Miracle-dz/UniFAR-FTUs huggingface dataset:
Strong latitudinal gradient in temperature-growth coupling near the treeline of the Canadian subarctic forest

Boreal forests are experiencing severe climatic changes that vary widely across the broad geographic distribution of the biome. The changes are greatest near the subarctic treeline where trees often exhibit high climatic sensitivity because climatic conditions approach the limits of their physiological tolerance. Despite the importance of subarctic boreal forests, the lack of field-acquired growth data remains a critical issue that limits the generalization of forest productivity models across the entire boreal biome. Using tree-ring chronologies from remote stands distributed along three latitudinal gradients ranging from 65 to 102°W, we investigated recent trends in black spruce growth and their relationships with recent climate warming near the subarctic treeline in eastern Canada. Our results show a generally positive effect of temperature and a negative effect of precipitation, both indicating that black spruce growth is temperature-limited near its northern range limit. However, we observed a strong gradient in temperature-growth coupling within a small latitudinal gradient (about one degree of latitude), where strong temperature constraints appear limited to the northernmost, coldest stands. Moreover, the positive growth response to temperature decreased from wetter to dryer sites and climate-growth coupling declined over the study period in the driest sites. These results suggest that the growth increase associated with warmer temperature may be limited by reduced precipitation and potential moisture limitation. Lastly, our results suggest that acute climatic events have the potential to induce abrupt shifts in tree climate-growth relationships. Such results indicate that the expected beneficial effect of warming on high latitude tree growth may be less generalized and more complex than previously thought in northeastern Canada, perhaps due to factors other than temperature, which might confound the climate-growth coupling southwards. Thus, our results highlight the need for a better understanding of additional growth drivers in these poorly studied regions and for physiologically informed definitions of acute climatic events, in order to refine broad-scale forest productivity modeling.
Phylogenetic analysis and temporal diversification of the tribe Alsineae (Caryophyllaceae) with the description of three new genera, Hesperostellaria, Reniostellaria and Torreyostellaria

Alsineae are one of the most taxonomically difficult tribes in Caryophyllaceae and consist of over 500 species distributed in the northern temperate zone. Recent phylogenetic results have improved our understanding on the evolutionary relationships among Alsineae members. Nevertheless, there are still some unresolved taxonomic and phylogenetic problems at the generic level, and the evolutionary history of major clades within the tribe was unexplored to date. In this study, we carried out phylogenetic analyses and divergence time estimation of Alsineae using the nuclear ribosomal internal transcribed spacer (nrITS) and four plastid regions (matK, rbcL, rps16, trnL-F). The present analyses yielded a robustly supported phylogenetic hypothesis of the tribe. Our results showed that the monophyletic Alsineae are strongly supported to be the sister of Arenarieae, and the inter-generic relationships within Alsineae were mostly resolved with strong support. Both molecular phylogenetic and morphological evidence supported the Asian species Stellaria bistylata and the two North American species Pseudostellaria jamesiana and Stellaria americana all should be recognized as new monotypic genera respectively, and three new genera Reniostellaria, Torreyostellaria, and Hesperostellaria were thereby proposed here. Additionally, molecular and morphological evidence also supported the proposal of the new combination Schizotechium delavayi. Nineteen genera were accepted within Alsineae and a key to these genera was provided. Molecular dating analysis suggested that Alsineae splitted from its sister tribe at ca. 50.2 million-years ago (Ma) during the early Eocene and began to diverge at ca. 37.9 Ma during the late Eocene, and divergent events within Alsineae occurred mainly since the late Oligocene. Results from the present study provide insights into the historical assembly of herbaceous flora in northern temperate regions.
K-band Low Noise Amplifier Design and Simulation

Using TSMC RF CMOS 65nm process design a K band two-stage low-noise amplifier(LNA) chip, the working frequency band is 18∼20GHz, the chip is used in wireless communication receivers, the chip area of 570μm× 988μm, using 1V power supply. The first stage adopts a common-source structure, and the second stage adopts a differential common-source common-gate structure. Both stages use source-stage degradation inductors to reduce the noise of the LNA, while the differential structure of the second stage suppresses interference from common-mode noise. Using the Spectre simulation in Cadence software, the LNA is set to 0000 at a supply voltage of 1V, consumes 22.42mW over the operating frequency range, has an input matching less than -10.72dB, an output matching less than -14.5dB, a gain greater than 17.3dB, and a noise figure(NF) is less than 3.23dB, the stability factor is greater than 1 in the frequency band range, and the input 1dB compression point is -16.46dB. The LNA chip meets the needs of wireless communication receivers.
Managing Cold-Start Issues in Music Recommendation Systems: An Approach Based on User Experience

Music recommendation systems have been widely used to suggest songs to users based on their listening history or interests. Traditionally, most recommender systems have focused on prediction accuracy without considering user experience (UX) in generating recommendations. In addition, there is also the problem of cold-start, which is when the system has new users and not enough data is available about them. This study presents a new approach for music recommendation based on user experience that explores the cold-start problem. We implemented our approach in a mobile application and evaluated the system’s communicability using the Intermediate Semiotic Inspection Method (ISIM). As a result, we identified three categories relevant to music recommendation systems: novelty in recommendations, continuous updates, and users’ interest in rating. In addition, we checked each participant’s understanding of the tool, which was generally very close to the intended proposal.
Summary on Inertia Weight in Particle Swarm Optimization Algorithm

Particle swarm optimization(thereafter as PSO) algorithm is a kind of new group intelligent algorithm based on foraging of birds while inertial weight is one of important parameters in PSO algorithm of which selection for the value is directly affecting development and exploration capabilities during the period of optimizing of the particle.On the basis of introducing basic principles of PSO algorithm,this paper analyzes impact of inertial weight on astringency and discusses study progress of inertial weight of present documents.In addition,it makes comments on research achievements and shortages of various value strategies for inertial weight.
Ethanol-induced transcriptional and translational changes in Aldh1l1-Egfp/Rpl10a cortical astrocyte cultures

The role astrocytes play in brain development and function has garnered greater attention as the diversity of roles they are involved in has become apparent. We have previously shown that ethanol-exposed astrocytes alter neuronal neurite outgrowth in an in vitro co-culture system and that ethanol alters the astrocyte-produced extracellular matrix (ECM) in vitro, with similar alterations in vivo. In this study, we utilized the translating ribosome affinity purification (TRAP) procedure in Aldh1l1-EGFP/Rpl10a transgenic mouse primary cortical astrocyte cultures to transcriptionally and translationally profile the astrocyte response to ethanol. We found a large number of differences between the total RNA pool and the translating RNA pool, indicating that the transcriptional state of astrocytes may not always reflect the translational state of astrocytes. In addition, there was a considerable overlap between ethanol-dysregulated genes in the total RNA pool and the translating RNA pool. Comparisons to published datasets indicate the in vitro model used here is most similar to PD1 or PD7 in vivo cortical astrocytes, and the ethanol-regulated genes showed a significant overlap with models of chronic ethanol exposure in astrocytes, a model of third-trimester ethanol exposure in the hippocampus and cerebellum, and an acute model of ethanol exposure in the hippocampus. These findings will further our understanding of the effects of ethanol on astrocyte gene expression and protein translation and how these changes may alter brain development and support the use of in vitro astrocyte cultures as models of neonatal astrocytes.
Combatting negative bias: a mental contrasting and implementation intentions online intervention to increase help-seeking among individuals with elevated depressive symptomatology

Background There are many reasons why individuals with depression may not seek help. Among those with elevated depressive symptomatology, some previous interventions aimed at increasing help-seeking have unintentionally decreased help-seeking intentions. Beck’s cognitive theory of depression posits that individuals with elevated depressive symptomatology process information differently from those without depression (i.e., increased cognitive errors, negative bias); potentially explaining the iatrogenic results of previous interventions. Mental contrasting and implementation intentions (MCII; a self-regulatory strategy) interventions have successfully influenced physical and mental health behaviors. However, MCII has not been used specifically for initiating help-seeking for depression. The goal of this research was to ascertain whether an online MCII intervention could increase actual help-seeking or the intention to seek help for depression. Method Two online randomized pre-post experiments were conducted to measure the primary outcome measures 2 weeks post-intervention (Study 1 collected Summer 2019: information-only control [“C”], help-seeking MCII intervention [“HS”], and comparison MCII intervention [“E”]; Study 2 collected Winter 2020: “C” and “HS”). At Time 1, adults recruited from MTurk had a minimum Beck Depression Inventory (BDI-II) score of 14 (mild depressive symptoms) and were not seeking professional help. Results Study 1 (N = 74) indicated that the intervention was feasible, provided preliminary support, and clarified intervention components for Study 2. Study 2 (N = 224) indicated that the HS group reported greater intentions to seek help and actual help-seeking than the C group. Proportionally, actual help-seeking was more likely among individuals who received the HS intervention and either did not perceive themselves as depressed at Time 2 or had BDI-II scores indicating that their depressive symptomatology decreased from Time 1. Limitations Participation was limited to US residents who self-reported data. Discussion These studies indicate that a brief online MCII intervention to encourage help-seeking is feasible and preliminarily successful. Future studies should consider using ecological momentary assessment measurements to establish the temporal precedence of intervention effects and whether MCII is effective for encouraging help-seeking among individuals prone to experiencing cognitive errors who may not be experiencing negative bias (e.g., bipolar disorder or anxiety). Clinicians may find this method successful in encouraging ongoing treatment engagement.
LATOA: Load-Aware Task Offloading and Adoption in GPU

The emerging new applications, such as data mining and graph analysis, demand extra processing power at the hardware level. Conventional static task scheduling is no longer able to meet the requirements of such complicated applications. This inefficiency is a major concern when the application is supposed to run on a Graphics Processing Unit (GPU), where millions of instructions should be distributed among a limited number of processing cores. A non-optimal scheduling strategy leads to unfair load distribution among the GPU’s processing cores. Consequently, while busy cores are stalled due to the lack of resources, waiting for their data from the main memory, other cores are idle, waiting for busy cores to complete their tasks. Our study introduces LATOA, a Load-Aware Task Offloading and Adoption method that tackles this problem by reducing both stall and idle cycles. LATOA is the first study moving from static to dynamic task scheduling based on run-time information obtained from the Miss Status Holding Register (MSHR) tables. In LATOA, all processing cores are dynamically tagged with critical, neutral, or relaxed states. Then, irregular warps with low locality properties are detected and offloaded from critical cores (going to the stall state) to relaxed ones (going to the idle state). Based on our experiments, LATOA reduces the number of stall cycles on average by 24% and increases the neutral states on average by 38%. In addition, with negligible hardware overhead, LATOA improves system performance and power efficiency on average by 26% and 7%, respectively.
Experimental Design and Data Analysis for Biologists: Randomized blocks and simple repeated measures: unreplicated two factor designs

In Chapter 9, we described the analyses of completely randomized (CR) designs where the factors were either crossed with, or nested in, others. There are several other experimental designs that have special analytical requirements, and are used very commonly in the biological sciences. These include unreplicated factorial designs and designs that combine crossed (factorial) and nested arrangements. We deal with these two groups of designs in the next two chapters. In most cases, the main aim of these designs is to reduce the unexplained variation (MS Residual ) compared to a CR design. Such designs can be more efficient than CR designs, i.e., they offer more precise estimates of parameters and more powerful tests of the null hypotheses of interest, with no increase in the overall resources needed for the experiment. In contrast to CR designs, however, they involve restricted randomization of factor levels to experimental units and usually have additional assumptions. We will consider the simplest of these designs in this chapter. We also recommend that biologists distinguish between the physical design (or structure) of an experiment and the linear model used to analyze it. The same model can be applied to a number of different experimental designs and we find some of the literature on these analyses confusing because the label used for the design is often interchanged with the label used for the analysis. Unreplicated two factor experimental designs A class of experimental designs commonly used in biology is based on a two factor crossed (factorial) design with a single observation in each cell.
Predictive Analytics Model for Optimizing Carbon Emission from Student Activity and Behavior with A Design Thinking Approach: Case Study: Bandung Institute of Technology

Global warming is starting to become a major issue to maintain the sustainability of the environment and the earth. This phenomenon is caused by high greenhouse gas emissions, most of which come from human activities. At the university level, there have been many studies related to carbon footprint in universities, but only a few have studied the behavior and activities of the people in it, especially students. Predictive Analytics can be applied as the model to predict the future trends of emission carbon in the university based on the emission carbon data. Design Thinking can be used as an approach to solve such an abstract and complex problem to use the emission data to optimize carbon emissions at the student level. This research is expected to provide insights for universities regarding their level of carbon footprint and provide awareness of this so that several decision-making steps can be taken regarding optimizing carbon emissions at the student level. Bandung Institute of Technology will be the subject of this research. This study is preliminary research which will be implemented in the future work.
Influence of tension-band plates on the mechanical loading of the femoral growth plate during guided growth due to coronal plane deformities

Introduction: Correction of knee malalignment by guided growth using a tension-band plate is a common therapy to prevent knee osteoarthritis among other things. This approach is based on the Hueter-Volkmann law stating that the length growth of bones is inhibited by compression and stimulated by tension. How the locally varying mechanical loading of the growth plate is influenced by the implant has not yet been investigated. This study combines load cases from the gait cycle with personalized geometry in order to investigate the mechanical influence of the tension-band plates. Methods: Personalized finite element models of four distal femoral epiphyses of three individuals, that had undergone guided growth, were generated. Load cases from the gait cycles and musculoskeletal modelling were simulated with and without implant. Morphological features of the growth plates were obtained from radiographs. 3D geometries were completed using non-individual Magnetic Resonance Images of age-matched individuals. Boundary conditions for the models were obtained from instrumented gait analyses. Results: The stress distribution in the growth plate was heterogenous and depended on the geometry. In the insertion region, the implants locally induced static stress and reduced the cyclic loading and unloading. Both factors that reduce the growth rate. On the contralateral side of the growth plate, increased tension stress was observed, which stimulates growth. Discussion: Personalized finite element models are able to estimate the changes of local static and cyclic loading of the growth plate induced by the implant. In future, this knowledge can help to better control growth modulation and avoid the return of the malalignment after the treatment. However, this requires models that are completely participant-specific in terms of load cases and 3D geometry.
Targeting NMDA receptor in Alzheimer’s disease: identifying novel inhibitors using computational approaches

The glutamate-gated ion channels known as N-methyl-d-aspartate receptors (NMDARs) are important for both normal and pathological brain function. Subunit-selective antagonists have high therapeutic promise since many pathological conditions involve NMDAR over activation, although few clinical successes have been reported. Allosteric inhibitors of GluN2B-containing receptors are among the most potential NMDAR targeting drugs. Since the discovery of ifenprodil, a variety of GluN2B-selective compounds have been discovered, each with remarkably unique structural motifs. These results expand the allosteric and pharmacolog-ical spectrum of NMDARs and provide a new structural basis for the development of next-generation GluN2B antagonists that have therapeutic potential in brain diseases. Small molecule therapeutic inhibitors targeting NMDA have recently been developed to target CNS disorders such as Alzheimer’s disease. In the current study, a cheminformatics method was used to discover potential antagonists and to identify the structural requirements for Gly/NMDA antagonism. In this case we have created a useful pharmacophore model with solid statistical values. Through pharmacophore mapping, the verified model was used to filter out virtual matches from the ZINC database. Assessing receptor-ligand binding mechanisms and affinities used molecular docking. To find the best hits, the GlideScore and the interaction of molecules with important amino acids were considered essential features. We found some molecular inhibitors, namely, ZINC13729211, ZINC07430424, ZINC08614951, ZINC60927204, ZINC12447511, and ZINC18889258 with high binding affinity using computational methods. The molecules in our studies showed characteristics such as good stability, hydrogen bonding and higher binding affinities in the solvation-based assessment method than ifenprodil with acceptable ADMET profile. Moreover, these six leads have been proposed as potential new perspectives for exploring potent Gly/NMDA receptor antagonists. In addition, it can be tested in the laboratory for potential therapeutic strategies for both in vitro and in vivo research.
Observations of weak double layers on auroral field lines

The wave instrument on the Swedish Viking satellite performed measurements of plasma density and potential fluctuations with high temporal and spatial resolution. In the auroral regions, double-layer structures were observed which have scale lengths of about 100 m and where the plasma density is reduced by up to 50%. The structures are negatively charged and have net potential drops of up to a few volts directed upwards in the same direction as the electric currents along the geomagnetic field lines; i.e., the structures are dissipative elements of the magnetospheric electric circuit. In some regions double-layer structures are so ubiquitous that it is possible that series of such double layers may form a large-scale equipotential pattern, with a substantial potential drop along the field lines, thus contributing to the energization of the electrons that produce the aurora and upward flowing ions. >
Commentary: Video games and stress: how stress appraisals and game content affect cardiovascular and emotion outcomes

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Research advances in drug therapy of endometriosis

Endometriosis is one of the most common benign gynecological disorders in reproductive-aged women. The major symptoms are chronic pelvic pain and infertility. Despite its profound impact on women’s health and quality of life, its pathogenesis has not been fully elucidated, it cannot be cured and the long-term use of drugs yields severe side effects and hinders fertility. This review aims to present the advances in pathogenesis and the newly reported lead compounds and drugs managing endometriosis. This paper investigated Genetic changes, estrogen-dependent inflammation induction, progesterone resistance, imbalance in proliferation and apoptosis, angiogenesis, lymphangiogenesis and neurogenesis, and tissue remodeling in its pathogenesis; and explored the pharmacological mechanisms, constitutive relationships, and application prospects of each compound in the text. To date, Resveratrol, Bay1316957, and bardoxifene were effective against lesions and pain in controlled animal studies. In clinical trials, Quinagolide showed no statistical difference with the placebo group; the results of phase II clinical trial of the IL-33 antibody have not been announced yet; clinical trial stage III of vilaprisan was suspended due to drug toxicity. Elagolix was approved for the treatment of endometriosis-related pain, but clinical studies of Elagolix for the pretreatment of patients with endometriosis to before In vitro fertilization treatment have not been fulfilled. The results of a clinical study of Linzagolix in patients with moderate to severe endometriosis-related pain have not been disclosed yet. Letrozole improved the fertility of patients with mild endometriosis. For endometriosis patients with infertility, oral GnRH antagonists and aromatase inhibitors are promising drugs, especially Elagolix and Letrozole.