The level of Marzano higher-order thinking skills among polytechnic students

This study aims to identify polytechnic students' level of Marzano Higher-Order Thinking Skills (HOTS) based on two dimensions, 'Extension and Refinement of Knowledge' and 'Meaningful Use of Knowledge,' and to analyze the difference in the students' level of Marzano HOTS based on these two dimensions depending on the students' demographic factors. This study design was a survey using quantitative methods. A total of 313 students were randomly selected as the survey sample. A questionnaire in the form of closed-ended questions was used as the research instrument. Data were analyzed using frequency percentage and MANOVA test. The findings showed no significant differences in the eight HOTS in the dimension of 'Extension and Refinement of Knowledge' with the gender and socio-economic status (SES) factors. However, there were significant differences in the eight HOTS with the academic achievement factor. Meanwhile, based on the dimension of 'Meaningful Use of Knowledge,' the findings showed no significant differences in the five HOTS in this dimension with the gender and academic achievement factors. The paper includes implications of the Higher-Order Thinking Skills (HOTS) for students to improve their academic performance. In future research, the authors can further identify university students' HOTS levels in the technical area

Penetration depth study of LaOs4_4Sb12_{12}: Multiband s-wave superconductivity

We measured the magnetic penetration depth $\lambda(T)$ in single crystals of LaOs$_{4}$Sb$_{12}$ ($T_c$=0.74 K) down to 85 mK using a tunnel diode oscillator technique. The observed low-temperature exponential dependence indicates a s-wave gap. Fitting the low temperature data to BCS s-wave expression gives the zero temperature gap value $\Delta (0)= (1.34 \pm 0.07) k_B T_c$ which is significantly smaller than the BCS value of 1.76$k_B T_c$. In addition, the normalized superfluid density $\rho(T)$ shows an unusually long suppression near $T_c$, and are best fit by a two-band s-wave model.Comment: 5 pages, 2 figure

Comparative study of selected indoor concentration from selective laser sintering process using virgin and recycled polyamide nylon (pa12)

Additive manufacturing (AM) stands out as one of the promising technologies that have huge potential towards manufacturing industry. The study on additive manufacturing impact on the environment and occupational exposure are attracting growing attention recently. However, most of the researcher focus on desktop and fused deposition modelling type and less attention given to the industrial type of AM. Usually, during the selective laser sintering process, recycle powder will be used again to reduce cost and waste. This article compares the PM 2.5, carbon dioxide (CO2) and total volatile organic compound (TVOC) concentration between virgin and recycles powder using polyamide-nylon (PA12) towards indoor concentration. Four phases of sampling involve during air sampling accordingly to the Industry Code of Practice on Indoor Air Quality 2010 by DOSH Malaysia. It was found that PM 2.5 and CO2 concentration are mainly generated during the pre-printing process. The recycle powder tended to appear higher compared to virgin powder in terms of PM 2.5, and CO2. The peak value of PM 2.5 is 1452 μg/m3 and CO2 is 1218 ppm are obtained during the pre-printing process during 8 hours of sampling. TVOC concentration from recycling powder is slightly higher during the post- printing phase where confirm the influence of the powder cake and PA12 temperature from the printing process. In summary, this work proves that elective laser sintering (SLS) machine operators are exposed to a significant amount of exposure during the SLS printing process. Mitigation strategies and personal protective equipment are suggested to reduce occupational exposure

Structural reliability analysis of multiple limit state functions using multi-input multi-output support vector machine

Selecting and using an appropriate structural reliability method is critical for the success of structural reliability analysis and reliability-based design optimization. However, most of existing structural reliability methods are developed and designed for a single limit state function and few methods can be used to simultaneously handle multiple limit state functions in a structural system when the failure probability of each limit state function is of interest, for example, in a reliability-based design optimization loop. This article presents a new method for structural reliability analysis with multiple limit state functions using support vector machine technique. A sole support vector machine surrogate model for all limit state functions is constructed by a multi-input multi-output support vector machine algorithm. Furthermore, this multi-input multi-output support vector machine surrogate model for all limit state functions is only trained from one data set with one calculation process, instead of constructing a series of standard support vector machine models which has one output only. Combining the multi-input multi-output support vector machine surrogate model with direct Monte Carlo simulation, the failure probability of the structural system as well as the failure probability of each limit state function corresponding to a failure mode in the structural system can be estimated. Two examples are used to demonstrate the accuracy and efficiency of the presented method

Measurement of the cross-section and charge asymmetry of WW bosons produced in proton-proton collisions at s=8\sqrt{s}=8 TeV with the ATLAS detector

This paper presents measurements of the $W^+ \rightarrow \mu^+\nu$ and $W^- \rightarrow \mu^-\nu$ cross-sections and the associated charge asymmetry as a function of the absolute pseudorapidity of the decay muon. The data were collected in proton--proton collisions at a centre-of-mass energy of 8 TeV with the ATLAS experiment at the LHC and correspond to a total integrated luminosity of 20.2~\mbox{fb^{-1}}. The precision of the cross-section measurements varies between 0.8% to 1.5% as a function of the pseudorapidity, excluding the 1.9% uncertainty on the integrated luminosity. The charge asymmetry is measured with an uncertainty between 0.002 and 0.003. The results are compared with predictions based on next-to-next-to-leading-order calculations with various parton distribution functions and have the sensitivity to discriminate between them.Comment: 38 pages in total, author list starting page 22, 5 figures, 4 tables, submitted to EPJC. All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/STDM-2017-13

Breast MRI and tumour biology predict axillary lymph node response to neoadjuvant chemotherapy for breast cancer

Background: In patients who have had axillary nodal metastasis diagnosed prior to neoadjuvant chemotherapy for breast cancer, there is little consensus on how to manage the axilla subsequently. The aim of this study was to explore whether a combination of breast magnetic resonance imaging (MRI) assessed response and primary tumour pathology factors could identify a subset of patients that might be spared axillary node clearance.Methods: A retrospective data analysis was performed of patients with core biopsy-proven axillary nodal metastasis prior to commencement of neoadjuvant chemotherapy (NAC) who had subsequent axillary node clearance (ANC) at definitive breast surgery. Breast tumour and axillary response at MRI before, during and on completion of NAC, core biopsy tumour grade, tumour type and immunophenotype were correlated with pathological response in the breast and the number of metastatic nodes in the ANC specimens.Results: Of 87 consecutive patients with MRI at baseline, interim and after neoadjuvant chemotherapy who underwent ANC at time of breast surgery, 33 (38%) had no residual macrometastatic axillary disease, 28 (32%) had 1–2 metastatic nodes and 26 (30%) had more than 2 metastatic nodes. Factors that predicted axillary nodal complete response were MRI complete response in the breast (p < 0.0001), HER2 positivity (p = 0.02) and non-lobular tumour type (p = 0.015).Conclusion: MRI assessment of breast tumour response to NAC and core biopsy factors are predictive of response in axillary nodes, and can be used to guide decision making regarding appropriate axillary surgery

Search for chargino-neutralino production with mass splittings near the electroweak scale in three-lepton final states in √s=13 TeV pp collisions with the ATLAS detector

A search for supersymmetry through the pair production of electroweakinos with mass splittings near the electroweak scale and decaying via on-shell W and Z bosons is presented for a three-lepton final state. The analyzed proton-proton collision data taken at a center-of-mass energy of √s=13  TeV were collected between 2015 and 2018 by the ATLAS experiment at the Large Hadron Collider, corresponding to an integrated luminosity of 139  fb−1. A search, emulating the recursive jigsaw reconstruction technique with easily reproducible laboratory-frame variables, is performed. The two excesses observed in the 2015–2016 data recursive jigsaw analysis in the low-mass three-lepton phase space are reproduced. Results with the full data set are in agreement with the Standard Model expectations. They are interpreted to set exclusion limits at the 95% confidence level on simplified models of chargino-neutralino pair production for masses up to 345 GeV

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Dual-modality gene reporter for in vivo imaging

The ability to track cells and their patterns of gene expression in living organisms can increase our understanding of tissue development and disease. Gene reporters for bioluminescence, fluorescence, radionuclide, and magnetic resonance imaging (MRI) have been described but these suffer variously from limited depth penetration, spatial resolution, and sensitivity. We describe here a gene reporter, based on the organic anion transporting protein Oatp1a1, which mediates uptake of a clinically approved, Gd(3+)-based, hepatotrophic contrast agent (gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid). Cells expressing the reporter showed readily reversible, intense, and positive contrast (up to 7.8-fold signal enhancement) in T1-weighted magnetic resonance images acquired in vivo. The maximum signal enhancement obtained so far is more than double that produced by MRI gene reporters described previously. Exchanging the Gd(3+) ion for the radionuclide, (111)In, also allowed detection by single-photon emission computed tomography, thus combining the spatial resolution of MRI with the sensitivity of radionuclide imaging

Dynamic Mechanisms of Cell Rigidity Sensing: Insights from a Computational Model of Actomyosin Networks

Cells modulate themselves in response to the surrounding environment like substrate elasticity, exhibiting structural reorganization driven by the contractility of cytoskeleton. The cytoskeleton is the scaffolding structure of eukaryotic cells, playing a central role in many mechanical and biological functions. It is composed of a network of actins, actin cross-linking proteins (ACPs), and molecular motors. The motors generate contractile forces by sliding couples of actin filaments in a polar fashion, and the contractile response of the cytoskeleton network is known to be modulated also by external stimuli, such as substrate stiffness. This implies an important role of actomyosin contractility in the cell mechano-sensing. However, how cells sense matrix stiffness via the contractility remains an open question. Here, we present a 3-D Brownian dynamics computational model of a cross-linked actin network including the dynamics of molecular motors and ACPs. The mechano-sensing properties of this active network are investigated by evaluating contraction and stress in response to different substrate stiffness. Results demonstrate two mechanisms that act to limit internal stress: (i) In stiff substrates, motors walk until they exert their maximum force, leading to a plateau stress that is independent of substrate stiffness, whereas (ii) in soft substrates, motors walk until they become blocked by other motors or ACPs, leading to submaximal stress levels. Therefore, this study provides new insights into the role of molecular motors in the contraction and rigidity sensing of cells