This paper attempts to fill a research gap of literature by constructing the dynamic model into which both ex ante and ex post patent value indicators are incorporated. A patent renewal model is tested using a large set of Pharmaceutical patents granted by the European Patent Office between 1996 and 2009. We test five ex ante indicators and single ex post indicator including family size, patent backward citations, backward references to non-patent literature, number of claims, number of inventors, renewal fee, patent age, application year, and the ex post indicator forward citations. Empirical findings show that three citation related indicators, family size, and the number of claims are positively associated with patent values, while the number of inventors, renewal fee, patent age, and application year are negatively correlated. In addition, forward citations seem to have persistent learning effects on patent values.

The global increase in the demand for fertilizers and thus phosphorus (P) contributes to the depletion of P reserves and the need to recycle this element. This paper presents the results of a pilot-scale experiment on the possibility of using a fertilizer preparation containing alginate, Fe and P (AFP) obtained in the process of P adsorption from sludge water on a hydrogel alginate adsorbent cross-linked with iron (III) ions. The influence of AFP on the growth of a model plant of the Italian ryegrass (Lolium perenne cv. Turtetra) was examined in comparison with differentiated mineral fertilization (MF) under the conditions of a pot experiment. The two fertilizers produced similar crop yields of the tested plant and had similar plant and soil macro- and micro-elements, except for the content of Fe and Cu in ryegrass, which was significantly higher with AFP fertilization. Further research on the use of the proposed sorbent for large-scale P recycling in an uncontrolled field environment should include acceptable limits for multivalent metal concentrations in wastewater, the mechanical/thermal stability, and the effectiveness of AFP under field conditions and a cost competitiveness. AFP has the potential to compete with mineral fertilizers for P fertilization, and this technology is in line with the EU circular economy vision.

Wastewater is characterized by a high content of phosphate and toxic metals. Many studies have confirmed the sorption affinity of alginate adsorbents for these ions. In this study, the adsorption of phosphate from effluent of sewage sludge on biodegradable alginate matrices cross-linked with Fe3+ ions (Fe_Alg) was investigated. Kinetics and adsorption isotherms were tested in laboratory conditions in deionized water (DW_P) and in the effluent (SW_P), and in the same solutions enriched in toxic metals ions—Cu2+, Cd2+, Pb2+, and Zn2+ (DW_PM and SW_PM). Batch experiments were performed by changing the concentration of phosphate at constant metal concentration. Kinetics experiments indicated that the pseudo-second-order model displayed the best correlation with adsorption kinetics data for both metals and phosphate. The Freundlich equation provided the best fit with the experimental results of phosphate adsorption from DW_P and DW_PM, while the adsorption from SD_P and SD_PM was better described by the Langmuir equation. For tested systems, the affinity of the Fe_Alg for metal ions was in the following decreasing order: Pb2+ > Cu2+ > Cd2+ > Zn2+ in DW_PM, and Pb2+ > Cu2+ > Cd2+ > Zn2+ in SW_PM. The metals’ enrichment of the DW_P solution increased the affinity of Fe_Alg beads relating to phosphate, while the addition of the metals of the SW_P solution decreased this affinity.

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The goal of this article was to perform analysis of usability possibilities of frontend framework AngularJS compared to native programming language JavaScript, on which it is based on. Several framework funcionalities were chosen and set together with self implemented solutions in JavaScript. Comparison was made according to specified criteria: usage simplicity, possibilities of utilization and reusability. Created scripts confirm accepted assumptions, that in JavaScript it is possible to write simplified and reusable implementations of useful mechanisms, which are present in AngularJS.

Modern vehicles contain a few controller area networks (CANs), which allow scores of on-board electronic control units (ECUs) to communicate messages critical to vehicle functions and driver safety. CAN provide a lightweight and reliable broadcast protocol but is bere of security features. As evidenced by many recent research works, CAN exploits are possible both remotely and with direct access, fueling a growing CAN intrusion detection system (IDS) body of research. A challenge for pioneering vehicle-agnostic IDSs is that passenger vehicles' CAN message encodings are proprietary, de ned and held secret by original equipment manufacturers (OEMs). Targeting detection of next-generation a acks, in which messages are sent from the expected ECU at the expected time but with malicious content, researchers are now seeking to leverage "CAN data models", which predict future CAN message contents and use prediction error to identify anomalous, hopefully malicious CAN messages. Yet, current works model CAN signals posttranslation, i.e., a er applying OEM-donated or reverse-engineered translations from raw data. In this work, we present initial IDS results testing deep neural networks used to predict CAN data at the bit level, thereby providing IDS capabilities but avoiding reverse engineering proprietary encodings. Our results suggest the method is promising for continuous signals in CAN data, but struggles for discrete, e.g., binary, signals. CCS CONCEPTS•Security and privacy →Arti cial immune systems;