Miracle-dz/UniFAR-FTUs huggingface dataset:
Behaviour and uptake of engineered gold nano particles in aquatic systems

Nanotechnology is a rapidly growing industry of global economic importance. However, there is concern that the unique properties of engineered nanoparticles (ENPs) which can make them useful to society could mean that they pose a risk to the natural environment. There are still many uncertainties around the behaviour of ENPs in aquatic systems, their capacity to be taken up by aquatic organisms, and their potential toxic effects. This study therefore used four different surface functionalised gold (Au) nanoparticles as exemplars and explored their behaviour in various aquatic systems and their uptake into aquatic organisms. Studies into the behaviour of the study ENPs in standardized ecotoxicity test media showed that the particles exhibit very different aggregation behaviour depending on the test media type, the chemical composition of the test media and surface capping of the nanoparticles. Based on the results of the aggregation studies in a range of natural waters, a series of methods to predict size of Au particles in different water chemistries were developed. Results showed that there would likely be big differences in the aggregation of the different Au nanoparticle types in UK water types which implies that aggregation of ENPs will vary widely across surface waters. The uptake of the four Au nanoparticles into the aquatic invertebrate, Gammarous pulex, did not show obvious relationship between the aggregation state in a treatment and uptake suggesting that the widely accepted assumption that ENP uptake is related to particle size does not hold for the range of aggregation states studied. The results of this thesis showed that the degree of aggregation of ENPs and uptake into aquatic organisms would vary depending on the surface functionalisation of the ENPs and water chemistry. The results imply that aggregation of ENPs will vary widely across surface waters which make assessment of risks a challenge. Additionally, the uptake data indicate that factors other than particle size determine uptake of ENPs into organisms. Therefore, it may be necessary to develop new paradigms and models for risk assessment of ENPs.
Effect of planting geometry and intercropping on growth attributes, leaf yield, quality of mulberry (Morus alba) and its economics under irrigated, Gangetic alluvial soil conditions

A field experiment was conducted under irrigated condition to study the effect of planting geometry and intercropping on growth characters, leaf yield and quality in newly evolved, triploid, high yielding, recommended and popular S 1635 mulberry (Morus alba L.) along with intercrop yield and additional net profit. The plants were established through saplings in seven different spacing with variable number of plants / ha and were maintained through recommended package of practices for irrigated garden. Four different suitable intercrops, one in each season and one green manure crop in July September were taken up annually in mulberry for judicious utilization of space, time, nutrients and also for soil enrichment. Significant differences were observed among the treatments in all the parameters studied. Growth attributes and leaf quality were improved along with soil nutrient status in paired row system, particularly in (90cm + 120cm) × 60cm spacing. Besides, it registered almost similar leaf yield (29 488.98kg/ha/year) compared to 60cm × 60cm spacing (control) in spite of 42.9% less plant population (15 873/ha) over control (27 777/ha), higher leaf yield / plant (0.37kg) and optimum intercrop yield as well as additional net profit of r35 368/ha/year (r5974.00 more over control). Hence, this paired row spacing [(90cm + 120cm) × 60cm] may be useful and recommended to the farmers for mass practice in the cultivation of S 1635 mulberry with four intercrops and one green manure crop / year at least up to three years which did not adversely affect mulberry under irrigated condition. In addition, there is also a scope for partial mechanization which enables to reduce manpower requirement as well as economy in cultivation.
The Ground Reaction Force Comparison Between Conventional Deadlift And Hacklift

The aim of this study was to determine and compare the ground reaction force (GRF) during conventional deadlift and hacklift. Twenty (n=20) recreationally active, resistance-trained men were recruited to this crossover design study and were instructed to perform both conventional deadlift and hacklift in random order. Participants were needed to lift 85% of their conventional deadlift one repetition maximum (1RM) score. One way repeated measure analysis of variances (ANOVA) was conducted to compare the differences of GRF during concentric and eccentric phase of both exercise. Results showed that the force production during concentric phase was significantly higher during traditional deadlift while no significant differences exist during eccentric phase. Findings of this study suggested that based on force production, performing conventional deadlift imposed better chances of strength adaptation.
Genetic evidence for the mating system and reproductive success of black sea bream (Acanthopagrus schlegelii)

Abstract Understanding the mating system and reproductive success of a species provides evidence for sexual selection. We examined the mating system and the reproductive success of captive adult black sea bream (Acanthopagrus schlegelii), using parentage assignment based on two microsatellites multiplex PCR systems, with 91.5% accuracy in a mixed family (29 sires, 25 dams, and 200 offspring). Based on the parentage result, we found that 93.1% of males and 100% of females participated in reproduction. A total of 79% of males and 92% of females mated with multiple partners (only 1 sire and 1 dam were monogamous), indicating that polygynandry best described the genetic mating system of black sea bream. For males, maximizing the reproductive success by multiple mating was accorded with the sexual selection theory while the material benefits hypothesis may contribute to explain the multiple mating for females. For both sexes, there was a significant correlation between mating success and reproductive success and the variance in reproductive success of males was higher than females. Variation in mating success is the greatest determinant to variation in reproductive success when the relationship is strongly positive. The opportunity for sexual selection of males was twice that of females, as well as the higher slope of the Bateman curve in males suggested that the intensity of intrasexual selection of males was higher than females. Thus, male–male competition would lead to the greater variation of mating success for males, which caused greater variation in reproductive success in males. The effective population number of breeders (N b) was 33, and the N b/N ratio was 0.61, slightly higher than the general ratio in polygynandrous fish populations which possibly because most individuals mated and had offspring with a low variance. The relatively high N b contributes to the maintenance of genetic diversity in farmed black sea bream populations.
Tied gender condition for facial expression recognition with deep random forest

Abstract. Facial expression recognition (FER) in an uncontrolled environment is difficult due to changes in occlusion, illumination, noise, and personal attributes. A deep learning enhanced gender conditional random forest (G_DRF) is proposed for FER in an uncontrolled environment. In order to reduce the influence of occlusion, illumination, low image resolution, etc., our method extracts robust facial features by deep multi-instance learning. Then a G_DRF is devised to address the facial personal attributes’ influence, such as gender variation by conditional RF. A large number of experiments were conducted on the public CK+, BU-3DEF, and LFW face databases. The experimental results showed that the proposed method had better performance and robustness than the state-of-the-art methods. The recognition rates of CK+, BU-3DEF, and LFW were 98.83%, 90%, 60.58%, respectively. Compared with other advanced deep learning methods that require a large number of training samples, the proposed method needs a small number of training samples and achieves better results.
Sequential Vessel Trajectory Identification Using Truncated Viterbi Algorithm

In this work, we propose a novel classification algorithm that used to classify vessel data points into different trajectories. The algorithm is a truncated version of Viterbi Algorithm. A physical model utilizing the observation information completely is used to simulate the movement of vessels during the period. Distributions of observation noise (also called residuals) are learned from the model. A directed graph is then constructed based on those distributions to portrait the relationship between data points. Truncated Viterbi Algorithm (TVA) is applied to this graph to find the most possible trajectories embedding in the data set. By doing experiments on the maritime domain and Automatic Identification System (AIS) data, we can demonstrate the efficacy of our algorithm.
Phylogenetic relationships of Clematis (Ranunculaceae) based on chloroplast and nuclear DNA sequences

Phylogenetic relationships within Clematis, including Naravelia, Archiclematis and Clematopsis, were analysed using nucleotide sequences of chloroplast DNA [(1) matK and trnK introns; (2) atpB–rbcL spacer; (3) rpoB–trnC spacer; (4) psbA–trnH–trnQ spacer; (5) rbcL–accD spacer] and the nuclear ITS regions. The phylogenetic trees resulting from these analyses suggested nine major clades. The genera Archiclematis, Naravelia and Clematopsis were found to be nested within the genus Clematis, and should be included within it. Within the genus Clematis, the traditional subgenus Viorna was found to be monophyletic. The remaining subgenera (Flammula, Clematis and Campanella) and sections Flammula, Clematis and Cheiropsis, however, were found to be paraphyletic or polyphyletic. Recircumscription of several groups in Clematis was suggested. Enormous morphological diversification and very few nucleotide substitutions within Clematis indicate the recent radiation of the genus. Clematidinae shares a gene order with Anemoninae between the starting point of large single copy region and trnQ of chloroplast DNA, although Hepatica, a genus in Anemoninae, shows a different order in the region near trnH. © 2006 The Linnean Society of London, Botanical Journal of the Linnean Society, 2006, 152, 153–168.
Virtual IoT HoneyNets to Mitigate Cyberattacks in SDN/NFV-Enabled IoT Networks

As the IoT adoption is growing in several fields, cybersecurity attacks involving low-cost end-user devices are increasing accordingly, undermining the expected deployment of IoT solutions in a broad range of scenarios. To address this challenge, emerging Network Function Virtualization (NFV) and Software Defined Networking (SDN) technologies can introduce new security enablers, thereby endowing IoT systems and networks with higher degree of scalability and flexibility required to cope with the security of massive IoT deployments. In this sense, honeynets can be enhanced with SDN and NFV support, to be applied into IoT scenarios thereby strengthening the overall security. IoT honeynets are virtualized services simulating real IoT networks deployments, so that attackers can be distracted from the real target. In this paper, we present a novel mechanism leveraging SDN and NFV aimed to autonomously deploy and enforce IoT honeynets. The system follows a security policy-based approach that facilitates management, enforcement and orchestration of the honeynets and it has been successfully implemented and tested in the scope of H2020 EU project ANASTACIA, showing its feasibility to mitigate cyber-attacks.
A Joint Learning Information Extraction Method Based on an Effective Inference Structure

Over the past few years, natural language processing is getting much attraction from more scholars and institutions. Knowledge graph has been regarded as a crucial role in pushing natural language understanding forward. The task of information extraction is the first step to build a large-scale knowledge graph, which means to identify information from the natural language text and extract it in the form of entity and relation triplets. Some joint learning method have been proposed in this domain recently. In this paper, we inherit the idea of joint learning, use a simple, lightweight but effective structure to solve this task and compare our method with some recent algorithms on the benchmark dataset NYT and WebNLG. Results show that our method can get an improvement in F1 score.
The impact of biofuel consumption on CO2 emissions: A panel data analysis for seven selected G20 countries

Internationally, biofuel energy as a renewable energy source has been increasingly appreciated by various industries. The benefits of biofuel energy for environmental protection and global climate change cannot be denied. Hence, this paper examines the nexus among economic growth, biofuel consumption, urbanization rate, and CO2 emissions in seven selected Group of Twenty countries (G20) over 2001–2017. The results of fully modified ordinary least squares suggest that the environmental Kuznets curve (EKC) exists between economic growth and CO2 emissions, and the impact of biofuel consumption and the urbanization rate on CO2 emissions is negative and positive, respectively. The purpose of this paper is to investigate the nexus among economic growth, biofuel consumption, urbanization rate, and CO2 emissions. The significance of this paper is to add biofuel consumption as a new variable for a panel of seven selected Group of Twenty (G20) countries covering 2001–2017. In addition, this study put urbanization into the current environmental Kuznets curve model to validate that urbanization can increase CO2 emissions. Developing the biofuel industry can not only diminish fossil fuel energy consumption but also offer huge potential to reduce CO2 emissions.
Melting of Perennial Sea Ice in the Beaufort Sea Enhanced Its Impacts on Early-Winter Haze Pollution in North China after the Mid-1990s

In recent years, haze pollution has become the most concerning environmental issue in China due to its tremendous negative effects. In this study, we focus on the enhanced responses of December–January haze days in North China to September–October sea ice in the Beaufort Sea during 1998–2015. Via both observation and numerical approaches, compared with an earlier period (1980–97), the sea ice concentration in the Beaufort Sea presented large variability during 1998–2015. During 1980–97, the Beaufort Sea was mainly covered by perennial ice, and the ablation and freezing of sea ice mainly occurred at the south edge of the Beaufort Sea. Thus, heavy sea ice in autumn induced negative sea surface temperature anomalies across the Gulf of Alaska in November. However, the colder sea surface in the Gulf of Alaska only induced a weak influence on the haze-associated atmospheric circulations. In contrast, during 1998–2015, a drastic change in sea ice existed near the center of the Arctic Ocean, due to the massive melting of multiyear sea ice in the western Beaufort Sea. The perennial ice cover in the western Beaufort Sea was replaced by seasonal ice. The broader sea ice cover resulted in positive sea surface temperature anomalies in the following November. Then, suitable atmospheric backgrounds were induced for haze pollution in December and January. Simultaneously, the response of the number of haze days over North China to sea ice cover increased. These findings were verified by the CESM-LE simulations and aided in deepening the understanding of the cause of haze pollution.
Biochemical components of the selected Macroflora associated with the Neyyar, Thiruvananthapuram, Kerala, India

Neyyar, the southernmost river of Kerala, originating from the Agasthaymala flows through the Neyyattinkara taluk of Thiruvananthapuram district. Ten identified stations were selected, macroflora associated with the river were collected and analyzed various biochemical components namely lipid, protein and carbohydrate adopting various standard methods. Seasonally minimum lipid, protein and carbohydrate content were registered in Saccharum spontaneum (Station 5), Cyperus tenuispica (Station 8) and Saccharum spontaneum (Station 4) respectively and the corresponding maxima in Pityrogramma calomelanos, Colocacia antiquorum and Limnocharis flava. On an annual basis it showed a pattern with lipid < carbohydrate < protein in all the selected macrophytes. Higher accumulation of protein and carbohydrate were registered in Colocacia antiquorum and Limnocharis flava, suggesting that it can be exploited as food, feed and fodder.
Review of Leadership Styles in Perspective of Dynamic Capabilities: An Empirical Research on Managers in Manufacturing Firms

Firms need to adapt to changes in both their internal and external environments and create new systems that let them focus on new trends, identify improvements, try to guess their potential impact on their management and manufacturing system. They try to learn quickly how to implement changes to their standard operating procedures. A wide range of factors affects this procedure. To achieve this, they should be managed by modern leaders. The purpose of this research is to investigate the leadership dimensions and a related framework for assessing leadership styles, in relation to the context in which the leader works in dynamic environment. Furthermore, the purpose of this study was to examine the relative impact of different types of leadership on firms’ dynamic capabilities. Research is reported on data from a large sample of leaders and managers (n 214) from a range of private manufacturing organizations in West of Turkey. Content analyses, one of the methods of quality analysis, and MAXMaps were performed in context of top-down &bottom-up confirmation method. SPSS and Maxqda analyses program was used to analyze data. The results show that agile and transformational leaders can enhance firms’ dynamic capabilities indirectly or indirectly by creating an organizational atmosphere where employees and followers are encouraged, motivated, inspired to be a role model, open to change, and innovation. However, it was found that the link between dynamic capabilities of a firm and hubristic and autocratic leadership was slightly positive.
Differentiation of Self, Couple Adjustment and Family Life Cycle: A Cross-Sectional Study

Abstract This study explores differentiation of self (DoS) and its association with couple adjustment across the family life cycle, in a sample of Spanish individuals (n = 506). Individuals in stage VII (nearing the end of life) revealed significantly lower levels of DoS than those in other stages, except for V (moving on at midlife). Individuals in stages V and VII also revealed lower couple adjustment than individuals in stage II (couple formation). DoS was positively associated with couple adjustment across all stages, particularly V-VII. Longitudinal studies will confirm the trend for decrease in DoS and couple adjustment. Implications for therapy are discussed.
Flow-TTS: A Non-Autoregressive Network for Text to Speech Based on Flow

In this work, we propose Flow-TTS, a non-autoregressive end-to-end neural TTS model based on generative flow. Unlike other non-autoregressive models, Flow-TTS can achieve high-quality speech generation by using a single feed-forward network. To our knowledge, Flow-TTS is the first TTS model utilizing flow in spectrogram generation network and the first non-autoregssive model which jointly learns the alignment and spectrogram generation through a single network. Experiments on LJSpeech show that the speech quality of Flow-TTS heavily approaches that of human and is even better than that of autoregressive model Tacotron 2 (outperforms Tacotron 2 with a gap of 0.09 in MOS). Meanwhile, the inference speed of Flow-TTS is about 23 times speed-up over Tacotron 2, which is comparable to FastSpeech.1
Mathematical morphology approach to internal defect analysis of A356 aluminum alloy wheel hubs

A356 aluminum alloy is a material widely used in the production of automobile wheels. Internal defects such as gas holes and shrinkage cavities are likely to develop in the process of low pressure casting. X-ray images of the hub are able to provide some information on such defects. This paper proposes a defect extraction method which is built on mathematical morphology. It involves three operations, i.e., the top-hat transform, the top-hat reconstruction transform and the dilation reconstruction. A larger square structuring element and a small threshold are used firstly to obtain all potential defect areas of the hub. A structuring element of a suitable size are applied to different defect areas in subsequent extraction. A new threshold is then decided to get the final defect extraction results. The experimental results show that the above defect extraction method not only works on X-ray hub images, but is robust against the interference caused by noises and hub geometry, and hence can potentially be extensively applied to X-ray detection of hubs.
An Automated Seepage Meter for Streams and Lakes

We describe a new automatic seepage meter for use in soft bottom streams and lakes. The meter utilizes a thin‐walled tube that is inserted into the streambed or lakebed. A hole in the side of the tube is fitted with an electric valve. Prior to the test, the valve is open and the water level inside the tube is the same as the water level outside the tube. The test starts with closure of the valve, and the water level inside the tube changes as it moves toward the equilibrium hydraulic head that exists at the bottom of the tube. The time rate of change of the water level immediately after the valve closes is a direct measure of the seepage rate (q). The meter utilizes a precision linear actuator and a conductance circuit to sense the water level to a precision of about ±0.1 mm. The meter can also provide an estimate of vertical hydraulic conductivity (Kv) if data are collected for a characteristic time. The detection limit for q depends on the vertical hydraulic head gradient. For Kv = 1 m/day, q of about 2 mm/day can be measured. Results from a laboratory sand tank show excellent agreement between measured and true q, and results from a field site are similar to values from calculations based on independent measurements of Kv and vertical head gradients. The meter can provide rapid (30 min) q measurements for both gaining and losing systems and complements other methods for quantifying surface water groundwater interactions.