Miracle-dz/UniFAR-FTUs huggingface dataset:
Practical issues and research trends of oncofertility in gynecologic cancer

In recent years, there has been a greater impetus toward preserving fertility in young women with gynecologic cancer. This is related to the increasing incidence of gynecologic cancer in young women and to the social phenomenon in which women, on average, are getting married and having their first child at an older age. For women with early gynecologic cancer, treatment strategies can be undertaken to preserve the uterus and part of the ovaries, which can be used to preserve fertility. For women with advanced gynecologic cancer, treatment strategies using assisted reproductive technology are the main option to preserve fertility. Young women with gynecologic cancer who want to preserve fertility should be counseled thoroughly regarding treatment options that allow fertility preservation before commencing anti-cancer treatment. This article describes various methods for preserving fertility and examines recent research trends related to young women with gynecologic cancer.
The Price of Wind: An Empirical Analysis of the Relationship between Wind Energy and Electricity Price across the Residential, Commercial, and Industrial Sectors

This paper quantifies the long-term impact of wind energy development on electricity prices across the residential, commercial, and industrial sectors in the United States. Our data set is made up of state level panel data from 2000 through 2018. This time period covers the vast majority of total wind energy capacity installed in the history of the USA. Our econometric model accounts for the primary factors that influence electricity prices, incorporating both fixed effects and general method of moments in order to more precisely isolate the effect of wind energy. The empirical results conclude that wind energy is positively and significantly related to electricity prices across all sectors, as indicated by the higher average electricity prices in states with higher percentages of wind energy. The price increase is largest in the industrial sector, followed by commercial, then residential. Wind turbine technology has become significantly more efficient, but the technical gains have been offset by the increased indirect costs of incorporating wind energy into the grid. Transmission and balancing costs have increased the final price to consumers. Our results highlight the need to view wind energy development from a more holistic perspective that accounts for structural and systemic costs. This will ensure the continued growth of wind energy. These results provide relevant insight to help wind energy developers, policy makers, and utility companies build a more sustainable energy future.
Chemotherapy‐induced peripheral neuropathy increases nontraumatic fracture risk in breast cancer survivors

Chemotherapy is a common treatment for breast cancer (BrCa) and can cause chemotherapy‐induced peripheral neuropathy (CIPN). CIPN contributes to falls, and is thus a potential risk factor for nontraumatic fractures (NTFx); yet, the effect of CIPN on NTFx risk has not been examined for BrCa survivors. We therefore investigated the association between CIPN and NTFx in BrCa survivors. Data were extracted from Optum's Deidentified Clinformatics® Data Mart Database years 2010–2015 in this retrospective cohort study. Among women, three groups were derived based on BrCa and CIPN status: BrCa+/CIPN+ (primary group of interest), BrCa+/CIPN− (first comparison group), and BrCa−/CIPN− (second comparison group). After propensity score matching the comparison groups to BrCa+/CIPN+ at a ratio of 1:11 (BrCa:control) for demographics, osteoporosis, glucocorticoid medication, comorbidities, and cancer‐related variables for BrCa+/CIPN−, 1‐year incidence rate (IR) of NTFx was determined for each group. The incident rate ratio (IRR) determined if the IR for NTFx was different for BrCa+/CIPN+ compared to BrCa+/CIPN− and BrCa−/CIPN−. Cox proportional hazards regression models estimated the hazard ratios (HRs) after adjusting for covariates that were unable to be matched for. The crude IR (95% confidence interval [CI]) of NTFx was 4.54 (2.32–6.77) for BrCa+/CIPN+ (n = 359), 2.53 (2.03–3.04) for BrCa+/CIPN− (n = 3949), and 1.76 (1.35–2.18) for BrCa−/CIPN− (n = 3949). The crude IRR of NTFx was significantly elevated for BrCa+/CIPN+ as compared to BrCa+/CIPN− (IRR = 1.80; 95% CI, 1.06–3.05) and BrCa−/CIPN− (IRR = 2.58; 95% CI, 1.50–4.44). The elevated rate of NTFx for BrCa+/CIPN+ remained unchanged after adjusting for aromatase inhibitors compared to BrCa+/CIPN− (HR = 1.79; 95% CI, 1.06–3.04). Female BrCa survivors have an increased 1‐year IR of NTFx after the onset of CIPN, suggesting that CIPN is an additive burden on NTFx risk among BrCa survivors. © 2021 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.
Transition Modeling for Low Pressure Turbines Using Computational Fluid Dynamics Driven Machine Learning

Existing Reynolds Averaged Navier-Stokes based transition models do not accurately predict separation induced transition for low pressure turbines. Therefore, in this study, a novel framework based on computational fluids dynamics driven machine learning coupled with multi-expression and multi-objective optimization is explored to develop models which can improve the transition prediction for the T106A low pressure turbine at an isentropic exit Reynolds number of Re2is=100,000. Model formulations are proposed for the transfer and laminar eddy viscosity terms of the laminar kinetic energy transition model using seven non-dimensional pi groups. The multi-objective optimization approach makes use of cost functions based on the suction-side wall-shear stress and the pressure coefficient. A family of solutions is thus developed, whose performance is assessed using Pareto analysis and in terms of physical characteristics of separated-flow transition. Two models are found which bring the wall-shear stress profile in the separated region at least two times closer to the reference high-fidelity data than the baseline transition model. As these models are able to accurately predict the flow coming off the blade trailing edge, they are also able to significantly enhance the wake-mixing prediction over the baseline model.
Optimal Investment in Preservation Technology for Variable Demand under Trade-Credit and Shortages

In particular business transactions, the supplier usually provides an admissible delay in settlement to its vendor to encourage further sales. Additionally, the demand for the commodity is inversely proportional to the function of the sales price, which is non-linear and, in some situations, a holding cost rises over time. Moreover, many goods often deteriorate consistently and shall not be sold after their expiration dates. This study analyses a model for perishable products with a maximum life span with price-dependent demand and trade credit by assimilating these variations and under the supposition of time-varying holding cost. Furthermore, to diminish the rate of deterioration, investment for preservation technology is often taken into account beforehand. Based on real-life circumstances, shortages are admitted and backlogged partially, with an exponential rise in wait time before the new good emerges. The key ambition is to calculate the optimum investment under preservation, sales price, and cycle time using the classical optimization algorithm to maximize the vendor’s net profit. Additionally, to clarify the outcomes, the numerical illustrations are addressed, and the sensitivity analysis of significant parameters is eventually implemented.
Total Phenol Analysis: Automation and Comparison with Manual Methods

A fully automated-continuous flow 40-sample/ hour procedure was adapted from the Singleton-Rossi method of analysis for total phenols in wine and other plant extracts. It was compared with small-volume manual and semiautomated versions of this analysis. The agreement in mg of gallic acid equivalent phenol (GAE) per liter among a series of dry wines was excellent by all three procedures. The coefficients of variation in replicate analyses averaged 5.8% for the manual, 6.2% for the semi-automated and 2.2% for the automated procedure. This greater reproducibility, plus savings of about 70% in labor and up to 40% in reagents, makes the automated procedure attractive for laboratories doing enough total phenol analyses to recoup the cost of the automating equipment. For continuous flow, color development with the Folin-Ciocalteu reagent in alkaline solution must be hastened by heating compared to slower room temperature development for the manual methods. Heating of sugar-containing samples in the alkaline solution gives interference presumably from endiol formation. Examples are given of corrections which were used successfully to estimate the true phenol content of sweet wines.
Homogeneously weighted moving average control chart based on Bayesian theory

The frequentist approach‐based control charts (CCs) have been widely used to monitor the performance of the process. As compare to frequentist approach, the CCs based on the Bayesian approach can be used with a small phase‐I dataset. This paper aims to propose a new homogenously weighted moving average CC based on the Bayesian theory. We have used two different loss functions, symmetric loss function as squared error loss function and asymmetric loss function as linex loss function under the informative prior as conjugate prior and noninformative prior by using posterior distribution (P dist) and posterior predictive distribution (PP dist). We calculated the values of average run length and standard deviation of run length to check the performance of the proposed homogenously weighted moving average CC based on the Bayesian theory. We also compared the proposed CC with the exponentially weighted moving average CC under the Bayesian theory. The results revealed that the proposed CC is more sensitive in the detection of small/moderate shifts than the considered CC. Finally, we presented an example based on a real‐life data for implementation purposes.
A Life Quality Architectural Approach to Enhance Digital Skills Training

The paper presents the demand for professional services and skills in the health sector. The Erasmus+ DIGI4ME project aims to enhance digital skills trainings. An analysis of the Romanian health information system was conducted based on the interviews of the National Public Health Institute of Romania with stakeholders. According to the incidents which occurred in hospitals around the world, a system based on sensors is proposed to mitigate the problems which can appear. The testing of the system was done in laboratory conditions and the reports display the evolution of the measured environmental parameters. The software solution can determine medical professionals to enhance their digital skills and trigger creative ideas to improve the experience of their patients.
From shaping to functionalization of micro-droplets and particles

The structure of microdroplet and microparticle is a critical factor in their functionality, which determines the distribution and sequence of physicochemical reactions. Therefore, the technology of precisely tailoring their shape is requisite for implementing the user demand functions in various applications. This review highlights various methodologies for droplet shaping, classified into passive and active approaches based on whether additional body forces are applied to droplets to manipulate their functions and fabricate them into microparticles. The passive approaches cover batch emulsification, solvent evaporation and diffusion, micromolding, and microfluidic methods. In active approaches, the external forces, such as electrical and magnetic fields or optical lithography, are applied to microdroplets. Special attention is also given to latest technologies using microdroplets and microparticles, especially in the fields of biological, optical, robotic, and environmental applications. Finally, this review aims to address the advantages and disadvantages of the introduced approaches and suggests the direction for further development in this field.
Machine Learning for Price Prediction for Agricultural Products

Family farms play a role in economic development. Limited in terms of land, water and capital resources, family farming is essentially characterized by its use of family labour. Family farms must choose which agricultural products to produce; however, they do not have the necessary tools for optimizing their decisions. Knowing which products will have the best prices at harvest is important to farmers. At this point, machine learning technology has been used to solve classification and prediction problems, such as price prediction. This work aims to review the literature in this area related to price prediction for agricultural products and seeks to identify the research paradigms employed, the type of research used, the most commonly used algorithms and techniques for evaluation, and the agricultural products used in these predictions. The results show that the mostly commonly used research paradigm is positivism, the research is quantitative and longitudinal in nature and neural networks are the most commonly used algorithms.
Serious Games and Mathematical Fluency: A Study from the Gender Perspective in Primary Education

In recent years, serious games offer great opportunities for learning processes at schools. However, it is unclear whether this type of proposals can offer differentiated answers among the students according to their gender. In this context, the aim of this paper is to know the possible differences that occur in primary school classrooms according to gender, with serious games designed for the development of mathematical fluency, and to examine to what extent these games contribute to the overall school performance. We carried out a quasi-experimental study, including pretest and posttest, without control group and with several experimental groups, and the participation of 284 students from first to fourth grade. The results show that the software benefits boys and girls equally, compared to the previously followed methodology that benefited boys. A clear relation between the results achieved and the performance in the overall students’ grades has also been observed. The conclusions show the potential of serious games in school settings, and the opportunity to approach performance differences based on the gender.
Did Politicians Use Non-Public Macroeconomic Information in Their Stock Trades? Evidence from the STOCK Act of 2012

Existing research shows that members of Congress made informed trades prior to the passage of the STOCK Act of 2012. There is also evidence in the literature to suggest that the STOCK Act was able to deter politicians from trading based on non-public information. However, the question of whether politicians made informed trades at the market level (using non-public macroeconomic information, not just firm-specific information) in the first place and whether they continued to do so even after the passage of the STOCK Act remains unexamined. We analyze 101,191 individual stock transactions covering the 2004–2014 period and find that the STOCK Act adversely affected the ability of politicians’ aggregated stock trades to predict the stock market returns. Our results imply that politicians used non-public macroeconomic information prior to the STOCK Act, and this legislation was influential in deterring politicians from using non-public macroeconomic information in their stock trades. Our findings also provide input on the current debate on the need for the STOCK Act 2.0.
Combination Therapy for Neuropathic Pain. A Systematic Review

Pharmacological treatment is poorly effective for neuropathic pain (NP). A progressive decrease in the estimated effect of NP drugs has been reported, giving rise to an increase in multimodal analgesic approach. We performed a systematic review to assess whether there is more and better-quality evidence available since the last review. We evaluated the efficacy, tolerability and safety of double-blind randomized controlled trials involving only adult participants comparing combination therapy (CT: ≥ 2 drugs) to placebo and/or at least one other comparator with NP indication. The primary outcome was the proportion of participants reporting ≥ 50% pain reduction from baseline. Secondary outcome was the proportion of drop-outs due to treatment-emergent-adverse-events. After removing duplicates, 2323 citations were screened. 164 articles were assessed for eligibility, from which 16 were included for qualitative analysis. From the latter, only 5 lasted for at least 12 weeks and only 6 complied with required data for complete analysis, but not for meta-analysis. CT has been adopted for years without robust evidence. Efforts to achieve better quality evidence have not improved over the years. In this regard, guidelines for NP should attempt to make recommendations on CT research, prioritizing which combinations to analyze.
A robust method for 2D occupancy map building for indoor robot navigation

This paper proposed an efficient method to provide a robust occupancy grid useful for robot navigation tasks. An omnidirectional indoor robot accomplishing logistics tasks, has been equipped with stereocameras for detecting the presence of moving and fixed obstacles. The stereocamera provides a 3D point cloud. Starting from the tridimensional information, the occupancy map can be computed. Nevertheless, the point cloud often owns unstable points mainly due to low accurate disparity map and to light reflections on the floor that produce mismatching during the stereo matching phase. The point cloud has been opportunely filtered by using a cascade approach in order to get more robust occupancy grids. Passthrough filters are applied to remove the too far 3D points. Since high reflective floors produce unwanted 3D points, a color filter is also used to remove those points having saturated intensity values. The remaining floating points related always to the floor are then filtered out by taking advantage of the knowledge about the camera tilt. At this stage, a preliminary 2D occupancy grid is built to sample the point cloud. Each bin of occupancy map is then processed. In case the cell under investigation contains points, a distribution analysis about the point spread is performed. If the height of the highest point is under a determined threshold value, the cell value is set to zero. The unwanted floor points are thus furtherly removed. The cells containing a low number of points are also cleared. Finally, the isolated cells of occupancy grid and the cells that do not have enough valid neighboring cells are reset. The noisy points and the edge points of objects do not concur to produce inaccurate occupancy maps. Final outcomes prove as the proposed methodology enables to provide robust occupancy maps ensuring high performance in terms of processing time.
Process research of removing arsenic and iron in copper sulfate

Copper sulfate for electroplating was obtained from agricultural copper sulfate after removing impurities.Arsenic and iron in agricultural copper sulfate were removed by oxidization,neutralization and hydrolysis, and the result meets the quality requirement of copper sulfate for electroplating. In our experiment,H 2O 2 was used to oxide As(Ⅲ)and Fe(Ⅱ) effectively with high rate.In addition appropriate Fe 2(SO 4) 3 was added into the solution in order to eleminate As in the form of preciptation of FeAsO 4.Further more,the additional Fe 3+ was removed in the form of precipitation of Fe(OH) 3 through maintaining the pH value of solution to be around four.
MFP-Net: Multi-scale feature pyramid network for crowd counting

Although deep learning has been widely used for dense crowd counting, it still faces two challenges. Firstly, the popular network models are sensitive to scale variance of human head, human occlusions, and complex background due to repeated utilization of vanilla convolution kernels. Secondly, the vanilla feature fusion often depends on summation or concatenation, which ignores the correlation of different features leading to information redundancy and low robustness to background noise. To address these issues, a multi-scale feature pyramid network (MFP-Net) for dense crowd counting is proposed in this paper. The proposed MFP-Net makes two contributions. Firstly, the feature pyramid fusion module is designed that adopts rich convolutions with different depths and scales, not only to expand the receptive ﬁeld, but also to improve the inference speed of models by using parallel group convolution. Secondly, a feature attention-aware module is added in the feature fusion stage. The module can achieve local and global information fusion by capturing the importance of the spatial and channel domains to improve model robustness. The proposed MFP-Net is evaluated on ﬁve publicly available datasets, and experiments show that the MFP-Net not only provides better crowd counting results than comparative models, but also requires fewer parameters.
A Multiple-Reference Complex-Based Controller for Power Converters

A multiple-reference complex-based controller is proposed for three-phase power converters feeding nonlinear and unbalanced loads. The control scheme incorporates a stable multiple-complex coefficient filter with bandwidths that are set arbitrarily and independently for every harmonic under consideration. The multiple-reference complex-based control scheme is applied to an uninterruptible power supply system with a voltage source converter. Each harmonic is controlled using a standard complex proportional-resonant controller that is designed for stability and robustness using the Nyquist criterion. Similar stability and robustness properties follow for the overall system due to the frequency-domain properties of the filter and of the controllers. The proposed methodology is validated in simulation and experimental tests.
Adsorption Equilibria of Carbon Dioxide and Ethane on Graphitized Carbon Black

Adsorption equilibrium data for pure carbon dioxide and ethane on STH-2 graphitized carbon black were measured by a volumetric method. The experiments were carried out over the temperature range (253.2 to 303.2) K and the pressure range (0 to 4) MPa. The relative pressure p/p0 and adsorption amount n have been adopted to express adsorption isotherms, and the experimental data present a generalized adsorption isotherm over the research range. On the basis of this generalized isotherm, a method of predicting gas adsorption equilibria was explored. The prediction accuracy is satisfactory. In addition, analysis of the BET equation provides proof that the generalized adsorption isotherm p/p0 ∼ n is reasonable.
First glaciological investigations at Ridge B, central East Antarctica

Abstract The region of Ridge B in central East Antarctica is one of the last unexplored parts of the continent and, at the same time, ranks among the most promising places to search for Earth's oldest ice. In January 2020, we carried out the first scientific traverse from Russia's Vostok Station to the topographical dome of Ridge B (Dome B, 3807 m above sea level, 79.02°S, 93.69°E). The glaciological programme included continuous snow-radar profiling and geodetic positioning along the traverse's route, installation of snow stakes, measurements of snow density, collection of samples for stable water isotope and chemical analyses and drilling of a 20 m firn core. The first results of the traverse show that the surface mass balance at Dome B (2.28 g cm−2 year−1) is among the lowest in Antarctica. The firn temperature below the layer of annual variations is −58.1 ± 0.2°C. A very low value of heavy water stable isotope content (-58.2‰ for oxygen-18) was discovered at a distance of 170 km from Vostok Station. This work is the first step towards a comprehensive reconnaissance study of the Ridge B area aimed at locating the best site for future deep drilling for the oldest Antarctic ice.