Miracle-dz/UniFAR-FTUs huggingface dataset:
FedScale: Benchmarking Model and System Performance of Federated Learning

We present FedScale, a diverse set of challenging and realistic benchmark datasets to facilitate scalable, comprehensive, and reproducible federated learning (FL) research. FedScale datasets are large-scale, encompassing a diverse range of important FL tasks, such as image classification, object detection, language modeling, speech recognition, and reinforcement learning. For each dataset, we provide a unified evaluation protocol using realistic data splits and evaluation metrics. To meet the pressing need for reproducing realistic FL at scale, we have also built an efficient evaluation platform to simplify and standardize the process of FL experimental setup and model evaluation. Our evaluation platform provides flexible APIs to implement new FL algorithms and includes new execution backends with minimal developer efforts. Finally, we perform indepth benchmark experiments on these datasets. Our experiments suggest fruitful opportunities in heterogeneityaware co-optimizations of the system and statistical efficiency under realistic FL characteristics. FedScale is open-source with permissive licenses and actively maintained,1 and we welcome feedback and contributions from the community.
Multi-dimensional sequential pattern mining

Sequential pattern mining, which finds the set of frequent subsequences in sequence databases, is an important data-mining task and has broad applications. Usually, sequence patterns are associated with different circumstances, and such circumstances form a multiple dimensional space. For example, customer purchase sequences are associated with region, time, customer group, and others. It is interesting and useful to mine sequential patterns associated with multi-dimensional information.In this paper, we propose the theme of multi-dimensional sequential pattern mining, which integrates the multidimensional analysis and sequential data mining. We also thoroughly explore efficient methods for multi-dimensional sequential pattern mining. We examine feasible combinations of efficient sequential pattern mining and multi-dimensional analysis methods, as well as develop uniform methods for high-performance mining. Extensive experiments show the advantages as well as limitations of these methods. Some recommendations on selecting proper method with respect to data set properties are drawn.
Evaluation of subcutaneous immunotherapy with birch pollen extract for pollen-food allergy syndrome

Some patients with pollen-food allergy syndrome (PFAS) develop systemic symptoms along with oral allergy syndrome upon ingesting processed foods as well as raw fruits and vegetables. This study aimed to investigate the efficacy of subcutaneous immunotherapy with birch pollen extract for patients with PFAS associated with soybean allergy. Subcutaneous immunotherapy with birch pollen extract was introduced in 6 patients with PFAS caused by alder/birch pollen and soybean allergy. An oral food challenge for ingestible amount of soy milk was performed before and 1 year after initiating subcutaneous immunotherapy with birch pollen extract. Before the treatment, the median intake of soy milk was 1.5 mL (interquartile range [IQR], 1–2 mL). One year after the treatment initiation, the median intake of soy milk increased significantly to 150 mL (IQR, 20–200 mL). Systemic reactions occurred in 4 of 6 patients in the rapid escalation phase of the treatment. The results thus suggest that subcutaneous immunotherapy with birch pollen extract could be beneficial for patients with PFAS associated with soybean allergy despite concerns regarding systemic reactions.
Promotion of reproductive and metabolic health - current trends in the treatment and prevention of polycystic ovary syndrome in different periods of life

Polycystic ovary syndrome (PCOS) is one of the most common hormonal disorders and causes of infertility in women in reproductive age. Diagnostic criteria of PCOS in adult women include: ovulation disorders, hyperandrogenism and polycystic ovaries. According to most recommendations, 2 out of these 3 criteria are confirm the diagnosis of PCOS. In girls during puberty and in the first years after menarche, different diagnostic criteria of menstrual disorders should be taken into account (variable length of menstrual cycles, monophasic cycles) and the limited usefulness of ultrasound examination for PCOS diagnosis within 8 years after menarche. Fairly extensive differential diagnosis is also necessary, especially – exclusion of adrenal hyperandrogenism. Moreover, the diagnostic criteria of PCOS do not take into account the metabolic disorders found in most patients (obesity, insulin resistance, type 2 diabetes), which should be diagnosed as early as possible and treated appropriately. This is especially true for teenagers, in whom the unequivocal diagnosis of PCOS or its exclusion may be very difficult. Current recommendations regard hormonal contraception as the first-line therapy in PCOS, in both adult women and adolescents. Together with its beneficial effect on the reduction of hyperandrogenism and obtaining regular bleeding (which in fact are not menstruations), the unfavorable metabolic effects of hormonal contraception are emphasized, as well as the inadequacy of its use if it is expected to achieve or restore ovulation and fertility. The latest reports indicate the legitimacy of treatment aimed at correcting disorders of carbohydrate metabolism and its greater effectiveness compared to the use of oral contraceptives in both adult women and girls with PCOS. In the pharmacotherapy of insulin resistance, metformin is of fundamental importance, the use of pioglitazone, GLP-1 receptor agonists or inositols is also proposed. Adequate lifestyle and dietary modification are of major importance in the treatment and prevention of PCOS. The mechanisms of "inheritance" of PCOS and insulin resistance with the participation of epigenetic modifications are still better understood, taking into account the effects of exposure to androgen excess in utero, intrauterine growth retardation, and maternal obesity and hyperalimentation. This creates new possibilities for PCOS prophylaxis.
Occurrence and Morpho-Molecular Identification of Botryosphaeriales Species from Guizhou Province, China

Botryosphaeriales is an important order of diverse fungal pathogens, saprobes, and endophytes distributed worldwide. Recent studies of Botryosphaeriales in China have discovered a broad range of species, some of which have not been formerly described. In this study, 60 saprobic isolates were obtained from decaying woody hosts in southwestern China. The isolates were compared with other species using morphological characteristics, and available DNA sequence data was used to infer phylogenetic analyses based on the internal transcribed spacer (ITS), large subunit rRNA gene (LSU), and translation elongation factor 1-α (tef) loci. Three novel species were illustrated and described as Botryobambusa guizhouensis, Sardiniella elliptica, and Sphaeropsis guizhouensis, which belong to rarely identified genera within Botryosphaeriaceae. Botryobambusa guizhouensis is the second species identified from the respective monotypic genus. The previously known species were identified as Aplosporella hesperidica, Barriopsis tectonae, Botryosphaeria dothidea, Diplodia mutila, Di. neojuniperi, Di. pseudoseriata, Di. sapinea, Di. seriata, Dothiorella sarmentorum, Do. yunnana, Lasiodiplodia pseudotheobromae, Neofusicoccum parvum, Sardiniella celtidis, Sa. guizhouensis, and Sphaeropsis citrigena. The results of this study indicate that numerous species of Botryosphaeriales are yet to be revealed in southwestern China.
Effect of Percutaneous Endoscopic Gastrostomy on Long-term Quality of Life in Patients with Locally Advanced Nasopharyngeal Carcinoma

Background: Previous study revealed that prophylactic percutaneous endoscopic gastrostomy (PEG) maintain nutritional status of patients with locally advanced nasopharyngeal carcinoma (LA-NPC). We aimed to further investigate the effect of PEG on the long-term quality of life of patients with LA-NPC. Methods: Patients with LA-NPC were selected and divided into PEG and non-PEG groups. The QLQ-C30 scores, incidence of adverse effects, weight and xerostomia recovery were compared between the two groups.Results: No statistically significant difference in the scores of each QLQ-C30 scales between the two groups (P>0.05). The incidence of xerostomia was higher in the PEG group than in the non-PEG group (P=0.044), but no significant difference in the incidence of the remaining adverse effects as well as in weight and dry mouth recovery (P>0.05). Conclusion: PEG seems not to have a detrimental effect on long-term quality of life, including the swallowing function of NPC patients.
Fog Asiste Cloud Paradigma para la Accesibilidad y Colaboración al Análisis de Datos Genómicos

La secuenciación de la próxima generación es cada vez más creciente y requiere recursos informáticos a gran escala para manejar la enorme cantidad de datos producidos. El paradigma Cloud computing fácilmente maneja datos enormes, pero el problema central con este paradigma es la transferencia de datos enormes hacia y desde las computadoras en cloud debido al ancho de banda limitado que radica en la naturaleza centralizada de la arquitectura Cloud computing la cual está localizada lejos de los usuarios. Una arquitectura donde la potencia de computación se distribuya de manera más uniforme en toda la red es una forma de combatir este problema. La arquitectura debe llevar la capacidad de procesamiento hacia el borde de la red, más cerca de la fuente de los datos. Para esta propuesta, Fog computing ofrece una solución prometedora para acercar las capacidades computacionales a los datos generados y será la solución para ganar fuerza en la investigación genómica. Proponemos un nuevo modelo llamado Collaborative-Fog (Co-Fog) que adopta los paradigmas Fog y Cloud computing para administrar grandes conjuntos de datos genómicos y para permitir la comprensión de cómo las partes interesadas pueden gestionar la interacción y la colaboración. El presente trabajo describe el modelo Co-Fog que promete un mayor rendimiento, eficiencia energética, menor latencia, tiempo de respuesta más rápido, escalabilidad y una mejor precisión localizada para futuras colaboraciones a gran escala en la genómica.
On A Family of Isospectral Pure-Birth Processes

The investigation of the spectra of finite Markov generators was first motivated by the quest of quantitative bounds on the convergence to equilibrium of the corresponding processes, see for instance the reference book Levin et al. (2009). There is also a classification reason: what are the possible spectra of Markov generators? , and for such a given spectrum, is there a simple representative Markov process? This structural question is related to the previous motivation, as ergodic finite isospectral Markov generators can be intertwined and under certain circumstances this relation enables good transfers of information about the speed of convergence, see e.g. Miclo (2018); Miclo and Patie (2021). Our goal here goes in this general direction, by providing a simple family of Markov generators for real spectra with geometric multiplicity 1.
The Synthesis and Properties of TIPA-Dominated Porous Metal-Organic Frameworks

Metal-Organic Frameworks (MOFs) as a class of crystalline materials are constructed using metal nodes and organic spacers. Polydentate N-donor ligands play a mainstay-type role in the construction of metal−organic frameworks, especially cationic MOFs. Highly stable cationic MOFs with high porosity and open channels exhibit distinct advantages, they can act as a powerful ion exchange platform for the capture of toxic heavy-metal oxoanions through a Single-Crystal to Single-Crystal (SC-SC) pattern. Porous luminescent MOFs can act as nano-sized containers to encapsulate guest emitters and construct multi-emitter materials for chemical sensing. This feature article reviews the synthesis and application of porous Metal-Organic Frameworks based on tridentate ligand tris (4-(1H-imidazol-1-yl) phenyl) amine (TIPA) and focuses on design strategies for the synthesis of TIPA-dominated Metal-Organic Frameworks with high porosity and stability. The design strategies are integrated into four types: small organic molecule as auxiliaries, inorganic oxyanion as auxiliaries, small organic molecule as secondary linkers, and metal clusters as nodes. The applications of ratiometric sensing, the adsorption of oxyanions contaminants from water, and small molecule gas storage are summarized. We hope to provide experience and inspiration in the design and construction of highly porous MOFs base on polydentate N-donor ligands.
Structural Analysis and Spatiotemporal Expression of Atxn1 Genes in Zebrafish Embryos and Larvae

Zebrafish have come into focus to model cerebellar diseases such as spinocerebellar ataxias (SCAs), which is caused by an expansion of translated CAG repeats in several unrelated genes. In spinocerebellar ataxia type 1 (SCA1), gain-of-function in the mutant ATXN1 contributes to SCA1’s neuropathy. Human ATXN1 and its paralog ATXN1L are chromatin-binding factors, act as transcriptional repressors, and have similar expression patterns. However, little is known about atxn1 genes in zebrafish. Recently, two family members, atxn1a and atxn1b, were identified as duplicate orthologs of ATXN1, as was atxn1l, the ortholog of ATXN1L. In this study, we analyzed the phylogenetic relationship of the atxn1 family members in zebrafish, compared their genetic structures, and verified the predicted transcripts by both RT-PCR and whole-mount in situ hybridization. All three genes, atxn1a, atxn1b, and atxn1l, show overlapping, but also distinct, expression domains during embryonic and larval development. While atxn1a and atxn1l display similar spatiotemporal embryonic expression, atxn1b expression is initiated during the onset of brain development and is predominantly expressed in the cerebellum throughout zebrafish development. These results provide new insights into atxn1 genes and their expression patterns in zebrafish during embryonic and late-larval development and may contribute importantly to future experiments in disease modeling of SCAs.
Understanding Variations in the Tracking and Erosion Performance of HTV-SR-Based Composites due to AC-Stressed Aging

Among the polymeric family, high-temperature-vulcanized silicone rubber (HTV-SR) is the most deployed material for high voltage insulation applications. However, in an outdoor environment, due to contamination and wetting-induced dry band arcing, consequently SR experiences surface tracking and erosion. From a practical standpoint, the tracking and erosion performance under multi-stress aging is required to be known. It is in that context that the present study was undertaken to measure and analyze the effect of multi-stress aging on tracking and erosion performance. Composite samples of SR having different filler concentrations of silica and alumina trihydroxide (ATH) were aged in a multi-stress chamber for a period of 5000 h, and after that their electrical tracking performance was studied. Simultaneously, unaged samples were also exposed to tracking test for comparison. To conduct this test, the inclined plane testing technique was used in accordance with IEC-60587. All samples exposed to tracking test were analyzed using different diagnostic and measuring techniques involving surface leakage current measurement, Fourier transform infrared spectroscopy (FTIR), thermal stability and hydrophobicity classification. Experimental results shown that the tracking lifetime increased through incorporation of silica and ATH fillers in the SR. Amongst all test samples, two samples designated as filled with 2% nano silica and 20% micro silica/ATH exhibited greater resistance to tracking. This was attributed to the optimum loading as well as better dispersion of the fillers in the polymer matrix. The presence of nano-silica enhanced time-to-tracking failure, owing to both improved thermal stability and enhanced shielding effect on the surface of nanocomposite insulators.
Victims or Criminals? Knowledge, Perceptions, and Attitudes of Ghanaian University Students on Illicit Drugs and Substance Users

Illicit drugs and other substances are serious threats to global health and security. Thus, there have been several global efforts to enact and enforce strict humane drug laws and adequate interventions to curb the trade and use of drugs. Nevertheless, there is a dearth of research in the area of knowledge, perception, and attitude of high-risk populations, like West African university students, to guide interventions and the implementation of drug laws. In this study, we explored the knowledge, perception, and attitude of university students regarding available illicit drugs and drug users in Ghana. Adopting a cross-sectional correlational design, our results from 562 students showed that a large proportion of Ghanaian students were aware of the widely used drugs. The majority of our participants reported having heard of alcohol, cocaine, and heroin. However, fewer people reported knowing drugs such as lysergic acid diethylamide (LSD). We observed that university students in Ghana shared positive attitudes towards drug users. Participants in our study viewed drug users and problem drug users as victims who needed support rather than criminals needing punishment. Future research is required among mental health service providers and law enforcement agencies to explore their knowledge, attitude, and perception of drug users and other related issues.
Using Natural Language Processing to Extract Information from Unstructured code-change version control data: lessons learned

Context: Natural Language Processing (NLP) is a branch of artiﬁcial intelligence that extracts information from language. In the ﬁeld of software engineering, NLP has been employed to extract key information from free-form text, to generate models from the analysis of text or to categorize code changes according to their commit messages. In literature, most of the approaches NLP-based focused on the impact of code changes on program execution or software architecture. Objective: In this study, we have applied NLP to code-change data to identify patterns of software code modiﬁcations and used Machine Learning techniques to build a model that determines how software has evolved over time and identiﬁes area of code that presents problems. Method: Considering that software projects use version control systems, such as github, to manage their code, we have collected software information by using git commands. These data contain diﬀerent unstructured information about the various ﬁles in a project. Each modiﬁcation entry includes a message that explains the reasons for the change. According to the content of the message, it is possible to identify key terms that can be used during the classiﬁcation of the entries. Results: In this study, we have considered the change history of software available on github to the High Energy Physics community. With the use of NLP techniques we have cleaned the messages and extracted some key terms to categorize both software problems and some other changes performed by developers, like the addition of a third party dependency or a script that starts a given service. We have built a code change dictionary combining the terms already in existing literature with the ones gathered directly from the
Regulation of signal transduction pathways in colorectal cancer: implications for therapeutic resistance

Resistance to anti-cancer treatments is a critical and widespread health issue that has brought serious impacts on lives, the economy and public policies. Mounting research has suggested that a selected spectrum of patients with advanced colorectal cancer (CRC) tend to respond poorly to both chemotherapeutic and targeted therapeutic regimens. Drug resistance in tumours can occur in an intrinsic or acquired manner, rendering cancer cells insensitive to the treatment of anti-cancer therapies. Multiple factors have been associated with drug resistance. The most well-established factors are the emergence of cancer stem cell-like properties and overexpression of ABC transporters that mediate drug efflux. Besides, there is emerging evidence that signalling pathways that modulate cell survival and drug metabolism play major roles in the maintenance of multidrug resistance in CRC. This article reviews drug resistance in CRC as a result of alterations in the MAPK, PI3K/PKB, Wnt/β-catenin and Notch pathways.
Interaction of Opioids with TLR4—Mechanisms and Ramifications

Simple Summary Recent evidence indicates that opioids can be active at a receptor that is abundantly expressed on innate immune cells as well as cancer cells: the receptor is termed toll-like receptor 4 (TLR4). TLR4 is increasingly recognised as playing key roles in tumour biology and anticancer defences. However, the issue of whether TLR4 mediates some of the effects of opioids on tumour growth and metastasis is entirely unknown. We review existing evidence, mechanisms, and functional consequences of the action of opioids at TLR4. This opens new avenues of research on the role of opioids in cancer. Abstract The innate immune receptor toll-like receptor 4 (TLR4) is known as a sensor for the gram-negative bacterial cell wall component lipopolysaccharide (LPS). TLR4 activation leads to a strong pro-inflammatory response in macrophages; however, it is also recognised to play a key role in cancer. Recent studies of the opioid receptor (OR)-independent actions of opioids have identified that TLR4 can respond to opioids. Opioids are reported to weakly activate TLR4, but to significantly inhibit LPS-induced TLR4 activation. The action of opioids at TLR4 is suggested to be non-stereoselective, this is because OR-inactive (+)-isomers of opioids have been shown to activate or to inhibit TLR4 signalling, although there is some controversy in the literature. While some opioids can bind to the lipopolysaccharide (LPS)-binding cleft of the Myeloid Differentiation factor 2 (MD-2) co-receptor, pharmacological characterisation of the inhibition of opioids on LPS activation of TLR4 indicates a noncompetitive mechanism. In addition to a direct interaction at the receptor, opioids affect NF-κB activation downstream of both TLR4 and opioid receptors and modulate TLR4 expression, leading to a range of in vivo outcomes. Here, we review the literature reporting the activity of opioids at TLR4, its proposed mechanism(s), and the complex functional consequences of this interaction.
Defective HDR through Homologous Recombination (HRR) Due to PALB2 Loss of Function

Biallelic loss-of-function mutations in PALB2 results in Fanconi anemia subtype N (FA-N), which is phen-otypically very similar to Fanconi anemia subtype D1, caused by biallelic loss-of-function of BRCA2 (Reid et al. 2007). FA-D1 and FA-N are characterized by developmental abnormalities, bone marrow failure and childhood cancer susceptibility, childhood solid tumors, Wilms tumor medullo-blastoma. Monoallelic PALB2 loss-of-function is an underlying hereditary breast cancer in par-ticular, but inactivating PALB2 mutations also a lesser extent found in some other cancer PALB2 mutations , risk breast cancer. PALB2 is a high-risk breast cancer predisposing gene