bluuebunny/crossref_metadata_2025 huggingface dataset:
A pretest‐posttest design to assess the effectiveness of an intervention to reduce HIV‐related stigma and discrimination in healthcare settings in Vietnam
Authors: Pollack Todd M. , Duong Hao Thi , Nhat Vinh Dang Thi , Phuong Do Thi , Thuy Do Huu , Nhung Vo Thi Tuyet , Uyen Nguyen Kieu , Linh Vuong The , Van Truong Nguyen , Le Ai Kim Anh , Ninh Nguyen Thi , Nguyen Asia , Canh Hoang Dinh , Cosimi Lisa A.
Published: July 2022

Introduction

Stigma and discrimination are important barriers to HIV epidemic control. We implemented a multi‐pronged facility‐level intervention to reduce stigma and discrimination at health facilities across three high‐burden provinces. Key components of the intervention included measurement of stigma, data review and use, participatory training of healthcare workers (HCWs), and engagement of people living with HIV and key populations in all stigma reduction activities.

Methods

From July 2018 to July 2019, we assessed HIV‐related stigma and discrimination among patients and HCWs at 10 facilities at baseline and 9 months following an intervention. A repeated measures design was used to assess the change in stigma and discrimination among HCWs and a repeated cross‐sectional design assessed the change in stigma and discrimination experienced by PLHIV. HCWs at target facilities were invited at random and PLHIV were recruited when presenting for care during the two assessment periods. McNemar's test was used to compare paired proportions among HCWs, and chi‐square test was used to compare proportions among PLHIV. Mixed models were used to compare outcomes before and after the intervention.

Results

Semi‐structured interviews were conducted with 649 and 652 PLHIV prior to and following the intervention, respectively. At baseline, over the previous 12 months, 21% reported experiencing discrimination, 16% reported self‐stigma, 14% reported HIV disclosure without consent and 7% had received discriminatory reproductive health advice. Nine months after the intervention, there was a decrease in reported stigma and discrimination across all domains to 15%, 11%, 7% and 3.5%, respectively (all p‐values <0.05). Among HCWs, 672 completed the pre‐ and post‐intervention assessment. At baseline, 81% reported fear of HIV infection, 69% reported using unnecessary precautions when caring for PLHIV, 44% reported having observed other staff discriminate against PLHIV, 54% reported negative attitudes towards PLHIV and 41% felt uncomfortable working with colleagues living with HIV. The proportions decreased after the intervention to 52%, 34%, 32%, 35% and 24%, respectively (all p‐values <0.05).

Conclusions

A multi‐pronged facility‐level intervention was successful at reducing healthcare‐associated HIV‐related stigma in Vietnam. The findings support the scale‐up of this intervention in Vietnam and highlight key components potentially applicable in other settings.
A qualitative study of how stigma influences HIV services for transgender men and women in Nigeria
Authors: Tun Waimar , Pulerwitz Julie , Shoyemi Elizabeth , Fernandez Anita , Adeniran Adepeju , Ejiogu Franklin , Sangowawa Olusegun , Granger Krista , Dirisu Osasuyi , Adedimeji Adebola A.
Published: July 2022

Introduction

Transgender men and women in Nigeria experience many barriers in accessing HIV prevention and treatment services, particularly given the environment of transphobia (including harassment, violence and discrimination) and punitive laws in the country. HIV epidemic control in Nigeria requires improving access to and quality of HIV services for key populations at high risk, including transgender men and women. We assessed how stigma influences HIV services for transgender people in Lagos, Nigeria.

Methods

In‐depth interviews (IDIs) and focus group discussions were conducted with transgender men (n = 13) and transgender women (n = 25); IDIs were conducted with community service organization (CSO) staff (n = 8) and healthcare providers from CSO clinics and public health facilities (n = 10) working with the transgender population in March 2021 in Lagos. Content analysis was used to identify how stigma influences transgender people's experiences with HIV services.

Results and discussion

Three main findings emerged. First, gender identity disclosure is challenging due to anticipated stigma experienced by transgender persons and fear of legal repercussions. Fear of being turned in to authorities was a major barrier to disclose to providers in facilities not affiliated with a transgender‐inclusive clinic. Providers also reported difficulty in eliciting information about the client's gender identity. Second, respondents reported lack of sensitivity among providers about gender identity and conflation of transgender men with lesbian women and transgender women with being gay or men who have sex with men, the latter being more of a common occurrence. Transgender participants also reported feeling disrespected when providers were not sensitive to their pronoun of preference. Third, HIV services that are not transgender‐inclusive and gender‐affirming can reinforce stigma. Both transgender men and women spoke about experiencing stigma and being refused HIV services, especially in mainstream public health facilities, as opposed to transgender‐inclusive CSO clinics.

Conclusions

This study highlights how stigma impedes access to appropriate HIV services for transgender men and women, which can have a negative impact along the HIV care continuum. There is a need for transgender‐inclusive HIV services and competency trainings for healthcare providers so that transgender clients can receive appropriate and gender‐affirming HIV services.
Implications of intracellular protein degradation pathways in Parkinson's disease and therapeutics
Authors: K Amrutha , Mishra Amit , Singh Sarika
Published: July 2022

Parkinson's disease (PD) pathology is the most common motor neurodegenerative disease that occurs due to the progressive degeneration of dopaminergic neurons of the nigrostriatal pathway of the brain. The histopathological hallmark of the disease is fibrillary aggregate called Lewy bodies which majorly contain α‐synuclein, suggesting the critical implication of diminished protein degradation mechanisms in disease pathogenesis. This α‐synuclein‐containing Lewy bodies are evident in both experimental models as well as in postmortem PD brain and are speculated to be pathogenic but still, the lineal association between these aggregates and the complexity of disease pathology is not yet well established and needs further attention. However, it has been reported that α‐synuclein aggregates have consorted with the declined proteasome and lysosome activities. Therefore, in this review, we reappraise intracellular protein degradation mechanisms during PD pathology. This article focused on the findings of the last two decades suggesting the implications of protein degradation mechanisms in disease pathogenesis and based on shreds of evidence, some of the approaches are also suggested which may be adopted to find out the novel therapeutic targets for the management of PD patients.
Effect of ElectroMagnetic interference from SmartPHone on cardiac ImplaNtable electronic device (EMI‐PHONE study)
Authors: Apakuppakul Sanatcha , Methachittiphan Nilubon , Apiyasawat Sirin
Published: July 2022

Background

Smartphone can emit two types of electromagnetic waves, static field and dynamic field. Evidence showed the interference from phones to cardiac implantable electronic devices (CIEDs). The smartphones and CIEDs are reportedly better designed to reduce electromagnetic interference (EMI).

Methods

80 consecutive subjects with CIEDs were recruited and tested for EMI. Subject was tested with three different smartphones (Nokia 3310, Iphone 7, and Samsung 9S). Phone was attached to chest wall at 0 cm at generator site, at atrial lead level, and at ventricular lead level. During the tests, real‐time interrogations were performed to detect any EMI from smartphone in standby mode, and during calling‐in and out for 30 s. After the tests, post‐test interrogations were performed to detect any parameter change. Adverse events including pacemaker inhibition, false ICD shock, CIEDs device malfunction, and urgent electrophysiologist consultations were recorded.

Results

80 subjects (mean age 70.5‐year‐old, 50% male) recruited in the study, all completed the testing protocol. The most common type of CIEDs tested was pacemaker (N = 56, 70%), followed by ICD (N = 16, 20%), and CRT (N = 8, 10%). Most patients (N = 62, 77.5%) had more than one lead implanted. The mean year of implantation was 5.2±2.8 (devices were implanted from 2008 to 2019). Of all the tests performed, there was no EMI or adverse events observed.

Conclusion

Current generation of smartphones has no EMI effect on CIEDs in our study and can be used safely with less concern about adverse events including pacemaker inhibition, inappropriate ICD shock, and CIEDs device malfunction.
Understanding the association between clinical staging accuracy, treatment response, and survival among gastric cancer patients through Bayesian analysis
Authors: da Costa Wilson Luiz , Tran Cao Hop S. , Gu Xiangjun , Massarweh Nader N.
Published: July 2022

Background

Neoadjuvant therapy (NAT) improves survival among patients with locally advanced gastric cancer (GC), but it remains unclear whether its benefit is contingent on treatment response.

Methods

This is a national cohort study of stage Ib‐III GC patients in the National Cancer Data Base (2006–2015) treated with upfront resection or NAT followed by surgery. Bayesian analysis was used for NAT patients to ascertain staging concordance and to account for down‐staging. We used multivariable Cox regression to evaluate the association between staging concordance, treatment, response to NAT, and survival.

Results

The cohort included 13 340 patients treated at 1124 hospitals. Staging concordance ranged from 86.1% for cT3‐4N+ to 34.7% for cT2N0 patients. Relative to accurately staged patients treated with upfront surgery, NAT was associated with a decreased risk of death if there was disease down‐staging among those with cT1‐2N+ (hazard ratio [HR]: 0.43 [0.30–0.61]), cT3‐4N0 (HR: 0.69 [0.54–0.88]), and cT3‐4N+ (HR: 0.51 [0.48–0.58]) tumors, and in the absence of down‐staging among cT3‐4N+ patients (HR: 0.83 [0.74–0.92]). Conversely, NAT without down‐staging increased the risk of death among those with intermediate‐stage disease.

Conclusions

NAT is associated with improved survival for GC, but it seems to be contingent on treatment response among patients with intermediate‐stage disease.
Mouse model of selective cryolipolysis
Authors: Salma Nunciada , Wang‐Evers Michael , Casper Malte Johannes , Karasik Daniel , Andrade Yanek Jiménez , Tannous Zeina , Manstein Dieter
Published: July 2022

Background

Cryolipolysis is a noninvasive method of destroying adipocytes using controlled cooling, thereby enabling localized and targeted fat reduction. Due to their greater vulnerability to cold injury, adipocytes are selectively targeted, while other cell types are spared.

Objectives

This study aims to develop a mouse model of cryolipolysis to offer a reliable and convenient alternative to human models, providing a methodology to validate clinical hypotheses in‐depth with relative ease, low cost, and efficiency. This further facilitates comprehensive studies of the molecular mechanisms involved in cryolipolysis.

Materials and Methods

Mice (C57BL/6J) were placed under general anesthesia and were treated using our custom, miniaturized cryolipolysis system. A thermoelectric cooling probe was applied to the inguinal (ING) area for either a cold exposure of −10°C, or for a room temperature exposure for 10 minutes. The thickness of the subcutaneous fat of the mice was quantified using an optical coherence tomography (OCT) imaging system before and after the treatment. Histological analyses were performed before and after cryolipolysis at multiple time points.

Results

OCT analysis showed that mice that underwent cold cryolipolysis treatment induced a significantly greater reduction of subcutaneous fat thickness 1 month after treatment than the control mice. The mice that received cold treatment had no skin injuries. The selective damage of adipocytes stimulated cold panniculitis that was characterized histologically by infiltration of immune cells 2 and 3 days after treatment.

Conclusion

This study shows that cryolipolysis performed in mice yields reproducible and measurable subcutaneous fat reduction, consistent with previous studies conducted in humans and pigs. Future studies can utilize the model of selective cryolipolysis developed by our group to further elucidate the cellular and molecular mechanisms of fat cell loss and improve clinical outcomes in humans.
Velocity‐selective arterial spin labeling perfusion MRI: A review of the state of the art and recommendations for clinical implementation
Authors: Qin Qin , Alsop David C. , Bolar Divya S. , Hernandez‐Garcia Luis , Meakin James , Liu Dapeng , Nayak Krishna S. , Schmid Sophie , van Osch Matthias J. P. , Wong Eric C. , Woods Joseph G. , Zaharchuk Greg , Zhao Moss Y. , Zun Zungho , Guo Jia ,   the ISMRMPerfusion Study Group
Published: July 2022

This review article provides an overview of the current status of velocity‐selective arterial spin labeling (VSASL) perfusion MRI and is part of a wider effort arising from the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group. Since publication of the 2015 consensus paper on arterial spin labeling (ASL) for cerebral perfusion imaging, important advancements have been made in the field. The ASL community has, therefore, decided to provide an extended perspective on various aspects of technical development and application. Because VSASL has the potential to become a principal ASL method because of its unique advantages over traditional approaches, an in‐depth discussion was warranted. VSASL labels blood based on its velocity and creates a magnetic bolus immediately proximal to the microvasculature within the imaging volume. VSASL is, therefore, insensitive to transit delay effects, in contrast to spatially selective pulsed and (pseudo‐) continuous ASL approaches. Recent technical developments have improved the robustness and the labeling efficiency of VSASL, making it a potentially more favorable ASL approach in a wide range of applications where transit delay effects are of concern. In this review article, we (1) describe the concepts and theoretical basis of VSASL; (2) describe different variants of VSASL and their implementation; (3) provide recommended parameters and practices for clinical adoption; (4) describe challenges in developing and implementing VSASL; and (5) describe its current applications. As VSASL continues to undergo rapid development, the focus of this review is to summarize the fundamental concepts of VSASL, describe existing VSASL techniques and applications, and provide recommendations to help the clinical community adopt VSASL.
Trout Responses to Stocking Rates and River Discharge within a Southeastern U.S. Hydropeaking Tailwater
Authors: Spurgeon Jonathan , Kaiser Joseph , Graham Christy , Lochmann Steve
Published: July 2022

Freshwater fish populations often exist in systems characterized by novel ecological processes resulting from human alteration. Salmonid populations embedded within coldwater sections of warmwater rivers are spatially constrained by habitat availability. Tailwater fish contend with fluctuating river discharges and density-dependent processes associated with fish stocking and exploitation. Salmonid populations sustained through stocking versus natural reproduction may respond differently to changes in hydrologic patterns (e.g., hydropeaking) as well as declines in fish abundance. We assessed differences between stocked (Rainbow Trout Oncorhynchus mykiss) and naturalized (Brown Trout Salmo trutta) trout populations in Greers Ferry tailwater, Arkansas, regarding (1) spatial and temporal patterns of mean length, electrofishing catch rates, and relative condition following reduced number of stocked Rainbow Trout and (2) evidence that hydrologic characteristics and fish stocking intensity influenced relative condition. A 56% reduction in Rainbow Trout stocking did not result in systemwide change in mean length or relative abundance for Rainbow Trout or Brown Trout over the 16-year study period. Hydrologic variability, where river discharge spanned both reduced and elevated levels, positively influenced condition of both Rainbow Trout and Brown Trout. Assessment of survival of stocked Rainbow Trout may aid in further refining the timing and amount of stocking needed to sustain the population at a desired abundance. Further, assessing the influence of stocking fewer but perhaps larger (in terms of mean length) fish to meet management goals may be warranted. The persistent differences in relative abundance among river sections can inform management actions directed at Brown Trout, including harvest regulations. Such regulations may aid in reaching desired management goals, including abundance and mean length targets not observed after reduced stocking.
A multisite focus group study of US adult women's beliefs and assumptions about bladder health and function
Authors: Williams Beverly Rosa , Burgio Kathryn L. , Hebert‐Beirne Jeni , James Aimee , Kenton Kimberly , LaCoursiere Daphne Yvette , Rickey Leslie , Brady Sonya S. , Kane Low Lisa , Newman Diane K. ,   Prevention of Lower Urinary Tract Symptoms (PLUS) Research Consortium
Published: July 2022

Aims

This analysis explored and characterized the ideas adult women have about how the bladder works, the assumptions guiding their bladder‐related behaviors, and the beliefs they hold about how their behaviors affect bladder health.

Methods

This was a directed content analysis of qualitative data from the Study of Habits, Attitudes, Realities, and Experiences, a focus group study conducted at seven United States research centers (July 2017 to April 2018). Participants were 316 adult women organized by four age categories (age range: 18−93 years). Analysis and interpretation focused on the “bladder assumptions and beliefs” code using a transdisciplinary lens and inductive approach.

Results

During their focus group discourse, participants exhibited a speculative mode of thinking about bladder health and function characterized by uncertainty about how the bladder works. They described the bladder as a mechanism for cleansing the body of impurities, viewing it as part of a larger interconnected bodily system to enable the body to stay healthy. They saw it as susceptible to anatomical changes, such as those related to pregnancy and aging. The women also postulated perceived relationships between bladder function and several health behaviors, including eating healthy foods, staying hydrated, engaging in physical activity and exercise, and adopting specific toileting and hygiene practices.

Conclusions

The findings underscore the importance of guidance from healthcare professionals and systematic community based educational programs for promoting women's understanding about bladder health and empowering them to exert agency to engage in healthy bladder behaviors.
Investigating the leaders' state of readiness in the Department of Telecommunications and Postal Services in South Africa to develop policy for the fourth industrial revolution
Authors: Maponya Cynthia M. , Naidoo Loganadhan Dalyiah
Published: July 2022

The study investigated the state of leadership readiness in the Department of Telecommunications and Postal Services (DTPS) to develop policy for the fourth industrial revolution (4IR). The DTPS is the lead Department in terms of 4IR within the Public Service and there are specific skills that are required within the DTPS to effectively lead in this regard. This study investigated the perceived gap between current skills and required skills in DTPS. The study adopted a qualitative method to obtain leaders' views and opinions by conducting structured and semi‐structured interviews. The nature of the study is exploratory. A total of 10 DTPS employees, both female and male on a 50/50 basis were interviewed on the skills of the leaders' state of readiness in developing policy for 4IR. The study findings identified an absence of problem‐solving, analytical, creative, technical, conflict management, collaboration and artificial intelligence, innovation and change management skills. It recommends that these competencies be included in the current Public Service Competency Assessment Framework that ensures that leaders are ready for policy development for 4IR.
The links among relative financial scarcity, thinking style, fatalism, and well‐being
Authors: Caballero Amparo , Fernández Itziar , Aguilar Pilar , Carrera Pilar
Published: July 2022

In the present research, we examined the links among relative financial scarcity, thinking style, fatalism, and well‐being and their roles in predicting protective behaviors against COVID‐19. Study 1 (N = 120) revealed that after an experimental manipulation to induce the perception of relative financial scarcity (versus financial abundance), people who perceived higher relative financial scarcity changed their thinking style to a more concrete mindset. In Study 2 (N = 873), the relative financial abundance–scarcity situation was measured, and the results showed that the greater the perceived relative financial scarcity was, the more concrete the mindset and the lower the sense of well‐being. Importantly, we found that individuals who felt poorer but maintained an abstract thinking style reported higher well‐being. Study 3 (N = 501) examined the influence of a concrete thinking style in people who perceived that their economic situation had worsened with the pandemic. The results showed that when this vulnerable population presented a more concrete mindset, they reported lower well‐being, higher fatalism, and lower protective behavior against COVID‐19. Thus, maintaining an abstract mindset promotes higher well‐being, lower fatalism, and greater protective behaviors against COVID‐19, even under economic difficulties. Because thinking style can be modified, our results encourage the development of new social intervention programs to promote an abstract mindset when people face important challenges.
Simulation‐based sequential design
Authors: Müller Peter , Duan Yunshan , Garcia Tec Mauricio
Published: July 2022

We review some simulation‐based methods to implement optimal decisions in sequential design problems as they naturally arise in clinical trial design. As a motivating example we use a stylized version of a dose‐ranging design in the ASTIN trial. The approach can be characterized as constrained backward induction. The nature of the constraint is a restriction of the decisions to a set of actions that are functions of the current history only implicitly through a low‐dimensional summary statistic. In addition, the action set is restricted to time‐invariant policies. Time‐dependence is only introduced indirectly through the change of the chosen summary statistic over time. This restriction allows computationally efficient solutions to the sequential decision problem. A further simplification is achieved by restricting optimal actions to be described by decision boundaries on the space of such summary statistics.
The cross‐over of statistical thinking and practices: A pandemic catalyst
Authors: Garrett Andrew D.
Published: July 2022

Written during the SARS‐CoV‐2 pandemic, and in recognition of Andy Grieve, the polymath, this article looks at an eclectic mix of topics where statistical thinking and practices should transcend typical dividing lines—with a particular focus on the areas of drug development, public health and social science. The case is made for embedding an experimental (or quasi‐experimental) framework within clinical practice for vaccines and treatments following their marketing authorisation. A similar case is made for public health interventions—facilitated by pre‐specification of effect size and by the greater use of data standards. A number of recommendations are made whilst noting that progress is being made in some areas.
From innovative thinking to pharmaceutical industry implementation: Some success stories
Authors: Walley Rosalind , Brayshaw Nigel
Published: July 2022

In industry, successful innovation involves not only developing new statistical methodology, but also ensuring that this methodology is implemented successfully. This includes enabling applied statisticians to understand the method, its benefits and limitations and empowering them to implement the new method. This will include advocacy, influencing in‐house and external stakeholders, such that these stakeholders are receptive to the new methodology. In this paper, we describe some industry successes and focus on our colleague, Andy Grieve's role in these.
Rationale for the update algorithm of the graphical approach to sequentially rejective multiple test procedures
Authors: Maurer Willi , Bretz Frank , Posch Martin
Published: July 2022

The graphical approach by Bretz et al. is a convenient tool to construct, visualize and perform multiple test procedures that are tailored to structured families of hypotheses while controlling the familywise error rate. A critical step is to update the transition weights following a pre‐specified algorithm. In their original publication, however, the authors did not provide a detailed rationale for the update formula. This paper closes the gap and provides three alternative arguments for the update of the transition weights of the graphical approach. It is a legacy of the first author, based on an unpublished technical report from 2014, and after his untimely death reconstructed by the other two authors as a tribute to Willi Maurer's collaboration with Andy Grieve and contributions to biostatistics over many years.
Domain adaptation metric learning method embedded with structural information for person re‐identification in internet of autonomous unmanned vehicles
Authors: Ni Tongguang , Zhu Chunyan , Qian Pengjiang
Published: July 2022

Internet of autonomous unmanned vehicles (IAUV) is a global network of sensors, robots, and autonomous vehicles. Person re‐identification (Re‐ID) is an important intelligent transportation application in IAUV, which needs to be solved using artificial intelligence algorithms. In this study, a domain adaptation metric learning method embedded with structural information (called DAML‐ESI) is designed for person Re‐ID in IAUV. Due to the lack of labeling information in the target domain, DAML‐ESI realizes person Re‐ID with the help of the discriminative and structural information of pedestrian images of related domains. DAML‐ESI projects pedestrian images selected from different domains into a common metric space and establishes a discriminative metric learning model, which requires that the positive sample pair be mapped to a point, and the distance distribution of the negative sample pair be mapped to a fixed value. The projection matrix learned by DAML‐ESI is used to eliminate the distribution differences between different domains, and the distance metric is used to ensure that the learned metric learning model has strong discriminative ability in the metric space. To verify the effectiveness of DAML‐ESI, experimental comparisons are conducted on three person Re‐ID datasets, and DAML‐ESI achieves satisfactory recognition performance.
Environmental factors have a major effect in shaping the gene expression of Siberian larch in the Altai Mountains of China
Authors: Liu Min , Liu Xiaobin , Zhou Peng , Jiang Shaowei , Huang Jian‐Guo , Dong Zhicheng
Published: July 2022

The differentiation of gene expression is an important link between genotype and phenotype and has important contributions to species adaptation and ecosystem evolution. As a major component of the world's forests, boreal forests play an important role in regulating the global climate, and the phenology of tree species has been and is undergoing changes during global warming. Here, to understand the impact of global warming on gene expression in boreal forest species, we used PacBio and Illumina sequencing methods to study the transcriptome of natural populations of Siberian larch (Larix sibirica Ledeb.) from the Altai Mountains in Xinjiang, China. We found that populations in this area had low genetic differentiation, but individuals were genetically clustered together when they had close geographic distance. Environmental factors, especially temperature, dominated differential gene expression of Siberian larch, while the contribution of genetic variation is relatively small. We speculate that Siberian larch adapts to changes in temperature and precipitation by altering its own gene expression. These results not only predict the tolerance of boreal forests to higher temperatures in the future, but also inform forest management strategies under global climate change.
Datum Problem Handling in Local Tie Surveys at Wettzell and Metsähovi
Authors: Kallio Ulla , Klügel Thomas , Marila Simo , Mähler Swetlana , Poutanen Markku , Saari Timo , Schüler Torben , Suurmäki Heli
Published: July 2022

The datum problem is a fundamental issue in the network adjustment when connecting a local measurement network to an external reference frame. Datum elements in 3D networks are scale, translation, and orientation. We consider here the local tie network at geodetic core stations, where the external reference frame is the latest ITRF realization, ITRF2014, in the mean epoch of terrestrial observations.

Accurate distance measurements are used for the determination of the network scale. Thus the improvement of its accuracy and the inclusion of weather measurements to account for refraction errors are essential. For rotation and translation of the network, we need external information. Angle observations are related to the coordinate system of the instrument (e.g. a tachymeter) which is usually aligned to the plumb line. Instruments have different vertical orientation at every station point and the direction of the plumb line does not coincide with the normal vector of the reference ellipsoid. Horizontally the observed set of angles are oriented in arbitrary or approximately oriented directions.

External information which is needed for solving the absolute orientation are datum points, providing the link to the global coordinate system, and correction terms for the vertical orientation (deflection of the vertical), which can be derived from combined terrestrial/GNSS observations, from a gravity based geoid model, or from astronomical observations.

In this article, we present the solutions/options for the datum problem in the framework of the EMPIR GeoMetre project using the example of the ITRF core stations Metsähovi and Wettzell using transformation-free approaches. The inclusion of distant targets is promising, since in small networks even a millimeter change in the coordinates of a datum point can significantly affect a local tie vector. It is shown that at both stations the determination of the deflection of the vertical using different techniques yield the same results within the measurement error.
Local Ties at SLR Station Riga
Authors: Salmins Kalvis , Sproģis Viesturs , Biļinskis Imants , del Pino Jorge
Published: July 2022

The SLR station Riga operates a SLR system within ILRS (Riga 18844401, DOMES number 12302S002) and a collocated GNSS system (RIGA00LVA, DOMES number 12302M002) within IGS and EUREF networks. The reference geodetic mark (DOMES number 12302M001) was used for the mobile SLR system MTLRS operation in 1991. Domes 12302M002 is situated on top of an historical time service building which sits directly on the bedrock. Both other points are placed on concrete foundations built more than 50 years ago. All these points are included in the ITRF database. The first full local ties set was determined in 1995 using a 6 h GPS session run using three GPS receivers. In 2018 three geodetic pillars were installed to improve the local geodetic network at the site. In January 2021, a multitechnique survey campaign produced a new set of local ties and reported to the ITRF and related services. The obtained results show that the local tie stability is at the subcentimeter level over a 25 years period. The true stability may be better, taking into account the measurement technology used in the first survey 25 years ago. But to verify it we need to do more surveys.
A Nonzero Set Problem with Aumann Stochastic Integral
Authors: Li Jungang , Meng Le
Published: July 2022

A nonzero set problem with Aumann set-valued random Lebesgue integral is discussed. This paper proves that the Aumann Lebesgue integral’s representation theorem. Finally, an important inequality is proved and other properties of Lebesgue integral are discussed.
Multivariate Passenger Flow Forecast Based on ACLB Model
Authors: Zheng Lin , Qi Chaowei , Zhao Shibo
Published: July 2022

With the rapid increase in urban population, urban traffic problems are becoming severe. Passenger flow forecasting is critical to improving the ability of urban buses to meet the travel needs of urban residents and alleviating urban traffic pressure. However, the factors affecting passenger flow have complex non-linear characteristics, which creates a bottleneck in passenger flow prediction. Deep learning models CNN, LSTM, BISTM and the gradually emerging attention mechanism are the key points to solve the above problems. Based on summarizing the characteristics of various models, this paper proposes a multivariate prediction model ACLB to extract the nonlinear spatio-temporal characteristics of passenger flow data. We compare the performance of ACLB model with CNN, LSTM, BILSTM, CNN-LSTM, FCN-ALSTM through experiments. ACLB performance is better than other models.
The Research on Fishery Metadata in Bohai Sea Based on Semantic Web
Authors: Du Meifang
Published: July 2022

In this paper, a data sharing and management mechanism suitable for the characteristics of fishery industry was established to clarify the phenomenon of heterogeneous Web data and Information Island based on Semantic Web technology, and unified interface specification information platform was established. Form the specification of metadata from the physical and chemical database, developing and publishing the corresponding metadata management tool, assisting, assisting and guiding a specialized database centre, completing the construction of metadata from the professional database.
Design of Portable Intelligent Traffic Light Alarm System for the Blind
Authors: Tang Lili
Published: July 2022

The system is composed of STC single chip microcomputer, color signal recognizer and sensor control module, wireless communication control module, voice and video synthesizer and broadcast control module. STC MCU adopts STC89C52; color recognition sensor module uses gy-33 color recognition sensor, which can identify the current traffic light conditions; wireless communication module uses nRF24L01 made by Nordic company, which needs to be installed at the sending end and the receiving end to send the current traffic light information; the speech synthesis broadcasting module uses the TTS speech synthesis broadcasting module xfs5152ce of iFLYTEK, after data recognition and analysis, it finally sends voice alarm about traffic lights to the blind, so as to effectively guide the blind whether it can pass through, so as to ensure the safety of the blind. This design combines artificial intelligence with daily life, which not only meets the development trend of the information age, but also meets the needs of the current society. It has a broad market prospect in the application of intelligent travel.
Research on Interdomain Routing Control in SDN Architecture
Authors: Chen Liangzhe , Zhu Yin , Sun Xinyu , Zhang Yinlin , Min Gang , Zou Yang , Shu Zhong
Published: July 2022

Aiming at the difficulty of network management due to the coexistence of traditional BGP network and new SDN network, this paper proposes a routing update algorithm with clear interdomain structure and network exception handling ability. By defining SDN, BGP-SDN fusion and BGP three network domains, a packet transmission path with route discovery and update capability were formed through the three network domains in sequence. On the premise of reducing the communication delay range, the route update delay is set, and the exception handling mechanism is introduced. Specify the master controller to make the Interzone routing control rules and make routing updates a key parameter in the data flow table of border switches. The algorithm firstly ensures the absolute unimpeded communication between network domains, provides a reliable time guarantee for network exception handling, enhances the connection between control servers between network domains and between control servers and boundary switches, and improves the synchronization of multiple links in network communication. By using Mininet to build a simulation experiment platform, the reliability and feasibility of the proposed algorithm are verified from the perspectives of data packet loss and Interzone route update delay, and it is suitable for application and implementation in the current Internet environment.
Multidimensional Data Analysis Based on LOGIT Model
Authors: Gan Jiahua , Zhang Meng , Xiao Yun
Published: July 2022

Logit Model is an important method for empirical analysis of multi-source data. In order to explore the traffic safety mechanism, The Paper taked traffic behavior data as an example, researched personal characteristics of truck drivers, Analyzed the influence of the driver’s personal traits on traffic violations. Based on the binary logistics regression model, the analysis model of traffic violations was established. The results show that personality, driver’s license level, daily driving time, transportation route, vehicle ownership, and occupational disease are important factors that affect drivers’ violations. Further data analysis shows that truck drivers with bile personalities, driving for more than 12 h per day, no fixed transportation routes, and vehicles with loans have the highest probability of violations. The data analysis conclusion provides data basis for truck driver management and improving truck traffic safety.
Leveraging Modern Big Data Stack for Swift Development of Insights into Social Developments
Authors: Huang He , He Yixin , Zhang Longpeng , Zeng Zhicheng , Ouyang Tu , Zeng Zhimin
Published: July 2022

Insights of social development, presented in various forms, such as metrics, figures, text summaries, whose purpose is to summarize, explain, and predict the situations and trends of society, is extremely useful to guide organizations and individuals to better realize their own objectives in accordance with the whole society. Deriving these insights accurately and swiftly has become an interest for a range of organizations, including agencies governing districts, city even the whole country, they use these insights to inform policy-makings. Business investors who peak into statistical numbers for estimating current economical situations and future trends. Even for individuals, they could look at some of these insights to better align themselves with macroscopical social trends. There are many challenges to develop these insights in a data-driven approach. First, required data come from a large number of heterogeneous sources in a variety of formats. One single source’s data could be in the size of hundreds of Gigabytes to several TeraBytes, ingesting and governing such huge amount of data is not a small challenge. Second, many complex insights are derived by domain human experts in a trail-and-error fashion, while interacting with data with the aid of computer algorithms. To quickly experiment various algorithms, it asks for software capabilities for infusing human experts and machine intelligence together, this is challenging but critical for success.

By designing and implementing a flexible big data stack that could bring in a variety of data components. We address some of the challenges to infuse data, computer algorithm and human together in Zilian Tech company [20]. In this paper we present the architecture of our data stack and articulate some of the important technical choices when building such stack. The stack is designed to be equipped with scalable storage that could scale up to PetaBytes, as well as elastic distributed compute engine with parallel computing algorithms. With these features the data stack enables a) swift data analysis, by human analysts interacting with data and machine algorithms via software support, with on-demand question answering time reduced from days to minutes; b) agile building of data products for end users to interact with, in weeks if not days from months.
Technological Intervention of Sleep Apnea Based on Semantic Interoperability
Authors: Liang Ying , Gao Weidong , Chuai Gang , Hu Dikun
Published: July 2022

Sleep apnea is an important factor that could affect sleep quality. A great number of existing monitoring and intervention devices, such as the polysomnography, mature heart rate respiratory monitoring bracelets and ventilator headgear can improve breathing in sleep, but are all functioning separately, with their data being disconnected, which fails to achieve multi-parameter fusion or a greater variety of applications. With the development of the Internet of Things (IoT), information interaction between IoT devices to facilitate integration of IoT devices has become a hot research topic. This paper focuses on the interoperability information model and technology for establishing interoperability information model among sleep and health devices for sleep apnea syndrome. This paper analyzes the heterogeneity of the knowledge organization system in sleep health data information through the abstract representation of data information, establishes the mapping relationship between data, information, and devices, and realizes the semantic heterogeneity elimination. It also defines inference rules about sleep apnea scenarios, achieves semantic interoperability between monitoring devices and other health devices, and finally realizes an unmonitored closed-loop control system for sleep apnea intervention. According to the test results, the system can react quickly in sleep apnea scenarios.
Research on Visualization of Power Grid Big Data
Authors: Zhou Jun , Tang Lihe , Shi Songyuhao , Li Wei , Hu Pan , Wang Feng
Published: July 2022

With the constant improvement of power grid planning and management requirements and the gradual advancement of the urbanization process, the problems that need to be taken into account in the planning process are increasing, especially the demand for big data visualization of the power grid has increased sharply. About 80% of the information that humans obtain from the external environment comes from the visual system. A picture is worth a thousand words. A good visualization platform can monitor the overall operation of the power grid, which is convenient for analyzing and monitoring the operation of power supply companies to provide customers with high-quality services. The platform can complete the interactive simulation of different services, and can display the monitoring and analysis of the power grid through a rich visual interface, which is convenient for people to understand the real-time status of the power grid. This paper uses various advanced visualization technologies and data module algorithms at home and abroad to cooperate with the monitoring network to realize the visualization platform of power grid big data, promote the further development of power grid big data applications, and form a big data standard system for power big data technology research, product research and development, and pilot construction.
Research on Positioning Technology of Facility Cultivation Grape Based on Transfer Learning of SSD MobileNet
Authors: Han Kaiyuan , Xu Minjie , Li Shuangwei , Xu Zhifu , Ye Hongbao , Hua Shan
Published: July 2022

There is an urgent need of developing grape picking robot with intelligent recognition function due to the decrease of grape picking workers’ population. Acquiring the 3D information of picking coordinate is the key process of constructing intelligent picking equipment. In this paper, based on SSD MobileNet neural network model, transfer learning and central deviation angle method were used to realize the positioning of picking coordinate points of facility cultivation grape by machine vision. After testing 720 fruit labels, 633 stem labels and 603 leaf labels labelled by pretreatment, the general precision was 79.5%, which was close to the inherent accuracy of the original model before transfer learning.
A Brief Comparison of K-means and Agglomerative Hierarchical Clustering Algorithms on Small Datasets
Authors: Abdalla Hassan I.
Published: July 2022

In this work, the agglomerative hierarchical clustering and K-means clustering algorithms are implemented on small datasets. Considering that the selection of the similarity measure is a vital factor in data clustering, two measures are used in this study - cosine similarity measure and Euclidean distance - along with two evaluation metrics - entropy and purity - to assess the clustering quality. The datasets used in this work are taken from UCI machine learning depository. The experimental results indicate that k-means clustering outperformed hierarchical clustering in terms of entropy and purity using cosine similarity measure. However, hierarchical clustering outperformed k-means clustering using Euclidean distance. It is noted that performance of clustering algorithm is highly dependent on the similarity measure. Moreover, as the number of clusters gets reasonably increased, the clustering algorithms’ performance gets higher.
Based on Internet of Things Platform Using NB-IoT Communication Low-Power Weather Station System
Authors: Wang Zhenxin , Deng Zhi , Xu Ke , Zhang Ping , Liu Tao
Published: July 2022

In recent years, meteorological environment has become a topic of concern to people. Various meteorological disasters threaten human life and production. Accurate and timely acquisition of meteorological data has become a prerequisite for dealing with various aspects of production and life, and also laid a foundation for weather prediction. For a long time, meteorological data acquisition system combined with modern information technology has gradually become a hot spot in the field of meteorological monitoring and computer research. The continuous development of NB-IoT technology has brought new elements to the research of meteorological monitoring system. This paper designs a weather station system based on NB-IoT, including data acquisition module, main controller module, NB-IoT wireless communication module, energy capture module, low power consumption scheme, etc.
Traffic Sign Detection Based on Improved YOLOv3 in Foggy Environment
Authors: Ma Luxi , Wu Qinmu , Zhan Yu , Liu Bohai , Wang Xianpeng
Published: July 2022

Aiming at the problem of poor detection accuracy and inaccurate positioning of traffic signs under foggy conditions, this paper proposes an improved YOLOv3 detection algorithm. Firstly, a data set of Chinese traffic signs in a foggy environment is constructed; The dark channel a priori algorithm based on guided filtering is used to process the image with fog, which overcomes the problem of image quality degradation caused by fog. Mosaic data enhancement is performed on the annotated data set image, which speeds up the convergence speed of the network. Increased the feature scale of YOLOv3 algorithm. The loss function of the network is optimized, CIOU is used as the positioning loss, and the positioning accuracy is improved. At the same time, the method of transfer learning is used to overcome the problem of insufficient samples. The enhanced yolov3 algorithm proposed in this paper has higher detection accuracy and shorter detection time than the standard yolov3 algorithm and SSD algorithm.