Miracle-dz/UniFAR-FTUs huggingface dataset:
Contrasting precipitation seasonality influences evapotranspiration dynamics in water‐limited shrublands

Water‐limited ecosystems occupy nearly 30% of the Earth, but arguably, the controls on their ecosystem processes remain largely uncertain. We analyzed six site years of eddy covariance measurements of evapotranspiration (ET) from 2008 to 2010 at two water‐limited shrublands: one dominated by winter precipitation (WP site) and another dominated by summer precipitation (SP site), but with similar solar radiation patterns in the Northern Hemisphere. We determined how physical forcing factors (i.e., net radiation (Rn), soil water content (SWC), air temperature (Ta), and vapor pressure deficit (VPD)) influence annual and seasonal variability of ET. Mean annual ET at SP site was 455 ± 91 mm yr−1, was mainly influenced by SWC during the dry season, by Rn during the wet season, and was highly sensitive to changes in annual precipitation (P). Mean annual ET at WP site was 363 ± 52 mm yr−1, had less interannual variability, but multiple variables (i.e., SWC, Ta, VPD, and Rn) were needed to explain ET among years and seasons. Wavelet coherence analysis showed that ET at SP site has a consistent temporal coherency with Ta and P, but this was not the case for ET at WP site. Our results support the paradigm that SWC is the main control of ET in water‐limited ecosystems when radiation and temperature are not the limiting factors. In contrast, when P and SWC are decoupled from available energy (i.e., radiation and temperature), then ET is controlled by an interaction of multiple variables. Our results bring attention to the need for better understanding how climate and soil dynamics influence ET across these globally distributed ecosystems.
Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization

We propose a general theory for studying the landscape of nonconvex optimization with underlying symmetric structures for a class of machine learning problems (e.g., low-rank matrix factorization, phase retrieval, and deep linear neural networks). In particular, we characterize the locations of stationary points and the null space of Hessian matrices of the objective function via the lens of invariant groups. As a major motivating example, we apply the proposed general theory to characterize the global landscape of the nonconvex optimization in low-rank matrix factorization problem. We illustrate how the rotational symmetry group gives rise to infinitely many nonisolated strict saddle points and equivalent global minima of the objective function. By explicitly identifying all stationary points, we divide the entire parameter space into three regions: (<inline-formula> <tex-math notation="LaTeX">$ \mathcal {R}_{1}$ </tex-math></inline-formula>) the region containing the neighborhoods of all strict saddle points where the objective has negative curvature; (<inline-formula> <tex-math notation="LaTeX">$ \mathcal {R}_{2}$ </tex-math></inline-formula>) the region containing neighborhoods of all global minima, where the objective enjoys strong convexity along certain directions; and (<inline-formula> <tex-math notation="LaTeX">$ \mathcal {R}_{3}$ </tex-math></inline-formula>) the complement of the above regions, where the gradient has sufficiently large magnitude. We further extend our result to the matrix sensing problem. Such global landscape implies that strong global convergence guarantees for popular iterative algorithms with arbitrary initial solutions.
Effects of dietary soyabean, rapeseed and linseed oils on performance, slaughter yield and fatty acid profile of breast meat in turkeys

The objective of this study was to determine the physiological effect of supplementing turkey diets with different vegetable oils, i.e. soyabean (S) oil, rapeseed (R) oil and linseed (L) oil, which have different concentrations of polyunsaturated fatty acids (PUFA). The total contents of n-6 PUFA and n-3 PUFA were as follows: diet S, 49.7 and 7.02%, diet R, 33.0 and 7.96%, and diet L, 30.3 and 30.6%; the n-6/n-3 PUFA ratio was 7.3, 4.4 and 1.0, respectively. The experimental materials comprised four groups of turkey hens (14 replications of fifteen birds each). The amount of dietary oil supplementation was increased from 2% in the first four weeks to 6% at the final stage of fattening (14-15 weeks). The apparent total tract digestibility of crude fat in 7-week-old turkeys (2.5% oil in diet) ranged from 89.9 to 91.1%, and showed no statistically significant differences. Dressing percentage, breast, thigh, and drumstick muscle contents did not differ among groups. Group L had a significantly higher intestinal fat weight (0.84% body weight (BW)) than the other groups (0.60-0.62%). In comparison with diet S, diets R and L contributed to a significant decrease in the levels of saturated fatty acids (from 32.9% to 30.3 and 30.2%) in breast meat lipids. In group L turkeys, the share of PUFA in total fatty acids in breast meat lipids was significantly higher (37.3%
Humoral antibody response of brown trout Salmo trutta vaccinated against furunculosis

Two year old brown trout Salmo trutta L in a freshwater farm with a history of enzootic Aeromonas salmonicida infections were vacclnated with a commercial vaccine against furunculosis by intrapentoneal injection either with or without a booster Antibody levels to 3 cellular antigen preparations from A salmoniclda, i e whole cells of A salmon~cida, Alaye~ protein, and l~popolysacchailde (LPS) lsolated from the bactenum, were measured using an ELISA technique Ant ibod~es to ivhole cell A salmonicida and LPS were demonstrated in both vaccinated and non-vacc~nated fish Antibodies to A-layer protein were only detected in very low quantities in non-vaccinated f ~ s h In vacclnated f ~ s h , the levels of these antibodies were significantly h ~ g h e r in boosted fish than in fish vaccinated only once Western blot analyses of fish serum also revealed antibodies to LPS and A-layer piotein Antlbody activit~es to extracellular products froin A salmonicida wele malnly against a 70 kDa component and LPS Prior to a challenge test in which furunculosis was induced by increasing the water temperature, all f ~ s h wele bled and lndiv~dually marked Only boosted fish showed s~gnificant protection in this challenge, and no mortalities were recorded In this group The groups ot f ~ s h which had recelved only 1 lmmunlzation were not protected against furunculosis In these g1 oups, pre-challenge antibody levels to cell membrane antigens, as measured by ELlSA d ~ d not differ between survivors and non-survivors This ind~cates that high levels ot spec~fic antibodies to cellular antigens do not correlate with survival of the ind~vidual fish
FEATURE SELECTION USING MODIFIED ANT COLONY OPTIMIZATION APPROACH ( FS-MACO ) BASED FIVE LAYERED ARTIFICIAL NEURAL NETWORK FOR CROSS DOMAIN OPINION MINING

Web mining and web usage mining are attracting many researchers to propose new ideas, models, deploying machine learning algorithms and more. Internet usage expands its wings to almost all kind of applications which includes e-commerce. E-commerce facilitates the consumers/customers to buy the products online and at the same time, web analytics helps the website administrators to identify which products sell more. Opinion mining is the key to analytics in many decision-making tasks in the ecommerce arena. This research work aims to propose feature election using modified ant colony optimization approach (FS-MACO) based five layered artificial neural networks for cross-domain opinion mining. Dataset is obtained which consists of reviews about products such as books, DVDs, electronics and kitchen appliances. The features are identified by making use of modified ACO and opinion mining is performed by using ANN. Accuracy and F-measure are the metrics chosen for the evaluating the performance of the proposed work. Comparison of domain-specific and domain – dependent words are presented. Results portray that the proposed work outperforms better than that of the existing work in terms of the chosen performance metrics.
Evaluation of the internal structure of the Cyberchondria severity scale (CSS): A Factor analytic study

Background & Aim: Cyberchondria is a form of anxiety characterized by excessive health- related internet search. The aim of this study was to evaluate the factorial structure of the Persian version of the Cyberchondria severity scale, designed to measure individuals' anxiety about their own health status caused by excessive health- related internet search. Methods: This is a descriptive /analytical study conducted on 228 students (154 males and 74 females) of Tabriz universities (Tabriz University, Payame Noor) through convenience sampling. Subjects completed the Cyberchondria severity scale questionnaire. Data were analyzed through exploratory factor analysis and confirmatory factor analysis using SPSS 22 and Mplus 6.12 softwares. Results: Although exploratory factor analysis identified a five-factor structure, further investigations showed that the four-factor structure is probably more suitable for Iranian population. The four discovered factors were named as: Compulsion, Excessiveness, Reassurance and Distress. In addition, the results of confirmatory factor analysis showed that the four-factor structure well fitted the data. Conclusion: Findings suggest that the Persian version of the Cyberchondria severity scale is an appropriate tool to measure the severity of health anxiety caused by excessive health-related internet search. However, further research should be carried out in this field.
The Effect of Health Status, Nutrition, and Some Other Factors on Low School Performance Using Induction Technique

Objectives: We investigated the effect of some hypothetical factors (nutrition, health indicators, risk behaviors, personal characteristics, and family indicators) on academic achievement using Logistic Regression (LR) and the Chi-squared Automatic Interaction Detection (CHAID) method. Study Design: Participants were 873 secondary school or high school students selected randomly from a total of 12,150 students after stratification according to school populations in Edirne, in 2003. Results: The sensitivity, positive predictivity, and specificity rates were 61.19%, 67.70%, and 74.25% for CHAID, and 50.00%, 64.29%, and 75.69% for LR, respectively. Fathera#39;s educational level was the most important factor in the CHAID method. Smoking status, time reserved for homework, and nutrition were the other important factors predicting low school performance according to the CHAID method. Conclusion: The classification tree algorithm can be used in risk analysis and target segmentation for academic achievement management. Our results may contribute to developing guidelines for those involved in secondary school and high school education. Turkish Baslik: Tumevarim Teknigi Kullanilarak Saglik Durumu, Beslenme ve Bazi Diger Faktorlerin Okul Basarisizligina Etkisinin Arastirilmasi Anahtar Kelimeler: Basari; adolesan davranisi/psikoloji; ki-kare dagilimi; diyet; aile ozellikleri; saglik durumu; lojistik yontem; regresyon analizi; sigara icme; ogretim Amac: Bu calismada Lojistik Regresyon (LR) ve Chi-squared Automatic Interaction Detection (CHAID) yontemleri kullanilarak bazi faktorlerin (beslenme, saglik gostergeleri, riskli davranislar, kisilik ozellikleri, aile gostergeleri, vb.) okul basarisi uzerindeki etkileri arastirildi. Calisma Plani: Calisma orneklemi, 2003 yilinda Edirnea#39;de okuyan 12150 ogrenciden olusan calisma evreninden, tabakali orneklemeyle rasgele secilen 873 ortaokul ve lise ogrencisinden olusturuldu. Bulgular: Duyarlilik, dogruluk ve ozgulluk oranlari CHAID icin sirasiyla %61.19, %67.70 ve %74.25; LR icin sirasiyla %50.00, %64.29 ve %75.69 bulundu. Babanin egitim duzeyi CHAID yonteminde en onemli faktor olarak bulundu. Ayni yontemle, sigara kullanimi, ev odevi icin ayrilan sure ve beslenme faktorleri, basarisizligi tahmin eden diger onemli faktorler olarak saptandi. Sonuc: Siniflandirma agaci algoritmasi, okul basarisinin kontrolu icin risk analizi ve hedef belirlemede kullanilabilir bir yontemdir. Bu calismanin sonuclari, ortaokul ve lise ogrencilerinin egitimiyle ilgili kisilere bir kilavuz olarak katkida bulunabilir.
Security Analysis of Cognitive Radio Netwoks Using Game Theory

In this paper, a cognitive radio network is considered where Alice wants to send confidential information to the Bob in the presence of primary user and eavesdropper. Effect of number of antennas in Bob and eavesdropper is discussed using the game theory. It is observed that number of antennas in Bob improves the security of the system. Keywords—cognitive radio, security, game theory, Nash equilibrium.
A Study on Compressive Sensing and Reconstruction Approach

: This paper gives the conventional approach of reconstructing signals or images from calculated data by following the well-known Shannon sampling theorem. This principle underlies the majority devices of current technology, such as analog-to-digital conversion, medical imaging, or audio and video electronics. The primary objective of this paper is to establish the need of compressive sensing in the field of signal processing and image processing. Compressive sensing (CS) is a novel kind of sampling theory, which predicts that sparse signals and images can be reconstructed from what was in the past thought to be partial information. CS has two distinct major approaches to sparse recovery that each present different benefits and shortcomings. The first, ℓ 1 -minimization methods such as Basis Pursuit use a linear optimization problem to recover the signal. This method provides strong guarantees and stability, but relies on Linear Programming, whose methods do not yet have strong polynomially bounded run times. The second approach uses greedy methods that compute the support of the signal iteratively. These methods are much faster than Basis Pursuit, but until recently had not been able to provide the same guarantees. This gap between the two approaches was bridged when we developed and analyzed the greedy algorithm.
3D object-based feature extraction from 3-stereo DSM in urban context

For urban planning purposes updated information on land-use and urban structures and change dynamics are essential. Satellite Earth observation is a very effective information source, to provide actual representations of the situation ‘as is’ in regular time steps. The Pleiades constellation offers very high resolution imagery with a triple-stereo acquisition. The intrinsic combination of thematic and height information is an additional asset provided by recent VHR stereo imagery. Digital surface models (DSM) can be derived through stereo matching algorithms, one of which is semi-global matching (SGM). SGM integrates local and global matching methods with a short processing time and accurate surface generation. We use the generated DSM for extracting 3-D features which enrich object-based class models of composite urban objects. These multi-purpose 3-D object feature datasets can be used for various planning and monitoring purposes, revealing height-related characteristics of urban objects (blocks, neighbourhoods, parks, industrial sites, etc.). In addition object-wise aggregated height information can be used to better assess the adherence of actual building activities to zoning or land development plans, e.g. with respect to maximum or average height in recreational areas etc. As compared to detailed and potentially more accurate DSMs generated from LiDAR data, a (3-)stereo DSM has the advantage of recording height and spectral information instantaneously, so not to lose any information in high dynamic urban settings due to a time gap. Height and colour information, when integrated by spatial context and multi-scale OBIA methods, enable a wealth of new applications in urban feature characterisation and 3D city model applications.
The Effect of Active Knee Extension in Sitting on Lumbopelvic Curvature in Individuals with Clinically Tight Hamstring Muscles: A Cross-Sectional Reliability Study

Relative flexibility between the hamstring and lumbar extensor muscles, which can be evaluated using lumbopelvic curvature during active knee extension in sitting, can sometimes be assessed in physical therapy. However, reliability for its quantitative measure has not been established yet and its establishment was the aim of the current study. Twenty-seven individuals with clinically tight hamstring muscles were recruited. On two separate sessions, the lumbopelvic curvature was evaluated in sitting when the right knee was moved from 90° flexion to 10° flexion on 15 occasions using a flexible ruler by two examiners on Day 1 and one on Day 2. Lines drawn tangential to the lumbopelvic curvature were traced at T12 and S2 vertebral levels and the angle between the two vertical lines was calculated. Using Day 1 data, the minimum number of repetitions and inter-examiner reliability were assessed. Inter-session reliability was also examined. As a result, there was no statistical difference (P > 0.05) in the mean absolute difference between the mean value of N-1 and N repetitions (6 ≤ N ≤ 15) in the lumbopelvic curvature angle, indicating that five was considered the minimum number of repetitions. Intraclass correlation coefficient (ICC)(1, 5) for the inter-session reliability and ICC(2, 5) for the inter-examiner reliability was 0.97 and 0.93, respectively, indicating excellent reliability. The measure for the lumbopelvic curvature during active knee extension in sitting, which was established in the current study, will be a foundation for further research regarding the relative flexibility of the lumbar and adjunct regions.
Species traits and plant performance: functional trade‐offs in a large set of species in a botanical garden

Earlier research has established a number of relationships between community structure and plant traits. However, these relationships are mediated by demographic processes that are constrained, but not determined, by the trait values, and involve responses of plants to their environments. In particular, life‐history costs and associated trade‐offs need to be examined at the level of demographic processes such as plant survival and reproduction, not only at the level of individual trait values. We examined these demographic trade‐offs using data on vegetative and seed reproduction from 951 species of the Central European flora kept in the Botanical Garden of Charles University in Prague. With each species grown under conditions close to its natural habitat, we view the data as information on vegetative and seed reproduction under favourable conditions. We used nonparametric tests and ordinal regressions to examine relationships of the vegetative and seed reproduction to each other, as well as to commonly used traits such as plant height, leaf size, specific leaf area, seed size and clonal traits. There was an overall negative correlation between seed and vegetative reproduction, indicating trade‐off between these two modes of reproduction. In contrast, there was no evidence of a trade‐off between clonal and seed traits. Traits of clonal growth were related to vegetative reproduction in the garden and seed trait to seed reproduction in the garden. Further, there were correlations between seed reproduction and clonal traits and vice versa. These results suggest that seed reproduction is associated with a wider array of traits than only seed traits, and vegetative reproduction with a wider array than clonal traits again indicating complex life‐history relationships. These relationships did not change substantially after the incorporation of phylogenetic information. Synthesis. The results suggest that trade‐offs between vegetative and seed reproduction are not revealed by analysis of species traits, probably due to the fact that trade‐offs often only arise due to life‐history costs that are shaped by the local environment. This highlights the importance of examining life‐history processes associated with trait values.
Considerations for Managing IoT Cybersecurity and Privacy Risks Workshop Summary

90 The Internet of Things (IoT) is a rapidly evolving and expanding collection of diverse 91 technologies that interact with the physical world. Many organizations are not necessarily aware 92 of the large number of IoT devices they are already using and how IoT devices may affect 93 cybersecurity and privacy risks differently than conventional information technology (IT) 94 devices do. The purpose of this publication is to help federal agencies and other organizations 95 better understand and manage the cybersecurity and privacy risks associated with their IoT 96 devices throughout their lifecycles. This publication is the introductory document providing the 97 foundation for a planned series of publications on more specific aspects of this topic. 98
THE EFFECTS OF INFORMATION QUALITY , SERVICE QUALITY , AND COMPATIBILITY ON CONTINUE USE OF M-LEARNING AMONG STUDENTS IN THE PUBLIC UNIVERSITIES OF IRAQI

The success of information system could be determined based on continuously using the technology for future benefits. In today’s era of technology, M-Learning (ML) system has become an important component of Information and Communication Technology provided by educational institutions such as universities to facilitate all the transactions between institutions and their students or lecturers. This system has gained the popularity in developed and developing countries alike. Despite the known benefits of ML to the education community, usage of ML services among students in the developing countries, especially in Iraq, is still low. Additionally, there has not been empirical study on the continuous usage of ML services in developing countries such as Iraq. The primary objective of this study is to determine the contributing factors for continuous usage of ML services among students in a higher education of Iraq. Moreover, the study used quantitative approach by distributing 600 questionnaires to respondents in the public universities of Iraq. Besides that, the collected data was analysed using a Structural Equation Model. The findings showed that information quality construct has a large effect on user satisfaction than service quality and compatibility constructs.
Above the Mean: Examining Variability in Behavioral and Neural Responses to Multisensory Stimuli

Even when experimental conditions are kept constant, a robust and consistent finding in both behavioral and neural experiments designed to examine multisensory processing is striking variability. Although this variability has often been considered uninteresting noise (a term that is laden with strong connotations), emerging work suggests that differences in variability may be an important aspect in describing differences in performance between individuals and groups. In the current review, derived from a symposium at the 2015 International Multisensory Research Forum in Pisa, Italy, we focus on several aspects of variability as it relates to multisensory function. This effort seeks to expand our understanding of variability at levels of coding and analysis ranging from the single neuron through large networks and on to behavioral processes, and encompasses a number of the multimodal approaches that are used to evaluate and characterize multisensory processing including single-unit neurophysiology, electroencephalography (EEG), functional magnetic resonance imaging (fMRI), and electrocorticography (ECoG). Please see http://dx.doi. org/10.1163/22134808-00002540