Critical Value Research Articles

Classification of Temperature and Humidity in Green Open Spaces by Implementing Internet of Things (IoT) using Mamdani Fuzzy Logic

The condition of green open spaces plays a pivotal role in influencing the comfort and well-being of users engaged in various activities within these environments. Hydrological and microclimate factors, particularly temperature and humidity, hold significant sway over the ecological balance in these areas. This study addresses the need for a tool to assess air temperature and humidity, facilitating public access to critical environmental data that impacts the psychological well-being of living organisms. In pursuit of this objective, a comprehensive monitoring system harnessing the power of the IoT was developed. This system integrates DHT22 and MQ-9 sensors to monitor temperature, humidity, and CO2 gas levels within multiple green open spaces. Data from these sensors is transmitted to a central database with minimal time delays: 2 seconds from the sensors to the server, 1 second from the server to the application, and 3 seconds from the hardware to the application. Impressively, this data transmission achieved a 100% success rate. To assess the comfort levels of these green open spaces, the system employs fuzzy Mamdani logic. It processes data obtained from the DHT22 sensor, using predefined temperature and humidity value thresholds. This innovative monitoring system provides valuable insights into the environmental conditions of green open spaces, contributing to the enhancement of the overall quality and suitability of these areas for various activities.

3D Topology Optimization and Mesh Dependency for Redesigning Locking Compression Plates Aiming to Reduce Stress Shielding.

Current fixation plates for bone fracture treatments are built with biocompatible metallic materials such as stainless steel, titanium, and its alloys (e.g., Ti6Al4V). The stiffness mismatch between the metallic material of the plate and the host bone leads to stress shielding phenomena, bone loss, and healing deficiency. This paper explores the use of three dimensional topology-optimization, based on compliance (i.e., strain energy) minimization, reshaping the design domain of three locking compression plates (four-screw holes, six-screw holes, and eight-screw holes), considering different volume reductions (25, 45, and 75%) and loading conditions (bending, compression, torsion, and combined loads). A finite-element study was also conducted to measure the stiffness of each optimized plate. Thirty-six designs were obtained. Results showed that for a critical value of volume reductions, which depend on the load condition and number of screws, it is possible to obtain designs with lower stiffness, thereby reducing the risk of stress shielding.

HPV Extended Genotyping to Triage Abnormal Cervical Cancer Screens-Balancing the Harms and Benefits of an Additional Triage Test before Direct Colposcopy Referral.

The Netherlands' cervical cancer screening program transitioned to primary human papillomavirus (HPV) screening in 2017. After the introduction of HPV-based screening, the country saw increases in colposcopy referral rates and detections of low-grade lesions. In July 2022, genotyping was introduced, and those with borderline or mild dyskaryotic (BMD) cytologic abnormalities were only referred to colposcopy if positive for HPV type 16 or 18, and repeat screening otherwise. In this article, various strategies using extended genotyping (HPV16/18/31/33/45/52/58) as a triage test after an abnormal screen were explored using data from HPV-positive participants with normal or BMD cytology in the Population-Based Screening Study Amsterdam (POBASCAM) trial. The authors assessed positive and negative predictive values and colposcopy referral rates for each strategy using extended genotyping to triage women to either direct referral to colposcopy or repeat screening. Direct referral did not meet positive and negative predictive value thresholds for efficiency for any strategies. However, the authors note that direct referral may nonetheless be useful among those with BMD due to minimal increases in colposcopy referrals and concerns of loss to follow-up at repeat screening. These findings demonstrate the potential utility of extended genotyping as a triage test in primary HPV screening programs. The results should be considered alongside the fact that referral to repeat screening may result in loss of engagement of women who need treatment to prevent invasive cancer. See related article by Kroon et al., p. 1037.

Incomplete label distribution learning via label correlation decomposition

Label distribution learning (LDL) has garnered increased attention in recent studies on label ambiguity. However, collecting complete annotations for LDL tasks is often time-consuming and labor-intensive compared to traditional learning paradigms. Therefore, designing effective incomplete LDL algorithms is crucial to broaden LDL’s application scope. In this paper, we propose a novel LDL algorithm, called Incomplete Label Distribution Learning via Label Correlation Decomposition (IncomLDL-LCD), which simultaneously learns label distributions and recovers missing description degrees of labels through label correlations. Specifically, we decompose the label correlation into sparse local label correlation and low-rank global label correlation using a soft-thresholding operator and a singular value thresholding operator, respectively. The former is utilized to capture the related label subsets necessary for reconstructing each possible label, while the latter focuses on extracting the coarse-grained semantic concepts from all labels and exploring the groupings of labels. Additionally, we develop an alternating solution with the accelerated proximal gradient descent method for optimization. Extensive experiments on 16 real-world data sets with varying degrees of missing annotations validate that our algorithm effectively handles incomplete LDL tasks and outperforms state-of-the-art algorithms.

O-260 Identifying seminiferous tubules for sperm retrieval during microdissection testicular sperm extraction (M-TESE) using deep learning

Abstract Study question Is it possible to utilize artificial intelligence (AI) in the selection of seminiferous tubules for sperm retrieval during microdissection testicular sperm extraction (M-TESE)? Summary answer AI algorithm was able to segment seminiferous tubules deemed to be good candidates for sperm retrieval with IoU of 0.746 and F1 score of 72.5%. What is known already M-TESE is an advanced surgical procedure reserved for sperm retrieval in men with non-obstructive azoospermia (NOA). Meta-analysis have shown M-TESE might be superior in relation to sperm retrieval rates and postsurgical complications when compared to conventional techniques. Limitations of the technique are the relatively long learning curve for the surgeons and the longer intraoperative time required to identify the tubules with active spermatogenesis. Convolutional neural networks (CNNs) have been shown to successfully identify areas of interest in medical images such as CT and MRI scans. The possibility of utilizing trained CNNs in M-TESE procedures has so far not been studied. Study design, size, duration This is a cross sectional study analyzing image data gathered during M-TESE procedures including the first five men enrolled in a prospective study designed specifically to test the utilization of AI in the treatment of NOA. All participants signed written informed consent. Images were collected intraoperatively with low and high resolution cameras according to predefined protocol. Participants/materials, setting, methods CNN model with down and upsampling architecture was trained using patch-based technique with corresponding labelled truth image pairs based on combination of semi-automated hue saturation value thresholding and manual segmentation of seminiferous tubules. Tubules were allocated into two different classes by the operating surgeon according to the visual perception of their morphology as type 1 (i.e. larger, opaque, good candidates for micro dissection) and type 2 (i.e. sclerotic or atrophic; unlikely to harbor active spermatogenesis). Main results and the role of chance CNN models were trained on 1809 patches with corresponding ground truth segmented images. Two algorithms were tested: the first was trained solely to detect and semantically distinguish type 1 seminiferous tubules. The second was trained to semantically segment the major anatomical structures: tunica albuginea, testicular parenchyma, blood vessels; lobules and the two types of seminiferous tubules describe above. Validation was performed on 988 image patches not previously shown to the algorithm. After grid search for optimal learning rate and augmentation the first algorithm was able to segment type 1 tubules with F1 score of 72.5% and Jaccard Index (IoU) of 0.746. Training took 856 minutes on 48 core high performance computer (HPC) equipped with single graphics processing unit (GPU). Same computational environment was used in the training of the second algorithm. This model was able to segment anatomical structures such as parenchyma (IoU=0.732) and testicular lobules (IoU=0.683) but performed sub optimally on the clinically relevant type 1 tubules (IoU=0.432). The first trained algorithm was able to segment a single high resolution surgical image in 3.4 seconds on an HPC. However, the same procedure took 5.5 minutes on standard desktop computer with 8 core Intel processor without GPU. Limitations, reasons for caution The number of patients is relatively small and therefore more training data would be needed to achieve robust performance. Training data were labelled by single surgeon limiting the generalizability and possibly biasing the selection process. The need of HPC environment for real time segmentation can limit the clinical use. Wider implications of the findings This pilot study shows the potential of AI to help in choosing suitable tubules for micro dissection, shortening the learning curve for young andrological surgeons. The access to cluster based computation is getting easier by the day and can soon allow instant intraoperative AI segmentation, thus shortening the surgical procedure. Trial registration number NA

Opportunistic use of chest low-dose computed tomography (LDCT) imaging for low bone mineral density and osteoporosis screening: cutoff thresholds for the attenuation values of the lower thoracic and upper lumbar vertebrae.

Osteoporosis remains substantially underdiagnosed and undertreated worldwide. Chest low-dose computed tomography (LDCT) may provide a valuable and popular opportunity for osteoporosis screening. This study sought to evaluate the feasibility of the screening of low bone mineral density (BMD) and osteoporosis with mean attenuation values of the lower thoracic compared to upper lumbar vertebrae. The cutoff thresholds of the mean attenuation values in Hounsfield units (HU) were derived to facilitate implementation of opportunistic screening using chest LDCT. The participants aged 30 years or older who underwent chest LDCT and quantitative computed tomography (QCT) examinations from August 2018 to October 2020 in our hospital were consecutively included in this retrospective study. A region of interest (ROI) was placed in the trabecular bone of each vertebral body to measure the HU values. The correlations of mean HU values of lower thoracic (T11-T12) and upper lumbar (L1-L2) vertebrae with age and lumbar BMD obtained with QCT were performed using the Pearson correlation coefficient, respectively. The area under the curve (AUC) of the receiver operator characteristic (ROC) curve was generated to determine the cutoff thresholds for distinguishing low BMD from normal and osteoporosis from non-osteoporosis. A total of 1,112 participants were included in the final study cohort (743 men and 369 women, mean age 58.2±8.9 years; range, 32-88 years). The mean HU values of T11-T12 and L1-L2 were significantly different among 3 QCT-defined BMD categories of osteoporosis, osteopenia, and normal (P<0.001). The differences in HU values between T11-T12 and L1-L2 in each category of bone status were statistically significant (P<0.001). The mean HU values of T11-T12 (r=-0.453, P<0.001) and L1-L2 (r=-0.498, P<0.001) had negative correlations with age. Positive correlations were observed between the mean HU values of T11-T12 (r=0.872, P<0.001) and L1-L2 (r=0.899, P<0.001) with BMD. The optimal cutoff thresholds for distinguishing low BMD from normal were average T11-T12 ≤157 HU [AUC =0.941, 95% confidence interval (CI): 0.925-0.954, P<0.001] and L1-L2 ≤138 HU (AUC =0.950, 95% CI: 0.935-0.962, P<0.001), as well as distinguishing osteoporosis from non-osteoporosis were average T11-T12 ≤125 HU (AUC =0.960, 95% CI: 0.947-0.971, P<0.001) and L1-L2 ≤107 HU (AUC =0.961, 95% CI: 0.948-0.972, P<0.001). There was no significant difference between the AUC values of T11-T12 and L1-L2 for low BMD (P=0.07) and osteoporosis (P=0.92) screening. We have conducted a study on low BMD and osteoporosis screening using mean attenuation values of lower thoracic and upper lumbar vertebrae. Assessment of mean attenuation values of T11-T12 and L1-L2 can be used interchangeably for low BMD and osteoporosis screening using chest LDCT, and their cutoff thresholds were established.

Preoperative Laboratory Values Predicting Periprosthetic Joint Infection in Morbidly Obese Patients Undergoing Total Hip or Knee Arthroplasty.

Morbidly obese patients are an ever-growing high-risk population undergoing total hip arthroplasty (THA) and total knee arthroplasty (TKA) for end-stage osteoarthritis. This study sought to identify preoperative laboratory values that may serve as predictors of periprosthetic joint infection (PJI) in morbidly obese patients undergoing THA or TKA. All morbidly obese patients with preoperative laboratory data before undergoing primary elective TKA or THA were identified using the Premier Healthcare Database. Patients who developed PJI within 90 days after surgery were compared with patients without PJI. Laboratory value thresholds were defined by clinical guidelines or primary literature. Univariate and multivariable regression analyses were utilized to assess the association between PJI and preoperative laboratory values, including total lymphocyte count, neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), monocyte-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), albumin level, platelet count, albumin-globulin ratio, hemoglobin level, and hemoglobin A1c. Of the 6,780 patients identified (TKA: 76.67%; THA: 23.33%), 47 (0.69%) developed PJI within 90 days after surgery. The rate of PJI was 1.69% for patients with a hemoglobin level of <12 g/dL (for females) or <13 g/dL (for males), 2.14% for those with a platelet count of <142,000/µL or >417,000/µL, 1.11% for those with an NLR of >3.31, 1.69% for those with a PLR of >182.3, and 1.05% for those with an SII of >776.2. After accounting for potential confounding factors, we observed an association between PJI and an abnormal preoperative NLR (adjusted odds ratio [aOR]: 2.38, 95% confidence interval [CI]: 1.04 to 5.44, p = 0.039), PLR (aOR: 4.86, 95% CI: 2.15 to 10.95, p < 0.001), SII (aOR: 2.44, 95% CI: 1.09 to 5.44, p = 0.029), platelet count (aOR: 3.50, 95% CI: 1.11 to 10.99, p = 0.032), and hemoglobin level (aOR: 2.62, 95% CI: 1.06 to 6.50, p = 0.038). This study identified preoperative anemia, abnormal platelet count, and elevated NLR, PLR, and SII to be associated with an increased risk of PJI among patients with a body mass index of ≥40 kg/m 2 . These findings may help surgeons risk-stratify this high-risk patient population. Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

A Rate of Change and Center of Gravity Approach to Calculating Composite Indicator Thresholds: Moving from an Empirical to a Theoretical Perspective

A composite indicator (CI) is the mathematical aggregation of sub-dimension (local) indicators used to provide an overall score for the multidimensional concept being measured. CIs are widely used to assess the benefits or risks in human endeavors, such as by creating life satisfaction indices or disaster risk indicators. One important aspect of the development of CIs is setting up value thresholds for taking action, such as in determining the minimum acceptable level of life satisfaction in a community or the maximum acceptable flood risk value beyond which people should be ordered to evacuate from the area in danger. The analytic hierarchy/network process (AHNP) is widely used for the development of CIs. In a review of 111 AHP/ANP CI studies, fewer than 10% discussed any threshold. This means that about 90% of the developed CIs were theoretically sound but lacked the actionable thresholds necessary to be of practical use. Furthermore, for the few studies that set thresholds, the values were typically set arbitrarily or using inadequate statistical approaches. To address this important concern, this study first discusses the most commonly used approaches to setting up thresholds, as well as their inadequacies, and proposes the development of AHP/ANP CI thresholds using a mathematical approach based on the rate of change and center of gravity (RCCG) concepts. Using this approach, a virtual reference alternative, i.e., a threshold profile (TP) made up of the local thresholds of each indicator, is calculated. The key advantage of the proposed method is that it not only provides a non-arbitrary way to set up a CI threshold; more importantly, it is independent of the data and/or alternatives to be evaluated; that is, a threshold calculated with the proposed approach constitutes an absolute reference value, outside the dataset.

Nanoscale gold nanoparticle (GNP)-laden tumor cell model and its use for estimation of intracellular dose from GNP-induced secondary electrons.

Gold nanoparticles (GNPs) accumulated within tumor cells have been shown to sensitize tumors to radiotherapy. From a physics point of view, the observed GNP-mediated radiosensitization is due to various downstream effects of the secondary electron (SE) production from internalized GNPs such as GNP-mediated dose enhancement. Over the years, numerous computational investigations on GNP-mediated dose enhancement/radiosensitization have been conducted. However, such investigations have relied mostly on simple cellular geometry models and/or artificial GNP distributions. Thus, it is at least desirable, if not necessary, to conduct further investigations using cellular geometry models that properly reflect realistic cell morphology as well as internalized GNP distributions at the nanoscale. The primary aim of this study was to develop a nanometer-resolution geometry model of a GNP-laden tumor cell for computational investigations of GNP-mediated dose enhancement/radiosensitization. The secondary aim was to demonstrate the utility of this model by quantifying GNP-induced SE tracks/dose distribution at sub-cellular levels for further validation of a nanoscopic dose point kernel (nDPK) method against full-fledged Geant4 Monte Carlo (MC) simulation. A transmission electron microscopy (TEM) image of a single cell showing cytoplasm, cellular nucleus, and internalized GNPs in the cellular endosome was segmented into sub-cellular levels based on pixel value thresholding. A corresponding material density was allocated to each pixel, and, by adding a thickness, each pixel was transformed to a geometric voxel and imported as a Geant4-acceptable input geometry file. In Geant4-Penelope MC simulation, a clinical 6MV photon beam was applied, vertically or horizontally to the cell surface, and energy deposition to the cellular nucleus and cytoplasm, due to SEs emitted by internalized GNPs, was scored. Next, nDPK calculations were performed by generating virtual electron tracks from each GNP voxel to all nucleus and cytoplasm voxels. Subsequently, another set of Geant4 simulation was performed with both Penelope and DNA physics models under the geometry closely mimicking in vitro cell irradiation with a clinical 6MV photon beam, allowing for derivation of nDPK specific to this geometry and further comparison between Gean4 simulation and nDPK method. The Geant4-calculated SE tracks and associated energy depositions showed significant dependence on photon incidence angle. For perpendicular incidence, nDPK results showed good agreement (average percentage pixel-to-pixel difference of 0.4% for cytoplasm and 0.5% for nucleus) with Geant4 results, while, for parallel incidence, the agreement became worse (-1.7%-0.7% for cytoplasm and -5.5%-0.8% for nucleus). Under the 6MV cell irradiation geometry, nDPK results showed reasonable agreement (pixel-to-pixel Pearson's product moment correlation coefficient of 0.91 for cytoplasm and 0.98 for nucleus) with Geant4 results. The currently developed TEM-based model of a GNP-laden cell offers unprecedented details of realistic intracellular GNP distributions for nanoscopic computational investigations of GNP-mediated dose enhancement/radiosensitization. A benchmarking study performed with this model showed reasonable agreement between Geant4- and nDPK-calculated intracellular dose deposition by SEs emitted from internalized GNPs, especially under perpendicular incidence - a popular cell irradiation geometry and when the Geant4-Penelope physics model was used.

An Inventory Control of Wuling Car Spare Parts Using a Risk Analysis Appoarch

PT XWZ is a service company engaged in the automotive sector, which serves the stages of unit sales to service car vehicles (after sales service) for the Wuling car brand. In improving the vehicle service or maintenance process, it is necessary to have an optimal availability of spare parts. From the inventory data in the warehouse, the majority of spare parts stored in the warehouse are classified as slow moving parts. By conducting an ABC and FMEA approach, it is expected to be able to increase the reliability of maintenance needs so as to increase inventory according to the criticality value of spare parts. In this research, 19 spare parts items were found to be classified as critical or high risk items.

Automated detection and analysis of coronal active region structures across solar cycle 24

ABSTRACT Observations from NASA’s Solar Dynamic Observatory Atmospheric Imaging Assembly were employed to investigate targeted physical properties of coronal active region structures across the majority of solar cycle 24 (From 2010 May to end of 2020 December). This is the largest consistent study to date which analyses emergent trends in structural width, location, and occurrence rate by performing an automatic and long-term examination of observable coronal and chromospheric limb features within equatorial active region belts across four extreme ultraviolet wavelengths (171, 193, 211, and 304 Å). This has resulted in over 30 000 observed coronal structures and hence allows for the production of spatial and temporal distributions focused upon the rise, peak, and decay activity phases of solar cycle 24. Employing a self-organized-criticality approach as a descriptor of coronal structure formation, power-law slopes of structural widths versus frequency are determined, ranging from -1.6 to -3.3 with variations of up to 0.7 found between differing periods of the solar cycle, compared to a predicted Fractal Diffusive Self-Organized Criticality (FD-SOC) value of -1.5. The North–South hemispheric asymmetry of these structures was also examined with the Northern hemisphere exhibiting activity that is peaking earlier and decaying slower than the Southern hemisphere, with a characteristic ‘butterfly’ pattern of coronal structures detected. This represents the first survey of coronal structures performed across an entire solar cycle, demonstrating new techniques available to examine the composition of the corona by latitude in varying wavelengths.

Comparison of the population covered by the 2024 version of the WHO's hepatitis B prevention and treatment guidelines and the Chinese antiviral treatment guidelines

Objective: This study aims to compare the antiviral treatment similarities and differences in the population covered by the 2024 version of the World Health Organization's (WHO) hepatitis B prevention and treatment guidelines and the current Chinese hepatitis B prevention and treatment guidelines, so as to explore their impact on the indications for antiviral therapy in Chinese patients with chronic hepatitis B (CHB). Methods: The information of patients with chronic hepatitis B virus infection who did not receive antiviral treatment was collected through the registration database of the China Clinical Research Platform for Hepatitis B Elimination. Descriptive statistics were conducted on the demographic, blood, biochemical, and virological levels of patients according to the treatment recommendations of the two versions of the guidelines. The Mann-Whitney U test and χ2 test were used to compare the differences and proportional distribution of the treatment populations covered by the two guidelines. The χ2 test was used to analyze the coverage rate of different antiviral treatment indications. Results: A total of 21,134 CHB patients without antiviral treatment were enrolled. 69.4% of patients met the 2024 versions of the WHO guidelines' recommendations. 85.0% of patients met the current Chinese hepatitis B prevention and treatment guidelines. The WHO guidelines for antiviral therapy indications were met in younger patients with higher levels of ALT, AST, and APRI scores, as well as greater proportion of patients with higher viral loads (P<0.001). The WHO guidelines recommended a cut-off value of APRI>0.5, which raised the proportion of patients on antiviral therapy from 6.6% to 30.9%. 45.7% of patients met the antiviral indications for HBV DNA >2000 IU/ml with abnormal transaminase (ALT>30 U/L for males and ALT>19 U/L for females). The reduced APRI diagnostic cut-off value and ALT treatment threshold had further increased the treatment coverage rate by 91.6% in patients with chronic HBV infection in line with the 2024 versions of WHO guidelines. Conclusion: The reduction of the APRI diagnostic cut-off value and the ALT treatment threshold, based on the current hepatitis B guidelines of China, will further improve the treatment coverage of CHB patients.

Susceptibility gene identification and risk evaluation model construction by transcriptome-wide association analysis for salt sensitivity of blood pressure

BackgroundSalt sensitivity of blood pressure (SSBP) is an intermediate phenotype of hypertension and is a predictor of long-term cardiovascular events and death. However, the genetic structures of SSBP are uncertain, and it is difficult to precisely diagnose SSBP in population. So, we aimed to identify genes related to susceptibility to the SSBP, construct a risk evaluation model, and explore the potential functions of these genes.Methods and resultsA genome-wide association study of the systemic epidemiology of salt sensitivity (EpiSS) cohort was performed to obtain summary statistics for SSBP. Then, we conducted a transcriptome-wide association study (TWAS) of 12 tissues using FUSION software to predict the genes associated with SSBP and verified the genes with an mRNA microarray. The potential roles of the genes were explored. Risk evaluation models of SSBP were constructed based on the serial P value thresholds of polygenetic risk scores (PRSs), polygenic transcriptome risk scores (PTRSs) and their combinations of the identified genes and genetic variants from the TWAS. The TWAS revealed that 2605 genes were significantly associated with SSBP. Among these genes, 69 were differentially expressed according to the microarray analysis. The functional analysis showed that the genes identified in the TWAS were enriched in metabolic process pathways. The PRSs were correlated with PTRSs in the heart atrial appendage, adrenal gland, EBV-transformed lymphocytes, pituitary, artery coronary, artery tibial and whole blood. Multiple logistic regression models revealed that a PRS of P < 0.05 had the best predictive ability compared with other PRSs and PTRSs. The combinations of PRSs and PTRSs did not significantly increase the prediction accuracy of SSBP in the training and validation datasets.ConclusionsSeveral known and novel susceptibility genes for SSBP were identified via multitissue TWAS analysis. The risk evaluation model constructed with the PRS of susceptibility genes showed better diagnostic performance than the transcript levels, which could be applied to screen for SSBP high-risk individuals.

Valorization of Biomass and Industrial Wastes as Alternative Fuels for Sustainable Cement Production

The cement industry contributes around 7% of global anthropogenic carbon dioxide emissions, mainly from the combustion of fuels and limestone decomposition during clinker production. Using alternative fuels derived from wastes is a key strategy to reduce these emissions. However, alternative fuels vary in composition and heating value, so selecting appropriate ones is crucial to maintain clinker quality and manufacturing processes while minimizing environmental impact. This study evaluated various biomass and industrial wastes as potential alternative fuels, characterizing them based on proximate analysis, elemental and oxide composition, lower heating value, and bulk density. Sawdust, pecan nutshell, industrial hose waste, and plastic waste emerged as viable options as they met the suggested thresholds for heating value, chloride, moisture, and ash content. Industrial hose waste and plastic waste were most favorable with the highest heating values while meeting all the criteria. Conversely, wind blade waste, tire-derived fuel, and automotive shredder residue did not meet all the recommended criteria. Therefore, blending them with alternative and fossil fuels is necessary to preserve clinker quality and facilitate combustion. The findings of this research will serve as the basis for developing a computational model to optimize the blending of alternative fuels with fossil fuels for cement production.

GaSb-based interband cascade laser with hybrid superlattice plasmon-enhanced claddings

We present an interband cascade laser (ICL) emitting at 5.2 µm consisting of an 8-stage active region and a hybrid cladding composed of outer plasmon-enhanced InAs0.915Sb0.085 and inner InAs/AlSb superlattice claddings. The hybrid cladding architecture shows an increase in mode confinement in the active region by 11.2% according to the simulation. This is a consequence of a significantly lower refractive index of plasmon-enhanced claddings. The threshold current density is 242 A/cm2 in pulsed operation at room temperature. This is the lowest value reported to date for ICLs emitting at wavelengths longer than 5 µm. We also report close to record value threshold power density of 840 W/cm2 for ICLs at such wavelengths.

Screw Stimulation Thresholds for Neuromonitoring in Minimally Invasive Oblique Lateral Lumbar Interbody Fusion (OLLIF): A Correlational Study.

This study presents findings from an investigation into the correlation of neuromonitoring techniques in minimally invasive lumbar fusions and their open counterparts regarding acceptable thresholds for screw stimulation. The threshold for acceptable stimulation value for open surgery has been established. The study compared acceptable thresholds for open pedicle screws where there is more connection between the screw and the soft tissue. The neuromonitoring data of 17 patients who underwent oblique lateral lumbar interbody fusion (OLLIF) procedures between September 2023 to May 2024 were reviewed. Neuromonitoring was conducted throughout surgeries, recording stimulation thresholds for pedicle screws insulated and uninsulated, to simulate the environment of a screw during open and minimally invasive surgery respectively. Patients' BMI was also collected for potential correlation analysis. Results indicate a discernible correlation between stimulation thresholds in open and minimally invasive surgeries, but no definitive correlation with BMI due to sample size limitations. Though a significant correlation between the two stimulating styles is apparent, there is a good correlation to suggest whatthreshold should determine astandard stimulation threshold for minimally invasive surgeries. The study emphasizes the need for refined neuromonitoring strategies in minimally invasive spinal fusion (MISF) surgeries to ensure patient safety and surgical effectiveness. Further research with larger cohorts is recommended to establish optimized protocols that have a clearly defined amplitude for MISF thresholds.

Quantitative assessment of full-width at half-maximum and detector energy threshold in X-ray imaging systems

BackgroundThe response function of imaging systems is regularly considered to improve the qualified maps in various fields. More the accuracy of this function, the higher the quality of the images. MethodsIn this study, a distinct analytical relationship between full-width at half-maximum (FWHM) value and detector energy thresholds at distinct tube peak voltage of 100 kV has been addressed in X-ray imaging. The outcomes indicate that the behavior of the function is exponential. The relevant cut-off frequency and summation of point spread function S(PSF) were assessed at large and detailed energy ranges. ResultsA compromise must be made between cut-off frequency and FWHM to determine the optimal model. By detailed energy range, the minimum and maximum of S(PSF) values were revealed at 20 keV and 48 keV, respectively, by 2979 and 3073. Although the maximum value of FWHM occurred at the energy of 48 keV by 224 mm, its minimum value was revealed at 62 keV by 217 mm. Generally, FWHM value converged to 220 mm and S(PSF) to 3026 with small fluctuations. Consequently, there is no need to increase the voltage of the X-ray tube after the energy threshold of 20 keV. ConclusionThe proposed FWHM function may be used in designing the setup of the imaging parameters in order to reduce the absorbed dose and obtain the final accurate maps using the related mathematical suggestions.

Comparison of Triglyceride–Glucose (TyG) Index and Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) Index in Prediction of Male Hypogonadism

Several studies have shown the association between decreased insulin sensitivity and the risk of male hypogonadism. Homeostatic model assessment of insulin resistance (HOMA-IR) is a well-established marker of decreased insulin sensitivity. The triglyceride–glucose index (TyG), calculated as ln fasting triglyceride mg/dL× fasting glucose mg/dL/2, was recently suggested to be a cheaper and a reliable surrogate marker to detect insulin resistance (IR). Our aim was to compare the performance of those two indexes in the prediction of male hypogonadism. The data on 192 men from infertile couples (18–50 years; sperm concentration &lt;20 x 106/mL) and 199 population-based matched controls collected during the years 2009–2012 (baseline) were evaluated retrospectively. Half of these subjects (72 subfertile men and 122 controls) were reinvestigated 5–10 years later (median year (range): 7 (5–10)). The patients receiving any hormonal therapy were excluded. Hypogonadism was defined as fasting, morning serum testosterone below 12 nmol/L. In receiver operating characteristic curve analysis, the optimal diagnostic cutoff values for baseline HOMA-IR and TyG to predict MetS at re-examination were 2.68 (Area Under Curve (AUC) = 0.886, p &lt; 0.001) and 8.60 (AUC = 0.816, p &lt;0.001), respectively. Moreover, in binary logistic regression analysis performed on the whole cohort using these thresholds for high values of HOMA-IR and high TyG, the odds-ratios (ORs) for hypogonadism were 6.48 (95% Confidence Interval (CI): 3.77–11.2; p &lt;0.001) and 3.58 (95% CI: 2.17–5.94; p &lt;0.001), respectively. Even though high HOMA-IR levels provided better risk estimates, high TyG was also highly related to the risk of hypogonadism. These markers can be utilized to identify men being at high risk of hypogonadism.

Hydraulic Connectiveness Metric for the Analysis of Criticality in Water Distribution Networks

Capturing the criticality of a water distribution network (WDN) is difficult because of its many constituent factors. In terms of operation, the arrangement of demand nodes and how they connect have a significant influence. This study aims to integrate hydraulic and topologic aspects into a single criticality measure by adapting the structural hole influence matrix concept. This method applies the nodal demand to the corresponding pipes to construct a weighted network. The matrix stores each node’s local and global connection information, and the criticality value is then assigned based on the adjacency information. The criticality value can reveal the locations in terms of nodes or pipes that are vital for maintaining a network’s level of service. By analyzing pipe-failure scenarios, the criticality value can be related to the loss of performance. Assessing the nodal criticality change behavior under an increased stress scenario can help uncover the impacted areas. The metric for district metered area (DMA) creation demonstrates its potential as a weighting to be considered. This unified criticality metric enables the evaluation of nodes and pipes in a WDN, thereby enabling resilient and sustainable development planning.

Validation of bidirectional cavotricuspid isthmus block using electrocardiographic imaging

Abstract Background The validation of bidirectional cavotricuspid isthmus (CTI) block following catheter ablation for typical atrial flutter (AFL) involves endocavitary manoeuvres using multiple catheters. The diagnostic capacity of electrocardiographic imaging (ECGi) as a non-invasive tool to confirm bidirectional CTI block may simplify the procedure but its benefit has not been investigated so far. Purpose To evaluate the diagnostic capacities of a novel imageless ECGi system in detecting bidirectional CTI block during AFL catheter ablation. Methods A total of 34 patients were consecutively included in a prospective single-centre study. Atrial activation maps were derived from a novel imageless ECGi system when pacing the septal and lateral aspects of the CTI, gauging the technology's capacities to detect bidirectional block by measuring transisthmic intervals (TII) and observing wave-front collision patterns. TII reflects the time taken for electrical activation to cross the CTI during pacing and we measured both the absolute value and the increase relative to its baseline value. The bidirectional CTI block was assessed by endocavitary manoeuvres using a multipole catheter as the gold-standard. We conducted a blind assessment of the diagnostic capacities of ECGi over endocavitary manoeuvres considering maps from the septal and lateral pacing to determine clockwise and counterclockwise CTI block, respectively. Results Our study established clear benchmarks for diagnosing CTI block using ECGi (Figure 1). Regarding the assessment of clockwise CTI block, the presence of a wave-front collision pattern at the CTI yielded a positive predictive value (PPV) of 91% and negative predictive value (NPV) of 69%. Furthermore, ROC analysis pinpointed 100 ms and 30 ms as the optimal threshold for TII absolute value (PPV=89%, NPV =78%) and TII increase from baseline (PPV=91%, NPV =65%), respectively. Taking together, the combination of these three parameters offered high diagnostic capacities (PPV=87%, NPV=90%). Regarding counterclockwise CTI block, the TII absolute value alone was a reliable predictor, with a threshold derived from ROC analysis of 115 ms providing a PPV of 77% and a NPV of 83% (Graphical abstract). Conclusion These results highlight the efficacy of ECGi in CTI block assessment, promising a streamlined and accurate diagnostic approach (Graphical abstract). The use of a single ablation catheter coupled with ECGi to assess the bidirectional CTI block offers a simplified and efficient alternative to traditional dual catheter techniques.ECGi-based CTI block assessment methodGraphical abstract