Miracle-dz/UniFAR-FTUs huggingface dataset:
Privacy Protection Method for Sensitive Weighted Edges in Social Networks

Privacy vulnerability of social networks is one of the major concerns for social science research and business analysis. Most existing studies which mainly focus on un-weighted network graph, have designed various privacy models similar to k-anonymity to prevent data disclosure of vertex attributes or relationships, but they may be suffered from serious problems of huge information loss and significant modification of key properties of the network structure. Furthermore, there still lacks further considerations of privacy protection for important sensitive edges in weighted social networks. To address this problem, this paper proposes a privacy preserving method to protect sensitive weighted edges. Firstly, the sensitive edges are differentiated from weighted edges according to the edge betweenness centrality, which evaluates the importance of entities in social network. Then, the perturbation operations are used to preserve the privacy of weighted social network by adding some pseudo-edges or modifying specific edge weights, so that the bottleneck problem of information flow can be well resolved in key area of the social network. Experimental results show that the proposed method can not only effectively preserve the sensitive edges with lower computation cost, but also maintain the stability of the network structures. Further, the capability of defending against malicious attacks to important sensitive edges has been greatly improved.
In-Silico Molecular Docking Show Mitocurcumin can Potentially Block Innate Immune Evasion Mechanism of SARS-CoV-2 and Enhance Viral Load Clearance

In the present work, we have employed a molecular docking approach to study the ability of mitocurcumin (MC), a triphenyl phosphonium conjugated curcumin derivative, to inhibit SARS-CoV-2 infection. Computational analysis revealed that MC can bind strongly to SARS-CoV-2 ADP Ribose Phosphatase (NSP3) with high binding energy of -10.3 kcal/mol and to SARS-CoV-2 methyltransferase (NSP10-NSP16 complex) with a high binding energy of -10.4 kcal/mol. We found that MC interacts with critical residues of viral NSP3 macro-domain, known to suppress host immune response, through hydrophobic interactions and occupies its active site. Furthermore, MC interacts with the critical residues of NSP10-NSP16 complex, known to prevent innate immune detection of viral mRNA, through hydrophobic and hydrogen bond interaction and occupies the methyl group donor site. MC is also found to bind to main protease of SARS-CoV-2 and may potentially act as an inhibitor of the viral protease. In conclusion, MC can potentially inhibit the activity of multiple SARS-CoV-2 proteins and may accentuate the innate immune system mediated clearance of viral load resulting in improved clinic outcome in COVID-19 patients.
ACCIDENT RISKS OF CAR DRIVERS IN WINTERTIME TRAFFIC

The winter accident risks of drivers and the factors affecting the risks were analyzed using statistical accident models. The evaluation method was based on reliability theory and survival modeling. The data consisted of two parts: responses to a postal questionnaire, addressed to 10,000 vehicle owners, about accidents during winter in the years 1991-1993; and detailed records of fatal accidents in the years 1987-1991, generated by in depth accident investigation teams and compiled by the Motor Insurers' Road Safety Committee (VALT).
Substitution of Fishmeal with Black Soldier Fly Hermetia illucens Linnaeus, 1758 Larvae in Finfish Aquaculture – A Review

The reliance of aquaculture feed industry on fishmeal has been challenged by ecological, economic, and ethical limitations leading fish nutritionists to look for viable alternatives, and conventional animal-based protein sources showed varying degrees of success in this regard. However, a non-conventional protein source, black soldier fly Hermetia illucens Linnaeus, 1758 larvae (BSFL), received due attention as a focal point in fish nutrition research. Though many studies were conducted on H. illucens as a potential protein source for fish, a comprehensive review is not available. Therefore, this article aims to review the existing literature on the use of BSFL as a fishmeal replacer in aquaculture. The nutrient composition of BSFL varied with the developmental stage and the composition of growing medium. High crude protein levels (40.4–56.2 %) and high crude fat levels (4.8–24.8 %) made BSFL suitable for high protein and high energy diet. Early prepupa was the best stage for harvesting, considering its high crude protein content and dry matter yield and less chitin content. Up to 100 % inclusion levels of BSFL meal were tested in a wide range of fish species. Most studies revealed that up to 50 % of fishmeal replacement would be possible without negative effects on the fish. Notable adverse effects were found beyond 50 % of fishmeal replacement, mainly due to high chitin levels in the pupal stage and high crude fat levels. Harvesting BSFL before the pupal stage and defattening made it possible to replace 100 % of fishmeal without adverse effects on fish.
Green, Pink & Silver? The Future of Labour in Europe

Work is both an essential part of our daily lives and one of the major policy concerns across Europe. In this second volume of The Future of Labour in Europe, the authors explain in accessible language the findings of the NEUJOBS project on the job prospects of key industries and groups of people. They use three colours – green, pink and silver – to pinpoint areas with the largest challenges as well as the greatest potential. The conclusions are addressed to policy-makers, the business world, journalists, fellow academics and to anyone interested in the shape, size and character of the labour markets of tomorrow.
A Strategic Framework for Natural Disaster-Induced Cost Risk Analysis and Mitigation: A Two-Stage Approach Using Deep Learning and Cost-Benefit Analysis

Abstract. Due to gradual increases in the frequency and severity of natural disasters, risks to human life and property from natural disasters are exploding. To reduce these risks, various risk mitigation activities have been widely conducted. Risk mitigation activities are becoming more and more important for economic analysis of risk mitigation effects due to limited public budget and the need for economic development. To respond to this urgent need, this study aims to develop a strategic evaluation framework for natural disaster risk mitigation strategies. The proposed framework predicts natural disaster losses using a deep learning algorithm (stage I) and introduces a new methodology that quantifies the effect of natural disaster reduction projects adopting cost-benefit analysis (stage II). To achieve the main objectives of this study, data of insured loss amounts due to natural disasters associated with the identified risk indicators were collected and trained to develop the deep learning model. The robustness of the developed model was then scientifically validated. To demonstrate the proposed quantification methodology, reservoir maintenance projects affected by floods in South Korea were adopted. The results and main findings of this study can be used as valuable guidelines to establish natural disaster mitigation strategies. This study will help practitioners quantify the loss from natural disasters and thus evaluate the effectiveness of risk reduction projects. This study will also assist decision-makers to improve the effectiveness of risk mitigation activities.
Space station propulsion

Two propulsion systems have been selected f o r the space station: gaseous H/O rockets f o r high t h r u s t applications and the multipropellant r e s i s t o j e t s f o r low t h r u s t needs. These two thruster systems i n t e g r a t e very well w i t h the f l u i d systems on the space station, u t i l i z i n g waste f l u i d s as t h e i r source o f propellant. The H/O rocket w i l l be fueled by electrolyzed water and the r e s i s t o j e t s w i l l use waste gases collected from the environmental control system and the various laboratories. This paper presents the r e s u l t s o f experimental e f f o r t s w i t h H/O and r e s i s t o j e t thrusters t o deter- mine t h e i r performance and l i f e c a p a b i l i t y , as w e l l as r e s u l t s o f studies t o determine the a v a i l a b i l i t y o f water and waste gases. cost, . l Two p r o p u l s i o n systems have been selected for the Space S t a t i o n : r o c k e t s f o r h i g h t h r u s t a p p l i c a t i o n s and the m u l t i p r o p e l l a n t r e s i s t o j e t s for low t h r u s t needs. These two t h r u s t e r systems i n t e g r a t e very w e l l w i t h the f l u i d systems on t h e space s t a t i o n , u t i t h H/O
A Simulation Method For Effectiveness Evaluation of Distributed Systems

This paper presents a simulation method for evaluating the effectiveness of distributed systems based on passing messages. For mathematical modelling of these systems, two paradigms were used, i.e. the paradigm of experimental modelling and the paradigm of probabilistic modelling. The paper proposes effectiveness measures of the considered family of systems. An algorithm of stochastic simulation for effectiveness evaluation of distributed systems was presented.
Adipogenesis within a Hollow Fiber-Based, Three-Dimensional Dynamic Perfusion Bioreactor

Adipose-derived stem cells (ASCs) represent a promising cell source in the field of tissue engineering and regenerative medicine. Due to the wide availability and multipotent ability of ASCs to differentiate into tissues such as bone, cartilage, muscle, and adipose, ASCs may serve a wide variety of regenerative medicine applications. Accordingly, ASCs have been utilized in studies addressing osteoarthritis, diabetes mellitus, heart disease, and soft tissue regeneration and reconstruction after mastectomy and facial trauma. Traditional, static, two-dimensional cell culture of ASCs do not allow for mature adipocyte differentiation or long-term maintenance of adipocytes in vitro. In order to study metabolic diseases, such as type II diabetes mellitus, a three-dimensional scaffold for in vitro adipocyte maintenance is necessary. In collaboration with the Bioreactor Laboratory at the McGowan Institute for Regenerative Medicine, our laboratory has developed the use of a hollow fiber-based bioreactor for three-dimensional, dynamic perfusion of ASCs and adipose tissue formation ex vivo, creating a stable system in which long-term culture of adipocytes is possible, providing a model useful for potential drug discovery and tissue engineering applications, specifically those addressing type II diabetes mellitus. The studies presented in this dissertation aim to assess metabolic activity and differentiation of ASCs from patients with or without type II diabetes in the bioreactor system; engineer a long-term culture environment relevant to physiological type II diabetic and non-diabetic conditions ex vivo; optimize tissue growth homogeneity; enhance adipogenesis within the bioreactor culture with the use of a decellularized adipose extracellular matrix (ECM) hydrogel. ASCs derived from patients with type II diabetes at time of isolation were found to behave metabolically similar and appear architecturally comparable to those derived from patients without type II diabetes mellitus when differentiated and maintained as adipocytes in the bioreactor system. When cultured at a physiologically relevant glucose level matching that of healthy patients or patients with type II diabetes, ASCs were able to proliferate, differentiate into adipocytes, and be maintained within the bioreactor system for at least one week. A decellularized adipose ECM hydrogel was established and applied to the bioreactor cultures; however, due to technical challenges, no firm conclusions can be made. The microenvironment by which ASCs are surrounded is critical for cell differentiation and growth. Engineering and control of such microenvironment is possible within the hollow fiber-based, three-dimensional, dynamic perfusion bioreactor culture system, proving to be a promising model for potential drug discovery and therapeutics. Future directions include further evaluation of ASC differentiation and adipocyte metabolism within type II diabetic environments, application of established decellularized adipose ECM hydrogels to wound healing treatments and adipose graft volume retention.
Penggunaan Learning Management System (LMS) Untuk Pembelajaran Dimasa Pandemi

Pandemi Covid-19 melanda hampir seluruh negara yang ada di dunia, situasi tersebut sangat tidak diharapkan terjadi. Semua aktifitas masyarakat yang dahulu dilakukan diluar rumah menjadi mengalami pembatasan. Salah satu dampak yang terjadi dari kondisi ini adalah proses pembelajaran dari semua pendidikan dilakukan secara daring. Kondisi tersebut memunculkan permasalahan baru untuk mensinkronkan seluruh pembelajaran dan memerlukan sebuah sistem media pembelajaran online. Salah satu sistem pembelajaran yang diterapkan adalah Learning Management System (LMS), namun sistem ini masih perlu dikembangkan untuk mempermudah melakukan pembelajaran secara daring. Salah satu E-Learning yang menggunakan sistem Learning Management System (LMS) adalah platform Moodle. Penelitian yang dilakukan oleh peneliti bertujuan untuk mengetahui seberapa efektif sistem Learning Management System (LMS) digunakan pada saat pandemi Covid-19 serta dapat mendeskripsikan pembelajaran yang cocok untuk diterapkan dan digunakan dalam pembelajaran jarak jauh agar para tenaga pengajar maupun mahasiswa dapat terbantu untuk memahami materi yang diberikan kemudian penelitian ini juga bertujuan untuk memaksimalkan penggunaan data internet dalam pembelajaran jarak jauh.
Sustainable Mining? Applying the Framework for Strategic Sustainable Development to Mining Projects

Precious and base metal mining projects can serve as a stepping-stone in moving the mining industry towards achieving compliance with a scientific-principled definition of global socio-ecological sustainability. Using the Framework for Strategic Sustainable Development to assess the current reality of mine project development has resulted in identifying gaps between current best practices and a desired vision of sustainability constrained by science based principles. These gaps provide opportunities for sustainability driven innovation. Evaluation of mining project phases and their impacts on ecological and social systems using the four Sustainability Principles highlight specific opportunities to create value for social, economic and ecologic systems. Companies choosing to develop mining projects using the Framework for Strategic Sustainable Development can expect to achieve many business benefits, including improved reputation, increased transparency and stakeholder trust. Strengthening these aspects will provide robust support to companies as they manoeuvre to define their role in a sustainable society. This thesis examines how current processes for mining projects can be developed to support a successful transition into a sustainable society.
Learning how to break rules: An exploration of why organizations still function despite dysfunctional rules

Rule breaking in organizations has traditionally been seen as deconstructive actions by angry or self-interested employees. An emerging research area is seeking to highlight a type of rule breaking behaviour that may bene t organizations. Some authors label this type of rule breaking \pro social rule breaking" and it refers to when employees break rules for such reasons as saving time or money for their company, or preserving customer relations. Instead of antagonizing the rule breaking employee, the pro-social rule breaking research area opens up for new perspectives on employees' motivations for breaking rules. The pro-social rule breaking has contributed to the organizational research area by acknowledging that rule-breaking behaviour occurs frequently in organizations, and that employees who break rules are motivated by things other than self-interest. Organizational rules are created by some part of the organization that perceives itself as having a better grasp of schedules and constraints than the employees who receive the rules. Dismissing rule breaking behaviour as isolated actions motivated by selfinterest leads rule-makers to have an incomplete understanding of how their rules are interpreted at the receiving end. This is of current importance to the IT industry where many companies are in the process of transitioning from waterfall to agile methodologies. This thesis is aimed at contributing to the emerging cause of acknowledging rule-breaking actions as potentially constructive. The report accounts for a multiple case study with the purpose of investigating how newcomers to organizations learn how to break rules. The research purpose made it possible for us to discuss rules, rule-interpretations and communication of rules and rule-breaking with new employees who had recently been included in the organization's social constructs. The study nds that employees most often learn how to break rules through socialization, and mostly through observing other employees deviating from rules. Rules are in many cases broken because they are found to be inadequate or even misleading in a certain situations. Employees are reluctant to changing a rule even if it is frequently broken; they nd that rules are guiding even if broken.The study also concludes that rule breaking is rarely spoken of in organizations. A rulemaker cannot teach rule breaking without changing the rule receiver's interpretation of the rule. The interpretation of the rule controls behaviour in relation to the rule. This phenomena is attributed to a social mechanism which we label \the interpretation system". The interpretation system is a part of the norms within a group that tell members how to interpret rules. By approaching rule breaking as objective researchers we were able to uncover how employees interpret rules; information which is normally obscured to the rule-designers within an organization. This is perhaps the most valuable contribution of this thesis.
Key User Extraction Based on Telecommunication Data

The number of systems that collect vast amount of data about users rapidly grow during last few years. Many of these systems contain data not only about people characteristics but also about their relationships with other system users. From this kind of data it is possible to extract a social network that reflects the connections between system’s users. Moreover, the analysis of such social network enables to investigate different characteristics of its users and their linkages. One of the types of examining such network is key users extraction. Key users are these who have the biggest impact on other network users as well as have big influence on network evolution. The obtained knowledge about these users enables to investigate and predict changes within the network. So this knowledge is very important for the people or companies who make a profit from the network like telecommunication company. The second important issue is the ability to extract these users as quick as possible, i.e. developed the algorithm that will be time-effective in large social networks where number of nodes and edges is equal few millions.
A Numerical Study of the Effects of Superhydrophobic Surfaces on Skin-Friction Drag Reduction in Wall-Bounded Shear Flows

Recent developments of superhydrophobic surfaces (SHSs) have attracted much attention because of the possibility of achieving substantial skin-friction drag reduction at high Reynolds number turbulent flows. An SHS, consisting of a hydrophobic surface combined with micro- or nano-scaled topological features, can yield an effective slip length on the order of several hundred microns. In this numerical study, direct numerical simulations of turbulent channel flows and turbulent boundary layers (TBLs) developing over SHSs were performed. An SHS was modeled through the shear-free boundary condition, assuming the sustainable gas-liquid interface remained as a flat surface. For the considered Reynolds number ranges and SHS geometries, it was found that the effective slip length normalized by viscous wall units was the key parameter and the effective slip length should be on the order of the buffer layer in order to have the maximum benefit of drag reduction. The effective surface slip length can be interpreted as a depth of influence into which SHSs affect the flow in the wall-normal direction. This result demonstrates that an SHS achieves its drag reduction by affecting the turbulence structures within the buffer layer of wall-bounded turbulent flow. It was also found that the width of an SHS, relative to the spanwise width of near-wall turbulence structures, was also a key parameter to the total amount of drag reduction. Significant suppression of near-wall turbulence structures were observed, which resulted in large skin-friction drag reduction due to the lack of the shear over SHSs. A comparison between TBLs and turbulent channel flows over SHSs were also examined. In contrast to fully developed turbulent channel flows, the effective slip velocity and hence the effective slip length varied in the streamwise direction of TBL, implying that total drag reduction of TBL would depend on the streamwise length of a given SHS. The present numerical study was compared with recent experimental results and showed good agreement. In addition to flow and SHS geometry conditions, the streamwise length of SHSs was also a key factor to understand the underlying physics of wall-bounded shear flows. Finally, it was found that the amount of drag reduction was theoretically estimated as a function of the effective slip length normalized by viscous wall units.
Multiple Potential Fields in Quake 2 Multiplayer

This thesis may be interesting for developers within video game industry, people who design the behaviour of agent systems, or those interested in complex robotic control systems. What potential fields give to the world of AI is a new way to implement the behaviour of the agents, giving weights to all the elements in the world, so the agent can decide if making some action deserves the cost, the combination of several potential fields is what makes this technique so efficient. An agent was created applying this technique. Implemented as a client application, the agent used the Quake protocol to connect and communicate with the server. Some tests were run on the model concerning the different functionalities a gamer agent should implement. The model turned out to be a success in a virtual environment like quake 2. Taking care of all the entities in the map and environmental factors, the agent is able to keep his state in balance, move to the most interesting positions and be able to face combat situations. The implementation is clean and mathematical oriented. Using algorithms as the heart of the model, we make the code lightweight in comparison with old bot models.