bluuebunny/crossref_metadata_2025_split huggingface dataset:
KnowMore: an automated knowledge discovery tool for the FAIR SPARC datasets
Authors: Quey Ryan , Schiefer Matthew A. , Kiran Anmol , Patel Bhavesh 
Published: August 2021

AbstractThis manuscript provides the methods and outcomes of KnowMore, the Grand Prize winning automated knowledge discovery tool developed by our team during the 2021 NIH SPARC FAIR Data Codeathon. The National Institutes of Health Stimulating Peripheral Activity to Relieve Conditions (NIH SPARC) program generates rich datasets from neuromodulation researches, curated according to the Findable, Accessible, Interoperable, and Reusable (FAIR) SPARC data standards. These datasets are publicly available through the SPARC Data Portal at sparc.science. Currently, the process of simultaneously comparing and analyzing multiple SPARC datasets is tedious because it requires investigating each dataset of interest individually and downloading all of them to conduct cross-analyses. It is crucial to enhance this process to enable rapid discoveries across SPARC datasets. To fill this need, we created KnowMore, a tool integrated into the SPARC Portal that only requires the user to select their datasets of interest to launch an automated discovery process. KnowMore uses several SPARC resources (Pennsieve, o2S2PARC, SciCrunch, protocols.io, Biolucida), data science methods, and machine learning algorithms in the back end to generate various visualizations in the front end intended to help the user identify potential similarities, differences, and relations across the datasets. These visualizations can lead to a new discovery, new hypothesis, or simply guide the user to the next logical step in their discovery process. The outcome of this project is a SPARC portal-ready code architecture that helps researchers to use SPARC datasets more efficiently and fully leverages their FAIR characteristics. The tool has been built and documented such that more data analysis methods and visualization items could be easily added. The potential for automated discoveries from SPARC datasets is huge given the unique SPARC data ecosystem promoting FAIR data practices, and KnowMore has only demonstrated a small highlight of what could be achieved to speed up discoveries from SPARC datasets.
SIRT5 is the desuccinylase of LDHA as novel cancer metastatic stimulator in aggressive prostate cancer
Authors: Kwon Oh Kwang , Bang In Hyuk , Choi So Young , Jeon Ju Mi , Na Ann-Yae , Gao Yan , Cho Sam Seok , Ki Sung Hwan , Choe Youngshik , Lee Jun Nyung , Ha Yun-Sok , Bae Eun Ju , Kwon Tae Gyun , Park Byung-Hyun , Lee Sangkyu 
Published: August 2021

AbstractProstate cancer (PCa) is the most commonly diagnosed genital cancer in men worldwide. Among patients who developed advanced PCa, 80% suffered from bone metastasis, with a sharp drop in the survival rate. Despite great efforts, the details of the mechanisms underlying castration-resistant PCa (CRPC) remains unclear. SIRT5, an NAD+-dependent desuccinylase, is hypothesized to be a key regulator of various cancers. However, compared to other SIRTs, the role of SIRT5 in cancer has not been extensively studied. Here, we showed significantly decreased SIRT5 levels in aggressive PCa cells relative to the PCa stages. The correlation between the decrease in the SIRT5 level and the patient’s survival rate was also confirmed. Using quantitative global succinylome analysis, we characterized a significant increase of lysine 118 succinylation (K118su) of lactate dehydrogenase A (LDHA), which plays a role in increasing LDH activity. As a substrate of SIRT5, LDHA-K118su significantly increased the migration and invasion of PCa cells and LDH activity in PCa patients. This study investigated the reduction of SIRT5 and LDHA-K118su as a novel mechanism involved in PCa progression. It can also be proposed as a new target that can prevent castration-resistant PCa progression, which is key to PCa treatment.
αS oligomers generated from polyunsaturated fatty acid and dopamine metabolite differentially interact with Aβ to enhance neurotoxicity
Authors: Dhakal Shailendra , Saha Jhinuk , Wyant Courtney E. , Rangachari Vijayaraghavan 
Published: August 2021

AbstractIt is increasingly becoming clear that neurodegenerative diseases are not as discrete as originally thought to be but rather display significant overlap in histopathological and clinical presentations. For example, nearly half of the patients with Alzheimer disease (AD) and synucleinopathies such as Parkinson disease (PD) show symptoms and pathological features of one another. Yet, the molecular events and features that underlie such comorbidities in neurodegenerative diseases remain poorly understood. Here, inspired to uncover the molecular underpinnings of the overlap between AD and PD, we investigated the interactions between amyloid-β (Aβ) and α-synuclein (αS), aggregates of which form the major components of amyloid plaques and Lewy bodies, respectively. Specifically, we focused on αS oligomers generated from the dopamine metabolite called dihydroxyphenylacetaldehyde (DOPAL), and a polyunsaturated fatty acid docosahexaenoic acid (DHA). Both αS oligomers showed structural and conformational differences confirmed by their disparity in size, secondary structure, susceptibility to proteinase K digestion and cytotoxicity. More importantly, the two oligomers differentially modulated Aβ aggregation. While both oligomers inhibited Aβ aggregation to varying extents, they induced structurally different Aβ assemblies. Furthermore, Aβ seeded with DHA-derived αS oligomers showed greater toxicity than DOPAL-derived αS oligomers in SH-SY5Y neuroblastoma cells. These results provide insights into the interactions between two amyloid proteins with empirically distinctive biophysical and cellular manifestations, enunciating a basis for potentially ubiquitous cross-amyloid interactions across many neurodegenerative diseases.
Analyzing the Perceptual Attributes of Electro-tactile Stimuli as Function of Various Signal Properties
Authors: Rahimi Mehdi , Jiang Fang , Shen Yantao 
Published: August 2021

AbstractThis study is designed to determine the proper electrical signals that induce various perceptual qualities. These perceptions are chosen from a wide range of feelings, comfort and even surface qualities such as smoothness or flatness. The goal is to derive the relationship between the electrical signal properties (i.e. voltage, frequency and duty cycle) and the perceived qualities which are understood by human observers and reveal any pattens in their reports. A total of 144 measurements are collected from 8 participants. The results are analyzed using numerous statistical methods. In the end, the governing factors are identified and a signal with specific properties is is determined for each of the perception qualities. A great number of plots are included in this study to facilitate the process of choosing the appropriate signal for each factor.
Economic policy uncertainty and stock prices in BRIC countries: evidence from asymmetric frequency domain causality approach
Authors: Aydin Mucahit , Pata Ugur Korkut , Inal Veysel 
Published: August 2021

Purpose
The aim of this study is to investigate the relationship between economic policy uncertainty (EPU) and stock prices during the period from March 2003 to March 2021.

Design/methodology/approach
The study uses asymmetric and symmetric frequency domain causality tests and focuses on BRIC countries, namely, Brazil, Russia, India and China.

Findings
The findings of the symmetric causality test confirm unidirectional permanent causality from EPU to stock prices for Brazil and India and bidirectional causality for China. However, according to the asymmetric causality test, the findings for China show that there is no causality between the variables. The results for Brazil and India indicate that there is unidirectional permanent causality from positive components of EPU to positive components of stock prices. Moreover, for Brazil, there is unidirectional temporary causality from the negative components of EPU to the negative components of stock prices. For India, there is temporary causality in the opposite direction.

Originality/value
The reactions of financial markets to positive and negative shocks differ. In this context, to the best of the authors’ knowledge, this study is the first attempt to examine the causal relationships between stock prices and uncertainty using an asymmetric frequency domain approach. Thus, the study enables the analysis of the effects of positive and negative shocks in the stock market separately.
Do generous trade credit terms provide a competitive edge?
Authors: Osiichuk Dmytro , Wnuczak Paweł 
Published: August 2021

PurposeThe authors document a persistent negative link between contemporaneous trade credit provision and subsequent firm-level operating performance.Design/methodology/approachTextual analysis of firms' profile descriptions is used to study the role of market segmentation and product differentiation in intermediating the nexus between trade credit and corporate performance. The paper relies on dynamic panel regression modeling to investigate the postulated empirical relationships. This approach allows to address endogeneity issues and to test a number of different model specifications.FindingsDespite fueling short-term sales growth, the more generous trade credit terms are found to be associated with lower post hoc margins and declining overall business profitability. The market share is not affected by firms' proclivity to provide trade credit suggesting that the latter may not be effectively used as a long-term growth enhancement strategy. Firms' similarity to their competitors is found to play a salient role in altering the magnitude of the discovered negative relationship.Originality/valueThe authors find that the intensity of intra-industry competition measured by firms' similarity to their competitors magnifies the discovered negative trade credit-performance nexus. Therefore, generous trade credit may play a more important role in solidifying client–supplier relationships on the more segmented markets with a higher degree of product differentiation.
A stability analysis on a smoking model with stochastic perturbation
Authors: Zeb Anwar , Kumar Sunil , Tesfay Almaz , Kumar Anil 
Published: August 2021

Purpose
The purpose of this paper is to investigate the effects of irregular unsettling on the smoking model in form of the stochastic model as in the deterministic model these effects are neglected for simplicity.

Design/methodology/approach
In this research, the authors investigate a stochastic smoking system in which the contact rate is perturbed by Lévy noise to control the trend of smoking. First, present the formulation of the stochastic model and study the dynamics of the deterministic model. Then the global positive solution of the stochastic system is discussed. Further, extinction and the persistence of the proposed system are presented on the base of the reproductive number.

Findings
The authors discuss the dynamics of the deterministic smoking model form and further present the existence and uniqueness of non-negative global solutions for the stochastic system. Some previous study’s mentioned in the Introduction can be improved with the help of obtaining results, graphically present in this manuscript. In this regard, the authors present the sufficient conditions for the extinction of smoking for reproductive number is less than 1.

Research limitations/implications
In this work, the authors investigated the dynamic stochastic smoking model with non-Gaussian noise. The authors discussed the dynamics of the deterministic smoking model form and further showed for the stochastic system the existence and uniqueness of the non-negative global solution. Some previous study’s mentioned in the Introduction can be improved with the help of obtained results, clearly shown graphically in this manuscript. In this regard, the authors presented the sufficient conditions for the extinction of smoking, if <1, which can help in the control of smoking. Motivated from this research soon, the authors will extent the results to propose new mathematical models for the smoking epidemic in the form of fractional stochastic modeling. Especially, will investigate the effective strategies for control smoking throughout the world.

Originality/value
This study is helpful in the control of smoking throughout the world.
A rotating superellipse inside a hexagonalshaped cavity suspended by nano-encapsulated phase change materials based on the ISPH method
Authors: Raizah Zehba , Aly Abdelraheem M. 
Published: August 2021

Purpose
The purpose of this paper is to perform numerical simulations based on the incompressible smoothed particle hydrodynamics (ISPH) method for thermo-diffusion convection in a hexagonal-shaped cavity saturated by a porous medium and suspended by a nano-encapsulated phase change material (NEPCM). Here, the solid particles are inserted into a phase change material to enhance its thermal performance.

Design/methodology/approach
Superellipse rotated shapes with variable lengths are embedded inside a hexagonal-shaped cavity. These inner shapes are rotated around their center by a uniform circular velocity and their conditions are positioned at high temperature and concentration. The controlling equations in a non-dimensional form were analyzed by using the ISPH method. At first, the validation of the ISPH results is performed. Afterward, the implications of a fusion temperature, lengths/types of the superellipse shapes, nanoparticles parameter and time parameter on the phase change heat transfer, isotherms, isoconcentration and streamlines were addressed.

Findings
The achieved simulations indicated that the excess in the length of an inner superellipse shape augments the temperature, concentration and maximum of the streamlines in a hexagonal-shaped cavity. The largest values of mean Nusselt number are attained at the inner rhombus shape with convex (n = 1.5) and the largest values of mean Sherwood number are attained at the inner rectangle shape with rounded corners (n = 4).

Originality/value
The ISPH method is developed to emulate the influences of the uniform rotation of the novel geometry shapes on heat/mass transport inside a hexagonal-shaped cavity suspended by NEPCM and saturated by porous media.
Service robots and COVID-19: exploring perceptions of prevention efficacy at hotels in generation Z
Authors: Romero Jaime , Lado Nora 
Published: August 2021

Purpose
COVID-19 is expected to enhance hospitality robotization because frontline robots facilitate social distancing, lowering contagion risk. Investing in frontline robots emerges as a solution to recover customer trust and encourage demand. However, we ignore how customers perceive these initiatives and, therefore, their efficacy. Focusing on robot employment at hotels and on Generation Z customers, this study aims to analyze guests’ perceptions about robots’ COVID-19 prevention efficacy and their impact on booking intentions.

Design/methodology/approach
This study tests its hypotheses combining an experimental design methodology with partial least squares. Survey data from 711 Generation Z individuals in Spain were collected in 2 periods of time.

Findings
Generation Z customers consider that robots reduce contagion risk at hotels. Robot anthropomorphism increases perceived COVID-19 prevention efficacy, regardless of the context where the robots are used. Robots’ COVID-19 prevention efficacy provokes better attitudes and higher booking intentions.

Research limitations/implications
The sampling method used in this research impedes this study’s results generalization. Further research could replicate this study using random sampling methods to ensure representativeness, even for other generational cohorts.

Practical implications
Employing robots as a COVID-19 prevention measure can enhance demand, especially if robots are human-like. Hoteliers need to communicate that robots can reduce contagion risk, particularly in markets more affected by COVID-19. Robots must be employed in low social presence contexts. Governments could encourage robotization by financially supporting hotels and publicly acknowledging its benefits regarding COVID-19 prevention.

Originality/value
This study combines preventive health, robotics and hospitality literature to study robot implementation during the COVID-19 pandemic, focusing on Generation Z guests – potential facilitators of robot diffusion.
Aligning organizational culture to enhance managerial effectiveness of academic leaders: an interface for employee engagement and retention
Authors: Tyagi Navneesh 
Published: August 2021

PurposeThe purpose of this paper is to measure the impact of organizational culture on managerial effectiveness of academic leaders to enhance employee engagement and retention in higher educational institutions. This study utilizes “Social Exchange Theory (SET)” as a theoretical lens to clarify the phenomena.Design/methodology/approachThis study uses an exploratory cum descriptive research design. Data collected via a structured questionnaire was analyzed and interpreted through structural equation modeling.FindingsOrganizational culture is found to have a significantly positive impact on managerial effectiveness. The findings also delineate a positive influence of managerial effectiveness on employee engagement and employee retention.Research limitations/implicationsThis study provides insights into the cultural neuances and subtleties of how organizational culture influences managerial effectiveness of institutional leaders. This has a direct bearing upon work engagement and retention of employees. Therefore if leaders focus on organizational culture they will succeed in creating a productive and healthier workplace for their employees. This study is also addressing the strategic concern of sustainability in higher educational institutions through employee engagement and retention.Originality/valueIt is an original work based on primary data to bridge the research gap concerning the prevalent OC shaping ME in Indian higher educational context. It also enriches understanding about alignment of cultural dimensions towards achieving work engagement, and retention of employees through managerial effectiveness of leaders in higher education institutions.
Modelling housing market fundamentals and the response to economic and political events: empirical evidence from Kuwait
Authors: Alfalah Abdullah , D’Arcy Eamonn , Heinig Steffen , Stevenson Simon 
Published: August 2021

Purpose
The purpose of this paper is to examine the sensitivity of the Kuwait housing market to major local and regional geo-political and economic events.

Design/methodology/approach
This paper examines the market dynamics of the housing market in Kuwait. Kuwait provides an interesting market to consider owing to its position as a major oil producer, its sensitivity to geo-political events and its unusual demographic characteristics.

Findings
The error-correction model highlights that market is relatively volatile, with evidence of mean-reverting behaviour. Only when the data is smoothed are their more consistent findings with respect to underlying fundamentals. This paper also examines the response of the market to seven regional and local events. Of particular interest is that the one event that results in a consistent significant response is domestic legislation directly concerned with housing. This has a far greater impact than local or regional geo-political events.

Originality/value
Very few papers have considered how economic and political shocks directly impact housing markets using an event study approach. Given its geographic location and also its economic dependence on oil, Kuwait is an interesting market to consider.
Evaluating innovation capability of Chinese listed companies based on comprehensive methods
Authors: Hu Yanrong , Liu Hongjiu 
Published: August 2021

Purpose
This paper aims to evaluate innovation capability of companies based on comprehensive methods.

Design/methodology/approach
This paper used principal component analysis (PCA), kernel principal component analysis (KPCA) and principal component cluster (PCC) analysis to analyze the listed companies’ innovation capability. On these bases, mean method, Borda method, Copeland method, alienation coefficient method and fuzzy Borda method were used separately for the comprehensive evaluation.

Findings
The results show that the comprehensive evaluation can overcome the shortage of the single method and improve the reliability of the innovation ability evaluation. In addition, the method also reveals that the innovation ability of the listed companies is closely related to the innovation investment and their industry and further regional economic development level of each province (city and area).

Originality/value
This paper uses PCA, KPCA and PCC to evaluate and study their innovation ability. On the basis of these, five methods (mean method, Copeland method, Borda method, divorced coefficient method and fuzzy Borda method) are applied respectively to combine the sort results of PCA, KPCA and PCC. The results show that combination methods have better theoretical and practical significance for innovation ability.
Dynamic prediction of Indian stock market: an artificial neural network approach
Authors: Goel Himanshu , Singh Narinder Pal 
Published: August 2021

Purpose
Artificial neural network (ANN) is a powerful technique to forecast the time series data such as the stock market. Therefore, this study aims to predict the Indian stock market closing price using ANNs.

Design/methodology/approach
The input variables identified from the literature are some macroeconomic variables and a global stock market factor. The study uses an ANN with Scaled Conjugate Gradient Algorithm (SCG) to forecast the Bombay Stock Exchange (BSE) Sensex.

Findings
The empirical findings reveal that the ANN model is able to achieve 93% accuracy in predicting the BSE Sensex closing prices. Moreover, the results indicate that the Morgan Stanley Capital International world index is the most important variable and the index of industrial production is the least important in predicting Sensex.

Research limitations/implications
The findings of the study have implications for the investors of all categories such as foreign institutional investors, domestic institutional investors and investment houses.

Originality/value
The novelty of this study lies in the fact that there are hardly any studies that use ANN to forecast the Indian stock market using macroeconomic indicators.