Miracle-dz/UniFAR-FTUs huggingface dataset:
Data-driven option pricing using single and multi-asset supervised learning

We propose three different data-driven approaches for pricing European-style call options using supervised machine-learning algorithms. These approaches yield models that give a range of fair prices instead of a single price point. The performance of the models is tested on two stock market indices: NIFTY50 and BANKNIFTY from the Indian equity market. Although neither historical nor implied volatility is used as an input, the results show that the trained models have been able to capture the option pricing mechanism better than or similar to the Black–Scholes formula for all the experiments. Our choice of scale free I/O allows us to train models using combined data of multiple different assets from a financial market. This not only allows the models to achieve far better generalization and predictive capability, but also solves the problem of paucity of data, the primary limitation of using machine learning techniques. We also illustrate the performance of the trained models in the period leading up to the 2020 Stock Market Crash (January 2019 to April 2020).
DNA Methylation Clocks and Their Predictive Capacity for Aging Phenotypes and Healthspan

The number of age predictors based on DNA methylation (DNAm) profile is rising due to their potential in predicting healthspan and application in age-related illnesses, such as neurodegenerative diseases. The cumulative assessment of DNAm levels at age-related CpGs (DNAm clock) may reflect biological aging. Such DNAm clocks have been developed using various training models and could mirror different aspects of disease/aging mechanisms. Hence, evaluating several DNAm clocks together may be the most effective strategy in capturing the complexity of the aging process. However, various confounders may influence the outcome of these age predictors, including genetic and environmental factors, as well as technical differences in the selected DNAm arrays. These factors should be taken into consideration when interpreting DNAm clock predictions. In the current review, we discuss 15 reported DNAm clocks with consideration for their utility in investigating neurodegenerative diseases and suggest research directions towards developing a more optimal measure for biological aging.
Modification of Lignocellulosic Materials with a Mixture of m-DMDHEU/Choline Chloride to Remove CrO42–, NO3–, and H2AsO4– in Aqueous Solution

A new denaturation agent is the mixture of 4,5-dihydroxy-1,3-bis(methoxymethyl)imidazolidin-2-one (m-DMDHEU)/choline chloride (CC) introduced to modify three kinds of lignocellulosic materials containing different lignin contents in the following order: cotton used in medicine < sawdust from acacia auriculiformis wood < powder from the coconut shell. The modification process is carried out through two main steps: 0.2 N NaOH solution with 70% v/v ethanol and 30% v/v water was applied to remove lignin and activate the initial raw materials, and then delignified materials were modified with m-DMDHEU/CC by using a parched heat supply method after chemical impregnation. Structural characterictics and physicochemical properties of modified materials were tested and dissected by scanning electron microscopy, Fourier transform infrared spectroscopy, solid-state 13C nuclear magnetic resonance spectroscopy (solid-state 13C CP-MAS NMR), specific surface area, and pH at the point of zero charge (pHPZC). The ability to adsorb and exchange anions of modified materials was referred and examined by using aqueous solutions containing CrO42–, NO3–, and H2AsO4– anions in different conditions. The results revealed that anionite lignocellulosic materials could separate these anions with very good efficiency and better than strong anion exchange resin (GA-13) in the same conditions; outlet water could meet the permissible drinking and living water standards; and the m-DMDHEU cross-link bridge also was a good bridge to connect CC to cellulose chain beside other common urea cross-link bridges.
Clinical Significance of ZNF711 in Human Breast Cancer

Purpose To investigate the clinicopathologic and prognostic significance of the zinc-finger protein 711 (ZNF711) in breast cancer (BCa). Materials and Methods The relevance of ZNF711 in BCa was analyzed using bioinformatics. The expression of ZNF711 was detected by immunohistochemistry in paraffin blocks of BCa. To evaluate its clinical significance, the correlation between the expression of ZNF711 and BCa clinical indicators, including estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER-2), was analyzed. Finally, the Kaplan–Meier method was applied to explore the prognostic value of ZNF711. Results ZNF711 expression was decreased in BCa and was negatively correlated with ER expression (P < 0.05) and positively correlated with HER-2 expression (P < 0.01), but there was no significant correlation between ZNF711 and PR expression. ZNF711 expression was not correlated with age, tumor diameter, or lymph node metastasis; however, ZNF711 expression was correlated with staging in BCa. Survival analysis results showed that the ZNF711-positive group patients had a poorer prognosis compared with the ZNF711-negative group. Conclusion The expression of ZNF711 was deceased in BCa and closely related to ER and HER-2 expression. Therefore, ZNF711 could not only serve as a predictor of BCa with poor prognosis but also as a potential biomarker for targeted therapy.
A Four Gene-Based Risk Score System Associated with Chemoradiotherapy Response and Tumor Recurrence in Rectal Cancer by Co-Expression Network Analysis

Aim Resistance to neoadjuvant chemoradiotherapy (NCRT) and tumor recurrence presents a major clinical problem in locally advanced rectal cancer (LARC) patients. This study aimed to explore a genetic risk score related to NCRT response and tumor recurrence in rectal cancer after NCRT. Materials and Methods Weighted gene co-expression network analysis was employed to identify hub genes associated with NCRT response from the GSE93375 dataset. Prognostic hub genes were determined using Cox regression analysis and associated with disease-free survival (DFS). A risk score system was constructed and the prognostic significance of the risk score was validated in our patient cohort. A predictive nomogram for DFS was developed and validated internally. Results The Tan module had the highest correlations with NCRT response. Ten hub genes (COL15A1, THBS2, ITGB1, MMP2, CD34, SPARC, NOTCH3, PDGFRB, DCN, and SERPINH1) were associated with NCRT response. Immunostaining expression of four genes (NOTCH3, SPARC, DCN, and ITGB1) was found to be significantly associated with both NCRT response and DFS in our patient cohort and was selected to build a prognostic risk score for DFS as follows: risk score= (0.6188×ExpNOTCH3) + (0.6511×ExpSPARC) + (−0.2976×ExpDCN) + (1.0035×ExpITGB1). Using this risk score, patients could be separated into high- and low-risk groups for tumor recurrence. A nomogram that incorporated the risk score, ypTNM stage, and tumor regression grade (TRG) was constructed and utilized to predict DFS in LARC patients. Conclusion The four-gene expression-based risk score system presented here could be potentially used for predicting tumor recurrence in LARC patients after NCRT.
Leptomeningeal Carcinomatosis Secondary to Esophageal Cancer Diagnosed on Cytology

Abstract Esophageal carcinoma is considered a common malignancy across the globe. These patients usually present with an advanced stage of the disease at the time of diagnosis. Herein, we report a 55-year male patient who presented with leptomeningeal carcinomatosis, detected on cerebrospinal fluid (CSF) cytology in a case of adenocarcinoma lower third esophagus. On radiological imaging, he also had extensive metastatic deposits in the liver, pleura, and regional and paravertebral lymph nodes.
Comparative effectiveness of different Rhizobium sp. for improving growth and yield of maize (Zea mays L.)

During the last couple of decades, it has been demonstrated that rhizobia can associate with roots of nonlegumes also without forming true nodules, and can promote their growth by using one or more of the direct or indirect mechanisms of actions. This work examines the growth and yield responses of maize to inoculation with different species of rhizobia, isolated from the root nodules of chickpea (Cicer arietinum L.), lentil (Lens culinaris M.) and mung bean (Vigna radiata L.) in pots and fields. Twenty isolates of rhizobia were isolated from root nodules each of mung bean, lentil and chickpea and were screened under axenic conditions. On the basis of their promising performance under axenic conditions, nine most efficient isolates (three from each legume host) were selected, characterized and further evaluated for their growth promoting activities by conducting pot and field experiments. Results of pot experiment revealed that maximum increase in grain yield, 1000 grain weight, N, P and K uptake (up to 47.89, 54.52, 73.46, 84.66 and 59.19% by CRI28, respectively, over un-inoculated control) was produced by the isolate of Mesorhizobium ciceri. Whereas, maximum improvement in rest of the parameters was caused by the isolates of Rhizobium phaseoli (i.e. fresh biomass, straw yield and root length up to 36.30% by A 18, 25.46% by S6 and 81.89% by A18, respectively over un-inoculated control). Rhizobium leguminosarum isolates came out to be the least effective among the species tested. Similarly, all the selected isolates improved the growth and yield attributing parameters in fields as well but with varying capacity compared with un-inoculated control. The selected isolates of Mesorhizobium ciceri and Rhizobium phaseoli again remained superior compared to the isolates of Rhizobium leguminosarum under field conditions. The results of this study imply that rhizobium species had potential to promote growth and yield of maize but this technology should be employed after appropriate site specific investigations of particular rhizobial specie with respect to specific non-leguminous crop variety to get maximum benefit in terms of better growth and yield.
Sarbanes-Oxley and Corporate Risk-Taking

We empirically examine whether risk-taking by publicly traded US companies declined significantly after adoption of the Sarbanes-Oxley Act of 2002 (SOX). Several provisions of SOX are likely to discourage risk-taking, including an expanded role for independent directors, an increase in director and officer liability, and rules related to internal controls. We find several measures of risk-taking decline significantly for US versus non-US firms after SOX. The magnitudes of the declines are related to several firm characteristics, including pre-SOX board structure, firm size, and R&D expenditures. The evidence is consistent with the proposition that SOX discourages risk-taking by public US companies.
Airline Disruption Management with Aircraft Swapping and Reinforcement Learning

Managing fleet disruption is essential for an airline to control delay costs. Delays emerging from these disruptions can be manipulated through fleet operations like aircraft swapping. This paper applies machine learning techniques to the disruption problem. While airlines might do this process manually or using basic predefined rules, the complexity of the problem makes it well suited for a computed approach. The paper describes the principles of reinforced learning and the model used for testing them. Two representations of decision states are considered and applied to a set of historical schedules for an airline. The performance obtained by swapping aircraft using the reinforced learning is finally compared to the idle option, i.e., do not swap any flight. The comparison evinces that while the algorithm is far from being optimal, the agent takes relevant decisions as it performs better than the idle behaviour in heavily disrupted simulations.
Managerial Incentives, Market Power and Bank Risk-Taking

We investigate the effect of managerial incentives and market power on bank risk-taking for a sample of 212 large US bank holding companies over 1997-2004 (i.e. 1,534 observations). Bank managers have incentives to prefer less risk while bank shareholders have preference for ‘excessive’ risk. Likewise, the market power is the centre piece of any bank regulation. However, the literature is inconclusive as to the effect of managerial incentives and market power on bank risk-taking. Our results reveal a U-shape relation between bank risk and CEO ownership (proxy for managerial incentives) and between bank risk and charter value (proxy for market power). Particularly, we find that bank risk initially decreases and then increases with both CEO ownership and charter value. These convex relations are robust to various bank risk proxies, different estimation approaches to account for endogeneity and several bank specific control variables.
Changes in Cheddar Cheese by Commercial Enzyme Preparations

Abstract Free volatile acids, soluble protein, and flavor production were accelerated in young ripened Cheddar cheese by adding various combinations of proteolytic and lipolytic commercial enzyme preparations with salt to curds before pressing. Cheese held 1 mo at 20C and containing about 2.5g mixed enzymes per 5.9kg curd had higher flavor than controls. Some rancidity but no bitterness accompanied this cheese flavor. Higher ripening temperature and longer holding times led to burnt flavors and pronounced rancidity. Processed cheese made by mixing mild 2 mo old natural Cheddar cheese with 10 to 40% 1 mo enzyme-treated cheese gave good texture and medium to very sharp flavor intensity. Various mixtures of neutral protease and lipase enzymes and of neutral protease-peptidase and lipase enzymes in cheese slurries developed cheese flavor rapidly with minimum bitterness. Microbial acid proteases in cheese slurries led to strong bitterness.
ACA Advocacy Competencies: A Social Justice Framework for Counselors

The importance of advocacy in counseling is explored through the framework of the ACA Advocacy Competencies in this inspiring new book that brings social justice to the forefront of the profession. Experts in the field discuss how counselors, counselor educators, and students can use the ideals in the Competencies with diverse client populations (people of color, clients living in poverty, people with disabilities, LGBTQ individuals, older persons); across various counseling settings (K–12, private practice, colleges and universities, counselor education and supervision); and in multiple specialty areas (group work, career counseling, rehabilitation, substance abuse counseling). Detailed examples in each chapter help to guide counselors as to when individual empowerment counseling alone is appropriate, or when situations call for advocacy on behalf of clients or their communities within the public arena or political domain. Thought provoking and engaging, this book is an invaluable resource for teaching and course work and an imperative call for all counselors to participate in social justice and systems change to provide the best services for their clients.
The effects of outdoor recreation on range use by semi‐domesticated reindeer

The effects of a large holiday resort on the distribution and range use of semi‐domesticated reindeer were studied in the three most important habitat types in Saariselka, eastern Finnish Lapland. In two of these habitats the relative reindeer densities increased in winter, when outdoor activities declined reaching density equal to the average for the herding association at a distance of about 10 km from the holiday resort. In summer, male reindeer adapted better than females to the proximity of the holiday resort. The feeding site preferences of the reindeer during winter followed, in general, the normal pattern in areas with little human interference. Although the economic value of the range loss appeared small compared to the gain from outdoor enterprises, better planning is needed to avoid the harmful effects of recreation on reindeer management.
Radiation of Electric and Magnetic Dipole Antennas in Magnetically Anisotropic Media

In this paper the exact analytical solutions of the Maxwell equations in boundless magnetically anisotropic media are obtained in the vector type by the method of generalized functions at the action of the distributed currents. The electrical and magnetic dipole directional diagrams are plotted. Ill. 6, bibl. 4 (in English; summaries in English; Russian and Lithuanian).
Real-time Assessment, Prediction, and Scaffolding of Middle School Students’ Data Collection Skills within Physical Science Simulations

Despite widespread recognition by science educators, researchers and K-12 frameworks that scientific inquiry should be an essential part of science education, typical classrooms and assessments still emphasize rote vocabulary, facts, and formulas. One of several reasons for this is that the rigorous assessment of complex inquiry skills is still in its infancy. Though progress has been made, there are still many challenges that hinder inquiry from being assessed in a meaningful, scalable, reliable and timely manner. To address some of these challenges and to realize the possibility of formative assessment of inquiry, we describe a novel approach for evaluating, tracking, and scaffolding inquiry process skills. These skills are demonstrated as students experiment with computer-based simulations. In this work, we focus on two skills related to data collection, designing controlled experiments and testing stated hypotheses. Central to this approach is the use and extension of techniques developed in the Intelligent Tutoring Systems and Educational Data Mining communities to handle the variety of ways in which students can demonstrate skills. To evaluate students’ skills, we iteratively developed data-mined models (detectors) that can discern when students test their articulated hypotheses and design controlled experiments. To aggregate and track students’ developing latent skill across activities, we use and extend the Bayesian Knowledge-Tracing framework (Corbett & Anderson, 1995). As part of this work, we directly address the scalability and reliability of these models’ predictions because we tested how well they predict for student data not used to build them. When doing so, we found that these models demonstrate the potential to scale because they can correctly evaluate and track students’ inquiry skills. The ability to evaluate students’ inquiry also enables the system to provide automated, individualized feedback to students as they experiment. As part of this work, we also describe an approach to provide such scaffolding to students. We also tested the efficacy of these scaffolds by conducting a study to determine how scaffolding impacts acquisition and transfer of skill across science topics. When doing so, we found that students who received scaffolding versus students who did not were better able to acquire skills in the topic in which they practiced, and also transfer skills to a second topic when was scaffolding removed. Our overall findings suggest that computer-based simulations augmented with real-time feedback can be used to reliably measure the inquiry skills of interest and can help students learn how to demonstrate these skills. As such, our assessment approach and system as a whole shows promise as a way to formatively assess students’ inquiry.
Expectation-Maximization for Speech Source Separation Using Convolutive Transfer Function

This study addresses the problem of under-determined speech source separation from multichannel microphone signals, i.e. the convolutive mixtures of multiple sources. The time-domain signals are first transformed to the short-time Fourier transform (STFT) domain. To represent the room filters in the STFT domain, instead of the widely used narrowband assumption, the authors propose to use a more accurate model, i.e. the convolutive transfer function (CTF). At each frequency band, the CTF coefficients of the mixing filters and the STFT coefficients of the sources are jointly estimated by maximising the likelihood of the microphone signals, which is resolved by an expectation-maximisation algorithm. Experiments show that the proposed method provides very satisfactory performance under highly reverberant environments.
Epidemics and Rumours in Complex Networks

Information propagation through peer-to-peer systems, online social systems, wireless mobile ad hoc networks and other modern structures can be modelled as an epidemic on a network of contacts. Understanding how epidemic processes interact with network topology allows us to predict ultimate course, understand phase transitions and develop strategies to control and optimise dissemination. This book is a concise introduction for applied mathematicians and computer scientists to basic models, analytical tools and mathematical and algorithmic results. Mathematical tools introduced include coupling methods, Poisson approximation (the Stein-Chen method), concentration inequalities (Chernoff bounds and Azuma-Hoeffding inequality) and branching processes. The authors examine the small-world phenomenon, preferential attachment, as well as classical epidemics. Each chapter ends with pointers to the wider literature. An ideal accompaniment for graduate courses, this book is also for researchers (statistical physicists, biologists, social scientists) who need an efficient guide to modern approaches to epidemic modelling on networks.
Adaptive array antenna based on estimation of arrival angles using DFT on spatial domain

Multipath fading is a factor degrading the communication quality in mobile communications. It has been reported that an adaptive array antenna can enable elimination of the effect of delayed signals by an appropriate control of the radiation pattern. In this paper, it is recognized that an optimum weight of the array antenna can be computed if the direction of arrival and the signal-to-noise ratio of the received signal are known. By using the spatial frequency derived by the discrete Fourier transform (DFT) of the received signal which is spatially sampled by the array antenna, an algorithm is proposed in which the directions of arrival and the signal-to-noise (SN) ratio of the desired and interference waves are estimated and an optimum weight coefficient of the antenna is computed. This algorithm is different from those in the conventional adaptive digital filter algorithms such as the LMS algorithm. It requires no reference signal and can follow quickly changes in the communication channel. Further, a method is proposed to improve the estimation accuracy of the direction of arrival and the SN ratio with a limited number of elements by using the property of the DFT. To confirm the principle of the proposed algorithm, the basic characteristics are evaluated by computer simulation.
Stable relations and abstract interpretation of higher-order programs

We present a novel denotational semantics for the untyped call-by-value λ-calculus, where terms are interpreted as stable relations, i.e. as binary relations between substitutions and values, enjoying a monotonicity property. The denotation captures the input-output behaviour of higher-order programs, and is proved sound and complete with respect to the operational semantics. The definition also admits a presentation as a program logic. Following the principles of abstract interpretation, we use our denotational semantics as a collecting semantics to derive a modular relational analysis for higher-order programs. The analysis infers equalities between the arguments of a program and its result—a form of frame condition for functional programs.