Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Combinations of Dietary Vitamin C and Acetylsalicylic Acid on Growth Performance, Carcass Traits and, Serum and Immune Response Parameters in Broilers

Simple Summary Chicken meat has become increasingly popular as a protein source due to its favorable protein content and balanced amino acid profile. Advances in genetics and feeding practices have led to rapid growth in commercial broiler production to meet consumer demands. As consumer preferences shift toward healthier food options, there is a need to enhance meat production and quality in the poultry industry. Compounds with antioxidant properties, such as vitamin C (VC) and acetylsalicylic acid (ASA), have been tested due to their antioxidant and anti-inflammatory properties. Studies have shown positive effects of both in growth performance and immune functions. While individual studies have explored the effects of vitamin C and ASA supplementation in broilers, few have investigated their combined effects under non-stressful conditions. This study aimed to fill this gap and revealed significant effects of ASA and VC combined supplementation, with improvements noted in growth performance, carcass composition and immune response and cecal coli count. However, creatine kinase levels increased with ASA and VC intake. These findings highlight the complex interactions between ASA and VC supplementation in broilers. Further investigation is warranted to explore optimal dosages and potential effects in non-stressful conditions. Abstract This study aimed to investigate the combined effects of ascorbic acid (VC) and acetylsalicylic acid (ASA) on broiler health and performance. A total of 200 Ross 308 male broilers were divided into five groups, each receiving different dietary combinations of ASA and VC (ASA: 50 or 100 mg/kg; VC: 200 or 400 mg/kg). The 42-day trial assessed parameters such as feed intake, average daily gain (ADG), feed conversion ratio (FCR), carcass characteristics, serum parameters, immune response and cecal microbial flora. The results indicate significant treatment effects on feed intake and growth performance, with a higher feed intake of ADG and FCR in treatment groups (p < 0.05). Serum lipid parameters were unaffected, but creatine kinase increased with ASA and VC intake (p < 0.05). Changes in sheep red blood cell titers and influenza antibodies were noted (p < 0.05). The combination of ASA and VC positively influenced carcass traits, reducing abdominal fat and altering the ratio of immune response organs to body weight (p < 0.05). Additionally, the cecal E. coli count decreased with treatment (p < 0.05). This study underscores the intricate interactions between ASA and VC supplementation, growth performance and carcass composition and immune response in broilers. Further research is warranted to explore dosage nuances and variations under specific stress conditions.
Digital WPI

Semantically rich metadata is foreseen to be pervasive in tomorrow’s cyber world. People are more willing to store metadata in the hope that such extra information will enable a wide range of novel business intelligent applications. Provenance is metadata which describes the derivation history of data. It is considered to have great potential for helping the reasoning, analyzing, validating, monitoring, integrating and reusing of data. In this paper, we introduce Butterﬂy, a provenance management system, which oﬀers the modeling, storage, and query of provenance.
Long-lasting forms of plasticity through patterned ultrasound-induced brainwave entrainment

Achieving long-lasting neuronal modulation with low-intensity, low-frequency ultrasound is challenging. Here, we devised theta burst ultrasound stimulation (TBUS) with gamma bursts for brain entrainment and modulation of neuronal plasticity in the mouse motor cortex. We demonstrate that two types of TBUS, intermittent and continuous TBUS, induce bidirectional long-term potentiation or depression-like plasticity, respectively, as evidenced by changes in motor-evoked potentials. These effects depended on molecular pathways associated with long-term plasticity, including N-methyl-d-aspartate receptor and brain-derived neurotrophic factor/tropomyosin receptor kinase B activation, as well as de novo protein synthesis. Notably, bestrophin-1 and transient receptor potential ankyrin 1 play important roles in these enduring effects. Moreover, pretraining TBUS enhances the acquisition of previously unidentified motor skills. Our study unveils a promising protocol for ultrasound neuromodulation, enabling noninvasive and sustained modulation of brain function.
Wire Bonding in Microelectronics: Materials, Processes, Reliability, and Yield

Technical Introduction to the Second Edition. Ultrasonic Bonding Systems and Technologies (Including Ultrasonic Wire Bonding Mechanism). Some Aspects of Bonding Wire Characteristics That can Affect Bonding, Reliability, or Testing. Wire Bond Testing. Gold-Aluminum Intermetallic Compounds and Other Metallic Interface Reactions Encountered in Wire Bonding. Bond Failures Resulting from Gold-Plating Impurities and Conditions. Cleaning to Improve Bondability and Reliability. Mechanical Problems in Wire Bonding. High-Yield and Fine-Pitch Wire Bonding. Wire Bonding to Multichip Modules and Other Soft Substrates. Glossary. Index.
Pathogenetic Contributions and Therapeutic Implications of Transglutaminase 2 in Neurodegenerative Diseases

Neurodegenerative diseases encompass a heterogeneous group of disorders that afflict millions of people worldwide. Characteristic protein aggregates are histopathological hallmark features of these disorders, including Amyloid β (Aβ)-containing plaques and tau-containing neurofibrillary tangles in Alzheimer’s disease, α-Synuclein (α-Syn)-containing Lewy bodies and Lewy neurites in Parkinson’s disease and dementia with Lewy bodies, and mutant huntingtin (mHTT) in nuclear inclusions in Huntington’s disease. These various aggregates are found in specific brain regions that are impacted by neurodegeneration and associated with clinical manifestations. Transglutaminase (TG2) (also known as tissue transglutaminase) is the most ubiquitously expressed member of the transglutaminase family with protein crosslinking activity. To date, Aβ, tau, α-Syn, and mHTT have been determined to be substrates of TG2, leading to their aggregation and implicating the involvement of TG2 in several pathophysiological events in neurodegenerative disorders. In this review, we summarize the biochemistry and physiologic functions of TG2 and describe recent advances in the pathogenetic role of TG2 in these diseases. We also review TG2 inhibitors tested in clinical trials and discuss recent TG2-targeting approaches, which offer new perspectives for the design of future highly potent and selective drugs with improved brain delivery as a disease-modifying treatment for neurodegenerative disorders.
SPR spectroscopic analysis of myosin binding to wild type and mutant UNC45B

UNC45B is a multidomain molecular chaperone that is essential for the proper folding and function of myosin. It has previously been demonstrated that the UCS domain is responsible for the chaperoning function of UNC45B and that removing its client-binding loop leads to a significant change in its solution conformation and a reduced chaperoning function. Here, we report the direct quantification of affinities of myosin binding to wild type and mutant UNC45B using surface plasmon resonance (SPR) spectroscopy. We found that deletion of the client-binding loop in UNC45B resulted in a dramatic decrease in myosin affinity.
Activity of biogenic silver nanoparticles in planktonic and biofilm-associated Corynebacterium pseudotuberculosis

Corynebacterium pseudotuberculosis is a gram-positive bacterium and is the etiologic agent of caseous lymphadenitis (CL) in small ruminants. This disease is characterized by the development of encapsulated granulomas in visceral and superficial lymph nodes, and its clinical treatment is refractory to antibiotic therapy. An important virulence factor of the Corynebacterium genus is the ability to produce biofilm; however, little is known about the characteristics of the biofilm produced by C. pseudotuberculosis and its resistance to antimicrobials. Silver nanoparticles (AgNPs) are considered as promising antimicrobial agents, and are known to have several advantages, such as a broad-spectrum activity, low resistance induction potential, and antibiofilm activity. Therefore, we evaluate herein the activity of AgNPs in C. pseudotuberculosis, through the determination of minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC), antibiofilm activity, and visualization of AgNP-treated and AgNP-untreated biofilm through scanning electron microscopy. The AgNPs were able to completely inhibit bacterial growth and inactivate C. pseudotuberculosis at concentrations ranging from 0.08 to 0.312 mg/mL. The AgNPs reduced the formation of biofilm in reference strains and clinical isolates of C. pseudotuberculosis, with interference values greater than 80% at a concentration of 4 mg/mL, controlling the change between the planktonic and biofilm-associated forms, and preventing fixation and colonization. Scanning electron microscopy images showed a significant disruptive activity of AgNP on the consolidated biofilms. The results of this study demonstrate the potential of AgNPs as an effective therapeutic agent against CL.
Monocyte Chemoattractant Protein-1 (MCP-1), Activin-A and Clusterin in Children and Adolescents with Obesity or Type-1 Diabetes Mellitus

Inflammation plays a crucial role in diabetes and obesity through macrophage activation. Macrophage chemoattractant protein-1 (MCP-1), activin-A, and clusterin are chemokines with known roles in diabetes and obesity. The aim of this study is to investigate their possible diagnostic and/or early prognostic values in children and adolescents with obesity and type-1 diabetes mellitus (T1DM). Methods: We obtained serum samples from children and adolescents with a history of T1DM or obesity, in order to measure and compare MCP-1, activin-A, and clusterin concentrations. Results: Forty-three subjects were included in each of the three groups (controls, T1DM, and obesity). MCP-1 values were positively correlated to BMI z-score. Activin-A was increased in children with obesity compared to the control group. A trend for higher values was detected in children with T1DM. MCP-1 and activin-A levels were positively correlated. Clusterin levels showed a trend towards lower values in children with T1DM or obesity compared to the control group and were negatively correlated to renal function. Conclusions: The inflammation markers MCP-1, activin-A, and clusterin are not altered in children with T1DM. Conversely, obesity in children is positively correlated to serum MCP-1 values and characterized by higher activin-A levels, which may reflect an already established systematic inflammation with obesity since childhood.
Natural Patterns in the Dawn and Dusk Choruses of a Neotropical Songbird in Relation to an Urban Sound Environment

Simple Summary Urban noise imposes significant challenges for the acoustic communication of birds that are able to survive inside cities. Birds sing most intensely during two periods of the day called dawn and dusk choruses, and although various responses to the urbanization of dawn songs have been reported, very little attention was paid to the dusk chorus. Our objective is to evaluate in urban and non-urban populations of the Chiguanco Thrush (Turdus chiguanco), a very common bird in the city of La Paz (Bolivia) if there are differences between the songs of both choruses, and if these variations are altered by urbanization. Our results show that the loudness, frequency range and number of songs per individual are greater in the dawn chorus and that urban individuals must increase the frequency and loudness of their songs in both choruses to cope with urban noise. Urban Chiguanco Thrushes even produce less than half as many songs per individual compared to non-urban individuals, probably due to the high cost of increasing loudness and frequency. If wild birds are forced to modify their songs so much within the city, this should alert us to the possible negative effects of urban noise on human health. Abstract Urbanization is one of the more important phenomena affecting biodiversity in the Anthropocene. Some organisms can cope with urban challenges, and changes in birds’ acoustic communication have been widely studied. Although changes in the timing of the daily organization of acoustic communication have been previously reported, there is a significant gap regarding possible variations in song structure between dawn and dusk choruses. Considering that urbanization imposes different soundscapes for dawn and dusk choruses, we postulate two hypotheses: (i) there are variations in song parameters between dawn and dusk choruses, and (ii) such parameters within the city will vary in response to urban noise. We studied urban and extra-urban populations of Chiguanco Thrush in La Paz, Bolivia, measuring in dawn and dusk choruses: song length; song sound pressure level; minimum, maximum, range and dominant frequency; and the number of songs per individual. The results support our two hypotheses: there were more songs, and songs were louder and had larger band widths at dawn than at dusk in urban and extra-urban populations. Urban Chiguanco Thrushes sing less, the frequency of the entire song rises, and the amplitude increases as compared with extra-urban Chiguanco Thrushes. Understanding variations between dawn and dusk choruses could allow for a better interpretation of how some bird species cope with urban challenges.
A Comparison of First and Second Order Training Algorithms for Artificial Neural Networks

networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no explicit model of the data is assumed. Therefore due to the high dimensionality of the data, linearization of the training problem through use of orthogonal basis functions is not desirable. The focus is functional minimization on any basis. A number of methods based on local gradient and Hessian matrices are discussed. Modifications of many methods of first and second order training methods are considered. Using share rates data, experimentally it is proved that Conjugate gradient and Quasi Newton's methods outperformed the Gradient Descent methods. In case of the Levenberg-Marquardt algorithm is of special interest in financial forecasting.
Some cognitive additions to Eysenck's “The conditioning model of neurosis”

of the original article: The long-term persistence of neurotic symptoms, such as anxiety, poses difficult problems for any psychological theory. An attempt is made to revive the Watson-Mowrer conditioning theory and to avoid the many criticisms directed against it in the past. It is suggested that recent research has produced changes in learning theory that.can be used to render this possible. In the first place, the doctrine of equipotentiality has been shown to be wrong, and some such concept as Seligman's "preparedness" is required, that is the notion that certain CS are biologically prepared to be more readily connected with anxiety responses than others. In the second place, the law of extinction has to be amended, and the law of incubation or enhancement added, according to which the exposure of the CS-only may, under certain specified conditions, have the effect of increasing the strength of the CR. rather than reducing it. The major conditions favouring incubation are (1) Pavlovian B conditioning, that is a type of conditioning in which the CR is a drive; (2) a strong UCS, and (3) short exposure of the CS-only. Personality differences are also important in this connection. It is possible, using these two recent developments of conditioning theory, to show that a conditioning paradigm can be used to explain the major facts relating to the development of neurotic disorders, and that similarly the success of methods of treatment, such as behaviour therapy, can be explained. The evidence is reviewed for the existence of the incubation phenomenon, both in the animal laboratory and in the clinic, and also for the relevance of the parameters suggested as being implicated in its occurrence. It is concluded that these modifications are sufficient to make the conditioning theory of neurosis and treatment the only viable scientific theory in the field, particularly when attention is paid to Pavlov's and Platonov's inclusion of the second signalling system.
Min-Max Bilevel Multi-objective Optimization with Applications in Machine Learning

This paper is the first to propose a generic min-max bilevel multi-objective optimization framework, highlighting applications in representation learning and hyperparameter optimization. In many machine learning applications such as meta-learning, multi-task learning, and representation learning, a subset of the parameters are shared by all the tasks, while each specific task has its own set of additional parameters. By leveraging the recent advances of nonconvex min-max optimization, we propose a gradient descentascent bilevel optimization (MORBiT) algorithm which is able to extract a set of shared parameters that is robust over all tasks and further overcomes the distributional shift between training and testing tasks. Theoretical analyses show that MORBiT converges to the first-order stationary point at a rate of O( √ nK−2/5) for a class of nonconvex problems, where K denotes the total number of iterations and n denotes the number of tasks. Overall, we formulate a min-max bilevel multi-objective optimization problem, provide a single loop two-timescale algorithm with convergence rate guarantees, and show theoretical bounds on the generalization abilities of the optimizer. Experimental results on sinusoid regression and representation learning showcase the superiority of MORBiT over state-of-the-art methods, validating our convergence and generalization results.
Anatomy of sea level variability - an example from the Adriatic.

Sea-level variability is described using data collected at an east Adriatic station, Bakar, since 1930. It is pointed out that the processes influencing the variability are spread over a wide frequency range. Starting from the smallest periods and progressing towards the largest, the relevant phenomena are (1) tides, (2) storm surges and seiches, (3) planetary-scale disturbances, (4) seasonal and interannual fluctuations, (5) bidecadal signal, and (6) long-term trend related either to natural causes or anthropogenic effects. Practical utility of the sea-level data and analyses is stressed.
Predictive Markers of Treatment Response to Neoadjuvant Systemic Therapy with Dual HER2-Blockade

Simple Summary In human epidermal growth factor receptor 2 (HER2)-positive breast cancer treated with neoadjuvant systemic therapy with docetaxel, carboplatin, trastuzumab, and pertuzumab (TCHP), estrogen receptor (ER) expression, HER2 protein expression, and tumor-infiltrating lymphocyte (TIL) levels are significantly associated with pathologic complete response (pCR). In ER-negative or low-ER (1–9%) breast cancer, treatment response is excellent, regardless of HER2 protein expression and TIL levels. Meanwhile, the pCR rate is notably lower in patients with ER-positive, HER2 immunohistochemistry (IHC) 2+ breast cancer, particularly in those with low TIL levels. Further investigation of novel treatment strategies for ER-positive breast cancer with HER2 IHC 2+ or low TIL levels is warranted. Abstract In patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer, achievement of pathologic complete response (pCR) is a known prognostic indicator after neoadjuvant systemic therapy (NAST). We investigated the clinicopathological factors associated with pCR in patients with HER2-positive breast cancer treated with dual HER2-blockade. In this retrospective study, 348 patients with HER2-positive breast cancer who received NAST with docetaxel and carboplatin, combined with trastuzumab and pertuzumab (TCHP), were included. Of the 348 patients with HER2 protein expression data, 278 (79.9%) had HER2 immunochemistry (IHC) 3+. Data on tumor-infiltrating lymphocyte (TIL) levels were available for 305 patients, showing a median TIL level of 20% (IQR 5–50), among which 121 (39.7%) had high TIL levels (≥30%). Estrogen receptor (ER) status (77.9% in ER-negative vs. 47.5% in ER-positive; p < 0.001), HER2 protein expression (71.6% in IHC 3+ vs. 34.3% in IHC 2+; p < 0.001), and TIL levels (71.9% in high vs. 57.6% in low; p = 0.011) were significantly associated with the pCR rate. In addition, we observed a significant link between numerical TIL levels (per 10% increment) and the pCR rate. After adjusting other clinicopathologic factors, ER status (low expression [defined as 1–9% expression] or negative), HER2 IHC 3+ and numerical TIL levels (per 10% increment), and high TIL levels (≥30%) were found to be independent predictors of pCR. Notably, in ER-negative breast cancer, the treatment response was excellent, irrespective of HER2 expression and TIL levels. Conversely, in ER-positive cases, low ER expression, HER2 IHC 3+, and numerical TIL levels or high TIL levels emerged as independent predictors of pCR. Our results suggest that ER expression, HER2 protein expression, and TIL levels serve as valuable predictors of the treatment response to neoadjuvant TCHP.
Context Adaptation in Statistical Machine Translation Using Models with Exponentially Decaying Cache Domain Adaptation to Summarize Human Conversations Exploring Representation-learning Approaches to Domain Adaptation Using Domain Similarity for Performance Estimation Self-training without Reranking

ii Preface Most modern Natural Language Processing (NLP) systems are subject to the well known problem of lack of portability to new domains and genres: there is a substantial drop in their performance when tested on data from a new domain, i.e., when test data is drawn from a related but different distribution from training data. This problem is inherent in the assumption of independent and identically distributed (i.i.d.) variables for machine learning systems, but has started to get attention only in recent years. The need for domain adaptation arises in almost all NLP tasks – the goal of this workshop is to provide a meeting point for research that approaches the problem of adaptation from the varied perspectives of machine learning and a variety of NLP tasks. We believe there is much to gain by treating domain adaptation as a general learning strategy that utilizes prior knowledge of a specific or a general domain in learning about a new domain. Sharing insights, methodologies and successes across tasks will contribute towards a better understanding of this problem. To this end, this workshop presents original research in areas such as parsing, machine translation, dialog act tagging, entity recognition, summarization, etc. with the common theme of domain adaptation. We received sixteen submissions in all, out of which eight were selected for inclusion in the workshop. We thank the members of the Program Committee for timely and insightful reviews, and the invited speaker John Blitzer for his talk. Abstract We discuss the problem of model adaptation for the task of named entity recognition with respect to the variation of label distributions in data from different domains. We investigate an adaptive extension of the sequence perceptron, where the adaptive component includes parameters estimated from unlabelled data in combination with background knowledge in the form of gazetteers. We apply this idea empirically on adaptation experiments involving two newswire datasets from different domains and compare with other popular methods such as self training and structural correspondence learning.