Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthesis and Biological Evaluation of Novel Dehydroabietic Acid-Oxazolidinone Hybrids for Antitumor Properties

Novel representatives of the important group of biologically-active, dehydroabietic acid-bearing oxazolidinone moiety were synthesized to explore more efficacious and less toxic antitumor agents. Structures of all the newly target molecules were confirmed by IR, 1H-NMR, 13C-NMR, and HR-MS. The inhibitory activities of these compounds against different human cancer cell lines (MGC-803, CNE-2, SK-OV-3, NCI-H460) and human normal liver cell line LO2 were evaluated and compared with the commercial anticancer drug cisplatin, using standard MTT (methyl thiazolytetrazolium) assay in vitro. The pharmacological screening results revealed that most of the hybrids showed significantly improved antiproliferative activities over dehydroabietic acid and that some displayed better inhibitory activities compared to cisplatin. In particular, compound 4j exhibited promising cytotoxicity with IC50 values ranging from 3.82 to 17.76 µM against all the test cell lines and displayed very weak cytotoxicity (IC50 > 100 µM) on normal cells, showing good selectivity between normal and malignant cells. Furthermore, the action mechanism of the representative compound 4j was preliminarily investigated by Annexin-V/PI dual staining, Hoechst 33258 staining, which indicated that the compound can induce cell apoptosis in MGC-803 cells in a dose-dependent manner and arrest the cell cycle in G1 phase. Therefore, 4j may be further exploited as a novel pharmacophore model for the development of anticancer agents.
Spontaneous closed zone IV rupture of flexor digitorum profundus tendon to the fifth finger

Abstract We present a case of spontaneous closed flexor digitorum profundus (FDP) tendon rupture of the fifth finger occurring in the carpal tunnel region (Zone IV) of the hand. A review of literature illustrates that spontaneous rupture of FDP in Zone IV is extremely rare and we wish to highlight this.
Two-microphone subband noise reduction scheme with a new noise subtraction parameter for speech quality enhancement

An improved subband noise reduction technique is proposed for two-microphone voice communication systems. The technique aims to enhance the speech quality by utilising a subband structure with different noise reduction schemes for different frequency bands. In the low-frequency band where dominant cues of speech spectral components are usually located and the noise signals from the two channels are mainly correlated, the spectral subtraction method, together with a new variable noise subtraction parameter, is employed so that the noise attenuation performance and speech distortion are controllable. In the high-frequency band where less-dominant frequency information of speech spectrum is located, the modified cross-spectral subtraction technique is utilised to remove the high-frequency decorrelated noise spectral components. Extensive comparisons among various noise reduction techniques based on computer simulations demonstrate that the proposed two-microphone subband noise reduction scheme achieves excellent noise attenuation performance while preserving the speech quality.
Confluence of pattern recognition and signal processing: application of Al-Alaoui pattern recognition algorithm to digital filters design

A weighted mean square error (WMSE) approach to optimising digital filters is delineated. It is applied in the current work to optimising the classical Al-Alaoui IIR differentiators to obtain new improved wideband differentiators of varying orders. These can be directly used for analog to digital conversion and in many digital signal processing applications. The weighted MSE approach is motivated by the Al-Alaoui WMSE approach to pattern recognition. In addition, the differentiators are converted to integrators of similar orders that are further optimised. Various examples and comparisons are presented to demonstrate the viability of the proposed approach.
Cryptanalysis of Low-Data Instances of Full LowMCv2

LowMC is a family of block ciphers designed for a low multiplicative complexity. The specification allows a large variety of instantiations, differing in block size, key size, number of S-boxes applied per round and allowed data complexity. The number of rounds deemed secure is determined by evaluating a number of attack vectors and taking the number of rounds still secure against the best of these. In this paper, we demonstrate that the attacks considered by the designers of LowMC in the version 2 of the round-formular were not sufficient to fend off all possible attacks. In the case of instantiations of LowMC with one of the most useful settings, namely with few applied S-boxes per round and only low allowable data complexities, efficient attacks based on difference enumeration techniques can be constructed. We show that it is most effective to consider tuples of differences instead of simple differences, both to increase the range of the distinguishers and to enable key recovery attacks. All applications for LowMC we are aware of, including signature schemes like Picnic and more recent (ring/group) signature schemes have used version 3 of the roundformular for LowMC, which takes our attack already into account.
From computer edit geometric design education to virtual worlds: Advantages and pitfalls of Computer‐Based Education

Nowadays, computers are an integral part of the education process in many fields and levels. Although numerous research has been done on Computer‐Based Education (CBE), there are still open questions that have to be answered. Authors have faced some of those important questions over the years while developing the teaching applications from various areas. In this paper, those questions are presented, while the authors' approaches and obtained results offer some answers to those questions. The paper identifies the areas where special attention is needed in order to preserve the effectiveness of the applications in the teaching process. Practical examples of their work are used to demonstrate how the integration level of computers in the teaching process and teaching goals, along with other factors, can affect the effectiveness of teaching applications. With the comparison of the findings with other authors, some crude guidelines are given on how to achieve the best teaching results.
Personal informatics systems for supporting self‐regulation in online learning environments

Personal informatics (PI) systems have emerged as powerful tools for helping people to be aware of their behaviors in diverse domains. Nevertheless, little attention has been devoted to educational scenarios. For this reason, this paper presents an educational PI system called Glance and, moreover, evaluates its usefulness in two fully online undergraduate courses.
Design and Performance Evaluation of a Wearable Sensing System for Lower-Limb Exoskeleton

Because the target users of the assistive-type lower extremity exoskeletons (ASLEEs) are those who suffer from lower limb disabilities, customized gait is adopted for the control of ASLEEs. However, the customized gait is unable to provide stable motion for variable terrain, for example, flat, uphill, downhill, and soft ground. The purpose of this paper is to realize gait detection and environment feature recognition for AIDER by developing a novel wearable sensing system. The wearable sensing system employs 7 force sensors as a sensing matrix to achieve high accuracy of ground reaction force detection. There is one more IMU sensor that is integrated into the structure to detect the angular velocity. By fusing force and angular velocity data, four typical terrain features can be recognized successfully, and the recognition rate can reach up to 93%.
A novel teaching platform design with CAI for EM education

Computers and multimedia technology can greatly facilitate the visualization of abstract concepts and intangible objects such as electromagnetic waves. An educational design platform is proposed to assist undergraduate students in understanding these waves. At present, most electromagnetics courses still use traditional teaching design ideas, from mathematics to reason, and spend much time on formula deduction. Educational design overturns this idea thoroughly to learn with problems and solve experiments related to uncertain concepts; this design will help undergraduate students learn the basic characters of electromagnetic waves intuitively and more easily. Through the experiment‐simulation method, students can experimentally sample data and process data real‐time using simulation software. In this way, students can grasp the physical meaning of abstract concepts more accurately through experiments; furthermore, computer simulations can show the relationships between parameters more intuitively. Thus, the original intention of teaching aided design is exactly reflected: “see knowledge and learn knowledge. ”
Integrative Acceleration of First-Order Boolean Masking for Embedded IoT Devices

Physical attacks, especially side-channel attacks, are threats to IoT devices which are located everywhere in the field. For these devices, the authentic functionality is important so that the IoT system becomes correct, and securing this functionality against side-channel attacks is one of our emerging issues. Toward that, Coron et al. gave an efficient arithmetic-to-Boolean mask conversion algorithm which enables us to protect cryptographic algorithms including arithmetic operations, such as hash functions, from the attacks. Recently, Biryukov et al. improved it by locally optimizing subroutines of the conversion algorithm. In this paper, we revisit the algorithm. Unlike Biryukov et al., we improve the Coron et al.’s algorithm with integrative optimizations over the subroutines. The gains against these algorithms are about 22.6% and 7.0% in the general setting. We also apply our algorithm to HMAC-SHA-1 and have an experiment to show that the implementation on a test vehicle smartcard leaks no sensitive information with the ISO/IEC17825 test.
Peer assessment and groups formation in massive open online courses

One of the major challenges facing Massive Open Online Courses (MOOCs) is assessing the learner performances beyond traditional automated assessment methods. This leads to a bottleneck problem due to the massiveness of course participants, especially in the context of problem solving. To tackle this issue, peer assessment has been proposed as an effective method. However, the validity of this process is still under discussion, suffers from a lack of credibility and has many weaknesses, particularly with regards to group formation. This paper develops a new method of peer assessment for MOOCs to improve the accuracy and exactitude of the learner grade. Our proposition is based on three main steps: the formation of learner groups, the assessment and synthesis of the results. First, the group definition process can use different elements of the learner model and enables to build heterogeneous groups. After, each learner is required to grade a small number of peer productions. Finally, a synthesis of the various grades is proposed using both data about the ability to assess of each learner and complexity of problems. To evaluate the proposed peer assessment process, we conducted an experimentation devoted to teaching Software Quality Assurance to beginners with computer science during the first university cycle.
Retinal Vessel Diameter Changes in Relation to Dark Adaptation and Acute Hyperglycemia

The purpose of this experimental clinical study was to assess the effects of dark adaptation and acute changes in glycemia on retinal vessel diameters in men. The study included 14 patients (mean age 63 years, range 48–74 years) with type 2 diabetes mellitus and minimal or no diabetic retinopathy. Retinal vessel diameters were assessed using infrared photography before and after dark adaptation, first while fasting and then at peak hyperglycemia during an oral glucose tolerance test (OGTT). Dark adaptation was accompanied by retinal vasodilatation, both during fasting (mean glycemia 7.6 ± 1.7 mM) and postprandial hyperglycemia (15.7 ± 4.2 mM). When fasting, the increase in vein diameter during dark adaptation was 2.0% after 20 min (P=0.018) and 2.9% after 40 min (P=0.010). When subjects were hyperglycemic, the increase during dark adaptation was 2.8% for retinal vein diameters (P=0.027) and 2.0% for retinal artery diameters after 20 min (P=0.002) and 1.7% for retinal artery diameters after 40 min (P=0.022). For identical conditions of light/dark adaptation, retinal vessels were dilated when subjects were fasting compared to postprandial hyperglycemia. Thus, darkness and fasting were both associated with retinal vasodilation in this short-term experiment in patients with type 2 diabetes. Future studies should determine whether both the stimuli of vasodilation lead to retinal hyperperfusion, which would support that they may be involved in the aggravation of diabetic retinopathy.
Pilot allocation approaches for channel estimation in MIMO relay networks

Distributed-compressed sensing (DCS)-based channel estimation of multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing for relay communication is considered in this study. Specifically, the pilot allocation is addressed to optimise the channel estimation performance. All the existing works on DCS-based channel estimation pilot placement discussed on the mean square error (MSE) of the estimation probabilistically based on the mutual coherence. On the contrary, the authors try to address the MSE of the estimation directly and optimise the MSE directly and design a pilot pattern to optimise the performance of the estimation. By taking into account the optimisation approach, two combinatorial stochastic algorithms have been presented. These two algorithms utilise cross entropy approach in sequential and parallel form. Simulation results represent that the DCS-based MIMO relay channel estimation using optimised pilot placements will increase the performance from 3 to 12 dB as compared with the conventional least squares (LS) method. Furthermore, parallelism has demonstrated the performance gain. Moreover, the DCS-based MIMO relay channel estimation shows 35 % improvement in spectrum efficiency under the same bit error rate performance over the traditional LS-based channel estimation approach, respectively.
A physical topology discovery method based on AFTs of down constraint

: Network physical topology discovery is the key issue for network management and application, the physical topology discovery based on Address Forwarding Table (AFT) is a hot topic on current study. This paper defines three constraints of AFTs, and proposes a tree chopping algorithm based on AFTs satisfying down constraint, which can discover the physical topology of a subnet accurately. The proposed algorithm decreases the demand for AFT integrity dramatically, and is the loosest constraint for discovering physical topology which just relies on AFTs of down ports. The proposed algorithm can also be used in the switch domain of multiple subnets.
Standard-Compliant Multiple Description Image Coding Based on Convolutional Neural Networks

Multiple description (MD) coding is an attractive framework for robust information transmission over non-prioritized and unpredictable networks. In this paper, a novel MD image coding scheme is proposed based on convolutional neural networks (CNNs), which aims to improve the reconstructed quality of side and central decoders. For this purpose initially, a given image is encoded into two independent descriptions by sub-sampling. Such a design can make the proposed method compatible with the existing image coding standards. At the decoder, in order to achieve high-quality of side and central image reconstruction, three CNNs, including two side decoder sub-networks and one central decoder subnetwork, are adopted into an end-to-end reconstruction framework. Experimental results show the improvement achieved by the proposed scheme in terms of both peak signal-to-noise ratio values and subjective quality. The proposed method demonstrates better rate central and side distortion performance. key words: image coding, multiple description (MD) coding, convolutional neural network
An empirical study to evaluate the relationship of object-oriented metrics and change proneness

: Software maintenance deals with changes or modifications which software goes through. Change prediction models help in identification of classes/modules which are prone to change in future releases of a software product. As change prone classes are probable sources of defects and modifications, they represent the weak areas of a product. Thus, change prediction models would aid software developers in delivering an effective quality software product by allocating more resources to change prone classes/modules as they need greater attention and resources for verification and meticulous testing. This would reduce the probability of defects in future releases and would yield a better quality product and satisfied customers. This study deals with the identification of change prone classes in an Object-Oriented (OO) software in order to evaluate whether a relationship exists between OO metrics and change proneness attribute of a class. The study also compares the effectiveness of two sets of methods for change prediction tasks i.e. the traditional statistical methods (logistic regression) and the recently widely used machine learning methods like Bagging, Multi-layer perceptron etc.
Sampling of multiple signals with finite rate of innovation and sparse common support

The authors focus on the minimum sampling rate and the exact recovery condition in the sampling of multiple signals with finite rate of innovation (FRI) and sparse common support (SCS). The authors first propose the subspace-based recovery method and analyse its relation with the annihilating filter; then the proposed method is used for sampling the multiple signals with FRI and SCS. It is observed that the minimum sampling rate for the exact recovery heavily depends on the signal structure described by the defined characteristic matrix, based on which a sufficient and necessary condition is also presented. The numerical simulations show that the proposed recovery method and the recovery condition are feasible for the sampling of multiple signals with FRI and SCS.
EEG Microstates Change in Response to Increase in Dopaminergic Stimulation in Typical Parkinson’s Disease Patients

Objectives: Characterizing pharmacological response in Parkinson’s Disease (PD) patients may be a challenge in early stages but gives valuable clues for diagnosis. Neurotropic drugs may modulate Electroencephalography (EEG) microstates (MS). We investigated EEG-MS default-mode network changes in response to dopaminergic stimulation in PD. Methods: Fourteen PD subjects in HY stage III or less were included, and twenty-one healthy controls. All patients were receiving dopaminergic stimulation with levodopa or dopaminergic agonists. Resting EEG activity was recorded before the first daily PD medication dose and 1 h after drug intake resting EEG activity was again recorded. Time and frequency variables for each MS were calculated. Results: Parkinson’s disease subjects MS A duration decreases after levodopa intake, MS B appears more often than before levodopa intake. MS E was not present, but MS G was. There were no significant differences between control subjects and patients after medication intake. Conclusion: Clinical response to dopaminergic drugs in PD is characterized by clear changes in MS profile. Significance: This work demonstrates that there are clear EEG MS markers of PD dopaminergic stimulation state. The characterization of the disease and its response to dopaminergic medication may be of help for early therapeutic diagnosis.
Understanding the message of images

We investigate the problem of understanding the message (gist) conveyed by images and their captions as found, for instance, on websites or news articles. To this end, we propose a methodology to capture the meaning of image-caption pairs on the basis of large amounts of machine-readable knowledge that have previously been shown to be highly effective for text understanding. Our method identifies the connotation of objects beyond their denotation: where most approaches to image or image-text understanding focus on the denotation of objects, i.e., their literal meaning, our work addresses the identification of connotations, i.e., iconic meanings of objects, to understand the message of images. We view image understanding as the task of representing an image-caption pair on the basis of a widecoverage vocabulary of concepts such as the one provided by Wikipedia, and cast gist detection as a concept-ranking problem with image-caption pairs as queries.
Fecal Microbiota Transplant for Recurrent Clostridium difficile Infection in Pediatric Inflammatory Bowel Disease

Objectives: Recurrent Clostridium difficile infection (RCDI) increases morbidity and mortality in patients with inflammatory bowel disease (IBD). Fecal microbiota transplant (FMT) is known to be very effective for RCDI in non-IBD patients with cure rates up to 91%. The same success rates of FMT have not been reported in patients with IBD with RCDI, and the data in pediatrics are limited. We aimed to determine the effectiveness of FMT for RCDI in established pediatric patients with IBD. Methods: We performed a retrospective chart review of pediatric patients with IBD and RCDI (≥3 episodes) who underwent FMT via colonoscopy at a tertiary care IBD center. The primary outcome was the rate of RCDI within 60 days post-FMT. The secondary outcomes were recurrence rate by 6 months, rate of colectomy, and time to recurrence. Results: Of the 8 eligible patients, 6 had ulcerative colitis, 1 had IBD-unspecified, and 1 had Crohn disease. Median (interquartile range) age was 13 (11–14) years. All patients were on vancomycin at FMT. Two patients (25%) had RCDI by 60 days post-FMT and another 3 patients had RCDI between 60 days and 6 months. The median time to recurrence was 101 (40–139) days. Two patients (25%) who developed recurrence went to colectomy after FMT. Conclusions: With a cure rate of 75% at 60 days, FMT administered for the treatment of RCDI may be an effective treatment option in pediatric IBD. However, there appears to be a significant rate of late recurrence of C difficile infection after 60 days in these patients.