Miracle-dz/UniFAR-FTUs huggingface dataset:
Weighted ensemble dynamics simulations for detecting metastable states

Based on multiple short simulation trajectories started from dispersively selected initial conformations, the weighted ensemble dynamics (WED) method [Phys Rev. E,80, 026707 (2009)] has been designed to explore the hierarchical state structure in conformational space. In this article, we have further improved the WED method. Several schemes have been designed respectively for reducing the statistical error, systematically selecting the physical variables in analysis and determining the only adjustable parameter of WED. Besides, we illustrate the application of WED in more complicated examples, including a system with transition network between multiple states, a system with entropy-dominated state, and the low-temperature simulation of solvated alanine dipeptide. WED is found to correctly capture the topology of the transition networks of the model systems. It can also identify the solvent effect for the solvated alanine dipeptide system, as well as the diffusion-like dynamical behavior both for the entropy-dominated system and the low-temperature simulation of solvated alanine dipeptide. These examples will serve as the references for the application of WED to more complicated biological macromolecules.
Impact of Enabling Environment Drivers on Public-Private Partnership investment in the Transport Sector

The research aims to analyze the impact of some drivers of the enabling environment, represented by the macroeconomic stability index (GDP, inflation, foreign exchange reserves and the ratio of debt reserves to short-term foreign exchange). And the financial market stability index (the amount of credit provided to private sectors, value of shares traded) on public-private partnerships in financing infrastructure in the transport sector for selected countries. The drivers of the enabling environment in general are considered one of the main pillars in the process of partnership between the public and private sectors. And the tangible results of the partnership between the public and private sectors that affect the daily lives of individuals have a clear impact on the economic construction of countries that seek advancement and development in all directions. On the other hand, there is an urgent need to increase the volume of financing infrastructure projects, as a result of the widening gap between the demand for infrastructure and the shortfall in the volume of supply that corresponds to it. Which requires the public sector to move towards partnership with the private sector, which has capabilities and efficiency in implementation and management. The research adopted the ARDL model to perform the regression, using longitudinal data for a group of selected countries (Brazil, Colombia, India, Mexico, Peru, Philippines, China) for the period (2000-2020). It was found that the flexibility of participatory investment in relation to changes in the gross domestic product, the inflation rate, the percentage of credit granted to the private sector, and the value of traded shares was high, while there was no significant effect of foreign exchange reserves and the ratio of short-term debt-to-foreign exchange reserves on investment. Participatory. On the other hand, it was found that the impact of GDP, the percentage of credit granted to the private sector and the value of traded shares were positive, while the effect of inflation was negative.
GLD-Net: Deep Learning to Detect DDoS Attack via Topological and Traffic Feature Fusion

Distributed denial of service (DDoS) attacks are the most common means of cyberattacks against infrastructure, and detection is the first step in combating them. The current DDoS detection mainly uses the improvement or fusion of machine learning and deep learning methods to improve classification performance. However, most classifiers are trained with statistical flow features as input, ignoring topological connection changes. This one-sidedness affects the detection accuracy and cannot provide a basis for the distribution of attack sources for defense deployment. In this study, we propose a topological and flow feature-based deep learning method (GLD-Net), which simultaneously extracts flow and topological features from time-series flow data and exploits graph attention network (GAT) to mine correlations between non-Euclidean features to fuse flow and topological features. The long short-term memory (LSTM) network connected behind GAT obtains the node neighborhood relationship, and the fully connected layer is utilized to achieve feature dimension reduction and traffic type mapping. Experiments on the NSL-KDD2009 and CIC-IDS2017 datasets show that the detection accuracy of the GLD-Net method for two classifications (normal and DDoS flow) and three classifications (normal, fast DDoS flow, and slow DDoS flow) reaches 0.993 and 0.942, respectively. Compared with the existing DDoS attack detection methods, its average improvement is 0.11 and 0.081, respectively. In addition, the correlation coefficient between the detection accuracy of attack flow and the four source distribution indicators ranges from 0.7 to 0.83, which lays a foundation for the inference of attack source distribution. Notably, we are the first to fuse topology and flow features and achieve high-performance DDoS attack intrusion detection through graph-style neural networks. This study has important implications for related research and development of network security systems in other fields.
Extracellular laccase activity among Ganoderma and Coriolopsis species grown on lignocellulosic wastes

The extensive application of laccase in various fields depends on the supply of a large amount of laccase with high activity and low cost. Interest on the screening of fungal strains suitable for obtaining massive high-activity laccase in solid-state fermentation with suitable low-cost lignocellulosic wastes has increased. The present work determined the laccase secretion from different species belonging to genera Ganoderma and Coriolopsis fermented on different lignocellulosic wastes. Maximal laccase activity was obtained from Ganoderma lingzhi Han 1345 grown on rice straw for 9 days and indicated the capacity of secreting laccase of G. lingzhi Han 1345 was superior to that of Coriolopsis trogii Han 1211, C. strumosa Han 1356, and G. applanatum Han 1578. The presence of cottonseed hull was more favorable for Coriolopsis species secreting laccase, while Ganoderma species were more preferred to secrete laccase on rice straw. Further, the consistent substrate preference in laccase production of different species in the same genus was first exhibited. The results are useful to screen and obtain new species with superior capacity of secreting laccase and suitable low-cost lignocellulosic wastes as fermentation substrate for further industrial application of laccase.
Deep Reinforcement Learning for Resource Constrained HLS Scheduling. (c2022)

High-level synthesis (HLS) scheduling, an NP-hard problem, is a process that auto-mates VLSI design and is a very important step in silicon compilation. HLS takes as input a behavioral description of a system with a set of constraints and outputs an RTL description of a digital system. The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. The actions and rewards for the proposed algorithm are selected carefully to guide the agent to its objective. We used a deep neural network to train the agent and in order to learn the the Q-values. The results of this work are compared to other state-of-the-art algorithms and are proven to be very effective and promising.
Current Opportunities for Targeting Dysregulated Neurodevelopmental Signaling Pathways in Glioblastoma

Glioblastoma (GBM) is the most common and highly lethal type of brain tumor, with poor survival despite advances in understanding its complexity. After current standard therapeutic treatment, including tumor resection, radiotherapy and concomitant chemotherapy with temozolomide, the median overall survival of patients with this type of tumor is less than 15 months. Thus, there is an urgent need for new insights into GBM molecular characteristics and progress in targeted therapy in order to improve clinical outcomes. The literature data revealed that a number of different signaling pathways are dysregulated in GBM. In this review, we intended to summarize and discuss current literature data and therapeutic modalities focused on targeting dysregulated signaling pathways in GBM. A better understanding of opportunities for targeting signaling pathways that influences malignant behavior of GBM cells might open the way for the development of novel GBM-targeted therapies.
Inversion tectonics in the Sorgenfrei–Tornquist Zone: insight from new marine seismic data at the Bornholm Gat, SW Baltic Sea

ABSTRACT New seismic profiles located within the Bornholm Gat in the SW Baltic Sea area image Late Cretaceous-Paleogene inversion and exhumation of a previously poorly characterized narrow crustal zone in the southern end of the Sorgenfrei–Tornquist Zone (STZ), a long pre-Alpine tectonic lineament in Europe. Thrusts and pop-up structures developed along the inversion axis accompanied by subsidence troughs on its sides. Stratigraphic analysis of chalk deposits indicates that structural shortening and inversion resulted from compressional deformation. Marginal troughs formed synchronously to inversion and adjacent to the tectonically active slope, where sediment redeposition was focused. Deposition of chalk units, composed predominantly of contourites and gravity-driven sedimentation were largely controlled by inversion tectonics and influenced by intensification of bottom currents. We find that allochthonous chalk has been buried in horizontally deposited autochthonous (pelagic) chalk. An erosional unconformity represents the base of the Maastrichtian and marks the onset of along slope deposition due to a more hydrodynamic environment. The revealed asymmetric inversion across the STZ with fold tightening and superposition of NE-NW folds attest to more than one pulse during the Late Cretaceous-Cenozoic inversion. The STZ may belong to the end-member mode of intraplate foreland basins resulting from a far-field NE-SW compression transmitted from the Africa-Iberia-Europe convergence. The intraplate stress associated with the following Maastrichtian enhanced collisional coupling between the Alpine-Carpathian orogen and its foreland, which is widely recognized (e.g., the Mid-Polish Trough, the Bohemian Massif and the Central Graben), may also have had its maximum extent to the northeast in southern Sweden.
Qualitative Evaluation of the Science Curriculum Applied in Science and Art Centers (SACs) for Gifted Students in Turkey Within the Framework of the CIPP Approach

This study was conducted using a qualitative approach as it aimed to evaluate the Science and Art Center Science Curriculum (SACSC), which was updated in 2020, within the framework of the context, input, process, and product (CIPP) approach by taking the opinions of science teachers working in Science and Art Centers (SACs) in Turkey. The data were collected according to the qualitative data collection method and a structured interview form was used as a data collection tool. The findings showed that science teachers working in SACs have generally negative views on SACSC based on the context dimension of the CIPP Model, while their views are generally positive based on input, process, and product dimensions. Based on the results of the research, it is recommended to conduct other comparative studies between the SACSC and similar curricula in other countries in order to reveal the relationship between the program components and the needs of children and society.
Identification of molecular subtypes in lung adenocarcinoma based on DNA methylation and gene expression profiling—a bioinformatic analysis

Background Molecular typing based on deoxyribonucleic acid (DNA) methylation and gene expression can extend understandings of the molecular mechanisms involved in lung adenocarcinoma (LUAD) and enhance current diagnostic, treatment, and prognosis prediction approaches. Methods Gene expression and DNA methylation data sets of LUAD were obtained from The Cancer Genome Atlas (TCGA), and the differential gene and methylation expression levels were analyzed. Results We successfully divided the LUAD samples into 2 clinically relevant subtypes with significantly different survival times and tumor stages according to the transcriptome and methylation data. We found significant differences in the survival status, age, gender, tumor stage, node stage, and clinical stage between the 2 subtypes. The hub genes identified in the subnetworks, including NCAPG, CCNB1, DLGAP5, HLA-DQA1, HLA-DPA1, HLA-DPB1, SFTP, SCGBA1A, and SFTPD, were correlated with the cell cycle and immune system. The Gene Ontology annotation of the hub genes showed that the biological processes included organelle fission mitotic nuclear division, and sister chromatid segregation. The cellular components included chromosomal region, spindle, and kinetochore. The molecular functions included tubulin-binding, microtubule-binding, and DNA replication origin binding. The Kyoto Encyclopedia of Genes and Genomes signaling pathways related to the hub genes mainly included the cell cycle, human T-cell leukemia virus (type 1) infection, inflammatory bowel disease, and the intestinal immune network for immunoglobulin A production. The clinical stage difference was also confirmed in the validation group using the GSE32863 data set. Conclusions Our findings extend understandings of the pathogenesis of LUAD and can be used to improve current diagnosis, treatment, and prognosis prediction strategies.
In Vivo Evaluation of PCL Vascular Grafts Implanted in Rat Abdominal Aorta

Electrospun tissue-engineered grafts made of biodegradable materials have become a perspective search field in terms of vascular replacement, and more research is required to describe their in vivo transformation. This study aimed to give a detailed observation of hemodynamic and structural properties of electrospun, monolayered poly-ε-caprolactone (PCL) grafts in an in vivo experiment using a rat aorta replacement model at 10, 30, 60 and 90 implantation days. It was shown using ultrasound diagnostic and X-ray tomography that PCL grafts maintain patency throughout the entire follow-up period, without stenosis or thrombosis. Vascular compliance, assessed by the resistance index (RI), remains at the stable level from the 10th to the 90th day. A histological study using hematoxylin-eosin (H&E), von Kossa and Russell–Movat pentachrome staining demonstrated the dynamics of tissue response to the implant. By the 10th day, an endothelial monolayer was forming on the graft luminal surface, followed by the gradual growth and compaction of the neointima up to the 90th day. The intense inflammatory cellular reaction observed on the 10th day in the thickness of the scaffold was changed by the fibroblast and myofibroblast penetration by the 30th day. The cellularity maximum was reached on the 60th day, but by the 90th day the cellularity significantly (p = 0.02) decreased. From the 60th day, in some samples, the calcium phosphate depositions were revealed at the scaffold-neointima interface. Scanning electron microscopy showed that the scaffolds retained their fibrillar structure up to the 90th day. Thus, we have shown that the advantages of PCL scaffolds are excellent endothelialization and good surgical outcome. The disadvantages include their slow biodegradation, ineffective cellularization, and risks for mineralization and intimal hyperplasia.
Ultrafast chaotic switching and monitoring using plasmonic add‐drop multiplexer

In this paper, we propose a plasmonic circuit based on optical add‐drop multiplexer. A stack of silicon–graphene–gold layers is used at optical add‐drop filter ends. The light input from a laser source at the silicon base of the stack enables ultrafast electrical switching by rapid light‐electron energy conversion. It allows feedback signals monitoring by the output mobility visibility, which is useful for system control. Certain results show ultra‐fast switching time of ~5.0 fs at a stable power of 3 mW. The results further demonstrate great avenues for the secured communication channel‐based on the plasmonic electronic circuit.
Experimental and theoretical examination of shock-compressed copper through the fcc to bcc to melt phase transitions

Recent studies show a face-centered cubic (fcc) to body-centered cubic (bcc) transformation along the shock Hugoniot for several metals (i.e., Cu, Au, and Ag). Here, we combine laser-shock compression of Cu foils on nanosecond timescales with in situ x-ray diffraction (XRD) to examine the microstructural changes with stress. We study the fcc phase and the phase transition from fcc to bcc (pressures greater than 180 GPa). Textural analysis of the azimuthal intensities from the XRD images is consistent with transformation into the bcc phase through the Pitsch-distortion mechanism. We use embedded atom model molecular dynamics simulations to determine the stability of the bcc phase in pressure–temperature space. Our results indicate that the bcc phase is stabilized only at high temperatures and remains stable at pressures greater than 500 GPa.
Timing Evaluation of Telecom Investment Decision under Demand Uncertainty

Under uncertain conditions, the problem of selecting investment timing for telecom network optimization and expansion projects is common in the investment practice of telecom operators. By examining the characteristics of the demand and price of the telecommunications industry, combined with historical data of the telecommunications industry, an exponential function relationship of prices meeting demand is proposed, and then an investment timing decision model under the condition of uncertain demand is established on this basis. Studies have shown that when the value of the investment project is 1.5634 times the investment cost, the value of the investment option is the largest, and this is the optimal investment opportunity. The value of the investment opportunity F(V), the value of the project V ∗ , the degree of demand uncertainty σ , and discount rate ρ are positively correlated, and it is negatively correlated with the opportunity cost δ of delaying project investment and keeping investment options alive.
Non-carcinogenic and Carcinogenic Health Risk Evaluation from Fish Contaminated with Heavy Metals

The pollution of water bodies with heavy metals can result into the possible contamination of freshwater fish. The levels of the heavy metals Pb, Fe, Cu, Zn, Ni and Cd were investigated in fish samples (Ameiurus nebulosus, Pylidictis olivaris, Tilapia zilli, Clarias gariepinus) collected from Kwanar-Are dam located at Rimi local government area Katsina State, Nigeria and the health risks of the evaluated heavy metals were estimated. The mean concentration ranges of Pb, Fe, Cu, Zn and Cd were (0.0851-0.4919, 0.3095-0.5039, 0.0366-0.0589, 0.1066-0.3015, 0.1048-0.1417, 0.0128-0.0686 mg/kg) respectively. The risk assessment for non-carcinogenic exposure effect showed that there was no health risk associated with these elements through consumption of the fish samples to the consumer population. However the risk assessment for carcinogenic exposure effect has revealed that the incremental lifetime cancer risk (ILCR) and the cumulative lifetime cancer risks (∑ILCR) were all above the safe limit for cancer in the children and the adults population for all the fish samples evaluated. The heavy metal Ni presented the greatest cancer risk and the fish sample Clarias gariepinus having the highest cancer risk. There is a degree of concern for consumption of the fish samples for their potentials to contribute to the population cancer risk load.
WER-Net: A New Lightweight Wide-Spectrum Encoding and Reconstruction Neural Network Applied to Computational Spectrum

The computational spectrometer has significant potential for portable in situ applications. Encoding and reconstruction are the most critical technical procedures. In encoding, the random mass production and selection method lacks quantitative designs which leads to low encoding efficiency. In reconstruction, traditional spectrum reconstruction algorithms such as matching tracking and gradient descent demonstrate disadvantages like limited accuracy and efficiency. In this paper, we propose a new lightweight convolutional neural network called the wide-spectrum encoding and reconstruction neural network (WER-Net), which includes optical filters, quantitative spectral transmittance encoding, and fast spectral reconstruction of the encoded spectral information. The spectral transmittance curve obtained by WER-net can be fabricated through the inverse design network. The spectrometer developed based on WER-net experimentally demonstrates that it can achieve a 2-nm high resolution. In addition, the spectral transmittance encoding curve trained by WER-Net has also achieved good performance in other spectral reconstruction algorithms.
Comment on “Dirac equation in the background of the Nutku helicoid metric” [J. Math. Phys. 48, 092301 (2007)]

The Dirac equation written on the boundary of the Nutku helicoid space consists of a system of ordinary differential equations. We tried to analyze this system and we found that it has a higher singularity than those of the Heun equations which give the solutions of the Dirac equation in the bulk. We also lose an independent integral of motion on the boundary. This facts explain why we could not find the solution of the system on the boundary in terms of known functions. We make the stability analysis of the helicoid and catenoid cases and end up with an Appendix which gives a new example wherein one encounters a form of the Heun equation.
Aspects of Developmental Pathways toward World-Class Parasport

The developmental pathways of athletes with a physical disability into world-class parasport are much less researched and understood compared to able-bodied athletes’ participation histories. The purpose of this study was to investigate the developmental pathways of para-athletes toward elite performance. Data from eight athletes with physical disabilities ranked among the top performers in Paralympics, World Championships, and/or European Championships were gathered. Thematic analysis of retrospective semi-structured interviews led to the identification of four themes. The findings showed the importance of early childhood sport-related encounters in a family environment followed by sampling of various organized and coach-led sports throughout the childhood period. The youth sport period was highly heterogenous, albeit with important transitions towards elite-level practice environments, competition, coaching, equipment adaptability and the first intentions of becoming an elite-level athlete. Throughout, significant contributions are attributed towards parents, friends, coaches, athletes, and others, towards fostering a sustained motivational climate focused on improvement and further progress. These findings could provide useful information to tailor developmental models towards elite-level performance in parasport.