Penerapan Strategi at-Ta'bir al-Mushawwar dalam Meningkatkan Minat Belajar Bahasa Arab dan Mahāratul Kalam Peserta Didik Kelas X MA al-Khairāt Gentuma Raya Kab. Gorontalo Utara

Dasil hasil analisis data terbukti bahwa strategi at-Ta’bir al-Mushawwar dapat meningkatkan minat dan mahāratul kalam peserta didik kelas eksperimen dilihat dari rata-rata hasil pre-tes kelas eksperimen 55.75 sebelum diberikan perlakuan, post-test kelas eksperimen 84.00 setelah diberikan perlakuan. Dan strategi at-Ta’bir al-Ara alRaisiyyah sama-sama dapat meningkatkan minat dan mahāratul kalam peserta didik dilihat dari rata-rata hasil pre-tes kelas kontrol 55.5 sebelum diberikan perlakuan dan post-tes kelas kontrol 80.25 setelah diberikan perlakuan. Berdasarkan perhitungan menggunakan rumus Uji T beda, ditemukan minat belajar bahasa Arab peserta didik diperoleh nilai Thitung 1.007 < Ttabel 2021. Maka Ho1, X MIA 2 diterima dan H1 ditolak, yang berarti tidak ada perbedaan antara kelas yang diterapkan dan kelas yang tidak diterapkan strategi at-Ta’bir al-Mushawwar. Mahāratul kalam peserta didik diperoleh nilai Thitung 1.757 < Ttabel 2021. Dari hasil perbandingan, nilai Thitung < Ttabel maka Ho diterima dan H1 ditolak, yang berarti tidak ada perbedaan antara kelas yang diterapkan dan kelas yang tidak diterapkan strategi at-Ta’bir al-Mushawwar. Strategi at-Tabir al-Mushawwar dan strategi at-Ta’bir al-Ara al-Raisiyyah dalam meningkatkan minat belajar bahasa Arab dan mahāratul kalam peserta didik kelas X MA al-Khairaat Gentuma Raya dapat diterapkan dan dipertahankan karena dapat membantu guru dan peserta didik dalam proses pembelajaran khususnya bidang studi bahasa Arab

Machine Learning for the Prediction of Converged Energies from Ab Initio Nuclear Structure Calculations

The prediction of nuclear observables beyond the finite model spaces that are accessible through modern ab initio methods, such as the no-core shell model, pose a challenging task in nuclear structure theory. It requires reliable tools for the extrapolation of observables to infinite many-body Hilbert spaces along with reliable uncertainty estimates. In this work we present a universal machine learning tool capable of capturing observable-specific convergence patterns independent of nucleus and interaction. We show that, once trained on few-body systems, artificial neural networks can produce accurate predictions for a broad range of light nuclei. In particular, we discuss neural-network predictions of ground-state energies from no-core shell model calculations for 6Li, 12C and 16O based on training data for 2H, 3H and 4He and compare them to classical extrapolations.Comment: 7 pages, 5 figures, 1 tabl

Dynamical analysis of extreme precipitation in the US northeast based on large-scale meteorological patterns

This is the author accepted manuscript. The final version is available from Springer via the DOI in this record.Previous work has identified six large-scale meteorological patterns (LSMPs) of dynamic tropopause height associated with extreme precipitation over the Northeast US, with extreme precipitation defined as the top 1% of daily station precipitation. Here, we examine the three-dimensional structure of the tropopause LSMPs in terms of circulation and factors relevant to precipitation, including moisture, stability, and synoptic mechanisms associated with lifting. Within each pattern, the link between the different factors and extreme precipitation is further investigated by comparing the relative strength of the factors between days with and without the occurrence of extreme precipitation. The six tropopause LSMPs include two ridge patterns, two eastern US troughs, and two troughs centered over the Ohio Valley, with a strong seasonality associated with each pattern. Extreme precipitation in the ridge patterns is associated with both convective mechanisms (instability combined with moisture transport from the Great Lakes and Western Atlantic) and synoptic forcing related to Great Lakes storm tracks and embedded shortwaves. Extreme precipitation associated with eastern US troughs involves intense southerly moisture transport and strong quasi-geostrophic forcing of vertical velocity. Ohio Valley troughs are associated with warm fronts and intense warm conveyor belts that deliver large amounts of moisture ahead of storms, but little direct quasi-geostrophic forcing. Factors that show the largest difference between days with and without extreme precipitation include integrated moisture transport, low-level moisture convergence, warm conveyor belts, and quasi-geostrophic forcing, with the relative importance varying between patterns.National Science FoundationSwiss National Science Foundation (SNSF

Revisiting the Local Scaling Hypothesis in Stably Stratified Atmospheric Boundary Layer Turbulence: an Integration of Field and Laboratory Measurements with Large-eddy Simulations

The `local scaling' hypothesis, first introduced by Nieuwstadt two decades ago, describes the turbulence structure of stable boundary layers in a very succinct way and is an integral part of numerous local closure-based numerical weather prediction models. However, the validity of this hypothesis under very stable conditions is a subject of on-going debate. In this work, we attempt to address this controversial issue by performing extensive analyses of turbulence data from several field campaigns, wind-tunnel experiments and large-eddy simulations. Wide range of stabilities, diverse field conditions and a comprehensive set of turbulence statistics make this study distinct

ACL injury prevention, more effective with a different way of motor learning?

What happens to the transference of learning proper jump-landing technique in isolation when an individual is expected to perform at a competitive level yet tries to maintain proper jump-landing technique? This is the key question for researchers, physical therapists, athletic trainers and coaches involved in ACL injury prevention in athletes. The need for ACL injury prevention is clear, however, in spite of these ongoing initiatives and reported early successes, ACL injury rates and the associated gender disparity have not diminished. One problem could be the difficulties with the measurements of injury rates and the difficulties with the implementation of thorough large scale injury prevention programs. A second issue could be the transition from conscious awareness during training sessions on technique in the laboratory to unexpected and automatic movements during a training or game involves complicated motor control adaptations. The purpose of this paper is to highlight the issue of motor learning in relation to ACL injury prevention and to post suggestions for future research. ACL injury prevention programs addressing explicit rules regarding desired landing positions by emphasizing proper alignment of the hip, knee, and ankle are reported in the literature. This may very well be a sensible way, but the use of explicit strategies may be less suitable for the acquisition of the control of complex motor skills (Maxwell et al. J Sports Sci 18:111-120, 2000). Sufficient literature on motor learning and it variations point in that direction

Differential neuromuscular training effects onACL injury risk factors in"high-risk" versus "low-risk" athletes

<p>Abstract</p> <p>Background</p> <p>Neuromuscular training may reduce risk factors that contribute to ACL injury incidence in female athletes. Multi-component, ACL injury prevention training programs can be time and labor intensive, which may ultimately limit training program utilization or compliance. The purpose of this study was to determine the effect of neuromuscular training on those classified as "high-risk" compared to those classified as "low-risk." The hypothesis was that high-risk athletes would decrease knee abduction moments while low-risk and control athletes would not show measurable changes.</p> <p>Methods</p> <p>Eighteen high school female athletes participated in neuromuscular training 3×/week over a 7-week period. Knee kinematics and kinetics were measured during a drop vertical jump (DVJ) test at pre/post training. External knee abduction moments were calculated using inverse dynamics. Logistic regression indicated maximal sensitivity and specificity for prediction of ACL injury risk using external knee abduction (25.25 Nm cutoff) during a DVJ. Based on these data, 12 study subjects (and 4 controls) were grouped into the high-risk (knee abduction moment >25.25 Nm) and 6 subjects (and 7 controls) were grouped into the low-risk (knee abduction <25.25 Nm) categories using mean right and left leg knee abduction moments. A mixed design repeated measures ANOVA was used to determine differences between athletes categorized as high or low-risk.</p> <p>Results</p> <p>Athletes classified as high-risk decreased their knee abduction moments by 13% following training (Dominant pre: 39.9 ± 15.8 Nm to 34.6 ± 9.6 Nm; Non-dominant pre: 37.1 ± 9.2 to 32.4 ± 10.7 Nm; p = 0.033 training X risk factor interaction). Athletes grouped into the low-risk category did not change their abduction moments following training (p > 0.05). Control subjects classified as either high or low-risk also did not significantly change from pre to post-testing.</p> <p>Conclusion</p> <p>These results indicate that "high-risk" female athletes decreased the magnitude of the previously identified risk factor to ACL injury following neuromuscular training. However, the mean values for the high-risk subjects were not reduced to levels similar to low-risk group following training. Targeting female athletes who demonstrate high-risk knee abduction loads during dynamic tasks may improve efficacy of neuromuscular training. Yet, increased training volume or more specific techniques may be necessary for high-risk athletes to substantially decrease ACL injury risk.</p

Central coordination as an alternative for local coordination in a multicenter randomized controlled trial: the FAITH trial experience

Contains fulltext : 110505.pdf (publisher's version ) (Open Access)BACKGROUND: Surgeons in the Netherlands, Canada and the US participate in the FAITH trial (Fixation using Alternative Implants for the Treatment of Hip fractures). Dutch sites are managed and visited by a financed central trial coordinator, whereas most Canadian and US sites have local study coordinators and receive per patient payment. This study was aimed to assess how these different trial management strategies affected trial performance. METHODS: Details related to obtaining ethics approval, time to trial start-up, inclusion, and percentage completed follow-ups were collected for each trial site and compared. Pre-trial screening data were compared with actual inclusion rates. RESULTS: Median trial start-up ranged from 41 days (P25-P75 10-139) in the Netherlands to 232 days (P25-P75 98-423) in Canada (p = 0.027). The inclusion rate was highest in the Netherlands; median 1.03 patients (P25-P75 0.43-2.21) per site per month, representing 34.4% of the total eligible population. It was lowest in Canada; 0.14 inclusions (P25-P75 0.00-0.28), representing 3.9% of eligible patients (p < 0.001). The percentage completed follow-ups was 83% for Canadian and Dutch sites and 70% for US sites (p = 0.217). CONCLUSIONS: In this trial, a central financed trial coordinator to manage all trial related tasks in participating sites resulted in better trial progression and a similar follow-up. It is therefore a suitable alternative for appointing these tasks to local research assistants. The central coordinator approach can enable smaller regional hospitals to participate in multicenter randomized controlled trials. Circumstances such as available budget, sample size, and geographical area should however be taken into account when choosing a management strategy. TRIAL REGISTRATION: ClinicalTrials.gov: NCT00761813