Miracle-dz/UniFAR-FTUs huggingface dataset:
More Time on Technology, Less Happiness? Associations Between Digital-Media Use and Psychological Well-Being

Studies using large samples consistently find that more frequent users of digital media are lower in psychological well-being than less frequent users; even data sets used as evidence for weak effects show that twice as many heavy users (vs. light users) are low in well-being. Differences in perspective may stem from the statistics used; I argue that comparing well-being across levels of digital-media use is more useful than the percentage of variance explained, as most studies on digital-media use do not measure other influences on well-being (e.g., genetics, trauma), and these other influences, unlike frequency of digital-media use, are rarely controllable. Nonusers are generally lower in well-being than light users of digital media, however, suggesting that limited use may be beneficial. Longitudinal and experimental studies suggest that at least some of the causation moves from digital-media use to lower well-being. Mechanisms may include the displacement of activities more beneficial to well-being (sleep, face-to-face social interaction), upward social comparison, and cyberbullying.
Structural Breaks in Nigeria’s Macroeconomic Time Series Data

This paper investigates empirically the analyses of structural breaks in Nigeria’s macroeconomic time series data using annual data spanning from 1970 to 2015. Among other objectives is to examine whether there is stability or breaks in the mean level of interest rates, exchange rates and inflation rates over the periods under review. The paper adopts a Lee and Strazicich (2003) unit root tests with multiple break test using LM approach to examine the stability of data employed and structural changes in linear regression model, using Chow test to identify the break dates. The paper further assumes three different dates – 1970 to 2015, where there was no break, 1970 to 1986 before break and 1986 to 2015 after break, at which there was a statistically significant breaks. The F-statistic test from the Chow test results indicates 28.98, which is greater than the 95 percent critical value of 2.62. This suggests that endogenously determined breaks for the macroeconomic variables (interest rates, exchange rates and inflation rates) of the Nigerian economy was found to exhibit structural breaks within the periods under review. This implies that the null hypothesis of no significant relationship between structural breaks and macroeconomic variables in Nigeria was rejected. Based on the above evidence, the paper submits that there should be an adoption of regime switching models that will minimize the potentiality of breaks in time series data in Nigeria. Keywords: Structural Breaks, Macroeconomic Variables, Chow Test, Nigeria.
Noise-Aware DVFS for Efficient Transitions on Battery-Powered IoT Devices

Low power system-on-chips (SoCs) are now at the heart of Internet-of-Things (IoT) devices, which are well-known for their bursty workloads and limited energy storage—usually in the form of tiny batteries. To ensure battery lifetime, dynamic voltage frequency scaling (DVFS) has become an essential technique in such SoC chips. With continuously decreasing supply level, noise margins in these devices are already being squeezed. During DVFS transition, large current that accompanies the clock speed transition runs into or out of clock networks in a few clock cycles, induces large ${\text {L}di}{/}{\mathrm {d}t}$ noise, thereby stressing the power delivery system (PDS). Due to the limited area and cost target, adding additional decoupling capacitance to mitigate such noise is usually challenging. A common approach is to gradually introduce/remove the additional clock cycles to increase/decrease the clock frequency in steps, also known as, clock skipping. However, such a technique may increase DVFS transition time, and still cannot guarantee minimal noise. In this paper, we propose a new noise-aware DVFS sequence optimization technique by formulating a mixed 0/1 programming to resolve the problems of clock skipping sequence optimization. Moreover, the method is also extended to schedule extensive wake-up activities on different clock domains for the same purpose. The experiments show that the optimized sequence is able to significantly mitigate noise within the desired transition time, thereby saving both power and energy.
“You have to say everything is nice here”

Purpose The purpose of this paper is to reflect on the author’s research experiences in northern Mozambique in order explore the multiplicity of gatekeeper relations that arose while seeking to arrange access to both “the field” and respondents, as well as the impacts that these relationships had on the research process. Although this dynamic has been thoroughly described within methodological literature, there exists a tendency to presume research–gatekeeper relations as static; once established, there is little discussion on how the relationships develop or can be managed, once access has (or has not) been achieved. Design/methodology/approach The paper draws upon qualitative fieldwork conducted predominantly in rural communities in northern Mozambique. The study analysed the development of the Nacala Development Corridor programme and the N13 Highway Rehabilitation Project in northern Mozambique in order to examine the impacts of the development on local citizens and examine the relationship between citizen and state within development processes. Fieldwork consisted of three different phases of semi-structured and open-ended interviews with key stakeholders and affected persons, spanning five different interview schedules, and a total of 77 individual interviews and 27 community focus groups conducted along the N13. Findings The study found that duality of Mozambican governance which includes both local officials and traditional leadership contributed to a multiplicity of local gatekeepers which impacted the research process in a multitude of ways. As a result, researcher–gatekeeper relations were not static, but had to be managed throughout the duration of the study. Originality/value This discussion provides a more dynamic representation of the challenges involved with establishing and managing gatekeeper relations in rural, developing, and in particular, southern African, contexts, while offering cautious practical advice to researchers working within rural or southern African contexts.
Feature extraction and scene classification for remote sensing image based on sparse representation

Sparse representation theory for classification is an active research area. Signals can potentially have a compact representation as a linear combination of atoms in an overcomplete dictionary. In this paper, a novel classification method is proposed, which combines sparse-representation-based classification (SRC) and K-nearest neighbor classifier for remote sensing image. Based on the extracted multidimensional features which are used to constitute an overcomplete dictionary, the image is expressed as the product of the dictionary and coefficient of sparse representation. Then the test image is reconstructed by utilizing correlation and distance information between the image and each class simultaneously. Finally, each image will be assigned a class label based on minimizing the reconstruction error. And then, the proposed method has been extended to a kernelized variant to solve linearly inseparable problems. The experimental results show that the proposed method and its variant not only improve the classification performance over SRC but also outperform typical classifiers, such as support vector machine(SVM), especially when the number of training samples is limited.
Modeling the Solar Radiation Parameter over Abuja using Neural Networks

Many computer simulation models which predict growth, development and yield of agronomic and horticultural crops require daily weather data as input. One of these inputs is daily total solar radiation, which in many cases is not available owing to the high cost and complexity of the instrumentation needed to collect the data. In this work, a neural network model of the solar radiation over Abuja, Nigeria is developed. The model is useful for predicting the solar radiation intensity over Abuja, and this prediction is very important for many solar radiation applications, including gathering and validating information on the potential of Abuja for location of a solar energy generating station. The model used was developed using the Levenberg-Marquardt back-propagation algorithm with data from the Campbell automatic weather station situated at the University of Abuja, Nigeria. Results show that the predictions from the model developed generally agree with the observations. Midday solar radiation values typically exceed 600 W/m2 during equinoxes and sometimes drop below 500 W/m2 during solstices. Two indices (the Solar Radiation Diurnal Index (SRDI) and the Solar Radiation Annual Index (SRAI)) were also introduced in this work to respectively characterize the amounts of solar radiations received in each day and in each year for a given location. Relevant information is also provided to guide stakeholders for the location of a solar energy generating station in the region. Keywords: Neural network, solar radiation, Abuja, prediction, solar radiation diurnal index, solar radiation annual index Cite this Article Iloanusi Nkiru Lilian, Okoh Daniel, Obi Joseph. Modeling the Solar Radiation Parameter over Abuja using Neural Networks. Research & Reviews: Journal of Space Science & Technology . 2017; 6(3): 40–48p.
Satisfaction des bénéficiaires du régime obligatoire d'assurance maladie des agents publics et assimilés à Lomé, Togo

Introduction En février 2011, le gouvernement togolais a instauré un régime obligatoire d'assurance maladie au profit des agents publics et assimilés. Quatre ans plus tard, cette étude a enquêté sur la satisfaction des bénéficiaires de ce régime dans la commune de Lomé. Méthodes L'enquête a été réalisée auprès d'un échantillon de bénéficiaires à l'aide d'un questionnaire anonyme administré en face-à-face à la sortie de huit établissements de soins. Une analyse des réponses a permis de mesurer le degré de satisfaction. Les données quantitatives ont été décrites à l'aide de médianes et d'étendues interquartiles (EIQ) et les données qualitatives transcrites verbatim. Résultats Parmi 288 sujet sollicités, 279 ont accepté de participer dont 58% étaient des femmes et 88% des agents encore en activité. L'âge médian était de 38 ans (EIQ: 30-47). Une très grande majorité de répondants (93,5%) a considéré cette assurance maladie « satisfaisante ». La note moyenne de satisfaction globale était de 6/10 (min: 5, max: 9). Les principaux éléments d'insatisfaction concernaient le refus de prise en charge des affections de longue durée (84% d'insatisfaits), la complexité des formalités administratives (84% d'insatisfaits), et les longueurs des délais de prise en charge (67% d'insatisfaits). Conclusion Le niveau de satisfaction très élevé encourage le maintien et le développement de ce régime d'assurance maladie au Togo. Toutefois, les éléments d'insatisfaction devraient faire l'objet d'une prompte attention et de véritables efforts de correction.
Dynamics of Gully-Formation by Considering the Wave Motion of Flow

The dynamics of the formation of ravines (gullies) by taking the wave motion of flow into account. The article considers the question of impact of the wave motion of flow on the erosion intensity in the ravines. The technique to predict the occurrence of waves on a free surface of alluvium-carrying flows is proposed. Wave motion stimulates the intensity of the soil and ground washout. The influence of wave formation on the process of the erosion intensity is assessed by using the correction factor for the average flow velocity in the clear section.
Unique Pharmacokinetic and Pharmacodynamic Parameters of Antimicrobials in Goats

Pharmacokinetics, the process that involves drug absorption, distribution, metabolism and excretion (ADME) of antimicrobials, determines pharmacodynamic response, that is, what drugs do to the body. Therefore, of all the pharmacokinetic parameters, elimination half-life (T 1 / 2 β ), volume of distribution (Vd), maximum plasma concentration (Cmax) and maximum time reached (Tmax) are the most important parameters. Hence, the parameters are unique in determining pharmacokinetic and pharmacodynamic response of antimicrobials. However, it is elimination half-life and minimum inhibitory concentration (MIC) that determine the dosing interval of antimicrobials. The dose range of 2.5 mg/kg for gentamicin passing through 4 mg/kg (ciprofloxacin), 4.2 mg/kg (ampicillin L/A), 5 mg/kg (kanamycin, enrofloxacin, gatifloxacin and norfloxacin), 7 mg/kg (mequindox), 10 mg/kg (amikacin, enrofloxacin, lincomycin, pefloxacin, cefpirome, erythromycin and isoniazid), 20 mg/kg (oxytetracycline) and 30 mg/kg (metronidazole) have elimination half-life of 1.2 – 67.2 h, Cmax of 0.12 – 54.4 μ g/ml, Tmax of 0.2 – 24 h, bioavailability of 16 – 99.8% and plasma protein binding of 0 – >80% when administered intramuscularly, intravenously and orally. Human equivalent dose formula could be used to extrapolate human-goat therapeutic doses of antimicrobials. How-ever, some antimicrobials such as sulfadimidine, tulathromycin, oxytetracycline and azithromycin may have high residues in the milk, kidneys, liver, intestines, brain and skeletal muscles and may portend high risk of antimicrobial resistance, hypersensitivity reaction, epidermal necrolysis, Stevens-Johnson syndrome and other adverse drug reactions.
Hybrid Odor Detection System for Search and Rescue Robot Based on PSO

Aiming at the problem of the search and rescue robots' perception of various gases in chemical engineering sites, a hybrid odor detection system for search and rescue robots based on particle swarm optimization was proposed. In order to improve the stability and prediction accuracy of the system, a method of using particle swarm (PSO) to optimize the weighting coefficients of the integrated neural network is proposed, that is, using the global search ability of PSO and introducing an improved PSO algorithm to optimize the weights and thresholds of the BP neural network on the basis of the original BP neural network, and the optimized network is used in the detection system, thus reducing the detection error of the system. The system analyzed the response signals of the 4 gas mixtures of the sensor array, the experimental results show that the neural network algorithm based on particle swarm optimization is applied to the training of gas mixture quantitative identification, the convergence speed is faster and the detection accuracy is higher than that of BP neural network algorithm.
Predictable Dynamics in the Implied Volatility Surface Based on Weighted Least Squares: Evidence from Soybean Meal Futures Options in China

ABSTRACT This article examines the dynamics and predictability of the implied volatility surface derived from weighed trading volume. We study the Chinese soybean meal futures options market. By assigning larger weights to options with higher trading volume, we find more precise fittings on the implied volatility surface. Our estimation method outperforms traditional methods in terms of the dynamics and predictability of the implied volatility surface, both in the sample and out of the sample. We also document that soybean futures options exhibit implied volatility smirk that is different from those in the stock index options. In addition, we find that the implied volatility term structure shows an inverted U-shape during the period of high implied volatility.
Constant Modulus Secure Beamforming for Multicast Massive MIMO Wiretap Channels

Massive MIMO attains high spectral and power efficiency transmission by leveraging a large number of transmit antennas. However, to capture the benefits of massive MIMO, each antenna should be accompanied with a dedicated RF chain, and consequently, the hardware costs would scale up tremendously with the increase of the antennas. Cheap implementations of massive MIMO have recently gained considerable attention, and constant modulus (CM) signaling is seen as a promising solution, owing to its low peak-to-average power ratio (PAPR). This paper investigates the physical-layer (PHY) security in massive MIMO with an emphasis on the CM signaling. In particular, we consider a transmitter with massive antennas broadcast common confidential information to a group of legitimate receivers, and a number of eavesdroppers overhear the transmission and attempt to intercept the information. Our goal is to design the CM beamforming at the transmitter so that the multicast secrecy rate is maximized. This secrecy rate maximization (SRM) problem is generally NP-hard. To tackle it, two tractable approaches are developed. The first one employs the semidefinite relaxation (SDR) technique and the Charnes–Copper transformation to obtain a convex relaxation of the SRM problem. However, due to the dimension lifting of SDR, this approach is feasible only for small to medium antenna sizes. The second approach leverages the Dinkelbach method to work directly over the beamformer domain; a custom-build nonconvex alternating direction method of multipliers (ADMM) algorithm is proposed to efficiently perform each Dinkelbach update. Simulation results demonstrate that the second approach is computationally more efficient and can achieve nearly optimal performance when the number of antennas is large.
Research on Improved LBP Algorithm Based on Euclidean Distance and Differential Coding

Local Binary Pattern (LBP) algorithm is a classical algorithm in the field of face recognition. It can capture local detail features, but its robustness and recognition rate are easily affected by external environmental changes.In this paper, an improved LBP algorithm which combines Euclidean distance and differential coding is proposed. The improved EDLBP operator is applied to feature extraction and compared with various improved LBP algorithms in different databases.The experimental results show that the correlation between the EDLBP algorithm and the LBP, MBP, LTP and ELBP algorithms is improved in the databases with illumination diversity and texture rotation. When compared to the recognition rate changes obtained using the CUReT database at different training samples, the highest recognition rate of EDLBP algorithm is 55.49%, 23.36% and 2.46% higher than that of LBP, MBP and LTP algorithms respectively. By comparing similarity of the two face images, the EDLBP algorithm is 1.04%, 2.94%, 4.69%, and 5.56% higher than the latest ELBP algorithm.
A multi-omics approach to microbial nitrogen and sulfur cycling in the oxygen starved ocean

Microbial communities mediate biogeochemical processes of Carbon (C), Nitrogen (N) and Sulfur (S) cycling in the ocean on global scales. Oxygen (O2) availability is a key driver in these processes and shapes microbial community structure and metabolisms. As O2 decreases, microbes utilize alternative terminal electron acceptors, nitrate (NO3 – ), nitrite, sulfate and carbon dioxide, depleting biologically available nitrogen and producing greenhouse gases nitrous oxide (N2O) and methane (CH4). Marine oxygen minimum zones (OMZs) are areas of O2-depletion (O2<20 μm) in sub-surface waters due to the respiration of organic matter from the surface. In areas of acute O2-depletion or where OMZs contact underlying sediments, hydrogen sulfide (H2S) and CH4 accumulate within OMZ waters, drastically altering microbial community structure and metabolism. In this thesis, I explore microbial cycles along defined gradients of O2, NO3 – and H2S in Saanich Inlet, a seasonally anoxic fjord on the coast of British Columbia Canada. I develop a time-resolved multi-omic dataset consisting of small subunit ribosomal RNA amplicon sequences, single cell amplified genomes (SAGs), metagenomes, -transcriptomes and -proteomes, coupled with geochemical measurements, enabling robust microbial metabolic reconstruction at the individual, population and community levels of organization. Using metaproteomics, I construct a conceptual model of metabolic interactions involving N and S cycling, and carbon fixation, forming the basis for a collaborative effort to build a gene-centric numerical model, identifying an unrecognised niche for N2O reduction. Using single cell amplified genomes (SAGs) from Saanich Inlet, I identify genes for N2O reduction, (nosZ), within the dark matter phylum Marinimicrobia clade SHBH1141, filling the proposed niche of non-denitrifying N2O-reducers. Using globally sourced Marinimicrobia SAGs, I further analyze energy metabolism and biogeography of several Marinimicrobia clades, revealing roles in C, N and S cycling along eco-thermodynamic gradients throughout the ocean. Finally, I chart the global abundance and distribution of nosZ genes and transcripts within the ocean, identifying previously unappreciated potential sinks for N2O. As OMZs continue to expand and intensify due to climate change, defining metabolic processes and interactions along gradients of O2-depletion becomes increasingly important. This thesis provides foundational knowledge related to the microbial communities driving coupled biogeochemical cycling in OMZs.
Effects of Combined Use of Ultrasonic Bone Scalpel and Hemostatic Matrix on Perioperative Blood Loss and Surgical Duration in Degenerative Thoracolumbar Spine Surgery

How to decrease intraoperative bleeding, shorten surgical time, and increase safety in spinal surgery is an important issue. Ultrasonic bone removers and FloSeal have been proven to increase safety, reduce the surgical duration, and decrease intraoperative bleeding in skull base surgery. Therefore, we aimed to compare the surgical duration, blood loss, and complications during spinal surgery with or without the use of FloSeal and an ultrasonic bone scalpel. Therefore, we retrospectively reviewed 293 patients who underwent thoracolumbar spinal surgery with decompression and instrumented fusion performed by a single surgeon. We divided these patients into three groups, including nonuse of FloSeal nor a bone scalpel (group A), use of FloSeal only (group B), and use of FloSeal and a bone scalpel (group C) intraoperatively after pairing in terms of age, sex, and surgical level. The surgical duration, blood loss, and occurrence of complications were all recorded. The mean surgical duration in group A was 160 mins, in group B it was 167 mins, and in group C it was 134 mins. The mean blood loss was 700 ml in group A, 682 ml in group B, and 383 ml in group C. Six patients sustained intraoperative dura injuries in total, 3 in group A, 2 in group B, and 1 in group C. No postoperative neurologic defects or occurrences of hematoma were recorded. According to our results, we concluded that combined use of FloSeal and bone scalpels is recommended during primary thoracolumbar spinal surgery to reduce the intraoperative blood loss and shorten the surgical duration.
High-Speed Ternary Half adder based on GNRFET

Superior electronic properties of graphene make it a substitute candidate for beyond-CMOSnanoelectronics in electronic devices such as the field-effect transistors (FETs), tunnel barriers, andquantum dots. The armchair-edge graphene nanoribbons (AGNRs), which have semiconductor behavior,are used to design the digital circuits. This paper presents a new design of ternary half adder basedon graphene nanoribbon FETs (GNRFETs). Due to reducing chip the area and integrated circuit (IC)interconnects, ternary value logic is a good alternative to binary logic. Extensive simulations have beenperformed in Hspice with 15-nm GNRFET technology to investigate the power consumption and delay.Results show that the proposed design is very high-speed in comparison with carbon nanotube FETs(CNTFETs). The proposed ternary half adder based on GNRFET at 0.9V exhibiting a low power-delayproduct(PDP) of ~10-20 J, which is a high improvement in comparison with the ternary circuits basedon CNTFET, lately proposed in the literature. This proposed ternary half adder can be advantageous incomplex arithmetic circuits.