Miracle-dz/UniFAR-FTUs huggingface dataset:
Restoration of Natural Herbaceous Vegetation of Xiangxi River’s Water-Level Fluctuation Zone after the Flooding in Three Gorges Reservoir Area

Water-level fluctuation zone (WLFZ) is the security barrier of reservoir. Herbaceous vegetation’s restoration characteristic of Xiangxi River’s WLFZ in Three Gorges reservoir area was investigated by using ecological methods. The results show that: The main plant types are annual herbs and perennial herbs, and plant communities are patchiness or zonal distribution. Two absolute dominant plant communities are build by Cynodondactylon(Linn.)Pers. and Rhizoma Cyperi (Nutgrass Galingale Rhizome) in the 145-155m area, and annual herbs are mainly distributed above the 155m area. As the elevation increasing, the β diversity increases. There are 22 dominant species of herbaceous in Xiangxi River’s WLFZ, 16 plants could complete life story, and 5 plants’ life story are threatened by impounding. Polygonum lapathifolium Linn.may not complete its life story.
A conceptual framework highlighting e-learning implementation barriers

E-learning has gained much focus from educators and researchers, with many extolling e-learning over traditional learning. Despite this focus, implementation of e-learning systems often fails. The purpose of this paper is to consider a range of barriers, impacting the success of e-learning implementations, yet to the best of the authors’ knowledge no conceptual framework is able to consolidate existing research. ,This paper undertook an in-depth review of literature concerning e-learning implementation barriers. Papers were extracted from established peer-reviewed journals and open sources. Articles not related to e-learning implementation barriers were discarded. A total of 259 papers were identified, published between 1990 and 2016. Hermeneutics and data-driven qualitative content analysis was used to define 68 unique barriers. ,The 68 unique barriers were thematically grouped into four conceptual categories, i.e. Technology (T), Individual (I), Pedagogy (P), and Enabling Conditions (EC). These four categories led to the conceptualization of “TIPEC” framework, which highlights the key concepts hindering e-learning implementation and delivery. Results show that most articles only consider a narrow range of success barriers. ,The proposed TIPEC framework acts as a guide for education practitioners, system developers, policy makers, and researchers. It provides stakeholders with a summary of e-learning barriers. ,This paper fulfils an identified need for a conceptual framework that consolidates all current research related to e-learning implementation barriers.
Formal Analysis of Workflow Systems with Security Considerations

Security considerations, such as role-based access control (RBAC) mechanism and separation of duty (SoD) constraints, are important and integral to workflow systems. We propose the use of an equation-based method – the OTS/CafeOBJ method to specify workflow systems with such security considerations, and verify some desired safety and liveness properties of workflow systems. Specifically, a workflow system, together with its security considerations, is modeled as an OTS, a kind of transition system. Then the OTS is written in CafeOBJ, an algebraic specification language. We express safety and liveness properties in CafeOBJ and verify that the OTS satisfies these properties by writing proof scores in CafeOBJ. We use a case study – formal analysis of a workflow system that deals with travel expense reimbursement, to demonstrate our method of modeling, specifying and verifying.
An overview of hand-based multimodal biometrie system using multi-classifier score fusion with score normalization

In the emerging trends of biometrie authentication, multimodal biometries getting more attention from researchers due to its universality, uniqueness, no intra-class variations, no inter-class similarities, and anti-spoofing attacks than unimodal biometrics. Hand-based multibiometric system is the most successful and used in many real time systems especially law enforcement and forensics. Moreover, it is very user friendly and ease of use among all other biometric traits. Multi classifier fusion is the use of more classifiers for each modality involved rather than single at the score fusion of multibiometric system. Furthermore, hand-based multimodal biometrics can use either or all traits of fingerprint, palm print, finger vein, palm vein, dorsal vein, hand geometry, finger knuckle print and many more. In this paper, we reviewed various score normalization techniques and multi-classifiers used in the hand-based multimodal biometrics for each modality involved at the matching score fusion for enhancing the system performance further.
Image mosaic based on SIFT and morphological component analysis

Due to traditional image mosaicing resulting in remarkable seams, we propose a novel method to address the problem to make the result more smooth. The approach is constructed based on SIFT algorithm and morphological component analysis(MCA) over trained dictionaries. The two cores of image mosaic are image registration and fusion. First, feature points are extracted by the SIFT algorithm which are used to realize image registration. Then we employ K-SVD algorithm to train an overcomplete dictionary based on the original images and use the MCA to decompose the images so that the decomposed components cartoon, texture can be used to fuse images, respectively. This method leads to a state-of-the-art mosaic performance, meanwhile, the noise contained by original images can also be filtered.
Boundary Spanners in Open Source Software Development: A Study of Python Email Archives

In many open source software development communities, a significant proportion of development is undertaken by a relatively small number of individuals, the "core members". The stability and longevity of this group of most active developers are crucial for the success of the project. While there has been prior work on identifying key individuals in open source development, little attention has been devoted to the identification of cross-cutting core individuals (boundary spanners) whose responsibilities span across different functional areas of open source development (e.g., who are involved both in development-centric activities and user-centric activities). To address this gap, we propose an approach to identify the core cross-cutting members and their roles within the community through analyzing email communication repositories. We use Social Network Analysis (SNA) tools to identify the most active core members in different forums (that have different focus such as Python-dev that focuses on language evolution and Python Lists that focus on user support), and their activities over time, thus identifying the core developers and their involvement in different community mailing lists. Based on the involvement of a core developer and the overall social structure of the network of core developers, we also present an approach for identifying a potential replacement for a community administrator that steps down. Using email repositories of six main Python forums as the case study domain, we computed several social network analysis metrics to characterize the core developers and their importance in the Python community.
Scalable and Distributed Detection Analysis on Wormhole Links in Wireless Sensor Networks for Networked Systems

Recent surge in cyber physical systems (CPSs) which integrate cyber and physical worlds, increases security risks at both the surfaces. The wireless sensor communication network is one of the major components of the critical infrastructure in all networked systems including networked control systems and CPSs. As these systems support range of time and data sensitive applications, varying from health care to emergency services, to transport, and to environmental monitoring services, core sensor network component faces potential threats due to varying attacks, including wormhole attack that can cause damage to the control system in terms of data leakage, data dropping, and delayed delivery. It is also difficult to detect, as it requires neither nodes in the network to be compromised nor adversaries to acquire valid network identity to instigate such attacks. Many existing solutions in the literature to detect wormholes are based on node’s static location information, synchronization of clocks, use of additional hardware, such as antennas and GPS, and neighborhood and traffic information, which may lead to large energy consumption. In this paper, a scalable and distributed scheme which uses sequential probability ratio test is proposed, to avoid single point failures and to handle high mobility, with no additional resource requirements. It is observed that wormholes are detected using few packets and detection is faster with increasing mobility. The system is highly customizable as system parameters can be chosen to balance the speed and accuracy of detection. System overheads in terms of communication, computation, and storage aspects are analyzed and presented.
Modified harmonic injection technique for electrolytic capacitor-less LED driver

Conventional LED drive has a limited lifetime due to present of bulky electrolytic output capacitor (E-Cap) which is essential to make the power difference balancing between the constant output power and the pulsating input power. In fact, LED chip has a longer lifetime than E-Cap. Therefore, it is insufficient to use this type of capacitors in LED driver. Increasing the LED lamp lifetime can be achieved through changing the E-Cap with Film or Ceramic one. But the LED current peak will be double as a result of using low energy density capacitors. However, the LED can be driven by a pulsating current with a defined peak value. Peak to average ratio (PTAR) of LED current has to be limited (less than 1.4) to save LED from overdriven, failure and flux saturation. Recently, the methodology of injecting a predefined value of harmonics to limit the PTAR is costly and complex to be used in interior and exterior LED applications. This paper will present an optimization methodology for the LED driver control circuitry to be simpler and more cost-effective. Three major parameters will constrain the design of the control circuitry are cost reduction, lifetime expansion and simplicity in implementation. The feasibility of the proposed control circuit has been verified by simulation and real prototyping as well.
Pathogenic Leptospires Modulate Protein Expression and Post-translational Modifications in Response to Mammalian Host Signals

Pathogenic species of Leptospira cause leptospirosis, a bacterial zoonotic disease with a global distribution affecting over one million people annually. Reservoir hosts of leptospirosis, including rodents, dogs, and cattle, exhibit little to no signs of disease but shed large numbers of organisms in their urine. Transmission occurs when mucosal surfaces or abraded skin come into contact with infected urine or urine-contaminated water or soil. Whilst little is known about how Leptospira adapt to and persist within a reservoir host, in vitro studies suggest that leptospires alter their transcriptomic and proteomic profiles in response to environmental signals encountered during mammalian infection. We applied the dialysis membrane chamber (DMC) peritoneal implant model to compare the whole cell proteome of in vivo derived leptospires with that of leptospires cultivated in vitro at 30°C and 37°C by 2-dimensional difference in-gel electrophoresis (2-D DIGE). Of 1,735 protein spots aligned across 9 2-D DIGE gels, 202 protein spots were differentially expressed (p < 0.05, fold change >1.25 or < −1.25) across all three conditions. Differentially expressed proteins were excised for identification by mass spectrometry. Data are available via ProteomeXchange with identifier PXD006995. The greatest differences were detected when DMC-cultivated leptospires were compared with IV30- or IV37-cultivated leptospires, including the increased expression of multiple isoforms of Loa22, a known virulence factor. Unexpectedly, 20 protein isoforms of LipL32 and 7 isoforms of LipL41 were uniformly identified by DIGE as differentially expressed, suggesting that unique post-translational modifications (PTMs) are operative in response to mammalian host conditions. To test this hypothesis, a rat model of persistent renal colonization was used to isolate leptospires directly from the urine of experimentally infected rats. Comparison of urinary derived leptospires to IV30 leptospires by 2-D immunoblotting confirmed that modification of proteins with trimethyllysine and acetyllysine occurs to a different degree in response to mammalian host signals encountered during persistent renal colonization. These results provide novel insights into differential protein and PTMs present in response to mammalian host signals which can be used to further define the unique equilibrium that exists between pathogenic leptospires and their reservoir host of infection.
Iterative Design of an Upper Limb Rehabilitation Game with Tangible Robots*

Rehabilitation aims to ameliorate deficits in motor control via intensive practice with the affected limb. Current strategies, such as one-on-one therapy done in rehabilitation centers, have limitations such as treatment frequency and intensity, cost and requirement of mobility. Thus, a promising strategy is home-based therapy that includes task specific exercises. However, traditional rehabilitation tasks may frustrate the patient due to their repetitive nature and may result in lack of motivation and poor rehabilitation. In this article, we propose the design and verification of an effective upper extremity rehabilitation game with a tangible robotic platform named Cellulo as a novel solution to these issues. We first describe the process of determining the design rationales to tune speed, accuracy and challenge. Then we detail our iterative participatory design process and test sessions conducted with the help of stroke, brachial plexus and cerebral palsy patients (18 in total) and 7 therapists in 4 different therapy centers. We present the initial quantitative results, which support several aspects of our design rationales and conclude with our future study plans.
A novel privacy protection scheme for participatory sensing with incentives

With the increasing popularity of smart phones, a new collaborative sensing application, named participatory sensing, gradually appeared. The key idea of participatory sensing is to employ so many users to collect and share sensed data using their mobile phones. Current relevant applications are mainly focused on how to collect sensed data. Few methods have been proposed for user privacy in participatory sensing applications. We proposed a novel privacy protection scheme for participatory sensing applications. In this scheme, we use the pseudonym, encryption function and hash function to protect the user's privacy and meanwhile to carry out incentives. Finally, we present an analysis of our protocol to show that our protocol meets the security requirements of participatory sensing application.
New maximum power point tracking technique of a grid-connected PV system with subtractive clustering

With great increasing concerns about fossil fuel shortage, global warming, and damage to the environmental system, the encouraging to increase in the alternative energy resources which have low operation cost and low pollutant emissions have a great concern. The photovoltaic (PV) system is one of the renewable energy resources widely spread in the energy market in the globe as well as Egypt. Several natural conditions affect the output power of the PV system such as solar irradiance and ambient temperature. Maximum Power Point Tracking (MPPT) techniques for controlling DC-DC boost converter tend to reach for the maximum output power. Various MPPT based techniques have been designated in the literature. In this paper, the Adaptive Neuro-Fuzzy Inference System technique based on Subtractive Clustering method is proposed and compared with other previously used techniques. A grid-connected PV system of 100kW is considered and investigated. From results, the system response with the proposed technique for MPPT is faster, robust, and more stable than other techniques. In addition, there are no any overshoots in the DC link voltage and the value of AC output power is increased the obtained results are promising.
Design Methodology for Six-Port Equal/Unequal Quadrature and Rat-Race Couplers With Balanced and Unbalanced Ports Terminated by Arbitrary Resistances

For the first time, the 6-port quadrature and rat-race couplers with balanced–unbalanced-hybrid ports are proposed. The corresponding design methodology is presented, which is capable of designing the proposed couplers with arbitrary power divisions and terminated resistances. In this paper, four types including quadrature and rat-race couplers are fully analyzed, covering all the application configurations of the balanced/unbalanced ports. Besides, the design equations are rigorously derived, with the final design procedures presented. Eventually, prototypes of the four coupler types are fabricated and experimentally measured. The final results sufficiently validate the proposed methodology.
Computational Account of Spontaneous Activity as a Signature of Predictive Coding

Spontaneous activity is commonly observed in a variety of cortical states. Experimental evidence suggested that neural assemblies undergo slow oscillations with Up ad Down states even when the network is isolated from the rest of the brain. Here we show that these spontaneous events can be generated by the recurrent connections within the network and understood as signatures of neural circuits that are correcting their internal representation. A noiseless spiking neural network can represent its input signals most accurately when excitatory and inhibitory currents are as strong and as tightly balanced as possible. However, in the presence of realistic neural noise and synaptic delays, this may result in prohibitively large spike counts. An optimal working regime can be found by considering terms that control firing rates in the objective function from which the network is derived and then minimizing simultaneously the coding error and the cost of neural activity. In biological terms, this is equivalent to tuning neural thresholds and after-spike hyperpolarization. In suboptimal working regimes, we observe spontaneous activity even in the absence of feed-forward inputs. In an all-to-all randomly connected network, the entire population is involved in Up states. In spatially organized networks with local connectivity, Up states spread through local connections between neurons of similar selectivity and take the form of a traveling wave. Up states are observed for a wide range of parameters and have similar statistical properties in both active and quiescent state. In the optimal working regime, Up states are vanishing, leaving place to asynchronous activity, suggesting that this working regime is a signature of maximally efficient coding. Although they result in a massive increase in the firing activity, the read-out of spontaneous Up states is in fact orthogonal to the stimulus representation, therefore interfering minimally with the network function.
Neural and behavioral mechanisms of proactive and reactive inhibition

Response inhibition is an important component of adaptive behavior. Substantial prior research has focused on reactive inhibition, which refers to the cessation of a motor response that is already in progress. More recently, a growing number of studies have begun to examine mechanisms underlying proactive inhibition, whereby preparatory processes result in a response being withheld before it is initiated. It has become apparent that proactive inhibition is an essential component of the overall ability to regulate behavior and has implications for the success of reactive inhibition. Moreover, successful inhibition relies on learning the meaning of specific environmental cues that signal when a behavioral response should be withheld. Proactive inhibitory control is mediated by stopping goals, which reflect the desired outcome of inhibition and include information about how and when inhibition should be implemented. However, little is known about the circuits and cellular processes that encode and represent features in the environment that indicate the necessity for proactive inhibition or how these representations are implemented in response inhibition. In this article, we will review the brain circuits and systems involved in implementing inhibitory control through both reactive and proactive mechanisms. We also comment on possible cellular mechanisms that may contribute to inhibitory control processes, noting that substantial further research is necessary in this regard. Furthermore, we will outline a number of ways in which the temporal dynamics underlying the generation of the proactive inhibitory signal may be particularly important for parsing out the neurobiological correlates that contribute to the learning processes underlying various aspects of inhibitory control.
Prospective study of dietary protein intake and risk of hip fracture in postmenopausal women.

BACKGROUND The role of dietary protein intake in osteoporosis remains controversial. Protein is an important structural component of bone and protein supplementation improves the medical outcome of hip fracture patients, but it is unknown whether protein intake can reduce the incidence risk of hip fracture. OBJECTIVE The relation between intake of protein and other nutrients and subsequent incidence of hip fracture was evaluated. DESIGN Nutrient intake was assessed with a food-frequency questionnaire in a cohort of Iowa women aged 55-69 y at baseline in 1986. Incident hip fractures were ascertained through follow-up questionnaires mailed to participants in 1987 and 1989 and verified by physician reports. RESULTS Forty-four cases of incident hip fractures were included in the analyses of 104338 person-years (the number of subjects studied times the number of years of follow-up) of follow-up data. The risk of hip fracture was not related to intake of calcium or vitamin D, but was negatively associated with total protein intake. Animal rather than vegetable sources of protein appeared to account for this association. In a multivariate model with inclusion of age, body size, parity, smoking, alcohol intake, estrogen use, and physical activity, the relative risks of hip fracture decreased across increasing quartiles of intake of animal protein as follows: 1.00 (reference), 0.59 (95% CI: 0.26, 1.34), 0.63 (0.28, 1.42), and 0.31 (0.10, 0.93); P for trend = 0.037. CONCLUSION Intake of dietary protein, especially from animal sources, may be associated with a reduced incidence of hip fractures in postmenopausal women.