bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dating death
Authors: Ermida Catarina , Cunha Eugénia , Ferreira Maria Teresa 
Published: December 2022

The estimation of the postmortem interval (PMI), particularly the late time since death, is a crucial issue when dealing with human remains. Its establishment is an important task for forensic scientists since it has important legal implications such as identifying a victim or prosecuting an offender. However, dating death is a very complex and challenging task due to the amount of intrinsic and extrinsic factors, that may influence the rate and nature of body decomposition. Many methods have been used to estimate PMI, from classical decomposition methods to entomological and botanical methods or more recently physics and biochemical methods.
This paper reviews current forensic dating methods, focusing especially on forensic anthropological techniques. Nevertheless, the existing literature is insufficient, denoting a lack of effective methods to achieve an accurate and reliable PMI estimation and further investigation is required. A holistic approach, where every element must be considered, is the key to achieving a reliable estimation of PMI. Interdisciplinarity is thus mandatory, allied with the capacity of forensic anthropologists to denote all the details.
Real-World Evidence Comparing Vedolizumab and Ustekinumab in Antitumor Necrosis Factor-Experienced Patients With Crohn's Disease
Authors: Kappelman Michael D. , Adimadhyam Sruthi , Hou Laura , Wolfe Audrey E. , Smith Samantha , Simon Andrew L. , Moyneur Érick , Reynolds Juliane S. , Toh Sengwee , Dobes Angela , Parlett Lauren E. , Haynes Kevin , Selvan Mano , Ma Qianli , Nair Vinit , Burris Jessica , Dorand Jennifer E. , Dawwas Ghadeer K. , Lewis James D. , Long Millie D. 
Published: December 2022

INTRODUCTION:
Many patients with Crohn's disease (CD) lose response or become intolerant to antitumor necrosis factor (TNF) therapy and subsequently switch out of class. We compared the effectiveness and safety of ustekinumab to vedolizumab in a large, geographically diverse US population of TNF-experienced patients with CD.

METHODS:
We conducted a retrospective cohort study using longitudinal claims data from a large US insurer (Anthem, Inc.). We identified patients with CD initiating vedolizumab or ustekinumab with anti-TNF treatment in the prior 6 months. Our primary outcome was treatment persistence for >52 weeks. Secondary outcomes included (i) all-cause hospitalization, (ii) hospitalization for CD with surgery, (iii) hospitalization for CD without surgery, and (iv) hospitalization for infection. Propensity score fine stratification was used to control for demographic and baseline clinical characteristics and prior treatments.

RESULTS:
Among 885 new users of ustekinumab and 490 new users of vedolizumab, we observed no difference in treatment persistence (adjusted risk ratio 1.09 [95% confidence interval 0.95–1.25]). Ustekinumab was associated with a lower rate of all-cause hospitalization (adjusted hazard ratio 0.73 [0.59–0.91]), nonsurgical CD hospitalization (adjusted hazard ratio 0.58 [0.40–0.83]), and hospitalization for infection (adjusted hazard ratio 0.56 [0.34–0.92]).

DISCUSSION:
This real-world comparative effectiveness study of anti-TNF-experienced patients with CD initiating vedolizumab or ustekinumab showed similar treatment persistence rates beyond 52 weeks, although secondary outcomes such as all-cause hospitalizations, nonsurgical CD hospitalizations, and hospitalizations for infection favored ustekinumab initiation. We, therefore, advocate for individualized decision making in this medically refractory population, considering patient preference and other factors such as cost and route of administration.
Artificial intelligence based prediction models for rubber compounds
Authors: Uruk Zeynep , Kiraz Alper 
Published: December 2022

Abstract
In the rubber industry, rheometric properties are critical in defining processing times and temperatures. These parameters of rubber compounds are determined by time-consuming and expensive laboratory studies performed in a rheometer. Artificial intelligence approaches, on the other hand, may be used to estimate rheometric properties in seconds without the need for any samples or laboratory experiments. In this research, artificial neural network, Gaussian process regression, and support vector regression techniques are used to predict minimum and maximum torque, 30% and 60% cure time of a rubber compound using both process parameters and raw material composition as input. The dataset comprises 1128 batches of the selected rubber compound. A detailed sensitivity analysis is performed to determine the best performing hyperparameters and the prediction performances are expressed as mean absolute percentage error (MAPE). Minimum, maximum, and average MAPE values are presented for each artificial intelligence technique. Besides this research contributes to fill the gap in rubber industry literature, the results obtained also strongly improve the existing literature results.
Pilotos para la transferencia de conocimiento entorno a la digitalización en la construcción en Medellín, Colombia
Authors: Rúa Machado Carlos Andrés , Arboleda López Sergio Andrés , Serna Machado Nicolás 
Published: December 2022

La investigación de la cual deriva el presente artículo busca fomentar el aprendizaje mediante la articulación de escenarios CAE (Clúster-Academia-Empresa) que permitan socializar criterios y establecer lenguajes formales del conocimiento frente a la adopción de BIM (Building Information Modelling) de forma interactiva y predefinida. Para ello se formaron grupos focales con el objeto de nivelar conceptualmente los alcances de BIM desarrollando criterios en común, generándose un banco de preguntas y respuestas relacionadas al tema; posteriormente, se seleccionan las brechas para consolidar este proceso de medición con las entrevistas de Santiago de Chile, para identificar las principales entidades y empresas promotoras de su digitalización y comprender sus particularidades, así como las posibilidades de transferencia de conocimiento como escenario de digitalización en la construcción. Así pues, se identifica que BIM se entiende como una metodología, pero su gestión, conocimiento y práctica son bajos; la visualización, coordinación y gestión de presupuestos, es incipiente. Por consiguiente, se concluye que la socialización de estos pilotos guiados permite una mejor comprensión entre actores y ayuda a entender las interfases de información.
An Evolutionary Sequential Transfer Optimization Algorithm for Well Placement Optimization Based on Task Characteristics
Authors: Qi Ji , Zhang Kai , Xue Xiaoming , Zhang Liming , Zhong Chao , Wang Haochen , Yao Jun 
Published: December 2022

Summary
Evolutionary transfer optimization (ETO) algorithms with the ability to learn from past tasks have made breakthroughs in more and more fields. When the experience embedded in the past optimization tasks is properly utilized, the search performance will be greatly improved compared to starting from scratch. Autoencoding evolutionary search (AEES) is an efficient ETO paradigm proposed in recent years. The solutions of each task are configured as input and output of a single-layer denoising autoencoder (DAE), and the across-problem mapping is established by minimizing the reconstruction error, which makes it possible to explicitly transfer the solutions across heterogeneous problems. However, despite the success of AEES, the population of the optimization task contains little information about the characteristics of the task and it is highly stochastic, especially in the early stages of searching. This restricts the effectiveness of the mapping constructed via AEES. On the other hand, most tasks do not save all candidate solutions in the search, which greatly limits the possibilities of traditional AEES applications; for example, well placement optimization (WPO) problems, which are a common engineering optimization problem in the oil industry. To overcome such limitations, a sequential ETO algorithm for WPO problems based on task characteristics and an autoencoder is developed in this paper. It uses the implicit relationship between reservoir characteristics and optimal well locations to learn from past tasks, and a mapping is calculated to transfer knowledge across tasks. The proposed algorithm aims to speed up the search for the optimal well locations and reduce the required time for WPO. The learned mapping is established by configuring the characteristics of past and current tasks as input and output of a single-layer DAE. The derived mapping holds a closed-form transformation matrix across heterogeneous tasks, and the optimal solution of the past task can be easily transferred to a dominant solution of the current task by matrix calculation, thus it will not bring much computational burden in the evolutionary search while improving search performance. Furthermore, according to the specific task, the construction scheme of the matrix of characteristics can be flexibly extended to achieve effective search enhancement. The comprehensive empirical studies of WPO and statistical analysis are carried out to verify the effectiveness.
Synthesis of Cd(OH) 2 -CdO Nanoparticles Using Veldt Grape Leaf Extract: Enhanced Dye Degradation and Microbial Resistance
Authors: R Prammitha , Y Samson , Jeice Rejo 
Published: December 2022

Abstract
This research work implies the development of a reliable, inexpensive, better and eco-friendly way to fabricate Cd(OH)2 and CdO nanoparticles green synthesis approach using three different source materials. The veldt grape leaf act as a chelating agent. The physical properties of prepared samples were analyzed by various characterization techniques such as X-Ray Diffractometer, Fourier Transform Infra-Red, Scanning Electron Microscopy, X-Ray Energy Dispersive Spectrometer, High-Resolution Transmission Electron Microscopy and UV-Visible Spectrometer. The investigation of the structural analysis showed the existence of Cd(OH)2, mixed Cd(OH)2/CdO and CdO nanoparticles. The optical absorption wavelength at 294nm in UV-Vis spectra confirmed that the reduction of Cd2+ ions. FTIR spectra display the vibrational modes of veldt grape leaf extract involved in chemical bonding and reductions. From EDAX spectrum confirmed the presence of Cd and O elements in the prepared samples. SEM and HRTEM images revealed nanorods, platelet and spherical shape morphologies with particle size ranging from 5.7 to 29nm. The photocatalytic activity of prepared nanoparticles was tested by degrading anionic and cationic dyes like congo red, methyl orange and crystal violet under UV-light irradiation. As well as antimicrobial activity was evaluated against gram-positive staphylococcus aureus, gram-negative proteus vulgaris and fungal- aspergillus niger. Comparing these three products CdO NPs exhibit high performance on both microbial and photocatalytic activity without a secondary product. Thus, the prepared CdO nanoparticles may further use in sewage treatment and biomedical applications.
Fractal Stability Applied to Forestry Patches
Authors: Nascimento Antonio Teófilo Ataide do , Santos Stefanie Chaves dos , de Matos Mara Rojane Barros , Orge Maria Dolores Ribeiro 
Published: December 2022

Abstract
Context:
The fractal analysis has been used by landscape ecologists as a shape metric in order to quantify the complexity of landscape patches. However the use of fractal geometry in ecology possesses an unexplored potential. We then developed a broader study of shapes with unitary fractal dimension.
Objectives:
Our aim is to amplify the use of fractal dimensions as a metric of shape in the analysis and discovery of forestry landscape patches with unitary fractal dimension. Furthermore, we develop a method for monitoring and recovery of forestry patches.
Methods:
We establish a method of expansion in order to obtain patches with a good perimeter-area ratio, i. e., unitary fractal dimension. In order to do that, to each landscape patch we associate a polygon and, to each side, we define a locus that expands the polygon so that its fractal dimension is equal to one.
Results:
This study reveals a range of patches’ shapes with unitary fractal dimension. Inspired by the proposed method's recursion we denote them as fractally stable polygons. To each side of the polygon we set a condition of expansion possibility. The locus of expansion was also defined. Additionally, we define a test of global expansion.
Conclusions:
Through the developed method it is possible to ascertain when the perimeter-area ratio of a landscape patch is compromised. To expandable sides, the method provides the locus of recovery of the perimeter-area ratio. This enables a wider applicability in the analysis of forestry fragmentation through fractal dimension.
Hepatoprotective Effects of N-acetylcysteine on Liver Injury by Irisin Upregulation and Oxidative Stress Reduction in Diabetic Rats
Authors: erdogan mehmet mustafa , erdogan mehmet ali , koc suleyman , yalcin Alper , turk ahmet , Yetkin Esra Akkus 
Published: December 2022

Abstract
Purpose; The current study aimed to investigate the oxidative stress in diabetic rat liver as well as the protective effects of N-acetylcysteine (NAC)on irisin expression.
Methods; Twenty-eight male Wistar rats were divided into four groups, 7 rats in each group and 30-d regimens of experimental or control groups. NAC treated group: 100mg/kg once daily was administered intraperitoneally (i.p.). Diabetes-induced group: Single dose intraperitoneal injection of streptozotocin (STZ) (50mg/kg B.W.) was used to induce diabetes mellitus in overnight fasting Wistar rats. By determining blood glucose concentration in STZ-induced rats 72 hours after injection of STZ, diabetes was assessed. DM+NAC group: STZ-induced DM plus NAC as described previously. Serial and liver samples were collected on the 30-day and after overnight fasting. Biochemical analyses were performed to measure total antioxidant status (TAS), total oxidant status (TOS), and Malondialdehyde (MDA)levels. Each liver sample was weighed, then prepared for histopathologic evaluation by light microscopy.
Results; There was a statistically significant decrease in TAS levels and an increase in TOS and MDA levels in the DM group compared to the control group.
In contrast, TOS and MDA levels were found significantly decreased, and TAS levels increased in the serum and liver tissues of the DM+NAC group compared to the DM group. Liver samples were also used for histopathological examination using hematoxylin-eosin and immunohistochemical staining. STZ-induced liver injury via increasing oxidative stress, sinusoidal dilatation, degeneration of hepatocytes, and in irisin, and immunoreactivity. NAC significantly reduced the STZ-induced hepatotoxicity.
Conclusion; In the early period of diabetes, due to the antioxidant properties of irisin related to the sudden response of liver tissue to oxidative stress, it is thought that the immunoreactivity in the tissue increases in the early period. As a result, NAC in diabetic rat liver tissue was found to suppress oxidative damage and irisin immunoreactivity.
Shedding Light on Consumer Sentiments: Evidence from India
Authors: Rooj Debasis , Banerjee Anurag , Sengupta Reshmi , Pathak Prasad 
Published: December 2022

Abstract
This paper shows how location-based indicators can influence consumer confidence in India. We capture local economic activity using city-wise night-time luminosity (NTL) data. Using data on unit-level observations on consumer confidence from the Consumer Confidence Survey (CCS) by the Reserve Bank of India from June 2016 to November 2021, we find that night-time luminosity positively impacts the perception and future outlook of Indian households. Our results are robust even after controlling for state-wise urban inflation. We also find the dynamic effect of NTL on consumer sentiments. Finally, we extend our study to analyze the impact of NTL on several individual components of household sentiments from the RBI survey, such as household perception and outlook on household income, spending, employment, and general price levels. Overall, our results provide fascinating insights about using NTL as a measure of local economic indicators and its implications on households' sentiment indicators.
Gut microbiota serve as a risk predictor of weight gain in schizophrenia patients with antipsychotic medication
Authors: Liu Yaxi , Wu Hui , Liu Bingdong , Chen Shengyun , Huang Liujing , Liu Zhihong , Wang Jie , Xie Liwei , Wu Xiaoli 
Published: December 2022

Abstract
Background:Emerging evidence indicates that gut microbial dysbiosis is associated with the development of antipsychotic-induced overweight/obesity in schizophrenia (SZ). We aim to determine the taxonomic composition and metabolites profiling of “obesogenic” microbiota in SZ patients after chronic antipsychotic medication.
Results:Our retrospective survey identified two groups of population separated by BMI, with 1/3 patients developing overweight/obesity after chronic antipsychotics treatment. Then, based on the 16S rRNA sequencing and multi-omics analyses, we found that SZ patients with overweight/obesity had lower relative abundances of the signature bacteria genera such as Bacteroides, Parabacteroides, Akkermansia, and Clostridium when compared to individuals with normal BMI. Further investigation revealed dysregulated energy expenditure and nutritional metabolism coupled with severe clinical indices and decreased levels of beneficial metabolites, e.g. indole-3-carboxylic acid, and propionic acid. The signature bacteria were positively associated with host metabolic homeostasis, according to the redundancy and co-occurrence analysis. Moreover, leveraging the data from first-episode drug-naïve SZ (FSZ) patients at 1-month and 1-year follow-up, both artificial neural network and random forest classifier-based prediction models demonstrated a strong ability of microbial profiles to predict antipsychotic-induced weight gain. Importantly, FSZ patients with a higher relative abundance of Parabacteria distasonisare less susceptible to antipsychotic-induced weight gain.
Conclusion: Gut microbiota could serve as a noninvasive approach to predict antipsychotic-induced weight gain, guiding clinical antipsychotics administration and developing novel therapeutic strategies for the weight management in SZ.
Effect of hydroxyl radical water treatment on functional components, volatile compounds and preservation of four different fruits and vegetables
Authors: Huang Zhenyu , Wang Jian , Cheng Hao , Yu Juncheng , Cai Ming 
Published: December 2022

Abstract
Hydroxyl radical has been widely applied in the non-food fields, but whether its feasibility for treating fruits and vegetables remains unknown. In this work, effects of hydroxyl radical water (HRW) treatment on functional components, volatile compounds, and preservation properties of cherry tomato, grape, coriander and celery were investigated. Results showed that HRW treatment could be significantly effective on delaying the color change and decay of fruits and vegetables. Besides causing a slim loss of total sugars, HRW-treated samples exhibited different losses of total phenols and ascorbic acid. The total phenol and ascorbic acid of celery were lost by 17.95% and 13.01% respectively, which may be caused by excessive surface area, indicating that the applicability of HRW to celery is still to be discussed. The loss of functional components of both fruits could be controlled under 4%. Phenolic profiles and volatile compounds kept almost steadily during treatment. Notably, the increased contents of partial ester compounds might improve the sensory of fruits and vegetables, cherry tomatoes treated with HRW showed an increase of 77.28% in ethyl caproate. Moreover, the reduction of some compounds obtained from the decomposition of fatty acid hydroperoxides may enhance the fresh odor of fruits and vegetables. Accordingly, HRW treatment is a safety and environmental technology for post-harvest processing of fruits and vegetables.
An approach for solving split common fixed point problems with multiple output sets that uses dynamic step sizes
Authors: Cui Huanhuan 
Published: December 2022

Abstract
We investigate split common fixed point problems with multiple output sets in this paper. We devise a new iterative approach to approximate its solution, in which the step size is determined independently of the norm of linear maps and the coefficient of nonlinear maps.
Under appropriate conditions, we establish two convergence theorems that cover some existing results as a special case.
Connection Number of Generalized two dimensional Rhombohedral Plane composed by p-sided Polygon
Authors: Mubashar Muhammad , Inc Mustafa , Hussain Muhammad , Rehman Atiq ur , Iqbal Muhammad Sajid 
Published: December 2022

Abstract
Gutman and Trinajstic deducted that total π-energy of a chemical molecule depends upon a numeric value which is termed as zagreb index. In that same report, they also defined a term for a particular atom with respect to other atom which is away from at a distance two. This quantity provides π-energy for a molecule. Now a days, in subject context, this quantity is termed as connection number. In this paper, we have discovered a new graph. It is composed of p-sided polygon in two dimensional rhombohedral plane. This 2D network astonishingly a new discovery in literature, its topological properties are explained via different connection numbers.
Structural optimization of sectoral exports from the perspective of water footprint: A study from Henan Province, China
Authors: Wen Faguang , Khanal Ribesh , Fang Xue , Shan Ang 
Published: December 2022

Abstract
Water used for production is the primary consumer of regional water. Water footprint reflects the actual water consumption of each product, which can reflect the intensity of water consumption of each production sector and the flow of water resources implied in the product trade. In this paper, the water footprint of each sector in Henan Province in 2017 was calculated using non-competitive input-output techniques. Furthermore, a dual-objective planning model that minimizes water resource export and maximizes labor compensation was established, based on which the export structure of the sector in the province was optimized. Research findings show that agriculture is the primary consuming sector of water resources from the direct water use perspective. In comparison, the food processing industry is the major consuming sector of water resources from the water footprint perspective. The difference in water resources consumed by sectors from the perspective of water footprint is smaller than that from the perspective of direct water use. Second, most water-intensive sectors have a relatively large water footprint of out-of-province use, which results in 52.75% of Henan Province's produced water being consumed outside the province. Third, the current export structure adjustment of sectors in Henan Province can achieve a Pareto improvement of water conservation and economic development. It is expected to save 14.65% of the province's export water resources and increase Henan Province's total exports by 170.61 billion (170.61 × 109) yuan and increase labor compensation by 39.76 billion yuan. This study can be used to optimize water allocation and improve sustainable water use in water-scarce regions.