bluuebunny/crossref_metadata_2025_split huggingface dataset:
Factors associated with an unfavorable outcome in patients visiting the emergency department with acute abdominal pain
Authors: Dadeh Ar-aishah 
Published: September 2022

Abstract
Background
Unfavorable outcome occurs in patients who visit the emergency department (ED) with acute abdominal pain. We aimed to determine the factors associated with unfavorable outcome in ED patients who presented with acute abdominal pain.
Methods
A retrospective cohort study was conducted from July 1, 2015 to June 30, 2016. The inclusion criteria were patients aged older than 18 years who presented to the emergency department (ED) with acute abdominal pain. The patients were divided into either the favorable outcome group or unfavorable outcome group. The two groups were compared in terms of baseline characteristics, triage category, physical examination findings, duration of symptoms, laboratory and imaging results, final diagnosis, treatment in the ED, emergency department length of stay (EDLOS), and ED disposition, morbidity, and mortality. The significant associated factors for an unfavorable outcome were examined using univariate and multivariate analyses by logistic regression.
Results
A total of 951 patients were included in the study. The multivariate logistic regression analysis showed EDLOS > 4 hours (adjusted odd ratio (AOR) 2.62, 95% CI: 1.33–5.14, p = 0.005), diastolic blood pressure (DBP) < 80 mmHg (AOR 3.31, 95% CI: 1.71–6.4, p ≤ 0.001), respiratory rate ≥ 24 breaths/min (AOR 2.03, 95% CI: 1.07–3.86, p ≤ 0.031), right lower quadrant (RLQ) tenderness (AOR 3.72, 95% CI: 1.89–7.32, p ≤ 0.001), abdominal distension (AOR 2.91, 95% CI: 1.29–6.57, p = 0.010), hypoactive bowel sounds (AOR 2.89, 95% CI: 1.09–7.67, p = 0.033), presence of specific abdominal signs (AOR 2.07, 95% CI: 1.1–3.88, p = 0.024), leukocytosis ≥ 12,000 cells/mm3 (AOR 2.37, 95% CI: 1.22–4.6, p = 0.011), and absolute neutrophil count (ANC) > 75% (AOR 2.83, 95% CI: 1.39–5.75, p = 0.004) were revealed as significant factors associated with unfavorable outcome. Significant variables associated with in-hospital mortality in the unfavorable outcome group were presence of shock (p ≤ 0.001), mechanical ventilation used (p = 0.008), emergency surgery required (p = 0.007), and occurrence of in-hospital cardiac arrest (p = 0.002). Emergency surgical procedures performed were appendectomy (58.5%, 38 patients), exploratory laparotomy (29.2%, 19 patients), laparoscopy (7.7%, 5 patients), and cholecystectomy (4.6%, 3 patients). Three patients died after admission and one patient died at the ED.
Conclusions
The present study revealed that the significant clinical signs associated with the occurrence of unfavorable outcome were DBP < 80 mmHg, tachypnea (≥ 24 breaths/minute), RLQ tenderness, abdominal distension, hypoactive bowel sounds, and presence of specific abdominal signs. Moreover, associated laboratory results identified from this study were leukocytosis and ANC > 75%. Finally, ED patients with abdominal pain who had EDLOS longer than 4 hours were associated with unfavorable outcome.
Distributed Computing With the Cloud
Authors: Afek Yehuda , Giladi Gal , Patt-Shamir Boaz 
Published: September 2022

Abstract
We investigate the effect of omnipresent cloud storage on distributed computing. To this end, we specify a network model with links of prescribed bandwidth that connect standard processing nodes, and, in addition, passive storage nodes. Each passive node represents a cloud storage system, such as Dropbox, Google Drive etc. We study a few tasks in this model, assuming a single cloud node connected to all other nodes, which are connected to each other arbitrarily. We give implementations for basic tasks of collaboratively writing to and reading from the cloud, and for more advanced applications such as matrix multiplication and federated learning. Our results show that utilizing node-cloud links as well as node-node links can considerably speed up computations, compared to the case where processors communicate either only through the cloud or only through the network links. We first show how to optimally read and write large files to and from the cloud in general graphs using flow techniques. We use these primitives to derive algorithms for combining, where every processor node has an input value and the task is to compute a combined value under some given associative operator. In the special but common case of “fat links,” where we assume that links between processors are bidirectional and have high bandwidth, we provide near-optimal algorithms for any commutative combining operator (such as vector addition). For the task of matrix multiplication (or other non-commutative combining operators), where the inputs are ordered, we present tight results in the simple “wheel” network, where procesing nodes are arranged in a ring, and are all connected to a single cloud node.
Ordinal conditional entropy displays reveal intrinsic characteristics of the Rosenberg Self- Esteem Scale
Authors: Furfaro Emanuela , Hsieh Fushing 
Published: September 2022

Abstract
Individual subjects’ ratings neither are metric nor have homogeneous meanings, so digital- labeled collections of subjects’ ratings are intrinsically ordinal and categorical. However, in these situations the literature privileges the use of measures conceived for numerical data. In this paper, we discuss the exploratory theme of employing conditional entropy to measure degrees of uncertainty in responding to self-rating questions, and that of displaying the computed entropies along the ordinal axis for visible pattern recognition. We apply this theme to the study of an online data set which contains responses to the Rosenberg Self-Esteem Scale. We report three major findings. First, at the fine scale level, the resultant multiple ordinal-display of response-vs-covariate entropy measures reveals that the subjects on both extreme labels (high self-esteem and low self-esteem), show distinct degrees of uncertainty. Secondly, at the global scale level, in responding to positively posed questions, the degree of uncertainty decreases for increasing levels of self-esteem, while, in responding to negative questions, the degree of uncertainty increases. Thirdly, such entropy-based computed patterns are preserved across age groups. We provide a set of tools developed in R that are ready to implement for the analysis of rating data and for exploring pattern-based knowledge in related research.
No “carry-over” effects of tracking devices on return rate and parameters determining reproductive success in once and repeatedly tagged common swifts (Apus apus) a long-distance migratory bird
Authors: Wellbrock Arndt Horst Johann , Witte Klaudia 
Published: September 2022

Abstract

Background:To understand life-history strategies in migratory bird species, we should focus on migration behaviour and possible carry-over effects on both population and individual level. Tracking devices are useful tools to directly investigate migration behaviour. With increased use of tracking devices, questions arise towards animal welfare and possible negative effects of logger on birds. Several studies were conducted to address this question in birds that were tagged and tracked for one complete non-breeding season including migration but with mixed results. To detect individual-based decisions regarding migration strategy, we need to track the same individuals several times. So far, there are no studies investigating effects of repeatedly tagging on reproduction and life-history traits in individual migratory birds, especially in small birds.Methods:We used long-term data of 85 tagged common swifts (Apus apus), a long-distance migratory bird, of a breeding colony in Germany to test whether carrying a geolocator or GPS logger once or repeatedly during non-breeding season affected return rate and parameters determining breeding success. Additionally, we checked for individual differences in arrival date and breeding parameters when the same individuals were tagged and when they were not tagged in different years. Further, we calculated the individual repeatability in arrival at the breeding colony and date of egg laying in repeatedly tagged swifts.Results:Once and repeatedly tagged birds returned to the colony at a similar rate as non-logger birds and arrived earlier than non-logger birds. We detected no differences in time lag to clutch initiation, date of clutch initiation, clutch size, number of chicks and fledglings between logger and non-logger birds. We found no effect of loggers on the arrival date and breeding parameter on individual-level. And arrival date and date of clutch initiation were moderately to highly repeatable within repeatedly tagged individuals.Conclusions:Our data indicated that carrying a logger once or repeatedly had no effect on return rate and breeding success in common swifts.
Energy-efficient power cap configurations through Pareto Front Analysis and Machine Learning Categorization
Authors: Cabrera Alberto , Almeida Francisco , Castellanos-Nieves Dagoberto , Oleksiak Ariel , Blanco Vicente 
Published: September 2022

Abstract

The growing demand for more computational resources has increased the overall energy consumption in computer systems. To support the increasing requirements, power and energy consumption have to be considered as a constraint to execute software. Modern architectures provide tools to manage directly the power constraints of a system. The Intel Power Cap is a relatively recent tool developed to offer fine control of power usage to users at a central processing unit (CPU) level.We propose a methodology to analyze the performance and the energy efficiency trade-offs using this power cap technology for a given algorithm.We extract a Pareto front for the multi-objective performance and energy problem to represent multiple feasible configurations for both objectives. We perform an extensive experimentation to categorize the different algorithms to reduce the total amount of optimal power cap configurations. We propose the use of Machine Learning (ML) clustering techniques to categorize any algorithm in the target architecture.The use of Machine Learning allows to automate the procedure and simplifies the effort required to solve the optimization problem.We present a practical case where we categorize the kernels using ML techniques, with the option to include a new algorithm into an already existing categorization.
Results on Certain Polymers using M-polynomial and NM-polynomial of Topological indices
Authors: H Mohammed Yasin , M Suresh 
Published: September 2022

Abstract
A topological index(TI) is a numerical value matching to a graph. It is frequently employed in chemometrics, biomedicines and bioinformatics to forecast various physiochemical attributes and biological activities of a substances. One of the polynomials named as neighborhood M-polynomial (NM-polynomial) which is used to derive numerous degree-based TI’s. Polysaccharide, poly-γ-glutamic acid and poly-l-lysine, which is a well-known biopolymer, It has extraordinary qualities that attracts a great deal of attention in the fields of medicine, the food industry, wastewater treatment, etc. In this we calculate the degree based and neighborhood degree based indices for above-stated biopolymers in consolidate by using. The NM-polynomial and M-polynomial is being utilized to consolidate the degree based and neighborhood degree based indices are calculated for the study.
Impact of Tax Administration on Revenue Generation in Lagos State
Authors: Ogundipe Michael 
Published: September 2022

Abstract
In this study, the impact of tax collection on state revenue creation in Lagos was assessed. 100 questionnaires were delivered. Frequency distribution statistics, percentages, the Pearson Product Moment Correlation Coefficient (PPMCC), and regression analysis are some of the techniques employed. This frequency and the percentage allow us to understand how the respondents feel about the queries posed and answers provided. The regression analysis was utilized to determine the variables' sign and size as well as their significance. The study's findings indicate a beneficial association between electronic tax payments, tax compliance, and revenue creation. The outcome has the implication that regular usage of the electronic tax payment system inside the FIRS organization will maintain the state's improvement in tax responsibility and revenue production. Tax avoidance and evasion have a detrimental impact on Lagos State's ability to generate income. The conclusion of the outcome is that rising tax avoidance and evasion will reduce state revenue production. The correlation coefficient, r, is -0.723, demonstrating a negative relationship between tax avoidance and evasion and income generation. There is no database for all people who are taxable in Lagos State, the tools used to collect and assess taxes in Lagos State are insufficient, the tax laws are extremely complex and difficult for most people to understand, there is a lack of transparency in the handling of tax payers' money, and taxes are occasionally levied on taxpayers' income by two or more jurisdictions.
JEL code: H20, H25, H26
The evolution of disability effects along the income distribution: Evidence from Italy
Authors: Mussida Chiara , Dario Dario 
Published: September 2022

Abstract
We investigate how disability affects income distribution and how this has evolved with the Great Recession in Italy, using 2005–2008 and 2015–2018 European Union Statistics for Income and Living Conditions data and a dynamic bivariate ordered probit model. We account for the extra costs of disability and model both income and disability processes, allowing for feedback effects from past income to disability. We find that disability is associated with income disadvantage, which the Great Recession has exacerbated. This has resulted in greater income inequality for non-disabled persons and smaller disparities for those with a disability, as a consequence of loss of income both at the bottom and the top of the distribution. Persistence in poverty for people with severe disability increased, while persistence in wealth decreased. In addition, the probability of moving from wealthy to poor conditions has increased for people with disabilities, whereas the opposite has occurred for non-disabled persons.
Use of acoustic stimulus to recognize abnormal zebrafish behavior in water quality warning systems
Authors: Huang Yi , 武 军旭 , 王 Yuetong , Zhao Pingge , 王 Ning 
Published: September 2022

Abstract
Fish behavioral responses have impeded the development of water quality warning technology due to high false alarm rates. The causes of abnormal behavior in fish such as zebrafish (Danio rerio), are often unknown. In this study, acoustic stimuli were tested in recognizing abnormal zebrafish behavior under cadmium exposure. Acoustic startle response sensitivity curves were obtained and analyzed to determine the loudness and frequencies at which the zebrafish responded to the stimuli. The standard stimulus duration was 30 s, and the interval between two stimulations was 20 min. It was found that Cd exposure can weaken zebrafish acoustic startle responses, particularly at 100 Hz and 97 dB, and was significantly correlated with the reduction of the response. After 30 min, the average rate of swimming activity decreased to 24% in 0.25 TU and to 17.6% in 2 TU exposure. This indicates that the acoustic stimulation elicits a response that could help determine a false alarm. Based on this data, we designed a model for testing the abnormal behavior. This study can offer insights for improving the accuracy and stability of water quality warning systems, and is beneficial to the development and application of early-warning systems with biological monitoring of water quality.
Detection and Analysis of Flooding Attacks in Wireless Sensor Networks
Authors: Gebremariam Gebrekiros Gebreyesus , Panda Jeepanda , Indu S. 
Published: September 2022

Abstract
Wireless sensor networks are distributed networks and randomly deployed in harsh environments. The scattered nature of the sensor nodes in an unattended environment makes them vulnerable to various types of attacks. Multiple attacks like flooding attacks degrade the network performance and lifetime by sending various requests to malicious nodes. This paper proposes the detection and analysis of flooding attacks in mesh wireless sensor networks using the Blue tooth communication package MATLAB 2020a toolbox. The flooding attack disabled the relay nodes during the routing path between sources and destination nodes for each simulation scenario. The simulations are conducted by the number of sensors variation for the random generator. After simulating the meshed nodes, the statistical results are the message delivery chance, average hope count, and critical relays. The opportunity of message delivery having a route between sources and destinations is 88.64%. The effectiveness of the proposed system for detection and analysis of flooding attacks is evaluated by random forest machine earing techniques with an average detection rate and accuracy of 99.83%, which is greater than by 3.8%.
Light-stimulated Ethylene Production by Germinating Cucumber Seeds1
Authors: Saltveit Mikal E. , Pharr David M. 
Published: September 2022

Abstract
The degree to which white light stimulated ethylene production in germinating seeds of cucumber (Cucumis sativus L.) was influenced by the length of time the seed had been germinated in the dark before being exposed to light. Maximum stimulation occurred when 24 hour old dark-grown seedlings were exposed to 40 μE m−2 sec−1 light for 24 hours. Ethylene production increased with the duration and intensity of light exposure at all seedling ages. Neither the light or dark rates of ethylene, or carbon dioxide production, nor their ratios, were highly correlated with the sexual phenotype of the 9 cultivars examined.
Sensory Characteristics of Apple Fruit1,2
Authors: Watada Alley E. , Abbott Judith A. , Hardenburg Robert E. 
Published: September 2022

Abstract
A profile was developed to describe sensory characteristics of ‘Golden Delicious’, ‘Miller Spur’, ‘Redspur’, ‘Rome Beauty’, and ‘York Imperial’ apples (Malus domestica Borkh.). Ten sensory attributes were selected and the intensities of the attributes were plotted on a circular graph. The patterns of the plots differed among cultivars and patterns of some cultivars changed with successive harvests and storage of apples. The patterns were used to describe the general sensory characteristics of apples.
Levels of Extractable Abscisic Acid in the Mesocarp and Seed of Persisting and Abscising Peach Fruit1
Authors: Ramina A. , Masia A. 
Published: September 2022

Abstract
Developing fruits of peach (Prunus persica (L.) Batsch cv. Andross) were classified as to abscission potential on the basis of fruit growth rate during stage I. Levels of inhibitors, as determined by wheat coleoptile and cress seed assays, were parallel in mesocarp and seed. Extracts from fruits with a high abscission potential contained significantly lower levels of an abscisic acid-like inhibitor than did those with low or intermediate potential. Thus ABA content appears to be positively correlated with the rate of fruit growth, and increases in concentration as the fruit is approaching maturity.
Solar photo-assisted electrochemical peroxidation process for the sustainable treatment of tannery industry wastewater
Authors: Gopal Selvabharathi , Somanathan Adishkumar , Jeyakumar RajeshBanu 
Published: September 2022

Abstract
Tannery wastewater is a complex mixture of organic and inorganic components from various processes with high concentrations of Cr, BOD, COD, TDS, strong colour and pH. The goal of the present work was to determine the optimal solar photo-assisted electrochemical peroxidation process (SPECP) experimental conditions for the treatment of tannery wastewater. Experiments were conducted in a bench-scale stirred tank SPECP reactor of 5 L with iron plates as anode and cathode in a contact effective area of 218 cm2. In the stirred tank reactor at optimal conditions, the SPECP yielded 97% COD, 98% of colour and 92% of chromium (III) removal after 60 min at 15 mA/cm2. SPECP improved the biodegradability (BOD5/COD) of tannery wastewater from 0.4 to 0.6 in 15 min. These results showed that wastewater from tannery industries could be treated up to the level of the minimal national standards of India for waste disposal; COD=90 mg/L, BOD=30 mg/L and chromium (III)=1.2 mg/L at a treatment time of 60 min. The operating cost of the best economic condition with maximum degradation was $8.2/m3.
Emulating the estuarine morphology evolution using a deep convolutional neural network emulator based on hydrodynamic results of a numerical model
Authors: Weber de Melo Willian , Pinho J. L. S. , Iglesias Isabel 
Published: September 2022

Abstract
Coastal and estuarine areas present remarkable environmental values, being key zones for the development of many human activities such as tourism, industry, fishing, and other ecosystem services. To promote the sustainable use of these services, effectively managing these areas and their water and sediment resources for present and future conditions is of utmost importance to implement operational forecast platforms using real-time data and numerical models. These platforms are commonly based on numerical modelling suites, which can simulate hydro-morphodynamic patterns with considerable accuracy. However, in many cases, considering the high spatial resolution models that are necessary to develop operational forecast platforms, a high computing capacity is also required, namely for data processing and storage. This work proposes the use of artificial intelligence (AI) models to emulate morphodynamic numerical model results, allowing us to optimize the use of computational resources. A convolutional neural network was implemented, demonstrating its capacity in reproducing the erosion and sedimentation patterns, resembling the numerical model results. The obtained root mean squared error was 0.59 cm, and 74.5 years of morphological evolution was emulated in less than 5 s. The viability of surrogating numerical models by AI techniques to forecast the morphological evolution of estuarine regions was clearly demonstrated.
The future of flood hydrology in the UK
Authors: Lamb Rob , Longfield Sean , Manson Susan , Cloke Hannah L. , Pilling Charlie , Reynard Nick , Sheppard Owain , Asadullah Anita , Vaughan Michael , Fowler Hayley J. , Beven Keith J. 
Published: September 2022

Abstract
A ‘roadmap’ for the future of UK flood hydrology over the next 25 years has been published, based on a wide-ranging and inclusive co-creation process involving more than 270 individuals and 50 organisations from different sectors and disciplines. This paper highlights key features of the roadmap and its development as a community-owned initiative. The roadmap's relationship with hydrological research and practice is discussed, as is its context within the wider flood risk management innovation landscape, including funding. While the paper has a focus on UK flood hydrology, reflecting the scope of the roadmap, it is also considered in the context of advances in hydrology internationally.