Versatile Environment Research Articles

Metal‐Organic Cages: Synthetic Strategies and Photocatalytic Application

AbstractMetal‐organic cages (MOCs) are a class of compounds formed through the coordination of metal ions with organic ligands to create well‐defined and cage‐like structure. These unique structures offer versatile environments for catalyzing a wide range of chemical reactions. The catalytic capabilities of MOCs are significantly influenced by the nature of the metal ions, functional ligands, and the cage structure. Notably, the confined spaces within MOCs can lead to enhanced reaction efficiencies, particularly in processes such as light‐induced hydrogen generation and the photocatalytic reduction of CO₂. Furthermore, MOCs show great potential in photo‐organic synthesis due to the cage structure, which provides a confined environment and allows for encapsulating organic molecules, making them useful for improving the selectivity and efficiency of catalytic process. This review reports the development of MOCs for photocatalysis, focusing on the structural design and regulation strategy to build functional MOCs for photocatalytic hydrogen production, CO2 reduction, organic transformation. Insights into the photocatalysis are discussed including the challenges and further research direction in MOC‐based photocatalysis.

Imperative Genetic Programming

Genetic programming (GP) has a long-standing tradition in the evolution of computer programs, predominantly utilizing tree and linear paradigms, each with distinct advantages and limitations. Despite the rapid growth of the GP field, there have been disproportionately few attempts to evolve ’real’ Turing-like imperative programs (as contrasted with functional programming) from the ground up. Existing research focuses mainly on specific special cases where the structure of the solution is partly known. This paper explores the potential of integrating tree and linear GP paradigms to develop an encoding scheme that universally supports genetic operators without constraints and consistently generates syntactically correct Python programs from scratch. By blending the symmetrical structure of tree-based representations with the inherent asymmetry of linear sequences, we created a versatile environment for program evolution. Our approach was rigorously tested on 35 problems characterized by varying Halstead complexity metrics, to delineate the approach’s boundaries. While expected brute-force program solutions were observed, our method yielded more sophisticated strategies, such as optimizing a program by restricting the division trials to the values up to the square root of the number when counting its proper divisors. Despite the recent groundbreaking advancements in large language models, we assert that the GP field warrants continued research. GP embodies a fundamentally different computational paradigm, crucial for advancing our understanding of natural evolutionary processes.

Integrating deep learning, MATLAB, and advanced CAD for predictive root cause analysis in PLC systems: A multi-tool approach to enhancing industrial automation and reliability

The integration of Deep Learning (DL), MATLAB, and Advanced Computer- Aided Design (CAD) in the root cause analysis of prognostic errors in Programmable Logic Controller (PLC) systems represents a significant advancement in industrial automation and reliability. This research explores the synergistic application of these technologies to diagnose, predict, and mitigate failures in PLC systems, which are critical for controlling automated processes in various industries. By employing DL algorithms, the study enhances predictive maintenance capabilities, allowing for early detection of anomalies and reducing downtime. MATLAB is utilized as the central platform for data processing, algorithm development, and simulation, providing a versatile environment for integrating DL models with real-time data from PLCs. Advanced CAD tools are employed to model and visualize the physical systems controlled by the PLCs, offering a comprehensive view that bridges the gap between digital analysis and physical implementation. The research methodology includes data collection from PLC systems, DL model training and validation, MATLAB-based simulations, and CAD modelling. The findings demonstrate improved accuracy in identifying the root causes of PLC prognostic errors, leading to more efficient maintenance strategies and enhanced system reliability. This paper concludes that the integration of DL, MATLAB, and CAD provides a powerful approach for advancing predictive maintenance in industrial settings, ultimately contributing to greater operational efficiency and cost savings.

Design Considerations for Virtual Reality Intervention for People with Intellectual and Developmental Disabilities: A Systematic Review.

This systematic review aims to explore virtual reality (VR) applications for rehabilitation purposes among people with intellectual and developmental disabilities (IDD), identify their effects on rehabilitation outcomes, explore themes to consider in VR intervention design, and provide guidance for designers and researchers in creating therapeutic environments using VR technology. VR has gained increasing attention in healthcare settings to assist in achieving rehabilitation goals for people with IDD. VR is particularly advantageous since it simulates the real world while providing controllable, safe, and versatile environments. It is necessary to expand the current body of knowledge on VR intervention's outcomes by synthesizing further information on VR application characteristics as well as identifying design considerations regarding feasibility, usability, safety, and other aspects that will benefit future VR intervention design and research. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framed the current review. Multiple databases were searched to identify studies published between 2001 and 2023. The review qualitatively organized VR environment design considerations according to three themes: feasibility, usability, and safety. This review included 27 articles and included 868 participants. The overall findings indicated that VR interventions are promising in enhancing rehabilitation outcomes among people with IDD, such as physical, cognitive, emotional, and functional independence domains. This review provides design recommendations to create effective, usable, and safe VR interventions for individuals with IDD. The suggested design implications should be applied with the awareness that VR is a relatively emerging technology with rapidly evolving features.

Optimized preparation of La3Mn2O7 with superior lattice oxygen mobility and adsorbed oxygen utilization for catalytic removal of toluene

The R-P type layered perovskite La3Mn2O7 (LLM) is considered a more promising toluene oxidation catalyst than perovskite LaMnO3 (LMO) due to the versatile environment it provides for oxygen atoms, yet the challenge of realizing an optimal synthesis route remains. Herein, we revealed how calcination temperature influenced the structure–activity relationship and the mechanism by which the layered structure enhanced oxygen species reactivity. LLM700 possesses optimal toluene adsorption performance, oxygen species activation capability and low-temperature reducibility, thus exhibiting the highest catalytic activity (T90 = 283 °C) among single layered perovskite catalysts. The large interlayer gaps in the layered structure, combined with the weaker Mn-O bond strength near the layered structure, facilitate the easy removal of oxygen atoms, creating oxygen vacancies that act as pathways for oxygen ions to migrate within the lattice. Together, these factors enable the layered structure to enhance the mobility of lattice oxygen and the utilization of adsorbed oxygen, making LLM an ideal model for catalyzing the oxidation of toluene. Furthermore, the possible reaction pathway for the oxidation of toluene on LLM700 was inferred using GC–MS. This work paves the way for the catalytic applications of layered perovskites.

IQuantum: A toolkit for modeling and simulation of quantum computing environments

SummaryQuantum computing resources are predominantly accessible through cloud services, with a potential future shift to edge networks. This paradigm and the increasing global interest in quantum computing have amplified the need for efficient, adaptable resource management strategies and service models for quantum systems. However, many limitations in the quantum resources' quantity, quality, availability, and cost pose significant challenges for conducting research in practical environments. To address these challenges, we proposed iQuantum, a holistic and lightweight discrete‐event simulation toolkit uniquely tailored to model hybrid quantum computing environments. We also present a detailed system model for prototyping and problem formulation in quantum resource management. Through rigorous empirical validation and evaluations using large‐scale quantum workload datasets, we demonstrate the flexibility and applicability of our toolkit in various use cases. iQuantum provides a versatile environment for designing and evaluating quantum resource management policies such as quantum task scheduling, backend selection, hybrid task offloading, and orchestration in the quantum cloud‐edge continuum. Our work endeavors to create substantial contributions to quantum computing modeling and simulation, empowering the creation of future resource management strategies and quantum computing's broader applications.

Advancing nerve regeneration: Peripheral nerve injury (PNI) chip empowering high-speed biomaterial and drug screening

Peripheral nerve injuries (PNIs) represent a significant challenge in regenerative medicine, often leading to long-term functional impairments. In this study, we introduce the peripheral nerve injury-on-a-chip (PNI chip), a cutting-edge platform designed for high-speed screening of biomaterials and drugs to enhance peripheral nerve regeneration. The PNI chip combines aligned nanofibers as topographical cues with microfluidic technology to create a controlled and versatile environment for investigating key factors influencing axonal growth and regeneration. Our study reveals that density of aligned nanofibers plays a pivotal role in axonal regeneration regarding regeneration velocity and the recovery of damaged axonal areas. Additionally, we investigate the dynamic interactions between regenerating axons and aligned nanofibers, shedding light on the adaptability of axonal growth cones to topographical cues. Moreover, the PNI chip serves as a potent tool for drug screening, as demonstrated by our evaluation of paclitaxel and M1. Paclitaxel exhibits concentration-dependent effects, while M1, a mitochondria fusion promoter, substantially enhances axonal growth velocity, emphasizing the potential of mitochondria dynamics as a target for improving nerve regeneration. The PNI chip represents a breakthrough in peripheral nerve regeneration research, offering the means to systematically explore nanofiber parameters and drug interventions in a controlled and high-throughput manner.

Participatory curriculum development: The case of EUTOPIA, a European university alliance

AbstractThis paper reports on a model for participatory curriculum development that builds on a ‘connected learning communities’ (CLC) approach. We describe and analyse the trajectory of six CLC‐cases using a framework informed by Social Practice Theory (SPT). The activities we report on took place during the first pilot year (2020–2021) of a transnational University Alliance involving six European universities. Data were drawn from document analysis, direct observations and ongoing dialogue with students and staff involved in the CLCs. Our findings illustrate the affordances of building on existing practice for curriculum development in international contexts and point out the importance of well‐equipped collaborative environments that encourage critical analysis and active experimentation. We found that the CLC model and SPT framework are helpful contributions in the field of curriculum development and argue that connected curriculum‐making approaches help shape versatile environments that can effectively transform and enhance educational provisions, experiences and outcomes.

Experimental capabilities for liquid jet samples at sub-MHz rates at the FXE Instrument at European XFEL.

The Femtosecond X-ray Experiments (FXE) instrument at the European X-ray Free-Electron Laser (EuXFEL) provides an optimized platform for investigations of ultrafast physical, chemical and biological processes. It operates in the energy range 4.7-20 keV accommodating flexible and versatile environments for a wide range of samples using diverse ultrafast X-ray spectroscopic, scattering and diffraction techniques. FXE is particularly suitable for experiments taking advantage of the sub-MHz repetition rates provided by the EuXFEL. In this paper a dedicated setup for studies on ultrafast biological and chemical dynamics in solution phase at sub-MHz rates at FXE is presented. Particular emphasis on the different liquid jet sample delivery options and their performance is given. Our portfolio of high-speed jets compatible with sub-MHz experiments includes cylindrical jets, gas dynamic virtual nozzles and flat jets. The capability to perform multi-color X-ray emission spectroscopy (XES) experiments is illustrated by a set of measurements using the dispersive X-ray spectrometer in von Hamos geometry. Static XES data collected using a multi-crystal scanning Johann-type spectrometer are also presented. A few examples of experimental results on ultrafast time-resolved X-ray emission spectroscopy and wide-angle X-ray scattering at sub-MHz pulse repetition rates are given.

Prediction and Rationalization of Abundant C-N-H Molecules in Different Environments.

The extreme chemical diversity of CmNnHk molecules is at the same time very important (central in organic chemistry) and difficult to rationalize in the sense that some molecules are abundant and easy to synthesize, while others are rare and difficult to make. Using the recently developed criteria of molecular "magicity", combined with evolutionary structure prediction and quantum-chemical calculations, we study these molecules in a wide range of compositions (0 ≤ m ≤ 13, 0 ≤ n ≤ 4, and 0 ≤ k ≤ 14). "Magic" molecules are defined as those that are lower in energy than any isochemical mixture of molecules with the nearest compositions. The predicted "magic" molecules are in good agreement with compounds found in versatile environments (interstellar and circumstellar media, Titan's lower atmosphere, and crude oil fractions) and in experimental chemistry. This work shows the predictive power of our approach, capable of predicting and explaining stable molecules in complex systems.

Impact of trans-Planckian excitations on black-hole radiation in dipolar condensates

We consider a quasi-one-dimensional dipolar condensate in a steplike analog black hole setup. It is shown that the existence of roton excitations leaves significant imprints onto the Hawking radiation spectrum. The emitted radiation depends on the depth of the roton minimum, and is in general more intense. In addition, we find a novel spontaneous particle creation mechanism with no counterpart in nondipolar condensates. Our results establish that dipolar condensates offer a richer and more versatile environment for the simulation of particle production from the quantum vacuum in the presence of horizon interfaces than contact-interaction condensates.

A NetHack Learning Environment Language Wrapper for Autonomous Agents

This paper describes a language wrapper for the NetHack Learning Environment (NLE) [1]. The wrapper replaces the non-language observations and actions with comparable language versions. The NLE offers a grand challenge for AI research while MiniHack [2] extends this potential to more specific and configurable tasks. By providing a language interface, we can enable further research on language agents and directly connect language models to a versatile environment.

Family doctors' and dentists' access and dissemination of medical information through social media.

The study purpose is to analyze how doctors in contract with the Health Insurance House in Romania use social media (SM) to access and disseminate medical information. Family doctors and dentists who had a contract with the Romanian National Health Insurance House during the year 2017 represented the targeted sample. Eight thousand four hundred ninety-seven e-mail addresses and 5,422 telephone numbers were identified and collected from the National Health Insurance House web page. The invitation to participate in the study (including the link to the online questionnaire) was sent via SMS, WhatsApp, and /or e-mail from 24 May to 14 July 2017. The experimental design was cross-sectional. In the statistical analysis the following generations were defined: "Baby Boomers", aged between 51-70 years, Generation X as people aged 38-51, and Millennials under 38 years. One hundred and twenty valid questionnaires were analyzed. The profile of the respondent was: woman (61%), from urban (71%), and specialist (50%) working in a private practice (70%). The majority of respondents use Facebook (85%). Generation X connect more to SM from public places than Baby Boomers (p = 0.007). Respondent doctors seek medical information on SM monthly (83%), but rarely give advice through SM to colleagues (28%) or contribute to patients' medical education (32%). Most physicians interact with their patients through SM (59%), but do not discuss with them how to search for health information. Social media has low professional usage among the respondents who perform their medical activity in Romania and is mainly used to search for medical information, but it does not contribute to patients' medical education. As expected, age is a factor that determines the susceptibility of SM usage.

Development of simulation model of smart phase selector device

In the quest for efficient and reliable power distribution systems, voltage asymmetry has emerged as a significant challenge. Voltage imbalances across different phases can lead to increased energy losses, compromised power quality, and reduced equipment lifespan. To address these issues, smart phase selector devices have gained attention as advanced electronic solutions for monitoring and managing voltage imbalances in low-voltage networks. This paper presents the development of a simulation model of a smart phase selector device using the Proteus software platform. Proteus offers a versatile environment for simulating electronic circuits and systems, making it an ideal choice for developing and evaluating the performance of the smart phase selector device. The primary objective of this research is to create a comprehensive simulation model that accurately represents the behavior and functionality of the smart phase selector device. Through a thorough literature review, the key principles and concepts underlying smart phase selector devices, voltage asymmetry, and related simulation techniques are explored. The developed simulation model incorporates the necessary circuit components, algorithms, and control mechanisms to faithfully simulate the operation of the smart phase selector device.

PocketOptimizer 2.0: A modular framework for computer-aided ligand-binding design.

The ability to design customized proteins to perform specific tasks is of great interest. We are particularly interested in the design of sensitive and specific small molecule ligand-binding proteins for biotechnological or biomedical applications. Computational methods can narrow down the immense combinatorial space to find the best solution and thus provide starting points for experimental procedures. However, success rates strongly depend on accurate modeling and energetic evaluation. Not only intra- but also intermolecular interactions have to be considered. To address this problem, we developed PocketOptimizer, a modular computational protein design pipeline, that predicts mutations in the binding pockets of proteins to increase affinity for a specific ligand. Its modularity enables users to compare different combinations of force fields, rotamer libraries, and scoring functions. Here, we present a much-improved version--PocketOptimizer 2.0. We implemented a cleaner user interface, an extended architecture with more supported tools, such as force fields and scoring functions, a backbone-dependent rotamer library, as well as different improvements in the underlying algorithms. Version 2.0 was tested against a benchmark of design cases and assessed in comparison to the first version. Our results show how newly implemented features such as the new rotamer library can lead to improved prediction accuracy. Therefore, we believe that PocketOptimizer 2.0, with its many new and improved functionalities, provides a robust and versatile environment for the design of small molecule-binding pockets in proteins. It is widely applicable and extendible due to its modular framework. PocketOptimizer 2.0 can be downloaded at https://github.com/Hoecker-Lab/pocketoptimizer.

Plating of Ion‐Exchange Membranes: A Molecular Dynamics Study

AbstractElectroless plating of membranes offers a viable pathway to create flexible electrodes for soft sensors and actuators, as well as flexible electronics and batteries. Ionic polymer metal composites are a promising class of active materials, realized through electroless plating of ion‐exchange membranes. The plating and electrode‐membrane interface play a key role on their performance, but computational tools to inform the selection of the plating material and optimize the plating process are currently lacking. Here, this gap is filled through the study of the electrode‐membrane interface in different types of ion‐exchange membranes via molecular dynamics simulations. Both commercially available cation‐ and research‐grade anion‐exchange membranes are studied here. For platinum coating, it is predicted that cation‐exchange membranes will have a superior interface than anion‐exchange membranes, in terms of metal penetration into the membrane, reliability of actuation performance, and interface stability. The results are in line with previous endeavors documenting the higher stability of the interface for cation‐ than for anion‐exchange membranes, easier plating processes, and better electrochemical performance when working with cation‐exchange membranes. The proposed computational framework offers a versatile environment for testing different types of coatings for specific membranes, toward optimizing the performance of electrochemical devices with plated flexible electrodes.

The International Space Station Environment Triggers Molecular Responses in Aspergillus niger.

Due to immense phenotypic plasticity and adaptability, Aspergillus niger is a cosmopolitan fungus that thrives in versatile environments, including the International Space Station (ISS). This is the first report of genomic, proteomic, and metabolomic alterations observed in A. niger strain JSC-093350089 grown in a controlled experiment aboard the ISS. Whole-genome sequencing (WGS) revealed that ISS conditions, including microgravity and enhanced irradiation, triggered non-synonymous point mutations in specific regions, chromosomes VIII and XII of the JSC-093350089 genome when compared to the ground-grown control. Proteome analysis showed altered abundance of proteins involved in carbohydrate metabolism, stress response, and cellular amino acid and protein catabolic processes following growth aboard the ISS. Metabolome analysis further confirmed that space conditions altered molecular suite of ISS-grown A. niger JSC-093350089. After regrowing both strains on Earth, production of antioxidant—Pyranonigrin A was significantly induced in the ISS-flown, but not the ground control strain. In summary, the microgravity and enhanced irradiation triggered unique molecular responses in the A. niger JSC-093350089 suggesting adaptive responses.

The Fight against Infectious Diseases: The Essential Role of Higher-Order Thinking and Problem-Solving.

The development of a vaccine marks a breakthrough in the fight against infectious diseases. However, to eradicate highly infectious diseases globally, the immunization of large parts of the population is needed. Otherwise, diseases, such as polio, measles, or more recently COVID-19, will repeatedly flare-up, with devastating effects on individuals and, in the worst case, on significant shares of the world population. For example, polio has been almost eradicated over the past three decades through an unprecedented global effort, but complete immunization has not yet been achieved. In this article, we use polio as an example to show how the global effort of developing and administering a vaccine can be understood as solving a complex problem since it involves cultural, political, and geographical barriers that demand solutions in dynamically changing and highly versatile environments. Referring to the literature on problem-solving, higher-order thinking, and complex reasoning, we demonstrate how the ability to deal with real-world environments that are complex and dynamically changing, adapting initial solutions to new circumstances and collaborate efficiently with others, has been essential for this endeavor. We argue that problem-solving abilities form one basis for solving consequential world problems.

Mechanistic Understanding of Gordonia sp. in Biodesulfurization of Organosulfur Compounds.

Although conventional oil refining process like hydrodesulfurization (HDS) is capable of removing sulfur compounds present in crude oil, it cannot desulfurize recalcitrant organosulfur compounds such as dibenzothiophenes (DBTs), benzothiophenes (BTs), etc. Biodesulfurization (BDS) is a process of selective removal of sulfur moieties from DBT or BT by desulfurizing microbes. Therefore, BDS can be used as a complementary and economically feasible technology to achieve deep desulfurization of crude oil without affecting the calorific value. In the recent past, members of biodesulfurizing actinomycete genus Gordonia, isolated from versatile environments like soil, activated sludge, human beings etc. have been greatly exploited in the field of petroleum refining technology. The bacterium Gordonia sp. is slightly acid-fast and has been used for unconventional but potential oil refining processes like BDS in petroleum refineries. Gordonia sp. is unique in a way, that it can desulfurize both aliphatic and aromatic organosulfurs without affecting the calorific value of hydrocarbon molecules. Till date, approximately six different species and nineteen strains of the genus Gordonia have been recognized for BDS activity. Various factors such as enzyme specificity, availability of essential cofactors, feedback inhibition, toxicity of organic pollutants and the oil-water separations limit the desulfurization rate of microbial biocatalyst and influence its commercial applications. The current review selectively highlights the role of this versatile genus in removing sulfur from fossil fuels, mechanisms and future prospects on sustainable environment friendly technologies for crude oil refining.

Enhanced IR Radiative Cooling of Silver Coated PA Textile.

Smart textile with IR radiative cooling is of paramount importance for reducing energy consumption and improving the thermal comfort of individuals. However, wearable textile via facile methods for indoor/outdoor thermal management is still challenging. Here we present a novel simple, yet effective method for versatile thermal management via silver-coated polyamide (PA) textile. Infrared transmittance of coated fabric is greatly enhanced by 150% due to the multi-order reflection of silver coating. Based on their IR radiative cooling, indoors and outdoors, the skin surface temperature is lower by 1.1 and 0.9 °C than normal PA cloth, allowing the textile to be used in multiple environments. Moreover, the coated fabric is capable of active warming up under low voltage, which can be used in low-temperature conditions. These promising results exemplify the practicability of using silver-coated textile as a personal thermal management cloth in versatile environments.