bluuebunny/crossref_metadata_2025 huggingface dataset:
Leadership, Millenials, And Job Satisfaction
Authors: Brand David , Walker Scott
Published: February 2022

Employee turnover is a disruptive and costly phenomenon for organizations. Understanding the causes of turnover and how to mitigate such causes offers a tangible benefit to organizations, especially as it relates to Millennials which are the largest portion of the workforce in 2020. The study herein sought to determine whether Millennial generation employee perceptions of leadership style have an association with job satisfaction for college-educated, full-time employees at a mid-sized professional services firm in the United States. The relationship between perceptions of leadership style and employee job satisfaction were evaluated via a non-experimental quantitative study. The research design was a cross-sectional survey administered to 1,567 participants with 354 usable responses obtained. Data collected via a survey demonstrated there is a statistically significant moderate correlation (rs = .32, p < .01) between perceptions of leadership style and job satisfaction at the scale level and that the relationship is stable regardless of gender, tenure, ethnicity, or age. The findings support previous studies of various generational cohorts and extend the knowledge base specific to a Millennial subgroup. This study extends the body of knowledge related to the Full Range of Leadership Theory and adds information for a specific generational cohort in one industry segment. Implications include opportunities for organizations to implement leadership development programs focused on specific behaviors that will increase employee satisfaction.
Website Characteristics on Customer Satisfaction
Authors: Supriyati  , P Harahap S
Published: February 2022

The purpose of this research is to find out how customer satisfaction in the field of online business. The research method used was descriptive qualitative research method. A descriptive qualitative method is a method used to describe or analyze the results of the research. Website characteristics are defined as attributes that consumers consider when evaluating an online site. Website characteristics are measured using five dimensions shopping convenience, design, informative, security, communication. Online business is an important tool for consumers to find products, the purchase intention of consumers through online stores tends to be high. Consumer satisfaction is greatly influenced by the transaction process and trust. And, based on the result of the research, that ease, security, site design, informative and communication as well as features of an online business affect customer satisfaction.
Human Resources Planning Strategy with SWOT Analysis Method at PT. X (Largest Cigarette Distributor in Indonesia)
Authors: Pancasasti Ranthy , Sapitri Dian , Oktavian Evan Nur , Mulyadi Adi , Saputra Agung Aditya
Published: February 2022

This research aims to find out how the human resource planning strategy conducted by PT X Cigarette Distributor. This company is a cigarette distributor company and is the largest cigarette "brand" in Indonesia, because it is a large company so there is also a lot of labor in it. So in this study analyzed whether existing human resources are effective or not. The type of research conducted is Field Research which is descriptive analysis that is research that describes the strategy of human resource planning in an effort to improve employee performance. Data collected by interview, observation, and documentation. Data analysis techniques used qualitative descriptive analysis combined with SWOT analysis approach. The results of the study explain that in human resource planning there are several stages in the process of procuring new employees. And in carrying out its operational activities, the company considers the strengths, weaknesses; opportunities and threats that one day can benefit or harm the company.
Cytokines and Inflammation in Meniere Disease
Authors: Frejo Lidia , Lopez-Escamez Jose Antonio
Published: February 2022

Meniere disease (MD) is a rare set of conditions associated with the accumulation of endolymph in the cochlear duct and the vestibular labyrinth with a decrease of endocochlear potential. It is considered a chronic inflammatory disorder of the inner ear with a multifactorial origin. The clinical syndrome includes several groups of patients with a core phenotype: sensorineural hearing loss, episodes of vertigo, and tinnitus with a non-predictable course. Genetic factors and the innate immune response seem to play a central role in the pathophysiology of the condition. Autoimmune MD should be diagnosed if a patient fulfills the diagnostic criteria for MD and one of the following autoimmune disorders: autoimmune thyroid disease, psoriasis, autoimmune arthritis, ankylosing spondylitis, or systemic lupus erythematosus. We summarize the evidence to support autoimmune MD as an endophenotype in bilateral MD associated with the allelic variant rs4947296 and nuclear factor-kappa B (NF-κB)-mediated inflammation, the role of cytokines (particularly interleukin-1β and tumor necrosis factor-α) in defining a subset of patients with autoinflammation, and the potential role of cytokines as biomarkers to distinguish between patients with MD and vestibular migraine. Finally, we also introduce a list of potential drugs that could regulate the immune response in MD with potential for repurposing in clinical trials.
Dynamics modeling and robotic-assist, leader-follower control of tractor convoys
Authors: Cook Joshua , Ray Laura , Lever James
Published: February 2022

This paper proposes a generalized dynamics model and a leader-follower control architecture for skid-steered tracked vehicles towing polar sleds. The model couples existing formulations in the literature for the powertrain components with the vehicle-terrain interaction to capture the salient features of terrain trafficability and predict the vehicles response. This coupling is essential for making realistic predictions of the vehicles traversing capabilities due to the power-load relationship at the engine output. The objective of the model is to capture adequate fidelity of the powertrain and off-road vehicle dynamics while minimizing the computational cost for model based design of leader-follower control algorithms. The leader-follower control architecture presented proposes maintaining a flexible formation by using a look-ahead technique along with a way point following strategy. Results simulate one leader-follower tractor pair where the leader is forced to take an abrupt turn and experiences large oscillations of its drawbar arm indicating potential payload instability. However, the follower tractor maintains the flexible formation but keeps its payload stable. This highlights the robustness of the proposed approach where the follower vehicle can reject errors in human leader driving.
Robust Feature Selection by Filled Function and Fisher Score
Authors: Hamidzadeh Javad , kelidari Mahsa
Published: February 2022

Feature selection is essential in high-dimensional data analysis and filter algorithms, and due to their simplicity and fast speed, they have increasingly been drawing attention in recent years. Retaining all features in machine learning tasks is not only inefficient but the irrelevant and redundant features may have an adverse impact on the classification accuracy rate. Feature selection is an optimization problem which aims to transform the dataset’s high-dimensional space to a lower-dimensional space by utilizing the relevant and suited features. Feature selection is a time-consuming task, while it is very effective in saving the time devoted to the learning algorithm. In feature selection algorithms, filter algorithms are increasingly attractive due to their simplicity and fast speed. In this paper, we are going to introduce a supervised filter feature selection using filled function and fisher score (FFFS). Based on this criterion, we try to find a feature subset resulting in the least classification error rate. In order to prove the effectiveness of the proposed algorithm, Extensive experiments have been conducted on 20 high-dimensional real-world datasets. Experimental results reveal the superiority of the proposed algorithm to state-of-the-art algorithms in terms of minimum classification error rate. Results validated through statistical analysis indicated that the proposed algorithm is able to outperform the reference algorithms by minimizing the redundancy of the selected features. So, the selected feature subset can avoid serious negative impacts on the classification process in real-world datasets. In addition, this paper proves the ability of the proposed algorithm in selecting the most relevant features for classification tasks by applying different noise rates to the datasets. According to the experiments, the FFFS is less affected by noisy attributes in comparison with other algorithms. Thus, it is a reasonable solution in handling noise and avoiding serious negative impacts on the classification error rate in real-world datasets.
Segmentation and Classification of Retinal Fundus Images using Convolutional Neural Networks: A systematic review of methods and latest trends
Authors: Ilesanmi Ademola , Ilesanmi Taiwo , Idowu Oluwagbenga P. , Torigian Drew A. , Udupa Jayaram K.
Published: February 2022

The retina fundus images are critical diagnostic tools for the early detection of ophthalmic problems. Prompt diagnosis and treatment of eye-related problems are important to prevent blindness or vision loss. Recently, CNN algorithms have become effective in tasks relating to recognition, delineation, and classification. Therefore we propose a review to summarize different CNN algorithms for segmenting and classifying retinal fundus images. This review systematically searches different repositories for methods that use CNN for the segmentation and classification of retinal fundus images. A thorough screening of abstracts and titles to ascertain their relevance was done. A total of fifty-two studies were included in our review, with content such as database usage, disadvantages, and advantages. A comparison of two accuracies was also carried out with a graph depicting database usage. Important insights, limitations, observations, and future directions were elucidated. Finally, findings suggest that CNN algorithms produce good accuracies despite their limitations.
Sensitivity of A Frequency-Based Alignment-Free Approach For Phylogeny Reconstruction.
Authors: Hrytsenko Yana , Daniels Noah M. , Schwartz Rachel S.
Published: February 2022

Background: Phylogenies enrich our understanding of how genes, genomes, and species evolve. Traditionally, alignment-based methods are used to construct phylogenies from genetic sequence data; however, this process can be time-consuming when analyzing the large amounts of genomic data available today. Additionally, these analyses face challenges due to differences in genome structure, synteny, and the need to identify similarities in the face of repeated substitutions resulting in loss of phylogenetic information contained in the sequence. Alignment Free (AF) approaches using k-mers (short subsequences) can be an efficient alternative due to their indifference to positional rearrangements in a sequence. However, these approaches may be sensitive to k-mer length and the distance between samples.Results: In this paper, we analyzed the sensitivity of an AF approach based on k-mer frequencies to these challenges using cosine and Euclidean distance metrics for both assembled genomes and unassembled sequencing reads. Quantification of the sensitivity of this AF approach for phylogeny reconstruction to branch length and k-mer length provides a better understanding of the necessary parameter ranges for accurate phylogeny reconstruction. Our results show that a frequency-based AF approach can result in accurate phylogeny reconstruction when using whole genomes, but not stochastically sequenced reads, so long as longer k-mers are used. Conclusions: In this study, we have shown an AF approach for phylogeny reconstruction is robust in analyzing assembled genome data for a range of numbers of substitutions using longer k-mers. Using simulated reads randomly selected from the genome by the Illumina sequencer had a detrimental effect on phylogeny estimation. Additionally, filtering out infrequent k-mers improved the computational efficiency of the method while preserving the accuracy of the results thus suggesting the feasibility of using only a subset of data to improve computational efficiency in cases where large sets of genome-scale data are analyzed.
E-Health and M-Health Interventions to Improve Eating Behaviour of People with a Lower Socioeconomic Position: A Scoping Review of Behaviour Change Techniques
Authors: Ronteltap Amber , Bukman Andrea J. , Nagelhout Gera E. , Hermans Roel C.J. , Hosper Karen , Haveman-Nies Annemien , Lupker Remko , Bolman Catherine A.W.
Published: February 2022

Specific approaches are needed to reach and support people with a lower socioeconomic position (SEP) to achieve healthier eating behaviours. There is a growing body of evidence suggesting that e-health tools exhibit potential to address these needs because of its specific features that enable application of various behaviour change techniques (BCTs). The overall aim of this scoping review is to identify the BCTs that are used in diet-related e-health and m-health interventions targeted at people with a low SEP. The systematic search was performed in 3 databases, using terms related to e/m-health, diet quality and socioeconomic position. A total of 17 full text papers were included. The average number of BCTs per intervention was 6.9 (ranged 3-15). BCTs from the cluster ‘Goals and planning’ were applied most often (25x), followed by the clusters ‘Shaping knowledge’ (18x) and ‘Natural consequences’ (18x). Other frequently applied BCT clusters were ‘Feedback and monitoring’ (15x) and ‘Comparison of behaviour’ (13x). Whereas some BCTs were frequently applied, such as goal setting, others were rarely used, such as social support. Most studies (n=13) observed a positive effect of the intervention on eating behaviour (e.g. having breakfast) in the low SEP group, but this was not clearly associated with the number or type of applied BCTs. In conclusion, more intervention studies focused on people with a low SEP are needed to draw firm conclusions as to which BCTs are effective in improving their diet quality. Also, further research should investigate combinations of BCTs, the intervention design and context, and the use of multicomponent approaches. We encourage intervention developers and researchers to describe interventions more thoroughly, following the systematics of a behaviour change taxonomy, and to select BCTs knowingly.
Time-resolved smoothness of distributed brain activity tracks conscious states and unifies emergent neural phenomena
Authors: Nanda Aditya , Johnson Graham , Mu Yu , Ahrens Misha , Chang Catie , Englot Dario , Breakspear Michael , Rubinov Mikail
Published: February 2022

Much of systems neuroscience posits that emergent neural phenomena underpin important aspects of brain function. Studies in the field variously emphasize the importance of distinct emergent phenomena, including weakly stable dynamics, arrhythmic 1/f activity, long-range temporal correlations, and scale-free avalanche statistics. Few studies, however, have sought to reconcile these often abstract phenomena with interpretable properties of neural activity. Here, we developed a method to efficiently and unbiasedly generate model data constrained by interpretable empirical features in long multiregional neurophysiological recordings. We used this method to ground several major emergent neural phenomena to time-resolved smoothness, the correlation of distributed brain activity between adjacent timepoints. We first found that in electrocorticography recordings, time-resolved smoothness closely tracked transitions between conscious and anesthetized states. We then showed that a minimal model constrained by time-resolved smoothness, variance, and mean, captured dynamical and statistical emergent neural phenomena across modalities and species. Our results thus decouple major emergent neural phenomena from network mechanisms of brain function, and instead couple these phenomena to spatially nonspecific, time-resolved changes of brain activity. These results anchor several theoretical frameworks to a single interpretable property of the neurophysiological signal and, in this way, ultimately help bridge abstract theories of brain function with observed properties of brain activity.
Thermoelectric signature of quantum critical phase
in a doped spin liquid candidate
Authors: Wakamatsu Kodai , Suzuki Yuji , Fujii Takenori , Miyagawa Kazuya , Taniguchi Hiromi , Kanoda Kazushi
Published: February 2022

Quantum spin liquid is a nontrivial magnetic state of longstanding interest, in which spins are strongly correlated and entangled but do not order1, 2; further intriguing is its doped version, which possibly hosts strange metal and unconventional superconductivity3. Promising and currently the only candidate of the doped spin liquid is a triangular-lattice organic conductor, κ-(BEDT-TTF)4Hg2.89Br8, recently found to hold metallicity, spin-liquid-like magnetism and BEC-like superconductivity4-6. The nature of the metallic state with the spin-liquid behaviour is awaiting to be further clarified. Here, we report the thermoelectric signature that mobile holes in the spin liquid background is in a quantum critical state and it pertains to the BEC-like superconductivity. The Seebeck coefficient divided by temperature, S/T, is enhanced on cooling with logarithmic divergence indicative of quantum criticality. Furthermore, the logarithmic enhancement is correlated with the superconducting transition temperature under pressure variation, and the temperature and magnetic field profile of S/T upon the superconducting transition change with pressure in a consistent way with the previously suggested BEC-BCS crossover. The present results reveal that the quantum criticality in a doped spin liquid emerges in a phase, not at a point, and is involved in the unconventional BEC-like nature.
Aptamer Loaded Superparamagnetic Beads For Selective Capturing And Gentle Release of Activated Protein C
Authors: Hamedani Nasim Shahidi , Happich Felix Lucian , Klein Eva-Maria , Rühl Heiko , Mayer Günter , Müller Jens , Pötzsch Bernd
Published: February 2022

Activated protein C (APC) is a serine protease with anticoagulant and cytoprotective activities which make it an attractive target for diagnostic and therapeutic applications. In this work, we present one-step activation of APC from a commercial source of protein C (PC, Ceprotin®) followed by rapid and efficient purification using the APC-specific aptamer HS02-52G loaded on MyOne superparamagnetic beads. Due to the Ca2+-dependent binding of APC to HS02-52G, an efficient capturing of APC was applied in the presence of Ca2+ ions, while a gentle release of captured APC was achieved in the elution buffer containing low EDTA concentration (5 mM). The captured and eluted APC showed more than 95% purity according to an enzyme-linked fluorescent assay (VIDAS® Protein C). The purification yield of 45% was calculated when 4.2 µg APC was used, however this yield reduced to 21% if the starting amount of PC increased to 28.5 µg. Altogether, this method is recommended for rapid and efficient PC activation and APC purification. The purified APC can be used directly for downstream processes where high concentration of pure and active APC is needed.
Intensifying Camel Productivity through Integrated Control of Surra within the Somali ecosystem of the Horn of Africa
Authors: Nuur Abdullahi Sheikh Mohamed , Awale Mousa Mohamed , Hersi Abdullahi A. , Awale Ismail A. , Awale Nashaad Fa. , Ali Yasir Hu. , Ismail Mohamoud Yu. , Chemuliti Judith K.
Published: February 2022

A two phase (10 November to 21 December 2019 dry season, and 6 June to 11 July 2021 rainy season) cross sectional Parasitological, Haematological and Entomological survey was carried out in Somaliland’s Saahil and Togdheer regions. A total of 390 and 395 camels were bled during first and second phase respectively to determine the prevalence of camel trypanosomosis and trap transmitting vectors. Thin and thick smears from Buffy coat and from direct venous blood samples were screened. Out of 390, only 2 camels (0.5%) from Saahil region were positive in first phase while out of 395, 68 camels, 67 Saahil and 1 Togdheer (17.2 %) were positive in second phase. Prevalence of Trypanosoma evansi (T. evansi) infection recorded were (10.6 %), (5.3%) and 1.3% for camels with poor, fair and good body conditions respectively and were statistically significant (P =0.002). No significant prevalence differences between sex and age recorded. Micro-hematocrit method was used to determine packed cell volume (PCV). Animals with (PCV) < 25% were considered anemic and prevalence was negatively correlated to PCV. Biting flies (vectors) were trapped using NZI trap. Traps were set and emptied 48 hours post setting in both regions and phases. Two families of vectors- Tabanidae and Muscidae were identified. The study revealed camel trypanosomosis is enzootic in the region. The disease and its vectors are strongly related to ecology and season.
A multicenter retrospective study of 239 patients aged over 70 years with diffuse large B-cell lymphoma in China
Authors: Yang Chunli , Li Qiaoer , Li Li , Xie Ke , Zhang Yakun , Han Yunwei , Zou Liqun
Published: February 2022

BackgroundDiffuse large B-cell lymphoma (DLBCL) is the most common aggressive lymphoma subtype worldwide and frequently occurs in the elderly population. However, there was a lack of large series of data regarding the clinical profiles of over 70 years in DLBCL patients in China. We aim to summarize this population’s clinical features and survival outcomes in the real world.MethodsThe multicenter retrospective study was conducted in Western China from Jan 2012 to July 2020 to investigate clinical features and survival outcomes of 239 DLBCL patients over 70 years. All patients underwent pre-treatment evaluations, treatment, and follow-up at local hospitals. The primary endpoints of this study were progression-free survival (PFS) rate and overall survival (OS) rate at two years. The second endpoints included median PFS and OS, 5-year PFS and OS rates, and adverse events during treatment.ResultsWith a median follow-up of 50 months (range, 1-102), the 2-year PFS and OS rates were 53.0% (95% CI: 46.5-59.5) and 65.5% (95% CI: 59.4-71.2). The median PFS and OS were 42.1 months and 96.4 months, and the 5-year PFS and OS rates were 44.7% (95% CI: 38.0-51.4) and 56.1% (95% CI: 49.4-62.8). Hematological toxicities were the most common adverse effects in this study, accounting for 90.4%, and leukopenia was the most frequently observed ≥ grade 3 events. Moreover, we observed that no rituximab-containing treatment and chemotherapy cycles < 6 were significantly associated with inferior survival. Furthermore, in the younger than 80 years group, reduced chemotherapy dose was associated with remarked shorter OS; the 2-y OS rate was 74.4% (95% CI: 67.0-81.8) in full dose group in comparison with 67.1% (95% CI: 51.8-82.4) in decreased dose group, p 0.044.ConclusionsOur study indicated that rituximab, enough treatment cycles, full chemotherapy dose should be administered for elderly DLBCL patients under the balance of benefit and risk.
Influence of monocalcium phosphate on the properties of bioactive magnesium phosphate bone cement
Authors: Lv Shaochun , Qu Tianyu , Al-Ward Hisham , Mu Liting , Qiu Hongbin , Zhang Yunlong
Published: February 2022

Background: The bone defects caused by different reasons led to deformity and dysfunction of human body. Considering the need for clinical application, it was essential for bone regeneration to exploit a scaffold with bioactive bone cement. In this paper, we fabricated bioactive magnesium phosphate bone cement (BMPC) at room temperature, then it was set at 37℃ and 100% humidity for 2h. Methods: The process was as follows. MgO was formed by calcining Mg2(OH)2CO3, MgO, KH2PO4 and carboxymethyl chitosan were mixed to form magnesium phosphate bone cement(MPC), then Ca(H2PO4)2 was added to neutralize alkaline product after MPC hydration to fabricate bioactive magnesium phosphate bone cement (BMPC). The influence of doped content of Ca(H2PO4)2 on the properties of bone cement was discussed. Results: The results showed that Ca(H2PO4)2 and carboxymethyl chitosan can adjust the setting time of bone cement within the scope of 8 minute and 25 minute. The compressive strength increased first and then decreased. After 48h without additional pressure, the compressive strength reached the maximum value, so it was about of 38.6 MPa. Ca(H2PO4)2 and carboxymethyl chitosan can play a synergistic role in regulating the BMPC properties. BMPC was degradable in the simulated body fluid (SBF). The results of cytotoxicity experiment and laser confocal microscopy experiment indicated that BMPC fabricated at room temperature had better biocompatibility and degradability, which was more consistent with clinical operation requirement.Conclusions: BMPC can be used as a promising orthopedic material, and it can meet with the needs for repairing bone defects.
A New Method for Axis Adjustment of the Hydro-generator Unit Using Machine Learning
Authors: Cao Jie , Li Yang , Qu Zhaoyang , Dong Yunchang , Liu Yaowei , Zhang Ruxuan
Published: February 2022

The power quality and efficiency of the hydro-power station depend on the stable operation of the hydro-generator unit, which needs to continue to operate and it is prone to axis failure. Therefore, to adopt effective axis adjustment technology to eliminate faults. This paper proposes a new method for axis adjustment of hydro-generator unit based on an improved grey prediction model and swarms intelligence optimization neural network. First of all, it proposes a sequence acceleration translation and mean value transformation method, which is used to pre-process the axis net total swing sequence that exhibits oscillating fluctuations. It uses e1 and e2 factor transformation to establish an improved axis net total swing gray prediction model. Then, the advanced flamingo search algorithm is used to search the maximum value of the sine function of the net total pendulum of the axis, and the axis adjustment orientation is obtained. This method solves the problem that GM(1, 1) can only be predicted by monotone sequence in the past and the problem that the search algorithm is easy to fall into local optimum, effectively improves the calculation efficiency of axis and shorts the search time. Simulation examples show that the proposed method can significantly improve accuracy of axis adjustment. This method greatly improves the efficiency of azimuth search for axis adjustment.
Efficacy and safety of anti-PD-1 monotherapy and combination therapy in Chinese advanced Gastric cancer: a real-world study
Authors: Li Tao , Liu Tingting , Zhao Lei , Liu Lu , Zheng Xuan , Wang Jinliang , Zhang Fan , Hu Yi
Published: February 2022

Purpose: Anti-PD-1 inhibitor, pembrolizumab, has been approved for the treatment of locally advanced or metastatic gastric or gastroesophageal junction cancer (GC/GEJC) patients. Our study aimed to evaluate the efficacy and safety profile of anti-PD-1-based treatment in Chinese advanced or metastatic GC/GEJCs and population with poor clinical conditions in a real-world setting.Methods: A retrospective cohort study was conducted and 54 patients were identified and included in our analysis, including 19 patients treated with anti-PD-1 monotherapy and 35 patients treated with anti-PD-1 combination therapy. Demographic and clinical information were evaluated. Clinical response, survival outcomes and safety profile were measured and analyzed. Results: In overall cohort, median overall survival (OS) was 11.10 months (95%CI, 7.05-15.15) and median progression-free survival (PFS) was 3.93 months (95%CI, 2.47-5.39). 16.7% patients reached clinical response and 72.2% patients got disease control. Prolonged OS and PFS and increased clinical response were observed in combination group compared with monotherapy group, although statistical significance was not reached. In subgroups with live metastases or elevated baseline NLR level, combination therapy outperformed anti-PD-1 alone in survival outcomes. 50% and 16.7% of the overall cohort experienced treatment-related adverse events (TRAEs) of any grade and grade 3-5. Conclusions: Anti-PD-1-based monotherapy and combination therapy showed favorable survival outcomes and manageable safety profile in advanced or metastatic GC/GEJCs. Specific population might benefit from combination therapy. Further study with larger sample size is needed.
Silage of Rehydrated Corn And Sorghum Grain Without And With Amylolytic Enzyme
Authors: Silva Janaina Tayna , De Oliveira Euclides Reuter , Gandra Jefferson Rodrigues , Neves Nathálie Ferreira , Gabriel Andrea Maria de Araújo , Monção Flávio Pinto , Okadad Elaine Sayuri Miyagi , Andrade Wagner da Paz , Fernandes Alexandre Rodrigues Mendes , Peixoto Eduardo Lucas Terra
Published: February 2022

Aimed of this work was to evaluate rehydrated corn and sorghum grains silages, with and without α-AMYLASE, on fermentation profile, nutritional value, digestion and metabolism on diets for sheep. Two experiments were conducted. In the first experiment 28 silos were divided into: 1- RSGS (rehydrated sorghum grain silage); 2- RSGS+A (rehydrated sorghum grain silage + amylase,); 3- RCGS (rehydrated corn grain silage); 4 RCGS+A (rehydrated corn kernel silage + amylase). In experiment II, 12 lambs were distributed in: RSGS; RSGS+A; RCGS; RCGS+A. In experiment I, there was an effect of grain x enzyme interaction for GL MN. The enzyme reduced the NFC content. In experiment II intake of DM kg/day was not affected by the starch content in the diet, with an average of 1.2 kg/day meaning that the type of grain and the enzyme had no influence on the intake of animals. There was an interaction for the intake of starch (kg/day), blood urea and N-NH 3. Lambs fed with RCGS+A had a higher concentration of ruminal ammonia. The use of enzymes improved the fermentation profile of the silages. RSGS can replace RCGS in sheep feed without modifying nutrient intake and digestibility.
Comprehensive Study of Semi-Supervised Learning for DNA Methylation-based Supervised Classification of Central Nervous System Tumors
Authors: Tran Quynh T. , Alom Md Zahangir , Orr Brent A.
Published: February 2022

Background: Optimal treatment for cancer patients relies on accurate pathological diagnosis. The world health organization has defined almost 100 known central nervous system (CNS) tumors, making the histopathological diagnostic process particularly challenging. To help reduce variability, validation costs, and standardize the histopathological diagnostic process, supervised machine learning techniques using epigenetic data have been developed. These methods require large labeled training data sets to obtain clinically acceptable classification accuracy. However, labeling pathology data for machine learning models is time-consuming and resource-intensive, especially for rare tumor types. On the other hand, there is now abundance of unlabeled epigenetic data across multiple databases. To maximize the utility of both labeled and unlabeled data, semi-supervised learning (SSL) approach has been proposed and shown to be effective in genomic field. However, it has not yet been explored with epigenetic data nor demonstrated beneficial to CNS tumor classification.Results: This paper explores the application of semi-supervised machine learning on methylation data to improve accuracy of supervised learning models in classifying CNS tumors. We comprehensively evaluated 11 SSL methods and developed a novel combination approach including a self-training with editing using support vector machine (SETRED-SVM) as the base learner model with an L2-penalized, multinomial logistic regression model to obtain high confidence labels from a small labeled instances. Results across 8 differently trained random forest and neural net models show that SETRED-SVM followed with multinomial logistic regression approach is able to produce high confidence training data set, leading to a statiscally significant increase in prediction accuracy of 82 CNS tumors.Conclusions: The proposed combination of semi-supervised technique and multinomial logistic regression holds the potential to leverage the abundant publically available unlabeled methylation data effectively. Such an approach is highly beneficial in providing additional training examples, especially for scarce tumor types, to boost the prediction accuracy of supervised models.
Three-dimensional Structural Modeling (3D SM) and Joint Geophysical Characterization (JGC) of Hydrocarbon Reservoir: A Case Study of the Kadanwari field in Middle Indus Basin (MIB), Southeastern Pakistan
Authors: Khan Umair , Du Jiangfeng , Hussain Shafqat , Jiang Zhengwen , Ali Shahzad , Ali Ikram , Khan Majid , Zhang Baoyi
Published: February 2022

Complex structural geology generally leads to significant consequences for hydrocarbon reservoir exploration that needs a comprehensive methodology for complete comprehension. Despite a large number of existing wells in the Kadanwari field, Middle Indus Basin (MIB), southeastern Pakistan, the depositional environment of the Early Cretaceous stratigraphic sequence is still poorly understood, which has implications for regional geology as well as economic significance. To improve the understanding of depositional environment of complex heterogeneous reservoirs with associated 3D stratigraphic architecture, spatial distribution of facies and properties, and hydrocarbon prospects, a new methodology of three-dimensional structural modeling (3D SM) and joint geophysical characterization (JGC) is introduced in this research. JGC makes use of seismic interpretation-aided 3D SM, 3D seismic attributes analysis coupled with petrophysical modeling using 3D seismic reflection, and borehole data. Subsequently, the 3D SM reveals that the Kadanwari field experienced multiple stages of complex deformation dominated by NW to SW normal fault system, high relief horsts, half-graben, and graben structures. 3D SM and 3D fault system models (FSMs) further depict that the middle part of the sequence experienced more deformation compared to the surroundings of major faults with predominant oriented in S30°-45°E and N25°-35°W, azimuth as 148°–170° and 318°–345°, minimum (28°), mean (62°), and maximum (90°) dip angles. The applied variance edge attribute better portrays the inconsistency of the seismic data associated with faulting and estimated high reflection sediments presumed to be potential hydrocarbon traps. The high amplitude and loss of frequency anomalies of sweetness and root mean square (RMS) amplitude attributes represent cleaner and payable sand-rich shoreward facies revealing gas saturated sand, while relatively low amplitude and high-frequency anomalies indicate sandy shale, shale, and pro-delta facies, unfavorable zones for gas potential. The quantitative petrophysical modeling result shows that E sand interval has good effective porosity (∅ eff ) and hydrocarbon saturation (S hc ) compared to G sand interval. The derived average petrophysical properties, such as volume of shale (V shale ), average porosity (∅ avg ), ∅ eff , water saturation (S W ), and S hc of the E sand interval are 30.5%, 17.4%, 12.2%, 33.2%, 70.01%, respectively. The newly introduced 3D SM and JGC workflow is an effective tool for highlighting potential areas of high quality reservoir development.
Cryptotanshinone Inhibits Ovarian Tumor Growth and Metastasis by Degrading c-Myc and Attenuating the FAK Pathway
Authors: Guo Huijun , Zhao Guannan , Wang Yaohong , Zhang Wenjing , Zhu Bing-Mei , Dong Peixin , Watari Hidemichi , Tigyi Gabor , Yue Junming
Published: February 2022

Background
Cryptotanshinone (CT), a natural compound derived from Salvia miltiorrhiza Bunge (Danshen, a traditional Chinese medicine), has been shown antitumor activity in various cancers. However, it remains unclear whether CT has a potential therapeutic benefit against ovarian cancers. The aim of this study was to test the efficacy of CT in ovarian cancer cells in vitro and using orthotopically implanted HEY A8 human ovarian cancer cells into NSG mice to determine its antitumor efficacy and explore the molecular mechanism underlying CT’s antitumor effects.
Results
We found that CT inhibited the proliferation, migration, and invasion of OVCAR3 and HEY A8 cell while sensitizing the cell responses to chemotherapy drugs paclitaxel and cisplatin. CT also suppressed ovarian tumor growth and metastasis in immunocompromised mice orthotopically inoculated with HEY A8 cells. Mechanistically, CT degraded oncogene c-Myc by promoting ubiquitination and disrupting the interaction with its partner protein Max. CT also attenuated the FAK (focal adhesion kinase) signaling and degraded FAK in both cell lines. Knockdown of c-Myc using lentiviral CRISPR/Cas9 nickase resulted in reduction of FAK expression, which phenocopies the effects of CT and 10058-F4.
Conclusions
Our studies demonstrate that CT inhibits primary ovarian tumor growth and metastasis by degrading c-Myc and attenuating the FAK pathway.
First report on the bacterial community composition, diversity, and functions in Ramsar site of Central Himalayas, Nepal
Authors: Adhikari Namita Paudel , Adhikari Subash , Liu Keshao , Chen Yuying , Sharma Birendra Prasad , Paudel Ganesh , Liu Yongqin
Published: February 2022

Ramsar sites are wetlands of international importance covering major ecosystem processes and services. Bacterial communities play a significant role in the lacustrine ecosystem and release major nutrients in wetlands, yet little is known about controls over their distribution and abundance from the Ramsar site of Central Himalayas, Nepal. Thus, we studied the bacterial community composition, diversity, and functions in the wetlands (designed as Ramsar site, Ramsar no 2257) during the autumn and spring by using 16S rRNA gene-based Illumina MiSeq sequencing. We reported a pronounced variation in water physicochemical and biological properties (temperature, pH, Chl a, DOC, and TN), bacterial diversity, and community composition. Alpha diversity was highest in Autumn while beta diversity (based on unifrac distance) in spring. Our results uncovered the effect of nutrients on bacterial abundance, richness, and community composition. Most unique operational taxonomic units (OTUs) (58%) belonged to autumn, while 14% of the OTUs were shared between spring and autumn. Planctomycetes and Bacteroidetes dominated the spring exclusive OTUs; meanwhile, Actinobacteria dominated the autumn exclusive OTUs. Bacteria in these wetlands exhibited divergent roles; however, a higher abundance of bacteria associated with animal parasites and human pathogens indicated a public health risk. By disclosing the seasonal variation of bacterial community and their relationship with environmental factors, this first-hand work in the Ramsar site of Nepal will develop a baseline dataset for the scientific community that will assist in understanding the wetlands microbial ecology and biogeography.
Geo-Statistical Assessment of Spatial Variability of Soil Water-Holding Capacity for Optimal Irrigation Under Semi-Arid Vertisols in South India
Authors: J RAMACHANDRAN , Lalitha R. , Kannan S.Vallal , Sivasubramanian K. , Sankar G.R.Maruthi
Published: February 2022

Based on a field survey conducted in Lalgudi block, Tiruchirapalli district, Tamil Nadu, India, details pertaining to the crops grown, cropping pattern, land utilization and soil samples were collected from 20 locations under 7 different soil textures of semi-arid vertisols. Using the data, efficient geostatistical models have been explored to study the spatial variation of irrigation water requirement of paddy, sugarcane and banana grown in the study area. Field capacity and wilting point are two major soil physical properties that would influence the available plant water. These parameters were estimated with the pressure plate apparatus using soil samples collected in the block. Soil texture-wise assessment was made with regard to the field capacity, wilting point and soil water holding capacity based on the observations. The locations of Lalgudi block were grouped into three categories based on the mean and standard deviation of available water holding capacity, field capacity and wilting point parameters and were statistically assessed. The groups were made by considering the locations with values of a parameter lying under (i) < (Mean – SD); (ii) (Mean – SD) to (Mean + SD); and (iii) > (Mean + SD) limits. Geostatistics were applied for identifying the best interpolation method in order to acquire the spatial map of the available water holding capacity. An initial data exploration indicated about non-normal distribution of the available water holding capacity. Accordingly, log-transformation was made before kriging technique was used for the data. Ordinary kriging and Disjunctive kriging were explored with six models viz., Circular, Spherical, Exponential, Gaussian, Penta-spherical and Sine-Hole effect models and were used for spatial prediction. An estimate of Root Mean Square Error (RMSE) based onthe six models ranged from 2.1 to 2.5 for available water holding capacity parameter. The cross validation statistics indicated that Sine-Hole effect model with disjunctive kriging of available water holding capacity was superior for interpolation with minimum value of RMSE and moderate spatial dependency. The Sine-Hole effect model was found to overestimate the soil properties when interpolation was carried out and gave mean prediction error of -0.07 which indicated that the model was highly efficient. With the available water holding capacity map of Lalgudi block, total available water, readily available water and irrigation interval of paddy, sugarcane and banana were estimated. The irrigation interval of paddy, sugarcane and banana were found to vary between 1-2, 3-5 and 2-4 days respectively within Lalgudi block. Adoption of spatial algorithms for estimating the crop water requirement would greatly help the irrigation planners and water policy makers to create efficient regional plans for making precision irrigation under semi-arid vertisols.
Influence of Lifestyle Patterns On Myopia In Students Aged 9 To 18 In Tianjin, China: A Latent Class Analysis
Authors: Cui Tingkai , Cao Yongjun , Liu Liyuan , Su Yuanyuan , Xi Wei , Gao Lei , Xiong Wenjuan , Zhang Xin
Published: February 2022

Purpose: This study aims to determine influence of lifestyle patterns on myopia and spherical equivalent refraction (SE) in school-aged children in Tianjin.Methods: Students aged 9 to 18 in grade 4 to 12 were recruited. Non-cycloplegic SE was obtained. A self-administration questionnaire was used to collect demographic and lifestyle information.Results: The overall prevalence of myopia of 8651 students was 81.5% and that of high myopia was 8.88%. Myopia and high myopia rate increased dramatically with grade (p<0.001). Students were classified into 3 groups based on latent class analysis (LCA). Students in class 2 had the lowest myopia rate of 74.1% and those in class 1 had the highest rate of 82.8%. Binary logistic regression analysis showed that class 1 and 3 had a higher risk for myopia compared to class 2 (OR= 1.68, p<0.001; OR= 1.46, p=0.004). The risk for high myopia of Class 1 and 3 were also higher compared to that of class2 (OR= 2.41, p<0.001; OR= 2.13, p=0.006). General linear model showed that SE of students in class 1 and 3 was lower than that of students in class 2 (β=-0.82, p<0.001; β=-0.68, p<0.001).Conclusion: Lifestyle is associated with myopia and SE value.
Analyzing Self-Evaluation Capacity Scores Related to Infectious Disease Control in International Health Regulations during the First Year of the COVID-19 Pandemic
Authors: Satria Fauzi Budi , Tsai Feng-Jen , Turbat Battsetseg
Published: February 2022

Background: COVID-19 is hitting the world hard despite the requirement to establish minimum core capacity by the International Health Regulations (IHR) 2005. In addition, COVID-19 was most severe in countries reporting good IHR capacities, such as the US, UK, Germany, and France. This study aimed to identify changes in the average score of member countries' IHR self-evaluation capacity (e-SPAR) in 2020 compared to 2019, then analyze the factors that influenced it. For that purpose, first, we calculated the absolute difference between e-SPAR scores in 2019 and 2020 of 154 countries. Then Wilcoxon Sign-rank test was performed to identify its significance. After Chi-Square Test, Multiple Regression Analysis was applied to analyze the relationship between countries’ changes in e-SPAR scores and their COVID-19’s case fatality rate (CFR), Human Development Index, Civil Liberties, and Government Effectiveness. Results: Our findings showed that the average e-SPAR score in 2020 was significantly higher than in 2019. Of the 154 countries, the e-SPAR score of 98 countries (63.63%) was increased in 2020. Among this group, 63 countries (64.28%) were middle-income countries. Capacities about Risk Communication, National Health Emergency Framework, and Ports of entry were the three capacities that experienced the most significant increase. Meanwhile, among 56 of 154 countries (36.36%) whose scores did ​​​​not increase, 26 countries (46.42%) were high-income countries. The IHR coordination and National Focal Points, Food Safety, and Risk Communication were the only capacities that significantly decreased during the pandemic. Our model showed that COVID-19 CFR influenced the changes in e-SPAR scores of 154 countries (p<0.01), as well as the countries whose score increased (p<0.05), but not the countries whose e-SPAR score did not increase.Conclusion: We concluded that the COVID-19 pandemic is an alarm for countries to re-evaluate their capacities more carefully. Continues external evaluation approach like Joint External Evaluation (JEE) should be a necessary approach for future preparation.
Cairo University Fibrosis Index (CUFI): A MicroRNA Based Score for Accurate Prediction of Hepatic Fibrosis: A Biopsy Controlled Study
Authors: Abdel-Haleem Hanan Abdel-Haleem , Zekri Abdel Rahman Zekri , Moniem Mostafa Abdel Moniem , Ray Ahmed Al Ray Al , Omar Mona Omar , Omran Mohamed Omarn , Omran Dalia Omran
Published: February 2022

Background: The exact identification of liver fibrosis is mandatory for customizing therapy and controlling complications. The aim of the current study is to measure the ability to circulate miRNAs; in the diagnosis of hepatic fibrosis.Methods: Routine laboratory, liver biopsy, and histopathological investigations were done on seventy HCV patients. In addition, estimation of HCV-RNA, serum micro RNA (miRNA)-122, 221, 192, 224, 375, and 885 were done by PCR. To assess the ability of each miRNA, the area under the receiver operating characteristics (AUC) curves were plotted. Significant miRNA were analyzed by linear regression analysis in a stepwise pattern to develop a score for pointing out significant fibrosis. Moreover, the following scores were calculated: aspartate aminotransferase (AST)/alanine aminotransferase (ALT) ratio (AAR), aspartate to platelet ratio index (APRI), FIB-4 score, Hui index, Fibrosis Index (FI), Fibro-Q, Fibro-Alfa Biotechnology Research Center (BRC) score, and Gotebörg University Cirrhosis Index (GUCI).Results: Patients with significant and advanced fibrosis have significantly lower miR-122. MiR-122, FIB4, total bilirubin, and miR-855 proved to be independent predictors of significant fibrosis in univariate analysis. A novel score; Cairo University Fibrosis Index (CUFI) based on microRNA 122, FIB4, bilirubin, and microRNA 855 were formulated for the identification of significant liver fibrosis. The AUC of the score, for predicting significant and advanced hepatic fibrosis was 0.85 and 0.81. This AUC was higher than those of other common fibrosis scores.Conclusion: Cairo University Fibrosis Index proved to be better than other existing scores in assessing fibrosis in chronic hepatitis C (CHC) patients.