Flexible Set Research Articles

La pedagogía de la tulpa: nuevas estrategias educativas y nuevos paradigmas de aprendizaje

The year 2020 has undoubtedly marked a before and after for our generation, everything that we believed so close is now utopian, everything that we had within our reach now slips through our fingers, different aspects of our lives have had a 180 ° turn and we have had to reinvent ourselves to properly navigate the blog of our existence. Likewise, the research specifies the transformation of the dynamics of the tutorial function in the face of new current challenges and that in the same way favor the formation of the subject in an intercultural space and environment. In this contrast, the tulpa pedagogy is a manifestation of the characterization of a curriculum oriented towards the participation of the educational community with the construction of flexible and transversal settings in new environments from rural areas. In this sense, educational models focus on the specific knowledge of a free pedagogy mediated by cultural traits from a rural mode with an entrepreneurial and productive purpose. In this way, the design of educational models conditioned by the culture and the nature of the community determine scenarios with dynamics that highlight the idiosyncrasies that characterize the human being in its dimensions in learning to learn. Similarly, tulpa pedagogy refers to a transformative curriculum in a problematic and subjective way of learning.

The aspect of information security in modern CRM-systems in the era of digitalization of the economy and business

The subject of the article is the application of CRM class systems in the modern economy. In the conditions of informatization of economic data of all enterprises, regardless of the forms of ownership, the importance of using CRM-systems is growing rapidly. Modern CRM-systems allow businesses to make high-quality and timely management decisions based on data received from CRM-class systems. Of course, one should not forget about information security, which consists in the protection of data from unauthorized access. Data protection is one of the main parameters for choosing a CRM-system. Therefore, as a result, the problem of CRM-systems arises, which consists in finding a compromise between security characteristics and ease of use, so the goal of this article is precisely to achieve the necessary information security with the maximum comfort of users of this system. The article examines the peculiarities of digitalization of the economic sector by combining CRM-systems with modern frameworks and IT-security technologies. The features of the functioning of the modern digital market, CRM-systems and security technologies are analyzed. The main modern technologies, standards and security protocols in the conditions of digitization are considered. The principles of security and convenience, on which CRM-systems should be based, are highlighted. In this study, the advantage in terms of efficiency, convenience, safety and security was given to the Oauth2 protocol and the technology implemented by Keycloak. Data security in the proposed CRM-system is ensured by flexible access settings. These two powerful tools allow you to protect any resource from unauthorized access without transferring important user data to another party and provide quite convenient options and alternatives for authorization. Using these technologies when developing your own CRM or integrating them into an already ready system is almost the best security solution.

Owner-Enabled Secure Authorized Keyword Search Over Encrypted Data With Flexible Metadata

Metadata plays an essential role in facilitating data organizing, finding, and understanding, but it also contains lots of sensitive information about the data and the data users, e.g., the location where a picture was taken. In practice, when sensitive data is encrypted before being uploaded to untrusted public clouds, an oblivious dilemma comes: if the metadata is totally encrypted, and its functionalities no longer exist; otherwise, sensitive information may be leaked. Hence, a secure and flexible mechanism for processing different fields (marked private or public for different scenario needs) of metadata simultaneously is desirable. We searched the literature for methods of achieving such a goal, it turned out that this was not explicitly considered or reasonably solved before. Therefore, in this paper, we investigate the problem of constructing privacy-enhancing metadata, namely, 1) flexible and tamper-resistant metadata setting, 2) owner-enabled secure search authorization with explicit metadata. Based on the concept of public key encryption with keyword search (PEKS), we propose a novel Authorized Keyword Search over Encrypted Data with Metadata scheme (MD-AKS), which firstly well addressed the above demands. We formalize the security model and prove the security of MD-AKS scheme. Our work maximizes the flexibility of metadata setting in two aspects: the associated metadata can be set as an arbitrary string and the costs of clients are independent of explicit metadata’s complexity. We implement MD-AKS, the theoretical comparison and experiment results further demonstrate the usability and scalability.

Monument und Monopoly. György Ligetis erstes Stück für zwei Klaviere und Spieltheorie

Motivated by the exchange of ideas with the biologist and chaos researcher Manfred Eigen and Douglas R. Hofstadter’s Gödel, Escher, Bach (1979), György Ligeti’s later compositions refer explicitly to mathematical phenomena (e.g., in the Piano Etudes since 1985). Ligeti himself recognized scientific models also in his works that were composed before this period. One of the significant pieces during the transition to his late works is Monument (the first movement of the Three Pieces for two Pianos from 1976) which points clearly in the direction of the late compositional style. Monument does not follow rigid mathematical rules, but rather a flexible set of game rules. A simple starting point and a clear goal cause continuously ramifying rules. Their complexity forces the composer to exert a maximum of control over the conception and the compositional process. Monument starts with six layers of tones, played in different dynamics, different cycles of varying durations and different “instrumentations”, i. e., the distribution of pitches over the octaves. Several processes like lowering the notes and dynamics, diminishing the duration cycles and changing the “instrumentation” interact with ideas of game-like fluctuations, ramifications and the aesthetic idea of wellformedness. There are several points during the course of the composition where the composer has to decide how he wants to change the rules. Whereas the over-all formal plan obviously was conceived graphically or spatially (thus being connected to Ligeti’s synaesthesia), the developmental character of the music stands somewhere between architectonic form and process form. This article develops an analysis in relation to game theory that tries to synchronize the conception with the creative process as far as it can be reconstructed from the score. Even though at first glance Ligeti’s compositional method seems to be axiomatic and mathematic, it contains many playful elements including “trial and error”. “I do not have a computer, not even a pocket calculator”, was one of his catch phrases – another one, as a consequence: “I always had to start anew because it didn’t work.” This way of working with game-like rules is significant and shows that Ligeti’s music cannot be thoroughly understood in the tradition of serial or process-like music; an important connection leads to Béla Bartók whose conceptions often lead in similar directions.

A flexible employee recruitment and compensation model: A bi-level optimization approach

The growing practice of flexible work following the COVID-19 pandemic is likely to have a significant impact on management and human resource (HR) practices. In this paper, we propose a novel bi-level mathematical programming model that can serve as a decision support tool for firms in real-life settings to improve recruitment and compensation decisions associated with hybrid and flexible work plans. The proposed model is composed of two levels: the first level reflects the company’s goal of maximizing profitability by offering competitive salaries to candidates. The second level reflects the candidate’s goal of minimizing the gap between their desired salary and the perceived benefits of a preferred flexible plan. We show that the model provides an exact solution based on a mixed integer formulation and present a computational analysis based on changing candidate behaviors in response to the firm’s strategy, thus demonstrate how the problem’s parameters influence the decision policy. Our proposed model leads to efficient managerial practices, compared to conventional models that utilize a single non-flexible plan. Results indicate that introducing a flexible work plan leads to an improvement of up to 59 percent in the firm’s profitability. We apply the optimal solution of the bi-level model to a real-world case study of a company recruiting software engineers. Results demonstrate the applicability of the optimal solution to a real-world dataset. This paper advances knowledge by proposing a novel bi-level model for effective recruitment and compensation decisions in real-world flexible workforce settings.

Values, emancipation, and the role of knowledge in tourism education. A critical realist perspective

ABSTRACT Values are important in education and their role in university studies is central in tourism teaching as well. How values are communicated to students is an important aspect of our axiological approach. In order to promote a fruitful approach to values in the students, this conceptual paper discusses the role of theoretical knowledge in achieving empowerment for the students based on the tenets of critical realism and on Gramsci’s philosophy. As students acquire disciplinary theoretical knowledge, they also develop the tools to make ethical evaluations. Knowledge is meant as the best possible understanding that we have of the world at the moment and it is always possible to achieve a better explanation of a phenomenon. Through an approach based on theoretical knowledge integrated with other creative ways to teach, the students can develop an ethical sensitivity and a flexible set of skills for both the workplace and academia.

Heavy-duty truck platooning on hilly terrain highways: Methods for assessment and improvement

Platooning heavy-duty trucks is a proven method to reduce fuel consumption on flat ground, but a significant portion of the U.S. highway system covers hilly terrain. The effort described in this paper uses experimentally gathered single truck data from a route with hilly terrain and an experimentally-validated two-truck platoon simulation framework to analyze control methods for effective platooning on hilly terrain. Specifically, this effort investigates two platoon control aspects: (1) the lead truck’s vehicle speed control and (2) the platoon’s transmission shifting algorithm. Three different types of lead truck speed control strategies are analyzed using the validated platoon model. Two are commercially available cruise control strategies – conventional constant set speed cruise control (CCC) and flexible set speed cruise control (FCC). The third lead truck speed control strategy was developed by the authors in this paper. It uses look-ahead grade information for an entire route to create an energy-optimal speed profile for the lead truck which is called long-horizon predictive cruise control (LHPCC). Then, a two-truck platoon transmission shifting strategy that coordinates the shift events – Simultaneous Shifting (SS) – is introduced and compared to a commercially available shifting strategy using the validated platoon model. This shifting strategy demonstrates further improvements in the platoon performance by improving the platoon gap control. A summary of these simulations demonstrates that the performance of the platoon can be improved by three methods: adding speed flexibility to the lead truck speed control method, using look-ahead road grade information to generate energy-optimal speed targets for the lead truck, and coordinating the timing of the transmission shifts for each truck in the platoon.

A short-term electric load forecast method based on improved sequence-to-sequence GRU with adaptive temporal dependence

Accurate and efficient short-term electric load forecast (STLF) is essential for power systems’ reliable and economical operation. The temporal dependence of actual load exhibits dynamics and variability, while the current STLF methods often neglect it, resulting in poor robustness. This paper proposes an STLF method based on an improved sequence-to-sequence gated recurrent unit network (S2S-IGRU) to solve this problem, with a three-step adaptive framework for following dynamic temporal dependency pattern. In the first step, the maximum duration of the temporal dependence is estimated empirically based on the autocorrelation coefficient. It is set as the initial upper limit of the window length to construct the time series samples. In addition, a sine–cosine cycle encoder is used for the periodic categorical inputs. In the second step, an S2S-IGRU initialized with a Chrono initializer is used to forecast the load in upcoming days, which enables a flexible setting of the memory retention time. In the third step, the prediction error changing curve with window length is selected as a fine-tuning criterion to obtain the optimal length of the time window. The results from two real examples justify the proposed method of significantly improving forecast accuracy and adaptability on varied forecast horizons and load datasets with different temporal dynamic patterns.

Enrolment in clinical research at UCLH and geographically distributed indices of deprivation

Healthcare should be judged by its equity as well as its quality. Both aspects depend not only on the characteristics of service delivery but also on the research and innovation that ultimately shape them. Conducting a fully-inclusive evaluation of the relationship between enrolment in primary research studies at University College London Hospitals NHS Trust and indices of deprivation, here we demonstrate a quantitative approach to evaluating equity in healthcare research and innovation. We surveyed the geographical locations, aggregated into Lower Layer Super Output Areas (LSOAs), of all England-resident UCLH patients registered as enrolled in primary clinical research studies. We compared the distributions of ten established indices of deprivation across enrolled and non-enrolled areas within Greater London and within a distance-matched subset across England. Bayesian Poisson regression models were used to examine the relation between deprivation and the volume of enrolment standardized by population density and local disease prevalence. A total of 54593 enrolments covered 4401 LSOAs in Greater London and 10150 in England, revealing wide geographical reach. The distributions of deprivation indices were similar between enrolled and non-enrolled areas, exhibiting median differences from 0.26% to 8.73%. Across Greater London, enrolled areas were significantly more deprived on most indices, including the Index of Multiple Deprivation; across England, a more balanced relationship to deprivation emerged. Regression analyses of enrolment volumes yielded weak biases, in favour of greater deprivation for most indices, with little modulation by local disease prevalence. Primary clinical research at UCLH has wide geographical reach. Areas with enrolled patients show similar distributions of established indices of deprivation to those without, both within Greater London, and across distance-matched areas of England. We illustrate a robust approach to quantifying an important aspect of equity in clinical research and provide a flexible set of tools for replicating it across other institutions.

Exploring the impact of the COVID-19 pandemic on approaches to innovation in the consulting industry: a grounded theory pilot study

PurposeThere is a significant pressure on consulting businesses to produce innovative solutions and to assist their clients in producing innovative solutions for their organizational problems as well. In addition to that challenging need to innovate for survival and competition, as other contemporary firms, consultancies must face the global changes brought by the outbreak of the coronavirus infection since 2019. This qualitative pilot study aimed at exploring the impact of the coronavirus disease 2019 (COVID-19) pandemic on the approaches to innovation in the consulting industry.Design/methodology/approachTriggered from the literature gap on approaches to innovation in consultancies during the unprecedented COVID-19 pandemic, a grounded theory approach was used to generate a theoretical explanation of how the COVID-19 is affecting the strategies and approaches of businesses in harnessing innovation opportunities from the perspectives of four professionals from an information technology (IT) consultancy in the USA.FindingsThe findings of this pilot study showed that organizational leaders' increased responsiveness, a Job-To-Be-Done strategy, organizational support and team adaption are the keys to harvesting dynamic capabilities for better competition, even during global environmental changes.Practical implicationsThis implies that managers remain the main actors in a firm's efforts to harvest dynamic capabilities. Innovation strategists, business leaders and policymakers can confidently work together to implement novel and flexible work settings that integrate both social and economic advancements.Originality/valueTheoretical implications support the sustainable innovation strategy concepts and the Job-To-Be-Done theory. Finally, the substantive theory from this pilot study lays the ground for future research on approaches to innovation in the consulting industry.

Tetrel Bonds between Phenyltrifluorosilane and Dimethyl Sulfoxide: Influence of Basis Sets, Substitution and Competition.

Ab initio calculations have been performed for the complexes of DMSO and phenyltrifluorosilane (PTS) and its derivatives with a substituent of NH3, OCH3, CH3, OH, F, CHO, CN, NO2, and SO3H. It is necessary to use sufficiently flexible basis sets, such as aug’-cc-pVTZ, to get reliable results for the Si···O tetrel bonds. The tetrel bond in these complexes has been characterized in views of geometries, interaction energies, orbital interactions and topological parameters. The electron-donating group in PTS weakens this interaction and the electron-withdrawing group prominently strengthens it to the point where it exceeds that of the majority of hydrogen bonds. The largest interaction energy occurs in the p-HO3S-PhSiF3···DMSO complex, amounting to −122 kJ/mol. The strong Si···O tetrel bond depends to a large extent on the charge transfer from the O lone pair into the empty p orbital of Si, although it has a dominant electrostatic character. For the PTS derivatives of NH2, OH, CHO and NO2, the hydrogen bonded complex is favorable to the tetrel bonded complex for the NH2 and OH derivatives, while the σ-hole interaction prefers the π-hole interaction for the CHO and NO2 derivatives.

Digital Twin Integrated Reinforced Learning in Supply Chain and Logistics

Background: As the Internet of Things (IoT) has become more prevalent in recent years, digital twins have attracted a lot of attention. A digital twin is a virtual representation that replicates a physical object or process over a period of time. These tools directly assist in reducing the manufacturing and supply chain lead time to produce a lean, flexible, and smart production and supply chain setting. Recently, reinforced machine learning has been introduced in production and logistics systems to build prescriptive decision support platforms to create a combination of lean, smart, and agile production setup. Therefore, there is a need to cumulatively arrange and systematize the past research done in this area to get a better understanding of the current trend and future research directions from the perspective of Industry 4.0. Methods: Strict keyword selection, search strategy, and exclusion criteria were applied in the Scopus database (2010 to 2021) to systematize the literature. Results: The findings are snowballed as a systematic review and later the final data set has been conducted to understand the intensity and relevance of research work done in different subsections related to the context of the research agenda proposed. Conclusion: A framework for data-driven digital twin generation and reinforced learning has been proposed at the end of the paper along with a research paradigm.

Coronavirus 2019 work-from-home productivity of inpatient and infusion pharmacists at a comprehensive cancer center

PurposeTo evaluate inpatient and infusion pharmacist order verification productivity when working from home and to report their perceptions of a flexible workplace setting. MethodsOrder verification data were pulled from the electronic medical record from April 27, 2020, to June 30, 2020, matched to the pharmacist schedule on the basis of work setting and reported as average orders verified per day. Pharmacist perceptions were gathered via a survey to evaluate practice setting background, workplace setting preference, and perceived changes in workflow and their productivity. ResultsThere was an overall increase in order verification productivity when working from home. Inpatient pharmacists, on average, verified 152 orders per day from home and 133 orders per day onsite. Infusion pharmacists, on average, verified 144 orders per day working from home and 117 orders per day working onsite. Fifty-nine percent of pharmacists reported preferring the mix of onsite and home workplace setting and noted little change in workflow. In addition, 57% of the pharmacists perceived themselves as being more productive, 32% as maintaining the same level of productivity, and 10% felt that they are less productive when working from home. The order verification data showed a greater increase in productivity for infusion shifts worked from home than inpatient shifts. ConclusionThe coronavirus 2019 pandemic prompted pharmacy departments to re-evaluate their ability to provide an option for a flexible workplace for pharmacists. Our study demonstrates that pharmacists, on average, verified more orders when working from home, and they also perceive themselves as being more productive. The results of this study support long-term applicability of a flexible work schedule for inpatient and infusion pharmacists.

ECG-Based Identification of Sudden Cardiac Death through Sparse Representations.

Sudden Cardiac Death (SCD) is an unexpected sudden death due to a loss of heart function and represents more than 50% of the deaths from cardiovascular diseases. Since cardiovascular problems change the features in the electrical signal of the heart, if significant changes are found with respect to a reference signal (healthy), then it is possible to indicate in advance a possible SCD occurrence. This work proposes SCD identification using Electrocardiogram (ECG) signals and a sparse representation technique. Moreover, the use of fixed feature ranking is avoided by considering a dictionary as a flexible set of features where each sparse representation could be seen as a dynamic feature extraction process. In this way, the involved features may differ within the dictionary’s margin of similarity, which is better-suited to the large number of variations that an ECG signal contains. The experiments were carried out using the ECG signals from the MIT/BIH-SCDH and the MIT/BIH-NSR databases. The results show that it is possible to achieve a detection 30 min before the SCD event occurs, reaching an an accuracy of 95.3% under the common scheme, and 80.5% under the proposed multi-class scheme, thus being suitable for detecting a SCD episode in advance.

Leadership for Family and Community Engagement: A Qualitative Policy Analysis of State Principal Evaluation Processes

Purpose: The primary purpose of this policy analysis is to examine how states changed their principal performance evaluation systems since the passage of Every Student Succeeds Act in 2015. In particular, we focus on whether states have capitalized on the flexible policy landscape to make space for meaningful family and community engagement (FCE) in assessing principals’ effectiveness. Research Methods: This study uses document analysis to review the structure of principal evaluation systems in all 50 states and selects 17 revised systems for a deeper review of their approach to leadership for partnering with families and communities. Findings: A plurality of states have not substantively revised their evaluation systems. Several of the revised systems narrowly focused on instructional leadership and student achievement measures and were thus unsupportive of meaningful FCE and federal policy aims for schools to work in partnership with family and community stakeholders. The principal evaluation systems most supportive of authentic family and community engagement allowed for flexible goal setting and explicitly encouraged the use of stakeholder feedback as evidence of principals’ effectiveness. Implications for Research and Policy: The authors discuss the implications of the results in terms of 1.) expanding definitions of educational leadership to include tenets of authentic FCE, 2.) creating coherent yet compendious systems for school improvement, and 3.) planning for and implementing a developmental approach to the evaluation of school leaders.

Semiparametric maximum likelihood probability density estimation.

A comprehensive methodology for semiparametric probability density estimation is introduced and explored. The probability density is modelled by sequences of mostly regular or steep exponential families generated by flexible sets of basis functions, possibly including boundary terms. Parameters are estimated by global maximum likelihood without any roughness penalty. A statistically orthogonal formulation of the inference problem and a numerically stable and fast convex optimization algorithm for its solution are presented. Automatic model selection over the type and number of basis functions is performed with the Bayesian information criterion. The methodology can naturally be applied to densities supported on bounded, infinite or semi-infinite domains without boundary bias. Relationships to the truncated moment problem and the moment-constrained maximum entropy principle are discussed and a new theorem on the existence of solutions is contributed. The new technique compares very favourably to kernel density estimation, the diffusion estimator, finite mixture models and local likelihood density estimation across a diverse range of simulation and observation data sets. The semiparametric estimator combines a very small mean integrated squared error with a high degree of smoothness which allows for a robust and reliable detection of the modality of the probability density in terms of the number of modes and bumps.

The role of selective attention in the positivity offset: Evidence from event related potentials.

Some research suggests that positive and negative valence stimuli may be processed differently. For example, negative material may capture and hold attention more readily than equally arousing positive material. This is called the negativity bias, and it has been observed as both behavioural and electroencephalographic (EEG) effects. Consequently, it has been attributed to both automatic and elaborative processes. However, at the lowest levels of arousal, faster reaction times and stronger EEG responses to positive material have been observed. This is called the positivity offset, and the underlying cognitive mechanism is less understood. To study the role of selective attention in the positivity offset, participants completed a negative affective priming (NAP) task modified to dissociate priming for positive and negative words. The task required participants to indicate the valence of a target word, while simultaneously ignoring a distractor. In experiment 1, a behavioural facilitation effect (faster response time) was observed for positive words, in stark contrast to the original NAP task. These results were congruent with a previously reported general categorization advantage for positive material. In experiment 2, participants performed the task while EEG was recorded. In additional to replicating the behavioural results from experiment 1, positive words elicited a larger Late Positive Potential (LPP) component on ignored repetition relative to control trials. Surprisingly, negative words elicited a larger LPP than positive words on control trials. These results suggest that the positivity offset may reflect a greater sensitivity to priming effects due to a more flexible attentional set.

Improvement of iron ore concentrate quality by gravity and magnetic separation at SSGPO JSC

The recent trends in the global iron ore industry are going to become the governing factors of technology and economy in iron ore concentration and metallurgy in the nearest future. As per the modern trends in iron ore concentration, and in line with the global market requirements, SSGPO JSC is to improve the iron ore concentrate quality up to the level of 67–68 % Fetotal. One of the ways of meeting the goal is introduction of stage-wise concentration using gravity and magnetic separation. The article presents the commercial test results of gravity and magnetic separator MGS-2.0 at the operating processing plant of SSGPO JSC. Efficiency of the separator is analyzed as function of the technology and equipment parameters. The proposed stage-wise marketable concentration can ensure improved product quality and reduce operating costs, which is beneficial for the production profitability. Adjustability of circulating load in milling cycle by varying the screen size and flexible setting of gravity and magnetic separation parameters ensures much better control as compared with PBM model separators, and enables production of an iron ore concentrate of the required quality. Introduction of the gravity and magnetic separation technology at SSPGO JSC is a promising way of stimulating complex magnetic ore concentration efficient scenarios of which have been the subject of discussion of scientists and practitioners in mining and processing for the last decades.

Uniformly perfect and hereditarily non uniformly perfect analytic and conformal non-autonomous attractor sets

Conditions are given which imply that certain non-autonomous analytic iterated function systems (NIFSs) in the complex plane have uniformly perfect attractor sets, while other conditions imply the attractor is pointwise thin and thus hereditarily non uniformly perfect. Examples are given to illustrate the main theorems, as well as to indicate how they generalize other results. Examples are also given to illustrate how possible generalizations of corresponding results for autonomous IFS's do not hold in general in this more flexible setting. Further, applications to non-autonomous Julia sets are given. Lastly, since our definition of NIFS is in some ways more general than others found in the literature, a careful analysis is given to show when certain familiar relationships still hold, along with detailed examples showing when other relationships do not hold.

Large-scale data analysis for robotic yeast one-hybrid platforms and multi-disciplinary studies using GateMultiplex

BackgroundYeast one-hybrid (Y1H) is a common technique for identifying DNA-protein interactions, and robotic platforms have been developed for high-throughput analyses to unravel the gene regulatory networks in many organisms. Use of these high-throughput techniques has led to the generation of increasingly large datasets, and several software packages have been developed to analyze such data. We previously established the currently most efficient Y1H system, meiosis-directed Y1H; however, the available software tools were not designed for processing the additional parameters suggested by meiosis-directed Y1H to avoid false positives and required programming skills for operation.ResultsWe developed a new tool named GateMultiplex with high computing performance using C++. GateMultiplex incorporated a graphical user interface (GUI), which allows the operation without any programming skills. Flexible parameter options were designed for multiple experimental purposes to enable the application of GateMultiplex even beyond Y1H platforms. We further demonstrated the data analysis from other three fields using GateMultiplex, the identification of lead compounds in preclinical cancer drug discovery, the crop line selection in precision agriculture, and the ocean pollution detection from deep-sea fishery.ConclusionsThe user-friendly GUI, fast C++ computing speed, flexible parameter setting, and applicability of GateMultiplex facilitate the feasibility of large-scale data analysis in life science fields.