Miracle-dz/UniFAR-FTUs huggingface dataset:
Validating pollutant load estimates from highways and roads.

Rain and snowmelt that runs off of roadways carries pollutants. Pollutant event mean concentrations have been developed for various land uses to calculate annual pollutant loads. These were developed for total suspended solids, total phosphorus, and total nitrogen. New Hampshire Department of Transportation (NHDOT) uses the Simple Method for estimating the pollutant load in runoff. This study collected real time in situ measurements to validate the concentrations used in Simple Method calculations for modeling pollutant loads from New Hampshire roadways. Three locations were picked to represent low, medium, and high traffic volume roadways. The actual measured amount of pollutants was compared to the loading predictions of the Simple Method. This study confirmed that using one modeling approach is effective for all New Hampshire roadways.
X-ray spectral properties of active galactic nuclei in the Chandra deep field south

We present a detailed X-ray spectral analysis of the sources in the 1Ms catalog of the Chandra Deep Field South (CDFS) taking advantage of optical spectroscopy and photometric redshifts for 321 extragalactic sources out of the total sample of 347 sources. As a default spectral model, we adopt a power law with slope Γ with an intrinsic redshifted absorption N H , a fixed Galactic absorption and an unresolved Fe emission line. For 82 X-ray bright sources, we are able to perform the X-ray spectral analysis leaving both Γ and N H free. The weighted mean value for the slope of the power law is $\langle \Gamma \rangle \simeq 1.75 \pm 0.02$, and the distribution of best fit values shows an intrinsic dispersion of $\sigma_{\rm int} \simeq 0.30$. We do not find hints of a correlation between the spectral index Γ and the intrinsic absorption column density N H . We then investigate the absorption distribution for the whole sample, deriving the N H values in faint sources by fixing $\Gamma = 1.8$. We also allow for the presence of a scattered component at soft energies with the same slope of the main power law, and for a pure reflection spectrum typical of Compton-thick AGN. We detect the presence of a scattered soft component in 8 sources; we also identify 14 sources showing a reflection-dominated spectrum. The latter are referred to as Compton-thick AGN candidates. By correcting for both incompleteness and sampling-volume effects, we recover the intrinsic N H distribution representative of the whole AGN population, $f(N_{\rm H}) {\rm d}N_{\rm H}$, from the observed one. $f(N_{\rm H})$ shows a lognormal shape, peaking around $\log(N_{\rm H})\simeq 23.1$ and with $\sigma \simeq 1.1$. Interestingly, such a distribution shows continuity between the population of Compton-thin and that of Compton-thick AGN. We find that the fraction of absorbed sources (with $N_{\rm H}>10^{22}$ cm -2 ) in the sample is constant (at the level of about 75%) or moderately increasing with redshift. Finally, we compare the optical classification to the X-ray spectral properties, confirming that the correspondence of unabsorbed (absorbed) X-ray sources to optical type I (type II) AGN is accurate for at least 80% of the sources with spectral identification (1/3 of the total X-ray sample).
Efﬁcacy of the Continuous Resuscitation Training with the Gap Period Due to the COVID-19 Pandemic

: (1) Objective: This study evaluates the effects of simulation education at our institute on cardiac arrest resuscitation regarding knowledge, attitude, and practice (KAP) over a ﬁve-year period (2016–2020). (2) Subjects: Staff responded to the annual survey questionnaires followed by monthly training in Basic Life Support/Advanced Cardiovascular Life Support (BLS/ACLS) and Immediate Cardiac Life Support (ICLS) of the Japanese Association for Acute Medicine (JAAM) in 2016, 2017, and 2018. Additionally, in-house training was implemented in 2019 without post-assessment followed by training suspension in 2020 due to the COVID-19 pandemic. The last delivery of the survey questionnaires was in late 2020 for KAP retention measurement. (3) Measurements and Results: The self-efﬁcacy level of BLS/ACLS/ICLS KAP of the survey respondents was analyzed using a ﬁve-point Likert scale. The mean self-efﬁcacy level of BLS/ACLS/ICLS KAP increased over time, and that of the trained people was three-fold that of the untrained people. Trainees that had no cardiopulmonary resuscitation (CPR) experience gained the BLS/ACLS/ICLS key-point self-efﬁcacy level, which we call the “Grip 14” in this study, as high as their untrained counterparts who had three-time CPR experience. Training suspension lessened the BLS/ACLS/ICLS KAP in both groups. (4) Conclusions: Continuous training enhances not only the BLS/ACLS/ICLS KAP of trainees but also of their untrained colleagues. The training likely had the same efﬁcacy as the CPR experience.
Trends in the formation of crystalline and amorphous phases during the firing of clay bricks

La composition des phases affecte notablement certaines proprietes techniques et esthetiques des briques (par ex. resistance mecanique et couleur). Par ailleurs, la mineralogie des briques resulte de complexes reactions a l'etat solide, qui impliquent les mineraux des argiles, les carbonates et, a un moindre degre, le quartz et les feldspaths. Les nouveaux composes qui se forment, pour les conditions usuelles de cuisson des briques sont anorthite, clinopyroxene, melilite, wollastonite, hematite, et une phase amorphe. On trouve aussi, mais moins frequemment: periclase spinelle, et CaO non reagi (mais qui se convertit rapidement en calcite secondaire). Il existe typiquement des residus de quartz et du feldspath. Cette etude visait a evaluer quantitativement la composition de phases (XRF avec methode RIR) de briques produites dans differentes conditions de cuisson (temperature maximale: 800-1100°C) et a partir d'une large variete d'argiles (par ex. avec une teneur en carbonates de 0 a 40% en masse). La formation des phases cristallines et amorphes au cours de la cuisson depend essentiellement de la temperature et de la teneur en CaO des argiles. Par exemple, la formation de pyroxene et de wallastonite est favorisee par un accroissement de temperature ou de teneur en calcium. En ce qui concerne le plagioclase, le role de la temperature de cuisson est particulierement marque pour des teneurs en CaO de 5 a 15% en masse, tandis que la melilite est plus abondante quand la teneur en calcium et la temperature croissent, bien qu'elle chute rapidement quand la temperature excede 1000°C. Il faut donc etre prudent dans l'exploitation des analyses mineralogiques pour deduire la temperature de cuisson des briques, du fait que la stabilite des differentes phases depend largement de la composition des matieres premieres. De ce point de vue, on peut etablir quelques regles predictives simples quant a la composition de phases des briques.
Learning Adverbs with Spectral Mixture Kernels

For humans and robots to collaborate more in 001 the real world, robots need to understand hu-002 man intentions from the different manner of 003 their behaviors. In our study, we focus on the 004 meaning of adverbs which describe human mo-005 tions. We propose a topic model, Hierarchi-006 cal Dirichlet Process-Spectral Mixture Latent 007 Dirichlet Allocation, which concurrently learns 008 the relationship between those human motions 009 and those adverbs by capturing the frequency 010 kernels that represent motion characteristics 011 and the shared topics of adverbs that depict 012 such motions. We trained the model on datasets 013 we made from movies about “walking” and 014 “dancing”, and found that our model outper-015 forms representative neural network models in 016 terms of perplexity score. We also demonstrate 017 our model’s ability to determine the adverbs for 018 a given motion and confirmed that the model 019 predicts more appropriate adverbs. 020
Fine-Tuning Language Models for Emotion Recognition in Lithuanian Texts Using Neural Machine Translation of Training datasets

Lithuanian language is a complex and rich language with a unique grammar structure, making it an interesting choice for natural language processing (NLP) tasks such as emotion detection. This study provides helpful insights into the emotional nuances of Lithuanian texts by utilizing a translated and augmented emotion dataset. We present a methodology that leverages translated datasets for emotion recognition and augmentation approaches to improve the performance of emotion identification models in low-resource languages. We compared the outcomes of transformer-based language models, such as RoBERTa, LaBSE, and LitLat BERT on the translated and augmented data. Our results demonstrated that LitLat BERT, which is primarily trained on Lithuanian texts, showed the most significant improvement in performance when data augmentation was applied. We conclude that LitLat BERT could be the preferred choice for emotion recognition tasks for Lithuanian language due to its specialized training and enhanced adaptability when provided with diverse and augmented data. This study provides valuable insights into the challenges and potential solutions for emotion identification tasks in morphology-rich languages, like Lithuanian language.
UR Scholarship Repository UR Scholarship Repository

There has been limited research investigating potential mechanisms that drive the association between obsessive-compulsive (OC) and depressive symptoms. Obsessive beliefs are implicated in the etiology and maintenance of OC symptoms and have been shown to correlate with depressive symptoms amongst OCD patients. I assessed whether obsessive beliefs moderate the relation between obsessive compulsive and depressive symptoms to replicate analyses from a study conducted by Teller et al. (2017). Forty-six participants with elevated OC symptoms were recruited through Amazon’s Mechanical Turk. Each participant completed the obsessing subscale of the Revised Obsessive-Compulsive Inventory (OCI-R), Dimensional Obsessive Compulsive Scale (DOCS), the Revised Obsessive Beliefs Questionnaire (OBQ-44), and the 7-item depression subscale of the Depression Anxiety and Stress Scale (DASS-21). Obsessive-compulsive symptoms were not a significant predictor of depressive symptoms ( B = 1.20, p = .28). Additionally, obsessive beliefs ( B = .00, p = .85), and the interaction between obsessive beliefs and obsessive-compulsive symptoms ( B = .01, p = .53), were not significant predictors of depressive symptoms. In exploratory analyses, obsessive-compulsive symptoms were a significant predictor of overall distress ( B = 6.91, p ≤ .01). However, obsessive beliefs ( B = .00, p = .93), and the interaction between obsessive beliefs and obsessive-compulsive symptoms ( B = .04, p = .41), were not significant predictors of distress. In exploratory post-hoc probing, the influence of OC symptoms on distress was greater when obsessive beliefs were high ( +1 SD [ t = 2.85, p ≤ .01]) compared to average obsessive beliefs ( Mean [ t = 2.72, p ≤ .01)]) or when obsessive beliefs were low (-1 SD [ t = 1.56, p = .13]). This was particularly true
RSC Chemical Biology

Interface peptides that mediate protein–protein interactions (PPI) are a class of important lead compounds for designing PPI inhibitors. However, their potential as precursors for radiotracers has never been exploited. Here we report that the interface peptides from programmed death-ligand 1 (PD-L1) can be used in positron emission tomography (PET) imaging of programmed cell death 1 (PD-1) with high accuracy and sensitivity. Moreover, the performance differentiation between murine PD-L1 derived interface peptide (mPep-1) and human PD-L1 derived interface peptide (hPep-1) as PET tracers for PD-1 unveiled an unprecedented role of a non-critical residue in target binding, highlighting the significance of PET imaging as a companion diagnostic in drug development. Collectively, this study not only provided a first-of-its-kind peptide-based PET tracer for PD-1 but also conveyed a unique paradigm for developing imaging agents for highly challenging protein targets, which could be used to identify other protein biomarkers involved in the PPI networks.
Journal of Reproduction and Development

The controlled activation of dormant primordial follicles is important for the maintenance of periodic ovulation. Previous reports have clearly identified the signaling pathway in granulosa cells and oocytes that controls the activation of primordial follicles; however, the exact cue for the in vivo activation of dormant primordial follicles is yet to be elucidated. In this study, we found that almost all activated primordial follicles made contact with blood vessels. Based on this result, we speculated that the contact between primordial follicles and blood vessels may provide a cue for the activation of dormant primordial follicles. To confirm this hypothesis, we attempted to activate dormant primordial follicles within the ovaries by inducing angiogenesis through the use of biodegradable gels containing recombinant vascular endothelial growth factor and in cultured ovarian tissues by increasing the serum concentration within the culture medium. The activation of dormant primordial follicles was promoted in both experiments, and our results indicated that an increase in the supply of the serum component, from new blood vessels formed via angiogenesis, to the dormant primordial follicles is the cue for their in vivo activation. In the ovaries, angiogenesis often occurs during every estrous cycle, and it is therefore likely that angiogenesis is the crucial event that influences the activation of primordial follicles.
Attaining reproductive solutions through activity monitoring

Today’s activity monitoring systems do much more than just identify cow/heifer for insemination. The addition of rumination monitoring allows the identification of health events along with reproductive events. Performance of automated activity monitoring (AAM) systems in combination with timed artificial insemination (TAI) compared to TAI exclusively has been widely researched and adopted. Detecting a high percentage of cows in estrus is essential to maintain reproductive performance in dairy herds using AI. The Dairy Records Management Systems reported a mean yearly estrus detection rate on 8,749 US Holstein herds (including all reproductive management strategies) as 46.5% in January of 2018. 1 Automated activity monitoring technologies are an available alternative to supplement or replace visual estrus detection. Parameters with potential for AAM include mounting events, activity level, lying time, rumination and eating times, feeding events, progesterone levels, body temperature, and more. The automatic measurement of chewing and ruminating activity can enable the early detection of feeding deficiencies and assist in ration adjustments. Feeding and ruminating behaviors have traditionally been monitored through visual observation or video recording methods, but these methods are time consuming and only practically used in research settings. Commercially marketed technologies recording feeding behavior, rumination, and lying behavior performed well when compared with visual observation. Rumination behavior was most variable from visual observation. Similar performance to visual observations and other validated technologies indicates dairy cattle behavioral monitors to provide accurate information for use in dairy cow management.
THE EFFECTIVENESS OF MONETARY TRANSMISSION THROUGH INTEREST RATE AND EXCHANGE RATE CHANNELS ON INDONESIA’S INFLATION RATE

The purpose of this research is to determine the effectiveness of monetary transmission on inflation in Indonesia through the interest rate and the exchange rate channel over a period of 2015Q1-2022Q4. This research analysis approach uses the variance decomposition and Vector Error Correction Model (VECM) methods. Quantitative methods are utilized, and the estimation tool used is Eviews 12. The findings of the variance decomposition analysis in this research indicate that to reduce inflation in Indonesia, monetary transmission through exchange rates is more effective than through the interest rate channel
ANALYSIS OF PAKISTAN’S CLIMATIC FACTORS AFFECTING MARINE FISH PRODUCTION

A lot of study has been done on how climate change impacts farming. But there aren't many studies in Pakistan that look at how climate change changes the number of fish that can be caught in the real world. This study's main goal is to look at the effects of climate change on fish in the sea around Pakistan from 1990 to 2020. It was given to us by the World Development Indicators. This study used the autoregressive distributed lag (ARDL) model to examine how the link between CO2 emissions, weather, rainfall, and sea fish production changes over time. Using the autoregressive distributed lag (ARDL) method to cointegration, a strong link was found between rains and the number of fish caught. To determine if rainfall has a statistically significant effect on sea fish production in the short term, we used the coefficient for rainfall (β = 5738.02) and found that it does. In the long run, it makes a difference at the 1% level of importance. Both changes in temperature and CO2 pollution hurt fish production a lot, according to the study. This is true in the short as well as in the long term. Researchers found that it would be helpful for lawmakers to make national policies that are better for adapting to climate change and supporting long-term control of marine fishing. Pakistan's fishing business should do a lot of research and development to find marine fish species that can live in places with a lot of CO2 and high temperatures.
Market Design for the Environment ∗

The main argument in favor of markets in environmental contexts is the same as in other contexts: their ability to promote efficient allocations and production. But environmental problems bring their own challenges: their underlying bio-physical processes - and the technologies to monitor them - constrain what is feasible or even desirable. This chapter illustrates the main design dimensions in environmental markets, the trade-offs involved and their impact on performance, through the lens of a regulated market for pollution rights (the EU emissions trading scheme) and a voluntary market for the provision of environmental services (the global market for carbon credits). While both markets eventually contribute to climate change mitigation, their organisation as a “pollution market”, for the former, and as a “provision market”, for second, means that different design considerations take precedence. Both markets also face challenges: volatile prices in the EU emissions scheme and low trust for voluntary carbon markets. We discuss how alternative design options could address those.
Mechanisms underlying alcohol-approach action tendencies: the role of emotional primes and drinking motives

The tendency to approach alcohol-related stimuli is known as the alcohol-approach bias and has been related to heavy alcohol use. It is currently unknown whether the alcohol-approach bias is more pronounced after emotional priming.The main aim of this study was to investigate whether positive and negative emotional primes would modulate the alcohol-approach bias. For this purpose, a new contextual emotional prime-approach avoidance task was developed, containing both negative and positive emotional primes. Explicit coping drinking motives were expected to be related to an increased alcohol-approach bias after negative primes. Results of 65 heavy and 50 occasional drinkers showed that the alcohol-approach bias was increased in both groups during negative emotional priming. This appeared to be due to slower alcohol avoidance rather than faster alcohol approach. This change in alcohol-approach bias was positively related to explicit enhancement drinking motives and negatively related to alcohol use-related problems. A stronger alcohol-approach bias in heavy compared to occasional drinkers could not be replicated here, and coping drinking motives were not related to the alcohol-approach bias in any of the emotional contexts. The current ﬁndings suggest that both occasional and heavy drinkers have a selective difﬁculty to avoid alcohol-related cues in a negative emotional context. Negative reinforcement may therefore be involved in different types of drinking patterns. The inﬂuence of emotional primes on alcohol-related action tendencies may become smaller when alcohol use becomes more problematic, which is in line with habit accounts of addiction.
Performance Analysis of Chrominance Red and Chrominance Blue in JPEG

While compressing text files is useful, compressing still image files is almost a necessity. A typical image takes up much more storage than a typical text message and without compression images would be extremely clumsy to store and distribute. The amount of information required to store pictures on modern computers is quite large in relation to the amount of bandwidth commonly available to transmit them over the Internet and applications. Image compression addresses the problem of reducing the amount of data required to represent a digital image. Performance of any image compression method can be evaluated by measuring the root-mean-square-error & peak signal to noise ratio. The method of image compression that will be analyzed in this paper is based on the lossy JPEG image compression technique, the most popular compression technique for color images. JPEG compression is able to greatly reduce file size with minimal image degradation by throwing away the least “important” information. In JPEG, both color components are downsampled simultaneously, but in this paper we will compare the results when the compression is done by downsampling the single chroma part. In this paper we will demonstrate more compression ratio is achieved when the chrominance blue is downsampled as compared to downsampling the chrominance red in JPEG compression. But the peak signal to noise ratio is more when the chrominance red is downsampled as compared to downsampling the chrominance blue in JPEG compression. In particular we will use the hats.jpg as a demonstration of JPEG compression using low pass filter and demonstrate that the image is compressed with barely any visual differences with both methods. Keywords—JPEG, Discrete Cosine Transform, Quantization, Color Space Conversion, Image Compression, Peak Signal to Noise Ratio & Compression Ratio.
Inflation Expectations, the Phillips Curve and Monetary Policy

Conjectures about inflation expectations are inextricably linked to our understanding of the relationship between the real and monetary sides of the economy; yet, direct empirical research on the matter has been scarce at best. This paper therefore examines the empirical properties of inflation expectations data constructed on the basis of both qualitative and quantitative surveys of consumers for a set of eight European countries. The rational perceptions hypothesis is tested and rejected by the data, a finding which in turn leads us to reject the rational expectations hypothesis and casts doubt on the New Keynesian Phillips Curve model. The popular alternative of using “rule-of-thumb” expectations in such models empirically is also found to be unrobust. Similarly, the conjecture by Akerlof et al. (2000) of a non-vertical long-run Phillips curve arising from the presence of “near-rationa l” expectations cannot be supported. The Mankiw and Reis (2002) Phillips curve based on the idea of “sticky information” succeeds in its intuition of a gradual adjustment of expectations, but its assumption of rational updating is challenged by the data in the context of the natural experiment provided by the UK's ERM disinflation. Instead, the adjustment mechanism for expectations appears to display largely adaptive characteristics. Finally, the paper provides some insights into the nature of the interaction between monetary policy and inflation expectations.