Miracle-dz/UniFAR-FTUs huggingface dataset:
Electrochemiluminescence of gold nanoparticles and gold nanoparticle-labelled antibodies as co-reactants

Gold nanoparticles (AuNPs) and AuNP-labelled antibodies can participate in the electrochemiluminescence (ECL) reaction of tris(2,2′-bipyridyl) ruthenium(ii) (Ru(bpy)32+) as a co-reactant. The electrochemical and spectral characteristics of this new ECL system were confirmed by experiments, and its reaction mechanism was speculated to be different from that of typical ECL. The experimental results showed that the new ECL system exhibited higher ECL efficiency, and AuNP-labelled substances can be sensitively measured with the help of AuNPs. Based on the dual role of AuNPs as a co-reactant and marker, the AuNP–Ru(bpy)32+ ECL system will be a useful tool in biochemical analysis.
Velocity-Preserving Trajectory Compression Based on Retrace Point Detection

With the increasing development of GPS-equipped mobile devices such as smart phones and vehicle navigation systems, the trajectories containing valuable spatiotemporal information are recorded. Typically, plenty of trajectory records are generated and stored, making the device memory suffer a heavy storage pressure. Thus, it is a vital issue to compress the trajectories. The trajectory semantics are usually ignored or reduced in traditional trajectory compression techniques. In addition, most of existing trajectory compression algorithms only concern the position errors rather than the velocity errors of trajectories. This paper proposes a velocity-preserving trajectory compression algorithm based on retrace point detection (VPTC-RP) that can compress a set of trajectories by removing unnecessary redundancy points, while the skeleton of these trajectories is maintained as much as possible. In VPTC-RP, the retrace points and the velocity errors are taken to reflect the speeds and directions attached with the points. VPTC-RP first determines the retrace points based on the changed movement directions, and then, the retrace points are extracted from the original trajectories. Especially, the retrace points are put in a buffer, and the subtrajectories in the buffer are compressed according to the measured velocity errors. Simulations are carried out on the Geolife trajectory dataset, and the simulation results indicate that VPTC-RP can achieve a preferable tradeoff among the compression error, compression ratio, and running time.
Multidrug salt forms of norfloxacin with non-steroidal anti-inflammatory drugs: solubility and membrane permeability studies

Multidrug solids have potential to efficiently treat and control a plethora of medical conditions. With the objective of discovering multidrug forms, three new multidrug salts and a salt hydrate of an antibacterial drug, norfloxacin (BCS class IV drug) with four non-steroidal anti-inflammatory drugs (NSAIDs, BCS class II drugs), diclofenac (NOR–DIC), diflunisal (NOR–DIF), mefenamic acid (NOR–MEF) and indomethacin (NOR–IND–H2O), were prepared by liquid-assisted grinding. Single crystal X-ray diffraction (SCXRD) reveals that proton transfer from the carboxylic acid of the NSAIDs to the piperazinyl group of norfloxacin occurs in all the salts to form a robust tetrameric R44 (12) ring piperazine–carboxylate synthon by N+–H⋯O− bonding. Studies on the equilibrium solubility in different biological pH buffer solutions and membrane permeability have been carried out and a comparison is made with those of the parent drugs. A significant enhancement of norfloxacin solubility was observed for the pH 7.4 buffer solution in all the binary systems with the exception of the NOR–MEF salt. Also, a cumulative amount of NOR–DIF and NOR–IND–H2O binary systems show remarkable improvement in diffusion behavior compared to that of the individual pure drugs. Thus, the increasing physicochemical properties through the combined effect of improved solubility and permeability leads to the enhancement of bioavailability, which has implications that overcome the formulation-related problems of APIs.
Potential Drought Mitigation Through Microbial Induced Calcite Precipitation‐MICP

Extreme drought events occur more frequently due to climate change. Soil water loss through evaporation is therefore significantly intensified. This study introduces an environment‐friendly and sustainable bio‐mediated technique, known as microbially induced calcite precipitation (MICP), for water evaporation suppression in clayey soils. Through lab‐scale evaporation tests, we investigate the effects of cementation solution concentration (0.5, 1.0, and 1.5 mol/L) and MICP treatment procedure (one‐phase and two‐phase MICP methods) on both macroscale (e.g., water loss, desiccation cracking) and microscale (e.g., microstructure variations) behaviors of soils. Experimental results show that MICP is capable of improving water retention capacity and enhancing the inter‐particle bonding of clayey soils. Both water evaporation rate and total water loss decrease with the increasing concentration of cementation solution and the number of MICP treatment cycle. For most testing samples, both one‐phase and two‐phase MICP treatment methods have a similar influence on soil properties. Further microstructure characterizations reveal four key factors contributing to the improved soil response under drying, including dense surface crust, remediated desiccation cracks, smaller pore size and residual solutes. Dense structure of surface crust suppresses the migration of water vapor into the atmosphere. Calcite crystals tend to reduce the evaporation surface if precipitated within cracks, and clog the movement of pore water if precipitated within the soil pore space. This study is expected to improve the fundamental understanding of soil‐atmosphere interactions under MICP treatment and provide insights into the potential application of bio‐mediated technologies as a nature‐based solution for drought mitigation in arid and semi‐arid region.
Role of economic development with past and present perspective

Economic development is the goal and objective of every man because it is only way humanity can enjoy the life. In the early age man started the trade for the earning. Economic development is a natural process which attracts the man to stream line all the function of commerce. When the trade was started between the cities the humanity was very ambitious about the development. Man fulfilled their need through trade which is called the barter system after that the enhance of economic system man started the metallic money. When we study the Chinese civilization and sanseis we can found all these evidence from the history of civilization the barter system and metallic money was used. After the enhancement of population of various part of world they started the trade on economic lines. In very early centuries the various tribe move to such areas which suitable for economic activities. For examples many tribe in Europe move to Baltic Sea and the some area which are suitable for trade. We can say this was base of economic system. With expansion of Roman Empire. Roman Empire made the conducts of trade. When Coloma’s discovered the American in 1492. Columbus want to reach the Asia started the new route between Asia and Europe. Some trade delegation visited the area which is called the USA for trade routes. When the colonization of USA was started by Spanish, French, English, Russian they established various way of trade between the continents Atlantic and Indian Ocean.
Has sustainable investing made an impact in the period of COVID-19?: evidence from Australian exchange traded funds

ABSTRACT We study the impact of sustainability on the financial performance of exchange-traded funds (ETFs) in the period of COVID-19. Using a sample of 244 Australian ETFs rated by Morningstar in April 2020, we conducted the portfolio analysis and cross-sectional regression analysis, and the results show that ETF portfolios with lower carbon risk and fossil fuel exposure tend to outperform. However, ETF portfolios with higher social risk tend to deliver a better performance. We also find that ETF portfolios with high environmental risk, governance risk, carbon risk and fossil fuel exposure are more likely to experience high volatility in stock returns. The findings will serve as an important point of reference for investors, businesses and wider stakeholders. The sustainable investing is proving to be resilient during the COVID-19 and a closer look at ESG risks is a lens through which business leaders can build better and more resilient enterprises.
Ageing Orders of Series-Parallel and Parallel-Series Systems with Independent Subsystems Consisting of Dependent Components

In this paper, we consider series-parallel and parallel-series systems with independent subsystems consisting of dependent homogeneous components whose joint lifetimes are modeled by an Archimedean copula. Then, by considering two such systems with di ﬀ erent numbers of components within each subsystem, we establish hazard rate and reversed hazard rate orderings between the two system lifetimes, and also discuss how these systems age relative to each other in terms of hazard rate and reversed hazard rate functions.
Preimplantation Genetic Testing Prevented Intergenerational Transmission of X-Linked Alport Syndrome

Background: Alport syndrome (AS) is a hereditary renal basement membrane disease that can lead to end-stage renal disease in young adults. It can be diagnosed by genetic analysis, being mostly caused by mutations in COL4A3, COL4A4, and COL4A5. To date, there is no radical cure for this disease. Objectives: The aim of this study was to avoid the transmission of AS within an affected family by selecting healthy embryos for uterine transfer. The embryos were identified by preimplantation genetic testing for monogenic disorders (PGT-M). Methods: We used next-generation sequencing (NGS) to identify mutations in the proband and his parents. The results of NGS were confirmed by Sanger sequencing. Targeted NGS combined with targeted single-nucleotide polymorphism haplotyping was used for the in vitro identification of COL4A5 mutations in human embryos to prevent their intergenerational transmission. Results: The c. 349_359delGGACCTCAAGG and c. 360_361insTGC mutations in COL4A5 were identified in a family affected by X-linked AS. Whole-genome sequencing by NGS with targeted haplotyping was performed on biopsied trophectoderm cells. A healthy baby was born after transfer of a single freeze-thawed blastocyst. Conclusions: The use of targeted NGS for identifying diagnostic markers combined with targeted haplotyping is an easy and efficient PGT-M method for preventing intergenerational transmission of AS.
A Perspective on the Sustainability of Cathode Materials used in Lithium‐Ion Batteries

Electric vehicles powered by lithium‐ion batteries are viewed as a vital green technology required to meet CO2 emission targets as part of a global effort to tackle climate change. Positive electrode (cathode) materials within such batteries are rich in critical metals—particularly lithium, cobalt, and nickel. The large‐scale mining of such metals, to meet increasing battery demands, poses concerns surrounding material exhaustion in addition to further environmental, social, and governance (ESG) issues. In particular, unethical mining practices and political instability within the Democratic Republic of the Congo (the world's largest cobalt producer) have prompted research into cobalt‐low and cobalt‐free alternatives. This review aims to provide a holistic view of lithium‐ion cathode development and inform advancements by highlighting the interdependencies across mining, material development, and end‐of‐life management. While material sustainability is reported through supply and demand projections, the potential socioenvironmental impacts of lithium‐ion battery technology represent a hugely underresearched area among the aforementioned themes. Notably, the lack of attention paid toward future implications of increased nickel use across material management and development disciplines is also discussed.
Distributed Dynamic Route Guidance and Signal Control for Mobile Edge Computing-Enhanced Connected Vehicle Environment

The benefit of real-time joint dynamic route guidance and signal control (DRG-SC) is usually compromised by a centralized framework since it naturally leads to an un-timely solution with the growing data-processing needs and problem-solving complexity. Mobile edge computing (MEC) pushes the data storage and computation from the remote cloud to local infrastructures and hence reduces response time and improves network bandwidth when further combined with 5G. As such, our study first develops a novel distributed framework to facilitate DRG-SC in connected vehicle (CV) environment with clarifying the MEC’s vital role. The method captures the interaction of vehicles’ routing and signal control, wherein we use a more realistic and accurate way to define the relationship between travel time and traffic volume. Vehicles make route decisions and cooperate to reach user optimal (UO) or system optimal (SO) traffic state. In tandem, the developed adaptive signal control (ASC) adjusts the signal timing plan with considering both the adjacent intersections’ traffic volume and the vehicles’ waiting time. Our method achieves significant reductions in vehicles’ average departure delay, waiting time and travel time when justified by a comprehensive case study implemented in SUMO. Moreover, the effectiveness of adopting such a distributed framework in saving computation time is verified. Overall, our study provides valuable and practical insights into the intelligent operation and control.
A 56-Gb/s 50-mW NRZ Receiver in 28-nm CMOS

A wireline receiver consisting of a linear equalizer, a decision-feedback equalizer (DFE), a clock and data recovery (CDR) circuit, and a demultiplexer (DMUX) employs new circuit and architecture techniques that afford substantial power savings. Realized in 28-nm technology, the 56-Gb/s receiver has a bit error rate (BER) of less than 10<inline-formula> <tex-math notation="LaTeX">$^{-12}$ </tex-math></inline-formula> for a channel loss of 25 dB at 28 GHz.
Association between Consumer Practices
and Phthalate Exposure in Children and their
Parents from Slovakia

Phthalates represent endocrine disrupting chemicals, with harmful effect on the hormonal balance of the human body. Food is a substantial source of exposure to phthalates. The aim of study was to investigate association between phthalate exposure of children and their parents from Slovakia (children n = 51, parents n = 27) and their consumer practices. We analysed urine samples by high performance liquid chromatography and tandem mass spectrometry (HPLC-MS/MS) to determine concentrations of phthalate metabolites monoethyl phthalate (MEP), monomethyl phthalate (MMP), mono-n-buthyl phthalate (MnBP), mono-iso-buthyl phthalate (MiBP), monocyclo-hexyl phthalate (MCHP), mono(2ethylhexyl) phthalate (MEHP), mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono(2-ethyl5-oxohexyl) phthalate (MEOHP), mono(2-ethyl-5-carboxypentyl) phthalate (MECPP) and mono(2carboxymethylhexyl) phthalate (McMHP), mono-n-octyl phthalate (MnOP) and mono-isononyl phthalate (MiNP). We observed significantly higher concentrations of di (2-ethylhexyl) phthalate (DEHP) metabolites and MiBP in children in comparison with parents (p≤0.05). We found statistically significant association between concentrations of some phthalates and consumption of food packed in the plastic containers, drinking of milk and strongest association was detected between consumption of sliced salami in a plastic package and concentrations of all DEHP metabolites (p≤0.05). We concluded that consumption of the fat rich food stored in the plastic containers together with socioeconomic status and age could affect urinary concentration of phthalate metabolites.
Bifactor analyses provide uncorrelated measures of activism intentions and radicalism intentions

ABSTRACT Activism is legal and non-violent political action, whereas Radicalism is illegal and sometimes violent action. Moskalenko and McCauley introduced the Activism Intentions Scale (AIS) and the Radicalism Intentions Scale (RIS) as related but distinguishable dimensions: the scales were significantly correlated but showed different correlates. The same pattern has been seen consistently in subsequent research using the scales. In this paper, two studies (280 Catalan university students, 163 Croatian adults) use bifactor analysis to measure Activism Intentions uncorrelated with Radicalism Intentions, and Radicalism Intentions uncorrelated with Activism Intentions. Scores on the purified scales show more differentiated patterns of correlates than scores on the usual item-average scales, that is, bifactor scores show improved discriminant validity. These results support the idea that activism and radicalism are different theoretical constructs. The distinction is important because it implies that fighting radicalization does not require fighting activism.
Discrete Human Activity Recognition and Fall Detection by Combining FMCW RADAR Data of Heterogeneous Environments for Independent Assistive Living

Human activity monitoring is essential for a variety of applications in many fields, particularly healthcare. The goal of this research work is to develop a system that can effectively detect fall/collapse and classify other discrete daily living activities such as sitting, standing, walking, drinking, and bending. For this paper, a publicly accessible dataset is employed, which is captured at various geographical locations using a 5.8 GHz Frequency-Modulated Continuous-Wave (FMCW) RADAR. A total of ninety-nine participants, including young and elderly individuals, took part in the experimental campaign. During data acquisition, each aforementioned activity was recorded for 5–10 s. Through the obtained data, we generated the micro-doppler signatures using short-time Fourier transform by exploiting MATLAB tools. Subsequently, the micro-doppler signatures are validated, trained, and tested using a state-of-the-art deep learning algorithm called Residual Neural Network or ResNet. The ResNet classifier is developed in Python, which is utilised to classify six distinct human activities in this study. Furthermore, the metrics used to analyse the trained model’s performance are precision, recall, F1-score, classification accuracy, and confusion matrix. To test the resilience of the proposed method, two separate experiments are carried out. The trained ResNet models are put to the test by subject-independent scenarios and unseen data of the above-mentioned human activities at diverse geographical spaces. The experimental results showed that ResNet detected the falling and rest of the daily living human activities with decent accuracy.
Fake News Data Exploration and Analytics

Before the internet, people acquired their news from the radio, television, and newspapers. With the internet, the news moved online, and suddenly, anyone could post information on websites such as Facebook and Twitter. The spread of fake news has also increased with social media. It has become one of the most significant issues of this century. People use the method of fake news to pollute the reputation of a well-reputed organization for their benefit. The most important reason for such a project is to frame a device to examine the language designs that describe fake and right news through machine learning. This paper proposes models of machine learning that can successfully detect fake news. These models identify which news is real or fake and specify the accuracy of said news, even in a complex environment. After data-preprocessing and exploration, we applied three machine learning models; random forest classifier, logistic regression, and term frequency-inverse document frequency (TF-IDF) vectorizer. The accuracy of the TFIDF vectorizer, logistic regression, random forest classifier, and decision tree classifier models was approximately 99.52%, 98.63%, 99.63%, and 99.68%, respectively. Machine learning models can be considered a great choice to find reality-based results and applied to other unstructured data for various sentiment analysis applications.
Impairment (in)visibility and stigma: how disabled entrepreneurs gain legitimacy in mainstream and disability markets

ABSTRACT Entrepreneurs’ use of linguistic practices, such as storytelling, in building legitimacy with customers and others is well documented. Yet, not all entrepreneurs may equally use or benefit from such practices in their legitimacy-building efforts. For those with stigmatized social identities, like disability, embodied properties and practices of non-linguistic, more visual kind, may be salient despite being under-explored in the entrepreneurial legitimacy studies. To address this knowledge gap, this article examines how disabled entrepreneurs gain legitimacy with customers and, more specifically, how impairment visibility shapes their capacity to do so. Drawing primarily on in-depth interviews with UK-based entrepreneurs, the article extends Suchman’s work by reconceptualizing his legitimacy-building strategies considering impairment visibility. It is argued that impairment visibility can both enable and constrain legitimacy depending on the product offering and the target market. Disabled entrepreneurs are found to adopt four embodied legitimacy-building strategies in the marketplace, each with specific implications for their micro-level interactions with customers.
Chinese investment in the Northeast region of Brazil: an analysis about the renewable energy sector

PurposeThis paper seeks to analyze the relationship between China and the Northeast region of Brazil, aiming to identify how the renewable energy sector is being developed.Design/methodology/approachThe authors analyzed secondary data from the official databases from China-Brazil chambers of commerce to establish the main points related to renewable energy in Brazil's Northeast.FindingsIt is possible to notice the main investments, highlighting the wind energy as a more prominent source recently. The authors also point the huge influence from China on Brazil's Northeast energy sector.Research limitations/implicationsIt is difficult to identify the amount of Chinese capital due to the large number of mergers and acquisitions that has been taking place in recent years.Practical implicationsIdentification of regions that have been receiving investments and the main interests of Chinese investors in the renewable energy sector.Social implicationsDemonstration of how the renewable energy sector has taken an important turn in Brazil due to Chinese investment.Originality/valueTo evaluate a regional consortium, analyzing its strategies for partnerships with China to help each other in global questions, as is the case of renewable energy.
Conteúdos de ciências sociais em saúde coletiva

Apresentamos um relato de experiência da oferta remota (educação online) da disciplina de Ciências Sociais em Saúde Coletiva, no Mestrado Profissional em Saúde Coletiva, em tempos de pandemia. Compartilhamos desde o planejamento à avaliação final da disciplina feita pelos discentes, apontando as limitações e os benefícios que experimentamos no uso dessa modalidade de educação. Ressaltamos uma característica singular do grupo, que era formado, em sua maioria, por trabalhadores da área da saúde, muitos deles atuantes na linha de frente ao combate do COVID-19. Portanto, para além das preocupações metodológicas, tivemos em consideração, durante todo o processo, as subjetividades envolvidas na relação de construção do conhecimento.