Miracle-dz/UniFAR-FTUs huggingface dataset:
Electronic Structure and Band Alignment of LaMnO<sub>3</sub>/SrTiO<sub>3</sub> Polar/Nonpolar Heterojunctions

DOI: 10.1002/admi.201801428 continues to be a subject of debate,[2] the original report has led to an explosion of research exploring the fascinating physics that can occur at polar/nonpolar oxide interfaces. Like LAO, orthorhombic perov­ skite LaMnO3 (LMO) consists of formally polar (LaO)/(MnO2) layers in the pseu­ docubic [001] growth direction. Unlike LAO, however, bulk LMO exhibits A­type antiferromagnetic ordering below a Néel transition temperature of ≈140 K. [3] High­ spin Mn3+ ↑ ↑ t e ( ) 2g 3 g 1 exhibits strong Jahn– Teller splitting; cooperative distortions of the oxygen octahedra and subsequent C­type orbital ordering below ≈780 K lifts the degeneracy of the eg band, resulting in electron localization and causing LMO to be a p­type Mott–Hubbard insulator. [4–6] The orbital ordering of LMO is also influ­ enced by magnetic superexchange. [4,7] In contrast to many other transition metal perovskites, bulk LMO can readily accommodate both oxygen deficiency (through the formation of oxygen vacancies and compensating Mn2+) and oxygen excess (through the formation of an equal number of La and Mn cation vacancies). [8] A large built­in electric field of 0.24 V Å−1[9] is predicted to occur on the LAO side of LAO/STO heterojunctions for LAO thicknesses less than the critical thickness for electronic reconstruction. This electric field has never been observed in experiments designed to detect it,[2,10,11] although a weaker, residual electric field has been inferred in thicker, electronically The behavior of polar LaMnO3 (LMO) thin films deposited epitaxially on nonpolar SrTiO3(001) (STO) is dictated by both the LMO/STO band alignment and the chemistry of the Mn cation. Using in situ X-ray photoelectron spectroscopy, the valence band offset (VBO) of LMO/STO heterojunctions is directly measured as a function of thickness, and found that the VBO is 2.5 eV for thicker (≥3 u.c.) films. No evidence of a built-in electric field in LMO films of any thickness is found. Measurements of the Mn valence by Mn L-edge X-ray absorption spectroscopy and by spatially resolved electron energy loss spectra in scanning transmission electron microscopy images reveal that Mn2+ is present at the LMO surface, but not at the LMO/STO interface. These results are corroborated by density functional theory simulations that confirm a VBO of ≈2.5 eV for both ideal and intermixed interfaces. A model is proposed for the behavior of polar/nonpolar LMO/STO heterojunctions in which the polar catastrophe is alleviated by the formation of oxygen vacancies at the LMO surface.
Stay or Leave? The Perceived Organizational Support, Affective Commitment, and Desire to Remain Among Lebanese High Performing Employees

For many decades, researchers have studied perceptions of organizational support and employees' work outcomes. The Perceived Organizational Support (POS) supposes that in order to define the extent of organization‟s willingness to reward efforts, employees compose general beliefs with regards to the degree to which their organizations value their contributions and show interest for their wellbeing (Eisenberger, Huntington, Hutchison, & Sowa, 1986). Two of the most regarded outcomes of POS are employees‟ affective commitment (AC) and desire to remain (DTR) with their organizations. This study used the data of 457 high performing employees among Lebanese companies in order to examine the effect of their perceptions of organizational support. Particularly, this research examined the role of POS in enhancing the affective commitment and desire to remain of high performing employees and it indicated the mediating role of affective commitment in the relationship between POS and DTR. The study resulted in high levels of perception of organizational support as well as of the affective commitment and that of desire to remain. Furthermore, the affective commitment mediated the relationship. Other constructive findings revealed the moderating role of the Job levels where it shows to strengthen the relationship of POS and DTR. The control variables, age, gender, performance rate, and educational level revealed strong correlations with the model variables.
A Comparative Study of Performance of ZVS and ZCS Converter Circuits

The comparative result of the performance parameters of resonant converters [ZVS (zero-voltage switching) and ZCS (zerocurrent switching) with buck converter is presented in this paper. ZVS and ZCS circuits are employed to eliminate the switching losses at high switching frequencies in device using resonance. A zero-current switch shapes the switch current waveform during its conduction time to create a zero-current condition for the switch to turn-off. A zero-voltage switch shapes the switch voltage waveform during the off time to create a zero-voltage condition for the switch to turn-on. IndexTerms Soft switching, resonant converters, zero-voltage switching (ZVS), zero-current switching (ZCS), THD, Power factor. ________________________________________________________________________________________________________
Effectiveness of infiltration galleries in reduction of surface runoff and flooding in urban areas Efficacité des galeries d'infiltration dans la réduction des eaux de ruissellement et des inondations en milieu urbain

Many times the design of drainage structures for storm water management (SWM) follows the conventional approach of conveying flows downstream as quickly as possible. Consequently, low lying and mostly urban poor areas suffer flooding problems. As a solution, the land upstream can be utilized to its maximum potential by incorporating infiltration practices that allow water to infiltrate before it is released downstream. This paper is based on a case study research project carried out at a plot scale on Makerere hill, Kampala, Uganda focused on investigation of the effectiveness of appropriately designed infiltration galleries on reduction of surface runoff. Results indicated that use of infiltration galleries can result into a 40% percentage reduction in the generated runoff. The results further suggested that this reduction is dependent on the soil permeability, size of available land and the size and number of perforated embedded pipes used for the infiltration structure.
Identification of disease-miRNA networks across different cancer types using the SWIM software

The idea that the greater complexity of higher eukaryotes arises from the portion of the genome called non-coding RNAs (ncRNAs) is becoming increasingly widespread [Costa 2008, Mattick 2009]. Indeed, ncRNAs are of growing interest, as they have been found to be important regulators of gene expression in development, physiology, and, when dysfunctional, in the presence of disease. This variegated class of RNA species encompasses the well-known microRNAs (miRNAs), as well as the most recently acknowledged long non-coding RNAs (lncRNAs). Discovered first, miRNAs have been intensively studied and much is now known about their biological functions, as opposed to lncRNAs that constitutes a new, potentially
Effects of Cleavers (Galium aparine) and Yarrow (Achillea millefolium) Extracts on Rumen Microbial Fermentation in In-vitro Semi- Continuous Culture System (RUSITEC)

Experimental data on the effects of cleavers (Galium aparine) and yarrow (Achillea millefolium) extracts on rumen microbial fermentation are scarce. The objective of this study was to determine the effects of cleavers and yarrow extracts on in vitro ruminal fermentation. Incubation trial was carried out using the long-term rumen simulation technique (RUSITEC). The experiment lasted 10 days. After an adaptation period of 5 days, the fermentation vessels divided into 3 groups; first three vessels received no additives (control), second three vessels received 500 mg/L cleavers extract daily, and third three vessels received 500 mg/L yarrow extract daily. Supplementations of cleavers and yarrow extracts had no significant effect on ruminal pH, total volatile fatty acids (VFA), acetate, propionate and methane production, NH3-N concentration and, total protozoa. However, both extracts decreased dry matter digestibility (DMD) (P<0.05). Butyrate production, on the other hand, increased with cleavers extract (P<0.05). In conclusion, there were only small effects of cleavers and yarrow extracts on the investigated microbial fermentation characteristics. Nevertheless, it may be considered advantageous for feed conversion that plant extracts did not suppress ruminal fermentation in spite of decreasing DMD.
304-309 Furhan Iqbal.pmd

Babesia microti (B. microti) is an intra erythrocytic protozoan that mainly infects red blood cells and causes babesiosis. Its frequent hosts are rodents, ticks and humans. Dog’s blood samples (N = 150) were collected from three different districts in Punjab including Multan (N = 49), Islamabad/Rawalpindi (N = 49) and Lahore (N = 52) while 159 cat’s blood samples were collected from Lahore (N = 159). Data on the epidemiological characters of all animals (including age, gender, breed, body temperature, deworming, vaccination, mucus membrane status, hydration status, presence of hematuria and tick infestation) was collected through questionnaire. Polymerase chain reaction (PCR) amplified a 238 base pair amplicon specific for 18S rRNA gene of B. microti in two (1.3%) dog and 21 (13.2%) cat blood samples. Amplified PCR products were confirmed by DNA sequencing and the four partial 18S rRNA gene sequences were submitted to the EMBL/GenBank. Among epidemiological factors, high body temperature (P < 0.05) and pale mucous membrane (P < 0.05) were the parameters associated with the presence of B. microti in infected dogs. Females were found to be more infected (P = 0.05) than males and incidence of B. microti infection was higher in cat samples collected during winter months (P = 0.0001) than in summer. In conclusion, we are reporting the prevalence of B. microti in blood samples of cats and dogs from Pakistan for the first time and recommending that this Protozoan parasite should be considered for screening in cats and dogs with compatible clinical signs.
Weighted Encoding Technique for Removal of Mixed Noise in an Image

: In today’s modern age, digital images are used to transmit visual information, but the drawback is that images get corrupted with different noises after transmission. Image denoising technique recovers original high quality image from noisy image. Many detection based methods for mixed noise removal, including AWGN and IN noise have been proposed in recent years of research. This proposed method uses weighted encoding technique to remove AWGN & IN simultaneously. Using basis of PCA, the algorithm uses the dictionary which effectively explains the content of image. The proposed method, gives promising results with higher PSNR.
DAO: Data Aggregation and Offloading in Sensor Networks

When sensor networks are deployed in an inaccessible or inhospitable region, or under extreme weather, it is not usually viable to install a long-term base station in the field to collect data. The generated sensory data is therefore stored inside the network first. However, when more data is generated than available storage spaces in the entire network can possibly store, data loss arises. This problem is referred to as the overall storage overflow in sensor networks. In this thesis, a new algorithmic problem called the data aggregation and offloading problem (DAO) , is used to overcome overall storage overflow. By taking advantages of data spatial correlation that commonly exists among sensory data, the DAO aggregates overflow data to the size that can be accommodated by the available storage capacity in the network, and then offloads the aggregated data inside the network to be stored. The goal of the DAO is to minimize energy consumption incurred in the above data aggregation and data offloading process. The research shows that the DAO is NP-hard. To solve the DAO, a naive two-stage solution is first proposed, which is referred to as DAO-N, wherein data offloading strictly follows data aggregation. A more unified method that is based upon data replication techniques, referred to as DAO-R, is proposed in order to further reduce energy consumption. Specifically, a series of data replication algorithms is designed to integrate data aggregation and data offloading. A sufficient condition to solve DAO-R optimally is also provided. The research shows via extensive simulations that DAO-R outperforms DAO-N by approximately 20% in terms of energy consumption, under different network parameters.
DeepBrainSeg: Automated Brain Region Segmentation for Micro-Optical Images With a Convolutional Neural Network

The segmentation of brain region contours in three dimensions is critical for the analysis of different brain structures, and advanced approaches are emerging continuously within the field of neurosciences. With the development of high-resolution micro-optical imaging, whole-brain images can be acquired at the cellular level. However, brain regions in microscopic images are aggregated by discrete neurons with blurry boundaries, the complex and variable features of brain regions make it challenging to accurately segment brain regions. Manual segmentation is a reliable method, but is unrealistic to apply on a large scale. Here, we propose an automated brain region segmentation framework, DeepBrainSeg, which is inspired by the principle of manual segmentation. DeepBrainSeg incorporates three feature levels to learn local and contextual features in different receptive fields through a dual-pathway convolutional neural network (CNN), and to provide global features of localization by image registration and domain-condition constraints. Validated on biological datasets, DeepBrainSeg can not only effectively segment brain-wide regions with high accuracy (Dice ratio > 0.9), but can also be applied to various types of datasets and to datasets with noises. It has the potential to automatically locate information in the brain space on the large scale.
Malware Detection Method based on Control Flow Analysis

With the rapid development of computer technology and the iteration of malware, numerous computer malware detection methods have been proposed, among which malware detection based on machine learning has become an important research direction. Opcode sequences are often used as an important feature of machine learning models for training and testing. However, opcode sequences extracted orderly from raw disassembly text may not adequately reflect the behavior of executables. In order to solve this problem, this paper proposes a new malware detection method based on the control flow of executables. This method analyzes the control flow of executables and extracts execution traces from by the unit of function. This paper uses the execution traces to represent the behavior of the executables and present the execution traces by opcode sequences. In order to improve the training efficiency and reduce the feature dimensionality, this paper propose an x86 intermediate code. Then we convert the opcode sequences into the corresponding intermediate code sequences and vectorize them using Vector Space Model (VSM) for training and testing. This paper implements Naïve Bayes Classifier, Support Vector Machines and Random Forest for classification. The experiment result shows that the Random Forest algorithm has the best performance, with an accuracy of 90.8% and the model establishment time is 22s. Compared with the traditional methods based on disassembly text, the accuracy is improved by 1.4%, compared with the methods using x86 opcode, the efficiency is increased by 62%.
Simulating the Cascading Effects of an Extreme Agricultural Production Shock: Global Implications of a Contemporary US Dust Bowl Event

Higher temperatures expected by midcentury increase the risk of shocks to crop production, while the interconnected nature of the current global food system functions to spread the impact of localized production shocks throughout the world. In this study, we analyze the global potential impact of a present-day event of equivalent magnitude to the US Dust Bowl, modeling the ways in which a sudden decline in US wheat production could cascade through the global network of agricultural trade. We use observations of country-level production, reserves, and trade data in a Food Shock Cascade model to explore trade adjustments and country-level inventory changes in response to a major, multiyear production decline. We find that a 4-year decline in wheat production of the same proportional magnitude as occurred during the Dust Bowl greatly reduces both wheat supply and reserves in the United States and propagates through the global trade network. By year 4 of the event, US wheat exports fall from 90.5 trillion kcal before the drought to 48 trillion to 52 trillion kcal, and the United States exhausts 94% of its reserves. As a result of reduced US exports, other countries meet their needs by leveraging their own reserves, leading to a 31% decline in wheat reserves globally. These findings demonstrate that an extreme production decline would lead to substantial supply shortfalls in both the United States and in other countries, where impacts outside the United States strongly depend on a country's reserves and on its relative position in the global trade network.
Traffic Flow Prediction Based on Self-attention Mechanism and Deep Packet Residual Network

Traffic flow forecasting is an important function of a traffic information system. In recent years, it has become a research hotspot of experts and scholars in the field of transportation. The traffic flow is affected by spatiotemporal factors, so the traffic flow data is highly nonlinear and complex, which makes the flow data difficult to predict accurately. Therefore, the previous traffic prediction model does not have accuracy and reliability. Under the circumstances, this paper proposes a self-attention mechanism-based packet residual network model (SA-Res2Net) to predict urban traffic flow. Firstly, the internal pixel connection and global correlation of the New York bike data is enhanced through the Self-Attention mechanism. Then, the Attention Map is input into the Res2Net model and divided into 8 channels of in and out traffic data to extract the spatiotemporal correlation of traffic flow with finer-grained multi-scale features. The experimental results show that compared with other traditional models, the model in this paper is of satisfactory predictive value.
A Novel Dynamic Energy Model for the Energy-Harvesting IoT Node

In this paper, we propose a novel dynamic energy model composed of a differential equation to describe the energy evolution of an IoT node, especially for the energy-harvesting-basedIoT node. By analyzing the state which is defined as the energy buffered in the node, a novel dynamic energy model is developed to characterize the process of energy harvest and consumption. By analyzing the specific energy harvesting mode and consuming activity, the concrete forms of the model can be obtained. Then some characteristics of the energy harvesting IoT node support, can be obtained. Finally, some experiments are designed to verify the model.
Child Labour and Schooling of Children in Rural Bangladesh : A Multinomial Logit Model on Determinants .

+8801755593699 +8801755593699 +Abstract This paper seeks better understanding the determinants of child labour and schooling of rural children in Bangladesh. Although literature identified the foremost factors of child labour which constrain schooling attainment of children, however literature has not clarified which determinants encourage children to combine school and work during their study period or solely work without schooling and how the effects of factors vary according to the gender of children as well. The present study contributes to fulfilling these gaps by studying the rural children of Bangladesh. Results show that some particular factors significantly affect to increase to combined (school and work) or work only outcomes and the effect size (size of odds) varies according to the gender of children. There is no significant factor which has a larger effect on the work only outcome for females compared to males.
Medical Policy Manual FEP 2 . 01 . 54 Endovascular Procedures for Intracranial Arterial Disease ( Atherosclerosis and Aneurysms ) Effective Policy

Intracranial arterial disease includes thromboembolic events, vascular stenoses, and aneurysms. Endovascular techniques have been investigated for the treatment of intracranial arterial disease. Endovascular therapy is used as an alternative or adjunct to intravenous tissue plasminogen activator and supportive care for acute stenosis and as an adjunct to risk-factor modification for chronic stenosis. For cerebral aneurysms, stent-assisted coiling and the use of flow-diverting stents have been evaluated as an alternative to endovascular coiling in patients whose anatomy is not amenable to simple coiling.
The Research of The Optimized Three-Dimensional Model Algorithm Based on Polygonal Segmentation

: Three-dimensional models are commonly used to describe the display requirements of 3D virtual objects in complex scenes. For the triangular grid model of complex objects, its huge amount of data to the storage, transmission and rendering, etc. has brought great difficulties. On the basis of summarizing the existing algorithms, this paper presents a general triangular simplification algorithm for polygon regions. The algorithm is applied to the triangular plane on a plane, and the two vertices are formed by using the coordinates of the known triangular plane in the space to form the data record, compare and delete the same coordinate record, and use the remaining data to record the polygon. The triangulation of the polygon is re-divided, and a new simplified model is formed to improve the performance of the algorithm effectively. The experimental results show that the algorithm is effective and feasible by using the triangulation model, indicating that the algorithm is practical and effective.
Electric Power Outages and the Productivity of Small and Medium Enterprises in Senegal By

This paper assesses the impact of electricity outages on firms’ productivity in Senegal, using cost technical and allocative efficiency scores. Results based on survey data from 528 businesses indicate that power outage duration has a positive significant effect on cost and technical efficiencies, and SMEs were more successful in doing so than larger ones. Further, power outages’ frequency, duration and their perceived severity have negative effects on scale efficiency. Finding a solution to the power outage issue while affecting negatively cost efficiency, seems to promote technical and scale efficiencies. Further, having a loans and/or a credit line appeared to have positive effects on technical and scale efficiencies. JEL Classification Codes: D24, L94.
SOTICS 2016

— TV broadcasters are increasingly adopting social TV strategies to affect the viewers’ online behavior. The research done so far suggests that different drivers play different roles and their effects are different according to the specific type of online behavior. In order to extend this research, through hierarchical linear regression models, we compare the effects of the different drivers on the online behavior of “influencers”, i.e., users having a large number of followers, and “ordinary” users. Despite some limitations, we show relevant differences between the online behaviors of these two kinds of users, particularly the social TV strategies do not affect the online behavior of the “influencers”, while some of them affect the online behavior of “ordinary” users