Miracle-dz/UniFAR-FTUs huggingface dataset:
Changes of digestive enzymes in totoaba (Totoaba macdonaldi Gilbert, 1890) during early ontogeny

Totoaba macdonaldi is an endemic specie which has been overexploited causing its population to decrease and to be cataloged as endangered. Understanding the larval period is the most critical stage in the development of marine fish farming. Our study aims to determine the changes of digestive enzyme activities during the early ontogeny of totoaba, using biochemical and electrophoretic techniques. The results show that the acid protease had maximum activity between days 28 and 32 DPH, when the Artemia was replaced by formulated food. Alkaline protease activity was detected at 2 DPH with maximal activity between 20 and 32 DPH; trypsin activity became active from 2 DPH; chymotrypsin activity increased at 6 DPH; leucine aminopeptidase activity was detected at 3 DPH, showing its maximal level at 22 DPH; carboxypeptidase A activity increased at 3 DPH; and lipase and amylase activities were detected at 2 DPH. Acid zymogram showed only one isoform (0.72 rf) from 2 DPH and increased in intensity from 8 DPH. For alkaline proteases, four isoforms were detected from yolk absorption (1 DPH), increasing to six isoforms (77.8, 47.3, 43.5, 21.0, 19.2 and 17.5 kDa) from 8 DPH onwards. Our results show that larvae of T. macdonaldi present characteristics typical of carnivore marine fish, showing the presence of alkaline digestive enzymes prematurely and the presence of offset pepsin. T. macdonaldi can be consider to be a youth beginning at 28 DPH, this being the most appropriate day to perform replacement by artificial food.
Habitat discontinuities form strong barriers to gene flow among mangrove populations, despite the capacity for long‐distance dispersal

Mangrove forests are among the world's most important ecosystems but are declining rapidly worldwide. Effective conservation management requires a better understanding of the patterns and drivers of gene flow across a range of spatial scales. Despite the capacity for long‐distance propagule dispersal, field studies suggest that mangrove propagules tend not to disperse far from the release point, which has important implications for the impact of habitat discontinuities on gene flow. We use a comprehensive seascape genomics approach to investigate this concept in the world's most widely distributed mangrove species, Avicennia marina.
World ocean circulation experiment. WOCE operations manual. Volume 3. The observational programme. Section 3.1. WOCE hydrographic programme. Part 3.1.3. WHP operations and methods. (revision 1)

;Contents: A Suggested Protocol for Continuous Flow Automated Analysis of Seawater Nutrients; Measuring C14 in Seawater CO2 by Accelerator Mass Spectrometry; CTD Oxygen Calibration Procedure; Determination of Dissolved Oxygen in Sea Water by Winkler Titration; and Improving NBIS MK III Measurements.
Characterization of Cooperative Breeding for the Buff-throated Partridge (Tetraophasis szechenyii) Based on Parentage Testing

1Key Laboratory of Bio-Resource and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University, Chengdu 610065, Sichuan, P.R. China 2College of Life Sciences and Food Engineering, Yibin University, Yibin 644007, P.R. China 3Institute of Ecology, China West Normal University, Nanchong 637002, P.R. China 4School of Life Sciences, Guizhou Normal University, Guiyang 550001, P.R. China Article Information Received Revised Accepted Available online 22 July 2020
Comparison of two methods of protein quality evaluation in rice, rye and barley as food protein sources in human nutrition

Different foods differ in their protein quality, which is characterized by the content and digestibility of individual amino acids. The Food and Agriculture Organisation has recommended replacing the method for protein quality evaluation of foods called protein digestibility corrected amino acid score (PDCAAS) with the new method - digestible indispensable amino acid score (DIAAS), in which the values of ileal amino acid digestibility obtained in pigs are used. However, the information about DIAAS values of foods are limited. Therefore, the study on growing pigs was conducted to determine true fecal protein digestibility and standardized ileal amino acid digestibility of rice, rye and barley. Using these values, the PDCAAS and DIAAS were calculated and compared. A total of 18 gilts with a T-cannula inserted in the terminal ileum were allotted to 3 diets with six replicate pigs per diet. Three semi-purified diets were formulated to contain the tested cereal grains (rice, rye, barley) as the sole nitrogen source. Chromic oxide was used as indigestible marker. Each experimental period comprised of a 7-d adaptation period followed by 24 h collection of feces and ileal digesta. The content of nitrogen, dry matter and chromic oxide was analyzed in samples of diets, feces and ileal digesta. Moreover, in the samples of diets and ileal digesta the content of amino acids was determined. Calculated ratio of crude protein to lysine was greatest in rice (4.50) followed by rye (3.65) and the lowest one in barley (3.35). True fecal protein digestibility was greater when compared with ileal amino acid digestibility for all tested samples, thus suggesting an overestimation of protein quality determined by PDCAAS. Calculated PDCAAS values for rice, rye and barley (81, 65 and 61%) were generally greater than the DIAAS values (79, 56 and 55%), especially for the poorer quality protein sources such as rye and barley in comparison with rice. The lysine was the first limiting amino acid in all tested cereal grains. Based on the DIAAS evaluation, rice is better protein source in human nutrition in comparison with rye or barley.
A Low-Profile Vertically Polarized Magneto-Electric Monopole Antenna With a 60% Bandwidth for Millimeter-Wave Applications

A millimeter-wave (mmW) low-profile wideband magneto-electric (ME) monopole antenna with the vertically polarized endfire radiation is presented by combining a pair of the top-loaded electric monopoles with a thin open-ended substrate integrated waveguide (SIW) with the extended lower broad wall. The antenna has a profile of 0.19 wavelength at the center frequency of the operating band, a wide bandwidth of 60.7% (from 23.5 to 44 GHz) covering all the fifth-generation (5G) mmW bands in the <italic>Ka</italic>-band, a stable gain of around 7 dBi, and a tilted radiation pattern. Then a <inline-formula> <tex-math notation="LaTeX">$1 \times 8$ </tex-math></inline-formula> ME-monopole array is designed to investigate the beam scanning properties and the effects of the metallic ground and the polycarbonate radome, which should be considered in practical applications. As a sample, a <inline-formula> <tex-math notation="LaTeX">$1 \times 8$ </tex-math></inline-formula> array fed by an SIW feed network, assembled on a metallic ground plane, and covered by a polycarbonate radome is finally designed, fabricated, and measured. The prototype achieves promising radiation features with a gain up to 15.3 dBi. Owing to the compact low-profile structure with good performance, the proposed design would be valuable to the mmW applications.
Ontogeny of Polycotylid Long Bone Microanatomy and Histology

Abstract Plesiosauria is an extinct clade of diapsid marine reptiles that evolved in the Late Triassic and radiated globally for the remainder of the Mesozoic. The recent description of a pregnant specimen of Polycotylus latipinnis demonstrates that some plesiosaurs were viviparous. To establish a baseline of histological data on plesiosaur ontogeny, we sampled the mother and fetus of the gravid plesiosaur specimen. To widen the base of data concerning ontogeny and life history of plesiosaurs, we gathered additional morphologic and histologic data from a securely identified growth series of polycotylids from the Pierre Shale of South Dakota. Paleohistological thin sections were prepared from the three humeri. Both adults show a dense, heavily remodeled cortex consisting entirely of longitudinally oriented secondary osteons, except for a thin rind of superficial primary bone. The mother exhibits an external fundamental system, indicating it was fully mature; the other adult does not. In both adults the cortex grades into a spongy medulla, comprising large vascular canals and erosion rooms surrounded by secondary lamellar trabecular bone, and lacking a marrow cavity. The fetal humerus possesses a medullary region similar to that of the Dolichorhynchops bonneri adult, although its lamellar bone is primary and deposited around calcified cartilage. The medulla is demarcated from the cortex by a prominent Kastschenko’s line. The cortex of the fetus is a relatively thin layer of periosteal woven bone, longitudinally to radially vascularized, and interfingered with columns of osteoblasts surrounded by rapidly-deposited extracellular matrix. The neonate humerus resembles the fetus, with its trabeculae identical in both size and histology, although it lacks calcified cartilage. The cortex is also similar but much thicker, consisting entirely of rapidly deposited, radially vascularized, woven to fibrolamellar bone. The cortex carries a line near its surface. This feature is not a line of arrested growth, but a sudden change in vascular angle and increase in bone density. We argue this feature is a birth line indicating a change in growth regime, possibly in response to increased hydrodynamic forces after birth. The birth line indicates that the neonate was about 40% of maternal length when born. Our histological data demonstrate that polycotylids had very high fetal growth rates, and that birth size was large. Comparison with the geologically oldest plesiosaur confirms that rapid growth evolved in the Triassic, although histological details differ, and the degree to which the polycotylid ontogenetic pattern is generalizable to other plesiosaurs is currently unknown. Further histological research utilizing full growth series is needed, particularly for Jurassic taxa.
Unconditionally Stable Implicit Schemes for Transient Analysis of Lossy Multiconductor Lines

This article shows the advantages provided by implicit time stepping schemes for the study of multiconductor transmission lines. Implicit schemes allow for choosing time and space steps independently by attending only to resolution criteria, without the limitation imposed by the Courant–Friedrich–Levy stability condition. Hence, they behave favorably whenever a large time step would be preferable, for instance when a massive number of simulations is required for sensitivity analyses. We focus our attention on two common schemes in electromagnetics, Crank-Nicolson and Newmark-$\beta$ methods, that are shown to have the same accuracy and to lead to the same solving-equation structure. We illustrate how to include frequency-dependent losses in the algorithms, and we show the influence of dispersion on fast transients. Results show that implicit formulations can be favorably compared with the classical explicit leap-frog scheme.
Changes in the Ecological Parameters of Mixed Forests of Sal (Shorea robusta Gaertn.) Are a Function of Distance from the Human Settlements

Forests in Nepal are extremely important for supporting the livelihood of millions of people who collect forest products for their subsistence use and partly for income generation. Such inherent dependence is expected to cause disturbance in the forest ecosystem. We investigated changes in the structural assemblages caused by the interaction between anthropogenic disturbances and forest management activities in the mixed forests of Sal (Shorea robusta Gaertn.) of Terai, Central Nepal. We evaluated three buffer zone community forests (BZCFs), namely, Radha Krishna, Musharni Mai, and Janajagaran of Parsa Wildlife Reserve (PWR); the forest inside PWR was taken as a control. A transect of 2 km length was laid in each forest, and six plots, each of 1 ha size, were established at a successive interval of 300 m along the edge to the interior of the forests to count and record the diameter at breast height (DBH) of the studied plants. We observed that the species diversity increased linearly (p < 0.05) towards the forest interior in the BZCFs. Species other than S. robusta had significantly higher (p < 0.05) dominance and Importance Value Indices in the interior sites. We did not observe such trends in the control forest. Multivariate analysis showed that the sites of BZCFs had higher structural dissimilarity, but the control forest sites were closer to each other in composition. The forest sites near the settlements had undergone biotic homogenization (S. robusta mixed forest changed to S. robusta forest) due to the interaction between anthropogenic disturbances and forest management activities. On the basis of vegetation density, the edges of BZCFs appeared to be protected, but on the basis of diversity failed to do so. Future management strategies should be directed towards enhancing the diversity, heterogeneity, and forest quality, especially near the forest edges.
C. elegans synMuv B proteins regulate spatial and temporal chromatin compaction during development

ABSTRACT Tissue-specific establishment of repressive chromatin through creation of compact chromatin domains during development is necessary to ensure proper gene expression and cell fate. Caenorhabditis elegans synMuv B proteins are important for the soma/germline fate decision and mutants demonstrate ectopic germline gene expression in somatic tissue, especially at high temperature. We show that C. elegans synMuv B proteins regulate developmental chromatin compaction and that the timing of chromatin compaction is temperature sensitive in both wild type and synMuv B mutants. Chromatin compaction in mutants is delayed into developmental time periods when zygotic gene expression is upregulated and demonstrates an anterior-to-posterior pattern. Loss of this patterned compaction coincides with the developmental time period of ectopic germline gene expression, which leads to a developmental arrest in synMuv B mutants. Finally, accelerated cell division rates at elevated temperature may contribute to a lack of coordination between expression of tissue specific transcription programs and chromatin compaction at high temperature. Thus, chromatin organization during development is regulated both spatially and temporally by synMuv B proteins to establish repressive chromatin in a tissue-specific manner to ensure proper gene expression. Summary: C. elegans synMuv B proteins regulate chromatin compaction preceding upregulation of zygotic gene expression to ensure proper gene repression and cell fate decisions, especially at high temperature.
Radio-Over-Fiber Technology: Present and Future

Radio-over-fiber (RoF) technology is a hybrid technology which was first introduced to the telecommunication arena in the eighties. The research topics have evolved over the last three decades with initial focus on backhaul transport to current focus of mobile fronthaul. This paper aims to provide an overview of the present research areas in RoF and discuss our recent work that highlights the benefits of centralized control configuration of RoF based fronthaul. The challenges and the future outlook of this research field will also be discussed.
Building a Lane Merge Coordination for Connected Vehicles Using Deep Reinforcement Learning

This article presents a data-driven framework for trajectory recommendation in automated and cooperative driving. The considered cooperative driving maneuver is lane-merge coordination, and while the trajectory recommendation can only be communicated to the connected vehicles, in computation of those recommendations both connected and unconnected vehicles are taken into account. The data-driven framework is implemented centrally, comprising of two main components of a traffic orchestrator (TO) and data fusion (DF). The TO predicts the safest trajectories for connected vehicles involved in the lane-merge maneuver. The DF incorporates camera detected vehicles in order to map all vehicles, including connected and unconnected. To this end, the recommendations are built using various state-of-the-art machine learning (ML) techniques, including deep reinforcement learning and dueling deep Q-network. Our evaluations are conducted using the real-system deployed in the test track, with a mix of connected and unconnected vehicles. The results demonstrate the precision of predicted trajectories, and the percentage of successful lane merge achieved deploying different ML techniques.
Development of an Optical Smart Portable Instrument for Fruit Quality Detection

In this study, a portable optical instrument was designed and developed for real-time nondestructive determination of fruit ripeness. A prototype of the instrument using inexpensive parts was developed and calibrated for apple ripeness detection based on moisture content, soluble solids content, pH, and firmness. An array of six optical point sources (light-emitting diodes (LEDs) that emit light at 520-, 670-, 920-, 970-, 1050-, and 1320-nm wavelengths) were selected using visible/near infrarred (Vis/NIR) spectral analysis on apple samples. The instrument was equipped with optical fibers, optical sensors, and an Arduino board for sending and receiving the waves and processing the received signals, as well as controlling the operation of the instrument. The decision tree method was utilized to create a classification model for training the instrument to classify ripe and unripe apples. Test results showed acceptable performance of the developed instrument for apple ripeness estimation and proved useful in classifying fruits into ripe and unripe groups based on their internal quality.
Traffic Signal Control Using Machine Learning

Traffic signal has been a long-standing topic in urban traffic control. Ineffective and inflexible traffic control at urban intersections can often lead to an obstruction in traffic flow and will definitely lead to congestion of traffic. How we manage the traffic in a smart manner is a big challenge in urban traffic management. If we introduce new techniques with ways of solving this problem then it will benefit the urban areas. As traffic light systems are everywhere it would be tough to change the system and we also need to cross certain barriers to achieve this task and instead of changing the current system and bringing up new things if we just solve this issue by making some changes in the existing software then it would cut down a lot of other barriers too. All we need to do is just add some algorithms to main software. With recent advances in machine learning, especially reinforcement learning (RL), traffic signal control using advanced machine learning techniques represents a promising solution to tackle this problem. The performance of the proposed method is comprehensively compared with two traditional alternatives for controlling traffic lights. Simulation results indicate that the proposed method significantly reduces the total delay in the network when compared to the alternative methods. Adjacent traffic light intersections will work independently and yet cooperate with each other to a common goal of ensuring the fluency of the traffic flow within traffic network. The experimental results show that the Q-Learning algorithm is able to learn from the dynamic traffic flow and optimized the traffic flow.
RSS: An Energy-Efficient Approach for Securing IoT Service Protocols Against the DoS Attack

Authentication protocols are powerful tools to ensure confidentiality as an important feature of Internet of Things (IoT). The Denial-of-Service (DoS) attack is one of the significant threats to availability, as another essential feature of IoT, which deprives users of services by consuming the energy of IoT nodes. On the other hand, computational intelligence algorithms can be applied to solve such issues in the network and cyber domains. Motivated by this, this article links these concepts. To do so, we analyze two lightweight authentication protocols, present a DoS attack inspired by users’ misbehavior and suggest a solution called received signal strength, which is easy to compute, applicable for resisting against different kinds of vulnerabilities in Internet protocols, and feasible for practical implementations. We implement it on two scenarios for locating attackers, investigate the effects of IoT devices’ internal error on locating, and propose an optimization problem to finding the exact location of attackers, which is efficiently solvable for computational intelligence algorithms, such as TLBO. Besides, we analyze the solutions for unreliable results of accurate devices and provide a solution to detect attackers with less than 12-cm error and the false alarm probability of 0.7%.
A Cloud-Edge-Aided Incremental High-Order Possibilistic c-Means Algorithm for Medical Data Clustering

Medical Internet of Things are generating a big volume of data to enable smart medicine that tries to offer computer-aided medical and healthcare services with artificial intelligence techniques like deep learning and clustering. However, it is a challenging issue for deep learning, and clustering algorithms to analyze large medical data because of their high computational complexity, thus hindering the progress of smart medicine. In this article, we present an incremental high-order possibilistic c-means algorithm (IHoPCM) on a cloud-edge computing system to achieve medical data coclustering of multiple hospitals in different locations. Specifically, each hospital employs the deep computation model to learn a feature tensor of each medical data object on the local edge computing system, and then uploads the feature tensors to the cloud computing platform. The high-order possibilistic c-means algorithm is performed on the cloud system for medical data clustering on uploaded feature tensors. Once the new medical data feature tensors are arriving at the cloud computing platform, the incremental high-order possibilistic c-means algorithm (IHoPCM) is performed on the combination of the new feature tensors and the previous clustering centers to obtain clustering results for the feature tensors received to date. In this way, repeated clustering on the previous feature tensors is avoided to improve the clustering efficiency. In the experiments, we compare different algorithms on two medical datasets regarding clustering accuracy and clustering efficiency. Results show that the presented IHoPCM method achieves great improvements over the compared algorithms in clustering accuracy and efficiency.
Dietary Fat Quality and Pre-diabetes: A Case-control Study

Background: The relationship between dietary fat quality (DFQ) indices and pre-diabetes has not been well studied. This study aimed to determine the association of DFQ indices and fatty acid intake with pre-diabetes. Methods: This case-control study included 150 subjects with normal fasting blood glucose (FBG) and 147 pre-diabetic subjects. Dietary intake was assessed by a validated food-frequency questionnaire. DFQ indices including atherogenicity (AI) and thrombogenicity (TI), the ratios of hypo- and hypercholesterolemic (h:H), polyunsaturated:saturated (P:S) and n-3:n-6 polyunsaturated fatty acids were calculated. FBG test and 2-hour oral glucose tolerance test (OGTT) were measured. Results: After adjustment for some confounding variables, a positive association was found between intake of total saturated fatty acids (SFA), myristic acid, palmitic acid, and pre-diabetes, and a negative association was observed among n-3 polyunsaturated fatty acids, eicosapentaenoic, docosahexaenoic and arachidonic acids intake and pre-diabetes. AI was found to be positively associated with pre-diabetes (OR 6.68, 95% CI 2.57-17.34). An inverse relationship was observed between n-3:n-6 (OR 0.37, 95% CI 0.14-0.93) and h:H (OR 0.20, 95% CI 0.07-0.52) ratios with pre-diabetes. Conclusions: Higher intake of dietary n-3 fatty acids was adversely, whereas SFA intake was positively related to pre-diabetes morbidity. DFQ indices may be a useful measure to investigate fat intakes and blood glucose disturbances.