Objective Comparison Research Articles

Comparison of Policy Responses to the COVID‐19 Pandemic. Does It Reproduce the Old Patterns?

ABSTRACTThe research's main objectives are to verify systemic differences between OECD countries in terms of their early responses to the COVID‐19 economic challenge and to compare newly established taxonomy with old patterns determined by classifications that can be found in the literature. Research is based on a few methods of cluster analysis—hierarchical clustering and the k‐means method are supplemented with insights derived from the application of c‐means fuzzy clustering. It also applies Rand and Jaccard indices to compare a new taxonomy with existing classifications of welfare states and capitalistic systems. Objective comparison of the new taxonomy with those existing in the literature with the application of statistical methods is the most significant contribution of the article. Results suggest that it is possible to distinguish various strategies for dealing with the COVID‐19 economic consequences in the early period of the pandemic, but demarcation lines between particular clusters significantly differ from the findings of previous studies.

Size scaling of large landslides from incomplete inventories

Abstract. Landslide inventories have become cornerstones for estimating the relationship between the frequency and size of slope failures, thus informing appraisals of hillslope stability, erosion, and commensurate hazard. Numerous studies have reported how larger landslides are systematically rarer than smaller ones, drawing on probability distributions fitted to mapped landslide areas or volumes. In these models, much uncertainty concerns the larger landslides (defined here as affecting areas ≥ 0.1 km2) that are rarely sampled and often projected by extrapolating beyond the observed size range in a given study area. Relying instead on size-scaling estimates from other inventories is problematic because landslide detection and mapping, data quality, resolution, sample size, model choice, and fitting method can vary. To overcome these constraints, we use a Bayesian multi-level model with a generalised Pareto likelihood to provide a single, objective, and consistent comparison grounded in extreme value theory. We explore whether and how scaling parameters vary between 37 inventories that, although incomplete, bring together 8627 large landslides. Despite the broad range of mapping protocols and lengths of record, as well as differing topographic, geological, and climatic settings, the posterior power-law exponents remain indistinguishable between most inventories. Likewise, the size statistics fail to separate known earthquakes from rainfall triggers and event-based triggers from multi-temporal catalogues. Instead, our model identifies several inventories with outlier scaling statistics that reflect intentional censoring during mapping. Our results thus caution against a universal or solely mechanistic interpretation of the scaling parameters, at least in the context of large landslides.

The scope and limits of fine-grained image and category information in the ventral visual pathway.

Humans can easily abstract incoming visual information into discrete semantic categories. Previous research employing functional MRI (fMRI) in humans has identified cortical organizing principles that allow not only for coarse-scale distinctions such as animate versus inanimate objects but also more fine-grained distinctions at the level of individual objects. This suggests that fMRI carries rather fine-grained information about individual objects. However, most previous work investigating fine-grained category representations either additionally included coarse-scale category comparisons of objects, which confounds fine-grained and coarse-scale distinctions, or only used a single exemplar of each object, which confounds visual and semantic information. To address these challenges, here we used multisession human fMRI (female and male) paired with a broad yet homogenous stimulus class of 48 terrestrial mammals, with 2 exemplars per mammal. Multivariate decoding and representational similarity analysis (RSA) revealed high image-specific reliability in low- and high-level visual regions, indicating stable representational patterns at the image level. In contrast, analyses across exemplars of the same animal yielded only small effects in the lateral occipital complex (LOC), indicating rather subtle category effects in this region. Variance partitioning with a deep neural network and shape model showed that across exemplar effects in EVC were largely explained by low-level visual appearance, while representations in LOC appeared to also contain higher category-specific information. These results suggest that representations typically measured with fMRI are dominated by image-specific visual or coarse-grained category information but indicate that commonly employed fMRI protocols may reveal subtle yet reliable distinctions between individual objects.Significance Statement While it has been suggested that functional MRI (fMRI) responses in ventral visual cortex carry fine-grained information about individual objects, much previous research has confounded fine-grained with coarse-scale category information or only used individual visual exemplars, which potentially confounds semantic and visual object information. Here we address these challenges in a multisession fMRI study where participants viewed a highly homogenous stimulus set of 48 land mammals with 2 exemplars per animal. Our results reveal a strong dominance of image-specific effects and additionally indicate subtle yet reliable category-specific effects in lateral occipital complex, underscoring the capacity of commonly employed fMRI protocols to uncover fine-grained visual information.

Parameter analysis in stereoelectroencephalography-guided radiofrequency thermocoagulation: A common basis for objective comparison between protocols

ObjectiveStereoelectroencephalography-guided radiofrequency thermocoagulation (SEEG-guided RF-TC) is an invasive procedure based on stereotactic lesioning of cortical targets in the brain using bipolar current through electrode contacts within the SEEG implant. To date, several RF-TC protocols have been described in the literature; however, a consensus has yet to be reached. This work aims to analyze the electrical parameters during RF-TC processes, offering a method to objectively describe and compare different SEEG-guided RF-TC protocols. MethodsThe study included patients who underwent RF-TC procedures at the IRCCS Istituto delle Scienze Neurologiche di Bologna from February 2022 to May 2023. During each procedure, modifications of the following parameters were measured: voltage, current, impedance, and electric power. An ad-hoc algorithm was implemented to detect abrupt impedance raises, which reflects the occurrence of the thermocoagulation. A two-sample t-test was used to compare parameter curves in RF-TC of different brain structures. ResultsA total of ninety-two RF-TC procedures were performed in eight patients according to a standardized protocol. During each procedure, impedance levels started at about 700Ω and rose up to 1300Ω, displaying an erratic pattern characterized by one or multiple raises. All measured parameters exhibited similar trends until the first peak, after which changes were influenced by the frequency of impedance raises. No significant correlations were observed between parameter modifications in distinct anatomical sites of RF-TC. SignificanceThe systematic analysis of electrical parameters may represent a reliable tool to compare different RF-TC protocols, paving the way for identifying optimal configurations for SEEG-guided RF-TC procedures in the future.

Hematopoietic Cell Transplant compared with Standard Care in Adolescents and Young Adults with Sickle Cell Disease

Disease-modifying therapies are standard of care (SOC) for sickle cell disease (SCD), but hematopoietic cell transplantation (HCT) has curative potential. We compared outcomes prospectively through 2-years after biologic assignment to a Donor or No Donor (SOC) Arm based on the availability of an HLA-matched sibling or unrelated donor (BMTCTN 1503; NCT02766465). A donor search was commenced after eligibility confirmation. The primary endpoint was the comparison of survival 2 years after biologic assignment between treatment arms. Power calculations required 60 participants on the Donor Arm and 140 on the No Donor Arm to determine if early transplant-related mortality might be balanced by disease-related mortality over a longer period of follow-up. Secondary objectives compared changes in SCD-related events, functional outcomes, and organ function. Data were analyzed by the intent-to-treat principle. A total of 113 participants were enrolled, 28 on the Donor and 85 on the No Donor Arm The 2-year probabilities of survival were 89% and 93%, on the Donor and No Donor Arms, respectively. Vaso-occlusive pain (VOC) was less frequent on the Donor Arm in the second year after biologic assignment (p < 0.001). On PROMIS-57 surveys there was decreased fatigue (p=0.003) and an increased ability to participate in social roles and activities (p=0.003) on the Donor Arm 2-years after biologic assignment. Differences in other secondary outcomes did not reach statistical significance. Barriers to accrual prevented an objective comparison of survival. Assignment to the Donor Arm led to improvements in VOC, fatigue, and social function.

121 year after Einthoven: show me the normal ECG?

Abstract Background The clinical electrocardiogram (ECG) is measured about 120 years. The interpretations of the ECG is an art mastered by only few. Rhythm and Interval analysis is relative reliable and well supported by the available ECG machines. However, the interpretation of the ECG waveform and where it starts to deviate from the normal waveforms is poorly defined for the clinical practice. To support the anatomical relationship of the ECG, the PathECG has been developed as part of the CineECG tool, expanding the view on the ECG. In this study normal ECG distributions were created from a public available database to enable a) visual comparison of the ‘normality’ of the ECG and PathECG and b) build a predictive model to classify an ECG as normal or abnormal. Purpose To create an objective and 3D visual comparison of an ECGs to "normal ECGs". Methods From the (Physionet) PTB-XL database (Germany) all verified ECGs with known gender were selected. From the these ECGs a median ventricular beat was automatically constructed and subsequently resampled to have a standardized number of samples (Figure: Normal ECGs on top of abnormal ECGs). These resampled ECGs were also converted to their equivalent PathECG. From the normal labeled ECGs (3124 female, 2283 male) distributions were created, representing the normal ECG for male, female or the combined group. With these distributions a percentage of ECG segments (QRS, ST, T wave) can be identified as being outside this distribution, and thus as potentially abnormal. A logistic regression model was fitted to determine the optimal outlier removal per segment for the ECG waveforms and the PathECG to classify and ECG as normal or abnormal per gender group. The performance was tested on the CPSC (Hong Kong) public available ECG database. Results The abnormal ECG data in both databases contained approximately 1/3 normal ECG, atrial and ventricular arrhythmias and 1/3 ischemia and conduction disorders. The performance (AUC) of the logistic regression model on the PTB-XL and CPSC data respectively was MALES: 87.5% - 81.5%, FEMALES: 86.7% - 83.7%, and COMBINED: 86.8%-82.9%. The visual overlay of the ECG significantly supports the identification of abnormal segments (Figure: Normal ECG distribution example). Conclusions The overlay of an ECG and PathECG on the normal distribution supports the identification and verification of abnormal ECGs. This method might increase the ability of less experienced ECG readers, like general practitioners, to identify patients that need to be transferred to a cardiologist. This method could also be used for the classification of P-waves, paediatric ECGs or ECGs in specific patient groups.Normal ECGs on top of abnormal ECGsNormal ECG distribution example

A comprehensive comparison of deep learning-based compound-target interaction prediction models to unveil guiding design principles

The evaluation of compound-target interactions (CTIs) is at the heart of drug discovery efforts. Given the substantial time and monetary costs of classical experimental screening, significant efforts have been dedicated to develop deep learning-based models that can accurately predict CTIs. A comprehensive comparison of these models on a large, curated CTI dataset is, however, still lacking. Here, we perform an in-depth comparison of 12 state-of-the-art deep learning architectures that use different protein and compound representations. The models were selected for their reported performance and architectures. To reliably compare model performance, we curated over 300 thousand binding and non-binding CTIs and established several gold-standard datasets of varying size and information. Based on our findings, DeepConv-DTI consistently outperforms other models in CTI prediction performance across the majority of datasets. It achieves an MCC of 0.6 or higher for most of the datasets and is one of the fastest models in training and inference. These results indicate that utilizing convolutional-based windows as in DeepConv-DTI to traverse trainable embeddings is a highly effective approach for capturing informative protein features. We also observed that physicochemical embeddings of targets increased model performance. We therefore modified DeepConv-DTI to include normalized physicochemical properties, which resulted in the overall best performing model Phys-DeepConv-DTI. This work highlights how the systematic evaluation of input features of compounds and targets, as well as their corresponding neural network architectures, can serve as a roadmap for the future development of improved CTI models.Scientific contributionThis work features comprehensive CTI datasets to allow for the objective comparison and benchmarking of CTI prediction algorithms. Based on this dataset, we gained insights into which embeddings of compounds and targets and which deep learning-based algorithms perform best, providing a blueprint for the future development of CTI algorithms. Using the insights gained from this screen, we provide a novel CTI algorithm with state-of-the-art performance.

Statistical monitoring applied to data science in classification: continuous validation in predictive models

PurposeThis study aims to analyze the performance of quality indices to continuously validate a predictive model focused on the control chart classification.Design/methodology/approachThe research method used analytical statistical methods to propose a classification model. The project science research concepts were integrated with the statistical process monitoring (SPM) concepts using the modeling methods applied in the data science (DS) area. For the integration development, SPM Phases I and II were associated, generating models with a structured data analysis process, creating a continuous validation approach.FindingsValidation was performed by simulation and analytical techniques applied to the Cohen’s Kappa index, supported by voluntary comparisons in the Matthews correlation coefficient (MCC) and the Youden index, generating prescriptive criteria for the classification. Kappa-based control charts performed well for m = 5 sample amounts and n = 500 sizes when Pe is less than 0.8. The simulations also showed that Kappa control requires fewer samples than the other indices studied.Originality/valueThe main contributions of this study to both theory and practitioners is summarized as follows: (1) it proposes DS and SPM integration; (2) it develops a tool for continuous predictive classification models validation; (3) it compares different indices for model quality, indicating their advantages and disadvantages; (4) it defines sampling criteria and procedure for SPM application considering the technique’s Phases I and II and (5) the validated approach serves as a basis for various analyses, enabling an objective comparison among all alternative designs.

Comparison of Friction Resistance Between Different Bracket Systems: An In Vitro Study

Introduction The efficiency of tooth movement associated with orthodontic sliding mechanics can be compromised by friction between archwire and tube or bracket slot. Orthodontic brackets and archwires are important constituents of an orthodontic appliance system. Friction is an uncontrolled variable of particular interest when continuous arch techniques are used to align and move teeth by way of sliding a tube or bracket along an arch. Aim and Objectives Comparison of frictional resistance between different bracket systems of 3M and MO brands in combination with different wires of 3M, MO, and G&amp;H brands. Evaluation of frictional resistance between two different types of bracket systems and different types of wire combinations. Materials and Methods Two types of bracket systems were used: metal bracket system and ceramic bracket system (3M and MO brands). Four different orthodontic wire alloys were used: stainless steel (SS), TMA, NiTi, and CuNiTi (3M, MO, and G&amp;H brands). A rectangular block made up of self-cure acrylic resin was designed to hold the bracket during the mechanical test. Each bracket base was glued to an acrylic block with cyanoacrylate glue. The wire segment was inserted into the bracket and was ligated passively with SS ligature wire. The bracket–wire combination was submitted to mechanical tests with a universal testing machine. One end of the acrylic block was mounted to the lower grip of the universal testing machine. The free end of the archwire was fixed to the upper grip of the universal testing machine. The friction which was generated between the wire and bracket was measured under dry conditions and at room temperature. The test wire was pulled through the bracket at a speed of 0.5 cm/min. The load cell registered a maximum force level. This data was stored in the computer and was submitted to statistical analysis, and parameter tests were applied. Results The highest mean friction resistance of 5.998 N was generated by group B2-E2 (ceramic bracket – MO + TMA archwire – MO). The lowest mean friction resistance of 2.552 N was generated by group A1-C1 (metal bracket – 3M + SS wire – 3M). There was a statistically significant difference between the friction generated by the metal bracket on SS archwire and the ceramic bracket on TMA archwire regardless of 3M or MO brand material ( p value &lt; .0001) and metal bracket ( p = .0004).

Real-Time Tracking Target System Based on Kernelized Correlation Filter in Complicated Areas.

The achievement of rapid and reliable image object tracking has long been crucial and challenging for the advancement of image-guided technology. This study investigates real-time object tracking by offering an image target based on nuclear correlation tracking and detection methods to address the challenge of real-time target tracking in complicated environments. In the tracking process, the nuclear-related tracking algorithm can effectively balance the tracking performance and running speed. However, the target tracking process also faces challenges such as model drift, the inability to handle target scale transformation, and target length. In order to propose a solution, this work is organized around the following main points: this study dedicates its first part to the research on kernelized correlation filters (KCFs), encompassing model training, object identification, and a dense sampling strategy based on a circulant matrix. This work developed a scale pyramid searching approach to address the shortcoming that a KCF cannot forecast the target scale. The tracker was expanded in two stages: the first stage output the target's two-dimensional coordinate location, and the second stage created the scale pyramid to identify the optimal target scale. Experiments show that this approach is capable of resolving the target size variation problem. The second part improved the KCF in two ways to meet the demands of a long-term object tracking task. This article introduces the initial object model, which effectively suppresses model drift. Secondly, an object detection module is implemented, and if the tracking module fails, the algorithm is redirected to the object detection module. The target detection module utilizes two detectors, a variance classifier and a KCF. Finally, this work includes trials on object tracking experiments and subsequent analysis of the results. Initially, this research provides a tracking algorithm assessment system, including an assessment methodology and the collection of test videos, which helped us to determine that the suggested technique outperforms the KCF tracking method. Additionally, the implementation of an evaluation system allows for an objective comparison of the proposed algorithm with other prominent tracking methods. We found that the suggested method outperforms others in terms of its accuracy and resilience.

When feedback backfires: Knowledge of results can impair cognitive strategy choice.

Frequently, problems can be solved in more than one way. In modern computerised environments, more ways than ever exist. Naturally, human problem solvers do not always decide for the best-performing strategy available. One underlying reason might be the inability to continuously and correctly monitor each strategy's performance. Here, we supported some of our participants' monitoring ability by providing written feedback regarding their speed and accuracy. Specifically, participants engaged in an object comparison task, which they were asked to solve with one of two strategies: an internal strategy (mental rotation) or an extended strategy (manual rotation). After receiving no feedback (30 participants), trialwise feedback (30 participants), or blockwise feedback (30 participants) in these no choice trials, all participants were asked to estimate their performance with both strategies and were then allowed to freely choose between strategies in choice trials. Results indicated that written feedback improves explicit performance estimates. However, results also indicated that such increased awareness does not guarantee improved strategy choice and that attending to written feedback might tamper with more adaptive ways inform the choice. Thus, we advise against prematurely implementing written feedback. While it might support adaptive strategy choice in certain environments, it did not in the present setup. We encourage further research that improves the understanding of how we monitor the performance of different cognitive strategies. Such understanding will help create interventions that support human problem solvers in making better choices in the future.

Comparative analysis of CNN and TNN models in environmental noise source identification

This paper presents a focused examination of environmental noise, an issue of relevance due to its implications for human health and well-being, compliant with ISO 1996-2:2017 standards. Moving beyond the traditional methodologies that primarily rely on level exceedance, our study integrates advanced machine learning techniques to address the challenges in noise source identification. With the advent of IoT Noise Monitoring Terminals, the conventional manual auditory analysis methods have become less feasible. Our research explores the application of convolutional neural networks (CNNs), a standard in environmental noise analysis, and assesses the emerging utility of Transformer Neural Network (TNN) models in this domain. The aim is to conduct an objective comparison of these models, applying them to identical datasets to determine their effectiveness in identifying noise sources. Through this analysis, the study seeks to contribute to the field of environmental acoustics by offering insights into the comparative strengths and limitations of CNN and TNN models.

Strategic approach to accelerating regional bioenergy development: Bioelectricity for emission reduction and sustainability

The western Himalayas hold significant potential for generating bioelectricity from dry pine needle biomass. This approach provides multiple benefits, including forest fire prevention, electricity generation, and emission reduction. However, despite these advantages, the growth of this sector has fallen short of expectations. The projected electricity generation potential from pine needle biomass in this region could lead to a significant annual emission reduction of 1.7 MtCO2e through forest fire prevention and an additional 0.49 MtCO2e by displacing carbon-intensive grid electricity. Regional bioenergy development plays a crucial role in the global energy transition and aligns with SDG 13, "Climate Action," and SDG 7, "Affordable and Clean Energy." By focusing on bioenergy as a renewable and accessible energy source, local and regional communities can contribute to climate action while simultaneously ensuring affordable and clean energy for their communities. Therefore, this paper employs a hybrid SWOT-AHP analysis as a strategic planning tool to achieve emission reduction targets by stimulating regional bioenergy growth. Twenty-nine SWOT factors were identified under four variables, and then the AHP technique was employed to assign priority weights to both SWOT variables and factors. Combining SWOT with AHP analysis provides quantitatively determined priorities for the factors, enabling their objective comparison. Eventually, this study offers a comprehensive perspective that leads to policy recommendations and serves as a valuable resource for relevant stakeholders, policymakers, and researchers seeking to achieve emission reduction goals through bioelectricity generation.

Application of deep learning reconstruction in abdominal magnetic resonance cholangiopancreatography for image quality improvement and acquisition time reduction

PurposeTo compare deep learning (DL)-based and conventional reconstruction through subjective and objective analysis and ascertain whether DL-based reconstruction improves the quality and acquisition speed of clinical abdominal magnetic resonance imaging (MRI). MethodsThe 124 patients who underwent abdominal MRI between January and July 2021 were retrospectively studied. For each patient, two-dimensional axial T2-weighted single-shot fast spin-echo MRI images with or without fat saturation were reconstructed using DL-based and conventional methods. The subjective image quality scores and objective metrics, including signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) of the images were analysed. An explorative analysis was performed to compare 20 patients’ MRI images with site routine settings, high-resolution settings and high-speed settings. Paired t tests and Wilcoxon signed-rank tests were used for subjective and objective comparisons. ResultsA total of 144 patients were evaluated (mean age, 62.2 ± 14.1 years; 83 men). The MRI images reconstructed using DL-based methods had higher SNRs and CNRs than did those reconstructed using conventional methods (all p < 0.01). The subjective scores of the images reconstructed using DL-based methods were higher than those of the images reconstructed using conventional methods (p < 0.01), with significantly lower variation (p < 0.01). Exploratory analysis revealed that the DL-based reconstructions with thin slice thickness and higher temporal resolution had the highest image quality and were associated with the shortest scan times. ConclusionsDL-based reconstruction methods can be used to improve the quality with higher stability and accelerate the acquisition of abdominal MRI.

An objective comparison of methods for augmented reality in laparoscopic liver resection by preoperative-to-intraoperative image fusion from the MICCAI2022 challenge

Augmented reality for laparoscopic liver resection is a visualisation mode that allows a surgeon to localise tumours and vessels embedded within the liver by projecting them on top of a laparoscopic image. Preoperative 3D models extracted from Computed Tomography (CT) or Magnetic Resonance (MR) imaging data are registered to the intraoperative laparoscopic images during this process. Regarding 3D-2D fusion, most algorithms use anatomical landmarks to guide registration, such as the liver’s inferior ridge, the falciform ligament, and the occluding contours. These are usually marked by hand in both the laparoscopic image and the 3D model, which is time-consuming and prone to error. Therefore, there is a need to automate this process so that augmented reality can be used effectively in the operating room. We present the Preoperative-to-Intraoperative Laparoscopic Fusion challenge (P2ILF), held during the Medical Image Computing and Computer Assisted Intervention (MICCAI 2022) conference, which investigates the possibilities of detecting these landmarks automatically and using them in registration. The challenge was divided into two tasks: (1) A 2D and 3D landmark segmentation task and (2) a 3D-2D registration task. The teams were provided with training data consisting of 167 laparoscopic images and 9 preoperative 3D models from 9 patients, with the corresponding 2D and 3D landmark annotations. A total of 6 teams from 4 countries participated in the challenge, whose results were assessed for each task independently. All the teams proposed deep learning-based methods for the 2D and 3D landmark segmentation tasks and differentiable rendering-based methods for the registration task. The proposed methods were evaluated on 16 test images and 2 preoperative 3D models from 2 patients. In Task 1, the teams were able to segment most of the 2D landmarks, while the 3D landmarks showed to be more challenging to segment. In Task 2, only one team obtained acceptable qualitative and quantitative registration results. Based on the experimental outcomes, we propose three key hypotheses that determine current limitations and future directions for research in this domain.

Deep endometriosis – impact on infertility, endometriosis fertility index, and reproductive prognosis (comparative study)

Introduction Deep infiltrating endometriosis (DIE) is the most severe form of endometriosis, contributes to pelvic pain syndrome, extragenital symptoms, fertility problems, and diminished reproductive prognosis for affected individuals. It is recommended to use the Endometriosis Fertility Index (EFI) to assess reproductive prognosis and conduct clinical research to compare reproductive prognosis in different forms of endometriosis. Objective Comparison of the impact of the DIE and others forms of endometriosis on EFI, patients' fertility and on reproductive prognosis to understand the management approach. Materials and methods A cohort study included 190 reproductive-age women, divided according to the #Enzian classification: the main group - 85 patients with DIE, the control group - 105 women with other forms of endometriosis. The EFI was utilized for reproductive prognosis. Pain was evaluated with Visual Analog Scale (VAS). Statistical analyses were performed using SPSS, with calculation of the Mann-Whitney U and Pearson's chi-square test (χ²). Results In main group, the frequency of infertility was 83.5% compared to the control group's 71.4% (p &gt; 0.05). The EFI in main group was 7.18±0.25 points vs the control group's 7.13±0.28 points (p = 0.852). Patients in the main group suffered from intense pelvic pain (&gt;7 points by the VAS, p &lt; 0.01), including severe dyspareunia (7.85±0.33 points vs 2.18±0.46 points in control group, p &lt; 0.01). Conclusions Our results suggest that infertility in women with DIE may be more often associated with sexual abstinence due to significant dyspareunia rather than organic impairments. Thus, EFI in patients with DIE does not reflect all aspects of infertility and has reservations, and consideration of both physical symptoms and sexual health is crucial in managing DIE to optimize fertility outcomes. These findings open the way to the feasibility of surgical treatment of DIE to improve sexual quality of life, which will reduce the need for IVF and increase the chances of spontaneous pregnancy in patients, but this conclusion requires further investigation in randomized clinical trials.

Spectral analysis comparison of pushbroom and snapshot hyperspectral cameras for in vivo brain tissues and chromophore identification.

Hyperspectral imaging sensors have rapidly advanced, aiding in tumor diagnostics for in vivo brain tumors. Linescan cameras effectively distinguish between pathological and healthy tissue, whereas snapshot cameras offer a potential alternative to reduce acquisition time. Our research compares linescan and snapshot hyperspectral cameras for in vivo brain tissues and chromophore identification. We compared a linescan pushbroom camera and a snapshot camera using images from 10 patients with various pathologies. Objective comparisons were made using unnormalized and normalized data for healthy and pathological tissues. We utilized the interquartile range (IQR) for the spectral angle mapping (SAM), the goodness-of-fit coefficient (GFC), and the root mean square error (RMSE) within the 659.95 to 951.42nm range. In addition, we assessed the ability of both cameras to capture tissue chromophores by analyzing absorbance from reflectance information. The SAM metric indicates reduced dispersion and high similarity between cameras for pathological samples, with a 9.68% IQR for normalized data compared with 2.38% for unnormalized data. This pattern is consistent across GFC and RMSE metrics, regardless of tissue type. Moreover, both cameras could identify absorption peaks of certain chromophores. For instance, using the absorbance measurements of the linescan camera, we obtained SAM values below 0.235 for four peaks, regardless of the tissue and type of data under inspection. These peaks are one for cytochrome b in its oxidized form at , two for at and , and one for water at . The spectral signatures of the cameras show more similarity with unnormalized data, likely due to snapshot sensor noise, resulting in noisier signatures post-normalization. Comparisons in this study suggest that snapshot cameras might be viable alternatives to linescan cameras for real-time brain tissue identification.

An innovative evaluation method for clinical comparative analysis of occlusal contact regions obtained via intraoral scanning and conventional impression procedures: a clinical trial

ObjectivesTo compare the occlusal contact regions (OCRs) obtained through an intraoral scanning system and conventional impression procedures via an innovative evaluation method.Materials and methodsFifteen participants with complete dentitions and stable centric occlusion were included. Three groups were created based on the technique used to obtain the OCRs of quadrant posterior teeth at the maximal intercuspal position: 100 μm articulating paper (Control), an intraoral scanner (Test 1, T1) and conventional impression procedure (Test 2, T2). OCRs of control group were digitized by the intraoral scanner, while all conventional impressions were cast and digitized by an extraoral scanner. The virtual occlusal records of the 2 test groups were obtained by buccal bite registration. The OCRs within 100 μm in the 3 groups were three-dimensionally superimposed based on the tooth surfaces and the area of OCRs (SC, ST1, ST2) was calculated. The area of overlapping OCRs (SO) between the test groups and the control group was calculated. In the two test groups, the consistency rate of OCRs (SO/SC) and the positive rate of OCRs (SO/ST) were calculated and compared. For occlusal tightness evaluation, the mean occlusal clearances (OC) as well as minimum OC between the upper and lower models were calculated and compared.ResultsThe consistency rate of OCRs was 0.73 ± 0.17 for T1 group and 0.23 ± 0.13 for T2 group (p < 0.001). The positive rate of OCRs was 0.67 ± 0.15 for T1 group and 0.56 ± 0.23 for T2 group (p = 0.143). The mean OC was 51.32 ± 16.04 μm for T1 group and 68.20 ± 18.15 μm for T2 group (p = 0.024). The minimum OC was − 61.74 ± 35.38 μm for T1 group and 4.09 ± 27.15 μm for T2 group (p < 0.001).ConclusionsFor obtaining occlusal records in the quadrant posterior region, the tested intraoral scanning system was more reliable for recording occlusal contact regions and showed higher occlusal tightness compared with conventional impression procedures.Clinical relevance(1) The evaluation method can assist clinicians in making more objective analysis and comparisons among different sources of virtual occlusal records. (2) Occlusal tightness is a key and indispensable indicator in the evaluation of virtual occlusal records, and it can be quantified by measuring the occlusal clearance utilizing the current evaluation method.

‘It is absolutely unnecessary, even detrimental, to embellish the façades’

Following World War I, Belgium faced a severe housing crisis, necessitating a comprehensive reform of social housing policy. Established in 1919, the National Society for Cheap Housing (Nationale Maatschappij voor Goedkope Woningen en Woonvertrekken, nmgww) aimed not only to repair material damage but also to address new social and societal demands. However, financial resources were limited, while there was also a severe shortage of (traditional) building materials and skilled labour. Progressive architects attempted to create a new, socially engaged architecture with a modernist vocabulary through the nmgww. They also advocated for the application of alternative building methods that had the added advantage of being financially favourable. The lack of expertise and experience with these alternative methods prompted the nmgww to set up an experimental project at Het Rad in Anderlecht in 1920. It entailed the construction of some sixty houses, employing eighteen different building systems. While most of these systems used concrete blocks, three utilized a prefabricated skeleton, and two opted for cast-in-situ concrete using monolithic casting systems. Nearly all utilized ‘lean concrete’, a type of concrete with a low cement content. Furthermore, in most cases part of the aggregate was replaced with industrial waste products to reduce costs and improve thermal properties. The intention was to perform an extensive evaluation and objective comparison of the different building systems. Yet even before the experiments had been concluded, the nmgww started to actively promote the German casting system Non Plus. For example, it invited local housing associations to participate in a study trip to Merseburg near Berlin to familiarize themselves with the system. Successfully, as it turns out as the system was subsequently used in the garden suburbs of Klein Rusland in Zelzate (1920-1923) and La Cité Moderne in Sint-Agatha-Berchem (1922-1925). The two districts were designed respectively by the architects Huib Hoste and Victor Bourgeois in a modernist idiom. The literature often refers to the economic benefits of the Non Plus system and to the impact of construction techniques on the aesthetics of these garden suburbs. However, in-depth research shows that the relationship between economic, technical and aesthetic aspects is not so straightforward: concrete was not necessarily cheaper than brick, while the plaster exterior often concealed a variety of systems. Moreover, both garden suburbs were initially designed in brick, indicating that there is no causal link between the material and the design language. It was not long, however, before the alternative building systems in lean concrete, particularly the monolithic casting systems, were abandoned. After 1926, as a result of political power shifts, the focus switched to small-scale projects and alternative building systems lost their scale-based economic advantage. Yet the experiment with alternative building practices, however brief, was an important phase in Belgian architectural and construction history. Projects like Het Rad and the modernist garden suburbs in cast-in-situ concrete show the interrelationship between societal, social, political, cultural and economic ambitions on the one hand, and the evolution of building culture on the other.

An unbiased comparison of immunoglobulin sequence aligners.

Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is critical for our understanding of the adaptive immune system's dynamics in health and disease. Reliable analysis of AIRR-seq data depends on accurate rearranged immunoglobulin (Ig) sequence alignment. Various Ig sequence aligners exist, but there is no unified benchmarking standard representing the complexities of AIRR-seq data, obscuring objective comparisons of aligners across tasks. Here, we introduce GenAIRR, a modular simulation framework for generating Ig sequences alongside their ground truths. GenAIRR realistically simulates the intricacies of V(D)J recombination, somatic hypermutation, and an array of sequence corruptions. We comprehensively assessed prominent Ig sequence aligners across various metrics, unveiling unique performance characteristics for each aligner. The GenAIRR-produced datasets, combined with the proposed rigorous evaluation criteria, establish a solid basis for unbiased benchmarking of immunogenetics computational tools. It sets up the ground for further improving the crucial task of Ig sequence alignment, ultimately enhancing our understanding of adaptive immunity.