National Adaptation Programme of Action on Climate Change - 2008 - 2012

The archipelago of Cape Verde is made up of ten islands and nine islets and is located between latitudes 14º 28' N and 17º 12' N and longitudes 22º 40' W and 25º 22' W. It is located approximately 500 km from the Senegal coast in West Africa (Figure 1). The islands are divided into two groups: Windward and Leeward. The Windward group is composed of the islands of Santo Antão, São Vicente, Santa Luzia, São Nicolau, Sal and Boavista; and the Leeward group is composed of the islands Maio, Santiago, Fogo and Brava. The archipelago has a total land surface of 4,033 km2 and an Economic Exclusive Zone (ZEE) that extends for approximately 734,000 km2. In general, the relief is very steep, culminating with high elevations (e.g. 2,829 m on Fogo and 1,979 m on Santo Antão). The surface area, geophysical configuration and geology vary greatly from one island to the next. Cape Verde, due to its geomorphology, has a dense and complex hydrographical network. However, there are no permanent water courses and temporary water courses run only during the rainy season. These temporary water courses drain quickly towards the main watersheds, where, unless captured by artificial means, continue rapidly to lower areas and to the sea. This applies equally to the flatter islands. The largest watershed is Rabil with an area of 199.2 km2. The watershed areas on other islands extend over less than 70 km2. Cape Verde is both a least developed country (LDC) and a small island development state (SIDS). In 2002, the population of Cape Verde was estimated at approximately 451,000, of whom 52% were women and 48% men. The population was growing at an average 2.4% per year, and the urban population was estimated at 53.7 %. Over the past 15 years, the Government has implemented a successful development strategy, leading to a sustained economic growth anchored on development of the private sector and the integration of Cape Verde into the world economy. During this period, the tertiary sector has become increasingly important, with strong growth in the tourism, transport, banking and trade sectors. Overall, the quality of life indicators show substantial improvements in almost all areas: housing conditions, access to drinking water and sanitation, use of modern energy in both lighting and cooking, access to health services and education. Despite these overall socio-economic successes, the primary sector has witnessed limited progress. Weak performance in the primary sector has had a severe negative impact on the incomes and poverty risks faced by rural workers1. Moreover, relative poverty has increased significantly during the past decade. The poverty profile shows that: (i) extreme poverty is mostly found in rural areas, although it has also increased in urban areas; (ii) poverty is more likely to occur when the head of the household is a woman; (iii) poverty increases with family size; (iv) education significantly affects poverty; (v) the predominantly agricultural islands of Santo Antão and Fogo have the highest poverty rates; (vi) unemployment affects the poor more than the nonpoor; (vii) agriculture and fisheries workers are more likely to be poor than those in other sectors. Therefore, the fight against poverty and income inequalities remains one of the greatest challenges for Cape Verde authorities. The various governments of Cape Verde over the last decade have demonstrated a commitment to improving governance, notably by encouraging a democratic culture that guarantees stability and democratic changes without conflicts. This democratic governance offers a space for a wider participation of citizens in public management and consolidates social cohesion. However, there are some remaining challenges related to democratic governance and the gains must be systematically monitored. Finally, it is worth emphasizing that the country’s insularity has stimulated a movement to decentralized governance, although social inequalities and contrasts from one island to the next constitute, at the same time, challenges and opportunities.

Iowa Communications Network Performance Plan, FY 2009

Agency Performance Plan, Iowa Communications Network

On bounds for network revenue management

The Network Revenue Management problem can be formulated as a stochastic dynamic programming problem (DP or the\optimal" solution V *) whose exact solution is computationally intractable. Consequently, a number of heuristics have been proposed in the literature, the most popular of which are the deterministic linear programming (DLP) model, and a simulation based method, the randomized linear programming (RLP) model. Both methods give upper bounds on the optimal solution value (DLP and PHLP respectively). These bounds are used to provide control values that can be used in practice to make accept/deny decisions for booking requests. Recently Adelman [1] and Topaloglu [18] have proposed alternate upper bounds, the affine relaxation (AR) bound and the Lagrangian relaxation (LR) bound respectively, and showed that their bounds are tighter than the DLP bound. Tight bounds are of great interest as it appears from empirical studies and practical experience that models that give tighter bounds also lead to better controls (better in the sense that they lead to more revenue). In this paper we give tightened versions of three bounds, calling themsAR (strong Affine Relaxation), sLR (strong Lagrangian Relaxation) and sPHLP (strong Perfect Hindsight LP), and show relations between them. Speciffically, we show that the sPHLP bound is tighter than sLR bound and sAR bound is tighter than the LR bound. The techniques for deriving the sLR and sPHLP bounds can potentially be applied to other instances of weakly-coupled dynamic programming.

European research funding and regional technological capabilities: Network composition analysis

We use network and correspondence analysis to describe the compositionof the research networks in the European BRITE--EURAM program. Our mainfinding is that 27\% of the participants in this program fall into one oftwo sets of highly ``interconnected'' institutions --one centered aroundlarge firms (with smaller firms and research centers providing specializedservices), and the other around universities--. Moreover, these ``hubs''are composed largely of institutions coming from the technologically mostadvanced regions of Europe. This is suggestive of the difficulties of attainingEuropean ``cohesion'', as technically advanced institutions naturally linkwith partners of similar technological capabilities.

An enhanced concave program relaxation for choice network revenue management

The network choice revenue management problem models customers as choosing from an offer-set, andthe firm decides the best subset to offer at any given moment to maximize expected revenue. The resultingdynamic program for the firm is intractable and approximated by a deterministic linear programcalled the CDLP which has an exponential number of columns. However, under the choice-set paradigmwhen the segment consideration sets overlap, the CDLP is difficult to solve. Column generation has beenproposed but finding an entering column has been shown to be NP-hard. In this paper, starting with aconcave program formulation based on segment-level consideration sets called SDCP, we add a class ofconstraints called product constraints, that project onto subsets of intersections. In addition we proposea natural direct tightening of the SDCP called ?SDCP, and compare the performance of both methodson the benchmark data sets in the literature. Both the product constraints and the ?SDCP method arevery simple and easy to implement and are applicable to the case of overlapping segment considerationsets. In our computational testing on the benchmark data sets in the literature, SDCP with productconstraints achieves the CDLP value at a fraction of the CPU time taken by column generation and webelieve is a very promising approach for quickly approximating CDLP when segment consideration setsoverlap and the consideration sets themselves are relatively small.

Iowa Communications Network, Strategic Plan, 2007

This report outlines the strategic plan for Iowa Communications Network, goals and mission.

Fiscal Year 2008 Annual Report of the Iowa Communications Network, December 2008

This is the Annual Report for Fiscal Year 2007 (July 1, 2007-June 30, 2008) for the Iowa Communications Network.

Iowa Department of Transportation Fiscal Year 2008 Report of Savings by Using Video Conferencing Through Iowa Communications Network to the Iowa General Assembly Pursuant to Iowa Code § II 84 Acts and Joint Resolutions Enacted at the 1994 Regular Session of the 75th General Assembly of the State of Iowa Iowa Code §8D.10 Report of Savings by State Agencies

Iowa Code § 8D.10 requires certain state agencies prepare an annual report to the General Assembly certifying the identified savings associated with that state agency’s use of the Iowa Communications Network (ICN). This report covers estimated cost savings related to video conferencing via ICN for the Iowa Department of Transportation (DOT). In FY 2008, the DOT did not conduct any sessions utilizing ICN’s video conferencing system. Therefore, no cost savings were calculated for this report.

Validation procedures in radiological diagnostic models. Neural network and logistic regression

The objective of this paper is to compare the performance of twopredictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validation methods did not reveal statistically significant differences between LR and NN rules. The neural network classifier performs better than the one based on logistic regression. This advantage is well detected by three-fold cross-validation, but remains unnoticed when leave-one-out or bootstrap algorithms are used.

Utilização da Virtual Private Network Caso da Universidade Jean Piaget de Cabo Verde

O trabalho científico realizado no âmbito dos regulamentos dos cursos de graduação para a obtenção de grau de licenciatura na Universidade Jean Piaget de Cabo Verde, pretende analisar a utilização da VPN, mais concretamente na Universidade Jean Piaget de Cabo Verde. Durante a elaboração desse trabalho será feito uma breve introdução sobre redes de computadores, sobre segurança na rede, um enquadramento teórico sobre VPN, bem como a sua contextualização num ambiente organizacional, mostrando as várias vantagens do seu uso, custo e beneficio e por fim o caso prático na Universidade Jean Piaget.

Red meat and cancer risk in a network of case-control studies focusing on cooking practices.

BACKGROUND: Consumption of red meat has been related to increased risk of several cancers. Cooking methods could modify the magnitude of this association, as production of chemicals depends on the temperature and duration of cooking. METHODS: We analyzed data from a network of case-control studies conducted in Italy and Switzerland between 1991 and 2009. The studies included 1465 oral and pharyngeal, 198 nasopharyngeal, 851 laryngeal, 505 esophageal, 230 stomach, 1463 colon, 927 rectal, 326 pancreatic, 3034 breast, 454 endometrial, 1031 ovarian, 1294 prostate and 767 renal cancer cases. Controls included 11 656 patients admitted for acute, non-neoplastic conditions. Odds ratios (ORs) and confidence intervals (CIs) were estimated by multiple logistic regression models, adjusted for known confounding factors. RESULTS: Daily intake of red meat was significantly associated with the risk of cancer of the oral cavity and pharynx (OR for increase of 50 g/day = 1.38; 95% CI: 1.26-1.52), nasopharynx (OR = 1.29; 95% CI: 1.04-1.60), larynx (OR = 1.46; 95% CI: 1.30-1.64), esophagus (OR = 1.46; 95% CI: 1.23-1.72), colon (OR = 1.17; 95% CI: 1.08-1.26), rectum (OR = 1.22; 95% CI:1.11-1.33), pancreas (OR = 1.51; 95% CI: 1.25-1.82), breast (OR = 1.12; 95% CI: 1.04-1.19), endometrium (OR = 1.30; 95% CI: 1.10-1.55) and ovary (OR = 1.29; 95% CI: 1.16-1.43). Fried meat was associated with a higher risk of cancer of oral cavity and pharynx (OR = 2.80; 95% CI: 2.02-3.89) and esophagus (OR = 4.52; 95% CI: 2.50-8.18). Risk of prostate cancer increased for meat cooked by roasting/grilling (OR = 1.31; 95% CI: 1.12-1.54). No heterogeneity according to cooking methods emerged for other cancers. Nonetheless, significant associations with boiled/stewed meat also emerged for cancer of the nasopharynx (OR = 1.97; 95% CI: 1.30-3.00) and stomach (OR = 1.86; 95% CI: 1.20-2.87). CONCLUSIONS: Our analysis confirmed red meat consumption as a risk factor for several cancer sites, with a limited impact of cooking methods. These findings, thus, call for a limitation of its consumption in populations of Western countries.

Outcome and patterns of failure in testicular lymphoma: a multicenter Rare Cancer Network study.

PURPOSE: To assess the outcome and patterns of failure in patients with testicular lymphoma treated by chemotherapy (CT) and/or radiation therapy (RT). METHODS AND MATERIALS: Data from a series of 36 adult patients with Ann Arbor Stage I (n = 21), II (n = 9), III (n = 3), or IV (n = 3) primary testicular lymphoma, consecutively treated between 1980 and 1999, were collected in a retrospective multicenter study by the Rare Cancer Network. Median age was 64 years (range: 21-91 years). Full staging workup (chest X-ray, testicular ultrasound, abdominal ultrasound, and/or thoracoabdominal computer tomography, bone marrow assessment, full blood count, lactate dehydrogenase, and cerebrospinal fluid evaluation) was completed in 18 (50%) patients. All but one patient underwent orchidectomy, and spermatic cord infiltration was found in 9 patients. Most patients (n = 29) had CT, consisting in most cases of cyclophosphamide, doxorubicin, vincristine, and prednisolone (CHOP) with (n = 17) or without intrathecal CT. External RT was delivered to scrotum alone (n = 12) or testicular, iliac, and para-aortic regions (n = 8). The median RT dose was 31 Gy (range: 20-44 Gy) in a median of 17 fractions (10-24), using a median of 1.8 Gy (range: 1.5-2.5 Gy) per fraction. The median follow-up period was 42 months (range: 6-138 months). RESULTS: After a median period of 11 months (range: 1-76 months), 14 patients presented lymphoma progression, mostly in the central nervous system (CNS) (n = 8). Among the 17 patients who received intrathecal CT, 4 had a CNS relapse (p = NS). No testicular, iliac, or para-aortic relapse was observed in patients receiving RT to these regions. The 5-year overall, lymphoma-specific, and disease-free survival was 47%, 66%, and 43%, respectively. In univariate analyses, statistically significant factors favorably influencing the outcome were early-stage and combined modality treatment. Neither RT technique nor total dose influenced the outcome. Multivariate analysis revealed that the most favorable independent factors predicting the outcome were younger age, early-stage disease, and combined modality treatment. CONCLUSIONS: In this multicenter retrospective study, CNS was found to be the principal site of relapse, and no extra-CNS lymphoma progression was observed in the irradiated volumes. More effective CNS prophylaxis, including combined modalities, should be prospectively explored in this uncommon site of extranodal lymphoma.

Iowa Influenza Surveillance Network Final Report 2007-2008

The Iowa Influenza Surveillance Network (IISN) was formally established in 2004, though surveillance has been conducted at the Iowa Department of Public Health (IDPH) for more than ten years. The IISN is comprised of four primary surveillance systems- sentinel health care providers, hospital-based, laboratory-based, and school-based. Sentinel health care providers are part of the U.S. Influenza Sentinel Provider Surveillance System. All systems, except certain sentinel sites, report October-March. Schools and long-term care facilities report data weekly into a Web-based reporting system. Schools report the number of students absent due to illness and the total enrolled. Long-term care facilities report cases of influenza and vaccination status of each case. Both passively report outbreaks of illness, including influenza, to IDPH.

Iowa Influenza Surveillance Network Final Report 2006-2008

The Iowa Influenza Surveillance Network (IISN) tracks the overall activity, age groups impacted, outbreaks, type and strain, and severity of seasonal influenza. In the 2006-2007 season the network had more than 90 reporting sites that included physicians, clinics, hospitals, schools and long term care facilities (Appendix A). Other non-network reporters who contributed influenza data included medical clinics, hospitals, laboratories, local public health departments and neighboring state health departments. 010203040506070424548495051521234567891011121314MMWR weekNumber of cases2006-20072005-2006 The 2006-2007 influenza season in Iowa began earlier than any previously recorded data indicates, however, the season’s peak occurred much later in the season. In addition to early cases, this season was also unusual in that all three anticipated strains (AH1N1, AH3N2, and B) were reported by the first of December (Appendix B). The first laboratory-confirmed case in the 2005-2006 season was identified December 5, 2005; the first case for the 2006-2007 season was on November 2, 2006. The predominant strain for 2005-2006 was influenza AH3, but for 2006-2007 both influenza AH1 and B dominated influenza infections. However improvements in influenza specimen submission to the University Hygienic Laboratory may have also played a role in early detection and overall case detection. In summary, all influenza activity indicators show a peak between the MMWR weeks 5 and 9 (i.e. February 14- March 4). Children from five years to eight years of age were impacted more than other age groups. There were few influenza hospitalizations and fatalities in all age groups.

Surveillance Network Overview, 2007-2008

Seasonal influenza surveillance is conducted October through March every year. The overall goal of surveillance is to be able to characterize the impact of seasonal influenza to create and design interventions that might reduce the burden of disease.