Miracle-dz/UniFAR-FTUs huggingface dataset:
Regional-scale phytoplankton dynamics and their association with glacier meltwater runoff in Svalbard

Abstract. Arctic amplification of global warming has accelerated mass loss of Arctic land ice over the past decades and lead to increased freshwater discharge into glacier fjords and adjacent seas. Glacier freshwater discharge is typically associated with high sediment loads which limits the euphotic depth, but may also provide surface waters with essential nutrients, thus having counter-acting effects on marine productivity. In-situ observations from a few measured fjords across the Arctic indicate that glacier fjords dominated by marine-terminating glaciers are typically more productive than those with only land-terminating glaciers. Here we combine chlorophyll a from satellite ocean colour, an indicator of phytoplankton biomass, with glacier meltwater runoff from climatic mass-balance modelling to establish a statistical model of summertime-phytoplankton dynamics in Svalbard (mid-June to September). Statistical analysis reveals positive spatiotemporal association of chlorophyll a with glacier runoff for 7 out of 14 primary hydrological regions. These regions consist predominantly of the major fjord systems of Svalbard. The adjacent land areas are characterized by a wide range of total glacier coverage (35.5 % to 81.2 %) and fraction of marine-terminating glacier area (40.2 % to 87.4 %). We find that an increase in specific glacier-runoff rate of 10 mm water equivalent per 8-day timeperiod raises summertime chlorophyll a concentrations by 5.2 % to 20.0 %, depending on region. During the annual peak discharge we estimate that glacier runoff contributes to 13.1 % to 50.2 % increase in chlorophyll a compared to situations with no runoff. This suggest that glacier runoff is an important factor sustaining summertime phytoplankton production in Svalbard fjords, in line with findings from several fjords in Greenland. In contrast, for regions bordering open coasts, and beyond 10 km distance from the shore, we do not find significant association of chlorophyll a with runoff. In these regions, physical ocean and sea ice variables control chlorophyll a, pointing at the importance of a late sea ice breakup in northern Svalbard, as well as the advection of Atlantic water masses along the West Spitsbergen Current for summertime phytoplankton dynamics. Our method allows for investigation and monitoring of glacier-runoff effects on primary production throughout the summer season and is applicable on a Pan-Arctic scale, thus complementing valuable but scarce in-situ measurements in both space and time.
Revisiting the Growth Effects of Sino–African Bilateral Trade on African Economies

In this paper, the effect of China-Africa’s bilateral trade intensity and concentration, which are alternatively incorporated as threshold variables, on economic growth of African countries, is examined through a non-linear panel threshold approach. Unlike the existing empirical literature on trade-growth nexus for African economies, our findings suggest a heterogeneous trade-growth nexus with the effect of bilateral trade intensity on Africa’s economic growth being higher in countries whose trade intensity with China is higher compared to those with lower-intensity. However, although the effect of bilateral trade concentration on Africa’s growth has been found for countries whose trade concentration is lower, the growth-effect of trade concentration for countries whose trade concentration is higher is unclear. These results are in contrast to some earlier literature relying on linear-based approaches which mask the parameter heterogeneity and may sometimes lead to inappropriate policy recommendations. Drawn implications emphasize the critical importance of addressing prevailing trade constraints as well as the provision of trade-capacity building for the Chinese market. Combined with the estimated thresholds for trade intensity and concentration, these findings imply four categories of trade policies depending on the position of countries in a trade intensity-concentration matrix.
Manager Uncertainty and Cross-Sectional Stock Returns

This paper evidences the explanatory power of managers’ uncertainty for cross-sectional stock returns. I introduce a novel measure of the degree of managers’ uncertain beliefs about future states: manager uncertainty (MU), defined as the count of the word “uncertainty” over the sum of the count of the word “uncertainty” and the count of the word “risk” in filings and conference calls. I find that managers’ level of uncertainty reveals valuation information about real options and thereby has significantly negative explanatory power for cross-sectional stock returns. Beyond existing market-based uncertainty measures, the manager uncertainty measure has incremental pricing power by capturing information frictions between managers’ reported uncertainty and investors’ perception of uncertainty. Moreover, a short-long portfolio sorted by manager uncertainty has a significantly positive premium and cannot be spanned by existing factor models. An application on COVID-19 uncertainty shows consistent results.
L OSS L ANDSCAPE M ATTERS : T RAINING C ERTIFIABLY R OBUST M ODELS WITH F AVORABLE L OSS L AND - SCAPE

In this paper, we study the problem of training certifiably robust models. Certifiable training minimizes an upper bound on the worst-case loss over the allowed perturbation, and thus the tightness of the upper bound is an important factor in building certifiably robust models. However, many studies have shown that Interval Bound Propagation (IBP) training uses much looser bounds but outperforms other models that use tighter bounds. We identify another key factor that influences the performance of certifiable training: smoothness of the loss landscape. We consider linear relaxation-based methods and find significant differences in the loss landscape across these methods. Based on this analysis, we propose a certifiable training method that utilizes a tighter upper bound and has a landscape with favorable properties. The proposed method achieves performance comparable to state-of-the-art methods under a wide range of perturbations.
Oblivious Sketching-based Central Path Method for Solving Linear Programming Problems

In this work, we propose a sketching-based central path method for solving linear programmings, whose running time matches the state of art results Cohen et al. (2019b); Lee et al. (2019). Our method opens up the iterations of the central path method and deploys an ”iterate and sketch” approach towards the problem by introducing a new coordinate-wise embedding technique, which may be of independent interest. Compare to previous methods, the work Cohen et al. (2019b) enjoys feasibility while being non-oblivious, and Lee et al. (2019) is oblivious but infeasible, and relies on dense sketching matrices such as subsampled randomized Hadamard/Fourier transform matrices. Our method enjoys the beneﬁts of being both oblivious and feasible, and can use sparse sketching matrix Nelson & Nguyˆen (2013) to speed up the online matrix-vector multiplication. Our framework for solving LP naturally generalizes to a broader class of convex optimization problems including empirical risk minimization.
A Trans-Niagara Tale of Informed Traders§

This research documents the impact of differential private information on relative asset pricing across borders by studying the probability of informed trading (pin) for Canadian shares traded on exchanges separated by Niagara Falls. Relative to the New York Stock Exchange (nyse), the Toronto Stock Exchange (tsx) has more informed trades and accounts for a larger information share, indicating that informed traders contribute to cross-border price discovery. The information imbalance across the two markets is associated with small but positive price premiums for New York trades. The dynamics of these premiums depends on trade informedness. Lastly, the pin of a tsx-listed share typically rises upon crosslisting on the nyse, which is consistent with negative event-study returns of the original listing.
The Moderating Effect of Gender on Adopting Digital Government Innovations in Ethiopia

s: Digital government innovation is being recognised as a solution to many problems faced by governments in providing services to their citizens. It is especially important for lowincome countries where there are resource constraints. This research was aimed at exploring the moderating effect of gender on the adoption of a digital government innovation in Ethiopia based on the UTAUT model (n=270) and using structural equation modeling (SEM). The results reveal that gender only moderates the relationship between facilitating conditions and usage behavior of government employees to adopt the digital government innovation which is inconsistent with other findings. Another key finding was that even though the innovation was regarded as not being easy to use, women identified that they would still use it because of the social influence from the peers and the bosses. This finding suggests that women government employees who obtain external support are more likely to use digital government innovations compared with men who are unlikely to use it even if they were facilitated. The paper recommends that governments of low-income countries like Ethiopia should design appropriate policies that encourage women in digital government.
MISMEASUREMENT OF TFP AND THE MYTH OF PRODUCTIVITY SHOCKS

Changes in measured total factor productivity (TFP) are correlated with changes in real GDP. However, this may be due to measurement error that is correlated with business cycle or true cycles in unobservable true productivity. Using a labor productivity series based on manufacturing workers from 1899 to the present, I am able to address this issue of measurement error. This results in an acyclical productivity series, while measured TFP remains strongly cyclical. While a simulated real business cycle model for the Great Depression with measured TFP shocks matches changes in Real GDP data during the Depression well, the simulation with my alternative productivity series sees no decline in GDP (and even a counterfactual increase in the early 1930s). These findings cast doubt on the importance of productivity shocks in explaining business cycles.
Epidemiological features and spatio-temporal clusters of hand-foot-mouth disease at town level in Fuyang, Anhui Province, China (2008–2013)

Hand-foot-mouth disease (HFMD) is a frequently occurring epidemic and has been an important cause of childhood mortality in China. Given the disease’s significant impact nationwide, the epidemiological characteristics and spatio-temporal clusters in Fuyang from 2008 to 2013 were analysed in this study. The disease exhibits strong seasonality with a rising incidence. Of the reported HFMD cases, 63·7% were male and 95·2% were preschool children living at home. The onset of HFMD is age-dependent and exhibits a 12-month periodicity, with 12-, 24and 36-month-old children being the most frequently affected groups. Across the first 60 months of life, children born in April [relative risk (RR) 8·18], May (RR 9·79) and June (RR 8·21) exhibited an elevated infection risk of HFMD relative to January-born children; the relative risk compared with the reference (January-born) group was highest for children aged 24 months born in May (RR 34·85). Of laboratory-confirmed cases, enterovirus 71 (EV71), coxsackie A16 (Cox A16) and other enteroviruses accounted for 60·1%, 7·1% and 32·8%, respectively. Spatiotemporal analysis identified one most likely cluster and several secondary clusters each year. The centre of the most likely cluster was found in different regions in Fuyang. Implications of our findings for current and future public health interventions are discussed.
JMIR Serious Games A multidisciplinary journal on gaming and gamification for health education/promotion, teaching and social change

Background: Existing research suggests that digital games can be used effectively for educational purposes at any level of training. Perioperative nursing educators can use games to complement curricula, in guidance and staff development programs, to foster team collaboration, and to give support to critical thinking in nursing practice because it is a complex environment. Objective: To describe the process of developing an educational game to set up surgical instruments on the Mayo stand or back table as a resource to assist the instructor in surgical instrumentation training for students and nursing health professionals in continued education. Methods: The study was characterized by applied research in production technology. It included the phases of analysis and design, development, and evaluation. The objectives of the educational game were developed through Bloom’s taxonomy. Parallel to the physical development of the educational game, a proposed model for the use of digital elements in educational game activities was applied to develop the game content. Results: The development of the game called “Playing with Tweezers” was carried out in 3 phases and was evaluated by 15 participants, comprising students and professional experts in various areas of knowledge such as nursing, information technology, and education. An environment was created with an initial screen, menu buttons containing the rules of the game, and virtual tour modes for learning and assessment. Conclusions: The “digital” nursing student needs engagement, stimulation, reality, and entertainment, not just readings. “Playing with Tweezers” is an example of educational gaming as an innovative teaching strategy in nursing that encourages the strategy of involving the use of educational games to support theoretical or practical classroom teaching. Thus, the teacher does not work with only 1 type of teaching methodology, but with a combination of different methodologies. In addition, we cannot forget that skill training in an educational game does not replace curricular practice, but helps. (JMIR Serious Games 2017;5(1):e1) doi:10.2196/games.6048
Demanding or Deferring? The Economic Value of Communication with Attitude

We present and test a formal framework for expressing the idea that taking account of the multiple meanings conveyed by natural language may help economists to better understand the impact of pre-play free-form communication. We model coordination games where each player simultaneously requests others to take a particular action. We assume requests include two independent features: the desired action as well as the request’s “attitude”. We show that, in relation to one-dimensional signals, communication with attitude increases the rate of coordination on actions. We test our model both in Shanghai and Washington D.C. using laboratory implementations of complete information coordination games with pre-play communication. Consistent with our model, we find (i) natural language action requests are made with attitude; (ii) people consider both the requested action and attitude when making action decisions; and (iii) the use of attitude improves coordination. We also find evidence of gender differences. Although males and females recognize and respond to attitude equally well, females are more likely to send more demanding action recommendations than males, while males generally focus more on which action request to send rather than which attitude to use. Our results imply that, when requesting actions of another, it is important to be clear not only about the action but also the attitude with which the request is made. Knowing that transparent attitude can improve economic outcomes can benefit conversational and social media strategies in any social, economic or political environment.
Stressors and Coping Strategies During the Outbreak of Coronavirus Disease 2019 Among Hospital Staff: A Case Study in Iran

Aims: The emergence of COVID-19 disease has created significant stress and anxiety for health care workers. This study aimed to investigate the stressors and coping strategies in the staff of Allameh Bohlool Hospital in Gonabad City, Iran, during the outbreak of the COVID-19 disease. Methods & Materials: This cross-sectional study was performed on 252 employees of Allameh Bohlool Hospital in Gonabad from March 2020 to April 2020. Study tools included a brief form of coping styles (Brief-COPE) and a researcher-made questionnaire of stressors due to the emergence of COVID-19 among health care workers. The obtained data were analyzed using linear regression and ordinal regression models at the significance level of 0.05. Findings: About 74.2%, 69.4%, 52.7%, 52.7%, and 99.2% of the hospital staff had moderate to high stress in the domains of internal, family-social, workplace-related, infection control, and government measures, respectively. The degree of using adaptive and maladaptive coping styles used by staff were 52.0% and 23.8% at the moderate to the high level, respectively. Maladaptive coping styles had a positive and significant relationship with stress intensity so that for each unit increase in maladaptive coping score, the odds of experiencing higher levels of stress increased 1.24 to 1.45 times (P<0.001). Also, the odds of experiencing higher levels of stress in those who had sports activities was 24% to 76% lower (P=0.003). Conclusion: The findings of the present study indicated a high level of stress among hospital staff. Also, the use of maladaptive coping styles and sports activities had a significant positive and negative relationship with stress intensity, respectively. Therefore, designing effective interventions focusing on reducing maladaptive coping patterns among hospital staff and encouraging people to engage in sports activities can help manage stress as much as possible due to the outbreak of COVID-19 disease.
Reduced ice number concentrations in contrails from low aromatic biofuel blends

Abstract. Sustainable aviation fuels can reduce contrail ice numbers and radiative forcing by contrail cirrus. We measured apparent ice emission indices for fuels with varying aromatic content at altitude ranges of 9.1–9.8 km and 11.4–11.6 km. Measurement data were collected during the ECLIF II/NDMAX flight experiment in January 2018. The fuels varied in both aromatic quantity and type. Between a sustainable aviation fuel blend and a reference fuel Jet A-1, a maximum reduction in apparent ice emission indices of 40 % was found. We show vertical ice number and extinction distributions for three different fuels and calculate representative contrail optical depths. Optical depths of contrails (0.5–3 minutes in age) were reduced by 40 to 52 % for a sustainable aviation fuel compared to the reference fuel. Our measurements suggest that sustainable aviation fuels result in reduced ice particle numbers, extinction coefficients, optical depth and climate impact from contrails.
A GENERALIZED PROBABILITY KERNEL ON DIS - CRETE DISTRIBUTIONS AND ITS APPLICATION IN TWO - SAMPLE TEST

We propose a generalized probability kernel(GPK) on discrete distributions with ﬁnite support. This probability kernel, deﬁned as kernel between distributions instead of samples, generalizes the existing discrepancy statistics such as maximum mean discrepancy(MMD) as well as probability product kernels, and extends to more general cases. For both existing and newly proposed statistics, we estimate them through empirical frequency and illustrate the strategy to analyze the resulting bias and convergence bounds. We further propose power-MMD, a natural extension of MMD in the framework of GPK, illustrating its usage for the task of two-sample test. Our work connects the ﬁelds of discrete distribution-property estimation and kernel-based hypothesis test, which might shed light on more new possibilities.
N EURAL SPATIO - TEMPORAL REASONING WITH OBJECT - CENTRIC SELF - SUPERVISED LEARNING

Transformer-based language models have proved capable of rudimentary symbolic reasoning, underlining the effectiveness of applying self-attention computations to sets of discrete entities. In this work, we apply this lesson to videos of physical interaction between objects. We show that self-attention-based models operating on discrete, learned, object-centric representations perform well on spatio-temporal reasoning tasks which were expressly designed to trouble traditional neural network models and to require higher-level cognitive processes such as causal reasoning and understanding of intuitive physics and narrative structure. We achieve state of the art results on two datasets, CLEVRER and CATER, signiﬁcantly outperforming leading hybrid neuro-symbolic models. Moreover, we ﬁnd that techniques from language modelling, such as BERT-style semi-supervised predictive losses, allow our model to surpass neuro-symbolic approaches while using 40% less labelled data. Our results corroborate the idea that neural networks can reason about the causal, dynamic structure of visual data and attain understanding of intuitive physics, which counters the popular claim that they are only effective at perceptual pattern-recognition and not reasoning per se.
Synthesis, characterization and electrochemical study of Mn-doped TiO2 decorated polypyrrole nanotubes

Nanostructured conductive polymers are the growing interest in the field of electrochemistry due to their superior conductivity and environmental friendliness. The existence of transition metal oxides could improve their nanostructure as well as conductive properties. In this study, polypyrrole nanotubes are synthesized in the presence of TiO2 and manganese (Mn)-doped TiO2 nanoparticles (NPs) to investigate their electrochemical properties. Details characterization of the synthesized composites were done by X-Ray diffraction (XRD) and TEM. The TEM analysis shows that doping of TiO2 with Mn decrease the grain size of the TiO2 nanoparticles and successively its effects on the synthesis of the PPy nanotubes (PPyNTs). TEM confirmed that PPyNTs synthesized in the presence of Mn-doped TiO2 are thinner in size compare to the PPyNTs synthesized in presence of pure TiO2. The electrochemical effectiveness of the synthesized PPy nanocomposite was investigated using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). CV and EIS both on a modified glassy carbon electrode reveal the better electron transportability for the Mn-doped TiO2 PPyNTs due to the synergistic effect of doping and decreased the size of PPyNTs as well as increased surface area.
Ionic Liquid Lubrication of Stainless Steel: Friction is Inversely Correlated with Interfacial Liquid Nanostructure

Atomic force microscopy (AFM) is used to measure the friction of a stainless steel surface lubricated with six different ionic liquids (ILs). The measurements reveal that, contrary to expectations, friction and the degree of interfacial ionic liquid nanostructure are inversely correlated. Six ILs were confined between a sharp Si tip and a stainless steel surface, and the friction force was measured as a function of normal load. Trihexyl(tetradecyl)phosphonium bis(trifluoromethane)sulfonamide (P6,6,6,14 TFSI) and trihexyl(tetradecyl)phosphonium bis(2,4,4-trimethylpentyl)phosphinate (P6,6,6,14 (iC8)2PO2) are the most effective lubricants, reducing lateral forces and friction coefficients by up to 3 times compared with the imidazolium-based ILs and the shorter-chained P4,4,4,1 TFSI. Force–separation profiles reveal no obvious interfacial layers for P6,6,6,14 (iC8)2PO2 and P6,6,6,14 TFSI, in contrast to extensive layering for the other ILs. The bulkiness of the [P6,6,6,14]+ cation weakens the electrostatic in.