bluuebunny/crossref_metadata_2025 huggingface dataset:
Intravoxel incoherent motion diffusion-weighted MRI for predicting the efficacy of high-intensity focused ultrasound ablation for uterine fibroids
Authors: Jiang Yu , Qin Shize , Wang Yanlin , Liu Yang , Liu Nian , Tang Lingling , Fang Jie , Jia Qing , Huang Xiaohua
Published: June 2023

Purpose

To evaluate the significance of magnetic resonance (MR) intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) quantitative parameters in predicting early efficacy of high-intensity focused ultrasound (HIFU) ablation of uterine fibroids before treatment.

Method

64 patients with 89 uterine fibroids undergoing HIFU ablation (51 sufficient ablations and 38 insufficient ablations) were enrolled in the study and completed MR imaging and IVIM-DWI before treatment. The IVIM-DWI parameters, including D (diffusion coefficient), D* (pseudo-diffusion coefficient), f (perfusion fraction) and relative blood flow (rBF) were calculated. The logistic regression (LR) model was constructed to analyze the predictors of efficacy. The receiver operating characteristic (ROC) curve was drawn to assess the model’s performance. A nomograph was constructed to visualize the model.

Results

The D value of the sufficient ablation group (931.0(851.5-987.4) × 10−6 mm2/s) was significantly lower than that of the insufficient ablation group (1052.7(1019.6-1158.7) × 10−6 mm2/s) (p<0.001). However, differences in D*, f, and rBF values between the groups were not significant (p>0.05). The LR model was constructed with D value, fibroid position, ventral skin distance, T2WI signal intensity, and contrast enhanced degree. The area under the ROC curve, specificity, and sensitivity of the model were 0.858 (95% confidence interval: 0.781, 0.935), 0.686, and 0.947. The nomogram and calibration curves confirmed that the model had excellent performance.

Conclusion

The IVIM-DWI quantitative parameters can be used to predict early effects of HIFU ablation on uterine fibroids. A high D value before treatment may indicate that the treatment will be less effective in the early stages.
Cariprazine for negative symptoms in early psychosis: a pilot study with a 6-month follow-up
Authors: Pappa Sofia , Kalniunas Arturas , Maret Jose
Published: June 2023

Background

Cariprazine, a novel antipsychotic drug that is a partial agonist with preferential binding to the D3 receptor, has demonstrated efficacy in clinical trials across all symptom domains, including negative symptoms, which can occur early in the course of psychotic illness. However, evidence, to date regarding its effects in early psychosis patients with primary negative symptoms has been limited.

Objectives

To evaluate the efficacy of cariprazine for negative symptoms in early psychosis patients.

Methods

Demographic and clinical information of the study population were collected from the electronic records and PANSS scale administered at baseline, 3 and 6 months. Tolerability and discontinuation reasons, where applicable, were also recorded.

Results

Ten patients with early psychosis (four men and six women, mean age – 25.5  years) with prominent or predominant negative symptoms were treated with cariprazine (range 1.5 – 3 mg). Three patients discontinued cariprazine within the first 3  months due to patient choice, lack of response and non-compliance, respectively. In the remaining patients, there was a significant reduction in the mean negative PANSS score from baseline to 6 months (from 26.3 to 10.6), mean total PANSS score (from 81.4 to 43.3) and in the mean positive PANSS score (from 14.4 to 9.9) which correspond to a 53.1, 41.5, and 28.5% mean score reduction.

Conclusion

This pilot study suggests that cariprazine is a safe and effective treatment in early psychosis, particularly for the alleviation of negative symptoms which remains an area of unmet treatment need.
Algorithm for Enhancing Event Reconstruction Efficiency by Addressing False Track Filtering Issues in the SPD NICA Experiment
Authors: Amirkhanova Gulshat , Mansurova Madina , Ososkov Gennadii , Burtebayev Nasurlla , Shomanov Adai , Kunelbayev Murat
Published: June 2023

This paper introduces methods for parallelizing the algorithm to enhance the efficiency of event recovery in Spin Physics Detector (SPD) experiments at the Nuclotron-based Ion Collider Facility (NICA). The problem of eliminating false tracks during the particle trajectory detection process remains a crucial challenge in overcoming performance bottlenecks in processing collider data generated in high volumes and at a fast pace. In this paper, we propose and show fast parallel false track elimination methods based on the introduced criterion of a clustering-based thresholding approach with a chi-squared quality-of-fit metric. The proposed strategy achieves a good trade-off between the effectiveness of track reconstruction and the pace of execution on today’s advanced multicore computers. To facilitate this, a quality benchmark for reconstruction is established, using the root mean square (rms) error of spiral and polynomial fitting for the datasets identified as the subsequent track candidate by the neural network. Choosing the right benchmark enables us to maintain the recall and precision indicators of the neural network track recognition performance at a level that is satisfactory to physicists, even though these metrics will inevitably decline as the data noise increases. Moreover, it has been possible to improve the processing speed of the complete program pipeline by 6 times through parallelization of the algorithm, achieving a rate of 2000 events per second, even when handling extremely noisy input data.
Effect of Irrigation Water Salinity on Soil Characteristics and Microbial Communities in Cotton Fields in Southern Xinjiang, China
Authors: Ding Bangxin , Bai Yungang , Guo Shuchen , He Zijian , Wang Bei , Liu Hongbo , Zhai Jiangrui , Cao Hongxia
Published: June 2023

Irrigation with saline water is a possible solution to alleviate freshwater shortages. The long-term use of saline water for irrigation requires consideration of the influence of salt on the environmental conditions of the soil. The objective of this field study was to determine the effects of three continuous years of saline water irrigation on physiochemical properties and microbial communities in drip-irrigated cotton fields. The three total dissolved solid (TDS) levels of irrigation water treatments were (i) 1 g L−1 (fresh water, FWI), (ii) 3 g L−1 (brackish water, BWI), and (iii) 7 g L−1 (salt water, SWI). After three years, the electrical conductivity (EC), sodium adsorption ratio (SAR), and contents of K+, Na+, Mg2+, Cl−, and SO42− in the SWI treatment were significantly higher than those in the FWI and BWI treatments, but there were no significant differences in EC and K+ between the FWI and BWI treatments. BWI treatment significantly increased microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), urease, and sucrase contents. The diversity and abundance of bacteria and fungi were not affected by saline water irrigation, but the microbial community structure was altered. Saline water irrigation resulted in an elevation in the bacterial abundance of the phylum Chloroflexi and a decline in Proteobacteria and Actinobacteria. For fungi, the abundance of the phylum Ascomycota in the BWI treatment was greater than that in the FWI and SWI treatments. Linear discriminant analysis effect size (NMDS) results indicated clear variation in the microbiota profiles between the FWI, BWI, and SWI treatments for bacteria. Regarding the fungal microbiota profiles, the BWI and SWI treatments had similar microbiota profiles but were different from the FWI treatment. The number of bacterial biomarkers gradually increased with increasing total dissolved solids of irrigation water, while the number of fungal biomarkers gradually decreased. Additionally, cotton yield was significantly and positively correlated with the observed species of fungi, while it was significantly and negatively correlated with EC. Redundancy analysis (RDA) showed that bacterial community structure was regulated by SAR and fungal community structure was regulated by soil salinity and bulk density (BD). Future research will need to look into how the structure of the microbial community and the associated functional microorganisms are gradually changing with increased irrigation frequency under saline irrigation, as well as explore and screen for advantageous functional microorganisms.
Humic Acid Improves the Resilience to Salinity Stress of Drip-Irrigated Mexican Lime Trees in Saline Clay Soils
Authors: Ennab Hassan A. , Mohamed Azza H. , El-Hoseiny Hanan M. , Omar Ahmad A. , Hassan Islam F. , Gaballah Maybelle S. , Khalil Soha E. , Mira Amany M. , Abd El-Khalek Ahmed F. , Alam-Eldein Shamel M.
Published: June 2023

Organic fertilization improves soil fertility and ameliorates the deleterious effects of accumulated salts in soil for sustainable agricultural production. This research was carried out on thirteen-year-old Mexican lime trees to study the effect of humic acid (HA), applied as soil (10, 20 or 30 mL·tree−1) and foliar (0.1 or 0.2%) applications, on soil fertility, tree growth, productivity and fruit quality. The experiment was conducted during the 2020 and 2021 seasons in a randomized complete block design of twelve treatments with three replicates with two trees each. Soil and foliar applications of HA were performed once and twice a month in Marsh, May and July, respectively. HA enhanced the soil’s N, P, K, Ca, Mg, Fe, Mn, Zn, Cu and B availability and microbial activity, in addition to improved tree growth, canopy size, leaf chlorophyll and nutrient contents with reduced proline levels. The total yield and number of fruit per tree were increased with increased HA levels. Fruit weight, juice and soluble solids were also increased. The best results were achieved with the combined soil (30 mL·tree−1) and foliar (0.2%) applications of HA, which indicated a great potential to alleviate the effects of salinity stress on Mexican lime growth and productivity.
Increased CCL-5 (RANTES) Gene Expression in the Choroid Plexus of Dogs with Canine Leishmaniosis
Authors: Silva José Eduardo dos Santos , Jussiani Giulia Gonçalves , Grano Fernanda Grecco , Pelissari Maria Cecília Clarindo , de Melo Guilherme Dias , Negrão Watanabe Tatiane Terumi , de Lima Valéria Felix , Machado Gisele Fabrino
Published: June 2023

Visceral canine leishmaniasis (CanL) can cause several clinical manifestations, including neurological lesions. Few reports have characterized the lesions observed in the central nervous system (CNS) during CanL; however, its pathogenesis remains unclear. The choroid plexus (CP) is a specialized structure responsible for the production and secretion of cerebrospinal fluid (CSF) and considered an interface between the peripheral immune system and CNS. It can allow the passage of inflammatory cells or pathogens and has the potential to act as a source of inflammatory mediators in several diseases. Thus, this study aimed to evaluate the role of CP as a possible route of inflammatory cells in the development of brain lesions in dogs with CanL, as well as its association with blood–CSF barrier (BCSFB) dysfunction. Samples were collected from 19 dogs that were naturally infected with CanL. We evaluated the histopathological lesions in the brain and investigated the gene expression of the cytokines. Capture enzyme-linked immunosorbent assay (ELISA) was used to evaluate the presence of the same cytokines in the CSF. Biochemical analysis was performed to compare the presence of albumin in the serum and CSF. Indirect ELISA was performed to measure the presence of anti-Leishmania antibodies in the CSF, which would suggest the disruption of the BCSFB. Histopathological evaluation of the dogs’ brains revealed mild-to-severe inflammatory infiltrates, mainly in the CP and meninges. We also detected the presence of anti-Leishmania antibodies and albumin in the CSF, as well as Leishmania DNA in the CP. The gene expression of CCL-5 was increased in the CP of infected dogs compared with that of controls, and there was a tendency for the increase in the gene expression of CXCL-10. Thus, our findings confirm the disfunction of the BCSFB during CanL and suggest that the chemokines CCL-5 and CXCL-10 can be responsible for the recruitment of inflammatory cells found in CP.
On-Site Inspection Form in Veterinary Cases: The Parma Veterinary Form
Authors: Marchetti Cristina , Mastrogiuseppe Luigi , Vanin Stefano , Cecchi Rossana , Gherardi Mirella
Published: June 2023

The on-site inspection of the scene of an animal cadaver is crucial for a correct interpretation of the autopsy results, to determine the manner, method, and cause of death. This information plays a crucial role in the control of public health including the prevention of zoonoses. It is also fundamental for the recognition and the contrast of crimes against animals and to animal abuse phenomena, considered an alert sign of an anti-social or violent behavior of humans. Today the best veterinary procedure requires an accurate collection of the evidence at the scene that can be then handed to experts belonging to other forensic disciplines for further evaluation and data interpretation. In this paper authors suggest a form aiming to facilitate either the on-site and the autopsy activities, as a guarantee of the quality of the forensic process starting from the discovery scene up to the reconstruction of the case. Essential is training of non-medical personnel who often represent the first responder to be present on the scene. The form is inspired by the interdisciplinary form developed by the European Council of Legal Medicine and represents an initial tool to stimulate a multidisciplinary activity in close synergy with other forensic experts.
Calcium/Calmodulin-Dependent Serine Protein Kinase (CASK) Gene Polymorphisms in Pigeons
Authors: Dybus Andrzej , Kulig Hanna , Grzesiak Wilhelm , Domke Justyna , Yu Yu-Hsiang , Cheng Yeong-Hsiang
Published: June 2023

Calcium/calmodulin-dependent serine protein kinase (CASK) is an multidomain protein involved in tissue development and cell signalling. In skeletal muscle, it is involved in the development of neuromuscular junctions. The participation of a pigeon in racing is a great physical effort that causes many changes in the skeletal muscles. Thus, the purpose of the study was to detect the nucleotide sequence variability in the calcium/calmodulin-dependent serine kinase (CASK) gene in domestic pigeons (Columba livia domestica) and assess the potential impact of DNA polymorphisms on the flight performance of pigeons. The research included a total of 517 individuals. DNA was extracted from the blood. A DNA fragment from nucleotides 8689 to 9049 of the CASK (NW_004973256.1 sequence) of six unrelated pigeons were sequenced. One of the detected polymorphic sites (g.8893G > A), located a very close to the start codon, was selected for genotyping in all individuals. The association studies included a total of 311 young homing pigeons that participated in racing competitions. The homing pigeons showed higher frequencies of the AA genotype than non-homing ones (p < 0.05). In rock pigeons only the GG genotype was found. Further research could confirm the functionality of the CASK g.8893G > A SNP in shaping the racing phenotype of pigeons, and the AA genotype could be useful as a selection criterion in pigeon breeding.
Profitability and Cost Analysis for Contract Broiler Production in Turkey
Authors: Karaman Suleyman , Taşcıoğlu Yavuz , Bulut Osman Doğan
Published: June 2023

This study uses the data obtained from 63 broiler farms engaged in contract farming in Akhisar, Turkey. The average feed conversion ratio in the broiler farms is 1.75, the average live weight 2.25 kg, and the mean market age 38.9 days. The feed conversion rate and the income generated are highly correlated (r = −0.76). The production index is 313.4. According to this production index value, 47.6% of the enterprises are below the average production index. It is highest when the marketing age is greater than 38 days, less than and equal to 40. In other words, it is the optimum market age range where carcass yield is at maximum. The average mortality rate is 4.68%. In 52.4% of the enterprises, the mortality rate is above 5%. There is a low level of correlation between the mortality rate and income (r = −0.26). In broiler farming, mortality rate, and feed conversion ratio are factors that directly affect the success and income of the breeder. In broiler farming, the heating cost has the largest share of the total cost, followed by the litter cost. They are followed by labor, electricity, and pesticide costs. Variable costs account for three-quarters of the total operating costs. The farms have a mean gross value of production of $23.797 per m2 and $1.400 per broiler in a breeding period. The profit margin is 0.572 $/kg per broiler. The mean enterprise net income in the breeding period is $9.197 per m2 and $0.541 per broiler. These findings suggest that broiler farming is a profitable venture.
Symptoms, Treatment, and Outcomes of COVID-19 Patients Coinfected with Clostridioides difficile: Single-Center Study from NE Romania during the COVID-19 Pandemic
Authors: Stămăteanu Lidia Oana , Miftode Ionela Larisa , Pleșca Claudia Elena , Dorneanu Olivia Simona , Roșu Manuel Florin , Miftode Ioana Diandra , Obreja Maria , Miftode Egidia Gabriela
Published: June 2023

The Coronavirus disease 2019 (COVID-19) pandemic has brought new challenges across medical disciplines, particularly in infectious disease medicine. In Romania, the incidence of SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2) infection increased dramatically since March 2020 until March 2022. Antibiotic administration for pulmonary superinfections in COVID-19 intensified and, consequently, increased rates of Clostridioides difficile infection (CDI) were hypothesized. We conducted a single-center, retrospective, observational study on patients from North-Eastern Romania to assess clinical characteristics and outcomes of COVID-19 and Clostridioides difficile (CD) coinfection, and to identify risk factors for CDI in COVID-19 patients. The study enrolled eighty-six CDI and COVID-19 coinfected patients admitted during March 2020–February 2021 (mean age 59.14 years, 53.49% men, 67.44% urban residents) and a group of eighty-six COVID-19 patients. On admission, symptoms were more severe in mono-infected patients, while coinfected patients associated a more intense acute inflammatory syndrome. The main risk factors for severe COVID-19 were smoking, diabetes mellitus, and antibiotic administration. Third generation cephalosporins (55%) and carbapenems (24%) were the main antibiotics used, and carbapenems were significantly associated with severe COVID-19 in patients coinfected with CD during hospitalization. Coinfection resulted in longer hospitalization and poorer outcomes. The extensive use of antibiotics in COVID-19, particularly carbapenems, contributed substantially to CD coinfection.
Implications of Arch Warp Altitudes on an Ancient Masonry Bridge under Ground Movements
Authors: Karalar Memduh , Yeşil Mustafa
Published: June 2023

Although only a few of the ancient masonry arch bridges (MABs) are in fairly good condition today, many ancient arch bridges are still in use. Over time, the condition of the masonry bridges declines and the safety requirements change. Therefore, it is important to examine these bridges under different influences. The strengthening of MABs is generally not essential. The major cause of damage to MABs is their insufficient width and height, and thus, it is not the safety but the usability that has restricted the life-time of the MABs. Therefore, in this investigation, the effect of the arch height on the static and dynamic behavior of a single-span MAB was investigated. For this aim, the Ancient Tokatlı Bridge, built in Karabük, Türkiye, was selected for investigation under near-fault (NF) and far-fault (FF) ground motions (GMs). To observe the altitude of the arch warp on the ancient MAB, first, the finite element model (FEM) was utilized, using ANSYS and SAP 2000. Furthermore, to constitute the arch warp’s influence on a MAB, the FEM was remodeled considering the different arch warps between 7.0 and 9.0 m. Moreover, GMs were applied to the FEM to investigate the effect of dynamic behavior. Under these GMs, stresses and strains (compression and tensile) were observed and compared with each other. Consequently, at the end of these investigations, it was observed that the maximum motions were reduced, while the height of the one-span MAB was increased under NF and FF GMs, and this was also true for the contrary situations. The compression stresses were not observed to be hazardous at the point of destruction, while the altitude of the one-span MAB increased.
Privacy-Aware Cloud Architecture for Collaborative Use of Patients’ Health Information
Authors: Alhaddadin Fadi , Gutierrez Jairo
Published: June 2023

Cloud computing appears to be the dreamed-of vision of the healthcare industry; it refers to means of storing and accessing data and programs over the Internet instead of the computer’s hard drive. However, the adoption of cloud computing requires solving several issues, and information privacy is a major one. This work proposes a cloud architecture design for the healthcare information system. The proposed architecture enables storing and sharing information in a privacy-preserving manner. Patients’ information in the proposed architecture is divided into four categories identified in the case study data analysis. User identity management protocol (U-IDM) is employed for controlling access to patients’ information, and patients have means of control over who can access their information. A scenario-based instantiation validated the proposed architecture’s privacy-preserving patient data exchange. The instantiation proved that the proposed architecture allows sharing healthcare information without violating the privacy of patients.
Artificial Intelligence in Agriculture: Benefits, Challenges, and Trends
Authors: Oliveira Rosana Cavalcante de , Silva Rogério Diogne de Souza e
Published: June 2023

The world’s population has reached 8 billion and is projected to reach 9.7 billion by 2050, increasing the demand for food production. Artificial intelligence (AI) technologies that optimize resources and increase productivity are vital in an environment that has tensions in the supply chain and increasingly frequent weather events. This study performed a systemic review of the literature using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology on artificial intelligence technologies applied to agriculture. It retrieved 906 relevant studies from five electronic databases and selected 176 studies for bibliometric analysis. The quality appraisal step selected 17 studies for the analysis of the benefits, challenges, and trends of AI technologies used in agriculture. This work showed an evolution in the area with increased publications over the last five years, with more than 20 different AI techniques applied in the 176 studies analyzed, with machine learning, convolutional neural networks, IoT, big data, robotics, and computer vision being the most used technologies. Considering a worldwide scope, the countries highlighted were India, China, and the USA. Agricultural sectors included crop management and prediction and disease and pest management. Finally, it presented challenges and trends that are promising when considering the future directions in AI for agriculture.
Spatial Distribution and Main Controlling Factors of Nitrogen in the Soils and Sediments of a Coastal Lagoon Area (Shameineihai, Hainan)
Authors: Yuan Kun , Song Yanwei , Fu Guowei , Lin Bigui , Fu Kaizhe , Wang Zhaofan
Published: June 2023

As the relationship between the spatial distribution characteristics and physicochemical properties of nitrogen in lagoon soil and sediment is still unclear, we obtained and systematically analyzed soil and sediment samples from the surroundings of a lagoon in the Shamei Inland Sea, Qionghai City, Hainan Province. The spatial distribution of nitrogen forms was investigated, and the soil physicochemical properties that predominantly influenced the nitrogen distribution were characterized. The results were as follows: (1) There are differences in nitrogen content in the soil and sediment around the Shamei Inland Sea. The total nitrogen levels in the Shamei Inland Sea were low, and organic nitrogen was dominant. The soil samples showed higher organic nitrogen concentrations than the sediment samples. Thus, the characteristics of dispersion in offshore waters differ from those in lagoons. The average contents of nitrate, ammonium and nitrite in the soil around the lagoon were higher than those in the sediment, and they were especially high in the lagoon mouth area. The nitrate content was greater in the estuary area in the northwest of the lagoon, and the contents of ammonium and nitrite in the estuary area in the south of the lagoon were the highest. (2) The changes in the basic physical and chemical properties of the soils and sediments in the Shamei Inland Sea area have an important coupled effect on the enrichment, preservation and mineralization of nitrogen. Through redundancy analysis (RDA), the explanatory degree of the organic matter content in relation to the nitrogen content was determined to be approximately 17.2%, contributing 80.9% of all nitrogen. The organic matter content, cation exchange capacity and clay content were positively correlated with the nitrogen content, indicating that changes in the basic physical and chemical properties of the soil and sediment had an important impact on nitrogen enrichment, preservation and mineralization processes. The total nitrogen and the organic matter content, cation exchange capacity and clay content of the soil and sediment were positively correlated. The high proportion of nitrate in the soil, the high proportion of ammonium in the sediment, the heavy texture of the sediment, poor soil ventilation and weak nitrification were related.
Efficient Roundabout Supervision: Real-Time Vehicle Detection and Tracking on Nvidia Jetson Nano
Authors: Elmanaa Imane , Sabri My Abdelouahed , Abouch Yassine , Aarab Abdellah
Published: June 2023

In recent years, a significant number of people in Morocco have been commuting daily to Casablanca, the country’s economic capital. This heavy traffic flow has led to congestion and accidents during certain times of the day as the city’s roads cannot handle the high volume of vehicles passing through. To address this issue, it is essential to expand the infrastructure based on accurate traffic-flow data. In collaboration with the municipality of Bouskoura, a neighboring city of Casablanca, we proposed installing a smart camera on the primary route connecting the two cities. This camera would enable us to gather accurate statistics on the number and types of vehicles crossing the road, which can be used to adapt and redesign the existing infrastructure. We implemented our system using the YOLOv7-tiny object detection model to detect and classify the various types of vehicles (such as trucks, cars, motorcycles, and buses) crossing the main road. Additionally, we used the Deep SORT tracking method to track each vehicle appearing on the camera and to provide the total number of each class for each lane, as well as the number of vehicles passing from one lane to another. Furthermore, we deployed our solution on an embedded system, specifically the Nvidia Jetson Nano. This allowed us to create a compact and efficient system that is capable of a real-time processing of camera images, making it suitable for deployment in various scenarios where limited resources are required. Deploying our solution on the Nvidia Jetson Nano showed promising results, and we believe that this approach could be applied in similar traffic-surveillance projects to provide accurate and reliable data for better decision-making.
Bearing Fault Diagnosis Method Based on Deep Learning and Health State Division
Authors: Shi Lin , Su Shaohui , Wang Wanqiang , Gao Shang , Chu Changyong
Published: June 2023

As a key component of motion support, the rolling bearing is currently a popular research topic for accurate diagnosis of bearing faults and prediction of remaining bearing life. However, most existing methods still have difficulties in learning representative features from the raw data. In this paper, the Xi’an Jiaotong University (XJTU-SY) rolling bearing dataset is taken as the research object, and a deep learning technique is applied to carry out the bearing fault diagnosis research. The root mean square (RMS), kurtosis, and sum of frequency energy per unit acquisition period of the short-time Fourier transform are used as health factor indicators to divide the whole life cycle of bearings into two phases: the health phase and the fault phase. This division not only expands the bearing dataset but also improves the fault diagnosis efficiency. The Deep Convolutional Neural Networks with Wide First-layer Kernels (WDCNN) network model is improved by introducing multi-scale large convolutional kernels and Gate Recurrent Unit (GRU) networks. The bearing signals with classified health states are trained and tested, and the training and testing process is visualized, then finally the experimental validation is performed for four failure locations in the dataset. The experimental results show that the proposed network model has excellent fault diagnosis and noise immunity, and can achieve the diagnosis of bearing faults under complex working conditions, with greater diagnostic accuracy and efficiency.
An Adaptive Subinterval Finite Element Method Based on Dynamic Sensitivity Analysis for Structures with Uncertain-but-Bounded Parameters
Authors: Huang Mian , Yao Guofeng , Gao Kuiyang , Wang Min
Published: June 2023

To overcome computational inefficiency of the traditional subinterval finite element method, a novel adaptive subinterval finite element method based on dynamic sensitivity analysis is proposed to evaluate static response bounds of structures with uncertain-but-bounded parameters. Firstly, the original interval is divided into subintervals, and expansion routes for each displacement component are constructed based on dynamic sensitivity analysis. Then, the structural response bounds are analysed using a modified interval finite element method within each subinterval on the expansion route. Finally, the bounds of all displacement components are obtained via the interval union operation. To determine the appropriate number of subintervals, an adaptive convergence mechanism is proposed. The proposed method has accuracy and efficiency advantages over traditional subinterval finite element methods. The accuracy and effectiveness of this method are verified via numerical calculations of a nine-bar truss and an impeller.
Exploring Sources and Health Risks in Beijing PM2.5 in 2019 and 2020
Authors: Yuan Jing , Zuo Hanfei , Jiang Yuchun , Zhang Puzhen , Wang Ziqi , Guo Chen , Wang Zhanshan , Wen Qing , Chen Ye , Wei Yongjie , Li Xiaoqian
Published: June 2023

The various industries, sectors, and citizens’ daily lives have undergone significant changes after the outbreak of the COVID-19 pandemic. The researchers collected and analyzed PM2.5 samples including secondary inorganic ions (SO42−, NO3−, and NH4+, namely SNA), organic carbon (OC), elemental carbon (EC), and other 16 metal elements in Beijing in 2019 (before the pandemic) and 2020 (after the pandemic). The particulate matter (PM2.5) concentration in the autumn and winter of 2020 is 21.16 µg/m3 and 14.05 µg/m3 lower than in 2019, respectively. The contribution of six sources of pollution, including coal combustion, secondary sources, transportation-related sources, dust, Industrial I, and Industrial II, were analyzed using the Positive Matrix Factorization (PMF) model. Due to the impacts of the COVID-19 pandemic, more and more people are choosing private transportation, such as private cars, instead of public transportation. As a result, the contribution of PM2.5 pollution related to transportation increased after the pandemic. The metal elements measured during the sampling period represent only a very small fraction (1%) of PM2.5. However, their health risk to humans cannot be ignored because of the toxicity of some metallic elements, and the carcinogenic risks induced by metal elements in PM2.5 exceeded the safety threshold (>10−6) during the autumn and winter of 2019 and 2020. Arsenic (As) contributes the most to carcinogenic risk, so controlling arsenic emissions is the primary approach to reducing cancer risk in Beijing. Considering the contribution to the health risk from various sources obtained in PMF, coal combustion is the most significant contributor to cancer risk. Therefore, serious consideration should be given to controlling coal combustion at the local and regional levels to reduce health risks in Beijing.
CNT and Graphene-Based Transistor Biosensors for Cancer Detection: A Review
Authors: Sengupta Joydip , Hussain Chaudhery Mustansar
Published: June 2023

An essential aspect of successful cancer diagnosis is the identification of malignant tumors during the early stages of development, as this can significantly diminish patient mortality rates and increase their chances of survival. This task is facilitated by cancer biomarkers, which play a crucial role in determining the stage of cancer cells, monitoring their growth, and evaluating the success of treatment. However, conventional cancer detection methods involve several intricate steps, such as time-consuming nucleic acid amplification, target detection, and a complex treatment process that may not be appropriate for rapid screening. Biosensors are emerging as promising diagnostic tools for detecting cancer, and carbon nanotube (CNT)- and graphene-based transistor biosensors have shown great potential due to their unique electrical and mechanical properties. These biosensors have high sensitivity and selectivity, allowing for the rapid detection of cancer biomarkers at low concentrations. This review article discusses recent advances in the development of CNT- and graphene-based transistor biosensors for cancer detection.
Pro-Gastrin-Releasing Peptide as a Biomarker in Lung Neuroendocrine Neoplasm
Authors: Rosiek Violetta , Kogut Angelika , Kos-Kudła Beata
Published: June 2023

There is a lack of effective biomarkers for diagnosing lung neuroendocrine neoplasms (LNENs). A known small cell lung cancer (SCLC) biomarker is a pro-gastrin-releasing peptide (ProGRP), but not for all LNENs, especially for bronchopulmonary carcinoids. This study aimed to evaluate the diagnostic value of ProGRP and chromogranin A (CgA) in diagnosing LNENs. The ProGRP and CgA levels in 290 cases of LNENs and 54 healthy controls (HCs) were measured. The median ProGRP concentration in the group of LNEN patients was 136.4 pg/mL, higher than that of HCs at 6.5 pg/mL. Most of the LNEN cohort was well-differentiated tumors (typical and atypical carcinoids, n = 262, 91.7% of all LNENs). The sensitivity, specificity, and area under the curve (AUC) of ProGRP when distinguishing LNENs vs. HCs were 94.8%, 100%, and 0.995. CgA (AUC = 0.375) could not determine LNENs vs. HCs. Therefore, based on these results, ProGRP may be considered as an effective marker for diagnosing LNENs.
Secondary-Type Mutations in Acute Myeloid Leukemia: Updates from ELN 2022
Authors: Bouligny Ian M. , Maher Keri R. , Grant Steven
Published: June 2023

The characterization of the molecular landscape and the advent of targeted therapies have defined a new era in the prognostication and treatment of acute myeloid leukemia. Recent revisions in the European LeukemiaNet 2022 guidelines have refined the molecular, cytogenetic, and treatment-related boundaries between myelodysplastic neoplasms (MDS) and AML. This review details the molecular mechanisms and cellular pathways of myeloid maturation aberrancies contributing to dysplasia and leukemogenesis, focusing on recent molecular categories introduced in ELN 2022. We provide insights into novel and rational therapeutic combination strategies that exploit mechanisms of leukemogenesis, highlighting the underpinnings of splicing factors, the cohesin complex, and chromatin remodeling. Areas of interest for future research are summarized, and we emphasize approaches designed to advance existing treatment strategies.
Titanium Carbide and Vibration Effect on the Structure and Mechanical Properties of Medium-Carbon Alloy Steel
Authors: Kovalyova Tatyana , Skvortsov Yevgeniy , Kvon Svetlana , Gerard Michot , Issagulov Aristotle , Kulikov Vitaliy , Skvortsova Anna
Published: June 2023

This study aimed to improve the hardness and wear behavior of medium-carbon alloy steel through the addition of titanium carbide ultradispersed powder and low-frequency vibration treatment during solidification. It was shown that the complex effect of low-frequency vibration with the additional introduction of a small amount of titanium carbide ultradispersed powder with the size of 0.5–0.7 μm during the casting process had a positive effect on structural changes and led to improved mechanical properties, and so increasing the value of microhardness by 37.2% was notable. In the process of shock dynamic impact, imprints with crater depths of 13.69 µm (500 N) and 14.73 (700 N) were obtained, which, respectively, are 23.34 and 42.34% less than that on the original cast sample. In the process of tribological testing, decreasing the depth of the wear track (50.25%) was revealed with decreasing the value of the friction coefficient by 14.63%.
Photocatalytic and Antimicrobial Activity of Titanium(IV)-Oxo Clusters of Different Core Structure
Authors: Kubiak Barbara , Piszczek Piotr , Radtke Aleksandra , Muzioł Tadeusz , Wrzeszcz Grzegorz , Golińska Patrycja
Published: June 2023

The purpose of this paper is to assess the relationship between the core architecture of titanium(IV)-oxo complexes (TOCs) known as {TiaOb} and their photocatalytic and antimicrobial activity. The following TOCs: [Ti6O4(OiBu)8(O2C13H9)8] · 2(CH3)2CO (1), [Ti6O6(OiBu)6(O2C13H9)6] (2), [Ti6O6(OiBu)6(O2C13H9)6] (3), [Ti3O(OiPr)8(O2C13H9)2] (4), and [Ti4O2(OiBu)10(O2C13H9)2] (5), where -O2C13H9represents 9-fluorene-carboxylate ligands, werestudied to investigate thiseffect. The structures of (1)–(5) were confirmed using single-crystal X-ray diffraction and spectroscopic methods. Since TOCs can be sensitive to hydrolysis processes, their photocatalytic and antimicrobial activity was evaluated after dispersing them in a polymer matrix, which acted as a protective agent against the aquatic environment. The results revealed that the photocatalytic activity of the studied TOCs follows the trend (2) > (5) > (4) > (1) in both the UV and visible ranges. All studied oxo complexes exhibited strong antibacterial activity against Gram-positive strains and weaker activity against Gram-negative strains. The proposed mechanism of the antimicrobial activity of TOCs assumes that this effect is associated with the generation of reactive oxygen species (ROS) on the surface of composite samples. Samples of PMMA + (1) 10 wt.% and PMMA + (5) 20 wt.%, in which both O− and O2− paramagnetic species were observed in the electron paramagnetic spectroscopy (EPR) spectra, demonstrated the highest antimicrobial activity.
Nature-Based Virtual Reality Feasibility and Acceptability Pilot for Caregiver Respite
Authors: Alanazi Mohammed Owayrif , Patano Arienne , Bente Gary , Mason Andrew , Goldstein Dawn , Parsnejad Sina , Wyatt Gwen , Lehto Rebecca
Published: June 2023

Home-based informal caregivers (CGs), such as the family members and friends of cancer patients, often suffer averse emotional symptoms, such as anxiety and depression, due to the burden associated with providing care. The natural environment has been valued as a healing sanctuary for easing emotional pain, promoting calmness, relaxation, and restoration. The use of virtual reality (VR) nature experiences offers an alternative option to CGs to manage emotional symptoms and improve their quality of life. The aim of this mixed-method pilot was to evaluate the feasibility and acceptability of a nature-based VR experience for home-based CGs. Nine informal CGs participated in a 10 min nature-based VR session and completed feasibility, acceptability, and VR symptom measures in the laboratory. Semi-structured interviews with five of the CGs provided qualitative data regarding their experiences with VR. The CGs (mean age 64.78 years) were mostly female (n = 7). Our analysis showed high feasibility (15.11 ± 1.76; range 0–16) and acceptability (15.44 ± 1.33; range 0–16), as well as low VR Symptoms (1.56 ± 1.33; range 0–27). Participants primarily expressed positive perceptions regarding VR feasibility and acceptability during interviews. Our findings show promise for the use of VR nature experiences. In the next phase of the study, the intervention will be tested on home-based informal CGs of patients at end of life.
Constructing the Schizophrenia Recognition Method Employing GLCM Features from Multiple Brain Regions and Machine Learning Techniques
Authors: Gengeç Benli Şerife , Andaç Merve
Published: June 2023

Accurately diagnosing schizophrenia, a complex psychiatric disorder, is crucial for effectively managing the treatment process and methods. Various types of magnetic resonance (MR) images have the potential to serve as biomarkers for schizophrenia. The aim of this study is to numerically analyze differences in the textural characteristics that may occur in the bilateral amygdala, caudate, pallidum, putamen, and thalamus regions of the brain between individuals with schizophrenia and healthy controls via structural MR images. Towards this aim, Gray Level Co-occurence Matrix (GLCM) features obtained from five regions of the right, left, and bilateral brain were classified using machine learning methods. In addition, it was analyzed in which hemisphere these features were more distinctive and which method among Adaboost, Gradient Boost, eXtreme Gradient Boosting, Random Forest, k-Nearest Neighbors, Linear Discriminant Analysis (LDA), and Naive Bayes had higher classification success. When the results were examined, it was demonstrated that the GLCM features of these five regions in the left hemisphere could be classified as having higher performance in schizophrenia compared to healthy individuals. Using the LDA algorithm, classification success was achieved with a 100% AUC, 94.4% accuracy, 92.31% sensitivity, 100% specificity, and an F1 score of 91.9% in healthy and schizophrenic individuals. Thus, it has been revealed that the textural characteristics of the five predetermined regions, instead of the whole brain, are an important indicator in identifying schizophrenia.
Evaluating Scoliosis Severity Based on Posturographic X-ray Images Using a Contrastive Language–Image Pretraining Model
Authors: Fabijan Artur , Fabijan Robert , Zawadzka-Fabijan Agnieszka , Nowosławska Emilia , Zakrzewski Krzysztof , Polis Bartosz
Published: June 2023

Assessing severe scoliosis requires the analysis of posturographic X-ray images. One way to analyse these images may involve the use of open-source artificial intelligence models (OSAIMs), such as the contrastive language–image pretraining (CLIP) system, which was designed to combine images with text. This study aims to determine whether the CLIP model can recognise visible severe scoliosis in posturographic X-ray images. This study used 23 posturographic images of patients diagnosed with severe scoliosis that were evaluated by two independent neurosurgery specialists. Subsequently, the X-ray images were input into the CLIP system, where they were subjected to a series of questions with varying levels of difficulty and comprehension. The predictions obtained using the CLIP models in the form of probabilities ranging from 0 to 1 were compared with the actual data. To evaluate the quality of image recognition, true positives, false negatives, and sensitivity were determined. The results of this study show that the CLIP system can perform a basic assessment of X-ray images showing visible severe scoliosis with a high level of sensitivity. It can be assumed that, in the future, OSAIMs dedicated to image analysis may become commonly used to assess X-ray images, including those of scoliosis.
Experiment Study of Single Event Functional Interrupt in Analog-to-Digital Converters Using a Pulsed Laser
Authors: Mai Ziqi , Zhu Xiang , Li Hongwei , Han Jianwei , He Tao
Published: June 2023

Single Event Functional Interrupt (SEFI) poses a severe threat to the normal operation of spacecraft. This paper investigates SEFI in Analog-to-Digital Converters (ADCs) with storage units using precision positioning of pulsed lasers. Based on the experiment, it was discovered that a bit flip in the configuration registers in ADCs results in changes in parameters such as digital filter frequency, operating mode, and gain, leading to an upward or downward offset of ADC output codes. Similarly, a bit flip in the calibration registers also causes ADC output codes to shift upwards or downwards, or even output a value of zero. Furthermore, it was observed that SEFI phenomena can occur due to current latch-up in ADC input pins, causing the inability to read or write data in ADC storage units. This current latch-up can be resolved through power cycling or configuring the pins into a high-impedance state. This work highlights the significance of SEFI phenomena in ADCs, emphasizing the serious threat posed by storage unit flipping-induced SEFI to the proper functioning of ADCs. Moreover, the SEFI phenomenon caused by current latch-up in input pins is difficult to detect in practice, making it highly elusive. Once it occurs, it severely impacts the functionality of ADCs.
A Regulated 400-mV CMOS DC-DC Converter with On-the-Fly Equivalent Output Resistance Tuning
Authors: Dutra Luis Felipe Machado , Girardi Alessandro G. , de Aguirre Paulo César C. , Compassi-Severo Lucas
Published: June 2023

Energy harvesting is a technology that can be applied to IoT systems to eliminate the need for batteries. Many types of energy sources are available for energy harvesting, such as light, thermal, vibration, and electromagnetic energy. Indoors, where most IoT devices are located, artificial light, such as from LED lamps, can be used for energy harvesting in circuits with very ultra-low power consumption. Integrated switch-capacitor DC-DC converters are required for this type of system to convert the harvested energy into a constant output voltage suitable for powering an electronic circuit. The idea of this work is to use a hysteretic feedback control consisting of comparators and a logic system to adjust the switching frequency and the voltage conversion ratio (VCR) of the converter. With this, the equivalent output resistance is tuned to a value that results in a constant output voltage. A new method for modeling the equivalent output resistance based on charge flow analysis is proposed, which also considers the effects of source resistance. An integrated energy-harvesting system consisting of a switched-capacitor DC-DC converter is implemented to obtain an output voltage of 400 mV using a small photovoltaic cell for energy harvesting from indoor light. The proposed system can power an ultra-low-power device between 20 μW and 40 μW with a minimum input voltage of 230 mV. Electrical simulation results show that the implemented converter can achieve a peak efficiency of 81.24% at an input voltage of 260 mV for a 20 μW load.