Miracle-dz/UniFAR-FTUs huggingface dataset:
Regulation of thymidylate synthase gene : effect of E2F and p53 /

Thymidylate synthase (TS) is an essential enzyme and thus an important target for cancer chemotherapeutic drugs. The proper S-phase regulation of the mouse TS gene requires the presence of the TS essential promoter region as well as a spliceable intron and may involve some form of communication between the promoter and the RNA processing machinery. The goal of my research is to further understand the regulatory mechanisms in the control of TS gene during the cell cycle, especially the involvement of E2F and p53 proteins. The sequence elements that are important for the transcription and regulation of the rat TS gene were analyzed. The rat TS promoter lacks a TATA box and directs transcriptional initiation at multiple sites. Promoter deletion analyses showed that the region between -100 and -42 nt relative to the AUG codon was both necessary and sufficient for high level promoter activity and was designated as the essential promoter region. The essential region also had bidirectional promoter activity. Site-directed mutagenesis revealed that four elements were especially important for promoter activity. These include Ets motifs at -85 and -50, an Spl motif at -80 and an LSF motif that overlapped the upstream Ets and Spl motifs. The rat TS promoter directed 8 phase-specific expression of a stably transfected minigene if a spliceable intron was included. If the intron was deleted or the E2F motifs upstream and downstream of the essential promoter region were inactivated, expression of the minigene changed very little during G1/S transition. Inactivation of both E2F elements had no measurable effect on promoter activity in transient transfection assays. E2F may regulate rat TS gene expression by repressing the transcription during G0/G1 phase. Releasing of the repression leads to the upregulation during G1-S transition. The effect of p53 on the expression of the mouse TS gene was studied by transient cotransfection of a luciferase indicator gene that was driven by various modified forms of the mouse TS promoter with a p53 expression plasmid. I found that wild-type p53 inhibited TS promoter activity by greater than 95%. Deletion of sequences upstream or downstream of the TS essential promoter region, or Inactivation of each of the known elements within the essential promoter region had no effect on the ability of wild-type p53 to inhibit TS promoter activity. My observations indicate that p53 inhibits the TS promoter by sequestering ("squelching") one or more general transcription factors. Finally, the expression of the TS gene in various mouse tissues was analyzed. The pattern of initiation sites was nearly identical in all the mouse tissues that were examined, although the amount of TS mRNA varied over a wide range, reflecting differences in cell proliferation rates. Therefore, transcription of the mouse TS gene is directed by a single promoter that is capable of being expressed in a wide variety of cellular environments.
Detangling the multilayer structure from an aggregated network

Multiplex interactions are common and essential in real-world systems. In many cases, we can only obtain aggregated networks without detailed information regarding the type of links contained within. Such single-layer networks oversimplify the structural information and lead to misunderstandings of some properties of real systems. In this context, network splitting which aims to correctly separate an aggregated network into multilayer networks, is a meaningful problem to address. To this end, we propose a simulated-annealing-like algorithm based on the link clustering coefficient. We verify the validity of this algorithm with several synthetic networks. Inter-similarities of layers are also taken into consideration, and we can find that the proposed method is valid even if there is a certain proportion of overlapping links between layers. Finally, we apply the algorithm to real international trading networks, which results in accurate splits of different layers.
Research on the Theory and Application of Deep Interactive Learning

Knowledge distillation (KD), in which a small network (students) is trained to mimic a larger one(teachers), with high precision, has been widely used in various fields. However, the interaction between teachers and students is still weak. It is found in this study that most existing methods, such as Deep Mutual Learning (DML), mainly construct loss function through soft weight indexes. Few researchers pay attention to the sharing of hard and heavy ones. As an improvement of DML, a new online learning distillation method, namely, Deep Interactive Learning (hereinafter DIL), was proposed in this research, which has deeper interaction than DML. We not only output the features of layers, but also disclose the features of hidden layers. We transfer the features to other models to obtain the corresponding softer distribution or features for distillation. Extensive experiments on various data sets show that the accuracy of our method is improved by almost 3% in CIFAR and 2% in ImageNet, which proves the validity of our method.
Single node failure repair method for distributed storage system based on genetic algorithm and MSR code

In view of the minimum storage regeneration (MSR) single fault node repair plan, design a kind of new single repair fault node topology. Consider link bandwidth available and the node processing power of heterogeneity, the repair delay and repair traffic node of combinatorial optimization. Topology can be converted to Steiner tree model with constraints, and design the corresponding hybrid genetic algorithm to solve the approximate global optimal solution. Finally, a compromise between the two optimization objectives is achieved. Simulation results show that under the same MSR code size, the repair delay of this topology is only 60%-80% of that of the traditional tree topology and 30%-40% of that of the traditional star topology. While the repair traffic for this topology is 9% to 65% higher than for the traditional star topology, the repair traffic is only 40% to 55% higher than for the traditional tree topology.
Beach Topographic Change Analysis Using Multi-temporal UAV Data

A time-serial topographic change was performed using two kinds of surveying methods, including direct measurement and indirect remote sensing technology for beach topography surveillance. Compared with reference topographic data, the root mean square error was 0.169 m. From May, 2018 to March, 2019, multi-temporal beach topographic change results indicated that the distance between baseline and shoreline varied in the range of −24.82∼9.58 meter, and weekly variates are −3.16∼0.45 m. The UAV technique can be efficiently used to detect topographic change information in the coastal area.
Research on Energy Saving Distribution in Cloud Computing Environment

With the huge increase of cloud infrastructure and the continuous expansion of cloud computing scale, the consumption promotion role of IT resources has been increasing, which has greatly hindered the development of IT industry. Energy consumption has become an important factor restricting the development of cloud computing. How to reduce energy consumption and improve the efficiency of energy utilization in cloud computing has become a new problem. At present, most of the cloud computing task scheduling algorithms are also carried out in job scheduling, which does not consider the allocation and energy consumption of resources. Therefore, the rational allocation of resources is an effective way to improve the efficiency of energy utilization and energy utilization. In this paper, the concept of resource waiting and resource consumption is proposed. It is considered that resource allocation is an effective way to improve the efficiency of platform software. In this paper, the resource space time energy consumption of intelligent energy is defined. The optimal ratio of known energy consumption to 0 and the resource needed for resource tasks and tasks is called map / task allocation and resource allocation. In this paper, the best resources than W test and wait for the relationship between the specific energy and resource; then, to verify that the map / mountain ice task division rationality by experiment; then the experimental data to verify the R2 algorithm can reduce the energy consumption of resources, improve the utilization rate of node resources, optimizing the energy efficiency of Map/Reduce task. The proposed resource ratio model and resource W method can be applied to existing map reduction system, which is of theoretical significance and practical value for improving and optimizing energy efficiency in cloud computing models.
Biophysical and socio‐economic causes for increasing fallow land in Tamil Nadu

The question of increasing fallow land assumes significance at national and international levels due to the decline in net cultivated area and increasing population. Biophysical characteristics of farmland and socio‐economic conditions of farmers are responsible for the increasing fallow. This study was carried out to assess the extent of permanent fallow and identify causes for its increase. High‐resolution remote sensing data were used to identify fallow land in two identified blocks of south India, viz. Nanguneri and Kangeyam. The land resources were characterized, and the specific biophysical and socio‐economic factors responsible for the increasing fallow land were assessed. Multiple regression analysis was carried out to identify the factors responsible for increasing fallows. Soil parameters such as erosion, soil texture, soil depth and available nitrogen contributed significantly (P > 0.05) to the increase in fallow land. The size of farm holding, number of farm fragments, distance from the road in Nanguneri and farm size and the distance to the nearest town in Kangeyam were socio‐economic factors that had a strong effect (P > 0.01) on increasing the fallow land. Variable importance rankings in random forest analysis indicated that soil erosion and soil pH had the largest impact on the decision to fallow land in Nanguneri and Kangeyam blocks, respectively. Based on biophysical and socio‐economic constraints, the land resources of fallow land were evaluated for other alternate land use options and policy measures were suggested.
Numerical Simulation of Multi-puffing Process of Electronic Atomizer

The thermodynamic behaviors of electronic atomizer during the multi-puffing process have an important influence on the product performances. Exploring the thermodynamic mechanisms behind the vaporization phenomena is helpful for engineers and consumers to understand electronic atomizer. The theoretical modelling and simulation of the multi-puffing process for the electronic atomizer were carried out in this study. During 1∼10 puffing number, the mass fraction of propylene glycol in the residual e-liquid reduced when the puffing number increased. Meanwhile, the mass fraction of vegetable glycerin in the residual e-liquid increased gradually. The total particulate matter of aerosol generated from the electronic atomizer decreased with the puffing number increasing. The maximum vaporization temperatures of the residual e-liquid rose gradually in the multi-puffing process.
Research on breach prediction for big data through hybrid ensemble learning and logistic regression

The fast-growing online lending sector faces the risk of borrowers defaulting. Network lending data are often unbalanced. On the basis of EasyEnsemble algorithm, we proposed a hybrid ensemble algorithm, which combines the advantages of Bagging and Boosting. By comparing the performance of different learning models, the experimental results show that the hybrid ensemble algorithm has good classification accuracy and generalization ability. Further, we find that social capital has a negative effect on borrower default rate. This paper provides a relatively reliable method for the credit risk assessment of online borrowers, and also provides a new idea for risk monitoring in the field of online lending.
Towards understanding reactor relevant tokamak pedestals

The physics of the tokamak pedestal is still not fully understood, for example there is no fully predictive model for the pedestal height and width. However, the pedestal is key in determining the fusion power for a given scenario. If we can improve our understanding of reactor relevant pedestals we will improve our confidence in designing potential fusion power plants. Work has been carried out as part of a collaboration on reactor relevant pedestal physics. We report some of the results in detail here and review some of the wider work which will be reported in full elsewhere. First, we attempt to use a gyrokinetic-based calculation to eliminate the pedestal top density as a model input for Europed/EPED pedestal predictions. We assume power balance at the top of the pedestal, that is, the heat flux crossing the separatrix must be equal to the heat source at the top of the pedestal and investigate the consequences of this assumption. Unfortunately, the transport assumptions of the EPED model mean that this method does not discriminate between different pairs of density and temperature profiles for a given pressure profile. Second, we investigate the effects of non flux surface density on the bootstrap current. Third, type I ELMs will not be tolerable for a reactor relevant regime due to the damage that they are expected to cause to plasma facing components. In recent years various methods of running tokamak plasmas without large ELMs have been developed. These include small and no ELM regimes, the use of resonant magnetic perturbations and the use of vertical kicks. We discuss the quiescent H-mode here. Finally we give a summary and directions for future work.
Importance and Performance Ratings Analysis for Implementation of Green Construction on Building Project

Green construction implementation which is part of sustainable construction development has more benefits for building industries, occupants, and public communities. The implementation of green construction is slow and still limited in Indonesia. Frequent opinions about green construction activities are difficult to implement and require different efforts from conventional building processes. Therefore, this study aims to identify the aspects that have prioritized to get improvement for the implementation of green construction in building projects using importance and performance ratings analysis which includes gap analysis, and quadrant analysis. This research identifies 17 criteria success factors approved and has 30 questionnaires received. The questionnaire survey was given based on the perceptions of owner, consultants, and contractors. The questions contain the criteria success factors in implementation of green construction related to the measurement of its importance or significance and extended to evaluate its performance. The results showed there are aspects that are prioritized because low performance. For Quadrant I “Concentrate Here” such as adequate financial resources, optimal cost management, and exactness selection of eco-friendly quality materials and For Quadrant III “Low Priority” such as Existence of green performance evaluation system during the project, changes in labor habits to support green concepts, frequently training/education, procurement related to integrated green concept, and availability of green construction pilots,.
Analysis on the lubrication performance of spiral-grooved journal bearing using CFD technique

As the main element, the lubrication characteristics of spiral-grooved journal bearing would decide the stability of mechanical systems. And, a effectivee model will represent the hydrodynamic characteristics of spiral-grooved journal bearing effectively. Based on the CFD technique, this work presents the simulation methodology for analyze the effects of spiral-grooved parameters on the lubrication performance of journal bearing. Compared with the published data, the proposed method is demonstrated effectiveness. Moreover, the influences of eccentricity ratio, groove number, spiral angle, groove width and groove depth are discussed by the orthogonal design method, which provide a reference for the optimized design of spiral-grooved journal bearing.
Bioinformatics Pathway Analysis Pipeline for NGS Transcriptome Profile Data on Nasopharyngeal Carcinoma

Next-Generation Sequencing (NGS)-based genomics data have a huge potential to be used in transcriptomic profiling of Nasopharyngeal Carcinoma (NPC) to study the biosynthesis mechanism behind it. The high dimensionality of NGS data is the main challenge in performing the data analysis to extract useful information. In this workflow pipeline, memory-efficient Linux-based software such as HISAT2 and HTSeq are utilized to process the raw NGS data. Furthermore, Differential Expression Gene (DEG) list can be obtained by performing advanced analysis to the aligned Ribonucleic Acid (RNA) sequence using the edgeR protocol. This DEG list is one of the main inputs of biological pathway analysis that can be done in DAVID and PANTHER web-based software. Both tools generate a different pathway result related to inflammation.
Principle of measuring the electron population of a quantum dot using a single-photon transistor based on an array of quantum dots

The scheme of a single-photon transistor formed by an array of semiconductor single-electron quantum dots in an optical resonator is considered. The spectral response of such a transistor depends on the Coulomb interaction of the electrons of the array with the electron at the measured quantum dot. An approximate analytical expression is obtained for the response function of a transistor with an arbitrary number of quantum dots. Using a one-dimensional array (chain) as an example, the dependences of the transistor response on the chain period, on the distance to the measured quantum dot, and on the degree of compensation for Coulomb effects are analysed. It is shown that the electron – photon dynamics of the transistor is substantially affected by the Förster effect, the suppression of which by alternating quantum dots with different symmetry of the excited state significantly increases the measurement accuracy.
Internet Live Broadcasting Information System Construction for Domain-Specific Knowledge and Susceptibility to Interpersonal Influence

Drawing on social identity theory and susceptibility to interpersonal influence theory, the study examine the influence of fans’ susceptibility to interpersonal influence on their buying intention during Internet Live Broadcasting, and the influence of domain-specific knowledge and social identity on susceptibility to interpersonal influence. By describing how fans’ personal characteristics determine their susceptibility to interpersonal influence, we built a mechanism explaining why fans may buy the product recommended by the Internet Live Broadcasting. We conducted an online survey to test the model. The findings may help sponsors of the Internet Live Broadcasting to turn more and more fans into consumers.
One-Step Synthesis of Mesoporous Silica Thin Films Containing Available COOH Groups

Inorganic–organic hybrid mesoporous silica thin films with covalently bonded carboxylic acid groups were synthesized in a one-step procedure, using carboxylic-derivatized alkoxysilanes obtained by photochemical radical thiol-ene addition (PRTEA). The organosilanes were synthesized by clicking mercaptosuccinic or mercaptoacetic thioacids with vinyltrimethoxysilane, using benzophenone as the photoradical initiator. The films were synthesized by evaporation-induced self-assembly of a sol containing a mixture of tetraethoxysilane and different quantities of the organosilanes, without any further treatment after the PRTEA reaction. Two nonionic surfactants were used as templates to produce different pore sizes. Different aging times were also applied. Structural characterization with electron microscopy, porosimetry measurements, and small angle X-ray scattering with two-dimensional detection demonstrated the obtention of mesoporous phases whose degree of ordering depended on the amount of added organosilane. The incorporation of the functional silanes was shown by X-ray photoelectron spectroscopy, and the presence of the COOH groups was confirmed by Fourier transform infrared (FTIR). Finally, the availability of the COOH groups for further chemical modification was demonstrated by FTIR by following the changes in the typical carbonyl IR bands during proton exchange and metal complexation. The proposed simple methodology allows obtaining COOH-modified silica thin films in one step, without the need of hard reaction conditions or deprotection steps. Functionalization with carboxyl groups brings a pH-dependent switch-ability to the pore surface that can be used for multifunctional mesoporous materials design.
Generation of the tumor-suppressive secretome from tumor cells

Rationale: The progression of cancer cells depends on the soil and building an inhibitory soil might be a therapeutic option. We previously created tumor-suppressive secretomes by activating Wnt signaling in MSCs. Here, we examined whether the anti-tumor secretomes can be produced from tumor cells. Methods: Wnt signaling was activated in tumor cells by overexpressing β-catenin or administering BML284, a Wnt activator. Their conditioned medium (CM) was applied to cancer cells or tissues, and the effects of CM were evaluated. Tumor growth in the mammary fat pad and tibia in C57BL/6 female mice was also evaluated through μCT imaging and histology. Whole-genome proteomics analysis was conducted to determine and characterize novel tumor-suppressing proteins, which were enriched in CM. Results: The overexpression of β-catenin or the administration of BML284 generated tumor-suppressive secretomes from breast, prostate and pancreatic cancer cells. In the mouse model, β-catenin-overexpressing CM reduced tumor growth and tumor-driven bone destruction. This inhibition was also observed with BML284-treated CM. Besides p53 and Trail, proteomics analysis revealed that CM was enriched with enolase 1 (Eno1) and ubiquitin C (Ubc) that presented notable tumor-suppressing actions. Importantly, Eno1 immunoprecipitated CD44, a cell-surface adhesion receptor, and its silencing suppressed Eno1-driven tumor inhibition. A pan-cancer survival analysis revealed that the downregulation of MMP9, Runx2 and Snail by CM had a significant impact on survival outcomes (p < 0.00001). CM presented a selective inhibition of tumor cells compared to non-tumor cells, and it downregulated PD-L1, an immune escape modulator. Conclusions: The tumor-suppressive secretome can be generated from tumor cells, in which β-catenin presented two opposing roles, as an intracellular tumor promoter in tumor cells and a generator of extracellular tumor suppressor in CM. Eno1 was enriched in CM and its interaction with CD44 was involved in Eno1's anti-tumor action. Besides presenting a potential option for treating primary cancers and metastases, the result indicates that aggressive tumors may inhibit the growth of less aggressive tumors via tumor-suppressive secretomes.
Measuring Innovation in Science

The importance of scientific advancement to economic growth and quality of life is rarely questioned, but concretely defining and measuring innovative science is a challenging task. Yet doing so is an important step towards understanding the inputs into and properties of High Impact and Transformative Science (HITS), which will in turn hopefully lead to insights that can be applied to better policy.1