Sentiment and semantic analysis: Urban quality inference using machine learning algorithms.

Sustainable urban transformation requires comprehensive knowledge about the built environment, including people's perceptions, use of sites, and wishes. Qualitative interviews are conducted to understand better people's opinions about a specific topic or location. This study explores the automatization of the interview coding process by investigating how state-of-the-art natural language processing techniques classify sentiment and semantic orientation from interviews transcribed in Swedish. For the sentiment analysis, the Swedish bidirectional encoder representations from transformers (BERT) model KB-BERT was used to perform a multi-class classification task on a text sentence level into three different classes: positive, negative, and neutral. Named entity recognition (NER) and string search were used for the semantic analysis to perform multi-label classification to match domain-related topics to the sentence. The models were trained and evaluated on partially annotated datasets. The results demonstrate that the implemented deep learning techniques are a possible and promising solution to achieve the stated goal.

Research Progress on the Cardiotoxicity of EGFR-TKIs in Non-Small Cell Lung Cancer.

OPINION STATEMENT: With the development of molecular biology and histology techniques, targeted therapy for non-small cell lung cancer (NSCLC) has emerged, which is highly effective and has marginal side effects. Epidermal growth factor receptor (EGFR) was the first driver gene discovered, whose three generations of therapeutic use have its characteristics and benefits in clinical practice. However, cardiovascular complications by EGFR-tyrosine kinase inhibitors (EGFR-TKIs) in preclinical studies have been increasingly reported, including heart failure, cardiomyopathy, and QT prolongation, among others. Cardiotoxicity of targeted drugs significantly affects the therapeutic effect of NSCLC and has become the second leading cause of death in NSCLC. The aim of the present review was to recognize the potential cardiotoxicity of third-generation targeted drugs in the treatment of NSCLC and their associated mechanisms to help clinicians identify and prevent it early in the treatment, minimize the cardiotoxicity of targeted drugs, and improve the therapeutic effect of patients.

Antifungal Activity and Action Mechanisms of 2,4-Di-tert-butylphenol against Ustilaginoidea virens.

Ustilaginoidea virens is a destructive phytopathogenic fungus that causes false smut disease in rice. In this study, the natural product 2,4-di-tert-butylphenol (2,4-DTBP) was found to be an environmentally friendly and effective agent for the first time, which exhibited strong antifungal activity against U. virens, with an EC50 value of 0.087 mmol/L. The scanning electron microscopy, fluorescence staining, and biochemical assays indicated that 2,4-DTBP could destroy the cell wall, cell membrane, and cellular redox homeostasis of U. virens, ultimately resulting in fungal cell death. Through the transcriptomic analysis, a total of 353 genes were significantly upregulated and 367 genes were significantly downregulated, focusing on the spindle microtubule assembly, cell wall and membrane, redox homeostasis, mycotoxin biosynthesis, and intracellular metabolism. These results enhanced the understanding of the antifungal activity and action mechanisms of 2,4-DTBP against U. virens, supporting it to be a potential antifungal agent for the control of false smut disease.

PD-1/PD-L1 immune checkpoint inhibitors in metastatic triple-negative breast cancer: a systematic review and meta-analysis.

Background: PD-1/PD-L1 immune checkpoint inhibitors (ICIs) have been controversial in the treatment of metastatic triple negative breast cancer (mTNBC). We collected randomized controlled trials in accordance with the study and carried out meta-analysis to comprehensively evaluate the efficacy and safety of immune checkpoint inhibitors in mTNBC. Aim: To systematically evaluate the efficacy and safety of PD-1/PD-L1 ICIs (hereinafter referred to as ICIs) in the treatment of mTNBC. Methods: As of 2023.2.5, Medline, PubMed, Embase, Cochrane library database and Web of Science were searched to determine the study in accordance with the trial of ICIs in the treatment of mTNBC. The assessment endpoints included objective response rate (ORR), progression-free survival (PFS), overall survival (OS), and safety. Meta-analysis of the included studies was performed using Revman 5.4. Results: A total of six trials with 3172 patients were included in this meta-analysis. The ORR of ICIs combined with chemotherapy was significantly improved compared with chemotherapy (HR=0.88, 95%CI: 0.81-0.94, I2 = 0%). For PFS, the experimental group were better than the control group in both intention-to-treat (ITT) population and PD-L1 positive population, showing statistical significance (ITT: HR=0.81, 95%CI: 0.74-0.89, P<0.05, I2 = 0%; PD-L1 positive: HR=0.72, 95%CI: 0.63-0.82, P<0.05, I2 = 18%); For OS, in the ITT population, no statistical difference was observed in either ICIs combined with chemotherapy(HR=0.92, 95%CI: 0.83-1.02, P=0.10)or immune monotherapy(HR=0.78, 95%CI: 0.44-1.36, P=0.37), in the PD-L1 positive population, ICIs group had better OS than chemotherapy group (HR=0.83, 95%CI: 0.74-0.93, P < 0.05); In safety, serious adverse event (SAE) was no statistically significant difference between the ICIs group and the chemotherapy group; however, the incidence of immune-related adverse event (irAE) was significantly higher in the ICIs group than in the chemotherapy group (HR=2.15, 95%CI: 1.45-3.19, P < 0.05). Conclusion: ICIs combined with chemotherapy significantly improved the PFS of mTNBC, however, ICIs only improved the OS in PD-L1 positive people, and no statistical difference was observed in ITT population; while benefiting from ICIs, we found that irAE in ICIs group increased significantly, and its high rate of adverse events still needs to be taken seriously.

Natural occurrence of ustiloxins in rice from five provinces in China and the removal efficiencies of different milling steps.

BACKGROUND: The widespread incidence of "false smut" disease in rice has caused extensive ustiloxin contamination around the world. Until now there has been a lack of knowledge regarding the natural occurrence of ustiloxins in paddy. The development of efficient removal methods is also still a challenge that remains unexplored. RESULTS: In the current study, three main ustiloxins - ustiloxin A (UA), ustiloxin B (UB), and ustiloxin G (UG) - were determined simultaneously by ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) in 206 paddy samples collected in 2021 from five rice-producing provinces in China. The predominant ustiloxin was UA with an occurrence of 46.1% and an average concentration of 49.71 µg kg-1 . This was followed by UB (31.1%, 13.31 µg kg-1 ) and UG (18.4%, 9.19 µg kg-1 ). No targeted ustiloxins were detected in white rice samples randomly collected from supermarkets in Shanghai. To reveal the causes, two approaches were tested for the removal of the ustiloxins: most of the targeted ustiloxins (>93%) were removed in brown rice by husking and, subsequently, all targeted ustiloxins (100%) were removed by whitening. CONCLUSION: A wide distribution of ustiloxins was discovered in paddy samples in this study. The UA contaminations were significantly different depending on their origin, with the highest occurrence in paddy from Shanghai and Jiangsu, southeast coast provinces in China. Contamination by UG was also found in paddy for the first time and was strongly correlated with those of UA and UB. A combination of husking and whitening has been verified to be a practicable and promising way to ensure efficient removal and food safety. © 2023 Society of Chemical Industry.

[Effect of electroacupuncture on pyroptosis of synovial tissues in rats with knee osteoarthritis].

OBJECTIVE: To observe the effect of electroacupuncture (EA) on pyroptosis-related proteins in synovium of knee joint in rats with knee osteoarthritis(KOA), in order to explore its mechanism underlying improvement of KOA. METHODS: Forty male SD rats were randomly divided into control， model, EA and medication groups, with 10 rats in each group. The KOA model was established by injecting 0.2 mL 4% papain solution into the right intra-articular cavity, followed by repeating the injection again on day 4 and 7 after the first injection. After successful modeling, rats of the EA group received EA stimulation of "Neixiyan" (EX-LE4) and "Dubi"(ST35) on the right limb for 15 min, once every day, 6 days per week, for a total of 4 weeks, and those of the medication group received gavage of celecoxib 24 mg/kg, once every day, 6 days per week, for a total of 4 weeks. The severity of dysfunction of the right knee was assessed by using Lequesne's score. Serum interleukin(IL)-1ß and IL-18 contents were detected by ELISA. Histopathological changes of the synovium tissue of the right knee joint were observed to give score (synovial pathological score) after H.E. staining. The expression position and intensity of Nod-like receptor pyrin domain 3 (NLRP3) in syno-vial tissue were observed by immunohistochemistry. The expression levels of NLRP3, apoptosis-associated speck-like protein containing card (ASC), Caspase-1, Gasdermin D(GSDMD), IL-1ß and IL-18 mRNAs and proteins (including GSDMD-N) in the synovial tissue of the right knee joint were detected by real-time fluorescence quantitative PCR and Western blot, separately. RESULTS: Compared with the control group, the model group had a significant increase in the Lequesne's score, synovial pathological score, serum IL-1ß and IL-18 contents, and the expression levels of NLRP3, ASC, Caspase-1, GSDMD, IL-1ß, IL-18 mRNAs and proteins and GSDMD-N protein (P<0.01). Whereas relevant to the model group, both the EA and medication groups had marked lower levels of Lequesne's score and synovial pathological score, serum IL-1ß and IL-18 contents, and expression levels of NLRP3, ASC, Caspase-1, IL-1ß, IL-18 mRNAs and proteins, GSDMD mRNA and GSDMD-N protein (P<0.01, P<0.05). Comparison between two intervention groups showed that the contents of serum IL-1ß and IL-18, and the expression levels of IL-1ß mRNA and protein were significantly higher in the EA group than in the medication group (P<0.05, P<0.01). No significant differences were found between the EA and medication groups in the Lequesne's score, synovial pathological score, NLRP3, ASC, Caspase-1 and IL-18 mRNAs and proteins, as well as GSDMD mRNA (P>0.05). CONCLUSION: EA can alleviate the inflammatory response of synovial tissues of knee joints in KOA rats, which may be related to its function in down-regulating the expression levels of synovial NLRP3, ASC, Caspase-1, IL-1ß and IL-18 mRNAs and proteins, and GSDMD mRNA and GSDMD-N proteins, reducing the occurrence of pyroptosis.

RAVAN: CubeSat Demonstration for Multi-Point Earth Radiation Budget Measurements.

The Radiometer Assessment using Vertically Aligned Nanotubes (RAVAN) 3U CubeSat mission is a pathfinder to demonstrate technologies for the measurement of Earth's radiation budget, the quantification of which is critical for predicting the future course of climate change. A specific motivation is the need for lower-cost technology alternatives that could be used for multi-point constellation measurements of Earth outgoing radiation. RAVAN launched 11 November 2016, into a nearly 600-km, Sun-synchronous orbit, and collected data for over 20 months. RAVAN successfully demonstrates two key technologies. The first is the use of vertically aligned carbon nanotubes (VACNTs) as absorbers in broadband radiometers for measuring Earth's outgoing radiation and the total solar irradiance. VACNT forests are arguably the blackest material known and have an extremely flat spectral response over a wide wavelength range, from the ultraviolet to the far infrared. As radiometer absorbers, they have greater sensitivity for a given time constant and are more compact than traditional cavity absorbers. The second technology demonstrated is a pair of gallium phase-change black body cells that are used as a stable reference to monitor the degradation of RAVAN's radiometer sensors on orbit. Four radiometers (two VACNT, two cavity), the pair of gallium black bodies, and associated electronics are accommodated in the payload of an agile 3U CubeSat bus that allows for routine solar and deep-space attitude maneuvers, which are essential for calibrating the Earth irradiance measurements. The radiometers show excellent long-term stability over the course of the mission and a high correlation between the VACNT and cavity radiometer technologies. Short-term variability-at greater than the tenths-of-a-Watt/m2 needed for climate accuracy-is a challenge that remains, consistent with insufficient thermal knowledge and control on a 3U CubeSat. There are also VACNT-cavity biases of 3% and 6% in the Total and SW channels, respectively, which would have to be overcome in a future mission. Although one of the black bodies failed after four months, the other provided a repeatable standard for the duration of the project. We present representative measurements from the mission and demonstrate how the radiometer time series can be used to reconstruct outgoing radiation spatial information. Improvements to the technology and approach that would lead to better performance and greater accuracy in future missions are discussed.

CLAss-Specific Subspace Kernel Representations and Adaptive Margin Slack Minimization for Large Scale Classification.

In kernel-based classification models, given limited computational power and storage capacity, operations over the full kernel matrix becomes prohibitive. In this paper, we propose a new supervised learning framework using kernel models for sequential data processing. The framework is based on two components that both aim at enhancing the classification capability with a subset selection scheme. The first part is a subspace projection technique in the reproducing kernel Hilbert space using a CLAss-specific Subspace Kernel representation for kernel approximation. In the second part, we propose a novel structural risk minimization algorithm called the adaptive margin slack minimization to iteratively improve the classification accuracy by an adaptive data selection. We motivate each part separately, and then integrate them into learning frameworks for large scale data. We propose two such frameworks: the memory efficient sequential processing for sequential data processing and the parallelized sequential processing for distributed computing with sequential data acquisition. We test our methods on several benchmark data sets and compared with the state-of-the-art techniques to verify the validity of the proposed techniques.

The role of spatial frequency in emotional face classification.

Previous studies with emotional face stimuli have revealed that our ability to identify different emotional states is dependent on the faces' spatial frequency content. However, these studies typically only tested a limited number of emotional states. In the present study, we measured the consistency with which 24 different emotional states are classified when the faces are unfiltered, high-, or low-pass filtered, using a novel rating method that simultaneously measures perceived arousal (high to low) and valence (pleasant to unpleasant). The data reveal that consistent ratings are made for every emotional state independent of spatial frequency content. We conclude that emotional faces possess both high- and low-frequency information that can be relied on to facilitate classification.

Microwave technology for detecting traumatic intracranial bleedings: tests on phantom of subdural hematoma and numerical simulations.

Traumatic brain injury is the leading cause of death and severe disability for young people and a major public health problem for elderly. Many patients with intracranial bleeding are treated too late, because they initially show no symptoms of severe injury and are not transported to a trauma center. There is a need for a method to detect intracranial bleedings in the prehospital setting. In this study, we investigate whether broadband microwave technology (MWT) in conjunction with a diagnostic algorithm can detect subdural hematoma (SDH). A human cranium phantom and numerical simulations of SDH are used. Four phantoms with SDH 0, 40, 70 and 110 mL are measured with a MWT instrument. The simulated dataset consists of 1500 observations. Classification accuracy is assessed using fivefold cross-validation, and a validation dataset never used for training. The total accuracy is 100 and 82-96 % for phantom measurements and simulated data, respectively. Sensitivity and specificity for bleeding detection were 100 and 96 %, respectively, for the simulated data. SDH of different sizes is differentiated. The classifier requires training dataset size in order of 150 observations per class to achieve high accuracy. We conclude that the results indicate that MWT can detect and estimate the size of SDH. This is promising for developing MWT to be used for prehospital diagnosis of intracranial bleedings.

Active cancellation of residual amplitude modulation in a frequency-modulation based Fabry-Perot interferometer.

Residual amplitude modulation (RAM) is one of the most common noise sources known to degrade the sensitivity of frequency modulation spectroscopy. RAM can arise as a result of the temperature dependent birefringence of the modulator crystal, which causes the orientation of the crystal's optical axis to shift with respect to the polarization of the incident light with temperature. In the fiber-based optical interferometer used on the National Institute of Standards and Technology calculable capacitor, RAM degrades the measured laser frequency stability and correlates with the environmental temperature fluctuations. We have demonstrated a simple approach that cancels out excessive RAM due to polarization mismatch between the light and the optical axis of the crystal. The approach allows us to measure the frequency noise of a heterodyne beat between two lasers individually locked to different resonant modes of a cavity with an accuracy better than 0.5 ppm, which meets the requirement to further determine the longitudinal mode number of the cavity length. Also, this approach has substantially mitigated the temperature dependency of the measurements of the cavity length and consequently the capacitance.

Pleth variability index-directed fluid management in abdominal surgery under combined general and epidural anesthesia.

Pleth variability index (PVI), a noninvasive dynamic indicator of fluid responsiveness has been demonstrated to be useful in the management of the patients with goal directed fluid therapy under general anesthesia, but whether PVI can be used to optimize fluid management under combined general and epidural anesthesia (GEN-EPI) remains to be elucidated. The aim of our study was to explore the impact of PVI as a goal-directed fluid therapy parameter on the tissue perfusion for patients with GEN-EPI. Thirty ASA I-II patients scheduled for major abdominal surgeries under GEN-EPI were randomized into PVI-directed fluid management group (PVI group) and non PVI-directed fluid management group (control group). 2 mL/kg/h crystalloid fluid infusion was maintained in PVI group, once PVI>13%, a 250 mL colloid or crystalloid was rapidly infused. 4-8 mL/kg/h crystalloid fluid infusion was maintained in control group, and quick fluid infusion was initiated if mean arterial blood pressure (BP)<65 mmHg. Small doses of norepinephrine were given to keep mean arterial BP above 65 mmHg as needed in both groups. Perioperative lactate levels, hemodynamic changes were recorded individually. The total amount of intraoperative fluids, the amount of crystalloid fluid and the first hour blood lactate levels during surgery were significantly lower in PVI than control group, P<0.05. PVI-based goal-directed fluid management can reduce the intraoperative fluid amount and blood lactate levels in patients under GEN-EPI, especially the crystalloid. Furthermore, the first hour following GEN-EPI might be the critical period for anesthesiologist to optimize the fluid management.

Microwave-based stroke diagnosis making global prehospital thrombolytic treatment possible.

Here, we present two different brain diagnostic devices based on microwave technology and the associated two first proof-of-principle measurements that show that the systems can differentiate hemorrhagic from ischemic stroke in acute stroke patients, as well as differentiate hemorrhagic patients from healthy volunteers. The system was based on microwave scattering measurements with an antenna system worn on the head. Measurement data were analyzed with a machine-learning algorithm that is based on training using data from patients with a known condition. Computer tomography images were used as reference. The detection methodology was evaluated with the leave-one-out validation method combined with a Monte Carlo-based bootstrap step. The clinical motivation for this project is that ischemic stroke patients may receive acute thrombolytic treatment at hospitals, dramatically reducing or abolishing symptoms. A microwave system is suitable for prehospital use, and therefore has the potential to allow significantly earlier diagnosis and treatment than today.

Microwave transitions in pairs of Rb Rydberg atoms.

We have observed microwave transitions between pairs of cold Rb atoms, specifically, transitions between the molecular nd(5/2)nd(5/2) and (n+1)d(j)(n-2)f states for 41≤n≤44. (We use the separated atom limits as labels.) The transition is allowed because the dipole-dipole induced configuration interaction between the nd(5/2)nd(5/2) state and the energetically close (n+2)p(3/2)(n-2)f state leads to an admixture of the latter into the former. Such transitions may provide a way of selecting closely spaced pairs of atoms.

Microwave technology for localization of traumatic intracranial bleedings-a numerical simulation study.

Traumatic brain injury (TBI) is a major public health problem worldwide. Intracranial bleedings represents the most serious complication of TBI and need to be surgically evacuated promptly to save lives and mitigate injury. Microwave technology (MWT) is promising as a complement to computed tomography (CT) to be used in road and air ambulances for early detection of intracranial bleedings. In this study, we perform numerical simulations to investigate if a classification algorithm based on singular value decomposition can distinguish between bleedings at different positions adjacent to the skull bone for a similar but simplified problem. The classification accuracy is 94-100% for all classes, a result that encourages us to pursue our efforts with MWT for more realistic scenarios. This indicates that MWT has potential for localizing a detected bleeding, which would increase the diagnostic value of this technique.

A novel algorithm for view and illumination invariant image matching.

The challenges in local-feature-based image matching are variations of view and illumination. Many methods have been recently proposed to address these problems by using invariant feature detectors and distinctive descriptors. However, the matching performance is still unstable and inaccurate, particularly when large variation in view or illumination occurs. In this paper, we propose a view and illumination invariant image-matching method. We iteratively estimate the relationship of the relative view and illumination of the images, transform the view of one image to the other, and normalize their illumination for accurate matching. Our method does not aim to increase the invariance of the detector but to improve the accuracy, stability, and reliability of the matching results. The performance of matching is significantly improved and is not affected by the changes of view and illumination in a valid range. The proposed method would fail when the initial view and illumination method fails, which gives us a new sight to evaluate the traditional detectors. We propose two novel indicators for detector evaluation, namely, valid angle and valid illumination, which reflect the maximum allowable change in view and illumination, respectively. Extensive experimental results show that our method improves the traditional detector significantly, even in large variations, and the two indicators are much more distinctive.