Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhanced Nitrate Fraction: Enabling Urban Aerosol Particles to Remain in a Liquid State at Reduced Relative Humidity

Nitrate has become the primary inorganic compound in urban aerosol particles, but its effects on particle phase state, which is crucial in multiphase chemistry, remains largely unknown. Herein, particle rebound measurements were conducted to explore the relationship between the liquid–phase–transition threshold relative humidity (RHthreshold) and the inorganic compounds mass fraction in dry particles (Finorg). Results revealed negative correlations between RHthreshold and Finorg, with more nitrate leading to lower RHthreshold. Even with RH < 20%, particles with ∼50% nitrate mass fraction remained in non‐solid state. Taking Beijing as an example, decreases were observed in RHthreshold from 64% in 2015 to below 53% nowadays during the moderate‐pollution periods (PM2.5 = 35–75 μg/m3) due to an enhanced nitrate fraction. This allowed urban aerosol particles to exist in liquid state at lower RH, and consequently, kinetic limitation by bulk diffusion in nitrate‐dominated particles might be negligible, making them key seeds for secondary aerosol formation through multiphase reactions.
Risk factors for recurrent cerebral amyloid angiopathy-related intracerebral hemorrhage

Background Cerebral amyloid angiopathy (CAA) is the most common cause of lobar intracerebral hemorrhage (ICH) in the elderly, and its multifocal and recurrent nature leads to high rates of disability and mortality. Therefore, this study aimed to summarize the evidence regarding the recurrence rate and risk factors for CAA-related ICH (CAA-ICH). Methods We performed a systematic literature search of all English studies published in PubMed, Embase, Web of Science, Cochrane Library, Scopus, and CINAHL from inception to June 10, 2023. Studies reporting CAA-ICH recurrence rates and risk factors for CAA-ICH recurrence were included. We calculated pooled odds ratios (ORs) with their corresponding 95% confidence intervals (CIs) using a random/fixed-effects model based on the I2 assessment of heterogeneity between studies. Publication bias was assessed using Egger's test. Results Thirty studies were included in the final analysis. Meta-analysis showed that the recurrence rate of CAA-ICH was 23% (95% CI: 18–28%, I2 = 96.7%). The risk factors significantly associated with CAA-ICH recurrence were: previous ICH (OR = 2.03; 95% CI: 1.50–2.75; I2 = 36.8%; N = 8), baseline ICH volume (OR = 1.01; 95% CI: 1–1.02; I2 = 0%; N = 4), subarachnoid hemorrhage (cSAH) (OR = 3.05; 95% CI: 1.86–4.99; I2 = 0%; N = 3), the presence of cortical superficial siderosis (cSS) (OR = 2.04; 95% CI: 1.46–2.83; I2 = 0%; N = 5), disseminated cSS (OR = 3.21; 95% CI: 2.25–4.58; I2 = 16.0%; N = 6), and centrum semiovale-perivascular spaces (CSO-PVS) severity (OR = 1.67; 95% CI: 1.14–2.45; I2 = 0%; N = 4). Conclusion CAA-ICH has a high recurrence rate. cSAH, cSS (especially if disseminated), and CSO-PVS were significant markers for recurrent CAA-ICH. The onset of ICH in patients with CAA is usually repeated several times, and recurrence is partly related to the index ICH volume. Identifying clinical and neuroimaging predictors of CAA-ICH recurrence is of great significance for evaluating outcomes and improving the prognosis of patients with CAA-ICH. Systematic review registration https://www.crd. york.ac. uk/PROSPERO/display_record. php? RecordID=400240, identifier [CRD42023400240].
Effective Supplier Selection Using ANP

A supplier provides monetary benefits as well as non-monetary benefits for the organization, especially to maintain company reputation and customer satisfaction. Therefore, an effective supplier network is an important key success factor of the organization. There are many common drawbacks in the existing supplier selection processes which hinder the selection of effective supplier/suppliers. Therefore, the objective of this research is to develop a model and a mechanism to overcome these common drawbacks while predicting the validity of the model across a few industries. With the scope of this paper, supplier selection was considered as a multi-criteria decision making problem (MCDM) because supplier selection is the evaluation of trade-offs between multiple criteria. Analytic Network Process (ANP) which is a technique to solve MCDM problems in which the criteria affect each other and have nonlinear correlation, is used here to prioritize criteria and alternatives. Therefore, this model is flexible for selecting suppliers for any product/service across any organization, sector, and industry. The significance of the proposed model is its Flexibility across any industry with limitations and supports multiple criteria with any number of alternatives.
Wireless sEMG Sensor for Neck Muscle Activity Measurement and Posture Classification Using Machine Learning

The nature of prolonged work and lifestyle has affected upper extremities, leading to neck musculoskeletal disorders (MSDs). The existing wired surface electromyography (sEMG) techniques limit the dynamic muscle activity measurement. In the current study, a wireless, lightweight, cost-effective, and fast data-transmitting sEMG module is developed and assisted with pattern classification techniques to identify neck postural risks. The developed system transmits EMG signals with a sampling rate of 1024 Hz and a signal-to-noise ratio (SNR) of 50–60 dB. When calibrated with a standard EMG system, error analysis indicates a maximum percentage of error (PoE) of 1.767% for the developed system. An experimental trial was performed on 30 subjects by measuring muscle activity on two neck muscles: sternocleidomastoid (SCM) and upper trapezius descendens (TRP). A 3-min experimental trial resulted in an increase of muscle activity by 1.64% maximum voluntary contraction (MVC) at SCM and 3.87% MVC at TRP muscle. Indicating TRP muscle shows more muscle activity than the SCM muscle during flexion. Three machine learning classification algorithms were used to distinguish neutral and flexed neck postures; the support vector machine (SVM) gives higher classification accuracy of 96% than other classification algorithms. The proposed system can be used to identify the fatigued muscles, which alerts the user to adjust the posture during prolonged flexed tasks.
Near‐surface salinity and stratification in the north Bay of Bengal from moored observations

A thin layer of fresh water from summer monsoon rain and river runoff in the Bay of Bengal (BoB) has profound influence on air‐sea interaction across the south Asian region, but the mechanisms that sustain the low‐salinity layer are as yet unknown. Using the first long time series of high‐frequency observations from a mooring in the north BoB and satellite salinity data, we show that fresh water from major rivers is transported by large‐scale flow and eddies, and shallow salinity stratification persists from summer through the following winter. The moored observations show frequent 0.2–1.2 psu salinity jumps with time scales of 10 min to days, due to O(1–10) km submesoscale salinity fronts moving past the mooring. In winter, satellite sea surface temperature shows 10 km wide filaments of cool water, in line with moored data. Rapid salinity and temperature changes at the mooring are highly coherent, suggesting slumping of salinity‐dominated fronts. Based on these observations, we propose that submesoscale fronts may be one of the important drivers for the persistent fresh layer in the north BoB.
Diabetes Pay-for-Performance Program Participation and Dialysis Risk in Relation to Educational Attainment: A Retrospective Cohort Study

Pay-for-performance (P4P) programs for diabetes care enable the provision of comprehensive and continuous health care to diabetic patients. However, patient outcomes may be affected by the patient’s educational attainment. The present retrospective cohort study aimed to examine the effects of the educational attainment of diabetic patients on participation in a P4P program in Taiwan and the risk of dialysis. The data were obtained from the National Health Insurance Research Database of Taiwan. Patients newly diagnosed with type 2 diabetes mellitus (T2DM) aged 45 years from 2002 to 2015 were enrolled and observed until the end of 2017. The effects of their educational attainment on their participation in a P4P program were examined using the Cox proportional hazards model, while the impact on their risk for dialysis was investigated using the Cox proportional hazards model. The probability of participation in the P4P program was significantly higher in subjects with a junior high school education or above than in those who were illiterate or had only attained an elementary school education. Subjects with higher educational attainment exhibited a lower risk for dialysis. Different educational levels had similar effects on reducing dialysis risk among diabetic participants in the P4P program.
Spatial Modeling of Whreathed Hornbill (Acerosundulatus) Habitat in Mount Ungaran Central Java

The objective of the research was to find the suitable habitat for Whreathed Hornbill (Acerosundulatus) using GIS in Mount Ungaran. The research was carried out in five stations: Banyuwindu, Gajah Mungkur, Watu Ondo, Gunung Gentong, and Gajah Mungkur. The method of data collection consisted of spatial data and tabular data. The determining of habitat and the nest distribution were carried out using GPS (Global Positioning System) andprocessing the data was using Arc Gis and Erdas Imagine 9.1 software.The results showed that very suitable area for bird habitat in Mount Ungaranwas 2436.73 ha (13%), whereas 985.11 ha (51%) was considered as suitable area and 7171.37 ha or 36% as unsuitable area. The results validate the suitability of habitat for Whreathed Hornbill is 75%. The accuracy value of 75% indicates that the suitability map model for Whreathed Hornbill habitat is relatively good and is acceptable.
ACNE AND INSULIN RESISTANCE: A SYSTEMATIC REVIEW

Acne is a skin disorder that is characterized by persistent inflammation and involves the folliculopilosebaceous unit. It has an impact on a sizeable portion of the general population. Acne affects a disproportionate number of females and teenagers, especially those between the ages of 15 and 24, who are most susceptible to the condition. In recent times, there has been seen to be a growing interest in the possible connection between acne and insulin resistance (IR). This attention has been seen, and it is appreciated. It would appear that IR has a strong connection to acne, which is a persistent skin condition that can lead to inflammation. Research has been conducted on a wide variety of etiopathological factors that have been associated with the progression of IR. It would appear that obesity is one of the most common. Additionally, it would appear that factors such as chronic inflammation, hypertriglyceridemia, low HDL serum concentration, mitochondrial dysfunction, gut microbiota, and the excess activity of antagonistic hormones such as cortisol, glucagon, and thyroid hormones all play a significant role in the development of this condition. We identified a linkage between insulin resistance and severe acne vulgaris, which was reported to have a positive link with insulin resistance. On the basis of these findings, it is a legitimate assumption to hypothesize that medications that are now utilized for the treatment of insulin resistance would also be helpful for the treatment of severe acne vulgaris.
Civil Society and Democratic Decline in Southeast Asia

This paper introduces a special issue that examines civil society and democratic decline in Southeast Asia. Using the Philippines, Indonesia, Thailand, Myanmar, Malaysia, and Cambodia as case studies, the articles in the special issue examine often divergent reactions in civil society to increasing authoritarian pressures, diminishing political space, and increased repression. The paper at hand reviews the literature on concepts at the core of this inquiry, including civil society, backsliding, and diagonal accountability, and summarises the main findings of the special issue for Southeast Asia specifically and more broadly.
Prevalence of Salmonella in retail whole chicken carcasses in Hanoi, Vietnam

In Vietnam, the data on the prevalence of Salmonella contamination in retail chicken meat is limited. We wanted to compare that prevalence at traditional and modern supermarkets, as well as in fresh versus frozen carcasses, and to verify the inner carcass temperatures at time of purchase. A collection of 245 whole chicken carcasses were purchased from traditional markets and supermarkets, in seven urban district areas of Hanoi in June and July, 2011. Sampling plan included 110 fresh chickens from traditional markets (F/M), 109 fresh chickens from supermarkets (F/SM) and 26 frozen chickens from supermarkets (FZ/SM). The inner carcass temperature was measured at the time of purchase. Salmonella was isolated from carcass rinses and isolates were serotyped. The overall prevalence of Salmonella-positive carcasses was 66.5% (163/245). The Salmonella prevalence in the three types of chickens varied significantly, 84.55% (93/110) from F/M, 59.63% (65/109) from F/SM and 19.23% (5/26) from FZ/SM (P< 0.05). A total of 25 serovars were recovered. The predominant serovars were Agona (24.78%), Albany (20.43%) and Corvallis (10%). Two different serovars were isolated and coexisted on the same carcass in 66 samples (26.9%). The inner carcass temperatures of fresh samples from traditional markets and supermarkets were significantly different (P < 0.05) with a mean inner carcass temperature of 27.3oC and 15.8oC respectively. This study revealed a high prevalence of Salmonella spp. from retail chickens in Hanoi and uncovered the difficulty encountered by all market types to store broiler chicken carcasses at a safe temperature.
Stochastic Circuits for Computing Weighted Ratio With Applications to Multiclass Bayesian Inference Machine

Bayesian inference is one method of statistical inference in machine learning. It predicts the probability that a given test belongs to a certain class and is widely used in various applications such as medical diagnosis, spam classification and fraud detection. The conventional binary architecture of computing the posterior probability is inefficient in practical implementation, which is involved in multiplication, addition and division operations. Recently, it has been shown that simple Muller C-elements, the asynchronous logic units, can perform stochastic Bayesian inference motivated by its truth table when the data is encoded as the bit-stream. The Bayesian inference machine is therefore implemented with low hardware cost. However, such an architecture is employed to compute the posterior probability of two classes only. This brief presents two stochastic circuit designs for computing the weighted ratio with multiple weights for generalized multi-class Bayesian machines. The first design is mainly based on the JK flip flop and multiplexers. The second approach is to construct the finite state machine (FSM) by manipulating the correlation between the input bit-streams. The FSM-based design requires fewer random number sources (RNSs) as compared to the JK flip flop-based implementation. These facts lead to a reduction of hardware area and energy. Simulation results show that the accuracy of the proposed JK flip flop-based and FSM-based designs is almost the same in the tested data sets. As compared to the traditional binary design, the circuit area of the proposed stochastic design is improved by <inline-formula><tex-math notation="LaTeX">$96\%$</tex-math><alternatives><mml:math><mml:mn>96</mml:mn><mml:mi mathvariant="normal">%</mml:mi></mml:math><inline-graphic xlink:href="chu-ieq1-3329998.gif"/></alternatives></inline-formula> at least in the cases of three and four classes. The consumed energy per operation is reduced by <inline-formula><tex-math notation="LaTeX">$58.1\%$</tex-math><alternatives><mml:math><mml:mn>58.1</mml:mn><mml:mi mathvariant="normal">%</mml:mi></mml:math><inline-graphic xlink:href="chu-ieq2-3329998.gif"/></alternatives></inline-formula> at least in the cases of three and four classes.
Benchmarking stereo-derived DSMs to lidar by land cover and slope for resource development in northern Ontario, Canada

ABSTRACT Topographic and elevation data are essential in the development of supporting infrastructure around mining sites. The de facto standard for acquiring elevation data is through light detection and ranging (lidar). The high labour and monetary cost of acquiring lidar has fostered more cost-effective approaches for creating elevation models that use stereo photogrammetry. To assess the accuracy of stereo-photogrammetry-derived elevation models and their potential application, we benchmark satellite (Worldview-2) and aircraft (South Central Ontario Orthoimagery Project; SCOOP) stereo-derived digital surface models (DSMs) against a lidar-derived DSM. Our results show that both stereo-derived DSMs have strong monotonic correlations with lidar across a range of land-cover types and slopes. The overall vertical accuracy of Worldview-2 and SCOOP DSMs are similar and do not meet the United States National Digital Elevation Program (NDEP) standards. However, accuracy assessment across land-cover types and slope categories show that specific land cover types (i.e. grass, row crops/pasture, sparse vegetation and marsh) on gently sloping terrain compare well to lidar data and meet NDEP accuracy standards. We situate the presented research in the context of northern resource development and discuss opportunities to improve the vertical accuracy of stereo-derived DSMs, for example, through unmanned aerial systems.
Alternativen im alternativlosen Kapitalismus

Alles begann mit dem lang gehegten Wunsch des Autors nach einem Büchlein, das den Kommunismus in das Weltgeschehen einbettet. Ein Abendessen mit einem Lektor der Harvard University Press führte zu dem vorliegenden Buch, das im genannten Verlag unter dem Titel „Capitalism, Alone“ erschien und dabei eine Vielzahl von Themen miteinander verknüpft, die Branko Milanovi¥ besonders am Herzen liegen. Der serbisch-amerikanische Ökonom gehört zu den weltweit führenden UngleichheitsforscherInnen. Spätestens mit seiner Elephant Curve, die die weltweiten GewinnerInnen und VerliererInnen der Globalisierung anhand ihrer relativen Einkommenszuwächse im Zeitraum von 1988 bis 2008 darstellte, erreichte er internationale Berühmtheit. Diese Themen beschäftigen den an der City University of New York (CUNY) Lehrenden seit Langem und fließen zusammen mit seiner umfassenden Belesenheit in die vorliegenden 404 Seiten ein. Das Buch ist in fünf Kapitel unterteilt und beginnt mit einem ausführlichen historischen Abriss, der mit der Zweiteilung der Welt in Kommunismus und Kapitalismus nach der Oktoberrevolution beginnt. Für Milanovi¥ ist klar, dass der Kommunismus trotz des Bekenntnisses zur Internationalisierung wahrscheinlich nicht zu einer Globalisierung geführt hätte, da die kommunistischen Gesellschaften autark und nationalistisch geprägt waren. Im Kapitalismus hingegen steht ein universelles und verbindendes Element im Zentrum: „Wir leben in einer Welt, in der alle Akteure dieselben Regeln befolgen und dieselbe Sprache der Gewinnmaximierung sprechen“ (16). Dieses Prinzip entspringt jedoch keiner natürlichen Ordnung, sondern „[v]iele unserer Bedürfnisse sind das Ergebnis der Sozialisierung in der Gesellschaft, in der wir leben [. ]“ (17). Bereits an dieser Stelle des Buches sowie an vielen folgenden scheint der Zwiespalt des Autors zwischen Faszination und Abscheu gegenüber den Auswüchsen des globalen Kapitalismus durch. Historisch und analytisch vergleicht Milanovi¥ in den beiden nächsten Kapiteln zwei von ihm definierte idealtypische Formen des Kapitalismus: den liberalen und den politischen Kapitalismus. Beide konkurrieren aus seiner Sicht um die Vorherrschaft. KennerInnen seiner wissenschaftlichen Publikationen und Monographien sind manche Ausführungen, insbesondere zur Entwicklung der Ungleichheit innerhalb und zwischen Ländern bereits bekannt und an mancher Stelle eine willkommene Wiederholung. Über Neulinge ergießt sich eine Fülle an Informationen und Erkenntnissen, die durchaus als Herausforderung wahrgenommen
A Brief Review of Bone Cell Function and Importance

This review focuses on understanding the macroscopic and microscopic characteristics of bone tissue and reviews current knowledge of its physiology. It explores how these features intricately collaborate to maintain the balance between osteoblast-mediated bone formation and osteoclast-mediated bone resorption, which plays a pivotal role in shaping not only our physical framework but also overall health. In this work, a comprehensive exploration of microscopic and macroscopic features of bone tissue is presented.
A Comprehensive Review of Modifiable Cardiovascular Risk Factors and Genetic Influences in Dementia Prevention

Dementia poses a growing global health challenge, demanding a multifaceted approach to prevention. This comprehensive review delves into the interplay between modifiable cardiovascular risk factors and genetic influences in dementia prevention. We examine key risk factors, including hypertension, diabetes, hyperlipidemia, obesity, smoking, and physical inactivity, elucidating their impact on dementia risk and the underlying biological mechanisms. Genetic factors, notably familial Alzheimer's disease (FAD) and the apolipoprotein E (APOE) gene, are explored in detail, offering insights into their contributions to dementia susceptibility. Importantly, we highlight the complex interrelationship between genetics and modifiable risk factors, emphasizing the need for personalized prevention strategies. Integrating lifestyle modifications and genetic considerations, a holistic approach is paramount in dementia prevention. Implications for public health initiatives and clinical practices underscore the urgency of tailored interventions. Our call to action urges continued research, precision medicine implementation, and collaborative efforts to mitigate the burden of dementia and enhance cognitive well-being globally.
AGROBIODIVERSITY OF CACTUS PEAR (OPUNTIA, CACTACEAE) IN THE MERIDIONAL HIGHLANDS PLATEAU OF MEXICO

Received 13.04. 2011 Accepted 09.07. 2011 Published 22.08. 2011 Mexico is characterized by a remarkable richness of Opuntia, mostly at the Meridional Highlands Plateau; it is also here where the greatest richness of Opuntia variants occurs. Most of these variants have been maintained in homegardens; however, the gathering process which originated these homegardens has been disrupted over the past decades, as a result of social change and the destruction of large wild nopaleras. If the variants still surviving in homegardens are lost, these will be hard to recover, that is, the millenary cultural heritage from the human groups that populated the Mexican Meridional Highland Plateau will be lost forever. This situation motivated the preparation of a catalogue that records the diversity of wild and cultivated Opuntia variants living in the meridional Highlands Plateau. To this end, 379 samples were obtained in 29 localities, between 1998 and 2003. The information was processed through Twinspan. All specimens were identified and preserved in herbaria. Botanical keys and descriptions were elaborated. The catalogue includes information on 126 variants comprising 18 species. There were species with only one variant (Opuntia atropes, O. cochinera, O. jaliscana, O. leucotricha, O. rzedowskii and O. velutina), two (O. durangensis, O. lindheimeri, O. phaeacantha and O. robusta), five (O. joconostle and O. lasiacantha), seven (O. chavena), 12 (O. hyptiacantha and O. streptacantha), 15 (O. ficus-indica), 22 (O. albicarpa), and up to 34 (O. megacantha). Additionally, 267 common cactus pear names were related to those variants. Keywords