Preparatory Steps Research Articles

Quantification and reliability of [11C]VC - 002 binding to muscarinic acetylcholine receptors in the human lung \u2014 a test-retest PET study in control subjects

BackgroundThe radioligand [11C]VC-002 was introduced in a small initial study long ago for imaging of muscarinic acetylcholine receptors (mAChRs) in human lungs using positron emission tomography (PET). The objectives of the present study in control subjects were to advance the methodology for quantification of [11C]VC-002 binding in lung and to examine the reliability using a test-retest paradigm. This work constituted a self-standing preparatory step in a larger clinical trial aiming at estimating mAChR occupancy in the human lungs following inhalation of mAChR antagonists.MethodsPET measurements using [11C]VC-002 and the GE Discovery 710 PET/CT system were performed in seven control subjects at two separate occasions, 2–19 days apart. One subject discontinued the study after the first measurement.Radioligand binding to mAChRs in lung was quantified using an image-derived arterial input function. The total distribution volume (VT) values were obtained on a regional and voxel-by-voxel basis. Kinetic one-tissue and two-tissue compartment models (1TCM, 2TCM), analysis based on linearization of the compartment models (multilinear Logan) and image analysis by data-driven estimation of parametric images based on compartmental theory (DEPICT) were applied.The test-retest repeatability of VT estimates was evaluated by absolute variability (VAR) and intraclass correlation coefficients (ICCs).ResultsThe 1TCM was the statistically preferred model for description of [11C]VC-002 binding in the lungs. Low VAR (< 10%) across analysis methods indicated good reliability of the PET measurements. The VT estimates were stable after 60 min.ConclusionsThe kinetic behaviour and good repeatability of [11C]VC-002 as well as the novel lung image analysis methodology support its application in applied studies on drug-induced mAChR receptor occupancy and the pathophysiology of pulmonary disorders.Trial registrationClinicalTrials.gov identifier: NCT03097380, registered: 31 March 2017.

The UA9 setup for the double-crystal experiment in CERN-SPS

Experiments to measure the electric and the magnetic moments of short-lived baryons using an internal target and two bent crystals in the vicinity of one of the existing LHC detectors were recently proposed, in the frame of the Physics Beyond Colliders Working Group at CERN. Investigating fixed-target physics in the LHC with in-vacuum solid targets is an unprecedented challenge. As a preparatory step, the layout of the UA9 experiment, installed in the CERN SPS to explore beam manipulations assisted by bent crystals, has been modified to study the feasibility of the double-crystal scenario in a circular accelerator. Ideally, the first crystal should capture halo protons in channeling states directing them onto the internal target to produce rare baryons, whilst the second crystal, located just downstream of the target, should channel the baryons, rotate their polarization vector and deflect them towards the detector area. The upgraded UA9 layout is presented. Preliminary measurements providing an insight of the beam behavior are reported.

Whole-slide Imaging: Clinical Workflows and Primary Diagnosis.

Digital pathology has made great strides in recent years culminating with the approval to market devices from the Food and Drug Administration. The pathology community is now poised to begin using these systems for diagnostic purposes. This article will discuss the preparatory steps needed to implement digital pathology as well as some implementation styles that may be sufficient for a pathology department.

PELAKSANAAN KEGIATAN EKSTRAKURIKULER DRUM BAND DI SMP NEGERI 11 PADANG

AbstractThis type of research in this study was a qualitative with using a descriptive analysis approach that aims to describe the process of implementation of Drum-band extracurricular activity in SMP Negeri 11 Padang. The object of research was Drum band of SMP Negeri 11 Padang. The main instruments of this research were the researcher as an observer, the participants (actor) in an insider position also played a direct role in the object under study. Meanwhile, the supporting instruments used in this study were done by taking documentation from recording device in the form of observation, interview lists and photo camera. The results of the study illustrate that in the implementation of Drum-band extracurricular activity in SMP Negeri 11 Padang, the preparatory step of activitiy begins with the selecting Drum-band members, determining training material, determining training schedules, training and performances. In getting the most out of it, the builder makes two forms of training, which are regular weekly exercises conducted on Saturdays in Personal Development lesson and additional exercises that are done two weeks before Drum-band takes part in competitions or holiday. The first training begins with group musical instrument exercises, then followed by joint training of all musical instruments.Keywords: Arts, Music, Drum Band, Students

The Leaders’ Dilemma

The threat of a pandemic places P-20 educational leaders in the difficult position of having to make decisions with incomplete information that affect the welfare of students, employees, and the community. Due to extraneous factors, pandemics are almost impossible to plan for in detail. In an effort to illustrate the unique position P-20 educational leaders find themselves in during the threat of a pandemic, a leaders’ dilemma matrix is presented to illustrate possible outcomes based on leaders’ responses. While educational leaders may feel a need to take unilateral actions, national- and state-level systems exist to guide appropriate responses. Ultimately, some preparatory steps are enumerated.

Automated extraction of left atrial volumes from two-dimensional computer tomography images using a deep learning technique

BackgroundPrecise segmentation of the left atrium (LA) in computed tomography (CT) images constitutes a crucial preparatory step for catheter ablation in atrial fibrillation (AF). We aim to apply deep convolutional neural networks (DCNNs) to automate the LA detection/segmentation procedure and create three-dimensional (3D) geometries. MethodsFive hundred eighteen patients who underwent procedures for circumferential isolation of four pulmonary veins were enrolled. Cardiac CT images (from 97 patients) were used to construct the LA detection and segmentation models. These images were reviewed by the cardiologists such that images containing the LA were identified/segmented as the ground truth for model training. Two DCNNs which incorporated transfer learning with the architectures of ResNet50/U-Net were trained for image-based LA classification/segmentation. The LA geometry created by the deep learning model was correlated to the outcomes of AF ablation. ResultsThe LA detection model achieved an overall 99.0% prediction accuracy, as well as a sensitivity of 99.3% and a specificity of 98.7%. Moreover, the LA segmentation model achieved an intersection over union of 91.42%. The estimated mean LA volume of all the 518 patients studied herein with the deep learning model was 123.3 ± 40.4 ml. The greatest area under the curve with a LA volume of 139 ml yielded a positive predictive value of 85.5% without detectable AF episodes over a period of one year following ablation. ConclusionsThe deep learning provides an efficient and accurate way for automatic contouring and LA volume calculation based on the construction of the 3D LA geometry.

Transition to the circular economy: the story of four case companies

Shifting from a linear sales model to a circular service-based business model is far from straightforward. Many challenges accrue in the transition process, including finding the right market for the recirculated product/service, setting up the reverse supply chain, selecting the right partners, and making sure the new business model is sustainable in the short, medium and long term. This paper discusses the challenges of four companies trying to close the loop while preserving current profit levels. It describes their initial ideas on how the circular business model should be designed, the process they went through, challenges faced, and the eventual outcome. Based on the learnings of the four case companies, we summarise recommendations about preparatory steps required before making the transition towards a circular business model.

Are Large Particles of Iron Detrimental to Properties of Powder Metallurgy Steels?

It is experimentally shown that a removal of particles exceeding 100 microns in size from iron powders typically used in the fabrication of medium density powder metallurgy steels has a weak effect on apparent density, flowability and compressibility of blends as well as on density and strength of green bodies. An elimination of such particles, i.e., cutting off a heavy tail of a size distribution histogram at the 100 μm threshold, improves a compositional uniformity of sintered materials, but has no noticeable beneficial effect upon the strength of a final product, which is likely be determined by a fraction of pores and their shapes. A presence of soft pearlitic inclusions hardly matters unless their number density becomes so large that a 3D continuity (integrity) of a hard martensitic matrix is lost. This finding suggests that such an expensive preparatory step as sieving away large particles from as-received mixtures would bear no technological advantages. It was experimentally found that an attempt to lower the threshold below 100 μm noticeably worsened apparent density, flowability and compressibility.

A Rapid Lysostaphin Production Approach and a Convenient Novel Lysostaphin Loaded Nano-emulgel; As a Sustainable Low-Cost Methicillin-Resistant Staphylococcus aureus Combating Platform.

Staphylococcus aureus is a Gram-positive pathogen that is capable of infecting almost every organ in the human body. Alarmingly, the rapid emergence of methicillin-resistant S. aureus strains (MRSA) jeopardizes the available treatment options. Herein, we propose sustainable, low-cost production of recombinant lysostaphin (rLST), which is a native bacteriocin destroying the staphylococcal cell wall through its endopeptidase activity. We combined the use of E. coli BL21(DE3)/pET15b, factorial design, and simple Ni-NTA affinity chromatography to optimize rLST production. The enzyme yield was up to 50 mg/L culture, surpassing reported systems. Our rLST demonstrated superlative biofilm combating ability by inhibiting staphylococcal biofilms formation and detachment of already formed biofilms, compared to vancomycin and linezolid. Furthermore, we aimed at developing a novel rLST topical formula targeting staphylococcal skin infections. The phase inversion composition (PIC) method fulfilled this aim with its simple preparatory steps and affordable components. LST nano-emulgel (LNEG) was able to extend active LST release up to 8 h and cure skin infections in a murine skin model. We are introducing a rapid, convenient rLST production platform with an outcome of pure, active rLST incorporated into an effective LNEG formula with scaling-up potential to satisfy the needs of both research and therapeutic purposes.

SARS-CoV-2: an unknown agent and challenges in vaccine development

SARS-CoV-2: an unknown agent and challenges in vaccine development

Preconditions and Preparatory Steps of Implementing CLIL for Future Mathematics Teachers

This article focuses on the problem of implementing the integrated learning of Mathematics and English by future Mathematics teachers based on the Content and Language Integrated Learning (CLIL) model. Our review of the literature confirms that this method is considered to be an effective approach to the formation and development of students’ subject knowledge and foreign language skills. This technology is significant for the professional training of future Mathematics teachers since they should be competent in both Mathematics and foreign language to effectively teach today’s schoolchildren. A student questionnaire was conducted and its analysis shows that students believe that CLIL will benefit them in the process of their professional training. Since the CLIL approach is multidimensional process, its implementation requires thorough preparation. This paper demonstrates and describes some specific steps in the preparatory stage for implementing the CLIL approach for the professional training of future Mathematics teachers: determining mathematical course, choosing its specific themes (units), planning for expected results, designing the organizational features of the educational process using the CLIL method and designing the appropriate teaching and methodological support. The possible variant for designing the preparatory stage for the integrated teaching and learning of “Number Theory” and English is suggested. It is demonstrated that the Mathematical and foreign language component of the expected educational outcomes need to be distinguished. The educational process should involve a special system of multilevel bilingual assignments. It also should have some special preconditions and joint activities of Mathematics and English teachers.

Study of the Reduction of Fe on Reduced Graphene Oxide as a Catalyst for Carbon Monoxide Reduction

This work aims at optimizing the H2 reduction time of Fe/rGO as a preparatory step for the use of the reduced catalyst in Fisher-Tropsch synthesis (FTS). The catalytic system used was Iron Nanoparticles (NPs) loaded on reduced graphene oxide (rGO) support. The as prepared sample was analyzed by TEM, FTIR and XRD spectroscopy. Samples of the produced Fe/rGO catalyst were used to optimize the reduction conditions in the FBR reactor. The three samples were reduced under 1atm H2 gas flow of 50 sccm at 500°C for 8, 12 and 24 hrs. The samples were collected after reduction and analyzed by XRD, FTIR and TEM imaging. The best condition showing full reduction with minimal sintering was at 12hr.

The Giving Punishment of School Rules Violation in Enforcing Discipline Characters on MTs. Raudlatussa'adah Pontianak

This research is motivated by the recent most cases of rule violations conducted by a number of students in MTs. Raudlatussa'adah Pontianak. From the results of observations and initial documentation of the research, the forms of violations that are often done by students are late, wearing needless uniforms, long hair, inappropriate hair cut for students, fighting and other forms of violations. Even though MTs. Raudlatussa'adah Pontianak has made written rules including the threat of sanctions / penalties for the perpetrators. Based on the background of the problem, the researcher then conducted further research in order to explore and analyze information about how the act of giving penalties in cases of school rules violations in order to uphold the character of students. The approach and method used in research is a qualitative approach with descriptive methods, that this study seeks to describe the phenomenon in accordance with the facts occurred in the field. Furthermore, the subjects in this study include: Principal of Madrasah, Deputy Head of Madrasah for Student Affairs, Teachers of Islamic Character and students. For data collection researchers used in-depth interview techniques, non-participant observation and study documentation. The data processing and analysis techniques used consist of data reduction, data presentation and conclusions. Meanwhile, to check the validity of the data, researchers used triangulation techniques. Based on the explanation and analysis of the research data, it can be concluded that the preparatory step for the punishment of school rules violations in an effort to uphold the character of student discipline is done by verbalizing the punishment in the Student Orientation Period (MOS) activities, flag ceremonies and through classroom wall magazines and billboards. . As for the implementation of the punishment given by the teacher, but it is not consistent with the existing rules and the implementation also does not contain educational elements.

ISSAID/EMQN Best Practice Guidelines for the Genetic Diagnosis of Monogenic Autoinflammatory Diseases in the Next-Generation Sequencing Era.

Monogenic autoinflammatory diseases are caused by pathogenic variants in genes that regulate innate immune responses, and are characterized by sterile systemic inflammatory episodes. Since symptoms can overlap within this rapidly expanding disease category, accurate genetic diagnosis is of the utmost importance to initiate early inflammation-targeted treatment and prevent clinically significant or life-threatening complications. Initial recommendations for the genetic diagnosis of autoinflammatory diseases were limited to a gene-by-gene diagnosis strategy based on the Sanger method, and restricted to the 4 prototypic recurrent fevers (MEFV, MVK, TNFRSF1A, and NLRP3 genes). The development of best practices guidelines integrating critical recent discoveries has become essential. The preparatory steps included 2 online surveys and pathogenicity annotation of newly recommended genes. The current guidelines were drafted by European Molecular Genetics Quality Network members, then discussed by a panel of experts of the International Society for Systemic Autoinflammatory Diseases during a consensus meeting. In these guidelines, we combine the diagnostic strength of next-generation sequencing and recommendations to 4 more recently identified genes (ADA2, NOD2, PSTPIP1, and TNFAIP3), nonclassical pathogenic genetic alterations, and atypical phenotypes. We present a referral-based decision tree for test scope and method (Sanger versus next-generation sequencing) and recommend on complementary explorations for mosaicism, copy-number variants, and gene dose. A genotype table based on the 5-category variant pathogenicity classification provides the clinical significance of prototypic genotypes per gene and disease. These guidelines will orient and assist geneticists and health practitioners in providing up-to-date and appropriate diagnosis to their patients.

Exploring the Role of ‘Shadowing’ as a Beneficial Preparatory Step for Sensitive Qualitative Research with Children and Young People with Serious Health Conditions

This article aims to explore and record the role of shadowing in preparation for a qualitative study involving children and families with sensitive health issues. The researcher was engaged for a study involving qualitative research involving paediatric patients (those under 18 years old) and their families, but was unfamiliar with a hospital environment and interviewing children and young people (CYP) with a serious health condition. The researcher ‘shadowed’ healthcare professionals (HCPs) at a children’s hospital during their day-to-day work in order to prepare for the research interviewing. From shadowing, the researcher gained: familiarity with a hospital environment, organisational processes, and medical terminology; an understanding of the appropriate ways to refer to patients; confidence and competence in talking to children with serious health conditions; and resilience to becoming upset during interviews while hearing patients’ distressing stories—they became ‘desensitised’. Shadowing can therefore be highly beneficial for researchers undertaking research in unfamiliar contexts, environments, and populations prior to interviewing.

A Direct PCR on Conidiospore of Aspergillus niger

In this paper, a simplified PCR protocol using intact conidiospore of Aspergillus niger was established by checking its internal transcribed spacers and inter-simple sequence repeat. The A. niger efficient conidiospore concentration range for direct PCR was investigated simultaneously. Compared to other methods, this protocol does not need a physical or chemical preparatory step which is especially beneficial to direct PCR on fungal conidiospore with massive metabolite secretion.

Aboveground carbon emissions from gold mining in the Peruvian Amazon

In the Peruvian Amazon, high biodiversity tropical forest is underlain by gold-enriched subsurface alluvium deposited from the Andes, which has generated a clash between short-term earnings for miners and long-term environmental damage. Tropical forests sequester important amounts of carbon, but deforestation and forest degradation continue to spread in Madre de Dios, releasing carbon to the atmosphere. Updated spatially explicit quantification of aboveground carbon emissions caused by gold mining is needed to further motivate conservation efforts and to understand the effects of illegal mining on greenhouse gases. We used satellite remote sensing, airborne LiDAR, and deep learning models to create high-resolution, spatially explicit estimates of aboveground carbon stocks and emissions from gold mining in 2017 and 2018. For an area of ∼750 000 ha, we found high variations in aboveground carbon density (ACD) with mean ACD of 84.6 (±36.4 standard deviation) Mg C ha−1 and 83.9 (±36.0) Mg C ha−1 for 2017 and 2018, respectively. An alarming 1.12 Tg C of emissions occurred in a single year affecting 23,613 hectares, including in protected zones and their ecological buffers. Our methods and findings are preparatory steps for the creation of an automated, high-resolution forest carbon emission monitoring system that will track near real-time changes and will support actions to reduce the environmental impacts of gold mining and other destructive forest activities.

Preparations for a Controversial Speaker and Anticipated Volatility in a College Town.

In summer of 2017 in Charlottesville, Virginia, white nationalists clashed with counterprotestors, ultimately leading to the death of three people and leaving 34 more injured. Soon after, the same group was granted permission to speak on the campus of the University of Florida in Gainesville, Florida. Despite our college town having limited resources and personnel, the comprehensive and extensive preparation preceding the event ensured a peaceful resolution for such a large and potentially volatile situation. The preparatory steps required joint efforts from local and state partners in law enforcement, emergency medical services, and emergency departments. We describe here the situation we faced, the pre-event preparations, the response in the field and in our emergency department, and the outcomes from an emergency and tactical medicine perspective. We hope our successful experience will impart knowledge for similar events.

Manifold Approximation by Moving Least-Squares Projection (MMLS)

In order to avoid the curse of dimensionality, frequently encountered in big data analysis, there has been vast development in the field of linear and nonlinear dimension reduction techniques in recent years. These techniques (sometimes referred to as manifold learning) assume that the scattered input data is lying on a lower-dimensional manifold; thus the high dimensionality problem can be overcome by learning the lower dimensionality behavior. However, in real-life applications, data is often very noisy. In this work, we propose a method to approximate $$\mathcal {M}$$ a d-dimensional $$C^{m+1}$$ smooth submanifold of $$\mathbb {R}^n$$ ( $$d \ll n$$ ) based upon noisy scattered data points (i.e., a data cloud). We assume that the data points are located “near” the lower-dimensional manifold and suggest a nonlinear moving least-squares projection on an approximating d-dimensional manifold. Under some mild assumptions, the resulting approximant is shown to be infinitely smooth and of high approximation order (i.e., $$\mathcal {O}(h^{m+1})$$ , where h is the fill distance and m is the degree of the local polynomial approximation). The method presented here assumes no analytic knowledge of the approximated manifold and the approximation algorithm is linear in the large dimension n. Furthermore, the approximating manifold can serve as a framework to perform operations directly on the high-dimensional data in a computationally efficient manner. This way, the preparatory step of dimension reduction, which induces distortions to the data, can be avoided altogether.

A Bayesian Hierarchical Model for Criminal Investigations

Potential violent criminals will often need to go through a sequence of preparatory steps before they can execute their plans. During this escalation process police have the opportunity to evaluate the threat posed by such people through what they know, observe and learn from intelligence reports about their activities. In this paper we customise a three-level Bayesian hierarchical model to describe this process. This is able to propagate both routine and unexpected evidence in real time. We discuss how to set up such a model so that it calibrates to domain expert judgments. The model illustrations include a hypothetical example based on a potential vehicle based terrorist attack.