Miracle-dz/UniFAR-FTUs huggingface dataset:
Specific changes in amino acid profiles in monocytes of patients with breast, lung, colorectal and ovarian cancers

Introduction Immunometabolism is essential factor of tumor progression, and tumor-associated macrophages are characterized by substantial changes in their metabolic status. In this study for the first time, we applied targeted amino acid LC-MS/MS analysis to compare amino acid metabolism of circulating monocytes isolated from patients with breast, ovarian, lung, and colorectal cancer. Methods Monocyte metabolomics was analyzed by liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/ MS) analysis of amino acid extracts. The targeted analysis of 26 amino acids was conducted by LCMS/MS on an Agilent 6460 triple quadrupole mass spectrometer equipped with an electrospray ionization source and an Agilent 1260 II liquid chromatograph. Results Comparison of monocytes of cancer patients with monocytes of healthy control individuals demonstrated that in breast cancer most pronounced changes were identified for tryptophan (AUC = 0.76); for ovarian cancer, aminobutyric acid was significantly elevated (AUC= 1.00); for lung cancer significant changes we indented for citrulline (AUC = 0.70). In order to identify key amino acids that are characteristic for monocytes in specific cancer types, we compared each individual cancer with other 3 types of cancer. We found, that aspartic acid and citrulline are specific for monocytes of patients with colorectal cancer (p<0.001, FC = 1.40 and p=0.003, FC = 1.42 respectively). Citrulline, sarcosine and glutamic acid are ovarian cancer-specific amino acids (p = 0.003, FC = 0.78, p = 0.003, FC = 0.62, p = 0.02, FC = 0.78 respectively). Glutamine, methionine and phenylalanine (p = 0.048, FC = 1.39. p = 0.03, FC = 1.27 and p = 0.02, FC = 1.41) are lung cancer-specific amino acids. Ornithine in monocytes demonstrated strong positive correlation (r = 0.63) with lymph node metastasis incidence in breast cancer patients. Methyl histidine and cysteine in monocytes had strong negative correlation with lymph node metastasis in ovarian cancer patients (r = -0.95 and r = -0.95 respectively). Arginine, citrulline and ornithine have strong negative correlation with tumor size (r = -0.78, citrulline) and lymph node metastasis (r = -0.63 for arginine and r = -0.66 for ornithine). Discussion These alterations in monocyte amino acid metabolism can reflect the reaction of systemic innate immunity on the growing tumor. Our data indicate that this metabolic programming is cancer specific and can be inhibiting cancer progression. Cancer-specific differences in citrulline, as molecular link between metabolic pathways and epigenetic programing, provide new option for the development and validation of anti-cancer therapies using inhibitors of enzymes catalyzing citrullination.
A new method for detecting differential peaks from ATAC-seq data

In the rapidly expanding domain of plant science research, epigenetics has gained significant attention due to its crucial role in understanding genomic and transcriptomic variations. A key aspect of this research is the study of chromatin accessibility and its open regions. Among various biotechnologies, the ATAC-seq technique, developed in 2013, stands out with its distinct advantages in investigating chromatin accessibility. However, the complexities inherent in plant cells and the limitations of the ATAC-seq data analysis process often result in overlooked or inaccurately identified signal peaks. As a consequence, the effectiveness of this technology in plant science research has been suboptimal compared to its application in animal research. This paper introduces a novel peak detection algorithm that overcomes these challenges by identifying peak differences in ATAC-seq signals without any preconditions. The algorithm's performance is evaluated using simulated data, demonstrating its ability to detect even minute signal differences. By enhancing the efficiency of ATAC-seq data analysis, our algorithm optimizes the analysis of plant chromatin accessibility and gene activity. Ultimately, this advancement can greatly contribute to upstream plant breeding and pathological research in transcription.
Nursing Workload Prediction for Upcoming Shifts: A Retrospective Observational Exploratory Study in the Postoperative and Intensive Care Unit

Aims. This study aimed to explore workload whether Nursing Activities Scores on one shift could predict workload for the next shift. Method. This was a retrospective observational exploratory study of cross-sectional design carried out in a postoperative and intensive care unit at a local, nonprofit hospital in Norway. Data were collected from the hospital’s internal database from January 1st to June 30th, 2016. Results. A total of 2,695 patients and 5,916 Nursing Activities Scores were included. The model could predict a 55.1% to 66.9% variation in Nursing Activities Scores for the next shift. When the number of patients was added, the model explained up to 80% of the variation. Conclusions. The Nursing Activities Score can be used to predict nursing workload from one shift to another and as an instrument for managers to adjust their staffing requirements. Implications for Nursing Management. Nursing Activities Score assessing nursing workload for all patients in a unit can support the resource planning with accuracy for nurse staffing.
Umbelliprenin via increase in the MECP2 and attenuation of oxidative stress mitigates the autistic-like behaviors in mouse model of maternal separation stress

Introduction: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition. Maternal separation (MS) stress is an early-life stress factor associated with behaviors resembling Autism. Both MECP2 and oxidative stress are implicated in the pathophysiology of Autism. Umbelliprenin (UMB) is a coumarin compound with various pharmacological properties. Our study aimed to investigate the potential effects of UMB in mitigating autistic-like behaviors in a mouse model subjected to MS stress, focusing on probable alterations in MECP2 gene expression in the hippocampus. Methods: MS paradigm was performed, and mice were treated with saline or UMB. Behavioral tests consisting of the three-chamber test (evaluating social interaction), shuttle box (assessing passive avoidance memory), elevated plus-maze (measuring anxiety-like behaviors), and marble-burying test (evaluating repetitive behaviors) were conducted. Gene expression of MECP2 and measurements of total antioxidant capacity (TAC), nitrite level, and malondialdehyde (MDA) level were assessed in the hippocampus. Results: The findings demonstrated that MS-induced behaviors resembling Autism, accompanied by decreased MECP2 gene expression, elevated nitrite, MDA levels, and reduced TAC in the hippocampus. UMB mitigated these autistic-like behaviors induced by MS and attenuated the adverse effects of MS on oxidative stress and MECP2 gene expression in the hippocampus. Conclusion: In conclusion, UMB likely attenuated autistic-like behaviors caused by MS stress, probably, through the reduction of oxidative stress and an increase in MECP2 gene expression.
Assessing International Tourism's Global Environmental Impact of Food and Beverages

Tourism harms the environment in many ways and agriculture is of particular importance because of a wide range of negative impacts, the specific spatial conditionality of tourists' consumption, and the change in their eating habits during travel. Despite the urgency of previous research, the environmental requirements of tourist consumption have not yet been quantified. The main aim of the paper is thus quantify in the long term the total amount of food consumed in international tourism and assess its environmental impacts: land use, water requirements, and emitted emissions. Furthermore, we deal with the projection of these impacts associated with meat consumption up to 2050. The investigation uses long-term secondary data on the number of tourists, national diets, and environmental requirements of foodstuffs. According to our research, 15.6 million tonnes of food was consumed globally in 2010 and this amount increased to 24.5 in 2019. Due to COVID-19, the amount decreased by 72%. Although vegetal foodstuffs account for a larger share of the total, the environmental requirements are primarily associated with animal foodstuffs. Compared to daily at-home eating, tourists’ consumption patterns, e.g., higher preference for meat or whole grains, increase the environmental requirements by more than 10%. This research serves destination management bodies and concludes that the food environmental impacts should be the subject of adequate measures that would mitigate them and would make tourism more sustainable.
Circulating erythroferrone has diagnostic utility for acute decompensated heart failure in patients presenting with acute or worsening dyspnea

Objectives In dyspneic patients with atrial fibrillation (AF) or obesity, the diagnostic performance of NT-proBNP for acute heart failure is reduced. We evaluated the erythroblast derived protein erythroferrone (ERFE) as an ancillary biomarker for the diagnosis of acute decompensated heart failure (ADHF) in these comorbid subgroups in both Western and Asian populations. Methods The diagnostic performance of ERFE (Intrinsic Lifesciences) and NT-proBNP (Roche Cobas e411) for ADHF was assessed in 479 New Zealand (NZ) and 475 Singapore (SG) patients presenting with breathlessness. Results Plasma ERFE was higher in ADHF, compared with breathlessness from other causes, in both countries (NZ; 4.9 vs. 1.4 ng/ml, p < 0.001) and (SG; 4.2 vs. 0.4 ng/ml, p = 0.021). The receiver operating characteristic (ROC) areas under the curve (AUCs) for discrimination of ADHF were reduced in the NZ cohort compared to SG for ERFE (0.75 and 0.84, p = 0.007) and NT-proBNP (0.86 and 0.92, p = 0.004). Optimal cut-off points for ERFE yielded comparable sensitivity and positive predictive values in both cohorts, but slightly better specificity, negative predictive values and accuracy in SG compared with NZ. In patients with AF, the AUC decreased for ERFE in each cohort (NZ: 0.71, n = 105, SG: 0.61, n = 44) but increased in patients with obesity (NZ: 0.79, n = 150, SG: 0.87, n = 164). Conclusions Circulating ERFE is higher in patients with ADHF than in other causes of new onset breathlessness with fair diagnostic utility, performing better in Asian than in Western patients. The diagnostic performance of ERFE is impaired in patients with AF but not patients with obesity.
Effect of Self-care Education Using Face-to-face Method and Pamphlets on Epilepsy Risk Awareness of Patients With Epilepsy and their Family Caregivers

Introduction: For patients with epilepsy and their family caregivers, epilepsy risk awareness (ERA) can affect various aspects of health. They need effective education to improve their quality of life. Objective: This study aims to compare the effect of self-care education on ERA in patients with epilepsy and their family caregivers using the face-to-face method and pamphlets. Materials and Methods: In this quasi-experimental study, participants were patients with epilepsy referred to a neurological outpatient clinic in Tabriz, Iran and their family caregivers. They were randomly assigned to the intervention (60 patients and 60 caregivers) and control (60 patients and 60 caregivers) groups. The ERA scales for patients and family caregivers were completed before and one month after the education. The intervention group received ERA-based self-care education in a 60-minute session using the face-to-face method. The pamphlet group received the same education using pamphlets. Data were analyzed using descriptive statistics, paired t-test, independent t-test, Fisher’s exact test, chi-square test, and ANCOVA. Results: Most of the patients (70%) and caregivers (53.3%) in the intervention group were female, and their mean age was 28.07 and 40.75 years, respectively. In the pamphlet group, most of the patients (68.67%) and caregivers (63.3%) were female, with a mean age of 30.28 and 42.32 years, respectively. After education, mean ERA scores increased significantly in both intervention and pamphlet groups (P=0.001). Except for the two domains of physical and mental health, the mean scores of ERA domains were higher in the intervention group than in the pamphlet group (P=0.01). These results were confirmed by ANCOVA results (P<0.01). Conclusion: Self-care education with the face-to-face method or pamphlets both can increase the ERA of patients with epilepsy and their family caregivers. Depending on the conditions and available facilities, nurses can use these methods to facilitate patient education and the learning process.
Hybrid ConvLSTM with Attention for Precise Driver Behavior Classification

Driving behavior classification plays an important role in many real-world applications, including traffic accident prevention, driver safety, usage-based insurance, and optimizing ridesharing services. In this research, we introduce a novel approach called Hybrid ConvLSTM with Attention for Driver Behavior Classification (HCLA-DBC), designed to achieve precise and reliable driver behavior classification. Our main focus is to distinguish three fundamental driving behavior classes: normal, drowsy, and aggressive, which play a vital role in supporting advanced driver-assistance systems (ADAS). To evaluate the performance of our proposed models, we conducted experiments using the publicly available UAH-DriveSet dataset. The evaluation comprised six distinct models, encompassing two machine learning models (SVM and Gradient Boosting) and four deep learning models (CNN, MLP, LSTM, and HCLADBC). Our HCLA-DBC model outperformed all other models and previous results on the same data. On the test data, it achieved an accuracy of 94.12%, precision of 94.24%, recall score of 94.12%, F1-score of 94.12%, and a macro-average ROC AUC of 98.83. These exceptional outcomes underscore the efficacy of our hybridized approach and its potential to significantly enhance driver behavior classification. The HCLA-DBC model not only promises new possibilities for driver behavior analysis but also paves the way for elevated ADAS capabilities and safer driving experiences.
Evaluating the Parallel Simulation of Dynamics of Electrons in Molecules on AWS Spot Instances

In this paper, we evaluate the cost-effectiveness and performance of simulating the dynamics of electrons in molecules on AWS and investigate the implications of using various types of storage solutions, contrasting the results with those obtained on a traditional HPC cluster. Our findings reveal key insights into the computational efficiency and cost-effectiveness of these diverse platforms, contributing to the critical discourse on how to optimally harness the power of modern computing infrastructures for complex molecular simulations.
Vid2Cuts: A Framework for Enabling AI-Guided Grapevine Pruning

Recent advances in machine learning and computer vision promoted a surge in the development of AI-based approaches aimed at improving various agricultural tasks. In this work, we focus on grapevine pruning, which is one of the labor-intensive tasks in viticulture that requires experienced workers and has a huge impact on grapevine health, future yields and grape quality. Our objective is to develop an AI-based application that provides pruning suggestions according to the “gentle pruning” strategy enabling non-experts in the field to easily engage in the process. To achieve that, we have to deal with multiple challenges such as a large number of grapevine varieties, complicated outdoor conditions characterized by varied light, weather and complex grapevine structures with multiple occlusions. In this work, we present a framework, which allows the generation of pruning suggestions using a video recorded by a smartphone and visualize them in a mobile AR application. Thus, our contributions are the following: 1) we present the collection of a large image segmentation dataset of dormant grapevines; 2) we propose a novel distributed approach to generate pruning suggestions via a semantic 3D grapevine model generated from a smartphone video; 3) we propose a mobile AR application to visualize the pruning suggestions. Results show the robustness of our approach to outdoor conditions as well as reasonable pruning suggestions according to evaluation by domain experts in 71% of cases. We demonstrate the main challenges that must be addressed for such an application and propose a distributed solution to handle them.
A Boundary Guided Cross Fusion Approach for Remote Sensing Image Segmentation

Remote sensing images have a variety of application prospects because of their rich information. Due to recent advances in deep learning methods, solid improvements have been made in the semantic segmentation of high-resolution remote sensing images. However, achieving precise segmentation of small and crowded objects remains a challenge. To tackle this challenging task, a Boundary Guided Cross Fusion module (BGCFM) is proposed. The Bidirectional Boundary Gate module (BBGM) is designed to provide reliable boundary information for BGCFM. Based on these two models, a remote sensing images real-time semantic segmentation network, boundary guided cross fusion network (BGCFNet), is designed. The effectiveness of the boundary-guided fusion method and the performance of BGCFNet were verified on the GID-5 dataset without pretraining. The application of the boundary-guided fusion method on the SOTA dual-branch real-time semantic segmentation network improves segmentation accuracy. BGCFNet achieves the best performance with a Mean Intersection over Union (mIoU) of 88.82%. Its inference speed is about 1.5 times that of other networks in the experiment, achieving an excellent balance between accuracy and speed.
Proof of the maximum principle for a problem with state constraints by the v-change of time variable

We give a new proof of the maximum principle for optimal control problems with running state constraints. The proof uses the so-called method of \begin{document}$ v- $\end{document} change of the time variable introduced by Dubovitskii and Milyutin. In this method, the time \begin{document}$ t $\end{document} is considered as a new state variable satisfying the equation \begin{document}$ {\rm d} t/ {\rm d} \tau = v, $\end{document} where \begin{document}$ v(\tau)\ge0 $\end{document} is a new control and \begin{document}$ \tau $\end{document} a new time. Unlike the general \begin{document}$ v- $\end{document} change with an arbitrary \begin{document}$ v(\tau), $\end{document} we use a piecewise constant \begin{document}$ v. $\end{document} Every such \begin{document}$ v- $\end{document} change reduces the original problem to a problem in a finite dimensional space, with a continuum number of inequality constrains corresponding to the state constraints. The stationarity conditions in every new problem, being written in terms of the original time \begin{document}$ t, $\end{document} give a weak * compact set of normalized tuples of Lagrange multipliers. The family of these compacta is centered and thus has a nonempty intersection. An arbitrary tuple of Lagrange multipliers belonging to the latter ensures the maximum principle.
Sea-Level Rise and Its Impact on Miami-Dade County

It is well-established that climate change has resulted in global sea-level rise. 1 The two most significant factors contributing to sea-level rise over the last 20 years have been warming ocean water (39 percent) and freshwater input from melting ice sheets, ice caps, and glaciers (49 percent): 2 Since 1870, average global sea level has risen by about 8 inches. 3 In Southeast Florida, sea level has risen 12 inches. 4 As the climate has become increasingly warmer, the annual rate of sea-level rise has accelerated. 5 Average annual sea-level rise between 1993 and 2010 was almost twice the rate from 1901-2010. 6 By the year 2060, it is estimated that sea levels along Florida's coastline could rise between another 9 inches to 2 feet.
Un índice de criminalidad para Colombia

espanolEl presente documento busca establecer un indice de criminalidad para Colombia, integrando los principales delitos del pais entre 1994 y 2007. Si bien es cierto que el homicidio es ampliamente reconocido como el delito mas grave y el mas homogeneo en el tiempo, existen otras manifestaciones de violencia y criminalidad que afectan profundamente a la poblacion, y por lo tanto es pertinente incluirlas dentro de un mismo indice para poder tener una vision completa del comportamiento de los problemas de seguridad. Luego de una revision de los instrumentos utilizados en Colombia y en el mundo para medir de manera agregada la criminalidad ano a ano, queda claro que no existe un indicador para tal fin. Asi, el documento presenta tres enfoques metodologicos diferentes, pero muy cercanos entre si, para entender la evolucion de la criminalidad en el pais, teniendo como base la combinacion ponderada de varios delitos, y no unicamente el homicidio. no unicamente el homicidio. Una innovacion interesante que presenta el documento es la de usar como ponderador la pena impuesta a cada delito en el Codigo Penal colombiano como una medida objetiva de como la sociedad valora cada hecho. EnglishThis paper attempts to establish a criminality index for Colombia integrating the major offenses in the country from 1994 to 2007. Though homicide is widely recognized and has been the most serious and homogeneous crime through time, there are other manifestations of violence and criminality that affect society profoundly. Hence, it is relevant to include such manifestations in the very same index in order to have a full spectrum of the behavior shown by security problems. After a revision of the instruments used in Colombia and worldwide to measure up criminality year after year, it is evident that there is no indicator for such a goal. Hence, the document presents three different - but closely related - methodological approaches to understand the development of criminality in the country based not only on homicide but on the pondered combination of various offenses. Using the punishment indicated for each offense in the Colombian Penal Code as a median measurer results in an interesting innovation as presented in this paper. This activity evidences some limitations concerning the source of information and the lack of a regional analysis. However, this analysis attempts to raise an interest in more and better approaches to the topic, thus strengthening the analysis of criminality data in Colombia and, therefore, designing public policies to face such an issue.
Export Market Size Matters: The Effect of the Market Size of Export Destinations on Manufacturing Growth

Literature contends that the manufacturing sector is crucial for economic development, and it is conventional wisdom that exports drive manufacturing growth. However, it has not yet been established empirically whether the market size of export destinations is an important factor to explain diverging regional and sectorial manufacturing growth patterns. This article argues that accessing large external markets reduces transaction costs, increases expectations of economies of scale and fosters capital formation. To test this hypothesis, we construct a novel Relative Export Market Size (REMS) index that measures whether the share of sectoral exports that are destined to large economies in one region is higher than in other regions. Using a PVAR model, we verify the impact of the REMS index on value added, employment and capital accumulation of 129 manufacturing sectors in 23 regions in Colombia during the period 1992-2017. The obtained results show that exporting to larger markets has a positive impact on employment, capital formation and value added per capita of manufacturing sectors at a regional level. This finding indicates that exporting to the largest market of the world helps to develop competitive manufacturing sectors.