Miracle-dz/UniFAR-FTUs huggingface dataset:
The Art of Effective Handoff Communication Among Medical and Surgery Residents

End-of-shift handoffs occur when physicians transfer care responsibilities from one shift to another. Typically viewed as a straightforward exchange of information, we argue that several contextually relevant factors shape the communication behaviors of outgoing and incoming residents during handoffs. Digital recordings and transcripts of resident handoffs in medicine and surgery were made at three VA Medical Centers. They were triangulated with cognitive task interviews that elicited residents’ reconstructions of their work practices. Analyses revealed clear distinctions among “day-to-night,” “night-to-day,” and “double handoffs” that involve transitions between day and night teams. Although residents preferred handing off in dedicated, quiet spaces, few (16%) occurred in such settings; 28% contained significant interruptions. The quality handoff artifacts (notes and forms) influenced interactions, especially in cases where multiple residents from different teams were involved, requiring incoming residents to adjust “on the fly. ” This study demonstrated that there are multiple contextual factors that affect, and are affected by, handoff interactions. The findings suggest that handoffs are less like the delivery of a telegram (unidirectional) and more like complex adaptive systems (products of interactional co-construction). Teaching communication practices based on interaction complexity may reduce errors and adverse outcomes for hospitalized patients.
Introducing teachers who use GUI-driven tools for the randomization test to code-driven tools

ABSTRACT The advent of data science has led to statistics education researchers re-thinking and expanding their ideas about tools for teaching statistical modeling, such as the use of code-driven tools at the secondary school level. Methods for statistical inference, such as the randomization test, are typically taught within secondary school classrooms using GUI-driven tools. A teaching experiment was conducted, using a learning task designed to introduce teachers familiar with using GUI-driven tools for teaching the randomization test to code-driven tools. Our findings from this exploratory study indicate that the design principles and considerations used to create the learning task supported teachers’ introduction to code-driven tools and encouraged an integration of statistical and computational thinking.
Predictors for Early Discharge Planning of Hospitalized Acute Geriatric Patients, a Retrospective Study

Purpose: When treated for an acute disorder, older adults are vulnerable for functional losses and the need of care after discharge. In a specialised geriatric ward, patients get a comprehensive treatment complementary to medical care in order to maintain and improve mobility and Activities of Daily Living (ADL) to facilitate the return to domesticity. The aim of this paper is to identify the relevant assessments at admission to predict the status at discharge for early discharge planning. Method: In a retrospective cohort study with 351 patients, we analysed the impact of acute geriatric early rehabilitation on the functional outcome after treatment. As a sufficient improvement of ADLs and mobility we defined as a suitable endpoint at least 60 Barthel Points (ADL) and the ability for “Timed-Up-and-Go-Test” (TUG) when discharged from hospital care. To identify relevant predictors in the set of the screening assessments at admission we used linear and logistic regressions as well as odds-ratios. Results: Statistical analysis shows that all patients benefit significantly from early rehabilitation in ADLs and the physical function. Barthel-Score, walking distance, cognition and handgrip are the strongest predictors for the outcome. Clinical condition, the medical treatment before admission, length of hospitalization, age or gender have no predictive quality.
Self-Limited Photo-Assisted Synthesis of Silicon Nanocrystals

Anomalous growth of silicon (Si) nanocrystals (NCs) was observed during Raman scattering measurements of nanosilica SiO x (x=0.9) powder with an average diameter of 40 nm. It was found that Si NCs were formed by exposure to the laser beam. This photo-assisted synthesis is similar to the thermal synthesis of Si NCs, which forms Si NCs by thermally decomposing SiO x into Si and SiO 2 . However, the photo-assisted synthesis is more effective in forming Si NCs than the thermal synthesis. Even one second after irradiation of the nanosilica SiO x powder with laser, Si NCs with an average size of 5 nm were formed. The Si NC size increases with increasing the laser power and exposure time. It is interesting to observe a self-limited size for higher laser power and prolonged exposure. The photo-assisted synthesis of Si NCs is proved to be a promising technique with a wide range of applications in nanotechnology.
Is nonparametric bootstrap an appropriate technique for estimating variance of the sample median?

Abstract The main objective of this study is to compare two different bootstrap algorithms for estimating the variance of sample median when the underlying distribution is symmetric, right or left skewed. Nonparametric bootstrap method and the formulated estimation approach of bootstrap method proposed by Ghosh et al., were compared at different sample sizes using Monte Carlo simulation technique. Simulation results showed that nonparametric bootstrap method has better efficiency for symmetric or right skewed distributions when the sample size was small. However, it had lower efficiency for left skewed distributions. For large sample sizes, both estimation methods gave similar variance estimates with lower bias.
Student Career Prediction Using Decision Tree and Random Forest Machine Learning Classifiers

Education is so important for the youngsters; some of them don’t have the interest towards schoolings, so they drop their study after certain time. As in this fastest world student are going through their academics and with their interested courses. So this is an important in the entire student to choose his future career. Machine learning approaches are applied in various domains. This proposed work deals with the career predication of the students as weather they will be going for their next level of higher education from their present graduation level using machine learning concepts like DT (Decision Tree) and RF (Random Forest). Applying the concept of DT it yields a result of about 91% of accuracy and applying RF it gives 93% of accuracy level. The result of the proposed system helps the recruiters to select the only needed and proper candidates.
Dynamics of Volumetric Moisture in Sand Caused by Injection Irrigation—Physical Model

The study was aimed at the determination of the dynamics of spatial distribution of moisture front, caused by pointwise application of water under conditions of high pressure. This was effected through a series of simulations of water injection to a porous material with particle size distribution corresponding to that of sand. The study was composed of six independent experimental series in which the sand monolith was supplied with water doses of 250, 500, 750, 1000, 1250, and 1500 cm3 under pressure (4 bar). At the same time, measurements of volumetric moisture were conducted with the use of TDR sensors, which were positioned within the soil in a regular grid pattern. It was demonstrated that the primary cause of water movement at the moment of injection is the pressure potential gradient of water molecules. The spatial reach of moisture change in relation to the injected water dose was also defined. It was also observed that in the course of water injection there is a risk of disturbing the structure of the porous material. The correctness of the adopted method was verified through the calculation of the water balance.
High-Resolution Observations of Upwelling and Front in Daya Bay, South China Sea

Field observations of coastal regions are important for studying physical and biological features. Observations of high-resolution coastal phenomena were obtained by using a tow-yo instrument and a turbulence profiler at Daya Bay in the South China Sea in October 2015. Details of coastal phenomena, including warm water from a nuclear plant discharge, as well as an upwelling, and front, were obtained. The upwelling, with a width of 2 km, resulted in saltier and more turbid water near the bottom, with low chlorophyll-a and dissolved oxygen contents being transported upward to the surface layer and changing the local water environment. The front, with the lateral salinity variations as large as 0.7 psu across 1 km, was active at the water intersection of the South China Sea and Daya Bay. Such events commonly form during weak stratification periods in autumn. Continuous measurements from VMP-250 profiler over circa 22 h revealed active fronts and an averaged dissipation rate of 8 × 10−8 W/kg and diffusivity of 5.8 × 10−5 m2/s (i.e., one order of magnitude larger than in the open ocean) in the thermocline. The front was accompanied by strong mixing, indicating that it had formed at the intersection of different water masses and played an important role in energy dissipation in Daya Bay, further affecting the distribution of ecological elements.
Relegating expertise: The outward and inward positioning of librarians in information literacy education

Previous research has demonstrated that professional narratives reference discourses that shape the practice of information literacy within higher education. This article uses discourse analysis method to identify how information literacy discourses construct and position teaching librarians within higher education. Texts analysed include four recent English-language models of information literacy and 16 textbooks. Analysis suggests the existence of two distinct narratives related to the role, expertise and professional practice of teaching librarians. In the outward-facing narrative librarian work is typically absent from guidelines for practice. In contrast, book introductions, which constitute the inward-facing narrative, centre professional librarians yet simultaneously position them as incompetent, or as lacking the skills and understandings that they need to be effective in this setting. These narratives constitute a form of othering that threatens professional practice at a time when the professionalisation of librarianship is being drawn into question. This article represents the second in a research programme that interrogates the epistemological premises and discourses of information literacy within higher education.
Rate controlled metal assisted chemical etching to fabricate vertical and uniform Si nanowires

Mac(metal assisted chemical) etching is a simple, low-cost and anisotropic etching method to make Si NWs (silicon nanowires). In this method, smaller surface area is damaged compared to dry etching process, either. Mac etching uses a combination of an oxide removal acid (e.g. HF), an oxidant (e.g. H2O2) with a noble metal (e.g. Au, Ag, Pt, etc.) as the catalyst. Typically, the Si beneath the noble metal is etched faster than the Si without noble metal coverage by electron transfer mechanism at the noble metal /solution and the noble metal/Si interface. While Mac etching to build Si NWs, unwanted etching occurs in the bulk silicon layer resulting from excess hole diffusion caused by the increase in hole concentration at the nearby metal layers. In this study, we explored the ratio of oxidant to oxide removal acid in the Mac etching solution that is most effective in etching the Si underneath the noble metal layer suppressing the unwanted etching. At the optimized ratio, Si NWs were fabricated at a faster rate with good uniformity.
A New k-Distribution Scheme for Clear-Sky Radiative Transfer Calculations in Earth’s Atmosphere. Part II: Solar (Shortwave) Heating due to H2O and CO2

A new k-distribution scheme without the assumption of the correlation between the absorption coefficients at different pressures is developed for solar heating due to water vapor and CO2. Grouping of spectral points is based on the observation that radiation at spectral points with a large absorption coefficient is quickly absorbed to heat the stratosphere, and the heating below is attributable to the absorption of the solar radiation at the remaining spectral points. By grouping the spectral points with a large absorption coefficient at low pressures, the range of the absorption coefficient of the remaining spectral points is narrowed, and the k-distribution approximation can be accurately applied to compute solar heating in both the stratosphere and troposphere. Grouping of the spectral points is based on the absorption coefficient at a couple of reference pressures where heating is significant. With a total number of 52 spectral groups in the water vapor and CO2 bands, fluxes and heating rates were calculated for various solar zenith angles in some typical and sampled atmospheres in diverse climatic regimes and seasons. The maximum heating rate difference between the k-distribution and line-by-line calculations is < 0.09 K day-1 for water vapor, and < 0.2 K day-1 for CO2. The difference in the surface radiation is ~ 1.4 W m-2 for water vapor and 0.6 W m-2 for CO2, while it could increase to 2.6 W m-2 due to overlapping absorption. These results can be improved by increasing the number of spectral groups at the expense of computational economy.
HP-SFC Algorithm for MmWave Massive MIMO Hybrid Precoding Systems

This paper presents an alternating iteration hybrid precoding algorithm for the switch network-based dynamic fully-connected (SFC) structure, namely HP-SFC algorithm. Firstly, based on the sparsity of switch network, the optimization problem of the analog switch precoding matrix is transformed into a binary dictionary updating problem, which avoids to deal with the binary constraint straightly. Then, the optimization problem of the analog phase shifter (PS) precoding matrix is modeled as a quadratic unimodular programming problem by the vectorization of the analog PS precoding matrix. So that the analog PS precoding matrix can be readily optimized. Finally, the analog switch precoding matrix, the analog PS precoding matrix and the digital precoding matrix are alternately optimized via the block coordinate descent, the generalized power method and the least square, respectively. Theoretical analysis and simulation results show that the proposed algorithm can provide brilliantly hybrid precoding performence campared with the previous works, for example: 1) it reduces the hybrid precoding matrix residual, so that its spectral efficiency is close to the full digital optimal precoding; 2) it provids at least 15\% energy efficiency improvement comparing with related algorithms.
Mechanism of interaction between cationic surfactant and kaolinite

The floatability of kaolinite was investigated in the presence of dodecylamine(DDA). Based on the analysis of chemical composition of each kaolinite cleavage plane and the quantum calculation of interaction between kaolinite surfaces and DDA,the interaction model under diverse pH values was constructed to explain the special flotation behavior of kaolinite in the presence of cationic surfactant.In alkaline pulp,the mineral powders can be fully dispersed in the suspension owning to negative charge held by both side and bottom surface of kaolinite crystal. The cationic surfactant DDA has the adsorption priority on the (001) surface of kaolinite resulting in the varying hydrophilic of different surfaces of kaolinite.Triggered by intensive hydrophilic force of mineral powder,hydrophobic flocculation occures, then the hydrophobic surface areas are reduced greatly and followed by the increased difficulties of mineral flotation. In acid pulp,dodecylamine can be fairly adsorbed on each surfaces of kaolinite for the similar surface properties of (001) surface and {001} resulted from the H~+ adsorption on the bottom surface. And the adsorptive density of collector is well increased for the decreased total surface areas of kaolinite powders as a result of the flocculation caused by the positive charge and the negative charge held by side and bottom surface respectively.Thus the kaolinite flotation rate could keep a relatively high level under lower pH values condition.
Human Activity Affects Forest Fires: The Impact of Anthropogenic Factors on the Density of Forest Fires in Poland

Forest fires, due to climate change, are a growing threat to human life, health, and property, especially in temperate climates. Unfortunately, the impact of individual factors on forest fires varies, depending on the geographical region and its natural and socio-economic conditions. The latter are rarely introduced into fire warning systems, which significantly reduces their effectiveness. Therefore, the main goal of this study was to quantify the impact of a wide range of anthropogenic factors on forest fires, using Poland as a representative example of a Central European country. Data were analyzed in relation to districts for the period 2007–2017, using correlation analysis and regression modeling applying global and local/mixed regression methods. It was found that almost all of the 28 variables taken for analysis significantly determined the density of forest fires, but the greatest role was played by the length of the border between forests and built-up areas, and road density. In addition, the impact of most of the analyzed variables on forest fires varied over the study area, so implementing non-stationarity in geographically weighted regression models significantly improved the goodness-of-fit compared to global models.
Gamification Framework for E-Learning Systems in Higher Education

This paper explains the concept of gamification, lists the current models according to which educational e-courses can be designed, and proposes a conceptual eRIOOS model aimed at higher education. The aim of the research as well as the purpose of creating a conceptual model of gamification is to standardize the elements of computer games that can be used in educational e-courses at higher education institutions. In the preparation of this research, the emphasis was placed on the invention and analysis of professional and scientific literature for creating a conceptual model. The model contains a logical representation of two levels of complexity. Three separate e-courses have been created in different courses within the two University institutions, which serve as a tool to check the correctness of the conceptual eRIOOS model. The result of the research is a confirmed conceptual model that is suitable for creating Moodle e-courses of IT teaching orientation in higher education institutions.
Sulfonic Acid-Functionalized Fe3O4 Reinforced Soluble Polyimide: Synthesis and Properties

ABSTRACT In this study, a series of nanocomposite films based on an aromatic polyimide and sulfonic acid-functionalized magnetic nanoparticles was successfully prepared via an in situ technique. For this purpose, new soluble aromatic polyimide containing sulfone group as a polymeric matrix of the nanocomposites was synthesized. The surfaces of MNP were grafted with 3-mercaptopropyl trimethoxysilane. Then sulfonic acid-functionalized magnetic nanoparticle was obtained by oxidation of the thiol group. Effects of sulfonic acid-functionalized magnetic nanoparticles on thermal, tensile, and magnetic properties of the prepared nanocomposite films were studied. The magnetic nanoparticles containing the sulfonic acid groups could have strong intermolecular bond interactions between the hydroxyl groups of SO3H and the sulfone and carbonyl groups of the polyimide matrix which caused the better dispersion of nanoparticle and exhibited superior mechanical properties, good magnetic properties, and high thermal stability. GRAPHICAL ABSTRACT
Fake Job Detection and Analysis Using Machine Learning and Deep Learning Algorithms

With the pandemic situation, there is a strong rise in the number of online jobs posted on the internet in various job portals. But some of the jobs being posted online are actually fake jobs which lead to a theft of personal information and vital information. Thus, these fake jobs can be precisely detected and classified from a pool of job posts of both fake and real jobs by using advanced deep learning as well as machine learning classification algorithms. In this paper, machine learning and deep learning algorithms are used so as to detect fake jobs and to differentiate them from real jobs. The data analysis part and data cleaning part are also proposed in this paper, so that the classification algorithm applied is highly precise and accurate. It has to be noted that the data cleaning step is a very important step in machine learning project because it actually determines the accuracy of the machine learning as well as deep learning algorithms. Hence a great importance is emphasized on data cleaning and pre-processing step in this paper. The classification and detection of fake jobs can be done with high accuracy and high precision. Hence the machine learning and deep learning algorithms have to be applied on cleaned and pre-processed data in order to achieve a better accuracy. Further, deep learning neural networks are used so as to achieve higher accuracy. Finally all these classification models are compared with each other to find the classification algorithm with highest accuracy and precision.
Seismic Design of Offshore Wind Turbines: Good, Bad and Unknowns

Large scale offshore wind farms are relatively new infrastructures and are being deployed in regions prone to earthquakes. Offshore wind farms comprise of both offshore wind turbines (OWTs) and balance of plants (BOP) facilities, such as inter-array and export cables, grid connection etc. An OWT structure can be either grounded systems (rigidly anchored to the seabed) or floating systems (with tension legs or catenary cables). OWTs are dynamically-sensitive structures made of a long slender tower with a top-heavy mass, known as Nacelle, to which a heavy rotating mass (hub and blades) is attached. These structures, apart from the variable environmental wind and wave loads, may also be subjected to earthquake related hazards in seismic zones. The earthquake hazards that can affect offshore wind farm are fault displacement, seismic shaking, subsurface liquefaction, submarine landslides, tsunami effects and a combination thereof. Procedures for seismic designing OWTs are not explicitly mentioned in current codes of practice. The aim of the paper is to discuss the seismic related challenges in the analysis and design of offshore wind farms and wind turbine structures. Different types of grounded and floating systems are considered to evaluate the seismic related effects. However, emphasis is provided on Tension Leg Platform (TLP) type floating wind turbine. Future research needs are also identified.