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The field of library and information sciences (LIS) is crucial to our educational system. Across the globe, the LIS systems operate at varying levels and rates of efficiency. One of the developing nations is Pakistan, which has LIS systems in all of its colleges, universities and schools. This multimethod study aims to identify and quantify elements that are detrimental to LIS progress as well as evaluate the faculty and infrastructure profiles of universities that offer LIS undergraduate and graduate level programmes.

Data was collected from the study's participants, who were mainly LIS professionals and faculty at 17 different universities, using survey questionnaires and in-person interviews. This study used a descriptive survey methodology, gathering information through a Google Survey and filling it out with a premade survey proforma. The survey responses were examined using content analysis. The development of LIS instructional and scholarly output is influenced by a variety of factors, which were investigated using a generalized linear model (GLM). To determine whether there was a statistically significant difference in opinion between faculty members and working professionals, as well as between men and women, the outcomes of an independent sample t-test were examined.

According to our data, the factors that have the biggest impact on the caliber and output of LIS research are “poor writing skills” (3.43), “lack of journal publication fees” (3.51) and “lack of research skills” (3.78). The top GLM model identified poor writing skills, a lack of publication fees and a lack of research expertise as bottleneck characteristics for producing high-quality LIS research. The aforementioned factors were 3.62, 2.41 and 2.19 times more significant than the average factor, respectively, to put it another way.

This study’s analysis revealed that there is no real distinction between the two groups' viewpoints. The results of this study can be applied to problems and challenges associated with LIS education in Pakistani educational institutions.

This paper aims to explore recent advances in drift compensation algorithms for Electronic Nose (E-nose) technology and addresses sensor drift challenges through offline, online and neural network-based strategies. It offers a comprehensive review and covers causes of drift, compensation methods and future directions. This synthesis provides insights for enhancing the reliability and effectiveness of E-nose systems in drift issues.

The article adopts a comprehensive approach and systematically explores the causes of sensor drift in E-nose systems and proposes various compensation strategies. It covers both offline and online compensation methods, as well as neural network-based approaches, and provides a holistic view of the available techniques.

The article provides a comprehensive overview of drift compensation algorithms for E-nose technology and consolidates recent research insights. It addresses challenges like sensor calibration and algorithm complexity, while discussing future directions. Readers gain an understanding of the current state-of-the-art and emerging trends in electronic olfaction.

This article presents a comprehensive review of the latest advancements in drift compensation algorithms for electronic nose technology and covers the causes of drift, offline drift compensation algorithms, online drift compensation algorithms and neural network drift compensation algorithms. The article also summarizes and discusses the current challenges and future directions of drift compensation algorithms in electronic nose systems.

The purpose of this paper is to study the relationship between high temperature oxidation and temperature rise rate of engine oil attempted to explore a new indicator to evaluate oil degradation.

Accelerated oxidation test combined with molecular simulation and road test is carried out in this paper. The temperature rise characteristics of mineral oil and synthetic oil under different oxidation temperatures (140°C, 155°C and 170°C) and time (50 h, 100 h, 150 h and 200 h) were determined by accelerated oxidation. The mechanism of temperature change characteristics of used oils was analyzed with molecular simulation. Two experimental vehicles carried six road tests with synthetic and mineral oil.

The results of this study show that the temperature rise rate of oxidized mineral and synthetic oil is higher than the new oil. The temperature rise rate is proportional to the oxidation time and oxidation temperature. The synthetic engine oil temperature rise rate is lower than that of the mineral engine oil. The same result was obtained in road tests. Molecular simulation verifies that small molecules were generated after oil oxidation which results in intermolecular friction and increased heat generation.

This paper indicates that temperature rise rate has potential to be taken as an indicator to evaluate oil oxidation which provides a new way for engine oil analysis.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0177/

With the rapid growth of the gig economy worldwide, gig workers’ perceived algorithmic control has been proven to have a crucial impact on the service performance, well-being and mental health of gig workers. However, the literature suggests that gig workers’ perceived algorithmic control may be a double-edged sword. The purpose of this research is to explore how the perceived algorithmic control of gig workers can accelerate thriving at work.

Based on the model of proactive motivation and work design literature, a three-wave survey was employed, yielding 281 completed responses. The structural equation modeling method was used to test the theoretical hypothesis.

The results indicate that gig workers’ perceived algorithmic control has positive and indirect effects on thriving at work through the mediating role of job crafting. In addition, job autonomy can moderate the mediated relationship; specifically, when job autonomy is high, this mediated relationship will be stronger.

The health and well-being of gig workers is a concern around the world. The findings provide insights for service platform enterprises and gig workers.

Perceived algorithmic control is critical to mental health and positive work experiences during a gig worker’s service process. However, the current literature focuses more on the negative aspects of algorithmic control. This paper provides a comprehensive research agenda for how to accelerate thriving at work for gig workers.

The application of galvanized steel is widespread across industries due to its protective zinc coating that protects against atmospheric corrosion. However, previous studies have primarily focused on long-term corrosion rates rather than the full-scale corrosion behavior of the zinc. This paper aims to study the full-scale corrosion evolution of galvanic steel under simulated marine atmospheric environment using real-time EIS measurement.

Electrochemical impedance spectroscopy (EIS) provides an advanced method in monitoring such behavior. Therefore, the EIS method has been used to conduct a comprehensive investigation on the corrosion behavior of galvanic steel in a full-time manner.

The results indicate that the corrosion process of galvanic steel can be divided into three stages: an initial stage with an increased corrosion rate, a subsequent stage with a reduced corrosion rate, and finally a third stage with the lowest and constant corrosion rate. The evolution of corrosion resistance is closely related to changes in composition and structure of the patina layer. In the initial stage, galvanized steel undergoes the formation of soluble ZnCl₂ and needle-like Zn₅(OH)₈Cl₂·H₂O, which promotes the generation and maintenance of an electrolyte layer, consequently leading to an increase in corrosion rate. With prolonged corrosion time, there is a continuous accumulation of Zn₅(OH)₈Cl₂·H₂O within the patina layer, which reduces the content of soluble components and promotes the development of a denser inner layer, thus enhancing corrosion resistance.

This work holds significance in the monitoring of corrosion, understanding the evolution of corrosion and predicting the lifespan of galvanized steel.

With the development of digitalization and interconnection, there is a growing need for enterprise customers to ensure the compatibility of the third-party components they are using in the manufacturing process, thus raising the integration requirements for the Industrial Internet platform and its third-party developers. Therefore, our study investigates the optimal integration decision of the Industrial Internet platform while considering its access price, the integration cost, and the net utility derived by enterprise customers from the third-party components.

We model a two-sided Industrial Internet platform that connects customers on the demand side to the developers on the supply side. We then explore the integration decision of the Industrial Internet platform and its important factors by solving the optimal profit function.

First, despite the high integration cost of third-party developers, the platform still chooses to integrate when enterprise customers derive high utility from the third-party components. Second, due to the compatibility effect, charging the enterprise customers a higher price may reduce the platform profits when these customers derive low utility from the third-party components. Third, the platform profits will increase along with the integration cost of third-party developers when it is low in the case where enterprise customers derive low utility from third-party components.

Our findings offer insightful takeaways for the Industrial Internet platform when making integration decisions.

While oft-ignored, grievances remain a central part of revolutions. We argue that the theorization of grievances requires conceptually unpacking specific complaints and relating them to mobilizing mechanisms. We thus focus on one set of grievances – corruption – that is especially prevalent in 21st century revolutionary episodes. Drawing on prior conceptualizations of corruption, we hypothesize that four different configurations of corruption influence five different mechanisms of contention. First, everyday street-level corruption creates the potential for sudden and spontaneous protest and creates the basis for widespread, coalitional mobilization. Second, institutional corruption focuses attention on the regime to make it a target of revolutionary claims. Third, competition among elites creates the potential for cross-class alliances but may forestall durable sociopolitical change and, in some cases, even allow for authoritarian consolidation of power through anti-corruption drives. We illustrate these dynamics through one clearly successful case of revolution in Tunisia in 2011, one case of mixed results from political revolution in Ukraine from 2004 to 2014, and a negative case of revolution in China since 2013.

In recent years, cost overrun becomes a common problem in steel building construction projects. The average percentage can vary widely depending on the project type, size, complexity and location. The steel structure change ratio in Taiwan is from 1 to 18% in statistics. The contractors always put every possible effort into preventing or mitigating project cost overruns, and one of the approaches is an accurate cost overrun risk estimate. Traditional project cost overrun risk assessment models mainly focus on macro-level evaluation and may not function well for the project-specific level (micro-level). This study creates a network-like connection model between the outcome (i.e. cost overrun risk) and the associated root causes in which the project status evaluation checklists of design, manufacturing, construction and interfaces are used to evaluate the checklists' influences through the Bayesian network (BN) composed by intermediate causes.

Due to the constraint of data availability, BN nodes, relationships and conditional probabilities are defined to establish a BN-based steel building project cost overrun assessment model following the knowledge of experts. Because of the complexity of the BN, the construction of the BN structure is first to build BN's fault tree (FT) hierarchy. And then, basic BN framework is constructed by the transformation of the FT hierarchy. Furthermore, some worthwhile additional arcs among BN nodes are inserted if necessary. Furthermore, conditional probability tables (CPTs) among BN nodes are explored by experts following the concept of the ranked node. Finally, the BN-based model was validated against the final cost analysis reports of 15 steel building projects done in Taiwan and both were highly consistent. The overall BN-based model construction process consists of three steps: (1) FT construction and BN framework transformation, (2) CPT computation and (3) model validation.

This study established a network-like bridge model between the outcome (i.e. cost overrun risk) and the root causes in a network of which cost influences are evaluated through the project-specific status evaluation checklists of design, manufacturing, construction and interfaces. This study overcame several limitations of the previous cost overrun risk assessment models: (1) few past research support assessment of cost overrun based on real-time project-owned data and (2) the traditional causal models inadequately depict interdependencies among influence factors of cost overrun at the network. The main influence factors of the cost overrun risk at the steel building projects in Taiwan were also examined using sensitivity analysis. The main root causes of cost overrun in steel building projects are design management and interface integration.

The proposed model belongs to the project-specific causal assessment model using real-time project-owned status checklist data as input. Such a model was seldom surveyed in the past due to the complicated interdependence among causes in the network. For practical use, a convenient and simple regression equation was also developed to forecast the cost overrun risk of the steel building project based on the root causes as input. Based on the analysis of cost overrun risk and significant influence factors, proper tailor-made preventive strategies are established to reduce the occurrence of cost overrun at the project.

Emerging from the COVID-19 pandemic, the Philippines has undergone the “new normal” transition, creating a strategic recovery effort to reinvigorate the industry. In tourism, these transitions aim to safeguard employees' and guests' health and safety, ensure continuity of business operations, boost tourism confidence leading to satisfaction, and establish a resilient and sustainable tourism industry in the postpandemic era. Hence, this chapter employs a system thinking leveraging a causal loop diagram (CLD) to construct a comprehensive roadmap for Philippine tourism's postpandemic resurgence through the system thinking lens. The CLD visually illustrates the inter-related factors influencing the recovery process, encompassing collaborative engagements, innovations, economic revitalization, and health and safety protocols. By analyzing the causal relationships among these variables, this chapter explicates the dynamic and interconnected nature of the postpandemic recovery leading to the recovery of the Philippine tourism industry, especially in the context of thinking small. Through this chapter, thinking small could involve a shift toward localized solutions and community-focused initiatives that allow them to foster local economies, build resilience, and create a more inclusive and sustainable postpandemic recovery.

This paper aims to fabricate a polymer-based polyethylene glycol (PEG) coating with acrylic resin as a binder that can show antiviral activity against the feline coronavirus (FCov) on the glass substrate.

The PEG/acrylic coating systems of different weight percentages were coated on the glass substrates using the spray-coating method and cured at room temperature for 24 h.

The coating system containing 20 Wt.% of PEG exhibits the highest antiviral activities as high as 99.9% against FCov compared with other samples.

Findings will be useful in the development of antiviral coating for PPE fabrics by using the simple synthesis method.

Application of PEG as an antiviral agent in the antiviral coating system with high antiviral activities about 99.9%.