Business Process Modeling and Quick Prototyping with WebRatio BPM

We describe a software tool called WebRatio BPM that helps close the gap between the modeling of business processes and the design and implementation of the software applications that support their enactment. The main idea is to enhance the degree of automation in the conversion of business process models into application models, defined as abstract, platform-independent representations of the application structure and behavior. Application models are themselves amenable to the semiautomatic transformation into application code, resulting in extremely rapid prototyping and shorter time-to-market. Thanks to the proposed chain of model transformations it is also possible to fine tune the final application in several ways, e.g., by integrating the visual identity of the organization or connecting the business process to legacy applications via Web Services

Neural precursor cells tune striatal connectivity through the release of IGFBPL1

The adult brain retains over life endogenous neural stem/precursor cells (eNPCs) within the subventricular zone (SVZ). Whether or not these cells exert physiological functions is still unclear. In the present work, we provide evidence that SVZ-eNPCs tune structural, electrophysiological, and behavioural aspects of striatal function via secretion of insulin-like growth factor binding protein-like 1 (IGFBPL1). In mice, selective ablation of SVZ-eNPCs or selective abrogation of IGFBPL1 determined an impairment of striatal medium spiny neuron morphology, a higher failure rate in GABAergic transmission mediated by fast-spiking interneurons, and striatum-related behavioural dysfunctions. We also found IGFBPL1 expression in the human SVZ, foetal and induced-pluripotent stem cell-derived NPCs. Finally, we found a significant correlation between SVZ damage, reduction of striatum volume, and impairment of information processing speed in neurological patients. Our results highlight the physiological role of adult SVZ-eNPCs in supporting cognitive functions by regulating striatal neuronal activity

CERN’s beam instrumentation R&D study for FCC-ee

The Future Circular Collider (FCC) R&D study was started in 2021 as a comprehensive feasibility analysis of CERN’s future accelerator project encompassing technical, administrative and financial aspects. As part of the study, Beam Instrumentation (BI) is a key technical infrastructure that will have to face unprecedented challenges. In the case of electron-positron FCC-ee, these are represented, among others, by the size of the accelerator, the amount of radiation produced along the ring and in machine-detector interaction region, the presence of the top-up booster and collider ring in the same tunnel. In this contribution we will present the current FCC-ee BI study and discuss its status and perspectives

Associations between depressive symptoms and disease progression in older patients with chronic kidney disease: results of the EQUAL study

Background Depressive symptoms are associated with adverse clinical outcomes in patients with end-stage kidney disease; however, few small studies have examined this association in patients with earlier phases of chronic kidney disease (CKD). We studied associations between baseline depressive symptoms and clinical outcomes in older patients with advanced CKD and examined whether these associations differed depending on sex. Methods CKD patients (>= 65 years; estimated glomerular filtration rate <= 20 mL/min/1.73 m(2)) were included from a European multicentre prospective cohort between 2012 and 2019. Depressive symptoms were measured by the five-item Mental Health Inventory (cut-off <= 70; 0-100 scale). Cox proportional hazard analysis was used to study associations between depressive symptoms and time to dialysis initiation, all-cause mortality and these outcomes combined. A joint model was used to study the association between depressive symptoms and kidney function over time. Analyses were adjusted for potential baseline confounders. Results Overall kidney function decline in 1326 patients was -0.12 mL/min/1.73 m(2)/month. A total of 515 patients showed depressive symptoms. No significant association was found between depressive symptoms and kidney function over time (P = 0.08). Unlike women, men with depressive symptoms had an increased mortality rate compared with those without symptoms [adjusted hazard ratio 1.41 (95% confidence interval 1.03-1.93)]. Depressive symptoms were not significantly associated with a higher hazard of dialysis initiation, or with the combined outcome (i.e. dialysis initiation and all-cause mortality). Conclusions There was no significant association between depressive symptoms at baseline and decline in kidney function over time in older patients with advanced CKD. Depressive symptoms at baseline were associated with a higher mortality rate in men

Combined Forward-Backward Asymmetry Measurements in Top-Antitop Quark Production at the Tevatron

The CDF and D0 experiments at the Fermilab Tevatron have measured the asymmetry between yields of forward- and backward-produced top and antitop quarks based on their rapidity difference and the asymmetry between their decay leptons. These measurements use the full data sets collected in proton-antiproton collisions at a center-of-mass energy of $\sqrt s =1.96$ TeV. We report the results of combinations of the inclusive asymmetries and their differential dependencies on relevant kinematic quantities. The combined inclusive asymmetry is $A_{\mathrm{FB}}^{t\bar{t}} = 0.128 \pm 0.025$. The combined inclusive and differential asymmetries are consistent with recent standard model predictions

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Intelligenza artificiale e sicurezza: opportunità, rischi e raccomandazioni

L'IA (o intelligenza artificiale) è una disciplina in forte espansione negli ultimi anni e lo sarà sempre più nel prossimo futuro: tuttavia è dal 1956 che l’IA studia l’emulazione dell’intelligenza da parte delle macchine, intese come software e in certi casi hardware. L’IA è nata dall’idea di costruire macchine che - ispirandosi ai processi legati all’intelligenza umana - siano in grado di risolvere problemi complessi, per i quali solitamente si ritiene che sia necessario un qualche tipo di ragionamento intelligente. La principale area di ricerca e applicazione attuale dell’IA è il machine learning (algoritmi che imparano e si adattano in base ai dati che ricevono), che negli ultimi anni ha trovato ampie applicazioni grazie alle reti neurali (modelli matematici composti da neuroni artificiali) che a loro volta hanno consentito la nascita del deep learning (reti neurali di maggiore complessità). Appartengono al mondo dell’IA anche i sistemi esperti, la visione artificiale, il riconoscimento vocale, l’elaborazione del linguaggio naturale, la robotica avanzata e alcune soluzioni di cybersecurity. Quando si parla di IA c'è chi ne è entusiasta pensando alle opportunità, altri sono preoccupati poiché temono tecnologie futuristiche di un mondo in cui i robot sostituiranno l'uomo, gli toglieranno il lavoro e decideranno al suo posto. In realtà l'IA è ampiamente utilizzata già oggi in molti campi, ad esempio nei cellulari, negli oggetti smart (IoT), nelle industry 4.0, per le smart city, nei sistemi di sicurezza informatica, nei sistemi di guida autonoma (drive o parking assistant), nei chat bot di vari siti web; questi sono solo alcuni esempi basati tutti su algoritmi tipici dell’intelligenza artificiale. Grazie all'IA le aziende possono avere svariati vantaggi nel fornire servizi avanzati, personalizzati, prevedere trend, anticipare le scelte degli utenti, ecc. Ma non è tutto oro quel che luccica: ci sono talvolta problemi tecnici, interrogativi etici, rischi di sicurezza, norme e legislazioni non del tutto chiare. Le organizzazioni che già adottano soluzioni basate sull’IA, o quelle che intendono farlo, potrebbero beneficiare di questa pubblicazione per approfondirne le opportunità, i rischi e le relative contromisure. La Community for Security del Clusit si augura che questa pubblicazione possa fornire ai lettori un utile quadro d’insieme di una realtà, come l’intelligenza artificiale, che ci accompagnerà sempre più nella vita personale, sociale e lavorativa.AI (or artificial intelligence) is a booming discipline in recent years and will be increasingly so in the near future.However, it is since 1956 that AI has been studying the emulation of intelligence by machines, understood as software and in some cases hardware. AI arose from the idea of building machines that-inspired by processes related to human intelligence-are able to solve complex problems, for which it is usually believed that some kind of intelligent reasoning is required. The main current area of AI research and application is machine learning (algorithms that learn and adapt based on the data they receive), which has found wide applications in recent years thanks to neural networks (mathematical models composed of artificial neurons), which in turn have enabled the emergence of deep learning (neural networks of greater complexity). Also belonging to the AI world are expert systems, computer vision, speech recognition, natural language processing, advanced robotics and some cybersecurity solutions. When it comes to AI there are those who are enthusiastic about it thinking of the opportunities, others are concerned as they fear futuristic technologies of a world where robots will replace humans, take away their jobs and make decisions for them. In reality, AI is already widely used in many fields, for example, in cell phones, smart objects (IoT), industries 4.0, for smart cities, cybersecurity systems, autonomous driving systems (drive or parking assistant), chat bots on various websites; these are just a few examples all based on typical artificial intelligence algorithms. Thanks to AI, companies can have a variety of advantages in providing advanced, personalized services, predicting trends, anticipating user choices, etc. But not all that glitters is gold: there are sometimes technical problems, ethical questions, security risks, and standards and legislation that are not entirely clear. Organizations already adopting AI-based solutions, or those planning to do so, could benefit from this publication to learn more about the opportunities, risks, and related countermeasures. Clusit's Community for Security hopes that this publication will provide readers with a useful overview of a reality, such as artificial intelligence, that will increasingly accompany us in our personal, social and working lives

Measurement of the dependence of transverse energy production at large pseudorapidity on the hard-scattering kinematics of proton-proton collisions at √s=2.76 TeV with ATLAS

The relationship between jet production in the central region and the underlying-event activity in a pseudorapidity-separated region is studied in 4.0 pb-1 of s=2.76 TeV pp collision data recorded with the ATLAS detector at the LHC. The underlying event is characterised through measurements of the average value of the sum of the transverse energy at large pseudorapidity downstream of one of the protons, which are reported here as a function of hard-scattering kinematic variables. The hard scattering is characterised by the average transverse momentum and pseudorapidity of the two highest transverse momentum jets in the event. The dijet kinematics are used to estimate, on an event-by-event basis, the scaled longitudinal momenta of the hard-scattered partons in the target and projectile beam-protons moving toward and away from the region measuring transverse energy, respectively. Transverse energy production at large pseudorapidity is observed to decrease with a linear dependence on the longitudinal momentum fraction in the target proton and to depend only weakly on that in the projectile proton. The results are compared to the predictions of various Monte Carlo event generators, which qualitatively reproduce the trends observed in data but generally underpredict the overall level of transverse energy at forward pseudorapidity

Measurement of the W-boson mass in pp collisions at √s=7 TeV with the ATLAS detector

A measurement of the mass of the W boson is presented based on proton–proton collision data recorded in 2011 at a centre-of-mass energy of 7 TeV with the ATLAS detector at the LHC, and corresponding to 4.6 fb−1 of integrated luminosity. The selected data sample consists of 7.8×106 candidates in the W→μν channel and 5.9×106 candidates in the W→eν channel. The W-boson mass is obtained from template fits to the reconstructed distributions of the charged lepton transverse momentum and of the W boson transverse mass in the electron and muon decay channels, yielding mW=80370±7 (stat.)±11(exp. syst.) ±14(mod. syst.) MeV =80370±19MeV, where the first uncertainty is statistical, the second corresponds to the experimental systematic uncertainty, and the third to the physics-modelling systematic uncertainty. A measurement of the mass difference between the W+ and W−bosons yields mW+−mW−=−29±28 MeV