Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Different Capsulotomy and Fragmentation Energy Levels on the Generation of Oxidative Stress Following Femtosecond Laser-Assisted Cataract Surgery

Purpose. This study was conducted to evaluate the effects of different capsulotomy and fragmentation energy levels on the production of oxidative free radicals following femtosecond laser-assisted cataract surgery (FLACS) with a low-energy platform. Methods. The experimental study included 60 porcine eyes (12 groups). In each group, capsulotomies with 90% or 150% energy, and fragmentations with 90%, 100%, or 150% energy or 150% with high spot density, respectively, were performed. Control samples were obtained from non-lasered eyes at the beginning (five eyes) and end (five eyes) of the experiment. In the clinical study, 104 eyes were divided into 5 groups, and they received conventional phacoemulsification (20 eyes), FLACS with 90% capsulotomy and 100% fragmentation energy levels without NSAIDs (16 eyes), FLACS with 90% (26 eyes) or 150% (22 eyes) capsulotomy energy levels, respectively, with a 100% fragmentation energy level and NSAIDs, and FLACS with 90% capsulotomy and 150% fragmentation energy levels and NSAIDs (20 eyes). Aqueous samples were analyzed for their malondialdehyde (MDA) and superoxide dismutase (SOD) levels. Results. In the experimental study, there were no significant differences in the MDA and SOD levels between the groups with different capsulotomy energy levels. An increase in the fragmentation energy from 100% to 150% led to significantly higher MDA levels in the groups with both 90% (p = 0.04) and 150% capsulotomy energy levels (p = 0.03), respectively. However, increased laser spot densities did not result in significant changes in MDA or SOD levels. In the clinical study, all four of the FLACS groups showed higher MDA levels than the conventional group. Similarly, the increase in the fragmentation energy from 100% to 150% resulted in significantly elevated levels of MDA and SOD, respectively. Conclusions. Although increasing the FSL capsulotomy energy level may not have increased free radicals, higher fragmentation energy levels increased the generation of aqueous free radicals. However, fragmentation with high spot density did not generate additional oxidative stress. Increased spot density did not generate additional oxidative stress, and this can be helpful for dense cataracts.
Segmentación de los turistas sobre la base de su comportamiento espacio-temporal en destinos culturales

El objetivo del trabajo es segmentar a los turistas de acuerdo con su comportamiento espacio-temporal en un destino cultural. Para ello se analizan los lugares que visitan, el tiempo que están en cada uno de ellos y el orden en el que realizan la visita. Para poder conocer la ruta seguida por los turistas, se han usado los datos de ubicación que proporciona la cronología de Google. El análisis de datos se ha realizado usando una metodología propia de la bioinformática, el alineamiento de secuencias. El uso de esta metodología resulta fundamental para la gestión estratégica de los destinos, ya que permite mejorar la gestión de los flujos, conocer las zonas con mayor densidad de visitantes y trabajar en su descongestión. Los resultados demuestran la existencia de cuatro segmentos que se diferencian en el número de zonas visitadas y en el tiempo que dedican a su visita.
Cytokines in Allergic Conjunctivitis: Unraveling Their Pathophysiological Roles

Allergic conjunctivitis is one of the common immune hypersensitivity disorders that affect the ocular system. The clinical manifestations of this condition exhibit variability contingent upon environmental factors, seasonal dynamics, and genetic predisposition. While our comprehension of the pathophysiological engagement of immune and nonimmune cells in the conjunctiva has progressed, the same cannot be asserted for the cytokines mediating this inflammatory cascade. In this review, we proffer a comprehensive description of interleukins 4 (IL-4), IL-5, IL-6, IL-9, IL-13, IL-25, IL-31, and IL-33, as well as thymic stromal lymphopoietin (TSLP), elucidating their pathophysiological roles in mediating the allergic immune responses on the ocular surface. Delving into the nuanced functions of these cytokines holds promise for the exploration of innovative therapeutic modalities aimed at managing allergic conjunctivitis.
The impact of long-distance travel to work on the health of commuting labour migrants: a literature review

This literature review analyzes the impact of commuting labour migration (CLM) on human health. Travel time is one of the major CLM factors affecting migrant health in both active and passive way. Fatigue and stress associated with commuting result in the increased blood pressure and risk of obesity. The paper also dwells upon the impact of CLM on worker stress by gender. The article also explores the relationship between CLM and mortality. Work-life balance plays a crucial role in migrant health, while satisfaction with life can be compromised due to insecure life style associated with CLM. There is an effect of adaptation that can influence migrant health in a positive way. In addition to negative aspects the article reviews benefits of CLM, including improved professional skills and higher income, and effective use of travel time. A special attention is payed to health of the Russian commuting migrants and their specific challenges and problems. The article is a comprehensive review of scientific literature on CLM impact of human health. the results obtained can be used to develop programs and policies aimed at improving health of labour migrants and mitigating negative effects of commuting labour migration.
Real-Time HIL Simulation of Nonlinear Generalized Model Predictive-Based High-Order SMC for Permanent Magnet Synchronous Machine Drive

The dynamics of the permanent magnet synchronous motor (PMSM) are described by nonlinear equations, which present challenges. Variations in external factors such as unidentified disturbances (loads) and evolving motor properties add complexity to control efforts. To tackle these intricacies and limitations, a nonlinear control approach is essential. Recent attention has turned to employing predictive control techniques for nonlinear multivariable systems, offering an intriguing avenue for research. In this context, this study introduces a novel hybrid control approach that addresses nonlinearity, parametric fluctuations, and external disturbances. The method combines two essential components: first, the outer loop utilizes high-order sliding mode control (HSMC) to optimize torque and trajectory speed, mitigating chattering phenomena while preserving the PMSM’s convergence and robustness traits. The inner loop, known as the current control, employs the newly developed nonlinear robust generalized predictive control (RNGPC) technique. Importantly, this strategy circumvents the need for direct measurement and observation of external disturbances and parameter uncertainties. The proposed strategy follows a two-phase process. Initially, the reference quadratic current is designed using the electromagnetic torque computed via HSMC, subsequently determining the necessary current to achieve the desired torque. The second phase involves computing the controller law through the robust generalized nonlinear predictive control technique. The approach’s strength lies in its ability to maintain stability and convergence in the face of external disturbances and parameter fluctuations, without necessitating precise measurements or knowledge of the disturbances. To validate the proposed control approach, simulation and experimental tests have been conducted across various operational scenarios. The obtained results demonstrate the method’s robustness against external disturbances and parameter changes while ensuring rapid convergence and reliable performance.
Enhancing Web Text Clustering Accuracy and Efficiency With a Maximum Entropy Function Model: Overcoming High-Dimensional and Directional Challenges

With the rapid development of large models such as Chatgpt, text clustering has become an important research topic in data mining. However, traditional clustering algorithms face challenges in terms of text clustering due to the high dimensionality and directionality of text data; in particular, the research on web text mining is insufficient, so the accuracy and efficiency of clustering algorithms need to be improved. Aiming at the above challenges, this paper proposes a maximum entropy function model and applies it to web text clustering to overcome these challenges and achieve better clustering results. Unlike the traditional clustering algorithm, this algorithm avoids the local minimum and realizes the global minimum. This study will help strengthen web text mining and provide valuable insights for future research. In summary, this paper proposes a novel text clustering method, MEMC, which uses the maximum entropy function model to overcome the challenges of high-dimensional and directional features. Compared with the popular algorithms in the international standard datasets, the method is 15% higher than the current popular k-means algorithm in purity and 6% higher than the AP algorithm.
In Vivo Osteogenic and Angiogenic Properties of a 3D-Printed Isosorbide-Based Gyroid Scaffold Manufactured via Digital Light Processing

Introduction: Osteogenic and angiogenic properties of synthetic bone grafts play a crucial role in the restoration of bone defects. Angiogenesis is recognised for its support in bone regeneration, particularly in larger defects. The objective of this study is to evaluate the new bone formation and neovascularisation of a 3D-printed isosorbide-based novel CSMA-2 polymer in biomimetic gyroid structures. Methods: The gyroid scaffolds were fabricated by 3D printing CSMA-2 polymers with different hydroxyapatite (HA) filler concentrations using the digital light processing (DLP) method. A small animal subcutaneous model and a rat calvaria critical-size defect model were performed to analyse tissue compatibility, angiogenesis, and new bone formation. Results: The in vivo results showed good biocompatibility of the 3D-printed gyroid scaffolds with no visible prolonged inflammatory reaction. Blood vessels were found to infiltrate the pores from day 7 of the implantation. New bone formation was confirmed with positive MT staining and BMP-2 expression, particularly on scaffolds with 10% HA. Bone volume was significantly higher in the CSMA-2 10HA group compared to the sham control group. Discussion and Conclusions: The results of the subcutaneous model demonstrated a favourable tissue response, including angiogenesis and fibrous tissue, indicative of the early wound healing process. The results from the critical-size defect model showcased new bone formation, as confirmed by micro-CT imaging and immunohistochemistry. The combination of CSMA-2 as the 3D printing material and the gyroid as the 3D structure was found to support essential events in bone healing, specifically angiogenesis and osteogenesis.
INDICATOR ENGINEERING FOR LAND TAKE CONTROL AND SETTLEMENT SUSTAINABILITY

In this paper, we describe some indicators used to interpret urban sprawl and some of its effects on the environmental and ecosystem matrix. These are examples taken from a number of research programs that the University of L’Aquila has been engaged in over the past ten years that have produced more than 15 new indicators of urban sprawl and the numerous threats that the latter poses for land and the environment. Using some parameters we were able to prove that the expansive settlement model that prevailed in Italy over the past 50 years does not follow the conventional international standard of sprawl, but has a different pattern named “sprinkling”. Other indicators show that this growth is independent of population dynamics, at least at microterritorial level (municipalities), while the result is different on a macroterritorial scale (regions). Furthermore, this highly sprinkled type of settlement also has adverse effects on the fragmentation of ecosystems and biodiversity hot spots and using other indices we were able to highlight these phenomena too, which are scarcely considered as territorial “diseases” that need to be tackled and overcome. Carefully designed sets of parameters, such as those described in this paper, should be included in technologyassisted regional platforms to control and govern land transformation, in order to make the pursuit of improved land planning more efficient than what it is today.
A Low Complexity Integrated Navigation System for Underwater Vehicles

This paper proposes a simplified algorithm for reducing the computational load of the conventional underwater integrated navigation system. The system usually comprises a three-dimensional accelerometer, a three-dimensional gyroscope, a three-dimensional Doppler Velocity Log (DVL) and a data fusion algorithm, such as a Kalman Filter (KF). Since the expected variations of roll, pitch and depth are small, these quantities are assumed to be constant, and the proposed system is designed in a two-dimensional form. Due to the low speed of the vehicle, the nonlinear dynamic equation of the velocity can be simplified in a linear form. We also simplify the conventional KF in order to avoid matrix multiplications and matrix inversions. The performance of the designed system is evaluated in a sea trial by an Autonomous Underwater Vehicle (AUV). The results show that the proposed system can significantly reduce the computational load of the conventional integrated navigation system without a significant reduction in position and velocity accuracy.
Impact of a Heart Team in patients with aortic stenosis who are candidates for transcatheter aortic valve replacement

As transcatheter aortic valve implantation (TAVI) for aortic stenosis (AS) became widespread, there arose the need for a Heart Team (HT) to choose the best treatment. There are few reports as regards its usefulness. Objectives: To analyze treatment outcomes in patients with AS evaluated by a HT for 10 years. Methods: Consecutive enrollment of all patients with AS who were candidates for TAVI between January 2012 and July 2021 to choose the best treatment, including surgical aortic valve replacement (SAVR) and conservative medical management (CMM). Results: Out of 841 patients, 455 were assigned to TAVI (53%), 213 to SAVR (24%), and 183 to CMM (23%). The percentage assigned to TAVI has increased from 48% to 62% over time (p <0.05). Patients who underwent TAVI versus those who underwent SAVR were older (86 ± 7 vs. 83 ± 7 years), had a higher EUROSCORE II (6.2, 95% CI 5.7-6.6 vs. 5.6; 95% CI 4.4-6.5) and were frailer (1.62 ± 1 vs. 0.91 ± 1) in all cases (p <0.01). Actuarial survival (95% CI) at 1 and 2 years was 88% (84-91%) and 82% (77-86%) for TAVI, 83% (76-88%) and 78% (70-84%) for SAVR, and 70% (60-87%) and 59% (48-68%) for CMM, respectively (p <0.001). Conclusions: For the first 10 years after a Heart Team was established for AS decision-making, approximately half of the patients were assigned to TAVI, and the rest were equally assigned in halves to either surgery or observation. Survival for patients who received interventions was similar at 2 years and higher than in those who did not.
SAR Image Feature Analysis for Slum Detection in Megacities

Urban areas have undergone major changes in the last decades. Especially in developing countries, megacities with more than 10 million inhabitants have developed. The number of such huge urban agglomerations is predicted to rise to 41 until 2030. The increasing influx of urban dwellers inevitably leads to the formation of informal settlements with poor living conditions. Monitoring, analysis and mapping of slums are necessary to provide information about such settlements and thus tackle these increasing challenges. Therefore, SAR remote sensing images are used in this study for an extensive mapping of slums conducted in Mumbai, India. In a broad experimental setup textural and morphological features are analyzed for the slum discrimination in an urban landscape. Two state-of-the-art supervised classification algorithms are compared in the experiments. By utilizing an area-wide reference data set, detailed accuracy assessment techniques are applied to determine the classification quality. The results indicate that it is possible to classify the urban landscape by using textural image features with an Overall Accuracy of 88.58% utilizing a Random Forest classifier. However, lower class specific accuracies of the slum areas show that slum mapping remains challenging. A patch based accuracy assessment proves that it is most difficult to detect small slum areas in the urban landscape. Furthermore, an experimental feature reduction experiment indicates that more image features are needed to detect slums than to discriminate urban and non-urban landscapes.
Rapid estimation of an earthquake impact area using a spatial logistic growth model based on social media data

ABSTRACT Rapid estimates of impact areas following large earthquakes constitute the cornerstone of emergency response scenarios. However, collecting information through traditional practices usually requires a large amount of manpower and material resources, slowing the response time. Social media has emerged as a source of real-time ‘citizen-sensor data’ for disasters and can thus contribute to the rapid acquisition of disaster information. This paper proposes an approach to quickly estimate the impact area following a large earthquake via social media. Specifically, a spatial logistic growth model (SLGM) is proposed to describe the spatial growth of citizen-sensor data influenced by the earthquake impact strength after an earthquake; a framework is then developed to estimate the earthquake impact area by combining social media data and other auxiliary data based on the SLGM. The reliability of our approach is demonstrated in two earthquake cases by comparing the detected areas with official intensity maps, and the time sensitivity of the social media data in the SLGM is discussed. The results illustrate that our approach can effectively estimate the earthquake impact area. We verify the external validity of our model across other earthquake events and provide further insights into extracting more valuable earthquake information using social media.
Node Localization Algorithm for Irregular Regions Based on Particle Swarm Optimization Algorithm and Reliable Anchor Node Pairs

In wireless sensor networks (WSN), node localization is a key function, and only by knowing the coordinate positions of the nodes can correct decisions be made. In certain applications, such as smart cities, environmental monitoring, or industrial automation, irregular areas can be complex and affected by environmental complexity and inhomogeneity. Coverage gaps may exist between the nodes to be located and the anchor nodes, and communication paths between the nodes may deviate significantly from the ideal straight line, resulting in a large error between the final positioning result of the algorithm and the actual position. In order to solve this problem, this paper proposes a non-ranging node localization method (RANP-PSO) for irregular regions based on PSO algorithm and anchor node pair selection. The way firstly selects anchor node pairs with higher reliability parameters for the nodes to be located by introducing the hop count constraint mechanism for distance estimation; then uses the regularized least squares method for further constraints on the estimated distances; Finally, the PSO algorithm is utilized to optimize the coordinates of the target node, so as to solve to obtain the position of the node. When the proportion of anchor nodes is 20%, the communication radius of nodes is 30m, and the distribution density of nodes is 0.008, the proposed algorithm reduces the root mean square error by approximately 11.94% compared to AEML and LRAQS algorithms, 7.26% compared to the BDMCL algorithm, and 0.69% compared to the MSVR-DV-Hop algorithm. This demonstrates the advantage of the proposed algorithm in terms of localisation accuracy.
Non-endodontic periapical radiopaque jaw lesions: A mini review

Endodontic practice may be affected by periapical radiopaque/ hyperdense lesions. Oral medicine specialists and endodontists may have trouble diagnosing and treating radiopaque lesions. Inflammatory, non-inflammatory, neoplastic, dysplastic, metastatic or metabolic bone changes may occur. With the increased use of cone-beam CT, a detailed review of radiopaque lesions may help clinicians differentiate these lesions. Differentiating inflammatory, non-inflammatory and neoplastic disorders simplifies diagnosis and helps choose the best treatment. Aim: The aim of this review was to investigate the periapical radiopaque/hyperdense lesions. An extensive review of the literature was carried through. The literature search was conducted using MEDLINE (National Library of Medicine)-PubMed, Web of Science and Google scholar without restrictions concerning the date of publication. The inclusion criterion was that the article should be written in English, whereas the exclusion criterion was the opposite. This literature review covers radiopaque/hyperdense lesion differential diagnoses, clinical, radiographic, histological, and management issues. The effectiveness of root canal therapy is measured by the absence of pain, the absence or reduction of periapical lesions, and the restoration of tooth function. In endodontic practice, the diagnosis of periapical lesions is difficult because many of these lesions can mimic endodontic lesions, even when derived from different sources. For the diagnosis of periapical lesions in this scenario, a comprehensive clinical examination, in conjunction with clinical and radiographic aspects of the disease, is essential. The oral medicine specialist and endodontist must know how to diagnose radiopaque periapical lesions. Knowing how to differentiate between inflammatory, non-inflammatory, neoplastic and metabolic lesions expedites diagnosis and ensures the selection of the appropriate treatment.
Magma emplacement in a thrust ramp anticline: The Gavorrano Granite (northern Apennines, Italy)

Magma emplacement in the upper crust is often associated with crustal extension, whereby space for intrusions is made by dilation along transtensive and strike‐slip faults. The lenticular shape of several intrusions indicates that a further mechanism for magma intrusion is laccolith emplacement with roof uplift of the overburden. Additionally, melts exploit rheological discontinuities (e.g., sedimentary layering) during their ascent. We present an emplacement model for intrusion of the shallow level Gavorrano Granite (northern Apennine, Italy), which is located at the core of an open anticline. The shape of the intrusion and structural features of the host rocks are indicative of a synkinematic emplacement in a growing thrust anticline. Space was provided by the opening of dilatation zones at the core of anticline as a consequence of different amounts of translation between hanging wall and footwall units which were separated by evaporitic rocks. These evaporitic units acted as major décollement layers. Analog models provide results in good agreement with the structural setting of the anticline and emphasize the possibility that melts filled the dilatation zone, with the décollement layers further facilitating intrusion.