bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ocean acidification in emission-driven temperature stabilization scenarios: the role of TCRE and non-CO2 greenhouse gases
Authors: Terhaar Jens , Frölicher Thomas L , Joos Fortunat 
Published: January 2023

Abstract
Future ocean acidification mainly depends on the continuous ocean uptake of CO2 from the atmosphere. The trajectory of future atmospheric CO2 is prescribed in traditional climate projections with Earth system models, leading to a small model spread and apparently low uncertainties for projected acidification, but a large spread in global warming. However, climate policies such as the Paris Agreement define climate targets in terms of global warming levels and as traditional simulations do not converge to a given warming level, they cannot be used to assess uncertainties in projected acidification. Here, we perform climate simulations that converge to given temperature levels using the Adaptive Emission Reduction Algorithm (AERA) with the Earth system model Bern3D-LPX at different setups with different Transient Climate Response to cumulative carbon Emissions (TCRE) and choices between reductions in CO2 and non-CO2 forcing agents. With these simulations, we demonstrate that uncertainties in surface ocean acidification are an order of magnitude larger than the usually reported inter-model uncertainties from simulations with prescribed atmospheric CO2. Uncertainties in acidification at a given stabilized temperature are dominated by TCRE and the choice of emission reductions of non-CO2 greenhouse gases (GHGs). High TCRE and relatively low reductions of non-CO2 GHGs, for example, necessitate relatively strong reductions in CO2 emissions and lead to relatively little ocean acidification at a given temperature level. The results suggest that choices between reducing emissions of CO2 versus non-CO2 agents should consider the economic costs and ecosystem damage of ocean acidification.
Two-dimensional Dirac operators with general δ-shell interactions supported on a straight line
Authors: Behrndt Jussi , Holzmann Markus , Tušek Matěj 
Published: January 2023

Abstract
In this paper the two-dimensional Dirac operator with a general hermitian δ-shell interaction supported on a straight line is introduced as a self-adjoint operator and its spectral properties are investigated in detail. In particular, it is demonstrated that the singularly continuous spectrum is always empty and that by switching a certain δ-shell interaction on, it is possible to generate an eigenvalue in the gap of the spectrum of the free operator or to partially or even fully close the gap. This suggests that the studied operators may serve as interesting continuum toy-models for Dirac materials. Finally, approximations by Dirac operators with regular potentials are presented.
Characterization of anomalous diffusion through convolutional transformers
Authors: Firbas Nicolas , Garibo-i-Orts Òscar , Garcia-March Miguel Ángel , Conejero J Alberto 
Published: January 2023

Abstract
The results of the Anomalous Diffusion Challenge (AnDi Challenge) (Muñoz-Gil G et al 2021 Nat. Commun.
12 6253) have shown that machine learning methods can outperform classical statistical methodology at the characterization of anomalous diffusion in both the inference of the anomalous diffusion exponent α associated with each trajectory (Task 1), and the determination of the underlying diffusive regime which produced such trajectories (Task 2). Furthermore, of the five teams that finished in the top three across both tasks of the AnDi Challenge, three of those teams used recurrent neural networks (RNNs). While RNNs, like the long short-term memory network, are effective at learning long-term dependencies in sequential data, their key disadvantage is that they must be trained sequentially. In order to facilitate training with larger data sets, by training in parallel, we propose a new transformer based neural network architecture for the characterization of anomalous diffusion. Our new architecture, the Convolutional Transformer (ConvTransformer) uses a bi-layered convolutional neural network to extract features from our diffusive trajectories that can be thought of as being words in a sentence. These features are then fed to two transformer encoding blocks that perform either regression (Task 1 1D) or classification (Task 2 1D). To our knowledge, this is the first time transformers have been used for characterizing anomalous diffusion. Moreover, this may be the first time that a transformer encoding block has been used with a convolutional neural network and without the need for a transformer decoding block or positional encoding. Apart from being able to train in parallel, we show that the ConvTransformer is able to outperform the previous state of the art at determining the underlying diffusive regime (Task 2 1D) in short trajectories (length 10–50 steps), which are the most important for experimental researchers.
Experimental Investigation for Free Overfall of Flow in Semi-circular Channels
Authors: Irzooki Raad Hoobi , Saoud Najem Ayad 
Published: January 2023

Abstract
In the present paper, the effects of diameter, bed slopes, and bed roughness on free overfall flow of semi-circular channels were investigated experimentally. For this purpose, three models of semi-circular channels with free overfall were built and installed in a 6m long laboratory flume. These three models were 250 cm long and had varying diameters 160, 200, and 250 mm. Four different bed slopes (S) were used in each of these models (0, 0.004, 0.008, and 0.012). For each bed slope, three sand particle sizes were used to roughen the bed (1.18mm, 2.36mm, and 4.75mm). For each model, the experimental testing program contained sixteen series of experiments. They were divided into two categories: four smooth beds and twelve rough beds. Different rates of discharge (Q) were examined in a total of 192 tests. According to the experimental results of all models, the Froude number (F

r
) of flow decreases as the end depth ratio ( y

b
/ y

c
) increases for various bed roughnesses. For varying bed slopes and bottom roughness, a simple linear formula was developed to relate the brink depth ( y

b
) with the critical depth ( y

c
). For various bed slopes and roughness conditions, simple empirical equations for the flow over the free overfall in semi-circular channels were found. The results demonstrate a good level of agreement.
Delineate the hydrological boundaries situation using the morphometric analysis and geological features: A case study of Laylan sub-basin, Kirkuk / NE Iraq
Authors: Al-Tamimi Omer Sabah , Abo-Khomra Najem Khaled , Othman Arsalan Ahmed 
Published: January 2023

Abstract
Water is the backbone of life for humans, animals, and plants; so, water is one of the necessities that are indispensable if life is to continue. Laylan area, as a part of Kirkuk governorate, suffers from water scarcity and the main source for this area is groundwater. The objectives of this study are to assess the hydro morphometric reality and compare it with the hydrogeological reality of the region depending on the fact that the hydrological boundaries are an indicator of the hydrological basins, The hydrological studies like the current this study in this region are almost non-existent, which motivates us to make this study. The digital elevation model (DEM) has been used to extract a set of morphometric parameters. The result showed that the study area is part of two hydrological sub-watersheds (Shirin and Masha) where erosion factors, geology, structural, and hydrological factors affected and shaped the features of the study area, through eroded the upper parts of the crest of the Kirkuk structure which represents the northern and northeastern boundary of the basin led to the entry of water into the study area easily, which came from the areas of the two upstreams. It is clear from the morphometric results that the two sub-watersheds still have a lot of time to complete their erosion cycle.
Assessment of Darbandikhan Reservoir’s water for different purposes by using (WQI), (HPI) and (MI) indices
Authors: Al-Obaidi Basim Shakir , Sarhat Abdulmutalib Raafat 
Published: January 2023

Abstract
This study aimed to evaluate the water quality of Darbandikhan Reservoir for different purposes by using an integrated approach of water quality index (WQI), heavy metal pollution index (HPI) and metal index (MI). The samples were collected from twenty sampling stations across the reservoir in December 2021, and the sampling stations were selected by using GPS. Seven physicochemical parameters were examined to determine (WQI) including: (pH, turbidity, TDS, NO3
-2, DO, BOD5 and fluoride). Also, five heavy metals were tested to determine (HPI) an (MI) indices. This integrated approach helps to give a comprehensive evaluation of water in the study area. This approach also can overcome limitations of traditional indices regarding water quality in order to make the evaluation outcome more accurate. The results showed that the mean value of (WQI) of the study area was (79.1) which fall under (very poor quality) category. The mean values of (HPI) were (66.75) - (High affected) and (14.09) - (Low affected) for drinking and irrigation uses respectively. However, the mean values of (MI) for the study area were (4.98) - (Strongly affected) and (0.37) – (Pure) for drinking and irrigation uses respectively. The results showed that Darbandikhan Reservoir’s water is suitable for irrigation and industrial purposes only; while, it is not fit for drinking use without high process of treatment. This paper helps to facilitate effective management practices of water quality.
The Hydrodynamic Model using HEC-RAS: The case of Tigris River Downstream of Samarra Barrage (Iraq)
Authors: Sabeeh Nadia Nazhat , Alabdraba Waleed M. Sh. 
Published: January 2023

Abstract
Tigris River is one of the Iraq’s two main rivers. In the present study, one dimensional hydrodynamic model (HEC-RAS) was used to simulate the flow pattern of Tigris River to understand the flow movement. The hydrodynamic model was calibrated by evaluating its performance using Manning’s roughness coefficients which has a final calibration range of 0.018–0.020, with an average of 0.019 in most parts of the study area. The values of the Nash-Sutcliffe coefficient (NSE) and the coefficient of discrimination (R2) were close to 1 which means a high degree of conformity between the simulated and observed data. The validation results show that there is a very close relationship between the observed flow discharge with the hydrodynamic model built by HEC-RAS. This finding would be a very productive tool to estimate the amount of discharge at ungagged locations along the Tigris River downstream of Samarra Barrage.
Runoff Estimation and Dam Selection Site in the Khur khur Watershed (KHW), Using (SCS-CN) Method and (GIS & RS) Techniques
Authors: Mamin Hemin N , Majeed Sabah A 
Published: January 2023

Abstract
The Soil Conservation Service Curve Number (SCS-CN) method was applied to calculate the runoff in the Khur khur watershed (KHW) based on (GIS and RS) techniques. The watershed (KHW) is located southeast of the Iraqi Kurdistan region and northeast Iraq in the foothill zone. The total area of (KHW) is (106.84) km2, and in the fifth order, it meets the Sirwan river. The study aim is to speculate annual runoff volume and to select the dam site in order to harvest water from (KHW). The research reached specific basic results; the annual rate of water returns was (14408514.23 m3), and a suitable dam location was proposed that could be exploited from the volume of surface runoff, with a capacity approximately (14 million m3).
A sawdust Filter is Used to Remove Oil From The Kitchen Wastewater
Authors: Majid Haneen , Al Kindi Ghayda Yaseen , Al Refaaec Jwad K. 
Published: January 2023

Abstract
Proteins, carbohydrates, detergents, oils, fats, and other dissolved and suspended compounds, as well as other concerns like clogged drainpipes, are the main contaminants in residential wastewater from the kitchen. The study’s purpose was to use sawdust as an agricultural waste which was used as absorbents in sink filters to treat the Gray water, many parameters were evaluated such as pH, electrical conductivity EC, total dissolved solid TDS, dissolved oxygen DO, biochemical oxygen demand BOD, and oil & grease O&G. from results were shown the removal rates of pH, EC, TDS, DO, BOD, and Oil & Grease are (6.2-7.41), (470- 1412 µs /cm), (357- 939 mg/L), (3.2- 4.2 mg/L), (40- 150) mg/L), and (190-1210 mg/L) respectively. however, the oil removal efficiency was high ranging from 94 to 98 %, implying that sawdust was successfully used to remove contaminants and O&G from Gray water by Kitchen filter.
Use poultry manure product of Biogas and its role in growth in Barley plants
Authors: Hasan Zainab K. , Jaber Ali M. 
Published: January 2023

Abstract
The accumulation of raw poultry residues in enormous quantities causes the release of odors and the leakage of toxic elements into the surface and groundwater, which negatively affects human health and the environment. So the bioreactor named the fixed-dome model as an anaerobic digester was designed and installed in the poultry field at the agricultural advisory office of college of agriculture at the University of Basra in Karmat-Ali, Iraq. Anaerobic organic fertilizer produced from anaerobic digestion pathway when raw poultry manure was fermented an aerobically for 56 days in the designed bioreactor, to study the use efficiency for anaerobic produced organic fertilizer and raw poultry manure when added at 150Kg N ha-1 at 0, 25, 50, 75, and 100 % of the recommended dose which was equal to a chemical recommendation for nitrogen as urea fertilizer while P and K were applied in a field experiment as traditional fertilizers(superphosphate and potassium sulfate respectively) to grow barley plants (Hordeum vulgare L.). Results showed that doses at 100% of anaerobic organic fertilizer were produced in the bioreactor with a significant increase in plant growth parameters as plant height, dry weight of shoot and amounts and their uptake of N and P elements in plants within 60 days of planting as compared to the rest treatments, so the biogas technology for the production of anaerobic organic fertilizer can help partly or mainly to reduce amounts of traditional doses of fertilizer.
Assessment of industrial effluent impacts on soil physiochemical properties in Kwashe Industrial Area, Iraq Kurdistan Region.
Authors: Meshabaz Ronak Abdulazeez , Umer Mustafa Ismail 
Published: January 2023

Abstract
The present investigation was conducted to assess the quality of industrial effluents of Kwashe industrial area in Kurdistan region, Iraq and evaluate the potential effects of these effluents on the quality of soil. Industrial effluents samples were collected at from the discharge point of various industries including (oil refineries, plastic, paper and printing, steel, aluminum, leather tanning, paint, food, detergent, fertilizer, construction, nylons, metals pipe, chemical, asphalt and petroleum product) at three different locations and analyzed for various physic-chemical characteristic. Soil samples were collected from different fields and analyzed for several soil properties. Result revealed; nearly almost physicochemical characteristics of industrial effluents are higher than the permissible levels of worldwide standard. Result also shows that the quality of industrial effluents is significantly deteriorated much more with the distance it passes through two plains in the region. Almost soil properties are negatively affected by effluents, organic matter in the soil affected by industrial effluents is higher 5 times greater than the normal range of organic matter in the soil due to the continuous deposition of petroleum hydrocarbons in the soil. Soil content of macronutrients is significantly affected by industrial effluents. Significant correlation between some studied soil parameters were found as determination coefficients (R2) are highly significant (P<0.01).
Review for Some Applications of Riverbanks Flood Models
Authors: Mohammed-Ali Wesam S. , Khairallah Rafal S. 
Published: January 2023

Abstract
The flood risk management is one of the primary concerns in water resources engineering. The flood occurs as a result of unexpected events in the hydrological cycle, such as rainfall in the upstream tributaries of the rivers. However, engineers have to have a precise tool to manage the risk of flood. Nowadays and due to the tremendous revolution in computers, which helps to build a credible mathematical models, management of flood become doable. In fact, expressive which model should be used is the challenge. This paper aims to review several hydraulics models that used in flood risk management.
Utilizing Underwater FRP System for Hydraulic Structures Application
Authors: Al-Jaberi Zuhair , Al-Jazeri Zena , Mahdi Rana 
Published: January 2023

Abstract
The development of the use of advance composites is remarkable, especially in applications that require the materials used to be corrosion resistant. One of the most important of these applications is the structures built inside or under water, especially hydraulic structures. Constant exposure to wet makes materials such as concrete and steel threatened to the high level of corrosion and deterioration. The traditional methods for repairing proved insufficient over time, in addition to being expensive in some cases. Therefore, it became necessary to search for alternatives that achieve engineering efficiency and lower costs. One of these alternatives is the use of fiber reinforced polymer (FRP) system. Until recent years, it was not possible to use FRP system under water as a repair system for hydraulic structures without cofferdam. However, during this period, types of underwater cured resins were produced and underwater FRP system is the best choice for this type of structures. There are no many practical applications for the use of FRP in repairing of hydraulic structures, so it is possible to study its application in marine structure to show the possibility of use it in hydraulic structure. This research highlight the advantages and disadvantages of traditional method in repairing underwater structures. Also present project that considered the underwater FRP as a construction material used in the rehabilitation of deteriorated concrete pile. As a conclusion, using fibers with water activated resin can provide an economical solution for future repair and rehabilitation projects. Also the pre-preg system is efficient for repairing dry zones, while the wet layup system is very effective in repairing splash zones of damaged structural elements.
Machine learning approach to understanding the ‘synergistic’ pseudocapacitive effects of heteroatom doped graphene
Authors: Chenwittayakhachon Apiphu , Jitapunkul Kulpavee , Nakpalad Bunyanuch , Worrayotkovit Phanit , Namuangruk Supawadee , Sirisinudomkit Pichamon , Iamprasertkun Pawin 
Published: January 2023

Abstract
In recent years, graphene has been widely utilised as a supercapacitor electrode, and doping heteroatom on graphene is reported to enhance the pseudocapacitance of the electrode materials significantly resulting in a high energy density. However, the relationship and charge storage mechanism of a so-called ‘synergistic effect’ between those doped atoms including oxygen-, nitrogen-, and sulphur-doping on supercapacitor performances remain inscrutable. In this study, machine learning models are used to predict the capacitance of heteroatom-doped graphene-based supercapacitors and establish the effects of heteroatom-doping. Trained artificial neural network can accurately predict the capacitance of the electrode, drawing the best synthesis conditions for the heteroatom-doped graphene. Furthermore, we successfully demonstrate the synergistic effect that arises from co-doping nitrogen, sulphur, and locate the optimised region for N/S-co-doping with high capacitance, and high retention rate. Machine learning methods allow us to consider a much larger space of heteroatom-doping combinations to maximise the supercapacitor performances and provide a useful guideline for co-doping graphene-based supercapacitors.
ZnO-CNT/Nano-Au modified electrodes for the detection of trace Hg(II) in coastal seawater
Authors: Wang Ping , Qu Wei , Qiu Chengjun , Zhuang Yuan , Yan Yirou , Wang Cong , Yan Jiaqi , Wu Yuxuan , Zeng Zexi , Gao Jiaqi 
Published: January 2023

Abstract
Mercury (Hg) in seawater enters the body through the food chain, causing damage to organs and the nervous system. Thus, there is an urgent need to explore a rapid and convenient sensor for the detection and monitoring of Hg(II) in seawater. Herein, a ZnO-CNTs/Nano-Au modified glassy carbon electrode was prepared by the dropping method. The structure of the composite membrane is mainly observed by scanning electron microscopy (SEM), and the results show that the composite has a larger specific surface area. Moreover, the composite can increase the ion adsorption of the surface electrode and enhance the conductivity. Differential pulse voltammetry (DPV) was applied to determine trace amounts of Hg(II) in seawater. The optimized conditions were as follows: accumulation potential, accumulation time, pH value, film thickness and concentration. Under the optimal experimental conditions, the linear relationship between the values of the oxidation peak current and concentration was kept in the range of 1.49 ∼ 5.97 μM, with a linear correlation coefficient R2 = 0.991 and a detection limit of Hg(II) of 0.0118 μM. The proposed method was applied to the analysis of coastal water of the Maowei Sea, giving values of recovery in the range of 94.2%∼98.4%. The ZnO-CNTs/Nano-Au-modified electrode has high sensitivity, convenient operation and good practical application value.
The potential synergies between synthetic data and in silico trials in relation to generating representative virtual population cohorts
Authors: Myles Puja , Ordish Johan , Tucker Allan 
Published: January 2023

Abstract

In silico trial methods promise to improve the path to market for both medicines and medical devices, targeting the development of products, reducing reliance on animal trials, and providing adjunct evidence to bolster regulatory submissions. In silico trials are only as good as the simulated data which underpins them, consequently, often the most difficult challenge when creating robust in silico models is the generation of simulated measurements or even virtual patients that are representative of real measurements and patients. This article digests the current state of the art for generating synthetic patient data outside the context of in silico trials and outlines potential synergies to unlock the potential of in silico trials using virtual populations, by exploiting synthetic patient data to model effects on a more diverse and representative population. Synthetic data could be defined as artificial data that mimic the properties and relationships in real data. Recent advances in synthetic data generation methodologies have allowed for the generation of high-fidelity synthetic data that are both statistically and clinically, indistinguishable from real patient data. Other experimental work has demonstrated that synthetic data generation methods can be used for selective sample boosting of underrepresented groups. This article will provide a brief outline of synthetic data generation approaches and discuss how evaluation frameworks developed to assess synthetic data fidelity and utility could be adapted to evaluate the similarity of virtual patients used for in silico trials, to real patients. The article will then discuss outstanding challenges and areas for further research that would advance both synthetic data generation methods and in silico trial methods. Finally, the article will also provide a perspective on what evidence will be required to facilitate wider acceptance of in silico trials for regulatory evaluation of medicines and medical devices, including implications for post marketing safety surveillance.