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Post-COVID-19, public K–12 schools are still facing the consequences of the years of interrupted learning. Schools serving minoritized students are particularly at risk for facing challenges with academics, behavior and student social emotional health. The university counseling programs are in positions to build capacity in urban schools while also supporting counselors-in-training through service-learning opportunities.

The following conceptual manuscript demonstrates how counselor education counseling programs and public schools can harness the capacity-building benefits of university–school partnerships. While prevalent in fields like special education, counselor educators have yet to heed the hall to participate in mutually beneficial partnership programs.

Using the multi-tiered systems of support (MTSS) and the components of the university–school partnerships, counselor educators and school stakeholders can work together to support student mental health, school staff well-being and counselor-in-training competence.

The benefits and opportunities within the university–school partnerships are well documented. However, few researchers have described a model to support partnerships between the university counseling programs and urban elementary schools. We provide a best practice model using the principles of university–school partnerships and a school’s existing MTSS framework.

The purpose of this paper is to demonstrate the impact of the welding sequence on the substrate plate distortion during the wire and arc additive manufacturing (WAAM) process. This paper also aims to show the capability of finite element simulations in the prediction of those thermally induced distortions.

An experiment was conducted in which solid aluminum blocks were manufactured using two different welding sequences. The distortion of the substrates was measured at predefined positions and converted into bending and torsion values. Subsequently, a weakly coupled thermo-mechanical finite element model was created using the Abaqus simulation software. The model was calibrated and validated with data gathered from the experiments.

The results of this paper showed that the welding sequence of a part significantly affects the formation of thermally induced distortions of the final part. The calibrated simulation model was able to capture the different distortion behavior attributed to the welding sequences.

Within this work, a simulation model was developed capable of predicting the distortion of WAAM parts in advance. The findings of this paper can be used to improve the design of WAAM welding sequences while avoiding high experimental efforts.

This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.

Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.

The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.

The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.

The aims of this Editorial are twofold: (i) synthesise emergent themes from the special issue (ii) tender four theoretical frameworks toward examination of crises in tourism.

The thematic analysis of papers highlights a diversity of COVID-19 related crises contexts and research approaches. The need for robust theoretical interventions is highlighted through the four proposed conceptual frameworks.

Crises provides a valuable seam from which to draw new empirical and theoretical insights. Papers in this special issue address the unfolding of crises in tourism and demonstrate how its theorization demands multi and cross-disciplinary entreaties. This special issue is an invitation to examine how global crises in tourism can be more clearly appraised and theorised. The nature of crisis, and the extent to which the global tourism community can continue to adapt remains in question, as dialogues juxtapose the contradictions between tourism growth and tourism sustainability, and between building back better and returning to normal.

The appraisal of four conceptual frameworks, little used in tourism research provides markers of the theoretical rigour and novelty so often sought. Beck’s risk society reconceptualises risk and the extent to which risk is manmade. Biopolitics refers to the power over the production and reproduction of life itself, where the political stake corresponds to power over society. The political ecology of crisis denaturalises “natural” disasters and their subsequent crises. Justice complements an ethic of care and values like conative empathy to advance social justice and well-being.

The operating wagon records were produced from distinct railway information systems, which resulted in the wagon routing record with the same oriental destination (OD) was different. This phenomenon has brought considerable difficulties to the railway wagon flow forecast. Some were because of poor data quality, which misled the actual prediction, while others were because of the existence of another actual wagon routings. This paper aims at finding all the wagon routing locus patterns from the history records, and thus puts forward an intelligent recognition method for the actual routing locus pattern of railway wagon flow based on SST algorithm.

Based on the big data of railway wagon flow records, the routing metadata model is constructed, and the historical data and real-time data are fused to improve the reliability of the path forecast results in the work of railway wagon flow forecast. Based on the division of spatial characteristics and the reduction of dimension in the distributary station, the improved Simhash algorithm is used to calculate the routing fingerprint. Combined with Squared Error Adjacency Matrix Clustering algorithm and Tarjan algorithm, the fingerprint similarity is calculated, the spatial characteristics are clustering and identified, the routing locus mode is formed and then the intelligent recognition of the actual wagon flow routing locus is realized.

This paper puts forward a more realistic method of railway wagon routing pattern recognition algorithm. The problem of traditional railway wagon routing planning is converted into the routing locus pattern recognition problem, and the wagon routing pattern of all OD streams is excavated from the historical data results. The analysis is carried out from three aspects: routing metadata, routing locus fingerprint and routing locus pattern. Then, the intelligent recognition SST-based algorithm of railway wagon routing locus pattern is proposed, which combines the history data and instant data to improve the reliability of the wagon routing selection result. Finally, railway wagon routing locus could be found out accurately, and the case study tests the validity of the algorithm.

Before the forecasting work of railway wagon flow, it needs to know how many kinds of wagon routing locus exist in a certain OD. Mining all the OD routing locus patterns from the railway wagon operating records is helpful to forecast the future routing combined with the wagon characteristics. The work of this paper is the basis of the railway wagon routing forecast.

As the basis of the railway wagon routing forecast, this research not only improves the accuracy and efficiency for the railway wagon routing forecast but also provides the further support of decision-making for the railway freight transportation organization.

At present numerical simulation of seismicity, used in mining and hydraulic fracturing practice, is quite time expensive what hampers its combined employing with observed seismicity in real time. The purpose of this paper is to suggest a mean for drastic speeding up numerical modeling seismic and aseismic events.

The authors propose the means to radically decrease the time expense for the bottleneck stage of simulation: calculations of stresses, induced by a large group of already activated flaws (sources of events), at locations of flaws of another large group, which may be activated by the stresses. This is achieved by building a hierarchical tree and properly accounting for the sizes of activated flaws, excluding check of their influence on flaws, which are beyond strictly defined near-regions of strong interaction.

Comparative simulations of seismicity by conventional and improved methods demonstrate high efficiency of the means developed. When applied to practical mining and hydrofracturing problems, it requires some two orders less time to obtain practically the same output results as those of conventional methods.

The proposed improvement provides a means for simulation of seismicity in real time of mining steps and hydrofracture propagation. It can be also used in other applications involving seismic and aseismic events and acoustic emission.

The purpose of this paper investigates dynamic ease distributions of clothes at bust and waist lines with different body surface angle by using a Qualisys three-dimensional motion capture system (3DMCS).

The current method first obtain the specific markers of participants and their clothes along the bust and waist lines through 3DMCS, then using the least square method and four piecewise polynomial fitting participants and their clothes' bust and waist curves. The coordinates of the markers were tracked by the 3DMCS, while the participants under different body surface angle walked on a treadmill calculated the distances of markers coordinates to the participants' bust and waist curves. Finally, the data of samples were analyzed. It was found that the dynamic ease distributions showed different patterns at different body surface angle.

The results revealed the bust convex angle is 26.53 degrees (Specification:X3) and back slope angle is 13.96 degrees (Specification: Y1), the fluctuation of participant ease distributions on bust section was most obvious, and the maximum fluctuation value was ±20 mm and ±25 mm. The ease distributions of participant waist section fluctuated most obviously when the bust convex angle is 28.10 degrees (Specification: X5) and the back slope angle is 13.96 degrees (Specification: Y1), and the maximum fluctuation was ±30 mm and ±20 mm. The bust convex angle has the greatest influence on 1# garment, and the back slope angle has the greatest influence on 2# garment.

Currently, there is little information in the literature about dynamic ease distributions of garment on a different body types. This paper takes different body surface angles as the research objects to analyze the ease distributions of different clothes, the conclusion can provide reference data for 3D garment modeling and improve the authenticity of virtual garment fitting.

The outbreak and the spreading of the COVID-19 pandemic have impacted the global financial sector, including the alternative clean and renewable energy sector. This paper aims to assess the impact of the pandemic, COVID-19 on the stock market indices of the clean energy sector using quantile regression methods.

This study utilized daily data sets on the four major categories of stocks: (1) Morgan Stanley Capital International Global Alternative Energy Index, (2) WilderHill Clean Energy Index, (3) Renewable Energy Industrial Index (RENIXX) and (4) the S&P 500 Global Clean Index. The study adopts a multifactor capital asset pricing model.

Clean and alternative energy stocks are powerful instruments for diversification. However, the impact of the volatility index induced by infectious disease is negative and significant across quantiles.

For investors and policymakers, considering how the uncertainty caused by COVID-19 and the geopolitical index influences renewable energy markets is of great practical importance. For investors, it throws insights into portfolio diversification. For policy makers, it helps to devise strategies to reboot the economy along the lines of the deployment of renewables. This study sheds light on a global green-energy transition and has practical implications for renewable energy resilience in post-pandemic times.

This paper can be considered as a pioneer that explores the nexus between oil prices, interest rates, volatility index, and geopolitical risk upon the stock indices of clean and alternative sources of (renewable) energy in the COVID-19 pandemic situation. The results have important insights into the area of energy and policy decision-making. Additionally, the paper's novelty lies in using the explanatory variables associated with the Covid 19 pandemic.

This paper aims to provide an overview of the current manufacturing methods for three-dimensional textile preforms while providing experimental data on the emerging techniques of combining yarn interlocking with yarn interlooping.

The paper describes the key textile technologies used for composite manufacture: braiding, weaving and knitting. The various textile preforming methods are suited to different applications; their capabilities and end performance characteristics are analysed.

Such preforms are used in composites in a wide range of industries, from aerospace to medical and automotive to civil engineering. The paper highlights how the use of knitting technology for preform manufacture has gained wider acceptance due to its flexibility in design and shaping capabilities. The tensile properties of glass fibre knit structures containing inlay yarns interlocked between knitted loops are given, highlighting the importance of reinforcement yarns.

The future trends of reinforcement yarns in knitted structures for improved tensile properties are discussed, with initial experimental data.

This paper aims to identify the factors that are constraining technological innovation to support the development of coalbed methane in China.

The analysis applies ideas relating to national and sector systems of innovation to explain why China’s strategies to support research and technological innovation have failed to stimulate the desired progress in coalbed methane production. It also provides a counter-example of the USA that implemented a number of measures in the 1970s that proved very effective.

The deficiencies of China’s research and development strategies in support of coalbed methane development reflect the national and sectoral systems of innovation. They are exacerbated by the structure of the national oil and gas industry. Key constraints include the excessively top-down management of the national R&D agenda, insufficient support for basic research, limited collaboration networks between companies, research institutes and universities and weak mechanisms for diffusion of knowledge. The success of the USA was based on entirely different systems for innovation and in quite a different industrial setting.

The originality of this analysis lies in placing the challenges facing research and innovation for China’s coalbed methane development in the context of the national and sectoral systems for innovation and comparing with the approach and success of the USA.