IBM (Germany)

Transsphenoidal surgery (TSS) is the recommended treatment for Cushing's disease (CD). While low morning serum cortisol (MSeC) indicates early remission, the predictive value of an early postoperative overnight 2mg low-dose dexamethasone suppression test (LDDST) remains unclear. This study compares the accuracy of early postoperative MSeC and LDDST for predicting early and long-term remission after TSS. We retrospectively analysed 342 CD surgical cases, who underwent TSS in our department between 2004 and 2024. Morning cortisol measurements were obtained postoperatively. An overnight 2mg LDDST was performed on postoperative day five, in selected cases, preferentially in those without immediate postoperative biochemical remission (MSeC > 50 nmol/L), rather than as a universal screening test. Immediate postoperative biochemical remission (IPBR; MSeC < 50 nmol/L) was achieved in 170 cases (49.7%). LDDST was performed in 197 cases (57.6%), with complete suppression (< 50 nmol/L) in 137 (69.5%). Remission at first follow-up (3-6 months) was significantly higher in cases with IPBR (99.4%) and/or complete LDDST suppression (98.5%) compared to those without (45.0%; p < .0001*). Long-term remission also correlated significantly with postoperative MSeC and LDDST (p < .0001*). ROC analyses confirmed strong predictive accuracy for remission during first FU (AUC MSeC: 0.9229; LDDST: 0.9413) and long-term (AUC MSeC: 0.8267; LDDST: 0.8058). Five-year recurrence risk was 71.1% without LDDST suppression versus 6.8% with suppression. Early postoperative MSeC and LDDST are reliable predictors of remission after TSS in CD. MSeC < 50 nmol/L safely define biochemical remission. LDDST adds diagnostic value, particularly in cases with borderline, normal or elevated MSeC, and should be included in routine postoperative assessment.

The IBM zNext's Telum II processor [1] is a full-stack overhaul of its predecessor [2], featuring a modified 5nm Samsung bulk technology [3], new IBM-created standard cell and IP libraries, and a variety of further design-technology co-optimizations (DTCO). While die size grew from <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$530\text{mm}^{2}$</tex> to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$600\text{mm}^{2}$</tex> (1.13×), each chip in the dual-chip module became denser, featuring 1.3T shapes (1.25×), 43B transistors (1.38×), and 38km of wire (1.28×) across 18 BEOL layers. As IBM's first 5nm processor, Telum II was a concurrent hierarchical design effort, with libraries, IP blocks (array / regfile / analog / phy / custom), and all gate-level entities designed simultaneously. These data volume and concurrent design pressures drove a variety of abstraction, modeling, and other EDA innovations in addition to those involving power, performance, area, and reliability targets.

Modern cloud applications increasingly depend on Infrastructure-as-Code (IaC) practices for infrastructure automation to help manage the complexity of deploying large-scale architectures. Additionally, the deployment of cloud applications is commonly subject to compliance rules. Moreover, designing compliant IaC-based cloud deployments is not enough since runtime changes to the infrastructure or the configuration of individual components may introduce compliance violations. Often, the process of checking and fixing such violations is done manually, which is time-consuming and error-prone. Therefore, this work aims to define and implement a method for runtime IaC compliance management that reduces the complexity, effort, and uncertainty of checking and enforcing compliance rules against IaC-based cloud deployments at runtime. To this end, we follow the design-science research methodology to design and implement (i) the Runtime IaC Compliance Management (RICMa) method and (ii) the IaC Compliance Management Framework (IaCMF) that supports the execution of the RICMa method. We prototypically implement IaCMF and evaluate it using a qualitative interview study with industry experts.

Quantum chromodynamics -the theory of quarks and gluons -has been known for decades, but it is yet to be fully understood. A recent example is the prediction and experimental discovery of tetraquarks, that opened a new research field. Crucially, numerous unsolved questions of the standard model can exclusively be addressed by nonperturbative calculations. Quantum computers can solve problems for which well established QCD methods are inapplicable, such as real-time evolution. We take a key step in exploring this possibility by performing a real-time evolution of tetraquark and pentaquark physics in one-dimensional SU(3) gauge theory on a superconducting quantum computer. Our experiment represents a first quantum computation involving quarks with three colour degrees of freedom, i.e. with the gauge group of QCD.

COVID-19 cases surged in late 2019, leading to worldwide lockdowns that closed non-essential places and activities, industries, and businesses to halt the spread of the virus. Many studies suggested improved air quality during lockdowns. However, these findings often focused on core city limits and did not account for heavy pollution sources outside cities (around the fringe areas), such as factories, power plants, and coal mines, which operated continuously for energy needs even during lockdowns. Therefore, this study quantified and re-analyzed the air quality data using a top-down approach. This study analyzed six major air quality parameters namely SO2, O3, NO2, PM2.5, AOD500, and UAI. The time-averaged approach was adopted to analyze the data followed by ground validation. High variability and anomalies in air quality parameters were observed at different levels of observations (i.e. city level, country level, etc.). However, it was found that during the lockdown period, PM2.5 and NO2 significantly dropped at the country level with few exceptions. Changes were also observed in AOD500, O3, and UAI concentrations from city to country scale. Mixed behaviors among the atmospheric pollutants were observed with changes in scale and time. This makes the claim about air quality improvements during COVID-19 lockdowns very relative to the scale of observation and the pollutant indicators being referred to. Multi-layered analyses of pollutant concentrations extending beyond the city limits to the meso-regional levels with varying space-time observations made the present work unique from existing literature that claimed a global air quality improvement during the COVID-19 lockdown period.

A product of the immediate early gene Arc (Activity-regulated cytoskeleton-associated protein or Arc protein) of retroviral ancestry resides in the genome of all tetrapods for millions of years and is expressed endogenously in neurons. It is a well-known protein, very important for synaptic plasticity and memory consolidation. Activity-dependent Arc expression concentrated in glutamatergic synapses affects the long-time synaptic strength of those excitatory synapses. Because it modulates excitatory-inhibitory balance in a neuronal network, the Arc gene itself was found to be related to the pathogenesis of epilepsy. General Arc knockout rodent models develop a susceptibility to epileptic seizures. Because of activity dependence, synaptic Arc protein synthesis also is affected by seizures. Interestingly, it was found that Arc protein in synapses of active neurons self-assemble in capsids of retrovirus-like particles, which can transfer genetic information between neurons, at least across neuronal synaptic boutons. Released Arc particles can be accumulated in astrocytes after seizures. It is still not known how capsid assembling and transmission timescale is affected by seizures. This scientific field is relatively novel and is experiencing swift transformation as it grapples with difficult concepts in light of evolving experimental findings. We summarize the emergent literature on the subject and also discuss the specific rodent models for studying Arc effects in epilepsy. We summarized both to clarify the possible role of Arc-related pseudo-viral particles in epileptic disorders, which may be helpful to researchers interested in this growing area of investigation.

It has been shown previously that switching the polarity of differential vias can lead to a cancellation of differential crosstalk. In this paper a printed circuit board structure with different routing length differences between victim and aggressor is investigated, to determine the effect of length differences on the crosstalk cancellation. The differential crosstalk of the proposed design is simulated with the Finite Element Method and measured with a vector network analyzer. It is verified that the crosstalk cancellation depends on the length differences.

In diesem Kapitel erfahren Sie mehr über die spezifische Rolle der Informationsarchitektur (IA) bei der Bereitstellung einer zuverlässigen und unternehmensweiten KI-Grundlage. Als Einführung in dieses Thema werden die wichtigsten Aspekte einer Informationsarchitektur (IA) kurz erläutert und die logischen und physischen IA-Komponenten im Kontext von KI hervorgehoben. Diese sind für den Leser wichtig, um die Auswirkungen von KI auf eine bestehende Informationsarchitektur vollständig zu verstehen. Jede Architektur muss mit Produkten und Angeboten untermauert werden. Wir lernen die Schlüsselkomponenten der KI-Informationsarchitektur und ihre Rolle für die Unternehmenstauglichkeit kennen. Wir schließen mit Anwendungsfällen, die KI in der Informationsarchitektur veranschaulichen.