Miracle-dz/UniFAR-FTUs huggingface dataset:
High-Flow Oxygen Therapy in the Perioperative Setting and Procedural Sedation: A Review of Current Evidence

High-flow oxygen therapy (HFOT) is a respiratory support system, through which high flows of humidified and heated gas are delivered to hypoxemic patients. Several mechanisms explain how HFOT improves arterial blood gases and enhances patients’ comfort. Some mechanisms are well understood, but others are still unclear and under investigation. HFOT is an interesting oxygen-delivery modality in perioperative medicine that has many clinical applications in the intensive care unit (ICU) and the operating room (OR). The purpose of this article was to review the literature for a comprehensive understanding of HFOT in the perioperative period, as well as its uses in procedural sedation. This review will focus on the HFOT definition, its physiological benefits, and their mechanisms, its clinical uses in anesthesia, and when it is contraindicated.
Porous Microgels for Delivery of Curcumin: Microfluidics-Based Fabrication and Cytotoxicity Evaluation

Polymeric microgels, fabricated via microfluidic techniques, have garnered significant interest as versatile drug delivery carriers. Despite the advances, the loading and release of hydrophobic drugs such as curcumin from polymeric microgels is not trivial. Herein, we report that effective drug loading can be achieved by the design of porous particles and the use of supramolecular cyclodextrin-based curcumin complexes. The fabrication of porous microgels through the judicious choice of chemical precursors under flow conditions was established. The evaluation of the curcumin loading dependence on the porosity of the microgels was performed. Microgels with higher porosity exhibited better curcumin loading compared to those with lower porosity. Curcumin-loaded microgels released the drug, which, upon internalization by U87 MG human glioma cancer cells, induced cytotoxicity. The findings reported here provide valuable insights for the development of tailored drug delivery systems using a microfluidics-based platform and outline a strategy for the effective delivery of hydrophobic therapeutic agents such as curcumin through supramolecular complexation.
Variational Inference-Based Channel Estimation for Reconfigurable Intelligent Surface-Aided Wireless Systems

We propose a variational inference-based channel estimation method in fully passive reconfigurable intelligent surface (RIS)-aided mmWave single-user single-input multiple-output (SIMO) communication systems. The main goal is to jointly estimate the user equipment (UE)-to-RIS (UE-RIS) and RIS-to-base station (RIS-BS) channels using uplink training signals in a passive RIS setup. Specifically, by using a variational inference framework, we approximate the posterior of the channels with convenient distributions given the received uplink training signals. The parameters of the approximated distributions are generated by deep neural networks trained using variational loss functions derived using a lower bound on the log-likelihood of the received signal. Then, the learned distributions, which are close to the true posterior distributions in terms of Kullback Leibler divergence, are leveraged to obtain the maximum a posteriori (MAP) estimation of the UE-RIS and RIS-BS channels. We evaluate the proposed channel estimation solution under two channel priors. The first channel prior models Rayleigh fading channels with Gaussian prior, whereas the second one represents sparse channels in the angular domain with Laplace prior. The simulation results demonstrate that MAP channel estimates using the approximated posteriors yield a capacity which is close to the one achieved with the true posteriors, thus demonstrating the effectiveness of the proposed method.
DNS Tunnel Detection for Low Throughput Data Exfiltration via Time-Frequency Domain Analysis

Domain Name System (DNS) is one of the most common and vital services on the Internet. Attackers take advantage of DNS tunneling to bypass firewalls for data exfiltration, which has been a significant risk in cyber security. Although there are studies on DNS tunneling detection, few are concerned with low-throughput data exfiltration over DNS tunnels. This paper proposes a low-throughput data exfiltration detection method via time-frequency domain analysis on DNS traffic. We conduct the time and frequency domain analysis on time windows of DNS traffic in different granularities. The frequency domain features effectively encode sequential information of the packet sequences, which sketch malicious patterns in low-throughput DNS tunnels. We evaluate our method on the DNS traffic of an enterprise network. Experimental results exhibit that our method significantly outperforms the existing approach in detecting low-throughput data exfiltration over DNS tunnels.
eLite : système de synthèse de la parole à orientation linguistique

eLite is the Text-to-Speech synthesis system developed by the TTS-NLP group of Multitel ASBL. The creation of eLite has been an opportunity for the group to carry out and integrate further research on all domains of textto-speech synthesis, like morphological analysis, syntactic desambiguation and non-uniform units selection. This paper presents the general features and techniques of the system.
Seasonal and regional features of long-term precipitation changes in Japan

1901～2009年の国内51地点の日降水量データを使って、降水の長期変動を調べた。 降水の尺度としては、世界気象機関（WMO）の気候委員会（CCl）や世界気候研究計画（WCRP）で提唱されているものの中から、降水量（PRCPTOT）、降水日数（R1mm）のほか、単純日降水強度（SDII），最大連続無降水日（CDD）、最大連続降水日（CWD）を取り上げた。 これらの尺度の年間統計値について、全国平均値の長期変化率（1次トレンド）を見ると、PRCPTOTは0. 055%/年の率で減少、R1mmはより大きく0. 126%/年の率で減少しており、これに伴ってSDIIは0. 076%/年の増加、CDDは0. 159%/年の増加、CWDは0. 151%/年の減少が認められる。 一方季節ごとに各尺度の変化率を見ると、さまざまな地域特性が見られ、そのパターンに季節同士の類似性は少ない。 さらに、月ごとあるいは6半旬平均の変化率も、月単位あるいは1～2ヶ月スケールで変動している。 こうした変動は降水の長期変化率における季節的特性の一端を捉えていると考えられ、東～西日本で梅雨期間が遅れる傾向など将来気候予測実験で得られた特徴と共通する部分もある。 しかし、今回の結果にはデータ数の制約による不確実性が影響している可能性もあり、降水の長期変化の地域性や季節性をより正確に捉えていくためには、それをもたらす循環場に対する研究を進めることが必要であると考えられる。
Studies on Tourism Commercialization in Historic Towns

This paper analyzes the current commercial status quo in the tourist historic towns of Zhouzhuang and Lijiang in China by using first-hand data. It examines the present use of historical buildings in the two towns in order to investigate the relationship between tourism and the use of buildings. In 2002, 682 building units in Lijiang, accounting for nearly 70% of all units in the main streets, were used for commercial purposes catering tourists; while 10.42% of the buildings catered local residents. These findings suggest that Lijiang has become a tourism-oriented town and its traditional culture is being threatened by tourism. This applies to Zhouzhuang, which attracted 1.5 million tourists in 2000, when 67.02% of building units in the main streets were used to cater tourists, while only 7.28% of them served local residents.A comparison with the use of historic buildings in 2000 and 2002 in Lijiang reveals that commercial units have been increasing rapidly. Tourism plays a key role in this process. As a result, tourism commercialization has taken place in Lijiang. The same case is also true for Zhouzhuang.
Forensic Analysis of Cryptojacking in Host-Based Docker Containers Using Honeypots

Blockchain-based cryptocurrencies have transformed financial transactions and created opportunities to profit from generating new coins through cryptomining. This has led to cybercriminals stealthily using their victim's computational power and resources for their own profit. Recent trends point to an increase in cryptojacking malware targeting devices with greater processing power such as host-based docker engines for faster and greater profit. In our study, we perform a forensic analysis for detecting cryptojacking (i.e., unauthorized cryptomining) in Docker containers using honeypots. Then, we present countermeasures for securing host-based Docker containers. In addition, we propose an approach for monitoring host-based Docker containers for cryptojacking detection. To the best of our knowledge, this is the first study investigating cryptojacking detection with the use of a honeypot system. Our results reveal that host resource usage and network traffic are the key indicators of possible unauthorized cryptomining in Docker containers.
Proximate Compositions Evaluation and Variabilityamong CultivarsofDate Palm (Phoenix dactyliferaL.) in Nigeria

Genetic variability among the fruits of 22 date palm cultivars was studied using 6 nutritional characters to enable us classify the available germplasm into distinct groups on the basis of their genetic diversity using their nutritional characteristics from proximate composition. The main date palm-growing areas of Nigeria were surveyed in 2011 with the objective of characterizing cultivars as to the quality and economic value of their fruits. Descriptive statistics and some multivariate analysis techniques were used to classify the 22 date palmcultivars. The genotypesbased on studied traitswere grouped intothree clusters.Discriminant function analysis was used to confirm the accuracy of grouping that was produced by cluster analysis. Sugar and crude protein content were identified as important traits that could be used to differentiate the genotypes as rev ealed by both principal component and discriminant analysis. Genetic distance between Daushenga 1 and Saberari 2 exhibited the greatest dissimilarity followed by Daushenga 1 and Hausawa. Hence the use of these parents for hybridization should be given grea ter emphasis for the production of transgressive segregants with high nutritional potential. The level of variability observed suggested a high diversity among the cultivars. The result
A Robust Iterative Method for Wideband DoA Estimation with a Uniform Circular Array

Wideband direction-of-arrival (DoA) estimation is desirable with the ever-increasing data rate in wireless communication systems. In this paper, an iterative coherent signal-subspace method for wideband two-dimensional DoA estimation with a uniform circular array is proposed, which includes three steps in each iteration. The first step selects a subset of frequency points for the subsequent focusing process to avoid unnecessary complexity. The second step realizes the focusing process, where the angle intervals for generating focusing matrices with robust-ness are designed, and then the signal-subspaces at the selected frequency points are focused into a reference frequency. The third step estimates DoAs with the multiple signal classification (MUSIC) algorithm where the range of MUSIC spatial spectrum is constrained by the aforementioned angle intervals, thereby further reducing the complexity. The key parameters of the proposed method in the current iteration are adjusted based on the previous estimation results. The simulation results show that the proposed method enjoys better performance and implementation efficiency when compared with benchmark methods.
Alleviation of Cadmium Toxicity in Thai Rice Cultivar (PSL2) Using Biofertilizer Containing Indigenous Cadmium-Resistant Microbial Consortia

Biofertilizer as an amendment has growing awareness. Little attention has been paid to bioremediation potential of indigenous heavy-metal-resistant microbes, especially when isolated from long-term polluted soil, as a bioinoculant in biofertilizers. Biofertilizers are a type of versatile nutrient provider and soil conditioner that is cost-competitive and highly efficient with nondisruptive detoxifying capability. Herein, we investigated the effect of biofertilizers containing indigenous cadmium (Cd)-resistant microbial consortia on rice growth and physiological response. The Thai rice cultivar PSL2 (Oryza sativa L.) was grown in Cd-enriched soils amended with 3% biofertilizer. The composition of the biofertilizers’ bacterial community at different taxonomic levels was explored using 16S rRNA gene Illumina MiSeq sequencing. Upon Cd stress, the test biofertilizer had maximum mitigating effects as shown by modulating photosynthetic pigment, MDA and proline content and enzymatic antioxidants, thereby allowing increased shoot and root biomass (46% and 53%, respectively) and reduced grain Cd content, as compared to the control. These phenomena might be attributed to increased soil pH and organic matter, as well as enriched beneficial detoxifiers, i.e., Bacteroidetes, Firmicutes and Proteobacteria, in the biofertilizers. The test biofertilizer was effective in alleviating Cd stress by improving soil biophysicochemical traits to limit Cd bioavailability, along with adjusting physiological traits such as antioxidative defense. This study first demonstrated that incorporating biofertilizer derived from indigenous Cd-resistant microbes could restrict Cd contents and consequently enhance plant growth and tolerance in polluted soil.
Joint Beamforming Design for STAR-RIS-Aided MU-MIMO System with SWIPT

This paper investigates the resource allocation problem in a simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) aided simultaneous wireless information and power transfer (SWIPT) system. Specifically, the considered system is motivated by the smart interference management of STAR-RIS with extended coverage capability and energy-efficient communication for the information receivers and intelligent power transfer to energy receivers present in private industry networks. We focus on the problem of power minimization for the STAR-aided SWIPT system via a joint beamforming design at the BS and STAR-RIS while guaranteeing the minimum QoS for SWIPT. To solve the formulated problem, we first transform the problem into a simplified form and later propose an alternating optimization framework to solve the problems of beamforming design at BS and STAR-RIS independently and iteratively. Simulation results confirm that STAR-RIS can significantly reduce the required transmission power approximately by 15-20% when compared to conventional RIS while satisfying given QoS constraints for SWIPT systems.
Modeling vulnerability of protected areas to invasion by chromolaena odorata under current and future climates

Invasive plant species and climate change are among the biggest threats to the ecological integrity of many ecosystems, including those of protected areas. Effective management of invasive plants requires information regarding their spatial distributions. Using maximum entropy, we modeled habitat suitability for an invasive plant species Chromolaena odorata under current and future climatic conditions (HadGEM2‐ES and MIROC5) in protected areas of four West African countries (Benin, Côte d'Ivoire, Ghana, and Togo). Under current climatic conditions, approximately 73% of total land area within the protected areas was suitable for colonization by C. odorata. Under future climate projections, the total area of suitable habitats for this invasive plant was projected to decrease by 7–9% (HadGEM2‐ES) and 12–14% (MIROC5). Country‐specific patterns suggest that major protected areas in Côte d'Ivoire and Ghana will be more vulnerable to invasion by C. odorata than those in Benin and Togo under both current and future climatic scenarios. To maintain normal ecosystem functioning and provisioning of ecosystem services within the protected areas studied here, locations that have been identified as most vulnerable to invasion by C. odorata should be accorded proportionately higher priority when formulating appropriate management strategies.
The Performance Analysis of Convolutional Neural Networks and Vision Transformers in the Classification of Sperm Morphology

The problem of infertility around the world is becoming more severe day by day. About half of the problem incidence is male-related. Computer Aided Sperm Analysis systems, accompanied by the usage of artificial intelligence, have been recently developed to measure the sperm quality. In particular, convolutional neural networks (CNNs) are one of the most widely used method for classifying sperm cells. Another method that has become popular in recent years and has started to be used in image classification problems is the vision transformer (ViT) models. In the proposed study, a comparative performance analysis of CNN and ViT architectures on open source HuSHeM, SMIDS and SCIAN human sperm cell image datasets was performed. The results obtained from 8 models, including 5 different traditional CNN architectures and 3 different variants of ViT models, were compared with each other. After 5-fold cross validation and data augmentation, the models were trained and the results were obtained. The results obtained were validated with t-test and the performance analysis was performed. Each model was compared with 7 different models on 3 different datasets for a total of 21 comparisons. As a result of the comparisons, 12 wins, 9 draws and 0 defeats were obtained with the ViT-L16 model. When comparing win rates, it has about %38 more win rates than its closest model.
Hybrid Spin-Orbit Torque/Spin-Transfer Torque-Based Multibit Cell for Area-Efficient Magnetic Random Access Memory

Spin-orbit torque (SOT) devices for magnetic random access memory (MRAM) are promising due to their higher endurance, faster switching speed, and higher energy efficiency compared to the spin-transfer torque (STT) devices. However, the SOT-MRAM’s areal density is approximately half that of STT-MRAM, thereby mitigating its advantage. In this study, we propose a hybrid SOT–STT-based MRAM cell design that combines the favorable features of both the STT and the SOT devices. The hybrid SOT–STT memory cell integrates two bits within a single memory device, employing both STT and SOT mechanisms to write information in the two bits. Notably, the hybrid SOT–STT memory cell achieves twice the areal density of the SOT memory cells. Furthermore, it demonstrates approximately three times lower write energy and is 2.7 times faster compared to the STT-MRAM devices. By leveraging the desirable characteristics of SOT and STT memory, the hybrid memory design enables high-density and energy-efficient nonvolatile spin memory.
ASTER Global Digital Elevation Model Version 2 - summary of validation results

NASA and the Ministry of Economy, Trade and Industry (METI) of Japan released a Global Digital Elevation Model (GDEM) to users worldwide at no charge as a contribution to the Global Earth Observing System of Systems (GEOSS). This " version 1 " ASTER GDEM (GDEM1) was compiled from over 1.2 million scene-based DEMs covering land surfaces between 83°N and 83°S latitudes. A joint U.S.-Japan validation team assessed the accuracy of the GDEM1, augmented by a team of 20 cooperators. The GDEM1 was found to have an overall accuracy of around 20 meters at the 95% confidence level. The team also noted several artifacts associated with poor stereo coverage at high latitudes, cloud contamination, water masking issues and the stacking process used to produce the GDEM1 from individual scene-based DEMs (ASTER GDEM Validation Team, 2009). Two independent horizontal resolution studies estimated the effective spatial resolution of the GDEM1 to be on the order of 120 meters. A second version of the ASTER GDEM (GDEM2) is scheduled for release by NASA and METI in mid-October, 2011. Improvements in the GDEM2 result from acquiring 260,000 additional scenes to improve coverage, a smaller correlation kernel to yield higher spatial resolution, and improved water masking. As with the GDEM1, the GDEM2 validation was performed by the U.S. and Japanese partners. Vertical accuracy assessments included a comparison of the GDEM2 against absolute geodetic references over the Conterminous US (CONUS), against national elevation grids over the US and Japan, against the Shuttle Radar Topography Mission (SRTM) 1 arc-second elevation grids over the US and 20 sites around the globe, and against space borne laser altimeter data globally. Horizontal accuracy assessments were conducted as part of the Japan and the global SRTM studies, and horizontal resolution studies were conducted in both Japan and the US. Each group documented changes in artifacts in GDEM2 due to processing improvements. The absolute vertical accuracy study found the GDEM2 to be within-0.20 meters on average when compared against 18,000 geodetic control points over the CONUS, with an accuracy of 17 meters at the 95% confidence level. The Japan study noted the GDEM2 differed from the 10-meter national elevation grid by-0.7 meters over bare areas, and by 7.4 meters over forested areas. Similarly, the CONUS study noted the GDEM2 to be about 8 meters above the 1 arc-second NED over most forested areas, and more than a meter below NED over bare areas. …
A novel ground electromagnetic system

A novel, moving‐source, ground electromagnetic system has been developed. The system, named the “Genie,” has been in routine field use since 1982. The system is based on measurement of the ratio of magnetic field amplitude at two widely separated frequencies. The design is presented and compared with traditional horizontal loop electromagnetic (HLEM) systems. Field survey results show the system is effective in detecting conductors at shallow to intermediate depths in resistive environments. The system is shown to be roughly equivalent in many aspects to conventional HLEM systems with important advantages in areas of moderate to rough terrain.
Do you really want to speak? Antecedent of Voice Behavior in Organization

Background: Voice behavior refers to the behavior that proactively communicates ideas, suggestions, attention, and information about organizational-related issues to promote organizational effectiveness. Employees are often reluctant to voice their thoughts out of fear of negative consequences, such as a threat to their career position and status quo. Study aims: To describe the factors influencing employees to voice their opinions. Method: 151 employees from various organizations voluntarily agreed to participate in this study (Xage=30.42, SDage: 7,683, Ma= 43.7%; F=56.3%) by filling out an open questionnaire on voice behavior. Data analysis was performed using NVivo 12 Plus. Result: Thematic analysis showed that four factors were evident: motivation, organization, individual, and situational. They served as inhibiting and supporting factors for voice behavior. Conclusion: There are four factors that motivate or inhibit employee voice behavior: motivational, organizational, situational, and personal. Aside from personal factors such as self-confidence and fear, the findings suggest that supervisors, workload, and opportunity can also both motivate and inhibit employees' voice behavior.
USO DELL'HABITAT NEL FRINGUELLO ALPINO Montifringilla nivalis IN PERIODO RIPRODUTTIVO IN UN'AREA SUB-ANTROPIZZATA: CAMPO IMPERATORE (GRAN SASSO - ABRUZZO)

(1) Corpo Forestale dello Stato Ufficio territoriale per la biodiversità di L’Aquila, Via delle Fratte snc – 67100 L’Aquila (2) Dipartimento di Scienze Ambientali Università degli Studi di L’Aquila, Via Vetoio Coppito – 67100 L’Aquila (3) Riserva Naturale Regionale Gole Sagittario, Piazza Roma 10 – 67030 Anversa Degli Abruzzi. (4) (S.O.A.) Stazione Ornitologica Abruzzese, c/o Museo Naturalistico De Leone C. da Collalto – 65017 Penne.