Exploring the Contribution of Pharmacists in Addressing the Opioid Crisis through Naloxone Prescriptions and Pharmacist-Led Interventions

The opioid epidemic in the United States continues to take the lives of many individuals, with overdoses continuing to rise every year. Naloxone is an opioid antagonist that is efficacious in temporarily reversing opioid overdoses. Pharmacists play an important role in the accessibility and education of naloxone in both the community and health system settings. Recent efforts, such as co-dispensing naloxone with opioid prescriptions, naloxone training programs, and approval of naloxone to be over-the-counter, have been implemented in hopes to better control the opioid epidemic. Despite the efforts to make naloxone more accessible, there are still some barriers to overcome such as lack of training, cost, stigma, and patient refusal. This review aims to explore the contributions pharmacists have made thus far and define the barriers that still have to be resolved.

Impact of the economic crisis and drug shortage on Lebanese cancer patients’care

BACKGROUND As a consequence of the economic crisis,the sociopolitical instability and the advent of the coronavirus disease-19 pandemic,nested challenges faced the Lebanese healthcare system.These have resulted in critical shortages of essential resources,including medications vital for oncologic patients.AIM To assess the ramifications of the ongoing economic crisis on oncology patient care focusing on our outpatient oncology department.METHODS A questionnaire was distributed during the month of February 2022 to oncology patients in Hôtel Dieu de France University Hospital in Beirut during their outpatient therapy.The primary objective was to assess the far-reaching impact of the economic crisis on patient care and the resulting psychological implications.RESULTS Among 182 interviewed patients,31.87%experienced treatment interruption mainly due to acute drug shortages.Despite 87.91%of the patients benefiting from third-party coverage,69.60%had to self-pay for their medications leading to 69.78%of patients perceiving that healthcare was more difficult to access after 2020.Psychologically,one-third of the patients exhibited symptoms of anxiety and/or depression,with 7 patients reporting suicidal ideations.Notably,37.93%of patients who interrupted cancer treatment reported a history of comorbidities,and 89.66%who altered their treatment cited financial difficulties.CONCLUSION Lebanese cancer patients face complex challenges spanning economic,healthcare,and psychological realms.Income inequalities exacerbated by the economic crisis hindered healthcare access.

Modeling Study of the Evolution of the Climate Crisis over Time

The research proposal has the following scope. In relation to the general objective, the aim is to model the evolution of the climate crisis over time taking as variables global warming, greenhouse gases, atmospheric temperature and ocean temperature, as well as the continuity of the natural phenomena in terms of their measurement, temporality and projection. To achieve the above, the description of the following specific objectives is proposed: - Identify the variables corresponding to the climate crisis, their relationship and correlation between them;- Develop projection models with mathematical and statistical arrangements to project them in a given time and, in this way, - Propose mitigation measures for different unfavorable scenarios. The main variables that are currently directly linked to Climate Change are: CO2, the atmospheric index, precipitation, temperature and wind speed. The correlation that exists between climatic elements is very high, both in historical behavior and projected behavior for 2035, their correlation is estimated at 0.90, 0.95, 0.93 and 91 respectively. The mathematical models used to manipulate the historical and projected analysis of the variables studied: are the normal arrangements, this ensures that the values can be used on a common scale;Then there is the analysis of the historical variables using the linear trend, and finally there is the analysis of the variables projected to the year 2035 using the polynomial trend. In both situations, the direct relationship of greenhouse gases, mainly CO2, is directly related to the variations of the variables over time, which is a very worrying result because we can no longer talk about climate change, but rather about CLIMATE CRISIS. To a large extent, a change in the paradigm of exploitation of the resources of our mother earth is required. Alert in an SOS manner to the great powers, which make reasonable use of technology, for this attenuation measures are proposed.

Identity Crisis and Construction in The Magic Barrel

Based on a detailed analysis of the text of the short story-The Magic Barrel,this article aims to explore the identity crisis and construction of the Jewish nation.Using Leo’s moral choices and dilemmas as clues,it showcases the development of Leo’s spiritual world,explores the protagonist’s love pursuit and sacrifice spirit,and includes discussions on the Jewish classic themes of suffering and redemption,which is hoped to provide a new perspective for the study of this short story.

Research on the Status Quo of Psychological Crisis Among College Students in Ethnic Areas

The article discusses the significance of the research,and outlines the concepts of psychological crisis,its intervention,and psychological crisis among college students,as well as relevant theories on psychological crisis.The research mainly adopts case study and interview methods.Through scientific analysis of psychological crisis cases in four grades of X College in ethnic regions,it summarizes the current situation of crisis psychology among X College students,hoping to provide some first-hand data and research ideas for relevant researchers.

Leveraging Predictive Analytics for Strategic Corporate Communications: Enhancing Stakeholder Engagement and Crisis Management

This study explores the integration of predictive analytics in strategic corporate communications, with a specific focus on stakeholder engagement and crisis management. Our mixed-methods approach, which combines a comprehensive literature review with case studies of five multinational corporations, allows us to investigate the applications, challenges, and ethical implications of leveraging predictive models in communication strategies. While our findings reveal significant potential for enhancing personalized content delivery, real-time sentiment analysis, and proactive crisis management, we stress the need for careful consideration of challenges such as data privacy concerns and algorithmic bias. This emphasis on ethical implementation is crucial in navigating the complex landscape of predictive analytics in corporate communications. To address these issues, we propose a framework that prioritizes ethical considerations. Furthermore, we identify key areas for future research, thereby contributing to the evolving field of data-driven communication management.

An Appraisal of the Major National Dialogue as a Panacea to the Anglophone Crisis in Cameroon

This paper explores the Major National Dialogue organised by Paul Biya from the 30th of September to the 4th of October,2019 as a panacea to the Anglophone.The paper also seeks to find out if this dialogue has been the panacea Cameroonians as a whole and the people of Southern Cameroons in particular have been waiting for to end this conflict.This research uses a qualitative research design.This is because the researcher culled information from Jeune Afrique Economie(2019a),Cameroon Tribune,and from Phoenix.Descriptive analysis was used to analyse the collected data.Descriptive analysis is used to get the views of the public whether the Major National Dialogue was really a panacea to the Anglophone crisis.The analysis revealed that there were two opposing opinions on the holding of this dialogue.The government thinks the dialogue was a panacea to put an end to this crisis because there is ongoing construction work in the war zones,and economic activities have witnessed an increase in the regions as the various production units of the Cameroon Development Corporation(CDC)and Pamol plantations have regained agricultural activities.The Ndawara tea estate now functions without problems.Trans-border trade is on the rise and transportation is fluid,except in the rural areas where the state of the road network is poor to name but these.On the other hand,politicians,political parties like the Social Democratic Front,activists,religious leaders,the affected populations,and Cameroonians at large think that the Major National Dialogue was a monologue and therefore was bound to fail because first,key actors arrested and detained in connection to this crisis were not part of this dialogue.For this reason,they are calling for a genuine and an inclusive dialogue.In addition,they argue that we cannot be talking of peace when fighting is still raging on and people are being killed,houses and schools are being burnt,and people are being kidnapped every day for ransom to mention but these.

Feature Selection with Optimal Variational Auto Encoder for Financial Crisis Prediction

Financial crisis prediction(FCP)received significant attention in the financial sector for decision-making.Proper forecasting of the number of firms possible to fail is important to determine the growth index and strength of a nation’s economy.Conventionally,numerous approaches have been developed in the design of accurate FCP processes.At the same time,classifier efficacy and predictive accuracy are inadequate for real-time applications.In addition,several established techniques carry out well to any of the specific datasets but are not adjustable to distinct datasets.Thus,there is a necessity for developing an effectual prediction technique for optimum classifier performance and adjustable to various datasets.This paper presents a novel multi-vs.optimization(MVO)based feature selection(FS)with an optimal variational auto encoder(OVAE)model for FCP.The proposed multi-vs.optimization based feature selection with optimal variational auto encoder(MVOFS-OVAE)model mainly aims to accomplish forecasting the financial crisis.For achieving this,the proposed MVOFS-OVAE model primarily pre-processes the financial data using min-max normalization.In addition,the MVOFS-OVAE model designs a feature subset selection process using the MVOFS approach.Followed by,the variational auto encoder(VAE)model is applied for the categorization of financial data into financial crisis or non-financial crisis.Finally,the differential evolution(DE)algorithm is utilized for the parameter tuning of the VAE model.A series of simulations on the benchmark dataset reported the betterment of the MVOFS-OVAE approach over the recent state of art approaches.

The Acute Angle Closure Crisis in Senegalese Melanodermas: Epidemiological and Clinical Aspects of 24 Cases

Introduction Acute angle closure crisis (AACC) is a major ophthalmic emergency. It is a sight-threatening pathology that is very common in women but rarely described in melanodermas. The aim of this work is to investigate the epidemiological and clinical aspects of acute angle closure crisis. Results We collected 24 patient records, totaling 25 eyes. The average age of our patients was 52.04 years, with a male-to-female ratio of 0.6. A family history of glaucoma occurred in 34% of patients. Patients consulted for a painful red eye associated or not with decreased visual acuity (DVA). The condition was bilateral in one patient. The average visual acuity wax 0.34/10e. The cornea was cloudy and the pupil in areflexic mydriasis in all sick eyes. Hypothalamia was present in 72% of eyes and cataracts in 54.16% of cases. The average intraocular press was 44.38 mmHg and the average cup/disc (C/D) was 0.46. Gonioscopy was performed in 7 patients. The fellow eye did not present any abnormalities in 92% of cases. Conclusion The acute angle closure crisis is a rare condition in melanodermas and common in woman. His diagnostic is essentially clinical and completed by gonioscopy which plays a fundamental role. .

A modified stochastic model for LS+AR hybrid method and its application in polar motion short-term prediction

Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currently,least squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM prediction.Besides,the weighted LS+AR hybrid method performs well for PM short-term prediction.However,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR model.In this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid method.By using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid method.Compared to the mean absolute errors(MAEs)of PMX/PMY sho rt-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61%/12.08%and 0.24%/11.65%,respectively.Besides,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods.

Exploring the Impact of Crisis and Trauma on the Mental Health and Psychological Well-Being of University Students in Northern Haiti

In recent decades,Haiti has been subject to man-made and natural disasters that have left its citizens vulnerable to a range of shocks.With a weak state unable to protect its populace,Haitians are exposed to some of the highest levels of poverty and violence in the Western Hemisphere.In recent years,Haitians have experienced two crises that this study analyzes:the instability and political violence of“peyi lòk”as well as the global pandemic of COVID-19.This community-based assessment explores the impact of these two crises on the mental health and psychological well-being of 38 Haitian university students in the understudied northern part of the country.Results indicate that both crises had similarities related to their psychological effects on young people,most notably in terms of traumatic experiences related to threats or violence,forced confinement,and large increases in population-wide uncertainty.Additionally,the extreme violence of“peyi lòk”and the widespread unpredictability of COVID-19 and its effects in the early days of the pandemic resulted in high levels of stress and fear.Both crises also resulted in extreme economic hardship for students,with many reporting difficulties accessing basic needs such as food and water.This study highlights how converging population-level crises in“complex emergencies”can heighten trauma and compromise mental health.

The aggregate and sectoral time‑varying market efficiency during crisis periods in Turkey:a comparative analysis with COVID‑19 outbreak and the global financial crisis

This study aims to examine the time-varying efficiency of the Turkish stock market’s major stock index and eight sectoral indices,including the industrial,financial,service,information technology,basic metals,tourism,real estate investment,and chemical petrol plastic,during the COVID-19 outbreak and the global financial crisis(GFC)within the framework of the adaptive market hypothesis.This study employs multifractal detrended fluctuation analysis to illustrate these sectors’multifractality and short-and long-term dependence.The results show that all sectoral returns have greater persis-tence during the COVID-19 outbreak than during the GFC.Second,the real estate and information technology industries had the lowest levels of efficiency during the GFC and the COVID-19 outbreak.Lastly,the fat-tailed distribution has a greater effect on multifractality in these industries.Our results validate the conclusions of the adaptive market hypothesis,according to which arbitrage opportunities vary over time,and contribute to policy formulation for future outbreak-induced economic crises.

Pulmonary Hypertension Crisis in Patient with Tetralogy of Fallot and Mixed Total Anomalous Pulmonary Vein Connection after the Primary Correction:A Rare Case Report

Tetralogy of Fallot(TOF)with total anomalous pulmonary vein connections(TAPVC)is a rare type of complex congenital heart disease among all TOF cases.Co-presentation of major aortopulmonary collateral arteries(MAPCAs)compensates for the lack of central pulmonary bloodflow and decreases the severity of right-to-left shunting in TOF.We present a case of a 2-year-old child with complex diagnoses of TOF,TAPVC,a large secun-dum atrial septal defect(ASD),and intraoperatively identified MAPCAs.She underwent surgery to repair the TAPVC,valve-sparing reconstruction of the right ventricular outflow tract,interventricular defect closure,and the creation of patent foramen ovale(PFO).After the operation,hemodynamic instability happened along with sudden blood pressure drop,desaturation,and increased central venous pressure,which subsided after adminis-tering inhalational nitric oxide(NO).A postoperative pulmonary hypertension crisis was suggested when the patient experienced recurrent symptoms after the termination of NO.Echocardiographicfindings of a D-shaped left ventricle(LV),right-to-left PFO shunt and high tricuspid valve gradientfirmly established the diagnosis.It was subsequently managed with continuous NO inhalation and sildenafil,which rendered a satisfactory outcome.Repaired TOF and TAPVC could be at particular risk of developing pulmonary hypertension crisis,especially in the presence of MAPCAs due to possible remodeling of the pulmonary vasculature.Furthermore,a relatively non-compliant LV function and small left atrial size may exacerbate the risk of developing postcapillary pulmonary hypertension after TAPVC repair.A successful postoperative outcome calls for a meticulous preoperative analysis of the anatomical lesions,as well as careful monitoring.

The Taiwan Question China From the Perspective of International Crisis Management:History and Future

The Taiwan Question China discussed in this paper belongs to the theoretical crisis discussion on international relations and does not regard the Cross-Strait relations as relations between different countries.The outcome of the 2024 Taiwan Election has a great impact on the Taiwan question,the latest poll shows that the possibility of the Democratic Progressive Party(DPP)candidate to come to power is still very high,because its political evolution trend of Taiwan independence still exists.

Tuberculosis-induced aplastic crisis and atypical lymphocyte expansion in advanced myelodysplastic syndrome:A case report and review of literature

BACKGROUND Myelodysplastic syndrome(MDS)is caused by malignant proliferation and ineffective hematopoiesis.Oncogenic somatic mutations and increased apoptosis,necroptosis and pyroptosis lead to the accumulation of earlier hematopoietic progenitors and impaired productivity of mature blood cells.An increased percentage of myeloblasts and the presence of unfavorable somatic mutations are signs of leukemic hematopoiesis and indicators of entrance into an advanced stage.Bone marrow cellularity and myeloblasts usually increase with disease progression.However,aplastic crisis occasionally occurs in advanced MDS.CASE SUMMARY A 72-year-old male patient was definitively diagnosed with MDS with excess blasts-1(MDS-EB-1)based on an increase in the percentages of myeloblasts and cluster of differentiation(CD)34+hematopoietic progenitors and the identification of myeloid neoplasm-associated somatic mutations in bone marrow samples.The patient was treated with hypomethylation therapy and was able to maintain a steady disease state for 2 years.In the treatment process,the advanced MDS patient experienced an episode of progressive pancytopenia and bone marrow aplasia.During the aplastic crisis,the bone marrow was infiltrated with sparsely distributed atypical lymphocytes.Surprisingly,the leukemic cells disappeared.Immunological analysis revealed that the atypical lymphocytes expressed a high frequency of CD3,CD5,CD8,CD16,CD56 and CD57,suggesting the activation of autoimmune cytotoxic T-lymphocytes and natural killer(NK)/NKT cells that suppressed both normal and leukemic hematopoiesis.Elevated serum levels of inflammatory cytokines,including interleukin(IL)-6,interferon-gamma(IFN-γ)and tumor necrosis factor-alpha(TNF-α),confirmed the deranged type I immune responses.This morphological and immunological signature led to the diagnosis of severe aplastic anemia secondary to large granule lymphocyte leukemia.Disseminated tuberculosis was suspected upon radiological examinations in the search for an inflammatory niche.Antituberculosis treatment led to reversion of the aplastic crisis,disappearance of the atypical lymphocytes,increased marrow cellularity and 2 mo of hematological remission,providing strong evidence that disseminated tuberculosis was responsible for the development of the aplastic crisis,the regression of leukemic cells and the activation of CD56+atypical lymphocytes.Reinstitution of hypomethylation therapy in the following 19 mo allowed the patient to maintain a steady disease state.However,the patient transformed the disease phenotype into acute myeloid leukemia and eventually died of disease progression and an overwhelming infectious episode.CONCLUSION Disseminated tuberculosis can induce CD56+lymphocyte infiltration in the bone marrow and in turn suppress both normal and leukemic hematopoiesis,resulting in the development of aplastic crisis and leukemic cell regression.

Matching Consequences and Causes in Crisis Public Relations

This exploratory study examines the phenomenon of consequence cause matching,which is based on the representativeness heuristic,from cognitive psychology,upon crisis management and public relations.A 2(Large Scale Crisis vs.Small Scale Crisis)×2(Large Scale Cause vs.Small Scale Cause)mixed factorial design experiment was conducted based upon a hypothetical crisis scenario.This study found initial evidence that consequence cause matching is a phenomenon that can impact the process of attribution for a crisis.It highlights a potential new area of theoretical growth for the situational crisis communication theory.

Regional Tourism Resilience under Crisis Impacts:The Cases of Yangtze River Delta and Pearl River Delta

Since the beginning of the 21st century,various crisis events have occurred frequently,inflicting substantial impacts on the tourism sector,which has garnered considerable scholarly and policy attention.Nevertheless,limited research has systematically explored tourism resilience at the urban scale,and there is a paucity of studies comparing regional differences in tourism resilience under distinct crisis scenarios and their underlying causes.Thus,this study focuses on the Yangtze River Delta and the Pearl River Delta,employing Martin’s regional economic resilience measurement method.It assesses the tourism resilience of the two regions under the impact of the 2008 financial crisis and the COVID-19 pandemic,subsequently visualizing the data results using ArcGIS software.The study also endeavors to unveil potential causes for disparities in urban tourism resilience.The main conclusions are as follows:Firstly,regions with higher economic development exhibit relatively weaker tourism resilience during economic crises,yet demonstrate comparatively stronger resilience during public crises.Secondly,distinct differentiations exist both between and within the Yangtze River Delta and the Pearl River Delta,primarily stemming from variations such as geographical positioning,tourism resource endowments,and industrial and economic structures,both regionally and within individual cities.Thirdly,the determination of regional tourism resilience is intricate and cannot be restricted to a single dimension;multidimensional indicators better encapsulate the essence of regional tourism resilience.

The Construction of Community Under the Subprime Crisis in Sunset Park

In Sunset Park,the contemporary American writer Paul Auster reveals the political,economic and social problems that have surfaced in America in the wake of the 9/11 incident.Focusing on the image of people on the edge of the city,the author describes how they rebuild their lives after illegally living in an abandoned apartment in Sunset Park,using the art and the community as a spiritual refuge to seek comfort and heal wounds,reconstruct self-identity,and fight against the unfair society.This article analyzes the characteristics of the community in the novel Sunset Park,to interpret its functions,and to show the healing power of a caring community.

Short-Term Household Load Forecasting Based on Attention Mechanism and CNN-ICPSO-LSTM

Accurate load forecasting forms a crucial foundation for implementing household demand response plans andoptimizing load scheduling. When dealing with short-term load data characterized by substantial fluctuations,a single prediction model is hard to capture temporal features effectively, resulting in diminished predictionaccuracy. In this study, a hybrid deep learning framework that integrates attention mechanism, convolution neuralnetwork (CNN), improved chaotic particle swarm optimization (ICPSO), and long short-term memory (LSTM), isproposed for short-term household load forecasting. Firstly, the CNN model is employed to extract features fromthe original data, enhancing the quality of data features. Subsequently, the moving average method is used for datapreprocessing, followed by the application of the LSTM network to predict the processed data. Moreover, the ICPSOalgorithm is introduced to optimize the parameters of LSTM, aimed at boosting the model’s running speed andaccuracy. Finally, the attention mechanism is employed to optimize the output value of LSTM, effectively addressinginformation loss in LSTM induced by lengthy sequences and further elevating prediction accuracy. According tothe numerical analysis, the accuracy and effectiveness of the proposed hybrid model have been verified. It canexplore data features adeptly, achieving superior prediction accuracy compared to other forecasting methods forthe household load exhibiting significant fluctuations across different seasons.

A Time Series Short-Term Prediction Method Based on Multi-Granularity Event Matching and Alignment

Accurate forecasting of time series is crucial across various domains.Many prediction tasks rely on effectively segmenting,matching,and time series data alignment.For instance,regardless of time series with the same granularity,segmenting them into different granularity events can effectively mitigate the impact of varying time scales on prediction accuracy.However,these events of varying granularity frequently intersect with each other,which may possess unequal durations.Even minor differences can result in significant errors when matching time series with future trends.Besides,directly using matched events but unaligned events as state vectors in machine learning-based prediction models can lead to insufficient prediction accuracy.Therefore,this paper proposes a short-term forecasting method for time series based on a multi-granularity event,MGE-SP(multi-granularity event-based short-termprediction).First,amethodological framework for MGE-SP established guides the implementation steps.The framework consists of three key steps,including multi-granularity event matching based on the LTF(latest time first)strategy,multi-granularity event alignment using a piecewise aggregate approximation based on the compression ratio,and a short-term prediction model based on XGBoost.The data from a nationwide online car-hailing service in China ensures the method’s reliability.The average RMSE(root mean square error)and MAE(mean absolute error)of the proposed method are 3.204 and 2.360,lower than the respective values of 4.056 and 3.101 obtained using theARIMA(autoregressive integratedmoving average)method,as well as the values of 4.278 and 2.994 obtained using k-means-SVR(support vector regression)method.The other experiment is conducted on stock data froma public data set.The proposed method achieved an average RMSE and MAE of 0.836 and 0.696,lower than the respective values of 1.019 and 0.844 obtained using the ARIMA method,as well as the values of 1.350 and 1.172 obtained using the k-means-SVR method.