Miracle-dz/UniFAR-FTUs huggingface dataset:
An aptamer and Au/Si CCA based SERS sensor for ultra-sensitive detection of Vimentin during EMT in gastric cancer

Introduction: In this study, a surface-enhanced Raman scattering (SERS) sensor based on a functionalized Au/Si cap-cone array (Au/Si CCA) was constructed using the identity-release strategy to detect Vimentin changes during epithelial-mesenchymal transition (EMT) in gastric cancer (GC). Methods: The periodic structure of Au/Si CCA, which can form “hot spots” with high density and regular arrangement, is a substrate with excellent performance. Au/Si CCA was functionalized with aptamers as the capture substrate, and Au nanocubes (AuNCs) were modified with 5-carboxyfluorescein (5-FAM) labelled complementary strand as SERS probe. The capture substrate and SERS probe were assembled by hybridization, and the SERS signal intensity of 5-FAM was greatly enhanced. The binding of Vimentin to the aptamer resulted in a broken connection between the SERS sensor Au/Si CCA array and AuNCs, which resulted in a decrease in the signal intensity of 5-FAM. The identity-release strategy requires only a simple step of reaction to achieve rapid detection of target proteins, which has clinical practicability. Results: Using this protocol, the concentration of Vimentin in GES-1 cells could be successfully detected, and the detection limit was as low as 4.92 pg/mL. Biological experiments of Vincristine, Oncovin (VCR)-treated GES-1 cells effectively mimicked the EMT process, and Vimentin changes during EMT could be accurately detected by this method. Discussion: This study provides a selective, ultra-sensitive and accurate assay for Vimentin detection, which may provide a means for the future detection of EMT process in GC.
Rank-based multiple change-point detection

Abstract A nonparametric procedure is proposed to estimate multiple change-points of location changes in a univariate data sequence by using ranks instead of the raw data. While existing rank-based multiple change-point detection methods are mostly based on sequential tests, we treat it as a model selection problem. We derive the corresponding Schwarz’s information criterion for rank-statistics, theoretically prove the consistency of the change-point estimator and use a pruned dynamic programing algorithm to achieve the change-point estimator. Simulation studies show our method’s robustness, effectiveness and efficiency in detecting mean-changes. We also apply the method to a gene dataset as an illustration.
Distance to vaccine sites is tied to decreased COVID-19 vaccine uptake

Abstract COVID-19 remains a leading cause of mortality in the United States, despite the widespread availability of vaccines. Conventional wisdom ties failure to vaccinate primarily to vaccine-skeptic beliefs (e.g. conspiracy theories, partisanship). Yet in this research, we find that vaccination is also hindered by travel distance to vaccine sites (a form of friction, or structural barriers). In study 1, Californians living farther from vaccine sites had lower vaccination rates, and this effect held regardless of partisanship. In study 2, Chicago zip codes saw an uptick in vaccination following vaccine site opening. These results proved robust in multiverse analyses accounting for a wide range of covariates, outcomes, and distance indicators. COVID-19 vaccination is hampered not only by vaccine hesitancy but also by structural barriers like distance. Efforts to boost vaccination could benefit from minimizing friction.
Self-Organizing Multiple Readouts for Reservoir Computing

With advancements in deep learning (DL), artificial intelligence (AI) technology has become an indispensable tool. However, the application of DL incurs significant computational costs, making it less viable for edge AI scenarios. Consequently, the demand for cost-effective AI solutions, other than DL-based approaches, is increasing. Reservoir computing (RC) has attracted interest owing to its ability to provide low-cost training alternatives, holding great promise for edge AI applications. However, the training capability of RC is constrained by its reliance on a single linear layer, while weight connections in the remaining layers remain static during training. Moreover, accomplishing continuous learning tasks is difficult owing to the catastrophic forgetting in the linear layer. Therefore, we propose the integration of self-organizing multiple readouts to enhance RC’s training capability. Our method distributes training data across multiple readouts, which prevents catastrophic forgetting of readouts and empowers each readout to adeptly assimilate new data, thereby elevating the overall training performance. The self-organizing function, which assigns similar data to the same readout, optimizes the memory utilization of these multiple readouts. Experimental results show that an RC equipped with the proposed multiple readouts successfully solved a continuous learning task by mitigating catastrophic forgetting because of the data distribution to the multiple readouts. Additionally, the RC achieved higher accuracy in a sound recognition task compared with the existing RC paradigm because of ensemble learning in the multiple readouts. Multiple readouts are effective in enhancing the training capability of RC and can contribute to the realization of RC applications.
An Optimised Fuzzy Approach to Remove Mixed Noise from Images

Mixed noises can be defined as a combination of different types of noises acting on a single carrier. There has been a mention of various mechanisms used to restore images corrupted with mixed noise in the past. This paper proposes a simple method based on fuzzy set theory and Bilateral Filter to remove mixed noises and compares it with previously mentioned techniques such as: Vector Median Filter(VMF), Vector Direction Filter (VDF), Fuzzy Peer Group Averaging (FPGA), Fuzzy Vector Median Filter (FVMF), Bilateral Filter (BF), Adaptive Bilateral Filter (ABF), Switching Bilateral Filter (SBF), Joint Bilateral Filter (JBF), and Trilateral Filter (TF) on the basis of performance metrics such as Peak Signal to Noise Ratio (PSNR), Mean Absolute Error (MAE), Mean Square Error (MSE) and Normalised Colour Difference (NCD). For the purpose of a detailed analysis, the performance of each method is evaluated by varying the image size and the noise density by implementing them in MATLAB-09. The mixed noise used in this paper is a combination of three noise i.e. poisson, impulse and Gaussian noise. The simulation and result shows that the proposed method provides better PSNR and hence better image quality than almost all the methods mentioned above.
Three-dimensional movement analysis for near infrared system using stereo vision and optical flow techniques

The purpose of this paper is the measurement of spatial-temporal movements by using stereo vision and 3D optical flow algorithms applied at biological samples. Stereo calibration procedures and algorithms for enhance the contrast intensity were applied. The system was implemented for working at the first near infrared windows (NIR-I) at 850 nm due of the penetration depth obtained at this region in biological tissue. Experimental results of 3D tracking of human veins are presented showing the characteristics of the implementation.
Enhanced central sympathetic tone induces heart failure with preserved ejection fraction (HFpEF) in rats

Heart failure with preserved ejection fraction (HFpEF) is a heterogenous clinical syndrome characterized by diastolic dysfunction, concentric cardiac left ventricular (LV) hypertrophy, and myocardial fibrosis with preserved systolic function. However, the underlying mechanisms of HFpEF are not clear. We hypothesize that an enhanced central sympathetic drive is sufficient to induce LV dysfunction and HFpEF in rats. Male Sprague–Dawley rats were subjected to central infusion of either saline controls (saline) or angiotensin II (Ang II, 20 ng/min, i.c.v) via osmotic mini-pumps for 14 days to elicit enhanced sympathetic drive. Echocardiography and invasive cardiac catheterization were used to measure systolic and diastolic functions. Mean arterial pressure, heart rate, left ventricular end-diastolic pressure (LVEDP), and ± dP/dt changes in responses to isoproterenol (0.5 μg/kg, iv) were measured. Central infusion of Ang II resulted in increased sympatho-excitation with a consequent increase in blood pressure. Although the ejection fraction was comparable between the groups, there was a decrease in the E/A ratio (saline: 1.5 ± 0.2 vs Ang II: 1.2 ± 0.1). LVEDP was significantly increased in the Ang II-treated group (saline: 1.8 ± 0.2 vs Ang II: 4.6 ± 0.5). The increase in +dP/dt to isoproterenol was not significantly different between the groups, but the response in -dP/dt was significantly lower in Ang II-infused rats (saline: 11,765 ± 708 mmHg/s vs Ang II: 8,581 ± 661). Ang II-infused rats demonstrated an increased heart to body weight ratio, cardiomyocyte hypertrophy, and fibrosis. There were elevated levels of atrial natriuretic peptide and interleukin-6 in the Ang II-infused group. In conclusion, central infusion of Ang II in rats induces sympatho-excitation with concurrent diastolic dysfunction, pathological cardiac concentric hypertrophy, and cardiac fibrosis. This novel model of centrally mediated sympatho-excitation demonstrates characteristic diastolic dysfunction in rats, representing a potentially useful preclinical murine model of HFpEF to investigate various altered underlying mechanisms during HFpEF in future studies.
Core loss resistance impact on sensorless speed control of an induction motor using hybrid adaptive sliding mode observer

: Induction motors (IMs) experience power losses when a portion of the input power is converted to heat instead of driving the load. The combined eﬀect of copper losses, core losses, and mechanical losses results in IM power losses. Unfortunately, the core losses in the motor, which have a considerable impact on its energy eﬃciency, are not taken into account by the generally employed dynamic model in the majority of the studies. Due to this, the motor rating often corresponds to the worst-case load in applications, but the motor frequently operates below rated conditions. A hybridized model reference adaptive system (MRAS) with sliding mode control (SMC) is used in this study for sensorless speed control of an induction motor with core loss, allowing the motor to operate under a variety of load conditions. As a result, the machine can run at maximum eﬃciency while carrying its rated load. By adjusting the 𝛼 -axis current in the 𝛼 − 𝛽 reference frame in vector-controlled drives, the system’s performance is enhanced by running the motor at its optimum ﬂux. Regarding the torque and speed of both induction motors with and without core loss, the Adaptive Observer Sliding Mode Control (AOSMC) has been constructed and simulated in this case. The AOSMC with core loss produced good performance when the proposed controller was tested.
Isolation and Characterization of Dye Decolorizing Bacteria from The Textile Dye Effluents

The most significant challenge confronted by the textile industries is the discharge of dye effluents which contains toxic chemicals posing a considerable threat to environmental pollution. Biological method of treating effluents using bacteria is one of the renewed and accepted method in effluent treatment. The present study aims to isolate and characterise the dye decolorizing bacteria from the effluent samples of a dye industry from Chinnalapatti, Tamilnadu. The dye effluents were collected from the effluent plant of a leading dye industry and the Physiochemical parameters were analysed. The samples were plated in a Nutrient Agar and bacterial isolation were performed according to the standard microbiological procedures. The bacterial isolates identified by biochemical identification were tested for its efficiency to decolorize Methyl red and crystal violet dyes. Among the three isolates S1showed 98% decolorizing efficiency in reducing Methyl red dye and 92% efficiency in decolorizing crystal violet dye. Sample S2 showed 85% activity in decolorizing methyl red dye and 86% activity in decolorising Crystal violet dye. S3 showed a low decolorizing activity compared to S1 and S2. Both of these phenotypically identified isolates are subjected to molecular identification by 16s gene amplification and gene sequencing. The obtained FASTA sequence were analysed for the phylogenetic relationship and submitted to NCBI. The potential isolate that has the capacity to decolorise the dyes were identified as Bacillus Tropicus and Pseudomonas mosselli. This study proves that these bacterial strains can be used as a potential bioremediation agent in decolorizing the dye effluents.
A meta-analysis

Background: To study the epidemic features of hand-foot-mouth disease (HFMD) in mainland China through systematic review and meta-analysis so as to provide evidence for the future prevention and control of HFMD. Methods: Articles on the epidemic features of HFMD in mainland China, written in English or Chinese and released between January 1, 2015 and January 1, 2020, were searched from English literature databases including Embase,Web of Science, PubMed, Cochrane library, Google academic, and Chinese literature databases including China national knowledge infrastructure (CNKI), Wanfang, and China Biology Medicine (CBM). Papers were selected according to the inclusion and exclusion criteria, and quality scoring was performed. Meta-analysis, sensitivity analysis, and identification of publication bias were finished through STATA version 12.0 software. Results:A total of 23 articles were included in this study, the total number of cases was 377,083, of which the total number of male cases was 231,798 and the total number of female cases was 145,285, the sex ratio was about 1.6:1, and the incidence of HFMD in China was 1.61‰ (95% confidence interval [CI]: 1.21‰–1.94‰). The results of the subgroup analysis showed that the incidence of HFMD in mainland China was the highest in South China, in 2014, in 1-year-old group and in other types of enteroviruses, respectively, with the rate of 3.48‰ (95% CI: 1.22‰–5.73‰), 1.81‰ (95% CI: 1.06‰–2.57‰), 15.20‰ (95% CI: 5.00‰– 25.30‰), and 1.83‰ (95% CI: 1.32‰–2.33‰), respectively. The differences among the above 4 subgroups were statistically significant (P< .05). There were no publication bias in this study, and the sensitivity analysis results suggested that the meta-analysis results were robust. Conclusion: There were differences in the distribution of region, time, population, and etiology of HFMD in mainland China. Health departments should adopt key strategies and measures for key populations in key areas to prevent and control the development of HFMD, and improve the ability of pathogen detection and typing in laboratories. Abbreviations: Cox A16 = coxsackievirus A16, EV71 = human enterovirus 71, HFMD = hand-foot-mouth disease.
Application of Sorbent-Based Extraction Techniques in Food Analysis

This review presents an outline of the application of the most popular sorbent-based methods in food analysis. Solid-phase extraction (SPE) is discussed based on the analyses of lipids, mycotoxins, pesticide residues, processing contaminants and flavor compounds, whereas solid-phase microextraction (SPME) is discussed having volatile and flavor compounds but also processing contaminants in mind. Apart from these two most popular methods, other techniques, such as stir bar sorptive extraction (SBSE), molecularly imprinted polymers (MIPs), high-capacity sorbent extraction (HCSE), and needle-trap devices (NTD), are outlined. Additionally, novel forms of sorbent-based extraction methods such as thin-film solid-phase microextraction (TF-SPME) are presented. The utility and challenges related to these techniques are discussed in this review. Finally, the directions and need for future studies are addressed.
Preventing Road Accidents Through Early Detection of Driver Behavior Using Smartphone Motion Sensor Data: An Ensemble Feature Engineering Approach

Driver behavior refers to the actions and attitudes of individuals behind the wheel of a vehicle. Poor driving behavior can have serious consequences, including accidents, injuries, and fatalities. One of the main disadvantages of poor driving behavior is the increased risk of road accidents, higher insurance premiums, fines, and even criminal charges. The primary aim of our study is to detect driver behavior early with high-performance scores. The publicly available smartphone motion sensor data is utilized to conduct our study experiments. A novel LR-RFC (Logistic Regression Random Forest Classifier) method is proposed for feature engineering. The proposed LR-RFC method combines the logistic regression and random forest classifier for feature engineering from the motion sensor data. The original smartphone motion sensor data is input into the LR-RFC method, generating new probabilistic features. The newly extracted probabilistic features are then input to the applied machine learning methods for predicting driver behavior. The study results show that the proposed LR-RFC approach achieves the highest performance score. Extensive study experiments demonstrate that the random forest achieved the highest performance score of 99% using the proposed LR-RFC method. The performance is validated using k-fold cross-validation and hyperparameter optimization. Our novel proposed study has the potential to revolutionize the early detection of driver behavior to avoid road accidents.
Existence and decay property of ground state solutions for Hamiltonian elliptic system

In this paper we study the following nonlinear Hamiltonian elliptic system with gradient term \begin{document}$ \begin{eqnarray*} \left\{ \begin{array}{ll} -\Delta u +\vec{b}(x)\cdot \nabla u +u+V(x)v = f(x, |z|)v, \; \; x\in\mathbb{R}^{N}, \\ -\Delta v -\vec{b}(x)\cdot \nabla v +v+V(x)u = f(x, |z|)u, \; \; x\in\mathbb{R}^{N}, \ \end{array} \right. \end{eqnarray*} $\end{document} where \begin{document}$ z = (u, v)\in\mathbb{R}^{2} $\end{document} . Under some suitable conditions on the potential and nonlinearity, we obtain the existence of ground state solutions in periodic case and asymptotically periodic case via variational methods, respectively. Moreover, we also explore some properties of these ground state solutions, such as compactness of set of ground state solutions and exponential decay of ground state solutions.
comparison of adherence and persistence among multiple sclerosis patients treated with disease-modifying therapies: a retrospective administrative claims analysis

Purpose: To compare adherence and persistence among patients with multiple sclerosis (MS) initiated on disease-modifying therapy (DMTs), including intramuscular (IM) interferon beta-1a (IFN β -1a), subcutaneous (SC) IFN β -1a, IFN β -1b, or glatiramer acetate (GA). Methods: MS patients initiated on IM-IFN β -1a, SC-IFN β -1a, IFN β -1b, or GA between January 1, 2000 and January 2, 2008 were identified from a retrospective claims database study associated with a large US health plan. The date of DMT initiation was the index date; patients were observed for 6 months before and 12–36 months after the index date. Adherence to the index DMT was measured with a medication possession ratio (MPR), the proportion of days patients possessed their index DMTs; MPR $ 0.80 was considered adherent. Persistence was time in days from index date until the earlier of a minimum 60-day gap in DMT therapy or the last DMT claim during follow-up. Adherence and persistence were modeled with logistic and Cox proportional hazard regressions, respectively. Results: The study population comprised 6,680 patients in the DMT cohorts: IM-IFN β -1a (N = 2,305, 34.5%); IFN β -1b (N = 894, 13.4%); GA (N = 2,270, 34.0%); and SC-IFN β -1a (N = 1,211, 18.1%). The IM-IFN β -1a cohort had significantly higher regression-adjusted odds of adherence relative to the other cohorts: 52.4% higher odds versus the IFN β -1b cohort (OR = 0.656, CI = 0.561–0.768); 33.5% higher odds versus the GA cohort (OR = 0.749, CI = 0.665–0.844); and 20.6% higher odds versus the SC-IFN β -1a cohort (OR = 0.829, CI = 0.719–0.957). There were no consistent differences in persistence between the cohorts. Conclusion: IM-IFN β -1a patients had significantly higher odds of adherence compared with other DMT cohorts, possibly attributable to IM-IFN β -1a’s less frequent dosing schedule. The benefits of adherence may include better quality of life, lower risk of relapse, and fewer hospitalizations and emergency visits, making adherence a critical component of MS management.
Frontline therapy with rituximab added to the combination of cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) significantly improves the outcome for patients with advanced-stage follicular lymphoma compared with therapy with CHOP alone: results of a prospective randomized study of t

Phase 2 studies suggest that the monoclonal antibody rituximab may improve the prognosis of patients with follicular lymphoma (FL) when it is added to chemotherapy. In the current study, 428 patients with untreated, advanced-stage FL were randomly assigned for therapy with cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) alone (n = 205) or CHOP combined with rituximab (R-CHOP) (n = 223). R-CHOP reduced the relative risk for treatment failure by 60% and significantly prolonged the time to treatment failure (P < .001). In addition, a significantly higher overall response rate (96% vs 90%; P = .011) and a prolonged duration of remission (P = .001) were achieved. In spite of a relatively short observation time, these beneficial effects even translated to superior overall survival (P = .016), with 6 deaths in the R-CHOP group compared with 17 deaths in the CHOP group within the first 3 years. The predominant treatment-related adverse effect was myelosuppression. Severe granulocytopenia was more frequently observed after R-CHOP (63% vs 53%; P = .01). However, severe infections were rare and of similar frequency after R-CHOP and CHOP (5% and 7%). Hence, adding rituximab to CHOP significantly improves the outcome for patients with previously untreated advanced-stage FL and does not induce major adverse effects.
Cost and Productivity of Tethered Cut-to-Length Systems in a Dry-Forest Fuel-Reduction Treatment: A Case Study

Fuel-reduction treatments on steep slopes across federal forests of the western United States have been limited by the high costs associated with cable logging on steeper slopes combined with poor market prospects for small-diameter material (Bolding 2003, Rummer 2008, Han et al. 2016). The emergence of tethered cut-to-length harvesting systems and small wood markets (e.g., biochar) could decrease costs and increase revenue generated from treatments. Over the course of 3 weeks, we observed both tethered (steeper slopes) and untethered cut-to-length fuel-reduction treatment on the Fremont-Winema National Forest in south-central Oregon and interviewed operators. We used those data to derive and contrast hourly costs and productivity for the harvester and forwarder. This was the first time a tethered harvester and forwarder were used in a fuel-reduction treatment on federal forests in this region. We developed and tested a variety of work time model forms for each machine. The mean utilization rate for the harvester was 64 percent on 17 tethered consolidated corridors but 87 percent on 28 untethered consolidated corridors. Similarly, the forwarder had a mean utilization rate of 76 percent on 30 tethered trips and 89 percent on 114 untethered trips. This reduced utilization rate could be because of the direct effects of tethering, the increased complexities of operations associated with steeper slopes, and the stand characteristics (e.g., lower stand density and tree sweep) associated with steeper slopes. Costs during tethered operations were higher than during nontethered operations, but lower than previous reports using cable logging.