Design Options Research Articles

Doxorubicin-Intercalated Li-Al-Based LDHs as Potential Drug Delivery Nanovehicle with pH-Responsive Therapeutic Cargo for Tumor Treatment.

Clinical oncology is currently experiencing a technology bottleneck due to the expeditious evolution of therapy defiance in tumors. Although drugs used in chemotherapy work for a sort of cell death with potential clinical application, the effectiveness of chemotherapy-inducing drugs is subject to several endogenous conditions when used alone, necessitating the urgent need for controlled mechanisms. A tumor-targeted drug delivery therapy using Li-Al (M+/M3+)-based layered double hydroxide (LDHs) family has been proposed with the general chemical formula [M+1-x M3+x (OH)]2x+[(Am-)2x/m. n(H2O)]2x-, which is fully biodegradable and works in connection with the therapeutic interaction between LDH nanocarriers and anticancerous doxorubicin (DOX). Compositional variation of Li and Al in LDHs has been used as a nanoplatform, which provides a functional balance between circulation lifetime, drug loading capacity, encapsulation efficiency, and tumor-specific uptake to act as self-regulatory therapeutic cargo to be released intracellularly. First-principle analyses based on DFT have been employed to investigate the interaction of bonding and electronic structure of LDH with DOX and assess its capability and potential for a superior drug carrier. Following the internalization into cancer cells, nanoformulations are carried to the nucleus via lysosomes, and the mechanistic pathways have been revealed. Additionally, in vitro along with in vivo therapeutic assessments on melanoma-bearing mice show a dimensional effect of nanoformulation for better biocompatibility and excellent synergetic anticancer activity. Further, the severe toxic consequences associated with traditional chemotherapy have been eradicated by using injectable hydrogel placed just beneath the tumor site, and regulated release of the drug has been confirmed through protein expression applying various markers. However, Li-Al-based LDH nanocarriers open up new design options for multifunctional nanomedicine, which has intriguing potential for use in cancer treatment through sustained drug delivery.

The beauty of symmetry: siRNA phosphorodithioate modifications reduce stereocomplexity, ease analysis, and can improve in vivo potency

Phosphorothioates (PS) can be essential in stabilizing therapeutic oligonucleotides against enzymatic degradation. However, unless synthesis is performed with stereo-defined amidites, each PS introduces a chemically undefined stereocenter, resulting in 2n unique molecules in the final product and affecting downstream analytics and purification. Replacing the second non-bridging oxygen with sulfur results in phosphorodithioate (PS2) linkages, thereby removing the stereocenter. We describe synthesis and analytical data for GalNAc-conjugated siRNAs with PS2 in the GalNAc cluster and at the siRNA termini. All siRNA conjugates with PS2 internucleotide linkages were produced with good yield and showed improved analytical properties. PS2 in the GalNAc cluster had no, or only minor, effect on in vitro and in vivo activity. Except for the 5′-antisense position, PS2 modifications were well tolerated at the siRNA termini, and a single PS2 internucleotide linkage gave similar or improved stabilization and in vitro activity as the two PS typically used for end stabilization. Surprisingly, several of the PS2-containing siRNA conjugates resulted in increased in vivo activity and duration of action compared to the same siRNA sequence stabilized with PS linkages, suggesting PS2 linkages as interesting options for siRNA strand design with reduced number of undefined stereocenters.

Data-enhanced design charts for efficient reliability-based design of geotechnical systems

This paper proposes a new design chart approach for reliability assessment, which enables clear visualization of the representative soil shear strength parameters under various reliability levels and effective stress levels. Utilizing the design charts, reliability assessment or reliability-based design can be performed with significantly reduced numbers of evaluations of the geotechnical system response. The design charts are established solely based on the probability distributions of soil parameters, and are applicable to a variety of geotechnical problems involving the same soil type. For practical illustration of the proposed approach, design charts are produced from the shear strength databases of saprolitic soils and colluvial soils in Hong Kong, and then applied to the reliability-based design of a slope with soil nail reinforcements. The ensuing design solutions require much fewer soil nails compared to the conventional design practice, while also achieving a better system reliability. The same charts are then applied to the reliability-based design of a retaining wall, where a series of design options are identified with equivalent reliability index against overturning failure and pullout failure. Through the proposed approach, the use of design charts promotes efficient reliability-based design of geotechnical systems with rational incorporation of reliability concepts.

Impact of Different π-Bridges on the Photovoltaic Performance of A-D-D'-D-A Small Molecule-Based Donors.

Three small donor molecule materials (S1, S2, S3) based on dithiophene [2,3-d:2',3'-d']dithiophene [1,2-b:4,5-b']dithiophene (DTBDT) utilized in this study were synthesized using the Vilsmeier-Haack reaction, traditional Stille coupling, and Knoevenagel condensation. Then, a variety of characterization methods were applied to study the differences in optical properties and photovoltaic devices among the three. By synthesizing S2 using a thiophene π-bridge based on S1, the blue shift in ultraviolet absorption can be enhanced, the band gap and energy level can be reduced, the open circuit voltage (VOC) can be increased to 0.75 V using the S2:Y6 device, and a power conversion efficiency (PCE) of 3% can be achieved. Also, after developing the device using Y6, S3 introduced the alkyl chain of thiophene π-bridge to S2, which improved the solubility of tiny donor molecules, achieved the maximum short-circuit current (JSC = 10.59 mA/cm2), filling factor (FF = 49.72%), and PCE (4.25%). Thus, a viable option for future design and synthesis of small donor molecule materials is to incorporate thiophene π-bridges into these materials, along with alkyl chains, in order to enhance the device's morphology and charge transfer behavior.

Perturbation approaches to achieving diverse and competitive designs in topology optimisation

Utilising topology optimisation to generate diverse and competitive structures enables designers to create elegant and efficient designs according to their aesthetic intuition and functional needs. This study proposes load and support perturbation approaches based on the bi-directional evolutionary structural optimisation (BESO) method to achieve diverse designs. During the optimisation process, noise is introduced to the sensitivity calculations by randomly perturbing the load angles or material properties near the supports, leading to a variety of local optima. Numerical results demonstrate that the proposed approaches are capable of creating designs with similar stiffness but distinct geometries. In addition, the diversity of the obtained solutions can be controlled by utilising different perturbation functions. This work is of significant practical importance in both architecture and engineering, where multiple design options of high structural performance are in demand.

Deep generative model-based synthesis framework of four-bar linkage mechanisms with target conditions

Abstract This paper proposes a deep generative model-based framework for synthesizing four-bar linkage mechanisms that satisfy specified kinematic and quasi-static conditions. We define two objective functions for crank-rocker mechanisms using kinematic workspaces and geometric configurations. Our approach utilizes a conditional generative adversarial network (cGAN) modified for mechanism synthesis, which learns the relationship between mechanism requirements and linkage lengths. The results demonstrate that the proposed model successfully generates multiple distinct mechanisms meeting specific kinematic and quasi-static requirements. We compare our cGAN approach to traditional optimization methods and other deep learning-based generative models. Our method offers several advantages over traditional design approaches, enabling efficient generation of diverse yet feasible design candidates while exploring a large design space. By considering both kinematic and quasi-static requirements, the proposed model can produce more effective mechanisms for real-world applications. This makes it a promising tool for linkage mechanism design, offering designers a way to efficiently generate multiple viable design options that satisfy key performance criteria.

Measurements and TCAD simulations of guard-ring structures of thin silicon sensors before and after irradiation

The developing of high performing silicon detectors for particle tracking in the next generation of high-energy physics experiments at future colliders (e.g., HL-LHC, FCC) able to operate efficiently up to very high fluence (∼1⋅10171MeVneq/cm2) is of the utmost importance. In order to sustain high voltage values with minimum leakage current injection into the core region of the sensor, the design and optimisation of the Guard-Ring (GR) protection structure is crucial, especially when small substrate thicknesses are used. In a recent R&D batch produced at Fondazione Bruno Kessler (FBK) in the framework of the “eXFlu” project - INFN CSN5 grant for Young Researchers, different optimisation studies of GR structures for thin substrates (45, 30, 20 and 15μm) up to high fluence (2.5⋅10151MeVneq/cm2) have been addressed. These have been enabled thanks to ad-hoc advanced Technology CAD (TCAD) modelling of different GR design strategies, accounting for the comprehensive bulk and surface radiation-induced damage effects, and an extensive test campaign on such GR structures, both before and after irradiation. In this paper the validation of the development framework of the various GR design options before and after irradiation is presented.

Semiautomatic Exploration of Conceptual Design Spaces through Parametric Shape Variability and Additive Manufacturing

Design ideation activities that involve the manipulation of geometry rely heavily on manual input. For feasibility reasons, the generation of design alternatives must often be limited, particularly when these alternatives need to be prototyped and tested. This paper describes a conceptual design strategy that leverages variational three-dimensional geometry to automatically generate a large number of design alternatives from a template model and their corresponding physical prototypes for evaluation and testing. In our approach, 3D geometric variations are produced automatically from a single design concept modeled parametrically, which are then used to generate 3D-printable files. Our method is suitable for design scenarios where real-world testing is preferred over virtual simulation and requires designers to consider a concept idea as a family of solutions, instead of a single design option. Our strategy enables an effective exploration of conceptual design spaces in highly constrained situations and facilitates parallel prototyping, which is known to produce better results than serial prototyping. We demonstrate the feasibility and effectiveness of the proposed method through a case study that involves the design of an instrument for ophthalmic surgery for extracting an intraocular lens (IOL) from the eye. Using our approach, nine unique concept families comprising a total of 150 designs were rapidly and successfully prototyped and tested.

Adapting Gamification Strategies According to Targeted Health Behavior Change: Findings from a Focus Group.

In healthcare, improving lifestyle behaviors like medication adherence remains challenging, with an impact on treatment success and patient outcomes. Mobile health (mHealth) applications offer promising solutions by leveraging smartphone ubiquity and digital accessibility. However, sustaining user engagement and behavior change presents obstacles. This study explores the specificities of gamification-integrating game-like elements into non-game contexts-to improve mHealth applications for 3 health behaviors. During a focus group, 15 participants discussed the potential of 17 gamification strategies to improve medication adherence, physical activity, and diet within mHealth applications. Individual choices varied widely, with preferences influenced by targeted behaviors. Physical activity focused on self-monitoring and challenges, while dieting emphasized cooperation. Simulation models were particularly intriguing, projecting long-term benefits of behavior changes. Future research should explore personalized design options and consider individual characteristics. Iterative design cycles with end-users are crucial for refining concepts and sustaining user engagement. Overall, gamification presents an innovative avenue for empowering patients and transforming healthcare delivery.

Strengthening energy system resilience planning under uncertainty by minimizing regret

This study applies the concept of regret in decision-making under uncertainty to an energy system optimization model to identify optimal robust and stochastic solutions amongst several design options. The approach is demonstrated on the case study of Accra, Ghana, considering uncertainties pertinent to the city, particularly under climate change. The evaluated uncertainty scenarios consider volatile fossil fuel supply, reduced hydropower generation, rising demand due to climate change-driven rural-urban migration and global warming, unplanned power outages due to increasing natural disasters, and currency depreciation. The evaluated systems include Pareto-optimal system solutions typically under consideration by planners, which balance costs and CO2 emissions. The regret performance is evaluated for each system subject to each uncertainty scenario. A near-CO2-minimized system is the optimal robust and stochastic least-regret solution. Two factors drive this result: (1) a diverse technology set, which provides generation and cross-sectoral flexibility for adaptation under uncertainty, and (2) effectively balancing rising investment and operation costs with decreasing unmet demand costs. The demonstrated method provides energy planners and policymakers with a pragmatic, effective and fast approach, which offers new insights into long-term energy system planning to improve resilience under uncertainty, supporting the aims of the United Nations Sustainable Development Goals 7 and 11.

Hydrogen production from wastewater using interdigitated printed electrode-based Single-Chamber microbial electrolysis cells

In the ever-increasing quest for alternative energy sources, hydrogen emerged as a promising green option, but efficient and economical production and management have been the primary constraints. Converting wastewater into H2 and other forms of energy attracted significant attention in terms of simultaneously and sustainably managing both the wastewater and the energy generation problems. Microbial Electrolysis Cells (MEC) evolved recently as promising options for converting wastewater into H2 and electricity but with serious constraints on scalability. The current research aims to explore design and manufacturing solutions to build structurally strong and electrochemically effective electrodes that can also lead to scalable MEC. Two designs based on the interdigitated and spiral electrode architectures are proposed and evaluated. The added design freedom with additive manufacturing by selective laser melting of specific alloys of choice is effectively utilised in physically prototyping the interdigitated and spiral electrode forms designed with controlled porosity constraints. Microstructural, electrochemical, and cell performance characterisations led to the understanding that the spiral electrode configuration with polypyrrole-coated stainless steel 316L anode is a promising design option for both longitudinal and lateral scale-up of the MEC.

Comparative review and novel design possibilities on solar-driven absorption LiBr-H2O refrigeration system

Solar energy is a promising source of energy because of its potential due to the reduction usage of non-renewable energy. As the demand for cooling increases, solar-powered cooling technologies are becoming increasingly promising. Among the different solar cooling systems, LiBr-H2O absorption chillers are commonly used due to their advantages over NH3-H2O systems. Multiple cycle LiBr-H2O chillers can be powered by easily available flat-plate, evacuated tubular or parabolic solar collectors. This paper reviews Theoretical Principles-Based Analysis and Simulations of solar LiBr-H2O absorption cooling systems, performance comparison of each types and introduces new design options related to auxiliary energy systems and cooling mode cycle. The paper also summarizes other main types of solar absorption cooling systems, including double-effect, half-effect, triple effect and give updates of new technology design of hybrid effect. The choice of water-cooled or air-cooled absorption refrigeration depends on the local climate and water availability. Recent advances have made air-cooled absorption refrigeration a viable option, with comparable COP to water-cooled systems and lower maintenance requirements. Additionally, geothermal heat rejection with low pressure drops can further reduce energy consumption. Solar-powered double-effect absorption cooling systems are recommended for buildings with high cooling loads, while half-effect are suitable for air-cooled solar absorption cooling systems in hot and dry regions with limited water. This paper is specifically intended for those interested in developing solar-driven LiBr-H2O absorption chillers, emphasizing the importance of establishing standardized design guidelines to specific regions and climates in order to promote and expand the usage of solar cooling systems.

Learning the optimal power flow: Environment design matters

To solve the optimal power flow (OPF) problem, reinforcement learning (RL) emerges as a promising new approach. However, the RL-OPF literature is strongly divided regarding the exact formulation of the OPF problem as an RL environment. In this work, we collect and implement diverse environment design decisions from the literature regarding training data, observation space, episode definition, and reward function choice. In an experimental analysis, we show the significant impact of these environment design options on RL-OPF training performance. Further, we derive some first recommendations regarding the choice of these design decisions. The created environment framework is fully open-source and can serve as a benchmark for future research in the RL-OPF field.

Novel load allocation analysis for energy management and carbon emissions reduction of chiller system in hotel buildings

The operation of chiller systems for cooling energy generation in hotel buildings consumes the highest proportion of electricity. This study aims to introduce load allocation analysis to assess the potential for energy savings by a chiller system. The cooling load profile of a hotel in a subtropical climate is simulated using EnergyPlus. Eleven design options for the system include 4 to 8 chillers of the same or different capacities. Restoring chiller sequencing with high load operation can reduce the system's energy use intensity (EUI) by 12.7 %. An optimal design of four large and two small chillers with proper sequencing can reduce the EUI by up to 26.82 % or carbon emissions by 551,516 kgCO2-e. Increasing capacity steps above ten brings no significant energy savings and imposes complicated chiller staging. The area of the load allocation region can be evaluated simply from the chiller system design and used to analyze the system's energy performance. The EUI can be reduced by 0.3261 % for a 1 % drop in the area of load allocation region. The novelty of this study lies in using the load allocation region to assess energy savings of a chiller system without referring to sophisticated operating data at short timesteps. The significance of this study is to highlight the limitations of energy savings from the optimum chiller system design and address the need for incorporating more low energy technologies to enhance decarbonization.

Dialogic incrementalism in deeply divided societies

Abstract A number of the world’s “deeply divided” societies are mired in violent conflicts which often grow out of historic tensions between the nation’s ethno-religious or linguistic groups. Elites within these societies tried to end these conflicts by drafting a constitution that would address the underlying grievances which fuel intergroup conflict. In many cases, however, rather than promoting peaceful political engagement, the process of constitution drafting seemed only to aggravate existing conflicts and create fresh sources of political unrest. Some deeply divided polities have avoided these worst-case outcomes by deploying an “incrementalist” approach to making constitutions. This approach asserts that deeply divided societies need not, and indeed should not, try to answer all constitutional questions. Rather, they can defer the most divisive questions for later resolution. By doing this, incrementalism focuses attention on issues over which some measure of agreement can be forged and enables constitutional ratification under fraught conditions. Critics have, however, identified two real problems with the incrementalist approach: first, once ethnopolitical elites agree to defer important questions, new developments may empower one group and allow it to stop good-faith negotiations and impose its preferred constitutional settlements. Second, the constitution’s open questions may not be resolved in a timely manner, and the lingering ambiguities can produce fresh sources of conflict. This article asks whether one can design constitution-making processes in a way that harvests the benefits of incrementalism while avoiding the problems associated with it. The article suggests that the experiences of Afghanistan and Iraq indicate that there is a particular type of constitutional incrementalism which is more likely than others to accomplish this. It describes three Afghan constitutions, each of which embraced, implicitly, the logic of incrementalism. Of these, however, only one allowed constitutional questions to be addressed in a dialogic fashion. By imposing a process of what I call “dialogic incrementalism,” Afghanistan’s 1931 Constitution helped generate a stable constitutional order. Further, the article suggests that the drafting of Iraq’s 2005 Constitution shows that dialogic incrementalism can be a conscious design option.

M-ARM: An automated systematic approach for generating new variant design options from an existing product family

Companies with established product families can meet emerging market needs by extending their product families over time, that is, by introducing new product variants sequentially. Starting points for each new design can be generated by integrating design solutions from existing products in the same family. This article introduces an automated systematic approach to derive all possible ways of combining existing designs to produce a new variant with a desired new combination of functionality, based on algorithmic analysis of product models. The approach considers the functions in existing products and how they are realised in specific CAD parts and the geometric features defining them. By automatically generating and evaluating all the options, the new approach helps identify the most efficient way to combine existing parts and features from a product family to generate a new product variant with distinct functionality. The approach has been applied to product families of mechanical and mechatronic consumer products. It was evaluated by manually implementing the automatically-generated redesign instructions in CAD for several product variants, which built confidence in the approach’s accuracy and performance. From the evaluation, opportunities for further work are suggested.

Assessment of building design strategies to enhance energy efficiency and thermal comfort: Case study in Morocco’s climate zones

Energy efficiency in the context of building design is a significant concern in Morocco. This paper offers a comprehensive analysis of how various design variables can impact both energy consumption and thermal comfort in the Moroccan context. Rather than isolating individual design variables, we investigate synergistic combinations of these variables. To achieve this, we develop multiple building design scenarios, each employing different combinations of design options, focusing on building orientation, window-to-wall ratio, building envelope construction, and window shading. We use EnergyPlus to conduct energy simulations for all scenarios under the hypothesis of air-conditioned houses and free-running houses with and without natural ventilation. Our results reveal that building design has the potential to significantly enhance energy efficiency and thermal comfort, but not for the same design strategies. In comparison to the most energy-efficient design scenario, the least favorable design scenario can lead to an increase in energy consumption between 237% in Agadir and 130% in Ifrane. Meanwhile, design scenarios favoring comfort can increase the number of comfortable hours by 85% in Agadir and 59% in Ifrane. We identify optimal building design scenarios that simultaneously offer the highest comfort levels with the lowest energy requirements. The findings provide valuable guidance for architects, allowing them to design high-performance buildings in all climate zones in Morocco.

Using Canva in Creating and Designing E-Module for English Language Teaching

The utilization of learning material via the use of technology is interesting. Visual, audio, and audiovisual learning mediums are all options. Memorable and simple-to-understand learning activities may be created using appealing learning material. This study simulates Canva in making and designing an e-module in English material. This research is descriptive qualitative. The analysis shows that Canva is an online graphic design tool that allows educators to generate a variety of creative products such as e-modules of teaching materials. This app can be used to design learning media with attractive templates, and a varied presentation of shapes, images, colors, and letters. To use the Canva app, we create a Canva account on canva.com, choose a template for design, design (insert elements), choose a background, edit the background, add texts, upload images/audio/videos, insert links, download or share designs e-module. Canva is a site that offers both free and paid (freemium) access to a wide variety of design tools and options. Canva has provided 'graphics capabilities for users who 'cannot or are not good at designing' by providing various templates ranging from lawyers, elements (icons, photos, lines, illustrations), text with various fonts, and 4) backgrounds. So, the 'material' has been presented and the users just have to create it. Teachers/lecturers may find Canva to design learning media and develop instructional material. By using Canva, teachers/lecturers can teach material, knowledge, creativity, and skills that will be obtained for students, so that this media can also be used in various areas of their lives.

Common sleep data pipeline for combined data sets.

Over the past few years, sleep research has shown impressive performance of deep neural networks in the area of automatic sleep-staging. Recent studies have demonstrated the necessity of combining multiple data sets to obtain sufficiently generalizing results. However, working with large amounts of sleep data can be challenging, both from a hardware perspective and because of the different preprocessing steps necessary for distinct data sources. Here we review the possible obstacles and present an open-source pipeline for automatic data loading. Our solution includes both a standardized data store as well as a 'data serving' portion which can be used to train neural networks on the standardized data, allowing for different configuration options for different studies and machine learning designs. The pipeline, including implementation, is made public to ensure better and more reproducible sleep research.

Sample size considerations for single-arm clinical trials with time-to-event endpoint using the gamma distribution

BackgroundTime-to-event (TTE) endpoints are evaluated as the primary endpoint in single-arm clinical trials; however, limited options are available in statistical software for sample size calculation. In single-arm trials with TTE endpoints, the non-parametric log-rank test is commonly used. Parametric options for single-arm design assume survival times follow exponential distribution or Weibull distribution. MethodsThe exponential- or Weibull-distributed survival time assumption does not always reflect hazard pattern of real-life diseases. We therefore propose gamma distribution as an alternative parametric option for designing single-arm studies with TTE endpoints. We outline a sample size calculation approach using gamma distribution with a known shape parameter and explain how to extract the gamma shape estimate from previously published resources. In addition, we conduct simulations to assess the accuracy of the extracted gamma shape parameter and to explore the impact on sample size calculation when survival time distribution is misspecified. ResultsOur simulations show that if a previously published study (sample sizes ≥ 60 and censoring proportions ≤ 20 %) reported median and inter-quartile range of survival time, we can obtain a reasonably accurate gamma shape estimate, and use it to design new studies. When true survival time is Weibull-distributed, sample size calculation could be underestimated or overestimated depending on the hazard shape. ConclusionsWe show how to use gamma distribution in designing a single-arm trial, thereby offering more options beyond the exponential and Weibull. We provide a simulation-based assessment to ensure an accurate estimation of the gamma shape and recommend caution to avoid misspecification of the underlying distribution.