Miracle-dz/UniFAR-FTUs huggingface dataset:
A High-Performance Day-Age Classification and Detection Model for Chick Based on Attention Encoder and Convolutional Neural Network

Simple Summary Most management methods for poultry farming currently rely on human labor. Such management is labor-intensive and inefficient, especially in identifying poultry growth stages. Given the lack of a high-precision artificial method for chick’s day-age detection, a high-performance day-age classification and detection model for chicks was proposed based on artificial intelligent techniques. This method can detect and classify chicks in six different living stages from 1 to 32 day-ages, and the accuracy is 95.2%, superior to other current ones. In order to apply this method in practical scenarios, it has been deployed into an application based on the IOS system, which can recoganize the day-age of chicks by capturing real-time photos. The system is currently deployed in Rizhao City, Shandong Province, China. It helps chicken farm staff automatically detect the behavior of chickens, whose excellent working effect proves the robust availibility of the proposed method. Abstract Thanks to the boom of computer vision techniques and artificial intelligence algorithms, it is more available to achieve artificial rearing for animals in real production scenarios. Improving the accuracy of chicken day-age detection is one of the instances, which is of great importance for chicken rearing. To solve this problem, we proposed an attention encoder structure to extract chicken image features, trying to improve the detection accuracy. To cope with the imbalance of the dataset, various data enhancement schemes such as Cutout, CutMix, and MixUp were proposed to verify the effectiveness of the proposed attention encoder. This paper put the structure into various mainstream CNN networks for comparison and multiple ablation experiments. The final experimental results show that by applying the attention encoder structure, ResNet-50 can improve the accuracy of chicken age detection to 95.2%. Finally, this paper also designed a complete image acquisition system for chicken houses and a detection application configured for mobile devices.
CNN-based Audio Event Recognition for Automated Violence Classification and Rating for Prime Video Content

Automated violence detection in Digital Entertainment Content (DEC) uses computer vision and natural language processing methods on visual and textual modalities. These methods face difﬁculty in detecting violence due to diversity, ambiguity and multilingual nature of data. Hence, we introduce a method based on audio to augment existing methods for violence and rating classiﬁcation. We develop a generic Audio Event Detector model (AED) using open-source and Prime Video proprietary corpora which is used as a feature extractor. Our feature set includes global semantic embedding and sparse local audio event probabilities extracted from AED. We demonstrate that a global-local feature view of audio results in best detection performance. Next, we present a multi-modal detector by fusing several learners across modalities. Our training and evaluation set is also at least an order of magnitude larger than previous literature. Furthermore, we show that, (a) audio based approach results in superior performance compared to other baselines, (b) beneﬁt due to audio model is more pronounced on global multi-lingual data compared to English data and (c) the multi-modal model results in 63% rating accuracy and provides the ability to back-ﬁll top 90% Stream Weighted Coverage titles in PV catalog with 88% coverage at 91% accuracy.
A Lightweight Authentication Scheme for a Network of Unmanned Aerial Vehicles (UAVs) by Using Physical Unclonable Functions

A network of agents constituted of multiple unmanned aerial vehicles (UAVs) is emerging as a promising technology with myriad applications in the military, public, and civil domains. UAVs’ power, memory, and size constraints, ultra-mobile nature, and non-trusted operational environments make them susceptible to various attacks, including physical capturing and cloning attacks. A robust and resilient security protocol should be lightweight and resource-efficient in addition to providing protection against physical and tampering threats. This paper proposes an authentication protocol for a UAV-based multi-agent system robust against various threats and adversaries, including strong resistance against cloning and physical attacks. The proposed protocol is based on a physical unclonable function (PUF), a well-known hardware security primitive that is utilized for low-cost authentication and cryptographic key generation. The analysis of the proposed approach shows that it provides strong protection against various attacks, including tampering and cloning, and exhibits scalability and energy efficiency.
Maternal Right Ventricular and Left Atrial Function in Uncomplicated Twin Pregnancies: A Longitudinal Study

Objective: The knowledge regarding maternal cardiovascular hemodynamic adaptation in twin pregnancies is incomplete. We performed a longitudinal investigation of maternal right ventricular (RV) and left atrial (LA) function in a cohort of uncomplicated twin pregnancies compared to singleton pregnancies. Study design: Healthy women with uncomplicated twin pregnancies were prospectively enrolled and assessed by transthoracic echocardiography at 10–15 weeks’ (w) gestation (T1), 19-26 w gestation (T2), and 30–38 w gestation (T3). Subjects with uneventful singleton pregnancies were selected as controls at the same gestational ages. Cardiac findings were compared to those of women with uneventful singleton gestations. RV systolic and diastolic functions were assessed by conventional echocardiography (FAC, TAPSE, sPAP, E, A, DT) and tissue Doppler imaging (TDI) (E’, A’, S’, IVA, IVCT, IVRT, ET, MPI), and LA dimensions were calculated. Speckle-tracking imaging was also applied to evaluate RV global longitudinal strain and LA 2D strains (at LV end-systole (LAS) and at atrial contraction (LAA)). Results: Overall, 30 uncomplicated twin and 30 uncomplicated singleton pregnancies were included. Regarding maternal RV function in twins, all the parameters (FAC, TAPSE, sPAP, E, A, E/A, DT, E/E’, IVA, IVCT, MPI and 2D longitudinal strain) were almost stable throughout gestation, with the exception of the TDI findings (E’ decreased from T1 to T3 (p = 0.03), while E’/A’ increased from T1 to T2 and then decreased (p = 0.01); A’ and basal S’ increased (p = 0.04 and p = 0.03, respectively), while IVRT and ET significantly decreased (p = 0.009 and p = 0.007, respectively)). These findings were similar to those found for singleton pregnancies. LA dimensions significantly increased throughout gestation in both twins and singletons (p < 0.001), without intergroup difference. LA strains did not vary during either twin or singleton pregnancies, except for LAA in T1, which was higher among twins than among singletons. Conclusion: Maternal RV and LA function in uncomplicated twin pregnancies does not seem to undergo more significant changes than in singletons, being characterized by similar findings in RV systolic and diastolic functions, as well as LA dimensions and strains.
Predicting VQVAE-based Character Acting Style from Quotation-Annotated Text for Audiobook Speech Synthesis

We propose a speech-synthesis model for predicting appropriate voice styles on the basis of the character-annotated text for audiobook speech synthesis. An audiobook is more engaging when the narrator makes distinctive voices depending on the story characters. Our goal is to produce such distinctive voices in the speech-synthesis framework. However, such distinction has not been extensively investigated in audiobook speech synthesis. To enable the speech-synthesis model to achieve distinctive voices depending on characters with minimum extra annotation, we propose a speech synthesis model to predict character appropriate voices from quotation-annotated text. Our proposed model involves character-acting-style extraction based on a vector quantized variational autoencoder, and style prediction from quotation-annotated texts which enables us to auto-mate audiobook creation with character-distinctive voices from quotation-annotated texts. To the best of our knowledge, this is the first attempt to model intra-speaker voice style depending on character acting for audiobook speech synthesis. We conducted subjective evaluations of our model, and the results indicate that the proposed model generated more distinctive character voices compared to models that do not use the explicit character-acting-style while maintaining the naturalness of synthetic speech.
A randomised controlled trial of high-flow nasal oxygen versus non-rebreathing oxygen face mask therapy in acute hypoxaemic respiratory failure

Background and Aims: A major limitation to providing oxygen therapy by high flow nasal oxygen (HFNO) delivery devices is its availability and therefore as an alternative many clinicians use a standard non rebreathing face mask (NRBM) in order to oxygenate their patients where low-flow nasal oxygen or simple facemask oxygen is not providing adequate respiratory support to achieve the target peripheral oxygen saturation (SpO2). We aimed to determine the clinical effectiveness of HFNO versus NRBM in terms of improving patient outcome among patients admitted to our intensive care unit (ICU) during coronavirus disease-2019 (COVID-19) outbreak. Methods: In this prospective open labelled study, 122 COVID-19 patients presenting with acute hypoxaemic respiratory failure (AHRF) were randomised to receive either HFNO or NRBM to achieve the target SpO2. The primary clinical outcome measured was device failure rate and secondary outcome was all-cause 28-day mortality rate. Results: The device failure rate was significantly higher in HFNO group (39% versus 21%, P = 0.030). Oxygen support with NRBM resulted in a reduced all mortality rate over HFNO (26.2% versus 45%) but the mortality rate after treatment failure in either group (HFNO or NRBM) remained high (91% versus 92%). Conclusion: Oxygen support with NRBM results in both reduced device failure rate and higher survival among patients of COVID-19 with AHRF.
Towards a generalization of Mumford’s Theorem

In this paper, we examine a theorem of Mumford, based on a technique of Severi, on the role of regular 2-forms in determining the "size" of the Chow group of 0-cycles on a smooth, complex, projective algebraic surface (cf [6]). L et X b e a smooth, complex projective algebraic variety of dim ension n, CH k (X) = C H (X ) = Chow group of algebraic cycles of dimension k (codim n — k) modulo rational equivalence, a n d Ak ( X ) = Iv E CHk (X)11) is algebraically equivalent to zero}. O n rational cohomology (of X) there is equipped an arithmetic filtration, fo r w h ich to quo te i n [2 ], " . embodies deep arithmetic properties of [the scheme] X " . O ur purpose is to apply Mumford's theorem to exhibit a connection between graded pieces o f th is filtration and the "size" of A 5 (X ) for k > O. According to the statement of the main theorem below, when k = 0, we arrive at the conclusion of Mumford's theorem for the case n = 2, and Roitman's generalization (see [8 ]) fo r n > 2, namely h ' ° (X) 0 0 fo r som e p > 2 implies A 0 (X) "infinite dimensional". We begin with the setting of this paper by recalling two filtrations (see also [2]). Fak (i)=Gysin images of Hi 2 4 (Y, Q) in H i (X, Q), where Y = desingularization o f T a n d w here T c X i s a subvariety o f codimension q > k; ( i ) = largest subHodge structure in {F i-I i (X, C)} fl 16X , Q ). There is the well known inclusion Fa (i) FL' (i), conjectured to be an equality ([Grothendieck amended] Hodge conjecture), and corresponding graded morphisms Tk ,i : Grak ( i ) = F ak(i)/Fak+1(i) n (i) /Fr(i) = G rti (i), w hich aga in translate to isom orphism s if one assum es th e Hodge conjecture to b e t r u e . N ow le t V b e a sm ooth projective variety, j : W c4 V a sm ooth hyperplane section, and recall the weak Lefschetz theorem, namely j*: H i ( W ) injective (resp. isom orphism ) for i = dim W (resp. i < dim W ). Let( j*) 1 b e the left inverse to j * (as introduced in [4]). Our main assumption is a standard conjecture of Lefschetz type: A (* ): ( j* ) is algebraic, i.e. induced by a n algebraic cycle with rational coeffi-
Derivation of the Hubble Redshift and the Metric in a Static Universe

This paper is the second of two papers on determining the dynamical state and metric of the universe. In the first paper, a new light curve broadening effect specific to type Ia supernovae was discovered which lead to the falsification of the expanding universe model. A static universe model was then confirmed by Tolman surface brightness tests of the brightest cluster galaxies.In this paper, a pure wave system is proposed as a basis for a new model of the universe. It is hypothesized that the constructive interference peaks of the wave modes are the mass particles. Furthermore, it is proved that the intensity of the wave modes varies as 1/r instead of the expected 1/r2. Consequently, the interactions of distant mass particles via the wave modes are the source of the energy for local mass particles and photons. The energy of these wave mode interactions and the classical gravitational potential energy then are identically the same.A “local” universe is studied first since it is simply a large sphere withi.
Modeling reduced field dependence of critical current density in YBa 2 Cu 3 O 6 + x films with nanorods

Flux pinning is still the main limiting factor for the critical current of the high-temperature superconductors in high fields. In this paper, we model the field dependence of the critical current in thin films with columnar defects aligned with the field. The characteristic shape of the critical current of the BaZrO${}_{3}$-doped YBa${}_{2}$Cu${}_{3}$O${}_{6+x}$ thin films is reproduced and explained. The model is based on solving the Ginzburg- Landau equations with columnar defects present in the lattice. The size of the columnar defect is found to be of key importance in explaining the rounded shape of the critical current of the BaZrO${}_{3}$-doped YBa${}_{2}$Cu${}_{3}$O${}_{6+x}$ thin films. It is also found that the size of the rod changes the long-range order of the vortex lattice.
Atrial Pacing Affects Left Atrial Morphological and Functional Parameters Early after Pacemaker Implantation

Background and Objectives: Chronic atrial stimulation might impair left atrial (LA) function. We aimed to assess the impact of atrial pacing burden on LA volumetric and functional parameters after implantation of a dual-chamber pacemaker. Materials and Methods: The prospective study included 121 subjects with sinus node disease (SND) or atrioventricular block (AVB) that received a dual-chamber pacemaker. After device implantation, the subjects were divided into three groups: (1) SND with a lower rate (LR) set to 60 bpm and rate response enabled; (2) AVB with an LR set to 60 bpm and no rate response; and (3) AVB with an LR set to 40 bpm and no rate response. Subjects were followed at one and three months. Two subsets of patients with high and low atrial pacing burdens accompanied by low ventricular pacing percentage were analyzed. LA function was evaluated with volumetric and strain parameters from transthoracic echocardiography. Results: The high atrial low ventricular pacing group consisted of 38 subjects, and the low atrial low ventricular group consisted of 22 subjects. When looking at the change in volumetric parameters, we observed a tendency for volumes to increase in both groups; however, only minimal LA volume reached statistical significance at three months in the high atrial pacing group. A trend towards the lowering of an active emptying fraction at one month (p = 0.076) became significant at three months (p = 0.043), and was also only observed in the same group. Moreover, a decrease in the tendency to reach statistical significance at three months for reservoir and contractile strain parameters and stiffness index was only observed in the high atrial pacing group. Meanwhile, in the low atrial pacing burden group, all parameters remained significantly unchanged. Conclusions: The burden of right atrial pacing in patients with preserved left ventricular function negatively influences functional and morphologic LA parameters. Moreover, negative effects take place soon after pacemaker implantation and appear to be sustained.
Low beta quadrupole fringing field on off-axis trajectory

DAφNE, the Frascati φ‐factory, is a twin ring e=e− collider. A discussion of nonlinear effects on the beams from fringing fields in the low‐beta quadrupoles is given. A multipolar expansion of the fringing field can be deduced from the longitudinal behavior of the beam‐beam interaction region (IR) quadrupole field gradients, and introduced in the IR optics description. (AIP)
On a Lagrangian formulation of the incompressible Euler equation

In this paper we show that the incompressible Euler equation on the Sobolev space $H^s(\R^n)$, $s > n/2+1$, can be expressed in Lagrangian coordinates as a geodesic equation on an infinite dimensional manifold. Moreover the Christoffel map describing the geodesic equation is real analytic. The dynamics in Lagrangian coordinates is described on the group of volume preserving diffeomorphisms, which is an analytic submanifold of the whole diffeomorphism group. Furthermore it is shown that a Sobolev class vector field integrates to a curve on the diffeomorphism group.
Speech2Slot: A Limited Generation Framework with Boundary Detection for Slot Filling from Speech

Slot filling is an essential component of Spoken Language Understanding. In contrast to conventional pipeline approaches, which extract slots from the ASR output, end-to-end approaches directly get slots from speech within a classification or generation framework. However, classification relies on predefined categories, which is not scalable, and the generative model is decoding in an open-domain space, suffering from blurred boundaries of slots in speech. To address the shortcomings of these two formulations, we propose a new encoder-decoder framework for slot filling, named Speech2Slot, leveraging a limited generation method with boundary detection. We also released a large-scale Chinese spoken slot filling dataset named Voice Navigation Dataset in Chinese (VNDC). Experiments on VNDC show that our model is markedly superior to other approaches, outperforming the state-of-the-art slot filling approach with 6.65% accuracy improvement. We make our code 1 publicly available for researchers to replicate and build on our work.
Self-regularised Minimum Latency Training for Streaming Transformer-based Speech Recognition

This paper proposes a self-regularised minimum latency training (SR-MLT) method for streaming Transformer-based automatic speech recognition (ASR) systems. In previous works, latency was optimised by truncating the online attention weights based on the hard alignments obtained from conventional ASR models, without taking into account the potential loss of ASR accuracy. On the contrary, here we present a strategy to obtain the alignments as a part of the model training without external supervision. The alignments produced by the proposed method are dynamically regularised on the training data, such that the latency reduction does not result in the loss of ASR accuracy. SR-MLT is applied as a fine-tuning step on the pre-trained Transformer models that are based on either monotonic chunkwise attention (MoChA) or cumulative attention (CA) algorithms for online decoding. ASR experiments on the AIShell-1 and Librispeech datasets show that when applied on a decent pre-trained MoChA or CA baseline model, SR-MLT can effectively reduce the latency with the relative gains ranging from 11.8% to 39.5%. Furthermore, we also demonstrate that under certain accuracy levels, the models trained with SR-MLT can achieve lower latency when compared to those supervised using external hard alignments.
Toward Corpus Size Requirements for Training and Evaluating Depression Risk Models Using Spoken Language

Mental health risk prediction is a growing field in the speech community, but many studies are based on small corpora. This study illustrates how variations in test and train set sizes impact performance in a controlled study. Using a corpus of over 65K labeled data points, results from a fully crossed design of different train/test size combinations are provided. Two model types are included: one based on language and the other on speech acoustics. Both use methods current in this domain. An age-mismatched test set was also included. Results show that (1) test sizes below 1K samples gave noisy results, even for larger training set sizes; (2) training set sizes of at least 2K were needed for stable results; (3) NLP and acoustic models behaved similarly with train/test size variations, and (4) the mismatched test set showed the same patterns as the matched test set. Additional factors are discussed, including label priors, model strength and pre-training, unique speakers, and data lengths. While no single study can specify exact size requirements, results demonstrate the need for appropriately sized train and test sets for future studies of mental health risk prediction from speech and language.
The Waxing, Waning, and Predictors of Humoral Responses to Vector-Based SARS-CoV-2 Vaccine in Hemodialysis Patients

Hemodialysis (HD) patients are vulnerable to coronavirus disease 2019 (COVID-19) and have a high mortality rate. We evaluated the anti-SARS-CoV-2 spike protein antibody (ACOV2S) levels in 385 HD patients before and 4 and 8 weeks after the second dose of vector-based ChAdOx1 nCoV-19 vaccine. For study control, week 4 ACOV2S levels after the second vaccination dose were measured in 66 healthcare workers (HCWs). The seroconversion rate of HD patients was 98.96% 4 weeks after the second vaccination. Despite low antibody levels before the second dose (week 0), week 4 ACOV2S levels after the second vaccine dose in HD patients increased prominently and were compatible with those in HCWs (p = 0.814 for HCWs vs. HD patients). The ACOV2S levels in HD patients waned significantly 8 weeks after the second vaccination dose (p < 0.001 at week 8 vs. 4). Older age and immunosuppressant use were negative predictors, while higher C-reactive protein (CRP) levels were positive predictors of ACOV2S waxing after the second vaccine dose in HD patients. Higher CRP levels and platelet counts were independently associated with decreased ACOV2S waning. The ChAdOx1 nCoV-19 vaccine is effective and safe for primary vaccination in HD patients and a booster dose is necessary.
The Relationship between Healthcare Experience and Perinatal Depression during COVID-19 Pandemic

Background: The prevalence of peripartum depression (PPD) has increased substantially since the start of the COVID-19 pandemic. To reduce the probability of contagion, hospitals had to adapt their care protocols, including the care of women in the perinatal period. Method: A cross-sectional study was used in a total sample of 3,356 women, 1,402 in the prenatal period and 1,954 in the postnatal period. They completed the Edinburgh Postnatal Depression Scale to assess depressive symptoms and the Spanish version of the Coronavirus Perinatal Experiences to assess health experience. Results: The results showed that feeling very well supported by a health professional was associated with a lower risk of PPD. On the other hand, believing it very important to have access to a mental health professional and being concerned about changes in infant care due to COVID-19 were associated with a higher risk of PPD. Conclusion: The results showed the relationship between health experience and the risk of depressive symptoms, highlighting the importance of considering the psychological aspects in the development of measures and protocols for perinatal care.