Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence and Risk Factors of Delirium in Patients Admitted to Intensive Care Units: A Multicentric Cross-Sectional Study

Background Delirium is a common and serious complication among critically ill patients in the intensive care unit. Knowledge of the risk factors of delirium can help tremendously in the diagnosis of delirium. Methods In April of 2023, a cross-sectional multicenter study was conducted in eight intensive care units (ICUs) across Pakistan. Delirium was assessed using the intensive care delirium screening checklist. Demographic and clinical data were collected, and multivariable logistic regression analysis was performed to identify predictors of delirium. A total of 256 patients were enrolled in the study. Results The mean age of participants was 56 (S.D. 12) years. The point prevalence of delirium was 39%, and the point prevalence did not vary significantly among the participating intensive care units. Advanced age, higher Acute Physiology and Chronic Health Evaluation - IV (APACHE IV) scores, and higher Richmond Agitation-Sedation Scale (RASS) scores at enrollment were identified as significant predictors of delirium. Conclusion The high prevalence of delirium, observed at 39.0%, emphasizes the importance of proactive screening and effective management strategies in the ICU setting. Healthcare providers in Pakistan should be mindful of these risk factors and implement preventive measures to minimize the occurrence of delirium in critically ill patients. Further research and implementation of targeted interventions are warranted to improve patient outcomes and enhance the overall quality of care in this population.
Хімія харчових продуктів і матеріалів / Chemistry of food products and materials

The article deals with the effect the lighting conditions of storage have on the oxidation stability of vegetable oils of various unsaturation degrees and made by different technologies (raw-pressed and unrefined sunflower oil and flaxseed oil) according to the main oxidation parameters: peroxide value (PV), acid value (AV), and colour value. It has been experimentally established that in natural lighting, at the end of the shelf life, the PV of flaxseed oil increased most significantly, from 0.55·10 to 11.2·10 mmolO2/kg (20 times). The PV of sunflower oils varied less: in unrefined oil, it changed from 0.48·10 to 4.5·10 mmolO2/kg (9 times), in raw-pressed, from 0.3·10 to 4.4·10 mmolO2/kg (14.7 times). Under artificial UV radiation, the PV of sunflower oil increased from 0.3 to 0.55 mmol O2/kg after 2 hours of the experiment, and remained practically unchanged. In the case of flaxseed oil, after a slight increase from 0.55 to 0.7 mmol O2/kg, within the same period of time, there was then a decrease in the PV to 0.45 mmol O2/kg, which may indicate a relative instability of hydroperoxides that, due to their degradation, converted into more stable secondary compounds. The analysis of the oil oxidation kinetics by the PV has shown that the average rates of peroxide compounds accumulation in unrefined, raw-pressed, and flaxseed oils was 47·10, 48·10, 127·10 mmol 1⁄2О/kg·hour, respectively. At the same time, under natural light, the true rate of change of the AV in the oils studied was uneven over time. At the beginning of the experiment, it increased (especially noticeably in the case of flaxseed oil), at the end of the shelf life (the 5 week), it was slowed down significantly, decreasing to negative values, and in flaxseed oil, it had zero value, which indicates a constant value of AV in the experimental setting.
Telerehabilitation Is a Valid Option for Total Knee Arthroplasty Patients: A Retrospective Pilot Study Based on Our Experience during the COVID-19 Pandemic

Introduction: Total knee arthroplasty is an effective operation. Post-surgery rehabilitation, based on early and intensive progressive exercise programs, plays a substantial role and telerehabilitation can be an effective safe option. This retrospective study aimed to compare traditional in-presence rehabilitation and telerehabilitation for total knee arthroplasty, based on our experience during the Italian COVID-19 lockdown. Materials and methods: We retrospectively analyzed 164 patients (94 females and 70 males) enrolled in 2020 within 2 weeks after total knee replacement to perform post-operative outpatient rehabilitation. The clinical results of 82 patients (mean age 66.8 ± 10.2 years) performing telerehabilitation with those obtained from a similar cohort of 82 patients (mean age 65.4 ± 11.8 years) performing traditional in-presence outpatient rehabilitation were compared. Clinical outcomes were examined by comparing the gait speed (Time Up and Go-TUG test), the range of motion, the pain intensity (VAS), the functional status (Oxford Knee Score—OKS and Knee injury and Osteoarthritis Outcome Score—KOOS) and the overall satisfaction (Self-administered patient satisfaction scale) 12 weeks after the beginning of the physiotherapeutic protocol. Results: Telerehabilitation was non-inferior to traditional in-presence rehabilitation in all of the investigated areas and no statistical difference in terms of effectiveness was detected at 12 weeks, as confirmed by the respective patient-reported outcome scores such as TUG test (reduced from 20 ± 2 s to 12 ± 1.5 s for the telerehab cohort and from 18 ± 1.5 s to 13.1 ± 2 s for the in-presence rehabilitation one), pain VAS, OKS (improved from 22 ± 1.3 to 36 ± 2.7 for the telerehab cohort and from 23 ± 2.1 to 35.1 ± 4.2 for the in-presence group), KOOS (improved from 46.2 ± 10.2 to 67.4 ± 3.8 for the telerehabilitation cohort and from 48.4 ± 8.4 to 68.3 ± 6.6 for the other group), and the Self-administered patient satisfaction scale (more than two-thirds of patients globally satisfied with the results of their surgery in both groups). Conclusion: The telerehabilitation program was effective after total knee replacement and yielded clinical outcomes that were not inferior to conventional outpatient protocols.
Investigation of risk factors for the diagnosis of heart disease

Introduction: Limited studies have investigated the association between diagnosis of heart disease and its relating risk factors and haven’t met with robust results. We hypothesized that all or part of the risk factors are correlated with the heart disease. Method: This dataset published in 1998 was obtained from UCI Machine Learning Repository and was collected at University of Irvine. The dataset has 303 instances with 76 attributes, but all published experiments refer to using a subset of 14 of them. Our study focuses on 11 parameters specifically, including body health conditions, historic medical records, and habits. Logistic regression analyses were conducted to assess the relative risks of heart disease. Results: Both chest pain type (p < 0.01) and ST depression (p < 0.05) are positively correlated with the incidence of heart disease. Maximum heart rate, on the other hand, are negatively correlated with the diagnosis of heart disease. Conclusion: Our study suggested that chest pain type, ST depression and maximum heart rate are saliant contributors to indicate the occurrence of heart disease. The findings from our study have implications for the heart disease and call for future studies to explore the underlying prevention strategies of this findings.
Joint Moment Responses to Different Modes of Augmented Visual Feedback of Joint Kinematics during Two-Legged Squat Training

This study examined the effects of different modes of augmented visual feedback of joint kinematics on the emerging joint moment patterns during the two-legged squat maneuver. Training with augmented visual feedback supports improved kinematic performance of maneuvers related to sports or daily activities. Despite being representative of intrinsic motor actions, joint moments are not traditionally evaluated with kinematic feedback training. Furthermore, stabilizing joint moment patterns with physical training is beneficial to rehabilitating joint-level function (e.g., targeted strengthening and conditioning of muscles articulating that joint). Participants were presented with different modes of augmented visual feedback to track a target squat-motion trajectory. The feedback modes varied along features of complexity (i.e., number of segment trajectories shown) and body representation (i.e., trajectories shown as sinusoids versus dynamic stick-figure avatars). Our results indicated that mean values and variability (trial-to-trial standard deviations) of joint moments are significantly (p < 0.05) altered depending on the visual feedback features being applied, the specific joint (ankle, knee, hip), and the squat movement phase (early, middle, or late time window). This study should incentivize more optimal delivery of visual guidance during rehabilitative training with computerized interfaces (e.g., virtual reality).
Identifying homogeneous rainfall catchments for non- stationary time series using tops is algorithm and bootstrap k-sample Anderson darling test

The reliability of extreme estimates of hydro-meteorological events such as extreme rainfalls may be questionable due to limited historical rainfall records. The problem of limited rainfall records, however, can be overcome by extrapolating information from gauged to ungauged rainfall catchments, which requires information on the homogeneity among rainfall catchments. The purpose of this study is to introduce a new regionalization algorithm to identify the most suitable agglomerative hierarchical clustering (AHC) algorithm and the optimum number of homogeneous rainfall catchments for non-stationary rainfall time series. The new algorithm is based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) algorithm. This study also suggests the use of Bootstrap K-sample Anderson Darling (BKAD) test for validating regionalized homogeneous rainfall catchments. The Cophenetic Correlation Coefficients (CCC) from ten similarity measures are used as attributes for the TOPSIS algorithm to identify the most suitable AHC algorithm out of seven algorithms considered. The C-index (δCI), Davies-Bouldin index (δDB), Dunn index (δDI) and Gamma index (δGI) are then used as attributes for the TOPSIS algorithm to determine the optimum number of homogeneous rainfall catchments. The results show that the most suitable AHC algorithm is able to cluster twenty rainfall catchments in Kuantan River Basin, Malaysia into two optimum significant homogeneous clusters. The results also imply that the BKAD test is invariant towards the number of Bootstrap samples in the validation of homogeneous rainfall catchments.
Research Progress of Combined Application of All-trans Retinoic Acid and Bone Morphogenetic Protein in Bone Metabolism

All-trans retinoic acid (ATRA) can both promote and inhibit osteogenic differentiation of cells, which is closely related to the concentration, dose and cell type. Low dose of ATRA inhibited the function of osteoclasts and promoted the differentiation of osteoblasts, thus achieving bone remodeling: Bone formation is achieved through the coordination of osteoblasts and osteoclasts. ATRA can be combined with various factors to produce different effects, among which, when combined with bone morphogenetic protein (BMP), the bone formation effect is significant. Compared with homologous dimer, BMP heterodimer can repair the bone defect area more effectively with a smaller dose, and promote the formation of bone tissue. Reduce the probability of secondary lesions such as swelling in the operative area and excessive osteogenesis, and greatly reduce the economic burden of patients. In addition, in vitro experiments showed that ATRA and BMP2/7 combined with mouse embryonic osteoblast precursor cells (MC3T3-E1) had synergistic effect on osteogenesis. This article reviews the recent progress in the studies on the combined effects of ATRA and BMP in bone metabolism.
Exploring Lexical Richness in English-Language theses Across Disciplines: A Comparative Analysis

This study investigates the variations in lexical richness within English language theses across diverse disciplines, focusing on areas where researchers exhibit higher degrees of lexical richness and the evolution of vocabulary usage over time. By analyzing these variations, the research aims to provide insights into the effective use of lexical richness in academic writing and contribute to the development of more engaging and comprehensible scholarly publications. A total of 320 theses were randomly selected from the Turkey National Thesis Center and classified according to their scientific discipline. Using natural language processing techniques, unique word count, word diversity, and other metrics were analyzed. Results reveal that social sciences tend to exhibit higher lexical richness compared to natural sciences, and no significant difference was observed in word richness between social and natural sciences disciplines. These findings contribute to the understanding of lexical richness in academic writing and highlight the importance of achieving a balance between lexical richness and readability.
Plant macrofossil analysis of Holocene alluvium, with special reference to the Lower Thames Basin

Alluvium is an important archaeological and palaeoenvironmental resource in lowland Britain. The research presented here develops plant macrofossil analysis of alluvial facies, with special emphasis on the depositional and natural environments of the Lower Thames Basin. Plant macrofossil analysis is a poorly developed area of alluvial research, usually limited to superficial description of the fossils seen in section, or detailed analysis of a narrow suite of remains. A comprehensive, quantitative method of macrofossil analysis using counts and cover abundance scores is developed. Identification criteria for several groups of macrofossils are presented, including leaves, rootlets and epidermis. Potential macrofossil incorporation was investigated at eight wetland and alluvial sites, including saltmarsh, wet woodland and herb fen environments. Macrofossil collections were compared to extant vegetation and subject to multivariate analysis. The results showed that macrofossil assemblages produce spatially and temporally precise data of plant presences, although spatial and temporal fidelity varies in different depositional environments and between plant taxa. Vegetation dominants were favoured in the assemblages of all classes of macrofossils, with bulky Monocotyledons and Therophytes favourably preserved and sparsely distributed taxa, such as rosette plants, less well favoured. The depositional environment and position in relation to environmental gradients were also found to affect macrofossil composition. Multiple approaches to macrofossil analysis using a wide range of macrofossils were found to produce improved interpretations. The value of different macrofossil classes and occurrences of the major observed taxa in alluvial sediments are discussed. The method was applied to samples from the Medway River at Chatham. Vegetation history, hydrology and traces of human disturbance are discussed from 7000BP to 2000BP. Analysis showed a gradual increase in human disturbance over time, development of a distinctive human-influenced upper salt marsh flora from 3000BP and supports the trend across southern Britain for a change in hydrology by the same period.
Intraoperative application of regional cerebral oxygen saturation monitoring for geriatric patients in China: a survey

Background Regional cerebral oxygen saturation (rSO2) monitoring is a real-time and non-invasive technique for estimating the balance of regional cerebral oxygen supply and consumption. Despite the growing popularity of this monitoring technique, data regarding outcome benefits remain sparse and contradictory. This study was conducted to explore the popularity and understanding of cerebral oxygen saturation monitoring during anesthesia in geriatric patients. Methods An online self-report questionnaire was distributed in March 2021 to various hospitals in China for dissemination to anesthesiologists. Questions surveyed cerebral oximetry equipment and utilization, demographics, and clinical practice of participants. Results In total, 447 anesthesiologists responded. Of these, 301 (67.3%) respondents reported that their hospitals were equipped with cerebral oximetry, which 274 anesthesiologists use during anesthesia. A high percentage of anesthesiologists chose to monitor rSO2 during cardiac surgery (77.4%, n = 212) and neurosurgery (40.5%, n = 111). Most anesthesiologists agreed that a 30% reduction from the rSO2 baseline requires intervention to avoid cerebral ischemia, mainly via elevating arterial pressure and fraction of inspired oxygen (FiO2). Of those without cerebral oximetry, 138 of 146 (94.5%) anesthesiologists were willing to monitor rSO2. In addition, 291 respondents believed that cerebral oxygen monitoring would help prevent postoperative cognitive dysfunction. Conclusion Our survey indicated that the prevalence of cerebral oximetry remains relatively low, while almost all anesthesiologists expressed their willingness to use rSO2 monitoring in geriatric anesthesia. Heterogeneity in clinical practice was identified, indicating relevant knowledge gaps that should encourage further clinical research to optimize treatment.
Aceleración hardware con propósitos criptográficos

La criptografia asimetrica esta siendo implementada hoy en dia en muchas ramas, principalmente en el cifrado de clave publica y en las firmas digitales. Esto es debido principalmente a que no hace falta el intercambio de claves de cifrado entre el emisor y el receptor lo que hace que el sistema sea mas seguro. Una variante de este tipo de criptografia es la criptografia de curvas elipticas. Este tipo de criptografia se basa en las matematicas de curvas elipticas y la aritmetica modular. Ademas, este tipo de criptografia es mucho mas interesante que, por ejemplo, RSA ya que utiliza una clave de longitud menor para el mismo nivel de seguridad. En este trabajo se realiza una implementacion de una nueva arquitectura de multiplicacion modular para las operaciones sobre los cuerpos primos Fp, utilizada en este tipo de criptografia. Para ello se han utilizado algoritmos ya conocidos y revisiones de los mismos. Las revisiones y mejoras implementadas estan orientadas al incremento de la velocidad de la operacion de multiplicacion. La implementacion se realiza sobre dispositivos de hardware reconfigurable de la familia Virtex5 de Xilinx. Toda la implementacion del sistema se hace mediante codificacion en VHDL y el software de desarrollo de Xilinx ISE 14.2. De esta forma se puede estudiar mejor el comportamiento de los algoritmos bajo distintos casos de uso, anchos de bus y familias de FPGA. [ABSTRACT] Asymmetric cryptography is being implemented today in many branches, mainly in public-key encryption and digital signatures. This is mainly because you do not need the encryption key exchange between sender and receiver which makes the system more secure. A variant of this type of cryptography is elliptic curve cryptography. This type of cryptography is based on the mathematics of elliptic curves and modular arithmetic. Furthermore, this kind of encryption is much more interesting, for example, RSA key since it uses a shorter length for the same level of security. In this paper a new architecture implementing a modular multiplication operations over Fp prime fields used in this type of cryptography. This has been known algorithms used and revisions thereof. Revisions and improvements implemented are aimed at increasing the speed of the multiplication operation. The implementation is done on reconfigurable hardware devices in the Xilinx Virtex5. The whole system implementation is done using VHDL coding and development software Xilinx ISE 14.2. In this way you can study better the behavior of the algorithms under different use cases, bus widths and FPGA families.
IRv2-Net: A Deep Learning Framework for Enhanced Polyp Segmentation Performance Integrating InceptionResNetV2 and UNet Architecture with Test Time Augmentation Techniques

Colorectal polyps in the colon or rectum are precancerous growths that can lead to a more severe disease called colorectal cancer. Accurate segmentation of polyps using medical imaging data is essential for effective diagnosis. However, manual segmentation by endoscopists can be time-consuming, error-prone, and expensive, leading to a high rate of missed anomalies. To solve this problem, an automated diagnostic system based on deep learning algorithms is proposed to find polyps. The proposed IRv2-Net model is developed using the UNet architecture with a pre-trained InceptionResNetV2 encoder to extract most features from the input samples. The Test Time Augmentation (TTA) technique, which utilizes the characteristics of the original, horizontal, and vertical flips, is used to gain precise boundary information and multi-scale image features. The performance of numerous state-of-the-art (SOTA) models is compared using several metrics such as accuracy, Dice Similarity Coefficients (DSC), Intersection Over Union (IoU), precision, and recall. The proposed model is tested on the Kvasir-SEG and CVC-ClinicDB datasets, demonstrating superior performance in handling unseen real-time data. It achieves the highest area coverage in the area under the Receiver Operating Characteristic (ROC-AUC) and area under Precision-Recall (AUC-PR) curves. The model exhibits excellent qualitative testing outcomes across different types of polyps, including more oversized, smaller, over-saturated, sessile, or flat polyps, within the same dataset and across different datasets. Our approach can significantly minimize the number of missed rating difficulties. Lastly, a graphical interface is developed for producing the mask in real-time. The findings of this study have potential applications in clinical colonoscopy procedures and can serve based on further research and development.
Cardiac microRNAs: diagnostic and therapeutic potential

MicroRNAs are small non-coding post-translational biomolecules which, when expressed, modify their target genes. It is estimated that microRNAs regulate production of approximately 60% of all human proteins and enzymes that are responsible for major physiological processes. In cardiovascular disease pathophysiology, there are several cells that produce microRNAs, including endothelial cells, vascular smooth muscle cells, macrophages, platelets, and cardiomyocytes. There is a constant crosstalk between microRNAs derived from various cell sources. Atherosclerosis initiation and progression are driven by many pro-inflammatory and pro-thrombotic microRNAs. Atherosclerotic plaque rupture is the leading cause of cardiovascular death resulting from acute coronary syndrome (ACS) and leads to cardiac remodeling and fibrosis following ACS. MicroRNAs are powerful modulators of plaque progression and transformation into a vulnerable state, which can eventually lead to plaque rupture. There is a growing body of evidence which demonstrates that following ACS, microRNAs might inhibit fibroblast proliferation and scarring, as well as harmful apoptosis of cardiomyocytes, and stimulate fibroblast reprogramming into induced cardiac progenitor cells. In this review, we focus on the role of cardiomyocyte-derived and cardiac fibroblast-derived microRNAs that are involved in the regulation of genes associated with cardiomyocyte and fibroblast function and in atherosclerosis-related cardiac ischemia. Understanding their mechanisms may lead to the development of microRNA cocktails that can potentially be used in regenerative cardiology.