bluuebunny/crossref_metadata_2025 huggingface dataset:
Schroth Physiotherapeutic Scoliosis-Specific Exercise (PSSE) Trials—Systematic Review of Methods and Recommendations for Future Research
Authors: Schreiber Sanja , Whibley Daniel , Somers Emily C
Published: May 2023

The Schroth method is a non-operative treatment for scoliosis and kyphosis, used standalone or as an adjunct to bracing. While supporting evidence for its effectiveness is emerging, methodologic standardization and rigor are equivocal. Thus, we aimed to systematically review methods of published Schroth physiotherapeutic scoliosis-specific exercise (PSSE) trials and provide guidance for future research. We searched six databases for randomized controlled trials (RCT) and non-randomized studies of interventions (NRSIs) investigating the effect of Schroth in children and adults with scoliosis or kyphosis. General characteristics, methodological approaches, treatment protocols, and outcomes reporting were analyzed. Risk of bias (RoB) was assessed using an adapted Cochrane RoB2 tool for RCTs and ROBINS-I for NRSI. Eligible studies (n = 7) were conducted in six countries and included patients with Scheuermann’s kyphosis (n = 1) and adolescent idiopathic scoliosis (n = 6). Though all seven studies used the term Schroth to describe their interventions, the Schroth method was used in four of seven studies, of which only one used Schroth classification, three used Schroth therapists, and none prospectively registered the study protocol. Overall, methodological rigor was suboptimal, potentially invalidating evidence synthesis. Authors should follow minimum standards for reporting, including prospectively registering detailed protocols; using appropriate exercise labeling, Schroth classification and certified therapists; naming and describing exercises per classification; and providing therapy dosages, prescription methods, and adherence.
Vitiligo: A Review of Aetiology, Pathogenesis, Treatment, and Psychosocial Impact
Authors: AL-smadi Khadeejeh , Imran Mohammad , Leite-Silva Vania R. , Mohammed Yousuf
Published: May 2023

Vitiligo is an acquired, chronic condition characterised by depigmentation of the epidermis or by destruction/loss of melanin. Skin cells (melanocytes) are responsible for producing melanin, the substance that gives pigmentation to the skin. This review aims to provide a comprehensive overview of the current state of knowledge about vitiligo. Although there is no specific ethnic group, gender, or skin type that is more prone to vitiligo than others, it can affect anyone. The most commonly prescribed treatments for vitiligo are systemic and topical phototherapy and immunomodulators such as corticosteroids, calcineurin inhibitors, and vitamin D analogues, in addition to cosmetics that can camouflage and improve the quality of life. Even though vitiligo is typically thought of as a cosmetic disorder, its effects on the physical and psychosocial health of sufferers cannot be ignored.
Graphene Supports for Metal Hydride and Energy Storage Applications
Authors: Comanescu Cezar
Published: May 2023

Energy production, distribution, and storage remain paramount to a variety of applications that reflect on our daily lives, from renewable energy systems, to electric vehicles and consumer electronics. Hydrogen is the sole element promising high energy, emission-free, and sustainable energy, and metal hydrides in particular have been investigated as promising materials for this purpose. While offering the highest gravimetric and volumetric hydrogen storage capacity of all known materials, metal hydrides are plagued by some serious deficiencies, such as poor kinetics, high activation energies that lead to high operating temperatures, poor recyclability, and/or stability, while environmental considerations related to the treatment of end-of-life fuel disposal are also of concern. A strategy to overcome these limitations is offered by nanotechnology, namely embedding reactive hydride compounds in nanosized supports such as graphene. Graphene is a 2D carbon material featuring unique mechanical, thermal, and electronic properties, which all recommend its use as the support for metal hydrides. With its high surface area, excellent mechanical strength, and thermal conductivity parameters, graphene can serve as the support for simple and complex hydrides as well as RHC (reactive hydride composites), producing nanocomposites with very attractive hydrogen storage properties.
Riparian Bird Occupancy in a Mountain Watershed in the Colorado Mineral Belt Appears Resilient to Climate-Change-Driven Increases in Metals and Rare Earth Elements in Water and Aquatic Macroinvertebrates
Authors: Watson Kelly E. , McKnight Diane M.
Published: May 2023

Acid rock drainage (ARD) impacts species composition in mountain streams. The potential impact for riparian birds experiencing elevated metal uptake by consumption of benthic invertebrates is concerning but not well studied. We investigated the influence of metal and rare earth element (REE) content in benthic invertebrates on the presence of breeding birds in an ARD-impacted watershed in Colorado, USA, where tree swallows in nest boxes had previously been found to have elevated metal concentrations at some sites. The concentrations of particular REEs in invertebrates were higher than those for cadmium or lead. Avian point counts indicated that most bird species detected were present at most sites, and that tree swallows were rarely found. Occupancy models showed that the availability of shrub or forest habitat was a good predictor for a few habitat-specialists, but metal and REE concentrations in water and invertebrates were not good predictors of avian presence. For other species, neither habitat type nor water quality were important predictors. Overall, this study indicates that the climate-change-driven increases in metals and REEs may not influence the presence of riparian birds in ARD-impacted streams.
On the Use of a Convolutional Block Attention Module in Deep Learning-Based Human Activity Recognition with Motion Sensors
Authors: Agac Sumeyye , Durmaz Incel Ozlem
Published: May 2023

Sensor-based human activity recognition with wearable devices has captured the attention of researchers in the last decade. The possibility of collecting large sets of data from various sensors in different body parts, automatic feature extraction, and aiming to recognize more complex activities have led to a rapid increase in the use of deep learning models in the field. More recently, using attention-based models for dynamically fine-tuning the model features and, in turn, improving the model performance has been investigated. However, the impact of using channel, spatial, or combined attention methods of the convolutional block attention module (CBAM) on the high-performing DeepConvLSTM model, a hybrid model proposed for sensor-based human activity recognition, has yet to be studied. Additionally, since wearables have limited resources, analysing the parameter requirements of attention modules can serve as an indicator for optimizing resource consumption. In this study, we explored the performance of CBAM on the DeepConvLSTM architecture both in terms of recognition performance and the number of additional parameters required by attention modules. In this direction, the effect of channel and spatial attention, individually and in combination, were examined. To evaluate the model performance, the Pamap2 dataset containing 12 daily activities and the Opportunity dataset with its 18 micro activities were utilized. The results showed that the performance for Opportunity increased from 0.74 to 0.77 in the macro f1-score owing to spatial attention, while for Pamap2, the performance increased from 0.95 to 0.96 owing to the channel attention applied to DeepConvLSTM with a negligible number of additional parameters. Moreover, when the activity-based results were analysed, it was observed that the attention mechanism increased the performance of the activities with the worst performance in the baseline model without attention. We present a comparison with related studies that use the same datasets and show that we could achieve higher scores on both datasets by combining CBAM and DeepConvLSTM.
Prognostic Factors for Cardiotoxicity among Children with Cancer: Definition, Causes, and Diagnosis with Omics Technologies
Authors: Antoniadi Kondylia , Thomaidis Nikolaos , Nihoyannopoulos Petros , Toutouzas Konstantinos , Gikas Evangelos , Kelaidi Charikleia , Polychronopoulou Sophia
Published: May 2023

Improvements in the treatment of childhood cancer have considerably enhanced survival rates over the last decades to over 80% as of today. However, this great achievement has been accompanied by the occurrence of several early and long-term treatment-related complications major of which is cardiotoxicity. This article reviews the contemporary definition of cardiotoxicity, older and newer chemotherapeutic agents that are mainly involved in cardiotoxicity, routine process diagnoses, and methods using omics technology for early and preventive diagnosis. Chemotherapeutic agents and radiation therapies have been implicated as a cause of cardiotoxicity. In response, the area of cardio-oncology has developed into a crucial element of oncologic patient care, committed to the early diagnosis and treatment of adverse cardiac events. However, routine diagnosis and the monitoring of cardiotoxicity rely on electrocardiography and echocardiography. For the early detection of cardiotoxicity, in recent years, major studies have been conducted using biomarkers such as troponin, N-terminal pro b-natriuretic peptide, etc. Despite the refinements in diagnostics, severe limitations still exist due to the increase in the above-mentioned biomarkers only after significant cardiac damage has occurred. Lately, the research has expanded by introducing new technologies and finding new markers using the omics approach. These new markers could be used not only for early detection but also for the early prevention of cardiotoxicity. Omics science, which includes genomics, transcriptomics, proteomics, and metabolomics, offers new opportunities for biomarker discovery in cardiotoxicity and may provide an understanding of the mechanisms of cardiotoxicity beyond traditional technologies.
Association between Childhood Onset Inflammatory Bowel Disease and Psychiatric Comorbidities in Adulthood
Authors: Sălcudean Andreea , Nan Andreea Georgiana , Bodo Cristina Raluca , Cosma Marius Cătălin , Strete Elena Gabriela , Lica Maria Melania
Published: May 2023

Inflammatory bowel disease (IBD), which includes Crohn’s disease, ulcerative colitis, and unspecified inflammatory bowel disease, is a chronic, unpredictable and immune-mediated condition of the gastrointestinal tract. In pediatric populations, the diagnosis of a chronic and debilitating pathology significantly reduces quality of life. Children diagnosed with IBD may cope with physical symptoms such as abdominal pain or fatigue, but mental and emotional well-being are also important for preventing and reducing the risk of developing psychiatric conditions. Short stature, growth delay and delayed puberty can contribute to poor body image and low self-esteem. Furthermore, treatment per se can alter psycho-social functioning due to the side effects of medication and surgical procedures such as colostomy. It is essential to acknowledge and treat early signs and symptoms of psychiatric distress in order to prevent the development of serious psychiatric disorders in adult life. The literature underlines the importance of incorporating psychological and mental health services as part of the management of inflammatory bowel disease. Diagnosing mental health problems in pediatric patients with IBD can improve their adherence to treatment and pathology course and, consequently, reduce long-term morbidity and mortality.
Arterial Stiffness as a Surrogate Marker of Cardiovascular Disease and Atherosclerosis in Patients with Arthritides and Connective Tissue Diseases: A Literature Review
Authors: Triantafyllias Konstantinos , Thiele Leif-Erik , Cavagna Lorenzo , Baraliakos Xenofon , Bertsias George , Schwarting Andreas
Published: May 2023

The increased cardiovascular (CV) risk among patients with autoimmune rheumatic diseases, such as arthritides and connective tissue diseases, has been extensively documented. From a pathophysiological standpoint, systemic inflammation in the context of the disease can lead to endothelial dysfunction, accelerated atherosclerosis, and structural changes in vessel walls, which, in turn, are associated with exaggerated CV morbidity and mortality. In addition to these abnormalities, the increased prevalence of traditional CV risk factors, such as obesity, dyslipidemia, arterial hypertension, and impaired glucose metabolism, can further worsen the status of and overall prognosis for CV in rheumatic patients. However, data on appropriate CV screening methods for patients with systemic autoimmune diseases are scarce, and traditional algorithms may lead to an underestimation of the true CV risk. The reason for this is that these calculations were developed for the general population and thus do not take into account the effect of the inflammatory burden, as well as other chronic-disease-associated CV risk factors. In recent years, different research groups, including ours, have examined the value of different CV surrogate markers, including carotid sonography, carotid–femoral pulse wave velocity, and flow-mediated arterial dilation, in the assessment of CV risk in healthy and rheumatic populations. In particular, arterial stiffness has been thoroughly examined in a number of studies, showing high diagnostic and predictive value for the occurrence of CV events. To this end, the present narrative review showcases a series of studies examining aortic and peripheral arterial stiffness as surrogates of all-cause CV disease and atherosclerosis in patients with rheumatoid and psoriatic arthritis, as well as in systemic lupus erythematosus and systemic sclerosis. Moreover, we discuss the associations of arterial stiffness with clinical, laboratory, and disease-specific parameters.
Rapid Whole-Body FDG PET/MRI in Oncology Patients: Utility of Combining Bayesian Penalised Likelihood PET Reconstruction and Abbreviated MRI
Authors: Inukai Junko Inoue , Nogami Munenobu , Tachibana Miho , Zeng Feibi , Nishitani Tatsuya , Kubo Kazuhiro , Murakami Takamichi
Published: May 2023

This study evaluated the diagnostic value of a rapid whole-body fluorodeoxyglucose (FDG) positron emission tomography (PET)/magnetic resonance imaging (MRI) approach, combining Bayesian penalised likelihood (BPL) PET with an optimised β value and abbreviated MRI (abb-MRI). The study compares the diagnostic performance of this approach with the standard PET/MRI that utilises ordered subsets expectation maximisation (OSEM) PET and standard MRI (std-MRI). The optimal β value was determined by evaluating the noise-equivalent count (NEC) phantom, background variability, contrast recovery, recovery coefficient, and visual scores (VS) for OSEM and BPL with β100–1000 at 2.5-, 1.5-, and 1.0-min scans, respectively. Clinical evaluations were conducted for NECpatient, NECdensity, liver signal-to-noise ratio (SNR), lesion maximum standardised uptake value, lesion signal-to-background ratio, lesion SNR, and VS in 49 patients. The diagnostic performance of BPL/abb-MRI was retrospectively assessed for lesion detection and differentiation in 156 patients using VS. The optimal β values were β600 for a 1.5-min scan and β700 for a 1.0-min scan. BPL/abb-MRI at these β values was equivalent to OSEM/std-MRI for a 2.5-min scan. By combining BPL with optimal β and abb-MRI, rapid whole-body PET/MRI could be achieved in ≤1.5 min per bed position, while maintaining comparable diagnostic performance to standard PET/MRI.
A Correlation Analysis between Arch Width and Molar Inclination Using Cone-Beam Computed Tomography Transverse Measurements: A Cross-Sectional Study
Authors: Albalawi Farraj , Alwakeel Reem , Alfuriji Samah , Alqahtani Nasser D. , Barakeh Rana M. , AlGhaihab Amjad , Alsaeed Suliman
Published: May 2023

A new era in 3-dimensional analysis has begun with the use of cone-beam computed tomography (CBCT) in orthodontics, which promises to provide a more thorough understanding of the craniofacial skeletal architecture. This study aimed to investigate the correlation between the transverse basal arches discrepancy and dental compensation by utilizing CBCT width analysis. An observational study was conducted to retrospectively review 88 CBCT scans of patients presented to dental clinics from 2014 to 2020 obtained from the Planmeca Romexis x-ray system at three centers. Dental compensation data across normal and narrow maxillae were analyzed and a Pearson correlation was used to find the relationship between molar inclination and width difference. Significant maxillary molar compensation differences were observed between the normal maxilla and narrow maxilla group, where the amount of dental compensation (164.73 ± 10.15) was higher in the narrow maxilla group. A significant negative correlation (r = −0.37) was observed between width difference and maxillary molar inclination. Maxillary molars were tipped buccally to compensate for the reduced maxillary arch width. These findings are important to determine the amount of needed maxillary expansion taking into account the buccal inclination while treating cases.
Protein Is an Intelligent Micelle
Authors: Roterman Irena , Konieczny Leszek
Published: May 2023

Interpreting biological phenomena at the molecular and cellular levels reveals the ways in which information that is specific to living organisms is processed: from the genetic record contained in a strand of DNA, to the translation process, and then to the construction of proteins that carry the flow and processing of information as well as reveal evolutionary mechanisms. The processing of a surprisingly small amount of information, i.e., in the range of 1 GB, contains the record of human DNA that is used in the construction of the highly complex system that is the human body. This shows that what is important is not the quantity of information but rather its skillful use—in other words, this facilitates proper processing. This paper describes the quantitative relations that characterize information during the successive steps of the “biological dogma”, illustrating a transition from the recording of information in a DNA strand to the production of proteins exhibiting a defined specificity. It is this that is encoded in the form of information and that determines the unique activity, i.e., the measure of a protein’s “intelligence”. In a situation of information deficit at the transformation stage of a primary protein structure to a tertiary or quaternary structure, a particular role is served by the environment as a supplier of complementary information, thus leading to the achievement of a structure that guarantees the fulfillment of a specified function. Its quantitative evaluation is possible via using a “fuzzy oil drop” (FOD), particularly with respect to its modified version. This can be achieved when taking into account the participation of an environment other than water in the construction of a specific 3D structure (FOD-M). The next step of information processing on the higher organizational level is the construction of the proteome, where the interrelationship between different functional tasks and organism requirements can be generally characterized by homeostasis. An open system that maintains the stability of all components can be achieved exclusively in a condition of automatic control that is realized by negative feedback loops. This suggests a hypothesis of proteome construction that is based on the system of negative feedback loops. The purpose of this paper is the analysis of information flow in organisms with a particular emphasis on the role of proteins in this process. This paper also presents a model introducing the component of changed conditions and its influence on the protein folding process—since the specificity of proteins is coded in their structure.
Critical Node Identification Method of Power Grid Based on the Improved Entropy Weight Method
Authors: Li Guanghuan , Zhang Lixia , Wang Yang , Kang Zhongjian
Published: May 2023

It is very important to accurately identify the critical nodes of the power grid for its safe and stable operation. In this paper, a method for identifying the critical nodes of the power grid based on the improved entropy weight method (IEWM) is proposed, and the IEWM corrects issues with the information overlap between evaluation indices and inconsistency between the entropy weight (EW) and entropy value (EV). First, considering the power grid topology and operating conditions, structural factor evaluation indices and state factor evaluation indices are established. On this basis, the IEWM is used to assign weights to nodes with different voltage levels, which strengthens the consideration of node voltage levels in the identification method of critical nodes and makes the results more accurate and effective. Simulation experiments of IEEE 30-bus and IEEE 118-bus systems verify the accuracy of the critical node identification method proposed in this paper.
Passivating Silicon Tunnel Diode for Perovskite on Silicon Nip Tandem Solar Cells
Authors: Marteau Baptiste , Desrues Thibaut , Rafhay Quentin , Kaminski Anne , Dubois Sébastien
Published: May 2023

Silicon solar cells featuring tunnel oxide passivated contacts (TOPCon) benefit from high efficiencies and low production costs and are on the verge of emerging as the new photovoltaic market mainstream technology. Their association with Perovskite cells in 2-terminal tandem devices enables efficiency breakthroughs while maintaining low fabrication costs. However, it requires the design of a highly specific interface to ensure both optical and electrical continuities between subcells. Here, we evaluated the potential of tunnel diodes as an alternative to ITO thin films, the reference for such applications. The PECV deposition of an nc-Si (n+) layer on top of a boron-doped poly-Si/SiOx passivated contact forms a diode with high doping levels (>2 × 1020 carrier·cm−3) and a sharp junction (<4 nm), thus reaching both ESAKI-like tunnel diode requirements. SIMS measurements of the nc-Si (n+) (deposited at 230 °C) reveal an H-rich layer. Interestingly, subsequent annealing at 400 °C led to a passivation improvement associated with the hydrogenation of the buried poly-Si/SiOx stack. Dark I–V measurements reveal similar characteristics for resistivity samples with or without the nc-Si (n+) layer, and modeling results confirm that highly conductive junctions are obtained. Finally, we produced 9 cm2 nip perovskite on silicon tandem devices, integrating a tunnel diode as the recombination junction between both subcells. Working devices with 18.8% average efficiency were obtained, with only 1.1%abs PCE losses compared with those of references. Thus, tunnel diodes appear to be an efficient, industrially suitable, and indium-free alternative to ITO thin films.
Dynamic Optimal Power Dispatch in Unbalanced Distribution Networks with Single-Phase Solar PV Units and BESS
Authors: Radosavljević Jordan , Ktena Aphrodite , Gajić Milena , Milovanović Miloš , Živić Jovana
Published: May 2023

Battery energy storage systems (BESSs) are a promising solution for increasing efficiency and flexibility of distribution networks (DNs) with a significant penetration level of photovoltaic (PV) systems. There are various issues related to the optimal operation of DNs with integrated PV systems and BESS that need to be addressed to maximize DN performance. This paper deals with day-ahead optimal active–reactive power dispatching in unbalanced DNs with integrated single-phase PV generation and BESS. The objectives are the minimization of cost for electricity, energy losses in the DN, and voltage unbalance at three-phase load buses by optimal management of active and reactive power flows. To solve this highly constrained non-linear optimization problem, a hybrid particle swarm optimization with sigmoid-based acceleration coefficients (PSOS) and a chaotic gravitational search algorithm (CGSA)called the PSOS-CGSA algorithm is proposed. A scenario-based approach encompassing the Monte Carlo simulation (MCS) method with a simultaneous backward reduction algorithm is used for the probabilistic assessment of the uncertainty of PV generation and power of loads. The effectiveness of the proposed procedure is evaluated through aseries test cases in a modified IEEE 13-bus feeder. The simulation results show that the proposed approach enables a large reduction in daily costs for electricity, as well as a reduction in expected daily energy losses in the DN by 22% compared to the base case without BESS while ensuring that the phase voltage unbalance rate (PVUR) is below the maximum limit of 2% for all three-phase buses in the DN.
A Fault Diagnosis Method Based on a Rainbow Recursive Plot and Deep Convolutional Neural Networks
Authors: Wang Xiaoyuan , Wang Xin , Li Tianyuan , Zhao Xiaoxiao
Published: May 2023

In previous deep learning-based fault diagnosis methods for rotating machinery, the method of directly feeding one-dimensional data into convolutional neural networks can lead to the loss of important fault features. To address the problem, a novel rotating machinery fault diagnosis model based on a rainbow recursive plot (RRP) is proposed. Our main innovation and contributions are: First, a RRP is proposed to convert the one-dimensional vibration signal from the rotating machinery into a two-dimensional color image, facilitating the capturing of more significant fault information. Second, a new CNN based on LeNet-5 is devised, which extracts a feature that describes substantial fault information from the converted two-dimensional color image, thus performing fault diagnosis recognition accurately. The public rolling bearing datasets and the online fault diagnosis platform are adopted to verify proposed method performance. Experiments on public datasets show that the proposed method can improve the accurate rate of recognition to 97.86%. More importantly, online experiment on the self-made fault diagnosis platform demonstrates that our approach achieves the best comprehensive performance in terms of recognition speed and accuracy compared to mainstream algorithms.
Assessment of Dispersed Oil Sorption in Oily Wastewater onto Hydrophobized/Oleophilized Autoclaved Aerated Concrete (AAC) Grains
Authors: Matsuno Akihiro , Kawamoto Ken
Published: May 2023

The discharge of untreated oily wastewater into the environment has serious impacts on human health, living nature, and ecosystems and leads to significant economic losses. Many engineering techniques have been proposed and applied to treat oily wastewater, but limited studies have investigated low-cost and effective techniques using by-products and waste/scrap materials from the construction industry. Materials to treat oily wastewater are needed not only to mitigate environmental pollution but also to promote the reuse and recycling of industrial by-products, especially in developing countries. This study, therefore, examined the sorption capacity of dispersed oil in wastewater (dispersed soybean oil in water; initial oil concentrations, Ci = 10–1000 mg/L; oil droplet size in water <2 μm) onto the hydrophobized/oleophilized autoclaved porous aerated concrete (AAC) grains made from waste scrap in Vietnam by using batch sorption tests in the laboratory. The AAC grains (sizes 0.106–0.25, 0.25–0.85, and 0.85–2.00 mm) were hydrophobized/oleophilized using oleic and stearic acids (coating concentrations of 1.0, 5.0, and 10 g/kg), and two sands (0.18–2.00 and 0.30–2.00 mm) were used as control samples. The results showed that the hydrophobized/oleophilized AAC grains had high sorption capacity for dispersed oil (i.e., high oil removal efficiency) compared to the control sands. Especially, the removal of AAC grains coated with stearic acid was >80% in high oil concentration solutions (Ci = 100 and 1000 mg/L), indicating that the hydrophobized/oleophilized AAC grains have high potential as useful adsorbents to trap dispersed oil in oily wastewater. Moreover, adsorption isotherms were drawn to examine the sorption characteristics of dispersed oil onto AAC grains. For all tested samples, the sorption of dispersed oil increased linearly with increasing equilibrium concentration. The commonly used Langmuir model, on the other hand, did not capture the measured isotherms.
The Response of Mesofauna to Nitrogen Deposition and Reduced Precipitation during Litter Decomposition
Authors: Zhou Shixing , Hu Junxi , Liu Xiong , Zou Xingcheng , Xiao Lin , Cao Dongyu , Tu Lihua , Cui Xinglei , Huang Congde
Published: May 2023

Soil mesofauna plays an important role in decomposing organic matter, recycling nutrients, and increasing nutrient availability. The effects of nitrogen (N) deposition and reduced precipitation on the litter-dwelling mesofaunal community and how this process affects litter decomposition remain poorly understood. Herein, a two-year simulated N deposition and throughfall reduction experiment was carried out in a natural evergreen broad-leaved subtropical forest to examine the effects of N deposition and reduced precipitation on soil mesofauna during litter decomposition. Four treatments were established: control (CK), N deposition (N), reduced precipitation (RP), and combined N deposition and reduced precipitation (N + RP). We collected and identified 19,782 individuals of mesofauna in litterbags during the whole experiment. Mites (Prostigmata, Mesostigmata, and Oribatida) and Collembola comprised almost 90% of the total number of individuals collected and dominated the soil mesofauna in our study. Our results revealed the negative effects of N deposition on the density of Oribatida mites and Collembola and the total density of soil mesofauna. Reduced precipitation significantly increased the density of Collembola and Oribatida mites and the total density of mesofauna and marginally significantly increased the density of Mesostigmata mites but decreased the diversity of mesofauna. The interaction effects of N deposition and reduced precipitation significantly affected the density of Prostigmata mites, Oribatida mites, Collembola, and the diversity of mesofauna. N deposition combined with reduced precipitation significantly inhibited litter decomposition, whereas no significant interaction effects were observed. Furthermore, correlation analysis indicated that litter mass loss was significantly positively correlated with the density of Prostigmata, Mesostigmata, and Oribatida, as well as the diversity of mesofauna. Overall, during the two-year decomposition process, our results suggest that N deposition and reduced precipitation interactively affected mesofaunal diversity and that N deposition adversely affected the mesofaunal community, while reduced precipitation increased the density of some groups but decreased mesofaunal diversity, consequently cascading on the decomposition of leaf litter.
The Action Potential of Antioxidant Grape Seed Proanthocyanidin as a Rumen Modifier to Mitigate Rumen Methanogenesis In Vitro
Authors: Zhang Fan , Zhang Zhenwei , Wen Ya , Wu Qichao , Zhang Luotong , Li Shengli , Yang HongJian
Published: May 2023

Grape seed proanthocyanidin (GSP) contains polyphenolic bioflavonoids ubiquitously found in the lignified portions of grape seeds from the winery and distillery industries, as an antioxidant. To explore its potential as a rumen modifier in methanogenesis inhibition, a 2 × 5 factorial experiment was conducted to determine the effect of GSP at 0, 15, 30, 60 and 120 mg/g of substrate on the rumen fermentation and methanogenesis of two representative total mixed rations (HY, a diet for high-yield (>2 kg/d) lactating cows, and LY, a diet for low-yield (<25 kg/d) lactating cows). By using the MIXED procedure, after a 48 h in vitro rumen incubation, increasing the GSP addition linearly decreased the in vitro dry matter digestion (IVDMD) and slowed down the rates of ration fermentation (RmaxS, g/h) and kinetic gas production (RmaxG, mL/h), with the decreases being more pronounced in the LY than HY group (p < 0.05). The GSP addition decreased hydrogen recovery (2Hrec) and altered the fermentation gas composition. The molar CH4 proportion was significantly reduced with both 60 and 120 mg GSP addition (p < 0.01). The total volatile fatty acid production was linearly decreased with the increasing GSP addition (p < 0.01). In addition, the GSP addition significantly decreased the ratio of methanogens to total bacteria (p < 0.05), and the reduction was notably greater in the HY than in the LY substrate (45.3% vs. 15.2% decrease), although the diversity of rumen methanogenic archaea was not affected in either the HY or the LY group. Bioinformatic analysis illustrated that the rumen archaeal community was predominated by a Methanobrevibacter genus (>72.5%), followed by Methanomassiliicoccus (>20.9%) and Methanosphaera (>1.0%). Methanobrevibacter could play an important role in methanogenesis in the presence of GSP, though it is usually considered to be the main hydrogenotrophic methanogen. In brief, the GSP addition presented high potential as a rumen modifier to mitigate methanogenesis by decreasing the ratio of methanogens to total bacteria. Methanobrevibacter could play an important role in methanogenesis in the presence of GSP. However, a relatively low administration level of GSP should be taken into consideration in order to obtain its inhibitory effect on CH4 emission, with a minimal negative effect on rumen digestion and fermentation.
Effect of Replacing Fish Meal Using Fermented Soybean Meal on Growth Performance, Intestine Bacterial Diversity, and Key Gene Expression of Largemouth Bass (Micropterus salmoides)
Authors: Weng Longfei , Wang Zhi , Zhuang Wei , Yang Tiezhu , Xu Xinxin , Liu Jinle , Liu Jixiang , Xu Zhengzhong , Chen Ruitao , Wang Qi , Wang Shilei , Cai Yafan , Ying Hanjie
Published: May 2023

In China, aquaculture costs have increased because of the increase in fish meal (FM) prices. Plant proteins, such as soybean meal, have the potential to replace FM partially and thus reduce the cost of aquatic feed. In this study, soybean meal (SBM) was fermented using compound microorganisms (lactic acid bacteria, yeast, and Bacillus). Fermented soybean meal (FSBM) replaced FM in the diet. The effect of replacing FM on largemouth bass was comprehensively evaluated at three levels: macro (growth performance), microbial (bacterial diversity and metabolic), and gene (key gene expression) levels. The results showed that FSBM increased the crude protein content by 7.45% and decreased the phytic acid concentration by 48.66% compared with original SBM. Compared with the control, the weight gain rate and feed conversion ratio showed no significant difference (p > 0.05) when the replacement amount of FM was less than 30%. Compared with the 50% FSBM treatment, the 10% and 30% treatments showed more steatosis in the liver slices. Although the replacement of FSBM with less than 30% did not have a significant (p < 0.05) negative impact on body weight, FSBM substitution adversely affected the height and width of the intestinal villi. The expression levels of Hepcidin-1, Hepcidin-2, TGF-β1, and IL-10 in 30% and 50% FSBM treatments were lower than those in the control, whereas the expression levels of SOD1 and SOD2 in 30% FSBM treatment were higher than those in the control group, and the expression level of SOD3a in 30% FSBM treatment was equal to the control. In addition, FSBM substitution could affect the composition of intestinal microorganisms and thus influence metabolic pathways, especially the biosynthesis of amino acids and plant secondary metabolites.
ChatGPT and Open-AI Models: A Preliminary Review
Authors: Roumeliotis Konstantinos I. , Tselikas Nikolaos D.
Published: May 2023

According to numerous reports, ChatGPT represents a significant breakthrough in the field of artificial intelligence. ChatGPT is a pre-trained AI model designed to engage in natural language conversations, utilizing sophisticated techniques from Natural Language Processing (NLP), Supervised Learning, and Reinforcement Learning to comprehend and generate text comparable to human-generated text. This article provides an overview of the training process and fundamental functionality of ChatGPT, accompanied by a preliminary review of the relevant literature. Notably, this article presents the first comprehensive literature review of this technology at the time of publication, aiming to aggregate all the available pertinent articles to facilitate further developments in the field. Ultimately, the authors aim to offer an appraisal of the technology’s potential implications on existing knowledge and technology, along with potential challenges that must be addressed.
Deep Learning-Based Symptomizing Cyber Threats Using Adaptive 5G Shared Slice Security Approaches
Authors: Majeed Abdul , Alnajim Abdullah M. , Waseem Athar , Khaliq Aleem , Naveed Aqdas , Habib Shabana , Islam Muhammad , Khan Sheroz
Published: May 2023

In fifth Generation (5G) networks, protection from internal attacks, external breaches, violation of confidentiality, and misuse of network vulnerabilities is a challenging task. Various approaches, especially deep-learning (DL) prototypes, have been adopted in order to counter such challenges. For 5G network defense, DL module are recommended here in order to symptomize suspicious NetFlow data. This module behaves as a virtual network function (VNF) and is placed along a 5G network. The DL module as a cyber threat-symptomizing (CTS) unit acts as a virtual security scanner along the 5G network data analytic function (NWDAF) to monitor the network data. When the data were found to be suspicious, causing network bottlenecks and let-downs of end-user services, they were labeled as “Anomalous”. For the best proactive and adaptive cyber defense system (PACDS), a logically organized modular approach has been followed to design the DL security module. In the application context, improvements have been made to input features dimension and computational complexity reduction with better response times and accuracy in outlier detection. Moreover, key performance indicators (KPIs) have been proposed for security module placement to secure interslice and intraslice communication channels from any internal or external attacks, also suggesting an adaptive defense mechanism and indicating its placement on a 5G network. Among the chosen DL models, the CNN model behaves as a stable model during behavior analysis in the results. The model classifies botnet-labeled data with 99.74% accuracy and higher precision.
Study on the Microflora Structure in a Litopenaeus vannamei–Sinonovacula constricta Tandem-Culture Model Based on High-Throughput Sequencing under Different Culture Densities
Authors: Zhao Chunpu , Xu Jilin , Xu Shanliang , Bao Gege , Wang Danli
Published: May 2023

In this study, we evaluated the intestinal contents of Pacific whiteleg shrimp (Litopenaeus vannamei), the visceral mass of razor clams (Sinonovacula constricta) and the water columns and the substrate sediments in different culture-density groups in a L. vannamei–S. constricta tandem-culture model by high-throughput sequencing of the 16S rRNA gene. The results show that the culture density affected the bacterial floral structure of the water columns, substrate sediment and razor-clam gut masses without making significant differences in the bacterial flora structure of the shrimp gut; the Shannon diversity indexes of the bacterial communities in the substrate sediment, shrimp gut and razor-clam gut masses were not significantly different among the density groups, and the Shannon diversity index of the bacterial communities in the water column was higher in the group with higher culture densities; at the phylum level, the dominant bacteria common to the shrimp guts, razor-clam visceral mass, water columns and substrate sediment were Proteobacteria and Bacteroidetes; Chloroflexi was the dominant bacterium specific to the substrate sediment; and Firmicutes was the dominant bacterium specific to the shrimp gut and razor-clam gut mass. We used national standards (GB 17378.4-2007, China) to evaluate the content of water-quality factors through the environmental factors and the genus-level correlation analysis of bacterial flora that follow: the dominant bacterium in the water column, uncultured_bacterium_f_Rhodobacteraceae, was negatively correlated with PO43−-P; the dominant bacteria in the substrate sediments, uncultured_bacterium_f_Anaerolineaceae and Woeseia, were significantly and negatively correlated with DO; and the dominant bacteria Lactococcus spp. in the razor-clam gut mass and the shrimp intestines were positively correlated with DO. These results show that culture density directly affects water-quality factors, which in turn affect the culture environment and the composition structure of the bacterial flora in a cultured organism.
Morphological Comparison of the Chesapeake Logperch Percina bimaculata with the Logperch Percina c. caprodes and Percina c. semifasciata in Pennsylvania
Authors: Stauffer Jay R. , Freedman Jonathan A. , Fischer Douglas P. , Criswell Robert W.
Published: May 2023

The Chesapeake logperch, Percina bimaculata (Halderman) has a disjunct distribution when compared to other species in the subgenus Percina. Members of this subgenus in Pennsylvania include Percina caprodes caprodes (Rafinesque), Percina caprodes semifasciata (DeKay), and P. bimaculata. Historically the Chesapeake logperch was known only from the Susquehanna River and Potomac River basins. Its range is now restricted to the Susquehanna River below Holtwood Dam and upper Chesapeake Bay. It has been extirpated from the Potomac River and the type locality near Columbia, PA. Attempts are being made to reintroduce it into tributaries of the Susquehanna River near Columbia, PA. We postulate that P. bimaculata diverged from a population of Percina caprodes semifasciata. A naked nape and the fact that both of these species do not occur above the fall line in Pennsylvania support such a relationship.
Multi-Scale Structural Insights into Enzymatically Hydrolyzed Lentil Starch Concentrates Prepared by In Vitro Method Using Different Types of Enzymes
Authors: Ren Namei , Hu Xinzhong , Ma Zhen
Published: May 2023

This study was undertaken to investigate the enzymatic hydrolysis of lentil starch concentrates from conventional cooked seeds (CCLSC) by the action of different types of enzymes, including pancreatin (PC-EHSC), heat-stable α-amylase (HS-EHSC), β-amylase (βA-EHSC), amyloglucosidase (AMG-EHSC), and multi-enzymes (βA-HS-AMG-EHSC); their multi-scale structural characteristics of the enzymatic hydrolysis products of lentil starch concentrates were compared. The morphological features distinguished among different samples. The Fourier-transform infrared spectroscopy and solid-state 13C CP/MAS NMR spectral features indicated the possible formation of a binary and ternary complex among amylose, protein and lipids. The X-ray diffraction results revealed that the V-type characteristic diffraction peaks were more obvious for samples including PC-EHSC and βA-EHSC, which was in line with their lowest polydispersity index (DPn). PC-EHSC and βA-EHSC also showed an increased peak intensity of the scattering maximum on the small-angle X-ray scattering spectra, whereas CCLSC exhibited an overall lower peak intensity within the studied q range of scattering. The highest XRD crystallinity and the lowest DPn value obtained for PC-EHSC indicated that the starch polymers modified by pancreatin could produce glucan chains with a comparatively homogenous Mw distribution that are readily recrystallized by hydrogen bonding through chain aggregation. Comparatively, the lowest relative crystallinity for HS-EHSC obtained from XRD suggested that thermostable α-amylolysis was unfavorable for the formation of starch structure with a higher degree of molecular order. This study could provide useful information for the needed research to obtain a deeper understanding of the impact of different amylolysis actions on the structural organization of starch hydrolysates and to provide a theoretical foundation for the development of fermentable enzymatically hydrolyzed starch with well-tailored physiological properties.
Preparation, Characterization and Antioxidant Activity of Glycosylated Whey Protein Isolate/Proanthocyanidin Compounds
Authors: Li Yaochang , Zhou Lian , Zhang Haizhi , Liu Gang , Qin Xinguang
Published: May 2023

A glycosylated protein/procyanidin complex was prepared by self-assembly of glycosylated whey protein isolate and proanthocyanidins (PCs). The complex was characterized through endogenous fluorescence spectroscopy, polyacrylamide gel electrophoresis, Fourier infrared spectroscopy, oil–water interfacial tension, and transmission electron microscopy. The results showed that the degree of protein aggregation could be regulated by controlling the added amount of procyanidin, and the main interaction force between glycosylated protein and PCs was hydrogen bonding or hydrophobic interaction. The optimal binding ratio of protein:PCs was 1:1 (w/w), and the solution pH was 6.0. The resulting glycosylated protein/PC compounds had a particle size of about 119 nm. They exhibited excellent antioxidant and free radical-scavenging abilities. Moreover, the thermal denaturation temperature rose to 113.33 °C. Confocal laser scanning microscopy (CLSM) images show that the emulsion maintains a thick interface layer and improves oxidation resistance with the addition of PCs, increasing the application potential in the functional food industry.
Assessment of Aspartame (E951) Occurrence in Selected Foods and Beverages on the German Market 2000–2022
Authors: Schorb Sydney , Gleiss Katharina , Wedekind Roland , Suonio Eero , Kull Ann-Kathrin , Kuntz Marcel , Walch Stephan G. , Lachenmeier Dirk W.
Published: May 2023

This study examines the occurrence of the artificial sweetener aspartame (E951) in foods and beverages sampled by food control authorities in Germany between 2000 and 2022. The dataset was obtained through the Consumer Information Act. Out of 53,116 samples analyzed, aspartame was present in 7331 samples (14%), of which 5703 samples (11%) in nine major food groups were further evaluated. The results showed that aspartame was most commonly found in powdered drink bases (84%), flavored milk drinks (78%), chewing gum (77%), and diet soft drinks (72%). In the solid food groups, the highest mean aspartame content was detected in chewing gum (1543 mg/kg, n = 241), followed by sports foods (1453 mg/kg, n = 125), fiber supplements (1248 mg/kg, n = 11), powdered drink bases (1068 mg/kg, n = 162), and candies (437 mg/kg, n = 339). Liquid products generally had the highest aspartame content in diet soft drinks (91 mg/L, n = 2021), followed by regular soft drinks (59 mg/L, n = 574), flavored milk drinks (48 mg/kg, n = 207), and mixed beer drinks (24 mg/L, n = 40). These results suggest that aspartame is commonly used in some foods and beverages in Germany. The levels of aspartame found were generally within the legal limits set by the European Union. These findings provide the first comprehensive overview of aspartame in the German food market and may be particularly useful in informing the forthcoming working groups of the WHO International Agency for Research on Cancer (IARC) and the WHO/FAO Joint Expert Committee on Food Additives (JECFA), which are in the process of evaluating the human health hazards and risks associated with the consumption of aspartame.