Search Results (13)

Climate-induced ocean warming poses a major threat to marine invertebrate reproduction, including the sea urchin Paracentrotus lividus, a species of considerable ecological, economic, and scientific interest. Its gonads, highly valued as a culinary delicacy, support local fisheries and aquaculture industries, making reproductive health a critical factor for both conservation and commercial viability. The present study reported the effects of elevated seawater temperatures, mimicking marine heatwave (MHW) conditions, on gonadal maturation and fertilization success on P. lividus. Here, adult specimens at the mature stage of gametogenesis were exposed to control (18 °C) and elevated temperature regimes (24 °C) over a six-week period, and key reproductive metrics were assessed, including histological analysis. Morphological analysis showed very evident gonadal retraction, nearly devoid of germ cells, both for males and females, with a significant decrease in the gonadal index. In addition, histological analysis revealed consistent damage to the gonads, with a significantly increase in histopathological index in specimens kept at 24 °C. These findings reinforce the temperature sensitivity of P. lividus reproduction, suggesting that recurrent heatwaves could severely impair its reproductive output and population dynamics with potential cascading effects on benthic community structure in a long-term ocean warming predicted to intensify. Full article

The Research Integrity Risk Index (RI²), introduced as a tool to identify universities at risk of compromised research integrity, adopts an overly reductive methodology by combining retraction rates and delisted journal proportions into a single, equally weighted composite score. While its stated aim is to promote accountability, this commentary critiques the RI² index for its flawed assumptions, lack of empirical validation, and disproportionate penalization of institutions in low- and middle-income countries. We examine how RI² misinterprets retractions, misuses delisting data, and fails to account for diverse academic publishing environments, particularly in Indonesia, where many high-performing universities are unfairly categorized as “high risk” or “red flag.” The index’s uncritical reliance on opaque delisting decisions, combined with its fixed equal-weighting formula, produces volatile and context-insensitive scores that do not accurately reflect the presence or severity of research misconduct. Moreover, RI² has gained significant media attention and policy influence despite being based on an unreviewed preprint, with no transparent mechanism for institutional rebuttal or contextual adjustment. By comparing RI² classifications with established benchmarks such as the Scimago Institution Rankings and drawing from lessons in global development metrics, we argue that RI², although conceptually innovative, should remain an exploratory framework. It requires rigorous scientific validation before being adopted as a global standard. We also propose flexible weighting schemes, regional calibration, and transparent engagement processes to improve the fairness and reliability of institutional research integrity assessments. Full article

Background: The tubular retractor-assisted minimally invasive parafascicular approach (trMIPS) is a transsulcal approach to deep-seated brain tumours. It is a safe surgical approach but its impact on the microvascular dynamics of the retracted cortex and its clinical implications are unknown. Methods: This was a single-centre prospective study including patients with deep-seated brain tumours operated on with a trMIPS (BrainPath Nico System^©). All patients underwent pre- and post-cannulation indocyanine green study using a FLOW 800 module in a KINEVO Zeiss^© microscope. Speed, delay, time-to-peak (TtP) rise-in-time and cerebral blood flow index (CBFI) metrics were assessed. Results: Thirty-five patients were included, with 144 regions-of-interest (ROIs) selected. The majority of patients were diagnosed with glioblastoma (51.43%), and 37.14% of patients had a preoperative focal neurological deficit (FND) at presentation. A ROI-based analysis concluded that an increase in speed and CBFI was related with a worse neurological outcome when comparing the pre- and post-brain cannulation assessments (speed: deterioration = 43.12 ± 80.60% versus stable = −14.51 ± 57.80% versus improvement = 6.93 ± 31.33%, p < 0.0001; CBFI: deterioration = 50.40 ± 88.17% versus stable = −2.70 ± 67.54% versus improvement = −38.98 ± 26.17%, p = 0.0005). These findings were reproducible in a combined-ROI per patient analysis and confirmed after adjustment for confounding. Conclusion: Microvascular flow dynamics impact trMIPS outcomes as an increase in the speed and CBFI after decannulation was related with worse neurological outcome. Full article

The value of ecosystem services (ESV) serves as a crucial metric for assessing the cost-effectiveness of ecosystems and evaluating their economic worth. Predicting the evolution of ESV across various land uses under different scenarios is essential for maintaining ecological stability and fostering sustainable developm0ent. Utilizing land use change data combined with the PLUS predictive model and ecosystem service value equivalence techniques, this study analyzes the spatiotemporal patterns and underlying drivers of ESV in Yuzhong County, China. The results indicate that the overall ESV distribution exhibits a “fragmented northeast, clustered southwest” pattern, dominated by high-high and low-low clustering. Among the driving factors, elevation exerts the greatest influence on ESV, followed by precipitation and population density, while slope contributes least. Under natural development scenarios, the ESV remains relatively stable compared to the base year of 2020. In contrast, the farmland protection scenario effectively preserves the ESV associated with cultivated land. However, the economic development scenario leads to a significant decline in the overall ESV, with a retraction of high-value areas and an expansion of low-value regions. These insights provide a fresh perspective for analyzing the factors influencing ESV and for conducting multi-scenario predictions, thereby aiding in the development of ecological resource conservation and landscape ecological risk prevention strategies in the study region. Full article

This paper presents a cost-effective approach for automated surface quality measurement in reamed bores. The study involved drilling 4000 holes into 42CrMo S4V steel, of which 3600 underwent subsequent reaming. Utilizing a CNC-controlled gantry coupled with a mobile roughness measurement device through a compliant mechanism, surface data of every bore were efficiently gathered and processed. Additionally, analytical methods are presented that extend beyond standardized, aggregated metrics. We propose the evaluation of retraction grooves by using autocovariance. In addition, the correlation between the phase position of the waviness profile and the positional deviation of the bore is analyzed. The position deviation is also associated with bending moments that occur during reaming using a sensory tool holder. Furthermore, a 360-degree surface scan is presented to visually inspect the retraction groove. This approach aims to enhance understanding of the reaming process, ultimately improving bore quality, reducing component rejects, and extending tool lifespan. Full article

This paper proposes a new strategy for a collision avoidance system leveraging time-to-collision (TTC) metrics for handling cut-in scenarios, which are particularly challenging for autonomous vehicles (AVs). By integrating deep learning with TTC calculations, the system predicts potential collisions and determines appropriate evasive actions compared to traditional TTC-based approaches. The methodology is validated through extensive simulations, demonstrating a significant improvement in collision avoidance performance compared to traditional TTC-based approaches. By integrating deep learning models with TTC calculations, the system predicts potential collisions and determines appropriate evasive actions. The use of the Gaussian model to contributes to time-to-collision (TTC) analysis by providing a probabilistic framework to quantify collision risk under uncertainty. It calculates the likelihood that TTC will fall below a critical threshold (TTC_crit), indicating a potential collision. By modeling input variations—such as sensor inaccuracies, fluctuating vehicle velocity, and unpredictable driving behavior—as a Gaussian distribution, the system can handle real-world uncertainties more effectively. This enables continuous, real-time risk prediction, allowing for dynamic and adaptive collision avoidance decisions. The Gaussian approach enhances the robustness of TTC-based systems by improving their ability to predict and prevent collisions in uncertain driving conditions. Full article

In this paper, we examine the role played by topology, and some specific boundary conditions as well, on the physics of a higher-dimensional black hole. We analyze the line element of a five-dimensional non-extremal Reissner–Nordström black hole to obtain a new family of subspaces that are types of strong retractions and deformations, and then we extend these results to higher dimensions in order to deduce the relationship between various types of transformations. We also study the scalar field perturbations in the background under consideration and obtain an analytical expression for the quasibound state frequencies by using the Vieira–Bezerra–Kokkotas approach, which uses the polynomial conditions of the general Heun functions, and then we discuss the stability of the system and present the radial eigenfunctions. Our main goal is to discuss the physical meaning of these mathematical applications in such higher-dimensional effective metric. Full article

The majority of people in the modern biosphere struggle with depression as a result of the coronavirus pandemic’s impact, which has adversely impacted mental health without warning. Even though the majority of individuals are still protected, it is crucial to check for post-corona virus symptoms if someone is feeling a little lethargic. In order to identify the post-coronavirus symptoms and attacks that are present in the human body, the recommended approach is included. When a harmful virus spreads inside a human body, the post-diagnosis symptoms are considerably more dangerous, and if they are not recognised at an early stage, the risks will be increased. Additionally, if the post-symptoms are severe and go untreated, it might harm one’s mental health. In order to prevent someone from succumbing to depression, the technology of audio prediction is employed to recognise all the symptoms and potentially dangerous signs. Different choral characters are used to combine machine-learning algorithms to determine each person’s mental state. Design considerations are made for a separate device that detects audio attribute outputs in order to evaluate the effectiveness of the suggested technique; compared to the previous method, the performance metric is substantially better by roughly 67%. Full article

Obtaining the size of the maxillary anterior teeth when performing an esthetic smile rehabilitation can be a difficult task. Metrics based on dental proportions to assist in the process are required. This study aimed to evaluate the lower facial third proportions i.e., the interalar, interphiltral, and intercommisural distance with dental proportions in predicting maxillary anterior teeth width in Pakistani citizens. This analytical study was conducted on 230 participants. Front face and retracted smile photographs were captured for all the participants, followed by maxillary impression making. The cast was then converted to 3D models for analysis. The data were entered into SPSS-25. Descriptive statistics were carried out for frequency, mean, standard deviation, and percentage calculation of gender, teeth widths, horizontal mid facial proportions, and age of the participants. Independent t-test was applied for analysis of gender and arch side disparity. Regression analyses were performed to analyze the relationship between independent variables (gender, age, weight, and height) and dependent variables (horizontal facial proportion, dental proportion). A p-value of ≤0.05 was considered statistically significant. The interphiltral distance (IPLD) modified with Preston proportion (PRP) showed no significant difference with combined central incisor width, whereas a significant difference was found with golden proportion (GP), 70% recurrent esthetic dental (RED) proportion, and golden percentage (GM) modification. However, the interalar (IAD) and intercommisural distance (ICoD) modified with dental proportions showed a significant difference with maxillary anterior teeth width. The width of maxillary anterior teeth determined by plaster dental cast and 3D dental cast showed no significant difference. The ICoD, IAD, and IPLD could not be used to determine combined central incisor and intercanine width directly. The interphiltral distance modified with Preston proportion is a reliable method to predict combined central incisor width in the population studied. There was a significant difference in gender disparity when ICD, IAD, and IPLD were modified with dental proportions, except in the case of IPLD by the Preston proportion group. The golden proportion, 70% RED proportion, and golden percentage by lower facial third facial proportions are not reliable methods to predict maxillary anterior teeth width. Full article

The pasturelands areas of Brazil constitute an important asset for the country, as the main food source for the world’s largest commercial herd, representing the largest stock of open land in the country, occupying ~21% of the national territory. Understanding the spatio-temporal dynamics of these areas is of fundamental importance for the goal of promoting improved territorial governance, emission mitigation and productivity gains. To this effect, this study mapped, through objective criteria and automatic classification methods (Random Forest) applied to MODIS (Moderate Resolution Imaging Spectroradiometer) images, the totality of the Brazilian pastures between 2000 and 2016. Based on 90 spectro-temporal metrics derived from the Red, NIR and SWIR1 bands and distinct vegetation indices, distributed between dry and wet seasons, a total of 17 pasture maps with an approximate overall accuracy of 80% were produced with cloud-computing (Google Earth Engine). During this period, the pasture area varied from ~152 (2000) to ~179 (2016) million hectares. This expansion pattern was consistent with the bovine herd variation and mostly occurred in the Amazon, which increased its total pasture area by ~15 million hectares between 2000 and 2005, while the Cerrado, Caatinga and Pantanal biomes showed an increase of ~8 million hectares in this same period. The Atlantic Forest was the only biome in which there was a retraction of pasture areas throughout this series. In general, the results of this study suggest the existence of two relevant moments for the Brazilian pasture land uses. The first, strongly supported by the opening of new grazing areas, prevailed between 2000 and 2005 and mostly occurred in the Deforestation Arc and in the Matopiba regions. From 2006 on, the total pasture area in Brazil showed a trend towards stabilization, indicating a slight intensification of livestock activity in recent years. Full article

Currently, there is no manual blind control guideline used consistently throughout the energy modeling community. This paper identifies and compares five manual blind control algorithms with unique control patterns and reports blind occlusion, rate of change data, and annual building energy consumption. The blind control schemes detailed here represent five reasonable candidates for use in lighting and energy simulation based on difference driving factors. This study was performed on a medium-sized office building using EnergyPlus with the internal daylight harvesting engine. Results show that applying manual blind control algorithms affects the total annual consumption of the building by as much as 12.5% and 11.5% for interior and exterior blinds respectively, compared to the Always Retracted blinds algorithm. Peak demand was also compared showing blind algorithms affected zone load sizing by as much as 9.8%. The alternate algorithms were tested for their impact on American Society of Heating, Refrigeration and Air-Conditioning Engineers (ASHRAE) Guideline 14 calibration metrics and all models were found to differ from the original calibrated baseline by more than the recommended ±15% for coefficient of variance of the mean square error (CVRMSE) and ±5% for normalized mean bias error (NMBE). The paper recommends that energy modelers use one or more manual blind control algorithms during design stages when making decisions about energy efficiency and other design alternatives. Full article