Miracle-dz/UniFAR-FTUs huggingface dataset:
Synchronous Sample Rate Converter for Digital Audio Luı́s

The work carried out intends to find a method to perform the conversion of sampling frequencies for digital audio signals in a simple, straightforward way and that occupies few resources on a FPGA. During this work two implementations were made, one in software and one in hardware. The software implementation aimed to perform tests with different parameters quickly and efficiently. The parameters tested were the fundamental signal frequency, the input sampling frequency, the interpolator polynomial order, and the sample rate ratios. Configurations with and without filtering were also tested. The purpose of the second implementation was to have a prototype that could be deployed on a FPGA and would take up few resources. A direct method (Lagrange polynomial) was used to perform the conversion, because it uses explicit formulas to obtain the coefficients, and there is no need for optimization. Additionally, for low frequencies they feature a very high quality ideal for digital audio. Finally, it can be implemented with efficient algorithms and structures, reducing computational effort. A high polynomial order was used, because it was found that anti-aliasing filters were resource intensive, but didn’t add significant improvement. The hardware implementation was validated by simulation and the total harmonic distortion plus noise in the Nyquist band was below -90 dB for some predefined sample rate ratios.
Evolution of morphology, modulus, and conductivity in polymer electrolytes prepared via polymerization-induced phase separation

Polymer electrolytes are alternatives to liquid electrolytes traditionally used in electrochemical devices such as lithium-ion batteries and fuel cells. In particular, block polymer electrolytes are promising candidates because they self-assemble into well-defined microstructures, in which orthogonal properties can be integrated into a single material (e.g., high modulus in domain A, fast ion transport in domain B). However, the performance of block polymer electrolytes often falls short, due to the lack of long-range continuity of both domains and relatively low strength. We recently reported a simple, one-pot synthetic strategy to prepare polymer electrolytes with the highest reported combination of modulus and ionic conductivity, attributes enabled by a co-continuous, cross-linked network morphology. In this work we aim to understand the mechanism by which this nanoscale morphology is formed by performing a series of in situ, time-resolved experiments—small-angle X-ray scattering, conductivity, rheolog.
Demarcation area between juvenile and mature wood in Elaeocarpus angustifolius

Abstract. Rahayu I, Laksono GD, Darmawan W, Maddu A, Prihatini E. 2021. Demarcation area between juvenile and mature wood in Elaeocarpus angustifolius. Biodiversitas 22: 2583-2590. Wood for use in building and industrial materials is generally supplied from plantations and natural forests. Timber demand has been increasing as the population grows, but the availability of timber from natural forests is declining. Therefore, to meet timber needs, wood from community forests is becoming a solution. Community forests are widely planted with fast-growing trees, such as Elaeocarpus angustifolius Blume. It offers the advantages of a short cutting cycle and large-diameter wood. This study aimed to determine the demarcation area between juvenile and mature wood on 6-year-old E. angustifolius based on anatomical, physical, and mechanical properties. The parameters used to determine the demarcation area included the following properties: anatomical (fiber length, cell wall thickness, and microfibril angle [MFA]), physical (moisture content and green density), and mechanical (modulus of elasticity [MOE], modulus of rupture [MOR], and hardness). Those parameters were measured from pith to bark. Data analyses were based on segmented linear regression models using PROC NLIN in SAS. Fiber length, cell wall thickness, green density, MOE, MOR, and hardness values increased from pith to bark. Results from the segmented linear regression models on anatomical properties allowed extrapolating that mature wood would begin at the 18 cm (based on fiber length), the 20 cm (based on cell wall thickness), and the 21 cm (based on MFA) distance from the pith. the proportion of juvenile wood in E. angustifolius was 100%. Fiber length, cell wall thickness, and MFA can be used to determine the transition point of juvenile wood and mature wood in E. angustifolius.
Pseudolaric Acid B Attenuates High Salt Intake-Induced Hypertensive Left Ventricular Remodeling by Modulating Monocyte/Macrophage Phenotypes

Background Studies in ApoE knockout mice have shown that pseudolaric acid B (PB) can act as an immunomodulatory drug and attenuate atherosclerosis progression by modulating monocyte/macrophage phenotypes. Our previous study demonstrated that high salt intake could shift the phenotype of monocytes/macrophages to an inflammatory phenotype, and that this shift was related to hypertension and hypertensive left ventricular (LV) remodeling. However, no comprehensive assessment of the effects of PB on hypertensive LV remodeling has been conducted. Material/Methods In this study, RAW264.7 macrophages cultured with different concentrations of NaCl were used to investigate the modulating effects of PB on macrophage phenotype. Furthermore, N-nitro-l-arginine methyl ester hypertensive mice were used to investigate the modulating effects of PB on monocyte phenotype. LV remodeling was investigated by echocardiography. LV morphologic staining (for cardiomyocyte hypertrophy and collagen deposition) was performed at the time of sacrifice. Results The results showed that PB significantly improved the viability of RAW264.7 cells, suppressed their phagocytic and migration abilities, and inhibited their phenotypic shift to M1 macrophages. In addition, the blood pressure of PB-treated mice was significantly decreased relative to that of control mice. Furthermore, after PB treatment, the percentage of Ly6Chi monocytes was significantly decreased while that of Ly6Clo monocytes was apparently increased. Moreover, PB preserved LV function and alleviated myocardial fibrosis and cardiomyocyte hypertrophy as measured at the end of the experimental period. The transfer of monocytes from PB-treated mice to hypertensive mice achieved the same effects. Conclusions Together, these findings indicate that PB exerts its protective effects on hypertensive LV remodeling by modulating monocyte/macrophage phenotypes and warrants further investigation.
Word Embeddings-based Sentence-Level Sentiment Analysis considering Word Importance

: Word2vec has been proven to facilitate various Natural Language Processing (NLP) tasks. We suppose that it could separate the vector space of word2vec into positive and negative. Hence, word2vec can be applied to Sentiment Analysis tasks. In our previous research, we proposed the word embeddings (WEMB) based Sentence-level Sentiment Analysis method. Word’s vectors from WEMB are utilized to calculate the sentence vector. Training of the classification model is done using sentence vector and the polarity. After training, the model predicts the polarity of the unlabeled sentence. However, the sentence vector was insufficient because the method treats all words with the same weight for calculating a sentence vector. In this paper, we propose a method to solve this problem. We consider word weight according to their importance for calculating sentence vector. The proposed method is compared with the method without word importance, and the accuracy is improved. However, there is still a grim difference with state of the art. We discuss the next improvement and present future work.
Economic development in Iraq: Foreign Financing Sources and the Terms of International Financing Institutions

The role of external financing sources that include both development assistance, foreign loans and foreign investment hold the possibility of rebuilding Iraq, and solve some sectorial problems of the Iraqi economy. In addition to the possibility of foreign companies entering with their huge financial capabilities, they have the ability to attract advanced technology, open job opportunities and introduce modern methods of management. However, some comment is needed on the expansion of dependence on external loans to cover the public budget deficit, as it represents a constraint on development rather than an alternative opportunity to finance it from non-oil sources. These loans also constitute a burden on the present and future generations in light of the lack of coherent and consistent macroeconomic policies that work to invest it with high efficiency. Iraq data was analysed over the period of 2003-2018, the results concluded that all variables have an impact on economic development in Iraq except for the development assistance variable.
Understanding the Lived Experiences of Athlete Elderly in COVID-19 Pandemic in Tehran (A Phenomenological Approach)

Objectives: Epidemics create extensive socio-behavioral changes in all areas, sport is no exception. The current study aimed at understanding the lived experience of athletic older adults from the Coronavirus Disease 2019 (COVID-19) pandemic. Methods & Materials: The present qualitative research applied a phenomenological approach. The study participants were 16 athletic older adults in Tehran City, Iran who were selected by the purposive sampling method. Through in-depth and unstructured interviews, the required data were collected. The obtained data were analyzed using the seven-step Diekelman’s (1993) approach. Results: According to the obtained data, 4 categories of meanings were identified about the lived experiences of the explored elderly from the COVID-19 pandemic. These categories included the experiences of psychosocial isolation and thinking about death; the marginalization of older adult's sports; mood swings and lifestyle changes, and finding opportunities for sports activism. Conclusion: These concepts of experiences in the life-world of athletic older adults in Tehran from the COVID-19 pandemic were the constitutions of their social action. In the case of proper analysis and application, they can be helpful in better managing professional sports in epidemics.
Histone H3K4me1 strongly activates the DNase I hypersensitive sites in super-enhancers than those in typical enhancers

Abstract Super-enhancers (SEs), which consist of multiple enhancer elements, are occupied by master transcription factors and co-activators, such as Mediator, and are highly acetylated at histone H3K27. Here, we have characterized the SEs in terms of DNase I hypersensitive sites (DHSs) by analyzing publicly available chromatin immunoprecipitation (ChIP)-seq and DNase-seq data of K562 cells and compared with the DHSs in typical enhancers (TEs). DHSs in the SEs were highly marked by histone H3K4me1 than DHSs in TEs. Loss of H3K4me1 by the deletion of catalytic domains in histone methyltransferases MLL3 and MLL4 remarkably decreased histone H3K27ac and histone H3 depletion at SE DHSs than at TE DHSs. The levels of enhancer RNA (eRNA) transcripts and mRNA transcripts from the putative target genes were notably reduced at and near SE DHSs than TE DHSs following H3K4me1 loss. These results indicate that histone H3K4me1 is a marker for DHSs in SEs and that this modification has a more significant impact on the activation of SE DHSs than TE DHSs.
Study for the Development of a Guidance and Information System Based on Wi-Fi for TU Wien

A guidance and information system based on Wi-Fi signals using fingerprinting for localization is currently under development for the whole University campus of TU Wien (Vienna University of Technology). In a first step, the availability, performance, and usability of Wi-Fi in selected areas of the University are analyzed. For this purpose, Wi-Fi received signal strengths (RSS) of the surrounding access points (APs) were measured in front of the main building of the University, in the library and in a large multi-storey office building called Freihaus under real conditions. The measurements were carried out in static, kinematic and stop-and-go mode with six different smartphones. In this paper, the kinematic measurements of users walking along predefined trajectories are analyzed. Kinematic measurements, however, pose much greater challenges than the usual static or stop-and-go measurements. The analysis of the system training measurements showed that there are sufficiently stable signals available everywhere on the campus to carry out a position determination using Wi-Fi fingerprinting. A probabilistic fingerprinting approach based on the Mahalanobis distance was then applied. The resulting deviations from the ground truth in the positioning phase were in the range of 1 to 3 m in the Freihaus office building. A significant dependence of the results in the kinematic mode, however, is caused by the duration of a single Wi-Fi scan. The durations were in the range of 2.4 to 4.1 s depending on the used smartphone. This can result in different accuracies for kinematic positioning, as fewer measurements along the trajectories for interpolation are available for a device with longer scan duration.
Classification trees using new criteria for two or more categories

Different node splitting criteria are available for the construction of classification and regression trees. Two of these criteria i.e. Gini and Twoing criterion have been implemented in CART (Salford systems, 1995), Entropy function in C4.5 (Quinlan, 1993) etc. These criteria provide similar results especially for the small number of categories but not for large. To overcome this problem, we proposed a new node splitting method for the construction of classification trees. The performance of the new method is compared with conventional methods using two real life datasets and it is observed that the new method gives better results in terms of misclassification and deviance.
CO2 fertilization physiological effect can cause rainfall decrease as strong as large-scale deforestation in the Amazon

Climate in the Amazon region is particularly sensitive to surface processes and properties such as heat fluxes and vegetation coverage. Rainfall is a key expression of land surface-atmosphere interactions in the region due to its strong dependence on forest transpiration. While a large number of past studies have shown the impacts of large-scale deforestation on annual rainfall, studies on the isolated effects of elevated atmospheric CO2 concentration (eCO2) on canopy transpiration and rainfall are scarcer. Here for the first time we make a systematic comparison of the plant physiological effects of eCO2 20 and deforestation on Amazon rainfall. We use the CPTEC-Brazilian Atmospheric Model (BAM) with dynamic vegetation under a 1.5xCO2 and a 100% substitution of the forest by pasture grassland, with all other conditions held similar between the two scenarios. We find that both scenarios result in equivalent average annual rainfall reductions (Physiology: -2572 mm, -12%; Deforestation: -292183 mm, -139%) that are well above observed Amazon rainfall interannual variability of 5.1%. Rainfall decrease in the two scenarios are caused bylinked to a reduction of approximately 20% of canopy 25 transpiration, but for different reasons: eCO2-driven reduction of stomatal conductance in Physiology; and decreased smaller leaf area index of pasture (-7266%) and its dry-season lower surface vegetation coverage in Deforestation. Walker circulation is strengthened modified in the two scenarios [(Physiology: a humidity-enriched free troposphere with decreased deep convection due to the heightening of a drier and warmer (+2.1oC) boundary layer; Deforestation: with enhanced convection over the Andes and a weak subsidence branch over east Amazon without considerable changes in temperature (30 0.2oC)]) but, again, through different mechanisms: enhanced strengthened west winds from the Pacific and reduced easterlies
The Conceptual Schema of Ethereum and of the ERC–20 Token Standard

There is an abundant literature on Ethereum, but as far as we know what is missing is its explicit conceptual schema. We present here the conceptual schema of Ethereum in UML. The schema should be useful to those that want to understand Ethereum. We also show that the schema is necessary for developing the schema of Ethereum–based DApps. We present a few population constraints, and show that they suffice for the specification at the conceptual level of what is understood by immutability of a blockchain. We also show that the well–known reification construct and an initial constraint suffice to specify at the conceptual level that the Ethereum blockchain stores the full state history.
Aerobic Physical Activity Participation and Correlates of Participating in Muscle Strengthening Physical Activity: A Cross-Sectional Analysis

The purpose of this study was to evaluate differences in correlates of muscle-strengthening physical activity (PA) between those meeting and not meeting aerobic PA guidelines. A sample of college students (n = 392) completed a survey measuring constructs from the reasoned action approach for musclestrengthening PA. Overall, 56% (n = 220) met the aerobic PA recommendations, and 25% (n = 99) met the muscle-strengthening PA recommendations. The mean age of participants was 19.9 years (± 1.76) (meeting aerobic PA = 20.0 years old ± 1.73; not meeting aerobic PA = 19.8 years old ± 1.79), and there were no differences between race or class standing between groups [a majority of the sample identified as white/Caucasian (83.4%; n = 327) and female (69.4%; n = 272)]. Separate linear regression models were created for college students meeting and not meeting aerobic PA guidelines. College students meeting aerobic guidelines (n = 220) reported significantly more muscle-strengthening PA (m = 2.89 days ± 2.0) than students not meeting guidelines (n = 172) (m = 2.06 days ± 1.9) (p < 0.001; d = 0.42). Regression models showed that attitudes, perceived norms, and perceived behavioral control (PBC) explained a substantial amount of the variance of intentions for both groups [meeting (45.5%); not meeting (59.7%)], however PBC moderated the relationship between intentions and muscle-strengthening PA for those not meeting aerobic recommendations. Results demonstrate that there are different correlates for muscle-strengthening PA, based on participation in aerobic PA, which translates to a need for different intervention approaches and strategies for both groups.
Research Towards Yolo-Series Algorithms: Comparison and Analysis of Object Detection Models for Real-Time UAV Applications

General Unmanned Aerial Vehicles (UAVs) are widely used through the computer vision functions of onboard cameras and embedded systems. However, due to the limited memory and computing power of embedded devices on the UAV platform, it is a very challenging issue to analyze the real-time scene through the object detection method. To deal with these challenges, this paper compares the performance of different Yolo series models on the Pascal VOC dataset, using mAP and FPS as evaluation metrics, and applies the training results to the XTDrone UAV Simulation Platform for testing. We evaluate YOLOv3, YOLOv3-tiny, YOLOv3-SPP3, YOLOv4, and YOLOv4-tiny on the Pascal VOC benchmark dataset; the mAP of YOLOv4 is 87.48%, which is 14.2% higher than that of YOLOv3. FPS reaches 72, and the test time on the test set is 103.86s; the shortest test time on the validation set is Yolov4-tiny, but the mAP only reaches 50.06%, which is not as good as Yolov3-tiny. This paper compares the performance of five models in the Pascal VOC Dataset and simulates them on the XTDrone platform, and finally concludes that Yolov3-Tiny can meet the requirements of real-time, lightweight, and high precision.
Video reconstruction of generative adversarial network based on global perception

Aiming at the problem that the current video reconstruction can not take into account the high perception quality and high temporal correlation, a video reconstruction of generative adversarial network based on global perception is proposed. The generator adopts a recurrent and iterative network architecture. In order to make up for the lack of extraction of global information by the frame alignment network, the alignment network combines the global information extracted by the global information perception to perform frame alignment. Through the static temporal loss and the temporal statistics loss, combined with the relative discriminator of sequence frames input, the temporal correlation of the generated images sequence is improved. Experimental comparisons were performed on the Vid4 and REDS test sets, and the best image perception quality index (LPIPS/NIQE) were obtained, as well as better temporal correlation (tLPIPS), reaching 0.192/3.417/0.328 and 0.138/3.223/0.217. Experimental results show that the proposed method can effectively improve the perceptual quality of reconstructed video frames and has good temporal correlation.
Multi-threshold channel pruning method based on L1 regularization

Aiming at the problem of single detection scene and poor detection speed, a multi-threshold channel pruning method based on L1 regularization is proposed. L1 regularization is applied to the scaling factor of the BN layer to push the scaling factor of the BN layer to zero, thereby identifying unimportant channels, and determining the initial threshold of channel pruning according to the scaling factor after sparse training; The most suitable pruning threshold of the convolutional layer is obtained through minimum error reconstruction. The least square method and the method of weighting the channel are used to reconstruct the error before and after pruning, and the most suitable pruning threshold is obtained by minimizing the error. Through the data set simulation experiment, the YOLOv3 network is pruned, so that the network has a smaller network structure and faster detection speed, which is suitable for deployment on mobile devices.
Hand Gesture Controlled Nursing Bed Using FMCW Radar

The nursing bed has become an important tool for medical and elder care, as a well-designed bed can prevent users from bedsores. To improve the user convenience, a user-friendly human-computer interface is also necessary. In this paper, we design a new nursing bed containing a FMCW millimeter wave radar for gesture recognition. A control system can help user frictionless back-up, integral turning over and leg raising when lying in the bed. Besides, we adopt the convolutional recurrent neural network for recognition of 6 gestures. Experiments with the nursing bed show that the control success rate of the bed reaches 93.75% and the response time achieves 1.03 s.
Radar Life Signal Processing Algorithm Based on Improved EEMD

Non-contact measurement of human vital signs is of great significance to the construction of smart homes and hospitals. The vital signal extracted from the FMCW radar contains a lot of noise. In order to reduce the noise impact and improve the life signal detection results accuracy, Ensemble Empirical Mode Decomposition (EEMD) algorithm is studied, and a new method based on the combination of EEMD and Translation Invariant Wavelet Transform (TIWT) is proposed. This method firstly decomposes the original signal using EEMD to obtain several Intrinsic Mode Function (IMF) components, and then changes the arrangement order of IMF by Translation Invariant Wavelet Transform to change the position of the singularity in the whole signal to reduce or eliminate the oscillations. Finally, signal screening is completed and life signals are reconstructed. Experiments show that, the proposed method has better detection accuracy in detecting vital signs collected by radar.