bluuebunny/crossref_metadata_2025 huggingface dataset:
Prevalence of Pathogenic Microbes within the Endometrium in Normal Weight vs. Obese Women with Infertility
Authors: King Sarah , Osei Florence , Marsh Courtney
Published: June 2024

This study investigates the association between body mass index (BMI) and the composition of the endometrial microbiota in infertile women of childbearing age. This is a retrospective clinical study comparing the endometrial microbiota across body weight in 132 patients presenting for care at an infertility clinic. The reason for infertility was recurrent pregnancy loss (RPL) or implantation failure with a prior IVF cycle. Microbe analysis was completed by Igenomix Laboratory (Valencia, Spain) using two comprehensive panels. Patients were separated into three groups based on their results: normal, dysbiotic, and pathogenic. Prevalence of these groups was compared across BMI categories and statistical analysis was used to determine significance. Of the 132 endometrial samples collected, 80 (60.6%) were normal, 16 (12.1%) were dysbiotic, and 36 (27.3%) were pathogenic. Patients with a BMI ≥ 30 showed a statistically significant increase in pathogenic endometrium compared to normal weight controls (p = 0.029). Our conclusion is that the prevalence of pathogenic endometrium was significantly higher in the obese group compared with normal weight controls. There is a possible association between obesity and the endometrial microbiome.
Systematic Literature Review of Land Use Conflicts in Northern Sweden—Lessons Learned and Ways Forward
Authors: Elomina Jerbelle , Živojinović Ivana
Published: June 2024

Land use conflicts are intensifying in Northern Sweden due to the increasing global demand for resources coupled with the green transition. In line with this, a thorough understanding of land use conflicts in the area is becoming necessary as economic activities expand and newer ones are developed. Hence, this paper aims to provide a systematic literature review of research on land use conflicts specific to Northern Sweden, focusing on various economic activities such as forestry, mining, tourism, energy sector and reindeer husbandry. Additionally, we aim to determine lessons learned and suggested ways forward based on a systematic review. We used Scopus and Web of Science on June 2023 and through descriptive statistical analysis of 33 articles, we summarized research trends and gaps. We found three main typologies of conflicts and five main themes of suggested ways forward. Recommendations agree that there should be a broader understanding of the underlying interests of the stakeholders; and there should be an inclusive, more participatory approach to discussing potential solutions, not to create an agreement but to come to an understanding. Beyond academic insights, the findings hold practical relevance for shaping effective land use policies. This paper offers valuable lessons that extend beyond the local context, informing broader discussions and policy considerations for sustainable land management in the larger Arctic setting, where similar challenges and resource demands are unfolding.
A Robust High-Accuracy Star Map Matching Algorithm for Dense Star Scenes
Authors: Sun Quan , Niu Zhaodong , Li Yabo , Wang Zhuang
Published: June 2024

The algorithm proposed in this paper aims at solving the problem of star map matching in high-limiting-magnitude astronomical images, which is inspired by geometric voting star identification techniques. It is a two-step star map matching algorithm relying only on angular features, and adopts a reasonable matching strategy to overcome the problem of poor real-time performance of the geometric voting algorithm when the number of stars is large. The algorithm focuses on application scenarios where there are a large number of dense stars (limiting magnitude greater than 13, average number of stars per square degree greater than 185) in the image, which is different from the sparse star identification problem of the star tracker, which is more challenging for the robustness and real-time performance of the algorithm. The proposed algorithm can be adapted to application scenarios such as unreliable brightness information, centroid positioning error, visual axis pointing deviation, and a large number of false stars, with high accuracy, robustness, and good real-time performance.
Instrument Overview and Radiometric Calibration Methodology of the Non-Scanning Radiometer for the Integrated Earth–Moon Radiation Observation System (IEMROS)
Authors: Zhang Hanyuan , Ye Xin , Wu Duo , Wang Yuwei , Yang Dongjun , Lin Yuchen , Dong Hang , Zhou Jun , Fang Wei
Published: June 2024

The non-scanning radiometer with short-wavelength (SW: 0.2–5.0 μm) and total-wavelength (TW: 0.2–50.0 μm) channels is the primary payload of the Integrated Earth–Moon Radiation Observation System (IEMROS), which is designed to provide comprehensive Earth radiation measurements and lunar calibrations at the L1 Lagrange point of the Earth–Moon system from a global perspective. This manuscript introduces a radiometer preflight calibration methodology, which involves background removal and is validated using accurate and traceable reference sources. Simulated Earth view tests are performed to evaluate repeatability, linearity, and gain coefficients over the operating range. Both channels demonstrate repeatability uncertainties better than 0.34%, indicating consistent and reliable measuring performance. Comparative polynomial regression analysis confirms significant linear response characteristics with two-channel nonlinearity less than 0.20%. Gain coefficients are efficiently determined using a two-point calibration approach. Uncertainty analysis reveals an absolute radiometric calibration accuracy of 0.97% for the SW channel and 0.92% for the TW channel, underscoring the non-scanning radiometer’s capability to provide dependable global Earth radiation budget data crucial to environmental and climate studies.
Transformable Quadruped Wheelchairs Capable of Autonomous Stair Ascent and Descent
Authors: Akamisaka Atsuki , Nagao Katashi
Published: June 2024

Despite advancements in creating barrier-free environments, many buildings still have stairs, making accessibility a significant concern for wheelchair users, the majority of whom check for accessibility information before venturing out. This paper focuses on developing a transformable quadruped wheelchair to address the mobility challenges posed by stairs and steps for wheelchair users. The wheelchair, inspired by the Unitree B2 quadruped robot, combines wheels for flat surfaces and robotic legs for navigating stairs and is equipped with advanced sensors and force detectors to interact with its surroundings effectively. This research utilized reinforcement learning, specifically curriculum learning, to teach the wheelchair stair-climbing skills, with progressively increasing complexity in a simulated environment crafted in the Unity game engine. The experiments demonstrated high success rates in both stair ascent and descent, showcasing the wheelchair’s potential in overcoming mobility barriers. However, the current model faces limitations in tackling various stair types, like spiral staircases, and requires further enhancements in safety and stability, particularly in the descending phase. The project illustrates a significant step towards enhancing mobility for wheelchair users, aiming to broaden their access to diverse environments. Continued improvements and testing are essential to ensure the wheelchair’s adaptability and safety across different terrains and situations, underlining the ongoing commitment to technological innovation in aiding individuals with mobility impairments.
Electrochemical Diffusion Study in Poly(Ethylene Glycol) Dimethacrylate-Based Hydrogels
Authors: Melnik Eva , Kurzhals Steffen , Mutinati Giorgio C. , Beni Valerio , Hainberger Rainer
Published: June 2024

Hydrogels are of great importance for functionalizing sensors and microfluidics, and poly(ethylene glycol) dimethacrylate (PEG-DMA) is often used as a viscosifier for printable hydrogel precursor inks. In this study, 1–10 kDa PEG-DMA based hydrogels were characterized by gravimetric and electrochemical methods to investigate the diffusivity of small molecules and proteins. Swelling ratios (SRs) of 14.43–9.24, as well as mesh sizes ξ of 3.58–6.91 nm were calculated, and it was found that the SR correlates with the molar concentration of PEG-DMA in the ink (MCI) (SR = 0.1127 × MCI + 8.3256, R2 = 0.9692) and ξ correlates with the molecular weight (Mw) (ξ = 0.3382 × Mw + 3.638, R2 = 0.9451). To investigate the sensing properties, methylene blue (MB) and MB-conjugated proteins were measured on electrochemical sensors with and without hydrogel coating. It was found that on sensors with 10 kDa PEG-DMA hydrogel modification, the DPV peak currents were reduced to 92 % for MB, 73 % for MB-BSA, and 23 % for MB-IgG. To investigate the diffusion properties of MB(-conjugates) in hydrogels with 1–10 kDa PEG-DMA, diffusivity was calculated from the current equation. It was found that diffusivity increases with increasing ξ. Finally, the release of MB-BSA was detected after drying the MB-BSA-containing hydrogel, which is a promising result for the development of hydrogel-based reagent reservoirs for biosensing.
Micro-Ring Resonator Assisted Photothermal Spectroscopy of Water Vapor
Authors: Kotlyar Maria V. , Mapranathukaran Jenitta Johnson , Biagi Gabriele , Walsh Anton , Lendl Bernhard , O’Faolain Liam
Published: June 2024

We demonstrated, for the first time, micro-ring resonator assisted photothermal spectroscopy measurement of a gas phase sample. The experiment used a telecoms wavelength probe laser that was coupled to a silicon nitride photonic integrated circuit using a fibre array. We excited the photothermal effect in the water vapor above the micro-ring using a 1395 nm diode laser. We measured the 1f and 2f wavelength modulation response versus excitation laser wavelength and verified the power scaling behaviour of the signal.
Identification of a Person in a Trajectory Based on Wearable Sensor Data Analysis
Authors: Yan Jinzhe , Toyoura Masahiro , Wu Xiangyang
Published: June 2024

Human trajectories can be tracked by the internal processing of a camera as an edge device. This work aims to match peoples’ trajectories obtained from cameras to sensor data such as acceleration and angular velocity, obtained from wearable devices. Since human trajectory and sensor data differ in modality, the matching method is not straightforward. Furthermore, complete trajectory information is unavailable; it is difficult to determine which fragments belong to whom. To solve this problem, we newly proposed the SyncScore model to find the similarity between a unit period trajectory and the corresponding sensor data. We also propose a Likelihood Fusion algorithm that systematically updates the similarity data and integrates it over time while keeping other trajectories in mind. We confirmed that the proposed method can match human trajectories and sensor data with an accuracy, a sensitivity, and an F1 of 0.725. Our models achieved decent results on the UEA dataset.
Detection of α-Galactosidase A Reaction in Samples Extracted from Dried Blood Spots Using Ion-Sensitive Field Effect Transistors
Authors: Kuznetsov Alexander , Sheshil Andrey , Smolin Eugene , Grudtsov Vitaliy , Ryazantsev Dmitriy , Shustinskiy Mark , Tikhonova Tatiana , Kitiashvili Irakli , Vechorko Valerii , Komarova Natalia
Published: June 2024

Fabry disease is a lysosomal storage disorder caused by a significant decrease in the activity or absence of the enzyme α-galactosidase A. The diagnostics of Fabry disease during newborn screening are reasonable, due to the availability of enzyme replacement therapy. This paper presents an electrochemical method using complementary metal-oxide semiconductor (CMOS)-compatible ion-sensitive field effect transistors (ISFETs) with hafnium oxide-sensitive surfaces for the detection of α-galactosidase A activity in dried blood spot extracts. The capability of ISFETs to detect the reaction catalyzed by α-galactosidase A was demonstrated. The buffer composition was optimized to provide suitable conditions for both enzyme and ISFET performance. The use of ISFET structures as sensor elements allowed for the label-free detection of enzymatic reactions with melibiose, a natural substrate of α-galactosidase A, instead of a synthetic fluorogenic one. ISFET chips were packaged with printed circuit boards and microfluidic reaction chambers to enable long-term signal measurement using a custom device. The packaged sensors were demonstrated to discriminate between normal and inhibited GLA activity in dried blood spots extracts. The described method offers a promising solution for increasing the widespread distribution of newborn screening of Fabry disease.
An Integrated Smart Pond Water Quality Monitoring and Fish Farming Recommendation Aquabot System
Authors: Hemal Md. Moniruzzaman , Rahman Atiqur , Nurjahan  , Islam Farhana , Ahmed Samsuddin , Kaiser M. Shamim , Ahmed Muhammad Raisuddin
Published: June 2024

The integration of cutting-edge technologies such as the Internet of Things (IoT), robotics, and machine learning (ML) has the potential to significantly enhance the productivity and profitability of traditional fish farming. Farmers using traditional fish farming methods incur enormous economic costs owing to labor-intensive schedule monitoring and care, illnesses, and sudden fish deaths. Another ongoing issue is automated fish species recommendation based on water quality. On the one hand, the effective monitoring of abrupt changes in water quality may minimize the daily operating costs and boost fish productivity, while an accurate automatic fish recommender may aid the farmer in selecting profitable fish species for farming. In this paper, we present AquaBot, an IoT-based system that can automatically collect, monitor, and evaluate the water quality and recommend appropriate fish to farm depending on the values of various water quality indicators. A mobile robot has been designed to collect parameter values such as the pH, temperature, and turbidity from all around the pond. To facilitate monitoring, we have developed web and mobile interfaces. For the analysis and recommendation of suitable fish based on water quality, we have trained and tested several ML algorithms, such as the proposed custom ensemble model, random forest (RF), support vector machine (SVM), decision tree (DT), K-nearest neighbor (KNN), logistic regression (LR), bagging, boosting, and stacking, on a real-time pond water dataset. The dataset has been preprocessed with feature scaling and dataset balancing. We have evaluated the algorithms based on several performance metrics. In our experiment, our proposed ensemble model has delivered the best result, with 94% accuracy, 94% precision, 94% recall, a 94% F1-score, 93% MCC, and the best AUC score for multi-class classification. Finally, we have deployed the best-performing model in a web interface to provide cultivators with recommendations for suitable fish farming. Our proposed system is projected to not only boost production and save money but also reduce the time and intensity of the producer’s manual labor.
Factors Affecting the Situational Awareness of Armored Vehicle Occupants
Authors: Pei Zihan , Zhao Wenyu , Hu Long , Zhang Ziye , Luo Yang , Wu Yixiang , Jin Xiaoping
Published: June 2024

In the field of armored vehicles, up to 70% of accidents are associated with low levels of situational awareness among the occupants, highlighting the importance of situational awareness in improving task performance. In this study, we explored the mechanisms influencing situational awareness by simulating an armored vehicle driving platform with 14 levels of experimentation in terms of five factors: experience, expectations, attention, the cueing channel, and automation. The experimental data included SART and SAGAT questionnaire scores, eye movement indicators, and electrocardiographic and electrodermal signals. Data processing and analysis revealed the following conclusions: (1) Experienced operators have higher levels of situational awareness. (2) Operators with certain expectations have lower levels of situational awareness. (3) Situational awareness levels are negatively correlated with information importance affiliations and the frequency of anomalous information in non-primary tasks. (4) Dual-channel cues lead to higher levels of situational awareness than single-channel cues. (5) Operators’ situational awareness is lower at high automation levels.
A Tutorial on Mechanical Sensors in the 70th Anniversary of the Piezoresistive Effect
Authors: Reverter Ferran
Published: June 2024

An outstanding event related to the understanding of the physics of mechanical sensors occurred and was announced in 1954, exactly seventy years ago. This event was the discovery of the piezoresistive effect, which led to the development of semiconductor strain gauges with a sensitivity much higher than that obtained before in conventional metallic strain gauges. In turn, this motivated the subsequent development of the earliest micromachined silicon devices and the corresponding MEMS devices. The science and technology related to sensors has experienced noteworthy advances in the last decades, but the piezoresistive effect is still the main physical phenomenon behind many mechanical sensors, both commercial and in research models. On this 70th anniversary, this tutorial aims to explain the operating principle, subtypes, input–output characteristics, and limitations of the three main types of mechanical sensor: strain gauges, capacitive sensors, and piezoelectric sensors. These three sensor technologies are also compared with each other, highlighting the main advantages and disadvantages of each one.
Dependence of Magnetic Properties of As-Prepared Nanocrystalline Ni2MnGa Glass-Coated Microwires on the Geometrical Aspect Ratio
Authors: Salaheldeen Mohamed , Zhukova Valentina , Lopez Anton Ricardo , Zhukov Arcady
Published: June 2024

We have prepared NiMnGa glass-coated microwires with different geometrical aspect ratios, ρ = dmetal/Dtotal (dmetal—diameter of metallic nucleus, and Dtotal—total diameter). The structure and magnetic properties are investigated in a wide range of temperatures and magnetic fields. The XRD analysis illustrates stable microstructure in the range of ρ from 0.25 to 0.60. The estimations of average grain size and crystalline phase content evidence a remarkable variation as the ρ-ratio sweeps from 0.25 to 0.60. Thus, the microwires with the lowest aspect ratio, i.e., ρ = 0.25, show the smallest average grain size and the highest crystalline phase content. This change in the microstructural properties correlates with dramatic changes in the magnetic properties. Hence, the sample with the lowest ρ-ratio exhibits an extremely high value of the coercivity, Hc, compared to the value for the sample with the largest ρ-ratio (2989 Oe and 10 Oe, respectively, i.e., almost 300 times higher). In addition, a similar trend is observed for the spontaneous exchange bias phenomena, with an exchange bias field, Hex, of 120 Oe for the sample with ρ = 0.25 compared to a Hex = 12.5 Oe for the sample with ρ = 0.60. However, the thermomagnetic curves (field-cooled—FC and field-heating—FH) show similar magnetic behavior for all the samples. Meanwhile, FC and FH curves measured at low magnetic fields show negative values for ρ = 0.25, whereas positive values are found for the other samples. The obtained results illustrate the substantial effect of the internal stresses on microstructure and magnetic properties, which leads to magnetic hardening of samples with low aspect ratio.
The Accuracy of Evaluation of the Requirements of the Standards IEC 61000-3-2(12) with the Application of the Wideband Current Transducer
Authors: Stano Ernest , Wiak Slawomir
Published: June 2024

The aim of this paper is to determine the conversion accuracy of the Danisense DC200IF (Danisense A/S, Taastrup, Denmark) wideband current transducer for its possible application to test electromagnetic compatibility requirements of the standards IEC 61000-3-2 and IEC 61000-3-12 with the digital power meter Yokogawa WT5000 (Yokogawa Electric Corporation, Tokyo, Japan). To obtain this goal for distorted current of main frequency equal to 50 Hz and in the frequencies range of higher harmonics from 100 Hz to 2500 Hz its amplitude error and phase shift are evaluated. Moreover, the measurable level of higher harmonics with the rated accuracy of the used precision power analyzer is also investigated. Finally, the measuring system is applied to determine the RMS values of current harmonics produced by the audio power amplifier in order to assess its compliance with the standard IEC 61000-3-12.
Investigation of Appropriate Scaling of Networks and Images for Convolutional Neural Network-Based Nerve Detection in Ultrasound-Guided Nerve Blocks
Authors: Sugino Takaaki , Onogi Shinya , Oishi Rieko , Hanayama Chie , Inoue Satoki , Ishida Shinjiro , Yao Yuhang , Ogasawara Nobuhiro , Murakawa Masahiro , Nakajima Yoshikazu
Published: June 2024

Ultrasound imaging is an essential tool in anesthesiology, particularly for ultrasound-guided peripheral nerve blocks (US-PNBs). However, challenges such as speckle noise, acoustic shadows, and variability in nerve appearance complicate the accurate localization of nerve tissues. To address this issue, this study introduces a deep convolutional neural network (DCNN), specifically Scaled-YOLOv4, and investigates an appropriate network model and input image scaling for nerve detection on ultrasound images. Utilizing two datasets, a public dataset and an original dataset, we evaluated the effects of model scale and input image size on detection performance. Our findings reveal that smaller input images and larger model scales significantly improve detection accuracy. The optimal configuration of model size and input image size not only achieved high detection accuracy but also demonstrated real-time processing capabilities.
One-Step Chromatographic Approach for Purifying Peptides and Proteins from Venoms
Authors: Boughanmi Yasmine , Aboudou Soioulata , Boyadjian Kayané , Charouandi Acil , Bouzid Sarra , Barnetche Thelma , Mansuelle Pascal , Lebrun Régine , Gigmes Didier , de Pomyers Harold , Mabrouk Kamel
Published: June 2024

Animal venoms are intricate and teem with potential for groundbreaking medical advancements. Although traditional methods for purifying venom proteins are effective, they usually require complicated, multi-step processes that lead to lower yields. Our study introduces an efficient, one-step technique for extracting venom-derived proteins through reverse-phase high-performance liquid chromatography (RP-HPLC). We carefully optimized the RP-HPLC process, focusing on the gradient elution conditions and the strategic use of our columns’ stationary phase characteristics, to enhance the effectiveness of our separations. This enabled us to efficiently isolate six venom proteins: melittin (2.846 kDa) from Apis mellifera with a yield of 4.5% and homogeneity of 99%; α-cobratoxin (7.821 kDa) from Naja kaouthia with a yield of 15% and homogeneity of 99%; α-bungarotoxin (7.983 kDa) from Bungarus multicinctus with a yield of 7% and purity of 99%; calciseptine (7.035 kDa) from Dendroaspis polylepis with a yield of 6% and homogeneity of 95%; notexin (13.593 kDa) from Notechis scutatus with a yield of 10% and homogeneity of 95%; and CVFm (150 kDa) from Naja melanoleuca with a yield of 0.8% and homogeneity of 94%. These were all accomplished in one step. This breakthrough simplifies the purification of venom peptides and proteins, making the process more feasible and economical. It paves the way for developing new drugs and promising treatments that are both more effective and precisely targeted.
Effects of Kin Ball Initiation: Pre- and Post-Pandemic Impact on Palmar Muscle Strength, Endurance, and Coordination in Non-Athlete Participants
Authors: Rosu Daniel , Enache Ion-Sebastian , Muntean Raul-Ioan , Stefanica Valentina
Published: June 2024

The aim of our research is to introduce Kin Ball for the first time in Romania and assess its impact on the motor capacities of practitioners, particularly focusing on its potential contribution to developing motor skills in young students within the academic sphere, despite the challenges posed by the COVID-19 pandemic. Design: A retrospective, case–control study with a focus on four distinct research groups. Setting: The research was conducted in a camp setting, situated in the mountainous region of Bughea de Sus, Romania. Participants: The study included 94 students, comprising 54 boys and 40 girls, with an overall average age of 20.85 ± 2 years. All participants were classified as non-athletes based on their level of sports practice. Interventions: The Kin Ball initiation program, a key component of the study, comprised 20 training sessions conducted in 10-day stages, systematically evaluating participants’ motor skills. Main outcome measures: The study assessed palmar muscle strength, endurance, and co-ordination function. Results: Statistical analyses, including the Kolmogorov–Smirnov test, revealed notable differences in the initiation process and significant variations (p < 0.05) in all measurements performed in 2022. In 2019, the tests recorded both significant and statistically insignificant differences, as indicated by the calculation of Cohen’s d indicator. Conclusions: The study underscored the influence of reduced movement during the pandemic on motor skills and highlighted Kin Ball’s potential as an alternative sport within physical education curricula. Despite lower baseline motor capacities observed in 2022, participants exhibited significant progress, emphasizing Kin Ball’s capacity to improve physical skills. These findings underscore the importance of alternative sports such as Kin Ball in fostering holistic personal development and mitigating the impact of pandemic-induced disruptions on motor skills.
Can Environmental Protection Tax Decrease Urban Ozone Pollution? A Quasi-Natural Experiment Based on Cities in China
Authors: Xue Wenhao , Xiong Zhenwu , Wang Liyun , Yang Zhe , Li Xinyao
Published: June 2024

The air pollution control in China has gradually transitioned from single pollutant control to multi-pollutant collaborative governance. Among the relevant factors, the control of ozone (O3) pollution has received widespread attention. Among the numerous air pollution regulations, environmental protection tax (EPT) is highly valued, as it can effectively control the emissions of O3 precursors. The objective of this study is to investigate whether the implementation of an EPT can reduce urban O3 pollution in China. Based on this, we used the difference-in-differences (DID) method, combined with the panel data from 221 cities in China from 2015 to 2020, to conduct an empirical analysis of the impacts of EPT reform policy on O3 pollution. The econometrics results indicate that the EPT reform policy can effectively inhibit urban near-surface O3 pollution by approximately 2.1%, and this result was confirmed to be accurate by multiple robustness tests. Additionally, significant spatial heterogeneities of this control effect are captured in this paper. Due to urban development levels and geographical factors, the better pollution reduction effects were national-model environmental protection, and efforts based on inland cities and high-level financial cities. Furthermore, three potential mechanisms, including cutting energy consumption, industrial structure optimization, and technological advance, were verified as being relevant to the impact path of EPT reform policy as to O3 pollution. This paper can provide empirical evidence for O3 pollution control in China, and also contribute to the further improvement of environmental protection policies.
Harnessing the Power of Algorithmic Human Resource Management and Human Resource Strategic Decision-Making for Achieving Organizational Success: An Empirical Analysis
Authors: Alabdali Mahmoud Abdulhadi , Khan Sami A. , Yaqub Muhammad Zafar , Alshahrani Mohammed Awad
Published: June 2024

This study examines the role of using algorithmic human resource management (HRM) to make strategic decisions concerning firms’ human resource (HR) activities. This study develops a scale to measure algorithmic HRM usage in its first phase. In the second phase, it is found that algorithmic HRM usage significantly impacts strategic HR decision-making, which helps and enables firms to create a competitive advantage. Utilizing the authors’ LinkedIn profiles, 234 participants were included in the fieldwork. Collected data were analyzed by applying partial least squares structure equation modeling (PLS-SEM). The mediating roles of HR strategic decision-making and HR digital maturity as moderators in enabling the impact of algorithmic HRM on the firm’s competitive advantage have been corroborated. This study finds a strong relationship between algorithmic HRM usage and competitive advantage, a significant relationship between algorithmic HRM usage and strategic HR decision-making, and a significant relationship between strategic HR decision-making and competitive advantage. The moderating role of HR digital maturity was insignificant in this research, paving the way for future research. This research, the model, and its findings contribute to the theory and implicate the practicality of algorithmic HRM. It is one of few papers addressing algorithmic HRM usage in a transitioning economy like Saudi Arabia.
Bituminous Soil Remediation in the Thermal Plasma Environment
Authors: Gimžauskaitė Dovilė , Tamošiūnas Andrius , Eimontas Justas , Aikas Mindaugas , Uscila Rolandas , Snapkauskienė Vilma
Published: June 2024

Petroleum hydrocarbons like diesel, crude oil, and bitumen are persistent soil contaminants, necessitating urgent remediation due to their harmful effects on the soil and living organisms. Plasma remediation is a thermochemical method that is gaining attention as an alternative to soil de-pollution. Accordingly, the purpose of this experimental research is to investigate the feasibility of thermal air and water vapour plasmas to de-pollute bituminous soil. Pre-/post-remediation of soil and generated products, an analysis was carried out using SEM, EDX, TGA, and elemental and gas analysers. Despite the plasma type, the research showed that the bituminous soil’s surface morphology changed and resembled clean soil after the remediation. The EDX analysis revealed that the carbon content in the soil reduced from 70.14 wt.% to 7.70 wt.% and 5.74 wt.% and the sulphur concentration decreased from 2.64 wt.% to 0.70 wt.% and 0.74 wt.% after treatment in the environment of water vapour and air plasmas, respectively. The gas analysis revealed that bitumen was mainly decomposed into a synthesis gas (H2 + CO) and CO2, with concentrations ranging from 8.67% to 13.66% and 10.89% to 12.82% when air and water vapour plasma were used. Thus, both thermal plasmas effectively remediated soil, with the bitumen concentration not being detected or below the laboratory’s finding limit (<0.089 g/kg).
Social Inclusion and Sustainable Development: Findings from Seven African and Asian Contexts
Authors: Mir Ghazala , Durrani Naureen , Julian Rachel , Kimei Yasah , Mashreky Saidur , Doan T. T. Duong
Published: June 2024

Social inequities have widened divisions between diverse population groups. Inequity is associated with social exclusion, structural and physical violence and reduced development, which in turn are linked to civil unrest, conflict and adverse health and social outcomes. Public services are key institutions through which social inequities are created and maintained, but evidence on viable interventions to reduce institutional exclusion is limited for low- and middle-income (LMIC) contexts. We identify common drivers of institutional exclusion across diverse populations in LMICs and inclusion strategies that could potentially work across populations, public service sectors and country contexts. Seven studies engaged with over 385 key stakeholders in healthcare, education and local government settings in Bangladesh, Kazakhstan, Kenya, Myanmar, Nepal, Nigeria and Vietnam. Participatory research, in-depth interviews, policy reviews and multi-stakeholder workshops focused on a range of disadvantaged groups. A multi-sector partnership co-produced recommendations at each site. Findings were synthesised to identify common themes and a framework for social inclusion across disadvantaged populations. The invisibility of disadvantaged communities in public service planning and delivery processes helped maintain their exclusion from opportunities and resources. A spectrum of neglect, restrictions and discriminatory practice reflected structural violence linked to poor life chances, illness, physical abuse and death. Key recommendations include the representation of disadvantaged groups in service staffing and decision-making and the transformation of public service policy and practice to develop inclusive, targeted, collaborative and accountable systems.
Crosswalking the EU Nature Restoration Regulation and the Kunming-Montreal Global Biodiversity Framework: A Forest-Centred Outlook
Authors: Aggestam Filip
Published: June 2024

Following the adoption of the Kunming-Montreal Global Biodiversity Framework (KM-GBF) under the Convention on Biological Diversity, the European Union (EU) introduced an EU Nature Restoration Regulation. This study systematically compares the restoration regulation with the KM-GBF, focusing on their implications for forest ecosystems. The paper identifies areas of alignment, divergence, and potential gaps concerning habitat restoration, species protection, climate resilience, and sustainable natural resource use. Employing a grounded methodology, the analysis begins with the 23 KM-GBF targets and proceeds to the 28 articles of the restoration regulation. The findings underscore the need for better alignment between the KM-GBF, the restoration regulation, and other forest-related EU policies. The study emphasises the importance of a coherent and integrated EU policy approach to address the complex challenges and varied policy objectives facing forests. It concludes that amendments to the restoration regulation have significantly diluted its potential impact, limiting the EU Member States’ accountability and ability to meet KM-GBF goals and targets. It further stresses the need for strategies to reconcile divergent EU policy pathways, support forest management and restoration efforts, and align with global biodiversity objectives.
Executives Implicated in Financial Reporting Fraud and Firms’ Investment Decisions
Authors: Cho Moon Kyung , Kang Minjung
Published: June 2024

This study examines the impact of executives implicated in fraud on firms’ investment decisions using publicly disclosed Accounting and Auditing Enforcement Releases (AAERs) of the U.S. Securities and Exchange Commission (SEC), aiming to address the underexplored aspect of rationalization within the fraud triangle. AAERs summarize enforcement actions subject to civil lawsuits brought by the SEC in federal court. Executives implicated in fraud often display abnormal attitudes to justify accounting irregularities, prompting an investigation into how abnormal investment decisions are used for rationalizing fraud, given their critical role in a firm’s long-term sustainability. We utilize bootstrap analysis to address the non-normality of fraud firms in our sample, and to acquire multiple bootstrap samples that represent the fraud population, thereby bolstering the reliability of our statistical analysis. Analysis of AAERs spanning from 1981 to 2013 reveals that implicated executives, particularly CEOs and CFOs, tend to make abnormal investment decisions, and that collusive fraud exacerbates this behavior. Notably, such executives lean towards overinvestment, particularly in R&D expenditure, to hide or justify fraud; the duration of fraud amplifies its impact on investment decisions. By shedding light on the rationalization aspect of the fraud triangle, this research contributes valuable insights for investors, regulators, and academia, emphasizing the significance of public disclosure of fraud by regulators to enhance transparency in capital markets and to alert capital market participants. Furthermore, this study underscores the importance of ethics-focused education in accounting to prevent corporate fraud.
Pesticidal Plant Treatments Combined with Improved Soil Fertility Can Reduce Damage Caused by Fusarium Wilt (Fusarium oxysporum f.sp. phaseoli) and Bean Fly (Ophiomyia phaseoli) in Common Bean Production (Phaseolus vulgaris L.)
Authors: Ngoya Zuwena J. , Mkindi Angela G. , Vanek Steven J. , Stevenson Philip C. , Ndakidemi Patrick A. , Belmain Steven R.
Published: June 2024

Common bean production is constrained by a multitude of biotic constraints including bean flies and Fusarium wilt in tropical and subtropical farming systems globally. As these pests and diseases attack the crop beneath the soil, excessive applications of synthetic pesticides are frequently used for their control. The use of plant-based pesticides could be a more sustainable management approach; however, few studies have investigated their application for controlling soil-borne pests and diseases. This study aimed to evaluate the efficacy of pesticidal plants and soil fertility management for controlling bean fly (Ophiomyia spp.) and Fusarium wilt (Fusarium spp.) using extracts and pastes of Azadirachta indica, Tephrosia vogelii, Tagetes minuta, Lippia javanica, Cymbopogon citratus and Ocimum gratissimum. To protect against Fusarium wilt and bean fly, pesticidal plants were applied as a seed coating and/or foliar spray, and demonstrated that common bean seeds coated with T. vogelii resulted in higher yields than other pesticidal plants and the synthetic pesticide control treatment. Treatments to target bean fly damage showed no significant difference between application methods on the oviposition rate of bean fly. An integrated treatment of T. minuta with 2 g Diammonium phosphate fertilizer and high compost led to higher yields than other treatments. Our results indicate that key soil-borne pests and pathogens of common bean can be effectively managed without synthetic pesticide inputs, while seed ball pastes of pesticidal plants combined with soil fertility management can increase crop yields using cost-beneficial agroecological farming systems.
Unveiling the Dynamics of Educational Equity: Exploring the Third Type of Digital Divide for Primary and Secondary Schools in China
Authors: Wang Ping , Li Zhiyuan , Wang Yujing , Wang Feiye
Published: June 2024

The COVID-19 pandemic has accelerated the integration of online learning into primary and secondary education. However, gaps persist in academic research, particularly in understanding its impact on educational equity within the third-type digital divide. This study conducted an equity-focused review to assess online learning’s impact on primary and secondary education within this context. It developed a theoretical framework integrating elements from schooling and home environments to explore equity implications in online learning. Building on this, the study proposed and validated a conceptual model using structural equation modeling (SEM), analyzing data from 1236 students in Shenzhen, China. The study found that both school investment and family involvement indirectly influence students’ online learning outcomes through complete mediating effects on students’ online learning engagement. Family investment slightly outweighs school education in its influence on outcomes. Consequently, online education within the environmental divide potentially hinders educational equity, necessitating caution with large-scale online education initiatives. This study fills research gaps on the digital divide in the third environment, leveraging China’s pandemic experience with online education. It also integrates school education and family input to examine the impact of large-scale online learning and its associated strategies on educational equity, providing insights into the promotion of educational equity.
Reading Harry Potter: A Journey into Students’ Understanding of Sustainable Development Goals
Authors: Zorba Mehmet Galip , Şahhüseyinoğlu Derya , Arikan Arda
Published: June 2024

Implementing education for sustainable development (SD) into higher education requires curricular changes, embodying various constraints. Therefore, exploring students’ understanding of sustainable development goals (SDGs) is part of the initial steps. In doing this, students’ reflections on literary works can yield valuable insights and guide what and how to teach for effective ESD practices. This study investigated university students’ understanding of SDGs through their reflections on a literary work. A mixed-methods research design was employed, collecting data from senior English literature students at a Turkish state university. Qualitative data were collected through an open-ended survey and students’ term papers, while quantitative data were collected through a questionnaire. The survey and term papers showed divergent results regarding students’ understanding of SDGs. Although the survey indicated a restricted understanding, the term papers showed a more nuanced understanding. The quantitative findings also suggested that students had a systems perspective related to SDGs. Moreover, the term paper findings showed that students focused primarily on characters and settings while clarifying and elaborating their associations. Literary texts can be valuable tools to gain more insights into students’ understanding of SDGs, as they provide explicit and implicit instances in which essential plot elements construct rich and meaningful contexts.
Brevinasia, a New Genus of Edaphic Weevils with Description of 13 New Species from South Africa (Coleoptera: Curculionidae: Entiminae)
Authors: Borovec Roman , Meregalli Massimo
Published: June 2024

Brevinasia gen. n., a new genus of edaphic weevils with 14 species from the South African provinces of Western Cape, Eastern Cape, KwaZulu-Natal, and Limpopo, is described. The genus is described and illustrated, its taxonomic placement is discussed, and a key to the species is given. The specimens are usually associated with leaf litter in forest habitats and were generally sampled by sifting forest soil. Its type species, B. brevicollis (Voss, 1974), is redescribed, and 13 new species are described: B. albonigra sp. n. (type locality: Hills east of Stilbaai); B. bulirschi sp. n. (type locality: Marloth Nature Reserve); B. inconspicua sp. n. (type locality: Robinson’s Pass); B. janaki sp. n. (type locality: Hawequas); B. leleupi sp. n. (type locality: Humansdorp); B. limpopoensis sp. n. (type locality: Kruger National Park); B. litoralis sp. n. (type locality: West Gouritsmond); B. longiseta sp. n. (type locality: Grootvadersbosch Nature Reserve); B. maior sp. n. (type locality: Salem); B. micros sp. n. (type locality: Royal Natal National Park); B. nigritarsis sp. n. (type locality: Olifantsbos); B. rotundipennis sp. n. (type locality: Mkhambati Nature Reserve); B. wanati sp. n. (type locality: Lillyvlei Nature Reserve). COI sequences of B. brevicollis, B. nigritarsis, and B. wanati were deposited on GenBank.
Denitrification Mechanism of Heterotrophic Aerobic Denitrifying Pseudomonas hunanensis Strain DC-2 and Its Application in Aquaculture Wastewater
Authors: Sui Xinya , Wu Xingqiang , Xiao Bangding , Wang Chunbo , Tian Cuicui
Published: June 2024

A novel heterotrophic aerobic denitrifying Pseudomonas hunanensis strain DC-2 was screened from the sediments of Lake Dianchi and identified with high nitrification/denitrification ability. Within 30 h, the removal efficiency of ammonium-N and nitrate-N could reach 98.8% and 88.4%, respectively. The results of the single-factor experiments indicated that strain DC-2 exhibited excellent denitrification ability under the conditions of using sodium citrate as the nitrogen source, with an initial pH of 7, a C/N ratio of 10, and a temperature of 30 °C. Nitrogen balance experiments suggested that this strain removed N mainly via assimilation. Moreover, the N removal pathway was explored by genome and enzymatic assays, and a complex nitrogen metabolism pathway was established, including heterotrophic nitrification-aerobic denitrification (HN-AD), assimilatory reduction of nitrate (ANRA), and ammonia assimilation. Additionally, strain DC-2 was immobilized into particles for denitrification, demonstrating excellent efficacy in continuous total nitrogen removal (84.8% for TN). Hence, strain DC-2 demonstrated significant potential in treating real aquaculture wastewater.
Study on the Impact of Closed Coal Mines on Groundwater in the Panlong River Basin (Shangdong Province, China) Based on Sulfur and Oxygen Isotopes
Authors: Chen Hao , Chen Hongnian , Zhang Feng , Han Zhantao , Shi Huijian , Meng Jia , Feng Qiyan , Chen Di
Published: June 2024

To deeply investigate the impact of closed coal mines on groundwater sulfate contamination in the Panlong River basin, Zaozhuang, Shandong Province, China, the hydrochemical characteristics and controlling factors of groundwater were analyzed based on 64 surface water and groundwater samples. The sources of sulfate contamination were identified by sulfur and oxygen isotope analysis. The results indicate that the sulfate content in the pore groundwater exceeds the Standard for Groundwater Quality (China) Category III (250 mg/L), with a maximum content of 666.2 mg/L. Specifically, the exceedance rate of sulfate in pore water near the western boundary of the Taozao coal field is directly related to mine water. The exceedance rate of sulfate in karst groundwater is 28%, peaking at 1131 mg/L, and is mainly distributed outside the western boundary of the Taozao coalfield and near the Dingzhuang water source in the southeast of the coalfield, indicating a significant influence from high-sulfate mine water in the coal-bearing strata. The sulfur and oxygen isotope differences are significant between surface water, mine water, karst water, and pore water. Through Bayesian end-member analysis, it was determined that 40–83% of sulfate in the downstream pore water of the Taozao coal field originated from mine water, while 48–86% of the sulfate in the karst water originated from mine water, which greatly affects the groundwater in the western and southeastern parts of the Taozao coalfield. Therefore, measures should be taken as soon as possible to control the risk of sulfate pollution of neighboring groundwater, especially karst groundwater, by mine water from closed coal mines.
Classification of powdery mildew disease symptoms on sandalwood using machine learning techniques
Authors: Kumar A. Muthu , Antony J. Cruz , Soundararajan V.
Published: June 2024

Powdery mildew (Oidium sp.) is a fungal disease that infects plants by creating white powdery spots on plants and trees, reducing in yield. Powdery mildew is often influenced by changes in climatic conditions with cloud factors, humidity, and temperature playing major roles. This study focuses on building a Machine learning model to classify powdery mildew disease symptoms on sandalwood trees based on abiotic features like soil moisture, temperature, humidity, and cloud factors. Various machine learning algorithms such as Decision Tree, Logistic Regression, Random Forest, Support Vector Machine, and K-Nearest Neighbors were used on the dataset, and the model with the highest accuracy was chosen for building a powdery mildew prediction web application on the cloud platform. This web application helps in the prediction of the disease incidence/intensity and thereby enlightens the farming community to adopt appropriate management strategies.