Note: Scanning Nano Lithography or Scanning Nano Lithography  enables the original or improved nano pattern in applied fields ranging from quantum technologies to material science.In particular, ultra-fast and highly localized thermal processing of surfaces can be achieved through a sharp heating tip to create high-resolution patterns. Many possible applications of nanoscale modifications with thermal probes such as Scanning Nano Lithography are still applicable in nanoelectronics, especially when which can use extremely high heating and cooling rates.Many microsystems and nanosystems require precise nanoscale patterns that exhibit intrinsic functionality, such as some electronic properties. , photonic, chemical and mechanical. To make these nanoscale patterns, electron beam lithography is the most common lithography technique without direct writing and without mask.Scanning Nano Lithography A complex electron compatible optic is required to focus the electron beam into a spot of a few nanometers. Another issue is electron scattering, a kind of proximity effect, on the surface of the sample, which leads to the exposure of additional undesirable resistivity that must be corrected by intensive calculation algorithms. Scanning Nano Lithography is another method of direct writing nanolithography, where patterns are created by scanning a nanometer tip on the sample to create local changes.  Sample-sample interactions are numerous and can include mechanical, electrical, diffusion, and thermal effects.

Photocatalytic processes of carbon dioxide (CO2) conversion and molecular hydrogen (H2) production could potentially address two major global challenges: greenhouse gas (GHG) mitigation and clean energy generation, respectively. During photocatalysis, the energy harvested via the light absorption in photosensitizers drives the important chemical reactions using the photogenerated charges to convert water into H2 or CO2 into value-added products. Recent decades have witnessed the widespread popularity of photocatalytic technology owing to its sustainable, renewable, and greener pathway to produce fuels and chemicals. Given this, a wide range of materials have been explored for photocatalytic applications. Among the developed materials, Ni-based photocatalysts have received considerable attention due to their distinct properties including low cost, stability, abundance, and high activity. This review addresses recent developments concerning nickel (Ni)-based photocatalysts used in photocatalytic CO2 conversion and H2 production. The use of Ni-materials plays a crucial role in enhancing photocatalytic activity through improved light-absorption, charge-separation, along with suppressed charge recombination to enhance the efficiency of hydrogen evolution and CO2 conversion. The performance of nickel-based photocatalysts during CO2 reduction and water splitting reactions is summarized, which provide a comprehensive overview of Ni-based photocatalyst efficiency and selectivity. Finally, challenges and future prospects are examined in detail for further optimization of Ni-based photocatalysts. This review also provides an update on the studies that have been conducted on Ni-based materials for H2 generation and CO2 reduction.

Progress in Li-O2 battery (LOB) research is pivotal for achieving the ambitious goal of full electrification of transport. However, difficulties in promptly catalysing the sluggish oxygen kinetics remain the long outstanding challenge hindering the progress in LOB technology. Herein, the groundsel flower-like hierarchical microsphere network of NiCoP/NiCo2O4 (NCP@NCO/Ni) is synthesised in situ grafting on nickel foam as a high-performing oxygen cathode for LOBs. Both oxygen reduction and evolution reactions are kinetically enhanced by the presence of heterogeneous NiCoP and NiCo2O4 promoting surface electron transfer. The assembled LOB cells demonstrate an exceptional lifespan, withstanding over 400 cycles under a very high charge rate of 800 mAg-1 while achieving the highest discharge/ charging capacities of 15710/ 14632 mAh g-1 at 100 mAg-1 with low charging overpotentials, owing to unique catalytic support and fast charge transfer occurred across the interface in the heterostructure. Interestingly, the discharge capacity is only reduced by 10% to 14092 mAh g-1 even after the charge rate increases by 6 times, where the capacities of the pure metal phosphide and metal oxide cathodes fade substantially. The facile decomposition of sheet-like Li₂O₂ well-attached to the cathode surface enhances the cell’s reversibility and performance, overcoming the drawbacks of alternative Li₂O₂ morphologies.

Traditionally, vulnerability assessments for climate change risks rely on randomized precipitation possibilities and lack a physical science basis. Additionally, limitations in representing local precipitation fields in General Circulation Models (GCM) hinder the usefulness of precipitation projections of future hydroclimatic extremes. To address these challenges in climate risk management, this study investigates the ability of large-scale atmospheric circulation patterns, or weather regimes (WRs), to explain local precipitation and regional precipitation drivers. Utilizing a Non-Homogeneous Hidden Markov Chain approach, we identified six primary WRs for South Africa, each exhibiting distinct seasonality. Three WRs, associated with higher precipitation near Cape Town, dominate in winter, while two WRs linked to lower precipitation are prevalent in summer. The WR-precipitation relationship in South Africa appears to be influenced by topographic features (e.g., The Great Escarpment and Cape Fold Mountains) and ocean currents (Agulhas and Benguela), leading to distinct spatial precipitation responses to regional WR configurations. The seasonal frequency of WRs in the South African region has shifted dramatically in the past 20 years. Changes in WR composition, particularly the replacement since 2010 of a WR associated with rain in Cape Town with a dry WR, may help to explain the worsening drought conditions in the past decade. During the 2015-2017 Day Zero drought in Cape Town, the regional WR associated with dryness in Cape Town occurred more frequently than the historical average. The insights from the WR-precipitation analysis can be used to inform WR-based stochastic weather generators for vulnerability assessment and climate change adaptation planning.

Since its detection by Mariner 10, Helium has been a key focus in studies of Mercury’s exosphere. Recently, Weichbold et al. (2024) provided the first in-situ Helium measurements, inferring density from Ion Cyclotron Wave (ICW) events observed by the MESSENGER spacecraft. This approach enables, for the first time, a Helium density profile across a broad altitude range without relying on prior models. We present an ab-initio model for a steady-state, solar wind-driven Helium exosphere, which informed the interpretation of these ICW measurements. We discuss Helium release processes and evaluate whether meteorite impacts could account for specific instances of elevated Helium measurements. We developed a global, semi-analytical model based on a Helium-saturated regolith and an average Helium source flux of 2.5x10²³ He/s from solar wind ion implantation. We calculate the Helium flux distribution using an analytical lateral transport model and then generate local radial density profiles from a numerical (Monte Carlo) radial transport model. Additionally, we applied the radial transport model to estimate the scale and duration of large, sporadic Helium release events and assess the likelihood of detecting these events in-situ. The strong agreement between our model and the novel measurements confirms that the measurable Helium exosphere is dominated by thermally recycled particles. We show that elevated Helium measurements can result from the vaporization and release of Helium from large (1m) meteorite impacts, but it is statistically unlikely that more than one impact event is captured in the given set of measurements.

A document by Han Qiu. Click on the document to view its contents.

The full-hydrometeor four-dimensional variational (4D-Var) assimilation scheme in the Weather Research and Forecasting (WRF) model, based on the WRF single-moment 6-class microphysics scheme (WSM6), is utilized to assimilate precipitation data. The focus is on short-term convective precipitation forecasts influenced by the Northeast cold vortex (NCCV). Four assimilation experiments were designed to compare the warm rain scheme with the full-hydrometeor scheme, as well as to examine the differences between assimilating hourly surface rain gauge data and multi-source integrated precipitation products. Ten cases of intense convective precipitation related to NCCV were analyzed. The results demonstrate that the initial analysis of ice-phase hydrometeors was satisfactory across the three experiments utilizing the full-hydrometeor 4D-Var schemes. The assimilation of precipitation data full-hydrometeor scheme in WRF 4D-Var effectively adjusted atmospheric thermodynamic properties and decreased model spin-up time, leading to improved precipitation forecasts, especially for the 0-3 hour period. Furthermore, the assimilation of rain gauge data or multi-source integrated precipitation data has been demonstrated to be an effective approach for enhancing the accuracy of weather forecasts.

Workplace ostracism can undermine employee morale, reduce productivity, and negatively impact organizational outcomes. Sparking leadership plays a vital role in shaping workplace culture and mitigating ostracism's effects. This study investigates the mediating role of work engagement in the relationship between organizational ostracism and sparking leadership. By examining data from 790 healthcare professionals in Turkey, the research highlights how sparking leadership can enhance work engagement and reduce ostracism. The findings show a significant negative correlation between sparking leadership and organizational ostracism, with work engagement serving as a key mediator. As perceptions of sparking leadership rise, ostracism decreases, leading to improved organizational performance. This study emphasizes the importance of sparking leadership in creating inclusive, high-performing workplace environments.

Ransomware attacks have become increasingly sophisticated, targeting critical systems and exploiting vulnerabilities at multiple stages of the attack lifecycle. A novel framework is introduced that leverages multicriteria decision-making (MCDM) to enhance ransomware detection through the integration of MITRE ATT&CK strategies, allowing for automated, real-time prioritization and mitigation of ransomware behaviors. The framework dynamically evaluates criteria such as attack severity, system detectability, and resource constraints, enabling a more adaptive and comprehensive approach to ransomware defense. The significance of this approach lies in its ability to automate decision-making processes without requiring human intervention, providing faster and more accurate mitigation strategies. Experiments demonstrated that the proposed system consistently outperformed traditional rule-based systems, offering a scalable solution for real-time cybersecurity operations.

In this letter, to handle the over-generation issue of photovoltaic (PV) systems based on maximal power point tracking (MPPT) algorithms, and to provide the power reservation for power grids, an optimal point shifting design based on virtual impedance is proposed for PV systems with flexible power point tracking. With the introduction of the virtual impedance, the virtual PV power is provided to auto-shift optimal power points on PV power-voltage curves. With a MPPT algorithm applied to the virtual PV power, the actual PV power is auto-turned without the estimation of maximum available PV power. The proposed design is validated through simulation studies of a PV-battery charging system and experimental studies of a grid-tied PV system, where both the overcharging of the battery and the over PV power generation are effectively avoided by reducing actual PV power according to the increasing of the battery SOC or the grid RMS voltage, respectively.

Abstract

Visual Tourettic OCD (VTO), also referred to as “Staring OCD”, is a symptom presentation that is characterized by a fear of staring at other people’s genitals or private body parts. Those with VTO also often experience somatic sensations similar to premonitory sensations in tic disorders (e.g., tingling around the eyes) leading some to suggest that this symptom presentation should be viewed as a distinct form of “Tourettic OCD” (TOCD) in which symptoms of OCD and chronic tic disorders are closely intertwined. Consequently, it has also been argued that existing cognitive-behavioral interventions for OCD need to be adapted to address the unique features of TOCD. The current case study describes the application of inference-based cognitive behavioral therapy (I-CBT) for a 52-year-old with a symptom presentation of VTO, including symptoms resembling those commonly ascribed to TOCD (tics, compulsions, and premonitory urges). Over the course of 16 weekly sessions with I-CBT, the client reached the complete remission of OC symptoms, together with a significant reduction in related symptoms (e.g., depression, social anxiety). Implications for the conceptualization and treatment of forms of OCD that appear to be intertwined with tic disorders will be discussed.

The Yarlung Zangbo River (YLZB), as the highest plateau river in the world, has a particularly fragile ecological environment and is easily impacted by global climate change. Studying the changes in its habitat quality and the driving mechanisms behind them is crucial for the ecological protection and sustainable development of the YLZB. Based on land use data from 2000 to 2020, using a habitat quality model, optimal parameter geographical detector, and partial least squares structural equation model (PLS-SEM), we conducted a quantitative study on the spatiotemporal changes and driving mechanisms of habitat quality in the YLZB from 2000 to 2020. The results show that: (1) Forests, grasslands, and unused land account for 94.14% of the basin area. The areas of unused land, forest land, and water bodies have continuously increased, while the areas of grasslands, permanent glaciers, and snowfields have continuously decreased. The decline was most pronounced from 2005 to 2010. The habitat quality in the study area is higher in the southeast and lower in the west. The area of degraded habitats is significantly larger than that of improved habitats. (3) NDVI, elevation, and annual average temperature are key factors affecting changes in habitat quality. Elevation indirectly affects NDVI by influencing climate conditions, leading to a decline in habitat quality. Our research findings help to better understand the ecological dynamics within the basin and provide scientific insights for sustainable management and conservation efforts.

A document by Naven Narayanan . Click on the document to view its contents.

: A total of 17605 gene sequences were obtained from transcriptome sequencing, 12,368 predictable proteins, 278 transcription factors and 51 family information of transcription factors were obtained through database comparison; 10072 peptides were found in the process of proteome identification, and 1917 protein components were deduced from the peptides; we matched 6758 peptides to 33834 peptides in the transcriptome database in the process of peptide identification; we further detected the protein changes of whole scorpion tail and whole scorpion tail removal in the bulk and tonic by protein de novo sequencing. In the identification of peptidome, we found 6758 peptides in the transcriptome database, and 33834 peptides were identified by protein de novo sequencing; by further examining the protein changes in the tails of scorpion and the tail of scorpion in the powder and decoction, it was found that different parts of the drug and the method of drug administration may lead to changes in the function of scorpion, for example, if the scorpion is powdered into medicine in bulk, the protein components are preserved more intact, and the efficacy is closely related to inflammatory response and signal transduction; In the decoction, the protein components are destroyed and hydrolysed into amino acids and peptide segments, and the efficacy is closely related to the regulation of amino acids and the maintenance of energy and other function

Protein-protein interactions (PPIs) are a major component of cellular organization, function, and biochemical reactions. Experimental detection of PPIs through high-throughput techniques as well as structure-based docking is costly and time-consuming. Existing computational techniques that use statistical measures or machine-learning algorithms are prone to overfitting and vulnerable to data noise or bias. To overcome these problems, we propose a deep-learning-based PPI prediction model, AttnSeq-PPI which is a combination of self and cross-attention with convolution operation. Protein sequences were embedded to vectors using the word2vec algorithm to generate a feature matrix. The attention mechanism captures relationships between distant elements in a sequence and understands complex patterns and dependencies. The 1-D convolution operation is used to extract the local features of the sequence, reducing the dimension of the vector and computational cost. Our proposed model was trained using intra-species human and multi-species datasets, validation was performed using four independent species and PPI network datasets. AttnSeq-PPI is very effective in performing the prediction and also in generalization ability, it outperformed the existing state-of-the-art models. The accuracy of our proposed model is 98.81% and recall is 98.67 % for the human dataset and can predict unknown protein pairs with fewer false negatives with higher precision.

Masking is a reporting bias where drug safety signals are muffled by elevated reporting of other medications in spontaneous reporting databases. While impacts of masking are often limited, its effect on restricted designs, such as active comparators, can be consequential. We used data from the United States Food and Drugs Administration Adverse Event Reporting System (1999Q3-2013Q3) to study masking in a real-world example. Rosiglitazone, a thiazolidinedione with elevated reporting after safety concerns over cardiovascular risks, was the masking candidate. We hypothesized stimulated reporting masked signals for another thiazolidinedione, pioglitazone. We computed estimates of proportional reporting ratios and information components, using the Bayesian confidence propagation neural network, for pioglitazone-myocardial infarction and pioglitazone-cardiac failure under unrestricted and active comparator designs, both with and without the mask, and before (1999Q3-2007Q1) and after (2007Q1-2013Q3) safety concerns. Relative change-in-estimates were computed to compare results with and without rosiglitazone. From 1999Q3-2007Q1, relative change-in-estimates of proportional reporting ratio for pioglitazone-myocardial infarction was 0.00 in unrestricted design and 0.10 in active comparator; For pioglitazone-cardiac failure, the change was 0.01 and 0.62, respectively. From 2007Q2-2013Q3, relative change in estimate for pioglitazone-myocardial infarction was 0.41 in unrestricted design and 18.00 in active comparator; the change for pioglitazone-cardiac failure was 0.04 and 1.03, respectively. Relative changes in estimates of information component mirrored these trends. In conclusion, masking can influence signal detection in active comparator designs where external events impact reporting rates in reference sets. Evaluating masking in related contexts is essential for drug safety monitoring and resource allocation for follow-up studies.

Montane cloud forest (MCF) is a rare and vulnerable forest type endangered by anthropogenic habitat loss and climate change impact. Understanding how fog affects the plant community is therefore an urgent task for conservation. We aim to clarify the relationship between fog frequency and environmental factors and evaluate the effect of fog frequency on woody species functional traits. We set up a horizontal transect along the fog frequency gradient in northeastern Taiwan at the elevation around 2000 m asl, in the winter monsoon-affected MCF. In each of 27 plots we collected species composition, leaf and wood functional traits of woody species, and climatic and soil properties. We used Pearson’s correlation to clarify the fog-environment relationships, and simple linear regression to test the relationship between fog frequency and site-specific, inter-specific, and intra-specific community-weighted mean (CWM) of functional traits. We found that in foggier sites, higher precipitation may contribute to the stronger leaching effect, which can lead to lower soil phosphorus content. Also, in this winter-monsoon-influenced cloud forest, foggier sites experience a longer time under subfreezing temperatures (-2.22˚C), explaining the lower specific leaf area (SLA) and higher leaf dry matter content (LDMC) in intra-specific CWM in foggier sites. Also, owing to the unbalanced freezing stress on leaves between evergreen and deciduous species in winter, deciduous species (with high SLA) aggregate more in foggier sites, which may be the reason for higher inter-specific SLA CWM observed there. Although our study is purely observational, we believe that careful selection of plots along the fog frequency gradient in similar elevation allowed us to eliminate most of the confounding environmental factors. It represents unique example of trait changes along fog frequency gradient and brings new ecological explanations. We hope the results can be useful for both theoretical science and also for conservation management decisions.

On the flanks of >6000 m Andean volcanoes that tower over the Atacama Desert, leaf-eared mice (Phyllotis vaccarum) live at extreme elevations that surpass known vegetation limits. What the mice eat in these barren, hyperarid environments has been the subject of much speculation. According to the arthropod fallout hypothesis, sustenance is provided by windblown insects that accumulate in snowdrifts (‘aolian deposits’). It is also possible that mice feed on saxicolous lichen or forms of cryptic vegetation that have yet to be discovered at such high elevations. We tested hypotheses about the diet of mice living at extreme elevations on Atacama volcanoes by combining metagenomic and DNA metabarcoding analyses of gut contents with stable-isotope analyses of mouse tissues. Genomic analyses of contents of the gastrointestinal tract of a live-captured mouse from the 6739 m summit of Volcán Llullaillaco revealed evidence for an opportunistic but purely herbivorous diet, including lichens. Although we found no evidence of animal DNA in gut contents of the summit mouse, stable isotope data for a larger sample of mice indicate that mice native to elevations at or near vegetation limits (~5100 m) include a larger fraction of animal prey in their diet than mice from lower elevations. Some plants detected in the gut contents of the summit mouse are known to exist at lower elevations at the base of the volcano and in the surrounding Altiplano, suggesting that such species may occur at higher elevations beneath the snowpack or in other cryptic microhabitats.

Background: Post-COVID-Syndrome (PCS) is the term for a condition with persistent symptoms in a proportion of COVID-19 patient after asymptomatic, mild or severe disease courses. Numbers vary but the current estimate is that after COVID-19 approximately 10% develop PCS. The aim of our study was to evaluate the impact of SARS-CoV-2 infection on the gastrointestinal (GI) tract and associations with the development of PCS with fatigue, post-exertional malaise (PEM), orthostatic dysregulation, autonomous dysregulation and/or neurocognitive dysregulation. Methods: By combining medical record data from a prospective observational study with symptom analysis before, during, and after SARS-CoV-2 infection, we aimed to identify potential risk factors and predictive markers for PCS. Additionally, we analyzed blood, saliva, and stool samples from this well-characterized PCS patient cohort to biologically validate our findings. Results: We identified significant associations between pre-existing GI complaints and the development of PCS Fatigue. PCS patients showed higher LBP/sCD14 ratios, lower IL-33 levels, and higher IL-6 levels compared to control groups. Our results highlight the critical role of the GI tract in PCS development of post-viral Fatigue. Conclusion: We propose that the viral infection disrupts pathways related to the innate immune response and GI barrier function, evidenced by intestinal low-grade inflammation and GI barrier leakage. Monitoring GI symptoms and markers before, during and after SARS-CoV-2 infection is crucial for identifying predictive clinical phenotypes in PCS. Understanding the interaction between viral infections, immune responses, and gut integrity could lead to more effective diagnostic and treatment strategies, ultimately reducing the burden on PCS patients.

X-linked chronic granulomatous disease (X-CGD) may be associated with McLeod syndrome (MLS) as a contiguous gene deletion syndrome. MLS is characterized by the loss of XK protein together with Kx antigen on red blood cell (RBC) surfaces and late-onset neurocognitive symptoms. X-CGD treatment involves hematopoietic cell transplantation (HCT), and severe hemolysis may occur due to Kx antigen sensitization. Here, we report successful HCT in a 7-year-old male with X-CGD and MLS achieved by depleting RBCs from the graft and adding rituximab to the conditioning regimen. No hemolytic events occurred, and he is doing well 2 years after HCT.

Our ability to recognize tens of thousands of words is attributed to a rich lexicon in our brains, referred to as the orthographic lexicon. Understanding how this lexicon is organized in the brain is key to uncovering the neural mechanisms of visual word recognition. Event-related potentials (ERPs) are an effective tool for investigating these mechanisms. A widely observed phenomenon in orthographic processing is a 250-ms ERP difference between real words and pseudowords (or between high-frequency (HF) and low-frequency (LF) words). However, this 250-ms ERP difference has been explained by competing theories—one attributing it to the activation of the orthographic lexicon, and the other suggesting it represents a prediction error signal related to orthographic processing. To resolve this debate, the present study uses handwritten words as control stimuli alongside printed words, as the 250-ms ERP difference is not observed with handwritten words. ERPs were obtained during an implicit reading task (color decision) for printed HF words, printed LF words, handwritten HF words, and handwritten LF words. The results show that the 250-ms ERP difference is significant when comparing printed LF words to handwritten LF words, but not when comparing printed HF words to handwritten HF words. This finding suggests that the 250-ms ERP difference reflects a prediction error rather than activation of the orthographic lexicon. These results support the Interactive Account of orthographic processing, clarify previous ERP findings in the literature, and underscore the potential applications of the 250-ms ERP difference (labeled as ND250) in future research.

Drug development for children presents unique challenges and is highly regulated. Novel approaches, such as the use of extrapolation to address for example the need to avoid unethical studies, whilst supporting robust evidence generation have been developed in support of benefit/risk considerations by regulatory authorities. This is only one step in the decision-making process towards access, which in Europe also includes health technology assessment (HTA) bodies. Discussions related to evidentiary requirements in small populations through the use of evidence transfer has been identified as a priority action by EMA/ EUnetHTA 21. We describe the outcome of this work; reflect on the discussions taken place how to leverage prior knowledge through identifying and addressing uncertainties during life cycle management to support regulatory and HTA decision making. Through examples, we discussed the spectrum of use to support evidence generation, and developed regulatory and HTA reflections on general design considerations important for robust evidence generation; reflective of the joint ambition. Early interactions with all respective stakeholders, particularly between regulators and HTA bodies are key to optimise data generation and utility in children. In Europe, the HTA regulation will offer opportunities for collaborations, which are important for all development efforts. We collaboratively explored the unique specific challenges relating to paediatric drug development, ethically and in its ability to leverage prior knowledge, as exemplified using extrapolation. Learnings from these offers opportunities to further develop methodology how to leverage uncertainties across a product’s life cycle for small populations generally.

A novel optimal LQR state-feedback control law is proposed for energy harvesting maximization in regenerative suspension systems where an actively governed electromechanical actuator is used in place of the viscous damper. A special LQR cost function is considered that directly maximizes the electrical power generated by the electromechanical actuator. Other conflicting control objectives, such as ride comfort and road handling, may be considered along with the energy harvesting objective in the proposed control setup, allowing one to directly trade-off among them depending on the application. Specifically, as an example, a condition for trading-off between energy harvesting and ride comfort is added to the optimization problem via forcing a bound on the so called Ride Index. The proposed control law is finally contrasted with other two control strategies usually considered in the literature for energy harvesting applications and is compared in simulative studies via MATLAB and Simulink on a quarter-car model.