Miracle-dz/UniFAR-FTUs huggingface dataset:
A Spectrum Efficient Constellation to Simultaneously Transmit Information and Synchronization Sequence

In this paper, a new type of quadrature phase shift keying (QPSK) modulation, named as special QPSK (SQPSK), is proposed and optimized. For SQPSK, the quadrant of the symbol is determined by the bits in information sequence according to QPSK constellation, while the offset relative to the original QPSK constellation is controlled by the bits in synchronization sequence. Under this scheme, the simultaneous transmission of information and synchronization sequences is implemented to improve spectrum efficiency with low computational complexity. In order to achieve the best balance beteween the bit error rate (BER) and the synchronization performance, we optimize the parameter design. Furthermore, a joint synchronization scheme is proposed for frame synchronization, frequency offset estimation, and frequency offset compensation to solve the performance loss caused by Doppler frequency shift in practical applications. Then based on the characteristics of the constellation map, a dynamic threshold demodulation scheme which further improves the BER performance is discussed. Finally, some simulation results are given to show that the SQPSK not only has both good error performance and acquisition performance, but also improves the spectrum utilization of channel resource significantly.
Economic performance indicators for fisheries

An outline of the concept of sustainable development is followed by a definition of the term ‘economics’ and a brief review of attempts to use economic principles to construct an integrated indicator to replace gross domestic product. Arange of proxy indicators is described; these are based on what is possible in countries that have minimal fisheries data and where fishers are making decisions on the crudest economic information.
Estimativas de parâmetros genéticos para produção de leite e persistência da lactação em vacas Gir, aplicando modelos de regressão aleatória

Com o objetivo de estimar parâmetros geneticos para a producao de leite no dia do controle (PLDC), foram usadas as 2.440 primeiras lactacoes de vacas da raca Gir leiteira, com partos registrados entre 1990 e 2005. As PLDC foram consideradas em dez classes mensais e analisadas por meio de modelo de regressao aleatoria (MRA) utilizando-se como efeitos aleatorios o genetico-aditivo, o de ambiente permanente e o residual e, como efeitos fixos, o grupo de contemporâneos (GC), a co-variavel idade da vaca ao parto (efeito linear e quadratico) e a curva media de lactacao da populacao. Os efeitos genetico-aditivos e de ambiente permanente foram modelados utilizando-se as funcoes de Wilmink (WIL) e Ali e Schaeffer (AS). As variâncias residuais foram modeladas utilizando-se 1, 4, 6 ou 10 classes. Os grupos de contemporâneos foram definidos como rebanho-ano-estacao do controle contendo no minimo tres animais. Os testes indicaram que o modelo com quatro classes de variâncias usando a funcao parametrica AS foi o que melhor se ajustou aos dados. As estimativas de herdabilidade variaram de 0,21 a 0,33 para a funcao AS e de 0,17 a 0,30 para WIL e foram maiores na primeira metade da lactacao. As correlacoes geneticas entre as PLDC foram positivas e elevadas entre os controles adjacentes e diminuiram quando a distância entre os controles aumentou. Para o melhor modelo, foram estimados os valores geneticos para a producao de leite acumulada ate os 305 dias e, para periodos parciais da lactacao, foram obtidas como medias dos valores geneticos preditos naquele periodo. Os valores geneticos foram comparados, por meio da correlacao de posto, ao valor genetico predito para a producao acumulada ate os 305 dias, pelo metodo tradicional. As correlacoes entre os valores geneticos indicaram que podem ocorrer divergencias na classificacao dos animais pelos criterios estudados.
Detecting and Estimating Amount of Energy Theft in the Distribution Network Using Linear Regression

Non-technical losses (NTL) in the distribution network has been an issue for a lot of electric utilities for a long time. Recent developments for NTL detection had focused on using energy meter consumption for pattern or anomaly detection in identifying suspicious consumption behavior. In this study, meter bypass and unmetered load tapping were modeled in OpenDSS to simulate the effect of NTL in the low voltage network. With the assumption that smart meter data from houses and check meter data from a distribution transformer is known, the voltage and power readings were used to build a linear regression model for estimating power consumption of each customer. A significant mismatch between the estimate and actual meter reading had been found to correspond to an anomalous consumption in the network. The algorithm had been able to identify the locations for meter bypass and narrow down the area for possible inspection for unmetered load connection.
Energy-Efficient Locomotion Generation and Theoretical Analysis of a Quasi-Passive Dynamic Walker

This Letter presents a robot walking control method, which we call “quasi-passive dynamic walking. ” The method is targeted at underactuated legged robots and applied to obtain energy-efficient limit cycle gait on level ground. To achieve efficient locomotion, as well as to overcome the underactuation of the system, two key points are implemented into this method to positively utilize the passive dynamics of the system. The first one is to initialize the walker at the fixed Poincaré section obtained from passive dynamic walking on a gentle downhill. The second one is to indirectly excite the hip angle by periodically oscillating a wobbling mass, which is attached to the body frame. The walker is, therefore, able to step forward on level ground without any torque actuation. Moreover, the phase diagram of the generated gait is entrained to limit cycle by the periodical oscillation of the wobbling mass. Numerical simulations and theoretical analysis are conducted to evaluate the efficiency as well as the local stability of the gait. Our control method enables underactuated legged robots to walk extremely efficiently on level ground with only one actuator, which provides the easiness for implementation on real machines.
Determining Corticospinal Tract Injury from Stroke Using Computed Tomography

ABSTRACT: Introduction: Damage to the corticospinal tract (CST) from stroke leads to motor deficits. The damage can be quantified as the amount of overlap between the stroke lesion and CST (CST Injury). Previous literature has shown that the degree of motor deficits post-stroke is related to the amount of CST Injury. These studies delineate the stroke lesion from structural T1-weighted magnetic resonance imaging (MRI) scans, often acquired for research. In Canada, computed tomography (CT) is the most common imaging modality used in routine acute stroke care. In this proof-of-principle study, we determine whether CST Injury, using lesions delineated from CT scans, significantly explains the variability in motor impairment in individuals with stroke. Methods: Thirty-seven participants with stroke were included in this study. These individuals had a CT scan within the acute stage (7 days) of their stroke and underwent motor assessments. Brain images from CT scans were registered to MRI space. We performed a stepwise regression analysis to determine the contribution of CST injury and demographic variables in explaining motor impairment variability. Results: Using clinically available CT scans, we found modest evidence that CST Injury explains variability in motor impairment (R2adj = 0.12, p = 0.02). None of the participant demographic variables entered the model. Conclusion: We show for the first time a relationship between CST Injury and motor impairment using CT scans. Further work is required to evaluate the utility of data derived from clinical CT scans as a biomarker of stroke motor recovery.
Analysis of Different Pre-Processing Techniques to the Development of Machine Learning Predictors with Gene Expression Profiles

In this ongoing research work we analyzed the impact of several different data pre-processing and normalization methods on the performance of Support Vector Machines (SVM). The pre-processing methods used are: deleting missing values, imputing zeroes, means, medians, modes, K-Nearest Neighbors (KNN), and Predictive Mean Matching (PMM). Each one of these pre-processing methods will be paired with two normalization methods, log2 and Z-Score. After training, the models will be tested using a validation set, derived from the training set, representing an unseen partition dataset. Subsequently performance metrics will be obtained and compared across each of the models for the training performance and the test performance. These comparisons will then be analyzed and interpreted. The aim of our work was to potentially identify the impact of pre-processing approaches on predictor construction to potentially identify a standard method for expression profile analysis using machine learning methods.
Reformulation of a Linear Program to Reduce the Average Current in a Modular Multilevel Converter

A modular multilevel converter contains many capacitor full-bridge converter cells. An increased capacitance in the converter means a large overall converter size and increased converter cost. Previous research has investigated methods to reduce converter cell capacitance. One paper presents an iterative linear program to reduce the capacitance while limiting the average currents. The work presented in this paper modifies the linear program to further reduce average currents for similar reduction in capacitance. Furthermore, the results presented here show root-mean-square currents will also be reduced.
Autoreactive CD8 T cells associated with β cell destruction in type 1 diabetes

Type 1 diabetes is a T cell-mediated autoimmune disease, and insulin is an important target of the autoimmune response associated with β cell destruction. The mechanism of destruction is still unknown. Here, we provide evidence for CD8 T cell autoreactivity associated with recurrent autoimmunity and loss of β cell function in type 1 diabetic islet transplant recipients. We first identified an insulin B chain peptide (insB10-18) with extraordinary binding affinity to HLA-A2(*0201) that is expressed by the majority of type 1 diabetes patients. We next demonstrated that this peptide is naturally processed by both constitutive and immuno proteasomes and translocated to the endoplasmic reticulum by the peptide transporter TAP1 to allow binding to HLA-A2 in the endoplasmic reticulum and cell surface presentation. Peripheral blood mononuclear cells from a healthy donor were primed in vitro with this peptide, and CD8 T cells were isolated that specifically recognize target cells expressing the insulin B chain peptide. HLA-A2insB10-18 tetramer staining revealed a strong association between detection of autoreactive CD8 T cells and recurrent autoimmunity after islet transplantation and graft failure in type 1 diabetic patients. We demonstrate that CD8 T cell autoreactivity is associated with β cell destruction in type 1 diabetes in humans.
Sepsis With Preexisting Heart Failure: Management of Confounding Clinical Features

Preexisting heart failure (HF) in patients with sepsis is associated with worse clinical outcomes. Core sepsis management includes aggressive volume resuscitation followed by vasopressors (and potentially inotropes) if fluid is inadequate to restore perfusion; however, large fluid boluses and vasoactive agents are concerning amid the cardiac dysfunction of HF. This review summarizes evidence regarding the influence of HF on sepsis clinical outcomes, pathophysiologic concerns, resuscitation targets, hemodynamic interventions, and adjunct management (ie, antiarrhythmics, positive pressure ventilatory support, and renal replacement therapy) in patients with sepsis and preexisting HF. Patients with sepsis and preexisting HF receive less fluid during resuscitation; however, evidence suggests traditional fluid resuscitation targets do not increase the risk of adverse events in HF patients with sepsis and likely improve outcomes. Norepinephrine remains the most well-supported vasopressor for patients with sepsis with preexisting HF, while dopamine may induce more cardiac adverse events. Dobutamine should be used cautiously given its generally detrimental effects but may have an application when combined with norepinephrine in patients with low cardiac output. Management of chronic HF medications warrants careful consideration for continuation or discontinuation upon development of sepsis, and β-blockers may be appropriate to continue in the absence of acute hemodynamic decompensation. Optimal management of atrial fibrillation may include β-blockers after acute hemodynamic stabilization as they have also shown independent benefits in sepsis. Positive pressure ventilatory support and renal replacement must be carefully monitored for effects on cardiac function when HF is present.
No effect of resveratrol supplementation after 6 months on insulin sensitivity in overweight adults: a randomized trial

ABSTRACT Background Effects of resveratrol on metabolic health have been studied in several short-term human clinical trials, with conflicting results. Next to dose, the duration of the clinical trials may explain the lack of effect in some studies, but long-term studies are still limited. Objectives The objective of this study was to investigate the effects of 6-mo resveratrol supplementation on metabolic health outcome parameters. Methods Forty-one overweight men and women (BMI: 27–35 kg/m2; aged 40–70 y) completed the study. In this parallel-group, double-blind clinical trial, participants were randomized to receive either 150 mg/d of resveratrol (n = 20) or placebo (n = 21) for 6 mo. The primary outcome of the study was insulin sensitivity, using the Matsuda index. Secondary outcome measures were intrahepatic lipid (IHL) content, body composition, resting energy metabolism, blood pressure, plasma markers, physical performance, quality of life, and quality of sleep. Postintervention differences between the resveratrol and placebo arms were evaluated by ANCOVA adjusting for corresponding preintervention variables. Results Preintervention, no differences were observed between the 2 treatment arms. Insulin sensitivity was not affected after 6 mo of resveratrol treatment (adjusted mean Matsuda index: 5.18 ± 0.35 in the resveratrol arm compared with 5.50 ± 0.34 in the placebo arm), although there was a significant difference in postintervention glycated hemoglobin (HbA1c) between the arms (P = 0.007). The adjusted means showed that postintervention HbA1c was lower on resveratrol (35.8 ± 0.43 mmol/mol) compared with placebo (37.6 ± 0.44 mmol/mol). No postintervention differences were found in IHL, body composition, blood pressure, energy metabolism, physical performance, or quality of life and sleep between treatment arms. Conclusions After 6 mo of resveratrol supplementation, insulin sensitivity was unaffected in the resveratrol arm compared with the placebo arm. Nonetheless, HbA1c was lower in overweight men and women in the resveratrol arm. This trial was registered at Clinicaltrials.gov as NCT02565979.
The effect of Effort expectancy, Ubiquity, and Context on intention to use online applications

In this paper, we developed a new conceptual model of integrating unified theory of acceptance and use of technology (UTAUT) with ubiquity, and context as constructs to measure their impact on user's intention to use online applications (apps). This research is conducted in Omani Community to look at their responses toward adopting and using mobile apps. For this reason, data was collected by distributing questionnaires among people at Dhofar University, besides an online sharing link for people to solve. The results of this research indicate the influence of Effort Expectancy, and Ubiquity as affected directly on the behavioral intention to use. This article will contribute in field of mobile applications, and propose recommendations for future studies to telecom providers, and mobile service developers.
In-Vitro antibacterial activity of bioactive plant extracts against methicillin-resistant strains of staphylococcus aureus

Methanol extract of leaves of five different Nigerian plants were tested for activity against three drug resistant strains of Staphylococcus aureus by the agar well diffusion and broth microdilution techniques. The S. aureus strains were composed of two clinical isolates and one reference strain. Promising antimicrobial activity was displayed by three of the five plants tested. Minimum inhibitory concentration (MIC) of the extracts ranged from 25 mg/ml to 100 mg/ml. The clinical isolates had comparable level of sensitivity to the three most active extracts. Both were also more susceptible to the extracts than the reference strain. Phytochemical analyses showed that secondary plant constituents were present in varied concentrations in all the extracts.
A revision of the Chilean Brachyglutini – Part 6. Revision of Achilia Reitter, 1890: A. grandiceps, A. valdiviensis, and A. bicornis species groups (Coleoptera: Staphylinidae: Pselaphinae)

Abstract: The Achilia grandiceps, A. valdiviensis, and A. bicornis species groups sensu Jeannel (1962) of the species-rich genus Achilia Reitter, 1890 are revised. Of the eigth taxa placed in these three groups of species, two subspecies, i.e. A. grandiceps grandiceps Jeannel, 1962 and A. grandiceps delamarei Jeannel, 1962 are raised to species level – A. grandiceps Jeannel, 1962 stat. nov. and A. delamarei Jeannel, 1962 stat. nov. – while three names are placed in synonymy – A. alticola Jeannel, 1962 = A. grandiceps Jeannel, 1962 syn. nov., A. kuscheli Jeannel, 1962 = A. valdiviensis (Blanchard, 1851) syn. nov., and A. chilotides Newton, 2017 = A. excisa (Schaufuss, 1880) syn. nov. – The remaining five species are redescribed, and the new species A. franzi n. sp. , A. jeanneli n. sp. , and A. elguetai n. sp. , attributed to the A. grandiceps group, are described. A new synonymy A. simpsoni Franz, 1996 = A. bicornis Jeannel, 1962 syn. nov. is also established, and the lectotypes of A. delamarei Jeannel, 1962 and A. valdiviensis (Blanchard, 1851) are designated. For all these species their distribution is detailed and mapped, and habitat/collecting data are summarized.
Genetic Variation for Seed Yield, Protein Content, Oil Content, and Seed Weight in Lupinus albus

The yield, protein content, oil content and weight of seeds of 14 lines of L. albus and of 232 F3 families derived from them have been determined in a favourable environment to assess the potential for the genetic improvement of this species. Yield and protein content exhibited wide variability around mean values of 1705 kg ha-l and 38.4% respectively. Their broad sense heritabilities were 57% and 83 % respectively, and neither character showed significant variety x environment interaction when parental lines were grown in two contrasting environments which significantly affected the mean values. These characters were predicted to respond to selection, but progress would be hindered by a genetic correlation between them of -0.53. Oil content had a low mean (9.1 %), high heritability (90%), but a low phenotypic variance, and hence would respond little to selection. It also was subject to variety x environment interaction. Seed size should respond readily to selection. No other unfavourable genetic correlations were found between flowering time, yield, protein and oil contents, and seed weight. Transgressive segregation was common in F3 families, many of which had lower protein, higher oil or smaller seeds than either of their parents.
Physical activity is positively related to local functional connectivity in adolescents’ brains

Adolescents have experienced decreased aerobic fitness levels and insufficient physical activity levels over the past decades. While both physical activity and aerobic fitness are related to physical and mental health, little is known concerning how they manifest in the brain during this stage of development, characterized by significant physical and psychosocial changes. Previous investigations have demonstrated associations of physical activity and aerobic fitness with the brain’s functional connectivity in both children and adults. However, it is difficult to generalize these results to adolescents because the development of functional connectivity has unique features during adolescence. Here, we examined how physical activity and aerobic fitness are associated with local and interhemispheric functional connectivity of the adolescent brain, as measured with resting-state functional magnetic resonance imaging (fMRI). Physical activity was measured by hip-worn accelerometers, and aerobic fitness by a maximal 20-m shuttle run test. We found that higher levels of moderate-to-vigorous physical activity, but not aerobic fitness, were linked to increased local functional connectivity as measured by regional homogeneity in 13–16-year-old participants. However, we did not find evidence for significant associations between adolescents’ physical activity or aerobic fitness and interhemispheric connectivity, as indicated by homotopic connectivity. These results suggest that physical activity, but not aerobic fitness, is related to local functional connectivity in adolescents. Moreover, physical activity shows an association with a specific brain area involved in motor functions but did not display any widespread associations with other brain regions. These results can advance our understanding of the behavior-brain associations in adolescents.
Cost minimization in a MicroGrid connected with Wind and PV generations using a hybrid Cat Swarm optimization and micro Differential Evolution

This paper proposes a new hybrid methodology to solve the cost minimization of generation in a MicroGrid. This solution methodology is modeled using two powerful heuristic based methods such that the main optimizer is the Cat Swarm optimization and final solution tuning is done by a micro Differential Evolution. The MicroGrid is modeled with three different types of generating sources such that diesel generating plant and renewable sources like wind and solar. The diesel generating plant is modeled as a non-convex fuelcost function and wind and solar generating sources are formulated as non-linear cost function but will be formulated as inequality constraints. The objective function is the combination of diesel generator fuel-cost and the cost of power transferable between main grid and micro grid. A 150 bus Islanded MicroGrid system is adopted such that the system has various types of distributed generations such that wind, Solar and diesel power plants are connected. Simulation results are shown for the proposed hybrid algorithm and compared with the techniques applied individually before they were hybridized. Final results demonstrates the applicability of the proposed hybrid algorithm for solving the cost minimization problem in a MicroGrid.
Distributed reinforcement learning for flexible UAV swarm control with transfer learning capabilities

Over the past few years, the use of swarms of Unmanned Aerial Vehicles (UAVs) in monitoring and remote area surveillance applications has become economically efficient thanks to the price reduction and the increased capabilities of drones. The drones in the swarm need to cooperatively explore an unknown area, in order to identify and monitor interesting targets, while minimizing their movements. In this work, we propose a distributed Reinforcement Learning (RL) approach that scales to larger swarms without modifications. The proposed framework can easily deal with non-uniform distributions of targets, drawing from past experience to improve its performance. In particular, our experiments show that when agents are trained for a specific scenario, they can adapt to a new one with a minimal amount of additional training. We show that our RL approach achieves favorable performance compared to a computationally intensive look-ahead heuristic.