Miracle-dz/UniFAR-FTUs huggingface dataset:
VAPOR-PHASE CATALYTIC UPGRADING OF BIOMASS PYROLYSIS PRODUCTS THROUGH ALDOL CONDENSATION AND HYDRODEOXYGENATION FOR THE FORMATION OF FUEL-RANGE HYDROCARBONS

Author: Caulkins, Richard, S. MSCHE Institution: Purdue University Degree Received: December 2018 Title: Vapor-Phase Catalytic Upgrading of Biomass Pyrolysis Products through Aldol Condensation and Hydrodeoxygenation for the Formation of Fuel-Range Hydrocarbons Committee Chair: Fabio Ribeiro Biomass-derived fuels have long been considered as a possible replacement for traditional liquid fuels derived from petroleum. However, biomass as a feedstock requires significant refinement prior to application as a liquid fuel. The H2Bioil process has previously been proposed in which biomass is pyrolyzed and the resulting vapors are passed over a catalyst bed for upgrading to hydrocarbon products in a hydrogen environment [1]. A PtMo catalyst has been developed for the complete hydrodeoxygenation (HDO) of biomass pyrolysis vapors to hydrocarbons [2]. However, the product hydrocarbons contain a large fraction of molecules smaller than C4 which would not be suitable as liquid fuels. In fast hydropyrolysis of poplar followed by hydrodeoxygenation over a PtMo/MWCNT catalyst at 25 bar H2 and 300C, only 32.1% of carbon is captured in C4 – C8 products; 21.7% of carbon is captured in C1 – C3 hydrocarbons [2]. Here, approaches are examined to increase selectivity of H2Bioil to desired products. Aldol condensation catalysts could be used prior to the HDO catalyst in order to increase the carbon number of products. These products would then be hydrodeoxygenated to hydrocarbons of greater average carbon number than with an HDO catalyst alone. Application of a 2% Cu/TiO2 catalyst to a classic aldehyde model compound, butanal, shows high selectivity towards aldol condensation products at low H2 pressures. In more complex systems which more closely resemble biomass pyrolysis vapors, this catalyst also shows significant yields to aldol condensation products, but substantial carbon losses presumed to be due to coke formation are observed. Both glycolaldehyde, a significant product of biomass pyrolysis, and cellulose, a component polymer of biomass, have been pyrolyzed and passed through aldol condensation followed by hydrodeoxygenation in a pulsed fixed-bed microreactor. Glycolaldehyde aldol condensation resulted in the formation of products in the C2-C9 range, while the major aldol condensation products observed from cellulose were C7 and C8 products. Carbon losses in glycolaldehyde aldol condensation were reduced under operation at increased hydrogen partial
Gas exchange and chlorophyll fluorescence in spearmint ( Mentha spicata L.) leaves influenced by mineral nutrition Intercambio gaseoso y fluorescencia de la clorofila en menta ( Mentha spicata L.) influenciados por la nutrición mineral

The production of export-quality spearmint is limited in Colombia because of low production volumes, poor compliance with good agricultural practices, nutrient availability, and fertilization management. This study aimed to identify how NPK fertilization influences photosynthesis and photochemistry in Mentha plants during vegetative growth in a mesh house. Increasing doses of chemical fertilization were evaluated with a 10-30-10 (N-P-K) formula at 0, 60, 90, 120, and 180 kg ha -1 . The evaluated variables were net photosynthesis ( A ), transpiration ( E ), stomatal conductance ( g s ), leaf temperature ( T leaf ), quantum yield ( Qy ), Non-photoche-mical quenching ( NPQ ), photochemical quenching ( qP ), and dry matter ( Dm ). The highest A , Qy , E , and g s values were in the plants treated with high NPK doses; the NPQ and qP increased in the plants with low NPK doses. These findings elucidated the influence of NPK on photosynthesis and other physiological parameters in the growth and development of spearmint. fertilización química a partir de la fórmula 10-30-10 (N-P-K) en las cantidades de 0, 60, 90, 120 y 180 kg ha -1 . Las variables estimadas fueron fotosíntesis neta ( A ), transpiración ( E ), conductancia estomática ( g s ), temperatura de la hoja ( T hoja ), rendimiento cuántico ( Qy ), desactivación no fotoquímica ( NPQ ), desactivación química ( qP ) y materia seca ( Dm ). Los mayores valores A , Qy , E y g s se presentaron en plantas tratadas con altas dosis de NPK; mientras que el NPQ y el qP aumentaron en las plantas con bajas dosis de NPK. Nuestros hallazgos proveen bases a cerca de la influencia del NPK sobre la fotosíntesis y otros parámetros fisiológicos, con relación al crecimiento y desarrollo de la menta.
ActivationResting Memory Versus Naive CD4 T Cell Differential Role of CTLA-4 in Regulation of

Regulation of peripheral T cell responses is critical for preserving self tolerance. Memory T cells have a lower threshold for activation through the TCR and are thought to be less dependent on costimulation than naive T cells, suggesting a requirement for more stringent regulation of memory T cells. We have recently shown that CD4 engagement apart from the TCR results in the inactivation of memory, but not naive, CD4 T cells. We show here that this inhibition requires ligation of CTLA-4, in that blocking CTLA-4-B7 interactions restores memory CD4 T cell responsiveness. Early signaling through CTLA-4 is possible because resting memory, but not naive, CD4 T cells contain intracellular stores of CTLA-4 that are continuously recycled between the cytoplasm and the cell surface. This mechanism ensures that low intensity TCR engagements, which are thought to be important for peripheral T cell longevity, do not cause memory T cell activation but instead raise their threshold for costimulatory signals. This may give memory T cells an extended lifespan with a reduced risk of inappropriate activation. The Journal of Immunology, 1998, 161: 5855–5861.
Intervene or wait? A model evaluating the timing of intervention in conservation conflicts adaptive management under uncertainty

The timing of biodiversity managers’ interventions can be critical to the success of conservation, especially in situations of conflict between conservation objectives and human livelihood, i.e., conservation conflicts. Given the uncertainty associated with complex social-ecological systems and the potentially irreversible consequences of delayed action for biodiversity and livelihoods, managers tend to simply intervene as soon as possible by precaution. However, refraining from intervening when the situation allows can be beneficial, notably by saving critical management resources. We introduce a strategy for managers to decide, based on monitoring, whether intervention is required or if waiting is possible. This study evaluates the performance of this waiting strategy compared to a strategy of unconditional intervention at every opportunity. We built an individual-based model of conservation conflict between a manager aiming to conserve an animal population and farmers aiming to maximize yield by protecting their crop from wildlife damage. We then simulated a budget-constrained adaptive management over time applying each strategy, while accounting for uncertainty around population dynamics and around decision making of managers and farmers. Our results showed that when the decision for the manager to intervene was based on a prediction of population trajectory, the waiting strategy performed at least as well as unconditional intervention while also allowing managers to save resources by avoiding unnecessary interventions. Under difficult budgetary constraints on managers, this waiting strategy ensured as high yields as unconditional intervention while significantly improving conservation outcomes by compensating managers’ lack of resources with the benefits accrued over waiting periods. This suggests that waiting strategies are worth considering in conservation conflicts because they can facilitate equitable management with a more efficient use of management resources, which are en évitant des interventions non nécessaires. Lorsqu'un budget trop faible rendait la gestion difficile, notre stratégie a considérablement amélioré les résultats relatifs à la conservation en compensant le manque de ressources par les bénéfices accumulés au cours des périodes sans intervention. Ces résultats montrent que notre stratégie devrait être envisagée car elle peut assurer une gestion équitable du conflit tout en permettant une utilisation plus efficace des ressources de gestion, souvent limitantes en conservation de la biodiversité.
BlackBox: A Container Security Monitor for Protecting Containers on Untrusted Operating Systems

Containers are widely deployed to package, isolate, and multiplex applications on shared computing infrastructure, but rely on the operating system to enforce their security guarantees. This poses a signiﬁcant security risk as large operating system codebases contain many vulnerabilities. We have created BlackBox, a new container architecture that provides ﬁne-grain protection of application data conﬁdentiality and integrity without trusting the operating system. BlackBox introduces a container security monitor, a small trusted computing base that creates protected physical address spaces (PPASes) for each container such that there is no direct information ﬂow from container to operating system or other container PPASes. Indirect information ﬂow can only happen through the monitor, which only copies data between container PPASes and the operating system as system call arguments, encrypting data as needed to protect interprocess communication through the operating system. Containerized applications do not need to be modiﬁed, can still make use of operating system services via system calls, yet their CPU and memory state are isolated and protected from other containers and the operating system. We have implemented BlackBox by leveraging Arm hardware virtualization support, using nested paging to enforce PPASes. The trusted computing base is a few thousand lines of code, many orders of magnitude less than Linux, yet supports widely-used Linux containers with only modest modiﬁcations to the Linux kernel. We show that BlackBox provides superior security guarantees over traditional hypervisor and container architectures with only modest performance overhead on real application workloads.
Method for detecting 2D grapevine winter pruning location based on thinning algorithm and Lightweight Convolutional Neural Network

: In viticulture, there is an increasing demand for automatic winter grapevine pruning devices, for which detection of pruning location in vineyard images is a necessary task, susceptible to being automated through the use of computer vision methods. In this study, a novel 2D grapevine winter pruning location detection method was proposed for automatic winter pruning with a Y-shaped cultivation system. The method can be divided into the following four steps. First, the vineyard image was segmented by the threshold two times Red minus Green minus Blue (2R − G − B) channel and S channel; Second, extract the grapevine skeleton by Improved Enhanced Parallel Thinning Algorithm (IEPTA); Third, find the structure of each grapevine by judging the angle and distance relationship between branches; Fourth, obtain the bounding boxes from these grapevines, then pre-trained MobileNetV3_small×0.75 was utilized to classify each bounding box and finally find the pruning location. According to the detection experiment result, the method of this study achieved a precision of 98.8% and a recall of 92.3% for bud detection, an accuracy of 83.4% for pruning location detection, and a total time of 0.423 s. Therefore, the results indicated that the proposed 2D pruning location detection method had decent robustness as well as high precision that could guide automatic devices to winter prune efficiently. based on thinning algorithm and Lightweight Convolutional Neural Network.
Gestion de l'eau et performances électriques d'une pile à combustible : des pores de la membrane à la cellule

Cette these apporte des elements sur la comprehension de la gestion de l'eau et de ses effets sur les performances electriques d'une PEMFC au moyen de modelisations multi-echelle des transferts. Une analyse du transport couple de charges et de matiere dans les pores de la membrane est proposee. La presence d'eau liquide est prise en compte dans les GDL (ecoulements diphasiques) et les couches actives (noyage). Le couplage de ces modeles a une description des transferts de matiere le long des canaux d'alimentation permet de mettre en evidence une repartition non-uniforme des concentrations en eau, des flux et donc de la densite de courant. Les resultats numeriques sont compares a des donnees experimentales (coefficient de partage de l'eau et performance electrique locale) obtenues au laboratoire sur deux piles. Ceci permet de valider les modeles de fonctionnement du coeur de pile et d'alimenter la reflexion sur la connaissance et la modelisation des transferts d'eau dans le coeur de pile
This paper is included in the Proceedings of the 16th USENIX Symposium on Operating Systems Design and Implementation.

The increasing use of sensitive private data in computing is matched by a growing concern regarding data privacy. System software such as hypervisors and operating systems are supposed to protect and isolate applications and their private data, but their large codebases contain many vulnerabilities that can risk data conﬁdentiality and integrity. We introduce Realms, a new abstraction for conﬁdential computing to protect the data conﬁdentiality and integrity of virtual machines. Hardware creates and enforces Realm world, a new physical address space for Realms. Firmware controls the hardware to secure Realms and handles requests from untrusted system software to manage Realms, including creating and running them. Untrusted system software retains control of the dynamic allocation of memory to Realms, but cannot access Realm memory contents, even if run at a higher privileged level. To guarantee the security of Realms, we veriﬁed the ﬁrmware, introducing novel veriﬁcation techniques that enable us to prove, for the ﬁrst time, the security and correctness of concurrent software with hand-over-hand locking and dynamically allocated shared page tables, data races in kernel code running on relaxed memory hardware, integrated C and Arm assembly code calling one another, and untrusted software being in full control of allocating system resources. Realms are included in the Arm Conﬁdential Compute Architecture.
Epidemiological aspects of the Oropouche virus (Orthobunyavirus) in South America: A systematic review

(12/18; 66.66%) and Peru (5/18; 27.77%), only one study collected samples from Peru, Ecuador, Bolivia and Paraguay. The test for the OROV was realized mainly by serological analysis. Of the 8005 samples analyzed, 1570 tested positive for the presence of OROV thus accounting a general exposure rate in South America of 19.61%. Brazil was responsible for more than half of the cases of OROV identified in South America (855/1570; 54.46%), however Peru has the highest rate of exposure to the virus (23.43% of frequency in Peru vs. 16.77% of frequency in Brazil). Conclusion: OROV stands out as an important public health problem in Amazonian countries in South America.
Point Cloud Pre-training with Natural 3D Structures

The construction of 3D point cloud datasets requires a great deal of human effort. Therefore, constructing a large-scale 3D point clouds dataset is difficult. In order to rem-edy this issue, we propose a newly developed point cloud fractal database (PC-FractalDB), which is a novel family of formula-driven supervised learning inspired by fractal geometry encountered in natural 3D structures. Our re-search is based on the hypothesis that we could learn rep-resentations from more real-world 3D patterns than con-ventional 3D datasets by learning fractal geometry. We show how the PC-FractalDB facilitates solving several re-cent dataset-related problems in 3D scene understanding, such as 3D model collection and labor-intensive annotation. The experimental section shows how we achieved the performance rate of up to 61.9% and 59.0% for the Scan-NetV2 and SUN RGB-D datasets, respectively, over the current highest scores obtained with the PointContrast, con-trastive scene contexts (CSC), and RandomRooms. More-over, the PC-FractalDB pre-trained model is especially ef-fective in training with limited data. For example, in 10% of training data on ScanNetV2, the PC-FractalDB pre-trained VoteNet performs at 38.3%, which is +14.8% higher accu-racy than CSC. Of particular note, we found that the pro-posed method achieves the highest results for 3D object de-tection pre-training in limited point cloud data. 11Dataset release: https://ryosuke-yamada.github. io/PointCloud-FractalDataBase/
WebQA: Multihop and Multimodal QA Supplementary Material

Qualification HIT. For quality control, we included a qualification task with 15 hard coded QA pair annotations, some of which obviously violate the annotation guidelines. Annotators had to point out the problematic pairs and explain in what ways they did not follow the instructions. We restricted to crowdworkers located in the US or Canada, with a general requirement of over 1,000 previously approved HITs with at least 95% approval rate. Additionally, one has to score 80% or higher on our qualification task before getting access to our main task. We gave workers who achieved 60% 80% at their first attempt a second chance because we believe that workers who had the patience to complete their first attempt were more coachable than others.
OLIVES Dataset: Ophthalmic Labels for Investigating Visual Eye Semantics

Clinical diagnosis of the eye is performed over multifarious data modalities including scalar clinical labels, vectorized biomarkers, two-dimensional fundus images, and three-dimensional Optical Coherence Tomography (OCT) scans. Clinical practitioners use all available data modalities for diagnosing and treating eye diseases like Diabetic Retinopathy (DR) or Diabetic Macular Edema (DME). Enabling usage of machine learning algorithms within the ophthalmic medical domain requires research into the relationships and interactions between all relevant data over a treatment period. Existing datasets are limited in that they neither provide data nor consider the explicit relationship modeling between the data modalities. In this paper, we introduce the Ophthalmic Labels for Investigating Visual Eye Semantics (OLIVES) dataset that addresses the above limitation. This is the first OCT and near-IR fundus dataset that includes clinical labels, biomarker labels, disease labels, and time-series patient treatment information from associated clinical trials. The dataset consists of 1268 near-IR fundus images each with at least 49 OCT scans, and 16 biomarkers, along with 4 clinical labels and a disease diagnosis of DR or DME. In total, there are 96 eyes' data averaged over a period of at least two years with each eye treated for an average of 66 weeks and 7 injections. We benchmark the utility of OLIVES dataset for ophthalmic data as well as provide benchmarks and concrete research directions for core and emerging machine learning paradigms within medical image analysis.
Supervision for the delivery of Mental Health Psychosocial Support in Emergency Humanitarian Settings A Desk Review Report

Against this background, this report examines the available evidence on MHPSS supervision by exploring: existing definitions of supervision, different approaches used to supervise, best practices in supervision and current barriers and challenges to conducting supervision. The findings from this report confirm a lack of consensus regarding a definition of MHPSS supervision in humanitarian settings in conjunction with a dearth of evidence relating as to when, how and for whom different models of MHPSS work. A number of challenges were identified that need to be overcome in order to improve MHPSS supervision including dealing with: a reliance on recruitment of expatriate personnel to serve in the capacity of a supervisor; a lack of available/allocated funding for MHPSS programming; inadequate availability and accessibility to supervision; a lack of cultural competence by the supervisor; language barriers; a lack of human resources and a lack of role clarity for supervisors. Despite these shortcomings, opportunities do exist to generate international consensus and developing guidelines for MHPSS supervision, with concerted efforts playing a key role in the process.
Analysis of Caustic Soda of Different Manufacturers in Pakistan for Mercerization of Cotton Textiles

Pakistan has sufficient production capacity of caustic soda to cater the needs of the local industry. Presently, Pakistan has four major plants with production capacity around 435,000 mega ton per year of caustic soda of various grades. Textile industry of Pakistan is the major consumer of produced high grade caustic soda; as the presence of any impurities especially dissolved salts and metals is unfavorable for wet processing of cotton. This study investigates the performance of three different local brands of caustic soda intended for use in textile wet processing of cotton fabric specifically for mercerization process. The brands were selected based on their purity grades. The selected caustic soda samples were chemically analyzed for the presence of impurities. Twenty seven cotton fabric samples (nine samples of each brand) were prepared by mercerization in slack state. The cotton fabric samples were tested for changes in surface morphology, tensile strength (warp and weft), tear strength, air permeability and K/S (Colour Strength). The results were analyzed using one-way ANOVA (Analysis of Variance) to ascertain the statistical equivalence within and between the tested brands. The results showed no significant differences across the tested brands at a 95% confidence level except for air permeability and K/S in blue shade.
Neural Head Avatars from Monocular RGB Videos –Supplemental Document–

We utilize the FLAME head model [15] in its updated version from 2020 as the geometric backbone of our method. As mentioned in the main paper, we perform minor adjustments to the FLAME topology, namely, we uniformly subdivide the faces (four-way subdivision), remove the faces belonging to the lower neck region, and add faces to close the mouth cavity, see Figure 2. This increases the original number of vertices from 5023 to 16227. Inspired by [4], we use tanh activation functions to limit the joint rotations of FLAME to physiologically plausible ranges.
Towards μs tail latency and terabit ethernet: disaggregating the host network stack

Dedicated, tightly integrated, and static packet processing pipelines in today's most widely deployed network stacks preclude them from fully exploiting capabilities of modern hardware. We present NetChannel, a disaggregated network stack architecture for μs-scale applications running atop Terabit Ethernet. NetChannel's disaggregated architecture enables independent scaling and scheduling of resources allocated to each layer in the packet processing pipeline. Using an end-to-end NetChannel realization within the Linux network stack, we demonstrate that NetChannel enables new operating points---(1) enabling a single application thread to saturate multi-hundred gigabit access link bandwidth; (2) enabling near-linear scalability for small message processing with number of cores, independent of number of application threads; and, (3) enabling isolation of latency-sensitive applications, allowing them to maintain μs-scale tail latency even when competing with throughput-bound applications operating at near-line rate.