bluuebunny/crossref_metadata_2025_split huggingface dataset:
London Protocol under water-perfused HRM in a healthy population, towards novel 3D manometric parameters in an evaluation of anorectal functional disorders
Authors: ANEFALOS ALEXANDRE , Martinez Carlos Augusto Real , Coy Claudio Saddy Rodrigues 
Published: January 2024

Abstract
Background/Aim London Protocol (LP) and Classification allied to high-resolution manometry (HRM) technological evolution has updated and enhanced the diagnostic armamentarium in anorectal disorders. This study aims to evaluate LP reproducibility under water-perfused HRM, provide normal data and new parameters based on 3D and healthy comparison studies under perfusional HRM.
Methods 50 healthy (25 F) underwent water-perfused 36 channel HRM based on LP at resting, squeeze, cough, push, and rectal sensory. Additional 3D manometric parameters were: pressure-volume (PV) 10⁴mmHg².cm (resting, short and long squeeze, cough); highest and lowest pressure asymmetry (resting, short squeeze, and cough). Complementary parameters (CP) were: resting (mean pressure, functional anal canal length); short squeeze (mean and maximum absolute squeeze pressure), endurance (fatigue rate, fatigue rate index, capacity to sustain); cough (anorectal gradient pressure); push (rectum-anal gradient pressure, anal canal relaxation percent); recto-anal inhibitory reflex (anal canal relaxation percent).
Results No difference to genders: resting (LP, CP, and 3D); short squeeze (highest pressure asymmetry); endurance (CP); cough (CP, highest and lowest pressure asymmetry); push (gradient pressure); rectal sensory. Higher pressure in men: short squeeze (maximum incremental, absolute, and mean pressure, PV, lowest pressure asymmetry); long squeeze (PV); cough (anal canal and rectum maximum pressure, anal canal PV); push (anal canal and rectum maximum pressure). Anal canal relaxation was higher in women (push).
Conclusions LP reproducibility is feasible under water-perfused HRM, and comparative studies could bring similarity to dataset expansion. Novel 3D parameters need further studies with healthy and larger data to be validated and for disease comparisons.
Effectiveness of digital health intervention on school adolescent and youth sexual and reproductive health in Jimma town, Southwest Ethiopia: a propensity score analysis
Authors: Tadele Afework , Kitila Oli , Wondimu Merertu , Dawud Badiru , Ali Rahma , Gizaw Getu 
Published: January 2024

Abstract
Background
Investments in youths’ sexual and reproductive health (SRH) has greatest gain as they are in a critical time across the period of transition from childhood to adulthood. This segment of population disproportionately from SRH ill health problems due to lack of adequate knowledge to make informed decisions and exercise their sexual and reproductive rights (SRHR).
Objectives
To examine effectiveness of digital health interventions on SRH among school adolescent and youth in Jimma Town, Southwest Ethiopia.
Methods
A quasi-experimental study conducted in Jimma town among school youths. The data were entered into Epidata™ manager v4.6 and analyzed using to STATA™ v 17.0. A propensity score matching (PSM) analysis was conducted to estimate the average treatments (ATE). In addition, two sample tests of proportion, and sensitivity analysis done using difference-in-differences (DID) analysis.
Result
A significant increase in SRH outcomes between baseline and end-line was found. The knowledge of SRHR increases by 26.8 percentage points (95% CI 14.5, 38.6), knowledge of SRH increases by 11.5 percentage points (95% CI 1.7, 21.4), and attitude towards SRHR increases by 27.4 percentage points (95% CI 17.5, 37.3) because of the digital health intervention among school adolescents and youths.
Conclusion
The digital health intervention significantly improved knowledge of SRHR, knowledge of SRH, and attitude towards SRHR among school adolescents and youths. Further studies on impacts of digital health interventions on reproductive health outcomes of public health importance such as teenage pregnancies, and unmet need for family planning are recommended.
Phytochemical Profiling and Molecular Docking Investigation of Avocado (Persea Americana Mill. Cultivar Hass) Leaves and Seeds: Implications for Antioxidant Activity and Health Benefits
Authors: Salau Shina , Olufemi Ademoyegun , Rabiat Ahmed Shola 
Published: January 2024

Abstract
Despite the rising interest in avocado leaves and seeds' health benefits, little or no research has been conducted on both their phytochemical profiles in conjunction with molecular docking investigations, particularly in relation to its antioxidant activity. Utilizing phytochemical screening, molecular docking, and ADMET predictions, this study, investigates the antioxidant properties of avocado leaves (AVL) and seeds (AVS). Results show that AVS has a high presence of flavonoids (+++), terpenoids (+++), but a low presence of phenols (+), while AVL has a high presence of tannins (+++) and phenols (++). Molecular docking studies validate two AVL (L01 and L02) and two AVS (S02 and S03) compounds based on binding affinity and interactions with 2rgu.pdb, 3mng.pdb, and 2vwi.pdb protein targets. ADMET studies indicate that AVL and AVS extracts have favourable bioavailability and health safety characteristics. Additionally, DPPH, ABTS and FRAP radical inhibition (%) results show that AVL (46.36%/DPPH, 6.67%/ABTS, 11.07%/FRAP) has lesser antioxidant activity than AVS (70.97%/DPPH, 47.35%/ABTS, 3.66%/FRAP).
Empirical Performance Analysis of Deep Convolutional Neural Networks Architectures for Face Liveness Detection
Authors: Khairnar Smita , Gite Shilpa , Thepade Sudeep D. 
Published: January 2024

Abstract
In the realm of biometrics, face recognition (F.R.) is one of the most exciting new developments. In the past decade, computer vision and artificial intelligence advancements have improved face recognition systems by several orders of magnitude. Many attacks can be launched against these systems, such as the low-cost and low-effort Presentation attacks. Face liveness detection is gaining momentum in research. With the advent of deep learning, observing the performance of pre-trained DCNN Architectures for Face Liveness Detection will be interesting. The paper proposes an Empirical Performance analysis of eight pre-trained DCNN Architectures allies VGG16, VGG19, ResNet50, InceptionResNetV2, MobileNetV2, DenseNet201, InceptionV3, Xception. The experimentation carried out on the NUAA dataset (120000 images) & and the Replay attack dataset has shown that the better performance is given by DenseNet201, closely followed by MobileNetV2. This study offers significant contributions to the understanding of the dynamic nature of face recognition technologies.
A model for recommending suitable LSP for improved service delivery in mobile network using affinity propagation machine learning
Authors: Ukekwe Emmanuel , Eneh Hyacinth 
Published: January 2024

Abstract
Network service request for voice and Internet may differ across locations. Network service providers are encouraged to conduct a quarterly check to identify the suitable network service request peculiar to locations of coverage so as to improve quality of service. In this work, a model that identifies and recommends the suitable location service plan for network providers is proffered. The 3-task model extracts data using quarterly averages, clusters the extracted data using affinity propagation machine learning and classifies the clusters into linguistic variables using the mean of the respective clusters. Using a dataset obtained from the Nigerian Bureau of Statistics on mobile telecommunication for three quarters in 2021, obtained results show that the model was able to identify states with heavy as well as low subscription rates across the states. Mtn, Airtel and Glo mobile network providers recorded equal voice and internet subscription rates across the states while 9Mobile showed signs of improvement in voice and Internet subscription for some states.
Rainfall-runoff modeling using the HEC-HMS flow modeling framework for the Halda River catchment, Bangladesh
Authors: Haque Marjena Binte , Karmakar Shyamal , Hossain Mohammad Mozaffar 
Published: January 2024

Abstract
The Halda River is a vital perennial river with significant ecosystem service throughout its course. We studied the characteristics of river monsoon flow using the HEC-HMS to determine the flash flood simulation potential of the cascade reservoir model. The curve numbers are optimized here based on SWAT simulation data. The NSE, R2(RMSE), RSE, and PBIAS estimate values agree with the observed discharge values for the calibration and validation periods. However, during the calibration period, the flow model showed a poor match for the baseflow part, which affected the model's efficiency. Using this approach, flash flood studies can potentially simulate flash floods in a relatively ungauged river basin with minimal discharge data and available water level data. Moreover, the computational cost is lower than that of a similar capacity flow model.
Synchronous versus metachronous spinal metastasis: a comparative study of survival outcomes following neurosurgical treatment
Authors: Banat Mohammed , Potthoff Anna-Laura , Hamed Motaz , Borger Valeri , Scorzin Jasmin E. , Lampmann Tim , Asoglu Harun , Khalafov Logman , Schmeel Frederic C. , Paech Daniel , Radbruch Alexander , Nitsch Louisa , Weller Johannes , Herrlinger Ulrich , Toma Marieta , Gielen Gerrit , Vatter Hartmut , Schneider Matthias 
Published: January 2024

Abstract
Purpose
Patients with spinal metastases (SM) from solid neoplasms typically exhibit progression to an advanced cancer stage. Such metastases can either develop concurrently with an existing cancer diagnosis (termed metachronous SM) or emerge as the initial indication of an undiagnosed malignancy (referred to as synchronous SM). The present study investigates the prognostic implications of synchronous compared to metachronous SM following surgical resection.
Methods
From 2015 to 2020, a total of 211 individuals underwent surgical intervention for SM at our neuro-oncology facility. We conducted a survival analysis starting from the date of the neurosurgical procedure, comparing those diagnosed with synchronous SM against those with metachronous SM.
Results
The predominant primary tumor types included lung cancer (23%), prostate cancer (21%), and breast cancer (11.3%). Of the participants, 97 (46%) had synchronous SM, while 114 (54%) had metachronous SM. The median overall survival post-surgery for those with synchronous SM was 13.5 months (95% confidence interval (CI) 6.1-15.8) compared to 13 months (95% CI 7.7-14.2) for those with metachronous SM (p=0.74).
Conclusions
Our findings suggest that the timing of SM diagnosis (synchronous versus metachronous) does not significantly affect survival outcomes following neurosurgical treatment for SM. These results support the consideration of neurosurgical procedures regardless of the temporal pattern of SM manifestation.
Unmet Needs and Strategies to Promote Patient Engagement in The Arab World: Experts' Opinion
Authors: Nabil Yehia , Eldaw Anwar , El-Shourbagy Dalia , Ibrahim Dima , Torkistani Hanan Al , Alshahrani Mohammad , Farghaly Mohamed , AlMadhi Sawsan , Mansour Romy 
Published: January 2024

Abstract
Background
The significance of Patient Engagement (PE) is widely acknowledged as a crucial element in fostering positive health outcomes, elevating care quality, and streamlining healthcare systems. Despite its recognized advantages, the level of patient engagement in Arab nations remains suboptimal.
Methods
A high-level assembly was convened in Dubai, assembling eleven distinguished patient advocates from diverse Arab countries. Their collective aim was to dissect the obstacles hindering patient engagement in the Arab world and propose pragmatic strategies to surmount them. First, a series of five open-ended, comprehensive questions were posed and thoroughly deliberated upon. Second, the barriers to patient engagement within the experts’ respective communities were debated. A qualitative thematic analysis was conducted and two reports were generated by two independent researchers from the original meeting recordings.
Results
This paper highlights the importance of patient engagement in advancing healthcare and categorizes barriers to patient engagement as patient-related, provider-related, or system/government related. The experts identified the primary gaps in patient engagement and proposed strategies to promote it, with a primary focus on motivating both patients and providers towards shared decision-making.
Conclusions
This paper amalgamates the insights and recommendations distilled from this expert gathering, juxtaposing them within the broader context of existing literature on patient engagement. Offering a comprehensive viewpoint, this article delves into the challenges and opportunities intrinsic to bolstering patient engagement in the Arab world. Moreover, it spotlights invaluable tools often overlooked within Arab countries. The practical insights furnished in this piece serve as a roadmap for administrators and decision-makers, providing guidance to enhance patient engagement on both a national and institutional scale.
Evolution properties of Laguerre higher order cosh-Gaussian beam propagating through Fractional Fourier transform optical system
Authors: Saad Faroq , Benzehoua Halima , Belafhal Abdelmajid 
Published: January 2024

Abstract
We theoretically investigate the propagation properties of a Laguerre higher order cosh Gaussian beam (LHOchGB) in a fractional Fourier transform (FRFT) optical system. Based on the Collins formula and the expansion of the hard aperture function into a finite sum of Gaussian functions, we derive analytical expressions for a LHOchGB propagating through apertured and unapertured FRFT systems. The analysis of the evolution of the intensity distribution at the output plane has shown from the obtained expressions, using illustrative numerical examples. The results show that the intensity distribution of the considered beam propagating in FRFT is significantly influenced by the source beam parameters and the parameters of the FRFT system. It is possible to demonstrate the potential benefits of the results obtained for applications in laser beam shaping, optical trapping, and micro-particle manipulation.
Automatic Pipeline for Information of Curve Graphs in Papers Based on Deep Learning
Authors: Han Yuexing 
Published: January 2024

Abstract

Extracting information from the vast amount of literature can help researchers quickly grasp the current state of development. Literature is a carrier of multiple forms of data while most researchers only pay attention to the text. Especially like the curve graphs include a great deal of critical numerical information that is not expressed in other data. The paper proposes a method to mine information from curve graphs in the literature. With this method, numerical values and coordinate axis entities of the curve graphs are extracted from the graphs and text. Foremost, curve graphs are cut out from literature with Yolov5s. Then, the exact title text corresponding to each curve graph is matched through operating Sentence-Bert. After obtaining the title text, the X-axis and the Y-axis name of a curve graph are extracted in the title with SCI-Bert. Meanwhile, techniques such as optical character recognition (OCR) are employed to parse the numerical data reflected on the charts automatically. Moreover, some principles are adopted to improve the performance. We validate each step with a dataset of 6042 articles from Elsevier. The accuracies of curve graph detecting and title matching with our principles are 96.4\% and 95.8\%. Both outperform better than inital models, proving the effectiveness of our principles. Entity and numerical data extraction achieve 76.3\% and 28.2\%. The experimental results show that our method can achieve large-scale extraction of the knowledge of those curve graphs from the literature.
Evolution behavior of pulsed chirped Laguerre higher-order cosh-Gaussian beam propagating through liver tissue
Authors: Benzehoua H. , Saad F. , Bayraktar M. , Chatzinotas S. , Belafhal A. 
Published: January 2024

Abstract
We perform an analytical study on the propagation properties of a pulsed chirped Laguerre higher-order cosh-Gaussian beam (cLhchGB) passing through liver tissue, utilizing the power spectrum refractive index, the extended Huygens-Fresnel integral, and the Fourier Transform method. Our investigation includes numerical simulations based on the derived formula, illustrating how varying beam parameter configurations within liver tissue impact the properties of the beam. Additionally, we thoroughly discuss the influence of both optical parameters and biological tissue characteristics on the spectral modifier, while also evaluating the impact of pulse duration and chirp parameter on spectral intensity at various observation positions. Our observations indicate that the pulsed cLhchGB undergoes changes in its shape as it traverses a considerable distance through this medium. The results presented in this paper hold significant importance for their potential applications in determining the deterioration or disruption of biological tissue, as well as in the fields of medical imaging and medical diagnosis.
Palladium(II) halide complexes of N,N,S-tridentate Schiff bases. Synthesis, structural studies in solution and solid state, and analysis of Hirshfeld surfaces
Authors: Alvarez-Hernández Jesús Alberto , Andrade-López Noemí , Alvarado-Rodríguez José G. , Muñoz-Granados Oscar , Sánchez-Cabrera Gloria , Martínez-Otero Diego 
Published: January 2024

Abstract

The synthesis and characterization of bromo- and iodo complexes of Pd(II) containing tridentate anionic Schiff bases, derived from the opening of 2-R-2-(2-pyridyl)benzothiazoline precursors (R = H, 1; R = Me, 2; R = C6H5, 3; R = C5H4N, 4) is described. The [Pd(Ln)X] complexes [for X = Br: n = 1 (1a), n = 2 (2a), n = 3 (3a), and n = 4, (4a); for X = I: n = 1 (1b), n = 2 (2b), n = 3 (3b), and n = 4 (4b)] were characterized in solution and in solid state by NMR and IR spectroscopy and by elemental analyses. In all complexes the corresponding anionic Schiff ligand {Ln}− displayed a κ2NκS-tridentate coordination mode. X-ray diffraction studies of [Pd(L3)Br] (3a), [Pd(L3)I] (3b), [Pd(L4)Br] (4a) and [Pd(L4)Br] (4b) complexes showed the formation of two five-membered chelate rings, with a distorted square planar geometry around the Pd(II) cation. Crystal structures of 3a, 3b, 4a, and 4b are stabilized by non-classical C–H···π, C–H···S, and C–H···X hydrogen bonding. For 3a, 3b, 4a, and 4b the Hirshfeld surface analysis allowed identify to the H···H contacts as the predominants, and the C–H···S or C–H···π non-classical hydrogen bonding as the stacking major contributions.
Design and Evaluation Analysis of Crowdsourced On-Demand Delivery Modes with the Substantial Involvement of Buses
Authors: Gao Gao , Huang Zhengfeng , Zheng Pengjun 
Published: January 2024

Abstract
With the rise of on-demand delivery, crowd shippers on third-party platforms are popular but come with higher external transportation costs and environmental impacts. To address these issues, we propose two crowdsourced delivery modes with bus involvement: "bus terminal + professional crowd shippers (B&P)" and "bus stop + crowdsourced passenger (B&C)." Both modes use buses to complete many of the delivery tasks, and fully utilize the free space at bus terminals, convenience stores around stations, automated parcel lockers, professional crowd shippers, and bus passengers to complete the entire delivery process. To assess the overall performance of these two delivery modes, we proposed a set of key performance indicators (KPIs) from four aspects: delivery cost, delivery efficiency, user experience, and external influence. Exploring the potential advantages of B&P and B&C modes based on 18349 delivery cases in downtown Ningbo, China. The results showed that the B&P and B&C modes can effectively reduce delivery cost and external influence while maintaining a comparable level of user experience and delivery efficiency as the P mode in the mid-to-long distance (3–10 km) delivery scenario. Finally, based on the above conclusions, we make some recommendations for the development planning of B&P and B&C modes.
Multi-Branch Deep Classification Models.
Authors: Fahim Mahmoud , Abdel-Nasser Mohamed , Abdelwahab Moataz , Abdelrahman Adel B. 
Published: January 2024

Abstract
Deep learning classification models, such as Convolutional Neural Networks (CNNs), Residual Networks (ResNets), Inception Networks, and MobileNet, are widely used for image classification tasks. These models employ sophisticated architectures, including specialized layers for feature extraction and hierarchical representation learning. EfficientNet optimizes the trade-off between accuracy and computational efficiency, while Capsule Networks aim to overcome limitations in capturing hierarchical features. Their adaptability, scalability, and effectiveness make them essential tools in various computer vision applications. In this paper, we explored three proposed classification models constructed from two CNNs followed by three branches, each with different configurations of convolution layers, activation functions, and pooling layers. The outputs of these branches were concatenated, and the model proceeded with additional layers, including convolution, activation, fully connected, and softmax layers. The proposed models were tested under three distinct scenarios with varying output configurations. Case 1 (two outputs), the models are evaluated for masked/unmasked classification, resulting in two output classes. Case 2 (50 outputs) aims to identify 50 different classes. Case 3 (85 outputs), the models were tested with an extended set of 85 output classes. This comprehensive testing across different scenarios demonstrated the versatility and applicability of the proposed models for diverse image classification tasks.