Miracle-dz/UniFAR-FTUs huggingface dataset:
Trophic Niche Breadth of Falconidae Species Predicts Biomic Specialisation but Not Range Size

Simple Summary The diversity of food consumed and the habitats occupied by species and populations, which is called a trophic niche, play a key role in biogeographic distribution patterns. Niche narrowing is considered a strategy to reduce resource-use overlap and competition among coexisting individuals, populations or species. However, the success of narrowing (specialism) or broadening (generalism) the trophic niche seems to depend on the temporal and spatial predictability of food resources. It is thought that specialist strategies are favoured in homogeneous environments predictable in time and space, while environmental unpredictability promotes generalist strategies that, in turn, allow a greater capacity to colonise new niches, thus tending to increase the geographic range size. Interestingly, although known at a within-population scale, the relationship between diet breadth and environmental heterogeneity at global and interspecific scales has not been explicitly assessed. Using the family Falconidae (Aves, Falconiformes) as a model study, we tested the prediction that those species with a wider diet spectrum will have larger geographic range sizes and inhabit more biomes. Our findings show that trophic breadth was not a good predictor for range size but was for total environmental heterogeneity, with more diet-generalist species occupying a higher number of biomes. Abstract Trophic niche breadth plays a key role in biogeographic distribution patterns. Theory posits that generalist strategies are favoured in a more heterogeneous set of environments across a spatio-temporal gradient of resources predictability, conferring individuals and species a greater capacity for colonising new habitats and thus expanding their distribution area. Using the family Falconidae (Aves, Falconiformes) as a model study, we tested the prediction that those species with a wider diet spectrum will have larger geographic range sizes and inhabit more biomes. We assessed the relationships between trophic breadth (diet richness and diversity) at different taxonomic resolutions of the prey (class and order), range size and biomic specialisation index (BSI; number of biomes inhabited) for the different species. Despite different diet breadth indexes and taxonomic resolutions defined differently the trophic niche of the clade and species, our findings revealed that trophic breadth was not a good predictor for range size but was for total environmental heterogeneity, with more diet-generalist species occupying a higher number of biomes. Diet breadth at the order taxonomic level showed a higher capacity of predicting BSI than at class level, and can be an important ecological trait explaining biogeographic patterns of the species.
Getting permission: how to license & clear copyrighted materials online & off, 2nd edition

If you plan to use any copyrighted material for your own purposes, you need to get permission first from the owners of that work. If you don't, you could find yourself slapped with a lawsuit.Getting Permission tackles the permissions process head on. It shines the light on whom to ask for permission, as well as when -- and how much to expect -- to pay for permission. Comprehensive and easy to read, the book covers:*the permissions process *the public domain *copyright research *fair use *academic permissions *the elements of a license and merchandise agreement *the use of a trademark or fictional character *and much moreGetting Permission includes agreements for acquiring authorization to use text, photographs, artwork and music. All agreements included as tear-outs and on CD-ROM.The 2nd edition of this essential book is completely updated to reflect the latest laws and court decisions. It also covers new directions in permissions rules, such as the "CopyLeft" movement and Copyright Commons.
Trophic Patterns of Freshwater Fish across the Balkan Biodiversity Hotspot

Ecological information regarding trophic patterns and the inherent structure of freshwater aquatic communities is considered fundamental in ecological research. In this study, the trophic patterns of the Greek freshwater fish fauna, belonging to the Balkan biodiversity hotspot, were investigated, and comparisons of freshwater fish species feeding habits among the Greek freshwater ecoregions were performed. The analyses based on the widely used trophic level index and the available composition feeding datasets, along with the utilization of clustering methods, indicated seven major distinct trophic guilds in the Greek ecoregions. The trophic level of the studied fish species ranged from 2.0 to 4.5, thus being within the expected values for freshwater ecosystems, revealing the presence of both top predators and primary consumers. The highest trophic level values were found in the ecoregions of northern Greece. The results also exhibited considerable predominance of higher-trophic-level zooplanktivorous and insectivorous freshwater fish species in the mainland, compared to lower-trophic-level opportunist species in the island-isolated ecoregions. These results could be used for the application of ecosystem-based models and the formulation of conservation and fishery management schemes.
Integrated Vehicle Stability Control and Power Distribution Using Model Predictive Control

There is a growing need for active safety systems to assist drivers in unfavorable driving conditions. In these conditions, the behavior of the vehicle is different than the linear response during everyday driving. Even experienced drivers usually lose control of the vehicle in such situations and that often results in a car accident. Stability control systems have been developed over the past few decades to assist drivers in keeping the vehicle under control. Most of these control systems are comprised of separate modules, each responsible for one task such as yaw rate tracking, sideslip control, traction control or power distribution. These objectives may be in conflict in some driving situations. In such cases, individual controllers fight over priority and produce conflicting control commands, to the detriment of the vehicle performance. In addition, in most stability control systems, transferring the controller from one vehicle to another with a different driveline and actuator configuration requires significant modifications in the controller and major re-tuning to obtain a similar performance. This is a major disadvantage for auto companies and increases the controller design and tuning costs. In this thesis, an integrated control system has been designed to address vehicle stability, traction control and power distribution objectives at the same time. The proposed controller casts all of these objectives in a single objective function and chooses control actions to optimize this objective function. Therefore, the output of the integrated controller is not altered by another module and the optimality of the solution is not compromised. Furthermore, the designed controller can be easily reconfigured to work with various driveline configurations such as all-wheel drive, front or rear-wheel drive. In addition, it can also work with various actuator configurations such as torque vectoring, differential braking or any combination of them on the front or rear axles. Moving from one configuration to another does not change the stability control performance and major re-tuning can be avoided. The performance of the designed model predictive controller is evaluated in software simulations with a high fidelity model of an electric Equinox vehicle. The stability and iii wheel slip control performance of the controller is evaluated in various driving and road conditions. In addition, the effect of integrated power distribution is studied. Experimental tests with two different electric vehicles are also carried out to evaluate the real-time performance of the MPC controller. It is observed that the controller is able to maintain vehicle and wheel stability in all of the driving scenarios considered. The power distribution system is able to improve vehicle efficiency by approximately 1.5% and acts in cooperation with the stability control objectives.
WYKORZYSTANIE ELEMENTÓW UCZENIA MASZYNOWEGO DO MODELOWANIA STĘŻENIA ZANIECZYSZCZEŃ ATMOSFERYCZNYCH: STUDIUM PRZYPADKU PYŁU PM2.5 W SZCZECINIE

pracy przedstawiono możliwość modelowania stężeń zanieczyszczeń w lokalizacji o określonym, stałym profilu emisji przy wykorzystaniu modeli uczenia maszynowego. Jako zanieczyszczenie wybrano pył PM2.5, a jako zmienne objaśniające przyjęto parametry metrologiczne mierzone na stacji synoptycznej. Przeprowadzono uczenie i walidację sześciu różnych modeli na podstawie obserwacji meteorologicznych zarejestrowanych w latach 2013–2018 na stacji IMGW-PIB w Szczecinie (Polska) oraz średniodobowych stężeń pyłu PM2.5 z tego samego okresu zmierzonych na stacji GIOŚ w Szczecinie przy ul. Andrzejewskiego, podzielonych na trzy równoliczne klasy stężeń. Dwa modele, które dawały najdokładniejsze wyniki, zostały szczegółowo przedstawione. Czułość tych modeli, w zależności od klasy stężenia pyłu, zawierała się pomiędzy 0,484 a 0,711. Te dwa modele zostały zastosowane do identyfikacji wzrostu średniodobowych stężeń w trakcie zdarzenia nietypowego – pożaru składowisk odpadów. Stężenia przewidziane w dniach, w których trwał pożar, były zaniżone względem faktycznych stężeń, co pozwala na zastosowanie modeli w identyfikacji zjawisk atypowych, które mają wpływ na stężenia zanieczyszczeń w danym miejscu.
Neonatal Neuroimaging in Neonatal Intensive Care Graduates Who Subsequently Develop Cerebral Palsy

Cerebral palsy is a common cause of physical disability. The New Zealand Cerebral Palsy Register (NZCPR) was established in 2015 and reports national data. Internationally, an early CP diagnosis has been a focus, with imaging and clinical tools used to enable early accurate detection. Accordingly, guidelines are being developed for New Zealand, including a specific pathway for high-risk neonatal intensive care (NICU) graduates, reflecting the high rate of CP in this group. To inform this work, we reviewed imaging data from a retrospective NICU cohort identified from the NZCPR. In these 140 individuals with CP and a confirmed NICU admission during 2000–2019 inclusive, imaging frequency, modality, and rate of abnormality was determined. Overall, 114 (81.4%) had imaging performed in the NICU, but the frequency and modality used varied by gestational subgroup. For infants born at less than 32 weeks gestation, 53/55 had routine imaging with ultrasound, and IVH was graded as none or mild (grade 1–2) in 35 or severe (grade 3–4) in 18 infants. For the 34 infants born between 32–36 weeks gestation, only 13/19 imaged in the NICU were reported as abnormal. For 51 term-born infants, 41/42 imaged in the NICU with MRI had abnormal results.
Real-Time Footprint Planning and Model Predictive Control Based Method for Stable Biped Walking

In order to walk in a physical environment, the biped will encounter various external disturbances, and walking under persistent conditions is still challenging. This paper tries to improve the push recovery performance based on capture point (CP) and model predictive control. The trajectory of zero moment point (ZMP) and center of mass are solved and predicted in a limited time horizon. Online footprint generator is combined with MPC walking pattern generation, which can keep biped stable in the next few steps, and projection of ZMP is used to calculate the next footprint and reach the target CP in an incremental way. Verification of the proposed stable biped walking method is conducted by simulation and experiments.
Image reconstruction using a refined Res-UNet model for medical image retrieval

Measurement of medical data and extraction of medical images with various sensory systems have become a crucial part of diagnosing and treating various diseases. In this contest measurement technology plays a key role in diagnosis. Medical experts usually use previous case studies to identify and deal with the current medical condition. In this context, an expert required to explore the large medical database to search relevant images for the required analysis. Searching such large database and retrieving an image efficiently becomes very tedious task. Therefore, this paper proposed a measurement-based image reconstruction using the refined Res-UNet Framework for Medical Image Retrieval (MIR) for managing such crucial tasks and reduce complexities. The proposed two stage framework consists of an image reconstruction using Res-UNet and index similarity matching of query image with history images. Res-UNet is a vanilla combination of ResNet50 as an encoder that gives latent information of input image, and the decoder from UNet reconstructs the image using latent information. Further, those latent features match similar image features and retrieve indexed images from the medical image database. The efficacy of proposed method was confirmed on benchmark medical image databases such as ILD and VIA/ELCAP-CT for MIR. The proposed framework outperforms the existing methods in the task of MIR.
Iterative learning control - an identification oriented approach

Introduces a new type of iterative learning control (ILC) which seeks the desired input in an appropriate finite dimensional input subspace. The method achieves perfect tracking for a class of uncertain systems without using time derivative of tracking error signals in the learning law. Its effectiveness is demonstrated by experiment using a two-link direct drive arm. One of the distinguish features of this method is that it is regarded as an identification oriented method rather than a pure I/O signal based (or model free) one.
Nicotiana benthamiana γ-Thionin Synthesis Is Induced in Response to Foreign Nucleus-Targeted Proteins

: Pathogenic and symbiotic bacteria secrete protein factors—nucleomodulins—to affect the host cell nucleus. During evolution, plants have acquired a great variety of defense mechanisms, including the synthesis of such antimicrobial peptides (AMPs) as defensins. We have demonstrated that the transient production of a foreign protein containing nuclear localization signal (NLS) in Nicotiana benthamiana leaves leads to the increased expression of the γ -thionin ( Nb γ Thio ) that belongs to the defensin group of AMPs. We hypothesized that Nb γ Thio is induced by the nucleomodulins of pathogenic bacteria and, in particular, in response to their NLSs. We used artiﬁcial nuclear proteins based on green ﬂuorescent protein (GFP) fused with the human prothymosin α NLS or VirE3 NLS from Agrobacterium tumefaciens as mimetics of bacterial effectors. We demonstrated that the super-production of these NLS-containing reporters in the transient expression system in N. benthamiana leaves resulted in the increase in the Nb γ Thio mRNA level. We isolated the Nb γ Thio gene promoter (Pr γ Thio ) and created an expression vector (Pr γ Thio -GUS) directing GUS synthesis in agroinﬁltrated leaves. The co-expression of Pr γ Thio -GUS with 35S-GFP:NLS variants led to the signiﬁcant stimulation of GUS synthesis. We concluded that Nb γ Thio gene expression is activated in response to bacterial nucleus-targeted proteins in the cell and is regulated both at the level of transcription and post-transcription stages.
Multifunctional Robot Grasping System Based on Deep Learning and Image Processing

This paper firstly introduces the general architecture of the multifunctional harvesting robot grasping system; then, deep learning is used to investigate the object target recognition, and a set of target detection algorithm based on convolutional neural network is implemented; then, image processing technology is used to realize the function of target object localization, which can guide the multifunctional harvesting robot to complete the picking of the target multifunctional. The experimental results show that the multifunctional harvesting robot has a small calculation error of multifunctional coordinates and has a strong multifunctional recognition and positioning capability.
Design method and mechanical properties of a new pipe lattice structure

Abstract A new tubular lattice structure is designed based on the "pipe-like" microstructure. Different from the parameter optimization method for classical lattice and the design method of super structured lattice, this method reconstructs the classical lattice to avoid complex new geometric structure design. In addition, it can also ensure that the lattice has stronger mechanical properties while being lightweight. The results show that under the same volume fraction, the stress of the improved and strengthened new pipe lattice structure under the same load are 14% − 39% lower than column lattice respectively, and the deformation has a similar law.
Comparison between Dry-Land and Swimming Priming on 50 m Crawl Performance in Well-Trained Adolescent Swimmers

The purpose of the study was to investigate the effect of dry-land priming (DLP) versus swimming priming (SP) on the 50 m crawl performance of well-trained adolescent swimmers. Thirteen adolescent swimmers were randomly assigned to perform either a DLP or SP 24 h prior to a 50 m sprint crawl time-trial. Baseline measurements included a 50 m sprint crawl time-trial as a control (C) condition, the evaluation of body composition, countermovement jump (CMJ), isometric peak torque (IPT), and rate of torque development (RTD). Rating of perceived exertion (RPE) was obtained following the DLP and SP programs. Both DLP and SP significantly decreased the 50 m crawl time-trial, by −2.51 ± 2.43% and −2.59 ± 1.89% (p < 0.01), respectively, compared with the C time-trial. RPE was not different between DLP and SP (p = 0.919). CMJ performance remained unchanged after DLP and SP programs compared with the C trial (p > 0.05). The percentage decrease in the 50 m crawl after DLP was significantly correlated with the percentage decrease in the 50 m crawl following SP (r = 0.720, p = 0.006). CMJ power, lean body mass, IPT, and RTD were significantly correlated with 50 m crawl performance. These results suggest that both DLP and SP strategies, when applied 24 h prior to a 50 m crawl time-trial, may enhance performance in well-trained adolescent swimmers.
Characteristics of CMOS device isolation for the ULSI age

Scaling requirements for abrupt active-isolation transitions, isolation depth, and isolation planarity are discussed quantitatively. We review how LOCOS and STI isolation are being improved to meet these requirements. Independent of fabrication techniques, we see that a necessary consequence of achieving the desired narrow isolation and abrupt transitions is a discrete edge parasitic. We show that the edge parasitic can be distinguished from the planar channel and can be characterized separately. Edge device sensitivities are investigated with experiment and simulation to show that design and process control of the discrete edge parasitic will be a significant thrust of device engineering for future isolation technologies. <<ETX>>
A hardware-efficient DOA estimation method based on digital channelization receiver

In this paper, we present a novel hardware-efficient direction of arrival (DOA) estimation method based on digital channelized receiver. The proposed method splits the wideband array output into multiple frequency sub-channels and estimates the signal parameters using digital channelization receiver. Based on the accurate signal parameters estimation, signals with different bandwidths are isolated reasonably. Different DOA estimation methods are used to signals with different bandwidths. The proposed channelization based method can improve the output signal noise ratio (SNR). It outperforms those conventional DOA estimation methods on estimation accuracy, especially in real environment. Simulations are presented to demonstrate the performance. The results verify the effectiveness of the proposed method.
Size Matters: Developing Design Rules to Engineer Nanoparticles for Solid Tumour Targeting

Nanotechnology enables the design of highly customizable platforms for producing minimally invasive and programmable strategies for cancer diagnosis and treatment. Advances in this field have demonstrated that nanoparticles can enhance specificity of anti-cancer agents, respond to tumour-specific cues, and direct the visualization of biological targets in vivo. Nanoparticles can be synthesized within the 1 to 100 nm range to achieve different electromagnetic properties and specifically interact with biological tissues by tuning their size, shape, and surface chemistry. However, it remains unclear which physicochemical parameters are critical for delivering nanomaterials to the tumour site. With less than 5% of administered nanoparticles reaching the tumour, engineering of nanoparticles for effective delivery to solid tumours remains a critical challenge to cancer nanomedicine. A more comprehensive understanding of the interplay between the nanomaterial physicochemical properties and biological systems is necessary to enhance the efficacy of nanoparticle tumour targeting. This thesis explores how nanoparticle size and functionalization with cancer cell specific agents impact nanoparticle delivery to tumours. Furthermore, this doctoral work (i) discusses how tumour structure evolves with growth, (ii) elucidates how such changes modulate nanoparticle accumulation, and (iii) identifies how the skin serves as a significant off-target site for nanoparticle uptake. This thesis also demonstrates the utility of empirically-derived parametric models, Monte Carlo simulations, and decision matrices for mechanistically understanding and predicting the impact of nanomaterial features and tumour biology on nanoparticle fate in vivo. These topics establish key design considerations to tailor nanoparticles for enhanced tumour targeting. Collectively, the concepts presented herein form a fundamental framework for the development of personalized nanomedicine and nano-diagnostic agents in the future.
Th1 / Th2 cytokine polarization in milk according to different pathogens causing subclinical mastitis in cows

The aim of this study to determine the Th1/Th2 cytokine balance in milk according to the bacterial species that cause subclinical mastitis in cows. The California Mastitis Test (CMT) was applied to the selected cows. The cows were divided into four groups: cows with negative CMT (n = 45); Escherichia coli (E. coli) group included only cows with E. coli growing in CMT-positive milk samples (n = 45); Streptococcus agalactiae (S. agalactiae) group included cows with only S. agalactiae growing in CMT-positive milk samples (n = 45); Staphylococcus aureus (S. aureus) group included cows with only S. aureus growing in CMT-positive milk samples (n = 45). Somatic cell count (SCC) in fresh milk samples was measured using the DeLaval Cell Counter device. Also, cytokine analyses were performed using Species-specific commercial ELISA kits. Tumor necrosis factor-alpha (TNF-α) and interferon-gamma (IFN-γ) concentrations were relatively high in the E. coli group, but the interleukin (IL)-2 concentration was low. The lowest concentration of IL-4 was found in the CMT-negative group. The highest IL-5 concentration was found in the S. agalactiae group, while the highest milk IL-10 concentration was found in the S. aureus group. Also, T helper (Th1/Th2) polarization shifted towards Th1 in milk with mastitis caused by E. coli. Th1/Th2 polarization was shifted to Th2 in milk with mastitis caused by S. aureus and S. agalactiae. Based on our findings, cellular immunity should be maintained in mastitis cases due to E. coli, and humoral immunity should be supported in mastitis caused by S. aureus and S. agalactiae.