Miracle-dz/UniFAR-FTUs huggingface dataset:
Structure-property correlation of an impact- modified random polypropylene copolymer

The combination of rheological and interfacial properties is utilized in this work to explain the thermal and mechanical properties of a random polypropylene copolymer (RPP) toughened with an ethylene-propylene copolymer (EPR). RPP/EPR blends are directly prepared by injection molding. The EPR exhibits higher viscosity in comparison with the RPP over the evaluated shear rate, while the RPP/EPR blends show similar viscosities at high shear rates. The interfacial properties indicate a strong interaction between the RPP and EPR domains. Differential scanning calorimetry analyses indicate that the EPR does not act as a nucleating agent for the RPP, with the RPP crystallinity only decreasing at high EPR contents, suggesting that the EPR can modify the RPP crystallite size. Scanning electron micrographs of the blends demonstrate a ductile fracture surface, indicating that EPR can increase the RPP tenacity. The RPP impact strength is improved by up to 102% in the RPP/EPR 90/10 wt. % blend, while the RPP deformation at break is increased from 183% to 246% after the incorporation of 10% EPR. The tensile strengths of the RPP and RPP/EPR blends are very similar, indicating that the RPP achieves a good balance between stiffness and toughness after being blended with the EPR.
Causal Inference with Complex Data Structures and Non-Standard Effects

Many modern problems in causal inference have non-trivial complications beyond the classical settings of randomized trials, parametric models, and average treatment effects.Despite their inherent complexities, many recent questions in causal inference are still tackled via overly simplified methods and data structures. My thesis is dedicated to overcoming some of these methodological limitations of classical causal inference, aiming to bridge the gapbetween methodological development and practice, by effectively harness advanced machine learning tools. My work can be categorized into the following three sub-topics.a. ) Stochastic interventions for general longitudinal data. We generalize novel "incremental" intervention effects to accommodate subject dropout in longitudinal studies. Ourmethods do not require positivity or parametric assumptions, and are less sensitive to the curse of dimensionality. We present efficient nonparametric estimators, showing that they converge at √ n rates and yield uniform inferential guarantees. Importantly, we argue that incremental effects are much more efficient than conventional deterministic effects in a novel infinite time horizon setting, where the number of timepoints can grow to infinity. b. ) Causal effects based on distributional distances. We have proposed a novel nonstandard causal effect based on the discrepancy between unobserved counterfactual distributions(i.e., L1 distance), in order to provide more nuanced and valuable information about treatment effects than simple mean shifts. We consider single- and multi-source randomized studies, as well as observational studies, and analyze error bounds and asymptotic properties of the proposed estimators. Special difficulties arise due to the non-smoothness of the L1 distance functional. c. ) Causal clustering. We give a novel adaptation of unsupervised learning methods for analyzing treatment effect heterogeneity. Specifically, we pursue an efficient way touncover subgroup structure in conditional treatment effects by leveraging tools in clustering analysis. We find conditions under which k-means, density-based, and hierarchical clustering algorithms can be successfully adopted into our framework. For k-means causal clustering, we develop a novel estimator that attains fast convergence rates and asymptotic normality of the cluster centers, even under weak nonparametric conditions on nuisance function estimation. Unlike previous studies, our framework can be easily extended to outcome-wide studies.
Impact of Dual Substrate Limitation on Biodenitrification Modeling in Porous Media

In this work, we consider a model of the biodenitrification process taking place in a spatially-distributed bioreactor, and we take into account the limitation of the kinetics by both the carbon source and the oxidized nitrogen. This model concerns a single type of bacteria growing on nitrate, which splits into adherent bacteria or free bacteria in the liquid, taking all interactions into account. The system obtained consists of four diffusion-convection-reaction equations for which we show the existence and uniqueness of a global solution. The system is approximated by a standard finite element method that satisfies an optimal a priori error estimate. We compare the results obtained for three forms of the growth function: single substrate limiting, “multiplicative” form, and “minimum” form. We highlight the limitation of the ‘ single substrate limiting model”, where the dependency of the bacterial growth on the nitrate is neglected, and find that the “minimum” model gives numerical results closer to the experimental results.
A systematic review of participatory scenario planning to envision mountain social-ecological systems futures

Mountain social-ecological systems (MtSES) provide crucial ecosystem services to over half of humanity. However, populations living in these highly varied regions are now confronted by global change. It is critical that they are able to anticipate change to strategically manage resources and avoid potential conflict. Yet, planning for sustainable, equitable transitions for the future is a daunting task, considering the range of uncertainties and the unique character of MtSES. Participatory scenario planning (PSP) can help MtSES communities by critically reflecting on a wider array of innovative pathways for adaptive transformation. Although the design of effective approaches has been widely discussed, how PSP has been employed in MtSES has yet to be examined. Here, we present the first systematic global review of singleand multiscalar, multisectoral PSP undertaken in MtSES, in which we characterize the process, identify strengths and gaps, and suggest effective ways to apply PSP in MtSES. We used a nine-step process to help guide the analysis of 42 studies from 1989 screened articles. Our results indicate a steady increase in relevant studies since 2006, with 43% published between 2015 and 2017. These studies encompass 39 countries, with over 50% in Europe. PSP in MtSES is used predominantly to build cooperation, social learning, collaboration, and decision support, yet meeting these objectives is hindered by insufficient engagement with intended end users. MtSES PSP has focused largely on envisioning themes of governance, economy, land use change, and biodiversity, but has overlooked themes such as gender equality, public health, and sanitation. There are many avenues to expand and improve PSP in MtSES: to other regions, sectors, across a greater diversity of stakeholders, and with a specific focus on MtSES paradoxes. Communicating uncertainty, monitoring and evaluating impacts, and engendering more comparative approaches can further increase the utility of PSP for addressing MtSES challenges, with lessons for other complex social-ecological systems.
Spread of Svalbard Glacier Mass Loss to Barents Sea Margins Revealed by CryoSat‐2

The Norwegian Arctic archipelago of Svalbard is located in the most rapidly warming area of the Arctic, at the interface of Arctic and Atlantic air and ocean masses. The presence of a large number of surge‐type glaciers and the potential for rapid changes in surface mass balance and ice dynamics necessitates regularly updated mass balance assessment. This study uses swath processing of CryoSat‐2 SARIn mode data to obtain glacier elevations for 2011–2017. Individual elevation estimates are collected into 1‐km2 grid cells, and a least squares plane‐fitting technique is used to calculate rates of elevation change, with residuals being used to reveal the temporal pattern. A 7‐year rate of mass change of −16.0 ± 3.0 Gt a−1 is estimated (equivalent to 0.044 mm a−1 of global sea level rise), of which −11.0 Gt a−1 results from the melt and dynamic thinning of nonsurging ice and −5.0 Gt a−1 results from surges. This compares to ‐3.4 Gt a−1 previously estimated using ice, cloud, and land elevation satellite (ICESat) (2003–2008). The west coast remains a major contributor to mass loss from nonsurging ice in the archipelago, with mass loss increasing from areas bordering the Barents Sea. Sea ice concentration and climate reanalysis data sets show ocean and lower atmospheric warming and sea ice decline in this region, likely contributing to enhanced glacier melt and discharge.
The Image Segmentation Based On K-Means With MAP

A major feature of quantitative cell biology is the identification of various cell compartments, cell types and their relationship. Automating of this problem has proven non-trivial, however, and it involves the object of multi-class image partition tasks that are difficult due to the high similarity of objects from various groups and irregularly found structures. To overcome this problem purpose, we propose k-means image segmentation method. And also in the current implementation of the proposed algorithm, the overall segmentation performance of the method can be confined by the graph generation quality. So the future work can be the development of a Maximum Posterior (MAP) estimation for graph generation that optimizes the graph structure jointly with label inference. On the other hand, it is valid to mentioning that the small margin of improvement by the proposed graph based spliting over segnet is because features learned by the CNN are minimizing the cost function rather than the cost function of the polytree.
Design of Logistic Transporter Robot System

The diversity of technology in the robotics world is currently developing a lot, especially in logistics distribution. The distribution of logistics goods using robotic power continues to develop towards high artificial intelligence, ensuring warehouse delivery management and intelligence implementation with challenging tasks. Autonomous robots are a community of intelligent robotic systems that can be seen as prototypes. It is an intelligent management and service system of the future that can reveal some important traits of the next generation of smart robot communities. In the smart logistics industry, designing an efficient communication and management platform from logistics robots is one of the fundamental problems. This study aims to implement smart robots in assisting distribution / logistical activities by following humans in bringing goods to the intended area by following green objects.
Nature and significance of rift-related, near-surface fissure-fill networks in fractured carbonates below regional unconformities

Fissure-fill networks are a widely recognized, but relatively little described, near-surface phenomenon (<1–2 km) hosted in carbonate and crystalline basement rocks below regional unconformities. Faults and fractures in otherwise tight Devonian carbonate basement rocks of the Tor Bay region, Devon, SW England are associated with the development of millimetre- to decametre-wide fissures containing red-coloured early Permian sedimentary material, vuggy calcite mineralization and wall rock collapse breccia. These features preserve evidence about the style and history of fault deformation and reactivation in near-surface settings and on fluid-related processes, such as elutriation and/or mineralization. Field observations, palaeostress analysis and fracture topology analyses show that the rift-related faults and fractures created a network of long-lived open cavities during the development of the Portland–Wight Basin in the early Permian. Once formed, they were subjected to episodic, probably seismically induced, fluid fluxing events and local karstification. The large, well-connected networks of naturally propped fractures were (and possibly still are) important fluid migration pathways within otherwise low-permeability host rocks. These structures are probably equivalent to those observed in many other rift-related, near-surface tectonic settings and suggest that the Tor Bay outcrops can be used as a global analogue for sub-unconformity open fissure systems hosted in low-permeability basement rocks. Supplementary material: Appendix A is available at https://doi.org/10.6084/m9.figshare. c.5023103
Requesting and Refusing Politeness Expression Teacher’s Instruction in Teaching Learning Process

This research conducted to describe the request and refusal polite expression when teacher instruct students. The writer has chosen English teacher and the object is 1 teacher. The writer joins in the class and records the activities when teachers teach students. The data analyzed by using qualitative method. The types of politeness are based on the Brown and Levinson’s theory about politeness strategy that should people use when they instruct others. There are 24 male students and 30 female students who are follow this research. The research instrument to collect the data is through observation the conversation during learning and teaching process. All the utterances relate to politeness strategy produced by the students and teacher write down and 2 conversations are chose to be analyzed based on politeness strategies The result of this research shows that there are three types of instructional activities; motivating students (1 expression), informing students of objective (1 expression), helping students recall prerequisites (1 expression), presenting information and example (1 expression) and providing practice and feedback (7 expressions). Teacher used four types of them, Bald on Record (4 expressions), Positive Politeness (16 expressions), Negative Politeness (6 expressions), and off- record (2 expressions). There are 3 expressions are polite requests and no impolite refusal. From that result, the writer concludes that teacher often to use Positive Politeness by reasoning that it types of politeness strategy is to make the relationship between teacher and students more intimate during teaching learning process. This research can lead other researcher to conduct research on Politeness strategy. It also can lead the teachers and the students to make a good interaction by applying the politeness strategy in the classroom so that they can maintain a good communication one another
Morphological and molecular identification of seahorses (Hippocampus spp.) from the coast of Sumatra Island, Indonesia

Hanifaturahmah F, Perwitasari-Farajallah D, Butet NA, Nurilmala M, Sudrajat AO, Ochiai Y. 2020. Morphological and molecular identification of seahorses (Hippocampus spp.) from the coast of Sumatra Island, Indonesia. Biodiversitas 21: 4116-4123. Seahorses (Hippocampus spp.) species are difficult to be identified based on their color, shape, and body size, especially for their juveniles. The purposes of this study were to identify seahorse species from Indonesian waters (Riau Islands and Lampung, Sumatra Island) based on the sequence variations in the 16S rRNA and COI genes and to analyze the kinship of these seahorses. The morphological identification was performed, followed by the validation of the identification based on a molecular approach. Both identification methods showed the one species from Riau Islands was H. kuda, while the others (n=2) were H. comes. All specimens from Lampung (n=3) were H. comes. The specimens of H. comes from Riau Islands and Lampung were the same haplotype based on the 16 S rRNA sequence. Based on the COI, H. comes from Riau Islands (n=2) were found to be one haplotype (haplotype 1; n=2), while those from Lampung (n=3) consisted of two haplotypes (haplotype 1; n=2 and haplotype 2; n=1). Phylogenetic analysis based on both genes revealed that H. comes from Riau Islands and Lampung belongs to the same clade, while H. kuda from Riau Islands (n=1) was included in the lineage B (Indian Ocean).
Challenges and controversies in COVID-19 respiratory failure

COVID-19 pneumonia presents distinctive questions and challenges traditional conventions of management of respiratory failure. The trajectory of recommendations on customary intubation practices has undertaken significant paradigm shifts. This review will discuss the role of high flow nasal cannula oxygenation in mitigating respiratory distress in SARS-COV2 pneumonia and will explore the indices that can aid in the timely recognition of failure of noninvasive respiratory support modalities and escalation to mechanical ventilation. The work of breathing is a valuable yardstick for understanding increasing lung elastance. Quantifying work of breathing, though, has its own unique challenges. This article also discusses the emerging controversial proposals of employing high tidal volumes and low PEEP in mechanical ventilation of COVID-19 pneumonia and will review the key concepts of lung stress and strain and the implications of “static” versus “dynamic” strain in ventilator induced lung injury. It considers the established facts of inducing lung strain with larger dynamic deformations caused by high tidal volumes and the benefit of high PEEP in homogenizing the strain distribution. The review suggests that the isolated ground glass opacities could pose as “stress raisers. ” The effects of these regional lung homogeneities in amplifying local and global lung stress are also discussed as well as the benefits of PEEP beyond its effect as a pressure barrier against alveolar filling and its utility in lungs with near normal compliance. A physiologic approach is presented to counter the non-uniform and heterogeneous presentations of this unique disease rather than conforming to rigid protocols. One size probably does not fit all.
A Rapid Method for Information Extraction from Borehole Log Images

Borehole logs are very important for geological analysis and application. Extracting structured information from borehole logs in the image format is the key to any analysis and application based on borehole data. The current method has defects in solving the beard phenomenon of the borehole log and the identification of special geological symbols. This paper proposes an automatic extraction method for borehole log information by combining the structural analysis based on the corner mark, as well as the structural understanding based on deep learning. The principles and key technologies of the method are described in detail. The performance of the method was tested by specific examples. This method is implemented on a geological information platform called QuantyView. The information extraction of 100 borehole logs with the same specification is used to verify the effectiveness of the proposed method. The results show that the method can not only effectively solve the inconsistency between the thickness and the description information in the borehole log but it can also address the low recognition efficiency of professional vocabulary, which can improve the extraction efficiency and accuracy of the borehole log information.
Detecting and remediating modern slavery in supply chains: a targeted audit approach

Abstract This paper investigates modern slavery detection and remediation. Action research has been conducted in the textiles and fashion industry, with the primary engagement involving a multi-billion pound (GBP) turnover company and their modern slavery investigation at a high-risk supplier in South East Asia. This paper responds to calls from the literature to investigate the modern slavery detection process and provides empirical evidence involving collaboration with a large multinational NGO and another of the audited supplier’s customers. Findings are presented from a first-hand account of the detection process and suggest that a targeted audit is more likely to identify key indicators of modern slavery. This type of audit includes investigating the end-to-end recruitment process by using a parallel structure of management and worker interviews and documentation review. Evidence is also provided of the company’s remediation process, which includes partnering with a local NGO to empower workers and collaboratively develop suppliers.
The Game of Developers and Planners: Ecosystem Services as a (Hidden) Regulation through Planning Delay Times

Planning delay time is a ubiquitous but under-researched land use regulation method. The aim of this study is to link planning delay time with the loss of urban locally provided ecosystem services (ULPES) caused by land development. Our main hypothesis is that the planning delay is an informal tool that ensures social welfare in a given urban area increases even if land is developed and the ULPES associated with the undeveloped land are lost. Whereas the developer’s objective is to maximize his profits, the planner’s target is to achieve the greatest social welfare, as calculated by considering public interest based on the value of open space and the developer’s expected profits. Our results show that, when the ULPES provided by an undeveloped parcel are sufficiently high, planning delay times can be used to prevent the execution of low quality initiatives and to only permit projects that improve general welfare and justify the potential ULPES loss. Planning delay times are interpreted as the expression of continuous negotiation between the interests of the public and those of real-estate developers, regarding the value of ULPES. The implication of the study is that ULPES values are introduced using a simple game-theoretic model allowing interaction between developers and planning authorities. The main significance is an alternative explanation for planning delay times as a consequence of ongoing negotiations between developers and urban planners that represent the general public in the city.
Controlling Drug Absorption, Release and Erosion of Photopatterned Protein Engineered Hydrogels.

A protein-engineered triblock copolymer hydrogel comprised of two self-assembling domains (SADs) has been fabricated by a photo-activatable diazirine group followed by ultraviolet (UV)-mediated crosslinking. The photo-crosslinkable protein polymer CEC-D has been patterned into various features including different micrometer-scale stripes using lithographic techniques. The patterned hydrogels are important for encapsulation of small molecule where a photopatterned fraction of 50% is optimal for maximum absorption. Stripe-patterned CEC-D100-100 exhibits slightly lower swelling ratios, 8.9 times lower erosion profile and 2.6-fold higher drug release compared to the unpatterned hydrogel control, CEC-D0. Our studies demonstrate the potential of photo-crosslinkable protein polymer hydrogels to be used as scaffolds for therapeutic delivery of small molecules. Through photolithographic techniques on the protein hydrogel, a variety of functionalities can be achieved by patterning different features enabling the mimicry of biological systems.