REFINEMENTS OF THE NORM OF TWO ORTHOGONAL PROJECTIONS

In this paper,some refinements of norm equalities and inequalities of combination of two orthogonal projections are established.We use certain norm inequalities for positive contraction operator to establish norm inequalities for combination of orthogonal projections on a Hilbert space.Furthermore,we give necessary and sufficient conditions under which the norm of the above combination of o`rthogonal projections attains its optimal value.

How do lateral septum projections to the ventral CA1 influence sociability?

Social dysfunction is a risk factor for several neuropsychiatric illnesses.Previous studies have shown that the lateral septum(LS)-related pathway plays a critical role in mediating social behaviors.Howeve r,the role of the connections between the LS and its downstream brain regions in social behavio rs remains unclea r.In this study,we conducted a three-chamber test using electrophysiological and chemogenetic approaches in mice to determine how LS projections to ventral CA1(vCA1)influence sociability.Our res ults showed that gamma-aminobutyric acid(GABA)-e rgic neuro ns were activated following social experience,and that social behavio rs were enhanced by chemogenetic modulation of these neurons.Moreover,LS GABAergic neurons extended their functional neural connections via vCA1 glutamatergic pyramidal neurons,and regulating LSGABA→vCA1Gluneural projections affected social behaviors,which were impeded by suppressing LSprojecting vCA1 neuronal activity or inhibiting GABAAreceptors in vCA1.These findings support the hypothesis that LS inputs to the vCA1 can control social prefe rences and social novelty behaviors.These findings provide new insights rega rding the neural circuits that regulate sociability.

Onto Orthogonal Projections in the Space of Polynomials Pn[x]

In this article, I consider projection groups on function spaces, more specifically the space of polynomials Pn[x]. I will show that a very similar construct of projection operators allows us to project into the subspaces of Pn[x] where the function h ∈Pn[x] represents the closets function to f ∈Pn[x] in the least square sense. I also demonstrate that we can generalise projections by constructing operators i.e. in Rn+1 using the metric tensor on Pn[x]. This allows one to project a polynomial function onto another by mapping it to its coefficient vector in Rn+1. This can be also achieved with the Kronecker Product as detailed in this paper.

Simulations and Projections of Winter Sea Ice in the Barents Sea by CMIP6 Climate Models

Dramatic changes in the sea ice characteristics in the Barents Sea have potential consequences for the weather and climate systems of mid-latitude continents,Arctic ecosystems,and fisheries,as well as Arctic maritime navigation.Simulations and projections of winter sea ice in the Barents Sea based on the latest 41 climate models from the Coupled Model Intercomparison Project Phase 6(CMIP6)are investigated in this study.Results show that most CMIP6 models overestimate winter sea ice in the Barents Sea and underestimate its decreasing trend.The discrepancy is mainly attributed to the simulation bias towards an overly weak ocean heat transport through the Barents Sea Opening and the underestimation of its increasing trend.The methods of observation-based model selection and emergent constraint were used to project future winter sea ice changes in the Barents Sea.Projections indicate that sea ice in the Barents Sea will continue to decline in a warming climate and that a winter ice-free Barents Sea will occur for the first time during 2042-2089 under the Shared Socioeconomic Pathway 585(SSP5-8.5).Even in the observation-based selected models,the sensitivity of winter sea ice in the Barents Sea to global warming is weaker than observed,indicating that a winter ice-free Barents Sea might occur earlier than projected by the CMIP6 simulations.

A Relation between Resolvents of Subdifferentials and Metric Projections to Level Sets

An equation concerning with the subdifferential of convex functionals defined in real Banach spaces and the metric projections to level sets is shown. The equation is compared with the resolvents of general monotone operators, and makes the geometric properties of differential equations expressed by subdifferentials clear. Hence, it can be expected to be useful in obtaining the steepest descents defined by the convex functionals in Banach spaces. Also, it gives a similar result to the Lagrange multiplier method under certain conditions.

Face recognition using illuminant locality preserving projections

A novel supervised manifold learning method was proposed to realize high accuracy face recognition under varying illuminant conditions. The proposed method, named illuminant locality preserving projections （ILPP）, exploited illuminant directions to alleviate the effect of illumination variations on face recognition. The face images were first projected into low dimensional subspace, Then the ILPP translated the face images along specific direction to reduce lighting variations in the face. The ILPP reduced the distance between face images of the same class, while increase the dis tance between face images of different classes. This proposed method was derived from the locality preserving projections （LPP） methods, and was designed to handle face images with various illumi nations. It preserved the face image＇ s local structure in low dimensional subspace. The ILPP meth od was compared with LPP and discriminant locality preserving projections （DLPP）, based on the YaleB face database. Experimental results showed the effectiveness of the proposed algorithm on the face recognition with various illuminations.

The Cartography of Focus and Interrogative Projections inǸjò`-Kóo

Researches on cartography have made universal predictions on the hierarchies of functional projections in language.Based on this assumption,the structural maps established by Rizzi(1997,2001b)for the left-peripheral elements suggest very strongly that Interrogative dominates Focus.Nevertheless,a straight-jacket adoption of this proposed hierarchical order to account for these left-peripheral projections inǸjò`-Kóo would be counterintuitive.Therefore,leaning on empirical and theoretical evidence,the paper calls to question the universality of the cartographers’claim,and argues that the opposite of the view is true ofǸjò`-Kóo.The paper adopts fieldwork method for data elicitation and descriptive approach as well as minimalist program for analysis of data.Data used in this study were elicited from purposively selected native speakers based on language proficiency.Data were acquired with syntactic checklist and structured interviews,and were subjected to interlinear and qualitative analysis.

Downscaled climate change projections for the Hindu Kush Himalayan region using CORDEX South Asia regional climate models

This study assessed the regional climate models (RCMs) employed in the Coordinated Regional climate Downscaling Experiment (CORDEX) South Asia framework to investigate the qualitative aspects of future change in seasonal mean near surface air temperature and precipitation over the Hindu Kush Himalayan (HKH) region. These RCMs downscaled a subset of atmosphere ocean coupled global climate models (AOGCMs) in the Coupled Model Intercomparison Project phase 5 (CMIP5) to higher 50 km spatial resolution over a large domain covering South Asia for two representation concentration pathways (RCP4.5 and RCP8.5) future scenarios. The analysis specifically examined and evaluated multi-model and multi-scenario climate change projections over the hilly sub-regions within HKH for the near-future (2036e2065) and far-future (2066e2095) periods. The downscaled multi-RCMs provide relatively better confidence than their driving AOGCMs in projecting the magnitude of seasonal warming for the hilly sub-region within the Karakoram and northwestern Himalaya, with higher projected change of 5.4
C during winter than of 4.9
C during summer monsoon season by the end of 21st century under the high-end emissions (RCP8.5) scenario. There is less agreement among these RCMs on the magnitude of the projected warming over the other sub-regions within HKH for both seasons, particularly associated with higher RCM uncertainty for the hilly sub-region within the central Himalaya. The downscaled multi-RCMs show good consensus and low RCM uncertainty in projecting that the summer monsoon precipitation will intensify by about 22% in the hilly subregion within the southeastern Himalaya and Tibetan Plateau for the far-future period under the RCP8.5 scenario. There is low confidence in the projected changes in the summer monsoon and winter season precipitation over the central Himalaya and in the Karakoram and northwestern Himalaya due to poor consensus and moderate to high RCM uncertainty among the downscaled multi-RCMs. Finally, the RCM related uncertainty is found to be large for the projected changes in seasonal temperature and precipitation over the hilly sub-regions within HKH by the end of this century, suggesting that improving the regional processes and feedbacks in RCMs are essential for narrowing the uncertainty, and for providing more reliable regional climate change projections suitable for impact assessments in HKH region.

The continuous wavelet projections algorithm: A practical spectral-feature-mining approach for crop detection

Spectroscopy can be used for detecting crop characteristics. A goal of crop spectrum analysis is to extract effective features from spectral data for establishing a detection model. An ideal spectral feature set should have high sensitivity to target parameters but low information redundancy among features.However, feature-selection methods that satisfy both requirements are lacking. To address this issue,in this study, a novel method, the continuous wavelet projections algorithm(CWPA), was developed,which has advantages of both continuous wavelet analysis(CWA) and the successive projections algorithm(SPA) for generating optimal spectral feature set for crop detection. Three datasets collected for crop stress detection and retrieval of biochemical properties were used to validate the CWPA under both classification and regression scenarios. The CWPA generated a feature set with fewer features yet achieving accuracy comparable to or even higher than those of CWA and SPA. With only two to three features identified by CWPA, an overall accuracy of 98% in classifying tea plant stresses was achieved, and high coefficients of determination were obtained in retrieving corn leaf chlorophyll content(R^(2)= 0.8521)and equivalent water thickness(R^(2)= 0.9508). The mechanism of the CWPA ensures that the novel algorithm discovers the most sensitive features while retaining complementarity among features. Its ability to reduce the data dimension suggests its potential for crop monitoring and phenotyping with hyperspectral data.

Supervised local and non-local structure preserving projections with application to just-in-time learning for adaptive soft sensor

In soft sensor field, just-in-time learning(JITL) is an effective approach to model nonlinear and time varying processes. However, most similarity criterions in JITL are computed in the input space only while ignoring important output information, which may lead to inaccurate construction of relevant sample set. To solve this problem, we propose a novel supervised feature extraction method suitable for the regression problem called supervised local and non-local structure preserving projections(SLNSPP), in which both input and output information can be easily and effectively incorporated through a newly defined similarity index. The SLNSPP can not only retain the virtue of locality preserving projections but also prevent faraway points from nearing after projection,which endues SLNSPP with powerful discriminating ability. Such two good properties of SLNSPP are desirable for JITL as they are expected to enhance the accuracy of similar sample selection. Consequently, we present a SLNSPP-JITL framework for developing adaptive soft sensor, including a sparse learning strategy to limit the scale and update the frequency of database. Finally, two case studies are conducted with benchmark datasets to evaluate the performance of the proposed schemes. The results demonstrate the effectiveness of LNSPP and SLNSPP.

Approximately Conformal,Equivalent and Equidistant Map Projections

If geodetic coordinates from an ellipsoid are included in the equations of a projection for mapping a sphere instead of geographical coordinates,the result will be a projection of the ellipsoid into a plane.This will slightly change the distortion distribution of the initial map projection.The question is to what extent the replacement of geographical with geodetic coordinates will affect this change.In this paper,we deal with conformal,equal-area and equidistant projections of the sphere,which we modify by using geodetic coordinates instead of geographical ones.The result will be an approximately conformal,approximately equal-area and approximately equidistant projection.It is shown that in this case the maximum distortion of the angles in approximately conformal projections will be approximately 23.09′,the maximum distortion of the area in approximately equal-area projections less than 0.7% and the maximum distortion of lengths in approximately equidistant projections less than 0.7%,therefore on the maps imperceptible.

Climate Change Projections and the Associated Potential Impacts for Somalia

Somalia has faced severe challenges linked to climate variability, which has been exacerbated by conflict and limited governance that persisted for decades. Today climate extremes such as floods, drought, and coastal marine severe systems among others are always associated with the destruction of property and livelihoods;losses of lives lost, migrations, and resource based conflicts among many other miseries. Intergovernmental Panel on Climate Change (IPCC) has shown that climate change is real and requires sound knowledge of local future climate change scenarios. The study attempted to provide projected rainfall and temperature change scenarios over Lower Jubba, Somalia. This was done using the downscaled Coordinated Regional Downscaling Experiment (CORDEX) RCMs data. The simulated temperature and rainfall data derived from the CORDEX RCMs ensemble were compared with the observed data. The study focused on the IPCC projected periods of 2030, 2050 and 2070 benchmarks. Analysis of the projected rainfall indicated a decreasing trend in rainfall leading up to 2030 followed by an increase in rainfall with the 2050 and 2070 scenarios. In the case of temperature, the projections from all the models showed increase in minimum and maximum temperatures in all seasons and sub periods, like being observed by temperature projection over other parts of the world. The 2030, 2050 and 2070 projected rainfall and temperature change scenarios show that Somalia future development and livelihoods will in future face increased threats of climate extremes unless effective climate smart adaptation systems form integral components of national development strategies.

Model Projections of East Asian Summer Climate under the ‘Free Arctic’ Scenario

This paper addresses the ‘ice-free Arctic’ issue under the future global warming scenario. Four coupled climate models used in the third phase of the Coupled Model Intercomparison Project (CMIP3) were selected to project summer climate conditions over East Asia once the Arctic becomes ice-free. The models project that an ice-free Arctic summer will begin in the 2060s under the SRESA1B (according to IPCC Special Reports on Emissions Scenarios) simulations. Our results show that the East Asian summer monsoons will tend to be stronger and that the water vapor transport to central northern China will be strengthened, leading to increased summer precipitation in central northern China. The models also project an intensified Antarctic Oscillation, a condition which favors increased precipitation in South China’s Yangtze River Valley. The overall precipitation in Northwest China is projected to increase under ice-free Arctic summer conditions.

Co-localization of two-color rAAV2-retro confirms the dispersion characteristics of efferent projections of mitral cells in mouse accessory olfactory bulb

The accessory olfactory bulb(AOB), located at the posterior dorsal aspect of the main olfactory bulb(MOB), is the first brain relay of the accessory olfactory system(AOS), which can parallelly detect and process volatile and nonvolatile social chemosignals and mediate different sexual and social behaviors with the main olfactory system(MOS). However, due to its anatomical location and absence of specific markers, there is a lack of research on the internal and external neural circuits of the AOB. This issue was addressed by singlecolor labeling and fluorescent double labeling using retrograde rAAVs injected into the bed nucleus of the stria terminalis(BST), anterior cortical amygdalar area(ACo), medial amygdaloid nucleus(MeA), and posteromedial cortical amygdaloid area(PMCo) in mice. We demonstrated the effectiveness of this AOB projection neuron labeling method and showed that the mitral cells of the AOB exhibited efferent projection dispersion characteristics similar to those of the MOB. Moreover, there were significant differences in the number of neurons projected to different brain regions, which indicated that each mitral cell in the AOB could project to a different number of neurons in different cortices. These results provide a circuitry basis to help understand the mechanism by which pheromone information is encoded and decoded in the AOS.

Effects of Sunspot on the Multi-Decadal Climate Projections

Most model generated projections of climate change for the future decades only consider anthro- pogenic activities. It is hard to think about the effects of solar activity and volcano effects, because the pre- dictions of both solar activity and volcano effects are difficult. But as we know, the sun is the source of en- ergy for the Earth＇s climate system, and observations show it to be a variable star.

Supervised Kernel Uncorrelated Discriminant Neighborhood Preserving Projections

To separate each pattern class more strongly and deal with nonlinear ease, a new nonlinear manifold learning algorithm named supervised kernel uneorrelated diseriminant neighborhood preserving projections （SKUDNPP） is proposed. The algorithm utilizes supervised weight and kernel technique which makes the algorithm cope with classifying and nonlinear problems competently. The within-class geometric structure is preserved, while maximizing the between-class distance. And the features extracted are statistically uneorrelated by introducing an uneorrelated constraint. Experiment results on millimeter wave （MMW） radar target recognition show that the method can give competitive results in comparison with current papular algorithms.

The Role of Nuclear Regulators in Reviewing Population Growth Projections

One of the roles of nuctear regulators is to review population projections calculated by applicants for populations lying in the vicinity of nuclear power plants. This paper examines methods of calculating rates of growth and thus calculating future population growth. This paper is concerned about regulators making sure that nuclear power plants are not located near densely populated centers and that population centers located near nuclear power plants do not become densely populated. In the case of El Dabaa city in the north coast of Egypt, south west of the nominated plant site, three rates of growth 1.5%, 2.5% and 3% were identified. The first is the current population growth rate of the city, the second is the average national growth rate and the third is the expected growth rate of the city when the nuclear power plant gets constructed and operated. In all three cases, this city is a population center and rules of distance from the nuclear power plant shall apply. Thus the further natural growth of this city should be controlled and directed away from the downwind of the plant.

Assessing Actuarial Projections Accuracy: Traditional vs. Experimental Strategy

This paper gives an overview of the Lee Carter method and reiterates the feasibility of using it to construct mortality forecast for the population data. In a first step, the model is fitted in a traditional way and used to extrapolate forecast of the time-varying mortality index. The observed pattern of the mortality rates shows a different variability at different ages, highlighting that the homoscedasticity hypothesis is quite unrealistic. Thus, in a second step, the paper aims to produce more reliable mortality forecasting, focusing on the errors in the estimation of the model parameters. The robustness of the estimated parameter is analysed throughout an experimental strategy which allows to assess the robustness of the Lee Carter model by inducing the errors to satisfy the homoscedasticity hypothesis. The graphical and numerical results are tested by means of a comparison in terms of prediction accuracy.

Climatic Projections of Lightning in Southeastern Brazil Using CMIP5 Models in RCP’s Scenarios 4.5 and 8.5

Given the high and increasing lightning incidence over the Southeast of Brazil and the various impacts that this phenomenon generates to society, there is a growing need in predicting its occurrence, in order to minimize its consequences. In this context, this work presents the development of a methodology for the projection of lightning in the State of S?o Paulo (Southeastern Brazil), using the HadGEM2-ES and CSIRO-Mk3.6 models in two IPCC climate change scenarios: RCP4.5 and RCP8.5. Since lightning is not an output variable of climate models, tests were carried out to evaluate the relationship between the observed data of oceanic and atmospheric fields, which are known as outputs of the models, and the lightning from the RINDAT and BrasilDAT detection networks. As result, a correlation of 0.84 was obtained. In the projections, it was verified that, while during a large portion of the current climate we observed events of lightning below the average, the future climate reveals the preponderance of anomalously above average events, both in the scenario of intermediate-low emissions (RCP4.5) and in the scenario of high emissions (RCP8.5), suggesting a change in the pattern of the lightning incidence in the State of S?o Paulo.

Climate Change Projections for Mediterranean Region with Focus over Alpine Region and Italy

Climate change projections over the Mediterranean region have been elaborated by using the outputs of ten ENSEMBLES regional climate simulations with an horizontal resolution of 25 km under the SRES A1B emission scenario. The analysis concerns some surface atmospheric variables： mean sea level pressure, temperature, precipitation and wind speed. At first, model validations have been performed by comparing model results with E-OBS and ERA-Interim data in reproducing the last decades over some Italian sub-areas and the Alpine region. In spite of the considerable spread in the models＇ performances to represent the reference climate, a multi-model reconstruction has been computed and some seasonal climate change projections have been elaborated. About the mean climate changes, the more significant signals expected by 2050 are a maximum warming （about 2 ~C） and maximum drying （about 20%） in the southern Europe in summer. Moreover, the results indicate an increasing risk for some severe weather conditions： more days of extremely high temperature in summer over the whole area, a greater occurrence of flooding and storms over coasts during spring and autumn seasons and a more serious wet-snow event over Alpine region in winter. No significant signals of wind changes have been detected.