Simple Guidelines Research Articles

A Simple Guideline for Applying Online or Offline Biochemical/Biological Databases Targeting Undergraduate Students up to Postgraduate Ones

About half a century ago, perhaps few people thought that the development of a particular type of viral disease and the vaccination process would take nearly a year; however, it happened (successful or unsuccessful). The best tool to help researchers in this direction is the subsequent development of computer-based science and proprietary processes. As we all know, biological science is largely attributed to the development of computers and artificial intelligence in the identification, prevention, and treatment of various diseases. The different overlap between these two disciplines has always attracted the audience of its attributes in the interdisciplinary field. For a specific group of science students, one of the disadvantages is familiarity with how they work and how to distinguish between databases. Many databases for researchers have been developed online in their specific fields. Searching and using this series of data on the Internet has become a common practice, which means that for a professional researcher, this in itself turns into an advantage. However, some groups are interested in using these data and do not have the special information as experienced researchers. This article briefly attempts to introduce a simple ladder of biochemical science and biology based solely on cyberspace.

Investigation of ultra-high performance concrete slabs under contact explosions with a calibrated K&C model

Karagozian and Case (K&C) concrete model is extensively adopted in the numerical simulations of ultra-high performance concrete (UHPC) structural members subjected to impulsive loads such as impact and blast. In this study, a calibration of the K&C concrete model was conducted for UHPC in terms of three strength surfaces, equation of state, shear dilatancy, damage evolution and strain rate effect to offer simple and general guidelines on the determination of key model parameters for this new class of concrete. With the calibrated concrete model, a single element method was adopted to verify its accuracy through a comparison to the results from the static tests of the uniaxial compression, direct tension and triaxial compression. Furthermore, the numerical simulations of contact explosion tests on the UHPC slabs with the incorporation of the strain rate effect were performed and the numerical results exhibited good predictions regarding the failure mode, crater and scabbing damage as compared to the test results. More importantly, this proposed numerical model and simulation methodology are reasonable to be generally used for structural members constructed of UHPC materials under contact explosions when lacking sufficient static and dynamic test data. Using the calibrated and validated K&C concrete model, parametric studies were conducted to derive a new empirical equation for predicting the local damage mode of UHPC slabs under contact explosions.

Efficacy of IOTA simple rules, O-RADS, and CA125 to distinguish benign and malignant adnexal masses

ObjectiveOvarian cancer is the most deadly deadliest gynecological tumor in the female reproductive system. Therefore, the present study sought to determine the diagnostic performance of International Ovarian Tumor Analysis Simple Rules (IOTA SR), the Ovarian-Adnexal Reporting and Data System (O-RADS), and Cancer Antigen 125 (CA125) in discriminating benign and malignant ovarian tumors. The study also assessed whether a combination of the two ultrasound categories systems and CA125 can improve the diagnostic performance.MethodsA total of 453 patients diagnosed with ovarian tumors were retrospectively enrolled from Fujian Cancer Hospital between January 2017 and September 2020. The data collected from patients included age, maximum lesion diameter, location, histopathology, levels of CA125, and detailed ultrasound reports. Additionally, all ultrasound images were independently assessed by two ultrasound physicians with more than 5 years of experience in the field, according to the IOTA simple rules and O-RADS guidelines. Furthermore, the area under the curve (AUC), sensitivity, and specificity of the above mentioned predictors were calculated using the receiver operating characteristic curve.ResultsOut of the 453 patients, 184 had benign lesions, while 269 had malignant ovarian tumors. In addition, the AUCs of IOTA SR, O-RADS, and CA125 in the overall population were 0.831, 0.804, and 0.812, respectively, and the sensitivities of IOTA SR, O-RADS, and CA125 were 94.42, 94.42, and 80.30%, respectively. On the other hand, the AUCs of IOTA SR combined with CA125, O-RADS combined with CA125, and IOTA SR plus O-RADS combined with CA125 were 0.900, 0.891, and 0.909, respectively. The findings also showed that the AUCs of a combination of the three approaches were significantly higher than those of individual strategies (p<0.05) but not significantly higher than the AUC of a combination of two methods (p>0.05).ConclusionThe findings showed that a combination of IOTA SR or O-RADS in combination with CA125 may improve the ability to distinguish benign from malignant ovarian tumors.

Should I use fixed effects or random effects when I have fewer than five levels of a grouping factor in a mixed-effects model?

As linear mixed-effects models (LMMs) have become a widespread tool in ecology, the need to guide the use of such tools is increasingly important. One common guideline is that one needs at least five levels of the grouping variable associated with a random effect. Having so few levels makes the estimation of the variance of random effects terms (such as ecological sites, individuals, or populations) difficult, but it need not muddy one’s ability to estimate fixed effects terms—which are often of primary interest in ecology. Here, I simulate datasets and fit simple models to show that having few random effects levels does not strongly influence the parameter estimates or uncertainty around those estimates for fixed effects terms—at least in the case presented here. Instead, the coverage probability of fixed effects estimates is sample size dependent. LMMs including low-level random effects terms may come at the expense of increased singular fits, but this did not appear to influence coverage probability or RMSE, except in low sample size (N = 30) scenarios. Thus, it may be acceptable to use fewer than five levels of random effects if one is not interested in making inferences about the random effects terms (i.e. when they are ‘nuisance’ parameters used to group non-independent data), but further work is needed to explore alternative scenarios. Given the widespread accessibility of LMMs in ecology and evolution, future simulation studies and further assessments of these statistical methods are necessary to understand the consequences both of violating and of routinely following simple guidelines.

A robust nonlinear PI-type controller for the DC–DC buck–boost power converter

In this study, a novel Lyapunov function-based robust nonlinear proportional–integral (PI)-type controller for regulating the output voltage of the direct current to direct current (DC–DC) inverting buck–boost power converter operating in continuous conduction mode (CCM) is presented. The control scheme guarantees global asymptotic stability of the closed-loop system even in case of parameter uncertainty. The analysis of the closed-loop trajectories is carried out using Lyapunov method and LaSalle’s invariance principle. Robustness to additive disturbances is shown and simple gain tuning guidelines are given. Real-time experiments support the theoretical results. Experimental tests are presented where the proposed PI-type control design is compared with other PI-type schemes found in the literature. The proposed scheme presents very good consistent performance under line and load disturbance.

Pilot Study to Quantify Palladium Impurities in Lead-like Compounds Following Commonly Used Purification Techniques.

Palladium-catalyzed reactions are among the most commonly used procedures in organic synthesis. The products have a range of uses, including as intermediates in total synthesis and as screening compounds for drug discovery or agrochemical projects. Despite the known and potentially deleterious effects of low-level metal impurities in biological assays, the quantification of metal remaining in reaction products to verify the effective removal of the transition element is rarely reported. Using palladium as an exemplar, we describe a pilot study that for the first time quantifies residual metal levels in reaction products following increasingly rigorous purification protocols. Our results demonstrate that significant levels of residual palladium can remain in isolated reaction products following chromatographic purification, and only by using a subsequent metal scavenging step are they reliably reduced to a low level. Finally, we provide a set of simple guidelines that should minimize the potential for issues associated with residual palladium in reaction products.

A Study on High-Speed Outlier Detection Method of Network Abnormal Behavior Data Using Heterogeneous Multiple Classifiers

As the complexity and scale of the network environment increase continuously, various methods to detect attacks and intrusions from network traffic by classifying normal and abnormal network behaviors show their limitations. The number of network traffic signatures is increasing exponentially to the extent that semi-realtime detection is not possible. However, machine learning-based intrusion detection only gives simple guidelines as simple contents of security events. This is why security data for a specific environment cannot be configured due to data noise, diversification, and continuous alteration of a system and network environments. Although machine learning is performed and evaluated using a generalized data set, its performance is expected to be similar in that specific network environment only. In this study, we propose a high-speed outlier detection method for a network dataset to customize the dataset in real-time for a continuously changing network environment. The proposed method uses an ensemble-based noise data filtering model using the voting results of 6 classifiers (decision tree, random forest, support vector machine, naive Bayes, k-nearest neighbors, and logistic regression) to reflect the distribution and various environmental characteristics of datasets. Moreover, to prove the performance of the proposed method, we experimented with the accuracy of attack detection by gradually reducing the noise data in the time series dataset. As a result of the experiment, the proposed method maintains a training dataset of a size capable of semi-real-time learning, which is 10% of the total training dataset, and at the same time, shows the same level of accuracy as a detection model using a large training dataset. The improved research results would be the basis for automatic tuning of network datasets and machine learning that can be applied to special-purpose environments and devices such as ICS environments.

Electrochemically exfoliated Ni-doped MoS2 nanosheets for highly efficient hydrogen evolution and Zn-H2O battery

Thanks to tunable physical and chemical properties, two-dimensional (2D) materials have received intensive interest, endowing their excellent electrocatalytic performances for applications in energy conversion. However, their catalytic activities are largely determined by poor adsorption energy and limited active edge sites. Herein, a one-step electrochemical exfoliation strategy was developed to fabricate 2D Ni-doped MoS2 nanosheets (Ni-EX-MoS2) with a lateral size of ∼500 nm and thickness of ∼3.5 nm. Profiting from high electrical conductivity and abundant exposing active sites, Ni-EX-MoS2 catalyst displayed an admirable performance for electrochemical hydrogen evolution reaction (HER) with a low overpotential of 145 mV at 10 mA/cm2 as well as a small Tafel slope of 89 mV/dec in alkaline media, which are superior to those of the most reported MoS2-based electrocatalysts. The formed Ni species with tuning electronic structure played a crucial role as primary active center of Ni-EX-MoS2, as well as the forming stable 1T/2H phase MoS2 interface demonstrated a synergistic effect on electrocatalytic HER performance. Further, Ni-EX-MoS2 was employed as a cathode electrode for alkaline Zn-H2O battery, which displayed a high power density of 3.3 mW/cm2 with excellent stability. This work will provide a simple and effective guideline for design of electrochemically exfoliated transition metal-doped MoS2 nanosheets to inspire their practical applications in energy catalytic and storage.

Development of 5-E Learning Cycle-Based Simple Chemistry Practicum Guideline Module for Eleventh Grade

The chemistry practicum activity in school is impossible due to the COVID-19 pandemic, whereas practicum is very important to train soft skills and understanding of chemistry materials. This research aimed to develop 5-e learning cycle-based simple chemistry practicum guideline module for students of class XI. The development model used was a 4-D development model. The quality of the product was assessed by one material expert, one media expert, five reviewers (chemistry teachers of high school), and responded by ten students of high school. The instruments used in the research were product quality assessment sheets using a Likert scale and student response sheets, in the form of a questionnaire, using the Guttman scale. The characteristics of the developed practicum module were in the form of a practicum module for hydrocarbons, thermochemistry, reaction rates, and chemical equilibrium, using simple tools and chemicals; being combined with the 5-e learning cycle model. The quality assessment on the practicum module, which was carried out by one material expert, media experts, and reviewers, gained 88.89. 95.83. and 94.00%. All assessments got a score with Very Good score. From these results, it can be concluded that the developed product is feasible to be used as a practicum guideline.

Simple and cost-effective cross-polarization experiments under dissolution-dynamic nuclear polarization conditions with a 3D-printed 1H-13C background-free radiofrequency coil

The low sensitivity of conventional nuclear magnetic resonance experiments can be overcome, in suitable cases, by employing hyperpolarization methodologies. One such technique, dissolution-dynamic nuclear polarization, provides a robust means of strongly polarizing a variety of small molecules. A drawback of the dissolution-dynamic nuclear polarization approach, the excessively long polarization timescales for insensitive nuclei, has been circumvented by using cross-polarization radiofrequency pulse sequences, which in general yield quick and substantial 13C polarizations. However, the capacity to effectively perform efficient cross-polarization experiments under dissolution-dynamic nuclear polarization conditions remains challenging, and polarization quantification can be plagued by additional complications including spurious background signals from the probe. Here we propose a background-free1H-13C radiofrequency coil specifically designed for use in cross-polarization experiments on samples of up to 500 μL in volume at liquid helium temperatures. We additionally introduce simple guidelines for the optimization and implementation of cross-polarization radiofrequency pulse sequences. Experimental demonstrations of 13C polarizations reaching ∼60% are presented for the case of [1-13C]sodium acetate.

Enhanced energy-storage performance in BNT-based lead-free dielectric ceramics via introducing SrTi0.875Nb0.1O3

Environmentally friendly lead-free ceramics capacitors, with outstanding power density, rapid charging/discharging rate, and superior stability, have been receiving increasing attention of late for their ability to meet the critical requirements of pulsed power devices in low-consumption systems. However, the relatively low energy storage capability must be urgently overcome. Herein, this work reports on lead-free SrTi0.875Nb0.1O3 (STN) replacement of (Bi0.47La0.03Na0.5)0.94Ba0.06TiO3 (BLNBT) ferroelectric ceramics with excellent energy storage performance. Improving relaxor behaviour and breakdown strength (Eb), decreasing grain size, and mitigating large polarization difference are conductive to the enhancement of comprehensive energy storage performances. The phase-field simulation methods are further analysized evolution process of electrical tree in the experimental breakdown. In particular, the 0.70BLNBT-0.30STN ceramic exhibit a large discharged energy density of 4.2 J/cm3 with an efficiency of 89.3% at room temperature under electric field of 380 kV/cm. Additionally, for practical applications, the BLNBT-based ceramics achieve a high power density (∼62.3 MW/cm3) and fast discharged time (∼148.8 ns) over broad temperature range (20–200 °C). Therefore, this work can provide a simple and effective guideline paradigm for acquiring high-performance dielectric materials in low-consumption systems operating in a wide range of temperatures and long-term operations.

Who should get the scarce ICU bed? The US public’s view on triage in the time of COVID-19

ObjectiveTo determine the relative importance members of the US public place on different patient attributes in triage decisions about who should receive the last available intensive care unit (ICU) bed.MethodsA...

Analytical Shielding Metrics-Based Shielding Configuration Guideline for ELF Magnetic Field Mitigation

This paper presents a simple guideline for configuration of the shielding materials that mitigates the extremely low-frequency (ELF) magnetic fields generated by power facilities located close to our daily life activities. Generally, materials with high permeability and conductivity are used to mitigate the magnetic field; however, in the current source region, before passing through the shielding material, the magnetic field may be increased by the configuration of the shielding material. To assess the effect of the shielding configuration in the current source and shielding regions, metrics are newly introduced, which were obtained based on the analytical solution for infinite width shields. In addition, the analytical solution of the shielding pipe wrapping a current source was deduced by solving the cylindrical Helmholtz equation. The shielding pipe is an important factor that can bring about changes in the metrics introduced in this study. The simple shielding guidelines suggested from these analyses help determine strategies for designing shields that can mitigate the magnetic field in both the current source and shielding regions.

A critical analysis of recursive model indexes

The recursive model index (RMI) has recently been introduced as a machine-learned replacement for traditional indexes over sorted data, achieving remarkably fast lookups. Follow-up work focused on explaining RMI's performance and automatically configuring RMIs through enumeration. Unfortunately, configuring RMIs involves setting several hyperparameters, the enumeration of which is often too time-consuming in practice. Therefore, in this work, we conduct the first inventor-independent broad analysis of RMIs with the goal of understanding the impact of each hyperparameter on performance. In particular, we show that in addition to model types and layer size, error bounds and search algorithms must be considered to achieve the best possible performance. Based on our findings, we develop a simple-to-follow guideline for configuring RMIs. We evaluate our guideline by comparing the resulting RMIs with a number of state-of-the-art indexes, both learned and traditional. We show that our simple guideline is sufficient to achieve competitive performance with other learned indexes and RMIs whose configuration was determined using an expensive enumeration procedure. In addition, while carefully reimplementing RMIs, we are able to improve the build time by 2.5x to 6.3x.

Distributed Hierarchical Control With Separation of Concerns for Parallel-Connected UPSs

This article presents a distributed hierarchical control structure for parallel uninterruptible power supplies. A dynamic approach with separation of concerns is proposed for the secondary control, where a so-called grid forming inverter is responsible for restoring the amplitude and frequency of the output voltage, while the remaining inverters, called grid supporting, are responsible for enhancing long-term power sharing. This strategy aims to minimize the tradeoff between voltage regulation and power sharing through secondary control, which uses a low bandwidth communication link. For the primary controller, resistive droop control with virtual resistance is employed to accomplish short-term power sharing. Simple design guidelines for the secondary controllers based on simplified models developed in the article are provided. Extensive experimental results obtained from two 500-VA prototypes demonstrated the good performance of the proposed strategy. The amplitude and power sharing errors remained below 1% and 2%, respectively, for the entire load range evaluated.

CHARACTERISTICS OF PATIENTS WITH PROCALCITONIN MEASUREMENTS DURING EARLY DIAGNOSIS PROCESS

Aim: To present the population of patients admitted to the Emergency Department in whom their attending physician decided to assess PCT level. Material and methods: All data were collected between 01/04/2022 and 30/04/2022. The inclusion criterion was performed PCT measurement at admission to the Emergency Department. The following data were noted: age, gender, temperature, blood pressure, heart rate, SpO2, respiratory rate, Glasgow Coma Scale, the diagnosis: pneumonia, infection tractus urinary, diabetes, SARS-Cov-2 infection, PCT level, C-reactive protein level, leucocyte level, glomerular filtration rate. PCT upper normal limit was 0.05 μg/L, C- reactive protein upper limit was 5 mg/dL and leucite number was between 4 and 10 G/dL. Results: PCT level was increased in 68 (83%) of the studied group. The patients with increased PCT level are older, have lower blood pressure and more often increased C-reactive protein concentration. These patients tended to have increased in-hospital mortality. Conclusions: PCT level was increased in the majority of patients in whom this parameter was assessed by emergency physicians. Abnormal leucocyte number and the presence of temperature above 37 Celsius degree had no prediction value of presence of increased PCT. Increased PCT level may indicate the increased risk of the in hospital death. Simple guidelines for PCT usage need to be created and implemented in everyday clinical practice.

Introduction to in silico synthesis of polymers via PySIMM [Article v1.0

Pysimm is a framework for molecular simulations of polymers and polymer-based nanostructures, which enables their direct chemical synthesis and preparation. Pysimm facilitates the understanding of novel, amorphous, processable materials for a broad range of applications, including heterogeneous catalysts, adsorbents and gas storage materials, as well as protein-polymer conjugates. This tutorial provides a detailed guide on the construction of atomistic and united-atom models of polymers using Pysimm: an open-source Python Application Programming Interface for atomistic molecular simulations. The API complements and simplifies the work of widely known molecular simulation software, such as LAMMPS, CASSANDRA, NAMD and Amber. Readers should be familiar with the basic concepts of atomistic molecular simulations, as well as the basic knowledge of Python programming language, before attempting to follow this tutorial. This work is separated into 3 main sections. First, the process of building an atomic-level model of a polymer chain from its repetitive units is described. The second section shows how to work with existing forcefields, and how Pysimm can automatically read, recognize, and assign appropriate Force Field parameters to a molecule. The final section discusses how to use Pysimm to construct polymer chains with pre-specified tacticity. The section is also available in the form of an interactive Jupyter notebook tutorial outlining simple guidelines to construct polymer models.

A Guide to Industry Payments and an Algorithm for Their Management.

The Open Payments database was created to increase transparency of industry payment relationships within medicine. The current literature often examines only 1 year of the database. In this study, the authors use 5 years of data to show trends among industry payments to plastic surgeons from 2014 to 2018. In addition, the authors lay out the basics of conflict-of-interest reporting for the new plastic surgeon. Finally, the authors suggest an algorithm for the responsible management of industry relationships. This study analyzed nonresearch payments made to plastic surgeons from January 1, 2014, to December 31, 2018. Descriptive statistics were calculated using R Statistical Software and visualized using Tableau. A total of 304,663 payments totaling $140,889,747 were made to 8148 plastic surgeons; 41 percent ($58.28 million) was paid to 50 plastic surgeons in the form of royalty or license payments. With royalties excluded, average and median payments were $276 and $25. The average yearly total per physician was $2028. Of the 14 payment categories, 95 percent of the total amount paid was attributable payments in one of six categories. Seven hundred thirty companies reported payments to plastic surgeons from 2014 to 2018; 15 companies (2 percent) were responsible for 80 percent ($66.34 million) of the total sum paid. Allergan was responsible for $24.45 million (29.6 percent) of this amount. Although discussions on the proper management of industry relationships continue to evolve, the data in this study illustrate the importance of managing industry relationships. The simple guidelines suggested create a basis for managing industry relationships in the career of the everyday plastic surgeon.

Prevalence and Impact Factors of COVID-19 Vaccination Hesitancy Among Breast Cancer Survivors: A Multicenter Cross-Sectional Study in China.

Cancer patients are at a high risk of being infected with COVID-19 and have a poor prognosis after infection. Breast cancer is one of the most common cancers. Since vaccination is an effective measure to prevent the spread of COVID-19, we studied the vaccination rate among breast cancer survivors and analyzed their characteristics to provide evidence for boosting the vaccination rate. The researchers conducted a multicenter, cross-sectional study on 747 breast cancer survivors from six hospitals in Wuhan city between June 5, 2021, and June 12, 2021. The self-administrated questionnaires based on relevant studies were distributed. The researchers then compared differences in characteristics among vaccinated patients, hesitant patients, and non-vaccinated patients. Moreover, they performed univariable and multivariable logistic regression analyses to identify potential factors associated with vaccination hesitancy. The researchers assessed a total of 744 breast cancer survivors −94 cases in the vaccinated group, 103 in the planning group, 295 in the hesitancy group, and 252 in the refusal group. The vaccination rate was 12.63% (95% CI 10.25–15.02%) and 37.23% (95% CI 27.48–47.82%) patients reported adverse reactions. The vaccination hesitancy/refusal rate was 73.52% (95% CI 70.19–76.66%), which was independently associated with current endocrine or targeted therapy (odds ratio [OR] = 1.52, 95% CI 1.03–2.24), no notification from communities or units (OR = 2.46, 95% CI 1.69–3.59) and self-perceived feel (general vs. good, OR = 1.46, 95% CI 1.01–2.13; bad vs. good, OR = 4.75, 95% CI 1.85–12.16). In the hesitancy/refusal group, the primary reason was “I did not know who to ask whether I can get vaccinated” (46.07%), the person who would most influence decisions of patients was the doctor in charge of treatment (35.83%). Effective interaction between doctors and patients, simple and consistent practical guidelines on vaccination, and timely and positive information from authoritative media could combat misinformation and greatly reduce vaccine hesitancy among breast cancer survivors.

Saddle-Point Convergence of Constrained Primal-Dual Dynamics

In this letter, we consider saddle-point convergence of primal-dual dynamics for inequality constrained convex optimization problems. By considering the primal-dual dynamics as the interconnection of (i) a gradient system and (ii) a nonlinear controller with incremental sector-bounded static nonlinearity, we establish asymptotic stability by invoking the classical notions of Lyapunov stability, the invariance principle, along with some regularity assumptions. For the special case of strongly convex problem with affine constraints, we prove global exponential convergence. As compared to existing techniques in the literature, the proposed approach offers simple and transparent tuning guideline for robust exponential stability of the saddle-point dynamics and allows for establishing an upper bound on the exponential decay rate.