Miracle-dz/UniFAR-FTUs huggingface dataset:
Temperature effects on oxygen thresholds for hypoxia in marine benthic organisms

The effect of warming on the oxygen requirements and the survival of benthic organisms under hypoxia was tested using a meta‐analysis of published results of experiments evaluating the effects of temperature on the median lethal time and median lethal concentration of benthic macrofauna under hypoxia. The meta‐analysis confirmed that survival times under hypoxia were reduced by on average 74% and that median lethal concentration increased by on average 16% when marine benthic organisms were exposed to warmer temperatures. Warming reduced survival times of marine benthic macrofauna under hypoxia by a median of 3.95±1.67 h °C−1 and increased the oxygen thresholds for hypoxia‐driven mortality by a median of 1.02±0.15% saturation °C−1 or 0.07±0.01 mg O2 L−1 °C−1. The corresponding Q10 values averaged 3.01±0.29 for the median survival time and 2.09±0.20 for the median lethal oxygen concentration. Use of these Q10 values predicts that the 4 °C warming expected during the 21st century will lead to survival times 35.6% lower under hypoxia and that the threshold oxygen concentrations for high mortality to occur will increase by, on average, 25.5% if bottom water temperature increased by 4 °C. Hence, ocean warming is expected to increase the vulnerability of benthic macrofauna to reduced oxygen concentrations and expand the area of coastal ecosystems affected by hypoxia.
Dynamics of Outsourcing in Industrial Clusters: a Study of the Gujrat Fan Industry in Pakistan

Firms in industrial clusters outsource extensively. Factors influencing outsourcing de cisions are reviewed in the context of industrial clusters, characterized by high levels of specialization, low transaction costs, and technology diffusion. A framework for mak ing outsourcing decisions is developed and illustrated using a case study of outsourcing practices in the Gujrat fan cluster. Core competencies, together with outsourcing prac tices, were found to vary according to the size of the manufacturing firm. Given the extremely low cost of conducting transactions and the presence of highly specialized and efficient vendors, the decision that core activities should be retained and devel oped in-house is the key to survival in clusters.
DVSP: Dynamic Virtual Sensor Provisioning in Sensor–Cloud-Based Internet of Things

Virtual sensor provisioning is an essential process in sensor-cloud-based Internet of Things (IoT), and it is responsible for the efficient utilization of physical resources in the system. However, the existing schemes for virtual sensor provisioning do not provide an optimal solution while considering overall demand of multiple users/services. As a result, redundant sensor nodes are provisioned, which leads to increased energy consumption and reduced network lifetime. In this paper, we present a dynamic virtual sensor provisioning scheme for sensor-cloud-based IoT applications to maintain the energy efficiency of the deployed physical sensor nodes while maintaining the quality of service (QoS) of the service requests. We model the interaction between the cloud service provider and the sensor owners using the single-leader multifollower Stackelberg game. The players of the game exploit the spatial correlation among the on-field sensor nodes, and consequently, the oligopoly created between the players is dynamically updated. We show the existence of a Stackelberg–Nash–Cournot equilibrium in the game. We evaluated the performance of the proposed scheme through extensive simulations. The results depict improvement in the energy efficiency of the nodes as well as increase in the lifetime of the deployed on-fields sensors in the proposed scheme compared to benchmark schemes. We also plot the average number of QoS violations in each iteration for the user requests.
Effects of Initiation Age of Skip-A-Day Feed Restriction on Skeletal Development in Broiler Breeder Males

Abstract This experiment was conducted over an 18-week period to determine the effects of initiating a skip-a-day (SAD) feed restriction program at 2, 4, and 6 weeks of age on male broiler breeders. For each of the SAD treatments, feed intake was manipulated so that the breeder's recommended target weight was reached by all groups at 18 weeks of age. Males were evaluated for shank and keel length and head width at 7 and 18 weeks of age. The results of this experiment show that starting a SAD feeding program at 2, 4, or 6 weeks of age will decrease shank and keel length as well as head width. Feed restriction affected keel length and head width in a very similar manner; shank length was not as sensitive to the time of initiation of the SAD feed restriction program.
Biomass Spectra of Aquatic Ecosystems in Relation to Fisheries Yield

The biomass density of aquatic ecosystems can be expressed as an allometric function of organism body size. The log–log plot of this relation, termed the biomass spectrum, is used to compare aquatic ecosystems in various parts of the world. We develop a standardized presentation for several example environments where detailed data on biomass density by body size in the trophic positions, phytoplankton, zooplankton, benthos, and fish, make it possible to establish overall or primary spectral slopes. The basic methodology is adapted for application to other ecosystems where less detailed data are available. Spectra from all the different environments exhibit a uniform low slope, but with different intercepts that appear to reflect ecosystem differences in nutrient circulation and availability. Detail on the secondary structuring at various positions in the trophic system appears to provide information useful for distinguishing between long-term changes in productivity and short-term perturbations in biomass.
Efficient Constant Envelope Precoding With Quantized Phases for Massive MU-MIMO Downlink Systems

This study considers a generalized constant envelope-based precoding design problem in massive multiuser multiple-input multiple-output systems, in which the output signals of digital-to-analog converters are restricted to $M$-ary phase-shift keying signaling to facilitate the use of low-cost and power-efficient power amplifiers at a base station. We aim to jointly optimize the precoding vector and the precoding factor to minimize the mean-squared error between the transmitted and the estimated symbols. However, the considered precoding problem is nonconvex and challenging to solve because the precoding vector and the precoding factor are coupled together. To address this problem, we apply the alternating minimization (AltMin) framework to decouple the considered problem into two problems: the precoding factor design problem and the precoding vector design problem. The former has an analytical solution, while the latter requires solving a difficult combinatorial problem, which we address by proposing a simple yet efficient gradient projection (GP)-based algorithm to find an approximate precoding vector. Simulation results demonstrate that the proposed GP-based AltMin algorithm achieves the same or higher BER performance than state-of-the-art algorithms while requiring lower complexity. In addition, when higher order modulations are employed, the error floor experienced by the existing algorithms can be substantially mitigated by the proposed GP-AltMin algorithm through increasing the number of phase bits.
First record of Saemundssonia australis Timmermann, 1955 (Mallophaga: Phthiraptera) from Lesser Sheathbill, Chionis minor (Charadriiformes: Chionididae) in the Prince Edward Islands

The object of the study was to devise a quick and reliable method for the collection and study of lice present in birds without harm or stress being inflicted on the birds. Described is the feather ruffling collection of parasitic lice Saemundssonia australis from Chionis minor and microscopic observations thereof. A random selection of 10 free-flying Lesser Sheathbills were caught on Marion Island (46°54´S, 37°45´E) with the aid of a hand net. Approximately 10 lice from each bird were collected. Examination of microphotographs of male and female lice was made. The sex ratio of parasites was approximately equal. All collected lice were adult. All 10 birds were parasitised.
Low Frequency Analysis of Acoustic and Vibration Data of a Remote Control Electronic Helicopter

The acoustic and vibration data of the tail rotor of a remote control unmanned electrical helicopter are simultaneously collected by sound and image data acquisition systems. To inspect the pure vibration spectrum in the extreme low frequency region, an image system containing a Web camera and having a sampling rate of 20 frames per second is proposed to collect the data of the tail boom. The total gray levels within a specified square of a frame are considered as a single image data at the corresponding instance. The image data string always involves the non-sinusoidal part which will introduce the Direct Current (DC) contamination to the spectrum. In order to exclude the contamination, the iterative Gaussian smoothing method is employed to remove the non-sinusoidal part. Then, both sound and image data strings are examined in terms of the Fourier sine spectrum. In order to capture information of minor modes, the Fourier sine spectrum of a sinusoidal data string is obtained through the following procedure: search zero points around the two ends, redistribute data so that the data size is an integer power of 2, perform odd function mapping, and apply the Fast Fourier Transform (FFT). A ball belling data is first employed to show that the Fourier sine spectrum can capture information of both the sub-harmonic and side band modes. With the help of the image data, many sub-harmonics and side-band modes embedded in the acoustic data of the tail rotor were identified by the Fourier sine spectrum.
Development of a Murine Model of Neuroparacoccidioidomycosis

Paracoccidioidomycosis is the most important systemic mycosis in Latin America. In the last decades, it was verified that central nervous system involvement is frequent, occurring in 12.5% of the cases. Despite the relevance of this severe form of the disease, there are not experimental models for the study of the interactions established between the fungus and the central nervous system. We developed a murine model of neuroparacoccid- ioidomycosis with intracranial inoculation of 10 6 yeast cells of Paracoccidioides brasiliensis (strain PB18) in C57BL/6 mice. Animals developed lesions similar to those described in human patients and morbidity was evaluated by the SHIRPA behavioral battery, showing progressive and severe cognitive compromise. With the development of this model, future studies will be able to evaluate several pathogenic and therapeutic aspects of neuroparacoccidioidomycosis in order to improve survival or lessen morbidity of this severe disease.
Intrusion Detection Systems with GPU-Accelerated Deep Neural Networks and Effect of the Depth

With the extended use of the Internet, which connects millions of computers across the world, there is a growing number and types of intrusions which complicate ensuring the security of information and computers. Although Firewalls and rule/signature base Intrusion Detection Systems (IDSs) are used as the first line of the defense of networks, they cannot be sufficient for detecting the zero-day type attacks, which are not previously encountered. For this type of attacks, Anomaly-Based Intrusion detection systems arise as an acceptable solution which models the normal communication behavior of the network and identifies the others as a suspicious transaction. To classify the normal behavior, usage of neural networks and machine learning approaches are accepted as powerful solutions. However, due to the lack of computation power, generally single hidden layer approach is preferred.With the enhancement of the parallel computation technology, especially in Graphics Processing Units (GPUs), it will be easy to implement a multi-layer approach in Deep Neural Network concept which has a great deal of attention within Deep Learning approach. Therefore, a better accuracy rate could be reached. In this paper, we aimed to implement a Deep Neural Network-based Intrusion Detection System. Moreover, we also study the performance of the proposed model in the binary classification with a different number of layers, neurons, and parameters. Additionally, the acceleration of the GPU usage is also measured and presented with a comparison. To measure the performance of the proposed system the NSL-KDD data set, which is a cleaned data set of the KDD data set, is preferred. The experimental results showed that the proposed multi-layer Deep Neural Network model produces an acceptable performance in its classification with a high accuracy rate with the design of a 64x32 hidden layer structure depending on the data set NSL-KDD.
Hydrolysed wool: a novel soil amendment for zinc and iron biofortification of wheat

Abstract Biofortification—with either the application of zinc and iron fertilizer or the application of amendments to increase their bioavailability in soil—is a possible strategy to tackle worldwide micronutrient malnutrition. We investigated the effect of hydrolysed wool on the uptake of zinc and iron by wheat (Triticum aestivum var. Greina). We performed pot experiments in which either hydrolysed wool or mineral fertilizer of the same elemental composition was incorporated into a loamy-sand collected from an agricultural field. Zinc grain concentrations were 37.7 mg kg−1 (control), 45.5 mg kg−1 (mineral fertilization) and 54.1 mg kg−1 (hydrolysed wool). In addition, hydrolysed wool application increased grain yield 2-fold and grain protein content 1.5-fold, compared with 1.4-fold and 1.3-fold, respectively, by the mineral fertilizer. We propose that hydrolysed wool could be used to supplement other fertilizers, enhancing the latter with an easily available N source as well as promoting zinc and iron uptake in plants.
El eje microbiota-intestino-cerebro y sus grandes proyecciones

Introduccion. Se denomina microbiota al conjunto de millones de microorganismos que conviven de manera simbiotica en nuestro organismo. Este conjunto bacteriano, que se localiza principalmente en el tracto digestivo, se distribuye a lo largo de los diferentes organos en funcion de las propiedades quimicas. Los factores que influyen en su composicion son multiples (dieta, habitos individuales, farmacos). La microbiota colabora en varias funciones, como pueden ser el metabolismo o la inmunidad. Desarrollo. En los ultimos anos se ha puesto de relieve el papel bidireccional de la microbiota del tracto digestivo y del sistema nervioso central, es el denominado eje intestino-cerebro. En lo que a este eje se refiere, se cree que la comunicacion se produce a traves de tres vias: el nervio vago, la via sistemica (mediante la liberacion de hormonas, metabolitos y neurotransmisores) y el sistema inmune (por la accion de las citocinas). Conclusiones. Aunque aun quedan muchas incognitas por esclarecer, este eje se postula como una posible base patogena para numerosos trastornos neurologicos de gran impacto sanitario, como la enfermedad de Alzheimer, la enfermedad de Parkinson o la esclerosis multiple. En el momento actual se estan llevando a cabo estudios que intentan evaluar el impacto de los probioticos sobre algunas de estas enfermedades neurologicas.
A novel framework for disentangling the scale‐dependent influences of abiotic factors on alpine treeline position

Low-temperature growth limitation largely determines alpine treeline position globally, but treeline elevation also varies locally at a range of scales in response to multiple biotic and abiotic factors. In this study, we conceptualise how variability in treeline elevation is related to abiotic factors that act as thermal modifiers, physiological stressors, or disturbance agents. We then present a novel analytical framework for quantifying how abiotic factors influence treeline elevation at different spatial scales using New Zealand Nothofagus treelines as a case study. We delineated Nothofagus treelines in a GIS, along which we extracted data for treeline elevation and eight abiotic explanatory variables at 54 000 points. Each location was classified at each of five spatial scales based on nested river catchments, ranging from large regional to small hillslope catchments. We used hierarchical linear models to partition the variation in both treeline elevation and the eight abiotic variables by spatial scale, and then quantified the relationships between these at each spatial scale in turn. Nothofagus treeline elevation varied from 800–1740 m a.s. l. across New Zealand. Abiotic factors explained 82% of the variation in treeline elevation at the largest (regional) scale and 44–52% of variation at the four finer scales. Broad-scale variation in Nothofagus treeline elevation was strongly associated with thermal modifiers, consistent with the idea that treelines coincide with a temperature-driven, physiological limit. However, much of the finer-scale variation in treeline elevation was explained by a combination of thermal, physiological stress-related, and disturbance variables operating at different spatial scales. The conceptual model and analytical methods developed here provide a general framework for understanding treeline variation at different spatial scales.
How to Master the "E": Tools for Competence Identification, Provision and Preservation in a Digitalized Public Sector

The digitalization of every aspect of life is in full swing and becoming an all-embracing societal phenomenon. Public administrations worldwide, eager to increase their efficiency and effectiveness, are in a change process, induced by the pervasiveness of technological advancements. This development does not only mean the substitution of analogue processes by the integration of information technologies, but first and foremost leads to changing demands on the tasks, roles and competences of the ones, who need to implement those changes, i.e. the public servants. This study therefore explores relevant roles and respective competences with regard to IT in public administrations and offers tools for their successful preservation to master this e-induced change: Based on a literature review, document analyses and expert workshops, 19 reference roles in public administrations are identified that are important for the implementation of eGovernment. In addition, we develop role fact sheets and competence matrices as possible means for the identification and documentation, which in turn can be supportive of a possible future competence preservation.
Pseudo Power Signatures for Nonstationary Signal Analysis and Classification.

This research focuses on the analysis and classi cation of multicomponent nonstationary signals of arbitrary duration. The proposed classi cation approach has potential applications in areas like moving target detection, object recognition, oil exploration, and speech processing. The wavelet transform is used as the basis for the analysis. The classi cation technique is based on novel scale energy density functions, called pseudo power signatures, which are independent of signal length, and which can be used to characterize the time-scale energy distribution of the signal. These signatures allow for fast classi cation of signals regardless of their length. Two approaches to determine pseudo power signatures are presented in this work. The rst approach is based on a singular value principal component analysis technique, which, though computationally simple, is not very sensitive to signal characteristics. The second is a more sophisticated approach, and is optimal in a weighted least mean squares sense. The latter technique involves solving an inverse projection problem arising from a nonlinear in nite dimensional minimization, and generates good quality signatures with excellent discriminating capability. An algorithm, with fast convergence, for application to discrete data sets is developed, and a complete analysis of the computational complexity is obtained. Several simulation examples are presented to illustrate the methodology, and its application to practical classi cation problems. Finally, suggestions for further work in the area are given. xi Chapter
Mycotoxin Contamination of Food and Associated Health Risk in Cameroon: A 25-years Review (1993-2018)

The Gross Domestic Product of Cameron is partially based on agricultural products. Crops like maize, peanuts, beans, cassava, cocoa and coffee are the most cultivated ones. A high portion of this production is locally consumed, and the other part is exported to foreign countries in order to balance the economy. Postharvest losses due to fungal contamination and the presence of mycotoxins in food represent some of the most important problems this producing country government and populations are facing. The analysis of food from animal or vegatal origin in this country during the last 25 years have highlighted the presence of mycotoxins such as aflatoxins, fumonisins, ochratoxins, zearalenone and deoxynivalenol in some cases. This paper reviews the effects of mycotoxins on human health and associated regulations, their occurrence in food commodities from Cameroon, as well as the dietary exposure of consuming populations and the results obtained from their bio-monitoring.
Comparison of methods to detect rare and cryptic species: A case study using the red fox (Vulpes vulpes)

Choosing the appropriate method to detect and monitor wildlife species is difficult if the species is rare or cryptic in appearance or behaviour. We evaluated the effectiveness of the following four methods for detecting red foxes (Vulpes vulpes) on the basis of equivalent person hours in a rural landscape in temperate Australia: camera traps, hair traps (using morphology and DNA from hair follicles), scats from bait stations (using DNA derived from the scats) and spotlighting. We also evaluated whether individual foxes could be identified using remote collection of their tissues. Genetic analysis of hair samples was the least efficient method of detection among the methods employed because of the paucity of samples obtained and the lack of follicles on sampled hairs. Scat detection was somewhat more efficient. Scats were deposited at 17% of bait stations and 80% of scats were amplified with a fox-specific marker, although only 31% of confirmed fox scats could be fully genotyped at all six microsatellite loci. Camera trapping and spotlighting were the most efficient methods of detecting fox presence in the landscape. Spotlighting success varied seasonally, with fox detections peaking in autumn (80% of spotlighting transects) and being lowest in winter (29% of transects). Cameras detected foxes at 51% of stations; however, there was limited seasonality in detection, and success rates varied with camera design. Log-linear models confirmed these trends. Our results showed that the appropriate technique for detecting foxes varies depending on the time of the year. It is suggested that wildlife managers should consider both seasonal effects and species biology when attempting to detect rare or elusive species.