Miracle-dz/UniFAR-FTUs huggingface dataset:
An Alternative to Data Transmission in the Amazon Region

ABSTRACT The low population density in the Amazon and the difficulty of access discourage telecommunication companies to expand their networks to meet the riparian communities. Regatao is a project that seeks to meet this need through the use of boats that navigate on Amazon rivers to connect these remote communities with public networks. The communication in this scenario, extremely dynamic as hostile, has intermittent connectivity, suitable for the implementation of delay-tolerant and disruption-tolerant networks (DTNs) technology. The communities and boats are fixed and mobile nodes of a large ad hoc network. Categories and Subject Descriptors C.2. 1 [Network Architecture and Design ]: Store and forward networks General Terms Measurement, Documentation, Design, Experimentation Keywords Amazon, DTN, Ad hoc. 1. INTRODUCTION The Amazon region covering 5.217. 423 km 2 , comprises more than half of the area of Brazil’s territory. However, its population corresponds to only 12% of the Brazilian population, featuring a human population index of 4%, the lowest in the country. Amazon rivers are roads to the residents of this region causing high traffic of vessels, which play an important role as a means of integrating riparian locales with large cities. Almost all Amazon cities and communities are located on the banks of rivers that account for more than 20,000 km of waterways. Regatao is a research project of Computer Networks and Multimedia Group of Federal University of Amazonas (UFAM). It started with the design of a multihop-based communication between boats and riparian communities, forming a mobile ad hoc network (MANET) [1]. Due intermittent connectivity, the project has been investigating DTN by means of simulation and network virtualization techniques and recently has been planning experimentations on a real testbed.
Comparative transcriptomic and proteomic signature of lung alveolar macrophages reveals the integrin CD11b as a regulatory hub during pneumococcal pneumonia infection

Introduction Streptococcus pneumoniae is one of the main causes of community-acquired infections in the lung alveoli in children and the elderly. Alveolar macrophages (AM) patrol alveoli in homeostasis and under infectious conditions. However, the molecular adaptations of AM upon infections with Streptococcus pneumoniae are incompletely resolved. Methods We used a comparative transcriptomic and proteomic approach to provide novel insights into the cellular mechanism that changes the molecular signature of AM during lung infections. Using a tandem mass spectrometry approach to murine cell-sorted AM, we revealed significant proteomic changes upon lung infection with Streptococcus pneumoniae. Results AM showed a strong neutrophil-associated proteomic signature, such as expression of CD11b, MPO, neutrophil gelatinases, and elastases, which was associated with phagocytosis of recruited neutrophils. Transcriptomic analysis indicated intrinsic expression of CD11b by AM. Moreover, comparative transcriptomic and proteomic profiling identified CD11b as the central molecular hub in AM, which influenced neutrophil recruitment, activation, and migration. Discussion In conclusion, our study provides novel insights into the intrinsic molecular adaptations of AM upon lung infection with Streptococcus pneumoniae and reveals profound alterations critical for effective antimicrobial immunity.
Communication-Free Power Control Algorithm for Drone Wireless In-Flight Charging Under Dual-Disturbance of Mutual Inductance and Load

Though the wireless in-flight charging is an ideal way for the energy supply of drones, it also faces the practical challenges, namely dual-disturbance of continuous fluctuation of mutual inductance and battery load variation, changed expected charging power, and the lightweight and no communication design demands for pickup, which have been nearly unexplored in previous article on wireless power transfer (WPT) system. To address the issue, this article proposes a novel communication-free output power control algorithm based on the load identification scheme with automatic frequency adjust. Only the primary current needs to be measured in the proposed algorithm, which can reduce the system complexity with the enhanced real-time performance for WPT system. Simulated and experimental results validate the feasibility of the proposed control algorithm with the identification accuracy of more than 92%, control accuracy of 95%, and average response time within 100 ms. Furthermore, the follow-up of desired output power and the implementation of lightweight pickup demonstrate the flexibility of the power control algorithm, which ensures the rapid and safe energy supply for drones in the drone wireless in-flight charging system.
Mediating effect of successful aging on the relationship between psychological resilience and death anxiety among middle-aged and older adults with hypertension

Objective The aging trend of China's population is severe and successful aging (SA) is imminent. Aging can lead to various chronic diseases, with hypertension being the most common. Due to this lifelong disease, patients suffer from many anxieties, as death anxiety (DA) can be the most prevalent. Studies have exhibited that middle-aged adults approaching the transition to an older state show more pronounced DA than the more senior. It has been suggested that psychological resilience (PR) can reduce DA. Therefore, this study aimed to analyze the mediating effect of SA between PR and DA in middle-aged and older adults with hypertension. Methods A cross-sectional survey was designed. From August to December 2021, 298 middle-aged and older adults with hypertension were selected by multistage cluster random sampling in three districts (Ling he District, Gu ta District, and Tai He District) of Jinzhou City, Liaoning Province. They were surveyed using the demographic questionnaires, the Conner-Davidson Resilience Scale, the Successful Aging Inventory, and the Chinese version of a Likert-type Templer-Death Anxiety Scale. Descriptive analyses, independent sample T-test, and one-way analysis of variance (ANOVA) were used to describe demographic characteristics among hypertensive patients with different characteristics, respectively. Statistics were considered significant when P < 0.05. Pearson correlation coefficients describe the relationship between PR, SA, and DA. The research model was shaped through Structural Equation Modeling (SEM). SPSS PROCESS macro was used to verify the mediation model. A binary logistic regression model was used with DA as the dependent variable. Results The scores for PR, SA, and DA in hypertensive patients are (49.52 ± 14.38) points, (51.22 ± 7.63) points, and (46.67 ± 9.03) points. PR was negatively correlated with DA (r = −0.307, P < 0.01). Moreover, incorporating SA as a mediating variable in PR and DA, SA was positively correlated with PR (r = 0.335, P < 0.01) and DA (r = 0.085, P > 0.05). The direct effect is opposite to the sign of the indirect effect. There is a suppression between PR and DA with a percentage of 20.7%. Good self-assessed health status [0.057 (0.018, 0.183)] may be a protective factor for DA. Conclusion Healthcare providers should improve the PR of middle-aged and older adults with hypertension through interventions that reduce DA and increase the likelihood of SA.
Experimental Evaluation of Proximal Policy Optimization and Advantage Actor-Critic RL Algorithms using MiniGrid Environment

—This paper studies the extended experiments of agent-environment interactions of recent reinforcement learning (RL) algorithms, i.e., Proximal Policy Optimization (PPO) and Advantage Actor Critic (A2C) . In addition to the evaluation of accumulated rewards in the MiniGrid environment, this work also assesses the learned value tables and others. The experiment platform is expanded with arbitrary shape of mazes, customized training scheme, and the average computation from different initial seeds. The key RL formulas and hyperparameters are explicitly discussed with MiniGrid settings. From the obtained results, the conclusion provides the strengths and weaknesses of neural network implementation for RL methods. This is an undergraduate project from summer 2020.
Research on Development Efficiency of Circular Economy of Silk Road Economic Belt: Based on Super Efficiency DEA Model

: With the rapid development of economy and the increasing problems of resource consumption and environmental pollution, circular economy has been recognized as a new way to promote the development of economy, society, ecology and harmony. DEA is a nonparametric efficiency evaluation method. The super efficiency DEA model was used to measure the circular economy development efficiency of nine provinces and cities along the western Silk Road Economic Belt during 2016-2020. Results prove that there is a big difference in circular economy efficiency among regions along the belt. The DEA average efficiency of Shaanxi, Chongqing, Xinjiang, Yunnan and Guangxi are all effective, while the DEA of Ningxia, Gansu, Qinghai and Sichuan is non-effective. The DEA of Ningxia and Sichuan is limited by the development scale. The results also show that Xinjiang, Gansu and Qinghai have input redundancy and output insufficiency to a certain extent. Based on the empirical results, suggestions on how to improve the efficiency of circular economy along the Silk Road Economic Belt are put forward.
Distributed Resource Allocation and User Association for Max-Min Fairness in HetNets

In heterogeneous networks (HetNets), it is difficult to guarantee uniform wireless connectivity satisfying quality of service (QoS) on users' minimum rates because of intensive and capricious inter-cell interference. Therefore, user association (UA) and resource allocation (RA) should be carefully designed at all interfering base stations (BSs) to enhance the achievable QoS on users' minimum rates. However, existing UA frameworks mainly focus on improving sum-rate and proportional fairness, which often results in frequent failure to guarantee minimum rate QoS. In addition, most of them require global channel state information (CSI) or time-consuming iterative optimization. Hence, existing UA approaches cannot be applied under practical conditions such as fast time-varying channels and highly limited information exchange among the BSs. To cope with these practical conditions, we propose a deep-reinforcement-learning (DRL)-based joint UA and RA scheme to maximize the minimum rate, i.e., max-min fairness (MMF), with highly limited information exchange among the BSs. The proposed DRL algorithm optimizes UA at each BS in a distributed manner to maximize an MMF objective function with only local CSI and without any iterative process. Numerical results show that the proposed scheme outperforms the existing schemes and CSI-exchange-based schemes under various scenarios with fast time-varying channels and highly limited information exchange among the BSs.
Optimization of the Non-Linearity Tolerant 4D Geometric Shaped Constellations for Optical Fiber Communication Systems Using Neural Networks

We propose a novel 4D geometric shaping (GS) method based on multilevel coding (MLC) for optical fiber communication systems that mitigates fiber non-linearity. To design non-linearity tolerant 4D constellations, non-linear interference noise (NLIN) and modulation dependency behavior of the fiber are considered during the optimization process. By doing so, the complexity of the 4D GS problem increases extremely, requiring novel optimization approaches to tackle this challenge. Hence, we build a novel deep neural network structure that can efficiently optimize the position of the 4D points. Moreover, we show that optimizing the geometry based on the well-known generalized mutual information rate is not efficient and results in a significant gap to the mutual information rate. To solve this issue, we take advantage of the concept of achievable information rates (AIRs) and multilevel coding. By optimizing the 4D constellations based on the proposed AIRs, our GS scheme provides higher rates than the traditional probabilistic shaping and the recent non-linearity tolerant GS methods.
A Recommender System for Increasing Energy Efficiency of Solar-Powered Smart Homes

Photovoltaic installations can be environmentally beneficial to a greater or lesser extent, depending on the conditions. If the energy produced is not used, it is redirected to the grid, otherwise a battery with a high ecological footprint is needed to store it. To alleviate this problem, an innovative recommender system is proposed for residents of smart homes equipped with battery-free solar panels to optimise the energy produced. Using artificial intelligence, the system is designed to predict the energy produced and consumed for the day ahead using three data sources: sensor logs from the home automation solution, data collected by the solar inverter, and weather data. Based on these predictions, recommendations are then generated and ranked by relevance. Data collected over 76 days were used to train two variants of the system, considering or without considering energy consumption. Recommendations selected by the system over 14 days were randomly picked to be evaluated for relevance, ranking, and diversity by 11 people. The results show that it is difficult to predict residents’ consumption based solely on sensor logs. On average, respondents reported that 74% of the recommendations were relevant, while the values contained in them (i.e., accuracy of times of day and kW energy) were accurate in 66% (variant 1) and 77% of cases (variant 2). Also, the ranking of the recommendations was considered logical in 91% and 88% of cases. Overall, residents of such solar-powered smart homes might be willing to use such a system to optimise the energy produced. However, further research should be conducted to improve the accuracy of the values contained in the recommendations.
Quantitative Analysis of Clot Deposition on Extracorporeal Life Support Membrane Oxygenators Using Digital and Scanning Electron Microscopy Imaging Techniques

Device-induced thrombosis remains a major complication of extracorporeal life support (ECLS). To more thoroughly understand how blood components interact with the artificial surfaces of ECLS circuit components, assessment of clot deposition on these surfaces following clinical use is urgently needed. Scanning electron microscopy (SEM), which produces high-resolution images at nanoscale level, allows visualization and characterization of thrombotic deposits on ECLS circuitry. However, methodologies to increase the quantifiability of SEM analysis of ECLS circuit components have yet to be applied clinically. To address these issues, we developed a protocol to quantify clot deposition on ECLS membrane oxygenator gas transfer fiber sheets through digital and SEM imaging techniques. In this study, ECLS membrane oxygenator fiber sheets were obtained, fixed, and imaged after use. Following a standardized process, the percentage of clot deposition on both digital images and SEM images was quantified using ImageJ through blind reviews. The interrater reliability of quantitative analysis among reviewers was evaluated. Although this protocol focused on the analysis of ECLS membrane oxygenators, it is also adaptable to other components of the ECLS circuits such as catheters and tubing. Key features • Quantitative analysis of clot deposition using digital and scanning electron microscopy (SEM) techniques • High-resolution images at nanoscale level • Extracorporeal life support (ECLS) devices • Membrane oxygenators • Blood-contacting surfaces Graphical overview
Reducing the risk of prenatal alcohol exposure and FASD through social services: promising results from the FAR SEAS pilot project

Introduction Within FAR SEAS, a multi-component evidence-based community intervention was implemented and evaluated in Mazovia (Poland), with the aim of preventing alcohol-exposed pregnancies, and therefore preventing FASD. Methods Multi-disciplinary professionals from different services (social, addiction, and psychology), recruited women of child-bearing age (pregnant and not pregnant) in local communities, screened them for alcohol risk, and allocated participants (n = 441) to groups for low- (70%), moderate- (23%), or high-risk (7%) of alcohol exposed pregnancy, to provide interventions tailored to their needs. The non-parametric sign test, testing differences between pairs of observations before and after intervention was used to evaluate the outcomes. Results Follow-up data (collected from 93% of participants) indicated positive changes in the key outcome variables: risky alcohol consumption dropped by 81%, contraception use increased by 15% and visiting a gynecologist increased by 39%; as well as in associated psychosocial risk factors (decrease in cigarette and drug use, domestic violence and depressive symptoms). No changes were noted in frequency of other service use (medical, psychological, or social). The most prominent changes were observed in the moderate-risk group. Discussion Changing risky behaviors (alcohol consumption and sex without contraception) to prevent alcohol exposed pregnancies is feasible at the local level, even without engagement of medical professionals. Key challenges, related to engaging professionals and local authorities, must be addressed; and procedures should be adapted to local contexts and needs.
Remodeling Tumor Immune Microenvironment by Using Polymer-Lipid-Manganese Dioxide Nanoparticles with Radiation Therapy to Boost Immune Response of Castration-Resistant Prostate Cancer

Despite substantial progress in the treatment of castration-resistant prostate cancer (CRPC), including radiation therapy and immunotherapy alone or in combination, the response to treatment remains poor due to the hypoxic and immunosuppressive nature of the tumor microenvironment. Herein, we exploited the bioreactivity of novel polymer–lipid manganese dioxide nanoparticles (PLMDs) to remodel the tumor immune microenvironment (TIME) by increasing the local oxygen levels and extracellular pH and enhancing radiation-induced immunogenic cell death. This study demonstrated that PLMD treatment sensitized hypoxic human and murine CRPC cells to radiation, significantly increasing radiation-induced DNA double-strand breaks and ultimately cell death, which enhanced the secretion of damage-associated molecular patterns, attributable to the induction of autophagy and endoplasmic reticulum stress. Reoxygenation via PLMDs also polarized hypoxic murine RAW264.7 macrophages toward the M1 phenotype, enhancing tumor necrosis factor alpha release, and thus reducing the viability of murine CRPC TRAMP-C2 cells. In a syngeneic TRAMP-C2 tumor model, intravenous injection of PLMDs suppressed, while radiation alone enhanced recruitment of regulatory T cells and myeloid-derived suppressor cells. Pretreatment with PLMDs followed by radiation down-regulated programmed death-ligand 1 and promoted the infiltration of antitumor CD8+ T cells and M1 macrophages to tumor sites. Taken together, TIME modulation by PLMDs plus radiation profoundly delayed tumor growth and prolonged median survival compared with radiation alone. These results suggest that PLMDs plus radiation is a promising treatment modality for improving therapeutic efficacy in radioresistant and immunosuppressive solid tumors.
PCB-pollution problem in the upper Hudson River: From environmental disaster to environmental gridlock

The PCB pollution of the upper Hudson River has been traced to two discharge pipes from capacitor-manufacturing plants of the General Electric Company (GE) at Hudson Falls and Fort Edward, located about 40 miles north of Troy, New York. In August 1974, EPA biologists carried out a field investigation upstream of, at, and downstream of the GE discharge pipes. In September 1975, goaded by articles about PCB-contaminated fish from the Hudson Estuary, the Commissioner of the New York State Department of conservation (NYS DEC) commenced an administrative proceeding against GE, alleging violations of several NY State Environmental Conservation Law sections, and seeking cessation of PCB discharges, penalties for past discharges, and rehabilitation of the upper river. One stipulation of the resulting settlement agreement was that New York State sign off with GE over PCB pollution of the Hudson River and, if the Advisory Committee recommended in favor of rehabilitation, it would use its best efforts to find funds from sources other than GE to help pay for rehabilitation. The future of the PCB problem in the upper Hudson River seems likely to be settled by the outcome of a class-action lawsuit that commercial fisherman have filed against GE. In Januarymore » 1989, a NEW York Appeals Court voted in favor of the ruling that the fishermen were entitled not only to payments for lost income, but to injunctive relief (which implies that GE must clean up the River). 311 refs., 30 figs., 14 tabs. « less
Molecular Insight into Iron Homeostasis of Acute Myeloid Leukemia Blasts

Acute myeloid leukemia (AML) remains a disease of gloomy prognosis despite intense efforts to understand its molecular foundations and to find efficient treatments. In search of new characteristic features of AML blasts, we first examined experimental conditions supporting the amplification of hematological CD34+ progenitors ex vivo. Both AML blasts and healthy progenitors heavily depended on iron availability. However, even if known features, such as easier engagement in the cell cycle and amplification factor by healthy progenitors, were observed, multiplying progenitors in a fully defined medium is not readily obtained without modifying their cellular characteristics. As such, we measured selected molecular data including mRNA, proteins, and activities right after isolation. Leukemic blasts showed clear signs of metabolic and signaling shifts as already known, and we provide unprecedented data emphasizing disturbed cellular iron homeostasis in these blasts. The combined quantitative data relative to the latter pathway allowed us to stratify the studied patients in two sets with different iron status. This categorization is likely to impact the efficiency of several therapeutic strategies targeting cellular iron handling that may be applied to eradicate AML blasts.
Streamflow model of Wisconsin River for estimating flood frequency and volume

A set of daily streamflow-routing models are used to simulate Streamflow at 10 sites along the Wisconsin River for water years 1915-76, to determine the effects the reservoir system has on flood discharges. Streamflow is simulated under the following two conditions: (1) No reservoirs are in the system and (2) all of the present reservoirs are in place and operated with current rules. At Wisconsin Dells, 20 miles upstream from Portage, daily Streamflow hydrographs are estimated for the 10-, 50-, 100-, and 500-year floods. These were determined from statistical analysis of the simulated daily streamflows for the condition of all reservoirs in place. The reservoirs have a significant impact on floods. The mean annual flood peak at Wisconsin Dells is lowered about 20 percent from 43,000 cubic feet per second for the simulated, unregulated condition to 34,000 cubic feet per second for the simulated, regulated condition. The 100-year flood peak at Wisconsin Dells is reduced about 10 percent (92,000 to 82,000 cubic feet per second) between the simulated, unregulated and simulated, regulated conditions. The 100-year flood peak at Wisconsin Dells, computed from the simulated, regulated Streamflow data for the period 1915-76, is 82,000 cubic feet per second, including the effects of all the reservoirs in the river system, as they are currently operated. It also includes the effects of Lakes Du Bay, Petenwell, and Castle Rock which are significant for spring floods but are insignificant for summer or fall floods because they are normally maintained nearly full in the summer and fall and have very little storage for floodwaters.