Miracle-dz/UniFAR-FTUs huggingface dataset:
Hubungan Tingkat Pengetahuan Perawat Tentang BTCLS (Basic Trauma Cardiac Life Support) Dengan Penanganan Primary Survey Di IGD RSU "X" Provinsi Kalimantan Barat

Latar Belakang: IGD (Instalasi Gawat Darurat) merupakan salah satu unit Rumah Sakit yang dimana perawat memberikan tindakan keperawatan gawat darurat yang memerlukan penanganan Primary Survey terkait dalam pengetahuannya.Tujuan: Penelitian ini bertujuan untuk mengetahui hubungan tingkat pengetahuan perawat tentang BTCLS (Basic Trauma Cardiac Life Support) dengan penanganan Primary Survey di IGD. Penelitian ini dilakukan di IGD RSU Yarsi Pontianak Provinsi Kalimantan Barat.Metode: Penelitian ini merupakan jenis penelitian kuantitatif dengan metode analitik korelatif menggunakan desain cross sectional. Teknik pengambilan sampel dalam penelitian ini menggunakan teknik total sampling yaitu sebanyak 16 responden. Uji data statistik ini menggunakan uji Chi-Squere dengan program SPSS.Hasil: Hasil penelitian menunjukan bahwa tingkat pengetahuan perawat dengan BTCLS 75 % dengan kategori baik pada penanganan primary survey yang terampil dan 25% dengan kategori kurang dalam pengetahuan perawat tentang BTCLS dengan penanganan Primary Survey tidak terampil. Maka didapatkan nilai p value =0,046 (p value 0,05) sehingga dapat disimpulkan bahwa Ha diterima, yang artinya ada hubungan pengetahuan perawat tentang BTCLS dengan penanganan Primary Survey.Kesimpulan: Tingkat pengetahuan perawat tentang Basic Trauma Cardiac Life Support ada berhubungan dengan penanganan Primary Survey. Sehingga rumah sakit secara umum dan instalasi gawat darurat pada khususnya diharapkan melakukan pelatihan, workshop dan seminar untuk meningkatkan ketempilan dan pengetahuan perawat dalam penanganan keperawatan gawat darurat .
Schwingungsspektroskopische Untersuchungen an Channelrhodopsin-2 mithilfe von zeitaufgelöster FTIR- und Raman-Spektroskopie

In dieser Arbeit wurde der Photozyklus des lichtgetriebenen Kationenkanals Channelrhodopin-2 schwingungsspektroskopisch untersucht. Durch Vergleiche von Messungen an verschiedenen Varianten des Proteins (erzeugt durch seitenspezifische Mutagenese sowie Isotopenmarkierungen) konnten zahlreiche Schwingungsbanden zugeordnet werden. In Messungen mit hoher Zeitauflosung wurde eine fruhe Spaltung des Photozyklus beobachtet. Daher musste das etablierte Photozyklusmodell erweitert werden. In einem Teil des Probenensembles kommt es nach Lichtaktivierung zu einer Isomerisierung des proteingebundenen Chromophors Retinal um zwei Doppelbindungen und zu einer schnellen Deprotonierung von Glutamat 90. Diese Prozesse fuhren zum vorgeoffneten, jedoch nichtleitenden lichtadaptierten Zustand des Kanals, der durch erneute Lichtaktivierung in einen Offenzustand uberfuhrt werden kann. Die Erkenntnisse dieser Arbeit liefern Erklarungsansatze fur das in anderen Arbeiten beobachtete Verhalten des Kanals.
INITIAL VALIDATION & PERFORMANCE ANALYSIS OF THE BEARINGLESS DOUBLE U-CORE SWITCHED RELUCTANCE MACHINE TOPOLOGY

Due to the capabilities which switched reluctance machines (SRMs) offer, including simple design, robustness of construction, reliability, low cost and low idle losses, developing and upgrading their structure is a vital issue to expand the industrial applications. During recent years, various structures have been carried out to enhance the efficiency of these type of electrical machines in which double u-core layout has been introduced as one of the viable solutions. In order to upgrade the technology to a bearingless double u-core SRM as a further investigation, this paper presents a feasible demonstrations and performance evaluation of a single phase double u-core SRM under three individual currents for each coil to examine the control and design topology. To this end, it is essential to scrutinize the behaviour of the single phase machine with producing three various duty cycles applied to each coil, and distinguish as a three individual controller coils to work not only as a motor and a generator, but also as a magnetic bearing. Moreover, the impact of varied currents on the force exerted to the rotor has been extracted for subsequent inquiry by a performance tracking of the single phase machine under three individual currents.
Microwave assisted biosynthesis of silver nanoparticles using banana leaves extract: Phytochemical, spectral characterization, and anticancer activity studies

Microwave assisted biosynthesis of nanoparticles has been a cost effective, environmentally benign, and alternative to the chemical method. In this context, we report eco-friendly and robust nanoparticles synthesized using the bio-waste (Banana leaves) extract material through a microwave method. The newly synthesized Banana Leaves extract -Silver Nanoparticles (BL-AgNPs) is confirmed by using the UV-Visible, FT-IR spectroscopy and Scanning Electron Microscopy (SEM) techniques. UV-Vis spectrum shows the widening of the band around 476 nm, which confirms the polydispersed nature of BL-AgNPs. FT-IR spectroscopy explores that, hydroxyl and carbonyl groups in the Banana Leaves extract play vital role in the reduction of silver ions and also attach with AgNPs. The phytochemical studies reveal that, the polyphenols and alkaloids present in the BL extract act as reducing and stabilizing agent, which is responsible for the reduction of Ag+ (silver ions) to Ag (BL-AgNPs) and stabilization of BL-AgNPs. This clearly confirms the formation of silver nanoparticles (AgNPs). SEM results revealed that, bead shape of BL-AgNPs with particle size of 80 to 100 nm. In conclusion, BL-AgNPs exhibits promising anticancer activity against lung cancer and breast cancer cell line by endorsing inhibition of cell migration and proliferation on low concentration.
Comparison of the Performance of the IDEXX SediVue Dx® with Manual Microscopy for Detection of Cells and Crystals in Urine Sediments

ii DEDICATION . iv ACKNOWLEDGEMENTS . v CONTRIBUTORS AND FUNDING SOURCES . vi NOMENCLATURE . vii TABLE OF CONTENTS . viii LIST OF FIGURES . x LIST OF TABLES . xi
Efektivitas Layanan Informasi Menggunakan Film Imperfect Untuk Mereduksi Self Harm

Penelitian ini bertujuan untuk mengetahui efektivitas layanan informasi dengan menggunakan film imperfect dapat mereduksi self harm. Pendekatan penelitian ini adalah kuantitatif. Jenis penelitian ini menggunakan rancangan penelitian pra-eksperimen one group pre-test post-test design. Penelitian ini memiliki dua variabel yaitu terdiri dari variabel terikat atau variabel X (layanan informasi dengan media film imperfect) dan juga variabel bebas atau variabel Y (self harm). Populasi dalam penelitian ini yaitu mahasiswa BK a1 angkatan 2017 Universitas PGRI AdiBuana Surabaya. Sampel dalam penelitian ini yaitu 5 mahasiswa yang memiliki skor self harm tertinggi dengan menggunakan purposive sampling. Hasil penelitian ini menunjukkan terdapat penurunan nilai mean pre-test 64,60 menjadi nilai mean post-test 53,40. Sehingga dapat disimpulkan penggunaan layanan informasi dengan menggunakan film imperfect secara signifikan efektif dalam mereduksi self harm.
Effect of Water Vapor on CO2 Sorption–Desorption Behaviors of Supported Amino Acid Ionic Liquid Sorbents on Porous Microspheres

Immobilizing amino acid ionic liquids (AAILs) into a porous support is a promising way to fabricate robust solid sorbents with high capacities for CO2 capture. One of important factors to be evaluated toward the practical use is the impact of water vapor in inlet gases on the CO2 capture performance as real flue gases contain some fraction of water vapor. In this study, CO2 sorption–desorption experiments of supported 1-ethyl-3-methylimidazolium amino acid ([EMIM][AA]) IL sorbents on porous microspheres were conducted under dry and humidified CO2 inlet conditions using a TGA-MS analysis system, and their outcomes were compared with those of supported amino acids (AA) sorbents. The presence of water vapor changed the CO2 sorption behaviors depending on the sorbent types. In humidified CO2 inlet, the CO2 capture capacities of supported [EMIM][glycine] and [EMIM][lysine] decreased as the adsorbed water hindered their reaction with CO2, whereas the CO2 capture of those with supported lysine and arginine incre.
Influence of Three Dimensions of Intellectual Capital on Relationship Performance of University Lecturers: A Case of Universities in Henan Province, China

Intellectual capital plays an important role in promoting the development of the universities. Individual lecturers are in an organizational environment, and their behavior is affected by the organizational environment. Therefore, the relationship between intellectual capital and relationship performance of university lecturers is an important research topic. This thesis used quantitative research methods, taking university lecturers in Henan Province as an example, and found that three dimensions of intellectual capital, human capital, structural capital and relational capital, have a significant positive impact on the relationship performance of university lecturers.
Does foreign investment hurt job creation at home? The geography of outward FDI and employment in the USA

Rising political skepticism on the benefits of global economic integration has increased public scrutiny of the foreign activities of domestic firms in virtually all advanced economies. Decisions to invest in new activities abroad are seen by some commentators as potentially detrimental to domestic employment. We contribute to this debate by scrutinizing the relationship between outward ‘greenfield’ Foreign Direct Investments (FDI) and local employment levels. The analysis, at the scale of USA Economic Areas, finds a generally positive link between outward investment and local employment, but with an important range of differences across regions and sectors. Less developed regions benefit the most from the positive returns of outward FDI, and, particularly, from outward FDI if it is undertaken by firms in high-tech manufacturing and services industries. But there is a downside, in the form of increasing intra-regional inequalities between high-skilled and low-skilled workers in these areas.
Saliency Enhanced Hierarchical Bilinear Pooling for Fine-Grained Classification

: Hierarchical bilinear pooling network considers the feature interaction in middle convolutional layers and works well in the classification of fine-grained images. However, it carries out feature interaction on all activated image regions including irrelevant background, which affects the classification performance. To address this problem, a saliency enhanced hierarchical bilinear pooling method is proposed, which combines with the saliency detection network to generate an attention map, and uses the attention map to interact with the feature extraction network to enhance the information of the salient regions. As the result, it can reduce the impact of background and other irrelevant information, and improve the classification performance. The classification accuracy on three commonly used fine-grained image datasets CUB-200-2011, Stanford Cars and FGVC-Aircraft is 86.5%, 92.9% and 90.8%, respectively, which is excellent compared with other mainstream methods.
Industry Factors and Adoption of Market Orientation Practices in Nigerian Small Business Enterprises

: Aim/purpose - This study aims at investigating the industry environmental factors that affectthe adoption of market orientation (MO) practices by Small Business Enterprises (SMEs) in Nigeria and their relative importance in the MO adoption process. In view of the gap in literature, Nigerian marketing practitioners may not know which of the task environments impact on the adoption of MO in SBEs, a critical growth engine in any country. Design/methodology/approach - A survey method was used to gather data from 545 top management and owner-managers of 160 SBEs from eight sectors using the Nigerian stock exchange classification. The sectors are located within Lagos, the commercial nerve-centre of Nigeria. Purposive sampling with some stratification was used. Data was collected with a hand delivered structured questionnaire. With the aid of Predictive Analytical Software (PASW)version 19.0, data was analyzed using descriptive statistics, factor analysis and multiple regression analysis. Findings – The study revealed that the critical industry environmental factors influencing the adoption of market orientation practices of Nigerian SBEs are mainly competitive risk/competitive rivalry, market attractiveness risk, buyer power risk, substitutability threat, and supplier power factor. The factor perceived as most crucial is market turbulence. The test of hypothesis revealed that there is significant relationship between these industry environmental factors and the adoption of market orientation practices by SBEs.Research implications/limitations – The implication of the findings is that the presence of certain industry and the adoption of market orientation by SBEs in Nigeria. Therefore,for better and improved performance, the study recommends that SBEs be conscious of, monitor and adapt their market orientation practices to the above identified industry factors. of factor analysis, the researcher used his subjective It is possible that the names may not fully represent the construct that underlie each factor. Originality/value/contribution –This empirical study has been able to show that as a consequence of adopting market orientation practices, SBEs have achieved improved quality of products/services offered and higher profitability in their business operations but the adoption of MO is shown not to lead to reduction in operating costs.
Multi-Modal Context Propagation for Person Re-Identification With Wireless Positioning

Existing person re-identification methods mainly rely on the visual appearance captured by cameras for identity matching. However, dueto the sensitivity of visual data to occlusion, blur, clothing change, etc., existing methods struggle to distinguish pedestrians in challenging scenarios. Inspired by the fact that most pedestrians carry around smart wireless devices, e.g. mobile phones that can be sensed by WiFi or cellular networks as wireless positioning signals, we propose to exploit the free yet informative wireless signals to assist person re-identification. It is well recognized that wireless signals are robust to visual noises mentioned above, which perform as a good complement to the visual data. To make full use of these multi-modal clues for person re-identification, we propose a multi-modal context propagation framework MCPF that contains a recurrent context propagation module RCPM and an unsupervised multi-modal cross-domain method UMM-ReID. RCPM enables context information to be continuously propagated and fused between visual data and wireless data. UMM-ReID utilizes wireless signals to constrain the estimation of pseudo labels. We contribute a new wireless positioning person re-identification dataset WP-ReID to evaluate our approach. Extensive experiments demonstrate the effectiveness of the proposed method. Benefiting from the collaboration of RCPM and UMM-ReID, the proposed framework MCPF achieves a significant performance improvement over existing methods.
An Electro-Thermal Model based fast optimal charging strategy for Li-ion batteries

This paper utilizes an integrated electro-thermal model of a lithium-ion battery to search for an optimal multistage constant current charge pattern that will minimize the total charging time of the battery, while restricting its temperature rise in each stage within safe limits. The model consists of two interlinked components, an electrical equivalent circuit model to continuously predict the battery's terminal voltage and a thermal model to continuously predict its temperature rise as charging progresses. The proposed optimization algorithm is based on a novel stepwise single-variable search technique that is very easy to implement and converges quickly. The results of our extensive simulation studies clearly indicate that the proposed charging strategy offers a fast, safe and easy-to-implement alternative to many of the existing computationally intensive optimal charging strategies.
Diffusive Bewegungen in molekularen Flüssigkeiten

Die Arbeit beschaftigt sich mit grundlegenden Untersuchungen zur Dynamik mittelkettiger molekularer Flussigkeiten (Coenzym Q10, n-Alkane) auf verschiedenen Zeitskalen mittels quasielastischer Neutronenstreuung (QENS) und gepulster Feldgradienten-Kernmagnetresonanzspektroskopie (PFG-NMR). Dazu wurden Neutronenstreuexperimente am Flugzeitspektrometer TOFTOF und am Spinechospektrometer J-NSE des FRM II durchgefuhrt. Zur Auswertung der TOF-QENS-Daten wurden verschiedene Streufunktionen fur die Beschreibung der lokalen Bewegungen getestet. Der ermittelte Diffusionskoeffizient war jedoch weitgehend unabhangig von den fur die internen Bewegungen verwendeten Modellen. Abhangig von der Kettenlange des Alkans zeigte der Vergleich von TOF-QENS-Diffusionskoeffizienten mit PFG-NMR-Werten erhebliche Unterschiede. Es wird die Zeitabhangigkeit des Diffusionskoeffizienten und die Komplementaritat von QENS und PFG-NMR im Hinblick auf die langreichweitige Diffusion gezeigt und diskutiert. Weiterhin wurden detaillierte QENS-Untersuchungen zur Beschreibung der Methylgruppenrotation sowohl im festen Zustand als auch in der Schmelze kleiner organischer Molekule mit den Modellsubstanzen Pentafluoranisol, Pentafluortoluol und Q0 durchgefuhrt. Wahrend im Festkorper fur jede kristallographisch nicht aquivalente Methylgruppe eine definierte Arrhenius-Aktiverungsenergie bestimmt werden konnte, ist die Methylgruppenrotation in der flussigen Phase barrierefrei.
Detailed Routing Short Violation Prediction Using Graph-Based Deep Learning Model

As the manufacturing process continuously shrinks, how to accurately estimate routability at placement is becoming increasingly important. In addition to extracting local features, this article innovatively constructs an adjacency matrix to represent the connection relationship among tiles, which can reflect the placement quality more comprehensively. To effectively map local features of tiles to the corresponding adjacency matrix, a graph neural network is employed. This trained model is used to predict short violations at the placement stage. Experimental results demonstrate the proposed method can achieve better binary classification quality for designs with severe shorts and outperforms in inductive learning than available machine learning frameworks.
Use of Filled Bioplastics in Construction

Polymers and associated composite materials play an increasingly prominent role among structural materials. The relevance of the use of bioplastics as an alternative to synthetic polymers increases year by year. In this regard, the paper describes the production of a ligno-filled polymer material based on polyhydroxyalkanoates to be used in the production of building materials. The studies allowed us to produce the material from wood hydrolyzates. The highest yield of reducing substances in course of pine sawdust hydrolysis with 4% sulfurous acid occurred at 170°C. To obtain a biopolymer in liquid wood hydrolyzate medium, the Cupriavidus necator strain was used, which after 50 hours of cultivation gave a biopolymer yield of up to 15 g/l. The studies of the strength characteristics of the composite based on the obtained bioplastic and dried solid wood hydrolysates allowed us to produce a balanced composition for subsequent use in construction.
Synthesis of surfactant-free micro- and nanolatexes from Pickering emulsions stabilized by acetylated cellulose nanocrystals

We report an easy route to surfactant-free micro- and nanolatexes of polystyrene dispersed in water from Pickering emulsion systems, using modified cellulose nanocrystals as stabilizing particles. Each step of the formation of these latexes was thoroughly investigated: modification of the cellulose nanocrystals, colloidal properties of the emulsions, impact of the polymerization initiator, impact of the ionic strength and mechanisms leading to the formation of the nanolatexes.
Smoothed-Particle-Hydrodynamics for the Control of Robotic Swarms, and Parametric Associations

A swarm of robots has several macroscopic properties that are extraneous to an individual robot. This is a direct consequence of the fact that a swarm is a coupled high-dimensional system that is characterized by interactions between individual robots. In a smoothed-particle-hydrodynamics-based control of a swarm of robots, the equations of motion may be parameterized by key parameters that affect the macroscopic properties of the swarm such as separation, compressibility, cohesivity, and velocity matching. In this article, we analyze this relation between the parameters in the equations of motion and the properties of the swarm. The resulting analysis enables the design of a versatile, scalable controller that may be modified and adopted to suit the desired objectives of individual applications. We also present a new interaction potential that enables controlling the robot-robot separation, beyond maintaining the robot density, and providing a swarm cohesive force that keeps the robots in the swarm together. The constructed interaction potential is conservative, and the overall swarm stability may still be established using passivity arguments in the presence of a dissipative process. In this article, we use Lyapunov methods on the total energy to establish this stability. The salient features of the proposed controller are verified using simulations and experiments. The experiments are conducted using two real physical airplanes to demonstrate the practical feasibility of the proposed controller.
Hierarchical Latent Variable Extraction and Multisegment Probability Density Analysis Method for Incipient Fault Detection

The incipient fault is difficult to detect because of its small amplitude and insignificant impact, however, ignoring such fault may cause irreversible damage to the system. In this article, a hierarchical latent variable extraction and multisegment probability density analysis method is proposed to detect the incipient fault. First, three data subspaces are constructed, which are named dominant, intermediate, and residual spaces, and key latent variables which contain more offline variance or online variation information will be retained. Afterward, the expanded data distribution interval and multiple data segmentsare constructed for the probability density estimation. Based on the improved symmetric divergence index, the distribution distance between the online data and offline modeling data can be evaluated, which has achieved 95.3% and 86.8% average detection rates for the faults in numerical case and Tennessee Eastman process. Finally, a real multiphase flow facility is used to demonstrate the effectiveness of the proposed method.
Identifying and Characterising Active Travel Corridors for London in Response to COVID-19 Using Shortest Path and Streetspace Analysis Paper 222 - May 20

, Covid-19 related restrictions are forcing public transport services to operate with less capacity. In response, trips are being channelled to walking and cycling. We use shortest-path analysis to identify all street-level connections between all rail and underground stations in inner London. We are able to identify the critical pathways which show a long tail distribution and a radial/cellular spatial pattern. We visually compare this network with the existing cycling network, and explore two scenarios of street interventions in 8 critical pathways using streetspace cross-section analysis. The methods presented here can offer valuable analytical capacity for developing new cycling and walking schemes and designing place-based streets that are more appropriate to control virus propagation.