bluuebunny/crossref_metadata_2025_split huggingface dataset:
Uranium capture from aqueous solution using Palm-waste based activated carbon: sorption kinetics and equilibrium
Authors: Youssef W. M. , El-Maadawy M. M. , Masoud A.M. , Alhindawy I. G. , Hussein A. E. M. 
Published: November 2023

Abstract
In this research, we examined the effectiveness of adsorbents derived from commercially available palm kernel shell bio-char (PBC), as well as palm shell carbon that was activated through treatment with H2SO4 (PBC-SA) and ZnCl2 (PBC-Zn). Our primary objective was to enhance the adsorption capabilities of carbon materials and develop efficient sorbents for the removal of uranium ions from aqueous solutions. To gain insight into the characteristics of these materials, we employed various analytical techniques, including SEM, EXD, BET, FTIR, and Zeta potential. The optimization of the adsorption process involved the careful consideration of key parameters such as pH, contact time, adsorbent dosage, and initial metal ion concentration. Under specific conditions, including a pH level of 4.5, a contact time of 60 minutes, an adsorbent dosage of 10.0 g/L, and an initial metal concentration of 50 mg/L, the adsorbent materials PBC, PBC-SA, and PBC-Zn demonstrated uranium ion sorption capacities of 9.89 mg/g, 16.81 mg/g, and 21.93 mg/g, respectively. The kinetics of the adsorption process were analyzed using three models: the pseudo first-order model, the pseudo second-order model, and the intraparticle diffusion model. Our findings indicated that the pseudo second-order kinetics model provided the most suitable description of the uranium adsorption onto the prepared materials. Furthermore, the adsorption isotherm data were consistent with the Langmuir model, suggesting that the adsorption of uranium ions onto all materials followed a monolayer adsorption mechanism. Lastly, thermodynamic analysis revealed that the adsorption process was spontaneous and exothermic in nature.
Multi-Class Support Vector Machine Based on Minimization of Reciprocal-Geometric-Margin Norms
Authors: Kusunoki Yoshifumi , Tatsumi Keiji 
Published: November 2023

Abstract
In this paper, we propose a SVM algorithm for multi-class classification. It follows multi-objective multi-class SVM (MMSVM), which maximizes class-pair margins on a multi-class linear classifier. The proposed method, called reciprocal-geometric-margin-norm SVM (RGMNSVM) is derived by applying the ℓp-norm scalarization and convex approximation to MMSVM. Additionally, we develop the margin theory for multi-class linear classification, in order to justify maximization of class-pair geometric margins. Experimental results on artificial datasets explain situations where the proposed RGMNSVM successfully works, while conventional multi-class SVMs fail in generalization. Results of classification performance evaluation using benchmark data sets show that RGMNSVM is generally comparable with one of the best multi-class SVMs proposed by Weston and Watkins (1999). However, we observe that the proposed approach to geometric margin maximization actually has better generalization capability for certain real-world data sets.
Automated Translation Accurately Translates Recorded Pediatric Neurosurgery Clinic Conversations between Spanish and English
Authors: Succop Ben , Currin Meghan , Hesse Gabriella , Andrews Bethany , Elton Scott Wentworth , Quinsey Carolyn 
Published: November 2023

Abstract

Objective
The purpose of this study is to analyze an automated voice to text translation device by reportingt he translation accuracy for recorded pediatric neurosurgery clinic conversations, classifying errors in translation according to their impact on overall understanding, and comparing the incidence of these errors in English to Spanish vs. Spanish to English conversations.
Methods
English and Spanish speaking patients at a single academic health system’s outpatient pediatric neurosurgery clinic had their conversations recorded. These recordings were played back to a Google Pixel handheld smartphone with Live Translate voice to text translation software. A certified medical interpreter evaluated recordings for incidence of minor errors, errors impacting understanding, and catastrophic errors affecting patient-provider relationship or care. Two proportion t-testing was used to compare these outcomes.
Results
50 patient visits were recorded: 40 English recordings translated to Spanish and 10 Spanish recordings translated to English. The mean transcript length was 4244 ± 992 words. The overall accuracy was 98.2% ± 0.5%. On average, 46 words were missed in translation (1.09% error rate), 31 understanding-altering translation errors (0.73% error rate), and 0 catastrophic errors were made. There was no significant difference in English to Spanish or vice versa.
Conclusion
Voice to text translation devices accurately translate recorded clinic conversations between Spanish and English and vice versa with high accuracy and very low incidence of errors impacting medical care or understanding. Further study should investigate additional languages as well as compare these devices directly to medical interpreters in live clinic settings.
Efficient Siamese Model for Visual Object Tracking with Attention-Based Fusion Modules
Authors: Zhou Wenjun , Liu Yao , Wang Nan , Liang Dong , Peng Bo 
Published: November 2023

Abstract

In the realm of visual object tracking, achieving precise target localization poses a significant challenge. While Siamese trackers based on shallow networks often prioritize speed, they tend to suffer from subpar localization performance. This can be attributed to the inadequacy of features extracted by shallow networks, making it challenging to accurately pinpoint the target within intricate backgrounds. This paper presents an efficient Siamese model architecture for visual object tracking, aimed at mitigating the challenge of suboptimal feature extraction often observed in shallow network designs. On the basis of the Siamese network, we devise the Channel Attention Feature Enhancement Fusion Module (CAFEF) and Spatial-Channel Attention Feature Enhancement Fusion Module (SCAFEF) to bolster feature extraction while suppressing background noise. Furthermore, we enhance the model's resilience to disturbances by combining Siamese classification scores with those from an online classifier and to maintain high-quality image features during tracking, we introduce an online updating strategy for refreshing the template image. Experimental results across four publicly available datasets consistently demonstrate the outstanding performance of the proposed Siamese model architecture. The code is available at https://github.com/lejunXTS/ESM-VOTAFM/tree/master.
Causal Relationship Study Between Basal Metabolic Rate and the Risk of Dental Caries: Evidence from Genome-Wide Association Analysis
Authors: Li Chengxi , Wang Xue 
Published: November 2023

Abstract
Background
Basal metabolic rate (BMR) may be a potential risk factor for dental caries; however, existing observational studies have failed to provide direct evidence of a causal relationship between basal metabolic rate and dental caries.
Methods
This study employed two-sample Mendelian randomization (MR) to investigate the genetic causal relationship between BMR and dental caries. Summary data for genome-wide association studies (GWAS) on BMR were sourced from the UK Biobank, while GWAS summary data for dental caries were obtained from the FinnGen Consortium. Inverse variance weighted (IVW), MR Egger, weighted median, simple mode, and weighted mode were used for MR analysis. Additionally, Cochrane’s Q test was employed to detect heterogeneity in MR estimates.Horizontal pleiotropy was examined using MR-Egger intercept test and MR-PRESSO test, and leave-one-out analysis was conducted to assess the sensitivity of this association. Results: The IVW method indicated that basal metabolic rate is an independent risk factor for dental caries (P = 0.029). Horizontal pleiotropy is unlikely to bias the causal relationship (P > 0.05), and no evidence of heterogeneity was found between genetic variants (P > 0.05). Lastly, leave-one-out analysis revealed the stability and robustness of this association.
Conclusion
Utilizing two-sample Mendelian Randomization (MR) analysis, our study establishes a genetic causal link between basal metabolic rate and dental caries, thereby offering invaluable insights for the comprehensive, lifelong management of dental caries.
Benzylidene-Directed Glycosylations – Mechanistic Insights from Cryogenic Infrared Spectroscopy
Authors: Pagel Kevin , Chang Chun-Wei , Greis Kim , Kirschbaum Carla , Leichnitz Sabrina , Meijer Gerard , von Helden Gert , Seeberger Peter 
Published: November 2023

Abstract

The stereoselective formation of 1,2-cis glycosidic linkages is challenging. The currently most widely used strategy for their installation uses 4,6-O-benzylidene protected building blocks. The stereoselectivity of this reaction is thought to be driven by a covalent intermediate, which reacts via an SN2 mechanism. However, the role of cationic SN1-type intermediates in this reaction is unclear. Here, we elucidate the structure of glycosyl cations carrying 4,6-O-benzylidene groups using cryogenic infrared ion spectroscopy and computational methods. The data reveal that the intermediates unexpectedly form anhydro cations, which correlates well with the stereoselective outcome of SN1-type glycosylations. The study highlights how cryogenic infrared spectroscopy can unravel novel intermediates in sugar chemistry and how this structural data can be linked to reactions in solution.
FCM-SWA : Hybrid Intelligent Approach Combining Fuzzy C-Means and Sperm Whales Algorithm for Cyber-Attack Detection in IoT Networks
Authors: Elsedimy E. I. , AboHashish Sara M. M. 
Published: November 2023

Abstract
Recently, the rapid proliferation of Internet of Things (IoT) technology has led to the development of smart cities, which utilize IoT for various applications, such as traffic monitoring, smart farming, connected vehicles, and environmental data collection. However, one of the most significant challenges faced by smart cities is the ever-present cyber threat to sensitive data. Therefore, a novel IoT-based smart model based on the Fuzzy C-Mean (FCM) and the Sperm Whale Algorithm (SWA), namely, FCM-SWA, was proposed to identify and mitigate cyber-attacks and malicious events within smart cities. First, a recent SWA optimization approach is used to improve FCM's performance and provide effective defenses against various forms of smart city threats. Next, an adaptive threshold strategy is introduced to enhance SWA's global search capabilities and prevent them from converging to local optima. Finally, an efficient scaling approach is proposed as an alternative to traditional normalization methods. The performance of the proposed model is evaluated on three public datasets: NSL-KDD, the Aegean WiFi intrusion dataset (AWID), and BoT-IoT. The accuracy of the proposed FCM-SWA model for the NSL-KDD, AWID, and BoT-IoT datasets is 98.82%, 96.34%, and 97.62%, respectively. Experimental results indicate that the proposed model outperforms related and state-of-the-art techniques in terms of accuracy, detection rate, precision rate, and F1-scores.
Multi-User and multi-keyword verifiable encrypted speech retrieval method based on blockchain
Authors: Li Fang-Peng , Zhang Qiu-yu , Huang Yi-bo , Wang Kai , Fan Le-tian 
Published: November 2023

Abstract

Aiming at the existing encrypted speech retrieval schemes that do not support multi-user multi-keyword retrieval, low retrieval efficiency and accuracy, lack of verifiability of encrypted speech retrieval results, and user fairness, a multi-user and multi-keyword verifiable encrypted speech retrieval method based on blockchain was proposed. Firstly, use the advanced encryption standard-128 (AES-128) to encrypt the speech and upload it to the cloud server. Secondly, the Mel-frequency cepstral coefficient (MFCC) and Filter bank (Fbank) speech features are extracted and fused into new MFCC-Fbank features, which are input into the designed CNN-BiGRU model for training. These features are used to extract more robust deep features to construct hash codes and are used as searchable encrypted keywords. Finally, use smart contracts to store encrypted speech hash codes and corresponding index values and manage multi-user keys through trusted institutions. When retrieval, smart contracts are used as trusted third parties for retrieval work, and the designed adaptive homomorphic Message Authentication Code (MAC) algorithm is used to verify the correctness of the retrieval results, ensuring fairness in verification and data privacy. The experimental results show that the proposed method effectively prevents user privacy leakage and improves encrypted speech retrieval accuracy and data security under multi-user and multi-keyword conditions.
Predictive Detection of Breast Cancer with Artificial Neural Network and Support Vector Machine
Authors: Kaur Prabhpreet 
Published: November 2023

Abstract
The early detection of breast cancer is critical as it is the major cause of cancer in women. With an increase in population, the risk of death from breast cancer is also increasing, so, there is a need for a system that can automatically detect disease and aids medical health workers. The chapter contrasts the use of Machine Learning (ML) algorithms with two benchmark datasets, Wisconsin and the Coimbra datasets used to test the algorithms. The algorithm’s output is evaluated in terms of accuracy, precision, and recall. These techniques also provide the ROC and Area Under the Curve (AUC). According to the results, ANN beats SVM for both datasets giving an accuracy of 97.37% and 75% respectively.
Conditions on detecting three-photon entanglement in psychophysical experiments
Authors: GASSAB LEA , Pedram Ali , Müstecaplıoğlu Özgür Esat 
Published: November 2023

Abstract
This paper explores the sensitivity of the human visual system to the quantum entangled photons. We examine the possibility of human subjects perceiving multi-photon entangled state through psychophysical experiments. Our focus begins with a two-photon entangled state to make a comparative study with the literature by taking into account additive noise for false positive on two-photon entanglement perception by humans. After that, we limit our similar investigation to a three-photon entangled state for simplicity in higher dimensions. To model the photodetection by humans, we employ the probability of seeing determined for coherently amplified photons in Fock number states, including an additive noise. Our results indicate that detecting two-photon and three-photon entanglement with the human eye is possible for a certain range of additive noise levels and visual thresholds.
Determinants of birth Asphyxia among newborns in Adama Hospital Medical College, Adama town, Oromia region, Ethiopia: A case control study
Authors: Alemayehu Terefe , Fati Nesra Mohammed , Megerso Abebe , Deksisa Alem 
Published: November 2023

Abstract
Background: Perinatal asphyxia is a common and serious global health problem. According to the World Health Organization, four million neonatal deaths occur each year due to birth asphyxia. Babies born in sub-Saharan Africa have a very high risk of birth asphyxia, which accounts for approximately 280,000 deaths per year. In Ethiopia, nearly 250,000 children die every year before reaching their fifth birthday; approximately one-fourth of these are newborns who die of birth asphyxia. Although asphyxia is a serious health problem, evidence on its determinants is scarce or not readily available in the country in general, and in the study area in particular. Therefore, this study aimed to identify the determinants of birth asphyxia in newborns.
Methods: A retrospective case-control study was conducted involving a sample of 345 newborns born at Adama Hospital Medical College from November 1, 2017, to February 30, 2018. All newborns diagnosed with birth asphyxia (Apgar score < 7 at 1st minute) were considered "cases" while newborns with no asphyxia (Apgar score ≥ 7 at 1st minute) were considered "controls.” The sample size was determined using the Epi Info 7 Statcalc in the facility with assumptions of a 95% confidence interval, 80% power, and an odds ratio of 2.5. Ethical issues were secured by the ethical committee of the Adama Hospital Medical College. Primary data were collected using structured and interviewer-administered questions regarding possible risk factors from mothers and newborns. The collected data were checked for completeness, entered using Epi Info7, and exported to SPSS version 20 for analysis.
Results: Of 345 newborns, 115 were cases and 230 were controls. The median maternal age in the case and control groups was 26 years, with IQR of 23–30 years and 23–29 years, respectively. Significant perinatal risk factors of birth asphyxia were rural residence (AOR: 2.34 95% CL 1.29-4.26), prolonged labour (AOR: 10.12 95% CL 5.36-19.11), prolonged rupture of membrane (AOR: 3.47 95% CL 1.52-7.92), instrumental delivery (AOR: 2.67 95% CL 1.15-6.16), delivery by emergency C/S (AOR: 3.9 95% CL 1.84-8.63), cephalopelvic disproportion (AOR: 5.90 95% CL 1.54-30.17), breech presentation (AOR:2.4 95% CL 1.01-5.74) Preterm delivery (AOR: 9.34, 95% CI: 2.20–39.70) and low birth weight (AOR: 2.69, 95% CI: 1.06–6.75)
Conclusion: Most of the risk factors associated with birth asphyxia can be prevented. Therefore, early and accurate diagnosis and proper management can reduce the incidence of birth asphyxia.
Interpreting test temperature and loading rate effects on the fracture toughness of polymer-metal interfaces via time-temperature superposition
Authors: DelRio Frank W. , Huber Todd , Jaramillo Rex K. , Reedy E. David , Grutzik Scott J. 
Published: November 2023

Abstract

In this letter, we present interfacial fracture toughness data for a polymer-metal interface where tests were conducted at various test temperatures T and loading rates An adhesively bonded asymmetric double cantilever beam (ADCB) specimen was utilized to measure toughness. ADCB specimens were created by bonding a thinner, upper adherend to a thicker, lower adherend (both 6061 T6 aluminum) using a thin layer of epoxy adhesive, such that the crack propagated along the interface between the thinner adherend and the epoxy layer. The specimens were tested at T from 25 to 65°C and δ ̇ from 0.002 to 0.2 mm/s. The measured interfacial toughness Γ increased as both T and δ ̇ increased. For an ADCB specimen loaded at a constant δ ̇, the energy release rate Γ increases as the crack length a increases. For this reason, we defined rate effects in terms of the rate of change in the energy release rate Ġ. Although not rigorously correct, a formal application of time-temperature superposition (TTS) analysis to the Γ data provided useful insights on the observed dependencies. In the TTS-shifted data, Γ decreased and then increased for monotonically increasing Ġ. Thus, the TTS analysis suggests that there is a minimum value of Γ. This minimum value could be used to define a lower bound in Γ when designing critical engineering applications that are subjected to T and δ ̇ excursions.
Vibrotactile enhancement of musical engagement
Authors: Siedenburg Kai , Michel Bürgel , Özgür Elif , Scheicht Christoph , Töpken Stephan 
Published: November 2023

Abstract
Sound is sensed by the ear but can also be felt on the skin, by means of vibrotactile stimulation. Although previous studies have addressed audio-tactile perception for music, the underlying perceptual dimensions of vibrotactile enhancement of music listening remain poorly understood. Here, 41 listeners were presented with vibrotactile stimuli via a chair’s four surfaces (left and right arm rests, back rest, seat surface) in addition to music presented over headphones. Vibrations were driven by different tracks of the music for each surface (multi condition) or conjointly by a mono-rendering (mono condition), in addition to incongruent and headphones-only conditions. Listeners evaluated excerpts of popular music on six scales, probing valence, arousal, groove, the feeling of being part of a live performance, the feeling of being part of the music, and liking. Results indicated that the multi-and mono vibration conditions robustly enhanced the nature of the musical experience compared to headphones alone, but both did not differ significantly from each other. They particularly enhanced the key latent dimension of ‘musical engagement’, encompassing the sense of being a part of the music, arousal, and groove. These findings highlight the specific role of vibrotactile cues in creating intensive musical experiences.
Comprehensive study reveals heterogeneity among the Klebsiella pneumoniae Species Complex Phenotypes
Authors: Rodríguez-Medina Nadia , Rodríguez-Santiago Jonathan , Alvarado-Delgado Alejandro , Sagal-Prado Alan , Silva-Sánchez Jesús , Cruz Miguel Angel , Ares Miguel Angel , Sánchez-Arias Margarita , Morfín-Otero Rayo , Hernández-Castro Rigoberto , Cornejo-Juárez Patricia , Jiménez-Villanueva Emmanuel , Sánchez-Francia Domingo , Garza-Ramos Ulises 
Published: November 2023

Abstract
Here, we conducted a comprehensive analysis of 356 Klebsiella pneumoniae species complex (KpSC) isolates. Overall, K. pneumoniae (82.3%), K. variicola (2.5%) and K. quasipneumoniae (2.5%) were identified. These isolates comprised 321 classical-KpSC, 7 hypervirulent-KpSC and 18 hypermucoviscous-like-KpSC. The cl-KpSC (207/321) and hmv-like-KpSC (8/18) were ESBL-producers and colistin-resistant isolates harboring different types of carbapenemases. Several assays and whole-genome sequencing were performed in a subset of KpSC isolates. Capsule amount differed in all hv and hmv-like produced higher capsule amounts than cl. Murine sepsis model showed that most of cl were nonlethal and unexpectedly some hv required 108 CFUs to cause 100% mortality whilst the hmv-like cause 100% mortality with 3x108 CFUs. hv-Kpn isolates were associated with ST23-KL1, ST86-KL2, ST380-KL2 and ST3999-KL2; the latter corresponded to a novel hypervirulent clone. Phylogenetic analysis showed that hv-Kpn strains ST23-KL1 and ST86-KL2 were clustered with reference hv-Kpn strains but the hv-Kpn clones ST3999, ST380 and hmv-like-Kpn isolates were closely related to cl-Kpn MDR strains this was supported by a wgSNP-based phylogeny. The information collected here is important to understand how the frequency and evolution of KpSC may changed mainly in Hypervirulent KpSC. Likewise, this study shows the main mechanism of resistance to colistin in Mexico.
High-Speed Photonic Decoder Employing Two-Dimensional Photonic Crystals
Authors: Esmaeili Amir Hosein , Daghighazar Shadi , Chaharmahali Iman 
Published: November 2023

Abstract

The objective of this study is to design, analyze, and simulate a novel and ultrafast 1 × 2 photonic decoder. The device is composed of two-dimensional (2D) photonic crystals where silicon rods are placed in air. It includes two beam splitters and a phase shifter, which are implemented using point defects. Additionally, line defects are integrated into the device to steer the light wave without causing dissipation. The simulation yielded 0.1 ps response time, contrast ratio of 2.55 dB, and a bit rate of 0.66 Tb/s. The simulation was performed using 2D finite difference time domain and plane wave expansion methods. The findings suggest that this device holds great potential as a candidate for all-optical digital integrated circuits.