effects of Emotional Expression and Group Membership in the Evaluative Priming Task
Authors: Gurbuz Emre , Rohr Michaela , Wentura Dirk
Published: December 2024

Abstract: Research on automatic evaluative responses to faces varying in emotional expression and ethnicity has yielded conflicting results. Some paradigms, like the Approach/Avoidance task, demonstrated interactive evaluation. In contrast, recent studies using the Evaluative Priming Task (EPT) yielded independent effects of expression and ethnicity. One key difference between these paradigms is the task relevance of the faces. In the EPT faces served solely as primes without direct relevance to the task. To examine whether increased task relevance could engender interactive processing in the EPT, we utilized a modified version of the “bona fide pipeline” EPT. In this adaptation, participants categorized the valence of target words succeeding prime faces followed by probe faces. Participants then judged whether the prime and probe faces depicted the same person, thereby adding task relevance to the prime faces. Experiment 1 revealed independent priming effects of emotion and ethnicity. Since error data and inverse efficiency scores provided evidence for an interactive evaluation, we replicated Experiment 1 using a sequential Bayes testing strategy. Experiment 2 confirmed that the effects of emotion and ethnicity remain independent, indicating that increased task relevance did not yield the integrated processing of emotion and ethnicity as initially hypothesized.
Probing the Causal Contribution of Reasoning to Third-Party Moral Judgment of Harm Transgressions
Authors: Schwartz Flora , Balat Florian , Trémolière Bastien
Published: December 2024

Abstract: Recent work has supported the role of reasoning in third-party moral judgment of harm transgressions. In particular, reasoning may increase the weight of intention in moral judgment, especially following accidental harm, a situation that presumably requires judges to balance considerations about the outcome endured by a victim on the one hand and considerations about an agent’s intention to cause harm on the other hand. Three preregistered lab-based studies aimed to test the causal contribution of reasoning to moral judgment of harm transgressions using experimental manipulations borrowed from the reasoning literature: time pressure (Experiment 1), cognitive load (Experiment 2), and priming (Experiment 3). Participants ( N = 284) were presented with short fictitious scenarios in which the agent’s intention toward a potential victim (harmful or neutral intent) and the action’s outcome (victim’s injury or no harm) were manipulated. Participants then reported their moral judgment of the agent’s behavior (wrongness and deserved punishment) and their empathy toward the victim. We found that time pressure reduced judgment severity toward agents who had the intention to harm, but the reasoning manipulations overall did not impact judgment severity toward agents who harmed accidentally. We discuss why reasoning may sometimes influence how individuals account for intention in third-party moral judgment of harm transgressions.
Bibliometrics Analysis of Digital Technology in Entrepreneurship
Authors: Fareeda Nafeesa , Irfana Shakira , A Chaithra , Shruthi
Published: December 2024

Digital technologies are frequently used in business, particularly for product advertising, sales, marketing, operations management, and improved customer service. This study used bibliometric visualization to map the position of digital technology in worldwide entrepreneurship studies published and indexed by the Web of Science. Bibliometric methodologies and research data analysis were carried out using the VOS viewer application’s analysis search results service and the Web of Science. The Web of Science database included research data for 558 documents published between 2015 and 2024. The findings revealed that England, People R China, Finland, France, and Sweden were the most productive nations, with institutional affiliations, and individuals publishing digital technology in entrepreneurship studies. Most document categories and subject areas in digital technology in entrepreneurship studies were openaccess documents. The findings highlight significant contributions to entrepreneurship by advancing the literature and highlighting key research fronts, offering insights that previous reviews still needed to fully grasp. The analysis and graphical displays provide valuable insights into how digitization affects entrepreneurship. The topic’s novelty and the gap revealed in previous research on digital technology on entrepreneurship prompted us to take an integrated strategy that included bibliometric analysis.
A comparative study on the benefits offered to faculty in private and public educational institutions
Authors: K Vanishree , Sharma Ankita , Mandava Vaishnavi , BH Kushal
Published: December 2024

This study aims to explore the quality of work life (QWL) for university teachers in Bangalore’s private sector. The purpose of this study is to evaluate the quality of work life (QWL) of private-sector teachers, compare it with their public-sector counterparts, and explore any potential benefits that public-sector employment might offer. A personal interview with a structured questionnaire was conducted with 100 teachers in Bangalore’s private sector. Data was analyzed with a T-test. Results indicate that while private sector teachers enjoy comparable professional development opportunities, they face challenges in work-life balance and lack non-financial incentives compared to public sector colleagues. These disparities create a stressful environment for private-sector teachers, potentially impacting their job satisfaction and student performance. The findings of this study advocate for reducing disparities between the public and private education sectors, adding to the ongoing dialogue between employees and employers in the educational sector. Additionally, the study aims to inform policymakers to foster a more equitable environment across the educational space. The findings of this study aim to inform policymakers in fostering a more equitable environment across the educational space by reducing disparities between the public and private education sectors. It also contributes to the ongoing dialogue between employees and employers in the educational sector.
Cutting-Edge AI for Healthcare: Optimized Pneumonia Diagnosis on MAX78000 Microcontroller
Authors: Poola Rahul Gowtham , Chodavarapu Tejaswi , Yellampalli Siva Sankar
Published: December 2024

The methodology discussed in the research herein results in the design of a pneumonia diagnosis system that can be executed in real time on hardware edge board. The methodology includes the design and optimization of a neural network classification model for a given pneumonia classifier within the scope of the study. The specifics of the neural network architecture are based upon the designed architecture, which has been modified to fit the computation requirements of the MAX78000 microcontroller. Once trained, the model is exported to file formats supported by the MAX78000 processor, which allows it to be used in the Eclipse programming environment. The final point is the deployment of the trained neural network model with a parallel camera and display which eliminates the need for external software and enables real-time pneumonia diagnosis. This integration emphasizes the flexibility and robustness of the system, and it demonstrates how a low-power system as the MAX78000 allows rethinking the approaches towards the medical diagnostics. After the system is deployed, it is able to deliver accurate predictions where it achieved 97% normal class prediction and 88% pneumonic class prediction. These results reaffirm the system’s efficacy in real-time classification tasks, highlighting the diagnostic potential.
Analysis of blockchain law and regulations
Authors: P Triveni , Jaikishen  , R Sanjana
Published: December 2024

Blockchain technology has brought significant innovation to various industries, including healthcare, supply chain, finance, and more. However, rapid adoption of the blockchain technology has outpaced the development of comprehensive legal frameworks, resulting in a complex and fragmented regulatory landscape. This paper aims to analyse current blockchain laws and regulations globally, identify the challenges faced in regulating blockchain, and propose potential solutions to harmonize these regulations to foster innovation while ensuring legal compliance and consumer protection. Key words: Block Chain technology, Legal framework, Regulations, Cryptocurrency
Algorithmic Trading and Sentiment Analysis in Indian Stock Market
Authors: Patil Smita Satish , Kubsad Pramod , Kulkarni Savitha
Published: December 2024

The rapid growth of social networks has produced an unprecedented amount of user-generated data, which provides an excellent opportunity for text mining. Sentiment analysis, an important part of text mining, attempts to learn about the author’s opinions on a text through its content and structure. Such information is particularly valuable for determining the overall opinion of a large number of people. Examples of its usefulness are predicting box office sales or stock prices. One of the most accessible sources of user-generated data is Twitter, which makes the majority of its user data freely available through its data access API. This study, will predict a sentiment value for stock-related tweets on Twitter, and demonstrate a correlation between this sentiment and the movement of a company’s stock price in a real-time streaming environment. This study data ranges from the period 2018 to 2024. The study reveals that the percentage of error which is less than 5% on almost all companies except one. Where it tells that if the percentage of Error is less than 5 then the accuracy is high and the predicted prices are more accurate.
Digital Edge Detection Based Pneumonia Detection in Chest Radiographs
Authors: Poola Rahul Gowtham , Kommineni Prema Teja , Lahari P.L , Yellampalli Siva Sankar
Published: December 2024

In response to the demand of pneumonia diagnosis, a digital detection algorithm utilizing chest X-ray images has been proposed. Despite this, X-ray images have the tendency of noise and spatial aliasing that tend to cause blurring of some boundaries, thus the importance of having a better edge detection algorithm is more warranted. The article presents a SIMULINK-based model for the process of edge detection, testing the performance of Canny, Laplacian of Gaussian, Prewitt, Sobel and Robert algorithms and most importantly their simulated results. Since some of the X rays are suspected to be afflicted by pneumonia, the radiographs are also converted into string numbers based on the features extracted as the Xray’s area of interest. One of the basic processes in image processing is the quality assessment of images, this work advocates for the inclusion of the objective criteria for the evaluation of the segmented images. Some performance evaluation metrics for various edge detection models are given and the relationships showed that the bacterial pneumonia affliction X rays have feature string values under 100 whereas the nonbacterial pneumonia X rays have values above 100.
The Transformative Influence of Artificial Intelligence on Supply Chain Management
Authors: Tarihal Balakrishna , Kaliwal Rohit , Ammanagi Ashok
Published: December 2024

The application of AI in supply chain management has revolutionised how organisations can improve, enhance and even transform their supply chain and operational structures. In the current and future business environment, characterised by globalisation and competition, AI has shifted from being a competitive advantage to a necessity. This paper aims to explore the effects of AI on supply chains with a particular emphasis on how machine learning and other forms of intelligent algorithms can improve decision-making, operational effectiveness and real-time responsiveness. This research focuses on the use of AI technologies like predictive analytics, RPA, and autonomous systems in supply chain management functions like inventory management, demand forecasting, procurement, and distribution. This is because predictive analytics allows organisations to anticipate market and consumer trends, thus improving the organisation’s predictions and planning. RPA involves automating rulebased processes, thus allowing employees to focus on more complex tasks, while autonomous systems, including drones and self-driving vehicles, enhance supply chain management by increasing the speed and reducing A combination of qualitative data collected through interviews and surveys and quantitative data collected through case studies and industry reports was used. The study indicates that AI can significantly decrease lead times, enhance the accuracy of demand planning, and decrease operational costs. However, issues such as scalability, data security, and the issue of employment losses are still crucial issues that need to be discussed. This study also discusses the ethical implications of AI in supply chains, focusing on the workforce impact and providing recommendations for addressing the workforce challenges and enhancing data governance. Through presenting solutions to these challenges, this paper highlights the importance of the ongoing evolution and flexibility of AI-based supply chains. The organisations that are able to tackle these concerns will be in a good place to harness the full value of AI in the supply chain management function.
An evaluation of the ed-tech sector in India
Authors: Sadavar Maruti , Shaikh Arif
Published: December 2024

This qualitative research paper seeks to deliver an exhaustive analysis of the Ed-Tech sector in India by assessing its present condition, pinpointing significant trends, and investigating the elements driving its expansion and obstacles. It examines the various instructional technologies utilised, including online platforms, mobile applications, virtual classrooms, and adaptive learning systems. The study rigorously evaluates the efficacy and consequences of various technologies on educational outcomes, alongside their effects on student involvement, accessibility, and equity. This report examines the drivers behind the expansion of the Ed-Tech sector in India, including rising smartphone usage, enhanced internet access, supportive government initiatives, and evolving perceptions of online learning. It also examines the obstacles encountered by the sector, including the digital divide, insufficient teacher training, issues related to data privacy and security, and the necessity for regulatory frameworks. It analyses their strategy, business structures, and collaborations, emphasising effective practices and insights gained. This research study presents a comprehensive examination of the Ed-Tech sector in India, offering significant insights for policymakers, educators, investors, and stakeholders in education. The study’s conclusions relate to existing literature on Ed-Tech, aiding in the formulation of future initiatives, policies, and investments in the Indian education system.
Implementation of artificial intelligence in human resource management practices
Authors: Rama Devi P. , Anusuya S. , Saraswathi S. , Sandra Carmel Sophia M. , Chacko Jose P. , Jayachandran T. , Girimurugan R.
Published: December 2024

Analyzing how AI will change HRM strategies is the focus of this research. We may achieve our goals by concentrating on the following: precision, automation, processing capacity and power, real-time experience, customization, and saving time and money. The possible advantages of AI adoption are the target of the study. A well-structured online survey is utilized to gather data from 300 IT employees in the city of Coimbatore. The study presents a new research framework that makes use of AMOS version 21 and IBM SPSS version 21 for analysis. The outcomes show that factors like Personalization, Computing Power and Capacity, and Accuracy have a substantial impact on Time-Saving and Cost Reduction, however factors like Real-Time Experience and Automation do not. This unique addition of the study’s is to investigate the concrete results of implementing artificial intelligence technologies into human resource management procedures. The study delves deeply into the expected results and interrelationships of artificial intelligence implementation in human resource management by concentrating on critical variables including Computing Power & Capacity, Precision, Real-time experience, Time-Saving and Cost Saving, Automation, and Personalization.
Embracing Electric Two-Wheelers: A Transformative Shift in Consumer Adoption of Eco-Friendly Transportation Technology
Authors: Kulkarni Ameet V. , Kudachimath B.S. , Ingalagi Sanjeev
Published: December 2024

This study investigates the pivotal shift in consumer behaviour towards adopting eco-friendly transportation technology, specifically focusing on the significant uptake of electric two-wheelers. Employing a comprehensive review of contemporary literature and empirical data, this research examines the multidimensional factors influencing consumers’ enthusiastic acceptance of electric two-wheelers using structural Equation Modelling and Technology Acceptance Model. The data would be collected from users of EVs and Non EVs. The analysis reveals a confluence of factors driving this transformative trend, including heightened environmental awareness, advancements in battery technology, cost-efficiency considerations, urban mobility needs, supportive governmental policies, diversification in brand offerings, and evolving consumer preferences. Understanding the motivations behind consumers’ shift towards electric two-wheelers holds crucial implications for policymakers, manufacturers, and marketers, guiding strategies for sustainable transportation development, infrastructure enhancement, and targeted marketing initiatives. This study contributes to the existing literature by consolidating insights into the profound transformation occurring in consumer preferences towards ecofriendly transportation solutions, particularly in the domain of electric twowheelers.
“Immersive Technologies in Retail: The Impact of AR on Packaged Food Product Marketing and Consumer Behaviour”
Authors: Kagawade Shivanand S. , K Shivashankar , Kudachimath Basavaraj , Patil Ruturaj
Published: December 2024

This study examines how Augmented Reality (AR) is used in retail advertising, focusing on trends, themes, and factors that influence its adoption, as identified in academic literature. The goal is to understand how AR applications have evolved and their impact on advertising strategies in retail. The study utilized various analytical methods, including bibliometric analysis, word cloud analysis, Principal Component Analysis (PCA), and streamgraph analysis. Data was collected from Scopus and Web of Science databases, and analysis tools included VOSviewer, Voyant Tools, Python (using the sklearn library), and R’s streamgraph library.The results indicate a rising interest in AR for boosting customer engagement. Major themes identified include user interaction, immersive shopping experiences, and technological innovation. PCA highlighted the key components that drive AR adoption, while streamgraph analysis illustrated how research trends have changed over time.This research sheds light on the increasing significance of AR in retail advertising and provides valuable insights for future research and practical applications in the industry.
Research on Problem Analysis and Reform Strategy of Digital Transformation of Emerging Industries
Authors: Shao Yunze
Published: December 2024

This study explores the challenges and reform approaches related to developing sectors’ digital transformation, which is being fueled by the convergence of cutting-edge technologies, including big data, cloud computing, artificial intelligence, and the Internet of Things. Digital transformation is reshaping the organizational structures, production models, business practices, and decision-making processes within enterprises, establishing itself as a crucial new force in economic development. However, this transformation is fraught with challenges, including the selection and integration of technologies, the adjustment of organizational structures, escalating market competition, and mounting data security concerns. The analysis begins by exploring the background of digital transformation, influenced by factors such as technological innovation, evolving market demands, global digitalization trends, enterprises’ developmental needs, and supportive national policies. It identifies key issues like the complexity of technology integration, the difficulties in organizational restructuring, the intensity of market competition, and the significant risks associated with data security. To address these challenges, the paper offers several strategic recommendations: enhancing technical research and innovation, optimizing organizational frameworks, improving personnel training, sharpening market insights, and bolstering data security measures. Looking forward, as digital technologies develop more and find more uses, the digital transformation of emerging industries is poised to provide enterprises with substantial competitive advantages and new market opportunities.
Research On Enterprise Digital Transformation -- Taking Alibaba as an Example
Authors: Zhao Xinghao
Published: December 2024

This paper deeply discusses the background, concept and path of enterprise digital transformation, and takes Alibaba Group as a typical case for detailed analysis. In the context of digital economy, enterprises realize the comprehensive transformation of economic model through digitalization, networking and intelligent technologies, which promotes the wide application of cloud computing, big data analysis, artificial intelligence and Internet of Things. Digital transformation requires companies to fundamentally reshape their core business processes, management systems, business models and service approaches in response to a rapidly changing market environment. As a model of digital transformation, Alibaba Group has successfully achieved continuous business innovation and market leadership by building a platform ecosystem, diversified business layout, big data analysis and globalization strategy. This paper summarizes the basic principles and strategies of enterprise digital transformation, emphasizes the importance of data-driven decision-making, innovation culture, organizational structure optimization and technology application in the transformation process, and provides valuable experience and reference for other enterprises’ digital transformation.