Island biogeography theory and the habitat heterogeneity jointly explain global patterns of Rhododendron diversity

Mountain biodiversity is of great importance to biogeography and ecology.However,it is unclear what ecological and evolutionary processes best explain the generation and maintenance of its high levels of species diversity.In this study,we determined which of six common hypotheses(e.g.,climate hypotheses,habitat heterogeneity hypothesis and island biogeography theory)best explain global patterns of species diversity in Rhododendron.We found that Rhododendron diversity patterns were most strongly explained by proxies of island biogeography theory(i.e.,mountain area)and habitat heterogeneity(i.e.,elevation range).When we examined other relationships important to island biogeography theory,we found that the planimetric area and the volume of mountains were positively correlated with the Rhododendron diversity,whereas the‘mountains-to-mainland’distance was negatively correlated with Rhododendron diversity and shared species.Our findings demonstrate that Rhododendron diversity can be explained by island biogeography theory and habitat heterogeneity,and mountains can be regarded as islands which supported island biogeography theory.

建设中山大学软件工厂,提高软件人才培养质量(英文)

Software School of SYSU(Sun Yat-Sen University) is in a positive school-enterprise cooperation, and establishes the Sysusoft (SYSU Software Factory). Sysusoft is market-oriented directly, follows the modern enterprise system operation and management, vigorously carries out the software training, software outsourcing, independent research and development, and studiously builds up the ‘Sysusoft’ brand. Sysusoft internally undertakes the practice teaching of Software School of SYSU undergraduate students. It promotes the students to synthesize the quality comprehensively, and improves the quality of software talents training. Sysusoft innovates the talents training mode creatively, carries large amount of "high-level, international, mixed type of application, project, and multi-skill" software talent according to the needs of the society, and encourages the students to venture the hypothesized imbark. All these have become the sponsoring software characteristics.

S.D. Krashen's Language Acquisition Theory and the Teaching of Business English Reading

This paper first illustrates S.D. Krashen's language acquisition theory, especially two of his five hypotheses as well as the guidance of these theories towards the teaching of business English reading for students majored in business English.

Two rare gastric hamartomatous inverted polyp cases suggest the pathogenesis of growth

Gastric hamartomatous inverted polyps(GHIP)are difficult to diagnose accurately because of inversion into the submucosal layer.GHIP are diagnosed using the pathological characteristics of the tumor,including the fibroblast cells,smooth muscle,nerve components,glandular hyperplasia,and cystic gland dilatation.Although Peutz-Jeghers syndrome,juvenile polyposis,and Cowden disease are hereditary,it is rare to encounter 2 cases of monostotic and asymptomatic gastric hamartomas.The pathogeneses of hamartomatous inverted polyps and inverted hyperplastic polyps remain controversial because of the paucity of reported cases.There are 3 hypotheses regarding the pathogenesis of complete gastric inverted polyps.Based on our experience with 2 successive,rare GHIP cases,we affirm the hypothesis that after a hamartomatous change occurs in the submucosal layer,some of these components are exposed to the gastric mucosa and,consequently,form a hypertrophic lesion.In Case 1,our hypothesis explains why a tiny hypertrophic change was first detected on the top of the submucosal tumor using a detailed narrow band imaging-magnified endoscopy.There was no confirmation that the milky white mucous and calcification structures were exuding directly from the biopsy site like Case 1,and in Case 2 the presence of this mucous was indirectly confirmed during an endoscopic submucosal dissection(ESD).Regarding the pathogenesis of GHIP,a submucosal hamartomatous change may occur prior to the growth of hypertrophic portions.An en bloc resection using ESD is recommended for treatment.

MULTITARGET STATE AND TRACK ESTIMATION FOR THE PROBABILITY HYPOTHESES DENSITY FILTER

The particle Probability Hypotheses Density (particle-PHD) filter is a tractable approach for Random Finite Set (RFS) Bayes estimation, but the particle-PHD filter can not directly derive the target track. Most existing approaches combine the data association step to solve this problem. This paper proposes an algorithm which does not need the association step. Our basic ideal is based on the clustering algorithm of Finite Mixture Models (FMM). The intensity distribution is first derived by the particle-PHD filter, and then the clustering algorithm is applied to estimate the multitarget states and tracks jointly. The clustering process includes two steps: the prediction and update. The key to the proposed algorithm is to use the prediction as the initial points and the convergent points as the es- timates. Besides, Expectation-Maximization (EM) and Markov Chain Monte Carlo (MCMC) ap- proaches are used for the FMM parameter estimation.

Multi-target tracking algorithm of boost-phase ballistic missile defense

Considering the problem of multiple ballistic missiles tracking of boost-phase ballistic missile defense, a boost-phase tracking algorithm based on multiple hypotheses tracking （MHT） concept is proposed. This paper focuses on the tracking algo- rithm for hypothesis generation, hypothesis probability calculation, hypotheses reduction and pruning and other sectors. From an engineering point of view, a technique called the linear assignment problem （LAP） used in the implementation of M-best feasible hypotheses generation, the number of the hypotheses is relatively small compared with the total number that may exist in each scan, also the N-scan back pruning is used, the algorithm＇s efficiency and practicality have been improved. Monte Carlo simulation results show that the proposed algorithm can track the boost phase of multiple ballistic missiles and it has a good tracking performance compared with joint probability data association （JPDA）.

A NEW DATA ASSOCIATION ALGORITHM USING PROBABILITY HYPOTHESIS DENSITY FILTER

Probability Hypothesis Density (PHD) filtering approach has shown its advantages in tracking time varying number of targets even when there are noise,clutter and misdetection. For linear Gaussian Mixture (GM) system,PHD filter has a closed form recursion (GMPHD). But PHD filter cannot estimate the trajectories of multi-target because it only provides identity-free estimate of target states. Existing data association methods still remain a big challenge mostly because they are com-putationally expensive. In this paper,we proposed a new data association algorithm using GMPHD filter,which significantly alleviated the heavy computing load and performed multi-target trajectory tracking effectively in the meantime.

The Application of Input Theory to English Classroom Teaching

Early in the 1980s,Stephen Krashen has proposed a comprehensive and overall Input Theory that explains how the second language is acquired.It is still very referential to present English classroom teaching.In this essay,applications of Input Theory to English classroom teaching are developed from six aspects,involving the nature of second language acquisition,comprehensible input and so on.

Analysis of Krashen's Affective Filter Hypothesis

Affective filter hypothesis is one of Krashen's five hypotheses on Second Language Acquisition (SLA), and it states that a number of affective variables play a very important role in Second Language Acquisition. Based on the introduction of affective filter hypothesis, this paper will analyze the significance and shortcomings of this hypothesis.

LOCAL CONVERGENCE OF INEXACT NEWTON-LIKE METHOD UNDER WEAK LIPSCHITZ CONDITIONS

The paper develops the local convergence of Inexact Newton-Like Method(INLM)for approximating solutions of nonlinear equations in Banach space setting.We employ weak Lipschitz and center-weak Lipschitz conditions to perform the error analysis.The obtained results compare favorably with earlier ones such as[7,13,14,18,19].A numerical example is also provided.

Sequence detection data fusion with distributed multisensor

This Paper presents a data fusion method with distributed sequence detection for on hypothasis testingtheory including the data fusion algorithm of sequence detection based on least error probability rule, the decision ruleand the calcation formula of the detction times and the simulation result of system performance as well.

Two Hypotheses of “Melanization” on Electrogalvanized Steel Surface

Melanization is harmful to the lightness of galvanized steel surface and also reduces the bonding force between a paint coat and the steel sheet. Experimental results showed that the hypothesis of Zn-Pb codeposition does not hold true, while the fact that PbSO4 micelles in sulfate bath settle on the coating surface support the second hypothesis. The authors come to the conclusions that (1) Any measure to eliminate PbSO4 micelles before or after passivation of the coating will prevent melanization; (2) PbSO4 micelles adsorbed on the surface of passivated film promote the growth of oxygen-deficient Zn oxide and result in the generation of melanization.

Limited negative semantics based inductive hypotheses

The Learning method of inductive logic programming evaluates the the quality of inductive hypotheses commonlyby how well the hypotheses cover training examples extensionally. Ths kind of evalution will be completely inapplica-ble to the situation where there are non-simple or noise examples. Based on Limited Negative semantics, This paperextends induction of simple examples to that of generalized ones and presents 3 criteria on accepting inductive hypothe-ses in order to fit for different goals of induction. The relation between inductive hypotheses and background knowledgeis also established in this Paper. The conclusions in this paper are helpful to implement learning algorithms and to ex-tend application fields of ILP.

Why It Is Problematic to Calculate Probabilities of Findings Given Range Null Hypotheses

An important problem with null hypothesis significance testing, as it is normally performed, is that it is uninformative to reject a point null hypothesis [1]. A way around this problem is to use range null hypotheses [2]. But the use of range null hypotheses also is problematic. Aside from the usual issues of whether null hypothesis significance tests can be justified at all, there is an issue that is specific to range null hypotheses. It is not straightforward how to calculate the probability of the data given a range null hypothesis. The traditional way is to use the single point that maximizes the obtained p-value. The Bayesian alternative is to propose a prior probability distribution and integrate across it. Because frequentists and Bayesians disagree about a variety of issues, especially those pertaining to whether it is permissible to assign probabilities to hypotheses, and what gets lost in the shuffle is that the two camps actually come to different answers for the probability of the data given a range null hypothesis. Because the probability of the data given the hypothesis is a precursor for both camps, for drawing conclusions about hypotheses, different values for this probability for the different camps is crucial but seldom acknowledged. The goal of the present article is to bring out the problem in a manner accessible to researchers without strong mathematical or statistical backgrounds.

THE PROBABILITY HYPOTHESIS DENSITY FILTER WITH EVIDENCE FUSION

The original Probability Hypothesis Density (PHD) filter is a tractable algorithm for Multi-Target Tracking (MTT) in Random Finite Set (RFS) frameworks. In this paper,we introduce a novel Evidence PHD (E-PHD) filter which combines the Dempster-Shafer (DS) evidence theory. The proposed filter can deal with the uncertain information,thus it forms target track. We mainly discusses the E-PHD filter under the condition of linear Gaussian. Research shows that the E-PHD filter has an analytic form of Evidence Gaussian Mixture PHD (E-GMPHD). The final experiment shows that the proposed E-GMPHD filter can derive the target identity,state,and number effectively.

Sequential Test of Fuzzy Hypotheses

In testing statistical hypotheses, as in other statistical problems, we may be confronted with fuzzy concepts. This paper deals with the problem of testing hypotheses, when the hypotheses are fuzzy and the data are crisp. We first give new definitions for notion of mass (density) probability function with fuzzy parameter, probability of type I and type II errors and then state and prove the sequential probability ratio test, on the basis of these new errors, for testing fuzzy hypotheses. Numerical examples are also provided to illustrate the approach.

Analysis of Variance for Three-Way Unbalanced Mixed Effects Interactive Model

In the study, a method of solving ANOVA problems based on an unbalanced three-way mixed effects model with interaction for data when factors A and B are fixed, and factor C is random was presented, and the required EMS was derived. Under each of the appropriate null hypotheses, it was observed that none of the derived EMS was unbiased for the other. Unbiased estimators of the mean squares were determined to test hypotheses. With the unbiased estimators,?appropriate F-statistics as well as their corresponding pseudo-degrees of freedom were obtained. The theoretical results presented in the paper were?illustrated using a numerical example.

Dark Matter and Gravitational Waves

Two reviews of papers are considered. The first paper for a galaxy model uses matter consisting of neutrinos, bosons and other similar particles. It is shown that these particles were introduced as a result of an incorrect description of interactions in the Theory of Relativity. In reality, with the relative motion of interacting particles, their interactions force changes, and not their mass. It is shown that models of such stellar associations as globular clusters and galaxies should be created on the basis of the substance that exists on Earth. The second peer-reviewed paper proposes to create LIGO on the Moon. It is shown that gravitational waves do not exist. They were introduced to explain the excessive rotation of the Mercury’s perihelion. However, the excessive rotation of the Mercury’s perihelion is due to the Sun oblateness. The paper shows that gravitational waves, the Big Bang, the expanding Universe, dark matter, dark energy, etc. appeared on the basis of unfounded hypotheses. The urgent task is to eliminate them from science.

Clinical Judgment Development: Six Steps to Establish Professional Identity and Role-Specific Competencies in Caring for a Sexual Assault Survivor

Background: Clinical judgment is a specific role that establishes a professional identity. The purpose of this paper is to prepare nursing students to make better judgments in the clinical setting and realign learning and teaching. Methods: We used six steps to arrive at a competent clinical judgment suggested by the National Council State Board of Nursing (NSCBN) as a clinical judgment model 1) recognizing cues, 2) analyzing cues, 3) prioritizing hypotheses, 4) generating solutions, 5) taking an action, and 6) evaluating outcomes during the head-to-toe examination of the patient. Results: The primary outcomes are stabilization of the hemodynamics of the patient and prevention of further blood loss. Fluids are being given to help keep the vascular volume from being depleted, but they cannot solve the underlying problem. Continued assessment, intervention, and monitoring of vital signs through the course of the hospital stay ending with the patient’s discharge. Discussion: Survivors of sexual assault are unique for a nurse to provide care. The nurse needs to assess, intervene, monitor, and pay attention to detail of the 6 steps to clinical judgment, resulting in positive outcomes for their patient. Conclusions: Forensic nursing is a field of nursing that focuses on sexual assault survivor care and works to make the aftermath of their tragic situation easier to cope with. Strengthening clinical judgment skills could remedy significant mistakes made by novice forensic nurses. Critical thinking and clinical ethical reasoning are the building blocks of clinical judgment.

Application Research of the Integrative Mathematics Model in Household Consumption Behavior

In this paper, two hypotheses are integrated into an independent model to explain consumer behavior. The model is empirically tested using data from China Family Cost Survey of 2001. The results indicate that China household consumption behavior is commonly explained by two hypotheses as an independent model, reverse to previously treating them as commutative exclusive hypotheses.