Critical Requirement Research Articles

In-vitro sensing of traumatic brain tissue by electrochemical impedance for diagnosis and therapeutic

Traumatic brain injury (TBI) induces neurogenerative disorders affecting severely daily human activities and early diagnosis is a critical requirement for prevention and cure. Here, we induced TBI formation in the Zebra fish, a model organism, by both mechanical (ultrasonic cleaner generated convulsive shock, UGCS) and chemical (pentylenetetrazol, PTZ) methods. The TBI induced cellular and neuronal changes are monitored by measuring the activities of the indicator biomarkers viz., superoxide anion (O2−) and glutamate by electrochemical techniques. For this, the α-lipoic acid (α-LA, LA) functionalized gold-silver (LA-Au/Ag) is used as an electrochemical sensor to diagnose the presence of these markers in physiological phosphate buffer saline (PBS, pH 7.4), 0.1 M KCl solutions and in TBI tissues. While the oxidation of glutamate is observed in the potential window 0.2–0.5 V, the metal mediated oxidation of O2− is observed at the potential window 0.6–1.0 V. The sensor showed good linear ranges for O2− (from 4 to 48 μM with the LOD of 4 μM for the O2− detection) and glutamate (from 20 to 130 μM with the LOD 19 μM). The TBI tissue modified electrode showed lower resistance than the normal brain tissue ((NBT), as control) due to the presence of higher amount of O2− and occurrence of Fenton’s and Heber-Weise’s reactions in the presence of [Fe(CN)6]3−/4−. For theragnostic application, the LA-Au/Ag nanoparticles is delivered into the UGCS and PTZ treated Zebrafish and electrochemical signal changes are monitored by cyclic voltammetry and impedance spectroscopy. Electrochemical data further corroborated with the activities of superoxide dismutase (SOD), Catalase (CAT) and lipid peroxidase (MDA) in parallel. The developed method of electrochemical sensing of TBI may provide alternative for the early TBI diagnosis and therapeutics for the prevention of TBI.

Facilitators and Barriers to Developing a Research Program: A Focused Ethnography of New Tenure-Track PhD-Prepared Nursing Faculty.

Creating a research program is a critical requirement for new PhD-prepared tenure-track nursing faculty in Canada. The purpose of this article is to present key findings of new faculty members focusing on facilitators and barriers to development of their research program. We conducted focused ethnography research examining the experience of 17 new faculty members from across Canada. The following themes were identified: teaching release, preparation from PhD program, intense feelings, supports and processes, mentoring, obtaining grants, and effects of the COVID-19 pandemic. Implications for practice include identifying ways to facilitate faculty retention as they develop their research program. This research will be of interest to deans of nursing and new faculty members.

3D path planning for UAV based on A hybrid algorithm of marine predators algorithm with quasi-oppositional learning and differential evolution

3D path planning is a critical requirement for the autonomy of unmanned aerial vehicle (UAV) navigation systems. In this paper, we propose a novel approach, the differential evolution combined marine predators algorithm (DECMPA), specifically tailored to address the UAV 3D path planning problem in complex scenarios. To handle stringent constraints, DECMPA adopts a multi-step approach. Initially, it utilizes quasi-oppositional learning to generate a more uniformly distributed initial population. Throughout the iterative process, it probabilistically generates quasi-oppositional populations and merges them with existing populations, selecting the superior individuals for the next generation to mitigate local optima. Additionally, DECMPA integrates the variance, crossover, and selection processes of differential evolution into the marine predators algorithm iterations. The greedy selection of test and target vectors further accelerates population convergence. Numerical optimization experiments are conducted using the 10 and 20-dimensional CEC 2021 test suite. Compared to other algorithms, DECMPA exhibits superior solution accuracy and convergence speed, resulting in substantial performance enhancement, thus establishing itself as an efficient algorithm. Furthermore, the adoption of spherical vector coordinates in solution encoding ensures higher quality and facilitates the production of feasible solutions. To verify the effectiveness and practicality of the proposed algorithm, comprehensive path planning simulation experiments are conducted. DECMPA is compared against nine other state-of-the-art heuristic algorithms across six 3D scenarios of varying complexity. The experimental results demonstrate DECMPA’s superiority in terms of optimal cost acquisition, solution quality, and stability. In conclusion, DECMPA presents a promising solution for addressing the challenges of UAV 3D path planning in complex environments. Its innovative approach and superior performance underscore its potential for real-world application in autonomous UAV navigation systems.

One Class of Ideally Secret Autonomous Symmetric Ciphering Systems Based on Wiretap Polar Codes

This paper introduces a class of symmetric ciphering systems with a finite secret key, which provides ideal secrecy, autonomy in key generation and distribution, and robustness against the probabilistic structure of messages (the Ideally Secret Autonomous Robust (ISAR) system). The ISAR system is based on wiretap polar codes constructed over an artificial wiretap channel with a maximum secrecy capacity of 0.5. The system autonomously maintains a minimum level of key equivocation by continuously refreshing secret keys without additional key generation and distribution infrastructure. Moreover, it can transform any stream ciphering system with a finite secret key of known length into an ISAR system without knowing and/or changing its algorithm. Therefore, this class of system strongly supports privacy, a critical requirement for contemporary security systems. The ISAR system’s reliance on wiretap polar coding for strong secrecy ensures resistance to passive known plaintext attacks. Furthermore, resistance to passive attacks on generated refreshing keys follows directly from ideal secrecy and autonomy. The results presented offer an efficient methodology for synthesizing this class of systems with predetermined security margins and a complexity of the order of nlog⁡n, where n is the block length of the applied polar code.

An automatic IoT application placement using an improved equilibrium optimizer algorithm in fog computing

PurposeThe rapid proliferation of Internet of Things (IoT) devices across various domains has created a demand for real-time computing resources that traditional cloud computing models struggle to meet. Fog computing, which brings computation resources closer to IoT devices, has emerged as a promising solution. An automatic service placement framework is needed to use fog computing resources efficiently.Design/methodology/approachIn this study, first a three-layer independent service framework is introduced to define relationships between IoT devices and fog layers, facilitating automatic application deployment. Next, an enhanced version of the equilibrium optimizer (EO) algorithm, inspired by physics, is designed for service placement in fog computing environments.FindingsSimulations reveal that the proposed approach surpasses existing methods, achieving a 99% success rate compared to the closest alternative’s 93%. The algorithm also significantly reduces waiting and planning times for service placement, proving its efficiency and effectiveness in optimizing IoT service deployment in fog computing.Research limitations/implicationsOne of the primary limitations is the computational complexity involved in dynamically adjusting to real-time changes in network conditions and IoT workloads. Although improved EO offers improvements in placement efficiency, it may not be fully optimized for highly fluctuating environments. Another important limitation is the uncertainty in node resources. Fog computing environments often face unpredictable changes in the availability and capacity of resources across nodes. This uncertainty can affect the algorithm’s ability to consistently make optimal decisions for IoT service placement.Practical implicationsFrom a practical perspective, the implementation of the proposed framework and the improved EO algorithm can drastically enhance the efficiency of IoT service deployment in fog computing systems. Organizations that rely on IoT networks, particularly those with critical real-time requirements, can benefit from reduced service placement times and lower failure rates. This can lead to better resource utilization, reduced operational costs and improved overall performance of IoT systems. The commercial impact is evident in industries such as smart cities, healthcare, where fast data processing is crucial.Social implicationsOur proposed framework has important implications for real-world IoT applications, particularly in areas requiring low latency processing, such as healthcare, smart cities. By reducing service delays and optimizing resource allocation, the framework can significantly improve the quality and reliability of services. Additionally, improved resource management leads to cost savings and better system efficiency, making the technology accessible to a wider range of applications.Originality/valueExisting resource placement strategies have shown inadequate performance, highlighting the need for more advanced algorithms. This study introduces a three-layer automatic framework for enhancing the application deployment of a fog system beside a novel improved EO algorithm to offer a robust solution for assigning IoT applications to fog nodes.

Phage cocktail amikacin combination as a potential therapy for bacteremia associated with carbapenemase producing colistin resistant Klebsiella pneumoniae

The increasing occurrence of hospital-associated infections, particularly bacteremia, caused by extensively drug-resistant (XDR) carbapenemase-producing colistin-resistant Klebsiella pneumoniae highlights a critical requirement to discover new therapeutic alternatives. Bacteriophages having host-specific bacteriolytic effects are promising alternatives for combating these pathogens. Among 12 phages isolated from public wastewater in Thailand, two phages-vB_kpnM_05 (myovirus) and vB_kpnP_08 (podovirus) showed broad-host range, producing bacteriolytic activities against 81.3% (n = 26) and 78.1% (n = 25) of 32 XDR carbapenemase-producing colistin-resistant K. pneumoniae, with capsular types—K15, K17, K50, K51, K52/wzi-50 and K2/wzi-2. Both phages showed short replication times, large burst sizes with rapid adsorptions. They exhibited significant stability under various environmental conditions. Genomic analysis revealed that both phages are genetically distinct phages from Myoviridae and Podoviridae family, with the lack of toxin, virulence, lysogeny and antibiotic resistance genes. These characteristics highlighted their promising potential for utilizing in phage therapy for combating XDR K. pneumoniae. Although phage cocktail combining vB_kpnM_05 and vB_kpnP_08 provided significant bacteriolysis for longer duration (8 h) than its monophage (6 h), bacterial regrowth was observed which suggested an evitable development of phage resistance under phages’ selection pressures. Future study will be undertaken to elucidate the precise mechanisms by which these XDR K. pneumoniae developed phage resistance and their associated fitness cost. Remarkably, combining phage cocktail with amikacin at their sub-inhibitory concentrations produced potent synergy by completely suppressing bacterial regrowth in vitro. Our study demonstrated the significant therapeutic and prophylactic effectiveness of a phage cocktail-amikacin combination as a promising alternative strategy for overcoming bacteremia associated with XDR K. pneumoniae having carbapenemase and colistin resistance in vivo.

Self-assembled electrically conductive biocompatible CNF wiring enables 3D-printed microfluidics applications

The emerging field of 3D-printed conductive microfluidics has a range of impactful applications, such as flexible electronics, biomedical diagnostic devices, artificial muscles, actuators, and biofuel cells. Using 3D printing for the related devices solves many problems and offers significant manufacturing advantages. At the same time it poses the unsolved problem when attempting to built electrical wiring into the print, because conductive/non-conductive hybrid 3D-printing using PolyJet technology remains outside reach. To circumvent this problem, we offer an alternative solution based on turning 3D-printed embedded microfluidic channels into electric wiring, by iteratively filling the microchannels with conductive carbon nanofibers (CNFs) suspended in organic solvent, then heating the devices to evaporate the solvent, thereby depositing the CNFs. Herein, we present the experimental procedure and the consecutive electrical measurements that establish an experimental proof-of-principle for the technique. For square microchannels of lateral size ranging from 600μm to 1080μm, the effective electrical conductivity achieved was 20.5 ±1.3Sm−1 for hard chips and 9.6 ±3.4Sm−1 for soft chips. This technique directly enables embedded wiring, a critical requirement for both electrostatic artificial muscles and benthic bacterial biofuel cells. More broadly, the technique enables 3D-printed actuators, flexible electronics, and biomedical devices requiring distributed embedded electric input and/or output. Hence, the presented development has high potential impact in multiple fields.

Robust Anticorrosive Polymer Thin Film for Reliable Protection of Ingestible Devices.

Ingestible devices (ID) provide a safe and noninvasive method for monitoring, diagnosing, and delivering drugs to specific sites in the human body, particularly within the gastrointestinal (GI) tract. However, the GI environment is highly acidic and humid, which can cause IDs to fail, and their corrosion in the acidic environment can cause leaching of toxic metal ions, thereby substantially limiting their long-term use. Thus, an efficient method is required to protect IDs, especially in the chemically and mechanically harsh GI environment. However, an anticorrosive polymer coating that can safeguard IDs in the GI environment without delamination or performance degradation has not been developed to date. The protective layer must satisfy several critical requirements, e.g., high biocompatibility, mechanical durability, and superior anticorrosion performance. This paper reports a highly cross-linked but submicron-thick siloxane-based anticorrosive polymer thin film that can be deposited directly onto IDs without damaging them. The 500 nm-thick cross-linked polymer coating demonstrates exceptional corrosion resistance and chemical and mechanical stability in the GI environment without cytotoxicity. A printed circuit board (PCB) coated with the developed ultrathin protective film sustained performance after exposure to a pH 1.00 phosphate buffered saline solution at 37 °C for 72 h without leaching of metal ions. The ID continued to operate effectively under such challenging conditions; thus, the developed film is suitable for applications that require prolonged functionality, e.g., diagnostics, drug delivery, and continuous health monitoring in the GI tract.

Control Software Engineering Approaches for Cyber-Physical Systems: A Systematic Mapping Study

Cyber-physical systems (CPS), robotics, the Internet of Things (IoT), and automotive systems are integral to modern technology. They are characterized by their safety criticality, accuracy, and real-time control requirements. Control software plays a crucial role in achieving these objectives by managing and coordinating the operations of various sub-systems. This paper presents a novel systematic mapping study (SMS) for control software engineering, analyzing 115 peer-reviewed papers. The study identifies, classifies, and maps existing solutions, providing a comprehensive and structured overview for practitioners and researchers. Our contributions include (i) a unique classification of literature into six research themes—engineering phases, engineering approaches, engineering paradigms, engineering artefacts, target application domains, and engineering concerns; (ii) insights into the specificity of approaches to target technologies and phases; (iii) the prominence of model-driven approaches for design and testing; (iv) the lack of end-to-end engineering support in existing approaches; and (v) the emerging role of agile-based methods versus the dominance of waterfall-based methods. This paper’s significance lies in its thorough analysis and the high-level mapping of the solution space, offering new perspectives and a detailed roadmap for future research and innovation in control software engineering. The findings will guide advancements and best practices in the field, underscoring the paper’s impact.

Hydroxyl and sulfate radicals-based electrochemical advanced oxidation process for treating dye-bearing wastewater – A review

ABSTRACT Dye-bearing wastewater presents a substantial ecological risk. Consequently, there is a critical requirement for efficient treatment strategies. Electrochemical advanced oxidation processes (EAOPs) utilizing hydroxyl and sulfate radicals emerge as viable alternatives to degrade dye pollutants effectively. This review article emphasizes the implementation of EAOPs in the treatment of both synthetic and actual dye-bearing wastewater. The fundamentals, chemistry, and recent developments concerning hydroxyl radicals-based EAOP, including anodic oxidation, electro-Fenton, and sulfate radicals-based EAOP, have been thoroughly reviewed. Furthermore, the article explores the comparative effectiveness of the individual hydroxyl and sulfate radical systems as well as the integrated hydroxyl and sulfate radical systems within a singular electrochemical cell. It has been established that sulfate radicals demonstrate a higher oxidation potential, greater pH adaptability, and a longer half-life in comparison to hydroxyl radicals, making them efficient for dye degradation when assessed against anodic oxidation and electro-Fenton processes. Thus, EAOPs represent a promising technological approach for the remediation of dye-bearing wastewater.

Personalized MRD Assessment in Peri-surgical ctDNA for Prognostic Prediction in Hepatocellular Carcinoma.

Detecting residual disease is a critical clinical requirement in the peri-surgical management of patients with resectable hepatocellular carcinoma (HCC). Previous studies focused on specific genomic regions exhibiting limited sensitivity and failed to meet the minimal residual disease (MRD) testing threshold. We introduce a next-generation sequencing (NGS) based assay, informed by baseline samples, facilitating MRD detection in hepatectomized HCC patients and offering prognostic predictions. This study involved 88 HCC patients who underwent surgical resections January 2016 to May 2016 in Zhongshan Hospital Fudan University. Tumor and normal tissue samples were collected during surgery, while plasma samples were obtained both before surgery and up to seven days post-surgery. Using an NGS-based personalized circulating tumor DNA assay, we analyzed MRD in both pre-surgical and post-surgical blood samples and the correlation with prognosis. With a median follow-up period of 80.7 months, our findings demonstrated significant correlations between pre-surgical ctDNA tumor fractions, post-surgical plasma MRD status, and both recurrence-free survival (RFS) and overall survival (OS). Post-surgical MRD status emerged as the most significant risk factor for cancer recurrence (HR=2.17, 95% CI: 1.09-4.30, p=0.027) compared to other clinical characteristics in multivariate Cox regression analysis. Notably, MRD status showed potential as a prognostic indicator among clinically low-recurrent-risk patients, such as those with BCLC stage 0-A, CNLC stage I-II. Evaluating personalized MRD provided crucial prognostic insights into RFS and OS. It efficiently identified patients at high risk of recurrence, even among those initially perceived as low-risk cases.

Bearing Electrical Erosion Signal Detection Technique Based on Current Signal Analysis for Electric Motors

Abstract In modern industries, enhancing the efficiency and performance of electric motors is a critical requirement. Pulse width modulation (PWM) inverters utilized to enhance the energy efficiency of electric motors generate complex shaft voltages and bearing currents, leading to bearing electrical erosion. This study proposes a new method for detecting high-frequency (HF) circulating current and electric discharge machining (EDM) current signals in bearings for electric motors. The proposed method utilizes common mode voltage (CMV) and bearing current data, analyzing the relationship between these signals. Subsequently, it applies filtering techniques and differentiation for signal preprocessing. The Interquartile Range (IQR) method is used to detect outliers, classify HF circulating current and EDM current signals, and perform time-series data clustering to determine the occurrence frequency and timing of EDM signals. Finally, the implementation outcomes of the proposed method are validated, and its classification efficacy is evaluated and benchmarked against established methodologies through a comprehensive performance analysis. The proposed technique is anticipated to be applicable to the maintenance and prediction of modern electric motors in future developments, contributing to enhanced durability and reliability.

Unveiling Cas8 Dynamics and Regulation within a transposon-encoded Cascade-TniQ Complex.

The Vibrio cholerae Cascade-TniQ complex unveiled a new paradigm in biology, demonstrating that CRISPR-associated proteins can direct DNA transposition. Despite the tremendous potential of "knocking in" genes at desired sites, the mechanisms underlying DNA binding and transposition remain elusive. In this system, a conformational change of the Cas8 protein is essential for DNA binding, yet how it occurs is unclear. Here, structural modeling and free energy simulations reconstruct the Cas8 helical bundle and reveal an open-to-close conformational transition at key steps of the complex's function. We show that when Cascade-TniQ binds RNA, the Cas8 bundle changes conformation mediated by the interaction with the Cas7.1 protein. This interaction alleviates unfavorable contacts and synchronizes Cas8's shift with neighboring subunits, lowering the barrier for the transition to the open state, a critical requirement for DNA binding. As DNA fully pairs with RNA, the open state becomes increasingly accessible, favoring interactions with DNA and aiding the formation of an R-loop. These outcomes provide the first dynamic representation of a critical conformational change in one of the largest CRISPR systems and illustrate its role at critical steps of the Cascade-TniQ biophysical function, advancing our understanding of nucleic acid binding and transposition mechanisms.

An efficient deep reinforcement learning based task scheduler in cloud-fog environment

Efficient task scheduling in cloud and fog computing environments remains a significant challenge due to the diverse nature and critical processing requirements of tasks originating from heterogeneous devices. Traditional scheduling methods often struggle with high latency and inadequate processing times, especially in applications demanding strict computational efficiency. To address these challenges, this paper proposes an advanced fog-cloud integration approach utilizing a deep reinforcement learning-based task scheduler, DRLMOTS (Deep Reinforcement Learning based Multi Objective Task Scheduler in Cloud Fog Environment). This novel scheduler intelligently evaluates task characteristics, such as length and processing capacity, to dynamically allocate computation to either fog nodes or cloud resources. The methodology leverages a Deep Q-Learning Network model and includes extensive simulations using both randomized workloads and real-world Google Jobs Workloads. Comparative analysis demonstrates that DRLMOTS significantly outperforms existing baseline algorithms such as CNN, LSTM, and GGCN, achieving a substantial reduction in makespan by up to 26.80%, 18.84, and 13.83% and decreasing energy consumption by up to 39.60%, 30.29%, and 27.11%. Additionally, the proposed scheduler enhances fault tolerance, showcasing improvements of up to 221.89%, 17.05%, and 11.05% over conventional methods. These results validate the efficiency and robustness of DRLMOTS in optimizing task scheduling in fog-cloud environments.

Imaging system high dynamic range colorimetric calibration method based on a digital chain

Research on high dynamic range (HDR) color management imposes critical requirements on calibration methods between imaging systems and standard radiation. This paper proposes a colorimetric calibration method based on digital chain measurement for imaging systems. First, a HDR colorimetric calibration process model for imaging systems is constructed based on an imaging chain. It includes a light source, target reflectance, optical system parameters, spectral sensitivities, and color matching functions. Subsequently, visual tristimulus values and three-channel response values of an imaging system are obtained using the proposed model in response to the same target, and the target characteristic parameters are adjusted to simulate different HDR imaging scenarios. Following that, various regression algorithms can be employed for HDR colorimetric calibration of imaging systems. The experimental findings demonstrate that the method proposed in this paper boasts a broader dynamic range and denser sampling, thereby enhancing the accuracy of colorimetric characterization models and achieving superior resolution in color measurement.

Energy-efficient design and CNFET implementation of GDI-based ternary prefix adders

Abstract Ternary adders have produced more benefits compared to binary adders i.e., the ternary adder occupies less amount of area as well as produces less interconnect complexity. However, the CMOS implementation of the ternary adders failed to perform the process when the channel length was taken as 32 nm. At 32 nm technology, the CMOS transistors exhibit undesired effects such as Short Channel Effects (SCEs), mobility degradation, high leakage current, etc. Multi-gate devices are preferred to overcome these issues. Carbon Nano-tube Field Effect Transistors (CNFETs) are one of the technologies to work efficiently when the channel length is 32 nm. In this paper, CNFET-based ternary prefix adders are designed. Power consumption is the most critical requirement for the VLSI system, as it enhances energy efficiency and reduces heat dissipation. One way to achieve this power reduction is by minimizing the number of transistors employed in the adder circuits. This study employed a reduction technique known as Gate Diffusion Input (GDI) logic included in the proposed prefix adder design. The overall experimental investigation is done with the help of the HSPICE supporting platform. The proposed adder improved by reducing the power by up to 83%, energy by up to 83%, current by up to 78%, and delay by up to 96%. Finally, the Power Delay product (PDP) was also reduced by 84% compared to existing ternary adders. The proposed design proves to be highly effective in implementing the neuron structure, with the corresponding parameters thoroughly analysed and well-documented in this study.

Optimizing Multiparametric MRI Protocols for Prostate Cancer Detection: A Comprehensive Assessment Aligned with PI-RADS Guidelines.

Multiparametric magnetic resonance imaging (mpMRI) is recognized as the most indicative method for diagnosing prostate cancer. The purpose of this narrative review is to provide a comprehensive evaluation aligned with the Prostate Imaging and Reporting Data System (PI-RADS) guidelines, offering an in-depth insight into the various MRI sequences used in a standard mpMRI protocol. Additionally, it outlines the critical technical requirements necessary to perform a standard mpMRI examination of the prostate, as defined by the PI-RADS specifications. European Society of Urogenital Radiology has released PI-RADS guideline detailing its suggestions aimed at improving the standards of the procedure. The purpose of this guideline is to establish a standard strategy for MRI protocols and image interpretation, aiming to prevent variability in each of the imaging and interpretation stages. A standard mpMRI protocol comprises morphological sequences and functional sequences. Morphological sequences which encompass T1- and T2-weighted images, and various functional sequences include diffusion-weighted imaging, and dynamic contrast-enhanced MRI. The PI-RADS recommendations assert that having a standard and uniform protocol for all MRI centers is imperative. Furthermore, the existence of a standardized checklist for interpreting MRI images can foster greater consensus in the process of diagnosing and treating patients. Standardized protocols and checklists for mpMRI interpretation are essential for achieving greater consensus among radiologists, ultimately leading to improved diagnostic outcomes in prostate cancer.

Quantification and spatial analysis of gridded (0.1° × 0.1°) emission of indirect GHGs/Air pollutants from anthropogenic sources in India

Indirect greenhouse gases (GHGs) play a key role in modulating both regional and global atmospheric chemistry and act as air pollutants that degrade air quality. The rising number of premature deaths and notable health hazards could be linked to increasing concentration of these air pollutants in the atmosphere. As a developing nation, India is often regarded as one of the most polluting countries due to increasing anthropogenic activities. Therefore, identifying the sources of these indirect GHGs gases such as CO, NOx, VOC and SO2 and quantifying their emissions has become a critical requirement for understanding regional atmospheric chemistry. In this study, we developed a comprehensive, technology-driven gridded emission inventory for India at a high resolution (0.1°×0.1°) for the base year 2020. Using the IPCC bottom-up approach, the study estimated the total emissions of CO (45 Tg/yr), NOx (22.8 Tg/yr), VOC (10.8 Tg/yr) and SO2 (15.1 Tg/yr) from all the dominating sources. Vehicle exhaust contributes the most NOx and VOC whereas the residential and power sectors are the highest emitters of CO and SO2, respectively. This newly reported surface emission data would be an essential tool for policymakers in formulating mitigation strategies and will also serve as a vital input for atmospheric chemistry and climate studies.

Reconfigurable dual-mode meta-waveguide

With the rapid growth of information flux, integrating more channels in limited spaces has been a critical requirement for highly-integrated long-range parallel transmissions. Although meta-waveguides, such as spoof surface plasmon polariton (SSPP) waveguides, can suppress crosstalk between adjacent channels, it is still urgent to seek new methods to further increase the number of channels without occupying additional space. Here, we propose a reconfigurable dual-mode meta-waveguide (RDMMW) by integrating diodes into meta-units, which supports two independent channels using two orthogonal modes. The RDMMW can be switched among dual-mode, even-mode, odd-mode and cutoff states by controlling the diodes, which provides more freedom to manipulate the channel features. The RDMMW possess two outstanding merits in highly-integrated long-range parallel transmissions, including lower coupling between two channels than conventional single-mode waveguides and constant mode coupling in longer waveguides. Thus the proposed RDMMW has advantages of multi-mode, reconfiguration, low coupling and high integration density, providing a new avenue to realize highly-integrated multi-functional systems.

Extrusion‐Based Additive Manufacturing of Cranial Implants Using High‐Performance Polymers: A Comparative Study on Mechanical Performance and Dimensional Accuracy

Fused filament fabrication (FFF) offers great potential to fabricate patient‐specific implants to treat large size defects resulting from craniectomy. Such cranial implants impose critical requirements on material and design. So far, the field has focused on printing cranial implants from polyetheretherketone (PEEK), which is semicrystalline in nature and, therefore, not ideal for FFF because of warping and nonhomogeneous crystallization. Consequently, this work aims at exploring alternative amorphous high‐performance polymers. The tensile and flexural mechanical properties of printed samples from PEEK, polyetherketoneketone (PEKK), and polyphenylsulfone (PPSU) according to ISO standards are compared. Testing of specimens obtained from three orthogonal build directions reveals nearly isotropic mechanical behavior (e.g. ultimate tensile strength differed no more than 8% between print orientations). This enables printing of patient‐specific cranial implants in vertical orientation with minimal support structures, which result in dimensional accuracies in the clinically acceptable range for craniofacial reconstructions. Mechanical assessment via an in‐house designed indentation set‐up shows that both PEKK and PPSU should be considered valid alternatives to PEEK for cranial implants. This work showcases the maturity of FFF for high‐performance polymers and leverages it for complex patient‐specific geometries such as a cranial implant.