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The purpose of this qualitative instrumental case study was to determine the perceptions of preservice teachers (PSTs) on the effectiveness of instructional rounds as a clinical experience in promoting awareness of student diversity and supporting the acquisition of professional knowledge (Essential 2).

The instructional rounds were implemented in a junior-level general pedagogy course prior to formal clinical experiences. Professional development school (PDS) personnel supported the course instructors by scheduling the classroom observations, supervising groups of PSTs and debriefing the PSTs after each observation (Essentials 4 and 8). The data were collected through an end-of-course survey of 18 secondary PSTs.

There were several themes that emerged from the analysis of data. First, the study revealed that PSTs credited the variety of campuses visited as supporting their awareness of student diversity and varied instructional strategies. Second, PSTs acknowledged that the instructional rounds supported their connection of theory to practice. Finally, over 70% of the participants noted that they most enjoyed in-person experiences in different classrooms to observe students and teachers in action.

The findings for this study were specific to the teacher preparation program (TPP) utilized for the research. Each TPP requires different coursework and clinical experiences; therefore, the inclusion of instructional rounds may not be possible in all programs. Yet, the implementation of the rounds as a PST experience prior to clinical experiences is a strategy to consider to support the preparation of PSTs for their clinical experiences.

This study supports the continuation of instructional rounds at the teacher preparation program where the research was conducted. This research also informs other TPPs that strive to provide early clinical experiences that support PSTs’ emerging perceptions of student diversity and applications of instructional knowledge.

The paper aims to study the constraint solutions of the periodic coupled operator matrix equations by the biconjugate residual algorithm. The new algorithm can solve a lot of constraint solutions including Hamiltonian solutions and symmetric solutions, as special cases. At the end of this paper, the new algorithm is applied to the pole assignment problem.

When the studied periodic coupled operator matrix equations are consistent, it is proved that constraint solutions can converge to exact solutions. It is demonstrated that the solutions of the equations can be obtained by the new algorithm with any arbitrary initial matrices without rounding error in a finite number of iterative steps. In addition, the least norm-constrained solutions can also be calculated by selecting any initial matrices when the equations of the periodic coupled operator matrix are inconsistent.

Numerical examples show that compared with some existing algorithms, the proposed method has higher convergence efficiency because less data are used in each iteration and the data is sufficient to complete an update. It not only has the best convergence accuracy but also requires the least running time for iteration, which greatly saves memory space.

Compared with previous algorithms, the main feature of this algorithm is that it can synthesize these equations together to get a coupled operator matrix equation. Although the equation of this paper contains multiple submatrix equations, the algorithm in this paper only needs to use the information of one submatrix equation in the equation of this paper in each iteration so that different constraint solutions of different (coupled) matrix equations can be studied for this class of equations. However, previous articles need to iterate on a specific constraint solution of a matrix equation separately.

This paper investigates share price clustering and its determinants across Nasdaq Stockholm, Copenhagen, Helsinki, and Iceland.

This paper investigates share price clustering and its determinants across Nasdaq Stockholm, Copenhagen, Helsinki, and Iceland. Univariate analysis confirms widespread clustering, notably favouring closing prices ending in zero. Multivariate analysis explores the impact of firm size, price level, volatility, and turnover on clustering.

Univariate analysis confirms widespread clustering, notably favouring closing prices ending in zero. Multivariate analysis explores the impact of firm size, price level, volatility, and turnover on clustering. Results reveal pervasive clustering, strengthening with higher prices and turnover but weakening with larger trade volumes, firm size, and smaller tick sizes. These empirical findings support the theoretical expectations of price negotiation and resolution hypotheses.

The observed clustering presents an opportunity for investors to potentially capitalize on this market anomaly and achieve supra-normal returns.

Price clustering, the phenomenon where certain price levels are traded more frequently, challenges the efficient market hypothesis and has been extensively studied in financial markets. However, the Scandinavian stock markets, particularly those in the Nasdaq Nordic Exchange, remain unexplored in this context.

This study aims to extend the known design guidelines for the polymer-based fused filament fabrication (FFF) 3D printing process with the focus on function-integrated components, specifically optomechanical parts. The potential of this approach is demonstrated by manufacturing function-integrated optomechanics for a low-power solid-state laser system.

For the production of function-integrated additively manufactured optomechanics using the FFF process, essential components and subsystems have been identified for which no design guidelines are available. This includes guidelines for integrating elements, particularly optics, into a polymer structure as well as guidelines for printing functional threads and ball joints. Based on these results, combined with prior research, a function-integrated low-power solid-state laser optomechanic was fabricated via the FFF process, using a commercial 3D printer of the type Ultimaker 3. The laser system's performance was assessed and compared to a reference system that employed commercial optomechanics, additionally confirming the design guidelines derived from the study.

Based on the design goal of function integration, the existing design guidelines for the FFF process are systematically extended. This success is demonstrated by the fabrication of an integrated optomechanic for a solid-state laser system.

Based on these results, scientists and engineers will be able to use the FFF process more extensively and benefit from the possibilities of function-integrated manufacturing.

Extensive research has been published on additive manufacturing of optomechanics. However, this research often emphasizes only cost reduction and short-term availability of components by reprinting existing parts. This paper aims to explore the capabilities of additive manufacturing in the production of function-integrated components to reduce the number of individual parts required, thereby decreasing the workload for system assembly and leading to an innovative production process for optical systems. Consequently, where needed, it provides new design guidelines or extends existing ones and verifies them by means of test series.

This study aims to solve the problem of job scheduling and multi automated guided vehicle (AGV) cooperation in intelligent manufacturing workshops.

In this study, an algorithm for job scheduling and cooperative work of multiple AGVs is designed. In the first part, with the goal of minimizing the total processing time and the total power consumption, the niche multi-objective evolutionary algorithm is used to determine the processing task arrangement on different machines. In the second part, AGV is called to transport workpieces, and an improved ant colony algorithm is used to generate the initial path of AGV. In the third part, to avoid path conflicts between running AGVs, the authors propose a simple priority-based waiting strategy to avoid collisions.

The experiment shows that the solution can effectively deal with job scheduling and multiple AGV operation problems in the workshop.

In this paper, a collaborative work algorithm is proposed, which combines the job scheduling and AGV running problem to make the research results adapt to the real job environment in the workshop.

An experimental investigation of hemispherical forebody interaction effects on the drag coefficient of a D-shaped model is carried out for three-dimensional flow in the subcritical range of Reynolds number 1 × 10⁵ ≤ Re ≤ 1.8 × 10⁵. To study the interaction effect, hemispherical shapes of various sizes are attached to the upriver of the D-shaped bluff body model. The diameter of the hemisphere (b₁) varied from 0.25 to 0.75 times the diameter of the D-shaped model (b₂) and its gap from the D-shaped model (g/b₂) ranged from 0.25 to 1.75 b₂.

The experiments were carried out in a low-speed open-circuit closed jet wind tunnel with test section dimensions of 1.2 × 0.9 × 1.8 m (W × H × L) capable of generating maximum velocity up to 45 m/s. The wind tunnel is equipped with a driving unit which has a 175-hp motor with three propellers controlled by a 160-kW inverter drive. Drag force is measured with an internal six-component balance with the help of the Spider 3013 E-pro data acquisition system.

The wind tunnel results show that the hemispherical forebody has a diameter ratio of 0.75 with a gap ratio of 0.25, resulting in a maximum drag reduction of 67%.

The turbulence intensity of the wind tunnel is about 5.6% at a velocity of 18 m/s. The uncertainty in the velocity and the drag coefficient measurement are about ±1.5 and ±2.83 %, respectively. The maximum error in the geometric model is about ±1.33 %.

The results from the research work are helpful in choosing the optimum spacing of road vehicles, especially truck–trailer and launch vehicle applications.

Drag reduction of road vehicle resulting less fuel consumption as well as less pollution to the environment. For instance, tractor trailer experiencing approximately 45% of aerodynamics drag is due to front part of the vehicle. The other contributors are 30% due to trailer base and 25% is due to under body flow. Nearly 65% of energy was spent to overcome the aerodynamic drag, when the vehicle is traveling at the average of 70 kmph (Seifert 2008 and Doyle 2008).

The benefits of placing the forebody in front of the main body will have a strong influence on reducing fuel consumption.

Healthcare organizations have been facing challenges due to high costs and low efficiency in health services. The growth of costs and losses caused by avoidable mistakes lead to the search for solutions, and Health Lean Management appears as a potential solution to help in solving service quality problems, as well as reducing risks. This study aims to analyse the state of the art in the literature centred on the Lean approach in the context of risk management in healthcare organizations, and to identify new research opportunities, highlighting possible lines of future research.

Following a systematic literature review approach, 51 papers were considered relevant for this research, and reviewed to explore the development of literature in this area.

Based on the results, five main research streams were identified: (1) risk management oriented towards patient safety; (2) risk management oriented towards employee safety; (3) importance of attitudes and behaviours in risk reduction projects; (4) Lean tools used in healthcare risk management and (5) Integration of approaches. Moreover, several shortcomings were identified in literature.

Identified shortcomings represent significant opportunities for further research development.

The study compares all three versions of sustainable development goal (SDG) India index and assess the pace and direction of each State/UT for the attainment of SDGs by 2030. The study is an attempt to scrutinise performance of each indicator of every State and UT of India across 16 SDGs from 2018 to 2020. For this purpose, 13 SDGs with 56 indicators for first version, 16 SDGs with 101 indictors from second version and 115 indicators across 16 SDGs from third version of SDG India Index are investigated. Instead of relining NITI Aayog's indexing methodology, the study uses the same dataset to assess the distance of each state from national target for SDG. Cursorily, it also derives statistical projections of duration required by each State/UT for achieving particular indicator and goal at large. The investigation derives statistical projections of duration required by each State/UT for achieving a particular indicator and goal at large.

Based on the progress made by each State/UT, distance from present conditions are categorised as a Very far (distance less than 0%), Far (distance from 1% to 25%), Near (distance from 26% to 50%), Very Near (distance from 51% to 75%), Achieving target (76%–100%).

The conclusion of the study intends to highlight the benefits and challenges for adopting indexing or ranking approach to monitor the sub-national level progress made for attainment SDGs.

The purpose of this study is to propose a precise and standardized strategy for numerically simulating vehicle aerodynamics.

Error sources in computational fluid dynamics were analyzed. Additionally, controllable experiential and discretization errors, which significantly influence the calculated results, are expounded upon. Considering the airflow mechanism around a vehicle, the computational efficiency and accuracy of each solution strategy were compared and analyzed through numerous computational cases. Finally, the most suitable numerical strategy, including the turbulence model, simplified vehicle model, calculation domain, boundary conditions, grids and discretization scheme, was identified. Two simplified vehicle models were introduced, and relevant wind tunnel tests were performed to validate the selected strategy.

Errors in vehicle computational aerodynamics mainly stem from the unreasonable simplification of the vehicle model, calculation domain, definite solution conditions, grid strategy and discretization schemes. Using the proposed standardized numerical strategy, the simulated steady and transient aerodynamic characteristics agreed well with the experimental results.

Building upon the modified Low-Reynolds Number k-e model and Scale Adaptive Simulation model, to the best of the authors’ knowledge, a precise and standardized numerical simulation strategy for vehicle aerodynamics is proposed for the first time, which can be integrated into vehicle research and design.