Miracle-dz/UniFAR-FTUs huggingface dataset:
MPGraf: a Modular and Pre-trained Graphformer for Learning to Rank at Web-scale

Both Transformer and Graph Neural Networks (GNNs) have been used in learning to rank (LTR), they however adhere to two distinct-yet-complementary problem formulations, i.e., ranking score regression based on query-webpage pairs and link prediction within query-webpage bipartite graphs, respectively. Though it is possible to pre-train GNNs or Transformers on source datasets and fine-tune them subject to sparsely annotated LTR datasets separately, the source-target distribution shifts across the pairs and bipartite graphs domains make it extremely difficult to integrate these diverse models into a single LTR framework at a web-scale. We introduce the novel MPGraf model, which utilizes a modular and capsule-based pre-training approach, aiming to incorporate regression capacities from Transformers and link prediction capabilities of GNNs cohesively. Specifically, rather than simply combining these two modules in stacking or parallelizing architectures, MPGraf proposes a three-step method to (1) construct query-webpage graphs from sparsely annotated query-webpage pairs, (2) pre-train the Transformer and GNN modules using source datasets from two domains, and (3) “surgically” fine-tune the integrated models with pretrained weights while handling the distribution shifts of two domains. Extensive experiments have been done to evaluate the performance of MPGraf using real-world datasets collected from large-scale search engines. The results show that MPGraf can outperform baseline algorithms on several major metrics. Further, we deploy and evaluate MPGraf atop a large-scale search engine with realistic web traffics via A/B tests, where we can still observe significant improvement. MPGraf performs consistently in both offline and online evaluations.
Mutational Dynamics Related to Antibiotic Resistance in M. tuberculosis Isolates from Serial Samples of Patients with Tuberculosis and Type 2 Diabetes Mellitus

Genetic variation in tuberculosis is influenced by the host environment, patients with comorbidity, and tuberculosis–type 2 diabetes mellitus (TB-T2DM) and implies a higher risk of treatment failure and development of drug resistance. Considering the above, this study aimed to evaluate the influence of T2DM on the dynamic of polymorphisms related to antibiotic resistance in TB. Fifty individuals with TB-T2DM and TB were initially characterized, and serial isolates of 29 of these individuals were recovered on day 0 (diagnosis), 30, and 60. Genomes were sequenced, variants related to phylogeny and drug resistance analyzed, and mutation rates calculated and compared between groups. Lineage X was predominant. At day 0 (collection), almost all isolates from the TB group were sensitive, apart from four isolates from the TB-T2DM group showing the mutation katG S315T, from which one isolate had the mutations rpoB S450L, gyrA A90G, and gyrA D94G. This pattern was observed in a second isolate at day 30. The results provide a first overview of the dynamics of mutations in resistance genes from individuals with TB-T2DM, describing an early development of resistance to isoniazid and a rapid evolution of resistance to other drugs. Although preliminary, these results help to explain the increased risk of drug resistance in individuals with TB and T2DM.
Analysis of the Effects of Pentose Phosphate Pathway Inhibition on the Generation of Reactive Oxygen Species and Epileptiform Activity in Hippocampal Slices

The pentose phosphate pathway (PPP) is one of three major pathways involved in glucose metabolism, which is regulated by glucose-6-phosphate dehydrogenase (G6PD) controls NADPH formation. NADPH, in turn, regulates the balance of oxidative stress and reactive oxygen species (ROS) levels. G6PD dysfunction, affecting the PPP, is implicated in neurological disorders, including epilepsy. However, PPP’s role in epileptogenesis and ROS production during epileptic activity remains unclear. To clarify these points, we conducted electrophysiological and imaging analyses on mouse hippocampal brain slices. Using the specific G6PD inhibitor G6PDi−1, we assessed its effects on mouse hippocampal slices, examining intracellular ROS, glucose/oxygen consumption, the NAD(P)H level and ROS production during synaptic stimulation and in the 4AP epilepsy model. G6PDi−1 increased basal intracellular ROS levels and reduced synaptically induced glucose consumption but had no impact on baselevel of NAD(P)H and ROS production from synaptic stimulation. In the 4AP model, G6PDi−1 did not significantly alter spontaneous seizure frequency or H2O2 release amplitude but increased the frequency and peak amplitude of interictal events. These findings suggest that short-term PPP inhibition has a minimal impact on synaptic circuit activity.
Simulation of Hydrology of Short Rotation Hardwood Plantations

A 76 ha hardwood plantation at Trice Research Forest near Sumter, SC is being used to study forest hydrology on an operational scale. The overall objective of this project is to develop tools to enable forest managers to assess and manage sustainable short rotation woody crop production systems. This paper reports on the use of the water management model, WATRCOM, as a tool for assessing and managing hydrology and water use in these plantations. Four drainage catchments are being monitored for surface and subsurface movement of water and nutrients. The water management model, WATRCOM, is being tested and evaluated on these catchments. Two years of field data are compared to model simulations. Future model development and application to these sites are also discussed.
Human-Induced Pluripotent Stem Cells in Plastic and Reconstructive Surgery

A hallmark of plastic and reconstructive surgery is restoring form and function. Historically, tissue procured from healthy portions of a patient’s body has been used to fill defects, but this is limited by tissue availability. Human-induced pluripotent stem cells (hiPSCs) are stem cells derived from the de-differentiation of mature somatic cells. hiPSCs are of particular interest in plastic surgery as they have the capacity to be re-differentiated into more mature cells, and cultured to grow tissues. This review aims to evaluate the applications of hiPSCs in the plastic surgery context, with a focus on recent advances and limitations. The use of hiPSCs and non-human iPSCs has been researched in the context of skin, nerve, vasculature, skeletal muscle, cartilage, and bone regeneration. hiPSCs offer a future for regenerated autologous skin grafts, flaps comprised of various tissue types, and whole functional units such as the face and limbs. Also, they can be used to model diseases affecting tissues of interest in plastic surgery, such as skin cancers, epidermolysis bullosa, and scleroderma. Tumorigenicity, immunogenicity and pragmatism still pose significant limitations. Further research is required to identify appropriate somatic origin and induction techniques to harness the epigenetic memory of hiPSCs or identify methods to manipulate epigenetic memory.
Examining the energetics of secondary downstream development for two

نيا رد قيقحت و يدروراشف شرتسگ و دشر يراشفژك جوم ود هرايس و هيروس ،هنارتيدم يايرد قرش هيحان رد يا ناريا برغ و شنكردنا اهنآ اب نيمز حطس ياهدنخرچ هدش يسررب يژرنا هاگديد زا تسا . هداد زا هدافتسا اب ياه CFSR يقفا كيكفت اب 5 . / هجرد هفلوم و يژرنا رادقم ه يا نوگانوگ تسا هدش هبساحم اهدنخرچ نيا يارب يژرنا شيارگ . هيوناژ هب طوبرم لوا دنخرچ 2004 برغ يور لكش هنارتيدم يم گ ي ر ناريا برغ يحاون ات دوخ ريسم يط رد اما فيعضت هنارتيدم قرش يور و د رد تيوقت رگيد هيحان ود يم دوش . يم ناشن جياتن هك دهد مهم نيرت لماع زكرم هيوناث دشر يژرنا رد نايرج وس ي هوان يور و ناتسبرع لامش سپس و هنارتيدم قرش و يژرنا يراشفژك ليدبت ناريا برغ آ راش ييارگمه يمز ن درگ تسا يژرنا . لاس هيوناژ هب طوبرم مود دنخرچ يارب 2000 ، لوا دروم هباشم يور يوق يژرنا زكرم كي ادتبا يايرد داپ رد هنارتيدم نايرج وس ي هوان دراد دوجو . دروم نيا رد تج روضح بنج هراح بجوم آ راش درگنيمز يوق هب زكرم نيا زا يژرنا نايرج وس هوان ي هجيتن رد و بجوم شرتسگ نايرج وس يژرنا زكرم ي يور ناريا برغ و ناتسبرع لامش يم دوش . و ناتسبرع لامش رد مرگ ياوه تفرارف شقن نينچمه شرتسگ و يراشفژك لماع تيوقت رد ناريا برغ رد اوه يرابجا دوعص سپس و هنارتيدم قرش نايرج وس دروم نيا يارب يژرنا ي ، تسا نيشيپ دروم هباشم . نيا رد اما يدروراشف لماع شقن دروم ) شنت زدلونير ياه ( لباق يژرنا زكرم نيا تيوقت رد زين تسا هجوت . هب نايب تج ريثات رگيد بنج هراح يم هديد ناريا برغ بونج رد دنخرچ تيوقت رد يا دوش .
Model Cloaking against Gradient Leakage

Gradient leakage attacks are dominating privacy threats in federated learning, despite the default privacy that training data resides locally at the clients. Differential privacy has been the de facto standard for privacy protection and is deployed in federated learning to mitigate privacy risks. However, much existing literature points out that differential privacy fails to defend against gradient leakage. The paper presents ModelCloak, a principled approach based on differential privacy noise, aiming for safe-sharing client local model updates. The paper is organized into three major components. First, we introduce the gradient leakage robustness trade-off, in search of the best balance between accuracy and leakage prevention. The trade-off relation is developed based on the behavior of gradient leakage attacks throughout the federated training process. Second, we demonstrate that a proper amount of differential privacy noise can offer the best accuracy performance within the privacy requirement under a fixed differential privacy noise setting. Third, we propose dynamic differential privacy noise and show that the privacy-utility trade-off can be further optimized with dynamic model perturbation, ensuring privacy protection, competitive accuracy, and leakage attack prevention simultaneously.
Environmental microbial diversity and anthropogenic impact on Lake Thingvallavatn basin

Lake Thingvallavatn is a unique groundwater dependent ecosystem. The water originates from glacier melt water and precipitation falling over the basin, located north of the lake. The basin stretches approximately 1300 km, largely consisting of wilderness that reaches Langjökull and Thórisjökull glacier in the north. The objectives of the study were to investigate the diversity of microbial communities of Lake Thingvallavatn and two fissures in its basin by differentiating the patterns of phylogenic composition and to establish a microbiological baseline that will enhance the understanding of this unusual ecosystem. In addition, one of the objectives was to evaluate environmental risks of anthropocentric activity to the lake by measuring potential faecal contamination. The results of this study indicate that microbial diversity in Lake Thingvallavatn is not as homogenous as one might think. Cell count and microbial diversity range significantly between sampling locations, showing differences among Lake Thingvallavatn and groundwater fissures in its basin. Furthermore, seasonal variation occurs in the lake but less variation was observed between different depth intervals. Diversity indices were used to estimate biodiversity at the sampling stations. Silfra shows the greatest diversity of all sampling stations in this study, followed by Flosagjá and Lake Thingvallavatn. Lake Thingvallavatn does not seem to follow a global distribution in microbial diversity compared to other freshwater lakes. The reasons behind this might be that Lake Thingvallavatn is a sub-artic lake ecosystem characterized by extreme conditions with especially low and stable water temperature that originates from the lake basin. Sequencing Archaea from Lake Thingvallavatn ecosystem proofed very difficult but members of Crenarcheaota and Euryarcaeota were found. Results show that faecal contamination is present in the lake. One location within Thingvellir National Park came back positive for both E. coli and Enterococcus spp. According to the Thingvellir National Park authorities, 15.126 scuba divers and snorkelers visited Silfra from March of 2013 to March of 2014. No legislations exist in Iceland that oversees the import of scuba diving equipment, which increases the risk of introducing new species to vulnerable ecosystems in Iceland. The author of this paper suggests that legislation on imported scuba equipment should be implemented in Iceland.
Entropy Maximization in High Dimensional Multiagent State Spaces

Underwater or planetary exploration are prime examples of missions that can benefit from autonomous agents working together. However, discovering effective team-level behaviors (i.e., coordinated joint actions) is challenging in these domains as agents typically receive a sparse reward (zero-or constant-for the majority of the interactions). To address this issue, intrinsic rewards encourage agents to explore diverse policies to visit the state space more effectively. Unfortunately, as the agents’ state space grows, intrinsic reward-based (i.e., curiosity) approaches become less effective as they cannot effectively distinguish a diverse set of states. In this direction, we introduce state entropy maximization for multiagent learning where agents explore using local (dense) rewards and learn to solve the coordination task by leveraging global (sparse) rewards. Because of the intrinsic ability to balance local and global rewards, our approach enables the state entropy function to remain effective in high dimensional state spaces. Experiments in tightly coupled tasks requiring complex joint actions, show that local entropy-based rewards enable agents to discover successful team behaviors in high dimensional spaces where previous hand-tuned count-based rewards fail.
Exploring Unseen Characteristics of Artificial Neural Networks for Improving Front Teat Placement Trait

We unfold the potential characteristics of artificial neural networks for cattle front teat placement trait, which refers to the location of a cow’s teats on its udder, specifically the placement of the front teats. For this purpose, we explore four deep learning models, namely the ResNet50 model (RNET50), the EfficientNet B1 model (ENET), a smaller customized convolutional model (SCNN), and a bigger customized convolutional model (BCNN). These models have variaitons in the feature extraction process. Our work contributes to the adoption of machine learning in cattle teat placement which is still in its early stage. We performed comprehensive experimental analysis on the front teat placement dataset we collected and prepared. We used the performance metrics: mean absolute error and average mean absolute error. We also exploit different augmentation techniques to encode variations in the collected data. These quantitative assessments provide good insights into how different architectures articulate around the front teat placement trait by capturing non-linear relationships conditioned on augmented and non-augmented data.
S-Allyl-L-Cysteine Affects Cell Proliferation and Expression of H2S-Synthetizing Enzymes in MCF-7 and MDA-MB-231 Adenocarcinoma Cell Lines

S-allyl-L-cysteine (SAC) is a sulfur compound present in fresh garlic. The reference literature describes its anticancer, antioxidant and neuroprotective effects. Breast cancer is infamously known as one of the most commonly diagnosed malignancies among women worldwide. Its morbidity and mortality make it reasonable to complete and expand knowledge on this cancer’s characteristics. Hydrogen sulfide (H2S) and its naturally occurring donors are well-known investigation subjects for diverse therapeutic purposes. This study was conducted to investigate the SAC antiproliferative potential and effect on three enzymes involved in H2S metabolism: 3-mercaptopyruvate sulfurtransferase (MPST), cystathionine γ-lyase (CTH), and cystathionine β-synthase (CBS). We chose the in vitro cellular model of human breast adenocarcinomas: MCF-7 and MDA-MB-231. The expression of enzymes after 2, 4, 6, 8, and 24 h incubation with 2.24 mM, 3.37 mM, and 4.50 mM SAC concentrations was examined. The number of living cells was determined by the MTS assay. Changes in cellular plasma membrane integrity were measured by the LDH test. Expression changes at the protein level were analyzed using Western blot. A significant decrease in viable cells was registered for MCF-7 cells after all incubation times upon 4.50 mM SAC exposure, and after 6 and 24 h only in MDA-MB-231 upon 4.50 mM SAC. In both cell lines, the MPST gene expression significantly increased after the 24 h incubation with 4.50 mM SAC. S-allyl-L-cysteine had opposite effects on changes in CTH and CBS expression in both cell lines. In our research model, we confirmed the antiproliferative potential of SAC and concluded that our studies provided current information about the increase in MPST gene expression mediated by S-allyl-L-cysteine in the adenocarcinoma in vitro cellular model for the MCF-7 and MDA-MB-231 cell lines. Further investigation of this in vitro model can bring useful information regarding sulfur enzyme metabolism of breast adenocarcinoma and regulating its activity and expression (gene silencing) in anticancer therapy.
Preconditioning point-source/point-receiver high-density 3D seismic data for lacustrine shale characterization in a loess mountain area

AbstractIn the study area, southeast of Ordos Basin in China, thick lacustrine shale/mudstone strata have been developed in the Triassic Yanchang Formation. Aiming to study these source/reservoir rocks, a 3D full-azimuth, high-density seismic survey was acquired. However, the surface in this region is covered by a thick loess layer, leading to seismic challenges such as complicated interferences and serious absorption of high frequencies. Despite a specially targeted seismic processing workflow, the prestack Kirchhoff time-migrated seismic data were still contaminated by severe noise, hindering seismic inversion and geologic interpretation. By taking account of the particular data quality and noise characteristics, we have developed a cascade workflow including three major methods to condition the poststack 3D seismic data. First, we removed the sticky coherent noise by a local pseudo f-x-y Cadzow filtering. Then, we diminished the random noise by a structure-oriented filtering. Finally, we extended the f.
Thermal evolution of a hyperextended rift basin, Mauléon Basin, western Pyrenees

Onshore and offshore geological and geophysical observations and numerical modeling have greatly improved the conceptual understanding of magma‐poor rifted margins. However, critical questions remain concerning the thermal evolution of the prerift to synrift phases of thinning ending with the formation of hyperextended crust and mantle exhumation. In the western Pyrenees, the Mauléon Basin preserves the structural and stratigraphic record of Cretaceous extension, exhumation, and sedimentation of the proximal‐to‐distal margin development. Pyrenean shortening uplifted basement and overlying sedimentary basins without pervasive shortening or reheating, making the Mauléon Basin an ideal locality to study the temporal and thermal evolution of magma‐poor hyperextended rift systems through coupling bedrock and detrital zircon (U‐Th)/He thermochronometric data from transects characterizing different structural rifting domains. These new data indicate that the basin was heated during early rifting to >180°C with geothermal gradients of ~80–100°C/km. The proximal margin recorded rift‐related exhumation/cooling at circa 98 Ma, whereas the distal margin remained >180°C until the onset of Paleocene Pyrenean shortening. Lithospheric‐scale numerical modeling shows that high geothermal gradients, >80°C/km, and synrift sediments >180°C, can be reached early in rift evolution via heat advection by lithospheric depth‐dependent thinning and blanketing caused by the lower thermal conductivity of synrift sediments. Mauléon Basin thermochronometric data and numerical modeling illustrate that reheating of basement and synrift strata might play an important role and should be considered in the future development of conceptual and numerical models for hyperextended magma‐poor continental rifted margins.
Canada Goose，一只高傲的鹅

Canada Goose服装售价不菲,一件羽绒服外套折合人民币最低也要数干块钱，动辄便上万——然而这在如今这个消费者日趋理性、更加注重性价比的时代，却成为了CanadaGoose能够更上一层楼的重要原因。
Microphysical Simulation of Polar Stratospheric Clouds Within the Community Earth System Model

Polar stratospheric clouds (PSCs) are critical elements for polar ozone depletion. A new PSC model coupling stratospheric chemistry, microphysics and climate is constructed and the formation of STS (Super-cooled Ternary Solution) and NAT (Nitric-Acid Trihydrate) PSCs are explored STS particle properties are dominated by thermodynamics. Simulations of particle volumes and size distributions are generally within the observational error bars. STS particles are not in equilibrium with their environment when the particle surface area is smaller than 4 μm 2 /cm 3 . A new nucleation rate equation for NAT is derived based on observed denitrification in the 2010-2011 Arctic winter. The homogeneous nucleation scheme leads to supermicron NAT particles as observed. The simulated the lidar backscatter, and denitrification are generally within observational error bars. However, the simulations are very sensitive to temperature. Using the same STS and NAT schemes, as well as a prognostic treatment for ice PSC formation and dehydration, the PSCs are simulated during the Antarctic winter of 2010. The current model correctly simulates large NAT particles and denitrification, but cannot produce NAT with high backscattering ratio/number density sometimes observed by CALIPSO. However, our simulated ice has similar backscatter and depolarization which is often attributed to NAT by CALIPSO. Possibly the CALIPSO algorithm misclassifies ice as NAT when the stratosphere is denitrified or dehydrated. STS and NAT form near the pole in May and June, but form a ring outside 80˚S later in the winter when polar HNO3 is depleted. Ice always forms in the coldest area, but becomes less abundant later in the winter. The model is missing some processes forming NAT such as gravity waves or evaporating ice. These processes should be added to the model in the future.
A novel Broadband Millimeter-Wave Microstrip Antenna for 5G Applications

The purpose of this work is to design a broadband millimeter-wave antenna that operates in the 28.42 GHz, 30.57 GHz, and 36.27 GHz frequency bands for 5G applications. That was done by etching four slots in the radiation element. To simulate this patch antenna and determine its electromagnetic properties, we used the commercially available software CST Microwave Studio (electromagnetic simulator) based on the FDTD method (S11, gain, VSWR, and current distribution), then we used HFSS to validate our results. Moreover, the antenna result shows an average gain of 4.27 dBi, a VSWR under 2 at all resonant frequencies, and a bandwidth of approximately 14 GHz from 26 GHz to 40 GHz. In addition, we can use the reconfigurability function on this antenna by using the PIN diode.
Connectivity-Preserving Distributed Informative Path Planning for Mobile Robot Networks

This letter addresses the distributed informative path planning (IPP) problem for a mobile robot network to optimally explore a spatial field. Each robot is able to gather noisy environmental measurements while navigating the environment and build its own model of a spatial phenomenon using the Gaussian process and local data. The IPP optimization problem is formulated in an informative way through a multi-step prediction scheme constrained by connectivity preservation and collision avoidance. The shared hyperparameters of the local Gaussian process models are also arranged to be optimally computed in the path planning optimization problem. By the use of the proximal alternating direction method of multiplier, the optimization problem can be effectively solved in a distributed manner. It theoretically proves that the connectivity in the network is maintained over time whilst the solution of the optimization problem converges to a stationary point. The effectiveness of the proposed approach is verified in synthetic experiments by utilizing a real-world dataset.