Miracle-dz/UniFAR-FTUs huggingface dataset:
Horizontally Aligned Carbon Nanotubes on a Quartz Substrate for Chemical and Biological Sensing

We have developed electrolyte-gated sensors based on a field-effect transistor (FET) consisting of horizontally aligned single-walled carbon nanotubes (CNTs) synthesized on single-crystal quartz. Dense well-aligned CNTs serving as device channels enabled high current and large transconductance. Owing to these excellent device properties, the pH resolution was much better in the aligned-channel CNTFETs than in single-channel devices. For immunosensing, selective detection of human immunoglobulin E (IgE) by using aptamer-functionalized CNTFETs was demonstrated in the presence of nontarget proteins at much higher concentration. Moreover, measurements of sensor response versus IgE concentration produced data that fit well to the Langmuir adsorption isotherm. The developed sensors with aligned channels exhibited a drain current of 400-fold that of single-channel devices. Therefore, aligned-channel CNTFETs are useful for highly sensitive and practicable solution sensing.
Targeted Alpha Therapy of mCRPC with 225Actinium-PSMA-617: Dosimetry estimate and empirical dose finding

To develop a treatment protocol for 225Ac-PSMA-617 alpha-radiation therapy in advanced stage, metastatic castration-resistant prostate cancer patients with PSMA-positive tumor phenotype. Methods: A dosimetry estimate was calculated based on time-activity-curves derived from serially performed 177Lu-PSMA-617 scans extrapolated to the physical half-life of 225Ac, assuming instant decay of instable daughter nuclides. Salvage therapies empirically conducted with 50kBq/kg (n=4), 100kBq/kg (n=4), 150kBq/kg (n=2), 200kBq/kg (n=4) 225AcPSMA-617 were evaluated retrospectively regarding toxicity and treatment response. 8 out of 14 patients received further cycles in either 2 or 4 months intervals with identical or de-escalated activities. Results: Dosimetry estimates for 1 MBq of 225Ac-PSMA-617 assuming a relative biological effectiveness of 5 revealed mean doses of 2.3 Sv for salivary glands, 0.7 Sv for kidneys and 0.05 Sv for red marrow that are composed of 99.4% alpha, 0.5% beta and 0.1% photon radiation, respectively. In clinical application, severe xerostomia became the dose-limiting toxicity if treatment activity exceeded 100kBq/kg per cycle. At 100kBq/kg duration of PSA-decline was <4 months, but if therapy was repeated every 2 months patients experienced additive anti-tumor effects. Treatment activities of 50kBq/kg were without toxicity but induced insufficient anti-tumor response in these high tumor burden patients. Remarkable anti-tumor activity by means of objective radiological response or tumor marker decline was observed in 9/11 evaluable patients. Conclusion: For advanced stage patients a treatment activity of 100kBq/kg 225Ac-PSMA-617 per cycle repeated every 8 weeks presents a reasonable trade-off between toxicity and biochemical response.
International Journal for Numerical Methods in Fluids a Fully Non-linear Model for Three-dimensional Overturning Waves over an Arbitrary Bottom

A combined pFFT-multipole tree code, unsteady panel method with vortex particle wakes SUMMARY Potential flow solvers for 3D aerodynamic flows are commonly used in industrial applications. Two main difficulties preventing the even more widespread use of these codes are the limitations on the number of discretization elements and the user expertise and effort required to specify the wake location. In the paper we present an automatic wake generation strategy for a potential flow solver, and accelerate the method using a pFFT-Fast Multipole Tree algorithm. The combined method can be used to simulate both steady and unsteady flows. The steady state solution is achieved by running an unsteady flow simulation until it reaches a steady state. Computation results are given to demonstrate that the method is fast enough to automatically simulate entire heaving and flapping wing crafts in under and hour on a desktop computer.
Recombination and Resistive Losses in Amorphous Silicon / Crystalline Silicon Heterojunction Solar Cells

This contribution investigates the electronic properties of a-Si:H/c-Si solar cells and explains their electrical output parameters open circuit voltage, short circuit current, and fill factor. Our device analysis is based on measurements of the internal quantum efficiency, of current/voltage and capacitance/voltage curves. We find carrier recombination within the crystalline silicon absorber material to be responsible for the limitation of the open circuit voltage. The short circuit current is restricted by collection losses in the absorber material and by absorption in the electrically inactive a-Si:H emitter. Resistive losses affecting the fill factor originate from the transport of minority carriers across the interface. The I/V curves measured at low temperatures reveal a characteristic S-shaped behavior. This effect increases with decrasing temperature and stems from the minority carrier transport, which is hindered by the band offset between a-Si:H and c-Si. We propose a new analytical model to describe this anomalous behavior.
Vehicle Fuel Optimization Under Real-World Driving Conditions: An Explainable Artificial Intelligence Approach

Fuel optimization of diesel and petrol vehicles within industrial fleets is critical for mitigating costs and reducing emissions. This objective is achievable by acting on fuel-related factors, such as the driving behaviour style. In this study, we developed an Explainable Boosting Machine (EBM) model to predict fuel consumption of different types of industrial vehicles, using real-world data collected from 2020 to 2021. This Machine Learning model also explains the relationship between the input factors and fuel consumption, quantifying the individual contribution of each one of them. The explanations provided by the model are compared with domain knowledge in order to see if they are aligned. The results show that the 70% of the categories associated to the fuel-factors are similar to the previous literature. With the EBM algorithm, we estimate that optimizing driving behaviour decreases fuel consumption between 12% and 15% in a large fleet (more than 1000 vehicles).
Model Analysis of High-Fogging Effects on the Work of Compression

In recent years, high fogging has received increasing attention as a comparatively simple and cost-efficient means of gas turbine power augmentation. The effects of high fogging on the work of compression are studied in this paper from a fundamental perspective. Considered is a prototype configuration, namely the evaporation of droplets in an initially saturated mixture of air and water, which is exposed to a prescribed pressure rise. Two different approaches are applied: The first approach (‘ideal model’) assumes that thermodynamic equilibrium prevails. In the second approach (‘droplet model’) the finite time of evaporation is taken into account by introducing discrete droplets and modeling explicitly the heat and mass transfer between liquid and gaseous phase. For compression speeds representative of modern gas turbines, it is found that droplets of 1μm in diameter are small enough to allow for approximate equilibrium during compression. The influence of polytropic efficiency on the gains of high fogging is addressed, and it is shown that high fogging is more effective for compressors of lower efficiency.Copyright © 2003 by ASME
Can We Stop Fake News? Using Agent-Based Modelling to Evaluate Countermeasures for Misinformation on Social Media

The internet and social media have been a huge force for change in our society, transforming the way we communicate and seek information. However, the unprecedented volumes of data have created a unique set of challenges: misinfor-mation, polarization and online conﬂict. Misinformation can be particularly detrimental to society, democracy and public health. As a result, there is a growing area of research into countermeasures against online misinformation. However, much of this research is conducted in small scale experiments and cannot predict the macro-level impact. This paper demonstrates that agent-based modelling can be a useful tool for policy-makers to evaluate these countermeasures at scale before implementing them on a social media platform. This research has the following contributions: (i) Development of an agent-based model of the spread of information on a social media network, based on Twitter. (ii) Calibration and validation of the proposed model by Twitter data following fake and true news stories. (iii) Using agent-based modelling to evaluate the impact of countermeasures on the spread of fake news and on general information sharing.
Chain Mobility, Thermal, and Mechanical Properties of Poly(ethylene furanoate) Compared to Poly(ethylene terephthalate)

Poly(ethylene furanoate) (PEF), the furan-derived analogue to poly(ethylene terephthalate) (PET), can provide a fully biosourced alternative to PET with greatly improved barrier properties and attractive thermal and mechanical properties. The improved barrier for PEF compared to PET is unexpected due to the higher free volume of PEF vs PET. Segmental motions related to penetrant diffusion in both polyesters were studied using dynamic mechanical analysis, 13C–CP/MAS solid-state NMR variable contact-time experiments, and centerband-only detection of exchange (CODEX) measurements. Unlike the active phenyl ring-flipping mechanism in PET, furan ring-flipping is greatly suppressed, thereby reducing β relaxation motions and diffusion in PEF due to the energy penalty associated with the nonlinear axis of ring rotation and ring polarity. Preliminary work also shows similar oxygen solubilities for PEF and PET, thereby proving that the drastic permeability reduction results from a decrease in diffusion coefficient c.
Feedback Graph Attention Convolutional Network for MR Images Enhancement by Exploring Self-Similarity Features

Artifacts, blur, and noise are the common distortions degrading MRI images during the acquisition process, and deep neural networks have been demonstrated to help in improving image quality. To well exploit global structural information and self-similarity details, we propose a novel MR image enhancement network, named Feedback Graph Attention Convolutional Network (FB-GACN). As a key innovation, we consider the global structure of an image by building a graph network from image sub-regions that we consider to be node features, linking them non-locally according to their similarity. The proposed model consists of three main parts: 1) The parallel graph similarity branch and content branch, where the graph similarity branch aims at exploiting the similarity and symmetry across diﬀerent image sub-regions in low-resolution feature space and provides additional priors for the content branch to enhance texture details. 2) A feedback mechanism with a recurrent structure to reﬁne low-level representations with high-level information and generate powerful high-level texture details by handling the feedback connections. 3) A reconstruction to remove the artifacts and recover super-resolution images by using the estimated sub-region self-similarity priors obtained from the graph similarity branch. We evaluate our method on two image enhancement tasks: i) cross-protocol super resolution of diﬀusion MRI; ii) artifact removal of FLAIR MR images. Experimental results demonstrate that the proposed algorithm outperforms the state-of-the-art methods.
A Matter of Kind and Degree

Variables are measurable representations. As such, they are located at the interface between theoretical constructs and empirical observations. For example, the concept of ‘social capital’ is a theoretical construct (see CONCEPT CONSTRUCTION) which can be OPERATIONALIZED using the variable ‘social club membership’. The variable ‘social club membership’ is easier to measure than the abstract notion of ‘social capital’. It also has more conceptual meaning than the observation that person A is a member of a book society. Deductive research identifies variables by operationalizing abstract concepts. Inductive research typically constructs variables from the observation of units (see DEDUCTIVE, INDUCTIVE, AND RETRODUCTIVE REASONING). However, irrespective of whether the research is deductive and theory-driven or inductive and empirically driven, variables occupy a central position in research methodology. They lie halfway between the theoretical and empirical realms. One of the key features of variables is that they vary across UNITS. Any variable can have at least two distinct values (also called attributes). As Gary King, Robert Keohane, and Sidney Verba argue, ‘a variable can represent anything whose values change over a set of units’ (King, Keohane, and Verba 1994: 51). For example, the national economy is not a well-defined variable as it is unclear on which dimension it varies. Variables for a given economy include the main factor of production (with qualitative values, such as labour, capital, and land) and the annual growth rate (with numerical values, ranging from 0 to an infinite number). This contribution is divided into three parts. The first part distinguishes dependent and independent variables, the second part introduces other types of variables, and the third part presents different types of values. The conclusion discusses the EPISTEMOLOGICAL assumptions underlying the notion of variables. The variables of ‘social club membership’ and ‘economic growth’ are used throughout for illustrative purposes.
Chinese Spelling Check based on Neural Machine Translation

We present a method for Chinese spelling check that automatically learns to correct a sentence with potential spelling errors. In our approach, a character-based neural machine translation (NMT) model is trained to translate the potentially misspelled sentence into correct one, using right-and-wrong sentence pairs from newspaper edit logs and artificially generated data. The method involves extracting sentences contain edit of spelling correction from edit logs, using commonly confused right-and-wrong word pairs to generate artificial right-and-wrong sentence pairs in order to expand our training data , and training the NMT model. The evaluation on the United Daily News (UDN) Edit Logs and SIGHAN-7 Shared Task shows that adding artificial error data can significantly improve the performance of Chinese spelling check system.
Ant Thermal Tolerance: A Review of Methods, Hypotheses, and Sources of Variation

Abstract Ants (Hymenoptera: Formicidae) are a conspicuous group of ectotherms whose behavior, distribution, physiology, and fitness are regulated by temperature. Consequently, interest in traits like thermal tolerance that enable ants to survive and thrive in variable climates has increased exponentially over the past few decades. Here, we synthesize the published literature on the thermal tolerance of ants. We begin our review with discussion of common metrics: critical thermal limits, lethal thermal limits, knock-down resistance, chill-coma recovery, and supercooling. In particular, we highlight the ways each thermal metric is quantified and offer a set of methodological caveats for consideration. We next describe patterns and hypotheses for ant thermal tolerance along spatial and temporal temperature gradients. Spatially, we focus on relationships with latitude, elevation, urbanization, and microclimate. Temporally, we focus on seasonal plasticity, daily variation, dominance-thermal tolerance tradeoffs, and acclimation. We further discuss other sources of variation including evolutionary history, body size, age, castes, and nutrition. Finally, we highlight several topics of interest to ant thermal biologists, ranging in scope from methods development to the impacts of climate change.
A Method for the Detection of Potential Fraud of Bringing Feline Meat in Food Chain

Adulteration of meat in processed food is a sensitive issue since certain meat species are prohibited in some religions such as Islam and Judaism. Some meat types are also potential carrier of some deadly diseases such as severe acute respiratory syndrome, anthrax, and hepatitis. Furthermore, unconscious consumption of certain meat might lead to an allergic reaction. Feline meat is not only taboo in most cultures but also under religious prohibition. However, cat meat has been consumed in certain countries including Cambodia, South Korea, China, and Vietnam. Several polymerase chain reaction assays are proposed for the detection of feline meat. However, those assays are not tested under processed food matrices. They are also based on longer targets (672, 331, 274, 180, and 108 bp) which breakdown under compromised states. Here we documented a very short-amplicon-length (69 bp) polymerase chain reaction assay and produced strong evidence that short targets are more stable than the longer ones. Feline specificity was confirmed by cross-challenging against 17 non-target species and target stability was tested after boiling, microwaving, and autoclaving treatments under complex matrices. The tested detection limit was 0.01% (w/w) of feline meat in ternary mixtures and 0.1% (w/w) in cooked meatballs.
Formal schedulability analysis based on multi-core RTOS model

Verification of real-time application schedulability is usually performed using a very abstract representation of the system which poorly supports inter-task dependencies. This paper presents the use of model-checking techniques to check the schedulability on a detailed model of a multi-core operating system. The operating system as a whole is modeled by a High-level Petri net reproducing the control flow and using the same variables as those of the implementation. Each task of the application is represented by a Stopwatch Petri Net whose transitions carry Best-Case Execution Time and Worst-Case Execution Time [BCET, WCET] firing intervals and make service calls to the OS. Preemption is supported by means of stopwatches. Verification is performed using observers and allows to determine the schedulability of the multi-core application, or, using parameters on the firing intervals, allows determining under which temporal conditions the application is schedulable.
Extractivism and Territorial Dispossession in Rural Colombia: A Decolonial Commitment to Campesinas’ Politics of Place

Linked to extractive practices, territorial dispossession can be traced back to the colonisation of Abya Yala. From a decolonial commitment, this article complicates notions of dispossession and extractivism as merely emerging from war in Colombia and focuses on their presence in Campesinas territories. Based on the conceptualisations of the coloniality of power and coloniality of gender, I narrate how territorial dispossession and extractivism are felt in women’s ‘body-lands’ through foreign tourism/conservation development and new export crops in two rural veredas in the Colombian Andes and in the Sierra Nevada de Santa Marta where I conducted participatory visual projects in 2016. From a relational understanding of place, I also demonstrate the ways that the rural population is resisting and negotiating within these processes. Ultimately, I make a call for feminist scholars to politically commit to the dismantling of the coloniality of gender, and to the resistances to territorial dispossession and extractivism (epistemic and economic) that rural women are leading in place in the Global South.
Local material symmetry group for first- and second-order strain gradient fluids

Using an unified approach based on the local material symmetry group introduced for general first- and second-order strain gradient elastic media, we analyze the constitutive equations of strain gradient fluids. For the strain gradient medium there exists a strain energy density dependent on first- and higher-order gradients of placement vector, whereas for fluids a strain energy depends on a current mass density and its gradients. Both models found applications to modeling of materials with complex inner structure such as beam-lattice metamaterials and fluids at small scales. The local material symmetry group is formed through such transformations of a reference placement which cannot be experimentally detected within the considered material model. We show that considering maximal symmetry group, i.e. material with strain energy that is independent of the choice of a reference placement, one comes to the constitutive equations of gradient fluids introduced independently on general strain gradient continua.
Engineering, decoding and systems-level characterization of chimpanzee cytomegalovirus

The chimpanzee cytomegalovirus (CCMV) is the closest relative of human CMV (HCMV). Because of the high conservation between these two species and the ability of human cells to fully support CCMV replication, CCMV holds great potential as a model system for HCMV. To make the CCMV genome available for precise and rapid gene manipulation techniques, we captured the genomic DNA of CCMV strain Heberling as a bacterial artificial chromosome (BAC). Selected BAC clones were reconstituted to infectious viruses, growing to similar high titers as parental CCMV. DNA sequencing confirmed the integrity of our clones and led to the identification of two polymorphic loci within the CCMV genome. To re-evaluate the CCMV coding potential, we analyzed the transcriptome and proteome of infected cells and identified several novel ORFs, splice variants, and regulatory RNAs. We further characterized the dynamics of CCMV gene expression and found that viral proteins cluster into five distinct temporal classes. In addition, our datasets revealed that the host response to CCMV infection and the de-regulation of cellular pathways are in line with known hallmarks of HCMV infection. In a first functional experiment, we investigated a proposed frameshift mutation in UL128 that was suspected to restrict CCMV’s cell tropism. In fact, repair of this frameshift re-established productive CCMV infection in endothelial and epithelial cells, expanding the options of CCMV as an infection model. Thus, BAC-cloned CCMV can serve as a powerful tool for systematic approaches in comparative functional genomics, exploiting the close phylogenetic relationship between CCMV and HCMV.