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Powder bed fusion-laser beam (PBF-LB) is a rapidly growing manufacturing technology for producing Al-Si alloys. This technology can be used to produce high-pressure die-casting (HPDC) prototypes. The purpose of this paper is to understand the similarities and differences in the microstructures and properties of PBF-LB and HPDC alloys.

PBF-LB AlSi10Mg and HPDC AlSi10Mn plates with different thicknesses were manufactured. Iso-thermal heat treatment was conducted on PBF-LB bending plates. A detailed meso-micro-nanostructure analysis was performed. Tensile, bending and microhardness tests were conducted on both alloys.

The PBF-LB skin was highly textured and softer than its core, opposite to what is observed in the HPDC alloy. Increasing sample thickness increased the bulk strength for the PBF-LB alloy, contrasting with the decrease for the HPDC alloy. In addition, the tolerance to fracture initiation during bending deformation is greater for the HPDC material, probably due to its stronger skin region.

This knowledge is crucial to understand how geometry of parts may affect the properties of PBF-LB components. In particular, understanding the role of geometry is important when using PBF-LB as a HPDC prototype.

This is the first comprehensive meso-micro-nanostructure comparison of both PBF-LB and HPDC alloys from the millimetre to nanometre scale reported to date that also considers variations in the skin versus core microstructure and mechanical properties.

This study aims to explore the impact of artificial intelligence-powered personalised recommendations (AI-PPRs) on user engagement, browsing behaviour and purchase intentions on TikTok (Douyin in China), focusing on how these recommendations affect user satisfaction and purchase intention, while also addressing potential privacy concerns. In addition, the research investigates the influence of AI-recommended product presentation, timing and placement, as well as social factors such as key opinion leaders’ (KOLs) influence on consumer decision-making.

Using the expectancy-value theory and the stimulus-organism-response model, this research used a qualitative methodology through interviews with Douyin users to explore their experiences and perceptions of AI-PPRs.

The findings indicate that Douyin’s proactive “push” mechanism of AI-PPRs enhances user engagement by effortlessly integrating product discovery into the entertainment experience. Content-driven AI-PPRs align with user preferences, decrease search time and increase satisfaction and purchase intentions through engaging short videos and live streaming. However, privacy concerns emerge when personalisation is perceived as excessively intrusive, leading to negative emotions and avoidance behaviours. Recommendation timing and cultural context significantly influence receptiveness, with inappropriate timing (e.g. during holidays) causing negative reactions. Technical challenges, such as network issues during live streaming, negatively impact user experience and engagement. Content quality is crucial, and poor or irrelevant content leads to negative perceptions and disengagement. While KOLs face scepticism due to perceived commercialisation, endorsements from trusted figures and authentic influencers are better received. Innovative payment methods, like “Douyin Monthly Payment”, enhance financial flexibility and promote customer loyalty. This study highlights the need to balance personalisation with privacy, emphasising the importance of content quality and authenticity in influencer marketing. For businesses using AI-PPRs, maintaining this balance is essential for preserving trust and sustaining consumer engagement and loyalty.

This study contributes valuable insights to the field by unravelling the intricate dynamics between AI-PPRs, user preferences and social influences. The findings provide practical implications for companies aiming to optimise personalised recommendation algorithms and enhance user engagement, thereby facilitating business growth in the dynamic short video e-commerce market.

The purpose of this paper is to propose an approach, which is easy to implement, for estimating the thickness of the air layer that may separate metallic parts in some aeronautical assemblies, by using the eddy current method.

Based on an experimental study of the coupling of a magnetic cup core coil sensor with a metallic layered structure (consisting of first metal layer/air layer/second metal layer), which is confirmed by finite element modelling simulations, an inversion technique relying on a polynomial forward model of the coupling is proposed to estimate the air layer thickness. The least squares and the nonnegative least squares algorithms are applied and analysed to obtain the estimation results.

The choice of an appropriate inversion technique to optimize the estimation results is dependent on the signal-to-noise ratio of measured data. The obtained estimation error is smaller than a few percent, for both simulated and experimental data. The proposed approach can be used to estimate both the air layer thickness and the second metal layer thickness simultaneously/separately.

This model-based approach is easy to implement and available to all types of eddy current sensors.

There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.

Monocytes are a leukocytes’ subset that plays an important role in immunity. Protein kinase B (AKT) is involved in monocytes' survival, proliferation and differentiation. Using phorbol 12-myristate 13-acetate (PMA) as an inducer for cell line U937 differentiation into macrophage-like cells may be used as a model for cancer cell therapy or other biomedical research studies. The authors investigated the Akt1 signaling pathway's involvement with PMA as a differentiating agent and survival in the U937 cell line.

PMA was utilized to stimulate the differentiation of the U937 cell line into macrophage-like cells at a concentration of 10 nM. Akt1-phosphorylated Serine 473, Bad-phosphorylated Serine 136 and Caspase9-phosphorylated Serine 196 were tested by flow cytometry for the involvement of the Akt1 signaling pathway during differentiation in addition to the expression of CD14, CD206 and CD83. DNA cell cycle variation analysis was done using PI staining and cell viability and apoptosis detection using Annexin V and PI flow cytometry.

There was a decrease in phosphorylated Akt1 and Bad activation and an increase in Caspase9 activation, with an increase in surface markers CD14, CD206 and CD83 acquired by PMA-differentiated cells. DNA cell cycle analysis revealed cell accumulation in the G2/M phase and fewer cells in the S phase of PMA-induced U937. Apoptosis induction for Ly294002 or Wortmannin-inhibited cells and part of PMA-induced cells were detected.

These results may be used to create a model for biomedical research studies and advance the understanding of the mechanism involving differentiation of the U937 cell line.

This paper centers on the exploration of Chinese conflict management styles in the context of international joint ventures in the People's Republic of China (PRC). Based on interviews conducted with directing managers in U.S.‐Chinese joint ventures and seminars held in China on conflict management in such ventures, major characteristics of Chinese conflict management styles are discussed. Influenced by the traditional Chinese values, norms, and philosophies, Chinese managers in joint ventures tend to adopt contingent, long‐term, contextual, and holistic approaches to conflict resolution.

This paper aims to promote a strength model for TiC-TiB2 composite ceramic with non-ellipsoidal particles bridging. Based on the microstructure of TiC-TiB2 composite ceramic, equivalent average residual stress under particles interaction is calculated with the interact direct derivative estimate. Supposing the crack opening displacement keeps ellipsoidal under the TiB2 particles bridging, crack growth resistance curve is obtained.

Composite strength under R-cure with crack unstable propagation is calculated. Based on this model, influences of particles volume fraction, shape, size and other parameters on strength are analyzed.

Results indicated that calculated values are consistent to the tested data. Crack growth resistance increases with crack propagation and TiB2 volume fraction. The TiB2 particle does not pull-out entirely even ceramic fracture. Ceramic strength increases with the TiB2 particle volume fraction, the ratio of platelet diameter and thickness, and it reduces with particle thickness.

Supposing the crack open displacement keeps ellipsoidal under the TiB2 particles bridging, crack growth resistance curve is obtained.

The purpose of this study comes from the need of defining improved durability values and the realization of a good traceability management for selected vegan cheeses has suggested the comparison between a processed cheese and its analogous version without animal-origin raw materials. The durability should be studied at a well-defined temperature, probably agreed among the food producer and the food processor. In addition, the traceability system should consider many components and related suppliers.

A supply chain risk assessment analysis has been carried out with relation to two different products: an analogue cheese and a vegan cheese-like preparation. Raw materials and ingredients have been evaluated (production method and origin; geographical identification), with the aim of identifying simplified food.

An assessment of food supply networks has been carried out. In the first situation (analogue cheeses), the ingredient “cheeses” shows an important complexity: five suppliers with a related six-interconnection hub. On the other side, vegan cheeses are obtained from 11 ingredients (a challenging hub); four of them may be produced from 2–5 components of different origin (five total hubs). Tested processed cheeses are represented by means of a linear food supply network with two hubs (cheeses and “arrival” show degrees 6 and 9, respectively). Networks concerning vegan cheeses include five different hubs: four complex raw materials (degree: 2, 3, 4 and 5) and the “arrival” step (degree: 12).

The information load of vegan cheeses (two hubs, degrees >> average degree) appears high if compared with processed cheeses (two hubs), although the complexity of networks appears similar. Vegan cheeses may seem technologically simpler than processed cheeses and be sometimes questioned because of important traceability issues. Adequate traceability countermeasures in terms of preventive monitoring actions should be recommended when speaking of vegan cheeses. Anyway, a centralized manager would be always required.

This study aims to empirically analyze the impact of technological innovation on the quantity and quality of employment in the hospitality industry.

Using the data of 30 provinces in China from 2010 to 2020, this paper makes an empirical analysis through the fixed effect model.

The results show that process innovation has a significant positive impact on employment quantity, while product innovation has a significant negative impact on employment quantity. The creative effect of process innovation and the substitution effect of product innovation offset each other, so in the long run, the impact of technological innovation on employment quantity is not significant. However, technological innovation has significantly improved the employment quality of the hospitality industry.

Because technological innovation has replaced part of the labor force, hospitality could guide the labor force in a positive direction. To promote innovation and retain talents, hotels should train employees’ digital thinking and attract high-skilled talents.

This research is unique in using process innovation and product innovation as the main measurement indicators of technological innovation, unlike previous studies that often relied on technological progress to conclude.

As an emerging discipline, data science represents a vital new current of school of library and information science (LIS) education. However, it remains unclear how it relates to information science within LIS schools. The purpose of this paper is to clarify this issue.

Mission statement and nature of both data science and information science are analyzed by reviewing existing work in the two disciplines and drawing DIKW hierarchy. It looks at the ways in which information science theories bring new insights and shed new light on fundamentals of data science.

Data science and information science are twin disciplines by nature. The mission, task and nature of data science are consistent with those of information science. They greatly overlap and share similar concerns. Furthermore, they can complement each other. LIS school should integrate both sciences and develop organizational ambidexterity. Information science can make unique contributions to data science research, including conception of data, data quality control, data librarianship and theory dualism. Document theory, as a promising direction of unified information science, should be introduced to data science to solve the disciplinary divide.

The results of this paper may contribute to the integration of data science and information science within LIS schools and iSchools. It has particular value for LIS school development and reform in the age of big data.