bluuebunny/crossref_metadata_2025 huggingface dataset:
Possible Eoarchean records of the geomagnetic field preserved in the Isua Supracrustal Belt, southern west Greenland
Authors: Nichols Claire , Weiss Ben , Eyster Athena , Martin Craig , Maloof Adam , Kelly Nigel , Zawaski Mike , Watson E. Bruce , Mojzsis Stephen , Cherniak Daniele
Published: June 2023

We present paleomagnetic field tests that hint that a record of Earth’s 3.7-billion-year (Ga) old magnetic field may be preserved as a chemical remanent magnetization acquired during amphibolite-grade metamorphism in the banded iron formation from the northeastern Isua Supracrustal Belt. Multiple petrological and geochronological lines of evidence indicate that the northern most part of Isua has not experienced metamorphic temperatures exceeding 350◦C since the Eoarchean, suggesting the rocks have not been significantly heated since magnetization was acquired. We use a ‘pseudo’ baked contact test to assess paleodirections in the banded iron formation that pre-date the intrusion of the 3.26-3.5 Ga Ameralik dyke swarm. We demonstrate that specimens that pass this test also go on to pass a fold test and may also pass a reversal test. We recover what appears to be the oldest known whole rock record of the geomagnetic field, and oldest known records of reversals suggesting that Earth’s magnetic field behaviour in the Eoarchean may have been similar to that observed today.
Adaptive Finetuning of 3D CNNs with Interpretation Uncertainty for Seismic Fault Prediction
Authors: Mustafa Ahmad , AlRegib Ghassan , Rastegar Reza
Published: June 2023

3D CNNs can exploit the full extent of spatial information in seismic volumes to predict faults. They require large quantities of training data, but this issue has been mitigated by training such networks with large amounts of synthetic training data to apply afterwards on real datasets. Because of domain shift, pre-trained networks may fail to perform as expected, emphasizing the need to finetune the network with labels obtained on target data of interest. The mismatch in dimensions of network input and interpreter annotations (mostly 2D slices) poses a problem in this respect. In addition, there is a high degree of uncertainty attached to such labels, both on a coarse level as well as on a more fine-grained basis. On an image level, the interpreter may only annotate structures in a small, localized portion of the seismic volume. Furthermore, owing to uncertainty regarding the exact delineation of the endpoints of picked faults, interpreters may only label certain segments on the complete fault line. We propose a method whereby we demonstrate a procedure to finetune the pretrained 3D CNNs with sparse 2D labels on target datasets, resulting in the adaption of their weights to better pick faults in the new domains. Secondly, we devise means to incorporate interpretation uncertainty on labels produced for finetuning to generate better, more reliable fault estimations. We validate our findings on various real datasets and demonstrate improved network performance over the pretrained CNN alone. Additionally, we show that incorporating label uncertainty while finetuning leads to better interpretation performance compared to uncertainty-agnostic finetuning.
Planteamiento de preguntas de investigación e hipótesis en estudios cuantitativos y cualitativos: clarificación de su uso y aplicación [Setting research questions and hypotheses in quantitative and qualitative studies: clarifying their use and application]
Authors: Goyanes Manuel
Published: June 2023

La formulación de hipótesis y preguntas de investigación como guías en el planteamiento de investigaciones cualitativas y cuantitativas es una práctica habitual en los estudios de comunicación. Sin embargo, en muchas ocasiones, existe cierta confusión acerca de bajo qué condiciones es conveniente el planteamiento de hipótesis o preguntas de investigación en función de la naturaleza cualitativa o cuantitativa de los datos del estudio. En este breve ensayo se examinan los objetivos y diferencias de la investigación cuantitativa frente a la cualitativa y se razona sobre cuándo es más apropiado y recomendable el planteamiento de hipótesis o preguntas de investigación.
ПЕРСОНАЛЬНА ЕЛЕКТРОННА БІБЛІОГРАФІЯ ВОУНБ ІМ. В. ОТАМАНОВСЬКОГО ЯК ДЖЕРЕЛО ДЛЯ ВИВЧЕННЯ ЖИТТЄДІЯЛЬНОСТІ ЗНАНИХ ДІЯЧІВ
Authors: Антонюк Оксана
Published: June 2023

У статті проаналізовано та охарактеризовано змістове наповнення персональних бібліографічних посібників, представлених на вебсайті Вінницької обласної універсальної наукової бібліотеки ім. В. Отамановського (далі ВОУНБ ім. В. Отамановського) в електронній бібліотеці у розділі «Видання бібліотеки» за період з 2008 по 2022 рр. Окреслено переваги створення електронних бібліографічних посібників, які спрямовані на відтворення життя і діяльності видатних українських діячів та є важливим джерелом у системі дослідження особистостей. З’ясовано, що на сучасному етапі пріоритетним напрямом є застосування сучасних інформаційних технологій, з розширенням сервісу, що дасть змогу оперативніше забезпечити інтернет-користувачів повнотекстовими інформаційними ресурсами. 
Наукова новизна. Вагоме місце в створенні електронної бібліографічної продукції займає підготовка персональної біобібліографії. Вони відображають науковий та творчий доробок установи за певний період, популяризують відомих діячів регіону. Саме тому в останні роки цей напрям діяльності бібліотек привертає значну увагу багатьох дослідників.
Висновки. Рекомендовано надалі готувати електронні персональні, біобібліографічні посібники, шляхом пошуку та відбору діячів, які залиш
ОСОБОВИЙ ФОНД ПРОФЕСОРА ЧЕРЕВАНЯ У ДЕРЖАВНОМУ АРХІВІ ПОЛТАВСЬКОЇ ОБЛАСТІ (ДАПО)
Authors: Капустян Ганна
Published: June 2023

Стаття присвячена аналізу документів про життя, викладацьку, наукову, громадську діяльність вченого, гуманіста, дисидента, першого доктора історичних наук на Полтавщині, професора Антона Самійловича Череваня, які надійшли до Державного архіву Полтавської області від Полтавського Національного педагогічного університету імені В.Г. Короленка та від професорки Ганни Капустян. Ці документи склали основу Особового Фонду професора Череваня у Державному архіві Полтавської області.
Мета статті – проаналізувати тематику документів Особового фонду професора Череваня, які фундують одноіменний фонд у Державному архіві Полтавської області. Викликати інтерес до життєвого і творчого шляху професора Череваня, людини, громадянина, наукового діяча.
В основу класифікації документів Особового фонду професора Череваня покладений тематичний принцип. Вагому частину документів Особового фонду професора Череваня складають відомості про його наукові дослідження, викладацьку діяльність.
Документи Фонду розкривають  динаміку становлення Череваня як ученого, підготовку і захист ним дисертації «Нариси історії соціально-економічного і правового становища державних селян Уралу і Європейської Півночі Росії до реформи П.Д. Кисільова» (рос.) на здобуття наукового ступеню доктора історичних наук. Джерельну базу докторської дисертації головним чином складали фонди державних архівів: Москви, Ленінграду, Архангельську, Петрозаводську, Вологди, Кірова, Пермі, Свердловська, Шадринська.
Документи Фонду засвідчують участь професора Череваня у дослідженнях історії Полтавщини, зокрема у Проєкті «Історія міст і сіл України».
Фонд містить цікаві і незвичайні документи для сьогодення – епістолярну спадщину, яку, з-поміж, інших поглинає мережева павутина інтернету – переписку з відомими ученими-істориками, основоположниками тематичних направлень радянської історичної науки.
Меморіальну складову документів Фонду представляють документи про увічнення пам’яті професора Антона Череваня: збірники шести наукових Череванівських читань, започаткованих у 2006 році у Полтавському Національному педагогічному університеті ім. В.Г. Короленка до 100-літнього ювілею вченого. Відтоді історичний факультет педуніверситету періодично організовує Череванівські наукові читання.
Occupational and environmental factors affect semen quality:
how exposure to mechanical viberation impacts reproductive indices
Authors: Khussein Abobakr Mokhamed abbakar
Published: June 2023

It is well known that sperm is a unique cell with a function to be done by itself outside the body and this function is second to none for species’ continuity. The sperm mission of reaching the ova and is affected by both chemical and physical factors influence its ability to survive, move and fertilize the ova.
Vibration as an environmental external physical stressor that affect semen viscosity and accordingly semen velocity, is reported to be prevalent among drivers occupied in industrial jobs whose inability to produce natural sperm compared to other occupation will be reviewed in this paper. We will also review the effects of mechanical vibrations with a special attention to shaking semen samples in assisted reproductive technologies in vitro. The effects of whole body exposure to vibrations on reproductive indices will also be investigated.
Ceratite superficial crônica em Pinscher: Relato de caso
Authors: Braga Nathalia Motta
Published: June 2023

Chronic superficial keratitis (CSK) is an inflammatory and progressive corneal disease that affects dogs, potentially leading to blindness. It is more common in certain breeds, particularly German Shepherds. Exposure to ultraviolet rays and high altitudes appears to be associated with the development of the disease. Clinical signs include fibrous proliferation in the temporal limbus, blood vessels advancing towards the central cornea, and corneal pigmentation. The immunomediated basis of the disease is supported by histopathological features and response to topical immunosuppressive treatment. Diagnosis is based on clinical examination, breed predisposition, and response to treatment. In this report, the objective was to describe a case of chronic superficial keratitis in a Pinscher with clinical characteristics different from those found in the literature.
PENGARUH PROJECT VIDEO VLOG YOUTUBE DALAM MENINGKATKAN KEMAMPUAN TALI-TEMALI DAN MOTIVASI BELAJAR PADA EKSTRAKURIKULER PRAMUKA DI MIN 1 MOJOKERTO
Authors: MURDIANTO RISKI , NIZZAM MOKHAMMAD
Published: June 2023

Perkembangan zaman yang semakin modern berdampak besar dalam ranah ‎pendidikan. Faktanya adalah di mana media elektronik telah banyak digunakan ‎oleh masyarakat, salah satunya adalah anak-anak yang berstatus sebagai peserta ‎didik. Ada pun salah satu media yang digemari peserta didik saat ini adalah ‎youtube. Sehingga, perlu juga adanya pembaharuan model-model belajar yang ‎terkini. Dilakukannya penelitian ini bertujuan untuk mengetahui pengaruh project ‎video vlog youtube dalam meningkatan kemampuan tali-temali dan motivasi belajar ‎pada ekstrakurikuler pramuka di MIN 1 Mojokerto. Penelitian ini menggunakan ‎pendekatan kuantitatif dengan model true eksperimen. Sehingga didapat data ‎hipotesis setelah melakukan pengujian terhadap variabel menggunakan uji ‎homogenitas, uji validitas dan reliabilitas, dan uji normalitas, maka didapatkan uji ‎hipotesis di mana terdapat pengaruh project video vlog youtube terhadap ‎kemampuan tali-temali peserta didik dan tidak terdapat pengaruh project video ‎vlog youtube terhadap motivasi belajar peserta didik ekstrakurikuler pramuka di ‎MIN 1 Mojokerto.‎
Effect of the probiotic feed additive “Immunobacterin-D” on the productivity of black speckled cows during lactation
Authors: Pogranichniy Roman , Lytvynenko Viktor , Vergeles Oleksandr
Published: June 2023

In Ukraine, as in every country in the world, an important task is to develop an effective development strategy for producing natural dairy products through probiotics. Feeding PFA to animals shows different effectiveness depending on their age, the intestinal microbiome's characteristics, the feed diet's composition and production technology. The purpose of the study was to identify the most effective period of application of PFA “Immunobacterin-D" and to select a yeast culture to increase the milk productivity of cows. The effectiveness of PFA was evaluated by the amount of milk produced, and its quality – by using an Ecomilk ultrasound analyser. The health status of cows was monitored based on the results of a spectrophotometric study of biochemical parameters of blood serum on a LabLine-010 biochemical analyser (Austria). As a result, it was determined that the optimal period of application of PFA is 30-60 days after calving. On the 13th day of PFA feeding, milk yields in cows of the experimental group increased by 1.2-2.5 L/day. The difference in the amount of milk produced between the animals of the experimental and control groups was 0.7-1.9 L/day. From 70 days after calving, the use of PFA in cows did not cause changes in the volume of milk yield but contributed to an increase in its fat content. By feeding cows of the experimental strain for 21 days S. cerevisiae as part of the PFA, the maximum increase in milk yield was obtained – by 2.13 L, and milk fat – by 0.45%. Whereas the use of PFA with a conventional strain S. cerevisiae AF 338 contributed to an increase in milk yield by 1.73 L, and in the control group of cows only by 1.30 L. According to the results of biochemical studies of blood serum, the positive effect of PFA “Immunobacterin-D” on the health status of cows was proved. PFA can be recommended for feeding cows in production, which will help increase milk yield and improve their health
Role of Interventional Techniques in the Management of Cancer Pain
Authors: Sharma Abhishek , Thakur Niketa , Thakur Abhishake , Bhardwaj Neha
Published: June 2023

Pain is the major cause of morbidity in cancer patients. Interventional techniques should be considered for the management of pain that is refractory to traditional analgesics or when patients are unable to tolerate opioids. Interventional techniques are intended to stop pain signals through neural pathways from the periphery to the brain. This article deals with major interventional pain management techniques such as central neuraxial block, sympathetic block, peripheral nerve block, percutaneous cordotomy, percutaneous vertebroplasty and kyphoplasty, radiofrequency ablation, and cryoablation. Besides this, the role of radiotherapy and radionuclides in cancer pain have also been discussed. Central neuraxial block can effectively reduce pain while preventing opioid toxicity. It involves a percutaneous epidural or intrathecal catheter, an external syringe pump, or a fully implanted intrathecal drug delivery system to give medication. Sympathetic blocks such as celiac plexus and superior hypogastric block have role in patients with visceral abdominal pain. Peripheral nerve blocks may be employed when the distribution of somatic pain is restricted to a single nerve or plexus. Percutaneous cordotomy could be useful for any unilateral cancer pain below C4 dermatome. Percutaneous vertebroplasty (PV) treatment is used to alleviate axial back pain due to osteoporotic wedge fracture or malignant vertebral body disease. RFA and cryoablation techniques are now widely used for back pain due to osteoporotic and malignant vertebral collapse that are resistant to conservative treatment. External beam radiotherapy and radionuclides are useful in relieving cancer pain due to bone metastasis. This article aims at summarizing the indications, mechanisms, drug agents, contraindications, and complications of interventional pain management techniques that may offer benefits to patients coping with cancer and its terrible symptoms. Even though there is some risk involved with the techniques discussed in this article, the advantages of reduced pain and enhanced quality of life usually outweigh the risk.
Influence of vacuum infiltration on mechanical properties of polymer concrete filled with lightweight ceramic aggregates
Authors: Smoleń Jakub , Pawlik Tomasz
Published: June 2023

In this paper, the influence of vacuum infiltration of lightweight ceramic aggregates as fillers in polymeric concretes was described. In the first stage of the investigation, a set of ceramic aggregates with a high open porosity of about 27% was produced on the basis of industrial wastes. Ceramic aggregates with a size of 2 to 4 mm, hereinafter referred to as granules, were produced using contaminated glass cullet waste and coal shale. The effectiveness of granule infiltration with epoxy resin in the production of polymer concrete with high mechanical strength and relatively low mass compared to traditional concrete was discussed. The compressive strength of polymer concrete, where the aggregates were infiltrated with resin, is 87 MPa, and the polymer concrete, in which the vacuum infiltration process was not used, reaches a compressive strength of approximately 42 MPa. The resulting concrete, due to its density, is classified as a lightweight high-strength concrete.
An integrative analysis of the tumor suppressors and oncogenes from sexual dimorphism and gene expression alteration features in thyroid cancer
Authors: Huang Yue , Wang Yaoxin , Liu Sining , Xu Zhengmin , Chen Wen-Xia
Published: June 2023

BACKGROUND: The incidence of thyroid cancer has risen rapidly over the last decades. Although mortality rates are relatively low compared to other cancers, the rate of new cases started to increase in the early 2000s. While tumor suppressors and oncogenes were recently identified in thyroid cancer, the potential roles of these genes in thyroid cancer remain unclear. OBJECTIVE: Analyze the roles and functions of tumor suppressors and oncogenes in thyroid cancer. METHODS: Thyroid cancer data were collected from public databases, such as the UCSC Xena database of TCGA thyroid cancer, TISIDB, and UALCAN. The genes frequently associated with unfavorable thyroid cancer were examined and validated. The association of these target genes with thyroid tumorigenesis, stages, subtypes, and survival rates were analyzed. Additionally, the genes aberrantly expressed in thyroid cancer and significantly involved in thyroid tumorigenesis, stages, subtypes, and survival rates were identified. RESULTS: Female sex was identified as a risk factor for thyroid cancer. The expression of PAPSS2, PDLIM3, COPZ2, ALDH1B1, ANTXR1, GUF1, and SENP6 negatively correlated with thyroid cancer prognosis. CONCLUSION: Female sex was a risk factor for thyroid cancer. In addition, our analysis suggested that PAPSS2, PDLIM3, COPZ2, ALDH1B1, ANTXR1, GUF1, and SENP6 are negatively correlated with the prognosis of thyroid cancer. The expression of ANTXR1, GUF1, and PDLIM3 was weakly associated with thyroid cancer’s immune and molecular subtypes.
Exact Wirelength of Embedding 3-Ary n-Cubes into Certain Cylinders and Trees
Authors: Rajeshwari S. , Rajesh M.
Published: June 2023

Graph embeddings play a significant role in the design and analysis of parallel algorithms. It is a mapping of the topological structure of a guest graph G into a host graph H, which is represented as a one-to-one mapping from the vertex set of the guest graph to the vertex set of the host graph. In multiprocessing systems, the interconnection networks enhance the efficient communication between the components in the system. Obtaining minimum wirelength in embedding problems is significant in the designing of networks and simulating one architecture by another. In this paper, we determine the wirelength of embedding 3-ary n-cubes into cylinders and certain trees.
Activation of TNF Receptor 2 Improves Synaptic Plasticity and Enhances Amyloid-β Clearance in an Alzheimer’s Disease Mouse Model with Humanized TNF Receptor 2
Authors: Ortí-Casañ Natalia , Wajant Harald , Kuiperij H. Bea , Hooijsma Annelien , Tromp Leon , Poortman Isabelle L. , Tadema Norick , de Lange Julia H.E. , Verbeek Marcel M. , De Deyn Peter P. , Naudé Petrus J.W. , Eisel Ulrich L.M.
Published: June 2023

Background: Tumor necrosis factor-alpha (TNF-α) is a master cytokine involved in a variety of inflammatory and neurological diseases, including Alzheimer’s disease (AD). Therapies that block TNF-α proved ineffective as therapeutic for neurodegenerative diseases, which might be explained by the opposing functions of the two receptors of TNF (TNFRs): while TNFR1 stimulation mediates inflammatory and apoptotic pathways, activation of TNFR2 is related to neuroprotection. Despite the success of targeting TNFR2 in a transgenic AD mouse model, research that better mimics the human context is lacking. Objective: The aim of this study is to investigate whether stimulation of TNFR2 with a TNFR2 agonist is effective in activating human TNFR2 and attenuating AD neuropathology in the J20xhuTNFR2-k/i mouse model. Methods: Transgenic amyloid-β (Aβ)-overexpressing mice containing a human extracellular TNFR2 domain (J20xhuTNFR2-k/i) were treated with a TNFR2 agonist (NewStar2). After treatment, different behavioral tests and immunohistochemical analysis were performed to assess different parameters, such as cognitive functions, plaque deposition, synaptic plasticity, or microglial phagocytosis. Results: Treatment with NewStar2 in J20xhuTNFR2-k/i mice resulted in a drastic decrease in plaque load and beta-secretase 1 (BACE-1) compared to controls. Moreover, TNFR2 stimulation increased microglial phagocytic activity, leading to enhanced Aβ clearance. Finally, activation of TNFR2 rescued cognitive impairments and improved synaptic plasticity. Conclusion: Our findings demonstrate that activation of human TNFR2 ameliorates neuropathology and improves cognitive functions in an AD mouse model. Moreover, our study confirms that the J20xhuTNFR2-k/i mouse model is suitable for testing human TNFR2-specific compounds.
Using mHealth for Primary Prevention of Dementia: A Proof-of-Concept Study on Usage Patterns, Appreciation, and Beliefs and Attitudes Regarding Prevention
Authors: Heger Irene , Deckers Kay , de Vugt Marjolein , Verhey Frans , Oenema Anke , van Boxtel Martin , Köhler Sebastian
Published: June 2023

Background: Health- and lifestyle factors account for a substantial part of all dementia cases, which opens the opportunity for primary prevention. However, the required behavioral change is complex and involves targeting multiple risk factors. mHealth interventions can potentially contribute to improving motivation in a low-cost and scalable way. Objective: To explore usage patterns, appreciation, and beliefs and attitudes regarding dementia risk reduction during the use of the MyBraincoach mobile app. Methods: Participants were community-dwelling middle-aged adults from the Netherlands and used either the standard (education) or extended (education+motivational triggers) app version for three months. Two panel studies were combined in this paper. Chi-square tests, t-tests and linear mixed models were used, adjusted for age, sex, and education. Results: Of all participants (n = 299, 50.2% male), 167 (55.9%) had installed the app. The most reported reason for non-use was technical problems (47%). Those who used the app were at baseline already more positive about dementia risk reduction than those who did not use the app. Of all users who completed the evaluation (n = 102), 78.4% (n = 80) stated that the app provided a positive approach towards brain health and 80.4% (n = 82) felt better informed. Younger (<60y) and lower educated participants evaluated the app most positively. Conclusion: Usage of the app was low, but users showed more positive beliefs and attitudes regarding dementia risk reduction. Most users evaluated the app positively and stated to have gained knowledge on the topic. Improving the use of the app must keep high priority in future studies.
Sensorless control of SPMSM based on an adaptive sliding mode observer with optimized phase-locked loop structure
Authors: Ding Hongchang , Li Jinhong , Wei Linchao , Zou Xinhong
Published: June 2023

To improve the speed and position detection accuracy of surface-mount permanent magnet synchronous motor (SPMSM) vector control and reduce unnecessary chattering of the system, this paper proposes a sensorless control strategy of SPMSM based on an adaptive sliding mode observer (ASMO) with optimized phase-locked loop (OPLL) structure. First, in order to overcome the chattering of system caused by discontinuous switching characteristic of signum function in conventional sliding mode observer (CSMO), a continuous saturation function is selected as the switching function. The ASMO adopts the system state-related adaptive gain function to adjust the switching gain value of the system in real time, which overcomes the slow response speed or severe chattering of the system caused by the constant switching gain of CSMO. Second, to reduce the phase delay between the rotor position estimation value and the actual value caused by the adoption of low-pass filter (LPF) and the position estimation error caused by arctangent function method, an OPLL method is designed for accurate estimation of rotor position and speed. Finally, the effectiveness and feasibility of the proposed improved SMO algorithm is verified by simulation and experiments on an SPMSM with rated power of 2 kW.
Bioactive properties of vinegars produced from prunus laurocerasus L. varieties
Authors: Yilmaz Kubra , Baltaci Cemalettin , Ozturk Seyda , Karpuz Omer
Published: June 2023

BACKGROUND:

Cherry laurel fruit (CLF) has distinctive bioactive properties, which may yield new food products based on CLF.

OBJECTIVE:

This research aimed to realize the production of vinegar from the CLF, thus, valorizing the CLF, which is rich in antioxidants and phenolic substances, and bringing a new nutrient-rich vinegar to the market.

METHODS:

Seven types of traditional CLF vinegar (CLFV) from three different species were produced, and their bioactive properties were examined. The bioactivity analyses of total phenolic substance (TPC), total flavonoid (TFC), total antioxidant activity (AA), DPPHࢫ (Free radical scavenging activity), FRAP (Ferric reducing antioxidant power), ABTSࢫ + (Radical cation scavenging effect) were conducted. In addition, the composition of phenolic substances was studied.

RESULTS:

This study showed that CLFV performed better than controls regarding antioxidant activity, phenolic compounds, and substances. The presence of intense phenolic elements in CLFV significantly impacts its antioxidant activity. The antioxidant activities of CLFV were detected to be greater than the previous reports on bioactivities of vinegar from various fruits.

CONCLUSIONS:

High antioxidant and phenolic content were observed in CLFV, similar to the composition of the CLF. The usability of CLFV as a healthy and nutritious food product seems achievable on an industrial scale.
Automatic access control method of PLC stacker crane based on GA optimization algorithm
Authors: Liu Xiaolin
Published: June 2023

At present, car ownership is expanding, and parking facilities are insufficient. This problem has plagued people’s lives and hindered the development of cities. The stereo garage has become the main way to solve the parking problem. But the existing stereo garage is low in intelligence and low in vehicle entry efficiency. Therefore, in this study, a new vehicle entry strategy for the road stacking stereo garage is designed. GA algorithm is innovatively improved and applied to vehicle strategy optimization. By taking the dual objective function as the fitness function of the algorithm, the access strategy is optimized. Using MATLAB software to simulate and verify each access strategy and its improvement effect. This study provides guidance and data support for seeking the best vehicle access strategy. It has good practical application value for vehicle access in 3D garage.
Internet speech denoising method based on IGAN algorithm
Authors: Luo Sanchuan
Published: June 2023

At present, to settle the question of excessive noise in the speech signal during the call of mobile devices in China, the research proposes that the Wiener filter and the generative adversarial network are combined into the IGAN algorithm. Firstly, the Wiener filter regularization algorithm is introduced to construct the preprocessing model of the speech signal; then the preprocessing model is fused with the generative adversarial network algorithm to construct the denoising model. Finally, the performance analysis and simulation experiments of the application effect of the model are carried out. The results show that in the experiment comparing IGAN with five traditional algorithms, when the SNR ratio is increased to 17.5 dB, the MOS and PESQ scores under the IGAN method can reach 4.9 and 3.5 respectively, and the DNN effect is second only to IGAN. Other algorithms perform poorly. Then compare the number of iterations and the loss value between the two. When the network voice signal begins to converge, the loss value corresponding to DNN is 1.132; while the loss value of IGAN is about 0.573, it can be found that the loss value of IGAN has dropped by half, which shows that IGAN Build the model with a smaller loss value. And IGAN tends to converge when iteratively is performed for about 200 times, and the average peak SNR can reach up to 33.85 dB, an increase of nearly 1.02 dB, and the effect is remarkable. This all shows that the IGAN algorithm has the best denoising performance for network speech signals, improves the denoising efficiency, and is conducive to obtaining a denoising signal with a higher fit with the clean signal, so that mobile devices can better serve the people.
Research on cross-border e-commerce logistics under the sharing economy model
Authors: He Lin , Wu Qixiang
Published: June 2023

As an important part of cross-border e-commerce, cross-border e-commerce logistics occupies a very important position in cross-border e-commerce, but its development in China is relatively lagging behind that of cross-border e-commerce, and this situation needs to be resolved urgently. The emergence of the sharing economy model provides possible solutions to the problems in cross-border e-commerce logistics. This article analyzes the current development status of cross-border e-commerce logistics in China, defines and analyzes the feasibility of the “sharing economy + cross-border e-commerce logistics” model, and finally proposes the “sharing economy + cross-border e-commerce logistics” model corresponding policy recommendations to better support cross-border e-commerce to achieve a high level of sustainable development.
Mentor and mentee matching
Authors: Van Pham Hai , Thuy Linh Hoang Thi , Hung Nguyen Chan , Dich Nguyen Quang , Ngoc Son Luong , Moore Philip
Published: June 2023

Pedagogic systems are gaining traction in the provision of training, learning, and continuing professional development (often required to maintain professional qualifications). An essential element in pedagogic systems is the matching of teachers (mentors) and students (mentees). In this paper we present an intelligent context-aware learning system based on profile criteria developed using big data analytic solutions. The proposed system is designed to provide systematic support for mentors based on student profiles. The goal of the proposed system is to match the mentor profiles with the type of pedagogic system, the student profile, the student requirements, and the student’s goals and expectations. The proposed system is predicated on the use of fuzzy logic definitions with a maximal length matching algorithm using expert knowledge. The proposed system implements a mentor (teacher) and mentee (student) matching algorithm based on their profile criteria. The proposed system has been successfully tested by matching mentor and mentee profiles and preferences. Experimental results show that the proposed system can access multi-factorial mentor and mentee profiles, effectively match suitable mentors (teachers) with appropriate mentees (students), and meet the mentee expectations.
Sports injury early warning of basketball players based on RBF neural network algorithm
Authors: Cui Zheng , Li Xiaoqi , Guo Jie , Lu Yunhang
Published: June 2023

Basketball has always been a relatively hot sport. However, the level of basketball in China does not maintain the synchronous development trend with competitive sports, which can be seen from the achievements of various international competitions. Many basketball players have retired due to sports injuries. How to avoid and delay the occurrence of injuries to the maximum extent, and make the best competitive state to get the longest time is an urgent problem to be solved in the current basketball training and competition process. Therefore, how to reduce sports damage in basketball sports has become a crucial problem. The artificial neural network algorithm is widely used in complex system hardware fault detection, medical diagnosis, medical image processing and other complex task, to classify and forecast, and achieved good results. But in the use of the sports injury risk prevention is very limited, in sports injury risk early warning research, predecessors to sports injury factors made a lot of research and the qualitative model was established, but no quantitative evaluation research, and artificial neural network algorithm has good performance in complex system classification and prediction, so the artificial neural network algorithm is applied to sports injury risk early warning study is a very meaningful work, can carry on the accurate to the athlete sports injury risk assessment. Using RBF neural network to achieve dimensional reduction preprocessing of high-dimensional data not only has sufficient theoretical basis, but also it is more superior. Based on the optimization study of RBF neural network algorithm, we study the data-based feature selection RBF neural network, and apply it in the high-dimensional multi-objective optimization decision space and pare to quality and disadvantages prediction. Through the evaluation of the test sample, the early warning model achieves ideal results, so it is feasible to apply to the sports injury risk warning.
Construction on precise-personalized-learning evaluation system based on cipp evaluation model and integrated FCE-AHP method
Authors: Zhao Jin , Wang Zhaohan , Jianjun Zhang
Published: June 2023

In the Big-data Era, the construction of precise personalized learning evaluation system forms an important part of analyzing learners’ learning behavior and predicting precise personalized learning performance. The CIPP evaluation model is introduced into the precise personalized learning evaluation, and 3 first-level indicators, 9 second-level indicators and 25 third-level indicators are designed to evaluate the learning process in terms of pre-class preview, in-class teaching and after-class consolidation. And then through the application of questionnaire survey, AHP method and fuzzy comprehensive evaluation method, the indicators are condensed and weighted, and the corresponding fuzzy comprehensive judgment matrix is figured out. Finally, a learning evaluation system for the whole process of precise personalized learning is constructed. An empirical study based on the learning behavior data of a certain number of online learners is carried out to test the value and feasibility of this learning evaluation system.
Express parcel detection based on improved faster regions with CNN features
Authors: Wu Cuiling , Duan Xiaodong , Ning Tao
Published: June 2023

Machine vision-based semi-automatic sorting in parcel sorting relies on specific sensors to read form information and synchronize it to the control system to complete a sort. The cost of traditional Faster RCNN parameter calculation is high, and the requirements for hardware equipment are high. In order to reduce the consumption of hardware resources and improve efficiency, we redesigned the traditional Faster RCNN to reduce the hardware cost requirements. The number of categories in package data sets varies greatly, and category imbalance is also one of the problems. To solve the express parcel category imbalance problem, an adaptive Mosaic method is proposed to improve the recognition accuracy of fine-grained similar parcels. To be deployed on edge devices with limited computational resources, a new lightweight network, Reparameterization Large Depthwise conv Normalization-based Attention (ReLDWNAM), is proposed. The experimental results show that compared with MobileNetV2, the number of parameters is reduced by 3.07M, and the computing resources are reduced by more than twice, 10 times faster time for feature extraction network, and more than double the overall detection speed of Faster RCNN with little difference in accuracy.
The supplier performance evaluation of sports event service under the COVID-19 outbreak: A novel hesitant fuzzy MARCOS method
Authors: Li Guo , Geng Xiuli , Yuan Yong
Published: June 2023

Under the COVID-19 pandemic, sports event is facing enormous challenges. Logistics and security are affected seriously. The ability of service suppliers to deal with uncertainty is critical. Considering complex uncertainty, evaluating the service suppliers of sports events is reasonable. This study proposes a new framework for selecting sports suppliers, which combines a hesitant fuzzy set (HFS) and Measurement of Alternatives and Ranking according to the Compromise Solution (MARCOS) method. MARCOS is based on determining the reference values of alternatives about the ideal and is a comprehensively rational and reasonable application methodology. HFS has the advantage of expressing fuzzy and hesitant evaluation information, which is seldom used in the MARCOS framework. A case study of a sports supplier selection for the 2022 China National Youth U Series Floorball Championship is given to demonstrate the practicability of the proposed approach. Finally, a comprehensive sensitivity analysis is performed to verify the proposed methodology’s stability and effectiveness.
A study on the sustainable development of regional water resources-socio-economic-ecological environment-tourism industry: survey evidence from the Yellow River Basin, China
Authors: Zhang Ning , Jung Kwansue
Published: June 2023

High-quality development of socio-economic, ecological environment, tourism industry and natural resources in the Yellow River Basin is a major strategic task for national development. High-quality development in the Yellow River Basin still has a lot of room for improvement, so it is important for the coupled and coordinated development of water resources-socio-economic-ecological environment-tourism industry in the Yellow River Basin region. In this study, we focus on the major strategic issues of high quality development in the Yellow River Basin in the context of the above-mentioned background and the current forms and policies of sustainable development in China, and conduct research on the theory and methods of assessing the sustainable development of regional water resources-socio-economic-ecological environment-tourism industry. However, by analyzing the existing research literature on sustainable development assessment, we find that most of them focus on a single area or two combinations of modal development studies, and focus on exploring micro-coupling mechanisms, so the generality of macro policy support is rather mediocre, which we fill this gap through this study. The study relies on an innovative macroscopic research perspective that draws pioneeringly on the quality function deployment (QFD) theory in the field of product quality management in marketing, which, it is worth stating, allows for a framework of research perspectives from a systematic and holistic perspective. In this framework, we will propose a G1-entropy value method for indicator importance (weight) assessment. It is worth stating that the G1 method used in this paper is different from the traditional G1 method in that we will introduce the identity information weights of experts to improve the reliability of the subjective assignment method. We will also construct an indicator system for studying the regional sustainable development issues in the Yellow River Basin on this basis, so as to complete the ranking and analysis of the nine provinces and the importance of indicators in the Yellow River Basin. This study will provide a comprehensive theoretical basis for Chinese government and related departments to formulate policies for the high-quality development of water resources, socio-economic, ecological environment and tourism industry in the Yellow River Basin, and also provide theoretical and empirical references for the analysis and assessment of similar international regional sustainability cases.
Global field of view-based pixel-level recognition method for medical images
Authors: He Keke , Tang Haojun , Gou Fangfang , Wu Jia
Published: June 2023

Artificial intelligence image processing has been of interest to research investigators in tumor identification and determination. Magnetic resonance imaging for clinical detection is the technique of choice for identifying tumors because of its advantages such as accurate localization with tomography in any orientation. Nevertheless, owing to the complexity of the images and the heterogeneity of the tumors, existing methodologies have insufficient field of view and require expensive computations to capture semantic information in the view, rendering them lacking in universality of application. Consequently, this thesis developed a medical image segmentation algorithm based on global field of view attention network (GVANet). It focuses on replacing the original convolution with a transformer structure and views in a larger field-of-view domain to build a global view at each layer, which captures the refined pixel information and category information in the region of interest with fewer parameters so as to address the defective tumor edge segmentation problem. The dissertation exploits the pixel-level information of the input image, the category information of the tumor region and the normal tissue region to segment the MRI image and assign weights to the pixel representatives. This medical image recognition algorithm enables to undertake the ambiguous tumor edge segmentation task with low computational complexity and to maximize the segmentation accuracy and model property. Nearly four thousand MRI images from the Monash University Research Center for Artificial Intelligence were applied for the experiments. The outcome indicates that the approach obtains outstanding classification capability on the data set. Both the mask (IoU) and DSC quality were improved by 7.6% and 6.3% over the strong baseline.
Ontological knowledge inferring approach: Introducing Directed Collocations (DC) and Joined Directed Collocations (JDC)
Authors: Tissera Muditha , Weerasinghe Ruvan
Published: June 2023

The growing need of utilizing unstructured knowledge embedded in open-domain natural language text into machine-processable forms requires the induction of hardly extracted structured knowledge into knowledge bases which makes the Semantic Web vision a reality. In this context, ontologies, and ontological knowledge (triples) plays a vital role. This research introduces two novel concepts named Directed Collocation (DC) and Joined Directed Collocation (JDC) along with a methodical application of them to infer new ontological knowledge. Introduced Quality-Threshold-Value (QTV) parameter improves the quality of the inferred ontological knowledge. Having set a moderate value (3) for QTV, this approach inferred 95,491 new ontological knowledge from 43,100 triples of open domain Sri Lankan English news corpus. Indeed, the outcome was approximately doubled in size as the source corpus. Some inferred ontological knowledge was identical with the original corpus content, which evidences the accuracy of this approach. The remaining were validated using inter-rater agreement method (high reliability) and out of which around 56% were estimated as effective. The inferred outcome which is in the triple format may use in any knowledge base. The proposed approach is domain independent. Thus, helps to construct/extend ontologies for any domain with the help of less or no human specialists.
Deriving semantic validation rules from industrial standards: An OPC UA study
Authors: Bareedu Yashoda Saisree , Frühwirth Thomas , Niedermeier Christoph , Sabou Marta , Steindl Gernot , Thuluva Aparna Saisree , Tsaneva Stefani , Tufek Ozkaya Nilay
Published: June 2023

Industrial standards provide guidelines for data modeling to ensure interoperability between stakeholders of an industry branch (e.g., robotics). Most frequently, such guidelines are provided in an unstructured format (e.g., pdf documents) which hampers the automated validations of information objects (e.g., data models) that rely on such standards in terms of their compliance with the modeling constraints prescribed by the guidelines. This raises the risk of costly interoperability errors induced by the incorrect use of the standards. There is, therefore, an increased interest in automatic semantic validation of information objects based on industrial standards. In this paper we focus on an approach to semantic validation by formally representing the modeling constraints from unstructured documents as explicit, machine-actionable rules (to be then used for semantic validation) and (semi-)automatically extracting such rules from pdf documents. While our approach aims to be generically applicable, we exemplify an adaptation of the approach in the concrete context of the OPC UA industrial standard, given its large-scale adoption among important industrial stakeholders and the OPC UA internal efforts towards semantic validation. We conclude that (i) it is feasible to represent modeling constraints from the standard specifications as rules, which can be organized in a taxonomy and represented using Semantic Web technologies such as OWL and SPARQL; (ii) we could automatically identify modeling constraints in the specification documents by inspecting the tables ( P = 87 %) and text of these documents (F1 up to 94%); (iii) the translation of the modeling constraints into formal rules could be fully automated when constraints were extracted from tables and required a Human-in-the-loop approach for constraints extracted from text.
Performance of deep learning in classifying malignant primary and metastatic brain tumors using different MRI sequences: A medical analysis study
Authors: Fauzi Adam , Yueniwati Yuyun , Naba Agus , Rahayu Rachmi Fauziah
Published: June 2023

BACKGROUND: Malignant Primary Brain Tumor (MPBT) and Metastatic Brain Tumor (MBT) are the most common types of brain tumors, which require different management approaches. Magnetic Resonance Imaging (MRI) is the most frequently used modality for assessing the presence of these tumors. The utilization of Deep Learning (DL) is expected to assist clinicians in classifying MPBT and MBT more effectively. OBJECTIVE: This study aims to examine the influence of MRI sequences on the classification performance of DL techniques for distinguishing between MPBT and MBT and analyze the results from a medical perspective. METHODS: Total 1,360 images performed from 4 different MRI sequences were collected and preprocessed. VGG19 and ResNet101 models were trained and evaluated using consistent parameters. The performance of the models was assessed using accuracy, sensitivity, and other precision metrics based on a confusion matrix analysis. RESULTS: The ResNet101 model achieves the highest accuracy of 83% for MPBT classification, correctly identifying 90 out of 102 images. The VGG19 model achieves an accuracy of 81% for MBT classification, accurately classifying 86 out of 102 images. T2 sequence shows the highest sensitivity for MPBT, while T1C and T1 sequences exhibit the highest sensitivity for MBT. CONCLUSIONS: DL models, particularly ResNet101 and VGG19, demonstrate promising performance in classifying MPBT and MBT based on MRI images. The choice of MRI sequence can impact the sensitivity of tumor detection. These findings contribute to the advancement of DL-based brain tumor classification and its potential in improving patient outcomes and healthcare efficiency.