Miracle-dz/UniFAR-FTUs huggingface dataset:
Face Recognition Based on Deep Learning Under the Background of Big Data

Face recognition has important value in real life. In this study, the application of the deep learning method in the field of face recognition was studied. The structure of LeNet-5 in convolutional neural network (CNN) was selected and improved; based on it, a face recognition method was designed. The performance of the method was analyzed taking CelebA as training set and LEW as testing set. The results showed that the improved LeNet-5 model which took A-softmax Loss as loss function not only had shorter training time, but also had higher recognition accuracy, its accuracy increased with the increase of sample size, and the highest accuracy rate reached 97.9%. The experimental results showed that the face recognition method designed in this study had good performance in large data background as it could effectively reduce the running time of the algorithm and improve the recognition accuracy. This study proves the reliability of deep learning methods such as CNN in face recognition, which is conducive to the further development of face recognition technology.
Perception of adults toward electronic cigarettes: a cross-sectional study from Jordan

Abstract Introduction: The rate of Jordanian tobacco smokers has been reported to be one of the highest rates in the world. The electronic cigarette (E-cig) has become an option, or an alternative, to tobacco cigarette smoking. This study was aimed to measure the perception of Jordanian adults toward E-cig use. Methods: A cross-sectional study design was used. A self-administered survey was developed and validated to solicit anonymous responses from the study participants. A convenience sample (n = 984) was recruited electronically through social media platforms. Descriptive statistics and correlation analyses were completed using the Statistical Package for the Social Sciences (SPSS). Results: More than half of the participants (53%) were females, and almost all participants had heard about E-cig (99.2%), mainly from their friends (40%) and social media (34.5%). About half of the participants were nonsmokers and around one-third of them (33.1%) were current E-cig users. The majority of the participating E-cig users had replaced tobacco with E-cig (56.4%)/All the E-cig users reported positive beliefs toward the E-cig as a safer alternative for tobacco smoking. About 45% of participants believed that the E-cig is helpful in tobacco smoking cessation, but should be highly regulated. Conclusion: This study illustrated a significant prevalence of E-cig usage among Jordanian adults. E-cig users perceived E-cig as a safer and cheaper alternative to tobacco smoking and that it helps in tobacco smoking cessation. However, health awareness campaigns are needed for the entire Jordanian community about E-cig use, related emerging health findings, and how to promote tobacco smoking cessation.
Fabrication of High‐Density, Large‐Area Conducting‐Polymer Nanostructures

The low‐cost, large‐scale fabrication of high‐density conducting‐polymer nanostructures is desirable for a variety of applications. We report the realization of high‐density conducting‐polymer nanostructures through a combination of nanoimprint lithography, a copolymer strategy, and a lift‐off process. Atomic force microscopy and optical measurements reveal that the quality of the prepared structures is rather good, and a resolution of 100 nm is achieved. Electrical measurements show that the conducting‐polymer nanowires are conductive and indicate great anisotropy in the parallel and perpendicular directions. Moreover, by further connecting them with larger electrodes, these nanowire arrays function as nanosensors.
Cadmium effects on the nitrogen fixation system of red alder

Red alder (Alnus rubra Bong.) was grown in sand culture in the greenhouse to obtain data on the effects of cadmium (Cd) on a symbiotic nitrogen (N) fixation system which contributes to the fertility of forest soils. Treatment of red alder seedlings for 11 weeks with 0.545 to 136 . mu.M CdCl/sub 2/ in N-free nutrient solution decreased in situ nitrogenase activity 25 to 89%, N fixation 23 to 98%, and the number of nodules per plant 29 to 74%, when compared to plants receiving no Cd. Similar reductions were observed in plant growth. Treatment with 0.054 to 0.545 . mu.M CdCl/sub 2/ decreased nitrogenase activity 6 to 31%. When non-nodulated A. rubra seedlings were inoculated in the presence of 0.054 and 0.109 . mu.M CdCl/sub 2/, N fixation decreased 52 and 89%, respectively. Plant growth decreased in a similar fashion. When non-nodulated seedlings were given 0.545 . mu.M CdCl/sub 2/ and 6 mM NH/sub 4/NO/sub 3/ or Ca(NO/sub 3/)/sub 2/, nitrate reductase activity decreased 22 and 24%, respectively, when compared to plants receiving no CdCl/sub 2/. Nitrogen accretion and plant dry weights were decreased by treatments in which plants were supplied with Ca(NO/sub 3/)/sub 2/ and 0.273 and 0.545 . mu.M CdCl/sub 2/, whenmore » compared to controls without CdCl/sub 2/. These results suggest that Cd can inhibit nitrogenase activity and therefore N fixation. Growth, nodulation, and nitrate reductase activity are also inhibited by Cd. « less
Design and Implementation of Virtual Security Function Based on Multiple Enclaves

Network function virtualization (NFV) provides flexible and scalable network function for the emerging platform, such as the cloud computing, edge computing, and IoT platforms, while it faces more security challenges, such as tampering with network policies and leaking sensitive processing states, due to running in a shared open environment and lacking the protection of proprietary hardware. Currently, Intel® Software Guard Extensions (SGX) provides a promising way to build a secure and trusted VNF (virtual network function) by isolating VNF or sensitive data into an enclave. However, directly placing multiple VNFs in a single enclave will lose the scalability advantage of NFV. This paper combines SGX and click technology to design the virtual security function architecture based on multiple enclaves. In our design, the sensitive modules of a VNF are put into different enclaves and communicate by local attestation. The system can freely combine these modules according to user requirements, and increase the scalability of the system while protecting its running state security. In addition, we design a new hot-swapping scheme to enable the system to dynamically modify the configuration function at runtime, so that the original VNFs do not need to stop when the function of VNFs is modified. We implement an IDS (intrusion detection system) based on our architecture to verify the feasibility of our system and evaluate its performance. The results show that the overhead introduced by the system architecture is within an acceptable range.
Drug Repurposing for Parkinson's Disease by Integrating Knowledge Graph Completion Model and Knowledge Fusion of Medical Literature

The prevalence of Parkinson’s disease increases a tremendous medical and economic burden to society. Therefore, the effective drugs are urgently required. However, the traditional development of effective drugs is costly and risky. Drug repurposing, which identifies new applications for existing drugs, is a feasible strategy for discovering new drugs for Parkinson’s disease. Drug repurposing is based on sufficient medical knowledge. The local medical knowledge base with manually labeled data contains a large number of accurate, but not novel, medical knowledge, while the medical literature containing the latest knowledge is difficult to utilize, because of unstructured data. This paper proposes a framework, named Drug Repurposing for Parkinson’s disease by integrating Knowledge Graph Completion method and Knowledge Fusion of medical literature data (DRKF) in order to make full use of a local medical knowledge base containing accurate knowledge and medical literature with novel knowledge. DRKF first extracts the relations that are related to Parkinson’s disease from medical literature and builds a medical literature knowledge graph. After that, the literature knowledge graph is fused with a local medical knowledge base that integrates several specific medical knowledge sources in order to construct a fused medical knowledge graph. Subsequently, knowledge graph completion methods are leveraged to predict the drug candidates for Parkinson’s disease by using the fused knowledge graph. Finally, we employ classic machine learning methods to repurpose the drug for Parkinson’s disease and compare the results with the method only using the literature-based knowledge graph in order to confirm the effectiveness of knowledge fusion. The experiment results demonstrate that our framework can achieve competitive performance, which confirms the effectiveness of our proposed DRKF for drug repurposing against Parkinson’s disease. It could be a supplement to traditional drug discovery methods.
A Comparative Study of Cryptographic Key Distribution Protocols

Key distribution protocols deal with generating, exchanging, and storing information (especially shared keys). In this paper, we compare three different types of protocols: classical, quantum key distribution, and blockchain-based protocols, with examples from each category, presenting the particularities and challenges of each one, including solutions and the impact of these protocols.
Capillary-flow dynamics in open rectangular microchannels

Abstract Spontaneous capillary flow of liquids in narrow spaces plays a key role in a plethora of applications including lab-on-a-chip devices, heat pipes, propellant management devices in spacecrafts and flexible printed electronics manufacturing. In this work we use a combination of theory and experiment to examine capillary-flow dynamics in open rectangular microchannels, which are often found in these applications. Scanning electron microscopy and profilometry are used to highlight the complexity of the free-surface morphology. We develop a self-similar lubrication-theory-based model accounting for this complexity and compare model predictions to those from the widely used modified Lucas–Washburn model, as well as experimental observations over a wide range of channel aspect ratios $\lambda$ and equilibrium contact angles $\theta _0$. We demonstrate that for large $\lambda$ the two model predictions are indistinguishable, whereas for smaller $\lambda$ the lubrication-theory-based model agrees better with experiments. The lubrication-theory-based model is also shown to have better agreement with experiments at smaller $\theta _0$, although as $\theta _0\rightarrow {\rm \pi}/4$ it fails to account for important axial curvature contributions to the free surface and the agreement worsens. Finally, we show that the lubrication-theory-based model also quantitatively predicts the dynamics of fingers that extend ahead of the meniscus. These findings elucidate the limitations of the modified Lucas–Washburn model and demonstrate the importance of accounting for the effects of complex free-surface morphology on capillary-flow dynamics in open rectangular microchannels.
RUP Security of the SAEF Authenticated Encryption mode

ForkAE is a family of authenticated encryption (AE) schemes using a forkcipher as a building block. ForkAE was published in Asiacrypt’19 and is a second round candidate in the NIST lightweight cryptography process. ForkAE comes in several modes of operation: SAEF, PAEF, and rPAEF. SAEF is optimized for authenticated encryption of short messages and processes the message blocks in a sequential and online manner. SAEF requires a smaller internal state than its parallel sibling PAEF and is better ﬁtted for devices with smaller footprint. At SAC 2020 it was shown that SAEF is also an online nonce misuse-resistant AE (OAE) and hence oﬀers enhanced security against adversaries that make blockwise adaptive encryption queries. It has remained an open question if SAEF resists attacks against blockwise adaptive decryption adversaries, or more generally when the decrypted plaintext is released before the veriﬁcation (RUP). RUP security is a particularly relevant security target for lightweight (LW) implementations of AE schemes on memory-constrained devices or devices with stringent real-time requirements. Sur-prisingly, very few NIST lightweight AEAD candidates come with any provable guarantees against RUP. Inthis work, we show that the SAEF mode of operation of the ForkAE family comes with integrity guarantees in the RUP setting. The RUP integrity (INT-RUP) property was deﬁned by Andreeva et al. in Asiacrypt’14. Our INT-RUP proof is conducted using the coeﬃcient H technique and it shows that, without any modiﬁcations, SAEF is INT-RUP secure up to the birthday bound, i.e., up to 2 n/ 2 processed data blocks, where n is the block size of the forkcipher. The implication of our work is that SAEF is indeed RUP secure in the sense that the release of unveriﬁed plaintexts will not impact its ciphertext integrity.
Cleaning and conditioning of the walls of plasma devices by glow discharges in hydrogen

Surface conditioning by rf‐assisted dc glow (RG) discharges has been studied in a stainless steel vessel in order to optimize the rate of surface deoxidization via water formation. This is the simplest way to decontaminate the almost carbon‐free surfaces of plasma devices which have been exposed to air after a prolonged operation in hydrogen. This rate depends strongly on the wall temperature TW, the pump speed Sp, the discharge current IRG, and the hydrogen pressure P2. It is small at ambient temperature; the conditioning should be made at TW>100 °C. Surface oxygen is removed, even at room temperature, when 1% to 2% of methane is added to the hydrogen. Carbon monoxide is formed and evacuated. The addition of He or Ne does not accelerate the oxygen removal from reoxidized surfaces. An equation derived from a simplified model describes the parametric dependences of the water release well. The occurrence of arcs during RG discharges depends on wall conditioning; they are not observed after a prolonged bakeo.
Geospatial Open Data Usage and Metadata Quality

The Open Government Data portals (OGD), thanks to the presence of thousands of geo-referenced datasets, containing spatial information are of extreme interest for any analysis or process relating to the territory. For this to happen, users must be enabled to access these datasets and reuse them. An element often considered as hindering the full dissemination of OGD data is the quality of their metadata. Starting from an experimental investigation conducted on over 160,000 geospatial datasets belonging to six national and international OGD portals, this work has as its first objective to provide an overview of the usage of these portals measured in terms of datasets views and downloads. Furthermore, to assess the possible influence of the quality of the metadata on the use of geospatial datasets, an assessment of the metadata for each dataset was carried out, and the correlation between these two variables was measured. The results obtained showed a significant underutilization of geospatial datasets and a generally poor quality of their metadata. In addition, a weak correlation was found between the use and quality of the metadata, not such as to assert with certainty that the latter is a determining factor of the former.
Structural Importance-based Link Prediction Techniques in Social Network

Link prediction in social network gaining high attention of researchers nowadays due to the rush of users towards social network. Link prediction is known as the prediction of missing or unobserved link, i.e., new interaction is going to be occurring in a near future. State-of-the-art link prediction techniques(e.g., Jaccard Index, Resource Allocation, SAM Similarity, Sorensen Index, Salton Cosine, Hub Depressed Index and Parameter-Dependent) considers only similarity of the pair of node in order to ﬁnd the link. However, we argued that nodes having same status of centralization along with high similarity can connect to each other in a future. In this paper, we have proposed structural importance-based state-of-the-art link prediction techniques and compared. We have compared structural importance-based link prediction techniques with state-of-the-art techniques. The experiments are performed on four di ﬀ erent datasets (i.e., Astro, CondMat, HepPh and HepTh). Our results show that structural importance-based link prediction techniques outperformed than state-of-the-art link prediction techniques by getting 95% at threshold 0.1 and 68% at threshold 0.7.
Why Psychology Needs to Stop Striving for Novelty and How to Move Towards Theory-Driven Research

Psychological science is maturing and therefore transitioning from explorative to theory-driven research. While explorative research seeks to find something “new,” theory-driven research seeks to elaborate on already known and hence predictable effects. A consequence of these differences is that the quality of explorative and theory-driven research needs to be judged by distinct criterions that optimally support their respective development. Especially, theory-driven research needs to be judged by its methodological rigor. A focus on innovativeness, which is typical for explorative research, will instead incentivize bad research practices (e.g., imprecise theorizing, ignoring previous research, parallel theories). To support the advancement of psychology, we must drop the innovation requirement for theory-driven research and instead require the strongest methods, which are marked by high internal and external validity. Precise theorizing needs to substitute novelty. Theories are advanced by requiring explicit, testable assumptions, and an explicit preference for one theory over another. These explicit and potentially wrong assumptions should not be silenced within the peer-review process, but instead be scrutinized in new publications. Importantly, these changes in scientific conduct need to be supported by senior researchers, especially, in their roles as editors, reviewers, and in the hiring process. An important obstacle to further theory-driven research is to measure scientific merit using researchers’ number of publications, which favors theoretically shallow and imprecise writing. Additionally, it makes publications the central target of scientific misconduct even though they are the main source of information for the scientific community and the public. To advance the field, researchers should be judged by their contribution to the scientific community (e.g., exchange with and support of colleagues, and mentoring). Another step to advance psychology is to clearly differentiate between measurement model and theory, and not to overgeneralize based on few stimuli, incidences, or studies. We will use ideas from the theory of science to underline the changes necessary within the field of psychology to overcome this existential replication crisis.
Seroprevalence and Risk Factors of the Bluetongue Virus in Cattle in China From 1988 to 2019: A Comprehensive Literature Review and Meta-Analysis

Background: Bluetongue caused by the bluetongue virus (BTV) is a non-contagious and an insect-borne disease mainly affecting domestic and wild ruminants. Bluetongue in cattle is associated with vesicular lesions, weight loss, low milk production, and low reproductive capacity. It should not be ignored as it is associated with large economic losses to the livestock breeding industry in China. Although many studies have investigated bluetongue virus infection in cattle, no nationwide study on the prevalence of bluetongue virus infection in cattle from China has yet been conducted. This meta-analysis aimed to evaluate the seroprevalence and risk factors for bluetongue in cattle. Results: We collected 50 publications from 1988 to 2019 through PubMed, ScienceDirect, Chinese Web of Knowledge (CNKI), VIP Chinese journal database, and Wanfang database. A total of the pooled bluetongue seroprevalence of 12.2% (5,332/87,472) in cattle was tested. The point estimate of bluetongue collected from 2001 to 2011 was 22.5% (95% CI: 1.2–58.9), which was higher than after 2012 (9.9%, 95% CI: 3.3–19.4). The analysis of the feeding model subgroup revealed that the seroprevalence of bluetongue was significantly higher (P < 0.05) among free-range cattle (22.5%; 95% CI: 7.7–42.3) than among cattle from intensive farming systems (1.8%; 95% CI: 0.0–6.7). The seroprevalence of bluetongue in different species showed significant variation (P < 0.05), with the highest seroprevalence of 39.8% (95% CI: 18.7–63.0) in buffalo and the lowest seroprevalence of 4.3% (95% CI: 1.2–9.0) in yak. In the zoogeographical division subgroup, the seroprevalence of bluetongue correlated positively within a certain range with the species distribution of Culicoides. Conclusion: Our findings suggested that bluetongue was prevalent in cattle in China. In addition, the contact with sheep, other ruminants, or transmission media such as Culicoides may increase the seroprevalence of bluetongue disease in cattle. It is necessary to carry out continuous monitoring of the bluetongue seroprevalence. Moreover, comprehensive and improved strategies and measures should be implemented to prevent and control the spread of bluetongue.
Measures of Interjoint Coordination Post-stroke Across Different Upper Limb Movement Tasks

Background: Deficits in interjoint coordination, such as the inability to move out of synergy, are frequent symptoms in stroke subjects with upper limb impairments that hinder them from regaining normal motor function. Kinematic measurements allow a fine-grained assessment of movement pathologies, thereby complementing clinical scales, like the Fugl–Meyer Motor Assessment of the Upper Extremity (FMMA-UE). The study goal was to investigate the effects of the performed task, the tested arm, the dominant affected hand, upper limb function, and age on spatiotemporal parameters of the elbow, shoulder, and trunk. The construct validity of the metrics was examined by relating them with each other, the FMMA-UE, and its arm section. Methods: This is a cross-sectional observational study including chronic stroke patients with mild to moderate upper limb motor impairment. Kinematic measurements were taken using a wearable sensor suit while performing four movements with both upper limbs: (1) isolated shoulder flexion, (2) pointing, (3) reach-to-grasp a glass, and (4) key insertion. The kinematic parameters included the joint ranges of shoulder abduction/adduction, shoulder flexion/extension, and elbow flexion/extension; trunk displacement; shoulder–elbow correlation coefficient; median slope; and curve efficiency. The effects of the task and tested arm on the metrics were investigated using a mixed-model analysis. The validity of metrics compared to clinically measured interjoint coordination (FMMA-UE) was done by correlation analysis. Results: Twenty-six subjects were included in the analysis. The movement task and tested arm showed significant effects (p < 0.05) on all kinematic parameters. Hand dominance resulted in significant effects on shoulder flexion/extension and curve efficiency. The level of upper limb function showed influences on curve efficiency and the factor age on median slope. Relations with the FMMA-UE revealed the strongest and significant correlation for curve efficiency (r = 0.75), followed by shoulder flexion/extension (r = 0.68), elbow flexion/extension (r = 0.53), and shoulder abduction/adduction (r = 0.49). Curve efficiency additionally correlated significantly with the arm subsection, focusing on synergistic control (r = 0.59). Conclusion: The kinematic parameters of the upper limb after stroke were influenced largely by the task. These results underpin the necessity to assess different relevant functional movements close to real-world conditions rather than relying solely on clinical measures. Study Registration: clinicaltrials.gov, identifier NCT03135093 and BASEC-ID 2016-02075.