A multifunctional smart field-programmable radio frequency surface.

Antennas that can operate across multiple communication standards have remained a challenge. To address these limitations, we propose a Field-Programmable Radio Frequency Surface (FPRFS), which is based on manipulating current flow on its surface to achieve desirable RF characteristics. In this work, we demonstrate that substantial enhancements in radiation efficiency can be achieved while preserving the high reconfigurability of antenna structures implemented on the FPRFS. This is accomplished by utilizing an asymmetric excitation, directing the excitation to the low-loss contiguous surface, and dynamically manipulating the imaged return current on a segmented ground plane by switches. This important insight allows for adaptable antenna performance that weakly depends on the number of RF switches or their loss. We experimentally validate that FPRFS antennas can achieve efficiencies comparable to traditionally implemented antenna counterparts. This permits the FPRFS to be effectively utilized as a productive antenna and impedance-matching network with real-time reconfigurability.

Learning Robust and Sparse Principal Components With the α-Divergence.

In this paper, novel robust principal component analysis (RPCA) methods are proposed to exploit the local structure of datasets. The proposed methods are derived by minimizing the α -divergence between the sample distribution and the Gaussian density model. The α- divergence is used in different frameworks to represent variants of RPCA approaches including orthogonal, non-orthogonal, and sparse methods. We show that the classical PCA is a special case of our proposed methods where the α- divergence is reduced to the Kullback-Leibler (KL) divergence. It is shown in simulations that the proposed approaches recover the underlying principal components (PCs) by down-weighting the importance of structured and unstructured outliers. Furthermore, using simulated data, it is shown that the proposed methods can be applied to fMRI signal recovery and Foreground-Background (FB) separation in video analysis. Results on real world problems of FB separation as well as image reconstruction are also provided.

Identifying potential catalysts to accelerate the achievement of Sustainable Development Goals (SDGs) among adolescents living in Nigeria.

Investing in adolescents in Africa holds great promise for the development of the continent. The steps involved in identifying factors linked to interventions that may accelerate the attainment of multiple SDGs for adolescents in Nigeria are described. Data from a survey to investigate the well-being of 1800 adolescents aged 10-19 years in Southwest Nigeria was analysed. A four-step process was employed: 1) Mapping of variables deemed as suitable proxies for SDG targets; 2) Mapping hypothesised protective factors (accelerators) from the study instruments. Consequently, SDG targets related to elimination of hunger, good health, gender equality and peace; and seven accelerators (safe schools, parenting support, good mental health, no survival work, food security, stable childhood, and regular physical activity) were identified; 3) evaluating associations using bivariate analysis and multivariable logistic regression, 4) calculating adjusted probabilities. The mean age of the adolescents was 15.02 ± 2.27 years (48.6% female). Good mental health, not doing survival work, safe schools, stable childhood and parental support were significantly associated with at least two SDG targets. For example, food security was significantly associated with the highest number of SDG outcomes: one SDG target related to child survival (no substance use: x2 = 3.39, p = <0.001); three SDG targets related to educational outcomes (school progression: x2 = 5.68, p = 0.017, ability to concentrate in school: x2 = 26.92, p = <0.001, and school attendance: x2 = 25.89, p = <0.001); and four SDG targets related to child protection (no risky sexual behaviours: x2 = 16.14, p = <0.001, no perpetration of violence: x2 = 15.74, p = <0.001, no community violence: x2 = 39.06, p =<0.001, and no sexual abuse: x2 = 7.66, p = 0.006). Interventions centred around good mental health, not doing survival work, safe schools, small family size, stable childhood and parental support are potential accelerators for the attainment of SDG outcomes by adolescents living in Nigeria.

Changes in arterial pH do not explain the reductions in ionised calcium observed during COVID-19 infection.

BACKGROUND: Hypocalcaemia predicts coronavirus disease 2019 (COVID-19) severity and mortality. We hypothesized an association between respiratory alkalosis secondary to hypoxia and low ionised calcium (iCa) concentration in patients with COVID-19. METHODS: Arterial blood gas samples taken from January 2019 to March 2021 were retrospectively matched with infection status. Principal components regression was undertaken to determine the correlation between pH, partial pressure arterial oxygen (PaO2), partial pressure arterial carbon dioxide (PaCO2), and iCa. RESULTS: We included 4056 patients (300 COVID-19 detected, 19 influenza detected), corresponding to 5960 arterial blood samples. The COVID-19 detected group had a statistically significantly lower iCa, PaO2 and PaCO2, and more alkalotic pH than infection-free groups. The influenza group had a lower iCa and PaCO2, higher PaO2, and a more alkalotic pH than infection-free groups, but these differences were non-significant. Principal components regression revealed that pH, PaCO2, and PaO2 explain just 2.72 % of the variance in iCa. An increase in pH by 1 unit was associated with an iCa reduction of 0.141 â€‹mmol/L (p â€‹< â€‹0.0001). CONCLUSION: Reduction in iCa concentration in patients with COVID-19 is not associated with pH derangement. Influenza infection was associated with a minor reduction in iCa in our small sample, a hitherto unreported finding, although statistical significance was not demonstrated.

Primary leiomyosarcoma of the small finger treated with ray amputation: A case report.

INTRODUCTION: Malignant sarcomas of the upper extremity are rare tumors that can have an overwhelming impact on a patient's function, quality of life, and life expectancy. Rarer still is the malignant tumor of the hand or digits, which represent an incredibly small percentage of upper extremity tumors. This paucity of cases can lead to difficult decision making and treatment options that may not always have clearly established results and outcomes. CASE: In this case, we present a young, otherwise healthy patient that was diagnosed with a primary leiomyosarcoma of the small finger. After her diagnosis, she underwent extensive oncologic workup, and subsequently underwent successful ray amputation with an excellent outcome. She remains disease free. DISCUSSION: Leiomyosarcoma is a malignant cancer that can be troublesome to diagnose in the extremities, as it is usually found in the smooth muscle of organs and the pelvis. Local control of the tumor is critical to successful, disease free treatment. Good functional and clinical outcomes can be attained with ray amputation, as seen in this patient. CONCLUSION: This case demonstrates a successful treatment approach to the patient with a primary malignant soft tissue sarcoma who was treated with a ray amputation. The clinician and surgeon must maintain a high index of suspicion of soft tissue malignancies, as a prompt diagnosis and treatment is critical to a good outcome and survival.

Passive Radar Tracking in Clutter Using Range and Range-Rate Measurements.

Passive bistatic radar research is essential for accurate 3D target tracking, especially in the presence of missing or low-quality bearing information. Traditional extended Kalman filter (EKF) methods often introduce bias in such scenarios. To overcome this limitation, we propose employing the unscented Kalman filter (UKF) for handling the nonlinearities in 3D tracking, utilizing range and range-rate measurements. Additionally, we incorporate the probabilistic data association (PDA) algorithm with the UKF to handle cluttered environments. Through extensive simulations, we demonstrate a successful implementation of the UKF-PDA framework, showing that the proposed method effectively reduces bias and significantly advances tracking capabilities in passive bistatic radars.

Environmental Contamination With SARS-CoV-2 in a Hospital Setting.

Background The coronavirus disease 2019 (COVID-19) pandemic is a global concern and has changed the way we practice medicine in acute hospital settings. This is particularly true with regard to patient triage, patient risk assessment, use of personal protective equipment, and environmental disinfection. Transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is primarily through inhalation of respiratory droplets generated through talking, coughing, or sneezing. There is, however, a potential risk that respiratory droplets settling on inanimate surfaces and objects in the hospital environment could provide a reservoir for nosocomial infections in patients and pose a healthcare risk to medical staff. Indeed, there have been previous reports of healthcare-associated outbreaks in hospitals. Several authors have argued that the risk of transmission via fomites may be insignificant. It is, however, not clear what proportion of SARS-CoV-2 infections are attributable to direct contact with fomites; a few reports have indicated possible transmission via this route. Environmental contamination with SARS-CoV-2 in healthcare institutions has been shown to vary according to the function or service provided by a unit or department. Information that identifies hospital areas that have a propensity for higher environmental burden may improve the practice of infection control and environmental cleaning and decontamination in healthcare institutions. This study aimed to investigate environmental SARS-CoV-2 contamination in the clinical areas of patients with COVID-19 infection. Methodology We conducted a cross-sectional study performing swabbing of frequently touched surfaces, equipment, and ventilation ducts in five specific clinical areas of Peterborough City Hospital which is part of the North West Anglia NHS Foundation Trust. The five clinical areas that were chosen for swabbing were the Emergency Department (ED), Intensive Care Unit (ICU), Isolation Ward, Respiratory Ward, and a Gastroenterology Ward that was serving as a receiving ward at the height of the second COVID-19 infection wave in the United Kingdom. Surfaces to be swabbed were divided into the patient zone, doctor zone, and nursing zone. Swabs from the chosen surfaces were collected on two consecutive days. A total of 158 surface swabs were collected during the second wave of the COVID-19 pandemic. SARS-CoV-2 RNA was detected by reverse transcription polymerase chain reaction. Results The most contaminated clinical areas were the three receiving wards where 12% (11/96) of the swabs were positive. Inside the patient rooms, these surfaces included bed rails and controls, bedside tables, television screens, remote control units, and the room ventilation system. Outside the patient room, these surfaces included mobile computers and computer desk surfaces in the doctors' offices. All swabs taken from the ED and ICU were found to be negative. Conclusions Our study confirms the potential infection risks posed by environmental contamination with the SARS-CoV-2 virus. This highlights the importance of adequate environmental cleaning for proper infection control and prevention in healthcare settings.

LncRNA MALAT1 Regulates Hyperglycemia Induced EMT in Keratinocyte via miR-205.

Epithelial-to-mesenchymal transition (EMT) is critical to cutaneous wound healing. When skin is injured, EMT activates and mobilizes keratinocytes toward the wound bed, therefore enabling re-epithelialization. This process becomes dysregulated in patients with diabetes mellitus (DM). Long non-coding RNAs (lncRNAs) regulate many biological processes. LncRNA-metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) influences numerous cellular processes, including EMT. The objective of the current study is to explore the role of MALAT1 in hyperglycemia (HG)-induced EMT. The expression of MALAT1 was found to be significantly upregulated, while the expression of miR-205 was downregulated in diabetic wounds and high-glucose-treated HaCaT cells. The initiation of EMT in HaCaT cells from hyperglycemia was confirmed by a morphological change, the increased expression of CDH2, KRT10, and ACTA2, and the downregulation of CDH1. The knockdown of MALAT1 was achieved by transfecting a small interfering RNA (SiRNA). MALAT1 and miR-205 were found to modulate HG-induced EMT. MALAT1 silencing or miR-205 overexpression appears to attenuate hyperglycemia-induced EMT. Mechanistically, MALAT1 affects HG-induced EMT through binding to miR-205 and therefore inducing ZEB1, a critical transcription factor for EMT. In summary, lncRNA MALAT1 is involved in the hyperglycemia-induced EMT of human HaCaT cells. This provides a new perspective on the pathogenesis of diabetic wounds.

Accelerating progress towards the sustainable development goals for adolescents in Ghana: a cross-sectional study.

Since the adoption of the sustainable development goals (SDGs) by the United Nations (UN), the search has been on to identify interventions that have effects on multiple SDG-targets simultaneously. Like other developing countries, Ghana has a youthful population and would require creative, urgent, youth-focused interventions to be able to attain the SDGs by 2030. This paper describes the application of the accelerator model on data from a sample of Ghanaian adolescents to identify potential accelerators towards selected SDG targets involving youth. The data for 944 adolescents, 10-19 years (mean age 12.31 ± 3.51 years), extracted from two cross-sectional surveys on children and adolescents aged 6-19 years in Kumasi, Ghana, were analysed in this paper. Variables considered suitable proxies for SDG targets and potential accelerators were identified from the study instruments. Consequently, four aligned SDG targets (good mental health, access to ICT, school completion and no open defaecation) and five accelerators (cognitive stimulation, no relative poverty, low student-teacher ratio, high caregiver education and safe water) were extracted. Associations between accelerators and SDG targets were assessed using multivariable logistic regression adjusting for sociodemographic covariates and multiple testing. Cumulative effects were tested by marginal effects modelling. The three hypothesised accelerators identified were cognitive stimulation, low student-teacher ratio, and no relative poverty. A combination of all three accelerators was associated with a higher likelihood of adolescents having access to Information and Communication Technology (ICT) by +73% (CI 0.72-0.74), no open defecation by +44% (CI 0.43-0.46), school completion by +27% (CI 0.26-0.27) and good mental health by +9% (CI 0.08-0.10). Three hypothesized accelerators showed association across all four SDG aligned targets. The accelerator model has been further validated in this dataset from Ghana. Robust interventions designed around these accelerators may represent an opportunity for achieving the SDGs in Ghana.

Testing for a Random Walk Structure in the Frequency Evolution of a Tone in Noise.

Inference and hypothesis testing are typically constructed on the basis that a specific model holds for the data. To determine the veracity of conclusions drawn from such data analyses, one must be able to identify the presence of the assumed structure within the data. In this paper, a model verification test is developed for the presence of a random walk-like structure in the variations in the frequency of complex-valued sinusoidal signals measured in additive Gaussian noise. This test evaluates the joint inference of the random walk hypothesis tests found in economics literature that seek random walk behaviours in time series data, with an additional test to account for how the random walk behaves in frequency space.

Adaptive Brain Activity Detection in Structured Interference and Partially Homogeneous Locally Correlated Disturbance.

OBJECTIVE: In this paper, we aim to address the problem of subspace detection in the presence of locally-correlated complex Gaussian noise and interference. For applications like brain activity detection using functional magnetic resonance imaging (fMRI) data where the noise is possibly locally correlated, using the sample covariance estimator is not a suitable choice due to significant dependency of its accuracy on the number of observations. METHODS: In this study, we take advantage of an assumed banded structure in the covariance matrix to model the local dependence in the noise and propose a new covariance estimation approach. In particular, we use the idea of factorizing the joint likelihood function into a few conditional likelihood terms and maximizing each term independently of the others. This process leads to an explicit estimator for banded covariance matrices which requires fewer observations to achieve the same accuracy as the sample covariance. This estimate is then fed into an adaptive matched filter, two-step Rao and two-step Wald tests for detection. RESULTS: Simulation results reveal the superiority of the proposed methods over well known classical detectors. Finally, the proposed methods are applied to functional magnetic resonance imaging (fMRI) data to localize neural activities in the brain. CONCLUSION: The proposed method can offer better activation maps in terms of accuracy and spatial smoothness. SIGNIFICANCE: The proposed methods can be seen as alternatives for standard detection approaches which are not perfectly aligned with the properties of fMRI data.

Robust Subspace Detectors Based on α-Divergence With Application to Detection in Imaging.

Robust variants of Wald, Rao and likelihood ratio (LR) tests for the detection of a signal subspace in a signal interference subspace corrupted by contaminated Gaussian noise are proposed in this paper. They are derived using the α- divergence, and the trade-off between the robustness and the power (the probability of detection) of the tests is adjustable using a single hyperparameter α . It is shown that when α→ 1 , these tests are equivalent to their well known classical counterparts. For example the robust LR test coincides with the LR test or the matched subspace detector (MSD). Asymptotic results are provided to support the proposed tests and robustness to outliers is obtained using values of . Numerical experiments illustrating the performance of these tests on simulated, real functional magnetic resonance imaging (fMRI), hyperspectral and synthetic aperture radar (SAR) data are also presented.

Multi-Radio Based Rendezvous Technique for Heterogeneous Cognitive Radio Sensor Network.

In a distributed cognitive radio (CR) sensor network, transmission and reception on vacant channels require cognitive radio nodes to achieve rendezvous. Because of the lack of adequate assistance from the network environment, such as the central controller and other nodes, assisted rendezvous for distributed CR is inefficient in a dynamic network. As a result, non-assisted blind rendezvous, which is unaware of its counterpart node, has recently led to a lot of interest in the research arena. In this paper, we study a channel rendezvous method based on prime number theory and propose a new multi-radio-based technique for non-assisted rendezvous with the blind and heterogeneous condition. The required time and the optimal number of radios for the guaranteed rendezvous are calculated using probability-based measurement. Analytical expressions for probabilistic guaranteed rendezvous conditions are derived and verified by Monte Carlo simulation. In addition, the maximum time to rendezvous (MTTR) is derived in closed form using statistical and probabilistic analysis. Under different channel conditions, our proposed solution leads to a substantial time reduction for guaranteed rendezvous. For the sake of over-performance of our proposed system, the simulation outcome is compared to a recently proposed heterogeneous and blind rendezvous method. The Matlab simulation results show that our proposed system's MTTR gains range from 11% to over 95% for various parametric values of the system model.

Exploring the relationship between pain and self-harm thoughts and behaviours in young people using network analysis.

BACKGROUND: Self-harm thoughts and behaviours (SHTBs) are a serious public health concern in young people. Emerging research suggests that pain may be an important correlate of SHTBs in young people. However, it remains unclear whether this association is driven by the shared association with other correlates of SHTBs. This study used network analysis to delineate the relationship between SHTBs, pain and other correlates of SHTBs in a population-based sample of young people. METHODS: We performed secondary analyses, using data from 7977 young people aged 5-16 years who participated in the British Child and Adolescent Mental Health Survey in 2004. We used χ2 tests and network analysis to examine the complex interplay between SHTBs, pain and other correlates of SHTBs, including psychiatric disorders, childhood trauma, stressful life events, parental distress, family dysfunction, peer problems and inhibitory control deficits. RESULTS: Pain was associated with a doubled risk of SHTBs, and likewise, SHTBs were associated with a doubled risk of pain. Furthermore, network analysis showed that although pain was significantly associated with all measured correlates of SHTBs, except family dysfunction, pain was most strongly associated with SHTBs, after accounting for these measured correlates. CONCLUSIONS: To the best of our knowledge, this is the first study to utilise network analysis to provide novel insights into the complex relationship between SHTBs, pain and other known correlates of SHTBs in young people. Results suggest that pain is an independent correlate of SHTBs. Future research should aim to identify underlying mechanisms.

The Development of Solvent Cast Films or Electrospun Nanofiber Membranes Made from Blended Poly Vinyl Alcohol Materials with Different Degrees of Hydrolyzation for Optimal Hydrogel Dissolution and Sustained Release of Anti-Infective Silver Salts.

INTRODUCTION: We previously described the manufacture and characterization of hydrogel forming, thin film, anti-infective wound dressings made from Poly Vinyl Alcohol (PVA) and silver nanoparticles, crosslinked by heat. However, these films were designed to be inexpensive for simple manufacture locally in Africa. In this new study, we have further developed PVA dressings by manufacturing films or electrospun membranes, made from blends of PVA with different degrees of hydrolyzation, that contain silver salts and degrade in a controlled manner to release silver in a sustained manner over 12 days. METHODS: Films were solvent cast as films or electrospun into nanofibre membranes using blends of 99 and 88% hydrolyzed PVA, containing 1% w/w silver sulphadiazine, carbonate, sulphate, or acetate salts. Dissolution was measured as weight loss in water and silver release was measured using inductively coupled plasma (ICP) analysis. RESULTS: Cast films generally stayed intact at PVA 99: PVA 88% ratios greater than 40:60 whereas electrospun membranes needed ratios greater than 10:90. Films (40:60 blend ratio) and membranes (10:90) all released silver salts in a sustained fashion but incompletely and to different extents. Electrospun membranes gave more linear release patterns in the 2-12 day period and all salts released well. CONCLUSION: Blended PVA cast films offer improved control over hydrogel dissolution and silver release without the need for high temperature crosslinking. Blended PVA electrospun membranes further improve membrane dissolution control and silver release profiles. These blended PVA films and membranes offer improved inexpensive systems for the manufacture of long lasting anti-infective hydrogel wound dressings.

The Design, Characterization and Antibacterial Activity of Heat and Silver Crosslinked Poly(Vinyl Alcohol) Hydrogel Forming Dressings Containing Silver Nanoparticles.

The prompt treatment of burn wounds is essential but can be challenging in remote parts of Africa, where burns from open fires are a constant hazard for children and suitable medical care may be far away. Consequently, there is an unmet need for an economical burn wound dressing with a sustained antimicrobial activity that might be manufactured locally at low cost. This study describes and characterizes the novel preparation of a silver nitrate-loaded/poly(vinyl alcohol) (PVA) film. Using controlled heating cycles, films may be crosslinked with in situ silver nanoparticle production using only a low heat oven and little technical expertise. Our research demonstrated that heat-curing of PVA/silver nitrate films converted the silver to nanoparticles. These films swelled in water to form a robust, wound-compatible hydrogel which exhibited controlled release of the antibacterial silver nanoparticles. An optimal formulation was obtained using 5% (w/w) silver nitrate in PVA membrane films that had been heated at 140 °C for 90 min. Physical and chemical characterization of such films was complemented by in vitro studies that confirmed the effective antibacterial activity of the released silver nanoparticles against both gram positive and negative bacteria. Overall, these findings provide economical and simple methods to manufacture stable, hydrogel forming wound dressings that release antibiotic silver over prolonged periods suitable for emergency use in remote locations.

Cranial floor fracture: A growing orbital roof fracture with encephalocele - Case Report.

Orbital roof fractures are among the rarest of craniofacial fractures. The mechanism of injury is typically a high-impact blunt force vector directly to the orbit or forehead. Most patients are males between 20 and 40 years old, involved in motor vehicle accidents. Although most orbital roof fractures are managed conservatively, there is a significant risk of ophthalmologic and neurologic complications. Detailed craniofacial examination and high-resolution CT imaging is necessary for diagnosis. A multidisciplinary team approach is required for these challenging fractures.

Dissociation in relation to other mental health conditions: An exploration using network analysis.

Dissociative experiences, traditionally studied in relation to trauma and PTSD, may be important phenomena across many different psychological conditions, including as a contributory causal factor for psychotic experiences. In this study, the aim was to explore, using network approaches, how dissociative experiences taking the form of a Felt Sense of Anomaly (FSA) relate to both common mental health conditions and psychotic experiences. 6941 individuals from the general population completed online assessments of FSA-dissociation, post-traumatic stress symptoms (PTSS), anxiety, depression, insomnia, worry, distress tolerance, hallucinations, grandiosity, paranoia, and cognitive disorganization. An undirected partial correlation network analysis was used to explore the network structure, then Bayesian inference with Directed Acyclic Graphs (DAGs) was used to identify potential directions of relationships between dissociation and mental health symptoms. Dissociation was found to be highly connected in both network models. Both networks found direct relationships between dissociation and hallucinations, grandiosity, paranoia, cognitive disorganization, anxiety, depression, and PTSS. In the DAGs analysis, the direction of influence between dissociation and hallucinations, PTSS, anxiety and depression was unclear, however it was found to be probable that dissociation influences paranoia (97.66% of sampled DAGs found the direction dissociation to paranoia, versus 2.34% finding the reverse direction), cognitive disorganization (99.74% vs. 0.26%), and grandiosity (93.49% vs. 6.51%). Further, dissociation was found to be a probable influence of insomnia and distress tolerance via indirect pathways. In summary, dissociation is connected to many mental health disorders, and may influence a number of presentations, particularly psychotic experiences. The importance of dissociation in mental health may therefore currently be under-recognised.

A New Evaluation Method for Medical Image Information Hiding Techniques.

Medical image scans and associated electronic medical records (EMR) could be stored locally or transmitted for use in autodiagnosis and remote healthcare in teleradiology. Hence, they require security against unauthorised access and modification. Among other means of providing this security, information hiding (IH) techniques have gained relevance especially for open networks that are prone to active attacks. However, the evaluation of the suitability of these IH algorithms in terms of preserving medical image diagnostic features is currently limited to signal processing parameters. This paper re-interprets existing evaluation parameters and provides a new framework that allows dynamic selection of medical image IH (watermarking and steganography) security algorithms. Specifically, criteria that capture medical statistics used in the diagnosis and monitoring of patients were incorporated. These criteria and framework were validated on the Pneumonia Chest Xray dataset (used in a Kaggle Competition) using three selected IH algorithms that offer privacy and image tamper detection.

Direct Electrohydrodynamic Patterning of High-Performance All Metal Oxide Thin-Film Electronics.

In this paper, we propose a scalable approach toward all-printed high-performance metal oxide thin-film transistors (TFTs), using a high-resolution electrohydrodynamic (EHD) printing process. Direct EHD micropatterning of metal oxide TFTs is based on diverse precursor solutions to form semiconducting materials (In2O3, In-Ga-ZnO (IGZO)), conductive metal oxide (Sn-doped In2O3 (ITO)), as well as aluminum oxide (Al2O3) gate dielectric at low temperatures. The fully printed TFT devices exhibit excellent electron transport characteristics (average electron mobilities of up to 117 cm2 V-1 s-1), negligible hysteresis, excellent uniformity, and stable operation at low-operating voltage. Furthermore, integrated logic gates such as NOT and NAND have been printed and demonstrated. All-printed logic with individual gating and symmetric input/output behavior, which is crucial for large-scale integration, is also demonstrated. The devices and fabrication process described in this paper enable high-performance and high-reliability transparent electronics.