Miracle-dz/UniFAR-FTUs huggingface dataset:
The effects of emerging adulthood on stress and depression

Many historical theories of development have evolved based on the premise that a person's identity is formed during adolescence. Upon reaching the age of 18, that person is identified as an adult and expected to have achieved a healthy identity. More recent studies suggest that a person continues to develop their identity well into their twenties. This age range is characterized by constant change, instability, and exposure to life stress events. Additional data shows that some people in this cohort do not consider themselves to be an adult, a se if-classffication that creates stress and decreased mental health. Researchers are now considering this age range to be an extended period of development termed "emerging adulthood. " Individuals who perceive themselves to still be developing during this stage (perceived emerging adults) are at higher risk of identity crisis, stress levels, and depression. In order to advance interventions and treatment plans for individuals in this cohort, it is important to understand the impact that this developmental period has on stress and depression. The purpose of this thesis was to investigate the impact that perceived emerging adult status had on mental health. Fifty adults (age 18-25) were surveyed on self-classification as an adult, life stress events, identity status, and depressive symptoms. It was found that there was a significant relationship between perceived adult status and certain life events, such as having children, being married, or living outside the parents ' home. No significant relationship was found between emerging adult status and identity status. Additionally, it was found that age and life stress was negatively correlated for emerging adults but not for perceived adults, indicating that life stress eased with age. Finally, for emerging adults but not perceived adults, stress level was positively correlated with depression.
A Literature Survey on ICTD Research by IS Community

Sejarah Artikel: Diterima Redaksi: 15 Juli 2017 Revisi Akhir: 05 September 2017 Diterbitkan Online: 10 September 2017 Despite a huge number of Information and Communications Technology for Development (ICTD) research so far, little is known about the landscape of published articles in Information Systems (IS) literature. This paper systematically reviews extant ICTD research published in the IS field from 1980-2016. The author systematically analyzed 192 articles published in A* and A-rank IS journals and explored which theoretical lenses, contexts, units of analysis, types of technology, and research methods dominate extant research in the field. As such, this present work provides a unique snapshot of the current research landscape that can help future ICTD field progress. KATA KUNCI ICTD ICT4D bibliographic study systematic literature review theoretical lenses
DNA Labels for Improved Detection and Capture with Solid-State Nanopores

Nanopores have emerged as a simple but effective tool to investigate the behavior of polymers in solution. They have shown great potential to simplify expensive and time consuming procedures like DNA sequencing, protein detection, and disease biomarker detection. With the development of in situ fabrication of solid-state nanopores by controlled breakdown (CBD) of a dielectric material, nanomanufacturing of nanopore-based technologies became feasible. However, there are still a lot of challenges to overcome for these applications to become reality. One of the major problems with solid-state nanopores is the rapid passage time of analytes going through the pore, complicating detection and reliable identification of molecules. In this thesis molecular structures are proposed that increase passage times due to increased interactions between analyte and pore wall, and at the same time increase signal amplitude due to increased blockage of the pore. These structures are short, branched DNA molecules that were assembled with built-in modifications and matching sequences to assume their structure. Nanopore experiments reveal that these structurally defined DNA produce higher detection rates than their linear DNA counterparts, making them better candidates for labels in single-molecule sensing experiments.
Investigation of Dispersion and Performance Based on Ring Cavity by Birefringent Interleaver for DWDM Transmission Systems

We theoretically investigate a 25 GHz multichannel filter based on ring cavity birefringent optical interleaver for dense wavelength division multiplexing (DWDM) transmission systems. The simulation tool used in this work is the Advanced System Analysis Program (ASAP) optical modeling software. We improve the dispersion performance by employing λ/6 and λ/4 wave plates as birefringent compensators for interleavers. The new structure exhibits a high performance with nearly zero ripple, a channel isolation greater than 102 dB, and a passband utilization of 86% within the C-band. The research results illustrate that our modified scheme can improve the dispersion of more than 76.6% in comparison with the previous studies of optical interleaver with birefringent crystal and ring cavity structures.
An Analytical Solution for Transient Heat Conduction in a Composite Slab with Time-Dependent Heat Transfer Coefficient

An analytical solution is derived for one-dimensional transient heat conduction in a composite slab consisting of layers, whose heat transfer coefficient on an external boundary is an arbitrary function of time. The composite slab, which has thermal contact resistance at interfaces, as well as an arbitrary initial temperature distribution and internal heat generation, convectively exchanges heat at the external boundaries with two different time-varying surroundings. To obtain the analytical solution, the shifting function method is first used, which yields new partial differential equations under conventional types of external boundary conditions. The solution for the derived differential equations is then obtained by means of an orthogonal expansion technique. Numerical calculations are performed for two composite slabs, whose heat transfer coefficient on the heated surface is either an exponential or a trigonometric function of time. The numerical results demonstrate the effects of temporal variations in the heat transfer coefficient on the transient temperature field of composite slabs.
INTERNET ADDICTION AMONG SECONDARY SCHOOL STUDENTS IN RIYADH CITY, ITS PREVALENCE, CORRELATES AND RELATION TO DEPRESSION: A QUESTIONNAIRE SURVEY

Background: There has been an explosive growth of internet usage worldwide and this is expected to continue with its use becoming an integral part of everyday life. The internet provides tremendous educational benefits; however, excessive internet use can lead to negative outcomes such as poor school performance and social isolation. Aims & Objective: To measure the prevalence of internet addiction among secondary school students in Riyadh city, its correlates and its relation to depression. Material and Methods: A cross sectional survey, was conducted between May and June 2010, using a self-administered questionnaire distributed to randomly selected 770 secondary schools students, using 20-item Young’s internet addiction test, and the Center for epidemiological studies depression scale, with questions related to demographic, social, academic and internet use factors. Results: 716 students answered the questionnaire, 391 are males and 325 are females. Prevalence was 5.3%, with male predominance. Internet addiction was associated with a lower degree of school performance, more hours using internet every day, lower level of parental control, and higher level of depression. Conclusion: Internet addiction has psychological, physical, and social effects on adolescents’ life, which requires preventive strategies and therapeutic interventions.
Can declining energy intensity mitigate climate change? Decomposition and meta-regression results

Drawing on the Kaya identity, we assess the role of the main driver of the decline in carbon intensity, namely the (economic) energy intensity. Using meta-signi? ficance testing for a sample of 44 studies, dealing with the causality between energy and GDP, we ? find that both variables are strongly coupled. Hence, after having exhausted energy savings from nonrecurring structural changes, the economic energy intensity may soon converge than being arbitrarily reducible. We suggest, therefore, not to rely on further reductions of economic energy intensity but rather to invest in the reduction of the carbon intensity of energy to mitigate climate change.
A prognostics approach based on the evolution of damage precursors using dynamic Bayesian networks

During the lifetime of a component, microstructural changes emerge at its material level and evolve through time. Classical empirical degradation models (e.g. Paris Law in fatigue crack growth) are usually established based on monitoring and estimating well-known direct damage indicators such as crack size. However, by the time the usual inspection techniques efficiently identify such damage indicators, most of the life of the component would have been expended, and usually it would be too late to save the component. Therefore, it is important to detect damage at the earliest possible time. This article presents a new structural health monitoring and damage prognostics framework based on evolution of damage precursors representing the indirect damage indicators, when conventional direct damage indicator, such as a crack, is unobservable, inaccessible, or difficult to measure. Dynamic Bayesian network is employed to represent all the related variables as well as their causal or correlation relationships. Since the degradation model based on damage precursor evolution is not fully recognized, the methodology needs to be capable of online-learning the degradation process as well as estimating the damage state. Therefore, the joint particle filtering technique is implemented as an inference method inside the dynamic Bayesian network to assess both model parameters and damage states simultaneously. The proposed framework allows the integration of any related sources of information in order to reduce the inherent uncertainties. Incorporating different types of evidences in dynamic Bayesian network entails advance techniques to identify and formulate the possible interaction between potentially nonhomogenous variables. This article uses the support vector regression in order to define generally unknown nonparametric and nonlinear correlation between the input variables. The methodology is successfully applied to damage estimation and prediction of crack initiation in a metallic alloy under fatigue. The proposed framework is intended to be general and comprehensive so that it can be implemented in different applications.
DOES MANAGEMENT ENTRENCHMENT EXPLAIN AGENCY COSTS OF EQUITY: EVIDENCE FROM FRENCH FIRMS

The purpose of this study is to examine the effect of the management entrenchment on the agency costs of equity. We conduct tests on 120 French companies over the period 2000-2014 in order to test the impact of the main factors that can intensify the conflicts between shareholders and managers. We use three alternative measures of agency costs of equity, namely asset utilization, operating expenses and administrative expenses. According to the empirical results, the CEO age, his dual role of executive and chairman, and the discrepancy between ownership and voting rights are relevant determinants of agency conflicts between shareholders and managers. Furthermore, we find that, the manager’s seniority and his ownership constitute internal governance mechanisms for the French companies.
Graph Cut Based approach in creating superpixel for Depth estimation

The Target of estimating the depth of each pixel in a scene from a single image which is a monocular image using the monocular cues. In past research work approaches [1, 2], which attempt to map from appearance features to depth directly, we first perform a generate segmentation (creation of Superpixels) of the scene and use the semantic labels to guide the 3D reconstruction. This approach provides several advantages: By knowing the segmentation class of a pixel or region, depth and geometry constraints can be easily enforced ( which gives idea about “sky” is far away and “ground” location of scene). In addition, depth can be more readily predicted by measuring the difference in appearance with respect to a given segmentation class. For example, a tree will have more uniform appearance in the distance than it does close up.by means of which, the incorporation of segmentation features allows us to achieve state-of-the-art results with a significantly simple model than previous research works.various models have been used to convert the monocular image into the 3d reconstruction model.
LPo 2 B-09 1 Magnetic Analysis of the Nb 3 Sn low-beta Quadrupole for the High Luminosity LHC

As part of the Large Hadron Collider Luminosity upgrade (HiLumi-LHC) program, the US LARP collaboration and CERN are working together to design and build 150 mm aperture Nb3Sn quadrupoles for the LHC interaction regions. A first series of 1.5 m long coils were fabricated, assembled and tested in the first short model. This paper presents the magnetic analysis, comparing magnetic field measurements with the expectations and the field quality requirements. The analysis is focused on the geometrical harmonics, iron saturation effect and cold-warm correlation. Three dimensional effects such as the variability of the field harmonics along the magnet axis and the contribution of the coil ends are also discussed. Moreover, we present the influence of the conductor magnetization and the dynamic effects.
Audio and Speech Classification Applied to Child Sexual Abuse Investigation

The complexity and scale of seized media in criminal investigations has increased dramatically in recent times, not least in child sexual abuse investigations. Manual examination of material impose great stress on the investigator and innovative aids can play a crucial role mitigating this. The thesis evaluates the use of machine learning algorithms for automatic speech classification. More specifically, we present the components of a system that uses acoustic features to identify speech in noisy environments and classify the speakers gender and spoken language. For each of the tasks, separate approaches based on earlier research were developed and experiments were devised to validate them. The results of all classification tasks were satisfactory, but the language classifier were found not to scale well with the number of supported languages. In conclusion, the thesis shows that machine learning models are well suited for speech classification. The thesis was performed at Safer Society Group.
Agricultural Literacy: Clarifying a Vision for Practical Application.

“Agricultural literacy” is a working concept with considerable range in meaning and impact. An overview of agricultural literacy curricula shows complementary deductive and inductive approaches to the systematic incorporation of agricultural education in K-12 classrooms. Based on positions discussed at the 2005 Agricultural Literacy Special Interest Group meeting of the American Association for Agricultural Education, the authors identified three curricular approaches to promote agricultural literacy: (1) a deductive approach based on programmed frameworks, (2) an inductive approach based on the application of knowledge and process skills, and (3) a utilitarian, values-based approach promoting evaluation of agri-food system issues. The authors provide an original conceptual model underscoring points of possible synergy between these approaches. The model points out interactions imposed on the system by cognitive-constructivist expectations for learning, which conflict with political and social pressures for a “traditional” curriculum assessed through “high-stakes” tests. The authors suggest capitalizing on the strengths of each approach to lever change within the current public education environment. The authors offer a systematic plan that may resolve the external conflict between the expectations of agricultural educators and political/social advocates of standardized curricula and high stakes testing, turning these pressures into forces to promote agricultural literacy.
Synthesis, biological evaluation and bioavailability prediction of novel furoxan derivatives as leishmanicidal compounds

Leishmaniasis is a neglected tropical disease, endemic in 98 countries and with more than 350 million people with risk to be sick. From 2001 to 2014, leishmanisis caused 797,849 of new cases of cutaneous and mucosal forms. Moreover, only in 2014, visceral leishmaniasis was detected in 3,624 american people, being Brazil responsible for 95% of this cases. Leishmania are protozoan parasites who lives in the midgut and foregut of the female sandfly of the genera Phlebotomus (Africa, Asia and Europe) and Lutzomyia (Central and South America), which is the sole vector responsible for transmitting this disease. Even though the knowledge in molecular biology and biochemistry about the parasite has increased, the first and second choice drugs for the treatment are still obsolete and with high toxicity in a long-term treatment. In this work, we describe the synthesis, leishmanicidal activity of furoxan derivatives against Leishmania amazonensis and Leishmania infantum and their bioavailability prediction. The compounds were synthesized from furoxan derivatives and aminoguanidine hydrochloride to give four new molecules in good global yields ranging from 30-60%. Compounds I-IV were characterized by analytical methods including NMR, infrared and mass spectrometry. The novel compounds were evaluated in two different species of Leishmania: Leishmania amazonensis and Leishmania infantum. The compounds were less cytotoxic than pentamidine. It is important to highlight the compound III, which presented a CC50 in macrophages of 1095.52 µM, which is considerably higher than pentamidine (35.69 µM), what means that its cytotoxicity is remarkably lower than the second line drug used in leishmaniasis treatment. In the evaluation against promatigotes forms, all compounds have demonstrated IC50 values superior to that of pentamidin against Leishmania amazonensis and a low IC50 values compared with pentamidine against Leishmania infantum. Compound II presented the most promissor IC50 against Leishmania infantum strain with a value of 8.87 µM, while pentamidine presents an IC50 value of 67.71 µM. For amastigote form, only two compounds with selective index superior to 15 (compounds I and III) were selected to be evaluated, and both of them presented an IC50 higher than pentamidine. The bioavailability prediction has demonstrated that all compounds are in agreement with the Lipinski rule, and their intestinal absorption was around 70%. All these data allow us to conclude that the compounds were more effective against the promastigote forms of Leishmania infantum, which is responsible for the visceral form of leishmaniasis. In addition to their important and significant low cytotoxicity, these compounds may be a future alternative to leishmaniasis treatment.
Kalman filtering without direct feed through from unknown inputs

The problem of joint input and state estimation is addressed in this paper for discrete-time stochastic systems without direct feedthrough from unknown inputs to outputs. Following the identical idea of previous study on discrete-time stochastic systems with direct feedthrough, the weighted least squares estimation for an extended state vector including unknown inputs and states is used to derive a Kalman filter with unknown inputs without directfeedthrough (KF-UI-WDF) approach. The information on unknown inputs is not needed for KF-UI-WDF and the necessary and sufficient conditions for the state and input detectability are presented. The estimators of KF-UI-WDF are proven minimum variance unbiased (MVU) ones.
The T-RFLP Analysis of Methanogenic Community during the an Aerobic Fermentation of Tofu Liquid Waste

The increase energy demand by the due to the growth of human population could cause decreasing fossil fuel energy. In near future energy demand will increase rapidly in the future. All those problems require each country to produce and to use renewal energy. Biogas is one of the renewable energy sources that can be used as the alternative energy. This is a kind of methane gas which is formed of various organic waste biomasses such as tofu waste. The aim of this research was to study the dynamic structure of methanogens community in the anaerobic digestion process by T-RFLP method. Sample was taken from anaerobic biodigester on day: 0, 5, 10, 15, and 20 to measure the pH, temperature, CH4, and molecular analysis. The dynamic of methanogens community during anaerobic digestion was observed by the TRFLP (Terminal Restriction Fragment Length Polymorphism) technique. The restriction enzyme used in that method was Alu1. The Shannon-Wiener (H’) index was used to analyze the community diversity. The research obtained by three filotipe detected by TRFLP , namely the Euryarchaeota on fragment size 62 bp, Archaea in the size of the fragment 136, and Methanosphaerula palustrispada in fragment size 167 bp. The Methanosphaerula palustris was dominating community member from beginning until the end of the fermentation process. The result of pH measurements ranged from 7 to 8. The highest CH4 production was on day 5 equal to 1092.6 ppm. The temperatures range from 30-310C.
Creep Prediction for Polymers: Implementation and Its Application on a Talc Filled Polypropylene

A creep predictive model in the literature based on strain energy equivalence theory has been implemented and tested. The model only utilizes stress -strain experimental data at two strain rates, and can predict the creep behavior of polymers for up to many years and its failure at any creep load. In addition, the model can extrapolate a given refer ence stress -strain curve to any strain rate. The implemented predictive model is applied to a 40% talc filled polypropylene (TFPP). Two stress -strain experiments were performed at strain rates of 0.01/min and 0.0001/min respectively. The creep behavior of the TFPP at creep stresses of 10 MPa, 15 MPa, and 20 MPa is predicted based on the two stress -strain tests. The prediction shows fairly good agreement with experimental data.