Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantifying the energy stores of capital breeding humpback whales and income breeding sperm whales using historical whaling records

Cetacean energy stores are known to vary according to life history, reproductive status and time of year; however, the opportunity to quantify these relationships is rare. Using a unique set of historical whaling records from Western Australia (1952–1963), we investigated energy stores of large cetaceans with differing life histories, and quantified the relationship between total body lipid and length for humpback whales (Megaptera novaeangliae) (n = 905) and sperm whales (Physeter macrocephalus) (n = 1961). We found that total body lipid increased with body length in both humpback and sperm whales, consistent with size-related energy stores. Male humpback whales stored 2.49 kl (15.6 barrels) (31.9–74.9%) more lipid than male sperm whales of equivalent length, to fuel their annual migration. Relative lipid stores of sperm whales (males) were constant throughout the year, while those of humpback whales varied with reproductive class and sampling date. Pregnant female humpback whales had higher relative energy stores than non-pregnant females and males (26.2% and 37.4%, respectively), to fuel the energy demands of gestation and lactation. Those that reached the sampling site later (en route to their breeding grounds) carried higher lipid stores than those that arrived earlier, possibly reflecting individual variation in residency times in the Antarctic feeding grounds. Importantly, longer pregnant females had relatively larger energy stores than the shorter pregnant females, indicating that the smaller individuals may experience higher levels of energetic stress during the migration fast. The relationships we developed between body lipid and length can be used to inform bioenergetics and ecosystem models when such detailed information is not available.
Increased freshwater discharge shifts the trophic balance in the coastal zone of the northern Baltic Sea

Increased precipitation is one projected outcome of climate change that may enhance the discharge of freshwater to the coastal zone. The resulting lower salinity, and associated discharge of both nutrients and dissolved organic carbon, may influence food web functioning. The scope of this study was to determine the net outcome of increased freshwater discharge on the balance between auto‐ and heterotrophic processes in the coastal zone. By using long‐term ecological time series data covering 13 years, we show that increased river discharge suppresses phytoplankton biomass production and shifts the carbon flow towards microbial heterotrophy. A 76% increase in freshwater discharge resulted in a 2.2 times higher ratio of bacterio‐ to phytoplankton production (Pb:Pp). The level of Pb:Pp is a function of riverine total organic carbon supply to the coastal zone. This is mainly due to the negative effect of freshwater and total organic carbon discharge on phytoplankton growth, despite a concomitant increase in discharge of nitrogen and phosphorus. With a time lag of 2 years the bacterial production recovered after an initial decline, further synergistically elevating the microbial heterotrophy. Current climate change projections suggesting increased precipitation may therefore lead to increased microbial heterotrophy, thereby decreasing the transfer efficiency of biomass to higher trophic levels. This prognosis would suggest reduced fish production and lower sedimentation rates of phytoplankton, a factor of detriment to benthic fauna. Our findings show that discharge of freshwater and total organic carbon significantly contributes to the balance of coastal processes at large spatial and temporal scales, and that model's would be greatly augmented by the inclusion of these environmental drivers as regulators of coastal productivity.
A soft label based linear discriminant analysis for semi-supervised dimensionality reduction

Dealing with high-dimensional data has always been a major problem with the research of pattern recognition and machine learning. And Linear Discriminant Analysis (LDA) is one of the most popular methods for dimensionality reduction. But it only uses labeled samples while neglect the unlabeled samples, which are abundant and can be easily obtained in the real world. In this paper, we propose a new dimensionality reduction method by using the unlabeled samples to enhance the performance of LDA. The new method first propagates the label information from labeled set to unlabeled set via a label propagation process, where the predicted labels of unlabeled samples, called soft labels, can be obtained. It then incorporates the soft labels into the construction of scatter matrixes to find a transformed matrix for dimensionality reduction. In this way, the proposed method can preserve more discriminative information, which is good when solving the classification problem. Extensive simulations are carried based several datasets and the results show the effectiveness of the proposed method.
Scene flow estimation from stereo video source

There are various methods to estimate the scene flow. Most of the methods use motion estimation with stereo re-construction. This paper describes an interesting way to fuse the video from two camera's and create a 3D reconstruction. The proposed algorithm incorporates probabilistic distributions for optical flow and disparity. Multiple such re-created renderings can be put together to create re-timed movies of the event, with the resulting visual experience richer than that of a regular video clip, or switching between images from multiple cameras, do a head tracking of the viewer and change the view angle accordingly or view it on a mobile device using the accelerometer for camera tilting for the 3D effect.
Why is it so hard to define software architecture?

In recent years, software engineering researchers have elevated the study of software architecture to the level of a major area of study. A review of the published literature however, shows quite clearly that a unified view of software architecture has not been forth-coming. This paper contends that the existence of a "software architecture level of design" is based on the implicit assumption that the software development process is analogous to those "construction" disciplines in which the completed artefacts or systems exhibit a unique representational abstraction, fixed during the early stages of design, which we describe as "the architecture". We argue that our problems in obtaining an acceptable definition of software architecture are due to the assumption that software systems have an analogous, unique design abstraction determinable at the early stages of the design. To determine the validity of this analogy, we contrast the nature and use of architecture in the traditional building process with software development to identify the differences, rather than the similarities that exist. These differences are explained using a theory of the software development process which highlights why these differences arise and, subsequently why there has been trouble in developing a community-wide understanding of software architecture. Our conclusion is that due to the fundamental nature of the systems we construct, attempts to depict the large-scale structure of the system, in an analogous manner traditional building disciplines, results in many different architectures. These are fundamentally different representations and not merely different views of a single whole. Moreover, each of these is equally qualified to be labelled as the system architecture with respect to the general notion of what architecture is.
Does the Hydrated Electron Occupy a Cavity?

Filling a Cavity Unlike liquid ammonia, water cannot sustain a steady concentration of isolated electrons. Nonetheless, high-energy irradiation can introduce a small number of free charges that engage in potent reductive chemistry and have clear spectroscopic signatures. The manner in which water solubilizes these hydrated electrons has remained uncertain, but the general consensus has been that repulsive interactions drive the nearest water molecules away, leaving the electron in a nearly spherical empty cavity. Larsen et al. (p. 65; see the Perspective by Jordan and Johnson) upend this consensus with simulations based on a more thorough potential function for modeling the competing attractions and repulsions between the electron and surrounding water. The calculations suggest that the hydrated electron actually draws water in, occupying a region denser than the pure bulk liquid. The model reproduces experimental spectral and dynamic observations as effectively as, and in some cases better than, the cavity framework. A long-standing model of the solvent geometry surrounding a free charge in water is questioned by new numerical simulations. Since the discovery of the hydrated electron more than 40 years ago, a general consensus has emerged that the hydrated electron occupies a quasispherical cavity in liquid water. We simulated the electronic structure and dynamics of the hydrated electron using a rigorously derived pseudopotential to treat the electron-water interaction, which incorporates attractive oxygen and repulsive hydrogen features that have not been included in previous pseudopotentials. What emerged was a hydrated electron that did not reside in a cavity but instead occupied a ~1-nanometer-diameter region of enhanced water density. Both the calculated ground-state absorption spectrum and the excited-state spectral dynamics after simulated photoexcitation of this noncavity hydrated electron showed excellent agreement with experiment. The relaxation pathway involves a rapid internal conversion followed by slow ground-state cooling, the opposite of the mechanism implicated by simulations in which the hydrated electron occupies a cavity.
HER2 status in non-small cell lung cancer: results from patient screening for enrollment to a phase II study of herceptin.

PURPOSE For the first time a large number (563) of non-small cell lung cancer (NSCLC) samples was used to compare three different technologies for the assessment of HER2 status. Fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC) were used for tumor tissue samples, and ELISA for serum samples. The results were compared with other tumor entities, mainly breast. EXPERIMENTAL DESIGN Samples (563) from patients suffering from primary advanced or metastatic NSCLC were evaluated. RESULTS HER2 overexpression was demonstrated using IHC in 20% (83 of 410) of the specimens, whereas 2% (7 of 378) were positive by FISH and 6% (31 of 511) showed elevated serum HER2 levels (>15 ng/ml) by ELISA. Sixty-six specimens were positive by IHC only and 13 by ELISA only, whereas none of the specimens was positive only by FISH. Concordance between all of the techniques was seen for only 3 specimens. Of 7 IHC 3+ specimens, 4 showed gene amplification by FISH, and 3 were positive by ELISA (>15 ng/ml), whereas of 76 IHC 2+ cases only 2 were amplified by FISH, and 4 were positive by ELISA. HER2 positivity by at least one of the three techniques was most common in adenocarcinomas, at 29% (42 of 143). CONCLUSION Gene amplification and HER2 protein overexpression at the 3+ level appear to be uncommon in NSCLC. The concordance between FISH and IHC 3+ disease was good in this study, in addition, ELISA would have detected several patients without IHC/FISH-positive disease.
On the use of divergent force fields in robot-mediated neurorehabilitation

The present study is aimed at developing new rehabilitation protocols to be used in post-stroke robotic-aided therapy. In the recent past, it has been suggested that the use of robotic training forces that enhance error instead of reducing it, could stimulate new learning and feedback strategies at the base of an effective motor recovery. Starting from these findings, in this work two different robotic-aided therapies were compared: the first was based on the constraint induced movement therapy, the second employed an unstable training force field increasing path errors performed by the subjects. The results shows that the use of the unstable divergent force field can increase the recovery, especially in people with mild level of impairment.
Establishing Trust in a Business-to-Business Collaboration: Results from an International Simulation

Businesses in the 21 st century have extended to a process oriented, e-business world that is increasing in business-to-business, web-centric interactions. The geographical dispersion of participants in this new process oriented e-business world introduces challenges of building a degree of trust needed for effective collaboration. Yet, examining the correlation of various trust manifestations to the success of business-to-business collaboration remains a challenge. This paper examines trust as a factor in successful business-to-business process implementations. Based on an international collaboration between two universities that address issues of new e-centric business practices, results in the form of students’ perceptions of trust manifestations are presented.
Break the "Right" Cycles and Get the "Best" Drawing

We consider the two-layer crossing minimization problem (CP): given a two-layered graph and a permutation of the vertices on a layer, nd a permutation of the vertices on the other layer so that the number of edge crossings is minimum. Solving CP represents a fundamental step in the construction of aesthetically pleasing layouts of hierarchies and directed graphs. As CP has been proved to be NP-complete, several heuristics for it have been designed, but unfortunately, according to previous experimental results, even algorithms with good theoretical performances appear not to be good in practice. The contribution of this paper is twofold. First, we present new theoretical results that allow us to design a polynomial-time approximation algorithm for CP (in short, PM) based on the computation of feedback arc sets. Furthermore, we perform an experimental analysis of algorithm PM both on randomly generated bipartite graphs and on pathological instances for CP. In particular, we compare its performances, with respect to the number of edge crossings and to the running time, to the performances of three classical algorithms for CP: the barycenter heuristic, an enhanced version of the median algorithm, and a recent attractive greedy strategy. Our experimental results show that algorithm PM stands out as a practical and eeective method for minimizing crossings in bipartite drawings.
FOCS: Fast Overlapped Community Search

Discovery of natural groups of similarly functioning individuals is a key task in analysis of real world networks. Also, overlap between community pairs is commonplace in large social and biological graphs, in particular. In fact, overlaps between communities are known to be denser than the non-overlapped regions of the communities. However, most of the existing algorithms that detect overlapping communities assume that the communities are denser than their surrounding regions, and falsely identify overlaps as communities. Further, many of these algorithms are computationally demanding and thus, do not scale reasonably with varying network sizes. In this article, we propose Fast Overlapped Community Search (FOCS), an algorithm that accounts for local connectedness in order to identify overlapped communities. FOCS is shown to be linear in number of edges and nodes. It additionally gains in speed via simultaneous selection of multiple near-best communities rather than merely the best, at each iteration. FOCS outperforms some popular overlapped community finding algorithms in terms of computational time while not compromising with quality.
CSense: A stream-processing toolkit for robust and high-rate mobile sensing applications

This paper presents CSense - a stream-processing toolkit for developing robust and high-rate mobile sensing application in Java. CSense addresses the needs of these systems by providing a new programming model that supports flexible application configuration, a high-level concurrency model, memory management, and compiler analyses and optimizations. Our compiler includes a novel flow analysis that optimizes the exchange of data across components from an application-wide perspective. A mobile sensing application benchmark indicates that flow analysis may reduce CPU utilization by as much as 45%. Static analysis is used to detect a range of programming errors including application composition errors, improper use of memory management, and data races. We identify that memory management and concurrency limit the scalability of stream processing systems. We incorporate memory pools, frame conversion optimizations, and custom synchronization primitives to develop a scalable run-time. CSense is evaluated on Galaxy Nexus phones running Android. Empirical results indicate that our run-time achieves 19 times higher steam processing rate compared to a realistic baseline implementation. We demonstrate the versatility of CSense by developing three mobile sensing applications.
A Sink-Controlled Energy-Efficient and Geographical Routing Protocol in Wireless Sensor Networks

One of the main problems facing routing protocol in wireless sensor networks is how to prolong the lifetime of the network, because the replacement of the embedded batteries is a very difficult process once these nodes have been deployed. In this paper, we propose a new centralized energy-efficient routing protocol called Sink-controlled Energy-efficient and Geographical Routing (SEGR), which concentrates the energy dissipation on sink node to alleviate the normal nodes' energy load. At sink node, we adapt Dijkstra algorithm to calculate the minimal energy consuming paths. The performance of SEGR is then compared to other similar routing protocols by software. Simulation results show that SEGR reduces overall energy consumption and improves network lifetime over its comparatives.
Energy Efficiency in TDMA-Based Next-Generation Passive Optical Access Networks

Next-generation passive optical network (PON) has been considered in the past few years as a cost-effective broadband access technology. With the ever-increasing power saving concern, energy efficiency has been an important issue in its operations. In this paper, we propose a novel sleep-time sizing and scheduling framework for the implementation of green bandwidth allocation (GBA) in TDMA-PONs. The proposed framework leverages the batch-mode transmission feature of GBA to minimize the overhead due to frequent ONU on-off transitions. The optimal sleeping time sequence of each ONU is determined in every cycle without violating the maximum delay requirement. With multiple ONUs possibly accessing the shared media simultaneously, a collision may occur. To address this problem, we propose a new sleep-time sizing mechanism, namely Sort-And-Shift (SAS), in which the ONUs are sorted according to their expected transmission start times, and their sleep times are shifted to resolve any possible collision while ensuring maximum energy saving. Results show the effectiveness of the proposed framework and highlight the merits of our solutions .
Analysis of reassigned spectrograms for musical transcription

The reassignment method for the short-time Fourier transform is proposed as a technique for improving the time and frequency estimates of musical audio data. Based on this representation, four classes of expected objects (sinusoid, unresolved sinusoid, transient and noise) are proposed and explained. Pattern classification methods are then used to extract objects conforming to these classes from individual frames of the reassigned spectrogram, with each frame being examined independently. Results for several simple real-world examples are presented, showing the capability of this method even without the aid of tracking from frame to frame. The main benefits of the proposed reassignment stage are that it yields an improved time-frequency localisation estimate relative to standard methods, and that it produces a measure of the variance of these estimates to be used as an aid in later processing.
Near-Optimal Method for Siting and Sizing of Distributed Storage in a Transmission Network

Energy storage can alleviate the problems that the uncertainty and variability associated with renewable energy sources such as wind and solar create in power systems. Besides applications such as frequency control, temporal arbitrage or the provision of reserve, where the location of storage is not particularly relevant, distributed storage could also be used to alleviate congestion in the transmission network. In such cases, the siting and sizing of this distributed storage is of crucial importance to its cost-effectiveness. This paper describes a three-stage planning procedure to identify the optimal locations and parameters of distributed storage units. In the first stage, the optimal storage locations and parameters are determined for each day of the year individually. In the second stage, a number of storage units is available at the locations that were identified as being optimal in the first stage, and their optimal energy and power ratings are determined. Finally, in the third stage, with both the locations and ratings fixed, the optimal operation of the storage units is simulated to quantify the benefits that they would provide by reducing congestion. The quality of the final solution is assessed by comparing it with the solution obtained at the first stage without constraints on storage sites or size. The approach is numerically tested on the IEEE RTS 96.
Region based elimination of noise pixels towards optimized classifier models for skin pixel detection

The extraction of the skin pixels in a human image and rejection of non-skin pixels is called the skin segmentation. Skin pixel detection is the process of extracting the skin pixels in a human image which is typically used as a pre-processing step to extract the face regions from human image. In past, there are several computer vision approaches and techniques have been developed for skin pixel detection. In the process of skin detection, given pixels are been transformed into an appropriate color space such as RGB, HSV etc. And then skin classifier model have been applied to label the pixel into skin or non-skin regions. Here in this research a “Region based elimination of noise pixels and performance analysis of classifier models for skin pixel detection applied on human images” would be performed which involve the process of image representation in color models, elimination of non-skin pixels in the image, and then pre-processing and cleansing of the collected data, feature selection of the human image and then building the model for classifier. In this research and implementation of skin pixels classifier models are proposed with their comparative performance analysis. The definition of the feature vector is simply the selection of skin pixels from the human image or stack of human images. The performance is evaluated by comparing and analysing skin colour segmentation algorithms. During the course of research implementation, efforts are iterative which help in selection of optimized skin classifier based on the machine learning algorithms and their performance analysis.