Sex-differences in socioeconomic status and health-seeking behaviour among tuberculosis patients in transitional Albania in 2012-2013

Aim: There is little scientific evidence about the main determinants of sex discrepancies in tuberculosis rates in Albania. The aim of this study was to assess the sex-differences in socioeconomic characteristics, knowledge and attitudes about tuberculosis and access to health care among tuberculosis patients in Albania, a transitional country in the Western Balkans. Methods: Our analysis involved all the new cases of pulmonary tuberculosis diagnosed in Albania during the period June 2012 – June 2013 (N=197; 69% males; overall mean age: 44±19 years). The recording and reporting system of tuberculosis cases was performed according to the WHO and EuroTB Surveillance guidelines. Information on socioeconomic characteristics of the patients, knowledge and attitudes about tuberculosis and access to health care was also collected. Logistic regression was used to assess the correlates of sex-differences among tuberculosis patients. Results: In multivariable-adjusted models, female sex was positively related to unemployment (OR=3.7, 95%CI=1.8-7.7), bad living conditions (OR=3.0, 95%CI=1.4-6.5), a longer distance to health care facility (OR=3.0, 95%CI=1.4-6.3), a lower level of knowledge about tuberculosis (OR=3.1, 95%CI=1.3-7.1) and a higher level of stigma against tuberculosis (OR=3.6, 95%CI=1.6-7.9). Conclusion: Our study informs about selected correlates of sex-differences in tuberculosis rates in post-communist Albania. Future studies should more vigorously explore determinants of sex-differences in tuberculosis rates in countries of the Western Balkans

Code Transpilation for Hardware Accelerators

DSLs and hardware accelerators have proven to be very effective in optimizing computationally expensive workloads. In this paper, we propose a solution to the challenge of manually rewriting legacy or unoptimized code in domain-specific languages and hardware accelerators. We introduce an approach that integrates two open-source tools: Metalift, a code translation framework, and Gemmini, a DNN accelerator generator. The integration of these two tools offers significant benefits, including simplified workflows for developers to run legacy code on Gemmini generated accelerators and a streamlined programming stack for Gemmini that reduces the effort required to add new instructions. This paper provides details on this integration and its potential to simplify and optimize computationally expensive workloads

Prevalence of chronic obstructive pulmonary disease (COPD) in Albania

Aim: The objective of this study was to determine the prevalence of COPD and its associated factors among adults in Albania. Methods: This was a cross-sectional study conducted in Albania in 2013-14. A nation-wide representative sample of 1200 adults aged ≥40 years was selected using multistage cluster sampling technique. All participants were interviewed about socio-demographic characteristics, respiratory symptoms, smoking status and clinical characteristics. Spirometry was performed according to standard methods. COPD was defined as post-bronchodilator FEV1/FVC ratio <70% predicted. Results: Of the 1200 adults invited to participate, 939 adults or 78% (467 men and 472 women) were eligible for the study. The overall COPD prevalence (GOLD stage 1 or higher) was 12.4%; it was higher in men (17.4%) than in women (7.7%). Using Lower Limit of Normal (LLN), the prevalence of COPD was 9.9%, again higher in men (13.2%) than women (6.6%). The prevalence of doctor-diagnosed COPD was 1.3% (1.9% in men, 0.6 % in women). Male sex, smoking and increasing age were significantly associated with COPD diagnosis. Conclusion: The overall prevalence of COPD in Albania was 9.9% using BOLD standards. Smoking and increasing age were the main risk factors for COPD. The study highlights the importance of raising awareness of COPD among health professionals

Using online photovoice and community-based participatory research to understand facilitators and barriers to online distance education during COVID-19

In this study, we used online photovoice and community-based participatory research to understand and address facilitators and barriers to online distance education for college students in Turkey. Out of 260 students who consented to the study, 240 shared the most important facilitator, 190 shared the most important barriers, and 190 completed our contextual questions related to their education. We used online interpretative phenomenological analysis to identify key facilitators and barriers. Ten main facilitator themes emerged, including advantages of using Internet and technology (n = 104; 43%); enjoyable feelings (n = 61; 25%); saving time (n = 37; 15%); and social support (n = 28; 12%). Nine main barrier themes emerged, including challenges of online education (n = 51; 31%); psychopathology and unenjoyable feelings, thoughts, and bodily sensations (n = 37; 19%); Internet problems (n = 34; 18%); and COVID-19 restrictions (n = 30; 16%). © 2023 Open and Distance Learning Association of Australia, Inc

Prevalence of chronic obstructive pulmonary disease (COPD) in Albania

Aim: The objective of this study was to determine the prevalence of COPD and its associated factors among adults in Albania. Methods: This was a cross-sectional study conducted in Albania in 2013-14. A nation-wide representative sample of 1200 adults aged ≥40 years was selected using multistage cluster sampling technique. All participants were interviewed about socio-demographic characteristics, respiratory symptoms, smoking status and clinical characteristics. Spirometry was performed according to standard methods. COPD was defined as post-bronchodilator FEV1/FVC ratio <70% predicted. Results: Of the 1200 adults invited to participate, 939 adults or 78% (467 men and 472 women) were eligible for the study. The overall COPD prevalence (GOLD stage 1 or higher) was 12.4%; it was higher in men (17.4%) than in women (7.7%). Using Lower Limit of Normal (LLN), the prevalence of COPD was 9.9%, again higher in men (13.2%) than women (6.6%). The prevalence of doctor-diagnosed COPD was 1.3% (1.9% in men, 0.6 % in women). Male sex, smoking and increasing age were significantly associated with COPD diagnosis. Conclusion: The overall prevalence of COPD in Albania was 9.9% using BOLD standards. Smoking and increasing age were the main risk factors for COPD. The study highlights the importance of raising awareness of COPD among health professionals.   Conflicts of interest: None declared

Phytochemical compositions, antioxidant properties, enzyme inhibitory effects of extracts of four endemic Lathyrus L. taxa from Türkiye and a taxonomic approach

ABSTRACT Lathyrus is an economically important genus, with different parts of some species used as foodstuff or animal feed. In this study, phytochemical compositions and bioactivities of Lathyrus brachypterus var. brachypterus, L. brachypterus var. haussknechtii, L. nivalis subsp. sahinii and L. tefennicus taxa which are endemic to Türkiye were investigated. Total phenolic and flavonoid contents (TPC, TFC) of methanolic extracts were detected. Then, phytochemical compositions, antioxidant features (radical scavenging (DPPH: 1,1-diphenyl-2-picrylhydrazyl, ABTS: 2,2′-azino-bis(3 ethylbenzothiazoline) 6 sulfonic acid), reducing power (FRAP:Ferric ion reducing antioxidant power, CUPRAC:Cupric ion reducing antioxidant capacity), metal chelating activity (MCA), and the phosphomolybdenum assays (PDA)) and enzyme inhibitory properties of the extracts were also determined. The highest values were found at L. brachypterus var. brachypterus for TPC, L. brachypterus var. haussknechtii for TFC. The highest antioxidant properties were seen in extracts of L. brachypterus var. brachypterus in DPPH, ABTS, FRAP, CUPRAC and PDA assays, while in extract of L. nivalis subsp. sahinii in MCA. The highest enzyme inhibitory activity was found in extract of L. brachypterus var. brachypterus in tyrosinase and glucosidase assays, while in extracts of L. nivalis subsp. sahinii in AChE (acetylcholinesterase), BChE (butyrylcholinesterase) and amylase. Finally, a taxonomic evaluation was made by considering the phytochemicals

Full Stack Optimization of Transformer Inference: a Survey

Recent advances in state-of-the-art DNN architecture design have been moving toward Transformer models. These models achieve superior accuracy across a wide range of applications. This trend has been consistent over the past several years since Transformer models were originally introduced. However, the amount of compute and bandwidth required for inference of recent Transformer models is growing at a significant rate, and this has made their deployment in latency-sensitive applications challenging. As such, there has been an increased focus on making Transformer models more efficient, with methods that range from changing the architecture design, all the way to developing dedicated domain-specific accelerators. In this work, we survey different approaches for efficient Transformer inference, including: (i) analysis and profiling of the bottlenecks in existing Transformer architectures and their similarities and differences with previous convolutional models; (ii) implications of Transformer architecture on hardware, including the impact of non-linear operations such as Layer Normalization, Softmax, and GELU, as well as linear operations, on hardware design; (iii) approaches for optimizing a fixed Transformer architecture; (iv) challenges in finding the right mapping and scheduling of operations for Transformer models; and (v) approaches for optimizing Transformer models by adapting the architecture using neural architecture search. Finally, we perform a case study by applying the surveyed optimizations on Gemmini, the open-source, full-stack DNN accelerator generator, and we show how each of these approaches can yield improvements, compared to previous benchmark results on Gemmini. Among other things, we find that a full-stack co-design approach with the aforementioned methods can result in up to 88.7x speedup with a minimal performance degradation for Transformer inference