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In addition to the physics program with proton beams, the Large Hadron Collider (LHC) at CERN also provides collisions of fully-stripped Pb beams for about one month per year. When colliding Pb nuclei, electromagnetic interactions are the dominating processes because of the intense Coulomb field produced by the ions. These ’ultra-peripheral’ interactions give rise to ions with a changed magnetic rigidity. This causes losses in the machine that can impose limits on the luminosity. Among them, the bound-free pair production (BFPP) causes a localised power deposition downstream of each collision point, which could induce superconducting magnet quenches if not well controlled. These losses were studied and successfully mitigated for most LHC experiments, however the recent request by LHCb to increase the Pb-Pb luminosity requires a revision of BFPP collisional loss limitations. In this paper, the simulation of BFPP losses from Pb-Pb collisions around LHCb is presented. The loss patterns are discussed for different beam parameters. Finally, a mitigation strategy by means of an orbit bump is studied.

Individuals are prioritized based on their risk profiles when allocating limited vaccine stocks during an influenza pandemic. Computationally expensive but realistic agent-based simulations and fast but stylized compartmental models are typically used to derive effective vaccine allocation strategies. A detailed comparison of these two approaches, however, is often omitted. We derive age-specific vaccine allocation strategies to mitigate a pandemic influenza outbreak in Seattle by applying derivative-free optimization to an agent-based simulation and also to a compartmental model. We compare the strategies derived by these two approaches under various infection aggressiveness and vaccine coverage scenarios. We observe that both approaches primarily vaccinate school children, however they may allocate the remaining vaccines in different ways. The vaccine allocation strategies derived by using the agent-based simulation are associated with up to 70% decrease in total cost and 34% reduction in the number of infections compared to the strategies derived by using the compartmental model. Nevertheless, the latter approach may still be competitive for very low and/or very high infection aggressiveness. Our results provide insights about potential differences between the vaccine allocation strategies derived by using agent-based simulations and those derived by using compartmental models.

A new beam dump has been designed, built, installed and operated to withstand the future proton beam extracted from the proton synchrotron booster (PSB) in the framework of the LHC Injector Upgrade (LIU) Project at CERN. The future proton beam consists of up to1×1014 protons per pulse at 2 GeV and is foreseen after the machine upgrades planned for CERN’s Long Shutdown 2 (2019-2020). In order to be able to efficiently dissipate the heat deposited by the primary beam, the new dump was designed as a cylindrical block assembly, made out of a copper alloy and cooled by forced airflow. In order to determine the energy density distribution deposited by the beam in the dump, Monte Carlo simulations were performed using the fluka code, and thermomechanical analyses were carried out by importing the energy density into ANSYS. In addition, computational fluid dynamics (CFD) simulations of the airflow were performed in order to accurately estimate the heat transfer convection coefficient on the surface of the dump. This paper describes the design process, highlights the constraints and challenges of integrating a new dump for increased beam power into the existing facility and provides data on the operation of the dump.

Background The hospital environment has been suggested as playing an important role in the transmission of hospital-associated (HA) pathogens. However, studies investigating the contamination of the hospital environment with methicillin-resistant Staphylococcus aureus (MRSA) or Clostridium difficile have generally focused on point prevalence studies of only a single pathogen. Research evaluating the roles of these two pathogens, concurrently, in the general hospital environment has not been conducted. The objectives of this study were to determine the prevalence and identify risk factors associated with MRSA and C. difficile contamination in the general environment of three community hospitals, prospectively. Methods Sampling of environmental surfaces distributed over the medicine and surgical wards at each hospital was conducted once a week for four consecutive weeks. Sterile electrostatic cloths were used for environmental sampling and information regarding the surface sampled was recorded. For MRSA, air sampling was also conducted. Enrichment culture was performed and spa typing was performed for all MRSA isolates. For C. difficile , isolates were characterized by ribotyping and investigated for the presence of toxin genes by PCR. Using logistic regression, the following risk factors were examined for MRSA or C. difficile contamination: type of surface sampled, surface material, surface location, and the presence/absence of the other HA pathogen under investigation. Results Overall, 11.8% (n=612) and 2.4% (n=552) of surfaces were positive for MRSA and C. difficile , respectively. Based on molecular typing, five different MRSA strains and eight different C. difficile ribotypes, including ribotypes 027 (15.4%) and 078 (7.7%), were identified in the hospital environment. Results from the logistic regression model indicate that compared to computer keyboards, the following surfaces had increased odds of being contaminated with MRSA: chair backs, hand rails, isolation carts, and sofas. Conclusions MRSA and C. difficile were identified from a variety of surfaces in the general hospital environment. Several surfaces had an increased risk of being contaminated with MRSA but further studies regarding contact rates, type of surface material, and the populations using these surfaces are warranted.

Background In hospitals, Clostridium difficile infection (CDI) surveillance relies on unvalidated guidelines or threshold criteria to identify outbreaks. This can result in false-positive and -negative cluster alarms. The application of statistical methods to identify and understand CDI clusters may be a useful alternative or complement to standard surveillance techniques. The objectives of this study were to investigate the utility of the temporal scan statistic for detecting CDI clusters and determine if there are significant differences in the rate of CDI cases by month, season, and year in a community hospital. Methods Bacteriology reports of patients identified with a CDI from August 2006 to February 2011 were collected. For patients detected with CDI from March 2010 to February 2011, stool specimens were obtained. Clostridium difficile isolates were characterized by ribotyping and investigated for the presence of toxin genes by PCR. CDI clusters were investigated using a retrospective temporal scan test statistic. Statistically significant clusters were compared to known CDI outbreaks within the hospital. A negative binomial regression model was used to identify associations between year, season, month and the rate of CDI cases. Results Overall, 86 CDI cases were identified. Eighteen specimens were analyzed and nine ribotypes were classified with ribotype 027 (n = 6) the most prevalent. The temporal scan statistic identified significant CDI clusters at the hospital (n = 5), service (n = 6), and ward (n = 4) levels (P ≤ 0.05). Three clusters were concordant with the one C. difficile outbreak identified by hospital personnel. Two clusters were identified as potential outbreaks. The negative binomial model indicated years 2007–2010 (P ≤ 0.05) had decreased CDI rates compared to 2006 and spring had an increased CDI rate compared to the fall (P = 0.023). Conclusions Application of the temporal scan statistic identified several clusters, including potential outbreaks not detected by hospital personnel. The identification of time periods with decreased or increased CDI rates may have been a result of specific hospital events. Understanding the clustering of CDIs can aid in the interpretation of surveillance data and lead to the development of better early detection systems.

Background In healthcare facilities, conventional surveillance techniques using rule-based guidelines may result in under- or over-reporting of methicillin-resistant Staphylococcus aureus (MRSA) outbreaks, as these guidelines are generally unvalidated. The objectives of this study were to investigate the utility of the temporal scan statistic for detecting MRSA clusters, validate clusters using molecular techniques and hospital records, and determine significant differences in the rate of MRSA cases using regression models. Methods Patients admitted to a community hospital between August 2006 and February 2011, and identified with MRSA > 48 hours following hospital admission, were included in this study. Between March 2010 and February 2011, MRSA specimens were obtained for spa typing. MRSA clusters were investigated using a retrospective temporal scan statistic. Tests were conducted on a monthly scale and significant clusters were compared to MRSA outbreaks identified by hospital personnel. Associations between the rate of MRSA cases and the variables year, month, and season were investigated using a negative binomial regression model. Results During the study period, 735 MRSA cases were identified and 167 MRSA isolates were spa typed. Nine different spa types were identified with spa type 2/t002 (88.6%) the most prevalent. The temporal scan statistic identified significant MRSA clusters at the hospital (n = 2), service (n = 16), and ward (n = 10) levels (P ≤ 0.05). Seven clusters were concordant with nine MRSA outbreaks identified by hospital staff. For the remaining clusters, seven events may have been equivalent to true outbreaks and six clusters demonstrated possible transmission events. The regression analysis indicated years 2009–2011, compared to 2006, and months March and April, compared to January, were associated with an increase in the rate of MRSA cases (P ≤ 0.05). Conclusions The application of the temporal scan statistic identified several MRSA clusters that were not detected by hospital personnel. The identification of specific years and months with increased MRSA rates may be attributable to several hospital level factors including the presence of other pathogens. Within hospitals, the incorporation of the temporal scan statistic to standard surveillance techniques is a valuable tool for healthcare workers to evaluate surveillance strategies and aid in the identification of MRSA clusters.

Physical activity (PA) is a key element in the management of successful aging. The aim of this paper was to show the effects of PA on the quality of life perception, nutritional status, and daily life management of 178 older adults (aged 63.87 ± 8.17) randomly assigned to an Experimental Group (EG), which performed moderate-to-high intensity aerobic and strengthening training, and a Control Group (CG) which performed low-impact PA, assessed after 6, 12, and 24 months. The Short-Form Health Survey (SF-36), Mini Nutritional Assessment (MNA), and Physical Activity Scale for the Elderly (PASE) were used for the study. In the SF-36 assessment, EG showed a good quality of life perception maintained after 24 months, while CG showed a worsening in the same period (p = 0.018). The EG reported a significant better nutritional status as compared to pre-intervention assessment (p = 0.003) and to CG (p < 0.001). Regarding the PASE, the EG showed a higher level of weekly activities than the CG after 24 months (p = 0.011), while the CG showed a worsening after 12 months (p = 0.008). The prolonged engagement in moderate-to high-intensity PA allowed the maintenance of a good quality of life perception, a good level of nutritional status, and daily life activities.

Background Several observational studies have shown that exercise reduces the risk of cognitive decline; however, evidences from long-term, well-conducted, randomized controlled trials are scanty. The principal aim of this study is to verify whether a long-term program of multimodal supervised exercise improves the cognitive function and/or reduces the rate of cognitive decline in older adults at different degrees of risk for dementia. Methods/design EPD is a parallel group, double-blind, randomized controlled trial. Community-dwelling volunteers aged 50 years or more are being recruited from different community centers and screened for eligibility. Enrolled subjects are being divided in 3 groups: a) without subjective or objective cognitive impairment, b) with subjective memory complaints, and c) with mild cognitive impairments. Participants in each group (at least 180) are being randomly assigned (1:1) to an experimental group, performing a supervised training including aerobic and resistance exercises of moderate/high intensity, or to a control group. Primary outcome will be 48-months changes in Mini Mental State Examinations. Secondary outcomes will be changes in several cognitive tests including a composite cognitive score. Time points will be at baseline, and at 6, 12, 24, 36 and 48 months. Statistical analysis will be done as intention to treat, complete case and mixed model analysis. Discussion EPD is the first trial to examine the effects of a long exercise program (48 months) on cognitive performances. If successful, this trial may provide evidence for using long-term and multimodal exercise interventions for dementia prevention programs in the aging population. Trial registration The study is registered at ClinicalTrials.gov with the code NCT02236416 .

The Upgrade II of the LHCb (Large Hadron Collider beauty) experiment is proposed for Long Shutdown (LS) 4, aiming to operate at 1.5 · 1034cm-2s-1 and reaching an integrated luminosity slightly less than 400fb-1 by the end of the High Luminosity LHC (HL-LHC) era. This increase of luminosity is going to enlarge the data sample at LHCb providing an unprecedented opportunity for heavy flavour physics measurements. During LS2, a first upgrade of LHCb (Upgrade I) has already been realised allowing operations at 2 · 1033cm-2s-1, five times more than the value reached during Run2. The mentioned luminosity increase will have an impact not only on the experimental apparatus but also on the functional elements of the LHC, magnets, cryogenics and electronic equipment placed in the Insertion Region 8 (IR8). The LHCb experiment was conceived to operate at a lower luminosity than the two LHC general purpose experiments, ATLAS and CMS. This implied minor requirements for protection of the LHC elements from the collision debris and therefore a different layout around the LHCb Interaction Point (IP8). However, with the HL-LHC era and the LHCb upgrades, the predicted radiation levels will be comparable with those achieved by ATLAS and CMS during Run2, requiring a systematic study of the current layout and the conceivable enforcement of a variety of protection measures in IR8 from the collision debris. Monte Carlo simulations are a powerful tool to predict the interaction between particle showers and accelerator elements, especially in case of future scenarios. In this regard, a FLUKA model of the experimental area in the LHCb region and of the LHC tunnel has been set up and benchmarked with experimental data to evaluate radiation levels and particle fluences due to proton collisions. Firstly, annual radiation levels after the Upgrade II of LHCb will increase by a factor of 5 with respect to the values after the Upgrade I, implying the need to shield the electronics placed in the experimental areas, to mitigate the single event effect (SEE) risk which may imply recurring downtime of the LHC and to preserve the electronics performance. Furthermore, the impact of radiation on the LHC magnets (i.e. final focusing quadrupoles, separation and recombination dipole, dispersion suppressor elements) was studied in terms of transient effects and damage risk. In conclusion, the luminosity target proposed for Upgrade II can be sustained with protection systems for magnets and electronics, requiring to review the layout of IR8 to ensure safe operation of the LHC magnets.

During the last decades, plant-based milk has become very appreciated by consumers, becoming a staple ingredient, especially for alternative breakfasts. Milk contains lactose, which is a sugar hydrolysed by the lactase enzyme. Lactose intolerance and lactose malabsorption are very common food intolerances among individuals. However, a lot of consumers consider themselves as lactose intolerant on the basis of self-reported intolerance and start to avoid dairy products, ignoring that plant-based milk alternatives are not nutritionally comparable to animal milk, especially in terms of protein intake. The aim of this study is to grow folder knowledge of the security of plant-based drinks, helping competent authorities to issue a risk assessment and to apply national plans about consumer safety. Results show that proper sanitary practices, such as pasteurization, are necessary in plant-based milk alternatives as well as in dairy milk. Chemical analysis has highlighted that there are no pesticide risks for consumers.