Miracle-dz/UniFAR-FTUs huggingface dataset:
Design, Optimization, and Application of a 3D-Printed Polymer Sample Introduction System for the ICP-MS Analysis of Nanoparticles and Cells

Commonly used sample introduction systems for inductively coupled plasma mass spectrometry (ICP-MS) are generally not well-suited for single particle ICP-MS (spICP-MS) applications due to their high sample requirements and low efficiency. In this study, the first completely 3D-printed, polymer SIS was developed to facilitate spICP-MS analysis. The system is based on a microconcentric pneumatic nebulizer and a single-pass spray chamber with an additional sheath gas flow to further facilitate the transport of larger droplets or particles. The geometry of the system was optimized using numerical simulations. Its aerosol characteristics and operational conditions were studied via optical particle counting and a course of spICP-MS measurements, involving nanodispersions and cell suspensions. In a comparison of the performance of the new and the standard (quartz microconcentric nebulizer plus a double-pass spray chamber) systems, it was found that the new sample introduction system has four times higher particle detection efficiency, significantly better signal-to-noise ratio, provides ca. 20% lower size detection limit, and allows an extension of the upper limit of transportable particle diameters to about 25 µm.
An overview of Business Intelligence research in healthcare organizations using a topic modeling approach

The intersection of Business intelligence (BI) and data analytics with healthcare has witnessed remarkable growth in recent decades. With the aim of identifying the most attentive themes, topics, and research priorities, this review endeavors to perform a literature analysis on research articles addressing business intelligence in healthcare. To conduct the study, a total of 751 articles, published between 2002 and 2023, were analyzed through topic modeling, a technique used in natural language processing (NLP) and machine learning. As a result, seven major themes were identified: Unique Device Identification, Big Data and Data Analytics, Operational Efficiency, Effective Decision-Making, Healthcare Delivery Optimization, Resource Optimization and Cost Reduction, and Nosocomial Infections are growing. The analysis revealed that there is a growing interest in leveraging business intelligence for infection control and operational improvements using health information technology and data analytics, while efforts to optimize resources/reduce costs appear to be on the decline. The research findings shed light on the increasing capabilities and use of business intelligence in healthcare, highlighting opportunities for future research.
Propidium Monoazide-Treated, Cell-Direct, Quantitative PCR for Detecting Viable Chloramphenicol-Resistant Escherichia coli and Corynebacterium glutamicum Cells

With the rapid development and commercialization of industrial genetically modified microorganisms (GMMs), public concerns regarding their potential effects are on the rise. It is imperative to promptly monitor the unintended release of viable GMMs into wastewater, the air, and the surrounding ecosystems to prevent the risk of horizontal gene transfer to native microorganisms. In this study, we have developed a method that combines propidium monoazide (PMA) with a dual-plex quantitative PCR (qPCR) approach based on TaqMan probes. This method targets the chloramphenicol-resistant gene (CmR) along with the endogenous genes D-1-deoxyxylulose 5-phosphate synthase (dxs) and chromosomal replication initiator protein (dnaA). It allows for the direct quantitative detection of viable genetically modified Escherichia coli and Corynebacterium glutamicum cells, eliminating the requirement for DNA isolation. The dual-plex qPCR targeting CmR/dxs and CmR/dnaA demonstrated excellent performance across various templates, including DNA, cultured cells, and PMA-treated cells. Repeatability and precision, defined as RSDr% and bias%, respectively, were calculated and found to fall within the acceptable limits specified by the European Network of GMO Laboratories (ENGL). Through PMA–qPCR assays, we determined the detection limits for viable chloramphenicol-resistant E. coli and C. glutamicum strains to be 20 and 51 cells, respectively, at a 95% confidence level. Notably, this method demonstrated superior sensitivity compared to Enzyme-Linked Immunosorbent Assay (ELISA), which has a detection limit exceeding 1000 viable cells for both GM bacterial strains. This approach offers the potential to accurately and efficiently detect viable cells of GMMs, providing a time-saving and cost-effective solution.
Silencing LY6D Expression Inhibits Colon Cancer in Xenograft Mice and Regulates Colon Cancer Stem Cells’ Proliferation, Stemness, Invasion, and Apoptosis via the MAPK Pathway

This study explored the role of lymphocyte antigen 6 family member D (LY6D) in colon cancer stem cells’ (CCSCs) proliferation and invasion. LY6D was knocked down using siRNA, and the down-regulation of LY6D was verified using Western blotting. After LY6D knockdown, CCSCs’ proliferation, stemness, and invasion were suppressed, whereas apoptosis was increased. Gene Ontology (GO) enrichment analysis revealed that the differentially expressed genes (DEGs) between siLY6D and the negative control groups were significantly enriched in the cell–substrate adherens junction, focal adhesion, and cell–substrate junction terms. Meanwhile, the Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that the DEGs were significantly enriched in the MAPK pathway. In addition, Western blotting results showed that pBRAF and pERK1/2, cascade kinases of the MAPK pathway, were significantly down-regulated after LY6D knockdown. In addition, nude mice xenograft experiments showed that the siLY6D treatment decreased tumor sizes and weights and improved tumor-bearing mice survival rates compared with the control group. In conclusion, these findings indicate that LY6D, which is highly expressed in CCSCs, is a key factor involved in tumor growth and development and might be a potential cancer marker and therapeutic target for colon cancer.
Ainda há esperança? Eficiência do gasto com segurança pública no Brasil

Introdução/objetivo: este artigo tem como objetivo identificar, mediante análise envoltória de dados (DEA, sigla em inglês), a eficiência do gasto em segurança pública nos estados brasileiros mais o Distrito Federal, de 2017 a 2020, com relação aos índices de criminalidade. Metodologia: o artigo é uma pesquisa descritiva e de natureza quantitativa. A técnica da DEA aplicada foi orientada ao modelo BCC (Banker, Charnes & Cooper, 1984 [retorno variável de escala]), com modelo input (orientado aos insumos). A variável de entrada utilizada foi a despesa com segurança pública, enquanto as variáveis de saída foram latrocínios, homicídios dolosos, roubo e furto de veículos, bem como tráfico de entorpecentes. Na sequência, foi executado o método proposto e foram apresentados os resultados encontrados após a análise do modelo. Resultados: os resultados indicam que, no período analisado, em média, a aplicação dos recursos das unidades federativas (UF) tem apresentado um percentual de 73.33%, mas ainda há muitas UF que apresentam potencial para utilizar de forma mais eficiente, quando os seus recursos são comparados aos demais estados. Ademais, os resultados demonstram que houve apenas três estados com eficiência máxima, em todos os anos, no período analisado. Conclusões: ainda há necessidade de que políticas públicas voltadas para a questão da segurança sejam refinadas para que as UF possam atingir maior eficiência dos dispêndios nessa área, com vistas a reduzir os índices de criminalidade. Por fim, a identificação detalhada das causas da ineficiência do estado de Roraima, Brasil, que apresenta maior gasto em segurança pública e menor eficiência técnica, pode contribuir para o entendimento de políticas públicas no âmbito da segurança.
Factors influencing strategy implementation in Community Based Organizations in Seme sub - county, Kenya

xi CHAPTER ONE: INTRODUCTION . 1 1.1 Background of study . 1 1.1.1 The Concept of Strategy Implementation.2 1.1.2 Community Based Organizations in Kenya . 4 1.1.3 Community Based Organizations in SemeSub County.6 1.2 Research Problem . 7 1.3 Research Objectives . 8 1.4 Value of the Study . 8 CHAPTER TWO: LITERATURE REVIEW . 10 2.
A Schema for Multimodal Communication Applied to Male Mantled Howler Monkeys (Alouatta palliata)

Our methodological framework is based upon Partan & Marler’s (2005) model. These authors considered the costs and benefits of multimodal communication, proposing a schema for its classification intended for general use that is well suited to both qualitative and quantitative analyses. In the present report, we reanalyze data collected in the mid-1970s (see Jones, 2006a) on the mantled howler monkey (Alouatta palliata), using Partan & Marler’s (2005) classification system to organize the results for the study animals. The present brief communication is intended to show that Partan & Marler’s (2005) classification system, intended for general use, provides a robust model for the study of multimodal communication in howlers; and that it may be helpful, as well, for the analysis of complex signaling in other primate taxa. Methods
A Description of the Advanced Research WRF Version 2

Abstract : The development of the Weather Research and Forecasting (WRF) modeling system is a multiagency effort intended to provide a next-generation mesoscale forecast model and data assimilation system that will advance both the understanding and prediction of mesoscale weather and accelerate the transfer of research advances into operations. The model is being developed as a collaborative effort ort among the NCAR Mesoscale and Microscale Meteorology (MMM) Division, the National Oceanic and Atmospheric Administration's (NOAA) National Centers for Environmental Prediction (NCEP) and Forecast System Laboratory (FSL), the Department of Defense's Air Force Weather Agency (AFWA) and Naval Research Laboratory (NRL), the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma, and the Federal Aviation Administration (FAA), along with the participation of a number of university scientists. The WRF model is designed to be a flexible, state-of-the-art, portable code that is an efficient in a massively parallel computing environment. A modular single-source code is maintained that can be configured for both research and operations. It offers numerous physics options, thus tapping into the experience of the broad modeling community. Advanced data assimilation systems are being developed and tested in tandem with the model. WRF is maintained and supported as a community model to facilitate wide use, particularly for research and teaching, in the university community. It is suitable for use in a broad spectrum of applications across scales ranging from meters to thousands of kilometers. Such applications include research and operational numerical weather prediction (NWP), data assimilation and parameterized-physics research, downscaling climate simulations, driving air quality models, atmosphere-ocean coupling, and idealized simulations (e.g boundary-layer eddies, convection, baroclinic waves).
Progresses and Perspectives of Ecological Research in China

Abstract: Ecology has been recognized as an independent discipline since 1869, when Ernest Haeckel first used this terminology and defines it as a branch of science for studying the interactions between organisms and their environment. The modern ecology expanded the subject and scope of the study; broke throw the limitation of pure naturalism tendency and was actively involved in solving the urgent task of world-concerned global development problem. While equipped by modern methodology and equipments, it becomes a bridge between science and development. Although a wealth of knowledge with deep ecological thought has been accumulated in the long course of China's development, it has not developed into a science until the 1950s. The development of ecology in China may roughly be divided into four phases (i.e. primitive embryonic phase, fundamental ecological study phase, ecosystem study phase, and the phase for sustainable development. This paper gives a general review of the development of ecology in China and introduced the progress in several selected areas. These include: biodiversity conservation, ecological research related to global change, restoration of degraded ecosystems, desertification control, ecosystem study on the Qinghai-Tibetan Plateau, promotion of sustainable development from concept to action, and evaluation of ecosystem services and eco-compensation, etc. Based on the current development status of ecological science in China and the needs of the country, six priority areas for development of Ecology in the future were recommended.
Prognostic value of lymphocyte-to-monocyte ratio in gastric cancer patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis

Background Emerging evidence suggests a correlation between the lymphocyte-monocyte ratio (LMR) and the prognosis in patients with gastric cancer (GC) undergoing immune checkpoint inhibitor (ICI) therapy. Nevertheless, the existing findings remain contentious. Methods A comprehensive search of literature was conducted in databases including PubMed, Embase, Web of Science, and the Cochrane Library, spanning from the inception of each database to August 30, 2023 to collect studies exploring the interplay between LMR and clinical outcomes. Eligible studies were selected following predefined inclusion and exclusion criteria. Primary outcomes encompassed progression-free survival (PFS) and overall survival (OS), which were estimated using hazard ratios (HR) and corresponding 95% confidence intervals (CI). Results Our analysis incorporated eight cohort studies, involving 815 patients. Aggregate data revealed associations between an elevated LMR at baseline and prolonged PFS (HR=0.58; 95% CI: 0.47–0.71, p<0.00001) and improved OS (HR=0.51, 95% CI: 0.33–0.79; p=0.003). Furthermore, LMR exhibited a favorable association with PFS after treatment (HR=0.48; 95% CI: 0.29–0.79; p= 0.004), while such a correlation was not evident in the OS analysis. Importantly, a high level of LMR was associated with prolonged PFS across varying sample sizes, follow-up duration, treatment combinations, line of therapy, and cut-off values. Conclusion A high pre-treatment LMR is associated with improved OS and PFS in GC patients treated with ICIs. LMR emerges as a potent biomarker for prognostic assessment in these patients, offering valuable insights for informed treatment decisions within the domain of GC immunotherapy. Systematic review registration PROSPERO, identifier CRD42021228512
Exploring 3D Transfer Learning CNN Models for Alzheimer's Disease Diagnosis from MRI Images

Lately, deep learning has become increasingly popular in resolving issues across multiple domains, including medical image analysis. This research introduces a process based on deep convolutional neural networks to diagnose Alzheimer's disease and its various stages by utilizing magnetic resonance imaging (MRI) scans. Identifying Alzheimer's disease (AD) in elderly individuals can be quite difficult. This is because it harms the brain cells related to memory and thinking abilities, and it's hard to tell apart from normal brain patterns in scans. Detecting it needs a special way to represent features for sorting it out. Deep learning methods can acquire such representations from the MRI data. In this paper, five different transfer learning models are trained in 15 binary classifiers, each of them can classify two of Alzheimer's disease, Mild Cognitive Impairment (MCI), and Cognitively Normal (CN) classes. This method finds the best transfer learning model for classifying each binary comparison. The proposed technique results in best accuracy of 92% for the AD vs. CN classifier, 94% for the AD vs. MCI classifier, and 72% for the MCI vs. CN classifier, which shows the effectiveness of transfer learning in distinguishing the AD vs. CN and the AD vs. MCI cases.
Application of Graphic Statics and Strut-and-Tie Models Optimization Algorithm in Innovative Timber Structure Design

Timber has long been extensively employed within the construction industry as a famous, environmentally friendly, and low-carbon material. Considering that construction constitutes one of the most significant contributors to carbon emissions throughout the entire life-cycle of a building, there is an urgent desire to incorporate timber into this domain. Nevertheless, the use of timber faces inherent challenges stemming from its anisotropic nature, a result of the natural growth of timber fibers, which makes it challenging for it to function as a primary load-bearing material in coping with the various complex stresses inherent in architectural applications. Numerous designers have attempted to address this limitation through over-sized members and reinforcement at joints; however, none have satisfactorily resolved this issue in an economical manner. In this article, we introduce the Strut-and-Tie models (STM) from Graphic Statics (GS) and a topological optimization algorithm. This algorithm has the capability to generate a ‘load-minimizing path’ STM based on external load support conditions and the maximum structural path span. Regardless of the complexity of the initial external loads, each load transfer path in the optimized STM bears loads in only one direction, representing an optimal solution with minimal internal loads that align seamlessly with the characteristics of timber. Consequently, we endeavor to adopt this optimization algorithm to propose a structural design methodology, with the aspiration of designing structural systems that harness the unique attributes of timber perfectly and applying them to various architectural scenarios. Ultimately, we conclude that structural systems designed based on optimized STM are adaptable to diverse architectural contexts, and when applied to small-scale buildings, this method can save approximately 20% of material consumption compared to conventional timber frame structures, while in the case of mid-rise to high-rise buildings, it can lead to a material savings of approximately 5%.
Aeolian dune migration along the Ceará coast, north‐eastern Brazil

Aeolian dune dimensions and migration rates are analysed along the Ceará coast, north‐east Brazil. Dunes that are currently mobile along the Ceará coast are composed of barchans and sand sheets. The results show that barchans maintain an equilibrium form, which can be characterized by values of dimensionless shape parameters H/W and W/L, where H is the dune height, W is the wing‐to‐wing width and L is the dune length. Dunes are highly mobile, with average migration rates of 17·5 m year−1 for barchans and 10 m year−1 for sand sheets. The calculated migration rates were found to depend strongly on dune dimensions for both barchans and sand sheets, i.e. the larger the dune is, the lower the migration rate will be. This size dependence was associated with the existence of a representative common transport rate along the dune fields, which induces a different dune migration rate dependent on dune size. Finally, from the observed dune evolution, an aggregated scale aeolian sediment transport was inferred. This bulk transport rate, of the order of 90–100 m3 m−1 year−1, is only valid for a timescale of years to decades, which is the timescale used in dune evolution analysis.
Measuring carbon dioxide emissions for regional tourism and its factor decomposition:A case study of Jiangsu province

Carbon dioxide emissions of tourism, as an important study issue in tourism industry in the 21 st century, is a vital index reflecting its effects on environment change. It is difficult to measure the emissions of regional tourism. The article, taking Jiangsu province as a case, based on the input-output tables and tourism expenditures of 1997, 2002 and 2007,makes an analysis of the direct emissions and indirect emissions of tourism from food,accommodation, transportation, sightseeing, shopping, entertainment and postal services, and then explores the mechanism of influencing factors by Logarithmic Mean Divisia Index. The results are as follows: The total emissions of tourism industry in Jiangsu province in 1997,2002 and 2007 were 22.57267 Mt, 33.90042 Mt and 62.43800 Mt, respectively, and the annual rate of growth was 10.71%. The indirect emissions account for about 73% of the total emissions. These percentages of food, accommodation, transportation, sightseeing, shopping and entertainment of total emissions in Jiangsu province are comparatively balanced, which,to some extent, reflects the character that the percentage of emissions from tourism sightseeing in China is higher than that of global level and national levels. The total emissions of domestic tourists are evidently higher than those of inbound tourists; however,the per- trip emissions of the inbound tourists are 4- 7 times more than those of domestic tourists. There are significant differences of total emissions and per capita emissions among the cities within the province. Among the five factors affecting emissions of tourism industry,the increase of industry size and expenditure size are generally found to be principal drivers of emission growth, whereas the main factors restricting emissions are the decrease of energy intensity and the change of energy share. In addition, the effect of consumption structure shows fluctuation in different stages. These results imply the emission reduction of tourism industry not only needs the share responsibility from all tourism sectors but also strongly relies on the cooperation with related industries, which offer the intermediate goods for the consuming of tourism. Domestic tourists are the main carbon source, but still require more emission space due to low per capita emissions. The cities with higher per capita emissions should bear more obligation of emission reduction. Finally, it should be the main direction of emission reduction to reduce energy use intensity and develop low-carbon tourism behavior.
Conflicts in Neogeography Maps

Creating maps, in web 2.0 environments, also called neogeography maps involves map mash-up techniques by which selected base map (Google Maps or OpenStreetMap or alike) is combined with the data collected by users. Unlike traditional maps, these maps are not often designed in balance (and by cartographic experts). Therefore, the maps often suffer from conflicts when the collected data is put together with the base map. The base map and the topic layers themselves suffer from 'internal' conflicts as well. This paper clearly illustrates these conflicts with categorization. A case study (Haiti Crisis Map) was selected to provide solutions for conflicts considering the damage assessment use and implemented through a web map. The improved map was tested against the original map. The study revealed that the original map have considerable amount of conflicts which were reduced in improved map.
Two approaches in defining topological charge of bound states in the continuum in multipolar lattices

Optical bound states in the continuum (BICs) are valuable in engineering effective optical resonators. These states are vortex centers of polarization vector in the far-field and gradient of quasi-mode coupling strength. We compare two approaches in defining topological charge of the BICs observed in lattice of resonant multipoles.