Exploring transport perceptions in London: A twitter-based analysis by country of residence

Indonesia telah melaksanakan proses pemilihan presiden dan wakil presiden pada tanggal 14 Februari 2024 dan pada tanggal 20 Maret 2024, KPU telah mengumumkan hasil rekapitulasi suara Pilpres 2024. Namun hasil rekapitulasi menuai beberapa polemik, sehingga dilakukan pengajuan gugatan sengketa pilpres 2024 ke Mahkamah Konstitusi atau MK. Putusan MK dalam menyelesaikan sengketa Pilpres 2024 berpengaruh terhadap kepercayaan masyarakat terhadap pemerintah dan lembaga peradilan di Indonesia. Dengan menggunakan teknik data mining, maka dapat dilakukan proses analisis sentimen di media sosial ‘X’ untuk mengetahui sentimen masyarakat terkait putusan MK dalam menyelesaikan sengketa Pilpres 2024. Pada penelitian ini menggunakan 145 data ulasan yang dikelompokkan menjadi dua jenis data yaitu sebagai data latih dengan jumlah 43 data dan sebagai data uji dengan jumlah 102 data, selanjutnya menerapkan algoritma naïve bayes classifier untuk melakukan proses klasifikasi. Hasil dari prediksi sentimen menunjukkan sentimen negatif sejumlah 56, sentimen netral sejumlah 15, dan sentimen positif sejumlah 31.

BackgroundTo understand the public sentiment regarding the Zika virus, social media can be leveraged to understand how positive, negative, and neutral sentiments are expressed in society. Specifically, understanding the characteristics of negative sentiment could help inform federal disease control agencies’ efforts to disseminate relevant information to the public about Zika-related issues.ObjectiveThe purpose of this study was to analyze the public sentiment concerning Zika using posts on Twitter and determine the qualitative characteristics of positive, negative, and neutral sentiments expressed.MethodsMachine learning techniques and algorithms were used to analyze the sentiment of tweets concerning Zika. A supervised machine learning classifier was built to classify tweets into 3 sentiment categories: positive, neutral, and negative. Tweets in each category were then examined using a topic-modeling approach to determine the main topics for each category, with focus on the negative category.ResultsA total of 5303 tweets were manually annotated and used to train multiple classifiers. These performed moderately well (F1 score=0.48-0.68) with text-based feature extraction. All 48,734 tweets were then categorized into the sentiment categories. Overall, 10 topics for each sentiment category were identified using topic modeling, with a focus on the negative sentiment category.ConclusionsOur study demonstrates how sentiment expressed within discussions of epidemics on Twitter can be discovered. This allows public health officials to understand public sentiment regarding an epidemic and enables them to address specific elements of negative sentiment in real time. Our negative sentiment classifier was able to identify tweets concerning Zika with 3 broad themes: neural defects,Zika abnormalities, and reports and findings. These broad themes were based on domain expertise and from topics discussed in journals such as Morbidity and Mortality Weekly Report and Vaccine. As the majority of topics in the negative sentiment category concerned symptoms, officials should focus on spreading information about prevention and treatment research.

Recently, as social networking websites become increasingly ubiquitous, there is also a surge in academia to study their potential impacts on business practice. One strand of literature focuses on the public sentiment expressed through social media and how such sentiment shape business environment. Previous researches have proved that public sentiment on social media does have an impact on movie's opening weekend box office. This study aims to specifically analyze both positive and negative sentiment by following this strand of research in movie industry. The results confirm that positive sentiment shares high covariance with profitability whereas negative sentiment becomes insignificant after controlling for the production budget. In other words, online negative sentiment towards a product does not necessarily affect profitability negatively.

This article evaluates the maximum data flow from a sender to a receiver via the internet when all transmissions are scheduled for early morning hours. The significance of early morning hours is that internet congestion is low while users sleep. When the sender and receiver lie in proximal time zones, a direct transmission from sender to receiver can be scheduled for early morning hours. When the sender and receiver are separated by several time zones such that their sleep times are non-overlapping, data can still be transmitted during early morning hours with an indirect store-and-forward transfer. The data are transmitted from the sender to intermediate end networks or data centers that serve as storage hops en route to receiver. The storage hops are placed in zones that are time proximal to the sender or the receiver so that all transmissions to and from storage hops occur during low-congestion early morning hours. This article finds the optimal locations and bandwidth distributions of storage hops for maximum nice internet flow from a sender to a receiver.

Control de la hipertensión arterial basado en la automedición ambulatoria de la presión arterial: Estudio APACHE

Reflex syncope during a hot bath as a specific cause of drowning in Japan

The subject of the paper is an analysis of the type of clouds in Poland in 1996–2020 on the low, middle and high levels. Daily data on cloud types and the cloudiness of the low-level from 36 IMWM-NRI stations were used. In the analysed multi-year period, the highest share of low-level clouds was observed (56%), followed by mid-level clouds (23%), and the lowest share of high-level clouds (21%). There was a slight decrease in the share of low-level clouds, and an increase in the share of middle and high levels clouds in the analysed period. The share of low-level clouds was highest in the cool season and during the afternoon and night hours; it was lowest in the summer, and early morning and evening hours. The middle and high levels had the highest share in the summer and during the early evening and early morning hours. These levels were least frequent in the winter, and around noon for the mid-level, and at night for the high-level. The Cumulus humilis and Stratocumulus cugen clouds were most frequently observed on the low-level during low cloudiness. Stratus fractus and Cumulonimbus capillatus were most frequently observed during total and high cloudiness on the low-level. In the warm season and the daytime, clouds are more isolated; in the cool season, they form more dense cloud layers.

Abstract. In the present study, the impact of aerosols on the photochemistry in Mexico City is evaluated using the WRF-CHEM model for the period from 24 to 29 March during the MCMA-2006/MILAGRO campaign. An aerosol radiative module has been developed with detailed consideration of aerosol size, composition, and mixing. The module has been coupled into the WRF-CHEM model to calculate the aerosol optical properties, including optical depth, single scattering albedo, and asymmetry factor. Calculated aerosol optical properties are in good agreement with the surface observations and aircraft and satellite measurements during daytime. In general, the photolysis rates are reduced due to the absorption by carbonaceous aerosols, particularly in the early morning and late afternoon hours with a long aerosol optical path. However, with the growth of aerosol particles and the decrease of the solar zenith angle around noontime, aerosols can slightly enhance photolysis rates when ultraviolet (UV) radiation scattering dominates UV absorption by aerosols at the lower-most model layer. The changes in photolysis rates due to aerosols lead to about 2–17 % surface ozone reduction during daytime in the urban area in Mexico City with generally larger reductions during early morning hours near the city center, resulting in a decrease of OH level by about 9 %, as well as a decrease in the daytime concentrations of nitrate and secondary organic aerosols by 5–6 % on average. In addition, the rapid aging of black carbon aerosols and the enhanced absorption of UV radiation by organic aerosols contribute substantially to the reduction of photolysis rates.

Social media has become part and parcel of students’ life in colleges as it occupies most of their free times. Over time, results of programming units have shown a downward trend among college students at Technical University of Mombasa in Kenya. Programming, like Mathematics, requires a lot of practice that is now consumed by social media. This study investigated the impact of Social Media on Grades in terms of hours spent and the time of day Social Media is used. Descriptive statistical research was used to gain understanding of the predictive power Social Media has on the Programming Grades. A total of 142 students pursuing Degree and Diploma courses in Information Technology participated in the study. The students were drawn from Technical University of Mombasa and Kenya Coast National Polytechnic. Over 90% of the students were active Social Media users. The research was conducted in 2018-2019 academic year. Results show that social media use could predict students who scored high grades in both Degree and Diploma courses. Such students controlled their usage of Social Media. They did not use Social Media in the early morning hours up to afternoons when they were engaged in serious studies. These students used Social Media anytime of the day - which means, in between serious study sessions. On the other hand, more average students used Social Media even in the early morning and up to afternoon sessions. Notably, more average Diploma students use Social Media at bedtime than anytime. Further research is recommended with more data using Machine Learning techniques to develop a model that will predict success or failure in Programming units depending on how one uses social media.

BackgroundAccessibility to community pharmacies is crucial for ensuring timely access to medications and essential health services. While accessibility to community pharmacies is critical, disparities driven by temporal and spatial factors persist, resulting in inequities in healthcare access. This study aims to comprehensively assess spatiotemporal and multimodal accessibility to community pharmacies in Lisbon, highlighting the influence of transport modes and time of day on accessibility disparities.Data and methodsThe study employed a methodology that considered five daily time slots and two modes of transport—walking and public transport—to evaluate accessibility to community pharmacies. Data was sourced from road and pedestrian networks, Google API, and GTFS data. Descriptive statistics and spatial analysis were utilized to assess travel time and accessibility disparities across different regions of Lisbon. The analysis focused on both the percentage of residents able to access pharmacies within 10 min and the total number of pharmacies accessible.Resultsndings reveal significant temporal variations in accessibility, with public transport consistently improving access compared to walking. Accessibility peaks in the evening (6–7 PM), when 83.3% of residential buildings are within a 10-min walking distance of a pharmacy, and 92.7% are reachable by public transport. In contrast, early morning hours (4–5 AM) show the lowest accessibility, with only 8.9% of buildings accessible by walking and 16.1% by public transport. During the daytime (8–9 AM), notable disparities emerge across the city: public transport enhances access in the southwest, northwest, and central areas, while limited pharmacy opening hours constrain accessibility in the north and southeast, where only 108 of 258 pharmacies are operational. Finally, travel time to pharmacy services for city residents highlight significant spatial and temporal disparities in pharmacy accessibility, emphasizing the role of transport modes and service hours in shaping urban healthcare access.ConclusionsThis study underscores the importance of addressing both temporal and spatial factors to ensure equitable accessibility to community pharmacies. The findings suggest the need for targeted policies to improve public transport services during off-peak hours and to extend pharmacy operating hours. Future research should focus on comparative studies across different urban contexts and incorporate more granular data to better understand accessibility to urban services.

Nlrp3 Inflammasome Activation in Bone Marrow-Residing Innate Immunity Cells Governs Circadian Changes in the Number of Circulating Hematopoietic Stem/Progenitor Cells in Peripheral Blood

Mice Deficient in the Fifth Complement Cascade Protein (C5) Do Not Display Circadian Changes in the Number of Circulating Hematopoietic Stem/Progenitor Cells (HSPCs) in Peripheral Blood (PB)—evidence for the Pivotal Role of the Distal Part of the Complement Cascade in Inducing the Circadian Release of HSPCs into PB

This study investigates whether news sentiment plays a role in setting social media sentiment to explore the dynamics of sentiment develop and diffusion within the public agenda. Based on the agenda-setting theory, this study analyzed the public and media sentiments towards the 2016 US election and the candidates using data from Twitter, CNN, and Fox News. Focusing on the Twitter messages created by the supporters of Hillary Clinton and Donald Trump, over 1.3 million Twitter messages were collected associated with the election, employing hashtags as indicators of support. The Granger causality test between social media and news sentiments revealed that there is a mutual influence between social media and news sentiments; CNN’s overall sentiment was influenced by the sentiment of Hillary Clinton’s supporters, whereas Trump supporters’ sentiment was influenced by Fox News’ negative sentiment. The results suggest that public sentiment is formed in response to public agenda and mass media, indicating that sentiment is a critical component in understanding public opinion. Implications for future studies and limitations are also discussed.

Microblog has become the “first scenario” under which the public learn about the epidemic situation and express their opinions. Public sentiment mining based on microblog data can provide a reference for the government’s information disclosure, public sentiment guidance and formulation of epidemic prevention and control policy. In this paper, about 200,000 pieces of text data were collected from Jan. 1 to Feb. 26, 2020 from Sina Weibo, which is the most popular microblog website in China. And a public sentiment analysis framework suitable for Chinese-language scenarios was proposed. In this framework, a sentiment dictionary suitable for Chinese-language scenarios was constructed, and Baidu’s Sentiment Analysis API was used to calculate the public sentiment indexes. Then, an analysis on the correlation between the public sentiment indexes and the COVID-19 case indicators was made. It was discovered that there is a high correlation between public sentiments and incidence trends, in which negative sentiment is of statistical significance for the prediction of epidemic development. To further explore the source of public negative sentiment, the topics of the public negative sentiment on Weibo was analyzed, and 20 topics in five categories were got. It is found that there is a strong linkage between the hot spots of public concern and the epidemic prevention and control policies. If the policies cover the hot spots of public concern in a timely and effective manner, the public negative sentiment will be effectively alleviated. The analytical framework proposed in this paper also applies to the public sentiment analysis and policy making for other major public events.

The present study was carried out with an aim of preparing modified release pellets of the antiasthma drug montelukast sodium. The patients suffering from chronic asthma many a times suffer from exacerbations during the early morning hours i.e. around 4am to 6 am. Thus the need to take an immediate release medication arises during early morning hours which is not quiet feasible for the patients. The delivery of the drug at this time can be made possible by the use of modified release formulation of montelukast sodium which when taken at the bed time would release the drug as a pulsed delivery without the need of the patient to wake up. The montelukast sodium pellets prepared by extrusion-spheronization were coated with release retarding polymer ethyl cellulose using the Wurster method. The ethyl cellulose coating helped in lag time increase due to prolonged water uptake time. The increase in the coating level increased the lag time sufficiently that might release the drug during the early morning hours. Thus a modified release pellets dosage form to prevent the early morning asthma attacks and exacerbations was developed successfully.