Miracle-dz/UniFAR-FTUs huggingface dataset:
Antibody masked cytokines as new approach in targeted tumor therapy

Cytokine-based cancer therapies are commonly applied treatment strategies in oncology. A prominent representative of this potent class of anti-tumor agents is interferon alpha. Interferon is well known for its anti-viral and anti-proliferative activities and a potent therapeutic agent in the treatment of multiple myeloma, chronic myeloid leukemia (CML), hairy cell leukemia (HCL) and malignant melanoma. Unfortunately, the application of interferon is always accompanied by severe adverse side effects and shows a strong toxicological profile. In order to overcome these obstacles and generate a more suitable therapeutic agent, a bispecific interferon-antibody fusion protein was designed. By introducing multiple point mutations, the pharmacodynamic potency of the cytokine was significantly improved compared to wild type interferon by increasing its affinity to the receptor IFNAR1. In order to prevent undesired interactions of the fusion protein during circulation in the periphery and consequently decrease toxic side effects, a masking antibody was connected by a linker sequence which led to a temporary neutralization of interferon. Local reactivation of the cytokine at the tumor site was initiated by the efficient cleavage of the dual MMP-9- and matriptase-cleavable linker peptide between masking antibody and interferon with suitable turnover rates. In addition, enrichment of the interferon fusion protein at the tumor site was enforced by using one arm of the antibody for targeting the fusion protein to the multiple myeloma-associated antigen CD138, as successfully confirmed by confocal microscopy. The potent anti-proliferative activity of the cytokine in combination with a striking interferon masking effect by the linked antibody were shown in several cell lines originating from different oncologic indications. The promising approach of temporary inhibition of the cytokine in combination with tumor-selective reactivation of its pharmacodynamic potency holds the potential to overcome current limitations in cytokine-based treatment strategies and makes a broad clinical application of this extraordinary class of biomolecules in oncology feasible.
A Novel Ensemble Method for Advanced Intrusion Detection in Wireless Sensor Networks

With the increase of cyber attack risks on critical infrastructures monitored by networked systems, robust Intrusion Detection Systems (IDSs) for protecting the information have become vital. Designing an IDS that performs with maximum accuracy with minimum false alarms is a challenging task. Ensemble method considered as one of the main developments in machine learning in the past decade, it finds an accurate classifier by combining many classifiers. In this paper, an ensemble classification procedure is proposed using Random Forest (RF), DensityBased Spatial Clustering of Applications with Noise (DBSCAN) and Restricted Boltzmann Machine (RBM) as base classifiers. RF, DBSCAN, and RBM techniques have been used for classification purposes. The ensemble model is introduced for achieving better results. Bayesian Combination Classification (BCC) has been adopted as a combination technique. Independent BCC (IBCC) and Dependent BCC (DBCC) have been tested for performance comparison. The model shows a promising result for all classes of attacks. DBCC performs over IBCC in terms of accuracy and detection rates. Through simulations under a wireless sensor network scenario, we have verified that DBCC-based IDS works with $\approx 100\%$ detection and $\approx 1.0$ accuracy rate in the existence of intrusive behavior in the tested Wireless Sensor Network (WSN).
Modelling the distribution of a threatened habitat: the California sage scrub

Aim Using predictive species distribution and ecological niche modelling our objectives are: (1) to identify important climatic drivers of distribution at regional scales of a locally complex and dynamic system – California sage scrub; (2) to map suitable sage scrub habitat in California; and (3) to distinguish between bioclimatic niches of floristic groups within sage scrub to assess the conservation significance of analysing such species groups.
Analysis of diversity and multiplexing tradeoff for multi-antenna systems with covariance feedback

We study a single-user multi-antenna system with perfect channel state information (CSI) at the receiver and imperfect CSI at the transmitter. The common downlink transmission model is assumed with one or more uncorrelated receive antennas and correlated transmit antennas. Zheng and Tse (see IEEE Transactions on Information Theory, Jan., 2002) discussed the tradeoff between diversity advantage and multiplexing gain for the asymptotic high SNR regime. At low and mid-range SNR values the connection between the multiplexing gain and diversity is not cleared. We extend our results for the optimal power allocation in MISO and MIMO systems with covariance feedback in order to characterize the multiplexing gain in small and mid-range SNR regions. We give analytical results for the case in which the optimal transmit covariance matrix has rank 1 the equivalent to the multiplexing gain. In addition to this, we discuss the outage capacity and its optimization for the MISO and MIMO case. We provide an asymptotic result for the outage probability which enables us to measure the impact of correlation on the outage probability.
A TM2 Residue in the β1 Subunit Determines Spontaneous Opening of Homomeric and Heteromeric γ-Aminobutyric Acid-gated Ion Channels*

γ-Aminobutyric acid type A (GABAA) receptors are major inhibitory neurotransmitter-gated ion channels in the central nervous system. GABAA receptors consist of multiple subunits and exhibit distinct pharmacological and channel properties. Of all GABAA receptor subunits, the β subunit is thought to be a key component for the functionality of the receptors. Certain types of GABAA receptors have been found to be constitutively active. However, the molecular basis for spontaneous opening of channels of these receptors is not totally understood. In this study, we showed that channels that contain the β1 but not β3 subunits opened spontaneously when these subunits were expressed homomerically or co-expressed with other types of GABAA receptor subunits in Xenopus oocytes. Using subunit chimeras and site-directed mutagenesis, we localized a key amino acid residue, a serine at position 265, that is critical in conferring an open state of the β1 subunit-containing GABAA receptors in the absence of agonist. Moreover, some point mutations of Ser-265 also produced constitutively active channels. The magnitude of spontaneous activity of these receptors was correlated with the molecular volume of the residue at 265 for both homomeric and heteromeric GABAA receptors, suggesting that the spontaneous activity of the β1 subunit-containing GABAA receptors may be mediated through a similar molecular mechanism that is dependent on the molecular volume of the residue at 265.
Prevalence of root filled teeth in an adult population (lviv, ukraine) found on digital panoramic radiographs.

OBJECTIVE The aim of this study was to determine the frequency of endodontic treatment in an adult Ukrainian population in relation to the age and its distribution depending on the type of the teeth. PATIENTS AND METHODS Materials and methods: A total of 435 digital panoramic radiographs of adults (aged 18 to 72 years) were examined. A tooth was qualified as root filled (endodontically treated), if radiopaque root-filling material was determined in the pulp chamber and/or in the root canals. Pearson's chi-squared test (χ2) and Spearman's rank correlation were applied for data analysis. RESULTS Results: It was revealed that 82.5% of patients had previously received endodontic treatment of the teeth. The overall percentage of root filled teeth in adult dentition is 12.08%. The analysis of the rate of endodontically treated teeth in different age groups identified an increasing of treated teeth with age - from 5.2% in the youngest cohort (18-19 years old) to 24.9% in the oldest cohorts. It was revealed that 822 teeth (14.2%) on maxilla and 569 (9.9%) on the mandible were endodontically treated. Most often root filled teeth were first mandibular molars (39.3%), first maxillary molars (26.7%) and second maxillary premolars (20.4%). Much lower rate of endodontic treatment were considered in lower mandibular incisors and canines (0.7%, 0.9% and 1.5% respectively). CONCLUSION Conclusions: A total of 82.5% examined adults had one or more endodontically treated teeth in this study. The obtained results prove the necessity of prevention of carieswith special emphasis on the first maxillary and mandibular molars, and maxillary second premolars, which have significantly higher frequency of root canal treatment in comparison to other teeth groups.
Abiotic factors promote plant heterogeneity and influence herbivore performance and mortality in Gambel's oak (Quercus gambelii)

Environmental gradients are expected to alter the relative effects of host‐plants and natural enemies on phytophagous insects. Moreover, studies of gradients may assist in an identification of the factors important to the outcomes of trophic interactions. We investigated the role of elevation‐based variation in environmental conditions (temperature and relative humidity) and foliar nitrogen on tri‐trophic interactions in Quercus gambelii Nutt. (Fagaceae) during 2001 and 2002. Quercus gambelii displayed significant elevational and seasonal fluctuation in foliar nitrogen content, and sites with similar environmental conditions produced similar foliar quality. However, leaf‐miners, Phyllonorycter spec. (Lepidoptera: Gracillariidae) and Cameraria spec. (Lepidoptera: Gracillariidae), did not perform better on trees with a greater nitrogen content. Overall densities of both species declined significantly in 2002, most likely due to severe drought conditions in the south‐western USA. Both species exhibited significant, but distinct, patterns in emergence rate with elevation. While environmentally based fluctuation in foliar nitrogen failed to predict the result of trophic interactions, site environmental conditions, as measured by temperature and relative humidity, were strongly related to differences in leaf‐miner performance and mortality. The ordination of sites by variation in environmental conditions accurately predicts the relative effect of unexplained vs. natural‐enemy sources of mortality for leaf‐miners.
A Modern Dilemma: How Experts Grapple with Ambiguous Genetic Test Results

Objective. Clinicians regularly use panel genetic testing to identify hereditary breast cancer risk, but this practice increases the rate of receiving an ambiguous test result, the variant of uncertain significance (VUS). VUS results are a growing and long-term challenge for providers and have caused negative patient outcomes. The objective of this study was to elicit expert opinions about patients’ decision making after receiving a VUS result to provide future guidance for VUS disclosure. Methods. Using an adapted mental models approach, experts (N = 25) completed an online survey and in-depth interview eliciting qualitative judgments of the factors relevant to informed patient decision making after receiving a VUS result. Content analysis of interview transcripts clarified the basis for these judgments. Results. Participants identified 11 decisions facing patients after receiving VUS results grouped into ambiguity management or risk management. The experts also identified 24 factors relevant to each decision, which reflected 2 themes: objective factors (e.g., clinical information, guidelines) and psychosocial factors (e.g., understanding or risk perception). Conclusion. This study presents an adaptation of the mental models approach for communication under conditions of ambiguity. Findings suggest providers who present VUS results from genetic testing for hereditary breast cancer should discuss decisions related to ambiguity management that focus on hope for future reclassification, and be directive when discussing risk management decisions. Objective and psychosocial factors should influence both ambiguity and risk management decisions, but especially risk management decisions.
Fundus Retinal Blood Vessel Segmentation Based on Active Learning

In this article, we conducted a blood vessel segmentation experiment by using an active learning method. Using fewer manually labeled pictures to train a neural network, the accuracy of the obtained blood vessel segmentation exceeded that of supervised learning. The highest accuracy is 96.97%. It is proved that active learning can reduce the workload of human annotation data and improve the accuracy of blood vessel segmentation.
Status of IL‐4 and IL‐10 driven markers in experimental models of Visceral Leishmaniasis

Leishmania donovani, the causative agent for visceral leishmaniasis (VL), modulates host monocytes/macrophages to ensure its survival. However, knowledge regarding the host‐parasite interactions underpinning the disease remains limited. As disease progression is associated with polarization of monocytes/macrophages towards M2, which is regulated by cytokines IL‐4/IL‐13 and IL‐10, this study evaluated the status of key IL‐4‐ and IL‐10 driven markers in experimental models of VL, as also evaluated their correlation, if any, with parasite load.
High Boredom Proneness and Low Trait Self-Control Impair Adherence to Social Distancing Guidelines during the COVID-19 Pandemic

Social distancing during the coronavirus-disease-2019 (COVID-19) pandemic is crucial to reduce the spread of the virus. However, its effectiveness hinges on adherence by individuals who face substantial burdens from the required behavioral restrictions. Here, we investigate sources of individual variation in adhering to social distancing guidelines. In a high-powered study (N = 895), we tested direct and indirect effects of boredom and self-control on adherence. The results showed that both traits were important predictors of adherence but the underlying mechanisms differed. Specifically, individuals high in boredom perceived social distancing as more difficult, which in turn reduced their adherence (i.e., a mediated effect). In contrast, individuals high in self-control adhered more to the guidelines without perceiving them as more or less difficult; however, self-control moderated the effect of difficulty on adherence. Our results are immediately relevant to improve the efficacy of social distancing guidelines in the COVID-19 response.
A Secure and Energy-Aware Approach For Cognitive Radio Communications

The cognitive radio (CR) technique has revealed a novel way of utilizing the precious radio spectrum via allowing unlicensed users to opportunistically access unutilized licensed bands. Using such a technique enables agile and flexible access to the radio spectrum and can resolve the spectrum-scarcity problem and maximize spectrum efficiency. However, two major impediments have been limiting the widespread adoption of cognitive radio technology. The software-defined radio technology, which is the enabling technology for the CR technique, is power-hungry and this raises a major concern for battery-constrained devices such as smart phones and laptops. Secondly, the opportunistic and open nature of the CR can lead to major security concerns about the data being sent and how safe it is. In this paper, we introduce an energy-and-security-aware CR-based communication approach that alleviates the power consumption of the CR technique and enhances its security measures according to the confidentiality level of the data being sent. Furthermore, the proposed approach takes into account user-related factors, such as the user’s battery level and user’s data type, and network-related factors, such as the number of unutilized bands and vulnerability level and then models the research question as a constrained optimization problem. Considering the time complexity of the optimum solution, we also propose a heuristic solution. We examine the proposed solution against existing solutions, and our obtained results show that the proposed approach can save energy consumption up to 18%, increase user throughput up to 20%, and achieve better spectrum utilization, up to 98%. Our proposed admission approach has the potential to open a new research direction towards safer and greener cognitive radio techniques
Environmental adversity is associated with lower investment in collective actions

Environmental adversity is associated with a wide range of biological outcomes and behaviors that seem to fulfill a need to favor immediate over long-term benefits. Adversity is also associated with decreased investment in cooperation, which is defined as a long-term strategy. Beyond establishing the correlation between adversity and cooperation, the channel through which this relationship arises remains unclear. We propose that this relationship is mediated by a present bias at the psychological level, which is embodied in the reproduction-maintenance trade-off at the biological level. We report two pre-registered studies applying structural equation models to test this relationship on large-scale datasets (the European Values Study and the World Values Survey). The present study replicates existing research linking adverse environments (both in childhood and in adulthood) with decreased investment in adult cooperation and finds that this association is indeed mediated by variations in individuals’ reproduction-maintenance trade-off.
No-tillage soybean response to banded and broadcast and direct and residual fertilizer phosphorus and potassium applications

Improved P and K management systems for no-tillage soybean [Glycine max (L.) Merr. ] may be needed to increase yield and profits. This study evaluated the response of soybean to fertilizer P or K rates and placement as well as residual and direct fertilization from 1995 through 1996. Two K and two P experiments were established on farmers' fields with 10-yr histories of no tillage. An additional P experiment was conducted on one of Iowa State University's research farms. Treatments on farmers' fields included two rates of P (0 and 19.5 kg P ha -1 ) or K (0 and 51 kg K ha -1 ), placement of fertilizer (surface broadcast or a subsurface band 5 cm beside and 5 cm below the seed ) and time of fertilizer application. Treatments on the research farm were similar, except the P fertilizer rates applied were 0, 19, 39, and 78 kg ha -1 . Leaf P and K concentrations and grain yields were measured. Soil test P and K levels at the 0- to 15-cm depths ranged from low to very high across sites at the beginning of the experiment. Placement effects were variable for leaf P or K concentrations. Grain yields for broadcast P and K were as good as or better than the banded applications. However, there may be an advantage to applying P directly to the soybean crop, at least when soil test levels are optimum or lower.
Energy-efficient clustering and routing algorithm for large-scale SDN-based IoT monitoring

In the context of large-scale Internet of Things (IoT), one of the main issues comes from the lack of an efficient routing protocol that could handle thousands of devices and provide a low-power forwarding mechanism for huge amounts of data. Furthermore, this routing protocol should cope with the intrinsic device-to-device communications paradigm of IoT, where nodes no longer need an intermediate station for communication and synchronizing, in order to exploit all options to deliver a better quality of service (QoS) for the network. Although many solutions have been proposed to meet QoS requirements for various applications based on IoT, they usually do not provide significant increase on a network performance when the number of nodes becomes too large. Therefore, in this work, we provide a new modelling paradigm, organized on a two-level control mechanism, to overcome this problem. For the first level, we propose a new Routing Protocol for Low-Power and Lossy Networks (RPL) approach based on multi-hop clustering technique (MHC-RPL). It is used as a local control to organize nodes in clusters, in order to reduce energy consumption in the IoT. The second level uses Software Defined Networking (SDN) with Q-routing algorithm for intelligent management of the global network. Our results show that the proposed model provides significant better results in terms of end-to-end delay, packet delivery ratio and energy-consumption than current state-of-the-art.
Relationship between Motor Estimation Error and Physical Function in Patients with Parkinson’s Disease

Background: Motor estimation error is an index of how accurately one’s body movement is recognized. This study determines whether motor estimation error distance is a Parkinson’s disease (PD)- or age-related disability using a two-step task. Methods: The participants were 19 PD patients and 58 elderly people with disabilities. A two-step prediction test and an actual two-step test were performed. The motor estimation error distance (prediction of two-step distance minus actual two-step distance) and error rate between the two groups were compared. We conducted a correlation analysis between the motor estimation error and clinical factor (e.g., Hoehn and Yahr stage (H & Y), Unified Parkinson’s Disease Rating Scale (UPDRS)) related to PD. Results: The motor estimation error distance was not significantly different between the PD patient group and the elderly group with disabilities. However, significant correlations between motor estimation error and H & Y, and between motor estimation error and UPDRS part II, were observed. The error rate was significantly correlated with the Fall Efficacy Scale. Conclusions: The motor estimation error distance is influenced by both aging and PD.
Security of Data on E-waste equipment to Africa: The Case of Ghana

As computers become old and are discarded, it is imperative that they are effectively cleansed of all personal data. As the study showed, by using a simple data recovery software, remnant data can be retrieved from some disposed computer hard drives even after they have been formatted. If hard drives are not properly cleansed of data before they are discarded, individuals and organizations run the risk of having their information recovered and exploited by people with criminal intent. The study examined discarded computer hard drives obtained from some electronic waste dumpsites and other second hand computer dealers in Ghana, in an attempt to recover remnant information from them using a data recovery software. Out of 50 hard drives examined, 39 of them representing 78% contained identifiable individual information present in them. The results from this study indicated that most individuals and organizations are oblivious of data that still remains on computer hard drive even after files have been deleted and thus, it is necessary to highlight best approaches to asset disposal such as proper hard disk erasure techniques.
Analyzing Spanish News Frames on Twitter during COVID-19—A Network Study of El País and El Mundo

While COVID-19 is becoming one of the most severe public health crises in the twenty-first century, media coverage about this pandemic is getting more important than ever to make people informed. Drawing on data scraped from Twitter, this study aims to analyze and compare the news updates of two main Spanish newspapers El País and El Mundo during the pandemic. Throughout an automatic process of topic modeling and network analysis methods, this study identifies eight news frames for each newspaper’s Twitter account. Furthermore, the whole pandemic development process is split into three periods—the pre-crisis period, the lockdown period and the recovery period. The networks of the computed frames are visualized by these three segments. This paper contributes to the understanding of how Spanish news media cover public health crises on social media platforms.