Miracle-dz/UniFAR-FTUs huggingface dataset:
Who cares? An ethnographic research on the workforce integration of first-generation immigrants in geriatric care in the Netherlands and Germany

Background: Several studies have investigated the experiences of first-generation immigrant nurses in new workplaces. Yet, little is known about how native nurses and newcomers collaborate in their care for ageing residents in European nursing homes. Objective: To gain a deeper understanding of interactions between first-generation immigrant nurses and native nurses in their care for ageing residents in a Dutch nursing home. Methods: Ethnography, including 105 hours of shadowing immigrant and native nurses, eight semi-structured interviews with four immigrant and four established nurses, and two focus group discussions with eight immigrant and six established nurses in a Dutch nursing home. Data were analyzed by a post-positivist grounded theory coding approach. Ethical consideration: The Medical Ethical Review Committee of the Leiden University Medical Center approved this study. Results: The interactions between established staff and newcomers were influenced by norms, rules and regulations, policies and protocols. In daily practice and institutional structure, we observed both opportunities and challenges. The strict time schedules and the requisite standards of care were opportunities related to nurses’ expectations. Residents’ needs were sometimes challenging and inhibited newcomers’ active participation. However, sometimes new practices were developed where nurses created common ground, tinkered, and formed an inclusive playing field to enact good care. Conclusion/ discussion: This study shows that despite obstacles, there was room to make small changes in the rules of the game of nursing. These moments of tinkering may be sufficient to establish a stable, inclusive workforce for first-generation immigrants and give room to the evolvement of hybrid professional identities. Implications: The findings of this Dutch study are relevant for nursing ethics related to ‘good care’ and nurses in other cultural contexts on how the integration of immigrant nurses in European countries in general could be facilitated.
Terahertz Sensing and Communication Towards Future Intelligence Connected Networks

The terahertz (THz) technologies are extremely promising for future 6G wireless communication and sensing systems because of the advantages of ultra-wide available bandwidth. However, the increased operating frequency and bandwidth pose higher requirements in terms of propagation channel modeling, new transmission technologies, high performance components, and signal processing complexity. Therefore, the challenge lies in how to achieve system demands as well as improve the system data rate and sensing resolution with limited hardware complexity and power consumption. In this paper, the latest progress on spectrum and potential application scenarios for the THz band are examined. A hybrid channel modeling framework for the THz band is proposed to improve the accuracy and efficiency of the modeling. The potential intermediate radio frequency (IRF) architecture, key components, and antenna and integration technologies have also been investigated. In particular, the THz subsystem with silicon and III-V compound semiconductor material heterogeneous integration is proposed to promote the performance by utilizing the advantages of different processes and materials. Finally, the prototype and measurement campaign are conducted, which illustrate the advantages of the THz band for high throughput communication and high resolution sensing scenarios. A variety of measurement campaign examples show 210 Gbit/s data transmission rate at 330 m distance, and up to 3 mm invisible imaging, which is the highest performance in this field.
Discovery of heavy negative ions in Titan's ionosphere

Titan's ionosphere contains a rich positive ion population including organic molecules. Here, using CAPS electron spectrometer data from sixteen Titan encounters, we reveal the existence of negative ions. These ions, with densities up to ∼100 cm−3, are in mass groups of 10–30, 30–50, 50–80, 80–110, 110–200 and 200+ amu/charge. During one low encounter, negative ions with mass per charge as high as 10,000 amu/q are seen. Due to their unexpectedly high densities at ∼950 km altitude, these negative ions must play a key role in the ion chemistry and they may be important in the formation of organic‐rich aerosols (tholins) eventually falling to the surface.
Representation Learning of Time Series Data with High-Level Semantic Features

This study proposes a representation method of time-series data by considering its high-level semantic features to help build interpretable neural networks. This method constructs human cognition features as specific high-level semantic information to tackle the issue that cognitions are challenging to apply in representation learning of time series data. Our approach can improve the performance of traditional networks and make it possible to use time-series data in a variety of tasks
CAN PLANNERS TAKE THE LEADERSHIP IN LOCAL ENVIRONMENTAL MANAGEMENT

There is an increasing demand for environmental leadership in the planning process. In collaborative planning models, planners have a distinct role as a bridge between citizens, politicians, and scientists. However, there is limited research evaluating the leadership role of planners in the process of creating high quality environmental plans for local jurisdictions. This study proposes and tests a conceptual model with measurable indicators of planners' use of leadership to facilitate the creation of plans that can benefit the environment. This paper examined two distinct roles for planners: as an information source and as a facilitator. The descriptive results suggest that planners are exercising limited environmental leadership in local land use planning. The explanatory results highlight that the key to improve planners' leadership abilities lies with increasing planning capacity. Several policy recommendations are provided to improve planner's use of leadership processes in environmental planning and management.
Riqueza de borboletas (Lepidoptera) em um fragmento urbano de Cerrado em Mato Grosso do Sul, Brasil

Borboletas estao entre os artropodes melhor estudados, pois participam de diversas interacoes ecologicas. Apesar de ja existirem muitos inventarios de borboletas publicados no Brasil, nenhuma informacao ainda existe em Mato Grosso do Sul. O presente estudo teve como objetivo avaliar a riqueza de especies de borboletas encontradas em um remanescente urbano de cerrado em Campo Grande, Centro-Oeste do Brasil, alem de indicar a presenca de especies raras e indicadora de ambiente preservado. Foram registradas 62 especies de borboletas, pertencentes a seis familias e 15 subfamilias. Entre as especies registradas, 28 pertencem a familia Nymphalidae (45,1%), 16 a Hesperiidae (25,8%), oito a Lycaenidae (12,9%), seis a Pieridae (9,7%) e quatro para Riodinidae (6,5%). As estimativas de riqueza Jack-Knife (de 1a ordem) e Chao2 mostram que entre 81 e 86% das especies, respectivamente, foram registradas durante o periodo do estudo para a area. A lepidopterofauna encontrada nao apresenta especies cuja presenca indica ambiente preservado. Embora a area de estudo seja pequena, estando imersa em uma matriz urbana e sendo constantemente impactada, a reserva representa um ambiente importante para a conservacao de borboletas na cidade de Campo Grande. Butterflies Species (Lepidoptera) in an Urban fragment of Savannah in Mato Grosso do Sul, Brazil. Abstract. Butterflies are among the better studied arthropods, because they participate in several ecological interactions. In spite of already many inventories of butterflies have been published in Brazil, still any information exist in Mato Grosso do Sul. The present study aimed to evaluate the species richness of butterflies found in an urban remnant of savannah in Campo Grande, Midwest of Brazil, besides indicating the presence of rare species and indicative of preserved atmosphere. We registered 62 species of butterflies, ranging in six families and 15 subfamilies, for the area. Among the registered species, 28 belong to the family Nymphalidae (45.1%), 16 to Hesperiidae (25.8%), 8 to Lycaenidae (12.9%), 6 to Pieridae (9.7%) and 4 to Riodinidae (6.5 %). The wealth estimates Jack-Knife (1st order) and Chao2 show that among 81 and 86% of species, respectively, were registered during the period of the study for the area. The found lepidopterofauna didn’t present species whose presence indicates preserved atmosphere. Although the small study area, being immersed in an urban matrix and constantly being impacted, the reserve represents an important environment for the conservation of butterflies in the city of Campo Grande.
Representation Learning for Scene Graphs

—Given the rich downstream use-cases for structured scene data in the form of a scene graph, as shown in [31], [30], [1], we are motivated to explore meth-ods in which scene graphs can be generated, represented, and manipulated. Speciﬁcally, we present work towards automatically learning lower dimensional representations for scene graphs that might be useful for tasks such as graph comparison and generation. In this milestone, we introduce an attempt at learning latent space encodings for scene graphs from the GQA dataset [15] using a Variational Graph Autoencoder (Graph-VAE) [33] [10] with various Graph-Convolutional operators. Initial experiments on a downstream link-prediction task with the Graph-VAE were encouraging, but structural properties inherent to scene graphs motivated additional experiments with different architectures for graph representation learning and graph generation. As such, we present several applications of various Graph-VAE architectures on the task of learning lower dimensional scene graph representations.
How to Run Essential Analyses in R Studio: For First Year Undergraduate Students with No Background in Programming

R is one of my go-to software for data analysis. Since SPSS does not offer some high-end analysis for us on a Macintosh operating system, I was always on the lookout for a better alternative. I have used JASP and JAMOVI as well. However, the degree to which it could assist me with various forms of statistical modeling is minimal. Unlike SPSS, R is more flexible and offers quite a lot of customization for researchers. At first, I was intimidated by R, but, slowly, I managed to learn the basics to help me run most of the analysis required to teach my undergraduate students. I am still learning R and the different packages it offers.
Comparison of Spectral and Finite-Difference Methods for Flood Routing

This investigation presents a spectral method for solving the one-dimensional shallow-water wave equations. The spectral method is based on the Chebyshev collocation technique and finite-difference time stepping. The spectral method and finite-difference Preissmann scheme are applied to route a log-Pearson Type III hydrograph through a wide rectangular channel, and the results are compared. The spectral method performs better than the Preissmann scheme as long as the time-stepping errors are kept low. However, for larger time steps, the Preissmann scheme, which is almost second-order accurate in time (and second-order accurate in space) performs better than the spectral scheme, which is first-order accurate in time and has so-called infinite-order accuracy in space. This seems to indicate that the order of accuracy in time discretization is more important than that in space discretization, in numerical models, for fast-rising floods and friction-dominated flows.
Impact of Performance-Based Financing Implementation on Healthcare Data Quality of Health Management Information System in Sierra Leone

Data quality is an important aspect of data for effective healthcare planning and decision making. The Government of Sierra Leone launched the performance-based financing (PBF) scheme in June 2011, whereby target indicators included improving the quality of data for an informed decision making. We investigated the impact of PBF scheme on healthcare data quality using mixed-method sequential explanatory research design considering three data reporting periods: the pre PBF scheme in 2010, during PBF scheme in 2012, and the post PBF scheme in 2018. Results on timely reporting rate show an average percentage improvement in 2012 by 1.9% and 6.7% compared to 2010 and 2018, respectively. Results on complete reporting rate show an average percentage improvement in 2012 by 2.8% and 6.2% compared to 2010 and 2018, respectively. Results on accurate reporting rate show an average percentage decrease in 2012 by of 5.6% and 8.4% compared to 2010 and 2018, respectively. The results were validated and shown to be statistically significant, implying that the PBF scheme had positive impact on timely and complete data quality dimensions, but on the contrary, negative impact on the accuracy data quality dimension. Quantitative results strongly correlate to the mixed views on PBF obtained from qualitative results.
New Fluorophore and Its Applications in Visualizing Polystyrene Nanoplastics in Bean Sprouts and HeLa Cells

In the domain of environmental science, pollutants of nanoscale plastic dimensions are acknowledged as subjects of intricate significance. Such entities, though minuscule, present formidable challenges to ecological systems and human health. The diminutive dimensions of these contaminants render their detection arduous, thus demanding the inception of avant-garde methodologies. The present manuscript postulates the employment of the tetraphenylethylene functional group with a fused xanthene (TPEF), a distinguished fluorophore, as an exemplary system for the discernment of nanoplastic particulates. The synthesis and characterization of TPEF have been exhaustively elucidated, revealing its paramount fluorescence attributes and inherent affinity for interaction with nanoplastics. When subjected to comparison with TPEF, nanoplastics are observed to manifest a more pronounced fluorescent luminescence than when associated with the conventional Nile Red (NR). Particularly, the TPEF has shown exceptional affinity for polystyrene (PS) nanoplastics. Further, the resilience of nanoplastics within the hypocotyl epidermis of soybeans, as well as their persistence in mung bean sprouts subsequent to rigorous rinsing protocols, has been meticulously examined. Additionally, this investigation furnishes empirical data signifying the existence of nano-dimensional plastic contaminants within HeLa cellular structures. The urgency of addressing the environmental ramifications engendered by these diminutive yet potent plastic constituents is emphatically highlighted in this manuscript. TPEF paves the way for prospective explorations, with the aspiration of devising efficacious mitigation strategies. Such strategies might encompass delineating the trajectories undertaken by nanoplastics within trophic networks or their ingress into human cellular architectures.
A Robot-Operation-System-Based Smart Machine Box and Its Application on Predictive Maintenance

Predictive maintenance is a proactive approach to maintenance in which equipment and machinery are monitored and analyzed to predict when maintenance is needed. Instead of relying on fixed schedules or reacting to breakdowns, predictive maintenance uses data and analytics to determine the appropriate time to perform maintenance activities. In industrial applications, machine boxes can be used to collect and transmit the feature information of manufacturing machines. The collected data are essential to identify the status of working machines. This paper investigates the design and implementation of a machine box based on the ROS framework. Several types of communication interfaces are included that can be adopted to different sensor modules for data sensing. The collected data are used for the application on predictive maintenance. The key concepts of predictive maintenance include data collection, a feature analysis, and predictive models. A correlation analysis is crucial in a feature analysis, where the dominant features can be determined. In this work, linear regression, a neural network, and a decision tree are adopted for model learning. Experimental results illustrate the feasibility of the proposed smart machine box. Also, the remaining useful life can be effectively predicted according to the trained models.
How much deep water is formed in the Southern Ocean

Three tracers are used to place constraints on the production rate of ventilated deep water in the Southern Ocean. The distribution of the water mass tracer PO4* (“phosphate star”) in the deep sea suggests that the amount of ventilated deep water produced in the Southern Ocean is equal to or greater than the outflow of North Atlantic Deep Water from the Atlantic. Radiocarbon distributions yield an export flux of water from the North Atlantic which has averaged about 15 Sv over the last several hundred years. CFC inventories are used as a direct indicator of the current production rate of ventilated deep water in the Southern Ocean. Although coverage is as yet sparse, it appears that the CFC inventory is not inconsistent with the deep water production rate required by the distributions of PO4* and radiocarbon. It has been widely accepted that the major part of the deep water production in the Southern Ocean takes place in the Weddell Sea. However, our estimate of the Southern Ocean ventilated deep water flux is in conflict with previous estimates of the flux of ventilated deep water from the Weddell Sea, which lie in the range 1–5 Sv. Possible reasons for this difference are discussed.
Macroelement for Statically Loaded Shallow Strip Foundation Resting on Unsaturated Soil

AbstractThe load deformation and failure behavior of shallow footings can be described in a macroelement formulation. This paper deals with the study of the failure surface and the definition and validation of plastic load deformation by single surface hardening models. The straightforward application of the plasticity theory to the soil-foundation system makes it possible to extend the given expression for the case of unsaturated soils. This paper studies a small-scale footing test on unsaturated sand for the formulation of the elastoplastic macroelement of shallow footings under a centrally applied vertical load. The influence of soil suction on different parameters associated with the macroelement is studied and calibrated against experimental results. The presented model shows good agreement with the experimental results. Finally, the limitations and still open questions of the approach are discussed in detail.
Exact Geosedics and Shortest Paths on Polyhedral Surface

We present two algorithms for computing distances along a non-convex polyhedral surface. The ﬁrst algorithm computes exact minimal-geodesic distances and the second algorithm combines these distances to compute exact shortest-path distances along the surface. Both algorithms have been extended to compute the exact minimal-geodesic paths and shortest paths. These algorithms have been implemented and validated on surfaces for which the correct solutions are known, in order to verify the accuracy and to measure the run-time performance, which is cubic or less for each algorithm. The exact-distance computations carried out by these algorithms are feasible for large-scale surfaces containing tens of thousands of vertices, and are a necessary component of near-isometric surface ﬂattening methods that accurately transform curved manifolds into ﬂat representations.
Comparison of loop-mediated isothermal amplification, multiplex PCR, and REP- PCR techniques for identification of carbapenem-resistant Acinetobacter baumannii clinical isolates

Background and Objectives: Acinetobacter baumannii, an opportunistic pathogen, is related to hospital-acquired infections and increased mortality. This study aimed to develop the loop-mediated isothermal amplification (LAMP) test for the fast-detecting of A. baumannii isolates as well as determining genetic relatedness for these isolates via the REP-PCR technique. Materials and Methods: LAMP primers and multiplex PCR primers were designed for recognizing A. baumannii isolates harboring the bla SHV-1 , bla PER-1 , bla TEM-1, AMPC, qnr, and aac (6)-1 genes, were collected (October 2020 to February 2021) from Shahid Motahari Hospital, Tehran, Iran. Combination disc test (CDT) results were used to assess the phenotypic identification of isolates from ESBL producers. The sensitivity of the LAMP method was evaluated using a range of serial dilutions of genomic DNA. Results were compared between the LAMP technique, and multiplex PCR. The genetic diversity of clinical isolates was determined by REP-PCR. Results: Among one hundred A. baumannii samples and based on the combined disc test, 56% of isolates were ESBL producers. The sensitivity of the LAMP technique for the identification of A. baumannii was 4.06 ng/μl whilst the multiplex PCR was (16.2 ng/μl). Regarding multiplex PCR, (68%) of the isolates were bla SHV-1 positive, (40%) bla PER-1, (85%) aac (6′)-1, AMPC (67%), bla TEM-1 (63%), and (15%) qnr respectively. While in LAMP, (69%) of isolates were bla SHV-1 positive, (86%) aac (6′)-1, and (20%) qnr. The results of AMPC, bla TEM-1 , and bla PER-1 genes showed 100% compatibility between multiplex PCR and LAMP assays. The results of REP-PCR indicated there were 17 clones, clone A at 14% was the most prevalent of the isolates. Conclusion: Wherever equipment and financial constraints are crucial, the LAMP test offers a better and more potent detection rate for the identification of A. baumannii isolates than multiplex PCR. Furthermore, the genetic diversity of A. baumannii in these clinical isolates showed frequent commonality of genotypes.
Relationship between erythemal irradiance and total solar irradiance in South‐Western Spain

[1] In the last years, many studies have focused on the study of the ultraviolet radiation or the total solar radiation in Southwestern Europe. This area presents a particular interest due to the intense solar radiation which reaches the Earth's surface at these latitudes. Despite of this high interest, the influence of the atmospheric factors on the relationship between both variables is not well documented for that region. In this work, the ultraviolet erythemal irradiance (UVER) and the total solar irradiance (310–2800 nm) at three locations in Southwestern Spain were measured between January 2001 and December 2005. The main goal of this paper is to analyze the relationship between ultraviolet and total solar irradiance as described by their ratio. This ratio represents the percentage of UV erythemal irradiance over the total solar irradiance at Earth's surface. The results show that this ratio varies in time. It shows a day-to-day and seasonal variability mainly due to changes in sky conditions (regarding cloudiness and aerosols) and in the slant column of ozone, respectively. Differences in ozone may cause a relative increase in the ratio higher than 100% between winter and summer. This fact stresses the importance of reporting information about the UV radiation at ground level to the people mainly during summer. Clouds play also an important role, since highly different conditions between consecutive days are responsible for up to 60% of the ratio variability. The results show that cloudiness attenuates more the total solar radiation than the UV solar radiation. Additionally, high changes in aerosol load can produce a short-term decrease in the ratio of 13–15%, attenuating differently UVER than total solar irradiance.