Miracle-dz/UniFAR-FTUs huggingface dataset:
MNSRQ: Mobile node social relationship quantification algorithm for data transmission in Internet of things

The rapid development of the Internet of things has led to the explosive development of data in various ﬁelds. Traditional routing protocols cannot effectively handle the reception and transmission of data. This makes it difﬁcult to exchange and transmit information in the Internet of things. Therefore, the choice of data transmission methods is particularly important. In order to solve this problem, this paper proposes a data transmission mechanism based on social relationships, namely, the mobile node social relationship quantiﬁca-tion (MNSRQ) algorithm, which analyses the social relationship characteristics of mobile nodes in the Internet of things, extracts decision-making features to study the dynamics of social relationship, then combines information entropy and fuzzy clustering theory to quantify the social relationship, and then selects the relay node with strong social relationship for data transmission. Theoretical analysis and experimental results show that the performance of the MNSRQ algorithm is better than previous studies. Compared with epidemic algorithm, ICMT algorithm, spray and wait algorithm, and EIMST algorithm, the MNSRQ algorithm can reduce end-to-end transmission delay and routing overhead while maintaining the life of the network, effectively reduce energy consumption during transmission, and maintain a high data transmission success rate, with a transmission success rate of 0.7–0.9.
Improved Glucose Recovery from Sicyos angulatus by NaOH Pretreatment and Application to Bioethanol Production

As greenhouse gases and environmental pollution become serious, the demand for alternative energy such as bioethanol has rapidly increased, and a large supply of biomass is required for bioenergy production. Lignocellulosic biomass is the most abundant on the planet and a large part of it, the second-generation biomass, has the advantage of not being a food resource. In this study, Sicyos angulatus, known as an invasive plant (harmful) species, was used as a raw material for bioethanol production. In order to improve enzymatic hydrolysis, S. angulatus was pretreated with different NaOH concentration at 121 °C for 10 min. The optimal NaOH concentration for the pretreatment was determined to be 2% (w/w), and the glucan content (GC) and enzymatic digestibility (ED) were 46.7% and 55.3%, respectively. Through NaOH pretreatment, the GC and ED of S. angulatus were improved by 2.4-fold and 2.5-fold, respectively, compared to the control (untreated S. angulatus). The hydrolysates from S. angulatus were applied to a medium for bioethanol fermentation of Saccharomyces cerevisiae K35. Finally, the maximum ethanol production was found to be 41.3 g based on 1000 g S. angulatus, which was 2.4-fold improved than the control group.
Engineering ethics education from the cultural and religious perspectives: a study among Malaysian undergraduates

ABSTRACT The aim of this research is to examine the influence of cultural and religious values in engineering ethics education, which has been largely adopted from Western ideologies among engineering undergraduates in Malaysia. Data were elicited from open-ended interviews involving a group of engineering students of a higher education institution in Malaysia. The findings revealed several themes showing that prevailing cultural and religious values have an important place in engineering ethics education by influencing ethical decision making among future engineers. The findings of this study would provide practitioners with considerable insight into the understanding of the immense impact of religious and cultural values on Malaysian engineering ethics education among engineering undergraduates. Conformity to such religious and cultural values was prevalent among engineering undergraduates, suggesting the need to factor in such values in the development of engineering ethics education model that helps strike a proper balance between local social ideologies and Western ethical principles.
Recidivism: Exploring Why Inmates Re-Offend in a Prison Facility in Ghana

ABSTRACT This study explores the causes of recidivism among inmates in a prison facility in Ghana. Eleven men who had served two or more terms of imprisonment, five prison officers who were in charge of rehabilitation, five community members, and two police officers (in Ghana, most offenses are prosecuted by the police) who had prosecuted at least three recidivists were interviewed. Based on the analysis, results suggest that the inmates were reincarcerated due to structural deficiencies (perceived overcrowding and inadequate rehabilitation in the prison), situational factors (perceived weak family ties during and post-prison), and personal or lifestyle factors (perceived laziness and reluctance to change on the part of some inmates). The limitations of the results have been highlighted and the need for future research has been discussed.
A Neighbourhood Encoding Framework for Deep Mining Heterogeneous Texts in Recipe-image Retrieval

Cross-modal retrieval usually fills the semantic gap between different modalities by sharing subspaces. However, existing methods rarely consider that the data in a certain modality may be heterogeneous when mapping multimodal data into a shared subspace. In addition, most existing methods focus on semantic associations between different modalities, while few approaches consider the semantic associations within a single modality. To address the above two deficiencies, we propose a Neighbourhood Encoding (NE) framework that mines the semantic association of data in the same modality, solves the problem of data heterogeneity by improving the semantic expression of a single modality. To verify the effectiveness of the proposed framework, we use two types of recurrent neural networks to instantiate the framework. Experiments show that the instantiated approaches outperform existing advanced methods in both text-to-image and image-to-text retrieval directions.
Input-to-state stability and integral input-to-state stability of non-autonomous infinite-dimensional systems

In this paper, we provide Lyapunov-based tools to establish input-to-state stability (ISS) and integral input-to-state stability (iISS) for non-autonomous infinite-dimensional systems. We prove that for a class of admissible inputs the existence of an ISS Lyapunov function implies the ISS of a system in Banach spaces. Furthermore, it is shown that uniform global asymptotic stability is equivalent to their integral input-to-state stability for non-autonomous generalised bilinear systems over Banach spaces. The Lyapunov method is provided to be very useful for both linear and nonlinear tools including partial differential equations (PDEs). In addition, we present a method for construction of iISS Lyapunov function in Hilbert spaces. Finally, two examples are given to verify the effectiveness of the proposed scheme.
Learning by P2P bidding

ABSTRACT Most of peer-to-peer (P2P) online borrowers are small business managers. Learning behavior of them is under-analyzed in the literature of P2P online lending. Using a large sample from one of the China’s largest online P2P lending marketplaces- renrendai.com, we examine whether a borrower in the P2P lending market has a learning behavior when he/she bids interest rates for a loan. We validate the existence of learning behavior in the interest rate bidding, in which they learn from the previous experience and adjust the interest rates downward, so that they can obtain finance at a lower cost. Further analysis shows the heterogeneity across gender and education. We find that female borrowers and highly educated borrowers are more effective in the learning process. Robustness check further supports our hypothesis. Our findings point to the importance of providing financial education for groups of low education level. Managerial implications are discussed.
Flow Induced Vibration of Cantilever Tapered Pipes Transporting Fluid

A cantilevered tapered slender pipe conveying an incompressible, inviscid fluid of one material is not a conserved system. For certain large fluid velocity, the pipe with uniform cross section would go unstable via flutter Hopf bifurcation. In this paper, the flow induced vibration for cantilever tapering pipe transporting a fluid is presented. Euler Bernoulli and Hamilton’s theories are applied to develop the mathematical model which will be solved using well known Galerkan’s procedure. The effect of smooth tapering of the circular cross sectional area, flow velocity and pipe to fluid mass fraction on the complex natural frequencies and stability will be investigated.
Evolution of Pitch Angle Distributions of Relativistic Electrons During Geomagnetic Storms: Van Allen Probes Observations

We present a study analyzing relativistic and ultra relativistic electron energization and the evolution of pitch angle distributions using data from the Van Allen Probes. We study the connection between energization and isotropization to determine if there is a coherence across storms and across energies. Pitch angle distributions are fit with a J0sinnθ function, and the variable “n” is characterized as the pitch angle index and tracked over time. Our results show that consistently across all storms with ultra relativistic electron energization, electron distributions are most anisotropic within around a day of Dstmin and become more isotropic in the following week. Also, each consecutively higher energy channel is associated with higher anisotropy after storm main phase. Changes in the pitch angle index are reflected in each energy channel; when 1.8 MeV electron pitch angle distributions increase (or decrease) in pitch angle index, so do the other energy channels. We show that the peak anisotropies differ between coronal mass ejection (CME)‐ and corotating interaction region (CIR)‐driven storms and measure the relaxation rate as the anisotropy falls after the storm. The isotropization rate in pitch angle index for CME‐driven storms is −0.15 ± 0.02 day−1 at 1.8 MeV, −0.30 ± 0.01 day−1 at 3.4 MeV, and −0.39 ± 0.02 day−1 at 5.2 MeV. For CIR‐driven storms, the isotropization rates are −0.10 ± 0.01 day−1 for 1.8 MeV, −0.13 ± 0.02 day−1 for 3.4 MeV, and −0.11 ± 0.02 day−1 for 5.2 MeV. This study shows that there is a global coherence across energies and that storm type may play a role in the evolution of electron pitch angle distributions.
Derivatives of lignin and ligninlike models with acrylate functionality

Acrylatation de l'hydroxypropyl lignine et de composes modeles (gaiacol et hydroxypropyl gaiacol) par le methacrylate d'isocyanatoethyle; la determination des rapports de reactivite de ces composes dans la copolymerisation avec le styrene et le MMA suggere que la copolymerisation est preferentiellement alternee. La copolymerisation du methacrylate de lignine donne des gels avec une fraction de gel qui diminue lorsque le degre de substitution par les groupes methacrylates diminue
Chair-CEO age variation and insurance risk-taking behavior

How to cite this paper: Daradkah, D. (2021). Chair-CEO age variation and insurance risk-taking behavior. Journal of Governance & Regulation, 10(1), 49-57. https://doi.org/10.22495/jgrv10i1art6 Copyright © 2021 The Author This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). https://creativecommons.org/licenses/by/
Data-driven Modeling of the Methane Adsorption Isotherm on Coal Using Supervised Learning Methods: A Comparative Study

Methane adsorption isotherm on coals is key to the development of coalbed methane (CBM). Laboratory measurement of adsorption isotherm is time-consuming. This paper presents a comparative study on the accuracy and robustness of seven supervised learning (SL) methods in estimating the methane adsorption isotherm based on coal properties. The SL methods used include the Gaussian process regression (GPR), kernel ridge regression (KRR), classifier and regression tree (CART) and four ensemble decision tree methods (random forests (RF), Adaboost, gradient boosting decision tree (GBDT) and extreme boosting (XGBoost)). The results show that all these SL methods are capable of correlating methane adsorption amounts with the feature variables with reasonable accuracies in the training stage. However, the KRR, GBDT and XGBoost are demonstrated to outperform other SL techniques in terms of the robustness and generalization capability, which therefore are recommended for fast estimation of the methane adsorption isotherms on coals.
A Visual Assessment Scale for Rapid Evaluation of Mangrove Degradation, Using Examples from Myanmar and Madagascar

Mangroves are globally threatened, disappearing and degraded. They are lost due to land use changes, mostly agricultural expansion and aquaculture, but also degraded by cutting by villagers and logging and timber extraction for domestic and economic purposes. Extent and conversion of mangroves can usually be estimated by applying remote sensing and modern drone technology, but the scale of degradation of mangrove habitats is not easily detected by such methods. In this paper we propose an assessment tool for a rapid evaluation on the degradation, using examples from different regions in Myanmar and Madagascar. We propose a visual and practical guide listing a range of 1–6 to identify and quantify the level of degradation. We demonstrate the application by displaying various examples from Myanmar and Madagascar and how this tool can be used for wider applications, discussing advantages scope, and limitations.
Image translation with dual-directional generative adversarial networks

Image ‐ to ‐ image translation is a class of vision and graphics problems where the goal is to learn the mapping between input images and output images. However, due to the unstable training and limited training samples, many existing GAN ‐ based works have difficulty in producing photo ‐ realistic images. Herein, dual ‐ directional generative adversarial networks are proposed, which consist of four adversarial networks, to produce images of high perceptual quality. In this framework, self ‐ reconstruction strategy is used to construct auxiliary sub ‐ networks, which impose more effective constraints on encoder ‐ generator pairs. Using this idea, this model can increase the use ratio of paired data conditioned on the same dataset and obtain well ‐ trained encoder ‐ generator pairs with the help of the proposed cross ‐ network skip connections. Moreover, the proposed framework not only produces realistic images but also addresses the problem where condition GAN produces sharp images containing many small, hallucinated objects. Training on
Joint Design of Physical-layer Network Coding and LDPC Code Modulated by 2FSK

In order to improve the transmission efficiency in wireless communication and reduce the bit error rate in the transmission process, a physical-layer network coding(PNC) system with 2FSK modulation and low-density parity check(LDPC) codes as the channel coding is established, and a relay detection scheme for the system is designed. This scheme first obtains the waveform diagram of the signal in the network encoding process. According to the characteristics of 2FSK modulation, and then we can extracts the prior probability soft information by the waveform characteristics, and finally we can combine the log likelihood ratio belief propagation(LLR-BP) algorithm to complete the decoding and relay mapping process. The simulation results show that the system adopts 2FSK modulation and has superior bit error rate performance compared with BPSK modulation. After introducing low-density parity check(LDPC) codes, the system can ensure high-speed transmission of information while effectively improving system Bit error ratio performance.
Study of surface evolution via Modified Ion Beam Sputtering Semi-Empirical Model (MIBSEM)

An Ion Beam Sputtering Monte Carlo Model (IBSM) was modified to study the effect of different surface diffusion mechanics on the surface height and surface roughness of materials when bombarded with energetic ions. The extension was done by incorporating Seahet al.’s semi-empirical ion sputtering equations into the sputter erosion algorithm of the MC model and by enforcing curvature dependence of sputter yield. Also, TRansport of Ions in Matter (TRIM) software, was used to calculate the sputter yield and the values obtained were compared with those obtained from Seahet al.’s semi-empirical model and the sputter yield obtained from sputtering experiments. Our studies show that the surface diffusion mechanics that occurs during a sputtering process controls the substrate surface height and its roughness while curvature dependence of sputter yield has little or no contribution to the target surface height and its roughness. Our comparison of the calculated sputter yield values of TRIM and Seahet al.’s model with experimental sputter yield values show that Seahet al.’s model gives sputter yield values closer to experimental values than TRIM at a normal angle of incidence while TRIM gives sputter yield values closer to experimental values at 60°angle of incidence.
History Erase Effect of Real Memristors

Different from the static (power-off) nonvolatile property of a memristor, the history erase effect of a memristor is a dynamic characteristic, which means that under the excitation of switching or different signals, the memristor can forget its initial value and reach a unique stable state. The stable state is determined only by the excitation signal and has nothing to do with its initial state. The history erase effect is a desired effect in memristor applications such as memory. It can simplify the complexity of the writing circuit and improve the storage speed. If the memristor’s response depends on the initial state, a state reset operation is required before each writing operation. Therefore, it is of great theoretical and practical significance to judge whether the memristor has a history erase effect. Based on the study of the history erase effect of real memristors, this paper focuses on the history erase effect of a Hewlett-Packard (HP) TiO2 memristor and the Self-Directed Channel (SDC) memristor of Knowm Company. The DC and AC responses of the HP TiO2 memristor are given, and it is pointed out that there is no AC history erase effect. However, considering the parasitic memcapacitance effect, it is found that it has the effect. Based on the theoretical model of the SDC memristor, its history erase properties with and without considering parasitic effects are studied. It should be noted that this study method can be useful for other materials such as Al2O3 and MoS2.
Blending in: A Case Study of Transitional Ambidexterity in the Financial Sector

Organizational ambidexterity is widely recognized as necessary for the economic sustainability of firms operating in the financial sector. While the management literature has recognized several forms of ambidexterity, the relationship between them and their relative merits remain unclear. By studying a process of implementation of ambidextrous capabilities within a large Scandinavian financial firm, we explore the role of top-down reforms and bottom-up reactions in determining the development of sector-specific innovative capabilities. We find that blended ambidexterity follows naturally from the attempt to correct the tensions arising from harmonic ambidextrous blueprints. The resulting blended practice appears to be closely related to the reciprocal model of ambidexterity, which appears to be a necessity rather than a choice, for large firms attempting to develop innovative capabilities. Consequently, we suggest to re-interpret current taxonomies of ambidexterity not as alternative blueprints, but rather as stages in a long-term process of transition.
Chapter 2.3 Dronning Maud Land Jurassic volcanism: volcanology and petrology

Abstract The Jurassic igneous rocks of Dronning Maud Land represent Karoo flood basalt magmatism in Antarctica. Fifty years of research has documented systematic differences between magmas associated with the Karoo rift-zone (Vestfjella and Ahlmannryggen) and the rift-shoulder (Sembberget, Kirwanveggen) settings. The 189–182 Ma rift-zone tholeiites were chemically diverse and mainly formed compound-braided flow fields which record several magnetic polarity reversals. In contrast, the c. 181 Ma rift-shoulder tholeiites were chemically uniform and formed thick tabular sheet lavas within a single normal polarity period. The volcanic architecture records a long initial phase of slow eruptions from shield volcanoes in the initial rift and a brief phase of voluminous fissure eruptions flooding the rift shoulder. All of the major magma types in the rift-zone and rift-shoulder settings belong to a Nb-depleted category of Karoo flood basalts and were mainly derived from depleted convective upper mantle by magmatic differentiation. Pyroxenite-rich mantle components may have been significant sources for the most enriched magma types. Geochemical fingerprints of recycled crustal material imply that the Nb-depleted Karoo tholeiites may have been derived from mildly subduction-modified parts of the same overall upper-mantle reservoir which has been associated with the Ferrar tholeiites.
Could Information Energy resolve Hubble Tension?

Stellar heated gas and dust has a universe total entropy/information content of ~10^86 bits. At typical temperatures ~10^7 the equivalent N kB T ln(2) information energy ~10^70 J is comparable to the mc2 of the universe’s ~10^53 kg of baryons. At low red-shifts, z<1.35 this dark energy contribution provides a near constant energy density, with an equation of state parameter, w=-1.03±0.05, effectively emulating a cosmological constant to within 1.8% in Hubble parameter, H(a). Earlier, z>1.35, the information energy contribution was phantom, w=-1.82±0.08. This dark energy differs from the cosmological constant by △w0= -0.03±0.05 and △wa= -0.79±0.08, sufficient to account for the value of the ‘Hubble Tension’ between early and late universe H0 values. An information energy model will fit most observations as well as Ʌ, and also resolve Hubble tension and cosmological coincidence problems. Furthermore, information energy could also account for many effects previously attributed to dark matter.