Miracle-dz/UniFAR-FTUs huggingface dataset:
A survey on supply chain ontologies

Nowadays, the business area cannot be sustainable and efficient without the presence of the Supply Chain. However, Supply Chain Management is by no means an easy task. Experts, in their effort to achieve the most efficient Supply Chain Management, have turned their attention to the management of knowledge related to supply chains. Thus, they model the concepts and the semantic relationships between them in Supply Chain Networks and create conceptual models and ontologies. In this paper, a survey of the existing ontologies in this field is carried out, with the aim of creating a new ontology of the Supply Chain that will unify its structural elements and lead to the integration of all supply systems. For this purpose, 22 ontological models from different supply systems, from over 90 sources, have been collected, briefly presented and commented on. These models, although being an intersection in the effort to model business operations and delineate a good basis for businesses to engage in Logistics processes, they lack an adequate formulation of appropriate semantics and terminology to describe all the different functions of the Supply Chain. Consequently, this lack inevitably leads to incompatible interpretations and uses of the knowledge that results from intercompany transactions.
Pyramidal Image Representation In Nonuniform Systems

In this paper we present a formalism for representation and processing of images which are not band-limited. Motivated by the properties of the visual system, we elaborated an example of a sampling scheme wherein the sampling rate decreases as a function of the distance from the center of the visual field. The broader class of images under consideration, obtained by the application of an appropriate projection filter, constitutes a Reproducing Kernel space which is characterized by "locally band-limited" properties. Sequential half-band filtering of such images generates a pyramidal scheme in the context of nonuniform systems and images.
A NEW COMPACTNESS RESULT FOR ELECTROMAGNETIC WAVES. APPLICATION TO THE TRANSMISSION PROBLEM BETWEEN DIELECTRICS AND METAMATERIALS

We consider the time-harmonic Maxwell equations, involving wave transmission between media with opposite sign dielectric and/or magnetic coefficients. We prove that, in the case of sign-shifting dielectric coefficients, the space of electric fields is compactly embedded in L2. We build a three-field variational formulation equivalent to Maxwell system for sign-shifting magnetic coefficients and show that, under some suitable conditions, the formulation fits into the coercive plus compact framework.
Self-Healing Control for Wastewater Treatment Process Based on Variable-Gain State Observer

This article proposes a variable-gain state observer-based sliding mode self-healing control (VSO-based SMSHC) method for a wastewater treatment process (WWTP) with changeable external disturbances and sensor failures. To reconstruct the disturbances and unmeasured system states, a novel VSO is developed, in which the VSO gains are adjusted by following an automatic variable-gain mechanism for adapting to the variation of external disturbances. An adaptive compensation coefficient of failure factor is designed to counteract the failure effects on observation and tracking performance. By utilizing the cubic absolute-value Lyapunov stability criterion, it is shown that system stability and tracking performance of WWTP are guaranteed. Experimental studies are carried out on a standardized platform of WWTP, and the results on dissolved oxygen and nitrate nitrogen regulation indicate that the proposed control strategy can ensure excellent control performance and reduce both failure and disturbance impacts.
Accumulation of pTau231 at the Postsynaptic Density in Early Alzheimer’s Disease

Background: Phosphorylated cytoplasmic tau inclusions correlate with and precede cognitive deficits in Alzheimer’s disease (AD). However, pathological tau accumulation and relationships to synaptic changes remain unclear. Objective: To address this, we examined postmortem brain from 50 individuals with the full spectrum of AD (clinically and neuropathologically). Total tau, pTau231, and AMPA GluR1 were compared across two brain regions (entorhinal and middle frontal cortices), as well as clinically stratified groups (control, amnestic mild cognitive impairment, AD dementia), NIA-AA Alzheimer’s Disease Neuropathologic Change designations (Not, Low, Intermediate, High), and Braak tangle stages (1–6). Significant co-existing pathology was excluded to isolate changes attributed to pathologic AD. Methods: Synaptosomal fractionation and staining were performed to measure changes in total Tau, pTau231, and AMPA GluR1. Total Tau and pTau231 were quantified in synaptosomal fractions using Quanterix Simoa HD-X. Results: Increasing pTau231 in frontal postsynaptic fractions correlated positively with increasing clinical and neuropathological AD severity. Frontal cortex is representative of early AD, as it does not become involved by tau tangles until late in AD. Entorhinal total tau was significantly higher in the amnestic mild cognitive impairment group when compared to AD, but only after accounting for AD associated synaptic changes. Alterations in AMPA GluR1 observed in the entorhinal cortex, but not middle frontal cortex, suggest that pTau231 mislocalization and aggregation in postsynaptic structures may impair glutamatergic signaling by promoting AMPA receptor dephosphorylation and internalization. Conclusion: Results highlight the potential effectiveness of early pharmacological interventions targeting pTau231 accumulation at the postsynaptic density.
GPS-Free Collaborative Elliptical Circumnavigation Control for Multiple Non-Holonomic Vehicles

This paper investigates a novel GPS-free collaborative elliptical circumnavigation control for multiple non-holonomic vehicles, where two realistic issues—achieving a higher efficiency observation and saving the energy expenditures during cooperation are involved. By defining a novel coordinated error relative to neighboring arc length, under the premise of accessible global position, a cooperative elliptical enclosing control strategy is derived for multiple vehicles connected by a digraph to enable formation behaviors with a uniform forward speed. To surmount the reliance on global position data in hostile surroundings where GPS is being attacked or disrupted, by resorting to a distance-based relative position observer, a new GPS-free cooperative elliptical circling controller is formulated to force all vehicles to collaboratively evolve along the prescribed ellipse. The special innovation includes two aspects, one is that by specifying the adjacent arc length instead of separation angles appearing in existing vehicle coordination, energy consumption can be reduced by approximately 7.6% during cooperative periodic enclosing process, another is that the dependency on global position can be removed by resorting to a relative position estimator utilizing distance-only data. It is inferred from Lyapunov stability that all signals are demonstrated to be convergent. Eventually, both simulation and experimental results substantiate the utility of suggested avenue.
Optical characterization of 4H-SiC by far ultraviolet spectroscopic ellipsometry

We have developed a far UV spectroscopic ellipsometer system working up to 9 eV, and applied it to the characterization of three 4H-SiC samples with different surface conditions [i.e., as-received and chemical mechanical processing (CMP) processed 4H-SiC bulk substrates and a 4H-SiC epi sample]. Pseudodielectric functions e1 and e2 clearly demonstrate the excellent surface sensitivity of the far UV ellipsometry system as it distinguishes the improvements provided by CMP process. Simulation results of ellipsometer data indicate the existence of a damaged subsurface layer in the as-received 4H-SiC bulk substrate. The investigation of sample surfaces using atomic force microscopy confirms the results of ellipsometry measurements.
Desynchronization by Means of a Coordinated Reset of Neural Sub-Populations A Novel Technique for Demand-Controlled Deep Brain Stimulation

The coordinated reset of neural sub-populations is introduced as an effectively desynchronizing stimulation technique. For this, short sequences of high-frequency pulse trains are administered at different sites in a coordinated way, i.e. separated by suitable fixed delays. Desynchronization is effectively maintained by performing a coordinated reset with demand-controlled timing or by periodically administering resetting high-frequency pulse trains of demand-controlled length. Unlike previously developed methods, this novel approach is robust against variations of model parameters, and does not require time-consuming calibration. I suggest the novel technique to be used for demand-controlled deep brain stimulation in patients suffering from Parkinson's disease or essential tremor. Furthermore, the novel stimulation method might even be applicable to diseases with intermittently emerging synchronized neural oscillations like epilepsy.
What drives cryptocurrency returns? A sparse statistical jump model approach

We apply the statistical sparse jump model, a recently developed, interpretable and robust regime-switching model, to infer key features that drive the return dynamics of the largest cryptocurrencies. The algorithm jointly performs feature selection, parameter estimation, and state classification. Our large set of candidate features are based on cryptocurrency, sentiment and financial market-based time series that have been identified in the emerging literature to affect cryptocurrency returns, while others are new. In our empirical work, we demonstrate that a three-state model best describes the dynamics of cryptocurrency returns. The states have natural market-based interpretations as they correspond to bull, neutral, and bear market regimes, respectively. Using the data-driven feature selection methodology, we are able to determine which features are important and which ones are not. In particular, out of the set of candidate features, we show that first moments of returns, features representing trends and reversal signals, market activity and public attention are key drivers of crypto market dynamics.
Partial least squares regression on DCT domain for infrared face recognition

Compact and discriminative feature extraction is a challenging task for infrared face recognition. In this paper, we propose an infrared face recognition method using Partial Least Square (PLS) regression on Discrete Cosine Transform (DCT) coefficients. With the strong ability for data de-correlation and compact energy, DCT is studied to get the compact features in infrared face. To dig out discriminative information in DCT coefficients, class-specific One-to-Rest Partial Least Squares (PLS) classifier is learned for accurate classification. The infrared data were collected by an infrared camera Thermo Vision A40 supplied by FLIR Systems Inc. The experimental results show that the recognition rate of the proposed algorithm can reach 95.8%, outperforms that of the state of art infrared face recognition methods based on Linear Discriminant Analysis (LDA) and DCT.
Identifying Redundant Constraints and Implicit Equalities in Systems of Linear Constraints

Redundant constraints are constraints that can be omitted from a system of linear constraints without changing the feasible region. Implicit equalities are inequality constraints that can be replaced by equalities without changing the feasible region. We prove some theorems concerning the identification of both kinds of constraints. Based on these theorems two methods are developed that allow identification of all redundant constraints and all implicit equalities. Computational experience on small problems indicates a behavior at least competitive with other methods in this field.
‘I Finally Get It!’: developing mathematical understanding during teacher education

A deep conceptual understanding of elementary mathematics as appropriate for teaching is increasingly thought to be an important aspect of elementary teacher capacity. This study explores preservice teachers’ initial mathematical understandings and how these understandings developed during a mathematics methods course for upper elementary teachers. The methods course was supplemented by a newly designed optional course in mathematics for teaching. Teacher candidates choosing the optional course were initially weaker in terms of mathematical understanding than their peers, yet showed stronger mathematical development after engaging in the extra hours the optional course provided.
Cross-Correlation Inspired Residual Network for Pulsed Eddy Current Imaging and Detecting of Subsurface Defects

The decay of pulsed eddy currents (PEC) with depth in diffusion decreases resultant signal changes, thus bringing a challenge for reliable and accurate evaluation of deep subsurface defects. In this article, a novel cross-correlation inspired residual network (ResNet), termed CCResNet, is proposed to improve the capability for smart evaluation of subsurface defects. It consists of a cross-correlation layer, a ResNet, and a novel loss function, namely, focal-probability of detection (Focal-POD) loss. The customized Gaussian wavelet basis enables us to derive weak features from heavily noised PEC signals due to the similarity by cross-correlation operation, which is the origin of the constructed cross-correlation layer. Then, a Focal-POD loss is proposed to address class imbalance and endow CCResNet with powerful capability for detection of deep subsurface defects by increasing their loss values. Finally, a semisupervised framework is built to retrain CCResNet using pseudo and labeled dataset to obtain classified results as imaging features. The experimental results show that the developed CCResNet is featured as better imaging resolution, more accurate evaluation, and intelligence in detection of deeper subsurface defects.
The Impact of Lung Cancer in Patients with Combined Pulmonary Fibrosis and Emphysema (CPFE)

Given the high risk of lung cancer (LC) in patients with combined pulmonary fibrosis and emphysema (CPFE), and the difficulty of early diagnosis, it is important to understand the impact of LC in these patients. The effect of LC on the development of acute exacerbation (AE) as a natural course of CPFE is still unknown. We retrospectively reviewed medical records of patients at the West China Hospital and enrolled 59 patients with CPFE combined with LC and 68 CPFE patients without LC for initial diagnosis matched in the same period. We compared the clinical characteristics and imaging features of CPFE patients with LC and without LC, and analyzed the associated factors for the prevalence of LC using binary logistic regression. Cox proportional hazards regression analysis was performed to explore risk factors of AE as a natural course of CPFE. Patients with CPFE combined with LC were more common among elderly male smokers. The most common pathological type of tumor was adenocarcinoma (24/59, 40.7%) and squamous cell carcinoma (18/59, 30.5%). Compared with those in the without LC group, the proportions of men, and ex- or current smokers, and the levels of smoking pack-years, serum CRP, IL-6, fibrinogen, complement C3 and C4 in patients with LC were significantly higher (p < 0.05). There was no significant difference in the proportion of natural-course-related AE (10.2% vs. 16.2%, p > 0.05) between the two groups. Logistic regression analysis demonstrated that pack-years ≥ 20 (OR: 3.672, 95% CI: 1.165–11.579), family history of cancer (OR: 8.353, 95% CI: 2.368–10.417), the level of fibrinogen > 4.81 g/L (OR: 3.628, 95% CI: 1.403–9.385) and serum C3 > 1.00 g/L (OR: 5.299, 95% CI: 1.727–16.263) were independently associated with LC in patients with CPFE. Compared to those without AE, CPFE patients with AE had significantly higher levels of PLR and serum CRP, with obviously lower DLCO and VC. The obviously increased PLR (HR: 3.731, 95% CI: 1.288–10.813), and decreased DLCO%pred (HR: 0.919, 95% CI: 0.863–0.979) and VC%pred (HR: 0.577, 95% CI: 0.137–0.918) rather than the presence of LC independently contributed to the development of natural-course-related AE in patients with CPFE. Pack-years, family history of cancer, the levels of fibrinogen and serum C3 were independently associated with LC in patients with CPFE. The presence of LC did not significantly increase the risk of AE as a natural course of CPFE. Clinicians should give high priority to CPFE patients, especially those with more severe fibrosis and systemic inflammation, in order to be alert for the occurrence of AE.
MAXIMUM LIKELIHOOD ESTIMATION BY MEANS OP NONLINEAR LEAST SQUARES

Methods are given for using readily available nonlinear regression programs to produce maximum likelihood estimates in a rather natural way. Used as suggested the common Gauss-Newton algorithm for nonlinear least squares becomes the Fisher scoring algorithm for maximum likelihood estimation. In some cases it is also the Newton-Raphson algorithm. The standard errors produced are the information theory standard errors up to a possible common multiple. This means that much of the auxiliary output produced by a nonlinear least squares analysis is directly applicable to a maximum likelihood analysis. Illustrative applications to Poisson, quantal response, multinomial, and log-linear models are given.
Quantifying colour appearance. part IV. Transmissive media

The experimental data from this study extends the LUTCHI colour-appearance data to cover transmissive media. Two further experiments were carried out: one used a large cut-sheet transparency viewed using a back-lit illuminator, and another used a 35-mm slide projected onto a white screen. These new data were used to reveal the changes in colour appearance caused by different viewing parameters studied, and to evaluate the predictive accuracy of five uniform colour spaces and colour-appearance models. The results show that Hunt's 91 model (developed to fit earlier experimental results) did not perform as well as it did in the previous studies using nontransmissive media. This implies that there are large differences in perceived colour appearance between transmissive and nontransmissive media viewing conditions. Some modifications were subsequently made to Hunt's 91 model and the predictive accuracy was greatly improved.
Slow Slip Detectability in Seafloor Pressure Records Offshore Alaska

In subduction zones worldwide, seafloor pressure data are used to observe tectonic deformation, particularly from megathrust earthquakes and slow slip events (SSEs). However, such measurements are also sensitive to oceanographic circulation‐generated pressures over a range of frequencies that conflate with tectonic signals of interest. Using seafloor pressure and temperature data from the Alaska Amphibious Community Seismic Experiment, and sea surface height data from satellite altimetry, we evaluate the efficacy of various seasonal and oceanographic pressure signal proxy corrections and conduct synthetic tests to determine their impact on the timing and amplitude prediction of ramp‐like signals typical of SSEs. We find that subtracting out the first mode of the complex empirical orthogonal functions of the pressure records on either the shelf or slope yields signal root‐mean‐square error (RMS) reductions up to 73% or 80%, respectively. Additional correction with proxies that exploit the depth‐dependent spatial coherence of pressure records provides cumulative variance reductions up to 83% and 93%, respectively. Our detectability tests show that the timing and amplitude of synthetic SSE‐like ramps can be well constrained for ramp amplitudes ≥4 cm on the shelf and ≥2 cm on the slope, using a fully automated detector. The principal limits on detectability are residual abrupt changes in pressure that occur as part of the transition to and from summer to winter conditions but are not adequately characterized by our seasonal corrections, as well as the inability to properly account for instrumental drift, which is not readily separated from the seasonal signal.
QiHuangYiShen Granules Modulate the Expression of LncRNA MALAT1 and Attenuate Epithelial-Mesenchymal Transition in Kidney of Diabetic Nephropathy Rats

Background QiHuangYiShen granules (QHYS), a traditional Chinese herbal medicine formula, have been used in clinical practice for treating diabetic kidney disease for several years by our team. The efficacy of reducing proteinuria and delaying the decline of renal function of QHYS has been proved by our previous studies. However, the exact mechanism by which QHYS exerts its renoprotection remains largely unknown. Emerging evidence suggests that lncRNA MALAT1 is abnormally expressed in diabetic nephropathy (DN) and can attenuate renal fibrosis by modulating podocyte epithelial-mesenchymal transition (EMT). Objective In the present study, we aimed to explore whether QHYS could modulate lncRNA MALAT1 expression and attenuate the podocyte EMT as well as the potential mechanism related to the Wnt/β-catenin signal pathway. Methods SD rats were fed with the high-fat-high-sucrose diet for 8 weeks and thereafter administered with 30 mg/kg streptozotocin intraperitoneally to replicate the DN model. Quality control of QHYS was performed using high-performance liquid chromatography. QHYS were orally administered at 1.25, 2.5, and 5 g/kg doses, respectively, to the DN model rats for 12 weeks. Body weight, glycated haemoglobin, blood urea nitrogen, serum creatinine, 24-h proteinuria, and kidney index were measured. The morphologic pathology of the kidney was evaluated by Hematoxylin-eosin and Masson's trichrome staining. The expression level of lncRNA MALAT1 was determined by quantitative real-time polymerase chain reaction. In addition, the expression levels of podocyte EMT protein markers and Wnt/β-catenin pathway proteins in renal tissues were evaluated by Western blotting and immunohistochemistry. Results The results showed that QHYS significantly reduced 24-h proteinuria, blood urea nitrogen, kidney index, and ameliorated glomerular hypertrophy and collagen fiber deposition in the kidney of DN rats. Importantly, QHYS significantly downregulated the expression level of lncRNA MALAT1, upregulated the expression of nephrin, the podocyte marker protein, downregulated the expression of desmin and FSP-1, and mesenchymal cell markers. Furthermore, QHYS significantly downregulated the expression levels of Wnt1, β-catenin, and active β-catenin. Conclusion Conclusively, our study revealed that QHYS significantly reduced proteinuria, alleviated renal fibrosis, and attenuated the podocyte EMT in DN rats, which may be associated with the downregulation of lncRNA MALAT1 expression and inhibition of the Wnt/β-catenin pathway.
Dual-Band Dual-Polarized Planar Antenna for 5G Millimeter-Wave Antenna-in-Package Applications

This article presents a dual-band, dual-polarized antenna operating from 24 up to 40 GHz at 5G new radio (NR) millimeter-wave (mm-Wave) Frequency Range 2 (FR2) bands. A novel stacking arrangement of ring patches is proposed to achieve wide dual-band operation with stable gain. Two pairs of stacked ring patches operating at lower (24.25–29.5 GHz) and upper (37–40 GHz) FR2 bands are alternately integrated at four metal layers. The antenna offers a sharp roll-off and a filter-like response with radiation nulls between the operating bands due to the stacking configuration. The antenna is aperture-coupled and stripline-fed, and it conforms to the antenna-in-package (AiP) requirements. The proposed single antenna element and a $2\times 2$ array are fabricated utilizing a standard commercial printed circuit board (PCB) fabrication facility. The measurement results show a decent agreement with the simulations in terms of impedance matching, isolation, radiation patterns, and realized gain. The proposed design is a promising candidate for 5G mm-Wave base station antenna arrays.