Industry Professionals Research Articles

PCR Based Technique for Identification of Bile Salt Hydrolase Positive Lactobacilli

In the burgeoning landscape of probiotic research, the intricate interplay between the gut microbiota and host health has underscored the significance of specific enzymatic activities, notably bile salt hydrolase (BSH) produced by Lactobacilli. Harnessing the potential health benefits associated with BSH activity necessitates a meticulous identification strategy. In response, this study introduces a sophisticated PCR-based technique tailored for the rapid and precise discrimination of lactobacilli strains boasting BSH enzymatic prowess. This PCR-based approach offers a valuable tool for researchers and industry professionals involved in the selection and characterization of probiotic strains with bile salt hydrolase activity. Its speed, accuracy, and adaptability make it a promising method for large-scale screenings and applications in diverse fields, ranging from food science to the development of probiotic supplements aimed at enhancing human health through the modulation of bile acid metabolism. robiotic supplementation, where the modulation of bile acid metabolism holds promise for promoting human health and well-being.

The Effect of Price Transparency on Young Travellers’ Choices: An Experimental Study of Resort Packages

Product bundling has gained significant traction in the hospitality industry, with an increasing number of businesses offering all-inclusive resort packages to attract consumers. With the increase in online travel purchases, both academics and industry professionals are increasingly interested in understanding the factors influencing consumer travel package choices. This study employs a 2 x 5 mixed-design experiment where participants evaluated both an all-inclusive and a non-inclusive resort, with variations in price presentation. Pricing was presented either transparently or non-transparently, and package savings were displayed in multiple formats. The results reveal a strong consumer preference for all-inclusive resort packages, regardless of the perceived value. Moreover, how pricing information is presented plays a crucial role in shaping consumer purchase decisions. These findings highlight the importance of price presentation strategies in the marketing of travel packages and offer valuable insights for both marketers and practitioners in the hospitality sector.

Advances in Emerging Non-Destructive Technologies for Detecting Raw Egg Freshness: A Comprehensive Review

Eggs are a rich food source of proteins, fats, vitamins, minerals, and other nutrients. However, the egg industry faces some challenges such as microbial invasion due to environmental factors, leading to damage and reduced usability. Therefore, detecting the freshness of raw eggs using various technologies, including traditional and non-destructive methods, can overcome these challenges. As the traditional methods of assessing egg freshness are often subjective and time-consuming, modern non-destructive technologies, including near-infrared (NIR) spectroscopy, Raman spectroscopy, fluorescence spectroscopy, computer vision (color imaging), hyperspectral imaging, electronic noses, and nuclear magnetic resonance, have offered objective and rapid results to address these limitations. The current review summarizes and discusses the recent advances and developments in applying non-destructive technologies for detecting raw egg freshness. Some of these technologies such as NIR spectroscopy, computer vision, and hyperspectral imaging have achieved an accuracy of more than 96% in detecting egg freshness. Therefore, this review provides an overview of the current trends in the state-of-the-art non-destructive technologies recently utilized in detecting the freshness of raw eggs. This review can contribute significantly to the field of emerging technologies in this research track and pique the interests of both food scientists and industry professionals.

Modelling Motor Insurance Claims Using Arma Model And Appropriate Statistical Distribution Of Insurance Companies, Machakos County, Kenya

The prediction of future claim amounts based on past or present claims is a challenging task for insurance companies. According to research carried out by Michael Barth and David L. Eccles (2009); claim costs constitute large proportion of insurers expenses in evaluating the premium growth on the loss ratio of property causality insurers. Various statistical techniques have been employed to analyze claims data and assess its impact on productivity. Autoregressive (AR), Moving Average (MA), and Auto Regressive Moving Average (ARMA) processes are commonly used to model the temporal dependencies and trends in the data. These techniques enable insurance companies to understand the dynamics of claim incidence and their effects on productivity over time (Philip J, 2016). Advanced modeling techniques such as generalized additive models, negative binomial regression, and multinomial logit models have been used to evaluate claims processes, predict claim occurrence, and model claim severity (Renshaw A.E, 1994; Edward. W Frees et al., 2008; Daiane Aparecida Zanetti et al., 2006). These models consider various factors such as driver age, gender, vehicle type, and no claim discount to assess their impact on claim incidence and productivity. Previous studies have overlooked the comprehensive examination of the impact of insurance claims on productivity on insurance companies. Therefore, this research aims to address this gap by investigating the factors associated with insurance motor claims and their effects on the productivity of insurance companies by employing statistical techniques like appropriate probability distribution, incorporation of moving average technique, Autoregressive process and ARMA process, as identified by industry professionals and experts. The results obtained from the real-life data for distinctive 11 years indicated the potential strength of ARMA models to provide insurance company's claim amount prediction that could assist the companies to have better planning. The findings of this study, if adopted by various keynote players in the insurance and regulatory sectors, can be highly beneficial in formulating appropriate policies to enhance the management of motor insurance claims and improve the productivity of insurance companies.

Transformative Impact of AI and Cloud Technologies: A Comparative Analysis across Healthcare, Retail, and Mobile Financial Services

This article examines the transformative impact of artificial intelligence (AI) and cloud technologies across healthcare, retail, and mobile financial services sectors. Through a comprehensive analysis of industry-specific applications, we explore how these technologies are revolutionizing operational efficiency, customer experiences, and innovation in each domain. In healthcare, we investigate the role of CI/CD automation and scalable cloud infrastructure in improving system reliability and patient care. The retail sector analysis focuses on AI-driven customer insights and supply chain optimization. For mobile financial services, we examine AI applications in fraud detection and real-time analytics. The findings reveal significant improvements in operational efficiency, decision-making processes, and customer satisfaction across all three industries. However, we also identify unique challenges and opportunities specific to each sector. This article contributes to the growing body of literature on digital transformation and provides valuable insights for industry professionals and policymakers navigating the integration of AI and cloud technologies in their respective fields.

Modeling noisy learning in a dynamic oligopoly experiment

Estimating demand before production poses a significant challenge for many industries, including vaccine manufacturing, newspapers, and perishable foods. Both industry professionals and experimental subjects in laboratory settings often struggle to determine optimal production. This paper sheds light on the cognitive processes that explain individuals' inability to act optimally, using data from Nagel and Vriend (1999a,b). In their experiment, participants, acting as firms, set production levels without prior knowledge of the demand generated by own and competitors' advertising efforts. We first reexamine their two-step learning model, which involves directional learning for production levels and a hill-climbing algorithm for advertising, utilizing exogenous adjustment size distributions. We improve upon this model, inspired by the macroeconomic learning literature, with agents using constant gain learning for production decisions and hill climbing for advertising decisions with endogenous adjustments. We demonstrate that our model provides a better fit to the data than the original model by Nagel and Vriend (1999a) and yields superior out-of-sample forecasts, both for one-period-ahead predictions and simulated paths.

Preface

The 2nd International Symposium on Frontiers of Mechanical and Material Engineering (MME2024) is a globally recognized event to be organized by the Hubei Digital Textile Equipment Key Laboratory, China, in collaboration with the Wuhan Textile University, China, Zhongnan University, East-Siberian State University of Technology and Management, Russia, Rongzhi Sciences and Technology Center, China, was held from 21-22 September 2024 in Hangzhou, China. Since its inception in 2014, MME has successfully encompassed a wide spectrum of cuttingedge research domains, developed into a premier international event held in China and which gathered the best scientists and world class experts to share leading edge and multidisciplinary research in various fields related to mechanical engineering, materials science and modern technologies. MME serves as a prestigious international platform, this conference will continue to facilitate the dissemination of cutting-edge advancements across a spectrum of disciplines, converge students, experts, researchers, scholars, and industry professionals from different nations to share and deliberate on their latest work. This volume comprises select proceedings of 18 papers from 56 contributions submitted to MME2024. All the papers underwent a meticulous peer-review process, with each paper being evaluated by at least one expert in the relevant field. It introduces latest advancements in the subjects of mechanical engineering, materials science and advanced manufacturing technology, et al. It will be beneficial for readers from both academia and industry to understand and tackle the challenges in an efficient manner and to adopt appropriate solutions in the mentioned fields above. We would like to extend our heartfelt gratitude to invited keynote speakers: Dr. Valeriy Buryachenko, Micromechanics & Composites LLC, Cincinnati, Ohio, USA; Prof. David BASSIR, French University of Technology UTBM, France; Prof. Raul Duarte Salgueiral Gomes Campilho, Department of Mechanical Engineering, ISEP - School of Engineering, Portugal, and Dr. Ghulam Yasin, Oxford Brookes University, UK, for their brilliant speeches. Thanks to all the international reviewers and program committee members for their valuable contributions and dedication. List of Conference Chair, Conference Co-Chair, Honorary Chair, Editors and Technical Program Committees are available in this Pdf.

DigiChemTree enables programmable light-induced carbene generation for on demand chemical synthesis

The reproducibility of chemical reactions, when obtaining protocols from literature or databases, is highly challenging for academicians, industry professionals and even now for the machine learning process. To synthesize the organic molecule under the photochemical condition, several years for the reaction optimization, highly skilled manpower, long reaction time etc. are needed, resulting in non-affordability and slow down the research and development. Herein, we have introduced the DigiChemTree backed with the artificial intelligence to auto-optimize the photochemical reaction parameter and synthesizing the on demand library of the molecules in fast manner. Newly, auto-generated digital code was further tested for the late stage functionalization of the various active pharmaceutical ingredient.

Ready, Set, Modernize – ASPRS Takes on Preparing the Geospatial Industry for the Modernized National Spatial Reference System (NSRS)

The National Geodetic Survey (NGS) is modernizing the National Spatial Reference System (NSRS) in the United States. The modernization involves significant updates to the official reference frames and vertical datum used across the country, affecting the entire geospatial industry. Key benefits of the Modernized NSRS will include improved accuracies and enhanced interoperability and sustainability of geospatial data and systems. The ASPRS NSRS Modernization Working Group produced this paper to help prepare the geospatial industry for the upcoming changes. It serves as a guide for industry professionals to understand the implications of the Modernized NSRS and recommendations to begin preparing for it. It emphasizes the importance of proactive measures to ensure a smooth transition to the new reference frames and vertical datum.

Lead-Free Halide Double Perovskites for Sustainable Environmental Applications

The development of renewable energy sources has become a crucial objective in today's world due to increasing environmental concerns and the depletion of fossil fuels. Solar energy has emerged as a promising alternative. In recent years, there has been a significant focus on perovskite solar cells due to their remarkable power conversion efficiencies and their ability to be produced in a cost-effective manner. These cells have attracted considerable attention from researchers and industry professionals alike. However, traditional perovskite materials often contain toxic lead, raising concerns about their environmental impact and long-term sustainability. This article highlights the environmental concerns associated with lead-based perovskite materials and explores the advantages, challenges, and potential of lead-free halide double perovskites as sustainable alternatives for achieving an enlightening and sustainable future in the field of photovoltaics. Lead-free halide perovskites have been an area of active research in the field of nanotechnology and material science due to their potential for various applications. We provide an overview of perovskite solar cells as a promising technology, discussing their material properties and device performance. Furthermore, we present a comparative analysis between lead-based and lead-free perovskites, emphasizing the challenges and future perspectives associated with the development and implementation of lead-free alternatives. Through this analysis, we aim to shed light on the potential of lead-free halide double perovskites and inspire further research in the quest for environmentally friendly materials for solar energy applications.

Financial Statement Audits and Data Breaches

Financial statement audits for public companies require auditors to test the internal controls over the client’s information systems that are material to the financial reporting process. Given the increasingly integrated nature of corporate data and control systems, a standard audit may have a positive effect on client firms’ other information systems, such as those that help prevent data breaches. In this paper, I provide evidence on whether and how auditors help prevent data breaches. Using plausibly exogenous improvements in auditing due to regulatory inspections and auditors’ cross-client learning, I find a decreased likelihood of data breaches among these auditors’ clients. Institutional insights gathered from interviews with accounting firm partners and industry professionals suggest two mechanisms for the role of auditors in preventing data breaches: the provision of relevant information and incentives for internal controls. Collectively, the findings provide evidence that improving accounting information systems can have a positive impact on nonaccounting systems. This paper was accepted by Ranjani Krishnan, accounting. Funding: I gratefully acknowledge financial support from Columbia Business School, the University of Chicago Booth School of Business, the Deloitte Foundation, and the Bradley Fellowship awarded by the Stigler Center for the Study of the Economy and the State. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.01357 .

Use of Nanotechnology in Cosmetics and Cosmeceuticals

Nanotechnology has revolutionized the cosmetic and cosmeceutical industries by enhancing product efficacy and enabling innovative formulations. This review paper delves into the various applications of nanotechnology in skincare and cosmetic products, highlighting its ability to improve the delivery of active ingredients, provide enhanced protection, and increase the bioavailability of beneficial compounds. Nanomaterials such as liposomes, nanoemulsions, nanocapsules, and solid lipid nanoparticles are now extensively utilized for their superior skin penetration capabilities, ensuring targeted delivery and prolonged effects. The paper explores the potential benefits and safety concerns associated with these nano-based cosmetic products. It also provides a comprehensive analysis of recent advancements, regulatory considerations, and future trends in the field, emphasizing the need for further research to fully understand the long-term implications of nanotechnology in cosmetics and cosmeceuticals. This review aims to provide a critical overview for researchers and industry professionals interested in the evolving landscape of nanotechnology in beauty and skincare. Findings Our research highlights the transformative impact of Artificial Intelligence (AI) and Machine Learning (ML) on the drug discovery and development process, particularly in enhancing efficiency and precision from initial screening to clinical trials. The integration of AI/ML has shown significant advancements in early-stage drug discovery, where data-driven algorithms enable rapid identification of potential drug candidates, reducing reliance on traditional, labor-intensive methods. In the drug design and optimization phase, AI-driven predictive models have streamlined the process, minimizing the need for extensive physical testing by accurately simulating drug interactions and predicting possible side effects. Additionally, AI and ML are revolutionizing clinical trials by optimizing trial design, improving patient recruitment and retention, and enhancing real-time data monitoring, leading to faster and more reliable trial outcomes. These technologies also support personalized medicine approaches and have proven essential in reducing both the time and cost associated with bringing new therapies to market. Overall, our findings underscore the critical role of AI and ML in reshaping the pharmaceutical landscape, making drug development faster, more cost-effective, and ultimately, more successful in delivering effective treatments to patients.

Reimagining sustainability: The power of AI and intellectual capital in shaping the future of tourism and hospitality organizations

This research investigates the effect of artificial intelligence (AI) on organizational sustainability (OS) and delves into how this relationship is mediated by various dimensions of intellectual capital (IC), namely human (HC), structural (SC), and relational capital (RC). Data were collected from employees of Saudi travel agencies, resulting in 1122 valid responses, which were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that AI positively impacts OS as well as the three IC dimensions. Additionally, HC, SC, and RC have a positive influence on OS. The study also reveals that these dimensions partially mediate the relationship between AI and OS. This study advances the literature by clarifying how AI-enabled capabilities are translated into sustainable outcomes within the tourism and hospitality sectors. The findings offer valuable insights for industry professionals aiming to harness AI technologies for sustainable transformation. The study also offers strategic recommendations for tourism and hospitality organizations to invest in enhancing their IC, thereby optimizing the sustainability advantages of AI integration.

Construction 5.0 and Sustainable Neuro-Responsive Habitats: Integrating the Brain–Computer Interface and Building Information Modeling in Smart Residential Spaces

This study takes a unique approach by investigating the integration of Brain–Computer Interfaces (BCIs) and Building Information Modeling (BIM) within residential architecture. It explores their combined potential to foster neuro-responsive, sustainable environments within the framework of Construction 5.0. The methodological approach involves real-time BCI data and subjective evaluations of occupants’ experiences to elucidate cognitive and emotional states. These data inform BIM-driven alterations that facilitate adaptable, customized, and sustainability-oriented architectural solutions. The results highlight the ability of BCI–BIM integration to create dynamic, occupant-responsive environments that enhance well-being, promote energy efficiency, and minimize environmental impact. The primary contribution of this work is the demonstration of the viability of neuro-responsive architecture, wherein cognitive input from Brain–Computer Interfaces enables real-time modifications to architectural designs. This technique enhances built environments’ flexibility and user-centered quality by integrating occupant preferences and mental states into the design process. Furthermore, integrating BCI and BIM technologies has significant implications for advancing sustainability and facilitating the design of energy-efficient and ecologically responsible residential areas. The study offers practical insights for architects, engineers, and construction professionals, providing a method for implementing BCI–BIM systems to enhance user experience and promote sustainable design practices. The research examines ethical issues concerning privacy, data security, and informed permission, ensuring these technologies adhere to moral and legal requirements. The study underscores the transformational potential of BCI–BIM integration while acknowledging challenges related to data interoperability, integrity, and scalability. As a result, ongoing innovation and rigorous ethical supervision are crucial for effectively implementing these technologies. The findings provide practical insights for architects, engineers, and industry professionals, offering a roadmap for developing intelligent and ethically sound design practices.

Evolving trends, limitations, and ethical considerations in AI-driven conversational interfaces: assessing ChatGPT's impact on healthcare, financial services, and educational sectors

ABSTRACT This study presents a comprehensive bibliometric analysis of ChatGPT's impact on three critical sectors: healthcare, financial services, and education, covering the period from 2022 to 2024. The research aimed to explore the evolving trends, limitations, and ethical considerations associated with the deployment of ChatGPT and similar AI-driven conversational interfaces. The findings reveal that while ChatGPT offers significant potential in enhancing efficiency and decision-making processes, it also faces substantial challenges in data privacy, integration with existing systems, and the need for improved emotional intelligence. The study highlights the inherent biases in AI models, raising concerns about the accuracy and fairness of AI-driven outputs. Ethical considerations, including data privacy, transparency, accountability, and equity in AI applications, are identified as crucial areas requiring urgent attention and development. Additionally, the research underscores the importance of developing robust regulatory frameworks and ethical guidelines to govern AI deployment in these sectors. Successful integration of ChatGPT and similar technologies depends on addressing these challenges and ethical considerations through collaborative efforts among AI developers, industry professionals, policymakers, and ethicists. Future research should focus on improving AI's data security, emotional intelligence, bias reduction, human-AI collaboration, and assessing long-term impacts across diverse settings.

Measuring palatability of pet food products: Sensory components, evaluations, challenges, and opportunities.

The pet food industry is a growing business launching a variety of new products in the market. The acceptability or preference of pet food samples has traditionally been measured using either one-bowl or two-bowl tests. Academic researchers and professionals in the pet food industry have explored other methods, including the cognitive palatability assessment protocols and the ranking test, to evaluate more than two samples. A variety of approaches and perspectives were also utilized to predict palatability and key sensory attributes of pet foods, including descriptive sensory analysis by human-trained panelists and pet food caregivers' perceptions of pet food. This review article examined a range of testing methods for evaluating the palatability of pet foods, specifically targeting products for dogs and/or cats. It outlined the advantages and disadvantages of each method. Additionally, the review provided in-depth insights into the key sensory attributes of pet foods and the methodologies for assessing palatability. It also explored pets' behavioral responses and facial expressions in relation to different pet foods. Furthermore, this review discussed current challenges and future opportunities in pet food development, including the use of instrumental analyses and artificial intelligence-based approaches.

Conclusion: addressing the labor shortage problem in the hospitality and tourism industries

PurposeThe main objective of this theme issue is to investigate the potential of cutting-edge technologies like AI, robotics and other innovative solutions to mitigate the skilled labor shortage crisis in the Hospitality and tourism (H&T) industries.Design/methodology/approachThis conclusion draws upon the collective insights from the articles in this thematic issue, providing a comprehensive overview of the key findings and their implications. A thorough analysis and discussion of the results are presented, offering a synthesis of the research and its significance for the hospitality and tourism industry.FindingsThis thematic issue examines the profound impact of automation and artificial intelligence on the tourism and hospitality industries, where advancements in technology are juxtaposed with the challenge of skill shortages. The special issue explores the application of AI and automation in operations, training and development as well as the need for a balanced approach to innovation and service delivery standards. As AI transforms the industry, this issue highlights the imperative for hotels and similar establishments to strike a delicate balance between technological innovation and preserving exceptional guest experiences.Originality/valueThis theme issue presents a comprehensive analysis of the key discussions on the strategic use of technology in the hospitality and tourism industries. The articles demonstrate the significance of these advancements in expanding our knowledge and driving innovation, ultimately benefiting various stakeholders in the sector. As these technologies continue to evolve at a rapid pace, it is crucial for industry professionals, decision-makers and researchers to understand their applications, benefits and challenges in order to effectively address the pressing issue of labor shortages in the hospitality and tourism industries.

Rail Detection Research Status of Multi -Sensing Technology

Traditional rail inspection methods, primarily relying on manual inspection and basic equipment, face significant challenges including low efficiency, poor accuracy, and susceptibility to human error. This paper presents a comprehensive review of the current research status and future trends in multi-sensor rail transit inspection vehicles. The focus is on the integrated application of various sensing technologies, particularly inertial systems and visual sensing, to achieve high-precision and efficient measurement of rail geometrical parameters. An in-depth analysis of key technologies and challenges in railway track inspection is provided, exploring how advanced sensing methods can overcome the limitations of traditional approaches. The paper also examines the market prospects for rail transit inspection, highlighting the growing demand for more sophisticated and reliable inspection systems. Furthermore, potential future research directions in this field are outlined, including the development of AI-powered data analysis, real-time defect detection algorithms, and the integration of emerging technologies such as LiDAR and thermal imaging. This review aims to provide valuable insights for researchers, engineers, and industry professionals working on advancing rail inspection technologies.

Genuine small talk, rapport, and negotiation outcomes in B2B relationship

Purpose Small talk is often regarded as important in business interactions, yet the effect of genuine engagement on B2B communication remains underexplored. Hence, the purpose of this study is to explore the concept of genuine small talk, contextualize its key dimensions and examine how it contributes to building rapport and mediates negotiation outcomes in B2B relationships. Design/methodology/approach This study uses a qualitative abductive research approach for this exploratory investigation as it allows for an in-depth examination of the complex relational dynamics inherent in B2B communication. Data were collected through semistructured interviews with 35 industry professionals from diverse sectors, ensuring a diverse understanding of the phenomenon across different B2B contexts. Findings The study identifies eight core dimensions of genuine small talk in B2B interactions: empathy, curiosity, adaptability, active listening, a nonjudgmental disposition, respect for boundaries, positivity and humility. These dimensions collectively contribute to the development of rapport. The findings also highlight that rapport, fostered through genuine small talk, plays a mediating role in achieving favorable negotiation outcomes. Originality/value This study adds to the B2B marketing literature by advancing the understanding of genuine small talk and its strategic importance in building rapport and improving negotiation outcomes.

A Narrative Review of Identity, Data and Location Privacy Techniques in Edge Computing and Mobile Crowdsourcing

As digital technology advances, the proliferation of connected devices poses significant challenges and opportunities in mobile crowdsourcing and edge computing. This narrative review focuses on the need for privacy protection in these fields, emphasizing the increasing importance of data security in a data-driven world. Through an analysis of contemporary academic literature, this review provides an understanding of the current trends and privacy concerns in mobile crowdsourcing and edge computing. We present insights and highlight advancements in privacy-preserving techniques, addressing identity, data, and location privacy. This review also discusses the potential directions that can be useful resources for researchers, industry professionals, and policymakers.