Dear Colleagues,
We are conducting a brief survey to assess the current state of Arabic NLP
datasets and to explore the challenges involved in creating new ones.
The survey consists of *7 short-answer questions* and should take less than
5* minutes* of your time. Your insights will be invaluable in helping to
advance research and development in Arabic Natural Language Processing.
Please consider participating by following this link:
https://forms.gle/ukyGk9pEzegGtHW29
We truly appreciate your time and contribution to this important area of
research.
----
Wajdi Zaghouani, Ph.D.
Associate Professor,
Communication Program
Northwestern Qatar | Education City
T +974 4454 5232 | M +974 3345 4992
ูุณุฑูุง ุงูุงุนูุงู ุนู ู ุนุฌู ูุจุณ ุงูุญุงุณูุจู
We are very happy to release
๐๐๐๐๐ฌ - ๐๐ฉ๐๐ง-๐๐จ๐ฎ๐ซ๐๐ ๐๐๐ฑ๐ข๐๐จ๐ ๐ซ๐๐ฉ๐ก๐ข๐ ๐๐๐ญ๐๐๐๐ฌ๐
Qabas = 60k Lemmas + manually linked with 12 corpora (2.3 tokens) + 110 lexicons (~ 300k lemmas)
Birzeit Universityโs SinaLab for Computational Linguistics and Artificial Intelligence <https://sina.birzeit.edu/> has officially launched Qabas <https://sina.birzeit.edu/qabas>, an open-source lexicographic database for Arabic, designed specifically for Natural Language Processing (NLP) applications.
Qabas stands out by linking its lexical entries (lemmas) with lemmas from 110 different lexicons and numerous morphologically annotated corpora (around 2 million tokens), creating an extensive lexicographic graph. This project has been under development for over fourteen years.
Lexicons have evolved from being primarily hard-copy resources for human use to having substantial significance in NLP applications. Although Arabic is a highly resourced language in terms of traditional lexicons, not enough attention is given to developing AI-oriented lexicographic databases. Additionally, none of the Arabic lexicons are available open-source, due to copyright restrictions imposed by their owners. As for Qabas, it is an open-source Arabic lexicon designed for NLP applications, and its novelty lies in its synthesis of many lexical resources. Each lexical entry (i.e., lemma) in Qabas is linked with equivalent lemmas in 110 other lexicons, and with 12 morphologically-annotated corpora (about 2M tokens); The philosophy of Qabas is to construct a large lexicographic data graph by linking existing Arabic lexicons and annotated corpora. Qabas stands as the largest Arabic lexicon, encompassing about 58K lemmas (45K nominal lemmas, 12.5K verbal lemmas, and 500 function word lemmas).
Prof. Mustafa Jarrar, the projectโs manager and main author, emphasized the importance of making Qabas freely available as an open-source resource, allowing everyone to access and use it for both commercial and non-commercial purposes. Prof. Jarrar hopes that researchers, companies, and software developers will leverage the lexiconโs data to develop innovative content and applications that benefit humanity.
Prof. Talal Shahwan, President of Birzeit University, stated that despite the challenging conditions in Palestine, the university remains committed to excellence and to its mission towards knowledge. He emphasized that this achievement was made possible by the dedication of the universityโs faculty and researchers.
Qabas is publicly available online at: https://sina.birzeit.edu/qabas
To download Qabas and find out more, see: https://sina.birzeit.edu/qabas/about
Article: https://www.jarrar.info/publications/JH24.pdf
Weโd love your feedback:
Facebook: https://www.facebook.com/watch?v=880418097306662
LinkedIn: https://www.facebook.com/watch?v=880418097306662
Best
--Mustafa
__________________________
Mustafa Jarrar, PhD
Professor of Artificial Intelligence
Chair, PhD Program in Computer Science
Birzeit University, Palestine
Page: http://www.jarrar.info <http://www.jarrar.info/>
SinaLab: https://sina.birzeit.edu <https://sina.birzeit.edu/>
Apologies for the multiple postings.
-------------------------------------
*Call for Doctoral Consortium Papers*
*FIRE 2024: 16th meeting of the Forum for Information Retrieval Evaluation*
12th - 15th December 2024
DA-IICT, Gandhinagar, India
Submission Deadline: 2nd October 2024 (Extended)
Website: fire.irsi.org.in
Submission Link : https://cmt3.research.microsoft.com/FIRE2024
------------------------------
*The goals of the symposium are to: *
- provide the participants with an independent and constructive
assessment of their current research and possible future research scopes;
- develop a supportive community of scholars and a spirit of
collaborative research;
- provide a platform for the doctoral participants to share and discuss
their ideas with distinguished researchers from their domain; and support
the participants further with an individual mentorship session with a
distinguished researcher.
*Who should participate? *
Students should consider participating in the Doctoral Consortium if they
are at least twelve months away from completing their dissertation at the
time of the event, but after having settled on a research area or thesis
topic.
In the area of research which largely covers AI / ML, and information
science-related, we do not have any fixed set of research areas for the DC.
However, it would be desirable to have information retrieval as a paradigm
in your research that can be in any domain like software engineering,
machine translation and image processing, etc.
*Submission*
Submissions can be based on early ideas or results (communicated elsewhere)
for further feedback, or well-rounded study, results, and analysis, on
approach to convert PhD work into a product, and the like.
The paper should be 4 pages long (including references) and may contain the
following aspects:
- the problem to be solved in the research; a justification of why the
problem is important; a summary of the previous research and related work
has not yet solved that problem,
- the expected contributions of the research,
- how the student aims to evaluate and analyze the results; acceptable
evidence of the results to the community,
- an outline and characterization of the results achieved so far, and
- the planned timeline for completion.
Students, whose submissions are accepted, will be invited to present a
poster at the consortium. They will also need to give a short talk at the
consortium.
Paper submission link: https://cmt3.research.microsoft.com/FIRE2024
*Format*
The submitted papers must follow follow LNCS (Springer conference) template
available on
https://www.overleaf.com/latex/templates/springer-lecture-notes-in-computerโฆ.
The only accepted format of submissions is PDF. Papers which do not conform
to the requirements may get rejected without review. Please note that it is
the responsibility of the authors to ensure that the PDF submission has
been uploaded successfully (we suggest that you try downloading your paper
again yourself, to check). Authors are invited to submit in any of the
following tracks:
Paper Length: 4 page single column
The author names and affiliations of the PhD Student or supervisors should
be included in the paper during submission. The first author of the paper
should be the PhD Student.
*Review Process*
Submissions will be reviewed by members of the Doctoral Symposium
Committee. Participants will be selected on the basis of their anticipated
contribution to the Doctoral Consortium goals as well as the potential
benefit to the participants. Among the criteria that will be considered in
reviewing submissions are:
- the potential quality of the anticipated contributions
- the stage of the research;
- the diversity of backgrounds, research topics, and approaches.
An additional review would be done to assess if the participants are
eligible for the PhD clinic, where potential research work can be reviewed
and discussed individually by a distinguished researcher.
*Consortium and PhD Clinic*
Authors of submissions selected for participation will have the opportunity
to present their work during the Doctoral Consortium and to have a
camera-ready version of their papers published in a companion volume to the
FIRE 2024 Conference Proceedings.
The presentation is expected to be delivered in person, unless this is
impossible due to travel limitations (related to, e.g., health or visa).
Selected participants will be also be eligible for the PhD clinic wherein
they will be assigned to a distinguished researcher who will conduct an
individual mentoring session with the participants. This session can be
constructively used by the participants to discuss their ideas, get more
insights and feedback and also directions forfuture work.
*Important dates*
*25th July 2024* DC Paper submission link
<https://cmt3.research.microsoft.com/FIRE2024> will be available
* 20th September 2024 2nd October 2024 * Paper submission deadline
*30th October 2024 * Paper acceptance notification
*10th November 2024 * Camera ready copy submission deadline
*12th-15th December 2023* In-person conference
Note: All submission deadlines are 11:59 PM AoE Time Zone (Anywhere on
Earth).
*Presentation Requirements*
If accepted, at least one author will have to register for the conference
and present their work in-person.
*Doctoral Consortium Co-ordinator *
- Soumen Paul ( IIT Kharagpur, India)
- Srijoni Majumdar, University of Leeds, UK
For queries related to conference please email us at [ clia(a)isical.ac.in ]
For latest updates subscribe the FIRE mailing List [
https://groups.google.com/forum/#!forum/fire-list ]
Dear all,
The Regulations Challenge aims to push the boundaries of LLMs in understanding, interpreting, and applying regulatory knowledge in the finance industry. In this challenge, participants will participate in 9 tasks to explore key issues, including, but not limited to, regulatory complexity, ethical considerations, domain-specific terminology, industry standards, and interpretability. We welcome students, researchers, and practitioners who are passionate about finance and LLMs. We encourage participants to develop solutions that advance the capabilities of LLMs in addressing the challenges of financial regulations and industry standards.
These tasks assess the LLM's ability to handle different types of questions within the regulatory domain which follow:
- Abbreviation Recognition Task:
Goal: Match an abbreviation with its expanded form.
Input Template: "Expand the following acronym into its full form: {acronym}. Answer:"
- Definition Recognition Task:
Goal: Correctly define a regulatory term or phrase.
Input Template: "Define the following term: {regulatory term or phrase}. Answer:"
- Named Entity Recognition (NER) Task:
Goal: Ensure the output correctly identifies entities and places them into groups that the user specifies.
Input Template: "Given the following text, only list the following for each: specific Organizations, Legislations, Dates, Monetary Values, and Statistics: {input text}."
- Question Answering Task:
Goal: Ensure the output matches the correct answer to a detailed question about regulatory practices or laws.
Input Template: "Provide a concise answer to the following question: {detailed question}? Answer:"
- Link Retrieval Task:
Goal: Ensure the link output matches the actual law.
Input Template: "Provide a link for ____ law, Write in the format of ("{Law}: {Link}" or "{Law}: Not able to find a link for the law")"
- Certificate Question Task:
Goal: Select the correct answer choice to a question that may be based on additional context.
Input Template: "(This context is used for the question that follows: {context}). Please answer the following question with only the letter and associated description of the correct answer choice: {question and answer choices}. Answer:"
- XBRL Analytics Task:
Goal: Ensure the output strictly matches the correct answer to a detailed question about financial data extraction and application tasks via XBRL filings. These standardized digital documents contain detailed financial information.
Input Template: "Provide the exact answer to the following question: {detailed question}? Answer:"
- Common Domain Model (CDM) Task:
Goal: Deliver precise responses to questions about the Fintech Open Source Foundation's (FINOS) Common Domain Model (CDM).
Input Template: "Provide a concise answer to the following question related to Financial Industry Operating Network's (FINO) Common Domain Model (CDM): {detailed question}? Answer:"
- Model Openness Framework (MOF) Licenses Task:
Goal: Deliver precise responses to questions concerning the requirement of license under the Model Openness Framework.
Input Template: "Provide a concise answer to the following question about MOF's licensing requirements: {detailed question}? Answer:"
The final score is determined by the weighted average of metrics for 9 tasks. We assign the weight of 10% to Task 1-5 each, 20% to Task 6, and 10% to Task 7-8 each.
Important Dates
Training Set Release: September 15, 2024
Training Data Details: Summary of Question Dataset
Validation Set Release: October 30, 2024
Systems Submission: November 7, 2024
Release of Results: November 12, 2024
Paper Submission Deadline: November 25, 2024
Notification of Acceptance: December 5, 2024
Camera-ready Paper Deadline: December 13, 2024
Workshop Date: January 19-20, 2025
Task Organizers
Keyi Wang, Columbia University, Northwestern University
Lihang (Charlie) Shen, Columbia University
Haoqiang Kang, Columbia University
Xingjian Zhao, Rensselaer Polytechnic Institute
Namir Xia, Rensselaer Polytechnic Institute
Christopher Poon, Rensselaer Polytechnic Institute
Jaisal Patel, Rensselaer Polytechnic Institute
Andy Zhu, Rensselaer Polytechnic Institute
Shengyuan Lin, Rensselaer Polytechnic Institute
Daniel Kim, Rensselaer Polytechnic Institute
Jaswanth Duddu, Rensselaer Polytechnic Institute
Matthew Tavares, Rensselaer Polytechnic Institute
Shanshan Yang, Stevens Institute of Technology
Sai Gonigeni, Stevens Institute of Technology
Kayli Gregory, Stevens Institute of Technology
Katie Ng, Stevens Institute of Technology
Andrew Thomas, Stevens Institute of Technology
Dong Li, FinAI
Supervisors
Yanglet Xiao-Yang Liu, Rensselaer Polytechnic Institute, Columbia University
Steve Yang, School of Business at Stevens Institute of Technology
Kairong Xiao, Roger F. Murray Associate Professor of Business at Columbia Business School
Matt White, Executive Director, PyTorch Foundation. GM of AI, Linux Foundation
Cailean Osborne, University of Oxford
Wes Turner, Rensselaer Center for Open Source (RCOS), Rensselaer Polytechnic Institute
Neha Keshan, Rensselaer Polytechnic Institute
Luca Borella, PM of AI Strategic Initiative, FINOS Ambassador, Linux Foundation
Karl Moll, Technical Project Advocate, FINOS, Linux Foundation
For more details, please visit https://coling2025regulations.thefin.ai/ or contact colingregchallenge2025(a)gmail.com
Best regards,
Jimin Huang
The Fin AI (https://thefin.ai)
Dear All,
We're excited to announce that we've just released all training datasets for Financial Misinformation Detection Challenge at FinNLP-FNP-LLMFinLegal Workshop @ COLING 2025, giving participants the resources needed to start building powerful models. This is your chance to explore, innovate, and contribute to the world of financial large language models.
This task tests the ability of LLM to verify financial misinformation while generating plausible explanations. Participants need to develop or adapt LLMs to identify financial claims (True'/'False'/'Not Enough Information') and give explanations for their decision according to the related information, following the designed prompt template of the query. For more details:
Contest Website: https://coling2025fmd.thefin.ai/
Team Registration: https://forms.gle/vh9MSQa31HwrS7Xm9
Shared Task Organizers:
Zhiwei Liu - University of Manchester, UK
Keyi Wang - Columbia University, Northwestern University, USA
Zhuo Bao - Internet Domain Name System Beijing Engineering Research Center Co, China
Xin Zhang - University of Manchester, UK
Jiping Dong - University of Chinese Academy of Sciences, China
Boyang Gu - Imperial College London, UK
Kailai Yang - University of Manchester, UK
Dong Li - FinAI, Singapore
Sophia Ananiadou - University of Manchester, UK; Archimedes RC, Greece
Important Dates:
Schedule: from Aug 15 to Dec 13, 2024
Solution submission deadline: Nov 7, 2024
Paper submission deadline: Nov 25, 2024
Notifications of Acceptance: Dec 5, 2024
Camera-ready Paper Deadline: Dec 13, 2024
We look forward to your participation and your brilliant contributions to this event.
Best regards,
Jimin Huang
The Fin AI (https://thefin.ai)
First call for participation in the SemEval 2025 shared task: Multilingual Characterization and Extraction of Narratives from Online News.
This task challenges participants to analyze news articles and automatically identify narratives, classify them, and determine the roles played by relevant entities. The task is multilingual, covering five languages: Bulgarian, English, Hindi, Portuguese, and Russian.
Participants can choose to participate in one or more of the following subtasks:
- Subtask 1: Entity Framing โ Classify the roles of named entities within news articles.
- Subtask 2: Narrative Classification โ Classify each article based on all the (sub)narratives given a specific domain.
- Subtask 3: Narrative Extraction โ Generate short textual explanations for dominant narratives in the articles.
The task covers news articles from two domains, namely, Ukraine-Russia War and Climate Change.
Important Dates:
- 31 January 2025: Test submission deadline
- 28 February 2025: System paper submission deadline
- 31 March 2025: Notification to authors
- 21 April 2025: Camera-ready papers due
- Summer 2025: SemEval workshop
For more details, visit https://propaganda.math.unipd.it/semeval2025task10/ or contact us at semeval2025narratives-task-participants(a)googlegroups.com.
We look forward to your participation and to advancing the state of multilingual news narrative analysis together!
--
Ion Androutsopoulos (http://www.aueb.gr/users/ion/)
Professor of AI, Head of Department, Information Processing Lab Director, NLP Group Co-director
Department of Informatics, Athens University of Economics and Business
and Adjunct Researcher, "Archimedes" Research Unit, Research Center "Athena"
The Computer Science department at Johns Hopkins University is hiring
tenure-track faculty. Our search includes two tracks: 1) Data Science and
AI, and 2) All other areas of Computer Science.
We offer special support for *spousal/partner placement. *Additionally,
starting October 1, *Early Action* hiring will consider candidates for fall
semester interviews with potentially early offers that have typical spring
deadlines. We encourage candidates to apply early to take advantage of
flexible scheduling and potentially receive an early offer before they
proceed to spring interviews. All applications submitted by December 1,
2024 will receive full consideration.
Our search supports the large-scale expansion of the Whiting School of
Engineering, which will add 150 new tenure-track professors at all ranks,
including 30 Bloomberg Distinguished Professorships and 80 positions that
will be part of the universityโs new Data Science and AI Institute. This
expansion includes a new building and extensive computational resources
that will establish Johns Hopkins as one of the largest and leading
engineering schools with a top AI research program. The expansion will grow
JHU CS to become one of the largest computer science departments at a U.S.
private university.
Feel free to forward this to interested parties.
Job Ad: https://www.cs.jhu.edu/about/employment-opportunities/
Applications: http://apply.interfolio.com/153420
Data Science AI: https://engineering.jhu.edu/Datascience-AI/
Computer Science DSAI: https://engineering.jhu.edu/Datascience-AI/CS/
Best,
Mark Dredze
==============
John C Malone Professor
Associate Head of Research and Strategic Initiatives, Computer Science
Johns Hopkins University
Call for papers: 1st Workshop on Computational Humor (CHum 2025)
================================================================
The 1st Workshop on Computational Humor (CHum 2025) will take place
virtually on January 19, 2025 as part of the 31st International
Conference on Computational Linguistics (COLING 2025).
Scope and topics
----------------
CHum 2025 aims to foster further work on modeling the processes of humor
with current methods in computational linguistics and natural language
processing, against the theoretical backdrop of humor research and with
reference to relevant corpora of textual, visual, and multimodal
materials. A principal goal of the workshop is to unite researchers who
can together probe the limits of various meaning representations --
symbolic, neural, and hybrid -- for humor processing.
We welcome contributions on any topic relevant to the computational
processing of humor, including but not limited to the following:
* LLMs, knowledge representation
* Resources and evaluation
* Human-computer interaction
* Computer-mediated communication
* Assisted content creation
* Machine and computer-assisted translation
* Digital humanities applications
* Formal modeling of humor
* Proof-of-concept humor detection and classification
Particularly encouraged are submissions describing inter- or
multi-disciplinary work, whether completed or in progress, and position
papers that critically discuss the past, present, and future of
computational humor systems.
Submission instructions
-----------------------
Long and short papers should be formatted according to the same
guidelines for the main COLING 2025 conference papers
<https://coling2025.org/calls/submission_guidlines/> and submitted
through START: <https://softconf.com/coling2025/CompHum25/>
Important dates
---------------
All deadlines are at 23:59 UTC-12:00 ("anywhere on Earth").
* Initial submission: November 15, 2024
* Notification of acceptance: December 2, 2024
* Camera-ready submission: December 13, 2024
* Workshop: January 19, 2025
Organizers
----------
* Christian F. Hempelmann, Texas A&M University-Commerce
* Julia Rayz, Purdue University
* Tiansi Dong, Fraunhofer IAIS
* Tristan Miller, University of Manitoba
Further information
-------------------
* Website: <https://chum2025.github.io/>
* E-mail: chum(a)groups.io
--
Dr. Tristan Miller, Assistant Professor
Department of Computer Science, University of Manitoba
https://logological.org/ | Tel. +1 204 474 6792
The HITS Independent Postdoc Program offers a great opportunity for highly talented young scientists wanting to transition from PhD student to junior group leader. It supports young scientists in exploring their own ideas and testing new hypotheses. High-risk, high-gain projects are encouraged. Selected postdocs will collaborate with group leaders at HITS while developing and pursuing their independent research projects.
What we offer:
The Fellowship is awarded for 2 years, with an option for a 1-year extension after positive evaluation. We offer a vibrant research community and a highly interdisciplinary and international working environment, with close links to Heidelberg University and the Karlsruhe Institute of Technology (KIT). In addition, successful candidates benefit from outstanding computing resources and various courses offered at HITS. A competitive salary, relocation and childcare allowances are provided.
Find the current job opening here: https://www.h-its.org/research/independent-postdoc-program/
2024 Deadline: November 3rd, 2024
Please don't hesitate to get in contact with Michael Strube (michael.strube รคt h-its.org) if you have any questions.
--
Michael Strube
NLP Group
HITS gGmbH
Schloss-Wolfsbrunnenweg 35
69118 Heidelberg, Germany
https://www.h-its.org/nlp
The 40th ACM/SIGAPP Symposium on Applied Computing
ACM SAC 2025
March 31 - April 4, 2025 - Catania, Italy
Knowledge and Natural Language Processing Track
*****************************************
Important Dates
Author deadline for submissions: September 20, 2024 October 4, 2024:
Author notification of acceptance: October 30, 2024
Author camera ready and registration due: November 29, 2024
*****************************************
Aim
Aim of the Knowledge and Natural Language Processing (KNLP) track at ACM SAC is to investigate techniques and application of knowledge engineering and natural language processing, two extremely interdisciplinary and lively research areas at the core of Artificial Intelligence.
In particular, the track welcomes contributions combining and complementing methods and approaches from both areas.
Topics of interest include, but are not limited to:
- Natural Language Processing
NLP tasks for Knowledge Extraction
NLP for Ontology Population and Learning
Sentiment Analysis and Opinion Mining for Knowledge Applications
Interplay between Language and Ontologies
NLP for Explainable Knowledge
Machine Translation techniques for Multi-lingual Knowledge
NLP for the Web
(Large) Language Models and Knowledge
- Knowledge
Knowledge to improve NLP tasks
Knowledge for Information Retrieval
Knowledge-based Sentiment Analysis and Opinion Mining
Combining Knowledge and Deep Learning for NLP
Knowledge for Text Summarization and Generation
Knowledge for Persuasion
Knowledge-based Machine Translation
Knowledge for the Web
Linked Data for NLP
Knowledge-based NL Explainability
RAG and Knowledge injection for Language Models
- Applications
Real-world applications that exploit Knowledge and NLP
Knowledge and NLP Systems for Big Data scenarios
Knowledge and NLP technology for diverse, equitable, and inclusive society
Deployment of Knowledge and NLP Systems in specific domains, such as:
Digital Humanities and Social Sciences
eGovernment and public administration
Life sciences, health and medicine
News and Data Streaming
*****************************************
Paper Submission
Research papers and experience reports related to the above topics are solicited. Submissions must not have been published or be concurrently considered for publication elsewhere. Papers should be submitted in PDF using the ACM-SAC proceedings format using the submission link on the SAC 2025 website (https://www.sigapp.org/sac/sac2025/). Authors' names and affiliations should be entered separately at the submission site and not appear in the submitted papers. Each submission will be reviewed in a DOUBLE-BLIND process according to the ACM-SAC Regulations. Student Research Competition (SRC) submissions are welcome (see SAC 2025 website for details).
Full papers are limited to 8 pages, in camera-ready format, included in the registration fee. Authors have the option to include up to two (2) extra pages (paying an extra charge).
Posters are limited to 2 pages, in camera-ready format, included in the registration fee. Authors have the option to include only one (1) extra page (paying an extra charge).
SRC Abstracts are limited to 3 pages, in camera-ready format, included in the registration fee. No extra pages are allowed.
Paper selection is based on originality, technical contribution, presentation quality, and relevance to the Knowledge and Natural Language Processing Track. Some papers may be accepted as posters.
Paper registration is required, allowing the inclusion of the paper/poster in the conference proceedings. An author or a proxy attending SAC MUST present the paper. This is a requirement for the paper/poster to be included in the ACM digital library. No-show of registered papers and posters will result in excluding them from the ACM digital library.
*****************************************
Track Co-Chairs
Patrizio Bellan, Fondazione Bruno Kessler (FBK)
Marco Bombieri, Universitร degli Studi di Verona
Mauro Dragoni, Fondazione Bruno Kessler (FBK)
Marco Rospocher, Universitร degli Studi di Verona
*****************************************
Programme Committee
TBA
*****************************************
General Inquiries
For further information, please visit SAC Knowledge and Natural Language Processing Track (https://knlp-sac.github.io/2025/) and SAC 2024 conference websites (https://www.sigapp.org/sac/sac2025/) or feel free to contact the Track Co-Chairs at knlp(a)fbk.eu<mailto:knlp@fbk.eu> .
--
--
Le informazioni contenute nella presente comunicazione sono di natura
privata e come tali sono da considerarsi riservate ed indirizzate
esclusivamente ai destinatari indicati e per le finalitร strettamente
legate al relativo contenuto. Se avete ricevuto questo messaggio per
errore, vi preghiamo di eliminarlo e di inviare una comunicazione
all'indirizzo e-mail del mittente.
--
The information transmitted is
intended only for the person or entity to which it is addressed and may
contain confidential and/or privileged material. If you received this in
error, please contact the sender and delete the material.