The widespread deployment of autonomous systems in safety-critical environments such as urban air mobility hinges on ensuring reliable, performant, and safe operation under varying environmental conditions. One such approach, value function-based safety filters, minimally modifies a nominal controller to ensure safety. Recent advances leverage offline learned value functions to scale these safety filters to high-dimensional systems. However, these methods assume detailed priors on all possible sources of model mismatch, in the form of disturbances in the environment -- information that is rarely available in real world settings. Even in well-mapped environments like urban canyons or industrial sites, drones encounter complex, spatially-varying disturbances arising from payload-drone interaction, turbulent airflow, and other environmental factors. We introduce SPACE2TIME, which enables safe and adaptive deployment of offline-learned safety filters under unknown, spatially-varying disturbances. The key idea is to reparameterize spatial variations in disturbance as temporal variations, enabling the use of precomputed value functions during online operation. We validate SPACE2TIME on a quadcopter through extensive simulations and hardware experiments, demonstrating significant improvement over baselines.

For decades the strong-field approximation (SFA) has been a theoretical backbone for describing the strong-field related phenomena such as above-threshold ionization (ATI) and high-order harmonic generation, even though it is well-known that it cannot accurately account for the long-range Coulomb interaction between the liberated electron and residual atomic ion. In this paper, we theoretically investigate high-order ATI. We use numerical solutions of the time-dependent Schrödinger equation (TDSE) and an improved SFA that includes electron rescattering. The analysis is performed for atomic anions and neutral atoms exposed to elliptically polarized laser fields. To validate the SFA and test its applicability, we compare both theoretical approaches for various targets and laser field parameters. We also show that the improved SFA in which the final electron plane wave is replaced by the Coulomb distorted plane wave leads to a better agreement with the results obtained using the solutions of the TDSE.

Purpose: Accurate target volume delineation is critical for effective stereotactic radiotherapy (SRT) of brain metastases. This study systematically investigates how MRI sequence selection and the time elapsed after contrast agent (CA) administration affect the apparent metastases volumes, with the goal of optimizing MRI protocols for radiation therapy planning. Materials and Methods: A total of 49 patients with 414 brain metastases were included and randomized into 6 groups with varying imaging sequences (MPRAGE, SPACE, and VIBE) and timepoints after CA administration. Lesions smaller than 0.03 cm3 were excluded due to resolution limitations. Lesion volumes were independently assessed by radiology and radiation oncology specialists, and mean values were analyzed. The effects of MRI sequence and time delay on lesion volume were evaluated using t tests, ANOVA, and multiple linear regression. Results: Both MRI sequence and CA timing significantly influenced measured volumes. On average, SPACE volumes were 20% larger than MPRAGE, and VIBE volumes were 10% larger than SPACE, independent of timing. Lesion volumes increased progressively with time after CA administration at rates of 0.63%, 0.58%, and 0.36% per minute for MPRAGE, SPACE, and VIBE, respectively. Smaller lesions (<1 cm3) showed greater relative intersequence differences, primarily due to variations in visible lesion borders. Conclusions: Both MRI sequence choice and imaging time after CA administration significantly affect the apparent volume of brain metastases in SRT planning. Although SPACE and VIBE sequences enhance small lesion detection, they may also increase border blurring and inter-rater variability. Standardizing protocols to account for these factors is essential for improving delineation accuracy, reducing toxicity risk, and optimizing SRT outcomes.

In today’s fast-paced society, most individuals commute either by personal vehicle or public transportation. User preferences and requirements are crucial, with design playing a significant role. The nature of design should be such that it is both inclusive and assimilative, and its purpose is to propel innovation and progress while also improving the quality of life of the user. That is why a general focus was given to the user-centered design approach while developing vehicles, especially, cabin (cockpit) design. With prioritizing the user activities, it is interesting to explore how users’ experience and behavior vary through the application of different design approaches. Nevertheless, existing literature has significantly overlooked the impact of design approaches on “human activity". Therefore, the main objective of the workshop is to examine the relationships between activity-centered design and user behavior.

BACKGROUND White cord syndrome (WCS) is a rare and extremely serious complication that can occur following spinal decompression procedures for severe mostly cervical spinal stenosis. It is often reported immediately after surgery or several hours to days postoperatively and is identified via a diagnosis of exclusion based on new-onset sudden motor weakness after a decompression procedure. OBSERVATIONS The authors report the illustrative case of a 54-year-old female patient with WCS, who was managed with surgical intervention, corticosteroid therapy, and mean arterial blood pressure support. Additionally, the authors systematically reviewed an additional 27 cases of WCS documented in the literature. LESSONS A relatively favorable clinical outcome was observed in this patient following surgical intervention combined with corticosteroid therapy and mean blood pressure support. Currently, there are no established guidelines for the treatment of WCS; however, in any patient experiencing sudden neurological deterioration after cervical spinal decompressive surgery—especially when a known cause is unidentified—WCS should be considered as a potential diagnosis, and prompt treatment should be initiated to attempt to improve outcomes. https://thejns.org/doi/10.3171/CASE25542

This study examines the role of public procurement in stimulating innovation in the United States, with particular attention to small and medium‐sized enterprises (SMEs). Public procurement of innovation (PPI) is widely regarded as a demand‐side policy instrument that can generate lead markets for emerging technologies, yet its scope and structural dynamics remain underexplored in large economies. To address this gap, we analyze more than 46 million procurement contracts (2007–2021) from USAspending.gov using a text‐mining approach informed by disruptive technology keywords from Bloom et al. We find that innovation‐related contracts constitute only 0.12% of the total, with SMEs securing around 41%. Nonetheless, SMEs face persistent difficulties in winning follow‐on contracts, reflecting resource limitations. Moreover, results reveal an inverted U‐shaped relationship between competition and innovation procurement, indicating that moderate competition fosters innovation most effectively. The study contributes to theory by extending the Resource‐Based View (RBV) to public procurement, demonstrating how resource heterogeneity and immobility shape outcomes in government‐led markets. Practically, we provide policy insights to strengthen SME participation in PPI through targeted support and simplified procedures, thereby advancing both innovation policy and SME competitiveness.

Automated vehicles (AVs) reached technological maturity and will soon arrive on streets as traffic participants. Human traffic participants such as drivers, pedestrians, or cyclists will be increasingly confronted with the presence of AVs within their environment, not necessarily knowing or understanding what to expect and how to interact with them. Although AVs are designed to act safely, effective interaction in mixed traffic scenarios will depend on successful communication, interaction, or even negotiation beyond static rules and regulations. Prosocial behavior, such as yielding one’s right of way, will be needed to resolve unclear traffic situations or foster traffic flow. However, what are the characteristics of such prosocial behavior, and how to measure this not only for automated vehicles but for all road users? Here, we describe a new scale to measure perceived social behavior in urban traffic scenarios. Through an online survey on N = 318 individuals and a validation study, we developed the Situational Prosocial and Aggressive Behavior in Traffic Scale and assessed it psychometrically.

BACKGROUND There is a lack of study on vitamin D and calcium levels in epileptic patients receiving therapy, despite the growing recognition of the importance of bone health in individuals with epilepsy. Associations one statistical method for finding correlations between variables in big datasets is called association rule mining (ARM). This technique finds patterns of common items or events in the data set, including associations. Through the analysis of patient data, including demographics, genetic information, and reactions with previous treatments, ARM can identify harmful drug reactions, possible novel combinations of medicines, and trends which connect particular individual features to treatment outcomes. AIM To investigate the evidence on the effects of anti-epileptic drugs (AEDs) on calcium metabolism and supplementing with vitamin D to help lower the likelihood of bone-related issues using ARM technique. METHODS ARM technique was used to analyze patients’ behavior on calcium metabolism, vitamin D and anti-epileptic medicines. Epileptic sufferers of both sexes who attended neurological outpatient and in patient department clinics were recruited for the study. There were three patient groups: Group 1 received one AED, group 2 received two AEDs, and group 3 received more than two AEDs. The researchers analyzed the alkaline phosphatase, ionized calcium, total calcium, phosphorus, vitamin D levels, or parathyroid hormone values. RESULTS A total of 150 patients, aged 12 years to 60 years, were studied, with 50 in each group (1, 2, and 3). 60% were men, this gender imbalance may affect the study’s findings, as women have different bone metabolism dynamics influenced by hormonal variations, including menopause. The results may not fully capture the distinct effects of AEDs on female patients. A greater equal distribution of women should be the goal of future studies in order to offer a complete comprehension of the metabolic alterations brought on by AEDs. 86 patients had generalized epilepsy, 64 partial. 42% of patients had AEDs for > 5 years. Polytherapy reduced calcium and vitamin D levels compared to mono and dual therapy. Polytherapy elevated alkaline phosphatase and phosphorus levels. CONCLUSION ARM revealed the possible effects of variables like age, gender, and polytherapy on parathyroid hormone levels in individuals taking antiepileptic medication.

BACKGROUND There is a lack of study on vitamin D and calcium levels in epileptic patients receiving therapy, despite the growing recognition of the importance of bone health in individuals with epilepsy. Associations one statistical method for finding correlations between variables in big datasets is called association rule mining (ARM). This technique finds patterns of common items or events in the data set, including associations. Through the analysis of patient data, including demographics, genetic information, and reactions with previous treatments, ARM can identify harmful drug reactions, possible novel combinations of medicines, and trends which connect particular individual features to treatment outcomes. AIM To investigate the evidence on the effects of anti-epileptic drugs (AEDs) on calcium metabolism and supplementing with vitamin D to help lower the likelihood of bone-related issues using ARM technique. METHODS ARM technique was used to analyze patients’ behavior on calcium metabolism, vitamin D and anti-epileptic medicines. Epileptic sufferers of both sexes who attended neurological outpatient and in patient department clinics were recruited for the study. There were three patient groups: Group 1 received one AED, group 2 received two AEDs, and group 3 received more than two AEDs. The researchers analyzed the alkaline phosphatase, ionized calcium, total calcium, phosphorus, vitamin D levels, or parathyroid hormone values. RESULTS A total of 150 patients, aged 12 years to 60 years, were studied, with 50 in each group (1, 2, and 3). 60% were men, this gender imbalance may affect the study’s findings, as women have different bone metabolism dynamics influenced by hormonal variations, including menopause. The results may not fully capture the distinct effects of AEDs on female patients. A greater equal distribution of women should be the goal of future studies in order to offer a complete comprehension of the metabolic alterations brought on by AEDs. 86 patients had generalized epilepsy, 64 partial. 42% of patients had AEDs for > 5 years. Polytherapy reduced calcium and vitamin D levels compared to mono and dual therapy. Polytherapy elevated alkaline phosphatase and phosphorus levels. CONCLUSION ARM revealed the possible effects of variables like age, gender, and polytherapy on parathyroid hormone levels in individuals taking antiepileptic medication.

significant median increase was also observed in proximal (z = -3.408, p < .001) and distal tibial M wave amplitude (z = -3.409, p < .001).

Background: Correct body posture should be at the very top, because it is an essential prerequisite for good health, normal growth and development, and good looks of every student. Inadequate spending of free time leads to the appearance of obesity, improper posture, and the appearance of physical deformities. Aims: This research aims to determine the prevalence of obesity, improper body posture, body deformities, and the way of spending free time among primary school students according to gender. Methods: The research was carried out on a sample of a total of N=1,850 primary school students, of which there were N=989 (53%) male respondents and N=861 (47%) female respondents. Analyzing the results of morphological characteristics, it was determined that boys have a higher body mass index (BMI) than girls. Result: The obtained results are statistically significant at the level of less than 1% (p<0.01), and the results were in favor of girls. Obesity and excessive nutrition are more prevalent in boys than in girls. By measuring the lateral curve of the spinal column, the following results were obtained: 67.24% of boys have improper posture, and 37.52% of girls. Conclusion: Classroom data show children spend substantial free time on electronic devices, especially boys gaming on computers and tablets. Girls more often engage in sports, television viewing, reading, and mobile communication. Preventive action is needed through regular student monitoring, testing, and measurement to track developmental changes and promote healthier lifestyle patterns in school contexts.

The paper deals with a simplified procedure for the assessment of steady-state temperature increase in one-dimensional 3-layer tissue model (composed of skin, fat and muscle) using analytical approach. The solution of a simplified variant of Pennes' bioheat transfer Equation (PBHE) reduces the number of parameters in the parametric analysis, resulting in modified equation that can be solved analytically using the classical theory of ordinary differential equations in each tissue layer. The steady-state temperature distribution in 3-layer tissue model, exposed to an incident time harmonic electromagnetic (EM) field, is governed by the stationary form of the PBHE supplemented by the Robin boundary condition (BC). The presented results are given for the case of a constant and exponentially decreasing power density vs tissue depth. The results show that the obtained solution gives an overestimation of steady-state temperature due to EM radiation compared to other analytical methods.

Decoding how specific neuronal subtypes contribute to brain function requires linking extracellular electrophysiological features to underlying molecular identities, yet reliable in vivo electrophysiological signal classification remains a major challenge for neuroscience and clinical brain-computer interfaces (BCI). Here, we show that pretrained, general-purpose vision-language models (VLMs) can be repurposed as few-shot learners to classify neuronal cell types directly from electrophysiological features, without task-specific fine-tuning. Validated against optogenetically tagged datasets, this approach enables robust and generalizable subtype inference with minimal supervision. Building on this capability, we developed the BCI AI Agent (BCI-Agent), an autonomous AI framework that integrates vision-based cell-type inference, stable neuron tracking, and automated molecular atlas validation with real-time literature synthesis. BCI-Agent addresses three critical challenges for in vivo electrophysiology: (1) accurate, training-free cell-type classification; (2) automated cross-validation of predictions using molecular atlas references and peer-reviewed literature; and (3) embedding molecular identities within stable, low-dimensional neural manifolds for dynamic decoding. In rodent motor-learning tasks, BCI-Agent revealed stable, cell-type-specific neural trajectories across time that uncover previously inaccessible dimensions of neural computation. Additionally, when applied to human Neuropixels recordings–where direct ground-truth labeling is inherently unavailable–BCI-Agent inferred neuronal subtypes and validated them through integration with human single-cell atlases and literature. By enabling scalable, cell-type-specific inference of in vivo electrophysiology, BCI-Agent provides a new approach for dissecting the contributions of distinct neuronal populations to brain function and dysfunction.

Abstract Effective voice education promotes healthy voice use, particularly for kindergarten teachers in demanding environments. This study assessed the effectiveness of a brief, workplace-based voice education program for the preschool teachers. Teachers were quasi-randomly assigned based on work schedules to either the Direct Voice Training Group (N = 31), which received a four-hour face-to-face training session and an educational booklet, or the Educational Booklet Only Group (N = 45). Outcomes were measured using the Vocal Fatigue Index (VFI) and blinded perceptual voice quality assessments via the GRBAS scale at baseline and three months post-intervention. Nonparametric Wilcoxon signed-rank tests assessed statistical significance, with effect sizes (r) calculated. Both groups improved significantly, but the Direct Voice Training Group showed broader improvements, with small to medium effect sizes (r = 0.25–0.38), whereas the Booklet Only Group had limited improvements (r < 0.3). Blinded evaluations confirmed greater benefits for the direct training group. These findings highlight the value of brief, targeted interventions for occupational vocal health, though small to medium effect sizes suggest that more intensive interventions may be required for clinically significant outcomes.