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Characterisation of traditional Albanian breads derived from different cereals
The long isolation of Albania and the scarcity
of raw materials has traditionally led to the production of
bread from crops other than wheat, like maize, which is
the basic ingredient for maize bread (buk misri), rye,
which is used to prepare rye bread (buk thekre), and
chick-pea, used in chick-pea bread (buk me qiqre). Today,
these traditional breads are accompanied by other
types, such as brown bread from soft wheat (buk zize). In
the present work, the traditional Albanian breads were
characterised in order to assess their quality. The results
obtained indicated that the protein content reflected the
characteristics of the raw material used, being higher in
the chick-pea bread and in bread made from high extraction
rate wheat flour, while both fat and yellow pigment
levels were higher in maize bread. A high humidity
value was found in many of the breads examined, especially
in maize bread, with consequent risks of moulds
and a shortened shelf-life
Bread production in Albania: a quality assessment
In the present work the state of bread production in Albania was examined and fourteen types
of Albanian bread, from different zones of the country, were characterised with the aim of
assessing their quality. A big variety was observed both in the type of flours used and in the
range of the possible ingredients, such as seeds of different oleaginous crops, reflecting in
significant differences in the overall chemical-nutritional composition of the examined breads.
Besides, in the course of the study some types of traditional breads were also individuated and
described for the first time. The obtained results indicated that the protein content reflected
the characteristics of the raw material used, being higher in the chick-pea bread and in bread
from wholemeal wheat flour. The breads containing maize flour or seeds of sunflower and
pumpkin or olive oil in their dough showed a significantly higher content of both carotenoids
and fat than the other samples. A high humidity value was found for many of the examined breads, with consequent possible risks of moulds and, then, a short shelf-life
Modeling Human Motor Skills to Enhance Robots’ Physical Interaction
The need for users’ safety and technology acceptability has incredibly increased with the deployment of co-bots physically interacting with humans in industrial settings, and for people assistance. A well-studied approach to meet these requirements is to ensure human-like robot motions and interactions. In this manuscript, we present a research approach that moves from the understanding of human movements and derives usefull guidelines for the planning of arm movements and the learning of skills for physical interaction of robots with the surrounding environment
From humans to robots: The role of cutaneous impairment in human environmental constraint exploitation to inform the design of robotic hands
Human hands are capable of a variety of movements, thanks to their extraordinary biomechanical structure and relying on the richness of human tactile information. Recently, soft robotic hands have opened exciting possibilities and, at the same time, new issues related to planning and control. In this work, we propose to study human strategies in environmental constraint exploitation to grasp objects from a table. We have considered both the case where participants' fingertips were free and with a rigid shell worn on them to understand the role of cutaneous touch. Main kinematic strategies were quantified and classified in an unsupervised manner. The principal strategies appear to be consistent in both experimental conditions, although cluster cardinality differs. Furthermore, as expected, tactile feedback improves both grasp precision and quality performance. Results opens interesting perspective for sensing and control of soft manipulators
Deep learning techniques for modelling human manipulation and its translation for autonomous robotic grasping with soft end-effectors
One of the key enablers for the extraordinary dexterity of human hands is their compliance and capability to purposefully adapt with the environment and to multiply their manipulation possibilities. This observation has also produced a significant paradigm shift for the design of robotic hands, leading to the avenue of soft endeffectors that embed elastic and deformable elements directly in their mechanical architecture. This shift has also determined a perspective change for the control and planning of the grasping phases, with respect to (w.r.t.) the classical approach used with rigid grippers. Indeed, instead of targeting an accurate analysis of the contact points on the object, an approximated estimation of the relative hand-object pose is sufficient to generate successful grasps, exploiting the intrinsic adaptability of the robotic systems to overcome local uncertainties. This chapter reports on deep learning (DL) techniques used to model human manipulation and to successfully translate these modelling outcomes for enabling soft artificial hands to autonomous grasp objects with the environment. Chapter Contents: • 1.1 Introduction • 1.2 Investigation of the human example • 1.2.1 Methods • 1.2.2 Experiments • 1.2.2.1 Evaluation on ECE data set • 1.3 Autonomous grasping with anthropomorphic soft hands • 1.3.1 High level: deep classifier • 1.3.1.1 Object detection • 1.3.1.2 Primitive classification • 1.3.2 Transferring grasping primitives to robots • 1.3.3 Experimental setup • 1.3.3.1 Approach phase • 1.3.3.2 Grasp phase • 1.3.3.3 Control strategy • 1.3.4 Results • 1.4 Discussion and conclusions • Acknowledgement • References
Evaluation of tocopherols and tocotrienols in Albanian cultivars
Wheat is a major component in the human diet with an impact on nutritional health due to its significant intake. The aim of this study was to evaluate the quality of Albanian wheat by analysing chemical and nutrition parameters and understanding the health impact of
the components in wheat flour. Five winter wheat cultivars grown during the year 2017 - 2018 on experimental fields of Agriculture Technology Transfer Center (ATTC) in Lushnja were analysed. Protein
content (%N x 5.7) was determined by the Kjedahl method and lipid content was evaluated by Soxhlet extraction method utilizing n-hexane as solvent. The starch content was analyzed following the Megazyme
Starch determination procedure (Megazyme International, Ireland, Ltd). The determination of the total content of tocopherols (TP) and tocotrienols (TT) in the five wheat cultivars was carried out using the High Performance Liquid Chromatography (HPLC) analysis. A descriptive statistical analysis was performed for result elaboration. The analysis of variance (ANOVA) and Principal Component Analysis (PCA) was performed using StatSoft Statistica 10.0 software and the significant differences were calculated according to post - hoc Tukey’s (HSD) test at p ˂ 0.05. All cultivars showed higher level of protein content ranging from 11.39% to 12.38% and the starch content
ranging from 58% to 62%. Statistical results indicated that the protein content was significantly affected by the wheat cultivars. ɑ-Tocopherol and ß-tocotrienol were the most abundant compounds in all samples,
ranging, from 9.8 mg/kg DW to 15.6 mg/kg DW and from 8.1 mg/kg to 12.7 mg/kg DW, respectively. The daily requirement of vitamin E calculated in whole flour ranges from 14.7% to 26%.By selecting the
suitable wheat cultivars with high vitamin E content, we can contribute to increasing the content of vitamin E in Albanian wheat flour and supporting the problems of vitamin E deficiency in the human diet
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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