Flexible Options Research Articles

Shifting to remote learning

The COVID-19 pandemic reached the U.S. in March 2020. This prompted an abrupt shift from face-to-face to remote instruction in universities globally. In one hard-hit urban region in the Midwestern Rust Belt, a public four-year university, its faculty, students, and staff struggled logistically, financially, academically, psychologically, and otherwise in order to create a working educational community during the pandemic. The social work department and its field education program were severely impacted and developed flexible options so that students could succeed in the classroom as well as in field.

Collaborative PrEP Implementation Strategies for Latino Men Who have Sex with Men: A Health Center-Community Consensus Process

Community-based organizations (CBOs) deliver services in culturally-responsive ways, and could effectively partner with health centers to deliver HIV pre-exposure prophylaxis (PrEP) to Latino men who have sex with men (LMSM). However, few such models exist. We conducted a planning study in collaboration with three CBOs serving LMSM to identify optimal PrEP delivery strategies for health centers and CBOs to implement jointly. We established a Community Expert Panel (CEP) of eight client-facing CBO and health center staff. Over 6 months, the panel met monthly to identify collaborative strategies for PrEP delivery, using a modified Delphi method consisting of the following steps: (1) brainstorming strategies; (2) rating strategies on acceptability, appropriateness and feasibility; (3) review of data from qualitative focus group discussions with CBO clients; and (4) final strategy selection. The panel initially identified 25 potential strategies spread across three categories: improving communication between health centers and CBOs; using low-barrier PrEP options (e.g. telemedicine), and developing locally-relevant, culturally-sensitive outreach materials. Focus groups with CBO clients highlighted a desire for flexible options for PrEP-related care and emphasized trust in CBOs. The final package of strategies consisted of: (1) a web-based referral tool; (2) telemedicine appointments; (3) geographically-convenient options for lab specimen collection; (4) tailored print and social media; and (5) regular coaching sessions with CBO staff. Through a community-engaged process, we identified a package of PrEP delivery strategies that CBOs and health centers can implement in partnership, which have the potential to overcome barriers to PrEP for LMSM.

Application of a flexibility estimation method for domestic heat pumps with reduced system information and data

Activation of heat pump flexibilities is a viable solution to support balancing the grid via Demand Side Management measures and fulfill the need for flexibility options. Aggregators as interface between prosumers, distribution system operators and balance responsible parties face the challenge due to data privacy and technical restrictions to transform prosumer information into aggregated available flexibility to enable trading thereof. Thereby, literature lacks a generic, applicable and widely accepted flexibility estimation method for heat pumps, which incorporates reduced sensor and system information, system- and demand-dependent behaviour. In this paper, we adapt and extend a method from literature, by incorporating domain knowledge to overcome reduced sensor and system information. We apply data of five real-world heat pump systems, distinguish operation modes, estimate power and energy flexibility of each single heat pump system, proof transferability of the method, and aggregate the flexibilities available to showcase a small HP pool as a proof of concept.

Flame (v2.0): advanced integration and interpretation of functional enrichment results from multiple sources.

. http://flame.pavlopouloslab.info. https://github.com/PavlopoulosLab/Flame. https://hub.docker.com/r/pavlopouloslab/flame. Supplementary data are available at Bioinformatics online.

Optimisation of generation unit commitment and network topology with the dynamic thermal rating system considering N-1 reliability

The electrical grid is a vital component of modern society that requires significant and cost-effective investments to ensure its reliability. The dynamic thermal rating system (DTR) and network topology optimization (NTO) aim to increase the capacity of existing networks and provide flexible options for enhancing power system reliability. The co-optimization framework for generation unit commitment and network switching is formulated with for N-1 reliability, a gap that has not been previously addressed. This is important as it ensures: (1) economic efficiency in power system despatch, (2) optimal operation of both generation and transmission systems, and (3) power grid operation that can withstand the loss of any single component without causing a cascading failure. The reliability impacts of these new proposed operating strategies are also tested on complex, large-scale power systems under long-term, multi-area weather conditions. This proposed work is useful for power system planners, as it helps them identify ways to improve the reliability and efficiency of power systems under various weather conditions. This paper shows that using the DTR-NTO combination improves EENS by 50% in both test cases compared to the original condition. Additionally, it also makes the reliability assessment more realistic when taking into account multi-area weather conditions.

Beyond the Grid: The Micropolitics of Off‐Grid Energy in Qandu‐Qandu, South Africa

AbstractIn this paper, we argue using smart technologies beyond the grid disrupts the access and use of existing energy sources, with profound impacts on everyday social life. We show how off‐grid smart energy solutions constitute their own politics when considering existing conceptualisations of urban infrastructures in geography and the social sciences. To expose its politics, or “micropolitics”, we consider how tensions occur at the interface between infrastructures, where there are additions and modifications. We draw on an empirical example of Qandu‐Qandu, an informal settlement in South Africa, to highlight how the placement, technical capabilities, and flexible financing options associated with off‐grid solar energy create micropolitics with profound implications for everyday life. To conclude, we reflect on the value of using disruptions for understanding and enhancing equity in off‐grid settings, contributing to the broader sustainability transitions narrative, and its “liveliness”.

GlycoDraw: a python implementation for generating high-quality glycan figures.

Glycans are essential to all scales of biology, with their intricate structures being crucial for their biological functions. The structural complexity of glycans is communicated through simplified and unified visual representations according to the Symbol Nomenclature for Glycans (SNFGs) guidelines adopted by the community. Here, we introduce GlycoDraw, a Python-native implementation for high-throughput generation of high-quality, SNFG-compliant glycan figures with flexible display options. GlycoDraw is released as part of our glycan analysis ecosystem, glycowork, facilitating integration into existing workflows by enabling fully automated annotation of glycan-related figures and thus assisting the analysis of e.g. differential abundance data or glycomics mass spectra.

Panek Carsharing 2.0: An innovative sharing economy platform for efficient and sustainable mobility

Purpose of Study: To investigate and evaluate the effectiveness and sustainability of the Panek Carsharing 2.0 platform as a solution for mobility needs Furthermore, The research aims to analyze the features and functionalities of the platform. assess its impact on the efficiency of car-sharing services and evaluate its contribution to sustainable mobility practices Followed by providing insights into the benefits and limitations of the Panek Carsharing 2.0 platform and identifying areas for improvement to enhance its efficiency and sustainability in the context of shared mobility.
 Methodology: The paper was prepared with the use the critical literature review method mainly in the field of sharing economy. In conducting a literature review, the researchers examined academic and professional literature, articles, publications, and relevant documents related to the subject matter. These sources provided valuable insights into the current state of carsharing platforms, with a particular emphasis on innovative approaches in the sharing economy sector.
 Main findings: Sharing economy and shared mobility are rapidly growing areas with the potential to transform resource utilization and transportation. The sharing economy allows for more efficient use of goods and services, while shared mobility enables flexible and convenient transportation options. Benefits of the sharing economy and shared mobility include sustainable resource utilization, reduced congestion, and financial savings. Panek S.A. aims to enhance their Panek CarSharing service by implementing innovative algorithms and modules to improve safety, optimize fleet management, and enhance the overall user experience.
 Application of the study: The application of this study in the carsharing market can provide valuable insights for carsharing providers, policymakers, and researchers. Carsharing providers can utilize the findings to enhance their service offerings and business strategies. The study can help identify key factors that influence customer preferences, usage patterns, and satisfaction levels, allowing providers to tailor their services accordingly. Policymakers can use the study's insights to inform regulations and policies that support the growth and sustainability of the carsharing industry. Additionally, researchers can build upon the study's findings to further investigate specific aspects of the carsharing market, such as pricing models, customer behavior, or the impact of carsharing on urban mobility and environmental sustainability. Ultimately, the application of this study can contribute to the development of a more efficient, accessible, and sustainable carsharing ecosystem.
 Originality/Novelty of the study: The originality of this study lies in the innovative approach taken by PANEK S.A. to enhance and develop their Panek CarSharing service. By leveraging modern technologies and innovative features, PANEK S.A. strives to improve their offering and create a more attractive experience for users.

Risk-averse and flexi-intelligent scheduling of microgrids based on hybrid Boltzmann machines and cascade neural network forecasting

The future of energy flexibility in microgrids (MGs) is steering towards a highly granular control of the end-user customers. This calls for more highly accurate uncertainty forecasting and optimal management of risk and flexibility options. This paper presents a novel data-driven model to optimize the operation of MGs based on a risk-averse flexi-intelligent energy management system (RFEMS), considering the rising challenge of global climate change. It considers the presence of renewables, a diesel generator, and flexibility resources (FRs) containing a demand response program (DRP), distributed electric vehicles (EVs), and electric springs (ESs). In the first phase, the proposed model, by means of a novel hybrid deep-learning (DL) model, forecasts uncertain parameters associated with wind and solar generations, load demand, and day-ahead energy market price. The architecture of the proposed hybrid forecasting model is composed of several stacked restricted Boltzmann machines and a cascade neural network. In the second phase, the MG operator (MGO), based on the obtained uncertainty forecasting results, in the context of a hybrid risk-controlling model, optimizes the MG operation using the provided demand-side flexibility. The proposed optimization problem is linearized stochastic programming with robust concepts, subject to AC optimal power flow constraints, MG flexibility restrictions, and operating limits of local resources. Finally, the efficiency of the proposed RFEMS by using real German datasets on a 33-bus test MG is analyzed. Numerical results demonstrate the superior performance of the proposed forecasting model over several hybrid DL models. In particular, the root mean square error (RMSE) index for wind, solar, load, and price forecasting is improved by 53.35%, 73.24%, 80.24%, and 58.1%, respectively. Further analysis of the proposed RFEMS reveals that operating indices in two 33-bus and 69-bus test networks are significantly improved. It paves pathways to risk-averse, flexible, and economic operation of smart active distribution networks.

Carbon allowance auction design of China's ETS: A comprehensive hierarchical system based on blockchain

This study proposes a blockchain-based optimization framework for carbon allowance allocation auctions. First, the study assesses the status quo of carbon trading, pinpointing barriers, future development trends, and identifying carbon quota auction standards and methods pertinent to the Chinese context. Second, based on China's carbon market needs and the technical characteristics of blockchain, this study reconfigures the functions and responsibilities of each participant and creates a framework for a carbon allowance auction system to optimize the carbon trading process. Third, an algorithm for the carbon allowance auction system is constructed, and the corresponding smart contract is created and simulated. The results illustrate that our proposed system framework facilitates universal carbon allowance auctions, efficiently addresses potential disputes during the auction process, enhances market transparency and credibility, and offers comprehensive privacy protection with flexible information disclosure options for corporations. Blockchain's role in fostering paid distribution and incentivizing participation in the carbon market is further recognized. A blockchain-based carbon trading system safeguards transaction security and efficiency, maintains precise transaction records, and provides automated settlement. Ultimately, this paper presents policy suggestions for the development of a national carbon market in China.

Influence of bioenergy and transmission expansion on electrical energy storage requirements in a gradually decarbonized European power system

With the ongoing energy transition in Europe, the share of variable renewable energies (VRE) in the power system increases steadily and different flexibility options gain importance. This work investigates the deployment of supply side flexibility options in the future European power system by energy system modelling focusing on classic power storage technologies, hydrogen storage, generation by biomass and grid expansion. While investigating different flexibility availability scenarios, for the first time the competition of long-term flexibility options is investigated across a broad decarbonization spectrum. In all scenarios, an increasing need for additional flexibility options is found for moderate decarbonization levels with VRE shares higher than 50%. From there on, the deployment of power storages grows nonlinearly, and eventually features a remarkable leap when approaching a zero-emission system, which is mainly driven by hydrogen storage investments. This also comes along with a leap in the total system costs. When the expansion of biomass capacities is available, biomass partly takes over the function of hydrogen as a long-term flexibility option. When enabling grid expansion, additional transmission capacities lead to a stronger integration of wind generation, while (especially short-term) storage requirements for higher decarbonization levels decrease. Both the additional investments into biomass generation and transmission grid result in up to 4% lower total system costs, yet, without completely displacing any other flexibility option. We conclude that the interaction of multiply flexibility options will lead to a cost minimal power system.

Representing decentralized generation and local energy use flexibility in an energy system optimization model

Local energy generation and energy use flexibility is becoming increasingly relevant for planning energy systems with a high level of renewables, electrification, and decentralization. Although current energy system models represent various flexibility options, capturing demand-side flexibility and prosumption remains challenging. In light of these challenges, this study presents a national-scale energy system optimization model covering the residential and commercial sectors of Belgium and considering the interplay between local energy use flexibility from electric vehicle (EV) charging, battery storage, rooftop photovoltaic (PV) systems and distribution grids. To adequately represent energy use flexibility, the model adopts a high temporal resolution, consisting of three representative weeks at an hourly time scale. The role of prosumption is analysed by introducing a prosumer potential reflecting the extent to which local energy production can be used to meet local demand ‘behind the meter’. The results show that flexibility significantly reduces total system costs with reduced distribution grid capacity investment by 48% by 2050. Furthermore, local energy use flexibility enables a significant uptake of rooftop PV (+6.7 GW), but only under a high prosumer potential condition. Finally, a curtailment of around 5–7% of PV production is cost-effective to sustain a more continuous use of the distribution grid at low peak capacity. To increase the robustness of the results, future research should consider expanding the model's sector coverage, adding additional flexibility sources, improving the representation of prosumption, soft-linking with distribution grid models and a better representation of mobility patterns.

A work-family enrichment model of perceived overqualification: the moderating role of flexibility human resource practices

PurposeThis research focuses on the work–family facilitation process to theorize and examine the potential positive impact of perceived overqualification (POQ) on an individual’s work–family interface. Drawing on social cognitive theory of self-regulation, this research identifies work–family balance self-efficacy (WFBSE) as a motivational mechanism through which POQ affects work engagement. Additionally, it proposes flexibility human resource (HR) practices as a key moderator of this process.Design/methodology/approachThis research collected multi-wave time-lagged data from 342 managers in the hospitality industry. The research focused on managers with the title of headwaiter and above, while front-line service personnel were not included.FindingsThe results showed that POQ had an indirect positive relationship with work engagement via WFBSE. The results also showed that employee-experienced flexibility HR practices moderated the effectiveness of WFBSE in translating POQ into work engagement.Practical implicationsThis research provides guidance and insights into how HRM systems can be customized to sustain positive outcomes in situations of overqualification. It is crucial that hotels offer flexibility options or individualization of work arrangements for overqualified employees.Originality/valueThe potential positive impact of POQ on employees’ work–family interface has been neglected. In addition, prior research has devoted little attention to potential organizational factors that enhance the positive effects of POQ. By examining the mediating and moderating effects, this research aims to explain how and under what conditions POQ facilitates work engagement.

Bankers’ Perspective on Challenges of Bad Debt Recovery: Empirical Evidence from Commercial Banks of Nepal

The purpose of this paper is to investigate bankers’ perspective on challenges of bad debt recovery in commercial banks of Nepal. This study is based on liquidity management theory and adopts explanatory research design to determine causal relationship between variables. Primary data has been collected from 220 bankers through the structured questionnaire by using KOBO Toolbox. SEM is used to analyze data inferentially. Findings indicate that lending decision and loan risk monitoring are significant to bad debt recovery. Unfavorable methods, availability of accurate and proper information about the loans, lack of payment visibility, and lack of flexible payment options are major challenges of bad debt recovery. Thus, commercial banks of Nepal must develop proper monitoring mechanism and government should develop proper regulation for debt collection.

Personal and Work-Oriented Characteristics Distinguishing Older Nurses' Partial or Complete Actual Retirement Behavior over Three Years.

To retain nurses and prevent worsening the nursing shortage, a key opportunity is to better understand the drivers of complete and partial retirement of older nurses. This study investigates the characteristics that distinguish older nurses' partial and complete actual retirement behavior, from those continuing to work, over a three-year period. A quantitative longitudinal design comprising 217 female Australian nurses aged 50 years or over, from two samples working at Time 1 (2012 and 2016), responding three years later (Time 2). Multinomial regression found two different patterns of drivers for each of completely retiring and partly retiring respectively. Age was the only variable distinguishing both partly and completely retired nurses from nurses who were not retired. The further variables distinguishing completely retired nurses were not being prosperous, having impaired work ability, being partnered, not stressed at work and working part-time. The only variable beyond age distinguishing partly retired nurses was having a casual contract. Offering flexible work options in terms of working hours and contracts that suit the nurse's lifestyle and supporting nurses with health impairments to continue working are options that may lessen the number of nurses completely retiring and instead either remaining at work or partly retiring.

A self-guided Internet-based intervention for individuals with chronic pain and depressive symptoms: study protocol of a randomized controlled trial

BackgroundDespite the existence of evidence-based therapy options for the treatment of chronic pain and comorbid depressive symptoms (e.g., CBT), many individuals remain untreated. Treatment gaps result from a lack of specialists, patient fear of stigmatization, or patient immobility. Internet-based self-help interventions could serve as an anonymous and flexible alternative treatment option. In a pilot study, chronic pain patients with comorbid depressive symptoms who used a generic Internet-based depression program showed a significant reduction in depressive symptoms (but not pain symptoms) compared to a waitlist control group. Based on these findings, we developed the low-threshold, anonymous, and cost-free Internet-based self-help intervention Lenio that is tailored to the specific needs of chronic pain patients with comorbid depressive symptoms. Lenio is accompanied by the smartphone application (app) COGITO designed to increase therapeutic success. With Lenio and COGITO addressing both chronic pain and depressive symptoms, the trial aims to increase treatment effects of online interventions for chronic pain patients by reducing both depressive symptoms and pain.MethodsThe effectiveness of the Internet-based self-help intervention and accompanying smartphone app will be evaluated in a randomized controlled trial (RCT). A total of 300 participants will be randomized into an intervention group (Lenio/COGITO), an active control group (depression-focused smartphone app), or a waitlist control group. Assessments will be done at baseline, after an 8-week intervention period (post), and after 16 weeks (follow-up). The primary outcome is the post-assessment reduction in “pain impairment” (mean value of impairment in daily life, free time, and work) as assessed by the DSF (German pain questionnaire). Secondary outcomes will include the reduction in depressive symptoms as well as in the severity of pain. DiscussionLenio is one of the first Internet-based interventions to reduce chronic pain and depression that will be empirically evaluated. Internet-based interventions could offer a promising alternative to conventional face-to-face psychotherapy in the treatment of chronic pain patients. The primary objective of the current study is to add essential insight into the feasibility, effectiveness, and acceptance of Internet-based interventions for people with chronic pain and depressive symptoms. Trial registrationDRKS-ID DRKS00026722, Registered on October 6th, 2021.

Multi-modal image matching to colorize a SLAM based point cloud with arbitrary data from a thermal camera

Thermal mapping of buildings can be one approach to assess the insulation, which is important in regard to upgrade buildings to increase energy efficiency and for climate change adaptation. Personal laser scanning (PLS) is a fast and flexible option that has become increasingly popular to efficiently map building facades. However, some measurement systems do not include sufficient colorization of the point cloud. In order to detect, map and reference any damages to building facades, it is of great interest to transfer images from RGB and thermal infrared (TIR) cameras to the point cloud. This study aims to answer the research question if a flexible tool can be developed, which enable such measurements with high spatial resolution and flexibility. Therefore, an image-to-geometry registration approach for rendered point clouds is combined with a deep learning (DL)-based image feature matcher to estimate the camera pose of arbitrary images in relation to the geometry, i.e. the point cloud, to map color information. We developed a research design for multi-modal image matching to investigate the alignment of RGB and TIR camera images to a PLS point cloud with intensity information using calibrated and un-calibrated images. The accuracies of the estimated pose parameters reveal the best performance of the registration for pre-calibrated, i.e. undistorted, RGB camera images. The alignment of un-calibrated RGB and TIR camera images to a point cloud is possible if sufficient and well-distributed 2D-3D feature matches between image and point cloud are available. Our workflow enables the colorization of point clouds with high accuracy using images with very different radiometric characteristics and image resolutions. Only a rough approximation of the camera pose is required and hence the approach reliefs strict sensor synchronization requirements.

The New Conception of Radiological Sustainability Possibilities by Reutilization of Residues Products and Building Materials

The concept of radiological sustainability has been reviewed using the possibility of the reutilization of NORMs regarding the 2050 sustainable development concepts. This study is reviewing the capability of re-production of NORM residues based on their properties and the applicable treatment before reutilization. Linking the waste producers and construction materials industry as mineral end-users could contribute to the creation of industrial symbiosis and result in waste reduction and preserving natural resources on one hand, and CO2 reducing and energy saving on the other hand. According to EU-BSS (European Basic Safety Standards Directive), the characterization of NORMs as a secondary raw material for use as construction materials is necessary, however as an additive or secondary material their radiological behavior and material properties are quite important regardless of their origin. This is to say that the reutilization of NORM residues provides a better financial and environmental solution while reducing possible radiological effects on humans. NORM residue or waste could become a high material resource for the cement industry. In this regard, the assessment of radium equivalents (Raeq) and external and internal indexes (I-indexes) are useful tools to classify NORM residues before their inclusion in building products. This assessment and/or indexes reflect the risk of external exposure much better than the specific activity concentration of Ra-226, Th-232 and K-40. Equally, building material properties such as density and thickness should be taken into consideration when designing building materials that contain NORM residue. Furthermore, mixtures or additives of NORM residues are proven to result in the reduction of activity concentration in the raw residue with other raw materials, and this offers flexible reuse options depending on the final product. By integrating radiological considerations into sustainable development initiatives, we can work towards a safer, healthier and more sustainable future.

Risk aversion and flexibility options in electricity markets

Flexibility options, such as demand response, energy storage and interconnection, have the potential to reduce variation in electricity prices between different future scenarios, thereby reducing investment risk. Investing in flexibility options can also lower the need for generation capacity. However, there are complex interactions between different flexibility options. In this paper, we investigate the interactions between flexibility and investment risk in electricity markets. In particular, we focus on the investment strategies of risk-averse decision-makers. We employ a large-scale stochastic transmission and generation expansion model of the European electricity system, providing it with uncertain future scenarios based on ENTSOs’ Ten-Year Network Development Plan. Using this model, we first investigate the effect of risk aversion on investment decisions. We find that the interplay of parameters leads to (i) more investment in a less emission-intensive energy system if planners are risk averse (hedging against CO2 price uncertainty), (ii) constant total installed capacity, regardless of the level of risk aversion (i.e. planners do not hedge against demand and uncertainties when deploying renewable energy sources) and (iii) an allocation of investments that disregards cost differences for load shedding across Europe. Second, we examine the individual effects of three flexibility elements on optimal investment levels at different levels of risk aversion: demand response, investment in additional interconnection capacity and investment in additional energy storage. We show that flexible technologies have a higher value for risk-averse decision-makers, although the effects are nonlinear. Finally, we investigate the interactions between the flexibility elements. We find that risk-averse decision-makers show a strong preference for transmission-grid expansion once flexibility is available at a low cost.

Revolutionizing Education: Unlocking the Potential of Asynchronous Video for Interactive Online Learning

The traditional education landscape has witnessed a significant transformation in recent years due to advancements in technology and the growing demand for flexible learning options. Asynchronous video has emerged as a powerful tool in online education, offering learners the freedom to access course materials and engage with interactive content at their own pace and convenience. This paper explores the potential of asynchronous video in revolutionizing education by unlocking new possibilities for interactive online learning. The paper begins by discussing the limitations of traditional synchronous learning models and the need for innovative approaches that cater to the diverse learning styles and schedules of today's students. It then delves into the concept of asynchronous video, highlighting its key features and advantages. By enabling learners to access video lectures, tutorials, and demonstrations anytime and anywhere, the asynchronous video promotes self-paced learning and facilitates personalized educational experiences. Moreover, the paper examines how interactive elements can be seamlessly integrated into asynchronous video content. By incorporating quizzes, assessments, and interactive discussions within video platforms, educators can foster active engagement, promote critical thinking, and enhance knowledge retention. The potential of augmented reality (AR) and virtual reality (VR) technologies in creating immersive and interactive learning experiences through asynchronous video is also explored. Furthermore, the paper addresses the challenges and considerations associated with implementing asynchronous video in educational settings. It discusses issues related to video production, accessibility, and learner support, offering practical solutions and best practices to overcome these hurdles. The paper highlights successful case studies and initiatives that have effectively harnessed the potential of asynchronous video for interactive online learning. It presents evidence of improved learning outcomes, increased student engagement, and enhanced instructor-student interaction through the utilization of asynchronous video