Miracle-dz/UniFAR-FTUs huggingface dataset:
Mediating Effect of CSR on the Relationship between Ethical Leadership and Organization Citizenship Behavior

: The primary goal of this study was to determine whether the ethical behavior of top executives in the academic sector of DIKhan has a positive impact on employee behavior and whether corporate social responsibility has any effect on the interim. To retrieve results, a multi-method approach was used. This is a cross-sectional study. This study employed quantitative methodology. To collect primary data from academics at two universities in DIKhan, Pakistan, an adapted questionnaire was used. The findings indicate that there is a positive and significant relationship between Ethical Leadership and Organizational Citizen Behavior, and that Corporate Social Responsibility has a significant effect on the relationship between Ethical Leadership and Organizational Citizen Behavior. Finally, the current research's conclusions will be critical for department representatives and intellectuals to conduct their institutions in accordance with the research's recommendations and conclusions.
12th Structural Engineering

The health monitoring of rail sections from the perspective is thought to be Asia's second-largest rail network. order to initiate the appropriate measures. One be used for this purpose. However, the literature challenging due to the complex geometry of the method often serves the purpose of simulated AE present in the PLB method due to its manual operation. complexity of the application of PLB is increased Velocity (UPV) instrument. UPV instrument produces and localize the simulated AE sources produced Earlier researchers used Wavelet Transform (WT is observed from the WT-based localization of AE complex geometry of the rail section. But with the is observed that the UPV and PLB produces similar Neural Network (ANN) based methodology. The sources are also applied to the rail section and localization and UPV-generate dones, are compared. It is found 1.3%. The technique is promising and there is structures.
Series of ERUDITE Working Papers

: The aim of this paper is to analyze the effects of quality competitiveness based on technological innovation on the bilateral trade of goods. Our approach is based on the estimation of an import demand model using the data for 19 manufacturing sectors across 28 OECD countries over the period 1998-2012. In a first step, to identify quality from prices, the logarithm of unit value (a proxy of price) is regressed on the logarithm of private R&D expenditure (a proxy for quality). The quality-adjusted prices are derived from the difference between the unit value and its predicted value. In a second step, an import demand function is used to distinguish the effects of quality (private R&D expenditure) from the effects of other factors, such as production costs, approximated by the quality-adjusted prices. The results of the first step indicate a significant positive effect of quality on the prices of imported goods in 7 out of 19 sectors. The results of the second step highlight significant nonlinear effects of prices and quality on the import demand of goods: the higher the quality of imported goods is, the greater the marginal effect of an increase in quality on the import demand.
University of Birmingham Compound heterozygotes and beta-thalassemia : top-down mass spectrometry for detection of hemoglobinopathies

We have shown previously that liquid extraction surface analysis of dried blood spots coupled to high resolution top-down MS may be applied for the diagnosis of hemoglobin (Hb) variants FS, FAS, FC, FAC, FAD in newborn samples. The objective of the current work was to determine whether the structural variant HbE, compound heterozygote variants FSC and FSD, and (cid:2) - thalassemia were amenable to diagnosis by this approach. Anonymized residual neonatal dried blood spot samples, taken as part of the routine newborn screening program, were analyzed by liquid extraction surface analysis coupled to high resolution MS/MS. The samples had been previously screened and were known to be FAE, FSC, FSD, or (cid:2) -thalassemia. Manual analysis of the mass spectra revealed that, in all cases, the variants may be conﬁrmed. Direct surface sampling MS should be considered as an alternative to current screening techniques for the diagnosis of Hb variants.
Multibeam 3-D-Printed Luneburg Lens Fed by Magnetoelectric Dipole Antennas for Millimeter-Wave MIMO Applications

A 3-D-printed Luneburg lens with a novel simplified geometry is presented. The rod-type structures are employed as the unit cell of the gradient-index material to realize the required permittivity distribution in the lens. A prototype designed in the Ka-band is manufactured successfully by using a commercial 3-D printing facility. The substrate-integrated waveguide fed magnetoelectric (ME)-dipole antenna with endfire radiation is introduced as the feed for the Luneburg lens due to its wideband performance and compact configuration. By combining the lens with a set of the ME-dipoles, a millimeter-wave (mm-wave) multibeam Luneburg lens antenna is designed, fabricated, and measured. An overlapped impedance bandwidth of wider than 40% that can cover the entire Ka-band and mutual coupling below −17 dB are verified by the fabricated prototype. Nine stable radiation beams with a scanning range between ±61°, gain up to 21.2 dBi with a variation of 2.6 dB, and radiation efficiency of around 75% are achieved as well. With the advantages of good operating features, low fabrication costs, and ease of integration, the proposed multibeam Luneburg lens antenna would be a promising candidate for the fifth-generation (5G) mm-wave multiple-input multiple-output (MIMO) applications in 28 and 38 GHz bands.
An adaptive fuzzy approach for modelling visual texture properties

This is the peer reviewed version of the following article: Jes´us Chamorro-Mart´ınez, Pedro Manuel Mart´ınez-Jim´enez, Jos´e Manuel Soto-Hidalgo, Bel´en Prados-Su´arez: An adaptive fuzzy approach for modeling visual texture properties. Fuzzy Sets and Systems 286: 86-113 (2016) , which has been published in ﬁ-nal form at https://doi.org/10.1016/j.fss. 2015.09. 008 . This article may be used for non-commercial purposes in accordance with Creative Commons Attribution Non-Commercial No Derivatives License (CC-BY-NC-ND license): https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode . Abstract The analysis of the perceptual properties of texture plays a fundamental role in tasks like semantic description of images, content-based image retrieval using linguistic queries, or expert systems design based on low level visual features. The presence of these properties in images is very diﬃcult to characterize due to their imprecision, and, moreover, because their perception may change depending on the user or the image context. In this paper, texture properties are modelled by means of an adaptive fuzzy approach that takes into account the subjectivity of the human perception. For this purpose, a methodology in two phases has been proposed. First, non-adaptive fuzzy models, that represent the average human perception about the presence of the texture properties, are obtained. For this modelling, we propose to learn a relationship between representative measures of the properties and the assessments given by human subjects. In a second phase, the obtained fuzzy sets are adapted in order to model the particular perception of the properties that
A novel computer vision based one class data driven modelling approach for person speciﬁc fall detection

In this paper, we propose a novel person speciﬁc fall detection system based on a monocular camera, which can be applied for assisting the independent living of an older adult living alone at home. A single camera covering the living area is used for video recordings of an elderly person’s normal daily activities. From the recorded video data, the human silhouette regions in every frame are then extracted based on the codebook background subtraction technique. Low-dimensionality representative features of extracted silhouetted are then extracted by convolutional neural network based autoencoder (CNN-AE). Features obtained from the CNN-AE are applied to construct an one class support vector machine (OCSVM) model, which is a data driven model based on the video recordings and can be applied for fall detection. From the comprehensive experimental evaluations on different people in a real home environment, it is shown that the proposed fall detection system can successfully detect different types of falls (falls towards different orientations at different positions in a real home environment) with small false alarms.
A Novel Elephant Heard Random Forest Machine Learning Approach to Estimate the Sentiment Value of Online Customer Review

: Nowadays, big data has attracted the attention of whole advanced world with its applications and features. Machine learning (ML) models are used to perform the online administrations in good manner . The ML approaches turned into a moving field in analyzing enormous data; consequently the accomplishment of online administrations or business depends on the client audits. Nearly the online customer review contains positive, negative and neutral sentiment value. In marketing system and product development fields the sentiment analysis value prediction has important role. In this paper, a novel Elephant Herd Random Forest Machine Learning (EHRFML) methodology is proposed to compute the sentiment value of online customer review. Moreover, customer review datasets are preprocessed and unwanted information is removed using machine learning approach. Sequentially, the outcomes of proposed system are compared with existing technique using parameters like accuracy, precision, recall, aspect term specification and opinion condition obtained good results by getting high accuracy based on opinion specification.
Period changes in men's class reproduction in Scotland, 1974-2001

In the 1970s Scotland appeared to be among the least fluid countries in Europe together with Germany, France and Ireland (Breen et al. 2004). Within Great Britain Scotland also displayed higher propensity for immobility within manual social classes than England and Wales (Erikson and Goldthorpe, 1992). More recent data show that nowadays the gap with the other European countries has reduced and that Scotland has a degree of social fluidity similar to that in England and Wales. This paper analyses this change comparing data of adult men from the 1974 Scottish Mobility Survey and from the 2001 Scottish Household Survey. Between these two time-points professional and managerial social classes have grown considerably while unskilled manual social classes have shrank. These trends are particularly marked in private services. Overall men were more likely to be socially immobile and less likely to be upwardly mobile in 1974 than in 2001. However, there are variations in this respect across sectors of activity. Finally, our results show that indeed Scottish society has become less unequal but that this has occurred in a very slow way. Only if we look at a long observation window, ie people born between 1910 and 1976, changes are detectable.
— Use Licence — Attribution-NonCommercial-ShareAlike 1 . 0

The ability to identify the behavior of people in a home is at the core of Smart Home functionality. Such environments are equipped with sensors that unobtrusively capture information about the occupants. Reasoning mechanisms transform the technical, frequently noisy data of sensors into meaningful interpretations of occupant activities. Time is a natural human way to reason about activities. Peoples‟ activities in the home often have an identifiable routine; activities take place at distinct times throughout the day and last for predicable lengths of time. However, the inclusion of temporal information is still limited in the domain of activity recognition. Evidence theory is gaining increasing interest in the field of activity recognition, and is suited to the incorporation of time related domain knowledge into the reasoning process. In this paper, an evidential reasoning framework that incorporates temporal knowledge is presented. We evaluate the effectiveness of the framework using a third party published smart home dataset. An improvement in activity recognition of 70% is achieved when time patterns and activity durations are included in activity recognition. We also compare our approach with Naïve Bayes classifier and J48 Decision Tree, with temporal evidence theory achieving higher accuracies than both classifiers.
Conflation via Knowledge Graph Representations of Digital Maps

Digital maps play a crucial role in various applications such as navigation, fleet management, and ride-sharing, necessitating their accuracy and timely updates. While the majority of geospatial databases (GDBs) provide high-quality information, their data is (i) limited to specific regions and/or (ii) missing some entities even in their covered areas. Map conflation is the process of the augmentation of a GDB using another GDB to conflate missing spatial features. Existing map conflation methods suffer from two main limitations: (1) They are designed for the conflation of linear objects (e.g., road networks) and cannot simply be extended to non-linear objects, thus missing information about most entities in the map. (2) They are heuristic algorithmic approaches that are based on pre-defined rules, unable to learn entities matching in a data-driven manner. To address these limitations, we design MINOR (Map Conflation via Knowledge Graph Representation), a machine-learning approach consisting of three parts: (1) Knowledge Graph Construction: where each GDB is represented by a knowledge graph (2) Map Matching: where we use a knowledge graph alignment method as well as a geospatial feature encoder to match entities in obtained knowledge graphs. (3) Map Merging: to consistently merge matched entities in the previous modules, we use a mixed integer linear programming formulation that fully merges the GDBs without adding any inconsistencies. Our experimental evaluation shows that not only MINOR achieves outstanding performance compared to state-of-the-art and baselines in map conflation tasks, but each of its modules (e.g., Map Matching and Map Merging) separately outperforms traditional matching and merging methods.
VIETNAMESE HIP HOP DON’T STOP Unsettling Normative Ideas of Gender around the Block

The city is not a static entity but an expression of past and current power struggles, whose ongoing conficts are frequently carried out in public spaces. The symbolism of public space is continuously negotiated as diverse individuals and groups ascribe diferent meanings to particular places. Lily Kong and Lisa Law (2002: 1505) defne cities as “excellent examples of medium and outcome of power relations”. In order to capture the domination of one group over others in giving meaning to urban objects, Kong and Law introduce the concept of ‘ideological hegemony’, drawing on Gramsci’s (1973) defnition of hegemony. Gramsci regards hegemony as the means through which domination and rule are achieved. In contrast to coercion, which implies clearly recognizable constraints in everyday life, hegemonic controls communicate ideas and values that the majority are persuaded to adopt as their own. If hegemonic control is successfully implemented, the people will desire the social order endorsed by ruling elites.
Animal Cytogenetics and Comparative Mapping

a Istituto di Clinica Neurologica – Università di Milano; b Dipartimento di Biopatologia e Diagnostica per Immagini – Sezione di Genetica – Università di Roma Tor Vergata; c CSS-IRCS Mendel Institute, Roma; d Dipartimento di Anatomia Patologica e di Genetica – Sezione di Genetica – Università di Bari; e Dipartimento di Medicina Sperimentale e Patologia, Università di Roma “La Sapienza”, Roma (Italy)
A Numerical Study on the Powder Flowability, Spreadability, Packing Fraction in Powder Bed Additive Manufacturing

The powder bed fusion (PBF) process is widely adopted in many manufacturing industries because of its capability to 3D print complex parts with micro-scale precision. In PBF process, a thermal energy source is used to selectively fuse powder particles layer by layer to build a part. The build quality in the PBF process primarily depends on the thermal energy deposition and properties of the powder bed. Powder flowability, powder spreading, and packing fraction are key factors that determine the properties of a powder bed. Therefore, the study of these process parameters is essential to better understand the PBF process. In our study, we developed a two-dimensional powder bed model using the granular package of the LAMMPS molecular dynamics simulator. Cloud-based deposition was adopted for pouring powder particles on the powder bed. The spreading of particles over the substrate was mimicked like a powder bed system. The powder flowability in the proposed study was analyzed by varying the particle size distribution. The simulation results showed that a greater number of larger particles in a power sample results in an increase in the Angle of Repose (AOR) which ultimately affects the flowability. Two different kinds of recoater geometry were considered in this study: circular and rectangular blades. Simulation results showed that depending on the recoater shape there is a change in the packing fraction in the powder bed. Cross-sectional analysis of the power bed showed a significant presence of voids when a greater number of larger particles existed in the powder batch. The packing fraction of the powder bed was found to be a strong function of particle size distribution. These analyses help understand the influence of particle size and recoater shape on the powder bed properties. Findings from this study help to provide a guideline for choosing particle size distribution if the spherical particles are considered. While the present study focuses on the spherical powder particles, the proposed system can also be adapted to the study of powder bed with aspherical particles.
Neighborhood Based Multi-Granularity

As a feature selection technique in rough set theory, attribute reduction has been extensively explored from various viewpoints especially the aspect of granularity, and multi-granularity attribute reduction has attracted much attention. Nevertheless, it should be pointed out that multiple granularities require to be considered simultaneously to evaluate the signiﬁcance of candidate attribute in the corresponding process of computing reduct, which may result in high elapsed time of searching reduct. To alleviate such a problem, an acceleration strategy for neighborhood based multi-granularity attribute reduction is proposed in this paper, which aims to improve the computational efﬁciency of searching reduct. Our proposed approach is actually realized through the positive approximation mechanism, and the processes of searching qualiﬁed attributes are executed through evaluating candidate attributes over the gradually reduced sample space rather than all samples. The experimental results over 12 UCI data sets demonstrate that the acceleration strategy can provide superior performance to the naive approach of deriving multi-granularity reduct in the elapsed time of computing reduct without generating different reducts.
Estimation of Directional Surface Wave Spectra from a Towed Estimation of Directional Surface Wave Spectra from a Towed Research Catamaran Research Catamaran

During the High-Resolution Remote Sensing Main Experiment (1993), wave height was estimated from a moving catamaran using pitch-rate and roll-rate sensors, a three-axis accelerometer, and a capacitive wave wire. The wave spectrum in the frequency band ranging roughly from 0.08 to 0.3 Hz was veriﬁed by independent buoy measurements. To estimate the directional frequency spectrum from a wave-wire array, the Data-Adaptive Spectral Estimator is extended to include the Doppler shifting effects of a moving platform. The method is applied to data obtained from a ﬁxed platform during the Risø Air–Sea Experiment (1994) and to data obtained from a moving platform during the Coastal Ocean Processes Experiment (1995). Both results show that the propagation direction of the peak wind waves compares well with the measured wind direction. When swells and local wind waves are not aligned, the method can resolve the difference of propagation directions. Using the ﬁxed platform data a numerical test is conducted that shows that the method is able to distinguish two wave systems propagating at the same frequency but in two different directions.
I The effect of prolonged decalcification on the immunohistochemical staining of Leishmania infantum amastigotes in formalin-fixed, paraffin-embedded

The aim of this report was to present the preliminary results of the effect of prolonged decalcification on the immunohistochemical staining of Leishmania infantum in formalin-fixed, paraffin-embedded canine soft tissues. A heavily parasitized by Leishmania infantum amastigotes popliteal lymph node was used in this study. One half of a surgically excised lymph node was processed according to a decalcification protocol (for 40 days), while the other half was processed without decalcification. Immunohistochemical staining for Leishmania infantum was then applied on both decalcified and non-decalcified lymph node sections. The amastigotes were stained and detected in non-decalcified sections, whereas a significant reduction of immunostaining was observed in decalcified sections. It is likely that parasite antigens are altered by the decalcification procedure, probably as a result of the long lasting effect of decalcifying acids on both the amastigotes and the host cell cytoplasm. Consequently, it seems that immunohistochemical detection of Leishmania infantum amastigotes is significantly affected following prolonged tissue decalcification.
The Future Crops for Biofuels

The Sun is sending around 174 peta watts of light energy to the Earth where only about 120 peta watts can reach the Earth surface after energy losses during penetrating of light through the Earth's atmosphere. In fact, the truly used solar energy for production of biomass on land is only 74 tera watts after counting arable land and photosynthesis efficiency, which is ca. 6% (the arable land area / the Earth area) and ca. 1%, respectively. Presently, the total human consumption requires about 15 tera watts, therefore it still makes the total bioenergy production on land 5 times more than what the human being consumes. Thus, the major question now and in the near future is how to efficiently transfer bioenergy from biomass to biofuels. This chapter will describe the current production of the four forms of biomass ie sucrose, starch, ligno-cellulose and plant oil by different bioenergy crops. It will also briefly describe how to convert the biomass to biofuels by different methods. An analysis of energy conversion efficiency during converting biomass to biofuels and an economic evaluation on using the different biomass will be carried out. A suggestion and discussion will be brought up on how to change biomass from one form to another in vivo and how to increase biomass production in the future crops for efficient use of bioenergy and economic production of biofuels.