Miracle-dz/UniFAR-FTUs huggingface dataset:
Human Serum and Salivary Metabolomes: Diversity and Closeness

Saliva, which contains molecular information that may reflect an individual’s health status, has become a valuable tool for discovering biomarkers of oral and general diseases. Due to the high vascularization of the salivary glands, there is a molecular exchange between blood and saliva. However, the composition of saliva is complex and influenced by multiple factors. This study aimed to investigate the possible relationships between the salivary and serum metabolomes to gain a comprehensive view of the metabolic phenotype under physiological conditions. Using 1H-NMR spectroscopy, we obtained the serum metabolite profiles of 20 healthy young individuals and compared them with the metabolomes of parotid, submandibular/sublingual, and whole-saliva samples collected concurrently from the same individuals using multivariate and univariate statistical analysis. Our results show that serum is more concentrated and less variable for most of the shared metabolites than the three saliva types. While we found moderate to strong correlations between serum and saliva concentrations of specific metabolites, saliva is not simply an ultrafiltrate of blood. The intense oral metabolism prevents very strong correlations between serum and salivary concentrations. This study contributes to a better understanding of salivary metabolic composition, which is crucial for utilizing saliva in laboratory diagnostics.
Selective submap joining SLAM for autonomous vehicles

Simultaneous Localization and Mapping (SLAM) do not result in consistent maps of large areas because of gradual increase of the uncertainty for long term missions. In addition, as the size of the map grows the computational cost increases, making SLAM solutions unsuitable for on-line applications. This thesis surveys SLAM approaches paying special attention to those approaches aimed to work on large scenarios. Special focus is given to existing underwater SLAM applications. A technique based on using independent local maps together with a global stochastic map is presented. This technique is called Selective Submap Joining SLAM (SSJS). A global map contains relative transformations between local maps, which are updated once a new loop is detected. Maps sharing several features are fused, maintaining the correlation between landmarks and vehicle's pose. The use of local maps reduces computational costs and improves map consistency as compared to state of the art techniques.
Moss flora of Yamal Peninsula (West Siberian Arctic)

Moss flora of Yamal Peninsula (west Siberian Arctic) has been studied in 27 localities. The list includes 276 species and 12 varieties of 33 families and 98 genera, with the information about species distribution in vegetational zones, in studied localities, habitat preferences, species frequency, sporophyte production, and associated species. The biodiversity peculiarities of moss flora are discussed.
Immersive visualization and analysis of Ground Penetrating Radar data

Ground Penetrating Radar devices send pulses from a transmitter into the earth and reflected pulses are collected by a receiver. The data collected is used by geologists to obtain a view of terrain underground. This data is typically viewed using a desktop interface where the user usually interacts using a keyboard and mouse. Visualizing the data in a slice by slice 2D format can be difficult to interpret. Instead of performing the visualization and interaction this way, I designed a program for an immersive visualization environment that uses tracked input devices. The visualization is done using real-time, stereoscopic, perspective-corrected, slice-based volume rendering. To aid with the visualization the user can modify the display of the volume using integrated tools, such as transfer functions, lighting, and color maps. Users are also given data analysis tools that provide natural interactions. These tools allow users to take application-specific measurements such as dip, strike, other angles, and distances in 3D. Compared to typical desktop interface interactions, the 6-degree of freedom user interface provided by the immersive visualization environment makes it notably easier to perform the application-specific measurements.
Dissipative Particle Dynamic Simulation on Self-Assembly of Symmetric CBABC Pentablock Terpolymers in Solution

Pentablock terpolymers are potential candidates for the self-assembly of multicompartment nanostructures. In this work, Dissipative Particle Dynamic simulation is employed to investigate how the equilibrium aggregate structures of C3B3A6B3C3 pentablock terpolymers are affected by polymer–solvent interactions in a solution. Multicompartment structures, such as layered micelles, onion-like micelles, onion-like vesicles, unilamellar vesicles, and vesicle-in-vesicle structures, are observed. Vesicles are obtained when the two end C-blocks or the central A-block are hydrophilic. The solvent encapsulation ability and vesicle membrane permeability are assessed. The unilamellar vesicle shows higher encapsulation efficiency and lower membrane permeability compared with the onion-like vesicles. Additionally, the two vesicles show different responses to shear. While the cargo release rate of the onion-like vesicle is not affected by shear, shear results in a slowdown of the release rate for the unilamellar vesicle. The membrane thickness of the unilamellar vesicle can be adjusted using the length of the central A-blocks. Vesicles with thicker membranes hold cargo more effectively.
Ground Point Detection Method Based on Grid Division and Plane Fitting

Ground point detection is an important part of unmanned driving technology, and the detection results will affect the subsequent tasks. Aiming at the problem of under-segmentation and mis-segmentation of lidar ground point segmentation in unstructured scenes, a ground point recognition method based on grid division is proposed. This method first uses the constraint conditions to preprocess and extract the ROI region; secondly, the point cloud is divided by the method of grid division; finally, the plane fitting method is used to realize the ground point recognition. Based on the structured data set KITTI and the unstructured data set ORFD data set, this paper compares them with RANSAC, LF and HDL algorithms. The experimental results show that the algorithm in this paper can segment the ground points well, which is superior to the three algorithms compared in the evaluation index, and can detect the ground points quickly and accurately.
Dynamic Timeframe and Anticipation-Based Migration: A Real-Time Framework for Ride-Sharing

Efficient and reliable ride-sharing services have gained significant attention in recent years as a means to address traffic congestion and reduce environmental impact. This paper presents a novel real-time ride-sharing framework that incorporates dynamic timeframes and anticipation-based migration to enhance the overall experience for users. The proposed framework leverages advanced algorithms and intelligent systems to optimize the matching of riders and drivers, considering various factors such as proximity, destination compatibility, and anticipated travel patterns. By dynamically adjusting the timeframe for ride requests and introducing anticipation-based migration, the framework aims to minimize waiting times and maximize resource utilization. The effectiveness of the framework is evaluated through extensive simulations, demonstrating its ability to improve the efficiency, scalability, and reliability of ride-sharing systems. The results highlight the potential of the proposed approach to revolutionize the ride-sharing industry and contribute towards more sustainable urban transportation solutions.
PSNS-SSD: Pixel-Level Suppressed Nonsalient Semantic and Multicoupled Channel Enhancement Attention for 3D Object Detection

In the field of 3D object detection, voxel-based methods are the most commonly used and exhibit high accuracy. However, point-based networks, which have the capability to preserve the original point features, are unable to surpass the accuracy achieved by voxel-based methods. We observed that during downsampling, too many useless background points are retained in the prevailing farthest point sample, which interferes with the accuracy of the point-based network and introduces redundant computation. To address this issue, in this letter, a point-based single-stage 3D detection network called PSNS-SSD is designed, and its accuracy rivals the accuracy of the two-stage voxel-based methods. Our method leverages the semantic information that suppresses nonsalient features used for guidance and discards background points during the downsampling process. In addition, we propose two modules, namely, linear-conv channel-enhanced self-attention for point cloud feature extraction and global-local coupling attention for center prediction, to enhance the performance and efficiency of our model. Our PSNS-SSD model is extensively tested on the most widely available 3D dataset—the KITTI dataset. The experimental results validate the three proposed modules in terms of accuracy for small object detection and speed, and the model achieves accuracy levels that are on par with the accuracy levels of cutting-edge voxel-based techniques. Moreover, our detector can achieve a speed of 70 FPS on the KITTI dataset, making it a promising candidate for practical applications.
A Holistic View of Psoriasis: Examining Its Association With Dyslipidemia and Obesity in a Decade-Long Systematic Review and Meta-Analysis

Psoriasis is a multifaceted inflammatory condition with systemic implications, impacting not only the skin but also various organs and overall health. It is associated with mood disorders, malignancy, infections, and components of metabolic syndrome, including diabetes, atherogenic dyslipidemia, and obesity. The coexistence of psoriasis with obesity poses additional challenges, as obesity worsens psoriasis severity and reduces treatment effectiveness. This systematic review and meta-analysis aim to further understand the associations between psoriasis, dyslipidemia, and obesity. Our systematic review of six studies revealed significant links between psoriasis and both dyslipidemia and obesity. Individuals with psoriasis exhibited a 1.40-fold higher likelihood of dyslipidemia (odds ratio (OR) 1.40, 95% confidence interval (CI) 1.24-1.58) and a 1.37-fold higher likelihood of obesity (OR 1.37, 95% CI 1.23-1.53) compared to those without psoriasis. These findings emphasize the systemic nature of psoriasis and its implications for metabolic health. In conclusion, this review underscores the importance of holistic management for psoriasis patients. Further research is warranted to explore underlying mechanisms and develop targeted therapeutic strategies. These findings contribute valuable insights to promote the overall well-being of individuals with psoriasis.
Non-Invasive Evaluation of Retinal Vascular Alterations in a Mouse Model of Optic Neuritis Using Laser Speckle Flowgraphy and Optical Coherence Tomography Angiography

Optic neuritis, a characteristic feature of multiple sclerosis (MS), involves the inflammation of the optic nerve and the degeneration of retinal ganglion cells (RGCs). Although previous studies suggest that retinal blood flow alterations occur during optic neuritis, the precise location, the degree of impairment, and the underlying mechanisms remain unclear. In this study, we utilized two emerging non-invasive imaging techniques, laser speckle flowgraphy (LSFG) and optical coherence tomography angiography (OCTA), to investigate retinal vascular changes in a mouse model of MS, known as experimental autoimmune encephalomyelitis (EAE). We associated these changes with leukostasis, RGC injury, and the overall progression of EAE. LSFG imaging revealed a progressive reduction in retinal blood flow velocity and increased vascular resistance near the optic nerve head in the EAE model, indicating impaired ocular blood flow. OCTA imaging demonstrated significant decreases in vessel density, number of junctions, and total vessel length in the intermediate and deep capillary plexus of the EAE mice. Furthermore, our analysis of leukostasis revealed a significant increase in adherent leukocytes in the retinal vasculature of the EAE mice, suggesting the occurrence of vascular inflammation in the early development of EAE pathology. The abovechanges preceded or were accompanied by the characteristic hallmarks of optic neuritis, such as RGC loss and reduced visual acuity. Overall, our study sheds light on the intricate relationship between retinal vascular alterations and the progression of optic neuritis as well as MS clinical score. It also highlights the potential for the development of image-based biomarkers for the diagnosis and monitoring of optic neuritis as well as MS, particularly in response to emerging treatments.
Eocene to Pleistocene magmatic evolution of the Delarof Islands, Aleutian Arc

The Delarof Islands in the Aleutian Arc near 179º W record ∼37 million years of discontinuous arc magmatism along a SW‐NE cross‐arc transect from near the trench to the active volcanic front. Geochemical and geochronologic data from the pre‐Pleistocene volcanic record in this region are limited and the 40Ar/39Ar, isotopic, and trace element data presented here are the first from units older than the Pleistocene‐Holocene volcanoes (Tanaga, Gareloi). Twenty‐two new 40Ar/39Ar ages establish a temporal framework for geochemical data and reveal that magmatism in the Delarof region was coincident with two arc‐wide magmatic flare ups in the late Eocene/early Oligocene and latest Miocene/Pliocene. Mafic lavas and plutons in the southern Delarofs give 40Ar/39Ar plateau ages ranging from 36.8 ± 0.2 to 26.9 ± 0.6 Ma on Amatignak Island and 37.0 ± 0.2 to 29.3 ± 1.0 Ma on Ulak Island. To the north 25 km, 40Ar/39Ar ages from the central Delarof Islands, Kavalga, Ogliuga, and Skagul are late Miocene (6.28 ± 0.04 Ma) to Pliocene (4.77 ± 0.18 Ma) with younger ages to the northeast. A significant transition in arc chemistry occurs in the Pleistocene where lavas from active volcanoes Gareloi and Tanaga exhibit higher sediment and hydrous fluid signatures (Th/La, Cs/Ta, La/Sm, LILE abundances) and lower 143Nd/144Nd than older Delarof Island units closer to the trench. Similar findings from Eocene‐Miocene lavas from Amchitka to Adak suggest that a previously minor sediment melt component became more pronounced in the Quaternary.
Is the C-Terminal Domain an Effective and Selective Target for the Design of Hsp90 Inhibitors against Candida Yeast?

Improving the armamentarium to treat invasive candidiasis has become necessary to overcome drug resistance and the lack of alternative therapy. In the pathogenic fungus Candida albicans, the 90-kDa Heat-Shock Protein (Hsp90) has been described as a major regulator of virulence and resistance, offering a promising target. Some human Hsp90 inhibitors have shown activity against Candida spp. in vitro, but host toxicity has limited their use as antifungal drugs. The conservation of Hsp90 across all species leads to selectivity issues. To assess the potential of Hsp90 as a druggable antifungal target, the activity of nine structurally unrelated Hsp90 inhibitors with different binding domains was evaluated against a panel of Candida clinical isolates. The Hsp90 sequences from human and yeast species were aligned. Despite the degree of similarity between human and yeast N-terminal domain residues, the in vitro activities measured for the inhibitors interacting with this domain were not reproducible against all Candida species. Moreover, the inhibitors binding to the C-terminal domain (CTD) did not show any antifungal activity, with the exception of one of them. Given the greater sequence divergence in this domain, the identification of selective CTD inhibitors of fungal Hsp90 could be a promising strategy for the development of innovative antifungal drugs.
Gastrointestinal Fistulas in Necrotizing Pancreatitis Receiving a Step-Up Approach Incidence, Risk Factors, Outcomes and Treatment

Purpose Necrotizing pancreatitis (NP) complicated by gastrointestinal fistula is challenging and understudied. As the treatment of necrotizing pancreatitis changed to a step-up strategy, we attempted to evaluate the incidence, risk factors, clinical outcomes and treatment of gastrointestinal fistulas in patients receiving a step-up approach. Methods Clinical data from 1274 patients with NP from 2014–2022 were retrospectively analyzed. Multivariable logistic regression analysis was conducted to identify risk factors and propensity score matching (PSM) to explore clinical outcomes in patients with gastrointestinal fistulas. Results Gastrointestinal fistulas occurred in 8.01% (102/1274) of patients. Of these, 10 were gastric fistulas, 52 were duodenal fistulas, 14 were jejunal or ileal fistulas and 41 were colonic fistulas. Low albumin on admission (OR, 0.936), higher CTSI (OR, 1.143) and invasive intervention prior to diagnosis of gastrointestinal fistula (OR, 5.84) were independent risk factors for the occurrence of gastrointestinal fistula, and early enteral nutrition (OR, 0.191) was a protective factor. Patients who developed a gastrointestinal fistula were in a worse condition on admission and had a poorer clinical outcome (p<0.05). After PSM, both groups of patients had similar baseline information and clinical characteristics at admission. The development of gastrointestinal fistulas resulted in new-onset persistent organ failure, increased open surgery, prolonged parenteral nutrition and hospitalization, but not increased mortality. The majority of patients received only conservative treatment and minimally invasive interventions, with 7 patients (11.3%) receiving surgery for upper gastrointestinal fistulas and 11 patients (26.9%) for colonic fistulas. Conclusion Gastrointestinal fistulas occurred in 8.01% of NP patients. Independent risk factors were low albumin, high CTSI and early intervention, while early enteral nutrition was a protective factor. After PSM, gastrointestinal fistulas resulted in an increased proportion of NP patients receiving open surgery and prolonged hospitalization. The majority of patients with gastrointestinal fistulas treated with step-up therapy could avoid surgery.
Poultry genetic resources in the countries of Eastern Europe – history and current state

Native poultry breeds of East-European countries suffered considerable losses during the Second World War and as a result of the ''socialization'' of agriculture. Currently, steps are being taken to protect against extinction of all that remains. Most advanced in the programme of preservation of the native breeds of chickens, turkeys, ducks, geese and other domestic and game birds are: the Czech Republic, Hungary, Poland, Romania, Russia, Slovakia & Ukraine. The authors are aware of the limited range of the presented material but a serious drawback has been the lack of information available from Albania, Bulgaria, Byelarus, Estonia, Latvia, Lithuania, Moldova and former Yugoslavia. The studies carried out so far suggest that in the countries of Eastern Europe there is awareness of the necessity to maintain for future generations established native breeds of poultry not only as genetic resources indispensable for further breeding activities, but also as live evidence of the great achievements of many generations of past breeders. The present survey has allowed us to summarize information on 56 indigenous breeds, varieties and strains of chickens, 13 of turkeys, four of Japanese quail, three of guinea fowl, nine of ducks and 36 of geese preserved in East-European countries as poultry genetic resources. The most impressive poultry breed collection is in Russia, with 50 native breeds (24 of chickens, seven of turkeys, one of Japanese quail, three of guinea fowl, four of ducks and 11 of geese). Ukraine and Poland are also remarkable for the large poultry genetic resources numbering respectively 20 (eight of chickens, one of turkeys, four of ducks and seven of geese) and 18 (seven of chickens, two of Japanese quail and nine of geese) native breeds, varieties and strains.
VARIASI BULANAN GELOMBANG LAUT DI INDONESIA

Indonesia merupakan negara kepulauan yang sebagian besar wilayahnya adalah perairan, maka segala aktivitas di laut menjadi bagian penting bagi kehidupan masyarakat Indonesia. Fenomena laut yang sangat mempengaruhi efisiensi dan keselamatan di laut adalah gelombang tinggi, oleh karena itu diperlukan informasi tentang variasi dan karakteristik tinggi gelombang di perairan Indonesia. Gelombang laut yang paling dominan diakibatkan oleh faktor angin, maka perhitungan tinggi gelombang laut dalam kajian ini menggunakan model gelombang Windwaves-05, dimana model ini menghitung tinggi gelombang berdasarkan energi dari angin permukaan. Hasil dari kajian ini menunjukkan bahwa, variasi gelombang di perairan Indonesia berkaitan erat dengan pola angin musiman yang terjadi di wilayah Indonesia. Pada saat monsun Asia dan Australia (DJF dan JJA), rata-rata tinggi gelombang lebih tinggi dibanding pada masa peralihan (MAM dan SON) dan puncak rata-rata gelombang tertinggi terjadi pada bulan Januari dan Juli. Rata-rata tinggi gelombang di wilayah perairan terbuka lebih tinggi dibandingkan dengan perairan antar pulau, kondisi ini terjadi karena adanya perbedaan panjang fetch yang terbentuk di wilayah perairan tersebut. Indonesia archipelago mostly consists of waters. All activities in the oceans become an important part of Indonesian society. One of the phenomena affects the efficiency and safety on the oceans is ocean wave heights, therefore, information about characteristics and variations of wave height is crucial to be studied. Wind wave is the most dominant factor on the ocean, so this study utilized Windwaves-05 model to produce the wave height value based on the surface wind energy. The results of this study indicate that the ocean wave variations are closely related to seasonal wind patterns over Indonesia. During the Asian and Australia monsoon (DJF and JJA), mean of wave height is higher than during the transition period (MAM and SON). Mean of the highest ocean waves occurrs on February and July. Mean of wave height on the offshore waters is higher than on the inter-islands waters, this condition caused by different fetch length.
Characterization of the Guinea Pig Production Chain in Southern Colombia and Identification of Determining Factors for Adequate Provision of Extension Services

The development of agrifood systems in Latin America reflects contrasting policy goals. Most governments advocate that “modernization,” measured as increased rates of technology adoption, is the way to address persistent food insecurity. By contrast, peasants’ and indigenous people’s organizations and social movements propose advancing knowledge co-production and co-innovation to increase the resilience of agrifood systems. Colombia reformed the National Innovation System for Agriculture in 2017. The policy reform instructed transitioning from providing “technical advice” to rural extension services. The research aimed to fill the knowledge gap regarding the transition to rural extension along the guinea pig production chain. In addition to characterizing the production chain, we conducted qualitative and reflectivity analyses to understand better how institutional practices and research cultures hinder or promote transitioning to rural extension. The investigation revealed that small-scale farmers who rely on the production and commercialization of guinea pigs as a livelihood strategy have continued receiving advice to adopt the latest technologies. In closing, besides addressing technological deficits or inefficiencies, a systemic approach that considers cultural context and identity must integrate into rural extension to ensure technological adoption is aligned with the sustainability and resilience objectives of the guinea pig production chain.