A Literature Review: Potential Effects That Health Apps on Mobile Devices May Have on Patient Privacy and Confidentiality

Purpose: This research aims to evaluate the potential threats to patient privacy and confidentiality posed by mHealth applications on mobile devices. Methodology: A comprehensive literature review was conducted, selecting eighty-eight articles published over the past fifteen years. The study assessed data gathering and storage practices, regulatory adherence, legal structures, consent procedures, user education, and strategies to mitigate risks. Results: The findings reveal significant advancements in technologies designed to safeguard privacy and facilitate the widespread use of mHealth apps. However, persistent ethical issues related to privacy remain largely unchanged despite these technological strides.

The Alzheimer’s Dementia Patients’ Observed Illness Course and Experience in Ghana and Care Lessons to Be Learnt: A Mental Health Professional’s Perspective

Alzheimer’s disease (AD) and associated dementia patient numbers continue to increase globally with associated economic costs to healthcare systems. Of note is the increase in numbers in lower and middle-income countries (LMICs) including Sub-Saharan African (SSA) countries, which already face challenges with their health budgets from communicable and non-communicable diseases. Ghana, an SSA country, faces the problem of healthcare budgetary difficulties and the additional impact of AD as a consequence of increasing population strata of old aged persons (OAPs) due to the demographic transition effect. This article uses examples of known patients’ illness courses to give a perspective on the lived experience of patients with dementia (PWD) in Ghana, living amongst a populace with a culture of stigmatization of PWD, and a relatively fragile public mental health system (PMHS) for those with mental illness, including AD. The lived experience of AD patients is characterised by stigmatisation, discrimination, non-inclusiveness, diminished dignity and human rights abuses in the face of their mental disability, and eventually death. This article is an advocacy article giving voice to the voiceless and all persons suffering from AD and other dementias in Ghana, whilst pleading for a call to action from healthcare professionals and responsible state agencies.

Expectations and Level of Satisfaction of the Patient with Parkinson’s Disease Undergoing Deep Brain Stimulation Surgery at the National Institute of Neurology and Neurosurgery

Background: Deep brain stimulation (DBS) is an established treatment for patients with advanced Parkinson’s disease (PD). Reports show continued patient satisfaction after surgery despite not maintaining clinical improvement as measured by evolution scales. Objectives: The present study sought to explore expectations and level of satisfaction in patients after DBS surgery with a semi-structured questionnaire and subsequent correlation with functional scales, Quality of Life (QoL), and motor and non-motor symptoms. Methods: We performed descriptive statistics to represent demographic data, Wilcoxon rank tests to determine significant differences, and Spearman correlation between the applied scales. Results: We evaluated 20 patients with a history of DBS surgery. 45% were female, with a mean age of 55.7 ± 14.15 years, a mean disease duration of 13.42 ± 8.3 years, and a mean time after surgery of 3.18 ± 1.86 years. Patients reported surgery meeting expectations in 85.5% and continued satisfaction in 92%. These two variables showed a significant correlation. Conclusions: This sample of patients remained satisfied after DBS surgery, although we found no differences in motor and non-motor clinimetric scales. Further studies are needed to confirm the importance of assessing quality of life in patients with DBS.

基于数据流的K-S变化检测的动态多目标规划算法

为了更加准确地判断环境是否发生变化并快速追踪动态多目标规划问题(dynamicmulti-objectiveoptimization problem,DMOP)当前时刻的Pareto前沿,提出了一种基于数据流的Kolmogorov-Smirnov(K-S)变化检测的动态多目标规划(DSK-SDMOP)算法。该算法以NSGA-Ⅱ为基础,通过数据流建立2个时刻的检验窗口,再利用K-S检验基于数据流的Pareto最优前沿是否发生变化,检测2个窗口的数据是否服从同一分布来判断环境是否发生变化,并就环境变化的剧烈程度实行相应的应答机制,以提高对环境的适应程度。利用基于数据流的K-S检测方法,对环境变化不会过于敏感,而且不用提前假设对应目标值的分布,易于操作。通过5个动态多目标规划标准测试函数对该算法进行测试,并和现有的2种算法进行对比分析,结果表明该算法处理动态多目标规划问题具有良好的性能。

三维各向异性TI介质中的P/S波快速解耦技术及在弹性波逆时偏移中的应用

随着多分量采集技术的发展,弹性波逆时偏移技术在三维各向异性介质复杂地质构造成像中得到了广泛的应用.然而耦合的P波场和S波场,会在传播过程中产生串扰噪声,降低弹性波逆时偏移的成像精度.为了解决这一问题,本研究针对具有倾斜各向异性对称轴的三维横向各向同性(Transverse Isotropy,TI)介质,提出了一种矢量弹性波场快速解耦方法,可以有效提高偏移剖面的成像质量.该方法首先通过坐标转换,将观测系统坐标系的垂直轴旋转到TI介质的对称轴方向,在新坐标系下,根据具有垂直对称轴的三维横向各向同性(Vertical Transverse Isotropy,VTI)介质中的分解算子,推导出三维TI介质解耦算子表达式.接着引入一种在空间域快速计算分解波场的方法,来实现空间域矢量P波场和S波场分离,极大地提高了计算效率.最后,通过点积成像条件,将提出的P/S波分解方法引入到三维TI介质弹性波逆时偏移中,得到高精度的PP和PS成像.与以往的波场分解方法相比,本文方法具有数值稳定和计算效率高的特点.数值算例表明,应用上述三维TI分解算子得到的偏移剖面有效压制了噪声,提高了成像质量.

基于D-S证据理论的农作物气候品质预测方法研究:以晚熟杂交柑橘春见为例

【目的】基于多源气象数据构建果实品质(糖含量等级)预测模型,为科学评价果实气候品质及深入挖掘农产品气候资源提供科学依据。【方法】以晚熟柑橘春见果实为研究对象,利用多源数据融合技术、人工神经网络(BP神经网络、RBF神经网络和Elman神经网络)和D-S证据理论,包括气象数据质量控制、特征选取、特征级融合、决策级融合4个步骤,构建基于多源气象数据的果实品质(糖含量等级)预测模型。【结果】春见果实品质预测模型采用BP神经网络预测结果总体准确率为87.50%,平均绝对误差(MAE)为0.150,均方根误差(RMSE)为0.447;RBF神经网络预测结果总体准确率为85.00%,MAE为0.175,RMSE为0.474;Elman神经网络预测结果总体准确率为87.50%,MAE为0.150,RMSE为0.447;D-S证据理论决策融合总体预测准确率达95.20%,分别较BP神经网络、RBF神经网络和Elman神经网络提升7.7百分点、10.2百分点和7.7百分点,MAE和RMSE分别为0.040和0.214,均明显降低。【结论】D-S证据理论决策融合后的果实品质预测准确率相比单一神经网络预测更高、误差更小。

An accessible strong-motion dataset(PGA,PGV,and site v_(S30))of 2022 M_(S)6.8 Luding,China Earthquake

A M_(S)6.8 earthquake occurred on 5th September 2022 in Luding county,Sichuan,China,at 12:52 Beijing Time(4:52 UTC).We complied a dataset of PGA,PGV,and site vS30 of 73 accelerometers and 791 Micro-Electro-Mechanical System(MEMS)sensors within 300 km of the epicenter.The inferred v_(S30)of 820 recording sites were validated.The study results show that:(1)The maximum horizontal PGA and PGV reaches 634.1 Gal and 71.1 cm/s respectively.(2)Over 80%of records are from soil sites.(3)The v_(S30)proxy model of Zhou J et al.(2022)is superior than that of Wald and Allen(2007)and performs well in the study area.The dataset was compiled in a flat file that consists the information of strong-motion instruments,the strong-motion records,and the v_(S30)of the recording sites.The dataset is available at https://www.seismisite.net.

基于S⁃G滤波算法的航空器着陆阶段滑行轨迹修正研究

对航空器着陆阶段运行轨迹分析是客观评价飞行员技术水平与航司运行品质的重要手段,在保障航空器安全高效运行等方面具有重要意义。通过对QAR数据中经纬度参数在地图软件中打点分析发现,航空器在跑道上减速滑行阶段轨迹出现明显的曲折、错位与偏移现象。采用S⁃G滤波算法,构建航空器着陆阶段轨迹修正模型,对航迹进行修正处理。结果表明,S⁃G滤波算法修正模型可对原始航迹进行良好修正。

A data assimilation-based forecast model of outer radiation belt electron fluxes

Because radiation belt electrons can pose a potential threat to the safety of satellites orbiting in space,it is of great importance to develop a reliable model that can predict the highly dynamic variations in outer radiation belt electron fluxes.In the present study,we develop a forecast model of radiation belt electron fluxes based on the data assimilation method,in terms of Van Allen Probe measurements combined with three-dimensional radiation belt numerical simulations.Our forecast model can cover the entire outer radiation belt with a high temporal resolution(1 hour)and a spatial resolution of 0.25 L over a wide range of both electron energy(0.1-5.0 MeV)and pitch angle(5°-90°).On the basis of this model,we forecast hourly electron fluxes for the next 1,2,and 3 days during an intense geomagnetic storm and evaluate the corresponding prediction performance.Our model can reasonably predict the stormtime evolution of radiation belt electrons with high prediction efficiency(up to~0.8-1).The best prediction performance is found for~0.3-3 MeV electrons at L=~3.25-4.5,which extends to higher L and lower energies with increasing pitch angle.Our results demonstrate that the forecast model developed can be a powerful tool to predict the spatiotemporal changes in outer radiation belt electron fluxes,and the model has both scientific significance and practical implications.

Detection of Alzheimer’s disease onset using MRI and PET neuroimaging:longitudinal data analysis and machine learning

The scientists are dedicated to studying the detection of Alzheimer’s disease onset to find a cure, or at the very least, medication that can slow the progression of the disease. This article explores the effectiveness of longitudinal data analysis, artificial intelligence, and machine learning approaches based on magnetic resonance imaging and positron emission tomography neuroimaging modalities for progression estimation and the detection of Alzheimer’s disease onset. The significance of feature extraction in highly complex neuroimaging data, identification of vulnerable brain regions, and the determination of the threshold values for plaques, tangles, and neurodegeneration of these regions will extensively be evaluated. Developing automated methods to improve the aforementioned research areas would enable specialists to determine the progression of the disease and find the link between the biomarkers and more accurate detection of Alzheimer’s disease onset.

Innovative Applications of Patient Experienee Big Data in Modern Hospital Management Improve Healthcare Quality

It is important for modern hospital management to strengthen medical humanistic care and build a harmonious doctor-patient relationship.Innovative applications of the big data resources of patient experience in modern hospital management facilitate hospital management to realize real-time supervision,dynamic management and s&entitle decision-making based on patients experiences.It is helping the transformation of hospital management from an administrator^perspective to a patients perspective,and from experience-driven to data-driven.The technological innovations in hospital management based on patient experience data can assist the optimization and continuous improvement of healthcare quality,therefore help to increase patient satisfaction to the medical services.

Forecasting patient demand at urgent care clinics using explainable machine learning

Urgent care clinics and emergency departments around the world periodically suffer from extended wait times beyond patient expectations due to surges in patient flows.The delays arising from inadequate staffing levels during these periods have been linked with adverse clinical outcomes.Previous research into forecasting patient flows has mostly used statistical techniques.These studies have also predominately focussed on short‐term forecasts,which have limited practicality for the resourcing of medical personnel.This study joins an emerging body of work which seeks to explore the potential of machine learning algorithms to generate accurate forecasts of patient presentations.Our research uses datasets covering 10 years from two large urgent care clinics to develop long‐term patient flow forecasts up to one quarter ahead using a range of state‐of‐the‐art algo-rithms.A distinctive feature of this study is the use of eXplainable Artificial Intelligence(XAI)tools like Shapely and LIME that enable an in‐depth analysis of the behaviour of the models,which would otherwise be uninterpretable.These analysis tools enabled us to explore the ability of the models to adapt to the volatility in patient demand during the COVID‐19 pandemic lockdowns and to identify the most impactful variables,resulting in valuable insights into their performance.The results showed that a novel combination of advanced univariate models like Prophet as well as gradient boosting,into an ensemble,delivered the most accurate and consistent solutions on average.This approach generated improvements in the range of 16%-30%over the existing in‐house methods for esti-mating the daily patient flows 90 days ahead.

Intensive care environment: Perspective of relatives of critically ill patient sustained by health technology

The intensive care unit(ICU)is a complex setting by nature,and some have described it as bizarre due to its numerous sirens that sound when anything is dangerous,constant activity,equipment,bright lights,and high fatality rate.The demands placed on nurses to care for critically ill patients in this environment frequently prevent nurses and other health‑care professionals from acknowledging the feelings of patient’s relatives or family caregivers,resulting in a hostile environment from the patient’s relative’s perspective.When a patient’s family enters the ICU,they feel that hospital administrators do little to nothing to alleviate their discomfort and fear.Despite research demonstrating the importance of providing a homely environment for patients’families,In Nigeria ICU is still far behind how a conventional ICU environment should be structured to accommodate patient’s relations in the unit.The goal of this study was to look at the patient’s relative’s perspective on providing care for a critically ill patient in an ICU,with a focus on the unit’s complexity and overall experience.Based on the findings of this study,we recommend that hospital administrators ensure that the environment of the upcoming ICU is designed to meet the needs of patient’s relatives by addressing identified environmental concerns,like caring neglect,by providing a friendly and stress‑free environment.

Crohn’s disease in human immunodeficiency virus-infected patient:A case report

BACKGROUND Inflammatory bowel disease(IBD)is an autoimmune condition treated with immunosuppressive drugs.However,the need for immune system suppression becomes questionable when infection with the human immunodeficiency virus(HIV)occurs simultaneously and impacts the course of IBD.Our reported case represents the clinical course,prescribed treatment and its effect,as well as clinical challenges faced by physicians in a combination of such diseases.We also present a comprehensive literature review of similar cases.CASE SUMMARY A 49-year-old woman suffering from a newly diagnosed Crohn’s disease was hospitalized due to exacerbated symptoms(abdominal pain,fever,and weight loss).During her hospital stay,she tested positive for HIV.With conservative treatment,the patient improved and was discharged.In the outpatient clinic,her HIV infection was confirmed as stage C3,and antiretroviral treatment was initiated immediately.That notwithstanding,soon the patient was rehospitalized with pulmonary embolism and developed a series of complications because of the subsequent coexistence of IBD and HIV.After intensive and meticulous treatment,the patient’s condition has improved and she remains in remission.CONCLUSION The paucity of studies and data on the coexistence of HIV and IBD leaves clinicians doubting the optimal treatment options.

Clinical Utilization of Nursing Process in Improving Patient’s Outcome and Its Associated Factors: A Cross-Sectional Study among Nurses and Midwives Working at Njombe Regional Referral Hospital, Tanzania

Background: Improvement of patient care in any hospital depends primarily on the quality of nursing care. Nursing care is enhanced by the nursing process, which outlines the nursing activities to be provided for a patient. Methods and Materials: A cross sectional design employing quantitative methods was conducted in Njombe RRH in December 2021. Quantitative data were collected from nurses and midwives from all wards by simple random sampling techniques using a sample-size calculator. SPSS version 26.0 was used to analyse data whereby a p-value of 0.05 was considered a decision mark for the significance of the result;Chi-square and Logistic regression respectively were used to find out the association and its strength between variables. Result: Majority of the respondents, 41 (85.4%), had inadequate knowledge and 33 (68.8%) found them people with a negative attitude to the nursing process. Significantly, there is an association between knowledge and clinical utilization (AOR 2.24;95% CI: 1.6 - 2.5;P 0.04), attitude and clinical utilization (AOR 4.32;95% CI: 1.8 - 3.7;P Conclusion: A knowledge gap in relation to the utilization of the nursing process and a negative attitude were noted to be associated significantly with the utilization of the nursing process among nurses and midwives. It is recommended on-job training, supportive supervision, and Value Clarification and Attitude Transformation (VCAT) are the best interventions to address the knowledge gap and negative attitudes respectively.

Effects of Physical Exercise and Music Therapy on Cognitive Aspects in Tunisian Patients with Mild Alzheimer’s Type Dementia

Aim: The objective of this research is to highlight the effectiveness of physical exercise and music therapy in older patients with Alzheimer’s disease (AD). Methods: Patients with a mild level of AD were included in this study, divided into the therapy group (TG;N = 30, aged 68 ± 3.2 years) and the control group (CG;N=30, aged 65 ± 2.6 years). The therapy group was enrolled in an exercise-training program (walking, resistance and balance exercises) combined with musical therapy for 10 weeks (three sessions of 60 minutes per week). The Control group was instructed to follow their daily rhythm of life (e.g., rest, reading) under the same conditions. The intervention program was enrolled under the supervision of;one psychologist;a neurologist;two music therapists, and two physiotherapists, all belonging to the same hospital unit. After 10 weeks of participation in the combined program, cognitive parameters were improved in the therapy group measured with the Behavior Pathology in Alzheimer Disease (BEHAVE-AD), (p < 0.05) for activity disturbance, diurnal rhythm disturbances, anxieties and phobias, affective disturbance. The percentage range of improvements is 1.07% to 2.96%. Results: Our results demonstrate that physical exercise combined with music therapy improves cognitive function in patients with Alzheimer’s disease. Conclusions: Physical exercise and music therapy are beneficial combined treatments for improving life quality in older patients. This approach may be useful to help patients with a mild level of Alzheimer’s disease improve their behavioral and psychological parameters.

Exploring the Impact of Factors Affecting the Lifespan of HIVs/AIDS Patient’s Survival: An Investigation Using Advanced Statistical Techniques

This study investigates the impact of various factors on the lifespan and diagnostic time of HIV/AIDS patients using advanced statistical techniques. The Power Chris-Jerry (PCJ) distribution is applied to model CD4 counts of patients, and the goodness-of-fit test confirms a strong fit with a p-value of 0.6196. The PCJ distribution is found to be the best fit based on information criteria (AIC and BIC) with the smallest negative log-likelihood, AIC, and BIC values. The study uses datasets from St. Luke hospital Uyo, Nigeria, containing HIV/AIDS diagnosis date, age, CD4 count, gender, and opportunistic infection dates. Multiple linear regression is employed to analyze the relationship between these variables and HIV/AIDS diagnostic time. The results indicate that age, CD4 count, and opportunistic infection significantly impact the diagnostic time, while gender shows a nonsignificant relationship. The F-test confirms the model's overall significance, indicating the factors are good predictors of HIV/AIDS diagnostic time. The R-squared value of approximately 72% suggests that administering antiretroviral therapy (ART) can improve diagnostic time by suppressing the virus and protecting the immune system. Cox proportional hazard modeling is used to examine the effects of predictor variables on patient survival time. Age and CD4 count are not significant factors in the hazard of HIV/AIDS diagnostic time, while opportunistic infection is a significant predictor with a decreasing effect on the hazard rate. Gender shows a strong but nonsignificant relationship with decreased risk of death. To address the violation of the assumption of proportional hazard, the study employs an assumption-free alternative, Aalen’s model. In the Aalen model, all predictor variables except age and gender are statistically significant in relation to HIV/AIDS diagnostic time. The findings provide valuable insights into the factors influencing diagnostic time and survival of HIV/AIDS patients, which can inform interventions aimed at reducing transmission and improving early diagnosis and treatment. The Power Chris-Jerry distribution proves to be a suitable fit for modeling CD4 counts, while multiple linear regression and survival analysis techniques provide insights into the relationships between predictor variables and diagnostic time. These results contribute to the understanding of HIV/AIDS patient outcomes and can guide public health interventions to enhance early detection, treatment, and care.

Exploring the Impact of Factors Affecting the Lifespan of HIVs/AIDS Patient’s Survival: An Investigation Using Advanced Statistical Techniques

This study investigates the impact of various factors on the lifespan and diagnostic time of HIV/AIDS patients using advanced statistical techniques. The Power Chris-Jerry (PCJ) distribution is applied to model CD4 counts of patients, and the goodness-of-fit test confirms a strong fit with a p-value of 0.6196. The PCJ distribution is found to be the best fit based on information criteria (AIC and BIC) with the smallest negative log-likelihood, AIC, and BIC values. The study uses datasets from St. Luke hospital Uyo, Nigeria, containing HIV/AIDS diagnosis date, age, CD4 count, gender, and opportunistic infection dates. Multiple linear regression is employed to analyze the relationship between these variables and HIV/AIDS diagnostic time. The results indicate that age, CD4 count, and opportunistic infection significantly impact the diagnostic time, while gender shows a nonsignificant relationship. The F-test confirms the model's overall significance, indicating the factors are good predictors of HIV/AIDS diagnostic time. The R-squared value of approximately 72% suggests that administering antiretroviral therapy (ART) can improve diagnostic time by suppressing the virus and protecting the immune system. Cox proportional hazard modeling is used to examine the effects of predictor variables on patient survival time. Age and CD4 count are not significant factors in the hazard of HIV/AIDS diagnostic time, while opportunistic infection is a significant predictor with a decreasing effect on the hazard rate. Gender shows a strong but nonsignificant relationship with decreased risk of death. To address the violation of the assumption of proportional hazard, the study employs an assumption-free alternative, Aalen’s model. In the Aalen model, all predictor variables except age and gender are statistically significant in relation to HIV/AIDS diagnostic time. The findings provide valuable insights into the factors influencing diagnostic time and survival of HIV/AIDS patients, which can inform interventions aimed at reducing transmission and improving early diagnosis and treatment. The Power Chris-Jerry distribution proves to be a suitable fit for modeling CD4 counts, while multiple linear regression and survival analysis techniques provide insights into the relationships between predictor variables and diagnostic time. These results contribute to the understanding of HIV/AIDS patient outcomes and can guide public health interventions to enhance early detection, treatment, and care.

Evaluation of the Protégé^(TM) stent in the treatment of carotid artery stenosis with adjunctive use of a filter Embolic Protection Device (PROCAR)-one-month follow-up data on 77 patients

Objective The trial was designed to evaluate the safety and performance of the ev3 Protégé TM stent in the treatment of de novo or re-stenotic common and/or internal carotid artery stenoses with adjunctive use of a CE-marked filter embolic protection device.Methods This study was a prospective multi-center, single-arm trial. Between June and October 2003, 77 patients were enrolled in 8 investigational centers throughout Europe. The primary endpoint was the incidence of Major Neurological Events (MANE) through one month. Other endpoints were the ability to properly place the stent, and primary patency and MANE after six months. Eligible for the study were patients with a de novo or restenotic target lesion located in the common and/or internal carotid artery (>70% stenosis for asymptomatic and >50% stenosis for symptomatic patients). The ev3 Spider (Embolic Protection Filter was used in 75 of 77 cases. Results In 76 out of the 77 patients (99%), the stent could be successfully implanted with a residual stenosis ≤30% as criterion. Of the 74 patients that had a carotid ultrasound at one month follow-up, none had a re-stenosis of the target lesion. There were three MANEs during or immediately after the procedure (3.9%), two were major and one was a minor stroke. There were eight severe complications (9.1%); six of these happened during or immediately after the procedure and were related to the procedure, none was related to the device. They are resolved without sequelae. No deaths have occurred.Conclusions The Protégé stent is safe and performs well in the treatment of carotid artery stenosis. The technical success rate for placement of the Protégé stent as assessed by the residual stenosis post implant was very high and all stents were successfully deployed. The incidence of MANE was comparable with that in other recent carotid stent studies and still lower than standard CEA.

A Survey of English Translation Studies of Lu You’s Poetry Based on the Data Analysis of Domestic Academic Journals (2001-2022)

This article presents a comprehensive analysis of the current state of research on the English translation of Lu You’s poetry, utilizing a data sample comprising research papers published in the CNKI Full-text Database from 2001 to 2022. Employing rigorous longitudinal statistical methods, the study examines the progress achieved over the past two decades. Notably, domestic researchers have displayed considerable interest in the study of Lu You’s English translation works since 2001. The research on the English translation of Lu You’s poetry reveals a diverse range of perspectives, indicating a rich body of scholarship. However, several challenges persist, including insufficient research, limited translation coverage, and a noticeable focus on specific poems such as “Phoenix Hairpin” in the realm of English translation research. Consequently, there is ample room for improvement in the quality of research output on the English translation of Lu You’s poems, as well as its recognition within the academic community. Building on these findings, it is argued that future investigations pertaining to the English translation of Lu You’s poetry should transcend the boundaries of textual analysis and encompass broader theoretical perspectives and research methodologies. By undertaking this shift, scholars will develop a more profound comprehension of Lu You’s poetic works and make substantive contributions to the field of translation studies. Thus, this article aims to bridge the gap between past research endeavors and future possibilities, serving as a guide and inspiration for scholars to embark on a more nuanced and enriching exploration of Lu You’s poetry as well as other Chinese literature classics.