Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrating knowledge from social and natural sciences for biodiversity management: The asymmetric information trap

Most problems related to biodiversity management have an ecological as well as a socio-economic dimension. Consequently, there has been a growing recognition that adequate management recommendations directed at such problems can only be developed if knowledge from ecology, economics and various social science disciplines is taken into account in an integrated manner. To respond to the need for integrated research, a number of approaches have been proposed over the last decade or so with the aim of integrating knowledge from the natural and social sciences. These approaches emerged in different contexts and have integrated different disciplines. As the recognition of the need for integrated research is rather recent the approaches that integrate natural and social sciences are still in a phase of development. In order to further this development, a better understanding of how to tackle specific challenges that arise when knowledge from different disciplines is integrated may be helpful. The aim of this paper is to contribute to this task by analysing and comparing how selected approaches cope with one key challenge of integration: ensuring that state-of-the-art knowledge from both disciplines is used in the integrated approach. We selected the following approaches for comparison: Ecological-economic modelling, political ecology, the resilience approach, multi criteria analysis, and methods of material and energy flow accounting (MEFA) of socio-ecological systems. [. ]
Sincast: a computational framework to predict cell identities in single-cell transcriptomes using bulk atlases as references

Characterizing the molecular identity of a cell is an essential step in single cell RNA-sequencing (scRNA-seq) data analysis. Numerous tools exist for predicting cell identity using single cell reference atlases. However, many challenges remain, including correcting for inherent batch effects between reference and query data and insufficient phenotype data from the reference. One solution is to project single cell data onto established bulk reference atlases to leverage their rich phenotype information. Sincast is a computational framework to query scRNA-seq data based on bulk reference atlases. Prior to projection, single cell data are transformed to be directly comparable to bulk data, either with pseudo-bulk aggregation or graph-based imputation to address sparse single cell expression profiles. Sincast avoids batch effect correction, and cell identity is predicted along a continuum to highlight new cell states not found in the reference atlas. In several case study scenarios, we show that Sincast projects single cells into the correct biological niches in the expression space of the bulk reference atlas. We demonstrate the effectiveness of our imputation approach that was specifically developed for querying scRNA-seq data based on bulk reference atlases. We show that Sincast is an efficient and powerful tool for single cell profiling that will facilitate downstream analysis of scRNA-seq data.
Picoplankton Diel Variability and Estimated Growth Rates in Epipelagic and Mesopelagic Waters of the Central Red Sea

The diel variability of the abundance and cell size of picoplanktonic groups in the central Red Sea was monitored every 2 h in situ on 4 occasions (once per season) from 2015 to 2016. We distinguished Prochlorococcus, low (LF-Syn) and high (HF-Syn) fluorescence Synechococcus, small (Speuk) and large (Lpeuk) picoeukaryotes and two groups of heterotrophic prokaryotes of low (LNA) and high (HNA) nucleic acid content. The diel variability in abundance was less marked than in cell size and more apparent in autotrophs than heterotrophs. Specific growth rates were estimated by an empirical relationship from measurements obtained in bottle incubations of surface and deep samples collected in the winter compared with in situ variations in cell size over 24 h. Autotrophic picoplankton groups generally grew faster (0.23–0.77 d–1) than heterotrophic prokaryotes (0.12–0.50 d–1). Surface to 100 m depth-weighted specific growth rates displayed a clear seasonal pattern for Prochlorococcus, with maxima in winter (0.77 ± 0.07 d–1) and minima in fall (0.52 ± 0.07 d–1). The two groups of Synechococcus peaked in spring, with slightly higher growth rates of LF-Syn (0.57 ± 0.04 d–1) than HF-Syn (0.43 ± 0.04 d–1). Speuk and Lpeuk showed different seasonal patterns, with lower values of the former (0.27 ± 0.02 and 0.37 ± 0.04 d–1, respectively). HNA consistently outgrew LNA heterotrophic prokaryotes, with a higher growth in the epipelagic (0–200 m, 0.36 ± 0.03 d–1) than in the mesopelagic (200–700 m, 0.26 ± 0.03 d–1), while no differences were found for LNA cells (0.19 ± 0.03 d–1 and 0.17 ± 0.02 d–1, respectively). With all data pooled, the mean diel abundances of autotrophic picoplankton in the upper epipelagic and of HNA cells in the epipelagic and mesopelagic layers were significantly correlated with the specific growth rates estimated from cell size variations. Our high-resolution sampling dataset suggests that changes in growth rates underlie the noticeable seasonality of picoplankton recently described in these tropical waters.
Fluid structure interaction modelling of cables used in civil engineering structures

Long, thin, flexible cylindrical elements of large scale structures are heavily influenced by the fluid flow around them. Equally, their movement has an appreciable effect on the fluid flow. This two-way interaction leads to complex dynamic behaviour that can cause fatigue and thus reduce operational lifetime. As demand for longer span bridges and drilling in deeper marine environments increases, research into the best modelling practice of this scenario gains importance. The work described in this thesis establishes a suitable method to model in CFD aero/hydro-elastic behaviour of slender cylindrical elements in large scale structures. In order to achieve this outcome, the author has: modelled the drag crisis on a static cylindrical element; developed a suitable FSI coupling program; combined the drag crisis model with the FSI coupling program and validate against published experimental data. The turbulence formulation used was carefully chosen taking into account the flow features that are important to the onset of the drag crisis. An LES formulation capable of adapting the model constant of the SGS model according to local shear conditions was identied as the best candidate to achieve this aim. The fluid and structural solvers used were loosely coupled by an explicit method that achieved a balance of kinetic energy as well as matching displacement at the moving fluid/solid interface. The integration method and implementation of this coupling strategy was verified by running a test case at low Reynolds number that produced a regular sinusoidal lift function on the cylinder that was kept stationary. The displacement, velocity, and acceleration response produced by the structural solver was compared against a closed solution and found to match with an acceptable level of error. A number of FSI simulations with the cylinder free to move in the cross-flow direction only was carried out. The displacement response was compared against published numerical and experimental data and the importance of having a sufficient spanwise dimension of flow domain was highlighted. Simulations with the cylinder free to move in the along-flow direction aswell as cross-flow direction were carried out. In some simulations where lock-in was observed, the effect of the drag crisis was clearly seen. Energy entered into the system as a result of low drag on the upstream motion of the cylinder caused by the drag crisis. More simulations at different velocities are recommended to define a displacement response curve and make further new observations.
SHORE: Hardware/Software Method for Memory Safety Acceleration on RISC-V

Memory corruption vulnerabilities can lead to software attacks. Pointer-based memory safety protection has been shown as a promising solution covering both out-of-bounds and use-after-free errors. Software only approaches have significant performance overhead. Existing hardware/software implementations are largely limited to proprietary closed-source microprocessors, simulation-only studies or require changes to the input source code.In this paper, we present a novel hardware/software co-design methodology consisting of a RISC-V based processor extended with new instructions and microarchitecture enhancements, enabling faster memory safety checks. A compiler is instrumented to provide security operations taking into account the changes to the processor. The entire system is realized by enhancing a RISC-V Rocket-chip system-on-chip (SoC)1. The resultant processor SoC is implemented on an FPGA and evaluated with applications from SPEC 2006 (for generic applications), MiBench (for embedded applications), and Olden benchmark suites for performance. Our experiments show that the proposed approach achieves up to 3. 79X speedup (average 2. 6X) in comparison to the traditional software-based approach for SPEC2006 while possessing an overhead of 6.33% in terms of area. This speedup is better than the state-of-the-art approach. Our security coverage using the NIST Juliet test suite shows better coverage than the software only method.
Deep Reinforcement Learning-Based Power Allocation for Ultra Reliable Low Latency Communications in Vehicular Networks

Ultra reliable and low latency communication (uRLLC) is of extreme importance in vehicular networks. To ensure the stringent quality of service of uRLLC in vehicular networks, this paper proposes a deep reinforcement learning-based power allocation scheme. Specifically, we formulate the power allocation problem to maximize the long-term averaged system capacity subject to the system reliability and latency constraints considering the finite blocklength constraint. It is analyzed that the problem is non-convex and intractable by the traditional optimization methods. To deal with the problem, we resort to a deep reinforcement learning (DRL) algorithm, which is widely referred as the deep deterministic policy gradient (DDPG) method, to learn the optimal policy with imperfect instantaneous channel state information (CSI). Simulation results reveal that our proposed DDPG-based power allocation algorithm can not only increase the long-term averaged system capacity but also greatly enhance the latency and reliability performance, compared with the traditional DRL-based power allocation algorithms.
Photonic Radio Frequency Memory - Design Issues and Possible Solutions

Abstract : False target generation, range and velocity gate pull-off are Electronic Attack (EA) techniques in which received radar pulses are stored, then read out and re-transmitted back to the source radar after the desired length of time. The memory can be either a recirculating delay line or a digital radio-frequency (RF) memory (DRFM). The DREM stores a digitized sample of each received pulse, which can provide high fidelity of the analogue-digital conversion process has sufficient dynamic range. The speed of digital signal processing and memory plays a critical role in DRFM design. The analogue-digital conversion process and bit-rate limit the range of frequencies that DRFMs can cover. Photonics is currently being investigated to implement EA techniques such as false target generation, range and velocity gate pull-off. To fully take advantage of the unique benefits offered by photonics to implement EA techniques, the development of photonic RF memory (PRFM) is required. PRFM can potentially cover frequencies from near DC to 110 GHz, which are of interest in Electronic Warfare (EW). Photonic technology offers the opportunity for high fidelity signal storage without the use of down-conversion or analogue-to-digital converters. In this report, design issues and possible solutions of PRFM are discussed to assist with the ongoing experimental investigation.
Hybrid Model of Quantum Transfer Learning to Classify Face Images with a COVID-19 Mask

The problem of the COVID-19 disease has determined that about 219 million people have contracted it, of which 4.55 million died. This importance has led to the implementation of security protocols to prevent the spread of this disease. One of the main protocols is to use protective masks that properly cover the nose and mouth. The objective of this paper was to classify images of faces using protective masks of COVID-19, in the classes identified as correct mask, incorrect mask, and no mask, with a Hybrid model of Quantum Transfer Learning. To do this, the method used has made it possible to gather a data set of 660 people of both sexes (man and woman), with ages ranging from 18 to 86 years old. The classic transfer learning model chosen was ResNet-18;the variational layers of the proposed model were built with the Basic Entangler Layers template for four qubits, and the optimization of the training was carried out with the Stochastic Gradient Descent with Nesterov Momentum. The main finding was the 99.05% accuracy in classifying the correct Protective Masks using the Pennylane quantum simulator in the tests performed. The conclusion reached is that the proposed hybrid model is an excellent option to detect the correct position of the protective mask for COVID-19.
Acceptability of Road User Charging: Meeting the Challenge

This chapter aims to identify the factors that limit the acceptability of road user charging (RUC), and also to consider various ways in which they can be addressed. Current knowledge about public attitudes and acceptability are reviewed, and these are compared with professional viewpoints. Specific issues are then identified that need to be recognized and dealt with in order to maximize public acceptance. A set of guidelines is proposed that outlines the stages that should be followed to introduce a successful RUC scheme. Some of the practical means by which public support can be increased are considered, and Edinburgh is used as an example of how stakeholder views can be included in the design process. Lastly, the chapter draws some general policy conclusions and identifies future research needs.
Virtual Team Member Perspectives on Personal Development: A Sequential Explanatory Study

The use of virtual teams in organizations has shifted upward exponentially since the onset of COVID–19, yet available research does not include findings based on workplace virtual team members, as opposed to student populations. Research is limited on what virtual workplace team members consider important in the performance coaching and personal development processes. Research on virtual team member perspectives is valuable for human resource professionals and organizational leaders and particularly helpful to organizations struggling to respond to the new work–at–home environment. The purpose of the mixed–methods study was to explore the perspectives of virtual team members about how performance coaching, mentoring, and training contribute to their personal development. Participants for the study were members of social network virtual team groups who have been members of virtual work teams. The sequential explanatory study data was from a sample of 149 virtual team members (12 for the pilot survey and 137 for the full study). The Kruskal–Wallis results led to the rejection of the null hypothesis at an overall significance level of 0.05, with significance levels of 0.014 for coaching and 0.008 for mentoring, indicating a perceived positive contribution from performance development efforts (coaching and mentoring) on the personal development of individual virtual team members. These results on the interpersonal aspects of virtual teams from team members and consideration of perspectives on their personal development provide organizations, leadership, and human resources professionals, valuable information to improve virtual teams and the team member experience in normal and unusual work situations.
Coordinating change: introducing pluralism in the assessment of a humanities module for improved engagement and attainment of first year architecture students

This paper reports on the process of diversifying assessment of the ‘History and Theory of Architecture and Design’ module at Level 1 in the undergraduate Architecture course at the University of Lincoln, UK. Replacing essays (the traditional form of assessment for theoretical subjects in our school) with other types of assignments was a strategic response to the mixture of academic ability shown in the last decade by first year students; amongst other things, this variety of knowledge and skills is a reflection of the liberalisation of Higher Education in the UK, which increased the diversity of student backgrounds along with the internationalisation of the course (RIBA 2012:7). In addition, statistically (James 2003), creative courses attract a higher incidence of dyslexia than other subjects. In this context, written assignments represented a deficit model of assessment, the solution being to make assessments less dependent on language and the module more immersive and participatory than traditional theoretical subjects, with assignments becoming episodes of active learning. The change in assessment was also seen as an opportunity to re-orient theoretical submissions to become more relevant to practice in architecture. This paper details the reasons and scope of the modifications, describes methods used, within the constraints currently placed on Higher Education in general and Schools of Architecture in particular, and comments on the consequences of these changes for students and academics, from the author’s point of view, as module coordinator.
WCDMA for UMTS: HSPA Evolution and LTE

As wireless communications technologies evolve, Wideband Code Division Multiple Access (WCDMA) seems a strong candidate for providing multimedia to the handset, as well as Universal Mobile Telecommunications Services (UMTS)--which is to say common wireless communications standards over most of the world. WCDMA for UMTS sets out to decipher the standards documents of the Third Generation Partnership Project (3GPP). Specifically, this book deals with the 3GPP documents on Frequency Division Duplex (FDD) and Time Division Duplex (TDD) for Universal Terrestrial Radio Access (UTRA). This book should prove valuable to readers who plan to implement WCDMA in hardware designs or service offerings. A series of engineering problems make up the backbone of the book, and each part of the deployment process is explained via text and calculations. For example, in the discussion on planning a radio network for WCDMA service provision, the book explains precisely how to take into account requirements (for quality of service, user capacity, and coverage) and conditions (such as terrain). Readers get formulas into which they can plug relative traffic predictions for voice, real-time data, non-real-time data, and overhead. There's also an explanation of how to interpret the formula output for deploying antennae. This is a serious engineering handbook for those who are involved in deploying WCDMA. --David Wall Topics covered: Wideband Code Division Multiple Access (WCDMA)--what it is, and (especially) how to implement it in a wireless network. Radio interface protocols, packet traffic, and network planning all are covered.
Switch voltage control versus switch current control method-principle and realization

New control methods for DC-DC voltage and current converters are studied. A brief introduction to switching network graph theory, focusing on the duality concept, is given. Starting with the open switch voltage control method, which is the topological dual of the current-programming technique, a comparative study of switch control methods reported in the literature is presented. The basic principles, realization, and the resulting performance of the set of control methods and some topological applications to switching electrical networks are discussed. Relevant experiments implementing switch voltage control are presented. <<ETX>>
Physiological Aspects of Sport Training and Performance

Part 1 Physiological adaptations to exercise: neuromuscular system and exercise endocrine system and exercise metabolic system and exercise cardiovascular system and exercise immunological system and exercise. Part 2 Exercise training principles and prescriptions: principles of training resistance training anaerobic conditioning and the development of speed and agility endurance training concurrent training periodization plyometrics warm-up and flexibility athletic performance testing. Part 3 Nutrition, fluid regulation and ergogenic aids: sports nutritiion hydration ergogenic aids. Part 4 Environmental factors: exercise in the heat exercise in the cold exercise at altitude. Part 5 Medical and health conditions: overtraining diabetes exercise-induced asthma.
Letermovir Prophylaxis and Cytomegalovirus Reactivation in Adult Hematopoietic Cell Transplant Recipients with and without Acute Graft Versus Host Disease

Simple Summary Cytomegalovirus (CMV) infection and graft versus host disease (GVHD) both contribute to increased morbidity and mortality following allogeneic hematopoietic cell transplantation (allo-HCT). Since the development of GVHD can increase a patient’s risk of developing CMV infection post-allo-HCT, the aim of our retrospective study was to assess the effectiveness of letermovir prophylaxis in preventing CMV infection in these patients at high risk for CMV reactivation. Letermovir is an antiviral approved for the prevention of CMV infection. This study demonstrated that patients with GVHD had significantly fewer CMV infections when they received letermovir prophylaxis compared to patients who did not receive letermovir. Abstract Cytomegalovirus (CMV) is the most clinically significant infection after allogeneic hematopoietic-cell transplantation (allo-HCT) and is associated with increased mortality. The risk for CMV reactivation increases with graft versus host disease (GVHD). GVHD contributes to significant morbidity and mortality and is treated with immunosuppressive therapies that can further increase CMV infection risk. Prophylaxis with letermovir, an oral antiviral approved to prevent CMV, has been shown to decrease the incidence of CMV infection post-allo-HCT in patients at high risk of CMV reactivation, but there is a lack of data confirming this benefit in patients with GVHD. In this single-center, retrospective study, we assessed the incidence of clinically significant CMV infection (CS-CMVi) in allo-HCT patients who received letermovir prophylaxis (n = 119) and who developed aGVHD compared to a control group (n = 143) who did not receive letermovir. Among aGVHD patients, letermovir prophylaxis decreased CS-CMVi in patients with aGVHD (HR 0.08 [95% CI 0.03–0.27], p < 0.001), reduced non-relapsed mortality (p = 0.04) and improved overall survival (p = 0.04). This data suggests that letermovir prophylaxis improves outcomes by preventing CS-CMVi in patients with aGVHD.
A subspace-based array shape estimation method using a single reference source in nearfield

This paper proposes a subspace-based array shape estimation method using a single reference source in nearfield. First, from the nearfield source received by hydrophones, setting the degree of freedom of the perturbation equal to one, a nearfield covariance matrix is derived. Second, a simplified subspace fitting method that requires only a single reference source is proposed. From the numerical experiments, the proposed method shows good performance in estimating the shape of the array using only a single reference source wherever the source exists.