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.

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.

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.

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.

Based on an early 2020s survey of 3,500 police officers from nine countries, this paper explores perceived community and police adherence to the COVID-19 regulations. We propose that both public and police perceived adherence with the COVID-19 rules are related not only to individual-level factors (e.g., gender, concern for own health) but also to country-level factors (e.g., quality of governance, protection of citizens' rights). Our findings reveal that individual-level factors, such as the concerns for personal and family health, were strong and consistent predictors of perceived community and police adherence. While misinformation about the COVID-19 pandemic was associated with the perceived community adherence, it was not related to the perceived police adherence. Moreover, country-level factors, such as the stringency of COVID-19 rules and regulations and the protection of citizens' rights, were also significantly related to both perceived community and police adherence.

This paper analyses the key aspects of the operation of geroler hydraulic motors, widely used rotary hydraulic motors. The focus is on understanding their performance, efficiency and durability in different working conditions. The work includes a theoretical analysis of the principles of work, supported by modelling. Furthermore, experimental tests conducted to characterize the motors in terms of torque, speed, flow and efficiency are considered. Special attention is paid to the analysis of factors that influence the wear of internal components. The results of the analysis provide deeper insight into the behaviour of geroler hydraulic motors, identify areas for potential improvements in design and application and for optimizing their operation and extending their service life in various industrial and mobile applications. In conclusion, the work contributes to a better understanding of hydraulic motors, which is crucial for engineers and technicians involved in the design, application and maintenance of hydraulic systems.

The original serial implementation of the segmentation algorithm exhibits suboptimal performance, motivating a systematic optimization effort without compromising accuracy.To analyze the unoptimized serial code and apply iterative code and compiler optimizations while preserving segmentation accuracy.A multi‐stage optimization process was employed: Initial algorithm profiling to identify bottlenecks. Iterative application of static code transformations. Integration of compiler‐level optimizations at each stage.Performance testing demonstrates substantial speedups: 6x to 8x improvement over the original implementation, depending on optimization stage. Parallelization in the final step further enhances throughput without sacrificing correctness.Systematic, profile‐guided optimization by combining code refactoring and compiler tuning yields significant performance gains. The approach maintains accuracy while enabling efficient parallelization, offering a scalable template for optimizing similar compute‐intensive algorithms.

The third-order difference equation yn+1=a1yn21+yn2+a2yn−121+yn−12+a3yn−221+yn−22, as a potential discrete time model of population dynamics with three generation involved, is studied. The parts of the basins of attraction of three equilibrium points that this equation admits are described. Some results about period-two and period-three solutions have been established.

Per- and polyfluoroalkyl substances (PFAS) are ubiquitous environmental pollutants that pose potential risks to ecosystems and human health. Prior to mass spectrometric analysis of environmental samples, it is necessary to separate PFAS from compounds that can cause ion suppression and compromise analyte identification and quantification accuracy. Although liquid chromatography-mass spectrometry (LC-MS) is the gold standard for PFAS trace analysis, some PFAS species still coelute in the LC dimension and could benefit from an orthogonal dimension of separation. Moreover, an additional orthogonal dimension of separation could potentially aid in the identification of unknown fluorinated species (e.g., those identified within a specified mass-defect range). Here, we investigate the sequential use of LC and differential mobility spectrometry (DMS) separation to analyze 34 PFAS species. Upon incorporating DMS in a two-dimensional (2D) separation scheme, we observed baseline resolution of 29 compounds in the 2D LC × DMS space, with partial resolution of the remaining five. In comparison, only five PFAS compounds were baseline-resolved in 1D LC experiments. Because DMS measurements can be acquired in milliseconds, targeted 2D LC × DMS-MS2 analyses operate on the same time scale as LC-MS2 analysis. However, the limits of quantitation for PFAS using the 2D LC × DMS-MS2 method are slightly higher than those achieved by the state-of-the-art LC-MS2 method owing to ion fragmentation within the energetic DMS environment. Nevertheless, distinct trends observed in the 2D separation space for the various PFAS subclasses will facilitate analyte identification of unknown species in future nontargeted analyses. Finally, we assessed the feasibility of our method for quantifying PFAS in a series of wastewater samples obtained from a Southern Ontario wastewater treatment plant. We were successful in quantifying PFOS, although the concentrations determined were consistently higher than those measured with LC-MS2.

Approximately 5–10% of patients with acute ischemic stroke (AIS) have known active cancer. These patients are at high risk for both recurrent AIS and major bleeding. The optimal antithrombotic strategy for cancer-related stroke is uncertain. This study compared clinical outcomes among patients with cancer-related stroke treated with anticoagulant versus antiplatelet therapy for secondary prevention.We identified consecutive patients with AIS and active cancer hospitalized at our comprehensive stroke center from 2015 through 2020. Patients with cardioembolic mechanisms were excluded. We used Cox regression and inverse probability of treatment weighting (IPTW) analyses to evaluate the associations between type of antithrombotic therapy at discharge (anticoagulant versus antiplatelet therapy) and the main outcomes of 1-year mortality and long-term recurrent AIS.Among 5,012 AIS patients, 306 had active cancer. After applying study eligibility criteria, we analyzed 135 patients (median age 72 years; 44% women), of whom 58 (43%) were treated with anticoagulant and 77 (57%) with antiplatelet therapy. The median follow-up time was 495 days (IQR, 57–1,029). Patients treated with anticoagulants, compared to patients treated with antiplatelet therapy, were younger (median 69 versus 75 years), had more metastatic disease (72% versus 41%), and higher median baseline D-dimer levels (median 8,536 μg/L versus 1,010 μg/L). Anticoagulant versus antiplatelet therapy was associated with similar risks of 1-year mortality (adjusted hazard ratio [aHR], 0.76; 95% confidence interval [CI], 0.36–1.63) and long-term recurrent AIS (aHR 0.49; 95% CI 0.08–2.83). The IPTW analyses for 1-year mortality confirmed the results of the main analyses (HR 0.82; 95%CI: 0.39–1.72, p = 0.61).Factors associated with anticoagulant use in patients with cancer-related stroke include younger age, more advanced cancer, and elevated D-dimer. Similar outcomes were seen with anticoagulant versus antiplatelet therapy in these patients highlighting the need for future randomized trials to determine the preferred antithrombotic strategy.

Introduction: Periarthritis humeroscapularis (PHS) is an inflammatory reaction of the muscle tendons of the shoulder joint and other adjacent tissues of the shoulder joint. The main clinical signs are pain and limitation of mobility, which endangers the daily life activities. The aim of this study is to determine the effectiveness of rehabilitation in reducing the pain and the effectiveness of rehabilitation in improving the daily life activities of respondents with PHS. Methods: This prospective, pre-post study, conducted from May to September 2023, included subjects of both sexes, different age groups, and different occupations, who were part of the rehabilitation program. The data were collected by filling out a questionnaires of the general data of the respondents and a the American Shoulder and Elbow Surgeon Score (ASES) questionnaire on activities of daily life and intensity of pain in the shoulder before and after the rehabilitation program. The rehabilitation program lasted an average of 14 days and included the following physical procedures: Electrotherapy, ultrasound, kinesitherapy, cryotherapy, short-wave diathermy, and manual massage. Results: Comparison of the average pain score on an ASES pain scale of 1-10 shows that the respondents rated pain with an average score of 7.32 before the treatment and with an average score of 2.14 after the treatment. The average scores on the activities of daily living subscale of the ASES questionnaire were worse before the treatment and amounted to 20.72 ± 10.46 (range 3.33-40.0) compared to the scores after the treatment when they averaged 40.95 ± 7.46 (range 21.67-50). The average total score on the ASES scale before the treatment was 34.10 ± 13.93 (range 8.33-58.33), and after the treatment, it was 80.27 ± 14.7 (range 48.33-100.0). Conclusion: The rehabilitation showed statistically significant improvement in the average score on the ASES subscales of pain and daily life activities.

The communal culture of traditional societies fundamentally contrasts with the individualistic framework of intellectual property rights (IPR). Indigenous communities prioritize collective interests without negating individual rights. This study aims to examine and analyze the optimization of traditional knowledge protection as an effort to improve the welfare of communal societies. The research employs a normative juridical method by reviewing statutory regulations and related legal instruments. The findings reveal that communal intellectual property is recognized under both international and national legal frameworks. National regulations require each region to conduct an inventory of community intellectual property; however, public awareness of its importance remains limited. Therefore, renewed strategies are needed to ensure that communities fully understand the economic, social, and cultural value of their traditional knowledge. Local governments play a crucial role in disseminating information and implementing inventory programs through regional regulations. Furthermore, the development of traditional knowledge–based products can be advanced to the industrialization stage through Micro, Small, and Medium Enterprises (MSMEs), thereby supporting the welfare of indigenous peoples. The ideal model of local government intellectual property protection is to guarantee community ownership rights while ensuring a fair profit-sharing mechanism with third parties.