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A caveat about the use of trigonometric functions in statistical tests of nutritional geometry models

Adoption of K-means clustering algorithm in smart city security analysis and mythical experience analysis of urban image

Objective An information security evaluation model based on the K-Means Clustering (KMC) +  Decision Tree (DT) algorithm is constructed, aiming to assess its value in evaluating smart city (SC) security. Additionally, the impact of SCs on individuals’ mythical experiences is investigated. Methods An information security analysis model based on the combination of KMC and DT algorithms is established. A total of 38 SCs are selected as the research objects for practical analysis. The practical feasibility of the model is assessed using the receiver operating characteristic (ROC) curve, and its performance is compared with that of the Naive Bayes (NB), Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM), and Gradient Boosting Machine (GBM) classification methods. Lastly, a questionnaire survey is conducted to obtain and analyze individuals’ mythical experiences in SCs. Results (1) The area under the ROC curve is significantly higher than 0.9 (0.921 vs. 0.9). (2) Compared to the NB and LR algorithms, the security analysis model based on the combination of KMC and DT algorithms demonstrated higher true positive rate (TPR), accuracy, recall, F-Score, AUC-ROC, and AUC-PR. Additionally, the performance metrics of RF, SVM, and GBM are similar to those of the KMC+DT model. (3) When the attributes are the same, the difference in smart risk levels is small, while when the attributes are different, the difference in risk levels is significant. (4) The support rates for various types of new folk activities are as follows: offline shopping festivals (17.6%), New Year’s Eve celebrations (16.7%), Tibet tourism (15.6%), spiritual practices (16.2%), green leisure (16.0%), and suburban/rural tourism (15.8%). (5) High-risk cities (Grade A) showed stronger support for modern activities such as offline shopping festivals and green leisure, while low-risk cities (Grades C and D) tended to favor traditional cultural activities. Conclusion The algorithm model constructed in this work is capable of effectively evaluating the information security risks of SCs and has practical value. A good city image and mythological experience are driving the development of cities.

Characteristics stochastic analysis of long and narrow deep excavations under soil spatial variability

Abstract The mechanical properties of soil, resulting from the weathering of rocks through physical and chemical processes, exhibit spatial variability. This variability introduces uncertainties in the design and characteristics of excavation projects. To address these uncertainties caused by soil spatial variability, safety factors are commonly used in excavation design. However, using the same safety factor for different indicators of soil spatial variability is illogical. Therefore, specialized research on the characteristics of deep excavations in the context of soil spatial variability is necessary, as it provides the theoretical basis for rational excavation design. In this study, we assumed that soil parameters follow a lognormal distribution, while spatial correlation adheres to a Gaussian function. We developed a random finite element algorithm for deep excavations, which incorporated Python programming and the ABAQUS computational platform. This algorithm was created within the framework of random field theory and Monte Carlo simulation. The results of our study indicate that, influenced by soil spatial variability, the lateral wall movements and ground surface settlements exhibit discrete distributions near the deterministic results. The maximum deformation of the excavation follows a normal distribution, while the pattern of ground surface settlements demonstrates diversity and chaotic characteristics. The extent to which soil spatial variability affects deep excavations is correlated with indicators of this variability. As the coefficient of soil spatial variability increases, the diversity and chaotic characteristics of ground surface settlements become more prominent. The locations of maximum ground surface settlement and maximum deformation becomes more scattered. Consequently, the probability of excavation failure increases, and the reliability index of the excavation decreases. In summary, soil spatial variability significantly impacts deformation prediction and safety control during the design and construction stages of deep excavations. Therefore, it is crucial to consider the influence of soil spatial variability when designing deep excavations, based on the variability indicators.

Research on the evaluation of China’s Supply Chain Finance policy based on text mining

Supply Chain Finance (SCF) aims to manage the capital flow, logistics flow, and information flow of small and medium-sized enterprises (SMEs) in the upstream and downstream of the supply chain while optimizing supply chain risk control. Like other types of financial services, the development of SCF is highly influenced by policy factors; however, related research remains relatively limited. This study aims to explore the current state of SCF policymaking in China and provide scientific recommendations for the development of SCF from a policy perspective. First, using the BERTopic model, 3,439 SCF-related academic papers and 181 central-level SCF policy texts from the CNKI database were analyzed for thematic clustering. Then, by comprehensively considering the thematic distribution of SCF research and the operational characteristics of SCF, the Policy Modeling Consistency (PMC) Index model was constructed to evaluate SCF policy texts. The findings reveal several issues in China’s SCF policymaking: limited thematic focus, fluctuating levels of policy formulation, and significant homogenization of policy content. The study proposes several optimization recommendations for SCF policies, including expanding the scope of policy focus, fostering synergy among different types of policies, diversifying the use of policy tools, and broadening the range of target groups addressed by policies.

Relational information framework, causality, unification of quantum interpretations and return to realism through non-ergodicity

Abstract In the framework of relational information, we explore analogs of physical theories and their properties. Specifically, we investigate the causal characteristics of relational information, examining how initial knowledge impacts future relational understanding of the universe/system. To achieve this, we establish a parameter space defining relational structures called dendrograms, exhibiting causal properties akin to those of Minkowski metric. Subsequently, we propose a statistical-dynamical model on this Minkowski-like parameter space, unifying Bohmian and Many Worlds interpretations of quantum theory in the framework of relational information. Additionally, we provide an analytical proof of the non-ergodicity of the relational information framework, revealing CHSH inequality violations as an emergent phenomenon. Our focus on relational information underscores its significance across scientific disciplines, where a single measurement or observation lacks meaning without context.

Leveraging time for better impulse control: Longer intervals help ADHD children inhibit impulsive responses

Children diagnosed with an Attention Deficit Hyperactivity Disorder (ADHD) often exhibit impulsivity and timing difficulties. Here, we investigated whether children (mean age =  9.9 years) with combined type ADHD, comprising both hyperactive-impulsive and inattentive symptoms, could use the temporal predictability of an event to help inhibit impulsive behaviour. In an adapted Simon task, we measured the effects of temporal predictability on the speed and accuracy of choice reaction times (RT) to targets appearing after short or long intervals. Temporally predictive information was conveyed either explicitly (visual cues) or implicitly (cue-target interval). Analysis of RT distributions allowed us to decompose impulsive behaviour into two key elements: the initial urge to react impulsively, and the subsequent ability to inhibit any impulsive erroneous behaviour. Both healthy controls and ADHD children could use temporal predictability conveyed by temporal cues and the length of the trial to speed their RT. However, in healthy children both explicit and implicit temporal predictability impaired inhibition of impulsive responses. In turn, although children with ADHD had stronger tendency for impulsive responding and abnormal patterns of inhibition as compared to controls, the temporal predictability of the target did not exacerbate these effects. Indeed, responding to targets appearing after long, rather than short, intervals improved inhibition in ADHD children. Taken together, our results suggest that children with ADHD can make use of longer preparatory intervals to help inhibit impulsive behaviour.

Hydrocarbon generation potential and geochemical characteristics comparison of source rocks in the Southwestern Qaidam basin, China

Abstract A primary source rock has developed in the Upper part of the Lower Ganchaigou Formation (E3 2) in the southwestern Qaidam Basin, China. This basin features typical brackish-saline lacustrine deposits, necessitating careful selection of appropriate standards for evaluating hydrocarbon generation potential. The presence of multiple sets of source rocks and complex migration pathways has led to the accumulation of mixed-source oils, complicating the relationship between crude oil and source rocks and the establishment of hydrocarbon migration system. To address these challenge, 113 source rock samples were analyzed using Rock–Eval 6, gas chromatography-mass spectrometry and microphotometer. R-type clustering and principal component analysis were employed to select two out of five biomarker parameters that reflect water salinity and parent material sources for Q-type clustering. The results indicate that the E3 2 source rock exhibits fair hydrocarbon potential and is predominantly composed Type I and Type II1 kerogens. It remains in a low-maturity to mature stage, with deposition occurring in environments characterized by either strong reduction and high salinity or relatively weak reduction and low salinity. The oil is derived from nearby source rocks in the Hongshi, Yingxiongling, and Chekrike-Zahazquan depressions. This study provides new insights into source rock evaluation and oil-source relationship analysis.

Deformation and energy damage characteristics of granite-concrete composite under uniaxial compression

To investigate the influence of the fractured rock-concrete interface on the mechanical response of the rock mass and engineering, the mechanical properties and energy evolution of granite-concrete composite specimens with 16 different fracture inclinations were examined through uniaxial compression particle flow simulation. The results show that when the relative area is constant, the larger the fracture dip angle is, the compressive strength of the composite body presents a similar “peak” type change; the dip angle appears to have the maximum value at 60 o and 90o and the minimum value at 0 o and 30 o, while the peak elastic modulus presents a “waterfall” type change, and the maximum value appears at 90o. The crack types were classified as shear cracks, tensile cracks, secondary shear cracks, secondary tensile cracks, shear-dominated mixed cracks, and tension-dominated mixed cracks. From the crack distribution, it was found that the root cause of crack initiation and propagation was affected by the crack inclination angle. The damage degree increased gradually with the increase of crack inclination angle. When the crack inclination angle was constant, the deterioration degree of the specimen weakened with the increase of relative area s. The elastic energy consumption ratio increases with the shaft deformation, first rapidly and steeply decreasing to the steady inflection point, then slowly increasing to the rapid and steep increase, showing a “fishhook” shape. When the strength failure occurs, the growth speed increases suddenly, and the elastic energy consumption ratio increases suddenly after the K peak. This phenomenon can be used as the basis for the occurrence of strength failure and can be used as a qualitative judgment of strength failure.

Mechanism of skull base osteoradionecrosis explored through laboratory assessment with propensity score-matched analysis

The transcription factor Jun is necessary for optic nerve regeneration in larval zebrafish

Damage to the axons of the adult mammalian central nervous system (CNS) from traumatic injury or neurodegenerative diseases often results in permanent loss of function due to failure of axons to regenerate. Zebrafish, however, can express regeneration-associated genes to revert CNS neurons to a growth-competent state and regenerate damaged axons to functionality. An established model for CNS axon regeneration is optic nerve injury in zebrafish, where it was previously shown that thousands of genes are temporally expressed during the regeneration time course. It is likely that hubs of key transcription factors, rather than individual factors regulate the temporal clusters of expression after injury to facilitate cell survival, regrowth, and synaptic targeting in the brain. One transcription factor of interest in orchestrating CNS axon regeneration is jun. However, it remains unclear if CNS regeneration can progress without Jun. To test this, a transgenic zebrafish line was developed to express a heat-shock inducible dominant negative Jun. Induction of dominant negative Jun downregulated endogenous jun expression and larvae with functional jun knockdown demonstrated impaired retinal ganglion cell axon regeneration. Analysis of select putative Jun target genes, previously shown to be upregulated in adult zebrafish optic nerve regeneration, demonstrated that with functional Jun knockdown, atf3 and ascl1a were significantly downregulated, and sox11a was upregulated at distinct time points. These results position jun as a key regulator for successful optic nerve regeneration, further distinguish the regeneration program from development, and advance our knowledge for the formation of future therapies to treat CNS damage.

A comprehensive study of multiscale pore structural characteristics in deep-buried coals of different ranks

Anatomy education potential of the first digital twin of a Korean cadaver

The objective of this study is to explore innovative integration within the field of anatomy education by leveraging HoloLens 2 Augmented Reality Head-Mounted Display (AR HMD) technology and real-time cloud rendering. Initial 3D datasets, comprising extensive anatomical information for each bone, were obtained through the 3D scanning of a full-body cadaver of Korean male origin. Subsequently, these datasets underwent refinement processes aimed at enhancing visual fidelity and optimizing polygon counts, utilizing Blender software. Unity was employed for the development of the Metaverse platform, incorporating tailored 3D User Experience (UX) and User Interface (UI) components to facilitate interactive anatomy education via imported cadaver models. Integration with real-time remote rendering cloud servers, such as Azure, was implemented to augment the performance and rendering capabilities of the HoloLens 2 AR HMD. The extended reality (XR) content uses the Photon Cloud network for real-time data synchronization and HoloLens 2 voice functionality. The metaverse platform supports user interaction through room creation and joining, with various tools for bone manipulation, color differentiation, and surface output. Collaboration features enable sharing and synchronization of model states. The study highlights the importance of technological innovation in anatomy education for future medical professionals. The proposed content aims to address limitations of traditional methods and enhance learning experiences. Continued efforts in developing and improving such technologies are crucial to equip learners with essential skills for adaptation in the evolving healthcare landscape.

Reply to: A caveat about the use of trigonometric functions in statistical tests of Nutritional Geometry models

Prediction of porosity, hardness and surface roughness in additive manufactured AlSi10Mg samples

Despite the advantages of additive manufacturing, its widespread adoption is still hindered by the poor quality of the fabricated parts. Advanced machine learning techniques to predict part quality can improve repeatability and open additive manufacturing to various industries. This study aims to accurately predict the relative density, surface roughness and hardness of AlSi10Mg samples produced by selective laser melting regarding process parameters such as scan speed, layer thickness, laser power, and hatch distance. For this purpose, data including porosity, surface hardness, and roughness were extracted from the literature, and additional measurements were performed on additive manufactured samples in the current work. This work compares five supervised machine learning algorithms, including artificial neural networks, support vector regression, kernel ridge regression, random forest, and Lasso regression. These models are evaluated based on the coefficient of determination and the mean squared error. On the basis of the computational results, the artificial neural network outperformed in predicting relative density, surface roughness, and hardness. Feature importance analysis on the compiled dataset using ANN revealed that laser power and scan speed are the most important features affecting relative density (e.g., porosity) and hardness, while scan speed and layer thickness significantly impact the surface roughness of the parts. The study identified an optimal laser power and scan speed region that achieves a relative density >  99%, surface roughness <  10 µm, and hardness >  120 HV. The results presented in this study provide significant advantages for additive manufacturing, potentially reducing experimentation costs by identifying the process parameters that optimize the quality of the fabricated parts.

Research and experiment on a mobile welding robot for expandable convoluted pipe

Prospective Analysis of urINe LAM to Eliminate NTM Sputum Screening (PAINLESS) study: Rationale and trial design for testing urine lipoarabinomannan as a marker of NTM lung infection in cystic fibrosis

Background Routine screening for nontuberculous mycobacterial (NTM) lung disease is dependent on sputum cultures. This is particularly challenging in the cystic fibrosis (CF) population due to reduced sputum production and low culture sensitivity. Biomarkers of infection that do not rely on sputum may lead to earlier diagnosis, but validation trials require a unique prospective design. Purpose The rationale of this trial is to investigate the utility of urine lipoarabinomannan (LAM) as a test to identify people with CF with a new positive NTM culture. We hypothesize that urine LAM is a sensitive, non-invasive screening test with a high negative predictive value to identify individuals with a relatively low risk of having positive NTM sputum culture. Study design This is a prospective, single-center, non-randomized observational study in adults with CF, 3 years of negative NTM cultures, and no known history of NTM positive cultures. Patients are followed for two year-long observational periods with the primary endpoint being a positive NTM sputum culture within a year of a positive urine LAM result and a secondary endpoint of a positive NTM sputum culture within 3 years of a positive urine LAM result. Study implementation includes remote consent and sample collection to accommodate changes from the COVID-19 pandemic. Conclusions This report describes the study design of an observational study aimed at using a urine biomarker to assist in the diagnosis of NTM lung infection in pwCF. If successful, urine LAM could be used as an adjunct to traditional sputum cultures for routine NTM screening, and replace cultures in low-risk individuals unable to produce sputum.

Diversity of ER-positive and HER2-negative breast cancer stem cells attained using selective culture techniques

Biologic therapies for the treatment of large vessel vasculitis: A systematic review and meta-analysis

Objective To summarize the existing evidence from double-blind randomized controlled trials (RCTs) and cohort studies regarding the effects of biologic agents for the treatment of large vessel vasculitis (LVV). Methods A systematic review and meta-analysis was conducted using MEDLINE, Embase, Cochrane Central Registry of Controlled Trials, and ClinicalTrials.gov covering the period from database inception to May 3rd, 2023. Double-blind RCTs and cohort studies reporting biologic therapies’ effects on LVV including giant cell arteritis (GCA) and Takayasu’s arteritis (TAK) with outcomes of interest in English were included. The primary outcome of interest was relapse rates during glucocorticoid tapering. The Cochrane Risk of Bias tool 2.0 and the Risk of Bias In Non-randomized Studies of Interventions tool were used for the quality assessment. Random-effects models were used for meta-analysis. Results Of the 4599 references retrieved, 10 RCTs regarding GCA, 6 cohort studies, and 2 RCTs regarding TAK were included, comprising 997 participants in total. All the included RCTs were of low risk of bias, while the 6 cohort studies were of moderate to serious risk of bias. Meta-analysis suggested a significant superiority of biologic agents in prolonging relapse-free survival, increasing glucocorticoid taper rate, and decreasing cumulative glucocorticoids dose for both GCA and TAK. Additionally, GCA patients using biologic agents had significantly lower relapse rates and ESR levels with higher remission rates. Trends of favoring biologic agents in reducing relapse rate, ITAS-2010, ITAS-A, ESR, and CRP along with increased remission rate for TAK were also observed. Conclusions Biologic agents significantly improved clinical outcomes in LVV by reducing relapse rates, enhancing remission, and enabling safer glucocorticoid tapering, offering an important therapeutic advantage for managing both GCA and TAK. Further well-designed studies and corresponding meta-analyses are needed to validate their long-term efficacy and safety.

Profiling eyewash usage and preferences in individuals with hay fever using a digital cross-sectional cohort study with AllerSearch

Strategies for relapse prevention among people with schizophrenia in KwaZulu-Natal Province, South Africa: Healthcare providers’ perspectives

Introduction Relapse is a significant challenge among people with schizophrenia and is broadly recognized by the aggravation of positive or negative symptoms, the need for re-hospitalization, more intensive case management, and/or changes in medication. The quality of inpatient care and proper transition to outpatient care are crucial in reducing the risk of relapse. Healthcare providers play vital roles in ensuring the continuity of care after patients are discharged from the hospital. Little is known about the roles of preventing relapse from the perspective of healthcare providers. This study explored the currently existing strategies for preventing relapse from the perspective of healthcare providers. Methods We captured the view of healthcare providers providing services to psychiatric patients using a qualitative methodological approach with descriptive phenomenology. We conducted audio-recorded, in-depth interviews with 15 consenting clinical providers from a public psychiatric hospital in Durban, South Africa. To facilitate analysis, we used Dedoose software (SocioCultural Research Consultants, LLC [www.dedoose.com]), and the themes were inducted from the data. Results Six major themes inducted from the analysis: Preparing patients and caregivers for discharge; Developing consistent and caring therapeutic relationships; Using an active approach to transition; Working with patients and caregivers concurrently; Creating and sustaining interagency connections; and Facilitating alternative forms of treatment. Conclusions Discharge planning and preparation are needed to ensure smooth transitions from hospital to outpatient care for relapse prevention. The healthcare system should ensure the availability of human resources for health at all levels of health facilities, and multidisciplinary teamwork will help a successful transition.