bluuebunny/crossref_metadata_2025 huggingface dataset:
Phenylalanine-Free Infant Formula in Patients with Phenylketonuria: A Retrospective Study
Authors: Yilmaz Nas Ozlem , Ashmore Catherine , Evans Sharon , Pinto Alex , Daly Anne , Yabancı Ayhan Nurcan , MacDonald Anita
Published: July 2024

The long-term efficacy and use of phenylalanine-free infant amino acid formula (PFIF) is understudied. This retrospective, longitudinal study evaluated PFIF (PKU Start: Vitaflo International) in children with phenylketonuria, collecting data on metabolic control, growth, dietary intake, and symptoms and the child’s experience with PFIF. Twenty-five children (12 males, 48%) with a median age of 3.6 years (2.0–6.2 years) were included. During 24 months follow-up, children maintained normal growth and satisfactory metabolic control. The protein intake from protein substitutes increased from 2.7 at 6 months to 2.8 g/kg/day at 24 months, while natural protein decreased from 0.6 to 0.4 g/kg/day. By 24 months, most children (n = 16, 64%) had stopped PFIF, while nine (36%) continued with a median intake of 450 mL/day (Q1:300 mL, Q3: 560 mL). Children who continued PFIF after 24 months of age had higher energy and fat intakes with higher weight/BMI z-scores compared with those who stopped earlier (p < 0.05). Constipation was reported in 44% of infants but improved with age. Initial difficulty with PFIF acceptance was reported in 20% of infants but also improved with time. Prolonged use of PFIF in pre-school children may contribute to poor feeding patterns and overweight; thus, replacing the majority of the protein equivalent provided by PFIF with a weaning protein substitute by 12 months and discontinuing PFIF before 2 years is recommended.
Real-World Use of Hybrid Closed-Loop Systems during Diabetes Camp: A Preliminary Study for Secure Configuration Strategies in Children and Adolescents
Authors: Olid-Cárdenas María José , Lendínez-Jurado Alfonso , Monroy-Rodríguez Gabriela , Gómez-Perea Ana , Cano-Ortiz Ana , Ariza-Jiménez Ana B. , García-Ruiz Ana , Jiménez-Cuenca Patricia , Picón-César María José , Leiva-Gea Isabel
Published: July 2024

The introduction of closed-loop systems in the pediatric population has been a revolution in the management and evolution of diabetes. However, there are not many published studies in situations in which the feeding, schedules, and activities of the children deviate from the routine for which the systems were programmed, as in the case of a summer camp for children and adolescents with diabetes, where the specific programming of this device is not well known. It was a single-center prospective preliminary study. A total of twenty-seven patients (mean age 11.9 ± 1.9 years, 40% male, duration of diabetes 6.44 ± 2.83 years) were included (twenty with Medtronic MiniMed 780G system and seven with Tandem Control-IQ). Glucometric variables and pump functionality were monitored during the 7-day camp and in the following 3 weeks. There was no decrease from the objective TIR 70% at any moment. The worst results in Time Below Range were at 72 h from starting the camp, and the worst results in Time Above Range were in the first 24 h, with a progressive improvement after that. No episodes of level 3 hypoglycemia or ketoacidosis occurred. The use of specific programming in two integrated systems, with complex blood glucose regulation algorithms and not-prepared-for situations with increased levels of physical activity or abrupt changes in feeding routines, did not result in an increased risk of level 3 hypoglycemia and ketoacidosis for our pediatric type 1 diabetes (T1D) patients, regardless of the closed-loop device.
Pre-or co-SARS-CoV-2 Infections Significantly Increase Severe Dengue Virus Disease Criteria: Implications for Clinicians
Authors: Bukhari Moeen Hamid , Annan Esther , Haque Ubydul , Arango Pedro , Falconar Andrew K. I. , Romero-Vivas Claudia M.
Published: July 2024

Few studies have investigated whether SARS-CoV-2 infections increase the incidence of dengue haemorrhagic fever/shock syndrome (DHF/DSS) and/or severe dengue (SD) in dengue virus (DENV)-infected patients. This study was performed on a site with high incidences of classical dengue, but relatively few DHF/DSS or SD cases as defined by the WHO 1997 or 2009 criteria, respectively. Clinical, haematological/biochemical, and viral diagnostic data were collected from febrile patients before, during, and after the COVID-19 epidemic to assess whether (a) DENV-infected patients with prior SARS-CoV-2 infections or (b) DENV-SARS-CoV-2-co-infected patients had increased incidences of SD/DHF/DSS using logistic regression and machine learning models. Higher numbers of DHF/DSS/SD occurred during the COVID-19 epidemic, particularly in males and 18–40-year-olds. Significantly increased symptoms in the DENV-SARS-CoV-2-co-infected cases were (a) haemoconcentration (p < 0.0009) and hypotension (p < 0.0005) (DHF/DSS and SD criteria), (b) thrombocytopenia and mucosal bleeding (DHF/DSS-criteria), (c) abdominal pain, persistent vomiting, mucosal bleeding, and thrombocytopenia (SD warning signs) and (d) dyspnoea, but without fluid accumulation. DENV-infected patients with prior SARS-CoV-2 infections had significantly increased incidences of thrombocytopenia (DHF/DSS-criteria) and/or abdominal pain and persistent vomiting and also thrombocytopenia (SD warning signs), but without significant haemoconcentration or hypotension. DENV-SARS-CoV-2 co-infections significantly increased the incidence of DHF/DSS/SD, while DENV-infected patients with prior SARS-CoV-2 infections displayed significantly increased incidences of thrombocytopenia (DHF/DSS-criteria) and three important SD warning signs, which are therefore very important for health workers/clinicians in assessing patients’ DHF/DSS/SD risk factors and planning their optimal therapies.
Role of Dapagliflozin in Ischemic Preconditioning in Patients with Symptomatic Coronary Artery Disease—DAPA-IP Study Protocol
Authors: Akamine Marco Alexander Valverde , Ferreira Soares Beatriz Moreira Ayub , Telles João Paulo Mota , Cicupira Rodrigues de Assis Arthur , Rodriguez Gabriela Nicole Valverde , Soares Paulo Rogério , Chalela William Azem , Scudeler Thiago Luis
Published: July 2024

Background: Ischemic preconditioning (IP) is a powerful cellular protection mechanism. The cellular pathways underlying IP are extremely complex and involve the participation of cell triggers, intracellular signaling pathways, and end-effectors. Experimental studies have shown that sodium-glucose transport protein 2 (SGLT2) inhibitors promote activation of 5′-adenosine monophosphate (AMP)-activated protein kinase (AMPK), the main regulator of adenosine 5′-triphosphate homeostasis and energy metabolism in the body. Despite its cardioprotective profile demonstrated by numerous clinical trials, the results of studies on the action of SGLT2 inhibitors in IP are scarce. This study will investigate the effects of dapagliflozin on IP in patients with coronary artery disease (CAD). Methods: The study will include 50 patients with multivessel CAD, ischemia documented by stress testing, and preserved left ventricular ejection fraction (LVEF). Patients will undergo four exercise tests, the first two with a time interval of 30 min between them after washout of cardiovascular or hypoglycemic medications and the last two after 7 days of dapagliflozin 10 mg once a day, also with a time interval of 30 min between them. Discussion: The role of SGLT2 inhibitors on IP is not clearly established. Several clinical trials have shown that SGLT2 inhibitors reduce the occurrence cardiovascular events, notably heart failure. However, such studies have not shown beneficial metabolic effects of SGLT2 inhibitors, such as reducing myocardial infarction or stroke. On the other hand, experimental studies with animal models have shown the beneficial effects of SGLT2 inhibitors on IP, a mechanism that confers cardiac and vascular protection from subsequent ischemia–reperfusion (IR) injury. This is the first clinical study to evaluate the effects of SGLT2 inhibitors on IP, which could result in an important advance in the treatment of patients with stable CAD.
Exogenous Sodium Nitroprusside Affects the Redox System of Wheat Roots Differentially Regulating the Activity of Antioxidant Enzymes under Short-Time Osmotic Stress
Authors: Lubyanova Alsu , Allagulova Chulpan
Published: July 2024

Nitric oxide (NO) is a multifunctional signalling molecule involved in the regulation of plant ontogenesis and adaptation to different adverse environmental factors, in particular to osmotic stress. Understanding NO-induced plant protection is important for the improvement of plant stress tolerance and crop productivity under global climate changes. The root system is crucial for plant survival in a changeable environment. Damages that it experiences under water deficit conditions during the initial developmental periods seriously affect the viability of the plants. This work was devoted to the comparative analysis of the pretreatment of wheat seedlings through the root system with NO donor sodium nitroprusside (SNP) for 24 h on various parameters of redox homeostasis under exposure to osmotic stress (PEG 6000, 12%) over 0.5–24 h. The active and exhausted solutions of SNP, termed as (SNP/+NO) and (SNP/−NO), respectively, were used in this work at a concentration of 2 × 10−4 M. Using biochemistry and light microscopy methods, it has been revealed that osmotic stress caused oxidative damages and the disruption of membrane cell structures in wheat roots. PEG exposure increased the production of superoxide (O2•−), hydrogen peroxide (H2O2), malondialdehyde (MDA), and the levels of electrolyte leakage (EL) and lipid peroxidation (LPO). Stress treatment enhanced the activities of superoxide dismutase (SOD), ascorbate peroxidase (APX), catalase (CAT), the excretion of proline, and the rate of cell death and inhibited their division. Pretreatment with (SNP/+NO) decreased PEG-induced root damages by differently regulating the antioxidant enzymes under stress conditions. Thus, (SNP/+NO) pretreatment led to SOD, APX, and CAT inhibition during the first 4 h of stress and stimulated their activity after 24 h of PEG exposure when compared to SNP-untreated or (SNP/−NO)-pretreated and stress-subjected plants. Osmotic stress triggered the intense excretion of proline by roots into the external medium. Pretreatment with (SNP/+NO) in contrast with (SNP/−NO) additionally increased stress-induced proline excretion. Our results indicate that NO is able to mitigate the destructive effects of osmotic stress on the roots of wheat seedlings. However, the mechanisms of NO protective action may be different at certain periods of stress exposure.
In Vitro Biotechnology for Conservation and Sustainable Use of Plant Genetic Resources
Authors: Tarraf Waed , De Carlo Anna
Published: July 2024

This Special Issue contains novel contributions related to the role and use of in vitro culture in the conservation and sustainable use of plant genetic resources [...]
Indigenous Medicinal Plants Used in the Management of Diabetes in Africa: 5 Years (2019–2024) in Perspective
Authors: Frimpong Ebenezer Kwabena , Thembane Nokukhanya , Hlatshwayo Sphamandla , Ngcobo Mlungisi , Gqaleni Nceba
Published: July 2024

(1) Background: The utilization of medicinal plants in the management of diabetes is of great importance to the health of the indigenous population on the African continent. The high cost of orthodox conventional medicines coupled with the perceived side effects encourages the high patronage of indigenous medicinal plants in the management of this metabolic disorder. We conducted a review on the indigenous African medicinal plants that could be useful in preclinical and clinical trials in the field of diabetes mellitus research. (2) Methods: Data were mined from research articles published and associated with the use of medicinal plants in the management of diabetes on the African continent (from January 2019 to March 2024). Literature from ethnobotanical studies on the African continent was searched from the Google Scholar, SCOPUS, Medline, Web of Science and PubMed databases. We employed the following keywords: “indigenous plants”, “diabetes in Africa” and “antidiabetic effect of medicinal plants”. (3) Results: A total of 52 medicinal plants belonging to 31 families were recorded in this study. Amaryllidaceae (14.28%), Fabaceae (9.52%) and Asteraceae (9.52%) were the most cited plant families. The frequently used indigenous medicinal plants on the African continent were Allium sativum L. (n = 6), Olea europaea L. (n = 6), Azadirachta indica A. Juss (n = 5), Allium cepa L. (n = 5) and Moringa oleifera Lam. (n = 5). The highly cited parts of the plant used in the management of diabetes were the leaves (45.55%), bark (14.44%) and bulbs (12.22%). The preferred methods of the preparation of herbal medicines were decoction (45.23%) and infusion (25%). Oral (52.32%) was the preferred route of the administration of herbal medicine on the African continent. (4) Conclusions: The data revealed some similarities in the way countries on the African continent manage diabetes. This interesting observation will assist in our quest towards obtaining a standardized protocol using indigenous medicinal plants to combat diseases on the African continent.
Cassava Breeding and Cultivation Challenges in Thailand: Past, Present, and Future Perspectives
Authors: Kongsil Pasajee , Ceballos Hernan , Siriwan Wanwisa , Vuttipongchaikij Supachai , Kittipadakul Piya , Phumichai Chalermpol , Wannarat Wannasiri , Kositratana Wichai , Vichukit Vichan , Sarobol Ed , Rojanaridpiched Chareinsak
Published: July 2024

Cassava (Manihot esculenta Crantz) was introduced to Southeast Asia in the 16th–17th centuries and has since flourished as an industrial crop. Since the 1980s, Thailand has emerged as the leading producer and exporter of cassava products. This growth coincided with the initiation of cassava breeding programs in collaboration with the International Center for Tropical Agriculture (CIAT), focusing on root yield and starch production. The success of Thai cassava breeding programs can be attributed to the incorporation of valuable genetic diversity from international germplasm resources to cross with the local landraces, which has become the genetic foundation of many Thai commercial varieties. Effective evaluation under diverse environmental conditions has led to the release of varieties with high yield stability. A notable success is the development of Kasetsart 50. However, extreme climate change poses significant challenges, including abiotic and biotic stresses that threaten cassava root yield and starch content, leading to a potential decline in starch-based industries. Future directions for cassava breeding must include hybrid development, marker-assisted recurrent breeding, and gene editing, along with high-throughput phenotyping and flower induction. These strategies are essential to achieve breeding objectives focused on drought tolerance and disease resistance, especially for CMD and CBSD.
A New Spectral Index for Monitoring Leaf Area Index of Winter Oilseed Rape (Brassica napus L.) under Different Coverage Methods and Nitrogen Treatments
Authors: Liu Hao , Xiang Youzhen , Chen Junying , Wu Yuxiao , Du Ruiqi , Tang Zijun , Yang Ning , Shi Hongzhao , Li Zhijun , Zhang Fucang
Published: July 2024

The leaf area index (LAI) is a crucial physiological indicator of crop growth. This paper introduces a new spectral index to overcome angle effects in estimating the LAI of crops. This study quantitatively analyzes the relationship between LAI and multi-angle hyperspectral reflectance from the canopy of winter oilseed rape (Brassica napus L.) at various growth stages, nitrogen application levels and coverage methods. The angular stability of 16 traditional vegetation indices (VIs) for monitoring the LAI was tested under nine view zenith angles (VZAs). These multi-angle VIs were input into machine learning models including support vector machine (SVM), eXtreme gradient boosting (XGBoost), and Random Forest (RF) to determine the optimal monitoring strategy. The results indicated that the back-scattering direction outperformed the vertical and forward-scattering direction in terms of monitoring the LAI. In the solar principal plane (SPP), EVI-1 and REP showed angle stability and high accuracy in monitoring the LAI. Nevertheless, this relationship was influenced by experimental conditions and growth stages. Compared with traditional VIs, the observation perspective insensitivity vegetation index (OPIVI) had the highest correlation with the LAI (r = 0.77–0.85). The linear regression model based on single-angle OPIVI was most accurate at −15° (R2 = 0.71). The LAI monitoring achieved using a multi-angle OPIVI-RF model had the higher accuracy, with an R2 of 0.77 and with a root mean square error (RMSE) of 0.38 cm2·cm−2. This study provides valuable insights for selecting VIs that overcome the angle effect in future drone and satellite applications.
Arbuscular Mycorrhizal Fungi Mediate the Acclimation of Rice to Submergence
Authors: Xu Yanggui , Tu Yuting , Feng Jiayi , Peng Zhiping , Peng Yiping , Huang Jichuan
Published: July 2024

Flooding is a critical factor that limits the establishment of a symbiosis between rice and arbuscular mycorrhizal fungi (AMF) in wetland ecosystems. The distribution of carbon resources in roots and the acclimation strategies of rice to flooding stress in the presence of AMF are poorly understood. We conducted a root box experiment, employing nylon sheets or nylon meshes to create separate fungal chambers that either prevented or allowed the roots and any molecules to pass through. We found that the mycorrhizal colonization rate and the expression of genes OsD14L and OsCERK1, which are involved in fungal perception during symbiosis, both increased in mycorrhizal rice roots following intermittent flooding compared to continuous flooding. Furthermore, AMF inoculation affected root morphological traits, facilitating both shallower and deeper soil exploration. Increased submergence intensity led to carbohydrate deprivation in roots, while high mycorrhizal colonization increased soil oxygen consumption and decreased the neutral lipid concentration in roots. However, mycorrhizal inoculation increased the rice photosynthesis rate and facilitated acclimation to submergence by mediating the expression of the genes OsCIPK15 and OsSUB1A to enhance rice shoot elongation and the sugar concentration in roots as a result of reduced competition for carbon between rice and AMF under different flooding conditions.
The Effect of the Overexpression or Addition of IGF1 and FGF2 in Human Chondrocytes Included in a Fibrin Matrix and Cultivated in a Dynamic Environment
Authors: Lara-Arias Jorge , Peña-Martínez Victor Manuel , Rodriguez-Corpus Luis Alejandro , Romero-Díaz Viktor J. , Álvarez-Lozano Eduardo , Martínez-Rodríguez Herminia G.
Published: July 2024

Hyaline cartilage is a highly specialized tissue. When injured, its repair capacity is low, which results in the massive destruction of the articular surface. Using tissue engineering and genetic engineering techniques, it is possible to provide a suitable microenvironment providing chondrocyte growth factors involved in the development of hyaline cartilage proteins, as well as cell proliferation and differentiation. Our aim was to stimulate the synthesis of an extracellular matrix via the chondrocytes included in a fibrin matrix through the addition or overexpression of IGF1 and/or FGF2, while maintaining a constant agitation of the culture medium. Collagen type II and glycosaminoglycans increased during the entire incubation time. In contrast, collagen type I decreased its expression under the same culture conditions, transfecting or supplementing growth factors to chondrocytes. However, chondrocytes that were not transfected or supplemented showed a general increase in the proteins analyzed in this study. The presence of IGF1 and FGF2 increased the protein synthesis of the hyaline cartilage, regardless of which one was the source of growth factors. Continuous agitation using the spinner flask allows for the adequate nutrition of chondrocytes included in the fibrin matrix. However, they require growth factors to up-regulate or down-regulate collagenous proteins.
The Rheology of Polyether Ether Ketone Concentrated Suspensions for Powder Molding and 3D Printing
Authors: Khashirova Svetlana Yu. , Slonov Azamat L. , Zhansitov Azamat A. , Musov Khasan V. , Tlupov Aslanbek F. , Khashirov Azamat A. , Mityukov Anton V. , Malkin Alexander Ya.
Published: July 2024

The main goal of the work was to use rheological methods for assessing the properties of a composition based on polyether ether ketone (PEEK) to determine the concentration limits of the polymer in the composition and select the optimal content of this composition for powder molding. The rheological properties of highly filled suspensions based on PEEK and paraffin, as well as in paraffin–polyethylene mixtures at various component ratios, were studied. These materials are designed for powder injection molding and 3D printing. Suspensions with a PEEK powder content above 50% are not capable of flow and, with increasing pressure, slide along the surface of the channel. For compositions with a higher content (60 and 70 vol.%) PEEK, independence of the storage modulus from frequency is observed, which is typical for solids and confirms the assignment of such suspensions to elastic–plastic media. The introduction of high-density polyethylene into the composition helps improve the technological properties of suspensions, expanding the range of fluidity, although it leads to an increase in viscosity. In suspensions with a mixed composition of the liquid phase, with increasing temperature, a decrease in the storage modulus is observed at 120 °C and, on the contrary, an increase at 180 °C. The latter may be a consequence of the evaporation of paraffin and the softening of PEEK due to the approach to the glass transition temperature of the polymer. Suspensions with 40% PEEK content have an optimal set of rheological properties for powder injection molding. A 3D printing filament was also obtained from a composition with 40% PEEK, which had good technological properties for FDM 3D printing. Products of satisfactory quality from suspensions with 50% PEEK can be produced by powder injection molding, but not by 3D printing. The selected compositions were used to obtain real PEEK products for practical applications.
Extraction and Structural Analysis of Sweet Potato Pectin and Characterization of Its Gel
Authors: Han Chunmeng , Zhao Xiangying , Yang Liping , Yao Mingjing , Zhang Jiaxiang , He Qiangzhi , Liu Jianjun , Liu Liping
Published: July 2024

Pectin is widely used in the food and pharmaceutical industries. However, data on sweet potato pectin extraction and structural property analyses are lacking. Here, for the high-value utilization of agricultural processing waste, sweet potato residue, a byproduct of sweet potato starch processing, was used as raw material. Ammonium oxalate, trisodium citrate, disodium hydrogen phosphate, hydrochloric acid and citric acid were used as extractants for the pectin constituents, among which ammonium oxalate had a high extraction rate of sweet potato pectin, low ash content and high molecular weight. Structural and gelation analyses were conducted on ammonium oxalate-extracted purified sweet potato pectin (AMOP). Analyses showed that AMOP is a rhamnogalacturonan-I-type pectin, with a molecular weight of 192.5 kg/mol. Chemical titration and infrared spectroscopy analysis confirmed that AMOP is a low-ester pectin, and scanning electron and atomic force microscopy demonstrated its linear molecular structure. Gelation studies have revealed that Ca2+ is the key factor for gel formation, and that sucrose significantly enhanced gel hardness. The highest AMOP gel hardness was observed at pH 4, with a Ca2+ concentration of 30 mg/g, pectin concentration of 2%, and sucrose concentration of 40%, reaching 128.87 g. These results provide a foundation for sweet potato pectin production and applications.
The Effect of the Incorporation of a 3D-Printed Titanium Framework on the Mechanical Properties CAD/CAM Denture Base Materials
Authors: Delgado-Ruiz Rafael , Brintouch Ido , Ali Aisha , Fang Yiwei , Romanos Georgios , Rafailovich Miriam
Published: July 2024

Background: Complete dentures should withstand occlusal forces and wear. However, over time, dentures can suffer fatigue and develop cracks, chipping, and fractures. Conventional methods for the fabrication of complete dentures involve injection molding, thermal curing, and the use of microwaves with polymethyl methacrylate (PMMA)-based materials. These methods have served well for many years. More recently, the incorporation of computer-aided design and computer-aided manufacturing (CAD/CAM) to fabricate complete dentures has been shown to enhance the dentures’ mechanical properties, including resistance to wear and impact strength. This study aims to investigate the mechanical properties and fracture types of CAD/CAM denture base materials (both milled and printed) as compared to a novel proprietary method that embeds a 3D-printed framework within PMMA-milled blocks. The null hypothesis is that incorporating a 3D-printed framework does not affect the mechanical properties of milled PMMA blocks. Methods: Three groups of bars were fabricated using CAD/CAM methods: printed (P), milled (M), and milled with a 3D-printed metallic framework reinforcement (M + F). A three-point bending test evaluated deformation, followed by an impact fracture test for fracture toughness. A descriptive fractographic analysis assessed the fracture characteristics. A statistical analysis using a paired t-test compared the differences between the groups. Results: The P group showed more elastic deformation than the M and M + F groups (p < 0.05). The M + F group achieved a higher fracture toughness as compared to the M and P groups (p < 0.05). Conclusions: Within the limitations of this experimental study, the null hypothesis can be rejected. Milled samples with an embedded 3D-printed titanium framework possess higher resistance to impact than milled samples without frameworks, and printed samples and milled samples with embedded 3d-printed titanium frameworks present increased flexural strength and lower elastic deformation as compared to milled samples without frameworks and printed samples.
Prototype Setup Hardware Choice for the DUCK System
Authors: Beznosko Dmitriy , Aseykin Valeriy , Dyshkant Alexander , Iakovlev Alexander , Krivosheev Oleg , Krivosheev Tatiana , Shiltsev Vladimir , Zhukov Valeriy
Published: July 2024

This article covers the overall design hardware choices for the prototyping activities for the DUCK (Detector system of Unusual Cosmic ray casKades). The primary goal of the DUCK system is to verify the existence of the unusual cosmic events reported by other collaborations and to look at the possibilities of adding innovations to the EAS (Extensive Atmospheric Shower) analysis methods of the EAS disk measurements at the observation level. Additionally, design and construction of the system provide educational experience to the students involved in the project and are developing the research capabilities of the university campus. The prototyping process has helped to choose between various design solutions in the process of optimizing of the individual detector components.
Comparative Evaluation of Two Analytical Functions for the Microdosimetry of Ions from 1H to 238U
Authors: Parisi Alessio , Furutani Keith M. , Sato Tatsuhiko , Beltran Chris J.
Published: July 2024

The analytical microdosimetric function (AMF) implemented in the Monte Carlo code PHITS is a unique tool that bridges the gap between macro- and microscopic scales of radiation interactions, enabling accurate microdosimetric calculations over macroscopic bodies. The original AMF was published in 2006, based on the results of track structure calculations. Recently, a newer version of the AMF was proposed, incorporating an improved description of the energy loss at the microscopic scale. This study compares the older and the newer AMFs in computing microdosimetric probability distributions, mean values, and the relative biological effectiveness (RBE). To this end, 16000 microdosimetric lineal energy probability density distributions were simulated with PHITS for ions from 1H to 238U over a broad energy range (1–1000 MeV/n). The newer AMF was found to offer superior performance, particularly for very heavy ions, producing results that align more closely with published in vitro clonogenic survival experiments. These findings suggest that the updated AMF provides a more reliable tool for microdosimetric calculations and RBE modeling, essential for ion radiation therapy and space radiation protection.
Anisometropic Patient and Current Bioelectrical Activity in the Masticatory and Cervical Muscles
Authors: Zieliński Grzegorz , Woźniak Anna , Ginszt Michał , Szkutnik Jacek , Marchili Nicola , Prost Marcin G. , Gawda Piotr , Rejdak Robert
Published: July 2024

(1) Background: This study aims to analyze the bioelectrical activity of the masticatory and cervical muscles in a subject with anisometropia. (2) Methods: A female patient aged 23 years with a best-corrected visual acuity of 1.0 in the right eye and 0.1 in the left eye, a refractive error of −2.25 Dsph in the right eye and +4.25 Dsph in the left eye, and astigmatism of −1.75 Dcyl axis 24° was examined. A comprehensive ophthalmological examination and the study of the bioelectrical activity of the muscles were carried out. During the ophthalmological examination, best-corrected visual acuity was determined, refractive error (spherical equivalent) was assessed, and additionally, retinal thickness, choroidal thickness, axial length, and intraocular pressure were measured. (3) Results: It was demonstrated that higher tension in the resting mandibular position and pain-free maximum unassisted opening were observed on the right side (myopia). Conversely, higher tension during maximum voluntary clenching in the intercuspal position and maximum voluntary clenching on dental cotton rolls in the intercuspal position was observed on the left side (hyperopia and astigmatism). (4) Conclusions: In the case study, muscle asymmetry was demonstrated, which is likely associated with anisometropia. This phenomenon requires further investigation.
BAFormer: A Novel Boundary-Aware Compensation UNet-like Transformer for High-Resolution Cropland Extraction
Authors: Li Zhiyong , Wang Youming , Tian Fa , Zhang Junbo , Chen Yijie , Li Kunhong
Published: July 2024

Utilizing deep learning for semantic segmentation of cropland from remote sensing imagery has become a crucial technique in land surveys. Cropland is highly heterogeneous and fragmented, and existing methods often suffer from inaccurate boundary segmentation. This paper introduces a UNet-like boundary-aware compensation model (BAFormer). Cropland boundaries typically exhibit rapid transformations in pixel values and texture features, often appearing as high-frequency features in remote sensing images. To enhance the recognition of these high-frequency features as represented by cropland boundaries, the proposed BAFormer integrates a Feature Adaptive Mixer (FAM) and develops a Depthwise Large Kernel Multi-Layer Perceptron model (DWLK-MLP) to enrich the global and local cropland boundaries features separately. Specifically, FAM enhances the boundary-aware method by adaptively acquiring high-frequency features through convolution and self-attention advantages, while DWLK-MLP further supplements boundary position information using a large receptive field. The efficacy of BAFormer has been evaluated on datasets including Vaihingen, Potsdam, LoveDA, and Mapcup. It demonstrates high performance, achieving mIoU scores of 84.5%, 87.3%, 53.5%, and 83.1% on these datasets, respectively. Notably, BAFormer-T (lightweight model) surpasses other lightweight models on the Vaihingen dataset with scores of 91.3% F1 and 84.1% mIoU.
Remote Sensing Thematic Product Generation for Sustainable Development of the Geological Environment
Authors: Li Jiabao , Ding Wei , Han Wei , Huang Xiaohui , Long Ao , Wang Yuewei
Published: July 2024

Remote sensing thematic data products are critical for assessing and analyzing geological environments, while efficient generation of thematic products is also highly significant for achieving corresponding sustainable development goals (SDGs). Currently, remote sensing thematic product generation has problems like low levels of automation and efficiency. Addressing these challenges is imperative for advancing sustainable development within the geological environment. This paper aims to address issues related to the generation of geological environment remote sensing thematic products, sorting through the overall process of remote sensing thematic product generation, exploring algorithm encapsulation, combination, and execution under technical methods for container and workflow, and relies on the Spark distributed processing architecture to achieve efficient thematic product generation supported by multiple geological environment data processing models. Finally, taking the three SDGs of SDG6, SDG11, and SDG15 as examples, we achieved the generation of a variety of thematic products such as the interpretation of water body distribution, extraction of urban informal settlements and distribution of water and soil erosion. Meanwhile, we comparatively analyzed the efficiency of thematic product generation on different processing architectures, and the experimental results further verified the feasibility and effectiveness of our proposed solution. This research provides a programme for the automated and intelligent generation of geological environment remote sensing thematic products and effectively assists the construction of sustainable development in the geological environment.
The Detectability of Post-Seismic Ground Displacement Using DInSAR and SBAS in Longwall Coal Mining: A Case Study in the Upper Silesian Coal Basin, Poland
Authors: Pawłuszek-Filipiak K. , Wielgocka N. , Rudziński Ł.
Published: July 2024

The Upper Silesian coal basin (USCB) in Poland faces significant ground deformation issues resulting from mining activities conducted without backfill, which can persist for years. These activities can cause damage to surface structures and phenomena such as induced seismicity. Ground deformations can be monitored using differential synthetic aperture radar interferometry (DInSAR). However, various DInSAR approaches have their own advantages and limitations, particularly regarding accuracy and atmospheric filtering. This is especially important for high-frequency displacement signals associated with seismic activity, which can be filtered out. Therefore, this study aims to assess the detectability of mining-induced seismic events using interferometric techniques, focusing on the USCB area. In this experiment, we tested two InSAR approaches: conventional DInSAR without atmospheric filtering and the small baseline subset (SBAS) approach, where the atmospheric phase screen was estimated and removed using high-pass and low-pass filtering. The results indicate that, in most cases, post-seismic ground displacement is not detectable using both methods. This suggests that mining-related seismic events typically do not cause significant post-seismic ground displacement. Out of the 17 selected seismic events, only two were clearly visible in the DInSAR estimated deformation, while for four other events, some displacement signals could neither be definitively confirmed nor negated. Conversely, only one seismic event was clearly detectable in the SBAS displacement time series, with no evidence of induced tremors found for the other events. DInSAR proved to be more effective in capturing displacement signals compared to SBAS. This could be attributed to the small magnitude of the tremors and, consequently, the small size of the seismic sources. Throughout the investigated period, all registered events had magnitudes less than 4.0. This highlights the challenge of identifying any significant influence of low-magnitude tremors on ground deformation, necessitating further investigations. Moreover, SBAS techniques tend to underestimate mining displacement rates, leading to smoothed deformation estimates, which may render post-seismic effects invisible for events with low magnitudes. However, after an in-depth analysis of the 17 seismic events in the USCB, DInSAR was found to be more effective in capturing displacement signals compared to SBAS. This indicates the need for significant caution when applying atmospheric filtering to high-frequency displacement signals.
An Efficient Sparse Recovery STAP Algorithm for Airborne Bistatic Radars Based on Atomic Selection under the Bayesian Framework
Authors: Liu Kun , Wang Tong , Huang Weijun
Published: July 2024

The traditional sparse recovery (SR) space-time adaptive processing (STAP) algorithms are greatly affected by grid mismatch, leading to poor performance in airborne bistatic radar clutter suppression. In order to address this issue, this paper proposes an SR STAP algorithm for airborne bistatic radars based on atomic selection under the Bayesian framework. This method adopts the idea of atomic selection for the process of Bayesian inference, continuously evaluating the contribution of atoms to the likelihood function to add or remove atoms, and then using the selected atoms to estimate the clutter support subspace and perform sparse recovery in the clutter support subspace. Due to the inherent sparsity of clutter signals, performing sparse recovery in the clutter support subspace avoids using a massive number of atoms from an overcomplete space-time dictionary, thereby greatly improving computational efficiency. In airborne bistatic radar scenarios where significant grid mismatch exists, this method can mitigate the performance degradation caused by grid mismatch by encrypting grid points. Since the sparse recovery is performed in the clutter support subspace, encrypting grid points does not lead to excessive computational burden. Additionally, this method integrates out the noise term under a new hierarchical Bayesian model, preventing the adverse effects caused by inaccurate noise power estimation during iterations in the traditional SR STAP algorithms, further enhancing its performance. Our simulation results demonstrate the high efficiency and superior clutter suppression performance and target detection performance of this method.
Navigating Digital Challenges for SMEs: A Two-Tier Approach to Risks Mitigation and Sustainability
Authors: Telukdarie Arnesh , Dube Thabile , Munsamy Megashnee , Murulane Khuliso , Mongwe Regionald
Published: July 2024

The global significance of SMEs has traditionally been recognized as a key driver of economic growth and sustainability. The emergence of digital technologies and Information and Communication Technology for Development (ICT4D) holds significant potential to further enhance this impact. However, SMEs in developing countries have faced challenges in adopting sustainable, resource-intensive digital systems. Factors such as limited skills, financial constraints, and the alignment of suitable solutions hinder this adoption. To address these challenges and promote sustainable digital transformation, this study proposes a two-tier approach. The first prong employs Natural Language Processing (NLP) techniques, including Word2Vec, for global analysis and digital systems identification. The second prong involves a country-specific analysis of SMEs’ digital requirements. This two-tier analysis aims to uncover the actual digital needs of SMEs while shedding light on high-intensity global SME activities that, if integrated through ICT4D, could effectively address the risks and challenges SMEs face in adopting, implementing, and maintaining digital systems. In addition, the study develops systems required by SMEs to optimize their business processes and production, thereby promoting their growth and sustainability in the digital era. The results of this study demonstrate the effectiveness of these proposed methods in addressing digital challenges for SMEs and fostering sustainable development.
Giving Wings to Sustainability: Brazil Needs to Consider Bats as Suppressors of Agricultural Pests and Tropical Disease Vectors
Authors: Carvalho William D. , Lourenço Elizabete C. , Luz Júlia L. , Xavier Bruna S. , Yantén Angélica V. , Costa Luciana M.
Published: July 2024

Insect-eating bats play a crucial role in agriculture and public health by suppressing populations of agricultural pests and disease vectors. These ecosystem services promoted by insect-eating bats are essential in a world that seeks sustainability in agricultural production and the management of urban areas. Despite Brazil’s status as one of the largest agricultural producers globally, research using insect-eating bats for pest control is lacking. This review underscores the importance of filling this knowledge gap and provides guidelines for future research. Bats exhibit diverse feeding habits and consume significant quantities of insects, including agricultural pests. While studies in the USA and Europe have highlighted insect-eating bats’ role in reducing agricultural losses, research in Brazil is limited. Challenges include the need for more advanced diet analysis techniques, such as DNA metabarcoding, and understanding bat habitat use in agricultural and urban landscapes. Research on natural and artificial roosts’ effectiveness and population dynamics is also essential. Integrating bat conservation into agricultural sustainability requires investment in technological methods, valuation of ecosystem services, population monitoring, habitat use studies and environmental education. Financial incentives and collaboration between sectors are crucial for advancing research and implementing bat-friendly practices in agriculture, ultimately enhancing biodiversity conservation and production sustainability in Brazil.
Spatiotemporal Dynamic Multi-Hop Network for Traffic Flow Forecasting
Authors: Chai Wenguang , Luo Qingfeng , Lin Zhizhe , Yan Jingwen , Zhou Jinglin , Zhou Teng
Published: July 2024

Accurate traffic flow forecasting is vital for intelligent transportation systems, especially with urbanization worsening traffic congestion, which affects daily life, economic growth, and the environment. Precise forecasts aid in managing and optimizing transportation systems, reducing congestion, and improving air quality by cutting emissions. However, predicting outcomes is difficult due to intricate spatial relationships, nonlinear temporal patterns, and the challenges associated with long-term forecasting. Current research often uses static graph structures, overlooking dynamic and long-range dependencies. To tackle these issues, we introduce the spatiotemporal dynamic multi-hop network (ST-DMN), a Seq2Seq framework. This model incorporates spatiotemporal convolutional blocks (ST-Blocks) with residual connections in the encoder to condense historical traffic data into a fixed-dimensional vector. A dynamic graph represents time-varying inter-segment relationships, and multi-hop operation in the encoder’s spatial convolutional layer and the decoder’s diffusion multi-hop graph convolutional gated recurrent units (DMGCGRUs) capture long-range dependencies. Experiments on two real-world datasets METR-LA and PEMS-BAY show that ST-DMN surpasses existing models in three metrics.
Digital Twin Technology in the Gas Industry: A Comparative Simulation Study
Authors: Yun Jaeseok , Kim Sungyeon , Kim Jinmin
Published: July 2024

Continuous innovation is essential in the urban gas industry to achieve the stability of energy supply and sustainability. The continuous increase in the global demand for energy indicates that the urban gas industry plays a crucial role in terms of stability, the economy, and the environmental friendliness of the energy supply. However, price volatility, supply chain complexity, and strengthened environmental regulations are certain challenges faced by this industry. In this study, we intend to overcome these challenges by elucidating the application of digital twin technology and by improving the performance of the prediction models in the gas industry. The real-time data and simulation-based predictions of pressure fluctuations were integrated in terms of pressure control equipment. We determined the contribution of this data integration to enhancing the operational efficiency, safety, and sustainable development in the gas industry. The summary of the results highlights the superior predictive performance of the autoregressive integrated moving average (ARIMA) model. It exhibited the best performance across all evaluation indices—mean absolute percentage error (MAPE), root mean square error (RMSE), and the coefficient of determination (R2)—when compared with the raw data. Specifically, the ARIMA model demonstrated the lowest RMSE value of 0.01575, the lowest MAPE value of 0.00609, and the highest R2 value of 0.94993 among the models evaluated. This indicates that the ARIMA model outperformed the other models in accurately predicting the outcomes. These findings validate that the integration of digital twin technology and prediction models can innovatively improve the maintenance strategy, operational efficiency, and risk prediction in the gas industry. Predictive maintenance models can help prevent significant industrial risks, such as gas leak accidents. Moreover, the integration of digital twin technology and predictive maintenance models can significantly enhance the safety and sustainability in the gas industry. The proposed innovative method of implementing digital twin technology and improved prediction models lays a theoretical foundation for sustainable development that can be applied to other industries with high energy consumption.
Navigating Sustainability and Inclusivity: Women-Led Community-Based Businesses in Post-Disaster Recovery
Authors: Matsumoto Aimi , Ishiwatari Mikio
Published: July 2024

Community-based businesses have emerged as a means of addressing socio-economic challenges in the aftermath of disasters. This study investigates the contribution of women-led community-based businesses to recovery and their long-term sustainability. It draws upon case studies in the Tohoku region of Japan and Banda Aceh, Indonesia, areas impacted by major earthquakes and tsunamis over a decade ago. Qualitative data were collected through semi-structured interviews. The findings reveal that the community-based businesses surveyed had evolved from mere “reconstruction goods” by maintaining sustained commitment and developing products. Enhancing organizational credibility through quality improvement efforts was crucial for securing long-term contracts with private companies, a key factor for business continuity. However, prioritizing sustainability often came at the cost of diminished community inclusivity, as differences in skill levels and misaligned values among participants led to departures. This study highlights the challenges in balancing business longevity with maintaining businesses’ role as spaces for social interaction and community rebuilding.