Miracle-dz/UniFAR-FTUs huggingface dataset:
Ultrafast excitonic dynamics in DNA: Bridging correlated quantum dynamics and sequence dependence

After photo-excitation of DNA, the excited electron (in the LUMO) and the remaining hole (in the HOMO) localized on the same DNA base form a bound pair, called the Frenkel exciton, due to their mutual Coulomb interaction. In this study, we demonstrate that a tight-binding (TB) approach, parametrized by ab initio data, allows to correlate relaxation properties, average charge separation, and dipole moments to a large ensemble of double-stranded DNA sequences (all 16,384 possible sequences with 14 nucleobases). This way, we are able to identify a relatively small sub-ensemble of sequences responsible for long-lived excited states, high average charge separation, and high dipole moment. Further analysis shows that these sequences are particularly T-rich. By systematically screening the impact of electron-hole interaction (Coulomb forces), we verify that these correlations are relatively robust against finite-size variations of the interaction parameter, not directly accessible experimentally. This methodology combines simulation methods from quantum physics and physical chemistry with statistical analysis known from genetics and epigenetics, thus representing a powerful bridge to combine information from both fields.
Probing Multimodal Large Language Models for Global and Local Semantic Representation

The advancement of Multimodal Large Language Models (MLLMs) has greatly accelerated the development of applications in understanding integrated texts and images. Recent works leverage image-caption datasets to train MLLMs, achieving state-of-the-art performance on image-to-text tasks. However, there are few studies exploring which layers of MLLMs make the most effort to the global image information, which plays vital roles in multimodal comprehension and generation. In this study, we find that the intermediate layers of models can encode more global semantic information, whose representation vectors perform better on visual-language entailment tasks, rather than the topmost layers. We further probe models regarding local semantic representations through object recognition tasks. We find that the topmost layers may excessively focus on local information, leading to a diminished ability to encode global information. Our code and data are released via https://github.com/kobayashikanna01/probing_MLLM_rep.
Aerodynamic Prediction of a CRM High-lift Configuration using a modified three equation turbulence mode

Aerodynamic simulations were carried out in the study presented in this paper focusing on the stall performance of the High-Lift Common Research Model obtained from the fourth AIAA High-Lift Prediction Workshop. Various turbulence models of Reynolds-average Navier-Stokes simulations are analyzed. A modified version of the transitional k-(v^2 )-{\omega} model developed to enhance stall prediction accuracy for high-lift configurations with a nacelle chine. The vortex generator, three-element airfoil, and high-lift model are numerically simulated. The results reveal that implementing a k-(v^2 )-{\omega} model with separation shear layer fixed notably enhances the stall prediction behavior for both the three-element airfoil and high-lift configuration without affecting the prediction of the vortex strength of a vortex generator. Moreover, incorporating rotation correction into the SPF k-(v^2 )-{\omega} model improves the prediction of vortex strength and further enhances stall prediction for the high-lift configuration. The relative error in predicting the maximum lift coefficient is less than 5% of the experimental data. The study also investigated the impact of the nacelle chine on the stall behavior of the high-lift configuration. The results demonstrate that the chine vortex can mitigate the adverse effects of the nacelle/pylon vortex system and increase the maximum lift coefficient.
HISTORICAL PRECIPITATION TRENDS AND FUTURE PRECIPITATION PROJECTIONS USING A STOCHASTIC WEATHER GENERATOR IN THE NORTHEASTERN UNITED STATES

According to the 2014 National Climate Assessment, annual rainfall has increased by approximately 10% from 1895 to 2011, and extreme precipitation events (the top 1% of all storms) have increased 70% since 1958 in the Northeast United States [Melillo et al., 2014]. These precipitation changes could have substantial impacts on the performance of bridges, stormwater drainage, pavement, water supply systems, and numerous other infrastructure projects. This study examines historical changes in Northeast rainfall and develops a computer model to simulate future precipitation. Historical precipitation trends were calculated for rainfall duration, depth, intensity and time between storms for 20 weather stations across the Northeast. In general, annual rainfall depth and intensity have increased over the past 50 years, while the annual time between storms has decreased over the same period. These changes differed among seasons. Winter storms have become shorter and more frequent. Summer storms have become longer and less frequent. Future precipitation at LaGuardia Airport was simulated using a three-step weather generation model. A generalized linear model was used to capture the seasonal pattern of precipitation occurrence. Events were identified as one of four storms types and simulated using a Markov Chain switching model. Precipitation intensity was simulated using a hybrid distribution, consisting of the Gamma and Generalized Pareto distributions, capable of capturing both mean and extreme rainfall events. The model projected annual rainfall increases, with especially large increases in winter precipitation. The frequency of extreme storms, exceeding the 97.5th percentile, was projected to increase substantially. Design storms, the two, 50 and 100 year storm depths, had limited change. This study shows that precipitation timing and intensity has changed in the past, and will likely continue to change in the future. Weather generators provide a means to understand the impacts from changing precipitation patterns beyond single extreme events. Their application can be used to determine the effectiveness and resiliency of existing infrastructure and to identify appropriate adaptation measures.
A Curious Case of Remarkable Resilience to Gradient Attacks via Fully Convolutional and Differentiable Front End with a Skip Connection

We tested front-end enhanced neural models where a frozen classifier was prepended by a differentiable and fully convolutional model with a skip connection. By training them using a small learning rate for about one epoch, we obtained models that retained the accuracy of the backbone classifier while being unusually resistant to gradient attacks including APGD and FAB-T attacks from the AutoAttack package, which we attributed to gradient masking. The gradient masking phenomenon is not new, but the degree of masking was quite remarkable for fully differentiable models that did not have gradient-shattering components such as JPEG compression or components that are expected to cause diminishing gradients. Though black box attacks can be partially effective against gradient masking, they are easily defeated by combining models into randomized ensembles. We estimate that such ensembles achieve near-SOTA AutoAttack accuracy on CIFAR10, CIFAR100, and ImageNet despite having virtually zero accuracy under adaptive attacks. Adversarial training of the backbone classifier can further increase resistance of the front-end enhanced model to gradient attacks. On CIFAR10, the respective randomized ensemble achieved 90.8$\pm 2.5$% (99% CI) accuracy under AutoAttack while having only 18.2$\pm 3.6$% accuracy under the adaptive attack. We do not establish SOTA in adversarial robustness. Instead, we make methodological contributions and further supports the thesis that adaptive attacks designed with the complete knowledge of model architecture are crucial in demonstrating model robustness and that even the so-called white-box gradient attacks can have limited applicability. Although gradient attacks can be complemented with black-box attack such as the SQUARE attack or the zero-order PGD, black-box attacks can be weak against randomized ensembles, e.g., when ensemble models mask gradients.
Factors associated with land transport accidents in the State of Espírito Santo

Objective: Verify the factors associated with the land transport accidents victims assisted by the Mobile Urgency Care Service in the state of Espírito Santo. Methods: Cross-sectional study with retrospective data collection from a sample of 2,502 pre-hospital printed care reports from Mobile Urgency Care Service in 2015, of these, 438 were victims of land transport accidents. Information was collected regarding: sex, age, life cycle, ethyl breath, vehicle involved, severity of trauma and outcome of the occurrence. Severity was established using the Revised Trauma Scale. Chi-square test was performed. Results: Land transport accidents represented 50.2% of the external causes victims assisted. Most of the victims were male (73.7%), adults (81.9%), had no ethyl breath (88.8%) and victims of minor trauma (95.3%). The Motorcycle was the vehicle most frequently involved (56.1%). It was found as factors associated (p <0.05) with the type of land transport accident: life cycle (adult and collision; elderly and run overs), vehicle (automobile - run over and collision; motorcycle and bicycle - falling) and severity of trauma (major and run over; minor and fall). Conclusion: The data reveals the main factors associated with land transport accidents, guiding the pre-hospital care to these occurrences. It is necessary to intensify specific educational measures for each risk group.
Diﬀerentially private SGD with random features

In the realm of large-scale machine learning, it is crucial to explore methods for reducing computational complexity and memory demands while maintaining generalization performance. Additionally, since the collected data may contain some sensitive information, it is also of great signiﬁcance to study privacy-preserving machine learning algorithms. This paper focuses on the performance of the diﬀerentially private stochastic gradient descent (SGD) algo-rithm based on random features. To begin, the algorithm maps the original data into a low-dimensional space, thereby avoiding the traditional kernel method for large-scale data storage requirement. Subsequently, the algorithm iteratively optimizes parameters using the stochastic gradient descent approach. Lastly, the output perturbation mechanism is employed to introduce random noise, ensuring algorithmic privacy. We prove that the proposed algorithm satisﬁes the diﬀerential privacy while achieving fast convergence rates under some mild conditions.
Underlying Factors in Students' Attitudes Towards Mathematics: A Factor Analysis and Its Educational Implications

, resaltando la naturaleza multifacética de las actitudes hacia esta disciplina. El análisis subraya que una relación positiva con el docente y una autopercepción favorable son elementos esenciales para promover actitudes positivas. Estos aspectos podrían ser tenidos en cuenta al diseñar intervenciones pedagógicas futuras. El estudio proporciona una perspectiva multidimensional de las actitudes hacia las matemáticas, ofreciendo un fundamento para futuras investigaciones. Es esencial explorar cómo estos factores identificados pueden influir y optimizar la experiencia educativa en matemáticas de los estudiantes.
East African Journal of Agriculture and Biotechnology

This study examines the accessibility of interactive radio-based agricultural information for women crop farmers in Dodoma City, Tanzania. With a focus on face-to-face interviews, supplemented by Focus Group Discussions (FGDs) and key informant interviews, the research involved 32 purposively selected individual participants. The study uses content analysis to unveil a limited interaction between radio programmers and women crop farmers in Dodoma City. Identified barriers include a scarcity of radios and mobile phones, absence of electricity for device charging, domestic responsibilities, fear of spousal disapproval, non-contact by programmers, voucher purchase costs
KOF Working Papers

Unionists and politicians frequently claim that globalization lowers employment protection of workers. This paper tests this hypothesis in a panel of 28 OECD countries from 1985 to 2003, differentiating between three dimensions of globalization and two labor market segments. While overall globalization is shown to loosen protection of the regularly employed, it increases regulation in the segment of limited-term contracts. We find the economic one to drive deregulation for the regularly employed, but the social one to be responsible for the better protection of workers in atypical employment. We offer political economy arguments as explanations for these differential effects. JEL Codes: C33, F15, F16, J81, J83, O57.
KOF Working Papers

This paper exploits Switzerland’s federal drug dispensation legislation to study the effect of different dispensing systems on the utilization of pharmacies. We enrich pharmacy level survey data with geo spatial information to assess the effect of dispensing physicians on utilization of pharmacies while controlling for chain affiliation, opening hours, socio-economic environment of a pharmacy as well as the number of pharmacies nearby. We find that pharmacies in regions that allow physicians to dispense drugs, face a decline in drug related revenue of more than 15 percent while revenue with non-drugs are almost 40 percent higher than in nonself-dispensing regions. These findings are particularly striking given that they come on top of long established, massive structural differences in the number of pharmacies per capita across regions with differing dispensation systems.
An Estimation of Digital Learning Culture Index of Secondary Education in Nigeria

The socioeconomic vulnerability of youths in developing economies is a challenge that can be mitigated by quality education and digital learning skills. However, it is increasingly demanding for developing economies still struggling with universal access to preadult education to provide their youths with quality education. Mitigating this challenge, therefore, will require a social reengineering of the educational system of developing economies. Critical to this, reengineering is a comprehensive appraisal of their educational system ’ s support for digital learning. We set two objectives for this study: (i) examine the digital learning culture (DLC) of secondary education in Nigeria — a typical developing economy and (ii) estimate the digital learning culture index (DLCI) of secondary education in readiness for a lifelong learning skill among the Nigerian youths. Data were collected using the questionnaire survey and the strati ﬁ ed random sampling technique. A total of 2,107 students ’ questionnaire feedback and 666 secondary schoolteachers ’ questionnaire feedback at all secondary education levels across communities in the six geopolitical zones of Nigeria were analyzed. The DLCI of secondary education in Nigeria has been estimated to be 0.21. The results revealed two key ﬁ ndings: (1) evidence of sharp divides in DLC of secondary education among the communities in Nigeria and (2) statistical evidence that secondary education in the North-East zone of Nigeria has a higher DLCI than all other zones in the country except for the South-East zone.
Residual incidence of pesticides in vegetable products sold in southern Brazil

Pesticide use is a widespread practice in agricultural production for pest control. The use of these products must adopt Good Agricultural Practices; therefore, the food is expected to be according to the current parameters. For this, the National Program for the Control of Residues and Contaminants of the Ministry of Agriculture and Livestock created a diagnosis of the products’ quality. In this way, the program carried out pesticide analyses to evaluate the conformity of products of plant origin. From the analyzed products, fruits with broad commercialization and production in a state with more analyses were segregated. Based on these data, the banana, potato, apple, tomato, and grape results in the Rio Grande do Sul state (Southern Brazil) were analyzed and interpreted. This survey was conducted from 2016 to 2020, and data were compiled to assess the conformity of fresh vegetables. Samples with residual levels of pesticides above the maximum reference limit for the crop or with residual not allowed for the crop no-tolerance were considered non-conformance. The overall compliance rate for the highlighted vegetables was greater than 95%. The data were similar to countries with rigorous monitoring and application standards for this chemical hazard. Most of the non-conformities occurred due to the presence of residues above the maximum reference limit for the crop, especially due to the presence of insecticides from the chemical groups organophosphates and pyrethroids. These results show that food produced and consumed in Brazil has quality characteristics similar to those in developed countries. Illustrating that the food consumed by the population is safe. To obtain better results, technical assistance to farmers is essential, aiming to reduce the incidence of residues above the Maximum Limit for the crop.
Research Paper Relationship Between Health Literacy and Addiction Susceptibility in High School Adolescents

and among its subscales, “showing off” with a mean score of 33.09±32.64 and “family dissatisfaction” with 19.75±35.47 had the highest and lowest mean scores, respectively. Health literacy and its dimensions had a negative correlation with addiction susceptibility (P<0.001). Conclusion: According to the findings, it is recommended to use appropriate strategies to increase adolescent health literacy by health service providers, school officials, school health nurses, and teachers. The results of this study can be used as a source for further research on addiction and health literacy in adolescents.
Validation of the Tranquillity Rating Prediction Tool (TRAPT): comparative studies in UK and Hong Kong

Abstract The Tranquillity Rating Prediction Tool (TRAPT) has been used to make predictions of the quality of tranquility in outdoor urban areas using two significant factors i.e. the average level of anthropogenic noise and the percentage of natural features in view. The method has a number of applications including producing tranquillity contours that can inform decisions regarding the impact of new anthropogenic noise sources or developments causing visual intrusion. The method was intended for use in mainly outdoor areas and yet was developed using responses from UK volunteers to video clips indoors. Because the volunteers for this study were all UK residents it was important to calibrate responses for other ethnic groups who may respond differently depending on cultural background. To address these issues further studies were performed in Hong Kong using the same video recording played back under the same conditions as the study in the UK. The HK study involved recruiting three groups i.e. residents from Hong Kong, Mainland China and a diverse group from 16 different nations. There was good agreement between all these groups with average tranquillity ratings for the different locations differing by less than one scale point in most cases.
The Potential of Digital Nature on Mental Health and Environmental Learning: Opportunities and Challenges

Digital technologies have revolutionized the way we interact with the world, blurring the lines between the physical and digital realms. This manuscript delves into the transformative potential of these technologies in bridging the gap between humans and nature. Specifically, we focus on the evolution of digital technologies and their role in enhancing well-being through a closer connection with nature. By exploring various applications, from mobile apps to immersive VR environments, this chapter discusses the potential psychological benefits of digital nature experiences. We also examine implications for future technological advancements and nature conservation strategies, emphasizing the balance between technological progress and natural harmony.
Stratigraphic and palaeoecological evidence for late medieval to early modern peat extraction from bogs in Het Gooi (Western Netherlands)

Abstract In the Monnikenberg estate, built in the mid-19th century in a Pleistocene coversand area to the south of Hilversum (the Netherlands), a depression with a small man-made mire was found to contain the remains of a complex peaty fill of a larger mire. Microfossil study and radiocarbon dating showed that its development started at the beginning of the third millennium BC through water stagnation on a podzol in combination with a high groundwater level, and about two millennia ago the vegetation had progressed from a mesotrophic mire to an ombrotrophic bog. Such origin, development and age are in conformity with the results for some other recently studied mires in the Het Gooi region (Gijzenveen; Van Geel et al., 2016). In the Monnikenberg mire, a discrepancy was found between the radiocarbon age of the upper part of the peaty fill and its clearly medieval or younger age as evidenced by its microfossil content, notably the occurrence of pollen of buckwheat (Fagopyrum) and cornflower (Centaurea cyanus). These species were first introduced in the Netherlands during the late Middle Ages. From further observations in a large pit in the former border zone of the mire, it is concluded that this discrepancy and the unique sedimentary structures, observed in this pit, result from peat exploitation and contemporary reworking of its sandy overburden during the Late Middle Ages or Early Modern Times. This is the first evidence for local early peat exploitation for such mires in Het Gooi. The results underpin the importance of microfossil analyses for proper interpretation of radiocarbon data, when studying mire fills. Additionally, they provide further proof for the development of podzols and ericaceous vegetation prior to and independent of early prehistoric agriculture in the Dutch Pleistocene coversand areas, and for the early (pre-medieval) start of wind erosion and deposition of drift sands.