bluuebunny/crossref_metadata_2025 huggingface dataset:
A Review of Orebody Knowledge Enhancement Using Machine Learning on Open-Pit Mine Measure-While-Drilling Data
Authors: Goldstein Daniel M. , Aldrich Chris , O’Connor Louisa
Published: June 2024

Measure while drilling (MWD) refers to the acquisition of real-time data associated with the drilling process, including information related to the geological characteristics encountered in hard-rock mining. The availability of large quantities of low-cost MWD data from blast holes compared to expensive and sparsely collected orebody knowledge (OBK) data from exploration drill holes make the former more desirable for characterizing pre-excavation subsurface conditions. Machine learning (ML) plays a critical role in the real-time or near-real-time analysis of MWD data to enable timely enhancement of OBK for operational purposes. Applications can be categorized into three areas, focused on the mechanical properties of the rock mass, the lithology of the rock, as well as, related to that, the estimation of the geochemical species in the rock mass. From a review of the open literature, the following can be concluded: (i) The most important MWD metrics are the rate of penetration (rop), torque (tor), weight on bit (wob), bit air pressure (bap), and drill rotation speed (rpm). (ii) Multilayer perceptron analysis has mostly been used, followed by Gaussian processes and other methods, mainly to identify rock types. (iii) Recent advances in deep learning methods designed to deal with unstructured data, such as borehole images and vibrational signals, have not yet been fully exploited, although this is an emerging trend. (iv) Significant recent developments in explainable artificial intelligence could also be used to better advantage in understanding the association between MWD metrics and the mechanical and geochemical structure and properties of drilled rock.
Cross-Validation Visualized: A Narrative Guide to Advanced Methods
Authors: Allgaier Johannes , Pryss Rüdiger
Published: June 2024

This study delves into the multifaceted nature of cross-validation (CV) techniques in machine learning model evaluation and selection, underscoring the challenge of choosing the most appropriate method due to the plethora of available variants. It aims to clarify and standardize terminology such as sets, groups, folds, and samples pivotal in the CV domain, and introduces an exhaustive compilation of advanced CV methods like leave-one-out, leave-p-out, Monte Carlo, grouped, stratified, and time-split CV within a hold-out CV framework. Through graphical representations, the paper enhances the comprehension of these methodologies, facilitating more informed decision making for practitioners. It further explores the synergy between different CV strategies and advocates for a unified approach to reporting model performance by consolidating essential metrics. The paper culminates in a comprehensive overview of the CV techniques discussed, illustrated with practical examples, offering valuable insights for both novice and experienced researchers in the field.
A Joint Limit Theorem for Epstein and Hurwitz Zeta-Functions
Authors: Gerges Hany , Laurinčikas Antanas , Macaitienė Renata
Published: June 2024

In the paper, we prove a joint limit theorem in terms of the weak convergence of probability measures on C2 defined by means of the Epstein ζ(s;Q) and Hurwitz ζ(s,α) zeta-functions. The limit measure in the theorem is explicitly given. For this, some restrictions on the matrix Q and the parameter α are required. The theorem obtained extends and generalizes the Bohr-Jessen results characterising the asymptotic behaviour of the Riemann zeta-function.
The Development Trends of Computer Numerical Control (CNC) Machine Tool Technology
Authors: Yao Kai-Chao , Chen Dyi-Cheng , Pan Chih-Hsuan , Lin Cheng-Lung
Published: June 2024

In the industrial era, production equipment serves as an essential mother machine. In the global manufacturing industry, components such as laptop computers, mobile phones, and automotive parts all strive for aesthetic appearance. Taiwan’s machine tool industry plays a significant role globally. Faced with the constantly changing market environment, the development and competitive advantage of CNC machines are crucial topics for manufacturers. Domestic manufacturers of computer numerical control machines should move towards the integration of automated equipment to accommodate various advanced parts processing procedures. Smart manufacturing will become the trend of the industry in the future. This study invited experts from academia, industry, and research institutions to conduct expert interviews. Their opinions were compiled and analyzed, supplemented by fuzzy Delphi analysis to establish the development trends of various modules. The feasibility and demand of the product’s functional technology for industrial development were analyzed under three research dimensions and eight technical items. A total of 26 key sub-technical items were identified, achieving an expert consensus level of over 80. Furthermore, the importance ranking was analyzed using the fuzzy analytic hierarchy process, and the consistency tests were passed with C.I. < 0.1 and C.R. < 0.1. Finally, the obtained importance ranking of the hierarchical structure was used to predict the future development of computer numerical control machines through a technology roadmap, helping manufacturers use it as a reference model for future development trends to enhance market competitiveness.
Mining Abnormal Patterns in Moving Target Trajectories Based on Multi-Attribute Classification
Authors: Xie Bin , Guo Hui , Zheng Guo
Published: June 2024

As a type of time series data, trajectory data objectively record the location information and corresponding time information of an object’s activities. It not only describes the spatial activity trajectory of a moving object but also contains the unique attributes, states, and behavioral characteristics of the moving object itself. It can also reflect the interaction relationship between the object’s activities and various elements in the environment to a certain extent. Therefore, mining from moving target trajectory data to discover implicit, effective, and potentially useful spatiotemporal behavior patterns of moving targets, such as anomaly detection, will have significant research significance. This paper proposes a method for mining abnormal patterns in the trajectory of moving targets based on multi-attribute classification. Firstly, to explore the activity location patterns of single moving targets, a frequent sequence discovery method for moving targets based on sequence patterns is proposed. Furthermore, for moving target trajectory data sets containing multiple attributes, numerical attributes are extracted, and the data are clustered according to attribute classification to extract a set of normal behavior patterns of moving targets. Then, combining the activity location patterns and normal behavior patterns of the moving target, the original trajectory data are compared with them to achieve the goal of detecting abnormal behavior of the moving target. Finally, an incremental anomaly detection scheme is proposed to address the characteristics of fast updates and large numbers of data in trajectory data sets. This involves synchronously updating the frequency of moving target activity patterns and the range of values for normal behavior patterns while updating the trajectory data set, in order to meet the needs of database updates and improve the accuracy and credibility of results.
Propagation Computation for Mixed Bayesian Networks Using Minimal Strong Triangulation
Authors: Liu Yao , Wang Shuai , Zhou Can , Wang Xiaofei
Published: June 2024

In recent years, mixed Bayesian networks have received increasing attention across various fields for probabilistic reasoning. Though many studies have been devoted to propagation computation on strong junction trees for mixed Bayesian networks, few have addressed the construction of appropriate strong junction trees. In this work, we establish a connection between the minimal strong triangulation for marked graphs and the minimal triangulation for star graphs. We further propose a minimal strong triangulation method for the moral graph of mixed Bayesian networks and develop a polynomial-time algorithm to derive a strong junction tree from this minimal strong triangulation. Moreover, we also focus on the propagation computation of all posteriors on this derived strong junction tree. We conducted multiple numerical experiments to evaluate the performance of our proposed method, demonstrating significant improvements in computational efficiency compared to existing approaches. Experimental results indicate that our minimal strong triangulation approach provides a robust framework for efficient probabilistic inference in mixed Bayesian networks.
Mental-Health: An NLP-Based System for Detecting Depression Levels through User Comments on Twitter (X)
Authors: Salas-Zárate Rafael , Alor-Hernández Giner , Paredes-Valverde Mario Andrés , Salas-Zárate María del Pilar , Bustos-López Maritza , Sánchez-Cervantes José Luis
Published: June 2024

The early detection of depression in a person is of great help to medical specialists since it allows for better treatment of the condition. Social networks are a promising data source for identifying individuals who are at risk for this mental disease, facilitating timely intervention and thereby improving public health. In this frame of reference, we propose an NLP-based system called Mental-Health for detecting users’ depression levels through comments on X. Mental-Health is supported by a model comprising four stages: data extraction, preprocessing, emotion detection, and depression diagnosis. Using a natural language processing tool, the system correlates emotions detected in users’ posts on X with the symptoms of depression and provides specialists with the depression levels of the patients. By using Mental-Health, we described a case study involving real patients, and the evaluation process was carried out by comparing the results obtained using Mental-Health with those obtained through the application of the PHQ-9 questionnaire. The system identifies moderately severe and moderate depression levels with good precision and recall, allowing us to infer the model’s good performance and confirm that it is a promising option for mental health support.
High-Performance Hybrid Algorithm for Minimum Sum-of-Squares Clustering of Infinitely Tall Data
Authors: Mussabayev Ravil , Mussabayev Rustam
Published: June 2024

This paper introduces a novel formulation of the clustering problem, namely, the minimum sum-of-squares clustering of infinitely tall data (MSSC-ITD), and presents HPClust, an innovative set of hybrid parallel approaches for its effective solution. By utilizing modern high-performance computing techniques, HPClust enhances key clustering metrics: effectiveness, computational efficiency, and scalability. In contrast to vanilla data parallelism, which only accelerates processing time through the MapReduce framework, our approach unlocks superior performance by leveraging the multi-strategy competitive–cooperative parallelism and intricate properties of the objective function landscape. Unlike other available algorithms that struggle to scale, our algorithm is inherently parallel in nature, improving solution quality through increased scalability and parallelism and outperforming even advanced algorithms designed for small- and medium-sized datasets. Our evaluation of HPClust, featuring four parallel strategies, demonstrates its superiority over traditional and cutting-edge methods by offering better performance in the key metrics. These results also show that parallel processing not only enhances the clustering efficiency, but the accuracy as well. Additionally, we explore the balance between computational efficiency and clustering quality, providing insights into optimal parallel strategies based on dataset specifics and resource availability. This research advances our understanding of parallelism in clustering algorithms, demonstrating that a judicious hybridization of advanced parallel approaches yields optimal results for MSSC-ITD. Experiments on the synthetic data further confirm HPClust’s exceptional scalability and robustness to noise.
A Range Query Scheme for Spatial Data with Shuffled Differential Privacy
Authors: Li Kaixuan , Zhang Hua , Xu Yanxin , Liu Zhenyan
Published: June 2024

The existing high-dimensional or multi-dimensional geographic spatial datasets have a large amount of data. When third-party servers collect and publish them, privacy protection is required to prevent sensitive information from being leaked. Local differential privacy can be used to protect location-sensitive information during range queries. However, the accuracy of a range query based on local differential privacy is affected by the distribution and density of spatial data. Based on this, aiming at the distribution and density characteristics of data, we designed a dpKD tree that supports high-precision range queries with shuffled differential privacy, and designed an algorithm KDRQ for range queries based on shuffled differential privacy. First, we employed the  dpKD to divide the data. Then, we shuffled the data based on SRRQ and reconstructed the tree. Finally, we used the SDRQ algorithm for the response range query. The experimental results show that the query accuracy of the KDRQ algorithm was at least 1–4.5 times higher than that of the existing algorithms RAPPOR, PSDA and GT-R under the same privacy budget.
Dysnatremia as a Mortality Marker in Intensive Care Patients with SARS-CoV-2 Infection: A Retrospective Study
Authors: Eraslan Doganay Guler , Doganci Melek , Yurtseven Gulsah , Ozanbarci Azra , Kahraman Abdullah , Cirik Mustafa Ozgur , Ozturk Yalcin Fatma , Hazer Seray , Ensarioglu Kerem
Published: June 2024

Background and Objectives: The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection may cause acute respiratory failure, but also remains responsible for many other pathologies, including electrolyte disorders. SARS-CoV-2 infection causes disorders in many systems and can disrupt water homeostasis with thirst and appetite abnormalities. Dysnatremia affects prognosis, and may be associated with mortality in patients admitted to an intensive care unit (ICU) diagnosed with SARS-CoV-2. Materials and Methods: The study included 209 patients admitted to the ICU between 12 April 2021 and 1 March 2022 who were over 18 years old and diagnosed with SARS-CoV-2 infection by clinical and thoracic tomography findings or with a positive reverse transcription polymerase chain reaction (RT-PCR) test result. The laboratory markers, treatment modalities, nutritional, and respiratory support also for outcome evaluation, length of stay in the ICU, total hospitalization duration, and mortality in the ICU were recorded. The laboratory marker comparison was made using admission with the final assessment performed before the time of mortality in the ICU or after discharge. Results: Inotropic requirements among patients were high, which reflected mortality in the ICU. Hypernatremia presence was associated with an increase in enteral support, the inotropic support requirement, and mortality. Hypernatremia was correlated with diabetes mellitus, chronic renal failure, and a longer duration under mechanical ventilation. Conclusions: Hypernatremia was an important risk factor in ICU patients hospitalized for SARS-CoV-2 infection, which was also affected by the treatment regimens given themselves. This complex relationship underlies the importance of proper electrolyte management, especially in patients who were under severe stress and organ failure.
An Overview of Methotrexate Indications in Skin Diseases
Authors: Mocanu Mădălina , Procopciuc Dorina , Gheucă-Solovăstru Dragoș-Florin , Popescu Ioana Adriana , Olinici Doinița Temelie , Pătrașcu Adriana Ionela , Vâță Dan , Gheucă-Solovăstru Laura
Published: June 2024

Methotrexate is an immunosuppressive drug with remarkable therapeutic results in the treatment of autoimmune and proliferative skin diseases. Although it has been more than half a century since it was first introduced into the therapeutic arsenal of dermatologists, there are currently no standardized therapeutic protocols regarding the prescription of methotrexate in dermatology, with the exception of psoriasis treatment. This review aims to highlight the indications and benefits of methotrexate beyond psoriasis, with a focus on a wide range of inflammatory, vesiculobullous, and proliferative dermatological pathologies.
Effects of Daily Physical Activity on Exercise Capacity in Chronic Obstructive Pulmonary Disease
Authors: Aiello Marina , Frizzelli Annalisa , Pisi Roberta , Accogli Rocco , Marchese Alessandra , Carlacci Francesca , Bondarenko Olha , Tzani Panagiota , Chetta Alfredo
Published: June 2024

Background and Objectives: In adults, 150 to 300 min a week of moderate-intensity physical activity is the recommended daily level to maintain or improve fitness. In subjects with chronic obstructive pulmonary disease (COPD), reductions in daily physical activity (DPA) amounts are related to clinically significant outcomes. In this study, we ascertain whether or not COPD patients, when clustered into active (DPA ≥ 30 min a day, 5 days a week) and inactive (DPA < 30 min a day, 5 days a week), may differ in exercise capacity, as assessed by a cardiopulmonary exercise test (CPET). Materials and Methods: A large sample of clinically stable COPD patients was retrospectively recruited and then underwent spirometry and an incremental ramp protocol 5–15 watts/min CPET. DPA was assessed by a questionnaire. Results: A total of 83 (female 25%, age range 41–85 y) active and 131 (female 31%, age range 49–83 y) inactive participants were enrolled. They were similar in age, sex distribution, body mass index (BMI) and in spirometry. The two groups were significantly different in dyspnea on exertion, as assessed by the modified Medical Research Council (mMRC), and in cardio-metabolic parameters, but not in ventilatory ones, as confirmed by the CPET. Conclusions: COPD patients experiencing physical activity of at least 30 min a day, 5 days a week, showed a greater exercise capacity and an improved cardiovascular response to exercise, when compared to inactive ones. Active and inactive participants did not differ in terms of airflow obstruction severity as well as in dynamic hyperinflation and ventilatory inefficiency during exercise. This study further suggests the benefits of regular physical activity in COPD.
Slip Statistics for a Bulk Metallic Glass Treated by Cryogenic Thermal Cycling Reflect Its Optimized Plasticity
Authors: Li Jiaojiao , Liu Yao , Zhao Wei , Zhang Huiyun , Zhang Yajun , Lu Huihu , Wang Zhong , Liu Yong
Published: June 2024

Enhanced plasticity is obtained in a structurally rejuvenated Zr-based bulk metallic glass (BMG) that has been treated via cryogenic thermal cycling (CTC) for one hundred cycles. More than one primary shear band is activated due to the structural rejuvenation, which can inhibit the jerky and system-spanning propagation of shear bands to generate sluggish shear-dynamics. These are mapped to the slip statistics, including the decreased critical avalanche size, the much longer avalanche duration of large (system-spanning) slips, and a great number of small avalanches. Moreover, the universal scaling of slip avalanches for three applied stress ranges is addressed to predict the applied stress at which the failure avalanche appears most. These results indicate that slip statistics can be the fingerprints to show how much the BMG is rejuvenated, and the failure avalanche provides a good opportunity to intervene in the failure of BMGs in advance.
Production of Rare-Earth-Free Iron Nitride Magnets (α″-Fe16N2)
Authors: Saito Tetsuji , Yamamoto Hitoshi , Nishio-Hamane Daisuke
Published: June 2024

To realize rare-earth-free magnets, we studied iron nitride (α″-Fe16N2) magnets, which contain no rare-earth elements. Fe-N powder with the α″-Fe16N2 phase has a high saturation magnetization comparable to high-performance rare-earth magnets but is not stable at temperatures over 539 K. We consolidated Fe-N powder into bulk material at low temperatures by spark plasma sintering (SPS) and spark plasma sintering with dynamic compression (SPS-DC). Fe-N magnets were successfully obtained at low temperatures of 373–573 K. The magnets produced by the SPS-DC method had a higher density than those produced by the SPS method. The density of the magnets produced by the SPS-DC method increased as the consolidation temperature increased. That produced at 373 K had a saturation magnetization of 1.07 T with a coercivity of 0.20 MA/m.
Multi Response Modelling and Optimisation of Copper Content and Heat Treatment Parameters of ADI Alloys by Combined Regression Grey-Fuzzy Approach
Authors: Čatipović Nikša , Peko Ivan , Grgić Karla , Periša Karla
Published: June 2024

This paper deals with the austempering of ductile iron (ADI) and clarifies the influential austempering parameters during the production of ADI. During the austempering process, the heat treatment parameters can be varied, thus influencing the final microstructure and, of course, the mechanical properties of ADI. To appropriately conduct experiments and obtain good results, an experimental plan was developed using the Design Expert 13 software. Along with the heat treatment parameters, the influence of the copper content on the ADI toughness, tensile strength, and elongation was determined. The obtained results from this experiment were used to develop unique mathematical models which describe the influences of heat treatment and copper content on the observed mechanical properties of ADI samples. These mathematical models can be applied to predict the analysed mechanical properties of ADI in the dependence of heat treatment parameters and copper content in base ductile iron. For the multi response optimisation of toughness, tensile strength, and elongation, a hybrid grey-fuzzy technique was presented as a significant contribution to the enhancement of the analysed mechanical properties. Consequently, the copper content and heat treatment parameter levels that resulted in the maximal mechanical properties’ functions were defined.
Numerical Simulation as a Tool for the Study, Development, and Optimization of Rolling Processes: A Review
Authors: Ojeda-López Adrián , Botana-Galvín Marta , González-Rovira Leandro , Botana Francisco Javier
Published: June 2024

Rolling is one of the most important processes in the metallurgical industry due to its versatility. Despite its inherent advantages, design and manufacturing by rolling still rely on trial-and-error-based optimizations, which reduces its efficiency. To minimize the cost and time spent on the development of new rolling schedules, various analytical and numerical methods have been used in recent years. Among other alternatives, simulations based on the finite element method (FEM) are the most widely used. This allows for the analysis of the feasibility of new rolling schedules considering metal alloys with different characteristics, process conditions, or the creation of new operations, as well as the optimization of existing ones. This paper presents a literature review including the latest developments in the field of numerical simulation of rolling processes, which have been classified according to the type of rolling into the following categories: flat rolling, shape rolling, ring rolling, cross-wedge rolling, skew rolling, and tube piercing.
Vision-Assisted Probabilistic Inference of Milling Stability through Fully Bayesian Gaussian Process
Authors: Ostad Ali Akbari Vahid , Eichenberger Andrea , Wegener Konrad
Published: June 2024

This paper presents a physics-free Bayesian approach for the learning and inference of probabilistic stability charts in milling operations. The approach does not require any information from machine tool structural dynamics or cutting force coefficients, and the underlying learning algorithm can operate with limited training data. A Fully Bayesian Gaussian Process with distributions on its kernel hyperparameters is employed to enable information transfer between different machine and process configurations. The vision system further automates the detection of necessary dimensions from the tool–holder assembly in the machine’s tool magazine, further enhancing the applicability of the approach. Experiments demonstrated the effectiveness of this approach, offering great promise as an industry-friendly solution.
Bile Acids in Pancreatic Carcinogenesis
Authors: Sharma Bharti , Twelker Kate , Nguyen Cecilia , Ellis Scott , Bhatia Navin D. , Kuschner Zachary , Agriantonis Andrew , Agriantonis George , Arnold Monique , Dave Jasmine , Mestre Juan , Shafaee Zahra , Arora Shalini , Ghanta Hima , Whittington Jennifer
Published: June 2024

Pancreatic cancer (PC) is a dangerous digestive tract tumor that is becoming increasingly common and fatal. The most common form of PC is pancreatic ductal adenocarcinoma (PDAC). Bile acids (BAs) are closely linked to the growth and progression of PC. They can change the intestinal flora, increasing intestinal permeability and allowing gut microbes to enter the bloodstream, leading to chronic inflammation. High dietary lipids can increase BA secretion into the duodenum and fecal BA levels. BAs can cause genetic mutations, mitochondrial dysfunction, abnormal activation of intracellular trypsin, cytoskeletal damage, activation of NF-κB, acute pancreatitis, cell injury, and cell necrosis. They can act on different types of pancreatic cells and receptors, altering Ca2+ and iron levels, and related signals. Elevated levels of Ca2+ and iron are associated with cell necrosis and ferroptosis. Bile reflux into the pancreatic ducts can speed up the kinetics of epithelial cells, promoting the development of pancreatic intraductal papillary carcinoma. BAs can cause the enormous secretion of Glucagon-like peptide-1 (GLP-1), leading to the proliferation of pancreatic β-cells. Using Glucagon-like peptide-1 receptor agonist (GLP-1RA) increases the risk of pancreatitis and PC. Therefore, our objective was to explore various studies and thoroughly examine the role of BAs in PC.
Beyond Color Boundaries: Pioneering Developments in Cholesteric Liquid Crystal Photonic Actuators
Authors: Zhang Jinying , Zhang Yexiaotong , Yang Jiaxing , Wang Xinye
Published: June 2024

Creatures in nature make extensive use of structural color adaptive camouflage to survive. Cholesteric liquid crystals, with nanostructures similar to those of natural organisms, can be combined with actuators to produce bright structural colors in response to a wide range of stimuli. Structural colors modulated by nano-helical structures can continuously and selectively reflect specific wavelengths of light, breaking the limit of colors recognizable by the human eye. In this review, the current state of research on cholesteric liquid crystal photonic actuators and their technological applications is presented. First, the basic concepts of cholesteric liquid crystals and their nanostructural modulation are outlined. Then, the cholesteric liquid crystal photonic actuators responding to different stimuli (mechanical, thermal, electrical, light, humidity, magnetic, pneumatic) are presented. This review describes the practical applications of cholesteric liquid crystal photonic actuators and summarizes the prospects for the development of these advanced structures as well as the challenges and their promising applications.
Dual Features, Compact Dimensions and X-Band Applications for the Design and Fabrication of Annular Circular Ring-Based Crescent-Moon-Shaped Microstrip Patch Antenna
Authors: Aras Unal , Delwar Tahesin Samira , Durgaprasadarao P. , Sundar P. Syam , Ahammad Shaik Hasane , Eid Mahmoud M. A. , Lee Yangwon , Zaki Rashed Ahmed Nabih , Ryu Jee-Youl
Published: June 2024

This study uses annular circular rings to create multi-band applications using crescent-shaped patch antennas. It is designed to be made up of five circular, annular rings nested inside of each other. Three annular rings are positioned and merged on top of the larger rings, with two annular rings set along the bottom of the feed line. The factors that set them apart, such as bandwidths, radiation patterns, gain, impedance, and return loss (RL), are analysed. The outcomes show how compact the multi-band annular ring antenna is. The proposed circular annular ring antenna has return losses of −33 dB and operates at two frequencies: 3.1 GHz and 9.3 GHz. This design is modelled and simulated using ANSYS HFSS. The outcomes of the simulation and the tests agree quite well. The X band and WLAN resonant bands have bandwidth capacities of 500 and 4300 MHz, respectively. Additionally, the circular annular ring antenna design is advantageous for most services at these operating bands.
Structural Optimization Design of Magnetoelectric Thin-Film Antenna for Bandwidth and Radiation Enhancement
Authors: Li Xiangyang , Zhao Pengchao , Wang Guangyuan , Li Na , Zhang Yiqun
Published: June 2024

The acoustically actuated nanomechanical magnetoelectric (ME) antennas represent a promising new technology that can significantly reduce antenna size by 1–2 orders of magnitude compared to traditional antennas. However, current ME antennas face challenges such as low antenna gain and narrow operating bandwidth, limiting their engineering applications. In this paper, we enhance the bandwidth and radiation performance of ME antennas through structural optimization, leveraging theoretical analysis and numerical simulations. Our findings indicate that optimizing the inner diameter of the ring-shaped ME antenna can elevate the average stress of the magnetic layer, leading to improved radiation performance and bandwidth compared to circular ME antennas. We establish an optimization model for the radiation performance of the ME antenna and conduct shape optimization simulations using COMSOL Multiphysics. The results of the Multiphysics field optimization align with the stress concentration theory, demonstrating a strong correlation between the radiation performance and bandwidth of the ME antenna with the average stress of the magnetic film. The resonant frequency in the thickness vibration mode is determined to be 170 MHz. Furthermore, shape optimization can enhance the bandwidth by up to 104% compared to circular ME antenna structures of the same size.
A 25 Mbps 15 ns Propagation Delay 150 kV/μs CMTI Configurable Dual-Channel Capacitive Digital Isolation Driver
Authors: Zhao Yuan , Wang Liang , Chen Zhifeng , Li Boyang , Zheng Ronghua , Chen Chengying
Published: June 2024

Electrical isolation devices are essential components for safeguarding the reliability of electronic systems under harsh conditions. Digital isolators are widely used in low-power circuits due to their high immunity to disturbances. In this paper, a capacitive digital isolator for high-efficiency power supply scenarios is proposed with a high common-mode transient immunity (CMTI) and high data transmission rate. The on–off keying (OOK) modulation technique is used to ensure a high speed and accurate signal transmission. A fully integrated high-voltage level-shift driver with an ns-scale delay is proposed for increasing the drive capacity. Post-simulation results in Cadence IC 6.1.7 with the standard 0.18 μm CMOS process show that the proposed architecture achieves a 25 Mbps data transmission rate and 15 ns typical propagation delay with output peak currents of 2 A/4 A, respectively. Meanwhile, a CMTI of more than 150 kV/μs is realized.
Characterisation of Legionella Clinical Isolates in Spain from 2012 to 2022
Authors: González-Rubio Juana María , Cascajero Almudena , Baladrón Beatriz , González-Camacho Fernando
Published: June 2024

Although cases of Legionnaires’ disease are notifiable, data on the phenotypic and genotypic characterisation of clinical isolates are limited. This retrospective study aims to report the results of the characterisation of Legionella clinical isolates in Spain from 2012 to 2022. Monoclonal antibodies from the Dresden panel were used for phenotypic identification of Legionella pneumophila. Genotypic characterisation and sequence type assignment were performed using the Sequence-Based Typing scheme. Of the 1184 samples, 569 were identified as Legionella by culture. Of these, 561 were identified as L. pneumophila, of which 521 were serogroup 1. The most common subgroups were Philadelphia (n = 107) and Knoxville (n = 106). The SBT analysis revealed 130 different STs, with the most common genotypes being ST1 (n = 87), ST23 (n = 57), ST20 (n = 30), and ST42 (n = 29). Knoxville has the highest variability with 32 different STs. ST23 is mainly found in Allentown/France (n = 46) and ST42 in Benidorm (n = 18), whereas ST1 is widely distributed. The results demonstrate that clinical isolates show high genetic diversity, although only a few sequence types (STs) are responsible for most cases. However, outbreaks can also occur with rare genotypes. More data on LD and associated epidemiological studies are needed to establish the risk of an isolate causing outbreak in the future.
Prevalence and Treatment Outcomes of Syphilis among People with Human Immunodeficiency Virus (HIV) Engaging in High-Risk Sexual Behavior: Real World Data from Northern Greece, 2019–2022
Authors: Nanoudis Sideris , Pilalas Dimitrios , Tziovanaki Theologia , Constanti Margarita , Markakis Konstantinos , Pagioulas Konstantinos , Papantoniou Eleni , Kapiki Konstantina , Chrysanthidis Theofilos , Kollaras Panagiotis , Metallidis Symeon , Tsachouridou Olga
Published: June 2024

In this study, we aimed to assess the prevalence of syphilis among people with human immunodeficiency virus (HIV; PWH) engaging in high-risk sexual behavior, determine the stage of syphilis, and evaluate treatment efficacy. A retrospective single-center cohort study was conducted at the AHEPA University General Hospital of Thessaloniki, focusing on PWH at high risk for sexually transmitted infections (STIs) attending outpatient care from January 2019 to December 2022. Sociodemographic and clinical data were collected, incident syphilis rates were identified, associations with HIV-related characteristics were explored, and the treatment response was assessed. Among 991 participants, 94 PWH were diagnosed with syphilis, representing 9.4% of the cohort. Incident syphilis cases experienced a decrease in the early COVID-19 era compared to 2019, followed by a gradual increase leading up to 2022. The majority of syphilis cases were asymptomatic latent syphilis (71.1%). Men who have sex with men (MSM) and younger individuals exhibited higher rates of co-infection during the study period. No significant association was found between incident syphilis and HIV-related factors. Most syphilis cases (86%) were treated with benzathine penicillin G (BPG). Treatment with BPG and doxycycline showed an increased success rate (96.7% vs. 92.9%), with no statistically significant difference observed between them (p = 0.438). This study highlights the alarming incidence of syphilis among PWH engaging in high-risk sexual behavior, particularly among younger MSM. BPG remains effective, and alternative regimens like doxycycline show promise, especially in settings with penicillin shortages or patient allergies.
A Predictive Model of the Start of Annual Influenza Epidemics
Authors: Castro Blanco Elisabet , Dalmau Llorca Maria Rosa , Aguilar Martín Carina , Carrasco-Querol Noèlia , Gonçalves Alessandra Queiroga , Hernández Rojas Zojaina , Coma Ermengol , Fernández-Sáez José
Published: June 2024

Influenza is a respiratory disease that causes annual epidemics during cold seasons. These epidemics increase pressure on healthcare systems, sometimes provoking their collapse. For this reason, a tool is needed to predict when an influenza epidemic will occur so that the healthcare system has time to prepare for it. This study therefore aims to develop a statistical model capable of predicting the onset of influenza epidemics in Catalonia, Spain. Influenza seasons from 2011 to 2017 were used for model training, and those from 2017 to 2018 were used for validation. Logistic regression, Support Vector Machine, and Random Forest models were used to predict the onset of the influenza epidemic. The logistic regression model was able to predict the start of influenza epidemics at least one week in advance, based on clinical diagnosis rates of various respiratory diseases and meteorological variables. This model achieved the best punctual estimates for two of three performance metrics. The most important variables in the model were the principal components of bronchiolitis rates and mean temperature. The onset of influenza epidemics can be predicted from clinical diagnosis rates of various respiratory diseases and meteorological variables. Future research should determine whether predictive models play a key role in preventing influenza.
Deciphering Microbial Composition in Patients with Inflammatory Bowel Disease: Implications for Therapeutic Response to Biologic Agents
Authors: Palmieri Orazio , Bossa Fabrizio , Castellana Stefano , Latiano Tiziana , Carparelli Sonia , Martino Giuseppina , Mangoni Manuel , Corritore Giuseppe , Nardella Marianna , Guerra Maria , Biscaglia Giuseppe , Perri Francesco , Mazza Tommaso , Latiano Anna
Published: June 2024

Growing evidence suggests that alterations in the gut microbiome impact the development of inflammatory bowel diseases (IBDs), including Crohn’s disease (CD) and ulcerative colitis (UC). Although IBD often requires the use of immunosuppressant drugs and biologic therapies to facilitate clinical remission and mucosal healing, some patients do not benefit from these drugs, and the reasons for this remain poorly understood. Despite advancements, there is still a need to develop biomarkers to help predict prognosis and guide treatment decisions. The aim of this study was to investigate the gut microbiome of IBD patients using biologics to identify microbial signatures associated with responses, following standard accepted criteria. Microbiomes in 66 stool samples from 39 IBD patients, comprising 20 CD and 19 UC patients starting biologic therapies, and 29 samples from healthy controls (HCs) were prospectively analyzed via NGS and an ensemble of metagenomics analysis tools. At baseline, differences were observed in alpha and beta metrics among patients with CD, UC and HC, as well as between the CD and UC groups. The degree of dysbiosis was more pronounced in CD patients, and those with dysbiosis exhibited a limited response to biological drugs. Pairwise differential abundance analyses revealed an increasing trend in the abundance of an unannotated genus from the Clostridiales order, Gemmiger genus and an unannotated genus from the Rikenellaceae family, which were consistently identified in greater abundance in HC. The Clostridium genus was more abundant in CD patients. At baseline, a greater abundance of the Odoribacter and Ruminococcus genera was found in IBD patients who responded to biologics at 14 weeks, whereas a genus identified as SMB53 was more enriched at 52 weeks. The Collinsella genus showed a higher prevalence among non-responder IBD patients. Additionally, a greater abundance of an unclassified genus from the Barnesiellaceae family and one from Lachnospiraceae was observed in IBD patients responding to Vedolizumab at 14 weeks. Our analyses showed global microbial diversity, mainly in CD. This indicated the absence or depletion of key taxa responsible for producing short-chain fatty acids (SCFAs). We also identified an abundance of pathobiont microbes in IBD patients at baseline, particularly in non-responders to biologic therapies. Furthermore, specific bacteria-producing SCFAs were abundant in patients responding to biologics and in those responding to Vedolizumab.
AG1®, a Novel Synbiotic, Maintains Gut Barrier Function following Inflammatory Challenge in a Caco-2/THP1-Blue™ Co-Culture Model
Authors: Sapp Philip A. , Townsend Jeremy R. , Kirby Trevor O. , Govaert Marlies , Duysburgh Cindy , Verstrepen Lynn , Marzorati Massimo , Marshall Tess M. , Esposito Ralph
Published: June 2024

Nutritional interventions to reduce gastrointestinal (GI) permeability are of significant interest to physically active adults and those experiencing chronic health conditions. This in vitro study was designed to assess the impact of AG1, a novel synbiotic, on GI permeability following an inflammatory challenge. Interventions [AG1 (vitamins/minerals, pre-/probiotics, and phytonutrients) and control (control medium)] were fed separately into a human GI tract model (stomach, small intestine, and colon). In the colonic phase, the GI contents were combined with fecal inocula from three healthy human donors. GI permeability was evaluated with transepithelial electrical resistance (TEER) in a Caco-2 (apical)/THP1-Blue™ (basolateral) co-culture model. The apical side received sodium butyrate (positive control) or Caco-2 complete medium (negative control) during baseline testing. In the 24 h experiment, the apical side received colonic simulation isolates from the GI model, and the basolateral side was treated with Caco-2 complete medium, then 6 h treatment with lipopolysaccharide. TEER was assessed at 0 h and 24 h, and inflammatory markers were measured at 30 h in triplicate. Paired samples t-tests were used to evaluate endpoint mean difference (MD) for AG1 vs. control. TEER was higher for AG1 (mean ± SD: 99.89 ± 1.32%) vs. control (mean ± SD: 92.87 ± 1.22%) following activated THP1-induced damage [MD: 7.0% (p < 0.05)]. AG1 maintained TEER similar to the level of the negative control [−0.1% (p = 0.02)]. No differences in inflammatory markers were observed. These in vitro data suggest that acute supplementation with AG1 might stimulate protective effects on GI permeability. These changes may be driven by SCFA production due to the pre-/probiotic properties of AG1, but more research is needed.
Surface Wettability Analysis from Adsorption Energy and Surface Electrical Charge
Authors: Zhang Chen , Wang Xuming , Li Lixia , Miller Jan D. , Jin Jiaqi
Published: June 2024

Surface wettability is determined by the attraction of a liquid phase to a solid surface. It is typically quantified by using contact angle measurements at mineral surfaces in the case of the flotation of mineral particles. Contact angle research to describe wettability has been investigated at different scales by sessile drop measurements, molecular dynamic simulation, and atomic force microscopy. In this study, the density functional theory (DFT) was employed for predicting the surface free energy and contact angles of a well-known hydrophobic phyllosilicate mineral talc and a well-known hydrophilic phyllosilicate mineral muscovite based on the calculated interfacial energy and surface charge. The results revealed that the predicted contact angle at the atomic scale was larger than the experimental value, and identified two interactions: electrostatic interaction and hydrogen bonding, between the hydrophilic muscovite surface and the water layer, while a water-exclusion zone of 3.346 Å was found between the hydrophobic talc surface and the first water layer. This investigation gives a new perspective for wettability determination at the atomic scale.
The Catalytic Potential of Modified Clays: A Review
Authors: Ochirkhuyag Altantuya , Temuujin Jadambaa
Published: June 2024

The need for innovative catalysts and catalytic support materials is continually growing due to demanding requirements, stricter environmental demands, and the ongoing development of new chemical processes. Since about 80% of all industrial processes involve catalysts, there is a continuing need to develop new catalyst materials and supports with suitable qualities to meet ongoing industrial demands. Not only must new catalysts have tailored properties, but they must also be suitable for large-scale production through environmentally friendly and cost-effective processes. Clay minerals, with their rich history in medicine and ceramics, are now emerging as potential catalysts. Their transformative potential is exemplified in applications such as hydrogenating the greenhouse gas CO2 into carbohydrate fuel, a crucial step in meeting the rising electrical demand. Moreover, advanced materials derived from clay minerals are proving their mettle in diverse photocatalytic reactions, from organic dye removal to pharmaceutical pollutant elimination and photocatalytic energy conversion through water splitting. Clay minerals in their natural state show a low catalytic activity, so to increase their reactivity, they must be activated. Depending on the requirements of a particular application, selecting an appropriate activation method for modifying a natural clay mineral is a critical consideration. Traditional clay mineral processing methods such as acid or alkaline treatment are used. Still, these have drawbacks such as high costs, long processing times, and the formation of hazardous by-products. Other activation processes, such as ultrasonication and mechanical activation routes, have been proposed to reduce the production of hazardous by-products. The main advantage of ultrasonication and microwave-assisted procedures is that they save time, whereas mechanochemical processing is simple and efficient. This short review focuses on modifying clay minerals using various new methods to create sophisticated and innovative new materials. Recent advances in catalytic reactions are specifically covered, including organic biogeochemical processes, photocatalytic processes, carbon nanotube synthesis, and energy conversion processes such as CO2 hydrogenation and dry reforming of methane.
Discrete Element Modeling of the Breakage of Single Polyhedral Particles in the Rotary Offset Crusher
Authors: Nghipulile Titus , Bwalya Mulenga Murray , Govender Indresan , Simonsen Henry
Published: June 2024

Innovation in comminution is expected to continue unabated to address the inefficiencies that are inherent in comminution circuits. The rotary offset crusher (ROC) is a new comminution device with a promising performance potential in terms of throughput due to the enhanced speed of transportation induced by the centrifugal force of the discs. However, the processes driving the comminution of particles trapped in the conical space between the two discs of the crusher are not fully understood. To gain a better insight into the comminution process in this device, discrete element modeling (DEM) simulations were conducted to study the breakage of a single particle for the crusher operated under two different dynamic conditions, i.e., (1) a stationary top disc and (2) both discs rotating at the same speed. For both scenarios, the speed of the discs was varied between 550 and 2350 rpm. Experimental testwork was also conducted with the laboratory prototype to generate the data that were used to calibrate the breakage parameters of the Ab × t10 breakage model. Simulations were performed using polyhedral UG2 ore particles that were generated with the in-built particle generator in the DEM simulator. The simulated ROC, which is operated with both discs rotating, outperformed the ROC with a stationary top disc in terms of the specific input energy and throughput. The crusher with a stationary top disc is characterized by high shear forces (suggesting a higher wear rate), specific input energies greater than 1 kWh/t, and low throughputs (<50 kg/h). The ROC operated with a stationary disc is not recommended for hard rock applications due to expected excessive wear of crushing surfaces and higher energy consumption. The freewheeling discs are recommended, but there is scope to optimize the crusher performance in terms of the power draw, size reduction, and throughput by manipulating the difference between the speeds of the discs. There is also scope to optimize the crusher performance when it is simulated with many particles. Once the full performance potential of the ROC is established, it will then be important to benchmark it against the existing crushers in the minerals industry as well as other industries where crushers are used.