Miracle-dz/UniFAR-FTUs huggingface dataset:
A Modular Magnetic Linked Converter Station for Offshore Power Transfer Through HVDC Link

This article proposes a modular magnetic linked converter station (CS) for offshore power transfer through a high voltage dc (HVDC) link. The proposed converter station can collect medium voltage ac and dc power simultaneously and transform the power to HVDC suitable for offshore power transmission. The proposed CS adopts multiple half-bridge (HB) converters to form a front-end interface that can collect both medium voltage ac and dc power. Moreover, several high-frequency magnetic linked multiport converters (MLMCs) are employed in the CS to isolate and step up the voltage. The MLMC is operated at a unity step-up voltage ratio which matches the turn ratio in multiple windings shared by a common magnetic link. This condition facilitates minimum current stress on the switches and inherent soft-switching operation. In the proposed CS, the hard switching operation of the front-end HB converters does not affect the switching condition of the MLMCs. Furthermore, the application of the switched capacitor-based HVDC converter enables discretized dc-link capacitor arrangement to limit high inrush current under dc fault. A controller structure is also proposed for the CS to balance the electrical parameters. The results from a simulation study of the proposed CS, both in steady-state and dynamic conditions, show that the proposed CS performs satisfactorily with the proposed controller, which is validated by the laboratory scale experiment.
A thelytokous predatory mite is more cannibalistic towards distant kin

Abstract Kin recognition has been widely observed in various taxa. Cannibalism avoidance may be a strong driver for the evolution of kin recognition, as it may avoid a reduction in inclusive fitness. Kin recognition has recently been observed in a generalist phytoseiid, Amblyseius herbicolus (Acari: Phytoseiidae). This study experimentally examined the degree of relatedness needed between prey larvae and cannibal adults of A. herbicolus for the occurrence of kin discrimination. The adults were individually placed in enclosed arenas with two prey, a daughter and a more distant related larva, to observe their cannibalizing choice. The adults of A. herbicolus did not discriminate between close relatives (daughter versus niece) but preferably cannibalized more distant kin (i.e., first and second cousins once removed). Phenotype matching and familiarization seem prominent as recognition mechanisms used by A. herbicolus adults. The effect of learning on kin recognition through prior contact in A. herbicolus requires further investigation. Studies on other adaptive functions of kin recognition of A. herbicolus, such as cooperation and parental care, may provide meaningful insights.
Multi-Stage Training Optimization for Pilot Compression and Channel Estimation in Massive MIMO Systems Under Quasi-Sparse Channel Environment

The huge pilot overhead required for channel estimation is one of the key issues for massive multiple-input multiple-output (MIMO) systems. Existing compressed sensing and deep learning methods generally implement pilot compression under the assumption of the huge number of antennas and strict channel sparsity, while the channel estimation performance decreases sharply under quasi-sparse channel environment. Motivated by the powerful learning ability of deep learning for extracting the major characteristics of the target, we propose approximate message passing (AMP) algorithm-based multi-stage training optimization architecture to solve the above problem, where the whole system is considered as a deep neural network (DNN). In the first stage, the optimized sensing matrix of the AMP algorithm is learned by training to match the quasi-sparse channel. In the second stage, we optimize the linear coefficients and nonlinear shrinkage parameters of AMP to further improve the performance. In the third stage, all parameters are jointly optimized by training to make the whole system optimal. Numerical simulation results show that the proposed architecture can achieve high precision channel estimation under the premise of reducing pilot overhead effectively.
Developing Big Data Analytics (BDA) Utilization Model in Indonesia

This paper intends to develop a model of Big Data Analytics (BDA) utilization in Indonesian context. This is important due to the lack of related research on what factors influencing company to adopt BDA as their strategic and somehow secret weapon to win in nowadays intensified competition among companies in industries. By the model, this paper aims to contribute additional knowledge on what factors influence company to adopt this emerging technology as part of their strategic action in winning the market. Thus, intended questionnaires are distributed to about 206 companies. However, only 124 responses can be gathered and proceed using Part-Least Square (PLS) Structural Equation Modeling (SEM) and TOE Framework by adopting SmartPLS 3.0. By processing those data, two significant insights can be generated. First, BDA adoption in Indonesia is mainly encouraged degree of technology savviness, organizational readiness, and better anticipating environmental changes. Second, Organization readiness is also influenced by technology savviness and environmental changes anticipation. the company needs to master its technology which in Indonesia, compatibility and relative advantage could be significant issue. Thus, for those who want to adopt this emerging technology need to develop technology savviness and organization readiness while anticipate environmental changes.
A 1.42-mm2 0.45–0.49 THz Monostatic FMCW Radar Transceiver in 90-nm SiGe BiCMOS

Terahertz frequency-modulated continuous-wave (FMCW) radars operating close to and beyond <inline-formula><tex-math notation="LaTeX">$f_{\max}$</tex-math></inline-formula> often use gain-enhancing lenses to improve the signal-to-noise ratio. A compact single-chip transceiver benefits a lot from the alignment of the lens to the single on-chip antenna in a monostatic system. The typically required coupler for monostatic operation adds an insertion loss. The proposed multiply-by-24 frequency multiplier-based FMCW radar transceiver removes the coupler and integrates both the final 0.48-THz doubler and subharmonic downconverter into a single common collector push–push doubler. The common emitter is the only port at 0.48 THz in this monostatic system, feeding the top-metal on-chip patch antenna using a direct via stack. The 1.42-mm<sup>2</sup> monostatic FMCW radar transceiver, manufactured in a 90-nm SiGe bipolar CMOS (BiCMOS) technology with an <inline-formula><tex-math notation="LaTeX">$f_\text{T}$</tex-math></inline-formula>/<inline-formula><tex-math notation="LaTeX">$f_{\max}$</tex-math></inline-formula> of 300/480 GHz consumes 85 mA when connected to a 3.3-V supply. At 0.48 THz, the output power is <inline-formula><tex-math notation="LaTeX">$-$</tex-math></inline-formula>12 dBm and the single-sideband noise figure is measured as 36.3 dB. FMCW radar measurements with operating bandwidths of up to 55 GHz, corresponding to a theoretical range resolution of 2.73 mm are performed using an on-board frequency source of a credit card sized demonstrator.
A Bayes‐Based Approach Against Sample Imbalance to Improving the Potential Forecasts of Gale

Sample imbalance prevents the Bayesian model from making effective potential forecasts of gale. An approach is thus proposed to modify the Bayesian model to deal with sample imbalance and verified using years (2015–2019) of reanalysis and radar data. The approach reduces sample imbalance by the resampling based on the value ranges of environmental parameters and the application of multi‐layer conditional probabilities. The samples that are insensitive to gale forecasts are excluded according to the value ranges of environmental parameters for gale occurrence. This resampling greatly improves gale occurrence hits of and suppresses its false alarms, leading to significant improvement in gale forecasting skill. On the basis of the resampling, the application of the multi‐layer conditional probabilities that forecast gale occurrence balances the samples to an equivalent magnitude. Consequently, the false alarms are further suppressed although some hits are reduced, resulting in a higher forecasting skill of gale.
Maternal Obesity: An Obstetric Risk

Objective: To analyze the obstetric risks and to evaluate the effects of maternal obesity during pregnancy and postpartum period. Method: This is a retrospective study of pregnant women with a BMI of more the 30 conducted at Bahrain Defence Force Hospital, West Riffa, Bahrain, from September 2019 to August 2020. Data includes demographic characteristics, and course of pregnancy from gestational age 24 weeks, through intrapartum to the postpartum period. Adverse maternal effects and delivery complications were the primary study outcomes. The BMI was calculated at the time of the booking visit. Comparative analysis was done to calculate the odds of each outcome taking a non-obese group (BMI less than 30) as a reference. Results: The total number of pregnant women studied was 2972, out of which 1657 had BMI ≥30. In our study, women with high BMI were older (p<0.0001). High BMI was associated with high parity and higher miscarriage history. High BMI increased the risk of developing hypertension (OR 2.5; 95%CI 1.1-5.3). This analysis also found that high BMI was associated with increased risk of antepartum hemorrhage (OR 2.4; 95%CI 1-5.4), postpartum complications (OR1.6; 95%CI 1.1-2.2), and a hospital stay of more than five days (OR 1.6; 95%CI 1.3-2). High BMI patients were less likely to have Intrauterine growth restriction (OR 0.6; 95%CI 0.3-0.9). High BMI patients did not have an increased risk of gestational diabetes mellitus, induction of labor, or caesarean birth. Conclusion: Higher BMI pregnant women are associated with higher incidences of hypertension. The high BMI group also had a significant relationship with antepartum hemorrhage and postpartum length of stay.
Comparison of Primers for the Detection of Phytophthora (and Other Oomycetes) from Environmental Samples

Many oomycetes are important plant pathogens that cause devastating diseases in agricultural fields, orchards, urban areas, and natural ecosystems. Limitations and difficulties associated with isolating these pathogens have led to a strong uptake of DNA metabarcoding and mass parallel sequencing. At least 21 primer combinations have been designed to amplify oomycetes, or more specifically, Phytophthora species, from environmental samples. We used the Illumina sequencing platform to compare 13 primer combinations on mock communities and environmental samples. The primer combinations tested varied significantly in their ability to amplify Phytophthora species in a mock community and from environmental samples; this was due to either low sensitivity (unable to detect species present in low concentrations) or a lack of specificity (an inability to amplify some species even if they were present in high concentrations). Primers designed for oomycetes underestimated the Phytophthora community compared to Phytophthora-specific primers. We recommend using technical replicates, primer combinations, internal controls, and a phylogenetic approach for assigning a species identity to OTUs or ASVs. Particular care must be taken if sampling substrates where hybrid species could be expected. Overall, the choice of primers should depend upon the hypothesis being tested.
ROBUST PHASE STABILITY ANALYSIS USING INTERVAL METHODS

Conventional equation solving and optimization techniques for solving the phase stability problem may fail to converge or may converge to an incorrect result. A technique for solving the problem with mathematical certainty is needed. One approach to providing such assurance can be found in the use of interval methods. An interval Newton/generalized bisection technique is applied here to solve the phase stability problem. Results for two models of liquid-phase systems, using several different feed compositions, indicate that the technique used is reliable and very efficient.
Predator movements in relation to habitat features reveal vulnerability of duck nests to predation

Abstract Nest predation is the main cause of nest failure for ducks. Understanding how habitat features influence predator movements may facilitate management of upland and wetland breeding habitats that reduces predator encounter rates with duck nests and increases nest survival rates. For 1618 duck nests, nest survival increased with distance to phragmites (Phragmites australis), shrubs, telephone poles, human structures, and canals, but not for four other habitat features. Using GPS collars, we tracked 25 raccoons (Procyon lotor) and 16 striped skunks (Mephitis mephitis) over 4 years during waterfowl breeding and found marked differences in how these predators were located relative to specific habitat features; moreover, the probability of duck nests being encountered by predators differed by species. Specifically, proximity to canals, wetlands, trees, levees/roads, human structures, shrubs, and telephone poles increased the likelihood of a nest being encountered by collared raccoons. For collared skunks, nests were more likely to be encountered if they were closer to canals, trees, and shrubs, and farther from wetlands and human structures. Most predator encounters with duck nests were attributable to a few individuals; 29.2% of raccoons and 38.5% of skunks were responsible for 95.6% of total nest encounters. During the central span of duck nesting (April 17–June 14: 58 nights), these seven raccoons and five skunks encountered >1 nest on 50.8 ± 29.2% (mean ± SD) and 41.5 ± 28.3% of nights, respectively, and of those nights individual raccoons and skunks averaged 2.60 ± 1.28 and 2.50 ± 1.09 nest encounters/night, respectively. For collared predators that encountered >1 nest, a higher proportion of nests encountered by skunks had evidence of predation (51.9 ± 26.6%) compared to nests encountered by raccoons (22.3 ± 17.1%). Because duck eggs were most likely consumed as raccoons and skunks opportunistically discovered nests, managing the habitat features those predators most strongly associated with could potentially reduce rates of egg predation.
A Rule-Based Decision Support Method Combining Variable Precision Rough Set and Stochastic Multi-Objective Acceptability Analysis for Multi-Attribute Decision-Making

In an open environment, the demands of users are diverse and dynamic because users can participate in product design from beginning to end. Owing to this, the disorderly and unplanned participation of users will greatly increase the complexity of multi-attribute decision-making (MADM) in the product design process. In order to ensure the smooth development of the open design process, the decision support model and method need to repeatedly provide decision makers (DMs) with necessary decision support information in a relatively short period of time, which can realize the evaluation of the scheme and improve the utilization efficiency of community resources. However, the process of eliciting preference information is complex, exhausting, inefficient, and time-consuming in existing methods, which will result in a poor decision-making. With the purpose of optimizing the eliciting process in MADM, a rule-based decision support method is proposed in this paper, where the process of eliciting preference information and decision-making are synchronized and guided by pre-extracted decision rules. The rules are deduced from comparison relations on attributes and their outcomes through the combination of variable precision rough set approach (VPRS) and stochastic multi-objective acceptability analysis (SMAA). With the concept of attribute reduction and approximation accuracy in rough set theory, the extracted rules could eliminate redundant attributes and assign the relative priority of preference information. Based on the extracted rules, the multi-attribute decision-making process could be carried out step by step in an orderly manner. In each step, DMs only need to provide partial preference information by non-quantitative statements according to extracted rules. Once the decision result is reliable enough, the eliciting and decision-making process can be terminated promptly. In order to validate the proposed approach, experiments of decision rule extraction are implemented, and the results show that the proposed approach is effective both in the weak rule extraction and the strong rule extraction.
Smart Early Screening System for COVID-19 Spreading Prevention

Since the end of 2019, a respiratory disease called COVID-19 caused by SARS- COV2 has been spread around the world. The disease has similar symptoms with influenza. The common symptoms are cough, fever and fatigue. The human-to human transmission occurs primarily through droplets spread by coughing or sneezing from infected people directly and indirectly. In this paper a system based on embedded devices that can be used to help prevent the spread of COVID-19 between humans through face mask detection and a contactless thermal sensor is proposed. CNN based deep learning for the facemask detection and IR thermal sensor for non-contact human temperature measurement are used. The system is implemented locally on the Raspberry Pi platform. The training result shows the accuracy of the face mask detector is higher than 90% and stable after epoch 2. The thermal sensor shows the stable input with 0.25 deviation.
Moderating Role of Coping Style on the Relationship between Stress and Psychological Well-Being in Hong Kong Nursing Students

Aims and objectives: To examine whether coping styles moderate the influence of stressors and psychological well-being in Hong Kong nursing students. Background: Stress could contribute to psychological distress in nursing students. Coping strategies are essential to mitigate psychological distress. So far, the moderating effects of coping between stressors and psychological well-being has not been thoroughly investigated. Design: This is a cross-sectional study conducted at four higher education institutions in Hong Kong. Methods: We recruited a convenience sample of 293 nursing students in February 2018. The Stressors in Nursing Students Scale-Chinese version (SINS-CN), Brief Cope Inventory-Chinese version (Brief COPE-C), and the Chinese version of the General Health Questionnaire-12 (C-GHQ-12) were used to measure the stressors, coping styles, and psychological well-being, respectively. Three multiple hierarchical linear regression models were used to identify the associations between the variables. Results: The stressors related to clinical learning, confidence, and personal problems were significant in explaining the psychological well-being. The coping strategies also predicted the psychological well-being and explained 44.5% of the variance. The coping strategy—accommodation—moderated the relationship between personal problems and psychological well-being. Conclusion: Problem-solving and accommodation types of coping were adaptive to stress and effective in promoting psychological well-being. However, using accommodation to cope with stressors related to personal problems will exacerbate the negative effects of the personal problems on the psychological well-being. Relevance to clinical practice: This study reveals the relationships between stressors, coping, and psychological well-being. Nurse educators must be aware of nursing student coping styles so they may devise strategies to promote effective coping to reduce the psychological distress among nursing students.
Immune Responses to Gene Editing by Viral and Non-Viral Delivery Vectors Used in Retinal Gene Therapy

Inherited retinal diseases (IRDs) are a leading cause of blindness in industrialized countries, and gene therapy is quickly becoming a viable option to treat this group of diseases. Gene replacement using a viral vector has been successfully applied and advanced to commercial use for a rare group of diseases. This, and the advances in gene editing, are paving the way for the emergence of a new generation of therapies that use CRISPR–Cas9 to edit mutated genes in situ. These CRISPR-based agents can be delivered to the retina as transgenes in a viral vector, unpackaged transgenes or as proteins or messenger RNA using non-viral vectors. Although the eye is considered to be an immune-privileged organ, studies in animals, as well as evidence from clinics, have concluded that ocular gene therapies elicit an immune response that can under certain circumstances result in inflammation. In this review, we evaluate studies that have reported on pre-existing immunity, and discuss both innate and adaptive immune responses with a specific focus on immune responses to gene editing, both with non-viral and viral delivery in the ocular space. Lastly, we discuss approaches to prevent and manage the immune responses to ensure safe and efficient gene editing in the retina.
Birth prevalence of omphalocele and gastroschisis in Sub-Saharan Africa: A systematic review and meta-analysis

Objective: To systematically summarize the burden of gastroschisis and omphalocele in Sub-Saharan Africa. Methods: Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, systematically reviewed and meta-analyzed literatures from Medline (PubMed), Cochrane Library, HINARI, and Google Scholar that investigated at the prevalence of major congenital abdominal wall malformation. The pooled prevalence of major abdominal wall defects was estimated using a weighted inverse variance random-effects model. The Q statistic and the I2 statistics were used to examine for heterogeneity among the included studies. The funnel plot and Egger’s regression test were used to check for publication bias. Results: A total of 1951 studies were identified; 897 from PubMed, 26 from Cochrane Library, 960 from Google Scholar, and 68 from other sources. Fourteen articles that met the eligibility criteria were selected for this meta-analysis with 242,462 total enrolled participants and 4693 births with congenital anomaly. The pooled prevalence of ompahalocele among congenital defect patients in Sub-Saharan Africa was found to be 4.47% (95% confidence interval: 3.04–5.90; I2 = 88.3%; p < 0.001). The pooled prevalence of omphalocele among births with congenital defect was found to be 4.04% (95% confidence interval: 2.62–5.46) in cross-sectional studies and 4.43% (95% confidence interval: 306–5.81) in cohort studies. The average prevalence of omphalocele among births with congenital defect was found to be 8% (95% confidence interval: 5.53–10.47) in Uganda and 6.65% (95% confidence interval: 4.18–9.13) in Nigeria. The pooled prevalence of gastroschisis among congenital birth defect in Sub-Saharan Africa was found to be 3.22% (95% confidence interval: 1.83–4.61; I2 = 33.1%; p = 0.175). Conclusion: Based on this review, the pooled prevalence of omphalocele and gastroschisis in sub-Saharan Africa are high. Therefore, a perinatal screening program for congenital anomalies should be implemented. In addition, early referral of suspected cases of congenital anomalies is required for better management until advanced diagnostic centers are established in various locations of Sub-Saharan Africa.