bluuebunny/crossref_metadata_2025_split huggingface dataset:
Restoration of the soil fertility under Cr (VI) and Artificial drought condition by the utilization of plant growth promoting Bacillus spp. SSAU2
Authors: Sharma Abhijeet , Singh Shailendra Kumar , Maurya Neetu , Tripathi Shashankmani , Jaiswal Saumya , Agarwal Manshi , Sundaram Shanthy 
Published: February 2024

Abstract
The study explores the potential of an indigenous halo-tolerant microbe identified as Bacillus spp. SSAU-2 in enhancing soil fertility and promoting plant growth for sustainable agricultural practices under the influence of multiple abiotic stresses such as Cr (VI), high salinity and artificial drought condition. The study investigated various factors influencing IAA synthesis by SSAU-2, such as pH (5 to 11), salinity (10 g/L to 50 g/L), tryptophan concentration (0.5 to 1%), carbon (Manitol and Lactose), and nitrogen sources (Peptone and Tryptone). The highest IAA concentration was observed at pH 10 (1.695 mg/ml) and pH 11 (0.782 mg/ml). IAA synthesis was optimized at a salinity level of 30g/l, with lower and higher salinity levels resulting in decreased IAA concentrations. Notably, the presence of mannitol and lactose significantly augmented IAA synthesis, while glucose and sucrose had inhibitory effects. Furthermore, peptone and tryptone played a pivotal role in enhancing IAA synthesis, while ammonium chloride exerted an inhibitory influence. SSAU-2 showed a diverse array of capabilities, including the synthesis of Gibberellins, Extracellular Polymeric Substances, Siderophores, and Hydrogen Cyanide along with nitrogen fixation and ammonia production. The microbe could efficiently tolerate 45% PEG-6000 concentration and effectively produce IAA in 15% PEG concentration. It could also tolerate high concentration of Cr (VI) and synthesize IAA even in 50 ppm Cr (VI). The findings of this study provide valuable insights into harnessing the potential of indigenous microorganisms to promote plant growth, enhance soil fertility, and establish sustainable agricultural practices essential for restoring the health of ecosystems.
The adverse effect of trial duration on the use of plea bargaining and penal orders in Italy
Authors: Paolini Gabriele 
Published: February 2024

Abstract

The average duration of first-instance criminal trials has steadily increased in Italy over the last twenty years. Over the same period, the use of both plea bargaining and penal orders has steadily decreased. This situation contradicts the predictions of the economic models of plea bargaining since longer trials, by imposing higher costs on both prosecutors and defendants, should result in a greater use of trial-avoiding procedures. The phenomenon can be explained by the unique regulation of the Italian statute of limitations: if trials last longer than a certain time threshold, defendants must be acquitted, regardless of the evidence collected against them. Hence, longer trials reduce defendants’ incentives towards the use of trial-avoiding procedures that result in a criminal conviction. In an instrumental variable analysis on a panel of 140 first-instance judicial districts over the period 2005–2021 I find that longer first-instance trials decrease the use of both plea bargaining and penal orders in Italy. The results of the analysis call for a reform of the Italian statute of limitations, considering its perverse effect on defendants’ incentives.
JEL Codes: K14; K41; K42.
Manufacturing and the synthesis of (CdTe)x: (S)1-x/PSi by laser-induced plasma technology
Authors: Shaker Abdulrhman. H. , Aadim Kadhim A. , Muhsen Riyam N. 
Published: February 2024

Abstract
In this work, the porous silicon (PS) layers were prepared with the electrochemical etching technique of the n-type silicon with the resistance (3.2 µm) in the hydrofluoric acid (HF) at a concentration of (1 ml )with the current density of (25 mA/cm2) with a (20) minute etching time. The morphological advantages (AFM) and the electrical properties of J-V were studied. The atomic force microscopy investigation displays the rough silicon surface, with the etching process (etching time) porous structure nucleates which leads to an increase in the depth and the average diameter (34.12 nm). Consequently, the surface roughness also increases. The electrical properties of produce PS; namely current density-voltage characteristics, show that Porous silicon has a sponge-like structure and the pore diameter is increased with etching current density which leads to an increase in the efficiency of Solar cell devices. This behavior was attributed to the increase in the depletion zone width which led to the increase in built-in potential.
Myocarditis and Pericarditis Following the COVID-19 Vaccination: A Single-Centre Case Seriese
Authors: Alshugair Nura , Helali Sumaya Al , Almousa Adnan , Elrasheed Mohammed , Sadraldin Rozana 
Published: February 2024

Abstract
The Surveillance of rare adverse events following vaccination, particularly related to COVID-19 vaccines, requires thorough examination. This paper investigates vaccine-associated myocarditis and/or pericarditis (VAMPS), presenting insights into clinical manifestations, management, and outcomes. Conducted at the Prince Sultan Cardiac Center in Saudi Arabia from March 2021 to May 2022, this retrospective case series comprises 20 patients with an average age of 27.9 ± 14.0 years, predominantly males (70%). Pfizer-BioNTech, AstraZeneca, and Moderna vaccines were administered in 74%, 21%, and 5% of cases, respectively, with 53% receiving the second dose, 26% the booster, and 21% the initial dose. Common symptoms included shortness of breath (60%), chest pain (50%), palpitations (40%), premature ventricular contractions (35%), and fever (25%). Cardiac magnetic resonance imaging revealed preserved left ventricular function (80%), subepicardial and/or mid-wall late gadolinium enhancement (65%), and lateral (39%), anterolateral (15%), inferolateral (15%), and anteroseptal (15%) segments affected. Myocarditis, pericarditis, and myopericarditis were diagnosed in 40%, 20%, and 40% of cases, respectively. C-reactive protein was elevated in two-thirds of patients. Recovery was achieved with anti-inflammatory medications, primarily colchicine (72%), aspirin(39%), and ibuprofen (33%). While no fatalities occurred, 30% experienced severe complications, and 15% had minor complications. In conclusion, VAMPS exhibits distinct characteristics and may lead to serious complications. Cardiologists should consider VAMPS in the differential diagnosis for symptomatic patients recently vaccinated against COVID-19, emphasizing the importance of ongoing surveillance and understanding of rare adverse events.
Holistic mind activity analytical models with systems and control theory
Authors: Zhang Long 
Published: February 2024

Abstract
Among the rich brain mind activities, two distinct modes have been identified: the driven doing mode often linked to mental health problem generation and the being mode known for its healing qualities. However, fully understanding these modes is challenging because measuring brain-mind performance is not straightforward and often indirect. In this paper, we propose a holistic approach, employing systems and control theory, to gain insights into these brain-mindful modes. In a typical control system, there are two main components: the controller, analogous to the brain-mind, and the system, which symbolizes the tasks and processes governed by the mind. By applying the framework of systems and control theory, we effectively interpret the two distinct mind modes through the concepts of open-loop and closed-loop (feedback) control strategies. Furthermore, the work in this paper primarily reveals that various brain-mind related issues, such as depression, delusion, and conflict, are often viewed as instabilities in control systems. We reinforce this perspective with numerical examples that not only illustrate the root causes of these issues but also highlight how altering goals, controllers, and models within brain-mind systems can potentially alleviate these problems. Finally, the work explores how mindfulness and biofeedback practices can be interpreted within the framework of systems and control theory, enhancing our understanding of these practices.
Feature-based visual odometry with fusion of optical flow method in weak texture environment
Authors: Han Yongchen , Wu Weichao , Lan Hongyu , Bai Chen , Wu Guoqiang , Guo Zhiming 
Published: February 2024

Abstract

Feature-based visual odometry has difficulty in feature extraction and matching in weak texture environment, resulting in substantial inter-frame pose resolution errors. Meanwhile, the computation and matching of feature point descriptors can be time-consuming and computationally inefficient. To address these issues encountered by traditional ORB-SLAM odometry in texture-lacking regions, an enhanced method for visual odometry estimation is proposed. First, the quadtree technique is employed to extract ORB feature points with a uniform distribution and an adequate number. Subsequently, when processing non-critical frames, the optical flow method is utilized to predict the precise locations of the feature points, circumventing the need for feature matching. Following this, the random sampling consistency method is applied to eliminate mismatched points in optical flow tracking, ensuring that only high-quality internal points are retained. Afterwards, a system of nonlinear equations is solved using AP3P method to estimate the precise position of the camera. Finally, the trajectory is optimized by Dogleg algorithm to achieve accurate and stable tracking and positioning. The experimental results demonstrate that the improved algorithm outperforms mainstream ORB-SLAM3 algorithm in terms of operation efficiency and positioning accuracy across multiple experimental scenarios. This method effectively addresses the challenges of low tracking accuracy and poor real-time performance commonly encountered by traditional visual odometers operating in weak texture environments. As a result, the method combining the feature-based method and the optical flow method significantly enhances the application of visual odometry in complex environments by improving the tracking stability, motion estimation accuracy, and real-time performance.
Population ecology of the red wing grasshopper, Celes skalozubovi akitanus (Orthoptera, Acrididae) in Japan
Authors: OKATSU Yutaro , NAGAHATA Yoshiyuki , TSUTSUMI Tadaaki 
Published: February 2024

Abstract

The red wing grasshopper, Celes skalozubovi akitanus has been declined rapidly in Japan, and only a few populations have been recorded. Information about ecological characteristics such as food plants, phenology and mating behavior are strictly limited, and population demographics of the grasshopper in its habitat is still unknown. Consequently, conservation actions for C. s. akitanus population are urgently needed in Japan. We studied the population structure and basic ecology of C. s. akitanus, to enable the conservation management of the grasshopper and its habitat. A field survey using the transect counts and mark release recapture method was conducted for two years (2016 and 2017). We revealed that C. s. akitanus in the study area fed on a variety of grassland plants but not on the dominant Miscanthus sinensis and Pteridium aquilinum. The recapture rate of C. s. akitanus is considerably high, about 68% or more, and the two isolated populations were found in the studied grassland. The estimated total population size is less than 120 to 140 individuals, indicating that the studied population is extremely small. Our results showed that this species has a strong sedentary behavior because most of the adults move less than 5 m in one season, and strongly prefer a bare ground within the grassland. The continuing implementation of annual prescribed burning and partial mowing in the habitat is important for the conservation of C. s. akitanus. In addition, creating continuity between two populations is effective for the survival of populations in this study area.
Forecasting of Reservoir Water Level by Remote Sensing and Deep Learning
Authors: Jin Yifan , Liu Dandan , Huang Jinhui 
Published: February 2024

Abstract

Accurate reservoir water level prediction is crucial for the safe operation of reservoirs and the utilization of their functions. Traditional physical-based water level forecasting methods rely heavily on auxiliary data, such as precipitation and reservoir outflow. However, obtaining timely and reliable data on reservoir discharge flow can be expensive and impractical due to limitations in infrastructure or data accessibility. To address this issue, the current study utilized multi-source remote sensing data to extract a time series of reservoir storage volume. A technical framework for predicting water levels using deep learning models and remote sensing technology was proposed. To validate the effectiveness of this method, we compared the predictive accuracy of reservoir water levels among 16 different machine learning input scenarios. The results indicate that the model incorporating water level, rainfall, water surface area, and daily changes in reservoir storage volume as input data performed the best. Compared to the input data that did not consider water surface area and daily changes in reservoir storage, it demonstrated higher accuracy, with an increase in R2 value by 1.13%, RMSE increased by 52.17%, and MAE increased by 63.80%. The framework proposed in this study offers a reliable method for predicting reservoir water levels in the absence of operational data for reservoirs.
On the variation of small-amplitude Forbush decreaseswith solar-geomagnetic parameters
Authors: Ugwu Chukwuebuka J. , Okike Ogbonnaya , Menteso Firew M. , Alhassan Jibrin A. , Obiegbuna Dominic C. , Chukwude Augustine E. , Ugwoke Romanus E. , Iyida Evaristus U. , Eya Innocent O. , Enwelum Ugochukwu C. , Orji Orji P. 
Published: February 2024

Abstract

Detection of weak signals remains challeng-ing in astrophysics. This is particularly applicable inthe investigation of Forbush events. There is thus,a paucity of catalogs of small-amplitude Forbush de-creases (FDs). Detail investigations of the space-weather implications of small FDs are, thus, lacking inthe literature. Recently, large catalogs of weak FDs, forthe ﬁrst time, have been published. This work employsthe newly created lists of small-amplitude FDs to inves-tigate the statistical link between small FDs and solar-geomagnetic variables. The solar-geomagnetic variableswere obtained from the OMNI database. A simple co-incident R software code was employed in matchingthe related solar-geomagnetic variables with the weakForbush events. The FD dates were taken as the inputsignal. Scatter plots of FD-IMF, FD-SWS, FD-Kp, FD-Ap reveal a negative relationship, while that of FD-Dstshows a positive relationship. Statistical signiﬁcanceof these relations were tested. The small-amplitudeFDs and solar-geomagnetic variables at Potchefstroom(PTFM) station register statistically signiﬁcant rela-tions. Non-statistically signiﬁcant correlation betweenthe small-amplitude FDs and solar-geomagnetic vari-ables were obtained at South Pole (SOPO) station, withthe exception of FD-SWS that reveals statistically sig-niﬁcant correlation. The diﬀerences in the correlationresults obtained at the two stations (PTFM and SOPO)could be attributed to the diﬀerences in the character-istics of the NM stations. These results suggest that geomagnetic storm indices play important role in theevolution of FDs.
The COVID-19 pandemic era impact on the incidence of the custodial death, due to illness in 36 states and union territories of India-A comparison study (2017–2022)
Authors: Kumar Piyush , Anupama Advocate 
Published: February 2024

Abstract
Mahatma Gandhi said that “crime is due to diseased mind and jail should have an environment like hospitals for prisoner’s treatment and care”. A lot of research is carried out globally during COVID-19, on the well being of peoples staying outside the prisons, but very few large scale researches are available to know about the well being of the prisoners during COVID-19 era. The data is provided by the Prison Section of all the 36 States/UTs in prearranged Performa of the NCRB, through an application made by NCRB. A total of 11,289 custodial death occurred among the prisoners residing in various prisons of India, during the study period, out of which 9,406 (83.32 percent, Total-9406 (Obs-216, Mean-43.55, Std. Dev.- 68.87, Min-0, Max-401, Std. Err.- 4.69, 95% Conf. Interval of mean-34.31 -52.78) mortalities were attributed due to illness. Compared to year 2020, our study revealed that the COVID-19 year 2021 has attributed to largest (16.47 percent increased illness custodial death and 12.14 percent increased total mortalities) number of custodial death due to illness. The study revealed that during the study period, majority of the mortalities were due to heart diseases in prisoners (27.28 percent, Total-2566 (Obs-216, Mean-11.88, Std. Dev.- 19.30, Min-0, Max-123, Std. Err.- 1.31, 95% Conf. Interval of mean-9.29 -14.47). Cholera / Diarrhoea attributed to the least number of mortalities during the study period (0.21 percent, Total-20 (Obs-216, Mean-0.09, Std. Dev. − 0.40, Min-0, Max-4, Std. Err. − 0.03, 95% Conf. Interval of mean-.04 − .15). This six years of study revealed that most of the custodial death (42%), due to illness in prisoners of India was due to CVDs and pulmonary diseases. This study also revealed that 27% of custodial deaths due to illness were not clearly categorized. Honourable Justice Lokur, of Supreme Court of India, said in a landmark judgment, in 2013, that "The distinction made by the NCRB [National Crime Records Bureau] between natural and unnatural custodial deaths is not clear. For example, if a prisoner dies due to a lack of proper medical attention or timely medical attention, would that be classified as a natural custodial death or an unnatural custodial death?" The policymakers and decision-makers must think on the necessity of developing Prisoners care policies following the COVID-19 pandemic, in light of the findings of this research study.
Classification and Diagnosis of Heart Disease Using Machine Learning
Authors: Mohsen‬‏ ‪Ayedh Abdulaziz , Naoufel Kharroubi , Alrashahy Taher , Noaman Somia 
Published: February 2024

Abstract
Heart disease is one of the most common causes of death worldwide, and accurate and rapid diagnosis is needed to avoid serious complications. This study aimed to present a system for diagnosing and classifying common heart diseases using machine learning techniques. The data used are a set of medical records for heart patients at Ibb Medical Clinic, Ibb City, Yemen. Fourteen different classification algorithms were implemented using the Weka tool to classify different heart diseases, including eight heart diseases. The results showed that the RF algorithm was the best in terms of accuracy, sensitivity, specification, and F-measure. Based on this algorithm, a web system based on the ASPX language was designed to help users enter patient data and obtain a diagnosis and classification of heart disease. The system can help doctors in the diagnosis process and increase the medical awareness of the community.
Qualitative Evidence Synthesis Using the Costaqda Online Software
Authors: Costa King , Letlhogonolo	Mfolo  
Published: February 2024

Abstract
The use of Qualitative Evidence synthesis (QES) in policy-making across sectors such as education, public health and management and economic sciences is rapidly growing across the globe as more scholars and practitioners require distilled information about “what works” as an intervention. However, QES methodology requires high levels of expertise and capabilities to ensure a rigorous study is conducted in line with established international standards. Furthermore, integrating the QES project with capabilities provided by computer assisted qualitative data analysis software (CAQDAS) is a further improvement to producing reliable/dependable knowledge whose methods can be replicable in similar situations. The COSTAQDA is one of the newly developed intuitive cloud based CAQDAS applications that enable scholars to conduct robust literature-based studies while maintaining the highest levels of rigor, including using Inter-Coder Reliability Statistics using Cohen’s Kappa. This chapter presents the best possible methods of using QES to assist policy-makers and decision-makers with credible and trustworthy information that has been processed through rigorous methods. Advantages and disadvantages, including limitations, are discussed, with further opportunities for effectively responding to these methodological constraints through the RETREAT framework. Finally, the COSTAQDA application is presented briefly and demonstrated by visuals to assist users on project creation to completion.
Ophthalmology Residents Experience in Cataract Surgery: Pre-Operative Risk Factors, Intraoperative Complications and Surgery Outcomes
Authors: Cnaany Yaacov , Goldstein Ayelet , Lavy Itay , Halpert Michael , Chowers Itay , Ben-Eli Hadas 
Published: February 2024

Abstract

Introduction
This retrospective study explores the connection between preoperative patient risk factors, the experience of ophthalmology residents, and the outcomes of cataract surgeries conducted at Hadassah Medical Center. It is hypothesized that with increased experience, residents may demonstrate greater proficiency in handling surgeries on higher-risk patients, potentially leading to improved surgical outcomes overall.
Methods
Data from 691 consecutive cataract surgeries conducted by Ophthalmology residents at Hadassah Medical Center (1.2018–2.2022) were examined. Demographics, surgeon experience, and preoperative cataract risk assessment score, and pre- and post-operative best-corrected visual acuity (BCVA) were analyzed. The risk score was based on cataract density, previous vitrectomy, presence of phacodonesis, small pupil, extreme axial length (> 30mm or < 21.5mm) or abnormal axial length (26-30mm), shallow anterior chamber (< 2.5 mm), poor patient cooperation, oral alpha-1 blocker use, diabetic retinopathy (DR), and Fuchs' endothelial dystrophy, and having one functioning eye. This study focused on the correlation of risk scores with residents' surgical experience, and surgical outcomes.
Results
As residents gained experience, surgeries on patients with at least one risk factor increased from 54% (1st year) to 75% (2nd year; p < 0.001) and fluctuated between 75%, 82%, and 77% (3rd, 4th, and 5th years, respectively), with initial pre-operative BCVA declining progressively. Despite handling more complex cases over time, the percentage number of intraoperative complications per patient decreased with each year of residents' experience (17%, 13%, 11%, 17%, 6%; respectively). Patients without any risk factor had a higher post-operative BCVA compared those with one or more risk factors (mean ± SD LogMAR,0.16 ± 0.26 vs. 0.27 ± 0.35; p < 0.001) and a higher BCVA percentage of improvement (63% vs 57%, p = 0.016).
Conclusions
Using a preoperative risk assessment scoring system to allocate surgeries to residents at varying experience levels may reduce the risk for surgical complications, thereby, ensuring patient safety, and providing residents with a gradual learning experience.