Miracle-dz/UniFAR-FTUs huggingface dataset:
What’s beyond BRCA Mutational Status in High Grade Serous Ovarian Cancer? The Impact of Hormone Receptor Expression in a Large BRCA-Profiled Ovarian Cancer Patient Series: A Retrospective Cohort Study

Simple Summary Ovarian hormones are involved in ovarian cancer pathogenesis. However, few reports have investigated the hormone receptor pattern according to BRCA mutational status. The aim of this single-center, observational, retrospective study was to explore the relationship between hormone receptor status and BRCA1/2 mutation in a cohort of 207 high-grade serous ovarian carcinoma (HGSOC) patients. Interesting differences emerged between BRCA-mutated and BRCA wild-type women, in terms of pattern of receptor expression and its association to the outcome. On the whole, our findings, though needing further validation, extend our understanding of the complex interplay between BRCA1/2 protein and hormone signaling, suggesting new pathways to be exploited in order to develop future personalized therapy. Abstract Several studies have explored the prognostic role of hormone receptor status in high-grade serous ovarian cancer (HGSOC) patients. However, few reports have investigated their expression according to BRCA mutational status. The aim of this single-center, observational, retrospective study was to explore the hormone receptor pattern and its potential prognostic role in a cohort of 207 HGSOC women stratified for BRCA mutational status. To this end, ERα, ERβ1, ERβ2, ERβ5, PR, and AR expression were assessed by immunohistochemistry in 135 BRCA-wild type (BRCA-wt) and 72 BRCA1/2 mutation carriers (BRCA-mut). No significant difference emerged in hormone receptor expression between the two sub-samples, except for a significantly lower ERα expression observed in pre-menopausal BRCA1/2-mut as compared to BRCA-wt patients (p = 0.02). None of the examined hormone receptors has revealed a significant prognostic role in the whole sample, apart from the ratio ERα/ERβ5 nuclear, for which higher values disclosed a positive role on the outcome in BRCA-wt subgroup (HR 0.77; CI 0.61–0.96; p = 0.019). Conversely, it negatively affected overall survival in the presence of BRCA1/2-mut (HR 1.41; CI 1.06–1.87; p = 0.020). Finally, higher PR levels were associated with platinum sensitivity in the whole sample (p = 0.019). Our data, though needing further validation, suggest a potential role of oestrogen-mediated pathways in BRCA1/2-associated HGSOC tumorigenesis, thus revealing a possible therapeutic potential for targeting this interaction.
Multiplexed label-free detection of single proteins

We report multiplexed spectral imaging of plasmon resonance shifts in a simple setup, capable of resolving single protein binding events with a high signal to noise ratio of up to 10 for single Fibronectin (450 kDa) proteins. We directly record 2-dimensional, spectrally dispersed images of multiple gold nanorods. The spectra are corrected via an overlapped particle image that correlates arbitrary particle positions to the reference slit position, allowing us to use the full 2D space of the sensor. Together with the simple experimental implementation, our approach paves the way towards routine and efficient label-free detection down to the single molecule level.
Extension of SoS sampling kernels for 2D FRI problems

The problem of sampling a 2D Poisson process is considered. Recently, such problems have been denoted as sampling of signals with finite rate of innovation. Therefore, a well-known sampling approach for the 1D approach is extended to the 2D case and the theoretic sampling bounds as well as the reconstruction approach are shown. By providing results from numerical simulations it can be demonstrated that reconstruction is exact up to numerical precision.
Robust Value at Risk Prediction: Appendix

This appendix extends simulation and empirical results reported in Mancini and Trojani (2010). It discusses the choice of the robustness tuning constants; describes the unconditional, independence and conditional coverage tests for VaR forecast evaluation; provides additional Monte Carlo simulation results on GARCH model estimation and VaR prediction; extends the empirical analysis on backtesting. Notation is the same as in Mancini and Trojani (2010).
Nitrated Fatty-Acids Distribution in Storage Biomolecules during Arabidopsis thaliana Development

The non-enzymatic interaction of polyunsaturated fatty acids with nitric oxide (NO) and derived species results in the formation of nitrated fatty acids (NO2-FAs). These signaling molecules can release NO, reversibly esterify with complex lipids, and modulate protein function through the post-translational modification called nitroalkylation. To date, NO2-FAs act as signaling molecules during plant development in plant systems and are involved in defense responses against abiotic stress conditions. In this work, the previously unknown storage biomolecules of NO2-FAs in Arabidopsis thaliana were identified. In addition, the distribution of NO2-FAs in storage biomolecules during plant development was determined, with phytosterol esters (SE) and TAGs being reservoir biomolecules in seeds, which were replaced by phospholipids and proteins in the vegetative, generative, and senescence stages. The detected esterified NO2-FAs were nitro-linolenic acid (NO2-Ln), nitro-oleic acid (NO2-OA), and nitro-linoleic acid (NO2-LA). The last two were detected for the first time in Arabidopsis. The levels of the three NO2-FAs that were esterified in both lipid and protein storage biomolecules showed a decreasing pattern throughout Arabidopsis development. Esterification of NO2-FAs in phospholipids and proteins highlights their involvement in both biomembrane dynamics and signaling processes, respectively, during Arabidopsis plant development.
Data-Driven Pick-Up Location Recommendation for Ride-Hailing Services

Ride-hailing service (RHS) has become an important transportation mode in our daily life. Although many works have been proposed to improve RHS from different aspects, only few works focus on the selections of pick-up locations, where rider and driver meet and start a trip. In this paper, we present MPLRec, a data-driven pick-up location recommendation system that exploits riders’ specific mobility demands, e.g., destination, and historical experiences to meet riders’ travel requirements. MPLRec generates potential pick-up locations over the road network and characterizes them with rich features that describe a location from the riders’ perspective. We also build spatio-temporal indexes to organize potential pick-up locations and historical data for facilitating online recommending. When processing an online recommendation request, MPLRec derives candidate pick-up locations and investigates them with materialized features, which are computed from historical order and trajectory data while considering rider's mobility demands. Based on these features, a novel scoring function is used to derive the best pick-up location for each request. Moreover, we implement an RHS simulator to evaluate MPLRec using large-scale practical ride-hailing datasets. Extensive experiments and simulations demonstrate the effectiveness and efficiency of MPLRec, which can complete each request within 0.5 s and largely reduce the ride-hailing costs when compared to baseline methods.
Electrochemical sensor based on green-synthesized iron oxide nanomaterial modified carbon paste electrode for Congo red electroanalysis and capacitance performance

ABSTRACT In this study, a facile protocol was used to convert non-valuable orange peels (OP) waste into a new sensing iron oxide orange-peel nanomaterial (FeOP). The presence of iron oxide nanoparticles in the modified OP was confirmed by physicochemical characterisations including Fourier-transform infrared spectroscopy, X-ray diffractometry, thermogravimetry, and scanning electron microscopy-energy dispersive X-ray. FeOP was used to modify a carbon paste electrode (CPE/FeOP) which displayed a significant increase in specific capacitance of 2939 F.g−1, two folds higher than that obtained with CPE at 10 m.s−1 in NaCl. The electroanalysis of Congo red (CR) in aqueous solutions using CPE/FeOP displayed detection limits of 2.8 × 10−7 mol.L−1 and 8.2 × 10−7 mol.L−1 respectively in deionised and spring waters, in the linear range of 5 to 55 µM. CPE/FeOP electrochemical sensor is therefore suitable for the determination of Congo red in wastewater.
Remanence deviations in permanent magnet synchronous machines evaluated using a model order reduction approach

In this article remanence deviations of a permanent magnet synchronous machine are studied with the proper orthogonal decomposition (POD). The design of experiments enables to create designs with a reduced sample size compared to full factorial designs without decreasing the stochastic significance of the remanence distributions. Next, a POD basis is created with the belonging design, that is distinctly smaller than the reference. From the POD basis the projection matrix is built to compute the flux density solutions. The machine's output is then analyzed regarding accuracy originating from numerical errors. Different parameters are evaluated and compared to the reference to appraise the accuracy of the flux density solutions, which includes the POD basis size, rotor angle step size and dimension of the reduced system. Results show, that the most influence has the dimension of the reduced system. Depending on the dimension and other parameters about one quarter of computational effort can be conserved without a significant loss in accuracy.
Progressive Attention-Based Feature Recovery With Scribble Supervision for Saliency Detection in Optical Remote Sensing Image

Salient object detection (SOD) task for optical remote sensing images (RSIs) plays an important role in many remote sensing applications. Most of the existing methods train their networks depending on a large amount of pixel-wise datasets. However, such expensive and time-consuming training setting prevents the approaches becoming flexible and scalable solutions. To this end, we explore efficient SOD for optical RSIs based on easily accessible weak supervision source. In this work, we propose a novel end-to-end progressive attention-based feature recovery framework with scribble supervision. Specifically, to better locate challenging salient objects in optical RSIs, an object position module (OPM) is proposed to capture and enhance the long-range semantic dependence of objects’ position information, which depends on the complementary attention mechanism. Also, to restore the entire salient objects, a context refinement module (CRM) is proposed, which extract local contextual information for better propagating high-level semantics to low-level details. Moreover, to improve the adaptability of the network to the changing scenarios of optical RSIs, we propose a salient region correcting (SRC) mechanism to help the predicted salient regions rectify their saliency values by constraining the saliency relationship between predictions from different augmentation models. In addition, due to the lack of dataset for weakly supervised SOD for optical RSIs, we relabeled an existing large-scale optical RSIs dataset with scribbles, namely, EORSSD-S. Experimental results on benchmark datasets demonstrate that the proposed method can outperform other weakly supervised SOD methods. Also, the proposed method even outperformed some fully supervised methods. https://github.com/melonless/PAFR.
Performance analysis of the speed sensorless induction motor drive with magnetizing reactance estimator

In this paper the sensorless induction motor drive performance with current-based MRAS speed and rotor flux estimator are tested in the wide speed range operation. This system has been equipped with additional estimator of the magnetizing reactance reconstruction. Methodology is based on the well known mathematical interpolation of the inverse magnetizing curve. Dynamical performances of the vector control system with such this current-type MRAS estimator with magnetizing reactance on-line adaptation are tested in simulation and experiments.
Basal Reactivity Evaluated by Infrared Thermography in the “Caballo de Deporte Español” Horse Breed According to Its Coat Color

Simple Summary The importance of the coat color in horses has been present since their domestication. The interactive effect of coat color-determinant genes on other traits, such as behavior, makes it a factor of importance in horse selection, as it determines the way the horse perceives and reacts to its environment. Eye temperature at rest (ETR) assessed with infrared thermography was used as a suitable non-invasive tool to assess basal reactivity. The aim of this study was to evaluate the influence of coat color on basal reactivity assessed with infrared thermography, determine their relationship with the results obtained in show jumping competitions, and to estimate the genetic parameters for ETR to test its suitability for genetic selection. Our results indicated differences in ETR due to six different factors. We also discovered a positive correlation with ranking in show jumping, indicating that less reactive horses were more likely to achieve better rankings. The genetic results indicated that part of the variability present in the basal reactivity due to coat color has an environmental origin. The heritability values indicate that ETR has a suitable genetic basis to be used in the breeding program to select for basal reactivity due to coat color. Abstract Horses have been valued for their diversity of coat color since prehistoric times. In particular, the pleiotropic effect that coat color genes have on behavior determines the way the horse perceives and reacts to its environment. The primary aim of this study was to evaluate the influence of coat color on basal reactivity assessed with infrared thermography as eye temperature at rest (ETR), determine their relation with the results obtained by these horses in Show Jumping competitions and to estimate the genetic parameters for this variable to test its suitability for genetic selection. A General Linear Model (GLM) and Duncan post-hoc analysis indicated differences in ETR due to coat color, sex, age, location, and breed-group factors. A Spearman’s rank correlation of 0.11 (p < 0.05) was found with ranking, indicating that less reactive horses were more likely to achieve better rankings. Heritability values ranged from 0.17 to 0.22 and were computed with a model with genetic groups and a model with residual variance heterogeneity. Breeding values were higher with the last genetic model, thus demonstrating the pleiotropic effect of coat color. These results indicate that ETR has a suitable genetic basis to be used in the breeding program to select for basal reactivity due to coat color.
Effect of Green Tea Extract Ingestion on Fat Oxidation during Exercise in the Menstrual Cycle: A Pilot Study

In women, fat oxidation during exercise changes with the menstrual cycle. This study aimed to investigate the effect of green tea extract (GTE) ingestion on fat oxidation during exercise depending on the menstrual cycle phase. Ten women with regular menstrual cycles participated in this randomized, double-blind, crossover study. GTE or placebo was administered during the menstrual cycle’s follicular phase (FP) and luteal phase (LP). Participants cycled for 30 min at 50% maximal workload, and a respiratory gas analysis was performed. Serum estradiol, progesterone, free fatty acid, plasma noradrenaline, blood glucose, and lactate concentrations were assessed before, during, and after the exercise. Fat oxidation, carbohydrate oxidation, and the respiratory exchange ratio (RER) were calculated using respiratory gas. Fat oxidation during the exercise was significantly higher in the FP than in the LP with the placebo (p < 0.05) but did not differ between the phases with GTE. Carbohydrate oxidation, serum-free fatty acid, plasma noradrenaline, blood glucose, and lactate concentrations were not significantly different between the phases in either trial. Our results suggest that GTE ingestion improves the decrease in fat oxidation in the LP.
Overall Efficiency Improvement of a Dual Active Bridge Converter Based on Triple Phase-Shift Control

This paper proposes a control scheme based on an optimal triple phase-shift (TPS) control for dual active bridge (DAB) DC–DC converters to achieve maximum efficiency. This is performed by analyzing, quantifying, and minimizing the total power losses, including the high-frequency transformer (HFT) and primary and secondary power modules of the DAB converter. To analyze the converter, three operating zones were defined according to low, medium, and rated power. To obtain the optimal TPS variables, two optimization techniques were utilized. In local optimization (LO), the offline particle swarm optimization (PSO) method was used, resulting in numerical optimums. This method was used for the low and medium power regions. The Lagrange multiplier (LM) was used for global optimization (GO), resulting in closed-form expressions for rated power. Detailed analyses and experimental results are given to verify the effectiveness of the proposed method. Additionally, obtained results are compared with the traditional single phase-shift (SPS) method, the optimized dual phase-shift (DPS) method, and TPS method with RMS current minimization to better highlight the performance of the proposed approach.
Systematic Review and Meta-Analysis of Pleurectomy/Decortication versus Extrapleural Pneumonectomy in the Treatment of Malignant Pleural Mesothelioma

Objective: Malignant pleural mesothelioma (MPM) is a rare and aggressive malignant cancer for which there are poor treatment options. Extrapleural pneumonectomy (EPP) and pleurectomy decortication (P/D) are the two most used surgical procedures in patients with resectable disease. We reviewed the available literature in order to compare the overall survival and postoperative complications of EPP and P/D and to provide evidence for the best procedure in the treatment of MPM. Methods: We performed a systematic review of the literature, including studies from August 2018 to May 2022. The primary outcome was 5-year overall survival (OS) and the secondary outcomes were 30-day mortality, 90-day mortality and peri-operative complications. Results: Thirteen studies were considered, including a total of 1624 patients treated with EPP and 2147 treated with P/D. The estimated pooled HR showed a significant lower hazard for P/D compared to EPP in terms of OS (HR = 0.76; 95% CI from 0.62 to 0.94; p < 0.001). In 12 studies, the risk for 30-day mortality was lower for patients treated with P/D (RR = 0.49; 95% CI from 0.31 to 0.76; p = <0.01), whereas only five studies reported 90-day mortality, and no statistically significant difference between EPP and P/D was found (RR = 0.71; 95% CI from 0.47 to 1.07; p = 0.10). The OS restricted mean survival time difference meta-analysis (RMSDT) confirms the superior survival of P/D on the EPP, a superiority that increases from 0.54 months at one year to 4.23 at five years. The incidence of postoperative empyema, atrial fibrillation, bleeding and bronchopleural fistula was significantly increased in the EPP group except for prolonged air leakage, which is only characteristic of P/D. Conclusions: Using two different statistical methods, this meta-analysis suggests that long-term survival after surgical treatment for resectable MPM is greater for patients undergoing P/D. Long-term survival had never been previously analyzed with appropriate tests; on the contrary, our result is consistent with the previous meta-analyses and reinforces the evidence of lower 30-day mortality and the prevalence of postoperative complications in P/D versus EPP patients. The recent introduction of innovative therapeutic schemes, both adjuvant and neoadjuvant therapy, keeps the discussion on surgical strategy open and will require new studies.
Heat Transfer Analysis of 3D Printed Wax Injection Mold Used in Investment Casting

Investment casting is one of the precise casting methods where disposable wax patterns made in wax injection molds are used to make a casting mold. The production capacity of precision foundry is determined by the time taken for producing wax patterns, which depends on the time taken for wax solidification. Wax injection molds are usually made of aluminum or copper alloys with the use of expensive and time-consuming computer numerical control (CNC) processing, which makes low-volume production unprofitable. To reduce these costs, the authors present a heat transfer analysis of a 3D printed wax injection mold. Due to the low thermal conductivity of the photopolymer resin, the influence of different cooling channels’ shapes was investigated to improve the time of the manufacturing process. Transient thermal analysis was performed using COMSOL software based on the finite element method (FEM) and included a simulation of wax injection mold cooling with cold air (−23 °C), water, and without cooling. The analysis showed that use of cooling channels in the case of photopolymer material significantly reduces the solidification time of the sample (about 10 s shorter), and that under certain conditions, it is possible to obtain better cooling than obtained with the aluminum reference wax injection mold (after approximately 25–30 s). This approach allows to reduce the production costs of low-volume castings.
Global Reduction of Spill Code by Live Range Splitting

Date ii Abstract Current, state-of-the-art compilers use Briggs' graph coloring heuristic for register allocation. This heuristic provides an eecient mapping of program variables to machine registers. However, if a variable cannot be assigned a register the variable is spilled and referenced through memory. Each use of the variable is preceded by a load from memory and each deenition is followed by a store to memory. The algorithm presented in this thesis is a method to reduce the amount of spill code added by a Briggs' allocator. Graph coloring maps the live range of a variable to a machine register. If no machine register is available for a live range, the variable is spilled. There are often areas in the live range where spill code is not needed. Our algorithm identiies there areas, known as low register pressure regions. Once low register pressure regions are found for a spilled live range, it is possible to limit the amount of spill code added to the low register pressure region. This is known as live range splitting. This step can be done without substantially increasing compile times since we base computing low register pressure regions on Reif and Tarjan's near linear algorithm for computing symbolic covers. The research done for this thesis shows that up to 25% of dynamic loads can be reduced with an up to 20% reduction in execution time and an average 2.3% increase register allocation time. iii Acknowledgments I would like to thank the support, advice, and guidance from my co-advisors, Dr. Carr and Dr. Sweany. With their encouragement, I've followed a challenging path for which I will always be grateful. I would also like to thank the rest of my committee, Dr. Poplawski and Dr. Gilpin, for their support. I need to thank my family, especially my parents, Richard and Veronica Suchyta. Finally, I need to thank Janice, without whom this would have not been possible.