Miracle-dz/UniFAR-FTUs huggingface dataset:
Social and Psychological Impacts of SMS Texting on Malaysian University Students

Short Message Service (SMS) texting is widely used in this technological era, which has led to the questioning of the social and psychological effects of this communication medium. The objective of this study is to investigate the social and psychological influence on using SMS texts among university students in Malaysia. A sample of 971 respondents completed the online questionnaire. The findings indicated that there was a clear distinction between ‘Texters’ (=those who prefer texting) and ‘Talkers’ (=those who prefer talking) in their way of using their mobile phones and their underlying incentives. The recommendation is to design a social interface to support the interconnectivity between texters whereby people can check the status of one’s ‘textmates’, who is busy, and who is texting who. To conclude, many people own a mobile phone but they are not using their phones in the same way since people have different personalities and needs. Keywords: SMS texting; mobile phones; communication.
Regularization methods for a Cauchy problem for a parabolic equation in multiple dimensions

Abstract We study a Cauchy problem for a parabolic equation in multiple dimensions, which is naturally a generalization of some one-dimensional and two-dimensional inverse heat conduction problems. This is a severely ill-posed problem, i.e., the solution (if it exists) does not depend continuously on the data. After simply analyzing the ill-posedness of the Cauchy problem in the frequency space, from a new viewpoint we propose two regularization methods: Tikhonov method and Fourier truncation method. We give and prove the convergence estimate between the exact solution and its regularized approximation. We also discuss the relationship of these two and other regularization methods. At last, we employ some numerical examples to illustrate the behavior of the proposed methods.
Perturbation expansions of signal subspaces for long signals

Singular Spectrum Analysis and many other subspace-based methods of signal processing are implicitly relying on the assumption of close proximity of unperturbed and perturbed signal subspaces extracted by the Singular Value Decomposition of special "signal" and "perturbed signal" matrices. In this paper, the analysis of the main principal angle between these subspaces is performed in terms of the perturbation expansions of the corresponding orthogonal projectors. Applicable upper bounds are derived. The main attention is paid to the asymptotical case when the length of the time series tends to infinity. Results concerning conditions for convergence, rate of convergence, and the main terms of proximity are presented.
Deep Convolution Neural Networks for Image Analysis Master’s thesis

This master’s thesis is about deep convolutional neural networks (DCNNs) and their application on classification tasks. It is particularly concerned with the fields of supervised learning and feedforward networks. At first, the architecture and the mechanisms behind DCNNs are explained from scratch. Next, the work gives an overview over different methodological approaches that are crucial for the training of neural networks in practice and also a description of the VGG, Inception and ResNet architecture. Further, results from the finetuning of pretrained VGG-19, Inception-v3 and ResNet-152 networks on small data sets are presented. With three classes of the Places2 data set, it was investigated how the test accuracy changes with respect to the three models and different data sizes (20 to 1000 images per class). The results showed the best test accuracies and smallest training times for the Inception-v3 network. They also indicate that 250 images per class can be enough to acquire a very competent model (e.g. 97.8 percent test accuracy for the Inception-v3). Applying finetuning to a medical data set on the other hand did not yield a network that can discriminate between benign and malignant breast cancer cases. The data set encompassed 29 benign and 30 malignant mammography images. Deep Convolution Neural Networks for Image Analysis Deep convolutional neural networks (DCNNs) are a part of machine learning, where machines learn to detect patterns solely from data. They can handle a wide range of applications. With regard to the classification of images, DCNNs are utilized for instance for facial recognition tasks [Sun2014], the determination of art epochs [Hentschel2016], and also medical applications like breast cancer classification [Lévy2016]. Challenges for the image recognition tasks are different sizes and viewpoints, but also background clutter and varying illumination. Nevertheless have stateof-the-art networks already reached and even surpassend human performance [He2015b]. These results are possible also because there are large-scale data sets like the ImageNet [Russakovsky2015] and Places [Zhou2016], which provide millions of labeled images. But not for all tasks are large amounts of labeled data at hand. This is why the application of convolutional neural networks on small data sets will be investigated in this work. This master’s thesis is about deep convolution neural networks, especially about their application on image analysis. It is confined to supervised learning and feedforward neural networks. The aim of the first part of this work is to enable the reader to understand how neural networks work in theory and give an understanding of current methods for their use in practice.
Alzheimer’s Disease: Beyond the Neuron

This chapter describes the various systems beyond the central nervous system that are associated with Alzheimer’s disease (AD). There is strong evidence to believe that while AD has symptoms of memory and cognitive impairment—undoubtedly domains of the central nervous system—the primary insult that causes this condition may arise systemi-cally. We describe associations with the immune system, gut microbiome, and endocrine abnormalities that may be at play. Our goal is to incorporate a multi-system approach to understand the pathogenesis of AD. Our body does not function as soloed organ sys- tems, and we hypothesize that the mechanisms described herein are similarly contribut-ing to the progression of cognitive impairment in AD.
Spatial and temporal variability of precipitation in East China from 1880 to 1999

In this study, updated seasonal precipitation time series for 1880-1999 from 71 sites in East China were analyzed to identify spatial and temporal precipitation variability, to document pos- sible climate regime changes, and to place the extreme climate events and disasters in the historical context of the last century. The records were constructed using a combination of historical documents and instrumental records. During the last 100 yr (1900-1999), dry and wet climate anomalies based on 3 decade averaged precipitation tended to initiate in NW China and shifted eastward or southeast- ward. In the spring and winter seasons, dry or wet anomaly centers first appeared in NW China and shifted eastward to North China and NE China. In the summer and autumn seasons, dry or wet centers also occurred first in NW China and shifted southeastward to the central and lower Yangtze Valley regions and South China. Annual mean precipitation series from 6 regions showed that the 1920s were the driest decade in East China during the last 100 yr.
The rotation of LAGEOS

In view of the need of an accurate modelling of nongravitational forces on laser-tracked satellites, it is important to understand their rotational dynamics, which determines the temperature anisotropy and the ensuing radiation recoil effects. We propose a model of the torques acting on LAGEOS due to eddy currents and gravity gradient. The electromotive forces induced in the spacecraft by its rotation in the magnetic field of the Earth dissipate angular momentum and produce a precession of the spin axis; the oblate spacecraft will precess in the gravitational field of the Earth at a rate proportional to the rotation period. Therefore the gravitational torques become more and more important with time and eventually may produce a chaotic dynamics. The predicted evolution of the spin period agrees very well with the few experimental data available and corresponds to an approximately exponential growth rate of about 3 years.
SOCIALLY EFFICIENT ALLOCATION OF GM AND NON-GM CROPS UNDER CONTAMINATION RISK

This paper develops a model of optimal allocation of GM and non-GM crops under contamination risk. The model is used to compare the producer optimal crop allocation at equilibrium to the social efficient crop allocation. From the socially optimum conditions, the paper identifies production environments under which GM crops are more likely to be overplanted.
A survey of molecular line emission towards ultracompact HII regions

We have used the JCMT to survey molecular line emission towards 14 ultracompact HII regions (G5.89, G9.62, G10.30, G10.47, G12.21, G13.87, G29.96, G31.41, G34.26, G43.89, G45.12, G45.45, G45.47, and G75.78). For each source, we observed up to ten 1 GHz bands between 200 and 350 GHz, covering lines of more than 30 species including multiple transitions of CO isotopes, CH3OH, CH3CCH, CH3CN and HCOOCH3, and sulphuretted molecules. The number of transitions detected varied by a factor of 20 between sources; which were chosen following observations of high-excitation ammonia (Cesaroni et al. 1994a) and methyl cyanide (Olmi et al. 1993). In half our sample (the line-poor sources), only (CO)-O-17: (CO)-O-18, SO, (CS)-S-34 and CH3OH were detected. In the line-rich sources, we detected over 150 lines, including high excitation lines of CH3CN, HCOOCH3; C2H5CN, CH3OH, and CH3CCH. We have calculated the physical conditions of the molecular gas. To reproduce the emission from the line-rich sources requires both a hot, dense compact core and an ambient cloud consisting of less dense, cooler gas. The hot cores, which are less than 0.1 pc in size; reach densities of at least 10(8) cm(-3) and temperatures of more than 80 K. The line-poor sources can be modelled without a hot core by a 20-30 K, 10(5) cm(-3) cloud. We find no correlation between the size of the HII region and the current physical conditions in the molecular environment. A comparison with chemical models (Millar et al. 1997) confirms that grain surface chemistry is important in hot cores.
A Deep Temporal Convolutional Neural Network for Regional and Teleseismic Detection

The detection of seismic events at regional and teleseismic distances is critical to Nuclear Treaty Monitoring. Traditionally, detecting regional and teleseismic events has required the use of an expensive multi-instrument seismic array; however in this work, we present DeepPick, a novel seismic detection algorithm capable of array-like performance from a single trace. We achieve this directly, by training our single-trace detector against labeled events from an array catalog, and by utilizing a deep temporal convolutional neural network. The training data consists of all arrivals in the International Seismological Centre Catalog for seven seismic arrays over a five year window from 1 Jan 2010 to 1 Jan 2015, yielding a total training set of 608,362 detections. The test set consists of the same seven arrays over a one year window from 1 Jan 2015 to 1 Jan 2016. We report our results by training the algorithm on six of the arrays and testing it on the seventh, so as to demonstrate the transportability and generalization of the technique to new stations. Detection performance against this test set is outstanding. Fixing a type-I error rate of 1%, the algorithm achieves an overall recall rate of 73% on the 141,095 array beam picks in the test set, yielding 102,394 correct detections. This is more than 4 times the 23,259 detections found in the analyst-reviewed single-trace catalogs over the same period, and represents an 8dB improvement in detector sensitivity over current methods. These results demonstrate the potential of our algorithm to significantly enhance the effectiveness of the global treaty monitoring network.
PV self-consumption optimization with storage and Active DSM for the residential sector

With the rising prices of the retail electricity and the decreasing cost of the PV technology, grid parity with commercial electricity will soon become a reality in Europe. This fact, together with less attractive PV feed-in-tariffs in the near future and incentives to promote self-consumption suggest, that new operation modes for the PV Distributed Generation should be explored; differently from the traditional approach which is only based on maximizing the exported electricity to the grid. The smart metering is experiencing a growth in Europe and the United States but the possibilities of its use are still uncertain, in our system we propose their use to manage the storage and to allow the user to know their electrical power and energy balances. The ADSM has many benefits studied previously but also it has important challenges, in this paper we can observe and ADSM implementation example where we propose a solution to these challenges. In this paper we study the effects of the Active Demand-Side Management (ADSM) and storage systems in the amount of consumed local electrical energy. It has been developed on a prototype of a self-sufficient solar house called “MagicBox” equipped with grid connection, PV generation, lead–acid batteries, controllable appliances and smart metering. We carried out simulations for long-time experiments (yearly studies) and real measures for short and mid-time experiments (daily and weekly studies). Results show the relationship between the electricity flows and the storage capacity, which is not linear and becomes an important design criterion.
The lithospheric architecture of Africa: Seismic tomography, mantle petrology, and tectonic evolution

We present a new analysis of the lithospheric architecture of Africa, and its evolution from ca. 3.6 Ga to the present. Upper-lithosphere domains , generated or reworked in different time periods, have been delineated by integrating regional tectonics and geochronology with geophysical data (magnetic, gravity, and seismic). The origins and evolution of lower-lithosphere domains are interpreted from a high-resolution global shear-wave tomographic model, using thermal/compositional modeling and xenolith/xenocryst data from volcanic rocks. These data are integrated to map the distribution of ancient highly depleted subcontinental lithospheric mantle (SCLM), zones of younger or strongly modified SCLM and zones of active mantle upwelling, and to relate these to the evolution of the upper lithosphere domains. The lithospheric architecture of Africa consists of several Archean cratons and smaller cratonic fragments, stitched together and flanked by younger fold belts; the continental assembly as we see it has only existed since lower Paleozoic time. The larger cratons are underlain by geochemically depleted, rigid, and mechanically robust SCLM; these cratonic roots have steep sides, extending in some cases to ≥300-km depth. Beneath smaller cratons (e.g., Kaapvaal) extensive refertilization has reduced the lateral and vertical extent of strongly depleted SCLM. Some cratonic roots extend ≥300 km into the Atlantic Ocean, suggesting that the upper lithosphere may detach during continental breakup, leaving fragments of SCLM scattered in the ocean basin. The cratonic margins, and some intracratonic domain boundaries, have played a major role in the tectonics of Africa. They have repeatedly focused ascending magmas, leading to refertilization and weakening of the SCLM. These boundaries have localized successive cycles of extension, rifting, and renewed accretion; the ongoing development of the East Africa Rift and its branches is only the latest stage in this process. The less depleted SCLM that underlies some accretionary belts may have been generated in Archean time, and repeatedly refertilized by the passage of magmas during younger tectonic events. Our analysis indicates that originally Archean SCLM is far more extensive beneath Africa than previously recognized, and implies that post-Archean SCLM rarely survives the collision/accretion process. Where continental crust and SCLM have remained connected, there is a strong linkage between the tectonic evolution of the crust and the composition and modification of its underlying SCLM.
Binational Marriages in Sweden: Is There an EU Effect?

This paper explores and explains the partner choice of Swedes in the period 1991-2008. The partner market for Swedes has expanded considerably in the last few decades, due to EU expansion, globalisation processes and an increased diversity of the migrant population. Besides increased opportunities, citizens who are better educated, younger and more mobile might prefer foreign partners of their own kind. The paper focuses on marriages between Swedish-born and foreign-born partners, and distinguishes people with Swedish-born parents from those with foreign-born parents. Using full-population register data, a systematic comparison between Swedes marrying EU partners and those marrying non-EU partners is conducted. I find that the binational marriage rate has increased over time, especially for native Swedish men and men who are second-generation Swedes. The increase is for the greater part attributable to an increase in the number of marriages to partners from outside the EU, while binational EU marriages have remained stable with no effects from EU accession. Patterns of binational marriages are highly gender-specific, with Finland being the most important supplier for foreign husbands, while Thai women are most popular amongst men. Against expectation, native Swedes in binational marriages are, by and large, older and less well-educated.
A dynamic model of transient NH4+ assimilation in red algae

A dynamic model has been developed describing the effects of transient N assimilation following NH,+pulses on protein synthesis and on C mobilization in red algae. The model simulations indicate that the differential response of phycobiliproteins to N availability seems to be related to a more general response of chloroplast proteins to N supply. The model displays a high robustness. The incorporation of different functions of amino acid transport between the chloroplast and cytosol fractions, as well as different initial distributions of amino aclds between these fractions, has little effect on N incorporation at the protein level, with chloroplast proteins being much more affected than cytosolic ones by the variation of the external forcing function, the NH,' supply. With respect to cell C metabolism, the main changes promoted by a transient NH,+assimilation were not in total cell C but in the allocation of C between C reserve structures (carbohydrates) and organic N compounds (amino acids and proteins). The stoich~ometry of 6 C molecules needed per N molecule assimilated seems to be crucial in determining the rate of C mobilization in response to transient N assimilation. The development of the model provides further insights in the mechanism of C-N interaction In marine red algae, where the presence of particular N compounds such as phycoblllproteins and of C compounds such as cell wall polysaccharides and floridean starch is different compared to green algae and higher plants. The results of the simulations compared favorably wlth the experimental data reported for the red alga Gracilariopsis lemaneiformis.
Alpha power , alpha asymmetry and anterior cingulate cortex activity in depressed males and females

Left fronto-cortical hypoactivity, thought to reflect reduced activity in approach-related systems, and right parietal hypoactivity, associated with emotional under-arousal, have been noted in major depressive disorder (MDD). Altered theta activity in the anterior cingulate cortex (ACC) has also been associated with the disorder. We assessed resting frontal and parietal alpha asymmetry and power in nonmedicated MDD (N 1⁄4 53; 29 females) and control (N 1⁄4 43; 23 females) individuals. Theta activity was examined using standardized low-resolution electromagnetic tomography (sLORETA) in the ACC [BA24ab and BA32 comprising the rostral ACC and BA25/subgenual (sg) ACC]. The MDD group, and particularly depressed males, displayed increased overall frontal and parietal alpha power and left midfrontal hypoactivity (alpha2-indexed). They also exhibited increased sgACC theta2 activity. MDD females had increased right parietal activity, suggesting increased emotive arousal. Thus, unmedicated depressed adults were characterized by lower activity in regions implicated in approach/positive affective tendencies as well as diffuse cortical hypoarousal, though sex specific modulations emerged. Altered theta in the sgACC may reflect emotion regulation abnormalities in MDD. 2012 Elsevier Ltd. All rights reserved.
Identification of duplicates of cassava accessions sampled on the North Region of Brazil using microsatellite markers

Duplicatas costumam ocorrer em bancos de germoplasma e a sua identificacao e necessaria para facilitar o manejo dos bancos ativos de germoplasma (BAGs) e diminuir custos de manutencao. O objetivo deste trabalho foi identificar duplicatas de mandioca determinadas previamente pela caracterizacao morfo-agronomica, em um BAG da Amazonia Oriental. Foram selecionados 36 acessos que se agrupavam em 13 grupos de similaridade morfo-agronomica para serem genotipados com 15 locos microssatelites. Todos os locos foram polimorficos, sendo obtidos 75 alelos, com media de cinco alelos por loco e HE = 0,66. Foram encontrados 34 pares de genotipos que apresentaram perfis multilocos identicos e a probabilidade de identidade genetica foi de 1,1x10-12 com probabilidade de exclusao de 99,9999%. Entre essas duplicatas, estao materiais coletados em epocas e locais diferentes, e com diferentes denominacoes e acessos com o mesmo nome coletados em diferentes locais e anos. O estudo identificou genotipos que vem sendo cultivados em diferentes locais e que vem sendo mantidos pelos agricultores ao longo dos anos.
Adopting a Strategic Approach to Matching People to Jobs

This conceptual analysis explores recruiters’ ability to utilize the practice of strategic foresight to scan internal and external environments as a strategic plan to matching people to jobs. In today’s volatile market, it is no longer useful for recruiters to attract and hire talent with a desultory mindset when filling open positions without considering internal and external factors. Today’s recruiters must become more deliberate in who they hire by having a tactical plan to attract and retain the most qualified people in an unpredictable global market. Through the process of developing a conceptual framework model, this paper aims to present three strategic foresight competencies required for recruiters to match people to jobs. Also, this conceptual analysis will argue the need for recruiters to possess a strategic mindset to attract and hire the most qualified people to an organization. Furthermore, discuss the implications of recruiters who lack strategic foresight competencies. The practice of strategic foresight is now a requirement for recruiters to become cognizant of internal and external factors such as competitive behavior, technological change, political and economic conditions and human capital, which can influence their approach to matching people to jobs. Overall, when recruiters match talent based on the company’s strategic drivers rather than blindly fill open positions without a tactical plan, organizations can better achieve its performance potential.