Miracle-dz/UniFAR-FTUs huggingface dataset:
Infection prevalence, intensity, and tissue damage caused by the parasitic flatworm, Bdelloura candida, in the American horseshoe crab (Limulus polyphemus)

Parasite infection dynamics can have profound implications on a host’s fitness; yet, there is a dearth of information on parasites in the American horseshoe crab (Limulus polyphemus) (Linnaeus 1758), a species that has experienced population declines in recent decades. Therefore, we aimed to quantify the prevalence, intensity, and gill surface area coverage of the ectoparasitic flatworm (cocoon and adult stages), Bdelloura candida in adult (n = 29), sub-adult (n = 7) and juvenile (n = 32) horseshoe crabs collected from Moriches Bay, NY (40.7810° N, 72.7171° W) in 2019 and 2020. Subsamples of horseshoe crab gill tissue (10%) were collected from live specimen, then B. candida cocoons were enumerated across the gill subsamples using microscopy while the extent of tissue damage was quantified with histology. B. candida was present in all adult and sub-adult crabs (100%), whereas juveniles exhibited 6.2% prevalence. Cocoon intensities per sample ranged from 28 to 805 cocoons, with 4.0–94.0% of gill lamellae harboring cocoons. In infected individuals, the total cocoon surface area coverage on gill tissues ranged from 0.06–14.51%, with higher cocoon intensities observed in the ventral-most gill quartiles relative to the dorsal-most gill regions. Sex was strongly supported as a primary driver behind B. candida infection intensities with adult females harboring higher intensities. Among infected gill lamellae, cocoon intensity was lower in mitochondrial-rich regions relative to mitochondrial-poor regions. These results provide novel insight into B. candida infection dynamics across horseshoe crab demographics, but further research is necessary to quantify the physiological impacts of the infection on L. polyphemus.
Physical Fitness and Learning Achievement Academic in Children Aged 10-12 years

The purpose of the study. The purpose of this study was to determine how big the impact of physical fitness on student achievement Materials and methods. The method in this research is a path analysis method with a correlational test technique. Correlational refers to taking the rsquare hypothesis, which is how big the impact of the correlation between physical fitness and student learning achievement is and this study uses the SPSS Version 25 application. Results.The results found that the level of the variable physical fitness on learning achievement with r = 0.708 with rsquare = 0.501 Coefficients sig value . 0.000. It turns out that the value of sig. 0.000 is less than the probability value of 0.00 or the value of 0.05>0.000. Conclusions. Then Ha is accepted and H0 is rejected, meaning that the path analysis coefficient is significant. This study proves that there is a direct impact of physical fitness on student achievement.
Variables clínicas del parto en posición vertical y horizontal: Revisión exhaustiva de literatura

Introducción. El trabajo de parto representa el acontecimiento más importante durante la culminación del periodo de gestación y, por lo tanto, la adecuada elección de su posición, ya sea vertical u horizontal, resulta indispensable para minimizar las complicaciones maternas y neonatales. Objetivo. Realizar una revisión de la literatura sobre el comportamiento clínico del parto vertical y horizontal, describiendo los principales resultados en diferentes países del mundo. Método. Revisión documental mediante la búsqueda de la literatura entre los años 2009 y 2020 en bases de datos especializadas seleccionándose 50 artículos. Resultados. La posición vertical se asoció a una menor duración del trabajo de parto, dolor referido y necesidad de episiotomía, no obstante, esta posición puede incrementar el riesgo de hemorragia postparto y daño perineal. Conclusión. La variedad de desenlaces obstétricos y neonatales asociados a las posiciones de parto vertical y horizontal hacen complejo definir una posición de parto óptima y, por lo tanto, se recomienda la libre elección de acuerdo con las características que presente cada paciente
Flexible Noncontact Approach for Fault Location of Transmission Lines Using Electro-Optic Field Sensors

Locating faults in transmission lines is important for the safety and continuous operation of power systems. The existing fault location methods based on traveling waves mostly use current transformers to obtain the transient signals, which requires a direct connection with the live lines and therefore brings inconvenience to the installation, debugging, and maintenance. In this article, we propose a flexible noncontact approach for locating faults in transmission lines based on broadband electro-optic field sensors, where the noncontact fault location system can be easily installed, debugged, and maintained. The approach uses an electric field sensor to directly measure the quasi-static electric field generated by the faults, and then the associated time difference of arrival of the transients at two ends of a transmission line can be obtained. The approach is validated and tested by experiments both in laboratory and real 500 kV transmission lines. The artificial fault experiment shows a location error of approximately 200 m on a 177-km- long 500 kV power transmission line.
A Novel Rank Learning Based No-Reference Image Quality Assessment Method

Recently, applying deep learning to no-reference image quality assessment (NR-IQA) has received significant attention. Especially in the last five years, an increasing interest has been drawn to the studies of rank learning since it can help mitigate the problem of small IQA datasets. However, on one hand, existing rank learning is not suitable for the authentically distorted images due to the lack of generated rank samples. On the other hand, the output of existing rank loss functions is uncontrollable, resulting in reduced performance. Motivated by these two limitations, we propose a novel rank learning based NR-IQA method, termed controllable list-wise ranking IQA (CLRIQA) in this paper. To be specific, we first present an imaging-heuristic approach, in which the over- and under-exposure is formulated as an inverse of the Weber-Fechner law, and fusion strategy and compression are adopted, to simulate the authentic distortion and generate the rank image samples. These samples are label-free yet associated with quality ranking information. Then we design a controllable list-wise ranking (CLR) loss function by setting an upper and lower bound of rank range and introducing an adaptive margin to tune rank interval. Finally, both the generated rank samples and proposed CLR are used to pre-train a convolutional neural network. Moreover, to obtain a more accurate prediction model, we take advantage of the IQA datasets to fine-tune the pre-trained network further. Various experiments are conducted on the IQA benchmark datasets, and experimental results demonstrate the effectiveness of the proposed CLRIQA method. The source code and network model can be downloaded at the following web address: https://github.com $/$ GZHU-DVL $/$ CLRIQA.
Nest-site selection and nest design of Iberian bullfinches Pyrrhula pyrrhula iberiae in northwestern Spain

Nest-habitat selection and nest design in a Eurasian bullfinch population in the Iberian Peninsula are thoroughly addressed in this study for the first time. Hedgerows and meadows were found around all of the nests and most of them were supported by hedgerows, so bullfinches consistently used the general woody vegetation available as reproduction habitat and site. Also, poplar plantations appeared preferentially in the immediate surroundings of the nests. Partly reflecting these results, bullfinches chose zones with greater shrub and tree cover than that available. Bullfinches placed their nests on a wide variety of plant species, but showed predilection for thorny species. Overall mean height of nests above the ground was 1.43 m and large-sized shrubs/trees were preferred. The most predominant bullfinch nest orientations were S, E and centered, which arguably provided thermal benefits and protected from severe weather. In general, there were no significant temporal variations in nest-site selection. With the exception of thorny support and favourable orientation, acting jointly, there was no significant association between nest-site characteristics and nesting success, presumably because many nests were already located in the most advantageous places at each time, and because despite this, predation pressure was high. Nest external dimensions were relatively variable, whereas internal width was the least variable nest dimension. No significant monthly or interannual variations in nest weight were observed. Larger nests did not hold larger clutches. Successful nests were larger than unsuccessful ones. The bullfinch nests were of simple construction, with two clearly different regions, the outer nest and the internal cup, with no significant temporal variations in the weight of either. The outer, structural nest consisted mainly of twigs, whereas roots and herbaceous shoots were the highest fractions lining the cup. Hair was the only animal-derived material used by bullfinches.
Natural Polymers for Biodegradable Dressings to Save the Environment

The current fashion system uses high volumes of non-renewable resources to produce clothes, being responsible for 10% of the global greenhouse gas emissions into the atmosphere every year and 20%of the global water wasted. At the same time people are buying 60%more clothing than 15 Years ago, which going in the landfills, causes 92 million tons of waste each year. This waste has been further increased by the surgical masks used for COVID-19 pandemic. Thus, a new way of designing and producing clothing needs to be incorporated into the current system to facilitate its recycling making it more circular. New tissues, therefore, are proposed made by natural polysaccharides, embedded by micro- Nano capsules of chitin Nano fibrils and Nano lignin all obtained as by- products from food and forestry waste respectively. Thus, pollution and waste will be reduced and the natural raw materials will be maintained for the future generations.
Using an Eigenvector Spatial Filtering-Based Spatially Varying Coefficient Model to Analyze the Spatial Heterogeneity of COVID-19 and Its Influencing Factors in Mainland China

Background: The COVID-19 pandemic has led to many deaths and economic disruptions across the world. Several studies have examined the effect of health risk factors on COVID-19 rates in different places, but the problem of spatial heterogeneity has not been adequately addressed.Methods: In this paper, we developed an Eigenvector Spatial Filtering based spatially varying coefficient model (ESF-SVC) to reveal the spatially varying impact of certain health risk factors on the COVID-19 spread. The experiment was conducted during 7 weeks within two study extents (Hubei province and mainland China). Spatial varying coefficient maps were produced for spatial pattern discovery.Results: Results showed that the ESF-SVC model could take good control of over-fitting problems, with average adjusted R2 16.31% (in Hubei province) and 10.25% (in mainland China) higher than that of GWR. The cross validation RMSE of ESF-SVC model was also the lowest. In Hubei province, Population density and wind speed had a significant impact on COVID-19 infection rates and that their effect was constant across cities. While in mainland China, migration score, building density, temperature and altitude showed significant impact and their effect varies across space. The influence of migration score was less contributive and less significant in cities around Wuhan than cities farther away, while the altitude showed stronger contributions in high altitude cities.Conclusions: Our study hopes to provide not only a feasible path to solve the problem of spatial autocorrelation and spatial heterogeneity in COVID-19 characterization but also an intuitive way to discover spatial patterns in large study areas, which could help people and government awareness of the potential health risks and shed some light in COVID-19 control strategies.
Physical layer secure key generation with nonlinear preprocessing of RSS for power constraint wireless networks

There has been growing attention in physical layer security (PLS) techniques for wireless networks. PLS techniques are based on physical layer characteristics and are less computationally complex than traditional cryptographic approaches, which work on higher layers of networks. Physical layer key generation (PLKG) is one of the prominent key based PLS techniques that exploits reciprocity and randomness of wireless fading channel to establish secure communication between two transceivers. PLKG system consists of five stages as RSS measurement, its preprocessing, quantization and encoding, key reconciliation, and privacy amplification. Each stage has a substantial role in deciding the performance of PLKG system, but RSS preprocessing offers wide scope in performance improvement for the system. In this work, we propose PLKG system using a new class of preprocessing technique first time, which is nonlinear. We formulated the problem uniquely and considered two nonlinear techniques: nonlinear preprocessing using expander (NLPE) and nonlinear preprocessing using compressor (NLPC). We analyzed the performance of system using NLPE and NLPC and found NLPE is most suitable. Performance of the system is evaluated in terms of bit disagreement rate (BDR) and randomness of keys. Results show that NLPE performs extremely well, as compared with linear approach and without preprocessing approach, especially at low signal to noise ratio (SNR) range. Emerging wireless networks such as internet of things (IoT), centralized radio access network (CRAN), wireless sensor network (WSN), and so forth are being operated at lower transmission power with lightweight hardware. Hence, for such type of power constraint networks, proposed PLKG system with NLPE can be proven a perfect security solution.
Effect of Microgravity Environment on Gut Microbiome and Angiogenesis

Microgravity environments are known to cause a plethora of stressors to astronauts. Recently, it has become apparent that gut microbiome composition of astronauts is altered following space travel, and this is of significance given the important role of the gut microbiome in human health. Other changes observed in astronauts comprise reduced muscle strength and bone fragility, visual impairment, endothelial dysfunction, metabolic changes, behavior changes due to fatigue or stress and effects on mental well-being. However, the effects of microgravity on angiogenesis, as well as the connection with the gut microbiome are incompletely understood. Here, the potential association of angiogenesis with visual impairment, skeletal muscle and gut microbiome is proposed and explored. Furthermore, metabolites that are effectors of angiogenesis are deliberated upon along with their connection with gut bacterial metabolites. Targeting and modulating the gut microbiome may potentially have a profound influence on astronaut health, given its impact on overall human health, which is thus warranted given the likelihood of increased human activity in the solar system, and the determination to travel to Mars in future missions.
Identifying opportunities and gaps in current evaluation frameworks – the knowns and unknowns in determining effective student engagement activity

Abstract The higher education sector is under increasing pressure to deliver more and to evidence the fruits of its contribution to society. There is a particular focus on the enhanced engagement of students in order to maximise success, and for this engagement to be achieved equitably across the student body, regardless of demographic backgrounds. This calls for the sector to increase its capability to enhance student engagement in a targeted manner, and to be able to evidence success. The purpose of this article is to critically review, as a result of trialling, frameworks which offer guidance on the structuring of student engagement activity and/or encouraging behaviours associated with student engagement whether at student, teacher or institutional level. We assess the value of these frameworks in practice by identifying opportunities provided by them, reveal gaps in how they support effective student engagement activity, and identify further work for the sector in plugging the guidance gaps that lead to sub-optimal evaluation.
GEOLOGY OF THE CHUGACH-PRINCE WILLIAM TERRANE IN NORTHERN PRINCE WILLIAM SOUND, ALASKA

This six-student project focused on the geology of the Chugach and Prince William terranes in northern Prince William Sound, Alaska. The Chugach-Prince William (CPW) composite terrane is a MesozoicTertiary accretionary complex that is well exposed for ~2200 km in southern Alaska and is inferred to be one of the thickest accretionary complexes in the world (Plafker et al., 1994; Cowan, 2003). The CPW terrane is bounded to the north by the Border Ranges fault, which shows abundant evidence of Tertiary dextral strike slip faulting, and inboard terranes of the Wrangellia composite terrane (Peninsular, Wrangellia, Alexander) (Pavlis, 1982; Cowan, 2003; Roeske et al., 2003). Throughout much of the 2200 km long belt of the CPW terrane it is bounded by the offshore modern accretionary complex of the Alaskan margin, but east of Prince William Sound the Yakutat block is colliding into the CPW and this young collision has significantly affected uplift and exhumation of inboard rocks.
An automatic machining process decision-making system based on knowledge graph

ABSTRACT Automatic process decision-making is a key module in intelligent process design(IPD), which determines the intelligence degree of IPD and affects the quality of product design. The traditional process decision-making method fails to solve the problem of knowledge expression, especially the integration of enterprise manufacturing resources and process knowledge. What’s more, heterogeneous knowledge also leads to the application of traditional knowledge mainly in keyword retrieval. So the process reasoning is mainly applied to the feature level, but the reasoning ability for the part level is weak. To overcome the above problems, the Knowledge Graph(KG) is introduced into the automatic machining process decision-making system. Firstly, a three-level information model is built to reorganize part information, process knowledge, and equipment resources based on KG. Secondly, the process reasoning framework based on KG is established, which is composed of process knowledge graph(PKG) information and process reasoning algorithm. Thirdly, to integrate process reasoning based on PKG, a hybrid reasoning algorithm based on semantic analysis(SA) and attributes weighting(AW) is built, which solved the problem of heterogeneity among process knowledge when making decisions. Finally, a prototype system was developed, and the aero-engine cone gear axis was tested to verify the effectiveness of the proposed system.
Quality measurements of various types of wastewaters and their impacts on plant growth

Wastewater is a rich source of essential nutrients for growth of plants. But accumulation of heavy metals restrict the uptake of nutrients that leads to the deficiency of nutrients in plant body and ultimately reduce its growth. In present study, different types of wastewaters from the Malir (Domestic and Industrial wastewater) and Lyari river were collected and analyzed to evaluate their quality. The effect of wastewater assessed on germination and growth parameters of Abelmoschus esculentus (Okra) and Phaseolus vulgaris (Common Beans). It was evaluated that pH and dissolved oxygen were detected to be under permissible limit of World Health Organization water-quality-standards in DWW (Domestic wastewater) and LWW (Lyari wastewater). Higher amounts of essential nutrients such as Ca, K and Mg were perceived in DWW. Consequently DWW and LWW significantly improved the germination (%) and growth of A. esculentus and P. vulgaris. IWW (industrial wastewater) and mix wastewater (combination of DWW and IWW) reduced germination (%) as well as growth of crops. Higher amount of as and Cd were detected in IWW. Thus, it might be due to their increased concentrations that effected plant growth. However, plant growth depends on quality of applied water as well as variety of crop that tolerate their characteristics.
The Architectonics Features of Heterostructures for IR Range Detectors Based on Polycrystalline Layers of Lead Chalcogenides

A model is developed for the formation of porous intragranular architectonics of nanostructured polycrystalline layers of lead chalcogenides for photodetectors and IR emitters. The layers are obtained under the conditions of thermal evaporation in a quasi-closed volume by the “hot wall” method followed by sensitizing heat treatment in an iodine-containing atmosphere. Model concepts are developed considering the experimental results of studying the intragranular structure of lead chalcogenides through original combined AFM methods over the cross-section of porous grains (cores) encapsulated by an oxide shell (lateral force microscopy and local tunneling I–V spectroscopy).
Coupling between Trigeminal-Induced Asymmetries in Locus Coeruleus Activity and Cognitive Performance

In humans, the asymmetry in the masseter electromyographic (EMG) activity during clenching is positively correlated with the degree of pupil size asymmetry (anisocoria) at rest. Anisocoria reveals an asymmetry in LC activity, which may lead to an imbalance in cortical excitability, detrimental to performance. Hereby, we investigated, in individual subjects, the possibility that occlusal correction, which decreases EMG asymmetry, improves performance by balancing LC activity. Cognitive performance, task-related mydriasis, and pupil size at rest were modified by changing the occlusal condition. Occlusal-related changes in performance and mydriasis were negatively correlated with anisocoria changes in only 12/20 subjects. Within this population, spontaneous fluctuations in mydriasis and anisocoria also appeared negatively coupled. Occlusal-related changes in performance and mydriasis were negatively correlated with those in average pupil size (a proxy of average LC activity) in 19/20 subjects. The strongest association was observed for the pupil changes occurring on the side with higher EMG activity during clenching. These findings indicate that the effects of occlusal conditions on cognitive performance were coupled to changes in the asymmetry of LC activity in about half of the subjects, while they were related to changes in the average tonic LC activity in virtually all of them.