10 research outputs found
Preemption-aware planning on Big-Data systems
No full textRecent developments in Big Data frameworks are moving towards reservation based approaches as a mean to manage the increasingly complex mix of computations, whereas preemption techniques are employed to meet strict jobs deadlines. Within this work we propose and evaluate a new planning algorithm in the context of reservation based scheduling. Our approach is able to achieve high cluster utilization while minimizing the need for preemption that causes system overheads and planning mispredictions
Total thyroidectomy for Graves' disease treatment
No full textObjectives. Graves' disease (GD) is the most common cause of hyperthyroidism, and accounts worldwide for 60-80% of all cases. The diagnosis is based on clinical findings, and is confirmed by the presence of TRAB, suppression of TSH, and elevation of free thyroxin (free T4), and triiodinethyronin (free T3). GD can be treated by antithyroid drugs, radioactive iodine, or surgery. The aim of this study was to review retrospectively the surgical management, in terms of safety and efficacy, in 50 patients operated in the Department of Surgical Sciences since 2005 through 2010 and followed up at the Endocrinology Unit A of the Experimental Medicine Department. We assessed postoperative complications, which included the presence, persistence and development of ophthalmopathy, transient hypocalcemia, permanent hypoparathyroidism and recurrent laryngeal nerve palsy. Materials and Methods. We analyzed data from 50 patients with GD who were eligible and underwent Total Thyroidectomy (TT). Thirty-nine patients underwent TT for recurrent hyperthyroidism after medical therapy and eleven patients for severe ophtalmopathy. The mean follow up was 41 months (range: 10-70). Results. Eleven patients had ophtalmopathy before surgery. Four patients developed an ophtalmopathy after surgery. Eleven patients presented hypocalcemia, transient in ten patients and permanent in one patient. Five patients developed a transient disphony. Conclusions. Total thyroidectomy is a safe and radical procedure in Graves' disease treatment. Complications of TT are not different than subtotal thyroidectomy if it's performed by expert surgeons
YARN++ : distributed scheduling and opportunistic resource utilization in Hadoop
No full textLAUREA MAGISTRAL
Commentaries and cases on italian business law
No full textThis casebook deals with the basic principles of the Italian business law and focuses on certain recent and pivotal cases in which important rules governing the modern public company have been applied. After a short overview of the main corporate and securities laws and regulation applicable to Italian listed companies, certain leading cases which triggered the application of such rules are analyzed. The main interrelationships between and among the economic and legal elements are scrutinized for the purpose of highlighting the economic logic underlying corporate law. In the financial markets’ dynamics, the public company plays a vital role since it attracts the public savings coming from the investors in order to finance business plans and strategies which create growth and welfare. In such a scenario, financial intermediaries must act in the interest of the investors, selecting among the potential issuers those who are the most attractive for their clients. When companies are structurally organized to attract standardized equity or debt investments, by issuing listed shares, bonds or other financial instruments, their operational and governance rules change in order to safeguard the public savings coming from the investors. In the end, what makes this branch of law so interesting to students, practitioners, and scholars alike is the open-textured relationship between corporate law and securities regulation which plays a crucial role in such context. The cases selected in the second part of this book deal with significant topics in the Italian market practice and are briefly commented making reference to an updated set of laws and references. Therefore, this book can be used also with a focus on comparative legal systems for corporations taught in Italy or abroad
Use of nebulized liposomal amphotericin B and posaconazole as antifungal prophylaxis in patients with severe SARS-CoV2 infection in intensive care unit
No full textPurpose COVID-19 associated pulmonary aspergillosis (CAPA) is common and linked with high fatality rates. To assess the impact on the incidence and outcome of CAPA of an antifungal prophylaxis (AFP) we compared two cohorts of COVID-19 patients admitted to intensive care units (ICU) in Brescia, Italy, from January to August 2021. Methods The study cohort included all mechanically ventilated patients observed between April 2021 and August 2021 with SARS-CoV-2-pneumonia, who received AFP with oral posaconazole (200 mg every 6 h) and nebulized liposomal amphotericin B (50 mg every 2 weeks) from ICU admission to 7 days after discharge or, if applicable, until tracheostomy removal. The control cohort included COVID-19 patients admitted to the same ICU between January and March 2021 who did not receive any AFP. Subjects with CAPA at ICU admission were excluded. Results We included 270 patients, of whom 64 (23.7%) received AFP. In patients in the study group, CAPA-related mortality was significantly reduced (29% vs. 48% p = 0.04), as well as the incidence of CAPA (3.1% vs 12.1%, p = 0.03). Patients who developed CAPA were older (mean of 70-y-old vs 63-y-old, p < 0.001). One subject discontinued posaconazole due to an adverse reaction. Among the 46 patients who received it, only one patient reached an effective plasma concentration of posaconazole. Conclusion AFP was associated with reduced incidence and mortality from CAPA and was well tolerated in patients with severe COVID-19. Posaconazole concentrations below the efficacy threshold in almost all patients may be attributable to drug interactions and prompt further studies to define its clinical significance
Real-life experience with compassionate use of cefiderocol for difficult-to-treat resistant Pseudomonas aeruginosa (DTR-P) infections
No full textObjectives: To describe our real-life experience with cefiderocol in XDR and difficult-to-treat resistant Pseudomonas aeruginosa (DTR-P) infections without any other available treatment options. Methods: We included patients with a proven infection due to an XDR/DTR-P, who had failed on previous regimens, and were treated with cefiderocol, following them prospectively to day 90 or until hospital discharge or death. Results: Seventeen patients treated for >72 h with cefiderocol were included: 14 receiving combination regimens (82.4%) and 3 receiving monotherapy (17.6%). Fourteen patients were males (82%) with a median age of 64 years (IQR 58-73). Fifteen patients (88.2%) were admitted to the ICU and five had septic shock (29%). Seven cases (41.2%) were ventilator-associated pneumonia, of which 71% (5/7) occurred in COVID-19 patients. Four were complicated intrabdominal infections, one ecthyma gangrenosum, one nosocomial pneumonia and one empyema, one osteomyelitis, one primary bacteraemia, and one nosocomial external ventricular drainage meningitis. Clinical cure and microbiological cure rates were 70.6% and 76.5%, respectively. There were six deaths (35.3%) after a median of 8 days (IQR 3-10) from the end of treatment, but only two of them (11.7%) were associated with P. aeruginosa infection progression. Conclusions: Our experience collecting this large case series of DTR-P treated with cefiderocol may help clinicians consider this new option in this hard-to-manage setting. Our results are even more relevant in the current scenario of ceftolozane/tazobactam shortage. Importantly, this is the first study providing real-life data indicating adequate cefiderocol concentrations in CSF
Hybrid centralized and distributed scheduling in large shared clusters.
No full textAbstract Datacenter-scale computing for analytics workloads is increasingly common. High operational costs force heterogeneous applications to share cluster resources for achieving economy of scale. Scheduling such large and diverse workloads is inherently hard, and existing approaches tackle this in two alternative ways: 1) centralized solutions offer strict, secure enforcement of scheduling invariants (e.g., fairness, capacity) for heterogeneous applications, 2) distributed solutions offer scalable, efficient scheduling for homogeneous applications. We argue that these solutions are complementary, and advocate a blended approach. Concretely, we propose Mercury, a hybrid resource management framework that supports the full spectrum of scheduling, from centralized to distributed. Mercury exposes a programmatic interface that allows applications to trade-off between scheduling overhead and execution guarantees. Our framework harnesses this flexibility by opportunistically utilizing resources to improve task throughput. Experimental results on production-derived workloads show gains of over 35% in task throughput. These benefits can be translated by appropriate application and framework policies into job throughput or job latency improvements. We have implemented and contributed Mercury as an extension of Apache Hadoop / YARN.
Hybrid centralized and distributed scheduling in large shared clusters.
No full textAbstract Datacenter-scale computing for analytics workloads is increasingly common. High operational costs force heterogeneous applications to share cluster resources for achieving economy of scale. Scheduling such large and diverse workloads is inherently hard, and existing approaches tackle this in two alternative ways: 1) centralized solutions offer strict, secure enforcement of scheduling invariants (e.g., fairness, capacity) for heterogeneous applications, 2) distributed solutions offer scalable, efficient scheduling for homogeneous applications. We argue that these solutions are complementary, and advocate a blended approach. Concretely, we propose Mercury, a hybrid resource management framework that supports the full spectrum of scheduling, from centralized to distributed. Mercury exposes a programmatic interface that allows applications to trade-off between scheduling overhead and execution guarantees. Our framework harnesses this flexibility by opportunistically utilizing resources to improve task throughput. Experimental results on production-derived workloads show gains of over 35% in task throughput. These benefits can be translated by appropriate application and framework policies into job throughput or job latency improvements. We have implemented and contributed 1 Mercury as an extension of Apache Hadoop / YARN
