Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of high sensitivity photonic sensing structures based on porous silicon substrates

Health and well-being have always been the center of attention of many research institutions and companies around the world. This led the technology to develop in the chemical, biological, medical and clinical fields with the aim to provide a better protection to the human being. As a consequence, a competition is born between the time necessary to the disease to progress and the time necessary to man to treat such disease. In order to win this competition, it is necessary to act with anticipation, when disease is not too developed yet. This is possible by performing an early-detection. The achievement of this goal paves the way for the development of optical biosensing devices able to detect the presence of certain molecules at extremely low concentrations. Among them, photonic integrated structures are finding a great success due to their considerably high sensitivity. However, the sensing mechanism of these structures is based on the interaction between the evanescent wave, propagating along the structure surface, and the target analyte to detect. In this way, not all the field propagating in the photonic structure is used for sensing purposes, but rather only a small amount of it. This represents a crucial limitation of the integrated photonics based sensors. The aim of this PhD Thesis is to overcome this limitation and to develop more sensitive photonic sensing structures able to detect the lowest concentration possible. To this aim, we focused on the study of porous silicon as platform for the development of optical structures with extremely high sensitivities thanks to the fact that the sensing interaction takes place directly inside the structure itself, allowing to exploit all the field propagating in the structure.
Design of two combined health recommender systems for tailoring messages in a smoking cessation app

In this article, we describe the design of two recommender systems (RS) designed to support the smoking cessation process through a mobile application. We plan to use a hybrid RS (content-based, utility-based, and demographic filtering) to tailor health recommendation messages, and a content-based RS to schedule a timely delivery of the message. We also define metrics that we will use to assess their performance, helping people quit smoking when we run the pilot.
MICRO-/NANOTECHNOLOGIES TO ENGINEER MICROENVIRONMENTAL CUES FOR REGENERATIVE HEART VALVE THERAPIES

Scaffold-based regenerative heart valve therapy represents a promising and innovative approach to address the unmet clinical need in treating valvular heart diseases. However, current tissue-engineered heart valve scaffolds often suffer from issues such as architectural and mechanical mismatch to native valve leaflet, thrombogenicity, and calcification tendency. Our overall goal is to provide effective strategies to improve the design of regenerative heart valve therapies by alleviating these common issues. This dissertation summarizes our efforts to develop micro-/nanotechnology-based strategies in mimicking the fibrous architecture and mechanical properties of the native valves while improving the biocompatibility of tissue-engineered scaffolds. We first synthesized a novel series of polyethylene glycol (PEG) functionalized biodegradable elastomers. With different molar ratios and molecular weights of PEG in the polymer backbone, these biodegradable and biocompatible elastomers possessed widely tunable mechanical properties and desirable degradation mechanism. We then fabricated PEGylated biodegradable elastomers into fibrous scaffolds by electrospinning. The introduction of PEG into the polymer backbone led to reduced thrombogenicity of the fibrous scaffolds. Moreover, the uniaxial and cyclic mechanical properties of fibrous scaffolds could be tuned to mimic those of the native valve leaflets. The electrospinning process was further modified to fabricate anisotropic fibrous scaffolds. By modulating polymer formulation, fibrous scaffolds were produced to possess anisotropic biaxial mechanical properties. The anisotropic nature of scaffold also guided the alignment of human valvular interstitial cells (hVICs) seeded on the scaffolds. To address the calcification tendency of heart valve substitutes, we developed shape-specific cerium oxide nanoparticles (CNPs), which have unique properties to mitigate oxidative stress. We demonstrated that the oxidative stress exacerbated the calcification in hVICs. We then demonstrated the effectiveness of CNPs in alleviating oxidative stress and preventing calcification in hVICs. Finally, we combined antioxidant CNPs with anisotropic fibrous scaffolds to obtain nanocomposite scaffolds. These scaffolds possessed antioxidant properties and supported hVIC attachment and proliferation. In an oxidative stress-induced calcification model, hVICs cultured on CNP encapsulated scaffolds displayed reduced calcification tendency. Collectively, using micro-/nanotechnology-based strategies, we developed novel tissue-engineered heart valve scaffolds with anisotropic mechanical properties and the potential to mitigate the thrombogenicity and calcification frequently observed in current valve replacement therapies.
Emerging bioinformatics for the metabolome

Metabolic profiling applied to functional genomics (metabolomics) is in an early stage of development. Here, the technologies used for metabolite profiling are briefly covered, illustrated by a few pioneering studies. Issues related to bioinformatics, namely data analysis, visualisation and archival, are the main focus of this review. Arguably there is already a need for databases containing metabolite profiles specific for a single organism, and a generic repository containing all metabolite profiling results, regardless of species. Data analyses and visualisations that combine the biological context with chemistry details are suggested as being the most promising.
Potato skin proteome is enriched with plant defence components

Periderm is a tissue of secondary origin that replaces damaged epidermis. It can be found in underground plant organs, as an above-ground tissue of woody species (cork), and as a wound-healing tissue. Its outer layers are composed of phellem cells with suberized walls that constitute a protective barrier, preventing pathogen invasion and fluid loss. In potato, a model for periderm studies, periderm tissue replaces the epidermis early in tuber development and the suberized phellems constitute the tuber's skin. To identify factors involved in phellem/skin development and that play a role in its defensive characteristics, two-dimensional gel electrophoresis was used to compare the skin and parenchymatic flesh proteomes of young developing tubers. Proteins exhibiting differentially high signal intensity in the skin were sorted by functional categories. As expected, the differential skin proteome was enriched in proteins whose activity is characteristic of actively dividing tissues such as cell proliferation, C1 metabolism, and the oxidative respiratory chain. Interestingly, the major functional category consisted of proteins (63%) involved in plant defence responses to biotic and abiotic stresses. This group included three isozymes of caffeoyl-CoA O-methyltransferase and five isozymes of peroxidase that may play a role in suberization processes. The differential expression of these proteins in the skin was further verified by RT-PCR of their corresponding transcripts in skin and tuber flesh samples. The results presented here shed light on the early events in skin development and further expand the concept of the periderm as a protective tissue containing an array of plant defence components.
Acquired Immunity Plays an Important Role in the Development of Murine Experimental Pancreatitis Induced by Alcohol and Lipopolysaccharide

Objective Although chronic alcohol ingestion is the major cause of chronic pancreatitis, less than 10% of alcohol abusers develop this disease. To address this issue, we created a murine model of pancreatitis induced by alcohol and lipopolysaccharide (LPS) and analyzed its immune responses. Methods C57BL/6 mice were administered 20% ethanol (AL) in their drinking water and then injected intraperitoneally with LPS twice weekly for 4 weeks. Severe combined immunodeficient mice were reconstituted with splenocytes, CD4+ cells, or CD8+ T cells isolated from wild-type mice and then treated similarly. The severity of pancreatitis was graded histologically, and serum cytokine levels were measured. Results Ethanol alone did not cause pancreatitis. However, the administration of AL+LPS or LPS alone induced pancreatitis. The histological scores were higher in the mice treated with AL+LPS than in those treated with LPS. Serum levels of interleukin 1&bgr;, interferon-&ggr;, and tumor necrosis factor &agr; were elevated in the AL+LPS-treated mice. The severe combined immunodeficient mice developed pancreatitis only after their reconstitution with splenocytes, CD4+ cells, or CD8+ T cells. Conclusions Repeated stimulation of the innate immune system is necessary, but not sufficient, to cause pancreatitis. The participation of the acquired immune response is essential for the development of the disease.
NEW STATISTICAL METHODS FOR ALLOMETRY WITH APPLICATION TO FLORIDA RED‐WINGED BLACKBIRDS

Allometry, the association of size and shape in populations of organisms, is the subject of an extensive literature (Reeve and Huxley, 1945; Gould, 1966, 1975; Spielman, 1973; Sprent, 1972; Thorpe, 1976). In this paper we present new statistical methods for the study of size and shape, and use these methods to study the morphology of red-winged blackbirds, Agelaius phoeniceus, breeding in Florida. We use definitions of size and shape variables that permit the study of the entire statistical distribution of a given variable. We offer these methods as an alternative to classical methods based on the allometric equation in which relations are summarized in single coefficients reflecting at best the mean trend of shape with some size variables. Our alternative goal is to determine visually and geometrically meaningful size and shape variables which permit the direct study of the association of size and shape. This paper is in two parts. In the first part we discuss definitions of size and shape variables and summarize statistical results which include exact tests for sizeshape associations (Mosimann, 1970, 1975a, 1975b). In the second part we use these methods to study geographic variation in red-winged blackbirds in Florida. Throughout we consider the following situation: N individuals are independently sampled from some population. For each individual there are k positive measurements, all in the same units, say millimeters. For the i-th individual we then
On the Partitioning Capabilities of Feedforward Neural Networks with Sigmoid Nodes

In this letter, the capabilities of feedforward neural networks (FNNs) on the realization and approximation of functions of the form g: R1 A, which partition the R1 space into polyhedral sets, each one being assigned to one out of the c classes of A, are investigated. More specifically, a constructive proof is given for the fact that FNNs consisting of nodes having sigmoid output functions are capable of approximating any function g with arbitrary accuracy. Also, the capabilities of FNNs consisting of nodes having the hard limiter as output function are reviewed. In both cases, the two-class as well as the multiclass cases are considered.
Characterization of a NADH-Dependent Glutamate Dehydrogenase Mutant of Arabidopsis Demonstrates the Key Role of this Enzyme in Root Carbon and Nitrogen Metabolism[W]

A third isoenzyme of Glu dehydrogenase (GDH) is expressed in mitochondria of Arabidopsis root companion cells. A GDH triple mutant differed greatly from the wild type in continuous darkness, suggesting that the main function of the enzyme is to provide 2-oxoglutarate for the tricarboxylic acid cycle, leading to an accumulation of Ala, γ-aminobutyrate, and Asp in both roots and leaves. The role of NADH-dependent glutamate dehydrogenase (GDH) was investigated by studying the physiological impact of a complete lack of enzyme activity in an Arabidopsis thaliana plant deficient in three genes encoding the enzyme. This study was conducted following the discovery that a third GDH gene is expressed in the mitochondria of the root companion cells, where all three active GDH enzyme proteins were shown to be present. A gdh1-2-3 triple mutant was constructed and exhibited major differences from the wild type in gene transcription and metabolite concentrations, and these differences appeared to originate in the roots. By placing the gdh triple mutant under continuous darkness for several days and comparing it to the wild type, the evidence strongly suggested that the main physiological function of NADH-GDH is to provide 2-oxoglutarate for the tricarboxylic acid cycle. The differences in key metabolites of the tricarboxylic acid cycle in the triple mutant versus the wild type indicated that, through metabolic processes operating mainly in roots, there was a strong impact on amino acid accumulation, in particular alanine, γ-aminobutyrate, and aspartate in both roots and leaves. These results are discussed in relation to the possible signaling and physiological functions of the enzyme at the interface of carbon and nitrogen metabolism.
Combinable memory-block transactions

This paper formalizes and studies combinable memory-block transactions (MBTs). The idea is to encode short programs that operate on a single cache/memory block and then to specify such a program with a memory request. The code is then executed at the cache or memory controller, atomically with respect to other accesses to that block by this or other processors. The combinable form allows combining within the memory system or network. In addition to allowing for the standard set of read-modify-write operations (e.g., test-and-set, compare-and-swap, fetch-and-add), MBTs can be used to define other useful operations--such as a fetch-and-add that does not decrement below zero. We show how MBTs can be used to design simple and efficient implementations of a variety of protocols and algorithms, including a priority write, a semaphore with a non-blocking P operation, a bounded queue, and a timestamp-based transactional memory system. In all cases the protocols gain some advantage by using MBTs that are different from the standard set of operations. To gain an understanding of the efficiency that can be gained by using combining, we define a notion of bounded contention and show that all our protocols have bounded contention under arbitrary loads.
A review on Purisha Pariksha in Ayurveda

Stool examination is an important laboratory investigative tool in medicine, which is used to understand the health and disease condition of a person. It is also included in Ashtasthana Pariksha. The factors which are described under Ashtasthana Pariksha indicate that these are the body parts or metabolic products, where there will be changes when a person suffers from diseases. Observing these changes, the diagnosis can be made, or these can help as tools in diagnosing a disease. The changes pertaining to Purisha (stool) have been described under various disease conditions in Brihattrayi but are scattered. Hence, a study is aimed to compile all such scattered data related to changes in stool in various disease conditions by following the scheme of Sushruta's Shadvidha Pariksha (6-fold examination). This will provide the first-hand information about the changes in stool and will act as a guide to diagnose the disease. Jala Nimajjana Purisha Pariksha is also another tool through which the status of Agni and the presence of Ama can be detected.
The meaning of pain: A cultural formulation of a Syrian woman in Sweden

Ethnography provides a method for psychiatric assessment to obtain an insight into the patient’s culture, context, and life situation. The Outline for a Cultural Formulation (CF) is an ethnography-based, idiographic formulation intended to complement the multiaxial assessment in DSM-IV. Its contribution to routine clinical praxis will be discussed with reference to a case of a Syrian-born woman in Sweden. Using the CF in the clinical diagnostic process shifted understanding of the patient’s suffering from a mainly somatic frame of reference to an emphasis on emotional and social aspects. The usefulness of ethnography in clinical psychiatric diagnostic practice is discussed.
Breast Cancer Screening Practices Among Hong Kong Chinese Women

Background: Although the incidence rates of breast cancer have been increasing remarkably in Hong Kong over the last 2 decades, little is known on breast cancer screening practices among this group of women. Objectives: This study aimed to report breast cancer screening practices among Hong Kong Chinese women and to examine the relationship between (1) demographic factors and (2) the modified Chinese Breast Cancer Screening Beliefs Questionnaire (CBCSB) score and women’s breast screening behaviors. Methods: A descriptive and cross-sectional method was used. Both English and Chinese versions of the modified CBCSB were administered. Of 946 Hong Kong Chinese women older than 18 years and invited to participate in the study, 753 (79.6%) completed and returned the questionnaire. Results: The majority of participants (70%–90%) had heard of breast self-examination (BSE), clinical breast examination (CBE), and mammograms. Only 33.3% performed a BSE monthly; 37.8% and 32.7% of women within the targeted age group had a CBE annually and had a mammogram every 2 years, respectively. Being married and part-time employment were positively associated with women who performed BSE as recommended. In terms of modified CBCSB score, women who had BSE, CBE, and mammogram as recommended had significantly higher scores on the subscale attitudes to health check-up. Conclusion: Attitudes toward health check-up was influential in compliance with breast cancer screening practices among Chinese-Australian women. Implications for Practice: Effort should be focused on specific subgroups of Hong Kong Chinese women, to fully understand the barriers involved in participating in breast cancer screening practices.
Anomalous Cerebellar Anatomy in Chinese Children with Dyslexia

The cerebellar deficit hypothesis for developmental dyslexia claims that cerebellar dysfunction causes the failures in the acquisition of visuomotor skills and automatic reading and writing skills. In people with dyslexia in the alphabetic languages, the abnormal activation and structure of the right or bilateral cerebellar lobes have been identified. Using a typical implicit motor learning task, however, one neuroimaging study demonstrated the left cerebellar dysfunction in Chinese children with dyslexia. In the present study, using voxel-based morphometry, we found decreased gray matter volume in the left cerebellum in Chinese children with dyslexia relative to age-matched controls. The positive correlation between reading performance and regional gray matter volume suggests that the abnormal structure in the left cerebellum is responsible for reading disability in Chinese children with dyslexia.
Text to Photo-Realistic Image Synthesis using Generative Adversarial Networks

Innovative design patterns have traditionally been constrained by time-consuming and expertise-intensive methods, limiting diversity and creativity in design. To overcome these challenges, our research focuses on revolutionizing the design process by leveraging Generative Adversarial Networks (GANs). Our goal is to offer an affordable and cutting-edge solution that enables the creation of unique design patterns based on user input text. By harnessing the power of GANs, we can generate high-resolution images, reducing the reliance on expensive designers and fostering creativity and idea generation in the design sector. Our methodology involves building upon a diverse dataset of sunflower images and associated text data borrowed from the Oxford-102 flowers dataset. We meticulously collect, clean, and normalize this dataset to ensure optimal training. U sing an encoder-decoder architecture, we train a GAN -based generative model to produce remarkable sunflower patterns. To enhance usability, we have developed a user-friendly graphical user interface (GUI) that allows users to input text and receive corresponding sunflower images seamlessly. Our current model has exhibited promising results, achieving an inception score of 3.45 ± 0.05 in generating sunflower patterns. These outcomes demonstrate the feasibility of our approach, which not only reduces design costs but also fosters innovation and ingenuity within the industry. By making this solution publicly accessible, we aim to support local businesses and individuals with limited finances in creating distinctive design patterns.
Additive Manufacturing Technology for Biomedical Components: A review

Over the last decades, additive manufacturing has shown potential application in ranging fields. No longer a prototyping technology, it is now being utilised as a manufacturing technology for giant industries such as the automotive, aircraft and recently in the medical industry. It is a very successful method that provides health-care solution in biomedical sectors by producing patient-specific prosthetics, improve tissues engineering and facilitate pre-operating session. This paper thus presents a brief overview of the most commercially important additive manufacturing technologies, which is currently available for fabricating biomedical components such as Stereolithography (SLA), Selective Laser Sintering (SLS), Selective Laser Melting (SLM), Fused Deposition Modelling (FDM) and Electron Beam Melting (EBM). It introduces the basic principles of the main process, highlights some of the beneficial applications in medical industry and the current limitation of applied technology.
Enhancing Breast Cancer Screening: Mammogram Image Analysis with Multiclass Support Vector Machine

Mammography is an essential screening test for the early detection of breast cancer, significantly increasing the patient's chances of complete recovery. In this paper, a Multi-Class Support Vector Machines (MSVM) is presented to address the overfitting problem and enhance the technique's performance in detecting locations and areas of breast cancer. This approach proves to be particularly effective in high-dimensional spaces, offering advantages in the context of breast cancer detection, where datasets may contain a large number of features. The MIAS dataset in the classification stage utilizing 60 breast cancer images including 100 malignant and 100 benign breast cancer images. All these images have been labeled with 63 images labeled as normal and 37 images as benign or micro, with an original pixel size of $\boldsymbol{1024}\times \boldsymbol{1024}$. After segmentation using Particle Swarm Optimizer (PSO) to segment nuclei and non-nuclei cells and involved parallel computing and global optimization to achieve superior results for the Super pixel. Feature extraction was performed using the Grey Level Co-Occurrence Matrix (GLCM). Finally, the (MSVM) classifier was utilized to grade the histology breast images. The experimental results demonstrate that the MSVM achieved an accuracy rate of 98.90% surpassing other existing models such as Convolutional Neural Network, Deep Neural Network, and Support Vector Machine.