Miracle-dz/UniFAR-FTUs huggingface dataset:
Decoding the Impact of Tumor Microenvironment in Osteosarcoma Progression and Metastasis

Simple Summary Osteosarcoma (OS) is the most common bone tumor in the pediatric population. Currently, no effective molecularly targeted therapies are available for OS. The five-year survival rate of OS has increased to about 70% since the 1970s but is only 20–30% for patients with metastasis. The management of OS is challenging and requires a multidisciplinary approach. Surgical excision and systematic multiagent therapy are standard clinical practices for OS treatment. However, there is a pressing need to identify novel therapeutic approaches and biomarkers to manage the disease better. Understanding osteosarcoma’s tumor microenvironment (TME) has recently gained much interest towards providing valuable insights into tumor heterogeneity, progression, metastasis, and the identification of novel therapeutic avenues. In this review, we discuss the current understanding of the OS TME, including different cellular and noncellular components, their crosstalk with OS tumor cells, and their involvement in tumor progression and metastasis. Discovering more specific therapeutic targets, determining interactions among cellular and noncellular components of the OS TME, and using rational combination therapies targeting tumor intrinsic and TME features will inevitably improve OS patient outcomes. Abstract Osteosarcoma (OS) is a heterogeneous, highly metastatic bone malignancy in children and adolescents. Despite advancements in multimodal treatment strategies, the prognosis for patients with metastatic or recurrent disease has not improved significantly in the last four decades. OS is a highly heterogeneous tumor; its genetic background and the mechanism of oncogenesis are not well defined. Unfortunately, no effective molecular targeted therapy is currently available for this disease. Understanding osteosarcoma’s tumor microenvironment (TME) has recently gained much interest among scientists hoping to provide valuable insights into tumor heterogeneity, progression, metastasis, and the identification of novel therapeutic avenues. Here, we review the current understanding of the TME of OS, including different cellular and noncellular components, their crosstalk with OS tumor cells, and their involvement in tumor progression and metastasis. We also highlight past/current clinical trials targeting the TME of OS for effective therapies and potential future therapeutic strategies with negligible adverse effects.
The effect of macroeconomic and environmental factors on innovation in EU member countries

This paper examines the long-run relationship between innovation and macroeconomic and environmental factors in the EU during the period 1990–2020. In the paper, the patents are used as a proxy of the innovation index. The market openness, per capita GDP, foreign direct investment, and oil prices are used as proxies for macroeconomic factors whereas per capita energy consumption, per capita CO2 emissions, and renewable energy sources are proxies for environmental factors. For the analysis of this relationship, two-panel count data models are used, the Poisson regression model and negative binomial model as well as the ARDL cointegration technique and the Dumitrescu and Hurlin causality test. The results of the negative binomial model showed that trade openness, renewable energy sources, and CO2 emissions have a significant and negative relationship with innovation, while GDP, investment, energy consumption, and oil prices have a significant and positive relationship with innovation. Furthermore, the causality test of Dumitrescu and Hurlin showed the presence of an unidirectional causal relationship between per capita CO2 emissions and per capita energy consumption towards innovation.
México : consumo, pobreza y desigualdad a nivel municipal 1990-2005

Este informe presenta los resultados de un estudio empírico para México, con el cual se elabora una tipología de territorios rurales basada en mejoras o detrimentos del nivel de bienestar de los habitantes en el plano municipal para los años 1990 y 2005. Para esto se consideran los niveles de consumo per cápita, la incidencia de pobreza y coeficientes de Gini. Con los resultados de la investigación, se sugiere de manera preliminar una serie de territorios para ser estudiados en profundidad durante la segunda etapa del proyecto de Rimisp “Dinámicas Territoriales Rurales”. Las conclusiones arrojan que el 53,1% de los habitantes de México vive en municipios que mejoraron al menos uno de los tres indicadores de bienestar. La marginación de cerca de la mitad de la población al acceso a estas mejoras se explica por las crisis que ha enfrentado el país con un bajo crecimiento económico. Al parecer, las condiciones que impulsan el bienestar y el desarrollo rural de México no se presentan de manera aleatoria, sino que parece estar más asociado a características locales y dinámicas generadas por las áreas que la comparten.
Where is inclusive growth happening? Mapping multi-dimensional living standards in OECD regions

This paper applies the Inclusive Growth framework to the OECD Regional Well-being Database in order to compute multidimensional living standards (MDLS) among OECD regions from the early 2000s to 2012. MDLS are based on the equivalent income approach, where, for different income groups, the monetised value of health status and unemployment are added to disposable income and aggregated with a generalised mean function to allow inequality to be taken into account. Results highlight that, due to the spatial concentration of good and bad outcomes, regional disparities are amplified when observed through the lens of MDLS as opposed to income-based regional disparities. The paper also shows that people living in metropolitan regions experienced, on average, higher levels of MDLS but also a sharper decline during the economic crisis. Growth of MDLS in metropolitan regions during this period was characterised by a higher contribution of life expectancy and a lower contribution of income inequality with respect to the other regions. Nous avons applique ici le cadre de l’OCDE pour une croissance inclusive a la base de donnees statistiques sur le bien-etre regional afin d’obtenir une mesure multidimensionnelle du niveau de vie dans les differentes regions de la zone OCDE pour la periode allant du debut des annees 2000 a 2012. Le niveau de vie multidimensionnel est calcule sur la base d’un revenu equivalent lui-meme obtenu, pour differentes categories de revenu, par l’ajout au revenu disponible d’une valeur monetisee de l’etat de sante et de l’emploi agregee selon la formule de la moyenne generalisee. Les resultats montrent que, du fait de la concentration geographique des meilleures performances, les disparites regionales sont amplifiees lorsqu’on les observe a travers le prisme du niveau de vie multidimensionnel et non plus sur la base du revenu monetaire. On note en outre que le niveau de vie multidimensionnel est en moyenne plus eleve dans les grandes regions metropolitaines, mais que ces regions metropolitaines ont aussi accuse une baisse relativement plus forte qu’ailleurs pendant la crise economique. Par rapport aux autres regions, l’esperance de vie a eu une incidence plus importante et les inegalites de revenu une incidence moins importante sur la progression des niveaux de vie multidimensionnels dans les grandes metropoles.
BIT @ TRECVid 2013 : Surveillance Event Detection

In this paper, we present an event detection system evaluated in TRECVid 2013. We investigated a generic statistical approach with spatio-temporal features applied to the event "Object Put". This approach is based on local spatial constrained spatio-temporal descriptors, named as SC-MoSIFT. We extended the spatio-temporal features, MoSIFT, by relative position to camera. We also statistic the frequency and the location of each event occurs, and use selective hot region to construct spatial Bag-of-Feature. Non-linear SVM is exploited to train classifier for each event on each camera. In the limited experimental time, we adopted experiments and got comparable results to show the effectiveness of our approach.
Research and applications of game intelligence

Game intelligence is a cross-disciplinary ﬁeld that encompasses game theory and artiﬁcial intelligence. It focuses on interactions between individuals or organizations and the accurate solution of optimal strategies through quantifying game relationships with modeling, ﬁnally forming intelligent decision-making and its knowledge base. In recent years, with the explosion of massive behavioral data and the diversiﬁcation of game forms, game intelligence has increasingly attracted the interest of researchers and has been used widely in real life. This paper systematically surveys game intelligence in three aspects. First, it reviews the relevant background of game intelligence, including single-agent Markov decision processes, multiagent modeling techniques based on game theory, and multiagent solution methods such as reinforcement learning and game learning. Second, based on the diﬀerent game relationships between intelligent agents, this paper categorizes games into three paradigms: cooperative games, adversarial games, and mixed games, and introduces the main research problems, the mainstream research methods, and typical applications in each game intelligence paradigm. Finally, this paper summarizes the current research status of game intelligence, the main problems and research challenges that need to be addressed, and the prospects for application in academia and industry, providing a reference for related research and further promoting the development of the national artiﬁcial intelligence strategy.
Water-Level Fluctuation Control of the Trophic Structure of a Yangtze River Oxbow

Simple Summary Seasonal fluctuations in the water level have the potential to alter the nutrient composition of the aquatic ecosystem and disrupt the trophic structure. Tian-e-Zhou Oxbow is the first ex situ reserve established for the Yangtze finless porpoise in China. The extant rich and abundant forage fish resources are a guarantee for the healthy development of the Yangtze finless porpoise population. However, the water-level difference between the Tian-e-Zhou Oxbow and the Yangtze mainstream has been increasing due to the barrier of the Sha-Tan Levee, and effective regulation measures have not been implemented. In this study, we aimed to explore the impact of water-level fluctuations on the trophic structure of the ecosystem in the Tian-e-Zhou Oxbow by analyzing the trophic position, trophic niche, and resource contribution to fish during both the wet and the dry seasons. The study will contribute to the conservation of the Yangtze finless porpoise and provide a valuable reference for habitat improvement and restoration efforts in the Tian-e-Zhou Oxbow of the Yangtze River. Abstract Seasonal water-level fluctuations can profoundly impact nutrient dynamics in aquatic ecosystems, influencing trophic structures and overall ecosystem functions. The Tian-e-Zhou Oxbow of the Yangtze River is China’s first ex situ reserve and the world’s first successful case of ex situ conservation for cetaceans. In order to better protect the Yangtze finless porpoise, the effects of water-level fluctuations on the trophic structure in this oxbow cannot be ignored. Therefore, we employed stable isotope analysis to investigate the changes in the trophic position, trophic niche, and contribution of basal food sources to fish during the wet and dry seasons of 2021–2022. The research results indicate that based on stable isotope analysis of the trophic levels of different dietary fish species, fish trophic levels during the wet season were generally higher than those during the dry season, but the difference was not significant (p > 0.05). Fish communities in the Tian-e-Zhou Oxbow exhibited broader trophic niche space and lower trophic redundancy during the wet season (p < 0.05), indicating a more complex and stable food web structure. In both the wet and dry seasons, fish in the oxbow primarily relied on endogenous carbon sources, but there were significant differences in the way they were utilized between the two seasons (p < 0.05). In light of the changes in the trophic structure of the fish during the wet and dry seasons, and to ensure the stable development of the Yangtze finless porpoise population, we recommend strengthening the connectivity between the Tian-e-Zhou Oxbow and the Yangtze River.
REPRESENTATION OF THE FATHER FIGURE IN PARENTING IN THE LATEST INDONESIAN NOVEL: A STUDY OF FATHER'S MASCULINITY

Discussions about masculinity, in general, will be associated with certain stereotypes of masculinity. This study aimed to describe the representation of masculinity-fatherhood in the latest Indonesian novels. This research was descriptive qualitative research using the fatherhood theory by Asy'ari and Ariyanto. Data sources were several novels entitled My Father (Not) a Liar (Tere Liye), Ayah (Andrea Hirata), Saturday with Father (Adhitya Mulya), and Father Loves Without End (Kirana Kejora). The steps of data analysis in this study used the technique stated by Miles, et al (2014: 10-12) which included collecting data by means of repeated reading of the novel manuscript and then marking/coding the data found, condensation, and categorizing, analyzing, and drawing a conclusion. The results of the research showed that there was a male role as a son, husband, or father who participated in the domestic sphere while still making or showing his masculine side who show with communication, responsibility, interaction with children, teaching methods, and supervisory roles. The conclusion was father's involvement in the parenting role was a manifestation of emotional closeness, the father's accessibility, and responsibility in various aspects. This was a form of support for men who are more pro-feminist where men can share roles in various aspects. This paternal role was also shown as a form of crossing over between masculine and feminine gender roles, which was a reaction to the hegemony of masculinity as a form of effort to eradicate the dominant father's role in a family.
Evaluation of Children’s Anxiety Level in Relation to a Dental Visit/Treatment and Their Parents’ Dental Fear

The patients’ fear of the dentist plays an important role in the everyday life of a dentist. The anxiety level of children in relation to dental treatment/visits and to their parents’ dental fear was evaluated in three different centers. Assessments of a modified CFSS-DS (mCFSS-DS) were performed by questionnaire with 60 children and their parents. Children’s dmft/DMFT scores, age and gender were evaluated in relation to the parents’ perception of their child’s anxiety levels. For statistical evaluation, Kruskal–Wallis and Wilcoxon tests as well as Spearman’s correlation coefficient (Spearman) were used. The significance level was set at 0.05. There were no significant differences regarding children’s mCFSS-DS between the three centers (p = 0.398, Kruskal–Wallis). The parents’ mCFSS-DS scores correlated significantly with their children’s mCFSS-DS scores (p = 0.004, Spearman). However, the mean mCFSS-DS score of the children was significantly higher than the mean score of parents’ perception of their child’s anxiety (p = 0.000, Wilcoxon). The age of the child had an influence on the mCFSS-DS score (p = 0.02, Kruskal–Wallis) but neither the children’s gender (p = 0.170, Kruskal–Wallis), nor the dmft/DMFT showed an impact (p < 0.725, Spearman). Although a positive correlation was found between the results of the children’s and parents’ questionnaire, many parents underestimated the anxiety level of their children.
Microwave Rectifiers With Wide Output Load Range Based on Multiple Single-Stage Voltage Multipliers in Parallel

A multiple single-stage voltage multipliers in parallel is analyzed and proved theoretically to exhibit slowly changing input impedance with the wide load range in this letter. Based on this unique property, a low-power microwave rectifier consisting of two (which is the optimal number) single-stage voltage multipliers in parallel is designed, fabricated, and measured for different output load, which showed a good characteristics in both efficiency and load range, and kept power conversion efficiency (PCE) higher than 60% from 3 to 20 k<inline-formula> <tex-math notation="LaTeX">$\Omega$ </tex-math></inline-formula>, in good agreement with simulation results.
Deep Unfolding Scheme for Grant-Free Massive-Access Vehicular Networks

Grant-free random access is an effective solution to enable massive access for future Internet of Vehicles (IoV) scenarios based on massive machine-type communication (mMTC). Considering the uplink transmission of grant-free based vehicular networks, vehicular devices sporadically access the base station, the joint active device detection (ADD) and channel estimation (CE) problem can be addressed by compressive sensing (CS) recovery algorithms due to the sparsity of transmitted signals. However, traditional CS-based algorithms present high complexity and low recovery accuracy. In this manuscript, we propose a novel alternating direction method of multipliers (ADMM) algorithm with low complexity to solve this problem by minimizing the $\ell _{2,1}$ norm. Furthermore, we design a deep unfolded network with learnable parameters based on the proposed ADMM, which can simultaneously improve convergence rate and recovery accuracy. The experimental results demonstrate that the proposed unfolded network performs better performance than other traditional algorithms in terms of ADD and CE.
Predicting Prolonged Wound Drainage after Hemiarthroplasty for Hip Fractures: A Stacked Machine Learning Study

Background Prolonged wound drainage (PWD) is one of the most important reasons that increase the risk of early periprosthetic joint infection after arthroplasty. It is very important to evaluate the risk factors for PWD in the surgical field after arthroplasty surgery. This can be accomplished using machine learning or artificial intelligence methods. Our aim in this study was to compare machine learning methods in predicting possible PWD. Methods The study was carried out on clinical, laboratory, and radiological data of 313 patients who underwent hemiarthroplasty (HA) for proximal femur fractures. We preprocessed the dataset and trained and tested machine learning methods using cross validation. We compared various machine learning algorithms (linear discriminant analysis, decision tree, k-nearest neighbors, gradient boosting machine, and logistic regression [LR]) based on performance measures. We also combined the most successful algorithms with a metaclassifier. To help understand the relationship between risk factors, we provided a risk factor severity ranking. Results To estimate the risk of PWD, classification was performed with first-level classifiers and then integrated as a LR-based meta-learner stacking method. More performance improvements were achieved with the stacking method. Conclusions We found that the stacking method was superior to other methods in PWD classification. We determined that the volume of fluid collected from the drain, morbid obesity class, blood transfusion, and body mass index score were the four most important risk factors according to stacking.
A Broadband and High-Aperture-Efficiency Multilayer Transmitarray Based on Aperture-Coupled Slot Unit Cells

A broadband high-gain multilayer transmitarray operating in the X-band is proposed in this work. Unlike most transmitarrays achieving phase compensation by changing their element sizes, the length of striplines of the proposed transmitarray is adjusted to control a wider range of phase responses of identical array elements. By reducing the mutual coupling between adjacent units using surrounded metallic vias, the performance of the proposed transmitarray cell units can be improved significantly. In addition, aperture-coupled bowtie slots with stacked patches are adopted for wideband matching and high gain. By exploiting the true stripline phase compensation and aperture coupled technique with mutual coupling improvement, the proposed transmitarray with a flat gain response is implemented. The designed transmitarray accomplishes an enhanced matching bandwidth covering 8.0–12.0 GHz while adopting the decoupling technique between adjacent unit cells. A square transmitarray of $10\times10$ cells forming an aperture area of $25{\lambda }_{o}^{\mathbf {2}}$ at 10 GHz is fabricated and measured. The measured realized gain is 22.05 dBi, achieving 50% aperture efficiency at 10 GHz. The 1- and 3-dB gain bandwidths are 17.6% (9.35–11.15 GHz) and 19.5% (9.25–11.25 GHz), respectively. The flat gain characteristic with high aperture efficiency candidates the proposed design for radar and satellite applications.
Combining MLP and Feature Engineering to Predict Avalanche Severity

Disasters and emergencies management requires four main phases. Mitigation phase is the first phase of the crisis management cycle. It basically aims to mitigate the danger or even to avoid the crisis. Understanding and anticipating crisis occurrence are key activities to succeed this phase. Snow avalanches are one of the natural disasters that affects several countries in the world. In this paper, we study and discuss the impact of land characteristics and snow stability on avalanche occurrence and severity level. We introduce a Machine learning framework for avalanches forecasting and we use a real dataset to determine prominent factors that can predict the class/severity of an avalanche. To achieve our goal, we apply a Multi-Layer Perceptron (MLP) and we determine a feature subset which achieves the highest accuracy
Exploring the Role of Techno-stress in Job Performance of Academic Librarians of Lahore Pakistan

Rapid changes in technology have affected all walks of life. Role of Techno-stress in job performance of academic librarians is the facts and impact on employees with higher stress levels. This paper studies four dimensions of techno-stress among academic librarians of Public and Private Colleges of Lahore in Punjab Province. Quantitative approach for this study was used with survey method and non-probability sampling technique was employed on population. Those 50 public and private colleges in Lahore were chosen, from which 180 academic librarians were the part of study. Online survey questionnaire was conducted. Frequencies, percentage, mean, standard deviation, correlation, t-test and regression was used for data analysis through SPSS. Results of this research carried out to study techno-stress, it described college librarians experienced moderate level of techno-stress in their job performance. There was particular difference found between male and female college librarians in terms of techno stress. The findings, however, show that techno-overload and techno uncertainty has negative effect on job-performance of female librarians.