Miracle-dz/UniFAR-FTUs huggingface dataset:
HEPATIC XENOBIOTIC RECEPTORS IN THE UBIQUITIN-PROTEASOME SYSTEM

Constitutive androstane receptor (CAR) and aryl hydrocarbon receptor (AhR) are liver-enriched xenobiotic receptors that are essential in the regulation of drug-metabolizing enzymes (DMEs) and drug transporters. Emerging evidence has also implicated CAR and AhR in the energy metabolism, cell proliferation and immune response, in addition to their classical function of xenobiotic detoxification. The cellular effects mediated by these xenobiotic receptors can be achieved canonically by the transcriptional modulation via direct interaction with the genomic DNA. There are also indirect mechanisms via protein-protein interactions by which CAR and AhR can alter the transcriptome. The preliminary results together with previous studies by others have suggested an interplay between the xenobiotic receptors and ubiquitin-proteasome system (UPS). In this dissertation study, I studied the E3 ubiquitin ligase activity of CAR and AhR in the context of hepatic gluconeogenesis and hepatic stellate cell (HSC) activation, respectively. My results demonstrated that (1) CAR suppresses hepatic gluconeogenic gene expression through post-translational regulation of the subcellular localization and degradation of PPAR-γ coactivator 1α (PGC1α). Activated CAR translocates into the nucleus and serves as a substrate adaptor protein recruiting PGC1α to the Cullin1 E3 ligase complex for ubiquitylation. The interaction between CAR and PGC1α also leads to their sequestration within the promyelocytic leukemia protein-nuclear bodies (PML-NBs), where PGC1α and CAR subsequently undergo proteasomal degradation, which is required for CAR-mediated inhibition of PGC1α. (2) AhR negatively regulates HSC activation by disrupting the interaction of Smad3 with β-catenin and impairing β-catenin-dependent stabilization of phosphorylated Smad2/3, which is independent of its E3 ubiquitin ligase activity. AhR is highly expressed in HSCs and activation of AhR prevents fibrogenesis and proliferation of HSCs. The expression of AhR in HSCs declines with the onset of HSC activation. Primary HSCs isolated from the AhR-/- mice exhibits accelerated spontaneous activation. Treatment with an AhR antagonist promotes, whereas the AhR agonists inhibit the activation of mouse and human HSCs, respectively. In vivo ablation of AhR in HSCs sensitizes mice to liver fibrosis. Overall, this dissertation elucidates a novel concept of xenobiotic receptors as the essential components in the UPS.
Estimating coefficient of linear extensibility using Vis–NIR reflectance spectral data: Comparison of model validation approaches

The coefficient of linear extensibility (COLE) is used to classify soils according to their swell–shrink potential, and its estimation is crucial for engineering and agronomic applications. The aims of the study were (a) to develop a visible–near‐infrared spectroscopy (Vis–NIRS, 400–2,500 nm) calibration model to estimate COLE, (b) to compare two model validation approaches (mixed data and country‐wise), and (c) to test if a variable selection method improves the estimation accuracy of the calibration models. For this purpose, partial least square regression (PLSR) was used on the spectra of 53 soil samples from Slovakia and 24 samples from the United States. First, a calibration model based on 70% of the entire dataset (including samples from both locations) was developed and validated with the remaining 30% (mixed data approach). Second, a calibration model based on the Slovakian samples was validated with the U.S. samples (country‐wise approach). Higher predictability for COLE with standardized root mean square error (SMRSE) of 0.099 was obtained for the mixed data approach than for the country‐wise validation with SRMSE of 0.279. Furthermore, using interval PLSR (iPLSR) as a variable selection method did not improve the estimation accuracy of the mixed data approach (SRMSE of 0.099), and rather resulted in a twofold increase in SRMSE (0.560) for the country‐wise validation approach. Overall, the good estimation of COLE from Vis–NIRS was attributed to the high correlation of COLE with clay content and spectrally active clay minerals.
An Optimized Training Method for GAN-Based Hyperspectral Image Classification

This letter explores how to apply a generative adversarial network (GAN) to the classification of hyperspectral images (HSIs) to obtain a smooth training process and better classification results. To this end, the ideas of the progressive growing GAN (PG-GAN) and Wasserstein generative adversarial network gradient penalty (WGAN-GP) are combined to propose a new method for HSI classification. PG-GAN is optimized from the training process of generating adversarial networks. It gradually increases the depth of the network and the size of the input image, making the training smoother. WGAN-GP is optimized in terms of the loss function. The gradient penalty method is used to solve the problems of vanishing gradient and exploding gradient, making the training more stable. Based on the combination of the two methods, a classifier is added to the model so that it can complete the HSI classification task. The proposed method is evaluated over two publicly available hyperspectral data sets, the Indian Pines and University of Pavia data sets. The results show that the proposed method can achieve good training results with only a small amount of labeled training data.
Privacy-Preserving Federated Deep Learning With Irregular Users

Federated deep learning has been widely used in various fields. To protect data privacy, many privacy-preservingapproaches have been designed and implemented in various scenarios. However, existing works rarely consider a fundamental issue that the data shared by certain users (called irregular users) may be of low quality. Obviously, in a federated training process, data shared by many irregular users may impair the training accuracy, or worse, lead to the uselessness of the final model. In this article, we propose PPFDL, a Privacy-Preserving Federated Deep Learning framework with irregular users. In specific, we design a novel solution to reduce the negative impact of irregular users on the training accuracy, which guarantees that the training results are mainly calculated from the contribution of high-quality data. Meanwhile, we exploit Yao's garbled circuits and additively homomorphic cryptosystems to ensure the confidentiality of all user-related information. Moreover, PPFDL is also robust to users dropping out during the whole implementation. This means that each user can be offline at any subprocess of training, as long as the remaining online users can still complete the training task. Extensive experiments demonstrate the superior performance of PPFDL in terms of training accuracy, computation, and communication overheads.
SIMILARITY COMPUTATION SUPPORTING CREATIVE ACTIVITIES

Creativity sessions in industry, when they are based solely on people's knowledge, produce less and less value. This is mainly due to the need to further expand the spectrum of knowledge needed to solve problems. We are therefore increasingly witnessing the limits of our knowledge capabilities to meet the demands of today's inventive problem-solving in industry. The research presented in this paper proposes a method of semantic association between problems extracted from an unstructured textual corpus of a patent using Google's Word2vec algorithm followed by cosine similarity to create original pairings between problems from different but semantically close domains. We postulate that such a method is a preamble to the automation of TRIZ and thus avoids the difficulties of not having been updated for a few decades.
A Study on the Effects of Advertising Attributes in YouTube e-sport Video

The purpose of this study is to analyze the structural relationship among advertising attribute, advertising attitude, product attitude and purchase intention in YouTube advertising. The survey subjects to achieve the purpose of this study were selected the group of 300 students who have been watching YouTube VOD once more and are attending in three universities that are located in Seoul, Gyeonggi and Chungnam. Data processing was done with SPSS 23 for frequency analysis, Cronbach's α analysis. Also, AMOS 18 was used for confirmatory factor analysis and structural equation model analysis. information, irrtation and individuality affect viewers' advertisement attitude, their product attitude and purchasing intent, among advertisement attributes of e-sports items perceived by viewers of YouTube's e-sports videos with the insertion of advertisements that cannot be skipped in the middle of the video.Therefore, the similarity between the video and the advertised product or brand should be taken into account when producing advertisements inserted in the YouTube video, and a more positive advertising effect can be achieved when advertisement can be carried out reflecting the characteristics of the target viewers.
Combinatorial width parameters for 3-dimensional manifolds

Algorithms in computational 3-manifold topology typically take a triangulation as an input and return topological information about the underlying 3-manifold. However, extracting the desired information from a triangulation (e.g., evaluating an invariant) is often computationally very expensive. In recent years this complexity barrier has been successfully tackled in some cases by importing ideas from the theory of parameterized algorithms into the realm of 3-manifolds. Various computationally hard problems were shown to be efficiently solvable for input triangulations that are sufficiently “tree-like. ” In this thesis we focus on the key combinatorial parameter in the above context: we consider the treewidth of a compact, orientable 3-manifold, i.e., the smallest treewidth of the dual graph of any triangulation thereof. By building on the work of Scharlemann–Thompson and Scharlemann–Schultens–Saito on generalized Heegaard splittings, and on the work of Jaco–Rubinstein on layered triangulations, we establish quantitative relations between the treewidth and classical topological invariants of a 3-manifold. In particular, among other results, we show that the treewidth of a closed, orientable, irreducible, non-Haken 3-manifold is always within a constant factor of its Heegaard genus.
Joint Optimization for Secure Intelligent Reflecting Surface Assisted UAV Networks

This letter proposes a novel secure intelligent reflecting surface (IRS)-assisted unmanned aerial vehicle (UAV) system, where the UAV sends confidential messages to a legitimate receiver, in the presence of a passive eavesdropper. We aim to maximize the secrecy rate by jointly designing the trajectory, the power control of UAV and the phase shifters of the IRS from the physical layer security perspective. Because the formulated problem is non-convex and intractable, we propose an iterative algorithm based on successive convex approximation (SCA) to solve this problem. Simulation results validate the effectiveness of the proposed algorithm and show that the secrecy rate is significantly improved with the assistance of the IRS.
Optical and Electrical Characteristics of an Endoscopic DBD Plasma Jet

In this work, a new cold plasma source design capable of generating and transporting a plasma jet over long distances (2 m) is presented with the purpose of being used in flexible endoscopy for treatment within the gastrointestinal tract. This dielectric barrier discharge helium plasma jet consists of a polytetrafluoroethylene capillary connected to a quartz chamber around which a copper electrode is wrapped. A copper wire is freely inserted inside the capillary. The applied voltage is a conventional AC 18-kHz signal to drive the discharge. In order to develop a safe and predictable treatment, a robust and reliable electrical model is necessary and we hypothesized that plasma transport can be modeled as a transmission line. We therefore assessed the electrical behavior of our new cold plasma source. As it is known that the target to which the plasma jet is applied drastically changes the behavior of the plasma itself, an electrical substitute simulating the impedance of a human body is introduced into the circuit, and the plasma behavior is then compared to the free-jet configuration. The effects of the input power (from 10 W to 80 W), and the length of the jet (from 60 cm to 220 cm) were investigated, as well as the electrical changes induced by the presence of an endoscope. The results obtained show trend curves similar to our hypothetical model, although the latter is still only qualitative. This long plasma jet model represents a promising approach that can be used, after further refinement, for controllability of plasma jets for endoscopy applications.
Biological and dosimetric evaluation of [11C]S-adenosyl Methionine as a potential agent for prostate cancer diagnosis

Introduction: [C]Choline ([C]COL) has been widely used for prostate cancer diagnosis; however, this radiopharmaceutical is not recommended for patients with a low absolute PSA value (< 1 ng/mL) due to its limited sensitivity and specificity. The enzyme glycine N-methyltransferase is overexpressed during prostate cancer progression. It catalyses the methylation of glycine using S-adenosyl methionine (SAM or AdoMet) as a substrate. The authors have previously reported the automated radiosynthesis of [C]SAM as a potential agent in the diagnosis of aggressive prostate cancer. In this study, a biological and dosimetric evaluation of [C]SAM was performed. Results: The evaluation of [C]SAM in a control group of healthy mouse model showed a relatively high tracer uptake in the kidneys and a rapid blood clearance. Most activity was eliminated in the urine. In a PC3 prostate cancer xenograft tumour model, [C]SAM tumour uptake was significantly higher in relation to [C]COL.The human dosimetry of [C]SAM was estimated by extrapolating the preclinical results. The mean effective dose was 8.17 x 10 mSv/MBq and 2.49 x 10 mSv/MBq without and with bladder voiding, respectively. The results for kidneys in humans were comparable to those previously described for [C]COL. Conclusions: The PET/CT studies showed a statistically higher in vivo tumour uptake of [C]SAM compared to [C]COL for the cancer xenograft model. The absorbed dose estimations of major organs and the effective dose were determined. The results suggested that [C]SAM may be a potential PET tracer for prostate cancer diagnosis.
The Impact of Community College Baccalaureate Adoption on Associate Degree Production

Background/Context As of 2018, a total of 19 states allow at least one community college to offer baccalaureate degrees. Previous researchers have suggested that community college baccalaureate (CCB) adoption will lead to a host of unintended consequences, including decreases in associate degree production. Purpose/Objective/Research Question/Focus of Study This study empirically examines the impact of CCB adoption on associate degree production and adds to conversations surrounding the consequences of CCB adoption. Research Design We use a quantitative quasi-experimental research design to examine the effect of CCB adoption on associate degree production. Findings/Results When comparing adopting and non-adopting community colleges within the state of Florida, the authors find that the adoption of CCB degree programs has a positive impact on overall associate degree production, but this impact varies considerably according to the type of academic degree program. Conclusions/Recommendations Opponents of CCB legislation have argued that giving community colleges the authority to confer baccalaureate degrees will detract from the sub-baccalaureate institutional mission of community colleges, but our results suggest that the adoption of a CCB degree program is associated with an overall increase in associate degree production. Findings from this work should be an important consideration for policymakers seeking to increase baccalaureate degree production in addition to—not at the expense of—associate degree programs.
Dual-Resonant Stacked Linear Array of Cross-Slotted Patches for Small SAR Satellites

A cross-slotted linear array antenna of four stacked patches is proposed for <inline-formula> <tex-math notation="LaTeX">$X$ </tex-math></inline-formula>-band synthetic aperture radar (SAR) on a small satellite platform. Owing to the reliability, small size and mass restriction features of small satellites, the antenna is based on a thin dual-substrate topology with each element surrounded by metal vias to form a cavity-backed patch to result in a lightweight and high efficiency. Although inherently narrowband due to the thin substrate layer, cross-slotted patches were proposed to yield a dual resonance, and lower input impedance at the desired band to meet the SAR requirement. The fabricated prototype exhibits a peak gain of 12 dBi with a radiation efficiency of 84% at 9.44–9.87 GHz for <inline-formula> <tex-math notation="LaTeX">$\vert S_{11}\vert < -10$ </tex-math></inline-formula> dB.
PRSRTI: A Novel Device-Free Localization Method Using Phase Response Shift Based Radio Tomography Imaging

Device-free localization (DFL) is a hot topic in passive sensing such as intrusion detection, pose estimation, and contact-tracing. To improve the performance, we propose a novel fine-grained DFL method using the phase response shift (PRS) to localize targets, which can mitigate the effect of multipath, and noise without phase ambiguity. The phases of received multi-frequency signals are linearly fitted as the phase response (PR). The shift of target-induced PR with respect to non-target PR is considered as the PRS. The PRSs at every location of the monitored area are observed with different length communication links, and are summarized as a PRS weight model. The PRS-based radio tomography imaging (PRSRTI) localization model is derived, and utilizes the PRS, and the weight model to localize targets. Experimental results validate that its performance is obviously higher than the received signal strength based radio tomography imaging (RTI).
Digital Transformation from an Inter-Organizational Perspective: Managing the Co-evolution of Platform Owners and Complementors in Platform Ecosystems (Digitale Transformation aus unternehmensübergreifender Perspektive: Management der Koevolution von Plattformbesitzern und Komplementoren in Plattfor

Digital platforms have the potential to transform how organizations are doing business in their respective ecosystems. Motivated by this transformation, the purpose of this thesis is to increase the understanding of digital transformation from an inter-organizational perspective. Therefore, this thesis clarifies the phenomenon of digital transformation, and models and analyzes multiple digital platform ecosystems. Building upon that, this dissertation reflects on multiple case studies on how platform owners can manage the co-evolution of their complementors in digital transformations in digital platform ecosystems.
Ammonium Sensor Fault Detection in Wastewater Treatment Plants

We develop a fault detection strategy for the output ammonium sensor present in wastewater treatment plants. The only assumed measurements are the output ammonium concentration, the aeration of the reactor and the incoming volumetric flow to the plant. The incoming ammonium concentration is not measured, resulting in an important source of uncertainty. We use a IIR model based on Volterra series for predicting the ammonium measurement and we design a fault detector based on a filter applied on the prediction error and a threshold comparator to decide whether the sensor is faulty or not. The faults in the sensor are assumed to produce a slowly decreasing gain due to dirtiness in its surface. The fault detector design is based on the trade-off between fault detection sensitivity and disturbance rejection (due to measurement noise and model uncertainty). The design parameters are based in understandable fault indices: time needed to detect the fault, gain deviation at the time of detection, and poured volume of ammonium until the fault is detected. We use the benchmark BSM1 to validate the results as a common frame in the study of waste water treatment plants.
Response of a DIN 18MnCrSiMo6-4 Continuous Cooling Bainitic Steel to Plasma Nitriding with a Nitrogen Rich Gas Composition

The use of continuous cooling bainitic steels can provide a more energy efficient manufacturing route. However, for their use in mechanical components like gears, it is necessary to improve their surface properties without impacting the core properties to guarantee reliable mechanical performance. The effect of temperature and time on the plasma nitriding response of a DIN 18MnCrSiMo6-4 steel was investigated. The plasma nitriding was performed for 3, 6 and 9 hours, at 400, 450, 500 and 550 °C, using a gas mixture composed of 76 vol.% nitrogen and 24 vol.% hydrogen. Samples were characterized before and after plasma nitriding concerning the microstructure, hardness and microhardness, fracture toughness, phase composition and residual stress states. Based on the results presented, layer growth constants (k) for different temperatures was determined. Moreover, it could be found that 500 °C gave the best results investigated here, as higher temperature took to core and surface hardness decrease. The nitrided samples with thicker compound layers presented a fracture behavior dominated by the formation of Palmqvist cracks. X-ray phase analysis indicated the formation of biphasic compound layer on the surface of all nitrided samples. The diffusion zone presented compressive residual stresses with highest values near the surface.
Feasibility Analysis of VR Technology in Physical Education and Sports Training

VR technology can simulate the complex environment; break through the limitations of traditional physical education curriculum on sports venues, equipment, safety and other aspects. It can provide scientific and accurate guidance for learners and obtain more technical knowledge by visualizing the complex and abstract sports theoretical knowledge. Compared with the traditional sports teaching activities, virtual reality technology can not only simulate the sports scene by generating VR panorama. On this basis, it can effectively improve learners' enthusiasm and motor skills. At present, due to the immaturity of VR technology and the high price of related equipment, people are cautious about the use of VR technology, so VR technology has not been popularized in education. In view of this situation, this paper studies whether VR technology can be effectively applied to physical education teaching and sports training. This paper is divided into four parts: the first part is the research of VR panorama; the second part is the research of VR video; the third part is the application of VR technology in physical education; the fourth part is the investigation. It is found that VR, as a new technology, has great application potential. As long as it is scientifically and reasonably used, VR can greatly promote the improvement of sports scene and the level of sports.