bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improved cost-sensitive multikernel learning support vector machine algorithm based on particle swarm optimization in pulmonary nodule recognition
Authors: Li Yang , Chang Jiayue , Tian Ying 
Published: January 2022

AbstractIn the lung computer-aided detection (Lung CAD) system, the region of interest (ROI) of lung nodules has more false positives, making the imbalance between positive and negative (true positive and false positive) samples more likely to lead to misclassification of true positive nodules, a cost-sensitive multikernel learning support vector machine (CS-MKL-SVM) algorithm is proposed. Different penalty coefficients are assigned to positive and negative samples, so that the model can better learn the features of true positive nodules and improve the classification effect. To further improve the detection rate of pulmonary nodules and overall recognition accuracy, a score function named F-new based on the harmonic mean of accuracy (ACC) and sensitivity (SEN) is proposed as a fitness function for subsequent particle swarm optimization (PSO) parameter optimization, and a feasibility analysis of this function is performed. Compared with the fitness function that considers only accuracy or sensitivity, both the detection rate and the recognition accuracy of pulmonary nodules can be improved by this new algorithm. Compared with the grid search algorithm, using PSO for parameter search can reduce the model training time by nearly 20 times and achieve rapid parameter optimization. The maximum F-new obtained on the test set is 0.9357 for the proposed algorithm. When the maximum value of F-new is achieved, the corresponding recognition ACC is 91%, and SEN is 96.3%. Compared with the radial basis function in the single kernel, the F-new of the algorithm in this paper is 2.16% higher, ACC is 1.00% higher and SEN is equal. Compared with the polynomial kernel function in the single kernel, the F-new of the algorithm is 3.64% higher, ACC is 1.00% higher and SEN is 7.41% higher. The experimental results show that the F-new, ACC and SEN of the proposed algorithm is the best among them, and the results obtained by using multikernel function combined with F-new index are better than the single kernel function. Compared with the MKL-SVM algorithm of grid search, the ACC of the algorithm in this paper is reduced by 1%, and the results are equal to those of the MKL-SVM algorithm based on PSO only. Compared with the above two algorithms, SEN is increased by 3.71% and 7.41%, respectively. Therefore, it can be seen that the cost sensitive method can effectively reduce the missed detection of nodules, and the availability of the new algorithm can be further verified.
Mit Herz und Verstand: Rolle der internen Kommunikation für die Etablierung neuer Nachhaltigkeitsstrategien
Authors: Strottner Lea , Huck-Sandhu Simone 
Published: January 2022

ZusammenfassungDie Erwartungen vieler Stakeholder an unternehmerische Nachhaltigkeit und Verantwortung sind gestiegen. In der Folge begeben sich Unternehmen in einen Transformationsprozess und verankern Nachhaltigkeitsziele und -strategie in ihrer Unternehmensstrategie. Dies bringt in der Regel einen fundamentalen Veränderungsprozess für die Mitarbeitenden mit sich. Die neue Nachhaltigkeitsorientierung intern durch- und umzusetzen bedeutet u. a., dass die interne Veränderungskommunikation die Nachhaltigkeitsthematik aktiv zu vermitteln und den Veränderungsprozess kommunikativ zu begleiten hat. Ziel dieses Beitrags ist es, Grundlagen, Rahmenbedingungen und Erfolgsfaktoren der internen Veränderungskommunikation im Zusammenhang mit der Etablierung einer Nachhaltigkeitsstrategie im Unternehmen zu analysieren und deren kommunikative Implementierung und Institutionalisierung zu beleuchten. Im Rahmen einer qualitativen Studie wurden Leitfadengespräche mit Verantwortlichen für interne Nachhaltigkeitskommunikation in Großunternehmen geführt. Die Ergebnisse bestätigen, dass interne Kommunikation unter bestimmten Rahmenbedingungen Treiber für eine neue, nachhaltigkeitsorientiere Unternehmensstrategie und die damit einhergehenden Wandlungsprozesse sein kann. Es deuten sich aber auch Besonderheiten an, die – anders als in allgemeinen Veränderungsprozessen – bei der Etablierung von Nachhaltigkeitsstrategien qualitativ wichtiger zu sein scheinen. Um die neue Strategie kognitiv und affektiv in den Köpfen und Herzen der Mitarbeitenden zu verankern, bedarf es einer systematischen Veränderungskommunikation, die über Werte, Kultur und kommunikatives Sensegiving Nachhaltigkeit verankert. Dazu kommen spezifische Kommunikationsmodi, -formate und -medien zum Einsatz. Für die Forschung liefert der Beitrag explorative Hinweise an einer bislang kaum beleuchteten Nahtstelle von interner Veränderungs- und Nachhaltigkeitskommunikation. Für die Unternehmenspraxis identifiziert er Rahmenbedingungen und Herausforderungen und zeigt auf, wie Ziele, Aufgabe und Maßnahmen der Kommunikationsarbeit für die Etablierung neuer Nachhaltigkeitsstrategien umgesetzt werden können.
Mining rules of decision-making for fleet composition under market uncertainty using a genetic algorithm
Authors: Hiekata Kazuo , Wanaka Shinnosuke , Okubo Yoshinori 
Published: January 2022

AbstractThis study proposes a method for determining decision-making rules on fleet composition that are effective from a perspective of profitability in the shipping industry, where there are several market uncertainties such as fuel prices, freight rates, exchange rate, transportation demand, world transportation capacity, and ship price. A simulator is used to calculate the revenue of the fleet composition based on the market scenario. Using this to optimize the buying and selling behavior of ships, decision-making rules regarding fleet composition can be determined. The rules are expressed as a vector, and a genetic algorithm (GA) is used for optimization. As a case study, the method was applied to container ships operating between Asia and Europe. The simulation revealed optimal decision-making rules. Moreover, a controlled experiment was conducted to validate the effectiveness of the rules. Participants were randomly divided into two groups: those with rules and those without rules, and they were asked to perform buying and selling behavior in a simulated environment. By comparing these groups’ profits, it is validated that the rules discovered by the method are useful because they encourage decision-making from a long-term perspective.
The impact of hormone receptor on the clinical outcomes of HER2-positive breast cancer: a population-based study
Authors: Han Yiqun , Wu Yun , Xu Hangcheng , Wang Jiayu , Xu Binghe 
Published: January 2022

Abstract
Background
To investigate the impact of hormone receptor (HR) on the clinicopathological characteristics and prognosis of human epidermal growth factor receptor 2 (HER2)-positive breast cancer.

Methods
Using the Surveillance, Epidemiology, and End Results database, we enrolled patients diagnosed with HER2-positive breast cancer between 2010 and 2016, which were successively assessed for eligibility and categorized into HR + /HER2 + and HR-/HER2 + subgroups. Clinicopathological characteristics were undergone comparative analyses with the baseline distinctions calibrated by propensity score matching, while the survival outcomes were compared using Kaplan–Meier method with log-rank tests.

Results
A total of 46,803 HER2-positive breast cancer patients were identified, of which 32,919 individuals were HR + /HER2 + subtype and 13,884 individuals were HR-/HER2 + subtype, respectively. Comparatively, HR + /HER2 + breast cancer presented a lower histological grade, a smaller tumor size, a lower nodal involvement, and a lower rate of de novo stage IV disease. Substantial heterogeneity was detected in the metastatic patterns of organ-specific involvement between the two subgroups with initial metastasis. Overall, patients with HR + /HER2 + tumors had increasingly favorable prognosis in terms of overall survival and breast cancer-specific survival than patients with the HR−/HER2 + subtype. However, this kind of tendency exhibited disparities associated with HR-specific subtypes based on estrogen receptor (ER) and progesterone receptor (PgR) status, in which ER−/PgR + tended to present the worst prognosis.

Conclusion
This study revealed profound heterogeneity associated with HR status in the clinical outcomes of HER2-positive breast cancer regarding clinicopathological features, metastatic patterns, and prognosis. Prospective studies to optimize therapeutic strategies for HER2-positive subgroups are warranted.
Metabolomics of Synovial Fluid and Infrapatellar Fat Pad in Patients with Osteoarthritis or Rheumatoid Arthritis
Authors: Nieminen Petteri , Hämäläinen Wilhelmiina , Savinainen Juha , Lehtonen Marko , Lehtiniemi Saara , Rinta-Paavola Juho , Lehenkari Petri , Kääriäinen Tommi , Joukainen Antti , Kröger Heikki , Paakkonen Tommi , Mustonen Anne-Mari 
Published: January 2022

AbstractOsteoarthritis (OA) and autoimmune-driven rheumatoid arthritis (RA) are inflammatory joint diseases with complex and insufficiently understood pathogeneses. Our objective was to characterize the metabolic fingerprints of synovial fluid (SF) and its adjacent infrapatellar fat pad (IFP) obtained during the same surgical operation from OA and RA knees. Non-targeted metabolite profiling was performed for 5 non-inflammatory trauma controls, 10 primary OA (pOA) patients, and 10 seropositive RA patients with high-resolution mass spectrometry-based techniques, and metabolites were matched with known metabolite identities. Groupwise differences in metabolic features were analyzed with the univariate Welch’st-test and the multivariate linear discriminant analysis (LDA) and principal component analysis (PCA). Significant discrimination of metabolite profiles was discovered by LDA for both SF and IFP and by PCA for SF based on diagnosis. In addition to a few drug-derived substances, there were 16 and 13 identified metabolites with significant differences between the diagnoses in SF and IFP, respectively. The pathways downregulated in RA included androgen, bile acid, amino acid, and histamine metabolism, and those upregulated included biotin metabolism in pOA and purine metabolism in RA and pOA. The RA-induced downregulation of androgen and bile acid metabolism was observed for both SF and IFP. The levels of 11 lipid metabolites, mostly glycerophospholipids and fatty acid amides, were also altered by these inflammatory conditions. The identified metabolic pathways could be utilized in the future to deepen our understanding of the pathogeneses of OA and RA and to develop not only biomarkers for their early diagnosis but also therapeutic targets.
Efficient query processing techniques for next-page retrieval
Authors: Mackenzie Joel , Petri Matthias , Moffat Alistair 
Published: January 2022

AbstractIn top-k ranked retrieval the goal is to efficiently compute an ordered list of the highest scoring k documents according to some stipulated similarity function such as the well-known BM25 approach. In most implementation techniques a min-heap of size k is used to track the top scoring candidates. In this work we consider the question of how best to retrieve the second page of search results, given that a first page has already been computed; that is, identification of the documents at ranks $$k+1$$

k
+
1

to 2k for some query. Our goal is to understand what information is available as a by-product of the first-page scoring, and how it can be employed to accelerate the second-page computation, assuming that the second-page of results is required for only a fraction of the query load. We propose a range of simple, yet efficient, next-page retrieval techniques which are suitable for accelerating Document-at-a-Time mechanisms, and demonstrate their performance on three large text collections.
Heuristic based approach for short term production planning in highly automated customer oriented pallet production
Authors: Kaltenbrunner Matthias , Huka Maria Anna , Gronalt Manfred 
Published: January 2022

AbstractWooden pallets are commonly used as load carriers in many industrial and logistic applications. This article investigates and formalizes the production planning for a highly automated but customized pallet production and provides a solution approach. For completing a specific pallet, the required boards must be cut and stacked in advance to meet the demand at the assembly line. The arising planning problem for producing the required boards consists of both a cutting stock and a constraining open stack problem. Further, both the changeover of raw material at the cutting process and the number of fully automated internal storages, for stacked boards, are restricted. The proposed solution heuristic aims at minimizing the cutting waste. Additionally, feasibility with regard to the buffers is tested using discrete event simulation. Different approaches to generate, select and sequence the cutting patterns are investigated.
Performance of implicit A-stable time integration methods for multibody system dynamics
Authors: Zhang Huimin , Zhang Runsen , Zanoni Andrea , Masarati Pierangelo 
Published: January 2022

AbstractThis paper illustrates the performance of several representative implicit A-stable time integration methods with algorithmic dissipation for multibody system dynamics, formulated as a set of mixed implicit first-order differential and algebraic equations. The integrators include the linear multi-step methods with two to four steps, the single-step reformulations of the linear multi-step methods, and explicit first-stage, singly diagonally-implicit Runge–Kutta methods. All methods are implemented in the free, general-purpose multibody solver MBDyn. Their formulations and implementation are presented. According to the comparison from linear analysis and numerical experiments, some general conclusions on the selection of integration schemes and their implementation are obtained. Although all of these methods can predict reasonably accurate solutions, the specific advantages that each of them has in different situations are discussed.
Education, social identity and self-employment over time: evidence from a developing country
Authors: Tamvada Jagannadha Pawan , Shrivastava Mili , Mishra Tapas Kumar 
Published: January 2022

AbstractWhile the extant literature suggests that an individual’s occupational choice depends on the level of economic development, little is known about how the dynamics of education and social identity impact self-employment choice over time in a developing country setting. The pseudo-panel regression results presented here suggest that higher education decreases the likelihood of individuals’ choice of self-employment over time in India, but increases it in most developed cohorts. Such transitional dynamics are more prominent amongst individuals who belong to historically determined backward classes. Furthermore, the results suggest sectoral differences in self-employment choice—individuals with higher education and wealth have a greater likelihood of transiting into self-employment over time in agriculture while similar individuals in non-agriculture exit self-employment. In both sectors, however, education moderates the impact of social identity on self-employment choice. The paper underscores the need for policy shifts towards entrepreneurship along the path of economic development.
Introducing the Disease Outbreak Resilience Index (DORI) Using the Demographic and Health Surveys Data from sub-Saharan Africa
Authors: Koomson Isaac , Okumu Moses , Ansong David 
Published: January 2022

AbstractAlthough most studies on disease emergencies underscore the need for household readiness for shocks associated with disease outbreaks, no study to date has provided a holistic measure for profiling households based on their readiness toward disease outbreaks. This paper introduces a novel Disease Outbreak Resilience Index (DORI) using a multidimensional approach that draws on the Alkire-Foster methodology. DORI measures disease outbreak resilience in four dimensions: (a) water and hygiene, (b) physical distancing, (c) energy and communication, and (d) economic security and resilience. The paper details the development of DORI and its use by presenting findings from ten countries in sub-Saharan Africa using data from the Demographic and Health Surveys (DHS) program. In addition to serving as a resilience index, we illustrate how DORI can be used to produce a disease outbreak vulnerability index (DOVI). As a versatile index, the indicators under each dimension can be tailored to meet country- and region-specific contexts based on indicators appropriate to each context.
Deep Learning Model for Wind Forecasting: Classification Analyses for Temporal Meteorological Data
Authors: Harbola Shubhi , Coors Volker 
Published: January 2022

AbstractThis paper proposes a multiple CNN architecture with multiple input features, combined with multiple LSTM, along with densely connected convolutional layers, for temporal wind nature analyses. The designed architecture is called Multiple features, Multiple Densely Connected Convolutional Neural Network with Multiple LSTM Architecture, i.e. MCLT. A total of 58 features in the input layers of the MCLT are designed using wind speed and direction values. These empirical features are based on percentage difference, standard deviation, correlation coefficient, eigenvalues, and entropy, for efficiently describing the wind trend. Two successive LSTM layers are used after four densely connected convolutional layers of the MCLT. Moreover, LSTM has memory units that utilise learnt features from the current as well as previous outputs of the neurons, thereby enhancing the learning of patterns in the temporal wind dataset. Densely connected convolutional layer helps to learn features of other convolutional layers as well. The MCLT is used to predict dominant speed and direction classes in the future for the wind datasets of Stuttgart and Netherlands. The maximum and minimum overall accuracies for dominant speed prediction are 99.1% and 94.9%, (for Stuttgart) and 99.9% and 97.5% (for Netherlands) and for dominant direction prediction are 99.9% and 94.4% (for Stuttgart) and 99.6% and 96.4% (for Netherlands), respectively, using MCLT with 58 features. The MCLT, therefore, with multiple features at different levels, i.e. the input layers, the convolutional layers, and LSTM layers, shows promising results for the prediction of dominant speed and direction. Thus, this work is useful for proper wind utilisation and improving environmental planning. These analyses would also help in performing Computational Fluid Dynamics (CFD) simulations using wind speed and direction measured at a nearby meteorological station, for devising a new set of appropriate inflow boundary conditions.
Therapy With Local Anesthetics to Treat Vulvodynia. A Pilot Study
Authors: Weinschenk Stefan , Benrath Justus , Kessler Eugen , Strowitzki Thomas , Feisst Manuel 
Published: January 2022

Abstract

Introduction
Vulvodynia (chronic vulvar pain) is a sexually debilitating disorder with a prevalence of ∼10%.

Aim
To investigate the effectiveness of therapy with local anesthetics (TLA) in women with severe vulvodynia, we conducted a prospective, non-controlled observational study.

Methods
45 patients with severe chronic vulvodynia (primary and secondary vulvodynia, 0–10 numeric analogue scale (NAS) ≥6, median 7.9, duration ≥6 months, median 65.2 months) in an outpatient practice in Germany were treated with TLA in 3–12 sessions using procaine 1% as local anesthetic. Effectiveness was analyzed with Wilcoxon signed rank tests and Wilcoxon rank sum tests.

Outcomes
Therapeutic success as a reduction of pain to ≤4 NAS lasting for ≥6 months after end of therapy.

Results
TLA successfully reduced vulvodynia in 36 of 45 patients (80 %, responders). The NAS reduction was from 7.9 to 2.4 (P &lt; .001). Even patients denominated as non-responders experienced a significant reduction in NAS (P = .03). In responders, long-term success was observed for 6.8–125 months (median 24.1 months). No adverse events occurred.

Clinical Translation
A promising new treatment for a hard-to-treat chronic female pain disorder.

Strengths and Limitations
Limitation: Monocentric, non-controlled observational design; Strength: the high number of patients treated.

Conclusion
The high success rate of TLA in this investigation offers new perspectives on the etiology of vulvodynia as a complex pain syndrome affecting several nerves of the pelvic floor, and also provides early insight into the effectiveness of TLA in women with vulvodynia.
Profiling third-level student mental health: findings from My World Survey 2
Authors: Mahon Ciara , Fitzgerald Amanda , O’Reilly Aileen , Dooley Barbara 
Published: January 2022

AbstractObjectives:This study aimed to identify risk and protective factors for mental health across student cohorts to guide mental health provision.Methods:Cross-sectional data from the My World Survey 2-Post Second Level (MWS2-PSL) were used. The sample consisted of N = 9935 students (18–65 years) from 12 third-level institutions (7 out of 7 universities and 5 out of 14 Institute of Technologies (IoTs)) across Ireland. Key outcomes of interest were depression, anxiety and suicidality. Risk factors included drug/alcohol use, risky sexual behaviours and exposure to stressors. Protective factors included coping strategies, help-seeking, resilience, self-esteem, life satisfaction, optimism and social support. These factors were profiled by degree type (undergraduate, postgraduate taught, postgraduate research), access route, and institution type (IoT, university). Chi-square tests of Independence and one-way ANOVAs compared groups on key risk and protective factors.Results:A total 71% of respondents were female, 85% were aged 23 or under and there was a 2.2% response rate in IoTs versus 10.6% in university students. Undergraduates demonstrated higher levels of depression, anxiety, self-harm and suicidal ideation than postgraduates. Undergraduates showed higher risk and lower protective factors than postgraduates. Students attending Institutes of Technology reported higher levels of depression and anxiety, lower protective and higher risk factors than university students.Conclusion:In this sample of students, undergraduates, especially those attending Institutes of Technology, were at increased risk of mental health difficulties. Findings suggest the need to tailor interventions to meet cohort needs, and consider the differing vulnerabilities and strengths across student cohorts. Due to limitations of this study, such as selection bias, further research is warranted.