Age at Sexual Assault and Posttraumatic Stress Disorder in Females Residents of Virginia

Background Post Traumatic Stress Disorder (PTSD) is a psychiatric debilitating condition that can occur in individuals who experience extremely stressful or traumatic life events. Sexual assault is considered as one of the most traumatic stressor in life. Although few studies investigated the association between history of sexual assault and PTSD, no studies have examined the impact of age at sexual assault on PTSD.Method A cross-sectional telephone survey was conducted among adult female residents of Virginia from November 2002 to February 2003. A total of 1,769 women aged 18 and older were interviewed using a random digit dialing method. Detailed screening questionnaire was utilized to ascertain the occurrence of sexual assault, age at sexual assault and PTSD. The DSM-IV diagnostic criteria were used to define PTSD.Result The prevalence of PTSD among women with no history of sexual assault, those victimized before the age of 18 and 18 and above was 8.1%, 35.3%, and 30.2% respectively. Multivariate logistic regression model showed an increase risk of PTSD among women assaulted at a younger age. Compared to women with no history of sexual assault, women who were victimized before their 18th birthday were 2.8 times more likely to suffer from PTSD [OR=2.78 (95% C1=1.87- 4.23)]. The risk of PTSD among women victimized as adults was 2.6 times higher compared to women with no history of sexual assault [OR=2.59 (95%CI =1.43-4.70)].Conclusion This study provided important information on the association between PTSD and age at sexual assault. The risk of PTSD is relatively higher among those assaulted before the age of 18. The adverse effect of sexual assault as a risk for PTSD in addition to other negative health problems is a major public health concern. Primary prevention strategies should be in place to detect sexual assault victims and prevent the occurrence of PTSD

A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition

Speech is a natural, convenient and rapid means of human communication. The abil ity to respond to spoken language is of special importance in computer application wherein the user cannot use his/her limbs in a proper way, and may be useful in office automation systems. It can help in developing control systems for many applications such as in telephone assistance systems. Rough sets theory represents a mathematical approach to vagueness and uncertainty. Data analysis, data reduction, approxi mate classification, machine learning, and discovery of pattern in data are functions performed by a rough sets analysis. It was one of the first non-statistical methodologies of data analysis. It extends classical set theory by incorporating into the set model the notion of classification as indiscernibility relation.In previous work rough sets approach application to the field of speech recognition was limited to the pattern matching stage. That is, to use training speech patterns to generate classification rules that can be used later to classify input words patterns. In this thesis rough sets approach was used in the preprocessing stages, namely in the vector quantization operation in which feature vectors are quantized or classified to a finite set of codebook classes. Classification rules were generated from training feature vectors set, and a modified form of the standard voter classification algorithm, that use the rough sets generated rules, was applied. A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. In addition to the Arabic speech data that used in the original experiments, for both speaker dependant and speaker independent tests, more verification experiments were conducted using the TI20 speech data. The rough sets vector quantization model proved its usefulness in the speech recognition framework, however it can be extended to different applications that involve large amounts of data such as speaker verification

Ensuring Access to Medicines in Qatar

Summary & Conclusion: * Good healthcare system should ensure coverage, continuity, accessibility, quality and accountability during crisis as it was normal situation. * An efficient actions & crisis management with quick solution for long term strategic effect to avoid similar condition in future. *Encouraging and supporting local manufacturing plants to participate in ensuring medication security in the state of Qatar

Assessment of poverty among the employees of the University of Gezira: Empirical analysis, 2006

This study aimed at estimating an income poverty line based on calorie requirements along with the different poverty indices, by applying the estimated poverty line to income distribution data for people working at the University of Gezira.  To estimate the poverty line, Annand and Nur (1988) methodology was followed using three selected consumption baskets to represent different consumption habits in Sudan. Applying the prices of 2006 on the consumption items of the selected baskets, the average cost of these baskets was obtained representing a minimum cash requirement for food consumption. Multiplying the above minimum cash requirement for food consumption by a conversion factor of 2, we obtained the poverty line for the year 2006. To estimate the poverty indices, the traditional measures of poverty such as the headcount, depth of poverty, severity of poverty, Gini Coefficient and Sen’s measure were applied. Results showed that the household income poverty line for the year 2006 was equal to SD 74202.48 (approximately equivalent to 371)  per month with a household size of 6.6. The head count index using expenditure and income approaches was equal to 48% and 54%, respectively. Moreover, results showed that the depth and severity of poverty using expenditure approach were equal to 17% and 8%, respectively, however, the depth and severity of poverty using income approach were equal to 24% and 13%, respectively. Regarding Sen's measure and Gini coefficient, results indicated that income was unequally distributed among the employees of the University of Gezira. In addition, results showed that the poverty indices using expenditure approach were below the poverty indices using income approach. This result may be attributed to the fact that people usually underestimate their income levels, hence, expenditure reflects the standard of living better than income.  تهدف هذه الدراسة إلى تقدير خط الفقر على أساس الاحتياجات من السعرات الحرارية وتقدير مختلف مؤشرات الفقر وذلك من خلال تطبيق خط الفقر المقدر على توزيع الدخل لبيانات العاملين في جامعة الجزيرة. لتقدير خط الفقر اتبعت الدراسة المنهجية التي استخدمها (1988) Annand and Nur وذلك باستخدام ثلاث سلات لتمثيل مختلف العادات الاستهلاكية في السودان. بتطبيق أسعار (2006) على سلات الغذاء التي تم اختيارها تحصلنا على التكلفة المتوسطة والتي تمثل الحد الأدنى للمتطلبات النقدية لاستهلاك الغذاء. تم تقدير خط الفقر بضرب الحد الأدنى للمتطلبات النقدية لاستهلاك الغذاء بمعامل التحويل 2 . بتطبيق خط الفقر على بيانات توزيع الدخل للعاملين بجامعة الجزيرة تحصلنا على تقديرات لمؤشرات الفقر التقليدية مثل مؤشر تعداد الرؤوس، مؤشر فجوة الفقر (عمق الفقر) ، مؤشر حدة الفقر ، معامل جيني ومؤشر سن . وضحت النتائج أن خط الفقر يساوي 74202.48 دينار شهرياً ويعادل (371) في الشهر عام 2006م للأسرة التي متوسط عدد أفرادها يساوي 6.6 . أوضحت النتائج ان مؤشر تعداد الرؤوس بالنسبة للعاملين بجامعة الجزيرة يساوي 48% و 54% باستخدام منهج الإنفاق والدخل على التوالي وأن مؤشر عمق الفقر وحدة الفقر باستخدام منهج الدخل يساويان 17% و 8% على التوالي. في حالة استخدام منهج الإنفاق وضح أن عمق وحدة الفقر يساويان 24% و 13% على التوالي. باستخدام مؤشر سن ومعامل جيني وضح أن توزيع الدخل في صفوف العاملين بجامعة الجزيرة غير عادل. كذلك أوضحت النتائج أن مؤشرات الفقر باستخدام منهج الإنفاق أقل من مؤشرات الفقر باستخدام منهج الدخل ويمكن أن تعزى هذه النتيجة إلى أن الإنفاق يعكس مستوى المعيشة بصورة أفضل من الدخل. &nbsp

Adaptive Coding, Modulation and Filtering of Radar Signals

In this chapter, some of the issues associated with radar signal processing are highlighted, with an emphasis on adaptability. Signal processing operations are carried by systems in order to enhance the received signal or to clarify its content of information. Received radar signal should be subjected to processing prior to the extraction of useful target information out of it so as to emphasize desired signal among other accompanying signals. Processing of the radio frequency (RF) signal is generally done in an analogue manner, while digital signal processing (DSP) became dominant in the intermediate-frequency (IF) and low-frequency portions of the system. Since the detectability and immunity against interference and clutter strongly depend on the waveform used, it will be more efficient to apply a diverse waveform instead of confinement to an invariable waveform of a fixed code and pattern. Adaptive coding, modulation and filtering of radar signals provide high degree of diversity as well as flexibility and agility for signal processors versus changing sources of interference and environmentally dependent reflectors. Constant false alarm rate (CFAR) is an adaptive processing technique that reduces noise and clutter. Different methods are applied in CFAR technique to adaptively cope with varying clutter density and distribution

Effect of sodium chloride concentration on the functional properties of selectec Legume flours

Providing safe, nutritious, and wholesome food for poor and undernourished populations has been a major challenge for developing countries. This has led to the necessity of assembling complete food composition tables, yielding information about the traditional foods and on the functional properties of the plant foods that are consumed regularly in the developing countries. Sodium Chloride (NaCl) is the common salt used at household and industry levels to improve palatability of processed foods. Therefore, the main aim of the present study was to investigate the influence of different concentrations of NaCl on the functional properties of selected legume flours. The effect of increasing concentration of NaCl on the protein solubility, emulsifying and foaming properties of white bean, pigeon pea, cowpea and hyacinth bean were studied. The results revealed that the protein solubility of pigeon pea, cowpea and white bean flours significantly increased by increasing salt concentration and reached a maximum at 0.4 M NaCl (for pigeon pea and cowpea flours) and 0.6 M for white bean flour and then gradually decreased at higher salt concentration. The protein solubility profile of hyacinth bean fluctuated with the salt concentration, with the highest solubility at 0.6 M NaCl and lowest solubility at 0.4M NaCl. With the exception of white bean, the maximum emulsifying activity of all selected legume flours was found at 0.4 M NaCl whereas that of white bean was found at 0.2 M NaCl. Generally, with increasing salt concentration, the emulsifying activity slightly decreased for the legume flours, except for cowpea which fluctuated. Addition of NaCl significantly decreased the emulsion stability and foaming capacity of the four of selected legume with the maximum improvement being observed at 0.2 M NaCl, and then decreasing gradually at higher salt concentration. Significant improvement of foaming stability was observed when salt concentration increased. Based on the results of the present study the selected legume flour demonstrated good functional properties following the addition of NaCl, which makes these legume flours potential ingredients for application in salt containing foods.Keywords: functional properties, Legumes, Protein solubilityAfrican Journal of Food, Agriculture, Nutrition and Development, Volume 12 No.