Miracle-dz/UniFAR-FTUs huggingface dataset:
A simulation model for the transient effects of climate change on forest landscapes

Prentice, I.C. , Sykes, M.T. and Cramer, W. , 1993. A simulation model for the transient effects of climate change on forest landscapes. Ecol. Modelling, 65: 51-70. Forests are likely to show complex transient responses to rapid changes in climate. The model described here simulates the dynamics of forest landscapes in a changing environment with simple phenomenological equations for tree growth processes and local environmental feedbacks. Tree establishment and growth rates are modified by species-specific functions describing the effects of winter and summer temperature limitations, accumulated annual foliage net assimilation and sapwood respiration as functions of temperature, CO 2 fertilization, and growing-season drought. These functions provide external conditions for the simulation of patch-scale forest dynamics by a forest succession model, FORSKA, in which all of the trees on each 0.1 ha patch interact by competition for light and nutrients. The landscape is simulated as an array of such patches. The probability of disturbance on a patch is a power function of time since disturbance. Forest structure, composition and biomass simulated for the landscape average in boreal and temperate deciduous forests approach reasonable equilibrium values in 200-400 years. A climatic warning scenario is applied to central Sweden, where temperature and precipitation increases are shown to interact with each other and with soil water capacity in determining the transient and equilibrium responses of the forest landscape to climate change.
Scalar field interacting with torsion and gravity

A non linear scalar field equation is proposed whose non linearity arises from an interaction between the scalar field and the trace of the torsion field. Correspondingly the scalar and gravitational field actions with torsion are defined. By requiring the total Action invariance with respect to arbitrary metric tensor variation, an Einstein-like field equation with torsion is obtained. Its formal consistency is directly checked. A cosmological interpretation of the coupled Einstein-scalar field equation is then proposed in the Robertson Walker space-time. It is shown that the three derived equations in two time functions are compatible. The equations are exactly solved for mass less scalar field in the flat space time and in the open space time case.
An Empirical Study of the Impact of Review Extremity on Negative Online Review Helpfulness

Original Research Article Previous studies did not discuss extremely positive and extremely negative reviews separately, which leads to inconsistent conclusions regarding the role of review extremity in predicting review helpfulness. Meanwhile, the direct relationship between review extremity and review helpfulness has been extensively explored in literature, but few studies on the moderating effect are available to reveal the boundary conditions of this effect. Therefore, this study focuses on the impact of extremity of negative reviews on the helpfulness of reviews and further explores the moderating role of review characteristics and product type. 86,930 negative reviews of hotels from Ctrip.com were used to perform Negative binomial regression to test our research model. Our findings reveal that for negative reviews, review extremity has a significant positive impact on review helpfulness, and the impact is much stronger when negative reviews are associated with lower hotel star level, photos and longer length. This study enriches the theoretical research of online review helpfulness and provides some managerial suggestions for online platforms and enterprise managers.
ControVol: A framework for controlled schema evolution in NoSQL application development

Building scalable web applications on top of NoSQL data stores is becoming common practice. Many of these data stores can easily be accessed programmatically, and do not enforce a schema. Software engineers can design the data model on the go, a flexibility that is crucial in agile software development. The typical tasks of database schema management are now handled within the application code, usually involving object mapper libraries. However, today's Integrated Development Environments (IDEs) lack the proper tool support when it comes to managing the combined evolution of the application code and of the schema. Yet simple refactorings such as renaming an attribute at the source code level can cause irretrievable data loss or runtime errors once the application is serving in production. In this demo, we present ControVol, a framework for controlled schema evolution in application development against NoSQL data stores. ControVol is integrated into the IDE and statically type checks object mapper class declarations against the schema evolution history, as recorded by the code repository. ControVol is capable of warning of common yet risky cases of mismatched data and schema. ControVol is further able to suggest quick fixes by which developers can have these issues automatically resolved.
ePubWU Institutional Repository

In networked MNCs where knowledge and power are distributed, corporate strategy processes benefit from input arising from many different levels of the organization. Recently, the regional (i.e., supra-national) level has been emphasized as an important additional source of knowledge and input, and as a bridge between local subsidiaries and global corporate headquarters This paper builds theory on the antecedents to regional headquarters’ influence on corporate decisions (i.e., organizational, behavioral, and motivational). Based on a survey of regional headquarters in Europe and their relations with MNC headquarters, we provide empirical evidence that a regional headquarters’ autonomy and signaling behavior have significant effects on its influence on corporate strategy. Furthermore, we find support for our hypothesis that the regional headquarters’ charter moderates such bottom-up influence.
Segmenting Snow Scene from CCTV using Deep Learning Approach

Recently, data from many sensors has been used in a disaster monitoring of things, such as river wa- ter levels, rainfall levels, and snowfall levels. These types of numeric data can be straightforwardly used in a further analysis. In contrast, data from CCTV cameras (i.e. images and/or videos) cannot be easily interpreted for users in an automatic way. In a tra- ditional way, it is only provided to users for a visual- ization without any meaningful interpretation. Users must rely on their own expertise and experience to interpret such visual information. Thus, this paper proposes the CNN-based method to automatically in- terpret images captured from CCTV cameras, by us- ing snow scene segmentation as a case example. The CNN models are trained to work on 3 classes: snow, non-snow and non-ground. The non-ground class is explicitly learned, in order to avoid a confusion of the models in differentiating snow pixels from non- ground pixels, e.g. sky regions. The VGG-19 with pre-trained weights is retrained using manually la- beled snow, non-snow and non-ground samples. The learned models achieve up to 85% sensitivity and 97% specificity of the snow area segmentation.
The effect of Facebook use on academic job performance / Nina Farisha Isa... [et al.]

As an academic use of social networking sites (SNS) has been playing a vital role in the way of doing business in education industry. Therefore, the present study is to propose a concept of ‘task characteristics’ using task- technology fit model. In this regard, this paper extend knowledge from Lee and Lee (2018) model that examine the use of Facebook on office workers. However, there is still lack of study about the relationship between SNS use and job performance in the context of academic industry especially in hospitality and tourism faculty. Thus, this study has implications for academic industry that are concerned about formulating policies related to academic use of SNS.
System Identification of Static Nonlinear Elements: A Unified Approach of Active Learning, Over-fit Avoidance, and Model Structure Determination

Systems containing linear first-order dynamics and static nonlinear elements (i.e., nonlinear elements whose outputs depend only on the present value of inputs) are often encountered; for example, certain automobile engine subsystems. Therefore, system identification of static nonlinear elements becomes a crucial component that underpins the success of the overall identification of such dynamical systems. In relation to identifying such systems, we are often required to identify models in differential equation form, and consequently, we are required to describe static nonlinear elements in the form of functions in time domain. Identification of such functions describing static elements is often a black-box identification exercise; although the inputs and outputs are known, correct mathematical models describing the static nonlinear elements may be unknown. Therefore, with the aim of obtaining computationally efficient models, calibrating polynomial models for such static elements is often attempted. With that approach comes several issues, such as long time requirements to collect adequate amounts of measurements to calibrate models, having to test different models to pick the best one, and having to avoid models over-fitting to noisy measurements. Given that premise, this paper proposes an approach to tackle some of those issues. The approach involves collecting measurements based on an uncertainty-driven Active Learning scheme to reduce time spent on measurements, and simultaneously fitting smooth models using Gaussian Process (GP) regression to avoid over-fitting, and subsequently picking best fitting polynomial models using GP-regressed smooth models. The principles for the single-input-single-output (SISO) static nonlinear element case are demonstrated in this paper through simulation. These principles can easily be extended to MISO systems.
Analyzing the Resonance Resultant from the Capacitive Effects in Bulk Current Injection Probe

In this paper, the effect of the slot distance, existed between the two parts of BCI-probe shield, on its performance is studied, therefore, two ferrite materials with the same size and different characteristics are used to implement two identical BCI-probes. The input impedance and reflection coefficient are measured for four different values of slot distance 0.5, 1, 2 and 3 mm. Practical results show a notable effect of the slot distance on measured quantities. Measured impedance analysis shows the appearance of three capacitive regions in its spectra, therefore, a three dimensional electromagnetic (EM) model is implemented in CST-Microwave Studio (MWS) software to disclose the main source parameters responsible for it. Results of achieved study, using developed EM model, were in accordance with measured data for the implemented prototypes, and showed the same resonance phenomena.
A Frame Work for Classification of Multi Class Medical Data based on Deep Learning and Naive Bayes Classification Model

— From the past decade there has been drastic development and deployment of digital data stored in electronic health record (EHR). Initially, it is designed for getting patient general information and performing health care tasks like billing, but researchers focused on secondary and most important use of these data for various clinical applications. In this paper we used deep learning based clinical note multi-label multi class approach using GloVe model for feature extraction from text notes, Auto-Encoder for training based on model and Navie basian classification and we map those classes for multi-classes. And we perform experiments with python and we used libraries of keras, tensor flow, numpy, matplotlib and we use MIMIC-III data set. And we made comparison with existing works CNN, skip-gram, n-gram and bag-of words. The performance results shows that proposed frame work performed good while classifying the text notes.
The role of ownership map in constraining discretionary loan loss-provisions decisions in Jordanian banks

Abstract Banks’ shareholders are mainly concerned with maximizing their profits. As a result of passing their monitoring tasks to another group (managers), the maximization goal could be threatened by manipulating bank’s provisions to accomplish a specific set of goals for managers. Hence, introducing active owners in banks ownership map is expected to reduce the agency problem among the different groups inside the bank. In line with this argument, this study aims mainly to explore the monitoring ability of different types of owners within the Jordanian banks listed on the Amman Stock Exchange in reducing the adoption of loan loss provisions (LLP) techniques to manipulate earnings figures. Selecting fifteen listed banks between 2013 and 2018, and applying a multivariate analysis, guide to the main findings of the study which introduced foreign owners, institutional owners, and blockholders owners as deterrent players in accepting LLP manipulations. However, family and managerial ownership showed a low level of conservatism in reducing LLP techniques within the Jordanian banking sector. The findings of this study present several shares of evidences that the ownership map in Jordanian banks needs more efforts and experience to protect bank’s earnings from being expropriated by banks boards members. Interestingly, this study adds to the current literature by exploring the roles of the various types of owners in constraining LLP techniques from a developing market such as Jordan.
UNIVERSIDADE FEDERAL DO RIO GRANDE DO NORTE INSTITUTO DO CÉREBRO PROGRAMA DE PÓS-GRADUAÇÃO EM NEUROCIÊNCIAS LABORATÓRIO DE NEURODINÂMICA DISSERTAÇÃO DE MESTRADO EFEITOS DA NICOTINA NO COMPLEXO DO SEPTO MEDIAL NA VIA SEPTOHIPOCAMPAL EM CAMUNDONGOS ANESTESIADOS POR KETAMINA

GÓIS, José Henrique Targino Dias. Effects Of Nicotine In The Medial Septum Complex On The Septohippocampal Pathway In Ketamine Anaesthetised Mice. 2015. 81f. Dissertação (Mestrado em Neurociências) – UFRN. Programa de Pósgraduação em Neurociências. Natal, 2015. Nicotine administration in humans and rodents enhances memory and attention, and also has a positive effect in Alzheimer's Disease. The Medial Septum / Diagonal Band of Broca complex (MS/DBB) – a main cholinergic system – massively projects to the hippocampus through the fimbria-fornix, and this pathway is called the septohippocampal pathway. It has been demonstrated that the MS/DBB acts directly on the local field potential (LFP) rhythmic organization of the hippocampus, especially in the rhythmogenesis of Theta (4-8Hz) – an oscillation intrinsically linked to hippocampus mnemonic function. In vitro experiments gave evidence that nicotine applied to the MS/DBB generates a local network Theta rhythm within the MS/DBB. Thus, the present study proposes to elucidate the function of nicotine in the MS/DBB on the septo-hippocampal pathway. In vivo experiments compared the effect of MS/DBB microinfusion of saline (n=5) and nicotine (n=8) on Ketamine/Xylazine anaesthetized mice. We observed power spectrum density in the Gamma range (35 to 55 Hz) increasing in both structures (Wilcoxon Rank-Sum test, p=0.038) but with no change in coherence between these structures in the same range (Wilcoxon Rank-Sum test, p=0.60). There was also a decrease in power of the ketamineinduced Delta oscillation (1 to 3 Hz). We also performed in vitro experiments on the effect of nicotine on membrane voltage and action potential. We patch-clamped 22 neurons in current-clamp mode; 12 neurons were responsive to nicotine, half of them increased firing rate and other 6 decreased, and they significantly differed in action potential threshold (-47.3±0.9 mV vs. -41±1.9 mV, respectively, p=0.007) and halfwidth time (1.6±0.08 ms vs. 2±0.12 ms, respectively, p=0.01). Furthermore, we performed another set of in vitro experiments concerning the connectivity of the three major neuronal populations of MS/DBB that use acetylcholine, GABA or glutamate as neurotransmitter. Paired patch-clamp recordings found that glutamatergic and GABAergic neurons realize intra-septal connections that produce sizable currents in MS/DBB postsynaptic neurons. The probability of connectivity between different neuronal populations gave rise to a MS/DBB topology that was implemented in a realistic model, which corroborates that the network is highly sensitive to the generation of Gamma rhythm. Together, the data available in the full set of experiments suggests that nicotine may act as a cognitive enhancer, by inducing gamma oscillation in the local circuitry of the MS/DBB. Key-words: Medial septum; Hippocampus; Nicotine; Electrophysiology; Mice.
The Role of Lung Ultrasonography in Etiologic Diagnosis of Acute Dyspnea in a Resource Limited Setting

The aim of the current study was to describe lung ultrasonography (LUS) characteristics and to evaluate the agreement between LUS and chest radiography (CXR) in diagnosis of four conditions causing most acute dyspnea in children, namely, pneumonia, pleural effusion, pneumothorax and acute pulmonary edema in children at a teaching hospital in Vietnam. We reviewed the records of the chidren between January and June 2018, who presented to emergency department (ED) or pediatric intensive care unit (PICU) at children hospital 1 (CH1) with acute dyspnea and had final diagnosis of one of four etiologies including pneumonia, pleural effusion, pneumothorax and acute pulmonary edema. All patients underwent CXR and LUS at the time of admission. Eighty-one children with acute dyspnea including pneumonia (n=65, 80%), pleural effusion (n=9, 11%), pneumothorax (n=3, 4%) and acute pulmonary edema (n=4, 5%) were enrolled. LUS was identified among 100% of cases with pleural effusion and pneumothorax (CXR only showed 73.3% and 50%, respectively); 92.3% of cases with pneumonia (CXR showed 93.8%) and only 75% of cases with acute pulmonary edema (CXR showed 50%). When comparing LUS with CXR, we noticed a good agreeement between the 2 methods in the diagnosis of pneumonia (kappa=0.64, p<0.001). LUS was shown to be a feasible and non-invasive technique which can help clinicians to comfirm the etiology of acute pulmonary dyspnea.
Self–Assembled Peptide Nanostructures for Biomedical Applications: Advantages and Challenges

Over the last 20 years, self-assembled nanostructures based on peptides have been investigated and presented as biomaterials with an impressive potential to be used in different bionanotechnological applications such as sensors, drug delivery systems, bioelectronics, tissue reparation, among others. Several advantages (mild synthesis conditions, relatively simple functionalization, low-cost and fast synthesis) confirm the promise of these biological nanostructures as excellent candidates for such uses. Through self-assembly, peptides can give rise to a range of well-defined nanostructures such as nanotubes, nanofibers, nanoparticles, nanotapes, gels and nanorods. However, there are several challenges that have yet to be extensively approached and solved. Issues like controlling the size during synthesis, the stability in liquid environments and manipulation have to be confronted when trying to integrate these nanostructures in the development of sensing devices or drug-delivery systems. The fact that these issues present difficulties is reflected in the low number of devices or systems using this material in real applications. The present chapter discusses these challenges and presents possible solutions. A review of the state-of-the-art work concerning the use of peptide self-assembled structures in biomedical applications is given. Additionally, our findings regarding the on-chip synthesis of peptide self-assembled nanotubes and nanoparticles, their controlled manipulation, as well as electrical and structural characterizations are introduced. Our latest results showing the interaction of peptide self-assembled structures with cells for the development of a combined sensing/cell culture platform and the use of these material in clean-room processes together with the stability of the biological structures in liquid are also presented.
Making Simple Electric Circuit with Potato: Introducing Easy DIY Science Lab Activity to Secondary School Students

Laboratorium activity and experiment related to Dynamic Electricity topic in secondary schools have always been a “scary” thing to science teachers in Indonesia, especially to those with more experience in teaching Biology than Physics. To our surprise, the problem was more related to teacher’s confidence to conduct lab acitivy rather than to the availability of experiment kit in school. Our visit to two schools in Padang revealed that each school has sufficient amout of experiment kit for Electricity but the science teachers were too scared to take students to lab and get nervous when something is not working, or too scared to damage the kit. Therefore, we would like to offer a solution to overcome this problem by intoducing an easy do-it-yourself simpe electricity circuit with potato. The activity is expected to build more confidence in teachers to conduct lab activity and make science learning more fun to the students. Keywords — electric circuits, electricity from potato, school science, simple science experiment, dynamic electricity
SOCIAL-ECONOMIC ANALYSIS OF PHYSICAL INTEGRATION BETWEEN BRAZIL AND PERU: FOCUS FOR THE REGIONS LINKED TO THE INTEROCEANIC HIGHWAY

The objective of the study was to estimate the impact of the interoceanic highway construction on trade facilitation between Brazil and Peru, especially in the states linked to the highway. The methodology starts from a panel data econometric approach. The results indicate a positive impact of highway construction on trade facilitation for the linked states. On the other hand, a positive relationship was found between greater distance and trade flow, which is justified by the fact that the more developed states and, therefore, with greater trade flow are located farther than the border of both countries.