Miracle-dz/UniFAR-FTUs huggingface dataset:
Handedness and 23 Early Life Characteristics in 37,495 Dutch Twins

Abstract In studies of singletons, a range of early-life characteristics have been reported to be associated with handedness, but some of these associations have failed to replicate. We examined associations between 23 early life characteristics with handedness in a large sample of 37,495 5-year-old twins. We considered three definitions of handedness: left-handedness (LH), mixed-handedness (MH), and non-right-handedness (NRH). Our main aim was to test whether the associations with sex, birth weight, gestational age, and season of birth — as reported in singletons — replicate in twins, and to examine twin-specific variables, including zygosity, chorionicity, birth order, and intertwin delivery time. Compared to previously published data from adults born as singletons (7.23%), the prevalence of NRH was higher in both twins (16.19%) and their parents (15.09%). In the twins, LH and NRH were associated with parents’ LH. Male sex and lower gestational age were associated with NRH, and LH was associated with not being breastfed. MH was related to neurodevelopmental delays and higher externalizing problems later in childhood. Other previously reported associations were not replicated, and no twin-specific characteristics were related to handedness. These results emphasize the importance of considering multiple definitions of handedness and indicate a small number of replicated associations across studies.
Early Counseling to Improve Oral Health Behavior in Children with Major Congenital Heart Defects: A Randomized Controlled Trial

Maintaining optimal oral health behavior in children with a congenital heart defect (CHD) is important in managing the risk for caries development and infective endocarditis. The aim of this study was to evaluate the impact of an early and repeat oral health promotion intervention (OHPI) among children with major CHD. Randomized controlled trial including 72 out of 91 children born in Finland April 1, 2017–October 31, 2020 with (a) major CHD potentially included in the criteria of endocarditis prophylaxis or (b) any CHD with surgical repair combined with a chromosomal syndrome. A parallel passive control (C) group of 87 healthy children were recruited at birth. CHD children were randomized 1:1 to intervention (CHD-I) and control (CHD-C) groups. The OHPI included counseling by motivational interviewing, home delivered toothpaste and toothbrushes, and written information, and was provided at baseline, 6, 12, and 18 months of age to CHD-I group. The primary outcome measure at 24 months was child’s oral health behavior (toothbrushing, sugar intake, and dental care contact). The secondary outcome measures were parents’ awareness of the importance of oral health behavior, and oral health behavior as a predictor for child behavior. At 24 months, toothbrushing was performed twice a day in 20/27 (74%) among CHD-I, in 13/30 (43%) among CHD-C (CHD-I vs. CHD-C p = 0.03), and in 37/50 (74%) among healthy comparisons (CHD-C vs. C p = 0.01). Electric toothbrush use was 12/27 (44%) in CHD-I, 5/30 (17%) in CHD-C (CHD-I vs. CHD-C p = 0.04), and 7/50 (14%) in healthy comparison (CHD-C vs. C p = 0.76) children. Among CHD-I, toothbrushing and use of electric toothbrush improved between 12 months and 24 months. Sugar drink intake was more common among CHD-C (CHD-C vs. C p = 0.02), but comparable to CHD-I children. Parental toothbrushing predicted child toothbrushing twice a day. There were no statistical group differences in dental care contact. Children with CHD are at risk for poor oral health behavior. This could be improved with early and repeat oral health promotion parental counseling.
Refugees, trade, and FDI

Humanitarian policies aimed at welcoming forced migrants may yield unexpected economic dividends. This article focuses on the trade and investment links forged by refugees between their countries of resettlement and the origins they fled. We document how such immigrant-links differ in the case of refugees, focusing on why their opportunity sets might differ and the difficulties in establishing economic connections against a backdrop of civil conflict and political unrest. We conclude by discussing a range of policies aimed at engaging refugee diasporas to foster development at refugees’ origins.
Gut microbiota and microbiota-derived metabolites in cardiovascular diseases

Abstract Cardiovascular diseases, including heart failure, coronary artery disease, atherosclerosis, aneurysm, thrombosis, and hypertension, are a great economic burden and threat to human health and are the major cause of death worldwide. Recently, researchers have begun to appreciate the role of microbial ecosystems within the human body in contributing to metabolic and cardiovascular disorders. Accumulating evidence has demonstrated that the gut microbiota is closely associated with the occurrence and development of cardiovascular diseases. The gut microbiota functions as an endocrine organ that secretes bioactive metabolites that participate in the maintenance of cardiovascular homeostasis, and their dysfunction can directly influence the progression of cardiovascular disease. This review summarizes the current literature demonstrating the role of the gut microbiota in the development of cardiovascular diseases. We also highlight the mechanism by which well-documented gut microbiota-derived metabolites, especially trimethylamine N-oxide, short-chain fatty acids, and phenylacetylglutamine, promote or inhibit the pathogenesis of cardiovascular diseases. We also discuss the therapeutic potential of altering the gut microbiota and microbiota-derived metabolites to improve or prevent cardiovascular diseases.
A Case for Synthetic Data in Regulatory Decision‐Making in Europe

Regulators are faced with many challenges surrounding health data usage, including privacy, fragmentation, validity, and generalizability, especially in the European Union, for which synthetic data may provide innovative solutions. Synthetic data, defined as data artificially generated rather than captured in the real world, are increasingly being used for healthcare research purposes as a proxy to real‐world data (RWD). Currently, there are barriers particularly challenging in Europe, where sharing patient's data is strictly regulated, costly, and time‐consuming, causing delays in evidence generation and regulatory approvals. Recent initiatives are encouraging the use of synthetic data in regulatory decision making and health technology assessment to overcome these challenges, but synthetic data have still to overcome realistic obstacles before their adoption by researchers and regulators in Europe. Thus, the emerging use of RWD and synthetic data by pharmaceutical and medical device industries calls regulatory bodies to provide a framework for proper evidence generation and informed regulatory decision making. As the provision of data becomes more ubiquitous in scientific research, so will innovations in artificial intelligence, machine learning, and generation of synthetic data, making the exploration and intricacies of this topic all the more important and timely. In this review, we discuss the potential merits and challenges of synthetic data in the context of decision making in the European regulatory environment. We explore the current uses of synthetic data and ongoing initiatives, the value of synthetic data for regulatory purposes, and realistic barriers to the adoption of synthetic data in healthcare.
Understanding how shared decision‐making approaches and patient aids influence patients with advanced cancer when deciding on palliative treatments and care: A realist review

Patients with advanced incurable cancer face difficult decisions about palliative treatment options towards their end of life. However, they are often not provided with the appropriate information and support that is needed to make informed decisions. This review aimed to identify contexts and mechanisms associated with communication tools, patient decision‐aids and shared decision‐making (SDM) approaches that influence patient outcomes.
Evaluating Surgical Cervical Arthrodesis With a Novel MRI Grading Score

Study Design: This was a single-institution retrospective study. Objective: Evaluate a magnetic resonance imaging (MRI)-scoring system to differentiate arthrodesis from pseudoarthrosis following anterior cervical discectomy and fusion. Summary of Background Data: Diagnostic workup following fusion surgery often includes MRI to evaluate neural structures and computed tomography (CT) and/or dynamic x-rays to evaluate instrumentation and arthrodesis. The use of MRI alone for these evaluations would protect patients from harmful CT and x-ray ionizing radiation. Methods: Neurosurgical attending evaluated CTs for arthrodesis or pseudoarthrosis. Blinded neuroradiology attending and neurosurgery senior resident evaluated independent T1 and T2 region of interest (ROI) signal intensity over instrumented disk space. Cerebral spinal fluid (CSF) at the cisterna magnum and distal adjacent uninstrumented vertebral body (VB) were also calculated. ROIinterspace/ROICSF and ROIinterspace/ROIVB quotients were used to create T1- and T2-interspace interbody scores (IIS). Results: Study population (n=64 patients, 50% female) with a mean age of 51.72 years and 109 instrumented levels with 45 fused levels (41.3%) were included. T1-weighted MRI, median T1-IISCSF for arthrodesis was 176.20 versus 130.92 for pseudoarthrosis (P<0.0001), T1-IISVB for arthrodesis was 68.52 and pseudoarthrosis was 52.71 (P<0.0001). T2-weighted MRI, median T2-IISCSF for arthrodesis was 27.72 and 14.21 for pseudoarthrosis (P<0.0001), while T2-IISVB for arthrodesis was 67.90 and 41.02 for pseudoarthrosis (P<0.0001). The greatest univariable discriminative capability for arthrodesis via AUROC was T1-IISVB (0.7743). Conclusion: We describe a novel MRI scoring system that may help determine arthrodesis versus pseudoarthrosis following anterior cervical discectomy and fusion. Postoperative symptomatic patients may only require MRI, which would protect patients from ionizing radiation. Level of Evidence: Level IV.
Post -COVID -19 rhino -orbito- cerebral mucormycosis -a clinicomycological study from North India.

The second wave of Coronavirus Disease 2019 (COVID-19), during the early 2021, lead to devastating outbreak of mucormycosis in India. This study aimed to determine the etiology, clinical features, co morbidities and risk factors of rhino -orbito -cerebral mucormycosis (ROCM) and antifungal susceptibility pattern for the isolates. The study included all suspected cases of ROCM in post COVID- 19 patients attending hospital from May to December 2021. 70 patients were diagnosed with mucormycosis during the study period. The commonest presentation was rhino-orbital and rhino-orbito-cerebral in 35.7% of cases each. Diabetes mellitus (DM) was the commonest associated risk factor in 95.7% of all patients while 78.5% of the patients were treated with corticosteroids in the recent past, and 25.7% presented with active COVID-19 pneumonia. The commonest isolate was Rhizopus arrhizus n = 14, followed by Aspergillus flavus n = 16, Aspergillus fumigatus n = 4, Aspergillus niger n = 3, Fusarium oxysporum n = 1, and Apophysomyces variabilis n = 1. Fungal species identification was done by phenotypic methods for all the isolates and DNA sequence analysis of 18 isolates, and antifungal susceptibility testing of 30 isolates was performed by commercially prepared HiMIC plate (HiMedia, Mumbai, India) using broth microdilution for amphotericin B, isavuconazole, itraconazole, voriconazole and posaconazole. The MIC50 and MIC90 of amphotericin B for R. arrhizus strains were 0.25 and 4 μg/ml; and the MIC50 and MIC90 results for itraconazole, posaconazole, and isavuconazole were 8 and 8, 2 and 2, and 2 and 8 μg/ml, respectively. In vitro data showed that amphotericin B was the most effective antifungal against most species. The commercially available ready to use MIC plates are user-friendly for performing antifungal susceptibility which may be useful in choosing appropriate regimens and monitor emerging resistance.
Using random forest machine learning on data from a large, representative cohort of the general population improves clinical spirometry references

Spirometry is associated with several diagnostic difficulties, and as a result, misdiagnosis of chronic obstructive pulmonary disease (COPD) occurs. This study aims to investigate how random forest (RF) can be used to improve the existing clinical FVC and FEV1 reference values in a large and representative cohort of the general population of the US without known lung disease.
University of Birmingham Efficient adaptive algorithms for elliptic PDEs with random data

We present a novel adaptive algorithm implementing the stochastic Galerkin ﬁnite element method for numerical solution of elliptic PDE problems with correlated random data. The algorithm employs a hierarchical a posteriori error estimation strategy which also provides eﬀective estimates of the error reduction for enhanced approximations. These error reduction indicators are used in the algorithm to perform a balanced adaptive reﬁnement of spatial and parametric components of Galerkin approximations. The results of numerical tests demonstrating the eﬃciency of the algo-rithm for three representative PDEs with random coeﬃcients are reported. The software used for numerical experiments is available online.
Robust dynamic surface trajectory tracking control for a quadrotor UAV via extended state observer

In this paper, we present an extended state observer–based robust dynamic surface trajectory tracking controller for a quadrotor unmanned aerial vehicle subject to parametric uncertainties and external disturbances. First, the original cascaded dynamics of a quadrotor unmanned aerial vehicle is formulated in a strict form with lumped disturbances to facilitate the backstepping design. Second, based on the separate outer‐ and inner‐loop control methodologies, the extended state observers are constructed to online estimate the unmeasurable velocity states and lumped disturbances existed in translational and rotational dynamics, respectively. Third, to overcome the problem of “explosion of complexity” inherent in backstepping control, the technique of dynamic surface control is utilized for trajectory tracking and attitude stabilization, and with the velocity and disturbance estimates incorporated into the dynamic surface control, a robust dynamic surface flight controller that guarantees asymptotic tracking in the presence of lumped disturbances is synthesized. In addition, the stability analysis is given, showing that the present robust controller can ensure the ultimate boundedness of all signals in the closed‐loop system and make the tracking errors arbitrarily small. Finally, comparisons and extensive simulations under different flight scenarios are performed to validate the effectiveness and superiority of the proposed scheme in accurate tracking performance and enhanced antidisturbance capability.
Distribution, cellular localization, and colocalization of several peptide neurotransmitters in the central nervous system of Aplysia

Neuropeptides are widely used as neurotransmitters in vertebrates and invertebrates. In vertebrates, a detailed understanding of their functions as transmitters has been hampered by the complexity of the nervous system. The marine mollusk Aplysia, with a simpler nervous system and many large, identified neurons, presents several advantages for addressing this question and has been used to examine the roles of tens of peptides in behavior. To screen for other peptides that might also play roles in behavior, we observed immunoreactivity in individual neurons in the central nervous system of adult Aplysia with antisera raised against the Aplysia peptide FMRFamide and two mammalian peptides that are also found in Aplysia, cholecystokinin (CCK) and neuropeptide Y (NPY), as well as serotonin (5HT). In addition, we observed staining of individual neurons with antisera raised against mammalian somatostatin (SOM) and peptide histidine isoleucine (PHI). However, genomic analysis has shown that these two peptides are not expressed in the Aplysia nervous system, and we have therefore labeled the unknown peptides stained by these two antibodies as XSOM and XPHI. There was an area at the anterior end of the cerebral ganglion that had staining by antisera raised against many different transmitters, suggesting that this may be a modulatory region of the nervous system. There was also staining for XSOM and, in some cases, FMRFamide in the bag cell cluster of the abdominal ganglion. In addition, these and other studies have revealed a fairly high degree of colocalization of different neuropeptides in individual neurons, suggesting that the peptides do not just act independently but can also interact in different combinations to produce complex functions. The simple nervous system of Aplysia is advantageous for further testing these ideas.
Frequency-Based Motion Representation for Video Generative Adversarial Networks

Videos contain motions of various speeds. For example, the motions of one’s head and mouth differ in terms of speed — the head being relatively stable and the mouth moving rapidly as one speaks. Despite its diverse nature, previous video GANs generate video based on a single unified motion representation without considering the aspect of speed. In this paper, we propose a frequency-based motion representation for video GANs to realize the concept of speed in video generation process. In detail, we represent motions as continuous sinusoidal signals of various frequencies by introducing a coordinate-based motion generator. We show, in that case, frequency is highly related to the speed of motion. Based on this observation, we present frequency-aware weight modulation that enables manipulation of motions within a specific range of speed, which could not be achieved with the previous techniques. Extensive experiments validate that the proposed method outperforms state-of-the-art video GANs in terms of generation quality by its capability to model various speed of motions. Furthermore, we also show that our temporally continuous representation enables to further synthesize intermediate and future frames of generated videos.
การเปรียบเทียบวิธีการพยากรณ์สำหรับความต้องการใช้พลังงานไฟฟ้าในจังหวัดนครพนมการเปรียบเทียบวิธีการพยากรณ์สำหรับความต้องการใช้พลังงานไฟฟ้าในจังหวัดนครพนม/A Comparison of the Forecasting Method for Electric Energy Demand in Nakhonphanom Province

งานวจยนมวตถประสงคเพอศกษาและเปรยบเทยบวธการพยากรณ สำหรบการพยากรณความตองการใชพลงงานไฟฟาในจงหวดนครพนม โดยใชขอมลจากการไฟฟาฝายผลตจงหวดนครพนม ตงแตเดอนมกราคม 2554 ถงเดอนกนยายน 2559 จำนวน 69 คา โดยแบงขอมลออกเปน 2 ชด ขอมลชดท 1 ตงแตเดอนมกราคม 2554 ถงเดอนธนวาคม 2558 จำนวน 60 คา สำหรบการเปรยบเทยบหาวธการพยากรณทเหมาะสมทสด โดยใชเกณฑพจารณาคาเฉลยความคลาดเคลอนสมบรณ (MAD) และคาเฉลยเปอรเซนตความคลาดเคลอนสมบรณ (MAPE) ทตำทสด โดยงานวจยนใชวธการพยากรณ 6 วธคอ 1) วธคาเฉลยเคลอนท 2) วธแนวโนมเชงเสน 3)วธปรบเรยบเอกซโพเนนเชยลอยางงาย 4) วธปรบเรยบเอกซโพเนนเชยลแบบโฮลท 5) วธปรบเรยบเอกซโพเนนเชยลแบบวนเทอร 6) วธแยกสวนประกอบ จากนนจงเลอกวธการทพยากรณทเหมาะสมทสด มาคำนวณหาชวงการพยากรณลวงหนากบขอมลชดท 2 คอขอมลตงแตเดอนมกราคม 2559 ถงเดอนกนยายน 2559 จำนวน 9 คาโดยใชเกณฑพจารณาคาเฉลยเปอรเซนตความคลาดเคลอนสมบรณ (MAPE) ทตำทสด ผลการศกษาพบวา วธการพยากรณทมความเหมาะสมทสดคอการพยากรณโดยวธแยกสวนประกอบ จากรปแบบดงกลาว นำมาคำนวณหาชวงพยากรณลวงหนา 3 เดอน 6 เดอน และ 9 เดอน พบวาวธนเหมาะสำหรบการพยากรณลวงหนา 9 เดอน The purpose of this research was to study and compare the forecasting methods for electric energy demand in Nakhonphanom province. The data was gathered from Provincial Electricity Authority of Nakhonphanom during January, 2011 to September, 2016 of 69 values which were used and separated into 2 groups. The first group contained 60 values from January, 2011 to December, 2015 for comparing and finding the most suitable forecasting method via criteria of the lowest Mean Absolute Deviation (MAD) and Mean Absolute Percent Error (MAPE). There were 6 forecasting methods: 1) Moving average, 2) Trend analysis, 3) Single exponential smoothing, 4) Double exponential smoothing (Holt), 5) Triple exponential smoothing (Winter), and 6) Decomposition. Then the selected suitable method was used to determine the most suitable forecasting period by the second group which contained 9 values from January, 2016 to September, 2016. The lowest MAPE was used as the criteria of each period. The result indicated that decomposition method was the best method. From that method, it was implemented for forecasting 3, 6 and 9 months and it showed that the method was suitable for advance 9 months.
Venetoclax Abrogates the Prognostic Impact of Splicing Factor Gene Mutations in Newly Diagnosed Acute Myeloid Leukemia.

Mutations in splicing factor (SF) genes SRSF2, U2AF1, SF3B1 and ZRSR2 are now classified as adverse risk (AR) in the European LeukemiaNet 2022 risk stratification for acute myeloid leukemia (AML). The prognostic impact of SF mutations in AML has been predominantly derived from younger patients treated with intensive (INT) therapy. We evaluated 994 patients with newly diagnosed AML, including 266 (27%) with a SFmut. Median age was 67 years overall, with SFmut pts older at 72 years. SRSF2 (=140, 53%) was the most common amongst SFmut. Amongst patients treated with INT therapy, median relapse-free survival (RFS) (9.6 versus 21.4 months, p=0.04) and overall survival (OS)(15.9 versus 26.7 months, p=0.06) were shorter for the SFmut compared to SFwt patients, however this significance abrogated when evaluating patients who received venetoclax with INT therapy (RFS 15.4 versus 20.3 months, p=0.36 and OS 19.6 versus 30.7 months, p=0.98). In patients treated with low-intensity (LI) therapy, median RFS (9.3 versus 7.7 months, p=0.35) and OS (12.3 versus 8.5 months, p=0.14) were similar for SFmut and SFwt patients, and outcomes improved in all groups with the receipt of venetoclax. On multivariate analysis, SFmut did not affect the hazards of relapse and death for INT therapy arm, arms but reduced both these hazards in the LI therapy arm. In this large AML dataset with >60% of patients receiving venetoclax with LI/ INT therapy, SFmut did not demonstrate independent prognostic impact. Newer prognostic models that consider LI therapy and the use of venetoclax amongst other factors are warranted.
Performance determinants and leg kinematics in the BMX supercross start

In competitive BMX racing, a fast start, that is, the shortest possible elapsed time and the highest possible instantaneous velocity at the end of the starting phase, is crucial for obtaining a favourable position in the middle portion of the race and the best possible final ranking. This study aimed first to evaluate several influencing factors for their relative importance in determining starting performance in competitive BMX racers. Also, this study describes basic leg kinematics during the first few pedal strokes of the starting phase. Subjects performed practice starts on a supercross ramp while various kinematic and kinetic parameters were obtained using a modified powermeter crank and a 3-d motion capture system. Â Data were analyzed with linear regression with starting performance as the output. The results show that an early turnaround during the preparation maneuver (countermovement) prior to the gat drop and a powerful first pedal stroke, with both a high torque and equivalent cadence, have the most influence on overall starting performance. End velocity is also related to attained peak cadence and the torque at peak cadence. Regarding leg kinematics, extension velocities are similar to ballistic jumps with relatively high loads. Thus, BMX racers should focus technical training on a quick and early turnaround in the preparation maneuver and strength training should be focused on developing strength and power at relatively high loads.