Improving resilience in Critical Infrastructures through learning from past events

Modern societies are increasingly dependent on the proper functioning of Critical Infrastructures (CIs). CIs produce and distribute essential goods or services, as for power transmission systems, water treatment and distribution infrastructures, transportation systems, communication networks, nuclear power plants, and information technologies. Being resilient, where resilience denotes the capacity of a system to recover from challenges or disruptive events, becomes a key property for CIs, which are constantly exposed to threats that can undermine safety, security, and business continuity. Nowadays, a variety of approaches exists in the context of CIs’ resilience research. This dissertation starts with a systematic review based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) on the approaches that have a complete qualitative dimension, or that can be used as entry points for semi-quantitative analyses. The review identifies four principal dimensions of resilience referred to CIs (i.e., techno-centric, organizational, community, and urban) and discusses the related qualitative or semi-quantitative methods. The scope of the thesis emphasizes the organizational dimension, as a socio-technical construct. Accordingly, the following research question has been posed: how can learning improve resilience in an organization? Firstly, the benefits of learning in a particular CI, i.e. the supply chain in reverse logistics related to the small arms utilized by Italian Armed Forces, have been studied. Following the theory of Learning From Incidents, the theoretical model helped to elaborate a centralized information management system for the Supply Chain Management of small arms within a Business Intelligence (BI) framework, which can be the basis for an effective decision-making process, capable of increasing the systemic resilience of the supply chain itself. Secondly, the research question has been extended to another extremely topical context, i.e. the Emergency Management (EM), exploring the crisis induced learning where single-loop and double-loop learning cycles can be established regarding the behavioral perspective. Specifically, the former refers to the correction of practices within organizational plans without changing core beliefs and fundamental rules of the organization, while the latter aims at resolving incompatible organizational behavior by restructuring the norms themselves together with the associated practices or assumptions. Consequently, with the aim of ensuring high EM systems resilience, and effective single-loop and double-loop crisis induced learning at organizational level, the study examined learning opportunities that emerge through the exploration of adaptive practices necessary to face the complexity of a socio-technical work domain as the EM of Covid-19 outbreaks on Oil & Gas platforms. Both qualitative and quantitative approaches have been adopted to analyze the resilience of this specific socio-technical system. On this consciousness, with the intention to explore systems theoretic possibilities to model the EM system, the Functional Resonance Analysis Method (FRAM) has been proposed as a qualitative method for developing a systematic understanding of adaptive practices, modelling planning and resilient behaviors and ultimately supporting crisis induced learning. After the FRAM analysis, the same EM system has also been studied adopting a Bayesian Network (BN) to quantify resilience potentials of an EM procedure resulting from the adaptive practices and lessons learned by an EM organization. While the study of CIs is still an open and challenging topic, this dissertation provides methodologies and running examples on how systemic approaches may support data-driven learning to ultimately improve organizational resilience. These results, possibly extended with future research drivers, are expected to support decision-makers in their tactical and operational endeavors

Reviewing qualitative research approaches in the context of critical infrastructure resilience

Modern societies are increasingly dependent on the proper functioning of critical infrastructures (CIs). CIs produce and distribute essential goods or services, as for power transmission systems, water treatment and distribution infrastructures, transportation systems, communication networks, nuclear power plants, and information technologies. Being resilient becomes a key property for CIs, which are constantly exposed to threats that can undermine safety, security, and business continuity. Nowadays, a variety of approaches exist in the context of CIs’ resilience research. This paper provides a state-of-the-art review on the approaches that have a complete qualitative dimension, or that can be used as entry points for semi-quantitative analyses. The study aims to uncover the usage of qualitative research methods through a systematic review based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). The paper identifies four principal dimensions of resilience referred to CIs (i.e., techno-centric, organisational, community, and urban) and discusses the related qualitative methods. Besides many studies being focused on energy and transportation systems, the literature review allows to observe that interviews and questionnaires are most frequently used to gather qualitative data, besides a high percentage of mixed-method research. The article aims to provide a synthesis of literature on qualitative methods used for resilience research in the domain of CIs, detailing lessons learned from such approaches to shed lights on best practices and identify possible future research directions

Learning from incidents: A supply chain management perspective in military environments

Supply chain management (SCM) represents a crucial role in the military sector to ensure operation sustainability. Starting from the NATO handbook for military organizational learning, this paper aims at investigating the link between technical inconveniences and sustainable supply chain operations. Taking advantage of the learning from incidents (LFI) models traditionally used in the risk and safety management area, this paper proposes an information management system to support organizational learning from technical inconveniences in a military supply chain. The approach is discussed with reference to the Italian context, in line with international and national standards for technical inconvenience reporting. The results of the paper show the benefits of adopting a systematic LFI system for technical inconveniences, providing related exemplar business intelligence dashboards. Further implications for the generalization of the proposed information management system are presented to foster a healthy and effective reporting environment in military scenarios

Therapeutic Peptides Targeting PPI in Clinical Development: Overview, Mechanism of Action and Perspectives

Targeting protein-protein interactions (PPIs) has been recently recognized as an emerging therapeutic approach for several diseases. Up today, more than half a million PPI dysregulations have been found to be involved in pathological events. The dynamic nature of these processes and the involvement of large protein surfaces discouraged anyway the scientific community in considering them promising therapeutic targets. More recently peptide drugs received renewed attention since drug discovery has offered a broad range of structural diverse sequences, moving from traditionally endogenous peptides to sequences possessing improved pharmaceutical profiles. About 70 peptides are currently on the marked but several others are in clinical development. In this review we want to report the update on these novel APIs, focusing our attention on the molecules in clinical development, representing the direct consequence of the drug discovery process of the last 10 years. The comprehensive collection will be classified in function of the structural characteristics (native, analogous, heterologous) and on the basis of the therapeutic targets. The mechanism of interference on PPI will also be reported to offer useful information for novel peptide desig

EMDR and CBT for Cancer Patients: Comparative Study of Effects on PTSD, Anxiety, and Depression

This pilot study examined the efficacy of eye movement desensitization and reprocessing (EMDR) treatment compared with cognitive behavioral therapy (CBT) in treating posttraumatic stress disorder (PTSD) in oncology patients in the follow-up phase of the disease. The secondary aim of this study was to assess whether EMDR treatment has a different impact on PTSD in the active treatment or during the followup stages of disease. Twenty-one patients in follow-up care were randomly assigned to EMDR or CBT groups, and 10 patients in the active treatment phase were assigned to EMDR group. The Impact of Event Scale-Revised (IES-R) and Clinician-Administered PTSD Scale (CAPS) were used to assess PTSD at pretreatment and 1 month posttreatment. Anxiety, depression, and psychophysiological symptoms were also evaluated. For cancer patients in the follow-up stage, the absence of PTSD after the treatment was associated with a significantly higher likelihood of receiving EMDR rather than CBT. EMDR was significantly more effective than CBT in reducing scores on the IES-R and the CAPS intrusive symptom subscale, whereas anxiety and depression improved equally in both treatment groups. Furthermore, EMDR showed the same efficacy both in the active cancer treatment and during the follow-up of the disease

Heat transfer measurements for Stirling machine cylinders

The primary purpose of this study was to measure the effects of inflow-produced heat turbulence on heat transfer in Stirling machine cylinders. A secondary purpose was to provide new experimental information on heat transfer in gas springs without inflow. The apparatus for the experiment consisted of a varying-volume piston-cylinder space connected to a fixed volume space by an orifice. The orifice size could be varied to adjust the level of inflow-produced turbulence, or the orifice plate could be removed completely so as to merge the two spaces into a single gas spring space. Speed, cycle mean pressure, overall volume ratio, and varying volume space clearance ratio could also be adjusted. Volume, pressure in both spaces, and local heat flux at two locations were measured. The pressure and volume measurements were used to calculate area averaged heat flux, heat transfer hysteresis loss, and other heat transfer-related effects. Experiments in the one space arrangement extended the range of previous gas spring tests to lower volume ratio and higher nondimensional speed. The tests corroborated previous results and showed that analytic models for heat transfer and loss based on volume ratio approaching 1 were valid for volume ratios ranging from 1 to 2, a range covering most gas springs in Stirling machines. Data from experiments in the two space arrangement were first analyzed based on lumping the two spaces together and examining total loss and averaged heat transfer as a function of overall nondimensional parameter. Heat transfer and loss were found to be significantly increased by inflow-produced turbulence. These increases could be modeled by appropriate adjustment of empirical coefficients in an existing semi-analytic model. An attempt was made to use an inverse, parameter optimization procedure to find the heat transfer in each of the two spaces. This procedure was successful in retrieving this information from simulated pressure-volume data with artificially generated noise, but it failed with the actual experimental data. This is evidence that the models used in the parameter optimization procedure (and to generate the simulated data) were not correct. Data from the surface heat flux sensors indicated that the primary shortcoming of these models was that they assumed turbulence levels to be constant over the cycle. Sensor data in the varying volume space showed a large increase in heat flux, probably due to turbulence, during the expansion stroke

Fast MacMillan's Imidazolidinone-Catalyzed Enantioselective Synthesis of Polyfunctionalized 4-Isoxazoline Scaffolds

The enantioselective 1,3-dipolar cycloaddition of nitrones and arylpropionaldehydes to generate highly functionalized scaffolds for application in drug discovery was herein investigated. The use of a second-generation MacMillan catalyst as hydrochloride salt consistently accelerated the reaction speed, allowing a decrease in the reaction time up to >100 times, still affording 4-isoxazolines with good to excellent enantiomeric ratios at room temperature. As a proof of concept, further functionalization of the isoxazoline core through Pd-catalyzed cross-coupling was performed, generating differently functionalized chemical architectures in high yield

Child-related characteristics predicting subsequent health-related quality of life in 8- to 14-year-old children with and without cerebellar tumors: a prospective longitudinal study

BackgroundWe identified child-related determinants of health-related quality of life (HRQoL) in children aged 8–14 years who were treated for 2 common types of pediatric brain tumors. MethodsQuestionnaire measures of HRQoL and psychometric assessments were completed by 110 children on 3 occasions over 24 months. Of these 110, 72 were within 3 years of diagnosis of a cerebellar tumor (37 standard-risk medulloblastoma, 35 low-grade cerebellar astrocytoma), and 38 were in a nontumor group. HRQoL, executive function, health status, and behavioral difficulties were also assessed by parents and teachers as appropriate. Regression modeling was used to relate HRQoL z scores to age, sex, socioeconomic status, and 5 domains of functioning: Cognition, Emotion, Social, Motor and Sensory, and Behavior. ResultsHRQoL z scores were significantly lower after astrocytoma than those in the nontumor group and significantly lower again in the medulloblastoma group, both by self-report and by parent-report. In regression modeling, significant child-related predictors of poorer HRQoL z scores by self-report were poorer cognitive and emotional function (both z scores) and greater age (years) at enrollment (B = 0.038, 0.098, 0.136, respectively). By parent-report, poorer cognitive, emotional and motor or sensory function (z score) were predictive of lower subsequent HRQoL of the child (B = 0.043, 0.112, 0.019, respectively), while age at enrollment was not. ConclusionsEarly screening of cognitive and emotional function in this age group, which are potentially amenable to change, could identify those at risk of poor HRQoL and provide a rational basis for interventions to improve HRQoL

Steps towards sustainable solid phase peptide synthesis: use and recovery ofN-octyl pyrrolidone

The investigation of new green biogenic pyrrolidinones as alternative solvents toN,N-dimethylformamide (DMF) for solid phase peptide synthesis (SPPS) led to the identification ofN-octyl pyrrolidone (NOP) as the best candidate. NOP showed good performances in terms of swelling, coupling efficiency and low isomerization generating peptides with very high purity. A mixture of NOP with 20% dimethyl carbonate (DMC) allowed a decrease in solvent viscosity, making the mixture suitable for the automated solid-phase protocol. Aib-enkephalin and linear octreotide were successfully used to test the methodologies. It is worth noting that NOP, DMC and the piperidine used in the deprotection step could be easily recovered by direct distillation from the process waste mixture. The process mass intensity (PMI), being reduced by 63-66%, achieved an outstanding value representing a clear step forward in achieving green SPPS