Train Control Research Articles

Saving energy resources during operation of rolling stock of underground electrified transport

Purpose. To analyze the energy saving reserves under the conditions of implementation and integration of the system in order to find rational driving modes in the general system of managing underground electrified transport. Methodology. The work presents the method for processing data arrays obtained experimentally with the help of a measuring system and theoretically with the use of the “Rational Trajectory” software. Findings. Experimental studies were carried out using a testing system created on the basis of a refurbished train with energy recovery system. Theoretical studies were carried out using the “Rational Trajectory” software, which is based on the principle of solving a multi-criteria problem by the method of the main criterion. The minimum amount of electricity consumption from the overhead contact line was chosen as the main criterion. The software was developed in the LabVIEW graphical programming environment in order to determine the rational modes of driving rolling stock and energy indicators in a given area of its operation. The amount of electricity consumed for traction and the amount of electricity generated by the train during regenerative braking were determined based on the results of experimental and theoretical studies, respectively, under typical and rational modes of driving the train for given identical operating conditions. Originality. Further research on the analysis of energy saving reserves on the rolling stock of underground electrified transport was achieved due to the introduction of a system for finding a rational driving mode. Practical value. It has been established that the implementation and incorporation of the “Rational Trajectory” software into the train control system will save up to 14.7 % of the amount of electricity consumed for traction, compared to typical modes operation on a given track section.

Method for Determining the Conditions for Ensuring Stable Rearward Movement of a Semi-trailer Combination with Non-turning Semi-trailer Wheels

The efficiency of organising freight transport and using motor transport in a Smart City depends on a set of its properties, which in the process of operation determine its suitability for use in given operating conditions. Vehicles have different overall dimensions and designs, which determine their maneuverability and directional stability, their ability to make a curve-line movement in the city, as well as to move safely in reverse. Nowadays, tractor-trailer combinations with non-turning semi-trailer wheels are widely used for freight transport. Such a scheme of vehicle construction does not ensure its directional stability when reversing, which can lead to the folding of the tractor and semi-trailer and loss of mobility of the combination. In the absence of additional special systems, the driver controls the rearward movement of the road train using the steering wheel and rear-view mirrors, and the accuracy of delivery to the object depends on the level of the driver's training. The research of driver's reaction time spent on situation assessment, decision making, and realisation has been carried out. It has been revealed that with manual control, there are difficulties connected with training of drivers to estimate the parameters of movement and control of the road train, in particular, with the process of parking and its accurate delivery to the object. With the help of the developed mathematical model of the rearward movement of the road train and the proposed new turn control law, the research of maneuvering of the road train during its delivery to the object has been carried out and the results confirming the possibilities of building an automated system allowing to reduce the influence of the human factor on the parking process, as well as to reduce the time required to perform the maneuver have been obtained. The conducted analysis of system stability with the help of Routh–Hurwitz criterion has determined the conditions of providing stability of the system moving in reverse. The method of controlling the backward movement of the road train and the design of the device realising it has been developed. The results of simulation modeling allowed us to find the necessary values for the control law for the movement of road trains of different lengths, as well as the preferred variants of the initial positions of the road train for the realisation of its precise delivery to the object.

Integral predictive sliding mode control for high-speed trains: A dynamic linearization and input constraint-based data-driven scheme

A control scheme with high reliability and excellent tracking performance is essential for the automatic operation of high-speed trains (HSTs). In this study, a novel discrete-time data-driven predictive sliding mode control (DDPSMC) scheme is proposed for multi-power unit HSTs. Initially, a nonlinear integral terminal sliding mode surface was designed to replace the traditional linear sliding mode function, thereby achieving a rapid system error convergence and alleviating chattering. Then, receding horizon optimization was integrated into predictive control, which allowed the predicted sliding mode state to follow the expected trajectory of a predefined continuous convergence law. This scheme enabled the system to obtain higher output error accuracy and explicitly handle input constraints. Moreover, to enhance robustness, a parameter update law and disturbance delay estimation algorithm were introduced to calculate the control gain and total uncertainty, respectively. Finally, a comparative test of the proposed control scheme was conducted using a CRH380A HST simulation experimental platform in a laboratory setting. Simulation results demonstrate that the velocity error range of each power unit of the HST under the proposed control scheme is within [−0.176 km/h, 0.152 km/h], while the control force and acceleration are within [−55.7 kN, 44.8 kN] and [−0.564 m/s2, 0.496 m/s2], respectively, with stable variation, and other performance indicators are also better than other comparison methods. These results satisfy the safety, stability, and punctuality requirements of the train.

Electromagnetic Compatibility Study of Trackside Antenna Array Miniaturization in the Subway Tunnel

Abstract To improve the compatibility of the subway tunnel’s electromagnetic environment and reduce the radiation impact of trackside antennas on subway workers. This paper proposes a miniaturized dual-band trackside antenna array by using metamaterial units. Its operation bandwidth is 2.33~2.56 GHz and 3.24~3.45 GHz, which could simultaneously satisfy the signal cover demands of the communications-based train control (CBTC) and the civil 5G wireless communication system. The proposed miniaturized antenna array has a maximum gain of 14.4 dBi and a maximum channel capacity of 13.9 bps/Hz at a signal-to-noise ratio (SNR) of 20 dB, which can effectively improve the quality of wireless communication systems. The number of trackside antennas with a single operation frequency band is reduced, and the distance between the antennas is enlarged at the same time. Besides that, we analyze the radiation impact on the tunnel electromagnetic environment of the proposed trackside antenna array. In particular, the electromagnetic dose absorbed by the human model of a tunnel worker is quantized. The results show that the electric field strength in the tunnel reduces by 4.11% at least after antenna array miniaturization, and the specific absorption rate (SAR) absorbed by the worker model's trunk, skull, brain, heart, and liver is reduced by a maximum of 19.02%, 33.16%, 28.27%, 41.75%, and 74.54%, respectively, further lowering the human electromagnetic exposure risk. Therefore, a miniaturized trackside antenna array could reduce the interference from other radiation sources in the tunnel while providing a new idea for electromagnetic protection for subway workers.

Undergraduate musculoskeletal ultrasound training based on current national guidelines—a prospective controlled study on transferability

IntroductionMusculoskeletal ultrasound (MSUS) is integral to routine clinical diagnostics for musculoskeletal and joint disorders. This study aims to establish and validate a sonography course tailored to undergraduate medical students acquiring MSUS-specific skills at a German university.MethodsA blended learning training concept, comprising 24 instruction sessions of 45 min each, was designed based on the current national guidelines of the German Society for Ultrasound in Medicine (DEGUM). This program was integrated into the clinical phase of the undergraduate students’ medical education. The self-perceived improvement in competency and the effectiveness of the course design were evaluated using a a 7-point Likert scale questionnaire. Objective learning success was evaluated via a written test and a “Direct Observation of Practical Skills” practical exam. Control groups included medical students without MSUS training (control group 1) and doctors who had completed DEGUM-certified basic MSUS courses (control group 2). Both control groups completed the written test, while control group 2 also took the practical final exam. The study involved 146 participants: 56 were allocated to the study group, 44 to control group 1, and 46 to control group 2.ResultsThe study group rated their skills significantly higher after the course (p < 0.01). Participants expressed high satisfaction with the course design, the teaching materials, and the teachers. The study group's performance on the final written test was comparable to those of control group 2 (p = 0.06) and significantly superior to control group 1 (p < 0.001). Additionally, the study group’s performance on the practical final exam was not significantly different from control group 2 (p = 0.28), with both groups achieving scores exceeding 80%.ConclusionBoth subjective and objective measures of learning suggest that an MSUS course designed for postgraduates can be effectively adapted for undergraduate medical students. Incorporating MSUS training into the clinical curriculum is recommended to enhance future medical professionals' educational experience and practical skills.

Effects of moderate-intensity aerobic training on cardiac structure and function in type 2 mellitus diabetic rats: Based on echocardiography and speckle tracking

PurposeThe present study aimed to evaluate the cardiac function changes using Layer-specific Speckle-tracking echocardiography (LS-STE) induced by Moderate-intensity aerobic training (MIAT) in Type 2 diabetes mellitus (T2DM) rats. MethodsTwenty-six rats were divided into four groups: the Control group (Con), the Training control group (CT), the T2DM group (DM), and the T2DM training group (DT). The CT and DT groups underwent an 8 weeks MIAT. Cardiac structure and function were evaluated by echocardiography and LS-STE. ResultsCompared with the Con group, left atrial diameter (LAD), left ventricular end-diastolic diameter(LVEDD), relation wall thickness (RWT), and left ventricular mass (LVM) were significantly higher, and the endo-, mid-, and epi-longitudinal strain (LS), global radial strain (GRS), and endo- and mid-circumferential strain (CS) were significantly lower in DM rats (all p < 0.05). The endo-, mid-, and epi-LS, GRS, endo- and mid-CS were increased in DT rats compared with DM rats (all p < 0.05). Compared with Con rats, CT rats had a significant increase in LVEDD and LVM (all p < 0.05), meanwhile myocardial strains had no significant differences (all p > 0.05). ConclusionLS-STE was a sensitive method to assess subclinical myocardial changes in T2DM rats. MIAT had the benefit of reversing cardiac systolic subclinical dysfunction in T2DM rats.

Energy consumption analysis of trains based on multi-mode virtual coupling operation control strategies

Urban rail transit, as a main mode of travel, has always been concerned with the balanced relationship between energy consumption and transport efficiency. The advent of the virtually coupled train set (VCTS) has significantly enhanced the efficiency of existing railway lines. Both energy consumption and comfort during the operation of VCTS control technology have emerged as significant challenges for the development of VCTS since the inception of onsite testing. A review of the current research status of VCTS control systems has revealed that the majority of current formation control systems are focused on the safe operation of formation trains, the stability of train control systems, and safe train separation models. However, a case study has shown there is a strong correlation between train operating intervals, train control strategies, and train operating energy consumption. Therefore, it is necessary to design and plan the operation modes of formation trains for different train operation requirements. This paper presents four distinct control modes, developed through the integration of the most prevalent VCTS control strategies, operational modes, and operational requirements. The design of these control modes is guided by considerations of energy consumption, safety, and comfort during train operation. A case study of Beijing Subway Line 11 revealed a significant correlation between energy consumption, control mode, and safety under different control modes. In particular, the correlation between train running intervals and energy consumption in a high-precision tracking state provides valuable technical support for the future operation of VCTS technology in different periods, scenarios, and environments.

Characterizing two hybrid exercise-cognitive training interventions with neurophysiological and behavioral indexes in post-stroke patients with cognitive dysfunction: a randomized controlled trial.

Combined exercise and cognitive training have been evidenced to be effective in cognitive and physical functions in post-stroke survivors. Recent interest has gradually shifted to technology-aided cognitive rehabilitation. However, clear neural makers or comprehensive behavioral indexes used for evaluating rehabilitation remain unexplored. The study aimed to examine the effects of two types of combined exercise-cognitive training on stroke patients with cognitive dysfunction, focusing on neural and behavioral markers. 39 patients were randomly assigned to sequential exercise-cognitive training, simultaneous exercise-cognitive training or active control groups and underwent 60 minutes/day training, 3 days/week, for 12 weeks. 29 patients ultimately completed the training. The markers/indexes included cognitive function, physical function, instrumental activities of daily living, and caregiver strain. Cognitive function included working memory task performance, neurophysiological markers, and cognitive indexes. The results indicated no d-prime difference between groups after the training. The simultaneous training demonstrated significant improvements in the neurophysiological marker of P300 and theta coherence compared to the other groups. Moreover, the simultaneous training also led to significant enhancements in physical function, as measured by the Rivermead Mobility Index, comparing to the other groups. Further analysis contrasting the two exercise-cognitive trainings revealed that improvements in cognition and multifaceted domains (i.e., instrumental activities of daily living and caregiver strain) were manifested in the simultaneous training. Together with the neural markers identified in the current interventions, the differential impacts of the two interventions indicates the potential of technology-driven and personalized rehabilitation in post-stroke patients.

The influence of a coordination training model that uses various manipulative movements on futsal kick accuracy

Achieving precise kick accuracy and coordinated movements in futsal was essential for competitive success. This study aimed to evaluate the differences between various futsal training approaches that incorporated distinct coordination exercises involving manipulative movements, specifically assessing their impact on kick accuracy. A quasi-experimental design with a control group was employed, focusing on shooting skills within the futsal context. The population consisted of 70 members from the Universitas Muhammadiyah Kalimantan Timur (UMKT) futsal team, from which 40 players were purposively selected based on their participation duration of over six months and their tier status within the university's core teams. Participants were divided into two groups: one received static coordination training (control group), and the other underwent dynamic coordination training (experimental group), each comprising 20 players. The intervention spanned 18 sessions, including pre- and post-tests. Data were collected through a modified shooting kick test at the futsal goal, utilizing a point distribution system. Analysis revealed significant differences in kick performance between the two training methods, with dynamic coordination training yielding superior results (t-count = 3.010 t-table = 2.024). These findings indicated that dynamic coordination exercises were more effective than static ones in enhancing futsal kick accuracy. Future research should have considered expanding the population and sample size to include amateur players, introducing additional variables and diverse training methodologies, extending training duration and frequency, conducting long-term evaluations, measuring shooting technique quality, and employing quantitative research methods. By addressing these suggestions, subsequent studies could contribute more comprehensively to the understanding of effective training strategies in futsal.

Efeitos da atividade física em crianças e adolescentes com síndrome metabólica: uma revisão sistemática

Introduction: evidence demonstrates that regular physical exercise has beneficial effects in the prevention and treatment of high blood pressure, insulin resistance, diabetes, dyslipidemia and obesity in the population. Objective: To evaluate the impact of physical activity on children and adolescents with metabolic syndrome. Methods: Data surveys. Medline (Pubmed), Cochrane Library, LILACS/VHL. Study selection. Cross-sectional studies (2008-2022) that evaluated the ability of physical training to reduce at least one of the following outcomes: HDL-C; triglycerides; HOMA-IR, Fasting Glucose, systolic blood pressure (SBP); diastolic blood pressure (DBP), Body Mass Index (BMI); 2) Intervention (modality, intervention period, weekly session and duration, weekly frequency, intensity, number of sets and repetitions); in children and adolescents classified as having metabolic syndrome. Data extraction and analysis. Two independent reviewers extracted the data and assessed the quality of the included studies. The differences (physical training group minus control group) in the evaluated results were analyzed using (mean values and standard deviation of pre- and post-intervention, and difference between means). Results. Of the 1,961 articles retrieved, 03 studies were included. This review showed that the practice of physical activity, in general, was associated with a reduction in HDL-C levels (before 44.21 mg/dL (± 9.6), after 42.13 mg/dL (± 7. 76), but was associated with reductions in TG levels (before 113.87 mg/dL after 87.53 mg/dL (26.34). AND HOMA (before 2.54 mg/dL after 2.61 mg /dL) Fasting glucose (before 79.86 mg/dL (±9.22) after 82.43 mg/dL (±8.31). Physical activity is associated with reduced HDL-C levels. Conclusion: seems likely that physical training can play an important role in preventing or delaying metabolic syndrome. We emphasize the need for future intervention studies that investigate the effects of physical activity with greater methodological quality. Keywords: Children; adolescent; physical activity; metabolic syndrome.

Tracking Control for High-Speed Train With Coupler Constraints

Tracking Control for High-Speed Train With Coupler Constraints

Spoofing attack recognition for GNSS-based train positioning using a BO-LightGBM method.

Trustworthy positioning is critical in the operational control and management of trains. For a train positioning system (TPS) based on a global navigation satellite system (GNSS), a spoofing attack significantly threatens the trustworthiness of positioning. However, the influence and recognition of GNSS spoofing attacks are not considered in the existing research on GNSS-enabled TPS. Spoofing attacks affect the performance of GNSS observations and the positioning results, allowing the development of data-driven spoofing recognition solutions. This study aims to achieve effective spoofing recognition for active security protection in TPS. Different features were designed to reflect the effects of a spoofing attack, including GNSS observation-related indicators and odometer-enabled parameters, and a novel Bayesian optimization-light gradient boosting machine (BO-LightGBM) solution was proposed. In particular, a Bayesian optimization technique was introduced into the LightGBM framework to improve the hyperparameter determination capability for recognition model training. Using a GNSS spoofing test platform with a specific GNSS signal generator and the SimSAFE spoofing test tool, different spoofing attack modes were tested to collect sample datasets for model training and evaluation. The results of model establishment and comparison of the model performance indicators illustrated the advantages of the proposed solution, its adaptability to different spoofing attack situations, and its superiority over state-of-the-art modeling strategies.

Effectiveness of hybrid simulation training on medical student performance in whole-task consultation of cardiac patients: The ASSIMILATE EXCELLENCE randomized waitlist-controlled trial

BackgroundAssessment of comprehensive consultations in medicine, i.e. a complete history, physical examination, and differential diagnosis, is regarded as authentic tests of clinical competence; however, they have been shown to have low reliability and validity due to variability in the real patients used and subjective examiner grading. In the ASSIMILATE EXCELLENCE study, our aim was to assess the effect(s) of expert tuition with hybrid simulation using a simulated patient wearing a novel auscultation vest, i.e. a hybrid simulated patient, and repeated peer grading using scoring checklists on student learning, performance, and acumen in comprehensive consultations of patients with valvular heart disease.MethodsASSIMILATE EXCELLENCE was a randomized waitlist-controlled trial with blinded outcome assessment undertaken between February 2021 and November 2021. Students at the Royal College of Surgeons in Ireland in either the second or third year of the four-year graduate-entry medical degree programme were randomized to a hybrid simulation training or waitlist control group and undertook three consultation assessments of three different clinical presentations of valvular heart disease (cases: C1–C3) using hybrid simulation. Our primary outcome was the difference in total score between and within groups across time; a secondary outcome was any change in inter-rater reliability across time. Students self-reported their proficiency and confidence in comprehensive consultations using a pre- and post-study survey.ResultsIncluded were 68 students (age 27.6 ± 0.1 years; 74% women). Overall, total score was 39.6% (35.6, 44.9) in C1 and increased to 63.6% (56.7, 66.7) in C3 (P < .001). On intergroup analysis, a significant difference was observed between groups in C2 only (54.2 ± 7.1% vs. 45.6 ± 9.2%; P < .001), a finding that was mainly driven by a difference in physical examination score. On intragroup analysis, significant improvement in total score across time between cases was also observed. Intraclass correlation coefficients for each pair of assessors were excellent (0.885–0.996 [0.806, 0.998]) in all cases. Following participation, students’ confidence in comprehensive consultation assessments improved, and they felt more prepared for their future careers.ConclusionsHybrid simulation-based training improves competence and confidence in medical students undertaking comprehensive consultation assessment of cardiac patients. In addition, weighted scoring checklists improve grading consistency, learning through peer assessment, and feedback.Trial registrationClinicalTrials.gov Identifier: NCT05895799

Theoretical basics of the self-learning system of intelligent locomotive decision support systems

Analysis of works in the field of artificial intelligence allows to make an assumption that today there is a sufficiently developed theoretical basis for the development of intelligent control systems for locomotive control. This will minimize the risks associated with the human factor on the railways. The paper presents the theoretical rationale for the development of a knowledge base for intelligent locomotive control systems. The approach and structure of the self-learning system of intelligent DSS is proposed, the advantage of which is the presence of a fuzzy classifier that works according to the set criteria and determines a fuzzy image of the current train situation. Learning a fuzzy classifier consists in finding a vector K that minimizes the distance between the results of logical inference and experimental data from the sample. The knowledge base is implemented using linguistic variables formalized by methods of fuzzy logic. The use of linguistic values makes it possible to design the base using the usual language of communication, which greatly simplifies both the design process itself and the analysis of the system's performance. Also, the knowledge base has the possibility of constant self-improvement. This happens in two ways. The first is by adding new rules to the knowledge base in case the current situation does not match the existing ones in the base, in which case an additional rule is created and checked for adequacy. The second way is a mechanism for ranking rules in the knowledge base. If the control action of the locomotive driver coincided with the recommendation of DSS in the current situation, then the rating of this recommendation (rule) increases, and in the future the rule selection algorithm will choose one or another control action for the current situation that has the highest rating (that is, it has already been verified several times person). The experiment has shown that the use of intelligent DSS has positive results. On average, the DSS made the correct train control decisions faster than the locomotive driver.

Measurement of emerging neurocognitive and language skills in the HEALthy Brain and Child Development (HBCD) study

The HEALthy Brain and Child Development (HBCD) study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. The study plans enrolling over 7000 families across 27 sites. This manuscript presents the measures from the Neurocognition and Language Workgroup. Constructs were selected for their importance in normative development, evidence for altered trajectories associated with environmental influences, and predictive validity for child outcomes. Evaluation of measures considered psychometric properties, brevity, and developmental and cultural appropriateness. Both performance measures and caregiver report were used wherever possible. A balance of norm-referenced global measures of development (e.g., Bayley Scales of Infant Development-4) and more specific laboratory measures (e.g., deferred imitation) are included in the HBCD study battery. Domains of assessment include sensory processing, visual-spatial reasoning, expressive and receptive language, executive function, memory, numeracy, adaptive behavior, and neuromotor. Strategies for staff training and quality control procedures, as well as anticipated measures to be added as the cohort ages, are reviewed. The HBCD study presents a unique opportunity to examine early brain and neurodevelopment in young children through a lens that accounts for prenatal exposures, health and socio-economic disparities.

Prospects of autonomous railway transport development

The implementation of unmanned train control systems offers a number of advantages, such as increasing the capacity of railway lines and traffi c volumes, reducing the ‘human factor’, as well as reducing operating costs. The paper considers the challenges arising from the use of automatic train control systems, and presents the prospects for the implementation of automatic technologies in railway transport for various railway systems. The social and economic aspects of changing professional activities in railway transport are described. Grades of automation applicable to surface urban railwaytransport are presented. The issues of proving the functional safety of machine vision systems as part of the train traffic control system and determining their level of safety completeness are discussed. Examples of railway transport automation in Russia and other countries are given. Basic scenarios of automatic control system operation describing normal and abnormal situations are formulated. In conclusion, the levels of technological readiness of the reviewed solutions in the fi eld of train traffic automation are defi ned. The tasks faced by railway companies in implementing these technologies are outlined, and possible ways of overcoming obstacles to the introduction of automatic systems are proposed, taking into account the current political situation.

The effects of chunk reading strategy training on the word chunking skills of L1-Japanese English learners

The Chunk-and-Pass model posits that language acquisition involves learning to effectively chunk linguistic input, thereby recoding it into larger linguistic sequences, such as from words to phrases, to form more abstract representations. This quasi-experimental study investigates the impact of Chunk Reading Strategy Training (CRST) on enhancing the word chunking skills of low-proficiency Japanese English learners. In the CRST intervention, English sentences were segmented into smaller units—each grammatically and semantically meaningful—and presented on a computer screen one chunk at a time. Using a pre-posttest design, 29 Japanese secondary school students underwent the CRST intervention (treatment group), while 21 students received block-format reading training (control group) in 10 sessions of 15–20 min each. Results from a self-paced reading task showed that the treatment group significantly improved their word chunking skills in the posttest, whereas the control group did not. These findings suggest that CRST has the potential to enhance word chunking skills among Japanese English learners and shed light on the pedagogical implications of the Chunk-and-Pass model.

Decentralized learning control for high-speed trains with unknown time-varying speed delays

Treating the multi-point-mass dynamic model of high-speed trains as an interconnected system, this study proposes a decentralized iterative learning control scheme for high-speed trains to achieve the trajectory tracking goal. By making reasonable estimates of the interaction term and compensating for it, the proposed control scheme utilizes only local information from each carriage and does not need any inter-carriage information exchange. The zero-error tracking of the desired trajectory is guaranteed even in a restricted communication environment. Considering unknown time-varying speed delays in the actual high-speed train operations, a modified decentralized iterative learning control scheme is also provided to address the negative impact of speed delays. The convergence of tracking errors is strictly proven by constructing appropriate composite energy functions. Numerical simulations further verify the theoretical results.

Exploring the Frontiers: A Comprehensive Review of Augmented Reality and Virtual Reality in Manufacturing and Industry

Augmented reality (AR) and virtual reality (VR) are revo- lutionizing manufacturing practices by offering immersive and interactive experiences. This review paper synthesizes current research on AR and VR’s applications, benefits, and challenges in manufacturing, covering design, training, maintenance, and quality control. Key findings highlight the applications and positive impact of AR/VR on efficiency, cost management, and quality control in manufacturing processes. Industries are in- creasingly adopting these technologies to enhance productivity and reduce errors. However, challenges such as cost, techno- logical infrastructure, and integration into existing workflows remain significant barriers. In conclusion, integrating AR and VR in manufacturing holds immense potential to transform traditional methods and improve operational efficiency. This paper advocates for broader implementation and research to harness the full benefits of immersive technologies in manufacturing.

Algorithmic trading and mini flash crashes: Evidence from Austria

We use stock-day level data on the market share of algorithmic trading to analyze whether algorithmic trading affects the frequency of mini flash crashes in the Austrian stock market. We use an instrumental variables approach and the Petrin and Train (2010) control function approach to address endogeneity concerns. We find no evidence that algorithmic trading significantly affects the probability of the occurrence of mini flash crashes.