Low Level Of Complexity Research Articles

Predictors of sentence recall performance in children with and without DLD: Complexity matters.

Using archival data from 106 children with and without DLD who spoke two dialects of English, we examined the independent contributions of vocabulary, morphological ability, phonological short term memory (pSTM), and verbal working memory (WM) to exact sentence recall, ungrammatical repetition, and incorrect tense production. For exact repetitions on simpler sentences, performance of the DLD group was predicted by morphological ability, pSTM and WM, while that of the TD group was predicted by vocabulary and sometimes pSTM. On complex sentences, performance of the DLD group was predicted by morphological ability, and the TD group was predicted by pSTM and WM. For ungrammatical repetitions and incorrect tense, morphological ability was a factor for both groups, with WM also affecting the DLD group for ungrammatical production. Thus, sentence recall taxes multiple resources, with more and different factors being taxed at lower levels of complexity for children with DLD than those without.

Online resources for strabismus: an evaluation of readability, complexity, and suitability.

Over one-third of US adults have never attended college, creating a large disparity in the readability of online health materials. Decreased health literacy and accessibility to medical information negatively affect patients and well-informed patients are more likely to experience better health outcomes (1). The NIH and AMA recommend patient-intended education materials be written at a sixth-grade reading level (2), therefore, this study analyzed the accessibility of the top ten web pages for "strabismus." The first ten online resources returned in a Google search for "strabismus" were analyzed. Web pages were then assessed for the readability level (Simple Measure of Gobbledygook), complexity (PMOSE/IKIRSCH), and suitability (Suitability Assessment of Materials). Two independent raters assessed the complexity and suitability. Readability analysis of the strabismus resources revealed an average reading grade level of 11.4 ± 1.07. There was a statistical difference in the reading grade level between the .com and .gov, and the .org and .com websites (p = .029 and p = .031, respectively). Complexity analysis revealed a mean score of 6.50 ± 2.29, corresponding to an 8th-12th grade reading level. The suitability assessment showed a mean value of 70.3 10.1%, representing a "superior" score for the information provided to the reader. The inter-rater agreement was similar for the complexity and fair for the suitability analysis. On average, online resources for strabismus have a low complexity level. However, the majority of the top ten articles reviewed are above the recommended literacy level, indicating a need for revision. The vast amount of available online health resources have significantly affected the field of medicine. Most patients research their disease process using online sources and many reference this material before their initial ophthalmologic consultation. Considering that more than half of Americans read below the equivalent of a sixth-grade level and that the AMA/NIH recommend all patient-intended materials to be written above this level, there is a health literacy disconnect. This limits patients' ability to educate themselves about their medical conditions and participate in informed conversations regarding their healthcare. Patients who are unable to interpret health information accurately have increased rates of hospitalization, develop more medical conditions, and experience a higher rate of mortality. This preventable impediment to informed healthcare care magnifies the urgency for easily readable online resources that are formatted in a manner that is clear to understand and suitable for patients with lower health literacy.

A Multilayer Architecture towards the Development and Distribution of Multimodal Interface Applications on the Edge.

Today, Smart Assistants (SAs) are supported by significantly improved Natural Language Processing (NLP) and Natural Language Understanding (NLU) engines as well as AI-enabled decision support, enabling efficient information communication, easy appliance/device control, and seamless access to entertainment services, among others. In fact, an increasing number of modern households are being equipped with SAs, which promise to enhance user experience in the context of smart environments through verbal interaction. Currently, the market in SAs is dominated by products manufactured by technology giants that provide well designed off-the-shelf solutions. However, their simple setup and ease of use come with trade-offs, as these SAs abide by proprietary and/or closed-source architectures and offer limited functionality. Their enforced vendor lock-in does not provide (power) users with the ability to build custom conversational applications through their SAs. On the other hand, employing an open-source approach for building and deploying an SA (which comes with a significant overhead) necessitates expertise in multiple domains and fluency in the multimodal technologies used to build the envisioned applications. In this context, this paper proposes a methodology for developing and deploying conversational applications on the edge on top of an open-source software and hardware infrastructure via a multilayer architecture that simplifies low-level complexity and reduces learning overhead. The proposed approach facilitates the rapid development of applications by third-party developers, thereby enabling the establishment of a marketplace of customized applications aimed at the smart assisted living domain, among others. The supporting framework supports application developers, device owners, and ecosystem administrators in building, testing, uploading, and deploying applications, remotely controlling devices, and monitoring device performance. A demonstration of this methodology is presented and discussed focusing on health and assisted living applications for the elderly.

Factors Influencing Adherence to Treatment in Adult Patients with Hypertension

Introduction Adherence to treatment including medication and lifestyle modification is crucial for improving health outcomes in patients with hypertension. However, there is limited research investigating the factors influencing adherence to medication and lifestyle modification, particularly among adult patients diagnosed with hypertension. Objective To investigate adherence to treatment and the predictive power of work status, comorbidity, complexity of medication regimens, perceived severity and risk of hypertension complications, and quality of care affecting adherence to treatment in adult patients with hypertension. Design Cross-sectional correlational predictive research using the multidimensional adherence model as the conceptual framework. Methodology The sample included 156 adult patients with essential hypertension aged 18 to 59 years old who had received antihypertensive medication and lifestyle modification treatment for at least six months at a super-tertiary hospital’s hypertension clinic. Data were collected between April and July 2023. The research instruments consisted of a general profile questionnaire, a treatment adherence questionnaire for patients with hypertension, a perceived severity and risk of hypertension complications questionnaire, a patient assessment of chronic illness care, the Charlson Comorbidity Index, a medication regimen complexity index, and an illness record form. These instruments were examined for content validity by experts and tested for reliability prior to use in data collection. The reliability ranged from .77-1.00. The data were analyzed using descriptive statistics and multiple linear regression. Results The sample had an average age of 46.50 years (SD = 9.65); 63.46% were female. The average score for adherence to treatment was 87.97 (SD = 9.02), with the highest score for average medication adherence of 34.37 (SD = 2.52) and the lowest score for average exercise adherence of 4.33 (SD = 1.89). Additionally, 14.74% were overweight, and 71.80% were obese. The majority were employed (83.33%), without any comorbidities (62.82%), and had a low level of medication regimen complexity (68.59%). Furthermore, they demonstrated a high level of perceived severity and risk of hypertension complications (96.15%) and reported a high level of quality of care (61.54%). In the Multiple linear regression, 30.9% of the variance in adherence to treatment was explained (Adjusted R2 = .309 F(5,150) = 14.858, p < .001). Work status (β = -.262, p < .001), comorbidity (β = -.184, p = .020), perceived severity and risk of hypertension complications (β = .466, p < .001), and quality of care (β = .165, p = .017) together were significant predictors of adherence to treatment in adult patients with hypertension. Recommendation To promote adherence to treatment in adult patients with hypertension, nurses should develop strategy to improve quality of care within hypertension clinics and enhance the perceived severity and risk of hypertension complications as well as enhance lifestyle modifications particularly regarding diet and exercise for overweight and obese adults with hypertension.

Reduced levels of MRE11 cause disease phenotypes distinct from ataxia telangiectasia-like disorder.

The MRE11/RAD50/NBS1 (MRN) complex plays critical roles in cellular responses to DNA double-strand breaks. MRN is involved in end binding and processing, and it also induces cell cycle checkpoints by activating the ataxia-telangiectasia mutated (ATM) protein kinase. Hypomorphic pathogenic variants in the MRE11, RAD50, or NBS1 genes cause autosomal recessive genome instability syndromes featuring variable degrees of dwarfism, neurological defects, anemia, and cancer predisposition. Disease-associated MRN alleles include missense and nonsense variants, and many cause reduced protein levels of the entire MRN complex. However, the dramatic variability in the disease manifestation of MRN pathogenic variants is not understood. We sought to determine if low protein levels are a significant contributor to disease sequelae and therefore generated a transgenic murine model expressing MRE11 at low levels. These mice display dramatic phenotypes including small body size, severe anemia, and impaired DNA repair. We demonstrate that, distinct from ataxia telangiectasia-like disorder caused by MRE11 pathogenic missense or nonsense variants, mice and cultured cells expressing low MRE11 levels do not display the anticipated defects in ATM activation. Our findings indicate that ATM signaling can be supported by very low levels of the MRN complex and imply that defective ATM activation results from perturbation of MRN function caused by specific hypomorphic disease mutations. These distinct phenotypic outcomes underline the importance of understanding the impact of specific pathogenic MRE11 variants, which may help direct appropriate early surveillance for patients with these complicated disorders in a clinical setting.

Examining the problem-posing performances of seventh-grade students in relation to response order

In this study, 176 Turkish seventh-grade students were asked to pose three problems for each of the swimming and purchasing tasks to examine how the solvability and complexity of the problems changed depending on the order of responses. The purchasing task required to pose a problem to derive a specific answer before posing new problems, whereas the swimming task required to pose problems based on existing data. The findings indicated that students performed poorly in terms of posing solvable problems in both tasks. The majority of solvable responses in the purchasing task were at the high complexity level, but most in the swimming task were at the low complexity level. No evidence of a relationship between the order of the responses and any of the analysis units (solvability and complexity) was found. Furthermore, when comparing the groups that posed and did not pose solvable problems for the specific answer in the purchasing task, the former group had a stronger tendency to maintain the complexity points in their other responses compared to their first response.

Playing to learn: developing self-directed learning skills through serious games

Purpose Higher education is undergoing a significant transformation, demanding a rethinking of instructional methods, the establishment of novel assessment frameworks and the incorporation of state-of-the-art technologies to advance the development of learning competencies. The use of simulations is an alternative that offers satisfactory results and favors learning in new generations. This study aims to present a methodology for assessing the advancement of self-directed learning (SDL) in participants through simulation techniques and show that the incorporation of simulations can improve participants’ SDL skills. Design/methodology/approach This study uses a quantitative approach to evaluate the evolution of various competencies related to SDL among participants. Includes the application of scales specifically designed to measure readiness for SDL, the use of factor analysis to identify and validate essential factors and conducting hypothesis testing to verify shifts in students’ perceptions regarding the significance of SDL-related skills. Findings The findings of this study reveal a positive impact of simulations on the SDL readiness. Factor analysis identified five key factors: self-management skills, openness to learning opportunities, initiative and independence in learning, self-concept as an effective learner and desire for Learning. The use of simulations significantly improved critical thinking, logical reasoning, analysis and decision-making capabilities. These results demonstrate the effectiveness of this technique as a valuable tool for developing SDL skills and highlight the potential of such interventions in complex and uncertain learning environments. Research limitations/implications The study provided valuable insights into the impact of simulations in the logistics field, particularly in the development of SDL-related skills. There is a need for studies in other areas of knowledge that would allow for the generalization of these results. Likewise, it is advisable to use scales that measure the development of other types of skills. Additionally, the study’s focus on short-term effects may not fully capture the long-term development of SDL-related skills. Future research should address these limitations, expand the sample size, conduct longitudinal studies and explore possible contextual and external factors that may influence SDL outcomes in various educational settings, leading to broader and more robust conclusions. Practical implications The practical implications of this study are significant for both higher education institutions and educators in the logistics domain. The positive impact of the serious game on participants’ SDL skills highlights the potential of incorporating interactive and engaging learning tools in the curriculum. Educators can leverage serious games to foster critical thinking, logical reasoning and decision-making abilities in their students. Moreover, the identified key factors influencing SDL development provide valuable guidance for designing targeted interventions to enhance students’ self-management, initiative and love for learning. Social implications The social implications of this study underscore the importance of equipping individuals with SDL skills in a rapidly changing world. By integrating serious games and fostering SDL competencies, higher education institutions can contribute to a more adaptable and resilient workforce. Empowering students with critical thinking, innovative thinking and independent learning, they can enhance their ability to navigate the challenges of the labor market. This, in turn, may lead to a more informed and proactive society capable of addressing complex issues and making well-informed decisions. Originality/value This article arises from empirical exploration with students from two countries in Latin America (Mexico and Colombia), examining the importance of games in developing SDL skills. Furthermore, it promotes the use of a methodology with a low level of complexity, and that can be replicated with different games. This perspective adds valuable insights to the existing literature, offering practical implications for educators and institutions seeking effective strategies to promote SDL skills among students.

MNEs engagement with environmental sustainability in an emerging economy: Do dynamic capabilities and entrepreneurial orientation matter?

In this study, we investigate the link between multinational enterprises’ (MNEs) dynamic capabilities (DC) and their environmental collaboration with suppliers mediated by entrepreneurial orientation (EO) and moderated by environmental complexity. Drawing on responses from 249 managers of MNEs in Türkiye, we find that DC improve environmental collaboration with suppliers. Moreover, we posit that through EO, MNEs achieves greater environmental collaboration with suppliers for effective environmental solutions, especially at a low level of environmental complexity. The results enrich the role of organizational capabilities in strengthening environmental collaboration with suppliers to achieve environmental sustainability, and provide suggestions for managers and policymakers to better understand capabilities for the purpose of attaining sustainability.

The elderly wayfinding performance in an informative healthcare design indoors

This study examines the influence of architectural design elements and age on the wayfinding performance (WP) of older adults in healthcare circulation patterns. The study was conducted at Milad Hospital in Tehran, Iran, and included the Emergency, Outpatient, Clinics, and Inpatient wards. The study used a quantitative research method to investigate and virtual reality (VR) to simulate. Wayfinders were shown the circulation patterns of five types of healthcare circulations in virtual reality (VR) using two design approaches: high indicative features (the most guiding design aids) and a neutral environment (the fewest design aids). The study revealed that architectural design elements and age influence users' WP. Initially, it is worth noting that the mental-perceptual conditions of users in both groups were almost indistinguishable. However, the records of the elderly group (from 66 to 82 years) indicated a lower frequency of environmental design aid scenes (base design), which enabled them to more effectively identify and focus on locating the destination points. Nevertheless, the control group, consisting of younger individuals (from 18 to 39 years), exhibited superior and more efficient performance than their senior counterparts. When the users of both groups perceived the route to be challenging to traverse, their performance dropped, and they felt disoriented and anxious. Also, the Corridor circulation pattern exhibited a relatively low level of navigational complexity. Overall, the results suggest that architects should prioritize the design of circulation routes that are easily recognizable and highlight prominent features while considering the cognitive and perceptual needs of the elderly population.

Variational inference-based transfer learning for profile monitoring with incomplete data

Profile monitoring is a widely used tool in quality control. The rapid development of sensor technology has created unprecedented opportunities for multi-channel profile data collection, which motivates the modeling and transfer learning for multi-profile data. The Multi-output Gaussian Process (MGP) is often used for multi-profile data, due to its flexible modeling capability and elegant mathematical properties. However, two practical concerns limit the broader application of MGP for transfer learning and monitoring of multi-profile data: high computational complexity and data incompleteness. In this article, we propose a Variational Inference (VI)-based MGP framework to facilitate transfer learning and profile monitoring using incomplete profile data. The proposed framework features a specially designed convolutional structure for constructing an explicit covariance relationship between the inducing variables in VI and the MGP in multi-profile data. This structure inspires a comprehensive solution to both computational complexity and data incompleteness in modeling multi-profile data, which facilities the transfer learning for profile monitoring. Various numerical studies and one real case study are conducted to demonstrate and compare the transfer learning and monitoring performance of the proposed method. The results show the method can achieve superior monitoring performance while maintain a very low level of computational complexity.

Erosion of community complexity increases temperature-dependency of microbial respiration, but not growth, in short-term incubations

Biodiversity loss and climate change are 2 of the most alarming threats to ecosystem functioning and stability. These factors are, however, typically investigated separately, overlooking potential interactions between species extinctions and climate change on ecosystems. Here, we evaluated how different temperature regimes impact the relationship between microbial diversity and ecosystem functioning, in terms of temperature sensitivity of carbon (C) cycling functions. We hypothesized that more complex communities promote the stability of C cycling functions under both temperature regimes. We did not observe a ubiquitous response of all C-cycling processes to temperature increases within communities of distinct complexities. While growth was stable with increasing temperatures across the complexity levels, respiration rates increased more strongly at low complexity than high complexity levels at higher temperatures. Carbon use efficiency, which integrates both growth and respiration, tended to decrease with temperature at lower levels of complexity. Jointly, these results demonstrate the importance of community complexity for maintaining C-cycling thermal response under a changing climate.

Real exchange rates and manufacturing exports in emerging economies: the role of sectoral heterogeneity and product complexity

The empirical evidence on the relationship between the real exchange rate and export performance in emerging economies is inconclusive. In this paper, we present evidence that one reason for this inconclusiveness is the use of real exchange rate (RER) measures that do not consider the heterogeneity between economic sectors. To this end, we calculate a unique sectoral bilateral RER index (SBRER) for 12 Latin American economies, which considers the variation of producer price differentials and bilateral nominal exchange rates across 21 manufacturing sectors and 38 trade partners between 2001–2018, and to estimate the effect of SBRER movements on manufacturing exports. The regression results show that the SBRER is a significant determinant of aggregate manufacturing exports, whereas the bilateral RER is not significant. Moreover, sectoral export elasticities indicate that mainly sectors with low levels of product complexity and, to a lesser extent, those of medium complexity are affected by RER movements. These findings show that it is important to consider sectoral heterogeneity when estimating RER export elasticities from a macroeconomic perspective.

Effects of management complexity on the composition, plant functional dominance relationships and physiognomy of high nature value grasslands

A significant proportion of Europe’s species-rich grasslands are semi-natural habitats. They have a long history of traditional management. Several studies have been carried out to conserve them, resulting in the establishment of subsidised conservation management schemes. On the other hand, many of these conservation management schemes have failed to provide locally adaptive solutions to maintain the diversity and functional status of species-rich grasslands. In addition, few studies have compared the conservation effectiveness of different levels of management complexity. The levels of management complexity in our study are based on how different management types (e.g. grazing and mowing etc.) and how different herbage removal intensities (e.g. lower and higher grazing intensities) are combined within and between years. To investigate this, we compared the overall effects of management complexity, herbage removal intensity and management type on plant diversity, plant functional type dominance relationships and plant physiognomy. Our field sampling was carried out in the sandy meso-xeric grasslands of the Turján Region of the Great Hungarian Plain (Central Hungary). We sampled nine 2 m × 2 m plots per grassland site (n = 12), recorded all the rooted plant species and estimated their percentage cover in each plot. High level of management complexity had significant positive effects on plant diversity, grazing had positive effects on plant diversity and phanerophyte density, while the studied levels of herbage removal intensity had no effect on diversity, plant functional types or plant physiognomy. In parallel, mowing and/or low levels of management complexity had some negative effects on conservation value (e.g. lower Shannon and Simpson diversity). In this landscape, the dominance of grazing and the more complex management is more optimal than relatively homogeneous mechanical mowing. The choice of management type and intensity is an important tool in the conservation management system of this landscape, but so too is its appropriate application in space and time. Through a detailed analysis of the effects of management complexity levels compared to management types and herbage removal intensity levels, we provide a new opportunity to make grassland management practices more effective for conserving biodiversity in this region, but it would be important to investigate these in different landscapes and conditions.

AI-powered mechanisms as judges: Breaking ties in chess.

Recently, Artificial Intelligence (AI) technology use has been rising in sports to reach decisions of various complexity. At a relatively low complexity level, for example, major tennis tournaments replaced human line judges with Hawk-Eye Live technology to reduce staff during the COVID-19 pandemic. AI is now ready to move beyond such mundane tasks, however. A case in point and a perfect application ground is chess. To reduce the growing incidence of ties, many elite tournaments have resorted to fast chess tiebreakers. However, these tiebreakers significantly reduce the quality of games. To address this issue, we propose a novel AI-driven method for an objective tiebreaking mechanism. This method evaluates the quality of players' moves by comparing them to the optimal moves suggested by powerful chess engines. If there is a tie, the player with the higher quality measure wins the tiebreak. This approach not only enhances the fairness and integrity of the competition but also maintains the game's high standards. To show the effectiveness of our method, we apply it to a dataset comprising approximately 25,000 grandmaster moves from World Chess Championship matches spanning from 1910 to 2018, using Stockfish 16, a leading chess AI, for analysis.

Tunnel Prescribed Control of Nonlinear Systems With Unknown Control Directions.

This article solves the entry capture problem (ECP) such that for any initial tracking error, it can be regulated into the prescribed performance constraints within a user-given time. The challenge lies in how to remove the initial condition limitation and to handle the ECP for nonlinear systems under unknown control directions and asymmetric performance constraints. For better tracking performance, we propose a unified tunnel prescribed performance (TPP) providing strict and tight allowable set. With the aid of a scaling function, error self-tuning functions (ESFs) are then developed to make the control scheme suitable to any initial condition (including the initial constraint violation), where the initial values of ESFs always satisfy performance constraints. In lieu of the Nussbaum technique, an orientation function is introduced to deal with unknown control directions while such way is capable of reducing the control peaking problem. Using ESFs, together with TPP and an orientation function, the resulted tunnel prescribed control (TPC) leads to a solution for the underlying ECP, which also exhibits a low complexity level since no command filters or dynamic surface control is required. Finally, simulation results are provided to further demonstrate these theoretical findings.

Theoretical aspects of designing the components of an aircraft onboard cable network

The article presents theoretical foundations of designing the components of an aircraft onboard cable network, proposed as a methodology for solving the problems of designing onboard equipment. The composition of the initial and developed technical documentation for the aircraft onboard cable network is determined. The article also shows the relationship between the stages of designing the onboard cable network and the stages of designing the aircraft. The formulation of the general task of creating the components of an onboard cable network is presented as a number of particular subtasks of a lower level of complexity. The method for solving the problem is based on a number of transformations performed with the original documentation in order to develop technical documentation for the introduction of the onboard system into the complex of onboard equipment. A number of successive transformations of the proposed bundle model using the apparatus of topology and multiset theory made it possible to form a model of the components of the onboard cable network of an aircraft that gives a detailed view of its future design. The proposed scientific approach to the design of aircraft onboard cable network components created the prerequisites for minimizing the heuristic component in the process of designing aircraft onboard cable network components.

Effects of Visual Complexity of Banner Ads on Website Users’ Perceptions

Design plays a major role in online advertising. While specific aspects such as color or animation have been extensively studied, there is a surprising lack of comprehensive research on the overall impact of visual design and aesthetics. This study delved into the effects of varying levels of visual complexity in banner ads using the eye-tracking method. Out of 108 participants browsing test webpages with specially designed banners, data from 90 adequately measured data sets were used in the study. Notably, ads with a low level of visual complexity outperformed ads with a high level of visual complexity. While users noticed complex ads slightly faster (by 0.84%), they fixated on them significantly less (by 9.09%) and looked at them less frequently (by 4.79%). An implemented survey questionnaire examining the user perception of the banners reinforced the superiority of simple ads, as they were perceived as 4.40% more appealing in comparison. The study further delved into the correlation between objectively and subjectively evaluated data, exploring the credibility of subjective methods in the process. Considering our results and findings from other studies, it was evident that visually complex ads demanded more cognitive effort, could be more distracting, negatively impacted attention, could contribute to banner blindness and were perceived as less appealing.

Hybrid‐simulation‐based model calibration method for nonlinear seismic analysis

AbstractThe calibration of parameters of hysteretic models that simulate the hysteretic behavior of key structural components is a crucial task in the nonlinear seismic analysis of structures to ensure accurate analysis results. For complicated systems, a direct calibration of model parameters at the system level is almost impossible due to the lack of test data. Consequently, the calibration is usually conducted using test results with lower levels of complexity. Currently, a widely accepted practice in calibrating hysteretic model parameters in structural models is to utilize standardized cyclic tests of a single component. However, due to the simplified and unrealistic loading profile of standardized cyclic tests, the relevance between the calibration and the system‐level prediction capabilities can be weak. In other words, a well‐tuned hysteretic model that matches the standardized cyclic test results very well may not be able to produce the same level of accuracy in estimating the system‐level structural dynamic response where the calibrated components will experience more random and complicated loadings. In this paper, a method is proposed to calibrate hysteretic models in a test method with more realistic loading histories through hybrid simulations. The proposed calibration method is then validated by conducting a large number of hybrid simulations on a type of small‐scale buckling‐restrained brace (BRB) specimen. A framework is also proposed to evaluate the relevance between the calibration and the system‐level response considering uncertainties in hysteretic model parameters. The results demonstrate the superiority of the hybrid‐simulation‐based calibration method over the conventional cyclic‐test‐based calibration method.

A proposed set of indicators for evaluating the performance of the operation and maintenance of photovoltaic plants

As photovoltaic plants (PV) age, the need for efficient monitoring of operations & maintenance (O&M) increases, helping to understand the situation of the plant, identify problems and propose solutions for future strategies. In this context, the objective of this paper is to propose a set of key performance indicators (KPIs), responsable to evaluate O&M performance in PV power plants, considering their importance and complexity mensuration levels. After refining and validating a set of KPIs using Delphi method with industry specialists, the KPIs are classified by energy performance assessment and O&M services assessment. Subsequently, the levels of importance and complexity of measurement are evaluated with stepwise weight assessment ratio analysis (SWARA) method. Finally, after obtaining this information, an importance-complexity matrix is developed, thus contemplating the proposed set of KPIs. This study presents a comprehensive set of 25 KPIs capable of quantitatively measuring the O&M performance of a PV plant. The results show that the KPIs, Performance Ratio and Spare Parts Availability are the most important in this evaluation, and KPI Contractual Availability presents greater complexity in measuring its parameters. Based on the importance-complexity matrix, it is possible to verify that the KPI, Schedule Compliance stands out compared to the others, presenting a high level of importance and a low level of complexity in its measurement. The information resulting from this study seeks to help PV plant managers to select the appropriate KPIs to measure the status of the O&M management of the PV plant.

Knowledge, attitudes, and perceptions of health care providers regarding the recommendation and use of long-acting reversible contraceptive devices for adolescent patients

Objective To describe the knowledge, attitudes, and perceptions of healthcare providers in a region in southwestern Colombia regarding the recommendation and use of long-acting reversible contraceptive (LARC) methods for adolescents. Study Design This was a cross-sectional study. An online exploratory survey was designed to assess healthcare providers’ knowledge, attitudes, and perceptions of Valle del Cauca hospitals. For the development of this the questionnaire, a literature search and validation of the instrument’s appearance were conducted. Results The survey was completed by 115 people. Knowledge: 62.6% and 33% of the participants did not consider themselves capable of correctly placing an intrauterine device (IUD) or a subdermal implant, respectively. However, 73.9% of the participants had adequate theoretical knowledge. Attitudes: 64.3% of the participants considered that adolescents can acquire contraceptive methods without limitations. Short-acting reversible methods were the least recommended. Perceptions: For IUDs, 40.8% and 16.5% of the participants imposed a minimum age and minimum parity requirement for their use, respectively. Side effects were the main reason for not recommending in health institutions with a lower level of complexity. Conclusion Healthcare providers had positive attitudes and adequate theoretical knowledge concerning to the effectiveness of LARCs. The main areas for improvement were practical knowledge about the insertion and proper use of the devices, indications for referral to gynaecologists for the insertion procedure, and concerns about side effects.