bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Potential of Constructed Wetlands for Liquid Waste Management in Small and Medium-Scale Tannery: A Literature Review
Authors: Purba Febriani 
Published: July 2021

The leather tanning industry or tannery, mainly in the small and medium scale (SMEs), is not environmentally friendly. Limited capitals drive the SMEs-scale tanneries to dispose of liquid waste directly into water bodies without proper treatment. It might cause serious environmental problems due to the high content of COD, BOD, chromium, and dyes. Treatment of liquid waste using constructed wetlands has been widely used because it is efficient, cheap, and powerful. This review discusses the latest studies in the wastewater treatment of tanneries using phytoremediation techniques and constructed wetlands and their potential applications in the SMEs tanneries.
PENGABDIAN KKM DI DESA TURUS KECAMATAN WALANTAKA KOTA SERANG DALAM MENGHADAPI PANDEMI COVID-19 AGAR TETAP PRODUKTIF
Authors: Utami Indri Sari , Aditya Raka , Aryani Novita Sri , Putri Renny Monica , Amelia Nanda , Septiani Tasyia Aji , Syifaurrohmah  , Widiana Siti , Amelyani Yuni 
Published: July 2021

Abstract
During the Covid-19 pandemic there were still many people who ignored health protocols and also many were affected by the economy. Therefore, the student work study (KKM) of Sultan Ageng Tirtayasa University is to provide education to the public to be alert, alert and resilient to face the covid-19 outbreak. The population of activities in Turus village is all residents because the intended target is that all residents can carry out health protocols, and those who are productive can create jobs, and those who are still in school can learn well even at home. The method of implementing this KKM is a program oriented towards community assistance in the economic field, exploring local potential, a combination of online media in preparing human resource potential. Some of the results achieved in this service are the understanding of residents about covid-19, how to prevent and make their own personal protective equipment in the form of masks without sewing machines and hand sanitizers, also providing online tutoring for students, and socializing training on making aquaponics for fish and plant cultivation and help create an online media shop to promote citizen entrepreneurship.

Abstrak
Di masa pandemi covid-19 ini masih banyak masyarakat yang mengabaikan protokol kesehatan dan juga banyak yang terdampak perekonomiannya. Oleh karena itu kuliah kerja mahasiswa (KKM) Universitas sultan ageng Tirtayasa adalah memberikan edukasi kepada masyarakat untuk siaga, sigap dan Tangguh menghadapi bencana wabah covid-19. Populasi kegiatan di desa Turus adalah seluruh warga karena sasaran yang dituju adalah seluruh warga dapat menjalankan protokol kesehatan, dan untuk yang produktif dapat membuat lapangan pekerjaan, serta yang masih bersekolah dapat belajar dengan baik meskipun dirumah. Metode pelaksanaan KKM ini yakni program berorientasi kepada pendampingan masyarakat dalam bidang ekonomi, menggali potensi lokal, kombinasi media daring dalam mempersiapkan potensi sumber daya manusia. Beberapa hasil yang dicapai dalam pengabdian ini adalah pemahaman warga mengenai covid-19, cara mencegah hingga membuat sendiri alat pelindung diri berupa masker tanpa mesin jahit dan hand sanitizer, juga memberikan bimbingan belajar online bagi siswa, dan mensosialisasikan pelatihan pembuatan akuaponik budidaya ikan dan tanaman serta membantu membuatkan media online shop untuk mempromosikan wirausaha warga.
Deep Reinforcement Learning for Generalizable Field Development Optimization
Authors: He Jincong , Tang Meng , Hu Chaoshun , Tanaka Shusei , Wang Kainan , Wen Xian-Huan , Nasir Yusuf 
Published: July 2021

Summary
The optimization of field development plans (FDPs), which includes optimizing well counts, well locations, and the drilling sequence is crucial in reservoir management because it has a strong impact on the economics of the project. Traditional optimization studies are scenario specific, and their solutions do not generalize to new scenarios (e.g., new earth model, new price assumption) that were not seen before. In this paper, we develop an artificial intelligence (AI) using deep reinforcement learning (DRL) to address the generalizable field development optimization problem, in which the AI could provide optimized FDPs in seconds for new scenarios within the range of applicability.
In the proposed approach, the problem of field development optimization is formulated as a Markov decision process (MDP) in terms of states, actions, environment, and rewards. The policy function, which is a function that maps the current reservoir state to optimal action at the next step, is represented by a deep convolution neural network (CNN). This policy network is trained using DRL on simulation runs of a large number of different scenarios generated to cover a “range of applicability.” Once trained, the DRL AI can be applied to obtain optimized FDPs for new scenarios at a minimum computational cost.
While the proposed methodology is general, in this paper, we applied it to develop a DRL AI that can provide optimized FDPs for greenfield primary depletion problems with vertical wells. This AI is trained on more than 3×106 scenarios with different geological structures, rock and fluid properties, operational constraints, and economic conditions, and thus has a wide range of applicability. After it is trained, the DRL AI yields optimized FDPs for new scenarios within seconds. The solutions from the DRL AI suggest that starting with no reservoir engineering knowledge, the DRL AI has developed the intelligence to place wells at “sweet spots,” maintain proper well spacing and well count, and drill early. In a blind test, it is demonstrated that the solution from the DRL AI outperforms that from the reference agent, which is an optimized pattern drilling strategy almost 100% of the time. The DRL AI is being applied to a real field and preliminary results are promising.
Because the DRL AI optimizes a policy rather than a plan for one particular scenario, it can be applied to obtain optimized development plans for different scenarios at a very low computational cost. This is fundamentally different from traditional optimization methods, which not only require thousands of runs for one scenario but also lack the ability to generalize to new scenarios.
NOTE: This paper is also published as part of the 2021 SPE Reservoir Simulation Conference Special Issue.
A Comparative study to evaluate the efficacy of Supervised Exercise Program and Cyriax Physiotherapy on pain and function in Lateral Epicondylitis
Authors: Kalaskar Gouri , Sinha R. K. , Phansopkar Pratik 
Published: July 2021

Abstract
Background: A typical musculotendinous degenerative condition of the extensors cause at the humerus lateral epicondyle is known as Lateral epicondylitis. Various treatment methods are used in treating lateral epicondylitis. Methods: Thirty Participants with Lateral Epicondylitis shall be recruited in a comparative experimental study. Subjects will be randomized to either (1) Supervised Exercise Programme group, or (2) Cyriax Physiotherapy group. Over a 4-week time period, a 3 times in week for the total of 12 sessions, immediately following baseline assessment and randomization, subjects in both groups will receive Extensor Carpi Radialis Brevis muscle’s static stretching along with the wrist extensor’s eccentric strengthening and Ultrasound and transverse deep friction massage for 10 min with Mill’s manipulation and Ultrasound respectively. Discussion: Effectiveness of the interventions on the pain and the functional improvement will be assessed by visual analogue scale and the Tennis Elbow Function Scale respectively.
Limited Evidence For Indicator Species of High Floristic Quality Wetlands In The US Southern Plains
Authors: Fouts Tommi S. , Jog Suneeti K. , Bried Jason T. 
Published: July 2021

Abstract
Floristic Quality Assessment requires compiling a full list of vascular plant species for the wetland. Practitioners may lack the time and taxonomic skills for full-community vegetation surveys, especially when wetlands are large and complex. In this paper we broadly ask whether floristic quality indicator species may exist for wetlands, specifically evaluating indicator species potential for high floristic quality wetlands in the US southern plains region. Indicators were identified for a broader context (wetlands in Oklahoma prairie ecoregions) and narrower context (depressional wetlands in the northern Central Great Plains ecoregion of Oklahoma) based on indicator value, indicator validity, hydrophytic status, and ecological conservatism. No candidate indicators satisfied all criteria for high floristic quality. Indicator values improved with increasing spatial-environmental context, but many candidates occurred too frequently in non-high quality sites or too infrequently in high quality sites, relative to predicted rates. The best performing indicator (Eleocharis compressa) lacked validity in the broader context and showed high false-positive rates in the narrower context. Combining E. compressa with select other candidates (Amorpha fruticosa, Juncus torreyi, Leersia oryzoides, Schoenoplectus pungens) may compensate for weaknesses but the combinations may rarely be found across the region. Overall, these results do not support relying on indicator species to rapidly identify or verify high floristic quality wetlands in the US southern plains. We recommend similar studies in other regions and testing other quality levels (low, moderate) before broadly concluding that floristic quality indicator species do not exist for wetlands.
Mid-Infrared Polarization Beam Splitter based on Square/circular Hybrid Air Holes with Wide Bandwidth and Ultrashort Length
Authors: Zheng Guangming 
Published: July 2021

Abstract
A novel mid-infrared polarization beam splitter (PBS) based on GaS is proposed. The high birefringence is achieved by using the cladding structure of alternating arrangement of square and circular air holes as well as introducing double elliptical air holes. The finite element method (FEM) is utilized to investigate the mode coupling characteristics in the proposed PBS. The results show that the highest extinction ratio of 115 dB and shortest length of only 40 µm can be realized at a wavelength of 4 µm. A wide bandwidth of 200 nm ranging from 3.9µm to 4.1µm is obtained.
Detection of Hypermethylation BRCA1/2 Gene Promotor in Breast Tumors Among Moroccan Women
Authors: Saif Imane , Bouziyane Amal , Benhessou Mustapha , karroumi Mohamed El , Ennaji Moulay Mustapha 
Published: July 2021

Abstract
Background: The promoter region is a key element of gene expression regulation. In mammals, most of the genes present, at the level of their promoter, a large number of islands CpG. Age is seen as another factor promoting breast cell cancer and the tumor stage. Aim: this study aimed to explore the hypermethylation of the BRCA1/2 promoter gene in breast cancer women and correlation with age and tumor stage.Materials and methods: fifty biopsies were derived from Moroccan women treated for breast carcinoma, the DNA extracted was treated by bisulphite and the targeted BRCA1/2 Amplicons were amplified by specific methylation primers (MSP). Results: the result shows that 62% of the samples were BRCA1 methylated in addition and negative result for BRCA2, these positive epigenetic factor were remarkable in women over 47 years and at the stage of malignant tumor.Conclusion: these results show that half of the methylated samples are positive and the majority are over 47 years old, and confirms the impact of age on methylation and might be other factor of breast cancer development.
The Effect of Fractional Damping and Time-delayed Feedback on the Stochastic Resonance of Asymmetric SD Oscillator
Authors: Wang Qiubao , Wu Hao , Yang Yuejuan 
Published: July 2021

Abstract
This paper proposes the stiffness nonlinearities and asymmetric SD (smooth and discontinuous) oscillators under time-delay feedback control with a fractional damping. With the effect of displacement and velocity feedback, the oscillator is adjusted to the desired vibration state and then the stochastic resonance (SR) is achieved. This article discusses the contribution of various system parameters and time-delay feedback to SR, especially which induced by fractional damping. It should be noted that this paper provides effective guidance for fault diagnosis and weak signal detection, energy harvesting, vibration isolation and vibration reduction.
Atherosclerosis Amelioration by Allicin in Raw Garlic through Gut Microbiota and Trimethylamine-N-Oxide Modulation
Authors: Sheen Lee-Yan , Panyod Suraphan , Wu Wei-Kai , Chen Pei-Chen , Chong Kent-Vui , Yang Yu-Tang , Chuang Hsiao-Li , Chen Chieh-Chang , Chen Rou-An , Liu Po-Yu , Chung Ching-Hu , Huang Huai-Syuan , Lin Angela Yu-Chen , Shen Ting-Chin David , Yang Kai-Chien , Huang Tur-Fu , Hsu Cheng-Chih , Ho Chi-Tang , Kao Hsien-Li , Orekhov Alexander , Wu Ming-Shiang 
Published: July 2021

Abstract
Cardiovascular disease (CVD) is strongly associated with the gut microbiota and its metabolites, including trimethylamine-N-oxide (TMAO) formed from ʟ-carnitine. Raw garlic juice, with allicin as its primary compound, has been shown to powerfully impact the gut microbiota. This study validated the benefits of raw garlic juice against CVD risk via modulation of the gut microbiota and its metabolites. Allicin supplementation significantly decreased serum TMAO in ʟ-carnitine-fed C57BL/6J mice. It also reduced aortic lesions and altered the fecal microbiota in carnitine-induced, atherosclerosis-prone, apolipoprotein E-deficient mice. In human subjects exhibiting high TMAO production, raw garlic juice intake for a week reduced TMAO formation, improved gut microbial diversity, and increased the relative abundances of beneficial bacteria. In in vitro study, raw garlic juice inhibited γ-butyrobetaine (γBB) and trimethylamine (TMA) production by the gut microbiota. Thus, raw garlic juice can potentially prevent cardiovascular disease by decreasing TMAO production through gut microbiota modulation.
Can Electric Fields Drive Chemistry for an Aqueous Microdroplet?
Authors: Hao Hongxia , Leven Itai , Head-Gordon Teresa 
Published: July 2021

Abstract
Reaction rates of common organic reactions have been reported to increase by one to six orders of magnitude in aqueous microdroplets compared to bulk solution, but the reasons for the rate acceleration are poorly understood. We investigate the role of electric fields at water droplet surfaces that might explain the promotion of unusual reactive chemistry, along with changes in electric field profiles as a function of excess charge to model the electrospray fragmentation process. We find that electric field alignments along free O-H bonds at the surface yield field strength distributions that are ~30 MV/cm larger on average than that found for O-H bonds in the interior of the water droplet, consistent with greater surface reactivity. We emphasize the importance of both nuclear and electronic effects at the surface, and the non-linear coupling of intramolecular solute polarization with intermolecular solvent modes, as a necessary feature for predicting the higher field strengths at water droplet surfaces.
Nexus Among Energy Consumption Structure, Energy Intensity, Population Density, Urbanization And Carbon Intensity: A Heterogeneous Panel Evidence Considering Differences In Electrification Rates
Authors: Sun Jingqi , Guo Xiaohui , Wang Yuan , Shi Jing , Zhou Yiquan , Shen Boyang 
Published: July 2021

Abstract
In this paper, the clustering method is used to divide the 30 provinces of the country into high, medium and low electrification rates according to the electrification rate from 2000 to 2017. The heterogeneous panel technology is used to analyze the relationship of energy consumption structure, energy intensity, population density, urbanization rate and carbon intensity. According to Cross-sectional dependence(CD) test and cross-section Im-Pesaran-Shin (CIPS) test results, the data of each panel are not in the form of same order single integer, so α convergence analysis, β absolute convergence, and β conditional convergence analysis are required. The results show that the carbon intensity of the four panels shows an α convergence; the β absolute convergence shows there is a “catch-up effect”; β conditional convergence indicates that the carbon intensity approaches their respective steady state levels; there is a long-term equilibrium relationship of energy consumption structure, energy intensity, population density and carbon intensity in all panels, but the urbanization rate has a significant impact on carbon intensity only in areas with high electrification rates. Finally, based on the results of empirical research, policy recommendations for reducing the carbon intensity in different regions are proposed.
Relation Between The Roughness, Linear Entropy and Visibility of A Quantum State, The Jaynes-Cummings Model.
Authors: de Oliveira Adélcio Carlos , Reis Mauricio 
Published: July 2021

Abstract
In this work, an analysis of the Jaynes-Cummings Model is conducted in the parameter spaces, composed of Roughness, Concurrence/Linear Entropy and Visibility. The analysis was carried out without including the effects of the environment and with the inclusion of a dispersive environment. As Roughness measures the state’s degree of non-classicality, its inclusion in the analysis allows to identify points in the dynamics that are not usually perceived by traditional analysis. It is observed that the parameter space is almost completely occupied when the dispersive term is small, and is concentrated in the region of less roughness and less purity as the dispersive coefficient is increased.
Molecular Characterization And Ecotoxicological Evaluation of The Natural Dye Madder And Its Chlorinated Products
Authors: Freeman Harold S. , Santos Tuane C. dos , Chen Yufei , Vendemiatti Josiane A.S. , de Oliveira Adria C. , Vacchi Francine I. , Vinueza Nelson R. , Umbuzeiro Gisela A. 
Published: July 2021

Abstract
There has been increased interest in the use of natural dyes for textile coloration as alternatives to synthetic dyes, due to the general belief that natural dyes are more environmentally friendly. However, natural dyes have poor affinity for textiles, which can lead to high dye levels in the resultant wastewater. While chlorine treatment has proven to be effective for dye wastewater disinfection and decolorization, this process can also lead to the formation of more toxic degradation products for certain synthetic dyes. On the other hand, little information is available regarding the ecotoxicity of natural dyes and their chlorination products. To advance knowledge in this area, madder was selected due to its historical importance and wide application in the textile industry. Specifically, we sought to characterize the chlorine-induced degradation products of an aqueous madder solution and to assess their ecotoxicity. The main component of the present madder sample was Alizarin (89.8%). Chlorination led to complete decolorization, and 2-hydroxynaphthalene-1,4-dione and phthalic anhydride were identified as key degradation products. Chlorination of madder decreased toxicity to Daphnia similis (microcrustacean) 10-fold and removed the toxicity to Raphidocellis subcapitata (algae), when compared to the parent dye.
Environmental Monitoring and Potential Health Risk Assessment from Pymetrozine Exposure among Communities in Typical Rice–Growing Areas of China
Authors: Tudi Muyesaier , RUAN Huada Daniel , Tong Shuangmei , wang li , Atabila Albert , Sadler Ross , Connell Des , Phung Dung Tri 
Published: July 2021

Abstract
Pymetrozine is one of the most common insecticides used in China. This study was conducted to analyse Pymetrozine’s potential exposures through various environmental routes beyond the treatment area. The aim was to estimate the potential health risk for communities due to non-dietary exposure to Pymetrozine in soil and paddy water. Data on registration of pesticides in China, government reports, questionnaires, interviews, literature reviews as well as toxicological health investigations were evaluated to determine the hazard and dose-response characteristics of Pymetrozine. These were based on the US EPA exposure and human health risk assessment methods using exposure from soil and paddy water samples collected between 10 to 20 meters around the resident’s location.The potential exposures from dermal contact through soil and paddy water were estimated. The potential cancer risk from the following routes was evaluated: the ingestion through soil; dermal contact exposure through soil; dermal contact exposure through paddy water; and the potential total cancer risk for residents was less than 1*10− 6. These were within the acceptable risk levels. The potential hazard quotient (HQ) from acute and lifetime exposure by dermal contact through paddy water and soil; acute and lifetime exposure by soil ingestion for residents were less than 1, indicating an acceptable risk level, thus both potential cancer risk and hazard quotient (HQ) were relatively low. Potential human health risk assessment of Pymetrozine in soil and paddy water suggested that negligible cancer risk and non-cancer risk based on ingestion and dermal contact are the main potential routes of exposure to residents.
WITHDRAWN: A Hybrid Methodology for Flower Images Segmentation &amp; Recognition with extended Deep-Convolution Neural Network (CNN)
Authors: Rathore Neeraj Kumar , Jaiswal Varshali , Sharma Varsha , Varma Sunita 
Published: July 2021

Abstract
Deep-Convolution Neural Network (CNN) is the branch of computer science. Deep Learning CNN is a methodology that teaches computer systems to do what comes naturally to humans. It is a method that learns by example and experience. This is a heuristic-based method to solve computationally exhaustive problems that are not resolved in a polynomial computation time like NP-Hard problems. The purpose of this research is to develop a hybrid methodology for the detection and segmentation of flower images that utilize the extension of the deep CNN. The plant, leaf, and flower image detection are the most challenging issues due to a wide variety of classes, based on their amount of texture, color distinctiveness, shape distinctiveness, and different size. The proposed methodology is implemented in Matlab with deep learning Tool Box and the dataset of flower image is taken from Kaggle with five different classes like daisy, dandelion, rose, tulip, and sunflower. This methodology takes an input of different flower images from data sets, then converts it from RGB (Red, Green, Blue) color model to the L*a*b color model. L*a*b has reduced the effort of image segmentation. The flower image segmentation has been performed by the canny edge detection algorithm which provided better results. The implemented extended deep learning convolution neural network can accurately recognize varieties of flower images. The learning accuracy of the proposed hybrid method is up to 98% that is maximizing up to + 1.89% from state of the art.