Miracle-dz/UniFAR-FTUs huggingface dataset:
Neuromorphic Tactile Edge Orientation Classification in an Unsupervised Spiking Neural Network

Dexterous manipulation in robotic hands relies on an accurate sense of artificial touch. Here we investigate neuromorphic tactile sensation with an event-based optical tactile sensor combined with spiking neural networks for edge orientation detection. The sensor incorporates an event-based vision system (mini-eDVS) into a low-form factor artificial fingertip (the NeuroTac). The processing of tactile information is performed through a Spiking Neural Network with unsupervised Spike-Timing-Dependent Plasticity (STDP) learning, and the resultant output is classified with a 3-nearest neighbours classifier. Edge orientations were classified in 10-degree increments while tapping vertically downward and sliding horizontally across the edge. In both cases, we demonstrate that the sensor is able to reliably detect edge orientation, and could lead to accurate, bio-inspired, tactile processing in robotics and prosthetics applications.
Deep Segment Model for Acoustic Scene Classification

In most state-of-the-art acoustic scene classification (ASC) techniques, convolutional neural networks (CNNs) are adopted due to their extraordinary ability in learning local deep features. However, the CNN-based approach is unable to effectively describe the structure of sound events in an audio clip, which is a key element in distinguishing acoustic scenes with similar characteristics, whereas the acoustic segment model (ASM) based approach shows its superiority. To take full advantage of these two types of approaches, we proposed a novel deep segment model (DSM) for ASC. DSM employs a fully convolutional neural network (FCNN) as a deep feature extractor and then guides the ASM to better capture semantic information among sound events. Specifically, the FCNN-based encoder is trained with the multi-task of classifying both three coarse-grained acoustic scenes and ten fine-grained acoustic scenes to extract multi-level acoustic features. Moreover, an entropy-based decision fusion strategy is designed to further utilize the complementarity of FCNN-based and DSM-based systems. The final system achieves an accuracy of 80.4% in the DCASE2021 Task1b audio dataset, yielding a relative error rate reduction of about 15% over the FCNN-based system.
MDMX Regulates Transcriptional Activity of p53 and FOXO Proteins to Stimulate Proliferation of Melanoma Cells

Simple Summary We have investigated the transcriptional changes occurring in uveal and cutaneous melanoma cell lines upon depletion of MDMX (aka:MDM4). Computational analyses of the mRNAs/genes affected upon MDMX depletion determined that many were containing a p53-bindingsite, but even more contained a FOX recognition site(s). Since connections between MDM2 and FOXO1 had already been published, we investigated whether indeed a subset of the MDMX-regulated genes are dependent on FOXO1/FOXO3 expression. Indeed, a number of such target genes, i.e., PIK3IP1, MXD4 and ZMAT3, were found to be FOXO target genes in our cell models. Some of these genes were recently identified as indirect p53-target genes, and their expression was found to be regulated by RFX7 transcription factor, which was found activated upon pharmacological activation of p53, e.g., by Nutlin-3. However, a clear involvement of RFX7 in our model could not be established, but an interplay between FOXO and RFX7 factors seems evident. Abstract The tumor suppressor protein p53 has an important role in cell-fate determination. In cancer cells, the activity of p53 is frequently repressed by high levels of MDMX and/or MDM2. MDM2 is a ubiquitin ligase whose activity results in ubiquitin- and proteasome-dependent p53 degradation, while MDMX inhibits p53-activated transcription by shielding the p53 transactivation domain. Interestingly, the oncogenic functions of MDMX appear to be more wide-spread than inhibition of p53. The present study aimed to elucidate the MDMX-controlled transcriptome. Therefore, we depleted MDMX with four distinct shRNAs from a high MDMX expressing uveal melanoma cell line and determined the effect on the transcriptome by RNAseq. Biological function analyses indicate the inhibition of the cell cycle regulatory genes and stimulation of cell death activating genes upon MDMX depletion. Although the inhibition of p53 activity clearly contributes to the transcription regulation controlled by MDMX, it appeared that the transcriptional regulation of multiple genes did not only rely on p53 expression. Analysis of gene regulatory networks indicated a role for Forkhead box (FOX) transcription factors. Depletion of FOXO proteins partly prevented the transcriptional changes upon MDMX depletion. Furthermore, depletion of FOXO proteins relatively diminished the growth inhibition upon MDMX knockdown, although the knockdown of the FOXO transcription factors also reduces cell growth. In conclusion, the p53-independent oncogenic functions of MDMX could be partially explained by its regulation of FOXO activity.
Large-scale 13CO J = 5 → 4 and [C I] Mapping of Orion A

We present maps of the 13CO J = 5 → 4 (551 GHz) and [C I] 3P1 → 3P0 (492 GHz) emission in the Orion A molecular cloud, covering a 0. °5 × 2° area. A large velocity gradient (LVG) analysis of 13CO J = 5 → 4 and J = 1 → 0 suggests that the gas temperatures in the northern part of OMC-1 (north of Δδ = -20′) are ~45 K and are, on average, at least 20 K higher than those to the south. The average 13CO column density is log(N/cm-2) = 16.4 ± 0.3 and is fairly constant throughout the cloud, even in the low-temperature region south of BN/KL. LVG modeling of the [C I] emission shows a typical C0 column density of 2 × 1017 cm-2, which yields a C/CO abundance ratio in the cloud of ~0.1 (rising to levels in excess of 0.5 at the cloud edges). Comparison of the Δ-variance (which measures spatial structure in a manner similar to a power spectrum) of the Submillimeter Wave Astronomy Satellite [C I], Five College Radio Astronomy Observatory 13CO J = 1 → 0, and CS J = 1 → 0 velocity-integrated maps suggests that the [C I] and 13CO emission arise from the same gas. In contrast, the CS emission likely originates in gas that is considerably more clumpy.
Non-destructive testing with surface acoustic waves using double-pulse TV holography

In this paper we present the visualization of the out-of-plane displacement fields produced by Rayleigh and Lamb waves on aluminium surfaces, using a double-pulse TV holography technique. This method presents several interesting characteristics, as a possible way of making whole-field remote measurements of instantaneous acoustic displacements, with good immunity from environmental perturbations. We also show examples where different surface and subsurface flaws have been detected, demonstrating the great potential of this technique for non-destructive testing in industrial applications.
Proses Perkembangan Pendidikan Islam Pada Periode Dinasti Bani Umayyah

Pendidikan Islam merupakan suatu hal yang paling utama bagi setiap warga, karena maju dan keterbelakangan suatu negara akan ditentukan oleh tinggi dan rendahnya tingkat pendidikan warga negaranya. Proses perkembangan pendidikan Islam pada hakekatnya sangat berkaitan erat dengan sejarah Islam. Periodesasi pendidikan Islam selalu berada dalam periode sejarah Islam itu sendiri. Pendidikan Islam di zaman Nabi Muhammad SAW merupakan periode pembinaan pendidikan Islam dengan cara membudayakan pendidikan Islam dalam kehidupan sehari-hari sesuai dengan ajaran Al-Qur’an. pendidikan pada periode Bani Umayyah telah berkembang jika dilihat dari aspek pengajarannya, walaupun sistemnya masih sama seperti pada masa Nabi dan khulafaur rasyidin
Analysis of expressivity transfer in non-autoregressive end-to-end multispeaker TTS systems

The main objective of this work is to study the expressivity transfer in a speaker’s voice for which no expressive speech data is available in non-autoregressive end-to-end TTS systems. We investigated the expressivity transfer capability of probability density estimation based on deep generative models, namely Generative Flow (Glow) and diffusion probabilistic models (DPM). The usage of deep generative models provides better log likelihood estimates and tractability of the system, subsequently providing high-quality speech synthesis with faster inference speed. Furthermore, we propose the usage of various expressivity encoders, which assist in expressivity transfer in the text-to-speech (TTS) system. More precisely, we used self-attention statistical pooling and multi-scale expressivity encoder architectures for creating a meaningful representation of expressivity. In addition to traditional subjective metrics used for speech synthesis evaluation, we incorporated cosine-similarity to measure the strength of attributes associated with speaker and expressivity. The performance of a non-autoregressive TTS system with a multi-scale expressivity encoder showed better expressivity transfer on Glow and DPM-based decoders. Thus, illustrating the ability of multi-scale architecture to apprehend the underlying attributes of expressivity from multiple acoustic features.
The complete chloroplast genome of Persicaria maackiana (Regel) Nakai ex T. Mori (Polygonaceae) in Korea

Abstract Persicaria maackiana (Regel) Nakai ex T. Mori (1922), a species of the Polygonaceae family, is an annual plant widely distributed in Northeast Asia. We aimed to sequence the complete chloroplast genome of P. maackiana using Illumina HiSeq paired-end sequencing. The chloroplast genome was determined to be 160,635 bp. The complete chloroplast genome contained 129 genes, including 84 protein-coding genes, 37 tRNA, and eight rRNA genes. Phylogenetic analysis of the chloroplast genome sequences of 15 Polygonaceae plants revealed that P. maackiana was most closely related to P. perfoliata. Our findings might be useful for future phylogenetic studies of Polygonaceae.
OPTIMASI ANFIS UNTUK PREDIKSI DATA TIME SERIES

ANFIS merupakan gabungan dari 2 metode yaitu fuzzy dan jaringan syaraf tiruan. Dari penggabungan 2 metode tersebut ANFIS memiliki kelebihan dalam melakukan prediksi data time series. Namun penggunaan metode ANFIS juga terdapat kekurangan. Kekurangan tersebut yaitu dapat menurunnya akurasi yang didapat. Penurunan tersebut dikarenakan data yang digunakan banyak yang bernilai error serta tidak bervariasi. Selain itu data yang digunakan tidak melalui proses preprocessing terlebih dahulu. Pengumpulan data berasal dari website BMKG. Data tersebut nantinya akan dilakukan proses preprocessing untuk mengatasi class imbalance. Hasil pelatihan dan pengujian dengan proses optimasi metode ANFIS dengan melakukan normalisasi dan pembersihan data erorr pada data curah hujan terdapat sedikit kesamaan baik dalam pelatihan dan pengujian. Untuk pengukuran performa akurasi prediksi menggunakan RMSE baik untuk rasio data 3:2 dan 4:1 masing – masing mendapatkan 0.0728 dan 0.0539. Berdasarkan hasil penerapan metode ANFIS dan normalisasi pada dataset curah hujan kabupaten sleman dengan parameter jumlah membership function, input membership function, learning rate, rasio data 3:2 dan 4:1 menunjukkan bahwa metode ANFIS dengan data yang sudah dilakukan proses normalisasi dan pembersihan data error dapat menjadi alternative metode untuk memprediksi tingkat curah hujan dengan data yang berjenis time series
Specializing in Politics: Effects of Specialization, Social Capital, and Human Capital on Corporate Lobbying

ABSTRACT Corporate lobbyists play a vital role in the Corporate Political Activity process. They act as a mediator between corporations and politicians when firms engage in lobbying activities. Firms value professional lobbyists for their connections in Washington and their knowledge of the political process. While previous Corporate Political Activity research on lobbying has focused primarily on the amount of money firms spend on lobbying, including antecedents of lobbying and outcomes, very little research has examined lobbyists’ individual differences and how those influence important outcomes. In this paper, we examine how lobbyists’ specialization and experience as both a lobbyist and a former politician can influence the number of bills lobbied on passed into law. Using a sample of corporate lobbyists who were hired by S&P 500 firms, we look at 8,630 lobbyist’s careers from 2005–2016. We find that lobbyists lower in specialization are more likely to lobby on bills which are eventually passed into law than highly specialized lobbyists. We also find that social capital moderates the relationship between specialization and lobbying effectiveness. These results suggest that while corporate political activity spending is important, both scholars and firms should also understand who firms are hiring to lobby for them and how differences in lobbyist specialization might influence firm effectiveness in the nonmarket arena.
Complete chloroplast genome sequences of Impatiens macrovexilla and I. macrovexilla var. yaoshanensis (Balsaminaceae)

Abstract Both Impatiens macrovexilla and I. macrovexilla var. yaoshanensis have potential to be exploited as ornamental plants, despite some of their morphological differences. In the present study, the complete chloroplast genome sequences of the two taxa are reported for the first time, which could facilitate their infraspecies classification, and analyses of their evolution, phylogeny, and breeding potential. The chloroplast genomes of I. macrovexilla and I. macrovexilla var. yaoshanensis were 152,437 and 152,286 bp in size, respectively. Their total GC contents were 36.77 and 36.80%, respectively. Both genomes contained 88 protein-coding genes, 8 rRNA genes, and 37 tRNA genes. The phylogenetic analysis revealed that the two specimens clustered next to each other and were closely related to I. alpicola, I. fanjingshanica, and I. piufanensis, but relatively distant from I. guizhouensis and I. pritzelii.
Contralesional Cortical and Network Features Associated with Preoperative Language Deficit in Glioma Patients

Simple Summary Gliomas that infiltrate eloquent areas can damage the corresponding cortical or subcortical structures, leading to language dysfunction. A total of 20–40% of eloquent area glioma patients have language deficits. Gliomas anchored in eloquent areas cause varying degrees of language impairment. A tumor’s size, grade, location, and contralesional compensation may explain these differences. This study aimed to retrospectively explore gray and white matter plasticity in the contralesional hemisphere of patients with gliomas in the eloquent area using VBM and DTI network analysis. Abstract Lower-grade Gliomas anchored in eloquent areas cause varying degrees of language impairment. Except for a tumor’s features, contralesional compensation may explain these differences. Therefore, studying changes in the contralateral hemisphere can provide insights into the underlying mechanisms of language function compensation in patients with gliomas. This study included 60 patients with eloquent-area or near-eloquent-area gliomas. The participants were grouped according to the degree of language defect. T1 and diffusion tensor imaging were obtained. The contralesional cortical volume and the subcortical network were compared between groups. Patients with unimpaired language function showed elevated cortical volume in the midline areas of the frontal and temporal lobes. In subcortical networks, the group also had the highest global efficiency and shortest global path length. Ten nodes had intergroup differences in nodal efficiency, among which four nodes were in the motor area and four nodes were in the language area. Linear correlation was observed between the efficiency of the two nodes and the patient’s language function score. Functional compensation in the contralesional hemisphere may alleviate language deficits in patients with gliomas. Structural compensation mainly occurs in the contralesional midline area in the frontal and temporal lobes, and manifests as an increase in cortical volume and subcortical network efficiency.
VoiceLab: Software for Fully Reproducible Automated Voice Analysis

There’s a problem with acoustic analyses because you often need to hand adjust parameters meaning you can only process them individually or in small batches. This creates two key problems. First, it compromises the reproducibility of measurements because setting parameters by hand requires specialist knowledge and is often poorly documented. Second, it means that you can’t easily process large samples of voices, which creates bottlenecks in workflows. This issue is compounded by researchers looking to use increasingly large and diverse samples. To address these issues, VoiceLab software offers automated acoustical analysis and automatically logs analysis parameters. VoiceLab analyses are fully reproducible and require little to no knowledge about acoustical analysis from the user. Analysis parameters can also be manually adjusted by experts. VoiceLab is used primarily by researchers studying person perception, creating reproducible voice manipulations, developing voices for conversational agents, and creating feature sets for machine learning.
uRLLC Shadowing Estimation in eMBB-uRLLC Multiplexing for Geospatially Correlated PPP Channel

This letter investigates eMBB-uRLLC multiplexing in which the eMBB users’ channel feedback is exploited for the uRLLC channel condition estimation. This approach allows instant and reliable transmission without acquiring the user’s CSI, which is especially advantageous in intermittent uRLLC traffic transmissions. This letter introduces two channel estimators for a geospatially-correlated channel and derives their estimation errors. Then, we propose an eMBB-uRLLC multiplexing algorithm based on the estimates and provide transmission reliability and spectral efficiency measures under adaptive modulation and coding. Simulation results confirm the effectiveness of the proposed approach in different propagation environments.
Effect of medieval farming activities on elemental composition of soils – case study of deserted village Regenholz (Czech Republic)

Regenholz is a deserted medieval village existing approximately between the 13th and 15th centuries. It originated in the colonisation period when the villages were usually founded in upland regions of Central Europe in the High Middle Ages. The study presents the results of a research based on geochemical and spatial analyses of one of the village’s field areas. The aim of the study was to reveal the spatial characteristics of the elemental composition of the previously ploughed soils which are now covered by forest. The analysed field area comprised bundles of 13 strip plots, which were approximately from 30 to 40 meters (up to 60 meters in two cases) wide and 300 meters long. The village and its fields were adjacent to the village Lovětín, which was analysed and published earlier. This made it possible to compare the geochemistry of the deserted fields of both villages with the same natural conditions and historical development. The soil samples were measured for elemental composition by portable XRF. The composition was dominated by elements generally interpreted as past human activity indicators: P, Zn, Mn, and Sr. Past human presence was represented mainly by Cu and partially by Mn content (P and Sr showed similar trends). The obtained results were compared with the data from the adjacent village Lovětín: the results were similar just by comparing the PCA data. The past human activity indicators reached less spatial diversity than those of natural factors.
CTFALite: Lightweight Channel-specific Temporal and Frequency Attention Mechanism for Enhancing the Speaker Embedding Extractor

Attention mechanism provides an effective and plug-and-play feature enhancement module for speaker embedding extractors. Attention-based pooling layers have been widely used to aggregate a sequence of frame-level feature vectors into an utterance-level speaker embedding. Besides, convolution attention mechanisms are introduced into convolution blocks to improve the sensibility of speaker embedding extractors to those features with more discriminative speaker characteristics. However, it is still a challenging problem to make a good trade off be-tween performance and model complexity for convolution attention models, especially for speaker recognition systems on low-resource edge computing nodes (smartphone, embedded devices, etc.). In this paper, we propose a lightweight convolution attention model named as CTFALite, which learns channel-specific temporal attention and frequency attention by leveraging both of the global context information and the local cross-channel dependencies. Experiment results demonstrate the effectiveness of CTFALite for improving performance. The further analysis about computational resource consumption shows that CTFALite achieves a better trade-off between performance and computational complexity, compared to other competing lightweight convolution attention mechanisms.
RefTextLAS: Reference Text Biased Listen, Attend, and Spell Model For Accurate Reading Evaluation

We present an automatic reading evaluator that listens to novice young readers and offers feedback based on the reading accuracy. In order to not discourage the reader, the model should not misrecognize correctly read tokens (false rejects), which may come at the expense of tolerating some reading mistakes (false accepts). To minimize the former, we explore two approaches to provide reference text – the text user is supposed to read – as context to automatic speech recognition (ASR) models: 1) a ﬁnite state transducer (FST) based error detection procedure, that restricts the grammar to tokens from reference text and an out of vocabulary (OOV) catch-all token, and 2) RefTextLAS, an attention-based end-to-end (E2E) ASR model, that takes tokens from reference text as an additional input. Our biasing approaches reduce false reject rate (FRR) by 38-56% on an in-house dataset compared to a baseline hybrid model, whose language model (LM) is trained on book texts, with 65-82% compromise on false accept rate (FAR). To reduce FAR, we present an ensemble approach that uses both baseline and RefTextLAS models to determine reading accuracy. The ensemble approach limits the relative degradation on FAR to 26.4% while providing a 42.7% improvement on FRR.
Effects of Traditional Chinese Exercises on Frailty, Quality of Life, and Physical Function on Frail and Pre-Frail Older People: A Systematic Review and Meta-Analysis

To explore the effects of traditional Chinese exercises (TCEs) on the frailty status, quality of life, and physical function of frail and pre-frail older adults. Eight databases were searched from inception to March 28, 2022. Methodological quality and heterogeneity were assessed. Mean difference (MD) or standardized MD (SMD) were pooled using random-effects or fixed-effects meta-analysis, depending on heterogeneity. A total of 12 articles were included. Results showed relieved frailty status of frail and pre-frail older adults (SMD = −1.46; 95% CI [−2.39, −0.53]; p < 0.01); quality of life improved (SMD = 0.91, 95% CI [0.19, 1.63]; p < 0.01); grip strength enhanced doing Badaunjin (MD = 2.51, 95% CI [1.09, 3.93]; p < 0.01), but no significant improvement with Taichi (MD = 0.10, 95% CI [−2.3,2.5]; p = 0.93); dynamic balance ability improved (MD = −2.57, 95% CI [−2.90, −2.25], p < 0.01); 4.5-m walking time shortened (MD = −0.95; 95% CI [−1.70, −0.20]; p < 0.001); gait speed improved (MD = 0.04; 95% CI [0.01, 0.07]; p = 0.003); lower body endurance increased (MD = 33.78; 95% CI [10.99, 56.68]; p = 0.004); Lower limb flexibility improved (SMD = −2.07; 95% CI [−2.94, −1.21]; p < 0.01). This study showed that TCEs may be helpful in alleviating frailty status and improving the quality of life and physical functions of frail and pre-frail older adults. Lastly, additional high-quality clinical trials are warranted despite the limited strong evidence.