Miracle-dz/UniFAR-FTUs huggingface dataset:
Vegetation dynamics of riparian forest in central Europe during the late Eocene

The Cenozoic basins in Germany (Weißelster) and the Czech Republic (Cheb, Sokolov and Most) have an extensive fossil record of riparian vegetation traceable from the middle Eocene to the early Miocene. Within this paper we focus on its evolution and gradual changes between the late Bartonian and the Eocene-Oligocene turnover, a time interval of gradual global cooling. For most of the time span a certain stasis in the development of azonal regional vegetation was previously observed resulting in the establishment of the Zeitz floristic complex (“Florenkomplex”) that covers ca. 3.0–3.5 Ma contradicting the suspected global climatic trend. Herein we summarize results of investigations of several fossil floras of the Weißelster Basin that were conducted over the last decade and allocate them into the modern lithostratigraphic concept for central Germany. Previously published floras from this basin that come from an unambiguous lithostratigraphic position are revisited. For comparison the floras from Northern Bohemia are included. Our results show that the Zeitz floristic complex cannot be maintained in its original circumscription but needs a subdivision into three floristic stages based on immigration and disappearance of key vegetation elements. Stage 1, representing the type horizon and flora of the Zeitz floristic complex, is characterized by the presence of typical ‘subtropical’ species persisting since the middle Eocene, e. g. Doliostrobus taxiformis, Laurophyllum syncarpifolium, Steinhauera subglobosa, and Rhodomyrtophyllum reticulosum. In stage 2 thermophilous deciduous elements such as Platanus neptuni and Taxodium dubium as well as new Lauraceae immigrate into the regional vegetation. The stage 3 is typified by the disappearence of the old ‘subtropical’ elements, whereas other evergreen warmtemperate or ‘subtropical’ elements such as Eotrigonobalaus furcinervis and Quasisequoia couttsiae persist. They were probably able to withstand significant climatic changes during the Eocene-Oligocene transition. A massive immigration of broad-leaved deciduous elements prior to the Eocene-Oligocene boundary, known from the Northern Bohemian flora of Roudníky has not been recognized in the Weißelster Basin.
Efficient Algorithms for Group Hitting Probability Queries on Large Graphs

—Given a source node s and a target node t , the hitting probability tells us how likely an α -terminating random walk (which stops with probability α at each step) starting from s can hit t before it stops. This concept originates from the hitting time, a classic concept in random walks. In this paper, we focus on the group hitting probability (GHP) where the target is a set of nodes, measuring the node-to-group structural proximity. For this group version of the hitting probability, we present efficient algorithms for two types of GHP queries: the pairwise query which returns the GHP value of a target set T with respect to (w.r.t.) a source node s , and the top-k query which returns the top-k target sets with the largest GHP value w.r. t. a source node s . We first develop an efficient algorithm named SAMBA for the pairwise query, which is built on a group local push algorithm tailored for GHP, with rigorous analysis for correctness. Next, we show how to speed up SAMBA by combining the group local push algorithm with the Monte Carlo approach, where GHP brings new challenges as it might need to consider every hop of the random walk. We tackle this issue with a new formulation of the GHP and show how to provide approximation guarantees with a detailed theoretical analysis. With SAMBA as the backbone, we develop an iterative algorithm for top-k queries, which adaptively refines the bounds for the candidate target sets, and terminates as soon as it meets the stopping condition, thus saving unnecessary computational costs. We further present an optimization technique to accelerate the top-k query, improving its practical performance. Extensive experiments show that our solutions are orders of magnitude faster than their competitors.
Effect of Oil on Phytoremediation of PCB Co-Contamination in Transformer Oil Using Chromolaena odorata

Greenhouse assessment of the effect of oil on Chromolaena odorata ability to remove PCB from soil treated with transformer oil co-contaminated with Aroclor 1260 was done. Method: Plants were transplanted into one kilogram of soil contained in 1L pots differently containing 100, 200, and 500 ml of transformer oil (T/O), co-contaminated with 100 ppm of Aroclor. Treatments were done in two microcosms; direct contamination and soil cultured method. Measured plant growth parameters showed that C. odorata growth was affected by the different concentrations of oil. Inhibition of plant growth by oil increased with concentrations. Results: At the end of six weeks, plant growth was affected in T/O amended soil. Plants size was increased by 1.4, 0.46 and -1.0% in direct treatment and 17.01, 6.09 and 1.08% in soil culture at the 100, 200 and 500 ppm respectively. Untreated control showed a 43.07% increase. Slight PCB recovery was observed in root tissues of C. odorata but soil PCB was reduced by 66.6%, 53.2%, 41.5% and 77.3%, 74.7%, 58.8% at both treatments in their respective concentrations of oil. However, unplanted control was reduced by 21.4% and 16.7% in the two treatments at 100 ppm of oil. Conclusion: This study has shown that with improved agronomic practices, there is a possibility of phytoremediation of soil PCB from PCB contained transformer oil contaminated soil using Chromolaena odorata, hence it should be optimized in the field.
Reducing Flooding of Zone Routing Protocol in Mobile Ad-Hoc Networks

Mobile ad-hoc networks (MANETs) are temporary networks without any pre-existing infrastructure in which nodes are connected through wireless channels. There is no centralized administration in this network because nodes are not fixed at their locations, they are continuously moving to different locations. Each node in MANETs has dynamic capabilities because at one point acts as a host while in some other time becomes a router which can forward messages on the network to other nodes. One of the complicated issues in MANETs is routing due to their dynamic topology which is frequently changes due to the mobility of nodes. In order to forward packets in this complex topology using optimal routes, there is a need for efficient routing protocols. There are three categories of routing protocols in MANETs named as reactive, proactive and hybrid respectively. We have used a hybrid type protocol named Zone Routing Protocol (ZRP) for routing in our research. In order to control unwanted flooding in the overlapping zones of ZRP, we have proposed a selective broadcasting technique for route discovery. In this technique route discovery exchange messages are highly reduced in the outer zone of the ZRP.
The Effect of Linker Group on Thermoelectric Properties of Dimer Zinc Porphyrin-Based Molecular Junctions

— The discovery of high-efficiency organic thermoelectric materials has the potential to pave the path for various energy-gathering innovations and the development of translucent, pliable thin-film materials for Peltier coolers. Our study involves a comparison of the electrical and thermoelectric characteristics of five zinc porphyrin configurations. The results show that changing the linker between zinc diner units has an essential effect on the electrical conductance and thermopower values of these structures. Consequently, the thermoelectric figure of merit ZT will change which means the thermoelectric efficiency change. We also observed a notable augmentation in the Seebeck coefficient when the linker connecting the Zinc porphyrin dimers is either (C - N) or (C - C). The augment in the Seebeck coefficient can be ascribed to a variety of factors. One plausible reason for this phenomenon is the dissimilarity in the electronic structure and energy levels between the zinc porphyrin molecule and the carbon-hydrogen linker. This dissimilarity has the potential to induce a modification in the density of states in the vicinity of the Fermi level, ultimately leading to an amplified thermopower.
Entity-Relation Extraction as Full Shallow Semantic Dependency Parsing

Entity-relation extraction is the essential information extraction task and can be decomposed into Named Entity Recognition (NER) and Relation Extraction (RE) subtasks. This paper proposes a novel joint entity-relation extraction method that models the entity-relation extraction task as full shallow semantic dependency graph parsing. Specifically, it jointly and simultaneously converts the entities and relation mentions as the edges of the semantic dependency graph to be parsed and their types as the labels. This model also integrates the advantages of multiple feature tagging methods and enriches the token representation. Furthermore, second-order scoring is introduced to exploit the relationships between entities and relations, which improves the model performance. Our work is the first time to fully model entities and relations into a graph and uses higher-order modules to address their interaction problems. Compared with state-of-the-art scores on five benchmarks (ACE04, ACE05, CoNLL04, ADE, and SciERC), empirical results show that our proposed model makes significant improvements and demonstrates its effectiveness and practicability.
A Comparative Study of Aromatic Pollutants Degradation Using Two Different Peroxidases

Enzyme based degradation of organic pollutants is a promising new remediation approach due to the promiscuous nature of the technique, the wide range of available enzymes, and the scalability of the process. Oxidoreductases, specifically, peroxidases are the most popular class of enzymes that have been used for the degradation of organic pollutants. It is generously assumed that all peroxidases behave similarly and produce similar degradation products. Our main objective was to test the hypothesis that related peroxidases may act differentially towards the degradation of aromatic pollutants. Therefore, in this study, we have carried out detailed degradation studies on three model of aromatic pollutants using two of the most commonly used peroxidases – Soybean peroxidase (SBP) and Chloroperoxidase (CPO). Our studies show that these two enzymes have very different optimum conditions when degrading these aromatic pollutants. For example, SBP had a pH optimum of 4, whereas CPO is most active at pH 2-3. Additionally, SBP and CPO had very different thermal stabilities, with SBP showing full activity up until 80C, which was very different than CPO, which was almost completely inactive at 60C. HPLC analyses confirmed that both SBP and CPO transformed the all the aromatic pollutants into different compounds, which was further confirmed by LC-MS-MS studies. Furthermore, toxicological evaluation showed that SBP-based treatment was able to reduce the toxicity, while CPO treatment failed to eliminate the toxicity of the compounds. Our results show that related peroxidases may behave very differently when used for remediation purposes and points to the need for toxicity analysis of peroxidase degraded pollutants, as well as to carry out detailed mechanistic studies to identify the intermediates produced.
Ergonomics and performance of using prismatic loupes in simulated surgical tasks among surgeons – a randomized controlled, cross-over trial

Introduction Recently developed prismatic loupes may mitigate the high physical workload and risk of neck disorders associated with traditional surgical loupes among surgeons. However, research in this area, particularly among surgeons, is sparse. This study examines the impact of prismatic loupes on surgeons’ physical workload, musculoskeletal discomfort, and performance during simulated surgical tasks. Materials and methods Nineteen out of twenty recruited surgeons performed three tasks in a fixed-order with their own loupes and both low-tilt (LT) and high-tilt (HT) prismatic loupes, in a randomized order. The primary outcomes were the median inclination angles and velocities of the head, trunk, and upper arms, along with the median muscle activity of the cervical erector spinae (CES), upper trapezius (UT), and lumbar erector spinae (LES) for each pair of loupes. The secondary outcomes included performance (completion time and errors), perceived body-part discomfort, and subjective evaluation of the three pairs of loupes. Results Using prismatic loupes, either LT or HT, compared with the surgeons’ own loupes yielded lower head inclinations (all p < 0.001), lower neck muscle activity (all p < 0.05), and lower neck discomfort in indirect comparisons (p < 0.01) with no significant difference in surgical errors (p = 0.628). However, HT loupes resulted in a longer task completion time in two tasks (p < 0.001). Most surgeons preferred LT loupes (N = 12) for their comfort and visual functions. Discussion The results indicate that prismatic loupes can reduce physical workload in the neck during simulated surgical task, with no significant difference in surgical errors. Future studies are needed to investigate the long-term effects of prismatic loupes among surgeons.
Histological and virological findings in severe meningoencephalitis associated with border disease virus in Alpine chamois (Rupicapra rupicapra rupicapra) in Aosta Valley, Italy

In 2015, a young female Alpine chamois (Rupicapra rupicapra rupicapra), originated from the Aosta Valley Region, Northernwestern Italy, was conferred to the National Reference Centre for Wild Animal Diseases for pathologic examinations. Histological analysis revealed a severe meningoencephalitis characterized by lymphocytic and plasmacellular infiltration, gliosis, perivascular cuffs, and leptomeningitis at the level of brain and brain stem. Laboratory investigations included polymerase chain reaction, sequencing and characterization by phylogenetic analysis, and evaluation of the internal ribosome entry site secondary structure in the 5’ untranslated region. These tests identified the pathological agent as border disease virus, a known health risk in domestic small ruminants. Genetic characteristics of the isolated strains, closely related to ovine and caprine strain sequences from neighboring regions of Piedmont, France, and Switzerland, suggested geographic segregation and micro-evolutive steps within the species.
Collaborative filtering recommendation method based on graph convolutional neural networks

In the rapidly advancing information technology era, information overload poses a significant challenge. Recommender systems offer a partial solution, yet traditional methods grapple with issues like sparse data and accuracy. For this reason, this paper introduces a novel approach—a high-order graph convolutional collaborative filtering model. This model employs a subgraph generation module to enhance the importance of neighbor nodes during high-order graph convolutions. Our approach yields enhanced embeddings by embedding user-item interaction information using graph techniques, stacking multi-layer graph convolutional networks to capture complex interactions, and leveraging both initial and convoluted embeddings. This paper introduces a constraint loss function to address over-smoothing in graph-based recommendations. Our method's effectiveness is confirmed through extensive experiments on three real-world datasets
NOx controls for shipping in EU seas

"This study presents a probable timeline for introduction of a Nitrogen Emission Control Area (NECA) in the Baltic Sea, North Sea and English Channel and an NOx emission projection based on the introduction date, comparing this with a scenario without a Northern European NECA. Alternative policy instruments for reducing shipping NOx emissions are discussed in a comparative analysis, including expected NOx cuts and cost estimates. The likely outcome of the Baltic Sea and North Sea NECA negotiations is assessed, along with the estimated timeline of the most probable outcome".
Comparative biological evaluation and G-quadruplex interaction studies of two new families of organometallic gold(I) complexes featuring N-heterocyclic carbene and alkynyl ligands

molecular sieves (4 Å) an inert atmosphere. After 6 h at room temperature, Au(tht)Cl mg, 0.28 mmol) was added and the suspension stirred overnight. Thus, potassium iodide (48 mg, 0.28 mmol) was added and the mixture was left under vigorous stirring for further 30 min. The final dark grey suspension was filtered over Celite® and washed with acetonitrile and DCM to give a clear colourless solution. After concentration to ca. 1 mL, an excess of Et 2 O was added to precipitate out the final white compound (34 mg, 20%). Cell lines and culture maintenance. The human cancer cell lines corresponding to breast carcinoma (MCF-7), ovarian adenocarcinoma (SKOV-3) and skin malignant melanoma (A375) were obtained from the ATCC. The SKOV-3 and A375 cells were cultured in Dulbecco`s Modified Eagle Medium (DMEM, 4,5 g/L glucose, Corning), supplemented with 10% fetal bovine serum (One-Shot FBS, EU-approved South American Origin, Thermo Fisher Scientific) and 1% penicillin/streptomycin (Gibco). MCF-7 cells were grown in Roswell Park Memorial Institute medium (RPMI, L -glutamine, Corning), supplemented with 10% fetal bovine serum (One Shot FBS, EU-approved South American Origin, Thermo Fisher Scientific) and 1% penicillin/streptomycin (Gibco). All cell lines were cultured at 37 °C, in a humidified atmosphere of 5% CO 2 and passage diluted upon reaching confluence. derivatives retained their selectivity for the G4 structures even in the presence of excess double-stranded DNA. While the complexes 3b-c are moderately cytotoxic in all cancer cell lines, the gold(I) mixed NHC-alkynyl complexes, though being less active, were selectively cytotoxic against the MCF-7 breast cancer cell line. Finally, a non-cytotoxic fluorescent gold(I) derivative ( 4d ) was shown to efficiently distribute into the cytoplasm of intact cells after 2 h incubation with melanoma cells, but did not enter the nuclei. Overall, these investigations provide further insight into the distinct biological activity of gold(I) organometallics and underline their promise for tuneable biological applications by appropriate chemical modifications.
Household Food Sufficiency Status and the Qualityof Children's Diets: An Analysis from the Continuing Survey of Food Intakes by Individuals 1994-1996, 1998

The relationship between food sufficiency and diet quality was explored among children 2-8 years of age living in households �185% poverty with 2-days of dietary recall data from 1994-96, 1998 Continuing Survey of Food Intakes by Individuals. Diet quality was assessed using measures of both adequacy and variety. Diet adequacy was measured by degree of adherence to age-specific daily serving recommendations for the 5 Food Guide Pyramid food groups and by intake of discretionary fat (grams) and added sugars (teaspoons). Variety was measured using the Healthy Eating Index Variety Score ( overall variety), the Dietary Diversity Score (among food group variety) and the Sub­ Group Contribution Score (within food group variety). When testing measures of adequacy, this study found that household food sufficiency status did not affect the ability to adhere to the serving recommendations for the major food groups of the Food Guide Pyramid and did not influence discretionary fat intake among low-income children ages 2-8 years. It did, however, affect consumption of added sugars in children 4-8 years of age. Furthermore, although the younger 2-3 year old low-income children seemed to eat a better diet than their 4-8 year old counterparts, both groups of children on average consumed diets that did not conform to the Food Guide Pyramid recommendations. This study also found that household food sufficiency status did not affect the three measures of variety used. However, participation in the WIC Program was a significant predictor of overall variety (2-3 year olds) and among food group variety (2-8 year olds). Variety within food groups, as measured by the Sub-Group Contribution Scores, lent no support to the concepts set forth in the qualitative research regarding
Blood Pressure Estimation from Photoplythmography Using Hybrid Scattering–LSTM Networks

One of the most significant indicators of heart and cardiovascular health is blood pressure (BP). Blood pressure (BP) has gained great attention in the last decade. Uncontrolled high blood pressure increases the risk of serious health problems, including heart attack and stroke. Recently, machine/deep learning has been leveraged for learning a BP from photoplethysmography (PPG) signals. Hence, continuous BP monitoring can be introduced, based on simple wearable contact sensors or even remotely sensed from a proper camera away from the clinical setup. However, the available training dataset imposes many limitations besides the other difficulties related to the PPG time series as high-dimensional data. This work presents beat-by-beat continuous PPG-based BP monitoring while accounting for the aforementioned limitations. For a better exploration of beats’ features, we propose to use wavelet scattering transform as a better descriptive domain to cope with the limitation of the training dataset and to help the deep learning network accurately learn the relationship between the morphological shapes of PPG beats and the BP. A long short-term memory (LSTM) network is utilized to demonstrate the superiority of the wavelet scattering transform over other domains. The learning scenarios are carried out on a beat basis where the input corresponding PPG beat is used for predicting BP in two scenarios; (1) Beat-by-beat arterial blood pressure (ABP) estimation, and (2) Beat-by-beat estimation of the systolic and diastolic blood pressure values. Different transformations are used to extract the features of the PPG beats in different domains including time, discrete cosine transform (DCT), discrete wavelet transform (DWT), and wavelet scattering transform (WST) domains. The simulation results show that using the WST domain outperforms the other domains in the sense of root mean square error (RMSE) and mean absolute error (MAE) for both of the suggested two scenarios.
Energy-Efﬁcient Resource Allocation for Heterogeneous Edge–Cloud Computing

—With the rapid development of Internet of Things (IoT) technology, billions of mobile devices (MDs) are putting a massive burden on limited radio resources. Mobile-edge computing (MEC) can save MDs’ energy consumption and relieve network pressure by ofﬂoading their tasks to edge servers. Compared with cloud servers, edge servers are closer to the users but have less storage capacity. The heterogeneous edge–cloud computing paradigm recently developed combines the advantages of both. In this architecture, edge servers provide powerful computing power, while the cloud provides sufﬁcient storage capacity. Since many IoT devices in such a scenario are mobile, it is more practical to consider user mobility when optimizing the network. Besides, properly utilizing the mobility context can be beneﬁ-cial for improving network performance as well. We focused on the edge–cloud collaborative computing scheme, as well as the joint optimization of power control, transmission scheduling, and ofﬂoading decisions among MDs and edge servers so as to minimize the total energy consumption of all MDs while considering user mobility. The problem was modeled as a mixed-integer programming (MIP) optimization problem that provided the optimal solution. We also proposed a low-complexity heuristic algorithm. Simulations showed that the proposed edge–cloud collaborative scheme could signiﬁcantly reduce the energy consumption of MDs compared with other schemes and demonstrated the importance of considering mobility awareness.