Cement production requires a significant amount of energy and natural resources, severely impacting the environment due to harmful gas emissions. Coal Bottom Ash (CBA) and Coal Boiler Slag (CBS), byproducts of coal-fired power plants, have pozzolanic properties. CBA and CBS can be mechanically ground to obtain Ground Coal Bottom Ash (GCBA) or Ground Coal Bottom Slag (GCBS), which can potentially replace cement in concrete, reducing waste in landfills, benefit the economy, preserving natural resources, and reducing health hazards. This study was performed to determine the optimum amount of GCBA and GCBS that can replace cement in concrete. The fresh, mechanical, and durability properties of the concrete containing GCBA were compared to a control mix consisting of 100% Portland cement. The optimum amount of cement replaced with GCBA and GCBS was 10% and 5%, respectively, based on compressive strength. The GCBA-based concrete's tensile strength, modulus of elasticity, and durability properties were better than the control. The compressive strength of the GCBA and GCBS-based mortars increased with an increase in fineness. GCBA and GCBS fineness should be within the limit recommended in the ASTM C618 standard to enhance concrete or mortar properties.

This literature review paper delves into the synergies between Climate-Smart Agriculture (CSA) and the effective management of food losses. With the escalating challenges posed by climate change and the pressing need to address food security concerns, the intersection of these two critical domains becomes paramount for sustainable agricultural practices. The review explores existing research on the implementation of climate-smart agricultural techniques and their impact on mitigating food losses throughout the agricultural value chain. The paper synthesizes findings related to climate-resilient crop varieties, precision farming, water-use efficiency, and sustainable soil management, highlighting their contributions to reducing post-harvest losses and enhancing overall food security. In addition to summarizing current knowledge, this paper identifies gaps in the literature and proposes avenues for future research. This review serves as a foundation for researchers, policymakers, and practitioners seeking to contribute to the advancement of climate-smart agriculture and the reduction of food losses, paving the way for a more sustainable and resilient global food system.

Last Chance Tourism (LCT) is an increasingly popular phenomenon whereby tourists seek encounters with vanishing landscapes, cultures, and endangered species. However, there are concerns that it is not sufficiently ecologically informed, has a large carbon footprint, and may put further pressure on vulnerable ecosystems and communities. The Arctic has emerged as a major global frontier for LCT, and at the same time is at the forefront of disruptive and accelerating climate change. Here a review of important LCT literature is combined with a review of key insights from the concept of Ecological Grief, which calls for explicitly mourning the losses of formerly ecologically rich landscapes, species diversity, and traditional knowledge. While there is currently insufficient engagement with grief and mourning in LCT, Ecological Grief can provide a new research focus as well as a pathway to share empathy, concern, and sorrow between scientists, communities, and visitors—thereby offering an alternative way to critically reflect upon our connections with the vanishing cryosphere in the Anthropocene.

Mutations in p53 and KRAS are seen in most cases of colon cancer. The impact of these mutations on signaling pathways related to cancer growth has been studied in depth, but relatively less is known on their effects on amino acid transporters in cancer cells. This represents a significant knowledge gap because amino acid nutrition in cancer cells profoundly influences macropinocytosis and ferroptosis, two processes with opposing effects on tumor growth. Here we used isogenic colon cancer cell lines to investigate the effects of p53 loss and KRAS activation on two amino acid transporters relevant to macropinocytosis (SLC38A5) and ferroptosis (SLC7A11). Our studies show that the predominant effect of p53 loss is to induce SLC7A11 with resultant potentiation of antioxidant machinery and protection of cancer cells from ferroptosis whereas KRAS activation induces not only SLC7A11 but also SLC38A5, thus offering protection from ferroptosis as well as improving amino acid nutrition in cancer cells via accelerated macropinocytosis. Niclosamide, an FDA-approved anti-helminthic, blocks the functions of SLC7A11 and SLC38A5, thus inducing ferroptosis and suppressing macropinocytosis with resultant effective reversal of tumor-promoting actions of oncogenic mutations in p53 and KRAS. These findings underscore the potential of this drug in colon cancer treatment.

Research indicates that brain region-specific synapse loss and dysfunction are early hallmarks and stronger neurobiological correlates of cognitive decline in Alzheimer’s disease (AD) than counts of amyloid plaques, neurofibrillary tangles, and neuronal loss. Even though the precise mechanisms underlying increased synaptic pruning in AD are still unknown, it has been confirmed that dysregulation of the balance between complement activation and inhibition is a crucial driver of pathology. The complement includes three distinct activation mechanisms, with activation products C3a and C5a, potent inflammatory effectors, and a membrane attack complex (MAC), leading to cell lysis. Besides pro-inflammatory cytokines, dysregulated complement proteins released by activated microglia bind to amyloid β at synaptic regions and cause microglia to engulf synapses. Additionally, research indicating that microglia-removed synapses are not always degenerating, and that suppression of synaptic engulfment can repair cognitive deficits point to an essential opportunity for intervention that can prevent the loss of intact synapses. In this study, we focus on the latest research on the role and mechanisms of complement-mediated microglial synaptic pruning at different stages of AD to find the right targets that could interfere with complement dysregulation and be relevant for therapeutic intervention at the early stages of the disease.

Sweat rate and electrolyte losses have a large inter-individual variability, a personalized approach to hydration can overcome this issue to meet an individual’s needs. This study aimed to investigate the effects of personalized hydration strategy (PHS) on fluid balance and intermittent exercise performance. Twelve participants conducted 11 laboratory visits including a VO2max test and two 5-day trial arms under normothermic (NOR) or hyperthermic (HYP) environmental conditions. Each arm began with 3-day of familiarization exercise following by two random exercise trials with a either PHS or control (CON). Then, participants crossed-over to the second arm for: NOR+PHS, NOR+CON, HYP+PHS, and HYP+CON. The PHS was prescribed according to participants’ fluid and sweat sodium losses. CON drank ad-libitum of commercially-available electrolyte solution. Exercise trials consisted of two phases: 1) 45min constant workload; 2) high-intensity intermittent exercise (HIIT) until exhaustion. PHS had a significantly greater fluid intake compared to CON. HYP+CON produced the lowest sweat sodium concentration. HYP+PHS had a lower thirst perception and a longer HIIT compared to HYP+CON. Thus, PHS reinforces fluid intake and successfully optimizes hydration status, regardless of environmental conditions. PHS may be or is an important factor to preventing negative physiological consequences during high-intensity exercise in the heat.

This paper studies the maximum reliability of multi-hop relay UAV, in which UAV provides wireless services for remote users without direct communication link on the ground as a coded cooperative relay. In this paper, the analytical expressions of total power loss and total bit error rate are derived as reliability measures. Firstly, based on the environmental statistical parameters, a LOS probability model is proposed. Then the problem of minimizing the bit error rate of static and mobile UAVs is studied. The goal is to minimize the total bit error rate by jointly optimizing the height, elevation, power and path loss, and subject to the maximum allowable path loss con-straints, transmission power allocation constraints and UAV height and elevation constraints. At the same time the total path loss is minimized to achieve maximum ground communication cov-erage. However, the formulated joint optimization problem is non-convex and generally difficult to solve. Therefore, we decomposed the problem into two subproblems and proposed an effective joint optimization iteration algorithm. Finally, the simulation results are given, and the analysis shows that the optimal height of different reliability measures is slightly different, and using the mobility of UAVs can improve the reliability of communication performance.

This study addresses the implementation of the International Financial Reporting Standard 9 (IFRS 9) in the European Union as of January 1, 2018, replacing the International Accounting Standard 39 (IAS 39) to introduce a new model for recognizing Loan Loss Provisions (LLP) based on Expected Credit Loss (ECL). This model responds to criticisms of the former Incurred Credit Loss (ICL) system for its inability to reflect credit losses in a timely manner, potentially exacerbating the effects of financial crises (Bushman & Williams, 2015; Gebhardt & Novotny-Farkas, 2011). The study focuses on the effects of adopting the ECL model on the level of Loan Loss Allowances (LLA) in loans, own equity, and the Common Equity Tier 1 (CET1) ratio across 13 Portuguese commercial banks. A mean comparison test is used to evaluate scenarios before and after the application of the ECL model, highlighting the importance of regulator actions and the adequacy of loss recognition policies, including the effects of Regulation (EU) 2017/2395 of December 12. The results obtained demonstrate significant negative impacts on the net values of loans, own equity, and the CET1 ratio upon adopting the IFRS 9 ECL model, due to the widespread increase in LLAs.

A large core size and bending resistance are very important properties of mid-infrared energy transfer fibers, but large core sizes usually lead to a deterioration of bending properties. A negative-curvature nested node-free anti-resonant hollow-core fiber (AR-HCF) based on quartz is proposed. It was made by adding a nested layer to a previous AR-HCF design to provide an additional anti-resonance region while keeping the gap between adjacent tubes strictly correlated to the core diameter to produce a node-free structure. These features improve the fiber’s bending resistance while achieving a larger core diameter. The simulation results show that the radial air-glass anti-resonant layer is increased by the introduction of the nested anti-resonant tube, and the weak interference overlap between the fiber core and the cladding mode is reduced, so the fiber core’s limiting loss and the sensitivity to bending are effectively reduced. When the capillary wall thickness t of the fiber is 0.71 μm, the core diameter D is 70 μm, the ratio of the inner diameter of the cladding capillary to the core diameter d/D is 0.62, and the diameter of the nested tube is d0=29 μm, the fiber has a lower limiting loss at the wavelength of 2.79 μm, and the limiting loss is 3.28×10-4 dB/m. At the same time, the optimized structure also has good bending resistance. When the bending radius is 30 mm, the bending loss is only 4.72×10-2 dB/m. To our knowledge, this is the first research to achieve an anti-bending low-loss micro-structure hollow fiber with a bending radius of less than 30 mm in the 2.79 μm band. An anti-bending low-loss anti-resonant hollow-core fiber with this structure constitutes a reliable choice for the light guiding system of a 2.79 μm band erbium laser therapy instrument.

The magnetic properties of 0.10 mm ultra-thin grain-oriented (UTGO) silicon steel and Fe-based amorphous (FBA) alloy under sinusoidal excitation were measured experimentally, and the magnetic field strength and iron loss of the two materials under different frequencies and magnetic densities were obtained. Based on the measured data, the magnetization and loss characteristics of the two materials were analyzed and compared. Furthermore, two Epstein square ring models of the same specification and different materials were designed, and the reliability of the models was verified. Then, the electromagnetic characteristics of the two Epstein square ring models at higher and lower frequencies were calculated by using the finite element method, and the iron loss was obtained and compared. The results show that the FBA alloy has good application characteristics at low frequency and low power, and the 0.10 mm UTGO silicon steel has good application characteristics at high frequency and high power. This research can provide important data basis to promote the application of these two materials in new energy equipment.

This paper presents a comprehensive investigation into the applicability and performance of two prominent growth models, namely the Verhulst model and the Montroll model, in the context of modeling tumor cell growth dynamics. Leveraging the power of Physics-Informed Neural Networks (PINNs), we aim to assess and compare the predictive capabilities of these models against experimental data obtained from the growth patterns of tumor cells. We employ a dataset comprising detailed measurements of tumor cell growth to train and evaluate the Verhulst and Montroll models. By integrating PINNs, we not only account for experimental noise but also embed physical insights into the learning process, enabling the models to capture the underlying mechanisms governing tumor cell growth. Our findings reveal the strengths and limitations of each growth model in accurately representing tumor cell proliferation dynamics. Furthermore, the study sheds light on the impact of incorporating physics-informed constraints on the model predictions. The insights gained from this comparative analysis contribute to advancing our understanding of growth models and their applications in predicting complex biological phenomena, particularly in the realm of tumor cell proliferation.

This study was conducted to determine the role of pre-operative 2 weeks use of Finasteride in reducing intra-operative blood loss in patients undergoing monopolar TURP. Number of enrolled patients were 120, on the basis of inclusion criteria. Patients who were candidates of monopolar TURP were given 5mg Finasteride for 2 weeks before the surgery. On the 13th day of medicine, they got admitted in ward and prepared for surgery. During surgery intra-operative irrigation fluid was measured and gathered, then tested for Hemoglobin and the blood loss was calculated with equation formula. Blood loss evaluation was done on the basis of irrigation fluid, hemoglobin in irrigation fluid, preoperative hemoglobin and resected tissue weight. Significant reduction in blood loss was observed in interventional group as compared to the control group. Mean blood loss was 296ml in Group-A and 370ml in Group-B while blood loss per gram was 11.7ml/g in Group-A and 14.7 ml/g in Group-B. Mean operative time was measured 42 minutes in Group-A and 49 minutes in Group-B. This research proclaims a clear-cut supremacy of pre-operative use of Finasteride for two weeks. It significantly reduces intraoperative blood loss and blood loss per gram in patients undergoing monopolar TURP.

The agricultural sector is amidst an industrial revolution driven by the integration of sensing, communication, and artificial intelligence (AI). Within this context, the internet of things (IoT) takes center stage, particularly in facilitating remote livestock monitoring. Challenges persist, particularly in effective field communication, adequate coverage, and long-range data transmission. This study focuses on employing LoRa communication for livestock monitoring in mountainous pastures in the north-western Alps in Italy. The empirical assessment tackles the complexity of predicting LoRa path loss attributed to diverse land-cover types, highlighting the subtle difficulty of gateway deployment to ensure reliable coverage in real-world scenarios. Moreover, the high expense of densely deploying end devices makes it difficult to fully analyze LoRa link behavior, hindering a complete understanding of networking coverage in mountainous environments. This study aims to elucidate the stability of Lora link performance in spatial dimensions and ascertain theextent of reliable communication coverage achievable by gateways in mountainous environments. Additionally an innovative deep learning approach was proposed to accurately estimate path loss across challenging terrains. Remote sensing contributes to land-cover recognition, while Bidirectional Long Short-Term Memory (Bi-LSTM) enhances the path loss model’s precision. Through rigorous implementation and comprehensive evaluation using collected experimental data, this deep learning approach significantly curtails estimation errors, outperforming established models. Our results demonstrate that our prediction model outperforms established models with a reduction in estimation error to less than 5dB, marking a 2X improvement over state-of-the-art models. Overall, this study signifies a substantial advancement in IoT-driven livestock monitoring, presenting robust communication and precise path loss prediction in rugged landscapes.

This work proposes a hollow-core photonic crystal fiber-based edible oil sensor in the terahertz (THz) range (e.g., 1.0THz ≤ f ≤ 3.0THz) and different sensing characteristics are numerically analyzed. The suggested sensor’s performance was assessed by means of COMSOL Multiphysics, a commercial program that uses the finite element approach. The computational results indicate that the relative sensitivity is 85.591%, 84.648%, 82.625%, 82.683%, and 79.161%, respectively, at f = 2.2 THz, for several types of sunflower oil, mustard oil, coconut oil, olive oil and palm oil; and the corresponding effective areas are 7.22×10-8 um2, 7.09×10-8 um2, 6.83×10-8 um2,7.09×10-8 um2, 6.5231 ×10-8 um2. In addition, the effective material loss for sunflower oil, muster oil, coconut oil, olive oil, and palm oil has been found to be 0.02561 cm-1, 0.027054 cm-1, 0.030322 cm-1, 0.028854 cm-1 ,0.035427cm-1 respectively. Moreover, the proposed sensor also has low confinement loss are 1.55×10-8 dB/m, 1.63×10-8 dB/m, 1.31×10-8 dB/m, 1.99×10-8 dB/m, 4.0345×10-8 dB/m.This proposed sensor can be fabricated using extrusion and 3D-printing technologies, and due to its augmented detecting capabilities, it can be a vital part of oil sensing devices implemented in real life such as industry fields.

Pavement crack detection is one of the key links in highway pavement maintenance management. In the current road crack detection, the network model easily ignores the shallow geometric features of cracks and cannot extract the key feature information of cracks. Aiming at the above problems, an EC-YOLOX network model is proposed. The CFPN is constructed to cross-fuse different scale features to solve the feature scale invariance. In the strengthen feature extraction layer, ECANet is fused to enhance the ability to pay attention to key information. The WEIoU loss function is proposed, which assigns different penalty terms to the target box in the vertical and horizontal directions. In terms of data, geometric distortion constraint correction is performed on the single-point perspective pavement image. The experimental data show that the accuracy of EC-YOLOX on the self-built data set reaches 76.34% mAP@0.5, which is 4.45% higher than that of YOLOX. The loss curve of EC-YOLOX is smoother than that of YOLOX, and the minimum training loss value is 2.136, which is 0.648 lower than the minimum loss value 2.784 of YOLOX. Many experiments have verified the effectiveness of EC-YOLOX in improving the detection effect in pavement crack detection.

Vision impairment may delay responses to hazards when driving. In a proof-of-concept driving simulator study, we evaluated a hazard warning device designed for vision impaired drivers. Three groups participated: 11 persons with central vision loss (CVL; median age 60 years), 12 with homonymous field loss (HFL; 52 years) and 11 with normal vision (NV; 60 years). CVL is characterised by impaired visual acuity and contrast sensitivity while HFL is a loss of vision in the same half of the visual field (blind side) in both eyes. Participants completed drives with and without the device which gave a directional vibro-tactile warning for an approaching pedestrian hazard when collision risk exceeded a pre-defined threshold. Warnings significantly (p< 0.001) reduced brake response times for CVL (∆= 0.54s) and HFL (∆= 0.30s), but not NV participants. For HFL participants, the reduction was greater (p = 0.02) for hazards on the blind (∆= 0.57s) than seeing side (∆= 0.10s). The warnings significantly reduced collision rates for CVL participants from 11 to 0% (all hazards) and for HFL participants from 30 to 1.7% (blind side hazards). Thus, hazard warnings may be beneficial in improving safety of vision impaired drivers; further research is warranted.

Quantum cryptography revolutionizes secure information transfer, providing defense against both quantum and classical computational attacks. The primary challenge in extending the reach of quantum communication comes from the exponential decay of signals over long distances. Addressing this challenge, we have developed Quantum-protected Control-based Key Distribution (QCKD), overcoming transmission range limitations by monitoring signal leakages and rendering leaked quantum states significantly non-orthogonal. This paper reports on the experiments with the QCKD, conducted over a 1,707 km fiber line. We demonstrate advancements in critical components of the protocol, showing its remarkable scalability and adaptability for extended distances and multi-user configurations.

Abstract—Hydraulic switching actuators are high efficiency, fast response, and low cost solutions for hydraulic control systems. One of the challenging problems is throttling losses during valve transitions. Previously the authors proposed a zero-flowrate switching method to reduce throttling energy loss of the switching valve, where a hydraulic resonator is applied to make the flowrates through the lines approaching zero before the valves are switched off. The major challenge of this approach is fast switching valves whose transition times are less than 2 ms. In this paper, an improved zero-flowrate switching method is presented. It utilizes the capacity with independent inlet/outlet ports to regulate flowrates through the lines. Models of capacity applied in a simple line with different pressure signals are developed to explore characteristics of the capacity, based on which a complete actuation system is developed. In the complete model, resistance and inductance are optimized to achieve desired flowrate response. The improved zero-flowrate switching method reduces throttling energy losses by 99.945% compared to a hard switching system. The simulation results demonstrated that the improved zero-flowrate switching method performs as expected in the design condition. A capacity with proper volume is able to regulate flowrates through all the lines to zero, with the help of appropriate resistance and inductance. Compared to previous zero-flowrate switching method, the novel strategy allows slower switching valves applied in hydraulic actuation systems and achieves better efficiency performance. This research paves a new avenue for reducing throttling energy losses and improves system efficiency in hydraulic switching actuators, as well as most of the hydraulic switch-mode circuits.

This paper aims to address the exponential stability and stabilization problems for a class of delayed nonlinear Markov jump systems under randomly occurring Denial-of-Service (DoS) attack and packet loss. Firstly, the stochastic characteristics of DoS attack and packet loss are depicted by the attack success rate and packet loss rate. Secondly, a Period Observation Window (POW) method and a hybrid-input strategy are proposed to compensate for the impact of DoS attack and packet loss on the system. Thirdly, A Dynamic Event-triggered Mechanism (DETM) is introduced to save more network resources and ensure the security and reliability of systems. Then, by constructing a general common Lyapunov functional and combining with the DETM and other inequality analysis techniques, the less conservative stability and stabilization criteria for the underlying systems are derived. In the end, the effectiveness of our result is verified through a numerical example.

Recurrent pregnancy loss (RPL) affects around 2 % of women of reproductive age. Primary RPL is defined by ≥2 pregnancy losses and no normal birth delivery. In secondary RPL, the losses are after a normal pregnancy and delivery. Most cases have no clear aetiology, although primary cases are the most complex. Several gene polymorphisms have been associated with RPL. Some polymorphisms are increased in women of Asian or Caucasian race. In admixed RPL populations, the information on possible genetic links is scarce and contradictory. The study aimed to assess the frequency of two SNP in different enzymes involved in medical conditions observed during pregnancy. Microsomal epoxy hydrolase (mEPH) is involved in detoxifying xenobiotics. It is present in ovaries, and it is hormonally regulated. The endothelial nitric oxide synthase forms nitric oxide from arginine and is involved in vascular tone. Two SNPs, rs1051740 and rs1799983, were assessed. The study included 26 controls and 63 primary RPL patients. Significant differences were observed in the frequencies of both SNP (p<0.05). The frequency of mutated alleles was higher in patients. Double mutated homozygotes were encountered only in RLP patients (p<0.05). Genetic polymorphisms rs1051740 and rs1799983 may be involved in primary RPL in the Venezuelan admix population. Genetic studies could provide crucial information on the aetiology of primary RPL.

Image stitching is a crucial aspect of image processing. However, factors like perspective and environment often lead to irregular shapes in stitched images. Cropping or completion methods typically result in substantial loss of information. This paper proposes a method for rectifying irregularly images into rectangles using deformable meshes and residual networks. The method utilizes a convolutional neural network to quantify rigid structures of images. Choosing the most suitable mesh structure based on the extraction results, offering options such as triangular, rectangular, and hexagonal. Subsequently, the irregularly image, predefined mesh structure, and predicted mesh structure are input into a wide residual neural network for regression. The loss function comprises local and global, aimed at minimizing the loss of image information within the mesh and global target. This method not only significantly reduces information loss during rectification but also adapting to different images with various rigid structures. Validation on the DIR-D dataset shows this method outperforms state-of-the-art methods in image rectification.

Background: One challenge in implant dentistry is to reduce marginal bone resorption to avoid long-term esthetic and biological complications. Sub-gingival implant placement has been suggested as a suitable strategy. Methods: 38 healthy patients were enrolled to receive bone level (BL – Control group) or 2 mm sub-crestal (SC - Test group) conical connection, platform-switched implants. An immediate tissue level abutment was used in the Test group by following a One Time Abutment (OTA) restorative procedure. Marginal Bone Modification (MBM) was calcu-latied on standardized radiographs at surgery (T0), loading (T1), and 6 months (T2) and 12 months after loading (T3), and cathegorised in Bone Loss (BL) if the resorption occurred below the implant neck and Bone Remodeling (BR) if above. Pocket probing depth (PPD), Bleeding on probing (BoP) and Plaque Index (PI) were also collected. Results: The mean MBM in the test group after 12 months was 0.61mm, compared to 0.52mm in the control group. However, no BL was observed in the test group, as the MBM completely occurred above the implant neck as BR, whilst in the control group MBM corresponded in total to BL. The average PPD was 2.38mm in the test group and 3.04mm in the control group after 12 months, BoP 50% and 43%, PI 33% and 19.44% respectively. Conclusions: Sub-crestal conical connection, platform-switched implants could be a suitable clinical choice to avoid BL with exposure of the treated implants surfaces.

Background and objective: Obesity is a growing global epidemic. The composition of the intestinal microbiota can be influenced by several factors. Studies highlight the role of intestinal bacteria in the pathophysiology of obesity. So, the objective of this study was to investigate whether the use of probiotics, together with healthy lifestyle habits, contributes to weight reduction in obese indi-viduals by analyzing the intestinal microbiota profile. Methods: A prospective study was carried out with 45 adults with obesity. Participants underwent guidance on healthy lifestyle habits, re-ceived a probiotic component containing different microbiological strains and were followed for 60 days. Clinical parameters, body composition, biochemical analysis and intestinal microbiota assessment were performed before and after treatment. After 60 days, it was observed that the bacterial strains present in the probiotic were present in the patients' intestinal microbiota. Par-ticipants also showed improvements in physical activity, sleep quality, anxiety management, as well as changes in some eating habits, such as a reduction in the consumption of processed foods and a significant increase in water intake. Results: A reduction in BMI, fasting glucose, insulin, HOMA-IR, LDL cholesterol and triglycerides was observed, in addition to an increase in HDL cholesterol, improvement in bowel movement frequency and stool consistency. Analysis of the intestinal microbiota revealed an increase in microbial diversity and a better balance between the bacterial phyla Firmicutes and Bacteroidetes. Conclusions: The changes related to improving the composition of the intestinal microbiota, dietary habits, increased physical activity, reduced anxiety, and better sleep quality have significantly contributed to weight loss and improvements in physiological parameters in obese individuals.

Hearing loss that arises from various causes at different stages of life has a direct impact on individuals' physical and mental well-being. This paper aimed to evaluate the employment, workplace adaptation, productivity, and professional success of individuals who have hearing loss and whose hearing loss is corrected with a cochlear implant. In this cross-sectional study, the data was collected between November 2022 and March 2023 with the participation of individuals with cochlear implants living in several settlements in all regions of Türkiye. A total of 142 participants with severe hearing loss who were corrected with a cochlear implant were included in this study. The survey method was used to collect data for the study. The questionnaire consisted of 32 questions and was distributed to the participants online. In the first part of the questionnaire (1-10 questions), general characteristics of implant patients were investigated. In the second part (11-32 questions), the positive or negative effects of implantation on the work life of the participants were evaluated. Almost half of the research group (49.3%, n = 70) consisted of women, and the mean age of the participants was determined to be 35.8 ± 14.8. There was no significant difference between gender, educational status, implanted side, working time, working style (physical, desk), and factors affecting work life (p > 0.05). Professional satisfaction and success at work increased significantly more in those with acquired hearing loss (p = 0.010). Post-implantation workplace compliance, success, and productivity were found to be higher in those with acquired hearing loss (p = 0.013). It was observed that hearing loss had a greater negative impact on the work life of married people (p = 0.006). Cochlear implantation greatly enhances workplace satisfaction, increases self-confidence, and has a positive impact on the future of profoundly deaf individuals.

This paper proposes training improvement methods of artificial neural networks (ANN) trajectory predictors. First, a dynamic power system time-series trajectory is split into several different segments to simplify the original ANN training problem. Moreover, the time-derivative of the trajectory is included to obtain an augmented loss function. Compared to previous studies which mainly focused on increasing the prediction accuracy, the aim of these novel techniques is to reduce the computational burden where the ANN output performance is still acceptable. The effectiveness of the developed methods is validated based on the WSCC three-machine nine-bus and IEEE 39-bus system models. The mean absolute error (MAE) and trajectory prediction results are analyzed, in which the numbers of neurons, hidden layers, and training epochs are constrained during the ANN training process. Rotor-angle difference between generators and the system frequency are investigated as the dynamic trajectories of the power system models. It is revealed that when the ANN architecture and epochs are constrained, the MAE results can be reduced, and the ANN training results can better reflect the original trajectory using the improvement approaches.

Children with hearing loss have been found to have significantly more behavioral and emotional challenges than their typically hearing peers, though these outcomes are variable at the individual level. Working memory deficits have been found to relate to executive functioning and overall emotion regulation, leading to behavior challenges. Language development is essential for development of social relationships and communicating one’s needs - this may lead to distress when children cannot communicate effectively. Based on prior findings in children with hearing loss and their typically hearing peers, working memory and language skills were hypothesized to be related to parent and teacher report of socioemotional functioning. Participants were 35 children with hearing loss (66% female, M = 5.17 years old, SD = ±1.97) whose language, working memory, and socioemotional functioning were evaluated during the course of treatment and educational planning. Bivariate analyses indicated that working memory was related to a number of socioemotional domains (e.g., functional communication, atypicality, withdrawal), as were language scores (e.g., social skills, inattention). The direction of these associations was such that stronger working memory and language skills were related to more regulated socioemotional functioning. A call to action of the current study includes more education with regard to profiles and presentations of children with hearing loss, and an early focus on socioemotional learning to foster the development of regulatory skills.

The global food system has three recognized challenges: (a)increasing the availability of food consumption, (b) reducing food loss, and (c) reducing food waste. The increasing demand for food consumption, increasing quantity of food loss, and corresponding increase in food waste are resulting in serious health, aesthetic, social, economic, and environmental problems due to a lack of appropriate planning and management. Despite its importance, there is no clear, concise, and comprehensive definition of food consumption, loss, and waste. Generally, food consumption, food loss, and food waste are dealt with separately. This article presents a logically constructed ontological framework of food consumption, loss, and waste. It gives equal importance to all three aspects of global food management. The systematic ontological framework is general, and the analysis can be applied to any country. The framework deconstructs the combinatorial complexity of the problem and explicates the pathways to manage the consumption, loss, and waste. The ontological framework encapsulates 19*8*7*4*5*6 = 25,536 possible components of the challenge. A critical analysis based on available data using the framework will help to develop strategies to deal with the problem. It can help to discover the gaps and to find ways to bridge the gaps. It is novel to conceptualize food consumption, loss, and waste together.

In dermatological practice, disturbances of the skin microbiome are found in various infectious and inflammatory dermatoses featuring one or more skin lesions with loss of tissue, directly exposing skin layers to microbial invasions. Literature data on the incidence of cutaneous-onset sepsis are, however, scarce. This retrospective observational study assessed hospital admissions for primary skin lesions with vs. without bacterial infections and sepsis during 2020-2022 in the largest emergency hospital in NE Romania. Of 509 patients 441 had infected lesions, 78 had sepsis caused by venous ulcers microbial eczema cellulitis, superinfected bullous dermatoses, erysipelas, erythroderma. Cultured samples revealed S. aureus, P. aeruginosa, E. coli, with K. pneumoniae, S. β-hemolytic associated with sepsis even if rarer. Clinical manifestations included ulcerations, erosions, fissures, excoriations, bullae, vesicles, pruritus, tumefaction, edema, fever, chills, pain, adenopathy, mildly altered mental status. Underlying chronic heart failure, atrial fibrillation, anemia, type-1 diabetes mellitus were comorbidities associated with infection and sepsis. Significant associations and risk factors, including their combined effects, are discussed to draw attention to the need for further research and adequate management to prevent sepsis in adult patients of any age presenting with infected skin lesions (especially cellulitis) and comorbidities (especially type 1 diabetes mellitus and anemia).

A facile and environmentally benign method for a single-phase barium titanate synthesis in water vapor medium was studied to reveal the mechanism of phase transformation of the initial simple oxides mixture and estimate the capability of the product to be used as a raw material for low-frequency dielectric ceramics. The composition and structure of the reaction mixture treated in vapor at 130…150 °C as well as 230 °C for various time were investigated by means of XRD, SEM, HRTEM, EDX, and FTIR methods. The kinetics of the occurring phase transformation was described by Johnson-Mehl-Avrami-Erofeev equation. The reaction between the initial oxides was considered as a topochemical process with an apparent activation energy of 74…80 kJ mol^-1. A crucial role in this process belonged to the water vapor medium, which facilitated the generation of the reaction zone and its spreading inward the solid particles. The synthesized tetragonal barium titanate powder (mean particle size of 135 ± 24 nm) was sintered by a conventional technique at 1250 °C to obtain ceramics with grains of about 2 μm. Capacitance measurements performed a dielectric constant and loss tangent of ceramics, which reached 3879 and 6.7 10^-3, respectively, at 1 kHz and room temperature.

With the development of artificial intelligence, the ability of capturing the background characteristics of hyperspectral imagery (HSI) is improved and promising performance in hyperspectral anomaly detection (HAD) tasks is yielded. However, existing methods proposed in recent years still suffer from certain limitations: 1) constraints are lacking in the deep feature learning process in terms of the issue for absence of prior background and anomaly information. 2) hyperspectral anomaly detectors with traditional self-supervised deep learning methods fail to ensure prioritized reconstruction of the background. 3) architectures of fully connected deep network in hyperspectral anomaly detectors lead to low utilization of spatial information and destruction for original spatial relationship of hyperspectral imagery, and disregard spectral correlation between adjacent pixels. 4) hypotheses or assumptions for background and anomaly distributions restrict the performance of many hyperspectral anomaly detectors because the distributions of background land covers are usually complex and not assumable in real-world hyperspectral imagery. With the consideration of above problems, in this paper, we propose a novel fully convolutional auto-encoder based on dual clustering and latent feature adversarial consistency (FCAE-DCAC) for HAD which is carried out in a self-supervised learning-based processing. Firstly, the density-based spatial clustering of applications with noise algorithm and connected component analysis are utilized for successive spectral and spatial clustering to obtain more precise prior background and anomaly information, which facilitates the separation between background and anomaly samples during the training of our method. Subsequently, a novel fully convolutional auto-encoder (FCAE) integrated with spatial-spectral joint attention (SSJA) is proposed to enhance the utilization of spatial information and augment feature expression. In addition, a latent feature adversarial consistency network is proposed to achieve pure background reconstruction with the ability of learning actual background distribution in hyperspectral imagery. Finally, a triplet loss is introduced to enhance the separability between background and anomaly, and the reconstruction residual serves as the anomaly detection result. We evaluate the proposed method on seven groups of real-world hyperspectral datasets, and the experimental results confirmed the effectiveness and superior performance of the proposed method versus nine state-of-the-art methods.

Radiotherapy is a crucial treatment for head and neck malignancies, but it usually leads to sensorineural hearing loss (SNHL). Changes in the immune microenvironment and sensorial neuroepithelium of the inner ear after radiation exposure remain poorly understood. This study investigated cochlear morphology and macrophages in the inner ear after high-dose irradiation. The heads of 8-week-old Cx3cr1GFP/+ heterozygous male mice were irradiated with 30Gy X-rays and biological samples were taken on the 1st, 7th, and 10th days after irradiation. Auditory brainstem responses were used to assess auditory function in mice. The changes of basal membrane hair cells, spiral ganglion (SGN), and inner ear macrophages were observed using hematoxylin-eosin (HE) staining and immunofluorescence staining. The expression of inflammatory mediators in the inner ear was detected by reverse transcription-polymerase chain reaction (RT-PCR) in cochlear tissue. As a result, there was no significant hair cell loss after high doses of radiation, but the mice developed full-frequency hearing loss on day 10 when HE staining revealed SGN atrophy and immunofluorescence revealed decreased neurofilament expression. The number of macrophages in the inner ear decreased over time. RT-PCR showed that cochlear inflammatory factors and chemokines were briefly up-regulated on the first day after irradiation and then decreased over time. In summary, high-dose irradiation causes acute SNHL that does not involve hair cell loss and may be associated with SGN changes. Radiation-induced SNHL is accompanied by a reduction in cochlear macrophages and changes in the immune microenvironment, but the relationship between the two has yet to be explored.

Image stitching is a crucial aspect of image processing. However, factors like perspective and environment often lead to irregular shapes in stitched images. Cropping or completion methods typically result in substantial loss of information. This paper proposes a method for rectifying irregularly images into rectangles using deformable meshes and residual networks. The method utilizes a convolutional neural network to quantify rigid structures of images. Choosing the most suitable mesh structure based on the extraction results, offering options such as triangular, rectangular, and hexagonal. Subsequently, the irregularly image, predefined mesh structure, and predicted mesh structure are input into a wide residual neural network for regression. The loss function comprises local and global, aimed at minimizing the loss of image information within the mesh and global target. This method not only significantly reduces information loss during rectification but also adapting to different images with various rigid structures. Validation on the DIR-D dataset shows this method outperforms state-of-the-art methods in image rectification.

The study of angular correlations of heavy-flavor particles in hadronic collisions can provide crucial insight into the heavy-quark production, showering and hadronization processes. The comparison with model predictions allows us to discriminate among different approaches for heavy-quark production and hadronization, as well as different treatments of the underlying event employed by the models to reproduce correlation observables. In ultra-relativistic heavy-ion collisions, where a deconfined state of matter, the quark-gluon plasma (QGP), is created, heavy-flavor correlations can shed light on the modification of the heavy-quark fragmentation due to interaction of charm and beauty quarks with the QGP constituents, as well as characterize their energy loss processes while traversing the medium. Insight into possible emergence of collective-like mechanisms in smaller systems, resembling those observed in heavy-ion collisions, can also be obtained by performing correlation studies in high-multiplicity proton-proton and proton-nucleus collisions. In this review, the most recent and relevant measurements of heavy-flavor correlations performed in all collision systems at the LHC and RHIC will be presented, and the new understandings that they provide will be discussed.

Experimental tests and numerical analyses were carried out on short, thin-walled channel columns with modified cross-sectional shape. The columns were loaded with an axial compressive force applied at the center of gravity of the cross section. Tests were carried out on a universal testing machine, while numerical analyses were performed in ANSYS software. The purpose of the tests was to determine the values of critical forces for the compressed columns and to determine the values of maximum forces at which failure of the columns occurs. Critical forces were determined based on the strain-averaged method. Based on the study, it was found that the strength and resistance to loss of stability of columns is primarily affected by their stiffness, and therefore by the shape of the cross-sections. In addition, for short columns, it seems more important to determine the value of maximum forces than the values of critical forces.

Street view images can help us better understand the city environment and potential characteristics. With the development of computer vision and deep learning, the technology of semantic segmentation algorithms has become more mature. However, DeeplabV3+, which is commonly used in semantic segmentation, has shortcomings such as a large number of parameters, high requirements for computing resources, and easy loss of detailed information. Therefore, this paper proposes LM-DeeplabV3+, which aims to greatly reduce parameters and computations of the model while ensuring the segmentation accuracy. Firstly, the lightweight network MobileNetV2 is selected as the backbone network, and the ECA attention mechanism is introduced after MobileNetV2 extracts shallow features to improve the ability of feature representation; secondly, the ASPP module is improved, and on its basis, the EPSA attention mechanism is introduced to achieve cross-dimensional channel attention and important feature interaction; thirdly, a loss function named CL loss is designed to balance the training offset of multiple categories and better indicate the segmentation quality. This paper conducted experimental verification on the Cityspaces dataset, and the results showed that the mIoU reached 74.9%, which was an improvement of 3.56% compared to DeeplabV3+; the mPA reached 83.01%, which was an improvement of 2.53% compared to DeeplabV3+.

The study delves into the critical examination of the Size of Loss distribution patterns in the context of auto insurance during pre- and post-pandemics, emphasizing their profound influence on insurance pricing and regulatory frameworks. Through a comprehensive analysis of the historical Size of Loss data, insurers and regulators gain essential insights into the probabilities and magnitudes of insurance claims, informing the determination of precise insurance premiums and the management of case reserving. This approach aids in fostering fair competition, ensuring equitable premium rates, and preventing discriminatory pricing practices, thereby promoting a balanced insurance landscape. The research further investigates the transformative impact of the COVID-19 pandemic on these Size of Loss patterns, given the substantial shifts in driving behaviors and risk landscapes. Also, the research contributes to the literature by addressing the need for more studies focusing on the implications of the COVID-19 pandemic on pre- and post-pandemic auto insurance loss patterns, thus offering a holistic perspective encompassing both insurance pricing and regulatory dimensions.

Mandibular third molar is the most frequently impacted tooth. Mandibular third molar impaction bears consequences on the adjacent mandibular second molar (MSM) like bone loss. It can be identified initially using orthopantomography (OPG). The objective is to compare the changes in the bone level distal to MSM between patients with extracted and non-extracted impacted man-dibular third molars (IMTM) using OPG. In this retrospective case-control study, 160 archived (OPGs) of 80 patients visiting the Dental Hospital of the University of Barcelona (HOUB) were randomly selected. The participants were stratified into two groups. The study group involved measuring the bone level distal to the mandibular second molar before and after the extraction of the IMTM. The control group, on the other hand, had bone levels measured twice within 3–6-month period without the extraction of the IMTM. The mean ages of patients in study and control groups were 35.5 ± 15.45 and 33 ± 16.49, respectively. Study group demonstrated signifi-cant (p < 0.05) bone gain after extraction, whereas control group demonstrated significant bone loss (p < 0.0001) after follow-up. Bone improvements were observed distal to the mandibular second molar after the extraction of the IMTM compared to those in control group.

Rosavin, a phenylpropanoid in Rhodiola rosea's rhizome, an adaptogen, is known for enhancing the body's response to environmental stress. It significantly affects cellular metabolism in health and many diseases, particularly influencing bone tissue metabolism. In vitro, rosavin inhibits osteoclastogenesis, disrupts F-actin rings formation, and lowers osteoclastogenesis-related gene expression (cathepsin K, CTR, TRAF6, TRAP, MMP-9). It also impedes NFATc1, c-Fos, NF-κB, and MAPK signaling pathways, and blocks phosphorylation processes crucial for bone resorption. Moreover, rosavin promotes osteogenesis, osteoblast differentiation and increases Runx2 and OCN expression. In vivo studies show its effectiveness in enhancing BMD in PMOP mice, re-straining osteoclast maturation, and increasing active osteoblast percentage in bone tissue. It modulates mRNA expressions (increasing EEF2 and decreasing HDAC1, thereby activating os-teoprotective epigenetic mechanisms) and alters various serum markers, including decrease of CTX-1, TRAcp5b, RANKL, M-CSF, TRAP, and increase of ALP and OCN. Additionally, when combined with zinc and probiotics, it reduces pro-osteoporotic MMP-3, IL-6, TNF-α, and en-hances anti-osteoporotic IL-10 and TIMP3 expressions. This paper aims to systematically review rosavin's impact on bone tissue metabolism, exploring its potential in osteoporosis prevention and treatment, and suggesting future research directions.

New insights into the causes and mechanisms of congenital heart disease (CHD) have been gained through the use of next-generation sequencing. Examination of the whole exome sequence detects detrimental gene variations modifying single or contiguous nucleotides, that are characterised as pathogenicity based on statistical assessments of families. and correlates with congenital heart disease, elevated expression during heart development, and reduction of harmful protein-coding mutations in the general population. Patients with CHD and extracardiac abnormalities enriched for gene classes meeting these criteria. CHDs and extracardiac defects, supporting a common set of pathways in the organogenesis of CHDs. Single-cell transcriptomics data reveal the expression of genes associated with CHD in specific cell lineages, and emerging evidence suggests that genetic variants disrupt multicellular genes essential for cardiogenesis. Metrics and units are being tracked in whole genome sequence studies.

This study investigates the emergence of ertapenem-resistant, meropenem-susceptible (ErMs) among non-carbapenemase producing (NCP) and carbapenemase producing (CP) Escherichia coli and Klebsiella pneumoniae. As mutations for ertapenem resistance establish the genetic background for non-carbapenemase meropenem resistance, there is a great need for antibiotic stewards and researchers to understand the determinants of a strain’s propensity to become resistant. Whole genome sequencing was conducted on clinical carbapenem-resistant E. coli (CREC) and K. pneumoniae (CRKP) across 5 hospitals in San Antonio, U.S. from 2012-2018. The majority of carbapenem resistant Enterobacterales (CRE) were NCP (54%; 41/76). The blaCTX-M was found to be most prevalent among NCP isolates (p = 0.02). LC-MS/MS analysis of carbapenem hydrolysis revealed that blaCTX-M-mediated carbapenem hydrolysis, indicating the need to reappraise the term, “non-carbapenemase (NCP)” for quantitatively uncharacterized CRE strains harboring blaCTX-M. Antimicrobial susceptibility results showed that 56% of all NCPE isolates had an ErMs phenotype (NCPE vs. CPE, p &lt; 0.001), with E. coli driving the phenotype (E. coli vs. K. pneumoniae, p &lt; 0.001). ErMs strains carrying blaCTX-M, had approximately 4-fold more copies of blaCTX-M than ceftriaxone-resistant but ertapenem and meropenem susceptible (EsMs) isolates (3.7 v. 0.9, p &lt; 0.001). ErMs also carried more mobile genetic elements (MGEs), particularly IS26 composite transposons, than EsMs (37 vs. 0.2, p &lt; 0.0001). Immunoblot analysis demonstrated the absence of OmpC expression in NCP-ErMs E. coli, with 92% of strains lacking full contig coverage of ompC. Overall, this work provides evidence of a collaborative effort between blaCTX-M and OmpC in NCP strains that confer resistance to ertapenem but not meropenem. To thwart potential mismanagement of CRE infected patients, future efforts should focus on understanding the mechanism(s) underlying OmpC loss, developing rapid methods to detect blaCTX-M copy number variants, and targeted antimicrobials for NCPE and ErMs strains.

The Southwest Alpine Canyon Area of China was one of the regions in the world that suffered from severe soil erosion. The focus of this research was to understand the response of land use change on soil loss by water erosion in alpine canyon on Southeast Tibet, we analyzed the characteristics of temporal and spatial dynamics of land use in the Niyang River Basin from 1990 to 2020 using GIS and statistical methods, assessed the spatial and temporal change characteristics of soil erosion in the Niyang River Basin using RUSLE model. For this purpose, the meteorological, soil, topographic, remote sensing data were collected. The results showed the area of cropland and construction land in the Niyang River Basin increased to 2.4 and 6.1 times the original from 1990 to 2020, respectively, the area of forest and water continued to decrease. Grassland, unused land and forest have always been the dominant land types in the Niyang River Basin. Tolerable soil erosion was distributed in the flat areas of the valley terraces in the main stream and its tributaries, slight soil erosion was mainly distributed in the flat areas at high altitudes, and moderate, severe, very severe and destructive soil erosion was sporadically distributed in the Niyang River Basin. The areas of tolerable and slight soil erosion exceeded 82% of the total area, The area of severe, very severe and destructive soil erosion was less than 6%, but the total soil loss amount of severe, very severe and destructive erosion was more than 27%. From 1990 to 2020, the soil erosion area decreased from 9219.34 km2 to 8,090.84 km2 in Niyang River Basin, more than 85% of the soil erosion class has not changed, and the change of total soil loss amount also shows a significant reduction trend as a whole. 99% of the total soil loss amount in the Niyang River basin is generated by grassland, forest and unused land. The conversion of various land use types to cropland will cause the enhancement in soil erosion grade. We recommend that the focus of soil erosion control in the Niyang River Basin is to protect grassland, forest and carry out scientific farming.

Epilepsy, a disorder of unprovoked recurring seizures, continues to be seen as a growing medical concern worldwide. It represents the most common, non-communicable brain disorder, affecting persons of all ages. Every year over five million persons are formally diagnosed with epilepsy when seeking medical care. Often diagnosed as a young child, most persons can live a seizure-free life once there is an early diagnosis, proper patient education, and keen clinical management. However, the reoccurrence of status epilepticus, a neurological emergency, can be linked to untreated underlying causes and lead to serious morbidity and even early mortality if not properly managed. The prognosis is heavily reliant on the discovery of the underlying cause. Epilepsy, in recent times, provides a terminology for ease of identification of the associated clinical symptomology. Epilepsy, an umbrella term, can manifest differently as either idiopathic, symptomatic, or cryptogenic. However, distinguishing epilepsy from other seizure mimics is critical to preventing complications. Epilepsy research, like many other neurological symptoms, is limited in low-resource areas. Therefore, through greater awareness of epilepsy and public education campaigns, better health outcomes can be achieved. There is huge utility in clear communication of medical information among healthcare providers as well as in optimizing treatment plans.

Background: One of the most astounding discoveries of recent times is the recognition that cancer embodies a transition from a higher level of metazoan cell organization to a more foundational pre-metazoic state. This shift is steered by genes housed within the ancestral genome compartment, pervasive across all metazoan genomes, encompassing humans, and governed by a pre-metazoic gene regulatory mechanism (aGRN). This work aims to highlight the emerging field of evolutionary cancer cell biology (ECCB), which points to the deep homology between cancer and protist life cycles tracing back to the common ancestor of amoebozoans, metazoans, and fungi (AMF). The ECCB analysis reveals the essence of the non-gametogenic germline of the AMF ancestor, which serves as a blueprint for all metazoan germlines and stem cell lineages and controls the life cycle of cancer. Every germ and stem cell lineage of humans and metazoans traces its lineage back to this Urgermline, transmitting crucial processes such as asymmetric cell cycling, differentiation, stemness, and phenomena like GST and SGT (aka EMT and MET) to their subsequent evolutionary descendants. Oxygen-sensitive germline and stem cells suffer DNA-DSB due to stress and oxygen ranges reminiscent of ancestral hyperoxia, leading to cell senescence. Cells that can overcome senescence can proliferate as DSCD cells with defective symmetric cell division, paving the way for malignancy and PGCC cancers. Conclusions: Understanding cancer from its evolutionary origins may help break some of the logjams in cancer prevention and open up new therapeutic pathways.

This article delves into the pro-cyclicality of Loan Loss Provisions (LLPs) and earnings management, along with equity management, in Portuguese banks against the backdrop of implementing the IFRS 9's Expected Credit Loss (ECL) model. It concentrates on how LLPs mirror economic cycles and financial management practices, providing valuable insights into the operational dynamics of the Portuguese banking sector, marked by distinct economic and regulatory challengesThe research examined a sample of five Portuguese commercial banks, chosen from a group of seventeen in the Portuguese Banking Association. Data spanning from 2013 to 2022 were manually gathered. A multiple linear regression model was employed to scrutinize the relationship between LLPs and variables indicative of economic cycles and the earnings and equity management. The methodology aligns with the approaches of Araújo et al. (2018), Beatty and Liao (2014), and Casta et al. (2019). The analysis indicates a pro-cyclicality in LLPs within the Portuguese context, with a positive response of LLPs to economic indicators like unemployment. Contrarily, the extent of earnings and equity management under the ECL model was less marked compared to the Incurred Credit Loss (ICL) model, suggesting the impact of more stringent regulatory measures. The research corroborates the pro-cyclicality of LLPs in Portuguese banks under the ECL framework, underscoring the necessity for ongoing monitoring and refinement of models for forecasting and recognizing credit losses. The findings point to an area for improvement in financial management practices, despite regulatory enhancements, to promote transparency and ensure financial stability.

The main aim of this work is to present a step-by-step procedure to model and analyze the power loss distribution of three-level Gallium Nitride (GaN) inverters. It has been applied to three distinct three-phase three-levels voltage source inverters utilized in electric traction drives: Active Neutral Point Clamped, Neutral Point Clamped and T-Type Neutral Point Clamped. The proposed analytical power loss modelling, combined to an equivalent representation of the electrical machine demonstrated to be a viable solution to achieve a time-saving and low computational burden simulation platform, leading to satisfying accuracy results. This has been confirmed by comparing the results carried out from the simulations of a 110kW permanent magnet synchronous motor drive and those determined by considering a simplified circuital representation based on the proposed analytical power loss modelling.

This study delves into the complex dynamics of Underwater Wireless Optical Communication (UWOC) in varied Harbor water conditions. Focusing on four distinct types of Harbor water, the research employs the Monte Carlo method to simulate photon transmission and analyze critical UWOC characteristics. Key parameters such as the transmitted full divergence angle, received aperture, and Field of View (FOV) are meticulously evaluated for their impact on communication efficacy. The study first explores the relationship between laser power variation, attenuation length, and divergence angle, revealing how different water qualities influence received power and time delay spread. Notably, the received normalized power loss and time delay spread are found to be more significantly affected by communication distance than water quality. In addition, under the condition of small received aperture and FOV, the influence on normalized power loss and time spread is more obvious in Harbor water. The findings offer novel insights into the challenges of UWOC in Harbor waters, particularly in terms of light scattering and absorption properties, and contribute to the optimization of communication systems in such complex underwater environments. Furthermore, the analysis of time pulse spread in turbid water quality is of great significance for the analysis and improvement of underwater wireless optical timing, ranging and positioning.

The Spiking Neural Network (SNN) has attracted more and more attention recently. It adopts binary spike signals to transmit information. Benefitting from the information passing paradigm of SNNs, the multiplications of activations and weights can be replaced by additions, which are more energy-efficient. However, its ``Hard Reset" mechanism for the firing activity would ignore the difference among membrane potentials when the membrane potential is above the firing threshold, causing information loss. Meanwhile, quantifying the membrane potential to 0/1 spikes at the firing instants will inevitably introduce the quantization error thus bringing about information loss too. To address these problems, we propose to use the ``Soft Reset" mechanism for the supervised training-based SNNs, which will drive the membrane potential to a dynamic reset potential according to its magnitude, and Membrane Potential Rectifier (MPR) to reduce the quantization error via redistributing the membrane potential to a range close to the spikes. Results show that the SNNs with the ``Soft Reset" mechanism and MPR outperform their vanilla counterparts on both static and dynamic datasets.

The consequences of climate change and anthropogenic stressors, such as habitat loss and overexploitation, are threatening the subsistence of species and communities across the planet. Therefore, it is crucial to analyze the impact of environmental perturbations on the diversity, structure and function of ecosystems. In this work, in silico simulations of biodiversity loss were carried out on the marine food web of Caleta Potter (25 de Mayo Island, Antarctica) where global warming has caused critical changes in the abundance and distribution of benthic and pelagic communities during the last 30 years. We performed species removal considering their degree and trophic level and including four different thresholds on the occurrence of secondary extinctions. We examined the impact of extinctions on connectance, modularity and stability of the food web. We found different responses of these properties depending on the extinction criteria used, e.g., large increase in modularity and rapid decrease in stability when most-connected and relatively high-trophic level species were removed. Additionally, we studied the complexity-stability relationship of the food web founding two regimes: 1) high sensitivity to small perturbations suggesting that Potter Cove would be locally unstable, and 2) high persistence to long-range perturbations suggesting global stability of this ecosystem.

The various methods used to choose the profile shift coefficients, primarily the so-called equalizations, were based on assumed advantages without physical evidence proving them. In this paper a new calculation method is presented for determining profile shift coefficient. The procedure gives the pair of values ​​of the profile shift coefficients, in which case, under the given load, the resulting bending stress will be of the lowest possible value.

Fruits and vegetable diagnosis and inspection is a crucial part of quality control and health safety. From harvesting to retailing, stakeholders encounter tons of food losses due to the lack of monitoring of the fruit condition in retail. The problem gets worse because it is being handled by many people, including retailers and customers. We propose a transparent fiberglass-made vertical fruit showcase, which provides 80 percent more visibility, takes lesser shop space, and prevents human contact. It is convenient for the retailer and customer to use. Moreover, the controlled fruit environment is easy to integrate with IoT, which will help to generate consensus data for fruit management decisions in machine learning.

Under high-frequency operating conditions, the high-speed solenoid valve (HSV) experiences energy loss and heat generation, which significantly impact its operational lifetime. Reducing the energy loss of HSV without compromising its opening response characteristics poses a significant challenge. To address this issue, a finite element simulation model of HSV coupled with a current feedback model is constructed to investigate the synergistic effects of dynamic response and energy loss. Predictive models for the opening response time, HSV driving energy, and Joule energy using Back Propagation neural network (BPNN) are established. Furthermore, a multi-objective optimization study on the current driving strategy using Non-dominated Sorting Genetic Algorithm II (NSGA-II) is conducted. After optimization, although there was a 6.24% increase in the opening response time, both HSV drive energy and Joule energy were significantly reduced by 15.67% and 22.49%, respectively. The proposed multi-objective optimization method for HSV driving strategy holds great significance in improving its working durability.

In high-traffic harbor waters, marine radar frequently encounters signal interference stemming from various obstructive elements, thereby presenting formidable obstacles in the precise identification of ships. To achieve precise pixel-level ship identification in the complex environments, a customized neural network-based ship segmentation algorithm named MrisNet is proposed. MrisNet employs a lightweight and efficient FasterYOLO network to extract features from radar images at different levels, capturing fine-grained edge information and deep semantic features of ship pixels. To address the limitation of deep features in the backbone network lacking detailed shape and structured information, an adaptive attention mechanism is introduced after the FasterYOLO network to enhance crucial ship features. To fully utilize the multi-dimensional feature outputs, MrisNet incorporates a Transformer structure to reconstruct the PANet feature fusion network, allowing for the fusion of contextual information and capturing more essential ship information and semantic correlations. In the prediction stage, MrisNet optimizes the target position loss using the EIoU function, enabling the algorithm to adapt to ship position deviations and size variations, thereby improving segmentation accuracy and convergence speed. Experimental results demonstrate that MrisNet achieves high recall and precision rates of 94.8% and 95.2%, respectively, in ship instance segmentation, outperforming various YOLO and other single-stage algorithms. Moreover, MrisNet has a model parameter size of 13.8M and real-time computational cost of 23.5G, demonstrating notable advantages in terms of convolutional efficiency. In conclusion, MrisNet accurately segments ships with different spot features and under diverse environmental conditions in marine radar images. It exhibits outstanding performance, particularly in extreme scenarios and challenging interference conditions, showcasing robustness and applicability.

This paper proposes a radial alternating materials phononic crystal (RAM-PnC). By simulating the band gap structure of the phononic crystal, it is verified that there is a complete acoustic band gap at the resonant frequency of 175.14 MHz, which can prevent the propagation of elastic waves in a specific direction. The proposed alternately arranged radial phononic crystal structure is applied to the thin-film piezoelectric-on-silicon (TPOPS) MEMS resonator. The finite element simulation method increases the anchor quality factor (Qanchor) from 60596 to 659536011 at the operating frequency of 175.14 MHz, which is about 10,000 times higher. The motion resistance of the RAM-PnC resonator is reduced from 156.25 Ω to 48.31 Ω compared with the traditional resonator. At the same time, the insertion loss of the RAM-PnC resonator is reduced by 1.1 dB compared with the traditional resonator.

Ecological changes evoke many felt losses and types of grief. These affect sustainability efforts in profound ways. Scholarship on the topic is growing, but the relationship between general grief research and ecological grief has received surprisingly little attention. This interdisciplinary article applies theories of grief, loss, and bereavement to ecological grief. Special attention is given to research about “non-death loss” and other broad frameworks about grief. Dynamics related to both local and global ecological grief are discussed. Kinds of potential losses arising out of ecological issues are clarified with the frameworks of tangible/intangible loss, ambiguous loss, nonfinite loss, and shattered assumptions. Various possible types of ecological grief are illuminated by discussing the frameworks of chronic sorrow and anticipatory grief/mourning. Earlier scholarship about disenfranchised ecological grief is augmented by further distinctions about various forms it may take. The difficulties in defining complicated or prolonged grief in ecological context are discussed, and four types of “complicated ecological grief” are explored. Based on the findings, three special forms of ecological loss and grief are named and discussed: transitional loss and grief, lifeworld loss, and shattered dreams. The implications of the results for ecological grief scholarship, counselling and coping are briefly discussed. The results can be used by psychological and healthcare professionals and researchers, but also by members of the public who wish to reflect on their eco-emotions.

The advent of zirconia ceramics with excellent mechanical, biomechanical and optical properties has made it an attractive metal-free substitute for titanium implants. Both animal and human studies have documented shortcomings with titanium implants. A review of the current literature on 3 iterations of zirconia implant designs has been challenging due to heterogeneous success data and limited follow-up. Zirconia implants hold promise for a new generation of dental implants, but technical developments are needed for design and material enhancements that will need to be validated by long-term rigorous studies.

In the field of computational fluid dynamics (CFD) for rotorcraft, two significant challenges are resolving the complex vortex structures in rotor wakes, and representing the moving rotor blades in the ambient airflow. This study addresses the first challenge by using a third-order unstructured finite volume solver, which, compared to its second-order counterpart, has substantially lower dissipation. Consequently, even relatively coarse meshes are capable of resolving small vortices. With this background flow field solver, the second challenge is addressed by modeling each rotor as an Actuator Disk Model (ADM), or describing individual rotor blades as actuator lines, designated as the Actuator Line Model (ALM). Both of these models are equipped with an improved correction for aerodynamic losses at blade tips, which is thoroughly presented in the methodology section. The numerical experiments section centers on analyzing errors linked to various sampling approaches. Additionally, the article discusses comparisons between vortex theory and ALM, specifically regarding calculations for fixed-wing aircraft. Furthermore, high-order precision and parallel efficiency are exemplified in scenarios encompassing rotors engaged in both hovering and forward flight rotors. The results in this paper demonstrate that the combination of the ALM/ADM with the improved tip loss correction and the third-order finite volume solver presents a new way of developing efficient tools for the aerodynamic analysis of helicopter rotors.

Background: Retinal diseases such as neovascular age related macular degeneration (nAMD), diabetic macular edema (DME) or branch-/central retinal vein occlusion (B/CRVO) have significant implications for patients' social and psychological well-being. To gain a comprehensive understanding of patients' backgrounds and attitudes, we developed an exploratory questionnaire, the Basic Care and Patient Satisfaction Questionnaire (BPZ-9). Methods: The ALBATROS study aimed to assess the care situation of treatment-naïve patients diagnosed with either nAMD, DME or B/CRVO. The data collection took place at the beginning of treatment and after twelve months of anti-VEGF (vascular endothelial growth factor) therapy. The BPZ-9 instrument comprises nine questions to evaluate patients’ psychological and social situation and their satisfaction with treatment. Results: Data were collected from 1.478 nAMD (mean 78 years), 445 DME (67 years), 233 BRVO (70 years) and 144 CRVO (71 years) patients at 102 study centers throughout Germany. Approximately one third of the patients was living alone and six percent were in organized care. One in four patients had difficulties to walk and one in five needed accompany for treatment. Anxiety to lose vision was present in three out of four patients at the beginning and slightly decreased to two out of three over the 12-month treatment preriod. The distress of having a retinal disease was generally higher than the distress related to treatment. Most patients reported high treatment satisfaction (73%) and felt well informed (81%). Conclusion: Patients receiving anti-VEGF therapy commonly experience impaired mobility, dependency on others, distress and the fear of vision loss.

Borderline ovarian tumors (BOTs) show intriguing characteristics distinguishing them from other ovarian tumors. This unique type of non-invasive neoplasms is characterized by atypical growth of epithelial cells, nuclear atypia, and a moderate-level mitotic activity that places BOTs between benign tumors and invasive cancers. Similar to invasive carcinomas, BOTs can be categorized into six histological subtypes based on the type of epithelial cells present. The most prevalent subtypes are serous and mucinous BOTs, whereas endometrioid, clear cell, seromucinous, and borderline Brenner tumors are diagnosed less often. Noticeably, molecular changes found in BOTs can vary on a case-by-case basis, which warrants further research on the molecular landscape of these tumors. Identifying carcinogenic mutations through molecular analysis and developing targeted therapies represent significant advancements in the diagnosis and treatment of ovarian malignancies. A growing body of evidence indicates that BOTs often remain clinically dormant for extended periods before a molecular trigger initiates increased cell replication, potentially leading to carcinoma development or recurrence. Continued research in this area is crucial for improving risk assessment and developing personalized treatment approaches. While molecular studies have contributed significantly to our understanding of BOT pathogenesis, substantial research is still required to elucidate the relationship between ovarian neoplasms and extraneous disease, identify accurate prognostic indicators, and develop targeted therapeutic approaches. The aim of the present systematic review was to analyze the spectrum of molecular changes found in BOTs and discuss their significance in the context of the overall therapeutic approach.

Osteoporosis, often linked to increased osteoclast activity due to menopause or aging, was the focus. In this study, the inhibitory effects of Salicornia europaea L. (SE) water extract of desalted SE (WSE) were investigated on osteoclast differentiation and bone loss in ovariectomized mice. The findings revealed that WSE effectively inhibited RANKL-induced osteoclast differentiation, as evidenced by TRAP staining, and also suppressed bone resorption and F-actin ring formation in a dose-dependent manner. Gene expressions related to osteoclast differentiation, including NFATc1, TRAP, cathepsin K, and DC-STAMP, were downregulated by WSE. Oral administration of WSE improved bone density and structural parameters in ovariectomized mice. Dicaffeoyl quinic acids (DCQAs) and saponins in WSE were detected, with 3,4-, 3,5-, and 4,5-DCQA isolated and identified. All tested DCQAs, including the aforementioned types, inhibited osteoclast differentiation, bone resorption, and the expression of osteoclast-related genes. Furthermore, WSE and DCQAs reduced ROS production mediated by RANKL. These results indicate the potential of WSE and its components, DCQA, as preventive or therapeutic agents against osteoporosis and related conditions.

Estimating age at death is essential to establish a biological profile from human skeletal remains in both forensic and archeological settings. Imaging studies of skeletal age changes in adults have described metamorphosis of trabecular bone structure and bone loss in the proximal femur , as well as changes in morphology during different stages of life. This study aims to assess the utility of a digital representation of conventional X-ray films of the proximal femur for the estimation of age at death in a sample of 91 adult individuals (47 females and 44 males) of the Coimbra Identified Skeletal Collection. The proposed approach showed a root mean squared error (RMSE) of 17.32 years (and mean absolute error of 13.47 years) for females and an RMSE of 14.06 years (mean absolute error of 11.08 years) for males. The main advantage of this approach is the consistency in the feature detection and extraction, as X-ray images projected on the femora space will always produce the same set features to be analyzed for age estimation while more traditional methods rely heavily on operator experience which can lead to inconsistent age estimates among experts.

The paper presents the main experimental capabilities of the automatic system for the study of the interaction between porous media and atmosphere. This system is one of the possible variants of patent 2-241-477. The paper shows the result of a drying and wetting study of a tailings sample. The sample is 32 cm in height and 29 cm in diameter. The saturation and drying process was carried out at 26 degrees Celsius at the sample surface, an air velocity of 2 m/s and a relative humidity of 60%. The recharge applied to the column surface was 0.3 cm3/cm2/minute. The results show the effectiveness of the system in controlling the spatial-temporal variation of different physical properties of the porous medium in the vertical and surface profile. The controlled variables include volumetric water content, suction, relative humidity, sample weight variation due to recharge or drying, shrinkage, temperature, etc. The experiment shows how the tailings saturate very quickly but dry very slowly. Tailings consolidation occurs in the drying and wetting processes, being higher in the first one.

This work presents a new algorithm to resolve the problem of distribution network reconfiguration using the Tabu Search metaheuristic and voltage drop. The proposed method presents a different way to obtain the initial solution using the voltage drop, as well as a new way to generate a neighborhood of candidate solutions, based on randomness and the voltage drop, to perform a smooth and steady descent execution of the algorithm. The proposed algorithm has the main objective to reduce the active power losses in distribution networks, but it also achieves an refinement in the voltage profile. The proposed method was tested in two distribution systems, the 33-Bus and 94-Bus systems, commonly found and tested in the literature. The results of the tests show that the proposed method presents a low computational cost, achieves good solutions, and is better than the other methods found in the literature.

Facial expression recognition is crucial for understanding human emotions and nonverbal communication. With the growing prevalence of facial recognition technology and its various applications, accurate and efficient facial expression recognition has become a significant research area. However, most previous methods have focused on designing unique deep-learning architectures while overlooking the loss function. This study presents a new loss function that allows simultaneous consideration of inter- and intra-class variations to be applied to CNN architecture for facial expression recognition. More concretely, this loss function reduces the intra-class variations by minimizing the distances between the deep features and their corresponding class centers. It also increases the inter-class variations by maximizing the distances between deep features and their non-corresponding class centers, and the distances between different class centers. Numerical results from several benchmark facial expression databases, such as Cohn-Kanade Plus, Oulu-Casia, MMI, and FER2013, are provided to prove the capability of the proposed loss function compared with existing ones.

There is no well-defined threshold for intra-operative blood transfusion (BT) in advanced epithelial ovarian cancer (EOC) surgery. We developed a Machine Learning (ML)-driven prediction algorithm to trigger and explain a communication alert for BT based on anticipated peri-operative events irrespective of BT policies. We analysed prospectively collected data from 403 EOC patients who underwent cytoreductive surgery between 2014 and 2019. We calculated the estimated blood volume (EBV) using the formula EBV = weight x 80 and set off 10%EBV as threshold for individual intervention. Based on the known estimated blood loss (EBL) we identified two groups. We employed Receiver operating characteristic (ROC) curves for performance metrics. The model performance for the above threshold prediction was satisfactory (AUC 0.823, 95% CI 0.76-0.88). The top feature commonly shared between interrogators was operative time (OT). Intra-operative blood loss of at least 10%EBV was associated with OT&gt;250 minutes, primary surgery, serous histology, performance status 0, R2 resection and surgical complexity score &gt;4. Large bowel resection, stoma formation, ileocecal resection/right hemicolectomy, mesenteric resection, bladder and upper abdominal peritonectomy were amongst sub-procedures clearly associated with increased intervention risk. Precise prediction of blood requirements is not possible unless a rough estimate of OT is known in advance.

Preserving and restoring biodiversity is becoming a great challenge as we face a world where planetary boundaries will likely be crossed over the following decades. Such challenge needs to consider multiple scales of complexity, both in space and time. A common thread in most cases is the presence of nonlinear phenomena generating shifts among alternative states. These breaking points imply a new perception of risk and different management strategies. A broad range of phenomena affect the preservation of healthy communities and constrain the ways to deal with conservation, from local features associated with habitat loss or facilitation to mesoscale or global network-level ecological complexity and the role played by extreme events. How are these scales connected? How can the emergent properties associated with ecosystem dynamics be exploited? Here a synthesis of ideas is presented, with a complex systems view of the different scales involved, the emergent phenomena separating them, and the universal properties that allow defining simple models on each scale.

Background: Autoimmune inner ear disease (AIED) is a rare autoimmune condition characterized by progressive sensorineural hearing loss with hearing fluctuations over weeks to months, presenting significant challenges in both diagnosis and treatment. Due to its rarity, treatment responses and prognosis in AIED remain poorly understood. Methods: This study reviewed medical records from Taipei Medical University Hospital documented between August 2016 and August 2021. Among 67 patients experiencing fluctuating hearing loss, 11 met the diagnostic criteria for AIED and underwent regular follow-up assessments within a 5-year timeframe. ROC curve was used to discriminate the power of these prognostic parameters. Results: In this study, several factors including younger age, milder initial hearing loss, meeting criteria for bilateral Meniere's disease (MD), having an ascending audiogram pattern, longer time interval between hearing impairment attacks in contralateral ears and responding well to steroids were associated with better prognosis. ROC curve demonstrated the diagnostic value of specific parameters such as the presence of bilateral MD (AUC 0.825, 95% CI 0.640–1.000), pretreatment HI ≤ 45 dB HL (AUC 0.808, 95% CI 0.610–1.000), response to steroids (AUC 0.800, 95% CI 0.595–1.000), and ascending audiogram (AUC 0.858, 95% CI 0.683–0.858). Conclusions: This study identified key prognostic factors for AIED, providing valuable insights for predicting AIED prognosis and facilitating personalized patient management.

The aim of this study was to evaluate the clinical and radiographic outcomes of the All-on-4 technique in fully edentulous maxilla using R2GATE software for flapless, computer-guided surgery and immediate loading. Ten adult patients with fully edentulous maxilla, aged between 35 and 60 years, were included in the study between April 2021 and April 2022. The surgical procedure was performed under local anesthesia and followed the All-on-4 approach with immediate loading of implants using a screw-retained provisional acrylic resin prosthesis on the same day. Final prosthesis was delivered four months after the surgery. Clinical and radiographic outcomes were evaluated at four- and twelve-months post-operation. The study reported a 95% implant survival rate using the All-on-4 technique. The mean marginal bone level was recorded at 0.35 mm and 0.66 mm during the 4 and 12-month follow-up periods, respectively. Fixed provisional prosthesis fracture, abutment, and prosthesis screw loosening were the most frequent mechanical complications reported. Within the limitations of this study, the use of computer-guided surgery in the All-on-4 technique seemed to be a promising treatment option with high implant survival rates that may help reduce post-surgical discomfort and mechanical complications in the rehabilitation of the edentulous maxilla.

In the FCC conversion of heavy petroleum fractions as atmospheric residues, the main challenge for refiners to achieve the quantity and quality of various commercial products depends essentially on the catalyst used in the process. A deep characterization of the catalyst at different steps of the process (fresh, regenerated, and spent catalyst) was investigated to study the catalyst's behavior including the physicochemical evolution, the deactivation factor, and kinetic-thermodynamic parameters. All samples have been characterized by various spectroscopy methods such as N2 adsorption-desorption, UV-visible spectroscopy, Raman spectroscopy, LECO carbon analysis, Scanning electron microscopy (SEM), X-ray diffraction (XRD), X‐ray fluorescence (XRF), nuclear magnetic resonance spectroscopy (NMR13C) analysis, and Thermogravimetric analysis. The results of N2 adsorption-desorption, UV-vis, Raman, LECO carbon, and SEM images showed that the main causes of catalyst deactivation and coking were the deposition of carbon species that covered the active sites and clogged the pores, and the attrition factor due to thermal conditions and poisonous metals. The XRD and XRF results showed the catalyst’s physicochemical evolution during the process and the different interlinks between catalyst and feedstock (Nickel, Vanadium, Sulfur, and Iron) elements which should be responsible for the coking and catalyst attrition factor. It has been found that, in addition to the temperature, the residence time of the catalyst in the process also has an influence on catalyst structure transformation. NMR13C analysis revealed that polyaromatic hydrocarbon is the main component in the deposited coke of the spent catalyst. Thermogravimetric analysis showed that the order of catalyst mass loss was fresh > regenerated > spent catalyst due to the progressive losses of the hydroxyl bonds (OH) and the structure change along the catalyst thermal treatment. Moreover, the kinetic and thermodynamic parameters showed that all zones are non-spontaneous endothermic reactions.

Soiling accumulated on a photovoltaic (PV) module can significantly reduce the transmittance of the cover glass, resulting in power losses and consequent economic losses. Natural atmospheric parameters influence the accumulation of soiling at the various geographic locations. In this paper, the approaches and outcomes of the research studies on either indoor (simulator-based) or outdoor (field-based) PV soiling have been thoroughly reviewed. Different parameters depicted for the power loss of PV modules are analyzed individually and presented. Moreover, this study delves into a detailed examination of the key factors influencing dust depositions on PV modules in various geographical regions, with a particular focus on their relationship with climatic conditions. This way, probable future research directions to quantify soiling losses are identified. In addition, different loss prevention and mitigation techniques are also reviewed. This makes it possible to highlight effective strategies and pinpoint potential future research lines in these areas.

This study tests the utilization of Bluetooth noise-canceling headphones in improving the quality of eye exams in patients with hearing loss. University of Texas Medical Branch patients above 55 years of age were screened for hearing loss using SoundCheck audiometry. All 29 subjects (18 red-zone and 11 yellow-zone) answered pre-recorded Amsler grid and patient education questions that solicited precise responses. As controls, subjects were randomly administered half of the questions via headphones and half via a smartphone at normal speech volume (60 decibels). Points were awarded for responses demonstrating comprehension, and a post-exam survey was collected. Collectively, the mean score was 1.79 with headphones versus 0.96 with control on the Amsler grid segment and 1.90 with headphones versus 0.97 with control on education questions (p=0.001). Between the red and yellow zone hearing loss patients, the red-zone group answered significantly better in both Amsler (1.78 versus 0.50; p=0.0003) and education questions (1.88 versus 0.44; p&lt;0.0001) with headphones. The yellow zone group answered better with headphones overall but failed to reach significance. Post-exam survey indicated that 28 of 29 patients (97%) preferred the headphones during ophthalmic exams. Patients with severe hearing loss demonstrated better comprehension with the noise-canceling headphones; thus these devices show great promise in improving effective, compassionate communication between providers and hearing-loss patients.

Liquidity providers for asset-pair pools with constant value distri- bution, such as Balancer pools, experience some impermanent loss whenever there is price divergence in the tokens’ fiat values. In this paper, we model this impermanent loss for geometric mean invariant pools by deriving a function of two parameters. We analyze our function graphically, showing that unevenly distributed pools with large weighting disparities best mitigate the risk of impermanent loss. We conclude by providing a general protocol for liquidity providers to choose a suitable pool based on their risk tolerance and profit goals.

Acute respiratory viruses (ARVs) are leading cause of diseases in human worldwide. High risk individuals including children and elderly could potentially develop severe illness that could result in hospitalization or death in the worst case. Most common ARVs are Human respiratory syncytial virus, Human Metapneumovirus, Human Parainfluenza Virus, rhinovirus, coronaviruses (including SARS and MERS CoV), adenoviruses, Human Bocavirus, enterovirus (-D68 and 71), and influenza viruses. The olfactory deficits due to ARVs infection is a common symptom among patients. This mini review provides an overview of the role of SARS-CoV-2 and other common ARVs in the development of human olfactory pathophysiology. We highlight the critical need for understanding the signaling underlying the olfactory dysfunction and the development of therapeutics for this wide-ranging category of AVRs to restore the altered or loss of smell in affected patients.

The electrical motor design requires a lot of work and resources. In the field, motor designers need to decide on competitive motor sizing quickly to compete with other motor suppliers. Generally, it requires expensive FEM S/W to get accurate motor sizing results, but buying and maintaining many licenses is costly. Moreover, it needs some patience to get the result from FEM analysis. In this paper, the motor sizing technique using an existing production motor is presented to respond to urgent requests from customers without using FEM analysis. In order to enhance the fidelity of the result, magnetic flux loss by magnet coating and non-linear characteristics are considered during the motor sizing process. The proposed sizing method was verified by comparison to the FEM analysis and test result and showed reasonable confidence in them. Also, this method has the substantial advantage of outputting accurate results instantly without taking any time. It helps with the modification design of electrical motors without using expensive FEM S/W and a certain level of skill or experience.

A friction loss model for brake testing platform is constructed to revise the braking force test results, which can largely improve the accuracy of automotive brake performance testing. Specifically, the influence of tire pressure, vehicle axle load, placement angle and vehicle speed on the friction loss is tested and analyzed on a wheelbase adjustable automotive anti-force brake testing platform. The friction loss model for the platform is constructed based on the defined relative slip and placement angle, which is validated through actual tests on four types of vehicles. The results showed that the maximum relative error between the values of the model calculated simulation and the measured was 2.2%, indicating the friction loss model is valid and can provide a basis for revising the braking force of automotive brake. Meanwhile, the maximum braking force increases from 3982 N to 4772 N, increased by 19.8%, when the placement angle increased from 36.9° to 47.0°. Accordingly, in order to improve the accuracy of detection results of the automotive anti-force rolling brake testing platform, the friction loss caused by the change in the placement angle should be revised, and then braking rate of the vehicle should be judged according to GB 7258-2017 and GB 38900-2020.

At present Coronavirus disease-2019 (COVID-19) is one of the leading contributing factor to mortality and the impact of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection on the sinonasal tract has become more prominent, particularly with the rising awareness of olfactory dysfunction (OD). We extracted data from published papers available in electronic databases (Wiley online library, PubMed, and Nature). We used the following search terms alone or with combinations - Olfactory dysfunction, SARS-CoV-2, mechanism and treatments. We found worldwide up to 98% of patients confirmed OD due to COVID-19. Current studies have implied that regardless of the high self-reported recovery rate, 25–40% of patients after 1 or 2 months and approximately 15%–28% of patients at six months struggle to fully restore their sense of smell. Moreover, female sex, younger and older age, active smoking, and chronic lung disease are reported as the associated risk factors of OD. Although the pathophysiological mechanism of action(s) of the OD is yet to be explored in depth, central nervous system (CNS) entrance, olfactory bulb (OB) and sustentacular cell damage, neural routes inflammation, non-neuronal cells damage, decreased OB volume and deregulation of olfactory receptor genes are among the commonly reported mechanisms for the development of OD.

Optic neuritis (ON) is the most common cause of vision loss in young adults. It manifests as acute or subacute vision loss, often accompanied by retrobulbar discomfort or pain on eye movements. Typical ON is associated with Multiple Sclerosis and is generally mild and steroid-responsive, whereas atypical forms are characterized by unusual features, such as optic disc edema, poor treatment response and bilateral involvement, and are often associated with autoantibodies against aquaporin-4 (AQP4) and Myelin Oligodendrocyte Glycoprotein (MOG). However, in rare cases AQP4 and MOG antibodies will come back negative, plunging the clinician in a diagnostic conundrum. Seronegative ON warrants a broad differential diagnosis, including autoantibody-associated, granulomatous, and systemic disorders. These rare forms need to be identified promptly, as their management and prognosis is greatly different. The scope of this review is to describe possible, rarer etiologies of ON when AQP4 and MOG antibodies are negative and discuss their diagnosis and treatment.

Diabetes is one of the fatal diseases that play a vital role in the growth of other diseases in the human body. Controlling and curing diabetes in its early stages is the most significant technique to avoid its effects of diabetes. However, lack of awareness and expensive clinical tests are the primary reasons to skip clinical diagnosis and take preventive methods in lower-income countries like Bangladesh, Pakistan, and India. From this perspective, the study aims to build an automated machine learning (ML) model, which will predict diabetes at an early stage using socio-demographic characteristics rather than clinical attributes. Because clinical features are not always known to all people from lower-income countries. To find the best fit supervised ML classifier of the model, we applied six classification algorithms and found that RF outperformed with an accuracy of 99.36%. In addition, the most significant risk factors were found based on the SHAP value by all the applied classifiers. The study reveals that polyuria, polydipsia, and delayed healing are the most significant risk factors for growing diabetes. The findings indicate that the proposed model is highly capable of predicting diabetes in the early stages.

The utilization of primary school buildings is multifaceted, primarily due to the high occupancy density, varying thermal preferences among occupants, diverse indoor activities (such as walking, sports, and conversation), and a constant flow of individuals entering and exiting the building. This results in frequent opening and closing of external windows and doors and fluctuations in internal heat gain. Consequently, frequent interactions between the indoor and outdoor microenvironments lead to energy losses. This study conducts a comprehensive literature review on building energy loss stemming from occupant behavior and the interactions between indoor and outdoor microenvironments. Furthermore, it proposes a dynamic real-time monitoring system based on a computer data capture and visualization platform foundation for building energy loss. The research methods include data crawling, data association rule mining, and data association analysis. The research findings yield a universally applicable and informative building energy-saving design theory based on extensive data analysis. Additionally, the system presents information on occupants' behavior and the microclimate data of indoor and outdoor environments on a computer screen, facilitating human-machine communication and enabling timely adjustments to design strategies for new buildings and operation and maintenance strategies for existing buildings.

Polycystic ovary syndrome (PCOS) is an insulin resistant state, compensated by hyperinsulinemia. More than 50% of the women with PCOS are obese, and/or have metabolic syndrome. Weight loss improves both metabolic and reproductive outcomes. Not only the energy content, but also the nutrient composition of a diet may be important. This article will present a series of studies from our research comparing effects of dietary protein vs. simple-carbohydrates (CHO). Results of the acute challenge studies demonstrate that simple-CHO intake causes reactive hypoglycemia in one third of the women with PCOS, especially among obese and insulin resistant individuals. Symptoms of hypoglycemia are associated with secretion of cortisol and adrenal androgens. Simple-CHO suppresses the hunger signal ghrelin for a shorter period. During weight loss, women who receive protein supplementation achieve larger amounts of weight- and fat-mass losses. Amino acid compositions of the protein supplements do not affect the improvements in weight and insulin resistance. It is plausible that simple-CHO intake leads to weight gain, or interferes with weight-loss, by causing reactive hypoglycemia, triggering adrenal steroid secretion, and leading to snacking. Since obese women with PCOS are more susceptible to reactive hypoglycemia, a vicious cycle establishes. Restriction of simple-CHO may break this cycle.

The research paper provides a mathematical framework for understanding phase shift in wave phenomena, bridging theoretical foundations with real-world applications. It emphasizes the importance of phase shift in physics and engineering, particularly in fields like telecommunications and acoustics. Key equations are introduced to explain phase angle, time delay, frequency, and wavelength relationships. The study also introduces the concept of time distortion due to a 1° phase shift, crucial for precise time measurements in precision instruments. The research also addresses infinitesimal wave energy loss related to phase shift, enriching our understanding of wave behavior, and impacting scientific and engineering disciplines.

This article presents a new design of supporting tethers through the concept of force distribution. The transmitted force applied on tethers will be distributed on the new tether design area resulting in low acoustic energy transferred to anchor boundaries and stored energy enhancement. This technique achieves an anchor quality factor of 175,000 compared to 58,000 obtained from con-ventional tether design representing 3-fold enhancement. Also, the unloaded quality factor of the proposed design improved from 23,750 to 27,442 representing 1.2-fold improvements.

Background: this study aimed to describe the distribution of the genotype and allele frequencies of GJB2 variants in the Chinese population of the Dongfeng Tongji cohort and to analyze the features of the hearing phenotype. Methods: we used data from 9910 participants in the Dongfeng Tongji cohort in 2013 and selected nine GJB2 variants. Pure-tone audiometry was employed to measure hearing. Differences in genotype and allele frequencies were analyzed by chi-squared test or Fisher's exact test. Results: of the 9910 participants, 5742 had hearing loss. The genotype frequency of the GJB2 variant p.V37I was statistically significantly distributed between the normal and impaired hearing groups, but not for the variant c.235delC. A higher frequency of the p.V37I homozygous genotype was found in the hearing loss group (0.5%) than in the normal hearing group (0.1%). Patients with p.V37I and c.235delC homozygous mutations exhibited varying degrees of hearing loss, mainly presenting sloping and flat audiogram shapes. Conclusions: a significant difference was found in the genotype frequency of the GJB2 variant p.V37I between the case and control groups, but not for the variant c.235delC. Different degrees of hearing loss and various audiogram shapes were observed in patients with p.V37I and c.235delC homozygous mutations.

Temporal lobe epilepsy is a common, chronic disorder with spontaneous seizures that is often refractory to drug therapy. A potential cause of temporal lobe epilepsy is primary brain injury, making prevention of epileptogenesis after the initial event an optimal method of treatment. Despite this, no preventive therapy for epilepsy is currently available. The purpose of this study was to evaluate the effects of anakinra, lamotrigine, and their combination on epileptogenesis using the rat lithium-pilocarpine model of temporal lobe epilepsy. The study showed that the treated and untreated animals showed no significant difference in the number and duration of seizures. However, the severity of seizures was significantly reduced after treatment. Anakinra and lamotrigine, alone or in combination, significantly reduced neuronal loss in the CA1 hippocampus compared to the control group. However, the drugs administered alone were found to be more effective for CA3 than their combination. The treatment alleviated the impairments in activity level, exploratory behavior and anxiety, but had a relatively weak effect on TLE-induced impairments in social behavior and memory. The efficacy of the combination treatment did not differ from that of anakinra and lamotrigine monotherapy. These findings suggest that anakinra and lamotrigine, alone or in combination, may have clinical utility in preventing epileptogenesis.

Eosinophilic Granulomatosis with Polyangiitis (EGPA) is a rare systemic necrotizing vasculitis, affecting small-to-medium sized vessels. EGPA’s clinical manifestations are heterogeneous affecting different organs and systems and the upper respiratory tract can be affected with Ear, Nose and Throat (ENT) involvement. The aim of our study was to assess type manifestations at time of diagnosis in a cohort of EGPA patients and correlate findings with baseline variables (sex, age, antineutrophil cytoplasmic antibodies –ANCA- status) and literature reports. Main ENT manifestations in our patients at time of diagnosis were: nasal polyposis (CRSwNP) (52%), turbinate hypertrophy (48%), nasal swelling (40%), rhinorrhoea (40%), chronic rhinosinusitis without nasal polyposis (CRSsNP) (32%), nasal bone deformities (32%), nasal crusts (20%), nasal mucosal ulcers (12%), corditis (12%), hoarseness/dysphonia (12%), hearing loss (12%), mucoceles(4%) eosinophilic rhinitis (4%). No correlations were found between sex, age, ANCA status and ENT clinical manifestations. A polymorphic ENT involvement is often observed at early stages of EGPA. The presence of nasal, sinus, ear and/or laryngeal manifestations in patients with asthma and hypereosinophilia, independently of sex, age or ANCA status, should raise allert for further investigation and differential diagnosis for EGPA. ENT specialists should be aware of their leading position in this diagnostic race.

The purpose of this study was to investigate the functional load capacity of the periodontal ligament (PDL) in a full arch maxilla and mandible model using numerical simulation. The goal of was to determine the functional load pattern in multi- and single rooted teeth with full and reduced periodontal support. CBCT data were used to create 3D-models of a maxilla and mandible. The DICOM dataset was used to create a CAD-model. For a precise description of the surfaces of each structure (enamel, dentin, cementum, pulp, PDL, gingiva, bone), each tooth was segmented separately, and the biomechanical characteristics were considered. A Finite-Element-Analysis (FEA) software computed the biomechanical behavior of stepwise increased force of 700N in cranial and 350N in ventral direction of the muscle approach of the Masseter muscle. The periodontal attachment (cementum-PDL-bone contact) was subsequently reduced in 1mm increments and the simulation repeated. Quantitative (pressure, tension, and deformation) and qualitative (color-coded images) data were recorded and descriptively analyzed. The teeth with the highest load capacities were the upper and lower molars (0.4-0.6MPa), followed by the premolars (0.4-0.5MPa) and canines (0.3-0.4MPa) when vertically loaded. Qualitative data showed that the area with the highest stress in the PDL were for single rooted teeth the cervical and apical area and for molars additionally the furcation roof. In both, single- and multi rooted teeth the gradual reduction of the bone levels caused an increase of the load on the remaining PDL. Cervical and apical areas as well as the furcation roof are the zones with the highest functional stress. The more bone loss, the higher the mechanical load on the residual periodontal supporting structures.

Our findings indicate that all five phytocannabinoids reduce HG-HL-induced -cell loss likely through reducing apoptosis and pyroptosis. The protective effects of CBD, THCV, CBC, and CBN were seen in the GSIS impairment by HG-HL. Although all five phytocannabinoids tested in this research demonstrated the capability to inhibit β-cell dedifferentiation induced by HG-HL, CBD seems to be more effective compared to the other phytocannabinoids, as indicated by the specific biomarker responses of β-cells and progenitor cells to CBD.

Results of profile loss measurements, including trailing edge flow details, are presented for the flow of an organic vapor through a linear turbine cascade. The so-called VKI-I blade profile from the open literature was chosen for the cascade, and the working fluid was NOVEC 649. Pitot probes and hot wire anemometry were employed to measure the flow field up and downstream of the cascade. Details of the unsteady flow caused by the trailing edge of the blades and the turbulent spectrum were investigated using hot-wire anemometry. The new organic vapor flow results were compared with literature data obtained for air and with the prediction of conventional literature loss models. It was found that under certain thermodynamic conditions, specific traditional loss models can reasonably predict organic Rankine cycle (ORC) turbines' profile loss. Still, significant deviations between the loss models and the experimental data can also occur.

When training deep neural networks tasks, the most popular choices are cross-entropy loss. On the other hand, in general speaking, a decent loss function can take on shapes that are considerably more flexible and ought to be adapted for different activities and datasets. In most of the classification tasks, generally if the true class is not correctly recognized by the network (top1), that class is placed among the five classes with the highest probability (top5). This shows that the network does not necessarily recognize the correct class with a low probability, but a class similar to it (such as 3 vs. 8 in mnist) assigns a higher probability and this causes a mistake in that task. Accordingly, we proposed a loss function deals with the error of class that the neural network incorrectly recognized as correct, in addition to the correct class error. We call our proposed loss as False Positive Loss (FPL), with the intention of viewing and designing loss functions not only through the utilization of true class but also through the utilization of the value of false positive classes. One of the core properties of our proposed loss is full adaptability, which makes False Positive Loss be fully capable of getting reformulated by using other widely used loss functions formulas based on the task or the need of the users. Extensive experimental results demonstrate that our suggested loss function outperforms other well-known losses on a variety of tasks and datasets. As can be observed, the performance of our False Positive Loss is superior to that of the cross-entropy loss when it comes to tasks involving 2D picture classification. We have compared our loss with cross entropy as the most common classification loss function on some models (such as ResNet-18, ResNet-50 and Efficientnet-V2) through classification known as a basic computer vision task. with both random or pre-trained initial weights. As a result, in some cases the models with our loss outperform the same tasks with cross entropy from the viewpoint of some metric (i.e. accuracy and FP). For example, the resnet-50 on cifar-10 dataset with random initialization indicated a top1 accuracy of 94.93 with cross entropy and 95.25 with our loss, while for top5 accuracy the results are 99.86 and 99.87, respectively.

This study aimed to compare the differences in durability and prestress loss between normal-weight concrete (NC) and lightweight aggregate concrete (LWC) prestressed box girders, which were constructed at the same time in the same area, so as to verify the superiority of using synthetic lightweight aggregate (LWA) made from reservoir sediments in prestressed bridges. For the NCs and LWCs used in prestressed box girders, the basic mechanical properties were tested on the one hand, and the durability properties were tested on the other hand. Then, through the prestress monitoring system, the prestress loss of the two groups of the prestressed box girders was tracked. The results of the durability test confirmed that LWC can inhibit the penetration of air, water, and chloride ions by strengthening the interfacial transition zone between the aggregate and the cement paste, thereby improving its durability. Moreover, the magnetic flux prestress loss of the NC prestressed box girder reached 8.1%. In contrast, the magnetic flux prestress losses on both sides of the LWC prestressed box girder were 4.6% and 4.9%, respectively. This verified that, under the same environmental conditions, the use of LWC produced less of a prestress loss than the use of NC.

Tissue bioengineering has been assuming a pivotal role in implementing alternatives to conven-tional ossicular middle ear replacement prostheses to overcome extrusion while preserving acoustic properties. This in vitro study aims to explore for the first time in current literature the feasibility of a biohybrid middle ear prosthesis composed of titanium surrounded by bone ex-tracellular matrix as bio-coating. We have hereby studied the adhesion and proliferation of human adipose-derived mesenchymal stem cells (hASC) on titanium scaffolds in vitro. Moreover, we identified the osteogenic differentiation of hASC using immunofluorescence assay to analyze osteoblasts gene expression profile (Alp, Runx2, Col1a1, Osx, and Bglap) and we accounted the presence of collagen as a marker of hASC ability to secrete extracellular matrix. We utilized scanning electron microscopy to evaluate the presence of extracellular matrix on the scaffolds. Our preliminary data demonstrated the titanium ability to support human adipose-derived mesenchymal stem cell colonization, proliferation, and osteoblastic differentiation, to obtain a biohybrid device. Our experience seems encouraging, we advocate further in vivo research to corroborate our results towards bone transplantation.

The changes in storage loss, water distribution status, gel characteristics, TBARS, total volatile basic nitrogen, and total plate count of cooked reduced-phosphate silver carp surimi batter during cold storage at 4 °C were investigated. The storage loss, content of free water, pH, hardness, TBARS, total volatile basic nitrogen value and total plate count of all cooked reduced-phosphate silver carp surimi batters significantly increased (P < 0.05) with increasing the cold storage time. Meanwhile, the content of immobilized water, whiteness, springiness, and cohesiveness decreased significantly (P < 0.05). At the same cold storage time, the sample of cooked reduced-phosphate silver carp surimi batter has lower water mobility, darker colour and better texture characteristics, but the values of TBARS, total volatile basic nitrogen and total plate count were not significantly different (P > 0.05). To sum up, the use of potassium bicarbonate instead of sodium tripolyphosphate could produce the cooked reduced-phosphate silver carp surimi batter with better water holding capacity and gel characteristics during cold storage.

The Colony-Forming Unit (CFU) counting problem remains a complex issue without a universal solution in biomedical and food safety domains. A multitude of sophisticated heuristics and segmentation-driven approaches have been proposed by numerous researchers. Among those, U-Net is the most frequently cited and popular Deep Learning method. The latter approach provides a segmentation output map and requires an additional counting procedure which accounts for unique segmented regions and detected microbial colonies. However, because of pixel-based targets it tends to generate irrelevant artifacts or errant pixels, leading to inaccurate and mixed post-processing results. In response to these challenges, we propose a novel hybrid counting approach, incorporating a multi-loss U-Net reformulation and a post-processing Petri dish localization algorithm. First of all, our unique innovation lies in the multi-loss U-Net reformulation. We introduce an additional loss term at the bottleneck U-Net layer, focusing on delivering an auxiliary signal indicating where to look for distinct CFUs. Second, our novel localization algorithm accurately incorporates an agar plate and its bezel into the CFU counting routines. Finally, our proposition is further enhanced by the integration of a fully automated solution. This comprises a specially designed uniform Petri dish illumination system and a counting web application. The latter application is capable of directly receiving images from the camera, which are subsequently processed, and the segmentation results are sent back to the user. This feature provides an opportunity to correct the CFU counts, offering a feedback loop that contributes to the continued development of the Deep Learning model. Through extensive experimentation, we have found that all probed multi-loss U-Net architectures incorporated in our hybrid approach consistently outperform their single-loss counterparts which utilize exclusively the combination of Tversky and Cross-Entropy training losses at the output U-Net layer. We report further significant improvements by the means of our novel localization algorithm. This reaffirms the effectiveness of our proposed hybrid solution in addressing contemporary challenges of the precise in-vitro CFU counting.

Microwave absorbers with lightweight, good stability and high efficiency have attracted much attention for their applications in many contemporary fields. In this work, the 3D porous (Ni@NO-C)n/NO-C composite absorber was prepared by a wet chemistry method with Ni chains and melamine as precursors, in which NO-C (N,O-doped carbon) encapsulated Ni particles are homogenously dispersed in the 3D porous networks of NO-C in the form of (Ni@NO-C)n chains. The special microstructure of the as-prepared material is proved to be benefit for the improvement of its microwave adsorption performance. The as-synthesized (Ni@NO-C)n/NO-C composite ab-sorber exhibited an effective absorption bandwidth of 4.1 GHz and an extremely large reflection loss of -72.3 dB. The excellent microwave absorbing performances can be ascribed to the coopera-tive consequence of dielectric loss and magnetic loss along with the balance between attenuation capability and impedance match.

Underwater target detection is widely used in various applications such as underwater search and rescue, underwater environment monitoring, and Marine resources survey. However, the visibility of the underwater environment and the accuracy of target detection can be affected by complex underwater light changes and unpredictable background noise. To address these issues, we propose an improved underwater target detection algorithm based on YOLOv8n. Our algorithm focuses on three aspects. Firstly, we replace the original C2f module with Deformable Convnets v2 to enhance the adaptive ability of the target region in the convolution check feature map and extract the target region's features more accurately. Secondly, we introduce SimAm, a non-parametric attention mechanism, which can deduce and assign three-dimensional attention weights without adding network parameters. Lastly, we optimize the loss function by replacing the CIOU loss function with the Wise-IOU loss function. To conduct our experiments, we create our own dataset of underwater target detection for experimentation. Meanwhile, we also utilized the Pascal VOC dataset to evaluate our approach. The mAP@0.5 and mAP@0.5:0.95 of the original YOLOv8n algorithm on the underwater target detection were 88.6% and 51.8%, respectively, and the improved algorithm mAP@0.5 and mAP@0.5:0.95 can reach 91.8% and 55.9%. The original YOLOV8n algorithm was 62.2% and 45.9% mAP@0.5 and mAP@0.5:0.95 on the Pascal VOC dataset, respectively. The improved YOLOV8n algorithm mAP@0.5 and mAP@0.5:0.95 were 65.7% and 48.3%, respectively. The floating-point computation volume of the model is reduced by about 6%. The above experimental results prove the effectiveness of our method.

The study presented here, through the use of GIS and physical variables, generate a new meth-odology for the calculation of erosivity (Factor R) for the qualitative evaluation of soil loss po-tential (laminar erosion) in the Northwest margin of the municipality of São Francisco, mostly located in the Pardo-MG river basin. The results obtained were statistically correct when com-pared to the traditional R calculation and the laminar erosion methodology. It is worth noting that the new proposal presented here indicated sites of qualitative loss of soil in the same places where there are closed-loop satellite signals of degraded Cerrado, something not identified in the traditional model. As conclusion it can be said that the obtained results were extremely sat-isfactory, being advised more studies to verify this new method proposed here in more places beyond the study area elaborated here

Modeling and assessing the sustainability of machining systems has been considered to be a crucial approach to improving the environmental performance of the machining processes. As the most common machining system, the computer numerical control (CNC) milling system is a typical man-machine cooperative system where the activities of the machine tool and operator generate material and energy consumption. However, the energy consumption of the operator in the CNC milling system has often been ignored in most existing research. Therefore, existing methods fail to provide a comprehensive understanding of the sustainability of the CNC milling system. To fill this gap, an exergy loss assessment method is proposed to investigate the sustainability of the CNC milling system, where the energy consumption of the operator, the energy consumption of the machine tool, and material consumption are taken into consideration. The key performance indexes of the energy consumption of the operator, the energy consumption of the machine tool, the exergy loss, and the specific exergy loss (SEL) are analyzed and modeled. To demonstrate the feasibility of the proposed method, a case study was carried out on a three-axis machining center (XH714D), in which SEL was found to be 88.04J/mm3. The proposed method is effective to assess the sustainability of the CNC milling system, and the established exergy loss models build a good basis for exergy efficiency optimization.

Evaporating liquid sessile drop deposited on horizontal surface is an important object of applications (printing technologies, electronics, sensorics, medical diagnostics, hydrophobic coatings, etc.) and theoretical investigations (microfluidics, self-assembly of nanoparticle, crystallization of the solute, etc.). The arsenal of formulas for calculating the slow evaporation of an axisymmetric drop of capillary dimensions deposited on a flat solid surface is reviewed. Such characteristics as vapor density, evaporation flux density, total evaporation rate are considered. Exact solutions obtained in the framework of the Maxwellian model, in which the evaporation process of the drop is limited by vapor diffusion from the drop surface to the surrounding air, are presented. The summary covers both well-known results obtained during the last decades and new results published by us in the last few years, but practically unknown to the wide scientific community. The newest formulas, not yet published in refereed publications, concerning exact solutions for a number of specific contact angles are also presented. In addition, new approximate solutions are presented for the first time (total evaporation rate and mass loss per unit surface area per unit time in the whole range of contact angles ), which can be used in modeling without requiring significant computational resources.

A novel prediction model for crack development of reinforced concrete (RC) piles with localized chloride corrosion in marine environment is proposed. A discrete method is used to solve the corrosion pit radius model and a crack extension model is developed to investigate the initiation and extension of cracks. The maximum corrosion degree of reinforced concrete pile is predicted according to the limit crack criterion, and finally a sensitivity analysis is carried out on the important parameters of crack extension. The results show that the radius of corrosion pit, the depth corrosion pit and cross-sectional area loss of reinforcement gradually increase as the corrosion level increases. The loss of local reinforcement section at crack initiation decreases with the increase of the ratio of concrete cover to initial diameter, and increases with the increase of pitting factor. The required pit depth for reinforcement cracking increases with the increase of the ratio of concrete cover thickness to diameter. The loss of cross-sectional area of reinforcement and the radius of corrosion pit increase with the increase of initial diameter of reinforcement. Increasing the pitting factor will reduce the pit depth and make the crack width develop faster before reaching the limit crack width. Increasing the concrete cover thickness can provide an improvement in the propagation of cracks. A comparative analysis shows that the localized corrosion pattern is more in conformity with marine engineering practice.

Chlorhexidine digluconate (CHX) has shown the ability to significantly reduce inflammation and marginal bone loss (MBL) at 1-year follow-up but limited data exists regarding its long-term efficacy in peri implant stability. The objective was to compare the long-term effects of a placebo gel (16 patients in Group A) or a 0.20% CHX gel (15 patients in Group B) used at each previous surgical and prosthetic stage. Follow-ups were conducted in 2022, investigating by biological, radiological, clinical, mechanical evaluation the long-term effects. Data were statistically analyzed. The research achieved a 96.7% implant success rate over five years, but 41.9% of patients didn't attend annual oral hygiene check-ups. The average MBL was 1.04 ± 0.39 mm, with no significant differences between the two groups. Notably, patients who attended regular periodontal check-ups experienced significantly less MBL than those who didn't (p &lt;0.05). At five years, the effects of CHX were reduced, with both groups showing moderate bone loss. The results suggest early disinfection could enhance both short and long-term outcomes. In fact, patient with initial minor MBL preserve this advantage also at 5 years of follow-up. Additionally, the data underscore the importance of annual check-ups in early detection and management of biological and mechanical complications.

The epistemology of the traditional risk assessment examined has a taxonomy based upon deterministic, behaviouristic and compatibilist methodologies which are likely driven by neo-liberal market related requirements for bigger, faster cheaper wind-turbines. Analysis of available risk assessments suggested that there is no conscious effort to deceive the reader although the intended audience is unclear. The language, and scoring mechanisms utilized indicates the presence of conformity bias, confirmation bias, and numerical inconsistency leading to data ossification. By reverse engineering risk assessment content, Pragmatic and Social Psychological aspects can be investigated, and the adequacy of the document can be evaluated using evidence-based models.