Iron porphyrin molecules on Cu(001): Influence of adlayers and ligands on the magnetic properties

The structural and magnetic properties of Fe octaethylporphyrin (OEP) molecules on Cu(001) have been investigated by means of density functional theory (DFT) methods and X-ray absorption spectroscopy. The molecules have been adsorbed on the bare metal surface and on an oxygen-covered surface, which shows a $\sqrt{2}\times2\sqrt{2}R45^{\circ}$ reconstruction. In order to allow for a direct comparison between magnetic moments obtained from sum-rule analysis and DFT we calculate the dipolar term $7$, which is also important in view of the magnetic anisotropy of the molecule. The measured X-ray magnetic circular dichroism shows a strong dependence on the photon incidence angle, which we could relate to a huge value of $7$, e.g. on Cu(001) $7$ amounts to -2.07\,\mbo{} for normal incidence leading to a reduction of the effective spin moment $m_s + 7$. Calculations have also been performed to study the influence of possible ligands such as Cl and O atoms on the magnetic properties of the molecule and the interaction between molecule and surface, because the experimental spectra display a clear dependence on the ligand, which is used to stabilize the molecule in the gas phase. Both types of ligands weaken the hybridization between surface and porphyrin molecule and change the magnetic spin state of the molecule, but the changes in the X-ray absorption are clearly related to residual Cl ligands.Comment: 17 figures, full articl

On the Inability of Markov Models to Capture Criticality in Human Mobility

We examine the non-Markovian nature of human mobility by exposing the inability of Markov models to capture criticality in human mobility. In particular, the assumed Markovian nature of mobility was used to establish a theoretical upper bound on the predictability of human mobility (expressed as a minimum error probability limit), based on temporally correlated entropy. Since its inception, this bound has been widely used and empirically validated using Markov chains. We show that recurrent-neural architectures can achieve significantly higher predictability, surpassing this widely used upper bound. In order to explain this anomaly, we shed light on several underlying assumptions in previous research works that has resulted in this bias. By evaluating the mobility predictability on real-world datasets, we show that human mobility exhibits scale-invariant long-range correlations, bearing similarity to a power-law decay. This is in contrast to the initial assumption that human mobility follows an exponential decay. This assumption of exponential decay coupled with Lempel-Ziv compression in computing Fano's inequality has led to an inaccurate estimation of the predictability upper bound. We show that this approach inflates the entropy, consequently lowering the upper bound on human mobility predictability. We finally highlight that this approach tends to overlook long-range correlations in human mobility. This explains why recurrent-neural architectures that are designed to handle long-range structural correlations surpass the previously computed upper bound on mobility predictability

Quantifying Social Influence in an Online Cultural Market

We revisit experimental data from an online cultural market in which 14,000 users interact to download songs, and develop a simple model that can explain seemingly complex outcomes. Our results suggest that individual behavior is characterized by a two-step process–the decision to sample and the decision to download a song. Contrary to conventional wisdom, social influence is material to the first step only. The model also identifies the role of placement in mediating social signals, and suggests that in this market with anonymous feedback cues, social influence serves an informational rather than normative role

Discovering temporal regularities in retail customers’ shopping behavior

In this paper we investigate the regularities characterizing the temporal purchasing behavior of the customers of a retail market chain. Most of the literature studying purchasing behavior focuses on what customers buy while giving few importance to the temporal dimension. As a consequence, the state of the art does not allow capturing which are the temporal purchasing patterns of each customers. These patterns should describe the customerâ\u80\u99s temporal habits highlighting when she typically makes a purchase in correlation with information about the amount of expenditure, number of purchased items and other similar aggregates. This knowledge could be exploited for different scopes: set temporal discounts for making the purchases of customers more regular with respect the time, set personalized discounts in the day and time window preferred by the customer, provide recommendations for shopping time schedule, etc. To this aim, we introduce a framework for extracting from personal retail data a temporal purchasing profile able to summarize whether and when a customer makes her distinctive purchases. The individual profile describes a set of regular and characterizing shopping behavioral patterns, and the sequences in which these patterns take place. We show how to compare different customers by providing a collective perspective to their individual profiles, and how to group the customers with respect to these comparable profiles. By analyzing real datasets containing millions of shopping sessions we found that there is a limited number of patterns summarizing the temporal purchasing behavior of all the customers, and that they are sequentially followed in a finite number of ways. Moreover, we recognized regular customers characterized by a small number of temporal purchasing behaviors, and changing customers characterized by various types of temporal purchasing behaviors. Finally, we discuss on how the profiles can be exploited both by customers to enable personalized services, and by the retail market chain for providing tailored discounts based on temporal purchasing regularity

Diagnostic role of new Doppler index in assessment of renal artery stenosis

BACKGROUND: Renal artery stenosis (RAS) is one of the main causes of secondary systemic arterial hypertension. Several non-invasive diagnostic methods for RAS have been used in hypertensive patients, such as color Doppler ultrasound (US). The aim of this study was to assess the sensitivity and specificity of a new renal Doppler US direct-method parameter: the renal-renal ratio (RRR), and compare with the sensitivity and specificity of direct-method conventional parameters: renal peak systolic velocity (RPSV) and renal aortic ratio (RAR), for the diagnosis of severe RAS. METHODS: Our study group included 34 patients with severe arterial hypertension (21 males and 13 females), mean age 54 (± 8.92) years old consecutively evaluated by renal color Doppler ultrasound (US) for significant RAS diagnosis. All of them underwent digital subtraction arteriography (DSA). RAS was significant if a diameter reduction > 50% was found. The parameters measured were: RPSV, RAR and RRR. The RRR was defined as the ratio between RPSV at the proximal or mid segment of the renal artery and RPSV measured at the distal segment of the renal artery. The sensitivity and specificity cutoff for the new RRR was calculated and compared with the sensitivity and specificity of RPSV and RAR. RESULTS: The accuracy of the direct method parameters for significant RAS were: RPSV >200 cm/s with 97% sensitivity, 72% specificity, 81% positive predictive value and 95% negative predictive value; RAR >3 with 77% sensitivity, 90% specificity, 90% positive predictive value and 76% negative predictive value. The optimal sensitivity and specificity cutoff for the new RRR was >2.7 with 97% sensitivity (p < 0.004) and 96% specificity (p < 0.02), with 97% positive predictive value and 97% negative predictive value. CONCLUSION: The new RRR has improved specificity compared with the direct method conventional parameters (RPSV >200cm/s and RAR >3). Both RRR and RPSV show better sensitivity than RAR for the RAS diagnosis

Working Group on Biological Parameters (WGBIOP) 2021

The main objective of the Working Group on Biological Parameters (WGBIOP) is to review the status, issues, developments, and quality assurance of biological parameters used in assessment and management. WGBIOP (1) plans workshops, exchanges, and validation studies on a range of biological varia-bles to review the quality of information supplied for stock assessment and improve quality as-surance and training; (2) investigates data availability and develops documentation and methods to improve communication between data collectors and end-users; (3) delivers new and im-proved functionality for the SmartDots platform. Four otolith exchanges and two workshops were completed in 2020–2021 using SmartDots— eight further exchanges are ongoing. Proposed future exchanges and workshops were reviewed and approved. The development of the SmartDots platform proceeded with the inclusion of the maturity, eggs, atresia, fecundity, and larval identification modules into the software version. A live SmartDots tutorial for event coordinators was conducted. Work to further develop quality assurance guidelines—and review national applications of these—progressed. Age and maturity validation studies were reviewed and a new method for prioritizing future validation work was proposed. Progress with the Stock Identification Database (SID) was reviewed, and the potential for creating a WGBIOP library collection and active involvement of WGBIOP in updating FishBase.org data were evaluated. The importance of identifying and documenting links be-tween all relevant databases and document repositories was identified, and a task to address this was initiated. Work on improving the feedback loop between data collectors and stock assessors on the usage and quality of biological parameters in stock assessment continued. Moving forward, WGBIOP aims to continue collaboration with WGALES and WGSMART on the development of the SmartDots platform, encouraging cross-group sharing of skills and ex-perience to optimize results. WGBIOP aims to improve accessibility to its outputs through up-dates to SID and FishBase.org, and the potential creation of a WGBIOP library collection. WGBIOP hopes to improve two-way communication between data collectors and end-users around the quality and utility of biological parameters used in assessment. WGBIOP also aims to amalgamate all validation activities into one coherent workstream.ICE