Miracle-dz/UniFAR-FTUs huggingface dataset:
Ecosystem transformation by emerging infectious disease: loss of large tanoak from California forests

1. Few pathogens are the sole or primary cause of species extinctions, but forest disease has caused spectacular declines in North American overstorey trees and restructured forest ecosystems at large spatial scales over the past 100 years. These events threaten biodiversity associated with impacted host trees and other resources valued by human societies even when they do not directly cause host extinction.
Auxin-Cytokinin Interactions in Wild-Type and Transgenic Tobacco

Cytokinins and auxins are important regulators of plant growth and development, but there is incomplete and conflicting evidence that auxins affect cytokinin metabolism and vice versa. We have investigated these interactions in Nicotiana tabacum L. by separate in planta manipulation of levels of the hormones followed by analysis of the induced changes in the metabolism of the other hormone. Cytokinin-overproducing plants (expressing the Agrobacterium tumefaciens ipt gene) had lower than wild-type levels of free IAA, and reduced rates of IAA synthesis and turnover, but there were no differences in the profiles of metabolites they produced from fed IAA. Similarly, auxin-overproducing plants (expressing the A. tumefaciens iaaM and iaaH genes), had lower levels of the major cytokinins than wild-type plants and lower cytokinin oxidase activity, but there were no differences in the profiles of metabolites they produced from fed cytokinins. The data demonstrate that cytokinin or auxin overproduction decreases the content of the other hormone, apparently by decreasing its rate of synthesis and/or transport, rather than by increasing rates of turnover or conjugation. Implications for the importance of cytokinin : auxin ratios in plant development are considered. et al. 1988). Further evidence for the hormones' mutual effects on one another has come from studies of crown gall tissues in which mutations in Agrobacterium genes involved in cytokinin or auxin synthesis, led to changes in concentrations of both auxins and cytokinins (Akiyoshi et al. 1983, Rudelsheim et al. 1987, Ishikawa et al. 1988, McGaw et al. 1988). There are also reports of direct auxinactivation of the cytokinin-catabolising enzyme, cytokinin oxidase (Hare and Van Staden 1994). The data so far amassed on the reciprocal effects of cytokinins on auxins, and auxins on cytokinins, however, is incomplete and conflicting. Our understanding of these hormonal interactions and their role in regulating plant development would therefore be greatly enhanced by separate in planta manipulation of the levels of the hormones, followed by high-resolution, kinetic analysis of the induced changes in the metabolism of the other hormone. In this investigation we have used fully-regenerated, fertile, seedsown, cytokinin and auxin overproducing, transgenic Nicotiana tabacum L. plants to study effects of cytokinin on auxin metabolism and vice versa. The data obtained has given a number of insights into the interactions, or "cross-communication", between the two hormones.
Comparisons of the thermal physiology of water hyacinth biological control agents: predicting establishment and distribution pre‐ and post‐release

Investigations into the thermal physiology of weed biological control agents may elucidate reasons for establishment failure following release. Such studies have shown that the success of water hyacinth biological control in South Africa remains variable in the high‐lying interior Highveld region, because the control agents are restricted to establishment and development due to extreme winter conditions. To determine the importance of thermal physiology studies, both pre‐ and post‐release, this study compared the known thermal requirements of Eccritotarsus catarinensis (Carvalho) (Hemiptera: Miridae) released in 1996, with those of an agent released in 1990, Niphograpta albiguttalis (Warren) (Lepidoptera: Pyralidae) and a candidate agent, Megamelus scutellaris Berg (Hemiptera: Delphacidae), which is currently under consideration for release. The lower developmental threshold (to) and rate of development (K) were determined for N. albiguttalis and M. scutellaris, using a reduced axis regression, and incorporated into a degree‐day model which compared the number of generations that E. catarinensis, N. albiguttalis, and M. scutellaris are capable of producing annually at any given site in South Africa. The degree‐day models predicted that N. albiguttalis (K = 439.43, to = 9.866) can complete 4–11 generations per year, whereas M. scutellaris (K =502.96, to = 11.458) can only complete 0–10 generations per year, compared with E. catarinensis (K = 342, to = 10.3) which is predicted to complete 3–14 generations per year. This suggests that the candidate agent, M. scutellaris, will not fare better in establishment than the other two agents that have been released in the Highveld, and that it may not be worth releasing an agent with higher thermal requirements than the agents that already occur in these high‐lying areas. Thermal physiology studies conducted prior to release are important tools in biological control programmes, particularly those in resource‐limited countries, to prevent wasting efforts in getting an agent established.
A calculus for rational tangles: applications to DNA recombination

There exist naturally occurring enzymes (topoisomerases and recombinases), which, in order to mediate the vital life processes of replication, transcription, and recombination, manipulate cellular DNA in topologically interesting and non-trivial ways [24, 30]. These enzyme actions include promoting the coiling up (supercoiling) of DNA molecules, passing one strand of DNA through another via a transient enzyme-bridged break in one of the strands (a move performed by topoisomerase), and breaking a pair of strands and recombining them to different ends (a move performed by recombinase). An interesting development for topology has been the emergence of a new experimental protocol, the topological approach to enzymology [30], which directly exploits knot theory in an effort to understand enzyme action. In this protocol, one reacts artificial circular DNA substrate with purified enzyme in vitro (in the laboratory); the enzyme acts on the circular DNA, causing changes in both the euclidean geometry (supercoiling) of the molecules and in the topology (knotting and linking) of the molecules. These enzyme-caused changes are experimental observables, using gel electrophoresis to fractionate the reaction products, and rec A enhanced electron microscopy [15] to visualize directly and to determine unambiguously the DNA knots and links which result as products of an enzyme reaction. This experimental technique calls for the building of knot-theoretic models for enzyme action, in which one wishes mathematically to extract information about enzyme mechanism from the observed changes in the DNA molecules.
Survey For Credit Scoring Model using Data Mining Algorithms

Credit scoring means applying a statistical model to assign a risk score to a credit application.Credit scoring techniques assess the risk in lending to a particular client. They not only identify good applications and bad applications on an individual basis, but also they forecast the probability that an applicant with any given score will be good or bad.Although credit scoring systems are being implemented and used by most banks nowadays, they do face a number of limitations.The availability of high-quality data is a very important prerequisite for building good credit scoring models. However, the data need not only be of high quality, but it should be predictive as well, in the sense that the captured characteristics are related to the customer defaulting or not.The statistical techniques used in developing credit scoring models typically assume a data set of sufficient size containing enough details. This may not always be the case for specific types of portfolios where only limited data is available, or only a low number of defaults is observed. It is observed that Credit Scoring Model is much more accurate and efficient when it is executed on data that has been carefully prepared and pre-processed. Data mining could be applied in the process of Credit Scoring that is used to predict default clients n order to decide whether to grant them a credit especially by using classification algorithms. Also, data pre-processing can be used on imbalance credit data for improving risk prediction.
Switching Constrained Max-Weight Scheduling for Wireless Networks

We consider the wireless scheduling problem of jointly activating/de-activating base-stations and (opportunistically) scheduling from among the active base stations. Such systems are of increasing relevance in emerging wireless networks with dense overlapping coverage, where it suffices for only a (time-varying) subset of the base-stations to be active at any given time to satisfy traffic demands. In addition to queue stability (to ensure that traffic demands are met), we focus on optimizing for costs arising due to activating base-stations (switching base-station state between active/inactive), and maintaining activation (these costs arising due to energy consumption). We propose two algorithms–LASS-Static and LASS-Dynamic (LASS: Learning Aided Switching and Scheduling), both of which are explore-exploit policies for base-station switching and channel scheduling. In our setting, the switching action consists of two key decisions: when to switch, and what base-station activation state to switch to. Both LASS-Static and LASS-Dynamic determine the resulting switching state (i.e. ‘what to switch to as well as the schedule using current queue-lengths and (estimated) channel states. The crucial difference is in ‘when to switch’–LASS-Static determines these statically (motivated by an epsilon-greedy bandit approach), whereas LASS-Dynamic does so using current queue-lengths (thus correlating switching times, switching states and schedules). For either algorithm, existing Lyapunov-based techniques fail to establish stability, as the switching state dynamics correlate the base-station activation decisions with the channel evolution over time. Using novel drift based techniques, in this paper we derive stability, and provide explicit bounds on the expected cost and queue lengths for both algorithms. Furthermore, we show that adaptively selecting switching times in LASS-Dynamic results in an improved upper-tail of queue lengths compared to LASS-Static.
LANE DETECTION USING CANNY EDGE DETECTION AND HOUGH TRANSFORM ON RASPBERRY PI

Many of the researchers are developing an efficient technology for automated alarm system while crossing through lanes on roads. Lane detection through image processing is one of the major tasks. A camera can be mounted in the front of vehicle to take real time images; and a fast processor can be use to automatically detect lanes according to image processing algorithms. This paper is based on algorithm development using canny edge detector and Houge transform. The algorithm is implemented on OpenCV and Python. The Raspberry Pi is used for real time processing of image. Algorithm and it’s implementation is discussed in this paper.
Growth rate and age at migration of Anguilla anguilla

The length, age and growth rate were investigated for downstream migrating male and female eels in the unexploited Burrishoole system, western Ireland. Significant differences were found in the age and length at migration with the larger, older female eels also showing faster annual growth as early as the first year in fresh water. Female eels normally migrated at lengths from 40.5 cm, exceptionally to 92.9 cm, and male eels at lengths between 28.9 and 46′0 cm. Back-calculation showed an irregular pattern of fast and slow annual growth. Mean annual growth increments were almost always greater for females than for males.
An Iterative Graph-based Image Restoration using Data-Adaptive Objective Function

: An image is defined as a function of weighted graph encoded with Laplacian matrices and its associated kernel similarities. An Iterative Graph (IG)-based Image Restoration with data-adaptive objective function is used to deblur the images that are degraded due to unconstrained conditions. From a normalized graph Laplacian, cost function is defined with a new regularization term and new data fidelity term. From the fast symmetry preserving balancing matrix, the normalizing coefficients are derived. This results in determining the spectral properties like symmetric, positive semi-definite and returning zero vector when applied to a constant Image. This algorithm has inner and outer iterations. In the inner conjugate gradient iterations, an updated objective function is minimized and the similarity weights are recalculated with earlier estimate in each outer iterations. The performance of this method is more effective for various restoration problems like sharpening, deblurring and denoising. Experimental results show that IG-based algorithm performs more powerfully in terms of objective criteria and visual quality .
Relating carrion breakdown rates to ambient resource level and community structure in four cave stream ecosystems

Abstract Detrital inputs into ecosystems vary in quantity and quality (e.g., plant litter vs carrion). Variability in detrital quantity and quality potentially affects consumer biomass and rates of organic matter (OM) breakdown. We used cave streams to test 2 linked hypotheses regarding the influence of total detrital inputs on consumer biomass and the breakdown of high-quality carrion detritus. First, we hypothesized that cave systems with higher total OM availability would support a higher biomass of consumers. Second, we predicted that higher consumer biomass would cause faster carrion breakdown rates. To test these hypotheses, we quantified macroinvertebrate biomass and breakdown rates (k, d−1) of carrion (mouse carcasses, Mus musculus) in 4 cave streams in northeastern Alabama and southeastern Tennessee (USA) that varied in total OM storage. We estimated carrion breakdown rates in coarse- and fine-mesh packs (10-mm and 500-µm mesh size) to isolate the influence of scavenging by crayfish. Macroinvertebrate biomass (excluding crayfish) in carrion packs was positively correlated with OM storage, but neither macroinvertebrate biomass (excluding crayfish) nor OM storage were strong predictors of carrion breakdown rates. Crayfish biomass was not correlated with total OM storage but was positively correlated with coarse-mesh breakdown rates. Our study illustrates the influence of community structure and consumer biomass on detrital breakdown rates in cave ecosystems. However, determining how detrital inputs structure cave communities will require further study.
Alliances in Industrial Purchasing: The Determinants of Joint Action in Buyer-Supplier Relationships

Recent trends in industrial markets indicate that buyers and sellers are increasingly supplanting conventional “arm's length” arrangements with “alliances” involving closer ties. The authors develop a theoretical model of industrial buyer-supplier ties that presents joint action as a key aspect of closeness. Whereas conventional ties emphasize a clearly defined division of labor, these newer relationships are distinguished by more tightly integrated roles based on undertaking activities jointly. Drawing primarily on a normative theory of transaction costs, the authors identify the conditions under which these relationships are useful. The utility of the relationships derives from an ability to safeguard relationship-specific investments and to facilitate adaptation to uncertainty. Using data from a sample of industrial firms and their suppliers, the authors test these predictions. The results show good support for the model. Consequences for research and practice in marketing are drawn.
Self-learning photonic signal processor with an optical neural network chip

Photonic signal processing is essential in the optical communication and optical computing. Numerous photonic signal processors have been proposed, but most of them exhibit limited reconfigurability and automaticity. A feature of fully automatic implementation and intelligent response is highly desirable for the multipurpose photonic signal processors. Here, we report and experimentally demonstrate a fully self-learning and reconfigurable photonic signal processor based on an optical neural network chip. The proposed photonic signal processor is capable of performing various functions including multichannel optical switching, optical multiple-input-multiple-output descrambler and tunable optical filter. All the functions are achieved by complete self-learning. Our demonstration suggests great potential for chip-scale fully programmable optical signal processing with artificial intelligence.
Joint Offloading Decision and Resource Allocation with Uncertain Task Computing Requirement

We study the problem of joint offloading decision and resource allocation for mobile cloud networks with a computing access point (CAP) and a remote cloud center. We consider the case where the task computing requirement is not fully known before their execution. We aim to jointly optimize the offloading decisions as well as the allocation of computation and communication resources, to minimize a weighted sum of the average cost and cost variation. The problem is formulated as a mixed-integer program. We propose an efficient algorithm, termed Task Offloading and Resource Allocation with Uncertain Computing (TORAUC), and show that it always converges to a Karush-Kuhn-Tucker (KKT) point of an alternate form of the original problem, which has its binary constraints removed but guarantees an offloading decision solution that is arbitrarily close to binary. We extend TORAUC to TORAUC-MP for the case of a multi-processor CAP. Through trace-based simulation, we study the performance of TORAUC and TORAUC-MP. We observe that TORAUC is nearly optimal, and both algorithms substantially outperform several alternatives.
DESIGN, PRODUCE AND CONTROL OF A 2-DOF UPPER LIMB EXOSKELETAL ROBOT

Exoskeletal robots are used as high-tech products in the military, health and industrial applications. The integration of robots and humans offers new opportunities for the creation of new assistive technologies that can be used in biomedical, industrial and military applications. This paper presents the mechanical design, modeling and simulation of 2 degrees of freedom (DOF) upper limb exoskeletal robot. The system can be used both for supporting load lifting and for rehabilitation of upper limbs. A load cell was used to measure the applied load. Encoders were used to measure the shoulder and elbow joint angles. An electromyograph was developed to measure muscular activation. In this study, simulation was conducted with the PID position control, however the system hardware is applicable for a force control architecture.
KEPERLUAN DAN PENERIMAAN GURU PELATIH TERHADAP PELAKSANAAN M-PEMBELAJARAN DALAM PENDIDIKAN GURU

The purpose of the study is to investigate the needs of developing M-Learning implementation model for teacher education. UTAUT theory was used as a basic model for the study. A survey method was utilized among 220 sample to investigate the needs of adopting M-Learning for this model. The data obtained were analyzed through descriptive statistics using the Statistical Packages for the Social Sciences (SPSS) software. Data interpretation was based on percentage and standard deviation values. The overall findings shows that teachers have at least one mobile technology device with at least at level 2 (voice call capability, SMS, video call, email, internet surfing, image and video recording and software to download). The finding of this study reveals that the sample have access to necessary technology for the implementation of M-Learning. The results also indicate the positive level of acceptance and intention to use the M-Learning model in teacher education.
Serum Biomarkers in Patients with Stable and Acute Exacerbation of Chronic Obstructive Pulmonary Disease: A Comparative Study

Summary Background Mean platelet volume (MPV), neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have all been investigated as novel inflammatory markers of cardiac and oncological diseases, while there is only a limited number of studies investigating these markers in chronic obstructive pulmonary disease (COPD). In the present study we examine NLR, PLR; and other markers, such as eosinophil, MPV, plateletcrit (PCT), platelet distribution width (PDW), red cell distribution width (RDW), and C-reactive protein (CRP) in patients with stable and acute exacerbation of COPD. Methods Stable COPD (Group 1, n=140), COPD with acute exacerbation (Group 2, n=110), and healthy controls (Group 3, n=50) were included in the study. Leukocyte, CRP, hemoglobin (HB), RDW, platelet, MPV, PCT, PDW, neutrophil, lymphocyte, eosinophil, NLR, and PLR were analyzed in all groups. Results HB, leukocyte, platelet, neutrophil, eosinophil, MPV, PCT, CRP, NLR, and PLR were significantly higher, while the lymphocyte was lower in Group 1 than in Group 3. Leukocyte, neutrophil, RDW, CRP, NLR, and PLR were significantly higher, while lymphocyte was lower in Group 2 than in Group 3. Leukocyte, neutrophil, RDW, CRP, NLR, and PLR were significantly higher, while HB, platelet, MPV, PCT, and lymphocyte were significantly lower in Group 2 than in Group 1. NLR and PLR increased significantly in patients with bronchiectasis when compared to those without in Group 1. Conclusions Our study results suggest that NLR, PLR and RDW can be used as simple and cost-effective markers for the evaluation of severity of exacerbation and for predicting hospitalization and further exacerbations in patients with COPD.
Response to selection for grazing tolerance in winter-active populations of phalaris (Phalaris aquatica L.). 2. Correlated response in yield potential, plant characteristics, and alkaloid levels

Phenotypic changes in populations of perennial grasses are known to occur in response to natural or deliberate selection under grazing. These changes may have agronomic significance. Associated changes in morphology and yield potential of young stands in response to 2 cycles of selection for grazing tolerance were examined in 3 winter-active breeding populations of the perennial grass, phalaris (Phalaris aquatica L.). Levels of alkaloids which potentially could affect palatability were also examined. There was a decline in seedling growth and autumn and winter yield in spaced plants of 6.3–7.5% per cycle pooled across populations. Seedling growth measured in sown swards at 2 sites was not affected by selection. Visually estimated sward yield in the second year, ignoring large gaps, agreed with the spaced plant results but the decline was not significant at P ≤ 0.05 when herbage yield was measured by mowing, probably due to effects of plant density. On balance, it was concluded that a decline in individual plant yield of 6–7% per cycle had occurred but this could be compensated by higher density, particularly over time as differences in persistence under grazing developed. The most pronounced morphological response to selection under grazing was towards a more densely tillered growth habit, although one exception occurred. There was also a tendency towards a more prostrate growth habit and later heading, but this was significant only for the most erect and earliest maturing population. Two cycles of selection did not significantly affect summer activity or area of plant base in any population. Tryptamine alkaloids were below the level likely to affect palatability but tended to increase with selection, particularly in a very low tryptamine base population, which suggested that they may play a role in persistence. Because of potentially deleterious effects on yield, care is required in using this selection method. A balance of yield potential and grazing tolerance appropriate to the management system is needed.