Miracle-dz/UniFAR-FTUs huggingface dataset:
Latitudinal variation of diversity in European freshwater animals is not concordant across habitat types

Aim We analysed the variation of species richness in the European freshwater fauna across latitude. In particular, we compared latitudinal patterns in species richness and β-diversity among species adapted to different habitat types. Location Europe. Methods We compiled data on occurrence for 14,020 animal species across 25 pre-defined biogeographical regions of European freshwaters from the Limnofauna Europaea. Furthermore, we extracted information on the habitat preferences of species. We assigned species to three habitat types: species adapted to groundwater, lotic (running water) and lentic (standing water) habitats. We analysed latitudinal patterns of species richness, the proportion of lentic species and β-diversity. Results Only lentic species showed a significant species–area relationship. We found a monotonic decline of species richness with latitude for groundwater and lotic habitats, but a hump-shaped relationship for lentic habitats. The proportion of lentic species increased from southern to northern latitudes. β-Diversity declined from groundwater to lentic habitats and from southern to northern latitudes. Main conclusions The differences in the latitudinal variation of species richness among species adapted to different habitat types are in part due to differences in the propensity for dispersal. Since lentic habitats are less persistent than lotic or groundwater habitats, lentic species evolved more efficient strategies for dispersal. The dispersal propensity of lentic species facilitated the recolonization of central Europe after the last glaciation. Overall, we stress the importance of considering the history of regions and lineages as well as the ecological traits of species for understanding patterns of biodiversity.
ADIPOR2 Polymorphisms in Cystic Fibrosis are Potential Modifiers of Clinical Severity

Objective: Cystic Fibrosis (CF) severity is determined by mutations in the Cystic Fibrosis Transmembrane Regulator (CFTR) gene, the environment and modifier genes. The adiponectin receptor 2 (ADIPOR2) gene is one of the potential modifier genes of CF and is responsible for expressing an anti-inflammatory protein. In this context, the 315 base deletion and the 134 base insertion polymorphisms in the ADIPOR2 gene are associated with CF severity. Methodology: A total of 169 CF patients were enrolled, and 27 CF clinical markers were analyzed. Results: The 315 base deletion and haplotypes analyses showed an association with the patient´s age and ethnicity. For the age, the deletion in both alleles was associated with a lower age in the patients without any identified CFTR mutations (OR= 7.257; 95%CI= 1.321-44.83) or disregarding CFTR mutations (OR= 2.394; 95%CI= 1.046- 5.721). For the ethnicity, the wild-type allele (315 base no deletion) showed lower risk of occurrence in Caucasians patients with two CFTR mutations identified (OR= 0.052; 95%CI= 0.002-0.382) or no CFTR mutations (OR= 0.154, 95%CI= 0.032-0.592). The same values were observed for the clustered analysis of the 315 base deletions. In the analysis of the haplotype, in the Caucasian group, the patients with two CFTR mutations were identified and demonstrated an OR of 0.076 (95%CI= 0.009-0.432) for wild-type alleles. The 134 base insertions were associated with the SpO2 [patients without considering the CFTR genotype (p-value= 0.034) and without any identified CFTR mutations (p-value= 0.034)] and the Kanga score (no CFTR mutations identified) (p-value= 0.008). The haplotype was associated with the forced vital capacity (disregarding CFTR genotype) (p-value= 0.028). Conclusion: The 315 base deletions and the insertion of 134 bases in the ADIPOR2 gene are potential modifiers of the severity of CF and should be considered during CFTR mutation screening.
Trade Secrets Protection and Corporate Tax Avoidance

This paper examines the relationship between an increase in legislative trade secrets protection and its effect on tax avoidance by large companies. We do this by examining the state-staggered implementation of the Uniform Trade Secrets Act, a state-level trade secrets law. First, we show that the adoption of the UTSA, by itself, does not have any effect on tax avoidance activities by firms located in UTSA states. However, our research demonstrates a negative association between large firms located in UTSA states and the accompanying tax avoidance by these firms. Additionally, we document the differences in tax avoidance activities by companies in different industries. Namely, we find that large high-technology companies engage in less tax avoidance as compared to companies in other industries. Overall, our results are consistent with stronger trade secrets protection leading to less tax avoidance activities by large firms.
Algorithm of IMM Combining Kalman and Particle Filter for Maneuvering Target Tracking

The particle filter can deal with nonlinear/non-Gaussian problems and it has been introduced to the algorithm of the interacting multiple model (IMM) for higher precision. The general IMM based on Kalman filter or extended Kalman filter (IMMEKF) cannot deal with non-Gaussian problems and also does not work as well as the IMM based on the particle filter (IMMPF) for the nonlinear problems. However the problem of the particle filter is its expensive computation, because a particle filter usually has a lot of particles, which will increase the computation load greatly. Here an algorithm of IMM combining the Kalman filter and the particle filter (IMMK-PF) for maneuvering target tracking is proposed to improve the computation efficiency as compared to the IMMPF. For nonlinear/Gaussian problems the new algorithm is expected to have a good performance as the IMMPF, while for linear problems it will perform similarly to the IMMEKF and will work better than the IMMPF.
Strategic Inventories in Vertical Contracts

Classical reasons for carrying inventory include fixed (nonlinear) production or procurement costs, lead times, nonstationary or uncertain supply/demand, and capacity constraints. The last decade has seen active research in supply chain coordination focusing on the role of incentive contracts to achieve first-best levels of inventory. An extensive literature in industrial organization that studies incentives for vertical controls largely ignores the effect of inventories. Does the ability to carry inventory influence the problem of vertical control? Conversely, can inventories arise purely due to incentive effects? This paper explicitly considers both incentives and inventories, and their interplay, in a dynamic model of an upstream firm (supplier) and a downstream firm (buyer) who can carry inventories. In our model, none of the classical reasons for carrying inventory exists. However, as we prove, the buyer's optimal strategy in equilibrium is to carry inventories, and the supplier is unable to prevent this. These inventories arise out of purely strategic considerations not yet identified in the literature, and have a significant impact on the equilibrium solution as well as supplier, buyer, and channel profits. We prove that strategic inventories play a pivotal role under arbitrary contractual structures, general (arbitrary) demand functions and general (finite or infinite) horizon lengths. As one example, two-part tariff contracts do not lead to optimal channel performance, nor can the supplier extract away all of the channel profits, in our dynamic model. Our results imply that firms can and must carry inventories strategically, and that optimal vertical contracts must take the possibility of inventories into account.
Evaluating derivatives - principles and techniques of algorithmic differentiation, Second Edition

Algorithmic, or automatic, differentiation (AD) is a growing area of theoretical research and software development concerned with the accurate and efficient evaluation of derivatives for function evaluations given as computer programs. The resulting derivative values are useful for all scientific computations that are based on linear, quadratic, or higher order approximations to nonlinear scalar or vector functions. AD has been applied in particular to optimization, parameter identification, nonlinear equation solving, the numerical integration of differential equations, and combinations of these. Apart from quantifying sensitivities numerically, AD also yields structural dependence information, such as the sparsity pattern and generic rank of Jacobian matrices. The field opens up an exciting opportunity to develop new algorithms that reflect the true cost of accurate derivatives and to use them for improvements in speed and reliability. This second edition has been updated and expanded to cover recent developments in applications and theory, including an elegant NP completeness argument by Uwe Naumann and a brief introduction to scarcity, a generalization of sparsity. There is also added material on checkpointing and iterative differentiation. To improve readability the more detailed analysis of memory and complexity bounds has been relegated to separate, optional chapters.The book consists of three parts: a stand-alone introduction to the fundamentals of AD and its software; a thorough treatment of methods for sparse problems; and final chapters on program-reversal schedules, higher derivatives, nonsmooth problems and iterative processes. Each of the 15 chapters concludes with examples and exercises. Audience: This volume will be valuable to designers of algorithms and software for nonlinear computational problems. Current numerical software users should gain the insight necessary to choose and deploy existing AD software tools to the best advantage. Contents: Rules; Preface; Prologue; Mathematical Symbols; Chapter 1: Introduction; Chapter 2: A Framework for Evaluating Functions; Chapter 3: Fundamentals of Forward and Reverse; Chapter 4: Memory Issues and Complexity Bounds; Chapter 5: Repeating and Extending Reverse; Chapter 6: Implementation and Software; Chapter 7: Sparse Forward and Reverse; Chapter 8: Exploiting Sparsity by Compression; Chapter 9: Going beyond Forward and Reverse; Chapter 10: Jacobian and Hessian Accumulation; Chapter 11: Observations on Efficiency; Chapter 12: Reversal Schedules and Checkpointing; Chapter 13: Taylor and Tensor Coefficients; Chapter 14: Differentiation without Differentiability; Chapter 15: Implicit and Iterative Differentiation; Epilogue; List of Figures; List of Tables; Assumptions and Definitions; Propositions, Corollaries, and Lemmas; Bibliography; Index
Evaluation of Two Lyophilized Molecular Assays to Rapidly Detect Foot‐and‐Mouth Disease Virus Directly from Clinical Samples in Field Settings

Summary Accurate, timely diagnosis is essential for the control, monitoring and eradication of foot‐and‐mouth disease (FMD). Clinical samples from suspect cases are normally tested at reference laboratories. However, transport of samples to these centralized facilities can be a lengthy process that can impose delays on critical decision making. These concerns have motivated work to evaluate simple‐to‐use technologies, including molecular‐based diagnostic platforms, that can be deployed closer to suspect cases of FMD. In this context, FMD virus (FMDV)‐specific reverse transcription loop‐mediated isothermal amplification (RT‐LAMP) and real‐time RT‐PCR (rRT‐PCR) assays, compatible with simple sample preparation methods and in situ visualization, have been developed which share equivalent analytical sensitivity with laboratory‐based rRT‐PCR. However, the lack of robust ‘ready‐to‐use kits’ that utilize stabilized reagents limits the deployment of these tests into field settings. To address this gap, this study describes the performance of lyophilized rRT‐PCR and RT‐LAMP assays to detect FMDV. Both of these assays are compatible with the use of fluorescence to monitor amplification in real‐time, and for the RT‐LAMP assays end point detection could also be achieved using molecular lateral flow devices. Lyophilization of reagents did not adversely affect the performance of the assays. Importantly, when these assays were deployed into challenging laboratory and field settings within East Africa they proved to be reliable in their ability to detect FMDV in a range of clinical samples from acutely infected as well as convalescent cattle. These data support the use of highly sensitive molecular assays into field settings for simple and rapid detection of FMDV.
Nonlinear system modeling with deep neural networks and autoencoders algorithm

Deep learning techniques have been successfully used for pattern classification. These advantage methods are still not applied in nonlinear systems identification. In this paper, the neural model has deep architecture which is obtained by a random search method. The initial weights of this deep neural model is obtained from the denoising autoencoders model. We propose special unsupervised learning methods for this deep learning model with input data. The normal supervised learning is used to train the weights with the output data. The deep learning identification algorithms are validated with three benchmark examples.
Benchmarking of Prelicensure Nursing Students’ Evidence-Based Practice Knowledge

Evidence-based practice (EBP) knowledge among prelicensure nursing students was measured before, immediately following, and 1 year after completion of an EBP course using a relatively new instrument. There was a significant increase in EBP knowledge immediately following the course, and knowledge was sustained 1 year later. Results enabled faculty to gauge the effectiveness of the EBP course within the curriculum to prepare students with the knowledge needed to enact EBP in practice.
Unexpected Foraminiferal Diversity Revealed by Small-subunit rDNA Analysis of Antarctic Sediment

Abstract Studies of benthic Foraminifera typically rely on the morphological identification of dried specimens. This approach can introduce sampling bias against small, delicate, or morphologically ambiguous forms. To overcome this limitation, we extracted total DNA from sediment followed by PCR using group- and species-specific primers. Phylogenetic analyses revealed that approximately ninety percent of the PCR products represented previously undescribed sequence types that group with undersampled members of the allogromiid Foraminifera. We also used a modification of this technique to track individual species in sediment fractions too fine for normal morphological identification, and to confirm species placement of morphologically ambiguous foraminiferans. We were able to identify the DNA of several large foraminiferal species in fine fractions in a seasonally-dependent manner, indicating that in some seasons the majority of the standing stock of these species exists as gametes/juveniles. The approach outlined here represents a powerful strategy for exploring the total diversity of benthic foraminiferal communities.
Data Transfer via Alternative Conduits: Using Fluid Networks

Digital convergence has reshaped a gamut of industry demographics in the 21C, comprised of cloud computing, healthcare, pharmaceutical, consumer supplies, government, defense, manufacturing, entertainment, and even on-line education, among many others. At the center of the web-convergence lies the problem of network bandwidth limitation. Traditionally, research has focused on two major resolution strategies in parallel: data compression to minimize the network traffic ( i.e. algorithmic; software) and alternative conduit for data transfer such as wireless ( i.e. infrastructural; hardware). Building a network infrastructure is extremely costly. In addition, maintenance and upgrade costs may be prohibitive, given the U.S. consumer demographics. To this end, the emphasis is placed on seeking existing infrastructure which connects business and residential entities. The objective of this research, therefore, is to seek the possibility and feasibility of (digital) data transfers via the extensive water and/or sewer network(s), while minimizing structural modifications to the existing infrastructure. To date, sonar has been proven to be effective. If successful, the value of this intellectual property may be immeasurable.
Passively Mode-Locked Fiber Laser Based on Reduced Graphene Oxide on Microfiber for Ultra-Wide-Band Doublet Pulse Generation

Graphene with zero-band gap can be easily saturated under strong excitation due to Pauli blocking. In this work, the graphene oxide membrane is reduced on the surface of microfiber by use of high temperature heating. Such reduced graphene oxide can interact with the strong evanescent field of the microfiber and enable saturable absorption in passively mode-locked fiber laser. The system can be effectively utilized to directly generate ultra-wide-band doublet pulses for high-capacity wireless communication applications.
Transformational Partnerships: Developing Effective University-enterprise Cooperation

This paper deals with the engagement of Higher Educational Institutions (HEIs) with the outside world, and how academic institutions build their relations with public, private and professional organisations. The research explores university-enterprise relations and the issues of employability of students in the 21st century, how universities respond to new demands and requirements in this field. The current research is based on the analysis of strategic planning in UK universities and considers several case studies as examples of developing mutually beneficial ‘transformational’ university-enterprise partnerships. The research analysis of the collected data aims to explore the importance of university-enterprise partnerships for students, academics, universities, and employers and how universities ensure effective developments in the field. The results of the research show that strategic planning is key in developing effective university-enterprise relations, and the strategic targets can only be achieved when there is evidence of active engagement of university staff and students in the process cooperation with enterprises.
Colon‐cancer cell variants producing regressive tumors in syngeneic rats, unlike variants yielding progressive tumors, attach to interstitial collagens through integrin α2β1

Nine clones of tumor cells, derived from a single rat colon carcinoma, were analyzed for their adhesive properties and in vivo growth patterns. Four clones (denoted REG) gave rise to regressively growing tumors. Cells from the 4 REG clones attached significantly better to collagen types I and III than did cells from the 5 clones (denoted PRO) which grew progressively in vivo. In contrast, REG and PRO clones did not differ in their attachment to collagen type IV, laminin or fibronectin. The attachment of REG cells to collagen was dependent on Mg2+, but not Ca2+. Monospecific rabbit IgG to rat integrin β1‐chain inhibited REG cell attachment to collagen, demonstrating involvement of a β1 integrin in this process. PRO and REG cells expressed an underglycosylated β1 chain (Mr ∼ 105,000) that was somewhat smaller than β1‐chains described previously on rat fibroblasts and hepatocytes (Mr ∼ 115,000). Monoclonal IgG to rat integrin α2β1, but not to α1β1, readily inhibited REG cell attachment to collagen, demonstrating the involvement of integrin α2β1. However, β1 and α2 integrin subunits were found in purified glycoproteins from both PRO and REG cells. This suggests that α2β1 integrin is expressed by both cell variants, but is functional as a collagen receptor on REG cells only. In this system of tumor‐cell variants, the clear‐cut differences in attachment to interstitial collagens of the 9 clones suggest a possible relationship between this attachment and the capacity to induce progressive or regressive tumors. © 1996 Wiley‐Liss, Inc.
FcVcA: A fuzzy clustering-based vehicular cloud architecture

Recently, involving wireless communication technologies in deployment of new vehicular networks becomes more attracting to the research community and vehicle manufacturers. It is beneficial in providing intelligent transportation system as well as new assistant services to drivers. However, the limitation of resources in mobile vehicles is a significant technical challenge in the deployment of new applications. In this paper, we propose a new vehicular cloud architecture used clustering technique to group vehicles and provide resources cooperatively. We make the cluster structure flexible by using the fuzzy logic in the cluster head selection procedure. Also, performance of the proposed architecture is evaluated using extensive simulation and its efficiency is demonstrated through comparison with other existing approaches.
QUANTITATIVE ANALYSIS ON THE LEVEL OF IBS ACCEPTANCE IN THE MALAYSIAN CONSTRUCTION INDUSTRY

This IBS Survey report continues a practice that began in 2003. The first report was published in 2003 followed by in 2005 and in 2008. It records recent trends in selected areas that reflect Malaysia’s achievement on the IBS usage in building construction industry. Due to the dynamic economic and technological changes, IBS usage reports have been increasingly important. The design of the quantitative survey in IBS acceptance questionnaire is based on the Technology Acceptance Model (TAM). The comparison was done between the class of contractors G7 and the combined groups of G6, G5, and G4. The t-test analysis shows that all the class of contractors (G7, G6, G5 and G4) have a common agreement on the awareness of IBS and IBS actual use (the benefits of using IBS in construction) but have a significant difference in opinion on IBS actual use (the problems faced in using IBS and promotion of IBS by the government through CIDB), perceived ease of IBS use and perceived IBS usefulness. However, there are items in the variable that show significant difference between the comparison groups.
Establishment of differential expression profiles from invasive and non-invasive pituitary adenomas.

OBJECTIVE To establish high resolution, reproducible 2-dimensional electrophoresis (2-DE) profiles of invasive and non-invasive pituitary adenoma tissues and to identify differentially expressed proteins between the invasive and non-invasive tissues. METHODS The proteome from invasive and non-invasive pituitary adenomas tissues was dissected and analyzed by: (1) immobilized pH gradient two-dimensional polyacrylamide gel electrophoresis, (2) silver staining, (3) imageMaster 2-D software analysis, (4) peptide mass fingerprint based (PMS) on matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS), and (5) database comparison. RESULTS High-resolution 2-D patterns of invasive and non-invasive pituitary adenoma tissues were successfully produced and repeated 3 times for each sample. An average of 1 080+/-24 and 1 035+/-28 spots were detected for invasive and non-invasive pituitary adenoma tissues, respectively. Additionally, 975+/-45 and 918+/-56 spots were found to have an average matching rate of 90.3% and 88.7% for invasive and non-invasive tissues, respectively. The spot positional deviation was (1.563+/-0.259) mm for IEF and (1.088+/-0.206) mm for SDS-PAGE. A total of 99 spots of differential expression were matched between the invasive and non-invasive pituitary adenoma tissues. Thirty differential proteins, some of which were involved in the regulation of cells cycle and signal transduction, were initially characterized by PMS. CONCLUSION The acquisition of well-resolved and reproducible 2-D patterns of invasive and non-invasive pituitary adenoma tissues and the identification of differentially expressed proteins provides a proteome database for invasive pituitary adenomas.