Miracle-dz/UniFAR-FTUs huggingface dataset:
Plant zonation in irregularly flooded salt marshes: relative importance of stress tolerance and biological interactions

1 Most studies of salt marsh plant zonation have been at middle to high latitudes of the northern hemisphere, in euhaline or periodically hypersaline marshes with regular tides. In this study, we examined plant zonation in an irregularly flooded marsh in southern Brazil. Pore water characteristics were compared in four vegetation zones across a marsh elevation gradient. Reciprocal transplants between vegetation zones and removal experiments were performed to examine species interactions in low and mid marshes. 2 There was no distinctive gradient of physical stress across the elevation of irregularly flooded low and mid marshes. Moreover, the three dominant plants, Spartina alterniflora, Spartina densiflora and Scirpus maritimus, were able to grow across the entire elevation gradient, i.e. within zones normally occupied by the other species. The only exception was Spartina alterniflora, which was strongly limited by selective herbivory by the crab Chasmagnathus granulata in the Scirpus maritimus zone. 3 Although intra‐ and interspecific competition reduced growth of all three species, no competitive hierarchy was found in any vegetation zone. 4 These results suggest that, as in tidal marshes of the north hemisphere, competition is important in structuring salt marsh plant communities. In contrast, however, plant zonation in irregularly flooded marshes cannot be explained by displacement of competitive subordinates to physically stressful habitats. The roles of founder effects and selective herbivory in such marshes therefore merits further investigation.
Does scale‐dependent feedback explain spatial complexity in salt‐marsh ecosystems?

Complexity theory highlights scale-dependent feedback mechanisms as an explanation for regular spatial patterning in ecosystems. To what extent scale-dependent feedback clarifies spatial structure in more complex, non-regular systems remains unexplored so far. We report on a scale-dependent feedback process generating patchy landscapes at the interface of intertidal flats and salt marshes. Here, vegetation was characterized by Spartina anglica tussocks, surrounded by erosion gullies. To demonstrate the presence of a scale-dependent feedback, we determined if vegetation induced habitat modification resulted in local facilitation and large scale-inhibition of plant growth. Field surveys revealed that larger tussocks have deeper gullies, suggesting that gully erosion is caused by increased water flow around tussocks. This was confirmed by flume experiments, showing that feedback effects vary with current velocity and water depth. Transplantation of small Spartina units inside and just outside present tussocks revealed that the growth of Spartina transplants compared to transplant growth on bare sediment was higher within the raised Spartina tussocks, but lower in the gully just outside Spartina tussocks, providing clear evidence of scale-dependent feedback. Our results emphasize that scale-dependent feedback is a more general explanation for spatial complexity in ecosystems than previously considered.
VOCALIZATIONS OF THE SEI WHALE BALAENOPTERA BOREALIS OFF THE HAWAIIAN ISLANDS

ABSTRACT Little is known about the sounds produced by the Sei Whale Balaenoptera borealis and no recordings have been made in their presence in the Pacific Ocean. This research presents sounds recorded in the presence of Sei whales near the Hawaiian Islands in November, 2002. A total of 107 vocalizations, including two variations of low-frequency downswept calls, were measured. Two of these calls were sweeps from 100 Hz to 44 Hz, over 1.0 seconds. The second call type (n=105) consisted of low- frequency calls which swept from 39 Hz to 21 Hz over 1.3 seconds. These calls are different from sounds attributed to Sei whales in the Atlantic and Southern Oceans, where recordings were made only in the summer months. These sounds are similar, however, to sounds attributed to fin whales in Hawaiian waters. Additional studies are needed in order to understand the spatial and temporal variation in the vocal repertoire of Sei and Fin whales in the Pacific Ocean.
Assessment of Risk of Type 2 Diabetes Mellitus with Stress as a Risk Factor using Classification Algorithms

Rising prevalence of type 2 diabetes mellitus is a vital health concern today, not only in India but across the world. Several factors including dietary habits, genetics, lack of physical exercise and stress are known to affect the risk of type 2 diabetes. Although awareness has increased to some extent, many people with diabetes have limited knowledge about the risk factors before the diagnosis of disease. For chronic disease prevention there is a necessity to find out such risk factors and manage them appropriately. Statistical techniques can be employed to understand the risk of type 2 diabetes in different age group of people. The objective of the research was to evaluate relationship among stress and type 2 diabetes in people with different age groups by a statistical tool. The proposed method uses three machine learning classifiers namely Support Vector Machine (SVM), Logistic Regression and Random Forest (RF) to detect type 2 diabetes at an early stage. To develop an adaptive model the preprocessing step has been applied. The accuracy of predicting diabetes using SVM, Random Forest and Logistic Regression was 80.17%, 79.37%, 78.67% respectively. The results suggest that as compared to Random Forest and Logistic Regression, SVM is better in predicting occurrence and progress of type 2 diabetes mellitus with stress as a risk factor.
Sentiment Mining of Product Opinion Data

Sentiment Analysis has gotten a focal point of consideration for the retrieving of web information and text corpora. At the point when we talk about sentiment analysis, it investigates the people's criticism or conclusion or audits in the wake of removing those reviews from various stages. While, when we find out about Sentiment Analysis, it recognizes the mining or analysis, which are communicated through content and afterward we investigate it. The fundamental goal of Sentiment Analysis is to reason feelings and ideas. In this paper the research work has done sentiment analysis on Amazon Reviews. The data set used is Amazon Reviews on Unlocked Mobile phones dataset of 413840 records. There are number of columns for the dataset like Product Name, Price, Rating, Brand Review text and the count of people for whom the review was helpful. But the research work has used on the Rating and Reviews columns. The research work has applied bag of words, tf-idf and n-grams techniques. It was found that n-gram with bag of words approach gave a maximum testing accuracy of 97% and AUCROC score of . 967. Using deep learning approaches and their comparing with used ones is left as future work.
Níveis protéicos na ração de frangos de corte na fase de crescimento

O objetivo deste trabalho foi determinar o nivel minimo de proteina bruta para atender as exigencias nutricionais de frangos de corte Hubbard, machos e femeas, na fase de crescimento. Oitocentos e oitenta pintos machos e femeas de 22 a 42 dias de idade foram distribuidos ao acaso em esquema fatorial 5x2 (niveis de proteina bruta x sexos), com quatro repeticoes de 22 aves. Os niveis de proteina testados foram 15%, 17%, 19%, 21% e 23%. Houve efeito quadratico dos niveis de proteina no ganho de peso e na conversao alimentar dos machos. Em relacao as femeas, o efeito foi quadratico no ganho de peso e linear na conversao. A relacao entre o rendimento de carcaca e o nivel de proteina bruta da racao foi linear e independente do sexo. O consumo de racao, a gordura abdominal e o rendimento de peito foram influenciados apenas pelo sexo. Recomenda-se 21,70% de proteina bruta para os machos e 19,00% para as femeas, na fase de crescimento.
SIRT1 LEVEL DIFFERENCES AMONG OLD RATS, STREPTOZOTOCIN-INDUCED DIABETIC RATS, AND D-GALACTOSE-INDUCED AGING RATS

Introduction: The Sirtuin 1 (SIRT1) level is suspected to be lower in older ages. In a study of rats, aging can be induced by D-galactose. Various degenerative diseases can also develop from streptozotocin induction (rat models for diabetes mellitus). This study aimed to verify SIRT1 level differences among old rats, D-galactose-induced diabetic rats and streptozotocin- induced aging rats. Material and Methods: A total of 20 female Wistar rats aged four months was divided into five groups of 4 rats each. Group K1 was directly terminated, K2 and K3 were kept until 18 and 33 months old, respectively, and later terminated. Rats in the K4 group were induced with streptozotocin at a dose of 65 mg/kg BW and nicotinamide at 120 mg/ kg BW and kept for one month. Rats in the K5 group were induced by 300 mg/kg BW of D-galactose for one month. Blood specimens were taken to examine SIRT1 levels using ELISA. The statistical test used in this study was the Kruskal-Wallis test (95% confidence level). Results: SIRT1 levels in rats aged 4, 18, and 33 months, diabetic rat models, and D-galactose-induced aging were 0.43 ± 0.12, 0.58 ± 0.15, 0.30 ± 0.01, 0.25 ± 0.13, and 0.21 ± 0.05, respectively (p=0.028). Conclusions: D-galactose- induced aging rat models had the lowest SIRT1 level compared to 33-month-old rats and diabetic rat models.
Unjuk kerja k-nearest neighbor untuk alihaksara citra aksara Nusantara

The concept of classification using the k-nearest neighbor (KNN) method is simple, easy to understand, and easy to be implemented in the system. The main challenge in classification with KNN is determining the proximity measure of an object and how to make a compact reference class. This paper studied the implementation of the KNN for the automatic transliteration of Javanese, Sundanese, and Bataknese script images into Roman script. The study used the KNN algorithm with the number k set to 1, 3, 5, 7, and 9. Tests used the image dataset of 2520 data. With the 3-fold and 10-fold cross-validation, the results exposed the accuracy differences if the area of the extracted image, the number of neighbors in the classification, and the number of data training were different.
Short Periods of Water Stress during Seed Filling, Leaf Senescence, and Yield of Soybean

The effects of short periods of water stress during seed-filling on leaf senescence, seed-fill duration, and yield of soybean [Glycine max (L.) Merrill] are not well understood. Short stress periods were investigated in two greenhouse experiments with cultivar Elgin 87 grown in soil-filled pots. All pots received adequate water until the beginning of growth stage R6 when a continuous water-stress treatment (pots received 40% of the water needed to bring controls to pot capacity) was initiated and maintained until maturity. Water stress was relieved in other pots (watered as the control) after 5 or 13 d in Exp. 1 and 3 or 6 d in Exp. 2. Each treatment was replicated six to eight times in a completely randomized design. The carbon exchange rate was rapidly reduced by continuous water stress resulting in earlier maturity, significantly lower yield (39%), and smaller seeds (25-33%). The carbon exchange rate rapidly increased to near control levels in the early stress-relief treatment, but it was always less than the control for the rest of seed filling. These plants matured sooner and produced significantly lower yields (10-23%) and smaller seeds (9-17%) than control plants. Late stress relief also reduced yield and seed size relative to the control. Yield and seed size of both stress relief treatments, however, were greater than the continuous stress treatment. Water stress-induced acceleration of senescence could not be stopped by eliminating the stress after a short period. Short periods of water stress during seed filling may, therefore, have larger than expected effects on yield.
Computer Aided Diagnosis System for Classification of Abnormalities in Thyroid Nodules Ultrasound Images using Deep Learning

: Thyroid nodules, which are abnormal cell growth that forms a lump in the thyroid gland occurs in more than 50% of the adult population. While ultrasonography is a commonly used for diagnosis because it is non-invasive, non-radioactive, relatively inexpensive and widely available, the usual visual interpretation results in subjective interpretation, inter-observer variability and it’s a time-consuming process. In addition, different stages of malignancy may not be detected, even in existing Computer Aided Diagnosis (CAD) systems. Therefore, there is need for CAD systems that can classify thyroid nodules into multiple stages of malignancies. In this work, we developed a classification system that classifies ultrasonic thyroid images into Thyroid Imaging Reporting and Data System (TIRADS) classes using convolutional neural network. Histogram equalization and adaptive filtering were used to improve the image contrast and noise removal respectively, while transfer learning with Alexnet was used to classify into 6 TIRADS classes. The developed system achieved an overall performance of 92% accuracy, 91% sensitivity and 99% specificity. The work will provide a second opinion, aid early and more accurate detection, thereby enhance treatment and management procedures.
Efficiency of Electric Fishing for Salmonids in Relation to River Width

The efficiency of electric fishing for salmonids was found to decrease with increasing river width. The results demonstrated that mean efficiencies in excess of 50% could be obtained using two anodes up to a river width of about 6.5 m and using three anodes up to a river width of about 11 m. Yearling and older fish were captured more efficiently than fry at equivalent river widths and this was discussed in relation to differences in their behaviour.
Enhanced Underwater Balanced Co-operative Routing Protocol

Underwater wireless sensor networks (UWSNs) is an developing area for research in the wireless sensor networks (WSN) area. The normal method is to adapt for underwater use presently accessible terrestrial architectures and well-proven architectures. Underwater Wireless Sensor Networks (UWSNs) have drawn a lot of concentration to help multiple applications such as tracking pollution, tsunami warnings, offshore exploration, tactical tracking, etc. For many applications, the efficiency and reliability of the network in terms of high performance, energy conservation, low bit error rate (BER) and reduced delay are prerequisites. However, UWSN's unique characteristics such as low bandwidth available, big delay in propagation, extremely vibrant network topology, and high probability of error pose many difficulties in the development of effective and reliable communication protocols. Therefore, in this proposed work, along with its mathematical model, we suggest a protocol that focuses on improving network reliability and effectiveness through cooperative routing and sink mobility. For reliable data transmission, cooperative transmission is well known. Based on their residual energy data and depth , prospective relay and target nodes for cooperative routing are chosen in this algorithm. Data from the source node is transferred in a cooperative way to the target node via the relay node. Mobile Sinks collect information straight from the nodes of the location. We consider as selection parameters the depth threshold of the source node, the residual energy of the destination nodes/ potential relay and the SNR of the relating source node to the potential relay / destination node. In this work, two distinct selection criteria for partner nodes are also introduced and contrasted. Partner node selection (relay / destination node) for cooperative routing should be carried out on the grounds of a certain criterion in order to achieve efficient outcomes. Based on the extensive simulations carried out in MATLAB, we note that our suggested method increases performance in terms of energy efficiency, network life and decreases BER relative to the existing depth-based routing protocols.
A Meta Classification Model for Stegoanalysis using Generic NN

The core idea behind deep learning is that comprehensive feature representations can be efficiently learned with the deep architectures which are collected of stacked layer of trainable non linear operation. However, because of the diversity of image content, it is hard to learn effective feature representations directly from images for steGAnalysis. SteGAnalysis may be generally figured as binary classification issue. This technique, which is called a universal/blind steGAnalysis, will become the principle stream around current steGAnalytic algorithms. In the preparation phase, effective features which are sensitive with message embedding are concentrated on highlight possibility control by steGAnographier. Then, a binary classifier will be discovered looking into pairs from claiming blanket pictures and their relating stegos pointing with Figure a limit on recognize steGAnography. On testing phase, those prepared classifier is used to anticipate labels from claiming new enter pictures. Past exploration indicated that it will be rather critical to power spread Characteristics Also stego offers to be paired, i. e. SteGAnalytic offers from claiming spread pictures And their stego pictures ought further bolstering be safeguarded in the preparing situated. Otherwise, breaking cover-stego pairs in distinctive sets might present biased error and prompt to a suboptimal execution. Proposed approaches have to fix the kernel of first layer as the HPF (high-pass filter). It is so-called pre-processing layer. We suggested another technic with characteristic decrease done which characteristic Choice and extraction And classifier preparation need aid performed at the same time utilizing a generic calculation. That generic calculation optimizes An characteristic weight vector used to scale the individual features in the unique example vectors. A masker vector may be likewise utilized to concurrent Choice of a characteristic subset. We utilize this technobabble clinched alongside mix with those RESNET, and look at the outcomes with established characteristic Choice and extraction systems.
NUEVA ESPECIE DEL GENERO ESTOLA FAIRMAIRE et GERMAIN 1859, PARA CHILE (COLEOPTERA: CERAMBYCIDAE, DESMIPHORINI)

Se describe una nueva especie del genero Estola para Chile, basado esencialmente en las figuras de genitalia masculina y femenina. Esta especie, que ataca la Araucaria araucana, se diferencia de las otras dos especies chilenas del genero particularmente por su tamano y por la forma de la espina del pronoto
Learning to Optimize Non-Rigid Tracking Supplementary Material

Nonrigid Dataset Fig. 1 shows the examples in the collected non-rigid dataset. Similar to the ScanNet, the RGB-D videos are captured via iPad mounted Structure Sensor. The depth frames are recorded at a resolution of 640×480. A variety of dynamic objects are included: animals, adults, children, cloth, furniture, etc. The backgrounds vary from static scenes to dynamic ones with multiple moving objects. Refer to [1] for more details.
Evaluating dialogue breakdown detection in chat-oriented dialogue systems

The task of detecting dialogue breakdown, the aim of which is to detect whether a system ut-terance causes dialogue breakdown in a given dialogue context, has been actively investigated in recent years. However, it is not clear which evaluation metrics should be used to evaluate dialogue breakdown detectors, hindering progress in dialogue breakdown detection. We propose an approach of ﬁnding appropriate metrics for evaluating such detectors. In our approach, we ﬁrst enumerate possible evaluation metrics then rank them on the basis of system ranking stability and discriminative power. By using the submitted runs (results of dialogue breakdown detection of participants) of a dialogue breakdown detection challenge, we experimentally found that MSE(NB+PB,B) and MSE(NB,PB,B), which represent the mean squared error calculated by comparing a detector’s output distribution and a gold distribution, are appropriate metrics for dialogue breakdown detection.
Growth habits and crown architecture of Betulapubescens Ehrh. of seed and sprout origin

Patterns of height increment and ramification in Betulapubescens Ehrh. of sprout and seed origin were studied at Kannus (63°53′ N) during the first few growing seasons, 1982–1985, employing trees of various ages (0–15 years). Sprouts developed very much more rapidly than seedlings during the first three seasons, as a consequence of the free growth pattern and associated pronounced growth flushes. Their annual height increment declined somewhat after a few years, however, whereas that of trees of seed origin remained constant or increased slightly. The mode of height growth in birches over 10 years of age appeared to approach the short-duration growth model. Branches of sprouts also grew more than those of seedlings, in the first few growing seasons, with distinct differences in branching pattern visible between the two tree forms, and also between sprouts originating from buds located above and below ground. Young sprouts used practically all buds to form branches and short shoots, giving them a bush-like.
Delayed Germination of Seeds: A Look at the Effects of Adult Longevity, the Timing of Reproduction, and Population Age/Stage Structure

The effects of adult longevity, the timing of reproduction, and population age/stage structure on the evolution of seed dormancy are explored in both constant and variable environment models. In the constant environment models complete germination is the evolutionarily stable strategy (ESS) regardless of adult longevity. Incorporating a cost of reproduction on subsequent survival does not alter this result. In contrast, in a variable environment changes in adult longevity can exert a strong selection pressure against seed dormancy. Incorporating a cost of reproduction for iteroparous species reduces adult longevity, which selects for more seed dormancy. The magnitude of the change in ESS germination probability depends on several factors, including which life-history stage is variable (e.g., fecundity, seedling survival), whether seeds can detect favorable sites for establishment, and the age/stage structure of the population. In general, increases in adult longevity select against seed dormancy, but exceptions to this pattern are discussed. The idea that established plant traits are uncoupled from those of the regenerative phase, as assumed by J. P. Grime's competition-stress-ruderal model, is considered critically.
Smart Vehicle Parking Monitoring System using RFID

With the vast growing influx of population in the developed, industrially and technologically sound urban cities, an urgent need to make the cities smart is surmounted. The cities are made smart utilizing data sharing, artificial intelligence, machine learning, analytics, and thousands of RFID tags and sensors. One of the significant concerns of today's smart cities is the growing need to manage the vehicles on-road as well as to create sufficient and well-managed parking lots to prevent urban areas from traffic congestion. This leads to a call for highly automated parking management system self-sufficient in guiding the driver to an available parking space in the nearby area. In this paper, a real-time prototype of the smart parking system (S.P system) based on Internet of Things (IoT) is discussed. The proposed smart parking system works on an electronic device that collects the parking availability status and assists drivers in finding and selecting the desired parking space among the available parking spaces that effectively reduces the traffic problems and mismanagement across the cities to a great extent.