Miracle-dz/UniFAR-FTUs huggingface dataset:
Steps towards end-to-end neural speaker diarization. (Étapes vers un système neuronal de bout en bout pour la tâche de segmentation et de regroupement en locuteurs)

Speaker diarization is the task of determining "who speaks when" in an audio stream that usually contains an unknown amount of speech from an unknown number of speakers. Speaker diarization systems are usually built as the combination of four main stages. First, non-speech regions such as silence, music, and noise are removed by Voice Activity Detection (VAD). Next, speech regions are split into speaker-homogeneous segments by Speaker Change Detection (SCD), later grouped according to the identity of the speaker thanks to unsupervised clustering approaches. Finally, speech turn boundaries and labels are (optionally) refined with a re-segmentation stage. In this thesis, we propose to address these four stages with neural network approaches. We first formulate both the initial segmentation (voice activity detection and speaker change detection) and the final re-segmentation as a set of sequence labeling problems and then address them with Bidirectional Long Short-Term Memory (Bi-LSTM) networks. In the speech turn clustering stage, we propose to use affinity propagation on top of neural speaker embeddings. Experiments on a broadcast TV dataset show that affinity propagation clustering is more suitable than hierarchical agglomerative clustering when applied to neural speaker embeddings. The LSTM-based segmentation and affinity propagation clustering are also combined and jointly optimized to form a speaker diarization pipeline. Compared to the pipeline with independently optimized modules, the new pipeline brings a significant improvement. In addition, we propose to improve the similarity matrix by bidirectional LSTM and then apply spectral clustering on top of the improved similarity matrix. The proposed system achieves state-of-the-art performance in the CALLHOME telephone conversation dataset. Finally, we formulate sequential clustering as a supervised sequence labeling task and address it with stacked RNNs. To better understand its behavior, the analysis is based on a proposed encoder-decoder architecture. Our proposed systems bring a significant improvement compared with traditional clustering methods on toy examples.
Gut Microbiota and Obesity: A Role for Probiotics

Nowadays, obesity is one of the most prevalent human health problems. Research from the last 30 years has clarified the role of the imbalance between energy intake and expenditure, unhealthy lifestyle, and genetic variability in the development of obesity. More recently, the composition and metabolic functions of gut microbiota have been proposed as being able to affect obesity development. Here, we will report the current knowledge on the definition, composition, and functions of intestinal microbiota. We have performed an extensive review of the literature, searching for the following keywords: metabolism, gut microbiota, dysbiosis, obesity. There is evidence for the association between gut bacteria and obesity both in infancy and in adults. There are several genetic, metabolic, and inflammatory pathophysiological mechanisms involved in the interplay between gut microbes and obesity. Microbial changes in the human gut can be considered a factor involved in obesity development in humans. The modulation of the bacterial strains in the digestive tract can help to reshape the metabolic profile in the human obese host as suggested by several data from animal and human studies. Thus, a deep revision of the evidence pertaining to the use probiotics, prebiotics, and antibiotics in obese patients is conceivable
New phenolics from Dianella ensifolia

Abstract Phytochemical investigation and chromatographic separation of extracts from the aerial parts of Dianella ensifolia (L.) DC. (synonym Dianella nemorosa Lam. Ex. Schiler f.) led to the isolation of 10 compounds, the structures of which were determined by HR-ESI-MS and 1 D- and 2 D-NMR spectroscopies, and by comparisons with published studies. Among the isolated compounds were three flavans, a biflavan, a biflavone, a tetralone, a naphthalen glycoside, an aromatic compound, and two steroids. Six of these were known chemicals, while three were identified as new compounds: 7-acetyl-4R,8-dihydroxy-6-methyl-1-tetralone, 2(S),2′,4′-dihydroxy-7-methoxyflavan, and diaensi-biflavan. 2(S),7,4’-dimethoxy flavan was obtained for the first time as a natural product. Graphical Abstract
Cancer patients with community-acquired pneumonia treated in intensive care have poorer outcomes associated with increased illness severity and septic shock at admission to intensive care: a retrospective cohort study

Patients with community-acquired pneumonia (CAP) and an underlying diagnosis of cancer have worse outcomes. However, the characteristics of cancer patients with CAP admitted to intensive care units (ICUs) are not well established. In a retrospective observational study, patients admitted to a London university hospital ICU between January 2006 and October 2011 with a primary diagnosis of CAP were included. Demographic, clinical, laboratory, and outcome data were collected from the ICU and hospital pathology databases. The analysis included 96 patients with CAP, 19 of whom had an existing diagnosis of cancer. Patients with cancer had a longer median time interval between hospital and ICU admission (1 vs 2 days, p = 0.049). On admission to ICU, there were no differences in white cell count, C-reactive protein, clotting, renal function, liver function, heart rate, temperature, systolic blood pressure or oxygenation index between patients with or without cancer. However, patients with cancer had significantly lower haemoglobin levels (median 8.6 vs 10.0 g/dl, p = 0.010) and lowest diastolic blood pressure (median 40 vs 50 mmHg, p = 0.026), and higher sodium levels (median 142 vs 139 mmol/l), p = 0.020), APACHE II (median 25 vs 20, p = 0.009), SAPS II (median 51 vs 43, p = 0.039) and SOFA (median 12 vs 9, p = 0.018) scores. There were no statistically significant differences in the proportion of patients receiving mechanical ventilation or renal support, the duration of mechanical ventilation or ICU or hospital length of stay. Patients with cancer were more likely to receive vasopressors (89.5% vs 63.6%, p = 0.030) and had increased ICU (68.4% vs 31.2%, p = 0.004) and hospital (78.9% vs 33.8%, p = 0.001) mortality. The limitations of this study are its relatively small sample size and those associated with the retrospective study design. In conclusion, cancer patients with CAP had an increased risk of death that was associated with increased illness severity and prevalence of septic shock at the time of ICU admission, suggesting there may be a delay in recognition for the need for intensive care support in these patients.
"I Think You'll Like It"

Understanding the roles of social factors in online purchase behavior has been a long standing research problem. The recently emerging social e-commerce platforms leverage the stimulated word-of-mouth effect to promote the sales of items, which offers a peek into the complex interplay between the social influence and online purchasing behavior. In this paper, we investigate this problem on a full-scale purchase behavior dataset from one of the leading social e-commerce platforms, Beidian. Specifically, we conduct a comparison study between the social e-commerce and conventional e-commerce that are both integrated in Beidian to examine how social factors affect user's purchase behavior. We reveal that social e-commerce leads to a 3.09~10.37 times higher purchase conversion rate compared with the conventional settings, which indicates users make purchase with significantly fewer item explorations. Then, we propose and validate four primary mechanisms that contribute to the efficient purchase conversion: better matching, social enrichment, social proof and price sensitivity. Moreover, we identify several behavioral indicators that are able to measure the effect of these mechanisms, based on which we design an accurate predictive model (AUC=0.7738) for user's purchase decision. These results combine to shed light on how to understand and model the purchase behavior in social e-commerce.
A Novel Method in Surface Water Quality Assessment Based on Improved Variable Fuzzy Set Pair Analysis

In the case of surface water pollution, it is important and necessary to accurately assess the level of contaminated water and ensure the safety of drinking water for people in disaster areas during floods. However, for the assessment of the strict requirements of drinking water, traditional assessment methods still have some limitations, such as low precision and rationality. In order to overcome these limitations, in the light of the theory of set pair analysis and variable fuzzy set, we propose an improved variable fuzzy set pair analysis method (IVFSPA), which combines the analysis framework of variable fuzzy set and set pair analysis, and has made some improvements to the fusion architecture. Firstly, we present a novel game theory comprehensive weighting method, in which the objective entropy method and the subjective analytic hierarchy process(AHP) method employed to obtain the reasonable weight. Then, based on the Nemerow index method, we improve the arithmetic form of “Pi” (Equation P) to replace the fuzzy comprehensive evaluation method. Furthermore, we design a double judgment mode of combining the principle of maximum membership degree with the positive and negative relationship between the standard value and the measured value, which can accurately judge the evaluation level of surface water quality. Finally, to validate and verify the effectiveness of the proposed method, experiments was conducted at the representative river collection sections of Nanking, China, employing water quality data of 14 sampling sections in their rivers in Nanking during the 2017 flood. In terms of performance metcrics of precision and rationality, based on the values of “TP”, “NH3-N”, “Pb”, “AS” and “KMnO4” of “Ch-lh section/Chuhe gate” are 0.415, 3.77, 0.07, 0.23 and 7.12, respectively, the level of Ch-lh section/Chuhe gate is that the IVFSPA is Class V and the rest are class IV. Results of experiments show that our IVFSPA method can achieve a good performance, compared with other traditional methods.
Computational simulations of TNF receptor oligomerization on plasma membrane

The interactions between tumor necrosis factors (TNFs) and their corresponding receptors (TNFRs) play a pivotal role in inflammatory responses. Upon ligand binding, TNFR receptors were found to form oligomers on cell surfaces. However, the underlying mechanism of oligomerization is not fully understood. In order to tackle this problem, molecular dynamics (MD) simulations have been applied to the complex between TNF receptor‐1 (TNFR1) and its ligand TNF‐α as a specific test system. The simulations on both all‐atom (AA) and coarse‐grained (CG) levels achieved the similar results that the extracellular domains of TNFR1 can undergo large fluctuations on plasma membrane, while the dynamics of TNFα‐TNFR1 complex is much more constrained. Using the CG model with the Martini force field, we are able to simulate the systems that contain multiple TNFα‐TNFR1 complexes with the timescale of microseconds. We found that complexes can aggregate into oligomers on the plasma membrane through the lateral interactions between receptors at the end of the CG simulations. We suggest that this spatial organization is essential to the efficiency of signal transduction for ligands that belong to the TNF superfamily. We further show that the aggregation of two complexes is initiated by the association between the N‐terminal domains of TNFR1 receptors. Interestingly, the cis‐interfaces between N‐terminal regions of two TNF receptors have been observed in the previous X‐ray crystallographic experiment. Therefore, we provide supportive evidence that cis‐interface is of functional importance in triggering the receptor oligomerization. Taken together, our study brings insights to understand the molecular mechanism of TNF signaling.
Screening yeast display libraries against magnetized yeast cell targets enables efficient isolation of membrane protein binders

When isolating binders from yeast displayed combinatorial libraries, a soluble, recombinantly expressed form of the target protein is typically utilized. As an alternative, we describe the use of target proteins displayed as surface fusions on magnetized yeast cells. In our strategy, the target protein is co-expressed on the yeast surface with an iron oxide binding protein; incubation of these yeast cells with iron oxide nanoparticles results in their magnetization. Subsequently, binder cells that interact with the magnetized target cells can be isolated using a magnet. Using a known binder-target pair with modest binding affinity (KD ~ 400 nM), we showed that a binder present at low frequency (1 in 105) could be enriched >100-fold, in a single round of screening, suggesting feasibility of screening combinatorial libraries. Subsequently, we screened yeast display libraries of Sso7d and nanobody variants against yeast displayed targets to isolate binders specific to the cytosolic domain of the mitochondrial membrane protein TOM22 (KD ~ 271-2009 nM) and the extracellular domain of the c-Kit receptor (KD ~ 131 to KD >2000 nM). Additional studies showed that the TOM22 binders identified using this approach could be used for the enrichment of mitochondria from cell lysates, thereby confirming binding to the native mitochondrial protein. The ease of expressing a membrane protein or a domain thereof as a yeast cell surface fusion – in contrast to recombinant soluble expression – makes the use of yeast-displayed targets particularly attractive. Therefore, we expect the use of magnetized yeast cell targets will enable efficient isolation of binders to membrane proteins.
Identifying the Cellular Interactome of Epstein-Barr Virus Lytic Regulator Zta Reveals Cellular Targets Contributing to Viral Replication

Epstein-Barr virus infects most people across the world and causes several kinds of cancer. Zta is an important viral protein that makes the virus replicate by binding to its DNA and turning on the expression of some genes. We used a sensitive, unbiased approach to isolate and identify viral and cellular proteins that physically interact with Zta. This revealed 39 viral and cellular proteins. We found that one protein, termed NFATc2, was already known to be important for a very early step in viral replication. We identify that once this step has occurred, Zta reduces the effectiveness of NFATc2, and we suggest that this is important to prevent cells from dying before viral replication is complete and the mature virus is released from the cells. ABSTRACT The human gammaherpesvirus Epstein-Barr virus (EBV) (human herpesvirus 4 [HHV4]) infects most adults and is an important contributor to the development of many types of lymphoid and epithelial cancers. Essential contributions of viral genes to viral replication are known, but the potential contributions of cell genes are less well delineated. A key player is the viral protein Zta (BZLF1, ZEBRA, or Z). This sequence-specific DNA-binding protein can disrupt EBV latency by driving the transcription of target genes and by interacting with the EBV lytic origin of replication. Here, we used an unbiased proteomics approach to identify the Zta-interactome in cells derived from Burkitt’s lymphoma. Isolating Zta and associated proteins from Burkitt’s lymphoma cells undergoing EBV replication, followed by tandem mass tag (TMT) mass spectrometry, resulted in the identification of 39 viral and cellular proteins within the Zta interactome. An association of Zta with the cellular protein NFATc2 was validated in independent experiments. Furthermore, the ability of Zta to attenuate the activity of an NFAT-dependent promoter was shown, which suggests a functional consequence for the association. The expression of Zta is itself regulated through NFAT activity, suggesting that Zta may contribute to a feedback loop that would limit its own expression, thus aiding viral replication by preventing the known toxic effects of Zta overexpression. IMPORTANCE Epstein-Barr virus infects most people across the world and causes several kinds of cancer. Zta is an important viral protein that makes the virus replicate by binding to its DNA and turning on the expression of some genes. We used a sensitive, unbiased approach to isolate and identify viral and cellular proteins that physically interact with Zta. This revealed 39 viral and cellular proteins. We found that one protein, termed NFATc2, was already known to be important for a very early step in viral replication. We identify that once this step has occurred, Zta reduces the effectiveness of NFATc2, and we suggest that this is important to prevent cells from dying before viral replication is complete and the mature virus is released from the cells.
Evidence for host effect on the intestinal microbiota of whitefish (Coregonus sp.) species pairs and their hybrids

Abstract Investigating relationships between microbiota and their host is essential toward a full understanding of how animal adapt to their environment. Lake Whitefish offers a powerful system to investigate processes of adaptive divergence where the dwarf, limnetic species evolved repeatedly from the normal, benthic species. We compared the transient intestinal microbiota between both species from the wild and in controlled conditions, including their reciprocal hybrids. We sequenced the 16s rRNA gene V3‐V4 regions to (a) test for parallelism in the transient intestinal microbiota among sympatric pairs, (b) test for transient intestinal microbiota differences among dwarf, normal, and hybrids reared under identical conditions, and (c) compare intestinal microbiota between wild and captive whitefish. A significant host effect on microbiota taxonomic composition was observed when all lakes were analyzed together and in three of the five species pairs. In captive whitefish, host effect was also significant. Microbiota of both reciprocal hybrids fell outside of that observed in the parental forms. Six genera formed a bacterial core which was present in captive and wild whitefish, suggesting a horizontal microbiota transmission. Altogether, our results complex interactions among the host, the microbiota, and the environment, and we propose that these interactions define three distinct evolutionary paths of the intestinal microbiota.
Emerging practices supporting diabetes self-management among food insecure adults and families: A scoping review

Background Food insecurity undermines a patient’s ability to follow diabetes self-management recommendations. Care providers need strategies to direct their support of diabetes management among food insecure patients and families. Objective To identify what emerging practices health care providers can relay to patients or operationalize to best support diabetes self-management among food insecure adults and families. Eligibility criteria Food insecure populations with diabetes (type 1, type 2, prediabetes, gestational diabetes) and provided diabetes management practices specifically for food insecure populations. Only studies in English were considered. In total, 21 articles were reviewed. Sources of evidence Seven databases: Cumulative Index of Nursing and Allied Health Literature, Cochrane Database of Systematic Reviews, Medline, ProQuest Nursing & Allied Health Database, PsychInfo, Scopus, and Web of Science. Results Emerging practices identified through this review include screening for food insecurity as a first step, followed by tailoring nutrition counseling, preventing hypoglycemia through managing medications, referring patients to professional and community resources, building supportive care provider-patient relationships, developing constructive coping strategies, and decreasing tobacco smoking. Conclusion Emerging practices identified in our review include screening for food insecurity, nutrition counselling, tailoring management plans through medication adjustments, referring to local resources, improving care provider–patient relationship, promoting healthy coping strategies, and decreasing tobacco use. These strategies can help care providers better support food insecure populations with diabetes. However, some strategies require further evaluation to enhance understanding of their benefits, particularly in food insecure individuals with gestational and prediabetes, as no studies were identified in these populations. A major limitation of this review is the lack of global representation considering no studies outside of North America satisfied our inclusion criteria, due in part to the English language restriction.
Optimized Power Allocation for Secure Transmission Using Polar Code and Artificial Noise

In this paper, we present a secure transmission scheme to improve the secrecy capacity of wiretap systems by blending the benefits of polar code and artificial noise (AN). In the considered system, a transmitter tries to communicate with a receiver without leaking any confidential information to an eavesdropper. We propose a new system utility function, referred to as message secrecy capacity (MSC), which is obtained by integrating the code rate of polar code into the conventional secrecy capacity. Then, in order to maximize the secrecy capacity of the information bits in polar code, we formulate a max-min optimization problem to optimize the powers allocated among useful signals and the AN. To address the highly non-convexity of the considered problem, we propose a concave-convex procedure (CCCP)-based algorithm by introducing some carefully designed auxiliary variables, and convergence to the set of KarushKuhn-Tucker (KKT) solutions is guaranteed. Numerical results demonstrate the effectiveness of the proposed MSC objective function and power allocation scheme.
Longitudinal Effects of Excessive Smartphone Use on Stress and Loneliness: The Moderating Role of Self-Disclosure

The present study investigates how excessive smartphone use predicts users' stress and loneliness while taking the moderating role of online self-disclosure into account. We conducted a two-wave panel survey with a quota sample of smartphone users (n = 461 at time 2 [T2]). We found no direct effects of excessive smartphone use on stress or loneliness. However, our results showed that online self-disclosure moderates the postulated relationships. That is, excessive smartphone use (time 1 [T1]) predicts increased stress (T2), for those smartphone users who do engage in little online self-disclosure. However, for those who communicate their feelings, anxieties, and problems online, excessive smartphone use (T1) can even reduce loneliness (T2) and relieve stress (T2).