Miracle-dz/UniFAR-FTUs huggingface dataset:
Neoadjuvant concurrent radiochemotherapy in locally advanced (IIIA-IIIB) non-small-cell lung cancer: long-term results according to downstaging.

BACKGROUND To report the efficacy of induction treatment (IT) protocol with concurrent radiochemotherapy in locally advanced non-small-cell lung cancer (NSCLC), and to analyze downstaging as a surrogate end point. PATIENTS AND METHODS Patients with histo- or cytologically confirmed stage IIIA or IIIB NSCLC were treated according to an IT protocol followed by surgery. Downstaging was assessed for all resected patients. RESULTS In the period between February 1992 and July 2000, 92 patients were enrolled in the study (57 IIIA, 35 IIIB). Response was observed in 63 patients; 56 patients underwent radical resection. Patients downstaged to stage 0-I (DS 0-I) showed a statistically significant improved disease-free survival (26.2 months pStage 0-I versus 11.2 months pStage II-III; P=0.0116) and overall survival (median 32.5 months pStage 0-I versus 18.3 months pStage II-III; P=0.025). Patients with DS 0-I had a significantly lower probability (P=0.0353) of developing distant metastases estimated in 0.2963 odds ratio. CONCLUSION Neoadjuvant radiochemotherapy is feasible with good pathological DS results. Pathological downstaging was confirmed to have high predictive value. Its use is suggested in the short-term evaluation of induction protocols efficacy in locally advanced NSCLC.
The Structure Properties of Carbon Materials Formed in 2,4,6-Triamino-1,3,5-Trinitrobenzene Detonation: A Theoretical Insight for Nucleation of Diamond-like Carbon

The structure and properties of nano-carbon materials formed in explosives detonation are always a challenge, not only for the designing and manufacturing of these materials but also for clearly understanding the detonation performance of explosives. Herein, we study the dynamic evolution process of condensed-phase carbon involved in 2,4,6-Triamino-1,3,5-trinitrobenzene (TATB) detonation using the quantum-based molecular dynamics method. Various carbon structures such as, graphene-like, diamond-like, and “diaphite”, are obtained under different pressures. The transition from a C sp2- to a sp3-hybrid, driven by the conversion of a hexatomic to a non-hexatomic ring, is detected under high pressure. A tightly bound nucleation mechanism for diamond-like carbon dominated by a graphene-like carbon layer is uncovered. The graphene-like layer is readily constructed at the early stage, which would connect with surrounding carbon atoms or fragments to form the tetrahedral structure, with a high fraction of sp3-hybridized carbon. After that, the deformed carbon layers further coalesce with each other by bonding between carbon atoms within the five-member ring, to form the diamond-like nucleus. The complex “diaphite” configuration is detected during the diamond-like carbon nucleation, which illustrates that the nucleation and growth of detonation nano-diamond would accompany the intergrowth of graphene-like layers.
Automating kidney transplant rejection diagnosis: a simple solution for a complex problem?

Yoo and colleagues developed the ‘Banff automation system’, an automated application of the Banff Classification rules for Kidney Allograft Pathology that uses simple logical operations to reach one or several diagnoses [ 1 ]. User input consists of histological information ( Banff lesion scores and concomitant diagnoses ) , serology ( presence of donor-specific antibodies ) and molecular data ( if available ) . The tool aims to avoid misclassifi-cations due to misinterpretation or errors, and provides not only the final diagnosi ( e ) s, but also a visualized decision tree illustrating the steps of the Banff rules used to reach it/them. Performance of the tool is assessed by comparing the automated diagnosis to the pathologist’s diagnosis, and by comparing their prognostic performance. This automated diagnosis enables an objective Banff diagnosis for clinical use, and is potentially relevant for determining endpoints in future studies. An important output of this study is how the painstaking analysis of discrepancies between pathologist and automated diagnoses reveals potential problems in how we diagnose rejection. Indeed, the tool demonstrates how convoluted the Banff Classification has become since its inception 30 years ago, and how easily it can be misunderstood [ 2 ]. Frequent changes
Employment leave for early pregnancy endings: A biopolitical reproductive governance analysis in England and Wales

When a pregnancy ends in England and Wales, statutory time away from paid employment is limited to circumstances where there is a live birth or stillbirth. Forms of leave, such as Maternity Leave or Paternity Leave, depend on parental status derived from the civil registration of a new person or a post‐viability stillbirth. Other early pregnancy endings, such as miscarriage or abortion, do not provide specific time off work after pregnancy. This paper uses the concept of reproductive governance to analyze current and shifting biopolitical truth discourses, strategies of intervention, and modes of subjectification around post‐pregnancy leaves. It shows how different inclusions and exclusions are generated by the classificatory boundaries which act as political technologies in this field. Contributing to an area that is under‐researched in the literature, we provide a review of post‐pregnancy statutory employment leave entitlements in this context. We then consider proposals for change presented in the United Kingdom political system in relation to more inclusive leave benefits offered by some employers and different pregnancy ending leaves offered in other jurisdictions. We argue that current arrangements and proposals do not adequately reflect the complexity and diversity of pregnancy endings. We conclude with a call to policymakers in all contexts to carefully assess the consequences of new ideas around leaves for pregnancy endings and to formulate inclusive and fair proposals for change.
Segmental Membranous Glomerulopathy in Adults

Introduction: The clinicopathological features of segmental membranous glomerulopathy (SMGN) have not been well characterized. The aim of this study was to investigate the prevalence and clinicopathological features of SMGN in adults. Methods: Adult patients with biopsy-confirmed SMGN in the native kidney at our center between January 2017 to September 2020 were identified. The clinicopathological features of SMGN were collected. The glomerular deposition of IgG subclasses, M-type phospholipase A2 receptor 1 (PLA2R), thrombospondin type 1 domain-containing 7A (THSD7A), and neural epidermal growth factor-like 1 protein (NELL1) were tested. Clinical and pathologic features were comparable between NELL1-positive and NELL1-negative SMGN. Results: A total of 167 patients with biopsy-proven SMGN were enrolled. During the same period, 32,640 (33.0%) out of 98,939 renal biopsies were diagnosed with membranous nephropathy (MN) in adults. SMGN accounted for 0.17% of total kidney biopsies and 0.51% of MN in adults. One hundred and fifty (89.8%) cases were isolated SMGN, and 17 (10.2%) cases were complicated with other kidney disease. Clinically, the median age of isolated SMGN patients was 41.5 years, with female (74%) predominance, and 33.1% had full nephrotic syndrome. Pathologically, IgG1 was the dominant subclass (92.5%), followed by IgG4 (45.0%). PLA2R and THSD7A staining were done in 142 and 136 isolated SMGN cases, respectively, in which, all the cases showed negative. NELL1 staining was done in 135 isolated SMGN cases; 58 cases (43.0%) showed positive. Fifty-eight patients (41.1%) had diffuse (≥90%) foot process effacement, and 119 patients (83.8%) had either stage I (38.0%) or stage II (45.8%) membranous alterations in patients with SMGN. Most patients with NELL1-positive SMGN were female. Patients with NELL1-positive SMGN were more likely with lower prevalence of full nephrotic syndrome than NELL1-negative SMGN. Conclusions: SMGN is a relatively rare pathological type. Majority of patients with isolated SMGN were female, with a median age of 41.5 years, 33.1% had full nephrotic syndrome, absence of PLA2R and THSD7A, 43.0% with NELL1-positive, and mainly stage I or II MN (83.8%). NELL1 is the major target antigen of SMGN in adults.
Structural Design and Simulation of a Multi-Channel and Dual Working Condition Wafer Defect Inspection Prototype

Detecting and classifying defects on unpatterned wafers is a key part of wafer front-end inspection. Defect inspection schemes vary depending on the type and location of the defects. In this paper, the structure of the prototype is designed to meet the requirements of wafer surface and edge defect inspection. This prototype has four inspection channels: scattering, reflection, phase, and contour, with two working conditions: surface and edge inspection. The key structure of the prototype was simulated using Ansys. The simulation results show that the maximum deformation of the optical detection subsystem is 19.5 μm and the fundamental frequency of the prototype is 96.9 Hz; thus, these results meet the requirements of optical performance stability and structural design. The experimental results show that the prototype meets the requirements of the inspection sensitivity better than 200 nm equivalent PSL spherical defects.
Lacunes are associated with late-stage multiple sclerosis comorbidities

Multiple sclerosis (MS) is a condition that affects the veins and small blood vessels. Previous research suggests that individuals with MS have an increased risk of vascular events and higher mortality rates. However, the relationship between MS and cerebral small vessel disease (CSVD) remains uncertain. This study aims to investigate the association between MS and lacunes. A prospective observational study was conducted, including a total of 112 participants, of which 46 had MS and 66 had CSVD. All participants underwent an MRI scan and a battery of neurological functional assessments. The presence of definite lacunes and black holes was determined through the analysis of T2-weighted, T1-weighted, and FLAIR images. The occurrence of lacunes in MS patients was found to be 19.6%. Notably, the duration of MS was identified as the sole risk factor for the development of lacune lesions in MS patients [odds ratio (OR) = 1.3, 95% confidence interval (CI) = 1.1–1.6, p = 0.008]. Comparatively, MS patients with lacunes exhibited a higher frequency of attacks and larger volumes of T2 lesions compared to MS patients without lacunes. Further analysis using receiver operating characteristic (ROC) curves showed that lacune lesions had limited ability to discriminate between MS and CSVD when disease duration exceeded 6 years. The presence of small arterial lesions in the brain of individuals with MS, along with the duration of the disease, contributes to the development of lacunes in MS patients.
The Application of Biometric Approaches in Agri-Food Marketing: A Systematic Literature Review

A challenge in social marketing studies is the cognitive biases in consumers’ conscious and self-reported responses. To help address this concern, biometric techniques have been developed to obtain data from consumers’ implicit and non-verbal responses. A systematic literature review was conducted to explore biometric applications’ role in agri-food marketing to provide an integrated overview of this topic. A total of 55 original research articles and four review articles were identified, classified, and reviewed. It was found that there is a steady growth in the number of studies applying biometric approaches, with eye-tracking being the dominant method used to investigate consumers’ perceptions in the last decade. Most of the studies reviewed were conducted in Europe or the USA. Other biometric techniques used included facial expressions, heart rate, body temperature, and skin conductance. A wide range of scenarios concerning consumers’ purchase and consumption behaviour for agri-food products have been investigated using biometric-based techniques, indicating their broad applicability. Our findings suggest that biometric techniques are expanding for researchers in agri-food marketing, benefiting both academia and industry.
Reducing Foster Care Entry Rates for Children in Sacramento County: A Spotlight on Practice

Abstract Beginning in 2006, Sacramento County implemented multiple child welfare practices and policies to reduce high rates of foster care entries (e.g., early intervention family drug courts, differential response, team decision-making, a family-centered approach to safety and risk assessment). Those strategies were identified through interviews with County child welfare leaders; and then the strategies were placed chronically in a table to inform a longitudinal data analysis. Between 2000 and 2020, entry rates in Sacramento County declined at a faster rate than entry rates in California (when all state counties but Sacramento were combined), and by 2020 were statistically significantly lower than entry rates in California. Between 2000 and 2020, recurrence of maltreatment rates for children in Sacramento County were higher than California; however, those declined more rapidly than recurrence rates in California and were similar by 2020. Both foster care entry and child maltreatment recurrence rates for children in Sacramento County declined between 2000 and 2020, indicating that foster care entry rates were safely reduced but additional data about child safety and well-being are needed. In addition, although Black children less than one year old continue to enter care at higher rates within Sacramento County, their entry rates declined more rapidly than other ethnic and age groups. This suggests that Sacramento’s focus on the youngest children, with multiple services specially designed for Black children and families, may be contributing to these positive trends. Future studies should examine the individual impact of the multiple interventions and programs implemented in Sacramento County on the rates of entry into foster care. Further investigations could also help unpack the racial/ethnic group and age differences seen in Sacramento County foster care entry rates and inform the timing of future practice improvements.
Modeling and assessment of the energy state of the technological system of mechanical processing when creating digital twins

An approach to the construction of digital twins of the technological system for turning low rigidity parts and the assessment of the energy state of the technological system is proposed in this article. The creating of the digital twin models by differential equations allows to excide a time-consuming procedure for training neural networks. The results obtained are transmitted to the energy state assessment block. Calculations are performed to determine the power consumption between the moving parts of the machine and the cutting process. To determine the energy, we use the Hamilton equations. The developed modeling technique and the results of computational experiments will provide an operational and resource-saving mode of production in the machining process.
Torque Ripple Suppression Strategy for Open-Winding PMSM With Zero-Sequence Loop Model-Free Control

To suppress the torque ripple caused by zero-sequence loop (ZSL) in open-winding permanent magnet synchronous motors, a <inline-formula> <tex-math notation="LaTeX">${q}$ </tex-math></inline-formula>-axis current injection strategy has been proposed. However, in this method, the torque ripple cannot be effectively suppressed and will even be augmented when the third flux linkage mismatch occurs. First, an extended state observer (ESO) based on the ultralocal model is established in this article to address the problem. In ESO, the future zero sequence current (ZSC) and ZSL back-electromotive force (EMF) can be estimated under complex conditions; then the injected <inline-formula> <tex-math notation="LaTeX">${q}$ </tex-math></inline-formula>-axis current can be calculated, which addresses the problem of one-step delay and aforementioned disturbance caused by third flux linkage mismatch. Second, the desired zero-sequence voltage (ZSV) can be calculated by ESO. Then zero voltage duration ratios are adjusted in space vector pulsewidth modulation to obtain the desired ZSV to suppress ZSC. Finally, comparative simulation and experimental results have been shown to prove the effectiveness of the proposed control method.
Estimation of suspended sediment concentration in the Saint John River using rating curves and a machine learning approach

ABSTRACT Sedimentation in navigable waterways and harbours is of concern for many water and port managers. One potential source of variability in sedimentation is the annual sediment load of the river that empties in the harbour. The main objective of this study was to use some of the regularly monitored hydro-meteorological variables to compare estimates of hourly suspended sediment concentration in the Saint John River using a sediment rating curve and a model tree (M5ʹ) with different combinations of predictors. Estimated suspended sediment concentrations were multiplied by measured flows to estimate suspended sediment loads. Best results were obtained using M5ʹ with four predictors, returning an R2 of 0.72 on calibration data and an R2 of 0.46 on validation data. Total load was underestimated by 1.41% for the calibration period and overestimated by 2.38% for the validation period. Overall, the model tree approach is suggested for its relative ease of implementation and constant performance. EDITOR M.C. Acreman; ASSOCIATE EDITOR B. Touaibia
Valuación de Títulos de Deuda Indexados al Comportamiento de un Índice Accionario: Un Modelo con Riesgo de Crédito

The aim of this paper is to approach the valuation of a particular type of structured products, which consist of zero-coupon debt securities, whose payment function is tied to the behavior of another variable. In the present case of study this variable is a stock index. The contribution is formed by the proposition of a formula or closed formed solution, under standards in derivative financial valuation of instruments and the existence of credit risk.
Goat Production, Supply Chains, Challenges, and Opportunities for Development in Vietnam: A Review

Simple Summary Over the last decade, the total goat population in Vietnam increased more than two-fold, from 1.29 million to 2.65 million heads. In spite of a transformation from extensive grazing to cut-and-carry intensive systems, more than three-fourths of goats in Vietnam are raised by small-scale producers. The demands for goat meat and milk are significantly increasing, leading to pressure for imports. Goat marketing primarily takes place through informal channels and is dominated by small-scale producers and traders. The formal goat market is poorly developed. The marketing research and statistical data on the goat value chain are scarce. This situation has led to an inconsistency in livestock supply and quality and, as a result, unstable pricing. Information and documentation regarding both horizontal and vertical linkages in the supply chain remain limited. Despite receiving strong support from the government and experiencing high demand, goat production and marketing systems have yet to achieve their full potential. This review overviews the current status of goat production and supply chains in Vietnam. It also identifies the main challenges and opportunities of, and provides suggestions through which improve, the nation’s goat production and marketing. Abstract The current situation of goat production and supply chains in Vietnam, along with its difficulties and possibilities, is presented in this review paper. The data and reports of government agencies, scientific journals, and websites were analysed in order to determine the prevailing situation in goat production and marketing. Goats are mainly raised on small-scale farms (73.4% of the total goat population). Goat production is transforming from extensive grazing to cut-and-carry intensive systems. Goat meat and milk supplies have not fully met domestic demand. However, the scale of the domestic market is difficult to ascertain, due to the lack of market research and statistics. Goat marketing is mostly informal and overwhelmingly conducted by small-scale producers and traders, although there are numerous governmental agencies at both the national and local levels regulating formal marketing. The major challenges facing the goat industry are feed shortage; supply inconsistency; limited market infrastructure and research; a lack of sustainable breeding programmes, price incentives, and processing facilities; and competition from foreign suppliers. However, there are opportunities to expand and develop the industry, such as consumers’ health consciousness, increasing demand, high-value adding, and strong government support.
Outlining guidelines for the application of the MF-DCCA in financial time series: non-stationary vs stationary

This paper disrupts mistaken applications of multifractal approaches in financial time series. Specifically, we have examined the non-linear cross-correlation between the São Paulo time series of the weekly price of ethanol and the other 14 Brazilian capitals’ time series of the weekly price of the same biofuel using the Multifractal Detrended Cross-Correlation Analysis (MF-DCCA). Given the statistical peculiars of stationary and non-stationary financial time series, we suggest two possibilities for employing multifractal approaches to these time series. Our findings shed light and promote alignment between basic time series analysis techniques and multifractal dynamics. Also, we discover that the use of MF-DCCA is highly impacted by choice of time series (stationary or non-stationary).
Machine learning decision tree models for multiclass classification of common malignant brain tumors using perfusion and spectroscopy MRI data

Background To investigate the contribution of machine learning decision tree models applied to perfusion and spectroscopy MRI for multiclass classification of lymphomas, glioblastomas, and metastases, and then to bring out the underlying key pathophysiological processes involved in the hierarchization of the decision-making algorithms of the models Methods From 2013 to 2020, 180 consecutive patients with histopathologically proved lymphomas (n = 77), glioblastomas (n = 45), and metastases (n = 58) were included in machine learning analysis after undergoing MRI. The perfusion parameters (rCBVmax, PSRmax) and spectroscopic concentration ratios (lac/Cr, Cho/NAA, Cho/Cr, and lip/Cr) were applied to construct Classification and Regression Tree (CART) models for multiclass classification of these brain tumors. A 5-fold random cross validation was performed on the dataset. Results The decision tree model thus constructed successfully classified all 3 tumor types with a performance (AUC) of 0.98 for PCNSLs, 0.98 for GBM and 1.00 for METs. The model accuracy was 0.96 with a RSquare of 0.887. Five rules of classifier combinations were extracted with a predicted probability from 0.907 to 0.989 for that end nodes of the decision tree for tumor multiclass classification. In hierarchical order of importance, the root node (Cho/NAA) in the decision tree algorithm was primarily based on the proliferative, infiltrative, and neuronal destructive characteristics of the tumor, the internal node (PSRmax), on tumor tissue capillary permeability characteristics, and the end node (Lac/Cr or Cho/Cr), on tumor energy glycolytic (Warburg effect), or on membrane lipid tumor metabolism. Conclusion Our study shows potential implementation of machine learning decision tree model algorithms based on a hierarchical, convenient, and personalized use of perfusion and spectroscopy MRI data for multiclass classification of these brain tumors.