Miracle-dz/UniFAR-FTUs huggingface dataset:
Phase dependent encapsulation and release profile of ZIF-based biocomposites

Biocomposites composed of Zeolitic Imidazolate Frameworks (ZIFs) are generating significant interest due to their facile synthesis, and capacity to protect proteins from harsh environments. Here we systematically varied the composition (i.e. relative amounts of ligand (2-methylimidazole), metal precursor (Zn(OAc)2·2H2O), and protein) and post synthetic treatments (i.e. washes with water or water/ethanol) to prepare a series of protein@ZIF biocomposites. These data were used to construct two ternary phase diagrams that showed the synthesis conditions employed gave rise to five different phases including, for the first time, biocomposites based on ZIF-CO3-1. We examined the influence of the different phases on two properties relevant to drug delivery applications: encapsulation efficiency and release profile. The encapsulation efficiencies of bovine serum albumin and insulin were phase dependent and ranged from 75% to 100%. In addition, release profiles showed that 100% protein release varied between 40 and 300 minutes depending on the phase. This study provides a detailed compositional map for the targeted preparation of ZIF-based biocomposites of specific phases and a tool for the straightforward analysis of the crystalline phases of ZIF based materials (web application named “ZIF phase analysis”). These data will facilitate the progress of ZIF bio-composites in the fields of biomedicine and biotechnology.
Complete mitochondrial genome of freshwater fish, Microphysogobio jeoni (Actinopterygii, Cypriniformes, Cyprinidae), from South Korea

Abstract In this study, we determined the complete mitochondrial genome sequences of cyprinid freshwater fish, Microphysogobio jeoni, belonging to the subfamily Gobioninae in the order Cypriniformes. The complete mitogenome of M. jeoni was 16,602 bp in length and consisted of 13 protein-coding genes (PCGs), 22 tRNAs, and two rRNAs. The gene order was identical with other Microphysogobio species. The overall nucleotide composition of M. jeoni was A + T: 56.1% and G + C: 43.9%, with slightly AT bias. In the phylogenetic tree, M. jeoni and other congeneric species clearly formed a monophyletic clade, and each species distinguished against each other well.
It’s Complicated: Plot and Formal Feature Complexity in Early Childhood Television Content

ABSTRACT The recent surge in television content targeting young children has led to questions about the appropriateness of the content for children’s developmental capabilities. The study comprehensively analyzed the manifestations of complexity – both in the plot and in formal features – in content aired on child-targeted television channels (from about 2 to 6 years of age). A qualitative analysis of content from 216 television shows from the six Israeli children’s television channels identified much complexity in children’s programming. Plot complexity involved intertwining sub-plots and characters, a weak problem-solution link in the narrative, and unclear messages. Formal feature complexity involved fast-pace, quick camera cuts, and an overload of visual elements. The study uniquely identified the shifts between “real” and “fantasy” worlds in children’s television shows as comn contexts of complexity that integrate both plot and formal feature indicators. Manifestations of complex messages in children’s television shows are discussed in light of toddlers’ and young children’s cognitive development. The findings are also discussed in light of the traveling lens model associated with children’s learning from television content.
Task-Scheduling Based on Multi-Objective Particle Swarm Optimization in
Spatial Crowdsourcing

As a result of the rapid growth of internet and smartphone technology, a novel platform that attracts individuals and groups known as crowdsourcing emerged. Crowdsourcing is an outsourcing platform that facilitates the accomplishment of costly tasks that consume long periods of time when traditional methods are used. Spatial crowdsourcing (SC) is based on location; it introduces a new framework for the physical world that enables a crowd to complete spatialtemporal tasks. The primary issue in SC is the assignment and scheduling of a set of available tasks to a set of proper workers based on different factors, such as the location of the task, the distance between task location and hired worker location, temporal conditions, and incentive rewards. In the real-world, SC applications need to optimize multi-objectives simultaneously to exploit the utility of SC, and these objectives can be in conflict. However, there are few studies that address this multi-objective optimization problem within a SC environment. Thus, the authors propose a multi-objective task scheduling optimization problem in SC that aims to maximize the number of completed tasks, minimize total travel cost, and ensure worker workload balance. To solve this problem, we developed a method that adapts the multi-objective particle swarm optimization (MOPSO) algorithm based on a proposed novel fitness function. The experiments were conducted with both synthetic and real datasets; the experimental results show that this approach provides acceptable initial results. As future work, we plan to improve the effectiveness of our proposed algorithm by integrating a simple ranking strategy based on task entropy and expected travel costs to enhance MOPSO performance.
Navigating Input and Output Legitimacy in Multi-Stakeholder Initiatives: Institutional Stewards at Work

Multi-stakeholder initiatives (MSIs) are a form of private governance sometimes used to manage the social and environmental impacts of supply chains. We argue that there is a potential tension between input and output legitimacy in MSIs. Input legitimacy requires facilitating representation from a wide range of organizations with heterogeneous interests. This work, however, faces collective action problems that could lead to limited ambitions, lowering output legitimacy. We find that, under the right conditions a relatively small group of motivated actors, who we call institutional stewards, may be willing to undertake the cost and labor of building and maintaining the MSI. This can help reconcile the tension between input and output legitimacy in a formal sense, though it also results in inequalities in power. We test this claim using a case study of organizations’ activities in the Roundtable on Sustainable Palm Oil (RSPO). We find that a small group of founding members—and other members of long tenure—account for a disproportionate level of activity in the organization.
Transactional Streaming: Managing Push-Based Workloads with Shared Mutable State in a Distributed Setting

of “Transactional Streaming: Managing Push-Based Workloads with Shared Mutable State in a Distributed Setting” by John Meehan, Ph.D., Brown University, May 2019. In the past, streaming data management systems (SDMSs) have eschewed transactional management of shared mutable state in favor of low-latency processing of high-velocity data. Streaming workloads involving ACID state management have required custom solutions involving a combination of database systems, complicating scalability by adding blocking communication, which severely impedes performance. This dissertation presents a solution: a transactional streaming system, S-Store. Built on a main-memory OLTP system, S-Store implements a novel transaction model and gives best-in-class performance on hybrid streaming and OLTP workloads while maintaining the correctness guarantees of both worlds. To achieve optimal performance, S-Store distributes processing across a cluster of machines. This requires an implementation which solves the unique challenges to system design and partitioning that arise from dataflow state management. This dissertation describes heuristics for optimizing two overarching workload categories: those that use data parallelism and those that use pipeline parallelism. Transactional streaming has opened opportunities for new solutions to real-world problems, particularly in streaming data ingestion. Together, these contributions provide a foundation for a new class of streaming research in which ACID state management is an essential feature rather than an afterthought. Transactional Streaming: Managing Push-Based Workloads with Shared Mutable State in a Distributed Setting by John Meehan Department of Computer Science Brown University A dissertation submitted in partial fulfillment of the requirements for the Degree of Doctor of Philosophy in the Department of Computer Science at Brown University Providence, Rhode Island May 2019
First validation of Aeolus wind observations by airborne Doppler wind lidar measurements

Abstract. Soon after the launch of Aeolus on 22 August 2018, the first ever wind lidar in space developed by the European Space Agency (ESA) has been providing profiles of the component of the wind vector along the instrument's line of sight (LOS) on a global scale. In order to validate the quality of Aeolus wind observations, the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt e.V., DLR) recently performed two airborne campaigns over central Europe deploying two different Doppler wind lidars (DWLs) on board the DLR Falcon aircraft. The first campaign – WindVal III – was conducted from 5 November 2018 until 5 December 2018 and thus still within the commissioning phase of the Aeolus mission. The second campaign – AVATARE (Aeolus Validation Through Airborne Lidars in Europe) – was performed from 6 May 2019 until 6 June 2019. Both campaigns were flown out of the DLR site in Oberpfaffenhofen, Germany, during the evening hours for probing the ascending orbits. All together, 10 satellite underflights with 19 flight legs covering more than 7500 km of Aeolus swaths were performed and used to validate the early-stage wind data product of Aeolus by means of collocated airborne wind lidar observations for the first time. For both campaign data sets, the statistical comparison of Aeolus horizontal line-of-sight (HLOS) observations and the corresponding wind observations of the reference lidar (2 µm DWL) on board the Falcon aircraft shows enhanced systematic and random errors compared with the bias and precision requirements defined for Aeolus. In particular, the systematic errors are determined to be 2.1 m s−1 (Rayleigh) and 2.3 m s−1 (Mie) for WindVal III and −4.6 m s−1 (Rayleigh) and −0.2 m s−1 (Mie) for AVATARE. The corresponding random errors are determined to be 3.9 m s−1 (Rayleigh) and 2.0 m s−1 (Mie) for WindVal III and 4.3 m s−1 (Rayleigh) and 2.0 m s−1 (Mie) for AVATARE. The Aeolus observations used here were acquired in an altitude range up to 10 km and have mainly a vertical resolution of 1 km (Rayleigh) and 0.5 to 1.0 km (Mie) and a horizontal resolution of 90 km (Rayleigh) and down to 10 km (Mie). Potential reasons for those errors are analyzed and discussed.
Virus-bacteria diagnostic test (vbd-test) in identifying biology teacher’s misconception

Article history Received: 20 September 2019 Revised: 9 November 2019 Accepted: 11 November 2019 Virus-Bacteria Diagnostic Test (VBD-Test) is three-tier diagnostic instrument for identification virus and bacteria topics. The purpose of this study was to determine the empirical validity of the VBDTest and identify misconceptions of virus and bacteria topics in biology teachers in Malang using VBD-Test. The development research model used was the Treagust development model, namely (1) Defining content, (2) Obtaining information, and (3) Developing a diagnostic test. The empirical validity on the VBDTest was carried out with the Pearson correlation test using Excel, while the reliability on the VBD-Test was carried out with a spearman brown split-half method using Anatest 4.0. 2. There were six valid questions and eight invalid questions on the virus topic, while in bacteria topic, there were nine valid questions and six invalid questions. The identification results on teacher's concept of the virus topic were 33.33% understood the idea, 13.66% false positive, 35.53% false negative, 17.01% did not understand the concept, and 4.39% guessed. While the results of the identification of the teacher's concept of bacteria topic were 30.13% understood the concept, 9.07% false positive, 227.63% false negative, 23.05% did not understand the concept, and 10.09% guessed. Based on these results, if identification misconception is not made to the teacher, then the misconception will not be known by the teacher on any material, and the learning material submitted by the teacher will remain a misconception so that students will also suffer the same.
Activation of the Sonic Hedgehog Effector Smoothened Counteracts L-Dopa Induced Dyskinesia by Restoring Cholinergic Interneuron Function

iv Acknowledgements . vi List of Figures . xiii 1. Chapter 1: Introduction . 1 1.1 Basal ganglia circuitry . 1 1.2 Striatal cholinergic interneurons . 8 1.3 Parkinson’s Disease and L-Dopa induced dyskinesia . 10 1.4 CIN involvement in LID . 13 1.5 Sonic Hedgehog signaling . 16 1.6 Intent of Thesis . 20 Part I: Reduced Sonic Hedgehog by DA neuron degeneration contributes to LID formation that can be alleviated by replacing both DA and Sonic Hedgehog signaling factors . 22 2. Chapter 2: Smo agonists attenuate LID in neurotoxic and genetic models of PD . 23 2.1 Chronic Smo inhibition augments, while Smo activation attenuates LIDs . 23 2.2 Acute activation of Smo decreases AIMs . 31 2.3 pErk1/2 activation in CINs is attenuated by Smo activation . 33 2.4 SAG Administration reduced dyskinetic behavior in the MPTP Macaque model of PD . 35 2.5 The attenuation of LID by Smo stimulation scales with the concentration of L-Dopa . 36 2.6 Smo activation potentially acts upstream of M4R activation on dSPN . 38
Extremes of log-correlated random fields and the Riemann zeta function, and some asymptotic results for various estimators in statistics

In this paper, we study a random field constructed from the two-dimensional Gaussian free field (GFF) by modifying the variance along the scales in the neighborhood of each point. The construction can be seen as a local martingale transform and is akin to the time-inhomogeneous branching random walk. In the case where the variance takes finitely many values, we compute the first order of the maximum and the log-number of high points. These quantities were obtained by Bolthausen et al. (2001) and Daviaud (2006) when the variance is constant on all scales. The proof relies on a truncated second moment method proposed by Kistler (2015), which streamlines the proof of the previous results. We also discuss possible extensions of the construction to the continuous GFF.
Integrated Reactive Power Optimization Method for Active Distribution Networks Based on a Quantum Krill Herd Algorithm

Abstract Aiming at the problem that the reactive power optimization of traditional distribution network can’t adapt to the active distribution network (ADN) of large-scale distributed power access, a comprehensive reactive power optimization method based on quantum krill herd algorithm for ADN is proposed. Firstly, a reactive power optimization model of ADN based on proportional coefficient is proposed by analyzing the characteristics of active control and active management. Secondly, the krill herd algorithm is easy to fall into local optimum when solving optimization problems. To overcome this shortcoming, a quantum krill swarm algorithm is proposed. The algorithm uses the probability amplitude of quantum bits to represent the information of particle position, uses quantum revolving gate to increase population diversity and generates new population through chaotic crossover, which improves the convergence accuracy of the algorithm. Finally, simulation experiments are carried out on the modified IEEE33 node and IEEE 69 node to verify the effectiveness of the proposed model and algorithm.
Novel Pulse Oximetry Sonifications for Eyes Free Monitoring

Pulse oximeters monitor a patient’s heart rate and oxygen saturation (SpO2) via visual and auditory displays. Heart rate is represented by the beep rate and SpO2 by beep pitch. However, the auditory display alone does not always accurately inform clinicians of the patient’s actual SpO2 level. Moreover, neonates have special oxygen needs that mean current pulse oximetry sounds are inadequate. In three studies we tested potentially improved pulse oximetry sounds for monitoring critically ill neonates. The control condition was a logarithmic mapping of percentage oxygen saturation to beep frequency in Hz. A sonification that added an intermittent reference tone, or “beacon” when SpO2 was out of the target range proved highly effective. We discuss the theoretical and practical implications of the findings.
Planning and Managing of Diagnostic Imaging Technologies in Healthcare: The Introduction of Managed Equipment Service (MES) for the System’s Sustainability

The lack of resources has driven healthcare management studies to recognise Private and Public Partnerships (PPP) as the solution in managing efficiency, effectiveness and profitability of technological innovation. Recent researchers have identified the buying model called Managed Equipment Service (MES), in which purchaser and seller share the risks of technology’s management and use, as an optimal problem-solving method. The aim of this research is to analyse the potential economic-financial and organizational benefits of MES introduction in healthcare, in particular for the acquisition of the diagnostic imaging technologies. The research applies the case study method. We have examined a representative Italian Local Health Authority for its dimensions, managerial characteristics and case-mix offered but, especially, for its high health standards. In the study we have involved the strategic figure of radiographer in diagnostic imaging. The data has been elaborated through statistical analysis to observe the correlations. Evidence demonstrates that MES costs are lower than all the other planning and purchasing methods analysed (between 11% - 239%). When correlations between age of facilities and effectiveness of provided services is strong, MES grants the maintenance of a lower average age of technologies and a more efficient use of resources and significant margins of profitability. The emerging model of PPP is a possible solution to the current issues surrounding economic and financial sustainability of healthcare systems, considered the fewer resources and the technological progress. MES in healthcare appears to be a highly efficient way of managing innovation, in particular for diagnostic imaging technologies. Keywords: Public Private Partnership (PPP), Managed Equipment Service (MES), middle-high technologies, diagnostic imaging.
Classification model for predictive maintenance of small steam sterilisers

With 35,000 small steam sterilisers in the German market, after-sales service and maintenance are critical issues for manufacturers and distributors. At present, preventive maintenance is one of the most commonly-implemented maintenance strategies. However, with an average failure probability of 10%, ∼3500 autoclaves require unplanned repair per year, causing customers’ business interruptions and increased maintenance costs. From the authors’ observation, a predictive failure detection mechanism is needed to prevent failures and reduce the significant safety risk. Hence, this study proposes a predictive maintenance mechanism for small steam sterilisers. The predictive maintenance mechanism is constructed from classification models that categorised the health condition of two critical components in small steam sterilisers, i.e. a vacuum pump and a steam generator. The classification models were built from multisensory data, obtained from 1000 protocol records of CertoClav Vacuum Pro steam sterilisers. They perform exploratory experiments to find a suitable classification model. This study found that the random forest algorithm performed best in terms of accuracy for both the vacuum pump and steam generator data sets (83.5 and 82.0%, respectively). They also found that the features related to the pre-vacuum stage profoundly influence the condition of the vacuum pump and the steam generator.
Synthesis and biological activities of local anesthetics

Local anesthetics are mainly used in stomatology, ophthalmology, gynecology and surgery to temporarily relieve pain. Local anesthetics act on nerve endings or around nerve trunks, and are combined with specific sodium ion (Na+) channel sites on the nerve membrane. They can affect the membrane potential by reducing Na+ passage through sodium ion channels, thus blocking the generation and conduction of nerve impulses, reversibly blocking the generation and conduction of sensory nerve impulses. Local anesthetics are used for convenience in local surgical operations and treatments. Herein, we mainly review the research progress on local anesthetics and discuss the important aspects of design, synthesis and biological activity of various new compounds.
Essentials of Bioinformatics, Volume I Understanding Bioinformatics: Genes to Proteins

Introduction to biological data -- Computers and bioinformatics -- Sequence biological databases -- Biological databases -- Other biological databases -- Nucleic acid sequencing -- Tools and methods in analysis of simple sequences -- Tools and methods in analysis of complex sequences -- Structural bioinformatics -- Protein structure annotations -- Introduction to functional bioinformatics -- Biological networks – tools, methods and analysis -- Metabolomics -- Drug discovery: concepts and approaches -- Drug designing methods and analysis -- Molecular molecular docking -- Insilico pcr -- Modeling and optimization of molecular bio-systems to generate predictive models -- Index.
Responses to the gender minority stress and resilience scales among transgender and nonbinary youth

Abstract Stress arising from the experience of stigma and discrimination around gender identity is known to negatively influence health outcomes for transgender individuals. The Gender Minority Stress and Resilience (GMSR) scale is a validated tool for measuring experiences of minority stress and resilience among transgender individuals. This paper seeks to examine whether there are differences in how youth respond to the GMSR scale. Using data from a sample of 202 transgender and gender nonbinary youth collected online, this analysis compares responses to the GMSR scale between transgender youth with binary and nonbinary gender identities. While reports of non-affirmation were generally high (M = 15.02), and community connectedness for all participants was generally low (M = 7.5), there were no significant differences to scale responses across gender identity. Nonbinary assigned male at birth (AMAB) reported greater rates of threats of physical violence due to gender identity or expression. Nonbinary assigned female at birth (AFAB) reported greater rates of feeling unique in their gender identity or expression. This preliminary analysis suggests that the GMSR scale is a useful tool, however, further research is needed to understand stress and resilience among transgender and gender nonbinary youth and developing specific measures that capture their experience.