bluuebunny/crossref_metadata_2025 huggingface dataset:
Co-infection of high-risk Human papillomavirus and Human T-lymphotropic virus-1 among women living with HIV on antiretroviral therapy at a tertiary hospital in Kenya
Authors: Kangethe James Mburu , Gichuhi Stephen , Odari Eddy Okoth , Pintye Jillian , Mutai Kenneth , Abdullahi Leila , Maiyo Alex , Mureithi Marianne W.
Published: July 2023

Background

Globally, 15% of reported cancers are virus-associated. Cancer-causing viruses include high-risk Human papillomavirus (HR-HPV), the causative agent of cervical cancer, and Human T-lymphotropic virus type-1 (HTLV-1), the causative agent of adult T-cell leukemia (ATL). HTLV-1 infection may enhance susceptibility to acquiring HR-HPV infections due to its retrovirus properties, resulting in increased cervical abnormalities among women living with HIV (WLHIV). In Kenya, there is a paucity of data on the burden of HR-HPV/HTLV-1 co-infection among WLHIV. We determined the prevalence of HR-HPV and HTLV-1 co-infection among WLHIV on antiretroviral therapy (ART) at Kenya’s national referral hospital, Kenyatta National Hospital (KNH).

Methodology

We conducted a cross-sectional study among WLHIV on ART attending KNH’s HIV care clinic. Study nurses collected a cervical sample with a cytobrush for HPV genotyping using Gene Xpert ® assays and HPV Genotypes 14 Real-TM Quant. Peripheral blood mononuclear cells were used for HTLV-1 DNA detection. Differences in frequency distributions of characteristics between WLHIV with and without HR-HPV and HTLV-1 co-infections were assessed using the Chi-square tests.

Results

A total of 647 WLHIV enrolled in this study with a mean age of 42.8 years (SD 8.7); 93% were on ART for >1 year and 8.8% were not virally suppressed (>1000 HIV RNA copies/mL). The HTLV-1 positivity rate among WLHIV was 3.1% overall and 7.6% among those with HR-HPV. WLHIV with HR-HPV 31 had the highest proportion of HR-HPV/HTLV-1 co-infection (31.6%). In contrast, WLHIV with HR-HPV 39 had the lowest proportion of co-infection (7.1%). Participants with HR-HPV/HTLV-1 co-infections were older compared to those without the co-infections (35.2% vs. 23.3%). A higher proportion of women with HR-HPV/HTLV-1 co-infections had their sex debut before the age of 18 years (p=0.012). Women co-infected with HR-HPV/HTLV-1 were diagnosed with HIV at ≥ 35 years compared to those without infection (70.6% vs. 41.9%, p= 0.019).

Conclusion

We found that HTLV-1 infection was more common among WLHIV on ART who also had HR-HPV and that co-infections were associated with the age of sexual debut and the age of HIV diagnosis.
Evolving Multi-Output Digital Circuits Using Multi-Genome Grammatical Evolution
Authors: Tetteh Michael , de Lima Allan de , McEllin Jack , Murphy Aidan , Dias Douglas Mota , Ryan Conor
Published: July 2023

Grammatical Evolution is a Genetic Programming variant which evolves problems in any arbitrary language that is BNF compliant. Since its inception, Grammatical Evolution has been used to solve real-world problems in different domains such as bio-informatics, architecture design, financial modelling, music, software testing, game artificial intelligence and parallel programming. Multi-output problems deal with predicting numerous output variables simultaneously, a notoriously difficult problem. We present a Multi-Genome Grammatical Evolution better suited for tackling multi-output problems, specifically digital circuits. The Multi-Genome consists of multiple genomes, each evolving a solution to a single unique output variable. Each genome is mapped to create its executable object. The mapping mechanism, genetic, selection, and replacement operators have been adapted to make them well-suited for the Multi-Genome representation and the implementation of a new wrapping operator. Additionally, custom grammar syntax rules and a cyclic dependency-checking algorithm have been presented to facilitate the evolution of inter-output dependencies which may exist in multi-output problems. Multi-Genome Grammatical Evolution is tested on combinational digital circuit benchmark problems. Results show Multi-Genome Grammatical Evolution performs significantly better than standard Grammatical Evolution on these benchmark problems.
Microbial Complexity of Oral Cavity of Healthy Dogs Identified by Mass Spectrometry and Next-Generation Sequencing
Authors: Portilho Fábio V. R. , Nóbrega Juliano , de Almeida Beatriz O. , Mota André R. , de Paula Carolina L. , Listoni Fernando J. P. , Bosco Sandra M. G. , Oliveira Alana L. , Cunha Maria de Lourdes R. S. , Ribeiro Márcio G.
Published: July 2023

The high complexity of the oral microbiota of healthy dogs and the close exposure of humans to companion animals represent a risk of the transmission of potential zoonotic microorganisms to humans, especially through dog bites, including multidrug-resistant ones. Nonetheless, a limited number of comprehensive studies have focused on the diversity of the microorganisms that inhabit the oral cavities of healthy dogs, particularly based on modern molecular techniques. We investigated bacterial and fungal organisms in the oral cavities of 100 healthy dogs based on a combination of conventional and selective microbiological culture, mass spectrometry (MALDI-TOF MS), and next-generation sequencing. In addition, in vitro antimicrobial susceptibility patterns of isolates and mecA resistance gene were assessed. A total of 213 bacteria and 20 fungi were isolated. Staphylococcus pseudintermedius (40/100 = 40%), α-hemolytic Streptococcus (37/100 = 37%), and Pasteurella stomatis (22/100 = 22%) were the most prevalent bacteria diagnosed by microbiological culture and MALDI-TOF MS, whereas Aspergillus (10/100 = 10%) was the most common fungi identified. Based on next-generation sequencing of selected 20 sampled dogs, Porphyromonas (32.5%), Moraxella (16.3%), Fusobacterium (12.8%), Conchiformibius (9.5%), Bergeyella (5%), Campylobacter (3.8%), and Capnocytophaga (3.4%) genera were prevalent. A high multidrug resistance rate was observed in Staphylococcus pseudintermedius isolates, particularly to azithromycin (19/19 = 100%), penicillin (15/19 = 78.9%), and sulfamethoxazole/trimethoprim (15/19 = 78.9%). In addition, the mecA resistance gene was detected in 6.1% (3/49) of coagulase-positive staphylococci. Here, we highlight the microbial complexity of the oral mucosa of healthy dogs, including potential zoonotic microorganisms and multidrug-resistant bacteria, contributing with the investigation of the microbiota and antimicrobial resistance patterns of the microorganisms that inhabit the oral cavity of healthy dogs.
Effect of Ferulic Acid on Semen Quality of Goat Bucks during Liquid Storage at 17 °C
Authors: Zhang Feng , Han Shichang , Zhang Nian , Chai Jin , Xiong Qi
Published: July 2023

This study investigated the effect of different concentrations of ferulic acid (FA) on the quality of goat semen preserved at 17 °C. First, semen was collected from three black-headed goat bucks using an artificial vagina. Then, the mixed semen was diluted with basal dilutions containing different concentrations of FA (0, 25, 50, 100, and 200 μmol/L) and stored at 17 °C. Sperm total motility, plasma membrane integrity, acrosome integrity, reactive oxygen species (ROS) levels, malondialdehyde (MDA) content, and total antioxidant capacity (T-AOC) were measured during semen storage. The results showed that sperm total motility, plasma membrane integrity, and acrosome integrity were significantly improved in the 50 μmol/L FA group compared with the control group (0 μmol/L) on days 1–5, and the level of T-AOC significantly increased, while the contents of ROS and MDA significantly reduced. Meanwhile, the goats’ conception rate showed that supplementing semen with 50 μmol/L FA preserved at 17 °C for 3 days had no significant effect on fertility. Taken together, our findings suggest that adding 50 μmol/L FA in dilution at 17 °C can improve goat bucks’ semen quality.
A Spanish Survey on the Perioperative Use of Antimicrobials in Small Animals
Authors: Otero Balda Ignacio , Fuertes-Recuero Manuel , Penelo Hidalgo Silvia , Espinel Rupérez Jorge , Lapostolle Benoit , Ayllón-Santiago Tania , Ortiz-Díez Gustavo
Published: July 2023

Appropriate use of perioperative antimicrobials can significantly reduce the risk of post-operative infections. However, inappropriate antimicrobial use can result in the creation of multidrug-resistant bacteria, increased costs, host flora disruption, side effects and increased risk of hospital-acquired infections. This survey evaluated the current perioperative use of antimicrobials in small animals by Spanish veterinarians using a web-based questionnaire. Responses were represented using descriptive statistics and a statistical analysis of the association between demographic data and perioperative antimicrobial use was performed. Pre-operative antimicrobials were administered in clean surgery by up to 68.3% of participants, 81.0% in clean-contaminated surgery and 71.3% in dirty surgery, while in the post-operative period, antimicrobials were administered by up to 86.3% of participants in clean surgery, 93.2% in clean-contaminated surgery and 87.5% in dirty surgery. Factors considered “very important” for antimicrobial selection were the degree of wound contamination, patient immunosuppression and use of prosthesis. The most frequently used antimicrobial was beta-lactamase-resistant (or potentiated) penicillin. Post-operative antimicrobial use was associated with participants without specific surgical postgraduate training. This study highlights an overuse of antimicrobials in perioperative procedures in small animal surgery in Spain. Therefore, evidence-based guidelines and further education regarding the correct use of antimicrobial prophylaxis are recommended.
Quantitative Evaluation of the Infrazygomatic Crest Thickness in Polish Subjects: A Cone-Beam Computed Tomography Study
Authors: Gibas-Stanek Marta , Ślusarska Julia , Urzędowski Michał , Żabicki Szczepan , Pihut Małgorzata
Published: July 2023

Infrazygomatic crest (IZC) mini-implants are frequently used as an absolute anchorage when intrusive or distally directed forces are required during orthodontic treatment. The aim of the present study was to evaluate the thickness of the IZC area in Polish patients as well as to assess dependency between bone availability, sex, and age. The study material was 100 cone beam computed tomography scans (CBCT) of the maxilla of patients of the University Dental Clinic in Krakow (50 men and women each). IZC bone thickness was measured at nine different points. The biggest bone thickness was recorded in the interdental space between the first and second molar at the height of 12 mm (6.03 ± 2.64 mm). The thinnest bone depth was localized at the level of the mesial root of the first molar, 16 mm above the occlusal plane (2.42 ± 2.16). There was a significant and negative correlation between bone thickness and age in the case of measurements taken buccally to the first molar. Only two out of nine measurements showed a sex dependency (points I2 and I3). Considering vertical and sagittal dimensions, the most favorable conditions for IZC mini-implant placement were found interdentally, between the first and second molar, 12 mm above the occlusal plane.
Using FRAM for Causal Analysis of Marine Risks in the Motor Vessel Milano Bridge Accident: Identifying Potential Solutions
Authors: Yu Yongung , Ahn Young-joong , Lee Chang-hee
Published: July 2023

The levels of informatization, automation, and intelligence are continuously improving; however, the risks associated with the increased design and operational complexity of ship systems are increasing. Large-scale ship accidents can occur for several reasons. Existing accident analysis methods that examine marine accidents from the perspective of causal one-to-one correspondence have limitations in systematically analyzing complex marine risks during cause identification for the prevention of similar accidents. This study focuses on a systematic causality analysis of the factors related to human error in marine accidents that may occur during the arrival and departure of mega container ships. In particular, a representative case of the Motor Vessel (MV) Milano Bridge crane contact accident at Busan New Port is considered. To explore the complex organizational–technical, human–technical, and organizational–human relationships relevant to this case, human factors (seafarer, pilot, etc.) that are closely related to the linked causes were analyzed using the functional resonance analysis method. This study aims to reduce human error and prevent marine accidents, including pilotage.
Utilizing Stereography to Compare Cultural Heritage in the Past and Now: An Interactive AR Application
Authors: Bolognesi Cecilia Maria , Sorrenti Daniele , Bassorizzi Deida
Published: July 2023

Due to the astonishing speed in technological progress for new heterogeneous experiences, the Mixed Reality continuum represents nowadays an invaluable tool for cultural heritage applications, and the possibility of seemingly natural interaction with virtual elements is paving the way for more immerse, ve and deeply enjoyable experiences, both in dedicated spaces, such as museums and exhibitions, and in public spaces via the latest mobile AR technologies. This paper illustrates the complete workflow followed for the design and implementation of an Augmented Reality application on a holographic table, along with critical latency-quality tradeoffs encountered when combining both high-fidelity surveys and latency-sensibility devices and experiences. A workaround is provided in order to mitigate the impact of low-importance models on the overall latency utilizing a software toolchain employing Google Maps/Earth web applications; each software comprises the toolchain Free and Open-Source Software (FOSS) for a more adaptive workaround with a wider range of suitable applications. The application is then tested with the students of LaborA, which is the modeling laboratory of “Politecnico di Milano”.
Estimation of Time-Series Forest Leaf Area Index (LAI) Based on Sentinel-2 and MODIS
Authors: Yang Zhu , Huang Xuanrui , Qing Yunxian , Li Hongqian , Hong Libin , Lu Wei
Published: July 2023

The LAI is a key parameter used to describe the exchange of material and energy between soil, vegetation and the atmosphere. It has become an important driving datum in the study of carbon and water cycle mechanism models at many regional scales. In order to obtain high temporal resolution and high spatial resolution LAI products, this study proposed a method to combine the high temporal resolution of MODIS LAI products with the high spatial resolution of Sentinel-2 data. The method first used the LACC algorithm to smooth the LAI time-series data and extracted the normalized growth curve of the MODIS LAI of forest and used this curve to simulate the annual variation of the LAI. Secondly, it estimated the LAI at the period of full leaf spread based on the traditional remote sensing statistical model and Sentinel-2 remote sensing data as the maximum value of the forest LAI in the study area and used it to control the LAI growth curve. Finally, the time-series LAI data set was created by multiplying the maximum LAI by the normalized forest LAI growth curve. The results indicate that: (1) the remote sensing statistical estimation model of LAI was developed using the atmospherically resistant vegetation index ARVI (R2 = 0.494); (2) the MODIS LAI normalized growth curve keeps a good level of agreement with the actual variation. This study provides a simple and efficient method for obtaining effective time-series forest LAI data for the scope of small- and medium-sized areas.
Event-Triggered Robust Fusion Estimation for Multi-Sensor Time-Delay Systems with Packet Drops
Authors: Du Xiaolei , Liu Huabo , Yu Haisheng
Published: July 2023

This paper investigates the robust fusion estimation problem for multi-sensor systems with communication constraints, parameter uncertainty, d-step state delays, and deterministic control inputs. The multi-sensor system consists of a fusion center and some sensor nodes with computational capabilities, between which there are random packet drops. The state augmentation method is utilized to transform a time-delay system into a non-time-delay one. The robust state estimation algorithm is derived based on the sensitivity penalty for each sensor node to reduce the impact of modelling errors, and modelling errors here are not limited to a unique form, which implies that the fusion estimator applies to a wide range of situations. An event-triggered transmission strategy has been adopted to effectively alleviate the communication burden from the sensor node to the fusion center. Moreover, the fusion estimator handles packet drops arising from unreliable channels, and the corresponding pseudo-cross-covariance matrix is provided. Some conditions are given to ensure that the estimation error of the robust fusion estimator is uniformly bounded. Two sets of numerical simulations are provided to illustrate the effectiveness of the derived fusion estimator.
Extreme Wave Loading on a Vertical Circular Cylinder
Authors: Liu Shi , Guo Xinran , Yang Yi , Lu Yatao , Chen Lifen
Published: July 2023

Extreme wave loading on a marine structure, consisting of a quasi-static and a dynamically slamming component, often drives the design of such a structure. Their accurate predictions remain challenging tasks. This paper examines the slamming contribution to the force–time histories from a series of experiments in which the crest of a wave is forced to hit a truncated cylinder suspended from above. A range of inundation levels, representing the breaker heights, are considered. The work also provides insights into nonlinear load characteristics on a vertical truncated cylinder. A simple analytical model based on the Newtonian momentum analysis is extended to describe the scaling of the horizontal peak force with the inundation level, i.e., the relationship between the wave slamming loads and the breaker height. More specially, it is found that the peak horizontal impact force is proportional to the inundation level and the square of the linear wave amplitude. In addition, the horizontal and the vertical impact forces on a truncated cylinder are found to increase with the increasing inundation level, while the effect from the wave steepness is relatively small. Furthermore, the higher-order wave components driving nonlinear (quasi-static) loading on a structure are separated by applying a phase-based separation method assuming a Stokes-like approximation. The separation method is found to work well even for long shallow-water waves that have strong nonlinearities. The results suggested that the relative contribution from the fundamental linear wave and higher-order wave components decreases and increases with the increasing nonlinearity of long waves, respectively, characterized by the Ursell number. Finally, this increase in the higher-order wave components is found to be saturated at large Ursell numbers.
Cumulative Impact of Wind Farm Noise
Authors: Josimović Boško , Bezbradica Ljubiša , Manić Božidar , Srnić Danijela , Srebrić Nikola
Published: July 2023

Although wind farms have an undeniable beneficial impact on the environment, certain negative environmental implications do appear as a consequence of their operation. One of them is the production of noise. The wind farm noise values decrease with distance, so that at a certain point they are within the legally prescribed limits. This is the case for individual wind farms noise impact assessments. However, with two or more wind farms in the same area, there is a superposition of noise and a consequential change in the noise value. The focus of the paper is on the results of modeling noise propagation in space in the case of the cumulative impact of two neighboring wind farms. The results are modeled during the process of strategically assessing the environment so as to determine territorial impacts and make informed decisions about future development. The paper presents the strategic answer to the model of the spatial propagation of noise in cases of cumulative impact with a view to including the preventive protection principle in the planning of several adjacent wind farms.
Interval Uncertainty Optimization Method for Electromagnetic Orbital Launcher
Authors: Jin Liang , Liu Lu , Song Juheng , Yan Yingang , Zhang Xinchen
Published: July 2023

The performance optimization and reliability of electromagnetic orbital launchers need to take into account the uncertainties that exist in the manufacturing and service processes. Considering that it is difficult to identify the problem of the parameter probability distribution in advance for electromagnetic orbital launchers, this paper uses the interval number to describe the uncertain variables and realizes the conversion of uncertainty optimization into deterministic optimization problems based on interval sequential relations; moreover, it establishes interval uncertainty optimization methods. The converted deterministic optimization problem is solved by combining a high-precision proxy model with an optimization algorithm to search for the optimal solution set. Finally, reliability estimation is achieved by taking the armature of the electromagnetic orbital launcher as the optimization object. The computational example proves that the method is able to deal with the optimization problem of the parameter interval of an electromagnetic orbital launcher containing uncertain parameters and has good engineering applicability.
Research on Improved GRU-Based Stock Price Prediction Method
Authors: Chen Chi , Xue Lei , Xing Wanqi
Published: July 2023

The prediction of stock prices holds significant implications for researchers and investors evaluating stock value and risk. In recent years, researchers have increasingly replaced traditional machine learning methods with deep learning approaches in this domain. However, the application of deep learning in forecasting stock prices is confronted with the challenge of overfitting. To address the issue of overfitting and enhance predictive accuracy, this study proposes a stock prediction model based on a gated recurrent unit (GRU) with reconstructed datasets. This model integrates data from other stocks within the same industry, thereby enriching the extracted features and mitigating the risk of overfitting. Additionally, an auxiliary module is employed to augment the volume of data through dataset reconstruction, thereby enhancing the model’s training comprehensiveness and generalization capabilities. Experimental results demonstrate a substantial improvement in prediction accuracy across various industries.
Exploring the Benefits and Limitations of Digital Twin Technology in Building Energy
Authors: Tahmasebinia Faham , Lin Lin , Wu Shuo , Kang Yifan , Sepasgozar Samad
Published: July 2023

Buildings consume a significant amount of energy throughout their lifecycle; Thus, sustainable energy management is crucial for all buildings, and controlling energy consumption has become increasingly important for achieving sustainable construction. Digital twin (DT) technology, which lies at the core of Industry 4.0, has gained widespread adoption in various fields, including building energy analysis. With the ability to monitor, optimize, and predict building energy consumption in real time. DT technology has enabled sustainable building energy management and cost reduction. This paper provides a comprehensive review of the development and application of DT technology in building energy. Specifically, it discusses the background of building information modeling (BIM) and DT technology and their application in energy optimization in buildings. Additionally, this article reviews the application of DT technology in building energy management, indoor environmental monitoring, and building energy efficiency evaluation. It also examines the benefits and challenges of implementing DT technology in building energy analysis and highlights recent case studies. Furthermore, this review emphasizes emerging trends and opportunities for future research, including integrating machine learning techniques with DT technology. The use of DT technology in the energy sector is gaining momentum as efforts to optimize energy efficiency and reduce carbon emissions continue. The advancement of building energy analysis and machine learning technologies is expected to enhance prediction accuracy, optimize energy efficiency, and improve management processes. These advancements have become the focal point of current literature and have the potential to facilitate the transition to clean energy, ultimately achieving sustainable development goals.
Debris Management in Turkey Provinces Affected by the 6 February 2023 Earthquakes: Challenges during Recovery and Potential Health and Environmental Risks
Authors: Mavroulis Spyridon , Mavrouli Maria , Vassilakis Emmanuel , Argyropoulos Ioannis , Carydis Panayotis , Lekkas Efthymis
Published: July 2023

On 6 February 2023, southeastern Turkey was struck by two major earthquakes that devastated 11 provinces. Tens of thousands of buildings collapsed and more were later demolished. During post-event field surveys conducted by the authors, several disposal sites set up in the most affected provinces were detected and checked for suitability. Based on field observations on the properties of sites and their surrounding areas as well as on the implemented debris management activities, it is concluded that all sites had characteristics that did not allow them to be classified as safe for earthquake debris management. This inadequacy is mainly attributed to their proximity to areas, where thousands of people reside. As regards the environmental impact, these sites were operating within or close to surface water bodies. This situation reveals a rush for rapid recovery resulting in serious errors in the preparation and implementation of disaster management plans. In this context, measures for effective debris management are proposed based on the existing scientific knowledge and operational experience. This paper aims to highlight challenges during earthquakes debris management and related threats posed to public health and the environment in order to be avoided in future destructive events.
Imaging Characteristics of Disturbance Flow Field Surrounding a Hypersonic Target
Authors: Chang Ning , Guo Shiping , Zhang Chunmin , Wang Yanqiang , Tang Feng
Published: July 2023

The disturbance flow field arises naturally with hypersonic target flying in near space. In situations where traditional infrared and radar systems lose effectiveness, space-based optical detection of this surrounding flow can serve as an alternative method for detecting high-speed targets. This paper presents a remote sensing imaging analysis of the disturbance flow field surrounding a hypersnoic target at different flight altitudes and Mach numbers. Utilizing Fourier Optics and Background-Oriented Schlieren, in conjunction with the fourth-order Runge-Kutta ray tracing algorithm, the imaging blurring and imaging deviation of three typical backgrounds under the influence of the disturbance flow field are obtained. Additionally, the study analyzes the influence of flight conditions and parameters of the imaging system on the imaging characteristics, and provides optical design recommendations. The results indicate that the presence of disturbance flow fields leads to varying degrees of visually apparent blurring effects and indiscernible deviation effects on the background images. Furthermore, the profiles of the disturbance flow field are extracted, in agreement with current experimental research. This study verifies the feasibility of space-based optical detection of hypersonic targets through disturbance flow field remote sensing imaging and contributes to the advancement of imaging research in this field.
Weed Detection in Wheat Crops Using Image Analysis and Artificial Intelligence (AI)
Authors: Haq Syed Ijaz Ul , Tahir Muhammad Naveed , Lan Yubin
Published: July 2023

In the present study, we used device visualization in tandem with deep learning to detect weeds in the wheat crop system in actual time. We selected the PMAS Arid Agriculture University research farm and wheat crop fields in diverse weather environments to collect the weed images. Some 6000 images were collected for the study. Throughout the season, tfhe databank was assembled to detect the weeds. For this study, we used two different frameworks, TensorFlow and PyTorch, to apply deep learning algorithms. PyTorch’s implementation of deep learning algorithms performed comparatively better than that of TensorFlow. We concluded that the neural network implemented through the PyTorch framework achieves a superior outcome in speed and accuracy compared to other networks, such as YOLO variants. This work implemented deep learning models for weed detection using different frameworks. While working on real-time detection models, it is very important to consider the inference time and detection accuracy. Therefore, we have compared the results in terms of execution time and prediction accuracy. In particular, the accuracy of weed removal from wheat crops was judged to be 0.89 and 0.91, respectively, with inference times of 9.43 ms and 12.38 ms on the NVIDIA RTX2070 GPU for each picture (640 × 640).
Experimental Study on Strength and Dry–Wet Cycle Characteristics of South China Coastal Soft Soil Solidified by Cement Collaborating Sand Particles
Authors: Liang Shihua , Wang Yuxin , Feng Deluan
Published: July 2023

To study the influence of sand particles on the strength and dry–wet cycle characteristics of cement-solidified South China coastal soft clay, a series of cement-solidified South China coastal soft clay samples with different contents and sizes of sand particles were prepared, and unconfined compression strength (UCS) tests, dry–wet cycle tests under seawater and freshwater conditions, scanning electron microscopy tests, and X-ray diffraction tests were carried out. The test results show that the UCS of cement–sand-solidified soil (CS-SS) samples at 7, 14 and 28 d increase as sand particle content increases, and their 28 d strength increase as sand particle size decreases; the average mass loss rate of sand–cement samples ranges from 14% to 61%. The properties of strength and dry–wet cycle durability improve as the sand particle content increases and the sand particle size decreases. Moreover, the anti-dry–wet cycle ability of samples under freshwater conditions is better than those under seawater conditions. The scanning electron microscopy (SEM), X-ray diffraction (XRD), and ion chromatography test results show that the stiffness replacement effect (the high stiffness of sand particles replaces the low stiffness of soft clay), the interface cementation effect between the sand particles and cemented soil, and the microcrack expansion-obstructing effects of sand particles contribute to the improvement of the strength and dry–wet cycle durability of cement–sand solidified South China coastal soft clay.
Simulation of Wave Propagation Using Finite Differences in Oil Exploration
Authors: Suárez-Carreño Franyelit , Rosales-Romero Luis , Salazar José , Acosta-Vargas Patricia , Mendoza-Cedeño Henry-Fabricio , Verde-Luján Hernán Edwin , Flor-Unda Omar
Published: July 2023

This paper presents a numerical solution for the 2D acoustic wave equation, considering heterogeneous media. It has been developed through a software in Fortran 90 that uses a second-order finite difference approximation. This program generates a set of patterns to detect the presence of oil in the subsurface. The algorithm is based on a geological domain where the sources (shots) and receivers are located. Each process takes care of a subset of sources and returns to the primary method patterns and seismograms corresponding to its group of sources. In the end, an image of the resulting seismogram is shown along the analyzed geologic profile. Stability and convergence tests were performed to ensure the reliability of the results. These tests were performed using a geological profile 100,000 m long and 17,400 m deep, divided into strata. For the execution of the software, a cluster of 16 processors was used as a computational platform.
On Entropy Estimation of Inverse Weibull Distribution under Improved Adaptive Progressively Type-II Censoring with Applications
Authors: Alam Farouq Mohammad A. , Nassar Mazen
Published: July 2023

This article utilizes improved adaptive progressively Type-II censored data to estimate the entropy of the inverse Weibull distribution. Rényi, q, and Shannon entropy measurements are used to define entropy to achieve this objective. Both point and interval estimations of the entropy quantities are investigated through the maximum likelihood and maximum product of spacing methods. Two parametric bootstrap confidence intervals based on the two estimation techniques are also considered for the various entropy measures. A Monte Carlo simulation study is conducted to investigate how estimates behave at various sample sizes and different censoring schemes based on some statistical measurements. The simulations demonstrate that, as anticipated, when the sample size grows, the estimation accuracy also grows. Furthermore, they show that the estimated entropy measures get closer to the actual entropy values when the censoring level decreases. For purposes of explanation, two applications to actual datasets are taken into consideration. The results verified that the adaptive or improved adaptive progressive censoring schemes give more information about data than the conventional progressive censoring scheme in terms of minimum entropy measures.
Qualitative Shotgun Proteomics Strategy for Protein Expression Profiling of Fish Otoliths
Authors: Rideout Rick M. , Youssef Trevena N. , Adamack Aaron T. , John Rince , Cohen Alejandro M. , Fridgen Travis D. , Banoub Joseph H.
Published: July 2023

Despite decades of research on fish otoliths and their capacity to serve as biochronological recorders, much remains unknown about their protein composition, the mechanisms by which proteins are incorporated into the otolith matrix, or the potential for using otolith proteins to provide insight into aspects of fish life history. We examined the protein composition of Atlantic cod (Gadus morhua) otoliths using a state-of-the-art shotgun proteomics approach with liquid chromatography coupled to an electrospray ionization-orbitrap tandem mass spectrometer. In addition to previously known otolith matrix proteins, we discovered over 2000 proteins not previously identified in cod otoliths and more than 1500 proteins not previously identified in any fish otoliths. These included three novel proteins (Somatolactin, F-actin-capping protein subunit beta, Annexin) primarily involved in binding calcium ions and likely mediating crystal nucleation. However, most of the otolith proteins were not necessarily related to otolith formation but rather to other aspects of fish physiology. For example, we identified sex-related biomarkers for males (SPATA6 protein) and females (Vitellogenin-2-like protein). We highlight some noteworthy classes of proteins having diverse functions; however, the primary goal here is not to discuss each protein separately. The number and diverse roles of the proteins discovered in the otoliths suggest that proteomics could reveal critical life history information from archived otolith collections that could be invaluable for understanding aspects of fish biology and population ecology. This proof-of-concept methodology paper provides a novel methodology whereby otolith proteomics can be further explored.
Manganese-Induced Parkinsonism: Evidence from Epidemiological and Experimental Studies
Authors: Lucchini Roberto , Tieu Kim
Published: July 2023

Manganese (Mn) exposure has evolved from acute, high-level exposure causing manganism to low, chronic lifetime exposure. In this latter scenario, the target areas extend beyond the globus pallidus (as seen with manganism) to the entire basal ganglia, including the substantia nigra pars compacta. This change of exposure paradigm has prompted numerous epidemiological investigations of the occurrence of Parkinson’s disease (PD), or parkinsonism, due to the long-term impact of Mn. In parallel, experimental research has focused on the underlying pathogenic mechanisms of Mn and its interactions with genetic susceptibility. In this review, we provide evidence from both types of studies, with the aim to link the epidemiological data with the potential mechanistic interpretation.
Radiomics and Machine Learning in Brain Tumors and Their Habitat: A Systematic Review
Authors: Tabassum Mehnaz , Suman Abdulla Al , Suero Molina Eric , Pan Elizabeth , Di Ieva Antonio , Liu Sidong
Published: July 2023

Radiomics is a rapidly evolving field that involves extracting and analysing quantitative features from medical images, such as computed tomography or magnetic resonance images. Radiomics has shown promise in brain tumor diagnosis and patient-prognosis prediction by providing more detailed and objective information about tumors’ features than can be obtained from the visual inspection of the images alone. Radiomics data can be analyzed to determine their correlation with a tumor’s genetic status and grade, as well as in the assessment of its recurrence vs. therapeutic response, among other features. In consideration of the multi-parametric and high-dimensional space of features extracted by radiomics, machine learning can further improve tumor diagnosis, treatment response, and patients’ prognoses. There is a growing recognition that tumors and their microenvironments (habitats) mutually influence each other—tumor cells can alter the microenvironment to increase their growth and survival. At the same time, habitats can also influence the behavior of tumor cells. In this systematic review, we investigate the current limitations and future developments in radiomics and machine learning in analysing brain tumors and their habitats.
Effect of a Multi-Ingredient Coriolus-versicolor-Based Vaginal Gel in Women with HPV–Dependent Cervical Lesions: The Papilobs Real-Life Prospective Study
Authors: Cortés Bordoy Javier , de Santiago García Javier , Agenjo González Marta , Dexeus Carter Damián , Fiol Ruiz Gabriel , García Ferreiro Carmen , González Rodríguez Silvia P. , Gurrea Soteras Marta , Martínez Lamela Ester , Palacios Gil-Antuñano Santiago , Romo de los Reyes José María , Sanjuán Cárdenas María del Pilar , Serrano Cogollor Luis , del Villar Vázquez Ana E.
Published: July 2023

Human papillomavirus (HPV) is responsible for virtually all cervical cancers in women. HPV infection and persistency may lead to different-grade squamous intraepithelial lesions that can result in high-grade lesions and cancer. The objective was to prospectively evaluate the results of using a Coriolus-versicolor-based vaginal gel (Papilocare®) on HPV-dependent low-grade cervical lesion repair in a real-life scenario. HPV-positive women ≥ 25 years with ASCUS/LSIL cervical cytology results and concordant colposcopy images were included, receiving the vaginal gel one cannula/day for 21 days (first month) + one cannula/alternate days (five months). A 6-month second treatment cycle was prescribed when needed. Repair of the cervical low-grade lesions through cytology and colposcopy, HPV clearance, and level of satisfaction, and tolerability were evaluated. In total, 192 and 201 patients accounted for the total and safety analyses, respectively, and 77.1% repaired cervical lesions at 6 or 12 months (76.0% for high-risk HPV). Additionally, 71.6% achieved HPV clearance throughout the study’s duration (70.6% for high-risk HPV). Satisfaction level was rated 7.9 and 7.5 out of 10 at 6 and 12 months, respectively. Only three mild–moderate product-related adverse events were reported, and all of them were resolved by the end of the study. In our study, we observed higher regression rates of low-grade cervical lesions in women treated with Papilocare® vaginal gel than spontaneous regression rates reported in the literature.
Mixed-Method Systematic Review and Meta-Analysis of Shared Decision-Making Tools for Cancer Screening
Authors: Herrera Deborah Jael , van de Veerdonk Wessel , Berhe Neamin M. , Talboom Sarah , van Loo Marlon , Alejos Andrea Ruiz , Ferrari Allegra , Van Hal Guido
Published: July 2023

This review aimed to synthesize evidence on the effectiveness of shared decision-making (SDM) tools for cancer screening and explored the preferences of vulnerable people and clinicians regarding the specific characteristics of the SDM tools. A mixed-method convergent segregated approach was employed, which involved an independent synthesis of quantitative and qualitative data. Articles were systematically selected and screened, resulting in the inclusion and critical appraisal of 55 studies. Results from the meta-analysis revealed that SDM tools were more effective for improving knowledge, reducing decisional conflict, and increasing screening intentions among vulnerable populations compared to non-vulnerable populations. Subgroup analyses showed minimal heterogeneity for decisional conflict outcomes measured over a six-month period. Insights from the qualitative findings revealed the complexities of clinicians’ and vulnerable populations’ preferences for an SDM tool in cancer screening. Vulnerable populations highly preferred SDM tools with relevant information, culturally tailored content, and appropriate communication strategies. Clinicians, on the other hand, highly preferred tools that can be easily integrated into their medical systems for efficient use and can effectively guide their practice for cancer screening while considering patients’ values. Considering the complexities of patients’ and clinicians’ preferences in SDM tool characteristics, fostering collaboration between patients and clinicians during the creation of an SDM tool for cancer screening is essential. This collaboration may ensure effective communication about the specific tool characteristics that best support the needs and preferences of both parties.
Preoperative Radiotherapy with a Simultaneous Integrated Boost Compared to Chemoradiotherapy for cT3-4 Rectal Cancer: Long-Term Results of a Multicenter Randomized Study
Authors: Engels Benedikt , De Paoli Antonino , Delmastro Elena , Munoz Fernando , Vagge Stefano , Norkus Darius , Everaert Hendrik , Tabaro Gianna , Gariboldi Elisabetta , Ricardi Umberto , Borsatti Eugenio , Gabriele Pietro , Innocente Roberto , Palazzari Elisa , Dubaere Emilie , Mahé Marc-André , Van Laere Sven , Gevaert Thierry , De Ridder Mark
Published: July 2023

Background: Preoperative chemoradiotherapy (CRT) is the standard treatment for T3-4 rectal cancer. Here, we compared image-guided and intensity-modulated RT (IG-IMRT) with a simultaneous integrated boost (SIB) (instead of concomitant chemotherapy) versus CRT in a multi-centric randomized trial. Methods: cT3-4 rectal cancer patients were randomly assigned to receive preoperative IG-IMRT 46 Gy/23 fractions plus capecitabine 825 mg/m² twice daily (CRT arm) or IG-IMRT 46 Gy/23 fractions with an SIB to the rectal tumor up to a total dose of 55.2 Gy (RTSIB arm). Results: A total of 174 patients were randomly assigned between April 2010 and May 2014. Grade 3 acute toxicities were 6% and 4% in the CRT and RTSIB arms, respectively. The mean fractional change in SUVmax at 5 weeks after completion of preoperative RT were −55.8% (±24.0%) and −52.9% (±21.6%) for patients in the CRT arm and RTSIB arm, respectively (p = 0.43). The pathologic complete response rate was 24% with CRT compared to 14% with RTSIB. There were no differences in 5-year overall survival (OS), progression-free survival (PFS) or local control (LC). Conclusions: The preoperative RTSIB approach was not inferior to CRT in terms of metabolic response, toxicity, OS, PFS and LC, and could be considered an available option for patients unfit for fluorouracil-based CRT.
Predictors of Long-Term Survival of Thoracoscopic Lobectomy for Stage IA Non-Small Cell Lung Cancer: A Large Retrospective Cohort Study
Authors: Gabryel Piotr , Skrzypczak Piotr , Campisi Alessio , Kasprzyk Mariusz , Roszak Magdalena , Piwkowski Cezary
Published: July 2023

The standard of care for patients with early-stage non-small cell lung cancer (NSCLC) is anatomical lung resection with lymphadenectomy. This multicenter, retrospective, cohort study aimed to identify predictors of 5-year survival in patients after thoracoscopic lobectomy for stage IA NSCLC. The study included 1249 patients who underwent thoracoscopic lobectomy for stage IA NSCLC between 17 April 2007, and December 28, 2016. The 5-year survival rate equaled 77.7%. In the multivariate analysis, higher age (OR, 1.025, 95% CI: 1.002 to 1.048; p = 0.032), male sex (OR, 1.410, 95% CI: 1.109 to 1.793; p = 0.005), chronic obstructive pulmonary disease (OR, 1.346, 95% CI: 1.005 to 1.803; p = 0.046), prolonged postoperative air leak (OR, 2.060, 95% CI: 1.424 to 2.980; p < 0.001) and higher pathological stage (OR, 1.271, 95% CI: 1.048 to 1.541; p = 0.015) were related to the increased risk of death within 5 years after surgery. Lobe-specific mediastinal lymph node dissection (OR, 0.725, 95% CI: 0.548 to 0.959; p = 0.024) was related to the decreased risk of death within 5 years after surgery. These findings provide valuable insights for clinical practice and may contribute to improving the quality of treatment of early-stage NSCLC.
Advances in the Early Detection of Hepatobiliary Cancers
Authors: Yıldırım Hasan Çağrı , Kavgaci Gozde , Chalabiyev Elvin , Dizdar Omer
Published: July 2023

Hepatocellular cancer (HCC) and biliary tract cancers (BTCs) have poor survival rates and a low likelihood of a cure, especially in advanced-stage disease. Early diagnosis is crucial and can significantly improve survival rates through curative treatment approaches. Current guidelines recommend abdominal ultrasonography (USG) and alpha-fetoprotein (AFP) monitoring for HCC screening in high-risk groups, and abdominal USG, magnetic resonance imaging (MRI), and magnetic resonance cholangiopancreatography (MRCP) monitoring for biliary tract cancer. However, despite this screening strategy, many high-risk individuals still develop advanced-stage HCC and BTC. Blood-based biomarkers are being developed for use in HCC or BTC high-risk groups. Studies on AFP, AFP-L3, des-gamma-carboxy prothrombin, glypican-3 (GPC3), osteopontin (OPN), midkine (MK), neopterin, squamous cell carcinoma antigen (SCCA), Mac-2-binding protein (M2BP), cyclic guanosine monophosphate (cGMP), and interleukin-6 biomarkers for HCC screening have shown promising results when evaluated individually or in combination. In the case of BTCs, the potential applications of circulating tumor DNA, circulating microRNA, and circulating tumor cells in diagnosis are also promising. These biomarkers have shown potential in detecting BTCs in early stages, which can significantly improve patient outcomes. Additionally, these biomarkers hold promise for monitoring disease progression and evaluating response to therapy in BTC patients. However, further research is necessary to fully understand the clinical utility of these biomarkers in the diagnosis and management of HCC and BTCs.