Miracle-dz/UniFAR-FTUs huggingface dataset:
Thermal acclimation of leaf respiration of tropical trees and lianas: response to experimental canopy warming, and consequences for tropical forest carbon balance

Climate warming is expected to increase respiration rates of tropical forest trees and lianas, which may negatively affect the carbon balance of tropical forests. Thermal acclimation could mitigate the expected respiration increase, but the thermal acclimation potential of tropical forests remains largely unknown. In a tropical forest in Panama, we experimentally increased nighttime temperatures of upper canopy leaves of three tree and two liana species by on average 3 °C for 1 week, and quantified temperature responses of leaf dark respiration. Respiration at 25 °C (R25) decreased with increasing leaf temperature, but acclimation did not result in perfect homeostasis of respiration across temperatures. In contrast, Q10 of treatment and control leaves exhibited similarly high values (range 2.5–3.0) without evidence of acclimation. The decrease in R25 was not caused by respiratory substrate depletion, as warming did not reduce leaf carbohydrate concentration. To evaluate the wider implications of our experimental results, we simulated the carbon cycle of tropical latitudes (24°S–24°N) from 2000 to 2100 using a dynamic global vegetation model (LM3VN) modified to account for acclimation. Acclimation reduced the degree to which respiration increases with climate warming in the model relative to a no‐acclimation scenario, leading to 21% greater increase in net primary productivity and 18% greater increase in biomass carbon storage over the 21st century. We conclude that leaf respiration of tropical forest plants can acclimate to nighttime warming, thereby reducing the magnitude of the positive feedback between climate change and the carbon cycle.
Secure Collaborative Integrity Verification for Hybrid Cloud Environments

A hybrid cloud is a cloud computing environment in which an organization provides and manages some internal resources and has others provided externally. However, this new environment could bring irretrievable losses to the clients due to a lack of integrity verification mechanism for distributed data outsourcing. To support scalable service and data migration, in this paper we address the construction of a collaborative integrity verification mechanism in hybrid clouds where we consider the existence of multiple cloud service providers to collaboratively store and maintain the clients' data. We propose a collaborative provable data possession scheme adopting the techniques of homomorphic verifiable responses and hash index hierarchy. In addition, we articulate the performance optimization mechanisms for our scheme and prove the security of our scheme based on multi-prover zero-knowledge proof system, which can satisfy the properties of completeness, knowledge soundness, and zero-knowledge. Our experiment.
Venture Capital in a Developing Country: The Case of the Philippines

In this paper we will present a summary of our initial research focusing on the development of the venture capital industry in the Philippines, which is a developing country that has recently been a recipient of significant venture capital investment. More specifically, we analyzed the impact of the lack of a fully developed institutional framework (primarily financial and legal) on the development of the venture capital industry in the Philippines. Fully developed institutions, which are characteristic of developed countries, are typically necessary for the efficient operations of Western venture capital firms. Yet recent venture capital investments have been flowing to developing countries in spite of the lack of fully developed institutions. We attempted to begin to identify unique characteristics and challenges facing venture capitalists operating in a developing country.
Experiments with Sentence Classification

We present a set of experiments involving sentence classification, addressing issues of representation and feature selection, and we compare our findings with similar results from work on the more general text classification task. The domain of our investigation is an email-based help-desk corpus. Our investigations compare the use of various popular classification algorithms with various popular feature selection methods. The results highlight similarities between sentence and text classification, such as the superiority of Support Vector Machines, as well as differences, such as a lesser extent of the usefulness of features selection on sentence classification, and a detrimental effect of common preprocessing techniques (stop-word removal and lemmatization).
Operating experience of shovel drives for mining applications

This paper presents an overview analysis and a discussion of field experience with different drive configurations used in shovel applications. The analysis includes different drive topologies, shovel duty cycles for A typical truck pass loading and energy regeneration capabilities. Special attention is given to the interaction between the high power shovel drives and grid harmonics injection, reactive power requirements, and voltage regulation. This paper presents operational experiences obtained in copper mine industries. The main characteristics of the newest shovels with active front end (AFE) at the line side are also included. Finally, a critical evaluation of the different topologies is presented, showing that the shovel drive operation strongly affects the behavior of the power distribution system and that the introduction of the AFE technology produces an important performance improvement.
Design and Implementation of a Tool to Detect Accounting Frauds

Accounting frauds of a company have direct and indirect effects on financial institutions. For instance, the well-known cases of Enron and WorldCom became a major scandal with worldwide repercussions in 2002. As a result, we began to pay attention to accounting transparency. Since then, many countries have established a law, a principle or a guide of accounting and accounting audit like Sarbanes-Oxley Act and Statements of Auditing Standards. However, some companies commit accounting frauds to manipulate, change or delete financial statements, despite these rules. The reason why companies do this is because they want to increase their stock prices. Thus, companies commit skillful frauds following accounting principles, which makes it difficult to detect a fraud unless one is a forensic accountant. In this paper we propose a method to detect accounts with fraud symptoms in financial statements which hide accounting frauds or attempts of tax evasions. Furthermore, we have implemented a tool to detect them and tested it using data of companies which committed accounting frauds.
Measuring and Evaluating Changes in Returns for Residential Property

Changes in home owners’ wealth is measured by using an index of property prices constructed from sales transactions. Since only a very small proportion of the housing stock is offered to the market in any given time period, the index is a proxy for change in the price of all properties. The accuracy of the index determines its suitability as a ‘good’ proxy in reflecting price changes. Several methods of index construction may be employed to measure price changes. A brief review of these methodologies and their shortcomings is presented. A hedonic regression analysis is employed to construct an index for ten Melbourne suburbs. The results are compared with the standard approach commonly employed by the property profession.
Low Encoding Complexity Video Compression Based on Low-Density Parity Check Codes

Conventional video compression methods generally require a large amount of computation in the encoding process because they perform motion estimations. In order to reduce the encoding complexity for video compression, this paper proposes a new video compression method based on low-density parity check codes. The proposed method is suitable for resource-constrained devices such as mobile phones and satellite cameras.
Towards a Unified Trust Model for M-commerce Systems

M-commerce has become one of the most evolutionary fields not only in the developed countries but also in the developing countries. It facilitates transactional procedures using mobile devices that are being enhanced rapidly to become simpler and more secured. Currently users can make any monetary transaction such as booking tickets or buying goods online anywhere anytime. One of the most challenging concerns in developing m-commerce systems and applications is trustworthiness, because trust is very hard to gain and very easy to lose. Trust is a fuzzy concept as it is defined differently in each discipline even within each, it's perceived in a subjective way. A key step to incorporate trust in m-commerce is to acquire an in-depth understanding of the trustworthiness. This paper presents an attempt to develop a unified trust model for m-commerce. To achieve unification and abstraction, the proposed unified trust model for m-commerce separates changeable and endurable aspects of trustiness. In addition, the proposed model is validated through the demonstration of how existing trust models are embedded within the proposed unified model.
The Relationship between IT Director Values and Extent of IT Disaster Recovery Planning in the Banking Industry

Information technology plays a pivotal role in defining the success of organizations. Given its importance, one might assume that modern organizations take steps to ensure the recovery of IT services following disasters. Unfortunately, this is rarely the case. To understand the variation in degree of IT disaster recovery planning, this research focused on those responsible for managing IT resources and IT directors. For the study, a survey was mailed to 337 financial service institutions in the southeastern United States. Over 150 IT directors completed self-assessments for measuring the extent to which their organization engages in IT disaster recovery planning. In addition, they responded to a number of questions regarding their work-related values, and over 63% of the variance in degree of IT disaster recovery planning was explained by two predictors: uncertainty avoidance and long-term orientation. Results show that firms with IT professionals who prefer to avoid uncertainty and who have long-term outlooks have more developed IT disaster recovery plans. DOI: 10.4018/978-1-4666-0167-3.ch009
Self-reported goal pursuit and purpose in life among people with dementia.

OBJECTIVES Existential aspects of well-being are rarely studied in people with dementia, despite their reported importance. Self-report methods are also rarely used, despite the growing evidence for its use in mild-to-moderate dementia and the lack of concordance between self-reports and proxy reports of well-being. The goal of this study was to examine the relationship between one aspect of well-being, purpose in life, and one of its predictors, goal pursuit, while employing the self-report of individuals with dementia. METHODS Questionnaire and experimental methods were used to gauge the relationship between goal pursuit and purpose in life. The experimental portion was structured around creative drawing activities that are often used in adult day service centers. RESULTS People with mild-to-moderate dementia were able to provide reliable self-report data on their well-being. A strong association between goal pursuit and purpose in life emerged, but dementia severity did not moderate this relationship. DISCUSSION People with dementia who engage in goal-directed activity may experience a greater sense of purpose. Results from this study illuminate the experience of psychological well-being in dementia and may inform activity programming for this population.
Psychological Briefing, Prevention Or Priming? or, How many psychiatrists does it take to change a mind?

This paper is a corollary of the recent Class Action against the MoD 2003 and should be read in conjunction with Palmer 2003. As fear is a prerequisite for the diagnosis of Post Traumatic Stress Disorder (PTSD) it was examined in some detail during this case. This paper serves to amplify those deliberations.
Artificial neural network based stock value prediction

Financial market turmoil is a new normal today and modern computer science is partialy responsible for this. In this paper we try to show that modern fincancial markets are informationally efficent. In order to show this attribute of financial markets we use a neural network and test it against the S & P 500 stock index. We train our neural network using index information from past in order to predict the future value of the index. We compare the results of neural network based index prediction and a simple buy & hold strategy. Based on this comparison we make a decision about validity of the market efficiency hypothesis. Finally we present some possible improvements to our solution of this problem.
Motor Phenotype of Decline in Cognitive Performance among Community-Dwellers without Dementia: Population-Based Study and Meta-Analysis

Background Decline in cognitive performance is associated with gait deterioration. Our objectives were: 1) to determine, from an original study in older community-dwellers without diagnosis of dementia, which gait parameters, among slower gait speed, higher stride time variability (STV) and Timed Up & Go test (TUG) delta time, were most strongly associated with lower performance in two cognitive domains (i.e., episodic memory and executive function); and 2) to quantitatively synthesize, with a systematic review and meta-analysis, the association between gait performance and cognitive decline (i.e., mild cognitive impairment (MCI) and dementia). Methods Based on a cross-sectional design, 934 older community-dwellers without dementia (mean±standard deviation, 70.3±4.9years; 52.1% female) were recruited. A score at 5 on the Short Mini-Mental State Examination defined low episodic memory performance. Low executive performance was defined by clock-drawing test errors. STV and gait speed were measured using GAITRite system. TUG delta time was calculated as the difference between the times needed to perform and to imagine the TUG. Then, a systematic Medline search was conducted in November 2013 using the Medical Subject Heading terms “Delirium,” “Dementia,” “Amnestic,” “Cognitive disorders” combined with “Gait” OR “Gait disorders, Neurologic” and “Variability. ” Findings A total of 294 (31.5%) participants presented decline in cognitive performance. Higher STV, higher TUG delta time, and slower gait speed were associated with decline in episodic memory and executive performances (all P-values <0.001). The highest magnitude of association was found for higher STV (effect size = −0.74 [95% Confidence Interval (CI): −1.05;−0.43], among participants combining of decline in episodic memory and in executive performances). Meta-analysis underscored that higher STV represented a gait biomarker in patients with MCI (effect size = 0.48 [95% CI: 0.30;0.65]) and dementia (effect size = 1.06 [95% CI: 0.40;1.72]). Conclusion Higher STV appears to be a motor phenotype of cognitive decline.
Exploring the identity formation of youth involved in an adapted sports program.

Identity is generally defined as an individual's mental representations of his or her personal and social characteristics. The belief that participation in sport may be linked to identity formation of adolescents with physical disabilities was the subject of this research. To explore this relationship, qualitative interviews were conducted with 11 youth. Analysis of the data revealed 4 themes: (a) skill and competence, (b) emotional expression, (c) social interaction and connectedness with others with a disability, and (d) decreased awareness of disability. Participation in adapted sports appeared to provide the majority of these youth with a heightened sense of competence and opportunities to express their "true" selves. In addition, sport participation by the youth with disabilities in this study led to decreased awareness of their disabilities and facilitated exploration and expression of identity alternatives. This exploratory study provided some evidence that involvement in an adapted sports program was related to identity formation for those involved.
SPAIN: COTS Data-Center Ethernet for Multipathing over Arbitrary Topologies

Operators of data centers want a scalable network fabric that supports high bisection bandwidth and host mobility, but which costs very little to purchase and administer. Ethernet almost solves the problem - it is cheap and supports high link bandwidths - but traditional Ethernet does not scale, because its spanning-tree topology forces traffic onto a single tree. Many researchers have described "scalable Ethernet" designs to solve the scaling problem, by enabling the use of multiple paths through the network. However, most such designs require specific wiring topologies, which can create deployment problems, or changes to the network switches, which could obviate the commodity pricing of these parts. In this paper, we describe SPAIN ("Smart Path Assignment In Networks"). SPAIN provides multipath forwarding using inexpensive, commodity off-the-shelf (COTS) Ethernet switches, over arbitrary topologies. SPAIN pre-computes a set of paths that exploit the redundancy in a given network topology, then merges these paths into a set of trees; each tree is mapped as a separate VLAN onto the physical Ethernet. SPAIN requires only minor end-host software modifications, including a simple algorithm that chooses between pre-installed paths to efficiently spread load over the network. We demonstrate SPAIN's ability to improve bisection bandwidth over both simulated and experimental data-center networks
Catch Me, If You Can: Evading Network Signatures with Web-based Polymorphic Worms

Polymorphic worms are self-replicating malware that change their representation as they spread throughout networks in order to evade worm detection systems. A number of approaches to detect polymorphic worms have been proposed. These approaches use samples of a polymorphic worm (and of benign traffic as well) to derive a signature that can detect all instances of the worm without producing excessive false positives. Even though these systems claim to be able to generate signatures for any type of worm, all the examples that are used to show the ability to detect polymorphic worms are based on exploits that target memory corruption vulnerabilities. In this paper, we show how a different class of worms, namely those based on web vulnerabilities and scripting languages, can be much harder to detect than "traditional" polymorphic worms. We developed a polymorphic engine for PHP code and we tested the ability of state-of-the-art tools to detect this type of worm. The results of our experiments show that a PHP-based polymorphic worm would be able to successfully evade existing signature generation systems.
Integral controller design for nonlinear systems using inverse optimal control

This paper proposes an integral controller design scheme for nonlinear systems based on optimal control and the passivity theorem in order to suppress the effect of external disturbances. The main strategy is to augment an optimal controller with a PI type controller. To guarantee the proposed controller has a desired stability margin, the passivity-based design method is introduced. Here, the inverse optimal control technique is employed to avoid the need of solving a Hamilton-Jacobi equation. An illustrative example is given to show the design procedure and the controller effectiveness.
A Diffusion Model for Energy Harvesting Sensor Nodes

Energy harvesting has recently attracted much interest due to the emergence of the Internet of Things, and the increasing need to operate wireless sensing devices in challenging environments without much human intervention and maintenance. This paper presents a novel approach for modeling the performance of an energy harvesting wireless sensor node, which takes into account fluctuations in the amount of energy extracted from the environment, energy loss due to battery leakage, as well as the energy cost of sensing, data processing and communication. The proposed approach departs from the common queueing-theoretic framework used in the literature, and instead uses Brownian motion to represent more accurately the time evolution of the distribution of the node's battery level. The paper derives some performance measures of interest along with the stationary solution of the system, and discusses possible directions for reducing the number of parameters and states of the model without compromising accuracy.
Buffer Management Strategies to Reduce HoL Blocking

Congestion management is likely to become a critical issue in interconnection networks, as increasing power consumption and cost concerns lead to improvements in the efficiency of network resources. In previous configurations, networks were usually oversized and underutilized. In a smaller network, however, contention is more likely to occur and blocked packets cause head-of-line (HoL) blocking among the rest of the packets, spreading congestion quickly. The best-known solution to HoL blocking is Virtual Output Queues (VOQs). However, the cost of implementing VOQs increases quadratically with the number of output ports in the network, making it unpractical. The situation is aggravated when several priorities and/or Quality of Service (QoS) levels must be supported. Therefore, a more scalable and cost-effective solution is required to reduce or eliminate HoL blocking. In this paper, we present a family of methodologies, referred to as Destination-Based Buffer Management (DBBM), to reduce/eliminate the HoL blocking effect on interconnection networks. DBBM efficiently uses the resources (mainly memory queues) of the network. These methodologies are comprehensively evaluated in terms of throughput, scalability, and fairness. Results show that using the DBBM strategy, with a reduced number of queues at each switch, it is possible to achieve roughly the same throughput as the VOQ mechanism. Moreover, all of the proposed strategies are designed in such a way that they can be used in any switch architecture. We compare DBBM with RECN, a sophisticated mechanism that eliminates HoL blocking in congestion situations. Our mechanism is able to achieve almost the same performance with very low logic requirements (in contrast with RECN).
Finite Time Fault Tolerant Control for Robot Manipulators Using Time Delay Estimation and Continuous Nonsingular Fast Terminal Sliding Mode Control

In this paper, a novel finite time fault tolerant control (FTC) is proposed for uncertain robot manipulators with actuator faults. First, a finite time passive FTC (PFTC) based on a robust nonsingular fast terminal sliding mode control (NFTSMC) is investigated. Be analyzed for addressing the disadvantages of the PFTC, an AFTC are then investigated by combining NFTSMC with a simple fault diagnosis scheme. In this scheme, an online fault estimation algorithm based on time delay estimation (TDE) is proposed to approximate actuator faults. The estimated fault information is used to detect, isolate, and accommodate the effect of the faults in the system. Then, a robust AFTC law is established by combining the obtained fault information and a robust NFTSMC. Finally, a high-order sliding mode (HOSM) control based on super-twisting algorithm is employed to eliminate the chattering. In comparison to the PFTC and other state-of-the-art approaches, the proposed AFTC scheme possess several advantages such as high precision, strong robustness, no singularity, less chattering, and fast finite-time convergence due to the combined NFTSMC and HOSM control, and requires no prior knowledge of the fault due to TDE-based fault estimation. Finally, simulation results are obtained to verify the effectiveness of the proposed strategy.