bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Co-Production of Service: Modeling Services in Contact Centers Using Hawkes Processes
Authors: Daw Andrew , Castellanos Antonio , Yom-Tov Galit B. , Pender Jamol , Gruendlinger Leor 
Published: June 2024

In customer support contact centers, every service interaction involves a messaging dialogue between a customer and an agent; together, they exchange information, solve problems, and collectively co-produce the service. Because the service progression is shaped by the history of conversation thus far, we propose a bivariate marked Hawkes process cluster model of the customer-agent interaction. To evaluate our stochastic model of service, we apply it to an industry contact center data set containing nearly 5 million messages. Through both a novel residual analysis comparison and several Monte Carlo goodness-of-fit tests, we show that the Hawkes cluster model indeed captures dynamics at the heart of the service and surpasses classic models that do not incorporate the service history. Furthermore, in an entirely data-driven simulation, we demonstrate how this history-dependent model can be leveraged operationally to inform a prediction-based routing policy. We show that widely used and well-studied customer routing policies can be outperformed with simple modifications according to the Hawkes model. Through analysis of a stylized model proposed in the contact center literature, we prove that service heterogeneity can cause this underperformance and, moreover, that such heterogeneity will occur if service closures are not carefully managed. This paper was accepted by Elena Katok, operations management. Funding: The authors are grateful for the generous support of this work by the National Science Foundation Division of Graduate Education [Grant DGE-1650441] (A. Daw), the Israel Science Foundation [Grant 336/19] (G. B. Yom-Tov), and the United States-Israel Binational Science Foundation [Grant 2022095] (A. Daw, G. B. Yom-Tov). Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.04060 .
Perturbed Utility Stochastic Traffic Assignment
Authors: Yao Rui , Fosgerau Mogens , Paulsen Mads , Rasmussen Thomas Kjær 
Published: June 2024

This paper develops a fast algorithm for computing the equilibrium assignment with the perturbed utility route choice (PURC) model. Without compromise, this allows the significant advantages of the PURC model to be used in large-scale applications. We formulate the PURC equilibrium assignment problem as a convex minimization problem and find a closed-form stochastic network loading expression that allows us to formulate the Lagrangian dual of the assignment problem as an unconstrained optimization problem. To solve this dual problem, we formulate a quasi-Newton accelerated gradient descent algorithm (qN-AGD*). Our numerical evidence shows that qN-AGD* clearly outperforms a conventional primal algorithm and a plain accelerated gradient descent algorithm. qN-AGD* is fast with a runtime that scales about linearly with the problem size, indicating that solving the perturbed utility assignment problem is feasible also with very large networks. Funding: This work has been financed by the European Union—NextGenerationEU.
Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) initially presenting as septic meningoencephalitis in a 16-year-old male
Authors: Karavassilis Maria Elizabeth , Chernov Dmitriy , Dakhlia Sinda , Saravanan Paramalingam 
Published: June 2024

Background: We describe a case of myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) in a 16-year-old patient who initially presented with clinical features of septic meningoencephalitis. This case outlines the importance of considering a diagnosis of MOGAD in patients who fail to improve with appropriate antimicrobial therapy or show a positive clinical response to glucocorticoids (often used in treatment of meningococcal meningitis). We emphasise the importance of recognising that an infectious prodrome can precede MOGAD. Case description: A 16-year-old male was admitted with vomiting, fever, headache, photophobia and altered mental state. He was treated for meningoencephalitis with initial clinical improvement. Lumbar puncture findings were suggestive of viral meningoencephalitis. During admission the patient went through several periods of transient clinical and biochemical improvement, alternating with periods of symptomatic relapse. On day 17 of admission, he was transferred to a tertiary centre for suspected autoimmune disseminated meningoencephalitis (ADEM) and two days later, he suffered a catastrophic neurological decline with new dysarthria, dysphagia, aphasia, horizontal nystagmus and facial paralysis. He made a remarkable neurological recovery after commencing treatment with IV immunoglobulin, IV methylprednisolone and plasma exchange, with complete resolution of symptoms. Conclusion: MOGAD can run a variable course and present soon after a central nervous system infection, making the diagnosis more challenging. Nonetheless, patients can achieve a full neurological recovery with early recognition, diagnosis and treatment of this rare entity.
Mismatched expectations: experiences of nurses returning to prescribing
Authors: McCulloch Margot , Wood Alison F 
Published: June 2024

Background: Research has identified continuing professional development for active prescribers to be a challenge; particularly a lack of confidence and anxiety around prescribing. Anecdotally, support to regain prescribing knowledge and competence to facilitate safe prescribing requires some exploration for organisations, mangers and practitioners. Aim: To obtain an insight into practitioners’ experiences of returning to prescribing in their clinical role following a period of non-activity. Methods: Online semi-structured interviews with five prescribers were conducted, with interview transcripts thematically analysed by the research team. Results: Four themes were generated: individual; the team; the organisation; and the mismatch between the three. Conclusion: Considering these results is important to support those who return to prescribing to ensure safe and effective practice, and a positive experience for all involved.
Cognition, physical function, and life purpose in the rural elderly population: A systematic review protocol
Authors: Morais Campos Hércules Lázaro , De Leon Elisa Brosina , Merllin Batista de Souza Ingred , Quialheiro Anna , Araújo de Oliveira Elizabete Regina 
Published: June 2024

Introduction
Aging in rural settings worldwide, from the perspective of cognition, physical function, and life purpose essential constructs for a prosperous old age, still needs comprehensive discussion. This systematic review protocol aims to highlight the prevalence of cognitive decline, physical functioning, and life purpose in older adults aging in rural community settings.

Methods and analysis
We will include cross-sectional studies published until April 2023 found in 8 databases: Embase, MEDLINE, LILACS, PsycINFO, Scopus, SciELO, and Web of Science. Ryyan software will be used for the first selection, and the Observational Study Quality Evaluation (OSQE) will assess methodological quality and risk of bias. Primary analysis will involve titles and abstracts using MeSH descriptors such as "Physical functioning," "Cognition," "Cognitive function," "Life purpose," "Elderly," "Older," "Rural aging," "Rural population," "Communities, rural," "Distribution, rural spatial," "Medium communities," "Rural settlement," "Small community." If necessary, secondary analysis will include a complete reading of selected articles by two blinded reviewers, confirmed by a third person. Publication bias will be assessed using cross-sectional analytical study quality. Sensitivity analyses will identify manuscripts significantly influencing combined prevalence of endpoints.
Case-control study: Unveiling human polyomaviruses and papillomavirus in Egyptian colorectal cancer patients
Authors: Darwish Marwa K. , Allayeh Abdou K. , Ahmed Amr E. , Abdelmaksoud Mohamed D. E. , Alkhalil Samia S. , Ageeli Hakami Mohammed , Hassan Ahmed , Mohamed Mahmoud Farrag Haiam , Saif Eldin M. Mohamed Samah , Gouda Weaam 
Published: June 2024

Background
Colorectal cancer (CRC) is a cancer type that is thought to be influenced by human papillomaviruses (HPVs) and human polyomaviruses (HPyVs). In Egypt, CRC ranks as the 7th most common cancer, accounting for 3.47% of male cancers and 3% of female cancers. However, there is currently a lack of information regarding the presence of PyVs and HPVs co-infection specifically in CRC cases in Egypt. Therefore, the aim of this study was to investigate the occurrence of HPVs and HPyVs (JCPyV, BKPyV, and SV40) infections, as well as co-infections, among CRC patients in Egypt. Additionally, the study aimed to assess any potential association between these viral infections and tumor stages.

Methods
In the present study, we analyzed a total of 51 tissue samples obtained from Egyptian CRC patients, along with 19 polyps’ samples. Our investigation focused on the detection and genotyping of HPyVs using Real-Time PCR. Additionally, we employed real-time PCR for the detection of HPVs, and for their genotyping, we utilized a combination of PCR amplification followed by sequencing.

Results
In our study, we found evidence of HPyVs infection in the CRC patients, specifically SV40 (25.5%) and BKPyV (19.6%). However, JCPyV was not detected in the samples that were examined. Additionally, we discovered that HPV was present in 43.1% of the CRC patients. When considering viral co-infections, 19.6% of the CRC samples showed coexistence of multiple viruses, while no co-infections were found in the polyps samples. Importantly, we observed a significant correlation between the presence of HPVs and advanced colorectal tumor grades B2 and D.

Conclusion
Our findings provide valuable data for the detection of oncogenic viruses in colorectal cancer (CRC) and underscore the association of viral co-infections with advanced tumor stages. However, further research with larger cohorts is necessary to validate these findings and strengthen their significance in the field of CRC.
Prevalence and predictors of antibiotic prescription among patients hospitalized with viral lower respiratory tract infections in Southern Province, Sri Lanka
Authors: Medrano Perla G. , Weerasinghe Nayani , Nagahawatte Ajith , Vanderburg Sky , Park Lawrence P. , Wijayaratne Gaya B. , Devasiri Vasantha , Dilshan Buddhika , Sheng Tianchen , Kurukulasooriya Ruvini , Anderson Jack , Nicholson Bradly P. , Woods Christopher W. , Bodinayake Champica K. , Tillekeratne L. Gayani 
Published: June 2024

Background
Antimicrobial overprescription is common for lower respiratory tract infections (LRTI), as viral and bacterial infections generally present with similar clinical features. Overprescription is associated with downstream antimicrobial resistance. This study aims to identify the prevalence and predictors of antibiotic prescription among patients hospitalized with viral LRTI.

Methods
A prospective cohort study was conducted among patients aged ≥1 year hospitalized with viral LRTI in a tertiary care hospital in Southern Province, Sri Lanka from 2018–2021. Demographic, clinical, and laboratory data were recorded. Nasopharyngeal and blood samples were collected for multiplex polymerase chain reaction testing for 21 respiratory pathogens and procalcitonin (PCT) detection, respectively. Demographic and clinical features associated with antibiotic prescription were identified using Chi Square and t-tests; significant variables (p<0.05) were further included in multivariable logistic regression models. The potential impact of biomarker testing on antibiotic prescription was simulated using standard c-reactive protein (CRP) and PCT cut-offs.

Results
Of 1217 patients enrolled, 438 (36.0%) had ≥1 respiratory virus detected, with 48.4% of these patients being male and 30.8% children. Influenza A (39.3%) and human rhinovirus/ enterovirus (28.3%) were most commonly detected. A total of 114 (84.4%) children and 266 (87.8%) adults with respiratory viruses were treated with antibiotics. Among children, neutrophil percentage (median 63.6% vs 47.6%, p = 0.04) was positively associated with antibiotic prescription. Among adults, headache (60.6% vs 35.1%, p = 0.003), crepitations/crackles (55.3% vs 21.6%, p<0.001), rhonchi/wheezing (42.9% vs 18.9%, p = 0.005), and chest x-ray opacities (27.4% vs 8.1%, p = 0.01) were associated with antibiotic prescription. Access to CRP and procalcitonin test results could have potentially decreased inappropriate antibiotic prescription in this study by 89.5% and 83.3%, respectively.

Conclusions
High proportions of viral detection and antibiotic prescription were observed among a large inpatient cohort with LRTI. Increased access to point-of-care biomarker testing may improve antimicrobial prescription.
Assessment of knowledge, attitudes, and practice regarding air pollution and health effects among general people: A multi-divisional cross-sectional study in Bangladesh
Authors: Siddique Abu Bakkar , Sujan Md. Safaet Hossain , Ahmed Sanjida , Ishadi Kifayat Sadmam , Tasnim Rafia , Islam Md. Saiful , Hossain Md. Shakhaoat 
Published: June 2024

Background
Bangladesh is one of the most densely populated countries in the world, with more than one-third of its people living in cities, and its air quality is among the worst in the world. The present study aimed to measure knowledge, attitudes and practice (KAP) towards air pollution and health effects among the general population living in the large cities in Bangladesh.

Methods
A cross-sectional e-survey was conducted between May and July 2022 among eight divisions in Bangladesh. A convenience sampling technique was utilized to recruit a total of 1,603 participants (55.58% males; mean age: 23.84 ± 5.93 years). A semi-structured questionnaire including informed consent, socio-demographic information, as well as questions regarding knowledge (11-item), attitudes (7-item) and practice (11-item) towards air pollution, was used to conduct the survey. All analyses (descriptive statistics and regression analyses) were performed using STATA (Version 15.0) and SPSS (Version 26.0).

Results
The mean scores of the knowledge, attitudes, and practice were 8.51 ± 2.01 (out of 11), 19.24 ± 1.56 (out of 21), and 12.65 ±5.93 (out of 22), respectively. The higher scores of knowledge, attitudes, and practice were significantly associated with several socio-demographic factors, including educational qualification, family type, residential division, cooking fuel type, etc.

Conclusions
The present study found a fair level of knowledge and attitudes towards air pollution; however, the level of practice is not particularly noteworthy. The finding suggests the need to create more awareness among the general population to increase healthy practice to reduce the health effects of air pollution.
Five records of new and rare alien species to the flora of the United Arab Emirates (UAE)
Authors: Byalt Vyacheslav V. , Korshunov Michael V. 
Published: June 2024

The article presents new records for five alien species previously unknown from the flora of the United Arab Emirates (UAE) or very rare in the country – Chenopodium ficifolium (Chenopodiaceae/Amaranthaceae s. l.), Acalypha indica, Euphorbia maculata (Euphorbiaceae), Gamochaeta pensylvanica (Gnaphalium pensylvanicum), and Verbesina encelioides (Asteraceae). Some of them have been recorded for the first time from the emirate Fujairah in north-eastern part of the UAE. Euphorbia maculata, which is rare in the country, was found only in “Salman Nursery” at Masafi town and in an irrigated garden near village Bithna, Chenopodium ficifolium was found in environs of Al Siji, in Wadi Siji on the road-dam and in “Al Phoenician Nursery” at Al Dibba town, Acalypha indica L. grows as weed in a plant market on the roadside in Al Bidya and in “The Green Nursery Sales Dibba” at Al Dibba town, they are new for the flora of Fujairah and UAE at all. Gamochaeta pensylvanica was found in a small quantity in a plant market and plant nursery in the Masafi friday market, and Verbesina encelioides – was found naturalized in Khor-Fakkan (Emirate of Sharjah) – both are very rare in the UAE.
Species, synonyms, spatial distribution, habitat preferences, and species taxonomy with remarks on identification and differentiation from the most similar taxa occurring in the study area, as well as the list of localities are presented. The herbarium materials were transferred to the Herbarium of the Komarov Botanical Institute (LE, St. Petersburg, Russia), the duplicates – to the Herbarium of Altai State University (ALTB, Barnaul, Russia) and the Scientific Herbarium of Fujairah (FSH, Wadi Wurayah national park, Fujairah, United Arab Emirates).
Umbilicaria aprina and U. rhizinata (Umbilicariaceae, lichenized Ascomycota) in Russia
Authors: Davydov Evgeny A. , Yakovchenko Lidiya S. , Kharpukhaeva Tatyana M. , Zheludeva Elena V. , Chesnokov Sergey V. , Konoreva Lyudmila A. , Kuznetsova Ekaterina S. , Storozhenko Yulia V. , Ryzhkova Polina Yu. , Himelbrant Dmitry E. 
Published: June 2024

The distribution of Umbilicaria aprina and U. rhizinata in Russia was revised basing on morphological and molecular-phylogenetic data. Umbilicaria aprina is new to Alexandra Land Island (Franz Josef Land Archipelago), Sverdrup Island (Taimyr Dolgano-Nenets District), the republics of Altai, North Ossetia-Alania and Sakha-Yakutia. Umbilicaria rhizinata is new to the republics of Tyva and Buryatia, Putorana Plateau, Kamchatka Peninsula, and the Magadan Region and is therefore reported for the first time to the Asian Subarctic. New localities of the species in other regions are cited. The ITS\5.8S phylogenetic tree supports the distinctness of U. aprina and U. rhizinata. The distribution map is drawn and patterns of distribution of two species are discussed. Umbilicaria aprina occurs in the high Arctic between 74°N and 81°N, whereas the northernmost locality of U. rhizinata is in the vicinity of Norilsk on the Putorana Plateau (ca. 70°N). In mountains U. aprina grows at higher maximal elevations compared to U. rhizinata.
Long-time asymptotic behavior for the Hermitian symmetric space derivative nonlinear Schrödinger equation
Authors: Chen Mingming , Geng Xianguo , Liu Huan 
Published: June 2024

Abstract
Resorting to the spectral analysis of the 4 × 4 matrix spectral problem, we construct a 4 × 4 matrix Riemann–Hilbert problem to solve the initial value problem for the Hermitian symmetric space derivative nonlinear Schrödinger equation. The nonlinear steepest decent method is extended to study the 4 × 4 matrix Riemann–Hilbert problem, from which the various Deift–Zhou contour deformations and the motivation behind them are given. Through some proper transformations between the corresponding Riemann–Hilbert problems, the basic Riemann–Hilbert problem is reduced to a model Riemann–Hilbert problem, by which the long-time asymptotic behavior to the solution of the initial value problem for the Hermitian symmetric space derivative nonlinear Schrödinger equation is obtained with the help of the asymptotic expansion of the parabolic cylinder function and strict error estimates.
Application value of artificial intelligence algorithm-based magnetic resonance multi-sequence imaging in staging diagnosis of cervical cancer
Authors: Chang Rui , Li Ting , Ma Xiaowei 
Published: June 2024

Abstract
The aim of this research is to explore the application value of Deep residual network model (DRN) for deep learning-based multi-sequence magnetic resonance imaging (MRI) in the staging diagnosis of cervical cancer (CC). This research included 90 patients diagnosed with CC between August 2019 and May 2021 at the hospital. After undergoing MRI examination, the clinical staging and surgical pathological staging of patients were conducted. The research then evaluated the results of clinical staging and MRI staging to assess their diagnostic accuracy and correlation. In the staging diagnosis of CC, the feature enhancement layer was added to the DRN model, and the MRI imaging features of CC were used to enhance the image information. The precision, specificity, and sensitivity of the constructed model were analyzed, and then the accuracy of clinical diagnosis staging and MRI staging were compared. As the model constructed DRN in this research was compared with convolutional neural network (CNN) and the classic deep neural network visual geometry group (VGG), the precision was 67.7, 84.9, and 93.6%, respectively. The sensitivity was 70.4, 82.5, and 91.2%, while the specificity was 68.5, 83.8, and 92.2%, respectively. The precision, sensitivity, and specificity of the model were remarkably higher than those of CNN and VGG models (P < 0.05). As the clinical staging and MRI staging of CC were compared, the diagnostic accuracy of MRI was 100%, while that of clinical diagnosis was 83.7%, showing a significant difference between them (P < 0.05). Multi-sequence MRI under intelligent algorithm had a high diagnostic rate for CC staging, deserving a good clinical application value.
Embedded monitoring system and teaching of artificial intelligence online drug component recognition
Authors: Ding Li , Wu Zhengrong , Zhang Junmin , Zhao Quanyi , Chen Xiaoling , Jia Zhong , He Dian 
Published: June 2024

Abstract
Drug testing has many test elements. It aims to prevent unqualified drugs from entering the market and ensure drug safety. The existing artificial intelligence (AI) online monitoring system identifies active ingredients in the process of use. Owing to their openness, data are easy to be lost, failing to meet user needs and inducing a specific impact on the use of the monitoring system. With the continuous development of computer and measurement technologies, various biochemical data are increasing at an unprecedented speed, and numerous databases are emerging. Extracting patterns from considerable known data and experimental facts is an essential task for a wide range of biological and chemical workers. Pattern recognition is one of the essential technologies for data mining. It is widely used in industry, agriculture, national defense, biomedicine, meteorology, astronomy, and other fields. To improve the effect of the online drug ingredient recognition system, this study used AI to design an online drug ingredient recognition-embedded monitoring system and applied AI to the teaching field to improve teaching efficiency. First, this study constructed the framework of the AI online drug ingredient recognition-embedded monitoring system and introduced the process of online drug ingredient recognition. Then, it introduced the pattern recognition method, constructed the pattern recognition system, and presented the pattern recognition algorithm and the algorithm evaluation index. Afterward, it used pattern recognition to conduct a qualitative analysis of the infrared spectrum of drug components and introduced the overall process of the qualitative analysis. In addition, this study employed AI to implement changes to the embedded system instruction in colleges and universities, summarizing the current issues. The impact of drug component recognition and the educational impact of embedded systems were investigated in the experimental portion. The experimental findings demonstrated the excellent accuracy, sensitivity, specificity, and Matthew correlation coefficient of the online drug component recognition-integrated monitoring system in this work. Compared with that of other systems, its average drug component recognition accuracy was above 0.85. Students in five majors reported high levels of satisfaction with the embedded system teaching, which is better for delivering college instruction.