Miracle-dz/UniFAR-FTUs huggingface dataset:
Planning for the persistence of river biodiversity: exploring alternative futures using process‐based models

Summary 1. Planning for the conservation of river biodiversity must involve a wide range of management options and account for the complication that the effects of many actions are spatially removed from these actions. Reserve design algorithms widely used in conservation planning today are not well equipped to address such complexities. 2. We used process-based models to estimate the expected persistence of river biodiversity under alternative catchment-wide management scenarios and applied it in the Hunter Region (37 000 km²) in southeastern Australia. 3. The biological condition of 12 197 subcatchments was estimated using a multiple linear regression model that related assessments of the integrity of macroinvertebrate assemblages to human-induced disturbances at river sites. The best-fit model (R2 = 0.76) used measures of both local and catchment-wide disturbances as well as elevation and distance from source as predictor variables. Based on the outputs of this model, we estimated that substantial loss of river biodiversity had occurred in some parts of the coastal fringes and the lower parts of the larger river systems. The most affected river type was small, low-gradient streams. 4. The predicted biodiversity condition together with river types based on macroinvertebrate assemblages and abiotic attributes was used to estimate a biodiversity persistence index (BDI). 5. A priority value for each subcatchment was calculated for different actions by changing the disturbance values for that subcatchment and calculating the resulting marginal change in regional BDI. Maps were thereby created for three different types of priority: catchment protection priority, catchment restoration priority and river section conservation priority. 6. The subcatchments of high catchment protection priority for river biodiversity were mostly in the uplands and within protected areas. The river sections of high conservation priority included many coastal lowland rivers in and around protected areas as well as many upland headwater streams. Subcatchments of high priority for catchment restoration were mostly in coastal areas or lowland floodplains. 7. This approach may be particularly well suited to guide the integrated implementation of three place-based protection strategies proposed for freshwaters: focal areas, critical management zones and catchment management zones.
Model of Transient Changes in Arctic and Boreal Vegetation in Response to Climate and Land Use Change

One of the greatest challenges in global-change research is to predict the future distribution of vegetation. Most models of vegetation change predict either the response of a patch of present vegetation to climatic change or the future equilibrium distribution of vegetation based on the present relationship between climate and vegetation. Here we present a model that is, to our knowledge, the first model of ecosystem change in response to transient changes in climate, disturbance regime, and recruitment over the next 50-500 yr. The frame-based model uses quantitative and qualitative variables to de- velop scenarios of vegetation change from arctic tundra to boreal forest in response to global changes in climate (as predicted by general circulation models (GCMs)), fire, and land use. Seed availability, tree growth rate, and probability of fire were the model param- eters that most strongly influenced the balance between tundra and boreal forest in tran- sitional climates. The rate of climatic warming strongly affected the time lag between the onset of climate change and the simulated ecosystem response but had relatively little effect on the rate or pattern of ecosystem change. The model calculated that, with a gradual ramped change of 3? C in the next century (corresponding to average rate of warming predicted by GCMs), any change from tundra to forest would take 150 yr, consistent with pollen records. The model suggested that tundra would first be invaded by conifer forests, but that the proportion of broad-leaved deciduous forest would increase, reflecting increased fire frequency, as climatic warming continued. The change in fire frequency was determined more strongly by climatically driven changes in vegetation than by direct climatic effects on fire probability. The pattern of climatic warming was more important than the rate of warming or change in precipitation in determining the rate of conversion from tundra to forest. Increased climatic variability promoted ecosystem change, particularly when oscil- lations were long relative to the time required for tree maturation. Management policies related to logging and moose-predator control affected vegetation as much or more than did changes in climate and must be included in future scenarios of global changes in ecosystem distribution. We suggest that frame-based models provide a critical link between patch and equilibrium models in predicting ecosystem change in response to transient changes in climate over the coming decades to centuries.
Personality Assessment Using Social Media for Hiring Candidates

Personality analysis is an intuitive ability of humans, carried out every day with multiple people, and for innumerable reasons. Personality profiling, specifically, has several real-life applications, such as mental health screening tests, screening during human resource interviews, etc. Hiring candidates is one of the most crucial and time-consuming processes for any company. Personality Analysis using social media is an actively developing field. It will help in the job hiring process to get an overall idea of the candidate's ideas and ideals, providing a consistent and fair ranking policy. This system aims to automate the personality assessment process by analyzing the text extracted from his/her tweets, and suggests general job roles suitable for the candidates. The models used for personality analysis are Myers Briggs Type Indicator (MBTI) personality analysis and Big Five personality analysis. The employer from the hiring company will be shown a metric of the applied candidates' personality analysis.
Double Current Limiter High Performance Voltage Level Shifter for IoT Applications

Multi supply voltage design technique is extensively used in modern VLSI designs to tradeoff energy and speed. Level shifters (LSs) are interfacing circuits that allow different voltage domains to be interfaced. This research article proposes a 0.125V- 0.325V input to 1.3V output-voltage Level Shifter that satisfies the requirements of Power, Delay, and voltage level shifting requirements of current IoT applications. The design was achieved using strong current limiters and potency pull down network. The proposed LS was implemented using 130nm technology and incurs static power of 6.6nW propagation delay of 10ns at the level shifting from 0.2V to 1.25V which is appropriate for IoT applications.
Microservice Orchestration for Process Control in Industry 4.0

New manufacturing applications in Industry 4.0 (I4.0) focus on the combination of industrial informatics and automation technologies, including the Industrial Internet of Things, Network Control Systems, Service Oriented Architectures and Cloud Computing. The great challenge of these applications is to promote the integration between these technologies, equipment and systems allocated at different hierarchical levels of industrial systems, making automation collaborative through the use and sharing of services. This paper focuses on the study, implementation and performance analysis of microservices orchestration for process control applications in I4.0. The Microservice-Oriented Architecture is described, as well as the development of microservices related to process control. The microservice orchestration is evaluated through experimental results considering a process control loop and the performance analysis of the service communication.
Blood Mixers for Transfusion Therapy:Photoplethysmogram application for blood velocity determination

Photoplethysmogram is an image of blood flow changes in the human body. It isn’t a simple shape signal rather it has at least six principle parameters form who derivate another useful. In the last decade, the PPG was exploited in order to extract more useful information about physiologic parameters. The current paper will focus on the blood flow velocity where this feature has a major implication in the blood mixer device. It needs to constantly monitor the transfused blood volume with the most accurate level. In transfusiological practice, special attention is paid to the accuracy of donation. The accuracy of donation means the correlation of a given volume and the resulting volume of the blood bag. Therefore, implementing the PPG principle to this device it can offer a good advantage at measuring the blood flow. This article is part of the work devoted to the modernization and development of new equipment for transfusion therapy based on LLC Lidkor production.
REVIEW OF THE PHILIPPINE GENERA CHROTOMYS AND CELAENOMYS (MURINAE) AND DESCRIPTION OF A NEW SPECIES

Abstract The murine genera Celaenomys and Chrotomys comprise a group of semifossorial, vermivorous rodents endemic to the Philippines. Analysis of variation within this group supports the recognition of 4 named species occurring on the large islands of Luzon and Mindoro, as well as our description of a 5th species from Sibuyan, a small island in the central Philippines that has remained isolated from the other islands by deep water channels. Examination of cytochrome-b gene sequence data from 4 of the 5 taxa indicates that Celaenomys silaceus may be basal and sister to the other taxa but morphological and chromosomal data do not support the recognition of Celaenomys as a separate genus. Analysis of the sequence data indicates a relatively early separation of the Sibuyan species and a later split between 2 species of Chrotomys on Luzon. Diversification of Chrotomys appears to have involved speciation associated with both habitat vicariance on Luzon and overwater dispersal to neighboring islands. Most of the members of this clade are restricted to mid- or high-elevation forests, have limited geographic ranges within the archipelago, and some may be imperiled due to loss of natural habitat.
Skin Lesion Classification using Deep Learning Architectures

Skin cancer is one of the major types of cancers that can arise from various dermatological disorders and can be classified into various types according to texture, structure, color and other morphological features. Identifying the lesions from skin images can be an important step in pre-diagnosis to aid the doctors and infer the medical condition of the patient. Recent work has focused on classifying only melanoma from a given set of skin lesion images. However, some types of skin lesions (Acctinic Keratosis and basal cell carcinoma) can become malignant over a period of time. So by detecting these classes we can say we are cutting down the risk of malignancy and doing the task of early detection. We are able to classify different types of skin lesions (basal cell carcinoma, benign keratosis, dermatofibroma, vascular lesions, melanoma, and melanocytic nevi) with an accuracy of above 80% with Mobilenet, VGG-16 and our custom model which we have designed. With the help of this models, which will be embedded in skin lesion analyzer machines. This can give the patients as well as doctors a good idea of whether or not there is a need for medical attention and can avoid unnecessary panic/false alarms. We are using different deep learning architectures to classify skin lesions with good accuracy relative to existing work.
Deep learning based Surgical Workflow Recognition from Laparoscopic Videos

Technical evolution within the surgical healthcare environment resulted in transformative and innovative surgical advancements in biomedical science, which require contemplation for further renovation. Systematizing of surgical workflow has immense potential in offering solutions to numerous stipulations of the modern operating room. Cataloging surgical phases are vital in developing context-aware systems that can supervise the surgical procedures, optimize the operating room environment, scheduling of medical staff, and provide automated assistance to the clinical personals. This research has mainly been focused on a deep learning approach to sense and detect phases of a surgical operation. Classification of surgical phases is based on the CNN architecture ResNet50 and performs the rolling average prediction method to accurate the results. The proposed framework automatically recognizes the various phases in the laparoscopic cholecystectomy videos reliably.
Diagonal Unloading Beamforming in the Spherical Harmonic Domain for Acoustic Source Localization in Reverberant Environments

Spherical microphone arrays allow the sound field analysis in three dimensions with the advantage of having the same resolution in all directions. By considering the frequency-independent character of the steering vectors in the spherical harmonic (SH) domain, we propose a very low-complexity SH diagonal unloading (DU) beamforming with a novel frequency smoothing power transform (FSPT) of the covariance matrices. We consider the direction of arrival (DOA) estimation problem of acoustic sources in reverberant conditions. The DU beamforming provides high resolution directional response since it exploits the subspace orthogonality property of the covariance matrix by the removal or the attenuation of the signal subspaces, obtained through the subtraction of an opportune diagonal matrix from the covariance matrix. The FSPT aims at smoothing the narrowband covariance matrices of the entire set of frequency domain components, and it pursues this goal by minimizing the narrowband error contributions due to reverberation in the broadband frequency smoothing covariance matrix. We analyze the DOA estimation performance using speech signals with simulations and real acoustic data in reverberant conditions. The results show that the proposed SH-DU-FSPT has a DOA estimation performance comparable to that of high resolution state-of-the-art methods with a significant reduction of the computational cost, since the steering directional responses are computed on the broadband frequency smoothing covariance matrix.
ELEVATED CO2 AND TEMPERATURE ALTER THE RESPONSE OF PINUS PONDEROSA TO OZONE: A SIMULATION ANALYSIS

We investigated the potential impact of projected future temperature and CO2 concentrations in combination with tropospheric O3 on the annual biomass increment of Pinus ponderosa Doug. ex Laws. TREGRO, a process-based whole-tree growth model in which trees experienced a seasonal drought, was used to study the interactions of CO2, temperature, and O3 on tree growth along a latitudinal gradient in California, Oregon, and Washington, USA. The annual biomass increment increased in proportion to CO2 concen- tration, although the magnitude varied among sites. Increasing air temperature ( 11.38C) increased growth at most sites. Elevated CO2 increased the temperature optimum for growth at four sites and decreased it at two sites. The annual biomass increment decreased with increasing O3 exposure. The differences in O3 effects among sites were primarily controlled by differences in precipitation. Although increasing CO 2 can reduce the O3 impact, it does not eliminate the impact of O3. Elevated CO2 would enhance tree growth more if O3 exposures were reduced, especially in the more polluted sites. The greatest benefit for tree growth would come from reducing O3 exposures in the most polluted sites, but we must also consider locations that have high inherent O 3 sensitivity because of their mesic con- ditions. Limiting the increase of O 3 levels in those areas will also increase tree growth.
Near-Field Noncircular Sources Localization Based on Fourth-Order Cumulant

This paper presents a cumulant-based algorithm for near-field noncircular sources localization with a symmetric uniform linear array. It first constructs three extended matrices. Then, based on the rotational invariance property in extended cumulant-domain signal subspace, coarse direction-of-arrival (DOA) estimates are obtained. With the course results used as reference, the algorithm is able to disambiguate the cyclic phase ambiguities when the equivalent sub-array spacing exceeds a half wavelength. Thus, higher precision DOA estimates can be obtained. Finally, with the estimated DOAs, only one-dimensional searching is needed to obtain the range estimates via rank-reduction algorithm. The proposed algorithm avoids two-dimensional searching and parameters pairing. In addition, compared with the existing near-field noncircular sources localization algorithm, the significant characteristic of the proposed algorithm is that it exploits cumulant and the noncircularity of signal to achieve extended steering vector. Cumulant is insensitive to Gaussian (white or color) noise. Consequently, the proposed one provides DOA estimates with improved precision especially at low signal-to-noise ratios. Furthermore, it doubles the number of detectable sources. Total least square ESPRIT algorithm is exploited to yield search free estimates of near-field bearing parameters. Computer simulations are carried out to demonstrate the superiority of the proposed algorithm.
Morfometria e distribuição de leite alveolar e cisternal na glândula mamária de vacas Holandesa e Girolanda

The milk distribution in alveolar and cisternal portions and the mammary gland morphometry were studied using 14 cows, being seven Holstein and seven Girolanda, with same parity and days in lactation, and milked twice a day. Milk yield was measured everyday, whereas alveolar and cisternal fractions were determined once a week. During the experiment, ultrasound scan measurements and morphometrical measures of the mammary gland were also performed. Girolanda cows had udder and teats larger than Holstein cows. Diameter, wall thickness, and length of the teat channel measured from ultrasound images were higher in Girolanda group, but cisternal area of the mammary gland was larger in Holstein cows. No differences in milk yield and cisternal and alveolar milk fractions between the studied breeds were observed.
Synthesis and Generalization of Parallel Algorithms Considering Communication Constraints

Recently, the opportunities of parallel computing are expanding rapidly in various applications including neural networks and machine learning. It is, however, not at all straightforward to develop an efficient algorithm for each parallel computing environment since communications always introduce overhead in computation. In this paper, we propose a design method of optimum parallel computing under user-specified communication constraints. The basic strategy is to automatically generate optimum scheduling from small instances of the target problem and then they are semi-automatically generalized to much larger problems. Several experiments targeting matrix vector multiplication and convolutional neural networks have been conducted. Their results show the correctness and usefulness of the proposed method as well as its scalability.
The Study of Mechanical Arm and Intelligent Robot

As an important part of the automation industrial system, mechanical arm robot plays an important role in service, exploration, automation engineering and other fields, and has a broad application prospect. The traditional mechanical arm and Sobel edge detection methods have some shortcomings: 1. The PID method is separated from the ontology model and only carries out simple and multiple calculations according to the code of the steering engine, which is not stable enough and will cause more time consumption; 2. In some complex environments, while Sobel edge detection is detecting the shape of objects, the separation between subject and background is not clear, which makes it impossible to obtain accurate object information. Therefore, this paper proposes a new PID method and Canny edge detection algorithm: 1. PID method combined with three-dimensional coordinate system modeling, to achieve a more stable, faster and more robust calculation formula, to complete the mechanical arm grasping function; 2. Using Canny edge detection and three-dimensional coordinate system to analyze the object image to obtain the accurate information of the target object.
Host plant defences and voltinism in European butterflies

Abstract 1. With respect to seasonal availability for herbivores, plants defended by synthesising qualitative compounds differ from those protected by accumulation of quantitative macromolecules, leaf toughness, and low water and/or nutrient content. While the palatability of the former plants remains relatively constant during the season, the palatability of the latter group decreases with leaf age.
Challenges and Perspectives in Control of Ionic Polymer-Metal Composite (IPMC) Actuators: A Survey

Ionic polymer-metal composites (IPMC) are electroactive polymers expected to be used as soft actuators in various practical areas like robotics, biomedicine and micro manipulation systems. Though IPMC actuators have many advantages (lightweight, noiseless operation, low operating voltage, possibility of miniaturization), some of their inherent properties (back-relaxation, hysteresis, high sensitivity to ambient conditions, aging) make their precise and reliable control a challenging task. This paper presents a survey of control methods for IPMC actuators. A systematic overview of the techniques, addressing the main challenges in IPMC control, is provided.
Single-Gateway Multi-Node Mesh Network for a Connected Electric Vehicle Ecosystem

A connected electric vehicle ecosystem can provide us with many benefits such as Better Range prediction, Over the air updates, Collision detection, Vehicle tracking and Traffic law enforcement. At the same time connecting every vehicle to the internet can turn out to be very costly, as each node may require its own internet connection which will be a repetitive cost depending upon the particular ISP providing the service. Using a mesh network of a single gateway and multiple nodes, can bring down the price of implementing such a system.
Structure of the gut of the racer goby Neogobius gymnotrachelus (Kessler, 1857)

The morphological and histological features of the gut of juvenile racer goby Neogobius gymnotrachelus [range of body mass 0·2–0·9 g and standard length (LS) 20·0–38·8 mm] were examined in fish collected from the Wloclawek Reservoir on the Vistula River, Poland. Evidence is provided of the stomachless nature of the gut of the racer goby. The intestine of the juveniles lacks the intestinal bulb. A particular feature of the racer goby gut is the secretory oesogaster (the transitional region where the secretory oesophagus merges into the intestine) with multicellular alveolar glands that secrete via a common duct to the surface between the mucosal folds. The cells in the secretory oesogaster alveolar glands are periodic-acid-Schiff (PAS) positive indicating the presence of neutral mucopolysaccharides. It is hypothesized that the secretory oesogaster is evidence of the loss of the functional stomach in this species. There are two sphincters: the oesogaster–intestinal and the intestinal–rectal in the racer goby gut. It can be concluded that the oesogaster–intestinal sphincter is functionally related to the gastro-intestinal sphincter described in many fish species having a stomach. Enterocytes with a distinct brush border and only a few goblet cells are observed in the epithelium along the whole intestine. The existence of vacuoles in the supranuclear region of the rectal enterocytes is also confirmed.