Abstract
The increasing world population, growing need for agricultural products, and labour shortages have driven the growth of robotics in agriculture. Tasks such as fruit harvesting require extensive hours of work during harvest periods and can be physically exhausting. Autonomous robots bring more efficiency to agricultural tasks with the possibility of working continuously. This paper proposes a stackable 3 DoF SCARA manipulator for tomato harvesting. The manipulator uses a custom electronic circuit to control DC motors with an endless gear at each joint and uses a camera and a Tensor Processing Unit (TPU) for fruit detection. Cascaded PID controllers are used to control the joints with magnetic encoders for rotational feedback, and a time-of-flight sensor for prismatic movement feedback. Tomatoes are detected using an algorithm that finds regions of interest with the red colour present and sends these regions of interest to an image classifier that evaluates whether or not a tomato is present. With this, the system calculates the position of the tomato using stereo vision obtained from a monocular camera combined with the prismatic movement of the manipulator. As a result, the manipulator was able to position itself very close to the target in less than 3 seconds, where an end-effector could adjust its position for the picking.

Abstract
A distinctive feature of this review is a critical analysis of methods and results of measurements of the optical properties of tissues in a wide spectral range from deep UV to terahertz waves. Much attention is paid to measurements of the refractive index of biological tissues and liquids, the knowledge of which is necessary for the effective application of many methods of optical imaging and diagnostics. The optical parameters of healthy and pathological tissues are presented, and the reasons for their differences are discussed, which is important for the discrimination of pathologies and the demarcation of their boundaries. When considering the interaction of terahertz radiation with tissues, the concept of an effective medium is discussed, and relaxation models of the effective optical properties of tissues are presented. Attention is drawn to the manifestation of the scattering properties of tissues in the THz range and the problems of measuring the optical properties of tissues in this range are discussed. In conclusion, a method for the dynamic analysis of the optical properties of tissues under optical clearing using an application of immersion agents is presented. The main mechanisms and technologies of optical clearing, as well as examples of the successful application for differentiation of healthy and pathological tissues, are analyzed. (c) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

Abstract
As gamification spreads to new areas, new applications are being developed and the interest in evaluating gamified systems continues to grow. To date, however, no one has comprehensively approached this topic: multiple evaluation dimensions and measures have been proposed and applied without any effort to organize them into a full gamut of tools for the multi-dimensional evaluation of gamified systems. This paper addresses this gap by proposing GATUGU, a set of six perspectives of evaluation of gamified systems: General effects of gamification, Area-specific effects of gamification, Technical quality of gamified systems, Use of gamified systems, Gamefulness of gamified systems, and User experience of gamified systems. For each perspective, GATUGU indicates the relevant dimensions of evaluation, and, for each dimension, one measure is suggested. GATUGU does not introduce any new measurement tools but merely recommends one of the available tools for each dimension, considering their popularity and ease of use. GATUGU can guide researchers in selecting gamification system evaluation perspectives and dimensions and in finding adequate measurement tools. Thanks to conforming to GATUGU, the published gamification system evaluation results will become easier to compare and to perform various kinds of meta-analyses on them.

Abstract
Temporal expression identification is crucial for understanding texts written in natural language. Although highly effective systems such as HeidelTime exist, their limited runtime performance hampers adoption in large-scale applications and production environments. In this paper, we introduce the TEI2GO models, matching HeidelTime's effectiveness but with significantly improved runtime, supporting six languages, and achieving state-of-the-art results in four of them. To train the TEI2GO models, we used a combination of manually annotated reference corpus and developed Professor HeidelTime, a comprehensive weakly labeled corpus of news texts annotated with HeidelTime. This corpus comprises a total of 138, 069 documents (over six languages) with 1, 050, 921 temporal expressions, the largest open-source annotated dataset for temporal expression identification to date. By describing how the models were produced, we aim to encourage the research community to further explore, refine, and extend the set of models to additional languages and domains. Code, annotations, and models are openly available for community exploration and use. The models are conveniently on HuggingFace for seamless integration and application.

Abstract

Abstract
In Europe, the Common Agricultural Policy (CAP) encouraged the specialisation of agriculture and forestry systems by supporting schemes that promoted productivity, despite the socio-ecological changes' detrimental effects on ecosystem services and biodiversity. In the case of mountain viticulture of southern Europe, the adoption of intensive management techniques triggered noticeable changes in farming systems, namely the removal of traditional stonewalls and semi-natural vegetation, partially compensated by eco schemes and agri-environment-climate measures. By combining fieldwork information with spatio-temporal modelling techniques, a novel hybrid framework is explained and implemented to predict the population trends of a critically en-dangered bird species in Portugal, the Black Wheatear (Oenanthe leucura), to the individual and/or combined effects of the removal of traditional stonewall terraced vineyards and the implementation of cover crops. The results obtained demonstrate the relevance of stonewall terraced vineyards (and the negative effects of their removal) for the conservation of Black Wheatear, namely during the breeding season when holes and crevices are used for nesting. Conversely, and in accordance with our simulations, the increase in the area occupied by vineyards with cover crops seems particularly detrimental for the species, by decreasing the quality of the feeding grounds. As cover crops, and possibly other eco schemes and agri-environment-climate measures, might not be the panacea for halting biodiversity loss in mountain viticulture, adaptation of measures to species' ecological requirements is urgent for a successful EU biodiversity strategy for 2030.