Miracle-dz/UniFAR-FTUs huggingface dataset:
Locality Preserving Projection for Domain Adaptation with Multi-Objective Learning

In many practical cases, we need to generalize a model trained in a source domain to a new target domain.However, the distribution of these two domains may differ very significantly, especially sometimes some crucial target features may not have support in the source domain.This paper proposes a novel locality preserving projection method for domain adaptation task,which can find a linear mapping preserving the 'intrinsic structure' for both source and target domains.We first construct two graphs encoding the neighborhood information for source and target domains separately.We then find linear projection coefficients which have the property of locality preserving for each graph.Instead of combing the two objective terms under compatibility assumption and requiring the user to decide the importance of each objective function,we propose a multi-objective formulation for this problem and solve it simultaneously using Pareto optimization.The Pareto frontier captures all possible good linear projection coefficients that are preferred by one or more objectives.The effectiveness of our approach is justified by both theoretical analysis and empirical results on real world data sets.The new feature representation shows better prediction accuracy as our experiments demonstrate.
Robotics-Based Location Sensing Using Wireless Ethernet

Abstract A key subproblem in the construction of location-aware systems is the determination of the position of a mobile device. This article describes the design, implementation and analysis of a system for determining position inside a building from measured RF signal strengths of packets on an IEEE 802.11b wireless Ethernet network. Previous approaches to location-awareness with RF signals have been severely hampered by non-Gaussian signals, noise, and complex correlations due to multi-path effects, interference and absorption. The design of our system begins with the observation that determining position from complex, noisy and non-Gaussian signals is a well-studied problem in the field of robotics. Using only off-the-shelf hardware, we achieve robust position estimation to within a meter in our experimental context and after adequate training of our system. We can also coarsely determine our orientation and can track our position as we move. Our results show that we can localize a stationary device to within 1.5 meters over 80% of the time and track a moving device to within 1 meter over 50% of the time. Both localization and tracking run in real-time. By applying recent advances in probabilistic inference of position and sensor fusion from noisy signals, we show that the RF emissions from base stations as measured by off-the-shelf wireless Ethernet cards are sufficiently rich in information to permit a mobile device to reliably track its location.
A Moment‐Based Quasilinear Theory for Electron Firehose Instability Driven by Solar Wind Core/Halo Electrons

In dilute space plasmas, especially in the solar wind, the microinstabilities are regarded as a major candidate to regulate the unchecked rise in temperature anisotropy near Earth orbit. The present paper considers parallel electron firehose mode, which is driven unstable under the condition of excessive electron temperature along the ambient magnetic field, that is, T∥e>T⊥e. The present study assumes bi‐Maxwellian model of solar wind species comprising ions, core, and halo electron components and, in addition, allowing their temperatures to evolve in time t. Employing the macroscopic quasilinear method, a set of equations has been constructed whose solutions give a dynamical picture of the modification in initial particles distributions and wave energy density associated with unstable electron firehose mode. The present scheme, further, confirms the marginal stability curves corresponding to ions, core, and halo electrons, separately. As we dynamically couple solar wind electrons with ions to determine the dynamics of instability, it may amount a further step toward global kinetic solar wind modeling.
Developmental stage-dependent transcriptional regulatory pathways control neuroblast lineage progression

Neuroblasts generate neurons with different functions by asymmetric cell division, cell cycle exit and differentiation. The underlying transcriptional regulatory pathways remain elusive. Here, we performed genetic screens in C. elegans and identified three evolutionarily conserved transcription factors (TFs) essential for Q neuroblast lineage progression. Through live cell imaging and genetic analysis, we showed that the storkhead TF HAM-1 regulates spindle positioning and myosin polarization during asymmetric cell division and that the PAR-1-like kinase PIG-1 is a transcriptional regulatory target of HAM-1. The TEAD TF EGL-44, in a physical association with the zinc-finger TF EGL-46, instructs cell cycle exit after the terminal division. Finally, the Sox domain TF EGL-13 is necessary and sufficient to establish the correct neuronal fate. Genetic analysis further demonstrated that HAM-1, EGL-44/EGL-46 and EGL-13 form three transcriptional regulatory pathways. We have thus identified TFs that function at distinct developmental stages to ensure appropriate neuroblast lineage progression and suggest that their vertebrate homologs might similarly regulate neural development.
Low-Rank Matrix Completion for Topological Interference Management by Riemannian Pursuit

In this paper, we present a flexible low-rank matrix completion (LRMC) approach for topological interference management (TIM) in the partially connected $K$-user interference channel. No channel state information (CSI) is required at the transmitters except the network topology information. The previous attempt on the TIM problem is mainly based on its equivalence to the index coding problem, but so far only a few index coding problems have been solved. In contrast, in this paper, we present an algorithmic approach to investigate the achievable degrees-of-freedom (DoFs) by recasting the TIM problem as an LRMC problem. Unfortunately, the resulting LRMC problem is known to be NP-hard, and the main contribution of this paper is to propose a Riemannian pursuit (RP) framework to detect the rank of the matrix to be recovered by iteratively increasing the rank. This algorithm solves a sequence of fixed-rank matrix completion problems. To address the convergence issues in the existing fixed-rank optimization methods, the quotient manifold geometry of the search space of fixed-rank matrices is exploited via Riemannian optimization. By further exploiting the structure of the low-rank matrix varieties, i.e., the closure of the set of fixed-rank matrices, we develop an efficient rank increasing strategy to find good initial points in the procedure of rank pursuit. Simulation results demonstrate that the proposed RP algorithm achieves a faster convergence rate and higher achievable DoFs for the TIM problem compared with the state-of-the-art methods.
The frequency offset algorithm of the multi-user access for OFDM systems

Multi-user access for the OFDM system is more sensitive to frequency offset than the broadcast access of OFDM. In this paper, the frequency synchronization algorithm according to the maximum-likelihood rule is discussed particularly which is based on the preambles of each frame specified by Hpi specification. Some theoretical analysis illustrates the algorithms is unbiased. The simulation results and emulation results based on DSP show that the proposed algorithm can estimate the frequency offset accurately.
Chinese named entity recognition using modified conditional random field on postal address

Named entity recognition(NER) has been studied for a long time as more and more researches about the embedding, neural network model and some others systems like Language Model have developed quickly. However, as these systems rely heavily on domain-specific knowledge and it can hardly acquires much data about Chinese postal addresses, Chinese Named entity recognition(CNER) task on postal address has developed slowly. In this paper, we use a modified Conditional Random Field(CRF) model to solve a CNER task on a postal address corpus. Since there has little data about Chinese postal addresses and parts of which are incomplete sentences, we utilize the known, useful, clearer semantics words and sentences to our model as the additional features. We make three experiments to evaluate our system which obtains good performance and it shows that our modified algorithm performs better than other traditional algorithms when processing postal addresses.
Sorption Capacity Measurement of Chlorella Vulgaris and Scenedesmus Acutus to Remove Chromium from Tannery Waste Water

Tanning process is a polluting activity due to the release of toxic agents into the environment. One of the most important of those toxic chemicals is chromium. Different alternatives have been proposed for the removal of this metal from tanning waste water which include the optimization of the productive processes, physicochemical and biochemical waste water treatment. In this study, the biological adsorption process of trivalent chromium was carried out in synthetic water and tannery waste water through two types of native green microalgae, called Chlorella vulgaris and Scenedesmus acutus in Free State and immobilized in PVA state. This, considering that cellular wall of microalgae has functional groups like amines and carboxyl that might bind with trivalent chromium. Statistical significance of variables as pH temperature, chromium and algae concentrations was evaluated just like bio sorption capacity of different types of water and kind of bioadsorbent was calculated to determine if this process is a competitive solution comparing to other heavy metal removal processes.
Effect of an oil heat treatment on the teachability and biological resistance of boric acid impregnated wood

Vegetable oils provide boron retention of about 30% of initial amount depending on oil drying properties. Linseed oil is the most efficient, followed by soybean oil and rapeseed oil. Durability of C. japonica and F. crenata wood specimens has been enhanced by application of linseed oil alone but not enough to reduce termite’s attack of Coptotermes formosanus. Treating wood with a 1.0% w/w boric acid solution prior to oil treatment protects C. japonica from termite and fungi degradations. Efficiency against termites is mainly due to boron retention by oil but hydrophobic oil also forms a barrier decreasing fungi penetration. Boron efficacy threshold around 0.7 kg/m3BAE, lower than classical boron treatments thresholds indicates that oil water-repellence reinforces boron biostatic effect. RésuméLa recherche en préservation du bois se tourne à présent vers des produits à faibles impacts environnementaux. Nous avons étudié l’opportunité d’associer borates et huiles végétales pour accroître la rétention du bore ainsi que la résistance du bois aux termites et aux champignons xylophages. Les huiles végétales permettent de retenir environ 30 % du bore initial selon leurs propriétés de séchage. Ainsi, l’huile de lin est plus efficace que les huiles de soja et de colza. La durabilité d’éprouvettes d’aubier de C. japonica et F. crenata est améliorée par l’ajout d’huile de lin mais trop peu pour éviter les attaques de termites Coptotermes formosanus. En revanche, la combinaison d’une imprégnation par une solution d’acide borique à 1.0 % m/m suivi d’une traitement à l’huile protège efficacement C. japonica contre les termites et les champignons. Alors que son efficacité contre les termites semble principalement due à la rétention du bore, l’huile semble former une barrière efficace contre la pénétration des champignons xylophages. Les seuils d’efficacité d’environ 0.7 kg/m3BAE, plus faible que ceux enregistrés pour les traitements classiques au bore indique que l’huile renforce l’effet biostatique du bore.
The Higgs Boson Masses and Mixings of the Complex MSSM in the Feynman-Diagrammatic Approach

New results for the complete one-loop contributions to the masses and mixing effects in the Higgs sector are obtained for the MSSM with complex parameters using the Feynman-diagrammatic approach. The full dependence on all relevant complex phases is taken into account, and all the imaginary parts appearing in the calculation are treated in a consistent way. The renormalization is discussed in detail, and a hybrid on-shell/ scheme is adopted. We also derive the wave function normalization factors needed in processes with external Higgs bosons and discuss effective couplings incorporating leading higher-order effects. The complete one-loop corrections, supplemented by the available two-loop corrections in the Feynman-diagrammatic approach for the MSSM with real parameters and a resummation of the leading (s)bottom corrections for complex parameters, are implemented into the public Fortran code FeynHiggs 2.5. In our numerical analysis the full results for the Higgs-boson masses and couplings are compared with various approximations, and -violating effects in the mixing of the heavy Higgs bosons are analyzed in detail. We find sizable deviations in comparison with the approximations often made in the literature.
Supporting the generation of argument structure within video sequences

We describe our approach to the automatic generation of argument structures in the domain of video documentaries. Our approach releases control of the final video sequencing from the film maker/annotator to the system and thus allows users to select their own documentaries for viewing. Each video segment is annotated using a formal structure filled in with terms from a thesaurus. The annotations are used for finding and combining video segments into a final presentation. In order to influence the documentaries that can be generated, we introduce three methods for the annotator to evaluate the effectiveness of the annotations and to influence the process of automatic link generation.
Long‐term morphodynamics of muddy backbarrier basins: Fill in or empty out?

The long‐term (3000 years) morphodynamics of an idealized muddy backbarrier tidal basins is studied using a shallow‐water hydrodynamics and wind‐wave model (Deltf3D‐FLOW‐WAVE), modified to include fully coupled marsh organogenic accretion, biostabilization, drag increase, and wave‐induced marsh edge erosion. The latter process is implemented with a novel probabilistic algorithm. Starting from an initially empty basin with a uniform bed slope, a network of channels incise the mudflat, sediment is released, and marshes establish at the basin landward margin. If enough mud is supplied to the basin from the shelf, marsh progradation counteracts marsh edge erosion and marshes expand. Marsh expansion does not completely fill the basin but leaves open a few km‐wide channels, large enough for waves to resuspend sediment. Starting from a basin (almost) filled with marshes, a drop in the external mud supply or an increase in the rate of relative sea level rise causes the basin to empty out by marsh edge erosion, while the marsh platform, aided by reworking of the sediment released by marsh retreat and mudflat deepening, keeps pace even with fast rates (10 mm/yr) of relative sea level rise. Even if the marsh does not drown, the marsh retreats faster if the rate of sea level rise increases, because more sediment is sequestered to fill the newly created accommodation space and is thus not available for marsh progradation. This study suggests that prediction of marsh erosion requires a basin‐scale sediment budget, and that edge erosion, not platform drowning, is likely to dominate marsh loss.
CORPORATE SUSTAINABILITY, STRATEGY AND ACCOUNTING CONTROLS: AN EXPLORATION OF CORPORATE PRACTICES

The accounting and management control literature demonstrates the key role of management control to support strategy implementation. However, despite several calls in the social and environmental accounting research (Parker, 2000; Chung and Parker, 2008), to date, very few studies have explored how management controls support the implementation of a sustainability strategy in practice. With reference to Malmi and Brown framework (2008), this paper explores the existence of a selection of accounting-based controls (planning, cybernetic control as well as reward and compensation systems) to support sustainability strategy deployment. Concretely, based on the qualitative analysis of seven cases, it investigates what kind of accounting-based management controls exists in multinational corporations to support the implementation of an explicit sustainability strategy.
Rich Man, Poor Man: Socioeconomic Adversity and Brain Development

Editor’s Note: Here’s a disturbing statistic that made headlines this past January: The richest 85 people in the world now hold as much wealth as the poorest half. Keeping in mind the goal of closing the ever-widening gap between the haves and the have-nots, our author examines new research that ties family income level and other factors to brain development. While socioeconomic adversity may not solely determine a child’s success later in life, its significant role in helping children develop language, memory, and life skills can no longer be ignored.
The Evolution of Social Orienting: Evidence from Chicks (Gallus gallus) and Human Newborns

Background Converging evidence from different species indicates that some newborn vertebrates, including humans, have visual predispositions to attend to the head region of animate creatures. It has been claimed that newborn preferences for faces are domain-relevant and similar in different species. One of the most common criticisms of the work supporting domain-relevant face biases in human newborns is that in most studies they already have several hours of visual experience when tested. This issue can be addressed by testing newly hatched face-naïve chicks (Gallus gallus) whose preferences can be assessed prior to any other visual experience with faces. Methods In the present study, for the first time, we test the prediction that both newly hatched chicks and human newborns will demonstrate similar preferences for face stimuli over spatial frequency matched structured noise. Chicks and babies were tested using identical stimuli for the two species. Chicks underwent a spontaneous preference task, in which they have to approach one of two stimuli simultaneously presented at the ends of a runway. Human newborns participated in a preferential looking task. Results and Significance We observed a significant preference for orienting toward the face stimulus in both species. Further, human newborns spent more time looking at the face stimulus, and chicks preferentially approached and stood near the face-stimulus. These results confirm the view that widely diverging vertebrates possess similar domain-relevant biases toward faces shortly after hatching or birth and provide a behavioural basis for a comparison with neuroimaging studies using similar stimuli.
Parent material and climate affect soil organic carbon fractions under pastures in south-eastern Australia

In the present field survey, 72 sites were sampled to assess the effect of climate (Monaro, Boorowa and Coleambally regions) and parent material (Monaro region only; basalt and granite) on soil organic carbon (OC) under perennial pastures. In the higher-rainfall zone (Monaro and Boorowa; >500mm mean annual rainfall), OC stocks under introduced and native perennial pastures were compared, whereas in the lower-rainfall zone (Coleambally; <500mm mean annual rainfall) OC stocks under crops and pastures were compared. Carbon fractions included total OC (TOC), particulate OC (POC), resistant OC (ROC) and humic OC (HUM). Higher OC stocks were associated with higher spring and summer rainfall and lower annual temperatures. Within a climatic zone, parent material affected the stock of OC fractions in the 0–30cm soil layer. Within a climatic zone, when grouped by parent material, there was no difference in OC stock with vegetation type. There were significant correlations between soil factors associated with parent material and OC concentration, including negative correlations between SiO2 and HUM (P<0.05) and positive correlations between cation exchange capacity and TOC, POC and ROC (P<0.01). TOC was also positively correlated with total nitrogen (N) and available sulfur (S; P<0.05), indicating organic matter in soil is important for N and S supply for plant production in the studied regions, and vice versa. Although ensuring adequate available S may increase OC stocks in south-eastern Australia, the large stock of OC in the soil under perennial pastures, and the dominating effect of climate and parent material on this stock, may mean that modest increases in soil OC due to management factors go undetected.
On locality and related problems: Communicating, computing, exploring

Locality is a peculiarity which is exhibited by many problems appearing in the most disparate domains of theoretical computer science and mathematics. In this thesis, we demonstrate this assertion by studying three classes of problems that are related to the task of communicating, computing and exploring, respectively. By a local problem, we understand a problem which is easily solved if the problem solver(s) would have access to the whole instance at once. However, the difficulty is that the problem solver is allowed to initially look only at a small portion of the instance, and at every point of the resolution process she gets a small piece of new information that depends on her choices and on the model she is operating with. The problem solver incurs a unit cost when she gets a new information, but can work with the information she already has for free. In the first part of this thesis we focus on the process of communication. We introduce and study the so called algebraic communication complexity of a multivariate polynomial or rational function. In this model two or more players aim to evaluate a rational function according to some input. However the input is distributed among the players. Hence, they exchange messages in such a way that eventually a player is able to correctly determine the value of the function at the given input. Our goal is to determine the least number of messages that are required to solve the task for every given input. We propose different techniques that establish lower bounds for this complexity measure. We apply these results to show that a broad class of multicast cost sharing mechanisms – namely truthful budget-balanced mechanisms – need to send many messages in a network in the worst case during the resolution process. In the second part we deal with the realm of computation. We focus on distributed algorithms for wireless sensor networks. In such a network, every node is a computational unit that performs some actions. However, its view is limited to the set of nodes that can be reached through direct communication with its wireless equipment. As an algorithm progresses, each node gathers more information about the network topology. We start with the observation that many such algorithms require to solve some graph-theoretical problem during their execution. Hence a good understanding of the locality of such problems is much needed. In this thesis we design
Modeling, Analysis, and Stabilization of Converter-Fed AC Microgrids With High Penetration of Converter-Interfaced Loads

This paper addresses ac microgrid stability under high penetration of converter-interfaced loads (CILs). According to the Nyquist admittance ratio criterion, destabilizing interaction dynamics are yielded among the interfacing voltage-source inverter (VSI) of the ac microgrid and CILs. Active stabilization techniques are proposed to maintain the overall system stability from the VSI side using admittance-based small signal analysis. Sensitivity and robustness analyses are presented to assess the dynamic coupling among active damping and voltage tracking controllers of the interfacing VSI. A complete Matlab/Simulink model of an ac microgrid with multiple CILs is used to demonstrate the effectiveness of the proposed active compensation techniques.