bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of Skeletal Jaw Relation by Different Cephalometric Angles for Sample of Kurdish Young Adults in Sulaimani City-A Cephalometric Study
Authors: Mohammed Shiler Abdul Hammed , Ali Trefa Mohammed , Rashid Zhwan Jamal 
Published: June 2021

Abstract
Background/Objectives An accurate evaluation of skeletal sagittal jaw relationship has an important role in orthodontic diagnosis and treatment planning. This study was done to establish cephalometric norms of all types of malocclusion using ANB, Wits appraisal and Beta angle, and evaluate the significance of W angle in comparison to these parameters. Subjects and Methods Ninety pre-treatment lateral cephalograms of male and female patients aged 18-28 years from Sulaimani City that met the sample criteria were traced digitally by the Easy Dent 4 software program. The sample was divided into three groups of skeletal malocclusion, class I, II, and III, based on ANB angle, Beta angle, and Wits appraisal, each group consisting of 30 patients. For each subject the following cephalometric parameters were measured: ANB angle, Beta angle, Wits apprasial, and W angle.Statistical analysis The Statistical Package for Social Sciences was used for analyzing data. ANOVA test was used to compare means of the three study groups. The post-hoc test was used to compare each two groups, Pearson correlation coefficient (r) was used to assess the strength of correlation between two numerical variables, and coefficient of variability was used to measure the extent of variability of each variable in relation to the population. The p value of ≤ 0.05 was considered statistically significant. ResultsSignificant differences were found in the ANB angle, Beta angle, Wits appraisal and W-angle in all 90 patients. The coefficient of variability showed that Wits appraisal was the most variable parameter and W angle was the least variable parameter. Conclusions ANB angle, Beta angle, Wits appraisal and W-angle are significant parameters to assess the sagittal jaw relationship. The use of W angle, along with other parameters, can provide more accurate assessment of the sagittal skeletal jaw relationship as it has the least coefficient of variance; it should therefore enable better diagnosis and treatment planning for patients.
The Effectiveness and Safety of Moxibustion for Peripheral Facial Paralysis：A Protocol for Systematic Review and Meta-Analysis
Authors: Xiang Shanshan , Fang Ting , Ren Changan , Qi Junnan , Guo Zheng , Liu Fushui , Yang Wenlong 
Published: June 2021

Abstract
Background: Moxibustion has been used in treating patients with Peripheral Facial Paralysis(PFP), but its effectiveness and safety have not been systematically evaluated. Therefore, the objective of this review is to comprehensively assess the effectiveness and safety of moxibustion for PFP.Methods: We will conduct a systematic document retrieval of databases from inception to March 18, 2021, including Embase, Cochrane Library, Pubmed, Chinese databases SinoMed, Chinese National Knowledge Infrastructure (CNKI), Chinese Scientific Journals Database and Wanfang Data (WF). Reviewers will independently retrieve databases, identify trials, extract data, and evaluate the quality of eligible randomized controlled trials(RCTs). The outcomes will include: the effective rate, the House-Brackmann (H-B) score, Facial Disability Index (FDI), and side effects. The quality of eligible RCT will be assessed by the Cochrane risk-of-bias. Meta-analysis will be processed by the Cochrane Collaboration’s RevMan 5.3.0.Discussion: This review will provide comprehensive evidence of moxibustion for PFP.Systematic review registration: PROSPERO CRD42020207068
Comparison of Sub-Series with Different Lengths Using Şen-Innovative Trend Analysis
Authors: Alashan Sadık 
Published: June 2021

Abstract
Climate change causes trends in hydro-meteorological series. Traditional trend analysis methods such as Mann-Kendall and Spearman Rho are sensitive to correlated series and cannot detect non-parametric trends. Şen-innovative trend analysis method is launched to literature in order to overcome these restrictions. It does not require any restrictive assumptions as serial dependence and normal distribution and examines a main series as equally divided two sub-series. Şen multiple innovative trend analyses methodology is improved to detect partial trends on different sub-series but again equal lengths. Climate change nowadays more effects hydro-meteorological parameters according to last two or three decades and gives asymmetric trend change point on main time series. Due to asymmetric trend change points, it may be necessary to analyze sub-series with different lengths to use all measured data. In this study, Şen innovative trend analyses method is revised for these requirements (ITA_DL). The new approach compared with traditional Mann Kendall (MK) and Şen innovative trend analysis (Şen_ITA) gives successful and consistent results. ITA_DL gives four monotonic trends on Oxford May, July, September and October rainfall series although MK gives three monotonic trends on May, July and December and cannot detect trends on September and October. In the ITA_DL visual inspection, the December rainfall series does not show a trend that is monotonic or non-monotonic. Şen_ITA trend results are consistent with ITA_DL except September, although there are different trend slopes.
An MDP-Based Lifter Assignment Algorithm for Inter-Line Transportation in Semiconductor Fabrication
Authors: Shin Kyohong , Jang Hoon , Kim Hae Joong 
Published: June 2021

Abstract
As semiconductor device geometries continue to shrink, the semiconductor manufacturing process becomes increasingly complex. This usually results in unbalanced utilization of machines and decreases overall productivity. One way to resolve such a problem is to share the resource capacity between different lines divided by floors. To this end, designing an efficient lifter assignment method to more efficiently manage transfer requests (TRs) of wafer lots to different floors is required. Motivated by this, our study addresses the assignment of lifters for delivering wafer lots to different floors. Unlike previous studies, which consider the current state of the system, our study considers both the current and possible future states of the system. We formulate an optimization model based on the Markov decision process. Then, we design an efficient method as a solution using both clustering and tournament selection methods. Experiments based on historical data confirm the effectiveness of the proposed algorithm in reducing travel times and delivery delays compared to the benchmark rules in practice. Sensitivity analysis demonstrates the robustness of the proposed model as the number of TRs increased. The proposed approach is expected to yield significant economic savings in both operating costs and labor.
Aberrant Topological Organization and Age-Related Differences of Human Connectome in Subjective Cognitive Decline by Using Regional Morphology from Magnetic Resonance Imaging
Authors: Fu Zhenrong , Zhao Mingyan , He Yirong , Wang Xuetong , Li Xin , Kang Guixia , Han Ying , Li Shuyu 
Published: June 2021

Abstract
Subjective cognitive decline (SCD) is characterized by self-experienced deficits in cognitive capacity with normal performance in objective cognitive tests. While, the previous structural co-variance researches showed particularly insights into understanding the structural alterations of brain in neurodegenerative diseases. However, the age-related variations in coordinated topological patterns of morphological networks in individuals with SCD remain poorly understood. In this study, 77 individual morphological networks were constructed including 42 normal controls (NC) and 35 SCD individuals from structural Magnetic Resonance Imaging (sMRI). A stepwise linear regression model was constructed to evaluate the differences of age-related alternation patterns of the network properties in individuals with SCD compared with NC. Compared with NC, the properties of integration and segregation in individuals with SCD were lower, and the aberrant metrics were negatively correlated with age in SCD, while not in NC. The connections of rich-club were persevered but the connections of paralimbic system were disrupted in SCD compared with NC. In addition, age-related differences of nodal global efficiency mainly distributed in prefrontal cortex regions. In conclusion, the age-related disruption of topological patterns in SCD provide evidence that SCD population are at high risk to cognitive decline further.
Counting Blessings Promotes an Athlete’s Sleep Quality Before an Upcoming Competition A Single-Case Study
Authors: Chen Jian-Hong , Kuo Chih-En , Chen Lung Hung 
Published: June 2021

Abstract
Background

Promotion of sleep quality without medication is a critical issue, which may directly or indirectly influence sports performance. This study adopted electroencephalography (EEG) to investigate gratitude intervention for improving elite athletes’ sleep quality before the National Games.
Case presentation:

We recruited a 20-year-old elite female Taekwondo athlete as a participant. Before the National Games, the athlete wore a micro EEG device for five days to collect baseline data and then counted her blessings as a gratitude intervention for the subsequent five days. The sleep EEG analysis included the power ratio and the polynomial regression trends in the 0.5-4 Hz band for N3 sleep and in the 0.5-4 Hz and 8–13 Hz bands for all-night sleep. Sleep quality was improved after counting blessing both subjectively and objectively. The polynomial regression curves for the 10 days of recording showed an upward tendency of power in the 0.5-4 Hz band for N3 and a downward tendency in the 8–13 Hz band.
Conclusion

This study describes a useful wearable EEG device for evaluating sleep during the competition preparation period. In addition, the brief gratitude intervention can be applied in practice to enhance sleep quality for elite athletes during periods of high tension.
Analyzing Driving Forces of China’s Carbon Emissions From 1997-2040 and the Potential Emission Reduction Path: Through Decomposition and Scenario Analyses
Authors: Song Ce , Zhao Tao , Wang Juan 
Published: June 2021

Abstract
To assess the evolution trend of China's carbon emissions (CEs) and related driving factors, this paper used scenario analysis to predict China's CEs from 2017 to 2040 at the industrial level. Then, LMDI decomposition model was applied to evaluate the driving forces of CEs changes during 1997-2040. Finally, the ST-LMDI model was used to explore the CEs reduction potential and the potential reduction path at provincial level. The results showed that (1) as the reduction of energy intensity cannot offset the growth of industrial scale, the CEs of all industries have shown an increasing trend from 1997 to 2017; (2) In the current policy scenario, China's CEs cannot reach the peak before 2040. And only in the sustainable development scenario, the CEs of the three industries will all reach the peaks before 2030. And the development of non-fossil energy will reduce CEs by more than 30%; (3) Hebei, Shanxi, Inner Mongolia, Ningxia, and Heilongjiang are key provinces and improving energy efficiency of the secondary industry is a potential way to promote CEs reduction.
Semi-Automated Identification of Biomedical Literature: A Proof of Concept Study
Authors: Adam Gaelen P. , Pappas Dimitris , Papageorgiou Haris , Evangelou Evangelos , Trikalinos Thomas A. 
Published: June 2021

Abstract
Background: The typical approach to literature identification involves two discrete and successive steps: (i) formulating a search strategy (i.e., a set of Boolean queries) and (ii) manually identifying the relevant citations in the corpus returned by the query. We have developed a literature identification system (Pythia) that combines the query formulation and citation screening steps and uses modern approaches for text encoding (dense text embeddings) to represent the text of the citations in a form that can be used by information retrieval and machine learning algorithms.Methods: Pythia incorporates a set of natural-language questions with machine-learning algorithms to rank all PubMed citations based on relevance. Pythia returns the 100 top-ranked citations for all questions combined. These 100 articles are exported, and a human screener adjudicates the relevance of each abstract and tags words that indicate relevance. The “curated” articles are then exploited by Pythia to refine the search and re-rank the abstracts, and a new set of 100 abstracts is exported and screened/tagged, until convergence (i.e., no other relevant abstracts are retrieved) or for a set number of iterations (batches). Pythia performance was assessed using seven systematic reviews (three prospectively and four retrospectively). Sensitivity, precision, and the number needed to read were calculated for each review. Results: The ability of Pythia to identify the relevant articles (sensitivity) varied across reviews from a low of 0.09 for a sleep apnea review to a high of 0.58 for a diverticulitis review. The number of abstracts that a reviewer had to read to find one relevant abstract (NNR) was lower than in the manually screened project in four reviews, higher in two, and had mixed results in one. The reviews that had greater overall sensitivity retrieved more relevant citations in early batches, but neither study design, study size, nor specific key question significantly affected retrieval across all reviews.Conclusions: Future research should explore ways to encode domain knowledge in query formulation, possibly by incorporating a "reasoning" aspect to Pythia to elicit more contextual information and leveraging ontologies and knowledge bases to better enrich the questions used in the search.
Concurrently Produce a Novel High-Potency Sweetener (Glycyrrhetic Acid 3-O-Mono-β-D-glucuronide) and Lignocellulolytic Enzymes using Plant Entophytic Chaetomium Globosum DX-THS3 by Solid-State Fermentation
Authors: Gao Boliang , Xiao Yiwen , Zhang Qian , Sun Junru , Zhang Zhibing , Zhu Du 
Published: June 2021

Abstract
Licorice straw was used for the first time as a medium for glycyrrhetic acid 3-O-mono-β-D-glucuronide (GAMG) and lignocellulosic enzyme production via solid-state fermentation (SSF) of endophytic fungus Chaetomium globosum DX-THS3. Under optimal fermentation conditions, the percent conversion of glycyrrhizin reached 90% in 15 days, whereas the control needed 35 days to achieve the same result. The productivity of optimization (P=2.1 mg•g-1•day-1) was 2.33-fold that of non-optimization (P=0.9 mg•g-1•day-1). Meanwhile, high activities of filter paper enzyme (FPase) (234.6 U/g), carboxymethyl cellulase (CMCase) (29.25 U/g), xylanase (72.52 U/g), and β-glucuronidase activity (264.17 U/g) were obtained faster than those in the control during SSF. Our study provides a novel and efficient strategy for GAMG production and indicates C. globosum DX-THS3 as a potential producer of lignocellulolytic enzymes.
New Climatic Zones in Iran: A Comparative Study of Different Empirical Methods and Clustering Technique
Authors: Abbasi Faezeh , Bazgeer Saeed , Kalehbasti Parviz Rezazadeh , Oskoue Ebrahim Asadi , Haghighat Masoud , Kalebasti Pouya Rezazadeh 
Published: June 2021

Abstract
It is a scientifically novel insight to classify the climate of a region using empirical methods together with clustering technique for practical usage in agricultural and industrial sectors. The main objective of this study is to compare the empirical approach to climate classification (Thornthwaite and Mather, De Martonne, the Extended De Martonne and the IRIMO (I.R. of Iran Meteorological Organization)) with clustering technique, Ward’s hierarchical agglomerative method over Iran. The maximum and minimum temperatures and precipitation data of 356 weather stations are used from IRIMO databases. 35 synoptic weather stations are selected for detailed inspection based on appropriate geographical distribution and availability of a continuous 50-year data (1966–2015). Compared with the three empirical reference methods of climate classification, the Thornthwaite and Mather method clearly shows the role of water bodies and air masses for determining the climate type in different regions. This factor is identified as the main advantage of this method over the three others. This superiority is the most visible for the highlands/mountainous regions, in the vicinity of the Zagros Mountains, and in the western regions of Iran. As a case in point, while in the De Martonne and the Extended De Martonne methods, the Zagros storm cell is climatically classified similar to patchy areas in Caspian Sea coastal zone, this cell is correctly identified as a separate zone in the Thornthwaite and Mather method. The results revealed that the clusters obtained from Ward’s algorithm are comparable to those of empirical climate classifications, particularly Thornthwaite and Mather method.
Removal of COVID-19 Spike Protein, Whole Virus, Exosomes and Exosomal microRNAs by the Hemopurifier® Lectin-Affinity Cartridge in Critically Ill Patients with COVID-19 Infection
Authors: Amundson Dennis E. , Shah Usman S. , de Necochea-Campion Rosalia , Jacobs Michael , LaRosa Steven P. , Fisher Charles J. 
Published: June 2021

Abstract
Coronavirus − 19 (COVID-19) has rapidly spread throughout the world resulting in a significant amount of morbidity and mortality. Despite advances in therapy, social distancing, masks, and vaccination many places in the world continue to see an increase in the number of cases and deaths. Viremia is commonly present in severely ill patients with COVID-19 infections and is associated with organ dysfunction and poor outcomes. Exosomes released by activated cells have been implicated in the pathogenesis of COVID-19 infection. We report the experience of two cases of critically ill COVID-19 patients treated with the Hemopurifier; a lectin affinity cartridge designed to remove mannosylated viruses and exosomes. Both patients tolerated the Hemopurifier sessions without adverse effects. In the first patient removal of exosomes and exosomal microRNAs was associated with improved coagulopathy, oxygenation, and clinical recovery, while in a second patient removal of COVID-19 by the Hemopurifier cartridge was observed. The Hemopurifier is currently under further investigation in up to 40-patients in a safety and feasibility study in ICU patients with COVID-19 infection.
A Framework to Predict the Applicability of Gene Signatures for Improving Prognostic Prediction
Authors: Yao Kevin , Tong Chun-Yip , Cheng Chao 
Published: June 2021

Abstract
To improve cancer precision medicine, prognostic and predictive biomarkers are critically needed to aid physicians in deciding treatment strategies in a personalized fashion. Due to the heterogeneous nature of cancer, most biomarkers are expected to be valid only in a subset of patients. Furthermore, there is no current approach to determine the applicability of biomarkers. In this study, we propose a framework to improve the clinical application of biomarkers. As part of this framework, we develop a clinical outcome prediction model (CPM) and a predictability prediction model (PPM) for each biomarker and use these models to calculate a prognostic score (P-score) and a confidence score (C-score) for each patient. Each biomarker’s P-score indicates its association with patient clinical outcomes, while each C-score reflects the biomarker applicability of the biomarker’s CPM to a patient and therefore the confidence of the clinical prediction. We assessed the effectiveness of this framework by applying it to three biomarkers, Oncotype DX, MammaPrint, and an E2F4 signature, which have been used for predicting patient response, pathologic complete response versus residual disease to neoadjuvant chemotherapy (a classification problem), and recurrence-free survival (a Cox regression problem) in breast cancer, respectively. In both applications, our analyses indicated patients with higher C scores were more likely to be correctly predicted by the biomarkers, indicating the effectiveness of our framework. This framework provides a useful approach to develop and apply biomarkers in the context of cancer precision medicine.
Immediate Outcomes of Traumatic Brain Injury at a Tertiary Care Hospital Of Pakistan- A Retrospective Study
Authors: Khan Maria , Yaqoob Uzair , Hassan Zair , Uddin Muhammad Muizz 
Published: June 2021

Abstract
Background: Traumatic Brain Injury (TBI) is the leading cause of morbidity and mortality all over the world and the impact is much worse in Pakistan. The objective here is to describe the epidemiological characteristics of patients with TBI in our country and to determine the immediate outcomes of patients with TBI after the presentation.Method: This retrospective study was conducted at the Lady Reading Hospital. Data were extracted from the medical record room from January 1st to December 31st, 2019. The severity of TBI was based on Glasgow Coma Scale (GCS) and was divided into mild (GCS 13-15), moderate (GCS 9-12), and severe TBI (GCS <8) based on the GCS. SPSS v.23 was used for data analysis. Results: Out of 5047 patients, 3689 (73.1%) males and 1358 (26.9%) females. The most commonly affected age group was 0-10 years (25.6%) and 21-30 years (20.1%). Road Traffic accident was the predominant cause of injury (38.8%, n=1960) followed by fall (32.7%, n=1649). Most (93.6%, n=4710) of the TBIs were mild. After the full initial assessment and workup, and completing all first-aid management, the immediate outcome was divided into four, most frequent (67.2%, n=3393) of which was “disposed (discharged)”, and 9.3% (n=470) were admitted for further management.Conclusion: Our study represents a relatively conclusive picture of epidemiological data on the burden of TBI in Pakistan. Although a large proportion of patients had a mild TBI, they may likely be under-diagnosed. This warrants further investigation of MTBI in population-based studies across the globe.
A new derivation of the relationship between diffusion coefficient and entropy in classical Brownian motion by the ensemble method
Authors: Liao Yi , Gong Xiao-Bo 
Published: June 2021

The diffusion coefficient–a measure of dissipation, and the entropy–a
measure of fluctuation are found to be intimately correlated in many
physical systems. Unlike the fluctuation dissipation theorem in linear
response theory, the correlation is often strongly non-linear. To
understand this complex dependence, we consider the classical Brownian
diffusion in this work. Under certain rational assumption, i.e. in the
bi-component fluid mixture, the mass of the Brownian particle
MM
is far greater than that of the bath molecule
mm,
we can adopt the weakly couple limit. Only considering the first-order
approximation of the mass ratio m/Mm/M,
we obtain a linear motion equation in the reference frame of the
observer as a Brownian particle. Based on this equivalent equation, we
get the Hamiltonian at equilibrium. Finally, using canonical ensemble
method, we define a new entropy that is similar to the Kolmogorov-Sinai
entropy. Further, we present an analytic expression of the relationship
between the diffusion coefficient DD
and the entropy SS
in the thermal equilibrium, that is to say,
D =\frac{\hbar}{eM} \exp{[S/(k_Bd)]}D=ℏeMexp[S/(kBd)],
where dd
is the dimension of the space, k_BkB
the Boltzmann constant, h the reduced Planck constant and
ee
the Euler number. This kind of scaling relation has been well-known and
well-tested since the similar one for single component is firstly
derived by Rosenfeld with the expansion of volume ratio.