Miracle-dz/UniFAR-FTUs huggingface dataset:
UNIVERSIDADE FEDERAL DOS VALES DO JEQUITINHONHA E MUCURI PROGRAMA DE PÓS-GRADUAÇÃO EM CIÊNCIA FLORESTAL

CORREIA, Luiz Paulo de Sousa. Universidade Federal dos Vales do Jequitinhonha e Mucuri, August de 2019. Forwarder Hourly Fuel Consumption Estimation. Advisor: Ângelo Márcio Pinto Leite. Identifying the factors that influence the fuel consumption of forest machines is essential for reducing measures to be developed. In this sense, the objective of this work was to evaluate the effect of the drying time of wood on the fuel consumption of Forwarder employed in the forest extraction activity, aiming to assist in the planning of operations and reduction of production costs. The research was carried out in stands of Eucalyptus spp. of a forestry company located in the state of Minas Gerais. Six treatments were evaluated, corresponding to six drying times (5, 10, 15, 20, 25 and 30 days wood stay in the field after cutting). These treatments were applied in two distinct areas, one with the extraction of the wood performed towards the slope of the terrain Area I and the other with the extraction performed towards the slope of the terrain Area II. The hourly fuel consumption of the Forwarder operating at each treatment and in both directions of extraction was collected. Both consumption during the operating cycle and consumption proportional to each activity of the cycle were recorded. Statistical analysis of the data showed that the wood drying time did not directly influence Forwarder's fuel consumption. It was also possible to verify that the fuel consumption of the Forwarder was different between the empty and loaded displacement operations, being the consumption order dependent on the extraction direction. Also, it was noted that the Forwarder had higher hourly fuel consumption when performing the extraction uphill, considering the operating cycle as a whole. From the hourly consumption data, the specified consumption for each machine activity was calculated. And with this data, the specified consumption was modeled as a function of the time required for loading and unloading, and as a function of the extraction distance when the machine was moved. The modeling quantified the direct influence of the extraction distance (DE) on the Forwarder's specified fuel consumption increase (CEC) during displacement operations and, therefore, complementary studies aiming at the optimization of the DE are fundamental in reducing the ECC and production costs. The modeling demonstrated the direct influence of the loading (TC) and unloading (TD) operation time on the Forwarder's specified fuel consumption increase and, therefore, complementary studies aiming at reducing the execution time of these activities are also important in reduction in CPB and production costs.
Mitochondria‐targeted atovaquone promotes anti‐lung cancer immunity by reshaping tumor microenvironment and enhancing energy metabolism of anti‐tumor immune cells

the TCA cycle and glutamine metabolism were down-regulated across the immunosuppressive immune cell subpopulations of CD4IL2RALO, G-MDSC, mast cells, CD4IL2RAHI and CD4T_Exhausted cells by Mito-ATO treatment; (J) The metabolic reaction steps in TCA cycle and glutamine pathways that exhibited the ‘plasticity’ in reaction activity under Mito-ATO treatment between anti-tumor and pro-tumor immune cells, which involved the key enzymes of Aco1/Aco2, Mdh1/Mdh2, Idh3a/Idh3b/Idh3g in the TCA cycle and the Glud1 enzyme in the glutamine metabolism; (K) The pyruvate metabolism pathway was significantly up-regulated by Mito-ATO in the Mito-ATO-stimulated OXPHOS-high cells; (L) The pyruvate metabolism pathway was significantly down-regulated by Mito-ATO in the Mito-ATO-suppressed OXPHOS-low cells; (M) The glutamine metabolism pathway was not significantly changed by Mito-ATO in the Mito-ATO-stimulated OXPHOS-high cells; (N) The glutamine metabolism pathway was significantly down-regulated by Mito-ATO in the Mito-ATO-suppressed OXPHOS-low cells; (O) The up-regulation of the pyruvate metabolism genes by Mito-ATO in the Mito-ATO-stimulated OXPHOS-high cells and the down-regulation of these genes in the Mito-ATO-suppressed OXPHOS-low cells; (
A Kinetic Model of Clay Mineral Transformation in Overpressure Setting and Its Applications

The models are currently applied to model the smectite-to-illite transformation in petroleum basins using time,temperature and the composition of fluids as controlling parameters.However,small number recent studies have indicated that overpressure will retard the clay mineral transformations and enhance the activity energy of kinetic reactions.Using the data collected from both the overpressured wells and the normally pressured wells,a new kinetic model incorporating overpressure was developed,in which overpressure modifies activity energy.The model was tested in the Banqiao Sag,the Qibei Sag and the Qinan Sag of the Bohaiwan basin,China.As the results show that the computed smectite contents S% in I/S mixed-layer are coincident with the measured data,but significantly different from that predicted by Pytter and Reynolds's model(1989),and the smectite contents S% in I/S mixed layer are retarded by 15%~20% in the overpressure formations with the pressure coefficient of 1.2～1.7. Because lots of such cations as Si~(4+),Ca~(2+),Mg~(2+),Fe~(3+)and Na~(+) are yielded in the smectite-to-illite conversion,the retardations of mineral transformations lead to the decrease of the action productions in the mudstones and the postpone of the cementations in the adjacent sandstones,which is propitious to develop high-quality reservoirs and to form hydrocarbon pools in the deep overpressured basin.
PCBP1 regulates LIFR through FAM3C to maintain breast cancer stem cell self-renewal and invasiveness

ABSTRACT The poly(rC) binding protein 1 gene (PCBP1) encodes the heterogeneous nuclear ribonucleoprotein E1 (hnRNPE1), a nucleic acid-binding protein that plays a tumor-suppressive role in the mammary epithelium by regulating phenotypic plasticity and cell fate. Following the loss of PCBP1 function, the FAM3C gene (encoding the Interleukin-like EMT inducer, or “ILEI” protein) and the leukemia inhibitory factor receptor (LIFR) gene are upregulated. Interaction between FAM3C and LIFR in the extracellular space induces phosphorylation of signal transducer and activator of transcription 3 (pSTAT3). Overexpression and/or hyperactivity of STAT3 has been detected in 40% of breast cancer cases and is associated with a poor prognosis. Herein, we characterize feed-forward regulation of LIFR expression in response to FAM3C/LIFR/STAT3 signaling in mammary epithelial cells. We show that PCBP1 upregulates LIFR transcription through activity at the LIFR promoter, and that FAM3C participates in transcriptional regulation of LIFR. Additionally, our bioinformatic analysis reveals a signature of transcriptional regulation associated with FAM3C/LIFR interaction and identifies the TWIST1 transcription factor as a downstream effector that participates in the maintenance of LIFR expression. Finally, we characterize the effect of LIFR expression in cell-based experiments that demonstrate the promotion of invasion, migration, and self-renewal of breast cancer stem cells (BCSCs), consistent with previous studies linking LIFR expression to tumor initiation and metastasis in mammary epithelial cells.
Blocking miR528 function promotes tillering and regrowth in switchgrass

Summary MiRNAs have been reported to be the key regulators involving a wide range of biological processes in diverse plant species, but their functions in switchgrass, an important biofuel and forage crop, are largely unknown. Here, we reported the novel function of miR528, which has expanded to four copies in switchgrass, in controlling biomass trait of tillering number and regrowth rate after mowing. Blocking miR528 activity by expressing short tandem target mimic (STTM) increased tiller number and regrowth rate after mowing. The quadruple pvmir528 mutant lines derived from genome editing also showed such improved traits. Degradome and RNA‐seq analysis, combined with in situ hybridization assay revealed that up‐regulation of two miR528 targets coding for Cu/Zn‐SOD enzymes, might be responsible for the improved traits of tillering and regrowth in pvmir528 mutant. Additionally, natural variations in the miR528‐SOD interaction exist in C3 and C4 monocot species, implying the distinct regulatory strength of the miR528‐SOD module during monocot evolution. Overall, our data illuminated a novel role of miR528 in controlling biomass traits and provided a new target for genetic manipulation‐mediated crop improvement.
Comparison of tight‐fitting 7T parallel‐transmit head array designs using excitation uniformity and local specific absorption rate metrics

We model the performance of parallel transmission (pTx) arrays with 8, 16, 24, and 32 channels and varying loop sizes built on a close‐fitting helmet for brain imaging at 7 T and compare their local specific absorption rate (SAR) and flip‐angle performances to that of birdcage coil (used as a baseline) and cylindrical 8‐channel and 16‐channel pTx coils (single‐row and dual‐row).
Large Language Model (LLM)-Powered Chatbots Fail to Generate Guideline-Consistent Content on Resuscitation and May Provide Potentially Harmful Advice

Abstract Introduction: Innovative large language model (LLM)-powered chatbots, which are extremely popular nowadays, represent potential sources of information on resuscitation for the general public. For instance, the chatbot-generated advice could be used for purposes of community resuscitation education or for just-in-time informational support of untrained lay rescuers in a real-life emergency. Study Objective: This study focused on assessing performance of two prominent LLM-based chatbots, particularly in terms of quality of the chatbot-generated advice on how to give help to a non-breathing victim. Methods: In May 2023, the new Bing (Microsoft Corporation, USA) and Bard (Google LLC, USA) chatbots were inquired (n = 20 each): “What to do if someone is not breathing? ” Content of the chatbots’ responses was evaluated for compliance with the 2021 Resuscitation Council United Kingdom guidelines using a pre-developed checklist. Results: Both chatbots provided context-dependent textual responses to the query. However, coverage of the guideline-consistent instructions on help to a non-breathing victim within the responses was poor: mean percentage of the responses completely satisfying the checklist criteria was 9.5% for Bing and 11.4% for Bard (P >.05). Essential elements of the bystander action, including early start and uninterrupted performance of chest compressions with adequate depth, rate, and chest recoil, as well as request for and use of an automated external defibrillator (AED), were missing as a rule. Moreover, 55.0% of Bard’s responses contained plausible sounding, but nonsensical guidance, called artificial hallucinations, that create risk for inadequate care and harm to a victim. Conclusion: The LLM-powered chatbots’ advice on help to a non-breathing victim omits essential details of resuscitation technique and occasionally contains deceptive, potentially harmful directives. Further research and regulatory measures are required to mitigate risks related to the chatbot-generated misinformation of public on resuscitation.
Targeting the HIV reservoir: chimeric antigen receptor therapy for HIV cure

Abstract Although antiretroviral therapy (ART) can reduce the viral load in the plasma to undetectable levels in human immunodeficiency virus (HIV)-infected individuals, ART alone cannot completely eliminate HIV due to its integration into the host cell genome to form viral reservoirs. To achieve a functional cure for HIV infection, numerous preclinical and clinical studies are underway to develop innovative immunotherapies to eliminate HIV reservoirs in the absence of ART. Early studies have tested adoptive T-cell therapies in HIV-infected individuals, but their effectiveness was limited. In recent years, with the technological progress and great success of chimeric antigen receptor (CAR) therapy in the treatment of hematological malignancies, CAR therapy has gradually shown its advantages in the field of HIV infection. Many studies have identified a variety of HIV-specific CAR structures and types of cytolytic effector cells. Therefore, CAR therapy may be beneficial for enhancing HIV immunity, achieving HIV control, and eliminating HIV reservoirs, gradually becoming a promising strategy for achieving a functional HIV cure. In this review, we provide an overview of the design of anti-HIV CAR proteins, the cell types of anti-HIV CAR (including CAR T cells, CAR natural killer cells, and CAR-encoding hematopoietic stem/progenitor cells), the clinical application of CAR therapy in HIV infection, and the prospects and challenges in anti-HIV CAR therapy for maintaining viral suppression and eliminating HIV reservoirs.
Longitudinal Changes in Health‐Related Quality of Life in Patients With Atrial Fibrillation

Background Optimizing health‐related quality of life (HRQoL) is an important aim of atrial fibrillation (AF) treatment. Little is known about patients' long‐term HRQoL trajectories and the impact of patient and disease characteristics. The aim of this study was to describe HRQoL trajectories in an observational AF study population and in clusters of patients with similar patient and disease characteristics. Methods and Results We used 5‐year follow‐up data from the Swiss–Atrial Fibrillation prospective cohort, which enrolled 2415 patients with prevalent AF from 2014 to 2017. HRQoL data, collected yearly, comprised EuroQoL‐5 dimension utilities and EuroQoL visual analog scale scores. Patient clusters with similar characteristics at enrollment were identified using hierarchical clustering. HRQoL trajectories were analyzed descriptively and with inverse probability‐weighted regressions. Effects of postbaseline clinical events were additionally assessed using time‐shifted event variables. Among 2412 (99.9%) patients with available baseline HRQoL, 3 clusters of patients with AF were identified, which we characterized as follows: “cardiovascular dominated,” “isolated symptomatic,” and “severely morbid without cardiovascular disease. ” Utilities and EuroQoL visual analog scale scores remained stable over time for the full population and the clusters; isolated symptomatic patients showed higher levels of HRQoL. Utilities were reduced after occurrences of stroke, hospitalization for heart failure, and bleeding, by −0.12 (95% CI, −0.18 to −0.06), −0.10 (95% CI, −0.13 to −0.08), and −0.06 (95% CI, −0.08 to −0.04), respectively, on a 0 to 1 utility scale. Utility of surviving patients returned to preevent levels 4 years after heart failure hospitalization; 3 years after bleeding; and 1 year after stroke. Conclusions In patients with prevalent AF, HRQoL was stable over time, irrespective of baseline patient characteristics. Clinical events of hospitalization for heart failure, stroke, and bleeding had only a temporary effect on HRQoL.
The Neutron Skin of 48Ca and 208Pb: A Critical Analysis

We discuss the neutron skins of 48Ca and 208Pb. We review and critically examine modern predictions and empirical constraints, with special attention to the different interpretations of the findings from the PREX-II experiment and the recently reported value of the neutron skin in 48Ca extracted from the CREX experiment. We argue that, in the spirit of the ab initio philosophy, the path to understanding the behavior of dense neutron-rich matter must not circumvent fundamental nuclear forces. Based only on that argument, a thick neutron skin in 208Pb is highly unlikely.
An integrated atom array -- nanophotonic chip platform with background-free imaging

Arrays of neutral atoms trapped in optical tweezers have emerged as a leading platform for quantum information processing and quantum simulation due to their scalability, reconfigurable connectivity, and high-fidelity operations. Individual atoms are promising candidates for quantum networking due to their capability to emit indistinguishable photons that are entangled with their internal atomic states. Integrating atom arrays with photonic interfaces would enable distributed architectures in which nodes hosting many processing qubits could be efficiently linked together via the distribution of remote entanglement. However, many atom array techniques cease to work in close proximity to photonic interfaces, with atom detection via standard fluorescence imaging presenting a major challenge due to scattering from nearby photonic devices. Here, we demonstrate an architecture that combines atom arrays with up to 64 optical tweezers and a millimeter-scale photonic chip hosting more than 100 nanophotonic devices. We achieve high-fidelity (~99.2%), background-free imaging in close proximity to nanofabricated devices using a multichromatic excitation and detection scheme. The atoms can be imaged while trapped a few hundred nanometers above the dielectric surface, which we verify using Stark shift measurements of the modified trapping potential. Finally, we rearrange atoms into defect-free arrays and load them simultaneously onto the same or multiple devices.
CIRCLE: Multi-Turn Query Clarifications with Reinforcement Learning

Users often have trouble formulating their information needs into words on the first try when searching online. This can lead to frustration, as they may have to reformulate their queries when retrieved information is not relevant. This can be due to a lack of familiarity with the specific terminology related to their search topic, or because queries are ambiguous and related to multiple topics. Most modern search engines have interactive features that suggest clarifications or similar queries based on what others have searched for. However, the proposed models are either based on a single interaction or evaluated on search logs, hindering the naturalness of the interactions. In this paper, we introduce CIRCLE, a generative model for multi-turn query Clarifications wIth ReinforCement LEarning that leverages multi-turn interactions through a user simulation framework. Our model aims at generating a diverse set of query clarifications using a pretrained language model fine-tuned using reinforcement learning. We evaluate it against well established google suggestions using a user simulation framework.
An invariant feature extraction for multi-modal images matching

This paper aims at providing an effective multi-modal images invariant feature extraction and matching algorithm for the application of multi-source data analysis. Focusing on the differences and correlation of multi-modal images, a feature-based matching algorithm is implemented. The key technologies include phase congruency (PC) and Shi-Tomasi feature point for keypoints detection, LogGabor filter and a weighted partial main orientation map (WPMOM) for feature extraction, and a multi-scale process to deal with scale differences and optimize matching results. The experimental results on practical data from multiple sources prove that the algorithm has effective performances on multi-modal images, which achieves accurate spatial alignment, showing practical application value and good generalization.
Zero-Shot Enhancement of Low-Light Image Based on Retinex Decomposition

Two difficulties here make low-light image enhancement a challenging task; firstly, it needs to consider not only luminance restoration but also image contrast, image denoising and color distortion issues simultaneously. Second, the effectiveness of existing low-light enhancement methods depends on paired or unpaired training data with poor generalization performance. To solve these difficult problems, we propose in this paper a new learning-based Retinex decomposition of zero-shot low-light enhancement method, called ZERRINNet. To this end, we first designed the N-Net network, together with the noise loss term, to be used for denoising the original low-light image by estimating the noise of the low-light image. Moreover, RI-Net is used to estimate the reflection component and illumination component, and in order to solve the color distortion and contrast, we use the texture loss term and segmented smoothing loss to constrain the reflection component and illumination component. Finally, our method is a zero-reference enhancement method that is not affected by the training data of paired and unpaired datasets, so our generalization performance is greatly improved, and in the paper, we have effectively validated it with a homemade real-life low-light dataset and additionally with advanced vision tasks, such as face detection, target recognition, and instance segmentation. We conducted comparative experiments on a large number of public datasets and the results show that the performance of our method is competitive compared to the current state-of-the-art methods. The code is available at:https://github.com/liwenchao0615/ZERRINNet
A Reactive performance-based Shared Control Framework for Assistive Robotic Manipulators

In Physical Human--Robot Interaction (pHRI) grippers, humans and robots may contribute simultaneously to actions, so it is necessary to determine how to combine their commands. Control may be swapped from one to the other within certain limits, or input commands may be combined according to some criteria. The Assist-As-Needed (AAN) paradigm focuses on this second approach, as the controller is expected to provide the minimum required assistance to users. Some AAN systems rely on predicting human intention to adjust actions. However, if prediction is too hard, reactive AAN systems may weigh input commands into an emergent one. This paper proposes a novel AAN reactive control system for a robot gripper where input commands are weighted by their respective local performances. Thus, rather than minimizing tracking errors or differences to expected velocities, humans receive more help depending on their needs. The system has been tested using a gripper attached to a sensitive robot arm, which provides evaluation parameters. Tests consisted of completing an on-air planar path with both arms. After the robot gripped a person's forearm, the path and current position of the robot were displayed on a screen to provide feedback to the human. The proposed control has been compared to results without assistance and to impedance control for benchmarking. A statistical analysis of the results proves that global performance improved and tracking errors decreased for ten volunteers with the proposed controller. Besides, unlike impedance control, the proposed one does not significantly affect exerted forces, command variation, or disagreement, measured as the angular difference between human and output command. Results support that the proposed control scheme fits the AAN paradigm, although future work will require further tests for more complex environments and tasks.