bluuebunny/crossref_metadata_2025 huggingface dataset:
Have I Been Touched? Subjective and Objective Aspects of Tactile Awareness
Authors: Cirillo Emanuele , Zavattaro Claudio , Gammeri Roberto , Serra Hilary , Ricci Raffaella , Berti Anna
Published: June 2024

Somatosensory tactile experience is a key aspect of our interaction with the environment. It is involved in object manipulation, in the planning and control of actions and, in its affective components, in the relationships with other individuals. It is also a foundational component of body awareness. An intriguing aspect of sensory perception in general and tactile perception in particular is the way in which stimulation comes to consciousness. Indeed, although being aware of something seems a rather self-evident and monolithic aspect of our mental states, sensory awareness may be in fact modulated by many different processes that impact on the mere stimulation of the skin, including the way in which we perceive our bodies as belonging to us. In this review, we first took into consideration the pathological conditions of absence of phenomenal experience of touch, in the presence of implicit processing, as initial models for understanding the neural bases of conscious tactile experience. Subsequently, we discussed cases of tactile illusions both in normal subjects and in brain-damaged patients which help to understand which high order processes impact tactile awareness. Finally, we discussed the observations reported in the review in light of some influential models of touch and body representation.
Bone Management in Patients with Prostate Cancer: FRAX Combined with Bone Mineral Density Can Prevent Unnecessary Treatment
Authors: Kawahara Takashi , Miyoshi Yasuhide , Uemura Koichi , Teranishi Jun-ichi , Ito Yusuke , Ito Hiroki , Makiyama Kazuhide , Uemura Hiroji
Published: June 2024

INTRODUCTION AND OBJECTIVES:
Osteoporosis is a common consequence of androgen deprivation therapy (ADT) for prostate cancer. Up to 20% of men on ADT have suffered from fracture within 5 years. The WHO Fracture Risk Assessment Tool (FRAX) has been utilized to predict the 10-year probability of major osteoporotic and hip fracture. However, no large studies assessing the utility of FRAX with versus without dual-energy X-ray absorptiometry (DEXA) in prostate cancer patients have been performed. We validated the usefulness of FRAX combined with DEXA in men with prostate cancer.

METHODS:
FRAX was done in a total of 1,220 prostate cancer patients including those who underwent brachytherapy (n=547), radical prostatectomy (n=200), external beam radiation therapy (n=264), hormonal therapy only (n=187), and definitive treatment along with hormonal therapy (n=645) in Yokohama City University Hospital. Of these, 109 patients received DEXA.

RESULTS:
In men without receiving DEXA, the median (mean ± SD) risks for major osteoporotic and hip fracture were 8.5% (9.3 ± 4.8) and 3.2% (4.2 ± 3.9), respectively. One hundred sixteen (9.5%) and 634 (52.0%) of these patients had the major osteoporotic risk of more than 15% and hip fracture risk of more than 3%, respectively. In contrast, in men with DEXA, the median (mean ± SD) risks for major osteoporotic and hip fracture were 5.3% (5.4 ± 2.1) and 0.85% (1.3 ± 1.2), respectively. Two (0.2%) and 4 (8.0%) of these patients had the major osteoporotic risk of more than 15% and hip fracture risk of more than 3%, respectively [Table1]. In the same cohort who received DEXA, the risks for major osteoporotic (p < 0.001) and hip (p < 0.001) fracture were significantly lower in men with DEXA than in those without DEXA.

CONCLUSIONS:
Our results suggest that FRAX combined with DEXA might prevent unnecessary osteoporosis medication in prostate cancer patients.
UV-A Supplementation in Plant Factory with Artificial Lighting Improves Growth, Photosynthesis, and Phytonutrients in Kale
Authors: Sonjaroon Weerasin , Tepkaew Teerapat , Kupia Manop , Tongkok Pattama , Boonkorkaew Patchareeya , Thussagunpanit Jutiporn
Published: June 2024

UV-A (315–400 nm) is a component of solar radiation impacting plant physiology. Consequently, the impact was investigated of UV-A supplementation on various aspects of kale cultivation in a plant factory with artificial lighting. Three UV-A intensity treatments (5, 10, or 15 W/m2) were applied to kale plants for 5 days before harvesting. The results revealed that 5 or 10 W/m2 UV-A supplementation provided significant advantages for kale growth. The fresh weight of the kale shoots increased by over 35–50% after UV-A exposure. In particular, the 10 W/m2 UV-A exposure significantly improved the photosynthetic rate, water use efficiency and quantum efficiency of photosystem II (Y(II)). In addition, the treatment with UV-A positively impacted changes in leaf spectral indices, resulting in decreases in the simple ratio index (SR), the nor-malized phaeophytinization index (NPQI), and the normalized difference red edge index (NDRE). Furthermore, the phytonutrients in kale (vitamin C, soluble protein, and total phenolics) were enhanced using the 10 W/m2 UV-A treatment. One notable outcome was the consistent reduction in nitrate contents across all UV-A treatment intensities. Therefore, supplementing kale cultiva-tion with UV-A radiation was a valuable strategy for enhancing kale yield and quality in plant factory production.
Central Difference Variational Filtering Based on Conjugate Gradient Method for Distributed Imaging Application
Authors: Ye Wen , Zhang Fubo , Chen Hongmei
Published: June 2024

Airborne distributed position and orientation system (ADPOS), which integrates multi-inertia measurement units(IMUs), data-processing computer and Global Navigation Satellite System (GNSS), serves as a key sensor in new higher-resolution airborne remote sensing, such as array SAR, multinode imaging loads and so on. ADPOS can provide multinode high accuracy spatio-temporal reference information to realize multinode motion compensation with the various state estimation methods such as Central Difference Kalman Filtering (CDKF), modifed CDKF. However, these methods focus on noise optimization based on known nonlinear models and its linear minimum variance estimation criterion, which cannot gain better estimation performance for high-dimensional nonlinear systems. For this reason, the variational optimization process based on conjugate gradient algorithm is proposed for the estimation of filtering update step, which is more efficient than linear minimum variance estimation criterion. Therefore, aiming at ADPOS with high-dimensional and nonlinearity, Central Difference Variational Filtering (CDVF) using variational optimization based on conjugate gradient algorithm for mean correction in the filtering update stage is devoted to advancing the estimation accuracy of multinode motion parameters. A real ADPOS flight test has been conducted, the experimental results show that the accuracy of the slave motion parameters has a distinct progress than the up to date CDKF, and the compensation performance is distinct.
Effects of biomaterials derived from germinated hemp seeds for stressed hair stem cells and immune cells
Authors: Kim Donghyun , Kim Namsoo Peter , Kim Boyong
Published: June 2024

Androgenetic alopecia is a genetic disorder caused by an excessive response to androgens. This alopecia is the most common cause of progressive hair loss in men and causes low self-esteem in patients. In this study we used various methods, including quantitative PCR, flow cytometry, ELISA, and immunocytochemistry, to evaluate the biological effects of germinated hemp seeds extract and exosomes derived from calli of germinated hemp seeds. This research reveals pre-ventive functions of two biomaterials (GE2000: 2000 ug/mL germinated hemp seeds extract; E40: 40 ng/mL exosomes derived from calli of germinated hemp seeds) for androgenetic alopecia through three biochemical categories: genetic modulation in hair follicle dermal papilla stem cells (HFDPSCs), cellular differentiation, and modulation of immune systems. Despite exposure to dihydrotestosterone (DT), two materials upregulated alopecia preventing genes including Wnt, β-catenin, and TCF in HFDPSCs. Conversely, alopecia activating genes (STAT1, 5α-reductase type 1, and IL-15R) were suppressed. Moreover, two materials suppressed alopecia genes (NKG2DL, IL2-Rβ, JAK1, and STAT1) in CD8+ T cells. Notably, E40 was effected more in-tensely in these biochemical categories than those of GE2000. Consequently, E40 and GE2000 ef-fectively prevented DT stress. Additionally, two materials activated mechanisms for hair for-mation through the biological activities of three categories.
The Impact of Plyometric Training on Agility, Speed, and Social Interaction in Children with Mild Intellectual Disability: A Special Olympics Framework Study
Authors: Stefanica Valentina , Joksimović Marko , Ceylan Halil İbrahim , Kontautienė Vytė , Pirvu Daniel
Published: June 2024

Aim: This study aimed to evaluate the effectiveness of a plyometric training program designed to enhance agility, speed, and social interaction among boys with mild intellectual disability (ID) aged 10-12, within the Special Olympics framework. Participants: Thirty-two boys (mean age = 10.69 ± 0.8 years; mean IQ = 61 ± 7) from three inclusive education centers participated in the study. Methods: The intervention consisted of a 10-week plyometric training program, conducted twice a week. Pre- and post-intervention assessments included the Reaction Time Test, 4-Corner Agility Test, 10-Meter Speed Run, 4x5 Meter Relay Test, and the Friendship Activity Scale (FAS). Results: The study found significant improvements across all measures. Reaction time decreased by 0.83 seconds (t = 7.44, p < 0.001), 4-corner agility improved by 0.77 seconds (t = 11.93, p < 0.001), 4x5 meter speed improved by 0.61 m/s (t = 17.37, p < 0.001), and 10-meter run speed improved by 1.55 m/s (t = -12.76, p < 0.001). Additionally, the FAS score increased by 0.81 points (t = 9.59, p < 0.001), indicating enhanced social interactions. Conclusion: The plyometric training program significantly improved agility, speed, and social interaction in children with mild ID, demonstrating the effectiveness of inclusive, adaptive physical education strategies within the Special Olympics framework.
Can Graph Machines Accurately Estimate 13C NMR Chemical Shifts of Benzenic Compounds?
Authors: Duprat François , Ploix Jean-Luc , Dreyfus Gérard
Published: June 2024

NMR spectroscopy, which is based on the phenomenon of nuclear magnetic resonance, has been widely popularized by its application in medical imaging under the name of MRI. In the organic laboratory, the 13C NMR spectrum of a newly synthetized compound remains an essential step in elucidating its structure. For the chemist, the interpretation of such a spectrum, which is a set of chemical shift values, is made easier if he has a tool capable of predicting with sufficient accuracy the carbon shift values from the structure he intends to prepare. As there are few open source methods for accurately estimating this property, we applied our graph machine approach to build models capable of predicting the chemical shifts of carbons. For this study, we have focused on benzene compounds building an optimized model derived from training a database of 10577 chemical shifts originating from 2026 structures which contain up to ten types of atoms other than carbon, namely H, O, N, S, P, Si and halogens. It provides a training root mean squared relative error (RMSRE) of 0.5 %, i.e. a root mean squared error (RMSE) of 0.6 ppm, and a mean absolute error (MAE) of 0.4 ppm for estimating the chemical shifts of the 10k carbons. The predictive capability of the graph machine model is also compared with that of three commercial software on a data set of 171 original benzenic structures (1012 chemical shifts). The graph machine model proves very efficient in predicting chemical shifts with an RMSE of 0.9 ppm, and compares favorably with the RMSEs of 3.4, 1.8 and 1.9 ppm computed with ChemDraw, ACD and MestReNova softwares respectively. Finally, a Docker-based tool is proposed to predict the carbon chemical shifts of benzenic compounds solely from their SMILES codes.
Sustainability and Dividends: Complements or Substitutes?
Authors: Krieger Kevin , Mauck Nathan
Published: June 2024

We examine the relation between environmental, social, and governance commitment levels (ESG) and firm dividend payer status. Given that larger and more profitable firms are positively associated with both payer status and ESG, it could be that ESG and dividends are complements. However, given that both dividends and ESG relate to firm spending decisions, it may be that the choice is “either/or” and that ESG and dividends are substitutes. We document a positive relation between ESG and dividend payer status in U.S. firms over the period 1991-2016. In particular we find that the proportion of dividend payers is roughly 13% higher for firms with positive ESG compared to those with negative ESG. Including ESG in the models used to predict payer status provides, on average, a nearly 26% improvement in relative forecast accuracy. Our results are robust to estimation techniques and the inclusion of variables known to be determinants of payer status.
The Challenge of a Recall Programme From a Community-Based Hepatitis C Screening Campaign: The Effectiveness in HCV Microelimination
Authors: Chien Cheng-Hung , Chou Tien -Shin , Chen Li-Wei , Lin Chih-Lang , Chang Jia-Jang , Liu Ching-Jung , Chen Shuo-Wei , Hu Ching-Chih , Chien Rong-Nan
Published: June 2024

Abstract:
Background: The optimal strategy for the microelimination of HCV within community settings remains ambiguous. We evaluated the percentage of participants who achieved linkage to care (LTC) following the conclusion of the screening campaign, and examined the diverse factors influencing LTC among these individuals. The effectiveness of recall intervention for the non-LTC population and its barriers were analyzed.

Methods:
We initiated an HCV patients recall program to identify the HCV participants who might not be treated after the HCV screening campaign. A program staff recalled HCV participants who lost to follow-up through the telephone from March 2019 to June 2019. They were informed of HCV treatment's importance, efficacy, availability, and safety.

Result:
Among 185 HCV-infected participants, 109 (58.9%) HCV-infected participants had obtained LTC. Compared with those who had LTC, those without LTC were older, lower education levels, were less aware of their HCV infection, less frequently lived in urban areas, and had less health insurance. At the end of the recall program, 125 (67.6 %) persons had liked to care. The proportion of LTC increased by 8.7 %. 119 persons had an HCV RNA test, and 82 (68.9%) had viremia. Of 82 patients with viremia, 78 (95.1%) received antiviral therapy. 76 (97.4 %) of them achieved a sustained virological response.

Conclusion:
After a community screening campaign, 59 % of participants with anti-HCV positive had LTC. The recall program can increase by 9 %. However, there were still 32% of HCV participants who couldn't be linked to care. Outreach care for non-LTC patients is a way worth trying to achieve micro-elimination of HCV in the rural community.
Phase I–IV Drug Trials on Hepatocellular Carcinoma in an Asian Population: A Systematic Review of Ten Years Studies
Authors: Raghav Alok , Jeong Goo Bo
Published: June 2024

Background: Despite advances in the treatment of hepatocellular carcinoma (HCC) over the last few decades, treatment opportunities for patients with HCC remain limited. HCC is the most common form of liver cancer, accounting for approximately 90% of all cases worldwide. Moreover, apart from the current pharmacological interventions, hepatic resection and liver transplantation are the mainstay curative approaches for patients with HCC.
Methods: This systematic review included phase I, II, III, and IV clinical trials (CTs) and randomized controlled trials (RCTs) on current treatments for patients with HCC in an Asian population (2013–2023). A total of 427 articles were screened, and 184 non-duplicate publications were identified. After screening titles and abstracts, 96 publications were excluded, and another 28 were excluded after full-text screening. The remaining 60 eligible RCTs/CTs were finally included.
Results: Sixty clinical trials fulfilled our inclusion criteria and screened 36 drugs as monotherapy or combination therapy for HCC. Most studies used sorafenib alone or in combination with any of the treatment regimens. Lenvatinib or atezolizumab with bevacizumab was used for HCC after initial sorafenib treatment. Eighteen studies compared the efficacy of sorafenib with that of other drugs, including lenvatinib, cabozantinib, tepotinib, tigatuzumab, linifanib, erlotinib, resminostat, brivanib, tislelizumab, selumetinib, and refametinib.
Conclusion: This study provides comprehensive insights into effective treatment interventions for HCC in Asian populations. The overall assessment indicated that sorafenib alone or in combination with atezolizumab and bevacizumab has been the first treatment choice in the past decade to achieve better outcomes in patients with HCC in an Asian population
First Data on Anthropic Debris Contamination in the Gastrointestinal Tract of Juvenile Scalloped Hammerhead Shark (Sphyrna lewini) in the Gulf of California
Authors: Malthaner Leony , Garcia Ximena , Ríos Mendoza Lorena Margarita , Rivera-Hernández José R. , Cruz Roberto , Amezcua Felipe
Published: June 2024

According to the International Union for Conservation of Nature Red List, the scalloped hammerhead (Sphyrna lewini) is a critically endangered species, primarily due to intense fishing and other anthropogenic effects such as pollution. Nowadays, plastic debris contamination is a subject of concern due to its extensive presence in the sea and the digestive tracts of many fish species. The possible effects of plastic debris as a vector of other pollutants are still unknown. We analyzed the digestive tract of hammerhead sharks to investigate the correlation between plastic and other anthropic debris contamination and feeding habits in the eastern region of the Gulf of California. A total of 58 specimens were analyzed from the coastal area, revealing a plastic occurrence frequency of 79.3%. Of these, 91.4% corresponded to fibers, and 8.6% to fragments. The composition of the polymers was primarily cellulose (64.4%). According to their diet, these organisms exhibit benthopelagic habits, feeding both in the water column and on the seabed. These results indicate a high level of contamination of anthropogenic cellulosic microfibers in the area. This changed according to the year, indicating that the anthropic debris ingestion is related to the discharges of human activities and their seasonality rather than to a selection process by the sharks. Although cellulosic microfibers are recognized as a biomaterial, they can harm marine species, posing an additional threat to this iconic shark.
Leveraging Gaussian Processes in Remote Sensing
Authors: Foley Emma
Published: June 2024

Power grid reliability is crucial to supporting critical infrastructure, but monitoring and maintenance activities are expensive and sometimes dangerous. Remote sensing enables real time data monitoring and collection related to environmental and industrial processes, like the power grid system. Monitoring the power grid successfully involves diverse sources of data including that inherent to the power operation and ambient atmospheric weather data. Detection methods can identify anomalies like arcing, and climate data in particular is becoming increasingly important in order to maintain power supply. Gaussian processes (GPs) are a well-established Bayesian method for analyzing data. However, the computational complexity of GPs limits their scalability. This is a challenge when dealing with remote sensing datasets, where acquiring a significant amount of data is common. Alternatively, traditional machine learning methods perform quickly and accurately, but lack the generalizability innate to GPs. The focus of this review is burgeoning research that leverages Gaussian processes and machine learning in remote sensing applications.
Back to the Metrics: Exploration of Distance Metrics in Anomaly Detection
Authors: Lin Yujing , Li Xiaoqiang
Published: June 2024

With increasing research focus on industrial anomaly detection, numerous methods have emerged in this domain. Notably, memory bank-based approaches, coupled with kNN distance metrics, have demonstrated remarkable performance in anomaly detection (AD) and anomaly segmentation (AS). However, upon examination of the Back to the Feature (BTF) method applied to the Mvtec-3D AD dataset, it was observed that while it exhibited exceptional segmentation performance, its detection performance was lacking. To address this discrepancy, this study base improves the implementation of BTF, especially the improvement of the anomaly score metric. It posits that different "clusters" necessitate distinct k values in kNN distance metrics. For simplify, this assumption is distilled into the proposition that AD and AS tasks impose differing requirements on the k value in kNN distance metrics. Consequently, the paper introduces the BTM method, which utilizes distinct distance metrics for AD and AS tasks. This innovative approach yields superior AD and AS performance (I-AUROC 93.0%, AURPO 96.9%, P-AUROC 99.5%), representing a substantial enhancement over the BTF method (I-AUROC 5.7% ↑, AURPO 0.5% ↑, P-AUROC 0.2% ↑).
Properties of Medium-Scale Traveling Ionospheric Disturbances Observed over Mexico During Quiet Solar Activity
Authors: Romero-Hernandez Esmeralda , Salinas-Samaniego Federico , Jonah Olusegun F. , Aguilar-Rodriguez Ernesto , Rodríguez-Martínez Mario , Picanço Giorgio A. S. , Denardini Clezio M. , Guerrero-Peña Carlos , Aguirre-Gutierrez Rogelio , Garcia-Castillo Flor Araceli , Ayala-Gomez Sandra A. , Perez-Tijerina Eduardo , Sergeeva Maria A. , Gonzalez-Esparza J. Americo
Published: June 2024

We present a statistical study of the physical properties of Medium Scale Traveling Ionospheric Disturbances (MSTIDs) registered over the Mexican territory during 2018 and 2019 (solar minimum). The analysis is based on Total Electron Content (TEC) approximations using data from the ground-based Global Navigation Satellite System (GNSS) receivers at different locations divided into three regions according to geomagnetic coordinates: North, Center, and South. The MSTIDs were classified into day and night events, and only geomagnetically quiet days were considered to reduce the solar influence. We explored fundamental aspects of the MSTIDs, such as differences between day and night events, occurrence patterns, and geographical differences. Our results show some similarities with the occurrence periods of gravity waves, exhibiting a high activity during summer and winter. For this period, however, most events occurred between 20:00 PM and 04:00 AM UT. Moreover, the disturbances’ energy was stronger (i.e., large amplitudes and power) around the sunset terminator for the three regions. This suggests that the density gradient generated when the sunlight falls benefits MSTIDs formation.
Experimental Study on the Importance of Interference in the Spreading Factor and Effects of Collisions for the LoRaWAN Radio Interface
Authors: Pires Luis Miguel , Martins José
Published: June 2024

The number of physical devices connected to the Internet such as vehicles, household appliances and other "things" has been steadily increasing in recent years, thus forming the basis for the Internet of Things (IoT). IoT ecosystem extends beyond country borders and application domains, combining thousands of versatile devices that differ in terms of their structures, capabilities, and available resources. It is therefore not surprising that the landscape of wireless communication technologies and the degree of IoT devices available today is excessively broad and diverse. Interference between networks leads to frame collisions and consequent packet loss. Frame collisions occur when two or more packets overlap in time and frequency and use the same LoRa parameters, i.e. the same spreading factor (SF), bandwidth (BW) and carrier frequency (CF). When most devices use the same configuration, collision probability is higher. The probability of frame collisions is also affected by traffic characteristics, particularly the periodicity of the transmission and the payload size. Larger payload sizes and more frequent transmissions accumulate with higher time on air (ToA) and channel occupancy [1]. Transmission powers and the location of the gateways also influences this situation. The aim of this experimental work is to verify the effects of collisions and interference in LoRaWAN, regarding the periodicity of transmissions and the payload sizes. The hardware used is an Arduino board programmed in C/C++, a LoRa Bee module operating at a frequency of 868 MHz and a LoRaWAN LG02 gateway. Different scenarios were tested in an outdoor environment, with Line of Sight and Non-Line of Sight, and different variables such as: SFs equal to 7, 9 and 12; distances of 20, 40 and 60 meters and different data sizes of 14, 32 and 51 bytes, over the same channel. The packets with different SF’s and different data sizes were transmitted in a (pseudo) random way, one after the other, overlapping different SFs in the same channel and testing this way (theoretical) orthogonality among them. By fixing the bandwidth in 125 kHz, and testing different SFs we intend to increase the probability of cause packet loss by applying to our connection a combination of emitted power/short distance that leaves an interference power received, strong enough [2] for the effect. We validate our conclusions by analyzing ToA according with RSSI and different data sizes, the RSSI for different SFs and different data sizes and finally the packet loss through the PDR-Packet Delivery Ratio for a better understanding of the reliability of packet transmission in our link.
Whey as an Optimal Substrate for the Development of Functional Products Enriched with Bioactive Peptides
Authors: Saubenova Margarita , Oleinikova Yelena , Rapoport Alexander , Maksimovich Sviatoslav , Yermekbay Zhanerke , Khamedova Elana
Published: June 2024

Milk serves as a crucial source of natural bioactive compounds essential for human nutrition and health. The gastrointestinal digestion of milk proteins releases various biologically active peptides that positively impact human health and enhance physiological performance. With the growing production of cheese, Greek yogurt, and other dairy products, the volume of unutilized acid whey is significantly increasing. Acid whey, containing almost all whey proteins and approximately one-quarter of casein, presents a valuable raw material for generating peptides with potential health benefits. These peptides exhibit properties such as antioxidant, antimicrobial, anti-inflammatory, anticarcinogenic, antihypertensive, antithrombotic, opioid, mineral-binding, and growth-stimulating activities, contributing to improved human immunity and the treatment of chronic diseases. Enzymatic hydrolysis of milk proteins has been developed as a method to produce these peptides, facilitating their use in food fortification. To incorporate whey into functional beverages, it undergoes fermentation by lactic acid bacteria with proteolytic activity. To specifically enrich these beverages with peptides exhibiting targeted bioactivities, it is essential to select lactic acid bacteria strains possessing the requisite protease profiles. Additionally, the sensory properties of the final product can be enhanced using starter cultures with diverse metabolic capabilities, even in the absence of added flavoring agents. Given the imperative to develop waste-free technologies and enhance the profitability of the dairy industry, there is a growing need to efficiently utilize and transform acid whey into a broad spectrum of valuable products and food additives. This approach is justified not only by the nutritional benefits of the bioactive components in whey but also by the commercial potential of safe and health-enhancing products.
Valorization of grain and oil by-products: with special focus on hemicellulose modification
Authors: Liu Xiaoxian , Xie Jin , Jacquet Nicolas , Blecker Christophe
Published: June 2024

Hemicellulose is one of the most important natural polysaccharides in nature. Hemicellulose from different sources varies in chemical composition and structure, which in turn affects the modification effects and industrial applications. Grain and oil by-products (GOBP) are important raw materials for hemicellulose. This article reviews the modification methods of hemicellulose in GOBP. The effects of chemical and physical modification methods on the properties of hemicellulose biomaterials were evaluated. The potential applications of GOBP hemicellulose in films, hydrogel, Three-dimensional (3D) printing and adsorbent are discussed. Future research directions and recommendations are also proposed to provide theoretical foundations and technical support for the efficient utilization of these by-products.
Unlocking Phytate with Phytase: A Meta-Analytic View of Meat-type Chicken Muscle Growth and Bone Mineralization Potential
Authors: Nuamah Emmanuel , Okon Utibe Mfon , Jeong Eungyeong , Mun Yejin , Cheon Inhyeok , Chae Byungho , Odoi Frederick Nii Ako , Kim Dong-wook , Choi Nag-Jin
Published: June 2024

The inclusion of exogenous phytase in broiler P and Ca deficient diets in response to heightened concerns over excessive P excretion into the environment over the years has remarkably been documented. However, responses among these studies have been inconsistent because of the several factors affecting P utilization. For this reason, a systematic review with meta-analysis of results from forty-one studies published from 2000 to February 2024 was evaluated to: 1) quantitatively summarize the size of phytase effect on growth performance, bone strength, and mineralization in broilers fed P and Ca deficient basal diets and 2) estimate and explore the heterogeneity of the effect sizes of outcomes using sub-group and meta-regression analyses. The quality of the included studies was assessed using the Cochrane Collaboration’s SYRCLE Risk of Bias checklists for animal studies. Additionally, applying the random-effects models, Hedges’ g effect size of supplementation with phytase was calculated using the R software to determine the standardized mean difference (SMD) at a 95% confidence interval. Sub-group analysis and meta-regression further explored heterogeneity (PSMD ≤ 0.05, I2 > 50%, n ≥ 10). The meta-analysis showed that supplemental phytase increases ADFI and BWG and reduces FCR at each time point of growth (< 0.0001). Additionally, phytase supplementation consistently increased tibia ash, P and Ca, and bone strength (< 0.0001) of broilers fed P and Ca deficient diets. Results of the subgroup and meta-regression analyses showed that age and strain of broiler, dietary P source, and duration of phytase exposure significantly influence the effect size of phytase on growth and bone parameters. In conclusion, phytase can attenuate the effect of reducing dietary available phosphorus and calcium and improve ADFI, BWG, and reduced FCR, especially when added to starter diets. It further enhances bone ash, bone mineralization, and bone-breaking strength of broilers, even though the effects of bone ash and strength can be maximized in the starter phase of growth. However, the effect sizes of phytase were related to the age and strain of the broiler, dietary P source, and duration of phytase exposure rather than the dosage.
Bridging Artificial Intelligence and Neurological Signals (BRAINS): A Novel Framework for EEG-Based Image Generation
Authors: Sokač Mateo , Mršić Leo , Balković Mislav , Brkljačić Maja
Published: June 2024

Recent advancements in cognitive neuroscience, particularly in Electroencephalogram (EEG) signal processing, image generation, and brain-computer interfaces (BCI), have opened up new avenues for research. This study introduces a novel framework, Bridging Artificial Intelligence and Neurological Signals (BRAINS), which leverages the power of AI to extract meaningful information from EEG signals and generate images. The BRAINS framework addresses the limitations of traditional EEG analysis techniques, which struggle with nonstationary signals, spectral estimation, and noise sensitivity. Instead, BRAINS employs Long Short-Term Memory (LSTM) networks and contrastive learning, which effectively handle time-series EEG data and recognize intrinsic connections and patterns. The study utilizes the MNIST dataset of handwritten digits as stimuli in EEG experiments, allowing for diverse yet controlled stimuli. The data collected is then processed through an LSTM-based network employing contrastive learning and extracting complex features from EEG data. These features are fed into an image generator model, producing images as close to the original stimuli as possible. This study demonstrates the potential of integrating AI and EEG technology, offering promising implications for the future of brain-computer interfaces.
The Impact of Industrial Fires in Urban Settings: Monitoring, Modelling, Health, and Environmental Justice Perspectives
Authors: Deary Michael Edward , Griffiths Simon David
Published: June 2024

Industrial fires at facilities including waste management sites, warehouses, factories, chemical works and fuel storage depots are relatively frequent occurrences. Often, these fires occur adjacent to urban communities and result in ground-level airborne pollutant concentrations that are well above guideline values. Land, water, livestock and crops may also be contaminated by the emissions and by firefighting activities. Moreover, impacted communities tend to have a higher proportion of minority ethnic populations, individuals with underlying health vulnerabilities, as well as those of lower socio-economic status. Nevertheless, this is an aspect of air quality that is under-researched, and so this review aims to highlight the public health hazards associated with industrial fires and the need for an effective, coordinated, public health response. We also review the range of monitoring techniques that have been utilised in such fires and highlight the role of dispersion modelling in predicting plume trajectories and in estimating population exposure. We recommend establishing 1-h guideline values for particulate matter to facilitate timely public health interventions and we highlight the need to review regulatory and technical controls for sites prone to fires, particularly in the waste sector.
Exploring the Implications of Supply Chain Disruptions on Organizational Resilience
Authors: Reynolds Samantha
Published: June 2024

Supply chain disruptions pose significant challenges to organizations, highlighting the critical importance of resilience in contemporary supply chains. This qualitative research explores the implications of supply chain disruptions on organizational resilience, drawing insights from interviews with supply chain managers and executives across various industries. The study identifies key factors that contribute to resilience, including agility, collaboration, risk management, strategic planning, technology integration, leadership, and organizational culture. Through thematic analysis, the research elucidates how these factors interact to enable organizations to manage and recover from disruptions effectively. Findings underscore the importance of agility in adapting to changing circumstances, collaboration with stakeholders to coordinate responses, and proactive risk management to anticipate and mitigate disruptions. Strategic planning and technology integration emerge as vital enablers of resilience, along with effective leadership and a resilient organizational culture that fosters adaptability and continuous improvement. The implications of supply chain disruptions extend beyond operational and financial impacts to include reputational and relational dimensions, emphasizing the importance of transparent communication and stakeholder engagement. The practical insights offered by this study provide guidance for organizations seeking to enhance their resilience and ensure continuity of operations in an increasingly complex and dynamic supply chain environment.
Impact of Hydroxyapatite on Gelatin/Oxidized Alginate 3D-Printed Cryogel Scaffolds
Authors: Zhanbassynova Ainur , Mukasheva Fariza , Abilev Madi , Berillo Dmitriy , Trifonov Alexander , Akilbekova Dana
Published: June 2024

Fabrication of scaffolds via 3D printing is a promising approach for tissue engineering. In this study, we combined 3D printing with cryogenic crosslinking to create biocompatible gela-tin/oxidized alginate (Gel/OxAlg) scaffolds with large pore sizes, beneficial for bone tissue re-generation. To enhance the osteogenic effects and mechanical properties of these scaffolds, we evaluated the impact of hydroxyapatite (HAp) on the rheological characteristics of the 2.86% (1:1) Gel/OxAlg ink. We investigated the morphological and mechanical properties of scaffolds with low, 5% and high 10% HAp content, as well as the resulting bio and osteogenic effects. Scanning electron microscopy revealed a reduction in pore sizes from 160-180 µm (HAp-free) to 120-140 µm for both HAp-containing scaffolds. Increased stability and higher Young’s moduli were measured for 5% and 10% HAp (18 and 21 kPa, respectively) compared to 11 kPa for HAp-free constructs. Biological assessments with mesenchymal stem cells indicated excellent cytocompati-bility and osteogenic differentiation in all scaffolds, with high degree of mineralization in HAp-containing constructs. Scaffolds with 5% HAp exhibit improved mechanical characteristics and shape fidelity, demonstrate positive osteogenic impact, and enhance bone tissue formation. Increasing the HAp content to 10% did not show any advantages in osteogenesis, offering a minor increase in mechanical strength at the cost of significantly compromised shape fidelity.
Enhancing Metabolic Syndrome Detection through Blood Tests Using Advanced Machine Learning
Authors: Paplomatas Petros , Rigas Dimitris , Sergounioti Athanasia , Vrahatis Aristidis
Published: June 2024

The increasing prevalence of Metabolic Syndrome (MetS), a serious condition associated with elevated risks of cardiovascular diseases, stroke, and type 2 diabetes, underscores the urgent need for effective diagnostic tools. This research carefully examines the effectiveness of 16 diverse machine learning (ML) models in predicting MetS, a multifaceted health condition linked to increased risks of heart disease and other serious health complications. Utilizing a comprehensive, unpublished dataset of imbalanced blood test results, spanning from 2017 to 2022, from the Laboratory Information System of the General Hospital of Amfissa, Greece, our study embarks on a novel approach to enhance MetS diagnosis. By harnessing the power of advanced ML techniques, we aim to predict MetS with greater accuracy using non-invasive blood test data, thereby reducing the reliance on more invasive diagnostic methods. Central to our methodology is the application of the Borda count method, an innovative technique employed to refine the dataset. This process prioritizes the most relevant variables, as determined by the performance of the leading ML models, ensuring a more focused and effective analysis. Our selection of models, encompassing a wide array of ML techniques, allows for a comprehensive comparison of their individual predictive capabilities in identifying MetS. This study not only illuminates the unique strengths of each ML model in predicting MetS but also reveals the expansive potential of these methods in the broader landscape of health diagnostics. The insights gleaned from our analysis are pivotal in shaping more efficient strategies for the management and prevention of Metabolic Syndrome, thereby addressing a significant concern in public health.
Linked Links. A Research Project: The Multiple Superimposed Soft Networks as Network Profiles
Authors: Minati Gianfranco
Published: June 2024

This article, based on network science, aims to contribute to overcoming its geometric and technological phases. The novelty consists in considering links of networks as linked by superimposed networks, termed here multiple superimposed soft networks (MSSN), which is introduced as a research issue. Such links of links (termed here as passive links) concern, for instance, correspondences, incompatibilities, and temporal synchronizations between the occurrences of pairs of active links of effective networks, such as those based on electrical and telecommunication. A possible constitutive mechanism of such passive linkage consists of linkage representations for practices and histories of use expressed by their validating statistical reoccurrences. We consider the possible emergent nature of the passive linkage. The reason for introducing the design and usage of MSSN properties as a research issue involves making new approaches to profile and manage networks available. Correspondence between active linkage and MSSN properties should be a matter for an experiential, machine-learning approach. Research issues relate their possible usage on the active linkage such as for classification, comparations, detection of criticalities, diagnosis, performance evaluation, and regulatory as weak forces. Furthermore, the possible identification of standard corresponding configurations of passive and active linkage are finalized to avoid their establishment or, conversely, in facilitating their establishment and keeping their replication in different contexts (or partially and in combinations) and identifying related standardized approaches (also for classes of configurations having significant levels of equivalence). This research project has methodological generalizing aspects of trans-disciplinarity. We conclude by mentioning related research issues.
Factors Associated With Complications of Snakebite Envenomation in Health Facilities in the Cascades Region of Burkina Faso, 2016 to 2021
Authors: Kinda Réné , Sidibe Sidikiba , Zongo Dramane , Millogo Tieba , Delamou Alexandre , Kouanda Seni
Published: June 2024

Snakebite envenomation remains a major cause of morbidity and mortality in rural populations. This study aimed to identify factors associated with complications from snakebite envenomation reported in health facilities in the Cascades region of Burkina Faso. This cross-sectional study used routine data of patients admitted for snakebite envenomation in five health facilities between January 1, 2016, and December 31, 2021. Data were collected on sociodemographic, clinical, and therapeutic characteristics of patients showing signs of envenomation. Bivariate and multivariate analyses were conducted to determine factors associated with complications. Among the 846 patients with envenomation, 355 (42%) experienced complications. Local complications at the bite site included wounds (21.5%) and skin necrosis (12.5%). Systemic complications included hemorrhage (30.5%), shock (16.3%), and coma (4.3%), with a mortality rate of 3.2%. Factors significantly associated with complications were rural residence (AOR: 4.80; 95% CI: 2.21-11.4), incision at the bite site (AOR: 4.31; 95% CI: 2.51-7.52), tourniquet application (AOR: 5.52; 95% CI: 1.42-30.8), bleeding (AOR: 14.2; 95% CI: 8.80-23.4), abnormal vital signs (AOR: 14.3; 95% CI: 9.22-22.7), and non-administration of antivenom serum (AOR: 2.92; 95% CI: 1.8-4.8). These findings highlight the importance of antivenom availability and public awareness to reduce complications from snakebite envenomation.
Comparitive Chloroplast Genomics of Nine Endangered Habenaria Species and Phylogenetic Relationship of Orchidaceae
Authors: Zhang Jinkui , Zhou Dangwei , Chen Weidong , Lin Pengcheng , Zhao Suqin , Wang Min , Wang Huan , Shi Shengbo , Mehmood Farrukh , Ye Xing , Meng Jing , Zhuang Yuanwen
Published: June 2024

Habenaria, a member of Orchidaceae family is the cosmopolitan distributions, which has significant medicinal and ornamental values. Regardless of morphology and molecular data that have been studied in recent times, the phylogenetic relationship is still under debate. Here, we sequenced, assembled, and annotated the whole chloroplast (cp) genome of two species (Habenaria aitchisonii Rchb.f. and Habenaria tibetica Schltr.ex Limpricht) of Habenaria grown on the Qinghai-Tibetan Plateau (QTP), and combined with seven already published cp genomes which may assist to uncover their genomic profiling. The two genomes ranged from 155259-155269 bp in length and both encoded 132 genes, including 86 protein, 38 tRNA and 8 rRNA. In the cp genomes, the tandem repeats (797), SSRs (2195) and diverse loci (3214) were identified. Comparative analyses of codon usage, amino frequency, microsatellite, oligo repeats and transition and transversion substitutions showed similarities among the species. Moreover, we identified 16 highly polymorphic regions with nucleotide diversity above 0.02, which may be suitable for robust authentic barcoding and inferring in the phylogeny of Habenaria species. Among the polymorphic regions, positive selection was significantly exerted on the several genes such as cemA, petA, and ycf1. This may suggest that the important adaptation stratagem for two Habenaria species on the QTP. The phylogenetic relationship displayed that H.aitchisonii and H. tibetica have closer relationship than others and the rest seven species clustered in the other three groups. Our findings also supported the idea that Habenaria could be divided into different sections. This study enriched the genomics resources of Habenaria, which may be helpful for the conservation efforts of these endangered species.
An Optofluidic Young Interferometer for Electrokinetic Transport Coupled Biosensing
Authors: Labella Elisabetta , Gupta Ruchi
Published: June 2024

Label-free optical biosensors such as interferometers can provide comparable limit of detection to widely used enzyme-linked immunosorbent assays, while minimizing the number of steps and reducing false positives/ negatives. In 2020, authors reported a novel optofluidic Young interferometer (YI) that can provide real-time spatial information on refractive index changes occurring along the length of sensor and reference channels. Herein, we exploited these features of the YI to study interactions of biomolecules with recognition elements immobilized in selected regions of agarose gel in the sensor channel. We showed that the YI is well suited for biosensing of an exemplar biomolecule, streptavidin, in the absence and presence of bovine serum albumin interferent. Equally, we coupled the YI with electrokinetic transport to reduce the time for biosensing.