Miracle-dz/UniFAR-FTUs huggingface dataset:
Fuel-Cell Electric Vehicles: Plotting a Scientific and Technological Knowledge Map

The fuel-cell electric vehicle (FCEV) has been defined as a promising way to avoid road transport greenhouse emissions, but nowadays, they are not commercially available. However, few studies have attempted to monitor the global scientific research and technological profile of FCEVs. For this reason, scientific research and technological development in the field of FCEV from 1999 to 2019 have been researched using bibliometric and patent data analysis, including network analysis. Based on reports, the current status indicates that FCEV research topics have reached maturity. In addition, the analysis reveals other important findings: (1) The USA is the most productive in science and patent jurisdiction; (2) both Chinese universities and their authors are the most productive in science; however, technological development is led by Japanese car manufacturers; (3) in scientific research, collaboration is located within the tri-polar world (North America–Europe–Asia-Pacific); nonetheless, technological development is isolated to collaborations between companies of the same automotive group; (4) science is currently directing its efforts towards hydrogen production and storage, energy management systems related to battery and hydrogen energy, Life Cycle Assessment, and greenhouse gas (GHG) emissions. The technological development focuses on technologies related to electrically propelled vehicles; (5) the International Journal of Hydrogen Energy and SAE Technical Papers are the two most important sources of knowledge diffusion. This study concludes by outlining the knowledge map and directions for further research.
N-Way Planar Balanced-to-Balanced Series Feeding Network for Balanced Frequency-Scanning Phased Array

In this article, a novel series feeding network as an N-way balanced-to-balanced structure for balanced frequency-scanning phased array is proposed. Design requirements of the N-way balanced-to-balanced series feeding (BBSF) network are extracted and mixed-mode S-parameters are expressed by using matrix transformation. Designing the BBSF network without using baluns at input and output paths of the network results in the compact and low-loss feeding network, while maintaining the common-mode suppression feature. Furthermore, to have a planar BBSF network, microstrip crossovers are utilized to avoid the use of multilayer PCB design, resulting in the elegant transfer of intersecting RF signals. To validate the proposed structure, a three-way BBSF network is fabricated which shows acceptable mixed-mode measurement results. Also, to demonstrate the performance of the proposed structure, a balanced frequency-scanning phased array is designed employing the proposed feeding network. The measurement results of the fabricated array show that the differential return loss and the differential mode to common mode conversions are better than 20 and 30 dB at 5.85 GHz, respectively. Meanwhile, the fabricated array shows a wide-range beam-scanning capability over its frequency band.
Minority Disk Failure Prediction Based on Transfer Learning in Large Data Centers of Heterogeneous Disk Systems

The storage system in large scale data centers is typically built upon thousands or even millions of disks, where disk failures constantly happen. A disk failure could lead to serious data loss and thus system unavailability or even catastrophic consequences if the lost data cannot be recovered. While replication and erasure coding techniques have been widely deployed to guarantee storage availability and reliability, disk failure prediction is gaining popularity as it has the potential to prevent disk failures from occurring in the first place. Recent trends have turned toward applying machine learning approaches based on disk SMART attributes for disk failure predictions. However, traditional machine learning (ML) approaches require a large set of training data in order to deliver good predictive performance. In large-scale storage systems, new disks enter gradually to augment the storage capacity or to replace failed disks, leading storage systems to consist of small amounts of new disks from different vendors and/or different models from the same vendor as time goes on. We refer to this relatively small amount of disks as minority disks. Due to the lack of sufficient training data, traditional ML approaches fail to deliver satisfactory predictive performance in evolving storage systems which consist of heterogeneous minority disks. To address this challenge and improve the predictive performance for minority disks in large data centers, we propose a minority disk failure prediction model named TLDFP based on a transfer learning approach. Our evaluation results in two realistic datasets have demonstrated that TLDFP can deliver much more precise results and lower additional maintenance cost, compared to four popular prediction models based on traditional ML algorithms and two state-of-the-art transfer learning methods.
Efecto de introducir Arachis pintoi sobre variables del suelo de pasturas de grama nativa del trópico húmedo mexicano

Native grass pastures account for 25 to 75 % of grazing lands in the Mexican humid tropics used for cow-calf and dual-purpose systems. These pastures have low productivity due to low soil fertility. Arachis pintoi is a persistent legume that effectively fixes N2, and is adapted to hot, humid tropical climate conditions as well as to low fertility, acid soils. Introduction of A. pintoi into native grass pastures was proposed as the best way to improve sustainable cattle productivity. Three and a half years after its introduction, soil under the native grass pasture + legume (NG+Ap) treatment showed slightly higher C levels than that under the native grass only (NG) treatment. Initial C value (1998) to 0.2 m depth was 24.7 t/ha, with a mean increase up to the year 2000 of 3.7 t/ha/year for the NG and 4.8 t/ha/year for the NG+Ap. The NG+Ap treatment added 60 kg/ha/year of N to the soil. Bulk density was unaffected by the treatments, with a mean of 1.21 g/cm3. It is concluded that C and N soil contents increase from introduction of A. pintoi may be an environmental bonus for pasture agroecosystems in the Mexican humid tropics.
Bruchids from Senna multijuga (Rich) I. & B. (Caesalpiniaceae) in Brazil with descriptions of two new species.

Samples of mature fruits of Senna multijuga (Rich) I. & B. (Caesalpinaceae), an ornamental tree, were collected in Curitiba, Parani, Brazil. The bruchid species that emerged were: Sennius bondari (Pic), Sennius puncticollis (Ff.hraeus) new combination, Sennius crudelis, new species and Sennius nappi, new species, here described and illustrated. A key to all bruchid species found developing on seeds of Senna multijuga is also provided. Ornamental plants are used in streets and public gardens to enhance the aesthetic value of these areas. Different bruchid species were found developing in such plants in Curitiba, Parana, Brazil. Although, some of these species are known to science, a few of them remain undescribed. Senna multijuga (Rich) I. & B. (Caesalpinaceae) is one of the most handsome of Neotropical sennas extensively planted in southeastern Brazil. Although Lorenzi (1992) has said this species is native in Brazil, Irwin and Barneby (1982) stated that the origin of much of the material planted in the American tropics as ornamental trees is uncertain. The only bruchid reported to feed in seeds of Senna multijuga was Acanthoscelides sennicola Johnson from Venezuela. This species also feeds in seeds of Senna saeri (Pittier) I. & B. (Johnson 1990, Johnson and Siemens 1995). For the present study, one sample of mature pods of this tree was collected in July, 1992, one in June, 1995, and others from four different specimens, from June until August, 1996, biweekly. In the laboratory samples were kept in thick-mesh bags and afterwards in inflated plastic bags, following the methodology of Janzen (1980). Three times a week these samples were observed and adult bruchids collected. Four different bruchid species were obtained from Senna multijuga pods: Sennius bondari (Pic), Sennius puncticollis (Fahraeus), and two undescribed species of Sennius Bridwell. We present here all the bibliography related to these species, original descriptions, justification for a new combination and a key to separate the bruchid species collected from Senna multijuga.
Re‐evaluation of acetic acid, lactic acid, citric acid, tartaric acid, mono‐ and diacetyltartaric acid, mixed acetic and tartaric acid esters of mono‐ and diglycerides of fatty acids (E 472a‐f) as food additives

Abstract The Panel on Food Additives and Flavourings (FAF) provided a scientific opinion re‐evaluating the safety of acetic acid, lactic acid, citric acid, tartaric acid, mono‐ and diacetyltartaric acids, mixed acetic and tartaric acid esters of mono‐ and diglycerides of fatty acids (E 472a‐f) as food additives. All substances had been previously evaluated by the Scientific Committee for Food (SCF) and by the Joint FAO/WHO Expert Committee on Food Additives (JECFA). Hydrolysis of E472a,b,c,e was demonstrated in various experimental systems, although the available data on absorption, distribution, metabolism, excretion (ADME) were limited. The Panel assumed that E472a‐f are extensively hydrolysed in the GI tract and/or (pre‐)systemically after absorption into their individual hydrolysis products which are all normal dietary constituents and are metabolised or excreted intact. No adverse effects relevant for humans have been identified from the toxicological database available for E472a‐f. The Panel considered that there is no need for a numerical acceptable daily intake (ADI) for E 472a,b,c. The Panel also considered that only l(+)‐tartaric acid has to be used in the manufacturing process of E472d,e,f. The Panel established ADIs for E 472d,e,f based on the group ADI of 240 mg/kg body weight (bw) per day, expressed as tartaric acid, for l(+)‐tartaric acid‐tartrates (E334‐337, 354) and considering the total amount of l(+)‐tartaric acid in each food additive. Exposure estimates were calculated for all food additives individually, except for E 472e and f, using maximum level, refined exposure and food supplements consumers only scenarios. Considering the exposure estimates, there is no safety concern at their reported uses and use levels. In addition, exposure to tartaric acid released from the use of E 472d,e,f was calculated. The Panel also proposed a number of recommendations.
SISALv2: a comprehensive speleothem isotope database with multiple age–depth models

Abstract. Characterizing the temporal uncertainty in palaeoclimate records is crucial for analysing past climate change, correlating climate events between records, assessing climate periodicities, identifying potential triggers and evaluating climate model simulations. The first global compilation of speleothem isotope records by the SISAL (Speleothem Isotope Synthesis and Analysis) working group showed that age model uncertainties are not systematically reported in the published literature, and these are only available for a limited number of records (ca. 15 %, n=107/691). To improve the usefulness of the SISAL database, we have (i) improved the database's spatio-temporal coverage and (ii) created new chronologies using seven different approaches for age–depth modelling. We have applied these alternative chronologies to the records from the first version of the SISAL database (SISALv1) and to new records compiled since the release of SISALv1. This paper documents the necessary changes in the structure of the SISAL database to accommodate the inclusion of the new age models and their uncertainties as well as the expansion of the database to include new records and the quality-control measures applied. This paper also documents the age–depth model approaches used to calculate the new chronologies. The updated version of the SISAL database (SISALv2) contains isotopic data from 691 speleothem records from 294 cave sites and new age–depth models, including age–depth temporal uncertainties for 512 speleothems. SISALv2 is available at https://doi.org/10.17864/1947.256 (Comas-Bru et al., 2020a).
Psychometrics at Work: How to Ensure Test Results You Can Trust

Psychometric testing is considered as the intersection of the fields of psychology and business, with potential benefits to both employees and employers. Recommendations for maximising contributions of occupational testing are presented. These are evaluated across five phases of the assessment process. The first is choosing a test, bearing in mind both psychometric and practical qualities of measures. Next, ways to increase positive responses to testing are discussed. The process of administration is examined, with suggestions for improved accuracy. Recommendations for score interpretation are provided, taking measurement error into account. Finally, implications for communicating test results are drawn. It is explained that these facets of psychometric testing are key in ensuring accurate, meaningful and trustworthy workplace measurement.
Type-II Fuzzy Neural Networks for Image Stabilization of the Airborne Camera

The vibration rule of the airborne camera was studied to solve the image vibration in aerial photography of the Micro Aircraft Vehicle. A method based on the ability of function approximation of type 2 fuzzy neural networks with self-organizing recurrent intervals (SRIT2FNN) to simulate the vibration rule of airborne camera in the MAV and predict the vibration displacement vectors during image stabilization was proposed. The SRIT2FNN has no initial rules, which are generated from the simultaneous on-line parameter and structure learning. The results show that SRIT2FNN control system is more stable and the higher precision, and good real-time performance than combined BP neural networks.
Development of Fish Separator Conveyor based on Fish Identification System

Indonesia as the largest archipelago and maritime country in the world has a very large marine resources. Fish is one of the marine wealthties (marine biota), which have large numbers in Indonesia. Fishermen is an important role in the process of fishing, however fish caught by fishermen are often mixed with other types of fish. Currently, the process of fist separation is done manually, which takes longer time and many error occur due to fatigue. In this work the conveyer separator based on the fish identification system is developed. The fish conveyer separator is designed and developed. The fish identification system is based on Fast Fourier Transform (FTT) technique and Artificial Neural Network (ANN). The system is working properly, since it resulting the training and testing accuracy of 80% and 66%, respectively.
Iron Metabolism in the Tubercle Bacillus and Other Mycobacteria

The mechanism of iron acquisition by mycobacteria, and by the tubercle bacillus in particular, is one of the central issues concerning the pathogenicity of this group of bacteria. This chapter describes the key components of the iron acquisition system, how they interlink in the sequestration of iron from the host sources of iron, and how the iron is then made available to the bacterial cell for its own purposes. Mycobactins have been isolated from M. tuberculosis and most other mycobacteria, both pathogens and nonpathogens alike. The only exceptions would appear to be some (but not necessarily all) strains of M. paratuberculosis, M. vaccae, M. chelonae, M. parafortuium, and M. thermoresistible. Two different types of ferritins involved in iron storage have been identified, the heme-containing bacterioferritins and the heme-free ferritins. In contrast to the genes of bacterial iron acquisition systems, which are upregulated under low-iron conditions, the genes encoding iron storage proteins appear to be upregulated under high-iron conditions. Interestingly, the first mycobacterial bacterioferritins were identified during the characterization of immunodominant and highly expressed mycobacterial proteins in the early 1990s. When a person becomes infected with the tubercle bacillus or, indeed, other bacteria, one of the earliest defense mechanisms put into operation by the infected host is the withholding of iron from the invading bacteria by the transfer of all free iron into transferrin or lactoferrin, both of which deliberately have spare iron-binding capacity for this very purpose. This means that iron is automatically in limiting supply to the bacteria also.
Offline mobile diagnosis system for citrus pests and diseases using deep compression neural network

This study presents an offline mobile diagnosis system for citrus pests and diseases by compression convolutional neural network. Recently, with the growth of labelled data, the deep neural network incites the revolutionary change with a quantum leap in various fields. Benefiting from the backpropagation method, the proper network structure can automatically extract high-level representations and find corresponding labels. The authors made use of the advantages of the deep neural network to design an android application, which can be installed in any stand-alone devices to instantaneously identify the citrus pests and diseases. The proposed diagnosis system has three characteristics: low cost, low latency and high accuracy. These characteristics contribute to make the professional offline prediction for avoiding further economic loss caused by disease spreading. In order to validate the proposed system, the authors conducted thorough evaluations on two data sets, `citrus pests and diseases', CIFAR, which show the superiority of the proposed approach in terms of the accuracy and the number of model parameters.
The origins of information processing preferences in politics: Examining parental influence

Cognitive motivations (e.g., need for cognition and need to evaluate) and decision strategies (e.g., rational choice vs. heuristic-based) importantly shape political understanding, evaluations, and vote choice. Despite the importance of these cognitive factors, few studies have examined their origins. Adopting an exploratory framework with a primary focus on parental influence, we uniquely address this research gap by identifying potential pathways through which parents can affect this development. Using a convenience sample of college students who participated in a 10-week panel study with their parents, we reveal that, unlike many other political characteristics, there is little parent-child similarity in cognitive motivations and decision strategies. We, however, find some similarity in the information search behaviors parents and children exhibit during the mock election campaign. The findings highlight the need to further investigate not only additional parenting behaviors, but also the socializing role of the information environment itself.
Generative modeling for renal microanatomy

Generative adversarial networks (GANs) have received immense attention in the field of machine learning for their potential to learn high-dimensional and real data distribution. These methods do not rely on any assumptions about the data distribution of the input sample and can generate real-like samples from latent vector space based on unsupervised learning. In the medical field, particularly, in digital pathology expert annotation and availability of a large set of training data is costly and the study of manifestations of various diseases is based on visual examination of stained slides. In clinical practice, various staining information is required to improve the pathological diagnosis process. But when the sampled tissue to be examined is limited, the final diagnosis made by the pathologist is based on limited stain styles. These limitations can be overcome by studying the usability and reliability of generative models in the field of digital pathology. To understand the usability of the generative models, we synthesize in an unsupervised manner, high resolution renal microanatomical structures like renal glomerulus in thin tissue histology images using state-of-art architectures like Deep Convolutional Generative Adversarial Network (DCGAN) and Enhanced Super-Resolution Generative Adversarial Network (ESRGAN). Successful generation of such structures will lead to obtaining a large set of labeled data for further developing supervised algorithms for disease classification and understanding progression. Our study suggests while GAN is able to attain formalin fixed and paraffin embedded tissue image quality, GAN requires further prior knowledge as input to model intrinsic micro-anatomical details, such as capillary wall, urinary pole, nuclei placement, suggesting developing semi-supervised architectures by using these above details as prior information. Also, the generative models can be used to create an artificial effect of staining without physically tampering the histopathological slide. To demonstrate this, we use a CycleGAN network to transform Hematoxylin and eosin (H&E) stain to Periodic acid-Schiff (PAS) stain and Jones methenamine silver (JMS) stain to PAS stain. In this way GAN can be employed to translate different renal pathology stain styles when the relevant staining information is not available in the clinical settings.
Rapid waxing and waning of Beringian ice sheet reconcile glacial climate records from around North Pacific

Abstract. Throughout the Pleistocene the Earth has experienced pronounced glacial-interglacial cycles, which have been debated for decades. One concept widely held is that during most glacials only the Laurentide-Eurasian ice sheets across North America and Northwest Eurasia became expansive, while Northeast Siberia-Beringia remained ice-sheet-free. However, the recognition of glacial landforms and deposits on Northeast Siberia-Beringia and off the Siberian continental shelf is beginning to call into question this paradigm. Here, we combine climate and ice sheet modelling with well-dated paleoclimate records from the mid-to-high latitude North Pacific to demonstrate the episodic occurrences of an ice sheet across Northeast Siberia-Beringia. Our simulations first show that the paleoclimate records are irreconcilable with the established paradigm of Laurentide-Eurasia-only ice sheets, and then reveal that a Beringian ice sheet over Northeast Siberia-Beringia causes feedbacks between atmosphere and ocean, the result of which better explains these climate records from around the North Pacific during the past four glacial-interglacial cycles. Our simulations propose an alternative scenario for NH ice sheet evolution, which involves the rapid waxing and waning of the Beringian ice sheet alongside the growth of the Laurentide-Eurasian ice sheets. The new scenario settles the long-standing discrepancies between the direct glacial evidence and the climate evolution from around the mid-to-high latitude North Pacific. It depicts a high complexity in glacial climates and has important implications for our understanding of the dispersal of prehistoric humans through Beringia into North America.