Miracle-dz/UniFAR-FTUs huggingface dataset:
Numerical de‐embedding and experimental validation of propagation properties of corrugated substrate integrated waveguide

In this article, a corrugated substrate integrated waveguide (CSIW) with no metallic vias is proposed, and its propagation characteristics are theoretically investigated via our numerical short‐open calibration (SOC) de‐embedding method. In our analysis, dominant operating modes in this CSIW at different frequencies are extensively discussed. Its complex propagation constant is derived to demonstrate its frequency‐dispersive transmission and attenuation performance. Then, the design rules are described to analyze and design CSIW line. In final, the fabricated CSIW with the microstrip‐line feeders are measured to validate the numerically de‐embedded attenuation constant over a wide frequency range. © 2016 Wiley Periodicals, Inc. Microwave Opt Technol Lett 58:2456–2460, 2016
Chemosensitization Effect of Seabuckthorn (Hippophae rhamnoides L.) Pulp Oil via Autophagy and Senescence in NSCLC Cells

The research has demonstrated a synergistic anticancer effect of Seabuckthorn pulp oil (SBO) and the standard chemotherapy regimen Docetaxel (DTX) against two non-small cell lung cancer (NSCLC) cell lines: A549 and H23. The synergizing effect of an SBO and DTX combination was detected utilizing SRB assay and combination index (CI) approaches. Flow cytometry was carried out using fluorescent probes to measure cell cycle analysis by DNA content and reactive oxygen species (ROS) generation. Further, we demonstrated that the synergistic anticancer activity of SBO merged with DTX was achieved by caspase-independent autophagy and senescence induction. These changes were concomitant with increased generation of ROS production and microtubule-associated protein 1 light chain 3 (LC3) protein expression, G1-phase arrest, and enhanced senescence-associated β-galactosidase staining activity. Our data also demonstrated that SBO or DTX treatment groups solely upregulated the phosphorylation of ERK, which coincided with the induction of autophagy vacuoles and was functionally associated with ROS activation. Moreover, endogenous LC3 puncta staining was performed and monitored by confocal microscopy. Overall, these results suggest new mechanisms for the antitumor activity of SBO co-treated with DTX through triggering autophagic cell death and senescence against cancer cells as a result of sustained ERK phosphorylation and intracellular ROS production in NSCLC. In addition, we also highlight SBO as an alternative therapeutic option or adjunct therapeutic strategy in combination with chemotherapeutic agents in lung cancer therapy management.
Crustal Shortening and Rheological Behavior Across the Longmen Shan Fault, Eastern Margin of the Tibetan Plateau

Knowledge of lithospheric rheology can provide fundamental insights into crustal deformation near the Longmen Shan fault (LMSF). Based on viscoelastic deformation models constrained by interseismic geodetic observations, we obtain an optimal crustal shortening rate of 4.8 ± 0.4 mm/a across the LMSF and an upper mantle viscosity of 5.0 × 1020−21 Pa · s beneath eastern Tibet. More importantly, we find a high‐viscosity zone (>1021 Pa · s) in the lower crust beneath the LMSF, where the steady‐state viscosity is significantly higher than the transient viscosity derived from postseismic deformation. Further investigations with a power‐law rheology suggest that, due to the stress loading of the Wenchuan earthquake and the relaxation afterwards, the effective lower crustal viscosity decreases to ∼1018 Pa · s immediately after the earthquake and finally recovers to interseismic level (∼1021 Pa · s). Our results highlight the stress‐dependent behavior and the viscoelastic effect of rheological structure beneath the LMSF during the earthquake cycle.
Learning Based Channel Allocation and Task Offloading in Temporary UAV-assisted Vehicular Edge Computing Networks

High-level autonomous decision making system is one of the key technologies in intelligent transportation networks, it requires the traffic information within a certain range of vehicles in real time. When the traffic roads become congested or the roadside units (RSUs) are unaccessed beyond the communication range, the unmanned aerial vehicle (UAV)-assisted vehicular edge computing network (VECN) is considered as a potential solution. In this paper, we propose a learning based channel allocation and task offloading strategy in temporary UAV-assisted VECNs from a user perspective, in which the UAV passing temporarily can serve as the relay and edge computing node to support the decision making system. However, the limited available computation resources and time-varying communication channel states make it critical to process the received computing tasks. To address the above mentioned challenges, we design an efficient data transmission strategy combined the long-term evolution vehicle-to-everything (LTE-V2X) and time-division multiple access (TDMA) technologies firstly, then, we propose a multi-option task processing scheme, a service cost minimization problem is proposed where the integral decisions of channel allocation and task processing mode selection are jointly optimized. Under dynamic computing resources and the current data transmission conditions, the UAV selects an optimal task processing service model based on deep reinforcement learning (DRL) algorithm. Simulation results show the proposed strategy greatly improves the data transmission efficiency.
Transfer-Learning-Aided Fault Detection for Traction Drive Systems of High-Speed Trains

Long-term operation may lead to performance degradation of the traction drive systems. It will naturally increase the difficulty of fault detection (FD). To ensure the safe and stable operation of the traction drive system, data-driven FD has received considerable attention, especially deep learning methods. By exploiting the idea of transfer learning, this article proposes a new FD method for traction converter faults in the traction drive systems of high-speed trains. Its structure consists of a federal neural network based on a variational autoencoder. The significant advantages of the proposed FD method based on transfer learning are summarized as follows: 1) FD is still valid for the systems with performance degradation; 2) it can also realize the FD function even if the physical model and related parameters are not provided; and 3) the proposed framework can adaptively adjust the model parameters by storing and reusing the prior knowledge in the neural network. Finally, the effectiveness of the proposed method is demonstrated through the platform of the traction drive control system.
Investigations on ion beams from a high-current ion source

An experimental study on an Ar + beam extracted from a high-current ion source was performed. For beam diagnostics, the beam current and the discharge current as a function of the extraction voltage and of the screening voltage, respectively, were measured. The real two-dimensional beam profile was measured using a multisegmented Faraday cup. A mass spectrum of the ion beam was obtained adjusting the dipole magnet.
Compressed domain ECG biometric with two-lead features

This study presents a new method to combine ECG biometrics with data compression within a common JPEG2000 framework. We target the two-lead ECG configuration that is routinely used in long-term heart monitoring. Incorporation of compressed-domain biometric techniques enables faster person identification as it by-passes the full decompression. Experiments on public ECG databases demonstrate the validity of the proposed method for biometric identification with high accuracies on both healthy and diseased subjects.
Assessment of advanced fluid neutral models for the neutral atoms in the plasma edge and application in ITER geometry

The neutral atoms in the plasma edge of nuclear fusion devices are typically modeled using either a fluid or kinetic approach. The kinetic approach is most accurate, but it has two main disadvantages. First, the usual solution of the high-dimensional kinetic equation using Monte Carlo techniques introduces statistical noise, which hampers the convergence of the coupled plasma-neutral model. Second, the computational time strongly increases for highly collisional regimes. For these reasons, deterministic fluid neutral models remain an attractive alternative, in particular for the highly collisional conditions where their accuracy is expected to be high. In recent years, efforts have been undertaken to improve the agreement between the fluid and kinetic approach by introducing consistent transport coefficients and consistent boundary conditions in the fluid models. In this work, these so-called advanced fluid neutral models are further enhanced by introducing different strategies to cope with the high heterogeneity of the ion-neutral collisionality encountered in realistic plasma-edge geometries, namely isotropic neutral flux limiters and an automated selection criterion for the optimal neutral boundary conditions. The validity of the resulting fluid neutral models is thoroughly assessed for various representative simulation cases with different geometries, divertor collisionalities, and wall materials, including, for the first time, simulations in a realistic ITER plasma edge geometry. Strong quantitative agreement between the fluid and kinetic models is achieved for cases with highest divertor collisionality.
Face liveness detection for face recognition based on cardiac features of skin color image

With the growth of biometric technology, spoofing attacks have been emerged a threat to the security of the system. Main spoofing scenarios in the face recognition system include the printing attack, replay attack, and 3D mask attack. To prevent such attacks, techniques that evaluating liveness of the biometric data can be considered as a solution. In this paper, a novel face liveness detection method based on cardiac signal extracted from face is presented. The key point of proposed method is that the cardiac characteristic is detected in live faces but not detected in non-live faces. Experimental results showed that the proposed method can be effective way for determining printing attack or 3D mask attack.
Lipedema prevalence and risk factors in Brazil

Abstract Background Lipedema is characterized as an abnormal deposition of fat in the buttocks and legs bilaterally that may be accompanied by swelling, pain, and tenderness. It is still often confused with more frequent conditions such as obesity and lymphedema. The estimated prevalence in Europe varies between 0.06% and 39%. Objectives To evaluate the prevalence of lipedema and identify health factors related to it in the Brazilian population. Methods Administration of a previously validated online screening questionnaire to a representative sample of the general population. The questionnaire was distributed and administered to anonymous volunteers representing the general Brazilian population using software designed for population analyses. Results 253 women answered the questionnaire, 12.3 ± 4% (Confidence Interval [CI] 95%) of whom presented symptoms compatible with a high probability of being diagnosed with lipedema. Furthermore, anxiety, depression, hypertension, and anemia were also correlated with a high probability of the diagnosis. Conclusions The estimated prevalence of lipedema in the population of Brazilian women is 12.3%.
Photopolymer characterization by high frequency pulsed laser

Maximizing phase modulation in photopolymers remains a challenge in order to use these materials to fabricate photonics devices. Different material compositions and irradiation conditions have been studied in order to achieve it. One of the main conclusions has been that with continuous laser exposure better results are achieved. However, our results show that higher phase modulation can be achieved using pulsed laser. The study has been done with crosslinked acrylamide-based photopolymers (AA/PVA), Biophotopol and Holographic Polymer-Dispersed Liquid Crystals (HPDLC) exposed with a pulsed laser (532 nm). Thus, phase modulation increases of 8-15% have been achieved between pulsed laser and continuous laser exposure, with a maximum phase depth of 3π radians in AA/PVA, ~3π/2 in Biophotopol and ~π in H-PDLC. This opens the door to the use of this photopolymer in large-scale manufacturing, such as H-PDLC photopolymers to fabricate tunable lenses using the laser-induced direct transfer (LIFT) technique.
Antibody-based in vivo leukocyte label for two-photon brain imaging in mice

Abstract. Significance To study leukocyte-endothelial interactions in a living system, robust and specific leukocyte labeling techniques are needed for in vivo two-photon microscopy of the cerebral microvasculature. Aim We tested fluorophore-conjugated anti-CD45.2 monoclonal antibodies (mAb) to optimize dosing and two-photon imaging parameters for leukocyte labeling in healthy mice and a venous microstroke model. Approach We retro-orbitally injected anti-CD45.2 mAb at 0.04, 0.4, and 2 mg/kg into BALB/c mice and used flow cytometry to analyze antibody saturation. Leukocyte labeling in the cortical microvasculature was examined by two-photon imaging. We also tested the application of CD45.2 mAb in a pathological leukocyte-endothelial adhesion model by photothrombotically occluding cortical penetrating venules. Results We found that 0.4 mg/kg of anti-CD45.2 antibody intravenously was sufficient to label 95% of circulating leukocytes. There was no depletion of circulating leukocytes after 24 h at the dosages tested. Labeled leukocytes could be observed as deep as 550 μm from the cortical surface. The antibody reliably labeled rolling, crawling, and adherent leukocytes in venules around the stroke-affected tissues. Conclusion We show that the anti-CD45.2 mAb is a robust reagent for acute labeling of leukocytes during in vivo two-photon microscopy of the cortical microvasculature.
The efficacy of pulmonary rehabilitation exercise training on complications and mortality after lung cancer resection: a systematic review and meta-analysis

Background The efficacy of pulmonary rehabilitation exercise training for patients after lung cancer resection has been controversial. We sought to evaluate the efficacy of pulmonary rehabilitation on the incidence of complications and mortality in patients after lung cancer resection. Methods Search English databases PubMed, EMBASE, Medline to obtain literature. The literature compared the effect of pulmonary rehabilitation exercise training intervention or not on the efficacy of patients after lung cancer resection, and the outcomes included postoperative complications and mortality. The quality of the included literature was assessed according to the Cochrane risk of bias assessment work. The chi-square test was used to test for heterogeneity. When there is heterogeneity, a random effect model is used; when there is no heterogeneity, a fixed effect model is used. Results A total of 9 prospective clinical studies (comprising 1,338 patients) were included in this meta-analysis. Among the patients, there were 571 cases in the rehabilitation group and 767 cases in the control group. The incidence of postoperative complications in the rehabilitation group was lower than that in the control group. The odds ratio (OR) value was 0.66 and 95% confidence interval (CI) was 0.47–0.94 (P=0.02). There was no heterogeneity among studies and no publication bias. The incidence of postoperative pulmonary complications in the rehabilitation group was lower than that in the control group, OR =0.33 (95% CI: 0.22–0.50) (P<0.00001). There was no heterogeneity among studies and no publication bias. There was no significant difference in postoperative mortality between the 2 groups (OR =0.77; 95% CI: 0.26–2.30; P=0.65). There was no heterogeneity among studies and no publication bias. Discussion Implementing pulmonary rehabilitation significantly reduced postoperative complications and the risk of pulmonary complications in lung cancer patients, but had no significant effect on mortality. Pulmonary rehabilitation exercise training is recommended for patients undergoing lung cancer resection.
Modifiers of and Disparities in Palliative and Supportive Care Timing and Utilization among Neurosurgical Patients with Malignant Central Nervous System Tumors

Simple Summary Guidelines recommend early initiation of palliative care (PC) for patients with advanced cancers. Central nervous system (CNS) malignancies pose particular challenges for patients, who benefit from supportive care services such as PC, home health, and social work support. We analyze a cohort of privately insured patients with malignant brain or spinal tumors from the Optum Clinformatics Datamart Database to investigate health disparities in supportive care service access and utilization. We introduce a novel construct, “provider patient racial diversity index” (provider pRDI), the proportion of non-white minority patients a provider encounters to approximate a provider’s patient demographics and suggest a provider’s exposure to diversity. Our manuscript adds to existing literature on patient-level health disparities and provides a platform for future research focused on provider-level quality improvement interventions for utilization of supportive care services. Abstract Patients with primary or secondary central nervous system (CNS) malignancies benefit from utilization of palliative care (PC) in addition to other supportive services, such as home health and social work. Guidelines propose early initiation of PC for patients with advanced cancers. We analyzed a cohort of privately insured patients with malignant brain or spinal tumors derived from the Optum Clinformatics Datamart Database to investigate health disparities in access to and utilization of supportive services. We introduce a novel construct, “provider patient racial diversity index” (provider pRDI), which is a measure of the proportion of non-white minority patients a provider encounters to approximate a provider’s patient demographics and suggest a provider’s cultural sensitivity and exposure to diversity. Our analysis demonstrates low rates of PC, home health, and social work services among racial minority patients. Notably, Hispanic patients had low likelihood of engaging with all three categories of supportive services. However, patients who saw providers categorized into high provider pRDI (categories II and III) were increasingly more likely to interface with supportive care services and at an earlier point in their disease courses. This study suggests that prospective studies that examine potential interventions at the provider level, including diversity training, are needed.
The evolution and future of lean Six Sigma 4.0

PurposeThis purpose of this study is to provide an overview of the current state of research on Lean Six Sigma (LSS) and Industry 4.0 and the key aspects of the relationships between them. The research analyses LSS's evolution and discusses the future role of LSS 4.0 in an increasingly digitalized world. We present the benefits and motivations of integrating LSS and Industry 4.0 as well as the critical success factors and challenges within this emerging area of research.Design/methodology/approachA systematic literature review methodology was established to identify, select and evaluate published research.FindingsThere is a synergistic nature between LSS and Industry 4.0. Companies having a strong LSS culture can ease the transition to Industry 4.0 while Industry 4.0 technologies can provide superior performance for companies who are using LSS methodology.Research limitations/implicationsOne limitation of this research was that as this area is a nascent area, the researchers were limited in their literature review and research. A more comprehensive longitudinal study would yield more data. There is an opportunity for further study and analysis.Practical implicationsThis study reviews the evolution of LSS and its integration with Industry 4.0. Organisations can use this study to understand the benefits and motivating factors for integrating LSS and Industry 4.0, the Critical Success Factors and challenges to such integration.Originality/valueThis is the first systematic literature review on LSS 4.0 and can provide insight for practitioners, organisations and future research directions.
Chronic unrelenting cough secondary to pericardial cyst impingement of right phrenic nerve

Abstract Located in the mediastinum, pericardial cysts are rare and benign congenital abnormalities commonly identified as incidental findings on imaging. However, some patients with abnormally enlarged cysts present with compressive symptoms, which include recurrent infections, tamponade from cardiac compression and respiratory complications. Our report highlights a challenging case of a patient with recurrent respiratory symptoms secondary to phrenic nerve compression. Misdiagnosis over the past decade resulted in ineffective interventions. After clear identification of the cyst compression of the ipsilateral phrenic nerve, the patient underwent a minimally invasive robotically assisted cyst resection with phrenic nerve preservation that alleviated respiratory symptoms.
Analysis of Features in a Sliding Threshold of Observation for Numeric Evaluation (STONE) Curve

We apply idealized scatterplot distributions to the sliding threshold of observation for numeric evaluation (STONE) curve, a new model assessment metric, to examine the relationship between the STONE curve and the underlying point‐spread distribution. The STONE curve is based on the relative operating characteristic (ROC) curve but is developed to work with a continuous‐valued set of observations, sweeping both the observed and modeled event identification threshold simultaneously. This is particularly useful for model predictions of time series data as is the case for much of terrestrial weather and space weather. The identical sweep of both the model and observational thresholds results in changes to both the modeled and observed event states as the quadrant boundaries shift. The changes in a data‐model pair's event status result in nonmonotonic features to appear in the STONE curve when compared to an ROC curve for the same observational and model data sets. Such features reveal characteristics in the underlying distributions of the data and model values. Many idealized data sets were created with known distributions, connecting certain scatterplot features to distinct STONE curve signatures. A comprehensive suite of feature‐signature combinations is presented, including their relationship to several other metrics. It is shown that nonmonotonic features appear if a local spread is more than 0.2 of the full domain or if a local bias is more than half of the local spread. The example of real‐time plasma sheet electron modeling is used to show the usefulness of this technique, especially in combination with other metrics.