Miracle-dz/UniFAR-FTUs huggingface dataset:
Opto-Thermal Investigation of Additively Manufactured Steel Samples as a Function of the Hatch Distance

Nowadays, additive manufacturing processes are becoming more and more appealing due to their production-oriented design guidelines, especially with regard to topology optimisation and minimal downstream production depth in contrast to conventional technologies. However, a scientific path in the areas of quality assurance, material and microstructural properties, intrinsic thermal permeability and dependent stress parameters inhibits enthusiasm for the potential degrees of freedom of the direct metal laser melting process (DMLS). Especially in quality assurance, post-processing destructive measuring methods are still predominantly necessary in order to evaluate the components adequately. The overall objective of these investigations is to gain process knowledge make reliable in situ statements about component quality and material properties based on the process parameters used and emission values measured. The knowledge will then be used to develop non-destructive tools for the quality management of additively manufactured components. To assess the effectiveness of the research design in relation to the objectives for further investigations, this pre-study evaluates the dependencies between the process parameters, process emission during manufacturing and resulting thermal diffusivity and the relative density of samples fabricated by DMLS. Therefore, the approach deals with additively built metal samples made on an EOS M290 apparatus with varying hatch distances while simultaneously detecting the process emission. Afterwards, the relative density of the samples is determined optically, and thermal diffusivity is measured using the laser flash method. As a result of this pre-study, all interactions of the within factors are presented. The process variable hatch distance indicates a strong influence on the resulting material properties, as an increase in the hatch distance from 0.11 mm to 1 mm leads to a drop in relative density of 57.4%. The associated thermal diffusivity also reveals a sharp decrease from 5.3 mm2/s to 1.3 mm2/s with growing hatch distances. The variability of the material properties can also be observed in the measured process emissions. However, as various factors overlap in the thermal radiation signal, no clear assignment is possible within the scope of this work.
Smart sensor interfacing circuit using square-rooting current-to-frequency conversion

A universal sensor interfacing circuit is presented in this paper. It is capable of giving a digital output directly proportional to various types of measured quantities, where those measured quantities are proportional to the square root of some other type of quantity. This sensor interfacing circuit is a square-rooting current-to-frequency converter. The design is based on two current-controlled resistors in CMOS technology with bisection of the input voltage used in place of the ordinary resistors within the relaxation oscillator. There is no need for highly stable voltage or current references in the proposed design. The temperature stability of the design is achieved without the need for any specific setting of the process parameters. Experimental results, obtained on a circuit implemented by discrete components, confirm the predictions of the analysis performed. The relative errors are less than 1% for the input current range from 12 µA to 650 µA, and for the output frequency range from 231 Hz to 2.625 kHz. A solution for extending the input current dynamic range is also given in the paper.
TapChain: A Rule Chain Recognition Model Based on Multiple Features

Trigger-action programming (TAP) is an intelligent tool, which makes it easy for users to make intelligent rules for IoT devices and applications. Unfortunately, with the popularization of TAP and more and more rules, the rule chain from multiple rules appears gradually and brings more and more threats. Previous work pays more attention to the construction of the security model, but few people focus on how to accurately identify the rule chain from multiple rules. Inaccurate identification of rule chains will lead to the omission of rule chains with threats. This paper proposes a rule chain recognition model based on multiple features, TapChain, which can more accurately identify the rule chain without source code. We design a correction algorithm for TapChain to help us get the correct NLP analysis results. We extract 12 features from 5 aspects of the rules to make the recognition of the rule chain more accurate. According to the evaluation, compared with the previous work, the accuracy rate of TapChain is increased by 3.1%, the recall rate is increased by 1.4%, and the precision rate can reach 88.2%. More accurate identification of the rule chain can help to better implement the security policies and better balance security and availability. What’s more, according to the rule chain that TapChain can recognize, there is a new kind of rule chain with threats. We give the relevant case studies in the evaluation.
Adjoint network of periodically switched linear circuits

This paper presents a general theory of the adjoint network of multiphase periodically switched linear (PSL) circuits in frequency domain. The phasor representation of Tellegen's theorem for PSL circuits in the steady-state is introduced and the adjoint networks of elements typically encountered in PSL circuits are developed. It is shown that the transfer functions from multiple input sources to one output of a PSL circuit can be computed efficiently by solving the adjoint network of the circuit only once. More importantly, it is demonstrated that the aliasing transfer functions from the input sources in the side bands to the output in the base band can be obtained efficiently by computing the corresponding high-order frequency components of the response of the adjoint network of the circuit.
Co-existing TP53 and ARID1A mutations promote aggressive endometrial tumorigenesis

TP53 and ARID1A are frequently mutated across cancer but rarely in the same primary tumor. Endometrial cancer has the highest TP53-ARID1A mutual exclusivity rate. However, the functional relationship between TP53 and ARID1A mutations in the endometrium has not been elucidated. We used genetically engineered mice and in vivo genomic approaches to discern both unique and overlapping roles of TP53 and ARID1A in the endometrium. TP53 loss with oncogenic PIK3CAH1047R in the endometrial epithelium results in features of endometrial hyperplasia, adenocarcinoma, and intraepithelial carcinoma. Mutant endometrial epithelial cells were transcriptome profiled and compared to control cells and ARID1A/PIK3CA mutant endometrium. In the context of either TP53 or ARID1A loss, PIK3CA mutant endometrium exhibited inflammatory pathway activation, but other gene expression programs differed based on TP53 or ARID1A status, such as epithelial-to-mesenchymal transition. Gene expression patterns observed in the genetic mouse models are reflective of human tumors with each respective genetic alteration. Consistent with TP53-ARID1A mutual exclusivity, the p53 pathway is activated following ARID1A loss in the endometrial epithelium, where ARID1A normally directly represses p53 pathway genes in vivo, including the stress-inducible transcription factor, ATF3. However, co-existing TP53-ARID1A mutations led to invasive adenocarcinoma associated with mutant ARID1A-driven ATF3 induction, reduced apoptosis, TP63+ squamous differentiation and invasion. These data suggest TP53 and ARID1A mutations drive shared and distinct tumorigenic programs in the endometrium and promote invasive endometrial cancer when existing simultaneously. Hence, TP53 and ARID1A mutations may co-occur in a subset of aggressive or metastatic endometrial cancers, with ARID1A loss promoting squamous differentiation and the acquisition of invasive properties.
Fall identification in rock climbing using wearable device

The present paper discusses the use of a Kalman filter-based method to identify fall events during rock climbing activity. The proposed technique relies on the acquisition of three-axis acceleration and altitude by means of a data logger integrated within the climber’s sit harness. Time-domain results exhibit the working principle of the algorithm. Furthermore, the data provided by eight climbers is analysed and discussed to validate the method.
Enhanced Microvasculature Formation and Patterning in iPSC–Derived Kidney Organoids Cultured in Physiological Hypoxia

Functional kidney organoids have the potential to be used in implantable kidney grafts for patients with end-stage kidney disease, because they have been shown to self-organize from induced pluripotent stem cells into most important renal structures. To date, however, long-term kidney organoid culture has not succeeded, as nephrons lose their phenotype after approximately 25 days. Furthermore, the renal structures remain immature with diminishing endothelial networks with low connectivity and limited organoid invasion. We hypothesized that introducing long-term culture at physiological hypoxia, rather than the normally applied non-physiological, hyperoxic 21% O2, could initiate angiogenesis, lead to enhanced growth factor expression and improve the endothelial patterning. We therefore cultured the kidney organoids at 7% O2 instead of 21% O2 for up to 25 days and evaluated nephrogenesis, VEGF-A expression and vascularization. Whole mount imaging revealed a homogenous morphology of the endothelial network with enhanced sprouting and interconnectivity when the kidney organoids were cultured in hypoxia. Three-dimensional quantification confirmed that the hypoxic culture led to an increased average vessel length, likely due to the observed upregulation of proangiogenic VEGF-A189 mRNA and downregulation of the antiangiogenic protein VEGF-A165b measured in hypoxia. This research indicates the importance of optimization of oxygen availability in organoid systems and the potential of hypoxic culture conditions in improving the vascularization of organoids. Significance statement Culturing kidney organoids in a hypoxic environment improved patterning of the endothelial network and improved vascularization. These findings may help improve the quality of kidney organoids, and could eventually improve the kidney graft for transplantation in patients with end-stage kidney disease. Furthermore, the organoids will be more suitable for drug testing and in developmental biology. The findings might also be translatable to other organoid models containing endothelial cells. Graphical abstract
Achieving multiple-performance excellence through lean manufactoring: empirical evidences using cumulative and trade-off models

1 INTRODUCTION The intensification of global competition and the crisis have forced manufacturing companies to explore all available opportunities for reducing their costs without compromising the other operational performance. As a consequence, there has recently been renewed attention towards Lean Manufacturing. This attention doesn't come only from managers, but also from academics. This thesis has the main purpose to understand the mechanism by which manufacturing companies could achieve multiple-performance excellence through the implementation of Lean Manufacturing. To obtain this objective I adopted one cumulative model and two trade-off models to empirically demonstrate how Lean Manufacturing could improve operational performance and to highlight possible problems and traps when implementing Lean Manufacturing practices in particular contexts and configurations. What is Lean Manufacturing? Shah and Ward (2007) defined Lean Manufacturing as a " methodology that aims at eliminating waste by reducing supplier, internal and customer variability through an integrated socio-technical system that involves the simultaneous use of many practices ". Starting with this definition, the preliminary step of a empirical research on Lean Manufacturing is to operationalized it into a measurable scale. Bearing in mind that to make significant academic contributions it is important to study a phenomenon using a commonly accepted and comprehensive measurement scale (McCutcheon and Meredith, 1993), in scientific literature it is possible to note that 2 Lean Manufacturing is often confused with other methodologies (for example with Just-In-Time, a methodology that is part of Lean Manufacturing, but it doesn't cover all the facets of Lean Manufacturing methodology) and it is measured with a multitude of different scales, thus limiting academic and managerial contributions of previous academic researches (Shah and Ward, 2007). Since in scientific literature there is a lack of a well defined and comprehensive Lean Manufacturing measurement scale, the first research question that this thesis wants analyze and answer is: Going beyond this problem, Shah and Ward (2007) argued that " the relationships among the elements of Lean Manufacturing are neither explicit nor precise in terms of causality ". This statement makes clear that in scientific literature there is a lack of empirical evidences about causality relations and interconnection between Lean Manufacturing practices. This academic gap arises a managerial problem because it is impossible to understand the right implementation sequence of Lean Manufacturing practices without a strong knowledge about causal relationships between these practices. The importance of filling this gap is given by John et al. (2001) because …
Delayed Returns to Open Source Participation: An Empirical Analysis of the Apache HTTP Server Project *

The availability of commercial quality, free software products such as the Apache HTTP (web) server or the Linux operating system has focused significant attention on the open source development process by which these products were created. One of the more perplexing aspects of open source software projects is why developers freely devote their time and energy to these projects. While many open source participants cite idealistic motives for participation, Lerner and Tirole (2000) argue that developer participation in open source projects may, in part, be explained by existing economic theory regarding career concerns. This research seeks to confirm or disconfirm the existence of economic returns to participation in open source development. Preliminary results of our empirical investigation suggest that greater open source participation per se, as measured in contributions made, does not lead to wage increases. However, a higher status in a merit-based ranking within the Apache Project does lead to significantly higher wages. This suggests that employers do not reward the gain in experience through open source participation as an increase in human capital. The results are also consistent with the notion that a high rank within the Apache Software Foundation is a credible signal of the productive capacity of a programmer.
Emerging trends in photonics modeling

Continued exponential improvements in computational resources bring new opportunities and challenges for photonics modeling. In particular, widely available and inexpensive computer clusters are making a dramatic impact by allowing larger simulation volumes to be computed faster. The growth in accessible computing power is driving a trend towards the most exact modeling techniques which can address an increasing range of applications in integrated optics, and allow designers to take advantage of state-of-the-art manufacturing technology. We demonstrate how this opportunity can be exploited in the area of photonic integration to rigorously simulate three-dimensional devices by FDTD previously thought to be intractable. For example, large-volume, hybrid devices composed of both dielectrics and metals with sub-wavelength structure can now be simulated. Moreover, simulations can include realistic manufacturing imperfections. This allows designers to create and optimize robust devices that are resistant to the imperfections introduced by viable, cost-effective manufacturing.
Analysis of current‐crowding effects in RF‐MEMS spiral inductors by simple equivalent circuits

The metal loss of multiturn spiral inductors is known to increase dramatically under current‐crowding effects at high frequencies. An equivalent circuit is derived to simulate this current crowding, including skin and proximity effects. An efficient formula is derived to calculate self‐ and mutual coupling of currents in irregular hexahedrons. Possible approaches for the design of high‐Q RF‐MEMS spiral inductors are discussed. © 2002 Wiley Periodicals, Inc. Microwave Opt Technol Lett 33: 218–221, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.10280
Bidirectional Multilevel Shunt Compensator with simultaneous functionalities based on the Conservative Power Theory

Renewable energy and storage technologies had a meaningful growth in the past decades. The use of multilevel topologies within these technologies is being preferable chosen due to better features over the conventional full bridge inverters when the applications involve high power processing. Moreover, digital control algorithms make possible power electronics converters to be operated in different manners without changing their structure. This paper presents a Bidirectional Multilevel Shunt Compensator (BMSC) able to perform different and simultaneous tasks. There are eight possible modes of operation that a decision-taker may demand to the BMSC. The control algorithm is based on the Conservative Power Theory (CPT). Simulation and experimental results are presented to verify the effectiveness of the BMSC.
Automatic segmentation of deep grey nuclei using a high‐resolution 7T magnetic resonance imaging atlas—Quantification of T1 values in healthy volunteers

We present a new consensus atlas of deep grey nuclei obtained by shape‐based averaging of manual segmentation of two experienced neuroradiologists and optimized from 7T MP2RAGE images acquired at (.6 mm)3 in 60 healthy subjects. A group‐wise normalization method was used to build a high‐contrast and high‐resolution T1‐weighted brain template (.5 mm)3 using data from 30 out of the 60 controls. Delineation of 24 deep grey nuclei per hemisphere, including the claustrum and 12 thalamic nuclei, was then performed by two expert neuroradiologists and reviewed by a third neuroradiologist according to tissue contrast and external references based on the Morel atlas. Corresponding deep grey matter structures were also extracted from the Morel and CIT168 atlases. The data‐derived, Morel and CIT168 atlases were all applied at the individual level using non‐linear registration to fit the subject reference and to extract absolute mean quantitative T1 values derived from the 3D‐MP2RAGE volumes, after correction for residual B1+ biases. Three metrics (the Dice and the volumetric similarity coefficients and a novel Hausdorff distance) were used to estimate the inter‐rater agreement of manual MRI segmentation and inter‐atlas variability, and these metrics were measured to quantify biases due to image registration, and their impact on the measurements of the quantitative T1 values was highlighted. This represents a fully automated segmentation process permitting the extraction of unbiased normative T1 values in a population of young healthy controls as a reference for characterizing subtle structural alterations of deep grey nuclei relevant to a range of neurological diseases.
Research on the Improvement of Teachers’ Artistic Accomplishment Based on the Status Quo of Contemporary Aesthetic Education

Contemporary aesthetic education is one of the educational methods under the contemporary cultural system, which includes contemporary educational ideas, methods, and countermeasures of art. Teachers under contemporary aesthetic education must take on the responsibility of improving their artistic qualities in this process, express differences through perceiving life, and reshape aesthetics by regulating oneself. Teachers need to be concerned about the society, and based on the present, with independent thinking, capture the essence of life and conform to the laws of art, maintain a vigilant and critical edge, advance with the times in teaching and life, as well as embody their own educational philosophies and value judgments.
Deep Transfer Learning Across Cities for Mobile Traffic Prediction

Precise citywide mobile traffic prediction is of great significance for intelligent network planning and proactive service provisioning. Current traffic prediction approaches mainly focus on training a well-performed model for the cities with a large amount of mobile traffic data. However, for the cities with scarce data, the prediction performance will be greatly limited. To tackle this problem, in this paper we propose a novel cross-city deep transfer learning framework named CCTP for citywide mobile traffic prediction in cities with data scarcity. Specifically, we first present a novel spatial-temporal learning model and pre-train the model by abundant data of a source city to obtain prior knowledge of mobile traffic dynamics. We then devise an efficient generative adversarial network (GAN) based cross-domain adapter for distribution alignment between target data and source data. To deal with data scarcity issue in some clusters of target city, we further design an inter-cluster transfer learning strategy for performance enhancement. Extensive experiments conducted on real-world mobile traffic datasets demonstrate that our proposed CCTP framework can achieve superior performance in citywide mobile traffic prediction with data scarcity.
DECISION SUPPORT SYSTEMS IN WATER MANAGEMENT

A Decision Support System (DSS) for water management is developed herein. The system works in an interactive manner between the computer and the user. A flood routing technique using hydrodynamic model is developed and used in order to find the discharge and depth of flow with respect to time and distance along the river. The system can be extended to incorporate other models such as transport dispersion, sediment transport and water quality in order to form a complete package for river system modeling. The system was applied to a given river system in Iraq. Results were obtained for three river system configurations (alternatives). The suitable alternative can be selected according to the requirements of the decision maker or user.
General sensitivity formulas for maximum loading conditions in power systems

General sensitivity formulas for maximum loading conditions of nonlinear power systems have been proposed. The proposed formulas allow computing the sensitivities of any system variable and, in particular, of the maximum loading margin with respect to arbitrary parameters. This approach extends previous results. It has also been shown that the sensitivity formulae available in the literature for static saddle-node and limit-induced bifurcation points are particular cases of the proposed general formulae. Two benchmark systems, namely a 6-bus system and the IEEE RTS-96 24-bus tests system, are used to illustrate and test the proposed technique.
Short-Term Prediction of Traffic Volume in Urban Arterials

This paper attempts to develop time-series models for forecasting traffic volume in urban arterials. The Box-Jenkins approach is used to estimate the time-series models. A 1-min data set representing traffic volume on five major urban arterials were available to estimate time-series models. The Box-Jenkins autoregressive integrated moving average (ARIMA) model of order (0, 1, 1) turned out to be the most adequate model in reproducing all original time series. The developed model is easy to understand and implement. Further, the model is computationally tractable, and only requires the storage of the last forecasted error and current traffic observation.