bluuebunny/crossref_metadata_2025_split huggingface dataset:
A large posterior fragment in pertrochanteric fractures – pathoanatomic and 3D CT study
Authors: Bartoníček Jan , Bartoška Radek , Skála-Rosenbaum Jiří , Alt Jan , Naňka Ondřej , Tuček Michal 
Published: October 2023

Abstract

Background
Three-part pertrochanteric fractures with a large posterior fragment have been reported both in historical and recent 3D CT studies, however, without a detailed description.
Methods
From the collection of the Institute of Anatomy, the authors obtained 6 specimens of hip joints of individuals who had sustained a three-part pertrochanteric fracture with a large posterior fragment, and 7 patients with the same type of fracture were identified in a cohort of 56 patients with a trochanteric fracture documented by 3D CT reconstructions. The study focused on the anatomy of the posterior fragment, the courses of the fracture lines, the integrity of the medial cortex and the lateral trochanteric wall.
Results
Two types of the posterior fragment were identified, the quadrangular and the triangular ones. Separation of either of them markedly weakened the lateral trochanteric wall, more specifically, one quarter to two-thirds of its lateral surface. The triangular fragment was associated with shear instability on the medial aspect of the proximal femur and was markedly displaced in 5 of 7 cases. Exact identification of the shape and size of the posterior fragment was impossible with the use of postinjury radiographs alone.
Conclusion
In agreement with historical and recent CT studies, the findings of this study confirm the existence of a three-part type of pertrochanteric fracture with a large posterior fragment, and provides its detailed description, including its relevance to clinical practice.
Hole quality and thermal defects in drilled CFRP by nanosecond pulsed laser
Authors: Liu Xinyi , Yang Sen , Gao Youdong , Xu Man , Wan Yu , Wu Meng , Li Lin , Wang Chenzhuo , Zhong Mian , Wang Biyi , Jiang Yong 
Published: October 2023

Abstract
To explore the effect of nanosecond pulse laser drilling on the quality of carbon fiber reinforced polymer (CFRP). The effects of laser parameters such as laser power, scanning speed, pulse width and laser frequency on micro-hole quality and the thermal damage generated during the drilling process, were studied by using the univariate methods and the orthogonal experimental method for drilling micro-holes with a diameter of 0.4 mm using a 1064 nm fiber laser. The results indicate that with the use of pumping at the entrance, the hole diameter and the heat-affected zone (HAZ) width at the entrance and exit increased significantly with the increase of laser power, pulse width and frequency, and the decrease of scanning speed. The variation in HAZ width at the exit was correlated with whether the energy reached the carbon fiber ablation threshold. All the holes were tapered and the hole taper was closely related to the magnitude of the change in the laser parameters on the hole diameter at the entrance and exit. Holes with a taper of about 0.3 were obtained when the parameter combination was 99 W, 50 mm/s, 13 ns and 1500 kHz. Experiments indicate that laser power and pulse width are important factors affecting the quality of micro-hole processing. However, thermal damage defects such as striations, micro-cracks, delamination, voids and surface fiber ‘fish scale’ peeling can occur during nanosecond laser drilling.
Novel Electrochemical Sensor based on rGO@TiO2 Composite Material and Ion-Imprinted Polymer Modification for Highly Selective Detection of Cadmium Ions in Real Samples
Authors: Zhang Yi , Liu Yanmeng , Huang Weihong , Wang Baozhi , Xu Wanzhen , Yang Wenmiing 
Published: October 2023

Abstract
Cd(II) has extensive applications in various industries such as electronics, batteries, and coatings, but it is also known as a highly hazardous pollutant. An electrochemical sensor based on ion-imprinted polymers (IIPs) and reduced graphene oxide-titanium oxide (rGO@TiO2) was prepared for the selective sensitive determination of Cd(II) in real samples. The IIPs were prepared using modified SiO2 as the carrier by surface imprinting technology, which increased the imprinting sites of the polymer and made template ions easy to eluate and improved the electron transfer rate and separation efficiency. The Cd(II) ion-imprinted electrochemical sensor was constructed by mixing IIPs with rGO@TiO2 in proportion. The morphologies of the imprinted composites were characterized by TEM, FT-IR, and XRD. The electrochemical behavior of imprinted polymers was characterized by CV, DPV, and EIS. The results demonstrated that the sensor has good selectivity for target Cd(II). Under optimized experimental conditions, the electrochemical sensor showed a good linear relationship in the range of 10− 8 ~ 10− 5 mol L-1, and the lowest detection limit was 1.2×10− 8 mol L-1. The sensor had excellent repeatability and stability in addition to high sensitivity and strong selectivity. Finally, the electrochemical sensor has been successfully applied to the determination of trace Cd(II) in practical samples.
Uncovering anisotropic effects of electric high-moment dipoles on the tunneling current in δ-layer tunnel junctions
Authors: Granado Juan Mendez , Mamaluy Denis 
Published: October 2023

Abstract
The precise positioning of dopants in semiconductors using scanning tunneling microscopes has led to the development of planar dopant-based devices, also known as δ-layers, facilitating the exploration of new concepts in classical and quantum computing. Recently it have been shown that two distinct conductivity regimes (low- and high- bias regimes) exist in δ-layer tunnel junctions due to the presence of quasi-discrete and continuous states in the conduction band of δ-layer systems. Furthermore, discrete charged impurities in the tunnel junction region significantly influence the tunneling rates in δ-layer tunnel junctions. Here we demonstrate that electrical dipoles, i.e. zero-charge impurities, present in the tunnel junction region can also significantly alter the tunneling rate, depending, however, on the specific conductivity regime, and orientation and moment of the dipole. In the low-bias regime, with high-resistance tunneling mode, dipole impurities of nearly all orientations and moments can alter the current, indicating the extreme sensitivity of the tunneling current to the slightest imperfection in the tunnel gap. In the high-bias regime, with low-resistivity, only dipole defects with high moments and oriented in the directions perpendicular to the electron tunneling direction can significantly affect the current, thus making this conductivity regime significantly less prone to the influence of dipole defects with low-moments or oriented along the propagation direction.
Induced turbulence in the quantum channel of high dimensional QKD system using structured light
Authors: KAMRAN MUHAMMAD , KHAN MUHAMMAD MUBASHIR , MALIK TAHIR 
Published: October 2023

Abstract
In the last two decades, structured light patterns with orbital angular momentum (OAM) have been extensively utilized in quantum cryptography or quantum key distribution, which is generally considered an unconditionally secure method of secret key transmission between two distant communicating entities. High-dimensional encoding of quantum bits in quantum key distribution improves the security and information-carrying capability of a quantum signal. Significant degradation in the efficiency of such communication is observed due to the aberration of OAM states under atmospheric turbulence. In this paper, we focus on analyzing the impact of atmospheric turbulence on the error-rates of quantum key distribution, which is considered the benchmark in analyzing the security of such communication over the quantum channel in the presence of an intruder (man-in-the-middle). Our results show that turbulence under normal conditions does not significantly affect the successful transmission of secret quantum bits between sender and receiver. Furthermore, we identify an interesting variation in the signature of error-rates to clearly detect the presence of an intruder as a result of medium-level turbulence.
Complex Networks Disintegration Based on Learning Automata
Authors: Eslahi Neda , Masoumi Behrooz 
Published: October 2023

Abstract

Complex network disintegration stands as a paramount challenge within network science, playing a pivotal role in the mitigation of malicious network behaviour. Beyond its defensive role, it offers a strategy with broader applicability, encompassing risk prediction for networks with positive attributes. Complex networks, deeply rooted in graph theory, serve as a fundamental modelling framework across diverse problem domains, ranging from social networks, communications, and telecommunications to security, power distribution, information transmission, and even weather analysis with geographical implications. Yet, the disintegration of real-world networks carries tangible costs, necessitating the development of cost-effective methods a pressing concern when confronting such networks. Additionally, real-world networks often exhibit heterogeneity, mandating practical considerations in proposed solutions. Traditionally, complex network disintegration has relied on graph theory-based algorithms and heuristic methods. Recent years, however, have witnessed the incorporation of learning algorithms that engage dynamically with complex environments. Reinforcement learning, owing to its interactive nature with the environment, emerges as a well-suited methodology. Moreover, this paper introduces an innovative approach leveraging the Learning Automata algorithm to enhance existing disintegration strategies. This research explores the central role of complex network disintegration, bridging conventional graph theory techniques with cutting-edge reinforcement learning methods. The outcome is a more comprehensive and adaptable framework for addressing real-world network challenges, spanning defence against malicious networks with the optimized cost in unknown networks.
Modeling cassava root system architecture and the underlying dynamics in shoot-root carbon allocation
Authors: Nattharat Punyasu , Thaiprsit Jittrawan , Kalapanulak Saowalak , Saithong Treenut ,   Johannes Auke Postma (S108)
Published: October 2023

Abstract

· Background and Aims:
Plants store carbohydrates for later use during, e.g., night, drought, and recovery after stress. Carbon allocation presents the plant with tradeoffs, notably between growth and storage. We asked how this tradeoff works for cassava (Manihot esculenta)pre- and post-storage root (SR) formation and if manipulation of the number of storage organs and leaf growth rate might increase yield.
· Methods:
We developed a functional-structural plant model, called MeOSR, to simulate carbon partitioning underlying cassava growth and SR formation in conjunction with the root system's three-dimensional (3D) architecture (RSA). We validated the model against experimental data and simulated phenotypes varying in the number of SR and leaf growth rate.
· Results:
The simulated 3D RSA and the root mass closely represented those of field-grown plants. The model simulated root growth and associated carbon allocation across development stages. Substantial accumulation of non-structural carbohydrates (NSC) preceded SR formation, suggesting sink-limited growth. SR mass and canopy photosynthesis might be increased by both increasing the number of SR and the leaf growth rate.
· Conclusion:
MeOSR offers a valuable tool for simulating plant growth, its associated carbon economy, and 3D RSA over time. In the first month, the specific root length increased due to root branching, but in the third month, it decreased due to secondary root growth. The accumulation of NSC might initiate SR development in cassava. Cassava growth is relatively slow during the first 3 months, and a faster crop establishment combined with a greater SR growth might increase yield.
Risk Factors, Prognostic Indicators, and a Prognostic Nomogram for Distant Metastasis in Thyroid Cancer Patients without Lymph Node Metastasis
Authors: Yu Xiaoqing , Deng Qin , He Lingyun , Hu Daixing , Yang Lu 
Published: October 2023

Abstract
Background:
Despite negative lymph node (N0) status, thyroid cancer (TC) patients may still experience distant metastasis (DM), which significantly affects their survival. This study aimed to investigate the risk factors for DM in thyroid cancer patients (N0) and develop a predictive nomogram model for analyzing the prognosis of TC N0 patients with DM.
Methods:
Collected data from the Surveillance, Epidemiology, and End Results (SEER) database for 18,487 thyroid cancer patients (N0) between 2004 and 2015 were analyzed. Multivariate logistic and Cox regression models were used to identify independent risk factors for DM and assess 1-, 3-, and 5-year overall survival (OS). Kaplan-Meier (K-M) survival curve was used to analyze the survival probability and cumulative risk of patients with different variables in the subgroup of DM in TC N0, and the Cox analysis results were used to construct an innovative nomogram model. The nomogram model's performance was evaluated using receiver operating characteristic (ROC) curves, concordance index (C-index), and calibration curves.
Result:
Six variables, including age (P < 0.001), race (P = 0.002), grade (P < 0.001), histology (P < 0.001), T stage (P < 0.001), and median income (P = 0.030), were identified as independent predictors of DM in thyroid cancer patients (N0), and we further achieved a good AUC of 0.837 (95% CI: 0.812–0.862) when predicting the risk of DM in TC N0. Similarly, age at diagnosis (p<0.001), sex (p<0.001), grade (p<0.001), histology (p<0.001), T stage (p<0.001), tumor size (p<0.001), and surgery (p<0.001) were identified as independent prognostic factors of DM in thyroid cancer patients (N0). An OS predictive nomogram was developed based on these factors, which demonstrated good performance according to the ROC, C-index, and calibration curves. In the training cohort, the areas under the ROC for 1-, 3-, and 5-year OS were 0.941, 0.915, and 0.902, respectively, while in the validation cohort, they were 0.929, 0.913, and 0.899.
Conclusion:
This study examined the clinicopathological features
associated with the risk and prognosis of DM in thyroid cancer patients (N0), and successfully established and validated a nomogram capable of predicting OS in individual patients with DM. The nomogram is highly useful for the timely identification of thyroid cancer patients (N0) at high risk of DM by physicians, enabling individualized survival evaluations and treatment for TC patients with DM (N0).
Characterizing the microbiome composition of the nares, oropharynx, and hand of monozygotic twins and its interplay with Staphylococcus aureus carriage
Authors: Dalman Mark , Simison Brian , Nielson Danny , Bhatta Sabana , Ramahi Noor , Yee Clair , Thapaliya Dipendra , Kadariya Jhalka , Cheatham Shanice , Olson Hailee 
Published: October 2023

Abstract
Background
Staphylococcus aureus is a gram-positive bacterium commonly found in the nares and oropharynx of one in three individuals and has the potential to cause significant health problems. With antibiotic resistant strains causing 11,000 deaths yearly and ~ 2% of the population nasally colonized with MRSA, a search for predictive markers and causal relationships between carriage have been long-sought goals. Within our study, we leveraged monozygotic twin participants in concert with spatial microbiome analyses to characterize impacts of S. aureus on composition.
Results:
We recruited 147 monozygotic twin pairs and characterized three sites: nares, oropharynx, and hand microbiomes using 16S rRNA v3-v4 sequencing in addition to S. aureus carriage status. Prevalence of S. aureus was highest in the oropharynx followed by nares and hand with concordance between twin pairs highest in the nares, followed by oropharynx. All microbiome sites were significantly modified by the presence of S. aureus as illustrated by beta diversity and DESeq2 analyses. Microbiome composition was most similar in twins’ nares that were S. aureus culture positive concordant, whereas twins that were culture negative concordant had the most similarity in the Oropharynx. Of significance, Moraxella nonliquefacians and Capnocytophaga were inversely associated with S. aureus in the nares and oropharynx, respectively. Based on Maaslin2 analyses, we identify that S. aureus prevalence significantly affected pathways associated with Biosynthesis of Secondary Metabolites, Infectious Diseases, Amino Acid Metabolism, Cellular Processes and Signaling, and Immune System Diseases only in the nares microbiome.
Conclusions:
This improved understanding of S. aureus colonization on nares, oropharynx, and hand microbiomes in monozygotic twin pairs is a further step towards unraveling the degree to which the microbiome are influenced by host genetics and S. aureus carriage.
A Multimodal Large Language Model for Forestry in pest and disease recognition
Authors: Zhang Maolin , Li Xianyong , Du Yajun , Rao Zihan , Chen Songlin , Wang Weicheng , Chen Xiaoliang , Huang Dong , Wang Shumin 
Published: October 2023

Abstract
In the context of generative multimodal dialogue, the amalgamation of image and text forms the fundamental basis for a wide array of visual and language tasks. Despite the proliferation of large language models (LLMs), research on training LLMs for multimodal reasoning has remained relatively scarce. The progression of existing multimodal models has been propelled by using expansive image-text datasets in broader domains. Nevertheless, these models need refinement when comprehending and engaging in dialogue concerning Chinese forestry biological images. This paper proposes an efficient and adaptive multimodal large language model for forestry (MLLM-For) in pest and disease recognition. The central concept involves harnessing our meticulously constructed, expansive Chinese forestry biological image caption dataset. We utilize open-ended instruction-following data to master the intricacies of open-ended dialogue semantics, facilitating the comprehensive assimilation of knowledge within forestry biology. In particular, the Querying Transformer (Q-Former) module is a conduit linking pre-trained visual and language models. Using image-text pairs, the China Open Source Chat Language Model (ChatGLM) can now align vocabulary specific to forestry pests and diseases. By aligning image features with the pre-trained language model, we undertake concurrent Low-Rank Adaptive (LoRA) fine-tuning of the ChatGLM model. Furthermore, we engage in high-caliber instruction data fine-tuning to 1 tailor it to the proposed multimodal task. The proposed MLLM-For model show-cases impressive proficiency in comprehending and engaging in dialogue regarding Chinese forestry pests and disease images. It also displays exceptional capabilities in multimodal dialogue and is adept at adhering to open-ended directives for retrieving information about forestry pests and diseases. Empirical findings affirm the competitive performance of the MLLM-For model within the realm of Chinese multimodal dialogue, surpassing five leading multimodal large language models.
Investigation of genetic variants causing Bardet–Biedl syndrome in Iranian families: Identification of a founder mutation in BBS2, p.T157T
Authors: Feizabadi Masoumeh Heidari , Alerasool Masoome , Eslahi Atieh , Esmaeilzadeh Emran , Mehrjardi Mohammad Yahya Vahidi , Saket Mitra , Farokhi Shima , Fatahi Zohreh , Khorshid Hamid Reza Khorram , Mojarrad Majid 
Published: October 2023

Abstract
Background
Bardet-Biedl Syndrome (BBS) is a rare inherited ciliopathy disorder characterized by a wide range of clinical symptoms affecting multiple body systems. All BBS genes are involved in cilia function as a part of the BBSome complex. Mutations of BBS genes are not completely understood, suggesting that more research is needed to develop a molecular diagnostic strategy for this syndrome.
Methods and Results
Whole exome sequencing (WES) was performed on eighteen patients. A comparative study based on Runs of homozygosity (ROH (calling was performed using the BCFtools/RoH software on WES data. The potential pathogenicity of the detected mutations and the effect on splicing was predicted by in-silico analysis. Copy Number Variation (CNV) analysis was performed from the read depth of WES data using the ExomeDepth pipeline in unsolved BBS patients. Eight variants including four novel mutations, and a synonymous splicing variant (c.G471A) in BBS2 were identified. By examining homozygous regions among these patients, the existence of common homozygous regions containing the identified mutation was proved in patients with Baloch ethnicity. In-silico analysis predicted the effect of the c.G471A mutations on BBS2 mRNA splicing, this mutation leads to broken wild-type donor site and intron retention in the mature mRNA. CNV analysis revealed a deletion of exons in the BBS1 gene.
Conclusion
Our results declared the founder mutation c.G471A in the BBS2 gene in the Baloch ethnicity of the Iranian population, which can determine the diagnostic approach of this syndrome in future studies.
Bayesian inversion of MDJ seismograms for source parameters of contained DPRK underground nuclear explosions
Authors: Ziolkowski Anton 
Published: October 2023

Abstract
Using seismograms recorded at Mudanjiang (MDJ) seismic station in China, I propose a new approach to obtain source parameters of the five Democratic People’s Republic of Korea (DPRK) contained underground nuclear explosions. The contained events were located within about 1 km of each other at the DPRK Punggye-ri nuclear test site at Mount Mantap, a granite peak. The Green’s function from Punggye-ri to MDJ is assumed to be the same for each source. Each source is modelled as a spherical cavity in a homogeneous isotropic elastic full space, with four independent parameters constrained by published data on the properties of granite and analysis of the recorded MDJ seismograms. The effect of the ground surface is included as a planar reflection that modifies the pressure at the cavity boundary. The Green’s function for each event is estimated by deconvolving the seismogram for the estimated source time function. Very fast simulated annealing (VFSA) is used to search the parameter space to minimise the root-mean square difference among the estimated Green’s functions and their mean. The estimated Green’s functions are not identical, but are similar, and differ in amplitude by less than a factor of 4. The estimated source time functions may be used to obtain Green’s functions from Punggye-ri nuclear test site to other seismic stations by deconvolution of the corresponding seismograms. Mapping the nonlinear zones surrounding each explosion indicates that this part of the site was destroyed by the underground nuclear tests before its official destruction on 24 May 2018.