Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributionally robust zero-sum games

We consider a two player zero-sum game with stochastic linear constraints. The probability distributions of the vectors associated with the constraints are partially known. The available information with respect to the distribution is based mainly on the two first moments. In this vein, we formulate the stochastic linear constraints as distributionally robust chance constraints. We consider three different types of moments based uncertainty sets. For each uncertainty set, we show that there exists a saddle point equilibrium of the game. The latter corresponds to the optimal solution of a primal-dual pair of second order cone programs. In order to illustrate our theoretical results, we consider an instance of a zero-sum game together with distributionally robust chance constraints. A comparison with expected value constraints zero-sum game is drawn to illustrate the effectiveness of our approach.
Active learning fosters financial behavior: Evidence from rural Uganda

We conduct a randomized field experiment to study the effects of two financial education interventions offered to small-scale retailers in Western Uganda. The treatments contrast “active learning” with “traditional lecturing” within standardized lesson-plans. We find that active learning has a clear positive impact on savings and investment outcomes, but weaker effects on financial literacy and debt-related outcomes, in contrast to precisely estimated insignificant impacts of lecturing. The active learning intervention is superior as it works via three mechanisms, i.e. increased financial literacy, self-control, and financial confidence, while lecturing only affects financial confidence. JEL-Classification: O16 (savings), D14 (personal finance), I21 (analysis of education)
Management Concentric Collapse of Velopharynx in Obstructive Sleep Apnoea Using a Modified Barbed Palato-Pharyngoplasty Technique

Background: Multilevel surgical techniques are important in the treatment of obstructive sleep apnoea especially when the patient is non-compliant to Continuous Positive Airway Pressure therapy (CPAP). A modified pharyngoplasty technique is described in OSA patients where the major cause of upper airway obstruction was due to concentric collapse of velopharynx. Methods: Twenty four patients with evidence of OSA on polysomnography were included. In all patients the major cause of obstruction was due to concentric collapse of velopharynx as evidenced on Muller Maneuver (MM) and Drug Induced Sleep Endoscopy (DISE). All had non-adherence to (CPAP) therapy and underwent Barbed Palato Pharyngoplasty (BPP) for correction of concentric collapse of velum. Apnoea-Hypopnoea Index (AHI), Lowest Oxygen Saturation (L-sat), Epworth Sleepiness Score (ESS), Visual Analog Score (VAS) for snoring were assessed both pre-operatively and six months post-operatively. All patients underwent awake flexible nasopharyngoscopy with MM to assess the site and score the severity of obstruction before and six months after surgery. Results: Post-operative flexible nasopharyngoscopy with Muller Maneuver revealed absence of collapse of velum in eleven patients, 25% collapse in 10 and 50% collapse in 3 patients. Post-operatively, significant reduction of mean values were observed in AHI, ESS, VAS for snoring from 32.04 to 15.27, 12.75 to 4.54 and from 7.17 to 2.54 respectively. The mean L-sat improved from 74.44 to 86.04. There were no major surgical complications. Conclusion: BPP is a minimally invasive knotless technique and is best suited in OSA, where the major obstruction is due to concentric collapse of the velum.
A Novel Adversarial Training Scheme for Deep Neural Network based Speech Enhancement

In this work, we propose a novel representationlearning technique for Deep Learning-based Speech Enhancement algorithms inspired by Domain-Adversarial training. A gradient reversal layer and an additional network are employed, only at training time, to explicitly enforce a representation that is orthogonal to the additive noise in the input signal. We show that such learning scheme, which can be applied easily to most mask-based Deep Neural Network Speech Enhancement approaches, is able to improve the denoising performance when used in conjunction with scale-invariant signal-to-distortion ratio loss and allows to reach state-of-the-art performance with no computational overhead at run-time. In particular, on the commonly used VoiceBank-DEMAND benchmarking dataset, we improve signal-to-distortion ratio and signal-to-noise ratio over the nonadversarial model and CSIG, COVL and CBAK over other, state-of-the art, adversarial training techniques.
Recent Progress in Tropical Cyclone Intensity Forecasting at the National Hurricane Center

It has been well documented that the National Hurricane Center (NHC) has made significant improvements in Atlantic basin tropical cyclone (TC) track forecasting during the past half century. In contrast, NHC’s TC intensity forecast errors changed little from the 1970s to the early 2000s. Recently, however, there has been a notable decrease in TC intensity forecast error and an increase in intensity forecast skill. This study documents these trends and discusses the advancements in TC intensity guidance that have led to the improvements in NHC’s intensity forecasts in the Atlantic basin. We conclude with a brief projection of future capabilities.
Deep Embedding for Relation Extraction on Insufficient Labelled Data

Many recently proposed relation extraction methods are based on distantly supervised learning. They use data from existing knowledge bases as training data. Although the methods solve the problem of insufficient labelled data and are highly scalable, they suffer from a large amount of incorrectly labelled data. Instead of using these distantly supervised approaches, this paper proposes an alternative relation extraction method. It firstly performs unsupervised learning to train relation embeddings by a neural network. As the relation embeddings encode the semantic information of the original sentences and their entity pairs, these embeddings can be efficiently classified by supervised learning. Since the relation embedding phase is based on unsupervised learning, labelled data is only required in the classification phase. Experiments show that our proposed approach significantly outperforms the state-of-the-art baselines when labelled training data is insufficient.
OBSERVATIONS ON THE FISHERIES OF THREADFIN BREAMS (NEMIPTERIDAE) AND ON THE BIOLOGY OF NEMIPTERUS lAPONICUS (BLOCK) FROM KAKINADA

Of the four species of threadfin breamf occurring, N. japonicus is the most dominant at Kakinada. Peak landings are obtained during first and last quarters. There is significant difference in length-weight relationship of males and females. Peak values of Relative condition factor are associated with accumulation of fat. This species is a fractional spawner releasing the ripe ova in two batches during a protracted spawning season: August-April. The length at first maturity is esti- , mated as 125 mm in females. The estimated fecundity ranges from 23049 to 139160 in fishes of 134-199 mm length; in this length range, there is linear relationship between length and fecundity and between weight and fecundity. Generally males outnumber females and attain larger length. N. japonicus attains 185 mm, 255 oun and 285 mm at the completion of the first, second and third years, respectively, at Kakinada. The various growth parameters are estimated as: L a " 314 mm, K « 0.75142 and t,, = -0.17309 years
Optimising efficacy of antibiotics against systemic infection by varying dosage quantities and times

Mass production and use of antibiotics has led to the rise of resistant bacteria, a problem possibly exacerbated by inappropriate and non-optimal application. Antibiotic treatment often follows fixed-dose regimens, with a standard dose of antibiotic administered equally spaced in time. But are such fixed-dose regimens optimal or can alternative regimens be designed to increase efficacy? Yet, few mathematical models have aimed to identify optimal treatments based on biological data of infections inside a living host. In addition, assumptions to make the mathematical models analytically tractable limit the search space of possible treatment regimens (e.g. to fixed-dose treatments). Here, we aimed to address these limitations by using experiments in a Galleria mellonella (insect) model of bacterial infection to create a fully parametrised mathematical model of a systemic Vibrio infection. We successfully validated this model with biological experiments, including treatments unseen by the mathematical model. Then, by applying artificial intelligence, this model was used to determine optimal antibiotic dosage regimens to treat the host to maximise survival while minimising total antibiotic used. As expected, host survival increased as total quantity of antibiotic applied during the course of treatment increased. However, many of the optimal regimens tended to follow a large initial ‘loading’ dose followed by doses of incremental reductions in antibiotic quantity (dose ‘tapering’). Moreover, application of the entire antibiotic in a single dose at the start of treatment was never optimal, except when the total quantity of antibiotic was very low. Importantly, the range of optimal regimens identified was broad enough to allow the antibiotic prescriber to choose a regimen based on additional criteria or preferences. Our findings demonstrate the utility of an insect host to model antibiotic therapies in vivo and the approach lays a foundation for future regimen optimisation for patient and societal benefits.
Development of a qualitative real-time RT-PCR assay for the detection of SARS-CoV-2: A guide and case study in setting up an emergency-use, laboratory-developed molecular assay

Developing and deploying new diagnostic tests is difficult, but the need to do so in response to a rapidly emerging pandemic such as COVID-19 is crucially important for an effective response. In the early stages of a pandemic, laboratories play a key role in helping health care providers and public health authorities detect active infection, a task most commonly achieved using nucleic acid-based assays. While the landscape of diagnostics is rapidly evolving, polymerase chain reaction (PCR) remains the gold-standard of nucleic acid-based diagnostic assays, in part due to its reliability, flexibility, and wide deployment. To address a critical local shortage of testing capacity persisting during the COVID-19 outbreak, our hospital set up a molecular based laboratory developed test (LDT) to accurately and safely diagnose SARS-CoV-2. We describe here the process of developing an emergency-use LDT, in the hope that our experience will be useful to other laboratories in future outbreaks and will help to lower barriers to fast and accurate diagnostic testing in crisis conditions.
Antibiotic Resistance in Escherichia coli from Broiler Chickens After Amoxicillin Treatment in an Experimental Environment

Groupwise antibiotic treatments are common in broiler chicken production. They induce selection for antibiotic resistance in commensal Escherichia coli. This study aimed to investigate antibiotic resistance after individual (I, drenching) or groupwise treatment (G, by water) with amoxicillin, and after contact with I or G (KI or KG), compared with untreated broilers without contact with treated broilers (C), and pretreatment values. Finally, we compared antibiotic resistance from broilers (G) after a second treatment, with a treatment in the contact animals (KG), and a first treatment in the control animals (C). Resistance to ampicillin and other antibiotics was significantly increased in groups G and I within 2 days, suggesting (co-)selection of resistance. The increase was lower in groups KI, KG, and C during the first treatment (days 1–5). The increased resistance in group C was interpreted as a change in the microbiota after initial moving and first feeding. After treatment, resistance rates decreased to initial or lower values in all groups. During the second treatment period (days 34–38), all three groups' (G, KG, and C) resistance levels increased to equally high levels. Cephalosporin resistance was low, and did not change over the experimental period. On days 3 and 38, resistance rates of E. coli from duodenum, jejunum, and cecum did not differ between segments and treatment routes. Overall, the baseline levels of antibiotic resistance in E. coli were high. Amoxicillin triggered an increase in resistance levels, irrespective of the mode of treatment. Substantial resistance dynamics in untreated controls warrant further investigation.
Prophylactical Low Dose Whole-Liver Irradiation Inhibited Colorectal Liver Metastasis by Regulating Hepatic Niche in Mice

Background The liver is the most common target for metastatic colorectal cancer. Changes of the local hepatic niche due to hepatic diseases such as cirrhosis decrease the incidence of colorectal cancer liver metastasis. Hepatic niche heterogeneity could influence the risk of hepatic metastasis. Materials and Methods We simulated changes of the hepatic niche via prophylactical liver irradiation with a safe dose of 6 Gy. GEO dataset and GO analysis revealed a difference in the expression of matrix metalloproteinase 1 (MMP1) in primary colorectal cancer versus liver metastasis, as well as synchronous versus metachronous liver metastasis. Western blotting, Immunofluorescence and qRT-PCR were conducted to measure protein expressions, location and RNA expressions. Colony formation, wound-healing, transwell assays experiments were performed to determine the malignant biological properties of colorectal cancer cells. shRNA transfection was used to conduct stable transfected cell lines. Results Tissue inhibitor of metalloproteinases 1 (TIMP1) expression was significantly higher in metastases lesions than primary tumors. In vivo, TIMP1 expression in the hepatic niche increased after a safe dose of 6 Gy irradiation, along with MMP1 decreased, leading to collagen fiber deposition and impairment of hepatic microcirculation. In vitro, irradiated hepatic stellate cells-conditioned media reduced the migration and clone formation ability of colon cancer cells SW480 and HCT116. Low TIMP1 expression in hepatic stellate cells reduced tumor cell invasion and migration. Conclusion Prophylactical 6 Gy whole-liver irradiation could inhibit colorectal cancer liver metastasis by regulating TIMP1/MMP1 balance in the hepatic niche before liver metastatic lesion formed.
Effect of Addition of Polyaniline on Polyethylene Oxide and Polyvinyl Alcohol for the Fabrication of Nanorods

For the first time, the fabrication of novel nanorods by the addition of polyaniline (PANI) to polyethylene oxide (PEO) and polyvinyl alcohol (PVA) polymers through electrospinning method is investigated. Field emission scanning electron microscopy observations reveal the formation of nanofibers and nanorods having diameters in the range of 26.87–139.90 nm and 64.11–122.40 nm, respectively, and lengths in the range of 542.10 nm to 1.32 μm. Photoluminescence (PL) analysis shows the presence of peaks which are characteristic of isotactic polymers (363–412, 529–691 nm), 412–529 nm for PVA/PEO and 363–691 nm for PVA/PEO/PANI. PL spectra also show peak bonding at a wavelength of 552 nm. Manufacture of nanorods by electrospinning method gives better options for controlling the diameter and length of nanorods.
Poly (I:C)- and doxorubicin-loaded magnetic dendrimeric nanoparticles affect the apoptosis-related gene expressions in MCF-7 cells

Use of nanoparticles as drug carrier vectors has great potential to circumvent the limitations associated with chemotherapy, including drug resistance and destructive side effects. For this purpose, magnetic generation 4 dendrimeric nanoparticles were prepared to carry chemotherapeutic agent doxorubicin (G4-DOX) and immune modulator polyinosinic:polycytidylic acid [Poly(I:C)]. As previously reported, DOX and Poly(I:C) was loaded onto G4 nanoparticles (PIC-G4-DOX). Cellular internalization study using confocal microscopy demonstrated high levels of cellular internalization of PIC-G4-DOX nanoparticles by MCF-7 cells. This resulted in higher efficacy of PIC-G4-DOX nanoparticles in killing MCF-7 breast cancer cells. Alteration in the expression levels of selected genes was determined by RT-qPCR analyses. Proapoptotic NOXA, PUMA, and BAX genes were upregulated, and SURVIVIN, APOLLON, and BCL-2 genes were downregulated, indicating the cell-killing effectiveness of PIC-G4-DOX nanoparticles. Gene expression analysis provided some insights into the possible molecular mechanisms on cytotoxicity of DOX and Poly(I:C) delivered through G4 magnetic nanoparticles. The results demonstrated that PIC-G4-DOX can be useful for targeted delivery affecting apoptotic pathways, resulting in an advanced degree of cancer-cell–killing. They are promising for targeting cancer-cells because of their stability, biocompatibility, higher internalization, and toxicity.
Specific immune landscapes and immune checkpoint expressions in histotypes and molecular subtypes of sarcoma

ABSTRACT Soft tissue sarcomas are a group of rare and aggressive connective tissue neoplasms for which curative therapeutic opportunities are limited in advanced phase. Clinical trials assessing immunotherapy in these tumors have so far reported limited efficacy. The objective of this study is to provide a description of the immunologic landscape of sarcomas to guide the next clinical trials of immunotherapy in these diseases. The gene expression profile of 93 immune checkpoint (ICP) and membrane markers (MM) of immune cells was analyzed in a series of 253 soft tissue sarcoma (synovial sarcoma, myxoid liposarcoma, sarcoma with complex genomic and GIST) using Agilent Whole Human Genome Microarrays. The unsupervised hierarchical clustering of gene expression level was found able to properly group patients according to the histological subgroup of sarcoma, indicating that each sarcoma subgroup is associated with a specific immune signature defined by its gene expression pattern. Using the prognostic impact of CIBERSORT signature on metastatic-free survival in each subgroup, specific target could be proposed for each of the four groups: Treg through ICOS and GITR in GIST, M0 macrophages in all four sarcoma subtypes, OX40 in SS, CD40 in GIST and SS. The immune landscape of sarcoma was found to be as heterogeneous as the histotypes and molecular subtypes, but strongly correlated to the histotype. Histotype adapted immunotherapeutic approaches in each sarcoma subtypes must be considered in view of these results, consistently with the already reported specific response of histotypes of ICPs.
A wide field-of-view, modular, high-density diffuse optical tomography system for minimally constrained three-dimensional functional neuroimaging

The ability to produce high-quality images of human brain function in any environment and during unconstrained movement of the subject has long been a goal of neuroimaging research. Diffuse optical tomography, which uses the intensity of back-scattered near-infrared light from multiple source-detector pairs to image changes in haemoglobin concentrations in the brain, is uniquely placed to achieve this goal. Here, we describe a new generation of modular, fibre-less, high-density diffuse optical tomography technology that provides exceptional sensitivity, a large dynamic range, a field-of-view sufficient to cover approximately one-third of the adult scalp, and also incorporates dedicated motion sensing into each module. Using in-vivo measures, we demonstrate a noise-equivalent power of 318 fW, and an effective dynamic range of 142 dB. We describe the application of this system to a novel somatomotor neuroimaging paradigm that involves subjects walking and texting on a smartphone. Our results demonstrate that wearable high-density diffuse optical tomography permits three-dimensional imaging of the human brain function during overt movement of the subject; images of somatomotor cortical activation can be obtained while subjects move in a relatively unconstrained manner, and these images are in good agreement with those obtained while the subjects remain stationary. The scalable nature of the technology we described here paves the way for the routine acquisition of high-quality, three-dimensional, whole-cortex diffuse optical tomography images of cerebral haemodynamics, both inside and outside of the laboratory environment, which has profound implications for neuroscience.
Intratumoral CCR5+ neutrophils identify immunogenic subtype muscle-invasive bladder cancer with favorable prognosis and therapeutic responses

ABSTRACT Our previous studies revealed tumor-infiltrating neutrophils (TINs) played dichotomous roles in different cancers, indicating diverse TINs subtypes might orchestrate anti-tumor immunity or immune evasion, respectively. This study aimed to investigate the clinical significance and immune characteristics of CCR5+TINs in muscle-invasive bladder cancer (MIBC). Two hundred and fifty-seven MIBC patients from two clinical centers and 95 fresh MIBC samples were included. CCR5+TINs were stained by immunohistochemistry, and the relationship between patients’ clinic-pathological features and prognosis was evaluated, respectively. Immunohistochemistry and flow cytometry were applied to assess the immune features of CCR5+TINs and their correlations with other immune cells. In vitro study was conducted to estimate immune characteristics of CCR5+TINs and their predictive potential for pembrolizumab therapeutic response. In the two MIBC cohorts, we found that high CCR5+TINs infiltration could predict better overall survival (OS, P= .032, 0.039) and recurrence-free survival (RFS, P= .001, 0.006) and be associated with survival benefit from adjuvant chemotherapy (ACT, P< .001 for OS and P= .022 for RFS, respectively) in merely pT2N0 MIBC. Maraviroc could partly reduce IFN-γ secretion by CCR5+TINs (P< .001). CCR5+TINs correlated with higher expression of effector molecules within CD8+T cells. Notably, pembrolizumab treatment could only elevate the apoptosis status of tumor cells in the CCR5+TINs high subgroup (P < .001), other than CCR5+TINs low subgroup (P= .481). Our results indicate that CCR5+TINs could prime anti-tumor immune response through autonomous IFN-γ release, thus leading to favorable prognosis and superior therapeutic response to ACT and immunotherapy in MIBC.
Air Pollution and Allergic Rhinitis: Role in Symptom Exacerbation and Strategies for Management

Abstract This article reviews the current understanding of the role of air pollution in both the symptom exacerbation and rising prevalence of allergic rhinitis (AR) for the development of future AR therapeutics and management strategies. We discuss the epidemiological evidence for this relationship through birth cohort studies, the economic impact of AR, and the influence of air pollution through the lens of the exposome framework of allergic disease development. This is followed by a discussion on the influence of diesel exhaust and diesel exhaust particles (DEP) from motor vehicle emissions and their implication in the rising prevalence of allergic disease and allergic sensitization through triggering inflammatory signalling pathways that exacerbate AR symptoms. Finally, a summary is provided of clinical trials assessing the influence of air pollution on AR with a depiction of currently available therapies and management strategies. Future directions in the development of AR modalities given the air pollution-mediated symptom exacerbation are challenged with unfolding the complex gene–environment interaction product of heterogenous AR presentation.