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نجد بين صفحات الكتاب مناقشات بين قادة حزب العمال الاشتراكي الأمريكي والثوري المنفي ليون تروتسكي في عام 1938. وقد اعتمد حزب العمال الاشتراكي نتاج هذه المناقشات، وهو برنامج مطالب فورية وديمقراطية وانتقالية، في وقت لاحق من ذلك العام. يظل برنامج الثورة الاشتراكية هذا أداة مهمة للعمال الشيوعيين اليوم، زقد أوضح الكاتب ان الأزمة الحالية للحضارة البشرية هي ازمة قيادة البروليتاريا.

Barley ( Hordeum vulgare ) is one of the most popular cereal crops globally. Although it is a diploid species, (2 n  = 2x = 14) the study of its genome organization is necessary in the framework of plant breeding since barley is often used in crosses with other cereals like wheat to provide them with advantageous characters. We already have an extensive knowledge on different stages of the meiosis, the cell division to generate the gametes in species with sexual reproduction, such as the formation of the synaptonemal complex, recombination, and chromosome segregation. But meiosis really starts with the identification of homologous chromosomes and pairing initiation, and it is still unclear how chromosomes exactly choose a partner to appropriately pair for additional recombination and segregation. In this work we present an exhaustive molecular analysis of both telomeres and subtelomeres of barley chromosome arms 2H-L, 3H-L and 5H-L. As expected, the analysis of multiple features, including transposable elements, repeats, GC content, predicted CpG islands, recombination hotspots, G4 quadruplexes, genes and targeted sequence motifs for key DNA-binding proteins, revealed a high degree of variability both in telomeres and subtelomeres. The molecular basis for the specificity of homologous recognition and pairing occurring in the early chromosomal interactions at the start of meiosis in barley may be provided by these polymorphisms. A more relevant role of telomeres and most distal part of subtelomeres is suggested.

Host cell proteins (HCPs) are one of the process-related impurities that need to be well characterized and controlled throughout biomanufacturing processes to assure the quality, safety, and efficacy of monoclonal antibodies (mAbs) and other protein-based biopharmaceuticals. Although ELISA remains the gold standard method for quantification of total HCPs, it lacks the specificity and coverage to identify and quantify individual HCPs. As a complementary method to ELISA, the LC-MS/MS method has emerged as a powerful tool to identify and profile individual HCPs during the downstream purification process. In this study, we developed a sensitive, robust, and reproducible analytical flow ultra-high-pressure LC (UHPLC)-high-resolution accurate mass (HRAM) data-dependent MS/MS method for HCP identification and monitoring using an Orbitrap Ascend BioPharma Tribrid mass spectrometer. As a case study, the developed method was applied to an in-house trastuzumab product to assess HCP clearance efficiency of the newly introduced POROS™ Caprylate Mixed-Mode Cation Exchange Chromatography resin (POROS Caprylate mixed-mode resin) by monitoring individual HCP changes between the trastuzumab sample collected from the Protein A pool (purified by Protein A chromatography) and polish pool (purified by Protein A first and then further purified by POROS Caprylate mixed-mode resin). The new method successfully identified the total number of individual HCPs in both samples and quantified the abundance changes in the remaining HCPs in the polish purification sample.

The role of power converters in modern electrical infrastructure (such as electric vehicle charging stations, battery energy storage systems and photovoltaic energy systems) has become critical. Given the high reliability required by these converters, continuous condition monitoring for predictive maintenance is mandatory. Traditional SCADA and HMI systems often face scalability bottlenecks and lack the flexibility in data aggregation and storage scalability required for long-term predictive maintenance. This paper proposes a scalable, containerized microservices-based architecture for degradation tracking and State-of-Health (SoH) monitoring in power conversion systems. The architecture features a decoupled four-layer structure, utilizing dedicated UDP servers for low-latency data ingestion, RabbitMQ (AMQP) for robust message routing, and a NoSQL (MongoDB) storage layer with a FastAPI interface. The proposed system was validated using a Hardware-in-the-Loop (HiL) setup with a Typhoon HIL606 simulator monitoring an Active Neutral Point Clamped (ANPC) power converter. Experimental stress tests demonstrated a Packet Delivery Ratio (PDR) of 1.0 at ingestion rates up to 100 messages per second (msgs/s) per node. The system exhibits transmission and processing overheads consistently below 5 ms, ensuring timely data availability for tracking thermal dynamics and parametric aging trends. This operational performance significantly exceeds the nominal requirement of 2 msgs/s for condition monitoring, ensuring robust data integrity. Finally, this modular approach provides the horizontal scalability necessary for Industry 4.0 integration, offering a high-performance framework for long-term health monitoring in modern power electronics.

Abstract Since oncologic patients have been considered an important risk group for parasitic infections, it is fundamental to find out what they know about intestinal parasites. This study aimed at evaluating knowledge that the adult oncologic patients undergoing chemotherapy in the main centers of treatment for cancer in the city of Pelotas, Brazil, has about intestinal parasites. A semi-structured questionnaire was used for collecting data from two hundred oncologic patients who were undergoing chemotherapy. Results showed that 69.5% know what intestinal parasites are and cited Ascaris lumbricoides and Taenia sp. as being the most known ones. The statistical comparison between the group that knows intestinal parasites and the one that does not know about them – associated with socioeconomic variables –, showed that factors that significantly influenced their knowledge were their place of residence, schooling and household income (p≤0.05). Only 36% stated that they know when they are infected with parasites and misdescribed some signs and symptoms. Regarding prevention, 52% mentioned that they do not know how to avoid parasitism. The population under study showed that there are some gaps in its knowledge of the theme under investigation. Therefore, it is important to implement socioeducational measures in hospitals and clinics that treat cancer patients. Resumo Pacientes oncológicos são considerados um importante grupo de risco para infecções parasitárias, logo, é fundamental conhecer o que sabem sobre parasitos intestinais. O objetivo deste estudo foi avaliar os conhecimentos de indivíduos oncológicos adultos submetidos à quimioterapia nos principais centros de tratamento para o câncer no município de Pelotas, RS, sobre as enteroparasitoses. O instrumento utilizado para coleta dos dados foi um questionário semiestruturado. Foram incluídos nesta pesquisa 200 pacientes oncológicos submetidos à quimioterapia. Destes, 69,5% sabem o que são parasitos intestinais, citando Ascaris lumbricoides e Taenia sp. como os mais conhecidos. Quando realizada a comparação estatística do grupo que conhece parasitos intestinais/vermes com o grupo dos que desconhecem o tema, associadas com variáveis socioeconômicas, foi verificado que a zona em que residiam, a escolaridade e a renda familiar são fatores que influenciam no conhecimento dos indivíduos de forma significativa (p≤0,05). Apenas 36% dos indivíduos afirmaram saber quando estão parasitados, relatando alguns sinais e sintomas equivocadamente. Relacionado à prevenção, 52% mencionaram não saber como evitar o parasitismo. A população estudada possui lacunas no conhecimento sobre o tema abordado e, por isso, é importante a realização de ações socioeducativas junto aos hospitais e clínicas de tratamento dos pacientes com câncer.

Numerous archaeal lineages are known to inhabit marine subsurface sediments, although their distributions, metabolic capacities, and interspecies interactions are still not well understood. Abundant and diverse archaea were recently reported in Costa Rica (CR) margin subseafloor sediments recovered during IODP Expedition 334. Here, we recover metagenome-assembled genomes (MAGs) of archaea from the CR margin and compare them to their relatives from shallower settings. We describe 31 MAGs of six different archaeal lineages (Lokiarchaeota, Thorarchaeota, Heimdallarchaeota, Bathyarcheota, Thermoplasmatales, and Hadesarchaea) and thoroughly analyze representative MAGs from the phyla Lokiarchaeota and Bathyarchaeota. Our analysis suggests the potential capability of Lokiarchaeota members to anaerobically degrade aliphatic and aromatic hydrocarbons. We show it is genetically possible and energetically feasible for Lokiarchaeota to degrade benzoate if they associate with organisms using nitrate, nitrite, and sulfite as electron acceptors, which suggests a possibility of syntrophic relationships between Lokiarchaeota and nitrite and sulfite reducing bacteria. The novel Bathyarchaeota lineage possesses an incomplete methanogenesis pathway lacking the methyl coenzyme M reductase complex and encodes a noncanonical acetogenic pathway potentially coupling methylotrophy to acetogenesis via the methyl branch of Wood–Ljungdahl pathway. These metabolic characteristics suggest the potential of this Bathyarchaeota lineage to be a transition between methanogenic and acetogenic Bathyarchaeota lineages. This work expands our knowledge about the metabolic functional repertoire of marine benthic archaea.

The servo drive system serves as the core power unit in high-end equipment such as industrial robots and computerized numerical control (CNC) machine tools, where mechanical resonance and shaft torque ripple induced by elastic deformation and backlash severely degrade motion accuracy and system stability. Conventional resonance suppression approaches, predominantly based on PI control and notch-filter-augmented PI control, suffer from critical limitations: high sensitivity to resonant frequency variations, inability to systematically enforce physical shaft torque constraints, poor robustness against parameter uncertainties and external disturbances, and significant degradation of dynamic performance when resonance is aggressively suppressed. This paper establishes a two-inertia elastic system model to investigate the effects of elastic deformation and backlash nonlinearities, revealing the mechanisms of mechanical resonance and torque ripple, and proposes control strategies for resonance suppression and shaft torque ripple limitation. A novel hierarchical control architecture is designed, consisting of a Luenberger-observer-based model predictive control (MPC) speed controller, and a super-twisting sliding mode controller (ST-SMC) for the current loop. Luenberger observer-based MPC with ST-SMC strategy is to simultaneously obtain: (a) enhanced robustness via state estimation, (b) superior dynamic performance via SMC, and (c) guaranteed shaft torque constraint satisfaction via MPC. Compared with conventional PI control and notch-filter-based PI control, simulation results demonstrate that Luenberger observer-based MPC with ST-SMC strategy effectively suppresses resonance, limits shaft torque ripple, and enhances the system’s disturbance rejection capability.

Model predictive control (MPC) is significantly affected by parameter mismatch in inverter applications, whereas model-free predictive control (MFPC) avoids parameter dependence through the ultra-local model (ULM). However, the traditional MFPC based on the algebraic method needs to store historical data for multiple cycles, which results in a sluggish dynamic response. To address the above problems, this paper proposes a model-free predictive control method based on the ultra-local model and an adaptive super-twisting sliding mode observer (ASTSMO). Firstly, the effect of parameter mismatch on the current prediction error of conventional MPC is analyzed through theoretical analysis, and a first-order ultra-local model of the inverter is established to enhance robustness against parameter variations. Secondly, a super-twisting sliding mode observer with adaptive gain is designed to estimate the unknown dynamic terms in the ultra-local model in real time. Finally, the superiority of the proposed method is verified through comparative validation against conventional MPC and the algebraic-based MFPC. Simulation results demonstrate that the proposed method can significantly enhance robustness against parameter variations and shorten the settling time during dynamic transients.

Hand-in-hand with the smart-grid paradigm development, power converters used in high-power applications are facing important challenges related to efficiency and power quality. To overcome these issues, the pre-programmed Pulse-Width Modulation (PWM) methods have been extensively applied to reduce the harmonic distortion with very low power switching losses for high-power converters. Among the pre-programmed PWM techniques, Selective Harmonic Elimination (SHE) has been the prevailing solution, but recently, Selective Harmonic Mitigation (SHM) stands as a superior alternative to provide further control of the harmonic spectrum with similar losses. However, the large computational burden required by the SHM method to find a solution confines it as an off-line application, where the switching set valid solutions are pre-computed and stored in a memory. In this paper, for the first time, a real-time implementation of SHM using an off-the-shelf mid-range microcontroller is presented and tested. The Exchange Market Algorithm (EMA), initially focused on optimizing financial transactions, is considered and executed to achieve the SHM targets. The performance of the EMA-based SHM is presented showing experimental results considering a reduced number of switching angles applied to a specific three-level converter, but the method can be extrapolated to any other three-level converter topology.

Three-level neutral-point-clamped (NPC) converter is widely used in energy conversion systems due to its good properties for high-power systems presenting output waveforms with reduced harmonic distortion. To obtain better system performance, an integral sliding-mode control (ISMC)-based direct power control (DPC) strategy is proposed for NPC converters. The controller achieves three objectives. First, an extended state observer (ESO)-based ISMC strategy, to enforce the active and reactive power to their reference values, is applied in the power tracking loop. ESO is used to reduce the influence of parameter uncertainties. Next, in the voltage regulation loop, a radial basis function neural network (RBFNN)-based adaptive ISMC strategy is applied to regulate the DC-link voltage. RBFNN is used to estimate the load variation, which is considered as a disturbance, to improve the system disturbance rejection ability. An adaptive law is used in the controller to reduce the chattering of reference active power which can reduce the current harmonic distortion. Finally, a proportional-integral (PI) control strategy is applied in the voltage balancing loop to achieve voltage balance between two DC-link capacitors. Experimental results show the effectiveness and superiority of the proposed control strategy for the NPC power converter compared with PI-based DPC strategy.