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The advent of ubiquitous internet access has led to a proliferation of cyber threats. Among these, botnets represent a significant and growing menace to cyber security. Addressing this challenge necessitates the development of potent botnet detection methods. Traditional approaches to botnet detection have predominantly relied on a range of features derived from static or dynamic analysis. This paper presents a novel approach to botnet detection, utilizing Natural Language Processing (NLP), a branch of machine learning (ML), for a more effective analysis. By analyzing behavioral reports through NLP methodologies, including bag-of-words (BoW), BERT, GloVe, and word2vec, we generate rich datasets for ML applications. This unique combination of NLP and ML techniques transforms behavioral data into valuable detection features. Our application of these techniques, reinforced by the XGboost classifier, demonstrates exceptional results in botnet detection, achieving an accuracy of 99.17% and a ROC/AUC score of 0.9995. These findings highlight the critical role of NLP in enhancing feature extraction and the effectiveness of ML in combating botnet threats.

Abstract Creoles represent an under-explored and marginalized group of languages, with few available resources for NLP research. While the genealogical ties between Creoles and a number of highly resourced languages imply a significant potential for transfer learning, this potential is hampered due to this lack of annotated data. In this work we present CreoleVal, a collection of benchmark datasets spanning 8 different NLP tasks, covering up to 28 Creole languages; it is an aggregate of novel development datasets for reading comprehension relation classification, and machine translation for Creoles, in addition to a practical gateway to a handful of preexisting benchmarks. For each benchmark, we conduct baseline experiments in a zero-shot setting in order to further ascertain the capabilities and limitations of transfer learning for Creoles. Ultimately, we see CreoleVal as an opportunity to empower research on Creoles in NLP and computational linguistics, and in general, a step towards more equitable language technology around the globe.

Large Language Models (LLMs) are susceptible to malicious influence by cyber attackers through intrusions such as adversarial, backdoor, and embedding inversion attacks. In response, the burgeoning field of LLM Security aims to study and defend against such threats. Thus far, the majority of works in this area have focused on monolingual English models, however, emerging research suggests that multilingual LLMs may be more vulnerable to various attacks than their monolingual counterparts. While previous work has investigated embedding inversion over a small subset of European languages, it is challenging to extrapolate these findings to languages from different linguistic families and with differing scripts. To this end, we explore the security of multilingual LLMs in the context of embedding inversion attacks and investigate cross-lingual and cross-script inversion across 20 languages, spanning over 8 language families and 12 scripts. Our findings indicate that languages written in Arabic script and Cyrillic script are particularly vulnerable to embedding inversion, as are languages within the Indo-Aryan language family. We further observe that inversion models tend to suffer from language confusion, sometimes greatly reducing the efficacy of an attack. Accordingly, we systematically explore this bottleneck for inversion models, uncovering predictable patterns which could be leveraged by attackers. Ultimately, this study aims to further the field's understanding of the outstanding security vulnerabilities facing multilingual LLMs and raise awareness for the languages most at risk of negative impact from these attacks. 11 pages, 4 figures, 7 tables

European bison ( Bison bonasus ) were widespread throughout Europe during the late Pleistocene. However, the contributions of environmental change and humans to their near extinction have never been resolved. Using process-explicit models, fossils and ancient DNA, we disentangle the combinations of threatening processes that drove population declines and regional extinctions of European bison through space and across time. We show that the population size of European bison declined abruptly at the termination of the Pleistocene in response to rapid environmental change, hunting by humans and their interaction. Human activities prevented populations of European bison from rebounding in the Holocene, despite improved environmental conditions. Hunting caused range loss in the north and east of its distribution, while land use change was responsible for losses in the west and south. Advances in hunting technologies from 1500 CE were needed to simulate low abundances observed in 1870 CE. While our findings show that humans were an important driver of the extinction of the European bison in the wild, vast areas of its range vanished during the Pleistocene–Holocene transition because of post-glacial environmental change. These areas of its former range have been climatically unsuitable for millennia and should not be considered in reintroduction efforts.

Assessing and comprehending the social impact of firms at global and local level is a pressing concern for both researchers and policy-makers. To address this concern, our paper contributes to the stream of literature that studies the content of Corporate Social Responsibility (CSR) reports (which are also referred to as non-financial statements, sustainability reports or parts of annual reports) using text mining methods. We present a novel approach called Standard-based Impact Classification method (SBIC method), which employs natural language processing (NLP) and supervised machine learning techniques to identify the types of social impacts reflected in CSR reports. We deploy a Random Forest model which we train on reports adhering to Global Reporting Initiative (GRI) framework, enabling the identification of social impact in the majority of CSR reports that do not conform to this standard. Our proposed SBIC method serves as a valuable tool for comparing the social impacts generated by firms, industries, or countries. We showcase an application of our approach by examining the relationship between a company’s social impact and its innovation capacity. Our findings support the existing literature consensus that CSR activities generally exhibit a positive correlation with a firm’s ability to innovate. Furthermore, we reveal that specific types of social impacts have a more pronounced influence on innovation capacity.

Le plus grand défi pour le secteur agricole au XXIe siècle est d'augmenter la production agricole pour nourrir la population mondiale en plein essor tout en maintenant la santé des sols et l'intégrité de l'agroécosystème. Actuellement, l'application du biochar est largement mise en œuvre comme un moyen efficace de stimuler l'agriculture durable tout en ayant une influence négligeable sur les écosystèmes et l'environnement. Par rapport au biochar traditionnel, le nano-biochar (nano-BC) possède une surface spécifique, une capacité d'adsorption et des propriétés de mobilité améliorées dans le sol, ce qui lui permet de promouvoir les propriétés du sol, la croissance des cultures et la réhabilitation de l'environnement. En outre, la séquestration du carbone et la réduction des émissions de méthane et d'oxyde nitreux provenant de l'agriculture peuvent être réalisées avec des applications nano-BC, contribuant ainsi à l'atténuation du changement climatique. Néanmoins, en raison de leur rapport coût-efficacité, de leur durabilité et de leur respect de l'environnement, les nano-BC dérivées des déchets peuvent apparaître comme l'alternative la plus viable aux stratégies conventionnelles de gestion des déchets, contribuant à la bioéconomie circulaire et à l'objectif plus large d'atteindre les objectifs de développement durable (ODD). Cependant, il est important de noter que la recherche sur le nano-BC en est encore à ses balbutiements. Les risques potentiels, y compris la toxicité dans les environnements aquatiques et terrestres, nécessitent des enquêtes approfondies sur le terrain. Cette revue définit le potentiel des nano-BC dérivés des déchets pour les applications agricoles et environnementales durables, en décrivant les progrès actuels, les défis et les possibilités dans les domaines du point de vue de la durabilité et de la bioéconomie circulaire. El mayor desafío para el sector agrícola en el siglo XXI es aumentar la producción agrícola para alimentar a la creciente población mundial mientras se mantiene la salud del suelo y la integridad del agroecosistema. Actualmente, la aplicación del biocarbón se implementa ampliamente como un medio eficaz para impulsar la agricultura sostenible, al tiempo que tiene una influencia insignificante en los ecosistemas y el medio ambiente. En comparación con el biochar tradicional, el nano-biochar (nano-BC) cuenta con una mayor superficie específica, capacidad de adsorción y propiedades de movilidad dentro del suelo, lo que le permite promover las propiedades del suelo, el crecimiento de los cultivos y la remediación ambiental. Además, el secuestro de carbono y la reducción de las emisiones de metano y óxido nitroso de la agricultura se pueden lograr con aplicaciones de nano-BC, lo que contribuye a la mitigación del cambio climático. No obstante, debido a la rentabilidad, la sostenibilidad y el respeto por el medio ambiente, el nano-BC derivado de los residuos puede surgir como la alternativa más viable a las estrategias convencionales de gestión de residuos, contribuyendo a la bioeconomía circular y al objetivo más amplio de alcanzar los Objetivos de Desarrollo Sostenible (ODS). Sin embargo, es importante tener en cuenta que la investigación sobre nano-BC aún se encuentra en sus etapas iniciales. Los riesgos potenciales, incluida la toxicidad en entornos acuáticos y terrestres, requieren extensas investigaciones de campo. Esta revisión delinea el potencial del nano-BC derivado de residuos para la agricultura sostenible y las aplicaciones ambientales, describiendo los avances, desafíos y posibilidades actuales en los ámbitos desde un punto de vista de sostenibilidad y bioeconomía circular. The greatest challenge for the agriculture sector in the twenty-first century is to increase agricultural production to feed the burgeoning global population while maintaining soil health and the integrity of the agroecosystem. Currently, the application of biochar is widely implemented as an effective means for boosting sustainable agriculture while having a negligible influence on ecosystems and the environment. In comparison to traditional biochar, nano-biochar (nano-BC) boasts enhanced specific surface area, adsorption capacity, and mobility properties within soil, allowing it to promote soil properties, crop growth, and environmental remediation. Additionally, carbon sequestration and reduction of methane and nitrous oxide emissions from agriculture can be achieved with nano-BC applications, contributing to climate change mitigation. Nonetheless, due to cost-effectiveness, sustainability, and environmental friendliness, waste-derived nano-BC may emerge as the most viable alternative to conventional waste management strategies, contributing to the circular bioeconomy and the broader goal of achieving the Sustainable Development Goals (SDGs). However, it's important to note that research on nano-BC is still in its nascent stages. Potential risks, including toxicity in aquatic and terrestrial environments, necessitate extensive field investigations. This review delineates the potential of waste-derived nano-BC for sustainable agriculture and environmental applications, outlining current advancements, challenges, and possibilities in the realms from a sustainability and circular bioeconomy standpoint. يتمثل التحدي الأكبر لقطاع الزراعة في القرن الحادي والعشرين في زيادة الإنتاج الزراعي لإطعام سكان العالم المتزايدين مع الحفاظ على صحة التربة وسلامة النظام الإيكولوجي الزراعي. في الوقت الحالي، يتم تطبيق الفحم الحيوي على نطاق واسع كوسيلة فعالة لتعزيز الزراعة المستدامة مع تأثير ضئيل على النظم الإيكولوجية والبيئة. بالمقارنة مع الفحم الحيوي التقليدي، يتميز الفحم الحيوي النانوي (nano - BC) بمساحة سطح محددة محسنة وقدرة امتزاز وخصائص تنقل داخل التربة، مما يسمح له بتعزيز خصائص التربة ونمو المحاصيل والمعالجة البيئية. بالإضافة إلى ذلك، يمكن تحقيق عزل الكربون وخفض انبعاثات الميثان وأكسيد النيتروز من الزراعة باستخدام تطبيقات النانو بي سي، مما يساهم في التخفيف من آثار تغير المناخ. ومع ذلك، نظرًا لفعالية التكلفة والاستدامة والصداقة البيئية، قد تظهر نانو بي سي المشتقة من النفايات كبديل أكثر قابلية للتطبيق لاستراتيجيات إدارة النفايات التقليدية، مما يساهم في الاقتصاد الحيوي الدائري والهدف الأوسع المتمثل في تحقيق أهداف التنمية المستدامة (SDGs). ومع ذلك، من المهم ملاحظة أن الأبحاث حول nano - BC لا تزال في مراحلها الوليدة. تتطلب المخاطر المحتملة، بما في ذلك السمية في البيئات المائية والبرية، إجراء تحقيقات ميدانية واسعة النطاق. تحدد هذه المراجعة إمكانات nano - BC المشتقة من النفايات للزراعة المستدامة والتطبيقات البيئية، وتحدد التطورات والتحديات والإمكانيات الحالية في العوالم من وجهة نظر الاستدامة والاقتصاد الحيوي الدائري.

This paper explores the relationship between historical research and the field of global mental health. It identifies a gap in the current literature, and argues that an in-depth historical approach is critical for understanding and overcoming current challenges and controversies in global mental health. The authors propose that a thick historical analysis has the capacity to broaden and diversify the discussion about the core concepts in global mental health (such as illness, suffering, care or culture), and to nuance our understanding of the field’s development and impact in specific political and social contexts. The paper analyzes how a systematic historical approach is crucial for understanding colonial and post-colonial power relations embedded in the field of global mental health, and encourages researchers and practitioners to view history as a source of imagination, and of alternative ideas and initiatives in mental health that go beyond existing psychiatric frames of representations, and towards truly radical and egalitarian projects and relations. This exercise in alternative historical imagination does not need to interfere with nor disrupt the urgency of mental health practice today; on the contrary, it is meant to improve the effectiveness of interventions. It can provide practitioners with a new and enriched language to resolve long-standing clinical dilemmas (e.g. related to patient adherence or limited success of certain cultural adaptations), which could not be properly addressed previously

Abstract Background Traditionally, in biomedical animal research, laboratory rodents are individually examined in test apparatuses outside of their home cages at selected time points. However, the outcome of such tests can be influenced by various factors and valuable information may be missed when the animals are only monitored for short periods. These issues can be overcome by longitudinally monitoring mice and rats in their home cages. To shed light on the development of home cage monitoring (HCM) and the current state-of-the-art, a systematic review was carried out on 521 publications retrieved through PubMed and Web of Science. Results Both the absolute (~ × 26) and relative (~ × 7) number of HCM-related publications increased from 1974 to 2020. There was a clear bias towards males and individually housed animals, but during the past decade (2011–2020), an increasing number of studies used both sexes and group housing. In most studies, animals were kept for short (up to 4 weeks) time periods in the HCM systems; intermediate time periods (4–12 weeks) increased in frequency in the years between 2011 and 2020. Before the 2000s, HCM techniques were predominantly applied for less than 12 h, while 24-h measurements have been more frequent since the 2000s. The systematic review demonstrated that manual monitoring is decreasing in relation to automatic techniques but still relevant. Until (and including) the 1990s, most techniques were applied manually but have been progressively replaced by automation since the 2000s. Independent of the year of publication, the main behavioral parameters measured were locomotor activity, feeding, and social behaviors; the main physiological parameters were heart rate and electrocardiography. External appearance-related parameters were rarely examined in the home cages. Due to technological progress and application of artificial intelligence, more refined and detailed behavioral parameters have been investigated in the home cage more recently. Conclusions Over the period covered in this study, techniques for HCM of mice and rats have improved considerably. This development is ongoing and further progress as well as validation of HCM systems will extend the applications to allow for continuous, longitudinal, non-invasive monitoring of an increasing range of parameters in group-housed small rodents in their home cages.