Negation in Modern Standard Arabic: An LFG approach

Modern Standard Arabic (MSA) uses five different particles to express sentential negation: the invariant particle maa, the particle laa and its tensed counterparts lam (PAST) and lan (FUT), and laysa which is marked only for SUBJ agreement. Partial analyses of these elements are offered in other frameworks, notably Minimalism (Shlonsky, 1997; Benmamoun, 2000), but have not to date received an analysis within LFG. We propose an approach to four of these particles: the fifth one, namely maa, raises a number of additional issues and we leave it to one side for reasons of space. laa, lam, lan show distinctions of TENSE, occur only with imperfective forms of the verb (excluding the perfective) and must immediately precede the verb itself. They are limited to occurrence in verbal sentences. We propose that the adjacency requirement follows from the fact that these negative particles are non-projecting words adjoined to the (imperfective) V. On the other hand, laysa is a fully verbal element, and is thus a negative verb, occurring only with present tense interpretation

Real options modeling and valuation of price adjustment flexibility with an application to the leasing industry

Uncertainty poses not only threats but also opportunities. This study sought to build the scientific foundation for introducing a real options (ROs) methodology for price risk management to the leasing industry. A price risk management that allows for both coping with threats and taking advantage of opportunities. In the leasing industry, fixed rate long-term lease contracts help contract parties stabilize cash flows within volatile markets. The contract\u27s term, however, may be extended long enough that prevent capturing the opportunities of gaining greater profits or reducing expenses. Therefore, the flexibility that enables participants to take advantage of favorable market price is desirable. This discussion is dedicated to the study of three different forms of price adjustments flexibility: 1) single-sided price adjustment flexibility (SSPAF). 2) double-sided price adjustment flexibility (DSPAF) with the preemptive right to exercise. 3) DSPAF with the non-preemptive right to exercise. Each was designed to meet various participants flexibility requirements and budgets. An ROs methodology was developed to model, price, and optimize these flexibility clauses. The proposed approach was then tested in the example of Time Charter (TC) rate contracts from the maritime transport industry. Both the metric and the process for quantifying the benefit of the proposed flexibility clauses are provided. This work provides an alternative approach to the price risk management, which is accessible to all participants in the leasing industry. It is also the starting point in studying the multiple-party, multiple-exercisable price adjustment flexibility. Moreover, both the flexibility designs and the proposed ROs methodology for price risk management are applicable to not only other forms of lease contracts but also to other forms of contract relationships. --Abstract, page iii

Financial model for private finance initiative projects applied to school buildings

Private Finance Initiative (PFI) has become a major procurement method in the UK and worldwide. The number of signed PFI deals is growing, but competition is restricted to those companies that are able to afford the initial investment. The bidding cost of PFI projects are high, and bidding companies are not compensated if the client does not award them the project. This is the reason behind several recent high-profile tender xvithdra« als. and is considered a major barrier for private companies wanting to take part in the bidding process. There is an obvious need for a tool to enable construction organizations to participate in PFI projects; one that can support these organizations in a decision-making process that is compatible with their project selection strategies, and will allow them to bid for PFI projects with clearer goals and reduced costs. A computer-based financial model was developed to predict the cost and cash flow of PFI projects, enabling project teams to assess investment decisions at the tendering stage. The proposed model consists of four modules to identify the required building area, predict the construction cost, distribute the occupancy cost, and predict the cash flow of the project. The output of the model provides the project investment results, such as the Net Present Value (NPV), Internal Rate of Return (IRR), Debt Service Coverage Ratio (DSCR), payback period and investment growth ratio. The model can predict the unitary payment but also allows the user to define the unitary payment. The reports of the model contain the cash flow and investment ratio for both types of unitary payment. The model attempts to provide the information required to assess the feasibility and affordability of the project. It gives the private sector the chance to assess the project before they spend unrecoupable funds on the project. It allows the public sector to determine the project cost, cash flow, unitary charge, and provide the information to be used for the Public Sector Comparator. The data required for the development of the model was collected from different sources. The model was initially developed on spreadsheet software: the final version was transformed into a web-based model using the Hypertext Preprocessor (PHP) and Javascript programming languages. The completed model was then sent to many practitioners for validation and assessment of both the concept and numerical application. The responses received show the valuable role the model could play in PFI projects.Ministry of Higher Education, Saudi Arabi

A novel approach for predicting the spatial patterns of urban expansion by combining the chi-squared automatic integration detection decision tree, Markov chain and cellular automata models in GIS

Urban development is a continuous and dynamic spatio-temporal phenomenon associated with economic developments and growing populations. To understand urban expansion, it is important to establish models that can simulate urbanization process and its deriving factors behaviours, monitor deriving forces interactions and predict spatio-temporally probable future urban growth patterns explicitly. In this research, therefore, we presented a hybrid model that integrates the chi-squared automatic integration detection decision tree (CHAID-DT), Markov chain (MC) and cellular automata (CA) models to analyse, simulate and predict future urban expansions in Tripoli, Libya in 2020 and 2025. First, CHAID-DT model was applied to investigate the contributions of urban factors to the expansion process, to explore their interactions and to provide future urban probability map; second, MC model was employed to estimate the future demand of urban land; third, CA model was used to allocate estimated urban land quantity on the probability map to present future projected land use map. Three satellite images of the study area were obtained from the periods of 1984, 2002 and 2010 to extract land use maps and urban expansion data. We validated the model with two methods, namely, receiver operating characteristic and the kappa statistic index of agreement. Results confirmed that the proposed hybrid model could be employed in urban expansion modelling. The applied hybrid model overcame the individual shortcomings of each model and explicitly described urban expansion dynamics, as well as the spatio-temporal patterns involved

Spatio-temporal prediction of urban expansion using bivariate statistical models: assessment of the efficacy of evidential belief functions and frequency ratio models

The urban development process is a continuous and dynamic spatio-temporal phenomenon associated with economic developments and growing populations. Understanding urban expansion processes require models capable of simulating, monitoring, and predicting both urban growth and urban sprawl. In this research, probability-based Evidential Belief Functions (EBF) and Frequency Ratio (FR) models were employed to simulate and to predict the urban expansion probability map of the metropolitan area in Tripoli, Libya. These methods have not been used before in the urban development simulations of cities. By using the geographic information system (GIS), three satellite imageries obtained from 1996, 2002, and 2010 were employed to extract seven urban-deriving factors for the study area. The urban factors are slope, distance to active economic center, distance to central business district (CBD), distance to roads, distance to built-up areas, distance to educational area, and distance to coastal areas. For model calibration, both the EBF and FR models were applied to simulate urban expansion from 1996 to 2002. Data from 2002 to 2010 were used for models validation. Consequently, future suitability maps of urban growth were produced. The validation results indicated 83 % prediction accuracy for the EBF model and 84 % for the FR model. The outcomes established that the models could be employed in the urban expansion modeling of metropolises. The applied models, however, have dynamic and temporal limitations that should be considered in urban growth analysis

Predicting the Standard and Deviant Patterns In EEG Signals Based On Deep Learning Model

In the recent years, there has been a significant growth in the area of brain computer interference. The main aim of such area is to read the brain activities, formulate a specific/desired output and power a specific approach using such output. Electroencephalography (EEG) may provide an insight into the analysis procedure of the human behavior and the level of the attention. Using the deep learning based neural network has a great success in different applications recently,such as making a decision, classifying a pattern and predicting an outcome by learning from a set of data and build the right weight matrices to represent the prediction outcome or the learning patterns. This research work proposes a novel model based on long short-term memory network to predict the standard and the deviant cases within EEG data sets. The EEG signals are acquired utilizing all the 128 electrodes that represent the 128 channels from infants aged between 5 and 7 months. Statistical approaches, principal component analysis (PCA) and autoregressive (AR) power spectral density estimate have been employed to extract the features from the EEG data sets. The proposed deep learning based model has shown great robustness dealing with different types of features extracted from the processed data sets. Very promising results have been achieved in predicting the standard and deviant cases. The standard case was presented with frequent, repetitive stimulus and the deviant case was presented with infrequent sounds

An Effective Hybrid Approach Based on Machine Learning Techniques for Auto-Translation: Japanese to English

In recent years machine learning techniques have been able to perform tasks previously thought impossible or impractical such as image classification and natural language translation, as such this allows for the automation of tasks previously thought only possible by humans. This research work aims to test a naïve post processing grammar correction method using a Long Short Term Memory neural network to rearrange translated sentences from Subject Object Verb to Subject Verb Object. Here machine learning based techniques are used to successfully translate works in an automated fashion rather than manually and post processing translations to increase sentiment and grammar accuracy. The implementation of the proposed methodology uses a bounding box object detection model, optical character recognition model and a natural language processing model to fully translate manga without human intervention. The grammar correction experimentation tries to fix a common problem when machines translate between two natural languages that use different ordering, in this case from Japanese Subject Object Verb to English Subject Verb Object. For this experimentation 2 sequence to sequence Long Short Term Memory neural networks were developed, a character level and a word level model using word embedding to reorder English sentences from Subject Object Verb to Subject Verb Object. The results showed that the methodology works in practice and can automate the translation process successfully

Beta-fibrinogen (-455 G/A) and Integrin beta-3 (PLA1/A2) polymorphisms and recurrent pregnancy loss in Gaza strip-Palestine

Background: This study was conducted in order to determine the relationship between the common polymorphisms in β-fibrinogen -455 G/A (rs1800790) and Integrin beta-3 T196C (PLA1/A2, rs5918) and recurrent pregnancy loss (RPL) in a group of Palestinian women residing in Gaza strip.Methods: The study presented here is a retrospective association study with a case-control design. The study population consisted of 102 women who suffered from RPL and 97 healthy women matched for age and without a previous history of RPL. DNA extracted from blood samples of all subjects was investigated for the β-fibrinogen (-455 G>A) and Integrin beta-3 (PLA1/A2) polymorphisms using PCR-RFLP and PCR-SSP, respectively.Results: The study revealed that β–fibrinogen -455G/A minor allele frequency (allele A) and its homozygous genotype (AA) were not significantly different between the RPL and the control groups. Likewise, there was no significant difference in the distribution of the ITGB-3 variant allele (PLA2) or PLA2/A2 genotype between the two groups. β–fibrinogen AA genotype was evident in 3.9% of the patients and in 4.1% of the controls (P-value = 0.94). The frequency of PLA2/A2 was observed in 2.0% of the patients and in 2.1% of the controls (P-value = 0.96).Conclusion: Results of the present study indicate that there is no significant association between the β–fibrinogen (455 G>A) or Integrin beta-3 (PLA1/A2) common polymorphisms and the occurrence of RPL in Gaza strip. This non-significant relation indicates that the investigated polymorphisms do not constitute a tangible risk for RPL in our population. Therefore, it is not recommended to consider these two polymorphisms when screening for inherited thrombophilia in Gaza strip

Beta-fibrinogen (-455 G/A) and Integrin beta-3 (PLA1/A2) polymorphisms and recurrent pregnancy loss in Gaza strip-Palestine

Background: This study was conducted in order to determine the relationship between the common polymorphisms in β-fibrinogen-455 G/A (rs1800790) and Integrin beta-3 T196C (PLA1/A2, rs5918) and recurrent pregnancy loss (RPL) in a group of Palestinian women residing in Gaza strip. Methods: The study presented here is a retrospective association study with a case-control design. The study population consisted of 102 women who suffered from RPL and 97 healthy women matched for age and without a previous history of RPL. DNA extracted from blood samples of all subjects was investigated for the β-fibrinogen (-455 G> A) and Integrin beta-3 (PLA1/A2) polymorphisms using PCR-RFLP and PCR-SSP, respectively. Results: The study revealed that β–fibrinogen-455G/A minor allele frequency (allele A) and its homozygous genotype (AA) were not significantly different between the RPL and the control groups. Likewise, there was no significant difference in the distribution of the ITGB-3 variant allele (PLA2) or PLA2/A2 genotype between the two groups. β–fibrinogen AA genotype was evident in 3.9% of the patients and in 4.1% of the controls (P-value= 0.94). The frequency of PLA2/A2 was observed in 2.0% of the patients and in 2.1% of the controls (P-value= 0.96). Conclusion: Results of the present study indicate that there is no significant association between the β–fibrinoge

Familial reciprocal translocation t (8; 17)(p23; q21) in a woman with recurrent spontaneous abortion

This work presents the results of cytogenetic analysis of a couple referred to our genetics laboratory with ten first trimester abortions and one IVF failure. The male showed a normal (46, XY) karyotype whereas the female was found to carry an apparently balanced reciprocal translocation [46, XX, t (8; 17)(p23; q21)]. Two sisters and two brothers of the eight siblings of the female proved to have the same translocation. Although the female's father is deceased and his sample was not available for investigation. The origin of this translocation must be paternal since the female's mother harbored a normal karyotype. It is concluded that the history of recurrent pregnancy losses in the couple is due to the production of unbalanced gametes in the female as a result of the reciprocal translocation she has and the couple was advised to undergo a PGD for embryo selection prior to their future IVF trials. The authors also recommend that all RSA couples with normal routine work-up results should be offered chromosomal analysis without delay