Miracle-dz/UniFAR-FTUs huggingface dataset:
Mosaic Hemagglutinin-Based Whole Inactivated Virus Vaccines Induce Broad Protection Against Influenza B Virus Challenge in Mice

Influenza viruses undergo antigenic changes in the immuno-dominant hemagglutinin (HA) head domain, necessitating annual re-formulation of and re-vaccination with seasonal influenza virus vaccines for continuing protection. We previously synthesized mosaic HA (mHA) proteins of influenza B viruses which redirect the immune response towards the immuno-subdominant conserved epitopes of the HA via sequential immunization. As ~90% of current influenza virus vaccines are manufactured using the inactivated virus platform, we generated and sequentially vaccinated mice with inactivated influenza B viruses displaying either the homologous (same B HA backbones) or the heterologous (different B HA backbones) mosaic HAs. Both approaches induced long-lasting and cross-protective antibody responses showing strong antibody-dependent cellular cytotoxicity (ADCC) activity. We believe the B virus mHA vaccine candidates represent a major step towards a universal influenza B virus vaccine.
A Large-Scale Interview Study on Information Security in and Attacks against Small and Medium-sized Enterprises

Cybercrime is on the rise. Attacks by hackers, organized crime and nation-state adversaries are an economic threat for companies world-wide. Small and medium-sized enterprises (SMEs) have increasingly become victims of cyber-attacks in recent years. SMEs often lack the awareness and resources to deploy extensive information security measures. However, the health of SMEs is critical for society: For example, in Germany, 38.8% of all employees work in SMEs, which contributed 31.9% of the German annual gross domestic product in 2018. Many guidelines and recommendations encourage companies to invest more into their information security measures. However, there is a lack of understanding of the adoption of security measures in SMEs, their risk perception with regards to cybercrime and their experiences with cyberattacks. To address this gap in research, we performed 5,000 computer-assisted telephone-interviews (CATIs) with representatives of SMEs in Germany. We report on their experiences with cybercrime, management of information security and risk perception. We present and discuss empirical results of the adoption of both technical and organizational security measures and risk awareness in SMEs. We ﬁnd that many technical security measures and basic awareness have been deployed in the majority of companies. We uncover differences in reporting cybercrime incidences for SMEs based on their industry sector, company size and security awareness. We conclude our work with a discussion of recommendations for future research, industry and policy makers.
The method for recovering lithium

Object of the present invention is to provide a method for recovering lithium, which is capable of efficiently recovering phosphorous, fluorine impurities from the separation of lithium from the lithium ion battery containing a lithium-containing solution of lithium hexafluorophosphate. In the present invention, the addition to the lithium-containing alkali hydroxide solution, the pH is 9 or more, thereby forming a phosphate and a fluoride salt precipitate, the precipitate formed separated and removed, recovering lithium from the filtrate.
COVID-19 Vaccination in Pregnancy and Lactation: Current Research and Gaps in Understanding

The COVID-19 pandemic has demonstrated the urgent need to develop vaccine strategies optimized for pregnant people and their newborns, as both populations are at risk of developing severe disease. Although not included in COVID-19 vaccine development trials, pregnant people have had access to these vaccines since their initial release in the US and abroad. The rapid development and distribution of novel COVID-19 vaccines to people at risk, including those who are pregnant and lactating, presents an unprecedented opportunity to further our understanding of vaccine-induced immunity in these populations. In this review, we aim to summarize the literature to date on COVID-19 vaccination in pregnancy and lactation and highlight opportunities for investigation that may inform future maternal vaccine development and implementation strategies.
CIPHERLEAKS: Breaking Constant-time Cryptography on AMD SEV via the Ciphertext Side Channel

AMD’s Secure Encrypted Virtualization (SEV) is a hardware extension available in AMD’s EPYC server processors to support conﬁdential cloud computing. While various prior studies have demonstrated attacks against SEV by exploiting its lack of encryption in the VM control block or the lack of integrity protection of the encrypted memory and nested page tables, these issues have been addressed in the subsequent releases of SEV-Encrypted State (SEV-ES) and SEV-Secure Nested Paging (SEV-SNP). In this paper, we study a previously unexplored vulnerability of SEV, including both SEV-ES and SEV-SNP. The vulnerability is dubbed ciphertext side channels, which allows the privileged adversary to infer the guest VM’s execution states or recover certain plaintext. To demonstrate the severity of the vulnerability, we present the C IPHER L EAKS attack, which exploits the ciphertext side channel to steal private keys from the constant-time implementation of the RSA and the ECDSA in the latest OpenSSL library.
Tumor-Associated Macrophages and Their Functional Transformation in the Hypoxic Tumor Microenvironment

Tumor-associated macrophages (TAMs) are some of the most abundant immune cells within tumors and perform a broad repertoire of functions via diverse phenotypes. On the basis of their functional differences in tumor growth, TAMs are usually categorized into two subsets of M1 and M2. It is well established that the tumor microenvironment (TME) is characterized by hypoxia along with tumor progression. TAMs adopt an M1-like pro-inflammatory phenotype at the early phases of oncogenesis and mediate immune response that inhibits tumor growth. As tumors progress, anabatic hypoxia of the TME gradually induces the M2-like functional transformation of TAMs by means of direct effects, metabolic influence, lactic acidosis, angiogenesis, remodeled stroma, and then urges them to participate in immunosuppression, angiogenesis and other tumor-supporting procedure. Therefore, thorough comprehension of internal mechanism of this TAM functional transformation in the hypoxic TME is of the essence, and might provide some novel insights in hypoxic tumor immunotherapeutic strategies.
Adaptive Parameter Modulation of Deep Brain Stimulation Based on Improved Supervisory Algorithm

Clinically deployed deep brain stimulation (DBS) for the treatment of Parkinson’s disease operates in an open loop with fixed stimulation parameters, and this may result in high energy consumption and suboptimal therapy. The objective of this manuscript is to establish, through simulation in a computational model, a closed-loop control system that can automatically adjust the stimulation parameters to recover normal activity in model neurons. Exaggerated beta band activity is recognized as a hallmark of Parkinson’s disease and beta band activity in model neurons of the globus pallidus internus (GPi) was used as the feedback signal to control DBS of the GPi. Traditional proportional controller and proportional-integral controller were not effective in eliminating the error between the target level of beta power and the beta power under Parkinsonian conditions. To overcome the difficulties in tuning the controller parameters and improve tracking performance in the case of changes in the plant, a supervisory control algorithm was implemented by introducing a Radial Basis Function (RBF) network to build the inverse model of the plant. Simulation results show the successful tracking of target beta power in the presence of changes in Parkinsonian state as well as during dynamic changes in the target level of beta power. Our computational study suggests the feasibility of the RBF network-driven supervisory control algorithm for real-time modulation of DBS parameters for the treatment of Parkinson’s disease.
Fuzzy-Based Mobile Edge Orchestrators in Heterogeneous IoT Environments: An Online Workload Balancing Approach

Online workload balancing guarantees that the incoming workloads are processed to the appropriate servers in real time without any knowledge of future resource requests. Currently, by matching the characteristics of incoming Internet of Things (IoT) applications to the current state of computing and networking resources, a mobile edge orchestrator (MEO) provides high-quality service while temporally and spatially changing the incoming workload. Moreover, a fuzzy-based MEO is used to handle the multicriteria decision-making process by considering multiple parameters within the same framework in order to make an offloading decision for an incoming task of an IoT application. In a fuzzy-based MEO, the fuzzy-based offloading strategy leads to unbalanced loads among edge servers. Therefore, the fuzzy-based MEO needs to scale its capacity when it comes to a large number of devices in order to avoid task failures and to reduce service times. In this paper, we investigate and propose an online workload balancing algorithm, which we call the fuzzy-based (FuB) algorithm, for a fuzzy-based MEO. By considering user configuration requirements, server geographic locations, and available resource capacities for achieving an online algorithm, our proposal allocates the proximate server for each incoming task in real time at the MEO. A simulation was conducted in augmented reality, healthcare, compute-intensive, and infotainment applications. Compared to two benchmark schemes that use the fuzzy logic approach for an MEO in IoT environments, the simulation results (using EdgeCloudSim) show that our proposal outperforms the existing algorithms in terms of service time, the number of failed tasks, and processing times when the system is overloaded.
Injection Attacks Reloaded: Tunnelling Malicious Payloads over DNS

The traditional design principle for Internet protocols indicates: “Be strict when sending and tolerant when receiv-ing” [RFC1958], and DNS is no exception to this. The transparency of DNS in handling the DNS records, also standardised speciﬁcally for DNS [RFC3597], is one of the key features that made it such a popular platform facilitating a constantly increasing number of new applications. An application simply creates a new DNS record and can instantly start dis-tributing it over DNS without requiring any changes to the DNS servers and platforms. Our Internet wide study conﬁrms that more than 1.3M (96% of tested) open DNS resolvers are standard compliant and treat DNS records transparently. In this work we show that this ‘transparency’ introduces a severe vulnerability in the Internet: we demonstrate a new method to launch string injection attacks by encoding malicious payloads into DNS records. We show how to weaponise such DNS records to attack popular applications. For instance, we apply string injection to launch a new type of DNS cache poisoning attack, which we evaluated against a population of open resolvers and found 105K to be vulnerable. Such cache poisoning cannot be prevented with common setups of DNSSEC. Our attacks apply to internal as well as to public services, for instance, we reveal that all eduroam services are vulnerable to our injection attacks, allowing us to launch exploits ranging from unauthorised access to eduroam networks to resource starvation. Depending on the application, our attacks cause system crashes, data corruption and leak-age, degradation of security, and can introduce remote code execution and arbitrary errors.
U Can't Debug This: Detecting JavaScript Anti-Debugging Techniques in the Wild

Through security contests such as Pwn2Own, we are constantly reminded that no complex piece of software should ever be considered secure. As we execute untrusted code in our browser every day, browser exploits written in JavaScript remain a constant threat to the security of our systems. In particular, evasive malware that detects analysis systems and then changes its behavior is a well-known problem. However, there are also anti-debugging techniques that interfere with the manual analysis of a website in a real browser. These techniques try to prevent, or at least slow down, any attempts at manually inspecting and debugging the JavaScript code of a website. For example, such a technique could constantly trigger breakpoints at random locations to effectively hinder single-stepping while debugging the code. More cunningly, it could also find out whether the browser’s integrated Developer Tools are open by using certain sidechannels available in JavaScript. With this knowledge, it is possible to subtly alter or suppress any malicious behavior while under analysis. In this paper, we systematically explore this phenomenon. To this end, we introduce 9 anti-debugging techniques and discuss their advantages and drawbacks. We then conduct a large-scale study on 6 of them, to investigate the prevalence of these techniques in the wild. We find that as many as 1 out of 550 websites contain severe anti-debugging measures, with multiple of these techniques active on the same site. Moreover, we present a novel approach based on a deterministic website replay and a comparison of JavaScript code coverage. The approach can automatically detect the remaining 3 timingbased anti-debugging techniques, which use side-channels to learn if the DevTools are open. In a targeted study on 2000 websites with anti-debugging techniques, we discover over 200 of them indeed execute different code when under analysis.
Pursuing Usable and Useful Data Downloads Under GDPR/CCPA Access Rights via Co-Design

Data privacy regulations like GDPR and CCPA deﬁne a right of access empowering consumers to view the data companies store about them. Companies satisfy these requirements in part via data downloads , or downloadable archives containing this information. Data downloads vary in format, organization, comprehensiveness, and content. It is unknown, however, whether current data downloads actually achieve the trans-parency goals embodied by the right of access. In this paper, we report on the ﬁrst exploration of the design of data down-loads. Through 12 focus groups involving 42 participants, we gathered reactions to six companies’ data downloads. Using co-design techniques, we solicited ideas for future data download designs, formats, and tools. Most participants indicated that current offerings need improvement to be useful, emphasizing the need for better ﬁltration, visualization
This paper is included in the Proceedings of the Seventeenth Symposium on Usable Privacy and Security.

This paper reports the security and privacy challenges and threats that people experience while working from home. We conducted semi-structured interviews with 24 participants working from home in the three weeks preceding the study. We asked questions related to participants’ challenges with telecommuting. Our results suggest that participants experienced challenges, threats, and potential outcomes of threats associated with the technological, human, organizational, and environmental dimensions. We also discovered two threat models: one in which the employer’s asset is at stake and another in which the employee’s privacy is compromised. We believe these insights can lead to better support for employees and possibly reduce cyber-attacks associated with telecom-muting during the pandemic and beyond.
Foliar Application of Nitrogen Affects Metabolism and Productivity of Soybean

Soybean is one of the world’s most economically important crops and several factors can affect the productivity of this culture. Among these factors is the supply of needed nitrogen, especially in the reproductive stage, as it acts in photosynthetic activity and in grain filling. In view of this, the objective of our work was to evaluate the effect of foliar application of nitrogen in different reproductive stages in soybean culture. Two sources of nitrogen were used: conventional urea and urea-formaldehyde/triazone, both applied in reproductive stages R2, R3, R4, or R5, as well as a control treatment without foliar application of nitrogen. Plants submitted to foliar application of urea-formaldehyde/triazone showed an increase in nitrogen metabolism (percentage of nitrogen derived from the atmosphere [Ndfa] and nitrate reductase activity [NR]), an increase in peroxidase (POD), and the consequent reduction in hydrogen peroxide (H2O2) in all stages of application of this treatment. When urea-formaldehyde/triazone was applied in R4, it resulted in a 7% increase in yield. The application of conventional urea in reproductive stages R4 and R5 increased nitrogen metabolism and resulted in an increase in yield by 4%. However, conventional urea reduced yield when applied in stages R2 and R3. The use of low doses of foliar nitrogen in stages R4 and R5, increased nitrogen metabolism in soybean plants. The timing of the application has a direct impact on the results with the slow-release nitrogen (urea formaldehyde /triazone) showing better results when applied in stage R4 and better results for conventional urea in R5.
PROVIDE: a probabilistic framework for unsupervised video decomposition

Unsupervised multi-object scene decomposition is a fast-emerging problem in representation learning. Despite signiﬁcant progress in static scenes, such models are unable to leverage important dynamic cues present in videos. We propose PROVIDE, a novel unsupervised framework for PRObabilistic VIdeo DEcomposition based on a temporal extension of iterative inference. PROVIDE is powerful enough to jointly model complex individual multi-object representations and explicit temporal dependencies between latent variables across frames. This is achieved by leveraging 2D-LSTM, temporally conditioned inference and generation within the iterative amortized inference for posterior re-ﬁnement. Our method improves the overall quality of decompositions, encodes information about the objects’ dynamics, and can be used to predict trajectories of each object separately. Additionally, we show that our model has a high accuracy even without color information. We demonstrate the decomposition capabilities of our model and show that it outperforms the state-of-the-art on several benchmark datasets, one of which was curated for this work and will be made publicly available.
CIA_A_256425 827..839

1Trauma Research Center, AJA University of Medical Sciences, Tehran, Iran; 2Student Research Committee, Babol University of Medical Sciences, Babol, Iran; 3Cellular and Molecular Biology Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran; 4Department of Clinical Biochemistry, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran; 5Student Scientific Research Center, Tehran University of Medical Sciences, Tehran, Iran; 6Metabolic Disorders Research Center, Golestan University of Medical Sciences, Gorgan, Iran; 7Department of Clinical Biochemistry, School of Medicine, Urmia University of Medical Sciences, Urmia, Iran; 8School of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran Abstract: Different factors influence the development and control of ageing. It is well
Alterations of Productive and Reproductive Efficiencies in Dairy Cows by the Inclusion of Protected Fats and Full-Fat Soy in the Diet

This study aimed to explore the impacts of protected fat and full-fat soybean on the dry matter intake, milk production and composition, blood metabolites and reproductive traits of early lactating dairy cows. Eighteen dairy cows at early lactation were randomly assigned into two equal groups (G; n= 9/G). Cows were housed in semi-shaded open barn with free access to fresh water and salt blocks licks. Cows of MEGALAC group (control) were fed on the basal diet of a concentrate mixture containing 10% soybean and supplementation of 600 g of protected fat /cow/ day and green roughage was offered three times a day. Cows of Full-Fat Soy group were offered a diet in which the soybean meal was replaced by extruded full-fat soy (10%) without a supplement of MEGALAC and green roughage as above. Results revealed that mean value of dry matter intake, feed efficiency, milk SNF, lactose and total solids were higher in the MEGALAC group. MEGALAC diet tended to increase milk yield, fat corrected milk and energy corrected milk. Conversely, milk fat/ protein ratio was higher in FullFat Soy group, however FullFat Soy diet decreased (P< 0.05) capric acid (C10:0), but tended to increase oleic acid (C18:1). Serum omega-3 fatty acid was higher in the MEGALAC group, while the ratio of omega-6/ omega-3 was lower in the MEGALAC group than FullFat Soy group. FullFat Soy diet increased serum albumin and albumin/ globulin ratio, while decreased serum globulin and urea. Concentrations of both Non-Esterified Fatty Acids (NEFA) and β-Hydroxy Butyrate (BHB) were not different between groups. Mean pulse rate was higher in MEGALAC group. Moreover, rectal temperature ranges within the normal values in MEGALAC group, but not in FullFat Soy group. MEGALAC diet decreased rectal temperature and respiration rate but not significant in cows exposed to heat stress. In conclusion, evidently, protected fat supplementation given to early lactating-dairy cows has shown positive impacts on their productive and reproductive traits.
WEAKNESSES IN THE KNOWLEDGE OF CRITICAL CARE UNIT TEAMS RELATED TO THE PROCESS OF ORGAN AND TISSUE DONATION

Objective: To assess the weaknesses of the teams of the critical care units related to the donation process. Method: A cross-sectional study conducted with 150 health professionals. Data collection took place between 2017 and 2018 in two public hospitals in Santa Catarina, with the aid of a specific instrument on the stages process of organ and tissue donation. Data was analyzed by absolute and relative frequencies, Kolmogorov-Smirnov and Mann-Whitney tests. Results: Hit rates: criteria for starting the diagnosis of brain death 137 (91.3%) and clinical signs of brain death 126 (84%). Weaknesses: criteria that prevent the diagnosis of brain death 36 (24%) and sequence of the stages of the donation process 56 (37%). There was a correlation between the length of professional activity in the unit and the criteria that prevent the diagnosis of Death p=0.039. Conclusion: The results can support actions in the face of the weaknesses, impacting on the improvement of the organ and tissue donation and transplantation process. DESCRIPTORS: Brain Death; Tissue and Organ Procurement; Nursing; Patient Care Team; Intensive Care Units. HOW TO REFERENCE THIS ARTICLE: Cordeiro TV, Knihs N da S, Magalhães ALP, Barbosa S de FF, Paim SMS. Weaknesses in the knowledge of critical care unit teams related to the process of organ and tissue donation. Cogitare enferm. [Internet]. 2020 [access “insert day, monh and year”]; 25. Available at: http://dx.doi. org/10.5380/ce.v25i0. 66128. 1Nurse. Resident in Family Health. Florianópolis City Hall. Florianópolis, SC, Brazil. 2Nurse. PhD in Nursing. Nursing Professor of the Federal University of Santa Catarina. Florianópolis, SC, Brazil. 3Nurse. PhD in Nursing. Nursing Professor of the Federal University of Santa Catarina. Florianópolis, SC, Brazil. 4Nurse. PhD in Nursing. Nursing Professor of the Federal University of Santa Catarina. Florianópolis, SC, Brazil. 5Nursing student. Federal University of Santa Catarina. Florianópolis, SC, Brazil. This work is licensed under a Creative Commons Attribution 4.0 International License. Tamara Vieira Cordeiro1, Neide da Silva Knihs2, Aline Lima Pestana Magalhães3, Sayonara de Fátima Faria Barbosa4, Sibele Maria Schuantes Paim5 dx.doi. org/10.5380/ce.v25i0. 66128 Cogitare enferm. 25: e66128, 2020