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Overlayer structures in bimetallic catalysts are relevant to a variety of catalytic reactions, particularly in electrocatalysis for fuel cell applications. Previous computational studies largely consider these overlayer structures to be those of a pseudomorphic overlayer, where there is a 1:1 atomic ratio between the overlayer and the support metal. Our previous work based on density functional theory (DFT) has shown that there exist nonstoichiometric overlayer structures that are more stable than the stoichiometric ones. In this work, we developed a graph neural network interatomic potential (GNN-IP) to analyze structures formed in Pt overlayers on Au(111). The GNN-IP was used to explore properties of nonstoichiometric overlayers at length scales that are prohibitively expensive to pursue with planewave DFT calculations. In particular, we examined large Pt islands on top of a 48 × 48 Au(111) unit cell to explore the influence of the rotational angle (α) between the Pt overlayer and support Au(111) on both the stability of and the preferred atomic density in the overlayer. Island structures with smaller rotational angles between the Pt overlayer and Au(111) tend to be more stable. Further, smaller rotational angles tend to result in lower atomic density in the Pt overlayer.

Biomass has been highlighted as an increasingly important renewable alternative energy source. Nonrenewable conventional energy sources covering global energy demands are processed to form solid, liquid, and gaseous hydrocarbons. Their environmental impact has led to the exploration of different types of biomasses for their potential to be used as raw materials. The present work reviews thermochemical processes, including pyrolysis, gasification, liquefaction, and torrefaction, on the conversion of biomass and plastic waste to gas, liquid, and solid fuels and chemicals. Upgrading some of the characteristics of bio-oil with various technologies has increased the interest in commercializing the usage of biomass in applications. In addition, biological conversion of biomass using second-generation feedstock instead of first-generation feedstock has decreased the cost and competition with food crops. The pretreatment of biomass using physical, chemical, physicochemical, and biological technologies is a typical process before biological conversion. Moreover, this work discusses biofuel production using syngas as feedstock through the Fischer–Tropsch process and organic acids as a feedstock for oleaginous microorganisms, including many species of yeast, bacteria, and algae.

The development of flexible phased array systems has drawn significant interest due to their adaptive beam steerability and deployable structures to support various platforms virtually on every conformal surface. Additively manufactured tile-based phased array offers a lightweight, flexible, and massively scalable solution with reduced cost and fabrication time. The main challenge for such conformal phased array systems is to maintain array performance under various deformations, which requires calibration of the amplitude and/or phase distribution of the antenna elements. To address this challenge, a computer vision-enabled on-the-fly adaptive shape calibration and phase correction method is proposed. The authors introduce the usage of smartphones, with integrated 3-D depth cameras and infrared (IR) sensors, and a novel computer vision algorithm to detect the bend angles between neighboring subarray tiles. A $2 \times $ additively manufactured tile-based flexible phased array is utilized as a proof-of-concept (POC) prototype to demonstrate the calibration approach. The proposed algorithm achieves a very good <1° angular prediction accuracy and demonstrates successful calibration of the phased array under 15°, 30°, and 45° bend angles under both symmetrical and asymmetrical configurations with improvements of gain as much as 7 dB. The calibrated bent phased arrays can also achieve a maximum steering range of 110°. This approach presents a highly accurate and cost-effective calibration process that can enable massive fabrication and implementation of tile-based flexible phased arrays for next-generation 5G/mmWave wearable and conformal smart skin, Internet of Things (IoT), Industry 4.0, and massive multiple-input multiple-output (MIMO) applications.

The incidence of recurrent peritonsillar abscess (7.4–22%) was estimated in retrospective studies. The aim of this prospective study was to estimate the cumulative incidence of recurrent peritonsillar abscess and related risk factors.

In this study, we introduce a novel antenna design method for superdirective antennas that combines low complexity with high radiation efficiency, while being impedance-matched to $50~\Omega $ . We applied this approach to design, fabricate, and measure a superdirective antenna array (SDA) with a high realized antenna gain (i.e., 6.3 dBi) and radiation efficiency (i.e., 99.3%), consisting of two strip dipole elements operating at a frequency of 3.5 GHz. The fabricated antenna has an electrical size of 1.55, underscoring its compactness in addition to its high gain. Our approach is distinguished by its ability to achieve high directivity and radiation efficiency, along with impedance-matching to $50~\Omega $ , through meticulous adjustments of the strip dimensions (i.e., length and width) and the phase difference between elements. This method eliminates the need for external impedance-matching networks, amplifiers, attenuators, parasitic elements, or loads, marking a significant advancement in the development of practical superdirective antenna designs.

A key design decision for data systems is whether they follow the row-store or the column-store paradigm. The former supports transactional workloads, while the latter is better for analytical queries. This decision has a significant impact on the entire data system architecture. The multiple-decade-long journey of these two designs has led to a new family of hybrid transactional/analytical processing (HTAP) architectures. Several efforts have been proposed to reap the benefits of both worlds by proposing systems that maintain multiple copies of data (in different physical layouts) and convert them into the desired layout as required. Due to data duplication, the additional necessary bookkeeping, and the cost of converting data between different layouts, these systems compromise between efficient analytics and data freshness. We depart from existing designs by proposing a radically new approach. We ask the question: “What if we could access any layout and ship only the relevant data through the memory hierarchy by transparently converting rows to (arbitrary groups of) columns?” To achieve this functionality, we capitalize on the reinvigorated trend of hardware specialization (that has been accelerated due to the tapering of Moore's law) to propose Relational Fabric, a near-data vertical partitioner that allows memory or storage components to perform on-the-fly transparent data transformation. By exposing an intuitive API, Relational Fabric pushes vertical partitioning to the hardware, which profoundly impacts the process of designing and building data systems. (A) There is no need for data duplication and layout conversion, making HTAP systems viable using a single layout. (B) It simplifies the memory and storage manager that needs to maintain and update a single data layout. (C) It reduces unnecessary data movement through the memory hierarchy allowing for better hardware utilization and, ultimately, better performance. In this paper, we present Relational Fabric for both memory and storage. We present our initial results on Relational Fabric for in-memory systems and discuss the challenges of building this hardware and the opportunities it brings for simplicity and innovation in the data system software stack, including physical design, query optimization, query evaluation, and concurrency control.

Emerging additive manufacturing (AM) technologies, specifically additively manufactured electronics (AME), 4-D printing, and origami, are reshaping the design capabilities and functionalities of contemporary electronic devices. Cutting-edge 3-D/4-D printing technologies facilitate the prototyping and realization of complex electronic functions that are challenging to conventional methods. This article provides a comprehensive overview of the evolving techniques in AME, 4-D printing, and origami, employing multimaterials (conductive and dielectric materials) and shape-memory materials (SMMs) to fabricate functional electronic components and devices. Additionally, the overview delves into the state-of-the-art AME and 4-D-printed electronic components across diverse fields, including biomedical electronics, space engineering, and the advancements in the next-generation wireless communications and sensing.

This article describes sensors and radio frequency (RF) components manufactured by applying selective-metallization processes (metal foil tape, liquid metal filling, electro and electroless plating, and surface embossing) to 3-D-printed and flexible dielectric substrates. All these technologies can be implemented at room temperature, thus enabling the adoption of unconventional materials and biopolymers with low glass transition temperatures. In this article, we also describe how the above technologies are used to manufacture wireless transponders for tracking and sensing applications. Several examples of RF components are reported, including antennas, beamforming networks, Doppler radars, and wireless passive transponders based on backscatter radio. Innovative circuit design approaches (such as the via-less approach) are presented and their impact on circuit manufacturing and recyclability is discussed.

The objective of this study was to compare the effectiveness of a second tumor necrosis factor inhibitor (TNFi) versus a non‐TNFi biologic following discontinuation of a TNFi for patients with polyarticular‐course juvenile idiopathic arthritis (pJIA). Using the Childhood Arthritis and Rheumatology Research Alliance Registry, patients with pJIA who started receiving a second biologic following a first TNFi were identified. Patients were required to have no active uveitis on the index date and a visit six months after the index date. Outcome measures included Clinical Juvenile Arthritis Disease Activity Score with a maximum of 10 active joints (cJADAS10), cJADAS10 inactive disease (ID; ≤2.5) and cJADAS10 minimal disease activity (MiDA; ≤5). Multiple imputation was used to account for missing data. Adjusted odds ratios (aORs) were calculated using propensity score quintiles to compare outcomes at six months following second biologic initiation. There were 216 patients included, 84% initially received etanercept, and most patients stopped receiving it because of its ineffectiveness (74%). A total of 183 (85%) started receiving a second TNFi, and 33 (15%) started receiving a non‐TNFi. Adalimumab was the most common second biologic received (71% overall, 84% of second TNFi), and tocilizumab was the most common non‐TNFi second biologic received (9% overall, 58% of non‐TNFi). There was no difference between receiving TNFi versus non‐TNFi in cJADAS10 ID (29% vs 25%; aOR 1.23, 95% confidence interval [CI] 0.47–3.20) or at least MiDA (43% vs 39%; aOR 1.11, 95% CI 0.47–2.62) at six months. Most patients with pJIA started receiving TNFi rather than non‐TNFi as their second biologic, and there were no differences in disease activity at six months.

Due to the large lattice mismatch between gold and nickel, gold–nickel surface alloys can form unique nonstoichiometric overlayer structures characterized by a moiré pattern and subsurface defects. We performed density functional theory (DFT) calculations to study the adsorption of molecular oxygen, atomic hydrogen, and atomic carbon on a gold–nickel(111) surface alloy with 0.46 monolayer gold randomly distributed in the surface layer. We observed six distinct adsorption structures for molecular oxygen characterized by intramolecular stretching frequencies of <700, 729, 795, 857, 929, and 1004 cm–1, which describe well the experimentally observed high-resolution electron energy-loss spectra. Surface atomic hydrogen adsorption is associated with adsorbate–surface modes in the ∼1000 cm–1range, while subsurface hydrogen can have features as low as ∼400 cm–1. We observed a unique adsorption structure for atomic carbon inside the surface dislocation loop defect, which explains the experimentally observed low carbon-surface mode at ∼340 cm–1. Our study sheds light on the unique adsorption properties of the gold–nickel surface alloys and helps with rationalizing vibrational frequency experimental studies for this system.

Graphical Abstract:

The incorporation of superhydrophobic properties into metal organic framework (MOF) materials is highly desirable to enhance their hydrolytic stability, gas capture selectivity in the presence of humidity and efficiency in oil–water separations, among others. The existing strategies for inducing superhydrophobicity into MOFs have several weaknesses, such as increased cost, utilization of toxic reagents and solvents, applicability for limited MOFs, etc. Here, we report the simplest, most eco-friendly, and cost-effective process to impart superhydrophobicity to MOFs, involving a rapid (90 min) treatment of MOF materials with solutions of sodium oleate, a main component of soap. The method can be applied to both hydrolytically stable and unstable MOFs, with the porosity of modified MOFs approaching, in most cases, that of the pristine materials. Interestingly, this approach was used to isolate superhydrophobic magnetic MOF composites, and one of these materials formed stable liquid marbles, whose motion could be easily guided using an external magnetic field. We also successfully fabricated superhydrophobic MOF-coated cotton fabric and fiber composites. These composites exhibited exceptional oil sorption properties achieving rapid removal of floating crude oil from water, as well as efficient purification of oil-in-water emulsions. They are also regenerable and reusable for multiple sorption processes. Overall, the results described here pave the way for an unprecedented expansion of the family of MOF-based superhydrophobic materials, as virtually any MOF could be converted into a superhydrophobic compound by applying the new synthetic approach.

Systemic juvenile idiopathic arthritis–associated lung disease (SJIA‐LD) is a life‐threatening disease complication. Key questions remain regarding clinical course and optimal treatment approaches. The objectives of the study were to detail management strategies after SJIA‐LD detection, characterize overall disease courses, and measure long‐term outcomes. This was a prospective cohort study. Clinical data were abstracted from the electronic medical record, including current clinical status and changes since diagnosis. Serum biomarkers were determined and correlated with presence of LD. We enrolled 41 patients with SJIA‐LD, 85% with at least one episode of macrophage activation syndrome and 41% with adverse reactions to a biologic. Although 93% of patients were alive at last follow‐up (median 2.9 years), 37% progressed to requiring chronic oxygen or other ventilator support, and 65% of patients had abnormal overnight oximetry studies, which changed over time. Eighty‐four percent of patients carried the HLA‐DRB1*15 haplotype, significantly more than patients without LD. Patients with SJIA‐LD also showed markedly elevated serum interleukin‐18 (IL‐18), variable C‐X‐C motif chemokine ligand 9 (CXCL9), and significantly elevated matrix metalloproteinase 7. Treatment strategies showed variable use of anti–IL‐1/6 biologics and addition of other immunomodulatory treatments and lung‐directed therapies. We found a broad range of current clinical status independent of time from diagnosis or continued biologic treatment. Multidomain measures of change showed imaging features were the least likely to improve with time. Patients with SJIA‐LD had highly varied courses, with lower mortality than previously reported but frequent hypoxia and requirement for respiratory support. Treatment strategies were highly varied, highlighting an urgent need for focused clinical trials.

The synthesis, characterization, and single–crystal–to–single–crystal (SCSC) exchange reactions of a new 3D Cu2+MOF based on 5-aminoisophthalic acid (H2AIP), [Cu6(μ3-ΟΗ)3(ΑΙΡ)4(HΑΙΡ)]n·6nDMF·nH2O - UCY-16·6nDMF·nH2O, are reported. It exhibits a 3D structure based on two [Cu4(μ3–OH)2]6+butterfly–like secondary building units, differing in their peripheral ligation, bridged through HAIP–/AIP2–ligands. This compound displays the capability to exchange the coordinating ligand(s) and/or guest solvent molecules through SCSC reactions. Interestingly, heterogeneous reactions of single crystals of UCY-16·6nDMF·nH2O with primary alcohols resulted not only in the removal of the lattice DMF molecules but also in an unprecedented structural alteration that involved the complete or partial replacement of the monoatomic bridging μ3–OH–anion(s) of the [Cu4(μ3–OH)2]6+butterfly structural core by various alkoxy groups. Similar crystal-to-crystal exchange reactions of UCY-16·6nDMF·nH2O with long-chain aliphatic alcohols (CxH2x+1OH, x= 8–10, 12, 14, and 16) led to analogues containing fatty alcohols. Notably, the exchanged products with the bulkier alcohols UCY-16/n-CxH2x+1OH·S′ (x= 6–10, 12, 14, and 16) do not mix with H2O being quite stable in this solvent, in contrast to the pristine MOF, and exhibit a hydrophobic/superhydrophobic surface as confirmed from the investigation of their water contact angles and capability to remove hydrophobic pollutants from aqueous media.

Suspended ceiling and fire sprinkler piping (CP) systems are two of the most common interacting nonstructural elements inside the buildings. While each of these elements individually is prone to losses during the earthquakes, their interaction can even more intensify their associated damage. This article aims to integrate system-level modeling methodology by using existing subsystem-level models in OpenSees platform to simulate the interacting behavior of CP systems. To do so, the numerical model of the CP systems is developed by using a series of previously developed component-level nonlinear models. Experimental results from a shake table study of CP systems installed in a five-story building (fully scaled) are used for the validation of the proposed methodology. Experimental acceleration and displacement responses of CP systems at different locations as well as the damage-progression pattern in the suspended ceiling system are predicted well through the use of the proposed modeling technique.

Hydrogen fuel cells have drawn increasing attention as one of the most promising next-generation power sources for future automotive transportation. Developing efficient, durable, and low-cost electrocatalysts, to accelerate the sluggish oxygen reduction reaction (ORR) kinetics, is urgently needed to advance fuel cell technologies. Herein, we report on metal–organic frameworks-derived nonprecious dual metal single-atom catalysts (SACs) (Zn/Co–N–C), consisting of Co–N4and Zn–N4local structures. These catalysts exhibited superior ORR activity with a half-wave potential (E1/2) of 0.938 V versus RHE (reversible hydrogen electrode) and robust stability (ΔE1/2= −8.5 mV) after 50k electrochemical cycles. Moreover, this remarkable performance was validated under realistic fuel cell working conditions, achieving a record-high peak power density of ∼1 W cm–2among the reported SACs for alkaline fuel cells. OperandoX-ray absorption spectroscopy was conducted to identify the active sites and reveal catalytic mechanistic insights. The results indicated that the Co atom in the Co–N4structure was the main catalytically active center, where one axial oxygenated species binds to form an Oads–Co–N4moiety during the ORR. In addition, theoretical studies, based on a potential-dependent microkinetic model and core-level shift calculations, showed good agreement with the experimental results and provided insights into the bonding of oxygen species on Co–N4centers during the ORR. This work provides a comprehensive mechanistic understanding of the active sites in the Zn/Co–N–C catalysts and will pave the way for the future design and advancement of high-performance single-site electrocatalysts for fuel cells and other energy applications.

Rhombic dodecahedral nanocrystals have been considered particularly difficult to synthesize because they are enclosed by {110}, a low-index facet with the greatest surface energy. Recently, we demonstrated the use of seed-mediated growth for the facile and robust synthesis of Au rhombic dodecahedral nanocrystals (AuRD). While the unique shape and surface structure of AuRD are desirable for potential applications in plasmonics and catalysis, respectively, their high surface energy makes them highly susceptible to thermal degradation. Here we demonstrate that it is feasible to greatly improve the thermal stability with some sacrifice to the plasmonic properties of the original AuRD by coating their surface with an ultrathin shell made of Pt. Our in situelectron microscopy analysis indicates that the ultrathin Pt coating can increase the thermal stability from 60 up to 450 °C, a trend that is also supported by the results from a computational study.

Transition metal nitride (TMN-) based materials have recently emerged as promising non-precious-metal-containing electrocatalysts for the oxygen reduction reaction (ORR) in alkaline media. However, the lack of fundamental understanding of the oxide surface has limited insights into structure–(re)activity relationships and rational catalyst design. Here we demonstrate how a well-defined TMN can dictate/control the as-formed oxide surface and the resulting ORR electrocatalytic activity. Structural characterization of MnN nanocuboids revealed that an electrocatalytically active Mn3O4shell grew epitaxially on the MnN core, with an expansive strain along the [010] direction to the surface Mn3O4. The strained Mn3O4shell on the MnN core exhibited an intrinsic activity that was over 300% higher than that of pure Mn3O4. A combined electrochemical and computational investigation indicated/suggested that the enhancement probably originates from a more hydroxylated oxide surface resulting from the expansive strain. This work establishes a clear and definitive atomistic picture of the nitride/oxide interface and provides a comprehensive mechanistic understanding of the structure–reactivity relationship in TMNs, critical for other catalytic interfaces for different electrochemical processes.

Social media is an important means of communication for political agencies, which makes it possible to engage with large sectors of the public. For institutions which are not directly elected by voters, such as the European Commission (EC), social media can be a strategic tool for increasing perceived legitimacy and citizen engagement, especially in contexts of high politicization. In this paper, we use natural language processing techniques to provide a comprehensive overview of how EC communication on Twitter has evolved between 2010 and 2022, with respect to both its topics and its style. Our analyses show that, over time, the focus of EC communication has shifted substantially from economy-, finance- and governance-related topics, towards social policy, digital and environmental policy, and identity. These changes have progressively differentiated the EC’s profile from that of other institutions (especially more technocratic ones) and contributed to better alignment with engagement patterns of its social media audience. In addition, EC communication has become less neutral (in favor of more positive sentiment), simpler, and more readable, all features which are associated with more accessible and engaging messaging. Yet, while the EC currently scores better than most other reference agencies on several descriptors of accessibility, its style is still lexically more complex, less concrete and less action-oriented than that of other institutions. Alongside providing novel insights on how the EC’s online communication and projected political identity have changed over time, this study lays the foundations for future experimental and hypothesis-driven work combining social media data with external data sources.

This article presents a wireless passive vibration sensor based on harmonic backscattering. The adopted vibration transducer is a commercial piezoelectric cantilever. The cantilever is connected to the gate of an NMOS transistor, which controls the self-bias point of the Schottky diode responsible for the second-harmonic generation. This way, vibrations induce the amplitude modulation of the backscattered second harmonic. A technique is presented to retrieve the vibration information (both acceleration and frequency) from the acquired spectrum. The vibration frequency is computed as the average frequency difference between the carrier and the first sidebands, while the vibration acceleration is encoded in the duty cycle of the amplitude modulation of the backscattered harmonic. In this contribution, we demonstrate for the first time that this information can be retrieved from the magnitude ratio of the first and second sidebands of the acquired spectrum regardless of the tag-to-reader distance. A complete wireless prototype, working at $f_{0}=1.5$ GHz, is manufactured and tested in a laboratory environment for tag-to-reader distances up to 1.3 m. Despite some sensor limitations, i.e., the nonlinear relationship between the duty cycle and the vibration acceleration and the dependence of the sensor sensitivity on the vibration frequency, excellent results are obtained for vibration frequencies around the natural oscillation frequency of the cantilever (i.e., 130 Hz), and for variable accelerations and distances, which testifies the high sensitivity and the robustness of the proposed solution.

It is well established that child poverty has a profound, costly, and long-term impact on physical and mental health, educational attainment, and outcomes in adulthood. However, to date, while among adults a correlation between income and subjective well-being has been found, findings of such an association during childhood are mixed. This may be because the indicators available for both child poverty and subjective well-being have been limited – mainly to household incomes reported by adults and single measures of life satisfaction. This article explores the opportunities presented by the data collected in the third wave of Children’s Worlds, the school-based survey of children in 35 countries. The study employed a wider range of measures of material well-being, as well as subjective well-being, in terms of living standards in a larger range of countries. We have found that at both country comparative level, and within the country level, there is an association between material deprivation and some measures of subjective well-being, but the strength of the association varied between the country level and individual-level analyses, and across countries at the individual-level. At the macro-country level, the Family Affluence Scale was not significantly associated with most subjective well-being measures, while the deprivation scale, and a multi-dimensional measure that was developed in this paper, showed high correlations with overall life satisfaction and feelings of sadness. At the individual-level, the correlations were generally weak and varied between countries. We conclude with a discussion regarding possible explanations for these findings and their possible implications.

An all-textile metamaterial absorber is proposed for Ku-, K-, and Ka-band applications. The proposed metamaterial absorber is based on square-shaped split ring resonators. The design parameters are chosen based on commonly used electronic textile (E-textile) and felt dielectric material. The proposed structure demonstrates has a high absorption property of >90% between 13.1 and 31.13 GHz. At the same time, it reaches 99% absorption value between 16.4 and 21 GHz. The textile metamaterial absorber features the advantages of ultrawideband operability, angular stability, and polarization insensitivity. A proof-of- concept all-textile metamaterial absorber prototype has been fabricated and its simulation performance has been confirmed successfully by measurements. The results obtained are promising for the development of E-textile-based applications, such as energy harvesting, camouflage systems, sensitive wearable electronics, health monitoring, and electromagnetic shielding.

To meet the increasing need of wireless communication, radio frequency (RF) modules are commonly included in the design of flexible hybrid electronics (FHE). The reliability of printed flexible electronics under deformation has been widely studied under direct current (dc) conditions, while limited studies have been conducted under RF conditions. This work provides insight into how monotonic stretching changes the RF performance at a frequency range of 2–20 GHz of a coplanar waveguide (CPW) transmission line. The CPW is a silver ink screen-printed on a polyethylene terephthalate (PET) substrate, with a thin encapsulation on top of the silver conductor. The sample is subjected to monotonic stretching at a rate of 10 mm/min up to 70% strain, while in situ scattering parameters (S-parameters) are recorded by a vector network analyzer (VNA). Greater changes are observed in the insertion loss than in the return loss as the CPW undergoes stretching. Normalized insertion loss decreases as the strain increases, and at higher frequencies, the amount of increase is greater. However, when the CPW is stretched to 65% and above, the overall shape of S-parameters changes indicating the open circuit of the CPW. Numerical models at different strain levels are also developed in CST Studio Suite to compare predictions with experimental data. It is seen in addition to geometry and conductivity changes in CPW that the dielectric constant of the substrate and the encapsulant and the surface roughness of the conductive silver ink need to be changed with stretching in the numerical model to be able to mimic the experimental data. With such changes, the numerical CPW simulation results match both the overall trend and the magnitude of insertion loss in measurement data.

We demonstrate an integrated opto-electronic (ΟΕ) device that can be programmed to provide a set of nonlinear activation functions (AFs) and present its operation within programmable tanh- and ELU-based photonic neurons at line rates up to 10 GBd. The OE activation module provides a set of well-known activation functions that are typically used in DL training models, including the tanh-, ELU- and inverted ELU-like functions. Its performance is experimentally evaluated when incorporated in a 4-input wavelength division multiplexed (WDM) photonic neuron and operating with non-deterministic data patterns, providing “noisy” tanh, ELU and inverted ELU AFs with an error-distribution that has in all cases a standard deviation of &lt;0.49. We also evaluate the trainability of these “noisy” AFs and present for the first time an optics-informed training framework that incorporates the pattern-induced AF variations into the training process, yielding the first noise-aware training scheme where the noise emerges at the nonlinear AF NN segment. The performance analysis of the optics-informed training framework for all three AFs was carried out via Deep Learning setups suitable for classifying the Fashion MNIST and the CIFAR-10 datasets. This analysis has shown that the employment of traditional training schemes leads to significant accuracy degradations, which can be, however, almost completely waived when employing the optics-informed training framework, leading to accuracy values that are almost identical to the reference accuracy values obtained when ideal and noise-less AFs are used.

Underwater vehicles utilized in net cages at aquaculture facilities are commonly utilized for the purpose of examining the deterioration of nets and the accumulation of biofouling. The implementation of a robotic system for repairing damages has the potential to decrease the expenses associated with employing divers while reducing the risk of their injury. This study details the development, fabrication, and simulation of a cost-effective subaquatic manipulator, denoted as MURA, which can be seamlessly incorporated into submersible vehicles. The Kalypso unmanned underwater vehicle (UUV) is utilized in this study. MURA exhibits a high degree of modularity, enabling seamless alteration of the end-effector tool. Additionally, its low-cost nature renders it a viable option for integration with any underwater vehicle. Three end-effectors were subjected to testing, one designed for the purpose of disposing fish morts, another intended for removing litters from net cages in fisheries, and a third for repairing net tears. This study outlines the MURA design, including the arm’s fabrication and constituent components. In addition, the modeling of the manipulator is presented accompanied by a water flow simulation of the three manipulators. Ultimately, the experimental findings are analyzed and evaluated. These include the field experiments performed at Kefalonia fisheries, along with the duration to complete each task. For instance, the capture of fish morts typically necessitates approximately 30 s, encompassing the entire process from initial targeting to actual capture. In a similar vein, the procedure of mending tears in a net necessitates an approximate duration of 70 s on average, encompassing the stages of initial identification and subsequent detachment. The suggested design exhibits adaptability and durability while upholding affordability when utilized in aquaculture.

Child neglect is the most common form of child maltreatment. Like child abuse, it may adversely influence children’s development, cognitive function, and mental and physical health. Most literature on child neglect addresses professional discourse as opposed to children’s and adolescents’ views. Through a qualitative context-informed paradigm, the aim of this study was to gain a more nuanced understanding of Muslim Palestinian-Arab youths’ life experiences and concerns, with attention to their perceptions of child neglect. Data collection and thematic analysis were based on eight focus group discussions with youths who may or may not have experienced neglect. Participants were sampled by age (13–14) and ethnic affiliation (Muslim Arabs residing in northern Israel).

Computational chemistry calculations are broadly useful for guiding the atom-scale design of hard–soft material interfaces including how molecular interactions of single-component liquid crystals (LCs) at inorganic surfaces lead to preferred orientations of the LC far from the surface. The majority of LCs, however, are not single-component phases but comprise of mixtures, such as a mixture of mesogens, added to provide additional functions such as responsiveness to the presence of targeted organic compounds (for chemical sensing). In such LC mixtures, little is understood about the near-surface composition and organization of molecules and how that organization propagates into the far-field LC orientation. Here, we address this broad question by using a multiscale computational approach that combines density functional theory (DFT)-based calculations and classical molecular dynamics (MD) simulations to predict the interfacial composition and organization of a binary LC mixture of 4′-cyano-4-biphenylcarbolxylic acid (CBCA) and 4′-n-pentyl-4-biphenylcarbonitrile (5CB) supported on anatase (101) titania surfaces. DFT calculations determine the surface composition and atomic-scale organization of CBCA and 5CB at the titania surface, and classical MD simulations build upon the DFT description to describe the evolution of the near-surface order into the bulk LC. A surprising finding is that the 5CB and CBCA molecules adopt orthogonal orientations at the anatase surface and that, above a threshold concentration of CBCA, this mixture of orientations evolves away from the surface to define a uniform far-field homeotropic orientation. These results demonstrate that molecular-level knowledge achieved through a combination of computational techniques permits the design and understanding of functional LC mixtures at interfaces.

Introduction:Toxic gain-of-function Apolipoprotein L1(APOL1) variants contribute to the development of proteinuric nephropathies collectively referred to as APOL1-mediated kidney disease (AMKD). Despite standard-of-care treatments, patients with AMKD experience accelerated progression to end-stage kidney disease. The identification of two APOL1variants as the genetic cause of AMKD inspired development of inaxaplin, an inhibitor of APOL1 channel activity that reduces proteinuria in patients with AMKD. Methods:We conducted two phase 1 studies evaluating the safety, tolerability, and pharmacokinetics of single-ascending doses (SAD) and multiple-ascending doses (MAD) of inaxaplin in healthy participants. In the SAD cohorts, participants were randomized to receive inaxaplin as a single dose (range, 7.5 mg to 165 mg) or placebo. In the MAD cohorts, participants were randomized to receive multiple doses of inaxaplin (range, 15 to 120 mg daily) or placebo for 14 days. We assessed safety and tolerability based on adverse events (AEs), clinical laboratory values, electrocardiograms (ECGs), and vital signs. Results:A total of 178 participants were randomized in the SAD/MAD cohorts of both studies (mean age: 36.7 years; 94.9% male). The proportion of participants with any AEs was similar in the inaxaplin (24.6%) and placebo (22.7%) groups. All AEs were mild or moderate in severity; there were no serious AEs. Headache was the most common AE: 10.4% and 2.3% in the inaxaplin and placebo groups, respectively. There were no drug-related treatment discontinuations and no clinically relevant trends in laboratory values, ECGs, or vital signs. Discussion/Conclusion:Inaxaplin is safe and well tolerated at single doses up to 165 mg and multiple doses up to 120 mg daily for 14 days. These results are consistent with the favorable safety profile of inaxaplin in a completed phase 2a proof-of-concept study. Together, these findings support continued evaluation of inaxaplin in an ongoing phase 2/3 pivotal trial as a potential precision medicine for patients with AMKD.

We demonstrate a programmable analog opto-electronic (OE) circuit that can be configured to provide a range of nonlinear activation functions for incoherent neuromorphic photonic circuits at up to 10 Gbaud line-rates. We present a set of well-known activation functions that are typically used to train DL models including tanh-, sigmoid-, ReLU- and inverted ReLU-like activations, introducing also a series of novel photonic nonlinear functions that are referred to as Rectified Sine Squared (ReSin), Sine Squared with Exponential tail (ExpSin) and Double Sine Squared. Experimental validation for all these activation functions is performed at 10 Gbaud operation. The ability of the mathematically modelled photonic activation functions to train Deep Neural Networks (DNNs) has been verified through their employment in Deep Learning (DL) models for MNIST and CIFAR10 classification purposes, comparing their performance against corresponding NNs that utilize an ideal ReLU activation function.

Health disparities in childhood‐onset systemic lupus erythematosus (SLE) disproportionately impact marginalized populations. Socioeconomically patterned missing data can magnify existing health inequities by supporting inferences that may misrepresent populations of interest. Our objective was to assess missing data and subsequent health equity implications among participants with childhood‐onset SLE enrolled in a large pediatric rheumatology registry. We evaluated co‐missingness of 12 variables representing demographics, socioeconomic position, and clinical factors (e.g., disease‐related indices) using Childhood Arthritis and Rheumatology Research Alliance Registry childhood‐onset SLE enrollment data (2015–2022; n = 766). We performed logistic regression to calculate odds ratios (ORs) and 95% confidence intervals (95% CIs) for missing disease‐related indices at enrollment (Systemic Lupus Erythematosus Disease Activity Index 2000 [SLEDAI‐2K] and/or Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index [SDI]) associated with data missingness. We used linear regression to assess the association between socioeconomic factors and SLEDAI‐2K at enrollment using 3 analytic methods for missing data: complete case analysis, multiple imputation, and nonprobabilistic bias analyses, with missing values imputed to represent extreme low or high disadvantage. On average, participants were missing 6.2% of data, with over 50% of participants missing at least 1 variable. Missing data correlated most closely with variables within data categories (i.e., demographic). Government‐assisted health insurance was associated with missing SLEDAI‐2K and/or SDI scores compared to private health insurance (OR 2.04 [95% CI 1.22, 3.41]). The different analytic approaches resulted in varying analytic sample sizes and fundamentally conflicting estimated associations. Our results support intentional evaluation of missing data to inform effect estimate interpretation and critical assessment of causal statements that might otherwise misrepresent health inequities.

The goal was to characterize short‐term kidney status and describe variation in early care utilization in a multicenter cohort of patients with childhood‐onset systemic lupus erythematosus (cSLE) and nephritis. We analyzed previously collected prospective data from North American patients with cSLE with kidney biopsy‐proven nephritis enrolled in the Childhood Arthritis and Rheumatology Research Alliance (CARRA) Registry from March 2017 through December 2019. We determined the proportion of patients with abnormal kidney status at the most recent registry visit and applied generalized linear mixed models to identify associated factors. We also calculated frequency of medication use, both during induction and ever recorded. We identified 222 patients with kidney biopsy–proven nephritis, with 64% class III/IV nephritis on initial biopsy. At the most recent registry visit at median (interquartile range) of 17 (8–29) months from initial kidney biopsy, 58 of 106 patients (55%) with available data had abnormal kidney status. This finding was associated with male sex (odds ratio [OR] 3.88, 95% confidence interval [95% CI] 1.21–12.46) and age at cSLE diagnosis (OR 1.23, 95% CI 1.01–1.49). Patients with class IV nephritis were more likely than class III to receive cyclophosphamide and rituximab during induction. There was substantial variation in mycophenolate, cyclophosphamide, and rituximab ever use patterns across rheumatology centers. In this cohort with predominately class III/IV nephritis, male sex and older age at cSLE diagnosis were associated with abnormal short‐term kidney status. We also observed substantial variation in contemporary medication use for pediatric lupus nephritis between pediatric rheumatology centers. Additional studies are needed to better understand the impact of this variation on long‐term kidney outcomes.

Despite the wide use of immune checkpoint inhibition for the treatment of melanoma, the mechanisms leading to long-term stable disease are incompletely understood. Patients with metastatic melanoma who had received ipilimumab alone or ipilimumab plus nivolumab 2+years prior and attained at least 6 months of stable disease were identified. Positron emission tomography/computed tomography (PET/CT) was performed. Pretreatment and posttreatment biopsies of areas of stable disease were assessed for tumor, fibrosis, and inflammation. Seven patients underwent PET/CT and tissue biopsy. Fluorodeoxyglucose avid lesions on PET/CT ranged from no activity to an SUV of 22. In 6 patients, the residual stable lesions were composed of necrosis and fibrosis with a prominent pigment containing macrophages and no residual melanoma. In 1 patient, a nodal lesion demonstrated melanoma with active inflammation. In most patients with durable stable disease after treatment with ipilimumab or ipilimumab/nivolumab, residual lesions demonstrated predominantly necrosis and fibrosis consistent with resolving lesions. The presence of melanophages in these samples may suggest ongoing immune surveillance. One patient did demonstrate residual melanoma, indicating the need for ongoing monitoring of this patient population.

Immune evasion, due to abnormal expression of programmed-death ligands 1 and 2 (PD-L1/PD-L2), predicts poor outcomes with chemoimmunotherapy in diffuse large B-cell lymphoma (DLBCL). Immune checkpoint inhibition (ICI) has limited efficacy at relapse but may sensitise relapsed lymphoma to subsequent chemotherapy. ICI delivery to immunologically intact patients may thus be the optimal use of this therapy. In the phase II AvR-CHOP study, 28 patients with treatment-naive stage II–IV DLBCL received sequential avelumab and rituximab priming (“AvRp;” avelumab 10 mg/kg and rituximab 375 mg/m2 2-weekly for 2 cycles), R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, prednisolone for 6 cycles) and avelumab consolidation (10 mg/kg 2-weekly for 6 cycles). Grade 3/4 immune-related adverse events occurred in 11%, meeting the primary endpoint of a grade ≥3 irAE rate of <30%. R-CHOP delivery was not compromised but one patient ceased avelumab. Overall response rates (ORR) after AvRp and R-CHOP were 57% (18% CR) and 89% (all CR). High ORR to AvRp was observed in primary mediastinal B-cell lymphoma (67%; 4/6) and molecularly-defined EBV-positive DLBCL (100%; 3/3). Progression during AvRp was associated with chemorefractory disease. Two-year failure-free and overall survival were 82% and 89%. An immune priming strategy with AvRp, R-CHOP and avelumab consolidation shows acceptable toxicity with encouraging efficacy.

Children with well‐controlled juvenile idiopathic arthritis (JIA) frequently experience flares after medication discontinuation, but the outcomes of these flares have not been well described. The objective of this study was to characterize the rates and predictors of disease recapture among children with JIA who restarted medication to treat disease flare. Children with JIA who discontinued conventional synthetic or biologic disease‐modifying antirheumatic drugs for well‐controlled disease but subsequently experienced a flare and restarted medication were identified from the Childhood Arthritis and Rheumatology Research Alliance (CARRA) registry. The primary outcome was inactive disease (ID) (physician global assessment <1 and active joint count = 0) 6 months after flare. A total of 333 patients had complete data for ID at 6 months after flare. The recapture rate for the cohort was 55%, ranging from 47% (persistent oligoarthritis) to 69% (systemic arthritis) (P= 0.4). Approximately 67% of children achieved ID by 12 months. In the multivariable model, history and reinitiation of biologic drugs were associated with increased odds of successful recapture (odds ratio [OR] 4.79 [95% confidence interval (95% CI) 1.22–18.78] and OR 2.74 [95% CI 1.62–4.63], respectively). Number of joints with limited range of motion was associated with decreased odds (OR 0.83 per 1 joint increase [95% CI 0.72–0.95]). Approximately half of JIA flares post‐discontinuation were recaptured within 6 months, but rates of recapture varied across JIA categories. These findings inform shared decision‐making for patients, families, and clinicians regarding the risks and benefits of medication discontinuation. Better understanding of biologic predictors of successful recapture in JIA are needed.

The frequency-diverse array (FDA) is a promising technology because of its angle- and range-dependent beam pattern. The FDA has unique properties, such as beam scanning and focusing, which are difficult to achieve using the conventional phased antenna array theory. In this study, the relationship between range and frequency increment is analyzed, and the fundamental operation principle of FDA is thoroughly investigated. The effect of coupling among antenna elements is also discussed to analyze the FDA theory. Furthermore, a novel exponential FDA method for short-range beam focusing is presented based on the proposed FDA analysis method. The proposed method has been investigated through various case studies and applied to research efforts on FDA methods. The FDA design procedures and analysis methods are also presented in this article.

A comprehensive database that has been used to develop ground motion models for induced earthquakes in the Groningen gas field is provided in a freely accessible online repository. The database includes more than 8500 processed ground motion recordings from 87 earthquakes of local magnitude MLbetween 1.8 and 3.6, obtained from a large network of surface accelerographs and borehole geophones placed at 50 m depth intervals to a depth of 200 m. The 5%-damped pseudo-acceleration spectra and Fourier amplitude spectra of the records are also provided. Measured shear-wave velocity (VS) profiles, obtained primarily from seismic Cone Penetration Tests (CPTs), are provided for 80 of the ∼100 recording stations. A model representing the regional dynamic soil properties is presented for the entire gas field plus a 5 km onshore buffer zone, specifying lithology, VS, and damping for all layers above the reference baserock horizon located at about 800 m depth. Transfer functions and frequency-dependent amplification factors from the reference rock horizon to the surface for the locations of the recording stations are also included. The database provides a valuable resource for further refinement of induced seismic hazard and risk modeling in Groningen as well as for generic research in site response of thick, soft soil deposits and the characteristics of ground motions from small-magnitude, shallow-focus induced earthquakes.

Reprogrammable optical meshes comprise a subject of heightened interest for the execution of linear transformations, having a significant impact in numerous applications that extend from the implementation of optical switches up to neuromorphic computing. Herein, we review the state-of-the-art approaches for the realization of unitary transformations and universal linear operators in the photonic domain and present our recent work in the field, that allows for fidelity restorable and low-loss optical circuitry with single-step programmability. These advantages unlock a new framework for matrix-vector multiplications required by neuromorphic silicon photonic circuits, supporting: i) high-speed and high-accuracy neural network (NN) inference, ii) high-speed tiled matrix multiplication, iii) NN training and iv) programmable photonic NNs. This new potential is initially validated through recent experimental results using SiGe EAM technology and static weights and, subsequently, utilized for demonstrating experimentally the first Deep NN (DNN) where optical tiled matrix multiplication up to 50 GHz is realized, allowing optics to execute DNNs with large number of trainable parameters over a limited photonic hardware. Finally, the new performance framework is benchmarked against state-of-the-art NN processors and photonic NN roadmap projections, highlighting its perspectives to turn the energy and area efficiency promise of neuromorphic silicon photonics into a tangible reality.

Hellenic Electricity Distribution Network Operator (HEDNO), the Hellenic distribution system operator (DSO), supports the energy transformation of ports, aiming at the faster decarbonization of the maritime sector, through the “Proteus Plan,” an initiative of an interdisciplinary group of engineers (the “Proteus team”), which is well aligned with the mission and vision of HEDNO. The mission of HEDNO is the development and operation of the electricity distribution network and the electricity systems of the noninterconnected islands as well as the assurance of equal access to them by all consumers, producers, and suppliers with transparency and objectivity.

ObjectiveTo describe the incidence and burden of illness at the Tokyo 2020 Paralympic Games, which was organised with strict COVID-19 countermeasures.MethodsDaily illnesses were recorded via the web-based injury and illness surveillance system (teams with their own medical staff; n=81), and local polyclinic services (teams without their own medical staff; n=81). Illness proportion, incidence and burden were reported for all illnesses and in subgroups by sex, age, competition period, sports and physiological system.Results4403 athletes (1853 female and 2550 male) from 162 countries were monitored for the 15-day period of the Tokyo Paralympic Games (66 045 athlete days). The overall incidence of illnesses per 1000 athlete days was 4.2 (95% CI 3.8 to 4.8; 280 illnesses). The highest incidences were in wheelchair tennis (7.1), shooting (6.1) and the new sport of badminton (5.9). A higher incidence was observed in female compared with male athletes (5.1 vs 3.6; p=0.005), as well as during the precompetition versus competition period (7.0 vs 3.5; p<0.0001). Dermatological and respiratory illnesses had the highest incidence (1.1 and 0.8, respectively). Illness burden was 4.9 days per 1000 athlete days and 23% of illnesses resulted in time loss from training/competition>1 day.ConclusionThe incidence of illness at the Tokyo 2020 Paralympic Games was the lowest yet to be recorded in either the summer or winter Paralympic Games. Dermatological and respiratory illnesses were the most common, with the burden of respiratory illness being the highest, largely due to time loss associated with COVID-19 cases. Infection countermeasures appeared successful in reducing respiratory and overall illness, suggesting implementation in future Paralympic Games may mitigate illness risk.

In this work, we propose MAGES 4.0, a novel software development kit to accelerate the creation of collaborative medical training applications in virtual/augmented reality (VR/AR). Our solution is essentially a low-code metaverse authoring platform for developers to rapidly prototype high-fidelity and high-complexity medical simulations. MAGES breaks the authoring boundaries across extended reality, since networked participants can also collaborate using different VR/AR as well as mobile and desktop devices, in the same metaverse world. With MAGES we propose an upgrade to the outdated 150-year-old master–apprentice medical training model. Our platform incorporates, in a nutshell, the following novelties: 1) 5G edge-cloud remote rendering and physics dissection layer, 2) realistic real-time simulation of organic tissues as soft-bodies under 10 ms, 3) a highly realistic cutting and tearing algorithm, 4) neural network assessment for user profiling and, 5) a VR recorder to record and replay or debrief the training simulation from any perspective.

When an electrode contacts an electrolyte, an interfacial electric field forms. This interfacial field can polarize the electrode’s surface and nearby molecules, but its effect can be countered by an applied potential. Quantifying the value of this countering potential (‘potential of zero charge’ (pzc)) is, however, not straightforward. Here we present an optical method for determining the pzc at an electrochemical interface. Our approach uses phase-sensitive second-harmonic generation to determine the electrochemical potential where the interfacial electric field vanishes at an electrode–electrolyte interface with Pt–water as a model experiment. Our method reveals that the pzc of the Pt–water interface is 0.23 ± 0.08 V versus standard hydrogen electrode (SHE) and is pH independent from pH 1 to pH 13. First-principles calculations with a hybrid explicit–implicit solvent model predict the pzc of the Pt(111)–water interface to be 0.23 V versus SHE and reveal how the interfacial water structure rearranges as the electrode potential is moved above and below the pzc. We further show that pzc is sensitive to surface modification; deposition of Ni on Pt shifts the interfacial pzc in the cathodic direction by ~360 mV. Our work demonstrates a materials-agnostic approach for quantifying the interfacial electrical field and water orientation at an electrochemical interface without requiring probe molecules and confirms the long-held view that the interfacial electric field is more intense during hydrogen electrocatalysis in alkaline than in acid.

In this work, for the first time, a 5G/mm-Wave harmonic frequency modulated continuous wave (FMCW) radar with dual Rotman lens-based harmonic millimeter identification (mmID) ranging system is proposed enabling ultralong range highly accurate localization for future localized sensing cyberphysical systems (CPSs). A detailed characterization of the fully-passive harmonic mmID is first presented with an estimated maximum harmonic radar cross section (RCS) of −35.8 dBsm and a 10 dB beamwidth of ±50°. The mmID fully overcomes the high-gain beamwidth tradeoff seen in typical high-gain designs enabling robust, ultralong-range detectability. A link budget analysis of the proposed harmonic mmID is presented with the current proof-of-concept (PoC) harmonic radar and with an equivalent isotropic radiated power (EIRP) of 75 dBm reading ranges in excess of 8 km are envisioned. In addition, the system provides a highly accurate ranging at long range with a bounded maximum ranging error of 17 cm up to 46 m from the radar. Furthermore, the 5G/mm-Wave system capitalizes on the highly sensitive phase information for ultrafine 0.4 mm accurate ranging at 10 m. Thus, the proposed system presents a fully-passive, long-range ranging system for future CPSs.

The paper presents road safety actions and measures proposed in the framework of the development of the Greek Strategic Road Safety Plan for the period 2021-2030. Five road safety pillars that concern all road crash factors are outlined. For each pillar, actions and particular measures are defined, adapted to the Greek reality and based on the principles of Vision Zero and the Safe System Approach. In total, 44 actions and 200 road safety measures are foreseen and implementation priorities are defined. Next, the framework for monitoring the implementation of actions is presented, taking into account the elements of the Safe System Approach. The use of a set of key performance indicators for road safety is proposed and the methodological framework for the collection of the necessary data and the calculation of road safety performance indicators is provided.

Despite the most significant improvement in road safety performance among the EU countries during the period 2010-2020 and achieving the target of halving road fatalities, Greece still remains behind the EU average in terms of road fatalities per population. This paper presents the Greek Road Safety Strategic Plan for the decade 2021-2030. With this Plan, Greece adopts the Safe System Approach and the Vision Zero by 2050. The Strategic Plan is in alignment with the EU Road Safety Strategy aiming to halve road fatalities and serious injuries by 2030. Eight targets for road crash casualties’ reduction and eight targets for the improvement of road safety performance are proposed for 2030, with intermediate targets for 2025. A list of 200 Road Safety Measures within 44 Actions within the five UN Pillars is also set. Finally, an integrated system for monitoring road safety is proposed.