Miracle-dz/UniFAR-FTUs huggingface dataset:
A survey of cryptographic algorithms for IoT devices

The future of Internet is “Internet of Things” where trillions of physical objects, most of them with low or extremely low resources, communicate with each other without human intervention. Light weight cryptography includes cryptographic algorithms specifically meant for extremely constrained resources. They can be applied not only for encryption but also for hashing and authentication under environments that are highly constrained. □ In this paper, we first discuss the need of light weight cryptography and their design differences with normal block ciphers. An overview of some of the light weight cryptographic algorithms is discussed after that. Also, we look into different types of attacks that has been studied on some of these ciphers. Finally, we compare the performance of some of these ciphers on Windows and Embedded platform.
Multifeedback Control of a Shape Memory Alloy Actuator and a Trial Application

Shape memory alloy (SMA) actuators exhibit high strain, high energy density, and self-sensing ability, which are promising characteristics for application in soft robot systems. This paper proposes a new SMA actuator with high accuracy that is driven by antagonistic SMA and super-elastic SMA (SSMA) wires or pairs of SMA wires that is intended to be used in miniature flexible structures. A multifeedback control methodology is presented for the actuator that uses feedback from both the SMA and SSMA wires. The prestress was chosen to minimize the gap between the heating and cooling paths of the strain-to-resistance (S-R) curve for both antagonistic SMA and SSMA. A radial basis function neural network was used to establish the S-R curve model for both self-sensing feedback and SSMA feedback. To achieve better system accuracy and stability, a data-fusion algorithm (based on the support function) was used to combine the multifeedback data. Accurate and stable motion control is demonstrated through multistep response, sinusoidal tracking, and force-disturbance tests. The experimental results show that the combination model using all the feedback has superior accuracy compared to the models that use self-sensing feedback or SSMA feedback. In addition, the maximum standard deviation within the SMA-SSMA antagonistic platform and the paired-SMA antagonistic platform can be reduced to 0.036% and 0.026%, respectively. A soft joint with two degrees of freedom is illustrated to demonstrate how the current research concept could potentially be implemented in bionic soft robots.
Static Malware Detection & Subterfuge: Quantifying the Robustness of Machine Learning and Current Anti-Virus

As machine-learning (ML) based systems for malware detection become more prevalent, it becomes necessary to quantify the benefits compared to the more traditional anti-virus (AV) systems widely used today. It is not practical to build an agreed upon test set to benchmark malware detection systems on pure classification performance. Instead we tackle the problem by creating a new testing methodology, where we evaluate the change in performance on a set of known benign & malicious files as adversarial modifications are performed. The change in performance combined with the evasion techniques then quantifies a system’s robustness against that approach. Through these experiments we are able to show in a quantifiable way how purely ML based systems can be more robust than AV products at detecting malware that attempts evasion through modification, but may be slower to adapt in the face of significantly novel attacks.
On direction-of-arrival (DoA) feedback and precoding for D2D assisted massive MIMO

Effective channel state information (CSI) feedback design is difficult for massive multiple-input multiple-output (MIMO) downlink transmissions in 5G frequency division duplexing (FDD) bands, where partial CSI could be directly exchanged between users through device-to-device (D2D) communications. In this work, we propose Direction of Arrival (DoA) adaptive codebook feedback, where the users exchange their CSI knowledge through D2D communications, estimate the precoder, and transmit it back to the base station (BS). That is, we first formulate an optimization problem of the feedback and precoding strategy on a Grassmann manifold. Using that, we are able to determine an optimal bit allocation of the precoder and the throughput of mmWave massive MIMO systems. Using simulations, we show that, compared with existing schemes, our proposed DoA adaptive codebook feedback scheme is able to achieve much higher throughput, and improve robustness and compatibility.
The abundance and mineral‐weathering effectiveness of Bacillus strains in the altered rocks and the soil

In this study, we collected different levels of altered rocks of a rocky mountain and the adjacent soil and characterized the abundance and weathering effectiveness of Bacillus strains. Based on qPCR and culture‐dependent approaches, the gene copies or the numbers of Bacillus strains were significantly higher in the soil than in the altered rocks, while the ratio of the gene copies or the numbers of Bacillus strains to those of total bacteria was higher in the less altered rock, followed by the more altered rock and the soil. The relative abundance of the highly active Al‐solubilizing Bacillus strains was higher in the more altered rock, followed by the less altered rock and the soil. Among the Al‐solubilizing Bacillus species, 30–36% of them were different between the altered rocks and the soil, however, similar Al‐solubilizing Bacillus species were found in the less altered rocks and the more altered ones. The results showed the alteration‐related changes in the abundance and mineral weathering effectiveness of Bacillus strains and suggested the ecological adaptation of the mineral‐weathering Bacillus populations and their role in mineral weathering in the rock and soil environments.
A 50Gb/s-PAM4 CDR with On-Chip Eye Opening Monitor for Reference-Level and Clock-Sampling Adaptation

A 50Gb/s-PAM4 Clock/Data Recovery (CDR) transceiver is designed in a 40nm-CMOS process. An on-chip Eye Opening Monitor (EOM) is introduced that enables adaptive reference level and timing sampling placement for non-uniform and distorted PAM4-inputs.
Microwave hyperthermia promotes caspase-3-dependent apoptosis and induces G2/M checkpoint arrest via the ATM pathway in non-small cell lung cancer cells

Post-operative microwave (MW) hyperthermia has been applied as an important adjuvant therapy to enhance the efficacy of traditional cancer treatment. A better understanding of the molecular mechanisms of MW hyperthermia may provide guided and further information on clinical hyperthermia treatment. In this study, we examined the effects of MW hyperthermia on non-small cell lung carcinoma (NSCLC) cells in vitro, as well as the underlying mechanisms. In order to mimic clinical treatment, we developed special MW heating equipment for this study. Various NSCLC cells (H460, PC-9 and H1975) were exposed to hyperthermia treatment using a water bath or MW heating system. The results revealed that MW hyperthermia significantly inhibited cell growth compared with the water bath heating system. Furthermore, MW hyperthermia increased the production of reactive oxygen species (ROS), decreased the levels of mitochondrial membrane potential (MMP) and induced caspase-3 dependent apoptosis. It also induced G2/M phase arrest through the upregulation of the expression of phosphorylated (p-) ataxia telangiectasia mutated (ATM), p-checkpoint kinase 2 (Chk2) and p21, and the downregulation of the expression of cdc25c, cyclin B1 and cdc2. On the whole, the findings of this study indicate that the exposure of NSCLC cells to MW hyper-thermia promotes caspase-3 dependent apoptosis and induces G2/M cell cycle arrest via the ATM pathway. This preclinical study may help to provide laboratory-based evidence for MW hyperthermia treatment in clinical practice.
u-OCEAN: An underwater omnidirectional communication environment using acoustic sensor nodes

This paper proposes a scheme for developing a low-cost underwater acoustic communication link and implements a portable underwater wireless sensor node capable of monitoring sub-aquatic parameters and transmitting them back to a land-based base station. The designed underwater communication link utilizes ultrasonic vibrations from off-the-shelf ultrasonic transducer pairs modified to achieve underwater wireless communication. The underwater sensor node is equipped with temperature and pressure sensors, measurements from which are periodically transmitted to the surface base station. The surface base station can additionally connect to various smartphones and computers using a Bluetooth interface. The proof of concept implementation shows consistent performance under laboratory conditions.
The Impact of Educational Interventions on Osteoporosis Knowledge among Korean Osteoporosis Patients

Background The purpose of this study was to determine the impact of an educational intervention that includes information sharing about absolute fracture risk on the knowledge of osteoporosis and modifiable risk factors among Korean patients with osteoporosis. Methods Adults aged >50 years who visited the outpatient clinic for osteoporosis were recruited. Subjects with trauma-related fractures or pathological fractures were excluded. The anthropometric data and clinical risk factors for fracture were collected at baseline. The participants completed the survey questionnaire that measured their knowledge regarding osteoporosis at baseline and then received information about the risk of fracture and individual education. Fracture risk was classified into five groups according to degree. The post-survey was conducted 3 months later. The pretest results were compared with the posttest results. Results In this study, 179 subjects (15 men and 164 women) were enrolled. After the educational intervention, the mean osteoporosis knowledge score significantly increased from 10.6±5.7 at pre-education (baseline) to 11.7±6.3 at post-education (P<0.001). When comparing the pre- and post-education Korean fracture risk scores, a negligible difference was found between the “very low risk” and “low risk” groups. However, the scores in the “very high risk” and “high risk” groups decreased from 77.6% to 76.0%. We found a difference over time only in physical activity. Conclusions Simple educational intervention is effective in increasing osteoporosis knowledge among Korean patients with osteoporosis. It may confer some benefit by providing information about osteoporotic fracture risks to improve knowledge and awareness regarding osteoporosis.
Molecular Genetics and Breeding for Nutrient Use Efficiency in Rice

In the coming decades, rice production needs to be carried out sustainably to keep the balance between profitability margins and essential resource input costs. Many fertilizers, such as N, depend primarily on fossil fuels, whereas P comes from rock phosphates. How long these reserves will last and sustain agriculture remains to be seen. Therefore, current agricultural food production under such conditions remains an enormous and colossal challenge. Researchers have been trying to identify nutrient use-efficient varieties over the past few decades with limited success. The concept of nutrient use efficiency is being revisited to understand the molecular genetic basis, while much of it is not entirely understood yet. However, significant achievements have recently been observed at the molecular level in nitrogen and phosphorus use efficiency. Breeding teams are trying to incorporate these valuable QTLs and genes into their rice breeding programs. In this review, we seek to identify the achievements and the progress made so far in the fields of genetics, molecular breeding and biotechnology, especially for nutrient use efficiency in rice.
Study of distance distributions and clustered user association in separation based two-tier HCNs

Homogeneous user models have been traditionally considered in heterogeneous cellular networks (HCNs) that comprise base transmitting stations (BTSs) operating at different power levels. As small-cell BTSs are usually deployed to cater to dense user clusters in limited spaces, Poisson cluster processes (PCPs) have found application in modeling non-homogeneous user distributions, for which deployments are placed at the center of user clusters. We propose a two-tier HCN model that comprises a single potential tier-2 small-cell deployment per user cluster. The potential tier-2 BTS deployments are offset by a randomly distributed distance with respect to the centers of their corresponding clusters, which are also known as social attractors (SAs). Deployment or active transmission of a tier-2 BTS may only occur if there is sufficient separation from active tier-1 BTSs in the network, effectively creating a Poisson hole process (PHP) of tier-2 BTSs. By using variations of the PCP to model clustered users that surround SAs, distance distributions are analyzed for two situations, where the offset between an SA and a potential tier-2 BTS is modeled by using the uniform and Gaussian distributions, respectively. This result is extended to obtain the probability of association of users to their corresponding cluster deployments, and the two BTS tiers.
Water Fluoridation and Dental Caries in U.S. Children and Adolescents

Fluoridation of America’s drinking water was among the great public health achievements of the 20th century. Yet there is a paucity of studies from the past 3 decades investigating its dental health benefits in the U.S. population. This cross-sectional study sought to evaluate associations between availability of community water fluoridation (CWF) and dental caries experience in the U.S. child and adolescent population. County-level estimates of the percentage of population served by CWF (% CWF) from the Centers for Disease Control and Prevention’s Water Fluoridation Reporting System were merged with dental examination data from 10 y of National Health and Nutrition Examination Surveys (1999 to 2004 and 2011 to 2014). Dental caries experience in the primary dentition (decayed and filled tooth surfaces [dfs]) was calculated for 7,000 children aged 2 to 8 y and in the permanent dentition (decayed, missing, and filled tooth surfaces [DMFS]) for 12,604 children and adolescents aged 6 to 17 y. Linear regression models estimated associations between % CWF and dental caries experience with adjustment for sociodemographic characteristics: age, sex, race/ethnicity, rural-urban location, head-of-household education, and period since last dental visit. Sensitivity analysis excluded counties fluoridated after 1998. In unadjusted analysis, caries experience in the primary dentition was lower in counties with ≥75% CWF (mean dfs = 3.3; 95% confidence limit [CL] = 2.8, 3.7) than in counties with <75% CWF (mean dfs = 4.6; 95% CL = 3.9, 5.4), a prevented fraction of 30% (95% CL = 11, 48). The difference was also statistically significant, although less pronounced, in the permanent dentition: mean DMFS (95% CL) was 2.2 (2.0, 2.4) and 1.9 (1.8, 2.1), respectively, representing a prevented fraction of 12% (95% CL = 1, 23). Statistically significant associations likewise were seen when % CWF was modeled as a continuum, and differences tended to increase in covariate-adjusted analysis and in sensitivity analysis. These findings confirm a substantial caries-preventive benefit of CWF for U.S. children and that the benefit is most pronounced in primary teeth.
Air quality estimation based on multi-source heterogeneous data from wireless sensor networks

It's a great challenge to offer a fine-grained and accurate air quality monitoring service in urban areas limited to the cost of the professional facilities. With the development of the wireless sensor networks (WSNs), it brings new opportunity to achieve this goal at low cost. However, WSNs are quite different on temporal and spatial distribution, some WSNs even have irregular real-time features, which makes it a hard problem to use the data collected from different WSNs to achieve the same goal. In this paper, we propose a framework for air quality estimation based on multi-source heterogeneous data collected from WSNs. We collect five kinds of data from different sources in real world, including the data with irregular real-time features. We divide the data sets into three sub classifiers to make the analysis and get the final results with an extreme learning machine (ELM) based multilayer perceptron model. The results show that our method outperforms other methods, and the precision of classification can be 90.8%.
Reverberator's late reflections parameters calculation

In this paper, a straightforward calculation of the comb filter based digital reverberator structure is given. It is based on geometrical properties of the closed room and also source and listener positions. Three possible groups of the sound wave propagation directions — axial, tangential and skew ones were taken into calculation. Signal structure is made from parallel connected comb filter but in this paper it is enhanced by the multitap comb filter structures to imitate the multiple sound wave passes through listener position. This structural modification also has changed the overall magnitude frequency response which became significantly less periodic. Also subjective listening of the processed sounds was much closer to the original room response.
Suppression of AMPA Receptor Exocytosis Contributes to Hippocampal LTD

The decrease in number of AMPA-type glutamate receptor (AMPAR) at excitatory synapses causes LTD, a cellular basis of learning and memory. The number of postsynaptic AMPARs is regulated by the balance of exocytosis and endocytosis, and enhanced endocytosis of AMPAR has been suggested to underlie the LTD expression. However, it remains unclear how endocytosis and exocytosis of AMPAR change during LTD. In this study, we addressed this question by analyzing exocytosis and endocytosis of AMPAR by imaging super-ecliptic pHlorin (SEP)-tagged AMPAR around postsynaptic structure formed directly on the glass surface in the hippocampal culture prepared from rat embryos of both sexes. Contrary to a prevailing view on the LTD expression by endocytosis enhancement, the LTD induction by NMDA application only transiently enhanced endocytosis of SEP-tagged GluA1 subunits of AMPAR, which was counteracted by simultaneous augmentation of exocytosis. As a result, soon after the start of the LTD induction (∼1 min), the surface AMPAR did not markedly decrease. Thereafter, the surface GluA1-SEP gradually decreased (2–5 min) and kept at a low level until the end of observation (>30 min). Surprisingly, this gradual and sustained decrease of surface AMPAR was accompanied not by the enhanced endocytic events of GluA1, but by the suppression of exocytosis. Together, our data highlight an unprecedented mechanism for the LTD expression by attenuation of exocytosis of AMPAR, but not by enhanced endocytosis, together with a reduction of postsynaptic AMPAR scaffolding protein PSD95. SIGNIFICANCE STATEMENT It has been generally assumed that LTD is expressed by enhancement of AMPAR endocytosis. Previous studies reported that endocytosis-related protein was involved in LTD and that significant amount of cell-surface AMPAR moved into intracellular compartments during LTD. Here, we report changes of cell-surface amount of AMPAR, and where and when individual exocytosis and endocytosis occurred during LTD. Cell-surface AMPAR gradually decreased in synchrony with suppression of exocytosis but not with enhancement of endocytosis. These results suggest that the decrease of cell-surface AMPAR amount during LTD was caused not by enhancement of endocytosis but rather by suppression of exocytosis, which revises current understanding of the expression mechanism of LTD.
Stateful process migration for edge computing applications

Low-latency is an advantage of edge computing. To utilize this advantage, a server-side application communicating with user equipment (UE) should be migrated from a server executing the application to a server near the UE's destination. However, the downtime caused by this migration can be a problem for applications that require ultra-low latency. To reduce the downtime, we propose a novel method for migrating only processes that contain UE-specific states, and not the entire application. The method introduces conversion of inter-process communication channels to enable communication continuity of the migrated processes. Finally, we show that the downtime for our method is shorter than that for VM migration and container migration.
A high gain Fabry-Perot cavity antenna designed by modified ray tracking model

A high gain Fabry-Perot cavity antenna (FPCA) designed by modified ray tracking model(MRTM) is presented in this paper. In particular, the conventional ray tracking is modified in order to calculate the electric field distribution on the partially reflective surface(PRS). Furthermore, the dependence of the magnitude of PRS reflection coefficients on aperture efficiency is studied, which shows that an optimal magnitude exists on aperture efficiency for a fixed size FPCA. By using the optimized reflection coefficient, a final compact single layer FPCA with a dimension of 6. 25λ0 × 6. 25λ0 and a profile of 0. 5λ0 is designed. The proposed antenna can reach a peak gain of 24.0dBi at 12.5GHz and an aperture efficiency of 51.2%.
Streamlining “smart grid end point devices” vulnerability testing using single board computer

The fourth industrial revolution is characterized by the digital transformation of industries that will vitally alter the way we live and work. Globally, developed and developing cities are eager to transform themselves into future cities or smart cities. Within the context of the smart city, a wide range of stakeholders interact to manage public services including the smart grid. A smart home is the ultimate pillar of a smart city and the classic approaches of providing untested and unsecured smart technologies to home tenants may lead to fading of satisfaction and losing ground. Several DDoS attacks that shut down portions of the internet were fueled by bots created from hacked connected devices, like internet-connected cameras and DVRs. It can also theoretically include other connected IoT (Internet Of Things) devices such as Smart CCTV Cameras, smart meters and other Smart Grid end point devices that are used for the safety and security of the Grid. CCTV cameras are increasingly in smart home and Smart Grid networks for monitoring the usage of sub-electrical power station for security, operation and maintenance. This paper proposes and evaluates a prototype of a portable reliable, cost effective and simple to use vehicle for security testing Smart Grid end point devices using single board computer as a starting point for identifying the vulnerabilities, leading to consumer confidence and satisfaction.