Miracle-dz/UniFAR-FTUs huggingface dataset:
A Deep Learning Application Built with Tkinter for Waste Recycling and Recommending Solutions

This paper presents a novel PyTorch model integrated with a Tkinter-based Recycling Recommendation Application to address the pressing issue of waste management. Our waste prediction and classification model achieve high precision by leveraging advanced machine learning techniques and a large dataset. We improve classification accuracy and speed using pre-trained models and transfer learning, which is critical for effective waste management. The accompanying Tkinter application improves recycling recommendations by allowing users to input information through an intuitive interface. Our PyTorch model has exceptional accuracy, scoring 99% on the training set and approximately 96% on validation, which is supported by robust stratified cross-validation. This fusion of cutting-edge machine learning and user-centered design represents a significant step toward more efficient waste management and environmentally friendly waste disposal practices. The system's potential for widespread adoption is highlighted by its accuracy in categorizing various waste items and providing tailored solutions, resulting in a positive environmental impact.
SOCIAL NORMS: AN UNDERESTIMATED AND UNDEREMPLOYED LEVER FOR MANAGING CLIMATE CHANGE

It is widely recognized that communications that make social norms salient can be effective in influencing behavior. What is surprising, given the strength of the evidence, is how little people are aware of the extent to which social norms affect their own behavior. Consequently, this low-cost persuasion strategy is considerably underutilized to promote behaviors to help reduce climate change. In this paper we review recent field experiments that harness the power of social norms to influence pro-environmental behavior. We also elucidate the circumstances under which providing normative information is optimal, as well as circumstances under which such information can backfire to produce the opposite of what a communicator intends.
In the Mood for Vlog

The prevalent “share what's on your mind” paradigm of social media can be examined from the perspective of mood: short-term affective states revealed by the shared data. This view takes on new relevance given the emergence of conversational social video as a popular genre among viewers looking for entertainment and among video contributors as a channel for debate, expertise sharing, and artistic expression. From the perspective of human behavior understanding, in conversational social video both verbal and nonverbal information is conveyed by speakers and decoded by viewers. We present a systematic study of classification and ranking of mood impressions in social video, using vlogs from YouTube. Our approach considers eleven natural mood categories labeled through crowdsourcing by external observers on a diverse set of conversational vlogs. We extract a comprehensive number of nonverbal and verbal behavioral cues from the audio and video channels to characterize the mood of vloggers. Then we implement and validate vlog classification and vlog ranking tasks using supervised learning methods. Following a reliability and correlation analysis of the mood impression data, our study demonstrates that, while the problem is challenging, several mood categories can be inferred with promising performance. Furthermore, multimodal features perform consistently better than single-channel features. Finally, we show that addressing mood as a ranking problem is a promising practical direction for several of the mood categories studied.
Incorporating augmented reality content in Engineering Design Graphics materials

This paper describes the development and integration of augmented reality content with traditional Engineering Design Graphics materials, and presents the results of a preliminary usability study conducted with Freshman Engineering students. The resources developed combine printed text and images with interactive three-dimensional content with the purpose of enhancing the understanding of technical graphics concepts and improving the students' visualization skills. In general, students had a very positive reaction when first presented with the materials and showed an optimistic attitude while interacting with the content. Additionally, augmented reality materials promote the development of self-directed learning skills and self-assessment.
Interpretation of Brain CT Scans in the Field by Critical Care Physicians in a Mobile Stroke Unit

In acute stroke, thromboembolism or spontaneous hemorrhage abruptly reduces blood flow to a part of the brain. To limit necrosis, rapid radiological identification of the pathological mechanism must be conducted to allow the initiation of targeted treatment. The aim of the Norwegian Acute Stroke Prehospital Project is to determine if anesthesiologists, trained in prehospital critical care, may accurately assess cerebral computed tomography (CT) scans in a mobile stroke unit (MSU).
The Association between the History of Cardiovascular Diseases and Chronic Low Back Pain in South Koreans: A Cross-Sectional Study

Background Cardiovascular disease and related risk factors have been suggested as a mechanism leading to atherosclerosis of the lumbar vessels and consequent lumbar pain or sciatica. But there is continued controversy concerning its generalization. This study examined whether cardiovascular disease or its risk factors were associated with chronic low back pain (cLBP) in Koreans. Methods Health surveys and examinations were conducted on a nationally representative sample (n = 23,632) of Koreans. A total of 13,841 eligible participants (aged 20 to 89 years) were examined to determine the association between cardiovascular disease, the Framingham risk score, major cardiovascular risk factors (blood pressure, diabetes, cholesterol, and smoking habits) and chronic LBP. Results The total prevalence of cLBP was 16.6% (men: 10.8%, women: 21.1%) and that in patients with a history of cardiovascular diseases was 36.6% (men: 26.5%, women: 47.1%). The results showed that patients’ medical history of cardiovascular disease was significantly associated with cLBP in both men and women when adjusted for covariates (men: OR 2.16; 95%CI 1.34∼3.49; women: OR 2.26; 95%CI 1.51∼3.38). No association was observed between cLBP and the Framingham risk score, medication for hyperlipemia, hypertension, diabetes, and major cardiovascular risk factors (systolic blood pressure, total cholesterol, high density lipoprotein cholesterol, triglycerides, glucose and smoking habits) in either men or women. Conclusions The prevalence of cLBP is correlated to a history of cardiovascular disease, but not to the major cardiovascular risk factors from the Framingham study. Further studies on whether these results were affected by psychological factors in patients with a history of cardiovascular diseases or whether new potential risk factors from the artery atherosclerosis hypothesis applying to Koreans exist are needed.
Detection of Types of Cancer of Unknown Primary in Big Data Using Map-Reduce Model

This study aims to detect types of Cancer of unknown primary in big data using the MapReduce model. In this research, we want to integrate two calculation methods, i.e., using the K-means clustering algorithm in the parallel programming (MapReduce) text, so that we can acceptably achieve the minimum difference between the actual number of classes in the dataset and the number of recycled clusters. The Rand index is the validation criterion. This research used standard Euclidean Similarity (EZ0) and Cosine Similarity (C) criteria. A total of 18 Rand indices were obtained by running the algorithm on 18 datasets, analyzing the number of samples in each cluster, and comparing them with the real classes in each dataset. Accordingly, 18 Rand indices were obtained, and the result of this operation was monitored with the Euclidean similarity. This result was extracted by averaging the 18 mentioned indices between the FMG and K-Means method compared to the output.
Adaptations in humans for assessing physical strength from the voice

Recent research has shown that humans, like many other animals, have a specialization for assessing fighting ability from visual cues. Because it is probable that the voice contains cues of strength and formidability that are not available visually, we predicted that selection has also equipped humans with the ability to estimate physical strength from the voice. We found that subjects accurately assessed upper-body strength in voices taken from eight samples across four distinct populations and language groups: the Tsimane of Bolivia, Andean herder-horticulturalists and United States and Romanian college students. Regardless of whether raters were told to assess height, weight, strength or fighting ability, they produced similar ratings that tracked upper-body strength independent of height and weight. Male voices were more accurately assessed than female voices, which is consistent with ethnographic data showing a greater tendency among males to engage in violent aggression. Raters extracted information about strength from the voice that was not supplied from visual cues, and were accurate with both familiar and unfamiliar languages. These results provide, to our knowledge, the first direct evidence that both men and women can accurately assess men's physical strength from the voice, and suggest that estimates of strength are used to assess fighting ability.
The Interactive Effect of Sodium Chloride and Diatomaceous Earth (DE) on Bacillus aquimaris

The growth of Bacillus aquimaris was inhibited from 6 - 20 % of NaCl but it showed some tolerance when Diatomaceous earth (DE) added from 2 - 12% NaCl. Concerning the effect of NaCl on polyol production, we can conclude that, the test bacterium showed some tolerate to NaCl by producing glycerol up to 8 % of NaCl. Then decreased sharply. The addition of DE decrease the amount of polyol and glycerol remarkably and this due to the productive effect of DE to the bacterial cells. The SEM figures represented the presence of electron dense bodies due to the accumulation of small particles of DE as protective molecules.
The Use of Wavelet Packet Transform and Artificial Neural Networks in Analysis and Classification of Dysphonic Voices

This paper presents a dysphonic voice classification system using the wavelet packet transform and the best basis algorithm (BBA) as dimensionality reductor and 06 artificial neural networks (ANN) acting as specialist systems. Each ANN was a 03-layer multilayer perceptron with 64 input nodes, 01 output node and in the intermediary layer the number of neurons depends on the related training pathology group. The dysphonic voice database was separated in five pathology groups and one healthy control group. Each ANN was trained and associated with one of the 06 groups, and fed by the best base tree (BBT) nodes' entropy values, using the multiple cross validation (MCV) method and the leave-one-out (LOO) variation technique and success rates obtained were 87.5%, 95.31%, 87.5%, 100%, 96.87% and 89.06% for the groups 01 to 06, respectively.
of Stem Cell Research

Northern White Rhinos (NWR) are functionally extinct, with only two females left on the planet. After various failed assisted reproduction and conservation attempts, one last effort to produce offspring from induced pluripotent stem cells taken from skin of NWR is being performed. After genetic analysis, the twelve White Rhino cell lines stored in the Frozen Zoo at the San Diego Zoo show enough genetic variability to support a population. A reference genome was developed, following the confirmation of successful induced pluripotent stem cells with the presence of SOX2 and OCT4 reprogramming factors. From these cells, primordial germ cells were developed and identified by the presence of PDPN and SOX17 markers, followed by sperm and oocyte development. Recently, four hybrid blastocysts have been developed from NWR sperm and SWR eggs and frozen. The next step is to extract NWR eggs from the last two remaining NWR and create healthy, pure NWR blastocysts that can be placed in a SWR surrogate mother. The generation of a pure Northern White Rhino blastocyst from frozen cell lines.
Ruminant and industrially produced trans fatty acids: health aspects

Fatty acids of trans configuration in our food come from two different sources – industrially produced partially hydrogenated fat (IP-TFA) used in frying oils, margarines, spreads, and in bakery products, and ruminant fat in dairy and meat products (RP-TFA). The first source may contain up to 60% of the fatty acids in trans form compared to the content in ruminant fat which generally does not exceed 6%. In Western Europe, including Scandinavia, the average daily intake of IP-TFA has decreased during the recent decade due to societal pressure and a legislative ban, whereas the intake of RP-TFA has remained stable. In spite of this decrease we have found that in many countries consumption >20 g of IP-TFA in a one-meal menu consisting of some popular foods is possible, even though the average intake of IP-TFA in these countries is low. Subgroups of the populations may therefore, on average, consume >5 g IP-TFA per day. This level of consumption is generally not possible for RP-TFA. A daily intake of 5 g TFA (primarily IP-TFA) is associated with a 29% increased risk of coronary heart disease. Such an association is not found for RP-TFA up to a daily intake of 4 g. The high amount of IP-TFA in popular foods, the evidence of a more harmful effect on health by IP-TFA than by RP-TFA, and the feasibility of eliminating IP-TFA from foods without side effects for the population, suggest that a selective elimination of IP-TFA from our food is a ‘low hanging fruit’ in the quest for a more healthy diet for subgroups of the population.
Report of the Scientific Committee of the Spanish Agency for Food Safety and Nutrition (AESAN) on the assessment of olive oil by its nutritional characteristics in the Nutri-Score labelling system

The Nutri-Score front-of-pack nutritional labelling system uses a code of letters and colours to inform consumers about the nutritional quality of foods and drinks. However, currently this system does not cover all the positive aspects of foods that possess a specific nutritional quality within the Mediterranean diet, as in the case of olive oil and extra-virgin olive oil. The AESAN Scientific Committee has suggested different possibilities for a more accurate assessment of olive oil and especially virgin olive oil, in the Nutri-Score front-of-pack labelling system, taking into consideration those compounds that are beneficial to the consumer owing to their nutritional qualities. These proposals include: differentiating virgin olive oil from other oils in the algorithm’s scoring system, establishing a specific category for virgin olive oil; the positive scoring of individual bioactive
Nutrilyzer: A Mobile System for Characterizing Liquid Food with Photoacoustic Effect

In this paper, we propose Nutrilyzer, a novel mobile sensing system for characterizing the nutrients and detecting adulterants in liquid food with the photoacoustic effect. By listening to the sound of the intensity modulated light or electromagnetic wave with different wavelengths, our mobile photoacoustic sensing system captures unique spectra produced by the transmitted and scattered light while passing through various liquid food. As different liquid foods with different chemical compositions yield uniquely different spectral signatures, Nutrilyzer's signal processing and machine learning algorithm learn to map the photoacoustic signature to various liquid food characteristics including nutrients and adulterants. We evaluated Nutrilyzer for milk nutrient prediction (i.e., milk protein) and milk adulterant detection. We have also explored Nutrilyzer for alcohol concentration prediction. The Nutrilyzer mobile system consists of an array of 16 LEDs in ultraviolet, visible and near-infrared region, two piezoelectric sensors and an ARM microcontroller unit, which are designed and fabricated in a printed circuit board and a 3D printed photoacoustic housing.
On the Routing Protocol Influence on the Resilience of Wireless Sensor Networks to Jamming Attacks

In this work, we compare a recently proposed routing protocol, the multi-parent hierarchical (MPH) protocol, with two well-known protocols, the ad hoc on-demand distance vector (AODV) and dynamic source routing (DSR). For this purpose, we have developed a simulator, which faithfully reifies the workings of a given protocol, considering a fixed, reconfigurable ad hoc network given by the number and location of participants, and general network conditions. We consider a scenario that can be found in a large number of wireless sensor network applications, a single sink node that collects all of the information generated by the sensors. The metrics used to compare the protocols were the number of packet retransmissions, carrier sense multiple access (CSMA) inner loop retries, the number of nodes answering the queries from the coordinator (sink) node and the energy consumption. We tested the network under ordinary (without attacks) conditions (and combinations thereof) and when it is subject to different types of jamming attacks (in particular, random and reactive jamming attacks), considering several positions for the jammer. Our results report that MPH has a greater ability to tolerate such attacks than DSR and AODV, since it minimizes and encapsulates the network segment under attack. The self-configuring capabilities of MPH derived from a combination of a proactive routes update, on a periodic-time basis, and a reactive behavior provide higher resilience while offering a better performance (overhead and energy consumption) than AODV and DSR, as shown in our simulation results.
Exploring Gender Disparities in Factors Influencing Colorectal Cancer Screening Compliance in Singapore.

OBJECTIVE The uptake of colorectal cancer (CRC) screening remains suboptimal in Singapore. Existing research highlights gender-related disparities in screening behaviors. This study aims to evaluate the gender differences in factors associated with CRC screening compliance in Singapore, with a specific focus on cancer screening beliefs and knowledge on CRC screening guidelines. METHODS Data were collected from an online survey on cancer screening belief, knowledge, and practices in Singapore. Multivariate logistic regression analysis was conducted to identify independent factors associated with compliance in CRC screening. RESULTS The study included 633 participants aged 50-69 years, eligible for CRC screening. Only 132 participants (20.9%) complied with CRC screening guidelines with no significant gender differences observed in compliance rates. Most participants held positive beliefs on routine screening (86.9%) and perceived screening benefits in improving treatment outcomes (89.6%) and reducing mortality rates (77.6%). However, both genders exhibited limited knowledge regarding CRC screening guidelines. Only 28.3% were aware that CRC screening should commence at age 50 years. While nearly half of participants knew FIT (44.7%) and colonoscopy (52.0%) as CRC screening modalities, only 27.5% and 15.2% recognized the recommended intervals for FIT and colonoscopy screening respectively. Multivariate analysis revealed a positive association between knowledge on CRC screening guidelines and CRC screening compliance for both genders. Gender-specific variations were observed in the factors associated with CRC screening compliance. Specifically, women with a family history of cancer, believing in routine cancer screening, and prior adherence to breast cancer screening and men within the older cohort (55-69 years) were more likely to comply with CRC screening. CONCLUSION Low compliance with CRC screening was observed in Singapore. Targeted interventions should address gender-specific factors and highlight CRC screening guidelines as a crucial component of cancer education for entire screening eligible population in order to improve CRC screening compliance.
Early Intravenous Infusion of Sodium Nitrite Protects Brain Against In Vivo Ischemia-Reperfusion Injury

Background and Purpose— The rate of nitric oxide (NO) generation from nitrite is linearly dependent on reductions in oxygen and pH levels. Recently, nitrite-derived NO has been reported to exert a profound protection against liver and heart ischemia-reperfusion injury. In this study, we hypothesized that nitrite would be reduced to NO in the ischemic brain and exert NO-dependent neuroprotective effects. Methods— Cerebral ischemia-reperfusion injury was induced by intraluminal thread occlusion of middle cerebral artery in the adult male rats. Solutions of sodium nitrite were infused intravenously at the time of reperfusion. Sodium nitrate and carboxy-PTIO (30 minutes before ischemic surgery), a direct NO scavenger, were infused for comparisons. Results— Nitrite reduced infarction volume and enhanced local cerebral blood flow and functional recovery. The effects were observed at concentrations of 48 nmol and 480 nmol, but not at 4800 nmol nitrite and 480 nmol nitrate. The neuroprotective effects of nitrite were inhibited completely by the carboxy-PTIO. The 480 nmol nitrite attenuated dihydroethidium activity, 3-nitrotyrosine formation, and lipid peroxidation in the ischemic brain. Conclusions— Nitrite exerted profound neuroprotective effects with antioxidant properties in the ischemic brains. These results suggest that nitrite, as a biological storage reserve of NO, may be a novel therapeutic agent in the setting of acute stroke.
High Prevalence of Cryptococcal Antigenemia among HIV-infected Patients Receiving Antiretroviral Therapy in Ethiopia

Background Cryptococcal disease is estimated to be responsible for significant mortality in Sub-Saharan Africa; however, only scarce epidemiology data exists. We sought to evaluate the prevalence of and risk factors for cryptococcal antigenemia in Ethiopia. Methods Consecutive adult HIV-infected patients from two public HIV clinics in Addis Ababa, Ethiopia were enrolled into the study. A CD4 count ≤200 cells/μl was required for study participation. Patients receiving anti-retroviral therapy (ART) were not excluded. A cryptococcal antigen test was performed for all patients along with an interview, physical exam, and medical chart abstraction. Logistic regression analysis was used to assess risk factors for cryptococcal antigenemia. Results 369 HIV-infected patients were enrolled; mean CD4 123 cells/μl and 74% receiving ART. The overall prevalence of cryptococcal antigenemia was 8.4%; 11% in patients with a CD4 count <100 cells/μl, 8.9% with CD4 100 to 150 cells/μl and 5.7% with CD4150-200 cell/μl. 84% of patients with cryptococcal antigenemia were receiving ART. In multivariable analysis, increasing age, self reported fever, CD4 count <100 cells/μl, and site of screening were associated with an increased risk of cryptococcal antigenemia. No individual or combination of clinical symptoms had optimal sensitivity or specificity for cryptococcal antigenemia. Conclusion Cryptococcal antigenemia is high in Ethiopia and rapid scale up of screening programs is needed. Screening should be implemented for HIV-infected patients with low CD4 counts regardless of symptoms or receipt of ART. Further study into the effect of location and environment on cryptococcal disease is warranted.