Each year in the United States over 1,000 fatalities occur as a result of collisions with utility poles. In addition, approximately 40% of utility pole crashes result in a non-fatal injury. Moreover, with over 88 million utility poles lining United States highways, it is not feasible to immediately remedy all poles that are potentially unsafe. Utility poles which pose a danger to motorists can, however, be identified and addressed over time in a structured, methodical manner. The goal of this project was to develop a method to identify and prioritize high risk utility poles that are good candidates for remediation as well as develop a standard operating procedure for the relocation of existing utility poles and placement of future utility poles along Massachusetts highways. This research found that the lateral offset, annual average daily traffic and density of the utility poles are major risk factors. Road geometry, however, also impacts the risk. Basic corrective measures such as delineation, placing poles as far from the edge of road as achievable, as well as placing poles a safe distance behind horizontal barriers are all suggested solutions.

Self-rated health (SRH) consists of a single question wherein individuals are asked to evaluate their general health status on a 5-point scale. This study investigated the relationship between SRH and depression/anxiety, with the purpose of getting a better understanding of how the two disorders are related to perceived general health, and to examine the possibility of using SRH as clinical tool for identifying individuals with increased risk for onset and persistent states of depression and anxiety. The study used cross-sectional and longitudinal data from the Västerbotten Environmental Health Study, a large questionnaire-based population study in northern Sweden. 2336 individuals participated at baseline (T1) and 3-year follow-up (T2). The Hospital Anxiety and Depression Scale was used to measure symptoms of depression and anxiety. The results showed that those with poor SRH rated more severe symptoms of depression and anxiety, than those with good SRH. Those with poor SRH at T1 had more than twofold increased risk of falling into the depression and anxiety case groups at T2. Specifically, they more often experienced onset of symptoms at T2 as well as symptoms that persisted across the two occasions. The results corresponds in large with those from previous studies and supports the utility of SRH as a clinical tool, with the reservation that it may not be strong enough predictor on its own.

The purpose of this study was to determine whether the Minnesota Multiphasic Personality Inventory (MMPI) could be used to discriminate between Vietnam veterans with Post-Traumatic Stress Disorder and those with other mental disorders. Scores on the 13 validity and clinical scales of the MMPI were used as predictor variables in two discriminant analyses. The first of these was performed in replication of studies in which cases of substance-abuse disorder were eliminated from the non-PTSD comparison group. Substance- abuse cases were included in the second discrimination. The results indicated that while the MMPI can be used to discriminate PTSD from non-PTSD veterans, this discrimination is weakened by the presence of cases with substance abuse disorders in the non-PTSD comparison group.

El virus de la hepatitis C (VHC) constituye la causa más prevalente de hepatitis crónica en los países desarrollados. El principal fármaco en el tratamiento de la hepatitis crónica C es el interferón. La monitorización de la respuesta a la terapia se basa en la evolución de los niveles de ALT, aunque más recientemente el desarrollo de técnicas de detección molecular del ARN del VHC ha permitido establecer la dinámica viral de la respuesta al tratamiento con interferón. En 1998 fueron publicados varios estudios que demostraron que la terapia combinada de interferón más ribavirina era más eficaz que el interferón. La dinámica viral de la respuesta a la terapia combinada no ha sido establecida. El objetivo de esta tesis es la valoración de la utilidad de la determinación del ARN de VHC durante la terapia antiviral como predictor de respuesta mantenida. Para conseguir este objetivo hemos llevado a cabo tres estudios.A) Para la evaluación de unas técnicas de RT/PCR de segunda generación en sus versiones cualitativa (Amplicor v2.0) y cuantitativa (Monitor v2.0) utilizamos tres tipos de muestras: donantes de sangre con anticuerpos Anti-VHC pero ARN no detectable por una técnica cualitativa de primera generación (n=132), pacientes con hepatitis crónica C (n=326) y diluciones de un estándar de VHC de concentración conocida. El límite inferior de detección fue de 100 copias de estándar del VHC /mL para Amplicor v2.0 y de 1000 copias/mL para Amplicor v1.0. De los 132 donantes de sangre con serología anti-VHC positiva y ARN del VHC indetectable por Amplicor v1.0, en 6 (5%) casos se detectó ARN del VHC utilizando Amplicor v2.0. La carga viral según Monitor v2.0 fue mayor que la obtenida mediante Monitor v1.0 para todos los genotipos. No hubo diferencias entre las cargas virales medias de los genotipos 1, 2 y 3 al utilizar Monitor v2.0, mientras que la carga viral del genotipo 4 fue inferior al resto. Se ha descrito que Monitor 1.0 subestima la carga viral en los genotipos 2 y 3 con respecto al genotipo 1. En cambio Monitor v2.0 cuantifica por igual los genotipos 1, 2 y 3. Además ha reducido la diferencia entre el genotipo 4 y el resto de 1.5 log a 0.5 log. En conjunto las técnicas de segunda generación son más sensibles en un logaritmo y menos genotipo dependientes que las de primer generación. B) Fueron incluidos 184 pacientes afectos de hepatitis la crónica C que habían seguido tratamiento antiviral: 62 pacientes con interferón y 122 pacientes con interferón más ribavirina. En ambos grupos ALT y ARN de VHC se determinaron mensualmente. La respuesta mantenida ocurrió en 13 (22%) pacientes en el grupo de interferón y 21 pacientes (17%) en el grupo de terapia combinada. La persistencia de viremia cualitativa tras un mes de interferón monoterapia y tras cinco mes de terapia combinada eran los predictores más potentes de no respuesta (valor predictivo negativo de 100% y 99%, respectivamente). Las variables asociadas con la respuesta mantenida eran HCV genotipo (P=0.06), carga viral < 5.1 log/ml (P=0.005) y ARN VHC no detectable tras un mes (P<0.0001) en el grupo de interferón monoterapia; sexo femenino (P=0.04), genotipo (P=0.03), la carga viral < 5.5 log/ml (P=0.01), ALT normal (P=0.001) y descenso en la carga viral >1.2 log/ml después de 2 meses de interferón monoterapia (P<0.001) y viremia negativa tras cinco meses de terapia combinada (P<0.0001) en el grupo de tratamiento combinado. La evaluación cualitativa de ARN de VHC durante el tratamiento es el predictor más potente de respuesta mantenida de la hepatitis crónica C.C) Se incluyeron 30 pacientes que habían seguido tratamiento con interferón-"2b más ribavirina durante 12 meses. Seis meses tras la retirada de la terapia 10 pacientes presentaron una respuesta mantenida y los otros 20 fueron considerados no respondedores. Se determinó la carga viral basal, al mes, dos meses y tres meses de tratamiento mediante una RT/PCR cuantitativa calibrada en unidades internacionales (Amplicor HCV Monitor v2.0). La carga viral no mostró variaciones significativas en los pacientes no respondedores durante los primeros meses de terapia combinada (6.3±0.7 versus 6±0.9, 5,7±1 and 5,9±0.9 log UI/mL al inicio y tras uno, dos y tres meses, respectivamente). Sin embargo la carga viral de los pacientes que presentaron respuesta mantenida disminuyó progresivamente en cada muestra mensual, llegando a ser indetectable al tercer mes en todos los pacientes. Se construyeron curvas COR referentes a la carga viral en los meses 1, 2 y 3 para predicción de respuesta mantenida. Fueron detectados los siguientes picos de sensibilidad: 5 log/mL en el mes 1, 4 log/mL en el mes 2 y 3 log/mL en el mes 3. La carga viral durante los tres primeros meses de tratamiento con interferón y ribavirina es el predictor de respuesta más potente. / The hepatitis C virus (HCV), a single-stranded RNA virus, is the etiologic agent in most cases of post-transfusion and sporadic non-A, non-B hepatitis worldwide. This infection has a high rate of persistence and progression to chronic liver disease. HCV infection is a leading cause of end-stage liver disease requiring liver transplantation, and is also associated with hepatocellular carcinoma. To evaluate the utility of monitoring RNA HCV levels during antiviral therapy as predictor of long-term response, we have done three studies.A) HCV RNA qualitative and quantitative second generation assays (Amplicor HCV v2.0 and Amplicor HCV Monitor v2.0, respectively) have been evaluated by testing serum samples from 132 blood donors anti-HCV positive HCV RNA negative by first generation qualitative assay and 326 viremic patients. An HCV RNA transcript was synthesized and ten-fold dilutions were used to assess sensitivity. Second generation assays were one log more sensitive than their respective first generation tests (102 copies/ml vs. 103 for the qualitative tests; 103 copies/ml vs. 104 for the quantitative tests). From the 132 anti-HCV positive RNA negative subjects, 6 (5%) were positive by Amplicor v2.0. Quantification figures by Monitor v2.0 were similar in genotypes 1, 2 and 3, whereas Monitor 1.0 values were higher in genotype 1 than in genotype 2 or 3. In 114 patients, branched-DNA v2.0 obtained higher values than Monitor v2.0 and Monitor v1.0 (6.6+0.6 log RNA copies/ml, 6.4+0.6, and 5.3+0.7, respectively, P<0.001). HCV RNA qualitative and quantitative second generation assays are more sensitive and genotype independent than first generation assays.B) One hundred and eighty-four patients with chronic hepatitis C treated with interferon alone (62 patients) or interferon plus ribavirin (122 patients) for 12 months were studied. In both groups aminotransferase and HCV RNA were tested weekly for one month, biweekly for two months and monthly thereafter. Sustained response ocurred in 13 (22%) and 21 patients (17%) in the interferon and combination group, respectively. Persistence of viremia at one month of interferon monotherapy and at five month of combination therapy were the strongest predictors of non-response (predictive value of 100% and 99%, respectively; 95% confidence interval 93.2-99.9%). Independent variables associated with sustained response were HCV genotype (P=0.06), viral load £ 5.1 logs/ml (P=0.005) and negative HCV RNA at one month (P<0.0001) in the interferon group. And female sex (P=0.04), genotype (P=0.03), viral load £ 5.5 logs/ml (P=0.01), normal ALT (P=0.001) and decline in viral load *1.2 logs/ml after 2 months of interferon monotherapy f(P<0.001) and negative viremia at five months of ribavirin onset (P<0.0001) in the combination group. Qualitative assessment of HCV RNA during treatment is the strongest predictor of sustained response during interferon or combination therapy for chronic hepatitis C.C) The dynamics of hepatitis C virus RNA during treatment with interferon plus ribavirin are not well known. We evaluated the predictive value of HCV RNA early decline during combination therapy. Thirty chronic hepatitis C patients that had followed interferon plus ribavirin for twelve months were included. Serum HCV RNA was measured in sera obtained at baseline and at 4, 8 and 12 weeks after initiation of treatment using a second generation commercially available quantitative RT/PCR assay. After six months of postherapy follow-up 10 (33%) patients were considered sustained responders and 20 (66%) non responders. While in non responders HCV RNA levels remained stable during the first three months of treatment (6.3±0.7 versus 6±0.9, 5,7±1 and 5,9±0.9 log10 HCV RNA IU/mL at baseline and at weeks 4, 8 and 12 respectively) sustained responders showed significant declines in viral load at each subsequent sample (rHCV RNA of 3.5±1.6 log10 IU/mL, 5.1±1.7, and 6±0.9 at weeks 4,8 and 12 respectively). At week 12 all sustained responders had HCV RNA levels below 600 IU/mL, as compared to only one of 20 non responders (P<0.001). ROC curves of HCV RNA level for sustained response prediction identified sensitivity peaks (5 log at 4 weeks, 4 log at 8 weeks and 3 log at 12 weeks) with 100% negative predictive value. Our results suggest that HCV RNA levels during the first three months of combination therapy for chronic hepatitis C are the strongest predictors of response.

No description available.

Thesis advisor: Samuel Richardson / HbA1c levels are the most frequently used test for diagnosis and prognosis of diabetes mellitus. Recent studies have shown the biases this test has in particular cohorts, that was not noted when it was originally accepted by the American Diabetes Association in 2008. This study examined how these biases affect HbA1c’s ability as a predictor for complications that arise due to diabetes in specific cohorts, those of ethnicity, age, weight, and other patient attributes, compared to other established diabetes prognosis tests. We discovered that both glucose and HbA1c share similar biases as predictors for particular cohorts (the high glucose, high BMI, Asian, African, and Hispanic descent cohorts), HbA1c works better as a predictor when it is combined with the results of a glucose test and more characteristics of the patient compared to a HbA1c test alone with fewer variables, and glucose and HbA1c are better predictors for different diseases, respectively, that may arise due to diabetes mellitus. / Thesis (BA) — Boston College, 2020. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: Departmental Honors. / Discipline: Economics.

The prevalence of side-channel attacks exploiting hardware vulnerabilities leads to the exfil- tration of secretive data such as secret keys, which poses a significant threat to the security of modern processors. The RISC-V BOOM core is an open-source modern processor design widely utilized in research and industry. It enables experimentation with microarchitec- tures and memory hierarchies for optimized performance in various workloads. The RISC-V BOOM core finds application in the IoT and Embedded systems sector, where addressing side-channel attacks becomes crucial due to the significant emphasis on security. While prior studies on BOOM mainly focus on the side channel in the memory hierarchy such as caches or physical attacks such as power side channel. Recently, the front-end of microprocessors, which is responsible for fetching and decoding instructions, is found to be another potential source of side-channel attacks on Intel Processors. In this study, I present four timing-based side-channel attacks that leverage components in the front-end of BOOM. I tested the effectiveness of the attacks using a simulator and Xilinx VCU118 FPGA board. Finally, I provided possible mitigation techniques for these types of attacks to improve the overall security of modern processors. Our findings underscore the importance of identifying and addressing vulnerabilities in the front-end of modern pro- cessors, such as the BOOM core, to mitigate the risk of side-channel attacks and enhance system security. / Master of Science / In today's digital landscape, the security of modern processors is threatened by the increasing prevalence of side-channel attacks that exploit hardware vulnerabilities. These attacks are a type of security threat that allows attackers to extract sensitive information from computer systems by analyzing the physical behavior. The risk of such attacks is further amplified when multiple users or applications share the same hardware resources. Attackers can ex- ploit the interactions and dependencies among shared resources to gather information and compromise the integrity and confidentiality of critical data. The RISC-V BOOM core, a widely utilized modern processor design, is not immune to these side-channel attacks. This issue demands urgent attention, especially considering its deploy- ment in data-sensitive domains such as IoT and embedded systems. Previous studies have focused on side-channel vulnerabilities in other areas of BOOM, ne- glecting the front-end. However, the front-end, responsible for processing initial information, has recently emerged as another potential target for side-channel attacks. To address this, I conducted a study on the vulnerability of the RISC-V BOOM core's front-end. By conduct- ing tests using both a software-based simulator and a physical board, I uncovered potential security threats and discussed potential techniques to mitigate these risks, thereby enhanc- ing the overall security of modern processors. These findings underscore the significance of addressing vulnerabilities in the front-end of processors to prevent side-channel attacks and safeguard against potential malicious activities.

No description available.

Economic justification for rehabilitative services has resulted in the need for outcome based research which could quantify success or failure in individual patients and formulate baseline variables which could predict outcomes. The purpose of this study is to investigate the utilization of baseline clinical, exercise test, and psychosocial variables to predict clinically relevant changes in exercise tolerance of cardiac patients who participated in early outpatient cardiac rehabilitation. Clinical records were analyzed retrospectively to obtain clinical, psychosocial and exercise test data for 94 patients referred to an early outpatient cardiac rehabilitation program at a large urban hospital in the Southeast US. All patients participated in supervised exercise training 3d/wk for 2-3 months. A standardized training outcome score STO) was devised to evaluate training effect by tabulating changes in patients predicted VO2, body weight and exercising heart rates after 8-12 weeks of exercise based cardiac rehabilitation. STO = Predicted VO2 change + BW change- HR change. The Multi-Factorial Analysis was applied to derive coefficients in the STO formula so that the STO scores reflected the independent effects of BW, HR and Predicted V02 changes on training outcome. Patients were classified into one of three possible outcome categories based on STO scores, i.e. improvement, no change, or decline. Thresholds for classifying patients were the following; STO scores greater than or equal to 3 SEM above the mean = improved, (N= 40: 41%), STO scores less than or equal to 3 SEM below the mean = decline, (N=34: 35%), STO scores within 3 SEM= no change, (N=23: 24%). Multiple logistic regression was used to identify patient attributes predictive of improvement, decline, or no change from measures routinely collected at the point of admission to rehabilitation. The model for prediction of improvement correctly classified 70% of patients as those who improved vs. those who did not (sensitivity 70%, specificity 71%). This model generated the following variables as having predictive capabilities; recent CABG, emotional status, social status, calcium channel blocker, recent angioplasty, maximum diastolic BP, maximum systolic BP and resting systolic BP. The model for predicting those who declined vs. those who did not decline demonstrated higher correct classification rate of 74% and specificity (84%). This model generated the following variables as having predictive capabilities; social status, calcium channel blocker, orthopedic limitation, role function, QOL score and Digitalis. However, these models may include certain bias because the same observations to fit the model were also used to estimate the classification errors. Therefore, cross validation was performed utilizing the single point deletion method; this method yielded somewhat lower fraction correct classification rates (66%,69%) and sensitivity rates (56%,44%) for improvement vs. no improvement and decline vs. no decline groups respectively. Conclusion A combined set of baseline clinical, psychosocial and exercise measures can demonstrate moderate success in predicting training outcome based on STO scores in hospital outpatient cardiac rehabilitation. In contrast psychosocial data seem to account for more of the variance in prediction of decline than other types of baseline variables examined in this study. Baseline blood pressure responses both at rest and during exercise were the greatest predictors of improvement. However, cross validation of these models indicates that these results could be biased eliciting overly optimistic predictive capabilities, due to the analysis of fitted data. These models need to be validated in independent sample with patients in similar settings. / Master of Science

The field of wireless communication is under massive development and the demands on the cellular system, especially, are constantly increasing as the utilizing devices are increasing in number and diversity. A key component of wireless communication is the knowledge of the channel, i.e, how the signal is affected when sent over the wireless medium. Channel prediction is one concept which can improve current techniques or enable new ones in order to increase the performance of the cellular system. Firstly, this report will investigate the concept of a predictor antenna on new, extensive measurements which represent many different environments and scenarios. A predictor antenna is a separate antenna that is placed in front of the main antenna on the roof of a vehicle. The predictor antenna could enable good channel prediction for high velocity vehicles. The measurements show to be too noisy to be used directly in the predictor antenna concept but show potential if the measurements can be noise-filtered without distorting the signal. The use of low-pass filter and Kalman filter to do this, did not give the desired results but the technique to do this should be further investigated. Secondly, a interpolation technique will be presented which utilizes predictions with different prediction horizon by estimating intermediate channel components using interpolation. This could save channel feedback resources as well as give a better robustness to bad channel predictions by letting fresh, local, channel predictions be used as quality reference of the interpolated channel estimates. For a linear interpolation between 8-step and 18-step Kalman predictions with Normalized Mean Square Error (NMSE) of -15.02 dB and -10.88 dB, the interpolated estimates had an average NMSE of -13.14 dB, while lowering the required feedback data by about 80 %. The use of a warning algorithm reduced the NMSE by a further 0.2 dB. It mainly eliminated the largest prediction error which otherwise could lead to retransmission, which is not desired.