Unconstitutional supranational arrangements for patent law: leaving out the elected legislators and the people’s participatory rights

Substantive economic law in the context of patents creates industrial property rights and monopolies in almost all fields of technology, affecting considerably the economic and social well-being of the state and its people. The mass nationalisation of the international patents of the European Patent Office (EPO) has long raised serious questions about democratic control, in view of the reality that most of its patents are taken by large companies and corporations from a small number of states, mostly from outside the EU. The EU has recently expanded this system by creating a federal (unitary) patent framework consisting of the EPO and a new international court, the Unified Patent Court (UPC), that abolishes the already limited national control. But how can national control ever be totally abolished, especially in such an important social–economic context? And, can the EU exercise effective democratic control of the federal system that it has created? The observed constitutional asymmetries of a federal/unitary patent system that is created in the absence of a federation and is based on two non-EU bodies (EPO, UPC) no longer guarantee the democratic participatory rights of the people for whose benefit economic rules and property rights are justified, regulated and applied.     

A reinforcement learning approach for individualizing erythropoietin dosages in hemodialysis patients

This paper presents a reinforcement learning (RL) approach for anemia management in patients undergoing chronic renal failure. Erythropoietin (EPO) is the treatment of choice for this kind of anemia but it is an expensive drug and with some dangerous side-effects that should be considered especially for patients who do not respond to the treatment. Therefore, an individualized treatment appears to be necessary. RL is a suitable approach to tackle this problem. Moreover, resulting policies are similar to medical protocols, and hence, they can easily be transferred to daily practice. A cohort of 64 patients are included in the study. An implementation of the Q-learning algorithm based on a state-aggregation table and another implementation using the multi-layer perceptron as a function approximator (Q-MLP) are compared with the protocols followed in the Nephrology Unit. The policy obtained by the Q-MLP approach outperforms the hospital policy in terms of the ratio of patients that are within the targeted range of hemoglobin (11.5–12.5 g/dl) at the end of the analyzed period, since an increase of 25% is observed. It ensures an improvement in patients’ quality-of-life and considerable economic savings for the health care system due to both the expensiveness of EPO treatment and the costs incurred by the health care system in order to alleviate problems related to EPO over-dosing. It should be pointed out that the approach presented here is completely general, and therefore, it can be applied to any problem of drug dosage optimization.     

Online collaboration products

The European Patent Office cooperates closely with the national patent offices from the member states of the European Patent Organization as well as many nonmember states. The EPO's Information Systems-Research and Prototyping directorate recently surveyed the functionality of available collaboration tools. The study looked at three scenarios related to EPO functions. The first concerns patent examiners. The second scenario relates to the EPO task of raising awareness about patent information, concerning both the patent-granting procedure and the patent documents themselves. Another aspect of raising awareness involves promoting the EPO's patent information services and stimulating the use of patent information. This leads to the third scenario: online support for esp@cenet users.     

Policy Improvements for Probabilistic Pursuit-Evasion Game

This paper focuses on a pursuit-evasion game (PEG) which involves two teams: one side consists of pursuers trying to minimize the time required to capture evaders, and the other side consists of evaders trying to maximize the capture time by escaping the pursuers. In this paper, we propose a hybrid pursuit policy for a probabilistic PEG, which possesses the combined merits of local-max and global-max pursuit policies proposed in previous literature. A method to find optimal pursuit and evasion polices for two competitive parties of the pursuers and evaders is also proposed. For this, we employ an episodic parameter optimization (EPO) algorithm to learn good values for the weighting parameters of a hybrid pursuit policy and an intelligent evasion policy. The EPO algorithm is performed during the numerous repeated simulation runs of the PEG and the reward of each episode is updated using reinforcement learning, and the optimal weighting parameters are selected by using particle swarm optimization. We analyze the trend of the optimal parameter values with respect to the number of the pursuers and evaders. The proposed strategy is validated both in simulations and experiments with small ground robots.     

Leveraging Retinal Fundus Images with Deep Learning for Diabetic Retinopathy Grading and Classification

Recently, there has been a considerable rise in the number of diabetic patients suffering from diabetic retinopathy (DR). DR is one of the most chronic diseases and makes the key cause of vision loss in middle-aged people in the developed world. Initial detection of DR becomes necessary for decreasing the disease severity by making use of retinal fundus images. This article introduces a Deep Learning Enabled Large Scale Healthcare Decision Making for Diabetic Retinopathy (DLLSHDM-DR) on Retinal Fundus Images. The proposed DLLSHDM-DR technique intends to assist physicians with the DR decision-making method. In the DLLSHDM-DR technique, image preprocessing is initially performed to improve the quality of the fundus image. Besides, the DLLSHDM-DR applies HybridNet for producing a collection of feature vectors. For retinal image classification, the DLLSHDM-DR technique exploits the Emperor Penguin Optimizer (EPO) with a Deep Recurrent Neural Network (DRNN). The application of the EPO algorithm assists in the optimal adjustment of the hyperparameters related to the DRNN model for DR detection showing the novelty of our work. To assuring the improved performance of the DLLSHDM-DR model, a wide range of experiments was tested on the EyePACS dataset. The comparison outcomes assured the better performance of the DLLSHDM-DR approach over other DL models.     

Value Creation in a Network: The Role of Pricing and Revenue Optimization and Enterprise Profit OptimizationTM

The Internet has created a virtual upheaval in the structural features of the supply and demand chains for most businesses. New agents and marketplaces have surfaced. The potential to create value and enhance profitable opportunities has attracted both buyers and sellers to the Internet. Yet, the Internet has proven to be more complex than originally thought. With information comes complexity: the more the information in real time, the greater the difficulty in interpretation and absorption. How can the value-creating potential of the Internet still be realized, its complexity notwithstanding? This paper argues that with the emergence of innovative tools, the expectations of the Internet as a medium for enhanced profit opportunities can still be realized. Creating value on a continuing basis is central to sustaining profitable opportunities. This paper provides an overview of the value creation process in electronic networks, the emergence of the Internet as a viable business communication and collaboration medium, the proclamation by many that the future of the Internet resides in “embedded intelligence”, and the perspectives of pragmatists who point out the other facet of the Internet—its complexity. The paper then reviews some recent new tools that have emerged to address this complexity. In particular, the promise of Pricing and Revenue Optimization (PRO) and Enterprise Profit Optimization^TM (EPO) tools is discussed. The paper suggests that as buyers and sellers adopt EPO, the market will see the emergence of a truly intelligent network—a virtual network—of private and semi-public profitable communities.     

Technology evaluation through the use of interval type-2 fuzzy sets and systems

Even though fuzzy logic is one of the most common methodologies for matching different kind of data sources, there is no study which uses this methodology for matching publication and patent data within a technology evaluation framework according to the authors’ best knowledge. In order to fill this gap and to demonstrate the usefulness of fuzzy logic in technology evaluation, this study proposes a novel technology evaluation framework based on an advanced/improved version of fuzzy logic, namely; interval type-2 fuzzy sets and systems (IT2FSSs). This framework uses patent data obtained from the European Patent Office (EPO) and publication data obtained from Web of Science/Knowledge (WoS/K) to evaluate technology groups with respect to their trendiness. Since it has been decided to target technology groups, patent and publication data sources are matched through the use IT2FSSs. The proposed framework enables us to make a strategic evaluation which directs considerations to use-inspired basic researches, hence achieving science-based technological improvements which are more beneficial for society. A European Classification System (ECLA) class – H01-Basic Electric Elements – is evaluated by means of the proposed framework in order to demonstrate how it works. The influence of the use of IT2FSSs is investigated by comparison with the results of its type-1 counterpart. This method shows that the use of type-2 fuzzy sets, i.e. handling more uncertainty, improves technology evaluation outcomes.     

Searching in Cooperative Patent Classification: Comparison between keyword and concept-based search

International patent corpus is a gigantic source containing today about 80 million of documents. Every patent is manually analyzed by patent officers and then classified by a specific code called Patent Class (PC). Cooperative Patent Classification CPC is the new classification system introduced since January 2013 in order to standardize the classification systems of all major patent offices. Like keywords for papers, PCs point to the core of the invention, describing concisely what they contain inside. Most of patents strategies are based on PC as filter for results therefore the selection of relevant PCs is often a primary and crucial activity. This task is considered particularly challenging and only few tools have been specially developed for this purpose. The most efficient tools are provided by patent offices of EPO and WIPO.This paper analyzes their PCs search strategy (mainly based on keyword-based engines) in order to identify main limitations in terms of missing relevant PCs (recall) and non-relevant results (precision). Patents have been processed by KOM, a semantic patent search tool developed by the authors. Unlike all other PC search tools, KOM uses semantic parser and many knowledge bases for carrying out a conceptual patent search. Its functioning is described step by step through a detailed analysis pointing out the benefits of a concept-based search vis-à-vis a keyword-based search. An exemplary case is proposed dealing with CPCs describing the sterilization of contact lenses. Comparison could be likewise conducted on other PCs such as International (IPC), European (ECLA) or United States (USPC) patent classification codes.     

Even-order linear dynamic equations with mixed derivatives

We consider the time scale $k$th-order differential operators $D_k^{\Delta }y≔\{\begin{array}{cc}{y}^{\Delta \nabla \dots \Delta \nabla }& k\text{ even ,}\\ y^{\Delta \nabla \dots \nabla \Delta }& k\text{ odd ,}\end{array}{\tilde{D}}_k^{\Delta }y≔\{\begin{array}{cc}{y}^{\nabla \Delta \dots \nabla \Delta }& k\text{ even ,}\\ y^{\Delta \nabla \dots \nabla \Delta }& k\text{ odd ,}\end{array}$$D_k^{\nabla }y≔\{\begin{array}{cc}{y}^{\nabla \Delta \dots \nabla \Delta }& k\text{ even ,}\\ y^{\nabla \Delta \dots \Delta \nabla }& k\text{ odd ,}\end{array}{\tilde{D}}_k^{\nabla }y≔\{\begin{array}{cc}{y}^{\Delta \nabla \dots \Delta \nabla }& k\text{ even ,}\\ y^{\nabla \Delta \dots \Delta \nabla }& k\text{ odd ,}\end{array}$ and the higher-order dynamic equations $L\left(y\right)≔\sum _{\nu =0}^n{(-1)}^{\nu }{\tilde{D}}_{\nu }^{\nabla }\left(r_{\nu }\left(t\right)D_{\nu }^{\Delta }y\right)=0\text{,}$$M\left(y\right)≔\sum _{\nu =0}^n{(-1)}^{\nu }{\tilde{D}}_{\nu }^{\Delta }\left(r_{\nu }\left(t\right)D_{\nu }^{\nabla }y\right)=0\text{.}$ We will show that these equations can be investigated as special cases of the so-called (delta or nabla) symplectic dynamic systems $z^{\Delta }=S\left(t\right)z\text{,}{z}^{\nabla }=S\left(t\right)z\text{,}$ whose qualitative theory is well developed. We also suggest further perspectives of the investigation of the qualitative properties of higher-order equations with mixed derivatives.     

Suslin’s algorithms for reduction of unimodular rows

A well-known lemma of Suslin says that for a commutative ring $A$ if $(v_1\left(X\right),\dots ,v_n\left(X\right))\in {\left(A\left[X\right]\right)}^n$ is unimodular where $v_1$ is monic and $n\ge 3$, then there exist ${\gamma }_1,\dots ,{\gamma }_{\ell }\in E_{n-1}\left(A\left[X\right]\right)$ such that the ideal generated by $\mathrm{Res}(v_1,e_1.{\gamma }_1{}^t(v_2,\dots ,v_n)),\dots ,\mathrm{Res}(v_1,e_1.{\gamma }_{\ell }{}^t(v_2,\dots ,v_n))$ equals $A$. This lemma played a central role in the resolution of Serre’s Conjecture. In the case where $A$ contains a set $E$ of cardinality greater than $deg{v}_1+1$ such that $y-y^{\prime }$ is invertible for each $y\ne y^{\prime }$ in $E$, we prove that the ${\gamma }_i$ can simply correspond to the elementary operations $L_1\to L_1+y_i{\sum }_{j=2}^{n-1}{u}_{j+1}{L}_j$, $1\le i\le \ell =deg{v}_1+1$, where $u_1{v}_1+\cdots +u_n{v}_n=1$. These efficient elementary operations enable us to give new and simple algorithms for reducing unimodular rows with entries in $K[X_1,\dots ,X_k]$ to ${}^t(1,0,\dots ,0)$ using elementary operations in the case where $K$ is an infinite field. Another feature of this paper is that it shows that the concrete local–global principles can produce competitive complexity bounds.     

Relations between matrix sets generated from linear matrix expressions and their applications

Let $A+BXC$ and $A+BX+YC$ be two linear matrix expressions, and denote by $\{A+BXC\}$ and $\{A+BX+YC\}$ the collections of the two matrix expressions when $X$ and $Y$ run over the corresponding matrix spaces. In this paper, we study relationships between the two matrix sets $\{A_1+B_1{X}_1{C}_1\}$ and $\{A_2+B_2{X}_2{C}_2\}$, as well as the two sets $\{A_1+B_1{X}_1+Y_1{C}_1\}$ and $\{A_2+B_2{X}_2+Y_2{C}_2\}$, by using some rank formulas for matrices. In particular, we give necessary and sufficient conditions for the two matrix set inclusions $\{A_1+B_1{X}_1{C}_1\}?\{A_2+B_2{X}_2{C}_2\}$ and $\{A_1+B_1{X}_1+Y_1{C}_1\}?\{A_2+B_2{X}_2+Y_2{C}_2\}$ to hold. We also use the results obtained to characterize relations of solutions of some linear matrix equations.     

Innovation based on Gaussian elimination to compute generalized inverse AT,S(2)

In this paper, we execute elementary row and column operations on the partitioned matrix $\left(\begin{array}{cc}\hfill GAG\hfill & \hfill G\hfill \\ \hfill G\hfill & \hfill 0\hfill \end{array}\right)$ into $\left(\begin{array}{cc}\hfill \left(\begin{array}{cc}\hfill I_s\hfill & \hfill 0\hfill \\ \hfill 0\hfill & \hfill 0\hfill \end{array}\right)\hfill & \hfill 0\hfill \\ \hfill 0\hfill & \hfill ?A_{T,S}^{\left(2\right)}\hfill \end{array}\right)$to compute generalized inverse $A_{T,S}^{\left(2\right)}$ of a given complex matrix $A$, where $G$ is a matrix such that $R\left(G\right)=T$ and $N\left(G\right)=S$. The total number of multiplications and divisions operations is $T(m,n,s)=2m{n}^2+\frac{4m?s?1}{2}ns+(m?s)ns+mns$ and the upper bound of $T(m,n,s)$ is less than $6m{n}^2?\frac{3}{2}{n}^3?\frac{1}{2}{n}^2$ when $n\le m$. A numerical example is shown to illustrate that this method is correct.     

Existence of positive ground state solutions for a critical Kirchhoff type problem with sign-changing potential

In this work, we are interested in studying the following Kirchhoff type problem

where $\Omega ?{\mathbb{R}}^N(N\ge 3)$ is a smooth bounded domain, $2^1=\frac{2N}{N?2}$ is the critical Sobolev exponent, $0<q<1,\lambda >0$, and $f\in L^{\infty }\left(\Omega \right)$ with the set $\{x\in \Omega :f\left(x\right)>0\}$ of positive measures, and $g\in L^{\infty }\left(\Omega \right)$ with $g\left(x\right)\ge 0,g?0.$ By the Nehari method and variational method, the existence of positive ground state solutions is obtained.