bluuebunny/crossref_metadata_2025_split huggingface dataset:
Seismic Ground Motion Alerts for Mines
Authors: Mendecki Aleksander J. 
Published: September 2022

Abstract
One of the objectives of seismic monitoring in mines is to detectstrong and unexpected changes in the spatial and/or temporal behaviourof seismic parameters that could lead to rock mass instability and affect working places immediately or in the short term. Wepresent an influence based polygon-less method of detecting such conditions, taking into account the influence of ground motion generated by all available seismic events, regardless of their location, on a particular working place. The measures of influence are the peak ground velocity, PGV, and the cumulative absolute displacement, CAD, since their influencesare moderated by the distance from the seismic source to the place of potential exposure. Both CAD and PGV are calculated for each point of interest from the ground motion prediction equation, GMPE, developed for a given mine. The CAD becomes CAID, i.e. cumulative absolute inelastic deformation, if the co-seismic strain, PGV/νS , exceeds the elastic threshold, e.g. 10-6 for hard rock. Alerts and Alarms are triggered if the rates of CAID and/or its activity, ACAID, exceed predefined reference levels. Since they have different units, we normalise each by its reference level and at each time step select the one which is greater and call it the GMAP rating. All points that at a given time trigger an Alert define the exclusion zone and are monitored as time progresses.
Passive Acoustic Monitoring application to evaluate the vocal behavior of wild howler monkeys (Alouatta guariba clamitans)
Authors: Paula Bruna Campos , Pinter Adriano , Padovese Linilson 
Published: September 2022

Abstract
Passive Acoustic Monitoring (PAM) provides the way to feature the status, presence and trends of species’ distribution in different landscapes, under different environmental conditions. The howler monkeys are known for investing a long time and energy in the vocal type known as roar, an important vocal type for intra- and inter-group dynamics. The aim of the present study was to evaluate the detection, distribution and vocal behavior of wild howler monkeys based on the PAM methodology due to the need of having a fast and effective method to evaluate this species’ population presence and status given the successive yellow fever outbreaks lethally affecting it. The study was carried out at Fontes do Ipiranga State Park, Southeastern São Paulo City, Brazil. The evaluation of howler monkeys roar vocal behavior’s temporal pattern was carried out by taking into consideration the number of roaring events counted based on time. Vocalization occurrences observed between stations were compared to express the roaring events on an hourly basis. In total, 1,531 hours of recordings were analyzed and it allowed detecting roars in all PAM stations. The number of roaring events ranged from 71 to 142 per station. The present study has shown the useful application of PAM to accurately detect the presence of howler monkey groups based on vocal behavior. Furthermore, this method helps assessing groups’ distribution and daily occurrence, besides giving tips about how they are distributed in the area based on their handling ability.
Ionic liquid-based dispersive liquid-liquid followed high-performance liquid chromatography for the determination of Silychristin, Silydianin, Silybin, Silybin B, Isosilybin A, Isosilybin B in silbbum marianum seed
Authors: Sun Peng , Wang Chao , Zhang Xiaolin , Liang Ting 
Published: September 2022

Abstract
A novel pretreatment method ionic liquid-based dispersive liquid-liquid followed high-performance liquid chromatography was established and applied in the analysis of Silychristin, Silydianin, Silybin ,Silybin B, Isosilybin A, Isosilybin B in silbbum marianum. The critical parameters affecting dispersive liquid-liquid micro-extraction (DLLME), including selection of dispersive solvent and extraction solvent, volume of dispersive solvent and extraction solvent, adjustment of pH, salt concentration, extraction time, were investigated by single factor study. Under optimum conditions, all of the target analytes presented good linearity (r > 0.9991) and satisfied recoveries (Recoveries > 89.5%, relative standard deviation (RSD) < 4.6%). The limits of detection and quantification were 0.16 to 0.74 ng kg− 1 and 0.42 to 2.52 ng kg− 1, respectively. The developed method is sensitive, rapid, accurate and employable to simultaneously determine six target compounds in silbbum marianum.
Optimal frequency-response corrections for eddy covariance flux measurements using the Wiener deconvolution method
Authors: Emad Anas 
Published: September 2022

Abstract
We describe a new direct correction approach to accurately restore frequency attenuated eddy covariance (EC) measurements. The new approach utilizes the Wiener deconvolution method to optimally estimate the original signal from noisy atmospheric measurements. Key features over conventional EC spectral correction methods includei) the use of physics-based response functions, ii) the ability to account for the non-linear phase contributions, and iii) the direct restoration of the original signal rather than simulating the effect on an ideal spectrum. The new correction approach is compared to conventional spectral correction methods in a numerical simulation where the magnitude of the key limitations of conventional methods is explored under conditions relevant to common EC set-ups. The simulation results showed that the spectral correction methods commonly used for calculating EC fluxes introduced systematic error up to 10\% to the restored fluxes and substantially increased their random uncertainty. The errors are attributed to the effect of using inappropriate response functions, failing to account for the contribution of the non-linear phase, and due to the assumption of spectral similarity on the scale of averaging intervals. The Wiener deconvolution method is versatile, can be applied under non-ideal conditions, and provides an opportunity to unify analytical and "in-situ" spectral correction methods by applying existing transfer functions to directly restore attenuated spectra. Furthermore, the Wiener deconvolution approach can be comfortably used with other micrometeorological measurement techniques such as eddy accumulation and flux profile measurements.
Sperm quality and fertility of Murrah and Nili-Ravi bulls compared with indigenous buffalo bulls in Bangladesh
Authors: MIRAZ MD FAIZUL HOSSAIN , Hossain SMJ , Akter Shahrina , Deb Gautam Kumar 
Published: September 2022

Abstract
Fresh and frozen semen quality of Murrah and Nili-Ravi bulls in comparison with indigenous buffalo bulls was evaluated by Computer Assisted Sperm Analyzer (CASA). Semen was collected regularly once a week semen collection schedule from six (two/group) buffalo bulls. Fresh semen was evaluated for sperm concentration, motility, sperm kinematics, morphology and dose/ejaculate. Semen was diluted in a commercial extender (AndroMed), equilibrated, cryopreserved and finally evaluated for post-thaw sperm quality. On-station Artificial Insemination (AI) was carried out in naturally estrus indigenous buffalo cows at their second or third parity. Semen volume and concentration did not vary significantly (p&gt;0.05). In fresh semen, total, static and slow motility differed significantly among the groups (p&lt;0.01). After cryopreservation, total, progressive and static motility shows significant differences (p&lt;0.01) among the groups followed by Indigenous, Murrah and Nili-Ravi. Indigenous buffalo bull has less morphological abnormalities than Murrah and Nili-Ravi bulls (p&lt;0.01). In fresh semen, VAP, VSL, STR, LIN and BCF differ significantly among the groups (p&lt;0.05) with higher values in indigenous bull followed by Nili-Ravi and Murrah. In frozen semen, STR, LIN, ALH and WOB differ significantly (p&lt;0.01) among the groups. Fertility did not vary significantly among the groups following 60 days post-AI. Irrespective of differences in fresh and frozen semen quality, all bulls from the three groups are suitable for AI with a considerable conception rate at least in on-station conditions. More dose/ejaculate can be produced from Murrah bulls (316.53±131.65) followed by Nili-Ravi (297.33±95.79) and Indigenous bulls (294.64±152.14). Murrah and Nili-Ravi breed can be used as similar efficiency of the indigenous bull for AI to increase the productivity of indigenous buffalo of Bangladesh.
An eigen decomposition based closed-form solution for the Discrete Lyapunov and Stein Equations
Authors: Patel Aaqib , Khan Mohammed Zafar Ali 
Published: September 2022

Abstract
A simple closed-form solution to the discrete Lyapunov equation(DLE) is established for certain families of matrices. This solution isexpressed in terms of the eigen decomposition (ED) for which closed-form solutions are known for all 2 × 2, 3 × 3 and certain familiesof matrices. For general matrices, the proposed ED based closed-formsolution can be used as an efficient numerical solution when the EDcan be computed. The result is then extended to give closed-formsolutions for a generalization of the DLE, called the Stein equation. The proposed explicit solution’s complexity is of the same order asiterative solutions and significantly smaller than known closed-formsolutions. These solutions may prove convenient for analysis and syn-thesis problems related to these equations due to their compact form.
Detection of DDoS attack in SDN network using Entropy in Pox controller
Authors: Shetty Anuj 
Published: September 2022

Abstract
Software-defined networking architectural is a sim- plified framework which reduces the work of the net- work administrators by differentiating the data plane from the control plane. An easy to configure network is made possible with this architecture by providing a programmable interface for applications related to management, security and control over the entire net- work is more easily achieved through centralized con- trollers that have complete network visibility. As a result of these advantages, software-defined networks are susceptible to attacks with much greater impact than traditional ones.
Multichannel Matrix Randomized Autoencoder
Authors: Zhang Shichen , Wang Tianlei , Cao Jiuwen 
Published: September 2022

Abstract
The existing randomized autoencoders (RAEs) are generally designed for vectorization data resulting in destroying the original structure information inevitably when dealing with multi-dimension data such as image and video. To address this issue, a one-side matrix randomized AE (OMRAE) is developed that takes the two-dimensional (2D) data as inputs directly by the linear mapping on one-side of inputs with matrix multiplication. For multichannel 2D (M2D) data, a multichannel OMRAE (OMMRAE) is proposed by training the output weights to rebuild each channel of inputs respectively. In this way, the structural information of each channel and the interaction between channels are explored. Then, a double-side structure using 2 OMMRAEs to simultaneously extracts the row and column structure information of M2D is developed. At last, a novel hierarchical matrix randomized neural networks is constructed for one-class classification (HMRNN-OC) where each layer passes information by bilinear mapping derived from DMMRAE. Experiments are conducted on 2 benchmark datasets for the effectiveness demonstration. Comparisons to several state-of-the-art AEs reveal that the proposed OMMRAE/DMMRAE can obtain better performance with a compact network size.
Prognostic Signature of Pyroptosis-Related LncRNA Correlates with Clinical and Immunological Characteristics of Hepatocellular Carcinoma
Authors: Xiao Junhao , Yuan Wei , Zhu Xuanjin , Yan Yong , Li Weitao , Wu Fan , Mao Benliang , Zhang Jiansong , Du Yongliang , Zhu Shanfei , Wang Bailin 
Published: September 2022

AbstractBackground Pyroptosis has dual effects and is involved in several malignancies, including hepatocellular carcinoma(HCC). Pyroptosis can rapidly lead to tumor regression, and also can promote the development of the tumor microenvironment. Long non-coding RNA has recently been considered to be closely related to the development of several cancers. However, the clinical significance of pyroptosis-related lncRNA remains largely unexplored. Methods Based on The Cancer Genome Atlas (TCGA) Liver hepatocellular carcinoma (LIHC) dataset, We identified characteristic prognostic long non-coding RNAs by univariate, LASSO, and multifactorial regression analysis and constructed a prognostic signature of pyroptosis-related lncRNAs in HCC. The prognostic potential of the characteristic lncRNAs was evaluated in each of the two cohorts created by randomly dividing the TCGA cohort into a training cohort and a test cohort in a 1:1 ratio. Subsequently, immune profiles in defined subgroups of pyroptosis-related lncRNA features as well as drug sensitivity were analyzed. Results We constructed a multigene signature based on 7 characteristic prognostic lncRNAs and classified HCC patients into high-risk and low-risk groups based on the median value of the risk score. The receiver operating characteristic curve (ROC) curves area under the curve (AUC) values for 1-, 3-, and 5-year survival were 0.843, 0.752, and 0.766, respectively. Univariate and multifactorial regression analyses indicated that this prognostic feature was an independent prognostic factor for hepatocellular carcinoma. Furthermore, gene set enrichment analysis showed that cell cycle, ubiquitin-mediated protein hydrolysis, pathways in cancer, NOTCH, and mTOR signaling pathways were significantly enriched in the high-risk group compared to the low-risk group. Moreover, there were significant differences in the expression of immune cell subpopulations, immune checkpoint genes, and potential drug screening that provided distinct therapeutic recommendations for individuals with various risks. The genes involved in new cell death (Copper-induced death), also differed significantly between the high- and low-risk groups. Conclusions In summary, our constructed prognostic signature of pyroptosis-related lncRNA showed significant predictive value for the prognosis of HCC patients, which provides insights for individualized immunotherapy.
Characterization of Cellulose Nanocrystalline (CNCs) Derived from Microcrystalline Cellulose (MCC) Synthesized Using Acid Hydrolysis Method
Authors: Whba Fathyah , Mohamed Faizal , Idris Mohd Idzat , Yahya Mohd Syukri 
Published: September 2022

Abstract
This paper documented the synthesis of cellulose nanocrystalline (CNCs) extracted from commercially-sourced microcrystalline cellulose (MCC) via acid hydrolysis and the subsequent characterization analyses of the yield. The hydrolysis process was completed using 64% sulphuric acid at 45°C for 1 hour. The yield exhibited prominent physicochemical properties. The X-ray diffraction (XRD) analysis suggested that the crystallinity degree of the CNCs was 8.94% higher than MCC sample. Meanwhile, zeta potential (ζ) analysis showed that the CNCs sample possesses highly negative surface charges of 25.6±8.24 mV. Further investigation by transmission electron microscopy (TEM) analysis revealed the rod-like morphology of the CNCs sample with average diameter of 9.36±3.81nm and 83.84% crystallinity index. Whereas, via field emission scanning electron microscopy (SEM) analysis confirmed considerable reduction in particle size and changes in surface morphology post-acid hydrolysis of the CNCs, with diameter of 7.65±2.56 nm. It is envisaged that the acid hydrolysis technique is promising in synthesizing CNCs of high crystallinity with smaller size for various possible applications, potentially as a contrast agent.
ICON-P - A prospective double-blind evaluation of quality improvements with Individualized CONstraints from low-cost knowledge-based radiation therapy planning in Prostate cancer
Authors: Saha Saheli , Pras S Sriram , Balakrishnan Arun , Kalita Smita Jagadish , Elavarasan Niranjan , Adhya Debashree Guha , Sarkar Arnab , Arunsingh Moses , Chakraborty Santam , Mallick Indranil 
Published: September 2022

Abstract
PURPOSE/OBJECTIVE(S)
A low-cost, prior knowledge-based individualized dose-constraint generator for organs-at-risk has been developed for prostate cancer radiation therapy (RT) planning. In this study, we aimed to prospectively evaluate the feasibility and improvements in organs-at-risk (OAR) doses in prostate cancer RT planning using this tool served on a web application.
MATERIALS AND METHODS:
A set of previously treated prostate cancer cases planned and treated with generic constraints were prospectively replanned using individualized dose constraints derived from a library of cases with similar volumes of target, OAR, and overlap regions and served on the web-based application. The goal was to assess the reduction in mean dose, specified dose volumes (V59Gy, V56Gy, V53Gy, V47Gy, and V40Gy), and generalized equivalent uniform dose (gEUD) to the rectum and bladder. Planners and assessors were blinded to the initial achieved doses and penalties. Sample size estimation was based on improvement in V53Gy for the rectum and bladder with a paired evaluation.
RESULTS:
Twenty-four patients were prospectively replanned. All the plans had a PTV D95 of at least 97% of the prescribed dose. The individualized OAR constraints could be met for 87.5% of patients for all dose levels. The mean dose, V59Gy, V53Gy, and V47Gy for the bladder was reduced by 7.5Gy, 1.12%, 5.51%, and 10.53% respectively. Similarly for the rectum, the mean dose, V59Gy, V53Gy, V47Gy and was reduced by 5.5Gy, 4.34%, 6.97%, and 11.61% respectively. All dose reductions were statistically significant. The gEUD of the bladder was reduced by 2.47Gy (p <0.001) and the rectum by 3.21Gy (p <0.001).
CONCLUSION:
Treatment planning based on individualized dose constraints served on a web application is feasible and leads to improvement at clinically important dose volumes in prostate cancer RT planning. This application can be served publicly for improvements in RT plan quality.
A new rotating machinery fault diagnosis method for different speeds based on improved multivariate multiscale fuzzy distribution entropy
Authors: Ma Yanli , Cheng Junsheng , Wang Ping , Wang Jian , Yang Yu 
Published: September 2022

Abstract
To abstract the fault features from multivariate vibration signals of the rotating machinery under different speeds, an improved multivariate multiscale fuzzy distribution entropy (IMMFDE) is proposed. Based on multivariate empirical mode decomposition (MEMD), the IMMFDE can determine the maximum scale adaptively, meanwhile eliminate the frequency aliasing and avoid the loss of potentially useful information in the multiscale process. The trait of IMMFDE is verified by calculating the sequences and their amplitude spectrums at each scale of the simulated multivariate signals. Further, the fault diagnosis method is proposed for the rotating machinery under different speeds based on IMMFDE. In the method, the statistical parameters (SPs) and IMMFDE are calculated as fault feature set, then support vector machine (SVM) is used for fault diagnosis. Applying the method to two types of the rotating machinery multi-fault diagnosis under different speeds, the results show the proposed method can obtain better fault diagnosis results.
Safety and Efficacy of Paclitaxel plus Carboplatin Versus Paclitaxel plus Cisplatin in Neoadjuvant Chemoradiotherapy for Patients with Locally Advanced Esophageal Carcinoma : A Retrospective Study
Authors: Jiang Li , Zhu Jie , Chen Xue , Wang Yi , Wu Lei , Wan Gang , Han Yongtao , Leng Xuefeng , Peng Lin , Wang Qifeng 
Published: September 2022

Abstract
Background and purpose
We evaluated and compared the efficacy and safety of chemotherapy with paclitaxel plus cisplatin (TP) or carboplatin (TC) in patients with locally advanced esophageal squamous cell carcinoma (LA-ESCC) who underwent neoadjuvant chemoradiotherapy (NCRT).
Materials and methods
This single-center retrospective study assessed patients with LA-ESCC (cT2N + M0, cT3-4aNanyM0) receiving NCRT plus curative-intent esophagectomy with TP or TC regimen. The primary endpoints were grade ≥ 3 adverse events (AEs) and overall survival (OS). AEs were compared using a t-test according to CTCAE 4.0. The Kaplan-Meier survival curves were compared using the log-rank test; the treatment effect was measured using hazard ratios (HR) and 95% confidence intervals (CI).
Results
We included 151 and 50 patients in the TC and TP groups, respectively. Baseline demographic and clinical characteristics were well balanced between groups. The TP group exhibited significantly higher hematologic and non-hematologic AEs than the TC group, and the noticeable difference was the incidence of febrile neutropenia of grade 3 or higher (P = 0.011). No significant intergroup differences were noted considering postoperative complications, resection margins, or pathological complete remission rate (all P > 0.05). OS and progression-free survival (PFS) did not significantly differ between groups. The estimated 3-year OS and PFS rates were 65.1% versus 69.4% and 58.4% versus 53.5% for TP and TC groups, respectively.
Conclusion
In patients with LA-ESCC, we recommend TC, not TP, as an optimal chemotherapy regimen for NCRT, given its superiorsafety profile and comparable efficacy.
Employment Demand Mining and Talent Training Enlightenment Based on Recruitment Data：Taking as an example Statistics
Authors: Yan Chun , Yang Lijuan , Liu Wei 
Published: September 2022

Abstract
To help candidates understand the specific needs of the market for talents, and provide references for education institutions to develop training programs and curricula. Scraping the recruitment data on the 51Job website with statistics as the keyword. After cleaning and labeling them, comparing the entity recognition effects of BiLSTM-CRF, BiGRU-CRF, BERT-BiLSTM-CRF, and BERT-BiGRU-CRF, and then selecting the best model to extract recruitment entities for mining analysis. The experimental results show that the BERT-BiGRU-CRF model has the best recognition effect, and the accuracy value and F1 value are increased by 7.05% and 4% respectively, which has certain advantages over the other three models. According to the selected recruitment entities, the skills and qualities that the statistics profession should possess are summarized from the three aspects of educational background, professional requirements, and personal qualities, and suggestions on training for statistics education are put forward.
An Efficient Data Compression Algorithm
Authors: Dey Swapan 
Published: September 2022

Abstract
This paper introduces a new and highly efficient data compression algorithm, which is a variant of Lempel-Ziv group of algorithms but much more efficient than other variants of Lempel-Ziv algorithm. Unlike popular data compression tools (zip, rar, 7z, gzip, bzip etc) available in the market that use multiple data compression algorithms together to achieve optimum compression, this algorithm alone is capable of compressing a data much better than deflate[8] (zip) for most of the files > 10–12 MB without using any other data compression technology at the second level, hence leaves enough opportunity for the researchers to achieve much better compression in future by using an entropy algorithm along with the proposed algorithm.