Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Hydraulic Tough Motors with High Power Density and their Application to a 7-axis Robotic Arm

A combination of electric motors and speed reducers are widely used as robot actuators. However, owing to problems such as low impact resistance and poor backdrivability, it is hard to use robots in actual disaster environments. Hydraulic actuators used in construction machines are not only applicable to such environments, but they also have good force density and power density. However, most conventional actuators are large, heavy, and have poor controllability and it is difficult to apply these to robots. In this research, we developed two actuators (a semi-rotary motor and an axial piston motor) with the aim of improving miniaturization and reduce weight for use in robots and evaluated their characteristics. The developed semi-rotary motor utilizes pure titanium and a hollow shaft form. They contributed to weight reduction and facilitated hydraulic robot composing method. The developed axial piston motor is a combination of a remodeled off-the-shelf motor and a special tooth-type planetary gear reducer that is expected to have high backdrivability. Both the actuators can bear high input pressures (35 MPa) and equip servo valve, absolute encoder, and pressure sensors directly to enhance their applicability to robots. The semi-rotary motor (high output, medium output) and axial piston motor (medium output, small output) achieved T/M (torque / mass) ratios of approximately 88.5 [Nm/kg] and 105.2 [Nm/kg], respectively, which are 5.6 times and 8.2 times greater than that of conventional oil hydraulic motors. In the evaluation test, we confirmed the possibility of estimating the torque by using the pressure sensors and found that it is possible with an accuracy of approximately ±13% of the rated torque for the high-output semi-rotary motor. In addition, as a prototype of a hydraulic legged robot, we developed a robot arm with seven degrees of freedom that is highly compatible with the four-limb electrically-actuated robot, WAREC-1, for use in disasters. WAREC-1 was mainly developed at Waseda University. The length of the developed robot arm is 1.2 m, which is similar to that of WAREC-1. The mass of the robot is 56 kg, which is heavier than WAREC – 1; however, the joint torques are equal or greater than those of WAREC-1. With respect to the movable range, it was able to be equal to or more than 214 degrees with WAREC-1 by using hollow shaft actuators and swivel joints. The power density and the backdrive torque ratio (backdrive torque / rated torque) of the developed actuators are 5.9 times higher and 1/26 smaller than those of the actuators of WAREC-1. In the demonstration, the arm succeeded in breaking a stuck of three concrete-boards, each 30mm-thick.
Subjective video quality prediction based on objective video quality metrics

This A method is proposed for the generation of a set of video sequence with a predictive subjective video quality (Mean Opinion Score) based on a limited number of sequences and the associated objective video quality measure (Peak Signal-to-Noise Ratio). The MOS is predicted using a sigmoid function model that is optimized based on a limited number of subjective tests for each video sequence. The correlation of the P-MOS to MOS achieved using this method is 0.94. The method can be used to enrich an existing video sequence dataset for the training phase in machine learning or deep leaning applications without bearing the burden and cost of the human opinion based regular subjective video quality test.
Geographic-genetic analysis of Plasmodium falciparum parasite populations from surveys of primary school children in Western Kenya

Background. Malaria control, and finally malaria elimination, requires the identification and targeting of residual foci or hotspots of transmission. However, the level of parasite mixing within and between geographical locations is likely to impact the effectiveness and durability of control interventions and thus should be taken into consideration when developing control programs. Methods. In order to determine the geographic-genetic patterns of Plasmodium falciparum parasite populations at a sub-national level in Kenya, we used the Sequenom platform to genotype 111 genome-wide distributed single nucleotide polymorphic (SNP) positions in 2486 isolates collected from children in 95 primary schools in western Kenya. We analysed these parasite genotypes for genetic structure using principal component analysis and assessed local and global clustering using statistical measures of spatial autocorrelation. We further examined the region for spatial barriers to parasite movement as well as directionality in the patterns of parasite movement. Results. We found no evidence of population structure and little evidence of spatial autocorrelation of parasite genotypes (correlation coefficients <0.03 among parasite pairs in distance classes of 1km, 2km and 5km; p value<0.01). An analysis of the geographical distribution of allele frequencies showed weak evidence of variation in distribution of alleles, with clusters representing a higher than expected number of samples with the major allele being identified for 5 SNPs. Furthermore, we found no evidence of the existence of spatial barriers to parasite movement within the region, but observed directional movement of parasites among schools in two separate sections of the region studied. Conclusions. Our findings illustrate a pattern of high parasite mixing within the study region. If this mixing is due to rapid gene flow, then “one-off” targeted interventions may not be currently effective at the sub-national scale in Western Kenya, due to the high parasite movement that is likely to lead to re-introduction of infection from surrounding regions. However repeated targeted interventions may reduce transmission in the surrounding regions.
EEG-based classification of video quality perception using steady state visual evoked potentials (SSVEPs)

Objective. Recent studies exploit the neural signal recorded via electroencephalography (EEG) to get a more objective measurement of perceived video quality. Most of these studies capitalize on the event-related potential component P3. We follow an alternative approach to the measurement problem investigating steady state visual evoked potentials (SSVEPs) as EEG correlates of quality changes. Unlike the P3, SSVEPs are directly linked to the sensory processing of the stimuli and do not require long experimental sessions to get a sufficient signal-to-noise ratio. Furthermore, we investigate the correlation of the EEG-based measures with the outcome of the standard behavioral assessment. Approach. As stimulus material, we used six gray-level natural images in six levels of degradation that were created by coding the images with the HM10.0 test model of the high efficiency video coding (H.265/MPEG-HEVC) using six different compression rates. The degraded images were presented in rapid alternation with the original images. In this setting, the presence of SSVEPs is a neural marker that objectively indicates the neural processing of the quality changes that are induced by the video coding. We tested two different machine learning methods to classify such potentials based on the modulation of the brain rhythm and on time-locked components, respectively. Main results. Results show high accuracies in classification of the neural signal over the threshold of the perception of the quality changes. Accuracies significantly correlate with the mean opinion scores given by the participants in the standardized degradation category rating quality assessment of the same group of images. Significance. The results show that neural assessment of video quality based on SSVEPs is a viable complement of the behavioral one and a significantly fast alternative to methods based on the P3 component.
Container Security: Issues, Challenges, and the Road Ahead

Containers emerged as a lightweight alternative to virtual machines (VMs) that offer better microservice architecture support. The value of the container market is expected to reach $2.7 billion in 2020 as compared to $762 million in 2016. Although they are considered the standardized method for microservices deployment, playing an important role in cloud computing emerging fields such as service meshes, market surveys show that container security is the main concern and adoption barrier for many companies. In this paper, we survey the literature on container security and solutions. We have derived four generalized use cases that should cover security requirements within the host-container threat landscape. The use cases include: (I) protecting a container from applications inside it, (II) inter-container protection, (III) protecting the host from containers, and (IV) protecting containers from a malicious or semi-honest host. We found that the first three use cases utilize a software-based solutions that mainly rely on Linux kernel features (e.g., namespaces, CGroups, capabilities, and seccomp) and Linux security modules (e.g., AppArmor). The last use case relies on hardware-based solutions such as trusted platform modules (TPMs) and trusted platform support (e.g., Intel SGX). We hope that our analysis will help researchers understand container security requirements and obtain a clearer picture of possible vulnerabilities and attacks. Finally, we highlight open research problems and future research directions that may spawn further research in this area.
Biomechanical characterization of slope walking using musculoskeletal model simulation.

PURPOSE Upslope and downslope walking are basic activities necessary for normal daily living in community, and they impose greater joint load on the lower extremities than during level walking. Thus, the purpose of this study was to quantify the resultant and shear forces in the hip and knee joints during slope walking. METHODS Twelve healthy volunteers were evaluated when walking under level and 10° up- and downslope conditions. Three-dimensional gait analysis was conducted using a 7-camera optoelectronic motion analysis system combined with a force plate to measure ground reactive force. Joint forces in the hip and knee joints were estimated using musculoskeletal model simulation. RESULTS Results showed that the resultant hip force was increased significantly to 117.2% and 126.9%, and the resultant knee force was increased to 133.5% and 144.5% in up- and downslope walking, respectively, compared to that of level walking. Furthermore, increased shear force in the hip and knee joints was noted during both slope walking conditions. CONCLUSIONS This information may be beneficial for therapists advising elderly people or patients with osteoarthrosis on an appropriate gait pattern, gait assistive devices, or orthoses according to their living environment.
A Consistently-Executing Graph-Based Approach for Malware Packer Identification

Packing is the most common malware obfuscation technique employed to evade detection by anti-virus systems. With the explosive growth of packed malware, packer identification has become increasingly important in current cybersecurity. Most prior studies lack resilience since they neglect the significance of preserving the semantic integrity for pursuing efficiency. Therefore, in this paper, we propose a novel approach based on consistently executing graph (CEG) mining, which can maximize semantics and facilitate the execution intents of executables for identification. We elaborate on the concepts of consistent execution and represent malware packers as structured CEGs. Then, we employ the bipartite matching algorithm built on a designed block proximity metric to extract the critical matching subgraphs. Weisfeiler–Lehman shortest path graph kernel is adopted for pairwise comparison to make the prediction. We have evaluated the efficacy extensively with several experiments on large-scale datasets containing manually packed benign apps, wild-packed malware, and wild-unpacked malware. The promising results demonstrate that our approach is valid and practical when applied to real-world packed malware analysis.
Novel 10-nm Gate Length MoS2 Transistor Fabricated on Si Fin Substrate

To allow the use of molybdenum disulfide (MoS<sub>2</sub>) in mainstream Si CMOS manufacturing processes for improved future scaling, a novel MoS<sub>2</sub> transistor with a 10-nm physical gate length created using a p-type doped Si fin as the back-gate electrode is presented. The fabrication technology of the ultra-small MoS<sub>2</sub> device shows fully process compatibility with conventional Si-FinFET process flow and it is also the first time to realize the large-scale fabrication of the arrayed MoS<sub>2</sub> transistors with 10-nm gate lengths. The fabricated ultrathin transistors, consisting of 10-nm gate length and 0.7-nm monolayer CVD MoS<sub>2</sub>, exhibit good switching characteristics and the average drain current on/off ratio reaches to over <inline-formula> <tex-math notation="LaTeX">$10^{6}$ </tex-math></inline-formula>. This technology provides a promising approach for future CMOS scaling with large scale new 2-D material transistors.
An end-to-end deep learning model to recognize Farsi speech from raw input

Automatic speech recognition systems usually solve the problem of recognizing speech by dividing the problem into different independent stages. First, they extract speech features and then use an acoustic model to reach the phoneme probabilities and from those probabilities, they reach a sequence of recognized words. Recent advances in technology, especially in the area of deep neural networks in combination with speech recognition, shows that this division is not necessary and we can reach a sequence of alphabet letters straight from the raw signal. In this work, we implemented and tested an end-to-end convolutional neural network system with raw input for Farsi speech recognition and then compared its performance to another system that uses MFCC features. We show that using an end-to-end system with our configuration, which reaches a series of phonemes from raw speech works better for Farsi speech as well as for English.
Mobile Picking-Robot having wide reach area for shelves

In this paper, we describe the development of a mobile picking-robot that can function as an “alternative worker” to compensate for a shortage of human workers at a logistics site. A requirement of a modern logistics site is that it have flexible systems that can handle numerous kinds of items. A country with a limited land area, such as Japan, particularly expects automated equipment to be compact and thus space-saving. Therefore, our work centered on developing robotic arm mechanisms that can be deployed in small spaces and on a mobile robotic system that can recognize, reach out and pick up items. This system has demonstrated in store test room for testing order picking by using proposal arms. Our solution can avoid singular configuration and can approach narrow workspace by combination with linear and rotational actuator.
Chlorotoxin-conjugated graphene oxide for targeted delivery of an anticancer drug

Current chemotherapy for glioma is rarely satisfactory due to low therapeutic efficiency and systemic side effects. We have developed a glioma-targeted drug delivery system based on graphene oxide. Targeted peptide chlorotoxin-conjugated graphene oxide (CTX-GO) sheets were successfully synthesized and characterized. Doxorubicin was loaded onto CTX-GO (CTX-GO/DOX) with high efficiency (570 mg doxorubicin per gram CTX-GO) via noncovalent interactions. Doxorubicin release was pH-dependent and showed sustained-release properties. Cytotoxicity experiments demonstrated that CTX-GO/DOX mediated the highest rate of death of glioma cells compared with free doxorubicin or graphene oxide loaded with doxorubicin only. Further, conjugation with chlorotoxin enhanced accumulation of doxorubicin within glioma cells. These findings indicate that CTX-GO is a promising platform for drug delivery and provide a rationale for developing a glioma-specific drug delivery system.
Fault Tolerance Based Indexing for Multidimensional Data Bases

Multidimensional databases are main source dataset for data analytics. They are designed to provide fast and efficient backend support. Efficient physical layer design of these data bases is foremost requirement. Efficiency of any storage system depends on the indexing system, which is measured in terms of time and space complexity of the indexing system. In this paper new dimension of accuracy is proposed which along with time and space which will be measure of efficiency for indexing system at physical level of multidimensional data base. Fault Tolerance capability of self-organizing neural network is used for mapping data at conceptual level to physical storage level. Results of the research are very exciting and can be used for further development of the similar techniques.
The impact of nocturnal disturbances on daily quality of life in patients with Parkinson’s disease

Objectives The aims of this study were to explore nocturnal disturbances in patients with Parkinson’s disease (PD) and to assess their impact on quality of life (QoL). Methods A total of 211 patients with PD were recruited for this study, and each participant was evaluated using the mini-mental state examination, PD sleep scale – second version (PDSS-2), pittsburgh sleep quality index (PSQI), PD QoL questionnaire (PDQ), Epworth sleepiness scale, Hoehn and Yahr (H&Y) staging, and unified Parkinson’s disease rating scale (UPDRS). Multiple regression analyses were performed to determine the contribution of the predictive variables on QoL. Results There were 56.4% males (mean age: 64.08 years; disease duration: 6.02 years; H&Y stage: 2.25; and UPDRS: 33.01) in this study. Our patients’ actual sleep time was 5.96±1.16 hours and the average sleep efficiency was 82.93%±12.79%. Up to 64.4% of patients were classified as “poor” sleepers and 23.8% suffered from daytime sleepiness. The final stepwise regression model revealed that UPDRS parts I and II, the sleep disturbance and daytime dysfunction components of the PSQI, the PD symptoms at night subscale of the PDSS-2, and the levodopa equivalent dose were significant predictors of the PDQ score (R2=53, F7,165=28.746; P<0.001). Conclusion Most of the PD patients have sleep problems, and nearly one-quarter of them have abnormal daytime somnolence. The nocturnal disturbances were found to result in worse QoL in PD patients. Ethnicity-specific effects of susceptibility to sleep disturbances were discussed, and these results also highlighted the direction for further studies to explore when examining effective management programs toward these disturbances.
Mineral Elements Bio-Accessibility and Antioxidant Indices of Blanched Basella rubra at Different Phases of in vitro Gastrointestinal Digestion

The present investigation was designed to evaluate the mineral element bio-accessibility and antioxidant indices of blanched Basella rubra at different phases of simulated in vitro digestion (oral, gastric, and intestinal). The phenolic composition of processed vegetable was determined using high-performance liquid chromatography (HPLC)-diode-array detection method. Mineral composition, total phenolic content (TPC), total flavonoid content (TFC), ferric reducing antioxidant power (FRAP), and total antioxidant activity (TAA) of the in vitro digested blanched and raw vegetable were also determined. HPLC analysis revealed the presence of some phenolic compounds, with higher levels (mg/g) of polyphenols in raw B. rubra (catechin, 1.12; p-coumaric acid, 6.17; caffeic acid, 2.05) compared with the blanched counterpart, with exeption of chlorogenic acid (2.84), that was higher in blanched vegetable. The mineral content (mg/100 g) showed a higher value in enzyme treated raw vegetable compared to their blanched counterparts, with few exceptions. The results revealed a higher level of some of the evaluated minerals at the intestinal phase of digestion (Zn, 6.36/5.31; Mg, 5.29/8.97; Ca, 2,307.69/1,565.38; Na, 5,128/4,128.21) for raw and blanched respectively, with the exception of Fe, K, and P. The results of the antioxidant indices of in vitro digested B. rubra revealed a higher value at the intestinal phase of in vitro digestion, with raw vegetal matter ranking higher (TPC, 553.56 mg/g; TFC, 518.88 mg/g; FRAP, 8.15 mg/g; TAA, 5,043.16 μM Trolox equivalent/g) than the blanched counterpart. The studied vegetable contains important minerals and antioxidant molecules that would be readily available after passing through the gastrointestinal tract and could be harnessed as functional foods.
Towards an ACL Anthology Corpus with Logical Document Structure. An Overview of the ACL 2012 Contributed Task

The ACL 2012 Contributed Task is a community effort aiming to provide the full ACL Anthology as a high-quality corpus with rich markup, following the TEI P5 guidelines---a new resource dubbed the ACL Anthology Corpus (AAC). The goal of the task is threefold: (a) to provide a shared resource for experimentation on scientific text; (b) to serve as a basis for advanced search over the ACL Anthology, based on textual content and citations; and, by combining the aforementioned goals, (c) to present a showcase of the benefits of natural language processing to a broader audience. The Contributed Task extends the current Anthology Reference Corpus (ARC) both in size, quality, and by aiming to provide tools that allow the corpus to be automatically extended with new content---be they scanned or born-digital.
Inferring Patterns for Taint-Style Vulnerabilities With Security Patches

Taint-style vulnerabilities can damage the service provided by mobile seriously. The pattern-based method is a practical way to detect taint-style vulnerabilities. Most of the methods extract the vulnerability patterns from the code base, however, sometimes missing the vulnerability patterns and resulting in some vulnerabilities undiscovered. The security patches contain valuable information about the vulnerabilities. To compensate for the inherent incompleteness of pattern matching, in this paper, we propose an approach to infer patterns with the security information carried on the security patches. The taint-style vulnerability is described as a 3-tuples <inline-formula> <tex-math notation="LaTeX">$(S_{src},S_{san},S_{sink})$ </tex-math></inline-formula> here, which consist of sources<inline-formula> <tex-math notation="LaTeX">$(S_{src})$ </tex-math></inline-formula>, sanitization <inline-formula> <tex-math notation="LaTeX">$(S_{san})$ </tex-math></inline-formula>, and sinks<inline-formula> <tex-math notation="LaTeX">$(S_{sink})$ </tex-math></inline-formula>. For each pair of vulnerable and patched programs, we extract the sanitizations from the changes between the vulnerable code and corresponding patches, infer the sinks with the impact analysis, and determine the sources through the backward traversal on the control flow graph. Finally, the complete-linkage clustering method is applied to the extracted triples to summary the patterns. We evaluate our method with open source projects. The results show our method is effective: 1) our method infers vulnerability patterns for taint-style vulnerabilities; 2) compared with the method inferring patterns from the code base, new patterns are discovered; and 3) the inferred patterns are applied to search the similar vulnerabilities successfully.