With the increased emphasis on competition in academic settings, anxiety is becoming more common, which inevitably has some impact on students’ learning process and result. This study aimed to explore how competition-induced anxiety influences the subjective cognitive load (SCL), attention level and test score. Meanwhile, we investigated the mediating role of the behavioral inhibition system/behavioral activation system (BIS/BAS) in those processes. A total of 101 college students were recruited in Study 1 to learn five micro-lectures from massive open online courses (MOOC) under with and without competitive conditions. The results showed that participants’ state anxiety (SA) scores were higher after the experiment, participants in the competition condition had higher test scores, and the relationship between SA/ trait anxiety (TA) and SCL could be mediated by the BIS. To obtain more objective data on learning processes (attention levels), we conducted Study 2, which collected behavioral and EEG data from 42 college students during the online learning. The results showed that the competition group had higher SA, lower attention levels, and worse test scores, and the relationship between SA/TA and attention levels could be mediated through the BIS. The present study not only expands previous research by finding that BIS functioning plays an important role in the effects of anxiety on cognitive load and attention, but also offers implications for using competitive strategies to motivate students according to their aptitude.

In our day-to-day life, Lie detection has a significant concern. We human beings are very much inaccurate while detecting the liars and We believe in what we are told. Lie detection is important in today’s life, because Concealing the information or faking it can sometimes take you to huge problems. In any areas like airport management[2], criminal investigations, counterterrorism, etc this concept has great importance. It is an evergreen challenging and changing topic. This paper presents the common technique which was followed up till now and why it was not considered effective and a review of Robust solutions to detection of deception. People generally do not[3] always believe on what someone says but also try to visualize their facial expressions. While in Robust solution these facial micro-expressions are identified, which are tiny, natural expressions seen on the individual’s face, when they try to conceal or suppress emotions. In addition, the article also provides the year-wise assessment and analysis of research articles published in the area of Lie detection from 2011 to 2022. In the end, our proposed framework for lie detection system is also presented. This paper cover up current issues as well as challenges that could be helpful to resolve in future research works. The review paper closes up by supporting future directions.

Background: Electrical Impedance Tomography (EIT), combined with variable ventilation strate-gies and Artificial Intelligence (AI), is poised to revolutionize critical care by transitioning from reactive to predictive approaches. This integration aims to enhance patient outcomes through personalized interventions and real-time monitoring. Methods: This narrative review explores the principles and applications of EIT, variable ventilation, and AI in critical care. EIT’s impedance sensing creates dynamic images of internal physiology, aiding in the management of conditions like Acute Respiratory Distress Syndrome (ARDS). Variable ventilation mimics natural breathing variability to improve lung function and minimize ventilator-induced lung injury. AI enhances EIT through advanced image reconstruction techniques, neural networks, and digital twin technology, offering more accurate diagnostics and tailored therapeutic interventions. Conclu-sions: The confluence of EIT, variable ventilation, and AI represents a significant advancement in critical care, enabling a predictive, personalized approach. EIT provides real-time insights into lung function, guiding precise ventilation adjustments and therapeutic interventions. AI inte-gration enhances EIT's diagnostic capabilities, facilitating the development of personalized treatment plans. This synergy fosters interdisciplinary collaborations and sets the stage for in-novative research, ultimately improving patient outcomes and advancing the future of critical care.

Radio loud active galactic nuclei are composed of different spatial features, each one characterized by different spectral properties in the radio band. Among them, blazars are the most common class of sources detected at gamma-rays by \fermi, and their radio emission is dominated by the flat spectrum compact core. In this contribution, we explore the connection between emission at high energy revealed by \fermi\ and at radio frequency. Taking as a reference the strong and very highly significant correlation found between gamma rays and cm-$\lambda$ radio emission, we explore different behaviours found as we change the energy range in gamma rays and in radio, therefore changing the physical parameters of the zones involved in the radiation emission. We find that the correlation weakens when we consider (1) gamma rays of energy above 10 GeV (except for high synchrotron peaked blazars) or (2) low frequency radio data taken by the Murchison Widefield Array; on the other hand, the correlation strengthens when we consider mm-$\lambda$ data taken by ALMA.

The flipped classroom is gaining prominence as an active learning pedagogy to engage a new generation of students. However, all courses do not lend themselves to a fully flipped design and instructors are often reluctant to flip lectures. In this study, I experimented with a “partial” flipped classroom design in a first-year undergraduate economics course. In this partial flipped format, traditional lectures were substituted with micro-lectures and the remaining class time was devoted to activities like quizzes, group work and student presentations. The full lectures were panopto recorded and put up on the e-learning site, Blackboard. This format enabled me to combine the benefits of a traditional lecture with a flipped classroom design. In order to evaluate the effectiveness of the partial flipped classroom format, I compared the final exam scores of students in the partial flipped classroom with those in the control group, which followed a traditional lecture-based approach. The key results from the analysis revealed that students in the partial flipped classroom performed better in the final exams vis-à-vis students in the traditional classroom format. Furthermore, the partial flipped classroom format was associated with lower odds of students failing in the module. This format also resulted in better student engagement, more flexibility and enhanced student-tutor interaction within the classroom.

This manuscript presents a study on the spatial relationships between bike accidents, the built environment, land use, and transportation network characteristics in Budapest, Hungary using Geographic Weighted Regression (GWR). The sample period included bike crash data between 2017 and 2022. The findings provide insights into the spatial distribution of bike crashes and their severity, which can be useful for designing targeted interventions to improve bike safety in Budapest and be useful for policymakers and city planners in developing effective strategies to reduce the severity of bike crashes in urban areas. The study reveals that the built environment features, such as traffic signals, road crossings, and bus stops, are positively correlated with the bike crashes index, particularly in the inner areas of the city. However, traffic signals have a negative correlation with the bike crash index in the suburbs, where they may contribute to making roads safer for cyclists. The study also shows that commercial activity and PT stops have a higher impact on bike crashes in the northern and western districts. The GWR analysis further suggests that one-way roads and higher speed limits are associated with more severe bike crashes, while green and recreational areas are generally safer for cyclists. Future research should be focused on the traffic volume and bikes trips’ effects on the severity index.

Titanium micro-scale topography results in excellent osteoconductivity and bone-implant integration. However, the biological effects of sub-micron topography are unknown. We compared osteoblastic phenotypes and in vivo bone and implant integration abilities between titanium surfaces with micro- (1–5 µm) and sub-micro-scale (0.1–0.5 µm) topographies and machined titanium. Average roughness was 12.5 ± 0.65 nm, 123 ± 6.15 nm, and 24 ± 1.2 nm for machined, micro-rough, and sub-micro-rough surfaces, respectively. The micro-rough surface showed the fewest cells attaching during the initial stage and the lowest proliferation. Calcium deposition and expression of osteoblastic genes were highest on the sub-micro-rough surface and lowest on the machined surface. Bone-to-implant integration was strongest for the micro-rough surface, consistent with it having the greatest ability to retain cells in vitro. Thus, the biological effects of titanium surfaces are not necessarily proportional to the degree of roughness in osteoblastic cultures or in vivo. Sub-micro-rough titanium ameliorates the disadvantage of micro-rough titanium by restoring cell attachment and proliferation and enhances the rate of osteoblastic differentiation over that of micro-rough titanium; however, bone integration and the ability to retain cells are compromised due to its lower interfacial mechanical locking compared to that of micro-rough titanium.

Neutron beams are an essential tool to investigate material structure and perform non-destructive analysis, as they give unique access to element composition, thus ideally complementing density analysis allowed by standard X-rays investigation. Laser-driven neutron sources, though compact and cost-effective, currently have lower average flux than conventional neutron sources, due to the limited repetition rate of the lasers used so far. However, advancements in laser technology allow nowadays to address this challenge. Here we report results obtained at the Advanced Laser Light Source (ALLS) characterizing stable production of broadband (0.1-2 MeV) neutrons produced at a high repetition rate (0.5 Hz). The interaction of laser pulses of 22 fs duration and 3.2 J on-target energy with 2-µm-thick tantalum targets produced protons in the Target Normal Sheath Acceleration (TNSA) regime up to 7.3 MeV. These protons were subsequently converted into neutrons by (p,n) reactions in Lithium fluoride (LiF). Activation measurements and bubble detectors were used to characterize neutron emissions, with a neutron fluence of up to ~ 1.4 × 10⁵ neutrons/shot/sr, and energies mainly between a few hundred of keV and 2 MeV. The total neutron yield was ~ 5 × 10⁵ neutrons/shot. This paves the way for numerous applications, e.g. in homeland security, material science or cultural heritage.

Fragile X syndrome (FXS) is the most frequent monogenic form of autism spectrum disorder (ASD). Autistic FXS is caused by loss of the fmr1 gene product, the fragile X mental retardation protein (FMRP), triggering physiological and behavioral abnormalities. It is correlated with clock components for behavioral circadian rhythm. Mutation of this gene causes the disturbances in sleep patterns and circadian behavior commonly observed in patients with autistic FXS, accompanied by frequent dysregulation of melatonin synthesis and melatonin-dependent signaling. These changes impair vigilance, learning and memory, and are also linked to autistic behavior including the abnormal anxiety response. However, although several possible causes, symptoms, and clinical features of ASD have been investigated, the correlation between an altered circadian rhythm and autistic FXS has not been extensively studied. Recent works have highlighted the impact of melatonin on the nervous, immune, and metabolic systems. Even though utilization of melatonin for sleep disorder in ASD has been considered in clinical research, further studies should be aimed at its neuroprotective role in ASD during developmental period. In this review, we focus on the regulatory circuits involved in melatonin dysregulation and circadian system disruption in those with autistic FXS. Additionally, we discuss the neuroprotective effect of melatonin intervention. This may improve neuroplasticity and physical capability. We also review the underlying molecular mechanisms, and suggest that melatonin may be a useful novel treatment for autistic FXS, countering the adverse effects of circadian variation.

Microplastics and nanoplastics (MP/NPs) have been found everywhere they have been searched. On the top of Everest, in the Mariana Trench, on the clouds e recently, microplastics have been discovered in the human placenta, meconium and babies’ feces. In this review we explain what the consequences of the presence of these pollutants in fetuses and newborns are, with particular attention to human breastfeeding. Finally, we outline the possible political and social solutions to the problem of plastic overproduction that characterizes the modern world.

The present article discusses the institutional model adopted in Brazil regarding energy production through biomass. The theoretical-empirical method is used to conclude that the model's difficulties can be overcome by adopting a network of contracts capable of subjecting renewable energy generation to an energy compensation model.

The Internet of Things (IoT) is a promising technology for sensing and monitoring the environment to reduce disaster impact. Energy is one of the major concerns for IoT devices, as sensors used in IoT devices are battery-operated. Thus, it is important to reduce energy consumption, especially during data transmission in disaster-adverse situations. Clustering-based communication helps reduce a node’s energy decay during data transmission and enhances the network’s lifetime. Many hybrid combination algorithms are proposed for clustering and the routing protocol to improve the network lifetime in disaster scenarios. However, the performance of these protocols is widely varied based on the underlying network configuration and the optimisation parameters considered. In this research, we have used the clustering parameters that are most relevant to disaster scenarios, such as the node’s residual energy, distance to sink, and network coverage. Then, we proposed a bio-inspired hybrid (BAO-PSO) algorithm where the Butterfly Optimisation Algorithm (BOA) is used for clustering and Particle Swarm Optimisation (PSO) is used for the routing protocol. The performance of the proposed algorithm is compared with the benchmark protocols LEACH, DEEC, PSO, PSO-GA, and PSO-HAS. Residual energy, network throughput, and network lifetime are considered performance matrices. The simulation result showed that the proposed algorithm increases network lifetime by 10%-20% by comparison with the benchmark algorithm.

Kisspeptin (KISS1) and its cognate receptor (KISS1R) are implicated in the progression of various cancers. However, a theranostic radiopharmaceutical targeting the KISS1 receptor (KISS1R) has yet to be explored. A gallium-68 labelled kisspeptin-10 (KP10) has potential as a pan-tumor radiopharmaceutical for the detection of cancers. Furthermore, a lutetium-177 labelled KP10 could find therapeutic application in treating oncological diseases. We attached DOTA to the NH2-terminus of KP10 as we posited that this modification would not impair biological activity and showed that receptor stimulation of inositol phosphate accumulation in HEK293 transfected with the KISS1R gene was similar for KP10 and DOTA-KP10. We describe optimization of radiolabeling with gallium-68 and lutetium-177 and stability in serum, plasma, and whole blood. Pharmacokinetics was established with µPET/CT and ex vivo measurements. Dynamic studies with µPET/CT demonstrated that background clearance for the radiopharmaceutical was rapid with a blood half-life of 18 ± 3 minutes. DOTA-KP10 demonstrated preserved functionality at KISS1R and good blood clearance. These promising results advocate the further development of KP10 structures which have high binding affinity along with proteolytic resistance.

Triple X syndrome (TXS, also known as trisomy X or 47,XXX) has been associated with impaired overall neurocognitive functioning in children and relatively young adults. However, neurocognitive functioning in adults with TXS is poorly understood. The aim of this study was, therefore, to examine cognitive functioning in adults with TXS. Methods: In this cross-sectional study, data were collected from 34 adult women with TXS (mean age = 32.9; SD = 13.1) and 31 controls (mean age = 34.9; SD = 13.7). General intellectual functioning, semantic/verbal memory, visual/episodic memory, psychomotor speed, and attention and executive functioning were then compared between these two groups. Results: We found that general intellectual functioning was significantly lower in the TXS group compared to the control group. In addition, women with TXS had more attention problems and lower psychomotor speed, particularly motor processing speed. When the analyses were adjusted for IQ, the strength of these associations decreased. The women in the TXS group also scored significantly lower at free recall in the verbal memory test, but not in immediate or delayed recognition. Finally, visual/episodic memory and executive functioning did not differ significantly between groups. Conclusions: Our analysis revealed that women with TXS score lower in general intellectual functioning and have impairments in motor processing speed and attention compared to controls, but do not differ with respect to executive functioning. These results offer new insights for improving the support of adults with TXS both at school and in the workplace.

In this review paper, we present a pellucid proof of how x tanh(x/µ) approximates |x|and is better than √x² +µ  when we are concernedwith accuracy.

International migrants comprised 14% of the UK population in 2020, but migrant health in the UK has rarely been studied at a population level using primary care electronic health records (EHRs). Given the difficulty of determining migration status using EHRs, this study developed a migration phenotype and assessed its validity. We developed a phenotyping algorithm using codes for country of birth, visa status, non-English main/first language and non-UK origin. It was applied to a Clinical Practice Research Datalink (CPRD) GOLD database of 16,071,111 primary care patients between 1997 and 2018. We compared the completeness and representativeness of the identified migrant population to Office for National Statistics (ONS) country of birth and 2011 census data by year, age, sex, geographic region of birth and ethnicity. Between 1997-2018, 403,768 migrants (2.51% of the CPRD GOLD population) were identified using the phenotype. 178,749 (1.11%) of these migrants were identified by codes indicating foreign country of birth or visa status, 216,731 (1.35%) a non-English main/first language, and 8,288 (0.05%) non-UK origin. The cohort was similarly distributed compared to ONS migration statistics in terms of sex and region of birth. Recording of migration improved from identifying approximately one-tenth of the expected proportion of migrants according to the ONS in 2004 to a quarter in 2018. Younger migrants were better represented than those aged 50 and over. The migration phenotype identified a large number of migrants and can be used to undertake large-scale migration health research in CPRD GOLD to inform healthcare policy, practice and action. While the cohort was representative of the UK migrant population in terms of sex and region of birth, migration status was under-recorded in earlier years and older ages, and future studies for these groups should therefore be interpreted with caution.

Radiation-induced lung injuries (RILI) are a notable complication of thoracic radiotherapy, significantly affecting the quality of life and prognosis for cancer patients. We present the case of a 68-year-old man with metastatic prostate cancer who underwent radiation therapy for a metastatic thoracic vertebral lesion identified with high uptake on a PET-PSMA scan. Four months later, a follow-up PET-PSMA scan indicated that the pathological uptake in the vertebra had resolved, but it also revealed a new lung consolidation with PSMA uptake. This case illustrates a potential pitfall in interpreting PSMA PET-CT findings, as the uptake in the lung lesion was due to RILI rather than malignancy, infection, or another form of pneumonia, highlighting the necessity for careful clinical correlation to avoid misdiagnosis and potentially inappropriate and unnecessary treatment.

Haug and Tatum have recently solved the Hubble tension within a type of R_h = ct cosmology using an intuitive, smart trial-and-error search algorithm. The trial-and-error algorithm demonstrates that one can start with the measured CMB temperature and a rough estimate of H0. Based on the algorithm, one ends up matching the entire distance ladder of the observed supernovas by finding a value for H_0. However, this is a numerical search procedure, even though it can be completed in a fraction of a second on a standard computer. Here, we will demonstrate that the trial-and-error numerical method is not needed and that the Hubble tension can be resolved using the same Haug and Tatum model through a closed- form solution. This means one simply solves an equation to find the correct H0 value. This is possible because an exact mathematical relation between H_0 and the CMB temperature has recently been established, in combination with the linearity in an R_h = ct model.

As an implementation of inverse Radon transform, the Second-order Divided-difference Back Projection (SDBP) technique has been proposed in this paper, by which the accurate CT reconstruction can be theoretically realized. A computational model for CT reconstruction filter expressions has been derived on the basis of SDBP technique. The method reveals the correlation between the convolution kernel for data restoration and the filter expression. By substituting kernel functions into the computational model, the amplitude sequences of a variety of filters can be calculated. On the proposed filter construction method, the decomposition form of filters has been discovered, where a series of basic filters have been acquired. The properties of any filter depend on the decomposed basic filters. Basic filters can be used to compose filters in actual needs.

The recent measurement of a cutoff k_min in the fluctuation power spectrum P(k) of the cosmic microwave background may vitiate the possibility that slow-roll inflation can simultaneously solve the horizon problem and account for the formation of structure via the growth of quantum fluctuations in the inflaton field. Instead, we show that k_min may be interpreted more successfully in the R_h=ct cosmology, as the first mode exiting from the Planck scale into the semi-classical Universe shortly after the Big Bang. In so doing, we demonstrate that such a scenario completely avoids the well-known trans-Planckian problem plaguing standard inflationary cosmology, with some additional clues that may motivate further development of Kaluza-Klein cosmologies, string theories and supergravity.

This article introduces a new MfEIT UDESC Mark I system, which consists of a 32-electrode setup featuring a modified Howland current source, low cost, portable and non radiation. The system is capable of reconstruction of electrical conductivity tomographic images at a rate of 30.624 frames per second and about 5 minutes for imaging. The current source employs 0.5 mA, adjacent current application pattern with frequencies ranging from 10 kHz to 1 MHz. The article outlines the hardware, firmware, and software design specifications, which include the design of the current source, calibration procedures, and image reconstruction process. Tomographic images of conductivity were reconstructed in ex vivo healthy pig lungs and those with pneumonia, as a proof of concept for future applications in live pigs. The high spectral power density, combined with real-time system calibration provides clinical advantages in veterinary medicine. The goal is to identify lung areas affected by Mycoplasma hyopneumoniae in pigs, through the analysis of electrical conductivity difference, offering a valuable tool to assist veterinarians for to obtain images of respiratory diseases. The reconstruction method (GREIT) was evaluated with experimental data and It was compared with the Gauss-Newton and Total Variation methods, where GREIT proved to be superior.

Fractures of the talar neck and body are associated with spine fractures and scoliosis deformity, which affect cosmetic appearance and cause difficulty in ambulation. The implant design for talus surgery is thriving as a functional alternative in case of severe talar destruction, focusing on segmentation and reconstruction of the talus’s shape. However, manual segmentation of the talus is time-consuming and subjective. In this study we exploited the automatic segmentation framework to efficiently train a deep learning-based model to accurately segment the talus based on computed tomography imaging. We developed three model configurations with nnU-Net and investigated their Dice similarity coefficients (DSC) and 95% Hausdorff distances (HD95) for talus segmentation on a CT image dataset. The three configurations performed well (DSC > 0.95, HD95 < 0.6). When tested on the same samples, one of the configurations was more efficient while ensuring higher accuracy. We propose to focus on talus anatomic variations with increasing age based on this framework and apply it to clinical trials at the next stage.

Several studies suggest that COVID-19 may be accompanied by symptoms such as a dry cough, muscle aches, sore throat, and mild to moderate respiratory illness. The symptoms of this disease indicate the fact that COVID-19 causes noticeable negative effects on the lungs. Therefore, considering the health status of the lungs using X-rays and CT scans of the chest can significantly help diagnose COVID-19 infection. Due to the fact that most of the methods that have been proposed to COVID-19 diagnose deal with the lengthy testing time and also might give more false positive and false negative results, this paper aims to review and implement artificial intelligence (AI) image-based diagnosis methods in order to detect coronavirus infection with zero or near to zero false positives and false negatives rates. Besides the already existing AI image-based medical diagnosis method for the other well-known disease, this study aims on finding the most accurate COVID-19 detection method among AI methods such as machine learning (ML) and artificial neural network (ANN), ensemble learning (EL) methods.

Limited availability of expensive alloying elements elevates low-alloyed steels to a unique position in the field of lightweight construction and mass production. Quenching and partitioning (Q&P) heat treatments of low-alloyed steels with exceptional property combinations are particularly promising. In this study, we characterize for the first time a new low-alloyed steel to be processed by Q&P heat treatments. In combined experimental and numerical studies, we design a novel approach that effectively combines the short cycle times of press hardening with the excellent property profiles of Q&P-treated steels. We identify appropriate transformation parameters for Q&P heat treatments by dilatometric studies and we adjust a number of reference conditions with different isothermal holding times. By means of SEM analysis and XRD measurements, we show that different fractions of retained austenite result in different mechanical properties. Initial numerical designs of the process can identify varying temperature profiles and cooling rates depending on the position in the die. The results show that the geometry of the part plays a minor role, but the die temperature is the dominant factor for successful partitioning directly in the press hardening process.

Sulphuric acid is a widely used raw material in the chemical industry. Its corrosive effect on materials varies considerably, depending on impurities, temperature and water content. Accordingly, good corrosion resistance under all conditions is very difficult to achieve. This is especially an issue for micro process apparatus with very thin walls. Furthermore, such devices are often joint by diffusion bonding what may alter materials properties due to high temperatures and long dwell times. In fact, for each new material, the diffusion bonding parameters must be optimized and the impact on mechanical as well as corrosion properties must be investigated. In this paper, two high molybdenum alloys, namely Hastelloy B3 and BC-1, were evaluated. Diffusion bonding tests were performed using ten layers of sheet material in between round stock. Corrosion tests were performed in 70 % sulphuric acid at 100°C for 1000 h. Tensile tests on both alloys were carried out for different material conditions, to determine the change in mechanical strength and elongation at fracture values. In general, independent of the condition of the materials, the fracture behavior of both alloys was found to be ductile and the specimens show the typical dimple structure, in the case of diffusion bonded samples, interrupted by weak spots or rather non-bonded areas. These areas are obviously causing the onset of material failure and thus, a degradation of mechanical properties. Tensile samples, that were aged in 70% sulphuric acid at 100°C for 1000 hours showed local corrosion attacks at the grain boundaries at the circumferential surfaces and especially at the joining planes – for Hastelloy B3 much more pronounced than for Hastelloy BC-1. Accordingly, a further decrease of both, the stress- and elongation at fracture values is observed. However, the typical material parameters like 0.2 % yield strength used for dimensioning components are found to be sufficient high, even when operating the materials under such harsh conditions. When concluding the results, at least Hastelloy BC-1 reveals both sufficient good mechanical properties and an excellent corrosion resistance, regardless of the heat treatment, and could be considered for manufacturing micro-process engineering apparatuses operated in a sulphuric acid environment. This is a significant advance compared to the results obtained within a AiF project, previously carried out on four different materials to investigate the corrosion resistance in sulphuric acid.

The aim of the study was to compare the standard baseline imaging, with extended radiological staging. To assess our hypothesis, we performed a prospective, single-centre study which included 132 participants recruited between October 2015 and March 2020. Descriptive statistics, the Friedman and chi-squared tests were performed and p &lt; 0.05 was considered significant. Patients were grouped into two cohorts, CT scan cohort (n=87) and PET-CT cohort (n=43). In the first group the originally determined disease stage changed in 36.8 % of cases, in second group in 51.2 %. The consistency between assessment of axillary lymph nodes by imaging (cN) and the postoperative pathology report (pN) was evaluated. In most cases, clinical and pathological evaluation of involved nodes was consistent, for CT scan the result was χ2(1) = 18.98; p &lt; 0.001, for PET-CT the result was χ2(1) = 6.41; p = 0.03. Highly customized radiation therapy defined as dose boost within the involved lymph nodes, not covered by surgeon, was applied in nine patients.

Spectral photon counting cone-beam CT imaging is challenged by individual pixel response behaviour, which leads to noisy projection images and subsequent image artefacts like rings. Existing methods to correct for this either use calibration measurements, like signal-to-thickness calibration (STC), or perform post-processing ring artefact correction of sinogram data or scan reconstructions, without taking the pixel response explicitly into account. Here we present a novel post-processing method (DAC-shifting), which explicitly measures the current pixel response using flat field images, and subsequently corrects the projection data. The DAC-shifting method was evaluated with a repeat series of spectral photon counting imaging (Medipix3) of a phantom with different density inserts, and in iodine K-edge imaging. The method was also compared against PMMA based STC. The DAC-shifting method was shown to be effective in correcting individual pixel response, and was robust against detector instability. On the contrary, STC correction showed varying results, which was almost as good as DAC-shifting when data was acquired just after STC calibration, but worse with larger time differences. In K-edge imaging, DAC-shifting provides a sharper attenuation peak, and more uniform CT values, which is expected to benefit iodine concentration quantification.

During the recent pandemics of COVID-19, sequencing technics became powerful tool for gaining information about the SARS-CoV-2 virus and using this knowledge in our advantage. Thanks to this advantage, scientists over the world were able to search for emerging variations, watching the virus evolving in real time. Assembly of the virus genomes is crucial part of getting this kind of useful information. In our study, we sequenced 79 samples from nasopharyngeal swabs of COVID-19 patients. Positivity on disease was evaluated by qRT-PCR. By studying assembly success rate, we noticed, that Ct-value of qRT-PCR can predict success of genome assembly and SARS-CoV-2 lineage assignment. In this work we described the relationship between Ct-value and further steps of genome construction and its assignment to specific viral strain.

Accurate retroperitoneal lymph node metastasis (LNM) prediction in early-stage testicular germ cell tumours (TGCT) harbours the potential to significantly reduce over- or undertreatment and treatment-related morbidity in this group of young patients as an important survivorship imperative. We investigated the role of computed tomography (CT) radiomics models integrating clinical predictors for the individualized prediction of LNM in early-stage TGCT. Ninety-one patients with surgically proven testicular germ cell tumours and contrast-enhanced CT were included in this retrospective study. Dedicated radiomics software was used to segment 273 retroperitoneal lymph nodes and extract features. After feature selection, radiomics-based machine learning models were developed to predict LN metastasis. The robustness of the procedure was controlled by 10-fold cross-validation. Using multivariable logistic regression modelling, we developed three prediction models: A radiomics-only model, a clinical-only model and a combined radiomics-clinical model. The models' performance was evaluated using the area under the receiver operating characteristic curve (AUC). Finally, decision curve analysis was performed to estimate the clinical usefulness of the predictive model. The radiomics-only model for predicting lymph node metastasis reached a greater discrimination power than the clinical-only model, with an AUC of 0.84 (± 0.17; 95% CI ) vs 0.60 (± 0.22; 95% CI) in our study cohort. The combined model integrating clinical risk factors and selected radiomics features outperformed the clinical-only and the radiomics-only prediction models and showed good discrimination with an area under the curve of 0.94 ( ± 0.10; 95% CI). The decision curve analysis demonstrated the clinical usefulness of our proposed combined model. The presented combined CT-based radiomics-clinical model represents an exciting non-invasive prediction tool for individualized prediction of LN metastasis in testicular germ cell tumours. Multi-centre validation is required to generate high-quality evidence for its clinical application.

The authors present a stereotypical case presentation of x-linked hypophosphatemia (XLH) and provide a review of the pathophysiology and related pharmacology of this condition, primarily focusing on the FDA-approved medication burosumab. XLH is a renal phosphate wasting disorder caused by loss of function mutations in the PHEX gene (phosphate-regulating gene with homologies to endopeptidases on the X chromosome). Typical biochemical findings include elevated serum levels of bioactive/intact Fibroblast Growth Factor 23 (FGF23) which lead to i) low serum phosphate levels, ii) increased fractional excretion of phosphorus, and iii) inappropriately low or normal 1,25-dihydroxyvitamin D (1,25-vitD). XLH is the most common form of heritable rickets and short stature in XLH patients is due to chronic hypophosphatemia. Additionally, XLH patients experience joint pain and osteoarthritis from skeletal deformities, fractures, enthesopathy, spinal stenosis, and hearing loss. Historically, treatment for XLH was limited to oral phosphate supplementation, active vitamin D supplementation, and surgical intervention for cases of severe bowed legs. In 2018, the United States Food and Drug Administration’s (FDA) approved burosumab for the treatment of XLH and this medication has demonstrated substantial benefit compared with conventional therapy. Burosumab binds circulating intact FGF23 and blocks its biological effects in target tissues, resulting in increased serum inorganic phosphate (Pi) concentrations and increased conversion of inactive vitamin D to active 1,25-vitD.

A typical vibrational spectrum in the ice phase has four separate bands: translation, libration, bending and stretching. Ice X, the final ice phase under high pressure, shows an exotic vibrational spectrum. Theoretically, an ideal crystal of ice X only has one peak at 998 cm-1 for Raman scattering and two peaks at 450 cm-1 and 1507 cm-1 for infrared absorption in this work. These three characteristic peaks are indicators of the phase transition between ice VII/VIII and ice X. Despite much experimental and theoretical work on ice X, only this study has clearly indicated these characteristic peaks in the region of the IR band. The phonon density of states shows quite different features than ice VIII, which could be verified by inelastic neutron scattering in the future. The dynamic processes of 15 vibrational normal modes are discussed and the typical hydrogen bonds are missing.

Extramammary Paget disease (EMPD) is an uncommon adenocarcinoma of apocrine gland-rich areas, presenting significant diagnostic challenges due to its nonspecific clinical appearance and frequent misidentification as benign, inflammatory skin conditions. Traditional diagnostic methods such as biopsy are invasive and uncomfortable, often required repeatedly due to high recurrence rates. Dermoscopy and non-invasive imaging techniques have been used but provide limited diagnostic accuracy due to their constraints in depth penetration and resolution. Recent advancements in imaging technologies, such as line-field confocal optical coherence tomography (LC-OCT), show promise in enhancing diagnostic precision while minimizing invasive procedures. LC-OCT merges high-resolution imaging with deep penetration capabilities, capturing detailed horizontal and vertical skin images akin to histopathology. This study evaluated the diagnostic performance of LC-OCT in detecting EMPD and its recurrence in 17 clinically suspicious anogenital regions, belonging to 6 patients. Data were collected prospectively at patient bedside by an LC-OCT expert with poor training for EMPD; and, then, reviewed retrospectively by an independent LC-OCT expert with adequate training for EMPD and no concerns about time. The prospective examination yielded 64.7%-accuracy, 71.4%-sensitivity, and 33.3%-specificity. The retrospective analysis achieved 94.1%-accuracy, 100%-sensitivity, and 66.7%-specificity, with the only false positive case being a difficult-to-diagnose concomitant presentation of a lichen sclerosus et atrophicus. Despite the need for specialized training, our results suggest that LC-OCT represents a valuable tool for accurately identifying EMPD and improve its management by reducing unnecessary biopsies. Further studies are needed to standardize its clinical application.

Coronary angiography, long considered the gold standard for coronary imaging, faces limitations in assessing coronary vessel wall anatomy and guiding percutaneous coronary intervention (PCI). Despite its prevalence, studies have demonstrated that it is suboptimal in estimating the severity of coronary disease and physiologic significance of stenosis. Intracoronary imaging techniques, such as intravascular ultrasound (IVUS) and optical coherence tomography (OCT), offer promising alternatives to overcome these limitations. This review delves into the nuances of IVUS and OCT, highlighting their strengths and limitations as adjuncts to PCI. IVUS, utilizing ultrasound technology, and OCT, based on near-infrared light, each provide unique insights into coronary pathology. They differ in terms of temporal and spatial resolution, influencing their capabilities in plaque characterization and vessel assessment. The discussion navigates their historical evolution, technical specifications, and clinical utility. Meta-analyses and adjusted observational studies suggest that both IVUS and OCT-guided PCI correlate with reduced cardiovascular risks compared to angiographic guidance alone. While IVUS has demonstrated consistent benefits in terms of clinical outcomes, the evidence supporting OCT is less robust. However, the utilization of these imaging modalities remains variable across regions, with increasing adoption in recent years, particularly in IVUS-guided PCIs. Intravascular ultrasound's journey from early motion detection to current high-resolution mechanical systems is traced, including improvements in catheter size and compatibility. On the other hand, optical coherence tomography has advanced significantly, utilizing near infrared light to achieve unparalleled resolutions, albeit requiring temporary blood clearance for optimal imaging. In conclusion, IVUS and OCT offer valuable insights into coronary pathophysiology and guide interventions with improved precision compared to traditional angiography. While IVUS remains more extensively utilized, OCT's growing potential is underscored by advancements in technology, culminating in enhanced imaging capabilities. Both modalities demonstrate comparable clinical outcomes, emphasizing the need for tailored imaging choices based on individual clinical scenarios. The continued refinement and broader integration of intravascular imaging are expected to play a pivotal role in optimizing coronary interventions and patient outcomes.

Wide bandgap semiconductors-based photocatalysts are usually limited by their low solar energy conversion efficiency due to their limited absorption solar wavelength, surface’s fast recombination of photoelectron–hole pairs and low charge-carrier mobility. Here we report a new stepwise solution synthesis for making a new photocatalytic core/shell of titanate nanowire/reduced graphene oxide shell (or titanate/rGO) 1D-nanocomposite. The new core/shell nanocomposite maximized the specific surface area, largely reduced the charge transfer resistance and reaction energy barrier, and significantly improved the absorption of the visible light. The core/shell nanocomposites’ large on/off current ratio and rapid photo-responses boosted the photocurrent by 30.0%, the photocatalysis rate by 50.0%, and the specific surface area by 16.4%, when comparing with the pure titanate nanowire core. Our numerical simulations support the effective charge separation on the new core-shell nanostructure, which can help further advance the new photocatalysis.

A novel physiologically based algorithm (PBA) for the computation of fractional flow reserve (FFR) in coronary artery trees (CATs) using computational fluid dynamics (CFD) is proposed and developed. The PBA is based on the extension of Murray's law and additional inlet conditions prescribed iteratively, and is implemented in OpenFOAM for testing and validation. 3D models of CATs are created using CT scans and computational meshes, and the results are compared to in-vasive coronary angiographic (ICA) data to validate the accuracy and effectiveness of the PBA. The discrepancy between calculated and experimental FFR is within 2.33-5.26% in steady-state and transient simulations, respectively, when convergence is reached. The PBA is a reliable and physiologically sound technique compared to the current lumped parameter model (LPM), which is based on empirical scaling correlations and requires nonlinear iterative computing for conver-gence. The accuracy of the PBA method is further confirmed using the FDA nozzle, which demonstrates good alignment with CFD-validated values.

Viruses frequently contain overlapping genes, which encode functionally unrelated proteins from the same DNA or RNA region but in different reading frames. Yet overlapping genes are often overlooked during genome annotation, in particular in DNA viruses. Here we looked for the presence of overlapping genes likely to encode a functional protein in human parvovirus B19 (genus erythroparvovirus), using an experimentally validated software, Synplot2. Synplot2 detected an open reading frame, X, conserved in all erythroparvoviruses, which overlaps the VP1 capsid gene, and is under highly significant selection pressure. In a related virus, human parvovirus (genus tetraparvovirus), Synplot2 also detected an open reading frame under highly significant selection pressure, ARF1, which overlaps the VP1 gene. X and ARF1 have exactly the same location (both overlap the region of VP1 encoding the phospholipase A2 domain), and encode proteins with similar predicted properties, such as a transmembrane region, strongly suggesting that they are homologous. These findings provide compelling evidence that the X protein must be expressed and functional. It is probably translated either from a polycistronic mRNA by a non-canonical mechanism, or from an unmapped monocistronic mRNA. Finally, we also discovered proteins predicted to be expressed from a frame overlapping VP1 in other species related to parvovirus B19: porcine parvovirus 2 (Z protein) and bovine parvovirus 3 (X-like protein).

For over a century, viruses have left a long trail of evidence implicating them as frequent suspects in the development of type 1 diabetes. Through vigorous interrogation of viral infections in individuals with islet autoimmunity and type 1 diabetes using serological and molecular virus detection methods, and mechanistic studies of virus infected human pancreatic β-cells, the prime suspects have been narrowed down to predominantly human enteroviruses. Here we provide a comprehensive overview of evidence supporting the hypothesised role of enteroviruses in the development of islet autoimmunity and type 1 diabetes. We also discuss concerns over the historical focus and investigation bias toward enteroviruses, and summarise current unbiased efforts aimed at characterising the complete population of viruses (the “virome”) contributing early in life to the development of islet autoimmunity and type 1 diabetes. Finally, we review the range of vaccine and antiviral drug candidates currently being evaluated in clinical trials for the prevention and potential treatment of type 1 diabetes.

The aim of this research is to investigate the influence of model height employed in the deep drawing of orthodontic aligner sheets on force transmission and aligner thickness. Forty sheets (Zendura FLX) were thermoformed over four models of varying heights (15, 20, 25, and 30 mm). Normal contact force generated on the facial surface of the upper right central incisor (Tooth 11) was measured using pressure-sensitive films. Aligner thickness around Tooth 11 was measured at five points. A digital caliper and a micro-computed tomography (µ-CT) were employed for thickness measurements. The normal contact force exhibited an uneven distribution across the facial surface of Tooth 11. Model 15 displayed the highest force (88.9±23.2 N), while Model 30 exhibited the lowest (45.7±15.8 N). The force distribution was more favorable for bodily movement with Model 15. Thickness measurements, conducted using a digital caliper and µ-CT, revealed substantial thinning of the aligner after thermoforming. This thinning was most pronounced at the incisal edge (50% of the original thickness) and least at the gingivo-facial part (85%). Additionally, there was a progressive reduction in aligner thickness with increasing model height, which was most significant on the facial tooth surfaces. We conclude that the thermoplastic aligner sheets undergo substantial thinning during the thermoforming process, which becomes more pronounced as the height of the model increases. As a result, there is a decrease in both overall and localized force transmission, which could lead to increased tipping by the aligner and a diminished ability to achieve bodily movement.

In this communication the concept of functional materials is understood such as real modified substrates for nanomedicine applications. Functional and modified substrates focused on microcapsules and devices for new nanomedicine diagnosis and treatments. Cases of different materials are shown to support the functionality strategy, as in particular chemicals, pharmacophores, and controlled nano-chemistry for the design of nanoplatforms. Recent studies have reported hybrid inorganic/organic compositions for biocompatible, biodegradable, and support materials added to particular physical properties such as conductive, semiconductive, and high electromagnetic fields from the near field within the nanoscale to far-field applications and new nano-pharmacophores and nanomedicine therapeutics. New approaches are shown from the nano-scale to the micro- and higher sizes of substrates for improved therapeutic strategies. Micro-capsules for biosensing and drug delivery applications were developed. In addition, we report recent and novel research centered on implantable, portable, and wearable devices applied to future treatments.

The current work investigates the auxetic tensile deformation behavior of the inversehoneycomb structure with 5 × 5 cells made of biodegradable poly(butylene adipate-coterephthalate) (PBAT). Fused deposition modeling, an additive manufacturing method, produced such specimens. Residual stress (RS) and warpage, more or less, always exist in such specimens due to layer-by-layer fabrication, i.e., repeated heating and cooling. The RS influences the auxetic deformation behavior, but its measurement is challenging due to the very fine structure. Instead, the finite-element(FE)-based process simulation realized by an ABAQUS plug-in numerically predicts the RS and warpage. The predicted warpage shows a negligible slight deviation compared to the design topology. This process simulation also delivers the temperature evolution of a small volume material, revealing the local cyclic heating and cooling. The achieved RS serves as the initial condition for the FE model used to investigate the auxetic tensile behavior. With the outcomes from FE calculation without considering RS at hand, the effect of the RS on the deformation behavior is discussed for the global force-displacement curve, the structural Poisson’s ratio evolution, the deformed structural status, the stress distribution, and evolution, where the first three and the warpage are also compared with experimental results. Furthermore, the FE simulation can easily provide the global stress-strain flow curve with the total stress calculated from the elemental ones.

A novel drive current model covering the effects of source/drain voltage (VDS) and gate voltage (VGS) and incorporating drift and diffusion current on the surface channel at the nano-node level, especially beyond 28nm node is presented. The effect of the diffusion current added is more satisfactory to describe the behavior of the drive current in nano-node MOSFETs, fabricated with the atomic-layer-deposition (ALD) technology. This breakthrough in model establishment can expose the long and short channel devices together. Introducing the variables of VDS and VGS, the mixed current model more effectively and meaningfully demonstrates the drive current of MOSFETs under the operation of horizontal, vertical, or mixed electrical field. In comparison between the simulation and experimental consequences, the electrical performance is impressive. The error between both is less than 1%, better than the empirical adjustment to issue a set of drive current models.

The difficulty in detecting tumors in earlier stages is the major cause of mortalities of patients, despite the advancements in treatment and research regarding ovarian cancer. Deep Learning algorithms are applied to serve the purpose of a diagnostic tool by applying them on CT scan images of the ovarian region. The images go through a series of pre-processing techniques and further the tumor is segmented using the UNet model. Instances are then classified into two categories – benign and malignant tumors. Classification is performed using Deep Learning models like CNN, ResNet, DenseNet, Inception-ResNet, VGG16 and Xception along with Machine Learning models such as Random Forest, Gradient Boosting, AdaBoosting, XGBoosting. DenseNet 121 emerges as the best model on this dataset even after applying optimization on the Machine Learning models by obtaining an accuracy of 95.7%. The current work demonstrates the comparison of multiple CNN architectures among themselves and with common Machine Learning algorithms, with and without optimization techniques applied.

The increased complexity of modern systems is calling for an integrated and comprehensive approach to system design and development and in particular, a shift towards Model-Based Systems Engineering (MBSE) approaches for system design. The requirements that serve as the foundation for these intricate systems are still primarily expressed in Natural Language (NL), which can contain ambiguities and inconsistencies that hinder their direct translation into models. The colossal developments in the field of Natural Language Processing (NLP) in general and Large Language Models (LLMs) in particular can serve as an enabler for the conversion of NL requirements into semi-machine-readable requirements. This is expected to facilitate their standardization and use in a model-based environment. This paper discusses a two-fold strategy for converting NL requirements into semi-machine-readable requirements using language models. The first approach involves creating a requirements table by extracting information from free-form NL requirements. The second approach is an agile methodology that facilitates the identification of boilerplate templates for different types of requirements based on observed linguistic patterns. For this study, three different LLMs were utilized. Two of these models were fine-tuned versions of Bidirectional Encoder Representations from Transformers (BERT), specifically aeroBERT-NER and aeroBERT-Classifier, which were trained on annotated aerospace corpora. Another LLM, called flair/chunk-english, was utilized to identify sentence chunks present in NL requirements. All three language models were utilized together to achieve the standardization of requirements. To demonstrate the effectiveness of the methodologies, requirements from Parts 23 and 25 of Title 14 Code of Federal Regulations (CFRs) were employed, and a total of two, five, and three boilerplate templates were identified for design, functional, and performance requirements, respectively.

Defectively manufactured and deliberately damaged composite laminates fabricated with different continuous reinforcing fibres (respectively, carbon and glass) and polymer matrices (respectively, thermoset and thermoplastic) were inspected in magnetic resonance imaging equipment. Two pulse sequences were evaluated during non-destructive examination conducted in saline solution-immersed samples to simulate load-bearing orthopaedic implants permanently in contact with biofluids. The orientation, positioning, shape, and especially the size of translaminar and delamination fractures were determined according to stringent structural assessment criteria. The spatial distribution, shape, and contours of water-filled voids were sufficiently delineated to infer the amount of absorbed water if thinner image slices than this study were used. The surface texture of composite specimens featuring roughness, waviness, indentation, crushing, and scratches was outlined, with fortuitous artefacts not impairing the image quality and interpretation. Low electromagnetic shielding glass fibres delivered the highest, while electrically conductive carbon fibres produced the poorest quality images, particularly when blended with thermoplastic polymer, though reliable image interpretation was still attainable.

Individual plant cells are the building blocks for all plantae and artificially constructed plant biomaterials, like biocomposites. Secondary cell walls (SCWs) are a key component for mediating mechanical strength and stiffness in both living vascular plants and biocomposite materials. In this paper, we study the structure and biomechanics of cultured plant cells during the cellular developmental stages associated with SCW formation. We use a model culture system that induces transdifferentiation of Arabidopsis thaliana cells to xylem vessel elements, upon treatment with dexamethasone (DEX). We group the transdifferentiation process into three distinct stages, based on morphological observations of the cell walls. The first stage includes cells with only a primary cell wall (PCW), the second covers cells that have formed a SCW, and the third stage includes cells with a ruptured tonoplast and partially or fully degraded PCW. We adopt a multi-scale approach to study the mechanical properties of cells in these three stages. We perform large-scale indentations with a micro-compression system and nanoscale indentations through atomic force microscopy (AFM), in three different osmotic conditions. We introduce a spring-based model to deconvolve the competing stiffness contributions from turgor pressure, PCW, SCW and cytoplasm in the stiffness of differentiating cells. Prior to triggering differentiation, cells in hypotonic pressure conditions are significantly stiffer than cells in isotonic or hypertonic conditions, highlighting the dominant role of turgor pressure. Plasmolyzed cells with a SCW reach similar levels of stiffness as cells with maximum turgor pressure. The stiffness of the PCW in all of these conditions is lower than the stiffness of the fully-formed SCW. Our results provide the first experimental characterization of the mechanics of SCW formation at single cell level.

In the paper, the effect of voltage increasing (from 500 VDC up to 650 VDC) on the structure and chemical composition of porous coating on titanium made by Plasma Electrolytic Oxidation, is presented. In the present paper, phosphates based coatings enriched with calcium, magnesium, zinc and copper in electrolyte based on 1 L of 85% concentrated H3PO4 with additions of Ca(NO3)2·4H2O, and Mg(NO3)2∙6H2O, and Zn(NO3)2∙6H2O, and Cu(NO3)2∙3H2O, are described. The morphology, chemical and phase composition, are evaluated using SEM, EDS, XRD, XPS, GDOES. Based on all the analyses, it was found out that the PEO coatings are porous and enriched with calcium, magnesium, zinc and copper. They consist mainly of the amorphous phase, which is more visible for higher voltages, and it is correlated with the increasing of the total PEO coating thickness (the higher the voltage, the thicker the PEO coating). However, for 650 VDC an amorphous phase and titanium substrate was also recorded with a signal from Ti2P2O7 crystalline, that was not observed for lower voltages. It was also found out that all the obtained coatings may be divided in three sub-layers, i.e. porous, semiporous, and transition one.

Recent research has highlighted associations between sleep and microbial taxa and pathways. However, the causal effect of these associations remains unknown. To investigate this, we performed a two-sample bidirectional Mendelian randomization (MR) analysis using summary statistics of genome-wide association studies (GWAS) from 412 gut microbiome traits (N = 7,738) and GWAS studies from seven sleep-associated traits (N = 345,552 to 386577). We employed multiple MR methods to assess causality, with Inverse Variance Weighted (IVW) as the primary method. We further applied Cochran’s Q statistical analysis, MR-Egger intercept, and MR-PRESSO for heterogeneity and pleiotropy assessment, alongside a Bonferroni correction ((P

CBCT significantly impacts dental procedures and has brought significant reforms in our approach to diagnosis & treatment planning despite its limitations in differentiating soft tissues. It is an excellent imaging modality and quickly identifies sinus opacification and provides valuable in-sight into paranasal sinus pathologies with considerably lower radiation exposure. The present study aimed to investigate the occurrence of maxillary sinus abnormalities in CBCT scans, identify the frequency, type, and location of these findings, and find the correlation between the distance of periapical lesions and radiographic changes in the maxillary sinus. Two examiners independently evaluated 117 patients to diagnose and classify the cases into different abnormality subtypes. The periapical lesions most closely related to the sinus were recorded. The diameters of the left and right maxillary sinus ostium and the distance of the ostium's lower border to the sinus's osseous floor were recorded. The findings were correlated with the age and gender of these patients. The present study revealed that sixty-one patients were diagnosed with mucosal thickening (52.1%). The sinus wall most affected by mucosal thickening was the maxillary sinus floor, followed by the medial and lateral walls. Of 19 patients with periapical lesions, 15 had maxillary sinus mucosal thickening and was statistically significant (p=0.004). The high occurrence of abnormalities in the maxillary sinus emphasizes the importance for the radiologist to comprehensively interpret the whole volume acquired in CBCT images, including the entire sinus. Incidental findings may be considered in the individual clinical context of signs and symptoms, reducing the risk of overes-timating the real impact of radiographic findings.

Based upon Maxwell's equations, it has long been established that oscillating electromagnetic (EM) fields incident upon a metal surface decay exponentially inside the conductor, leading to a virtual EM vacuum at sufficient depths. Magnetic resonance imaging (MRI) utilizes radiofrequency (r.f.) EM fields to produce images. Here we present the first visualization of a virtual EM vacuum inside a bulk metal strip by MRI, amongst several novel findings. We uncover unexpected MRI intensity patterns arising from two orthogonal pairs of faces of a metal strip, and derive formulae for their intensity ratios, revealing differing effective elemental volumes (voxels) underneath these faces. Further, we furnish chemical shift imaging (CSI) results that discriminate different faces (surfaces) of a metal block according to their distinct nuclear magnetic resonance (NMR) chemical shifts, which holds much promise for monitoring surface chemical reactions noninvasively. Bulk metals are ubiquitous, and MRI is a premier noninvasive diagnostic tool. Combining the two, the emerging field of bulk metal MRI can be expected to grow in importance. The fundamental nature of results presented here may impact bulk metal MRI and CSI across many fields.

Micro-nano-plastics (MNPs) are an important constituent of atmospheric aerosol. However, there is still no standard procedure for their sampling and size fractionation, which is an obstacle to the aggregation and critical analysis of results obtained by different research groups. This review focuses on the sampling and fractionation methodologies used for MNPs. Moreover, a straightforward optimized methodology for the sampling and fractionation is proposed.

Poverty exists through the world as a curse and a big trouble in the way of development. When people deprived of their basic needs such as food, cloth, shelter, education, treatment and so on is termed as poverty .This paper is to examine empirically the impact of micro-credit on poverty alleviation in Bangladesh. The regular growth of the micro finance concerned parties has been promoted not only by market forces but also by conscious actions of national governments,Non-Governmental Organizations (NGOs) and the donors who view microfinance as an effective tool for eradicating poverty. This paper argues that microfinance can be considered as an important element for an effective poverty reduction strategy especially in rural areas. This study is developed by descriptive analysis based on secondary data. After the analysis of collected data and information, it shows evidence that practically microcredit can be considered as an effective tool for poverty reduction in developing countries like Bangladesh. To be more ensure that how much and how the microcredit really reduces poverty, further study and research should be carried out in future.

Because Newton's gravitation and Einstein's general theory of relativity are macroscopic gravitational theories, lack of explanations for gravitation at the microscopic level. Therefore, this paper attempts to establish a set of micro-gravity theory, which is to explain the origin of Newtonian gravity and Einstein's general theory of relativity from the micro level. Based on the knowledge of Newton's gravitation and Einstein's general theory of relativity, the gravitational field is interpreted as a gradient field of space-time density; the Newtonian potential is interpreted as the density of an object at the micro level; gravity is interpreted as the potential pressure(space-time pressure) exhibited by the gradient of the density of the object at the micro level; flection space-time is interpreted as the presentation of the gradient distribution of density at the micro level. Based on the understanding of gravitation at the micro level, motion is interpreted as the embodiment of the change of space-time density. The motion of the object needs space-time density difference (potential difference) to maintain, thus a new equation of motion is obtained. Through this new equation of motion, It can explain the origin of inertia, the orbital motion of the stars, the rotation and the revolution.

Parts of shotgun cartridges are a significant source of plastic litter in the marine environment. Empty cartridge shells may not be picked up by the hunter who fired them, and plastic wads that serve to separate the propellant from the shot load, are lost down-range when a shot is fired. Such litter items constitute a cosmetic and aesthetic problem on coastlines and may cause harm to marine animals and in the later stages of decomposition break down into harmful micro plastic particles. There exists no reliable estimate of the global exposure of marine ecosystems to this plastic source. However, in some countries it has been subject to closer examination, including for example, Denmark where the annual contribution of plastic wads into marine systems was estimated to 600,000 pieces (c2 tonnes), and the accumulated density of washed-up items (both wads and shells) was 3.7 items per 100 m coastline. Increasing awareness of this problem has caused scientists, hunters’ communities and governments to suggest altered practice including transition to the use of biodegradable cartridge components, first and foremost wads as this item is invariable lost during hunting. Several manufacturers provide shotgun cartridges containing biodegradable wads based on different types of materials, including fibers and various types of plastics, for example PVAL (poly(vinyl alcohol)) and PHA (polyhydroxyalkanoate). In this paper, we review the most recent literature on the amounts and related environmental hazards of plastic dispersed from hunting ammunition into marine ecosystems. We summarize the market availability of shotgun cartridges with biodegradable wads and discuss chemical, technical, economical and legal aspects of a transition to the use of such products.

Mexico is a well-known seismically active country, which is primarily affected by several tectonic plate interactions along the southern Pacific coastline and by active structures in the Gulf of Baja California. In this paper we investigate this seismicity in the context of a non-extensive statistical approach based on Tsallis entropy. The analysis is performed using data from the corrected Mexican seismic catalogue provided by the National Seismic Service, spanning a period from January 2000 to October 2023. The Gutenberg-Richter law fitting to the earthquake sub-catalogues for all six regions studied indicates magnitudes of completeness between 3.30 and 3.76. All six regions display values of the entropic index in the range 1.52≲q≲1.61, which are lower than the previously estimated range 1.54≲q≲1.70 using catalogue data from 1988 to 2010. The cause of this discrepancy is certainly due to the use of modern recording devices, which are sensitive enough to detect a larger number of low-magnitude events compared to older instrumentation.

The Hennovation project, an EU H2020 funded thematic network, aimed to explore the potential value of practice-led multi-actor innovation networks within the laying hen industry. The project proposed that husbandry solutions can be practice-led and effectively supported to achieve durable gains in sustainability and animal welfare. It encouraged a move away from the traditional model of science providing solutions for practice, towards a collaborative approach where expertise from science and practice were equally valued. During the 32-month project, the team facilitated 19 multi-actor networks in 5 countries through 6 critical steps in the innovation process: problem identification, generation of ideas, planning, small scale trials, implementation and sharing with others. The networks included farmers, processors, veterinarians, technical advisors, market representatives and scientists. The interaction between the farmers and the other network actors, including scientists, was essential for farmer innovation. New relationships emerged between the scientists and farmers, based on experimental learning and the co-production of knowledge for improving laying hen welfare. The project demonstrated that a practice-led approach can be a major stimulus for innovation with several networks generating novel ideas and testing them in their commercial context. The Hennovation innovation networks not only contributed to bridging the science-practice gap by application of existing scientific solutions in practice but more so by jointly finding new solutions. Successful multi-actor, practice-led innovation networks appeared to depend upon the following key factors: active participation from relevant actors, professional facilitation, moderate resource support and access to relevant expertise. Farmers and processors involved in the project were often very enthusiastic about the approach, committing significant time to the network’s activities. It is suggested that the agricultural research community and funding agencies should place greater value on practice-led multi-actor innovation networks alongside technology and advisor focused initiatives to improve animal welfare and embed best practices.

Miniature sensors are key components for the applications in the Internet of Things (IoT), wireless sensor networks, autonomous vehicles, smart cities and smart manufacturing. As a miniature and self-powered magnetic sensor, Wiegand sensor possesses the advantageous traits including changing-rate-independent output, low cost, and remarkable repeatability and reliability. Typical Wiegand sensor requires hard magnetic pole pieces that provide external fields for triggering voltage outputs that are called Wiegand pulses. However, the wire-shaped sensing element of Wiegand sensor is the critical issue that limits the design, selection, and adoption of the external triggering magnets. Currently, the widely used pole piece materials are rare-earth magnets. However, adopting rare-earth magnets brings strong stray fields, causing electromagnetic interference (EMI) problem. In this study, patterned CoNiP hard magnets were electrodeposited on flexible substrates through microfabrication. Origami magnetization was utilized to control the resultant stray fields, and hence the pole piece of CoNiP magnets can successfully trigger the output of Wiegand pulse. In comparison, the output voltage of the triggered pulse acquired through the patterned CoNiP magnets is comparable to that by using the rare-earth magnets. Furthermore, both the volume (meanwhile the weight) of the Wiegand sensor and the EMI issue can be significantly reduced and mitigated by the CoNiP magnets.

Transcutaneous injection laryngoplasty is a well-known procedure for treating paralyzed vocal fold by injecting augmentation material into it. Hence, vocal fold localization plays a vital role in the preoperative planning as the fold location is required to determine the optimal injection route. In this communication, we propose a mirror environment based reinforcement learning (RL) algorithm for localizing the right and left vocal folds in preoperative neck CT. RL-based methods commonly showed noteworthy outcome in general anatomic landmark localization problem in the recent years. However, such methods suggest training individual agent for localizing each fold, though the right and left vocal folds are located in close proximity and have high feature-similarity. Utilizing the lateral symmetry between the right and left vocal folds, the proposed mirror environment allows for a single agent for localizing both the folds by treating the left fold as a flipped version of the right fold. Thus, localization of both folds can be trained using a single training session which utilizes the inter-fold correlation and avoids redundant feature learning. Experiment with 120 CT volumes showed improved localization performance and training efficiency of the proposed method compared with the standard RL method.

Imaging techniques such as computed tomographies (CT) play a major role in clinical imaging and diagnosis of malignant lesions. In recent years, spectral CT has emerged in the field of computed tomographies, utilizing detailed information from extracted spectral parameters of the specimen. Metal nanoparticle platforms enable effective payload delivery for this technique. Due to the possibility of surface modification, metal nanoparticles are predestined to facilitate molecular tumor targeting. In this work, we demonstrate the feasibility of anti-plasma membrane Heat shock protein 70 functionalized gold nanoparticles (AuNPs) for tumor specific multimodal imaging. Membrane-associated Hsp70 is exclusively presented on the plasma membrane of malignant cells of multiple tumor entities, but not on corresponding normal tissue cells, predestining this target epitope for tumor-selective in vivo targeting. In vitro microscopical analysis revealed the presence of cmHsp70.1-AuNP in the cytosol of tumor cell lines, being internalized via the endosomal-lysosomal pathway. In tumor bearing mice the biodistribution as well as the intratumorally enrichment of AuNP were examined 24h after i.v. application, in vivo. In parallel to spectral CT analysis, histological analysis confirmed the presence of tumor cells. In contrast to control NP, a significant enrichment of cmHsp70.1-AuNPs has been detected selectively in tumors of different preclinical mouse models. Furthermore, the biodistribution of AuNP, following i.v. injection, was analyzed by a machine-learning approach on digitalized slides. In summary, utilizing mHsp70 on tumor cells for guidance of cmHsp70.1 antibody functionalized nanoparticles enables sufficient enrichment and uniform distribution of AuNPs in mHsp70-expressing tumor cells, adequate for various microscopical imaging techniques and spectral-CT-based tumor delineation, in vivo.

Due to their remarkable intrinsic physical properties, carbon nanotubes (CNTs) can enhance mechanical properties and confer electrical and thermal conductivity to polymers currently investigated for use in advanced applications based on thermal management. An epoxy resin filled with varying concentrations of CNTs (up to 3 wt.%) was produced and experimentally characterized. The electrical percolation curve identified two critical filler concentrations: 0.5 wt%, near the electrical percolation threshold, suitable for exploring mechanical and piezoresistive properties, and 3 wt% for investigating thermo-electric properties due to the Joule effect with applied voltages ranging from 70V to 200V. Numerical models were developed using multiphysics simulation software. Once validated with experimental data, these models were used to investigate additional physical properties of the composites. Furthermore, a statistical approach based on the design of experiments (DoE) was employed to examine the influence of certain thermal parameters on the final performance of the materials. The purpose of this research is to promote the use of contemporary statistical and computational techniques alongside experimental methods to enhance understanding of materials science. New materials can be identified through these integrated approaches, or existing ones can be more thoroughly examined.

Coronary optical coherence tomography (OCT) is an intravascular, near-infrared light-based imaging modality capable of reaching axial resolutions of 10-20 µm. This resolution allows for accurate determination of high-risk plaque features, such as thin cap fibroatheroma; however, visualisation of morphological features alone still provides unreliable positive predictive capability for plaque progression or future major adverse cardiovascular events (MACE). Biomechanical simulation could assist in this prediction, but this requires extracting morphological features from intravascular imaging to construct accurate three-dimensional simulations of patients’ arteries. Extracting these features is a laborious process, often carried out manually by trained experts. To address this challenge, numerous techniques have emerged to automate these processes while simultaneously overcoming difficulties associated with OCT imaging, such as its limited penetration depth. This systematic review summarises advances in automated segmentation techniques from the past five years (2016-2021) with a focus on their application to the three-dimensional reconstruction of vessels and their subsequent simulation. We discuss four categories based on the feature being processed, namely: coronary lumen; plaque characteristics and subtypes; artery layers; and stents. Areas for future innovation are also discussed as well as their potential for future translation.

Early detection improves prognosis in pancreatic ductal adenocarcinoma (PDAC) but is challenging as lesions are often small and poorly defined on contrast-enhanced computed tomography scans (CE-CT). Deep learning can facilitate PDAC diagnosis, however current models still fail to identify small (&lt;2cm) lesions. In this study, state-of-the-art deep learning models were used to develop an automatic framework for PDAC detection, focusing on small lesions. Additionally, the impact of integrating surrounding anatomy was investigated. CE-CT scans from a cohort of 119 pathology-proven PDAC patients and a cohort of 123 patients without PDAC were used to train a nnUnet for automatic lesion detection and segmentation (nnUnet_T). Two additional nnUnets were trained to investigate the impact of anatomy integration: (1) segmenting the pancreas and tumor (nnUnet_TP), (2) segmenting the pancreas, tumor, and multiple surrounding anatomical structures (nnUnet_MS). An external, publicly available test set was used to compare the performance of the three networks. The nnUnet_MS achieved the best performance, with an area under the receiver operating characteristic curve of 0.91 for the whole test set and 0.88 for tumors &lt;2cm, showing that state-of-the-art deep learning can detect small PDAC and benefits from anatomy information.

The spatial segregation is a characteristic of Latin American cities, resulting in distinct dynamics of social inclusion and exclusion at both spatial and identity levels. Then, specific green spaces may convert into appreciated and contested territories, where various actors negotiate their uses and regulations. Considering a case-study in a green icon of the metropolitan city of Santiago de Chile, the main objective of the present study was to describe and comprehend the uses and meanings of the Quebrada Macul park among different social groups over the past two decades. We employed qualitative methods including six in-depth interviews with key informants (social and ecological leaders, historical neighbors, and park workers), five participant observations in the park, and statistical analysis of visitors. Results reveal that (1) the transition of being a popularly used hill to a metropolitan park rises tensions between public and private statuses of place; (2) conflicts emerge regarding who uses the space and how, reflecting power dynamics among different social groups; (3) the park, beyond being a public space, holds significant identity value for its historical residents, both for those who fought for its recovery and those who have lived closely, so processes of forgetfulness might be resentful. We conclude on enduring meanings of the park associated with the struggle for the place among different groups, highlighting the role of memory for the social integration of groups among natural spaces.

Differentiated thyroid cancer (DTC), comprising papillary and follicular thyroid carcinoma, is the most common thyroid malignancy and typically has a favourable prognosis when detected early. Positron emission tomography/computed tomography (PET/CT) has emerged as a valuable imaging modality, integrating metabolic and anatomical data. Although PET/CT is not usually part of the initial diagnostic process due to DTC's indolent nature and low metabolic activity, it plays an essential role in selected clinical scenarios. This includes identifying recurrence in patients with elevated thyroglobulin (Tg) levels and negative radioactive iodine (RAI) scans, evaluating metastatic disease, and guiding treatment in advanced cases. As the use of PET/CT evolves in oncology, this review explores its application in the staging, detection of recurrence, follow-up, and future challenges in managing DTC. The review also considers emerging radiotracers and the theragnostic potential of PET/CT.

Pulmonary sarcoidosis is a multisystem granulomatous interstitial lung disease (ILD) with a variable presentation and prognosis. Early accurate detection of pulmonary sarcoidosis may prevent progression to pulmonary fibrosis, a serious and potentially life-threatening form of the disease. However, the lack of a gold-standard diagnostic test and specific radiographic findings pose challenges in diagnosing pulmonary sarcoidosis. Chest computed tomography (CT) imaging is commonly used but requires expert, chest-trained radiologists to differentiate pulmonary sarcoidosis from lung malignancies, infections, and other ILDs. In this work, we developed a multichannel, CT and radiomics-guided ensemble network (RadCT-CNNViT) with visual explainability for pulmonary sarcoidosis vs. lung cancer (LCa) classification using chest CT images. We leverage CT and hand-crafted radiomics features as input channels, and a 3D convolutional neural network (CNN) and vision transformer (ViT) ensemble network for feature extraction and fusion before a classification head. The 3D CNN sub-network captures localized spatial information of lesions, while the ViT sub-network captures long-range, global dependencies between features. Through multichannel input and feature fusion, our model achieved the highest performance with accuracy, sensitivity, specificity, and combined AUC of 0.93±0.04, 0.94±0.04, 0.93±0.08 and 0.97 respectively in a 5-fold cross-validation study with pulmonary sarcoidosis (n=126) and LCa (n=93) cases. The model offers promising potential for improving the diagnosis of pulmonary sarcoidosis. A detailed ablation study showing the impact of CNN+ViT compared to CNN or ViT alone, and CT+radiomics input, compared to CT or radiomics alone, is also presented in this work.

Abstract: The pursuit of youth and attractiveness is a fundamental desire in contemporary society. For many individuals, the appearance of visible signs of aging, such as skin laxity, gravitational changes in facial and neck soft tissues, and loss of harmonious proportions, can be psychologically distressing. The choice of effective methods for addressing these changes depends on their specific characteristics, the patient's anatomical features, and the type of facial aging. The introduction of 3D imaging to determine the hyoid bone level, the volume of soft tissue structures in the cervico-mental area, ptosis of subplatysmal structures, and the volume of submandibular glands, in addition to ultrasound study of the submental projection at the preoperative stage, are key for taking the best decision regarding preoperative planning. This case report aims to illustrate how modern imaging techniques are a fundamental part of the preoperative assessment of the mid and lower third of the face to ensure the most favorable aesthetic outcomes for each patient. Key message: To attain harmonious results in surgical correction of age-related facial and neck changes, it is crucial to consider the patient's anatomical features and the extent of age-related alterations. A comprehensive facial analysis, taking into account the type of facial aging and employing a CT scan and ultrasound examination of the soft tissues in the chin region, facilitates the development of an individualized plan tailored to achieve the patient's desired outcome.

Obtaining a proper position for THA’s components is a crucial aspect for the implant perfor-mance and consequently patient outcomes. Patient specific kinematic seems to be a key factor to reach the optimal implant positioning. The aim of this study was to assess the accuracy and safety of a computed dynamic analysis system which through patient specific guides tries to improve implant positioning and functional orientation according to patient’s spinopelvic mobility and anatomy.A total of 100 consecutive patients were prospectively enrolled. All patients received an OPS dynamic hip preoperative planning. A TC scan protocol follow up analysis has done at 6 month after surgery.The mean deviation from the planned acetabular inclination and anteversion was 4.3° e 3.8° respectively. The 98% of cases was within +/- 10° of Lewinnek safe zone both for inclination and anterversion. The height of osteotomy deviated on the average of 1.6mm. The 100% cases were included within 4mm of osteotomy. Patient specific and laser guided instru-mentation is safe and accurately reproduce the dynamic planning in terms of components orien-tation, osteotomy level, leg length and offset.

Objectives: Prostate cancer is well known to express high levels of somatostatin receptors and preliminary data suggests that PET imaging with the somatostatin analog, 68Ga-DOTATATE, may allow for whole body staging of patients with metastatic castration resistant prostate cancer (mCRPC) and neuroendocrine prostate cancer (NePC). This study explores the utility of 68Ga-DOTATATE PET-CT to identify metastatic deposits in men with mCRPC and NePC and prognosticate disease progression. Methods: 68Ga-DOTATATE PET-CT was performed in 17 patients with mCRPC and of those 2/17 had NePC. Semiquantitative analysis with standardized uptake values (SUV) (e.g. SUVmax, SUVmean) was performed for each metastatic lesion and reference background tissues. 68Ga-DOTATATE uptake in metastatic deposits was further classified as: mild (less than liver), moderate (up to liver average), or marked (greater than liver). Serial prostate-specific antigen measurements and patient survival were followed up to 3 years after PET imaging to assess response to standard of care treatment. Results: All patients had at least one metastic lesion with identifiable 68Ga-DOTATATE uptake. Marked 68Ga-DOTATATE uptake was found in 7/17 patients, including both NePC patients, and all were non-responders to systemic therapy and died within the follow up period, with a mean time to death of 8.1 months. 3 patients had mild 68Ga-DOTATATE uptake, and all were responders to systemic therapy and were alive 36 months after 68Ga-DOTATATE imaging. Conclusions: 68Ga-DOTATATE is able to identify mCRPC and NePC metastatic deposits, and lesions with 68Ga-DOTATATE uptake > liver may portend poor outcomes in patients with mCRPC.

The primary purpose of this article is to study the asymptotic and numerical estimates in detail for higher degree polynomials in $\pi(x)$ having a general expression of the form, \begin{align*} P(\pi(x)) - \frac{e x}{\log x} Q(\pi(x/e)) + R(x) \end{align*} $P$, $Q$ and $R$ are arbitrarily chosen polynomials and $\pi(x)$ denotes the \textit{Prime Counting Function}. The proofs require specific order estimates involving $\pi(x)$ and the \textit{Second Chebyshev Function} $\psi(x)$, as well as the famous \textit{Prime Number Theorem} in addition to certain meromorphic properties of the \textit{Riemann Zeta Function} $\zeta(s)$ and results regarding its non-trivial zeros. A few generalizations of these concepts have also been discussed in detail towards the later stages of the paper, along with citing some important applications.

Alzheimer's disease (AD) is a complex disease involving multiple factors such as amyloid plaque formation, mitochondrial dysfunction, telomere length, and oxidative stress. As the disease began 20 years before the onset of clinical symptoms, treatment of AD after its onset is likely to be too late to have a significant effect. Therefore, prevention from an early stage is important. Twendee X®︎ (TwX, Oxicut®︎) is an antioxidant supplement consisting of eight ingredients. TwX has been proven to prevent dementia in patients with mild cognitive impairment (MCI) in a multicenter, randomized, double-blind, placebo-controlled, prospective intervention trial. To elucidate the mechanisms of TwX on brain and cellular function, TwX was administered in in vitro experiments and in a C57BL/6 old wild-type, and spontaneous hyperglycemia model with accelerated cognitive decline, and its effects on diabetes, brain autophagy, neurogenesis, and telomere length were evaluated in comparison with those of the non-treated groups. TwX protected mitochondria from oxidative stress with higher antioxidant capacity than a single antioxidant. TwX not only lowered blood glucose levels, but also suppressed reduction of brain neurogenesis and loss of autophagy. Telomeres in aged mice were significantly longer than those in non-TwX-treated mice. Development of dementia is based on many factors of brain function. TwX was suggested to prevent dementia not only by its antioxidant effects, but also by its effects on diabetes, brain neurogenesis, telomere deficiency, and energy production.

Recent studies investigated the detectability of ship wake signatures on SAR imagery using a large number of SAR images collocated with Automatic Identification System data for training machine learning models. These detectability models are in agreement with oceanographic expectations from preceding studies and can therefore be used for comparing the performance of different SAR sensors in terms of wake detectability. Previous model comparisons showed better wake detection performance of TerraSAR-X (TS-X) than of RADARSAT-2 (RS2) and Sentinel-1 (S1). A comparison between CosmoSkymed (CSK) and RS2 is performed here, to examine the hypothesis that X-Band is generally better for wake detection than C-Band. Finally, this hypothesis is not confirmed, as the detectability models for TS-X, CSK and RS2 reveal similar performances. A comparison of wake detection performance should take the individual wake components into account separately.

A surgical technique aimed at rerouting aqueous humor (AH) outflow from the anterior chamber to the suprachoroidal space (SCS) without performing surgical cyclodialysis was developed to decrease intraocular pressure (IOP) in glaucoma patients. The surgical outcomes of the technique were retrospectively analyzed in fifty-eight patients. At 6, 12, and 24 months, the mean IOP decreased from 27.8±8.3 to 14.95.0 mmHg, median 15.0 (25th percentile (p25 )13.0; 75th percentile (p75) 18.0), and 15.23.3 mmHg; hypotensive medication use reduced from median (p25; p75) 3 (2; 3) to 0 (0; 2), 0 (0; 2), and 0 (0; 1.5), and complete success was achieved in 62.8%, 51.2%, and 32.5% cases, with partial success in 28.4%, 44.2%, and 62.5% cases, respectively. Eight cases (13.8%) presented unsatisfactory outcomes. Intra- and postoperative complications were few and manageable. No bleb formation was observed in any of the cases. In 50% of cases, conjunctival lymphatic vessels (CLVs) developed following surgery in superior quadrants. The technique is safe and effective in providing a long-term decrease in IOP and hypotensive medication use. It was hypothesized in this study that the IOP decrease occurred as a result of enhanced AH outflow from the SCS to CLVs through intrascleral microchannels connecting the SCS to CLVs.

Smallholder farmers in Ethiopia face increasing challenges from climate change and variability, which threaten their food security and livelihoods. This study examines how adopting single and combined climate change adaptation practices affects their vulnerability to food insecurity in Bench Maji Zone, southwest Ethiopia. Through multistage sampling, data was gathered from 390 rural households in four climate-prone districts. The study examines the impacts resulting from both individual and combined implementations of adaptation techniques. These techniques encompass crop management practices, soil and water conservation measures, and livelihood portfolio diversification strategies. The study employed the multinomial endogenous treatment effect regression model to address selection bias and endogeneity resulting from various sources of heterogeneity, whether observed or unobserved. The results show that farmers who adopted adaptation practices were less vulnerable to food insecurity than those who did not. The study also finds that adopting multiple practices has a more significant impact than adopting single practices. Our findings suggest that implementing climate change adaptation strategies can increase the resilience of smallholder farmers in the study area and decrease their vulnerability to food insecurity. The study recommends supporting farmers in adopting these strategies through research and development, information dissemination, and collaborations among farmers, researchers, and extension services.

The practical necessity of strengthening of reinforced concrete structure elements requires a choice of a method which would provide cost-effectiveness, simplicity of construction and durability of the chosen solution. One of the ways is strengthening using the material belonging to the group of micro-reinforced concretes called ferrocement. The paper presents the comparative analysis of some of the results of RC beams exposed mainly to flexure, strengthened with ferrocement elements (strips) applied by gluing on the on the tensed side of RC beams. The results are obtained using the experimental, analytical and numerical research on the adequate models. Strengthening of the beams was performed in the form of four types of ferrocement strips (four different strip widths and four different numbers of wire mesh layers). The numerical non-linear analysis using finite elements method (FEM) was employed, with the introduction of the corresponding characteristics of constitutive material obtained by the experiments on the test specimens. The analytical researches were performed using known analytical calculation methods in order to formulate the model for the calculation of the ultimate and serviceability limit states of the strengthened cross-section. The results presented in the paper, through their comparative compatibility, confirmed the applicability of this strengthening method.

The genus Eucalyptus is a globally captivated source of hardwood and is well known for its medicinal uses. The hybrid and wild species of Eucalyptus are widely used as exotic plantations due to their renowned potential of adapting to various systems and sites, furthermore, making the species the most extensively propagated. Despite unquestionable progression in biotechnological and tissue culture approaches, the productivity of plantations is still limited often due to the low efficiency of clonal propagation from cuttings. The obtained F1 hybrids yield high biomass and High-quality low-cost raw material for large-scale production, however, the development of hybrid, clonal multiplication, proliferation, and post-developmental studies are still major concerns. This riveting review describes the problems concerned with in-vitro and clonal propagation of Eucalypt plantation; recent advances in biotechnological and tissue culture practices for massive and rapid micro-propagation of Eucalyptus; as well, highlights the Eucalypt germplasm preservation techniques.

Nonwoven fabrics have been widely used in textile manufacturing industry as a sheet or web structure because of soft, water-repellent, recycle, ecological and resilient functions. Ultrasonic welding method has been applied for bonding nonwoven fabrics due to clean, fast and reliable approach. In this work, the ultrasonic stepped horn is designed to generate uniform amplitudes on the working surface by using finite element analysis (FEA) simulation. Chromium carbon steels are utilized to produce ultrasonic horns due to high wear resistant and hardness. Isotactic polypropylene nonwoven fabrics fabricated by spunbond process were bonded by continuous ultrasonic sewing machine. Ultrasonic horn with 70 mm in diameter working at 20 kHz, polypropylene (PP) nonwoven density of 80 gsm and various design of welding joints were applied. A typical image in the case of number one was investigated by the scanning electron microscope (SEM) images of inter-facial micro-structure. However, welding joints of totally eight roller patterns was test the tensile strength of the ultrasonic welding joints on PP nonwoven fabrics. The tensile strength of the welding joints is proportional to the area ratio between the welding area and cycling area. The results showed that the melted zone without welding defects such as crack or blowhole can be seen. Furthermore, the tensile strength of welding joints in eight cases of roller patterns (No.1-No.8) was described in details. The ultrasonic welding joints with brick structures give higher tensile strength while the solid line in the pattern gave less strength.

The papaya mealybug Paracoccus marginatus is an invasive, polyphagous pest and poses a quarantine threat to tropical and subtropical countries. Infested commodity internationally should be undergoing phytosanitary treatment, while irradiation is recommended to replace methyl bromide fumigation. Dose-response tests were conducted on the 2-, 4-, and 6-d-old eggs and gravid females of P. marginatus using the X-ray radiation doses of 15–105 Gy with an interval of 15 Gy, respectively. Radiotolerance was compared using fiducial overlapping and lethal dose ratio (LDR) test, resulting in insignificant difference except for LDR test at LD90 (leading 90% mortality at 95% confidence level (CL)); the estimated dose for 99.9968% mortality at 95% CL was 176.5–185.2 Gy, which was validated in the confirmatory tests using gamma irradiation because gammy and X-rays have equal biological effect on pests. Therefore, a total of estimating 60,386 gravid females of papaya mealybug irradiated with 146.8–185.0 Gy resulted in no F1 nymphs developing. Eggs can therefore be used as an alternative to gravid females for dose-response tests; the recommended minimum dose for phytosanitary treatment of P. marginatus on infested commodity is 185 Gy, with treatment efficacy ≥ 99.9950% at 95% CL.

The present work reports on the calculated electronic and magnetic structure of the binary Co-Ga system at high Co content. β-CoGa adopts a simple cubic CsCl type structure. Well-ordered CoGa does not exhibit collective magnetism but is a paramagnetic, metallic compound. Neither Co nor Ga deficiency induces magnetic order, however, ferromagnetism is observed for Co-Ga anti-site disorder. The magnetic moment per cell increases up to about 1.2 μB in the completely disordered body centered cubic structure. With increasing Co content, Co1+xGa1−x maintains the CsCl type structure and becomes ferromagnetic. Most important, a discontinuity of the magnetic order with composition is observed at about 10% excess Co, where a change from a low magnetic moment state to a high moment state is observed. This is accompanied by a change in the electronic structure and transport properties. The discontinuity is forced by the increasing exchange splitting related to the localized moment of the additional Co atoms that replace Ga. Subsequently, the magnetic moment increases continuously up to 2.5 μB for x=0.6. For x≳0.6, the structure changes to face centered cubic with random site occupation and the magnetic moment further increases. Above the magnetic discontinuity, the Curie temperature increases linearly with the Co content from the onset of ferromagnetism, until it reaches its maximum in pure Co.

This hypothesis demonstrates that the efficiency of Loop-Mediated Isothermal Amplification (LAMP) for nucleic acid detection can be positively influenced by preconcentration of microbial cells onto hydrophobic paper surfaces. The mechanism of this model is based on the high attraction of microbes towards hydrophobic surfaces. Extensive studies have demonstrated that hydrophobic surfaces exhibit enhanced bacterial and fungal adhesion. The preconcentration approach by exploiting this inherent affinity of hydrophobic paper substrates enables the adherence of a greater number of target cells, resulting in a higher concentration of target templates for amplification directly from urine samples. In contrast to conventional methods, which often involve complex procedures, this approach offers a simpler, cost-effective, and user-friendly alternative. Moreover, the integration of cell adhesion, LAMP amplification, and signal readout within paper origami-based devices can provide a portable, robust, and highly efficient platform for rapid nucleic acid detection. This innovative hypothesis holds significant potential for point-of-care (POC) diagnostics and field surveillance applications. Further research and development in this field will advance the implementation of this technology, contributing to improved healthcare systems and public health outcomes.

Programmable Object Interfaces are increasingly intriguing researchers because of their broader applications, especially in the medical field. In Wireless Body Area Network (WBAN), for example, the patients’ health can be monitored using clinical nano sensors. Exchanging such sensitive data requires a high level of security and protection against attacks. To that end, the literature is rich with security schemes that include the advanced encryption standard, secure hashing algorithm, and digital signatures that aim to secure the data exchange. However, such schemes elevate the time complexity rendering the data transmission slower. Cognitive Radio technology with a medical body area network system involves communication links between WBAN gateways, server and nano sensors rendering the entire system vulnerable to security attacks. In this paper, a novel DNA-based encryption technique is proposed to secure medical data sharing between sensing devices and central repositories. It has less computational time throughout authentication, encryption, and decryption. Our analysis of experimental attack scenarios shows that our technique is better than its counterparts.

The optimization problem of two or more special-purpose functions of the energy system is subjected to an analysis. Based on experience of our research and general knowledge of partial solutions of energy system optimization at the level of control of production and power energy supply by energy companies in the Czech Republic, a special-purpose (cost) function has been defined. By analysing the special-purpose function, penalty and limitations have been defined. Using the fuzzy logic, a set of suitable solutions for the special-purpose function is accepted. An optimum of the special-purpose function is looked for using the simulated annealing method. The history of electricity consumption is sorted by day and by hour, representing the multidimensional data. When using the cluster analysis, type daytime diagrams of consumption are defined. Type daytime diagrams form prototypes of identified clusters. The so-called self-organizing neural network with Kohonen map attached is used to perform the cluster analysis. The result of our research is presented by an experiment.

Image-guided radiotherapy supported by surface guidance can help track lower lung lesion respiratory motion while reducing a patient’s exposure to ionizing radiation. However, it is not always clear how skin respiratory motion magnitudes and correlations with lung lesion respiratory motion vary between different skin regions of interest (ROI). Four-dimensional Computed Tomography (4DCT) images provide information on both skin and lung respiratory motion and are routinely acquired for the purpose of treatment planning in our institution. Analysis of 4DCT images for 57 patients treated in our institution has been conducted to provide information on respiratory motion magnitudes of nine skin ROIs of the torso, a tracking structure (TS) representing lower lung lobe lesion, as well as respiratory motion correlations between nine ROIs and TS. The effects of gender and adipose tissue volume and distribution on these correlations and magnitudes have been analyzed. Significant differences between ROIs in both respiratory motion magnitudes and correlations to TS have been detected. An overall negative correlation between ROI respiratory magnitudes and the adipose tissue has been detected for ROIs with rib cage support. A weak to moderate negative correlation between adipose tissue volume and ROI-to-TS respiratory correlations has been detected for upper thorax ROIs. Respiratory magnitudes in regions without rib support tended to be larger for men than for women, but no differences in ROI-to-TS correlation between sexes have been detected. Described findings should be considered when choosing skin surrogates for lower lung lesion motion management.

Cancer stem cells (CSCs) are one of the cell types that account for cancer heterogeneity. They arrest in the G0 phase and generate non-CSC progeny by self-renewing and pluripotency activity, resulting in tumor recurrence, metastasis, and chemoresistance. One CSC can stimulate tumor relapse and can re-grow a metastatic tumor. So, CSC is a promising target for eradicating tumors, and developing an anti-CSC method has become a top priority in cancer therapy. In recent years competing endogenous RNA (ceRNA) have emerged as an important class of post-transcriptional regulators that affect gene expression via competition for microRNA (miRNA) binding. Furthermore, aberrant ceRNA expression is associated with tumor progression. To overcome therapeutic resistance due to CSCs, we need to improve our existing understanding of the mechanisms by which ceRNAs are implicated in CSC-related relapse. Thus, this review was designed in order to discuss the role of ceRNAs in CSCs function. We reviewed the role of ceRNAs in acquiring CSCs characteristics in the form of different pathways including Rho GTPase/F-actin_ Yes-associated protein (YAP)/transcriptional co-activator with PDZ-binding motif (TAZ) (Hippo), Wnt/β-catenin pathway, transforming growth factor (TGF)-b–urothelial carcinoma-associated 1 (UCA1)–Slug pathway, etc. Finally, considering the comprehensive impacts of the ceRNA network on different pathways, a treatment strategy driving the ceRNA network might be effective. Targeting ceRNAs may open the path for new cancer therapeutic targets and can be used in clinical research.

With the digital transformation of the logistics industry, smart logistics algorithms have become a core technology to improve efficiency and reduce costs. This paper reviews the development history of traditional logistics technology and discusses the key role of technologies such as the Internet of Things, big data analysis, artificial intelligence, and automation in logistics technology innovation. It focuses on the application of intelligent logistics algorithms in path optimization, intelligent scheduling, data mining and prediction, and intelligent warehousing. To solve the problem of inconsistency between training and testing objectives, this paper proposes DRL4Route, a deep reinforcement learning-based path optimization framework, and designs the DRL4Route-GAE model. Validated through extensive offline experiments and online deployments, the model significantly outperforms existing optimal benchmark methods on real datasets, improving the location deviation squared metrics and the top-three location prediction accuracy metrics. These research results provide important support to further promote the intelligent development of the logistics industry.

The results of a study of the processes of formation of macro- and micro-inhomogeneity of ingots and rolled sheets are presented. To study the nature and sources of surface defects in rolled sheets, a comparative method of structural-concentration analysis of metal at the end-to-end metallurgical process of ingot - slab - sheet metal has been developed, based on the metallographic method of studying the structure and qualitative analysis of non-metallic inclusions. The research results showed that the quality of the surface of rolled sheets is determined mainly by the physical heterogeneity of the crust zone of the ingots, and the internal defects of thin rolled sheets largely depend on the contamination of the metal with non-metallic inclusions and off-axis segregation. A mechanism for transforming defects in the casting cortical zone into surface and internal defects in rolled sheets is proposed.

The study investigates the evolution of soil pore structure and shear strength deterioration in compacted clayey soil under controlled wetting and drying (wd) cycles, which are expected to become more frequent due to climate change. Thirty soil samples were compacted at optimal moisture content and 90% of maximum dry density. These samples were then subjected to 0, 1, 5, 10, and 15 controlled wd cycles from saturation to the wilting point, and volumetric changes were recorded during each cycle. After the wd treatment, the soil samples were scanned using X-ray Computed Tomography (CT) at 50 μm resolution and then sheared under unconsolidated-undrained and consolidated-undrained conditions in a triaxial test. Significant shrinkage and swelling of soil samples were observed during wd cycles, with average volumetric strain fluctuating between +12% at saturation and -5% at the wilting point. X-ray CT visualisation and analysis revealed higher porosity, more prominent pores and increased pore length in soil samples with increasing wd cycles. Both undrained and effective soil shear strength markedly decreased with increasing wd cycles. CT-derived macroporosity and pore length were significant predictors of the soil's undrained and effective shear strength when exposed to wd cycles. The findings emphasise the considerable impact of climate change, specifically wd cycles, on clayey soil, highlighting the need for consideration in the design of earth-based infrastructure.

Newborn screening (NBS) is hailed as a public health success, but little is known about long-term outcomes following a positive newborn screen. There has been difficulty gathering long-term follow-up (LTFU) data consistently, reliably, and with minimal effort. Six programs developed and tested a core set of minimal LTFU data elements. After an iterative data collection process and the development of a data collection tool, the group agreed on minimal LTFU data elements. The denominator captured all infants with an NBS diagnosis, accounting for children who moved or died prior to the follow-up year. They also agreed on three LTFU outcomes: if the child was still alive, had contact with a specialist, and received appropriate care specific to their diagnosis within the year. The six programs representing NBS public health programs, clinical providers, and research programs provided data across multiple NBS disorders. In 2022, 83.8% (563/672) of the children identified by the LTFU programs were alive and living in the jurisdiction; of those, 92.0% (518/563) saw a specialist, and 87.7% (494/563) received appropriate care. The core LTFU data elements can be applied as a foundation to address the impact of early diagnosis by NBS within and across jurisdictions.

Taking into account modern technologies in the mining industry and in the processing of industrial waste, we propose to reprocess cemented low- and intermediate level radioactive waste by extracting all chemical compounds from them. Because of the low cost of space flights in the near future, we propose to use chemical compounds, extracted from radioactive waste, in the production of space electronics and structural materials for automatic space probes and rovers. At the same time, since nano- and micro powders, as well as composites with these fillers, are widely used today in electronics and technology, including in the space industry, the production of radioactive powders and composites will provide new scientific results in the field of materials science and solid-state physics, since nothing is known today about the properties of radioactive powders and composites containing radioactive sources inside.

Inflammation has a critical role in the development and progression of atherosclerosis. On the molecular level, inflammatory pathways negatively impact endothelial barrier properties and thus tissue homeostasis. Conformational changes and destruction of the glycocalyx further promote proinflammatory pathways also contributing to procoagulability and a prothrombotic state. In addition, changes in the extracellular matrix composition lead to (peri-)vascular remodelling and alterations of the vessel wall, e.g., aneurysm formation. Moreover, progressive fibrosis leads to reduced tissue perfusion due to loss of functional capillaries. The present review aims at discussing molecular and clinical effects of inflammatory processes on the micro- and microvas-culature with a focus on peripheral artery disease.

The use of flexible sensors has tripled over the last decade due to the increased demand in various fields including health monitoring, food packaging, electronic skins and soft robotics. Flexible sensors have the ability to be bent and stretched during use and can still maintain their electrical and mechanical properties. This gives them an advantage over rigid sensors that lose their sensitivity when subject to bending. Advancements in 3D printing have enabled the development of tailored flexible sensors. Various additive manufacturing methods are being used to develop these sensors including inkjet printing, aerosol jet printing, fused deposition modelling, direct ink writing, selective laser melting and others. Hydrogels have gained much attention in the literature due to their self-healing and shape transforming. Self-healing enables the sensor to recover from damages such as cracks and cuts incurred during use and this enables the sensor to have a longer operating life and stability. Various polymers are used as substrates on which the sensing conductive material is placed. Polymers including polydimethylsiloxane (PDMS), polyvinyl acetate (PVA), and Kapton are extensively used in flexible sensors. The most widely used nanomaterials in flexible sensors are carbon and silver, however, other nanomaterials such as iron, copper, manganese dioxide and gold are also used to provide controlled levels of conductivity or other functional properties.

Objective: The purpose of this study was to evaluate the surface texture and biofilm adhesion of veneered or CAD/CAM milled zirconia (partially stabilized with yttrium) after professional oral hygiene procedures. Samples (4x4 mm, thickness 2 mm; n = 72) were separated from zirconia blanks (3Y-TZP-LA). One group was veenired with ceramics and the other group of samples was CAD/CAM milled. Each group had 2 subgroups: polished and glazed. The samples were subjected to simulated strokes of professional brushing using abrasive paste and ultrasonic scaling. Parameters of surface micromorphology and receptivity to biofilm were calculated before and after simulating the given methods of professional maintenance of oral hygiene. The characteristics of zirconia surface were evaluated by scanning electron microscopy (SEM). Microbial bacterial/fungal species (Staphylococcus aureus, Streptococcus sanguinis and Candida albicans) were used and cultured on the respective sterilized zirconia surfaces. The amount of biofilm formation on zirconia surface was quantified by colony forming unit (CFU) counts. Results: SEM analysis showed the greatest change in surface microtopography after the use of ultrasonic scaling, in glazed zirconia samples. Less formation of colonies on the surface CAD/CAM milled zirconia restorations was observed. Conclusion: Routine methods of professional maintenance of oral hygiene can damage the surface of glazed zirconia restorations.

In this study, we aimed to identify the features of indeterminate choroidal melanocytic lesions visualized on optical coherence tomography angiography (OCTA) and to identify predictors of growth. We retrospectively evaluated 86 patients with indeterminate lesions treated at our cen-tre from 2016 to 2021. Clinical management involved active surveillance followed by brachy-therapy if growth was detected. The lesions were classified into two groups according to wheth-er they grew (small melanomas) or remained stable (choroidal nevi). Growth was detected in 19 (22.1%) lesions. All patients underwent OCTA at baseline. These images were compared to iden-tify possible predictors of growth. Significant between-group differences were observed in thickness (p=0.00), greatest basal diameter (p=0.00), number of risk factors (p=0.00), symptoms (p=0.001; relative risk [RR]: 4.3), orange pigment (p=0.00; RR: 6.02), and ultrasonographic hol-lowness (Kappa sign); p=0.000; RR: 5.3). The melanomas had significantly more vessels with a diameter ≥ 76.3 µm (p=0.02; RR: 2.46). The time to growth in these lesions was significantly shorter (p=0.05) than in lesions with smaller vessels. These findings show that vessel diameter quantified by OCTA can differentiate between choroidal nevi and small melanomas, especially when considered together with clinical risk factors.

In this work, backscattering signatures of snow-covered lake ice and sea ice from X- and Ku-band synthetic aperture radar (SAR) data are investigated. The SAR data were acquired with the ESA airborne SnowSAR sensor in winter 2012 over Lake Orajärvi in northern Finland and over landfast ice in the Bay of Bothnia of the Baltic Sea. Co-incident with the SnowSAR acquisitions in-situ snow and ice data were measured. In addition, time series of TerraSAR-X images and ice mass balance buoy data were acquired for the Lake Orajärvi in 2011-12. The main objective of our study was to investigate relationships between SAR backscattering signatures and snow depth over lake and sea ice, with the ultimate objective of assessing the feasibility of retrieval of snow characteristics using X- and Ku-band dual-polarisation (VV and VH) SAR over freshwater or sea ice. This study constitutes the first comprehensive survey of snow backscattering signatures at these two combined frequencies over both lake and sea ice. For lake ice, we show that X-band VH-polarized backscattering coefficient (σo) and the Ku-band VV/VH-ratio exhibited the highest sensitivity to the snow depth. For sea ice, the highest sensitivity to the snow depth was found from the Ku-band VV-polarised σo and the Ku-band VV/VH-ratio. However, the observed relations were relatively weak, indicating that at least for the prevailing snow conditions, obtaining reliable estimates of snow depth over lake and sea ice would be challenging using only X- and Ku-band backscattering information.

Immune-mediated bowel diseases (IMBD), including Ulcerative colitis and Crohn's disease, represent a significant global health burden with their complex etiology and increasing prevalence. The connection between intestinal parasites and the gut microbiome in immune-mediated bowel disease is a complex and evolving field of research. Several studies have demonstrated that intestinal parasites can modulate the composition and function of the gut microbiome. Parasitic infections can result in alterations in the gut microbial community, including changes in microbial diversity, abundance, and metabolic activity. These changes can influence the immune response and contribute to the development of IMBDs. In contrast, the gut microbiome serves a pivotal function in maintaining intestinal homeostasis and immune regulation. Dysbiosis, characterized by changes in the gut microbial composition, has been associated with the pathogenesis of IMBDs. Imbalances in the gut microbiota can result in increased gut permeability, chronic inflammation, and aberrant immune responses, all of which are hallmarks of IMBDs. The bidirectional interaction between intestinal parasites and the gut microbiome further complicates the understanding of immune-mediated bowel diseases. Certain parasites, such as hookworms and Necator americanus, have been found to downregulate immune responses and may have therapeutic potential in treating celiac disease. On the other hand, infections with parasites like Strongyloides stercoralis and Blastocystis have been shown to mimic the symptoms of IBD, highlighting the intricate relationship between parasites and the pathogenesis of these diseases. Additional investigation is required to comprehensively elucidate the mechanisms that underlie the association between intestinal parasites and the gut microbiome in immune-mediated bowel disease. This knowledge could potentially lead to the development of targeted therapeutic strategies that aim to restore gut microbiota homeostasis and alleviate the symptoms of these debilitating conditions. By understanding and harnessing the complex interplay between parasites, the gut microbiome, and the host immune system, researchers may uncover novel approaches for the management and treatment of immune-mediated bowel diseases.

The aim of the present study was to predict the response of non-small cell lung cancer (NSCLC) patients to immune checkpoint inhibitors (ICIs) by leveraging computed tomography (CT) images using deep learning techniques. Retrospectively, 624 sequential CT images were gathered from 156 patients at Jiangsu Province Hospital, along with their clinical data. The dataset was subsequently partitioned into three groups: training (n=547), validation (n=64), and test (n=64). Moreover, an external validation cohort included 37 CT images from patients at Nanjing Pukou Peoples' Hospital, accompanied by comprehensive clinical data. An advanced Video Vision Transformer (ViViT) model incorporating global self-attention was utilized to analyse patients treated with ICIs and predict their response. The ViViT model's efficacy was evaluated using a confusion matrix and a receiver operating characteristic curve (ROC). Notably, the ViViT model demonstrated predictive prowess for ICIs response, yielding respective areas under the receiver operating characteristic curve (AUC) of 0.74 (95% CI: 0.69-0.78), 0.74 (95% CI: 0.61-0.86), 0.76 (95% CI: 0.62-0.88), and 0.69 (95% CI: 0.5-0.87) in the training, validation, test, and external validation cohorts. The present study illustrates how a deep learning model can provide a non-invasive means to predict clinical outcomes in NSCLC patients undergoing ICIs, potentially transforming personalized treatment approaches for individuals with NSCLC.

In this paper, we present sums and partial sums of Horadam sequences via generating functions which extends a recent result of Prodinger.

Conventional pervious pavement materials (PPM) consist of cement and aggregate materials and are known for poor durability due to their brittle behavior. Herein, we fabricated polymeric PPMs from durable and abundant polyurethane (PU) to enhance the durability of the material and undertook mechanical and microscopic characterizations. PU-based PPM samples with varying aggregate sizes were produced and the compressive strength and water permeability of each were examined. The pore and tortuosity characteristics of the specimens were analyzed using X-ray micro-computed tomography (micro-CT). Through the micro-CT analysis, the morphological characteristics of the internal structures of PPM were identified and the correlations between the pore size distribution, connectivity, and tortuosity within the specimen were quantitatively analyzed. The microstructures derived from micro-CT were generated as a finite element model and the stress distribution generated inside was numerically determined.

Microfluidic devices which integrate both rapid mixing and liquid jetting for sample delivery are an emerging solution for studying molecular dynamics via X-ray diffraction. Here we use finite element modelling to investigate the efficiency and time-resolution achievable using microfluidic mixers within the parameter range required for producing stable liquid jets. Three-dimensional simulations, validated by experimental data, are used to determine the velocity and concentration distribution within these devices. The results show that by adopting a serpentine geometry, it is possible to induce chaotic mixing, which effectively reduces the time required to achieve a homogeneous mixture for sample delivery. Further, we investigate the effect of flow rate and the mixer microchannel size on the mixing efficiency and minimum time required for complete mixing of the two solutions whilst maintaining a stable jet. In general, we find that the smaller the cross-sectional area of the mixer microchannel, the shorter the time needed to achieve homogeneous mixing for a given flow rate. The results of these simulations will form the basis for optimised designs enabling the study of molecular dynamics occurring on millisecond timescales using integrated mix-and-inject microfluidic devices.

Objective: With just ten questions, the Berlin questionnaire (BQ) stands out as one of the simplest and most widely implemented non-invasive screening tools for detecting subjects at high risk for Obstructive Sleep Apnea (OSA), a still underdiagnosed syndrome characterized by partial or complete obstruction of the upper airways during sleep. The main aim of this study was to enhance the diagnostic accuracy of the BQ through Machine Learning (ML) techniques. Methods: A ML classifier (hereafter, ML-10) was trained using the ten questions of the standard BQ. A simplified variant of the BQ, BQ-2, which comprises only two questions out of the total of ten, was also assessed in a ML context. A 10-fold cross validation scheme was used. Ground truth was provided by the Apnea-Hypopnea Index (AHI) measured by Home Sleep Apnea Testing. Model performance was determined comparing ML-10 and BQ-2 with the standard BQ by the Receiver Operating Characteristic Curve (ROC), Area Under the Curve (AUC), sensitivity, specificity, and accuracy. Results: ML-10 demonstrated superior performance in predicting the risk for OSA compared to the standard BQ and was also capable in classifying OSA with two different AHI thresholds (AHI>=15, AHI>=30), typically used in clinical practice. Remarkably, BQ-2 was also better in sensibility to assess moderate to severe OSA (AHI≥ 15) compared to the ML-10. Conclusions: The study underscores the importance of integrating ML techniques for early OSA detection, suggesting a direction for future research to improve diagnostic processes and patient outcomes in sleep medicine.

Shut-in after fracturing is generally adopted for wells in shale oil reservoirs, and imbibition occurring in matrix nanopores has been proven as an effective way to improve recovery. In this research, the molecular dynamics (MD) simulation was used to investigate the effects of wettability and pressure on nanopores imbibition during shut-in for a typical shale reservoir Jimsar. The results indicate that the microscopic advancement mechanism of the imbibition front is the competitive adsorption between “interfacial water molecules” at the imbibition front and “adsorbed oil molecules” on the pore wall. The essence of spontaneous imbibition involves the adsorption and aggregation of water molecules onto the hydroxyl groups on the pore wall. The flow characteristics of shale oil suggest that the overall push of the injected water to the oil phase is the main reason for the displacement of adsorbed oil molecules. Thus, shale oil especially the heavy hydrocarbon component in the adsorbed layer tends to slip on the walls. However, the weak slip ability of heavy components on the wall surface is an important reason that restricts the displacement efficiency of shale oil during spontaneous imbibition. The effectiveness of spontaneous imbibition is strongly dependent on the hydrophilicity of the matrix pore's wall. The better hydrophilicity of the matrix pore's wall facilitates higher levels of adsorption and accumulation of water molecules on the pore wall and requires less time for “interfacial water molecules” to compete with adsorbed oil molecules. During the forced imbibition process, the pressure difference acts on both the bulk oil and the boundary adsorption oil, but mainly on the bulk oil, which leads to the occurrence of wetting hysteresis. Meanwhile, shale oil still existing in the pore always maintains a good stratified adsorption structure. Because of the wetting hysteresis phenomenon, as the pressure difference increases, the imbibition effect gradually increases, but the actual capillary pressure gradually decreases and there is a loss in the imbibition velocity relative to the theoretical value. Simultaneously, the decline in hydrophilicity further weakens the synergistic effect of pressure difference because of the more pronounced wetting hysteresis. Thus, selecting an appropriate well pressure enables cost savings and maximizes the utilization of the formation's natural power for EOR.

The calculation of echo intensity involved in the SAR image simulation is usually based on the electromagnetic formula or approximate formula derived under certain assumptions. However, the parameters used in these formulas are often difficult to obtain, and the formulas have errors with the actual situation. In this paper, a method of embedding deep neural network (DNN) into the simulation process based on ray tracing is proposed, so that the DNN model can be directly used to fit the calculation formula of echo intensity from real SAR images. Simulation results show that this method can obtain SAR images with high similarity.