Miracle-dz/UniFAR-FTUs huggingface dataset:
Engineered device in E. coli lyses S. aureus at physiological fever temperatures

Multiple strains of Staphylococcus are resistant to antibiotics, including the well-known methicillin-resistant Staphylococcus aureus (MRSA). We share an engineered plasmid device in Escherichia coli that lyses the disease-causing pathogen, S. aureus. The device was engineered using BioBrick parts obtained from the International Genetically Engineered Machine foundation (iGEM). The cI-blue-lysostaphin device consists of a temperature-sensitive promoter that is activated under physiological fever temperatures above 35°C that drives expression of a blue chromoprotein reporter and mature truncated lysostaphin enzyme. The functioning cI-blue-lysostaphin device was tested for optimal lysis conditions in MM294 and DH5α E. coli chassis and across incubation temperatures ranging from 30-42°C. We conclude that the lysostaphin activity of the cI-blue-lysostaphin device differs between chassis and increases with greater incubation temperature.
Considerations for extracting blood from turtles and tortoises: venipuncture sites and anticoagulants

Objective . Evaluate different venipuncture points and the use of two anticoagulants to obtain blood samples in turtles. Materials and methods. Eighty-two turtles of the species Trachemys callirostris, Podocnemis unifilis and Chelonoidis carbonaria were sampled. Three venipuncture points were evaluated: subcarapacial venous sinus, dorsal coccygeal vein, and jugular vein. Two anticoagulants were tested: sodium heparin and EDTA. Results. The jugular vein was the best place to practice venipuncture as the blood samples obtained were free of hemodilution and enough volume to carry out a blood profile. In contrast, samples from the other venipuncture points were usually hemodiluted. Blood samples from C. carbonaria stored with EDTA (40 µl/ml of blood) showed haemolisis, which was not observed using sodium heparin (100 UI/ml of blood) as anticoagulant. Conclusions. The jugular vein is the most recommended venipuncture site for the extraction of blood samples for clinical purposes. Sodium heparin was the best anticoagulant to store blood samples due to the fact that it does not induce haemolisis in any sample.
Gradient symbolic representations in Harmonic Grammar

This paper presents an overview of Gradient Harmonic Grammar, a weighted-constraint model of grammatical computation in which language structures are represented with numerically continuous levels of activity, or degree of presence. In this system, the penalty of each constraint violation is proportional to the activity of the structure that incurs it. The adoption of gradient activity permits unique advances in generative approaches to key types of idiosyncratic patterns in language. I review the main proposals that have been made in the framework, and outstanding issues such as the existence of gradient activity in output structures
The short-term recovery of sprint cycling performance

Short-term sprint cycling performance recovery was investigated, with consideration to the Match Sprint. Fifteen strength-trained men (age: 24 ± 6 years; height: 1.81 ± 0.08 m; body mass: 83.4 ± 8.4 kg) were first familiarised with an 18 s sprint. During the baseline trial, blood lactate concentration, tissue saturation index, and oxygen uptake were monitored following a single sprint. In the remaining trials, the recovery duration (45, 90, 135, 180, 360, and 720 s) between two sprints was varied. Peak (PPO) and mean (MPO) power output were computed for each sprint. The recovery percentage of MPO and the recovery time-course of the physiological variables were modelled using one- and two-phase exponential functions. Statistical significance was set a priori at p < 0.05. Effects of sprint number, recovery time, and a sprint number × recovery time interaction were found for both PPO and MPO. Post hoc tests revealed significant differences between sprints at all time-points for both variables. The time constant (τ), 130.6 ± 95.6 s, of the one-phase exponential function (asymptotic amplitude [A0] = 97.4 ± 2.5%), suggested that performance recovery had stabilised within 12 minutes. However, the parameters of the two-phase function indicated that recovery was incomplete (A0 = 87.7 ± 6.4%, A1 = 11.9 ± 5.2%, τ0 = 56.3 ± 33.3 s, τ1 = 458.2 ± 283.3 s). The τ for MPO recovery was not significantly correlated with any of the physiological variables. The reduction in sprint cycling performance throughout the tested time-period could be meaningful for athletes competing in the Match Sprint.
Potentialities of the microbial consortium Curvularia kusanoi -Trichoderma pleuroticola as a biological pretreatment for the degradation of fibrous sources

Objective. To evaluate the potentiality of the microbial consortium Curvularia kusanoi L7- Trichoderma pleuroticola as biological pretreatment of high fiber sources destined for animal production. Materials and methods . The Strains used where Curvularia kusanoi L7 and Trichoderma pleuroticola . The degradative potential was evaluated through the production kinetics of cellulolytic (endo-1,4-β glucanase and exo-1,4-β-glucanase) and ligninolytics enzymes (laccase and peroxidase) in solid submerged fermentation of bran wheat and sugarcane bagasse. The growth of the co culture in plates was analyzed. The effect of the consortium on the carbon mineralization of raw wheat straw was determined and the degree of fiber degradation was evaluated by infrared spectroscopy (IR). Resulted. Both strains showed high cellulolytic production. Only C. kusanoi L7 showed ligninolytic activity, with a maximum laccase activity of 1400 U/L. No antagonism was found between the strains and the results of carbon mineralization and evaluation of their final products by IR indicate the effectiveness of the consortium to degrade the cell wall more efficiently than each of the strains individually. Conclusions. It is concluded that the microbial consortium C. kusanoi L7- T. pleuroticola has great potential for structural modification of fibrous sources destined for animal feeding.
Macroprudential Regulation of Investment Funds

The investment fund sector, the largest component of the non-bank financial system, is growing rapidly and the economy is becoming more reliant on investment fund financial intermediation. This paper builds a dynamic stochastic general equilibrium model with banks and investment funds. Banks grant loans and issue liquid deposits, which are valuable to households. Funds invest in corporate bonds and may hold liquidity in the form of bank deposits to meet investor redemption requests. Without regulation, funds hold insufficient deposits and must sell bonds when hit by large redemptions. Bond liquidation is costly and eventually reduces investment funds’ intermediation capacity. Even when accounting for side effects due to a reduction of deposits held by households, a macroprudential liquidity requirement improves welfare by reducing bond liquidation and by increasing the economy’s resilience to financial shocks akin to March 2020.
Online Music Consumption Characterizing Depression Risk

Music, an integral part of our lives, which is not only a source of entertainment but plays an important role in mental well-being by impacting moods, emotions and other affective states. In this age of Big Data, online music streaming services allow us to capture ecologically valid music listening behavior and provide a rich source of information to identify several user-specific aspects. Music preferences and listening strategies have been shown to be associated with the psychological well-being of listeners including internalized symptomatology and depression. However, till date no studies exist that examine music-related social tags, static & time-varying audio-derived features, in terms of acoustic and emotional content, and its association with users well-being. The current work aims at unearthing static and dynamic patterns and trends in the individuals at risk for depression as it manifests in naturally occurring online music consumption. Mental well-being scores and listening histories of 541 Last.fm users were examined. Social tags associated with each listener’s most popular tracks were analyzed to unearth the mood/emotions and genres associated with the users. Results revealed that social tags prevalent in the users at risk for depression were predominantly related to emotions depicting Sadness associated with genre tags representing neo-psychedelic-, avant garde-, dream-pop. Static and dynamic acoustic and emotion-related features were extracted from each user’s listening history and correlated with their mental well-being scores. Results revealed that individuals with greater depression risk resort to higher dependency on music with greater repetitiveness in their listening activity. Furthermore, the affinity of depressed individuals towards music that can be perceived as sad was found to be resistant to change over time. This study has large implications for future work in the area of assessing mental illness risk by exploiting digital footprints of users via online music streaming platforms. This study will open up avenues for an MIR-based approach to characterizing and predicting risk for depression which can be helpful in early detection and additionally provide bases for designing music recommendations accordingly.
The role of wind, mesoscale dynamics, and coastal circulation in the interannual variability of the South Vietnam Upwelling, South China Sea – answers from a high-resolution ocean model

The South Vietnam Upwelling (SVU) develops in the South China Sea (SCS) under the inﬂuence of southwest monsoon winds. To study the role of small spatiotemporal scales on the SVU functioning and variability, a simulation was performed over 2009–2018 with a high-resolution conﬁguration (1 km at the coast) of the SYMPHONIE model implemented over the western region of the SCS. Its capability to represent ocean dynamics and water masses from daily to interannual scales and from coastal to regional areas is quantitatively demonstrated by comparison with available satellite data and four in situ datasets. The SVU interannual variability is examined for the three development areas already known: the southern (SCU) and northern (NCU) coastal upwelling areas and the offshore upwelling area (OFU). Our high-resolution model, together with in situ observations and high-resolution satellite data, moreover shows for the ﬁrst time that upwelling develops over the Sunda Shelf off the Mekong Delta (MKU). Our results conﬁrm for the SCU and OFU and show for the MKU the role of the mean summer intensity of wind and cyclonic circulation over the offshore area in driving the interannual variability of the upwelling intensity. They further reveal that other factors contribute to SCU and OFU variability. stronger in the NCU area: the NCU is when alongshore (offshore) currents prevail.
Residual Cusum Test for Parameters Change in ARCH Errors Models with Deterministic Trend

This paper analyzes the problem of testing for parameters change in ARCH errors models with deterministic trend based on residual cusum test. It is shown that the asymptotically limiting distribution of the residual cusum test statistic is still the sup of a standard Brownian bridge under null hypothesis. In order to check this, we carry out a Monte Carlo simulation and examine the return of IBM data. The results from both simulation and real data analysis support our claim. We also can explain this phenomenon from a theoretical viewpoint that the variance in ARCH model in mainly determined by its parameters.
The Allocation of Talent to Financial Trading versus Entrepreneurship: Welfare Effects of Trading in General Equilibrium∗

This paper investigates the implications of the Grossman-Stiglitz (1980) model on the informational efficiency of financial markets for the optimality of the allocation of talent to financial trading versus production. Informed traders make the financial market more informationally efficient, entrepreneurs create output and jobs. The model indicates that financial trading attracts too much, rather than too little, talent. JEL classification: G14, J24
Exploiting Cross-Modal Redundancy for Audio-Visual Generation

We interact with the world around us through multiple sensory streams of information such as audio, vision, and text (language). Each of these streams complement each other, but also contain redundant information, albeit in different forms. For example, the content of a person speaking can be captured by listening to the sounds in the speech, or partially understood by looking at the speaker’s lip movements, or by reading out the text transcribed from the vocal speech. This redundancy across modalities is utilized in human perceptual understanding that helps us to solve various practical problems. However, in the real-world, more often than not, information in individual streams is corrupted by various types of degradation like electronic transmission, background noise, and blurring which lead to deterioration in the content quality. In this work, we aim to recover the distorted signal in a given stream by exploiting the redundant information in another stream. Specifically, we deal with talking-face videos involving vision and speech signals. We propose two core ideas to explore cross-modal redundancy: (i) denoising speech using visual assistance, and (ii) upsampling very low-resolution talking-face videos using audio assistance. The first part focuses on the task of speech denoising. We show that the visual stream helps in distilling the clean speech from the corrupted signal by suppressing the background noise. We identify the key issues prevailing in the existing state-of-the-art speech enhancement works: (i) most of the current works use only the audio stream and are limited in their performance in a wide range of realworld noises, and (ii) few recent works use the lip-movements as additional cues with an aim to improve the quality of the generated speech over “audio-only” methods. However, they cannot be applied for several applications where the visual stream is unreliable or completely absent. Thus, in this work, we propose a new paradigm for speech enhancement: “pseudo-visual” approach, where the visual stream is synthetically generated from the noisy speech input. We demonstrate that the robustness and the accuracy boost obtained from our model lead to various real-world applications which were previously not possible. In the second part, we explore an interesting question of what can be obtained from an 8 × 8 pixel video sequence by utilizing the corresponding speech of the person talking. Surprisingly, it turns out to be quite a lot. We show that when processed with the right set of audio and image priors, we can obtain a full-length talking video sequence with a 32× scale-factor. When the semantic information about the identity, including basic attributes like age and gender, are almost entirely lost in the input low-resolution video, we show that utilizing the speech that accompanies the low-resolution video aids
The Impact of Transport Infrastructure on Productivity in Canada

This study examines the relationship between transportation infrastructure and output and productivity in Canada. We estimate different specifications of a static Cobb-Douglas production function (in levels and in differences). The impact of highway infrastructure is mixed. For the 1997-2018 period a higher stock of highways does not translate into higher productivity for the business sector, But from 2009 to 2018, the impact of highways is positive and statistically significant, when we account for province-specific characteristics. The long run elasticity of output with respect to railway lines is statistically significant and quite large (0.27). For this type of infrastructure, then, our results are more conclusive and point to a positive impact of railways on output and productivity. study examines the relationship between transportation infrastructure and output and productivity. We estimate different specifications of a static Cobb-Douglas production function (in levels and in differences). Suspecting that investment in infrastructure could affect output with a lag, and to control for the possible non-stationarity in output time series, we also estimate a dynamic production function that includes lags of the dependent variable our interest. We with OLS and System GMM. order to further explore the relationship between transportation infrastructure and productivity, we also estimate a multifactor productivity growth function. dataset did not allow to disaggregate transportation infrastructure sufficiently, we also estimate the static functions using an alternative data set that allows a more granular disaggregation but covers a shorter time period. allowed us to estimate the impact of railway lines, seaports and airports. The results indicate a positive impact from other transportation infrastructure (the category that includes railway lines) on production, with a 1 per cent increase in that type of infrastructure increasing output by about 0.1 per cent (statistically significant at the 1 per cent level). The results show the opposite impact from roads, bridges, and tunnels, with a 1 per cent increase in that type of infrastructure corresponding to a 0.2 per cent decrease in output (statistically significant at the 1 per cent level). Results also indicate a small and negative impact of marine engineering infrastructure on production (-0.02 per cent), but only statistically significant at the 10 per cent level. which does not account for province-specific characteristics, would then show that a larger stock of highways does not necessarily translate into more production. The fixed effects model focuses on within- province variation and shows that, when we only look within a specific province, an increased stock of highways and roads does in fact lead to a higher level of GDP, everything else fixed.
Neural Machine Translation for Low Resource Languages

Machine Translation is the task where a machine generates a sentence in language T , given an input sentence in language S. The generated and input sentences must have similar semantics. In the current literature, there are various methods proposed to solve the task. Deep neural network based translation models (Neural Machine Translation (NMT)) have been shown to achieve state-of-the-art performance for multiple language pairs. However, neural methods struggle to perform well for lowresource languages. Low-resource languages are understudied, suffer from the data scarcity problem, and lack efficient language processing tools. Since neural methods require large amount of data for training effective models, less-complex statistical methods outperform these methods. Transformer-based NMT models have achieved state-of-the-art performance for various languages. Multiple parallel attention mechanisms that use multiple attention heads facilitate greater performance of the Transformer model for various applications e.g., NMT), text classification. However, transformer models do not perform well in low-resource conditions. In this thesis, we propose a novel Dynamic Head Importance Computation Mechanism (DHICM), which enhances the performance of the transformer model, especially, in low-resource conditions. In multi-head attention mechanism, different heads attend to different parts of the input. However, the limitation is that multiple heads might attend to the same part of the input, resulting in multiple heads being redundant. Thus, the model resources are underutilized. One approach to avoid this is to prune least important heads based on certain importance score. We focus on designing a head importance computation method to dynamically calculate the importance of a head with respect to the input. Our insight is to design an additional attention layer together with multi-head attention, and utilize the outputs of the multi-head attention along with the input, to compute the importance for each head. Additionally, we add an extra loss function to prevent the model from assigning same score to all heads, to identify more important heads and improvise performance. We analyzed performance of DHICM for NMT with different languages. Experiments on different datasets show that DHICM outperforms traditional Transformer-based approach by large margin, especially, when less training data is available. Code mixing is a phenomena of mixing two or more languages, prevalent in multilingual communities. In recent years, due to the prevalence of social media platforms, there has been a surge in the usage of code-mixed texts. Code-mixed texts are informal in nature, and do not necessarily follow pre-defined syntactic structures. Due to the informal nature, traditional NLP systems for monolingual languages, do not perform well for code-mixed inputs. Moreover, good quality code-mixed data is scarce, hence,
Improving Password Generation Through the Design of a Password Composition Policy Description Language

Password managers help users more effectively manage their passwords, yet the adoption of password generation is minimal. One explanation for this problem is that websites’ password composition policies (PCPs) can reject generated passwords, creating a usability impediment. To address this issue, we design a PCP language that websites use to describe their PCP and that managers use to generate compliant passwords. We develop this language using an iterative process involving an extensive collection of PCPs scraped from the Web. We provide libraries for adopting our PCP language into websites and password managers and build proof-of-concept prototypes to verify the real-world feasibility of our PCP language. Using a 25-person user study, we demonstrate that our language and libraries are easy to pick up and correctly use for novice developers. Finally, we replicate and extend past research evaluating Web PCPs, showing that half of PCPs fail to require passwords that resist ofﬂine attacks when considering that users prefer certain character classes when selecting their passwords.
Studies of orD-Dependent Functions in Bacillus subtilis

Gene expression in Bacillus subtilis can be controlled by alternative forms of RNA polymerase programmed by distinct a factors. One such factor, SD ((r28), is expressed during vegetative growth and has been implicated in the transcription of a regulon of genes expressed during exponential growth and the early stationary phase. We have studied several functions related to flagellar synthesis and chemotaxis in B. subtilis strains in which ufD is missing or is present at reduced levels. Previous studies showed that a null mutant, which contains a disrupted copy of the JD structural gene (sigD), fails to synthesize flagellin and grows as long filaments. We now show that these defects are accompanied by the lack of synthesis of the methyl-accepting chemotaxis proteins and a substantial decrease in two autolysin activities implicated in cell separation. A strain containing an insertion upstream of the sigD gene that reduces the level of e protein grew as short chains and was flagellated but was impaired in chemotaxis and/or motility. This reduced level of cr3 expression suggests that the sigD gene may be part of an operon. A strain containing an insertion downstream of the sigD gene expressed nearly wild-type levels of crD protein but was also impaired in chemotaxis and/or motility, suggesting that genes downstream of sigD may also be involved in these functions. Genetic experiments