Suwa Red Cross Hospital

Systematic effects can hinder the sought-after detection of primordial gravitational waves, impacting the reconstruction of the B-mode polarization signal which they generate in the cosmic microwave background (CMB). In this work, we study the impact of an imperfect knowledge of the instrument bandpasses on the estimate of the tensor-to-scalar ratio r in the context of the next-generation LiteBIRD satellite. We develop a pipeline to integrate over the bandpass transmission in both the time-ordered data (TOD) and the map-making processing steps. We introduce the systematic effect by having a mismatch between the “real”, high resolution bandpass τ, entering the TOD, and the estimated one τs , used in the map-making. We focus on two aspects: the effect of degrading the τs resolution, and the addition of a Gaussian error σ to τs . To reduce the computational load of the analysis, the two effects are explored separately, for three representative LiteBIRD channels (40 GHz, 140 GHz and 402 GHz) and for three bandpass shapes. Computing the amount of bias on r, Δr, caused by these effects on a single channel, we find that a resolution ≲ 1.5 GHz and σ ≲ 0.0089 do not exceed the LiteBIRD budget allocation per systematic effect, Δr < 6.5 × 10-6. We then check that propagating separately the uncertainties due to a resolution of 1 GHz and a measurement error with σ = 0.0089 in all LiteBIRD frequency channels, for the most pessimistic bandpass shape of the three considered, still produces a Δr < 6.5 × 10-6. This is done both with the simple deprojection approach and with a blind component separation technique, the Needlet Internal Linear Combination (NILC). Due to the effectiveness of NILC in cleaning the systematic residuals, we have tested that the requirement on σ can be relaxed to σ ≲ 0.05.

The rapid growth of internet-based activities has led to an increase in cyber threats, particularly in the form of malicious URLs. Detecting these URLs is crucial for user safety. As the source of URL sharing can be in any form of digital media to popular social networks like Facebook, WhatsApp, Viber, Instagram. The research thoroughly explores the use of machine learning techniques such as Random Forest, Support Vector Machines, and Artificial Neural Networks for detecting these malicious URLs. This study employs a Kaggle dataset containing labeled URLs, focusing on extracting relevant features using only lexical-based features. Experimental results show promising outcomes for all three algorithms, indicating their ability in identifying and categorizing malicious URLs. In particular, the ANN algorithm outperforms SVM and RF by achieving an accuracy of $98.97 \%$ in detection. This study aids in enhancing the security of digital systems and protecting individuals from potential cyber dangers associated with harmful URLs.

ObjectiveTo investigate the effect of headaches on women’s pregnancy plans and fertility intentions.MethodsWe prospectively performed a school-based online survey for students’ parents in Suwa city, Japan, in 2023. We asked their age, sex, the number of children, the presence of headache attacks, the use of acute and prophylactic medications, monthly headache days (MHD), monthly acute medication intake days (AMD), headache impact test-6 (HIT-6), and whether or not headaches worsen during menstruation. We also examined headache’s effect on pregnancy plans and asked about how headaches would affect pregnancy, the ability to raise a child, and the child’s health.Of 5558 students' households, we retrieved 1142 (20.1%) answers, and 717 (12.9%) responses from parents with headaches.ResultsOf 5558 students’ households, we retrieved 1142 (20.1%) answers, and 717 (12.9%) responses from parents with headaches were finally analyzed. The median (first quartile-third quartile) age was 43 (37–46) years, and 653 (91.1%) were female. Median MHD, AMD, and HIT-6 were 3 (1–6), 3 (1.5-6), and 62 (58–65), respectively. Twenty-four (3.3%) used prophylactic medications and 562 (78.4%) used acute medications for headache attacks. The median number of children was 2 (1–2). Avoid pregnancy group consisted of 39/717 (5.4%) respondents. They were younger (median 39 years; first quartile-third quartile 33–42 years), with more respondents with headaches worsening during menstruation (28/35; 80.0%), with acute medication use (36/39; 92.3%), and had more MHD (5; 3–10), more AMD (5; 2–11), and high HIT-6 score (66; 60–67), compared to the no impact group. They tended to think that headaches would be worse during pregnancy (16/39; 41.0%) and that headaches negatively affect pregnancy (28/39; 71.8%), raising a child (20/39; 51.3%), and the child’s development (31/39; 79.5%) and risk of having a headache (28/39; 71.8%) compared to the no impact group.ConclusionsSome of the respondents avoided pregnancy because of their headaches. Those in avoid pregnancy group had severe headaches and felt that headaches negatively affected family planning.Supplementary InformationThe online version contains supplementary material available at 10.1186/s10194-025-02102-3.

We aimed to clarify the clinical characteristics and outcomes of patients with in-hospital onset ischemic stroke (IOS) compared with those in patients with community-onset ischemic stroke (COS). Patients from the Japan Stroke Data Bank, a hospital-based multicenter prospective registry, who were diagnosed with acute ischemic stroke (AIS) within 24 h of onset between January 2001 and December 2020 were included in this study. We assessed favorable outcomes at discharge corresponding to a modified Rankin Scale (mRS) score of 0-2, unfavorable outcomes corresponding to an mRS score of 5-6, and mortality. We also examined trends in these outcomes at 4-year intervals over a period of 20 years. Of the 100,865 patients analyzed, 2979 had IOS (1416 women, mean age 77 ± 12 years) and were older than those with COS (n = 97,886; 39,110 women, mean age 74 ± 12 years). Multivariate analysis revealed that younger age, higher premorbid mRS score, absence of stroke history, normotension, congestive heart failure, coronary artery disease, chronic kidney disease, liver disease, malignancy, tendency to bleed, and cardioembolic stroke were positively associated with IOS. Compared with COS, IOS was inversely associated with a favorable outcome (42.1% vs 64.8%, adjusted odds ratio [aOR] 0.72 [95% confidence interval (CI) 0.63-0.82]), positively associated with an unfavorable outcome (mRS 5-6 at discharge; 34.3% vs 15.5%, aOR 1.31 [95% CI 1.16-1.48]), and mortality (11.8% vs 4.6%, aOR 1.59 [95% CI 1.37-1.84]). Over 20 years, the mortality rate significantly decreased in both patients with IOS and COS (p < 0.01 both). IOS is associated with unfavorable outcomes and higher mortality rates during acute hospitalization. The mortality rates in patients with IOS decreased over time, similar to those observed in patients with COS.

The detection of primordial B modes of the cosmic microwave background (CMB) could provide information about the early stages of the Universe's evolution. The faintness of this signal requires exquisite calibration accuracy and control of instrumental systematic effects which otherwise could bias the measurements. In this work, we study the impact of an imperfect relative polarisation gain calibration on the recovered value of the tensor-to-scalar ratio r for the LiteBIRD experiment, through the application of the blind Needlet Internal Linear Combination (NILC) foreground-cleaning method. We derive requirements on the relative calibration accuracy of the overall polarisation gain (Δgν ) for each LiteBIRD frequency channel. Our results show that minimum variance techniques, as NILC, are less sensitive to systematic gain calibration uncertainties compared to a parametric approach, if the latter is not equipped with a proper modelling of these instrumental effects. In this study, the most stringent requirements are found in the channels where the CMB signal is relatively brighter, with the tightest constraints at 166 GHz (Δgν ≈ 0.16%). This differs from the outcome of an analogous analysis performed with a parametric method, where the tightest requirements are obtained for the foreground-dominated channels. Gain calibration uncertainties, corresponding to the derived requirements, are then simultaneously propagated into all frequency channels. By doing so, we find that the overall impact on estimated r is lower than the total gain systematic budget for LiteBIRD approximately by a factor 5, due to the correlations of the impacts of gain calibration uncertainties in different frequency channels. In order to decouple the systematic effect from the specific choice of the model, we derive the requirements assuming constant spectral parameters for the foreground emission. To assess the robustness of the obtained results against more realistic scenarios, we repeat the analysis assuming sky models of intermediate and high complexity. In these further cases, we adopt an optimised NILC pipeline, called the Multi-Clustering NILC (MC-NILC). We find that the impact of gain calibration uncertainties on r is lower than the LiteBIRD gain systematics budget for the intermediate-complexity sky model. For the high-complexity case, instead, it would be necessary to tighten the requirements by a factor 1.8.