Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanical and Structural Correlation of Lateritic Soil Road Base Stabilized with Cement and Selected Biochars

The study considers the strength and structural characterization of lateritic soil road base in order to increase the strength of low-volume sealed road construction. Sugar Cane Bagasse Ash (SCBA) and Saw Dust Ash (SDA), mixed with soil and in combination with different percentages of Ordinary Portland Cement (OPC), were utilized in the current study. Structural and mechanical characterization of the investigated samples was performed by X-Ray Fluorescence (XRF), X-Ray Diffraction (XRD), Standard Proctor Test (SPT), Unconfined Compression Strength (UCS) Test, and California Bearing Ratio (CBR) Test. The observed increase in strength may be due to the reduction of mica, quartz, and calcite in the investigated samples. CaO and SiO2 contribute to the development of strength in cement, while SCBA, and SDA-stabilized lateritic soils. The microstructural study revealed that the mica, quartz, and calcite phases play a very important role in maintaining the strength and stability of the investigated samples.
Quantifying changes in the T cell 1 receptor repertoire during thymic 2 development 3

One of the feats of adaptive immunity is its ability to recognize foreign pathogens while 11 sparing the self. During maturation in the thymus, T cells are selected through the binding 12 properties of their antigen-speciﬁc T-cell receptor (TCR), through the elimination of both weakly 13 (positive selection) and strongly (negative selection) self-reactive receptors. However, the impact of 14 thymic selection on the TCR repertoire is poorly understood. Here, we use transgenic Nur77-mice 15 expressing a T-cell activation reporter to study the repertoires of thymic T cells at various stages of 16 their development, including cells that do not pass selection. We combine high-throughput 17 repertoire sequencing with statistical inference techniques to characterize the selection of the TCR 18 in these distinct subsets. We ﬁnd small but signiﬁcant diﬀerences in the TCR repertoire parameters 19 between the maturation stages, which recapitulate known diﬀerentiation pathways leading to the 20 CD4+ and CD8+ subtypes. These diﬀerences can be simulated by simple models of selection acting 21 linearly on the sequence features. We ﬁnd no evidence of speciﬁc sequences or sequence motifs or 22 features that are suppressed by negative selection. These results favour a collective or statistical 23 model for T-cell self non-self discrimination
The effect of speaker reliability on adult cross-situational word learning

Word learning is guided by the statistical co-occurrence between spoken words and potential referents, through which learners gradually map labels to objects across situations. Given that word learning does not occur in a vacuum, rather in a communicative context, it is relevant to evaluate the role that speakers play. Because we do not evaluate the information provided by every person equally, it is reasonable to think that someone who makes lexical errors is not a reliable speaker from whom to learn new words. The current study focuses on speaker reliability in adult cross-situational word learning (CSWL). In two experiments we investigated the extent to which adults attend to the reliability of the speaker and how this affects word learning in a CSWL task. We varied the consistency with which a speaker mapped novel words to familiar objects. We hypothesized (1) that the speakers’ reliability would be judged differently depending on their past object-labeling accuracy, and (2) that new words would be more difficult to learn when presented by an unreliable speaker. Experiment 1 shows that the unreliable speaker was assessed as less reliable, compared to the reliable speaker, but this effect disappeared in Experiment 2, when participants were taught new words by two speakers, a reliable and an unreliable one. Furthermore, we found no evidence to support the hypothesis that being exposed to an unreliable speaker impairs CSWL in adults. We discuss the relevance of these findings and the importance of further research on the role of speaker reliability in CSWL.
Learning robust representation for reinforcement learning with distractions by reward sequence prediction

Reinforcement learning algorithms have achieved remarkable success in acquiring behavioral skills directly from pixel inputs. However, their application in real-world scenarios presents challenges due to their sensitivity to visual distractions (e.g., changes in viewpoint and light). A key factor contributing to this challenge is that the learned representations often suffer from overﬁtting task-irrelevant information. By comparing several representation learning methods, we ﬁnd that the key to alleviating overﬁtting in representation learning is to choose proper prediction targets. Motivated by our comparison, we propose a novel representation learning approach—namely, r eward s equence p rediction (RSP)—that uses reward sequences or their transforms (e.g., discrete time Fourier transform) as prediction targets. RSP can efﬁciently learn robust representations as reward sequences rarely contain task-irrelevant information while providing a large number of supervised signals to accelerate representation learning. An appealing feature is that RSP makes no assumption about the type of distractions and thus can improve performance even when multiple types of distractions exist. We evaluate our approach in Distracting Control Suite. Experiments show that our method achieves state-of-the-art sample efﬁciency and generalization ability in tasks with distractions.
Education, Innovation and Software Production: the contributions of the Reflective Practice in a Software Studio

The growth of the mobile phone market has been generating a great demand for professionals qualified for applications (APPs) development. The required profile includes technical skills, also known as hard skills, and behavioral or soft skills. The training of these professionals in speed, quantity, and quality demanded by the market poses a significant challenge for educational institutions. Apple and PUCPR have established a partnership to build a software studio to develop such talents using the Challenge Based Learning (CBL) method and associated practices whose effects need to be studied. This research aims to analyze the contributions of reflective practice in a software studio to teach the main professional competencies regarding app development, including hard and soft skills. The research method was the case study, based on semi-structured interviews with 28 participants in three cycles. The collected data were analyzed with open and axial coding from Grounded Theory and Atlas.ti tool. The results demonstrate that reflective practice, applied in a software studio environment that uses CBL was able to help students to map new ideas and acquire valuable hard and soft skills. The study pointed out that reflective practice is an effective instrument for developing the skills required by the app market, which demands innovation and quality at high speed.
PACO: Parts and Attributes of Common Objects (Supplementary)

We show sample images obtained by querying the web for “parts of an object category” for different object categories in Fig. 1. We see that the images provide a good vocabulary of parts for each of the objects. Alongside, they also provide clear pointers to the regions of the object the parts correspond to. We use these as reference images for annotators wherever such well defined part images are available from the web. Additionally, we also manually define parts for few objects when the web images aren’t illustrative enough. In such cases, we came up with reasonable names for different regions of an object along with reference images to guide the annotators. Such manually defined parts with sample reference images are shown in Fig. 2 as well. Tab. 1 contains the final taxonomy of parts for the 75 object classes.
The world of organic agriculture: statistics and emerging trends.

Organic agriculture is practiced in 186 countries, and 71.5 million hectares of agricultural land are managed organically by approximately 2.8 million farmers. The global sales of organic food and drink reached more than 96 million euros in 2018. The 21st edition of The World of Organic Agriculture, published by the Research Institute of Organic Agriculture (FiBL) and IFOAM – Organics International, provides a comprehensive review of recent developments in global organic agriculture. It includes contributions from representatives of the organic sector around the world and presents detailed organic farming statistics that cover the area under organic management, specific information about land use in organic systems, the number of farms and other operator types, and selected market data. The book also contains information about the global market for organic food, information on standards and regulations, organic policy, and insights into current and emerging trends in organic agriculture in Africa, Asia, Europe, the Mediterranean, Latin America and the Caribbean, North America, and Oceania. In addition, the volume includes reports about the organic sector in Australia, Canada, the Pacific Islands, and the United States of America and brief updates for various countries in Asia. This book has been produced with the support of the International Trade Centre (ITC), the Swiss State Secretariat for Economic Affairs (SECO), the Coop Sustainability Fund of Coop, and NurnbergMesse. The views expressed herein can in no way be taken to reflect the official opinions of ITC, SECO, or NurnbergMesse. +++ Affiliates of IFOAM – Organics International order the book at a reduced price directly from IFOAM – Organics International . Tel. +49 (0)228 926 50-10+49 (0)228 926 50-10; HeadOffice@ifoam.bio; www.ifoam.bio
Assessment and Prediction of Adherence to Methotrexate Using Three Self-Report Questionnaires in Patients with Rheumatoid Arthritis

Introduction: Methotrexate (MTX) reduces rheumatoid arthritis activity and ameliorates the long-term functional status in these patients. To achieve this aim, patients need to take their medication regularly. Nevertheless, non-adherence to MTX still remains a considerable issue in the management of rheumatoid arthritis. Objective: This study aimed to estimate the adherence to methotrexate in patients with rheumatoid arthritis and to identify specific non-adherence risk factors. Methods: A cross-sectional study included 111 patients (mean age 56.2 ± 10.6 years, 78.4% female, and mean disease duration 6 years (3–13)). Three adherence self-assessment questionnaires were used: the Compliance-Questionnaire-Rheumatology (CQR19), the Medication Adherence Reports Scale (MARS-5), and the Visual Analogue Scale (VAS). We also collected demographic data, disease and treatment characteristics, and anxiety/depression estimation results (Hospital Anxiety and Depression Scale, HADS). Results: Adherence was identified in 48.6% of patients (COR19), 70.3% of patients (MARS-5), and 82.9% of patients (VAS questionnaire). All three questionnaires displayed a significant positive mutual correlation: CQR19 with MARS-5 and VAS (r = 0.364, r = 0.329, respectively, p < 0.001 for both) and between the VAS and MARS-5 scores (r = 0.496, p < 0.001). A significant positive prediction was shown for urban residence (0.347 (0.134–0.901), p = 0.030) using the MARS-5, female sex (0.264 (0.095–0.730), p = 0.010) according to the CQR19, and for a dose of methotrexate (0.881 (0.783–0.992), p = 0.036) using the VAS, while negative predictions were shown for comorbidity number (3.062 (1.057–8.874), p = 0.039) and depression (1.142 (1.010–1.293), p = 0.035) using the MARS-5 and for older age (1.041 (1.003–1.081), p = 0.034) according to the CQR19. The use of steroids was a significant positive predictor in all three questionnaires and remained an independent predictor for methotrexate adherence in the multivariate logistic regression. Conclusions: We showed non-adherence to methotrexate in a significant number of patients using all three questionnaires. Concomitant steroid therapy emerged as an independent positive predictor for adherence.
Characteristics of the 14 April 1999 Sydney Hailstorm Based on Ground Observations, Weather Radar, Insurance Data and Emergency Calls

Hailstorms occur frequently in metropolitan Syd-ney, in the eastern Australian State of New South Wales, which is especially vulnerable due to its building exposure and geographical location. Hailstorms challenge disaster response agencies and pose a great risk for insurance companies. This study focuses on the Sydney hailstorm of 14 April 1999 – Australia's most expensive insured natural disaster, with supporting information from two other storms. Comparisons are drawn between observed hailstone sizes, radar-derived reflectivity and damage data in the form of insurance claims and emergency calls. The " emergency response intensity " (defined by the number of emergency calls as a proportion of the total number of dwellings in a Census Collection District) is a useful new measure of the storm intensity or severity experienced. The area defined by a radar reflectivity ≥55 dBZ appears to be a good approximation of the damage swath on ground. A preferred area for hail damage is located to the left side of storm paths and corresponds well with larger hailstone sizes. Merging hail cells appear to cause a substantially higher emergency response intensity, which also corresponds well to maximum hailstone sizes. A damage threshold could be identified for hailstone sizes around 2.5 cm (1 cm), based on the emergency response intensity (insurance claims). Emergency response intensity and claims costs both correlate positively with hailstone sizes. Higher claim costs also occurred in areas that experienced higher emergency response intensities .
The combined use of shade-cloth covers and monolayers to prevent evaporation in irrigation reservoirs

One of the most efficient techniques to prevent evaporation is suspended shade covers, reported to reduce evaporation up to 85%, although at considerable cost. Another option is the application of a chemical monolayer which creates a film over the water surface that can reduce evaporation, but performance of these is limited by environmental exposure. In this study, a detailed trial was conducted in southern Queensland (Australia) to assess the benefits of the combined use of monolayers and shade-cloth covers. Three experimental tanks were monitored to measure evaporation, water temperature profile and the meteorological factors driving evaporative demand. Tanks 1 and 2 were covered with a black polyethylene mesh; a monolayer was added to Tank 2; and Tank 3 was uncovered and used as a control. The comparison of Tanks 1 and 2 with Tank 3 provided the evaporation reduction factors. The differences between the reduction factors of Tanks 2 and 3 allowed assessment of the performance of the combination of the two evaporation-suppression methods.
ImageAlly: A Human-AI Hybrid Approach to Support Blind People in Detecting and Redacting Private Image Content

Many people who are blind take and post photos to share about their lives and connect with others. Yet, current technology does not provide blind people with accessible ways to handle when private information is unintentionally captured in their images. To explore the technology design in supporting them with this task, we developed a design probe for blind people — ImageAlly — that employs a human-AI hybrid approach to detect and redact private image content. ImageAlly notifies users when potential private information is detected in their images, using computer vision, and enables them to transfer those images to trusted sighted allies to edit the private content. In an ex-ploratorystudywithpairs ofblindparticipants andtheirsighted allies,wefoundthatblindpeoplefeltempoweredbyImageAlly topreventprivacyleakageinsharingimagesonsocialmedia. They also found other benefits from using ImageAlly, such as potentially improving their relationship with allies and giving allies the awareness of the accessibility challenges they face.
1 Balancing the information gain against the movement cost for multi-robot frontier exploration

This article investigates the scenario where a small team of robots needs to explore a hypothetical disaster site. The challenge faced by the robot-team is to coordinate their actions such that they efficiently explore the environment in their search for victims. A popular paradigm for the exploration problem is based on the notion of frontiers: the boundaries of the current map from where robots can enter yet unexplored area. Coordinating multiple robots is then about intelligently assigning frontiers to robots. Typically, the assignment of a particular frontier to a particular robot is governed by a cost measure, e.g. the movement costs for the robot to reach the frontier. In more recent approaches these costs are traded off with the potential gain in information if the frontier would be explored by the robot. In this paper we will further investigate the effect of balancing movement costs with information gains while assigning frontiers to robots. In our experiments we will illustrate how various choices for this balance can have a significant impact on the exploratory behavior exposed by the robot team.
Shamed and Able: How Firms Respond to Information Disclosure

We examine how firms respond to third-party ratings of their corporate environmental activities. Using insights from institutional theory, we hypothesize that ratings are particularly likely to spur responses from firms whose legitimacy is threatened—and thus are shamed—by these ratings. We extend existing theory by drawing on the strategic choice perspective to hypothesize that the greatest performance improvements will be exhibited by those shamed firms that face lower-cost opportunities to improve—and thus are particularly able to respond. We take advantage of a natural experiment, when a major social rating agency expanded the scope of its ratings, to empirically test these hypotheses in the context of environmental ratings and environmental performance of more than 650 firms in the United States. We find empirical evidence that supports our hypotheses, and present implications for theory and public policy.
Estimating Heterogeneous Treatment Effects: Mutual Information Bounds and Learning Algorithms

Estimating heterogeneous treatment effects (HTE) from observational studies is rising in importance due to the widespread accumulation of data in many fields. Due to the selection bias behind the inaccessibility of counterfactual data, the problem differs fundamentally from supervised learning in a challenging way. However, existing works on modeling selection bias and corresponding algorithms do not naturally generalize to non-binary treatment spaces. To address this limitation, we propose to use mutual information to describe selection bias in estimating HTE and derive a novel error bound using the mutual information between the covariates and the treatments, which is the first error bound to cover general treatment schemes including multinoulli or continuous spaces. We then bring forth theoretically justified algorithms, the Mutual Information Treatment Network (MitNet), using adversarial optimization to reduce selection bias and obtain more accurate HTE estimations. Our algorithm reaches remarkable performance in both simulation study and empirical evaluation.
correlation of 18 F-fluoroethyl tyrosine positron-emission tomography uptake values and histomorphological findings by stereotactic serial biopsy in newly diagnosed brain tumors using a refined software tool

Background: Magnetic resonance imaging (MRI) is the standard neuroimaging method to diagnose neoplastic brain lesions, as well as to perform stereotactic biopsy surgical planning. MRI has the advantage of providing structural anatomical details with high sensitivity, though histological specificity is limited. Although combining MRI with other imaging modalities, such as positron-emission tomography (PET), has proven to increment specificity, exact correlation between PET threshold uptake ratios (URs) and histological diagnosis and grading has not yet been described. Objectives: The aim of this study was to correlate exactly the histopathological criteria of the biopsy site to its PET uptake value with high spatial resolution (mm 3 ), and to analyze the diagnostic value of PET using the amino acid O -(2-[ 18 F]fluoroethyl)- l -tyrosine ( 18 F-FET) PET in patients with newly diagnosed brain lesions in comparison to histological findings obtained from stereotactic serial biopsy.
Robust planning for heterogeneous UAVs in uncertain environments

Future Unmanned Aerial Vehicle (UAV) missions will require the vehicles to exhibit a greater level of autonomy than is currently implemented. While UAVs have mainly been used in reconnaissance missions, future UAVs will have more sophisticated objectives, such as Suppression of Enemy Air Defense (SEAD) and coordinated strike missions. As the complexity of these objectives increases and higher levels of autonomy are desired, the command and control algorithms will need to incorporate notions of robustness to successfully accomplish the mission in the presence of uncertainty in the information of the environment. This uncertainty could result from inherent sensing errors, incorrect prior information, loss of communication with teammates, or adversarial deception. This thesis investigates the role of uncertainty in task assignment algorithms and develops robust techniques that mitigate this effect on the command and control decisions. More specifically, this thesis emphasizes the development of robust task assignment techniques that hedge against worst-case realizations of target information. A new version of a robust optimization is presented that is shown to be both computationally tractable and yields similar levels of robustness as more sophisticated algorithms. This thesis also extends the task assignment formulation to explicitly include reconnaissance tasks that can be used to reduce the uncertainty in the environment. A Mixed-Integer Linear Program (MILP) is presented that can be solved for the optimal strike and reconnaissance mission. This approach explicitly considers the coupling in the problem by capturing the reduction in uncertainty associated with the reconnaissance task when performing the robust assignment of the strike mission. The design and development of a new addition to a heterogeneous vehicle testbed is also presented. Thesis Supervisor: Jonathan P. How Title: Associate Professor