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Background The bleach-boosting capability of xylanases is well-known. The use of xylanase pre-treatment before the application of chemical bleach has multiple advantages including (i) lesser use of polluting chemicals of the traditional bleaching process; (ii) less damage to the cellulosic fbers, therefore better recyclability; and (iii) better brightness of chemical bleach. The major impediment in the application is the availability of commercial enzymes that are active at the elevated temperature and pH that exist during the industrial pulping process. In the present paper, xylanase having suitability for application in deinking is reported. Results The xylanase used showed high deinking potential. Optimal deinking was obtained at the xylanase dosing of 20U/g of the dried pulp at 60°C for a treatment time of 1h. It could bring about a 50% reduction in the usage of chemical bleach that was applied after xylanase pre-treatment. The comparison of FTIR spectra showed changes in intensity without signifcant changes in the functional group signatures implying that there is negligible damage to the fber strength in the xylanase pre-treatment process as compared to the chemical bleach process. Conclusion The xylanase used in this study was efective in deinking paper pulp and can be used for bio-bleaching of recycled paper. [ABSTRACT FROM AUTHOR]

Key summary points: Aim: To summarize the literature on medication review and deprescribing in older adults, and formulate recommendations to improve prescribing medications in older, multimorbid adults with polypharmacy. Findings: Current evidence demonstrates a need for a multifaceted and wide-scale change in education, guidelines, research, advocacy, and policy to improve the management of polypharmacy in older people, and to make deprescribing part of routine care for the ageing generations to come. Message: By implementing the recommendations in this paper, healthcare professionals will be better prepared to address the challenges associated with an ageing population and provide high-quality care to older patients with complex health and social care needs. Inappropriate polypharmacy is highly prevalent among older adults and presents a significant healthcare concern. Conducting medication reviews and implementing deprescribing strategies in multimorbid older adults with polypharmacy are an inherently complex and challenging task. Recognizing this, the Special Interest Group on Pharmacology of the European Geriatric Medicine Society has compiled evidence on medication review and deprescribing in older adults and has formulated recommendations to enhance appropriate prescribing practices. The current evidence supports the need for a comprehensive and widespread transformation in education, guidelines, research, advocacy, and policy to improve the management of polypharmacy in older individuals. Furthermore, incorporating deprescribing as a routine aspect of care for the ageing population is crucial. We emphasize the importance of involving geriatricians and experts in geriatric pharmacology in driving, and actively participating in this transformative process. By doing so, we can work towards achieving optimal medication use and enhancing the well-being of older adults in the generations to come. [ABSTRACT FROM AUTHOR]

Key summary points: Aim: The recent World Guidelines for Falls Prevention and Management provide several recommendations on how to prevent medication-related falls. Findings: Medication review and deprescribing are key interventions in falls prevention and should be structured, personalized, and patient-centered. Preferably, the medication review should be conducted as part of a comprehensive geriatric assessment. Message: Improved information sharing between various prescribers, deprescribing recommendations implemented in guidelines, and increased education and training for health care professionals are warranted to facilitate the deprescribing process. Falls prevention and management in older adults is a critical global challenge. One of the key risk factors for falls is the use of certain medications. Therefore, to prevent medication-related falls, the following is recommended in the recent World Guidelines for Falls Prevention and Management: (1) assess for fall history and the risk of falls before prescribing potential fall-risk-increasing drugs (FRIDs), (2) use a validated, structured screening and assessment tool to identify FRIDs when performing a medication review, (3) include medication review and appropriate deprescribing of FRIDs as a part of the multifactorial falls prevention intervention, and (4) in long-term care residents, if multifactorial intervention cannot be conducted due to limited resources, the falls prevention strategy should still always include deprescribing of FRIDs. In the present statement paper, the working group on medication-related falls of the World Guidelines for Falls Prevention and Management, in collaboration with the European Geriatric Medicine Society (EuGMS) Task and Finish group on FRIDs, outlines its position on how to implement and execute these recommendations in clinical practice. Preferably, the medication review should be conducted as part of a comprehensive geriatric assessment to produce a personalized and patient-centered assessment. Furthermore, the major pitfall of the published intervention studies so far is the suboptimal implementation of medication review and deprescribing. For the future, it is important to focus on gaining which elements determine successful implementation and apply the concepts of implementation science to decrease the gap between research and practice. [ABSTRACT FROM AUTHOR]

This paper presents the case of an adjunct university professor to illustrate the dilemma of using artificial intelligence (AI) technology to grade student papers. The hypothetical case discusses the benefits of using a commercial AI service to grade student papers—including discretion, convenience, pedagogical merits of consistent feedback for students, and advances made in the field that yield high-quality work—all of which are achieved quickly. Arguments against using AI to grade student papers involve cost, privacy, legality, and ethics. The paper discusses career implications for faculty members in both situations and concludes with implications for researchers within the discourse on academic integrity. [ABSTRACT FROM AUTHOR]

Background: Lignocellulosic biomasses produced from agriculture and forest-based industries are the cheapest or negative-cost biomass with a great potential for biotransformation to value-added bioproducts. Paper mill sludge, an important lignocellulosic biomass creates an environmental threat, which requires financial input for disposal. Thus, this study was aimed to isolate a novel bacterial strain capable of degrading cellulosic biomass including paper mill sludge to produce reducing sugar and other value-added bioproducts. Results: A novel bacterial strain Arthrobacter woluwensis TDS9 isolated from the soil was screened for its cellulolytic activity using carboxymethyl cellulose (CMC) as the sole carbon source. The incubation period, temperature, pH, carbon, and nitrogen sources are the most important factors ruling the CMCase and sugar productions of the strain A. woluwensis TDS9, and an alkaline pH (pH 8.0) led to enhanced sugar production up to 1100.09 μg/mL after 72 h of incubation at 25°C in a medium containing 1.5% CMC and 1.25% beef extract. The optimal conditions for maximum CMCase activity were defined, and the potassium ion boosted the CMCase activity up to 1.06 U/mL when the enzymatic reaction was performed for 30 min at 50°C and pH 8 using CMC as a substrate. Moreover, the strain A. woluwensis TDS9 produced 433.33 μg/mL reducing sugar from 1% pretreated paper mill sludge. Significant alterations in the structural arrangement of cellulosic fiber of paper mill sludge observed under microscope after each step of chemical treatment process helped for loosening the cellulose fibers and increased the saccharification for enzymatic hydrolysis. Endoglucanase IV (33 KDa) and beta-glucosidase II (53 KDa) were identified in crude enzyme based on the zymogram analysis and substrate specificity. Conclusions: The research has for the first time proved that this A. woluwensis TDS9 strain can efficiently convert cellulose. Therefore, the strain TDS9 could be a potential candidate for cellulase production in an industrial biotransformation process of paper mill sludge to produce reducing sugar. This sugar stream can be further used as a substrate to produce biofuels and other organic acids using another microorganism, which represents a greener alternative to add value to the paper production helping paper mill industries. [ABSTRACT FROM AUTHOR]

Dementia Day Care Centres (DDCCs) are defined as services providing care and rehabilitation to people with dementia associated with behavioural and psychological symptoms (BPSD) in a semi-residential setting. According to available evidence, DDCCs may decrease BPSD, depressive symptoms and caregiver burden. The present position paper reports a consensus of Italian experts of different disciplines regarding DDCCs and includes recommendations about architectural features, requirements of personnel, psychosocial interventions, management of psychoactive drug treatment, prevention and care of geriatric syndromes, and support to family caregivers. DDCCs architectural features should follow specific criteria and address specific needs of people with dementia, supporting independence, safety, and comfort. Staffing should be adequate in size and competence and should be able to implement psychosocial interventions, especially focused on BPSD. Individualized care plan should include prevention and treatment of geriatric syndromes, a targeted vaccination plan for infectious diseases including COVID-19, and adjustment of psychotropic drug treatment, all in cooperation with the general practitioner. Informal caregivers should be involved in the focus of intervention, with the aim of reducing assistance burden and promoting the adaptation to the ever-changing relationship with the patient. [ABSTRACT FROM AUTHOR]

Key summary points: Aim: To describe the evidence on the usefulness of a Comprehensive Geriatric Assessment (CGA)-based approach during the COVID-19 pandemic. Findings: The multidimensional, CGA-based approach allows better identification of individual risk profiles and frailty status of infected, recovered but with a post-COVID-19 condition, and non-infected older adults. Message: Capturing older patients' needs through CGA may offer the possibility to guide clinical decision and implement personalized medicine. Purpose: The COVID-19 pandemic has been a dramatic trigger that has challenged the intrinsic capacity of older adults and of society. Due to the consequences for the older population worldwide, the Special Interest Group on Comprehensive Geriatric Assessment (CGA) of the European Geriatric Medicine Society (EuGMS) took the initiative of collecting evidence on the usefulness of the CGA-based multidimensional approach to older people during the COVID-19 pandemic. Methods: A narrative review of the most relevant articles published between January 2020 and November 2022 that focused on the multidimensional assessment of older adults during the COVID-19 pandemic. Results: Current evidence supports the critical role of the multidimensional approach to identify older adults hospitalized with COVID-19 at higher risk of longer hospitalization, functional decline, and short-term mortality. This approach appears to also be pivotal for the adequate stratification and management of the post-COVID condition as well as for the adoption of preventive measures (e.g., vaccinations, healthy lifestyle) among non-infected individuals. Conclusion: Collecting information on multiple health domains (e.g., functional, cognitive, nutritional, social status, mobility, comorbidities, and polypharmacy) provides a better understanding of the intrinsic capacities and resilience of older adults affected by SARS-CoV-2 infection. The EuGMS SIG on CGA endorses the adoption of the multidimensional approach to guide the clinical management of older adults during the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Background: Visual analogue scales (VASs) are used in a variety of patient-, observer- and clinician-reported outcome measures. While typically included in measures originally developed for pen-and-paper completion, a greater number of clinical trials currently use electronic approaches to their collection. This leads researchers to question whether the measurement properties of the scale have been conserved during the migration to an electronic format, particularly because electronic formats often use a different scale length than the 100 mm paper standard. Methods: We performed a review of published studies investigating the measurement comparability of paper and electronic formats of the VAS. Results: Our literature search yielded 26 studies published between 1997 and 2018 that reported comparison of paper and electronic formats using the VAS. After excluding 2 publications, 23 of the remaining 24 studies included in this review reported electronic formats of the VAS (eVAS) and paper formats (pVAS) to be equivalent. A further study concluded that eVAS and pVAS were both acceptable but should not be interchanged. eVAS length varied from 21 to 200 mm, indicating that 100 mm length is not a requirement. Conclusions: The literature supports the hypothesis that eVAS and pVAS provide comparable results regardless of the VAS length. When implementing a VAS on a screen-based electronic mode, we recommend following industry best practices for faithful migration to minimise the likelihood of non-comparability with pVAS. [ABSTRACT FROM AUTHOR]

Background and objective: The number of people suffering from dementia is increasing worldwide and so is the need for reliable and economical diagnostic instruments. Therefore, the aim of this study was to compare the processing times of the neuropsychological tests Trail Making Tests A and B (TMT-A/B) and Color-Word Interference Test (CWIT), which were performed in both digital and paper versions. Methods: The pilot study was conducted among 50 healthy participants (age 65–83 years) using a randomized crossover design. The correlations and differences in the individual processing times of the two test versions were statistically analyzed. Further research questions concerned the influence of the individual usage of technology and the technology commitment of participants as well as the influence of the assessed usability on participants' performance. Results: Between the two versions (paper-based vs. digital) statistically significant correlations were found in all tests, e.g., TMT-A r(48) = 0.63, p < 0.01; TMT-B rs(48) = 0.77, p < 0.001). The mean value comparison showed statistically significant differences, e.g., interference table (CWIT) t(49) = 11.24, p < 0.01). Correlations with medium effect were found between the differences in processing times and the individual usage of computer (e.g., rs(48) = − 0.31) and smartphone (rs(48) = − 0.29) and between the processing times of the TMT-B and the usability (rs(48) = 0.29). Conclusions: The high correlations between the test procedures appear promising. However, the differences found in the processing times of the two test versions require validation and standardization of digitized test procedures before they can be used in practice. [ABSTRACT FROM AUTHOR]

Bacteria often cause infections, and we take antibiotics to help us recover. Antibiotics are like magic pills that have saved millions of lives. However, the overuse of antibiotics is now making bacteria evolve fast and evade these antibiotics. A few bacteria like the purple one in the petri plate (Figure 1) have evolved a way to dodge and not get killed by one particular kind of antibiotic. The day might come soon when not a single antibiotic would work, and we could die of even tiny paper cuts. In this article, we discuss what antibiotics are, how they target bacteria, and why bacteria are suddenly becoming resistant to antibiotics. We include a list of ten points that each of us must follow and a pledge for everyone to take, to help stop the spread of antibiotic resistance. A small questionnaire is included that we would like you all to answer. Together we can win the battle against antibiotic resistance. [ABSTRACT FROM AUTHOR]

The complexity and inter-connectedness of operating in a global world for drug product supply has become an undeniable reality, further underscored by the COVID-19 pandemic. For Post-Approval Changes (PACs) that are an inevitable part of a product's commercial life, the impact of the growing global regulatory complexity and related drug shortages has brought the GlobalPACManagement System to an inflection point in particular for companies that have their products marketed in many countries. This paper illustrates through data analyzed for the first time from 145,000 + PACs for 156 countries, collected by 18 global pharma companies over a 3-year period (2019–2021), how severe the problem of global regulatory complexity is. Only PACs requiring national regulatory agency (NRA) approval prior to implementation were included in the data set. 1 of the 156 country NRAs approved all submitted PACs within a period of 6 months. The 6-month timeline was chosen because it is the recommended review timeline for major changes in the WHO guidance for vaccines and biotherapeutic products. 10 out of the 156 (6%) countries had no more than 10% of the PACs reviewed and approved in > 6 months. In 33 (22%) countries more than half of the PACs took > 6 months for approval. It is rare that the same PAC is approved globally within 6 months as individual NRAs take from a few months to years (in some cases > 5 years) for their review. The global PAC management complexity has steadily grown over the past 20 years. Attempts thus far to solve this problem have not made any meaningful difference. Senior leaders and decision-makers across the interdependent components of the complex Global PAC Management System (industry and regulators) must come together and collaboratively manage the problem holistically with the objective of ensuring global drug product availability instead of continuing with distinct stakeholder or country-focused solutions, which can tend to worsen the problem. In this paper, the Chief Quality Officers (CQOs) from 18 of the largest innovator pharma companies (see Acknowledgements) are speaking with One-Voice-of-Quality for PACs (1VQ for PACs Initiative). They are recommending a set of 8 approaches to activate a holistic transformation of the Global PAC Management System. This article presents their view on the problem of global regulatory complexity for managing PACs, it's impact on continual improvement and the risk to drug product supply, as well as approaches that can help alleviate the problem. [ABSTRACT FROM AUTHOR]

Regulating the surface instability of thin film/substrate structures has been successfully applied to prepare new ductile electronic devices. However, such electronic devices need to be subjected to external loads during operation, which can easily induce delamination of the thin-film electronic device from the substrate. This study aims to investigate the instability characteristics of hard films on flexible substrate surfaces from theoretical analysis and numerical simulation perspectives. Considering finite-thickness substrates, this paper establishes theoretical models for pure bending, bent wrinkle, partial delamination, and total delamination buckling of film/substrate structures based on the nonlinear Euler–Bernoulli beam theory and the principle of minimum energy; then the effects of material and geometric parameters of the structure, interfacial adhesion strength, and pre-strain on the evolutionary path of the four patterns are discussed. The study results show that: the greater Young's modulus of the substrate is, the larger the parameter region where partial delamination of the film/substrate structure occurs, and the smaller the parameter region where bent wrinkle occurs. By varying Young's modulus, thickness of the film and substrate, interfacial adhesion coefficient, and pre-strain, the buckling pattern of the structure can be predicted and regulated. The parametric design intervals for each pattern are summarized in the phase diagram. The results of this paper provide theoretical support for the design and reliability evaluation of flexible electronic devices. [ABSTRACT FROM AUTHOR]

In this paper, a model predictive control scheme is developed for networked interval type-2 (IT-2) Takagi–Sugeno (T–S) fuzzy systems. To prevent the excessive use of bandwidth, the controller is designed in an event-trigger manner. However, the event conditions often require the transmission of all system states, imposing a substantial demand on network bandwidth; on the other hand, they are subject to network delay and packet loss. For this reason, in the existing approaches, event-triggered mechanisms primarily deployed in close proximity to the plant, or observer-based structures are used to enhance flexibility for implementing the controller. However, a common limitation in all these solutions is the assumption of network links being ideal, or at the very least, not accounting for all network-related limitations. The occurrence of faults is also an inevitable factor that has been overlooked in most related methods. To resolve this issue, a more comprehensive framework for event-triggered controllers is proposed in this paper in which an adaptive fuzzy observer is embedded, and the effects due to delay and packet loss are included in this observer. In addition, by developing an adaptive fault estimator and the introduction of a compensator term into the observer and controller formulations, a fault-tolerant performance of the event-triggered mechanism along with the controller is provided. These features enable the possibility of implementing the event-triggered mechanism next to the controller and at any desired distance from the plant, which resolves a serious concern in this area. Another important challenge considered in this work is ensuring the optimal performance of the controller in the entire prediction horizon. Also, the stochastic stability of the closed-loop system is proved such that defined H 2 and H ∞ performance indices are satisfied. Finally, the proposed control approach is evaluated using numerical and practical examples. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of feedback control for a class of affine T–S fuzzy models using piece-wise Lyapunov functions. Although a large number of works on the issue have been published, several crucial problems still remain open. First, the paper shows what problems arise when using the affine T–S fuzzy model to design a controller, and in turn by employing the S-procedure, what kind of quadratic inequalities are required to help solve the resulting LMIs. It turns out that by partitioning the state space into certain cells based on the information of the antecedents of fuzzy rules, the required quadratic inequalities can be formularised. Taking advantage of the cell partition, a fuzzy controller is proposed using piece-wise Lyapunov functions, in which ensuing problems such as continuity functions used in the piece-wise Lyapunov functions and control input chattering also are addressed. Finally, examples are provided to illustrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Due to the significant gap between demand and supply of electricity, power utility companies employ rolling blackouts, in which the power supply to different regions is cut-off periodically for a specified duration. However, this causes increased user inconvenience as consumers are left without power; also, a large undesirable blackout may occur if the circuit breakers are not opened in time. To solve this problem, this paper has developed a more pragmatic approach in which a power threshold limit is imposed on households during times of deficit power supply. This paper presents five algorithms designed to allocate load thresholds to households in a fair manner. Some of these algorithms perform the worst (high violations) in some time slots and best (minimal violations) in other slots, but none guarantees minimal mean violation across all the time slots. In this regard, this paper has also developed a novel optimal algorithm that ensures a minimal violation percentage of the allotted thresholds across all time slots in all the households of a neighbourhood. It also employs multiple heuristics for threshold allocation, thereby preventing household starvation. The algorithms are evaluated on a real-world dataset. Its mean violation across all the houses goes as low as nearly 45% and is minimum across all the time slots. It performs all the algorithms used for power limit distribution. This result demonstrates the effectiveness of the developed technique in the implementation of the brownout scheme in practise. [ABSTRACT FROM AUTHOR]

This paper presents a new robust control structure to control a 3-degree-of-freedom (3-DoF) helicopter in the presence of uncertainties, disturbance and actuators saturation. The 3-DoF helicopter is an underactuated system where only two DoFs can be fully controlled, so elevation and pitching motions are considered in this paper. Robust control methods conventionally generate control signals with high amplitude to suppress model uncertainties. Nonetheless, the practical actuators might not be able to supply such control efforts, causing actuator saturation. The actuator saturation phenomenon highly affects the motion control performance of the system and even can cause instability. To address this issue in this paper, firstly a smooth prevention function is utilized as an approximation of the practical actuator saturation, limiting the input torque/force in a prescribed range. However, to avoid violating the stability of the system by a prevention function, it should be considered in the dynamic model of the system, leading to a non-affine structure. Hence, the problem of controlling a non-affine system is addressed by proposing a new third-order dynamic model, as well as a robust control scheme. In this approach, a backstepping control is utilized, equipped with an adaptive radial basis function neural network to estimate and compensate for the adverse terms. Finally, the effectiveness of the proposed scheme is evaluated through a detailed simulation study on a 3-DoF helicopter. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for jointly optimizing the sizing and operation of AC microgrids. The methodology is applied to the CAMPUSGRID microgrid, which is currently being developed at the State University of Campinas (UNICAMP) in Brazil. The distributed energy resources (DERs) considered in the study include a battery energy storage system (BESS), a dispatchable gas generator, and photovoltaic (PV) generation. The proposed energy management system (EMS) minimizes the costs associated with day-ahead operation of the DERs in an unbalanced three-phase AC microgrid. To develop the EMS as a mixed-integer linear programming (MILP) model, the MATLAB Link module of HOMER Pro and the AMPL API are used. Heuristic rules are also developed for contingency and post-contingency operations in case of unintentional disconnection from the main grid. The sizing simulations combine tariff regimes, contingencies, and dispatch strategies. The results demonstrate the influence of the tariff on the net present cost (NPC) and the importance of resilience in sizing DERs. Additionally, the proposed model is capable of assessing the impact of DERs on the electrical grid. Finally, the joint strategy proposed in this paper leads to a reduction in microgrid investment cost, improvement in voltage magnitude profile, and reduction in active power losses when compared to the default dispatch strategies of HOMER Pro. [ABSTRACT FROM AUTHOR]

When the regulatory requirements are converged or harmonized, the country-specific variance of countries is often reduced or omitted, and this facilitates the possibility of preparing a core dossier that caters to multiple countries. When such options of a core dossier are acceptable to multiple countries, the resource required to prepare the dossier and the time taken to prepare it is also reduced, thus eliminating resource constraints in supporting dossier planning and preparation and indirectly facilitating earlier submission in countries. In this paper, the authors have illustrated a process applied to standardize the dossier requirements amongst selected countries in Asia, producing an output of a core dossier that applies to four submission types amongst these countries. The core dossier adopts the International Council for Harmonization—Common Technical Dossier format as a reference. Main focus is the standardization of format and requirements within the Module 3 or Chemistry Manufacturing Controls sections of the dossier, which from the authors' organizational experience usually notes a higher variances and country-specific elements. Development of the dossier standardization process is due to an internal hurdle within the authors' organization, where global resource constraints and prioritizations of dossier preparation and compliance review process needed to be improved to facilitate earlier or near-simultaneously submissions in the majority of the Asia countries. The paper demonstrates an assessment of the dossier components and standardization to assemble a fit-for-purpose core dossier termed 'Asia Core Dossier' (ACD). ACD has been successfully implemented within the authors' organization to reduce country-specific requirements and facilitate earlier (fit for strategy) submissions in the selected Asia countries. The paper also discusses the tangible benefits of the authors' experiences from utilizing the ACD. Regulatory professionals in different organizations could reference the ACD as a template for preparing a simplified and efficient dossier and as a relevant component of Good Submission Practice (GSubP). [ABSTRACT FROM AUTHOR]

Aggregating various decision information provided by a group of decision makers (DMs) into an integrated one is essential for seeking the optimal solution. This paper aims to propose an effective method for information aggregation in group decision-making (GDM) in an uncertain environment. The approach introduces a family of incentive-induced cluster-based uncertain ordered weighted averaging (II-CUOWA) operators from the perspective of incentive management. Specifically, the II-CUOWA operator is first introduced, involving the definition, the clustering method of judgment information, the calculation method of position weights, and several mathematical properties. Then, the study delves into the exploration of generalized formulas for the II-CUOWA operator, as well as discussing special cases achievable by adjusting internal parameters. Finally, this paper outlines the aggregation process of II-CUOWA operators when addressing GDM problems, accompanied by a practical example illustrating its application and validity in employees' performance assessment. The results show that II-CUOWA operators not only highlight the distributed structure of decision information but also possess the capability to reward or penalize alternatives, thereby guiding their development by considering the manager's incentive preference. The proposed method enriches the methodology of GDM theory from a novel research perspective and provides a solution to practical GDM problems. [ABSTRACT FROM AUTHOR]

The T-spherical fuzzy set (T-SFS) has been widely used in multi-attribute decision-making (MADM) problems due to its powerful expression ability for uncertain information. The evidential reasoning (ER) method can avoid the information loss when aggregating the evaluation values of an alternative with regard to all attributes, which can prevent the decision result from being dominated by extreme evaluation values. Considering the significant advantage of the ER method in information aggregation, this paper develops a new aggregation model assimilating the T-SFSs and the ER method, which is called evidential T-spherical fuzzy MADM (ET-SFMADM). The ET-SFMADM can prevent information loss in the decision process, so as to obtain a correct ranking of the alternatives. Furthermore, this paper also proposes a T-spherical fuzzy cross entropy (T-SFCE) to determine the weights of attributes, which can reduce dependence on decision-makers. Finally, the viability of the ET-SFMADM is illustrated through a numerical example for the implementation effect of the hierarchical medical treatment system in different regions, and further the sensitivity analysis and comparison analysis with existing MADM methods are carried out to demonstrate the advantages of the proposed method. [ABSTRACT FROM AUTHOR]

This paper is concerned with the stabilization and event-triggered control for positive nonlinear systems in terms of Takagi–Sugeno (T–S) fuzzy models. By employing the unique positivity of positive systems, a new event-triggered mechanism is introduced to select necessary signals so that the communication resources can be saved effectively while guaranteeing the system performance. It is different from the traditional event-triggered mechanism that is designed in the quadratic form for general systems, the one adopted in this paper is in linear form which is beneficial to facilitate the stability analysis in terms of a linear copositive Lyapunov function. However, the tricky non-convex problem makes controller design extremely challenging. For handling this issue, the matrix decomposition technique plays a very important part in designing the feedback control law. Furthermore, improving the relaxation of the analysis results is another considerably vital but challenging issue. To break through this difficulty, an asynchronous premise re-construct method is presented to extract the information of membership functions (MFs), which is conducive to obtaining more relaxed stability and positivity analysis. Finally, the validity of this control strategy is illustrated by simulation examples. [ABSTRACT FROM AUTHOR]

The concomitants of order statistics (COS) is a variable associated with a bivariate sample when ordered with respect to the other variable. The distribution theory of COS is widely developed for various families of bivariate distributions. The COS have a wide variety of applications in different fields such as selection procedures, parameter estimation, ranked set sampling (RSS), etc. The notion of RSS in bivariate setup has been used to obtain improved estimates of parameters in many practical situations. Furthermore, many variations in the original idea of RSS have also been introduced. In this paper, we present a detail review of the families of bivariate distributions in view of the theory development of COS, the variations in RSS schemes and the use of RSS schemes in the estimation of parameters for different bivariate distributions. The shortfalls and advantages of RSS estimation are also summarised. The paper ends with some concluding remarks and possible future work in the area of RSS estimation. [ABSTRACT FROM AUTHOR]

With the rapid proliferation of IoT and Cloud networks and the corresponding number of devices, handling incoming requests has become a significant challenge. Task scheduling problems have emerged as a common concern, necessitating the exploration of new methods for request management. This paper proposes a novel approach called the Fuzzy Inverse Markov Data Envelopment Analysis Process (FIMDEAP). Our method combines the strengths of the Fuzzy Inverse Data Envelopment Analysis (FIDEA) and Fuzzy Markov Decision Process (FMDP) techniques to enable the efficient selection of physical and virtual machines while operating in a fuzzy mode. We represent data as triangular fuzzy numbers and employ the alpha-cut method to solve the proposed models. The paper provides a mathematical optimization model for the proposed method and presents a numerical example for illustration. Furthermore, we evaluate the performance of our method in a cloud environment through simulations. The results demonstrate that our approach outperforms existing methods, namely PSO + ACO and FBPSO + FBACO, in terms of key metrics, including energy consumption, execution cost, response time, gain of cost, and makespan. [ABSTRACT FROM AUTHOR]

A sensorless control method of permanent magnet synchronous motor (PMSM) based on adaptive super-twisting algorithm sliding mode observer (STASMO) is proposed in this paper. The traditional sliding mode observer (SMO) algorithm has the problem of inherent high-frequency chattering due to the use of switching function. The phase delay will be caused by using low-pass filter to deal with the problem of high-frequency buffeting. In this paper, the chattering of the system is effectively suppressed by combining the super-twisting algorithm and the SMO algorithm. The chattering suppression ability of the algorithm is further improved by adding an adaptive coefficient associated with speed in front of the higher-order integral term of the observer. At the same time, the speed and rotor position information are extracted by normalized phase-locked loop (PLL), which avoids the use of low-pass filter and phase compensation module. In order to overcome the influence of the change of motor parameters on the control system, an online estimation method of motor parameters is proposed. The values of stator resistance and stator inductance are estimated online in real time, and the estimated values are fed back to the SMO, which improves the system performance and estimation accuracy. Through simulations and experiments, it is proved that the proposed algorithm can effectively suppress high-frequency chattering, effectively improve the estimation performance of PMSM sensorless control system, and obtain more accurate speed and rotor position information. [ABSTRACT FROM AUTHOR]

Since the future grid needs to provide sufficient electrical energy with high quality, it is envisaged that most of the used energy will be supplied by grid-connected voltage source converters (VSCs). The VSCs are used for connecting renewable energy source to the grid, e.g., wind and solar power. The grid-connected VSC considered in this paper is a three-phase three-wire full-bridge converter in which a capacitor is connected to its dc side, while its ac-side is connected to the grid with current control. When operating under unbalanced voltages at the point of common coupling, either due to the presence of unbalanced loads or due to a grid fault condition, a voltage ripple appears at the dc side. The interaction between the VSC dc- side voltage ripple and the VSC ac-side currents is the main focus of this study. In this paper, we analyze the interaction between the VSC dc-side voltage ripple and the VSC ac-side currents under unbalanced voltages. Furthermore, the proposed model is used to determine in which conditions the stability of the VSC ac-side currents can be guaranteed even in the presence of the dc-side voltage ripple. Experimental results confirm that the system remains stable, although with distorted currents due to the dc voltage ripple. Furthermore, it is also shown that the injection of negative sequence currents can decrease the current distortion. [ABSTRACT FROM AUTHOR]

Demand side management (DSM) is widely utilized in smart grid for its reliable features, flexibility, and cost benefits that it offers to customers on reduction of the energy bill. In the smart grid, demand response aggregator, power customers, and utility operator all strive to increase their individual profits. However, it is extremely challenging to guarantee profits for all of the candidates simultaneously. In this paper, these criteria are employed to execute a problem with multiple objectives by combining the concept of DSM and dynamic economic emission dispatch considering uncertainties of renewable energy sources (RESs). The uncertainties of RESs can bring adverse effects on the grid operator. Thus, Weibull probability distribution function and lognormal probability distribution function are used to model the uncertainties of wind speed and solar irradiation, respectively, in this paper. Further, the multi-objective improved DSM scheme is optimized by Class Topper optimization algorithm. The objective here is to optimally schedule load demand and generation pattern simultaneously to improve load factor, minimize electricity bill and maximize the profits of all candidates of the day-ahead electricity market simultaneously. Error in the load forecasting model may lead to growing operational cost of energy generation. In this paper, a machine learning model using linear regression is used for short-term load forecasting (STLF) to forecast day-ahead load demand. The simulation results show the importance of the improved DSM scheme and the advantage of STLF, which further help to improve the economy and efficiency of the smart grid. [ABSTRACT FROM AUTHOR]

Background: Proper investigation of digital evidence is of prime significance in cyber investigations. From the collection of evidence, its preservation, and its analysis, it is important to maintain its integrity in the legal system due to the involvement of different stakeholders like law enforcement agencies, digital analysts, and the judiciary. This review paper focuses on how blockchain technology can be used to collect evidence efficiently. Main text: In the present scenario, the manual logs of the chain of custody are used to ensure that the evidence remains confidential and transparent. It is accompanied by filling out the application forms and maintaining logs within the organization handling the evidence. Hence, it is important to ensure the validity, integrity, and verifiability of evidence as it moves through different hierarchical levels. There are certain issues associated with the current chain of custody, such as evidence loss, theft, tampering, and, even worse, evidence manipulation inside the system. To avoid this situation and to make the process coherent, this review paper aims to highlight the potential use of blockchain technology to preserve chain of custody. Conclusion: Although this scientific technology is mainly used to run cryptocurrencies, with careful consideration and application, this could play a key role in supporting and managing the chain of custody. It is a distributed database that keeps track of blocks. These blocks are collection of entries that keep growing continually and are secured from editing and manipulation by retaining the hash of the previous block in the chain. This is a decentralized technology that is not easily compromised in terms of security and therefore has the potential to solve our problem area. A future research agenda needs to be established, which lays the solid foundation for further studies on this evident emerging area. [ABSTRACT FROM AUTHOR]

This article is an introduction to Part II of a special section on "Behavior and Cultural Systems Analysis for Climate Change" published in Behavior & Social Issues. The introduction highlights the growing severity of the climate crisis and the need for behavior analysis to play a role in shaping solutions. Part I of the special section provided examples of how behavior analysis can contribute to climate change mitigation, including interventions for reducing greenhouse gas emissions and conserving resources. Part II includes four papers that further explore these topics, such as incorporating climate resilience into educational practices, analyzing participants' willingness to enroll in green home energy programs, examining framing effects on public transportation use, and discussing the challenging role of behavior science in achieving global climate justice. The introduction also identifies common themes that emerged from the papers, including the importance of verbal behavior and climate change communication, the need for education and scaling of interventions, the use of behavioral economic analyses, leveraging technological innovations, and engaging policymaker support. The article concludes by emphasizing the urgency of avoiding a catastrophic rise in global temperature and the potential for behavior analysis to contribute to climate solutions. [Extracted from the article]

This paper presents a method for verifying and validating a cyber-physical system. The proposed method identifies possible blockings between the physical and cybernetic parts and is based on the controllability and non-blocking tests of the supervisory control theory. Furthermore, the proposed modeling complies with the hierarchical structure inherent to the cyber-physical system. The paper also presents a method for extracting models of the cybernetic part as it is and puts together models of both physical and cybernetic components that interact with each other. We have also developed tools to perform the verification and validation task and illustrate the proposed method with a computer-integrated manufacturing platform case study. [ABSTRACT FROM AUTHOR]

A formal approach to rephrasing nonlinear filtering of stochastic differential equations is the Kushner setting in applied mathematics and dynamical systems. Thanks to the ability of the Carleman linearization, the 'nonlinear' stochastic differential equation can be equivalently expressed as a finite system of 'bilinear' stochastic differential equations with the augmented state under the finite closure. Interestingly, the novelty of this paper is to embed the Carleman linearization into a stochastic evolution of the Markov process. The nonlinear swing equation is the cornerstone and lays the foundation of the power systems dynamics. To illustrate the Carleman linearization of the Markov process, this paper embeds the Carleman linearization into a nonlinear swing stochastic differential equation. Furthermore, we achieve the nonlinear swing equation filtering in the Carleman setting. Filtering in the Carleman setting has simplified algorithmic procedures. The concerning augmented state accounts for the nonlinearity as well as stochasticity. We show that filtering the nonlinear stochastic swing equation in the Carleman framework is more refined as well as sharper in contrast to the benchmark nonlinear extended Kalman filter (EKF). The Carleman filtering framework reduces approximately three times more conditional mean absolute errors as compared to the benchmark EKF method for the application of machine swing dynamics. This paper suggests the usefulness of the Carleman embedding into the stochastic differential equation to filter the concerning nonlinear stochastic differential system. This paper will interest nonlinear stochastic dynamists exploring and unfolding linearization embedding techniques to their research. [ABSTRACT FROM AUTHOR]

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The paper analyzes a numerical model of an "active medium" with linear elasticity and a negative initial dissipation constant dynamically renormalized under deformation. The analysis shows that such a system, being seemingly unstable over a wide range of geometries and origins of deformation, can spontaneously reach stable dynamic modes in which its time- and space-alternating dissipation forms complex quasiperiodic patterns and its total volume (length, area) oscillates on a large scale. The results presented in the paper are of interest in academic terms and in terms of mechanical and biological application. [ABSTRACT FROM AUTHOR]

As an extension of mean regression and being robust against outliers, quantile regression has been used in many fields such as biomedicine, ecology, economics. However, it is theoretically and computationally challenging to find the optimal experimental design for quantile regression due to the complexity of the optimization problem. The purpose of this paper is to provide theoretical necessary conditions for A- and c-optimality of a design separately, and a numerical algorithm to find optimal designs for quantile regression models. The algorithm is constructed through particle swarm optimization so as to solve the problem of non-convexity of optimality criteria. In this paper, the algorithm is applied to obtain locally as well as Bayesian optimal designs for Michaelis–Menten, Emax and Exponential quantile regression models. We demonstrate that this technique can be applied to a variety of optimality criteria and scale functions without making any further assumption. [ABSTRACT FROM AUTHOR]

Cavitation commonly induces performance deterioration and system vibration in many engineering applications. This paper aims to investigate the effects of air injection on cavitation evolution, pressure pulsation and vibration in a centrifugal pump with inducer. In this paper, the high-speed camera is used to capture the gas flow pattern and cavitation evolution process in the inducer. The impacts of air injection on the inlet pressure pulsation and vibration are also investigated. The results show that the cavitation development in the inducer undergoes four patterns: incipient cavitation, sheet cavitation, cloud cavitation and super cavitation. During the development of cavitation, the main frequency of the pressure pulsation shifts to lower frequencies, and the amplitude of the vibration increases. In addition, air injection promotes the incipient cavitation but delays the cavitation development. A small amount of air can effectively decrease amplitudes of pressure pulsation and vibration. But as the air content increases, the fluctuations and amplitudes of pressure pulsation and vibration increase. [ABSTRACT FROM AUTHOR]

Background: With the increase in the aging population, informal caregivers have become an essential pillar for the long-term care of older individuals. However, providing care can have a negative impact and increase the burden on caregivers, which is a cause for concern. Objective: This study aimed to comprehensively depict the concept of "informal caregiver burden" through bibliometric and content analyses. Methods: We searched the Web of Science (WoS) database to obtain bibliometric data and included only papers published between 2013 and 2022. We used content analysis to extract and identify the core concepts within the text systematically. Results: Altogether, 934 papers were included in the bibliometric analysis, from which we selected 19 highly impactful papers for content analysis. The results indicate that researchers have focused on exploring the factors that impact informal caregiver burden. Meanwhile, there has been a widespread discussion regarding the caregiver burden among those caring for recipients with specific illnesses, such as dementia, Alzheimer's disease, and cancer, as these illnesses can contribute to varying levels of burden on informal caregivers. In addition, questionnaires and interviews emerged as the predominant methods for data collection in the realm of informal caregiver research. Furthermore, we identified 26 distinct assessment tools specifically tailored for evaluating burden, such as caregiver strain index (CSI). Conclusion: For future studies, we suggest considering the intersectionality of factors contributing to the burden on informal caregivers. This approach could enhance the well-being of both caregivers and older care recipients. [ABSTRACT FROM AUTHOR]

The probabilistic rough set (PRS) model, through the incorporation of error levels, represents a quantitative extension of the classical rough set model. It serves as a fundamental expansion that enables robust fault tolerance capabilities by employing relative quantitative description. However, when confronted with interval-valued fuzzy data, the PRS model is rendered ineffective. The primary reason for this lies in the absence of a unique equivalence relation in interval-valued decision systems. This paper presents a novel approach to address this limitation. In this paper, we first propose a fuzzy similarity relation based on diversity function, which establishes a viable foundation for constricting models of probabilistic rough fuzzy set and multi-granularity probabilistic rough set models for interval-valued fuzzy decision systems. Then the decision rules are derived from the presented three kinds of multi-granularity probabilistic rough fuzzy sets, respectively. In order to elucidate the concepts of interval-valued probabilistic rough fuzzy sets and multi-granularity probabilistic rough fuzzy sets, a case study is considered, which is helpful for applying these theories to deal with practical issues. [ABSTRACT FROM AUTHOR]

Discussions around assessment integrity often focus on the exam conditions and the motivations and values of those who cheated in comparison with those who did not. We argue that discourse needs to move away from a binary representation of cheating. Instead, we propose that the conversation may be more productive and more impactful by focusing on those who do not cheat, but who are tempted to do so. We conceptualise this group as being at risk of future cheating behaviour and potentially more receptive of targeted strategies to support their integrity decisions. In this paper we report on a large-scale survey of university students (n = 7,511) who had just completed one or more end of semester online exams. In doing so we explore students' reported temptation to cheat. Analysis surrounding this "at risk" group reveals students who were Tempted (n = 1379) had significant differences from those who Cheated (n = 216) as well as those who were Not tempted (n = 5916). We focus on four research questions exploring whether there are specific online exam conditions, security settings, student attitudes or perceptions which are more strongly associated with the temptation to cheat. The paper offers insights to help institutions to minimise factors that might lead to breaches of assessment integrity, by focusing on the temptation to cheat during assessment. [ABSTRACT FROM AUTHOR]

This paper connects the problem of artificial intelligence (AI)-facilitated academic misconduct with crime-prevention based recommendations about the prevention of academic misconduct in more traditional forms. Given that academic misconduct is not a new phenomenon, there are lessons to learn from established information relating to misconduct perpetration and frameworks for prevention. The relevance of existing crime prevention frameworks for addressing AI-facilitated academic misconduct are discussed and the paper concludes by outlining some ideas for future research relating to preventing AI-facilitated misconduct and monitoring student attitudes and behaviours with respect to this type of behaviour. [ABSTRACT FROM AUTHOR]