Miracle-dz/UniFAR-FTUs huggingface dataset:
Changes in particulate organic matter passing through a large shallow lowland lake

Different sources of particulate organic matter (POM) as well as its composition affect the biological food web and hence the self-purification potential and water quality of rivers. We studied the effect of a large shallow lake on the POM pool of the water passing through it. Over four years, we analysed monthly the amount and composition of POM and a set of environmental variables in the inflows and in the outflow of Lake Võrtsjärv (Estonia). In the inflows, the live pool of POM consisted of phytoplankton – small crypto-, dino-, and chlorophytes. The concentration of chlorophyll a (Chl a), as a proxy of phytoplankton biomass, was positively correlated with temperature and total phosphorus and negatively with dissolved silica, total nitrogen, and discharge. In the outflow, the share of the live component of POM was much larger than in the inflows but was also dominated by phytoplankton represented by grazing resistant filamentous cyanobacteria. Chl a was positively correlated with total phosphorus, temperature, pH, and precipitation, and negatively with dissolved silica, total nitrogen, and discharge in the outflow. The different amounts, composition, and seasonal dynamics of POM in the inflows and in the outflow have potentially substantial impacts on the food web with a predominating classical pathway in the inflows versus a detrital pathway in the outflow.
Targeting Bacterial Nanocellulose Properties through Tailored Downstream Techniques

Bacterial nanocellulose (BNC) is a biodegradable polysaccharide with unique properties that make it an attractive material for various industrial applications. This study focuses on the strain Komagataeibacter medellinensis ID13488, a strain with the ability to produce high yields of BNC under acidic growth conditions and a promising candidate to use for industrial production of BNC. We conducted a comprehensive investigation into the effects of downstream treatments on the structural and mechanical characteristics of BNC. When compared to alkaline-treated BNC, autoclave-treated BNC exhibited around 78% superior flexibility in average, while it displayed nearly 40% lower stiffness on average. An SEM analysis revealed distinct surface characteristics, indicating differences in cellulose chain compaction. FTIR spectra demonstrated increased hydrogen bonding with prolonged interaction time with alkaline solutions. A thermal analysis showed enhanced thermal stability in alkaline-treated BNC, withstanding temperatures of nearly 300 °C before commencing degradation, compared to autoclaved BNC which starts degradation around 200 °C. These findings provide valuable insights for tailoring BNC properties for specific applications, particularly in industries requiring high purity and specific mechanical characteristics.
Optimisation of borehole-jack fracturing technique for in situ stress measurement

Abstract The technology of stress measurement by the borehole jack is a modification of the hydraulic fracturing method aimed at the determination of the stresses in permeable rocks. The standard procedure for the application of this technique is to form fractures by a borehole jack, which is not always possible at great depth due to the high rock pressure. To address these problems, we propose a two-step technique that involves the formation of extended fractures in the isolated interval of the borehole by working fluid and the subsequent determination of the number, orientation, and reopening pressure of fractures by a special directional loading tool. The developed tool has a higher load transfer efficiency on the borehole wall in comparison with existing analogues. The article describes the results of numerical simulations and laboratory tests.
Exploring Brainstem Structural Abnormalities: Potential Biomarkers for Panic Disorder

Panic disorder (PD), characterized by recurrent and intense panic attacks, presents a complex interplay between psychological and neurobiological factors. Although the amygdala and hippocampus have been studied extensively in the context of PD, the brainstem’s involvement remains relatively underexplored. This study aims to address this gap by examining structural abnormalities within specific brainstem regions, including the medulla, pons, and midbrain. The study sample population comprised twenty-one adult patients diagnosed with PD and an age-gender-education-matched control group. Utilizing rigorous inclusion and exclusion criteria, confounding factors related to comorbid psychiatric conditions and brain structure abnormalities were minimized. Our findings revealed a significant reduction in medulla volume among PD patients, a finding that persisted even after correcting for individual differences in total intracranial volume. The medulla’s role in cardiovascular regulation and autonomic function, coupled with its involvement in fear responses, underscores its potential significance in the pathophysiology of PD. This study elucidates the medulla’s structural abnormalities as a potential biomarker for PD. Understanding the role of the brainstem in PD could pave the way for more targeted and effective interventions for this condition.
A practical approach for the evaluation of tunnel water inflow by means geostructural field survey

Procedura geostrutturale e di filtrazione idraulica per la stima di venute d'acqua in uno scavo in sotterraneo.Nella letteratura dei grandi scavi in sotterraneo vi sono numerosi esempi di situazioni in cui l'impatto dell'opera sulla risorsa idrica disponibile e stato devastante, danneggiando in primo luogo il contesto ambientale in cui l'opera si inserisce, e in secondo luogo l'opera stessa a causa di ritardi nei lavori e nel conseguente aumento dei costi. Nei casi piu estremi puo venir messa in serio pericolo anche l'incolumita dei lavoratori, poiche ingenti venute idriche innescano frane e sfornellamenti che proiettano grandi quantita di materiale all'interno del cantiere. Durante gli scavi di una galleria o di una miniera il rinvenimento di acqua sotterranea e un'evenienza molto frequente ed e pertanto importante venire a conoscenza, in sede previsionale, di quelle situazioni idrogeologiche che potrebbero comportare all'atto dell'apertura degli scavi rifluimenti idrici di particolare entita.Nel presente lavoro e stata effettuata una applicazione della procedura geostrutturale e di filtrazione idraulica proposta da Pinzani & Coli (2011), ancora in via di sviluppo, per la stima delle portate in galleria attraverso il calcolo del tensore permeabilita a partire da dati geostrutturali. Secondo tale metodologia, le direzioni principali del tensore vengono calcolate attraverso la formula proposta da Kiraly (1969), che tiene conto delle proprieta fisiche e direzionali dei principali sistemi di discontinuita. La valutazione delle portate in condizioni di flusso stazionario relative ai tratti geologicamente omogenei in cui e suddivisa la tratta di galleria in esame viene ottenuta attraverso l'implementazione di un modello di filtrazione agli elementi finiti. Al fine di valutare la funzionalita di tale metodo, nel presente studio si e scelto di applicarlo ad un caso studio relativo ad una sezione trasversale unitaria di una galleria scavata nella Formazione di Monte Morello (Unita Morello), profonda 50-150 m. L'applicazione di questa procedura di filtrazione ha permesso di stimare le portate relative alla tratta di galleria in esame in condizioni stazionarie, e si e rivelata di estremo interesse per individuare i parametri che piu influenzano la variabilita dei risultati.
Persistent Hydrological Consequences of Hurricane Maria in Puerto Rico

In September 2017, Hurricane Maria severely defoliated Puerto Rico's landscape, coinciding with a series of persistent hydrological consequences involving the atmospheric, terrestrial, and marine components of the water cycle. During the defoliated period, the atmosphere's thermodynamic structure more strongly explained daily cloud activity (R2PRE = 0.02; R2POST = 0.40) and precipitation (R2PRE = 0.19; R2POST = 0.33) than before landfall, indicating that post‐Maria land‐atmosphere interactions were comparatively muted, with similar precipitation patterns also found following Hurricanes Hugo (1989) and Georges (1998). Meanwhile, modeled post‐Maria runoff exceeded statistical expectations given the magnitude of contemporaneous precipitation. Enhanced runoff also coincided with greater sediment loads in nearshore waters, increasing sediment content greater than twofold. This study offers a holistic narrative of hydrospheric disturbance and recovery, whereby the instantaneous, large‐scale removal of vegetation is accompanied by hydrologic changes “upstream” in the atmosphere and “downstream” in rivers and estuaries.
Concentration dependences of properties in the region of homogeneity of SnTe

This paper studies the concentration dependences of microhardness, thermo-emf, the x-ray line width, Hall constant, and the coefficient of thermo-emf within the region of homogeneity of SnTe. Special points have been found at a composition ca 50.4 at . % Te in the concentration-dependence curves of properties within the region of homogeneity of SnTe.
Surface-SOS: Self-Supervised Object Segmentation via Neural Surface Representation

Self-supervised Object Segmentation (SOS) aims to segment objects without any annotations. Under conditions of multi-camera inputs, the structural, textural and geometrical consistency among each view can be leveraged to achieve fine-grained object segmentation. To make better use of the above information, we propose Surface representation based Self-supervised Object Segmentation (Surface-SOS), a new framework to segment objects for each view by 3D surface representation from multi-view images of a scene. To model high-quality geometry surfaces for complex scenes, we design a novel scene representation scheme, which decomposes the scene into two complementary neural representation modules respectively with a Signed Distance Function (SDF). Moreover, Surface-SOS is able to refine single-view segmentation with multi-view unlabeled images, by introducing coarse segmentation masks as additional input. To the best of our knowledge, Surface-SOS is the first self-supervised approach that leverages neural surface representation to break the dependence on large amounts of annotated data and strong constraints. These constraints typically involve observing target objects against a static background or relying on temporal supervision in videos. Extensive experiments on standard benchmarks including LLFF, CO3D, BlendedMVS, TUM and several real-world scenes show that Surface-SOS always yields finer object masks than its NeRF-based counterparts and surpasses supervised single-view baselines remarkably. Code is available at: https://github.com/zhengxyun/Surface-SOS.
Machine Learning Method to Explore the Correlation between Fly Ash Content and Chloride Resistance

Chloride ion corrosion has been considered to be one of the main reasons for durability deterioration of reinforced concrete structures in marine or chlorine-containing deicing salt environments. This paper studies the relationship between the amount of fly ash and the durability of concrete, especially the resistance to chloride ion erosion. The heat trend map of total chloride ion factor correlation displayed that the ranking of factor correlations was as follows: sampling depth > cement dosage > fly ash dosage. In order to verify the effect of fly ash dosage on chloride ion resistance, three different machine learning algorithms (RF, GBR, DT) are employed to predict the total chloride content of fly ash proportioned concrete with varying admixture ratios, which are evaluated based on R2, MSE, RMSE, and MAE. The results predicted by the RF model show that the threshold of fly ash admixture in chlorinated salt environments is 30–40%. Replacing part of cement with fly ash in the mixture of concrete below this threshold of fly ash, it could change the phase structure and pore structure, which could improve the permeability of fly ash concrete and reduce the content of free chloride ions in the system. Machine learning modeling using sample data can accurately predict concrete properties, which effectively reduce engineering tests. The development of machine learning models is essential for the decarbonization and intelligence of engineering.
Uplift and denudation history of the Akaishi Range, a thrust block formed by arc‐arc collision in central Japan: Insights from low‐temperature thermochronometry and thermokinematic modeling

Fission track (FT), (U‐Th)/He (He), and U‐Pb data were used to identify the denudation history of the Akaishi Range, central Japan. The northern Akaishi Range is bounded on the east by the Itoigawa‐Shizuoka Tectonic Line Fault Zone (ISTL‐FZ). The thermochronometric ages progressively decrease with the decreasing distance to the ISTL‐FZ. Thermokinematic calculations suggest that the age pattern observed can be explained by 5–7.5 mm/yr reverse slip on the ISTL‐FZ that dips 34–45° west and soles onto detachment at 20–22.5 km depth. By assuming the same geometry and slip rate of the fault, the bedrock uplift rates and denudation rates are estimated at ~4 mm/yr. Thus, the uplift and denudation style of the northern Akaishi Range is well explained as a simple tilted thrust block that has been exhumed along the listric ISTL‐FZ. On the other hand, considering both the difference in apatite FT age and the active fault distribution, the southern Akaishi Range might be different in uplift origin and timing, although the difference in apatite FT ages between them may be attributable to the chlorine content variation in apatite. The inferred total denudation is larger than several kilometers and likely exceeds 10 km since the beginning of the northern Akaishi Range uplift, suggesting that the low‐relief surfaces on the ridges and the relatively constant elevations of the summits reflect postuplift denudation rather than preexisting low‐relief landforms.
Semantics Disentangling for Cross-Modal Retrieval

Cross-modal retrieval (e.g., query a given image to obtain a semantically similar sentence, and vice versa) is an important but challenging task, as the heterogeneous gap and inconsistent distributions exist between different modalities. The dominant approaches struggle to bridge the heterogeneity by capturing the common representations among heterogeneous data in a constructed subspace which can reflect the semantic closeness. However, insufficient consideration is taken into the fact that learned latent representations are actually heavily entangled with those semantic-unrelated features, which obviously further compounds the challenges of cross-modal retrieval. To alleviate the difficulty, this work makes an assumption that the data are jointly characterized by two independent features: semantic-shared and semantic-unrelated representations. The former presents characteristics of consistent semantics shared by different modalities, while the latter reflects the characteristics with respect to the modality yet unrelated to semantics, such as background, illumination, and other low-level information. Therefore, this paper aims to disentangle the shared semantics from the entangled features, andthus the purer semantic representation can promote the closeness of paired data. Specifically, this paper designs a novel Semantics Disentangling approach for Cross-Modal Retrieval (termed as SDCMR) to explicitly decouple the two different features based on variational auto-encoder. Next, the reconstruction is performed by exchanging shared semantics to ensure the learning of semantic consistency. Moreover, a dual adversarial mechanism is designed to disentangle the two independent features via a pushing-and-pulling strategy. Comprehensive experiments on four widely used datasets demonstrate the effectiveness and superiority of the proposed SDCMR method by achieving a new bar on performance when compared against 15 state-of-the-art methods.
Thermo-mechanical investigation of the short glass fibre reinforced epoxy used as the cortical bone analgoue in sawbones femurs

Tensile and four point bending tests were used to assess the material properties of the short glass fibre reinforced (SGFR) epoxy resin that are used as the cortical analogue in third generation Sawbones, at both room (22 degrees Celsius) and body temperatures (37 degrees Celsius). This research demonstrates that the modulus of elasticity of SGFR epoxy used in third generation Sawbones is highly temperature dependent. A reduction in modulus of elasticity of up to 63 percent was observed when increasing the temperature of the specimens from room to body temperature. When performing in vitro total hip modelling ideally the specimens should be at 37°C due to the properties of PMMA cement, however SGFR epoxy Sawbones do not accurately represent bone at this temperature. Hence, this material is not an appropriate model for testing the mechanics of implants that use bone cement.
A type VI secretion system effector TseG of Pantoea ananatis is involved in virulence and antibacterial activity

Abstract The type VI secretion system (T6SS) of many gram‐negative bacteria injects toxic effectors into adjacent cells to manipulate host cells during pathogenesis or to kill competing bacteria. However, the identification and function of the T6SS effectors remains only partly known. Pantoea ananatis, a gram‐negative bacterium, is commonly found in various plants and natural environments, including water and soil. In the current study, genomic analysis of P. ananatis DZ‐12 causing brown stalk rot on maize demonstrated that it carries three T6SS gene clusters, namely, T6SS‐1, T6SS‐2, and T6SS‐3. Interestingly, only T6SS‐1 secretion systems are involved in pathogenicity and bacterial competition. The study also investigated the T6SS‐1 system in detail and identified an unknown T6SS‐1‐secreted effector TseG by using the upstream T6SS effector chaperone TecG containing a conserved domain of DUF2169. TseG can directly interact with the chaperone TecG for delivery and with a downstream immunity protein TsiG for protection from its toxicity. TseG, highly conserved in the Pantoea genus, is involved in virulence in maize, potato, and onion. Additionally, P. ananatis uses TseG to target Escherichia coli, gaining a competitive advantage. This study provides the first report on the T6SS‐1‐secreted effector from P. ananatis, thereby enriching our understanding of the various types and functions of type VI effector proteins.
Dark Green Color Index as a Method of Real-time In-season Corn Nitrogen Measurement and Fertilization

Corn (Zea mays L.) requires higher rates of nitrogen fertilizer th an any other major U.S. crop. Soil and applied N are subject to loss throug h various mechanisms. A timely, accurate, and precise method for measuring in-season corn N statu s is needed to ensure high yield and to allow producers to increase nitrogen use efficiency. Using appropriate software, images from a digital c amera can be used to determine the greenness, or dark green color index (DGCI) of corn leaves, which is closely associated with leaf N concentration. Our objectives were: (1) to deve lop quantitative relationships among yield, corn leaf N concentration and DGCI measurements tak en in the mid-vegetative stages of corn growth; (2) to determine the amount of N to apply t o recover yield based upon DGCI measurements on 6-to-10-leaf corn (V6-V10); and (3) explor e the efficacy of the DGCI method in other, non-leguminous crops. Several regionally-adapted corn hybrids were plante d for 2 years in Arkansas over a range of N treatments. Leaf chlorophyll (SPAD), DG CI, and leaf N measurements were taken prior to midseason N application. There was a signi ficant relationship (p ≤0.05) between DGCI and SPAD (r =0.48 to 0.87), DGCI and leaf N concentration (r =0.56 to 0.70), and SPAD and leaf N concentration (r =0.43 to 0.80). Combining the responses of yield to midseason N application amounts with concurrent mid-season DGCI, SPAD, or leaf N measurements allowed for the development of equations (r 2 f om 0.57 to 0.83) that predicted the amount of N required to attain 90 or 95% of the yield potential. Significant relationships between DGCI and leaf N c oncentrations were also found in other crops tested under varying N treatments. Wint er wheat (r =0.79), bermudagrass (r =0.77), creeping bentgrass (r =0.49), and tall fescue (r =0.53) demonstrated DGCI-leaf N concentration relationships. Flooded rice was sampled but no sign ifica t relationship was found between DGCI and leaf N concentration in those crops. This thesis is approved for recommendation to the Graduate Council. Thesis Directors: Dr. Larry C. Purcell Dr. Morteza Mozzafari
Elevated level of circulating calprotectin correlates with severity and high mortality in patients with COVID‐19

Abstract Background Patients with coronavirus disease‐2019 (COVID‐19) are characterized by hyperinflammation. Calprotectin (S100A8/S100A9) is a calcium‐ and zinc‐binding protein mainly secreted by neutrophilic granulocytes or macrophages and has been suggested to be correlated with the severity and prognosis of COVID‐19. Aim To thoroughly evaluate the diagnostic and prognostic utility of calprotectin in patients with COVID‐19 by analyzing relevant studies. Methods PubMed, Web of Science, and Cochrane Library were comprehensively searched from inception to August 1, 2023 to retrieve studies about the application of calprotectin in COVID‐19. Useful data such as the level of calprotectin in different groups and the diagnostic efficacy of this biomarker for severe COVID‐19 were extracted and aggregated by using Stata 16.0 software. Results Fifteen studies were brought into this meta‐analysis. First, the pooled standardized mean differences (SMDs) were used to estimate the differences in the levels of circulating calprotectin between patients with severe and non‐severe COVID‐19. The results showed an overall estimate of 1.84 (95% confidence interval [CI]: 1.09–2.60). Diagnostic information was extracted from 11 studies, and the pooled sensitivity and specificity of calprotectin for diagnosing severe COVID‐19 were 0.75 (95% CI: 0.64–0.84) and 0.88 (95% CI: 0.79–0.94), respectively. The AUC was 0.89 and the pooled DOR was 18.44 (95% CI: 9.07–37.51). Furthermore, there was a strong correlation between elevated levels of circulating calprotectin and a higher risk of mortality outcomes in COVID‐19 patients (odds ratio: 8.60, 95% CI: 2.17–34.12; p < 0.1). Conclusion This meta‐analysis showed that calprotectin was elevated in patients with severe COVID‐19, and this atypical inflammatory cytokine might serve as a useful biomarker to distinguish the severity of COVID‐19 and predict the prognosis.
Assessing gambling disorder using frequency‐ and time‐based response options: A Rasch analysis of the gambling disorder identification test

Abstract Objectives The Gambling Disorder Identification Test (GDIT) is a recently developed self‐report measure. The GDIT includes items with multiple response options that are either based on frequency or time, and item response theory evaluations of these could yield vital knowledge on its measurement performance. Methods The GDIT was evaluated using Rasch analysis in a study involving 597 Swedish gamblers. Results In a three‐dimensional Rasch model, the item response difficulty range extended from −1.88 to 4.06 and increased with higher time‐ and frequency‐based responses. Differential item functioning showed that some GDIT items displayed age and gender‐related differences. Additionally, person‐separation reliability indicated the GDIT could reliably be divided into three to four diagnostic levels. Conclusions The frequency‐ and time‐based item response options of the GDIT offer excellent measurement, allowing for elaborate assessment across both lower and higher gambling severity. The GDIT can be used to detect DSM‐5 Gambling Disorder, thereby holding significance from both epidemiological and clinical standpoints. Notably, the 3‐item GDIT Gambling Behavior subscale also shows potential as a brief screening tool for identifying at‐risk gambling behavior.