Miracle-dz/UniFAR-FTUs huggingface dataset:
How Choice of Depth Horizon Influences the Estimated Spatial Patterns and Global Magnitude of Ocean Carbon Export Flux

Estimated rates and efficiency of ocean carbon export flux are sensitive to differences in the depth horizons used to define export, which often vary across methodological approaches. We evaluate sinking particulate organic carbon (POC) flux rates and efficiency (e‐ratios) in a global earth system model, using a range of commonly used depth horizons: the seasonal mixed layer depth, the particle compensation depth, the base of the euphotic zone, a fixed depth horizon of 100 m, and the maximum annual mixed layer depth. Within this single dynamically consistent model framework, global POC flux rates vary by 30% and global e‐ratios by 21% across different depth horizon choices. Zonal variability in POC flux and e‐ratio also depends on the export depth horizon due to pronounced influence of deep winter mixing in subpolar regions. Efforts to reconcile conflicting estimates of export need to account for these systematic discrepancies created by differing depth horizon choices.
Oversold and underused : computers in the classroom

Impelled by a demand for increasing American strength in the new global economy, many educators, public officials, business leaders, and parents argue that school computers and Internet access will improve academic learning and prepare students for an information-based workplace. Just how valid is this argument? In "Oversold and Underused", Larry Cuban argues that when teachers are not given a say in how the technology might reshape schools, computers are merely souped-up typewriters and classrooms continue to run much as they did a generation ago. In his studies of early childhood, high school, and university classrooms in Silicon Valley, he found that students and teachers use the new technologies far less in the classroom than they do at home, and that teachers who use computers for instruction do so infrequently and unimaginatively. Cuban points out that historical and organizational economic contexts influence how teachers use technical innovations. Computers can be useful when teachers sufficiently understand the technology themselves, believe it will enhance learning, and have the power to shape their own curricula. But these conditions can't be met without a broader and deeper commitment to public education beyond preparing workers. More attention, Cuban says, needs to be paid to the civic and social goals of schooling, goals that make the question of how many computers are in classrooms trivial.
45 o CONGRESO ESPAÑOL DE ACÚSTICA 8 o CONGRESO IBÉRICO DE ACÚSTICA EUROPEAN SYMPOSIUM ON SMART CITIES AND ENVIRONMENTAL ACOUSTICS CHARACTERIZATION OF THE ULTRASONIC ACOUSTIC FIELD OF A WIND TURBINE PACS

Wind energy is a sector of the alternative energy industry that is growing worldwide. However, there are concerns regarding bat fatalities at wind turbines. This phenomenon is widespread and has received attention to warrant investigation into how and why these collisions occur. In this paper we characterize the ultrasonic acoustic field of a wind turbine in order to find out if the turbines emit ultrasound. We conducted this study at Serra dos Candeeiros near Lisbon, Portugal, where some bats have been found injured or dead beneath wind turbines [1]. The measurements were divided into 3 different campaigns: 1) seven acquisitions at ground level in front of the nacelle, 2) five acquisitions around the turbine at ground level and 3) one acquisition inside the nacelle. The analysis of the results shows that the analysed wind turbine does not reveal any ultrasound noise source.
Thematic Analysis for Classifying the Main Challenges and Factors Influencing the Successful Implementation of E-learning System Using NVivo

The problem of low usage of e-learning system still exists due to some factors that cause students' reluctance to use this system. However, the successful implementation of e-learning system relies on understanding the adoption factors as well as the main challenges that face the current e-learning systems. There is lack of agreement about the main factors that shape the successful adoption of e-learning system; hence, a clear gap has been identified in the knowledge on the critical factors of e-learning adoption. Therefore, this research seeks to explore the main challenges that face the current e-learning systems and investigate the main factors that support the adoption of e-learning system. This study employed the interview approach using thematic analysis through NVivo software. The interview was conducted with 31 experts in e-learning systems at five Jordanian universities. The results highlight 20 e-learning adoption factors and challenges that strengthen the findings from previous literature. The study reveals e-learning system adoption factors and challenges, namely, change management issues, financial support issues, e-learning system quality factors, culture factors, Self-efficacy factors and trust factors, which unexplored in e-learning system adoption literature previously.
Last-Iterate Convergence Rates for Min-Max Optimization: Convergence of Hamiltonian Gradient Descent and Consensus Optimization

While classic work in convex-concave min-max optimization relies on average-iterate convergence results, the emergence of nonconvex applications such as training Generative Adversarial Networks has led to renewed interest in last-iterate convergence guarantees. Proving last-iterate convergence is challenging because many natural algorithms, such as Simultaneous Gradient Descent/Ascent, provably diverge or cycle even in simple convex-concave min-max settings, and there are relatively few papers that prove global last-iterate convergence rates beyond the bilinear and convex-strongly concave settings. In this work, we show that the H AMILTONIAN G RADIENT D ESCENT (HGD) algorithm achieves linear convergence in a variety of more general settings, including convex-concave problems that satisfy a sufﬁciently bilinear condition. We also prove convergence rates for stochastic HGD and for some parameter settings of the Consensus Optimization algorithm of Mescheder et al. (2017).
The changing face of the Mediterranean – Land cover, demography and environmental change: Introduction and overview

This paper introduces a special issue on The Changing Face of the Mediterranean: Land Cover, Demography, and Environmental Change, which brings together up-to-date regional or thematic perspectives on major long-term trends in Mediterranean human–environment relations. Particularly, important insights are provided by palynology to reconstruct past vegetation and land cover, and archaeology to establish long-term demographic trends, but with further significant input from palaeoclimatology, palaeofire research and geomorphology. Here, we introduce the rationale behind this pan-Mediterranean research initiative, outline its major sources of evidence and method, and describe how individual submissions work to complement one another.
An On-Chip Self-Characterization of a Digital-to-Time Converter by Embedding it in a First-Order Loop

To characterize an on-chip programmable delay in a low-cost and high-resolution manner, a built-in self-test based on a first-order time-to-digital converter with self-calibration is proposed and implemented in TSMC 28-nm CMOS. The system is self-contained, and only one digital clock is needed for the measurements. A system self-calibration algorithm is proposed to calibrate nonlinearities of the analog circuitry. The operation is robust over PVT variations since the delay information is normalized to the input clock period. To verify the proposed idea, two different digital-to-time converters performing the on-chip delay are measured and analyzed at 50-MHz clocking frequency with 0.65-ps standard time deviation per measurement.
Is Automated Topic Model Evaluation Broken

Topic model evaluation, like evaluation of other unsupervised methods, can be contentious. However, the field has coalesced around automated estimates of topic coherence, which rely on the frequency of word co-occurrences in a reference corpus. Contemporary neural topic models surpass classical ones according to these metrics. At the same time, topic model evaluation suffers from a validation gap : automated coherence, developed for classical models, has not been validated using human experimentation for neural models. In addition, a meta-analysis of topic modeling literature reveals a substantial standardization gap in au- tomated topic modeling benchmarks. To address the validation gap, we compare automated coherence with the two most widely accepted human judgment tasks: topic rating and word intrusion. To address the standardization gap, we systematically evaluate a dominant classical model and two state-of-the-art neural models on two commonly used datasets. Automated evaluations declare a winning model when corresponding human evaluations do not, calling into question the validity of fully automatic evaluations independent of human judgments.
Predicting the Evolution of COVID-19 Mortality Risk: a Recurrent Neural Network Approach

Background: The propagation of COVID-19 in Spain prompted the declaration of the state of alarm on March 14, 2020. On 2 December 2020, the infection had been confirmed in 1,665,775 patients and caused 45,784 deaths. This unprecedented health crisis challenged the ingenuity of all professionals involved. Decision support systems in clinical care and health services management were identified as crucial in the fight against the pandemic. Methods: This study applies Deep Learning techniques for mortality prediction in COVID-19 patients. Two datasets with clinical information (medication, laboratory tests, vital signs etc.) of 2,307 and 3,870 COVID-19 infected patients admitted to two Spanish hospital chains were used. Firstly, we built a sequence of temporal events gathering all the clinical information for each patient. Next, we used the temporal sequences to train a Recurrent Neural Network (RNN) model with an attention mechanism exploring interpretability. We conducted extensive experiments and trained the RNNs in different settings, performing hyperparameter search and cross-validation. We ensembled resulting RNNs to reduce variability and enhance sensitivity. Results: We assessed the performance of our models using both global metrics, by averaging the performance across all the days in the sequences. We also measured day-by-day metrics starting from the day of hospital admission and the outcome day and evaluated the daily predictions. Regarding sensitivity, when compared to more traditional models, our best two RNN ensemble models outperform a Support Vector Classifier in 6 and 16 percentage points, and Random Forest in 23 and 18 points. For the day-by-day predictions from the outcome date, the models also achieved better results than baselines showing system's ability towards early predictions. Conclusions: We have shown the feasibility of our approach to predict the clinical outcome (i.e. discharged alive or death) of patients infected with SARS-CoV-2. The result is a time series model that can support decision-making in healthcare systems and aims at interpretability. Despite the low-resource scenario, the results achieved are promising and suggests that more data will further increase the performance of the model.
Ionospheric Response to 22–23 June 2015 Storm as Investigated Using Ground‐Based Ionosondes and GPS Receivers Over India

In this paper, we present response of equatorial and low‐latitude ionosphere to 22/23 June 2015 geomagnetic storm using a chain of ground‐based ionosondes located at Tirunelveli (8.73°N,77.70°E; geomagnetic latitude: 0.32°N), Hyderabad (17.36°N, 78.47°E; geomagnetic latitude: 8.76°N), and Allahabad (25.45°N, 81.85°E; geomagnetic latitude: 16.5°N) along with a chain of GPS receivers. Uniqueness of this storm is that in contrast to the equatorial plasma bubbles that were detected in the European sector, we see suppression of plasma bubbles in the Indian sector. The observations suggest that westward penetration electric field during local midnight caused abrupt decrease of virtual height (h'F (km)) to ~200 km and suppressed plasma bubbles due to undershielding. Later, the layer increased to 500 km simultaneously due to overshielding effect. On 23 June, we observed negative storm in the Northern Hemisphere while positive storm in the Southern Hemisphere. In addition, absence of equatorial Es layers at Tirunelveli and presence of F3 layer at Tirunelveli/Hyderabad seem to be associated with equatorial electrojet (EEJ)/counter electrojet (CEJ) variations. However, on 24 June, we observed strong negative storm effects at Allahabad/Hyderabad, while positive storm effect at Tirunelveli. Simultaneous enhancement of h'F (km) at all three ionosonde stations at 20:30 UT on 23 June during recovery phase suggest eastward disturbance dynamo (DD) electric field that caused presunrise spread F at Hyderabad/Allahabad but void of spread F at Tirunelveli suggesting its midlatitude origin. Periodogram analysis of foF2 and h'F (km) in the present analysis suggest the presence of shorter periods (~< 2 h) associated with prompt penetration (PP) electric fields while larger periods (>2 h) associated with DD electric field/winds.
4 F eb 2 01 6 A Generalised Quantifier Theory of Natural Language in Categorical Compositional Distributional Semantics with Bialgebras

Categorical compositional distributional semantics is a m odel of natural language; it combines the statistical vector space models of words with the compositi onal models of grammar. We formalise in this model the generalised quantifier theory of natural language, due t o Barwise and Cooper. The underlying setting is a compact closed category with bialgebras. We start from a gen erative grammar formalisation and develop an abstract categorical compositional semantics for it, then instantiate the abstract setting to sets and relations and to finite dimensional vector spaces and linear maps. We pr ove the equivalence of the relational instantiation to the truth theoretic semantics of generalized quant ifiers. The vector space instantiation formalises the statistical usages of words and enables us to, for the first ti me, reason about quantified phrases and sentences compositionally in distributional semantics.
Stalloris: RPKI Downgrade Attack

We demonstrate the first downgrade attacks against RPKI. The key design property in RPKI that allows our attacks is the tradeoff between connectivity and security: when networks cannot retrieve RPKI information from publication points, they make routing decisions in BGP without validating RPKI. We exploit this tradeoff to develop attacks that prevent the retrieval of the RPKI objects from the public repositories, thereby disabling RPKI validation and exposing the RPKI-protected networks to prefix hijack attacks. We demonstrate experimentally that at least 47% of the public repositories are vulnerable against a specific version of our attacks, a rate-limiting off-path downgrade attack. We also show that all the current RPKI relying party implementations are vulnerable to attacks by a malicious publication point. This translates to 20.4% of the IPv4 address space. We provide recommendations for preventing our downgrade attacks. However, resolving the fundamental problem is not straightforward: if the relying parties prefer security over connectivity and insist on RPKI validation when ROAs cannot be retrieved, the victim AS may become disconnected from many more networks than just the one that the adversary wishes to hijack. Our work shows that the publication points are a critical infrastructure for Internet connectivity and security. Our main recommendation is therefore that the publication points should be hosted on robust platforms guaranteeing a high degree of connectivity.
Workshop: Combinatorics, Probability and Computing Table of Contents

One of the exciting phenomena in mathematics in recent years has been the widespread and surprisingly effective use of probabilistic methods in diverse areas. The probabilistic point of view has turned out to be very profitable in Discrete Mathematics, Analysis and Theoretical Computer Science. The meeting was dedicated to recent developments in these areas, focusing on the investigation of random graphs and probabilistic methods, on the study of stochastic processes including questions on percolation and random triangulations, on the design and analysis of randomized algorithms, and on the relationship between complexity and randomness. Mathematics Subject Classification (2000): 05D05, 05D10, 05D40, 68Q25. Introduction by the Organisers The conference was organized by Noga Alon (Tel Aviv), Béla Bollobás (Cambridge and Memphis) and Ingo Wegener (Dortmund). The programme consisted of 8 main lectures, supplemented by 21 shorter contributions, and covered many areas in Extremal and Probabilistic Combinatorics as well as in Theoretical Computer Science. In its simplest form, the Probabilistic Method refers to the technique of proving the existence of structures with unexpected properties by showing that a randomly chosen object from an appropriate probability distribution has the properties with positive probability. The probabilistic method has been strikingly successful in Combinatorics, Graph Theory and Combinatorial Number Theory, and the probabilistic point of view has had an enormous influence on theoretical computer science. 2876 Oberwolfach Report 48/2006 The speakers reported on recent developments in Ramsey theory, including variants of these problems for Random Graphs and for Geometric questions, extending classical work in Functional Analysis. Extremal graph and hypergraph theory has also been discussed extensively, combining combinatorial, probabilistic and analytic tools. Additional active topics discussed included Percolation on quasi-random graphs and the properties of random triangulations of point sets in the plane as well as novel results in Complexity Theory including connections between communication complexity and geometric problems, and the study of refutation proofs for random instances of satisfiability. The aim of the workshop was to focus on the connections and common themes of Combinatorics, Discrete Probability and Theoretical Computer Science. The diversity of the topics and participants stimulated a lot of fruitful discussions between researchers in different and yet related branches and gave rise to interesting discussions and new collaborations between the participants including the younger generation of researchers. 49 scientists, including 36 from countries other than Germany participated in the meeting. The organizers and participants would like to thank the Mathematisches Forschungsinstitut Oberwolfach for providing an inspiring setting for this conference. Combinatorics, Probability and Computing 2877 Workshop: Combinatorics, Probability and Computing
Knowledge and learning in online networks in development: a social-capital perspective

The authors examine whether the concept of social capital can facilitate our understanding of online networks in development. Much of the knowledge generation and social learning in development takes place in networks, which increasingly operate online. Although these networks are assumed to be a positive force in development, there are many unknown factors, partly because they are in their infancy. The concept of social capital has traditionally been applied to examine the functioning of groups and societies. More recently, it has also been applied to development and to online networks outside development. Three non-development approaches to examining social capital in online networks and communities are reviewed in the article. Elements of these approaches, combined with development-related aspects, are used to produce a framework to facilitate the analysis of social capital in online networks in a development context.
A study on physico-chemical parameters of Urinjikulam Pond, Thiruthangal (Virudhunagar District, Tamil Nadu)

Present paper deals with the study of Physico-chemical parameters of Urinjikulam pond, Thiruthangal (Virudhunagar district, Tamil Nadu). Monthly variations in the physical and chemical parameters such as temperature, pH (7.5 to 8.8), dissolved oxygen (1.62-5.92 mg/L), total alkalinity (81-271mg/L), total hardness (48 to 364mg/L), chlorides (11 to 1030mg/L), Phosphate (0.36 to 2.86mg/L) and nitrate (0 to 0.40mg/L) were investigated. All the parameters were beyond the permissible limits.
Rice Production, Income Diversification and Rural Development in Myanmar

Among agricultural produce, rice is still dominating the Myanmar’s agriculture sector, as it is a staple food crop and a principal export crop. Although previous market reforms and major investment in the agriculture sector have led to an increase in rice production, there have been challenges, such as limited availability of loans, poor infrastructure, application of farm inputs and the quality of seeds. My thesis comprises three essays that, together, fill the gaps in the existing literature on most of the key issues affect rural development in Myanmar. The first essay analyses the source and extent of potential productivity and efficiency gains, and investigates how Myanmar can increase its rice productivity. The data used in this thesis is taken from 634 farm households in the main rice growing regions, specifically Ayeyarwaddy, Bago and Sagaing. The stochastic production frontier and technical inefficiency models are applied to capture which farm-specific factors determine efficiency gains. The findings show that rice production in the selected regions can be improved through farm workers with better education, agricultural extension services, and efficient fertilizer and pesticide application. This essay also analyses the impact of land reforms and market reforms on rice production in Myanmar and Vietnam. Although there are differences between the two countries, especially in terms of government policy and institutions, both share some similarities when it comes to rice production. Vietnam is a more efficient rice producer than Myanmar, due to its better irrigation system, use of better quality seeds, higher application rate of fertilizers, and more intensive cropping. There may be many lessons for Myanmar to learn Vietnam’s to increase the quantity and quality of its rice production by applying certified seeds and efficient use of fertilizers, and using sufficient irrigated water. The second essay examines the impact of credit policy on rice production in the selected regions. The provision of agricultural credit is used as a major
AIS Electronic Library (AISeL)

Curriculum mapping is an important task in implementing, embedding and monitoring the knowledge, skills and attributes that graduates must acquire in their program of study. Curriculum mapping ensures correspondence between learning outcomes, learning activities and assessments. To aid in performing this complex task, many higher education institutions are using unit/study guide tools or curriculum mapping tools. These tools may be known under different names in different institutions but we will refer to these tools as unit guide information systems. To evaluate the utilisation and acceptance of these tools, this research-in-progress paper draws on an extensive body of literature related to technology acceptance that includes social cognitive theory and model of PC utilization to explain the influence of perceived usefulness and perceived ease of use. Our research extends the technology acceptance model by incorporating the external variables of self-efficacy, anxiety and social influence. The results are expected to indicate which of the external factors are most important in predicting and explaining attitude and intention to use unit guide information systems.