Miracle-dz/UniFAR-FTUs huggingface dataset:
Curriculum Management Challenges, Obstacles For Government And Private Pupils’ Academic Performance Results In Mozambique

This study examined curriculum management styles applied by government and private schools in different pupils’ academic performance levelsin reading, writing, counting as well as Grade Seven results and proposepotential solutions. The study was undertaken through mixed methods and underpinned by pragmatism philosophy. The design for this study was concurrent triangulation. The population of the study included Grade Three pupils, teachers, and head teachers, ministry of education officials, parents and guardians. Probability and purposive sampling techniques were used to select . pupils and 45 participants respectively. Quantitative data were collected through. Data were analysed through . Qualitative data were generated using interviews, documents analysis and observations. The data were analysed using grounded theory. The key result was that pupils learning in public primary schools did not performe well in reading, writing and countingas compared to pupils from private primary schools.Private schools’ pupils perfomed well because they had well experienced teachers and there are well organsed. The key finding was that government schools’ classrooms are overloaded, the teachers are demotivated, schools’ infrastructure is dilapidated and the head teachers do not have enough financial resources to manage the schools effectively. The study concludes that inequality in academic performance at the early ages of the education system impacts on the achievement of sustainable development goals. The study recommends that the government allocates more financial resources to the education system and that government school curriculum managers implement the curriculum in collaboration with teachers, school committee, parents and guardians. -------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 18-03-2020 Date of Acceptance: 03-04-2020 -------------------------------------------------------------------------------------------------------------------------------------
IMPLICIT SHAPE MODELS, MODEL SELECTION, AND PLANE SWEEPING FOR 3D FACADE INTERPRETATION

: In this paper we address the automatic 3D interpretation of facades from terrestrial image sequences making two novel contributions: First, we employ Implicit Shape Models (Leibe and Schiele, 2004) coherently for the detection as well as for the delineation of windows, allowing to learn the appearance of windows and their outline from training data. Second, we use model selection to choose the most appropriate model for the conﬁguration of windows in terms of rows or columns. These components are complemented by plane sweeping for the 3D determination of the windows or rows / columns made up from them. Results show the feasibility of the approach.
Use of miRNA as a Biomarker in Prostate Cancer and New Approaches

Prostate cancer has been found to be the most life-threatening disease among men all over the world, given its wide occurrence and partially-successful therapies associated with a high rate of mortality. Thus, meticulous analysis of this cancer and its characteristics, including molecular biology, epigenetic mechanisms and markers during tumor development, may provide the scientists with valuable insights to design the therapeutic protocol with improved efficiency and low rate of failure and limited further side effects, such as infertility. Moreover, the risk associated with the current invasive procedures on prostate cancer patients has prompted researchers to invest effort in the discovery of being less-invasive and more advantageous procedures based on the patient’s own physiological and anatomical characteristics. This paper reviews past and present studies on epigenetics and molecular markers of prostate cancer, as well as the designed therapies. Additionally, we present a future vision and prospect of the current treatments.
Ipsilateral Fractures of the Hip, Femoral Shaft, Distal Femur and Patella

The case reports unusual ipsilateral fracture of the femur, i.e. intertrochanteric fracture, diaphyseal fracture, intra-articular fracture of the distal femur and cominuted fracture of the patella. The fracture of the femur was succesfully treated by the long gamma nail and angled condylar plate, the fracture of the patella by tension wiring.
The Representative Areas Program for Protecting Biodiversity in the Great Barrier Reef World Heritage Area

1 Great Barrier Reef Marine Park Authority, PO Box 1379 Townsville Queensland 4810, Australia 2 Cooperative Research Centre of the Great Barrier Reef World Heritage Area, James Cook University, Townsville Queensland 4810, Australia 3 9 Butler Drive, Kuranda Queensland 4872, Australia 4 previously GBRMPA; New South Wales Department of Fisheries Port Stephens, Taylors Beach NSW 2317, Australia 5 previously GBRMPA; International Centre for Living Aquatic Resources Management, PO Box 500, Penang 10670 Malaysia 6 Institute for Regional Development, University of Western Australia, Nedlands WA 6907, Australia Abstract Existing no-take areas within the Great Barrier Reef Marine Park reflect a historical focus on coral reefs and remote ‘pristine’ areas. The Representative Areas Program (RAP) aims to enhance protection of the region’s biodiversity by developing a network of no-take areas that represents the range of habitats and communities within the Marine Park. A comprehensive range of biological and physical information was used to define 70 reef and non-reef bioregions across the World Heritage Area. The Great Barrier Reef Marine Park Authority is identifying options for no-take area networks using a combination of expert opinion, stakeholder involvement and analytical approaches. Marine reserve design software has been adapted and expanded for use in the RAP. The aim in selecting the final no-take area network is to maximise biodiversity protection whilst minimising economic, cultural and social costs. The RAP is therefore being undertaken with comprehensive public participation involving all interested parties.
IOT based Air Quality Monitoring System

1*Assistant Professor, Department of Civil Engineering, Dr.N. G.P. Institute of Technology, Coimbatore, Tamilnadu. 2,3,4,*Students, Department of Civil Engineering, Dr.N. G.P. Institute of Technology, Coimbatore, Tamilnadu. ---------------------------------------------------------------------***---------------------------------------------------------------------Abstract Air quality observation is that the method of mensuration the standard of air that gift within the atmosphere exploitation IoT. the most objective of the Air quality display is to live the standard of the gases quality of air within the Atmosphere. so Air quality observation techniques square measure necessary to confirm the nice quality of air, in order that it will with success monitor the wide ranges of gases and their danger. The contaminated gases that square measure extremely active, additionally it affects heaps of lives in one and differently. in comparison to the tactic of commutation the total pollution level. Air quality techniques square measure necessary to confirm sensible quality of the gases within the open atmosphere. This project deals with the entire analysis of the advance of air constant properties and it’s Quality with the assistance of the web of things (IoT). With a similar objective the literature review is undertaken on utilization of the IoT platform for the advance of the Air and their performance was mentioned.
Paradigms of Artificial General Intelligence and Their Associated Risks

The first Asilomar principle states: “the goal of AI research should be to create not undirected intelligence, but beneficial intelligence”. Artificial general intelligence (AGI), however, is specifically characterised by its generality, which would allow AGI systems to be applied to a wide range of applications and display a variety of behaviours. Consequently, it seems that the greater the generality of a system, the more difficult it will be to direct its behaviour. Unfortunately, we lack proper tools to understand the relation between the generality of a system, its capacity, and the resources it uses, to the question of how these factors affect its control, potential and predictability and, accordingly, several safety issues.
AMBIENT 2011

- The use of multimodality improves interaction between the user and the computer. Particularly, the use of multimodal feedback within a smart environment facilitates the integration of technology into the daily activities of the user. However the choice of the suitable output modalities requires knowledge of the user context to be effective. This paper presents an approach for the generation of context-aware multimodal feedback in the context of ambient intelligence. Our solution is based on the NAIF Framework, which handles the creation and management of a smart environment. A preliminary prototype has been developed and tested in order to validate the proposed approach.
SMS Spam Identification Based on Message Duplication Detection by Cuckoo Filters

Short message service (SMS) spamming has become a large problem due to the wide spread of smart phones in the past few years. Modern smart phones processing power and extended connectivity has been employed by new spamming techniques to send spam messages from multiple infected devices controlled by command centres. Besides the annoyance for the receiver, this new breed of SMS spamming is causing financial loss for the infected devices owners since these devices has been used as tools for SMS transmission and spending the owner credit in the process. These new methods introduce a challenge for the telecommunication companies since it requires new techniques to identify and stop spam messages and the suggested method provide one practical solution for this problem. This paper presents a method to detect spam messages using the chronological characteristics of the spamming campaigns and the similarity among the spam messages’ contents which servers a single goal. A system has been built to recognize the repeated transmission of identical or near identical spam using the compact and high-performance Cuckoo filter. Real SMS messages were used to evaluate the system performance and detection rate
Imbalance-Based Option Pricing∗

I develop an equilibrium model of fragmented options markets in which option prices and bid-ask spreads are determined by the nonlinear risk imbalance between dealers and customers. In my model, dealers optimally exploit their market power and charge higher spreads for deep out-of-the-money (OTM) options, leading to an endogenous skew in both prices and spreads. In stark contrast to theories of price pressure in option markets, I show how wealth effects can make customers’ net demand for options be negatively correlated with option prices. Under natural conditions, the skewness risk premium is positively correlated with the variance risk premium, consistent with the data. JEL Classification: G12, G13
Assessment of Oxidative Stress Among Type 2 Diabetes Mellitus Patients Attending in A Rural Teaching Hospital, Sangareddy

Background: Oxidative stress is associated with the poor glycemic control in diabetes mellitus. Severe oxidative stress may cause cellular inflammation and damaging blood vessels in type 2 diabetic patients. Objectives: The present study was aimed to assess oxidative stress among type 2 diabetic patients by estimating MDA along with the lipid profile and blood glucose. Materials and methods: The present study was carried out at MNR Medical college & hospital situated in Sangareddy, part of Medak District, Telangana state. The 80 study subjects were selected from the medicine ward of MNR hospital during the period from February 2016 to July 2016. Results: A significantly higher level of MDA, total cholesterol, triglycerides, low-density lipoprotein and very low-density lipoprotein was estimated in type 2 diabetic patients (cases) when compared with non diabetic patients (controls) (p<0.0001). The mean HDL of cases was significantly lower than that of controls (p< 0.0001). Conclusion: Our study concludes that good glycemic control will prevent in alteration in lipid peroxidation and the lipid metabolism. This helps in prognosis and preventing complications in type 2 diabetes mellitus.
ICAS 2016 Proceedings

In this research, we developed a modular robot by improving our previous rescue robot. The previous robot has many serially connected crawlers to realize high mobility. However, the number of the crawler units was fixed and the operator could not customize the robot for the given task. In this research, we modularized our previous robot to solve this problem. We conducted experiments and demonstrated that the proposed robot can be applied to various search tasks by changing its formation. Keywords-snake-like robot; rescue robot; module; passive mechanism.
On the occurrence of the Persian Lizard, Iranolacerta brandtii (De Filippi, 1863) (Squamata: Sauria: Lacertidae) in Eastern Anatolia, Turkey

This is the first report of the occurrence of Iranolacerta brandtii in Eastern Anatolia. The distribution of I. brandtii is extended approximately 230 km eastwards into Van province, Turkey, showing that this species is not endemic to Iran as previously stated in the literature. Seven specimens were collected from four different localities between May and September 2014. Specimens were evaluated with respect to their morphological characters and some ecological features and their taxonomical status is also discussed.
Web Mining for Business Intelligence: Discovering Novel Association Rules from Competitors’ Websites

The Web has offered companies a convenient way to publish their information and conduct business with customers and partners, and it also opens an opportunity to companies to acquire knowledge of their competitors. Such knowledge is critical for a company to define its business strategies and to establish a network with business partners. This paper proposes a content web mining technique that discovers novel association rules among noun phrases extracted from web pages on one’s competitors’ websites. Novelty of an association rule is measured as the distance between the antecedent and the consequent of the rule in the background knowledge, which is developed from documents on one’s own website are. Incorporating background knowledge into the web mining process enables us to discover previously unknown but potential useful patterns. A running example demonstrates that the novelty prediction accuracy is high in terms of correlating with human judgments.
3D Partitioning in SPECFEM3D Internal Mesher

The SPECFEM3D package simulates seismic wave propagation using a parallel implementation of a variation of the Galerkin procedure called Spectral Element Method (SEM). The advantage of this method is that it produces a diagonal mass matrix which allows for quick explicit solving of the seismic wave equations. The drawback is that using an explicit method the solver is not stable unless the Courant-Friedrichs-Lewy (CFL) condition for convergence holds, imposing a certain inequality relation between the time step and spatial size of the spectral elements. The internal mesher provided with the package uses a partitioning approach that directly links the number of parallel solver tasks with the spatial size of the elements. For any given mesh, increasing the number of parallel processes leads to decreasing the element size, and via the CFL condition to decreasing the time step. This directly compromises the scalability of the solver by requiring more time steps for the same amount of work with no gain in performance. The goal of this project is to improve the scalability of the package by reconsidering the partitioning approach of the internal mesher. We analyze the existing approach and propose a new one, based on using the SCOTCH partitioning library, already integrated in the workflow for solving the problem on externally generated mesh. Our results indicate that the modified partitioning scheme leads to substantial performance benefits for regional modeling with the internal mesher in petascale environments. We validate the results by running the examples included in the package and observe that the solver produces identical synthetic seismograms when run with meshes generated by the original and modified internal mesher.
A CASEâ€“CONTROL STUDY TO ASSESS AND COMPARE THE EFFICACY OF 0.2% CHLORHEXIDINE AND 0.25% SODIUM HYPOCHLORITE MOUTHWASH IN TREATMENT OF CHRONIC GINGIVITIS

Objective: The objective of present study was to compare the efficacy of 0.2% chlorhexidine and 0.25% sodium hypochlorite as a mouthwash in controlling chronic gingivitis.Methods: A total of 80 patients suffering from chronic marginal gingivitis were recruited for the study. Non-surgical periodontal therapy was completed for all the patients to bring the gingival status to healthy levels. The patients were divided into two study groups with 40 patients in each group, Group A patients were asked to use 0.2% chlorhexidine mouthwash, and Group B patients used 0.25% sodium hypochlorite mouthwash as an adjunct to brushing twice daily for 2 weeks. After a period of 2 weeks, the gingival status was recorded using the oral hygiene index simplified (OHIS), plaque index (PI), and modified gingival index (MGI) and compared between the two groups.Results: The mean OHIS score for Group A was 1.38 and for Group B it was 1.05. The mean PI for Group A and B was 3.62 and 2.32, respectively. The mean MGI score for Group A was 1.22 and for Group B was 1.20. Group B showed better results than Group A. Intergroup comparison of OHIS and PI revealed significantly better results in Group B than Group A while MGI did not show any statistical difference on comparison.Conclusion: Nearly 0.25% sodium hypochlorite was more effective than 0.2% chlorhexidine in reducing the gingival inflammation. Thus, 0.25% sodium hypochlorite may represent an efficacious, safe and affordable antimicrobial agent in the prevention and treatment of gingival disease.
Common Ground? Explaining the Willingness to Share Knowledge in Organizational Teams

Knowledge is a resource that is considered to be important for organizational success and survival (Hinds & Pfeffer, 2003). Nevertheless, processes of knowledge sharing in organizations are often far from optimal. This can be partially explained by the unwillingness of employees to share knowledge (Hall, 2001; Hinds & Pfeffer, 2003). The willingness to share knowledge is closely related to social relationships. The stronger these relationships are, the more employees are willing to exchange knowledge with their colleagues (Hinds & Pfeffer, 2003).
BlockFlow: A Decentralized SDN Controller Using Block-chain

With the rise of cloud computing, data centers, and big data, the current rigid network architecture has been found to be inadequate. The modern technological demands require a flexible and easily reconfigurable network architecture. Software Defined Networking is a revolutionary concept that separates the control plane of network devices from their data plane and centralizes the control plane of all devices, facilitating the controlling of the entire network through a single portal. This helps us create flexible network architectures that can be reconfigured quickly to fit different needs. However, centralizing control leads to a Single Point of Failure and makes the network vulnerable to Denial of Service attacks, which is one of the major reasons why industries are reluctant to adopt this technology. Block-chain provides us a with a distributed ledger and a decentralized state, allowing us to create decentralized applications that run over multiple computers. This research aims to distribute the control plane of Software Defined Networks across multiple devices using block-chain. This addresses the existing security vulnerabilities of the Software Defined Network architecture such as Single Point of Failure while continuing to keep the control plane logically centralized, thereby allowing the network to be configured through a single portal. The resulting architecture has a physically distributed control plane whose logic is centralized.
CHANGE DETECTION OF BUILDING MODELS FROM AERIAL IMAGES AND LIDAR DATA

Building models are built to provide three dimensional (3D) spatial information, which is needed for varieties of applications, such as city planning, construction of location-based services, and the like. However, three dimensional building models need to be updated from time to time. Rather than reconstructing building models for the entire area, it would be more effective to only revise the parts that have changed. In this study, we aim at finding changes with 3D building models. The proposed scheme comprises three steps, namely, (1) data registration, (2) change detection of three dimensional building models, and (3) detection of new building models. The first step performs data registration for multi-source data. The second step performs the rule-based change detection, it include examination of spectrum from aerial images, examination of height difference between building models and LIDAR points, and examination of linear features from aerial images. A double-threshold strategy is applied to cope with the highly sensitive thresholding often encountered when using the rule-based approach. In the third step, we detect the LIDAR point clouds in the new building areas by removing vegetation, ground and old building areas. We then use region growing to separate the LIDAR point clouds into different groups. Finally, we use boundary tracing to get the new building areas. Ground truth data are used for validation. The experimental results indicate that the double-threshold strategy improves the overall accuracy from 93.1% to 95.9%. To provide comprehensive observations, the different cases are scrutinized. * Corresponding author.
The Labor Force Trajectories of Immigrant Women: Intersecting Personal Characteristics and Migration Dynamics

While research on immigrant women’s labor market incorporation has increased in recent years, systematic comparisons of employment trajectories by national origin and over time remain rare, and the literature remains dominated by the male experience. Especially lacking are studies that take both individual factors and larger migration dynamics into account, limiting our understanding of women’s contributions to the economic well-being of immigrant families, and of the process of incorporation more broadly. Using U.S. Census and ACS data from 1990 to 2016, we construct synthetic cohorts by national origin, period, and age at arrival to track their labor force participation over time. We construct a typology of national origin trajectories and then model them adjusting for individual characteristics and gendered dynamics of migration flows, namely the sex ratio, share of women arriving single, and share of men arriving with a college education. Results indicate that immigrant women tend to gradually join the workforce over time, though with significant variation in starting levels and growth rates. Cohorts from Mexico, Central America, and South America exhibited a delayed pattern of incorporation (though Mexican women start at lower levels than others), while women from India, Korea and other Asian countries followed an accelerated incorporation trajectory from very low starting rates. Those from Europe, Africa, China, Vietnam, and Canada showed gradual incorporation while Filipinas and Caribbeans exhibited continuous, intensive employment. We show that historically produced gendered dynamics of migration flows explain a substantial share of national origin variation in workforce incorporation.