bluuebunny/crossref_metadata_2025_split huggingface dataset:
Social media intention mining for sustainable information systems: categories, taxonomy, datasets and challenges
Authors: Rashid Ayesha , Farooq Muhammad Shoaib , Abid Adnan , Umer Tariq , Bashir Ali Kashif , Zikria Yousaf Bin 
Published: April 2021

AbstractIntention mining is a promising research area of data mining that aims to determine end-users’ intentions from their past activities stored in the logs, which note users’ interaction with the system. Search engines are a major source to infer users’ past searching activities to predict their intention, facilitating the vendors and manufacturers to present their products to the user in a promising manner. This area has been consistently getting pertinence with an increasing trend for online purchasing. Noticeable research work has been accomplished in this area for the last two decades. There is no such systematic literature review available that provides a comprehensive review in intension mining domain to the best of our knowledge. This article presents a systematic literature review based on 109 high-quality research papers selected after rigorous screening. The analysis reveals that there exist eight prominent categories of intention. Furthermore, a taxonomy of the approaches and techniques used for intention mining have been discussed in this article. Similarly, six important types of data sets used for this purpose have also been discussed in this work. Lastly, future challenges and research gaps have also been presented for the researchers working in this domain.
A Dynamic Oligopoly with Price Stickiness and Risk-Averse Agents
Authors: Valentini Edilio , Vitale Paolo 
Published: April 2021

AbstractIn this paper we present a dynamic discrete-time model that allows to investigate the impact of risk-aversion in an oligopoly characterized by a homogeneous non-storable good, sticky prices and uncertainty. The continuous-time limit of our formulation nests the classical dynamic oligopoly model with sticky prices by Fershtman and Kamien (Econometrica 55:1151–1164, 1987) and extends it by accommodating uncertainty and risk-aversion. We show that in the continuous-time limit of our infinite horizon formulation the optimal production strategy and the consequent equilibrium price are, respectively, directly and inversely related to the degrees of uncertainty and risk-aversion. However, the effect of uncertainty and risk-aversion crucially depends on price stickiness since, when prices can adjust instantaneously, the steady state equilibrium in our model with uncertainty and risk-aversion collapses to Fershtman and Kamien’s analogue.
A Natural Polymer Captor for Immobilizing Polysulfide/Polyselenide in Working Li–SeS2 Batteries
Authors: Zhang Yin , Wang Menglei , Guo Yi , Huang Lingzhi , Wang Boya , Wei Yunhong , Jing Peng , Zhang Yueying , Zhang Yun , Wang Qian , Sun Jingyu , Wu Hao 
Published: April 2021

AbstractSeS2 has become a promising cathode material owing to its enhanced electrical conductivity over sulfur and higher theoretical specific capacity than selenium; however, the working Li–SeS2 batteries have to face the practical challenges from the severe shuttling of soluble dual intermediates of polysulfide and polyselenide, especially in high-SeS2-loading cathodes. Herein, a natural organic polymer, Nicandra physaloides pectin (NPP), is proposed to serve as an effective polysulfide/polyselenide captor to address the shuttling issues. Informed by theoretical calculations, NPP is competent to provide a Lewis base-based strong binding interaction with polysulfides/polyselenides via forming lithium bonds, and it can be homogeneously deposited onto a three-dimensional double-carbon conductive scaffold to finally constitute a polysulfide/polyselenide-immobilizing interlayer. Operando spectroscopy analysis validates the enhanced polysulfide/polyselenide trapping and high conversion efficiency on the constructed interlayer, hence bestowing the Li–SeS2 cells with ultrahigh rate capability (448 mAh g−1 at 10 A g−1), durable cycling lifespan (≈ 0.037% capacity attenuation rate per cycle), and high areal capacity (> 6.5 mAh cm−2) at high SeS2 loading of 15.4 mg cm−2. Importantly, pouch cells assembled with this interlayer exhibit excellent flexibility, decent rate capability with relatively low electrolyte-to-capacity ratio, and stable cycling life even under a low electrolyte condition, promising a low-cost, viable design protocol toward practical Li–SeS2 batteries.
Environmentally Friendly and Multifunctional Shaddock Peel-Based Carbon Aerogel for Thermal-Insulation and Microwave Absorption
Authors: Gu Weihua , Sheng Jiaqi , Huang Qianqian , Wang Gehuan , Chen Jiabin , Ji Guangbin 
Published: April 2021

Highlights

The eco-friendly shaddock peel-derived carbon aerogels were prepared by a freeze-drying method.

Multiple functions such as thermal insulation, compression resistance and microwave absorption can be integrated into one material-carbon aerogel.

Novel computer simulation technology strategy was selected to simulate significant radar cross-sectional reduction values under real far field condition.

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Abstract
Eco-friendly electromagnetic wave absorbing materials with excellent thermal infrared stealth property, heat-insulating ability and compression resistance are highly attractive in practical applications. Meeting the aforesaid requirements simultaneously is a formidable challenge. Herein, ultra-light carbon aerogels were fabricated via fresh shaddock peel by facile freeze-drying method and calcination process, forming porous network architecture. With the heating platform temperature of 70 °C, the upper surface temperatures of the as-prepared carbon aerogel present a slow upward trend. The color of the sample surface in thermal infrared images is similar to that of the surroundings. With the maximum compressive stress of 2.435 kPa, the carbon aerogels can provide favorable endurance. The shaddock peel-based carbon aerogels possess the minimum reflection loss value (RLmin) of − 29.50 dB in X band. Meanwhile, the effective absorption bandwidth covers 5.80 GHz at a relatively thin thickness of only 1.7 mm. With the detection theta of 0°, the maximum radar cross-sectional (RCS) reduction values of 16.28 dB m2 can be achieved. Theoretical simulations of RCS have aroused extensive interest owing to their ingenious design and time-saving feature. This work paves the way for preparing multi-functional microwave absorbers derived from biomass raw materials under the guidance of RCS simulations.
A review of machine learning experiments in equity investment decision-making: why most published research findings do not live up to their promise in real life
Authors: Buczynski Wojtek , Cuzzolin Fabio , Sahakian Barbara 
Published: April 2021

AbstractThe numerical nature of financial markets makes market forecasting and portfolio construction a good use case for machine learning (ML), a branch of artificial intelligence (AI). Over the past two decades, a number of academics worldwide (mostly from the field of computer science) produced a sizeable body of experimental research. Many publications claim highly accurate forecasts or highly profitable investment strategies. At the same time, the picture of real-world AI-driven investments is ambiguous and conspicuously lacking in high-profile success cases (while it is not lacking in high-profile failures). We conducted a literature review of 27 academic experiments spanning over two decades and contrasted them with real-life examples of machine learning-driven funds to try to explain this apparent contradiction. The specific contributions our article will make are as follows: (1) A comprehensive, thematic review (quantitative and qualitative) of multiple academic experiments from the investment management perspective. (2) A critical evaluation of running multiple versions of the same models in parallel and disclosing the best-performing ones only (“cherry-picking”). (3) Recommendations on how to approach future experiments so that their outcomes are unambiguously measurable and useful for the investment industry. (4) An in-depth comparison of real-life cases of ML-driven funds versus academic experiments. We will discuss whether present-day ML algorithms could make feasible and profitable investments in the equity markets.
Ecological risk of heavy metal in agricultural soil and transfer to rice grains
Authors: Mahmud Upoma , Salam Md. Tareq Bin , Khan Abu Shamim , Rahman Md. Mizanur 
Published: April 2021

AbstractHigher accumulation of heavy metals in food grains is one of the leading problems for carcinogenic effects in the body. That’s why; scientists have taken this problem as a potential indicator for ensuring safe food. The present study was carried out to assess the ecological risk of heavy metals such as nickel, copper, arsenic, lead, and manganese in agricultural soil and transfer status to rice grain. Soil samples were collected from four agricultural fields at different times in the Dumuria Upazila under Khulna district in Bangladesh. Heavy metal concentration in soil extracts, irrigation water samples, and grain samples was determined by Atomic Absorption Spectrometer. Average metal concentrations in soil were calculated and compared with the reference value in soil. In most cases, heavy metals in agricultural soil (Ni: 61.73–94.52 mg/kg; Cu: 23.33–37.5 mg/kg; As: 7.53–19.63 mg/kg; Pb: 15.17–29.19 mg/kg; Mn: 322.98–478.45 mg/kg) were greater than the reference soil (Ni: 13.08–24.55 mg/kg; Cu: 10.35–13.28 mg/kg; As: 1.87–4.61 mg/kg; Pb: 4.88–8.27 mg/kg; Mn: 52.17–74.3 mg/kg). Overall risk index stated that the examined soils were at moderate risk of contamination. Transfer Factor of arsenic (0.018–0.032 mg/kg) and manganese (0.059–0.155 mg/kg) was higher from soil to rice grain. On the other hand, transfer factor of lead was found negligible that is a good sign of improvement. The findings of the study will be good documentation for planning, risk assessment, and decision-making by environmental managers in this region.
Can Hernia Sac to Abdominal Cavity Volume Ratio Predict Fascial Closure Rate for Large Ventral Hernia? Reliability of the Tanaka Score
Authors: Fafaj Aldo , Thomas Jonah , Zolin Samuel J. , de Figueiredo Sergio Mazzola Poli , Tastaldi Luciano , Liu Peter S. , Petro Clayton C. , Krpata David M. , Prabhu Ajita S. , Rosen Michael J. 
Published: April 2021

BACKGROUND:
The hernia sac to abdominal cavity volume ratio (VR) on abdominal CT was described previously as a way to predict which hernias would be less likely to achieve fascial closure. The aim of this study was to test the reliability of the previously described cutoff ratio in predicting fascial closure in a cohort of patients with large ventral hernias.

METHODS:
Patients who underwent elective, open incisional hernia repair of 18 cm or larger width at a single center were identified. The primary end point of interest was fascial closure for all patients. Secondary outcomes included operative details and abdominal wall-specific quality-of-life metrics. We used VR as a comparison variable and calculated the test characteristics (ie, sensitivity, specificity, and positive and negative predictive values).

RESULTS:
A total of 438 patients were included, of which 337 (77%) had complete fascial closure and 101 (23%) had incomplete fascial closure. The VR cutoff of 25% had a sensitivity of 76% (95% CI, 71% to 80%), specificity of 64% (95% CI, 54% to 74%), positive predictive value of 88% (95% CI, 83% to 91%), and negative predictive value of 45% (95% CI, 36% to 53%). The incomplete fascial closure group had significantly lower quality of life scores at 1 year (83.3 vs 52.5; p = 0.001), 2 years (85 vs 33.3; p = 0.003), and 3 years (86.7 vs 63.3; p = 0.049).

CONCLUSIONS:
In our study, the VR cutoff of 25% was sensitive for predicting complete fascial closure for patients with ratios below this threshold. Although there is a higher likelihood of incomplete fascial closure when VR is ≥ 25%, this end point cannot be predicted reliably. Additional studies should be done to study this ratio in conjunction with other hernia-related variables to better predict this important surgical end point.
Predictors of Remission and Relapse of Diabetes after Conventional Gastrectomy for Gastric Cancer: Nationwide Population-Based Cohort Study
Authors: Kwon Yeongkeun , Kwon Jin-Won , Kim Dohyang , Ha Jane , Park Shin-Hoo , Hwang Jinseub , Heo Yoonseok , Park Sungsoo 
Published: April 2021

BACKGROUND:
We investigated whether preoperative clinical parameters predict diabetes remission and relapse after conventional gastrectomy for cancer and whether postoperative weight changes influence diabetes remission and relapse.

STUDY DESIGN:
This study included 5,150 patients with diabetes who underwent gastrectomy for cancer from 2004 to 2014. Diabetes remission was defined in 3 ways, according to postoperative antidiabetic medication and fasting plasma glucose (FPG) levels. Diabetes relapse was defined as reinitiating antidiabetic medication among patients in diabetes remission.

RESULTS:
Six predictors (higher body mass index [BMI], total gastrectomy, younger age, FPG levels, number of oral hypoglycemic agents [OHAs], and no insulin use) of diabetes remission increased the likelihood of remission by >13-fold (odds ratio [OR], 13.67; 95% confidence interval [CI], 8.65-19.11). Three factors (younger age, lower FPG levels, and use of only 1 OHA) predicted a 58% decreased likelihood of diabetes relapse (hazard ratio, 0.42; 95% CI 0.35-0.48). The lowest interval of postoperative BMI decrease (<-20%) showed a >3-fold increased likelihood of diabetes remission than the highest interval (≥-5%; OR 3.14; 95% CI 2.08-4.75), independent of baseline BMI.

CONCLUSIONS:
Six variables (BMI, type of gastrectomy, age, FPG levels, number of OHAs used, and insulin use/non-use), and 3 variables (age, FPG levels, number of OHAs used) significantly predict diabetes remission and relapse after gastrectomy for cancer, respectively. Greater postoperative weight decrease may increase the likelihood of diabetes remission, independent of baseline weight. Our results may serve as a basis for the establishment of diabetes and weight management strategies after conventional gastrectomy for cancer.
Applying Machine Learning Across Sites: External Validation of a Surgical Site Infection Detection Algorithm
Authors: Zhu Ying , Simon Gyorgy J. , Wick Elizabeth C. , Abe-Jones Yumiko , Najafi Nader , Sheka Adam , Tourani Roshan , Skube Steven J. , Hu Zhen , Melton Genevieve B. 
Published: April 2021

BACKGROUND:
Surgical complications have tremendous consequences and costs. Complication detection is important for quality improvement, but traditional manual chart review is burdensome. Automated mechanisms are needed to make this more efficient. To understand the generalizability of a machine learning algorithm between sites, automated surgical site infection (SSI) detection algorithms developed at one center were tested at another distinct center.

STUDY DESIGN:
NSQIP patients had electronic health record (EHR) data extracted at one center (University of Minnesota Medical Center, Site A) over a 4-year period for model development and internal validation, and at a second center (University of California San Francisco, Site B) over a subsequent 2-year period for external validation. Models for automated NSQIP SSI detection of superficial, organ space, and total SSI within 30 days postoperatively were validated using area under the curve (AUC) scores and corresponding 95% confidence intervals.

RESULTS:
For the 8,883 patients (Site A) and 1,473 patients (Site B), AUC scores were not statistically different for any outcome including superficial (external 0.804, internal [0.784, 0.874] AUC); organ/space (external 0.905, internal [0.867, 0.941] AUC); and total (external 0.855, internal [0.854, 0.908] AUC) SSI. False negative rates decreased with increasing case review volume and would be amenable to a strategy in which cases with low predicted probabilities of SSI could be excluded from chart review.

CONCLUSIONS:
Our findings demonstrated that SSI detection machine learning algorithms developed at 1 site were generalizable to another institution. SSI detection models are practically applicable to accelerate and focus chart review.
Neurophysiological evidence of motor imagery training in Parkinson’s disease: a case series study
Authors: Lambert Kathryn J. M. , Singhal Anthony , Leung Ada W. S. 
Published: April 2021

AbstractBackground:Motor imagery (MI) has become an increasingly popular rehabilitation tool for individuals with motor impairments. However, it has been proposed that individuals with Parkinson’s Disease (PKD) may not benefit from MI due to impairments in motor learning.Objective:This case series study investigated the effects of a 4-week MI training protocol on MI ability in three male individuals with PKD, with an emphasis on examining changes in brain responses.Methods:Training was completed primarily at home, via audio recordings, and emphasized the imagination of functional tasks. MI ability was assessed pre and post-training using subjective and objective imagery questionnaires, alongside an electroencephalographic (EEG) recording of a functional MI task. EEG analysis focused on the mu rhythm, as it has been proposed that suppression in the mu rhythm may reflect MI success and motor learning. Previous research has indicated that mu suppression is impaired in individuals with PKD, and may contribute to the disease’s associated deficits in motor learning.Results:Following training, all three participants improved in MI accuracy, but reported no notable improvements in MI vividness. Greater suppression in the mu rhythm was also exhibited by all three participants post-training.Conclusion:These results suggest the participants learned from the training protocol and that individuals with PKD are responsive to MI training. Further research on a larger scale is needed to verify the findings and determine if this learning translates to improvements in motor function.
Cost-Effective Cranioplasty Utilizing 3D Printed Molds: A Canadian Single-Center Experience
Authors: Lannon Melissa , Algird Almunder , Alsunbul Waleed , Wang Bill Hao 
Published: April 2021

ABSTRACT:Background:Cranioplasty is a commonly performed neurosurgical procedure used to repair defects of the cranial vault. For large defects, 3D printing allows for the creation of patient-specific synthetic cranioplasties. Although these implants provide excellent cosmetic results for patients, costs are quite high. This makes their routine use challenging in the current Canadian healthcare environment. The purpose of this study is to report our experience with a novel, cost-effective method for cranioplasty using desktop 3D printers to manufacture patient-specific molds to aid in the shaping of polymethyl methacrylate (PMMA) cranioplasty intraoperatively.Methods:A retrospective review of patients who underwent cranioplasty utilizing 3D printed custom molds was conducted at a single center between 2018 and 2020. Either a two-piece self-align or open-air mold was utilized. Material cost, as well as demographic, clinical, and radiologic data, was reviewed. A five-point ordinance scale was used to evaluate patient satisfaction with cosmesis.Results:Four patients had previous craniectomies with infected bone flaps, 2 patients had significant bony destruction from tumor invasion, and 1 patient had bone flap resorption. Three patients underwent an open-air mold technique with a Ti-mesh/PMMA-combined implant. The remaining 4 patients underwent two-piece mold with PMMA-only implant. All patients had ‘Good’ to ‘Excellent’ cosmetic outcome with one post-operative acute subdural hematoma and one post-operative infection. Two-piece mold resulted in improved cosmetic outcome and cost savings.Conclusions:3D printing can be used in a cost-effective manner to deliver good cranioplasty cosmesis. Wider adoption of this technique can result in significant healthcare cost savings without compromising patient outcome.
Factors That Affect Emergency Responder Wellbeing: Considerations for Public Health Responders
Authors: Gebreyesus Tsega , Cohen Julia , Rasulnia Bobby , Kuwabara Sachiko 
Published: April 2021

AbstractPurpose:The purpose of this study is to identify key risk factors that could negatively affect public health emergency responders’ health and wellbeing. We seek to use this information to provide recommendations and strategies to mitigate such risks.Design/Methodology/Approach:A narrative review of the peer-reviewed literature on wellbeing of military personnel and other responders was conducted. Data was grouped and categorized according to overarching domains.Findings:Factors associated with wellbeing were categorized into 5 domains: (1) demographics; (2) mental health concerns; (3) social networks; (4) work environment; and (5) postdeployment life. The strategies identified to promote wellbeing included mental health assessments, preparedness trainings, debriefs in the field, postdeployment debriefs, resources in the field, and further postdeployment decompression strategies.Originality/Value:This study provides a unique understanding of the risk factors associated with poor health and wellbeing outcomes in public health emergency response work by extending the body of knowledge that focuses on other types of emergency and military response.
Deception-Based Hermeneutical Injustice
Authors: Luzzi Federico 
Published: April 2021

AbstractI argue that patients who suffer genital surgery to ‘disambiguate’ their sexual anatomy, a practice labelled ‘intersex genital mutilation’ (IGM) by intersex advocates, can be understood as victims of hermeneutical injustice in the sense elaborated by Miranda Fricker. This claim is clarified and defended from two objections. I further argue that a particular subset of cases of IGM-based hermeneutical injustice instantiate a novel form of hermeneutical injustice, which I calldeception-based hermeneutical injustice.I highlight how this differs from central types of hermeneutical injustice in the literature and trace its harms.
Rethinking Epistemic Appropriation
Authors: Podosky Paul-Mikhail Catapang 
Published: April 2021

AbstractEmmalon Davis has offered an insightful analysis of an under-theorized form of epistemic oppression calledepistemic appropriation.This occurs when an epistemic resource developed within marginalized situatedness gains inter-communal uptake, but the author of the epistemic resource is unacknowledged. In this paper, I argue that Davis's definition of epistemic appropriation is not exhaustive. In particular, she misses out on explaining cases of epistemic appropriation in which an intra-communal epistemic resource isobscuredthrough inter-communal uptake. Being attentive to this form of epistemic appropriation allows us to identify unique forms of epistemic oppression that emerge as a result of socially maintained active ignorance.