Miracle-dz/UniFAR-FTUs huggingface dataset:
Response Spectrum Analysis of Blasting Vibration Signal with Different Microsecond Delay Time

In order to study the response spectrum property of basting vibration signals with different microsecond delay time,basing on monitored data on field blasting vibration in Jinduicheng open pit,the response spectrum analysis was done of two holes blasting vibration with different microsecond delay time.Firstly,the acceleration signal was obtained by direct differentiation method using monitored of VOD signal,the accurate and clear accelerating curve was gained by LPF(low pass filtering) De-noising processing using EEMD decomposition.Then,the velocity response spectrum and the standard velocity response spectrum of basting vibration signal with different microsecond delay time are given by exact methods.Analysis results show that the peak value of velocity response spectrum maybe larger the signals with less acceleration peak;the standard velocity response spectrum of blasting vibration signal with different microsecond delay time corresponded different natural vibration period.Therefore,it can be considered that choosing of reasonable delay time should comprehensive consider blasting vibration and dynamic response of construction.
Retrospective Evaluation of Non-Invasive Assessment Based on Routine Laboratory Markers for Assessing Advanced Liver Fibrosis in Chronic Hepatitis B Patients

Background At present, there is a lack of cheap, effective and convenient detection methods for hepatitis B-related liver fibrosis, especially in the developing area. Aim To evaluate the non-invasive methods for the significant and advanced fibrosis stage in chronic hepatitis B virus (HBV) patients in basic hospitals and to assess their diagnostic utility. Methods The study included 436 consecutive naive HBV individuals who had their livers biopsied. They were examined in one week using aspartate aminotransferase-to-aspartate aminotransferase ratio (AAR), age-platelet index (API), aspartate aminotransferase-to-platelet ratio index (APRI), fibrosis-4 (FIB-4), Forns, gamma-glutamyl transpeptidase-to-platelet ratio (GPR), S-index and transient elastography (TE). Scheuer scoring system was used to determine the histologic fibrosis grades (S0–S4). The diagnostic effectiveness was assessed using AUROCs and the DeLong test, both of which were based on statistical comparisons. Results For both substantial (≧S2) and advanced (≧S3) fibrosis phases, TE had good diagnostic performance in determining the hepatic fibrosis. Similar diagnostic performance was shown with Forns and S-index when it came to detecting fibrosis stages lower than S3. One model’s diagnostic value was not significantly improved by combining serum models. Correlation coefficients between clinical features and fibrosis phases were greatest for Forns (r = 0.397), S-index (r = 0.382) and TE (r = 0.535) when compared to other variables. Conclusion This investigation showed that Forns and S-index may be helpful strategies for detecting advanced fibrosis in HBV patients admitted to community hospitals.
A multi-parameter-level model for simulating future mortality scenarios with COVID-alike effects

Abstract There has been a growing interest among pension plan sponsors in envisioning how the mortality experience of their active and deferred members may turn out to be if a pandemic similar to the COVID-19 occurs in the future. To address their needs, we propose in this paper a stochastic model for simulating future mortality scenarios with COVID-alike effects. The proposed model encompasses three parameter levels. The first level includes parameters that capture the long-term pattern of mortality, whereas the second level contains parameters that gauge the excess age-specific mortality due to COVID-19. Parameters in the first and second levels are estimated using penalised quasi-likelihood maximisation method which was proposed for generalised linear mixed models. Finally, the third level includes parameters that draw on expert opinions concerning, for example, how likely a COVID-alike pandemic will occur in the future. We illustrate our proposed model with data from the United States and a range of expert opinions.
In Vitro Characterization and Identification of Potential Probiotic Yeasts Isolated from Fermented Dairy and Non-Dairy Food Products

This study is about the isolation of yeast from fermented dairy and non-dairy products as well as the characterization of their survival in in vitro digestion conditions and tolerance to bile salts. Promising strains were selected to further investigate their probiotic properties, including cell surface properties (autoaggregation, hydrophobicity and coaggregation), physiological properties (adhesion to the HT-29 cell line and cholesterol lowering), antimicrobial activities, bile salt hydrolysis, exopolysaccharide (EPS) producing capability, heat resistance and resistance to six antibiotics. The selected yeast isolates demonstrated remarkable survivability in an acidic environment. The reduction caused by in vitro digestion conditions ranged from 0.7 to 2.1 Log10. Bile salt tolerance increased with the extension in the incubation period, which ranged from 69.2% to 91.1% after 24 h. The ability of the 12 selected isolates to remove cholesterol varied from 41.6% to 96.5%, and all yeast strains exhibited a capability to hydrolyse screened bile salts. All the selected isolates exhibited heat resistance, hydrophobicity, strong coaggregation, autoaggregation after 24 h, robust antimicrobial activity and EPS production. The ability to adhere to the HT-29 cell line was within an average of 6.3 Log10 CFU/mL after 2 h. Based on ITS/5.8S ribosomal DNA sequencing, 12 yeast isolates were identified as 1 strain for each Candida albicans and Saccharomyces cerevisiae and 10 strains for Pichia kudriavzevii.
Spacing-Tailored Multicore Fiber Interface for Efficient FIFO Devices

Multicore fibers (MCFs) have attracted intense attention to overcome the capacity limit of single-core optical fiber communication system. However, as indispensable connection devices between the MCF and the individual single mode fiber (SMF), fan-in and fan-out (FIFO) devices are challenging to achieve overall performance in terms of coupling efficiency, crosstalk, return loss, and device compactness. Here we develop an MCF reverse-tapering technique to increase the core-to-core spacing of the MCF and construct a spacing-tailored interface between the MCF and the normal SMF bundle. The fabricated FIFO device for the small-core MCF with narrow core-to-core spacing of 35 μm features a low average coupling loss (∼0.6 dB), extraordinarily low crosstalk (<−65 dB) and a return loss (<−60 dB) without using any bridge elements, where the remarkably low crosstalk is about 20 dB lower than using special bridge fibers for the same type of MCF. The flexibility of reverse tapering of MCFs can overcome its intrinsic integration challenge and provide a powerful approach to constructing all-fiber FIFO devices with compact construction and excellent overall performance.
Shame- and guilt-proneness and self-compassion as predictors of self-forgiveness

ABSTRACT The purpose of the present study was to examine the mediating role of self-compassion in the relationship between guilt–/shame-proneness and self-forgiveness. The study is based on the Hall and Fincham’s self-forgiveness model which indicated guilt and shame proneness as emotional predictors of self-forgiveness. The sample consisted of 300 participants. They completed online self-report questionnaires related to shame and guilt-proneness (TOSCA-3), self-compassion (Self-Compassion Scale) and self-forgiveness (State Self-Forgiveness Scale). The multiple mediation models were developed to assess the extent to which selfcompassion mediates the relationship between shame- and guilt –proneness and selfforgiveness. The results showed that self-compassion mediated the link between shame-proneness and self-forgiveness (Total indirect effect B=-.24 CI95% [-.331 - .164]), shame-proneness and self-forgiving feeling and action (Total indirect effect B=- .15 CI95% [-.195 -.101], and shame-proneness and self-forgiving beliefs(Total indirect effect B=-.10 CI95% [-.149 -.051]). Shame activated during a transgression leads to less understanding, forbearance and compassion toward oneself. This attitude inhibits self-forgiveness.
Designing Neural Network Using Genetic Algorithm

The study introduces a neural network to predict the bankruptcy of insurance companies. As a method to optimize the network, a genetic algorithm suggests optimal structure and network parameters. The neural network designed by genetic algorithm is compared with discriminant analysis, logistic regression, ID3, and CART. The robust neural network model shows the best performance among those models compared
Determination of percentage yield and total phenolic content of ethanol extract from purple passion (Passiflora edulis f. edulis Sims) fruit peel

Free radicals can trigger various diseases, such as cancer, cardiovascular, arthritis, diabetes, neurological disorders, and aging. Thus, antioxidants are needed to reduce these free radicals. The peel of the purple passion fruit (Passiflora edulis f. edulis Sims) has many phenolic compounds that indicate antioxidant capacity. This study aims to determine the percentage yield and total phenolic contents in the ethanol extract of purple passion fruit peel. Extraction of purple passion fruit peel using the method of maceration with ethanol solvent. Measurement of total phenolic levels in ethanol extract from purple passion fruit peel using the UV–Vis Spectrophototometry method with Folin-Ciocalteu reagent. The principle of this method is based on the reagent between gallic acid and the Folin-Ciocalteu reagent that will produce a molybdenum-tungsten complex. Furthermore, the addition of Na2CO3 solution will change the color of the solution to blue, and its absorbance can be measured at a wavelength of 765 nm. The results showed that the ethanol extract from purple passion fruit peel yielded 1.363% and total phenolic levels of 30.758 mg of gallic acid equivalent per the gram of extract. The existence of the total phenolic content proves that the ethanol extract from purple passion fruit peel has the potential to be used as an alternative source of natural antioxidants.
Reassessment of Reliability and Reproducibility for Triple-Negative Breast Cancer Subtyping

Simple Summary Triple-negative breast cancer (TNBC) is a heterogeneous disease. A proper classification system is needed to develop targetable biomarkers and guide personalized treatment in clinical practice. However, there has been no consensus on the molecular subtypes of TNBC, probably due to discrepancies in technical and computational methods chosen by different research groups. In this paper, we reassessed each major step for TNBC subtyping and provided suggestions, which promote rational workflow design and ensure reliable and reproducible results for future studies. We presented a recommended pipeline to the existing data, validated established TNBC subtypes with a larger sample size, and revealed two intermediate subtypes with prognostic significance. This work provides perspectives on issues and limitations regarding TNBC subtyping, indicating promising directions for developing targeted therapy based on the molecular characteristics of each TNBC subtype. Abstract Triple-negative breast cancer (TNBC) is a heterogeneous disease with diverse, often poor prognoses and treatment responses. In order to identify targetable biomarkers and guide personalized care, scientists have developed multiple molecular classification systems for TNBC based on transcriptomic profiling. However, there is no consensus on the molecular subtypes of TNBC, likely due to discrepancies in technical and computational methods used by different research groups. Here, we reassessed the major steps for TNBC subtyping, validated the reproducibility of established TNBC subtypes, and identified two more subtypes with a larger sample size. By comparing results from different workflows, we demonstrated the limitations of formalin-fixed, paraffin-embedded samples, as well as batch effect removal across microarray platforms. We also refined the usage of computational tools for TNBC subtyping. Furthermore, we integrated high-quality multi-institutional TNBC datasets (discovery set: n = 457; validation set: n = 165). Performing unsupervised clustering on the discovery and validation sets independently, we validated four previously discovered subtypes: luminal androgen receptor, mesenchymal, immunomodulatory, and basal-like immunosuppressed. Additionally, we identified two potential intermediate states of TNBC tumors based on their resemblance with more than one well-characterized subtype. In summary, we addressed the issues and limitations of previous TNBC subtyping through comprehensive analyses. Our results promote the rational design of future subtyping studies and provide new insights into TNBC patient stratification.
Bioinformatics Study Identified EGF as a Crucial Gene in Papillary Renal Cell Cancer

Background Due to a lack of knowledge of the disease process, papillary renal cell carcinoma (PRCC) has a dismal outlook. This research was aimed at uncovering the possible biomarkers and the underlying principles in PRCC using a bioinformatics method. Methods We searched the Gene Expression Omnibus (GEO) datasets to obtain the GSE11151 and GSE15641 gene expression profiles of PRCC. We used the R package limma to identify the differentially expressed genes (DEGs). The online tool DAVID and ClusterProfiler package in R software were used to analyze Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway dominance, respectively. The STRING database was utilized to construct the PPI network of DEGs. Using the Cytoscape technology, a protein-protein interaction (PPI) network that associated with DEGs was created, and the hub genes were identified using the Cytoscape plug-in CytoHubba. The hub genes were subjected to a Kaplan-Meier analysis to identify their correlations with survival rates. Results From the selected datasets, a total of 240 common DEGs were identified in the PRCC, including 50 upregulated genes and 190 downregulated regulated genes. Renal growth, external exosome, binding of heparin, and metabolic processes were all substantially associated with DEGs. The CytoHubba plug-in-based analysis identified the 10 hub genes (ALB, KNG1, C3, CXCL12, EGF, TIMP1, VCAN, PLG, LAMC1, and CASR) from the original PPI network. The higher expression group of EGF was associated with poor outcome in patients with PRCC. Conclusions We revealed important genes and proposed biological pathways that may be implicated in the formation of PRCC. EGF might be a predictive biomarker for PRCC and therefore should be investigated as a novel treatment strategy.
The mediation effect of inventory management practices on operational performance in public university

Purchasing and inventory managements are essential in both public and private organizations, especially in public higher education institutions and universities since they can they affect achievement of the country mission and fully respond to needs of the people. The objectives of this research are to study the effects of purchasing strategies (PUF) and inventory management practices (INV) on operational performance (OPE), as well as the mediation effect of INV on the effect of PUF on OPE. The study used quantitative method. The sample was 293 staff involved in purchasing and inventory managements in the public university in Thailand, arisen from convenience sampling. The instruments used in the research were questionnaires. The statistics used for data analysis were frequency, percentage, mean, standard deviation, confirmative factor analysis and structural equation modeling. The findings revealed that PUF and INV had a direct positive effect on OPE and INV mediated the effect of PUF on OPE. For practical recommendation, such findings can be a guideline for public higher education institutions to improve their logistics management, especially in purchasing and inventory managements
Channel Estimation Evaluation For a Massive MIMO System Considering Spatially Correlated Channels in an Urban Network

Channel estimation (CE) is an important process that is done during the pilot transmission phase in each base station. This work addresses this process for the massive multiple-input multiple-output systems by studying the scenario where the channels are spatially correlated. Throughout this work, the spatial correlation between channels is modeled using the exponential correlation model. The minimum mean square error (MMSE) estimator’s performance for uncorrelated and correlated channels is compared and examined using the normalized mean square error (NMSE) metric, where the correlated scenario is presented through two array designs, namely proposed uniform planar array (UPA) and uniform linear array (ULA). In comparison to the uncorrelated situation, the correlated channels scenario is a more practical scenario that represents the real- world environment and provides superior channel estimate quality since the spatial correlation is advantageous for CE. Hence, we proposed a proposed UPA arrangement for correlated channels based on the Kronecker product of the ULA arrangement that outperforms the ULA arrangement and offers superior performance comparedto ULA. Numerical results are offered in order to support our analytical study.
Robust Cooperative Spectrum Sensing under PrimaryUser EmulationAttack in Cognitive Radio Networks

Cooperative Spectrum Sensing (CSS) is an effective approach to improve the detection performance of vacant frequency bands in Cognitive Radio (CR) networks. The CSS process imposes some security threats to the CR networks. One of these common threats is Primary User Emulation Attack (PUEA). In PUEA, some malicious users try to mimic primary signal characteristics and deceive CR users to prevent them from accessing the vacant frequency bands. The present study introduces a new CSS scheme, in the presence of a malicious PUEA, called Attack-aware CSS (ACSS). The idea is based on the estimation of attack parameters including probabilities of the fake PUEA signals’ presence in both occupied and unoccupied frequency bands. The obtained parameters are innovatively applied in Neyman-Pearson (N-P) or Log-Likelihood Ratio Test (LLRT) to improve collaborative sensing performance. Simulation results verify the performance improvement of the proposed method against PUEA compared with conventional method. c © 2015 JComSec. All rights reserved.
Distributed Event-Triggered Hierarchical Control of PV Inverters to Provide Multi-Time Scale Frequency Response for AC Microgrid

With the increasing penetration of inverter-interfaced photovoltaic (PV) systems in AC microgrids, the system inertia is increasingly deficient and the frequency response ancillary service provided by PV systems will be inevitable. In this paper, in order to make the PV systems provide multi-time scale frequency response, a novel distributed event-triggered hierarchical control (DEHC) of PV inverters is proposed, which includes a primary frequency response (PFR) control loop and a secondary frequency response (SFR) control loop. For the PFR, the PV inverters that operate in frequency regulation (FR) mode can arrest the frequency deviation in sub-seconds time-scale by an automatic deloading strategy, which is with low cost and easy to implement as no requirements for a storage system, irradiance sensors, and MPP estimators. For the SFR, the PV inverters that operate in FR mode can respond to the reference instruction assigned by a high-level AGC control center in seconds time-scale based on a novel distributed control strategy, which can converge within a fixed-time that independents to the initial conditions of the system. Furthermore, a novel event-triggered mechanism is designed to reduce the communication costs between PV inverters. Finally, case study results verify the effectiveness and improved performance of the proposed method.
PTBP1 as a Promising Predictor of Poor Prognosis by Regulating Cell Proliferation, Immunosuppression, and Drug Sensitivity in SARC

Background Sarcomas (SARC) have been found as rare and heterogeneous malignancies with poor prognosis. PTBP1, belonging to the hnRNPs family, plays an essential role in some biological functions (e.g., pre-mRNA splicing, cell growth, and nervous system development). However, the role of PTBP1 in SARC remains unclear. In this study, the aim was to investigate the potential role of PTBP1 with a focus on SARC. Methods The expression, prognostic value, possible biological pathways of PTBP1, and its relationship with immune infiltration and drug sensitivity were comprehensively analyzed based on multiple databases. PTBP1 was further validated in osteosarcoma as the most prominent bone SARC. The expression of PTBP1 was investigated through IHC. The prognostic value of PTBP1 was verified in TARGET-OS databases. CRISPR/Cas9-mediated PTBP1 knockout HOS human osteosarcoma cell lines were used to assess the effect of PTBP1 on cell proliferation, migration, metastasis and cell cycle by CCK-8, Transwell migration, invasion, and FACS experiment. Result PTBP1 was highly expressed and significantly correlated with poor prognosis in several cancers, especially in SARC, which was validated in the clinical cohort and osteosarcoma cell lines. The genetic alteration of PTBP1 was found most frequently in SARC. Besides, PTBP1 played a role in oncogenesis and immunity through cell cycle, TGFB, autophagy, and WNT pathways at a pan-cancer level. Knockout of PTBP1 was observed to negatively affect proliferation, migration, metastasis, and cell cycle of osteosarcoma in vitro. Furthermore, PTBP1 was significantly correlated with tumor immune infiltration, DNA methylation, TMB, and MSI in a wide variety of cancers. Moreover, the potential of the expression level of PTBP1 in predicting drug sensitivity was assessed. Conclusions PTBP1 is highly expressed and correlated with prognosis and plays a vital pathogenic role in oncogenesis and immune infiltration of various cancers, especially for SARC, which suggests that it may be a promising prognostic marker and therapeutic target in the future.