Female vs Males inmates: Authors' reply and sample size calculation

Bruno and colleagues highlighted the relatively low absolute-percentage of psychiatric morbidity that we found in our sample, as compared to their male sample. They invited to the use of diagnostic tools, specific for personality disorders and suicidal risk factors, to better investigate these critical issues. In summary, our results showed high percentages of psychiatric morbidity (44%), especially anxiety and depression. Female inmates declared to be most stressed by the distance from family and loved ones, and they did not present any antisocial personality diagnosis. They also showed a resilient reaction to their situation, because more than a half of women requested a supportive psychological therapy during their detention (14/25= 56%), and 10 of them were those with a psychiatric disorder (10/11= 90.9%), thus a higher proportion than those reported in male detainees at the Messina jail (56%), by Zoccali and colleagues (Zoccali et al., 2008). As we have acknowledged, we could further explore other personality disorders and not merely the antisocial personality pathological traits, as we did in our study. In conclusion, we agree with them about the need to repeat the screening for mental health and a deeper ascertainment of specific suicidal risk factors, with an adequate sample. Nonetheless, we believe that our data were not biased, and likely represented the psychological asset of the ladies’ detainee with a final sentence at the Pagliarelli jail of Palermo

Head Tracking via Robust Registration in Texture Map Images

A novel method for 3D head tracking in the presence of large head rotations and facial expression changes is described. Tracking is formulated in terms of color image registration in the texture map of a 3D surface model. Model appearance is recursively updated via image mosaicking in the texture map as the head orientation varies. The resulting dynamic texture map provides a stabilized view of the face that can be used as input to many existing 2D techniques for face recognition, facial expressions analysis, lip reading, and eye tracking. Parameters are estimated via a robust minimization procedure; this provides robustness to occlusions, wrinkles, shadows, and specular highlights. The system was tested on a variety of sequences taken with low quality, uncalibrated video cameras. Experimental results are reported

Selective polyfunctional synthesis through organoboron compounds

La primera part d’aquesta tesi aborda el tema de la b-boració d’iminas α,β-insaturades per la síntesi de γ-amino alcohols. Es descriu un nou mètode basat en la organocatàlisi, evitand la ultilizació de metalls de transició com catalizadors. En aquest cas el reactiu bis(pinacolat)diboron s’activa amb una base i MeOH generand in situ un bor nucleòfil que interacciona amb el doble enllaç d’imines α,β-insaturades, com sustrat acceptor. La ultilizació de fosfina és necessaria per activar el sustrat. En el cas de que la fosfina és (S)-MeBoPhoz la β-boración es produeix de forma enantioselectiva amb excessos enantiomèrics fins 70%. Una major diastereoselectividad s’obte despres de la reducció i oxidació per la formació del compost dessitjat γ-amino alcohol. De manera interesant, es pot dir que en pressència de catalitzadors de Cu, la utilización de aquesta mateixa fosfina como lligand, la enenatioselectivitat baixa fins valors moderats. S’ha tractat de utilizar aquesta mateixa via de síntesi per la preparació d’un compost bioactiu como el Tramadol. El capítulo 3, tracta d’aquesta síntesi i a pesar de que molts sistemas catalítics han estat considerats, cap ha donat un producte final òptim. La darrera part d’aquesta tesis tracta de la inserció d’un sistema diazo, tal como (trimetilsilil)diazometà), per generar compostos gem-diborans. El tractament dels compuestos gem-diborans com a bases litiadas, LiTMP, van genrar un carbanió estable el qual pot atacar compostos carbonílics como cetonas per donar lloc a la B-O eliminació via Peterson, i generar olefines gem-sililborans. Posterior funcionalizació, via Suzuki-Miyaura cross-coupling, ha estat demostrada en aquesta tesis. Més innovador ha resultat el process d’iododesililació, que ha permés la síntesi d’olefinas tetrasustituidas despres de dos acoplamients creuats selectius. S’ha pogut concluir la tesis amb la preparació de (E)-Tamoxifen amb elevats valors de selectivitat ( E/Z = 90:10).La primera parte de esta tesis cubre el tema de la b-boración de iminas α,β-insaturadas para la síntesis de γ-amino alcoholes. Se describe un nuevo método basado en la organocatalisis, evitando la ultilización de metales de transición como catalizadores. En este caso el reactivo bis(pinacolato)diboron se activa con una base y MeOH generando in situ un boro nucleófilo que interacciona con el doble enlace de iminas α,β-insaturadas, como sustrato aceptor. La ultilización de fosfina es necesaria para activar el sustrato. Cuando la fosfina es (S)-MeBoPhoz la β-boración se produce de forma enantioselectiva con excesos enantiomericos hasta 70%. Una mayor diastereoselectividad se obtiene despues de la reducción y oxidación para la formación del compuesto deseado γ-amino alcohol. De manera interesante, se debe decir que en presencia de catalidores de Cu, la utilización de esta misma fosfina como ligando, la enenatioselectividad bajó hasta valores moderados. Se ha tratado de utilizar esta misma via de síntesis para la preparación de un compuesto bioactivo como el Tramadol. El capítulo 3, trata de esta síntesis y a pesar de que muchos sistemas catalíticos se han considerado, ninguno ha dado un producto final deseado. La última parte de esta tesis trata de la inserción de un sistema diazo, tal como (trimetilsilil)diazometano), para generar compuestos gem-diboranos. El tratamiento de los compuestos gem-diboranos con bases litiadas, tales como LiTMP, generaron un carbanion estabilizado el cual puede atacar compuestos carbonílicos como cetonas para dar lugar a la B-O eliminacion via Peterson, y dar lugar a las olefinas gem-sililboranos. Posterior funcionalización, via Suzuki-Miyaura cross-coupling, has sido demostrada en esta tesis. Incluso más innovador ha resultado el proceso de iododesililación, permitiendo la síntesis de olefinas tetrasustituidas despues de dos acoplamientos cruzados selectivos. Se ha podido concluir la tesis con la preparación de (E)-Tamoxifen con elevados valores de selectividad ( E/Z = 90:10).The first part covered the topic of the β-boration reaction towards the synthesis of γ-amino alcohols. A new metal-free approach to the β-borylation of α,β-unsaturated imines generated in situ has been reported. In this case the diboron compound, bis(pinacolato)diboron, is activated by a base/MeOH system which generates a nucleophilic boron moiety that can interact with a α,β-unsaturated acceptor (imine). This latter is activated by a catalytic amount of phosphine. When a chiral phosphine such as (S)-MeBoPhoz is used, the β-borylation can be performed in an enantioselective manner with ee values up to 70%. After a high diasteroselective protocol of reduction and oxidation we could provide the desired γ-amino alcohol. Interestingly, when a copper salt is modified with the (S)-MeBoPhoz ligand the enantioselectivities dropped showing generally lower values of ee than the organocatalytic approach. It has been tried to apply this chemistry to the synthesis of bioactive compounds such as Tramadol This part of the manuscript covered the attempts that were made to achieve the total synthesis. Many catalytic systems have been tried but unfortunately, none of them had positive results. The last part of the thesis is based on the insertion of a diazocompound, such as (trimethylsilyl)diazomethane), to generate the gem-diboron compound 18. The treatment of compound 18 with a lithiated base, such as LiTMP, generated a stabilized carbanion which can attack carbonyl compounds like ketones to afford, after a Peterson-type B-O elimination, a gem-silylboron olefin. We demonstrated that further functionalizations, suck as Suzuki-Miyaura cross-coupling, could be performed. Even the more challenging iododesilylation was successfully allowing the synthesis of tetrasubstituted olefins after two consecutive cross-couplings. Towards this aim, the synthesis of (E)-Tamoxifen was achieved with high values of selectivity (ratio E/Z = 90:10)

Mobile Interface for Content-Based Image Management

People make more and more use of digital image acquisition devices to capture screenshots of their everyday life. The growing number of personal pictures raise the problem of their classification. Some of the authors proposed an automatic technique for personal photo album management dealing with multiple aspects (i.e., people, time and background) in a homogenous way. In this paper we discuss a solution that allows mobile users to remotely access such technique by means of their mobile phones, almost from everywhere, in a pervasive fashion. This allows users to classify pictures they store on their devices. The whole solution is presented, with particular regard to the user interface implemented on the mobile phone, along with some experimental results

Keyword Based Keyframe Extraction in Online Video Collections

Keyframe extraction methods aim to find in a video sequence the most significant frames, according to specific criteria. In this paper we propose a new method to search, in a video database, for frames that are related to a given keyword, and to extract the best ones, according to a proposed quality factor. We first exploit a speech to text algorithm to extract automatic captions from all the video in a specific domain database. Then we select only those sequences (clips), whose captions include a given keyword, thus discarding a lot of information that is useless for our purposes. Each retrieved clip is then divided into shots, using a video segmentation method, that is based on the SURF descriptors and keypoints. The sentence of the caption is projected onto the segmented clip, and we select the shot that includes the input keyword. The selected shot is further inspected to find good quality and stable parts, and the frame which maximizes a quality metric is selected as the best and the most significant frame. We compare the proposed algorithm with another keyframe extraction method based on local features, in terms of Significance and Quality

Mean shift clustering for personal photo album organization

In this paper we propose a probabilistic approach for the automatic organization of pictures in personal photo album. Images are analyzed in term of faces and low-level visual features of the background. The description of the background is based on RGB color histogram and on Gabor filter energy accounting for texture information. The face descriptor is obtained by projection of detected and rectified faces on a common low dimensional eigenspace. Vectors representing faces and background are clustered in an unsupervised fashion exploiting a mean shift clustering technique. We observed that, given the peculiarity of the domain of personal photo libraries where most of the pictures contain faces of a relatively small number of different individuals, clusters tend to be not only visually but also semantically significant. Experimental results are reported

Video Object Recognition and Modeling by SIFT Matching Optimization

In this paper we present a novel technique for object modeling and object recognition in video. Given a set of videos containing 360 degrees views of objects we compute a model for each object, then we analyze short videos to determine if the object depicted in the video is one of the modeled objects. The object model is built from a video spanning a 360 degree view of the object taken against a uniform background. In order to create the object model, the proposed techniques selects a few representative frames from each video and local features of such frames. The object recognition is performed selecting a few frames from the query video, extracting local features from each frame and looking for matches in all the representative frames constituting the models of all the objects. If the number of matches exceed a fixed threshold the corresponding object is considered the recognized objects .To evaluate our approach we acquired a dataset of 25 videos representing 25 different objects and used these videos to build the objects model. Then we took 25 test videos containing only one of the known objects and 5 videos containing only unknown objects. Experiments showed that, despite a significant compression in the model, recognition results are satisfactory

Is text preprocessing still worth the time? A comparative survey on the influence of popular preprocessing methods on Transformers and traditional classifiers

With the advent of the modern pre-trained Transformers, the text preprocessing has started to be neglected and not specifically addressed in recent NLP literature. However, both from a linguistic and from a computer science point of view, we believe that even when using modern Transformers, text preprocessing can significantly impact on the performance of a classification model. We want to investigate and compare, through this study, how preprocessing impacts on the Text Classification (TC) performance of modern and traditional classification models. We report and discuss the preprocessing techniques found in the literature and their most recent variants or applications to address TC tasks in different domains. In order to assess how much the preprocessing affects classification performance, we apply the three top referenced preprocessing techniques (alone or in combination) to four publicly available datasets from different domains. Then, nine machine learning models – including modern Transformers – get the preprocessed text as input. The results presented show that an educated choice on the text preprocessing strategy to employ should be based on the task as well as on the model considered. Outcomes in this survey show that choosing the best preprocessing technique – in place of the worst – can significantly improve accuracy on the classification (up to 25%, as in the case of an XLNet on the IMDB dataset). In some cases, by means of a suitable preprocessing strategy, even a simple Naïve Bayes classifier proved to outperform (i.e., by 2% in accuracy) the best performing Transformer. We found that Transformers and traditional models exhibit a higher impact of the preprocessing on the TC performance. Our main findings are: (1) also on modern pre-trained language models, preprocessing can affect performance, depending on the datasets and on the preprocessing technique or combination of techniques used, (2) in some cases, using a proper preprocessing strategy, simple models can outperform Transformers on TC tasks, (3) similar classes of models exhibit similar level of sensitivity to text preprocessing