Miracle-dz/UniFAR-FTUs huggingface dataset:
RETHINKING AND UNTHINKING DEVELOPMENT: Perspectives on Inequality and Poverty in South Africa and Zimbabwe

Development has remained elusive in Africa. Through theoretical contributions and case studies focusing on Southern Africa’s former white settler states, South Africa and Zimbabwe, this volume responds to the current need to rethink (and unthink) development in the region. The authors explore how Africa can adapt Western development models suited to its political, economic, social and cultural circumstances, while rejecting development practices and discourses based on exploitative capitalist and colonial tendencies. Beyond the legacies of colonialism, the volume also explores other factors impacting development, including regional politics, corruption, poor policies on empowerment and indigenization, and socio-economic and cultural barriers.
A Novel Set-Valued Sensor Fault Diagnosis Method for Lithium-Ion Battery Packs in Electric Vehicles

Sensor fault diagnosis is of great significance to ensure safe battery operation. This paper proposes a novel sensor fault diagnosis method that achieves the simultaneous fault detection, fault source and type identification, and fault estimation in a comprehensive way. Specifically, a set-valued observer, featuring a state predictor and a state estimator, is first constructed and designed to guarantee the inclusion of the unavailable actual battery state due to unknown modeling errors and noises at every instant of time. Compared with the traditional observers, a distinct feature of the proposed one lies in that the calculated state predictions and estimations of the battery system at each time step are ellipsoidal sets in state space rather than single vectors. The boundedness of state prediction and estimation errors is formally proved, and the tractable design criteria for determining the real-time optimal prediction and estimation ellipsoids are also derived. As for diagnosis algorithm, fault detection is implemented based on the intersection between the prediction and estimation ellipsoids. Then, a two-layer Pearson correlation coefficient analysis mechanism is developed to identify the source and type of sensor faults. Another set-valued observer based on an augmented battery model is further designed to estimate the fault level. Finally, experimental studies of a battery cell under different sensor fault sources, types and values are elaborated to verify the effectiveness of the proposed method.
Krylov precise time‐step integration method

An efficient precise time‐step integration (PTI) algorithm to solve large‐scale transient problems is presented in this paper. The Krylov subspace method and the Padé approximations are applied to modify the original PTI algorithm in order to improve the computational efficiency. Both the stability and accuracy characteristics of the resultant algorithms are investigated. The efficiency can be further improved by expanding the dimension to avoid the computation of the particular solutions. The present algorithm can also be extended to tackle nonlinear problems without difficulty. Two numerical examples are given to illustrate the highly accurate and efficient algorithm. Copyright © 2006 John Wiley & Sons, Ltd.
Alzheimer Disease Classification through Transfer Learning Approach

Alzheimer’s disease (AD) is a slow neurological disorder that destroys the thought process, and consciousness, of a human. It directly affects the development of mental ability and neurocognitive functionality. The number of patients with Alzheimer’s disease is increasing day by day, especially in old aged people, who are above 60 years of age, and, gradually, it becomes cause of their death. In this research, we discuss the segmentation and classification of the Magnetic resonance imaging (MRI) of Alzheimer’s disease, through the concept of transfer learning and customizing of the convolutional neural network (CNN) by specifically using images that are segmented by the Gray Matter (GM) of the brain. Instead of training and computing the proposed model accuracy from the start, we used a pre-trained deep learning model as our base model, and, after that, transfer learning was applied. The accuracy of the proposed model was tested over a different number of epochs, 10, 25, and 50. The overall accuracy of the proposed model was 97.84%.
Physical Inactivity Levels of European Adolescents in 2002, 2005, 2013, and 2017

Sport and Physical Activity (PA) Special Eurobarometer surveys may inform of the physical inactivity (PIA) levels in the European Union (EU). This study aimed to analyse the PIA levels of EU adolescents (15–17 years) in four time points, according to gender. The data were from 2002, 2005, 20013, and 2017 Special Eurobarometers. Adolescents were categorised as “Inactive” when performing less than 60 min/day of moderate to vigorous PA on average. A χ2 test was used to compare the levels of PIA between survey years. PIA levels between gender were analysed using a Z-score test for two population proportions. PIA levels ranged from 67.2% for boys (59.4% to 71.5%;) to 76.8% for girls (76.0% to 83.4) across the time points. Adjusted standardised residuals revealed a decrease in the observed levels versus the expected for 2005 (whole sample: −4.2; boys: −3.3) and an increase for 2013 (whole sample: +2.9; boys: +2.5). Boys presented lower PIA levels than girls in all years (p ≤ 0.003), but descriptively, the difference progressively decreased (from 18.4% to 11.8%). No significant reductions in PIA levels were observed between 2002 and 2017, and girls reported consistently higher levels of PIA than boys.
Enhanced thermal conductivity of carbon fiber/phenolic resin composites by the introduction of carbon nanotubes

The authors report a significant enhancement in the thermal conductivity of a conventional carbon fiber/phenolic resin composite system when adding highly crystalline multiwalled carbon nanotubes. They demonstrate that 7wt% of carbon nanotubes dispersed homogeneously in a phenolic resin acted as an effective thermal bridge between adjacent carbon fibers and resulted in an enhancement of the thermal conductivity (e.g., from 250to393W∕mK). These results indicate that highly crystalline carbon nanotubes can be used as a multifunctional filler to enhance simultaneously the mechanical and thermal properties of the carbon fiber/phenolic resin composites.
A Doherty Power Amplifier for Ultrasound Instrumentation

The ultrasound instrumentation uses linear power amplifiers with low power efficiency, generating unwanted heat and resulting in the deterioration of the echo signal quality of measured targets. Therefore, this study aims to develop a power amplifier scheme to increase power efficiency while maintaining appropriate echo signal quality. In communication systems, the Doherty power amplifier has shown relatively good power efficiency while producing high signal distortion. The same design scheme cannot be directly applied to ultrasound instrumentation. Therefore, the Doherty power amplifier needs to be re-designed. To verify the feasibility of the instrumentation, a Doherty power amplifier was designed to obtain high power efficiency. The measured gain, output 1-dB compression point, and power-added efficiency of the designed Doherty power amplifier were 33.71 dB, 35.71 dBm, and 57.24% at 25 MHz, respectively. In addition, the performance of the developed amplifier was measured and tested using the ultrasound transducer through the pulse-echo responses. The output power with 25 MHz, 5-cycle, and 43.06 dBm generated from the Doherty power amplifier was sent through the expander to the focused ultrasound transducer with 25 MHz and 0.5″ diameter. The detected signal was sent via a limiter. Afterwards, the signal was amplified by a 36.8 dB gain preamplifier, and then displayed in the oscilloscope. The measured peak-to-peak amplitude in the pulse-echo response with an ultrasound transducer was 0.9698 V. The data showed a comparable echo signal amplitude. Therefore, the designed Doherty power amplifier can improve the power efficiency used for medical ultrasound instrumentation.
Associating Compositional, Nutritional and Techno-Functional Characteristics of Faba Bean (Vicia faba L.) Protein Isolates and Their Production Side-Streams with Potential Food Applications

Faba beans (Vicia faba L.) show exciting prospects as a sustainable source of protein and fibre, with the potential to transition to a more sustainable food production. This study reveals the compositional, nutritional and techno-functional characteristics of two protein isolates from faba beans (Vicia faba L.), a high-starch fraction and a high-fibre side-stream. During the analysis of those four ingredients, particular attention was paid to the isolates’ protein profile and the side-streams’ carbohydrate composition. The isoelectric precipitated protein isolate 1 showed a protein content of 72.64 ± 0.31% DM. It exhibited low solubility but superior digestibility and high foam stability. High foaming capacity and low protein digestibility were observed for protein isolate 2, with a protein content of 71.37 ± 0.93% DM. This fraction was highly soluble and consisted primarily of low molecular weight proteins. The high-starch fraction contained 83.87 ± 3.07% DM starch, of which about 66% was resistant starch. Over 65% of the high-fibre fraction was insoluble dietary fibre. The findings of this study provide a detailed understanding of different production fractions of faba beans, which is of great value for future product development.
Residue-to-binary decoder for an enhanced moduli set

Previous publications have given the moduli set (2/sup n/, 2/sup n/-1, 2/sup n/+1) considerable attention. In the residue number system literature this moduli set was referred to as the popular set. However, the dynamic range of this set is limited to 3n bits. A new moduli set (2/sup 2n/, 2/sup n/-1, 2/sup n/+1) is proposed with a dynamic range of 4n bits. This enhanced set enjoys the same features of the popular one. Also proposed are closed forms for multiplicative inverses for the set and an algorithm for decoding the residue digits into their binary equivalent. Although it increases the dynamic range by 33%, the residue-to-binary decoder of the new set requires the same hardware and time complexity as the popular one.
Pharmacogenetics in the Treatment of Huntington’s Disease: Review and Future Perspectives

Huntington’s disease (HD) is an autosomal dominant progressive brain disorder, caused by a pathological expansion of a CAG repeat that encodes the huntingtin gene. This genetic neurodegenerative rare disease is characterized by cognitive, motor, and neuropsychiatric manifestations. The aim of the treatment is symptomatic and addresses the hyperkinetic disorders (chorea, dystonia, myoclonus, tics, etc.) and the behavioural and cognitive disturbances (depression, anxiety, psychosis, etc.) associated with the disease. HD is still a complex condition in need of innovative and efficient treatment. The long-term goal of pharmacogenetic studies is to use genotype data to predict the effective treatment response to a specific drug and, in turn, prevent potential undesirable effects of its administration. Chorea, depression, and psychotic symptoms have a substantial impact on HD patients’ quality of life and could be better controlled with the help of pharmacogenetic knowledge. We aimed to carry out a review of the available publications and evidence related to the pharmacogenetics of HD, with the objective of compiling all information that may be useful in optimizing drug administration. The impact of pharmacogenetic information on the response to antidepressants and antipsychotics is well documented in psychiatric patients, but this approach has not been investigated in HD patients. Future research should address several issues to ensure that pharmacogenetic clinical use is appropriately supported, feasible, and applicable.
NONDETECTION OF THE NEPTUNE-MASS PLANET REPORTED AROUND GJ 176

Endl et al. reported a Neptune-mass planet in a 10.24 day orbit around GJ 176. This planet has raised interest because of its low mass (Msin i = 24 MEarth), correspondingly small velocity amplitude (K = 11.7 m s−1), and because GJ 176 is an M star. We report 41 precise Doppler measurements of GJ 176 obtained with the Keck-HIRES spectrometer over a 10 year time span. These measurements show no evidence of the 10.24 day companion, at a threshold of 4 m s−1, a factor of 3 less than the amplitude reported by Endl et al. The Keck velocities are consistent with instrumental noise and stellar jitter. The existence of the planet is thus called into question.
Progress in single‐walled carbon nanotube based nanoelectromechanical systems

We present torsional pendulums based on small bundles of single‐walled carbon nanotubes and ultimately on individual single‐walled carbon nanotubes. The nanotubes serve as mechanical support and torsional spring for a lithographically defined metal plate. The plate can be actuated in an electric field and the device is operated inside the transmission electron microscope. In comparison with previous works we have built mechanically much more fragile devices, i.e. almost three orders of magnitude heavier suspended metal structures, and metal blocks suspended on smaller diameter nanotubes. (© 2006 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Diurnal variation of marine stratocumulus over San Nicolas Island during July 1987

Abstract Surface measurements made at San Nicolas Island during the intensive field observation marine stratocumulus phase of the First International Satellite Cloud Climatology Progam Regional Experiment, July 1987, are analyzed to retrieve the average diurnal variation of marine stratocumulus and related surface variables. Cloud thickness and integrated liquid-water content show a clear decrease during the day from sunrise to sunset, increasing thereafter. The average liquid-water density in the cloud is closely related to the cloud thickness, decreasing as the cloud thickness decreases. The cloud-base height has a diurnal range of 150 ± 30 m, rising from sunrise till midafternoon. The cloud-top height has a similar diurnal range of 130 ± 30 m, but the main descent occurs in the late afternoon. Surface air temperature also increases at sunrise, directly in phase with the cloud-base lifting, and has a diurnal range of 2°C. The diurnal behavior of the cloud base appears to be consistent with model-predict.
Characterization of bent large-mode-area photonic crystal fiber

In this paper, the characteristics of bent large-mode-area photonic crystal fibers are investigated comprehensively by using a finite difference mode solver with perfectly matched layers. Numerical results show that in bent large-mode-area photonic crystal fibers, the mode-field distributions are deformed and the effective mode area and the width of the guided region are reduced. The propagation character of bent photonic crystal fibers is determined by normalized propagation number and normalized bend radius. Meanwhile, the bending loss oscillation is observed and the position of the first loss peak is obtained in bent large-mode-area photonic crystal fibers.
An Ultra-Fast Temporal Talbot Array Illuminator

We propose an all-optical temporal Talbot array illuminator (T-TAI) enabling denoising passive amplification of broadband ($>$10 GHz-bandwidth) optical signals. The key element is an ultra-fast temporal phase grating based on cross-phase modulation. Whereas previous implementations of the T-TAI suffer from the bandwidth limitations inherent to electro-optic systems, the all-optical nature of the proposed approach allows to simultaneously realize high amplification factors and sampling rates, which in turn allows for the efficient processing of broadband signals. In our experiments, we demonstrate a (signal bandwidth) × (amplification factor) product exceeding 370 GHz, more than an order of magnitude improvement as compared with previous electro-optic implementations. We show the prospects of the proposed approach through the recovery of noisy high-speed optical waveforms, namely a $\sim$10 Gbps data signal buried in a much stronger noise background. Additionally, we experimentally demonstrate that the T-TAI samples preserve the full complex information (amplitude and phase) of the incoming signal. The proposed approach should prove useful in multiple fields requiring the detection of weak and noisy broadband signals as well as for other related applications, such as photonics-assisted analog-to-digital conversion.
Disentangling Relationships among the Alpine Species of Luzula Sect. Luzula (Juncaceae) in the Eastern Alps

Polyploidisation, agmatoploidy and symploidy have driven the diversification of Luzula sect. Luzula. Several morphologically very similar species with different karyotypes have evolved, but their evolutionary origins and relationships are unknown. In this study, we used a combination of relative genome size and karyotype estimations as well amplified fragment length polymorphism (AFLP) fingerprinting to investigate the relationships among predominately (sub)alpine Luzula alpina, L. exspectata, L multiflora and L. sudetica in the Eastern Alps, including also some samples of L. campestris and L. taurica as outgroup. Our study revealed common co-occurrence of two or three different ploidies (di-, tetra- and hexaploids) at the same localities, and thus also common co-occurrence of different species, of which L. sudetica was morphologically, ecologically and genetically most divergent. Whereas agmatoploid L. exspectata likely originated only once from the Balkan L. taurica, and hexaploid L. multiflora once from tetraploid L. multiflora, the AFLP data suggest multiple origins of tetraploid L. multiflora, from which partly agmatoploid individuals of L. alpina likely originated recurrently by partial fragmentation of the chromosomes. In contrast to common recurrent formation of polyploids in flowering plants, populations of agmatoploids resulting by fission of complete chromosome sets appear to have single origins, whereas partial agmatoploids are formed recurrently. Whether this is a general pattern in Luzula sect. Luzula, and whether segregation of ecological niches supports the frequent co-occurrence of closely related cytotypes in mixed populations, remains the subject of ongoing research.
A systematic review of follow-up results of additively manufactured customized implants for the pelvic area

ABSTRACT Introduction While 3D printing of bone models for preoperative planning or customized surgical templating has been successfully implemented, the use of patient-specific additively manufactured (AM) implants is a newer application not yet well established. To fully evaluate the advantages and shortcomings of such implants, their follow-up results need to be evaluated. Area Covered This systematic review provides a survey of the reported follow-ups on AM implants used for oncologic reconstruction, total hip arthroplasty both primary and revision, acetabular fracture, and sacrum defects. Expert Opinion The review shows that Titanium alloy (Ti4AL6V) is the most common type of material system used due to its excellent biomechanical properties. Electron beam melting (EBM) is the predominant AM process for manufacturing implants. In almost all cases, porosity at the contact surface is implemented through the design of lattice or porous structures to enhance osseointegration. The follow-up evaluations show promising results, with only a small number of patients suffering from aseptic loosening, wear, or malalignment. The longest reported follow-up length was 120 months for acetabular cages and 96 months for acetabular cups. The AM implants have proven to serve as an excellent option to restore premorbid skeletal anatomy of the pelvis.
Ambiguity in Determining the Effective Action for String-Corrected Einstein Gravity

We attempt to clarify some issues dealing with the determination of some of the coefficients in the low-energy gravitational effective action for closed stringll. An explicit calculation is generalized demonstrating that the coefficients of the R~v and R2 terms of completely general quadratic curvature corrections to the Einstein-Hilbert action cannot be determined by matching the on-shell Smatrix of the effective theory with those of the string theories. Although ghost poles will appear in the graviton propagator for general quadratic curvature corrections, the effective theory remains unitary, the pole dependence cancelling completely from the scattering amplitude. The manifest absence of ghosts is achieved by choosing the Gauss·Bonnet combination of quadratic curvatures, but the reql! irement of unitarity does not uniquely specify this combination.
Highly sensitive magnetic sensor made with a superconducting Y-Ba-Cu-O thick film

In the research, Y-Ba-Cu-O (YBCO) thick film was fabricated to form a highly sensitive magnetic sensor, constructed to maintain the superconducting state at the boiling point of liquid nitrogen (77.4 K). Superconducting film will, in general, break the superconducting state of the flow of current at the value of current density J greater than that of the critical current density J/sub c/, when the resistance R/sub sen/ to the flow of current occurs. The magnetic sensitivity increases as the value of the resistivity /spl rho//sub seu/ of R/sub sen/ decreases. The value of /spl rho//sub sen/ can be readily controlled by the value of J. The average sensitivity S of this magnetic sensor was determined as about 154%/gauss, over the magnetic range of 0 gauss to /spl plusmn/40 gauss. In addition,the sensitivity is about 154 times that of a giant magneto-resistance sensor. The paper examines the fabrication process and conditions, the characteristics of S as related to /spl rho//sub sen/, and the magnetic response of the highly sensitive magnetic sensor.
Space-Time Adaptive Processing via Random Matrix Theory for Finite Training Samples

Space-time adaptive processing (STAP) is one of the most effective approaches for clutter suppression in airborne radar systems. However, when the number of training samples is less than two times system degrees of freedom (DoFs), the performance of conventional full-dimension (FD)-STAP degrades severely due to inaccurate clutter-plus-noise covariance matrix (CNCM) estimation. In order to enhance the STAP performance under the situation of insufficient training samples, this article proposes a novel STAP method based on the random matrix theory (RMT). According to the spiked covariance model in RMT, we can obtain the estimate of inverse CNCM by determining its eigenvalues, including the noise-related ones and the clutter-related ones from the eigenvalues of sample covariance matrix (SCM) while keeping its eigenvectors consistent with that of SCM. Specifically, the noise-related eigenvalues are directly determined according to the noise power, while the clutter-related eigenvalues are determined by minimizing the output clutter-plus-noise power in terms of RMT. Ultimately, the optimal RMT-STAP weight is derived according to the classical minimum variance distortionless response (MVDR) criterion. Profiting from the great estimation performance on the inverse CNCM, RMT-STAP is significantly superior to other-related FD STAP methods when the number of training samples is less than two times system DoFs. Numerical and real-data experiments verify the effectiveness and robustness of the proposed RMT-STAP method.