bluuebunny/crossref_metadata_2025_split huggingface dataset:
Organized crime as a link between inequality and corruption
Authors: Schwuchow Soeren C. 
Published: March 2023

AbstractWe study a model that establishes a novel theoretical rationale for the empirically well-documented relation between inequality and corruption. According to our model, inequality can nurture corruption by empowering organized crime because collusion between local police forces and criminal organizations is more likely in societies characterized by high inequality or weak security forces. Law enforcement and organized crime have a strong incentive to collude due to efficiency gains from specialization. However, their agreement breaks down when the mobsters can no longer credibly commit to joint rent maximization and thus start to compete with law enforcement for citizens’ wealth. The mobsters then non-violently monopolize the market for extortion by undercutting the police forces, similar to a strategy of predatory pricing. Criminal collusion is thus not very different from its corporate equivalent; hence, similar policy measures should be promising. In addition, our model also suggests that the criminal organization’s higher efficiency in extracting rents has a greater impact when the relative power between law enforcement and organized crime is rather balanced. Accordingly, when violent conflict becomes less predictable, non-violent elements of relative power become more relevant. Our model also allows for the interpretation that in the absence of strong social norms against corruption, organized crime is more difficult to challenge.
Visualising data science workflows to support third-party notebook comprehension: an empirical study
Authors: Ramasamy Dhivyabharathi , Sarasua Cristina , Bacchelli Alberto , Bernstein Abraham 
Published: March 2023

AbstractData science is an exploratory and iterative process that often leads to complex and unstructured code. This code is usually poorly documented and, consequently, hard to understand by a third party. In this paper, we first collect empirical evidence for the non-linearity of data science code from real-world Jupyter notebooks, confirming the need for new approaches that aid in data science code interaction and comprehension. Second, we propose a visualisation method that elucidates implicit workflow information in data science code and assists data scientists in navigating the so-calledgarden of forking pathsin non-linear code. The visualisation also provides information such as the rationale and the identification of the data science pipeline step based on cell annotations. We conducted a user experiment with data scientists to evaluate the proposed method, assessing the influence of (i) different workflow visualisations and (ii) cell annotations on code comprehension. Our results show that visualising the exploration helps the users obtain an overview of the notebook, significantly improving code comprehension. Furthermore, our qualitative analysis provides more insights into the difficulties faced during data science code comprehension.
ADHD Symptoms and Educational Level in Adolescents: The Role of the Family, Teachers, and Peers
Authors: Schmengler Heiko , Peeters Margot , Stevens Gonneke W. J. M. , Hartman Catharina A. , Oldehinkel Albertine J. , Vollebergh Wilma A. M. 
Published: March 2023

Abstract
Few studies have explored the contribution of family and school factors to the association between ADHD symptoms and lower education. Possibly, having more ADHD symptoms contributes to poorer family functioning and less social support, and consequently a lower educational level (i.e., mediation). Moreover, the negative effects of ADHD symptoms on education may be stronger for adolescents with poorer family functioning or less social support (i.e., interaction). Using data of the Dutch TRAILS Study (N = 2,229), we evaluated associations between ADHD symptoms around age 11 and educational level around age 14, as well as between ADHD symptoms around age 14 and 16 years and subsequent changes in educational level around age 16 and 19, respectively. We assessed the potential mediating role of family functioning, and social support by teachers and classmates, all measured around ages 11, 14, and 16, while additionally evaluating interactions between ADHD symptoms and these hypothesized mediators. ADHD symptoms were associated with poorer family functioning, less social support by teachers and classmates, and lower education throughout adolescence. No conclusive evidence of mediation was found, because unique associations between family functioning and social support by teachers and classmates and education were largely absent. Furthermore, we found no interactions between ADHD symptoms and family functioning and social support by teachers and classmates. Although social support by teachers and classmates and good family functioning may benefit the wellbeing and mental health of adolescents with high levels of ADHD symptoms, they will not necessarily improve their educational attainment.
Role of sirtuins in attenuating plaque vulnerability in atherosclerosis
Authors: Velpuri Prathosh , Rai Vikrant , Agrawal Devendra K. 
Published: March 2023

AbstractAtherosclerosis is characterized by the development of intimal plaque, thrombosis, and stenosis of the vessel lumen causing decreased blood flow and hypoxia precipitating angina. Chronic inflammation in the stable plaque renders it unstable and rupture of unstable plaques results in the formation of emboli leading to hypoxia/ischemia to the organs by occluding the terminal branches and precipitate myocardial infarction and stroke. Such delibitating events could be controlled by the strategies that prevent plaque development or plaque stabilization. Despite the use of statins to stabilize plaques, there is a need for novel targets due to continuously increasing cases of cardiovascular events. Sirtuins (SIRTs), a family of signaling proteins, are involved in sustaining genome integrity, DNA damage response and repair, modulating oxidative stress, aging, inflammation, and energy metabolism. SIRTs play a critical role in modulating inflammation and involves in the development and progression of atherosclerosis. The role of SIRTs in relation to atherosclerosis and plaque vulnerability is scarcely discussed in the literature. Since SIRTs regulate oxidative stress, inflammation, and aging, they may also regulate plaque progression and vulnerability as these molecular mechanisms underlie the pathogenesis of plaque development, progression, and vulnerability. This review critically discusses the role of SIRTs in plaque progression and vulnerability and the possibility of targeting SIRTs to attenuate plaque rupture, focusing on the highlights in genomics, molecular pathways, and cell types involved in the underlying pathophysiology.
Affective social anthropomorphic intelligent system
Authors: Mamun Md. Adyelullahil , Abdullah Hasnat Md. , Alam Md. Golam Rabiul , Hassan Muhammad Mehedi , Uddin Md. Zia 
Published: March 2023

AbstractHuman conversational styles are measured by the sense of humor, personality, and tone of voice. These characteristics have become essential for conversational intelligent virtual assistants. However, most of the state-of-the-art intelligent virtual assistants (IVAs) are failed to interpret the affective semantics of human voices. This research proposes an anthropomorphic intelligent system that can hold a proper human-like conversation with emotion and personality. A voice style transfer method is also proposed to map the attributes of a specific emotion. Initially, the frequency domain data (Mel-Spectrogram) is created by converting the temporal audio wave data, which comprises discrete patterns for audio features such as notes, pitch, rhythm, and melody. A collateral CNN-Transformer-Encoder is used to predict seven different affective states from voice. The voice is also fed parallelly to the deep-speech, an RNN model that generates the text transcription from the spectrogram. Then the transcripted text is transferred to the multi-domain conversation agent using blended skill talk, transformer-based retrieve-and-generate generation strategy, and beam-search decoding, and an appropriate textual response is generated. The system learns an invertible mapping of data to a latent space that can be manipulated and generates a Mel-spectrogram frame based on previous Mel-spectrogram frames to voice synthesize and style transfer. Finally, the waveform is generated using WaveGlow from the spectrogram. The outcomes of the studies we conducted on individual models were auspicious. Furthermore, users who interacted with the system provided positive feedback, demonstrating the system’s effectiveness.
Efficient GPU implementation of a Boltzmann-Schrödinger-Poisson solver for the simulation of nanoscale DG MOSFETs
Authors: Vecil Francesco , Mantas José Miguel , Alonso-Jordá Pedro 
Published: March 2023

AbstractA previous study by Mantas and Vecil (Int J High Perform Comput Appl 34(1): 81–102, 2019) describes an efficient and accurate solver for nanoscale DG MOSFETs through a deterministic Boltzmann-Schrödinger-Poisson model with seven electron–phonon scattering mechanisms on a hybrid parallel CPU/GPU platform. The transport computational phase, i.e. the time integration of the Boltzmann equations, was ported to the GPU using CUDA extensions, but the computation of the system’s eigenstates, i.e. the solution of the Schrödinger-Poisson block, was parallelized only using OpenMP due to its complexity. This work fills the gap by describing a port to GPU for the solver of the Schrödinger-Poisson block. This new proposal implements on GPU a Scheduled Relaxation Jacobi method to solve the sparse linear systems which arise in the 2D Poisson equation. The 1D Schrödinger equation is solved on GPU by adapting a multi-section iteration and the Newton-Raphson algorithm to approximate the energy levels, and the Inverse Power Iterative Method is used to approximate the wave vectors. We want to stress that this solver for the Schrödinger-Poisson block can be thought as a module independent of the transport phase (Boltzmann) and can be used for solvers using different levels of description for the electrons; therefore, it is of particular interest because it can be adapted to other macroscopic, hence faster, solvers for confined devices exploited at industrial level.
QoL Following Dacryocystorhinostomy: Linguistic Adaptation of Italian Version of GBI
Authors: Cantone Elena , Torrisi Aldo , D’Ecclesia Aurelio , Massimilla Eva Aurora , Motta Giovanni , Motta Gaetano 
Published: March 2023

AbstractThe Glasgow Benefit Inventory (GBI) is a generic patient recorded outcome measure assessing the quality of life of patients undergoing ear nose and troth surgery. Although largely used in the clinical practice, it has never been adapted and validated in the Italian language. The aim of the study was to translate the original GBI from English to Italian and to examine its reliability for use in the Italian adult population of patients undergoing endonasal endoscopic dacryocystorhinostomy. After translation and back-translation of the original English we evaluated the reliability of GBI for use in 79 Italian adults undergoing dacryocystorhinostomies. Reliability of GBI-IT was examined by the internal consistency of the scale (using the Cronbach’s alpha coefficient), and by the test–retest analysis. The GBI-IT showed adequate internal consistency (Cronbach’s alpha = 0.85 for the total scale). The total GBI-IT score showed a strong correlation in retests (CCC 0.87). In conclusion, our study showed that the GBI-IT has satisfactory internal consistency and reliability and is equivalent to the original English version. In addition, it can be considered a valuable measure for both clinical and research uses.
Impact of Mineral Fertilizers on Anaerobic Digestion of Vegetable Waste
Authors: Borowski Sebastian , Cieciura-Włoch Weronika , Boniecki Paweł , Bednarek Agata 
Published: March 2023

Abstract This study investigated the use of mineral fertilizers for the improvement of biogas production from vegetable wastes. Five fertilizers of various chemical compositions were selected, and two blends of vegetable wastes were composed for the experiments. The results demonstrated the highest improvement in biogas production using the mineral fertilizer SUBSTRAL dedicated to conifers, which was characterized by a diverse chemical composition and the lack of sulfur. The addition of this fertilizer in a dose of 1 g/kg increased methane and hydrogen yields by up to 49% compared to the control. The maximum methane production of 336 NmL/gVS was achieved after supplementation of the mixture containing corn, green peas, and green bean wastes, whereas the highest hydrogen yield of 49 NmL/gVS was reported in the experiments with the blend containing carrot, cauliflower, and broccoli. A simplified cost analysis showed that the use of 1 kg of mineral fertilizer to supplement the anaerobic digestion of vegetable waste for biogas production can generate additional revenues of up to 2399 €.
The Metaphysics of Living Consciousness: Metabolism, Agency and Purposiveness
Authors: Meincke Anne Sophie 
Published: March 2023

AbstractLife has evolved; and so must have consciousness, or subjective experience, as found in living beings, Eva Jablonka and Simona Ginsburg contend. In their target article, which summarises the main theses of their seminal book The Evolution of the Sensitive Soul, the authors put forward an evolutionary account of consciousness that builds upon the intimate connection between consciousness and life without, however, equating the two. Instead, according to Jablonka & Ginsburg, there was life before there was consciousness, and there are still living beings without consciousness. Here I offer some metaphysical considerations in favour of a more inclusive notion of consciousness than Jablonka & Ginsburg’s. These considerations turn on the role played by metabolism and agency in the processual constitution of living beings as well as on the continuum between sensation and perception. Rather than postulating a mindless inwardness in presumably non-conscious organisms, we ought to recognise the constitutive experiential nature of life, rooted in its intrinsic purposiveness.
Distribution network optimization: predicting computation times to design scenario analysis for network operators
Authors: Burmeister Sascha Christian , Schryen Guido 
Published: March 2023

AbstractThe increased use of renewable energies promotes decarbonization and raises the load on power distribution networks, forcing responsible distribution network operators to re-evaluate and re-design their networks. Infrastructure planners employ a rolling-horizon planning procedure with frequent recalculations to face informational uncertainty, which require solving multiple scenarios. Keeping complexity manageable is particularly challenging as distribution network areas may span multiple cities and counties. In this study, we focus on infrastructural decomposition, where the distribution network is decomposed into multiple parts and planning problems, which are then optimized separately. However, infrastructure planners lack the knowledge of how they should design a scenario analysis for a subnetwork to account for informational uncertainties subject to limited planning time and computing resources. Based on empirical requirements from literature and discussions with experts, we present a novel mixed integer linear optimization model that allows to use exact solution approaches for realistic large-scale distribution networks. Our approach considers the primary and secondary distribution network in an integrated way and designs a flexible topology for high reliability power distribution. We perform extensive computational experiments and a sensitivity analysis to determine correlations between the values of model parameters and computation times required to solve the resulting model instances to optimality. The results of the sensitivity analysis indicate that the combination of the number of buses, lines and the considered action scope have a considerable influence on the solving time. In contrast, a higher number of available transformers led to a better solvability of the model. From these computational insights, we derive implications for infrastructure planners who wish to perform scenario analysis for planning their power distribution networks.
Investigation of overexploitation groundwater in arid areas: case of the lower Jurassic aquifer, Bechar province Southwest of Algeria
Authors: Kendouci Mohammed Amin , Mebarki Saliha , Kharroubi Benali 
Published: March 2023

AbstractThe conservation of natural non-renewable water resources is an important part of the expectations of the Algerian population, especially in the south of the country. Groundwater is provided in the southwest of Algeria, and the demand for water is high including agriculture. Studies have shown that the quality of these resources has changed after many years of continuous exploitation. To meet the satisfaction and the need for drinking water, for the city of Bechar, located in southwest Algeria, technicians and decision-makers have sought additional water resources, namely in the Jurassic groundwater located at the region of Mougheul (Sahara Algerian). The intense use of pumping at Mougheul has led to serious local problems (rapid drawdown and drying up of the source). The obtained results reveal that the piezometric charts, established in October 2001 and November 2009, show that the main flow of water is from north to south, exactly to the source of Mougheul. The flow rates of the drillings made are very varied, and between 6 and 30 l/s, this amounts to the heterogeneity of the medium. The pumping tests give low transmissivity values varying between 3.22 10–5 and 5.49 10−3 m2/s.
Output Prediction of Helical Microfiber Temperature Sensors in Cycling Measurement by Deep Learning
Authors: Chen Minghui , Han Jinjin , Liu Juan , Zheng Fangzhu , Geng Shihang , Tang Shimeng , Wu Zhijun , Pu Jixiong , Zhang Xining , Dai Hao 
Published: March 2023

AbstractThe inconsistent response curve of delicate micro/nanofiber (MNF) sensors during cycling measurement is one of the main factors which greatly limit their practical application. In this paper, we proposed a temperature sensor based on the copper rod-supported helical microfiber (HMF). The HMF sensors exhibited different light intensity-temperature response relationships in single-cycle measurements. Two neural networks, the deep belief network (DBN) and the backpropagation neural network (BPNN), were employed respectively to predict the temperature of the HMF sensor in different sensing processes. The input variables of the network were the sensor geometric parameters (the microfiber diameter, wrapped length, coiled turns, and helical angle) and the output optical intensity under different working processes. The root mean square error (RMSE) and Pearson correlation coefficient (R) were used to evaluate the predictive ability of the networks. The DBN with two restricted Boltzmann machines (RBMs) provided the best temperature prediction results (RMSE and R of the heating process are 0.9705 °C and 0.9969, while the values of RMSE and R of the cooling process are 0.786 6 °C and 0.997 7, respectively). The prediction results obtained by the optimal BPNN (five hidden layers, 10 neurons in each layer, RMSE=1.126 6 °C, R=0.995 7) were slightly inferior to those obtained by the DBN. The neural network could accurately and reliably predict the response of the HMF sensor in cycling operation, which provided the possibility for the flexible application of the complex MNF sensor in a wide sensing range.
Insight into the key kinetic steps in the pyrolysis of coking and non-coking coals, characterization of the pyrolysis products
Authors: Кuznetsov P. N. , Fetisova O. Yu. , Kuznetsova L. I. , Avid B. , Purevsuren B. 
Published: March 2023

AbstractThe chemical composition, structural and plastometric properties of different-ranked coals from Mongolia deposits were studied. The non-isothermal iso-conversion Ozawa–Flynn–Wall and Friedman model-free methods were used to assess kinetic parameters and to differentiate decomposition steps. Key peculiarities of the pyrolysis kinetics of brown and bituminous coals were revealed and discussed in terms of the composition and plastometric properties. Brown coal was shown to undergo three decomposition steps with ever increasing activation energy as temperature increased because of the decomposition of thermally more and more stable molecular fragments. The pyrolysis of bituminous coals occurred in four steps, the activation energy having extreme mode of temperature dependence. An important new finding was that the temperature range of the second, major pyrolysis step well corresponded to that between the softening and re-solidification temperatures according to Gieseler plastometry. The yield and composition of the pyrolysis products obtained under isothermal conditions were also characterized depending on coal rank and temperature, and the ways for qualified utilizations were offered.
Morphological analysis and high-temperature phase stability of spark plasma sintered TiN-MWCNTs ceramic composite
Authors: Akinribide Ojo Jeremiah , Akinwamide Samuel Olukayode , Olubambi Peter Apata 
Published: March 2023

AbstractThe microstructure, mechanical properties, and phase stability of TiN+MWCNTs ceramic-based composite were studied. Ball milling and spark plasma sintering (SPS) techniques were adopted for synthesizing titanium nitride (TiN) composites containing 1, 3, and 5 wt. percent (wt. %) multiwalled carbon nanotubes (MWCNT). At a temperature of 1000 °C where the phase stability was investigated, the effects of MWCNT addition on thermal treatment and mechanical characteristics of the fabricated composites were explored. According to the results, the resultant effect of ball milling on the ad-milled powders and sintering at a temperature of 1800 °C played a critical role in the homogenous diffusion of MWCNTs into the TiN ceramic matrix. It was further noted that the addition of different wt. % of multiwalled carbon nanotube helped in stabilizing the FCC-crystal phases at this elevated temperature. A slight transformation was observed in the microstructures, as the core and the outer rim phases remained stable in their crystallographic orientation. The varying addition of MWCNTs retained the α-FCC phase both at the core and the outer rim phase during and after thermal exposure of 1000 °C for 3 h. The composite with 1wt. % MWCNT content exhibited the highest hardness of 40 GPa with a fracture toughness of 12.22 MPa m1/2, while the least hardness value of 12.5 GPa was recorded by the unreinforced TiN sample. The effect of mechanical alloying and thermal exposure of the ceramic composites significantly enhanced the strengthening and toughening of the composites.