Miracle-dz/UniFAR-FTUs huggingface dataset:
On the effects of seasonality on soil water balance and plant growth

The partitioning of rainfall into evapotranspiration, runoff, and deep infiltration in seasonally dry climates is influenced by strong temporal variability in rainfall and potential evapotranspiration at the intra‐annual scale, which cannot be captured by conventional steady state water balance models. Guided by dimensional analysis and using simplified stochastic soil moisture models, we develop analytical expressions describing the annual partitioning of rainfall into evapotranspiration and deep percolation/runoff in seasonally dry, surface water dependent landscapes. We discuss the related changes to Budyko's curve under different seasonality scenarios, showing that an increase in seasonal rainfall and potential evapotranspiration variability as well as dry season length can lead to a decrease in the annual evapotranspiration ratio. In addition, our model shows that although increased soil water storage can compensate for the decrease in evapotranspiration due to climate seasonality, this effect is more marked in drier climates (higher annual dryness index) compared to wetter climates. Finally, the coupling of the soil moisture model to a minimalist plant growth model shows that in seasonally dry climates, a maximum in biomass is to be expected for a wet season of optimal length, for which the limitations imposed by both water availability and growth duration are at a minimum.
Numerical study on relationship between lightning types and distribution of space charge and electric potential

The favorable factors that affect the initiation of intracloud (IC) lightning and cloud‐to‐ground (CG) flashes are investigated by using a fine resolution two‐dimensional lightning model. Simulation results indicate that potential at initiation point is a key to decide whether downward leader reaches ground. The absolute values of initiation potential of CG flashes are greater than 30 MV, while the absolute values of initiation potential of IC lightning are basically less than 30 MV. Since potential field is determined by space charge distributions, polarities and types of lightning discharges are also dependent on relative locations and magnitudes of positive and negative charge zones near initiation points. In general, dipoles (positive charge above negative) initiate normal IC lightning and positive CG flashes and inverted dipoles are associated with inverted IC lightning and negative CG flashes. The magnitude of upper charge near initiation point is generally larger than that of lower charge when CG flashes occur, and the two are comparable when IC lightning occur. For CG flashes, the magnitude of lower charge near initiation points should be enough for initiation breakdown, but not so strong that the lower potential well prevents propagation to ground. In addition, CG flashes are initiated within various special charge distributions, only if the reference potentials at initiation point are far away from 0 MV.
Generation Y – Between Challenges of the Knowledge Society and Demands of a Prosperous Market

This paper deals with elements from which modern society has created a particular gap into which it has pushed young generations, named by scientists, the media and the public, Generation Y. This gap appears between the society of knowledge, in all its conceptual poverty and absurdity on the one hand, and demands of prosperous markets, on the other. The first part of this paper will present the definition and main characteristics of millennials, as well as the socio-historical context of their development. This is followed by an analysis of the media that reproduce and, to a large extent, determine the conditions and environment in which these generations exist. They are subject to technological socialization, which means they do not come into contact with each other but with machines. In this way they achieve only contact, instead of actual human relationships as experienced by previous generations. This paper also deals with technologies commonly known as “new”, although, as we write these lines, some of them have probably already become outdated and are being replaced by newer ones. This is how fast the world changes.
The Anatomical Layering Assessment: The Construction of Beauty

Abstract Restructuring an aging face from bone structure to the surface of the skin can be metaphorically compared to building and renovating a house. While each anatomical layer of the face undergoes an aging process of its own, there is also an interdependency of superficial structures on deeper layers, so that a change in one layer may lead to changes to the adjacent layers. This interaction among the structures deep into the skin, along with the skin’s ability to envelope them is what determine the aspect of the aging face. Thus, a careful assessment of all the layers is imperative and we describe herein a step-by-step facial layering assessment and facial restructuring approach from bone structure to the surface of the skin to implement a treatment plan able to deliver a harmonious rejuvenating outcome.
Perceptions and Experiences of Parents of Burn-Injured Children during Hospital Stay: A Need for Integrated Care

Pediatric burn injuries are a critical medical condition that triggers a series of ongoing multifactorial stressors that affect both children and their families. To inform healthcare research and clinical practice, this study aimed to understand and describe the perceptions and experiences of the parents of burn-injured children during hospital stay. Forty-six parents (thirty-eight mothers) of forty-six children (eighteen girls) with a mean age of 2.28 years (SD = 1.52) answered ten open-ended questions. This qualitative study was conducted in a referral hospital in the northern region of Portugal. Qualitative data were analyzed using an inductive content analysis. Five key themes emerged from the data analysis: diving into the crisis of the child burn injury, being together and in good hands, becoming aware of an uncertain future, enhancing supportive care and environment, and finding ways to guide parents. Qualitative findings underlined the pressing need for integrated care within this context. Parents were significantly burdened and distressed during the inpatient phase. These parents should be included in the integrated care plan starting from admission. Understanding and addressing parents’ healthcare needs and psychosocial adjustment difficulties is paramount to the development of future intervention programs and the delivery of suitable integrated healthcare.
MSR405: Inhibiting Neuroinflammation after Spinal Cord Injury in Rats

The treatment of spinal cord injury (SCI) is often ineffective. Additionally, SCI-induced inflammation leads to secondary injury. Current anti-inflammatory hydrophilic drugs fail to reach the nerve injury site due to the blood–brain barrier. Here, we synthesized MSR405, a new lipophilic unsaturated fatty acid derivative of Radix Isatidis and investigated its therapeutic effect in SCI model rats. Furthermore, we systematically investigated its structure, toxicity, anti-inflammatory effect, and the underlying mechanism. MSR405 was injected into the abdominal cavity of the Sprague Dawley SCI model rats, and the effect on their behavioral scores and pathology was estimated to assess the status of neurological inflammation. Our data show that MSR405 treatment significantly improved the motor function of SCI rats, and markedly suppressed the associated neuroinflammation. Moreover, MSR405 could attenuate LPS-induced inflammatory response in BV2 cells (Mouse microglia cells) in vitro. Mechanistically, MSR405 inhibits proinflammatory cytokines, supporting the anti-inflammatory response. Additionally, MSR405 can significantly block the TLR4/NF-κB signaling pathway and nitric oxide production. In summary, MSR405 reduces inflammation in SCI rats through the TLR4/NF-κB signal cascade and can inhibit neuroinflammation after spinal cord injury.
The Genetic Basis Underpinning Sexually Selected Traits across Different Animal Lineages: Are There Genetic Mechanisms in Common?

Simple Summary Sexual selection, through female choice or male–male competition, plays a crucial role in evolutionary diversification and speciation. While the evolutionary benefits and history of traits influenced by sexual selection are well-studied, the molecular genetic mechanisms of their development are less explored. Recent advances in genomic technologies such as RNA-Seq have shed light on the genetic basis of these traits across diverse taxa. This review compiles data on the genes and genetic processes involved in the development of sexually selected traits, revealing a common genetic architecture across different lineages. It highlights the frequent use of pre-existing genetic networks (i.e., gene network “co-option”) in the evolution of these traits, suggesting the repeated involvement of specific genes or gene sets in various sexually selected traits. Information on the genetic regulation of the development of sexually selected traits is valuable in providing a complete picture of their origin and evolution. Abstract Sexual selection involving female choice or female preference (‘inter-sexual’ selection) and/or male–male competition (‘intra-sexual’ selection) is one of the key mechanisms for evolutionary diversification and speciation. In particular, sexual selection is recently suggested to be an important mode to drive the evolution of the “novel” phenotype (i.e., “evolutionary novelty”). Despite extensive studies performed on sexually selected traits or male-specific ornaments (or weapon-like structures) with respect to their evolutionary origin, history and fitness benefits, relatively little is known about the molecular genetic mechanisms underlying their developmental process. However, with advances in genomic technologies (including whole transcriptome analysis using Next Generation Sequencing [NGS] techniques; RNA-Seq), progress has been made to unveil the genetic background underpinning diverse sexually selected traits in different animal taxa. In the present review, empirical data on the genes, genetic mechanisms, or regulatory pathways underlying various sexually selected traits were compiled to explore whether “common” genetic architectures shape the development and evolution of these traits across evolutionarily distant animal lineages. It is shown that the recruitment of the pre-existing genetic network for a new purpose (i.e., gene network “co-option”) is rather widespread in the development and evolution of sexually selected traits, indicating that particular genes or gene sets are repeatedly involved in different sexually selected traits. Information on genes or genetic mechanisms regulating the development of sexually selected traits is an essential piece to complete a whole picture of the origin and evolution of sexually selected traits.
Prognostic Value of Neutrophil-to-lymphocyte Ratio for Patients with Acute Coronary Syndrome and Obstructive Sleep Apnea

Objective: This study was aimed at investigating the effects of the neutrophil-to-lymphocyte ratio (NLR) on the long-term prognosis of patients with acute coronary syndrome (ACS) and obstructive sleep apnea (OSA). Methods: This prospective study enrolled patients with ACS and OSA at Anzhen Hospital between June 2015 and January 2020. OSA was defined by an apnea-hypopnea index ≥15 events·h−1. Baseline NLR was classified as high or low, according to the median. The primary endpoint was major adverse cardiovascular events (MACE), comprising cardiovascular death, recurrent myocardial infarction, stroke, and ischemia-driven revascularization. Results: A total of 1011 patients with ACS and OSA were enrolled, 506 of whom were in the high NLR (≥2.54) group. No significant differences in sleep monitoring indicators were observed. During a median follow-up of 2.8 (1.4, 3.6) years, a non-linear correlation between NLR and the incident risk of MACE was observed. After adjustment for clinically relevant confounders, a high NLR was independently associated with elevated MACE risk (adjusted HR = 1.45, 95% CI: 1.02–2.06, P = 0.040). Conclusions: In patients with ACS and OSA, a high NLR was associated with poorer clinical outcomes during long-term follow-up. Trial registration: ClinicalTrials.gov; Number: NCT03362385; URL: www.clinicaltrials. gov.
Robust Decision Aggregation with Adversarial Experts

We consider a binary decision aggregation problem in the presence of both truthful and adversarial experts. The truthful experts will report their private signals truthfully with proper incentive, while the adversarial experts can report arbitrarily. The decision maker needs to design a robust aggregator to forecast the true state of the world based on the reports of experts. The decision maker does not know the specific information structure, which is a joint distribution of signals, states, and strategies of adversarial experts. We want to find the optimal aggregator minimizing regret under the worst information structure. The regret is defined by the difference in expected loss between the aggregator and a benchmark who makes the optimal decision given the joint distribution and reports of truthful experts. We prove that when the truthful experts are symmetric and adversarial experts are not too numerous, the truncated mean is optimal, which means that we remove some lowest reports and highest reports and take averaging among the left reports. Moreover, for many settings, the optimal aggregators are in the family of piecewise linear functions. The regret is independent of the total number of experts but only depends on the ratio of adversaries. We evaluate our aggregators by numerical experiment in an ensemble learning task. We also obtain some negative results for the aggregation problem with adversarial experts under some more general information structures and experts' report space.
McCatch: Scalable Microcluster Detection in Dimensional and Nondimensional Datasets

How could we have an outlier detector that works even with nondimensional data, and ranks together both singleton microclusters ('one-off' outliers) and nonsingleton microclusters by their anomaly scores? How to obtain scores that are principled in one scalable and 'hands-off' manner? Microclusters of outliers indicate coalition or repetition in fraud activities, etc.; their identification is thus highly desirable. This paper presents McCatch: a new algorithm that detects microclusters by leveraging our proposed 'Oracle' plot (1NN Distance versus Group 1NN Distance). We study 31 real and synthetic datasets with up to 1M data elements to show that McCatch is the only method that answers both of the questions above; and, it outperforms 11 other methods, especially when the data has nonsingleton microclusters or is nondimensional. We also showcase McCatch's ability to detect meaningful microclusters in graphs, fingerprints, logs of network connections, text data, and satellite imagery. For example, it found a 30-elements microcluster of confirmed 'Denial of Service' attacks in the network logs, taking only ~3 minutes for 222K data elements on a stock desktop.
Token Alignment via Character Matching for Subword Completion

Generative models, widely utilized in various applications, can often struggle with prompts corresponding to partial tokens. This struggle stems from tokenization, where partial tokens fall out of distribution during inference, leading to incorrect or nonsensical outputs. This paper examines a technique to alleviate the tokenization artifact on text completion in generative models, maintaining performance even in regular non-subword cases. The method, termed token alignment, involves backtracking to the last complete tokens and ensuring the model's generation aligns with the prompt. This approach showcases marked improvement across many partial token scenarios, including nuanced cases like space-prefix and partial indentation, with only a minor time increase. The technique and analysis detailed in this paper contribute to the continuous advancement of generative models in handling partial inputs, bearing relevance for applications like code completion and text autocompletion.
Flexible Non-intrusive Dynamic Instrumentation for WebAssembly

A key strength of managed runtimes over hardware is the ability to gain detailed insight into the dynamic execution of programs with instrumentation. Analyses such as code coverage, execution frequency, tracing, and debugging, are all made easier in a virtual setting. As a portable, low-level bytecode, WebAssembly offers inexpensive in-process sandboxing with high performance. Yet to date, Wasm engines have not offered much insight into executing programs, supporting at best bytecode-level stepping and basic source maps, but no instrumentation capabilities. In this paper, we show the first non-intrusive dynamic instrumentation system for WebAssembly in the open-source Wizard Research Engine. Our innovative design offers a flexible, complete hierarchy of instrumentation primitives that support building high-level, complex analyses in terms of low-level, programmable probes. In contrast to emulation or machine code instrumentation, injecting probes at the bytecode level increases expressiveness and vastly simplifies the implementation by reusing the engine's JIT compiler, interpreter, and deoptimization mechanism rather than building new ones. Wizard supports both dynamic instrumentation insertion and removal while providing consistency guarantees, which is key to composing multiple analyses without interference. We detail a fully-featured implementation in a high-performance multi-tier Wasm engine, show novel optimizations specifically designed to minimize instrumentation overhead, and evaluate performance characteristics under load from various analyses. This design is well-suited for production engine adoption as probes can be implemented to have no impact on production performance when not in use.
Segmentation of Knee Bones for Osteoarthritis Assessment: A Comparative Analysis of Supervised, Few-Shot, and Zero-Shot Learning Approaches

Knee osteoarthritis is a degenerative joint disease that induces chronic pain and disability. Bone morphological analysis is a promising tool to understand the mechanical aspect of this disorder. This study proposes a 2D bone morphological analysis using manually segmented bones to explore morphological features related to distinct pain conditions. Furthermore, six semantic segmentation algorithms are assessed for extracting femur and tibia bones from X-ray images. Our analysis reveals that the morphology of the femur undergoes significant changes in instances where pain worsens. Conversely, improvements in pain may not manifest pronounced alterations in bone shape. The few-shot-learning-based algorithm, UniverSeg, demonstrated superior segmentation results with Dice scores of 99.69% for femur and 99.60% for tibia. Regarding pain condition classification, the zero-shot-learning-based algorithm, CP-SAM, achieved the highest accuracy at 66% among all models. UniverSeg is recommended for automatic knee bone segmentation, while SAM models show potential with prompt encoder modifications for optimized outcomes. These findings highlight the effectiveness of few-shot learning for semantic segmentation and the potential of zero-shot learning in enhancing classification models for knee osteoarthritis diagnosis.
Final state radiation from high and ultrahigh energy neutrino interactions

Charged leptons produced by high-energy and ultrahigh-energy neutrinos have a substantial probability of emitting prompt internal bremsstrahlung $\nu_\ell + N \rightarrow \ell + X + \gamma$. This can have important consequences for neutrino detection. We discuss observable consequences at high- and ultrahigh-energy neutrino telescopes and LHC's Forward Physics Facility. Logarithmic enhancements can be substantial (e.g.\ $\sim 20\%$) when either the charged lepton's energy, or the rest of the cascade, is measured. We comment on applications involving the inelasticity distribution including measurements of the $\nu/\bar{\nu}$ flux ratio, throughgoing muons, and double-bang signatures for high-energy neutrino observation. Furthermore, for ultrahigh-energy neutrino observation, we find that final state radiation affects flavor measurements and decreases the energy of both Earth-emergent tau leptons and regenerated tau neutrinos. Finally, for LHC's Forward Physics Facility, we find that final state radiation will impact future extractions of strange quark parton distribution functions. Final state radiation should be included in future analyses at neutrino telescopes and the Forward Physics Facility.
Data-oriented Dynamic Fine-tuning Parameter Selection Strategy for FISH Mask based Efficient Fine-tuning

In view of the huge number of parameters of Large language models (LLMs) , tuning all parameters is very costly, and accordingly fine-tuning specific parameters is more sensible. Most of parameter efficient fine-tuning (PEFT) concentrate on parameter selection strategies, such as additive method, selective method and reparametrization-based method. However, there are few methods that consider the impact of data samples on parameter selecting, such as Fish Mask based method. Fish Mask randomly choose a part of data samples and treat them equally during parameter selection, which is unable to dynamically select optimal parameters for inconstant data distributions. In this work, we adopt a data-oriented perspective, then proposing an IRD ($\mathrm{\underline I}$terative sample-parameter $\mathrm{\underline R}$ange $\mathrm{\underline D}$ecreasing) algorithm to search the best setting of sample-parameter pair for FISH Mask. In each iteration, by searching the set of samples and parameters with larger Fish information, IRD can find better sample-parameter pair in most scale. We demonstrate the effectiveness and rationality of proposed strategy by conducting experiments on GLUE benchmark. Experimental results show our strategy optimizes the parameter selection and achieves preferable performance.
Curved commutators in the plane

We complete the $L^p$ boundedness theory of commutators of Hilbert transforms along monomial curves by providing the previously missing lower bounds. This optimal result now covers all monomial curves while previous results had significant geometric restrictions. We also, for the first time, develop the corresponding necessity theory for curves with non-vanishing torsion.
A Fast Adaptive-Gain Complementary Filter Algorithm for Attitude Estimation of an Unmanned Aerial Vehicle – CORRIGENDUM

In Yang et al. (2018), the authors derive an observation model of attitude quaternions from normalised accelerometer measurements. The method of Yang et al. builds up the linear measurement model via Taylor approximations. Some significant contributions and new filter designs are shown in this paper which deal with the problem of adaptive estimation. Regarding the factorization of the direction cosine matrix, it has been systematically described in Wu et al. (2018), but this has not been noticed by Yang et al. as this paper was published after the original submission of Yang et al. (2018). Yang et al. (2018) uses different compositions of a dynamical system that achieves the same result as in Wu et al. (2016).