Miracle-dz/UniFAR-FTUs huggingface dataset:
competitive advantage and business performance in the Spanish hotel

Purpose: This paper analyses the influence of environmental proactivity on cost and differentiation competitive advantages, and explores the double relationship between environmental proactivity and business performance. Design/methodology/approach: The population consists of all 3-to-5 star hotels in Spain. A sample of 350 hotels was classified according to environmental proactivity and performance levels employing a two-step cluster analysis. Significant differences between groups were examined. Findings: The results show two types of environmental behaviour (reactive and proactive), with proactive hotels developing significantly better on both cost and differentiation competitive advantage and achieving significantly higher performance levels. Hotels which achieve above average business performance levels are significantly more environmentally proactive. Practical implications: The present paper demonstrates that environmental management is related to competitive advantages and business performance. Environmental management systems are more developed in higher category, chain-affiliated, and larger hotels. This could be due to having more resources to develop their environmental capability. The environmental proactivity scale employed in this study is presented as a reference measure for hotel managers to benchmark their current practices and implement environmental improvements. Originality/value: First, measuring environmental proactivity using four managerial systems (operative, information, strategic and technical) is innovative and provides a more detailed approach to measuring environmental proactivity. Second, demonstrating a double association between environmental proactivity and performance provides fresh insights into the relationship between these variables. Hypothesis 2: The more environmentally proactive, the better a hotel’s differentiation competitive advantage.
R ELATIONSHIP BETWEEN CEO O VERCONFIDENCE , P AY G AP AND E XTERNAL G UARANTEE

This paper attempts to disclose the intrinsic relationship between CEO overconfidence, pay gap and external guarantee. First, the CEO overconfidence was measured by four personal traits of the CEO, namely, gender, age, education level and tenure. Then, an empirical analysis was performed to disclose the impact of CEO overconfidence on the pay gap of senior executives and the decisions on external guarantee of a listed company. Moreover, the authors analyzed how this impact is regulated by corporate governance mechanism. The results show that the level of CEO overconfidence is negatively correlated with the pay gap of senior executives; the external guarantee of the company is greatly suppressed by CEO overconfidence.
The Convolution Exponential

This paper introduces a new method to build linear ﬂows, by taking the exponential of a linear transformation. This linear transformation does not need to be invertible itself, and the exponential has the following desirable properties: it is guaranteed to be invertible, its inverse is straightforward to compute and the log Jacobian determinant is equal to the trace of the linear transformation. An important insight is that the exponential can be computed implicitly, which allows the use of convolutional layers. Using this insight, we develop new invertible transformations named convolution exponentials and graph convolution exponentials , which retain the equivariance of their underlying transformations. Empirically, we show that the convolution exponential outperforms other linear transformations in generative ﬂows on CIFAR10 and the graph convolution exponential improves the performance of graph normalizing ﬂows.
Internet of things and supply chain management: a literature review

This paper explores the role of Internet of Things (IoT) and its impact on supply chain management (SCM) through an extensive literature review. Important aspects of IoT in SCM are covered including IoT definition, main IoT technology enablers and various SCM processes and applications. We offer several categorisation of the extant literature, such as based on methodology, industry sector and focus on a classification based on major supply chain processes. In addition, a bibliometric analysis of the literature is also presented. We find that most studies have focused on conceptualising the impact of IoT with limited analytical models and empirical studies. In addition, most studies have focused on the delivery supply chain process and the food and manufacturing supply chains. Areas of future SCM research that can support IoT implementation are also identified.
DEEP LEARNING-BASED BUILDING EXTRACTION USING AERIAL IMAGES AND DIGITAL SURFACE MODELS

Building information is essential in multiple applications. The emerging of very high-resolution remote sensing imagery made the recognition of small-scale objects like buildings possible. However, manually extracting buildings from images is time-consuming. Therefore, different automatic or semi-automatic approaches have been developed for building extraction. With the rise of deep learning, Convolutional Neural Networks (CNNs) have outperformed traditional methods based on handcrafted features and become the dominant approach in image analysis. As the most popular CNN type for semantic segmentation, fully convolutional networks (FCNs) are widely used in building extraction. Most deep learning-based building extraction methods produce building masks in raster format, which cannot be directly integrated in geographic information systems (GIS) applications. Hence, some deep learning-based semantic segmentation models have been adapted for focusing on extracting building footprints as polygons directly. However, these models face the challenge of producing precise and regular building outlines. Recently, a building delineation method based on frame field learning was proposed by Girard et al., (2020) to extract regular building footprints as vector polygons directly from aerial RGB images. An FCN is trained to learn simultaneously the building mask, contours, and frame field followed by a polygonization method.
Impact of ICT on Teaching and Learning: A Literature Review

: The initiation of Information and communication technology has made tremendous changes in the present day world. There is no area that has not been influenced by this digital phenomena. The advent of ICT in education helped to improve the quality of education where teaching and learning eventually became an engaging active process related to real life. The present study intends to collate the findings from a review of an array of available literature related to the impact of ICT on education. Twenty-first-century teaching learning skills emphasise the need to transform the conventional teacher-centered pedagogy to more learner-centered methodology. Active and collaborative learning conditions facilitated by ICT helps to develop a knowledge-based student community. The present literature review gives an over view of the use of ICTs in the field of education focusing on its impact on teaching learning process, quality and accessibility of education, motivating learners, learning environment, and students' academic performance.
Momordica foetida (Cucurbitaceae) methanol extract protects against Parastar®-induced reproductive dysfunction and testicular oxidative stress in male rats

Many plant extracts have been found to exert therapeutic effects against different diseases including their abilities to alleviate toxic effects caused by environmental pollutants such as pesticides. This study aimed at evaluating the protective ability of the methanol extract of Momordica foetida (MEMF) on reproductive function and testicular oxidative stress makers in albino Wistar male rats exposed to Parastar® insecticide. To this end, five groups of eight adult albino male Wistar rats (191±2g) each, were orally treated daily with either the vehicle (distilled water 5 ml/kg), Parastar® (6.23 mg/kg) alone, or Parastar® (6.23mg/kg) plus MEMF (50 mg/kg, 100 mg/kg, 200 mg/kg) for 64 days. The animal body weight was recorded every three days. At the end of the treatment, the animals were sacrificed, and the relative weights of the reproductive organs determined. Epididymal sperm density, and sperm motility were evaluated. Serum testosterone, vesicular fructose, testicular cholesterol, and testicular antioxidant markers were also assessed. Parastar® decreased (P<0.05) seminal vesicle fructose levels testicular weight, testosterone levels, sperm density and motility, increased cholesterol levels, and induced oxidative stress (decrease GSH, activity of antioxidants enzymes catalase and superoxide dismutase, and increased TBARS concentration) in the testes. When co-administered with the pesticide, MEMF significantly (P<0.05) alleviated the Parastar® -induced alterations. Therefore, MEMF protects the reproductive function of male rats against Parastar® insecticide-induced toxicity. M. foetida is therefore a medicinal plant with promising beneficial properties against the toxicity of pesticides on reproductive function.
DDOS Mitigation In Cloud Computing Environment By Dynamic Resource Scaling With Elastic Load Balancing

: The major attack in cloud computing is Distributed Denial of Service (DDoS) which brings more attention to cloud users in the past decade. A DDoS attack can be avoided or controlled by allocating enough resources whenever demanded. Resource allocation will induce additional costs when the attacks reside for a long duration or more frequently. To control and avoid the DDoS attacks dynamic resource allocation has been employed in specific target services for mitigating the attack effectively. During the attack, the resources are overloaded with higher usage and lead to denial of required service for legitimate users forcefully. By adjusting the resource utilization, the attacks can be completely mitigated by which the genuine users' request for the resources can be apparently handledbesidesthe disbandment of established connection with the attacker’s node. Thus resource utilization factor plays a significant role in attack mitigation and recovery which is the number of various resources allocated to the victim service. In this research, a new method has been proposed to evaluate the resource utilization by ‘scaling down the resources’which is an enhancement of the 'scale inside out' model. The proposed method exploits the usage of two components such as verification module and elastic load balancer in order to detect and mitigate the DDoS attack commendably.This enhanced method optimally reduces the resource utilization factor through elastic load balancing by analyzing the incoming traffic data and server condition. The main idea of scaling down the resources and services is to sacrifice the victim’s resources during an attack period in order to mitigate the effect and recover from the attack. The performance of the proposed model is evaluated using various metrics to analyze the attack detection time, attack reporting time, and attack mitigation time. The results show that the proposed method works well to mitigate the DDoS attack by consuming the minimum resources thereby decreasing the service time of the user
Research on the mechanism of a newly developed levitation frame with mid-set air spring

ABSTRACT To reduce the vehicle/guideway-coupled vibration and improve the levitation stability of medium–low-speed maglev vehicle, a new type of levitation frame with air springs installed in the middle of the longitudinal beams is developed. This levitation frame with mid-set air spring (LFMAS) is studied comparatively with the levitation frame with end-set air spring (LFEAS) in electromagnetic levitation mode. The coupling degrees of the two kinds of frames are analysed by vertical motion equations; the energy consumptions for levitation control system to overcome the spring resistance in the whole adjustment process are calculated by the energy method; and the vibration accelerations are compared by dynamics analysis and bench test. The equations indicate that the LFMAS has a better decoupling effect and lower energy consumption than that of the LFEAS in any adjustment process. Simulation and test results show that the LFMAS can effectively reduce the vibration acceleration at a low-speed and achieve a better levitation stability in working conditions, validating that the LFMAS has a better levitation performance and adaptability to the guideway, which is attributed to the mechanical decoupling of the levitation module. It is expected that this new levitation frame will be very helpful in enhancing levitation stability and the ride index of medium–low-speed maglev vehicle.
Maximising the Potential of Longitudinal Cohorts for Research in Neurodegenerative Diseases: A 1 Community Perspective 2

51 Despite a wealth of activity across the globe in the area of longitudinal population cohorts, 52 surprisingly little information is available on the natural biomedical history of a number of age- 53 related neurodegenerative diseases (ND), and the scope for intervention studies based on these 54 cohorts is only just beginning to be explored. The Joint Programming Initiative on Neurodegenerative 55 Disease Research (JPND) recently developed a novel funding mechanism to rapidly mobilise scientists 56 to address these issues from a broad, international community perspective. Ten expert Working 57 Groups, bringing together a diverse range of community members and covering a wide ND landscape 58 (Alzheimer’s, Parkinson’s, frontotemporal degeneration, amyotrophic lateral sclerosis, Lewy-body 59 and vascular dementia) were formed to discuss and propose potential approaches to better 60 exploiting and coordinating cohort studies. The purpose of this work is to highlight the novel funding 61 process along with a broad overview of the guidelines and recommendations generated by the ten 62 groups, which include investigations into multiple methodologies such as cognition/functional 63 assessment, biomarkers and biobanking, imaging, health and social outcomes, and pre-symptomatic 64 ND. All of these were published in reports that are now publicly available online. 65
Splicing and Immunomodulatory Function : A Gene with Extensive Alternative LST1

The gene of the leukocyte-speciﬁc transcript (LST1) is encoded within the TNF region of the human MHC. The LST1 gene is constitutively expressed in leukocytes and dendritic cells, and it is characterized by extensive alternative splicing. We identiﬁed 7 different LST1 splice variants in PBMC; thus, 14 LST1 splice variants (LST1/A-LST1/N) have been detected in various cell types. These isoforms code for transmembrane as well as soluble LST1 proteins characterized by two alternative open reading frames at their 3 * end. We demonstrate the presence of the transmembrane variant LST1/C on the cell surface of the monocytic cell lines U937 and THP1. Recombinant expression of LST1/C permitted its profound inhibitory effect on lymphocyte proliferation to be observed. In contrast, the alternative transmembrane variant LST1/A, the extracellular domain of which shows no amino acid sequence homology to LST1/C exerted a weaker but similar inhibitory effect on PBMC. These data demonstrate the protein expression of LST1 on the cell surface of mononuclear cells, and they show an inhibitory effect on lymphocyte proliferation of two LST1 proteins although they have only a very short amino acid homology. The Journal of Immunology, 2000, 164: 3169–3176. short of chromosome 6 MHC class IV TNF complex The MHC class IV region telomeric part of the former MHC III complex, and it
Emotion Recognition using Python

Human-computer contact will be more natural if computers can perceive and respond to nonverbal communication such as emotions. Although various ways to recognizing human emotions based on facial expressions or speech have been presented, there has been relatively little effort done to merge these two modalities, as well as others, to improve the accuracy and robustness of the emotion detection system. This research examines the benefits and drawbacks of systems that rely solely on facial expressions or audio data. Facial expression recognition is a subset of facial recognition that is gaining in importance as the need for it grows.
EVALUATION MODEL FOR THE USABILITY OF WEB-BASED LEARNING MANAGEMENT SYSTEMS WITH USER PROFILE

The main purpose of Web-Based Educational Resources Management Systems (WERMSs) is to deliver knowledge, share information to help learners in their learning activities with an effective and efficient way by involving advanced electronic technologies. However, the Usability of these systems that is the degree of these systems to enable their users to use them effectively, efficiently and with satisfaction in a specified context of use, is one the challenges faced in the design of these systems. One of the main purposes of Human Computer Interaction (HCI) is using usability concept to create WERMSs that provide a relationship between user information and the WERMSs-content. Consequently, the next step is to evaluate the WERMSs will be based on usability metrics. This paper proposes a model for usability of WERMSs. The model introduced effectiveness, efficiency satisfaction, learnability, interactivity, consistency, motivation, learner's control, and user profile (age, gender, and level of experience) as the attributes that determine the usability of such systems. The model tested and verified using questionnaires and experiments. The results showed up that effectiveness, efficiency, satisfaction, learnability, motivation, interactivity, consistency, learner's control, and user profile (age, gender, and level of experience) affects the usability of WERMSs.
Follicles on the Antimesenteric Wall of the Identification of Multiple Isolated Lymphoid

We have revealed that 100–200 clusters, ﬁlled with closely packed lymphocytes, can be found throughout the length of the antimesenteric wall of the mouse small intestine. They are composed of a large B cell area, including a germinal center, and epithelia overlying the clusters contain M cells. A large fraction of B cells displays B220 (cid:1) CD19 (cid:1) CD23 (cid:1) IgM low IgD high CD5 (cid:2) Mac-1 (cid:2) phenotype, and the composition of IgA (cid:1) B cells is smaller but substantial. To our knowledge, these clusters are the ﬁrst identiﬁcation of isolated lymphoid follicles (ILF) in mouse small intestine. ILF can be ﬁrst detected at 7 (BALB/c mice) and 25 (C57BL/6 mice) days after birth, and lymphoid clusters equivalent in terms of cellular mass to ILF are present in germfree, athymic nude, RAG-2 (cid:2) / (cid:2) , TCR- (cid:3) (cid:2) / (cid:2) , and Ig (cid:4) -chain mutant ( (cid:4) m (cid:2) / (cid:2) ) mice, although c- kit (cid:1) cells outnumber B220 (cid:1) cells in germfree and athymic nude mice, and most lymphoid residents are c- kit (cid:1) B220 (cid:2) in RAG-2 (cid:2) / (cid:2) , TCR- (cid:3) (cid:2) / (cid:2) , and (cid:4) m (cid:2) / (cid:2) mice. ILF develop normally in the progeny of transplacentally manipulated Peyer’s patch (PP)-deﬁcient mice, and decreased numbers of conspicuously atrophied ILF are present in IL-7R (cid:5) (cid:2) / (cid:2) PP null mice. Neither ILF nor PP are detectable in lymphotoxin (cid:5) (cid:2) / (cid:2) and aly/aly mice that retain well-developed cryptopatches (CP) and thymus-independent subsets of intraepithelial T cells, whereas ILF, PP, CP, and thymus-independent subsets of intraepithelial T cells disappear from common cytokine receptor (cid:6) -chain mutant mice. These ﬁndings indicate that ILF, PP, and CP constitute three distinct organized gut-associated lymphoid tissues that reside in the lamina propria of the mouse small intestine. The Journal of Immunology, 2002, 168: 57–64.
Peak Caller: A Peak Calling Algorithm for DNase-seq Data

: With the development of bioinformatics, the performance of Next Generation Sequencing (NGS) technology is also improving. Peak detection is always a very active field in NGS, because the success of data analysis largely depends on the accuracy of peak detection. based on the characteristics of existing peak detection technology, in this paper we developed a peak detection algorithm for DNase-seq data analysis. The process of PeakCaller algorithm mainly includes the following three stages: 1) data preprocessing; 2) data analysis, which is specifically divided into a) detecting the genomic location of dnase-seq data, b) using gaussian convolution to trim configuration data, c) determining candidate peaks, and d) determining DHSS peaks; 3) algorithm performance evaluation. PeakCaller algorithm is a peak detection algorithm for DNase-seq data. PeakCaller is written in Python3. the algorithm is open source and available at: https://sourceforge.net/projects/peakcaller1/
A Novel Framework for Personalized and Context-aware Indoor Navigation Systems

—The recent indoor localization techniques use inertial sensors for position estimations in order to obtain a certain degree of freedom from RF solutions. Unfortunately, this dependency cannot be completely eliminated due to the cumulative errors introduced in the localization process; thus, RF or visual reference points are still necessary. In this paper we propose a novel approach for architectural design of indoor localization and navigation services by introducing a context-aware and extendable system framework. We exploit the ability to recognize certain human motion patterns and by using a scenario speciﬁc navigation language, for guiding the localization and position reﬁnement process, we will be able to control the navigation on a much ﬁner level. Therefore, in our system the reference points become needless or for scenarios with topological black holes at least the reﬁnement process is automated, the user can be omitted from ﬁnding these points.
Enabling RF/microwave devices using negative-refractive-index transmission-line metamaterials

In this paper, we are presenting the latest results on a number of RF/Microwave devices that we have developed at the University of Toronto based on transmission-line NRI materials. This includes a brief exposition of the effective medium theory for such TL NRI media followed by the presentation of a backward leaky-wave antenna radiating its fundamental spatial harmonic. This followed by a peculiar planar coupled-line coupler in which the phase flow is co-directional but the power flow is contradirectional leading to a high coupling level. Finally, a class of metamaterial phase-shifting lines is presented that offer phase shifts around the 360-degree mark at a small length and with a high bandwidth and linearity.
Algorithms for Intersection Graphs of 𝑡 -Intervals and 𝑡 -Pseudodisks

Intersection graphs of planar geometric objects such as intervals, disks, rectangles and pseudodisks are well-studied. Motivated by various applications, Butman et al. (ACM Trans. Algorithms, 2010) considered algorithmic questions in intersection graphs of 𝑡 -intervals. A 𝑡 -interval is a union of 𝑡 intervals—these graphs are also referred to as multiple-interval graphs. Subsequent work by Kammer et al. (APPROX-RANDOM 2010) considered intersection graphs of 𝑡 -disks (union of 𝑡 disks), and other geometric objects. In this paper we revisit some of these algorithmic questions via more recent developments in computational geometry. For the minimum-weight dominating set problem in 𝑡 -interval graphs, we obtain a polynomial-time 𝑂 ( 𝑡 log 𝑡 ) -approximation algorithm, improving upon the previously known polynomial-time 𝑡 2 -approximation by Butman et al. (op. cit.). In the same class of graphs we show that it is NP -hard to obtain a ( 𝑡 − 1 − 𝜖 ) -approximation for any ﬁxed 𝑡 ≥ 3 and 𝜖 > 0. The approximation ratio for dominating set extends to the intersection graphs of a collection of 𝑡 -pseudodisks (nicely intersecting 𝑡 -tuples of closed Jordan domains). We obtain an Ω ( 1 / 𝑡 ) -approximation for the maximum-weight independent set in the