Miracle-dz/UniFAR-FTUs huggingface dataset:
Low-complexity Multi-Channel Speaker Extraction with Pure Speech Cues

Most multi-channel speaker extraction schemes use the target speaker’s location information as a reference, which must be known in advance or derived from visual cues. In addition, memory and computation costs are enormous when the model deals with the fusion input. In this paper, we propose Speaker-extraction-and-filter Network (SeafNet), which is a low-complexity multi-channel speaker extraction network with only speech cues. Specifically, the SeafNet separates the mixture by utilizing the correlation between an estimation of target speaker on reference channel and the mixed input on rest channels. Experimental results show that compared with the baseline, the SeafNet model achieves 6.4% relative SISNRi improvement on the fixed geometry array and 8.9% average relative SISNRi improvement on the ad-hoc array. Meanwhile, the SeafNet achieves 60% relative reduction in the number of parameters and 42% relative reduction in the computational cost.
Sentiment-Oriented Transformer-Based Variational Autoencoder Network for Live Video Commenting

Automatic live video commenting is getting increasing attention due to its significance in narration generation, topic explanation, etc. However, the diverse sentiment consideration of the generated comments is missing from current methods. Sentimental factors are critical in interactive commenting, and there has been lack of research so far. Thus, in this article, we propose a Sentiment-oriented Transformer-based Variational Autoencoder (So-TVAE) network, which consists of a sentiment-oriented diversity encoder module and a batch attention module, to achieve diverse video commenting with multiple sentiments and multiple semantics. Specifically, our sentiment-oriented diversity encoder elegantly combines a VAE and random mask mechanism to achieve semantic diversity under sentiment guidance, which is then fused with cross-modal features to generate live video comments. A batch attention module is also proposed in this article to alleviate the problem of missing sentimental samples, caused by the data imbalance that is common in live videos as the popularity of videos varies. Extensive experiments on Livebot and VideoIC datasets demonstrate that the proposed So-TVAE outperforms the state-of-the-art methods in terms of the quality and diversity of generated comments. Related code is available at https://github.com/fufy1024/So-TVAE.
KEPUTUSAN PAPUA NUGINI DALAM KERJASAMA BILATERAL PNG SOLUTION DENGAN AUSTRALIA

ABSTRACT This research analyzes the rationale of Papua New Guinea’ decision to collaborate with Australia in PNG Solution policy, that has drawn a considerable amount of critiques. This research adopted the qualitative method, and aimed at interpreting distinctive feature of PNG Solution based on emerging facts. In addition, the secondary data generated for this research is obtained from literature review as well as online research. Furthermore, this topic is selected based on the fact that Papua New Guinea withdrawal from its commitment to ‘seven reservations’, which is initially submitted by Papua New Guinea itself in order to ratify the 1951’s Refugee Convention. Thus, according to the result of this research, it is indicated that Papua New Guinea’ visions and missions in Alotau Accord 2012 is paralleled to the benefit gained from PNG Solution. Additionally, this particular decision also correspond with two concepts Rational Actor Model and National Interest, which has been adopted for this research, and therefore is a rational decision based on Rational Choice Theory. Keywords : asylum seeker, PNG Solution, Papua New Guinea, Australia, rational choice theory
Temperature Cycle Reliability Analysis of an FBAR Filter-Bonded Ceramic Package

On the background that the operating frequency of electronic devices tends to the radio frequency (RF) segment, a film bulk acoustic resonator (FBAR) filter is widely used in communication and military fields because of its advantages of high upper frequency, ample power capacity, small size, and low cost. However, the complex and harsh working environment puts higher requirements for packaging FBAR filters. Based on the Anand constitutive equation, the stress–strain response of the bonded ceramic package was studied by the finite element method for the FBAR filter-bonded ceramic package, and the thermal fatigue life of the device was predicted. We developed solder models with various spillage morphologies based on the random generation technique to examine the impact of spillage on device temperature reliability. The following are the primary conclusions: (1) Solder undergoes periodic deformation, stress, and strain changes throughout the cycle. (2) The corner of the contact surface between the chip and the solder layer has the largest stress at the end of the cycle, measuring 19.377 MPa. (3) The Engelmaier model predicts that the gadget will have a thermal fatigue life of 1928.67 h. (4) Expanding the layered solder area caused by any solder overflow mode may shorten the device’s thermal fatigue life. The thermal fatigue life of a completely spilled solder is higher than that of a partially spilled solder.
The origin of hummocks, western Arctic coast, Canada

Hummocks (nonsorted circles) are widely distributed in arctic and subarctic regions. The hummocks under discussion are composed of fine-grained frost-susceptible soils; the late summer frost table is bowl-shaped; and the hummocks grade from those which are completely vegetated (earth hummocks) to those with bare centres (mud hummocks). The mound form is usually attributed to an upward displacement of material resulting from cryostatic (freeze-back) pressure generated in a confined, wet, unfrozen pocket of the active layer. Theoretically, cryostatic pressure should not develop in a frost-susceptible hummock soil, because ice lensing at the top and (or) bottom of the active layer will desiccate the last unfrozen pocket so that the pore water is under tension, not pressure. Field observations carried out at Garry Island, Northwest Territories, for 1965–1979 and for 1967–1979 at Inuvik, Northwest Territories, involving: summer and winter excavations; the measurement of the deformation of tubes, soil pressure,.
Carbonate dissolution revealed by silt grain‐size distribution: comparison of Holocene and Last Glacial Maximum sediments from the pelagic South Atlantic

The current issue of global warming and the role of the ocean in global exchange of CO2 increases the interest in solid budgets of marine carbonate production and dissolution. The present study utilizes grain‐size composition of pelagic sediments in order to trace spatial and temporal variability of carbonate sedimentation in the South Atlantic for the Holocene and Last Glacial Maximum (LGM, 19–23 cal kyr BP). A decrease in grain size (e.g. sand content, mean grain size of coarse carbonate silt) indicates increased carbonate dissolution as a result of increased fragmentation of calcareous microfossils. The spatial grain‐size pattern suggests a threshold water depth below which a gradual grain‐size decrease becomes increasingly rapid. This water depth is considered as the sedimentary lysocline. For the Holocene time slice, a constant, gradual decrease of foraminifer carbonate of about 5–10% per 1000 m water depth above the lysocline gives evidence for supra‐lysoclinal dissolution. The water depth of the lysocline for the Holocene is tied to the interface of North Atlantic Deep Water and Antarctic Bottom Water (AABW) (ca 4100 m). Submarine ridges which restrict intrusion of AABW into the Angola Basin cause an asymmetry in carbonate preservation across the Mid‐Atlantic Ridge. The lysocline was reconstructed at ca 3100 m for the LGM. These data suggest that the ca 1000 m rise of the lysocline eradicated the Holocene east–west asymmetry.
Learning Degradation-Aware Deep Prior for Hyperspectral Image Reconstruction

Reconstructing the 3-D hyperspectral image (HSI) from 2-D snapshot measurements is a key task in spectral snapshot compressive imaging (SCI). Traditional model-based HSI reconstruction methods rely on hand-crafted priors. Recently, deep unfolding networks (DUNs) learn the priors using convolutional neural networks (CNNs) and have achieved satisfactory results. Most of the DUNs assume the degradations of SCI are known. However, due to the phase aberration and distortion problems in a real imaging process, there is a certain gap between the ideal and real degradation patterns, which may hinder the accurate HSI reconstruction. In this study, we propose a degradation-aware deep prior learning network (D2PL-Net), which tries to adaptively learn the practical degradation matrix during HSI reconstruction, and thus bridges the gap between the ideal and real degradations. Specifically, we first propose a joint variational compressive reconstruction model, and both the latent HSI and unknown degradation can be explicitly solved. By unfolding the solutions into a deep network, D2PL-Net is built, which mainly consists of two parts, degradation matrix learning (DML) mechanism and degradation-guided spectral–spatial transformer (DSST) in each stage. The former learns the degradation that approximates the real one; the latter represents the deep prior of latent HSI, and it could exploit the spectralwise and spatialwise long-range dependencies of HSI under the guidance of learned degradation, and then reconstruct the HSI. To ensure an effective training of D2PL-Net, we propose a joint loss function constraining the HSI reconstruction errors, degradation fidelity and degradation consistency. Experiments on simulated and real-life datasets show that the proposed method is competitive with the state-of-the-art methods.
Characterization of Rickets Type II Model Rats to Reveal Functions of Vitamin D and Vitamin D Receptor

Vitamin D has been known to exert a wide range of physiological effects, including calcemic, osteogenic, anticancer, and immune responses. We previously generated genetically modified (GM) rats and performed a comparative analysis of their physiological properties to elucidate the roles of vitamin D and vitamin D receptor (VDR). In this study, our primary goal was to investigate the manifestations of type II rickets in rats with the VDR(H301Q) mutation, analogous to the human VDR(H305Q). Additionally, we created a double-mutant rat with the VDR(R270L/H301Q) mutation, resulting in almost no affinity for 1,25-dihydroxy-vitamin D3 (1,25D3) or 25-hydroxy-vitamin D3 (25D3). Notably, the plasma calcium concentration in Vdr(R270L/H301Q) rats was significantly lower than in wild-type (WT) rats. Meanwhile, Vdr(H301Q) rats had calcium concentrations falling between those of Vdr(R270L/H301Q) and WT rats. GM rats exhibited markedly elevated plasma parathyroid hormone and 1,25D3 levels compared to those of WT rats. An analysis of bone mineral density in the cortical bone of the femur in both GM rats revealed significantly lower values than in WT rats. Conversely, the bone mineral density in the trabecular bone was notably higher, indicating abnormal bone formation. This abnormal bone formation was more pronounced in Vdr(R270L/H301Q) rats than in Vdr(H301Q) rats, highlighting the critical role of the VDR-dependent function of 1,25D3 in bone formation. In contrast, neither Vdr(H301Q) nor Vdr(R270L/H301Q) rats exhibited symptoms of alopecia or cyst formation in the skin, which were observed in the Vdr-KO rats. These findings strongly suggest that unliganded VDR is crucial for maintaining the hair cycle and normal skin. Our GM rats hold significant promise for comprehensive analyses of vitamin D and VDR functions in future research.
On-Device MFCC-CNN Voice Recognition System with ESP-32 and Web-Based Application

The ever-increasing need for intelligence applications capable of assisting human daily life has become a critical topic in current human everyday life. As the primary communication source, deep learning (DL) based speech recognition technique has spread in significant areas in education, transportation, and smart-home system. However, this technique has challenges as it requires numerous datasets and is difficult to implement on a low-cost and low-power system on a chip microcontroller, i.e., ESP-32 or Arduino. With its implementation in controlling the household device, a speech recognition system based on a convolutional neural network (CNN) and MFCC algorithm is proposed in this paper. Firstly, the audio datasets containing specified instructions (in Indonesian) are created, and their features are extracted using MFCC algorithms. Then, the CNN model trains the MFCC vector coefficients and saves them in the Hierarchical Data Format 5 File (h5). This CNN model is stored in the back-end part of the web application and accessed using Flask Python. The audio input (using. wav file format) is sent to the Flask using XMLHttpRequest (XHR) and processed to ESP-32 for controlling the devices. The simulation results, which contain six command words, showed that the selected model achieved 93 % accuracy and 28,39 ms response time.
Permian radiolarians from the Kosado area of Sado Island, central Japan

Late Permian (early Kuman) radiolarians are reported and depicted from Sado Island of Niigata Prefecture, central Japan, for the first time. The radiolarian fauna is obtained from mudstone. It is composed of Follicucullus charveti Caridroit et De Wever, FoUicucullus ventricosus Ormiston et Babcock, Entactinosphaera aff. Cimelia Nazarov et Ormiston, Entactinosphaera pseudocimelia Sashida et Tonishi, Hegleria mammilla (Sheng et Wang) and so on. A part of the pre-Tertiary rocks of Sado Island should be correlated to the Permian of the Ultra-Tanba Belt or Joetsu Belt, although they have previously been regarded as one of the Mesozoic accretionary complexes of the Ashio Belt.
Fuzzy Hilbert Spaces

we introduce the definition of afuzzy inner product space and discuss some properties of this space,and we use the definition of fuzzy inner product space to introduced anew definitions such that the definition of fuzzy Hilbert space ,Fuzzy convergence, ,Fuzzy complete,and we studied the relation between ordinary inner product space and fuzzy inner product space.
Particle dynamics, black hole shadow and weak gravitational lensing in the f (Q) theory of gravity

We study the particle dynamics around a black hole (BH) in f(Q) gravity. First, we investigate the influence of the parameters of f(Q) gravity on the horizon structure of the BH, photon orbits and the radius of the innermost stable circular orbit (ISCO) of massive particles. We further study the effects of the parameters of f(Q) gravity on the shadow cast by the BH. Moreover, we consider weak gravitational lensing using the general method, where we also explore the deflection angle of light rays around the BH in f(Q) gravity in uniform and nonuniform plasma mediums.
RESTORATION OF IRONSTONES OUTCROPS DEGRADED BY IRON MINNING ACTIVITY IN MINAS GERAIS STATE-BRAZIL 1

The properties of the soils and underlying substrates of "canga" (ironstones outcrops) in central Brazil have a number of restrictions for the establishment of plant species, and the high specialization of local vegetation contributes to a high rate of endemic adaptations. The close association between the mining of iron and the need for locally adapted vegetation presents a special condition of vulnerability. This study evaluated varied approaches to the restoration of "canga" fields considering technical and economic aspects related to the application of topsoil, re-introduction of plants from local sources and their regeneration. We set up a field experiment on one overburden pile of Capao Xavier iron mine (mined by the Vale Company), composed of eight treatments formed from combinations of two thicknesses of "canga" and associated salvaged soils (20 and 40 cm) and four levels of fertilization. In each plot, we planted the same number of seedlings following the same spatial arrangement. The evaluation of the treatments was made at 10 and 42 months after planting for survival of the planted species. There was no significant difference among the average survival of seedlings planted for the different thicknesses of substrate and fertilization levels. The development of programs for ecological restoration of ferruginous fields should therefore consider, among other factors, the complex soil x vegetation mosaic commonly found in natural settings and thus carry out the "canga" material soil reconstruction sequence in order to reproduce this scenario. Furthermore, in view of the possible reduction in the number of plant individuals over time, there must be a satisfactory amount of individual species selected for reintroduction.
Bilayer-Barrier Ferroelectric-HfO2 Tunnel Junction with High ON Current and Giant ON/OFF ratio Arising from Resonant Tunneling

The hafnium oxide (HfO<inf>2</inf>) based ferroelectric tunnel junction (FTJ) using ferroelectric-dielectric (FE-DE) bilayer-barrier structure is studied by physical modeling. The FTJ performance strongly depends on the barrier height of DE with respect to that of FE-HfO<inf>2</inf>. Compared with FE-HfO<inf>2</inf>/SiO<inf>2</inf> case, FE-HfO<inf>2</inf>/Ta<inf>2</inf>O<inf>5</inf> based FTJ shows high ON current (J<inf>ON</inf>) and giant ON/OFF ratio. The underlying physics is to introduce resonant tunneling (RT) by forming a quantum well and to shift resonance peak close to the Fermi level. The switching between the direct tunneling (DT) and RT under different polarization direction leads to an enhanced TER effect.
MÃ¡s AllÃ¡ de la Sensibilidad Materna: Modelo Predictivo de la Calidad del Apego

El estudio del apego de los bebÃ©s con sus madres es objeto de las ciencias mÃ©dicas y sociales, investigÃ¡ndose desde la actividad genÃ©tica hasta los efectos de la cultura. Como parte de la gran diversidad de estudios, una problemÃ¡tica de investigaciÃ³n fundamental es comprender si y cÃ³mo las conductas maternales influyen en el desarrollo de la calidad y tipo de apego del infante. En la actualidad, las propuestas han sido muy generales, no pudiÃ©ndose evidenciar modelos predictivos significativos. El presente estudio analiza si un modelo especÃ­fico de conductas maternales puede predecir la calidad y patrÃ³n de apego durante los primeros dos aÃ±os de vida del bebÃ©, controlando la salud mental de ambos, a travÃ©s de una metodologÃ­a microobservacional experimental. Se evaluÃ³ a 103 madres y sus infantes (de 15 a 20 meses) a travÃ©s de dos procedimientos de microobservaciÃ³n: situaciÃ³n extraÃ±a y AMBIANCE. Se utilizÃ³ un modelo de regresiÃ³n logÃ­stica multinomial para verificar el modelo propuesto. Los resultados indican que el comportamiento materno, relacionado con errores comunicacionales, podrÃ­an predecir tanto la calidad como el tipo de apego del infante, controlando la salud mental de la madre y el niÃ±o ya que en el 71,5% de los casos, los errores comunicativos explicarÃ­an la varianza del apego infantil desarrollado (r2 de Nagelkerke = 0,715); p < 0,001). Este modelo puede ser una avenida prometedora para la elaboraciÃ³n de programas preventivos en salud mental infantil. El presente estudio es el primero realizado en LatinoamÃ©rica bajo este tipo de metodologÃ­a microanalÃ­tica.
PARENT (cross-border Patient Registries Initiative)

U travnju 2011. godine Ministarstvo zdravlja dodijelilo je Hrvatskom zavodu za javno zdravstvo pripremu prijave DG SANCO/EAHC Joint Action projekta koji je kasnije u aplikacijskom procesu dobio skraceni naziv PARENT (cross-border Patient Registries Initiative). Slovenija je voditelj i koordinator projekta, a Hrvatska je među 11 pridruženih (associated) partnera, te je jos 12+ suradnih (collaborating) partnera (Slika 1) i 9+ pridruženih projekata (APG). Ispred Hrvatske HZJZ je nositelj cetvrtog od 6 radnih paketa (WP's) koji ima zadatak provesti snimku stanja registara u EU i tehnicki pokrenuti pilot Registra svih registara prema americkom modelu (AHRQ) za potrebe cijele Europske Unije. Ukupan iznos projekta je 3.360. 548,96 eura, a WP4 iznosi 569.929,08 eura (ili 16,95% od ukupnog iznosa), od cega EU financira 60% ili 341.957,45 eura. Hrvatska u troskovima projekta sudjeluje s 84.591. 00 € kroz rad zaposlenika i s 143.380,63 € kroz izravne financijske troskove. Nakon godinu dana po uspjesno provedenom postupku prijave projekta u kojem je tim vec u prvom krugu dobio, za ovakav tip projekta rekordnih 83 od 100 mogucih bodova. Ugovor s EAHC je konacno, 24. travnja 2012. godine i potpisan,a kick-off meeting je 12. i 13. svibnja. Opis projekta i njegovih komponenti dat je u PDF verziji clanka.
Compensating for Size Effect in Shear Wave Elastography Using Deep Neural Networks

In ultrasound shear wave elastography (USWE), the elasticity of a small lesion is underestimated due to the wave reflection inside the lesion. This paper proposes using a deep neural network to compensate for the size effect without explicit size information. The deep neural network corrects the underestimation of the elastic modulus. The dataset for the training process consists of 4000 images with lesions of random sizes and elastic moduli, obtained from the k-Wave MATLAB Toolbox. A mean absolute error (MAE) is calculated between the ground truth and the image generated by the generator network for 500 test datasets with the unitary elasticity background. The maximum value of MAE is 0.0082, indicating that the generator network generates images that are similar to the ground truth in size and modulus. When the unitary elasticity background is replaced by the image of the breast phantom, the neural network proves to be effective in size effect compensation.
OPTIMIZING MILK PRODUCTION, QUALITY AND SAFETY THROUGH ESSENTIAL OIL APPLICATIONS

This study comprehensively explores the integration of essential oils (EOs) into dairy livestock nutrition and milk production, focusing on optimising various facets of dairy farming. Food safety and biosecurity are paramount when introducing EOs into dairy farming practices. Rigorous safety assessments, including toxicity, allergenicity and potential adverse effects on animal health, are essential for the welfare of both livestock and consumers. Additionally, managing EO residues is challenging due to their potential impact on dairy product composition. Moreover, the variable effects of EOs on dairy animals` performance add complexity. While EOs show potential for inhibiting oxidative reactions and microbial spoilage, their influence on nutrient utilisation, ruminal fermentation and milk performance varies. Extensive research is required to optimise EO dosage and formulation for consistent performance benefits. Sustainability is a critical concern, requiring the alignment of EO utilisation with sustainable agricultural practices to address environmental and resource constraints. Lastly, consumer perception and acceptance are vital, necessitating transparent communication and an understanding of consumer preferences to maintain trust in dairy products. Addressing these challenges enables the dairy industry to harness the full potential of EOs, ensuring ongoing safety, quality and sustainability in dairy product production. This study provides practical insights and outlines future research directions to advance dairy production, quality and safety. Rezumat