On the parallelism between the rate of change in electric resistance at fusion and the degree of closeness of packing of metallic atoms in crystals

Digiteeritud Euroopa Regionaalarengu Fondi rahastusel, projekti "Eesti teadus- ja õppekirjandus" (2014-2020.12.03.21-0848) raames.https://www.ester.ee/record=b2360511*es

Explaining the emergence of cooperative traits: An axiomatic theory of accumulation

In this dissertation I construct an axiomatic theory of action that explains how originally selfish individuals form aggregations and develop cooperative abilities. This theory is more general than the two most widespread biological explanations of the emergence of cooperation: kinship theory and game theoretic models. In particular, it introduces the notions of space and time that are more general (individual specific) than standard physical notions on which biological theories mostly rely. While predictions of my theory agree, in principle, with predictions of other main theories of aggregation, its scope goes well beyond that of any other theory of aggregation. For instance, I am able to show that two different arguments about properties of optimal size aggregations do in fact follow from a single set of assumptions, namely those of my theory of accumulations. I am also able to explain a paradoxical empirical finding on genetic variation. More specifically, Sibly (1983) has shown that under a certain type of a fitness function individuals will form aggregations with fitness optimizing group size being larger than the eventually emerging in equilibrium group size. In a response to Sibly, Giraldeau and Gillis (1984) presented a type of fitness function where the optimal group size is equal to the equilibrium group size. Both arguments rely, however, on fitness functions that are postulated ad hoc. In my theory I show how both of these functions can be derived analytically from a set of more fundamental assumptions. This shows that claims of Sibly and Giraldeau's and Gillis' while seemingly contradictory, were in fact consistent. Another example of an application of my theory concerns a genetic puzzle posed by Hedrick and Parker (1997). Hedric and Parker have observed that genetic variation in eusocials is not only a higher than predicted by kinship but even higher than in solitaries. This empirical observation, paradoxical in the light of standard biological explanations, can in fact be explained by my theory

Point-of-care testing for influenza in a university emergency department: a prospective study

Hintergrund: Influenzawellen führen zu hohen Belastungen der Notaufnahmen. Viele Patient*innen stellen sich mit unspezifischen respiratorischen Symptomen vor. Nicht immer sind die gezielte Isolation und die spezifische Therapie möglich, was sowohl zur Auslastung der Notaufnahmen als auch zu Infektionen des Personals und anderer Patient*innen führt. Methoden: Um zu untersuchen, ob sich Abläufe verbessern lassen und das Personal vor Infektionen geschützt werden kann, wurde mittels eines Cross-Over-Designs der Roche cobas® Liat® Influenza A/B POC-PCR-Test mit der gängigen klinischen Praxis zur Influenzatestung in der Notaufnahme verglichen. Diese bestand aus selektiven PCR-Tests im Zentrallabor, überwiegend bei stationären Fällen. Während der Influenzasaison 2019/2020 wurden alle erwachsenen Patient*innen mit respiratorischen Symptomen an zwei Standorten eingeschlossen. Als primäre Endpunkte wurden die Prävalenz von Influenzainfektionen und die Krankheitstage des Personals festgelegt. Unter anderem wurden die bildgebende Diagnostik, die Häufigkeit von antibiotischer und antiviraler Therapie sowie die Aufenthaltsdauer in der Notaufnahme (EDLOS) und die Zeit von der Patientenaufnahme bis zur Verfügbarkeit eines Testergebnisses beziehungsweise darauffolgender Therapieinitiierung als sekundäre Endpunkte untersucht. Ferner wurde die Disposition und Liegedauer von hospitalisierten Patient*innen (LOS) verglichen. Um die Implementierung des POC-PCR-Tests zu evaluieren, wurde das Pflegepersonal befragt. Ergebnisse: Von 828 Patient*innen waren 375 in der Interventions- und 453 in der Kontrollgruppe. Alle Patient*innen der Interventionsgruppe wurden mittels POC-PCR-Test auf Influenza getestet. In der Kontrollgruppe wurden 53,9% der Patient*innen im Rahmen des klinischen Routinevorgehens auf Influenza getestet. In der Interventionsgruppe waren bestätigte Infektionen häufiger (27,5% vs. 18,1%, p<0,001). Die Krankheitstage des Personals waren signifikant reduziert (457 vs. 697, p=0,023). Neuraminidaseinhibitoren (NAI) wurden häufiger verabreicht (7,2% vs. 3,8%, p=0,028) und getestete Patient*innen erhielten häufiger eine antibiotische Therapie (40,0% vs. 31,6%, p=0,033). Patient*innen wurden ähnlich häufig stationär aufgenommen, die der Interventionsgruppe jedoch häufiger auch in externe Krankenhäuser (5,6% vs. 1,3%, p=0,010). Fazit: Insbesondere bei hohem Fallaufkommen von Patient*innen mit respiratorischen Symptomen ist eine Influenza POC-PCR-Testung in der Notaufnahme geeignet, um Abläufe zu verbessern und das Personal vor Infektionen zu schützen.Background: Influenza waves lead to high number of patients in emergency departments. Many patients present with non-specific respiratory symptoms. Targeted isolation and treatment are not always possible, leading to emergency department utilization and infections of staff and other patients. Methods: To investigate whether procedures can be improved and emergency department staff can be protected from influenza infections, the Roche cobas® Liat® Influenza A/B POC PCR test was compared with current clinical routine of selective PCR testing in the central laboratory, predominantly for inpatient cases, using a cross-over design. Patients were included during the 2019/2020 influenza season at two sites and had to be 18 years of age. In addition, fever and respiratory symptoms had to be present. Prevalence of influenza infection and staff sick days were set as primary endpoints. Secondary endpoints included diagnostic procedures, frequency of antibiotic and antiviral treatment and emergency department length of stay and time from patient admission to availability of a test result or subsequent initiation of therapy. Furthermore, the disposition and length of stay of hospitalized patients were compared. To evaluate the implementation of the POC PCR test nurses were surveyed. Results: Of 828 patients, 375 were in the intervention group and 453 were in the control group. All patients of the intervention group were tested for influenza by POC PCR test. In the control group, 53.9% of patients were tested for influenza as part of routine clinical practice. In the intervention group, confirmed infections were more frequent (27.5% vs. 18.1%, p<0.001). Staff sick days were significantly reduced (457 vs. 697, p=0.023). Neuraminidase inhibitors (NAI) were administered more frequently (7.2% vs. 3.8%, p=0.028) and patients tested received antibiotic therapy more frequently (40.0% vs. 31.6%, p=0.033). Patients were similarly frequently admitted as inpatients, but those in the intervention group were more frequently admitted to external hospitals (5.6% vs. 1.3%, p=0.010). Conclusion: Influenza POC PCR testing in the emergency department is particularly useful to improve procedures and to protect staff from infections when there is a high case load of patients with respiratory symptoms

nBIIG: A Neural BI Insights Generation System for Table Reporting

We present nBIIG, a neural Business Intelligence (BI) Insights Generation system. Given a table, our system applies various analyses to create corresponding RDF representations, and then uses a neural model to generate fluent textual insights out of these representations. The generated insights can be used by an analyst, via a human-in-the-loop paradigm, to enhance the task of creating compelling table reports. The underlying generative neural model is trained over large and carefully distilled data, curated from multiple BI domains. Thus, the system can generate faithful and fluent insights over open-domain tables, making it practical and useful.Comment: Accepted to AAAI-2

Point‐of‐care testing for influenza in a university emergency department: A prospective study

Background: Seasonal influenza is a burden for emergency departments (ED). The aim of this study was to investigate whether point-of-care (POC) PCR testing can be used to reduce staff sick days and improve diagnostic and therapeutic procedures. Objectives The aim of this study was to investigate whether point-of-care (POC) PCR testing can be used to reduce staff sick days and improve diagnostic and therapeutic procedures. Methods: Using a cross-over design, the cobas (R) Liat (R) Influenza A/B POC PCR test (Liat) was compared with standard clinical practice during the 2019/2020 influenza season. All adult patients (aged >= 18 years) with fever (>= 38 degrees C) and respiratory symptoms were included. Primary end points were the prevalence of influenza infections in the ED and staff sick days. Secondary end points were frequency of antiviral and antibacterial therapy, time between admission and test result or treatment initiation, patient disposition, ED length of stay (LOS), and for inpatients mortality and LOS. Nurses were interviewed about handling and integration of POC testing. The occurrence of SARS-CoV-2 infections coincided with the second half of the study. Results A total of 828 patients were enrolled in the study. All 375 patients of the intervention group were tested with Liat, and 103 patients of them (27.6%) tested positive. During the intervention period, staff sick days were reduced by 34.4% (P = .023). Significantly, more patients in the intervention group received antiviral therapy with neuraminidase inhibitors (7.2% vs 3.8%, P = .028) and tested patients received antibiotics more frequently (40.0% vs 31.6%, P = .033). Patients with POC test were transferred to external hospitals significantly more often (5.6% vs 1.3%, P = .01). Conclusion: We conclude that POC testing for influenza is useful in the ED, especially if it is heavily frequented by patients with respiratory symptoms

¿Se han modificado las preferencias de los ciudadanos sobre las políticas de bienestar en España (1985-2005)?

Este trabajo es uno de los frutos empíricos del proyecto de investigación Reformas en el Estado de Bienestar: Actores y Apoyos Ciudadanos (REBAAC), http://www.iesam.csic.es/proyecto/rebaac.htm, dirigido por Luis Moreno, que se completará en los próximos meses con otros escritos sobre el tema.[EN] In recent years pressures for the reform of the Welfare State have been voiced despite that public opinion has kept opposed to the retrenchment of social policies. Some studies have pointed out that governments have learned how to avoid popular resistance to the reforms due to a change in citizens’ attitudes. This Working Paper explores the attitudes of the Spaniards with respect to the process and outcomes of the welfare policies implemented in Spain in the last 20 years. Whenever possible this paper takes a comparative. Time series have been worked out covering the period under analysis. Likewise, preferences towards the various welfare policies and these and other public policies are also compared. The two main conclusions are that the support for the welfare policies is solid (despite some qualifications) and that the public preference for the meso or intermediate level of government as provider of social policies has increased.[ES] En los últimos años parece que las presiones para la reforma del Estado de Bienestar están siendo más insistentes que una opinión pública hasta ahora opuesta a cualquier tipo de recorte de los programas sociales. Algunos estudios sugieren que los gobiernos parecen haber aprendido como esquivar la resistencia de los ciudadanos a las reformas aprovechando un supuesto cambio en sus actitudes durante los últimos años. Con esta hipótesis de cambio en las actitudes ciudadanas se exploran en este trabajo las preferencias de los españoles hacia el proceso y los resultados de las políticas del bienestar en los últimos veinte años. Siempre que es posible se sigue una estrategia comparativa. Por un lado, se han construido series temporales que cubren todo el periodo estudiado y, por otro, se comparan las preferencias entre las políticas de bienestar y entre éstas y el resto de las políticas públicas. Las dos conclusiones más significativas son que, si bien con algunos matices, el apoyo a la provisión pública del bienestar continúa siendo muy sólido y crece también la preferencia por el nivel intermedio de gobierno como proveedor de tales programas de bienestar

Active Learning for Natural Language Generation

The field of text generation suffers from a severe shortage of labeled data due to the extremely expensive and time consuming process involved in manual annotation. A natural approach for coping with this problem is active learning (AL), a well-known machine learning technique for improving annotation efficiency by selectively choosing the most informative examples to label. However, while AL has been well-researched in the context of text classification, its application to text generation remained largely unexplored. In this paper, we present a first systematic study of active learning for text generation, considering a diverse set of tasks and multiple leading AL strategies. Our results indicate that existing AL strategies, despite their success in classification, are largely ineffective for the text generation scenario, and fail to consistently surpass the baseline of random example selection. We highlight some notable differences between the classification and generation scenarios, and analyze the selection behaviors of existing AL strategies. Our findings motivate exploring novel approaches for applying AL to NLG tasks

Efficient Benchmarking (of Language Models)

The increasing versatility of language models LMs has given rise to a new class of benchmarks that comprehensively assess a broad range of capabilities. Such benchmarks are associated with massive computational costs reaching thousands of GPU hours per model. However the efficiency aspect of these evaluation efforts had raised little discussion in the literature. In this work we present the problem of Efficient Benchmarking namely intelligently reducing the computation costs of LM evaluation without compromising reliability. Using the HELM benchmark as a test case we investigate how different benchmark design choices affect the computation-reliability tradeoff. We propose to evaluate the reliability of such decisions by using a new measure Decision Impact on Reliability DIoR for short. We find for example that the current leader on HELM may change by merely removing a low-ranked model from the benchmark and observe that a handful of examples suffice to obtain the correct benchmark ranking. Conversely a slightly different choice of HELM scenarios varies ranking widely. Based on our findings we outline a set of concrete recommendations for more efficient benchmark design and utilization practices leading to dramatic cost savings with minimal loss of benchmark reliability often reducing computation by x100 or more