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The IPCC’s Special Report on Climate Change and Cities shows how cities must adapt to climate risks. Urban planners need to create solutions that fit each city’s needs, enhancing urban adaptability and resilience in the context of increasing climate-related risks. Sustainable urban planning, increased citizen awareness, and resilient infrastructure design are crucial in mitigating the growing impacts of climate change on human settlements. Addressing these challenges requires the integration of perspectives from diverse disciplines, including the natural sciences, social sciences, and engineering fields. This article draws on insights from a collaborative effort among experts in these areas, promoting a more coordinated and interdisciplinary approach. By bridging this expertise, we aim to advance resilience practices and awareness, fostering effective urban climate solutions in Texas and beyond. 

Radiolysis is a complex phenomenon in which molecules subjected to ionizing radiation form new chemical species. Electron-beam irradiation has proven to be a versatile approach for significantly altering materials’ properties and forms the basis for electron-beam lithography using both organic and inorganic resists. Electron-beam exposure is normally carried out under high vacuum conditions to reduce contamination and allow for unhindered interaction between the electrons and the resist material. Exposure under an ambient gas at sub-atmospheric pressures has been found to provide a distinct mechanism which can be exploited to circumvent some of the challenges associated with material processing and significantly alter or enhance material’s properties. This dissertation discusses the modifications in standard electron beam resist characteristics during gas assisted electron beam pattering. We studied the effect of water vapor pressure on positive and negative tone electron-beam patterning of poly methyl methacrylate (PMMA). For both positive and negative-tone patterning, it was found that increasing the water vapor pressure considerably improved the contrast of PMMA. As expected from electron scattering in a gas, the clearing dosage for positive tone patterning gradually increased with vapor pressure. Also, electron scattering in water vapor yielded a substantially larger clear region around the negative-tone patterns. This effect could be useful for increasing the range of the developed region around cross-linked PMMA far beyond the backscattered electron range. As a result, VP-EBL for PMMA offers a new means of tuning clearing/onset dose and contrast while enabling more control over the size of the cleared region around negative-tone patterns. We provide a novel way to simultaneously tune the emission wavelength and enhance the fluorescence intensity of fluorophores formed by irradiating polystyrene with a focused electron beam under various gaseous environments. We studied the effect of electron dose and gas pressure on the emission spectra and photon yield of irradiated polystyrene film on a variety of substrates. Up to 10x enhancement in fluorescence yield was achieved using water vapor and the peak emission wavelength tuned over a wide wavelength range. Thus, localized electron-beam synthesis of fluorophores in polystyrene can be controlled by both dose and by ambient water-vapor pressure. This technique could enable innovative approaches to photonics where fluorophores with tunable emission properties can be locally introduced by electron-beam patterning. We also studied the effect of ambient gases on contrast and resolution of PMMA on conducting and insulating substrates. E-beam exposures were conducted under vacuum conditions and 1 mbar of water vapor, helium, nitrogen and argon to study their effect on contrast and resolution of PMMA on silicon, fused silica and soda lime glass substrates. On silicon, exposure under water vapor yielded contrast values significantly higher than vacuum exposure, consistent with our previous work. However, exposure under helium yielded slightly improved contrast compared to vacuum exposure. On insulating substrates exposure under helium environment yielded contrast values significantly higher compared to vacuum exposure. The clearing dose was found to increase with the gases’ molecular weight and proton number, consistent with the increase in scattering cross-section. The improved contrast and sensitivity (dose to clear) of PMMA under helium motivated us to study the resolution under various gases. Resolution testing indicated that despite the lower clearing dose, helium still exhibited the best resolution with 25-nm half-pitch dense lines and spaces clearly resolved on soda lime glass. Thus, VP-EBL of PMMA under helium yields higher sensitivity and contrast on insulating substrates without sacrificing resolution. 

IntroductionThe long-distance, seasonal migrations of birds make them an effective ecological bridge for the movement of ticks. The introduction of exotic tick species to new geographical regions can cause the emergence of novel tick-borne pathogens. This study examined the prevalence of exotic tick species parasitizing migratory songbirds at stopover sites along the northern Gulf of Mexico using the mitochondrial 12S rRNA gene. MethodsOverall, 421 individual ticks in the generaAmblyomma,Haemaphysalis, andIxodeswere recorded from 28 songbird species, of whichAmblyommaandAmblyomma longirostrewere the most abundant tick genera and species, respectively. A high throughput 16S ribosomal RNA sequencing approach characterized the microbial communities and identified pathogenic microbes in all tick samples. Results and discussionMicrobial profiles showed that Proteobacteria was the most abundant phylum. The most abundant pathogens wereRickettsiaand endosymbiontFrancisella,Candidatus Midichloria, andSpiroplasma. Permutation multivariate analysis of variance revealed that the relative abundance ofFrancisellaandRickettsiadrives microbial patterns across the tick genera. We also noted a higher percentage of positive correlations in microbe-microbe interactions among members of the microbial communities. Network analysis suggested a negative correlation between a)FrancisellaandRickettsiaand, b)FrancisellaandCutibacterium. Lastly, mapping the distributions of bird species parasitized during spring migrations highlighted geographic hotspots where migratory songbirds could disperse ticks and their pathogens at stopover sites or upon arrival to their breeding grounds, the latter showing mean dispersal distances from 421–5003 kilometers. These findings spotlight the potential role of migratory birds in the epidemiology of tick-borne pathogens. 

To our knowledge, these are the first studies of molecules other than water for EBL in gaseous environments. Exposure of PMMA under helium yields higher sensitivity, contrast (12.5) and the highest resolution (25-nm half-pitch dense lines and spaces) demonstrated to date for EBL on insulating substrates in a gaseous environment. 

Social scientists and computer scientists are increasingly using observational digital trace data and analyzing these data post hoc to understand the content people are exposed to online. However, these content collection efforts may be systematically biased when the entirety of the data cannot be captured retroactively. We call this often unstated assumption the problematic assumption of accessibility. To examine the extent to which this assumption may be problematic, we identify 107k hard news and misinformation web pages visited by a representative panel of 1,238 American adults and record the degree to which the web pages individuals visited were accessible via successful web scrapes or inaccessible via unsuccessful scrapes. While we find that the URLs collected are largely accessible and with unrestricted content, we find there are systematic biases in which URLs are restricted, return an error, or are inaccessible. For example, conservative misinformation URLs are more likely to be inaccessible than other types of misinformation. We suggest how social scientists should capture and report digital trace and web scraping data. 

Reliable nanoswitch operation requires low contact voltages and stable electrical contact resistance (ECR). Surface cleanliness is crucial to prevent nanomechanical switch failure, which can occur due to the presence of insulating adventitious hydrocarbon films. In situ O2 plasma cleaning is effective but oxidizes metal surfaces. Here, the noble metal Pt, which forms PtOx, is employed to form electrodes. Previous studies report on PtOx electrical resistivity, but the effects of PtOx evolution at contacting interfaces due to electrical and mechanical stimuli have not been explored. This study investigates the impact of PtOx on ECR at low contact voltages under hot switching, cold switching, and mechanical cycling conditions. An increase in ECR upon plasma cleaning indicates the presence of a resistive PtOx layer. After hot and cold switch cycling at applied voltages of 300 mV or less, a low stable ECR is achieved. A higher contact voltage accelerates ECR stabilization. The results are consistent with PtOx film volatilization, which is primarily due to Joule heating rather than mechanical rupture. This investigation advances the understanding of interface evolution in plasma-cleaned nanoswitches. 

PurposeThe purpose of this study is to develop a deep learning framework for additive manufacturing (AM), that can detect different defect types without being trained on specific defect data sets and can be applied for real-time process control. Design/methodology/approachThis study develops an explainable artificial intelligence (AI) framework, a zero-bias deep neural network (DNN) model for real-time defect detection during the AM process. In this method, the last dense layer of the DNN is replaced by two consecutive parts, a regular dense layer denoted (L1) for dimensional reduction, and a similarity matching layer (L2) for equal weight and non-biased cosine similarity matching. Grayscale images of 3D printed samples acquired during printing were used as the input to the zero-bias DNN. FindingsThis study demonstrates that the approach is capable of successfully detecting multiple types of defects such as cracks, stringing and warping with high accuracy without any prior training on defective data sets, with an accuracy of 99.5%. Practical implicationsOnce the model is set up, the computational time for anomaly detection is lower than the speed of image acquisition indicating the potential for real-time process control. It can also be used to minimize manual processing in AI-enabled AM. Originality/valueTo the best of the authors’ knowledge, this is the first study to use zero-bias DNN, an explainable AI approach for defect detection in AM. 

We establish the existence of a cusp in the curvature of a solid sheet at its contact with a liquid subphase.