Miracle-dz/UniFAR-FTUs huggingface dataset:
Nano-Lipids Based on Ginger Oil and Lecithin as a Potential Drug Delivery System

Lipid nanoparticles based on lecithin are an interesting part of drug delivery systems. However, the stability of lecithin nano-lipids is problematic due to the degradation of lecithin, causing a decrease in pH. In this study, the modification of the conventional nano-lipid-based soybean lecithin was demonstrated. Ginger-oil-derived Zingiber officinale was used along with lecithin, cholesterol and span 80 to fabricate nano-lipids (GL nano-lipids) using a thin-film method. TEM and a confocal microscope were used to elucidate GL nano-lipids’ liposome-like morphology. The average size of the resultant nano-lipid was 249.1 nm with monodistribution (PDI = 0.021). The ζ potential of GL nano-lipids was negative, similarly to as-prepared nano-lipid-based lecithin. GL nano-lipid were highly stable over 60 days of storage at room temperature in terms of size and ζ potential. A shift in pH value from alkaline to acid was detected in lecithin nano-lipids, while with the incorporation of ginger oil, the pH value of nano-lipid dispersion was around 7.0. Furthermore, due to the richness of shogaol-6 and other active compounds in ginger oil, the GL nano-lipid was endowed with intrinsic antibacterial activity. In addition, the sulforhodamine B (SRB) assay and live/dead imaging revealed the excellent biocompatibility of GL nano-lipids. Notably, GL nano-lipids were capable of carrying hydrophobic compounds such as curcumin and performed a pH-dependent release profile. A subsequent characterization showed their suitable potential for drug delivery systems.
Failure Modes and Effect Analysis of Use Cases: A Structured Approach to Engineering Fault Tolerance Requirements

— Fault tolerance – an ability of a system to cope with errors – is an important characteristic of dependable systems. However, software development approaches traditionally give precedence to modelling nominal system behaviour over modelling system behaviour in presence of faults. This leads to ad-hoc and error prone implementation of fault tolerance mechanisms. In this paper, we propose a systematic approach to elicitation and modelling of fault tolerance-related requirements. Our approach is based on using Failure Modes and Effect Analysis (FMEA) that is used to identify faults, their detection and error recovery. We rely on use-case modelling to structure system behaviour and propose to conduct FMEA of each individual use case. Our approach facilitates elicitation and structuring of fault tolerance behaviour. It enables an integrated modelling of nominal and abnormal system behaviour from early development phases.
Predicting Frost Depth of Soils in South Korea Using Machine Learning Techniques

Predicting the frost depth of soils in pavement design is critical to the sustainability of the pavement because of its mechanical vulnerability to frozen-thawed soil. The reliable prediction of frost depth can be challenging due to the high uncertainty of frost depth and the unavailability of geotechnical properties needed to use the available empirical- and analytical-based equations in literature. Therefore, this study proposed a new framework to predict the frost depth of soil below the pavement using eight machine learning (ML) algorithms (five single ML algorithms and three ensemble learning algorithms) without geotechnical properties. Among eight ML models, the hyperparameter-tuned gradient boosting model showed the best performance with the coefficient of determination (R2) = 0.919. Furthermore, it was also shown that the developed ML model can be utilized in the prediction of several levels of frost depth and assessing the sensitivity of pavement-related predictors for predicting the frost depth of soils.
The effect of the interplanetary magnetic field on sidereal variations observed at medium depth underground detectors

It has been known for some years that the intensity variations in sidereal time observed by muon detectors at moderate underground depths are sensitive to the polarity of the interplanetary magnetic field (ipmf) near the Earth. There are differences in the response to these anisotropies as observed in the Norhtern and southern hemispheres. When fully understood, the nature of the anisotropy seems likely to provide information on the 3-dimensional structure of the heliomagnetosphere, its time variations, and its linking with the local interstellar field. The summation harmonic dials for the sidereal diurnal variation during 1958 to 1982 show that there is a strong dependence on whether the ipmf near the Earth is directed outwards from the Sun or inwards it.
Economical Chemical Recycling of Complex PET Waste in the Form of Active Packaging Material

Since millions of tons of packaging material cannot be recycled in conventional ways, most of it ends up in landfills or even dumped into the natural environment. The researched methods of chemical depolymerization therefore open a new perspective for the recycling of various PET materials, which are especially important for packaging. Food preservative packaging materials made from PET plastics are complex, and their wastes are often contaminated, so there are no sophisticated solutions for them in the recycling industry. After integrating the biopolymer chitosan, which is derived from natural chitin, as an active surface additive in PET materials, we discovered that it not only enriches the packaging material as a microbial inhibitor to reduce the bacteria Staphylococcus aureus and Escherichia coli, thus extending the shelf life of the contained food, but also enables economical chemical recycling by alkaline or neutral hydrolysis, which is an environmentally friendly process. Alkaline hydrolysis at a high temperature and pressure completely depolymerizes chitosan-coated PET packaging materials into pure terephthalic acid and charcoal. The products were characterized by Fourier-transform infrared spectroscopy, proton nuclear magnetic resonance spectroscopy, and elemental analysis. The resulting reusable material represents raw materials in chemical, plastic, textile, and other industries, in addition to the antimicrobial function and recyclability itself.
Evaluation of Gridded Precipitation Data for Hydrologic Modeling in North-Central Texas

Over the past few decades, several high-resolution gridded precipitation products have been developed using multiple data sources and techniques, including measured precipitation, numerical modeling, and remote sensing. Each has its own sets of uncertainties and limitations. Therefore, evaluating these datasets is critical in assessing their applicability in various climatic regions. We used ten precipitation datasets, including measured (in situ), gauge-based, and satellite-based products, to assess their relevance for hydrologic modeling at the Bosque River Basin in North-Central Texas. Evaluated datasets include: (1) in situ station data from the Global Historical Climate Network (GHCN); (2) gauge-based dataset Daymet and the Parameter-elevation Regression on Independent Slope Model (PRISM); (3) satellite-based dataset Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG), Early and Late, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) and PERSIANN-CCS (Cloud Classification System); (4) satellite-based gauge-corrected dataset IMERG-Final, PERSIANN-CDR (Climate Data Record), and CHIRPS (Climate Hazards Group Infrared Precipitation with Station data). Daily precipitation data (2000–2019) were used in the Soil and Water Assessment Tool (SWAT) for hydrologic simulations. Each precipitation dataset was used with measured monthly United States Geological Survey (USGS) streamflow data at three locations in the watershed for model calibration and validation. The SUFI-2 (Sequential Uncertainty Fitting) method on the SWAT-CUP (Calibration and Uncertainty Program) was used to quantify and compare the uncertainty in streamflow simulations from all precipitation datasets. The study has also analyzed the uncertainties in SWAT model parameter values under different gridded precipitation datasets. The results showed similar or better model calibration/validation statistics from gauge-based (Daymet and PRISM) and satellite-based gauge-corrected products (CHIRPS) compared with the GHCN data. However, satellite-based precipitation products such as PERSIANN-CCS and PERSIANN-CDR unveil comparatively inferior to capture in situ precipitation and simulate streamflow. The results showed that gauge-based datasets had comparable and even superior performances in some metrics compared with the GHCN data.
Robust Structural Stability, Stability Margins, and Maximum Uncertainty Amplification for 2-D Uncertain Systems via Structured Lyapunov Functions and Matrix Annihilators

This article considers two-dimensional (2-D) uncertain systems with homogeneous or mixed dynamics, and addresses the following three problems: establishing robust structural stability, computing robust structural stability margins, and determining the maximum uncertainty amplification that preserves robust structural stability. Two sufficient linear matrix inequality (LMI) conditions are proposed for establishing robust structural stability obtained by introducing an equivalent closed-loop complex system and by searching for real or complex structured Lyapunov functions and matrix annihilators parameterized by the uncertainties and auxiliary quantities. Moreover, it is shown that lower bounds of the introduced robust structural stability margins and maximum uncertainty amplification can be obtained by solving quasi-convex optimization problems under some restrictions on the sought Lyapunov functions or on the set of uncertainties. Lastly, the nonconservatism of the proposed results is analyzed, showing that the proposed LMI condition based on the use of complex Lyapunov functions is not only sufficient but also necessary under some assumptions.
Sistema de detección de movimiento con sensor ultrasonido y Arduino para controlar el aforo de turistas

Resumen Introducción: A raíz de la pandemia ocasionada por el virus Sars-Cov-2, los países han impuesto medidas para que los establecimientos puedan normalizar poco a poco sus actividades en una etapa de transición que apunta a la reactivación económica en el sector turismo. Para la reapertura de los escenarios dispuestos en el turismo cultural, es necesario el estricto cumplimiento del distanciamiento social y evitar las aglomeraciones, razón por la cual resulta indispensable limitar el aforo o la capacidad de visitantes. Objetivo: Presentar la implementación de un modelo de adquisición de datos utilizando un sensor ultrasonido HC-SR04 programado con Arduino para controlar el aforo máximo de turistas en entornos cerrados tales como museos, bibliotecas, parques temáticos, edificaciones, galerías de arte y sitios arqueológicos. Método: Se propuso la implementación de un sistema basado en IoT y analítica de datos en un contexto turístico. La programación con código Arduino permitió la captura y visualización de datos durante de 48 horas. Resultados: Mediante el análisis de la información capturada fue posible alertar el sobrelimite del aforo parametrizado identificando a través de las notificaciones los niveles de riesgo. Conclusiones: El sistema desarrollado permite alertar sobre el aforo máximo en espacios cerrados, generando control y reduciendo la probabilidad de contagio en estos espacios.
Modern Immunotherapy in the Treatment of Triple-Negative Breast Cancer

Simple Summary This review summarizes reports from the latest clinical trials assessing the safety and clinical effectiveness of new biological drugs stimulating the immune system to fight cancer. The aim of this study is to show the enormous therapeutic potential of monoclonal antibodies in the treatment of cancer, in particular triple negative breast cancer (TNBC). Introduction of these innovative drugs to the standard clinical cancer therapies, including TNBC, allows for an increase in the response rate to the applied treatment, and consequently extending the lives of patients suffering from cancer. We hope to draw attention to the extremely difficult-to-treat TNBC, as well as the importance of the development of clinical trials evaluating drugs modulating the immune system in TNBC therapy. Abstract Triple-Negative Breast Cancer is a subtype of breast cancer characterized by the lack of expression of estrogen receptors, progesterone receptors, as well as human epidermal growth factor receptor 2. This cancer accounts for 15–20% of all breast cancers and is especially common in patients under 40 years of age, as well as with the occurring BRCA1 mutation. Its poor prognosis is reflected in the statistical life expectancy of 8–15 months after diagnosis of metastatic TNBC. So far, the lack of targeted therapy has narrowed therapeutic possibilities to classic chemotherapy. The idea behind the use of humanized monoclonal antibodies, as inhibitors of immunosuppressive checkpoints used by the tumor to escape from immune system control, is to reduce immunotolerance and direct an intensified anti-tumor immune response. An abundance of recent studies has provided numerous pieces of evidence about the safety and clinical benefits of immunotherapy using humanized monoclonal antibodies in the fight against many types of cancer, including TNBC. In particular, phase three clinical trials, such as the IMpassion 130, the KEYNOTE-355 and the KEYNOTE-522 resulted in the approval of immunotherapeutic agents, such as atezolizumab and pembrolizumab by the US Food and Drug Administration in TNBC therapy. This review aims to present the huge potential of immunotherapy using monoclonal antibodies directed against immunosuppressive checkpoints—such as atezolizumab, avelumab, durvalumab, pembrolizumab, nivolumab, cemiplimab, tremelimumab, ipilimumab—in the fight against difficult to treat TNBCs as monotherapy as well as in more advanced combination strategies.
Redes Auto-Reconfiguráveis Randomizadas para Comunicação Distribuída em Datacenters

Neste artigo nós estudamos os benefícios de randomização no projeto de topologias de redes auto-reconfiguráveis, ou seja, redes que se adaptam dinamicamente à demanda que atendem em tempo real, de forma online. Apresentamos uma rede randomizada auto-reconfigurável com topologia em árvore, que utiliza randomização para reduzir o custo esperado de reconfiguração por um fator constante, comparado a soluções determinísticas existentes. A nova solução é simples, de fácil implementação, totalmente distribuída e concorrente. Nós provamos que o algoritmo proposto é correto, provamos limites de custo amortizado no pior caso e apresentamos resultados de simulação em sequências de requisições com localidade de referência espacial e temporal variáveis.
Image secure transmission for optical orthogonal frequency-division multiplexing visible light communication systems using chaotic discrete cosine transform

Abstract. A physical encryption scheme for orthogonal frequency-division multiplexing (OFDM) visible light communication (VLC) systems using chaotic discrete cosine transform (DCT) is proposed. In the scheme, the row of the DCT matrix is permutated by a scrambling sequence generated by a three-dimensional (3-D) Arnold chaos map. Furthermore, two scrambling sequences, which are also generated from a 3-D Arnold map, are employed to encrypt the real and imaginary parts of the transmitted OFDM signal before the chaotic DCT operation. The proposed scheme enhances the physical layer security and improves the bit error rate (BER) performance for OFDM-based VLC. The simulation results prove the efficiency of the proposed encryption method. The experimental results show that the proposed security scheme not only protects image data from eavesdroppers but also keeps the good BER and peak-to-average power ratio performances for image-based OFDM-VLC systems.
Correlation Between Internal States and Strength in Bulk Metallic Glass

The internal states or local structures of bulk metallic glass (BMGs) can be well reflected from the changes of density, structural relaxation as well as the elastic constants. With the increasing free volume (FV) content, more local atomic clusters are capable of simultaneous plastic shear at different sites in the metallic glasses, inducing large plasticity. In this work, we report a close correlation between the internal states and strength in a BMG and discover that the yield strength can be changed by varying of the casting current, revealing that the yielding strength of BMGs is not only intrinsically associated with the glass transition, but also with the internal states, such as free volume and elastic properties. Such results may have some implications for understanding the correlations between the internal states and mechanical properties of BMGs.
Searching for the Best Inflation Forecasters within an Employment Survey: Microdata Evidence from Chile

This article aims to evaluate quantitative inflation forecasts for the Chilean economy, taking advantage of a specific survey of consumer perceptions at the individual microdata level, which, at the same time, is linked to a survey of employment in Chile’s capital city. Thus, it is possible to link, with no error, consumer perceptions and 12-month-ahead inflation forecasts with personal characteristics such as gender, age, educational level, county of living, and the economic sector in which they are currently working. By using a sample ranging from 2005.III to 2018.IV, the results suggest that women aged between 35 and 65 years old, with a college degree, living in the North-eastern part of Santiago (the richest of the city), and working in the Community and Social Services sector are the best forecasters. Men aged between 35 and 65 years old, with a college degree, in a tie living in the North-eastern and South-eastern zones but working in Government and Financial Services and Retail sectors, respectively, come in second. Some econometric exercises reinforce and give greater support to the group of most accurate forecasters and reveal that another group of forecasters, different from the second-best in terms of forecast accuracy, displays the characteristics required of a forecasting variable. Remarkably, this group has the same specifications as the most accurate group, with the only difference being that it is composed of men instead of women. Thus, it looks promising for further consideration. Importantly, a forecast accuracy test reveals that no factor comes out as superior to the naïve random walk forecast used as a benchmark. These results are important because they help to identify the most accurate group when forecasting inflation and, thus, help refine the information provided by the survey for inflation forecasting purposes.
Encouraging China’s College Students to Achieve Sustainable Careers: Evidence from Structural Equation Modeling

China’s college graduates are experiencing extreme employment pressure, especially under the effects brought about by COVID-19. This study examines whether career-related psychological factors jointly affect college students’ career decision-making self-efficacy (CDMSE) to achieve sustainable career development. Leveraging self-administrated survey data with 703 undergraduate students, we find that career awareness, job search self-efficacy (JSSE), and career planning ability positively relate to CDMSE. We also find that career awareness positively correlates with JSSE and career planning ability. In addition, the results support that perceived career reality positively relates to JSSE and career planning ability. However, no evidence indicates the positive relationship between perceived career reality and CDMSE. Furthermore, mediation tests confirm that JSSE and career planning ability partially mediate the relationship between career awareness and CDMSE. Practical implications, limitations, and future directions are also discussed.
Public Perception and Attitude towards Transit Advertisement as Outdoor Media Platform: Investigating Age and Gender-based Associations

The study was primarily designed to explore public perception and attitude towards transit advertisements in Pakistan. The population of this study comprised of passengers who travel outside of Multan city. The data was collected through a survey (questionnaire) which was designed after the observation of advertisements by the researchers. A total 400 of passengers, who were waiting for the departure in the passenger’s lounge of intercity bus terminals, filled the questionnaire including both males and females, ages ranging from 18 years to onwards. Perception of passengers was explored in association with the age group regarding various aspects of transit advertisements in terms of liking, reliability, beautification, economic value, society norms, joy, and entertainment source. The results demonstrated that people having different ages perceived transit advertisements differently in all dimensions. The second objective of the study was to explore appealing attitudinal factors and their association with gender regarding attention, understanding, buying, novelty, and recalling of advertisements, results revealed that both males and females had different attitudes towards all aspects. The study also found significant associations between ‘product buying and authenticity’ and ‘perceived novelty and recall of transit advertising.
Application of Career Ecosystems Theory and the New Psychological Contract to the Field of Project Management: Toward a Conceptual Model

The purpose of this article is to explore how different actors can operate within a project management ecosystem to sustain a pool of project management personnel with the knowledge, skills, and abilities of the standards required to support successful project delivery into the future. A new conceptual model is presented offering a set of six propositions whereby professional associations mediate the relationship between project management personnel and employers. The article advances understanding of career ecosystems theory and the new psychological contract via application to a new domain of project management. Practical implications and future research opportunities are also discussed.