Food waste has been widely valorized in the past years in order to develop eco-friendly materials... more Food waste has been widely valorized in the past years in order to develop eco-friendly materials. Among others, bread waste is currently of increasing interest, as it is considered a huge global issue with serious environmental impacts and significant economic losses that have become even greater in the post-pandemic years due to an increase in cereal prices, which has led to higher production costs and bread prices. Owing to its richness in polysaccharides, bread waste has been previously studied for its physico-chemical characteristics and its numerous biotechnological applications. The present review highlights the re-use of bread waste and its valorization as a valuable resource by making value-added products through numerous technological processes to increase efficiency at all stages. Many research studies reporting several transformation methods of surplus bread into ethanol, lactic acid, succinic acid, biohydrogen, hydroxymethylfurfural, proteins and pigments, glucose–fruct...
Background: There has been increasing evidence and support for the use of digital technology in t... more Background: There has been increasing evidence and support for the use of digital technology in the cognitive health field. Despite the growing use of innovative digital technology to assess cognitive function, such technology remains scarce in Arabic countries, particularly in Tunisia. Objective: To investigate the effectiveness of a digitally delivered cognitive assessment battery in differentiating varying degrees of cognitive function in older Tunisian adults. Methods: One hundred fifty-five Tunisian older adults (age: 62.24±7.52 years) were assigned to one of four groups: healthy controls (HC), at-risk (AR), mild cognitive impairment (MCI), and Alzheimer’s disease (AD). Participants completed a translated version of the Neurotrack digital cognitive battery. Results: The AD group performed significantly lower on the associative learning (p = 0.01) and associative memory assessments (p = 0.002), than the HC and AR groups. The AD group also performed worse on the inhibition measur...
We propose a supervised approach to detect falls in home environment using an optimised descripto... more We propose a supervised approach to detect falls in home environment using an optimised descriptor adapted to real-time tasks. We introduce a realistic dataset of 191 videos, a new metric allowing to evaluate fall detection performance in a video stream, and an automatically optimised set of spatio-temporal descriptors which fed a supervised classifier. We build the initial spatio-temporal descriptor named ST HF using several combinations of transformations of geometrical features (height and width of human body bounding box, the user's trajectory with her/his orientation, projection histograms and moments of order 0, 1 and 2). We study the combinations of usual transformations of the features (Fourier Transform, Wavelet transform, first and second derivatives), and we show experimentally that it is possible to achieve high performance using Support Vector Machine and Adaboost classifiers. Automatic feature selection allows to show that the best tradeoff between classification performance and processing time is obtained combining the original low-level features with their first derivative. Hence, we evaluate the robustness of the fall detection regarding location changes. We propose a realistic and pragmatic protocol which enables performance to be improved by updating the training in the current location with normal activities records.
Non-standard heat treatments, i.e. 68°C 2.5 min-1 , 75°C 10 min-1 and 100°C 5 min-1 , were applie... more Non-standard heat treatments, i.e. 68°C 2.5 min-1 , 75°C 10 min-1 and 100°C 5 min-1 , were applied to evaluate the effects on physicochemical and microbiological characteristics of donkey milk compared to bovine milk. The most significant (P<0.05) changes were the decrease of pH, the increase of casein nitrogen and the denaturation degree of whey proteins, which exceeded 80% in donkey milk compared to about 66% in bovine milk, at 100°C 5 min-1. Conversely, calcium and phosphorus were more heat stable in donkey milk than in bovine milk. Hydroxymethylfurfural (HMF) resulted absent in donkey milk. Significant changes in free fatty acids (FFA) were observed in both heated milks, although donkey milk showed lower lipolysis rates. The lysozyme activity of donkey milk was inversely related to the intensity of heat treatments but even at 100°C 5 min-1 a relevant activity was still observed.
Food waste has been widely valorized in the past years in order to develop eco-friendly materials... more Food waste has been widely valorized in the past years in order to develop eco-friendly materials. Among others, bread waste is currently of increasing interest, as it is considered a huge global issue with serious environmental impacts and significant economic losses that have become even greater in the post-pandemic years due to an increase in cereal prices, which has led to higher production costs and bread prices. Owing to its richness in polysaccharides, bread waste has been previously studied for its physico-chemical characteristics and its numerous biotechnological applications. The present review highlights the re-use of bread waste and its valorization as a valuable resource by making value-added products through numerous technological processes to increase efficiency at all stages. Many research studies reporting several transformation methods of surplus bread into ethanol, lactic acid, succinic acid, biohydrogen, hydroxymethylfurfural, proteins and pigments, glucose–fruct...
Background: There has been increasing evidence and support for the use of digital technology in t... more Background: There has been increasing evidence and support for the use of digital technology in the cognitive health field. Despite the growing use of innovative digital technology to assess cognitive function, such technology remains scarce in Arabic countries, particularly in Tunisia. Objective: To investigate the effectiveness of a digitally delivered cognitive assessment battery in differentiating varying degrees of cognitive function in older Tunisian adults. Methods: One hundred fifty-five Tunisian older adults (age: 62.24±7.52 years) were assigned to one of four groups: healthy controls (HC), at-risk (AR), mild cognitive impairment (MCI), and Alzheimer’s disease (AD). Participants completed a translated version of the Neurotrack digital cognitive battery. Results: The AD group performed significantly lower on the associative learning (p = 0.01) and associative memory assessments (p = 0.002), than the HC and AR groups. The AD group also performed worse on the inhibition measur...
We propose a supervised approach to detect falls in home environment using an optimised descripto... more We propose a supervised approach to detect falls in home environment using an optimised descriptor adapted to real-time tasks. We introduce a realistic dataset of 191 videos, a new metric allowing to evaluate fall detection performance in a video stream, and an automatically optimised set of spatio-temporal descriptors which fed a supervised classifier. We build the initial spatio-temporal descriptor named ST HF using several combinations of transformations of geometrical features (height and width of human body bounding box, the user's trajectory with her/his orientation, projection histograms and moments of order 0, 1 and 2). We study the combinations of usual transformations of the features (Fourier Transform, Wavelet transform, first and second derivatives), and we show experimentally that it is possible to achieve high performance using Support Vector Machine and Adaboost classifiers. Automatic feature selection allows to show that the best tradeoff between classification performance and processing time is obtained combining the original low-level features with their first derivative. Hence, we evaluate the robustness of the fall detection regarding location changes. We propose a realistic and pragmatic protocol which enables performance to be improved by updating the training in the current location with normal activities records.
Non-standard heat treatments, i.e. 68°C 2.5 min-1 , 75°C 10 min-1 and 100°C 5 min-1 , were applie... more Non-standard heat treatments, i.e. 68°C 2.5 min-1 , 75°C 10 min-1 and 100°C 5 min-1 , were applied to evaluate the effects on physicochemical and microbiological characteristics of donkey milk compared to bovine milk. The most significant (P<0.05) changes were the decrease of pH, the increase of casein nitrogen and the denaturation degree of whey proteins, which exceeded 80% in donkey milk compared to about 66% in bovine milk, at 100°C 5 min-1. Conversely, calcium and phosphorus were more heat stable in donkey milk than in bovine milk. Hydroxymethylfurfural (HMF) resulted absent in donkey milk. Significant changes in free fatty acids (FFA) were observed in both heated milks, although donkey milk showed lower lipolysis rates. The lysozyme activity of donkey milk was inversely related to the intensity of heat treatments but even at 100°C 5 min-1 a relevant activity was still observed.
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