Critical Elements Research Articles

Viscoelastic Slider Blocks as a Model for a Seismogenic Fault.

In this work, a model is proposed to examine the role of viscoelasticity in the generation of simulated earthquake-like events. This model serves to investigate how nonlinear processes in the Earth's crust affect the triggering and decay patterns of earthquake sequences. These synthetic earthquake events are numerically simulated using a slider-block model containing viscoelastic standard linear solid (SLS) elements to reproduce the dynamics of an earthquake fault. The simulated system exhibits elements of self-organized criticality, and results in the generation of avalanches that behave similarly to naturally occurring seismic events. The model behavior is analyzed using the Epidemic-Type Aftershock Sequence (ETAS) model, which suitably represents the observed triggering and decay patterns; however, parameter estimates deviate from those resulting from natural aftershock sequences. Simulated aftershock sequences from this model are characterized by slightly larger p-values, indicating a faster-than-normal decay of aftershock rates within the system. The ETAS fit, along with realistic simulated frequency-size distributions, supports the inclusion of viscoelastic rheology to model the seismogenic fault dynamics.

Assessment of anti-malondialdehyde-acetaldehyde antibody frequencies in rheumatoid arthritis with new data from two independent cohorts, meta-analysis, and meta-regression

BackgroundAutoantibodies are critical elements in RA pathogenesis and clinical assessment. The anti-malondialdehyde-acetaldehyde (anti-MAA) antibodies are potentially useful because of their claimed high sensitivity for all RA patients, including those lacking RF and anti-CCP antibodies. Therefore, we aimed to replicate these findings.MethodsWe independently attempted replication in Santiago and Barcelona using sera from 517 and 178 RA patients and 272 and 120 healthy controls, respectively. ELISA protocols for anti-MAA antibodies included five antigens (human serum albumin in three formulations, fibrinogen, and a synthetic peptide) and assays for the IgG, IgM, and IgA isotypes. We integrated our results with information found by searching the Web of Science for reports of anti-MAA antibodies in RA. The available patients (4989 in 11 sets) were included in a meta-analysis aimed at heterogeneity between studies. Factors accounting for heterogeneity were assessed with meta-regression.ResultsThe sensitivity of anti-MAA antibodies in our RA patients was low, even in seropositive patients, with the percentage of positives below 23% for all ELISA conditions. Our results and bibliographic research showed IgG anti-MAA positive patients ranging from 6 to 92%. The extreme between-studies heterogeneity could be explained (up to 43%) in univariate analysis by sex, African ethnicity, the site of study, or recruitment from the military. The best model, including African ancestry and smoking, explained a high heterogeneity fraction (74%).ConclusionAnti-MAA antibody sensitivity is extremely variable between RA patient collections. A substantial fraction of this variability cannot be attributed to ELISA protocols. On the contrary, heterogeneity is determined by complex factors that include African ethnicity, smoking, and sex.

Short-Loop Recycling of Nd-Fe-B Permanent Magnets: A Sustainable Solution for the RE2Fe14B Matrix Phase Recovery.

The green transition initiatives and exploitation of renewable energy sources require the sustainable development of rare earth (RE)-based permanent magnets prominent technologies like wind turbine generators and electric vehicles. The recycling of RE-based permanent magnets is necessary for the future supply of critical rare-earth elements. The short-loop recycling strategies to directly reprocess Nd-Fe-B magnet waste are economically attractive and practical alternatives to conventional hydro- and pyrometallurgical processes. This study focuses on the development of a procedure to extract the (Nd, Pr)2Fe14B hard-magnetic phase from sintered Nd-Fe-B magnets. The extraction is achieved through preferential chemical leaching of the secondary, RE-rich phases using 1 M citric acid. Before the acid treatment, the magnets were pulverized through hydrogen decrepitation (HD) to increase the material's surface-to-volume ratio. The as-pulverized Nd-Fe-B powder was subsequently exposed to a 1 M citric acid solution. The effect of leaching time (5-120 min) on the phase composition and magnetic properties was studied. The results of the microstructural (SEM) and compositional (ICP-MS) analyses and the study of thermal degassing profiles revealed that the RE-rich phase is preferentially leached within 5-15 min of reaction time. Leaching of the secondary phases from the magnet's multi-phase microstructure is governed by the negative electrochemical potential of Nd and Pr. The extraction of (Nd, Pr)2Fe14B grains by the proposed acid leaching approach is compatible with the existing hydrogen processing of magnetic scrap (HPMS) technologies. The use of mild organic acid as a leaching medium makes the leaching process environmentally friendly, as the leaching medium can be easily neutralized after the reaction is completed.

Customer segmentation research in marketing through clustering algorithm analysis

In marketing, customer segmentation is a very critical element. This paper focuses on clustering algorithms. First, the commonly used K-means algorithm was introduced, and then, it was optimized using the improved Lion Swarm Optimization (ILSO) algorithm and the Calinski-Harabasz (CH) index. The results of the experiment for the UCI dataset showed that the CH indicator obtained an accurate number of clusters, and the clustering accuracy of the ILSO-K-means algorithm was higher, both above 90%. Then, in customer segmentation, the customers of an enterprise were divided into four groups using the ILSO-K-means algorithm, and different marketing suggestions were given. The experimental analysis proves the usability of the ILSO-K-means algorithm in customer segmentation, which can be further applied in practice.

Ethics of New Technologies in Distance Learning of a Foreign Language: a Neuroscientific Approach

The article proves that in recent years important advances have been made in neurobiology regarding education. With advanced scientific knowledge of cerebral activity in learning, educators have the opportunity to use interesting tools to improve academic performance in higher education when teaching a foreign language. Based on research on brain function, educators have created distance-learning tools useful for teaching a foreign language. While these tools are an important and critical element of the learning process, the emphasis in this study is different, that is, to teach students to become familiar with their own brain function and then to mobilize their metacognitive resources during distance learning. In this regard, teachers have faced many issues of organizing feedback from the study group, transferring learning materials to distance education platforms, monitoring progress and many others, while engaging the metacognitive resources of students. The issue of formation of information and communication and neurocompetence of foreign language teachers has become especially urgent in the pedagogical environment. Due to the lack of relevant skills, teachers had to adapt to the new educational conditions and completely restructure the educational process.

Intricate Interplay between Knowledge Management and Creative Organizational Climate effecting Smart Organization

In today's hypercompetitive and rapidly evolving business environment, organizations strive to embrace smart practices that foster innovation, agility, and sustainable growth. This research investigates the transformative influence of two critical elements, Knowledge Management (KM) and Creative Organizational Climate (COC), on the development of smart organizations. Knowledge Management encompasses a systematic approach to identifying, capturing, organizing, and sharing both tacit and explicit knowledge within an organization. In the context of a smart organization, KM serves as the backbone of informed decision-making, enabling efficient knowledge flow across functional units and facilitating the creation of a learning-oriented culture. This research explores diverse KM strategies, technologies, and implementation challenges, highlighting their contributions to building knowledge-driven organizations.
 Through an extensive review of existing literature and case studies, this research reveals the complex interplay between Knowledge Management and Creative Organizational Climate in shaping the emergence of a smart organization. By combining these two essential factors, organizations can harness the full potential of their knowledge assets, boost organizational learning, and cultivate an innovative workforce.

Evaluation of chlorpyrifos and Beauveria bassiana as a strategy in the Egyptian sugar beet fields: impact on Spodoptera littoralis (Boisduval) and its associated predators populations and the sugar beetroot yield

BackgroundThe susceptibility of pests and natural enemies to conventional insecticides is a critical element in judging the success of integrated pest management programs implementing biological control as a tactic. In this study, the susceptibility of the cotton leafworm Spodoptera littoralis (Boisd.) (Lepidoptera: Noctuidae) to an organophosphorus insecticide (chlorpyrifos) and the entomopathogenic fungus Beauveria bassiana was evaluated through field applications during two successive sugar beet seasons. The populations of the coccinellid, chrysopid, and formicid predators were estimated to indicate pesticide risk assessment strategy. The root and sugar yields were compared during the whole experiment to emphasize the impact of both control strategies on the pre-harvest loss in this strategic crop.ResultsResults indicated that over the course of the two seasons of the investigation, chlorpyrifos significantly reduced the population density of S. littoralis and its associated predators. It showed a detrimental effect on S. littoralis larval population than untreated areas, causing an overall reduction of 97 and 92% during the 1st and 2nd seasons, respectively. The biopesticide based on entomopathogenic fungus Beauveria bassiana caused an overall reduction of S. littoralis, reaching 96 and 65% during the 1st and 2nd seasons, respectively. Meanwhile, B. bassiana slightly affects the population of predators compared to insecticide-free areas, so it was recommended for application in sugar beet fields without providing considerable risk to the associated insect predators. The sugar beetroot production and its sugar content increased significantly in both treatments during the two growing seasons compared to non-treated plots.ConclusionChlorpyrifos is not recommended for pest control; instead, B. bassiana is considered an effective biopesticide in the Egyptian sugar beet fields infested with S. littoralis as part of an integrated pest management program. Their effect was direct through reducing pest population and indirectly increasing the sugar beetroot production and increasing its total sugar content. Hence, both the sugar beetroot quality and quantity were improved favoring the microbial agent over the chemical insecticide in application for mitigating the chemical hazards toward the associated predators.

The Stochastic Climate Model helps reveal the role of memory in internal variability in the Bohai and Yellow Sea

Hasselmann’s theory elucidates how short-term random noise leads to longer-term unprovoked variations, i.e., red spectra. Here, we study ensembles of numerical model simulations of the hydrodynamics of the Bohai and Yellow Sea concerning internal variability formation. Short(/long) term variations are associated with small(/large) spatial scales, and the internal variability of long-term temporal and large-scale variations is markedly enhanced, even without external forcing on these scales, when the tides are turned off. This pattern is well explained by Hasselmann’s theory. A critical element in this theory is the concept of memory, which in our ensembles exhibits a scale dependence that aligns with the scale-dependent nature of redness. Additionally, this framework clarifies why there is a significant reduction of long-term fluctuations during winter and when tides are active: the system’s memory is notably diminished under these conditions.

Critical elements of pediatric testicular germ cell tumors surgery

Children, adolescents and young adults with testicular germ cell tumors require appropriate surgical care to insure excellent outcomes. This article presents the most critical elements, and their basis in evidence, for surgery in this population. Specifically, the importance of inguinal radical orchiectomy for malignant tumors, partial orchiectomy for prepubertal tumors and normal serum tumor markers, and the appropriate use of post-chemotherapy retroperitoneal lymph node dissection in those with residual retroperitoneal masses.

Critical elements in the operative management of pediatric malignant ovarian germ cell tumors

Performance of the appropriate operation is highly important to ensure that any patient with a suspected ovarian germ cell tumor receives optimal therapy that prioritizes cure while simultaneoulsy minimizing risk of short and long-term toxicities of treatment. The following critical elements of any operative procedure performed for a suspected pediatric or adolescent ovarian germ cell tumor are reviewed: 1. Complete resection of the tumor via ipsilateral oophorectomy while avoiding tumor rupture and spillage, and 2. Performance of complete intraperitoneal staging at the time of initial tumor resection.

Novel model predictive control-based motion cueing algorithm for compensating centrifugal acceleration in KUKA robocoaster-based driving simulators.

The washout motion cueing algorithm (MCA) is a critical element in driving simulators, designed to faithfully reproduce precise motion cues while minimizing false cues during simulation processes, particularly deceptive translational and rotational cues. To enhance motion sensation accuracy and optimize the use of available workspace, model predictive control (MPC) has been employed to develop innovative motion cueing algorithms. While most MCAs have been tailored for the Steward motion platform, there has been a recent adoption of the motion platform based on KUKA Robocoaster as an economical option for driving simulators. However, leveraging the full potential of the KUKA Robocoaster requires trajectory conversion of the motion base. Thus, this research proposes a novel MCA specifically designed for the KUKA Robocoaster-based motion platform, utilizing large planar circular motion to simulate lateral movement for drivers. Nonetheless, circular motion introduces disruptive centrifugal forces, which can be mitigated through proper pitch-tilted angles. The novel MPC generates simulated motion that accurately follows the lateral specific force target and effectively maintains the roll angular velocity below its threshold value. Additionally, it compensates for disturbing centrifugal acceleration by implementing pitch rotational motion, ensuring the pitch angular velocity remains below its threshold. Simulation tasks conducted on the motion platform, focusing solely on lateral acceleration, demonstrate the successful elimination of false motion cues in both the roll/sway and pitch/surge channels. The proposed innovative MPC solution offers an original approach to motion cueing algorithms in KUKA Robocoaster-based driving simulators. It enables the exploitation of the KUKA Robocoaster platform's capabilities while delivering accurate and immersive motion cues to drivers during simulation experiences.

Enhancing Higher Education Writing Achievement: An Experimental Exploration Of Problem-Based Learning And Technological Integration

This research aims to improve higher education writing achievement through a ground-breaking experimental investigation of problem-based learning and technological integration. Motivated by recognized issues in English education at Adzkia University, where students struggle with weaknesses in paragraph building, idea production, and organizational skills, our research strives to reshape the landscape of writing training. Our study pioneers a unique departure from previous techniques by recognizing instructional methodology and technology as critical elements. Problem-based learning and technological integration emerge as dynamic alternatives, promising a paradigm shift in how writing skills are developed in higher education. The instruments that were used for this research were writing tests. T-test analysis was used in analyzing the data. Our findings from T-test analysis show that students exposed to problem-based learning and technology significantly improve their writing proficiency, exceeding their counterparts in traditional education. In summary, this study drives the conversation on educational technique, asking institutions to embrace the dynamic integration of problem-based learning and technology. The findings not only demonstrate the effectiveness of this novel strategy, but also herald a new age in higher education in which writing prowess becomes an empowered manifestation of student accomplishment.

A Data-Driven Rutting Depth Short-Time Prediction Model with Metaheuristic Optimization for Asphalt Pavements Based on RIOHTrack

Rutting of asphalt pavements is a crucial design criterion in various pavement design guides. A good road transportation base can provide security for the transportation of oil and gas in road transportation. This study attempts to develop a robust artificial intelligence model to estimate different asphalt pavements' rutting depth clips, temperature, and load axes as primary characteristics. The experiment data were obtained from 19 asphalt pavements with different crude oil sources on a 2.038 km long full-scale field accelerated pavement test track (RIOHTrack, Road Track Institute) in Tongzhou, Beijing. In addition, this paper also proposes to build complex networks with different pavement rutting depths through complex network methods and the Louvain algorithm for community detection. The most critical structural elements can be selected from different asphalt pavement rutting data, and similar structural elements can be found. An extreme learning machine algorithm with residual correction (RELM) is designed and optimized using an independent adaptive particle swarm algorithm. The experimental results of the proposed method are compared with several classical machine learning algorithms, with predictions of Average Root Mean Squared Error, Average Mean Absolute Error, and Average Mean Absolute Percentage Error for 19 asphalt pavements reaching 1.742, 1.363, and 1.94\% respectively. The experiments demonstrate that the RELM algorithm has an advantage over classical machine learning methods in dealing with non-linear problems in road engineering. Notably, the method ensures the adaptation of the simulated environment to different levels of abstraction through the cognitive analysis of the production environment parameters.

Critical elements of pediatric neuroblastoma surgery

Neuroblastoma (NB) is the most common solid extracranial malignancy of childhood with an incidence of 1 per 100,000 in the United States compromising approximately 10 % of childhood cancer. Unfortunately, patients with high-risk NG continue to have long-term survival less than 50 %. Both Children's Oncology Group and the International Society of Paediatric Oncology have demonstrated the important role of surgery in the treatment of high-risk NB. Herein, we compose the results of an extensive literature review as well as expert opinion from leaders in pediatric surgical oncology, to present the critical elements of effective surgery for high-risk neuroblastoma.

From the Editors.

Some of us may recall a time in healthcare when it seemed that the summer months were a bit quieter, providing an opportunity to catch our breath before the onslaught of fall and the ramp-up to flu season. Yet, with the increasing demand on our health systems, the sense of downtime has all but disappeared. This may suggest that we collectively have less time available for review, reflection and learning - all of which are critical elements for improvement and transformation. As an editorial team, our contribution is to continue synthesizing and presenting leading practices and innovative concepts to our readers, enabling them to access knowledge and ideas more easily. It is how we can help build capacity in our system to deliver better healthcare at a time when renewal is needed more than ever.

Effectiveness of Gamification in Enhancing Learning and Attitudes: A Study of Statistics Education for Health School Students.

Gamification is the use of game design elements in non-game contexts. It is considered a student-centered instructional design to motivate student learning and academic behavior. In this study, the effects of gamification on learning statistics (hypothesis testing issue) and attitude toward statistics in comparison with the common e-learning approach were investigated. The students' experience and critical elements of gamification on learning statistics were assessed, too. In a before and after trial, in a census manner, 64 health faculty students of Guilan University of Medical Sciences, Rasht, Iran, non-randomly were assigned to the intervention (n=42) and control (n=22) groups. Learning activities were gamified in the intervention group, while the control group received traditional problem-solving in the learning management system. Narrative, avatar, level, point, progress bar, scoreboard, challenge and feedback elements were used in the game experience. The implementation of gamification was applied based on Landers' theory of gamified content. Valid and reliable Persian version of the Survey Attitude toward Statistics questionnaire measured the students' attitude before and after the intervention. The EGameFlow questionnaire and a valid and reliable researcher-made exam measured the users' experience of gamified content and learning hypothesis testing after the intervention. The independent samples T-test, analysis of covariance and the partial eta-squared effect size were calculated by SPSS software, version 26. Compared to the control group, the intervention group had a more positive attitude toward learning difficulty (moderate partial eta-squared 0.099), value and cognitive competency (weak partial eta-squared=0.01 and 0.05). Learning between the two groups was not different (P=0.522). There was a significant correlation between learning and the students' perceived experience with feedback (r=0.583, P<0.001), concentration (r=0.509, P=0.005), and challenge (r=0.421, P=0.023) of the gamified content. It suggests using gamification on learning statistics while optimizing the design with more focus on the feedback, challenge and concentration elements.

Critical elements of pediatrics sacrococcygeal germ cell tumor surgery

Sacrococcygeal teratoma is the most common extragonadal germ cell tumor in the pediatric population, and accounts for approximately 70% of all teratomas in childhood.1,2 They present in two distinct phases, with most cases seen in neonates with large predominately exophytic tumors, often detected in utero on prenatal sonography or at birth. A smaller cohort presents in older infants and children with primarily hidden tumors in the pelvis which have a much higher rate of malignancy. The primary surgical objective is complete tumor resection without compromise to critical structures or function. Herein we outline the critical elements of tumor resection and management of sacrococcygeal germ cell tumors with a focus on the technical aspects of this tumor across a range of presentations.

Effect of Plasma-Activated Time for Ozone Generation in SDBD System Under Pulse and Sinusoidal Excitation

In the surface dielectric barrier discharge (SDBD) excitation schema, different power source topologies, such as the pulse and sinusoidal voltage inverters, are used to obtain the plasma. The inverter design is a critical element for consumer applications. However, some works in the literature have explained plasma properties and high-voltage excitation, but no clear definition has been identified to select a plasma property for a particular application. In general, SDBD is used for nonthermal plasma applications such as air purification and sterilization. Plasma generates reactive species that can react with target substances. Therefore, the reactive species generation rate greatly affects the plasma reaction performance. In addition, some researchers compare the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathrm{O}_3$</tex-math> </inline-formula> generation rate with sinusoidal and pulse power supply, but they do not focus enough on the plasma which determines the electrical properties. In this study, the plasma-activated time (PAT) is introduced to link the plasma properties and electrical parameters. Sinusoidal and pulse voltage excitation characteristics and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathrm{O}_3$</tex-math> </inline-formula> generation rates are used to experiment with this concept. The generation of reactive species is tested by measuring the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathrm{O}_3$</tex-math> </inline-formula> generation rate under fixed electrical and environmental conditions such as voltage, temperature, humidity, frequency, and PAT.

A Practitioner’s Experience as Chief Compliance Officer: Ideal Versus Reality

The Chief Compliance Officer (CCO) role within organizations continues to grow and evolve. As reported by Snell in an interview with the CCO of a major healthcare organization, compliance is a critical element of strategic directions and organizational objectives. Compliance must not be considered a roadblock but rather one of strategic collaboration and a valued resource for the organization. There is no definitive guidebook for CCOs, and the external demands for compliance continue to grow and evolve rapidly. For example, in 2023, a Memorandum on Establishing the Fight Against Corruption was issued by the White House. In 2022, the Department of Justice (DoJ) issued directives empowering CCOs regarding the assurance of compliance and maintaining a high level of compliance awareness. The DoJ also asserted that other executive leadership must be held accountable for compliance. Many states have implemented laws designed to protect consumers, including the California Consumer Protection Act, partially based on the General Data Protection Regulations (GDPR) applied in Europe. As the CCO of a mid-sized Unified Communications as a Service (UCaaS) provider, however, the most significant challenge was the application of best practices for compliance as indicated by research and scholarly efforts with the realities of funding, profitability, and acceptance of compliance as a strategic asset. This article reviews compliance opportunities and challenges through the lens of what succeeded, what failed, and the compromises required in the real world rather than a romantic version where everything follows a best practices model.

Critical elements of radical nephroureterectomy for pediatric unilateral renal tumor

Children with renal masses require surgical management to provide accurate surgical staging and skilled resection of the tumor. This document includes evidence-based recommendations for pediatric surgeons regarding the resection, staging, and proper nodal basin evaluation.