bluuebunny/crossref_metadata_2025_split huggingface dataset:
Use of Neuromuscular Blockade for Neck Dissection and Association with Iatrogenic Nerve Injury
Authors: Smith Joshua D. , Mentz Graciela , Leis Aleda M. , Yuan Yuan , Stucken Chaz L. , Chinn Steven B. , Casper Keith A. , Malloy Kelly M. , Shuman Andrew G. , McLean Scott A. , Rosko Andrew J. , Prince Mark E.P. , Tremper Kevin K. , Spector Matthew E. , Schechtman Samuel A. 
Published: May 2023

Abstract
Background Cranial nerve injury is an uncommon but significant complication of neck dissection. We examined the association between the use of intraoperative neuromuscular blockade and iatrogenic cranial nerve injury during neck dissection.Methods This was a single-center, retrospective, electronic health record review. Study inclusion criteria stipulated patients > 18 years who had ≥ 2 neck lymphatic levels dissected for malignancy under general anesthesia with a surgery date between 2008–2018. Use of neuromuscular blockade during neck dissection was the primary independent variable. This was defined as any use of rocuronium, cisatracurium, or vecuronium upon anesthesia induction without reversal with sugammadex prior to surgical incision. Univariate tests were used to compare variables between those patients with, and those without, iatrogenic cranial nerve injury. Multivariable logistic regression determined predictors of cranial nerve injury and was performed incorporating Firth’s estimation given low prevalence of the primary outcome.Results Our cohort consisted of 925 distinct neck dissections performed in 897 patients. Neuromuscular blockade was used during 285 (30.8%) neck dissections. Fourteen instances (1.5% of surgical cases) of nerve injury were identified. On univariate logistic regression, use of neuromuscular blockade was not associated with iatrogenic cranial nerve injury (OR: 1.73, 95% CI: 0.62–4.86, p = 0.30). There remained no significant association on multivariable logistic regression controlling for patient age, sex, weight, ASA class, paralytic dose, history of diabetes, stroke, coronary artery disease, carotid atherosclerosis, myocardial infarction, and cardiac arrythmia (OR: 1.87, 95% CI: 0.63–5.51, p = 0.26).Conclusions In this study, use of neuromuscular blockade intraoperatively during neck dissection was not associated with increased rates of iatrogenic cranial nerve injury. While this investigation provides early support for safe use of neuromuscular blockade during neck dissection, future investigation with greater power remains necessary.
Stent strut dilation in branch pulmonary artery stenosis following stenting of arterial duct in duct dependent pulmonary circulation
Authors: KONETI NAGESWARA RAO , BAKHRU SHWETA , DHULIPUDI BHARGAVI , RAJAN SAILEELA , SREE NARAYANASWAMY 
Published: May 2023

Abstract
Objective To assess the feasibility and outcome of stent strut dilation after arterial duct stenting with associated branch pulmonary artery (BPA) stenosis.Background Stenting of arterial duct in infants with duct dependent pulmonary circulation is technically challenging. Presence of BPA stenosis is a relative contraindication for stent implantation.Methods Infants with duct dependent pulmonary circulation and associated BPA stenosis were assessed either by transthoracic echocardiogram alone or additional computerized tomography (CT) angiogram when required. Following ductal stenting, the stent struts of the stenosed BPA were crossed with an additional 0.014″ coronary guide wire and dilated using coronary balloons (2.0 or 2.5 mm in diameter).Results Seventeen (12 male) patients were considered for the procedure. The median age and weight were 27 days (range 2 to 94) and 2.6 kilograms (range 2.2 to 5) respectively. Fourteen patients (78%) underwent stent strut dilation after arterial duct stenting. Struts to left pulmonary artery was opened in 9 (64%) and right pulmonary artery in 5 (35%). The baseline saturation improved from 66.23 ± 8.9% to 89.29 ± 4.3% after successful strut dilation. Angiographic pulmonary flow improved in all cases. Stent strut dilation could not be done in 3 patients due to unfavorable anatomy. One patient had acute stent thrombosis and died in the hospital. Two others died during follow-up, during an acute febrile illness and gastroenteritis. All survivors underwent cardiac surgery and were on regular follow-up.Conclusions Strut dilation of BPA stenosis is feasible to augment pulmonary blood flow, following arterial duct stenting.
A DFT investigation on transition metal (Co, Cr, Cu, Mn, Mo and Nb) doped Bismuth Ferrite Oxide (BiFeO3 ) for CO gas adsorption
Authors: Sambare Amogh , Pawar Ramkisan , Shirsat Mahendra 
Published: May 2023

Abstract
Using density functional theory, the structural and electronic configuration of transition metal atom (Co, Cr, Cu, Mn, Mo, and Nb) doped BiFeO3(BFO) perovskite for adsorption of CO gas molecules have been studied in a systematic way. A detailed analysis of energy, geometry and an electronic configuration of transition metal atoms doped in A site of BFO perovskite structure towards CO adsorption is carried out. The CO gas molecule adsorption phenomenon on transition metal-doped BFO are investigated in terms of adsorption energy after geometry optimization, adsorption distance, charge density difference, and the spectrum of the density of states. Our results revealed that CO gas is chemisorbed on Mo-doped BiFeO3 perovskite structure. Also, calculation results indicates that CO preferably adsorbs on Mo-doped BiFeO3 with an adsorption energy of -1.0532 eV. Further results from the Density of states plot (DOS) suggest that Mo-doped BFO (010) can be introduced as a promising candidate in chemiresistive gas sensing devices for detecting CO gas molecule.
Effectiveness, and Safety of Eptinezumab in Episodic and Chronic Migraine Headache in the UAE: A retrospective study
Authors: Bader Yazan , Suliman Reem , Harb Mohamad , Santos Vanessa , Qaisi Ibrahim Al , Alsaadi Taoufik 
Published: May 2023

Abstract
Background Eptinezumab-jjmr is a humanized IgG1 immunoglobulin monoclonal antibody administered intravenously as a preventative migraine treatment. Previously conducted randomized, double-blind, placebo-controlled trials exhibited significant reduction in monthly migraine frequency among adults experiencing episodic and chronic migraine. The present study seeks to expand upon the current findings and evaluate Eptinezumab-jjmr’s efficacy as a preventative migraine treatment for chronic and episodic migraine patients in the United Arab Emirates. This study is intended to represent the first real-world evidence study and will hopefully serve as a valuable complement to the existing literature on the subject.Methods This was a retrospective, observational, and exploratory study. The participants included within the study were adult (≥ 18 years) patients diagnosed with either episodic or chronic migraine. Patients were categorized according to their history of previous preventative treatment failure. For the final assessment of treatment efficacy, we included only patients with a minimum of 6 months of clinical follow-up data. Patients were assessed at baseline for their monthly migraine frequency and assessed again at months 3 and 6. The primary objective was to evaluate the efficacy of Eptinezumab-jjmr in reducing migraine frequency among chronic and episodic migraine patients.Results 100 participants were identified, of whom 53 patients completed the study protocol to month 6. 40 (75.5%) were female, 46 (86.8%) were Emirati locals, and 16 (30.2%) were pharmaceutically naïve, having never tried any prior preventative therapy. Additionally, 25 (47.2%) patients met the criteria for chronic migraine (CM), whereas the remaining 28 (52.8%) were diagnosed with episodic migraine (EM). The baseline monthly migraine frequency (MMD) was 12.2 (4.97) days across all participants, 15.6 (3.97) for CM patients, and 9.25 (3.76) for EM patients; by month 6, these frequencies reduced to 3.66 (4.21), 4.76 (5.32), and 2.68 (2.61), respectively. Overall, 58.5% of those enrolled experienced > 75% reduction in MMD frequency by month 6.Conclusion Patients enrolled in this trial experienced clinically significant reductions in MMD by month 6. Eptinezumab-jjmr was well tolerated with only one AE of note.
Incidence and Adverse Clinical Events of Primary Sclerosing Cholangitis with Ulcerative Colitis
Authors: Han In Sub , Baek Dong Hoon , Hong Seung Min , Lee Bong Eun , Lee Moon Won , Kim Gwang Ha , Song Geun Am 
Published: May 2023

Abstract
Purpose The aim of this study was to conduct a nationwide population-based study to estimate the incidence of primary sclerosing cholangitis in patients with ulcerative colitis (UC-PSC) and investigate healthcare use, medication use, surgery, cancer, and death as adverse clinical events of UC-PSC.Methods We identified incident cases of UC with (UC-PSC) or without PSC (UC-alone) between 2008 and 2018 using health insurance claims data in Korea. Univariate (crude hazard ratio [HR]) and multivariate analyses were performed to compare the risk of adverse clinical events between groups.Results Overall, 3.38% (487/14,406) patients developed UC-PSC. During a mean follow-up duration of approximately 5.92 years, the incidence of PSC in patients with UC was 185 per 100,000 person-years. The UC-PSC group showed statistically more frequent healthcare use (hospitalization and emergency department visits: HRs, 5.986 and 9.302, respectively; P < .001), higher immunomodulator and biologic use (azathioprine, infliximab, and adalimumab: HRs, 2.061, 3.457, and 3.170, respectively; P < .001), and higher surgery rate (resection of small bowel, operation for intestinal obstruction, and colectomy: HRs, 7.110, 9.728, and 2.940, respectively; P < .001) than did the UC-alone group. The UC-PSC group also showed significantly higher colorectal cancer and biliary tract cancer (HRs, 2.799 and 36.343, respectively; P < .001) and mortality (HR, 4.257) rates than did the UC-alone group.Conclusion Patients with UC-PSC have higher risks of colorectal cancer, biliary tract cancer, and death than do patients with UC-alone. Although considered a rare disease, managing this complex and costly disease requires recognition of the impact of increased burden on health care services.
Text line and word detection and recognition of historical Arabic manuscripts
Authors: Hakim Bouchal , Ahror Belaid 
Published: May 2023

Abstract
The old Arabic manuscripts are highly sought-after documents but very difficult to access. Digitization, and thus handwriting recognition, is a beneficial way to make these resources accessible. This paper presents an end-to-end approach to the offline recognition of ancient manuscripts. First, a crucial pre-processing step is to extract text lines and words by applying transfer learning on YOLO (You Only Look Once) architecture. Thus the segmentation problem is treated as a detection problem. Then for the recognition of old handwritten words, we propose ensemble learning techniques based on recurrent neural networks associated with the Connectionist Temporal Classification layer (CTC) combined to convolution networks with Squeeze-and-Excitation blocks. The presented work accurately detects lines of text and words, even when overlapping or touching words are present, and correctly identifies those with multiple connected components. We evaluate this approach on a collection of 20 pages for text line detection. Moreover, we introduce a new consistent and accurate dataset for word detection and recognition. We have achieved promising results with 98.1% and 94.38% F1-measure on the text line and word detection, respectively, with a character error rate recognition of 8.27%.
TFDF and TF-IDF in Financial Analysis
Authors: HASHEMI MEISAM , REZAEI MEHRAN , KAEDI MARJAN 
Published: May 2023

Abstract
Textual analysis in the realm of business depends on text processing techniques borrowed mainly from information retrieval. However, it is not a viable solution capable of developing in finance. We suggest developing financial homegrown techniques for processing textual data. Especially in the course of scoring words where standard techniques are incongruous in financial analysis. On that matter, we pursue two issues. First, we examine major information retrieval heuristics. We find TF-IDF a facile solution that falters in predicting trend and generates high errors on large numbers. Second, we work on a new heuristic satisfying financial concernments. We consider the relation between publication rate of information and their importance. The proposed heuristic provides results of unmatchable performance in both predicting trend and precision measures. In additional analysis, we optimize our scheme using Genetic algorithm in a machine learning approach and get greater precision. In comparison with TF-IDF, the proposed heuristic conduces to 38.5 percent lower error in closeness measures which is again reduced by 16.46 percent with the help of machine learning. Our findings suggest that financial textual analysis and information retrieval should go their separate ways.
Serial Document Layout Analysis Method Based on Improved Mask R-CNN Architecture
Authors: Zhao weidong , Zhang xiaoming , Li xujian 
Published: May 2023

Abstract
Document Layout Analysis plays an important part in understanding the content of the document and extracting OCR text. Existing methods rely primarily on parallel analytical and identification techniques. Based on the analysis of the advantages and disadvantages of parallel methods, this article proposes a Serial Classification Recognition Method based on the improved architecture of the Mask R-CNN. To be specific, an improved feature pyramid model SCBAM-FPN is proposed, which utilizes Spatial Attention Module and Channel Attention Module as well as Atrous Convolution to reduce the loss of local information in feature maps and expand the receptive field, thereby increasing the performance of FPN express ability. Experiments show that using SCBAM-FPN to replace the original feature pyramid network in Mask R-CNN improves the detection performance of Mask R-CNN network for multi-scale targets. In addition, in order to improve the accuracy of segmentation, a Mask edge correction algorithm is proposed, which combines the FCN semantic segmentation results with edge superpixel information and uses the Mask-IoU mechanism to perform edge corrections on Masks with scores of less than 90%. The serial classification recognition method utilizes the improved Mask R-CNN architecture to perform Document Layout Analysis. Firstly, the document image is recognized and the table is segmented. Secondly, the image after the split table is used to identify and segment the illustrations. Finally, identify the title and paragraph of the image after removing the table and the illustration. Although the serial classification and recognition method has a certain degree of decline in speed, this method solves the problem of competition among multiple attributes and improves the accuracy of recognition compared with existing methods. In this article, experiments that were conducted on three datasets show that the proposed method surpasses existing methods in terms of accuracy and efficiency.
A new Excess-1 circuit based High-Speed Carry Select Adder in 18 nm FinFET Technology
Authors: BATTINI JEEVAN , PASHYA NARAYANA , KOSARAJU SIVANI 
Published: May 2023

Abstract
Conventional carry select adder (CCSA) uses a multiplexer in the final stage to select either an excess-1 result or a normal result. To improve the delay and number of transistors a new topology is Proposed (PCSA) that uses only a single type of cell i.e., a 2 − 1 multiplexer. The 2 − 1 multiplexer is constructed in CMOS and TGL logic styles using 18nm FinFETs. The sub-blocks such as half adder and excess-1 circuit used in this PCSA is realized using only a 2:1 multiplexer. Due to the usage of a single type 2:1 multiplexer, the PCSA exhibits better circuit regularity. The new topology of PCSA is designed using FinFET-based TGL and CMOS styles. All the adders such 4- and 8-bit are designed, simulated, and analyzed using Cadence Virtuoso, ADEL, and ADEXL at 18nm FinFET technology. The result analysis reveals that the speed performance and the number of transistors of 8-bit PCSA are better by 44.02% and 4% respectively compared to existing adders.
Mesoderm/mesenchyme homeobox l as a potential target that orchestrates hepatic stellate cell activation
Authors: Ruan Jie , Xie Ying , Zhou Huifang , Su Libo , Liu Chao , Zhang Chaoqun , Sun Dianxing 
Published: May 2023

Abstract
Aim: Hepatic stellate cell (HSC) activation is considered as a key event during the occurrence of liver fibrosis. Recent studies have shown that Mesoderm/mesenchyme homeobox l (Meox1) can promote organ fibrosis, such as in the skin and heart. We aimed to elucidate a potential role of the Meox1 during Hepatic stellate cell (HSC) activation.
Methods: The human HSC cell line Lx-2 was employed as model to evaluate the function of Meox1 in HSC activation. The expression of fibrotic genes was measured, and proliferation, migration, cell cycle assays were performed.
Results: In this study, Meox1 was recognized as a positive regulated factor of HSC activation. Following transforming growth factor-β1 (TGF-β1)-treated Lx-2 cells, the expression level of Meox1 was upregulated significantly. Meox1 knockdown mediated by small interference RNA (siRNA) was observed to inhibit TGF-β1-induced expression of HSC activation markers and fibrotic genes, including α smooth muscle actin (α-SMA), collagen type I (collagen-I) and matrix metalloproteinase 2 (MMP-2). Overexpression of Meox1 promoted HSC activation, as demonstrated by an increase in specific markers, including α-SMA, collagen-I and MMP-2 and enhancement of proliferation and migration. We also found that phosphorylation of Smad3 was elevated with forced expression of Meox1 in Lx-2 cells, whereas the TGF-β1 and total Smad3 protein levels were not changed. In addition, Meox1 could induce extension of the G1 phase and expression of the p21CIP1/WAF1 in Lx-2 cells.
Conclusions: Our results indicate that Meox1 could play a crucial role in HSC activation and potential participation in the canonical TGF-β1/Smad pathway.
Enhanced PSHE based refractive index sensor using nanophotonic resonator
Authors: Goyal Amit Kumar , Divyanshu Divyanshu , Massoud Yehia 
Published: May 2023

Abstract
This manuscript presents a dielectric resonator structure with altered dispersion characteristics to enhance the photonic spin hall effect (PSHE). The structural parameters are optimized to enhance the PSHE at 632.8 nm operating wavelength. The thickness-dependent angular dispersion analysis is carried out to optimize the structure and obtain the exceptional points. The PSHE-induced spin splitting shows a high sensitivity to the optical thickness of the defect layer. This gives a maximum PSHE-based transverse displacement (PSHE-TD) of around 56.66 times the operating wavelength at an incidence angle of 61.68°. Moreover, the structure’s capability as a PSHE-based refractive index sensor is also evaluated. The analytical results demonstrate an average sensitivity of around 33,720 μm/RIU. The structure exhibits around five times higher PSHE-TD and approximately 150% improvement in sensitivity than the recently reported values in lossy mode resonance structures. Due to the purely dielectric material-assisted PhC resonator configurations and significantly higher PSHE-TD, the development of low-cost PSHE-based devices for commercial applications is envisaged.
Opinions and Algorithms: Trust, Neutrality and Legitimacy
Authors: Razmetaeva Yulia 
Published: May 2023

The article is devoted to opinions and algorithms in the digital age, with a focus on how the manipulation of the former while using the latter affects trust and legitimacy. In addition, some attention is paid to the issue of neutrality, both in relation to unbiased opinions and in relation to unbiased technologies. The article raises questions about whether we can be self-determining and self-governing agents, especially in terms of how we make decisions and what opinions we trust, if we are skillfully led to this by algorithms or those behind them.

Considering that not only corporations, but also governments today use technologies to influence our preferences and opinions, issues of autonomy and personal interests are touched upon, as well as the problem of nudging for certain behaviors that are defined as the best for people, including in a paternalistic sense. The article argues that the merging of everyday life with digital spaces and algorithmization form our experience as a fundamentally new one and does not contribute to the ability to separate imposed interests from really our own.
The questions of how power and legitimacy are redistributed in a digital society dependent on algorithms are discussed in this study. It has been suggested that the impact on our preferences and management of them, when someone try to sell us certain opinions, may be more dangerous than selling us goods and services, since it destroys institutional and interpersonal trust and contributes to the erosion of public institutions. The study shows how some technologies, primarily algorithmic ones, which are not neutral either in their essence or in the way they are used by their creators and owners, contribute to growing addiction and impoverish human interaction and the ability to form meanings.
Development of a genetic algorithm-based graph model for conflict resolution for optimizing resolutions in environmental conflicts
Authors: Pourvaziri Mitra , Mahmoudkelaye Samira , Yousefi Saied 
Published: May 2023

AbstractGraph model for conflict resolution (GMCR) is a robust tool for resolving disagreements among parties with contradictory interests in a potential conflict. In GMCR, decision-makers (DMs) and their preferences are determined. The DMs are defined as people, parties, or groups having the authority to make decisions and the power to get these decisions approved. This definition excludes some potential stakeholders with no ability to make and exert decisions, like the natural environment. Therefore, this study aims to find an impartial viewpoint representing the natural environment's interests. A new GMCR based on genetic algorithm (GA) optimization is proposed to modify and optimize the final resolution of the GMCR regarding natural environment benefits. Having been applied to a real-world case study, this methodology showed competence in satisfying the fundamental interests of the natural environment to an acceptable extent. This case study is about an endangered seasonal lake, where there is contention between the governmental and agricultural sectors. The results revealed that the disagreement between two conflicting groups could be resolved by modifying the current agreement to consider both groups' demands. Finally, GA, incorporated in GMCR, proved to be a robust optimization technique in complex environmental conflicts.