Miracle-dz/UniFAR-FTUs huggingface dataset:
pTLC: Personalized Traffic Light Control Based on Deep Reinforcement Learning Approach

Traffic signal control is a critical aspect of improving urban traffic efficiency and reducing road accidents. Reinforcement learning (RL) has been applied to solve the intersection traffic control problem, which is flexible and can be adapted to dynamic traffic conditions. However, most existing RL methods only consider a single vehicle type, ignoring the impact of multiple vehicle types on traffic and safety. To address this gap, we propose a new RL method called pTLC, which aims to allow trucks to cross intersections quickly while minimizing the impact on other vehicles. In this method, vehicle type is added as a state variable to capture the influence of different vehicle types on traffic flow. At the same time, a new state representation method is proposed that divides the road into several road sections to balance the environmental information and the size of the state space. We design simulation experiments under different traffic demand scenarios, including cars and trucks, to verify the effectiveness of the method. The results show significant improvements in traffic efficiency and safety, especially for mixed vehicle types.
A Systematic Review of Blockchain Solutions for Routing Protocols in Low Power and Lossy Networks

: Low Power and Lossy Networks (LLNs) are a class of networks characterized by constrained resources, intermittent connectivity, and potential lossy links. These networks find applications in various domains such as Internet of Things (IoT), smart grids, and industrial automation. However, the inherent challenges of LLNs, including energy efficiency, routing reliability, and scalability, have prompted researchers to explore innovative solutions. Blockchain, a de - centralized and secure distributed ledger technology, has emerged as a potential candidate to address these challenges. This systematic review aims to comprehensively analyze and evaluate the existing research on utilizing blockchain solutions for routing protocols in LLNs. The review follows a structured methodology to identify, categorize, and critically assess the state - of - the - art research contributions in this domain.
Draft genome of methanol-oxidizing Methylobacterium fujisawaense strain LAC1

ABSTRACT We report the draft genome of Methylobacterium fujisawaense LAC1 isolated from an acidic aquifer in Indian Head, MD, USA. The genome contains 5,883,000 bp and has a GC content of 70% with 5,434 protein-encoding genes with functional assignments. This strain can grow on methanol with lanthanum, a rare earth element.
A Reinforcement Learning-Based Incentive Scheme for Multi-Hop Communications in Vehicular Networks

Vehicular network applications heavily rely on multi-hop communication technologies to ensure efficient and reliable data transmissions because of the limited wireless transmission range of vehicles, road side units, and some other mobile devices in the network. There is a common assumption in most of the applications that all network nodes are cooperative during the entire network procedure. However, this is not practical in reality, because rational nodes are reluctant to assist others with consuming own precious resources. Hence, incentive mechanisms are inevitably required to encourage the intermediate nodes to forward data packets for multi-hop communications. Nevertheless, the high mobility of nodes and the intermittent connectivity among them make the estimation of the environment extremely challenging in vehicular networks. Moreover, in some traffic scenarios where there is a lack of fixed infrastructures (rural area, disaster areas, or during maintenance), the incentive schemes should be self-organized in a distributed manner. In this paper, we propose an incentive scheme for multi-hop communications in vehicular networks. The proposed scheme estimates the complicated dynamic environment based on a fuzzy logic approach, then further stimulates intermediate nodes to maximize the expected utility from a long-term perspective based on a reinforcement learning method in a fully distributed manner. To evaluate the performance of our proposed scheme, we conducted extensive computer simulations based on realistic traffic networks in Xi’an city of China. The results of the simulations demonstrate that the proposed scheme has the superiority of incentive capabilities over other baseline approaches in terms of packet delivery ratio, end-to-end delay within vehicular networks.
Low-Cost ZnO Spray-Coated Optical Fiber Sensor for Detecting VOC Biomarkers of Diabetes

A non-invasive optical fiber sensor for detecting volatile organic compounds (VOCs) as biomarkers of diabetes is proposed and experimentally demonstrated. It offers a low-cost and straightforward fabrication approach by implementing a one-step spray coating of a ZnO colloidal solution on a glass optical fiber. The structure of the optical fiber sensor is based on a single-mode fiber–coreless silica fiber–single-mode fiber (SMF-CSF-SMF) structure, where the CSF is the sensor region spliced between two SMFs. The ZnO layer of a higher refractive index coated over the sensing region improves the light interaction with the surrounding medium, leading to sensitivity enhancement. The optical properties, morphology, and elemental composition of the ZnO layer were analyzed. The sensing mechanism of the developed sensor is based on a wavelength interrogation technique showing wavelength shifts when the sensor is exposed to various VOC vapor concentration levels. Various concentrations of the three VOCs (including acetone, isopropanol, and ethanol) ranging from 20% to 100% were tested and analyzed. The sensor noticeably shows a significant response towards acetone vapor, with a better sensitivity of 0.162 nm/% vapor than for isopropanol (0.082 nm/% vapor) and ethanol (0.075 nm/% vapor) vapors. The high sensitivity and selectivity towards acetone, a common biomarker for diabetes, offers the potential for further development of this sensor as a smart healthcare system for monitoring diabetic conditions.
Plug-and-Play Priors for Multi-Shot Compressive Hyperspectral Imaging

Multi-shot coded aperture snapshot spectral imaging (CASSI) uses multiple measurement snapshots to encode the three-dimensional hyperspectral image (HSI). Increasing the number of snapshots will multiply the number of measurements, making CASSI system more appropriate for detailed spatial or spectrally rich scenes. However, the reconstruction algorithms still face the challenge of being ineffective or inflexible. In this paper, we propose a plug-and-play (PnP) method that uses denoiser as priors for multi-shot CASSI. Specifically, the proposed PnP method is based on the primal-dual algorithm with linesearch (PDAL), which makes it flexible and can be used for any multi-shot CASSI mechanisms. Furthermore, a new subspaced-based nonlocal reweighted low-rank (SNRL) denoiser is presented to utilize the global spectral correlation and nonlocal self-similarity priors of HSI. By integrating the SNRL denoiser into PnP-PDAL, we show the balloons ( $512\times 512\times31$ ) in CAVE dataset recovered from two snapshots compressive measurements with MPSNR above 50 dB. Experimental results demonstrate that our proposed method leads to significant improvements compared to the current state-of-the-art methods.
Spectral mixture analysis and object-based image analysis for forestry applications

El objetivo de la presente tesis doctoral es analizar la aplicacion de la teledeteccion optica -imagenes captadas por satelite- a la estimacion de biomasa aerea forestal, a la cartografia de severidad de incendios forestales, a la cartografia de masas de pino silvestre y a la de cambios de cobertura de bosques producida por mineria a cielo abierto en bosques mediterraneos espanoles. El trabajo se centro en el estudio de la utilidad del analisis de mezclas espectrales lineales (LSMA) y del analisis de imagenes basado en objetos (OBIA) como principales tecnicas para el procesado de imagenes de satelite. Medidas en el terreno e inventarios forestales fueron utilizados como datos de referencia. Imagenes de satelite de los sensores ASTER, Landsat TM y Landsat ETM+ fueron los principales datos satelitales empleados. Segun el autor, los resultados indican que la utilizacion de imagenes de fraccion ASTER en modelos de regresion mejoran la estimacion de la biomasa aerea en pinares mediterraneos; del mismo modo, el analisis de mezclas espectrales junto a tecnicas de regresion pueden ser empleados para la cuantificacion de volumen en masas forestales de pino silvestre en entornos de transicion mediterraneos; ademas, la utilizacion conjunta de LSMA y OBIA para evaluar y cartografiar los diferentes niveles de severidad de un incendio forestal consiguieron una mayor precision , incluso mejorando la de los niveles o clases individuales de severidad. Una conclusion mas fue que las tecnicas de teledeteccion al integrarse en procesos de seguimiento permiten a las agencias responsables de la regulacion y restauracion de explotaciones mineras a cielo abierto, ejecutar de forma mas eficiente sus trabajos y ayudar a evitar o minimizar los efectos adversos de este tipo de mineria.
Geochronological study of post-metamorphic granite from Kasumi Rock, Lutzow-Holm Complex, East Antarctica

Kasumi Rock is situated in the amphibolite-facies metamorphic zone in the Lützow-Holm Complex, East Antarctica. In this area, granitic rocks occur as steeply dipping linear dykes with sharp intrusive contacts, and cross-cut the foliation of layered metamorphic rocks. A geochronological study of this post-metamorphic granite (PMG) has been performed. An Rb-Sr whole rock isochron for five granitic rocks defines an age of . 3,. + ,-. Ma with an initial Sr/ Sr ratio of *. 1*/-/ *. ***,1 (MSWD *.*2). In the Sm-Nd isochron diagram, four rock samples yield an age of . 32. 3*. 0Ma with an initial Nd/ Nd ratio of *. /++12, *. ***+*+ (MSWD *.*/). The whole rock isochron ages and mode of occurrence suggest that the Kasumi PMGs were intruded after regional cooling of the area, and probably a#ected local reequilibrium for isotopic systems of surrounding metamorphic rocks. The PMGs might have been slowly cooled and crystallized after the intrusion. The Kasumi PMGs have no genetic relation to the Oku-iwa PMGs as regards Rb-Sr and Sm-Nd isotopic systems, because the initial ratios of both PMGs are quite di#erent from each other. This is interpreted to mean that the PMGs in the Lützow-Holm Complex were originated from di#erent source materials or had di#erent chemical reaction processes with crustal materials. key words: Rb-Sr whole rock isochron, Sm-Nd whole rock isochron, post-metamorphic granite, Kasumi Rock, Lützow-Holm Complex
RNA‐based medicine: from molecular mechanisms to therapy

RNA‐based therapeutics have the potential to revolutionize the treatment and prevention of human diseases. While early research faced setbacks, it established the basis for breakthroughs in RNA‐based drug design that culminated in the extraordinarily fast development of mRNA vaccines to combat the COVID‐19 pandemic. We have now reached a pivotal moment where RNA medicines are poised to make a broad impact in the clinic. In this review, we present an overview of different RNA‐based strategies to generate novel therapeutics, including antisense and RNAi‐based mechanisms, mRNA‐based approaches, and CRISPR‐Cas‐mediated genome editing. Using three rare genetic diseases as examples, we highlight the opportunities, but also the challenges to wide‐ranging applications of this class of drugs.
Atomic cluster expansion force field based thermal property material design with density functional theory level accuracy in non-equilibrium molecular dynamics calculations over sub-million atoms

Non-equilibrium molecular dynamics (NEMD) techniques are widely used for investigating lattice thermal conductivity. Recently, machine learning force fields (MLFFs) have emerged as a promising approach to enhance the precision in NEMD simulations. This study is aimed at demonstrating the potential of MLFFs in realizing NEMD calculations for large-scale systems containing over 100,000 atoms with density functional theory (DFT)-level accuracy. Specifically, the atomic cluster expansion (ACE) force field is employed, using Si as an example. The ACE potential incorporates 4-body interactions and features a training dataset consisting of 1000 order structures from first-principles molecular dynamics calculations, resulting in a highly accurate vibrational spectrum. Moreover, the ACE potential can reproduce thermal conductivity values comparable with those derived from DFT calculations via the Boltzmann equation. To demonstrate the application of MLFFs to systems containing over 100,000 atoms, NEMD simulations are conducted on thin films ranging from 100 nm to 500 nm, with the 100 nm films exhibiting defect rates of up to 1.5%. The results show that the thermal conductivity deviates by less than 5% from DFT or theoretical results in both scenarios, which highlights the ability of the ACE potential in calculating the thermal conductivity on a large scale with DFT-level accuracy. The proposed approach is expected to promote the application of MLFFs in various fields and serve as a feasible alternative to virtual experiments. Furthermore, this work demonstrates the potential of MLFFs in enhancing the accuracy of NEMD simulations for investigating lattice thermal conductivity for systems with over 100,000 atoms.
Pinning Control of Complex Networks Based on Node In-Out Degree and Neighbor Nodes

In order to solve the selection problem of pinning nodes in directed and weighted networks, a new pinning control algorithm called DN (node in-out degree and neighbor nodes) is proposed. Firstly, based on the general dynamic model, the synchronicity of the complex network is analyzed, and the conditions for the complex network to achieve synchronization are obtained. Secondly, the pinning control algorithm of nodes is given, and the ranking of pinning nodes in the network is obtained through this algorithm. The conditions under which synchronization is achieved through a complex network determine which nodes in the network should be pinned. Finally, an experimental simulation is carried out on a directed weighted network. By comparing the node pinning control strategy based on the adjacency information entropy, it is concluded that under the same coupling strength, in order to achieve synchronization of the network, the number of nodes pinned by this algorithm is less.
Open-Endedness Induced Through a Predator-Prey Scenario Using Modular Robots

This work investigates how a predator-prey scenario can induce the emergence of Open-Ended Evolution (OEE). We utilize modular robots of fixed morphologies whose controllers are subject to evolution. In both species, robots can send and receive signals and perceive the relative positions of other robots in the environment. Specifically, we introduce a feature we call a tagging system: it modifies how individuals can perceive each other and is expected to increase behavioral complexity. Our results show the emergence of adaptive strategies, demonstrating the viability of inducing OEE through predator-prey dynamics using modular robots. Such emergence, nevertheless, seemed to depend on conditioning reproduction to an explicit behavioral criterion.
Safety and tolerability of continuous inhaled iloprost in critically ill pediatric pulmonary hypertension patients: A retrospective case series

Abstract Inhaled iloprost (iILO) has shown efficacy in treating patients with hypoxic lung disease and pulmonary hypertension, inducing selective pulmonary vasodilation and improvement in oxygenation. However, its short elimination half‐life of 20–30 min necessitates frequent intermittent dosing (6–9 times per day). Thus, the administration of iILO via continuous nebulization represents an appealing method of drug delivery in the hospital setting. The objectives are: (1) describe our continuous iILO delivery methodology and safety profile in mechanically ventilated pediatric pulmonary hypertension patients; and (2) characterize the initial response of iILO in these pediatric patients currently receiving iNO. Continuous iILO was delivered and well tolerated (median 6 days; range 1–94) via tracheostomy or endotracheal tube using the Aerogen® mesh nebulizer system coupled with a Medfusion® 400 syringe pump. No adverse events or delivery malfunctions were reported. Initiation of iILO resulted in an increase in oxygen saturation from 81.4 ± 8.6 to 90.8 ± 4.1%, p < 0.05. Interestingly, prior iNO therapy for >1 day resulted in a higher response rate to iILO (as defined as a ≥ 4% increase in saturations) compared to those receiving iNO <1 day (85% vs. 50%, p = 0.06). When the use of iILO is considered, continuous delivery represents a safe, less laborious alternative and concurrent treatment with iNO should not be considered a contraindication. However, given the retrospective design and small sample size, this study does not allow the evaluation of the efficacy of continuous iILO on outcomes beyond the initial response. Thus, a prospective study designed to evaluate the efficacy of continuous iILO is necessary.
Enhanced molybdenum(VI) adsorption by zirconia sol-modified nanoscale iron sulfide: performance, mechanism and influencing factors

The significant increase in demand for molybdenum (Mo) resources has led to excessive molybdate (Mo(VI)) content in water, posing a challenge to the innovation of Mo(VI) removal technology in water bodies. Nanoscale iron sulfide (FeS) has an important effect on the environmental behav - ior of Mo(VI) in aquatic solutions. To address the issue of easy agglomeration and poor stability of FeS, zirconia sol-modified nanoscale iron sulfide (Zr-FeS) was synthesized, and the adsorption behavior of Zr-FeS on Mo(VI) from diverse aquatic solutions was also investigated in this study. The results showed that the removal rate of Mo(VI) was increased from 28.60% to 78.32% within pH value of 7.0 when Zr/Fe molar ratio was elevated from 0 to 0.5. Moreover, the Mo(VI) adsorp - tion efficiency by Zr-FeS was closely related to pH values, and acid conditions were beneficial for Mo(VI) adsorption. The pseudo-second-order model demonstrated a better fit to the data compared to other models. The maximum adsorption capacity of Zr-FeS towards Mo(VI) value calculated by Langmuir isotherm model was 118.48 mg/g at 298 K. The thermodynamic analysis revealed that the adsorption process of Mo(VI) was endothermic, entropically favorable, and spontaneous in nature. Competing anions (e.g., PO 4 3– , HCO 3– , and SO 4 2– ) partially inhibited the adsorption process of Mo(VI) by Zr-FeS. While the process was less affected by dissolved oxygen and aging. The results of Fourier-transform infrared spectroscopy, X-ray diffraction, X-ray photoelectron spectroscopy, and density functional theory (DFT) calculations revealed that the main mechanisms for Mo(VI) removal were hydrogen bonding, electrostatic interaction and surface complexation. The high sta - bility and fast adsorption rate indicated that Zr-FeS was a promising material to remove Mo(VI) from the aquatic solutions.
Impact of body mass index on outcome and treatment-related toxicity in young adults with acute lymphoblastic leukemia

Abstract Background Data on outcome for patients in different body mass index (BMI) categories in young adults with acute lymphoblastic leukemia (ALL) are scarce. We explored survival and toxicities in different BMI categories in young adults with ALL. Material and methods Patients aged 18–45 years, diagnosed with ALL between July 2008 and June 2022 in the Nordic countries, Estonia, or Lithuania, and treated according to the NOPHO ALL2008 protocol, were retrospectively enrolled and classified into different BMI categories. Endpoints were overall survival (OS), event-free survival (EFS) and cumulative incidence of relapse as well as incidence rate ratio (IRR) of severe predefined toxic events, and treatment delays. Results The group comprised 416 patients, of whom 234 (56%) were stratified to non-high-risk (non-HR) treatment. In the non-HR group, patients with severe obesity, BMI ≥35 kg/m2 had worse EFS due to relapses but there was no effect on toxicity or treatment delays compared with the healthy-weight patients. There was no association between BMI category and OS, overall toxicity, or treatment delays in the patients with high-risk treatment. Conclusion Severe obesity is associated with worse EFS in young adults treated according to the non-HR arms of the NOPHO ALL2008 protocol. Poorer outcome is explained with a higher risk of relapse, possibly due to under treatment, and not caused by excess therapy-related mortality.
Increased task-relevant fMRI responsiveness in comatose cardiac arrest patients is associated with improved neurologic outcomes

Early prediction of the recovery of consciousness in comatose cardiac arrest patients remains challenging. We prospectively studied task-relevant fMRI responses in 19 comatose cardiac arrest patients and five healthy controls to assess the fMRI’s utility for neuroprognostication. Tasks involved instrumental music listening, forward and backward language listening, and motor imagery. Task-specific reference images were created from group-level fMRI responses from the healthy controls. Dice scores measured the overlap of individual subject-level fMRI responses with the reference images. Task-relevant responsiveness index (Rindex) was calculated as the maximum Dice score across the four tasks. Correlation analyses showed that increased Dice scores were significantly associated with arousal recovery (P < 0.05) and emergence from the minimally conscious state (EMCS) by one year (P < 0.001) for all tasks except motor imagery. Greater Rindex was significantly correlated with improved arousal recovery (P = 0.002) and consciousness (P = 0.001). For patients who survived to discharge (n = 6), the Rindex’s sensitivity was 75% for predicting EMCS (n = 4). Task-based fMRI holds promise for detecting covert consciousness in comatose cardiac arrest patients, but further studies are needed to confirm these findings. Caution is necessary when interpreting the absence of task-relevant fMRI responses as a surrogate for inevitable poor neurological prognosis.
Research on a Mediation Model of the Impact of Parental Involvement on Children's Cognitive and Language Skills based on Process Macro in SPSS

This study used PROCESS Macro software in SPSS to examine the relationship between Chinese parental educational involvement and preschool children's cognitive and language skills as well as the mediating role of children's social-emotional competence in this relationship. A total of 311 third-year kindergarten Chinese preschool children and their parents in Shanghai, China participated in this study. Results indicated that parental involvement positively predicted children's cognitive and language skills. The relationship between parental involvement and children's early cognitive and language skills was partially mediated by children's social-emotional competence. This study validated a mediation model of the indirect effect of parental involvement on children's cognitive and language skills through children's social-emotional competence.