Miracle-dz/UniFAR-FTUs huggingface dataset:
How does variation in total and relative abundance contribute to gradients of species diversity?

Abstract Patterns of biodiversity provide insights into the processes that shape biological communities around the world. Variation in species diversity along biogeographical or ecological gradients, such as latitude or precipitation, can be attributed to variation in different components of biodiversity: changes in the total abundance (i.e., more‐individual effects) and changes in the regional species abundance distribution (SAD). Rarefaction curves can provide a tool to partition these sources of variation on diversity, but first must be converted to a common unit of measurement. Here, we partition species diversity gradients into components of the SAD and abundance using the effective number of species (ENS) transformation of the individual‐based rarefaction curve. Because the ENS curve is unconstrained by sample size, it can act as a standardized unit of measurement when comparing effect sizes among different components of biodiversity change. We illustrate the utility of the approach using two data sets spanning latitudinal diversity gradients in trees and marine reef fish and find contrasting results. Whereas the diversity gradient of fish was mostly associated with variation in abundance (86%), the tree diversity gradient was mostly associated with variation in the SAD (59%). These results suggest that local fish diversity may be limited by energy through the more‐individuals effect, while species pool effects are the larger determinant of tree diversity. We suggest that the framework of the ENS‐curve has the potential to quantify the underlying factors influencing most aspects of diversity change.
Rationally Designed Anisotropic and Auxetic Hydrogel Patches for Adaptation to Dynamic Organs

Current hydrogel or fabric patches for organ repair are generally not designed to conform to the complex mechanics of dynamic organs such as the lung or heart. This study presents a new, biocompatible and bilayered, hydrogel‐based patch platform, consisting of a non‐fouling top layer and a cell adhesive bottom layer, that caters to the anisotropic and auxetic characteristics of dynamic organs. Integrated computational and experimental studies are used to screen over 116 unique anisotropic‐auxetic architectures to establish design rules and tailor the patches to a broad range of target organ dynamics. The patches are then validated in ex vivo and in vivo animal models, where the auxetic patches outperformed non‐auxetic patches in conforming to the volumetric dilation‐contraction of dynamic organs. To further expand the functionality of the auxetic patch platform, novel hole‐filling auxetic patches are developed. These hole‐filling patches composited with fibrin robustly reduce pulmonary air leakage in rats with surgically induced lung puncture. This is the first demonstration of a rational patch design framework that features both anisotropic and auxetic properties to cater to a wide range of organ dynamics. These studies pave the way for future clinical development of biomimetic patches.
Pre-Training on In Vitro and Fine-Tuning on Patient-Derived Data Improves Deep Neural Networks for Anti-Cancer Drug-Sensitivity Prediction

Simple Summary Cancer cell lines vary greatly from one another because each one underwent a combination of random mutations. Therefore, the effectiveness of anti-cancer drugs also varies across cancer cell lines. In order to understand which drugs are effective against which cancer cells, researchers expose cultivated cell lines to drug candidates. However, these results are not entirely realistic, mostly because cultivated cells live in a two-dimensional in vitro environment without interacting with other types of cells. There are more realistic ways to test drug effectiveness—e.g., organoids that are 3D-printed from tumor cells—but since these processes are more complex, much fewer data are available. We studied an approach in which a neural network is first trained on the wealth of available in vitro drug-sensitivity data, before being fine-tuned on smaller but more realistic databases. We found that this training procedure improves the neural network’s ability to predict how effective a particular drug will be for a given tumor cell line. Such neural networks can serve as a tool, both for personalized treatment of cancer and for drug development. Abstract Large-scale databases that report the inhibitory capacities of many combinations of candidate drug compounds and cultivated cancer cell lines have driven the development of preclinical drug-sensitivity models based on machine learning. However, cultivated cell lines have devolved from human cancer cells over years or even decades under selective pressure in culture conditions. Moreover, models that have been trained on in vitro data cannot account for interactions with other types of cells. Drug-response data that are based on patient-derived cell cultures, xenografts, and organoids, on the other hand, are not available in the quantities that are needed to train high-capacity machine-learning models. We found that pre-training deep neural network models of drug sensitivity on in vitro drug-sensitivity databases before fine-tuning the model parameters on patient-derived data improves the models’ accuracy and improves the biological plausibility of the features, compared to training only on patient-derived data. From our experiments, we can conclude that pre-trained models outperform models that have been trained on the target domains in the vast majority of cases.
A Systematic Review of Project Safe Neighborhoods Effects

Abstract Project Safe Neighborhoods (PSN) is an ongoing national program, implemented by U.S. Attorney’s Offices and funded by the U.S. Department of Justice, to address gun and gang violence in local jurisdictions within all 94 federal districts in the United States. While dozens of studies have evaluated the local effects of PSN programs, a comprehensive review of PSN literature is missing; this article addresses that gap. The current study conducts a systematic review of empirical studies of PSN programs from 2001 to 2021 across nine major academic databases and five websites. Twenty-one evaluations were retained for a detailed review and categorized based on Maryland Scientific Methods Scale values. PSN initiatives produce overall favorable results in reducing violence in the short-term, though long-term impacts are rarely explored. PSN had an indicated positive effect on 91.9% of the examined outcomes, 54.5% of which attained statistical significance. Task force members state that likelihood of PSN success improves when working groups remain consistent in personnel, communicate regularly, and achieve buy-in from all involved parties. Future research should report effect sizes when appropriate, evaluate PSN programs absent in other high-populated areas, and employ more rigorous experimental and quasi-experimental designs so a meta-analysis can be conducted.
Spinopelvic Adaptations in Standing and Sitting Positions in Patients With Adult Spinal Deformity

Purpose To describe spinopelvic adaptations in the standing and sitting positions in patients with adult spinal deformity (ASD). Methods Ninety-five patients with ASD and 32 controls completed health-related quality of life (HRQOL) questionnaires: short form 36 (SF36), Oswestry Disability Index (ODI), and visual analog scale (VAS) for pain. They underwent biplanar radiography in both standing and sitting positions. Patients with ASD were divided into ASD-front (frontal deformity Cobb > 20°, n = 24), ASD-sag (sagittal vertical axis (SVA) > 50 mm, pelvic tilt (PT) > 25°, or pelvic incidence (PI)-lumbar lordosis (LL) > 10°, n = 40), and ASD-hyper thoracic kyphosis (TK >60°, n = 31) groups. Flexibility was defined as the difference (Δ) in radiographic parameters between the standing and sitting positions. The radiographic parameters were compared between the groups. Correlations between HRQOL scores were evaluated. Results All participants increased their SVA from standing to sitting (ΔSVA<0), except for patients with ASD-sag, who tended to decrease their SVA (78-62 mm) and maximize their pelvic retroversion (27-40° vs 10-34° in controls, p<0.001). They also showed reduced thoracic and lumbar ﬂexibility (ΔLL = 3.4 vs 37.1°; ΔTK = −1.7 vs 9.4° in controls, p<0.001). ASD-hyperTK showed a decreased PT while sitting (28.9 vs 34.4° in controls, p<0.001); they tended to decrease their LL and TK but could not reach values for controls (ΔLL = 22.8 vs 37.1° and ΔTK = 5.2 vs 9.4°, p<0.001). The ASD-front had normal standing and sitting postures. ΔSVA and ΔLL were negatively correlated with the physical component scale (PCS of SF36) and ODI (r = −0.39 and r = −0.46, respectively). Conclusion Patients with ASD present with different spinopelvic postures and adaptations from standing to sitting positions, with those having sagittal malalignment most affected. In addition, changes in standing and sitting postures were related to HRQOL outcomes. Therefore, surgeons should consider patient sitting adaptations in surgical planning and spinal fusion. Future studies on ASD should evaluate whether physical therapy or spinal surgery can improve sitting posture and QOL, especially for those with high SVA or PT.
Evaluation of the acid-binding capacity of ingredients and complete diets commonly used for weanling pigs.

Some ingredients bind more acid in the stomach than others which can increase gastric pH in weaned pigs causing decreased protein digestion and allow pathogenic micro-organisms to proliferate. Our objective was to measure acid-binding capacity at a pH of 4 (ABC-4) of common nursery ingredients and determine additivity in diets. Ingredient categories included: cereal grains, vegetable proteins, animal proteins and milk, vitamin premixes and minerals, amino acids, and fiber sources. A 0.5-g sample of each ingredient was suspended in 50 mL of distilled deionized water and titrated with 0.1-N hydrochloric acid. Sample ABC-4 was calculated as the amount of acid in milliequivalents (meq) required to lower 1 kg to a pH of 4. Cereal grains were found to have lower ABC-4 compared to other ingredients. Vegetable proteins had higher ABC-4 with more variation than cereal grains. Soybean meal (SBM) had an ABC-4 of 602 ± 28.2 meq. Soy protein concentrate and enzymatically treated soybean meal (ESBM) had higher ABC-4 compared to SBM while fermented soybean meal (FSBM) was lower. Zinc oxide (ZnO) and calcium carbonate (CaCO3) had the highest ABC-4 among all ingredients with values of 21,863 ± 598.7 and 18,384 ± 769.7 meq, respectively. Following ingredient analysis, a series of diets were analyzed to determine additivity by comparing the differences between calculated and analyzed ABC-4 value. All diets analyzed had lower ABC-4 than calculated values; however, analyzed ABC-4 increased along with calculated values across diets. The first series of diets were arranged in a 2 × 5 factorial consisting of increasing CaCO3 with or without ZnO. There was a ZnO × CaCO3 interaction (P = 0.020) for difference between calculated and analyzed ABC-4. Within the interaction, differences between calculated and analyzed ABC-4 increased (linear, P < 0.001) as CaCO3 increased in diets without ZnO, but not in diets with ZnO. The second series of diets analyzed consisted of different levels of SBM with either FSBM or ESBM included at 5% of the diet. Differences between calculated and analyzed values were not different between treatments (P = 0.640). In conclusion, perfect ABC-4 additivity in diets was not found due to lower analyzed than calculated values; however, analyzed ABC-4 still increased as calculated values increased. This data suggests diet ABC-4 can be adjusted through selection of ingredients but more feeding trials are needed to determine its impact on pig performance.
Fine-tuning of BERT Model to Accurately Predict Drug–Target Interactions

The identification of optimal drug candidates is very important in drug discovery. Researchers in biology and computational sciences have sought to use machine learning (ML) to efficiently predict drug–target interactions (DTIs). In recent years, according to the emerging usefulness of pretrained models in natural language process (NLPs), pretrained models are being developed for chemical compounds and target proteins. This study sought to improve DTI predictive models using a Bidirectional Encoder Representations from the Transformers (BERT)-pretrained model, ChemBERTa, for chemical compounds. Pretraining features the use of a simplified molecular-input line-entry system (SMILES). We also employ the pretrained ProBERT for target proteins (pretraining employed the amino acid sequences). The BIOSNAP, DAVIS, and BindingDB databases (DBs) were used (alone or together) for learning. The final model, taught by both ChemBERTa and ProtBert and the integrated DBs, afforded the best DTI predictive performance to date based on the receiver operating characteristic area under the curve (AUC) and precision-recall-AUC values compared with previous models. The performance of the final model was verified using a specific case study on 13 pairs of subtrates and the metabolic enzyme cytochrome P450 (CYP). The final model afforded excellent DTI prediction. As the real-world interactions between drugs and target proteins are expected to exhibit specific patterns, pretraining with ChemBERTa and ProtBert could teach such patterns. Learning the patterns of such interactions would enhance DTI accuracy if learning employs large, well-balanced datasets that cover all relationships between drugs and target proteins.
Lowering water table reduces carbon sink strength and carbon stocks in northern peatlands

Peatlands at high latitudes have accumulated >400 Pg carbon (C) because saturated soil and cold temperatures suppress C decomposition. This substantial amount of C in Arctic and Boreal peatlands is potentially subject to increased decomposition if the water table (WT) decreases due to climate change, including permafrost thaw‐related drying. Here, we optimize a version of the Organizing Carbon and Hydrology In Dynamic Ecosystems model (ORCHIDEE‐PCH4) using site‐specific observations to investigate changes in CO2 and CH4 fluxes as well as C stock responses to an experimentally manipulated decrease of WT at six northern peatlands. The unmanipulated control peatlands, with the WT <20 cm on average (seasonal max up to 45 cm) below the surface, currently act as C sinks in most years (58 ± 34 g C m−2 year−1; including 6 ± 7 g C–CH4 m−2 year−1 emission). We found, however, that lowering the WT by 10 cm reduced the CO2 sink by 13 ± 15 g C m−2 year−1 and decreased CH4 emission by 4 ± 4 g CH4 m−2 year−1, thus accumulating less C over 100 years (0.2 ± 0.2 kg C m−2). Yet, the reduced emission of CH4, which has a larger greenhouse warming potential, resulted in a net decrease in greenhouse gas balance by 310 ± 360 g CO2‐eq m−2 year−1. Peatlands with the initial WT close to the soil surface were more vulnerable to C loss: Non‐permafrost peatlands lost >2 kg C m−2 over 100 years when WT is lowered by 50 cm, while permafrost peatlands temporally switched from C sinks to sources. These results highlight that reductions in C storage capacity in response to drying of northern peatlands are offset in part by reduced CH4 emissions, thus slightly reducing the positive carbon climate feedbacks of peatlands under a warmer and drier future climate scenario.
3D Forensic Crime Scene Reconstruction Involving Immersive Technology: A Systematic Literature Review

Recreation of 3D crime scenes is critical for law enforcement in the investigation of serious crimes for criminal justice responses. This work presents a premier systematic literature review (SLR) that offers a structured, methodical, and rigorous approach to understanding the trend of research in 3D crime scene reconstruction as well as tools, technologies, methods, and techniques employed thereof in the last 17 years. Major credible scholarly database sources, Scopus, and Google Scholar, which index journals and conferences that are promoted by entities such as IEEE, ACM, Elsevier, and SpringerLink were explored as data sources. Of the initial 17, 912 papers that resulted from the first search string, 258 were found to be relevant to our research questions after implementing the inclusion and exclusion criteria. To summarize the existing efforts, we compared and analysed various classical 3D reconstruction approaches. This study presents the first comprehensive review of key milestones in the development of methods for 3D crime scene reconstruction, gaps for improvement and where immersive technology has been used to enhance crime scene findings. This study found that the implementation of light detection and ranging (LiDAR) scanners and immersive technologies, alongside traditional methods, has been beneficial in the recreation of crime scenes. The SLR is limited to existing applications with peer-reviewed papers published between 2005 and 2021. Results based on the analysed published data indicated that 20.2% of the articles implemented immersive technologies in crime scene reconstruction, of which Augmented Reality (AR) accounted for 15.3%, Virtual Reality (VR) accounted for 75%, Mixed reality (MR) accounted for 5.9% and VR and AR mixture accounted for 3.8%. Finally, we summarize the development trend of design and key technology prospects of crime scene recreation using immersive technology and provide insights into potential future research. To the best of the researchers’ knowledge, this is the first survey that accomplishes such goals.
Mixing Improvement by Manipulation of Multiple Jets Using Active Plasma Actuator

This study interests in defining a new type of dielectric barrier discharge actuator for mixing improvement purpose. The actuator is composed of a perforated plate (121 holes) housing embedded and printed electrodes between which a high voltage is applied. The electrode arrangement is such that the holes where the gas flows are surrounded by dielectric barrier discharges. Electrical and optical characterizations of the discharge are proposed to characterize the typical streamer and glow regimes that occur during one period of the AC sine voltage. Fast flow imaging by smoke streamwise and cross-sectional visualizations has been conducted for a freestream flow of 5 m/s. Depending on the applied frequency, the plasma discharge can modify the outer region where secondary instability takes place or it can produce a laminar-to-turbulent transition, enhancing then the mixing of the flow exiting from the perforated plate. Keywords—Plasma actuator, dielectric barrier discharge, jet flow, flow control
Komposisi dan distribusi hasil tangkapan kapal pukat cincin KM Grasia 04 di perairan Laut Maluku (Composition and distribution catch of Grasia 04 purse seiner in Molucca Sea waters)

Purse seine is considered to be the most productive fising gear to catch pelagic fish, so there are many purse seiners that based in Bitung Oceanic Fishing Port operate in Fisheries Management Area of the Republic of Indonesia (WPP) 715 Moluccas Sea. There was and issue that the catches of purse seiner around FADs was classified as immature fish. Therefore, necessary to study the diversity and distribution of purse seiner catches in the area. The data collection was done by direct observation and active participation in the field and deep interviews with the crews of Grasia 04 purse seiner. At each hauling, twenty fish from each species were taken randomly measured their fork lengths. Catches during the study consisted of six species; namely skipjack (Katsuwonus pelamis) , yellow fin tuna (Thunnus albacores) , little tuna (Auxis thazard) , scad mackerel ( Decapteru smacarellus ), rainbow runner ( Elagatis bipinnulata ), oceanic trigger fish ( Canthidermis maculata ) and trevally (Selaroides leptolepis ). The dominatcatch in each hauling were skipjack, yellowfin, tuna and scad mackerel. Results were showed that most of the catches of Grasia 04 purse seinerin the waters of Moluccas Sea not legal size. Keywords : Composition and distribution catch, purse seiner Grasia 04, Molucca Sea. ABSTRAK Alat tangkap purse seine dianggap paling produktif untuk menangkap ikan pelagis, sehingga banyak kapal purse seine yang berpangkalan di Pelabuhan Perikanan Samudera Bitung beroperasi di Wilayah Pengelolaan Perikanan RI (WPP) 715 Laut Maluku. Beberapa issue menyebutkan bahwa hasil tangkapan purse seine terutama di sekitar rumpon tergolong ikan-ikan yang belum dewasa. Oleh karena itu, perlu mempelajari keragaman dan distribusi hasil tangkapan purse seine di wilaya tersebut. Pengumpulam data dilakukan dengan cara pengamatan langsung dan partisifasi aktif dilapangan, wawancara dengan anak buah kapal KM Grasia 04. Pada setiap kali hauling , diambil secara acak 20 ekor ikan sampel setiap jenis dan mengukur panjang bakunya. Hasil tangkapan selama penelitian adalah 6 jenis ikan; yaitu ikan cakalang ( Katsuwonuspelamis ), madidihang ( Thunnusalbacores ), tongkol ( Auxis thazard ), malalugis ( Decapterus macarellus ), sunglir ( Elagatis bipinnulata ), tato batang ( Canthidermis maculata ) dan selar ( Selaroides leptolepis). Tetapi hasil tangkapan yang dominan pada setiap hauling adalah cakalang, madidihang, tongkol dan malalugis. Hasil analisis menunjukan bahwa sebagian besar hasil tangkapan kapal purse seine Grasia 04 di perairan Laut Maluku belum layak tangkap. Kata kunci: Komposisi dan distribusi tangkapan, pukat cincin KM Grasia 04, Laut Maluku
An erasure-based scheme for reduction of PAPR in spatial multiplexing MIMO-OFDM using Reed-Solomon codes over GF(216 + 1)

ABSTRACT In this paper, a novel erasure-based scheme which uses long Reed-Solomon (RS) codes over GF(65537) is proposed for the reduction of the peak-to-average power ratio (PAPR) in coded orthogonal frequency division multiplexing (OFDM). The motivation for using the field GF(65537) is to generate long code words (up to 65536 symbols in just one code word). Using long codes results in greater flexibility to search for low PAPR OFDM frames within the subsets of symbols of a code word because RS codes are maximum distance separable and any subset of a high enough number of symbols is sufficient for the recovery of data. Over this field, the lengths of code words are exponents of 2. Hence, low-complexity radix-2 fast Fourier transform can be exploited. RS codes are deployed for both PAPR reduction and error correction. Simulation results show that in similar PAPR reduction performances, the proposed scheme outperforms the previously reported work with RS codes in both error correction and computation complexity. The proposed scheme can be applied to both single-input single-output and multi-input multi-output systems.