Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the Link between Competitiveness and Innovation

Competitiveness is one of the most complex and controversial areas among economists. The literature on the subject is vast, but the more one studies competitiveness, the more one can become aware of the contradictions, debates and different views on the subject. There is, of course, an explanation for all this. Competitiveness can be analysed in relation to all economic actors, whether national, regional, industrial, corporate or individual. In addition, the market in which an economic operator operates and the factors that actually contribute to its performance are not entirely irrelevant. It can be said that even firms within the same industry may not have the same competitiveness factors. Competitiveness means slightly different things to different people, and we do not always find the same opinions on the sources of competitiveness. This paper does not set out to undertake the impossible task of providing a broad interpretation of the concept and levels of competitiveness. Instead, it attempts to relate innovation as a competitiveness factor to the evolution of competitiveness over time. It does so by focusing on competitiveness in the national economy. The study argues that innovation is one of the most important pillars of competitiveness and that countries considered to be more innovative are much higher in the competitiveness rankings, also primarily because of their conscious investment in knowledge or innovation. To prove this, use international multidimensional innovation and competitiveness analyses carried out by the European Commission or by the best-known competitiveness research centres. And it will use the literature review to find further evidence of the positive interaction between competitiveness and innovation.
Lightweight Protective Clothing Detection Algorithm Based on Ghost Convolution and GSConv Convolution

GhostNet is proposed by Huawei Noah’s Ark Laboratory in CVPR2020, which can be used with the same accuracy, with less speed and less computation than SOTA method. This convolution is a low-cost operation used to decrease the amount of computation and related parameters. Ghost convolution can be used as an alternative to traditional convolution operations because they have the same accuracy. However, utilize significantly less computation and a much smaller parameter count. GSConv(Group-Shared Convolution) is a convolution operation based on group shared weights. This operation achieves efficient parallel convolution operations by grouping convolution kernels. In this way, the parameters used and calculation complexity of the model can be reduced to some extent. This makes the network more computationally efficient and smaller in model size while maintaining accuracy. The algorithm can detect the location of protective clothing quickly and efficiently, and its accuracy and efficiency have been verified. Because the algorithm adopts lightweight network structure, real-time detection can be realized on lowpower devices efficiently. The model architecture enhances the performance based on the YOLOv5 target detection algorithm by incorporating additional features. So that the model can maintain a high precision, which is crucial for the protective clothing detection algorithm.
Databases for Digital Infrastructure of Small Modular Reactors Considering Dynamic Subject Area

The paper analyses the digital infrastructure (DIS) of small modular reactors (SMRs), their main systems (Instrumentation and Control Systems of SMR, Supervision Information and Control System, System of Exchanging and Processing Information of Crisis Center, System of Physical Security and Protection, System of Radiation Control, UAV Fleet Control System, System of Consumption Management), and requirements to databases as a part of the DIS. It describes methods of forming dynamic subject areas (DSA) considering the specific features of SMR DIS. The results of DSA analysis and suggestions for developing an integrative database for SMR are presented.
Exploring Large Language Models for Low-Resource IT Information Extraction

Information Extraction (IE) in IT is an important foundational task that is needed for many AIOps applications. A major challenge of IE in IT is that we often do not have sufficient labelled data for training machine learning algorithms since acquiring labels is labor-intensive and costly. In this paper, we propose to leverage Large Language Models (LLMs) to address this challenge of low resources and study two data augmentation strategies, i.e., using LLMs to generate pseudo labels and generate synthetic data. We use multiple IE tasks and datasets, including a new Semantic Troubleshooting-Segment Extraction task and Named Entity Recognition, to evaluate the benefits of LLMs. Our experiment results suggest that data augmentation using LLMs, specifically, using SeqMix model that combines active labeling with synthetic data samples generated in the embedding-vector space, is a promising approach for IT domain IE. Our study also shows that although data augmentation and direct labeling with the state-of-the-art, ChatGPT model achieves a high performance on general domain IE, there is a need to adapt it for IE from IT text data. Moreover, our initial exploration of two label weighting and selection strategies (confidence and consistency-based) suggests that they could be used to improve data augmentation with ChatGPT for IT domain IE. Finally, we also suggest directions for future research on the new STSE task, including developing better evaluation metrics. 1
Air Quality Index Prediction Based on CNN-LSTM-Attention Hybrid Modeling

Air Quality Index (AQI) is an important indicator for determining good or bad air quality. The accurate and efficient prediction of AQI plays a positive role in promoting the management of air pollution. However, current algorithms for predicting AQI usually do not comprehensively consider the effects of pollutant factors and meteorological factors on the prediction performance. Therefore, taking pollutant factors and meteorological factors as the basis of the model study, a CNNLSTM-Attention hybrid model is proposed. The CNN-LSTM module is used to obtain the air quality-related features, and the attention mechanism is introduced to weigh and sum the output of the LSTM in order to obtain the final attention-weighted features. The results show that the model has better performance than the single model for the prediction of the air quality index.
Bidirectional Radio Over Fiber with Millimeter Wave to Support 5G Fronthaul Network

The cellular network continues to grow due to the increasing needs of users. Recently, the 5G network has offered not only higher capacity mobile broadband known as Enhanced Mobile Broadband (eMBB) but also Massive Machine-Type Communications (mMTC) and Ultra-Reliable and Low Latency Communication (uRLLC). These promising applications require high data transfer, especially in fronthaul networks, to support radio access to users. The millimeter wave-based bidirectional Radio over Fiber (RoF) technology is prospective for 5G fronthaul due to its reliable link performance. However, dispersion has become an issue in obtaining an optimum performance in desired distances. This research designs a bidirectional radio over fiber system and studies a dispersion compensating fiber (DCF) optimization. The system is analyzed with Bit Error Rate (BER) and Q Factor parameters by varying distances and bit rates. The bidirectional Radio over Fiber system achieves the standard at 1-2 km with a peak bit rate of 16 Gbps for the downstream scheme, while the upstream scheme achieves the standard at 1-4 km with a peak bit rate of 16 Gbps. Moreover, the bidirectional Radio over Fiber system with DCF shows a 150% increase in signal quality for the downstream scheme and a 140% increase for the upstream scheme by meeting the standards at 1-15 km with a peak bit rate of 16 Gbps.
An Experimental and Theoretical Investigation on the Micro Drilling of PMMA Samples

Laser drilling on Poly Methyl Methacrylate (PMMA) samples has several uses in a variety of industries including sensors, microelectronics and medical devices. A continuous CO2 laser is utilized for micro-drilling PMMA samples. The design of experiments using Box Behnken Design (BBD) were applied to examine the impact of laser factors, such as power, exposure time, and focal plane position on the micro-drilling process to analyze the results using the statistical technique (ANOVA). Simulation of the drilling mechanism's temperature distribution was achieved by the COMSOL multi-physics software to conduct virtual experiments. This simulation accuracy was fit to predict the holes' geometry and offered results that favorably match with the experimental outputs. The numerical optimization was used to predict the ideal hole quality, whereby the ideal hole for PMMA sheet resulted is a full hole of 1mm, with a suitable diameter of 360µm, and a small HAZ of 60 µm.
Modeling Invasive Aspergillosis Risk for the Application of Prophylaxis Strategies

Abstract The epidemiology of invasive aspergillosis (IA) is evolving. To define the patient groups who will most likely benefit from primary or secondary Aspergillus prophylaxis, particularly those whose medical conditions and IA risk change over time, it is helpful to depict patient populations and their risk periods in a temporal visual model. The Sankey approach provides a dynamic figure to understand the risk of IA for various patient populations. While the figure depicted within this article is static, an internet-based version could provide pop-up highlights of any given flow's origin and destination nodes. A future version could highlight links to publications that support the color-coded incidence rates or other actionable items, such as bundles of applicable pharmacologic or non-pharmacologic interventions. The figure, as part of the upcoming Infectious Diseases Society of America's aspergillosis clinical practice guidelines, can guide decision-making in clinical settings.
A Robot Hand for Versatile Grasping With Tendon-Driven Telescopic Fingers

Service robots need robot hands that are versatile to grasp various objects while being lightweight to ensure robot mobility, minimize power consumption, and prioritize safety. In this paper, we propose a robot hand capable of adjusting the length of its fingers using a tendon-driven telescopic mechanism to accommodate objects of different sizes. The telescopic mechanism utilizes embedded wires to extend actively and an external silicone rubber glove to contract passively. The initial length of the fingers is set at 81.5 mm, with a maximum length of 141.5 mm, resulting in an elongation rate of 73.6%. The bending mechanism of the finger, which is independent from the telescopic mechanism, is realized with wires for active flexion and torsion springs for passive extension. Underactuated bending of the three finger joints is incorporated to conform to object shapes. The implemented robot hand with 3 fingers weighed only 230 g including 2 motors for telescopic extension and finger flexion. To evaluate the effectiveness of the telescopic robot hand, a two-way pull-out experiment was conducted using cylindrical objects of seven different sizes. The results demonstrated that adjusting finger length according to the objects improves grasping stability. The grasping experiments with daily objects indicated that the robot hand with telescopic fingers can stably grasp most of the objects used in daily life.
La campagne KARUBAR en Indonésie, au large des îles Kai et Tanimbar

Despite a long-established scientific reputation as a hotspot of marine species richness, the seas of Indonesia remain Hni. HH"? "̂ " in terms of their deep-sea fauna. Since the landmark "Siboga" expedition a century ago, comparatively mtle additional deep-sea exploration has been carried out in the archipelago. A remarkable exception was the Danish T^MnPxPMc. u conducted in 1922 by an equally remarkable man. Professor
Caractérisation géochimique des oxydes de FE-TI dans un dépôt de FE-TI-P associé à la suite anorthositique du Lac-Saint-Jean, Québec, Canada secteur Lac à Paul et intégration des données du secteur Lac à la Mine

Dans les intrusions litees, la caracterisation geochimique des oxydes de Fe-Ti marque l’evolution du magma en regard sur la stratigraphie (Barnes 2004, Meric 2010). L’analyse par ablation laser jumele avec le ICP-MS sur des echantillons provenant du secteur du Lac a Paul (Fredette 2006) correspondant a un depot d’oxyde Fe-Ti-P associe a la suite anorthositique du Lac-St-Jean (SALSJ), a permis de determiner les differences et les similitudes avec les intrusions litees. Pour ce faire, des analyses, par LA-ICP-MS, ont ete effectuees sur la magnetite, l’ilmenite et le spinelle de 10 echantillons (3 oxydes de Fe-Ti massif, 2 dunites riche en Fe-Ti, 3 peridotites nelsonitiques et 2 troctolites). Un bilan de masse a determine que, pour la SALSJ, l’olivine controle Mg, Mn, Co et Ni, le plagioclase controle Al et Ga, les pyroxenes controlent Sc, Ni, V et Cr, l’ilmenite controle Ti, Nb et Ta et finalement Y, Mo, Zr et Hf sont compris dans des phases accessoires. Parmi les oxydes de Fe-Ti, c’est l’ilmenite que controle la majorite des elements traces. A l’interieur de ce meme secteur, on ne note pratiquement aucune variation de concentration des elements traces dans les unites petrographiques a l’exception de Zr, Hf, Ni et Cr. Pour Zr et Hf, ils sont relies a la quantite de zircons presents dans la roche total. Pour Cr et Ni, la variation est probablement causee par la presence de pyroxene. Selon le bilan de masse, seul le Ta et Nb est present dans une seule phase minerale (l’ilmenite), et ce, dans toutes les lithologies. Le comportement de ces elements ne montre pas de distinction entre les unites petrographiques. La comparaison avec un autre secteur anorthositique, Lac a La Mine, a ete effectuee. Les spectres pour les elements traces dans la magnetite concordent parfaitement. La comparaison avec une intrusion litee, le Bushveld, a aussi ete effectuee. Globalement, pour les elements qui sont controles par l’ilmenite, on observe un appauvrissement des elements traces dans la magnetite de l’anorthosite comparativement a celles des intrusions litees. Ce comportement peut etre explique par 1) l’ilmenite qui aurait cristallise avant la magnetite, ce qui laisse moins d’elements dans le liquide residuel pour la magnetite ou 2) l’ilmenite est exsolvee de la magnetite pour former des grains et ainsi appauvrir les magnetites. Au final, ce present projet montre que le comportement des elements traces dans les oxydes de Fe-Ti de l’anorthosite n’est pas similaire qu’a celui dans les intrusions litees. De plus, il n’est pas possible d’observer une evolution du magma a l’aide des elements traces suggerant que la cristallisation fractionnee n’est pas le processus le plus important. De plus, une classification pour la geologie d’exploration a ete determinee permettant de distinguer les anorthosites avec les intrusions litees.
Lnc-CLSTN2-1:1 Promotes Osteosarcoma Progression by Disrupting Redox Balance through PI3K/AKT Signaling Pathway

Objective: Most patients with osteosarcoma (OS) have an extremely poor prognosis. The primary purpose of this investigation was to explore the biological effect of Lnc-CLSTN2-1:1 on OS and the potential processes involved. Materials and procedures: We selected differentially overexpressed Lnc-CLSTN2-1:1 from our laboratory's existing RNA sequence analysis data (fibroblast osteoblast (hFOB 1.19) and three osteosarcoma cell lines (HOS, MG63, and U2OS) as the research object. Next, we detected Lnc-CLSTN2-1:1 in the osteosarcoma HOS cell line and fibroblast cells using qRT-PCR. We evaluated cell proliferation ability using EdU incorporation test, CCK-8 test, and cell clone formation; cell invasion and migration were assessed using the Transwell test, while flow cytometry examined cell cycle, apoptosis, and reactive oxygen species (ROS); Subsequently, the activity changes of selenase (GPx) glutathione peroxidase and (TrxR) thioredoxin reductase were detected. In addition, changes in related proteins were analyzed through Western blotting. Results: The expression of Lnc-CLSTN2-1:1 in osteosarcoma cells was significantly increased. The proliferation, invasion, and migration of osteosarcoma cells were significantly inhibited by knockdown of the expression of Lnc-CLSTN2-1:1, and the cell cycle-related signaling pathway PI3K/AKT/GSK-3β/cycinD1 was also inhibited. However, insulin-like growth factor-1 (igf-1) could reverse this process. In addition, we examined the activity of two selenophenases (TrxR and GPx) and the changes of ROS before and after Lnc-CLSTN2-1:1 knockdown. The results showed that both TrxR and GPx activities were reduced after Lnc-CLSTN2-1:1 knockdown, resulting in the inhibition of antioxidant stress levels, while intracellular ROS levels were high, which eventually caused killing effects on tumor cells due to the imbalance between oxidative stress and antioxidant stress. Conclusion: Our results showed that Lnc-CLSTN2-1:1 enhanced anti-oxidative stress TrxR and GPx selenoprotein activities through the PI3K/AKT signaling pathway while counteracting the loss of reactive oxygen species ROS produced by mitochondria to osteosarcoma cells, which protected osteosarcoma cells and thus promoted the proliferation and metastatic ability of OS.
A Novel VLC Channel Model Based on Beam Steering Considering the Impact of Obstacle

In this letter, a novel channel model of a visible light communication (VLC) system was proposed with the impact of position, size, and shape of the obstacle taken into account. The illumination area of the light-emitting diode (LED) was divided into independent solid angles and the ray was transmitted in every solid angle by beam steering; then, the point cloud of the obstacle was determined by the received rays in photodetector (PD). Furthermore, the convex hull model was used to represent the point cloud for simplification, the complex VLC channel model was set up, and the expression of the channel impulse response (CIR) was derived. Five scenarios with different obstacles were simulated for analysis, and the results revealed that the position, shape, and size of the obstacle have deep impact on the channel characteristics of the VLC system. Besides, beam steering increased the uniformity of the signal-to-noise ratio (SNR) distribution and the available bandwidth. Monte Carlo (MC) simulation was also provided to confirm the correctness of the proposed channel model.
Development of CGA-PWW Devices Based on Advanced Wafer-Level Processing Technology

This letter presents a novel air-filled post-wall waveguide (PWW) in an advanced wafer-level planting process for millimeter-wave applications. This PWW, consisting of two metal plates and numerous regular copper columns, is implemented by an improved column grid array (CGA) bonding process with a high alignment accuracy of less than $50~\mu \text{m}$ . Since air is the only transmission medium, the CGA-PWW has a low-loss advantage over the traditional dielectric-filled substrate-integrated waveguide. For demonstration, the prototype CGA-PWW transmission lines with a standard waveguide transition are designed and fabricated by adopting the 8-inch wafer-level processing technology. An extremely low transmission loss of 0.0032 dB/mm is achieved in the entire V-band. A good agreement between the measured and simulated results verifies the process’s stability. Moreover, introducing the redistribution layer technology and the multilayer stacking process could significantly enhance the external integration capabilities. Hence, the CGA-PWW solution is appropriate for millimeter-wave radio-frequency components and system integrations.
Rapid Assessment of Tree Debris Following Urban Forest Ice Storms

This paper presents a rapid assessment method to estimate urban tree debris following an ice storm. Data were collected from 60 communities to quantify tree debris volumes, mostly from public rights-of-way, following ice storms based on community infrastructure, weather parameters, and urban forest structure. Ice thickness, area of a community, and street distance are significant predictors for estimating debris from ice storms. Results from this study provide a way to estimate woody debris volumes from urban trees immediately following an ice storm. The model can also be used to predict debris volumes for storm preparedness planning.
MazEF Homologs in Symbiobacterium thermophilum Exhibit Cross-Neutralization with Non-Cognate MazEFs

Toxin–antitoxin systems are preserved by nearly every prokaryote. The type II toxin MazF acts as a sequence-specific endoribonuclease, cleaving ribonucleotides at specific sequences that vary from three to seven bases, as has been reported in different host organisms to date. The present study characterized the MazEF module (MazEF-sth) conserved in the Symbiobacterium thermophilum IAM14863 strain, a Gram-negative syntrophic bacterium that can be supported by co-culture with multiple bacteria, including Bacillus subtilis. Based on a method combining massive parallel sequencing and the fluorometric assay, MazF-sth was determined to cleave ribonucleotides at the UACAUA motif, which is markedly similar to the motifs recognized by MazF from B. subtilis (MazF-bs), and by several MazFs from Gram-positive bacteria. MazF-sth, with mutations at conserved amino acid residues Arg29 and Thr52, lost most ribonuclease activity, indicating that these residues that are crucial for MazF-bs also play significant roles in MazF-sth catalysis. Further, cross-neutralization between MazF-sth and the non-cognate MazE-bs was discovered, and herein, the neutralization mechanism is discussed based on a protein-structure simulation via AlphaFold2 and multiple sequence alignment. The conflict between the high homology shared by these MazF amino acid sequences and the few genetic correlations among their host organisms may provide evidence of horizontal gene transfer.
Cloud Computing Education Laboratory Safety Research

Education laboratory cloud platform has many characteristics, such as access nodes, small regional, and sudden access more, sometimes the need for experimental project needs to transfer the storage and computing resources are not fixed; The safety protection of reason for cloud platform put forward higher requirements. For education laboratory cloud platform carries the characteristics of the business, and the characteristics of the calculation, the security module of the platform, make it effective defense network attack and the risk of systemic paralysis.
Closed-form Bayesian image denoising: improving the adaptive Wiener filter through pairwise Gaussian-Markov random fields

Abstract In this paper, we propose a contextual adaptive Wiener filter by using an isotropic pairwise Gaussian Markov random field (GMRF) prior to model the spatial correlation existing in natural images. The motivation for the development of the proposed method is that, in the context of Bayesian estimation, the Wiener filter is known to be the optimal estimator under Gaussian noise. The resulting closed-form filter can be viewed as a two-stage denoising process in which the first stage considers independent pixels whereas the second stage incorporates a degree of spatial dependence by means of maximum pseudo-likelihood estimation of the coupling parameter. The obtained results show that the proposed method outperforms the classical pointwise Wiener filter, in some cases reaching results comparable to some state-of-the-art methods in denoising, but with a reduced computational cost.