Miracle-dz/UniFAR-FTUs huggingface dataset:
Data evaluation workshop of ICES WKAngHake: Benchmark Workshop on

Hake stocks in ICES area can be considered “data poor” stocks in terms of biological information, being this one of the main difficulties to get a good assessment model. Difficulties to estimate growth, as well as the usual problems in estimating M compromise a good quality assessment model. There is a need of increasing stocks assessed and improve the quality of existing assessments. However, there is a lot of biological information in similar species that can help to fill this gap. Life history invariants theory and hierarchical bayesian models can be combined to better understand biological processes needed in most stock assessment models (maturity, growth and natural mortality) providing the required parameters together with their statistical structure (posteriors). As an example of this approach we use the two European hake stocks in the Northeast Atlantic Ocean. The Bayesian hierarchical analysis provides posteriors for the main biological Linf, k and M. In the case of Southern hake, for which sex maturity at length data are available sex separated parameters are also provided. However, these results cannot be used directly in SS and further work is required to implement these in the SS model. Options to do it include fix some of them and allow SS to estimate others, use the posteriors as SS priors or combine these two options. Warning! An error in the data base of Merluccius information was found an we are now revising these data to guaranty that the selected records accomplish the quality required for this kind of analysis. Results presented here should be considered preliminary although the methodology proposed are the definite one.
Conceptualizing the Impact of Geographical Ignorance on Online Trip Planning

Abstract In this study, 28 participants with little geographical knowledge of the destination were asked to plan a week-long trip to China online. The participants were asked to create a detailed seven-day itinerary outline with activities or attractions they would like to participate in or visit, as well as restaurants in which they would like to dine. The participants were given a computer with internet access to conduct an online search to complete this task. Interestingly, despite an overall lack of geographical knowledge about China, few employed geographical learning techniques during the experiment. Specifically, most participants surrogated geographical knowledge for ‘geographical imaginations’ and they delegated geographical learning to dependence on recommendations from outside sources for their place knowledge. The results of this paper illustrate how participants' lack of their geographical knowledge and skills affected their trip planning, the strategies they used to cope with the ignorance and the effects on their trip plans. As a result of this research, recommendations to tourism marketers about how to address customers' lack of geographical knowledge are provided.
Predictable embedding of large data structures in multiprocessor networks-on-chip

Predictable, tile-based multiprocessor networks-on-chip are considered as future embedded systems platforms. Each tile contains one or a few processors and local memories. These memories are typically too small to store large data structures (e.g. a video frame). A solution to this is to embed tiles with large memories in the architecture. However, fetching data from these memories is slow because of the large network delays. The delay can be hidden by using prefetching. Our main contributions are models that allow timing analysis to provide guaranteed quality and performance when using remote memories and prefetching. We use two realistic video applications to show that our models can be used in practice to derive a predictable system using large memory tiles and prefetching, and to provide guaranteed real-time performance.
Inside the Family Firm: the Role of Families in Succession Decisions and Performance

This paper uses a unique dataset from Denmark to investigate the impact of family characteristics in corporate decision making and the consequences of these decisions on firm performance. We focus on the decision to appoint either a family or external chief executive officer (CEO). The paper uses variation in CEO succession decisions that result from the gender of a departing CEO's firstborn child. This is a plausible instrumental variable (IV), as male first-child firms are more likely to pass on control to a family CEO than are female first-child firms, but the gender of the first child is unlikely to affect firms' outcomes. We find that family successions have a large negative causal impact on firm performance: operating profitability on assets falls by at least four percentage points around CEO transitions. Our IV estimates are significantly larger than those obtained using ordinary least squares. Furthermore, we show that family-CEO underperformance is particularly large in fast-growing industries, industries with highly skilled labor force and relatively large firms. Overall, our empirical results demonstrate that professional, non-family CEOs provide extremely valuable services to the organizations they head. and Wolfenzon (dwolfenz@stern.nyu.edu). We thank three anonymous referees and Ed Glaeser and Larry Katz (the editors) for valuable comments. We also thank Entrepreneurial studies at Stern for comments. Pérez-González thanks Chicago-GSB for providing a stimulating research environment while writing this paper. We are grateful to the Berkley Center for Entrepreneurial Studies, CEBR and the Danish Social Science Research Foundation (project GOCOW) for financial support. We are also grateful to the Danish Commerce and Companies Agency and the Research Office in Statistics Denmark for providing us with data. We thank Frederik Vinten for excellent research assistance. All errors are our own.
Comments welcome Inside the Family Firm : The Role of Families in Succession Decisions and Performance *

This paper uses a unique dataset from Denmark to investigate (1) the role of family characteristics in corporate decision making, and (2) the consequences of these decisions on firm performance. We focus on the decision to appoint a family or an external chief executive officer (CEO). We show that departing CEO's family characteristics have a strong predictive power in explaining this choice: family CEOs are more frequently selected the larger the size of the family, the higher the ratio of sons to children and when the departing CEOs had only had one spouse. We then analyze the impact of family successions on performance. We overcome endogeneity and omitted variables problems of previous papers in the literature by using the gender of a departing CEO's first-born child as an instrumental variable (IV) for family successions. This is a plausible IV as male first-child family firms are more likely to pass on control to a family CEO than female first child families, but the gender of the first child is unlikely to affect firms' performance. We find that family successions have a dramatic negative causal impact on firm performance: profitability on assets falls by at least 6 percentage points around CEO transitions. These estimates are significantly larger than those obtained using ordinary least squares. Finally, our findings demonstrate that professional non-family CEOs provide extremely valuable services to the organizations they work for.
Inside the Family Firm

This paper uses a unique dataset from Denmark to investigate (1) the role of family characteristics in corporate decision making, and (2) the consequences of these decisions on firm performance. We focus on the decision to appoint either a family or an external chief executive officer (CEO). We show that a departing CEO’s family characteristics have a strong predictive power in explaining CEO succession decisions: family CEOs are more frequently selected the larger the size of the family, the higher the ratio of male children and when the departing CEOs had only had one spouse. We then analyze the impact of family successions on performance. We overcome endogeneity and omitted variables problems of previous papers in the literature by using the gender of a departing CEO’s first-born child as an instrumental variable (IV) for family successions. This is a plausible IV as male first-child family firms are more likely to pass on control to a family CEO than female first-child firms, but the gender of the first child is unlikely to affect firms’ performance. We find that family successions have a dramatic negative causal impact on firm performance: profitability on assets falls by at least 6 percentage points around CEO transitions. These estimates are significantly larger than those obtained using ordinary least squares. Finally, our findings demonstrate that professional non-family CEOs provide extremely valuable services to the organizations they work for. in firm profitability around CEO successions. Firm profitability industry adjusted EBIT / assets, as the difference between EBIT / assets and the average of its four-digit NACE (European industry classification system) benchmark. Changes in profitability are computed as the difference between the average three-year post-succession profitability minus the three-year average before transition. The year of is omitted. of the first-born child an indicator variable equal one if the first-born child of the departing is male, if she natural log book value of at of age difference between the of succession and establishment, year of or adjusted Assets (European benchmarks Danish Ministry of
Detecting Paleoclimate Transitions With Laplacian Eigenmaps of Recurrence Matrices (LERM)

Paleoclimate records can be considered low‐dimensional projections of the climate system that generated them. Understanding what these projections tell us about past climates, and changes in their dynamics, is a main goal of time series analysis on such records. Laplacian eigenmaps of recurrence matrices (LERM) is a novel technique using univariate paleoclimate time series data to indicate when notable shifts in dynamics have occurred. LERM leverages time delay embedding to construct a manifold that is mappable to the attractor of the climate system; this manifold can then be analyzed for significant dynamical transitions. Through numerical experiments with observed and synthetic data, LERM is applied to detect both gradual and abrupt regime transitions. Our paragon for gradual transitions is the Mid‐Pleistocene Transition (MPT). We show that LERM can robustly detect gradual MPT‐like transitions for sufficiently high signal‐to‐noise (S/N) ratios, though with a time lag related to the embedding process. Our paragon of abrupt transitions is the “8.2 ka” event; we find that LERM is generally robust at detecting 8.2 ka‐like transitions for sufficiently high S/N ratios, though edge effects become more influential. We conclude that LERM can usefully detect dynamical transitions in paleogeoscientific time series, with the caveat that false positive rates are high when dynamical transitions are not present, suggesting the importance of using multiple records to confirm the robustness of transitions. We share an open‐source Python package to facilitate the use of LERM in paleoclimatology and paleoceanography.
NBER WORKING PAPER SERIES EXCESS SAVINGS AND TWIN DEFICITS: THE TRANSMISSION OF FISCAL STIMULUS IN OPEN ECONOMIES

We study the effects of debt-financed fiscal transfers in a general equilibrium, heterogeneousagent model of the world economy. In the long run, increases in government debt anywhere raise the world interest rate and increase private wealth everywhere. In the short run, a country with a larger-than-average fiscal deficit experiences both a large increase in private savings (“excess savings”) and a small but persistent current account deficit (a slow-motion “twin deficit”). These patterns are consistent with the evolution of the world’s balance of payments since the beginning of the Covid pandemic. Rishabh Aggarwal Stanford University arishabh@stanford.edu Adrien Auclert Department of Economics Stanford University 579 Jane Stanford Way Stanford, CA 94305 and NBER aauclert@stanford.edu Matthew Rognlie Department of Economics Northwestern University 2211 Campus Drive Evanston, IL 60208 and NBER matthew.rognlie@northwestern.edu Ludwig Straub Department of Economics Harvard University Littauer 211 Cambridge, MA 02139 and NBER ludwigstraub@fas.harvard. edu
Reducing the determination errors of the international normalized ratio by using plasma cogulation calibrators

The objective was to use of a minimum number of ISI (International Sensitivity Index) to determine the International Normalized Ratio (INR). This specific calibration methods allowed to calculate ISI for all other thromboplastines comparative with the reference thromboplastine. Bigger values than 1 show a decrease sensitivity, as compared with the reference thromboplastine. The Prothrombin Time (PT) values are not the same in all laboratory because of differences in sensitivity of thromboplastins used. To standardize the same results in any laboratory, an INR (International Normalised Ratio) constant has been introduced. Estimation of thromboplastine sensitivity is useful in any laboratory involved in the medical control of therapy with AVK, being also helpull for the clinicians to find out a suitable curative dealing.
Mobility and diet in Neolithic, Bronze Age and Iron Age Germany : evidence from multiple isotope analysis

Prehistoric human diet can be reconstructed by the analysis of carbon (C), nitrogen (N) and sulphur (S) stable isotopes in bone, whereas ancient mobility and provenance can be studied using the isotopes of strontium (Sr) and oxygen (O) in tooth enamel, and of sulphur in bone. Although thirty years have passed since the first application of the stable isotope method to European skeletal material, gaps in biochemical research have remained within German archaeology. This dissertation seeks to fill these gaps by providing novel evidence from multiple isotope analyses in different transitional periods of German prehistory, including the earliest Neolithic farmers of the Linearbandkaramik culture, the Early Bronze Age necropolis site of Singen, and the elite burial population from the Early Iron Age site of Magdalenenberg. To assess the local characteristics of Sr isotopes in south-western Germany, environmental samples (n=93) were collected and analysed from the different geological formations between the Black Forest and Lake Constance. As a result of this work, these reference data are now available for future research. A substantial dataset of C and N isotopes was obtained from the human populations from the Linearbandkeramik sites of Derenburg, Halberstadt and Karsdorf (n=97) in Central Germany. The data provides information on early Neolithic subsistence and individual diet, and can be connected to evidence from a previous palaeogenetic study on lactose intolerance. Furthermore, the analysis of contemporary fauna (n=45) provides novel evidence on Neolithic livestock management strategies. The reconstruction of ancient mobility using the isotopes of Sr, O and S provided information on human provenance at the Early Bronze Age cemetery site of Singen. While the population had been considered mobile because of exotic grave goods found at the site, biochemical evidence suggests all sampled individuals (n=29) originated and lived locally in the region of Lake Constance. A very distinct pattern was found at the Early Iron Age monumental tumulus site of Magdalenenberg in the Black Forest. The results of Sr, O and S analyses in the skeletal remains (n=90) of this elite Hallstatt Culture burial population suggest various regions of human origin. Only a small proportion of the people originated locally. The majority of the burial population is derived from the Black Forest highlands or from the plains towards Lake Constance. In some cases, individual origin could be assigned to specific areas in the Alps and Italy through the application of various isotope systems.
A Climate Change Primer for Land Managers: An Example from the Sierra Nevada

Morelli, Toni Lyn; McGlinchy, Maureen C. ; Neilson, Ronald P. 2011. A climate change primer for land managers: an example from the Sierra Nevada. Res. Pap. PSW-RP-262. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station. 44 p. Interest in location-specific climate projections is growing. To facilitate the communication of these data, we provide here an example for how to present climate information relevant at the scale of a national forest. We summarize some of the latest data on climate change projections and impacts relevant to eastern California, from the global scale to the state level, then focus on the Sierra Nevada, and finally the Inyo National Forest. Most climate models project increased temperatures and reduced snow cover across most of the Sierra Nevada, potentially causing water shortages and cascading ecological impacts. For the Inyo National Forest, we provide MC1 Dynamic General Vegetation Model outputs projecting a reduction in the extent of alpine/subalpine ecosystems, an increase of woodlands and grasslands, and an emergence of novel desert habitat in eastern Sierra Nevada by the end of the 21 century. Finally, we offer resources and possible alternatives to land managers for climate change adaptation. Thus, our study provides climate change information for a specific management unit in the West as well as an example for other regions. We used this information as background for a climate-adaptation workshop held in Bishop, California, in 2009. This workshop was part of a Westwide Climate Initiative project to work with land managers to develop climate change adaptation options.
User Centered Design to Improve Information Exchange in Diabetes Care Through eHealth - Results from a Small Scale Exploratory Study

Heterogeneity of people with diabetes makes maintaining blood glucose control and achieving therapy adherence a challenge. It is fundamental that patients get actively involved in the management of the disease in their living environments. The objective of this paper is to present and evaluate the processes needed to build a supporting self-management system for diabetes in community settings. We used User Centered Design techniques for deﬁning and personalizing an eHealth solution for the management of diabetes, and assessing the use and compliance of a self-management system in a multicenter randomized pilot study. Particularly, User Centered Design principles were used to involve diabetic patients and treating professionals into the design, development and evaluation of a self-management system; which comprised three iterative cycles: scenario deﬁnition, user archetype deﬁnition and system development. A comprehensive system was developed integrating modules for the management of blood glucose levels, medication, food intake habits, physical activity, diabetes education and sending messages. The sys-G
A plan for hydrologic investigations of in situ, oil-shale retorting near Rock Springs, Wyoming

The recovery of shale oil by the in situ retort process may cause hydrologic impacts, the most significant being ground-water contamination and possible transport of contaminants into unaffected areas. Although these impacts are site-specific, many of the techniques used to investigate each retort operation commonly will be the same. The U.S. Geological Survey has begun a study of hydrologic impacts in the area of an in situ retort near Rock Springs, Wyoming, as a means of refining and demonstrating these techniques. Geologic investigations include determining the areal extent and thickness of aquifers. Emphasis will be placed on determining lithologic variations from geophysical logging. Hydrologic investigations include mapping of potentiometric surfaces, determining rates of ground-water discharge, and estimating aquifer properties by analytical techniques. Water-quality investigations include monitoring solute migration from the retort site and evaluating sampling techniques by standard statistical procedures. A ground-water-flow and solutetransport model will be developed to predict future movement of the solute plume away from the retort.
Ensuring a connected structure for Retinal Vessels Deep-Learning Segmentation

Retinal vessels identification plays a critical role in computer-aided diagnosis and analysis of fundus images. While Deep-Learning-based segmentation methods have shown remarkable performances in handling detailed and pathological fundus, they produce disconnected components whereas retinal vessels are a connected structure. In this work, we developed a post-processing pipeline to ensure a connected structure for the retinal vessels networks. The proposed pipeline named VNR for Vessels Network Retrieval, generates segmentations with a single connected component (CC). This is performed by removing artifacts that are pixels-miss-classified as retinal vessels, and by reconnecting branches that are well-classified but disconnected. By retrieving the structural coherence in the retinal vessels networks, we enable measurements such as vessels length, tortuosity and depth of the vessels tree structure in a more reliable manner. We evaluate our results using pixel-wise and structural metrics, comparing against manually labelled groundtruth. Before applying VNR the predicted segmentations had an average Dice score of 0.839 with 174 CCs. As a result, 173 CCs need to be deleted or reconnected. After applying VNR, the segmentations have an average Dice score of 0.840 with only 1 CC. VNR is thus able to retrieve the connected structure of the retinal vessels networks while also keeping or increasing pixel information.
In silico and in vitro identification of microRNAs that regulate HNF4A expression.

Hepatic nuclear factor 4 α (HNF4A) is a nuclear transcription factor that regulates the expression of many genes involved in drug disposition. To identify additional molecular mechanisms that regulate HNF4A, we identified microRNAs (miRNAs) that target HNF4A expression. In silico analyses suggested that HNF4A is targeted by many miRNAs. We conducted in vitro studies to validate several of these predictions. Using an HNF4A 3’UTR luciferase reporter assay, five out of six miRNAs tested significantly down-regulated (~20–40%) the luciferase activity. In HepG2 cells, miR-34a and miR-449a also down-regulated the expression of both the HNF4A protein and an HNF4A target gene, PXR (~30-40%). This regulation appeared without reduction in HNF4A mRNA expression, suggesting that they must be blocking HNF4A translation. Using additional bioinformatic algorithms, we identified polymorphisms that are predicted to alter the miRNA targeting of HNF4A. Luciferase assays indicated that miR-34a and miR-449a were less effective in regulating a variant (rs11574744) than the wildtype HNF4A 3’UTR. In vivo , although not statistically significant (p=0.16), subjects with the variant HNF4A had lower CYP2D6 enzyme activity. In conclusion, our findings demonstrate strong evidence for a role of miRNAs in the regulation of HNF4A.